**Solid-State Fermentation in a Bag Bioreactor: Effect of Corn Cob Mixed with Phytopathogen Biomass on Spore and Cellulase Production by** *Trichoderma asperellum*

Reynaldo De la Cruz-Quiroz, Sevastianos Roussos, Daniel Hernandez-Castillo, Raúl Rodríguez-Herrera, Lluvia López-López, Francisco Castillo and Cristóbal N. Aguilar

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/64643

#### **Abstract**

[40] Wang S, Zhu Y, Zhang Y. Controlling the oxidoreduction potential of the culture of *Clostridium acetobutylicum* leads to an earlier initiation of solventogenesis, thus increas‐ ing solvent productivity. Applied Microbiology and Biotechnology. 2012;93:1021‐1030.

[41] Li T, Yan Y, He J. Reducing cofactors contribute to the increase of butanol production by a wild‐type *Clostridium* sp. strain BOH3. Bioresource Technology. 2014;155:220‐228.

[42] Bui L M, Lee J Y, Geraldi A. Improved n‐butanol tolerance in *Escherichia coli* by controlling membrane related functions. Journal of Biotechnology. 2015;204:33‐44. DOI:

[43] Fu J, Wang Z W, Chen T. NADH plays the vital role for chiral pure D‐(‐)‐2,3‐Butanediol production in *Bacillus subtilis* under limited oxygen conditions. Biotechnology and

[44] Wang Y, Li L, Ma C. Engineering of cofactor regeneration enhances (2S,3S)‐2,3‐ butanediol production from diacetyl. Scientific Reports. 2013;3:2643. DOI: 10.1038/

[45] Lin Y H, Chien W S, Duan K J. Correlations between reduction‐oxidation potential profiles and growth patterns of *Saccharomyces cerevisiae* during very‐high‐gravity fermentation. Process Biochemistry. 2010;45:765‐770. DOI: 10.1016/j.procbio.

[46] Jeon B Y, Park D H. Improvement of ethanol production by electrochemical redox combination of *Zymomonas mobilis* and *Saccharomyces cerevisiae*. Journal of Microbiology

[47] Na B K, Hwang T S, Lee S H. Effect of electrochemical redox reaction on growth and metabolism of *Saccharomyces cerevisiae* as an environmental factor. Journal of Microbi‐

[48] Liu C G, Lin Y H, Bai F W. Development of redox potential‐controlled schemes for very‐ high‐gravity ethanol fermentation. Journal of Biotechnology. 2011;153:42‐47. DOI:

[49] Liu C G, Lin Y H, Bai F W. Ageing vessel configuration for continuous redox potential‐ controlled very‐high‐gravity fermentation. Journal of Bioscience and Bioengineering.

and Biotechnology. 2010;20:94‐100. DOI: 10.4014/jmb.0904.04029

ology and Biotechnology. 2007;17:445‐453.

2011;111:61‐66. DOI: 10.1016/j.jbiosc.2010.09.003

10.1016/j.jbiotec.2011.03.007

Bioengineering. 2014;111:2126‐2131. DOI: 10.1002/bit.25265

DOI: 10.1007/s00253‐011‐3570‐2

DOI: 10.1016/j.biortech.2013.12.089

10.1016/j.jbiotec.2015.03.025

srep02643

42 Fermentation Processes

2010.01.018

The solid-state fermentation (SSF) is the best option to produce spores of biological control agents (BCA), because the spores have a long shelf life, compared with the obtained in liquid cultures. The spore production under SSF conditions using poly‐ ethylene bioreactors (bag-type) is a new topic. Only little information mainly about bioreactors design and adequate conditions to spore production is available. The main aim of this study was to use the corn cob as substrate in SSF and produce spores of the fungi BCA *Trichoderma asperellum* in a polyethylene bioreactor. In the process was added biomass of the phytopathogenic fungi *Colletotrichum gloeosporioides* and *Phytophthora capsici* as inducers of hydrolase enzymes (endoglucanases, exoglucanases and chitinases). It is possible to obtain high levels of spores, cellulases and chitinases using a polyethylene bioreactor under SSF conditions by *T. asperellum* and corn cob as substrate. Under the SSF conditions evaluated, the biomass of *C. gloeosporioides* has an inducer effect just on the spore production. However, *P. capsici* have effect on all response variables evaluated. The spore production was twice when used *P. capsici* as inducer. The most influential factor under SSF was the moisture. Levels of 66 and 50% of this factor increase the yield in all response variables evaluated (sporulation, cellulases and chitinases), *C. gloeosporioides* and *P. capsici*, respectively.

**Keywords:** spores, cellulase, *Trichoderma asperellum*, solid-state fermentation, bag bio‐ reactor

© 2017 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

#### **1. Introduction**

The diseases induced by phytopathogens are the leading cause of losses in the most crops worldwide. It is well known that the control of such diseases through the use of chemical pesticides is not effective, they generate resistant strains phytopathogenic, the wastes are toxic and they have carcinogenic effects [1, 2]. In the last years, the alternative proposed is the use of antagonist microorganism of phytopathogens, which results in an adequate biological con‐ trol, which is highly effective and environmental friendly [2]. For this, the production of high concentrations of the spores of biological control agents (BCA) is necessary, and so currently there are several production processes of different microorganisms. The solid-state fermenta‐ tion (SSF) is the best to this aim, because the spores have a long shelf life, compared with the obtained in liquid cultures [3, 4]. In other way, the spore production in SSF is relatively easiest, so it can be realized by personal with no experience, and therefore make possible the technol‐ ogy transference to farmers [3]. The spore production under SSF conditions using polyethy‐ lene bioreactors (bag-type) is a new topic. Only little information mainly about bioreactors design andadequate conditions to sporeproduction [1, 5, 6]is available.In SSF, most ofthe time wastes from other manufacturing process are used; therefore, this potential is commonly investigated in developing countries [1].Wastes ofrice, maize meal, corn cob,rice husk, banana husk, wheat bran and tea leaves, among others have been used as substrate to spore produc‐ tion by SSF [3, 5, 6]. There are some compounds that can be added to the substrate of SSF in little proportions to induce some interest metabolite. For example, there are reports of the addition of casein and gluten to produce proteases, waste shrimp silage to chitinase production, among others [7, 8]. The main aim of this study was to use the corn cob as substrate in SSF and produce spores of the fungi BCA *Trichoderma asperellum* in a polyethylene bioreactor. In the process was added biomass of the phytopathogenic fungi *Colletotrichum gloeosporioides* and *Phytophthora capsici* as inducers of hydrolase enzymes (endoglucanases, exoglucanases and chitinases).

#### **2. Materials and methods**

#### **2.1. Microorganism and culture conditions**

The *T. asperellum* (T2-10) and *P. capsici* were kindly proportioned by the Agricultural Parasi‐ tology Department of the UAAAN (Universidad Autónoma Agraria Antonio Narro, Saltillo, México). *C. gloeosporioides* was proportioned by the Food Research Department of the UAdeC (Universidad Autónoma de Coahuila). The fungi were cultivated and conserved in a milkglycerol 8.5% solution. Potato dextrose agar (PDA) was used to reactivate the fungi. In HACH® tubes, 5 mL of PDA was taken, then they were closed and sterilized at 121°C for 15 min. The tubes in slant were inoculated with the fungal strains and incubated at 30°C for 5 days. The conservation was at ± 4°C.

#### **2.2. Phytopathogen biomass production**

A cornmeal medium (17 g/L) was used to produce phytopathogen biomass. This medium was maintained under shaking for 1 h at 58°C. Then, it was filtrated and sterilized (15 at 115°C). The inoculation of phytopathogens was as follows: *C. gloeosporioides* (1×106 spores/mL) and *P. capsici* (10 PDA plugs from a culture of 7days old), and incubated at 28°C for 7 days under shaking (200 rpm).

#### **2.3. Substrates**

**1. Introduction**

44 Fermentation Processes

**2. Materials and methods**

conservation was at ± 4°C.

**2.1. Microorganism and culture conditions**

The diseases induced by phytopathogens are the leading cause of losses in the most crops worldwide. It is well known that the control of such diseases through the use of chemical pesticides is not effective, they generate resistant strains phytopathogenic, the wastes are toxic and they have carcinogenic effects [1, 2]. In the last years, the alternative proposed is the use of antagonist microorganism of phytopathogens, which results in an adequate biological con‐ trol, which is highly effective and environmental friendly [2]. For this, the production of high concentrations of the spores of biological control agents (BCA) is necessary, and so currently there are several production processes of different microorganisms. The solid-state fermenta‐ tion (SSF) is the best to this aim, because the spores have a long shelf life, compared with the obtained in liquid cultures [3, 4]. In other way, the spore production in SSF is relatively easiest, so it can be realized by personal with no experience, and therefore make possible the technol‐ ogy transference to farmers [3]. The spore production under SSF conditions using polyethy‐ lene bioreactors (bag-type) is a new topic. Only little information mainly about bioreactors design andadequate conditions to sporeproduction [1, 5, 6]is available.In SSF, most ofthe time wastes from other manufacturing process are used; therefore, this potential is commonly investigated in developing countries [1].Wastes ofrice, maize meal, corn cob,rice husk, banana husk, wheat bran and tea leaves, among others have been used as substrate to spore produc‐ tion by SSF [3, 5, 6]. There are some compounds that can be added to the substrate of SSF in little proportions to induce some interest metabolite. For example, there are reports of the addition of casein and gluten to produce proteases, waste shrimp silage to chitinase production, among others [7, 8]. The main aim of this study was to use the corn cob as substrate in SSF and produce spores of the fungi BCA *Trichoderma asperellum* in a polyethylene bioreactor. In the process was added biomass of the phytopathogenic fungi *Colletotrichum gloeosporioides* and *Phytophthora capsici* as inducers of hydrolase enzymes (endoglucanases, exoglucanases and chitinases).

The *T. asperellum* (T2-10) and *P. capsici* were kindly proportioned by the Agricultural Parasi‐ tology Department of the UAAAN (Universidad Autónoma Agraria Antonio Narro, Saltillo, México). *C. gloeosporioides* was proportioned by the Food Research Department of the UAdeC (Universidad Autónoma de Coahuila). The fungi were cultivated and conserved in a milkglycerol 8.5% solution. Potato dextrose agar (PDA) was used to reactivate the fungi. In HACH® tubes, 5 mL of PDA was taken, then they were closed and sterilized at 121°C for 15 min. The tubes in slant were inoculated with the fungal strains and incubated at 30°C for 5 days. The In this work, we evaluate as substrate corn cob (CC) proportioned by the Mexican Institute of Maize, UAAAN Coahuila, México. The material was dried, ground, fractioned (300–1680 μm) and stored under low moisture conditions for further evaluation. This material was used as a substrate on SSF without pretreatment.

#### **2.4. Solid-state fermentation**

Polyethylene bags were used as bioreactor in all experiments. Sporulation and cellulase production were evaluated. Plackett-Burman design (PBD) was used in this experiment to determine the most influential factors on spore and enzyme production by *T. asperellum* under SSF conditions on a bag bioreactor. The factors such as temperature (°C), pH, substrate (g), inoculum (spores/g), moisture (%), phytopathogen biomass (%) and incubation time (days) were evaluated, one maximum (+1) and one minimum (−1) (**Table 1**). Spore counting was done at the end of SSF process using a hemocytometer. The fermented material was placed in a Falcon® tube with 10 mL of distilled water. The enzymatic extract was homogenized in a vortex (1 min) for further determination of enzyme activity.

#### **2.5. Enzyme activity determination**

After SSF each sample was analyzed to determine cellulase activity [9], chitinase activity [10] and reducing sugars [11]. The carboxymethylcellulose activity (CMCA) was carried out at 50°C for 30 min. Sample (1 mL) and substrate (1 mL of carboxymethylcellulose 1%) were the mix reaction. Citrate buffer (1 mL at 50 mM, pH 4.8) and substrate (1 mL) were the substrate control. The enzyme control was the mix of sample (1 mL) and citrate buffer (1 mL).

The filter paper activity (FPA) was carried out at 50°C for 1 h. Sample (1 mL) and substrate (filter paper Whatman No.1 (1 cm×5 cm) in 1 mL of citrate buffer at 50 mM, pH 4.8) were the reaction mix. The control substrate was the mix of citrate buffer (2 mL) and filter paper. Sample (1 mL) and citrate buffer (1 mL) were the enzyme control.

Chitinase activity was carried out at 37°C for 1 h. The reaction mix, enzyme and substrate control were done similar to carboxymethylcellulose activity. In this case, substrate (chitin oligosaccharides) and buffer solution (acetate 50 mM, pH 4.0) were replaced.

Sugar concentration was determined after each enzyme reaction. An enzyme activity (U) was defined as the amount of enzyme that catalyze the release of 1 μmol of glucose per minute.


**Table 1.** PBD matrix used to determine the influence of different variables (A, B, C, D, E, F and G) on spore and enzyme activity in SSF by *T. asperellum*.

#### **2.6. Design and statistical analysis**

A PBD was used to SSF. Spore and enzyme production were the response variables. Data were analyzed by ANOVA using STATISTICA 7.0 software; when needed mean treatments were compared using Tukey's multiple range procedure. A *p*-value of less than 0.05 was regarded as significantly different.

#### **3. Results**

#### **3.1. Screening of significant factors using Plackett-Burman design**

Studies were performed in eight runs each one to identify the combination of factors which allow us to obtain a significant level of spore, cellulase and chitinase production by *T. asper‐ ellum* on corn cob under SSF conditions using phytopathogen biomass (*C. gloeosporioides* and *P. capsici*).

#### **3.2. Solid-state fermentation with C. gloeosporioides biomass**

**Table 2** summarizes the results obtained in SSF using the biomass of *C. gloeosporioides* blended with corn cob. The sporulation index is favored by the treatments F and G (7.3×108 and 6.2×108 Spores/g CS, respectively), with no significant difference among the values. The conditions of treatment C allow the best production to CMCA, FPA and CA (2.582, 1.549 y 5.118 U/g), respectively).

Solid-State Fermentation in a Bag Bioreactor: Effect of Corn Cob Mixed with Phytopathogen Biomass on Spore and Cellulase Production by *Trichoderma asperellum* http://dx.doi.org/10.5772/64643 47


Numbers in each column followed by a common letter are not significantly different (*P*<0.05).

**Run A B C D E F G** 1 −1 −1 −1 1 1 1 −1 2 1 −1 −1 −1 −1 1 1 3 −1 1 −1 −1 1 −1 1 4 1 1 −1 1 −1 −1 −1 5 −1 −1 1 1 −1 −1 1 6 1 −1 1 −1 1 −1 −1 7 −1 1 1 −1 −1 1 −1 8 1 1 1 1 1 1 1 **Code Factors High value Low value** A Substrate (g) 30 15 B pH 8.0 6 C Inoculum (spores/g) 1×107 1×105 D Temperature (°C) 30 24 E Moisture (%) 66 50 F Inducer (%) 3 1 G Time (days) 7 5

**Table 1.** PBD matrix used to determine the influence of different variables (A, B, C, D, E, F and G) on spore and

**3.1. Screening of significant factors using Plackett-Burman design**

**3.2. Solid-state fermentation with C. gloeosporioides biomass**

A PBD was used to SSF. Spore and enzyme production were the response variables. Data were analyzed by ANOVA using STATISTICA 7.0 software; when needed mean treatments were compared using Tukey's multiple range procedure. A *p*-value of less than 0.05 was regarded

Studies were performed in eight runs each one to identify the combination of factors which allow us to obtain a significant level of spore, cellulase and chitinase production by *T. asper‐ ellum* on corn cob under SSF conditions using phytopathogen biomass (*C. gloeosporioides* and

**Table 2** summarizes the results obtained in SSF using the biomass of *C. gloeosporioides* blended with corn cob. The sporulation index is favored by the treatments F and G (7.3×108 and

 Spores/g CS, respectively), with no significant difference among the values. The conditions of treatment C allow the best production to CMCA, FPA and CA (2.582, 1.549 y

enzyme activity in SSF by *T. asperellum*.

as significantly different.

**3. Results**

46 Fermentation Processes

*P. capsici*).

6.2×108

5.118 U/g), respectively).

**2.6. Design and statistical analysis**

**Table 2.** Enzyme production and sporulation index of *T. asperellum* on a mixture of corn cob and *C. gloeosporioides* biomass under SSF conditions.

**Figure 1.** Pareto plot of the standardized effects on the spore production of *T. asperellum* using corn cob in SSF with *C. gloeosporioides* as inducer.

In the first case, the spore production was influenced by the temperature in a negative way. Between the range of the values (24 and 30°C), the study shows that 24°C is the best to produce a better sporulation index and possibly if we reduce the value, the sporulation can be major. The moisture, inoculum and inducer are the other factors that also have influence on spore production, just in a positive way. It means, it is necessary to increase the value of each factor (**Figure 1**). The moisture, pH and inoculum were the factors more determining endoglucanase production (CMCA). These factors had positive values, which mean that high values allow high enzyme activity. A significant effect was observed with the substrate concentration, but this effect was negative, so low amount of substrate is needed to obtain high enzyme yields (**Figure 2**).

**Figure 2.** Pareto plot of the standardized effects on CMCA from an extract of *T. asperellum* using corn cob in SSF with *C. gloeosporioides* as inducer.

**Figure 3.** Pareto plot of the standardized effects on FPA from an extract of *T. asperellum* using corn cob in SSF with *C. gloeosporioides* as inducer.

The exoglucanase (FPS) in the same way to CMCA was influenced by the moisture (Positive). Low levels in the substrate and temperature show the best enzymatic yields (**Figure 3**). The moisture was the factor with major influence on the chitinase production. The substrate and Solid-State Fermentation in a Bag Bioreactor: Effect of Corn Cob Mixed with Phytopathogen Biomass on Spore and Cellulase Production by *Trichoderma asperellum* http://dx.doi.org/10.5772/64643 49

inducer were also significant, but in negative way, it is necessary to use low values to increase the yield. The time and pH were important, so these factors must be in high levels (**Figure 4**).

**Figure 4.** Pareto plot of the standardized effects on chitinase from an extract of *T. asperellum* using corn cob in SSF with *C. gloeosporioides* as inducer.

#### **3.3. Solid-state fermentation with P. capsici as inducer**

**Figure 2.** Pareto plot of the standardized effects on CMCA from an extract of *T. asperellum* using corn cob in SSF with

**Figure 3.** Pareto plot of the standardized effects on FPA from an extract of *T. asperellum* using corn cob in SSF with *C.*

The exoglucanase (FPS) in the same way to CMCA was influenced by the moisture (Positive). Low levels in the substrate and temperature show the best enzymatic yields (**Figure 3**). The moisture was the factor with major influence on the chitinase production. The substrate and

*C. gloeosporioides* as inducer.

48 Fermentation Processes

*gloeosporioides* as inducer.

Now, **Table 3** shows the results obtained in SSF using the biomass of *P. capsici* as inducer. The conditions of treatment G allow the best production to all dependent variables evaluated. The values obtained were sporulation index (1.2×109 Spores/g CS), CMCA (7.825 U/g), FPA (2.764 U/g) and CA (3.609 U/g).


Numbers in each column followed by a common letter are not significantly different (*P*<0.05).

**Table 3.** Enzyme production and sporulation index of *T. asperellum* grown on a mixture of corn cob with *P. capsici biomass under SSF conditions*.

**Figure 5.** Pareto plot of the standardized effects on the spore production of *T. asperellum* using corn cob in SSF with *P. capsici* as inducer.

**Figure 6.** Pareto plot of the standardized effects on CMCA from an extract of *T. asperellum* using corn cob in SSF with *P. capsici* as inducer.

Solid-State Fermentation in a Bag Bioreactor: Effect of Corn Cob Mixed with Phytopathogen Biomass on Spore and Cellulase Production by *Trichoderma asperellum* http://dx.doi.org/10.5772/64643 51

**Figure 7.** Pareto plot of the standardized effects on FPA from an extract of *T. asperellum* using corn cob in SSF with *P. capsici* as inducer.

**Figure 5.** Pareto plot of the standardized effects on the spore production of *T. asperellum* using corn cob in SSF with *P.*

**Figure 6.** Pareto plot of the standardized effects on CMCA from an extract of *T. asperellum* using corn cob in SSF with

*capsici* as inducer.

50 Fermentation Processes

*P. capsici* as inducer.

**Figure 8.** Pareto plot of the standardized effects on chitinase from an extract of *T. asperellum* using corn cob in SSF with *P. capsici* as inducer.

The sporulation of *T. asperellum* was not influenced by the pH and inoculum. But low levels (moisture, temperature and time) and high levels (inducer and substrate) show high spore production (**Figure 5**). In endoglucanase production, four factors are important under the SSF conditions evaluated. Low levels of moisture, time and substrate and high levels of the inducer show the major levels of enzymatic activity (**Figure 6**). All factors evaluated were significant to the exoglucanase production. Low levels of moisture, time, pH, substrate ad inoculum and high levels of inducer and temperature show the best enzyme yields (**Figure 7**). Finally, low levels of moisture, time and pH and high levels of inducer shows the major chitinolytic activity (**Figure 8**).

#### **4. Discussion**

There are several studies that report the production of different enzymes under SSF [12, 13]. Currently, the SSF is a commonly used system because the raw materials such as sugarcane bagasse, wheat bran, among others [14] are cheaper. The control of temperature, pH, moisture, purity of the culture and process time are some factors that difficult the rigorous control of the fermentation process [8].

Sometimes, it is hard to find one combination of the SSF conditions in which we can obtain high yield in all response variables evaluated (sporulation, cellulases and chitinases). In the case of SSF with biomass of *C. gloeosporioides*, the best results were observed in the treatment F to spore production and the treatment C to enzyme activities. However, the treatment F also shows great enzyme yields. So the treatment F allow obtain high values of spores, cellulases and chitinases. Substrate (30 g), pH (6), inoculum (1×107 Spores/g), temperature (24°C), moisture (66%), inducer (1%) and time (5 days) were the treatment F conditions.

Now, in the SSF with *P. capsici* biomass, the best results were in the treatment G. It means that the spore, cellulase and chitinase production were high when the conditions are substrate (15 g), pH (8), inoculum (1×107 Spores/g), temperature (24°C), moisture (50%), inducer (3%) and 5 days of incubation.

In the start of the study, we think that the addition of certain concentration of phytopathogen biomass could generate an induction effect of some hydrolase enzymes. The production of chitinases when were used *C. gloeosporioides* and cellulases when were used *P. capsici*. This effect is influenced by the phytopathogen composition (chitin and cellulose, respectively).

In the SSF with *C. gloeosporioides*, the induction of enzymes did not happen maybe because the chitinase is a constitutive enzyme result of the natural metabolism of the microorganism. Previously, the same effect in the chitinase production with *Meyerozyma caribbica* in liquid culture using *C. gloeosporioides* as inducer [15] was observed. A similar study was also reported evaluating the β-*N*-acetylhexosaminidase (a chitinase) by *Verticillium lecanii* using shrimp waste silage as inducer and sugarcane bagasse as support [8].

In the case of SSF with *P. capsici*, the inductor was effective and shows an important effect in all enzyme activities evaluated. We did not find reports of the use of biomass to induce some types of cellulase.

In this study, the moisture and temperature are the two important factors. Among the values evaluated, a level of 66% of moisture and 24°C of temperature shows the best yields in spore and enzymes production on SSF with *C. gloeosporioides* as inducer. In the SSF with *P. capsici* as inducer, the level of moisture was 50%. The two values of moisture used in this study are low which is reported in the literature [8]. They mentioned that the inducer is very important, but also the moisture because they observed that above 75% it can affect the porosity, oxygen diffusion and favor the bacterial contamination. In other hand, low moisture percentage reduces the microbial growth.

This study demonstrated that the biomass addition of any one phytopathogen shows an increment in the spore production by *T. asperellum*. The fungi sporulation starts when the environmental and nutritional conditions become hard to life support. The chemical compo‐ sition of the inducer possibly causes some stress on *T. asperellum* which accelerate the sporu‐ lation process. The experimental stage suggests that high levels of biomass of the inducer increase the sporulation.

Currently, there researches are aimed at the high biomass production of the biological control agents using several systems to produce it. Kancelista *et al*. [16] reported the use of corn cob under SSF by *T. asperellum* obtaining a yield of 3.13×109 spores/g. Motta and Santana [17] who working the SSF with empty fruit bunch and a *Trichoderma* spp. The sporulation index was 4.4×109 spores/g in a Raimbault columns.

There are few works that report the use of polyethylene bioreactors to produce spores in SSF using some biological control. The use of this kind of bioreactor needs to utilize special plastic bags which allow the gas exchange and microorganism respiration [18]. In some cases, we can use a cotton tap on the bag to allow gas exchange. In this study, the maximal spore production obtained was 7.3×108 and 1.4×109 spores/g CS to the SSF with *C. gloeosporioides* and *P. capsici*, respectively. Singh *et al*. [6] used a *Trichoderma harzianum* strain and a similar bioreactor, obtaining a production of 8×108 y de 4.4×106 spores/g CS using tea leaves and sawdust, respectively. Viccini *et al*. [3] did a study of the spore production of *Clonostachys rosea* under SSF conditions using a polyethylene bioreactor and rice grains as substrate. The yield obtained was 1.8×108 spores/g CS.

#### **5. Conclusion**

show the major levels of enzymatic activity (**Figure 6**). All factors evaluated were significant to the exoglucanase production. Low levels of moisture, time, pH, substrate ad inoculum and high levels of inducer and temperature show the best enzyme yields (**Figure 7**). Finally, low levels of moisture, time and pH and high levels of inducer shows the major chitinolytic activity

There are several studies that report the production of different enzymes under SSF [12, 13]. Currently, the SSF is a commonly used system because the raw materials such as sugarcane bagasse, wheat bran, among others [14] are cheaper. The control of temperature, pH, moisture, purity of the culture and process time are some factors that difficult the rigorous control of the

Sometimes, it is hard to find one combination of the SSF conditions in which we can obtain high yield in all response variables evaluated (sporulation, cellulases and chitinases). In the case of SSF with biomass of *C. gloeosporioides*, the best results were observed in the treatment F to spore production and the treatment C to enzyme activities. However, the treatment F also shows great enzyme yields. So the treatment F allow obtain high values of spores, cellulases

Now, in the SSF with *P. capsici* biomass, the best results were in the treatment G. It means that the spore, cellulase and chitinase production were high when the conditions are substrate

In the start of the study, we think that the addition of certain concentration of phytopathogen biomass could generate an induction effect of some hydrolase enzymes. The production of chitinases when were used *C. gloeosporioides* and cellulases when were used *P. capsici*. This effect is influenced by the phytopathogen composition (chitin and cellulose, respectively).

In the SSF with *C. gloeosporioides*, the induction of enzymes did not happen maybe because the chitinase is a constitutive enzyme result of the natural metabolism of the microorganism. Previously, the same effect in the chitinase production with *Meyerozyma caribbica* in liquid culture using *C. gloeosporioides* as inducer [15] was observed. A similar study was also reported evaluating the β-*N*-acetylhexosaminidase (a chitinase) by *Verticillium lecanii* using shrimp

In the case of SSF with *P. capsici*, the inductor was effective and shows an important effect in all enzyme activities evaluated. We did not find reports of the use of biomass to induce some

In this study, the moisture and temperature are the two important factors. Among the values evaluated, a level of 66% of moisture and 24°C of temperature shows the best yields in spore

Spores/g), temperature (24°C), moisture (50%), inducer (3%)

moisture (66%), inducer (1%) and time (5 days) were the treatment F conditions.

Spores/g), temperature (24°C),

and chitinases. Substrate (30 g), pH (6), inoculum (1×107

waste silage as inducer and sugarcane bagasse as support [8].

(**Figure 8**).

52 Fermentation Processes

**4. Discussion**

fermentation process [8].

(15 g), pH (8), inoculum (1×107

and 5 days of incubation.

types of cellulase.

It is possible to obtain high levels of spores, cellulases and chitinases using a polyethylene bioreactor under SSF conditions by *T. asperellum* and corn cob as substrate. Under the SSF conditions evaluated, the biomass of *C. gloeosporioides* has an inducer effect just on the spore production. However, *P. capsici* have effect on all response variables evaluated. The spore production was twice when used *P. capsici* as inducer. The most influential factor under SSF was the moisture. Levels of 66 and 50% of this factor increase the yield in all response variables evaluated (sporulation, cellulases and chitinases), *C. gloeosporioides* and *P. capsici*, respectively. When the biomass of *C. gloeosporioides* was used as a inducer, the best SSF conditions with corn cob and *T. asperellum* are as follows: substrate (30 g), pH (6), inoculum (1×107 Spores/g), temperature (24°C), moisture (66%), inducer (1%) and time (5 days). In the case of *P. capsici*, the conditions are: substrate (15 g), pH (8), inoculum (1×107 Spores/g), temperature (24°C), moisture (50%), inducer (3%) and time (5 days). Further research on SSF with agroindustrial wastes using polyethylene bioreactors, mainly to the reduction of cost in the process, is necessary. Also, it must be make more analyses to determine the optimal production condi‐ tions, as well as, the use of inducers.

#### **Acknowledgements**

The authors thank National Council of Science and Technology (CONACYT, Mexico) for the financial support of this research project. Author de la Cruz-Quiroz thanks IMBE personal for all technical support.

#### **Author details**

Reynaldo De la Cruz-Quiroz1 , Sevastianos Roussos2 , Daniel Hernandez-Castillo3 , Raúl Rodríguez-Herrera1 , Lluvia López-López1 , Francisco Castillo4 and Cristóbal N. Aguilar1\*

\*Address all correspondence to: cristobal.aguilar@uadec.edu.mx

1 Group of Bioprocesses, Food Research Department, Universidad Autónoma de Coahuila, Blvd. V. Carranza esquina González Lobo, Colonia República Oriente, Saltillo, México

2 Equipe Eco technologies et Bioremédiation, Aix Marseille Université & Université Avig‐ non; IMBE UMR CNRS-7263/IRD-237, Case 421, Campus Etoile, Faculté St Jérôme, Marseille Cedex 20, France

3 Agricultural Parasitology Department, Universidad Autónoma Agraria Antonio Narro, Calzada Antonio Narro, Buenavista, Saltillo, México

4 National Institute of Forestry, Agriculture and Livestock Research, Blvd. Vito Alessio Ro‐ bles, Col. Nazario Ortiz Garza, Saltillo, México

#### **References**


[3] Viccini G, Mannich M, Fontana-Capalbo DM, Valdebenito-Sanhueza R, Mitchell DA. 2007. Spore production in solid-state fermentation of rice by *Clonostachys rosea*, a biopesticide for gray mold of strawberries. *Process Biochemistry*. 42:275-278. doi:10.1016/ j.procbio.2006.07.006.

moisture (50%), inducer (3%) and time (5 days). Further research on SSF with agroindustrial wastes using polyethylene bioreactors, mainly to the reduction of cost in the process, is necessary. Also, it must be make more analyses to determine the optimal production condi‐

The authors thank National Council of Science and Technology (CONACYT, Mexico) for the financial support of this research project. Author de la Cruz-Quiroz thanks IMBE personal for

, Daniel Hernandez-Castillo3

and

, Francisco Castillo4

,

, Sevastianos Roussos2

1 Group of Bioprocesses, Food Research Department, Universidad Autónoma de Coahuila, Blvd. V. Carranza esquina González Lobo, Colonia República Oriente, Saltillo, México

2 Equipe Eco technologies et Bioremédiation, Aix Marseille Université & Université Avig‐ non; IMBE UMR CNRS-7263/IRD-237, Case 421, Campus Etoile, Faculté St Jérôme, Marseille

3 Agricultural Parasitology Department, Universidad Autónoma Agraria Antonio Narro,

4 National Institute of Forestry, Agriculture and Livestock Research, Blvd. Vito Alessio Ro‐

[1] Millner RJ. 2000. Current status of *Metarhizium* as mycoinsecticide in Australia. *Biocontrol News and Information*. 21(2):47-50. doi:10.1080/03235400601160065.

[2] Abo-Elyousr KAM, Abdel-Hafez SII, Abdel-Rahim IR. 2014. Isolation of *Trichoderma* and evaluation of their antagonistic potential against *Alternaria porri. Journal of Phyto‐*

, Lluvia López-López1

\*Address all correspondence to: cristobal.aguilar@uadec.edu.mx

Calzada Antonio Narro, Buenavista, Saltillo, México

*pathology*. 162: 567–574. doi:10.1111/jph.12228.

bles, Col. Nazario Ortiz Garza, Saltillo, México

tions, as well as, the use of inducers.

**Acknowledgements**

54 Fermentation Processes

all technical support.

**Author details**

Reynaldo De la Cruz-Quiroz1

Raúl Rodríguez-Herrera1

Cristóbal N. Aguilar1\*

Cedex 20, France

**References**


cellulase by co-culture solid-state bio-processing of corn stover. *WSEAS Transactions on Environment and Development*. 4(9):263-267. Available at: http://www.wseas.org/ multimedia/journals/environme…


#### **Characterization of the Solid-State and Liquid Fermentation for the Production of Laccases of** *Pleurotus ostreatus* **Characterization of the Solid-State and Liquid Fermentation for the Production of Laccases of** *Pleurotus ostreatus*

Gerardo Díaz-Godínez, Maura Téllez-Téllez, Carmen Sánchez and Rubén Díaz Gerardo Díaz-Godínez, Maura Téllez-Téllez, Carmen Sánchez and Rubén Díaz

Additional information is available at the end of the chapter Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/64239

#### **Abstract**

cellulase by co-culture solid-state bio-processing of corn stover. *WSEAS Transactions on Environment and Development*. 4(9):263-267. Available at: http://www.wseas.org/

[15] Bautista-Rosales PU, Calderon-Santoyo M, Servín-Villegas R, Ochoa-Álvarez NA, Ragazzo-Sánchez JA. Action mechanisms of the yeast *Meyerozyma caribbica* for the control of the phytopathogen *Colletotrichum gloeosporioides* in mangoes. *Biological*

[16] Kancelista A, Tril U, Stempniewickz R, Piegza M, Szczech M, Witowska D. 2013. Application of lignocellulosic waste materials for the production and stabilization of *Trichoderma* biomass. Polish Journal of Environmental Studies. 22(4):1083-1090.

[17] Motta FL, Santana MHA. 2014. Solid-state fermentation for humic acid production by *Trichoderma reesei* strain using an oil palm empty fruit bunch as the substrate. *Applied*

[18] Krishna C. 2005. Solid-state fermentation an overview. *Critical Reviews in Biotechnolo‐*

*Biochemistry and Biotechnology*. 172:2205-2217. doi:10.1007/s12010-013-0668-2.

doi:bwmeta1.element.agro-6ccb71f0-b739-49a9-a9ea-2b515c9f6d5a.

multimedia/journals/environme…

56 Fermentation Processes

*Control*. 65:293-301. doi:10.1016/j.biocontrol.2013.03.010

*gy*. 25(1): 1-30. doi:10.1080/07388550590925383.

In this chapter, the activity and isoenzymes number of laccases of *Pleurotus ostreatus* grown in solid-state and liquid fermentations are reported. An atypical behavior of this fungus with relation on enzyme production was observed, since the major laccase activity levels were observed in liquid fermentation, whereas the solid-state fermentation has been recognized as better system for enzyme production.

**Keywords:** laccases, *Pleurotus ostreatus*, solid-state fermentation, submerged fermentation, ligninolytic enzymes

#### **1. Introduction**

Laccases are enzymes oxygen oxidoreductases produced by plants, insects, bacteria, and fungi. The most studied laccases are fungal origin, mainly of white rot fungi using different culture systems, mainly in solid-state fermentation (SSF) and liquid fermentation (SmF). In general, it has been suggested that the solid-state fermentation is better for the production of metabolites and enzymes compared with SmF [1]; however, in recent studies has been observed that the basidiomycete *Pleurotus ostreatus* grown in SmF reported higher laccases values compared to those when the fungus grown in solid-state fermentation. *P. ostreatus* strain ATCC 32783 has been studied for the production of intracellular laccases of peripheral and central vegetative mycelium [2], have also been evaluated the solid-state fermentation and SmF systems for laccases

© 2017 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2017 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

production, observing different levels of activity and number of isoenzymes depending on the culture system [3, 4]. When compared some strains of *P. ostreatus* with ATCC 32783, the latter being better than others [5]. In other study, the effect of pH of the culture medium on the laccases activity of *P. ostreatus* developed in SmF was evaluated, where the activity was seven times higher when the pH of the medium did not change [6]. It has been reported the description of a novel gene encoding a laccase of *P. ostreatus* ATCC 32783 called lacP83, which is preferentially expressed in liquid culture conditions [7]. Recently, the effect of initial pH of development from 3.5 to 8.5 on the laccase activity was evaluated; the pattern of production and the expression profile of five laccase genes of *P. ostreatus* ATCC 32783 grown in SmF, showing that the pH of 8.5 favors biomass production but not enzymatic activity and shows repression of gene expression, however, the pH 4.5 showed higher laccase enzyme activity, reaching up to 78,500 U/L [8].

#### **2.** *Pleurotus ostreatus*

#### **2.1.** *Pleurotus ostreatus***: phases of growth and composition**

The genus *Pleurotus* (Jacq.: Fr.) Kummer (Pleurotaceae, higher Basidiomycetes) comprises a group of edible ligninolytic mushrooms, which have two phases of growth: one is called vegetative or mycelial and is seen as strands of hyphae, which colonize the substrate and the other, the reproductive or fruit body, is represented by the mushroom itself that in basidiomycetes, is called the basidiome. *P. ostreatus* is characterized by a white spore print, with an eccentric stipe and a fan or oyster-shared pileus or cap (5–25 cm). The Latin *Pleurotus* means "beside the ear" and *ostreatus* means "oyster shaped." This fungus is commonly named "oyster mushroom" for the resemblance of its fruiting body a white shell [9]. In this case, the spores are located in a special structure called basidium. In the *P. ostreatus* growth, after spore germination (or inoculation of *in vitro*-grown mycelia), the substrate is invaded by microscopic filaments called hyphae. Hyphae continually grow and branch to form a network of hyphae. Mycelial growth is generally coupled with increased enzyme production and respiration. Hyphae absorb digestive products, penetrating the substrate until its complete hyphal invasion. The vegetative growth is in direct contact with the support (substrate), providing the nutritive materials required for mushroom growth (**Figure 1**)[10].

The growth of all parts of a fungus occurs at the hyphal tips. The mycelial structure grows by synthesizing new wall at the hyphal apex, as they increase in length, additional sites for wall synthesis are formed in the subapical region, originating lateral branches that synthetize wall again confined to the hyphal tip [11]. The formation of a new branch requires the production of a new apex from the existing mature hyphal cell. It has been reported that some enzymes such as proteinases could create weakened zones in the cell wall, which could be pushed out by cytoplasmic flow to initiate branching. So in the mycelial growth, in addition to activation of the cell wall synthesis, enzymes such as chitin synthetase and proteinases, which might weaken the lateral cell walls, are also important. During growth of vegetative hyphae, a large amount of nutrient absorbed from the substrate is stored. Polysaccharide may be stored in the form of glucans in secondary wall layers and/or as glycogen granules in the cytoplasm in the cell. The cells in a hypha are separated by a cross-wall called septum. Septa placement has been production, observing different levels of activity and number of isoenzymes depending on the culture system [3, 4]. When compared some strains of *P. ostreatus* with ATCC 32783, the latter being better than others [5]. In other study, the effect of pH of the culture medium on the laccases activity of *P. ostreatus* developed in SmF was evaluated, where the activity was seven times higher when the pH of the medium did not change [6]. It has been reported the description of a novel gene encoding a laccase of *P. ostreatus* ATCC 32783 called lacP83, which is preferentially expressed in liquid culture conditions [7]. Recently, the effect of initial pH of development from 3.5 to 8.5 on the laccase activity was evaluated; the pattern of production and the expression profile of five laccase genes of *P. ostreatus* ATCC 32783 grown in SmF, showing that the pH of 8.5 favors biomass production but not enzymatic activity and shows repression of gene expression, however, the pH 4.5 showed higher laccase enzyme activity, reaching up to 78,500 U/L [8].

The genus *Pleurotus* (Jacq.: Fr.) Kummer (Pleurotaceae, higher Basidiomycetes) comprises a group of edible ligninolytic mushrooms, which have two phases of growth: one is called vegetative or mycelial and is seen as strands of hyphae, which colonize the substrate and the other, the reproductive or fruit body, is represented by the mushroom itself that in basidiomycetes, is called the basidiome. *P. ostreatus* is characterized by a white spore print, with an eccentric stipe and a fan or oyster-shared pileus or cap (5–25 cm). The Latin *Pleurotus* means "beside the ear" and *ostreatus* means "oyster shaped." This fungus is commonly named "oyster mushroom" for the resemblance of its fruiting body a white shell [9]. In this case, the spores are located in a special structure called basidium. In the *P. ostreatus* growth, after spore germination (or inoculation of *in vitro*-grown mycelia), the substrate is invaded by microscopic filaments called hyphae. Hyphae continually grow and branch to form a network of hyphae. Mycelial growth is generally coupled with increased enzyme production and respiration. Hyphae absorb digestive products, penetrating the substrate until its complete hyphal invasion. The vegetative growth is in direct contact with the support (substrate), providing the

The growth of all parts of a fungus occurs at the hyphal tips. The mycelial structure grows by synthesizing new wall at the hyphal apex, as they increase in length, additional sites for wall synthesis are formed in the subapical region, originating lateral branches that synthetize wall again confined to the hyphal tip [11]. The formation of a new branch requires the production of a new apex from the existing mature hyphal cell. It has been reported that some enzymes such as proteinases could create weakened zones in the cell wall, which could be pushed out by cytoplasmic flow to initiate branching. So in the mycelial growth, in addition to activation of the cell wall synthesis, enzymes such as chitin synthetase and proteinases, which might weaken the lateral cell walls, are also important. During growth of vegetative hyphae, a large amount of nutrient absorbed from the substrate is stored. Polysaccharide may be stored in the form of glucans in secondary wall layers and/or as glycogen granules in the cytoplasm in the cell. The cells in a hypha are separated by a cross-wall called septum. Septa placement has been

**2.** *Pleurotus ostreatus*

58 Fermentation Processes

**2.1.** *Pleurotus ostreatus***: phases of growth and composition**

nutritive materials required for mushroom growth (**Figure 1**)[10].

reported to depend on the position of nuclear division. The septum is formed by chitin deposition on a preformed ring of actin microfilament. Dolipore septa divide hyphae into compartments or cells where movement of cytoplasmic material between them is carefully regulated. It gives rigidity to the hyphae and it can help avoid further injury if damage occurs at the hyphal tip [12]. In a developed colony, the hyphae tip growth or peripheral growth zone forms continuity between hyphae because of the presence of dolipore septa. The growing tips have a constant forward advance, so the mycelium that is left behind seems no longer involved in the growth. At the beginning of the fructification, the characteristic invasive growth of the vegetative mycelium in the substrate is modified. The fruit body initial is formed by increase in mycelial mass, with the formation of additional hyphal branching between the hyphae. The fruit body formation begins with the aggregation of hyphae to form a "knot" that will develop into a primordium and then a mature fruit body with differentiated stem and cap. It has been reported that the most important quantitative change in the cell wall during fruiting is the almost total loss of water-soluble glucan, instead, chitin has been reported important in fruit body development, which is essential for elongation of the stem hyphal walls. The precursor of chitin is N-acetylglucosamine and it is incorporated in the elongation of the hyphae of fruit bodies during expansion. Glycogen is accumulated in the base of fruit bodies at very earlier stages of growth and then disappears from the base as it is accumulated in the cap. In fruit body development, carbohydrates from the culture medium are temporarily store in R-glucan (alkali insoluble glucan) in the wall of mycelia and fruit body primordium hyphae, which is utilized for pileus development in the growing fruit bodies. *Pleurotus* species are cosmopolitan reported mainly as subtropical mushrooms. The optimal temperatures for growth of the mycelium are around 25–28°C and the range of pH is about 6.0–7.0. For fruit body formation, optimal temperature, relative humidity, CO2, and light are 10−21°C, 85–90%, <1000 ppm, and 1000–1500 lx, respectively [13].

**Figure 1.** Schematic representation of the growth of *Pleurotus ostreatus* [10].

*P. ostreatus* can be considered as functional food with nutritional and health benefits in addition to nutritional value [14]. This mushroom contains vitamins as well as an abundance of essential amino acids. It also has proteins, lipids, ash, glycosides, tocopherols, phenolic compounds, flavonoids, carotenoids, folates, organic acids, etc. [15, 16]. In general, mushrooms contain 90% water and 10% dry matter, and their nutritional value can be compared to those of eggs, milk, and meat [17]. The total energetic value of cultivated species of *P. ostreatus* is 151 J in 100 g of fresh mushrooms [18].

*P. ostreatus* is the second most cultivated edible mushroom worldwide after *Agaricus bisporus* [13]. Technological improvements have made possible this mushroom cultivation worldwide. It has ability to degrade several lignocellulosic substrates due to its ability to secrete a wide range of hydrolyzing and oxidizing enzymes [19] and can be produced on natural materials from agriculture, woodland, animal husbandry, and manufacturing industries [13].

#### **2.2. Ligninolytic enzymes of** *Pleurotus* **spp.**

From an ecophysiological point of view, white-rot basidiomycetes are microorganisms able to degrade lignin efficiently. However, the degree of lignin degradation with respect to other wood components depends on the environmental conditions as well as the fungal species involved. *Pleurotus* species cause white rot of wood and other lignocellulosic materials, due to their oxidative and extracellular ligninolytic system. The fungal degradation occurs exocellularly, either in association with the outer cell envelope layer or extracellularly, because of the insolubility of lignin, cellulose, and hemicellulose. Three ligninolytic enzyme families have been reported as the enzymatic complex from *Pleurotus* species; manganese peroxidase (EC 1.11.1.13), versatile peroxidase (EC 1.11.1.16) and laccase (EC 1.10.3.2) but lack lignin peroxidase. Recently, was reported that in *Pleurotus ostreatus*, the role that generally played the lignin peroxidase, has been assumed by versatile peroxidase. [20]. Studies on the enzymes secreted by *P. ostreatus* have shown that the concerted action of laccase and aryl-alcohol oxidase produce significant reduction in the molecular mass of soluble lignosulphonates [21].

Additional peroxidases, such as dye decolorizing peroxidases have also been detected in *P. ostreatus* [22, 23]. Lignin biodegradation is an oxidative process, as a consequence *Pleurotus* enzymes can be involved in such processes. The manganese peroxidase gene family (mnps) of *P. ostreatus* is composed of five Mn2+-dependent peroxidases (mnp3, 6, 7, 8, and 9) and four versatile peroxidases (mnp1, 2, 4, and 5), all having related gene and protein structure [24]. Mn2+-dependent peroxidases (MnP) catalyze the H2O2-dependent oxidation of lignin and its derivatives [25]. Mn is an obligatory cosubstrate for these enzymes, as it is required to complete the catalytic cycle. In fact, the oxidation of lignin and other phenols by MnP is dependent on free Mn2+ ions. This peroxidase does not oxidize nonphenolic lignin structures. It lacks sufficient oxidative potential to cleave the major nonphenolic units of lignin. MnP contains Mn2+-binding catalytic site that is formed by three acidic residues (two Glu and one Asp) and generates Mn3+, which acts as a diffusible oxidizer on phenolic or nonphenolic lignin units through lipid peroxidation reactions [26, 27]. In many fungi, MnP thought to play a crucial role in the primary attack of lignin because it generates a diffusible and strong oxidant (Mn3+). Organic acids such as oxalate and malonate are secreted by white-rot fungi, stimulating the MnP reaction throughout the stabilizing of Mn3+ [28, 29]. Versatile peroxidases feature Mnbinding residues as well as conserved Trp involved in the electron transfer that enables oxidation of nonphenolic compounds. Versatile peroxidases possess two catalytic sites, one for the direct oxidation of low- and high-redox potential compounds, and the other for oxidation of Mn in a preferred manner [23, 30–33]. This dual activity mode of action enables versatile peroxidases to modify a wide range of substrates. It has been suggested a role for versatile peroxidases of *P. ostreatus* in the transformation of azo dyes [23, 30, 34] and carbamazepine [35].

Laccases are blue copper oxidases that catalyze the one-electron oxidation of *ortho*- and *para*diphenols, aromatic amines by removing an electron and a proton from a hydroxyl group to form a free radical. Their oxidation of the phenolic units in lignin generates phenoxy radicals. Laccases also catalyze the demethoxylation of several lignin model compounds [36–38], such oxidation activity is accompanied by the reduction of molecular oxygen to water. In laccase, histidine and aspartic residues are involved in binding the phenolic compounds, and histidine residue itself is involved in the binding of nonphenolic substrates [39]. Laccase activity in fungal cultures can be increased by the addition of different aromatic compounds to the media, producing different forms of laccase due to the supplementation of aromatic compounds [40, 41]. The ligninolytic system of *P. ostreatus* makes this organism useful in several practical applications of cell-free or purified forms of peroxidases in bioremediation and biotransformation of persistent organic pollutant.

#### **2.3. Laccases**

amino acids. It also has proteins, lipids, ash, glycosides, tocopherols, phenolic compounds, flavonoids, carotenoids, folates, organic acids, etc. [15, 16]. In general, mushrooms contain 90% water and 10% dry matter, and their nutritional value can be compared to those of eggs, milk, and meat [17]. The total energetic value of cultivated species of *P. ostreatus* is 151 J in 100 g of

*P. ostreatus* is the second most cultivated edible mushroom worldwide after *Agaricus bisporus* [13]. Technological improvements have made possible this mushroom cultivation worldwide. It has ability to degrade several lignocellulosic substrates due to its ability to secrete a wide range of hydrolyzing and oxidizing enzymes [19] and can be produced on natural materials

From an ecophysiological point of view, white-rot basidiomycetes are microorganisms able to degrade lignin efficiently. However, the degree of lignin degradation with respect to other wood components depends on the environmental conditions as well as the fungal species involved. *Pleurotus* species cause white rot of wood and other lignocellulosic materials, due to their oxidative and extracellular ligninolytic system. The fungal degradation occurs exocellularly, either in association with the outer cell envelope layer or extracellularly, because of the insolubility of lignin, cellulose, and hemicellulose. Three ligninolytic enzyme families have been reported as the enzymatic complex from *Pleurotus* species; manganese peroxidase (EC 1.11.1.13), versatile peroxidase (EC 1.11.1.16) and laccase (EC 1.10.3.2) but lack lignin peroxidase. Recently, was reported that in *Pleurotus ostreatus*, the role that generally played the lignin peroxidase, has been assumed by versatile peroxidase. [20]. Studies on the enzymes secreted by *P. ostreatus* have shown that the concerted action of laccase and aryl-alcohol oxidase produce

Additional peroxidases, such as dye decolorizing peroxidases have also been detected in *P. ostreatus* [22, 23]. Lignin biodegradation is an oxidative process, as a consequence *Pleurotus* enzymes can be involved in such processes. The manganese peroxidase gene family (mnps) of *P. ostreatus* is composed of five Mn2+-dependent peroxidases (mnp3, 6, 7, 8, and 9) and four versatile peroxidases (mnp1, 2, 4, and 5), all having related gene and protein structure [24]. Mn2+-dependent peroxidases (MnP) catalyze the H2O2-dependent oxidation of lignin and its derivatives [25]. Mn is an obligatory cosubstrate for these enzymes, as it is required to complete the catalytic cycle. In fact, the oxidation of lignin and other phenols by MnP is dependent on free Mn2+ ions. This peroxidase does not oxidize nonphenolic lignin structures. It lacks sufficient oxidative potential to cleave the major nonphenolic units of lignin. MnP contains Mn2+-binding catalytic site that is formed by three acidic residues (two Glu and one Asp) and generates Mn3+, which acts as a diffusible oxidizer on phenolic or nonphenolic lignin units through lipid peroxidation reactions [26, 27]. In many fungi, MnP thought to play a crucial role in the primary attack of lignin because it generates a diffusible and strong oxidant (Mn3+). Organic acids such as oxalate and malonate are secreted by white-rot fungi, stimulating the MnP reaction throughout the stabilizing of Mn3+ [28, 29]. Versatile peroxidases feature Mnbinding residues as well as conserved Trp involved in the electron transfer that enables

from agriculture, woodland, animal husbandry, and manufacturing industries [13].

significant reduction in the molecular mass of soluble lignosulphonates [21].

fresh mushrooms [18].

60 Fermentation Processes

**2.2. Ligninolytic enzymes of** *Pleurotus* **spp.**

Laccases (benzenediol: oxygen oxidoreductases, EC 1.10.3.2) are enzymes classified as multicopper oxidases. These glycoproteins have the redox ability of copper ions to catalyze the oxidation of a wide range of aromatic substrates where water is obtained as by-product from the reduction of molecular oxygen [42, 43]. Laccases were first time reported in the Japanese lacquer tree (*Rhus vernicifera*) [44]. Laccases has been observed in plants, insects, bacteria, but the most studied are from the fungi classified as of rot-white, where are considered as ligninolytic enzymes because lignin sources are the best substrate for the growth of these fungi. These enzymes occur mainly in basidiomycetes, deuteromycetes, and ascomycetes, but their production in lower fungi has never been observed [45]. There exists a wide diversity of laccases including isoenzymes produced by fungi that have very different physicochemical properties. Numbers of isoenzymes depend on the fungal species [2, 7, 46–48]. In general, laccases show molecular weight between 40 and 100 kDa with 10–50% of their total weight of glycosylation and with isoelectric point (p*I*) around pH 4.0. It has been reported that the glycosylation in fungal laccase plays a role in secretion, copper retention, susceptibility to proteolytic degradation, and thermal stability [49, 50]. The growth conditions of fungi and their physiological states are responsible for the expression of different laccase isoenzymes, which are coded by gene families and differentially regulated [4, 7, 41, 51, 52]. In *P. ostreatus*, 12 possible genes encoding laccases have been reported and only described and characterized 7 isoenzymes laccase: lacc2 [47], lacc4 [53], lacc6 [54], lacc9 [55], lacc10 [56, 57], lacc12 [58] and lacP83 [7]. The characteristics of some purified enzymes from *P. ostreatus* using 2,6-dimethoxyphenol (DMP), 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid) (ABTS), syringaldazine (SYR) and guaiacol (GUA) as substrate are reported in **Table 1**[**59**–**65**].


**Table 1.** Characteristics of laccases from *Pleurotus* spp.

Laccases have a high capacity and nonspecific oxidation which allow their use in many biotechnology applications, such as detoxification of wastewater produced in pulp bleaching process [66] and from industrial plants [67], treatment of elimination of phenolic compounds in beer and processed fruit juices [68], in effluent discoloration and modification of textile fibers [69], as biosensors [70], as drug testing (to distinguish morphine from codeine) [71]. Another important application is in environmental remediation; laccases have shown ability of degrading hazardous compounds that have carcinogenic and/or mutagenic effects, including polycyclic aromatic hydrocarbons (PAH), polychlorinated biphenyls (PCB), 1,1,1-trichloro-2,2 bis (4-chlorophenyl) ethane (DDT), pentachlorophenols (PCP), toluene, benzene, xylene (BTEX), ethylbenzene, and trinitrotoluene (TNT) [72].

#### **2.4. Production of laccases of** *Pleurotus* **in solid-state and submerged fermentation**

SSF has been defined as the bioprocess carried out in the absence or near absence of free water by the use a solid matrix with high water adsorption; the solid matrix could be biodegradable or inert, but in both cases must possess enough moisture to support growth and metabolism of the microorganism. Biodegradable solid matrix acts as support and source of nutrients and in the inert matrix, it is only the support and the culture liquid medium must be added [73, 74]. SSF has been a very efficient process for the production of enzymes by filamentous fungi [75, 76], possibly, they reproduce the natural living conditions [77].

**Fungal species**

62 Fermentation Processes

*POXA1b P. ostreatus*

*POXA1w P. ostreatus*

*POXA2 P. ostreatus*

*POXA3a P. ostreatus*

*POXA3b P. ostreatus*

*POXC P. ostreatus*

Lcc2

*P. pulmonarius*

**Optimum pH of activity using different**

**DMP ABTS SYR GUA**

*P. ostreatus* 5.8 3.6 67 50 [59]

*P. florida* 4.1 77 [63] *P. sajor-caju* IV 2.1 3.6 55 [64] *P. eryngii* I 4.5 4.1 65 55 [65] *P. eryngii* II 4.5 4.2 61 55 [65]

Laccases have a high capacity and nonspecific oxidation which allow their use in many biotechnology applications, such as detoxification of wastewater produced in pulp bleaching process [66] and from industrial plants [67], treatment of elimination of phenolic compounds in beer and processed fruit juices [68], in effluent discoloration and modification of textile fibers [69], as biosensors [70], as drug testing (to distinguish morphine from codeine) [71]. Another important application is in environmental remediation; laccases have shown ability of degrading hazardous compounds that have carcinogenic and/or mutagenic effects, including polycyclic aromatic hydrocarbons (PAH), polychlorinated biphenyls (PCB), 1,1,1-trichloro-2,2 bis (4-chlorophenyl) ethane (DDT), pentachlorophenols (PCP), toluene, benzene, xylene

**2.4. Production of laccases of** *Pleurotus* **in solid-state and submerged fermentation**

SSF has been defined as the bioprocess carried out in the absence or near absence of free water by the use a solid matrix with high water adsorption; the solid matrix could be biodegradable

**pI MW (kDa)**

4.5 3.0 6.0 6.9 62 [54]

3.0–5.0 3.0 6.0 6.7 61 45–65 [60]

6.5 3.0 6.0 6.0 4.0 67 25–35 [61]

5.5 3.6 6.2 4.1 83–85 35 [47]

5.5 3.6 6.2 4.3 83–85 35 [47]

3.0–5.0 3.0 6.0 6.0 2.9 59 50–60 [56–61]

4.0–5.5 6.2–6.5 6.0–8.0 46 50 [62]

**Optimum temperature (°C)** **Reference**

**substrates**

**Table 1.** Characteristics of laccases from *Pleurotus* spp.

(BTEX), ethylbenzene, and trinitrotoluene (TNT) [72].

SSF is the best culture system to study the morphological and metabolic differences between aerial hyphae and those that penetrate in the solid matrix [78]. It has been reported that SSF is better system than SmF for production of fungal enzymes, because it provides higher volumetric productivities, is less sensible to catabolite repression and yields enzymes with a higher stability at temperature and/or pH [1]. The fermentation could be carried out in less time and the productions of undesirable proteases that degrade enzymes of interest are minimized [78, 79]. Several studies in this field have determined the physiological differences during the growth of microbial cells in the two types of processes. The use of an adequate support for performing SSF is essential, since the success of the fermentation depends on it [80]. Castanera et al. [81] reported that laccase gene transcription is upregulated in an induced SmF but downregulated in the SSF, when were determined the laccases expression profiles in different fungal strains under SmF and SSF using wheat straw extract as inducer.

In a study was found that *P. ostreatus* grown in SSF on wheat bran and vinasse produced twice laccase activity (20 U/ml and three isoforms) than those reported in SmF (10 U/ml and two isoforms) [82]. It has been reported the intracellular activity and isoenzymes number of laccase of 10 strains of *Pleurotus* spp. grown on agar without addition of inducers. Differences in the *in vitro* activities using different substrates (2,6-dimethoxyphenol, *p*-anisidine, or *o*-tolidine) were observed between all the strains; zymogram patterns were similar for strains within same species, independently of any of the three substrate used [2]. Similar results were found in the extracellular extracts obtained of the same strains grown as above was mentioned [7]. In other study was used the same composition of the culture medium to grow *P. ostreatus* (ATCC 32783) in both SmF and SSF using polyurethane foam (PUF) as inert support. Atypical behavior was observed, since in SmF the fungus reported a laccase activity of 13,000 U/L with a biomass production of 5.6 g/L and four laccase isoforms, while SSF had a much lower laccase activity (2430 U/L), with biomass production of 4.5 g/L and three laccase isoforms. These results show that *P. ostreatus* performs much better in SmF than in SSF [4].

*P. ostreatus* (ATCC 32783) was grown at different initial pH of the culture medium in SSF using PUF. In general, the fungus showed high values of specific growth rate at all pH tested, the higher were at pH 3.5 and 8.5 (0.078 and 0.082 h-1, respectively), whereas at pHs of 4.5, 6.5, and 7.5 were 0.047, 0.034, and 0.047 h-1. Furthermore, the maximum biomass values were low, about 3.7 g/L in all cases. The maximum values of laccase activity were approximately 40,000 U/L observed in fermentation development at pH 4.5 and 6.5. The largest number of isoenzymes was observed in fermentations carried out at pH 7.5 and 8.5 [83].

*Pleurotus pulmonarius* (Fr) Quélet was cultivated on SSF using corn cob as substrate to produce laccase. The addition of 25 mM CuSO4 increased from 270 to 1420 U/L the laccase production [84]. In other study, *Pleurotus pulmonarius* was grown on SSF using several natural supports, obtaining high laccase activities in wheat bran (2860 ± 250 U/L), pineapple peel (2450 ± 230 U/

L), and orange bagasse (2100 ± 270 U/L) [85]. Recently, the growth of *Pleurotus eryngii* on SSF using different agricultural wastes was reported and its laccase activity was evaluated in mycelium, primordium, and fruiting body. Laccase activities were comparably low in mycelial and primordium. The highest laccase activity was obtained in fruiting body developed on both wheat straw and cotton stalk. The laccase activities of 125.65 and 205.83 U/L of fruiting body were observed on wheat straw +5% of rice bran and on cotton stalk +5 % of rice bran, respectively [86]. Maximum activity of laccase during vegetative phase of growth of *P. ostreatus* can be directly correlated with degradation of lignin in this stage [87].

Different strains of *Lentinula edodes* and *Pleurotus* species were compared for the first time for their ability to produce lignocellulolytic enzymes in SmF and SSF using various plant raw materials. Two strains of *Lentinula edodes* (IBB 123 and IBB 363) appeared to be better producers of laccase than oyster mushrooms. In SSF, *Lentinula edodes* IBB 123 reached laccase activity of 57 U/flask on day 7 of fermentation. *Pleurotus tuber-regium* IBB 624 showed 20 U/flask of laccase activity after 10 days of fermentation, other fungi of this genus produced only 7–16 U/flask of laccase during 7 or 10 days of SSF [88].

*P. ostreatus* and *Pleurotus sajor-caju* were grown in SSF and their ability to produce laccase and carboxymethylcellulase (CMCase) on different agricultural wastes was studied. *Pleurotus* was inoculated on viticulture wastes, wheat straw, paddy straw, sesame straw, sawdust, and the mixtures of these wastes with wheat bran. Different mycelial growth times were related with different patterns of enzyme activities. During the incubation period, *P. ostreatus* showed its highest values of laccase activity at 10th day and decreased gradually until the first harvest. The highest laccase activity was observed on mixture of wheat straw:bran (2:1) (5.48 U/mg), followed by on paddy straw:bran (2:1) (4.36 U/mg) and on viticulture wastes:bran (2:1) (3.51 U/mg) at 10th day of mycelial growth. The lowest laccase activity was obtained on viticulture wastes (0.30 U/mg) [89]. It has been reported that laccase activity could be regulated, increasing the activity in morphogenesis during the mycelial growth and then the enzyme level decreases rapidly [90]. The laccase production of an indigenous strain of *P. ostreatus* (HP-1) was studied on SSF. Culture parameters, including type and concentration of substrate, moisture content, inoculum size, temperature, pH, surfactant presence, and nitrogen source, were optimized by conventional one factor at a time methodology. Maximum laccase activity of 3952 U/g of dry substrate was obtained with wheat straw as substrate, incubation temperature 28°C, five agar plugs as inoculum, pH 5.0, 60% moisture content, surfactant concentration 0.015 g/L, and combination of L-asparagine and NH4NO3 at 10 mM concentration each as nitrogen source. Laccase activity was increased with the use of various aromatic inducers and CuSO4. Highest laccase activity of 14189 U/g of dry substrate was obtained using 0.28 mM CuSO4 under optimized conditions [91]. *P. ostreatus* was grown in SSF conditions for production of laccase, manganese peroxidase, and lignin peroxidase. Highest enzymes levels (laccase 455.11, manganese peroxidase 210.77, and lignin peroxidase 54.50 U/ml) were observed at 7 days in a medium containing 5 g wheat straw (66% w/w moisture), 4 ml inoculum at pH 4.5 and 30°C, using 1% (v/v) glycerol as carbon source, 0.2% (w/w) urea as nitrogen source, 1% (w/v) 2,2 azinobis 3-ethylbenzthiazoline 6 sulphonate as laccase inducer and 1% (w/v) MnSO4 for manganese peroxidase, 1% (w/v) CuSO4 as metal ion for laccase, and Mn+ for manganese peroxidase [92].

L), and orange bagasse (2100 ± 270 U/L) [85]. Recently, the growth of *Pleurotus eryngii* on SSF using different agricultural wastes was reported and its laccase activity was evaluated in mycelium, primordium, and fruiting body. Laccase activities were comparably low in mycelial and primordium. The highest laccase activity was obtained in fruiting body developed on both wheat straw and cotton stalk. The laccase activities of 125.65 and 205.83 U/L of fruiting body were observed on wheat straw +5% of rice bran and on cotton stalk +5 % of rice bran, respectively [86]. Maximum activity of laccase during vegetative phase of growth of *P. ostreatus* can

Different strains of *Lentinula edodes* and *Pleurotus* species were compared for the first time for their ability to produce lignocellulolytic enzymes in SmF and SSF using various plant raw materials. Two strains of *Lentinula edodes* (IBB 123 and IBB 363) appeared to be better producers of laccase than oyster mushrooms. In SSF, *Lentinula edodes* IBB 123 reached laccase activity of 57 U/flask on day 7 of fermentation. *Pleurotus tuber-regium* IBB 624 showed 20 U/flask of laccase activity after 10 days of fermentation, other fungi of this genus produced only 7–16 U/flask of

*P. ostreatus* and *Pleurotus sajor-caju* were grown in SSF and their ability to produce laccase and carboxymethylcellulase (CMCase) on different agricultural wastes was studied. *Pleurotus* was inoculated on viticulture wastes, wheat straw, paddy straw, sesame straw, sawdust, and the mixtures of these wastes with wheat bran. Different mycelial growth times were related with different patterns of enzyme activities. During the incubation period, *P. ostreatus* showed its highest values of laccase activity at 10th day and decreased gradually until the first harvest. The highest laccase activity was observed on mixture of wheat straw:bran (2:1) (5.48 U/mg), followed by on paddy straw:bran (2:1) (4.36 U/mg) and on viticulture wastes:bran (2:1) (3.51 U/mg) at 10th day of mycelial growth. The lowest laccase activity was obtained on viticulture wastes (0.30 U/mg) [89]. It has been reported that laccase activity could be regulated, increasing the activity in morphogenesis during the mycelial growth and then the enzyme level decreases rapidly [90]. The laccase production of an indigenous strain of *P. ostreatus* (HP-1) was studied on SSF. Culture parameters, including type and concentration of substrate, moisture content, inoculum size, temperature, pH, surfactant presence, and nitrogen source, were optimized by conventional one factor at a time methodology. Maximum laccase activity of 3952 U/g of dry substrate was obtained with wheat straw as substrate, incubation temperature 28°C, five agar plugs as inoculum, pH 5.0, 60% moisture content, surfactant concentration 0.015 g/L, and combination of L-asparagine and NH4NO3 at 10 mM concentration each as nitrogen source. Laccase activity was increased with the use of various aromatic inducers and CuSO4. Highest laccase activity of 14189 U/g of dry substrate was obtained using 0.28 mM CuSO4 under optimized conditions [91]. *P. ostreatus* was grown in SSF conditions for production of laccase, manganese peroxidase, and lignin peroxidase. Highest enzymes levels (laccase 455.11, manganese peroxidase 210.77, and lignin peroxidase 54.50 U/ml) were observed at 7 days in a medium containing 5 g wheat straw (66% w/w moisture), 4 ml inoculum at pH 4.5 and 30°C, using 1% (v/v) glycerol as carbon source, 0.2% (w/w) urea as nitrogen source, 1% (w/v) 2,2 azinobis 3-ethylbenzthiazoline 6 sulphonate as laccase inducer and 1% (w/v) MnSO4 for

be directly correlated with degradation of lignin in this stage [87].

laccase during 7 or 10 days of SSF [88].

64 Fermentation Processes

Different concentrations of apple pomace were evaluated on laccase production by *P. ostreatus*. During the first four days of fermentation, there was not laccase production. The maximum laccase activity (114.64 U/ml), was observed at 9 days of fermentation in the medium with 2.5% (w/v) apple pomace. This activity was approximately 2.8 times (30.24 U/ml) and 0.9 times (60.49 U/ml) higher than that of *P. ostreatus* with 5% (w/v) and without apple pomace, respectively. These results suggest that *P. ostreatus* might use the nutrient content of apple pomace (rich in carbohydrates, dietary fiber, and minerals) without laccase activity in the initial stages of cultivation (approximately 4 days) [93].

Recently, optimization of the laccases production of *P. ostreatus* grown on sugarcane bagasse in SSF was worked. Water activity, pH, temperature, and concentrations of CuSO4, (NH4)2SO4, KH2PO4, asparagine, and yeast extract were variables used in the optimization. The concentrations of CuSO4 and (NH4)2SO4 had a significant influence on the production of laccase, but the use of yeast extract and the addition of ferulic acid as inducer provided increases of laccase activity of 5.7 times and 2.0 times, respectively. The highest laccase activity of 151.6 U/g was produced at the 5th day of SSF [94].

Cocultivation of *P. ostreatus* MTCC 1804 and mutant *Penicillium oxalicum* SAUE-3.510 was studied for the production of xylanase-laccase mixture under SSF condition. Growth compatibility between both fungi was analyzed by growing them on potato dextrose agar plate, obtaining 58% and 33% higher levels of xylanase and laccase production, respectively. A mixture of sugarcane bagasse and black gram husk (3:1) was the best solid substrate and support for fungal colonization and enzyme production during co cultivation. Maximum activity values of xylanase (8205.31 IU/g) and laccase (375.53 IU/g) during SSF were observed using 4 g of solid support with 80% of moisture content. The coculture system was efficient in the production of xylanases and laccases that may be employed in agroindustrial waste degradation [95].

*P. ostreatus* (ATCC 32783) was grew under SmF conditions and found the production profile of laccases as well as the isoenzymes patterns through zymograms. Four laccase isoenzymes were produced, one throughout the fermentation time and three only during growth stationary phase. The maximum laccase activity (12200 U/L) was observed in the growth stationary phase. Kinetic parameters of a purified isoenzyme (enzyme produced throughout the fermentation), such as the apparent molecular weight of 43.7 kDa, *K*m 90 μM, *V*max 1.18 ΔAbs/min, and p*I* of 2.3, were obtained [3].

On the other hand, the growth and activity of laccases from of five different strains of *P. ostreatus* developed under SmF conditions with and without copper added to the culture medium was studied. It was observed that the concentration of CuSO4·5H2O (0.25 g/L) did not affect the growth of the strain ATCC 32783, however, other strains showed lower growth rates and less biomass, the ATCC 201216 strain almost was inhibited. ATCC 32783 strain showed the highest values of laccase activity in the presence of copper reaching up to 37490 U/L, whereas in the culture without copper was obtained 1086 U/L; ATCC 201216 strain in the presence and absence of copper produced 1400 and 1000 U/L, respectively. These results suggest that not all strains have the same answer to the presence of Cu in the culture medium, and the sensitivity to Cu be could use to select strains with high laccase production for commercial exploitation [5].

The activity and isoenzymes number of laccase from *P. ostreatus* ATCC 32783 grown in SmF conditions using a buffered and nonbuffered media were studied. For both culture media, the initial pH was 3.5. Laccase activity was around 100–500 U/L during the 100–400 h (approximately) of fermentation in both media. Buffered culture medium showed minimal pH changes, while the pH in nonbuffered medium changed drastically, reached a value of 6.5 after 240 h of fermentation. The highest laccase activity (3200 U/L) at 500 h of fermentation was obtained in the buffered medium and in nonbuffered culture medium was only of 450 U/L. One laccase isoenzyme was observed during the entire fermentation process in both media, but in the nonbuffered medium, an additional isoenzyme was produced when the pH reached a value of 6.5. These results suggest that some laccase isoenzymes are regulated by pH signals and also observed that the fungus produces metabolites to regulate the pH of the medium [6].

A gene called lacP83 that encode a laccase isoenzyme of *P. ostreatus* ATCC 32783 grown in SmF was described. Using the PCR inverse strategy, a 2887 bp sequence was obtained from a genomic library of *P. ostreatus*. The coding sequence was of 1527 bp long with 17 exons and the protein encoded had 509 amino acids, shows a putative signal peptide and conserved Cu binding domains. In the promoter region (466 bp upstream of ATG), putative binding transcription factors such as metal response element, xenobiotic response element, a stress response element, and a defense response element were found. The gene and protein sequences of lacP83 had 85–94% and 90–96%, respectively, of similarity with laccases of *Pleurotus* previously reported. This laccase showed differences in its promoter sequence and apparent molecular weight [7].

Recently, the effect of pH on the expression of five genes of laccases (lacc1, lacc4, lacc6, lacc9 and lacc10) and isoenzymes profiles produced by *P. ostreatus* ATCC 32783 developed under SmF conditions was evaluated. The initial pH of the culture media was adjusted at 3.5, 4.5, 6.5, and 8.5. In this research, it was observed that pH is a very important factor for growth, development and production of enzymes, and metabolites of this fungus. The specific growth rate increased with the increase of initial pH of the culture medium, higher biomass values were obtained at pH 6.5 and 8.5; highest laccases activity was obtained at initial pH of culture media of 4.5 and 6.5 and determined at the same values of pH reaching up to 77,500 U/L. The isoenzyme patterns were different depending on the initial pH of the culture medium, to acidic pH was observed up to three isozymes (29, 47, and 65 kDa), at pH near neutrality were observed four isoenzymes (29, 38, 47, and 65 kDa), and alkaline pH three isozymes (29, 47, and 65 kDa) were observed. Since the expression of four genes of laccases (lacc1, lacc4, lacc6, and lacc10) and four isoenzymes was observed, it was suggested that lacc6, lacc10, lacc4, and Lacc1 correspond to isoenzymes of 65, 47, 38, and 29 kDa, respectively. The authors suggest that the pH has a very important role as a transcriptional factor that determines the expression profile and pattern of production of laccase enzymes under conditions SmF [8].

#### **Author details**

of copper produced 1400 and 1000 U/L, respectively. These results suggest that not all strains have the same answer to the presence of Cu in the culture medium, and the sensitivity to Cu be could use to select strains with high laccase production for commercial exploitation [5].

The activity and isoenzymes number of laccase from *P. ostreatus* ATCC 32783 grown in SmF conditions using a buffered and nonbuffered media were studied. For both culture media, the initial pH was 3.5. Laccase activity was around 100–500 U/L during the 100–400 h (approximately) of fermentation in both media. Buffered culture medium showed minimal pH changes, while the pH in nonbuffered medium changed drastically, reached a value of 6.5 after 240 h of fermentation. The highest laccase activity (3200 U/L) at 500 h of fermentation was obtained in the buffered medium and in nonbuffered culture medium was only of 450 U/L. One laccase isoenzyme was observed during the entire fermentation process in both media, but in the nonbuffered medium, an additional isoenzyme was produced when the pH reached a value of 6.5. These results suggest that some laccase isoenzymes are regulated by pH signals and also observed that the fungus produces metabolites to regulate the pH of the medium [6].

A gene called lacP83 that encode a laccase isoenzyme of *P. ostreatus* ATCC 32783 grown in SmF was described. Using the PCR inverse strategy, a 2887 bp sequence was obtained from a genomic library of *P. ostreatus*. The coding sequence was of 1527 bp long with 17 exons and the protein encoded had 509 amino acids, shows a putative signal peptide and conserved Cu binding domains. In the promoter region (466 bp upstream of ATG), putative binding transcription factors such as metal response element, xenobiotic response element, a stress response element, and a defense response element were found. The gene and protein sequences of lacP83 had 85–94% and 90–96%, respectively, of similarity with laccases of *Pleurotus* previously reported. This laccase showed differences in its promoter sequence and apparent

Recently, the effect of pH on the expression of five genes of laccases (lacc1, lacc4, lacc6, lacc9 and lacc10) and isoenzymes profiles produced by *P. ostreatus* ATCC 32783 developed under SmF conditions was evaluated. The initial pH of the culture media was adjusted at 3.5, 4.5, 6.5, and 8.5. In this research, it was observed that pH is a very important factor for growth, development and production of enzymes, and metabolites of this fungus. The specific growth rate increased with the increase of initial pH of the culture medium, higher biomass values were obtained at pH 6.5 and 8.5; highest laccases activity was obtained at initial pH of culture media of 4.5 and 6.5 and determined at the same values of pH reaching up to 77,500 U/L. The isoenzyme patterns were different depending on the initial pH of the culture medium, to acidic pH was observed up to three isozymes (29, 47, and 65 kDa), at pH near neutrality were observed four isoenzymes (29, 38, 47, and 65 kDa), and alkaline pH three isozymes (29, 47, and 65 kDa) were observed. Since the expression of four genes of laccases (lacc1, lacc4, lacc6, and lacc10) and four isoenzymes was observed, it was suggested that lacc6, lacc10, lacc4, and Lacc1 correspond to isoenzymes of 65, 47, 38, and 29 kDa, respectively. The authors suggest that the pH has a very important role as a transcriptional factor that determines the expression profile

and pattern of production of laccase enzymes under conditions SmF [8].

molecular weight [7].

66 Fermentation Processes

Gerardo Díaz-Godínez1\*, Maura Téllez-Téllez2 , Carmen Sánchez1 and Rubén Díaz1

\*Address all correspondence to: diazgdo@hotmail.com

1 Laboratory of Biotechnology, Research Center for Biological Sciences, Autonomous University of Tlaxcala, Tlaxcala, Mexico

2 Laboratory of Mycology, Biological Research Center, Autonomous University of State of Morelos, Morelos, Mexico

#### **References**


[22] Faraco V, Piscitelli A, Sannia G, Giardina P. Identification of a new member of the dyedecolorizing peroxidase family from *Pleurotus ostreatus*. World J Microbiol Biotechnol. 2007;23:889–893. DOI: 10.1007/s11274-006-9303-5.

[8] Díaz R, Téllez-Téllez M, Sánchez C, Bibbins-Martínez MD, Díaz-Godínez G, Soriano-Santos J. Influence of initial pH of the growing medium on the activity, production and genes expression profiles of laccase of *Pleurotus ostreatus* in submerged fermentations. Electron J Biotechnol. 2013;16(4):fulltext 6. DOI: 10.2225/vol16-issue4-fulltext-6.

[9] Chang ST. Global impact of edible and medicinal mushroom on human welfare in the 21st century: non-green revolution. Int J Med Mushroom. 1999;1:1–7. DOI: 10.1615/

[10] Sánchez C. Morphogenesis of mushroom fungi: ultrastructural, physiological and histological study of *Pleurotus ostreatus* [thesis]. Manchester: University of Manchester;

[11] Deshpande MV. Proteinases in fungal morphogenesis. World J Microbiol Biotechnol.

[13] Sánchez C. Cultivation of *Pleurotus ostreatus* and other edible mushrooms. Appl Microbiol Biotechnol. 2010;85:1321–1337. DOI: 10.1007/s00253-009-2343-7.

[14] Deepalakshmi K, Mirunalini S. *Pleurotus ostreatus*: an oyster mushroom with nutritional

[15] Sánchez C. Modern aspects of mushrooms culture technology. Appl Microbiol Bio-

[16] Patel S, Goyal A. Recent developments in mushrooms as anticancer therapeutics: a

[17] Oei P. Manual on mushroom cultivation: techniques species and opportunities for commercial application in developing countries. Amsterdam: TOOL Publications;

[18] Manzi P, Aguzzi A, Pizzoferrato L. Nutritional value of mushrooms widely consumed in Italy. Food Chem. 2001;73:321–325. DOI: 10.1016/S0308-8146(00)00304-6.

[19] Sánchez C. Lignocellulosic residues: biodegradation and bioconversion by fungi.

[20] Fernández-Fueyo E, Ruiz-Dueñas FJ, Martínez MJ, Romero A, Hammel KE, Medrano FJ, Martínez AT. Ligninolytic peroxidase genes in the oyster mushroom genome: heterologous expression, molecular structure, catalytic and stability properties, and lignin-degrading ability. Biotechnol Biofuel. 2014;7:1–23. DOI: 10.1186/1754-6834-7-2.

[21] Marzullo L, Cannio R, Giardina P, Santini MT, Sannia G. Veratryl alcohol oxidase from *Pleurotus ostreatus* participates in lignin biodegradation and prevents polymerization of laccase-oxidized substrates. J Biol Chem. 1995;270:3823–3827. DOI: 10.1074/jbc.

Biotechnol Adv. 2009;27:85–194. DOI: 10.1016/j.biotechadv.2008.11.001.

[12] Moore D. Fungal morphogenesis. New York: Cambridge University Press; 1998.

and medicinal properties. J Biochem Tech. 2014;5(2):718–726.

technol. 2004;64:756–762. DOI: 10.1007/s00253-004-1569-7.

review. Biotechnology. 2012;2:1–15. DOI: 10.1007/s13205-011-0036-2.

IntJMedMushrooms.v1.i1.10.

1992;8:242–250. DOI: 10.1007/BF01201871.

1998.

68 Fermentation Processes

2003.

270.8.3823.


targeting system for *Pleurotus ostreatus*. Appl Environ Microbiol. 2012;78:5341–5352. DOI: 10.1128/AEM.01234-12.


[48] Rodríguez E, Ruiz-Dueñas FJ, Kooistra R, Ram A, Martínez AT, Martínez MJ. Isolation of two laccase genes from the white-rot fungus *Pleurotus eryngii* and heterologous expression of the pel3 encoded protein. J Biotechnol. 2008;134:9–19. DOI: 10.1016/ j.jbiotec.2007.12.008.

targeting system for *Pleurotus ostreatus*. Appl Environ Microbiol. 2012;78:5341–5352.

[35] Golan-Rozen N, Chefetz B, Ben-Ari J, Geva J, Hadar Y. Transformation of the recalcitrant pharmaceutical compound carbamazepine by *Pleurotus ostreatus*: role of cytochrome P450 monooxygenase and manganese peroxidase. Environ Sci Technol. 2011;45:6800–

[36] Kirk TK, Farrell RL. Enzymatic "combustion": the microbial degradation of lignin. Annu Rev Microbiol. 1987;41:465–505. DOI: 10.1146/annurev.mi.41.100187.002341. [37] Eriksson KEL, Blanchette RA, Ander P. Microbial and enzymatic degradation of wood

[38] Hammel KE. Organopollutant degradation by ligninolytic fungi. In: Young LY, Cerniglia CE, editors. Microbial transformation and degradation of toxic organic

[39] Garzillo AM, Colao MC, Buonocore V, Oliva R, Falcigno L, Saviano M, Santoro AM, Zappala R, Bonomo RP, Bianco C, Giardina P, Palmieri G, Sannia G. Structural and kinetic characterization of native laccases from *Pleurotus ostreatus*, *Rigidoporus lignosus*, and *Trametes trogii*. J Prot Chem. 2001;20:191–201. DOI: 10.1023/A:1010954812955.

[40] Platt MW, Hadar Y, Chet I. Fungal activities involved in lignocellulose degradation by *Pleurotus*. Appl Microbiol Biotechnol. 1984;20:150–154. DOI: 10.1007/BF00252594. [41] Bollag JM, Leonowicz A. Comparative studies of extracellular fungal laccase. Appl

[42] Thurston CF. The structure and function of fungal laccases. Microbiology. 1994;140: 19–

[43] Solomon EI, Sundaram UM, Machonkin TE. Multicopper oxidases and oxygenases.

[44] Yoshida H. LXIII.—Chemistry of lacquer (Urushi). Part I. Communication from the Chemical Society of Tokio. J. Chem. Soc., Trans. 1883;472. DOI: 10.1039/CT8834300472.

[45] Messerschmidt A, Huber R. The blue oxidases, ascorbate oxidase, laccase and ceruloplasmin- Modelling and structural relationships. Eur J Biochem. 1990;187:341. DOI:

[46] Yaver DS, Xu F, Golightly EJ, Brown KM, Brown SH, Rey MW, Schneider P, Halkier T, Mondorf K, Dalboge H. Purification, characterization, molecular cloning, and expression of two laccase genes from the white rot basidiomycete *Trametes villosa*. Appl

[47] Palmieri G, Cennamo G, Faraco V, Amoresano A, Sannia G, Giardina P. Atypical laccase isoenzymes from copper supplemented *Pleurotus ostreatus* cultures. Enzyme Microb

Technol. 2003;33: 220–230. DOI: 10.1016/S0141-0229(03)00117-0.

Environ Microbiol. 1984;48:849–854. DOI: 10.1128/AEM.71.4.1775.

Chem Rev. 1996;96:2563–2605. DOI: 10.1021/cr950046o.

10.1111/j.1432-1033.1990.tb15311.x.

Environ Microbiol. 1996;62: 834–841.

and wood components. Berlin, Heidelberg: Springer; 1990.

chemicals.New York: Wiley-Liss; 1995. p. 331–346.

DOI: 10.1128/AEM.01234-12.

70 Fermentation Processes

6805. DOI: 10.1021/es200298t.

26.


[74] Singhania RR, Patel AK, Soccol CR, Pandey A. Recent advances in solid-state fermentation. Biochem Eng J. 2009;44(1):13–18. DOI: 10.1016/j.bej.2008.10.019.

[60] Palmieri G, Giardina P, Bianco C, Scaloni A, Capasso A, Sannia G. A novel white laccase from *Pleurotus ostreatus*. J Biol Chem. 1997;272:31301–31307. DOI: 10.1074/jbc.

[61] Sannia G, Giardina P, Luna M, Rossi M, Buonocore V. Laccase from *Pleurotus ostreatus*.

[62] De Souza CGM, Peralta RM. Purification and characterization of the main laccase produced by the white-rot fungus *Pleurotus pulmonarius* on wheat bran solid state

[63] Das N, Chakraborty TK, Mukherjee M. Purification and characterization of laccase-1 from *Pleurotus florida*. Folia Microbiol. 2000;45:447–451. DOI: 10.1007/BF02817619. [64] Lo SC, Ho YS, Buswell JA. Effect of phenolic monomers on the production of laccases by the edible mushroom *Pleurotus sajor-caju*, and partial characterization of a major

[65] Muñoz C, Guillen F, Martinez AT, Martinez MJ. Laccase isoenzymes of *Pleurotus eryngii*: characterization, catalytic properties, and participation in activation of molec-

[66] Bajpai P. Application of enzymes in the pulp and paper industry. Biotechnol Prog.

[67] Durán N, Esposito E. Potential applications of oxidative enzymes and phenoloxidaselike compounds in wastewater and soil treatment: a review. Appl Catal B: Environ.

[68] Minussi R, Pastore GM, Duran N. Potential applications of laccase in the food industry. Trends Food Sci Technol. 2002;13:205–216. DOI: 10.1016/S0924-2244(02)00155-3. [69] Abadulla E, Tzanov T, Costa S, Robra KH, Covaco-Paulo A, Gübitz A. Decolorization and detoxification of textile dyes with a laccase from *Trametes hirsute*. Appl Environ

[70] Amir L, Tam TK, Pita M, Meijler MM, Alfonta L. Katz E. Biofuel cell controlled by enzyme logic systems. J Am Chem Soc. 2009;131:826–832. DOI: 10.1021/ja8076704. [71] Mayer AM, Staples RC. Laccase: new functions for an old enzyme. Phytochemistry.

[72] Desai SS, Nityanand C. Microbial laccases and their applications: a review. Asian J

[73] Pandey A, Soccol CR, Mitchell D. New developments in solid state fermentation. I. Bioprocesses and products. Proc Biochem. 2000;35:1153–1169. DOI: 10.1016/

Microbiol. 2000;66:3357–3362. DOI: 10.1128/AEM.66.8.3357-3362.2000.

oxidation. Appl Environ Microbiol. 1997;63:2166–2174.

medium. J Basic Microbiol. 2003;43:278–286. DOI: 10.1002/jobm.200390031.

laccase component. Mycologia. 2001;93:413–421. DOI: 10.2307/3761726.

Biotechnol Lett. 1986;8:797–800. DOI: 10.1007/BF01020827.

272.50.31301.

72 Fermentation Processes

ular oxygen and Mn2+

S0032-9592(00)00152-7.

1999;15:147–157. DOI: 10.1021/bp990013k.

2000;28:83–99. DOI: 10.1016/S0926-3373(00)00168-5.

2002;60:551–565. DOI: 10.1016/S0031-9422(02)00171-1.

Biotechnol. 2011;3:98–124. DOI: 10.3923/ajbkr.2011.98.124.


**Fermentation Parameters and Modeling**

[86] Yildirim N, Yildirim NC, Yildiz A. Laccase enzyme activity during growth and fruiting of *Pleurotus eryngii* under solid state fermentation medium containing agricul-

[87] Pandey VK, Singh MP. Biodegradation of wheat straw by *Pleurotus ostreatus*. Cell Mol

[88] Elisashvili V, Penninckx M, Kachlishvili E, Tsiklauri N, Metreveli E, Kharziani T, Kvesitadze G. *Lentinus edodes* and *Pleurotus species* lignocellulolytic enzymes activity in submerged and solid-state fermentation of lignocellulosic wastes of different composition. Bioresour Technol. 2008;99(3):457–462. DOI: 10.1016/j.biortech.2007.01.011. [89] Kurt S, Buyukalaca S. Yield performances and changes in enzyme activities of *Pleurotus* spp. (*P. ostreatus* and *P. sajor-caju*) cultivated on different agricultural wastes. Bioresour

[90] Tan YH, Wahab MN. Extracellular enzyme production during anamorphic growth in the edible mushroom, *Pleurotus sajor-caju*. World J Microb Biot. 1997;13(6):613–617. [91] Patel H, Gupte A, Gupte S. Effect of different culture conditions and inducers on production of laccase by a basidiomycete fungal isolate *Pleurotus ostreatus* HP-1 under solid state fermentation. BioResources 2009;4(1):268–284. DOI: 10.15376/biores.

[92] Aslam S, Asgher M. Partial purification and characterization of ligninolytic enzymes produced by *Pleurotus ostreatus* during solid state fermentation. Afr J Biotechnol.

[93] Park YJ, Yoon DE, Kim HI, Kwon O, Yoo YB, Kong WS, Lee CS. Overproduction of laccase by the white-rot fungus *Pleurotus ostreatus* using apple pomace as inducer.

[94] Karp SG, Faraco V, Amore A, Letti LAJ, Soccol VT, Soccol CR. Statistical optimization of laccase production and delignification of sugarcane bagasse by *Pleurotus ostreatus* in solid-state fermentation. Biomed Res Int. 2015;12(16):19. DOI: 10.1155/2015/181204.

[95] Dwivedi P, Vivekanand V, Pareek N, Sharma A, Singh RP. Co-cultivation of mutant *Penicillium oxalicum* SAU E-3.510 and *Pleurotus ostreatus* for simultaneous biosynthesis of xylanase and laccase under solid-state fermentation. N Biotechnol. 2011;28(6):616–

Mycobiology. 2014;42(2):193–197. DOI: 10.5941/MYCO.2014.42.2.193.

Technol. 2010;101(9):3164–3169. DOI: 10.1016/j.biortech.2009.12.011.

tural wastes. IJPAS. 2015; 1:64–71.

4.1.268-284.

74 Fermentation Processes

Biol. 2014;60(5):29–34. DOI: 10.14715/cmb/2014.60.5.6.

2011;10(77):17875–17883. DOI: 10.5897/AJB11.2233.

626. DOI: 10.1016/j.nbt.2011.05.006.

#### **Factors Affecting Rumen Fermentation Using Batch Culture Technique Factors Affecting Rumen Fermentation Using Batch Culture Technique**

#### WenZhu Yang WenZhu Yang

Additional information is available at the end of the chapter Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/64207

#### **Abstract**

The method of batch culture has been widely applied to evaluate feed value and screen feed additives. The advantages of using this in vitro technique as compared to in vivo methods are many, including low cost, simplicity, requirement of small quantities of feed or additives and the ability to screen large numbers of samples under similar experimental conditions. However, the number of factors associated with the batch culture could alter fermentation outcomes. This chapter discusses the potential impact of series factors on in vitro fermentation and the considerations on improving application of batch culture in ruminant nutrition. The factors that are discussed include inoculum source, gas-recording methods, substrate particle size, substrate delivery method, ratio of rumen inoculum to buffer in mixture of media and addition of soluble carbohydrate in media. Some recent important results obtained using batch culture technique have been highlighted and discussed. Any particular batch system being accepted as the 'standard' procedure seems difficult. However, before any protocol can be adopted, sufficient data need to be developed to reduce the variation and improve the consistence of the measurements.

**Keywords:** batch culture, feed evaluation, gas production, inoculums, rumen fermentation

#### **1. Introduction**

Rumen fermentation plays a major role in feed digestion and microbial production in ruminants. The rate and extent of feed digestion in the rumen, rumen fermentation pattern and amount of microbial protein production ultimately determine the feed value, nutrient provision and animal productivity. Therefore, determining the feed digestibility in the rumen is necessary to predict

© 2017 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2017 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

animal production and optimum ration formulation. In addition, substantial feed additives are presently used to improve or modify rumen fermentation and their activities need to be determined. The use of animal to measure either feed digestibility or activity of feed additives is a reliable approach but disadvantages are numerous such as time consuming, expensive, require large quantities of feed (or feed additives), and unsuitable for large-scale feed evaluation. As a result, many biological methods which simulate the rumen fermentation process have been developed.

The method of batch culture has been widely applied to screen and compare various feeds and feed additives (e.g., feed enzymes). The advantages of using in vitro techniques as compared to in vivo methods using animals include low cost, its simplicity, small feedstuff requirement and particularly the ability to screen large numbers of samples under similar experimental conditions [1]. However, a number of factors used in the batch culture method including inoculum source, recording system of gas production, method of substrate dispersal in the bottle, sample size and method of substrate preparation could alter fermentation results [2–4]. For example, venting methods for gas measurement is a noticeable issue. In a closed system, gas accumulates and the rise in pressure in headspace may affect the rate of substrate fermentation [5]. Different venting systems to relieve gas pressure have been compared, but results on feed digestion have been inconclusive [2, 6]. Tagliapietra et al. [3] reported that using manual pressure measurements, headspace volume, venting frequency and amount of fermentable substrate need to be carefully balanced to avoid high headspace pressures that could alter fermentation kinetics. Other researchers have reported placing substrates in porous bags within incubation vials [1, 7] or placing it freely into the inoculum [8, 9]. Greater amounts of methane were observed from samples directly dispersed in vials as compared to that enclosed in bags [4]. It is possible that the bags create a microenvironment that is distinct from that of free inoculum and may vary with changes in the pore size of bags [10]. The substrates that are incubated in batch culture need to be processed to obtain an adequate particle size prior to incubation because of lack of mastication and rumen contraction occurs in animal. The use of a finely ground sample reduces the risk of sampling bias, especially for forage samples, but fine particles may exit the bags prior to true digestion. All these factors related to batch culture have not been standardized across the laboratory, and they could significantly impact the fermentation results, thus increase the variability and reduce the reliability of the method. The objective of this chapter is to discuss several key factors that potentially influence the outcomes of the batch culture and to provide useful information to better use the batch culture technique in the evaluation of feeds or feed additives in ruminant nutrition.

#### **2. What is the batch culture?**

Batch culture is a technique for large-scale production of microbes or microbial products in which, at a given time, the fermenter is stopped and the culture is worked up. The 'batch culture' fermentation is also known as 'closed culture' system. In this system, at the beginning, the nutrients and other additives are added in required amounts. There is no refill of nutrients once the fermentation process has started and the product is recovered at the end of the process. In the beginning, microorganisms grow at a rapid rate due to availability of excess nutrients. As time passes, they increase in number with rapid use of the nutrients and simultaneously produce toxic metabolites. The batch culture that is currently used to evaluate ruminant feeds or feed additives is primarily based on the in vitro technique developed by Tilley and Terry [11] and modified by Goering and Van Soest [12]. The batch culture consists of collection of rumen fluid as inoculum, inoculation of dried, ground feed samples contained in a flask with a buffering and nutritive in vitro medium. Sample digestion is measured following anaerobic degradation by rumen bacteria. The batch culture can measure the kinetics and volume of gas production (mainly CO2, CH4), as well as gas profiles, rate, and extent of substrate digestion, which can then be used to evaluate feed values (ranking feed) and feed additive screening. The kinetics of gas production or feed digestion can be a developed model to predict feed intake, microbial protein synthesis, and metabolizable energy.

During the fermentation of feedstuff, the truly digested substrate is partitioned among volatile fatty acids, gas and microbial biomass. Gas production occurs when substrate carbohydrates are fermented to generate acetate or butyrate but no gas is produced with fermentation of carbohydrate to generate propionate. However, gas is also produced when volatile fatty acid causes gas to be released from the bicarbonate buffer [13]. Although gas production is a reflection of the generation of volatile fatty acids and microbial mass as a result of substrate fermentation, gas measurements only account for substrate that is used for volatile fatty acids and gas production and does not consider substrate utilized for microbial growth. Therefore, the volume of gas produced during fermentation is highly associated with the amount of substrate digested. Currently, the gas production technique is commonly used to evaluate and predict feed value and screening feed additives for ruminants. One major advantage of in vitro gas measurement technique is that it focuses on the appearance of fermentation products and non-fermentable substrates do not contribute to gas production [13]. Since gas production does not consider the amount of substrate converted into microbial biomass, the substrate digestibility that is estimated based on gas measurement is considered as apparent digestibility [14]. Feed protein degradation does not contribute to gas but the high ammonia nitrogen concentration in in vitro systems might prevent the release of gas due to its highly basic nature. As one of major measures of batch culture, gas measurement is widely used to predict rate and extent of feed digestion in the rumen as well as feed intake and microbial protein synthesis [14].

#### **3. Factors affecting batch culture fermentation**

#### **3.1. Effect of inoculum source**

animal production and optimum ration formulation. In addition, substantial feed additives are presently used to improve or modify rumen fermentation and their activities need to be determined. The use of animal to measure either feed digestibility or activity of feed additives is a reliable approach but disadvantages are numerous such as time consuming, expensive, require large quantities of feed (or feed additives), and unsuitable for large-scale feed evaluation. As a result, many biological methods which simulate the rumen fermentation process have been

The method of batch culture has been widely applied to screen and compare various feeds and feed additives (e.g., feed enzymes). The advantages of using in vitro techniques as compared to in vivo methods using animals include low cost, its simplicity, small feedstuff requirement and particularly the ability to screen large numbers of samples under similar experimental conditions [1]. However, a number of factors used in the batch culture method including inoculum source, recording system of gas production, method of substrate dispersal in the bottle, sample size and method of substrate preparation could alter fermentation results [2–4]. For example, venting methods for gas measurement is a noticeable issue. In a closed system, gas accumulates and the rise in pressure in headspace may affect the rate of substrate fermentation [5]. Different venting systems to relieve gas pressure have been compared, but results on feed digestion have been inconclusive [2, 6]. Tagliapietra et al. [3] reported that using manual pressure measurements, headspace volume, venting frequency and amount of fermentable substrate need to be carefully balanced to avoid high headspace pressures that could alter fermentation kinetics. Other researchers have reported placing substrates in porous bags within incubation vials [1, 7] or placing it freely into the inoculum [8, 9]. Greater amounts of methane were observed from samples directly dispersed in vials as compared to that enclosed in bags [4]. It is possible that the bags create a microenvironment that is distinct from that of free inoculum and may vary with changes in the pore size of bags [10]. The substrates that are incubated in batch culture need to be processed to obtain an adequate particle size prior to incubation because of lack of mastication and rumen contraction occurs in animal. The use of a finely ground sample reduces the risk of sampling bias, especially for forage samples, but fine particles may exit the bags prior to true digestion. All these factors related to batch culture have not been standardized across the laboratory, and they could significantly impact the fermentation results, thus increase the variability and reduce the reliability of the method. The objective of this chapter is to discuss several key factors that potentially influence the outcomes of the batch culture and to provide useful information to better use the batch culture technique

in the evaluation of feeds or feed additives in ruminant nutrition.

Batch culture is a technique for large-scale production of microbes or microbial products in which, at a given time, the fermenter is stopped and the culture is worked up. The 'batch culture' fermentation is also known as 'closed culture' system. In this system, at the beginning, the nutrients and other additives are added in required amounts. There is no refill of nutrients once the fermentation process has started and the product is recovered at the end of the process.

**2. What is the batch culture?**

developed.

78 Fermentation Processes

The inoculum is often the major source of variation on the variable measurements in the use of batch culture technique to study fermentation kinetics of ruminant feeds. The effect of inoculum source on in vitro gas production was considerably discussed in a review by Rymer et al. [2]. Considerable animal variation in the quality of rumen fluid inoculum, prepared identically, is known to exist both within and among donor animals [15, 16]. The variation of batch fermentation due to inoculum source is ultimately attributed to the variation of microbial population profiles and microbial activities in the rumen. Therefore, all the factors that potentially affect the ruminal microbial activity would affect inoculum quality, thus varying the batch fermentation. In this section, the effects on batch fermentation of the inoculum from sampling schedule, different species, rumen versus faeces as well as inoculum preparation are discussed.

#### *3.1.1. Effect of donor animals, diet and collection time*

The donor animals, type of diet and the inoculum collection time may all have an effect on consistency of fermentation results between cultures. It is well known that there is considerable individual animal variation on rumen pH and rumen fermentation pattern under the same feeding and management conditions. Therefore, it is often recommended to collect rumen inoculum from several animals and then combined to reduce the variation. Recently, we have conducted a batch culture to compare rumen inoculum of cattle with low- and high-feed digestion. It was observed the differences in gas production and dry matter digestibility of barley straw when the low- and high-feed-digesting rumen inocula were used. However, the use of such inoculum did not result overall in the differences in gas production kinetics. The effect of the inoculum sources on the in vitro effective dry matter digestibility agrees with previous reports that a difference in the activity of the inoculum exist among individual donor animals [16]. In another batch culture using always the same inoculum (low- versus high-feeddigesting cattle), we observed that the gas production and dry matter digestibility of barley straw werenot affected by inoculum source. The results suggest that inoculum from high-feeddigesting cattle did not necessary improve in vitro digestion of straw.

The rate and extent of feed degradability in the rumen vary with the type of feeds and feed processing. Therefore, diet is considered as a significant factor influencing the inoculum activity. Cone et al. [17] reported that the degradability of starch from different feed sources was greater for the donor cow fed a diet containing equal concentrate and hay compared with a hay-based diet. However, the composition of the concentrate mixture had only a minor effect on degradability values. It is clear that the ruminal microbial activity was different between cows fed hay versus hay and concentrate mixed diet. However, manipulating concentrate composition would not dramatically change ruminal microbial profiles. Mertens et al. [18] reported that the higher-fibre diets tended to produce more gas than the lower-fibre diets, which may explain by more acetate production with high-fibre diet, since fermentation of substrate fibre generates primarily acetate and gas is produced when substrate is fermented to generate acetate or butyrate rather than propionate. Huntington et al. [19] showed a similar response when dry cows were fed a diet of either straw or grass silage with rolled barley, and no differences in the gas production with a diet of a dried grass. Menke and Steingass [20] indicated that there was little difference in gas production of treated straw when hay in the diet of donor animals was replaced with treated straw. The inconsistent effect of donor animal diet suggests that it is more important to ensure the minimum microbial activity in the rumen fluid, rather than ensuring that donor animals are fed the substrate incubated.

Rumen microbial activity is increasing following feed ingestion, thus different sampling times have been applied to collect inoculum in literature either for obtaining high activity (i.e., 2 h after feeding) or for reducing variation (i.e., before feeding). Cone et al. [21] reported the increased rate of fermentation with rumen fluid that was collected after the morning although the total gas production was not affected. Menke and Steingass [20] stated that sampling rumen contents just before feeding reduced variation in activity of the inoculum. Although differences in microbial activity of inoculum occur at different sampling times, it appears that the most important factor is whether the sampling schedule will allow collection of inoculum with sufficient microbial activity. Payne et al. [22] observed less variation between replicates when rumen fluid was collected either 4 or 8 h after feeding, compared with before or 2 h after feeding.

The rumen fluid preparation procedure had relatively little effect on gas production [23]. However, Bueno et al. [24] reported an increase of in vitro organic matter digestibility by increasing the proportion of the solid phase relative to liquid phase in inoculum preparation and concluded that the contribution of microorganisms from the solid phase of rumen inoculum is important, especially in studies to evaluate high-fibre feeds. Recently, comparing the rumen inocula from low- and high-feed-digesting cattle, we did not find the differences in fibre digestibility of barley straw between the two inoculum sources, which may be explained by the method of inoculum preparation. Although whole ruminal contents were collected, rumen inoculum was obtained by squeezing manually, and it would represent primarily the bacteria associated with liquid or loosely associated with feed particles but not with bacteria tightly associated with particles. The proportion of bacteria associated with rumen feed particulate has been found to range from 50 to 70% and mainly characterized as fibrolytic bacteria [25].

#### *3.1.2. Inoculum from different species*

population profiles and microbial activities in the rumen. Therefore, all the factors that potentially affect the ruminal microbial activity would affect inoculum quality, thus varying the batch fermentation. In this section, the effects on batch fermentation of the inoculum from sampling schedule, different species, rumen versus faeces as well as inoculum preparation are

The donor animals, type of diet and the inoculum collection time may all have an effect on consistency of fermentation results between cultures. It is well known that there is considerable individual animal variation on rumen pH and rumen fermentation pattern under the same feeding and management conditions. Therefore, it is often recommended to collect rumen inoculum from several animals and then combined to reduce the variation. Recently, we have conducted a batch culture to compare rumen inoculum of cattle with low- and high-feed digestion. It was observed the differences in gas production and dry matter digestibility of barley straw when the low- and high-feed-digesting rumen inocula were used. However, the use of such inoculum did not result overall in the differences in gas production kinetics. The effect of the inoculum sources on the in vitro effective dry matter digestibility agrees with previous reports that a difference in the activity of the inoculum exist among individual donor animals [16]. In another batch culture using always the same inoculum (low- versus high-feeddigesting cattle), we observed that the gas production and dry matter digestibility of barley straw werenot affected by inoculum source. The results suggest that inoculum from high-feed-

The rate and extent of feed degradability in the rumen vary with the type of feeds and feed processing. Therefore, diet is considered as a significant factor influencing the inoculum activity. Cone et al. [17] reported that the degradability of starch from different feed sources was greater for the donor cow fed a diet containing equal concentrate and hay compared with a hay-based diet. However, the composition of the concentrate mixture had only a minor effect on degradability values. It is clear that the ruminal microbial activity was different between cows fed hay versus hay and concentrate mixed diet. However, manipulating concentrate composition would not dramatically change ruminal microbial profiles. Mertens et al. [18] reported that the higher-fibre diets tended to produce more gas than the lower-fibre diets, which may explain by more acetate production with high-fibre diet, since fermentation of substrate fibre generates primarily acetate and gas is produced when substrate is fermented to generate acetate or butyrate rather than propionate. Huntington et al. [19] showed a similar response when dry cows were fed a diet of either straw or grass silage with rolled barley, and no differences in the gas production with a diet of a dried grass. Menke and Steingass [20] indicated that there was little difference in gas production of treated straw when hay in the diet of donor animals was replaced with treated straw. The inconsistent effect of donor animal diet suggests that it is more important to ensure the minimum microbial activity in the rumen

discussed.

80 Fermentation Processes

*3.1.1. Effect of donor animals, diet and collection time*

digesting cattle did not necessary improve in vitro digestion of straw.

fluid, rather than ensuring that donor animals are fed the substrate incubated.

Rumen microbial activity is increasing following feed ingestion, thus different sampling times have been applied to collect inoculum in literature either for obtaining high activity (i.e., 2 h Rumen fluid from sheep is often used as inoculum on the batch culture because housing sheep is easier and less expensive than the cattle, whereas the results obtained with batch culture technique are mainly used to evaluate feeds for beef or dairy cattle. As a result, numbers of studies were conducted in comparison of rumen fluid between cattle and sheep on in vitro gas production and rumen fermentation [24, 26]. Cone et al. [26] compared rumen fluid from cows and sheep fed a similar diet, and they found that the gas production was lower with sheep rumen fluid, but there was a good relationship between volumes of gas produced by the two inocula. They concluded that sheep rumen fluid could replace cow rumen fluid for accurate determination of 24 and 48 h gas production and the gas production profile. However, rumen fluid of cows could not be replaced by that of sheep for the rate of gas production determination. Similarly, Bueno et al. [24] observed the similar gas production and degradability between sheep and cattle under the same feeding and management conditions. However, kinetics of gas production differed between species and so dynamic determinations, such as rate of gas production data, using sheep inoculum cannot be extrapolated to cattle. Bueno et al. [27] found the similar gas production and organic matter degradability of tropic forage between cow and sheep rumen fluid, whereas rumen fluid from sheep resulted in gas production with a longer lag time (6.1 h versus 4.2 h). Differences in microbial composition of rumen fluid from these sheep and cattle appeared to especially affect kinetics of fermentation, but not the end point measures. Few studies were compared between cattle and buffalo on the effects of rumen fluid on rumen fermentation. Calabrò et al. [28] found higher gas volume and earlier maximum rate of substrate degradation with cow than buffalo inoculum. All of these data indicate that species of donor animal will affect rumen fermentation.

#### *3.1.3. Rumen versus faecal inocula*

Use of faecal inoculum in batch culture has been paid great attention in scientific community during last two decades as it would overcome the need for surgically modified animals. The comparison between rumen fluid and faecal inoculum on in vitro gas production and extent of feed fermentation were well documented in several review articles [2, 15]. In general, the use of faecal inoculum give lower cumulative gas production and feed digestibility than use of rumen fluid although a good correlation is often determined. It suggests that the microbial activity in faecal inoculum is lower than in rumen inoculum. The difference between rumen and faecal inoculum may vary with feed degradability in the rumen. When the diet of the donor animal is highly fibrous, such that the microbial activity of the rumen is low, then differences between rumen fluid and faecal inoculum would be smaller, but when highproductive animals are used, the faecal inoculum are of limited value. Mauricio et al. [29] stated that the faecal inoculum could replace rumen fluid where incubations were over extended periods and cumulative gas volumes were examined since the gas release kinetics differed up to 48 h of incubation between the two inocula. Cone et al. [26] concluded that cow rumen fluid cannot be replaced by cow faeces for determination of 24 h gas production, but to be a good alternative for cow rumen fluid to accurately determine 48 h gas production. Mould et al. [15] suggested that faeces may replace rumen fluid as an inoculum for end-point measures (i.e., degradability or cumulative gas volume at the end of extended incubation periods); faecal material is likely an unsuitable inoculum for estimating rate of fermentation.

#### **3.2. Manual versus automated methods**

The gas generated from batch fermentation is generally measured either manually using the manual pressure transducer developed by Theodorou et al. [5] or automatically with the automated systems as described by Pell and Schofield [30], Cone et al. [21] and Davies et al. [31]. It has been reported that the headspace gas production associated with feed fermentation can be manually measured by inserting a needle attached to a pressure transducer into the vials at fixed time points [1, 8], or measured automatically using a transducer recording system [32]. Theoretically, the automated recording system, which vents gas at regular intervals may be more accurate than the manual system as where headspace gas can reach higher pressures. Accumulation of gas (i.e., the rise of gas pressure) may influence the release of gas from buffered ruminal fluid [3] and reduce the fermentation rate of substrate [5]. In closed systems, where gas is not released and accumulates, the rise of pressure in the headspace may cause a staircase effect in the recorded data. Especially with fast-fermenting substrates, some of the headspace gas may be forced into the liquid phase, and this dissolved gas may not be released instantly in the following reading, thus affecting successive measurements. Several studies were carried out to compare the gas produced using manual pressure transducers and automated pressure systems. The studies by Rymer et al. [2] and Gierus et al. [6] have observed greater gas production with the manual procedure than automated system. Similarly, we previously used two gas production systems, which were differed in gas pressure recording (automated versus manual), headspace and sample size of the bottle. Serum bottles (100 mL) sealed with a rubber stopper were used for manual gas pressure recording and a 500-mL Ankom gas production module (a computerized system with automated pressure transducers, Ankom Technology, Macedon, NY, USA) equipped with an Ankom pressure sensor module including a microchip and a radio transponder was used for automated gas pressure recording. The result also showed that the gas production was different when gas pressure was recorded using the two systems but it was interacted with the type of substrate incubated. The gas production was higher using manual system when the substrates had higher digestibility such as alfalfa hay and wheat distiller grains, whereas no difference in gas production was observed with the incubation of barley straw which had lower digestibility. The similar gas production of barley straw between the two systems may reflect the slower digestion rate of straw generating less gas. In addition, the gas production values from manual and automated recording systems in our study were calculated from different formulas, this may have biased gas production estimates. For the manual system, the gas volume was calculated using the equation described by Mauricio et al. [33]: gas volume, mL = 0.18 + (3.697 × gas pressure) + (0.0824 × gas pressure2 ), whereas for the automated system, the gas volume was estimated according to Avogadro's law (gas volume, mL = gas pressure × [*V*/ *RT*] × 22.4 × 1000, where *V* is headspace volume in the bottle in litres, *R* is the gas constant 8.314472 L kPa/K/mol, and *T* is the temperature in Kelvin). Rymer et al. (2005) reported the stronger relationships between laboratories with manual system than with automated system and suggested that the increased complexity and cost of automated system may not be repaid by increased value of the results. However, the automated system produced good reproducibility among laboratories [21].

#### **3.3. Effect of material delivery**

measures. Few studies were compared between cattle and buffalo on the effects of rumen fluid on rumen fermentation. Calabrò et al. [28] found higher gas volume and earlier maximum rate of substrate degradation with cow than buffalo inoculum. All of these data indicate that species

Use of faecal inoculum in batch culture has been paid great attention in scientific community during last two decades as it would overcome the need for surgically modified animals. The comparison between rumen fluid and faecal inoculum on in vitro gas production and extent of feed fermentation were well documented in several review articles [2, 15]. In general, the use of faecal inoculum give lower cumulative gas production and feed digestibility than use of rumen fluid although a good correlation is often determined. It suggests that the microbial activity in faecal inoculum is lower than in rumen inoculum. The difference between rumen and faecal inoculum may vary with feed degradability in the rumen. When the diet of the donor animal is highly fibrous, such that the microbial activity of the rumen is low, then differences between rumen fluid and faecal inoculum would be smaller, but when highproductive animals are used, the faecal inoculum are of limited value. Mauricio et al. [29] stated that the faecal inoculum could replace rumen fluid where incubations were over extended periods and cumulative gas volumes were examined since the gas release kinetics differed up to 48 h of incubation between the two inocula. Cone et al. [26] concluded that cow rumen fluid cannot be replaced by cow faeces for determination of 24 h gas production, but to be a good alternative for cow rumen fluid to accurately determine 48 h gas production. Mould et al. [15] suggested that faeces may replace rumen fluid as an inoculum for end-point measures (i.e., degradability or cumulative gas volume at the end of extended incubation periods); faecal

material is likely an unsuitable inoculum for estimating rate of fermentation.

The gas generated from batch fermentation is generally measured either manually using the manual pressure transducer developed by Theodorou et al. [5] or automatically with the automated systems as described by Pell and Schofield [30], Cone et al. [21] and Davies et al. [31]. It has been reported that the headspace gas production associated with feed fermentation can be manually measured by inserting a needle attached to a pressure transducer into the vials at fixed time points [1, 8], or measured automatically using a transducer recording system [32]. Theoretically, the automated recording system, which vents gas at regular intervals may be more accurate than the manual system as where headspace gas can reach higher pressures. Accumulation of gas (i.e., the rise of gas pressure) may influence the release of gas from buffered ruminal fluid [3] and reduce the fermentation rate of substrate [5]. In closed systems, where gas is not released and accumulates, the rise of pressure in the headspace may cause a staircase effect in the recorded data. Especially with fast-fermenting substrates, some of the headspace gas may be forced into the liquid phase, and this dissolved gas may not be released instantly in the following reading, thus affecting successive measurements. Several studies were carried out to compare the gas

of donor animal will affect rumen fermentation.

*3.1.3. Rumen versus faecal inocula*

82 Fermentation Processes

**3.2. Manual versus automated methods**

The feed substrates can be incubated directly by dispersing in the medium or incubated in a filter bag. Incubating feeds in filter bags has been widely applied in batch culture [1, 8] because of its practical convenience. In comparison with dispersing the substrate into the medium, enclosing feed in bags has the advantage of being able to simultaneously determine in vitro digestibility of dry matter and fibre without the need to capture residues after incubation. However, incubating feeds in bags can have concerns on restricting microbial access to the substrates, particle loss from the bags during incubation, and the accumulation of the fermentation products which may inhibit microbial activity [34]. The lower in vitro dry matter and fibre digestibility was reported when feeds were incubated in filter bags as compared to when feeds were dispersed in the medium [35]. Krizsan et al. [36] suggested that this lower feed digestibility may arise from the inability of microbes to readily gain access to substrates within the bags, thus lowering the digestion. Additionally, the possible poor fluid exchange within the bags may result in an accumulation of the fermentation products which could further inhibit the fermentation. Ramin et al. [4] reported lower methane production for feed incubated in filter bags than dispersed in medium because of reduced feed digestion in vitro; however, the proportion of methane to total gas production was greater for feeds incubated in bags than for feeds dispersed in the medium. It was suggested an alteration of microbial population or fermentation pattern of the feeds incubated in bags versus feeds dispersed in the medium. There was also interaction between feed and method (i.e., bag versus dispersing) on ranking of methane output. It was concluded that the bag method should not be used when measuring methane emission during 48 h of incubation. In contrast, our recent study [9] showed that the incubation of feeds in filter bags consistently increased the digestibility of dry matter and fibre as compared to when the feeds were dispersed in the medium. The discrepancy with other studies may be resulted from the low densities of feed substrates being incubated. In this study, Barley straw, alfalfa hay and wheat distiller grain were ground through either 1- or 2-mm sieve and were incubated. It was observed that some feed particles were floating on the top of media and adhered to the sides of the bottles as a result of agitation during incubation. Obviously, this portion of the substrate would not come in direct contact with microbial populations and thus feed digestion would be compromised. Additionally, incubating substrate in bags to measure dry matter digestibility may have potentially resulted in overestimation of digestibility due to possible washout of feed particles from bags. The washout fraction varied with substrate and ranked as wheat distiller grain (18.8%) > alfalfa hay (12.1%) > barley straw (5.9%). However, because the washout fraction could primarily depend on the soluble fraction, and the soluble fraction is considered to be highly fermentable in the rumen, the impact of washout fraction would be minimal for the dry matter digestibility at longer incubation hour, for example, 24 h, whereas it would have a significant impact on the gas production kinetic measurement. He et al. [9] suggested that the method of substrate delivery could be a primary factor to be considered if the dry matter digestibility is a key variable measured. Therefore, lower microbial activity within the bags, altering microbial population or fermentation pattern of the samples incubated in bags compared with those directly dispersed in the medium show negative aspects of the bag method, but such disadvantages may have limited impact when using the batch culture for screening feed additives or ranking feedstuff. The practical convenience of using bags is highly attractive, thus commonly used currently.

#### **3.4. Effect of substrate particle size**

Feed digestion in the rumen requires that microorganisms colonize and produce enzymes that hydrolyse feed particles. Increasing the feed surface area increases the accessibility of microbes to substrate, thus potentially increasing feed digestibility. Anele et al. [37] reported that more processed barley grain (i.e., lower processing index at 0.75 which is calculated as ratio of density after rolling to the density before rolling) produced more cumulative gas volume than less processed barley samples with processing index of 0.85 due to less fermentable nutrients. Yang et al. [38] also reported higher in vitro gas production and dry matter digestibility of ground barley (1-mm sieve) as compared to dry-rolled barley (processing index at 0.80), suggesting that grinding increased the surface area available for microbial attachment. However, Rymer et al. [2] suggested that with highly soluble feeds such as some cereal grain, as long as the feed has undergone some abrasion, its particle size does not affect estimates of gas production rate. Lowman et al. [39] reported the similar gas production profiles of incubated naked oats that were cut at half, quarter, coarse and finely ground except the whole naked oats. Similarly, McAllister et al. [40] found the similar in situ dry matter digestibility of halved and quartered grains but significant lower dry matter digestibility of whole grain. Seed grains are generally protected by the pericarp and a processing by rolling or grinding is necessary to make the nutrient-rich endosperm available to the microbes, and to increase the rate and extent of digestion. However, there are many evidences that particle size of processed grain has significant impact on in vitro digestibility. Rymer et al. [2] indicated that maize grain that was steam-flaked, rolled or left intact had the same rate and extent of gas production when it was ground through a 1-mm screen but not when it had been ground through a 4-mm screen. With fibrous and more slowly degraded feeds, gas production rate increases as particle size decreases [39] and it appears that the increased gas production has resulted from an increased surface area as a result of grinding, thereby allowing better microbial access. It seems that there is interaction between feed particle size and type of feeds on in vitro gas production and dry matter digestibility. In the study of He et al. [9], a greater digestibility of dry matter and fibre of alfalfa hay ground 1 mm over 2 mm was observed; however, the digestibility of dry matter of barley straw did not respond to the particle size, and even less gas production and fibre digestibility with barley straw ground through a 1-mm screen as compared to a 2-mm screen was noticed. There was no clear explanation on this unexpected finding and authors speculated that finer straw adhered to the bottle more readily due to its greater buoyancy resulting in a lower digestibility.

in filter bags than dispersed in medium because of reduced feed digestion in vitro; however, the proportion of methane to total gas production was greater for feeds incubated in bags than for feeds dispersed in the medium. It was suggested an alteration of microbial population or fermentation pattern of the feeds incubated in bags versus feeds dispersed in the medium. There was also interaction between feed and method (i.e., bag versus dispersing) on ranking of methane output. It was concluded that the bag method should not be used when measuring methane emission during 48 h of incubation. In contrast, our recent study [9] showed that the incubation of feeds in filter bags consistently increased the digestibility of dry matter and fibre as compared to when the feeds were dispersed in the medium. The discrepancy with other studies may be resulted from the low densities of feed substrates being incubated. In this study, Barley straw, alfalfa hay and wheat distiller grain were ground through either 1- or 2-mm sieve and were incubated. It was observed that some feed particles were floating on the top of media and adhered to the sides of the bottles as a result of agitation during incubation. Obviously, this portion of the substrate would not come in direct contact with microbial populations and thus feed digestion would be compromised. Additionally, incubating substrate in bags to measure dry matter digestibility may have potentially resulted in overestimation of digestibility due to possible washout of feed particles from bags. The washout fraction varied with substrate and ranked as wheat distiller grain (18.8%) > alfalfa hay (12.1%) > barley straw (5.9%). However, because the washout fraction could primarily depend on the soluble fraction, and the soluble fraction is considered to be highly fermentable in the rumen, the impact of washout fraction would be minimal for the dry matter digestibility at longer incubation hour, for example, 24 h, whereas it would have a significant impact on the gas production kinetic measurement. He et al. [9] suggested that the method of substrate delivery could be a primary factor to be considered if the dry matter digestibility is a key variable measured. Therefore, lower microbial activity within the bags, altering microbial population or fermentation pattern of the samples incubated in bags compared with those directly dispersed in the medium show negative aspects of the bag method, but such disadvantages may have limited impact when using the batch culture for screening feed additives or ranking feedstuff. The practical

convenience of using bags is highly attractive, thus commonly used currently.

Feed digestion in the rumen requires that microorganisms colonize and produce enzymes that hydrolyse feed particles. Increasing the feed surface area increases the accessibility of microbes to substrate, thus potentially increasing feed digestibility. Anele et al. [37] reported that more processed barley grain (i.e., lower processing index at 0.75 which is calculated as ratio of density after rolling to the density before rolling) produced more cumulative gas volume than less processed barley samples with processing index of 0.85 due to less fermentable nutrients. Yang et al. [38] also reported higher in vitro gas production and dry matter digestibility of ground barley (1-mm sieve) as compared to dry-rolled barley (processing index at 0.80), suggesting that grinding increased the surface area available for microbial attachment. However, Rymer et al. [2] suggested that with highly soluble feeds such as some cereal grain, as long as the feed has undergone some abrasion, its particle size does not affect estimates of gas production rate. Lowman et al. [39] reported the similar gas production profiles of

**3.4. Effect of substrate particle size**

84 Fermentation Processes

The feeds that are incubated in vitro are often finely ground (e.g., ground through 1-mm sieve) since the particle size reduction during in vitro incubation is minimal due to absence of mastication and ruminal contractions. The use of finely ground sample also reduces the risk of sampling bias considering usually only less 1.0 g of sample is included in incubations. Yang et al. [38] concluded, based on a comparison of 60 barley samples either ground or dry rolled, that grinding is likely an appropriate processing method to evaluate digestion characteristics of barley using batch culture technique. In fact, the starch digestibility of ground barley after 24 h of incubation was similar to in vivo values observed in the rumen [41]. There was also less variability in digestibility and better correlation between chemical composition of barley and in vitro digestibility for the ground than the rolled barley. The advantage of using finely ground sample has no concern on processing quality associated with kernel uniformity. However, one can make the argument that barley that is tested in vitro should be processed in a manner similar to the form that it is fed to the animal. Although this approach does not consider the impact of mastication on digestion, it is equally clear that fine grinding also eliminates any sample-mediated differences in the particle sizes that may be generated after dry rolling of barley. Nocek [42] stated that reducing the variability of particle size by grinding through 1 mm sieve may not mimic the in vivo conditions ideally but it does tend to improve the precision of both in vitro and in situ measures. Yang et al. [38] reported the low correlation for digestibility of dry matter between ground and rolled barley (*R*<sup>2</sup> = 0.12), and suggested that the processing associated with kernel uniformity affected at least partly the digestibility of rolled barley. It can be concluded that the impact of particle size on in vitro feed digestibility can be significant but vary with the type of feed incubated. If the gas production technique is to be used as a means of feed evaluation, it may be necessary to require a standardized particle size

and sample preparation procedure in order to reduce variation among experiments and laboratories. Adoption of a standardized approach to sample preparation may be possible to enable comparison between independently produced gas production and digestion data of different feeds. Additionally, as substrate particles are continually changing shape, size and composition in the gut, it seems unlikely that gas production or dry matter digestion data will represent kinetics of plant biomass as it is digested in the rumen.

#### **3.5. Ratio of rumen inoculum to buffer**

The ratio of rumen inoculum to buffer varies considerably in the various batch culture techniques from 1:9 to 1:4 Cabral Filho et al. [43]. Increasing the proportion of rumen inoculum in the incubation medium reduced lag time of gas production, but increased the volume or the rate of gas production [23, 30]. Navarro-Villa et al. [44] incubated with three different ratios of rumen fluid to buffer (i.e., 1:2, 1:4, and 1:6), and observed the increased gas production per unit of dry matter input, CH4 to gas production and CH4 to total volatile fatty acid ratio in all feeds incubated with increasing the proportion of rumen fluid in the mixture. The increase in CH4 output due to change of rumen inoculum to buffer ratio can be resulted from different fermentation pattern, such as for barley grain appeared to be associated with higher acetate to propionate ratios and for barley straw was due to higher volatile fatty acid production. There was also a quadratic response of dry matter digestibility to increased ratios of rumen fluid to buffer with feed dependent, wherein decreasing the ratio resulted in a decline in digestibility with barley grain, an increase with grass silage and an increase (between 1:2 and 1:4) followed by a larger decrease (between 1:4 and 1:6) with barley straw. The decrease in ratio of rumen fluid to buffer would decrease microbial activity of the mixture media, thereby reduced feed digestibility. Pell and Schofield [30] included rumen fluid at the proportions of 5, 10, 20 and 40% in the total medium mixture, and observed the increase of alfalfa hay digestibility with increasing the proportion of ruminal fluid. It suggested that a 20% inoculum is sufficient to ensure the maximum rate of fibre digestion but lower percentages of inoculum are not sufficient. The increased lag time without altering maximum gas productions by lowering the ratio of rumen fluid to buffer appeared to reflect the time required for the microbial numbers to increase to levels comparable with those in the higher inocula. The microbial activity in rumen fluid can be determined by measuring absorbance of the inoculum following a 50-fold dilution at 600 nm and it is recommended a minimum microbial activity of 94 mg bacterial DM/ml [45].

#### **3.6. Effect of concentrate addition on roughage fermentation**

The inclusion of readily digestible carbohydrates in forage-based diets for ruminants can restrict microbial digestion of structural polysaccharides because rumen pH can be below the optimum [46]. The rumen pH below the optimum level is especially unfavourable for microbial fibrolysis. However, when poor quality of roughage such as straw is incubated in batch culture, there may be nutrient deficiency to support microbial growth or lack of fermentable carbohydrate to attract microbes to adhesion on the substrate, consequently reducing digestibility of substrate. Barrios-Urdaneta et al. [47] reported that the low available energy content of the straw cell wall that was incubated in vitro resulted in low fibre digestion even after long hours of incubation (i.e., 72 h). In addition, the low energy was also responsible for low numbers of bacteria associated with the substrate and a low level of polysaccharidase activity, both of which were corrected by the inclusion of energy supplements. Several studies indicated that the source of carbohydrate inclusion could also influence in vitro cell wall fermentation of crop straw. The higher in vitro straw cell wall digestion was observed with addition of pectin versus soluble sugars or starch [47] or when supplemented with sugar beet pulp, a source of highly digestible structural carbohydrates, compared with barley grain as a source of starch [46]. Barrios-Urdaneta et al. [47] suggested that the effect on increased cell wall digestion of straw was mainly attributed to higher bacterial adhesion to cell wall particles at early incubation time. We conducted a batch culture to incubate barley straw alone or barley straw plus a concentrate mix. For the treatment of straw + concentrate, 30% of barley straw was replaced by the equal amount of concentrate mix which consisted of 60% corn distillers grain, 22% canola meal, and 18% mineral and vitamin supplement in dry matter basis. The concentrate was incubated in a second bag within serum bottle. We observed greater rate of gas production and a shorter lag time with adding concentrate than the incubation of barley straw alone. An increased soluble fraction and dry matter degradability as well as increased fibre digestibility of straw by adding concentrate were noticed. The concentrate used in our study consisted of primarily corn distillers' grain which contained very low starch, but high protein and fibre. The fibre in corn distillers' grain has twice hemicellulose compared to original corn and it is highly fermentable in the rumen. Additionally, the protein from concentrate would favour microbial growth compared with straw alone by providing necessary nutrients. It is suggested that adding concentrate would increase microbial colonization on straw and consequently improved dry matter and fibre degradation of poor quality substrate in the rumen. In our study, although rate of gas production was higher, the volume of gas production was lower by adding concentrate, and along with higher digestibility of dry matter, it is suggested that the fermentation efficiency would be improved by adding the concentrate. Doane et al. [48] also noted that gas production of the in vitro fermentation was negatively related to fibre degradation. The lower fibre content of the substrate and the increased fibre degradation by adding concentrate may explain the lower volume of gas production in our study. The positive response of in vitro digestion of poor-quality feed substrates to high fermentable carbohydrate addition suggests necessary consideration when needing to determine the potential digestibility of poor-quality roughage.

#### **4. Conclusions**

and sample preparation procedure in order to reduce variation among experiments and laboratories. Adoption of a standardized approach to sample preparation may be possible to enable comparison between independently produced gas production and digestion data of different feeds. Additionally, as substrate particles are continually changing shape, size and composition in the gut, it seems unlikely that gas production or dry matter digestion data will

The ratio of rumen inoculum to buffer varies considerably in the various batch culture techniques from 1:9 to 1:4 Cabral Filho et al. [43]. Increasing the proportion of rumen inoculum in the incubation medium reduced lag time of gas production, but increased the volume or the rate of gas production [23, 30]. Navarro-Villa et al. [44] incubated with three different ratios of rumen fluid to buffer (i.e., 1:2, 1:4, and 1:6), and observed the increased gas production per unit of dry matter input, CH4 to gas production and CH4 to total volatile fatty acid ratio in all feeds incubated with increasing the proportion of rumen fluid in the mixture. The increase in CH4 output due to change of rumen inoculum to buffer ratio can be resulted from different fermentation pattern, such as for barley grain appeared to be associated with higher acetate to propionate ratios and for barley straw was due to higher volatile fatty acid production. There was also a quadratic response of dry matter digestibility to increased ratios of rumen fluid to buffer with feed dependent, wherein decreasing the ratio resulted in a decline in digestibility with barley grain, an increase with grass silage and an increase (between 1:2 and 1:4) followed by a larger decrease (between 1:4 and 1:6) with barley straw. The decrease in ratio of rumen fluid to buffer would decrease microbial activity of the mixture media, thereby reduced feed digestibility. Pell and Schofield [30] included rumen fluid at the proportions of 5, 10, 20 and 40% in the total medium mixture, and observed the increase of alfalfa hay digestibility with increasing the proportion of ruminal fluid. It suggested that a 20% inoculum is sufficient to ensure the maximum rate of fibre digestion but lower percentages of inoculum are not sufficient. The increased lag time without altering maximum gas productions by lowering the ratio of rumen fluid to buffer appeared to reflect the time required for the microbial numbers to increase to levels comparable with those in the higher inocula. The microbial activity in rumen fluid can be determined by measuring absorbance of the inoculum following a 50-fold dilution at 600 nm and it is recommended a minimum microbial activity of 94 mg bacterial

represent kinetics of plant biomass as it is digested in the rumen.

**3.6. Effect of concentrate addition on roughage fermentation**

The inclusion of readily digestible carbohydrates in forage-based diets for ruminants can restrict microbial digestion of structural polysaccharides because rumen pH can be below the optimum [46]. The rumen pH below the optimum level is especially unfavourable for microbial fibrolysis. However, when poor quality of roughage such as straw is incubated in batch culture, there may be nutrient deficiency to support microbial growth or lack of fermentable carbohydrate to attract microbes to adhesion on the substrate, consequently reducing digestibility of substrate. Barrios-Urdaneta et al. [47] reported that the low available energy content of the

**3.5. Ratio of rumen inoculum to buffer**

86 Fermentation Processes

DM/ml [45].

Several factors including inoculum source, gas venting system, substrate particle size and delivery, ratios of inoculum to buffer, and concentrate addition to media can influence the outcomes of fermentation in batch culture. The rumen inoculum plays a major role in the fermentation in batch culture. The purpose of the inoculum is to provide a suitable microflora to degrade a feed over time and to use the outcome to provide an estimate of rate or extent of feed digestion. The microbial activity of the inoculum can be considerably varied with animal species (e.g., cattle versus sheep), diets, sampling schedule following feeding time, but the most important consideration is to ensure sufficient microbial activity in the inoculum and to reduce the variation of microbial activity among inocula. A means of reducing the variation, perhaps by increasing the number of donor animals and standardizing the inoculum collection time, is likely required. Many researches have been conducted to compare rumen fluid and faeces and aimed to develop an alternative to rumen fluid. The advantage of using faecal inoculum is primarily to reduce the requirement to rumen cannulated animals. However, it should be recognized that faecal and rumen inocula are slightly different. It appears that faeces have the potential to replace rumen fluid if long term in vitro end-point measurements are considered, whereas rumen fluid should be used if short-term or kinetic data are needed. Gas production that is main measurement in batch culture is highly adaptable and powerful research tools at present ruminant nutrition research. The discussion of different venting systems and substrate delivery methods is inconclusive. It suggests that other factors such as bottle size, headspace and type of feeds incubated could be interacted with these systems. The particle size of substrate incubated has consistent influence on rate and extent of feed digestion. The recommendation on the particle size of feed may be not easily provided and may depend on type of feed (e.g., concentrate versus roughage) and the objective of the study. Varying ratios of rumen fluid to buffer volume changes microbial activity in fermentation media, thus potentially alter rate of fermentation and lag time. The recommendation is to ensure sufficient microbial activity in the mixture of fermentation media without too much rumen fluid which may increase proportion of gas from inoculum over substrate. Finally, adding highly fermentable carbohydrate is helpful to maximize the fermentation of poor-quality feeds.

#### **Author details**

#### WenZhu Yang

Address all correspondence to: wenzhu.yang@agr.gc.ca

Agriculture and Agri-Food Canada, Lethbridge Research and Development Centre, Lethbridge, Alberta, Canada

#### **References**


[3] Tagliapietra F, Cattani M, Bailoni L, Schiavon S. In vitro rumen fermentation: effect of headspace pressure on the gas production kinetics of corn meal and meadow hay. Anim. Feed Sci. Technol. 2010;158:197–201.

species (e.g., cattle versus sheep), diets, sampling schedule following feeding time, but the most important consideration is to ensure sufficient microbial activity in the inoculum and to reduce the variation of microbial activity among inocula. A means of reducing the variation, perhaps by increasing the number of donor animals and standardizing the inoculum collection time, is likely required. Many researches have been conducted to compare rumen fluid and faeces and aimed to develop an alternative to rumen fluid. The advantage of using faecal inoculum is primarily to reduce the requirement to rumen cannulated animals. However, it should be recognized that faecal and rumen inocula are slightly different. It appears that faeces have the potential to replace rumen fluid if long term in vitro end-point measurements are considered, whereas rumen fluid should be used if short-term or kinetic data are needed. Gas production that is main measurement in batch culture is highly adaptable and powerful research tools at present ruminant nutrition research. The discussion of different venting systems and substrate delivery methods is inconclusive. It suggests that other factors such as bottle size, headspace and type of feeds incubated could be interacted with these systems. The particle size of substrate incubated has consistent influence on rate and extent of feed digestion. The recommendation on the particle size of feed may be not easily provided and may depend on type of feed (e.g., concentrate versus roughage) and the objective of the study. Varying ratios of rumen fluid to buffer volume changes microbial activity in fermentation media, thus potentially alter rate of fermentation and lag time. The recommendation is to ensure sufficient microbial activity in the mixture of fermentation media without too much rumen fluid which may increase proportion of gas from inoculum over substrate. Finally, adding highly ferment-

able carbohydrate is helpful to maximize the fermentation of poor-quality feeds.

Agriculture and Agri-Food Canada, Lethbridge Research and Development Centre,

methods. Anim. Feed Sci. Technol. 2005;123–124:225–241.

[1] Eun JS, Beauchemin KA, Schulze H. Use of exogenous fibrolytic enzymes to enhance in vitro fermentation of alfalfa hay and corn silage. J. Dairy Sci. 2007;90:1440–1451.

[2] Rymer C, Williams BA, Brooks AE, Davies DR, Givens DI. Inter-laboratory variation of in vitro cumulative gas production profiles of feeds using manual and automated

Address all correspondence to: wenzhu.yang@agr.gc.ca

**Author details**

Lethbridge, Alberta, Canada

WenZhu Yang

88 Fermentation Processes

**References**


In: In vitro techniques for measuring nutrient supply to ruminants, Proceedings of Occasional Meeting of the British Society of Animal Science, 8–10 July 1997, University of Reading, UK.

[30] Pell AN, Schofield P. Computerised monitoring of gas production to measure forage digestion in vitro. J. Dairy Sci. 1993;76:1063–1073.

[16] Soder KJ. Technical note: influence of rumen inoculum source on in vitro dry matter

[17] Cone W J, Cliné-Theil W, Malestein A, Vant Klooster AT. Degradation of starch by inoculum with rumen fluid. A comparison of different starch sources. J. Sci. Agric.

[18] Mertens DR, Weimer PJ, Waghorn GM. Inocula differences affect in vitro gas production kinetics. In: Deaville, E.R., Owen, E., Adesogen, A.T., Rymer, C., Huntington, J.A., Lawrence, T.L.J. (Eds.), In Vitro Techniques for measuring nutrient supply to rumi-

[19] Huntington JA, Rymer C, Givens DI. The effect of host diet on the gas production profile

[20] Menke KH, Steingass H. Estimation of the energetic feed value obtained from chemical analysis and in vitro gas production using rumen fluid. Anim. Res. Dev. 1988;28:7–55.

[21] Cone JW, van Gelder AH, Visscher GJW, Oudshoorn L. Influence of rumen fluid and substrate concentration on fermentation kinetics measured with a fully automated time

[22] Payne JS, Hamersley AR, Milligan JC, Huntington JA. The affect of rumen fluid collection time on its fermentative capacity and the stability of rumen conditions in

[23] Rymer C, Huntington JA, Givens DI. Effects of inoculum preparation method and concentration, method of inoculation and pre-soaking the substrate on the gas production profile of high temperature dried grass. Anim. Feed Sci. Technol. 1999;78:199–

[24] Bueno Ives CS, Sergio LS, Cabral Filho SP, Gobbo, Helder Louvandini, Dorinha MSS Vitti, Adibe L Abdall. Influence of inoculum source in a gas production method. Anim.

[25] Cheng K-J, Akin DE, Costerton JW. Rumen bacteria: interaction with particulate dietary components and response to dietary variations. Fed. Proc. 1977;36:193–197.

[26] Cone JW, van Gelder AH, Bachmann H. Influence of inoculum source on gas production

[27] Bueno ICS, Abdalla AL, Cabral Filho SLS, Vitta DMSS, Owen E, Mauricio RM, Givens I, Sutton JD, Mould FL. Comparison of inocula from sheep and cattle for the in vitro gas production technique under tropical conditions. Proc. Br. Soc. Anim. Sci. 1999;151.

[28] Calabrò S, Williams BA, PiccoloV, Infascelli F, Tamminga S. A comparison between buffalo (*Bubalus bubalis*) and cow (*Bos taurus*) rumen fluids in terms of the in vitro fermentation

[29] Mauricio RM, Owen E, Dhanoa MS, Theodorou MK. Comparison of rumen liquor and faeces from cows as source of microorganisms for the in vitro gas production technique.

characteristics of three fibrous feedstuffs. J. Sci. Food Agric. 2004;84:645–652.

related gas production apparatus. Anim. Feed Sci. Technol. 1996;61:113–128.

nants. BSAS, Edinburgh, UK, 1998;95–98, BSAS Occ. Publ. No. 22.

of hay and high-temperature dried grass. Anim. Sci. 1998;67:59–64.

sheep fed a constant diet. Proc. Br. Soc. Anim. Sci. 2002;165.

Feed Sci. Technol. 2005;123–124:95–105.

profiles. Anim. Feed Sci. Technol. 2002;99:221–231.

digestibility of pasture. Prof. Anim. Sci. 2005;21:45–49.

1989;49:173–183.

90 Fermentation Processes

213.


#### **Kinetic Modeling of 1‐G Ethanol Fermentations** Kinetic Modeling of 1-G Ethanol Fermentations

Samuel C. Oliveira, Dile P. Stremel, Eduardo C. Dechechi and Félix M. Pereira Samuel C. Oliveira, Dile P. Stremel, Eduardo C. Dechechi and Félix M. Pereira

Additional information is available at the end of the chapter Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/65460

#### Abstract

[42] Nocek JE. In situ and other methods to estimate ruminal protein and energy digesti-

[43] Cabral Filho SLS, Abdalla AL, Bueno ICS, Nozella EF, Rodrigues JAS. Ruminal fermentation and degradability of sorghum cultivar whole crop, and grains, using an in vitro gas production technique. Anim. Feed Sci. Technol. 2005;123–124:329–339. [44] Navarro-Villa A, O'Brien M, López S, Boland TM, O'Kiely P. Modifications of a gas production technique for assessing in vitro rumen methane production from feedstuffs.

[45] Nagadi S, Herrero M, Jessop NS. The influence of diet of the donor animal on the initial bacterial concentration of ruminal fluid and in vitro gas production degradability

[46] Fondevila M, Castrillo C, Guada JA, Balcells J. Effect of ammonia treatment and carbohydrate supplementation of barley straw on rumen liquid characteristics and

[47] Barrios-Urdaneta A, Fondevila M, Balcells J, Dapoza C, Castrillo C. In vitro microbial digestion of straw cell wall polysaccharides in response to supplementation with

[48] Doane PH, Schofield P, Pell AN. Neutral detergent fiber disappearance and gas and volatile fatty acid production during the in vitro fermentation of six forages. J. Anim.

substrate degradation by sheep. Anim. Feed Sci. Technol. 1994;50:137–155.

different sources of carbohydrates. Aust. J. Agric. Res. 2000;51:393–399.

bility: a review. J. Dairy Sci. 1988;71:2051–2069.

92 Fermentation Processes

Anim. Feed Sci. Technol. 2011;166–167:163–174.

Sci. 1997;75:3342–3352.

parameters. Anim. Feed Sci. Technol. 2000;87:231–239.

The most recent rise in demand for bioethanol, due mainly to economic and environmental issues, has required highly productive and efficient processes. In this sense, mathematical models play an important role in the design, optimization, and control of bioreactors for ethanol production. Such bioreactors are generally modeled by a set of first-order ordinary differential equations, which are derived from mass and energy balances over bioreactors. Complementary equations have also been included to describe fermentation kinetics, based on Monod equation with additional terms accounting for inhibition effects linked to the substrate, products, and biomass. In this chapter, a reasonable number of unstructured kinetic models of 1-G ethanol fermentations have been compiled and reviewed. Segregated models, as regards the physiological state of the biomass (cell viability), have also been reviewed, and it was found that some of the analyzed kinetic models are also applied to the modeling of second-generation ethanol production processes.

Keywords: ethanol fermentation, kinetic modeling, unstructured and unsegregated models, inhibition phenomena, bioreactors

#### 1. Introduction

The interest in producing industrial bioethanol essentially comes from economic and environmental issues. Bioethanol can be produced from batch, fed-batch, and continuous processes, as well as in some cases using flocculating yeasts [1–6].

The development of efficient control strategies for the main operating variables in ethanol fermentations, such as pH, temperature, residual sugars concentration, agitation speed, foam level, among others, requires accurate dynamic models. In addition, mathematical models are important tools for the design, optimization, and control of bioreactors. Bioreactor models seek to describe the overall performance of the bioreactor and consist of two submodels: a balance/

Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and eproduction in any medium, provided the original work is properly cited.

transport submodel that describes mass and heat transfer within and between the various phases of the bioreactor and a kinetic submodel that describes how the rates of the microorganism's growth, substrate consumption, and product formation depend on the key local environmental variables [7].

In ethanol fermentation, the main bioreactions can be summarized by the reductive pathway S ! X + P + CO2. According to this reaction, substrates S (glucose and fructose, which result from hydrolysis of sucrose as the limiting substrate), in anaerobic conditions, are metabolized to produce a yeast population X, ethanol P (mainly produced by yeast through the Embden-Meyerhof-Parnas metabolic pathway), and carbon dioxide (CO2). The hydrolysis of sucrose promoted by the invertase present in the yeast is not the limiting step of ethanol production in industrial processes. The stoichiometry of ethanol-formation reaction from glucose is given by the classical Gay-Lussac equation: C6H12O6 !2CH3CH2OH + 2CO2

According to Doran [8], both Saccharomyces cerevisiae yeast and Zymomonas mobilis bacteria produce ethanol from glucose under anaerobic conditions without external electron acceptors. The biomass yield from glucose is 0.11 g/g for yeast and 0.05 g/g for Z. mobilis. In both cases, the nitrogen source is NH3, and the cell compositions are represented by the formula C1.8O0.5N0.2. From these data, Doran [9] proposed the following stoichiometric equation for ethanol fermentation (the values of stoichiometric coefficients a, b, c, d, e, and f are presented in Table 1):

$$\text{cC}\_6\text{H}\_{12}\text{O}\_6 + b\text{NH}\_3 \rightarrow \text{cCH}\_{1.8}\text{O}\_{0.5}\text{N}\_{0.2} + d\text{CO}\_2 + e\text{H}\_2\text{O} + f\text{C}\_2\text{H}\_6\text{O} \text{(molar basis)}$$

Kinetic modeling of growth, ethanol production, and substrate consumption by yeasts has been traditionally conducted using an unsegregated and unstructured approach for the biomass. This approach ignores the presence of individual cells and structural, functional, and compositional aspects of the cell, describing the complex processes of growth, ethanol production, and substrate consumption through simple kinetic equations [10–15]. Figure 1 shows a simplified scheme of this approach for the ethanol fermentation process by yeasts and bacteria.


Table 1. Stoichiometric coefficients for ethanol fermentation.

Figure 1. Kinetic modeling of ethanol fermentation based on an unsegregated and unstructured approach for cells (yeasts or bacteria).

#### 2. Kinetics of cell growth and ethanol formation

In ethanol fermentation, the kinetics of growth and ethanol production are generally the following:

$$
\mu\_X = f\_1(\mathbb{S}) \mathbb{g}\_1(P) \tag{1}
$$

$$
\mu\_p = f\_2(\mathcal{S}) \mathcal{g}\_2(P) \tag{2}
$$

where μ<sup>X</sup> and μp, are, respectively, the specific rate of yeast growth and ethanol production, whereas S and P represent the limiting substrate and ethanol concentrations.

#### 2.1. Effect of substrate concentration

transport submodel that describes mass and heat transfer within and between the various phases of the bioreactor and a kinetic submodel that describes how the rates of the microorganism's growth, substrate consumption, and product formation depend on the key local

In ethanol fermentation, the main bioreactions can be summarized by the reductive pathway S ! X + P + CO2. According to this reaction, substrates S (glucose and fructose, which result from hydrolysis of sucrose as the limiting substrate), in anaerobic conditions, are metabolized to produce a yeast population X, ethanol P (mainly produced by yeast through the Embden-Meyerhof-Parnas metabolic pathway), and carbon dioxide (CO2). The hydrolysis of sucrose promoted by the invertase present in the yeast is not the limiting step of ethanol production in industrial processes. The stoichiometry of ethanol-formation reaction from glucose is given by

According to Doran [8], both Saccharomyces cerevisiae yeast and Zymomonas mobilis bacteria produce ethanol from glucose under anaerobic conditions without external electron acceptors. The biomass yield from glucose is 0.11 g/g for yeast and 0.05 g/g for Z. mobilis. In both cases, the nitrogen source is NH3, and the cell compositions are represented by the formula C1.8O0.5N0.2. From these data, Doran [9] proposed the following stoichiometric equation for ethanol fermentation (the values of stoichiometric coefficients a, b, c, d, e, and f are presented in Table 1):

aC6H12O6 þ bNH3 ! cCH1:8O0:5N0:<sup>2</sup> þ dCO2 þ eH2O þ f C2H6Oðmolar basisÞ

Kinetic modeling of growth, ethanol production, and substrate consumption by yeasts has been traditionally conducted using an unsegregated and unstructured approach for the biomass. This approach ignores the presence of individual cells and structural, functional, and compositional aspects of the cell, describing the complex processes of growth, ethanol production, and substrate consumption through simple kinetic equations [10–15]. Figure 1 shows a simplified

Yeast 1 0.16 0.81 1.75 0.35 1.72 Bacteria 1 0.074 0.37 1.89 0.17 1.87

ab c d e f

Figure 1. Kinetic modeling of ethanol fermentation based on an unsegregated and unstructured approach for cells (yeasts

scheme of this approach for the ethanol fermentation process by yeasts and bacteria.

Microorganism Stoichiometric coefficients

Table 1. Stoichiometric coefficients for ethanol fermentation.

the classical Gay-Lussac equation: C6H12O6 !2CH3CH2OH + 2CO2

environmental variables [7].

94 Fermentation Processes

or bacteria).

The functions f1(S) and f2(S) are generally of the Monod type [11], except when an inhibition caused by high concentrations of substrate or diffusional limitations occurs due to high cell concentrations.

$$f(S) = \frac{\mu\_{\text{max}} S}{K\_S + S} (\text{Monod equation}) \tag{3}$$

The inhibition caused by the excess of substrate has generally been modeled by applying the Andrews equation [16–19], though there are other types of equations that are less commonly used [20].

$$f(S) = \frac{\mu\_{\text{max}} S}{K\_S + S + S^2/K\_I} (\text{Andrews equation}) \tag{4}$$

In the case of continuous processes operated near to the steady state, the inhibition concentrations of the substrate are rarely identified. However, inhibitory concentrations can occur during the start-up of these processes or in situations resulting from changes in the substrate feed load.

Atala et al. [21], modeling the effect of temperature upon the kinetics of ethanol fermentation with a high concentration of biomass in a continuous system with total cell retention, used an inhibitory factor (IF) of the exponential type to describe the inhibitory effect of the substrate upon the kinetics of cell growth, which was inserted in the expression of f(S), being f(S), in this case, given by the Monod equation.

$$IF = (e^{-\mathcal{K}\_l S})\tag{5}$$

Tsuji et al. [22] evaluating the performance of different ethanol fermentation systems (conventional chemostat, multiple bioreactors, cell recycle bioreactor, extractive bioreactor, and immobilized cell bioreactor) expressed the specific growth rate by an equation analogous to Eq. (1):

$$
\mu\_X = \mu\_1(S)\mu\_2(P) \tag{6}
$$

One of the analyzed cases considered growth inhibition by substrate, represented by a hyperbolic equation:

$$
\mu\_1(S) = \frac{\mu\_{\text{max}} S}{K\_S + S} \left(\frac{K\_i}{K\_i + S}\right) \tag{7}
$$

Sousa and Teixeira [23] reported that one of the main disadvantages of the systems that use flocculating cells (bacteria or yeast) is the reduced reaction rates caused by diffusional limitations of the substrate within the flocs and that, in most cases, the diffusion rate is lower than the reaction rate, which means that the process is controlled by diffusion. Sousa and Teixeira [23] reported that it is generally accepted that yeast flocs are formed by a mediator cation (usually Ca2+) from the interaction between protein and mannans on adjacent cell walls. According to Sousa and Teixeira [23], one means through which to avoid diffusional limitations within the flocs is by using polymeric additives, which act by widening the bridges formed between adjacent cells.

Fontana et al. [24] reported that when the yeast flocs are suspended in a sucrose solution, various phenomena occur simultaneously: the sugar penetrates by diffusion in the aggregates and is hydrolyzed into glucose and fructose by an invertase that is primarily located on the yeast's cell wall. These two sugars diffuse inside and outside of the particle and are fermented in ethanol and CO2, which in turn diffuse back in the liquid medium.

Fontana et al. [24] assumed that the Fick's law was valid for the aggregate and that the temporal variation of the concentration of each component involved in the transformation is represented by the following equation:

$$\frac{\partial \mathcal{L}\_i}{\partial t} = D\_{\mathcal{eff},i} \frac{\partial \,^2 \mathcal{L}\_i}{\partial \, x^2} + \Sigma r\_i \tag{8}$$

where Ci is the concentration of the component i in the aggregate in time t and distance x as of the floc surface; Def,i is the effective diffusion coefficient, while ∑ri is the sum of the consumption or production rates of component i, which are given by Michaelis-Menten-type equations, such as the following:

$$
\Sigma r\_i = -r\_{S\_{\text{max}}} \frac{S}{K\_S + S} \text{ (Sucrose)}\tag{9}
$$

$$r\_i \Sigma r\_i = +Y\_{G/S} r\_{\text{S\_{max}}} \frac{S}{K\_S + S} - r\_{G\_{\text{max}}} \frac{G}{K\_G + G} (\text{Glucose}) \tag{10}$$

where S and G represent, respectively, the concentration of sucrose and glucose, while YG/S is the conversion factor in glucose based on the hydrolyzed sucrose (YG/S = 0.505g-glucose/gsucrose). One relation identical to Eq. (10) can be obtained for fructose.

However, the theoretical descriptions of the diffusional resistances in systems that make use of flocculating microorganisms are generally conducted by introducing a factor into the Monod equation that takes into account the reduction in growth rate due to mass transfer limitations. One equation of this type is that proposed by Contois [25].

$$f(S) = \frac{\mu\_{\text{max}}S}{K\_S X + S} (\text{Contois equation}) \tag{11}$$

According to Menezes et al. [26], the Monod model is appropriate at low cell concentrations, while the Contois model is more appropriate at high concentrations, given that the variable saturation term, KSX, can describe the diffusional limitations present in high cell concentrations. Oliveira et al. [27], modeling a continuous process of ethanol fermentation in a tower bioreactor with recycling of flocculating yeasts, obtained a high value for KS, which was attributed to the diffusional limitations caused by the high cell concentrations reached in the bioreactor.

#### 2.2. Effect of ethanol concentration

μ<sup>X</sup> ¼ μ1ðSÞμ2ðPÞ (6)

<sup>∂</sup> <sup>x</sup><sup>2</sup> <sup>þ</sup> <sup>∑</sup>ri (8)

KS <sup>þ</sup> <sup>S</sup> <sup>ð</sup>Sucrose<sup>Þ</sup> (9)

KG <sup>þ</sup> <sup>G</sup> <sup>ð</sup>Glucose<sup>Þ</sup> (10)

(7)

One of the analyzed cases considered growth inhibition by substrate, represented by a hyper-

KSþS

Sousa and Teixeira [23] reported that one of the main disadvantages of the systems that use flocculating cells (bacteria or yeast) is the reduced reaction rates caused by diffusional limitations of the substrate within the flocs and that, in most cases, the diffusion rate is lower than the reaction rate, which means that the process is controlled by diffusion. Sousa and Teixeira [23] reported that it is generally accepted that yeast flocs are formed by a mediator cation (usually Ca2+) from the interaction between protein and mannans on adjacent cell walls. According to Sousa and Teixeira [23], one means through which to avoid diffusional limitations within the flocs is by using polymeric additives, which act by widening the bridges

Fontana et al. [24] reported that when the yeast flocs are suspended in a sucrose solution, various phenomena occur simultaneously: the sugar penetrates by diffusion in the aggregates and is hydrolyzed into glucose and fructose by an invertase that is primarily located on the yeast's cell wall. These two sugars diffuse inside and outside of the particle and are fermented

Fontana et al. [24] assumed that the Fick's law was valid for the aggregate and that the temporal variation of the concentration of each component involved in the transformation is

> ∂ 2 Ci

where Ci is the concentration of the component i in the aggregate in time t and distance x as of the floc surface; Def,i is the effective diffusion coefficient, while ∑ri is the sum of the consumption or production rates of component i, which are given by Michaelis-Menten-type equations,

S

where S and G represent, respectively, the concentration of sucrose and glucose, while YG/S is the conversion factor in glucose based on the hydrolyzed sucrose (YG/S = 0.505g-glucose/g-

However, the theoretical descriptions of the diffusional resistances in systems that make use of flocculating microorganisms are generally conducted by introducing a factor into the Monod

G

S KS <sup>þ</sup> <sup>S</sup> <sup>−</sup>rGmax

in ethanol and CO2, which in turn diffuse back in the liquid medium.

∂ Ci <sup>∂</sup> <sup>t</sup> <sup>¼</sup>Def ,<sup>i</sup>

∑ri ¼ −rSmax

∑ri ¼ þYG=SrSmax

sucrose). One relation identical to Eq. (10) can be obtained for fructose.

Ki KiþS 

<sup>μ</sup>1ðSÞ ¼ <sup>μ</sup>max<sup>S</sup>

bolic equation:

96 Fermentation Processes

formed between adjacent cells.

represented by the following equation:

such as the following:

The dependence of μ<sup>X</sup> and μ<sup>P</sup> on the ethanol concentration is due to the fact that this product has been reported in the literature to act as a noncompetitive inhibitor both for growth and its own production [10, 28–32].

Noncompetitive inhibition is characterized by the fact that in the graph of 1/μ<sup>X</sup> or 1/μ<sup>p</sup> versus 1/S (Figure 2), for each ethanol concentration (P), straight lines with different slopes

Figure 2. Lineweaver-Burk graph for the specific rates of cell growth (μX) and ethanol production (μP) (adapted from Aiba et al. [31]).

KS,<sup>i</sup> μmax,<sup>i</sup> gi <sup>ð</sup>P<sup>Þ</sup> , <sup>i</sup> <sup>¼</sup> <sup>1</sup>; <sup>2</sup> and different intercepts <sup>1</sup> μmax,<sup>i</sup> gi <sup>ð</sup>P<sup>Þ</sup> , <sup>i</sup> <sup>¼</sup> <sup>1</sup>; <sup>2</sup> are obtained, but the same intersections with the abscissa are maintained (−1/KS,i; i = 1, 2).

The molecular base of the mechanism through which the ethanol exerts an inhibitory effect upon fermentation is complex so long as this component, which acts as a denaturing agent, not only acts directly upon the proteins and causes an inactivation or inhibition of the enzymes from the glycolytic pathway but can also act upon the integrity of the lipid membranes, affecting the essential factors, including membrane components, such as transport proteins and the enzymes linked to it [33].

Table 2 presents the main equations proposed for g1(P) and g2(P), which are first approximations of much more complicated effects [10, 28–32, 34–42].


Table 2. Types of commonly proposed equations to describe the inhibitory effect of ethanol upon μ<sup>X</sup> and μP.

The type of inhibition that affects cell growth is not mandatorily the same as that which affects ethanol production, as it is necessary to determine separately each effect, as proposed by Oliveira et al. [27]. According to Bonomi et al. [17], one of the major difficulties during the development of a mathematical model that fits experimental data of ethanol fermentation is the definition of the type of product inhibition exhibited by the yeast's metabolism. Bonomi et al. [17] reported that this inhibition is characterized by the behavior of the specific growth and production rates with an increase in ethanol concentration, while holding constant the substrate concentration. When developing a mathematical model for a batch system of ethanol production, Bonomi et al. [17] set three values for substrate concentration and determined the corresponding pairs of values (μX, P) and (μP, P) in each fermentation test. These points—(μX, P) and (μP, P)—were then plotted to define the types of existing relations between the specific rates and ethanol concentration which, in this case, were both exponential. The values of the specific growth and ethanol production rates were calculated based on experimental data, using the geometric approach proposed by Le Duy and Zajic [43].

The conceptual limitation of the hyperbolic and exponential inhibition is that they predict cell growth and production for all of the ethanol concentrations, even though many experimental tests have shown that cell growth and production cease upon reaching a given high concentration of ethanol [44]. The models of linear, generalized nonlinear, and parabolic inhibition consider that there is a determined concentration of ethanol above which growth and production do not occur. In these models, the Pm parameters represent the ethanol concentrations for which the growth and production processes are completely interrupted.

In the linear, generalized nonlinear, and parabolic models, the exponents of the term (1−P/Pm) are called by Levenspiel [40] as "toxic powers." The values of toxic powers are indicative of how the term of inhibition (1−P/Pm) strongly affects the specific growth and ethanol production rates. With the rise in toxic power, the intensity of inhibition increases for a determined ethanol concentration.

KS,<sup>i</sup> μmax,<sup>i</sup> gi

98 Fermentation Processes

<sup>ð</sup>P<sup>Þ</sup> , <sup>i</sup> <sup>¼</sup> <sup>1</sup>; <sup>2</sup> 

and the enzymes linked to it [33].

and different intercepts <sup>1</sup>

sections with the abscissa are maintained (−1/KS,i; i = 1, 2).

tions of much more complicated effects [10, 28–32, 34–42].

Linear (L) <sup>g</sup>ðPÞ ¼ <sup>1</sup><sup>−</sup> <sup>P</sup>

Generalized nonlinear (GN) <sup>g</sup>ðPÞ ¼ <sup>1</sup><sup>−</sup> <sup>P</sup>

Hyperbolic (H) <sup>g</sup>ðPÞ ¼ KP

Parabolic (P) <sup>g</sup>ðPÞ ¼ <sup>1</sup><sup>−</sup> <sup>P</sup>

using the geometric approach proposed by Le Duy and Zajic [43].

which the growth and production processes are completely interrupted.

μmax,<sup>i</sup> gi

The molecular base of the mechanism through which the ethanol exerts an inhibitory effect upon fermentation is complex so long as this component, which acts as a denaturing agent, not only acts directly upon the proteins and causes an inactivation or inhibition of the enzymes from the glycolytic pathway but can also act upon the integrity of the lipid membranes, affecting the essential factors, including membrane components, such as transport proteins

Table 2 presents the main equations proposed for g1(P) and g2(P), which are first approxima-

The type of inhibition that affects cell growth is not mandatorily the same as that which affects ethanol production, as it is necessary to determine separately each effect, as proposed by Oliveira et al. [27]. According to Bonomi et al. [17], one of the major difficulties during the development of a mathematical model that fits experimental data of ethanol fermentation is the definition of the type of product inhibition exhibited by the yeast's metabolism. Bonomi et al. [17] reported that this inhibition is characterized by the behavior of the specific growth and production rates with an increase in ethanol concentration, while holding constant the substrate concentration. When developing a mathematical model for a batch system of ethanol production, Bonomi et al. [17] set three values for substrate concentration and determined the corresponding pairs of values (μX, P) and (μP, P) in each fermentation test. These points—(μX, P) and (μP, P)—were then plotted to define the types of existing relations between the specific rates and ethanol concentration which, in this case, were both exponential. The values of the specific growth and ethanol production rates were calculated based on experimental data,

Exponential (E) <sup>g</sup>ðPÞ¼ðe<sup>−</sup>KPP<sup>Þ</sup> (16)

Table 2. Types of commonly proposed equations to describe the inhibitory effect of ethanol upon μ<sup>X</sup> and μP.

The conceptual limitation of the hyperbolic and exponential inhibition is that they predict cell growth and production for all of the ethanol concentrations, even though many experimental tests have shown that cell growth and production cease upon reaching a given high concentration of ethanol [44]. The models of linear, generalized nonlinear, and parabolic inhibition consider that there is a determined concentration of ethanol above which growth and production do not occur. In these models, the Pm parameters represent the ethanol concentrations for

<sup>ð</sup>P<sup>Þ</sup> , <sup>i</sup> <sup>¼</sup> <sup>1</sup>; <sup>2</sup> 

> Pm

Pm <sup>n</sup>

Pm <sup>0</sup>:<sup>5</sup>

KPþP  are obtained, but the same inter-

(12)

(13)

(14)

(15)

In the hyperbolic and exponential inhibition models, the KP parameters do not admit a physical meaning and can be considered simple empirical constants that apparently depend on the cultivation mode: batch or continuous [31, 32, 37]. Aiba and Shoda [32] argued that the fact that the hyperbolic inhibition constant of the specific growth rate (KP) has been lower in a batch culture (KP = 16.0 g/L) than in a continuous culture (KP =5 5.0 g/L) suggests the possibility that a chemical affinity of ethanol for a key participating enzyme in cell growth appeared in batch experiments. By contrast, the fact that the hyperbolic inhibition constant of the specific ethanol production rate (K′ P) has been lower in continuous cultures (K′ <sup>P</sup> = 12.5 g/L) than in batch cultures (K′ <sup>P</sup> = 71.5 g/L) suggests that the ethanol inhibition upon another key enzyme responsible for the fermentation activity was more expressive in continuous experiments.

Another inhibition model commonly used in the literature is that proposed by Luong [37]:

$$\text{g}(P) = 1 - \left(\frac{P}{P\_m}\right)^{\beta} \tag{17}$$

where Pm continues to be the ethanol concentration above which no growth or production can occur, and β is an empirical constant.

One different proposal to describe the inhibitory effects of ethanol upon μ<sup>X</sup> and μ<sup>P</sup> was presented by Wang and Sheu [45] when they applied multiobjective optimization methods to estimate the parameters of kinetic models of batch and fed-batch processes for ethanol production, using one yeast that is highly tolerant to ethanol (Saccharomyces diastaticus). In their study, the kinetic models for the specific rate of cell growth and product formation were represented as follows:

$$
\mu\_X = \left(\frac{\mu\_m S}{K\_S + S + S^2/K\_{IS}}\right) \left(\frac{K\_P}{K\_P + P + P^2/K\_{IP}}\right) \tag{18}
$$

$$
\mu\_p = \left(\frac{\nu\_m S}{K\_S + S + S^2/K\_{IS}^{'}}\right) \left(\frac{K\_p^{'}}{K\_P + P + P^2/K\_{IP}^{'}}\right) \tag{19}
$$

Olaoye and Kolawole [46], modeling the kinetics of ethanol fermentation in batch culture of Kluyveromyces marxianus, used a semiempirical approach to describe the fermentation process. To model the temporal profile of the biomass concentration, the authors inserted Eq. (20) in the cell mass balance (dX/dt = μXX) and analytically integrated the resulting equation to obtain the so-called logistic growth curve (Eq. 21). The ethanol concentration was described, directly applying the modified Gompertz equation (Eq. 22), which represented the empirical part of the proposed mathematical model. The authors did not report the values of the model's parameters.

$$
\mu\_X = \mu\_m \left( 1 - \frac{X}{X\_m} \right) \tag{20}
$$

$$X = \frac{X\_m}{1 + \left(\frac{X\_m - X\_0}{X\_0}\right)e^{-\mu\_m t}};\\X\_0 = X(0) \tag{21}$$

$$P = P\_m \exp\left\{-\exp\left[\frac{\text{Pr}\_m \exp\left(1\right)}{P\_m}(\lambda - t) + 1\right]\right\} \tag{22}$$

where Pm and Pr<sup>m</sup> are, respectively, the maximum concentration and maximum productivity of ethanol; λ is the time of duration of the lag phase, anterior to the exponential phase of ethanol production.

The logistic equation has been used to model fermentation kinetics due to its mathematical simplicity. According to Mitchell [7], the logistic equation can, many times in a single equation, offer an adequate approximation of the entire growth curve, including the lag phase and the cessation of growth in the latter stages of fermentation.

#### 2.3. Effect of cell concentration

The inhibition models presented thus far have been sufficient to satisfactorily describe a large number of fermentations. However, in continuous processes with cell recycling, high cell densities are obtained in the fermenter, and the consideration of other factors, such as the inhibition caused by the excess of biomass, may well be necessary for a better description of the bioprocess kinetic behavior.

The inhibition of cell growth by cell concentrations has been modeled using the following generalized equation [44]:

$$h(X) = \left(1 - \frac{X}{X\_{\text{max}}}\right)^{\delta} \tag{23}$$

where Xmax is the maximum cell concentration that would be reached if ideal conditions for growth were observed, that is, an adequate supply of nutrients and the absence of inhibitory effects [44]. Analogous to the term of inhibition caused by the product, δ indicates the intensity of the inhibition due to the high cell concentrations.

Jarzebski et al. [47], modeling a continuous ethanol fermentation process with high yeast concentrations in a membrane filtration module system, used the following expressions for μ<sup>X</sup> and μP, in which other formats can be observed for the terms that describe the inhibitory effects of the biomass itself:

$$
\mu\_X = \left(\frac{\mu\_0 S}{K\_S + S}\right) \left[1 - \left(\frac{P}{P\_m}\right)^{A\_1}\right] \left[1 - \left(\frac{X}{X\_m}\right)^{A\_2}\right] \tag{24}
$$

$$
\mu\_P = a \exp\left(-bX\right) \tag{25}
$$

In cases occurring inhibition of cell growth and product formation by the biomass itself, the expressions of the specific growth and ethanol production rates must be augmented to incorporate these inhibitory effects, that is,

<sup>μ</sup><sup>X</sup> <sup>¼</sup> <sup>μ</sup><sup>m</sup> <sup>1</sup><sup>−</sup> <sup>X</sup>

<sup>X</sup> <sup>¼</sup> Xm <sup>1</sup> <sup>þ</sup> Xm−X<sup>0</sup> X0 � �

P ¼ Pm exp − exp

cessation of growth in the latter stages of fermentation.

of the inhibition due to the high cell concentrations.

<sup>μ</sup><sup>X</sup> <sup>¼</sup> <sup>μ</sup>0<sup>S</sup>

KS þ S � �

ethanol production.

100 Fermentation Processes

2.3. Effect of cell concentration

the bioprocess kinetic behavior.

generalized equation [44]:

effects of the biomass itself:

Xm � �

e<sup>−</sup>μm<sup>t</sup>

where Pm and Pr<sup>m</sup> are, respectively, the maximum concentration and maximum productivity of ethanol; λ is the time of duration of the lag phase, anterior to the exponential phase of

The logistic equation has been used to model fermentation kinetics due to its mathematical simplicity. According to Mitchell [7], the logistic equation can, many times in a single equation, offer an adequate approximation of the entire growth curve, including the lag phase and the

The inhibition models presented thus far have been sufficient to satisfactorily describe a large number of fermentations. However, in continuous processes with cell recycling, high cell densities are obtained in the fermenter, and the consideration of other factors, such as the inhibition caused by the excess of biomass, may well be necessary for a better description of

The inhibition of cell growth by cell concentrations has been modeled using the following

where Xmax is the maximum cell concentration that would be reached if ideal conditions for growth were observed, that is, an adequate supply of nutrients and the absence of inhibitory effects [44]. Analogous to the term of inhibition caused by the product, δ indicates the intensity

Jarzebski et al. [47], modeling a continuous ethanol fermentation process with high yeast concentrations in a membrane filtration module system, used the following expressions for μ<sup>X</sup> and μP, in which other formats can be observed for the terms that describe the inhibitory

> <sup>1</sup><sup>−</sup> <sup>P</sup> Pm � �<sup>A</sup><sup>1</sup> " #

<sup>1</sup><sup>−</sup> <sup>X</sup> Xm � �<sup>A</sup><sup>2</sup> " #

μ<sup>P</sup> ¼ a exp ð−bXÞ (25)

Xmax � �<sup>δ</sup>

<sup>h</sup>ðXÞ ¼ <sup>1</sup><sup>−</sup> <sup>X</sup>

Pr<sup>m</sup> exp ð1Þ Pm

� � � �

ðλ−tÞ þ 1

(20)

(22)

(23)

(24)

; X<sup>0</sup> ¼ Xð0Þ (21)

$$
\mu\_X = f\_1(S) g\_1(P) h\_1(X) \tag{26}
$$

$$
\mu\_p = f\_2(\mathcal{S}) \mathcal{g}\_2(P) h\_2(X) \tag{27}
$$

As regards the procedures of many authors using a kinetic expression for μ<sup>P</sup> detached from μX, Bu'Lock et al. [10] reported that this does not mean that there is no association between these rates, so long as the ethanol production has been commonly reported in the literature as a process associated with growth. Bu'Lock et al. [10] justified the adoption of such a procedure due to the simplicity and to the better adaptation of such equations to experimental data.

In relating the kinetics of ethanol production to the kinetics of cell growth, the procedure has been to apply the Luedeking-Piret model:

$$
\mu\_P = \alpha \mu\_X + \beta \tag{28}
$$

The Luedeking-Piret model is based on the classification of products of the fermentation process as associated (α > 0, β = 0), nonassociated (α = 0, β > 0), and partially associated with cell growth (α > 0, β > 0) [12]. Since ethanol is a product of the primary metabolism of the yeasts, the majority of described cases assumes α > 0 and β = 0, as reported by Oliveira et al. [19] when they modeled the batch ethanol production, using the expression μ<sup>P</sup> = αμX, with α = 4.17 g/g. However, it is possible to find descriptions in the literature of ethanol production, parts associated and not associated with cell growth, that is, α > 0 and β > 0, as is the case with that reported by Guidini et al. [18] that used the following equation to describe μ<sup>P</sup> in a fedbatch ethanol fermentation process with flocculating yeasts (S. cerevisiae):

$$
\mu\_p = \underbrace{\left(\frac{Y\_{P/S}}{Y\_{X/S}}\right)\mu\_X + b}\_{a} \tag{29}
$$

Rivera et al. [48], modeling a fed-batch ethanol fermentation process with a strain of industrial yeast (S. cerevisiae), used a modified version of the Luedeking and Piret model in which the β coefficient is given as a function of the substrate concentration (S):

$$
\mu\_P = Y\_{P/X}\mu\_X + \underbrace{\left(\frac{\beta\_m S}{K\_{\beta S} + S}\right)}\_{\beta} \tag{30}
$$

Ghosh and Ramachandran [49], analyzing the effect of in situ product removal on the stability and performance of a continuous bioreactor with cell separator for ethanol production, emphasized the use of the Luedeking-Piret model to represent the kinetics of product formation.

In Table 3, typical kinetic parameter values for ethanol fermentation are presented [10, 19, 28– 32, 34–41].

Table 3 shows large variations in the values of kinetic parameters, demonstrating that these parameters are strongly dependent upon the operational conditions for which they were adjusted, from the culture medium and from the microorganisms used in the fermentation.

Oliveira et al. [50] analyzed the scale-up effects on kinetic parameters and predictions of a mathematical model developed for a continuous process, in small scale, of ethanol fermentation in a tower bioreactor with flocculating yeast recycling, and concluded that the scale-up did not affect the parameter values and that the model continued to be valid to describe the process in the newly investigated scale.

Although the great majority of mathematical models reviewed thus far have been developed for free cell systems, these are equally valid for naturally or artificially immobilized cell systems. However, physiological changes in microbial cells caused by immobilization can significantly affect the values of the kinetic parameters of such models. Moreover, internal and external diffusion effects in microbial particles and flocs can affect the fermentation kinetics. Admassu et al. [38], modeling the hydrodynamics and the profile of product concentration in a tower fermenter for the continuous production of ethanol with flocculating yeasts, reported that the growth and reaction rates for these flocculating microorganisms are frequently limited by mass transfer.

Vicente et al. [51], developing a new technique to measure kinetics and mass transfer parameters in flocs of S. cerevisiae, modeled the kinetics of oxygen consumption using the following equation:


Table 3. Typical values of kinetics parameters in ethanol fermentation.

$$r\_{\mathbb{C}} = -\left(\frac{p\_1 \mathbb{C}}{p\_2 + \mathbb{C}}\right) X \tag{31}$$

where rC is the oxygen consumption rate (mg O2/(L h)) from which the specific rate of respiration qO can be calculated, C is the dissolved oxygen concentration (mg O2/L), X is the active biomass concentration (g/L), p<sup>1</sup> corresponds to qO,m (mg O2/(g h)), qO,m and p2 corresponds to Km (mg O2/L).

According to Vicente et al. [51], although Eq. (31) represents a Monod-type kinetic model, the calculated values of p<sup>1</sup> and p<sup>2</sup> are only apparent and have no direct relationship with the usual kinetic parameters. Vicente et al. [51] argue that the designations qO,m and Km were not used because they are generally applied to suspended free cell cultures and that, in this case, cell aggregates were studied, which significantly change the overall behavior of the system and, therefore, the meaning of such parameters.

#### 3. Kinetics of substrate consumption

In Table 3, typical kinetic parameter values for ethanol fermentation are presented [10, 19, 28–

Table 3 shows large variations in the values of kinetic parameters, demonstrating that these parameters are strongly dependent upon the operational conditions for which they were adjusted, from the culture medium and from the microorganisms used in the fermentation.

Oliveira et al. [50] analyzed the scale-up effects on kinetic parameters and predictions of a mathematical model developed for a continuous process, in small scale, of ethanol fermentation in a tower bioreactor with flocculating yeast recycling, and concluded that the scale-up did not affect the parameter values and that the model continued to be valid to describe the

Although the great majority of mathematical models reviewed thus far have been developed for free cell systems, these are equally valid for naturally or artificially immobilized cell systems. However, physiological changes in microbial cells caused by immobilization can significantly affect the values of the kinetic parameters of such models. Moreover, internal and external diffusion effects in microbial particles and flocs can affect the fermentation kinetics. Admassu et al. [38], modeling the hydrodynamics and the profile of product concentration in a tower fermenter for the continuous production of ethanol with flocculating yeasts, reported that the growth and reaction rates for these flocculating microorganisms are fre-

Vicente et al. [51], developing a new technique to measure kinetics and mass transfer parameters in flocs of S. cerevisiae, modeled the kinetics of oxygen consumption using the following

Parameters of f1(S), f2(S) h(X) Parameters of g1(P) g2(P)

Kp,<sup>1</sup> (L/g or g/L) 16.0–105.2 0.016–0.029 Kp,<sup>2</sup> (L/g or g/L) 12.5–71.5 0.015–0.094

Pm,<sup>1</sup> (g/L) 87.0–95.0 73.0–87.5 93.6 Pm,<sup>2</sup> (g/L) 114.0–135.0 87.5 99.0

n<sup>1</sup> (–) 0.41–4.0 n<sup>2</sup> (–) 0.41

Table 3. Typical values of kinetics parameters in ethanol fermentation.

L GN P H E

32, 34–41].

102 Fermentation Processes

process in the newly investigated scale.

quently limited by mass transfer.

equation:

μmax,<sup>1</sup> (/h) 0.11–0.56 μmax,<sup>2</sup> (g/g/h) 0.21–1.90 KS,<sup>1</sup> (g/L) 0.07–0.57 KS,<sup>2</sup> (g/L) 0.33–60.0

Xmax (g/L) 100.0–330.0

The kinetics of substrate consumption can generally be described by the Herbert-Pirt model, according to which the substrate is consumed for cell growth and maintenance and the production of a specific product [26]:

$$
\mu\_S = \frac{\mu\_X}{Y\_{\chi|S}^\*} + \frac{\mu\_P}{Y\_{P/S}^\*} + m \tag{32}
$$

where Y\* <sup>X</sup>/<sup>S</sup> and Y\* <sup>P</sup>/<sup>S</sup> are, respectively, the stoichiometric coefficients of substrate conversion in cells and product based on the substrate consumed exclusively for each process.

Substrate consumption for cell maintenance refers to the substrate used in the generation of energy for distinct growth functions, such as the maintenance of the concentration gradients between the interior and exterior environment of the cell (osmotic work), synthesis of the cell components that are being continuously degraded, among others [12].

Equation (32) considers that the specific rate of cell maintenance m is a constant, hypothesis, which Ramkrishna et al. [52] do not adopt. According to these authors, the cells suffer a process of degradation in stages in which, at the first stage, the cells would lose their cell viability and, at a second stage, they would die if their maintenance requirements were not attended. To recover the viability, the nonviable cells would need a substrate that would be the same used for growth (exogenous substrate) or an internally stored substrate (endogenous substrate). From these considerations, the following modification in the mathematical representation of the metabolism of maintenance can be introduced, in turn substituting the constant term m in Eq. (32) by a Monod-type expression [26, 53]:

$$\zeta = \frac{\zeta\_{\text{max}} S}{K\_{\text{S},m} + S} \tag{33}$$

Equation (33) shows that, at high concentrations of substrate, there is a predominance of exogenous metabolism with ζmax!m when S>>KS,m, whereas at low concentrations, the endogenous metabolism predominates with ζ!0 when S!0.

Generally, the kinetics of substrate consumption is not described using the Herbert-Pirt model to its full extent. The more common approach is the use of apparent coefficients of substrate conversion in cells (YX/S) and ethanol (YP/S), relating μ<sup>S</sup> to μ<sup>X</sup> or to μ<sup>p</sup> by means of these coefficients (Eqs. (34) and (35)). Another approach to describe μ<sup>S</sup> is that represented by Eq. (36).

$$
\mu\_S = \frac{\mu\_X}{Y\_{X/S}} \tag{34}
$$

$$
\mu\_{\mathcal{S}} = \frac{\mu\_P}{Y\_{P/\mathcal{S}}} \tag{35}
$$

$$
\mu\_S = \frac{\mu\_X}{Y\_{X/S}} + m
\tag{36}
$$

Applications of these approaches can be found in the studies listed in Table 4.

Sinclair and Kristiansen [12] emphasize the importance of not confusing the stoichiometric coefficients with apparent coefficients as is normally reported in the literature. The stoichiometric coefficient is a constant that depends on the chemical equation, relating the substrates and the products (Y\* P/S = 0.511g-ethanol/g-glucose in the fermentation of glucose to ethanol). The apparent coefficient is the ratio of the mass of a product formed by the total mass of a consumed substrate, which could be participating in multiple reactions, forming a variety of products, including new cells. In this sense, the following definitions for the stoichiometric and apparent coefficients are convenient:


Table 4. Mathematical models used for modeling of substrate-consumption kinetics in 1-G ethanol fermentation processes.

$$\bullet \, \mathrm{Y}\_{\mathrm{X}/\mathrm{S}}^{\*} = \frac{\text{Mass of new cells formed}}{\text{Substrate mass consumed only for the formation of new cells}} \tag{37}$$

Equation (33) shows that, at high concentrations of substrate, there is a predominance of exogenous metabolism with ζmax!m when S>>KS,m, whereas at low concentrations, the

Generally, the kinetics of substrate consumption is not described using the Herbert-Pirt model to its full extent. The more common approach is the use of apparent coefficients of substrate conversion in cells (YX/S) and ethanol (YP/S), relating μ<sup>S</sup> to μ<sup>X</sup> or to μ<sup>p</sup> by means of these coefficients (Eqs. (34) and (35)). Another approach to describe μ<sup>S</sup> is that represented by

> <sup>μ</sup><sup>S</sup> <sup>¼</sup> <sup>μ</sup><sup>X</sup> YX=<sup>S</sup>

> <sup>μ</sup><sup>S</sup> <sup>¼</sup> <sup>μ</sup><sup>P</sup> YP=<sup>S</sup>

Sinclair and Kristiansen [12] emphasize the importance of not confusing the stoichiometric coefficients with apparent coefficients as is normally reported in the literature. The stoichiometric coefficient is a constant that depends on the chemical equation, relating the substrates

The apparent coefficient is the ratio of the mass of a product formed by the total mass of a consumed substrate, which could be participating in multiple reactions, forming a variety of products, including new cells. In this sense, the following definitions for the stoichiometric and

Study μ<sup>S</sup> Reference

Ethanol fermentation modeling in a tower bioreactor with flocculating yeasts Eq. (35) [38]

Bifurcation analysis of two continuous membrane fermentor configurations for ethanol production Eq. (36) [55]

Modeling of a fed-batch ethanol fermentation process with flocculating yeasts (S. cerevisiae) Eq. (36) [18]

Table 4. Mathematical models used for modeling of substrate-consumption kinetics in 1-G ethanol fermentation

P/S = 0.511g-ethanol/g-glucose in the fermentation of glucose to ethanol).

<sup>μ</sup><sup>S</sup> <sup>¼</sup> <sup>μ</sup><sup>X</sup> YX=<sup>S</sup>

Applications of these approaches can be found in the studies listed in Table 4.

Optimization of an industrial bioprocess of ethanol fermentation with multiple stages and cell recycle, using techniques of factorial design and response surface analysis in combination with

Analysis of the steady-state stability and modeling of the dynamic behavior of a continuous ethanol

Modeling, simulation, and analysis of an ethanol fermentation process with control structure in

Modeling of a fed-batch ethanol fermentation process with a strain of industrial yeast

fermentation process in a gas-lift tower bioreactor with high cell densities

(34)

(35)

Eq. (34) [54]

Eq. (35) [36]

Eq. (36) [56]

Eq. (36) [48]

þ m (36)

endogenous metabolism predominates with ζ!0 when S!0.

Eq. (36).

104 Fermentation Processes

and the products (Y\*

industrial scale

processes.

(Saccharomyces cerevisiae)

apparent coefficients are convenient:

phenomenological modeling and simulation

$$\bullet \,\mathrm{Y}\_{\mathrm{X}/\mathrm{S}} = \frac{\text{Mass of new cells formed}}{\text{Total mass of substrate consumed}} \tag{38}$$

$$\zeta\_{P/S}^\* = \frac{\text{Mass of product formed}}{\text{Substrate mass consumed only for the formation of product}} \tag{39}$$

$$\bullet \, Y\_{\text{P}/S}^{\*} = \frac{\text{Substrate mass consumed only for the formation of product}}{\text{Substrate mass consumed only for the formation of product}} \tag{39}$$

$$\bullet \, Y\_{\text{P/S}} = \frac{\text{Mass of product formed}}{\text{Total mass of substrate consumed}} \tag{40}$$

Oliveira et al. [57], modeling a continuous ethanol fermentation process in a two-stage tower bioreactor cascade with flocculating yeast recycle, used simplified (μ<sup>S</sup> = μP/YP/S) and generalized (μ<sup>S</sup> ¼ μX=Y� <sup>X</sup>=<sup>S</sup> þ μP=Y� <sup>P</sup>=<sup>S</sup> þ m) kinetic expressions to describe μ<sup>S</sup> and obtained similar predictions of the state variables by both employed approaches.

Bonomi et al. [17], modeling the ethanol production using cassava hydrolyzate in a batch bioreactor, defined the following equation for the mass balance of substrate:

$$\frac{dS}{dt} = -\frac{1}{2} \left( \frac{1}{Y\_{X/S}} \mu\_X X + \frac{1}{Y\_{P/S}} \mu\_P X \right) \tag{41}$$

According to these authors, the definition of the apparent coefficients YX/<sup>S</sup> and YP/<sup>S</sup> guarantee that the terms μXX=YX=<sup>S</sup> and μPX=YP=<sup>S</sup> are equal; this equality was also reported by Aiba et al. [31] and Ghose and Tyagi [28]. Bonomi et al. [17] argue that the two terms are not exactly equal due to the fact that the calculated values of YX/<sup>S</sup> and YP/<sup>S</sup> are affected by different experimental errors and the values of μ<sup>X</sup> and μ<sup>P</sup> are calculated using estimates of other parameters of the model. These authors justify the introduction of the average among the aforementioned terms in Eq. (41), as a means through which to minimize the propagation of errors discussed above.

By contrast, Jin et al. [42], modeling the kinetics of batch fermentation for ethanol production with S. cerevisiae immobilized in calcium alginate gel, presented the following mass balance equation for the substrate, without the introduction of the 1/2 factor in the equation:

$$\frac{dS}{dt} = -\left(\frac{1}{Y\_{X/S}}\mu\_X X + \frac{1}{Y\_{P/S}}\mu\_P X\right) \tag{42}$$

One equation like μ<sup>S</sup> ¼ μX=YX=<sup>S</sup> þ μP=YP=<sup>S</sup> was also employed by Marginean et al. [58] to model, simulate, and develop proportional integral derivative (PID) control strategies for temperature and the pH of an ethanol production process in a continuous stirred tank reactor (CSTR).

A different proposal was presented by Limtong et al. [35] to model a continuous process of ethanol fermentation in a tower bioreactor with recycle of flocculating yeasts. The authors determined linear relations between the product concentration (P (g/L)) and the specific rates of glucose consumption (μS) and ethanol production (μP). The ratios between the corresponding angular and linear coefficients of the straight lines (1.63/3.74 and 0.020/0.046) provide a reasonable estimate of the value of YP/S (=0.43 g/g), which demonstrates the consistency of such relations (Eqs. (43) and (44)).

$$
\mu\_{\rm S} = -0.046P + 3.74(\text{g/g/h})\tag{43}
$$

$$
\mu\_p = -0.020P + 1.63(\text{g/g/h})\tag{44}
$$

Another situation to be analyzed is when there is more than one fermentable sugar present in the medium, as is the case in the production of beer. Ramirez [59], modeling the dynamic of batch beer fermentation, considered the glucose (G), maltose (M), and maltotriose (N) to be the three majority sugars contained in the fermentative medium. The specific consumption rates of these sugars were described by equations that exhibit a kinetic pattern of preferential use of these substrates, that is, the preferred sugar (G) is first used until its complete exhaustion; next, the second sugar (M), of intermediate preference, is consumed; and lastly, the third sugar (N), the least preferred, is consumed. According to Ramirez [59], this pattern of sequential use is modeled by inserting terms of inhibition of the consumption of a less preferential sugar by one or more preferential sugars in such a way that the specific consumption rates of these sugars μ<sup>i</sup> are given by

$$
\mu\_G = \frac{V\_G G}{K\_G + G} \tag{45}
$$

$$
\mu\_M = \frac{V\_M M}{K\_M + M} \left(\frac{K\_G^{'}}{K\_G^{'} + G}\right) \tag{46}
$$

$$
\mu\_N = \frac{V\_N N}{K\_N + N} \left(\frac{K\_G^{'}}{K\_G^{'} + G}\right) \left(\frac{K\_M^{'}}{K\_M^{'} + M}\right) \tag{47}
$$

where Vi is the maximum specific consumption rate of the sugar i (g/g/h), Ki is the saturation constant for the sugar i (g/L), and K' <sup>i</sup> is the constant of inhibition caused by the sugar i (g/L).

Additionally, the specific rates of cell growth (μX) and ethanol production (μE) were given by the following equations [59]:

$$
\mu\_X = R\_{X\!G} \mu\_G + R\_{X\!M} \mu\_M + R\_{X\!N} \mu\_N \tag{48}
$$

$$
\mu\_E = R\_{EG}\mu\_G + R\_{EM}\mu\_M + R\_{EN}\mu\_N \tag{49}
$$

where RXi and REi are, respectively, the stoichiometric yield of the biomass and ethanol per gram of sugar i consumed (g/g).

A similar approach was employed by Lee et al. [60] when they modeled the batch ethanol production by S. cerevisiae from a mixture of glucose and maltose. One term ξ was included in the equation of μ<sup>M</sup> to represent the glucose repression effect upon the maltose consumption. The final set of the mathematical model equations is presented as follows, highlighting the prediction of diauxic growth in the expression of μ<sup>X</sup> and the production of ethanol from the two sugars in the expression of μE.

#### Kinetic Modeling of 1‐G Ethanol Fermentations http://dx.doi.org/10.5772/65460 107

$$\frac{dX}{dt} = \mu\_X X = \left(\frac{\mu\_{G,\text{max}} G}{K\_G + G} + \frac{\mu\_{M,\text{max}} M \xi}{K\_M + M}\right) \eta X \tag{50}$$

$$\frac{dG}{dt} = -\mu\_G X = -\left(\frac{\mu\_{G,\text{max}} G}{Y\_{X/G} (K\_G + G)} \eta\right) X\tag{51}$$

$$\frac{dM}{dt} = -\mu\_M = -\left(\frac{\mu\_{M,\text{max}}M\xi}{Y\_{X/M}(K\_M + M)}\eta\right)X\tag{52}$$

$$\frac{dE}{dt} = \mu\_E X = \left(\frac{Y\_{E/G}\mu\_{G,\text{max}}G}{Y\_{X/G}(K\_G + G)} + \frac{Y\_{E/M}\mu\_{M,\text{max}}M\xi}{Y\_{X/M}(K\_M + M)}\right)\eta X\tag{53}$$

$$
\eta = \left( 1 - \frac{X}{X\_{\text{max}}} \right) \cdot \left( 1 - \frac{E}{E\_{\text{max}}} \right) \tag{54}
$$

$$\xi = \frac{1}{1 + G/k\_i} \tag{55}$$

#### 4. Loss of cell viability

provide a reasonable estimate of the value of YP/S (=0.43 g/g), which demonstrates the consis-

Another situation to be analyzed is when there is more than one fermentable sugar present in the medium, as is the case in the production of beer. Ramirez [59], modeling the dynamic of batch beer fermentation, considered the glucose (G), maltose (M), and maltotriose (N) to be the three majority sugars contained in the fermentative medium. The specific consumption rates of these sugars were described by equations that exhibit a kinetic pattern of preferential use of these substrates, that is, the preferred sugar (G) is first used until its complete exhaustion; next, the second sugar (M), of intermediate preference, is consumed; and lastly, the third sugar (N), the least preferred, is consumed. According to Ramirez [59], this pattern of sequential use is modeled by inserting terms of inhibition of the consumption of a less preferential sugar by one or more preferential sugars in

<sup>μ</sup><sup>G</sup> <sup>¼</sup> VGG

K0 G K0 <sup>G</sup> þ G

where Vi is the maximum specific consumption rate of the sugar i (g/g/h), Ki is the saturation

Additionally, the specific rates of cell growth (μX) and ethanol production (μE) were given by

where RXi and REi are, respectively, the stoichiometric yield of the biomass and ethanol per

A similar approach was employed by Lee et al. [60] when they modeled the batch ethanol production by S. cerevisiae from a mixture of glucose and maltose. One term ξ was included in the equation of μ<sup>M</sup> to represent the glucose repression effect upon the maltose consumption. The final set of the mathematical model equations is presented as follows, highlighting the prediction of diauxic growth in the expression of μ<sup>X</sup> and the production of ethanol from the

!

K0 G K0 <sup>G</sup> þ G

!

K0 M K0 <sup>M</sup> þ M

!

<sup>i</sup> is the constant of inhibition caused by the sugar i (g/L).

μ<sup>X</sup> ¼ RXGμ<sup>G</sup> þ RXMμ<sup>M</sup> þ RXNμ<sup>N</sup> (48)

μ<sup>E</sup> ¼ REGμ<sup>G</sup> þ REMμ<sup>M</sup> þ RENμ<sup>N</sup> (49)

such a way that the specific consumption rates of these sugars μ<sup>i</sup> are given by

<sup>μ</sup><sup>N</sup> <sup>¼</sup> VNN KN þ N

constant for the sugar i (g/L), and K'

the following equations [59]:

gram of sugar i consumed (g/g).

two sugars in the expression of μE.

<sup>μ</sup><sup>M</sup> <sup>¼</sup> VMM KM þ M

μ<sup>S</sup> ¼ −0:046P þ 3:74ðg=g=hÞ (43)

μ<sup>P</sup> ¼ −0:020P þ 1:63ðg=g=hÞ (44)

KG <sup>þ</sup> <sup>G</sup> (45)

(46)

(47)

tency of such relations (Eqs. (43) and (44)).

106 Fermentation Processes

The loss of cell viability during continuous ethanol fermentation processes with high cell density has been observed by many authors; however, few studies consider this phenomenon in the kinetic modeling of the process.

Jarzebski et al. [47] studied a continuous system of ethanol fermentation consisting of a perfect mixture reactor and a filter with a membrane for separation and posterior recycling of the cells for the fermenter. These authors compared the predictions of an intrinsic model, in which the loss of cell viability was considered, with the predictions of a modified nonintrinsic model where this phenomenon was not considered. The authors concluded that the predictions provided by the two models were similar, and for proposals of simulation and additional analyses of the process, both models could be used. The intrinsic model was thus called because the substrate and ethanol concentrations in this model are defined as regards a corrected volume that neglects the volume occupied by the cells in systems with high cell densities. Monbouquette [61] presented a detailed mathematical development for the formulation of mass balance equations in terms of these intrinsic concentrations.

Lafforgue-Delorme et al. [62] studying a system similar to that of Jarzebski et al. [47] pointed out the need to consider other factors other than the dilution rate and concentration of yeasts that would be important for the modeling of processes with high cell densities, as is the case of continuous ethanol fermentations with cell recycling. These authors developed a model considering the following aspects: dilution and yeast purge, broth viscosity, filter plugging, limitation by substrate, physiological state of the yeasts (cell viability), and inhibition phenomena linked both to ethanol and biomass. They also introduced the concept of steric "stress," according to which, at high cell densities, there would be a reduction in the specific growth rate due to the lack of space for cell division. The effects of inhibition, owing to high cell concentrations and steric stress, were described, respectively, by the terms KX/(KX + XV) and (1−X/Xm), where KX is an empirical constant, Xv is the viable cell concentration, and X is the total concentration of cells (viable + nonviable). The final expressions of μ<sup>X</sup> and μ<sup>P</sup> in the proposed model are given by Eqs. (56) and (57). The predictions of the model agreed satisfactorily with the experimental data both for the operation of the bioreactor with total recycle as well as for the operation with partial recycle.

$$
\mu\_X = \left(\frac{\mu\_{\text{max}}S}{K\_S + S}\right) \cdot \left(1 - \frac{P}{P\_m}\right) \left(\frac{K\_X}{K\_X + X\_V}\right) \left(1 - \frac{X}{X\_m}\right) \tag{56}
$$

$$
\mu\_P = \mu\_{P^m} \exp\left(-\frac{K\_P X\_V}{D}\right) \tag{57}
$$

Augusto [63], investigating the influence of the specific rate of oxygen consumption in a continuous ethanol fermentation with high cell density, established the range of 0.1–0.8 mmol O2/(g-cell h) as being that which the oxygen participates in the metabolism as a micronutrient that is essential to the synthesis of the cell membrane compounds, which would in turn increase the tolerance of the membrane to ethanol and to other inhibitors produced in the fermentation. The greatest tolerance resulted in a lower specific rate of cell death and in a greater efficiency of substrate conversion in ethanol due to the reduction in the value of the maintenance coefficient by the activation of the oxidative catabolic pathway. According to this author, this range of oxygen consumption for which the positive effects of this nutrient are observed in the bioconversion of the substrate would be dependent on the microorganism used, on the fermentation medium, and on the mode in which the process is conducted (batch, fed-batch, and continuous). To calculate the many parameters of fermentation, Augusto [63] segregated the microbial population into viable and nonviable cells, this procedure being possible due to the availability of experimental measures of the concentration of each type of cell separately.

Hojo et al. [41], studying the ethanol production with a strain of flocculating yeast in CSTR with and without cell recycle, concluded that the cell viability was of utmost importance in developing the mathematical model of the process with cell recycle and that cell death is a phenomenon that should be considered in the kinetic modeling of prolonged continuous fermentations in cases in which the hydraulic residence time is high. The kinetic expressions for the specific rates of cell growth (μX), substrate consumption (μS), ethanol production (μP), and cell death (μd) were represented by

$$
\mu\_X = \left(\frac{\mu\_{\text{max}}S}{K\_S + S}\right) \cdot \left(1 - \frac{P}{P^\*}\right)^n; \mu\_{\text{max}} = 0.6/\text{h}^{-1}, \ K\_S = 0.57 \text{ g/L}, \ P^\* = 80 \text{ g/L}, \ n = 1.8 \tag{58}
$$

$$
\mu\_{\mathcal{S}} = \frac{\mu\_{\mathcal{X}}}{Y\_{\mathcal{S}}} ; Y\_{\mathcal{S}} = 0.014 \,\text{g/g} \tag{59}
$$

$$
\mu\_P = A + B\mu\_S; A = 0.065 \text{ g/g/h}; B = 2.24 \text{ g/g} \tag{60}
$$

$$
\mu\_d = k\_d; k\_d = 0.0054 \text{ h}^{-1} \tag{61}
$$

In the aforementioned works, it was considered that the microbial population consisted solely of viable and nonviable cells, with the latter being incapable of growing and producing the desired product. Although inactive in both processes, it was assumed that the nonviable cells remained intact, which means that cell lysis phenomenon was not considered.

concentrations and steric stress, were described, respectively, by the terms KX/(KX + XV) and (1−X/Xm), where KX is an empirical constant, Xv is the viable cell concentration, and X is the total concentration of cells (viable + nonviable). The final expressions of μ<sup>X</sup> and μ<sup>P</sup> in the proposed model are given by Eqs. (56) and (57). The predictions of the model agreed satisfactorily with the experimental data both for the operation of the bioreactor with total recycle as

> <sup>1</sup><sup>−</sup> <sup>P</sup> Pm KX

μ<sup>P</sup> ¼ μPm exp −

of experimental measures of the concentration of each type of cell separately.

; <sup>μ</sup>max <sup>¼</sup> <sup>0</sup>:6=h<sup>−</sup><sup>1</sup>

<sup>μ</sup><sup>S</sup> <sup>¼</sup> <sup>μ</sup><sup>X</sup> Yg

Augusto [63], investigating the influence of the specific rate of oxygen consumption in a continuous ethanol fermentation with high cell density, established the range of 0.1–0.8 mmol O2/(g-cell h) as being that which the oxygen participates in the metabolism as a micronutrient that is essential to the synthesis of the cell membrane compounds, which would in turn increase the tolerance of the membrane to ethanol and to other inhibitors produced in the fermentation. The greatest tolerance resulted in a lower specific rate of cell death and in a greater efficiency of substrate conversion in ethanol due to the reduction in the value of the maintenance coefficient by the activation of the oxidative catabolic pathway. According to this author, this range of oxygen consumption for which the positive effects of this nutrient are observed in the bioconversion of the substrate would be dependent on the microorganism used, on the fermentation medium, and on the mode in which the process is conducted (batch, fed-batch, and continuous). To calculate the many parameters of fermentation, Augusto [63] segregated the microbial population into viable and nonviable cells, this procedure being possible due to the availability

Hojo et al. [41], studying the ethanol production with a strain of flocculating yeast in CSTR with and without cell recycle, concluded that the cell viability was of utmost importance in developing the mathematical model of the process with cell recycle and that cell death is a phenomenon that should be considered in the kinetic modeling of prolonged continuous fermentations in cases in which the hydraulic residence time is high. The kinetic expressions for the specific rates of cell growth (μX), substrate consumption (μS), ethanol production (μP),

In the aforementioned works, it was considered that the microbial population consisted solely of viable and nonviable cells, with the latter being incapable of growing and producing the

KX þ XV 

KPXV D 

<sup>1</sup><sup>−</sup> <sup>X</sup> Xm 

, KS ¼ 0:57 g=L , P� ¼ 80 g=L, n ¼ 1:8 (58)

; Yg ¼ 0:014 g=g (59)

<sup>μ</sup><sup>d</sup> <sup>¼</sup> kd; kd <sup>¼</sup> <sup>0</sup>:0054 h<sup>−</sup><sup>1</sup> (61)

μ<sup>P</sup> ¼ A þ BμS; A ¼ 0:065 g=g=h; B ¼ 2:24 g=g (60)

(56)

(57)

well as for the operation with partial recycle.

108 Fermentation Processes

and cell death (μd) were represented by

<sup>1</sup><sup>−</sup> <sup>P</sup> P� <sup>n</sup>

<sup>μ</sup><sup>X</sup> <sup>¼</sup> <sup>μ</sup>max<sup>S</sup> KS þ S  <sup>μ</sup><sup>X</sup> <sup>¼</sup> <sup>μ</sup>max<sup>S</sup> KS þ S  For Borzani [64], when intending to apply such an approach, the segregation of the microbial population must be performed considering the active and inactive cells in the growth process, as well as the active and inactive cells in the production process. According to Borzani [64], this differentiation is justified by the fact that a cell that is considered to be active in a given process may not be active in another, or vice-versa. Though quite realistic, this approach is rarely applied, given the enormous experimental difficulty to quantify the concentration of each group of cells separately.

Using an approach that is quite similar to that suggested by Borzani [64], Ghommidh et al. [65], modeling the oscillatory behavior of Z. mobilis in continuous cultures for ethanol production, segregated the microbial population in three distinct groups: viable cells that grow and produce ethanol (Xv), nonviable cells that do not grow but produce ethanol (Xnv), and dead cells (Xd). The processes of ethanol production, cell growth, loss of viability, and cell death were represented according to the scheme shown in Figure 3.

Starting from the scheme proposed by Ghommidh et al. [65], Jarzebski [66] modeled the oscillatory behavior of the state variables X, S, and P in a continuous ethanol fermentation process with S. cerevisiae, introducing the concept of combined effect of inhibition by substrate and ethanol simultaneously, since, according to that author, the inhibition by substrate would depend on the ethanol concentration and vice-versa. Taking into account this combined effect of inhibition, Jarzebski [66] proposed the following equations to describe the specific rates of viable cell growth (μv), conversion of viable cells into nonviable cells (μnv), and cell death (μd):

$$
\mu\_v = \left(\frac{\mu\_{\text{max}}S}{K\_1 + S}\right) \cdot \left(1 - \frac{P}{P\_c}\frac{S}{K\_2 + S}\right) \text{ for } P < P\_c(K\_2 + S)/S \tag{62}
$$

$$
\mu\_{nv} = \left(\frac{\mu\_{\text{max}}S}{K\_1 + S}\right) \cdot \left(1 - \frac{P}{P\_c'} \frac{S}{K\_2 + S}\right) \cdot \mu\_v \text{ for } P < P\_c'(K\_2 + S)/S \tag{63}
$$

$$S \xrightarrow{\mu\_p, \left(X\_\mathbf{v} + X\_{\mathbf{m}}\right)} \xrightarrow{} \square$$

$$X\_\mathbf{v} \xrightarrow{\mu\_\mathbf{v}} \square X\_\mathbf{v}$$

$$X\_\mathbf{v} \xrightarrow{\mu\_\mathbf{m}} X\_\mathbf{m}$$

$$X\_\mathbf{v} \xrightarrow{\mu\_d} X\_d$$

$$X\_\mathbf{v} \xrightarrow{\mu\_d} X\_d$$

Figure 3. Schematic representation of the cell processes involved in ethanol production by Zymomonas mobilis in continuous cultures, according to the model proposed by Ghommidh et al. [65].

$$
\mu\_d = -\mu\_v \text{ for } P < P\_c^{'} (\text{K}\_2 + \text{S}) / \text{S} \tag{64}
$$

Watt et al. [67], using the mathematical model proposed by Jarzebski [66], simulated the continuous ethanol fermentation process for different feed volumetric flow rates and substrate concentrations in the feed stream.

The mathematical modeling of ethanol fermentation processes in which the loss of cell viability occurs is generally conducted by dividing the cell population into two distinct groups: viable cells (Xv) which would be growing and producing ethanol and nonviable or dead cells (Xd), which would be inactive in both processes [68]. The conversion rate from the viable to the nonviable cells is considered to be the first order regarding the concentration of viable cells [12]. The specific rates of cell growth, ethanol production, substrate consumption, and loss of cell viability are defined as regards the viable cell concentration, which refer to the effectively active cells in all of these processes. Mass balance equations for viable and nonviable cells are developed separately. The mass balance equations for ethanol and substrate are similar to those of the conventional model (model that does not incorporate the loss of cell viability) with the previously discussed modifications in the terms involving the specific rates.

Based on these premises, Oliveira et al. [69] developed a mathematical model for a continuous ethanol fermentation process in a tower bioreactor with recycle of flocculating yeasts, in which the loss of cell viability was considered and the predictions of this model were compared with those of the conventional model. Both models provide similar predictions and were equally appropriate for the fermentation process modeling. Later, in another publication, the authors analyzed the scale-up effects on the kinetic parameters and on the predictions of the modified model, and found changes in the values of some of the parameters [70]. In addition, the predictions of the modified model agreed better with the experimental data than did those of the conventional model, especially for the cell concentration variable.

A better description of the fermentation process by the modified model is always the desired result, primarily in those cases in which the levels of cell viability are significantly different than 100%. The cell viability level in ethanol fermentations with high yeast densities has been reported as being strongly dependent on the rate of aeration imposed upon the system [34], varying from 40% to 90% [10, 34, 38, 71]. Under anaerobic conditions, unsaturated fatty acids are not synthesized and the yeasts become more sensitive to ethanol [72]. However, the high levels of cell viability in aerated systems are achieved at the expense of the reduction in ethanol yields [70]. Thus, the rate of aeration is an important variable to be optimized in these systems, seeking to provide an adequate level of oxygen dissolved in the medium [70].

Other aforementioned works in which the segregated approach, regarding cell viability, was applied to describe the microbial population are as follows: Kalil et al. [54], Atala et al. [21], Costa Filho et al. [56], Nelson and Hamzah [53], and Watt et al. [67].

#### 5. Conclusions

μ<sup>d</sup> ¼ −μ<sup>v</sup> for P < P

concentrations in the feed stream.

specific rates.

110 Fermentation Processes

variable.

medium [70].

0

Watt et al. [67], using the mathematical model proposed by Jarzebski [66], simulated the continuous ethanol fermentation process for different feed volumetric flow rates and substrate

The mathematical modeling of ethanol fermentation processes in which the loss of cell viability occurs is generally conducted by dividing the cell population into two distinct groups: viable cells (Xv) which would be growing and producing ethanol and nonviable or dead cells (Xd), which would be inactive in both processes [68]. The conversion rate from the viable to the nonviable cells is considered to be the first order regarding the concentration of viable cells [12]. The specific rates of cell growth, ethanol production, substrate consumption, and loss of cell viability are defined as regards the viable cell concentration, which refer to the effectively active cells in all of these processes. Mass balance equations for viable and nonviable cells are developed separately. The mass balance equations for ethanol and substrate are similar to those of the conventional model (model that does not incorporate the loss of cell viability) with the previously discussed modifications in the terms involving the

Based on these premises, Oliveira et al. [69] developed a mathematical model for a continuous ethanol fermentation process in a tower bioreactor with recycle of flocculating yeasts, in which the loss of cell viability was considered and the predictions of this model were compared with those of the conventional model. Both models provide similar predictions and were equally appropriate for the fermentation process modeling. Later, in another publication, the authors analyzed the scale-up effects on the kinetic parameters and on the predictions of the modified model, and found changes in the values of some of the parameters [70]. In addition, the predictions of the modified model agreed better with the experimental data than did those of the conventional model, especially for the cell concentration

A better description of the fermentation process by the modified model is always the desired result, primarily in those cases in which the levels of cell viability are significantly different than 100%. The cell viability level in ethanol fermentations with high yeast densities has been reported as being strongly dependent on the rate of aeration imposed upon the system [34], varying from 40% to 90% [10, 34, 38, 71]. Under anaerobic conditions, unsaturated fatty acids are not synthesized and the yeasts become more sensitive to ethanol [72]. However, the high levels of cell viability in aerated systems are achieved at the expense of the reduction in ethanol yields [70]. Thus, the rate of aeration is an important variable to be optimized in these systems, seeking to provide an adequate level of oxygen dissolved in the

Other aforementioned works in which the segregated approach, regarding cell viability, was applied to describe the microbial population are as follows: Kalil et al. [54], Atala et al. [21],

Costa Filho et al. [56], Nelson and Hamzah [53], and Watt et al. [67].

<sup>c</sup>ðK<sup>2</sup> þ SÞ=S (64)

The facility to model the kinetics of ethanol fermentation processes is due to the fact that the governing factors of these processes (limitation by substrate, inhibition, loss of cell viability, death, among others) are well known and that they have a large quantity of mathematical models that have already been developed and made available within the literature.

The present work compiles, in a single publication, a reasonable quantity of kinetic models that are potentially applicable to the adjustment of experimental data of ethanol fermentation processes obtained under the broadest and most varied operating conditions. The models can also be applied to the production processes of another generation, such as is the case of obtaining ethanol from lignocellulosic feedstocks (second-generation bioethanol) for which the literature presents the use of such models as being confirmed by the following recent publications:


In general, many fermentation studies have confirmed that the unstructured models poorly describe dynamic experiments in which composition and biomass activity change [13, 15]. By contrast, the use of a more detailed approach of cell metabolism, aimed at better describing the dynamic behavior of the process, can lead to the development of structured models containing a large number of variables and parameters. In these cases, the parameter estimation can become a difficult task due to the large experimental effort required and to the need to apply complex numerical methods, which can lead to obtaining parameter values without physical meaning. To illustrate such a scenario, Rivera et al. [76] used a structured model to interpret experimental data of a tower bioreactor for ethanol production by immobilized S. cerevisiae. The model contains 34 kinetic parameters and 9 parameters related to the glycolytic and respiratory (tricarboxylic acid [TCA]) pathways. Thus, greater experimental and computational efforts would be required to estimate the parameters associated with this mathematical model.

The class of structured models that are potentially useful is formed by simply applying the structured formulation, through which the description of the quantity and of the biomass properties is performed by using two or three variables, resulting in the so-called two- or three-compartment models. These models combine a better description of the system's behavior with a reasonable mathematical complexity and a smaller number of parameters [77].

Therefore, it is important to balance the complexity of the model with its identification and to seek expressions that are as simple as possible and that are capable of accurately describing the process in both dynamic and steady states [69].

#### Author details

Samuel C. Oliveira1 \*, Dile P. Stremel<sup>2</sup> , Eduardo C. Dechechi<sup>3</sup> and Félix M. Pereira<sup>4</sup>

\*Address all correspondence to: samueloliveira@fcfar.unesp.br

1 Department of Bioprocesses and Biotechnology, School of Pharmaceutical Sciences (FCF), São Paulo State University (UNESP), Araraquara-SP, Brazil

2 Department of Engineering and Forestry Technology, Federal University of Paraná (UFPR), Curitiba-PR, Brazil

3 CECE/PTI-Department of Engineering and Sciences at Itaipu Research Park (PTI), Western Paraná State University (UNIOESTE), Foz do Iguaçu-PR, Brazil

4 Department of Chemical Engineering, Engineering School of Lorena (EEL), University of São Paulo (USP), Lorena-SP, Brazil

#### References


[7] Mitchell DA, Von Meien OF, Krieger N, Dalsenter FDH. A review of recent developments in modeling of microbial growth kinetics and intraparticle phenomena in solid-state fermentation. Biochem. Eng. J. 2004; 17: 15–26.

Therefore, it is important to balance the complexity of the model with its identification and to seek expressions that are as simple as possible and that are capable of accurately describing the

1 Department of Bioprocesses and Biotechnology, School of Pharmaceutical Sciences (FCF),

2 Department of Engineering and Forestry Technology, Federal University of Paraná (UFPR),

3 CECE/PTI-Department of Engineering and Sciences at Itaipu Research Park (PTI), Western

4 Department of Chemical Engineering, Engineering School of Lorena (EEL), University of

[1] Zanin GM, Santana CC, Bon EP, Giordano RCL, de Moraes FF, Andrietta SR, de Carvalho Neto CC, Macedo IC, Fo DL, Ramos LP, Fontana JD. Brazilian Bioethanol Program. Appl.

[2] Vasconcelos JN, Lopes CE, França FP. Continuous ethanol production using yeast

[3] Xu TJ, Zhao XQ, Bai FW. Continuous ethanol production using self-flocculating yeast in a

[4] Cardona CA, Sánchez OJ. Fuel ethanol production: Process design trends and integration

[5] Carere CR, Sparling R, Cicek N, Levin DB. Third generation biofuels via direct cellulose

[6] Mussatto SI, Dragone G, Guimarães PMR, Silva JPA, Carneiro LM, Roberto IC, Vicente A, Domingues L, Teixeira JA. Technological trends, global market, and challenges of bio-

immobilized on sugar-cane stalks. Braz. Chem. Eng. J. 2004; 21: 357–365.

fermentation. Int. J. Mol. Sci. 2008; 9: 1342–1360. DOI: 10.3390/ijms9071342

cascade of fermenters. Enzyme Microb. Technol. 2005; 37(6): 634–640.

opportunities. Bioresour. Technol. 2007; 98: 2415–2457.

ethanol production. Biotechnol. Adv. 2010; 28: 817–830.

, Eduardo C. Dechechi<sup>3</sup> and Félix M. Pereira<sup>4</sup>

process in both dynamic and steady states [69].

\*, Dile P. Stremel<sup>2</sup>

\*Address all correspondence to: samueloliveira@fcfar.unesp.br

São Paulo State University (UNESP), Araraquara-SP, Brazil

Paraná State University (UNIOESTE), Foz do Iguaçu-PR, Brazil

Biochem. Biotechnol. 2000; 84–86: 1147–1161.

Author details

112 Fermentation Processes

Samuel C. Oliveira1

Curitiba-PR, Brazil

References

São Paulo (USP), Lorena-SP, Brazil


[37] Luong JHT. Kinetics of ethanol inhibition in alcohol fermentation. Biotechnol. Bioeng. 1985; 27: 280–285.

[22] Tsuji S, Shimizu K, Matsubara M. Performance evaluation of ethanol fermentor systems using a vector-valued objective function. Biotechnol Bioeng. 1987; 30: 420–426.

[23] Sousa ML, Teixeira JA. Reduction of diffusional limitations in yeast flocs. Biotechnol. Lett.

[24] Fontana A, Bore C, Ghommidh C, Guiraud JP Structure and sucrose hydrolysis activity of

[25] Contois DE. Kinetics of bacterial growth: Relationship between population density and specific growth rate of continuous cultures. J. Gen. Microbiol. 1959; 21: 40–50.

[26] Menezes JC, Alves SS, Lemos JM, Azevedo SF. Mathematical modelling of industrial pilot-plant penicillin-G fed-batch fermentations. J. Chem. Tech. Biotechnol. 1994; 61:

[27] Oliveira SC, Paiva TCB, Visconti AES, Giudici R. Discrimination between ethanol inhibition models in a continuous alcoholic fermentation process using flocculating yeast.

[28] Ghose TK, Tyagi RD. Rapid ethanol fermentation of cellulose hydrolysate. II. Product and substrate inhibition and optimization of fermentor design. Biotechnol. Bioeng. 1979; 21:

[29] Bazua CD, Wilke CR. Ethanol effects on the kinetics of a continuous fermentation with

[30] Novak M, Strehaiano P, Moreno M, Goma G. Alcoholic fermentation: On the inhibitory

[31] Aiba S, Shoda M, Nagatani M. Kinetics of product inhibition in alcohol fermentation.

[32] Aiba S, Shoda M. Reassessment of the product inhibition in alcohol fermentation. J.

[33] Pascual C, Alonso A, García I, Romay C, Kotyk A. Effect of ethanol on glucose transport, key glycolytic enzymes, and proton extrusion in Saccharomyces cerevisiae. Biotechnol.

[34] Jones ST, Korus RA, Admassu W, Heimsch RC. Ethanol fermentation in a continuous

[35] Limtong S, Nakata M, Funahashi H, Yoshida T, Seki T, Kumnuanta J, Taguchi H. Continuous ethanol production by a concentrated culture of flocculating yeast. J. Ferment.

[36] Comberbach DM, Ghommidh C, Bu'Lock JD. Steady-state stability and dynamic behavior of continuous ethanol fermentation at high cell densities. Enzyme Microb. Technol.

Saccharomyces cerevisiae. Biotechnol. Bioeng. Symp. 1977; 7: 105–118.

effect of ethanol. Biotechnol. Bioeng. 1981; 23: 201–211.

tower fermentor. Biotechnol. Bioeng. 1984; 26: 742–747.

Biotechnol. Bioeng. 1968; 10: 845–864.

Ferment. Technol. 1969; 47(12): 790–794.

Bioeng. 1988; 32: 374–378.

Technol. 1984; 62(1): 55–62.

1987; 9: 676–684.

Saccharomyces cerevisiae aggregates. Biotechnol. Bioeng. 1992; 40: 475–482.

1991; 13(12): 883–888.

Appl. Biochem. Biotechnol. 1998; 74: 161–172.

123–138.

114 Fermentation Processes

1401–1420.


[66] Jarzebski AB. Modelling of oscillatory behaviour in continuous ethanol fermentation. Biotechnol. Lett. 1992; 14(7): 137–142.

[51] Vicente AA, Dluhý M, Teixeira JA. A new technique for measuring kinetic and mass transfer parameters in flocs of Saccharomyces cerevisiae. Biotechnol. Tech. 1997; 11(2): 113–116. [52] Ramkrishna D, Fredrickson AG, Tsuchiya HM. Dynamics of microbial propagation models considering endogenous metabolism. J. Gen. Appl. Microbiol. 1966; 12(4): 311–327.

[53] Nelson MI, Hamzah N. Performance evaluation of bioethanol production trough continuous fermentation with a settling unit. J Energ Power Eng. 2013; 7: 2083–2088.

[54] Kalil SJ, Maugeri F, Rodrigues MI. Response surface analysis and simulation as a tool for

[55] Garhyan P, Elnashaie SSEH. Bifurcation analysis of two continuous membrane fermentor

[56] Costa Filho MVA, Monteiro JB, Magazoni FC, Colle S. Modeling, simulation and analysis of ethanol fermentation process with control structure in industrial scale. In: Proceedings of the 22nd International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS); August 31–September 3 2009; Foz do

[57] Oliveira SC, De Castro HF, Visconti AES, Giudici R. Mathematical modeling of a continuous alcoholic fermentation process in a two-stage tower reactor cascade with flocculat-

[58] Marginean AM, Trifa V, Marginean C. Simulation of fermentation bioreactor control for ethanol production. In: Proceedings of the 11th International Conference on Develop-

[59] Ramirez WF. Computational Methods for Process Simulation. Stoneham: Butterworth

[60] Lee Y-S, Lee WG, Chang YK, Chang HN. Modelling of ethanol production by Saccharomyces cerevisiae from a glucose and maltose mixture. Biotechnol. Lett. 1995; 17(8): 791–

[61] Monbouquette HG. Modeling high-biomass-density cell recycle fermenters. Biotechnol.

[62] Lafforgue-Delorme C, Delorme P, Goma G. Continuous Alcoholic Fermentation with Saccharomyces cerevisiae Recycle by Tangential Filtration: Key points for process model-

[63] Augusto EFP. Continuous alcoholic fermentation with high cell density: Influence of the specific oxygen consumption rate [thesis]. São Paulo: University of São Paulo (USP); 1991.

[64] Borzani W. Cinética de processos fermentativos. Rev. Brasileira Engenharia.1986; 3(2): 1–

[65] Ghommidh C, Vaija J, Bolarinwa S, Navarro JM. Oscillatory behaviour of Zymomonas in continuous cultures: A simple stochastic model. Biotechnol. Lett. 1989; 2(9): 659–664.

ment and Application systems; 17–19 May 2012; Suceava; 2012. pp. 17–20.

bioprocess design and optimization. Process Biochem. 2000; 35: 539–550.

configurations for producing ethanol. Chem. Eng. Sci. 2004; 59: 3235–3268.

ing yeast recycle. Bioprocess Biosyst. Eng. 2015; 38: 469–479.

Iguaçu; 2009.

116 Fermentation Processes

Publishers; 1989.

Bioeng. 1992; 39: 498–503.

ling. Biotechnol. Lett. 1994; 16(7): 741–746.

796.

51.


#### **Microbial Population Optimization for Control and Improvement of Dark Hydrogen Fermentation Microbial Population Optimization for Control and Improvement of Dark Hydrogen Fermentation**

Sompong O‐Thong Sompong O‐Thong

Additional information is available at the end of the chapter Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/64208

#### **Abstract**

Dark hydrogen fermentation (DHF) is a process that can achieve two simultaneous objectives: the production of bioenergy and reduction of pollution. Complex microbio‐ logical communities containing efficient producers of hydrogen usually carry out the process. Ordinarily, control and operation strategies optimized the process by chemical and physical factors that usually provide only short‐term solutions and adverse effects on microbial properties. Microbial population optimization methods are designed to overcome these problems using knowledge on microbiological aspects, especially regarding optimizing microbial community structure and property. Optimizing microbial community structure and property should be an explicit aim for the (i) design and operation of reactors for DHF process, (ii) creating conditions that select for the stable and productive growth of desired microbes, and (iii) preventing or limiting growth of organisms that would be reducing hydrogen yields. Microbial population optimization could be managed by biostimulization by adding nutrient species specific for their community, bioaugmentation by adding dominant species or efficient hydrogen‐producing bacteria into the system, and online process control for maintain‐ ing their community.

**Keywords:** dark fermentation processes, biohydrogen production, sludge population optimization, molecular biological techniques, microbial community structure

#### **1. Introduction**

In recent years, the worldwide awareness of global climate change, urban air pollution, and security of future supply of energy carriers stimulates the study on alternative fuels. Hydrogen is a clean and promising fuel when it is ultimately derived from renewable energy sources. It is also efficient and environmentally friendly, as it has high energy content and water is the sole

© 2017 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2017 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

end product [1, 2]. Today, approximately 95% of commercial hydrogen is generated by steam reforming of natural gas and gasification of coal [3]. As these processes use fossil fuels, they are not environmentally friendly. An alternative way to circumvent the dependence of hydrogen production from fossil fuels is to utilize the potential of hydrogen producing microorganisms to drive hydrogen from widely available biomass. Given these perspectives, biological hydrogen production hashigh potential as an alternative energy source. Dark fermentative hydrogen production from wastewater yields relatively higher hydrogen production rates than other biohydrogen production processes [4], with the benefit that the substrate cost (wastewater) is free. For example, a fermentative hydrogen‐producing process produces hydrogen at a higher rate (0.5–65.0 l H2l ‐1d‐1) compared to a light‐driven process (0.04–4.3 l H2l ‐1d‐1) [5]. In addition, the major advantages are low energy demands, resulting in minimal pollution, operation without light sources, no oxygen limitation problems, and low capital costs for at least small‐scale production facilities (100–1000 m3 H2·h‐1) [5, 6–9]. Both mesophilic and thermophilic continuous dark fermentative hydrogen production have been investigated. Thermophilic operation may be particularly appropriate when meeting legislation for the treatment of feedstock containing pathogens or coupled to a process with associated waste heat. Otherwise, because of the energy input needed, thermophilic operation is less likely to be the technically and economically favored option.

An economically feasible biological approach for hydrogen generation is the conversion of (often negatively valued) organic wastes into hydrogen‐rich gas using fermentative bacteria [2, 10]. Various organic waste materials and wastewater from corn, palm oil, soybean, and meat processing plants have been studied for hydrogen production [11, 12]. As dark‐fermentative hydrogen production processes involve non‐sterile feedstock, mixed microflora derived from natural sources has been commonly used. Theoretically, 4 moles of hydrogen are produced from glucose concomitantly with 2 moles of acetate (Eq. 1,3) with only 2 moles of hydrogen produced when butyrate is the main fermentation product (Eq. 2,4). From the above reactions, it can be concluded that the highest theoretical yield of hydrogen is associated with acetic acid as the fermentation end product. In practice, however, when contents of acetic acid and butyrate in mixture are higher than that of propionate, the yield of hydrogen is higher than in other cases [6, 13]. Typically, 60–70% of the aqueous product during sugar fermentation is butyrate and low hydrogen yields (up to 2.5‐2.9 mol H2/mol glucose) compared to the theoretical yield of 4 mol H2/mol glucose for fermentation with only acetate as liquid end fermentation product [14]. Hydrogen yields can be improved by increasing hydrogen pro‐ duction through reaction (1) and decreasing or preventing reaction (2). This could be accom‐ plished through dark hydrogen fermentation (DHF) with thermophiles or extreme thermophiles, operating at temperatures above 60°C [15, 16].

Mesophilic (35°C)

$$\rm C\_6H\_{12}O\_6 + \rm 2H\_2O \rightarrow 4H\_2 + \rm 2CO\_2 + \rm 2C\_2H\_4O\_2 \rightarrow \rm 4G^\circ = -184.2 \text{ kJ mol}^{-1} \tag{1}$$

Microbial Population Optimization for Control and Improvement of Dark Hydrogen Fermentation http://dx.doi.org/10.5772/64208 121

$$\rm C\_6H\_{12}O\_6 \rightarrow 2H\_2 + 2CO\_2 + C\_4H\_8O\_2 \rightarrow \Lambda G^\odot = -244.2 \text{ kJ mol}^{-1} \tag{2}$$

Thermophilic (60°C)

end product [1, 2]. Today, approximately 95% of commercial hydrogen is generated by steam reforming of natural gas and gasification of coal [3]. As these processes use fossil fuels, they are not environmentally friendly. An alternative way to circumvent the dependence of hydrogen production from fossil fuels is to utilize the potential of hydrogen producing microorganisms to drive hydrogen from widely available biomass. Given these perspectives, biological hydrogen production hashigh potential as an alternative energy source. Dark fermentative hydrogen production from wastewater yields relatively higher hydrogen production rates than other biohydrogen production processes [4], with the benefit that the substrate cost (wastewater) is free. For example, a fermentative hydrogen‐producing process produces hydrogen at a higher

‐1d‐1) compared to a light‐driven process (0.04–4.3 l H2l

the major advantages are low energy demands, resulting in minimal pollution, operation without light sources, no oxygen limitation problems, and low capital costs for at least small‐scale

dark fermentative hydrogen production have been investigated. Thermophilic operation may be particularly appropriate when meeting legislation for the treatment of feedstock containing pathogens or coupled to a process with associated waste heat. Otherwise, because of the energy input needed, thermophilic operation is less likely to be the technically and economically favored

An economically feasible biological approach for hydrogen generation is the conversion of (often negatively valued) organic wastes into hydrogen‐rich gas using fermentative bacteria [2, 10]. Various organic waste materials and wastewater from corn, palm oil, soybean, and meat processing plants have been studied for hydrogen production [11, 12]. As dark‐fermentative hydrogen production processes involve non‐sterile feedstock, mixed microflora derived from natural sources has been commonly used. Theoretically, 4 moles of hydrogen are produced from glucose concomitantly with 2 moles of acetate (Eq. 1,3) with only 2 moles of hydrogen produced when butyrate is the main fermentation product (Eq. 2,4). From the above reactions, it can be concluded that the highest theoretical yield of hydrogen is associated with acetic acid as the fermentation end product. In practice, however, when contents of acetic acid and butyrate in mixture are higher than that of propionate, the yield of hydrogen is higher than in other cases [6, 13]. Typically, 60–70% of the aqueous product during sugar fermentation is butyrate and low hydrogen yields (up to 2.5‐2.9 mol H2/mol glucose) compared to the theoretical yield of 4 mol H2/mol glucose for fermentation with only acetate as liquid end fermentation product [14]. Hydrogen yields can be improved by increasing hydrogen pro‐ duction through reaction (1) and decreasing or preventing reaction (2). This could be accom‐ plished through dark hydrogen fermentation (DHF) with thermophiles or extreme

<sup>1</sup> CH O 6 12 6 2 <sup>2</sup> 2 242 2H O 4H 2CO 2C H O G° 184.2 kJ mol- + ® + + ®D = - (1)

thermophiles, operating at temperatures above 60°C [15, 16].

H2·h‐1) [5, 6–9]. Both mesophilic and thermophilic continuous

‐1d‐1) [5]. In addition,

rate (0.5–65.0 l H2l

120 Fermentation Processes

Mesophilic (35°C)

option.

production facilities (100–1000 m3

$$\text{C}\_6\text{H}\_{12}\text{O}\_6 + 2\text{H}\_2\text{O} \rightarrow 4\text{H}\_2 + 2\text{CO}\_2 + 2\text{C}\_2\text{H}\_4\text{O}\_2 \rightarrow \Lambda\text{G}^\circ = -20.1 \text{ kJ mol}^{-1} \tag{3}$$

$$\rm C\_6H\_{12}O\_6 \rightarrow 2H\_2 + \ 2CO\_2 + C\_4H\_8O\_2 \rightarrow \Delta G^\circ = -84.2 \text{ kJ mol}^{-1} \tag{4}$$

Higher temperatures thermodynamically favor hydrogen production. Besides, elevated temperatures contribute to better pathogenic destruction and limit hydrogen consumption by hydrogen consumers (methanogens, homoacetogens, sulfate reducers). Normally 67% of the original organic matter will remain in solution (chemical oxygen demand (COD) basis) under optimal conditions of the DHF process. For achieving a full gain of chemical energy preserved in biomass, a coupled process is required that involves the recovery of the remaining organic matter and production of methane, electricity, bioplastics, and hydrogen by photofermentation process. Two‐stage processes are already well developed, and they could conceivably be adapted for both hydrogen and methane production [17], and hydrogen and electricity generated from microbial fuel cells [18]. The efficiency of DHF from food waste in anaerobic mesophilic and thermophilic acidogenesis, followed by a two‐phase digestion or photo‐ fermentation, has also been assessed [19]. Overall, many technologies for the improvement of biohydrogen production have been increasingly examined to determine their likely successful industrial implementation and sustainability for the generation of alternative renewable bioenergy.

A large number of microbial species, including strict and facultative anaerobic chemohetero‐ trophs such as Clostridia, Enteric bacteria, *Caldicellulosiruptor* spp., *Thermotoga* spp., and *Thermoanaerobacterium* spp., are efficient producers of hydrogen, while degrading various types of carbohydrates [20]. When using mixed microflora, experimental conditions to suppress methanogenic activity (which consumes hydrogen) and favor hydrogen producing metabolism are necessary. These include inoculum conditioning, optimizing operating conditions such as hydraulic retention time (HRT), pH and substrate concentration, and reducing hydrogen partial pressure [4, 7, 21]**.** Some challenges for optimizing dark hydrogen fermentation processes have been summarized by Hawkes et al*.* [7] and there has been considerable progress in research in the last few years, although an economically and techni‐ cally feasible process is not yet established. In general, control and operation strategies are used to optimize the process by chemical, physical, and biological factors independently that usually provide only short‐term solutions by adversely affecting the microbial properties of the system. The process is usually carried out by complex microbiological communities containing efficient producers of hydrogen. Recently, many studies [19, 22–28] have demon‐ strated molecular evidence related to these various effects. Most of *Clostridium* species have been recognized as desirable bacteria for mesophilic, whereas *Thermoanaerobacterium* species, *C. thermocellum*, *C. cellulose,* and *C. thermoamyloticum* have been recognized as desirable bacteria for thermophilic conditions. Knowledge and information of microbial community structure and function is the key to improvement of hydrogen productivities through microbial population optimization. Microbial population optimization is a solution based on the existing knowledge of the microbial community data to overcome various technical barriers, such as low hydrogen yields, biomass washout, inhibition by hydrogen, non‐stable hydrogen pro‐ duction, and short‐time reactor operation. Microbial population optimization requires an integrated knowledge of the microbiology and the physicochemical characteristics of the process. Knowledge on microbiological aspects includes microbial consortia structure and function, the interactions that occur within, and the microbial key players for hydrogen production and their kinetics. The strategies that can be employed following an analysis of the population structure and function include controlling the growth of undesirable microorgan‐ isms (i.e., methanogens, propionic acid bacteria, and lactic acid bacteria) that consume hydrogen, while enhancing the numbers and stability of the hydrogen‐producing bacteria.

#### **2. The dark hydrogen fermentation process**

#### **2.1. Basic principle for dark hydrogen fermentation**

Fermentative hydrogen production yields theoretically a maximum of 4 moles (498 ml‐H2/g‐1 glucose) of hydrogen from glucose concomitantly with 2 moles of acetate, and 2 moles (249 ml‐H2/g‐1 glucose) of hydrogen are produced from glucose concomitantly with 1 moles of butyrate. A large number of microbial species, including strict and facultative anaerobic chemoheterotrophs, such as *Clostridia*, enteric bacteria, and *Thermoanaerobacterium,* are efficient producers of hydrogen. Fermentation of glucose to hydrogen, pyruvate, and acetyl CoA, which can be converted to acetyl phosphate, subsequently results in the generation of ATP and the excretion of acetate. Pyruvate oxidation to acetyl CoA requires reduction by ferredoxin (Fd). Reduced Fd is oxidized by hydrogenase, which generates oxidized Fd and releases electrons as molecular hydrogen (Eq.5–8). The practical yield is even lower when other metabolic compounds such as propionate, ethanol, and lactate are produced as the fermentation products. These metabolic products bypass the major hydrogen‐producing reaction in carbohydrate fermentation as a consequence of thermodynamic limitations [9].

$$\rm{C}\_6\rm{H}\_{12}\rm{O}\_6 + \rm{2H}\_2\rm{O} \rightarrow 4\rm{H}\_2 + \rightarrow 2\rm{CO}\_2 + \rm{2C}\_2\rm{H}\_4\rm{O}\_2\tag{5}$$

$$\rm C\_6H\_{12}O\_6 \rightarrow 2H\_2 + \rightarrow 2CO\_2 + \rm C\_4H\_8O\_2 \tag{6}$$

$$\text{Pyruvate} + \text{CoA} + 2\text{Fd} \text{(ox)} \rightarrow \text{Acetyl} \cdot \text{CoA} + 2\text{Fd} \text{(red)} + \text{CO}\_2 \tag{7}$$

Microbial Population Optimization for Control and Improvement of Dark Hydrogen Fermentation http://dx.doi.org/10.5772/64208 123

$$2\operatorname{Fd}(\operatorname{red}) \to 2\operatorname{Fd}(\operatorname{ox}) + \operatorname{H}\_2 \tag{8}$$

The proton‐reducing ability of Fdred and NADH is thermodynamically limited by the maxi‐ mum hydrogen partial pressures (PH2) of 0.3 and 6x10‐4 atm (60 Pa), respectively. This confers that as long as the PH2 is still less than 0.3 atm, hydrogen production can continue with transferring electrons from Fdred which contains electrons from oxidative decarboxylation of pyruvate by pyruvate:ferredoxin oxidoreductase (PFOR). Meanwhile, the oxidation of NADH by NADH:Fd oxidoreductase (NFOR) can generate Fdred that subsequently generates addi‐ tional hydrogen when the PH2 is maintained less than 60 Pa. However, the PH2 limited to hydrogen generation via the oxidation of NADH could be increased to 0.1–0.2 atm at a temperature of 70°C [16]. Therefore, increasing cultivation temperature is necessary to overcome thermodynamic limitation, thereby resulting in a decrease of the Gibbs free energy of conversion according to the second law of thermodynamics (ΔG = ΔH‐T ΔS) [29]. Thermo‐ philic microorganisms produce generally higher hydrogen yields compared to mesophiles because they are thermodynamically favorable [30]. High hydrogen yields in the range of 314.0–473.0 ml‐H2/g‐1 sugars have been previously reported using thermophiles such as *C. thermocellum* and *Thermoanaerobacterium thermosaccharolyticum* and extreme thermophiles such as *Thermotoga elfi*, *Caldicellulosiruptor saccharilyticus,* and *Caldanaerobacter subterraneus* [15, 31–34]. In a practical sense, through controlling the fermentative types of microorganisms, it is possible to maximize the amount of hydrogen produced by fermentation.

#### **2.2. Dark hydrogen fermentation by mixed cultures**

*C. thermocellum*, *C. cellulose,* and *C. thermoamyloticum* have been recognized as desirable bacteria for thermophilic conditions. Knowledge and information of microbial community structure and function is the key to improvement of hydrogen productivities through microbial population optimization. Microbial population optimization is a solution based on the existing knowledge of the microbial community data to overcome various technical barriers, such as low hydrogen yields, biomass washout, inhibition by hydrogen, non‐stable hydrogen pro‐ duction, and short‐time reactor operation. Microbial population optimization requires an integrated knowledge of the microbiology and the physicochemical characteristics of the process. Knowledge on microbiological aspects includes microbial consortia structure and function, the interactions that occur within, and the microbial key players for hydrogen production and their kinetics. The strategies that can be employed following an analysis of the population structure and function include controlling the growth of undesirable microorgan‐ isms (i.e., methanogens, propionic acid bacteria, and lactic acid bacteria) that consume hydrogen, while enhancing the numbers and stability of the hydrogen‐producing bacteria.

Fermentative hydrogen production yields theoretically a maximum of 4 moles (498 ml‐H2/g‐1 glucose) of hydrogen from glucose concomitantly with 2 moles of acetate, and 2 moles (249 ml‐H2/g‐1 glucose) of hydrogen are produced from glucose concomitantly with 1 moles of butyrate. A large number of microbial species, including strict and facultative anaerobic chemoheterotrophs, such as *Clostridia*, enteric bacteria, and *Thermoanaerobacterium,* are efficient producers of hydrogen. Fermentation of glucose to hydrogen, pyruvate, and acetyl CoA, which can be converted to acetyl phosphate, subsequently results in the generation of ATP and the excretion of acetate. Pyruvate oxidation to acetyl CoA requires reduction by ferredoxin (Fd). Reduced Fd is oxidized by hydrogenase, which generates oxidized Fd and releases electrons as molecular hydrogen (Eq.5–8). The practical yield is even lower when other metabolic compounds such as propionate, ethanol, and lactate are produced as the fermentation products. These metabolic products bypass the major hydrogen‐producing reaction in

carbohydrate fermentation as a consequence of thermodynamic limitations [9].

CH O 6 12 6 2 <sup>2</sup> 2 242 + ® +® + 2H O 4H 2CO 2C H O (5)

Pyruvate ( ) ( ) 2 ++ ® + + CoA 2Fd ox Acetyl CoA ‐ 2Fd red CO (7)

C H O 2H 6 12 6 2 2 482 ® +® + 2CO CHO (6)

**2. The dark hydrogen fermentation process**

122 Fermentation Processes

**2.1. Basic principle for dark hydrogen fermentation**

Dark fermentation process in combination with environmental biotechnology in terms of organic wastes or residue treatment with industrial biotechnology that aims for hydrogen maximization and mixed culture fermentation could thereby become more attractive com‐ pared to pure culture fermentation, as mixed cultures are applied originally in the waste treatment fields. Compared to pure culture fermentation, mixed culture fermentation does not require sterilization of the media, offers better adaptation capacity due to its high microbial content and the possibility of mixed substrate co‐fermentation, and also allows a continuous fermentation process [35]. Undefined mixed cultures taken from different natural sources need pretreatment or enrichment, by manipulating the operation of the fermentation process and/or by varying the sources of the natural inoculum in order to obtain the required metabolic capacities and the corresponding microbial population for development of the dark fermen‐ tation process [36, 37]. To prepare the inoculum for hydrogen production by fermentation of carbohydrates, the original anaerobic sludge is first pretreated to suppress methanogenic archaea, which consume hydrogen generated and subsequently enrich hydrogen‐producing bacteria in various reactor configurations [38]. Pretreating anaerobic seed sludge under harsh conditions, spore‐forming bacteria involved in anaerobic conversion of carbohydrates to hydrogen could have a better chance to survive compared to the non‐spore‐forming metha‐ nogenic archaea. The spores formed can be activated when the required environmental conditions are provided during subsequent enriching for hydrogen production [39]. Methods, including heat shock, load shock, acid, base, and chemical pretreatments are usually applied to pretreat anaerobic seed sludge for fermentative hydrogen production

#### *2.2.1. Heat shock*

Heat shock has been the most common and effective method for eliminating methanogenic archaea and is achieved by steam heating the seed sludge at 75–121°C with an exposure time between 15 and 120 min, which is relatively easy and inexpensive. The heat shock may also suppress the activity of non‐spore‐forming propionate producers, but could not effec‐ tively deactivate homoacetogens [21, 40]. The existence of homoacetogenic bacteria results in a decrease of hydrogen production because these bacteria further consume hydrogen pro‐ duced from the fermentation process for the production of acetate [41]. In addition, Duang‐ manee et al. [42] have previously observed that an inoculum pretreated by heat shock was not stable for hydrogen production in the continuous reactor, and a repeated heat treatment was needed every month to maintain some stability in hydrogen production.

#### *2.2.2. Load shock*

During load shock using the pulse load technique in batch and organic fermentation, or hydraulic shock in continuous fermentation, volatile fatty acids (VFAs) tend to accumulate in the fermentative reactor in high concentrations, associated with acidic conditions, and they inhibit methanogens [42, 43]. Applying a load shock with a pulse load of about 40–50 g‐sugar/ l, the pretreated anaerobic sludge effectively suppressed methanogenic activity [24, 44]. Furthermore, O‐Thong et al. [24] have described that load shock‐pretreated seed sludge could result in high level of hydrogen production similar to the heat shock‐pretreated seed sludge and that load shock would be technically easier to do and more economical than heat shock for implementation on an industrial scale.

#### *2.2.3. Acid and alkali pretreatment*

The bioactivity of methanogens during the conventional anaerobic process treatment of or‐ ganic wastes occurs in neutral to slightly alkaline environments (pH 6.8–8.0) [38]. Limiting methanogenesis can be achieved by adjusting the acidity of the anaerobic sludge substan‐ tially away from the preferable range to either pH 3–4 or pH 12. The acid or alkali pretreat‐ ment is considered to be technically easier than the heat shock pretreatment for industrial scale implementation [21]; however, the inoculum obtained from an acid or alkali pretreat‐ ment requires a much longer acclimatization time of 10 to 30 days to establish hydrogen production [45].

#### *2.2.4. Methanogen inhibitors*

2‐bromoethanesulfonate acid (BESA), an analog of the coenzyme‐M in methanogens, is a chemical that deactivates methanogens. Using BESA at concentrations of 25–100 mM has been found to effectively inhibit the bioactivity of methanogens; however, treating an anaerobic sludge at these levels would not be cost effective for a commercial scale operation [39].

### **3. Molecular methods for microbial community structure and function studies**

including heat shock, load shock, acid, base, and chemical pretreatments are usually applied

Heat shock has been the most common and effective method for eliminating methanogenic archaea and is achieved by steam heating the seed sludge at 75–121°C with an exposure time between 15 and 120 min, which is relatively easy and inexpensive. The heat shock may also suppress the activity of non‐spore‐forming propionate producers, but could not effec‐ tively deactivate homoacetogens [21, 40]. The existence of homoacetogenic bacteria results in a decrease of hydrogen production because these bacteria further consume hydrogen pro‐ duced from the fermentation process for the production of acetate [41]. In addition, Duang‐ manee et al. [42] have previously observed that an inoculum pretreated by heat shock was not stable for hydrogen production in the continuous reactor, and a repeated heat treatment

During load shock using the pulse load technique in batch and organic fermentation, or hydraulic shock in continuous fermentation, volatile fatty acids (VFAs) tend to accumulate in the fermentative reactor in high concentrations, associated with acidic conditions, and they inhibit methanogens [42, 43]. Applying a load shock with a pulse load of about 40–50 g‐sugar/ l, the pretreated anaerobic sludge effectively suppressed methanogenic activity [24, 44]. Furthermore, O‐Thong et al. [24] have described that load shock‐pretreated seed sludge could result in high level of hydrogen production similar to the heat shock‐pretreated seed sludge and that load shock would be technically easier to do and more economical than heat shock

The bioactivity of methanogens during the conventional anaerobic process treatment of or‐ ganic wastes occurs in neutral to slightly alkaline environments (pH 6.8–8.0) [38]. Limiting methanogenesis can be achieved by adjusting the acidity of the anaerobic sludge substan‐ tially away from the preferable range to either pH 3–4 or pH 12. The acid or alkali pretreat‐ ment is considered to be technically easier than the heat shock pretreatment for industrial scale implementation [21]; however, the inoculum obtained from an acid or alkali pretreat‐ ment requires a much longer acclimatization time of 10 to 30 days to establish hydrogen

2‐bromoethanesulfonate acid (BESA), an analog of the coenzyme‐M in methanogens, is a chemical that deactivates methanogens. Using BESA at concentrations of 25–100 mM has been found to effectively inhibit the bioactivity of methanogens; however, treating an anaerobic sludge at these levels would not be cost effective for a commercial scale operation [39].

to pretreat anaerobic seed sludge for fermentative hydrogen production

was needed every month to maintain some stability in hydrogen production.

*2.2.1. Heat shock*

124 Fermentation Processes

*2.2.2. Load shock*

production [45].

*2.2.4. Methanogen inhibitors*

for implementation on an industrial scale.

*2.2.3. Acid and alkali pretreatment*

Molecular monitoring techniques such as fluorescence in situ hybridization (FISH) [46], a combination of FISH and microautoradiography (FISH–MAR) [47], stable isotope probing (SIP) [48], denaturing gradient gel electrophoresis (DGGE) [49], ribosomal intergenic spacer analysis (RISA) [23], and clone libraries have been developed for studying microbial com‐ munity and function. These methods are used intensively in natural and engineered systems for wastewater treatment. Principles of and deeper insights on these molecular tools are available elsewhere (e.g. [50]). Among these techniques, cloning and the creation of a gene library, DGGE, TRFLP, RISA, and FISH stand out. DGGE was one of the first techniques used to describe DHF microflora [51, 52]. DGGE is a rapid and simple method that provides characteristic band patterns for different samples, allowing quick sample profiling, while retaining the possibility of a more thorough genetic analysis by sequencing of particular bands. DGGE provides information about the structure of microbial communities and can relatively quantify species abundance through DNA band intensities. Cloning provides very precise taxonomical information, but is time consuming and requires specialized personnel and hence, its introduction in the DHF process has been slow. FISH helps identify microorganisms at any desired taxonomical level, depending on the specificity of the probe used. It is the only quantitative molecular biology technique, although quantification is either complex or tedious and subjective. Combination with a confocal laser scanning microscope allows the visualiza‐ tion of three‐dimensional microbial structures (granules and biofilms). Both DGGE and FISH have been extensively employed. Other techniques such as RISA [23] provide information on microbial diversity and species dominance. The advantages and disadvantages of the molec‐ ular techniques frequently applied to microbial ecology research in DHF process are shown in **Table 1**.



**Table 1.** Brief description of frequently molecular methods that have been used for microbial community analysis in dark fermentative hydrogen production.

For decades, a biological reactor has been considered as a black box. The new insights in microbiology have helped to improve the design and performance of new generation reactors [53, 54]. Probably it is true that it is not essential to know the phylogenetic position of the individual microorganisms that dwell inside a system for the design of a biohydrogen facility. But the knowledge on microbial community structure and function is needed. The more recent reports on microbial community structures of DHF processes still interpret the results with reactor performance and metabolic by‐products (indirect function) [55, 56]. However, we are still uncertain regarding which microorganisms can function effectively in DHF and whether the whole community takes part. Thus, deeper insight into the function is required, not just community structure. The latter is due to a general shortcoming in all these molecular tools. However, some attempts have been made in this direction, as FISH–MAR and FISH combined with biosensors could be applied to reveal the microbial community structure and function in parallel. Furthermore, other techniques such as DNA microarrays are being developed with the goal of being able to infer the in situ physiology of the microorganisms [57], and these should find application in the hydrogen‐producing biosystems.

**Molecular methods** 

126 Fermentation Processes

electrophoresis (DGGE)

Cloning and sequencing **Nucleic acid extraction**  **PCR Advantages Disadvantages** 

‐ The number of detected bands is usually small, which implies: the number of identified species is also small; the bands correspond, although not necessarily, to the predominant

‐ The sequences of the bands obtained from a gel correspond to short DNA fragments (200– 600 bp), and so phylogenetic relations are less reliably established than with cloning of the whole 16S rRNA gene. In addition, short sequences are less useful for designing new

species in the original sample

specific primers and probes.

for positive diversity

other and libraries

target site accessibility

and the original mixture

‐ GC content of the amplified DNA can modulate the *Tag* polymerase activity

‐ A large number of clones must be sequenced

‐ Sequences need to be compared with each

‐ Very time consuming and laborious, making it unpractical for high sample throughput ‐ It is not quantitative. The PCR step can favor certain species due to differences in DNA

‐ Bias from PCR, total universal primers cannot be totally universal bacteria ‐ Exponential amplification of the DNA mixture may result in ratio discrepancies between the amplified 16S rDNA fragments

temporal variability of microbial populations if just band patterns are considered ‐ It is relatively easy to obtain an overview of the dominant species of an ecosystem ‐ It is adequate for analysis of a large number of samples (far more than cloning)

Yes Yes ‐ Contain larger sequence

‐ Complete 16S rRNA

‐ Identification of

been yet cultured or identified

methods

dark fermentative hydrogen production.

sequencing allows: very precise taxonomic studies and phylogenetic trees

of high resolution to be obtained

microorganisms that have not

‐ Covers most microorganisms, including minority groups, which would be hard to detect with genetic fingerprinting

**Table 1.** Brief description of frequently molecular methods that have been used for microbial community analysis in

For decades, a biological reactor has been considered as a black box. The new insights in microbiology have helped to improve the design and performance of new generation reactors [53, 54]. Probably it is true that it is not essential to know the phylogenetic position of the individual microorganisms that dwell inside a system for the design of a biohydrogen facility. But the knowledge on microbial community structure and function is needed. The more recent reports on microbial community structures of DHF processes still interpret the results with reactor performance and metabolic by‐products (indirect function) [55, 56]. However, we are

Post‐genomic research and systems biology tools such as metaproteomics will greatly con‐ tribute to the development by providing functional performance insights of the microorgan‐ isms and their metabolism [55]. Recent work on post‐genomics involving microbial ecosystems has expanded to both natural microbial biofilms and activated sludge [56, 58]. These cutting‐ edge technologies are aimed at using new molecular tools to understand the microbial community structures in relation to functions [55] or metabolic transformations [58]. It is commonly known that 16S rRNA genes approaches have copy numbers and PCR bias problems. Housekeeping genes with a single copy are now the focus for population genomic analysis. Multilocus sequence typing (MLST) of housekeeping genes could provide a deeper insight on how microbial populations evolved [59]. These modern molecular monitoring techniques are vital tools and could also be applied for DHF, as they will particularly break new ground for the quantification and dynamics of microorganisms in complex consortia.

A whole variety of analytical methods for both microbial community structure and function are now available. However, microbiologists and engineers should take efforts to apply these tools for quantitative studies of DHF. With a more thorough understanding of the microbial community and its dynamics, an improvement of expectations and optimization of fermen‐ tative processes will be possible. The microbial community structure and microbial function may be further optimized by adding species and specific nutrients for the dominant species.

#### **4. Molecular evidence in dark hydrogen fermentation processes**

#### **4.1. Effect of inoculum types and conditioning on microbial community structure**

It has been previously reported that the methods for seed preparation can affect both start up and overall efficiency of the hydrogen‐producing reactors [7]. Quick recovery from process upsets in full‐scale applications may also require large quantities of readily available hydro‐ gen‐producing seeds. Therefore, induction of hydrogen accumulation in fermentative consor‐ tia is related to the inhibition of hydrogen consumers which is essential for its further scale‐ up and industrial applications. Several types of inocula have been used for anaerobic hydrogen fermentation, such as anaerobic‐digested sludge [60], sewage treatment sludge [61], agricul‐ tural soil [62], sludge compost [63], and isolated bacteria [64]. In addition, several methods are used for conditioning inocula such as acid conditioning [65], heat conditioning [60, 62], chemicals conditioning such as 2‐bromoethanesulfonic acid (BESA) [66], short hydraulic retention time (HRT) without conditioning [67], and overload conditioning [24]. All condi‐ tioning methods aid in inhibiting methane formation, as well as accelerating the enrichment of hydrogen producing bacteria, such as spore‐forming *Clostridium* species, as these are highly tolerant to extreme environments [68]. The effect of conditioning on hydrogen production rates is inoculum dependent, with appreciable hydrogen production yields being demonstrated with anaerobic‐digested sludge and agricultural soil [69]. Several studies (e.g. [23, 51, 70–73] reveal that heat‐conditioned anaerobic‐digested sludge guarantees the highest hydrogen production yields. Heat shock treatment of sludge gave highest hydrogen yield (2 mol H2/mol glucose), while base treatment of sludge gave lowest hydrogen yield (0.48 mol H2/mol glucose) [74]. Sung et al. [71] illustrated that hydrogen production using heat‐treated seeds declined after 1‐month operation and repeated heat treatment of sludge to recover from reactor every month is not credible. However, others claim that high yields can be achieved without heat treatment [68]. Zhu and Beland [75] have demonstrated that heat shock and acid treatment methods completely repressed methanogenic activity, while base treatment methods did not completely repress methanogenic activity and also significantly affected hydrogen production. Hwang et al. [76] reported that the acidic conditions (pH 4.5–6) can act as a weak inhibitor, but not complete long‐term inhibition of methanogenic activity. Elsewhere, it has been shown that acid pretreatment is particularly effective for enhancing the growth of lactic acid bacteria (LAB) [52, 77]. Five methods for preparation of hydrogen‐producing seeds (base, acid, 2‐ bromoethanesulfonic acid (BESA), and load shock and heat shock treatments) as well as an untreated anaerobic digested sludge were evaluated for their hydrogen production perform‐ ance and responsible microbial community structures under thermophilic conditions (60°C) by O‐Thong et al. [24]. The results showed that the load shock treatment method was the best for enriching thermophilic hydrogen‐producing seeds from mixed anaerobic cultures as it completely repressed methanogenic activity and gave a maximum hydrogen production yield of 1.96 mol H2 mol‐1 hexose with a hydrogen production rate of 11.2 mmol H2 l‐1 h‐1.

In general, microbial profiles in fermentative production processes occur as a result of a combination of process conditions, such as feedstock characteristics, environmental conditions (pH, temperature, and H2 partial pressure), and metabolic pathways existing in the microbes involved [51]. Iyer et al. [51] investigated hydrogen‐producing bacterial communities from a heat‐treated soil inoculum by RISA. They found that species of Clostridiaceae, Bacillaceae, and Enterobacteriaceae responded to hydrogen production at 30°C and a 30‐h HRT. The gene pool at 30‐h HRT, as determined by 16S rRNA gene sequences, was more diverse than at the 10‐h HRT, as only Clostridiaceae were detected at this later point. The application of DGGE indicated *Clostridium tyrobutyricum*, *Lactobacillus ferintoshensis*, *Lactobacillus paracasei*, and *Coprothermobacter* species to be dominant in bacterial communities developed from pH‐ pretreated inocula [68]. *Lactobacillus* species are common coexisting bacteria in hydrogen fermentation processes. However, they have adverse effects on hydrogen production by competing for sugars and producing acidic products [78, 79]. Interference by lactic acid bacteria is often prevented by feedstock heat treatment at 50°C or by thermophilic fermentation at temperatures beyond 50°C [80]. Load shock and heat shock treatments under thermophilic conditions resulted in a dominance of *T. thermosaccharolyticum* while base‐ and acid‐treated seeds were dominated by *Clostridium* and BESA‐treated seeds were dominated by *Bacillus* sp. [24]. The comparative experimental results from hydrogen production performance and microbial community analysis showed that the load shock treatment method was better than base‐ and acid‐treated, heat shock, BESA‐treated methods for enriching thermophilic hydro‐ gen‐producing seeds from anaerobic‐digested sludge. Load shock‐treated sludge was imple‐ mented in palm oil mill effluent (POME) fermentation and was found to give maximum hydrogen production rates of 13.34 mmol H2 l‐1h‐1 and resulted in a dominance of *Thermoa‐ naerobacterium* spp. Load shock treatment is an easy and practical method for enriching thermophilic hydrogen‐producing bacteria from anaerobic‐digested sludge. The efficiency of preparation methods could be considered based on hydrogen production yield together with microorganisms revealed in the process. Therefore, the microbiological aspects and hydrogen production performance information are needed to identify effective methods for preparation of hydrogen‐producing seeds.

#### **4.2. Effect of reactor design and operation on microbial community structure**

tioning methods aid in inhibiting methane formation, as well as accelerating the enrichment of hydrogen producing bacteria, such as spore‐forming *Clostridium* species, as these are highly tolerant to extreme environments [68]. The effect of conditioning on hydrogen production rates is inoculum dependent, with appreciable hydrogen production yields being demonstrated with anaerobic‐digested sludge and agricultural soil [69]. Several studies (e.g. [23, 51, 70–73] reveal that heat‐conditioned anaerobic‐digested sludge guarantees the highest hydrogen production yields. Heat shock treatment of sludge gave highest hydrogen yield (2 mol H2/mol glucose), while base treatment of sludge gave lowest hydrogen yield (0.48 mol H2/mol glucose) [74]. Sung et al. [71] illustrated that hydrogen production using heat‐treated seeds declined after 1‐month operation and repeated heat treatment of sludge to recover from reactor every month is not credible. However, others claim that high yields can be achieved without heat treatment [68]. Zhu and Beland [75] have demonstrated that heat shock and acid treatment methods completely repressed methanogenic activity, while base treatment methods did not completely repress methanogenic activity and also significantly affected hydrogen production. Hwang et al. [76] reported that the acidic conditions (pH 4.5–6) can act as a weak inhibitor, but not complete long‐term inhibition of methanogenic activity. Elsewhere, it has been shown that acid pretreatment is particularly effective for enhancing the growth of lactic acid bacteria (LAB) [52, 77]. Five methods for preparation of hydrogen‐producing seeds (base, acid, 2‐ bromoethanesulfonic acid (BESA), and load shock and heat shock treatments) as well as an untreated anaerobic digested sludge were evaluated for their hydrogen production perform‐ ance and responsible microbial community structures under thermophilic conditions (60°C) by O‐Thong et al. [24]. The results showed that the load shock treatment method was the best for enriching thermophilic hydrogen‐producing seeds from mixed anaerobic cultures as it completely repressed methanogenic activity and gave a maximum hydrogen production yield

128 Fermentation Processes

of 1.96 mol H2 mol‐1 hexose with a hydrogen production rate of 11.2 mmol H2 l‐1 h‐1.

In general, microbial profiles in fermentative production processes occur as a result of a combination of process conditions, such as feedstock characteristics, environmental conditions (pH, temperature, and H2 partial pressure), and metabolic pathways existing in the microbes involved [51]. Iyer et al. [51] investigated hydrogen‐producing bacterial communities from a heat‐treated soil inoculum by RISA. They found that species of Clostridiaceae, Bacillaceae, and Enterobacteriaceae responded to hydrogen production at 30°C and a 30‐h HRT. The gene pool at 30‐h HRT, as determined by 16S rRNA gene sequences, was more diverse than at the 10‐h HRT, as only Clostridiaceae were detected at this later point. The application of DGGE indicated *Clostridium tyrobutyricum*, *Lactobacillus ferintoshensis*, *Lactobacillus paracasei*, and *Coprothermobacter* species to be dominant in bacterial communities developed from pH‐ pretreated inocula [68]. *Lactobacillus* species are common coexisting bacteria in hydrogen fermentation processes. However, they have adverse effects on hydrogen production by competing for sugars and producing acidic products [78, 79]. Interference by lactic acid bacteria is often prevented by feedstock heat treatment at 50°C or by thermophilic fermentation at temperatures beyond 50°C [80]. Load shock and heat shock treatments under thermophilic conditions resulted in a dominance of *T. thermosaccharolyticum* while base‐ and acid‐treated seeds were dominated by *Clostridium* and BESA‐treated seeds were dominated by *Bacillus* sp. [24]. The comparative experimental results from hydrogen production performance and Various reactor types seeded with the same inoculum and operating under similar process conditions could develop microbial communities with different properties. For instance, in batch mode under mesophilic conditions with glucose as a substrate, microbial communities became dominated by *Clostridium butyricum*‐like species [51], *Clostridium* spp*.* [52] *C. butyricum* [81], and *Clostridium sp*\_T5zd [77]. Conversely, a continuous stirred tank reactor (CSTR) was dominated by *Clostridium sporogenes*‐like and *Clostridium celerecrescens*‐like species [82]. Yet, in an anaerobic membrane reactor (MBR), the main population consisted of Clostridiaceae, Flexibacteraceae, *Clostridium acidisoli, Linmingia china,* and *Cytophaga* [23]. *Clostridium* spp. were also dominant in a CSTR used to produce hydrogen from sucrose at 35°C, pH 5.5, and HRT 12 h, as analyzed by DGGE [51, 71]. Xing et al. [83] followed communities in a CSTR operating on molasses at a low pH with acidophilic bacteria from sewage, which established an ethanol–acetate hydrogen‐producing community after 28 days. This was also consistent with other studies, i.e., the hydrogen production rate increased with the increase of *Ethanolo‐ genbacterium* sp., *Clostridium* sp., and *Spirochaetes*. Some types of *Clostridium* sp., *Acidovorax* sp., *Kluyvera* sp., and *Bacteriodes* were found throughout all periods of reactor operation [83]. It appeared that hydrogen production depended not only on hydrogen producers but also on cometabolism in the whole community.

In common with many other systems, in batch fermentations without pH control, it has been found that microbial communities change with pH [77], and their biodiversity decreased considerably as the pH decreased from 6.5 to 4.5. Kim et al. [81] reported the effect of substrate concentration on dark hydrogen fermentation using a CSTR. At the peak of hydrogen production yields, all bacterial species detected by DGGE analysis were *Clostridium* spp. and at inlet sucrose concentrations below 20 gCOD l‐1, the hydrogen yield per hexose consumed decreased, while *Clostridium scatologenes* (an H2‐consuming acetogen) was found in the sludge. Moreover, it has been shown that short HRT operation without anaerobic sludge preparation allowed for more microbial diversity and increasing the system robustness [22]. Species that differ in optimal growth conditions but are metabolically similar are then present, sharing the same function. Such advantages allow for flexibility in performance when perturbations in process conditions occur. Overall, under mesophilic conditions, hydrogen may be produced by a large group of bacteria such as the three main groups belonging to the low‐GC(guanine‐ cytosine)gram positive bacteria, i.e., Clostridaceae, Enterobacteriacea, and Bacillaceae. A number of studies have focused on the analysis of the 16S rRNA gene to understand the species richness of microbial communities in lab‐scale reactors under mesophilic conditions, as shown in **Table 2**.


**Table 2.** Microbial community structure, operational conditions and reactor performance of fermentative hydrogen production process from various organic wastes under mesophilic condition.

Different microbial community structures develop within different temperature regimes. For instance, a comparative study on hydrogen production from food waste between mesophilic and thermophilic acidogenic conditions revealed that biogas produced in thermophilic conditions was methane free, whereas methane was still detected under mesophilic condi‐ tions [19]. Species such as *Thermoanaerobacterium thermosaccharolytium* and *Desulfotomaculum geothermicum* were detected in the thermophilic acidogenic culture, while *Clostridium* and *Bacillus* species were detected in the mesophilic acidogenic culture with DGGE. The compo‐ sition of microbial communities in thermophilic dark hydrogen fermentation production was investigated in more detail using quantitative FISH and DGGE [8, 22, 86]. This demonstrated that *Thermoanaerobacterium* made up almost half of the total community in thermophilic dark hydrogen fermentation production.

by a large group of bacteria such as the three main groups belonging to the low‐GC(guanine‐ cytosine)gram positive bacteria, i.e., Clostridaceae, Enterobacteriacea, and Bacillaceae. A number of studies have focused on the analysis of the 16S rRNA gene to understand the species richness of microbial communities in lab‐scale reactors under mesophilic conditions, as

**microorganisms**

Clostridiaceae Enterobacteriaceae *Streptococcus bovis*

Clostridiaceae Flexibacteracae *Clostridium acidisoli Linmingia china Cytophaga*

*Bacillus* spp. *Prevotella species*

*Bacillus* sp.

*Clostridium tyrobutyricum*

*Clostridium sporogenes Clostridium celerecrescens*

Bacillaceae Clostridiaceae Enterobacteriaceae Only Clostridiaceae at HRT 10 h

*Clostridium ptoteolyticum Clostridium acidisoli*

Sucrose CSTR, HRT 12 h, pH 6.8 and 35°C *Clostridium ramosum* 0.9–3.5 9.1 [85]

**Table 2.** Microbial community structure, operational conditions and reactor performance of fermentative hydrogen

*Rhodobacter capsulatus*

*Clostridia*

**H2 yield (mol H2 mol-1 hexose)**

2.1 and 2.5

*Clostridium* sp. 44a‐T5zd 2.5 2.1 [77]

*Clostridium butyricum* 1.11 5.2 [83]

**H2 rates (l H2 l-1d-1)**

0.47 4.6 [52]

4.5 and 0.3

1.1 15.36 [23]

0.03–0.1 0.22 [19]

2.3 0.1 [71]

1.61 10.4 [51]

1.68 6.45 [81]

0.6 6.8 [82]

**References**

[84]

shown in **Table 2**.

130 Fermentation Processes

Carbohydrate‐ containing wastewater

**Substrate Processes and operation condition Dominating**

Two‐step process using CSTR, pH

3.3 h, pH 5.5, mixed at 200 rpm and

Food waste CSTR, HRT 5 d, pH 5.6 and 35°C *Thermotogales*

Sucrose CSTR, HRT 24 h, 37°C and pH 5.5 *Clostridium* sp.

5.5, HRT 6 h, 36°C and complete‐mix cylindrical photoreactor, HRT 25 h, pH 8.0,

Glucose Anaerobic membrane reactor, HRT

Glucose Batch experiment, pH 5.5 and 36°C

32°C

35°C

Glucose CSTR, pH 5.5 and 30°C at

Rice slurry Batch experiment, pH 4.5 and 45°C

Sucrose CSTR, gas sparging at 300 ml/min, pH 5.3 and 35°C

Glucose CSTR; glucose to peptone ratio (5:3) 35°C, pH 7 and HRT 12 h

Glucose Batch; glucose to peptone ratio (5:3) 35°C, pH 7 and HRT 12 h

production process from various organic wastes under mesophilic condition.

30 h and 10 h HRT

In thermophilic fermentative hydrogen production, a number of microbial species are known, including *C. thermoamylolyticum* [84]*, C. cellulose, C. thermocellum, T. thermosaccharoly‐ tium* [22, 84]*, D. geothermicum* [19]*, Saccharococcus* sp. clone ETV‐T2 [8], *Mitsuokella jalaludinii* [84]. *Thermoanaerobacterium* sp. and the related genotypes are found to be dominant in many thermophilic fermentations operating at 55°C and neutral pH with feedstocks, including starch, organic waste [22], and cellulose‐rich materials [84]. Thus, many studies on microbial consortia of thermophilic fermentations resulted in the detection of the same dominant species. This is in contrast to observations from mesophilic fermentations, and it might therefore indicate that thermophilic conditions lead to a convergence of microbial populations. In this way, thermophilic reactors can provide an additional benefit for the application in sludge population optimization. One of the problems of bioreactor operation is washout of microor‐ ganisms. Trickling biofilter reactors (TBR) have been proposed as a solution to this problem, with continuous hydrogen production under thermophilic conditions being successfully demonstrated [22, 23]. In those studies, the TBR was dominated by *T. thermosaccharolytium* and *Clostridia* and *Bacilli* in the phylum *Firmicutes*.

Microbial community structure dynamics in the ASBR for biohydrogen production from palm oil mill effluent during changing of hydraulic retention time (HRT) and organic loading rate (OLR) was studied by denaturing gradient gel electrophoresis (DGGE) aiming at improved insight into the hydrogen fermentation microorganisms. The microbial community structure was strongly dependent on the HRT and OLR. DGGE profiling illustrated that *Thermoanaero‐ bacterium* spp., such as *T. thermosaccharolyticum,* and *T. bryantii*, were dominant and probably played an important role in hydrogen production under thermophilic conditions. The shift in the microbial community from a dominance of *T. thermosaccharolyticum* to a community where *Caloramator proteoclasticus* also constituted a major component occurred at suboptimal HRT (1 d) and OLR (80 gCOD l‐1d‐1) conditions [25]. The information showed that the hydrogen production performance was closely correlated with the bacterial community structure. A number of studies have focused on the analysis of the 16S rRNA gene to understand the species richness of microbial communities in lab‐scale reactors under thermophilic conditions, as shown in **Table 3**.


**Table 3.** Microbial community structure, operational conditions and reactor performance of fermentative hydrogen production process from various organic wastes under thermophilic condition.

In addition to volatile fatty acids (VFAs), anaerobic fermentations may also lead to the production of reduced end products such as ethanol, butanol, and lactate [5], thus reducing H2 yield potential. Therefore, bacterial metabolism must avoid VFAs by efficient product removal [7, 8] or metabolic engineering. Stripping gas may be used to remove H2 from the liquid phase to prevent product inhibition. N2 is used often, but it increases the costs of H2 purification. For economical reasons, CO2 might be a better choice, as it is relatively easy to separate from the gas phase. Using CO2 rather than N2 for stripping H2 resulted in a higher production of H2 and butyrate [79, 89]. High CO2 partial pressures had little effect on hydrogen‐ producing bacteria but were inhibitory to other competitive microorganisms such as acetogens and lactic acid bacteria. The microbial community structure under CO2 sparging conditions was dominated by *C. tyrobutylicum*, *C. proteolyticum*, and *C. acidisoli*. CO2 sparging has another beneficial effect on reactor performance by improving mixing and contact between substrate and microorganisms and also decreased the effects of hydrogen partial pressure [89, 90].

#### **4.3. Microbial key players in dark hydrogen fermentation**

**Substrate Processes and operation condition** 

132 Fermentation Processes

Glucose Fed batch experiment,

60°C

Cellulose Batch experiment, stirring

60°C

and 55°C

Cellulose Batch experiment, pH 6.5 and 55°C

Food waste CSTR, HRT 5 d, pH 5.6, and 55°C

Glucose Trickling biofilter reactor

64°C

Food waste CSTR; HRT 5 d, pH 5.5, and 55°C

(TBR), HRT 2 h and 55–

Jar fermentor; HRT 1d, pH

production process from various organic wastes under thermophilic condition.

6.0, and 60°C

Starch in wastewater

Artificial garbage slurry HRT 0.5 d, pH 6.6, and

at 200 rpm, pH 6.4, and

Batch experiment, pH 6.0

**Dominating microorganisms H2 yield (mol**

*Thermoanaerobacterium*

*Clostridium* and *Bacillus T. thermosaccharolyticum Clostridium thermocellum Clostridium cellulosi*

*Thermoanaerobacteriaceae Saccharococcus* sp. clone ETV‐

*Thermoanaerobacterium Clostridium thermoamylolyticum*

*Thermoanaerobacterium thermosaccharolytium Desulfotomaculum geothermicum*

**Table 3.** Microbial community structure, operational conditions and reactor performance of fermentative hydrogen

In addition to volatile fatty acids (VFAs), anaerobic fermentations may also lead to the production of reduced end products such as ethanol, butanol, and lactate [5], thus reducing H2 yield potential. Therefore, bacterial metabolism must avoid VFAs by efficient product removal [7, 8] or metabolic engineering. Stripping gas may be used to remove H2 from the liquid phase to prevent product inhibition. N2 is used often, but it increases the costs of H2 purification. For economical reasons, CO2 might be a better choice, as it is relatively easy to separate from the gas phase. Using CO2 rather than N2 for stripping H2 resulted in a higher production of H2 and butyrate [79, 89]. High CO2 partial pressures had little effect on hydrogen‐ producing bacteria but were inhibitory to other competitive microorganisms such as acetogens and lactic acid bacteria. The microbial community structure under CO2 sparging conditions was dominated by *C. tyrobutylicum*, *C. proteolyticum*, and *C. acidisoli*. CO2 sparging has another

T2

*thermosaccharolyticum* KU‐001

**H2 mol-1 hexose)**  **H2 rates (l H2 l-1d-1)** 

2.4 3.5 [70]

2.0 1.35 [87]

0.68 2.8 [8]

0.2 0.82 [84]

0.9–1.8 4.56 [19]

*T. thermosaccharolyticum* 1.1 23.25 [22]

*T. thermosaccharolyticum* 2.2 1.4 [86]

*T. thermosaccharolyticum* 1.99 4.46 [88]

**References** 

**Figure 1** summarizes the richness of the microbial key players of mesophiles. Fermentative hydrogen production has been studied for a large group of pure cultures, including species of *Enterobacter*, *Bacillus*, and *Clostridium*. However, hydrogen‐producing microflora obtained from natural sources, which are able to survive on non‐sterile substrates, contain mostly *Clostridium* spp., such as *C. butyricum*, *C. acidosoli, C. tyrobutylicum*, and *C. acetobutylicum*. Although the numbers of case studies are still low to infer solid conclusions, they indicate that the *Clostridium* genus represents the major group in dark mesophilic fermentation under mesophilic conditions. Various *Clostridium* species are found in mesophilic environments, but only four species are highly frequently observed (*C. acetobutylicum* (24%), *C. tyrobutyricum*(9%), *C. acidisoli* (16%), and *C. pasteurianum* (13%)) and related with high hydrogen yield [52,81]. However, *C. saccharolyticum, C. butyricum, C. sporogenes, C. celerecrescens, C. cellulosi*, and *C. beijerinkii* were also found to be strong hydrogen producers [83]. Others species (*Citrobacter sp., Sporolactobacillus racemicus, Streptococcus bovis*, and *B. racemilaticus*) that differ in optimal growth conditions from *Clostridium* but are metabolically similar are allow for flexibility in performance when perturbations in process conditions occur.

**Figure 1.** Summary of all fermentative hydrogen‐producing bacteria frequently observed based on molecular tools studied under mesophilic conditions.

The *Thermoanaerobacterium* genus represents the major group in dark thermophilic fermenta‐ tion. **Figure 2** summarizes the richness of the microbial key players of thermophiles. Thermo‐ philic conditions clearly show that *T. thermosaccharolyticum* is a key player in fermentative hydrogen production. *Thermoanaerobacterium* spp. have also been found to dominate in a long‐ term hydrogen production reactor. Bacteria species are highly frequently observed under thermophilic conditions and they are *Thermoanaerobacterium* sp. (47%) and *T. thermosaccharo‐ lyticum* (30%). The microbial community structure of thermophilic mixed culture sludge used for biohydrogen production from palm oil mill effluent was analyzed by fluorescence in situ hybridization (FISH) and 16S rRNA gene clone library techniques. The microbial community was dominated by *Thermoanaerobacterium* species (∼66%). The remaining microorganisms belonged to *Clostridium* and *Desulfotomaculum* spp. (∼28% and ∼6%, respectively). The hydrogen‐producing bacteria were isolated and their ability to produce hydrogen was confirmed. Three hydrogen‐producing strains, namely HPB‐1, HPB‐2, and HPB‐3, were isolated. The 16S rRNA gene sequence analysis of HPB‐1 and HPB‐2 revealed a high similar‐ ity to *T. thermosaccharolyticum* (98.6% and 99.0%, respectively). The *Thermoanaerobacterium* sp. HPB‐2 strain was a promising candidate for thermophilic fermentative hydrogen production with a hydrogen yield of 2.53 mol H2 mol‐1 hexose from organic waste and wastewater containing a mixture of hexose and pentose sugars. *Thermoanaerobacterium* species play a major role in thermophilic hydrogen production as confirmed by both molecular and cultivation‐ based analyses [91]. Various Clostridium species ( *C. cellulose, C. thermoamyloticum, and C. thermocellum*) that differ in optimal growth conditions from *Thermoanaerobacterium* but are metabolically similar are allow for flexibility in performance when perturbations in process conditions occur. Other species (*Saccharococcus spp., D. geothermicum*, and *Bacillus* spp.) could allowed for more microbial diversity and increasing the system robustness.

**Figure 2.** Summary of all fermentative hydrogen producing bacteria frequently observed based on molecular tools studied under thermophilic conditions.

### **5. Microbial population optimization for dark hydrogen fermentation**

The *Thermoanaerobacterium* genus represents the major group in dark thermophilic fermenta‐ tion. **Figure 2** summarizes the richness of the microbial key players of thermophiles. Thermo‐ philic conditions clearly show that *T. thermosaccharolyticum* is a key player in fermentative hydrogen production. *Thermoanaerobacterium* spp. have also been found to dominate in a long‐ term hydrogen production reactor. Bacteria species are highly frequently observed under thermophilic conditions and they are *Thermoanaerobacterium* sp. (47%) and *T. thermosaccharo‐ lyticum* (30%). The microbial community structure of thermophilic mixed culture sludge used for biohydrogen production from palm oil mill effluent was analyzed by fluorescence in situ hybridization (FISH) and 16S rRNA gene clone library techniques. The microbial community was dominated by *Thermoanaerobacterium* species (∼66%). The remaining microorganisms belonged to *Clostridium* and *Desulfotomaculum* spp. (∼28% and ∼6%, respectively). The hydrogen‐producing bacteria were isolated and their ability to produce hydrogen was confirmed. Three hydrogen‐producing strains, namely HPB‐1, HPB‐2, and HPB‐3, were isolated. The 16S rRNA gene sequence analysis of HPB‐1 and HPB‐2 revealed a high similar‐ ity to *T. thermosaccharolyticum* (98.6% and 99.0%, respectively). The *Thermoanaerobacterium* sp. HPB‐2 strain was a promising candidate for thermophilic fermentative hydrogen production with a hydrogen yield of 2.53 mol H2 mol‐1 hexose from organic waste and wastewater containing a mixture of hexose and pentose sugars. *Thermoanaerobacterium* species play a major role in thermophilic hydrogen production as confirmed by both molecular and cultivation‐ based analyses [91]. Various Clostridium species ( *C. cellulose, C. thermoamyloticum, and C. thermocellum*) that differ in optimal growth conditions from *Thermoanaerobacterium* but are metabolically similar are allow for flexibility in performance when perturbations in process conditions occur. Other species (*Saccharococcus spp., D. geothermicum*, and *Bacillus* spp.) could

allowed for more microbial diversity and increasing the system robustness.

**Figure 2.** Summary of all fermentative hydrogen producing bacteria frequently observed based on molecular tools

studied under thermophilic conditions.

134 Fermentation Processes

Different species likely possess different growth properties (growth rates, affinity constants with substrates, and yields), and perhaps different capacities in coping with stress arising from variations in growth conditions. Obviously, the species with the most desirable properties would be selected to perform a required function. The possibility of selecting species with better properties has huge potential for improving the performance (efficiency and reliability) of a DHF system. Unfortunately, we still lack knowledge concerning the species to be selected and how they may be selected. Furthermore, 16S rRNA sequence‐based identification does not allow inference of functional properties. The correlation between microbial community composition and reactor performance would provide a rationale to further improve the efficiency of fermentative hydrogen production. The characterization of the microbial com‐ munity as a whole contributes to meaningful data regarding structure and function of such communities and their activities.

The interest in hydrogen as a clean energy carrier has strongly increased recently. Cost‐effective generation of hydrogen through fermentation will have an important role in making this idea a reality. Future dark hydrogen fermentation from organic wastes depends on a thorough understanding of the microbiological community structure and function for enhanced or controllable hydrogen production and reactor. Sludge population optimization aims to obtain the best performance of a system through maximizing the properties of the sludge such as kinetics, yields, and robustness to environmental disturbance. A systematic investigation on the effects of a number of operational conditions on fermentative hydrogen production community and their properties is essential for sludge population optimization. The opera‐ tional parameters to be studied include pH, temperature, hydraulic retention time, sludge retention time, organic loading rate, and nutrient concentration.

Additional improvements of microbial communities should be considered such as creating conditions that select for the stable and productive growth of desired microbes, while pre‐ venting or limiting growth of organisms that reduce hydrogen yields. Microbial population optimization could be achieved by biostimulation using the additive of various nutrient species specifically for the community, bioaugmentation using the additive of dominant species or efficient hydrogen‐producing bacteria into the system, and online process control for main‐ taining their community.

A successful selection of such organisms, in particular those responsible for hydrogen production, will be used for recovery from off‐set reactors by bioaugmentation strategy. To achieve high and stable hydrogen yield and long‐term operation, it is necessary to control the growth of undesirable microorganisms such as hydrogen‐consuming bacteria, propionic acid bacteria, and lactic acid bacteria via pH adjustment and reducing of H2 partial pressure. The absence of hydrogen‐consuming bacteria leads to relatively high hydrogen concentrations in the biogas and would significantly reduce costs for gas purification. Enhancement of hydro‐ gen‐producing bacteria via specific nutrient supplements will improve the reliability and performance of the process. Sludge population optimization strategies under thermophilic conditions shown in **Figure 3**.

**Figure 3.** Summary of sludge population optimization strategies under thermophilic conditions.

#### **6. Future directions**

The use of hydrogen as a clean energy carrier has recently attracted great interest. The cost‐ effective generation of hydrogen via fermentation will have an important role in this endeavor. Future DHF from organic wastes depends on microbiological community structure and function for enhanced or controllable hydrogen production and reactor. Sludge population optimization aims to obtain the best performance of a system through maximizing the properties of the sludge such as kinetics, yields, and robustness to environmental disturbance. A systematic investigation on the effects of a number of operational conditions on fermentative hydrogen production community and their properties is essential for sludge population optimization. The operational parameters on the appearance of function of microbial species to be studied include pH, temperature, hydraulic retention time, sludge retention time, organic loading rate, and nutrient concentration. Additional improvements on microbial communities should be considered such as creating conditions that select for the stable and productive growth of desired microbes, while preventing or limiting growth of organisms that would reduce hydrogen yields. Microbial population optimization could be managed by biostimu‐ lization with the addition of nutrient species specific for their community, bioaugmentation by addition of dominant species or efficient hydrogen‐producing bacteria into the system, and online process control for maintaining their community. A successful selection of such organisms, in particular those responsible for hydrogen production, will be useful for the recovery of off‐set reactor by bioaugmentation strategy. To achieve high hydrogen yield and long‐term operation, it is necessary to control the growth of undesirable microorganisms such as hydrogen‐consuming bacteria, propionic acid bacteria, and lactic acid bacteria via pH adjustment and reduction of pH2. The absence of hydrogen‐consuming bacteria leads to relatively high hydrogen concentrations in the biogas and would significantly reduce costs for gas purification. Enhancement of hydrogen‐producing bacteria via specific nutrient supple‐ ments will improve the reliability and performance of the process.

#### **Acknowledgements**

This work was supported by the Core‐to‐Core Program, which was financially supported by Japan Society for the Promotion of Science (JSPS), National Research Council of Thailand (NRCT), Vietnam Ministry of Science and Technology (MOST), the National University of Laos, Beuth University of Applied Sciences and Brawijaya University, Research Group for Development of Microbial Hydrogen Production Process from Biomass, Khon Kaen University and Thailand Research Fund (RTA5780002).

#### **Author details**

**Figure 3.** Summary of sludge population optimization strategies under thermophilic conditions.

The use of hydrogen as a clean energy carrier has recently attracted great interest. The cost‐ effective generation of hydrogen via fermentation will have an important role in this endeavor. Future DHF from organic wastes depends on microbiological community structure and function for enhanced or controllable hydrogen production and reactor. Sludge population optimization aims to obtain the best performance of a system through maximizing the properties of the sludge such as kinetics, yields, and robustness to environmental disturbance. A systematic investigation on the effects of a number of operational conditions on fermentative hydrogen production community and their properties is essential for sludge population optimization. The operational parameters on the appearance of function of microbial species to be studied include pH, temperature, hydraulic retention time, sludge retention time, organic loading rate, and nutrient concentration. Additional improvements on microbial communities should be considered such as creating conditions that select for the stable and productive growth of desired microbes, while preventing or limiting growth of organisms that would reduce hydrogen yields. Microbial population optimization could be managed by biostimu‐ lization with the addition of nutrient species specific for their community, bioaugmentation by addition of dominant species or efficient hydrogen‐producing bacteria into the system, and online process control for maintaining their community. A successful selection of such organisms, in particular those responsible for hydrogen production, will be useful for the recovery of off‐set reactor by bioaugmentation strategy. To achieve high hydrogen yield and long‐term operation, it is necessary to control the growth of undesirable microorganisms such as hydrogen‐consuming bacteria, propionic acid bacteria, and lactic acid bacteria via pH adjustment and reduction of pH2. The absence of hydrogen‐consuming bacteria leads to

**6. Future directions**

136 Fermentation Processes

Sompong O‐Thong

Address all correspondence to: sompong.o@gmail.com

Biotechnology Program, Department of Biology, Faculty of Science, Thaksin University, Phatthalung, Thailand

#### **References**


[20] Nandi, R. and Sengupta, S. 1998. Microbial production of hydrogen: an overview. Crit. Rev. Microbiol. 24 (1): 61–84.

[6] Ren, N., Li, Y., Wang, A., Li, J., Ding, J. and Zadsar, M. 2006. Hydrogen production by fermentation: Review of a new approach to environmentally safe energy production.

[7] Hawkes, F. R., Dinsdale, R., Hawkes, D. L. and Hussy, I. 2002. Sustainable fermentative hydrogen production: challenges for process optimization. Int. J. Hydrogen Energy. 27:

[8] Zhang, T., Liu, H. and Fang, H. H. P. 2003. Biohydrogen production from starch in wastewater under thermophilic condition. J. Environ. Manage. 69: 149–156.

[9] Angenent, L., Karim, L., Al‐Dahhan, M., Wrenn, B. and Domiguez‐Espinosa, R. 2004. Production of bioenergy and biochemicals from industrial and agricultural wastewater.

[10] Montgomery, R. 2004. Development of biobased products. Bioresour. Technol. 91: 1–29.

[11] Claassen, P. A. M., Van Lier, J. B., Lopez Contraras, A. M., Van Niel, E. W. J., Sijtsma, L., Stams, A. J. M., de Vries, S. S. and Weusthuis, R. A. 1999. Utilization of biomass for the

[12] Kapdan, I.K. and Kargi, F. 2006. Bio‐hydrogen production from waste materials.

[13] Ren, N., Qin, Z. and Li, J. 2003. Comparison and analysis of hydrogen production capacity with different acidogenic fermentative microflora. Huan Jing Ke Xue. 24 (1):

[14] Liu, W., Chan, O. And Fang, H. 2002. Microbial community dynamics during start‐up

[15] Van Niel, E. W. J., Budde, M. A. W., de Haas, G. G., van de Wal, F. J., Claassen, P. A. M. and Stams, A. J. M. 2002. Distinctive properties of high hydrogen producing extreme thermopiles, *Cadicellulosiruptor saccharolyticus* and *Thermotoga elfii*. Int. J. Hydrogen.

[16] Van Niel, E. W. J., Claassen, P. A. M. and Stams, A. J. M. 2003. Substrate and product inhibition of hydrogen production by the extreme thermophile, *Caldicellulosiruptor*

[17] Hallenbeck, P.C., Ghosh, D., 2009. Advances in fermentative biohydrogen production:

[18] Logan, B. 2005. Production of electricity from acetate or butyrate using a single‐chamber

[19] Shin, H. S., Youn, J. H. and Kim, H. S. 2004. Hydrogen production from food waste in anaerobic mesophilic and thermophilic acidogenesis. Int. J. Hydrogen Energy. 29: 1355–

supply of energy carriers. Appl. Microbiol. Biotechnol. 52: 741–755.

of acidogenic anaerobic reactors. Water Res. 36: 3203–3210.

*saccharolyticus*. Biotechnol. Bioeng. 81: 254–262.

the way forward? Trends Biotechnol. 27 (5), 287–297.

microbial fuel cell. Environ. Sci. Technol. 39: 658–662.

Aquat. Eco. Health. Manage. 9: 39–42.

TRENDS Biotechnol. 22: 477–485.

Enzyme Microb. Technol. 38: 569–582.

1339–1347.

138 Fermentation Processes

70–74.

1363.

Energy. 27: 1391–1398.


semi‐continuous solid substrate anaerobic reactors: influence of the temperature. Int. J. Hydrogen Energy. 30 (13–14): 1383–1391.

[46] Amann, R.I., Fuchs, B.M., Behrens, S. 2001. The identification of microorganisms by fluorescence in situ hybridization. Curr. Opin. Microbiol. 12: 231–236.

[32] Ivanova G, Rákhely G, Kovács K. 2009. Thermophilic biohydrogen production from energy plants by *Caldicellulosiruptor saccharolyticus* and comparison with related

[33] O‐Thong S, Prasertsan P, Karakashev D, Angelidaki I. 2008. Thermophilic fermentative hydrogen production by the newly isolated *Thermoanaerobacterium thermosaccharolyti‐*

[34] Yokoyama H, Moriya N, Ohmori H, Waki M, Ogino A, Tanaka Y. 2007. Community analysis of hydrogen‐producing extreme thermophilic anaerobic microflora enriched from cow manure with five substrates. Appl. Microbiol. Biotechnol. 77(1), 213–222.

[35] Kleerebezem R, van Loosdrecht M. 2007. Mixed culture biotechnology for bioenergy

[36] Temudo M, Muyzer G, Kleerebezem R, van Loosdrecht M. 2008. Diversity of microbial communities in open mixed culture fermentations: impact of the pH and carbon source.

[37] Ozmihci S, Kargi F. 2010. Comparison of different mixed cultures for biohydrogen production from ground wheat starch by combined dark and light fermentation. J. Ind.

[38] Demirel B, Scherer P, Yenigun O, Onay T. 2010. Production of Methane and Hydrogen from Biomass through Conventional and High‐Rate Anaerobic Digestion Processes.

[39] Li C, Fang H. 2007. Fermentative hydrogen production from wastewater and solid

[40] Arooj M, Han S, Kim S, Kim D, Shin H. 2008. Continuous biohydrogen production in a CSTR using starch as a substrate. Int. J. Hydrogen Energy. 33(13), 3289–3294.

[41] Gavala H, Skiadas I, Ahring B. 2006. Biological hydrogen production in suspended and attached growth anaerobic reactor systems. Int. J. Hydrogen Energy. 31(9), 1164–1175.

[42] Duangmanee T, Padmasiri S, Simmons J, Raskin L, Sung S. 2007. Hydrogen production by anaerobic microbial communities exposed to repeated heat treatments. Water

[43] Kaparaju P, Serrano M, Angelidaki I. 2009. Effect of reactor configuration on biogas production from wheat straw hydrolysate. Bioresour. Technol. 100, 6317–6323.

[44] Luo G, Xie L, Zou Z, Wang W, Zhou Q. 2010. Evaluation of pretreatment methods on mixed inoculum for both batch and continuous thermophilic biohydrogen production

[45] Valdez‐Vazquez, I., Rios‐Leal, E., Esparza‐Garcia, F., Cecchi, F. and Poggi‐Varaldo, H. M. 2005. Hydrogen production from the organic fraction of municipal solid waste using

wastes by mixed cultures. Crit. Rev. Environ. Sci. Technol. 37(1), 1–39.

studies. Int. J. Hydrogen Energy. 34(9): 3659–3670.

140 Fermentation Processes

*cum* PSU‐2. Int. J. Hydrogen Energy. 33(4), 1204–1214.

production. Curr. Opin. Biotechnol. 18(3), 207–212.

Appl. Microbiol. Biotechnol. 80(6), 1121–1130.

Crit. Rev. Environ. Sci. Technol. 40(2), 116–146.

from cassava stillage. Bioresour. Technol. 101,959‐964.

Microbiol. Biotechnol. 37:341–347.

Environ. Res. 79, 975–983.


[72] Hasyim, R., Imai, T., Reungsang, A., O‐Thong, S. (2011) Extreme‐thermophilic biohy‐ drogen production by an anaerobic heat treated digested sewage sludge culture. Int. J. Hydrogen Energy. 36 (14): 8727–8734.

[59] Banfield, J.F., Verberkmoes, N.C., Hettich, R.L., Thelen, M.P. 2005. Proteogenomic approaches for the molecular characterization of natural microbial communities.

[60] Okamoto, M., Miyahara, T., Mizuno, O. and Noike, T. 2000. Biological hydrogen potential of materials characteristic of the organic fraction of municipal solid wastes.

[61] Yu, H., Z. Zhu, W. Hu, and H. Zhang. 2002. Hydrogen production from rice winery wastewater in an up‐flow anaerobic reactor by using mixed anaerobic cultures. Int. J.

[62] Van Ginkel, S.W. and Logan, B. 2005. Increased biological hydrogen production with

[63] Kataoka, N., Miya, A. and Kiriyama, K. 1997. Studies on hydrogen production by continuous cultures system of hydrogen producing anaerobic bacteria. Water. Sci.Te‐

[64] Wang, C. C., Chang, C. W., Chu, C. P. and Lee, D. J. 2003. Sequential production of hydrogen and methane from wastewater sludge using anaerobic fermentation. J. Chin.

[65] Chang, J. S., Lee, K. S. and Lin, P. J. 2002. Biohydrogen production with fixed bed

[66] Kotsopoulos, T., Zeng, R. and Angelidaki, I. 2006. Biohydrogen production in granular up‐flow anaerobic sludge blanket (UASB) reactors with mixed cultures under hyper‐

[67] Fan, K. S., Kan, N. R. and Lay J. J. 2006. Effect of hydraulic retention time on anaerobic

[68] Kawagoshi, Y., Hino, N., Fujimoto, A., Nakao, M., Fujita, Y., Sugimura, S. And Furu‐ kawa, K. 2005. Effect of inoculum conditioning on hydrogen fermentation and pH effect on bacterial community relevant to hydrogen production. J. Biosci. Bioeng. 100: 524–

[69] Hussy, I., F. Hawkes, R. Dinsdale, and D. Hawkes. 2003. Continuous fermentative hydrogen production from a wheat starch co‐product by mixed microflora. Biotechnol.

[70] Ueno, Y., Haruta, S., Ishii, M. and Igarashi, Y. 2001. Characterization of a microorganism isolated from the effluent of hydrogen fermentation by microflora. J. Biosci. Bioeng.

[71] Sung, S., Raskin, L., Duangmanee, T., Padmasiri, S. and Simmons, J. J. 2002. Hydrogen production by anaerobic microbial communities exposed to repeated heat treatments.

thermophilic temperature (70 degrees C). Biotechnol. Bioeng. 94(2): 296–302.

OMICS. 9:301–333.

142 Fermentation Processes

chol. 36: 41–47.

530.

Bioeng. 84: 619–626.

92(4): 397–400.

Water. Sci. Technol. 41: 25–32.

Hydrogen Energy. 27: 1359–1365.

Inst. Chem. Engrs. 34(6): 683–687.

reduced organic loading. Water Res. 39: 3819–3826.

bioreactors. Int. J. Hydrogen Energy. 27: 1167–1174.

hydrogenesis in CSTR. Bioresour. Technol. 97: 84–89.

Proc. of the 2002 U. S. DOE Hydrogen Program Review.


#### **Biosensors in Fermentation Applications Biosensors in Fermentation Applications**

Jianguo Shi, Derong Feng and Yiwei Li Jianguo Shi, Derong Feng and Yiwei Li

Additional information is available at the end of the chapter Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/65077

#### **Abstract**

[86] Shin, H. S. and Youn, J. H. 2005. Conversion of food waste into hydrogen by thermo‐

[87] Ueno, Y., Haruta, S. and Igarashi, Y. 2001. Microbial community in anaerobic hydrogen producing microflora enriched from sludge compost. Appl. Microbiol. Biotechnol. 57:

[88] Ueno, Y., Sasaki, D., Fukui, H., Haruta, S., Ishii, M., Igarashi, Y. 2006. Changes in bacterial community during fermentative hydrogen and acid production from organic

[89] Mizuno, O., Dinsdale, R., Hawkes, D. L. and Noike, T. 2000. Enhancement of hydrogen production from glucose by nitrogen gas sparging. Bioresour. Technol. 73: 59–65. [90] Mandal, B., Nath, K. and Das, D. 2006. Improvement of biohydrogen production under decreased partial pressure of H2 by *Enterobacter cloacae*. Biotechnol. Lett. 28: 831–835.

[91] Nitipan, S., Mamimin, C., Intrasungkha, N., Birkeland, N.K. and O‐Thong, S. 2014. Microbial community analysis of thermophilic mixed culture sludge for biohydrogen production from palm oil mill effluent. Int J. Hydrogen Energy. 39(33):19285–19293.

waste by thermophilic anaerobic microflora. Appl. Microbiol. 101: 331–343.

philic acidogenesis. Biodegradation. 16: 33–44.

555–562.

144 Fermentation Processes

Biosensing technology offers new analytic routes to the use and study of fermentations, taking advantage of the high selectivity and sensitivity of the bioactive elements it exploits. Various biosensors had been commercially available today; they provide fermentation processes with convenient, accurate, and cost-effective ways of monitoring for key biochemical parameters. In this chapter, the basic ideas and principles of biosensors, especially applications of the most popular biosensors related to fermentations were highlighted.

**Keywords:** biosensor, electrochemical techniques, enzyme electrode, amino acid, sugar, alcohol

#### **1. Introduction**

Biosensor is a field of interdisciplinary studies and applications, which is underlain by many theoretical and technical fundaments from life science, physics, analytical chemistry, information technology, and so forth. The study of biosensors is a branch of analytical biology. It is largely aimed to construct rapid, stable, and facile analytical devices and analytical technologies used thereby. As a novel analytical technique, biosensors features small size, high sensitivity, high analytical specificity, and rapid accessibility, ready to realize reagentless analyses. This technology has made its way in great advances and attracted attentions since it wasfirst proposed in 1960s.

The first biosensor was reported to be constructed and succeeded in measuring medical data, a biological electrode by Pro. Clark and co-works in 1962. **Figure 1** is a schematic of it. The electrode is fabricated via fixing a layer of immobilized glucose oxidase (glucose oxidase, EC 1.1.3.4) membrane onto an ion selective electrode that is capable of detecting dissolved oxygen

© 2017 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2017 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

concentrations. When working, glucose oxidase catalyzes the conversion from the substrates β‐D‐glucose (the analyte, exists in the solution environment) and molecular oxygen into gluconic acid and hydrogen peroxide (H2O2), the products. The electrode could detect oxygen changes in the environment as it is consumed by the enzymatic reaction and transmit the sensing signal into form of voltages, and, in turn, the glucose concentration can be determined, for it is proportional to the dissolved oxygen concentration in certain range. In this method, the high specificity of enzymatic reaction and powerful detecting ability of electrochemical electrode was judiciously integrated so that the biochemical reaction can be monitored through a physicochemical detector. After this exemplification, biosensors had being hot topics among the researchers worldwide. Now, biosensors had found their way in both practical applications and scientific researches in many forms of commercially available products.

**Figure 1.** A schematic representation of the classic Clark enzyme electrode with glucose oxidase (Gox) as its biological element.

#### **1.1. Classification of biosensors**

As is recommended by IUPAC in 1999, a biosensor is an independently integrated receptor transducer device, which is capable of providing selective quantitative or semiquantitative analytical information using a biological recognition element [1].

A typical biosensor is made up of two main parts: (a) a biological element that can give any form of detectable signals, enzymatically catalyzed reactions, and biomolecular recognitions are the most referred, among others. Enzymes, antibodies, and nucleic acids are often exploited as the biological element; (b) a transducer by which the signal produced by the biological element can be detected and converted into measurable electrical signal.

To construct a biosensing system, three main elements are often required, they are as follows: a biological element, a transducer, and a signal processing system [2]. A schematic of a typical biosensor system can be seen in **Figure 2**.

**Figure 2.** Basic elements to construct a biosensor system.

concentrations. When working, glucose oxidase catalyzes the conversion from the substrates β‐D‐glucose (the analyte, exists in the solution environment) and molecular oxygen into gluconic acid and hydrogen peroxide (H2O2), the products. The electrode could detect oxygen changes in the environment as it is consumed by the enzymatic reaction and transmit the sensing signal into form of voltages, and, in turn, the glucose concentration can be determined, for it is proportional to the dissolved oxygen concentration in certain range. In this method, the high specificity of enzymatic reaction and powerful detecting ability of electrochemical electrode was judiciously integrated so that the biochemical reaction can be monitored through a physicochemical detector. After this exemplification, biosensors had being hot topics among the researchers worldwide. Now, biosensors had found their way in both practical applications

**Figure 1.** A schematic representation of the classic Clark enzyme electrode with glucose oxidase (Gox) as its biological

As is recommended by IUPAC in 1999, a biosensor is an independently integrated receptor transducer device, which is capable of providing selective quantitative or semiquantitative

A typical biosensor is made up of two main parts: (a) a biological element that can give any form of detectable signals, enzymatically catalyzed reactions, and biomolecular recognitions are the most referred, among others. Enzymes, antibodies, and nucleic acids are often exploited as the biological element; (b) a transducer by which the signal produced by the biological

analytical information using a biological recognition element [1].

element can be detected and converted into measurable electrical signal.

element.

146 Fermentation Processes

**1.1. Classification of biosensors**

and scientific researches in many forms of commercially available products.

According to the difference of the biological element and transducer utilized, biosensors can be divided into several categories as what shall we introduced in the following listed in **Figure 3**.

**Figure 3.** Classifications of common biosensors.

As is shown in the figure, electricity, light, sound, heat, and force, almost all physical dimen‐ sions have been available to be used as the target property for constructing a biosensor. Biosensors based on different physical principles have both their advantages and disadvan‐ tages and befit various kinds of analyzing targets. Electrochemical biosensors are inexpensive, easy to be prepared, and available to meet various ranges of analyte concentration [3]; this strategy is most often used in both fermentation and other practical applications. Optical ones can detect biological parameters with UV‐visible [4], infrared [5], fluorescent [6], and chemi‐ luminescent [7] lights. Thermal ones detect heat released in physicochemical processes. For fermentation uses, heat is released by both cellular and non‐cellular processes to facilitate monitoring the fermentation progress [8]. Other strategies are often seen in comparatively highly specific uses, for example, SPR and microcantilever sensors are good choices to facilitate biomolecular researches [9], although they are often cost non‐saving and high in instrumental and operative requirements.

Biosensors, other than those fit into the definition given above, and some sensing technologies that are aimed at detecting biologically related parameters yet contain not any biologically active elements are also counted, and they are usually called "generalized biosensors." Examples of generalized biosensors include for instance: mass spectrometric measurements used in off‐gas analyses in fermentation processes [10, 11] and cytometry for fermentation process controls [12].

Out of its prevalence, robust analyzing capability, cost‐saving, and facile instrumenting, in this text, we put the most focus on the most studied and relatively mature in practical applications such as electrochemical biosensors.

#### **1.2. Basic principles**

Electrochemical biosensors are based on various kinds of electrodes by which electrical signals can be produced and sensed. There are three main techniques widely used for electrochemical biosensors [13]:


#### **2. Applications**

Biosensors based on different physical principles have both their advantages and disadvan‐ tages and befit various kinds of analyzing targets. Electrochemical biosensors are inexpensive, easy to be prepared, and available to meet various ranges of analyte concentration [3]; this strategy is most often used in both fermentation and other practical applications. Optical ones can detect biological parameters with UV‐visible [4], infrared [5], fluorescent [6], and chemi‐ luminescent [7] lights. Thermal ones detect heat released in physicochemical processes. For fermentation uses, heat is released by both cellular and non‐cellular processes to facilitate monitoring the fermentation progress [8]. Other strategies are often seen in comparatively highly specific uses, for example, SPR and microcantilever sensors are good choices to facilitate biomolecular researches [9], although they are often cost non‐saving and high in instrumental

Biosensors, other than those fit into the definition given above, and some sensing technologies that are aimed at detecting biologically related parameters yet contain not any biologically active elements are also counted, and they are usually called "generalized biosensors." Examples of generalized biosensors include for instance: mass spectrometric measurements used in off‐gas analyses in fermentation processes [10, 11] and cytometry for fermentation

Out of its prevalence, robust analyzing capability, cost‐saving, and facile instrumenting, in this text, we put the most focus on the most studied and relatively mature in practical applications

Electrochemical biosensors are based on various kinds of electrodes by which electrical signals can be produced and sensed. There are three main techniques widely used for electrochemical

**1.** *Potentiometric*. It includes zero‐current potentiometry and techniques of applying ampli‐ tude controlled current onto the working electrode. In these methods, electrical potential

**2.** *Amperometric*. Amperometric method is based on detecting current produced by applying a known potential. There are mainly two forms of amperometric methods: constant‐ potential amperometry and amperometry with applying various potential waveforms.

**3.** *Impedimetric*. It is also called impedance spectrometry, which is based on detections of impedance, conductance, and capacitance of a certain electrochemical system. It is more

Most of the biosensors used in fermentations are of amperometric type.

often used in theoretical analyses of the sensing surface.

and operative requirements.

148 Fermentation Processes

process controls [12].

**1.2. Basic principles**

biosensors [13]:

such as electrochemical biosensors.

is detected for measurements.

#### **2.1. Amino acid detection**

Amino acid is one of the most important biomolecules for life, and they act as building blocks of numerous proteins, precursors in the synthesis of many biologically functional molecules and energy resource, in some cases. For human beings, counting in the eight essential and two semi‐essential ones, in total about 22 natural amino acids are required to maintain a healthy human body. In food and medicine applications, amino acid is a vital material.

Biosensing tactics for amino acids are mainly realized by using enzyme biosensors. The enzymes are often amino acid oxidases as L‐amino acid oxidase [14], glutamate oxidase [15– 17], leucine dehydrogenase [18], tyrosinase [19, 20], and L‐phenylalanine dehydrogenase [21].

Glutamate is very important in medical uses [22, 23], and sodium salt is a widely used seasoning additive, which is now mainly produced by large‐scale cellular fermentations. Amperometric enzyme electrodes that detect glutamate is one of the most widely and maturely used biosensors. In majority of the now commercially available glutamate biosensors, a typical strategy is to integrate a glutamate oxidase onto a platinum electrode. When use, preset potential is applied upon the electrode to electrochemically catalyze the oxidation of the enzymatic reaction's product—hydrogen peroxide. Computer records the electrical current produced in this process and translates it into the corresponding concentration as the readout [24]. In a research, glutamate oxidase (EC 1.4.3.11) and NADP+ ‐dependent glutamate dehy‐ drogenase (EC 1.4.1.3) were co‐immobilized onto an oxygen electrode to fabricate an enzymatic MSG detector for food uses. By exploiting those two enzymes, monosodium salt of glutamate and glutamic acid can be distinguished to perform more accurate measurements [25]. Rita et al. [26] constructed a glutamate enzyme sensor by immobilize L‐glutamate oxidase (GLOD, EC 1.4.3.11) and Gox on glass carbon electrode. To minimize the interference, the enzyme electrode was then modified with the polymer Nafion, a very widely used material to improve the sensing selectivity of amperometric enzyme sensors. The electrode can perform simulta‐ neous measurement of L‐glutamate and glucose without any obvious interference. Tang et al. [27] constructed glutamate enzyme electrode with NAD+ ‐dependent glutamate dehydrogen‐ ase (EC 1.4.1.3). To improve its sensitivity, the electrode was modified with nanocomposite. The electrode has a very rapid response and good stability (remains 85% sensing intensity after 4 weeks). For quantifications of total L‐amino acid, enzyme electrode based on immobilized L‐amino acid oxidase can be a very good choice [28].

Stasyuk et al. [29] used recombinant yeast cells as the arginine activity source to establish an amperometric biosensor along with immobilized urease. The cell‐enzyme coupled sensor reportedly exhibited a linear range cross 3 orders of magnitude up to 0.6 mM and can give the result within no more than 1 min. Another strategy is by coupling arginase (EC 3.5.3.1) and urease (EC 3.5.1.5). An arginine biosensor was constructed on ion‐selective field effect transistors (ISFETs) surface via co‐immobilizing arginase and urease. When working, arginine catalyzes the conversion of arginine into ornithine with release of urea, which, in turn, is degraded by urease to produce ammonium ions. Production of ammonium is accompanied by the subtle change of pH and thus can be detected by the transmitter [30].

All amino acids exist in humans are of L‐form, for enzyme dealing with D‐amino acids are in lack in human body. Therefore, were there D‐amino acids in food or medical products, it is of danger to cause problems of safety and monitoring of their presence is often one part of many fermentation products' quality control. To meet this need, an enzyme electrode was developed by co‐immobilizing D‐amino acid oxidase (DAAO, EC 1.4.3.3) and peroxidase onto polymer electron mediator modified electrode [31]. Zain et al. devised a D‐serine‐sensitive electro‐ chemical detector via immobilizing DAAO onto polymer functionalized metal electrode. The detector is reported to have ideal interference resistance toward most of the neurochemicals and can be used for *in vivo* D‐serine detections [32].

Other than enzyme‐biosensing methods, amino acid measurement can also be accomplished by enzyme‐free techniques. Dai et al. [33] prepared nanoporous nickel‐modified boron‐doped diamond electrode with electron‐assisted hot filament chemical vapor deposition method, and the electrode can capture redox processes of L‐alanine and can perform anti‐interference, sensitive detections of it. Seki et al. developed a tryptophan sensitive, potentiometric detector with microbial cells as the biological element. In the scenario, an auxotrophic bacterial strain *Escherichia coli* WP2—a mutant requiring tryptophan for its growth was monitored with a light‐ addressable potentiometric sensor. When L‐tryptophan is in present, the bacterial metabolic result of it will cause pH changes, which can be detected and used for quantification by the sensor [34].

#### **2.2. Sugar detection**

In fermentation processes, sugars can either a vital substrate for cellular fermentations or in some cases the target product (e.g. oligosaccharides in isomalto‐oligosaccharide [35] and chito‐ oligosaccharide preparations [36]; glucose from enzymatically degraded starch). The most commercially available and under‐research biosensors for sugars are aiming at detections of monosaccharides. For oligo‐ and polysaccharides, very mature sensing platform is rarely seen mainly because accessible biological elements that exhibit good biorecognitions toward them are difficult to obtain.

Up to now, glucose is the target analyte in most biosensor researches during which its medical uses are most concerned. For fermentation uses, there had been many kinds of commercial biosensors for choice; the majority of them are operated under off‐line mode.

A very widely applied glucose biosensor is much the same like the typical glutamate enzyme electrode aforementioned, with the only difference being that the enzyme alters into usually glucose oxidase (Gox). Although the rare metal‐based enzyme glucose biosensors are easy to prepare, cost acceptable, and often renewable (in a typical mode of Pt‐based Gox electrode, the enzyme is immobilized onto a polymer permeable membrane), biosensor is achieved by covering the enzyme laden side tightly to the Pt electrode surface. When the detected signals are seen obviously declined after a period of use, operators need to only replace the enzyme membrane with a new one from the same manufacturer to refresh the sensor. Pt base is electrochemically inert and thus is resistant to repeated use (**Figure 4**). Difficulties in modifying the base electrode to functionalize it, high cost of the electrode hinders it from altering into disposable forms, etc., are often motives for researchers to develop more sophisticated ones.

degraded by urease to produce ammonium ions. Production of ammonium is accompanied

All amino acids exist in humans are of L‐form, for enzyme dealing with D‐amino acids are in lack in human body. Therefore, were there D‐amino acids in food or medical products, it is of danger to cause problems of safety and monitoring of their presence is often one part of many fermentation products' quality control. To meet this need, an enzyme electrode was developed by co‐immobilizing D‐amino acid oxidase (DAAO, EC 1.4.3.3) and peroxidase onto polymer electron mediator modified electrode [31]. Zain et al. devised a D‐serine‐sensitive electro‐ chemical detector via immobilizing DAAO onto polymer functionalized metal electrode. The detector is reported to have ideal interference resistance toward most of the neurochemicals

Other than enzyme‐biosensing methods, amino acid measurement can also be accomplished by enzyme‐free techniques. Dai et al. [33] prepared nanoporous nickel‐modified boron‐doped diamond electrode with electron‐assisted hot filament chemical vapor deposition method, and the electrode can capture redox processes of L‐alanine and can perform anti‐interference, sensitive detections of it. Seki et al. developed a tryptophan sensitive, potentiometric detector with microbial cells as the biological element. In the scenario, an auxotrophic bacterial strain *Escherichia coli* WP2—a mutant requiring tryptophan for its growth was monitored with a light‐ addressable potentiometric sensor. When L‐tryptophan is in present, the bacterial metabolic result of it will cause pH changes, which can be detected and used for quantification by the

In fermentation processes, sugars can either a vital substrate for cellular fermentations or in some cases the target product (e.g. oligosaccharides in isomalto‐oligosaccharide [35] and chito‐ oligosaccharide preparations [36]; glucose from enzymatically degraded starch). The most commercially available and under‐research biosensors for sugars are aiming at detections of monosaccharides. For oligo‐ and polysaccharides, very mature sensing platform is rarely seen mainly because accessible biological elements that exhibit good biorecognitions toward them

Up to now, glucose is the target analyte in most biosensor researches during which its medical uses are most concerned. For fermentation uses, there had been many kinds of commercial

A very widely applied glucose biosensor is much the same like the typical glutamate enzyme electrode aforementioned, with the only difference being that the enzyme alters into usually glucose oxidase (Gox). Although the rare metal‐based enzyme glucose biosensors are easy to prepare, cost acceptable, and often renewable (in a typical mode of Pt‐based Gox electrode, the enzyme is immobilized onto a polymer permeable membrane), biosensor is achieved by covering the enzyme laden side tightly to the Pt electrode surface. When the detected signals are seen obviously declined after a period of use, operators need to only replace the enzyme membrane with a new one from the same manufacturer to refresh the sensor. Pt base is

biosensors for choice; the majority of them are operated under off‐line mode.

by the subtle change of pH and thus can be detected by the transmitter [30].

and can be used for *in vivo* D‐serine detections [32].

sensor [34].

150 Fermentation Processes

**2.2. Sugar detection**

are difficult to obtain.

Commercial blood glucose biosensor had been used to monitor glucose concentration in the fermentation broth. The result shown the method is potent to fill formation needs and is a good alternative for HPLC analysis and reducing sugar assay [37]. White et al. used screen‐printed Gox electrode as the glucose detector to perform real‐time fermentation control [38]. The electrode is a classical form of electrochemical detector, which is extremely inexpensive, highly reproducible, and repeatable, and very large‐scale production is suitable. To overcome the problem of on‐line sensing, the researchers introduced flow injection analysis system to rid the gap between sampling and the sensor.

In fermentations, high‐temperature processing is often inevitable for preventing the fermen‐ tation processes from biological contaminations. However, biosensors are in most cases non– high‐temperature tolerant. To tackle the problem, Phelps et al. proposed a glucose‐sensing device that is autoclavable and can be repeatedly used [39]. Unlike the conventional immobi‐ lized enzyme electrodes, the electrode consists largely of a semipermeable membrane in protecting the sensing surface from fouling by the fermentation broth, a Pt electrode functions as its conventional versions, and a chamber with conduits through which electrolyte and enzyme solutions can be filled or discarded. The design circumvented the contact between the intense autoclaving conditions and the temperature vulnerable enzyme.

**Figure 4.** A schematic representation of screen‐printed electrode. The base electrode is derived from a printing technol‐ ogy called "screen printing," which uses a mesh with predrawn patterns hollowed out and let the printing ink to through it so that the pattern is printed onto the base material. Enzyme electrodes prepared with this method are near two dimensional so they are potable. The high reproducibility of its preparing progress grants high reproducibility to electrodes made in the same batch.

Another strategy aiming at on‐line biosensor design can be seen in a research that uses non‐ immobilized, liquid Gox as its biological element. The base electrode is not in direct contact with the enzyme, and it only detects the catalytic product in the enzyme solution [40]. Other than the on‐line uses, this design open a new way to devise biosensors that are target at measuring high‐concentration glucose in consideration that it is especially useful in fermen‐ tations. In large number cases of fermentation processes, glucose concentrations at the initial and early period are often too high, which exceed the upper detection limit of most enzyme‐ immobilized sensors. Therefore, continuous monitoring is hard to be realized without gradient dilutions that are performed, yet the process is often the key source of sampling error. The enzyme‐injected mode can allow the electrode to direct detection of high glucose concentration broths.

Development of enzyme electrode has gone though three main stages, in which Gox electrode is a very good example:

Stage I: Gas‐sensitive electrodes represented by Clark enzyme electrode. The measurement is performed in potentiometric method by detecting changes of dissolved oxygen or any acid or base produced in the enzymatic reaction. The problem of this strategy is as dissolved oxygen consumed, measuring results are liable to become awry of the electrode's linear range and as a result brings huge errors to the quantification.

Stage II: Electron mediator‐functionalized electrodes overcome the shortcut of gas‐sensitive electrodes and established new strategy for enzyme electrode designs. Electron mediators were found by researcher that when they were integrated into the biosensing interfaces, electrons produced by the enzymatic reaction can be relied by the mediator, which, in turn, is oxidized by the base electrode. By this way, electrochemical detection can become oxygen consumption independent. Electron mediators can be either natural substances, for example cytochromes and co‐enzymes, or artificial ones as some organic dyes, ferrocene and its derivatives, metal complexes, and some conductive polymers. By using electron mediators, detecting potentials can be effectively lowered so that much interference would thus be eliminated.

Stage III: Direct enzyme electrode was proposed after phenomenon that some proteins can make direct electrochemical communications with the electrode, which is represented by the finding of reversible cyclic voltammetric response on the electrode. Principle of the phenom‐ enon is suggested to be when the redox center of the protein molecule is in close adjacent to the electrode surface, electrons can transport between them directly without the aid of any mediators. By using this mechanism, an obviously improved electron transfer efficiency can be obtained and the sensing capability is enhanced. However, it is often difficult to achieve the required conditions for enzymes. Taking Gox for example, its electrochemical active center —FAD+ cofactor—is wrapped into the space formed by the dimmer subunits and therefore is difficult to build direct electrochemical communication between the electrode and the enzyme. When Gox is tightly adsorbed onto some electrochemical active materials such as carbon nanotubes and graphenes, the direct electron transfer can be observed. Researchers have to pay more attention and efforts to develop direct enzyme electrodes, as it is a promising strategy to construct more rapid, sensitive, and reagentless biosensors.

#### **2.3. Alcohol detection**

Another strategy aiming at on‐line biosensor design can be seen in a research that uses non‐ immobilized, liquid Gox as its biological element. The base electrode is not in direct contact with the enzyme, and it only detects the catalytic product in the enzyme solution [40]. Other than the on‐line uses, this design open a new way to devise biosensors that are target at measuring high‐concentration glucose in consideration that it is especially useful in fermen‐ tations. In large number cases of fermentation processes, glucose concentrations at the initial and early period are often too high, which exceed the upper detection limit of most enzyme‐ immobilized sensors. Therefore, continuous monitoring is hard to be realized without gradient dilutions that are performed, yet the process is often the key source of sampling error. The enzyme‐injected mode can allow the electrode to direct detection of high glucose concentration

Development of enzyme electrode has gone though three main stages, in which Gox electrode

Stage I: Gas‐sensitive electrodes represented by Clark enzyme electrode. The measurement is performed in potentiometric method by detecting changes of dissolved oxygen or any acid or base produced in the enzymatic reaction. The problem of this strategy is as dissolved oxygen consumed, measuring results are liable to become awry of the electrode's linear range and as

Stage II: Electron mediator‐functionalized electrodes overcome the shortcut of gas‐sensitive electrodes and established new strategy for enzyme electrode designs. Electron mediators were found by researcher that when they were integrated into the biosensing interfaces, electrons produced by the enzymatic reaction can be relied by the mediator, which, in turn, is oxidized by the base electrode. By this way, electrochemical detection can become oxygen consumption independent. Electron mediators can be either natural substances, for example cytochromes and co‐enzymes, or artificial ones as some organic dyes, ferrocene and its derivatives, metal complexes, and some conductive polymers. By using electron mediators, detecting potentials can be effectively lowered so that much interference would thus be

Stage III: Direct enzyme electrode was proposed after phenomenon that some proteins can make direct electrochemical communications with the electrode, which is represented by the finding of reversible cyclic voltammetric response on the electrode. Principle of the phenom‐ enon is suggested to be when the redox center of the protein molecule is in close adjacent to the electrode surface, electrons can transport between them directly without the aid of any mediators. By using this mechanism, an obviously improved electron transfer efficiency can be obtained and the sensing capability is enhanced. However, it is often difficult to achieve the required conditions for enzymes. Taking Gox for example, its electrochemical active center

cofactor—is wrapped into the space formed by the dimmer subunits and therefore is

difficult to build direct electrochemical communication between the electrode and the enzyme. When Gox is tightly adsorbed onto some electrochemical active materials such as carbon nanotubes and graphenes, the direct electron transfer can be observed. Researchers have to pay more attention and efforts to develop direct enzyme electrodes, as it is a promising strategy

to construct more rapid, sensitive, and reagentless biosensors.

broths.

152 Fermentation Processes

eliminated.

—FAD+

is a very good example:

a result brings huge errors to the quantification.

Alcohol content in fermentation broths can be realized by many conventional methods, for example hydrometry and gas chromatography. Considered the error limit or high expense or time‐costing procedures of them, biosensor is a good alternative.

A colorimetric biosensor was proposed by Kuswandi et al. The sensor was constructed by polyaniline film immobilized alcohol oxidase. When ethanol is in presence, a color change from green to blue can be observed due to the oxidation of polyaniline by the enzyme reaction product H2O2. Through the computer processing software, the method can determine alcohol quantitatively range between 0.01 and 0.8% [41]. Gotoh et al. devised an amperometric alcohol sensor based on co‐immobilized alcohol dehydrogenase and coenzyme NAD+ , the enzyme electrode shown linear response to solution contains ethanol between 0.05 and 10v/v%. As a reagentless enzyme sensor, it can stand at least weeks of continual detections without addition of the coenzyme [42].

#### **3. Future perspectives**

In the applications of fermentation processes, although many tangible advances have been achieved and a bunch of biosensors are now commercially accessible, many questions are still in need of further studies.

First, due to the biologically active species that can serve as biological elements are still in a limited range, the parameters detectable for biosensor in fermentation processes are restricted to the several kinds of target constituents. This, in one hand, can be gradually extended by finding and isolating new suitable biological constituents from the natural world. With respect to enzyme biosensors, dehydrogenase is becoming the most widely used. Over 400 dehydro‐ genases have been discovered or isolated; many biological constituents would be allowed to be detected by dehydrogenase sensors. Dehydrogenases often have their isozymes, and they require NAD+ or NADP+ or quinones as the cofactors. Comparing to oxidases, the redox center of dehydrogenases is not wrapped tightly by the protein components so more liable to establish direct electronic communications with electrodes. One of the most thorny problems is to establish methods for cofactors' immobilization to realize the reagentless biosensors. On the other hand, new generations may provide opportunities. One technical route is developing molecular imprinting sensors, in which artificial polymers that mimic the structure of natural enzymes, antibodies, or antigens to produce the alike high specificity can be synthesized. Even though, in some examples, the potent polymers are obtained, there still a long way ahead of the application of the technique. Another route is to establish aptamers, usually short nucleic acid chains or peptides judiciously devised and synthesized. Aptamers are alternatives yet can provide the same biorecognition functions to their natural forms. Many usable aptamers have been established, and it is a critical mission to its applications establishing a high‐throughput selecting technology to accelerate the discovery of new aptamers.

Second, endeavor to improve the base electrode is never ended, and it is one of the core topics of electrochemistry. By modification, electrodes can be endowed with new functions or get their sensor capacities enhanced. The most promising materials for electrode functionalization include nanocomposites, conductive polymers, novel electron mediators, liquid ions, and so forth. Among others, nanocomposites such as carbon nanotubes, graphene, and metal nano‐ particles are attracting most of researchers' interests as they have both robust physical and chemical properties that are useful for improving sensing capabilities (e.g., limit of detection, sensitivity, selectivity, anti‐interference, and electrochemical stability) and huge potential to exploit for conducting immobilization of biological elements. Nanocomposite per se is also a platform for preparing complex composites via combination of the materials mentioned above.

Third, miniaturization, integration, and automation of biosensors in fermentation uses are still at its preliminary stage. Although many commercial biosensors have, to a great extent, facilitated the detection of several kinds of constituent, it is uneasy to realize multiple param‐ eter automatic controls for the whole fermentation process. Aside of developing more and more diverse biosensors fit for different targets, testing conditions, microfabrication technol‐ ogy, and Internet of Things are promising tools for achieving this goal.

#### **Author details**

Jianguo Shi\* , Derong Feng and Yiwei Li

\*Address all correspondence to: shijg@sdas.org

Shandong Provincial Key Laboratory of Biosensors, Biology Institute, Shandong Academy of Sciences, Jinan, Shandong, China

#### **References**


deuteration on the detection of the Aβ peptide. Spectroscopy, 2010, 119(15): 5055‐5061. DOI: 10.3233/spe‐2010‐0405

sensor capacities enhanced. The most promising materials for electrode functionalization include nanocomposites, conductive polymers, novel electron mediators, liquid ions, and so forth. Among others, nanocomposites such as carbon nanotubes, graphene, and metal nano‐ particles are attracting most of researchers' interests as they have both robust physical and chemical properties that are useful for improving sensing capabilities (e.g., limit of detection, sensitivity, selectivity, anti‐interference, and electrochemical stability) and huge potential to exploit for conducting immobilization of biological elements. Nanocomposite per se is also a platform for preparing complex composites via combination of the materials mentioned above. Third, miniaturization, integration, and automation of biosensors in fermentation uses are still at its preliminary stage. Although many commercial biosensors have, to a great extent, facilitated the detection of several kinds of constituent, it is uneasy to realize multiple param‐ eter automatic controls for the whole fermentation process. Aside of developing more and more diverse biosensors fit for different targets, testing conditions, microfabrication technol‐

Shandong Provincial Key Laboratory of Biosensors, Biology Institute, Shandong Academy of

[1] Thevenot D R, Toth K, Durst R A, et al. Electrochemical biosensors: recommended definitions and classification. Pure and Applied Chemistry. Chimie pure et appliqué,

[2] Morrison D W G, Dokmeci M R, Utkan D, et al. Biomedical Nanostructures: Clinical Applications of Micro‐ and Nanoscale Biosensors. 2008, John Wiley & Sons, Inc., New

[3] Kauffmann J M, Pravda M, Kauffmann J M. The electrochemical biosensor era.

[4] Nidhi N, Ashutosh C. A colorimetric gold nanoparticle sensor to interrogate biomo‐ lecular interactions in real time on a surface. Analytical Chemistry, 2002, 74(3): 504‐509.

[5] Kleiren E, Ruysschaert J M, Goormaghtigh E, et al. Development of a quantitative and conformation‐sensitive ATR‐FTIR biosensor for Alzheimer's disease: the effect of

ogy, and Internet of Things are promising tools for achieving this goal.

1999, 71 (12): 2333‐2348. DOI: 10.1351/pac199971122333

Jersey. DOI: 10.1002/9780470185834.ch17

Analytical Chemistry, 2012, 84(2): 685‐707.

DOI: 10.1021/ac015657x

, Derong Feng and Yiwei Li

\*Address all correspondence to: shijg@sdas.org

Sciences, Jinan, Shandong, China

**Author details**

Jianguo Shi\*

154 Fermentation Processes

**References**


[30] Sheliakina M, Arkhypova V, Soldatkin O, et al. Urease‐based ISFET biosensor for arginine determination. Talanta, 2014(121): 18–23. DOI: 10.1016/j.talanta.2013.12.042.

[18] Labroo P, Cui Y. Amperometric bienzyme screen‐printed biosensor for the determina‐ tion of leucine. Analytical & Bioanalytical Chemistry, 2014, 406(1): 367‐372. DOI:

[19] Mangombo Z A, Key D, Iwuoha E I, et al. Development of L‐phenylalanine biosensor and its application in the real samples. In Science Journal, 2013, 03(01): 1‐23. DOI:

[20] Kanchana P, Lavanya N, Sekar C. Development of amperometric L‐tyrosine sensor based on Fe‐doped hydroxyapatite nanoparticles. Materials Science & Engineering C,

[21] Villalonga R, Fujii A, Shinohara H, et al. Supramolecular‐mediated immobilization of L‐ phenylalanine dehydrogenase on cyclodextrin‐coated Au electrodes for biosensor applications. Biotechnology Letters, 2007, 29(3): 447‐452. DOI: 10.1007/s10529‐006‐9259‐4.

[22] Villarta R L, Cunningham D D, Guilbault G G. Amperometric enzyme electrodes for the determination of L‐glutamate. Talanta, 1991, 38(1): 49‐55. DOI:

[23] Wolf M E. The role of excitatory amino acids in behavioral sensitization to psychosti‐ mulants. Progress in Neurobiology, 1998, 54(6): 679‐720. DOI: 10.1016/

[24] Chen Y, Feng D, Bi C Y, et al. Recent progress of commercially available biosensors in China and their applications in fermentation processes. Journal of Northeast Agricul‐

[25] Basu A K, Chattopadhyay P, Roychudhuri U, et al. A biosensor based on co‐immobi‐ lized L‐glutamate oxidase and L‐glutamate dehydrogenase for analysis of monosodi‐ um glutamate in food. Biosensors & Bioelectronics, 2006, 21(10): 1968‐1972. DOI:

[26] Rita M, Hann C a, Youssef S. Amperometric and impedimetric characterization of a glutamate biosensor based on Nafion and a methyl viologen modified glassy carbon electrode. Biosensors & Bioelectronics, 2007, 22(11): 2682‐2688. DOI: 10.1016/j.bios.2006.11.003. [27] Tang L H, Zhu Y H, Xu L H, et al. Amperometric glutamate biosensor based on self‐ assembling glutamate dehydrogenase and dendrimer‐encapsulated platinum nano‐ particles onto carbon nanotubes. Talanta, 2007, 73(3): 438‐443. DOI: 10.1016/j.talanta.

[28] Lata S, Pundir C S. L‐amino acid biosensor based on L‐amino acid oxidase immobilized onto NiHCNFe/c‐MWCNT/PPy/GC electrode. International Journal of Biological

[29] Stasyuka N Ye, Gaydaa G Z, Gonchar M V. L‐Arginine‐selective microbial amperomet‐ ric sensor based on recombinant yeast cells over‐producing human liver arginase I. Sensors and Actuators B: Chemical, 2014(204): 515–521. DOI: 10.1016/j.snb.2014.06.112.

Macromolecules, 2013, 54(3): 250–257. DOI: 10.1016/j.ijbiomac.2012.12.004.

tural University, 2014, 21(4): 73‐85. DOI: 10.1016/S1006‐8104(15)30023‐4.

10.1007/s00216‐013‐7443‐7.

10.1016/0039‐9140(91)80008‐N

S0301‐0082(97)00090‐7.

10.1016/j.bios.2005.09.011.

2007.04.008.

2014, 35(2): 85‐91. DOI: 10.1016/j.msec.2013.10.013.

10.5640/insc.030101.

156 Fermentation Processes


**Products from Fermentation Process**

#### **Biogas - Turning Waste into Clean Energy Biogas - Turning waste into clean energy**

Otávio Bravim da Silva, Lucas Silva Carvalho, Otávio Bravim da Silva, Lucas Silva Carvalho,

Gabriela Carneiro de Almeida, Gabriela Carneiro de Almeida,

Juliana Davies de Oliveira, Talita Souza Carmo and Juliana Davies de Oliveira, Talita Souza Carmo and Nádia Skorupa Parachin

Nádia Skorupa Parachin

Additional information is available at the end of the chapter Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/64262

#### **Abstract**

Expertise in biogas production using anaerobic digestion (AD) can offer many benefits in addition to being an alternative source of energy. This process involves plant digesters and provides an alternative destination for biomass that would eventually go unutilized and deposited in a trash heap. The application of the appropriate plant digester technology can generate energy, and the gas produced can be used for many purposes, such as water and space heating, lighting, and grain drying. In this context, agro residues are one of the most abundant energy sources available world wide. Nevertheless, the bioconversion of organic matter to biogas is a complex process of AD that involves many reactions among several microorganisms living in a stable community. Microorganisms from many diverse genera of obligate anaerobes and facultative anaerobes constitute these steps, and four groups are recognized to be the most frequent in biogas production plants. These groups, in order of substrate hydrolysis, are hydrolytic, acidogenic, and acetogenic bacteria, followed by the core group, the methanogenic archaea. All together, they compose the operation of a systematized activity with synergistic effects that ensure the stability of the process.

**Keywords:** anaerobic digestion, methanogens, methane, hydrogen, waste utilization

#### **1. Introduction**

Increased efforts to reduce the utilization of petroleum have encouraged the development of new technologies for the utilization of alternative energy matrices for the production of different compounds such as novel fuels. Among available biofuels, biogas has been produced for over approximately 2000–3000 years for sanitation purposes [1]; however, the first documented

© 2017 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2017 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

generation of biogas comes from a carefully designed installation from England in 1895. The interest in its usage grew during World War II when France and Germany started to build biogas facilities and used them to fuel vehicles and tractors. After the war, interest in biogas waned, but recovered during the oil crisis of 1973 with improved technology. Nowadays, Germany is by far the world leader in biogas generation.

Biogas is generated from anaerobic digestion (AD) in a bioreactor (also called a digester unit). Its production can be done through a batch or continuous process, in one-, two-, or multiphased steps, and it utilizes mainly organic matter from waste as the substrate. It is considered a carbon-neutral biofuel since it uses carbon dioxide that was recently taken up by plants from the atmosphere and is able to return it through the fermentation of waste residues [2]. This biofuel also protects the environment from pathogens by reducing the waste that would rot in the open air, which would have increased the possibility of attracting disease-carrying vectors. Moreover, it considerably reduces air and water pollution, helps the conservation of forests, and replaces inorganic fertilizer with its digested residues [3]. According to the European Union, biogas has the potential to produce 25% of all clean energy. It can be used to produce electricity, heat, and vehicle fuel, thus substituting conventional sources of energy that produce greenhouse gases.

In recent years, biogas production has increased greatly. This can be evidenced by the rapid construction of biogas plants, which have been built exclusively in Europe. The world's biogas production in 2012 reached 17.2 ktoe/year (the equivalent of millions of tonnes of oil per year) and Europe alone produced 60% (about 10.5 ktoe/year) of this amount. In 2013, European Union production grew to 13.4 ktoe/year, a 27.6% increase, and it is expected to reach 33.0 ktoe/ year by 2022. Several European countries face enormous issues related to the excess of organic waste production from industry, agriculture, and households. AD can also contribute to waste minimization by eliminating the accumulation of harmful and persistent wastes while simultaneously lowering prices for waste disposal.

Taking into account the importance of biogas production, this chapter will discuss, in general, the production of this clean energy source. Therefore, the following topics will be addressed: (1) biogas composition; (2) types of substrate used for their production; (3) overview of biogas production; (4) physical and chemical AD; and (5) anaerobic bioreactors. Specifically, greater emphasis will be given to important aspects of fermentation, such as: (1) the microorganisms and the trophic groups involved in each step (hydrolytic bacteria, acidogenic bacteria, acetogenic bacteria, methanogenic groups); (2) factors affecting biogas production efficiency (temperature, pH and chemical aspects of biomass); (3) the biochemical substrates by the population of microorganisms.

The bioreactor types and their strategies for biogas production will be discussed superficially. However, greater emphasis will be given to important aspects of fermentation, such as: (1) the microorganisms involved, and the trophic groups involved in each step (hydrolytic bacteria, acidogenic bacteria, acetogenic bacteria, and methanogenic groups); (2) factors affecting the efficient production of biogas (temperature, pH and chemical aspects of biomass); (3) the biochemical changes in substrates by the microorganism population.

#### **2. Biogas composition**

generation of biogas comes from a carefully designed installation from England in 1895. The interest in its usage grew during World War II when France and Germany started to build biogas facilities and used them to fuel vehicles and tractors. After the war, interest in biogas waned, but recovered during the oil crisis of 1973 with improved technology. Nowadays, Germany is

Biogas is generated from anaerobic digestion (AD) in a bioreactor (also called a digester unit). Its production can be done through a batch or continuous process, in one-, two-, or multiphased steps, and it utilizes mainly organic matter from waste as the substrate. It is considered a carbon-neutral biofuel since it uses carbon dioxide that was recently taken up by plants from the atmosphere and is able to return it through the fermentation of waste residues [2]. This biofuel also protects the environment from pathogens by reducing the waste that would rot in the open air, which would have increased the possibility of attracting disease-carrying vectors. Moreover, it considerably reduces air and water pollution, helps the conservation of forests, and replaces inorganic fertilizer with its digested residues [3]. According to the European Union, biogas has the potential to produce 25% of all clean energy. It can be used to produce electricity, heat, and vehicle fuel, thus substituting conventional sources of energy that produce

In recent years, biogas production has increased greatly. This can be evidenced by the rapid construction of biogas plants, which have been built exclusively in Europe. The world's biogas production in 2012 reached 17.2 ktoe/year (the equivalent of millions of tonnes of oil per year) and Europe alone produced 60% (about 10.5 ktoe/year) of this amount. In 2013, European Union production grew to 13.4 ktoe/year, a 27.6% increase, and it is expected to reach 33.0 ktoe/ year by 2022. Several European countries face enormous issues related to the excess of organic waste production from industry, agriculture, and households. AD can also contribute to waste minimization by eliminating the accumulation of harmful and persistent wastes while

Taking into account the importance of biogas production, this chapter will discuss, in general, the production of this clean energy source. Therefore, the following topics will be addressed: (1) biogas composition; (2) types of substrate used for their production; (3) overview of biogas production; (4) physical and chemical AD; and (5) anaerobic bioreactors. Specifically, greater emphasis will be given to important aspects of fermentation, such as: (1) the microorganisms and the trophic groups involved in each step (hydrolytic bacteria, acidogenic bacteria, acetogenic bacteria, methanogenic groups); (2) factors affecting biogas production efficiency (temperature, pH and chemical aspects of biomass); (3) the biochemical substrates by the

The bioreactor types and their strategies for biogas production will be discussed superficially. However, greater emphasis will be given to important aspects of fermentation, such as: (1) the microorganisms involved, and the trophic groups involved in each step (hydrolytic bacteria, acidogenic bacteria, acetogenic bacteria, and methanogenic groups); (2) factors affecting the efficient production of biogas (temperature, pH and chemical aspects of biomass); (3) the

biochemical changes in substrates by the microorganism population.

by far the world leader in biogas generation.

simultaneously lowering prices for waste disposal.

population of microorganisms.

greenhouse gases.

162 Fermentation Processes



**Table 1.** Approximate percentage of biogas components [4].

The main cause of the high variation in percentages of biogas composition (**Table 1**) is due to the substrate utilized. The fact that methane is present at high concentration makes biogas a very attractive source of energy considering that methane has a heating value of 8500 kcal/m3 and that CO2 has no energy associated with it. The heating value of biogas is on average 5000– 7000 kcal/m3 , approaching nearly 12,000 kcal/m3 when in a high degree of purity (65% CH4). Comparatively, a cubic meter of biogas has the same calorific power as 0.613 L of gasoline, 0.579 L of kerosene, 0.553 L of diesel, 0.454 L of cooking gas, 1.536 kg of wood, and 0.790 L of ethanol and produces the equivalent power of 1.4208 kW.

Typically, 0.2–3% of biogas is composed of gases that enter the digester with air included in the substrate (N2 and O2). Among these, nitrogen and CO2 (produced during the digestion process) are included in the inert gases that compose the total biogas mix. On the other hand, the remaining NH3, O2, and H2S gases are unwanted gases due to their toxicity to strict anaerobes that are essential for the process. Both O2 and H2S can be removed from biogas through chemical processes such as iron based processes, for example, with the addition of iron chloride, while NH3 can be degassed through an H2SO4 absorber.

Another component, hydrogen sulfide (H2S), is normally present in biogas as a by-product from anaerobic digestion. It is considered a major cause of corrosion of metal parts and degradation of engine oil, and during the fermentation process, it can precipitate metal elements. This gas is prevenient to the degradation of sulfur-containing proteins (i.e., cysteine and methionine), and besides being prevenient to normal metabolism of fermentation organisms, it has to be removed from the biogas before utilization.

#### **3. Types of substrates**

The most utilized residues for biogas production are found in animal manure, agriculture residues, and general organic wastes from food (both vegetable and animal in origin), organic fractions of municipal waste and from catering, sewage sludge and residues from crops dedicated to energy (i.e., biofuels), such as sugar cane and sorghum. These can be classified into various criteria: its origin, organic content, methane yield and dry matter content (**Table 2**). These substrates usually have a high content of sugar, starch, proteins, or fats, which are decomposed through AD. **Table 2** shows several substrates and their classifications according to organic content, carbon:nitrogen ratio, percentage of dry matter, percentage of volatile solids in dry matter, and its biogas yield [5]. It is noticeable how the utilization of different biomasses has a consequence in the biogas yield, for example, it can vary from 0.15 m3 /kg VS (volatile solids) (utilizing straw) to 0.9 m3 /kg VS. When the utilized substrate is concentrated whey, a


a Dry matter.b Volatile solids. NR, not reported.

**Table 2.** Substrates commonly utilized for biogas production, its composition, and average biogas yield [5].

500% increase in growth can be observed (**Table 2**). Generally, the C:N ratio also affects the production of biogas. As can be seen in **Table 2**, low C:N ratios (between 3 and 20) produce a yield ranging between 0.25 and 0.78 m3 /kg VS. Higher C:N ratios (above 20, reaching up to 150) do not produce greater yields, since the greater yield obtained is 0.56 m3 /kg VS, approximately 30% lower than that obtained at lower C:N ratios.

In spite of the numerous advantages of utilizing biogas digesters, there are still challenges that need to be overcome in order to maximize fuel production. Methanogenic archaea, microorganisms that produces methane, have specific requirements such as temperature and pH, and they must be maintained within specific ranges for optimal production, which increases the production cost of biogas [6]. Another challenge is hydraulic retention time (HRT), which is the normal time that the input substrate spends in the digester before it is removed. At tropical temperatures, the HRT is 30–50 days, although in colder atmospheres, it may go up to 100 days without heating, which requires a bigger digester volume and raises costs. While digesters can save energy at small-scale production on farms, finding the right economic balance for largescale production is yet another challenge.

#### **4. Overview of biogas production**

**3. Types of substrates**

164 Fermentation Processes

solids) (utilizing straw) to 0.9 m3

a

Dry matter.b

Volatile solids. NR, not reported.

The most utilized residues for biogas production are found in animal manure, agriculture residues, and general organic wastes from food (both vegetable and animal in origin), organic fractions of municipal waste and from catering, sewage sludge and residues from crops dedicated to energy (i.e., biofuels), such as sugar cane and sorghum. These can be classified into various criteria: its origin, organic content, methane yield and dry matter content (**Table 2**). These substrates usually have a high content of sugar, starch, proteins, or fats, which are decomposed through AD. **Table 2** shows several substrates and their classifications according to organic content, carbon:nitrogen ratio, percentage of dry matter, percentage of volatile solids in dry matter, and its biogas yield [5]. It is noticeable how the utilization of different biomasses

/kg VS. When the utilized substrate is concentrated whey, a

 **(%) VSb (% of DM)** 

/kg VS (volatile

**Biogas (yield**

**/kg VS)** 

**m3**

has a consequence in the biogas yield, for example, it can vary from 0.15 m3

Pig slurry Carbohydrates, proteins, lipids 3–10 3–8 70–80 0.25–0.50 Cattle slurry Carbohydrates, proteins, lipids 6–20 5–12 80 0.20–0.30 Poultry slurry Carbohydrates, proteins, lipids 3–10 10–30 80 0.35–0.60 Stomach/intestine content Carbohydrates, proteins, lipids 3–5 15 80 0.40–0.68 Whey 75–80% lactose, 20–25% protein NR 8–12 90 0.35–0.80 Concentrated whey 75–80% lactose, 20–25% protein NR 20–25 90 0.80–0.90 Flotation sludge 65–70% proteins, 30–35% lipids NR NR NR NR Fermented slops Carbohydrates 4–10 1–5 80–95 0.35–0.78 Straw Carbohydrates, lipids 80–100 70–90 80–90 0.15–0.35 Garden wastes NR 100–150 60–70 90 0.20–0.50 Grass NR 12–25 20–25 90 0.55 Grass silage NR 10–25 15–25 90 0.56 Fruit wastes NR 35 15–20 75 0.25–0.50 Fish oil 30–50% lipids NR NR NR NR Soya oil/margarine 90% vegetable oil NR NR NR NR Alcohol 40% alcohol NR NR NR NR Food remains NR NR 10 80 0.50–0.60

**Table 2.** Substrates commonly utilized for biogas production, its composition, and average biogas yield [5].

**Biomass type Organic content C:N ratio DMa**

Biogas production is an established process in which there is little information available on the microorganisms involved using different wastes. Thus, an understanding of the microorganisms' activity and the factors that can influence biogas composition are crucial in order to maximize fermentation performance and reduce process costs. Therefore, in order to discover which microorganisms are involved in anaerobic digestion, sequencing of 16SrRNA and metagenomics [7] has been performed, as well as the analysis of the methyl-coenzyme M reductase encoding gene, as this is a marker for identification of archaea that are specifically methanogenic [8]. DNA isolated from different bioreactors using different substrates demonstrated a very direct link between reactor type and taxonomic groups. For example, in a stirred digester fed with fodder beet silage, mainly Bacilli, Clostridiales, Deltaproteobacteria, and Bacteroidetes have been found [9], while the microbial population of a thermophilic digester described in another study was particularly rich in Clostridia [10]. Another important relationship is the microorganism present according to the physical location of the digester [11]. The results of several studies inferred that, in the first and second phases of AD, at least 58 species of 18 genera are involved, which categorize biogas production as mixed fermentation.

#### **4.1. Microorganisms and the biochemistry of AD**

The production of biogas is performed by a microbial consortium through four main reactions: hydrolysis, acidogenesis, acetogenesis, and methanogenesis, where organisms from the bacteria and archaea domains are involved in consortia that lead to substrate conversion into CH4 and CO2 among other gases. The microorganism types involved and an overview of the substrate process are illustrated in **Figure 1**.

**Figure 1.** Microorganisms involved in each catabolic step during biogas biosynthesis.

#### *4.1.1. Hydrolytic bacteria*

Anaerobic digestion starts with the polymer hydrolysis of fats, proteins, and carbohydrates into monomers that are suitable for further digestion. Hydrolytic bacteria, which can be either facultative or strict anaerobes, are capable of hydrolyzing the bonds of these compounds, converting them into oligomers, monomers, amino acids, and unsaturated fats. For example, cellulose [(C6H12O6)*n*], an insoluble substrate commonly found in sludge, is hydrolyzed by bacteria from the genus *Cellulomonas*, resulting in glucose monomers. The hydrolysis of polymers that are difficult to decompose restrains the rate of waste processing, and just half of these compounds experience hydrolysis in a one-stage digester. In some cases, pretreatment involving an aerobic step can be added. The concept of aerobic treatment consists in the knowledge that some aerobic microorganisms can produce hydrolytic enzymes that are able to generate monomers from the polymers present in the biomass. Moreover, inhibitory macromolecules such as lignin may also be transformed, resulting in a less toxic substrate to the microorganisms that start the AD process [12].

Anaerobic digesters that utilize substrates derived from wastewater treatment from industry, such as dairy and agro industries, are usually composed of soluble organic compounds and therefore do not experience this kind of hydrolysis. However, different sugars such as sucrose and lactose must be hydrolyzed despite being soluble, since they are larger than most cells can absorb [13].

#### *4.1.2. Acidogenic bacteria*

In regard to the second reaction stage, acidogenic bacteria will then convert these molecules into volatile fatty acids (VFAs) with high carbon numbers such as butyrate, propionate, and alcohols in addition to CO2, H2, and acetate [14]. These biochemical steps depend on various factors, like pH, enzyme production by bacteria, diffusion, and adsorption of enzymes by the biomass undergoing the process of digestion. This is executed by microorganisms from the group of anaerobic bacteria of genera such as *Streptococcus* and *Enterobacteria*.

However, VFAs produced during this stage may negatively affect the AD process depending on its concentration in the bioreactor. When unstable, the AD process accumulates VFAs inside the reactor, which results in a drop of pH-value and consequently a decrease in methane yield. This is explained by the low tolerance of methanogenic archaea in an acidic environment. It is demonstrated that different digesters can react differently in response to the same amount of VFA, where, in one digester, the concentration may be optimal and, in another, it is a considerable inhibitor to methane production. One conceivable explanation is the microorganism population, which varies from digester to digester. It can also be explained by the buffering capacity of the substrate.

#### *4.1.3. Acetogenic bacteria*

**Figure 1.** Microorganisms involved in each catabolic step during biogas biosynthesis.

166 Fermentation Processes

For the third reaction stage, acetogenic bacteria convert VFAs into acetate. Acetogenic bacteria are obligate proton-reducing bacteria (OPR) and are known for the production of H2 during acetate production. Some VFA conversions are displayed below in Eq. (1):

$$\begin{aligned} \text{propionate} + 3\text{H}\_{2}\text{O} &\rightarrow \text{acetate} + \text{HCO}\_{3}^{-} + \text{H}^{+} + 3\text{H}\_{2}\Delta G = +76.1 \,\text{kJ/mole} \\ \text{butyrate} + 2\text{H}\_{2}\text{O} &\rightarrow 2\text{acetate} + \text{H}^{+} + 2\text{H}\_{2}\Delta G = +48.1 \,\text{kJ/mole} \\ \text{ethanol} + 2\text{H}\_{2}\text{O} &\rightarrow \text{acetate}^{-} + \text{H}^{+} + 2\text{H}\_{2}\Delta G = +9.6 \,\text{kJ/mole} \end{aligned} \tag{1}$$

In accordance with the examples above, it is important to note that all of them require energy input. However, in the presence of low hydrogen concentrations provided by the digester, the reaction moves to the product side to maintain equilibrium. To this end, they only live in coexistence with a H2, utilizing species, which are the methanogenic archaea. A genus such as *Desulfovibrio* oxidizes alcohols and organic acids into acetate and transfers the electrons released to sulfate. Genera such as A*minobacterium* and A*cidaminococcus* ferment amino acids, trans-aconitate and citrate into acetate, CO2, and H2. Sulfate-reducer organisms such as the acetogenic *Desulfovibrio*, which oxidizes organic acids and alcohols to acetate and transfers the released electrons to sulfate resulting in a higher energy yield than fermentation, are deeply involved in compound decomposition by AD. These bacteria form cultures from obligated and facultative anaerobes to ferment available substrates such as lactate and alcohol from the acidogenic step.

#### *4.1.4. Methanogenic group*

The last phase of anaerobic digestion is catalyzed by a group of microorganisms from the archaea group. This group is subdivided into two groups: a hydrogenotrophic methanogenic group and aceticlastic methanogenic group. The first group utilizes the H2 produced by the OPR group. Their affinity to uptake hydrogen is on the order of parts per million, making them very efficient in maintaining the substrate with a very low hydrogen partial pressure. The aceticlastic methanogenic group consists of only two genera: *Methanosarcina* and *Methano‐ thrix*. These microorganisms can produce methane from acetic acid, and approximately 70% of all methane produced in biogas reactors originates from this conversion. The reactions of the processes are displayed below (Eqs. (2) and (3)).

$$\text{CH}\_2 + 4\text{H}\_2 \rightarrow \text{CH}\_4 + 2\text{H}\_2\text{O} \tag{2}$$

$$\text{CH}\_3\text{COOH} \rightarrow \text{CH}\_4 + \text{CO}\_2\tag{3}$$

Methanogenic archaea have, in their metabolism, the enzyme methyl-CoM reductase. This hexamer is a large complex composed by two copies of three different subunits (*α, β*, and *γ*) containing a unique coenzyme, the nickel phorphinoid factor F430 and with activity deep inside the complex for protection from the surrounding water. This complex catalyzes the release of the CH4 from methyl-CoM [15]. The F430 ring needs a nickel atom that is stabilized in the reactive state, which is an important property of this enzyme because the substrate methyl-coenzyme M is rather inert, which makes the reaction easier.

Acetoclastic archaea are well known for their slow doubling time (1–12 days in thermophilic conditions) because of their relative inefficiency in taking up acetate, but on the other hand, hydrogenotrophic methanogenic bacteria are extremely productive and have moderately quick doubling times (0.5–2 days in thermophilic conditions) [16].

#### **5. Physical and chemical AD parameters**

The growth and metabolism of anaerobic microorganisms are essentially impacted by physical and chemical conditions such as temperature, pH value, nutrient supply, mixing intensity, and the additional presence of inhibitors.

#### **5.1. Temperature**

+

*G G*

*G*

CO 4H CH 2H O 22 42 +® + (2)

CH COOH CH CO <sup>3</sup> ® +4 2 (3)

(1)

2 2 3

+

propionate 3H O acetate HCO H 3H 76.1kJ/mole

+ ® + + + D =+


In accordance with the examples above, it is important to note that all of them require energy input. However, in the presence of low hydrogen concentrations provided by the digester, the reaction moves to the product side to maintain equilibrium. To this end, they only live in coexistence with a H2, utilizing species, which are the methanogenic archaea. A genus such as *Desulfovibrio* oxidizes alcohols and organic acids into acetate and transfers the electrons released to sulfate. Genera such as A*minobacterium* and A*cidaminococcus* ferment amino acids, trans-aconitate and citrate into acetate, CO2, and H2. Sulfate-reducer organisms such as the acetogenic *Desulfovibrio*, which oxidizes organic acids and alcohols to acetate and transfers the released electrons to sulfate resulting in a higher energy yield than fermentation, are deeply involved in compound decomposition by AD. These bacteria form cultures from obligated and facultative anaerobes to ferment available substrates such as lactate and alcohol from the

The last phase of anaerobic digestion is catalyzed by a group of microorganisms from the archaea group. This group is subdivided into two groups: a hydrogenotrophic methanogenic group and aceticlastic methanogenic group. The first group utilizes the H2 produced by the OPR group. Their affinity to uptake hydrogen is on the order of parts per million, making them very efficient in maintaining the substrate with a very low hydrogen partial pressure. The aceticlastic methanogenic group consists of only two genera: *Methanosarcina* and *Methano‐ thrix*. These microorganisms can produce methane from acetic acid, and approximately 70% of all methane produced in biogas reactors originates from this conversion. The reactions of

Methanogenic archaea have, in their metabolism, the enzyme methyl-CoM reductase. This hexamer is a large complex composed by two copies of three different subunits (*α, β*, and *γ*) containing a unique coenzyme, the nickel phorphinoid factor F430 and with activity deep inside the complex for protection from the surrounding water. This complex catalyzes the release of the CH4 from methyl-CoM [15]. The F430 ring needs a nickel atom that is stabilized in the reactive state, which is an important property of this enzyme because the substrate methyl-coenzyme

2 2 2 2

acidogenic step.

168 Fermentation Processes

*4.1.4. Methanogenic group*

the processes are displayed below (Eqs. (2) and (3)).

M is rather inert, which makes the reaction easier.

+ ® + + D =+ + ® + + D =+

butyrate 2H O 2acetate H 2H 48.1kJ/mole ethanol 2H O acetate H 2H 9.6 kJ/mole


A large portion of reactor cost comes from the energy spent to maintain its temperature stable. Thus, an optimum temperature setting is the most critical factor in temperate countries since more energy is needed to maintain the temperature of AD and consequently methane production. Temperature parameters for AD can take place at different levels: cryophilic (below 25 °C) mesophilic (25–45 °C), and thermophilic (45–70°C). There is an inverse relationship between the temperature range and the HRT, meaning that thermophilic digesters have a shorter retention time than mesophilic and cryophilic ones.

Many facilities operate their biodigesters at the optimum temperature of thermophilic microorganisms because this reduces number of pathogens, favors methanogenic bacteria growth, improves the separation of liquid and solid fractions, and improves degradation of the substrate since there is more metabolic activity. Moreover, the methane production in thermophilic digesters is 25% greater than in mesophilic digesters. Nevertheless, the utilization of thermophilic temperatures also has disadvantages such as a higher degree of imbalance due to an increased production of volatile fatty acids. When dealing with manure, for example, reactors had optimal production in mesophilic reactors with the temperature between 30 and 35 °C, with only a 3% difference in the methane yield between these two temperatures. The same substrate at 25 °C had a decrease in methane yield of 17.4% [17]. In another study, two reactors, a one-stage reactor operated at mesophilic temperatures and a two-stage reactor operated at thermophilic (first stage) and mesophilic (second stage) temperatures, had their volatile solid consumption compared. The results demonstrated that a thermophilic (60 °C) stage was especially effective in degrading sludge waste substrates, with a 35% reduction in VFAs compared to the one-stage mesophilic digester.

#### **5.2. pH**

The pH value of utilized substrates affects AD by influencing the methanogenic-organisms' doubling time. Moreover, pH also influences the dissociation of some important compounds, such as ammonia, sulfide, and some organic acids. Methane generation takes place in the range of 5.5–8.5 pH, with optimal production in the 7.0–8.5 pH range. Most of the problems in AD can be attributed to acid accumulations and a consequent drop in the pH value. Considering that CO2 solubility decreases when the temperature increases, the pH of thermophilic reactors is higher than mesophilic ones and therefore has less carbon dioxide dissolved in carbonic acid form, making it more endurable for methanogenic groups. In a two-phase digester, the hydrolytic-acidogenic and acetogenic phases are separated from methanogenesis, and with this, the pH can be controlled to the optimum range for the first phase (4.0–6.0) and second phase (7.0–8.5). In a single-phase reactor, the pH is usually maintained around the tolerance of the methanogenic group (6.6–8.0) since the other population groups of organisms can tolerate these conditions [18].

#### **5.3. Ammonia**

Nitrogen in the form of ammonia (NH4) is present in the environment of the digester as a gas. It originates from protein degradation and from animal slurry, due to its high ammonia concentration. The precise concentration of free ammonia at which it starts to be toxic remains uncertain, but when dealing with a non-adapted digester (i.e., a digester that has not had enough time to acclimate its methanogenic population to a high ammonia concentration), its inhibition starts at 0.08–0.15 gN/L of free ammonia and 2.5 gN/L of total ammonia. In an adapted digester, it is 0.7–1.1 gN/L of free ammonia and 4–6.5 gN/L of total ammonia [19]. Methanogenic bacteria are very sensitive to the presence of ammonia as its presence can disturb the process in two forms, (1) inhibiting methanogenic enzymes in archaea and (2) entering the archaea cell and causing an unbalance in the electrons and disrupting the process [20].

#### **5.4. Micronutrients (trace elements)**

The impact of trace elements and changes in its concentration in bioreactors depends on various factors, such as the microbial community structure; population dynamics; individual trophic group metabolism; and meta-community (e.g., the microbial community as a group, incorporating compounds as well as cells). With that in mind, it is hard to fix micronutrient concentrations that are fully satisfactory for the microorganisms' community present in the reactor.

Although nutritional demand for each microorganism species varies, this topic will explore general guidelines of micronutrients, which are limiting for methane-forming archaea. These microorganisms have specific methanogenic enzyme systems with different requirements when compared to other microorganisms. These systems need specific micronutrients that must be incorporated or added to the substrate for its proper degradation and efficiency of CH4 production.

Cobalt, iron, nickel, and sulfide are obligatory micronutrients, because they are cofactors of the methane pathway enzymes that convert acetate into methane. In some cases, molybdenum, tungsten, and selenium can be obligatory micronutrients as well as barium, calcium, magnesium, and sodium [21].

These micronutrients are usually present in municipal wastewater, although the digester effluent, in some cases, must be analyzed to ensure their presence in enough quantities and guarantee that these nutrients are in a soluble form since micronutrient deficiency can be mistaken with toxicity from the accumulation of volatile fatty acids.

Simple variations in the amounts of elements can disturb the environment inside the digester by unbalancing the substrate process and then causing inhibition of the whole process. For example, under co-limiting conditions, methanogenic activity was lost within ten days by acidification of a methylotrophic digester. In other study, Zn deprivation affected methane production significantly, which could not be later restored by a continuous supply of Zn [22].

#### **6. Anaerobic bioreactors**

that CO2 solubility decreases when the temperature increases, the pH of thermophilic reactors is higher than mesophilic ones and therefore has less carbon dioxide dissolved in carbonic acid form, making it more endurable for methanogenic groups. In a two-phase digester, the hydrolytic-acidogenic and acetogenic phases are separated from methanogenesis, and with this, the pH can be controlled to the optimum range for the first phase (4.0–6.0) and second phase (7.0–8.5). In a single-phase reactor, the pH is usually maintained around the tolerance of the methanogenic group (6.6–8.0) since the other population groups of organisms can

Nitrogen in the form of ammonia (NH4) is present in the environment of the digester as a gas. It originates from protein degradation and from animal slurry, due to its high ammonia concentration. The precise concentration of free ammonia at which it starts to be toxic remains uncertain, but when dealing with a non-adapted digester (i.e., a digester that has not had enough time to acclimate its methanogenic population to a high ammonia concentration), its inhibition starts at 0.08–0.15 gN/L of free ammonia and 2.5 gN/L of total ammonia. In an adapted digester, it is 0.7–1.1 gN/L of free ammonia and 4–6.5 gN/L of total ammonia [19]. Methanogenic bacteria are very sensitive to the presence of ammonia as its presence can disturb the process in two forms, (1) inhibiting methanogenic enzymes in archaea and (2) entering the archaea cell and causing an unbalance in the electrons and disrupting the process [20].

The impact of trace elements and changes in its concentration in bioreactors depends on various factors, such as the microbial community structure; population dynamics; individual trophic group metabolism; and meta-community (e.g., the microbial community as a group, incorporating compounds as well as cells). With that in mind, it is hard to fix micronutrient concentrations that are fully satisfactory for the microorganisms' community present in the

Although nutritional demand for each microorganism species varies, this topic will explore general guidelines of micronutrients, which are limiting for methane-forming archaea. These microorganisms have specific methanogenic enzyme systems with different requirements when compared to other microorganisms. These systems need specific micronutrients that must be incorporated or added to the substrate for its proper degradation and efficiency of

Cobalt, iron, nickel, and sulfide are obligatory micronutrients, because they are cofactors of the methane pathway enzymes that convert acetate into methane. In some cases, molybdenum, tungsten, and selenium can be obligatory micronutrients as well as barium, calcium, magne-

These micronutrients are usually present in municipal wastewater, although the digester effluent, in some cases, must be analyzed to ensure their presence in enough quantities and

tolerate these conditions [18].

**5.4. Micronutrients (trace elements)**

**5.3. Ammonia**

170 Fermentation Processes

reactor.

CH4 production.

sium, and sodium [21].

The biodigester (or anaerobic bioreactors) must guarantee optimal conditions for feedstock transformation to occur, such as the retention of the active biomass and favorable environmental conditions for biomass degradation of organic matter [23]. A report, dating from the 1880s, presents a biodigester, named by its inventor, Donald Cameron (Exeter, England), as a "Septic Tank," which was much more efficient than previous, and more rudimentary tanks since its design promoted microbial growth by adopting an organic material entry and exit system below water level in order to minimize the entry of air and turning of the upper part of the tank [24]. The precursor tank, called the "automatic scavenger," was built by Jean Louis M. Mouras, author of the first reference to the liquefaction of organic matter of wastewater under anaerobic conditions (patented in 1881) [24]. However, it is worth noting that this is not the first AD bioreactor, but one of the first reports in the literature.

The increase in demand of organic matter degradation has allowed for further development of these bioreactors, such as the addition of a heating system [25] and mechanical agitation– – Patent US2605220 [26]. Additionally, there are many studies regarding bioreactor design and the way the digestion is conducted, as described in the next Section (6.1).

#### **6.1. Bioreactors types**

The digestion unit is the most important part of a biogas plant; after all, it is where organic matter is reduced into biogas by microorganisms. An anaerobic digester design should allow for a continuously high load rate of organic matter, short hydraulic retention time (to reduce bioreactor volume), and a maximization of methane production. The shape of the bioreactor should take important considerations into account, such as the exchange of heat and the mixture, which is not observed in underground reactors (**Figure 2**). In general, these bioreactors are built from concrete blocks in a rectangular or square shape format that does not benefit the mixture. Furthermore, they have accumulated points (edges) of raw materials that lead to reduction in plant efficiency and require more frequent maintenance and thus idle time [27].

**Figure 2.** Underground reactor.

The choice of bioreactor for biogas production will depend directly on the characteristics of the raw materials utilized such as dry matter content, rate of degradation, and risk of inhibition. Among the main processing technology options available, there are feeding systems, reactor type, temperature reactor, number of phases, and agitation system (**Figure 3**) [28]. Nevertheless, only the most frequently used options of reactor type and number of phases will be described in more detail in this chapter.

**Figure 3.** Fermentation modes utilized for biogas production batch digester—one-stage continuously fed system (A); two- or multistage continuously fed system: first stage (B) and second stage (C).

They may be dry or wet, batch or continuous, one step or multistep, and one phase or multiphase and may operate under different temperature conditions (mesophilic or thermophilic). However, the main bioreactor groups commonly employed are as follows: (1) batch bioreactors (**Figure 3A**); (2) continuous fed system: (a) one stage (**Figure 3B**); and (b) two stage or multistage [29] (**Figure 3C**).

#### *6.1.1. Batch bioreactors*

In this type of system (**Figure 3A**), a digestion vessel is loaded once with the feedstock then sealed off and left to ferment until gas production decreases. Then, the bioreactor is emptied and filled again with a new batch of feedstock. It is worth noting that part of the digestate should be left in the vessel, which will serve as inoculum for the next batch [30]. This type of bioreactor is generally utilized for feedstock that has a high solid content (between 30 and 40%) and with a high fiber content [31], and it requires little daily attention and it is notable for its simplicity. Moreover, batch reactors may be more suitable when using small amounts of substrate [32].

However, batch bioreactors have some limitations, for example (1) high variation in gas quality and production; thus, a series of batch digesters are employed, which are fed sequentially to generate a reasonably homogenous production of biogas; (2) a considerable time requirement to empty and load the batch digesters; (3) biogas losses during discharging the bioreactors; and (4) limited bioreactor heights [29]. The production of methane may vary from 44.6 to 290 mL/g VS for yard trimmings and rice straw as substrate, respectively [2].

#### *6.1.2. Continuously fed system*

**Figure 2.** Underground reactor.

172 Fermentation Processes

described in more detail in this chapter.

or multistage [29] (**Figure 3C**).

The choice of bioreactor for biogas production will depend directly on the characteristics of the raw materials utilized such as dry matter content, rate of degradation, and risk of inhibition. Among the main processing technology options available, there are feeding systems, reactor type, temperature reactor, number of phases, and agitation system (**Figure 3**) [28]. Nevertheless, only the most frequently used options of reactor type and number of phases will be

**Figure 3.** Fermentation modes utilized for biogas production batch digester—one-stage continuously fed system (A);

They may be dry or wet, batch or continuous, one step or multistep, and one phase or multiphase and may operate under different temperature conditions (mesophilic or thermophilic). However, the main bioreactor groups commonly employed are as follows: (1) batch bioreactors (**Figure 3A**); (2) continuous fed system: (a) one stage (**Figure 3B**); and (b) two stage

two- or multistage continuously fed system: first stage (B) and second stage (C).

For continuous digesters, unlike the batch bioreactors, the feedstock is constantly fed mechanically or by flow force by the newly entered feedstock, enabling uninterrupted production of biogas [33]. Among the types of continuous digesters, the multiple tank system (or multistage system) stands out, which will now be described.

#### *6.1.2.1. One‐stage, two‐stage, or multistage continuous fed system*

As previously discussed in this chapter (Section 4.1), there are four biochemical reactions in anaerobic digestion: hydrolysis, acidogenesis, acetogenesis, and methanogenesis. When all of these biochemical reactions take place in one reactor, it is called a one-stage continuously fed system (**Figure 3B**), in contrast, when the biochemical reactions occurs separately in two reactors, it is called a two-stage (or multistage) continuously fed system (**Figure 3C**) [27].

Organic waste treatment systems that use the two-stage system present advantages over onestage systems, such as high biogas production rates and yields. One study demonstrated a 13% increase in methane production from cellulosic material in a process that used a two-stage process compared to a single phase [34]. A similar increase was obtained using olive mill solid residues as the substrate [35]. Another study [36] compared one- and two-stage digestions for the treatment of thin stillage. It obtained approximately 57% total volatile fatty acids to the total chemical oxygen demand ratio, while the digestion obtained from one stage is only 10%. Additionally, the use of two-stage digestion also increased the production of methane, from 0.26 L CH4 /g of the chemical oxygen demand added (one stage) to 0.33 L CH4/g of the chemical oxygen demand added [36]. This is because the system that performs the separation stages of the biochemical anaerobic digestion benefits the selection and development of different microorganisms for each stage. In addition, the conditions in each respective phase are controlled to generate an optimal environment for the action of each microorganism [37].

Acidogenic bacteria are the prevailing microorganisms in the first stage while the methanogenic group is dominant in the second one. In addition, as previously discussed, the intense production of acids inhibits methane formation in a one-phase system. Hence, the second stage favors bacteria that perform the production of methane gas [28]. The multiple-step system allows a faster, higher performance, and less expensive process than those that use single-stage digester, even though multistage digesters were more expensive to build and maintain [38]. The methane yield from municipal solid waste using a two-stage reactor can be 21% greater than the methane yield obtained from a single-stage process [39].

#### **6.2. Microorganisms retention**

In general, the generation time of hydrolytic and acidogenic bacteria ranges from approximately 1–3 days, whereas methanogenic and acetogenic bacteria range from about 1–4 and 5– 12 days, respectively [13]. Due to the slow growth of microorganisms during the process of digestion, a reactor operated in a continuous mode can result in washout. Therefore, the rate of loading and unloading cannot exceed the maximum growth rate of microorganisms. In addition, the calculation of this rate is one of goals of process optimization. Additionally, one other way to prevent this type of accident is to use immobilized cells [19]. The use of microbial consortium retention contributes to increased performance of the anaerobic phase [40]. The use of support material such as toasted coconut shells and wood chips produced 720 and 144 L/kg VS of biogas, respectively, while the use of expanded clay showed nearly no production [40].

Anaerobic filters use inert supporting materials such as clay fibers, polyvinyl-chloride sheets, polyurethane foam, polypropylene membranes, carbon fiber textiles, tire rubber, zeolite filters, glass, and polyethylene fibers [40]. It is practical at this point to highlight that not only is the type of support material directly related to the performance of the anaerobic reactor, but so are other factors such as specific surface area, porosity, surface roughness, pore size, and orientation of the packaging material [40].

Microbial immobilization on the surface and in the pores of the inert material allows a reduction in the hydraulic residence time, which can decrease from 30 days to under a week, and it consequently reduces reactor volume and initial cost and increases the yield [32]. Among the used systems are (1) fixed- or packed-bed reactors and (2) fluidized-bed reactors (**Figure 4**).

#### *6.2.1. Fixed‐bed reactors*

In its initial application, the fixed-bed system was used as biological filters for sewage treatment, so it is also known as an anaerobic filter (similarly called a biofilm reactor or packed bed). In this system, the particles containing the immobilized cells are fixed or packed into the reactor and the liquid flows through the bed. The fixed-bed reactor (**Figure 4A**) allows the application of greater organic loads than those applied in the complete mixture of anaerobic digesters. This system uses one kind of reactor that maintains a high biomass density within the reactor through microorganism retention from biofilms that have developed on the support material [32].

**Figure 4.** Microorganisms' retention reactors: (A) fixed-bed reactor and (B) fluidized-bed reactor.

#### *6.2.2. Fluidized‐bed reactors*

Acidogenic bacteria are the prevailing microorganisms in the first stage while the methanogenic group is dominant in the second one. In addition, as previously discussed, the intense production of acids inhibits methane formation in a one-phase system. Hence, the second stage favors bacteria that perform the production of methane gas [28]. The multiple-step system allows a faster, higher performance, and less expensive process than those that use single-stage digester, even though multistage digesters were more expensive to build and maintain [38]. The methane yield from municipal solid waste using a two-stage reactor can be 21% greater

In general, the generation time of hydrolytic and acidogenic bacteria ranges from approximately 1–3 days, whereas methanogenic and acetogenic bacteria range from about 1–4 and 5– 12 days, respectively [13]. Due to the slow growth of microorganisms during the process of digestion, a reactor operated in a continuous mode can result in washout. Therefore, the rate of loading and unloading cannot exceed the maximum growth rate of microorganisms. In addition, the calculation of this rate is one of goals of process optimization. Additionally, one other way to prevent this type of accident is to use immobilized cells [19]. The use of microbial consortium retention contributes to increased performance of the anaerobic phase [40]. The use of support material such as toasted coconut shells and wood chips produced 720 and 144 L/kg VS of biogas, respectively, while the use of expanded clay showed nearly no production

Anaerobic filters use inert supporting materials such as clay fibers, polyvinyl-chloride sheets, polyurethane foam, polypropylene membranes, carbon fiber textiles, tire rubber, zeolite filters, glass, and polyethylene fibers [40]. It is practical at this point to highlight that not only is the type of support material directly related to the performance of the anaerobic reactor, but so are other factors such as specific surface area, porosity, surface roughness, pore size, and

Microbial immobilization on the surface and in the pores of the inert material allows a reduction in the hydraulic residence time, which can decrease from 30 days to under a week, and it consequently reduces reactor volume and initial cost and increases the yield [32]. Among the used systems are (1) fixed- or packed-bed reactors and (2) fluidized-bed reactors (**Figure 4**).

In its initial application, the fixed-bed system was used as biological filters for sewage treatment, so it is also known as an anaerobic filter (similarly called a biofilm reactor or packed bed). In this system, the particles containing the immobilized cells are fixed or packed into the reactor and the liquid flows through the bed. The fixed-bed reactor (**Figure 4A**) allows the application of greater organic loads than those applied in the complete mixture of anaerobic digesters. This system uses one kind of reactor that maintains a high biomass density within the reactor through microorganism retention from biofilms that have developed on the support

than the methane yield obtained from a single-stage process [39].

**6.2. Microorganisms retention**

174 Fermentation Processes

orientation of the packaging material [40].

*6.2.1. Fixed‐bed reactors*

material [32].

[40].

In fluidized-bed systems (**Figure 4B**), the supporting material particles are maintained in suspension within the reactor due to substrate flow. This allows the particles to become unrestricted, and therefore, its entire external surface is available for interaction with the feedstock. This type of system has an advantage over packed-bed because we could substrate particulate packed beds. Furthermore, control of the temperature and the pH is more effective than the packed beds [32].

The performance of both reactors (fixed bed and fluidized bed) was compared with that of a fixed-bed reactor under similar conditions (feed gas to steam ratios of 1.5 and 0.75 at a reactor temperature of 750 °C, GHSV (gas hourly space velocity) of 300 L/min) [41]. This study showed a conversion of 75% CH4 in a fixed-bed reactor. On the other hand, when using the fluidizedbed reactor, the production was much greater, reaching up to 90% conversion. The authors of this study reported the low yield of the fixed-bed reactor creates points of temperatures below the optimum process temperatures.

#### **7. Conclusions and perspectives**

Currently, numerous efforts are being made to reduce energy dependence on oil. This requirement has led to the development of new technologies for the use of other energy sources, such as the production of biogas. This biofuel is an important alternative to ensure the supply of clean and affordable energy and to contribute toward reducing the accumulation of waste, as biomass can be used as raw materials for biogas production. However, obtaining high yields is still a major challenge. One solution is to optimize the process, adjusting some of the physical and chemical parameters, such as temperature and pH. This is because this fermentation process involves several microbial groups and therefore needs to be adjusted to the environment of each of these groups. One way to do this is to include fermentation stages, in which more than one reactor is used, allowing the maintenance of optimum conditions for each microbial group involved in each step. Another challenge is the hydraulic retention time, which is the normal time that the input substrate spends in the digester before it is removed. A solution for this is microorganism retention, where they are imprisoned within inert materials, allowing the microorganisms to remain longer inside the reactor. It is worth noting that a deeper understanding of the physiology of each microbial gender participating in the process should be performed in order to be able to more precisely optimize the process parameters. Finally, despite biogas production being an age-old process, little is known about this process. Therefore, further studies on this process are necessary to achieve greater production and thus more amplified outcomes of this process.

#### **Author details**

Otávio Bravim da Silva1 , Lucas Silva Carvalho1 , Gabriela Carneiro de Almeida1,2, Juliana Davies de Oliveira2 , Talita Souza Carmo1 and Nádia Skorupa Parachin1\*

\*Address all correspondence to: nadiasp@gmail.com

1 Group of Applied Metabolic Engineering to Bioprocess, Institute of Biological Sciences, University of Brasilia, Brasilia-DF, Brazil

2 Postgraduate in Genomic Sciences and Biotechnology, Catholic University of Brasilia, Brasilia-DF, Brazil

#### **References**

[1] Deublein D, Steinhauser A. Biogas from waste and renewable resources: an introduction, 2nd ed. Weinheim, Germany: Wiley-VCH; 2010. doi:10.1002/9783527632794.

[2] Mao C, Feng Y, Wang X, Ren G. Review on research achievements of biogas from anaerobic digestion. Renew. Sustain. Energy Rev. 2015; 45:540–555. doi:10.1016/j.rser. 2015.02.032.

**7. Conclusions and perspectives**

176 Fermentation Processes

production and thus more amplified outcomes of this process.

\*Address all correspondence to: nadiasp@gmail.com

University of Brasilia, Brasilia-DF, Brazil

, Lucas Silva Carvalho1

, Talita Souza Carmo1

1 Group of Applied Metabolic Engineering to Bioprocess, Institute of Biological Sciences,

2 Postgraduate in Genomic Sciences and Biotechnology, Catholic University of Brasilia, Bra-

[1] Deublein D, Steinhauser A. Biogas from waste and renewable resources: an introduction, 2nd ed. Weinheim, Germany: Wiley-VCH; 2010. doi:10.1002/9783527632794.

, Gabriela Carneiro de Almeida1,2,

and Nádia Skorupa Parachin1\*

**Author details**

silia-DF, Brazil

**References**

Otávio Bravim da Silva1

Juliana Davies de Oliveira2

Currently, numerous efforts are being made to reduce energy dependence on oil. This requirement has led to the development of new technologies for the use of other energy sources, such as the production of biogas. This biofuel is an important alternative to ensure the supply of clean and affordable energy and to contribute toward reducing the accumulation of waste, as biomass can be used as raw materials for biogas production. However, obtaining high yields is still a major challenge. One solution is to optimize the process, adjusting some of the physical and chemical parameters, such as temperature and pH. This is because this fermentation process involves several microbial groups and therefore needs to be adjusted to the environment of each of these groups. One way to do this is to include fermentation stages, in which more than one reactor is used, allowing the maintenance of optimum conditions for each microbial group involved in each step. Another challenge is the hydraulic retention time, which is the normal time that the input substrate spends in the digester before it is removed. A solution for this is microorganism retention, where they are imprisoned within inert materials, allowing the microorganisms to remain longer inside the reactor. It is worth noting that a deeper understanding of the physiology of each microbial gender participating in the process should be performed in order to be able to more precisely optimize the process parameters. Finally, despite biogas production being an age-old process, little is known about this process. Therefore, further studies on this process are necessary to achieve greater


[27] Ward AJ, Hobbs PJ, Holliman PJ, Jones DL. Optimisation of the anaerobic digestion of agricultural resources. Bioresour. Technol. 2008; 99(17):7928–7940. doi:10.1016/ j.biortech.2008.02.044.

[14] Cibis KG, Gneipel A, König H. Isolation of acetic, propionic and butyric acid-forming bacteria from biogas plants. J. Biotechnol. [Internet]. 2016; 220:51–63. doi:10.1016/

[15] Grabarse W, Mahlert F, Shima S, Thauer RK, Ermler U. Comparison of three methylcoenzyme M reductases from phylogenetically distant organisms: unusual amino acid modification, conservation and adaptation. J. Mol. Biol. 2000; 303(2):329–344. doi:

[16] Mata-Alvarez J, Macé S, Llabrés P. Anaerobic digestion of organic solid wastes. An overview of research achievements and perspectives. Bioresour. Technol. [Internet].

[17] Chae KJ, Jang A, Yim SK, Kim IS. The effects of digestion temperature and temperature shock on the biogas yields from the mesophilic anaerobic digestion of swine manure.

[18] Taconi KA, Zappi ME, Todd French W, Brown LR. Methanogenesis under acidic pH conditions in a semi-continuous reactor system. Bioresour. Technol. 2008; 99(17):8075–

[19] Morita M, Sasaki K. Factors influencing the degradation of garbage in methanogenic bioreactors and impacts on biogas formation. Appl. Microbiol. Biotechnol. 2012; 94(3):

[20] Kadam PC, Boone DR. Influence of pH on ammonia accumulation and toxicity in halophilic, methylotrophic methanogens. Appl. Environ. Microbiol. 1996; 62(12):4486–

[21] Stronach SM, Rudd T, Lester JN. Anaerobic Digestion Processes in Industrial Wastewater Treatment. 1st ed. Berlin, Heidelberg: Springer-Verlag; 1986. doi:

[22] Fermoso FG, Collins G, Bartacek J, Lens PNL. Zinc deprivation of methanol fed anaerobic granular sludge bioreactors. J. Ind. Microbiol. Biotechnol. 2008; 35(6):543–

[23] Lettinga G, Field J, Van Lier J, Zeeman G, Hulshoff Pol LW. Advanced anaerobic wastewater treatment in the near future. Water Sci. Technol. 1997; 35(10):5–12. doi:

[24] Pullen T. Anaerobic digestion–making biogas—making energy: the earthscan expert

[25] Fair GM, Moore EW. Time and rate of sludge digestion, and their variation with

2000 [cited 2015 Jan 7]; 74(1):3–16. doi:10.1016/S0960-8524(00)00023-7.

Bioresour. Technol. 2008; 99(1):1–6. doi:10.1016/j.biortech.2006.11.063.

j.jbiotec.2016.01.008.

178 Fermentation Processes

10.1006/jmbi.2000.4136.

8081. doi:10.1016/j.biortech.2008.03.068.

575–582. doi:10.1007/s00253-012-3953-z.

10.1007/978-3-642-71215-9.

557. doi:10.1007/s10295-008-0315-z.

10.1016/S0273–1223(97)00222–9.

guide. London and New York: Routledge; 2014.

temperature. Sewage Work. J. 1934; 6(1):3–13.

[26] Logan RP. US. Pat. No. 2,605,220 Anaerobic digester. 1952; 1–11.

4492.


#### **Production Processes for Monoclonal Antibodies Production Processes for Monoclonal Antibodies**

[39] Liu D, Liu D, Zeng RJ, Angelidaki I. Hydrogen and methane production from household solid waste in the two-stage fermentation process. Water Res. 2006; 40(11):2230–

[40] Singh SP, Prerna P. Review of recent advances in anaerobic packed-bed biogas reactors. Renew. Sustain. Energy Rev. 2009; 13(6–7):1569–1575. doi:10.1016/j.rser.2008.08.006.

[41] Effendi A, Zhanga Z-G, Hellgardt K, Hondaa K, Yoshidaa T. Steam reforming of a clean model biogas over Ni/Al2O3 in fluidized- and fixed-bed reactors. Catal. Today. 2002;

2236. doi:10.1016/j.watres.2006.03.029.

180 Fermentation Processes

77:181–189. doi:10.1016/j.cattod.2011.07.011.

Lucas Silva Carvalho, Otávio Bravim da Silva, Lucas Silva Carvalho, Otávio Bravim da Silva,

Gabriela Carneiro de Almeida, Gabriela Carneiro de Almeida,

Juliana Davies de Oliveira, Juliana Davies de Oliveira, Nadia Skorupa Parachin and Talita Souza Carmo

Nadia Skorupa Parachin and Talita Souza Carmo

Additional information is available at the end of the chapter Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/64263

#### **Abstract**

Antibodies are glycoprotein structures with immune activity. They are able to identify or induce a neutralizing immune response when they identify foreign bodies such as bacteria, viruses, or tumor cells. Immunoglobulins are produced and secreted by B lymphocytes in response to the presence of antigens. The first monoclonal antibodies (mAbs) have emerged from a survey of hybridomas, and nowadays mAbs are produced mostly from cultivations of these cells. Additionally, there are studies and patents using a range of cells and microorganisms engineered for the production of mAbs at commercial scale. For some years, new methodologies have advanced with new production processes, allowing scale-up production and market introduction. Largescale production has revolutionized the market for monoclonal antibodies by boosting its production and becoming a more practical method of production. Production techniques have only had a sizable breakthrough due to molecular techniques. Various systems of production are used, including animal cells, microorganisms, plants, and mammary glands. All of these require the technological development of production process such as a stirrer, a wave bioreactor, and roller bottles.

**Keywords:** monoclonal antibodies, bioprocess, bioreactors, antibodies, mAbs

#### **1. Introduction**

Monoclonal antibodies (mAbs) have been widely used as a way to successfully achieve a broad range of extracellular targets with high specificity [1]. mAbs have various applications in

© 2017 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2017 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

diagnosis and therapy for several diseases such as cancers, autoimmune diseases, sexually transmitted infections (STIs), and others [2, 3]. In recent years, the use of mAbs has been expanded due to significant advances in design. The effect of decreasing immunogenicity in humans, improvement in their bioavailability, optimizing the affinity and antigen-binding specificity, and other advances in protein engineering are improving therapeutic mAb profiles (**Figure 1**) [2].

**Figure 1.** Schematic overview of a monoclonal antibody, showing their heavy and variable chain.

With the advent of genetic engineering, it has been possible to develop new methods to obtain monoclonal antibodies, both for improvement with regard to these humanized antibodies and for production models [4–6]. Advances in molecular and cell biology for the development of more efficient antibodies have allowed advances in diagnostic and therapeutic areas. Such advances have triggered improvements in production processes, allowing for the reduction of production costs and thus leading to an increase in the popularization of treatments with mAbs. All process improvements provide a consistent and reproducible production of large quantities of mAbs at a moderate cost [4–6].

Large-scale production has revolutionized the market for monoclonal antibodies by boosting its production, making this a more practical method of production. Production techniques have only had a sizable breakthrough due to molecular techniques [1, 7].

In general, a process of commercial production of mAb begins with the generation of an mAb by immunizing an animal or by molecular biology methods involving the identification and optimization of the coding DNA sequence and the construction and identification of a stable high-producing clone. Improvements in cultivation are similar to those applied in other bioproducts that rely on culturing microorganisms or cells, requiring the development of a well-designed culturing process comprising the full range of control and associated operations that will support technical evaluations [1, 8].

mAbs production processes in wave or single-use bioreactor (SUBs) are characterized by flexibility and low operating costs when compared to the production processes in fixed stainless steel vats. The development of bioprocesses involving these production platforms can reap greater acceptance by the industry [9–11].

Drugs based on mAbs have been controlled by regulatory agencies around the world. Therefore, it is necessary to elaborate regulatory protocols accompanying the increase in production and the nuances of the characteristics of this class of drugs [10, 11].

The proposed chapter covers the fundamental aspects of monoclonal antibody production methods, with emphasis on methodologies using immobilized cells, wave bioreactor systems, SUBs, and finally the roller bottles technique. Such techniques have been described in the most recent literature, both for murine monoclonal antibody production and for production of antibodies from modified microorganisms.

#### **2. mAbs production techniques**

#### **2.1. Hybridoma and phage display**

diagnosis and therapy for several diseases such as cancers, autoimmune diseases, sexually transmitted infections (STIs), and others [2, 3]. In recent years, the use of mAbs has been expanded due to significant advances in design. The effect of decreasing immunogenicity in humans, improvement in their bioavailability, optimizing the affinity and antigen-binding specificity, and other advances in protein engineering are improving therapeutic mAb profiles

**Figure 1.** Schematic overview of a monoclonal antibody, showing their heavy and variable chain.

have only had a sizable breakthrough due to molecular techniques [1, 7].

quantities of mAbs at a moderate cost [4–6].

that will support technical evaluations [1, 8].

With the advent of genetic engineering, it has been possible to develop new methods to obtain monoclonal antibodies, both for improvement with regard to these humanized antibodies and for production models [4–6]. Advances in molecular and cell biology for the development of more efficient antibodies have allowed advances in diagnostic and therapeutic areas. Such advances have triggered improvements in production processes, allowing for the reduction of production costs and thus leading to an increase in the popularization of treatments with mAbs. All process improvements provide a consistent and reproducible production of large

Large-scale production has revolutionized the market for monoclonal antibodies by boosting its production, making this a more practical method of production. Production techniques

In general, a process of commercial production of mAb begins with the generation of an mAb by immunizing an animal or by molecular biology methods involving the identification and optimization of the coding DNA sequence and the construction and identification of a stable high-producing clone. Improvements in cultivation are similar to those applied in other bioproducts that rely on culturing microorganisms or cells, requiring the development of a well-designed culturing process comprising the full range of control and associated operations

mAbs production processes in wave or single-use bioreactor (SUBs) are characterized by flexibility and low operating costs when compared to the production processes in fixed

(**Figure 1**) [2].

182 Fermentation Processes

Milstein and Köhler described the first technique developed for stable monoclonal antibody production in 1975. This technique consists of creating a hybridoma, a stable hybrid cell capable of producing a single type of antibody against a specific epitope present in an antigen. Hybridoma construction was initially produced from murine models. The technique consists of removing a pool of activated B lymphocytes from an immunized animal spleen and combining them with immortalized myeloma cells unable to produce the enzyme hypoxanthine-guanine-phosphoribosyltransferase (HGPRT), an important enzyme present in the *salvage* pathway, one of the pathways responsible for nucleotide production [1]. To select hybridoma cells, the pool of cells resulting from the fusion (a mix of hybridoma cells and nonfused B lymphocytes and myeloma cells) are cultivated in a selective medium containing aminopterin, which inhibits the nucleotide de novo synthesis. Myeloma cells lack the *salvage* pathway for nucleotide production. When they are exposed to aminopterin present in selective medium, the de novo synthesis is also blocked, and as a result, myeloma cells are no longer viable since all major pathways for nucleotide production are blocked. In contrast, non-fused, activated B lymphocytes can survive as their *salvage* pathway works perfectly and they can continue nucleotide production even if the de novo pathway is blocked by aminopterin. However, these cells are not immortalized and can replicate only a limited number of times after which they eventually die. With this in mind, only cells capable of replicating indefinitely and synthesizing nucleotides through the *salvage* pathway can survive through selection conditions, and these cells are the hybridomas.

In spite of the fact that the primary recombinant mAbs were delivered utilizing this innovation —including the first medication approved by the Food and Drug Administration (FDA) for therapeutic proposes (**Table 1**)—the great contribution of this technology was mostly to elucidate immune response mechanisms and control in vitro antibody production. Therefore, mAb hybridoma production from murine sources exhibits a genuine downside in human therapeutics (**Figure 1**).



**Drug name Active ingredient Description Target Therapeutic**

scFvs

IgG1κ

PEG

Humanized Fab',

ILARIS Canakinumab Human IgG1κ uman-IL-1β Immunological/

Humanized IgG1;

Humanized IgG4κ, calicheamicin

KEYTRUDA® Pembrolizumab Humanized IgG4κ PD-1 Cancer 2014 LEMTRADA™ Alemtuzumab Humanized IgG1κ CD52 Immunological 2001 LUCENTIS Ranibizumab Humanized IgG1κ VEGF-A Ophthalmic 2006 Muromomab Orthoclone Murine IgG2α CD3 Immunological 1992

DM1

Alemtuzumab Humanized

ADCETRIS® Brentuximab

184 Fermentation Processes

BEXXAR Tositumomab;

CIMZIA® Certolizumab

KADCYLA® Ado-trastuzumab

Mylotarg® Gemtuzumab

emtansine

ozogamicin

pegol

CAMPATH (LEMTRADA™) vedotin

iodine I 131 tositumomab

BLINCYTO Blinatumomab BiTE antibody-

ACTEMRA® Tocilizumab Humanized IgG1κ IL-6 receptor Immunological 2010

ARZERRA® Ofatumumab Human IgG1κ CD20 Cancer 2009 AVASTIN® Bevacizumab Humanized IgG1 VEGF Cancer 2004 BENLYSTA® Belimumab Human IgG1λ BLyS Immunological 2011

CEA-SCAN Arcitumomab Murine IgG1 Fab' CEA Diagnosys 1996

COSENTYX® Secukinumab Human IgG1κ IL-17A Immunological 2015 CYRAMZA Ramucirumab Human IgG1 VEGRF-2 Cancer 2014 DARZALEX Daratumumab Human IgG1κ CD38 Cancer 2015 HERCEPTIN® Trastuzumab humanized IgG1κ HER2 Cancer 1998 EMPLICITI™ Elotuzumab Humanized IgG1 SLAMF7 Cancer 2015 ENTYVIO Vedolizumab Humanized IgG1 α4β7 Integrin Immunological 2014 ERBITUX® Cetuximab Chimeric IgG1 EGFR Cancer 2004 GAZYVA® Obinutuzumab Humanized IgG1 CD20 Cancer 2013 HUMIRA Adalimumab Human IgG1 TNF Immunological 2002

**category**

CD19/CD3 Cancer 2014

CD52 Immunological 2001

TNFα Immunological 2008

anti-inflammatory

HER2 Cancer 2013

CD33 Cancer 2000

2009

Chimeric IgG1 CD30 Cancer 2011

IgG2αλ, I131 CD20 Cancer 2003

**approval (FDA)**


**Table 1.** Monoclonal antibody-based therapeutic drugs approved by FDA (Food and Drug Administration) until 2015.

After a few infusions, murine antibody molecules trigger the human anti-mouse antibody (HAMA) response of the human immune system [1, 12]. To work around this issue, new methodologies have been developed to deliver antibodies similar to human molecules, so the technology evolved to less immunogenic chimeric antibodies (constant regions of human antibodies linked to the variable region of the murine source), creating a new set of therapeutic possibilities (**Figure 1**). Subsequently, the need for an even less immunogenic alternative boosted the production of humanized antibodies (only the region that interacts with the antigen epitope is from mouse origin) (**Figure 1**). Even fully human antibodies (**Figure 1**) can be produced from genetically modified mice [13].

A great improvement in mAb production has come with the development of phage display libraries. This methodology helps to investigate interactions between molecules (proteinprotein, protein-peptide, and protein-DNA) and consists, basically, in cloning Fab-regioncoding genes amplified from B lymphocytes into bacteriophage plasmid vectors. Then the bacterium can be transformed with these vectors, going on to express the heterologous genes from a viral capsid. This capsid contains viral proteins and proteins encoded by the Fab sequence received by that specific cell. Once the library is complete, the affinity between proteins produced from different Fab regions can be tested against the antigen of interest and the cell transformed with the plasmid that contains those genes can be readily sequenced. The advantages of this methodology are the following: the same library has the potential to generate a great number of new antibodies, it is an in vitro process, so it does not require animal immunizations steps, and because of that, toxic antigens can be tested. Also, a greater variety of antigens can be tested, and antibody molecules can be rapidly obtained [13].

#### **2.2. Culture production factors**

#### *2.2.1. Cell lines*

One of the most critical steps in developing an mAb production system is to choose the cell line. The cells must be stable and secrete the desired protein with the correct conformation at high levels. Based on these requirements, the mammalian cell is the most commonly chosen expression system for mAb production. The main advantage of a mammalian expression system is that the cellular machinery is adapted for the production, processing, and secretion of highly complex molecules. The great majority of commercial mAbs are produced in Chinese hamster ovary (CHO) and NS0 cells, originating from plasmacytoma cells that were modified until IgG generation in nonsecreting B cells. Genetic modifications in CHO cells have generated cell lines capable of producing a high quantity of humanized mAbs. These cell lines were able to secrete up to 100 pg/cell/day [14]. Other modifications led to a high production of a chimeric mAb, ranging from 80 to 110 pg/cell/day [15]. NS0 modifications also have been made, leading to higher mAb production rates, ranging from 20 to 50 pg/cell/day [16]. In smaller quantities, hybridoma cell lines are also used in industrial mAb production. Some hybridoma strains are reported to have a production rate up to 80 pg/cell/day [16]. In spite of this, different mammalian cell lines and even more peculiar expression systems such as genetically modified plant cells, genetically modified insect cells, and genetically modified microorganism cells have also been used in mAb production and have gained space in the biopharmaceutical industry [1, 8]

Microorganisms modified by genetic engineering techniques have attracted much focus in industry, because these cells are simpler to handle and to modify when compared to animal cells. Other advantages of production methods using genetically modified microorganisms are that these cells have well-defined expression systems, and the production methodology is reproducible and easy to validate. Modified yeast cells, such as *Pichia pastoris* have a great potential for usage since these cells are known to achieve high secretion levels of heterologous proteins. Yeast cultivation systems for mAb production are easier scale-up and are cheaper when compared to mammalian cell cultivation systems. They can be cultivated in regular stirred tank bioreactors, in batch, or in feed-batch modes of operation. Generally, microorganisms do not have physicochemical and biological characteristics for the appropriate expression and posttranslational processing of mAbs [4].

Modified plants have also gained attention since plants are easy to cultivate and propagate. Other cultivation advantages such as cheap medium, low maintenance cost, and high production yields make plant production a cheaper alternative when compared to mammalian cell cultures [17]. However, there are some limitations—different glycosylation patterns and post-translational processing can also make plant cell utilization difficult [17].

#### *2.2.2. Culture medium*

**Drug name Active ingredient Description Target Therapeutic**

murine IgG1κ, Yttrium-90

ZEVALIN® Ibritumomab

186 Fermentation Processes

tiuxetan

be produced from genetically modified mice [13].

**2.2. Culture production factors**

*2.2.1. Cell lines*

XGEVA Denosumab Human IgG2 RANKL Cancer 2010 XOLAIR® Omalizumab Humanized IgG1κ Human IgE Immunological 2003 YERVOY® Ipilimumab Human IgG1κ CTLA-4 Cancer 2011 ZENAPAX® Daclizumab Humanized IgG1 IL-2 receptor Immunological 1997

**Table 1.** Monoclonal antibody-based therapeutic drugs approved by FDA (Food and Drug Administration) until 2015.

After a few infusions, murine antibody molecules trigger the human anti-mouse antibody (HAMA) response of the human immune system [1, 12]. To work around this issue, new methodologies have been developed to deliver antibodies similar to human molecules, so the technology evolved to less immunogenic chimeric antibodies (constant regions of human antibodies linked to the variable region of the murine source), creating a new set of therapeutic possibilities (**Figure 1**). Subsequently, the need for an even less immunogenic alternative boosted the production of humanized antibodies (only the region that interacts with the antigen epitope is from mouse origin) (**Figure 1**). Even fully human antibodies (**Figure 1**) can

A great improvement in mAb production has come with the development of phage display libraries. This methodology helps to investigate interactions between molecules (proteinprotein, protein-peptide, and protein-DNA) and consists, basically, in cloning Fab-regioncoding genes amplified from B lymphocytes into bacteriophage plasmid vectors. Then the bacterium can be transformed with these vectors, going on to express the heterologous genes from a viral capsid. This capsid contains viral proteins and proteins encoded by the Fab sequence received by that specific cell. Once the library is complete, the affinity between proteins produced from different Fab regions can be tested against the antigen of interest and the cell transformed with the plasmid that contains those genes can be readily sequenced. The advantages of this methodology are the following: the same library has the potential to generate a great number of new antibodies, it is an in vitro process, so it does not require animal immunizations steps, and because of that, toxic antigens can be tested. Also, a greater variety

of antigens can be tested, and antibody molecules can be rapidly obtained [13].

One of the most critical steps in developing an mAb production system is to choose the cell line. The cells must be stable and secrete the desired protein with the correct conformation at high levels. Based on these requirements, the mammalian cell is the most commonly chosen expression system for mAb production. The main advantage of a mammalian expression

**category**

CD20 Cancer 2002

**approval (FDA)**

> Cultivation media for mammalian cells must have a complex content of ingredients ranging from amino acids to trace elements. To supply the cellular demand of these nutrients, the culture medium uses serum in its composition, however, due to the emergence of diseases caused by defective prions, such as bovine spongiform encephalitis (BSE), there is a great incentive to remove any animal component of culture media composition, especially if the medium is used for industrial production of biopharmaceuticals products. This has led to the emergence of media free from any animal components, including well-defined media for CHO and NS0, the two most utilized cell types in mAb production. The development of a proper medium can be time consuming and very expensive. However, many companies prefer to develop their own production media to maintain the composition between production lots as well as develop an appropriate medium composition for the specific cell type that will be used

and to achieve greater control over production. Added to this, the development of downstream processes that meet the requirement for high-purity products and tests to validate the final product quality raises the overall production cost of a drug based on monoclonal antibodies [1].

Despite the complexity of developing a culture medium, much progress has been made in this area, allowing for greater cell growth and increasing cell conservation time in suitable conditions for the growth and production of molecules of interest [8].

#### *2.2.3. Culture conditions*

Growing conditions can directly influence the cell growth and production levels of molecules of interest. Usually, mammalian cell culture conditions for mAb production are very well defined: 37 °C, pH 7.15, and dissolved O2 (OD) levels at 30–60%. CO2 level is monitored to mimic the physiological standard between 31 and 54 mmHg. However, changes in cellular conditions have shown great potential to change cellular metabolism toward cellular growth or molecule production and this can be used to increase mAb production. Bioprocesses can be designed to occur in two phases. First, cell growth is optimized to reach a certain cell density. Once this density is reached, the second phase begins and the bioreactor conditions are shifted so the cells continue to grow just at a maintenance rate and directing the metabolism toward monoclonal antibody production. Some CHO cell strains and hybridoma cells are sensitive to changes in temperature and pH. When subjected to temperature and pH values lower than those normally used, values between 30 and 35 °C and 6.7–7.0, respectively, cell growth metabolism is reduced and specific production increases. The growth metabolism reduction also contributes to lower production of some metabolic compounds which are toxic for cell cultures, allowing increased cell viability, which spend more time producing molecules of interest. A good way to monitor the growth stage of a cell culture for controlling changes in cultivation is watching the DO and pCO2 levels, which can also be adjusted to maximize the production of proteins such as mAbs [1].

#### *2.2.4. Production platforms*

The cell culture for mAb production can follow three different types of processes. The simplest of them is batch production, which consists of a closed system where a bioreactor is sterilized and prepared with a medium containing all the nutrients needed for cellular growth and product manufacturing and then, cells are inoculated. There is no feeding system with fresh medium or withdrawal of spent medium. As the process runs, nutrient concentration decreases and waste metabolites are produced, lowering cell viability. In spite of being a simple process, batch is not the most suitable type of production platform for mammalian cell cultures, as the environment inside the reactor quickly becomes unfavorable for cell growth and, at the same time, waste product concentration increases. Cultivation factors such as initial nutrient concentration and waste metabolite production directly determine the maximum concentration that cells can reach in a bath culture. Generally, this type of cultivation reaches a maximum density of 1–2 × 106 cells/mL, and then the cell viability drops rapidly [1]. The production process lasts for 4–7 days, when productivity reaches certain concentration of interest [1]. Supernatant is collected and the product is recovered by downstream processes. The time that each batch takes to finish also depends on the production kinetics. If the production is growth dependent (production occurs concomitantly with cellular growth), batch processes can be stopped as soon as cells reach the stationary phase. But if the product is not associated with growth (production only starts when the growth rate decreases), the culture needs to be carried for a longer period of time since production only starts at stationary phase.

and to achieve greater control over production. Added to this, the development of downstream processes that meet the requirement for high-purity products and tests to validate the final product quality raises the overall production cost of a drug based on monoclonal antibodies [1].

Despite the complexity of developing a culture medium, much progress has been made in this area, allowing for greater cell growth and increasing cell conservation time in suitable

Growing conditions can directly influence the cell growth and production levels of molecules of interest. Usually, mammalian cell culture conditions for mAb production are very well defined: 37 °C, pH 7.15, and dissolved O2 (OD) levels at 30–60%. CO2 level is monitored to mimic the physiological standard between 31 and 54 mmHg. However, changes in cellular conditions have shown great potential to change cellular metabolism toward cellular growth or molecule production and this can be used to increase mAb production. Bioprocesses can be designed to occur in two phases. First, cell growth is optimized to reach a certain cell density. Once this density is reached, the second phase begins and the bioreactor conditions are shifted so the cells continue to grow just at a maintenance rate and directing the metabolism toward monoclonal antibody production. Some CHO cell strains and hybridoma cells are sensitive to changes in temperature and pH. When subjected to temperature and pH values lower than those normally used, values between 30 and 35 °C and 6.7–7.0, respectively, cell growth metabolism is reduced and specific production increases. The growth metabolism reduction also contributes to lower production of some metabolic compounds which are toxic for cell cultures, allowing increased cell viability, which spend more time producing molecules of interest. A good way to monitor the growth stage of a cell culture for controlling changes in cultivation is watching the DO and pCO2 levels, which can also be adjusted to maximize the

The cell culture for mAb production can follow three different types of processes. The simplest of them is batch production, which consists of a closed system where a bioreactor is sterilized and prepared with a medium containing all the nutrients needed for cellular growth and product manufacturing and then, cells are inoculated. There is no feeding system with fresh medium or withdrawal of spent medium. As the process runs, nutrient concentration decreases and waste metabolites are produced, lowering cell viability. In spite of being a simple process, batch is not the most suitable type of production platform for mammalian cell cultures, as the environment inside the reactor quickly becomes unfavorable for cell growth and, at the same time, waste product concentration increases. Cultivation factors such as initial nutrient concentration and waste metabolite production directly determine the maximum concentration that cells can reach in a bath culture. Generally, this type of cultivation reaches a maximum

process lasts for 4–7 days, when productivity reaches certain concentration of interest [1]. Supernatant is collected and the product is recovered by downstream processes. The time that

cells/mL, and then the cell viability drops rapidly [1]. The production

conditions for the growth and production of molecules of interest [8].

*2.2.3. Culture conditions*

188 Fermentation Processes

production of proteins such as mAbs [1].

*2.2.4. Production platforms*

density of 1–2 × 106

In contrast to batch, a second type of production process utilized is continuous fermentation. There are two types of continuous production: chemostat cultures and perfusion cultures. Concerning chemostat cultures, fresh medium is added to the bioreactor and fermented medium is removed along with cells at a constant flow rate so that the culture volume remains unchanged. The flow rate (dilution rate) controls cellular growth and when these two variables are equal, the bioreactor reaches equilibrium—cell concentration, nutrient concentration, and product concentration are held constant. In this context, the culture can be kept in equilibrium for several months reaching a cell density of 10–30 × 106 cells/mL [1]. To avoid viable cell loss along with the constant outflow of the by-products of cell metabolism, many manufacturing plants have developed a cell-recycling system and thus, the perfusion culture method was developed where cells are kept inside the bioreactor. The disadvantages of continuous fermentation are the use of a large amount of expensive culture media and the difficulty in recovering the product, which comes out fairly diluted. These two disadvantages are consequences of the constant medium flow rate. To work around the product dilution problem, some production manufacturing plants have ultrafiltration systems which retain the product inside the bioreactor [18]. Another obstacle of this type of process is that the establishment of culture conditions for a stable industrial production plant can take months. For this to occur, the strain used must be very stable and have its physiological aspects clearly elucidated, such as growth rate, productivity, and response to certain stress conditions. It is not uncommon to hear that numerous attempts are made before the settlement of a stable production plant is achieved, but, once settled, this production process can bring many advantages, since it can be operated in smaller-volume bioreactors, and therefore have greater production flexibility.

The third type of process for producing monoclonal antibodies is by far the most utilized at industrial scale, which is fed-batch process. In this process, the cell density reaches 8–12 × 106 cells/mL, and cell viability in the bioreactor is enhanced by controlled nutrient addition at specified intervals [1]. The production process can take 12–20 days [1]. Usually, the same medium used in the initial culture is also used for feeding, but in a more concentrated version. The feeding solution composition can be designed to supply the cells based on their metabolic state at different culture phases by analyzing and identifying the spent medium nutrients that are being more consumed. Furthermore, the medium used in feeding can be modified to promote cell growth or to stimulate molecule production, since different components may modify the behavior of cells, changing the metabolism for different purposes. The feed solution can also be designed to minimize the production of waste metabolites that cause cell stress when in excess. However, their production is not completely avoidable as they eventually reach harmful concentrations. It is relatively easy to scale up and operate this system. More summarized data about the advantages and disadvantages of each process for mAb production can be seen in **Table 2**.


**Table 2.** Comparison between different operation modes that can be used for mAbs production.

A lot of effort has been made to increase cell longevity in batch and feed-batch modes of operation. It is expected that the longer the cells are maintained viable, the greater the antibodies' production will be. So, in order to maintain cell viability, some culture parameters can be optimized, such as culture media, feed solution, and mAb secretion rates and byproduct production. To improve mAb titers in the batch platform, the start medium can be supplemented with glucose and amino acids, increasing mAb production up to eightfold when compared with regular media [9, 26]. Improvements for the fed-batch platform can be achieved by adjustments in feed solution, as mentioned before. Feed solutions containing glucose and aminoacids/glutamine have been reported to increase mAb titers from two to fourfold, reaching production of up to 2 g/L, when compared with the batch production platform [19].

The optimization of the antibody secretion rate can be achieved by high-density cell cultivation. On a fed-batch platform, a high cell cultivation culture can reach an mAb productivity rate of 0.94 g/L/day and a final titration of 17 g/L, while a continuous culture performed at high density conditions can reach final titration and productivity rates of 0.8 and 1.6 g/L/day, respectively [20]. Optimizing mAb secretion highly depends on the cell line chosen for production. Each cell strain can be influenced by the manufacturing conditions and respond differently to increasing or decreasing mAb production and secretion [19]. The accumulation of toxic byproducts is a great bottleneck in manufacturing processes since they can inhibit cell growth and then directly affect mAb production. Although a few strategies to minimize this byproduct accumulation have shown to be promising, some are not applicable for a large-scale production. Optimizing medium composition and feed solutions with substrates that reduce toxic compound production is the most common strategy used at industrial scales of production [19].

Although most mAbs are produced by fed-batch process, there are tendencies indicating that in the future many bioprocesses will be operated in continuous platforms, especially for the production of biopharmaceuticals. On these platforms, the production system will be coupled to upstream and downstream processes [21]. However, for this to actually happen, a great improvement in technological development still needs to be achieved.

#### **2.3. Production systems**

**Production platform** 

190 Fermentation Processes

Advantages **•** Simple to scale-up

lot

Disadvantages **•** Difficult to define initial

Adapted from [1, 21] (colocar referencias).

**•** Accumulation of waste metabolites

**•** Control by production

concentration of nutrients

**•** Degradation of more sensitive products

**Batch Feed-batch Perfusion culture** 

**•** Simple to scale-up

**•** Control by production lot **•** Production facility is simple **•** Process is easy to perform and to validate

**•** Cells are maintained in a relatively optimal biochemical environment

**•** Culture reaches high cell density **•** Higher volumetric production

**•** Lack of homogeneity in the continuous reactor vessel

**•** Challenges regarding long-term operability and maintenance

**•** High cost and long times required for process development

experiments

**•** Genetic instability of cells

**•** Higher volumetric production

**•** Accumulation of waste

**•** Degradation of more sensitive

A lot of effort has been made to increase cell longevity in batch and feed-batch modes of operation. It is expected that the longer the cells are maintained viable, the greater the antibodies' production will be. So, in order to maintain cell viability, some culture parameters can be optimized, such as culture media, feed solution, and mAb secretion rates and byproduct production. To improve mAb titers in the batch platform, the start medium can be supplemented with glucose and amino acids, increasing mAb production up to eightfold when compared with regular media [9, 26]. Improvements for the fed-batch platform can be achieved by adjustments in feed solution, as mentioned before. Feed solutions containing glucose and aminoacids/glutamine have been reported to increase mAb titers from two to fourfold, reaching production of up to 2 g/L, when compared with the batch production platform [19].

The optimization of the antibody secretion rate can be achieved by high-density cell cultivation. On a fed-batch platform, a high cell cultivation culture can reach an mAb productivity rate of 0.94 g/L/day and a final titration of 17 g/L, while a continuous culture performed at high density conditions can reach final titration and productivity rates of 0.8 and 1.6 g/L/day, respectively [20]. Optimizing mAb secretion highly depends on the cell line chosen for production. Each cell strain can be influenced by the manufacturing conditions and respond differently to increasing or decreasing mAb production and secretion [19]. The accumulation of toxic byproducts is a great bottleneck in manufacturing processes since they can inhibit cell growth

metabolites

products

**Table 2.** Comparison between different operation modes that can be used for mAbs production.

The use of monoclonal antibodies as therapeutic drugs requires a large-scale production that far exceeds that of laboratory production (**Figure 2**). Various production systems have been developed and have evolved, while new alternatives are emerging. The production of mAbs at commercial scale can be performed with adherent cells or suspension cells, although the latter is by far the most used and is better established with more efficient production methods available for cells cultivation. Thus, scale-up using suspension cells is easier. Another advantage of the suspension production system is that a bioreactor with a large area for cell adhesion is not necessary since the cultivation of adherent cell productivity is directly linked to the bioreactor's area [22].

**Figure 2.** Work volumes used for industrial production of some commercial monoclonal antibodies [27, 28].

Some cultivation issues and worries have arisen regarding the production scale increase, maintenance of product quality, contamination control, demand for oxygen supply, and control over DO and CO2 removal, among others. Regarding suspension cell cultures, aeration is in part dependent on the agitation of the culture inside the bioreactor, which can lead to cell shear stress. To work around cultivation problems, major advances have been made in the process itself by developing better culture control and conditions, as well as the improvement and development of new bioreactors [7, 23].

#### *2.3.1. Production systems for cells in suspension cultures*

The different types of bioreactors commonly used for mAb production in submerged mammalian cells are stainless steel stirred tank bioreactors (STR), air-lift reactors, and disposable bioreactors. More details on each of these bioreactors are discussed below.

#### *2.3.2. Stainless steel stirred tank bioreactors*

Stainless steel stirred tank bioreactors are the most consolidated type of bioreactor used for industrial mAb production and consist of baffle-stirred tanks linked to rotor systems (**Figure 3**). It is a consolidated system, and there is a lot of knowledge and experience surrounding this technology, acquired by its vast industrial use beyond production using mammalian cells.

The cultivation in this bioreactor allows for wide flexibility of working volumes, ranging from 1.0 to 25.0 L [1], since this system is easily scalable to larger volumes due to its high control over production conditions and extensive handling knowledge. The mechanisms and cleaning and sterilization protocols are well defined. Additionally, cultivation parameters for this system, such as gas transfer coefficient, agitation, aeration, temperature maintenance, pH, and

**Figure 3.** Schematic representation of a stainless steel stirred tank bioreactor. Showing the main components in a cell cultivation.

others are well controlled and regulated when compared to other production systems. Another advantage of the STR is that it can be used for cultivation of various cell types and in addition, the products obtained from the cultivation in this type of bioreactor are easily approved for therapeutic use, as regulatory terms are well defined for this type of production [11].

However, the biggest disadvantage for the use of STR is the stress caused by shear. It can cause cell lysis and lead to loss in mAb productivity.

#### *2.3.3. Air-lift reactors*

is in part dependent on the agitation of the culture inside the bioreactor, which can lead to cell shear stress. To work around cultivation problems, major advances have been made in the process itself by developing better culture control and conditions, as well as the improvement

The different types of bioreactors commonly used for mAb production in submerged mammalian cells are stainless steel stirred tank bioreactors (STR), air-lift reactors, and disposable

Stainless steel stirred tank bioreactors are the most consolidated type of bioreactor used for industrial mAb production and consist of baffle-stirred tanks linked to rotor systems (**Figure 3**). It is a consolidated system, and there is a lot of knowledge and experience surrounding this technology, acquired by its vast industrial use beyond production using

The cultivation in this bioreactor allows for wide flexibility of working volumes, ranging from 1.0 to 25.0 L [1], since this system is easily scalable to larger volumes due to its high control over production conditions and extensive handling knowledge. The mechanisms and cleaning and sterilization protocols are well defined. Additionally, cultivation parameters for this system, such as gas transfer coefficient, agitation, aeration, temperature maintenance, pH, and

**Figure 3.** Schematic representation of a stainless steel stirred tank bioreactor. Showing the main components in a cell

bioreactors. More details on each of these bioreactors are discussed below.

and development of new bioreactors [7, 23].

*2.3.2. Stainless steel stirred tank bioreactors*

mammalian cells.

192 Fermentation Processes

cultivation.

*2.3.1. Production systems for cells in suspension cultures*

Air-lift reactors are also broadly used for the industrial production of mAbs. The reactor consists of tanks with a bubble column inside, and air is injected into the column base (**Figure 4**). The air flows through the column's length to the top of the bioreactor as degassed culture medium flows in the opposite direction to the reactor bottom. This creates a constant gentle mixing of the medium as well as proper culture aeration, annulling part of the shear stress caused by other stirring systems. Other advantages of this operation system are that it is easier to scale-up, contamination problems are more unlikely to occur, and the equipment is simpler. In spite of these advantages, this system is less utilized than STR reactors because

**Figure 4.** Schematic representation of an air-lift bioreactor. Showing the main components in a cultivation process.

the working volume ranges only from 2.0 to 5.0 L [1] and the air-lift reactor handling is not so well elucidated [11].

#### *2.3.4. Disposable bioreactors*

The first single-use bioreactors emerged in the late 1990s with the launch of a wave reactor system. After that, disposable stirred tank bioreactors were developed [11].

This method brought many advantages for mAb manufacturing. At the end of the process, the bioreactor is discarded and replaced by a new clean and sterile one. This eradicates cross contamination between batches and decreases the time consumed with the equipment preparation between batches. When all the advantages of this process are taken in account, the savings made regarding production and investment capital are highly significant when compared with other process methods. The great disadvantage of this production system is the small work volume supported, ranging from 50 to 2000 L [1].

The wave system consists of a sterile plastic bag (CellBag™) lying on a rocking platform (**Figure 5**). The bag is half filled with cultivation medium and half filled with a gas mix of interest. The platform motion creates an undulation movement in the culture, ensuring efficient aeration and culture mixing without causing shear damage [10, 11, 13]. The other available systems combine the convenience of a disposable system with the well-known stirred tank system and they are HyClone S.U.B®, Millipore® (CellReady™), or Xcellerex® (XDR™).

**Figure 5.** Schematic representation of a disposable wave bioreactor. Showing the main components in a cell cultivation process.

The main features of SUBs are related to their technical characteristics similar to those of stainless steel bioreactors, that is, aeration rate, agitation, reactor geometry, and ease of monitoring internal conditions, a process similar to stainless steel bioreactors [9].

SUBs are being widely used to replace many processes for the production of bioproducts. SUBs may be a cheaper and more efficient alternative from an industrial point of view, and its principle can easily replace any bioprocess to adapt the method to the platform of interest to be replaced, such as large tanks and stainless steel or the motion rocking platforms [9, 24].

SUBs have been used in bioprocesses for monoclonal antibody production involving several expression systems, including mammalian cells, microorganisms, plants, mammary glands, etc. Animal cell culture technology is one of the oldest techniques for the production of mAbs.

There is also the production of bottles known as roller bottles, consisting of mammalian cells growing in nutritional and physical conditions controlled in bottles which remain in rotational movement.

#### *2.3.5. Roller bottles*

the working volume ranges only from 2.0 to 5.0 L [1] and the air-lift reactor handling is not so

The first single-use bioreactors emerged in the late 1990s with the launch of a wave reactor

This method brought many advantages for mAb manufacturing. At the end of the process, the bioreactor is discarded and replaced by a new clean and sterile one. This eradicates cross contamination between batches and decreases the time consumed with the equipment preparation between batches. When all the advantages of this process are taken in account, the savings made regarding production and investment capital are highly significant when compared with other process methods. The great disadvantage of this production system is

The wave system consists of a sterile plastic bag (CellBag™) lying on a rocking platform (**Figure 5**). The bag is half filled with cultivation medium and half filled with a gas mix of interest. The platform motion creates an undulation movement in the culture, ensuring efficient aeration and culture mixing without causing shear damage [10, 11, 13]. The other available systems combine the convenience of a disposable system with the well-known stirred tank system and they are HyClone S.U.B®, Millipore® (CellReady™), or Xcellerex® (XDR™).

**Figure 5.** Schematic representation of a disposable wave bioreactor. Showing the main components in a cell cultivation

The main features of SUBs are related to their technical characteristics similar to those of stainless steel bioreactors, that is, aeration rate, agitation, reactor geometry, and ease of

SUBs are being widely used to replace many processes for the production of bioproducts. SUBs may be a cheaper and more efficient alternative from an industrial point of view, and its

monitoring internal conditions, a process similar to stainless steel bioreactors [9].

system. After that, disposable stirred tank bioreactors were developed [11].

the small work volume supported, ranging from 50 to 2000 L [1].

well elucidated [11].

194 Fermentation Processes

process.

*2.3.4. Disposable bioreactors*

Roller bottles are a rotary motion system for growing cells and for the production of some bioproducts. It has been an alternative to other monoclonal antibody production systems (**Figure 6**). Roller bottles provide conditions that favor the transfer of oxygen and temperature control without aeration, agitation propellers, or circulation pumps. The bottle is mounted on a turntable which gives homogeneity of growth and aeration of the culture medium [11, 25, 28].

**Figure 6.** Schematic representation of roller bottles bioreactor and a rack with the rotational motion system in a cultivation for mAb production.

For the production of monoclonal antibodies at commercial scale, the roller bottle technique can be adapted to racks containing tens of bottle in a production line. The advantages of this technique is the high growth potential linked to ease of handling and monitoring of certain conditions such as temperature and rotation. However, the scale of view requires a large physical footprint, which can make the process less economical [11, 25].

#### **3. Conclusions and perspectives**

Actually, the trade of monoclonal antibodies makes up half of marketed biopharmaceuticals, reaching \$ 75 billion. For some years, new development methodologies of antibodies have advanced with new production processes, allowing scale-up production and market introduction, and demands for high-quality biologics will continue to increase in the coming decades. Generally, processes are similar to those applied in the scheduling for other bioproducts/biosimilars that rely on culturing microorganisms or cells, requiring the development of a well-designed culturing process comprising the full range of control and associated operations that will support technical evaluations.

In combination with increasing pressure from regulatory agencies for enhanced quality and lower process costs from the health care systems, we are facing an important challenge. It will be necessary to make changes in plant design aiming for highly flexible multi-purpose facilities for small production volumes.

#### **Author details**

Lucas Silva Carvalho1 , Otávio Bravim da Silva1 , Gabriela Carneiro de Almeida1,2, Juliana Davies de Oliveira2 , Nadia Skorupa Parachin1 and Talita Souza Carmo1\*

\*Address all correspondence to: talitacarmo@gmail.com

1 Group of Applied Metabolic Engineering to Bioprocess, Institute of Biological Sciences, University of Brasilia, Brasilia, DF, Brazil

2 Postgraduate in Genomic Sciences and Biotechnology, Catholic University of Brasilia, Brasilia, DF, Brazil

#### **References**

[1] Chartrain M, Chu L. Development and production of commercial therapeutic monoclonal antibodies in Mammalian cell expression systems: an overview of the current upstream technologies. Curr Pharm Biotechnol 2008;9:447–67. doi: 10.2174/138920108786786367.

[2] Ecker DM, Jones SD, Levine HL. The therapeutic monoclonal antibody market. MAbs 2015;7:9–14. doi:10.4161/19420862.2015.989042.

technique is the high growth potential linked to ease of handling and monitoring of certain conditions such as temperature and rotation. However, the scale of view requires a large

Actually, the trade of monoclonal antibodies makes up half of marketed biopharmaceuticals, reaching \$ 75 billion. For some years, new development methodologies of antibodies have advanced with new production processes, allowing scale-up production and market introduction, and demands for high-quality biologics will continue to increase in the coming decades. Generally, processes are similar to those applied in the scheduling for other bioproducts/biosimilars that rely on culturing microorganisms or cells, requiring the development of a well-designed culturing process comprising the full range of control and associated opera-

In combination with increasing pressure from regulatory agencies for enhanced quality and lower process costs from the health care systems, we are facing an important challenge. It will be necessary to make changes in plant design aiming for highly flexible multi-purpose facilities

, Gabriela Carneiro de Almeida1,2,

and Talita Souza Carmo1\*

physical footprint, which can make the process less economical [11, 25].

, Otávio Bravim da Silva1

\*Address all correspondence to: talitacarmo@gmail.com

University of Brasilia, Brasilia, DF, Brazil

10.2174/138920108786786367.

, Nadia Skorupa Parachin1

1 Group of Applied Metabolic Engineering to Bioprocess, Institute of Biological Sciences,

2 Postgraduate in Genomic Sciences and Biotechnology, Catholic University of Brasilia, Bra-

[1] Chartrain M, Chu L. Development and production of commercial therapeutic monoclonal antibodies in Mammalian cell expression systems: an overview of the current upstream technologies. Curr Pharm Biotechnol 2008;9:447–67. doi:

**3. Conclusions and perspectives**

tions that will support technical evaluations.

for small production volumes.

**Author details**

196 Fermentation Processes

silia, DF, Brazil

**References**

Lucas Silva Carvalho1

Juliana Davies de Oliveira2


#### **Production of Lipopeptides by Fermentation Processes: Endophytic Bacteria, Fermentation Strategies and Easy Methods for Bacterial Selection Production of Lipopeptides by Fermentation Processes: Endophytic Bacteria, Fermentation Strategies and Easy Methods for Bacterial Selection**

Esteban Beltran-Gracia, Gloria Macedo-Raygoza, Juan Villafaña-Rojas, America Martinez-Rodriguez, Yur Yenova Chavez-Castrillon, Froylan M. Espinosa-Escalante, Paolo Di Mascio, Tetsuya Ogura and Miguel J. Beltran-Garcia Esteban Beltran-Gracia, Gloria Macedo-Raygoza, Juan Villafaña-Rojas, America Martinez-Rodriguez, Yur Yenova Chavez-Castrillon, Froylan M. Espinosa-Escalante, Paolo Di Mascio, Tetsuya Ogura and Miguel J. Beltran-Garcia Additional information is available at the end of the chapter

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/64236

#### **Abstract**

[16] Savinell JM, Palsson BO. Network analysis of intermediary metabolism using linear optimization. J Theor Biol 1992;154:455–73. doi:10.1016/S0022-5193(05)80162-6. [17] Moussavou G, Ko K, Lee J-H, Choo Y-K. Production of monoclonal antibodies in plants for cancer immunotherapy. Biomed Res Int 2015;2015:306164. doi:10.1155/2015/306164.

[18] Rodrigues ME, Costa AR, Henriques M, Azeredo J, Oliveira R. Technological progresses in monoclonal antibody production systems. Biotechnol Prog 2009;26:332–51. doi:

[19] Bibila TA, Robinson DK. In pursuit of the optimal fed-batch process for monoclonal antibody production. Biotechnol Prog 1995;11:1–13. doi:10.1021/bp00031a001.

[20] Chang HN, Jung K, Choi J-D-R, Lee JC, Woo H-C. Multi-stage continuous high cell

[21] Croughan MS, Konstantinov KB, Cooney C. The future of industrial bioprocessing: batch or continuous? Biotechnol Bioeng 2015;112:648–51. doi:10.1002/bit.25529. [22] Shukla AA, Thömmes J. Recent advances in large-scale production of monoclonal antibodies and related proteins. Trends Biotechnol 2010;28:253–61. doi:10.1016/

[23] Munro TP, Mahler SM, Huang EP, Chin DY, Gray PP. Bridging the gap: facilities and technologies for development of early stage therapeutic mAb candidates. MAbs

[24] Ferrara N. Pathways mediating VEGF-independent tumor angiogenesis. Cytokine

[25] Chu L, Robinson DK. Industrial choices for protein production by large-scale cell culture. Curr Opin Biotechnol 2001;12:180–7. doi:10.1016/S0958-1669(00)00197-X. [26] Jain E, Kumar A. Upstream processes in antibody production: evaluation of critical parameters. Biotechnol Adv 2008;26:46–72. doi:10.1016/j.biotechadv.2007.09.004. [27] Genentech Manufacturing 2009. http://www.gene.com/media/company-information/

[28] Tebbey PW, Varga A, Naill M, Clewell J, Venema J. Consistency of quality attributes for the glycosylated monoclonal antibody Humira® (adalimumab). MAbs 2015;7:805–11.

density culture systems: a review. Biotechnol Adv 2014;32:514–25.

Growth Factor Rev 2010;21:21–6. doi:10.1016/j.cytogfr.2009.11.003.

10.1002/btpr.348.

198 Fermentation Processes

j.tibtech.2010.02.001.

2011;3:440–52. doi:10.4161/mabs.3.5.16968.

manufacturing (accessed March 10, 2016).

doi:10.1080/19420862.2015.1073429.

Lipopeptides constitute an important class of microbial secondary metabolites. Some lipopeptides have potent therapeutic activities such as antibacterial, antiviral, antifungal, antitumor and immunomodulator. Surfactin, iturin, fengycin, lichenysin and bacillomycin D from *Bacillus* species, daptomycin from *Streptomyces roseosporus* and rhamnolipids from *Pseudomonas aeruginosa* are among the most studied lipopeptides. These molecules are good candidates to replace those antibiotics and antifungals with no effect on pathogenic microorganisms. Microbial lipopeptides are produced via fermentation processes by bacteria, yeast and actinomycetes either on water miscible and immiscible substrates. However, the major bottlenecks in lipopeptide production are yield increase and cost reduction. Improving the bioindustrial production processes relies on many issues such as selecting hyperproducing strains and the appropriate extraction techniques; purification and identification by Polymerase Chain Reaction(PCR), High Performance Liquid Chromatography-Mass Spectrometry(HPLC-MS), Matrix Assisted Laser Desorption Ionization-Time of Flight-Mass Spectrometry(MALDI-TOF-MS); the use of cheap raw materials and the optimization of medium-culture conditions. The purpose of this chapter is to orient the reader on the key elements in this field, including the selection of analytical strategies to get a good microbial strain as well as to show some examples of liquid and solid-state low-cost fermentation processes. Last, we introduce endophytic bacteria as lipopeptide-producer candidates.

© 2017 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2017 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

**Keywords:** endophytic bacteria, fermentation, lipopeptide-producers, microbial lipopeptides, quorum sensing

#### **1. Introduction**

In recent years, the production of microbial lipopeptides (LPs) has been widely studied for their biotechnological application in several areas including pharmaceutical industry, food preservation and agriculture. Lipopeptides are characterized for their highly structured diversity and their ability to decrease the surface and interfacial tension. Structurally, they consist of a hydrophilic peptide and a hydrophobic fatty acid acyl chain. The number of amino acids generally varies from 7 to 25, whereas the length of the fatty acid chains varies from 13 to 17 carbons. One strain is able to produce several isoforms of the same polypeptide. *Bacillus*- and *Paenibacillus*-related lipopeptides (firmicutes) and *Pseudomonas*-related lipopeptides (Proteobacteria) are the most studied [1,2]. Besides, LPs can also be produced by *Streptomyces* [3,4] and fungal strains [5]. The LPs are highly variable and their structural analogues results from frequent amino acid substitutions. Among the most documented LPs produced by *Bacillus* strains are surfactin, iturin, fengycin and lichenysin. On the other hand, those produced by *Pseudomonas* strains are viscosin, tensin, arthrofactin, massetolid, pseudodesmin, xantholysin, pseudofactin and syringomicin. These lipopeptides as many others, are good candidates to replace those antibiotics and antifungals with no effect on the control of pathogenic microorganisms.

Lipopeptide surfactants are naturally produced as mixtures of several macromolecules belonging to the same family or class. The nutritional parameters can influence the nature of the produced LPs [6]. However, the major limitations on their production are the production costs and yields. A wide range of carbon sources and culture conditions have been reported in order to increase the production of iturins, surfactins and fengycins. Nowadays, a variety of cheap raw materials have been used in their production: rice bran, soybean, potato peels, molasses, etc. In addition, it has been demonstrated that divalent cations have an important influence on LP production, mainly Mn2+ and Fe2+. The manganese addition to the medium culture increased yield rates from 0.33 to 2.6 g/L [7]. Furthermore, the presence of ZnSO4, FeCl3 and MnSO4 increased surfactin production in *Bacillus subtilis* [8]. In this context, we will highlight the key parameters for the maximization of LPs production and to development future strategies for optimizing liquid and solid-state fermentations (SSFs). Both fermentation types are important on industrial scale production processes.

Another important issue to address here relates to the microbial-producing strains. The genetic load of the microorganisms is a determining factor on LPs production yields, since the capacity to generate a metabolite is controlled by genes. There is a need for hyperproducer strains. But how can we recognize these over producing microbes? Lipopeptides production can be detected by: (i) culture dependent methods; (ii) methods relying on surface analysis and emulsifying activity; (iii) cell surface hydrophobicity and (iv) chemical identification [9]. An optimal and widely accepted study must combine the genetic identification and the structural and genetic analysis of the produced LPs by the particular isolate. This methodology assures the phenotypic and genotypic features of the microbial isolates for LPs production. Currently, the PCR and gene sequencing are quick tools for screening and identification of microbialproducers, as well as to identify the genes involved in the LPs synthesis. Also, the isolation and identification techniques such as liquid chromatography coupled to mass spectrometry (LC-MS) and more recently the MALDI-TOF mass spectrometry, have been considered as the fastest and most efficient tools for identification of LPs in mixtures and peptide sequencing, respectively. These techniques are also useful to identify the most novel LPs and even the small compositional changes in the sequence of amino acids that will determine its properties. There is no doubt, that these tools will increase and incentive the development of this field in fermentation processes.

In our lab, we are particularly interested in bacterial endophytes. By definition, an endophyte is a bacteria or fungus that lives in the internal tissues of plants without disease manifestation. Endophytes are ubiquitous to virtually all-terrestrial plants. With the increasing appreciation of studies that unravel the mutualistic interactions between plant and microbes, functions of endophytes are gaining value, so these microorganisms have become the target of biotechnological developments for biological control of plant pathogens (fungi and bacteria). We have evidence that a large group of endophytic bacteria have the ability to eradicate their competitors (pathogens) from the niche using LPs. In this chapter, we are interested in discussing endophytic microorganisms known as lipopeptide-producers beyond the genus *Bacillus*. We believe this information will be of value for alternative research in agricultural microbiology as well as for the production of antimicrobial molecules. However, given that some endophytic bacteria have a closer relationship with human pathogens, the application on commercial crops as biopesticides is strictly regulated. This last point impacts negatively the use endophytic microbes as tools for disease control and the development of new bioinoculants for agriculture; therefore, such LPs must be produced by fermentation.

Finally, it must be considered that the production of biosurfactants is associated with the physiological status of the bacteria, where quorum sensing (QS) is probably a condition. Quorum sensing is perhaps an overlooked variable in fermentation processes. In this chapter, we try to explain how this phenomenon and other conditions can alter the performance of LP production.

#### **2. Lipopeptides: classes, microbial producers, fermentation processes and downstream processes**

#### **2.1. Classes of lipopeptides and their applications**

**Keywords:** endophytic bacteria, fermentation, lipopeptide-producers, microbial lipo-

In recent years, the production of microbial lipopeptides (LPs) has been widely studied for their biotechnological application in several areas including pharmaceutical industry, food preservation and agriculture. Lipopeptides are characterized for their highly structured diversity and their ability to decrease the surface and interfacial tension. Structurally, they consist of a hydrophilic peptide and a hydrophobic fatty acid acyl chain. The number of amino acids generally varies from 7 to 25, whereas the length of the fatty acid chains varies from 13 to 17 carbons. One strain is able to produce several isoforms of the same polypeptide. *Bacillus*- and *Paenibacillus*-related lipopeptides (firmicutes) and *Pseudomonas*-related lipopeptides (Proteobacteria) are the most studied [1,2]. Besides, LPs can also be produced by *Streptomyces* [3,4] and fungal strains [5]. The LPs are highly variable and their structural analogues results from frequent amino acid substitutions. Among the most documented LPs produced by *Bacillus* strains are surfactin, iturin, fengycin and lichenysin. On the other hand, those produced by *Pseudomonas* strains are viscosin, tensin, arthrofactin, massetolid, pseudodesmin, xantholysin, pseudofactin and syringomicin. These lipopeptides as many others, are good candidates to replace those antibiotics and antifungals with no effect on the control of pathogenic microorganisms.

Lipopeptide surfactants are naturally produced as mixtures of several macromolecules belonging to the same family or class. The nutritional parameters can influence the nature of the produced LPs [6]. However, the major limitations on their production are the production costs and yields. A wide range of carbon sources and culture conditions have been reported in order to increase the production of iturins, surfactins and fengycins. Nowadays, a variety of cheap raw materials have been used in their production: rice bran, soybean, potato peels, molasses, etc. In addition, it has been demonstrated that divalent cations have an important influence on LP production, mainly Mn2+ and Fe2+. The manganese addition to the medium culture increased yield rates from 0.33 to 2.6 g/L [7]. Furthermore, the presence of ZnSO4, FeCl3 and MnSO4 increased surfactin production in *Bacillus subtilis* [8]. In this context, we will highlight the key parameters for the maximization of LPs production and to development future strategies for optimizing liquid and solid-state fermentations (SSFs). Both fermentation

Another important issue to address here relates to the microbial-producing strains. The genetic load of the microorganisms is a determining factor on LPs production yields, since the capacity to generate a metabolite is controlled by genes. There is a need for hyperproducer strains. But how can we recognize these over producing microbes? Lipopeptides production can be detected by: (i) culture dependent methods; (ii) methods relying on surface analysis and emulsifying activity; (iii) cell surface hydrophobicity and (iv) chemical identification [9]. An optimal and widely accepted study must combine the genetic identification and the structural

types are important on industrial scale production processes.

peptides, quorum sensing

**1. Introduction**

200 Fermentation Processes

The production of LPs in their active form requires transcriptional induction, translation and post-translational modifications. The main machinery for their synthesis is multi-modular and consists of non-ribosomal peptide synthetases (NRPSs) [10]. Synthetases are organized on modules; each module permits the incorporation of a specific amino acid, subsequent condensation, termination and cyclization of the peptide chain. The synthesized peptides contain d-amino acids, β-amino acids and hydroxyl- or *N*-methylated amino acids. The integrated system introduces heterogeneity among LPs. The peptide moiety is inactive until it is coupled to a fatty acyl chain. The lipid aliphatic chain, of variable length, fuses with the N-terminal residue of the peptide chain, and then the bioactive LP is generated. After the biosynthesis of the LPs is finished, the molecule is modified by glycosylation or halogenation by specific enzymes associated to the synthetases [11].


**Table 1.** Important and the most studied lipopeptides from *Bacillus*, *Pseudomonas* and *Streptomyces* and their activity roles.

Many bacteria and some fungi produce LPs, which have several roles including activity against bacteria, fungi, virus and more recently, it has been discovered their antitumor activity. Lipopeptides are also are involved in bacterial motility, in the swarming behavior and in the attachment to surfaces [1]. On the other hand, the extensive use of chemicals to control pathogens (bacteria and fungi) has modified the behavior of these microorganisms in humans and plants. The growing drug resistance, in these pathogens, urges for alternative antimicrobial molecules for clinical and crop protection, as well as for food preservation. As we mentioned above, LPs can be cyclic or linear based on the topology of the peptide chain. Here, we

Production of Lipopeptides by Fermentation Processes: Endophytic Bacteria, Fermentation Strategies and Easy... http://dx.doi.org/10.5772/64236 203

d-amino acids, β-amino acids and hydroxyl- or *N*-methylated amino acids. The integrated system introduces heterogeneity among LPs. The peptide moiety is inactive until it is coupled to a fatty acyl chain. The lipid aliphatic chain, of variable length, fuses with the N-terminal residue of the peptide chain, and then the bioactive LP is generated. After the biosynthesis of the LPs is finished, the molecule is modified by glycosylation or halogenation by specific

> -Enhanced oil recovery Antibacterial Antiviral Antimycoplasma Antitumoral Anticoagulant Enzyme inhibition


*Mycobacterium tuberculosis*, Gram positive bacteria, *G. candidum* and *R. pilimanae*

(MRSA), beta-hemolytic *Streptococcus spp*., *Pneumococci, Clostridium spp., and Enterococci sp.*


*Pseudomonas sp* -Antibacterial and Antifungal activity against;

*Staphylococcus aureus* -Antiparasitic -Immunosuppressor


fungi

–MRSA

Daptomycin *Streptomyces roseosporus* -Broad spectrum activity against *staphylococci*

**Table 1.** Important and the most studied lipopeptides from *Bacillus*, *Pseudomonas* and *Streptomyces* and their activity

Many bacteria and some fungi produce LPs, which have several roles including activity against bacteria, fungi, virus and more recently, it has been discovered their antitumor activity. Lipopeptides are also are involved in bacterial motility, in the swarming behavior and in the attachment to surfaces [1]. On the other hand, the extensive use of chemicals to control pathogens (bacteria and fungi) has modified the behavior of these microorganisms in humans and plants. The growing drug resistance, in these pathogens, urges for alternative antimicrobial molecules for clinical and crop protection, as well as for food preservation. As we mentioned above, LPs can be cyclic or linear based on the topology of the peptide chain. Here, we

**Lipopeptides** *Microbial-producers* **Activity roles**

*B. subtilis B. polyfermenticus B. megaterium B. licheniformis B. pumilus B. amyloliquefaciens*

*B. subtilis B. megaterium*

*B. subtilis B. thuringiensis B. circulans B. megaterium*

enzymes associated to the synthetases [11].

pumilacidin WH1 fungin

Bacillomycins Mycosubtilin Subtulene (contains a unique Iso C15-long chain *β* -amino acid)

Plipastatin Agrastatin1

Viscosin Massetolide Entolysin

Surfactin family Surfactin linchenysin

Iturin family Iturin

202 Fermentation Processes

Fengycin family Fengycin

*Pseudomonas sp.* Lipopeptides

*Streptomyces sp.* Lipopeptides

roles.

**Figure 1.** Pharmaceutically and economically important lipopeptides. Structures of representative member of lipopeptide synthesized by *Bacillus* and *Streptomyces*. (A) Daptomycin, (B) surfactin, (C) iturin and (D) fengycin.

present an updated overview on the bioactive LPs and their uses, being the cyclic lipopeptides the most biologically relevant with proved activity and more market applications in several fields. The characteristics of the LPs are discussed below, and their properties, structures and uses have been summarized in **Table 1** and **Figure 1**.

**Daptomycin.** This structure is a cyclic decanoyl lipid chain attached to 13 amino acids (a 10 member macrolactone and three exocyclic residues) peptide. It is produced by *Streptomyces roseosporus*, a Gram-positive bacterium. It has potent antimicrobial properties and it has been clinically approved for its use as antibiotic since 2003. It is marketed under the tradename Cubicin. The mode of action of daptomycin is still unclear, but two hypotheses have been proposed, the first one states the inhibition of lipoteichoic acid synthesis (proteoglycan component of the cell wall of Gram-positive bacteria); the second states the disruption of bacterial membrane potential (depolarization) via pore formation and its calcium ion dependence. Concomitantly, the bacterial cell loses the ability to accumulate amino acid substrates while leaving glucose uptake intact [12,13]. It has been successfully used to control skin infections, endocarditis, osteomyelitis and soft-tissue infections [14]. The cost of daptomycin in the market is approximately €125/day at dose of 6 mg/kg/day.

**Surfactin.** Surfactins constitute a major class of antibiotic LPs produced by *Bacillus* spp. They are highly active biosurfactants able to reduce the surface tension of water to 27 mN m−1 at 20 μmol. This group consist of a heptapeptide bonded to a C13–C15 fatty acyl chain [15]. Surfactins are able to permeate the lipid membranes as dimer and form ion channels in planar lipid bilayer membranes. These compounds are effective against Gram-positive and Gram-negative bacteria and also have antimycoplasma, antiviral and antitumor activity and suppress inflammatory responses through inhibition of phospholipase A2 [16,17]. Surfactin also inhibits phytopathogens such as *Pseudomonas syringae*, *Xanthomonas axonopodis*, *Sclerotinia sclerotium*, *Botrytis cinerea*, *Colletotrichum gloeosporioides* and stimulates plant defense [18,19]. Since surfactins have hemolytic activity their medical applications are limited.

**Iturins.** Iturin is an antifungal cyclic lipopeptide produced by *Bacillus* spp. These amphiphilic compounds are characterized by a peptide ring of seven amino acid residues including an invariable d-Tyr2, with the constant chiral sequence LDDLLDL closed by a C14–C17 aliphatic β-amino acid. Iturins have a high polymorphism due to amino acid variations. These variants including iturin A, iturin C, iturin D, iturin E, Bacillomycin D, Bacillomycin F, Bacillomycin Lc, Mojavensin A and mycosubtilin [20]. Iturin A has been shown to form potassium ionconducting channels in lipid bilayers. Iturins can act as biocontrol agents of plant pathogens [14]. They exert their fungicidal action by interacting with sterol components in the fungal membrane. Mojavensin A, a new member of the family, is cytotoxic [21]. From a clinical perspective, a disadvantage associated with iturins is their haemolytic activity.

**Fengycins.** This class of cyclic lipopeptides includes fengycins and plispastatins produced by some *Bacillus* and *Paenibacillus* strains. Fengicins are decapetides acylated with a βhydroxylipid tail (C14–C18) and cyclized between the phenol side chain of Tyr 3 and the Cterminus. They act on plasma membrane of fungal cells and have been suggested for agriculture. They have antitumor activity because of the production of reactive oxygen species and mitochondria-dependent apoptosis [22]. They are good candidates for medical applications due their milder haemolytic activity.

**Pseudofactin I and II.** These compounds are cyclic octapeptides bonded to palmitic acid produced by *Pseudomonas fluorescens* BD5. The C-terminal of the carboxylic group forms a lactone with the –OH of threonine. Their emulsification activity and stability are greater in comparison to other synthetic surfactants, thus have a great potential for bioremediation or biomedicine. For example, Pseudofactin II exerts cytotoxicity in human melanoma [23].

**Viscosin** is obtained from *Pseudomonas fluorescens*. It has antibiotic activity, is highly surface active and is able to inhibit the migration of cancer cells. In *Pseudomonas*, this LP protects it from protozoan predation. Viscosin increases the efficiency of surface spreading over plant roots and protects germinating seedlings in soil infected with plant pathogen [24].

**Linear cationic lipopeptides.** Limited research has been performed on this small group. This is surprising as they have the potential to be more accessible than cyclic lipopeptides. This group includes saltavalin (which was named because contains serine, alanine, leucine, threonine, valine and 2,4-diaminobutyric acid, isolated from *P. polymyxa*), jolipeptin (*B. polymyxa*), cerexins (*B. cereus*, *B. mycoides*), tridecaptins (*P. terrae*). All exhibit antibacterial activity against Gram-negative and Gram-positive bacteria.

#### **2.2. Endophytic bacteria as lipopeptide-producers**

Due to the nature of the endophytic life style, endophytic microbes establish a long-lasting stable relationship with the plant. In this symbiotic association, the plant provides nutrients and shelter for the microbes and, in turn, the endophyte benefits plants by imparting biotic and abiotic stress tolerance and promoting its growth. Some endophytes are known to produce anti-pest compounds. These bioactive secondary metabolites can be either directly involved in antibiosis and/or triggering induced systemic resistance (ISR). There have been published some reports of the production of LPs by endophytic bacteria that may explain the antifungal or antibacterial activity on plant pathogens. Recently, Gond et al. reported an endophytic *Bacillus* that produces antifungal LPs and host defense gene expression in maize [25]. Understanding the mechanism of biological control helps to manipulate the environment to create conditions for better biocontrol. Nowadays, in Mexico, some groups are developing research focused in field applications of LPs rather than bacteria, since many of the bacteria belong to genera related to human pathogens. In unpublished studies from our group, we have found strains of bacteria with the ability to produce LPs isolated from plants, including agave, banana and maize (Beltran-Gracia, manuscript in preparation). In **Table 2**, we list some of endophytic strains reported to be lipopeptide-producers.


**Table 2.** Endophytic bacteria reported as lipopeptide-producers.

**Iturins.** Iturin is an antifungal cyclic lipopeptide produced by *Bacillus* spp. These amphiphilic compounds are characterized by a peptide ring of seven amino acid residues including an invariable d-Tyr2, with the constant chiral sequence LDDLLDL closed by a C14–C17 aliphatic β-amino acid. Iturins have a high polymorphism due to amino acid variations. These variants including iturin A, iturin C, iturin D, iturin E, Bacillomycin D, Bacillomycin F, Bacillomycin Lc, Mojavensin A and mycosubtilin [20]. Iturin A has been shown to form potassium ionconducting channels in lipid bilayers. Iturins can act as biocontrol agents of plant pathogens [14]. They exert their fungicidal action by interacting with sterol components in the fungal membrane. Mojavensin A, a new member of the family, is cytotoxic [21]. From a clinical

**Fengycins.** This class of cyclic lipopeptides includes fengycins and plispastatins produced by some *Bacillus* and *Paenibacillus* strains. Fengicins are decapetides acylated with a βhydroxylipid tail (C14–C18) and cyclized between the phenol side chain of Tyr 3 and the Cterminus. They act on plasma membrane of fungal cells and have been suggested for agriculture. They have antitumor activity because of the production of reactive oxygen species and mitochondria-dependent apoptosis [22]. They are good candidates for medical applica-

**Pseudofactin I and II.** These compounds are cyclic octapeptides bonded to palmitic acid produced by *Pseudomonas fluorescens* BD5. The C-terminal of the carboxylic group forms a lactone with the –OH of threonine. Their emulsification activity and stability are greater in comparison to other synthetic surfactants, thus have a great potential for bioremediation or biomedicine. For example, Pseudofactin II exerts cytotoxicity in human melanoma [23].

**Viscosin** is obtained from *Pseudomonas fluorescens*. It has antibiotic activity, is highly surface active and is able to inhibit the migration of cancer cells. In *Pseudomonas*, this LP protects it from protozoan predation. Viscosin increases the efficiency of surface spreading over plant

**Linear cationic lipopeptides.** Limited research has been performed on this small group. This is surprising as they have the potential to be more accessible than cyclic lipopeptides. This group includes saltavalin (which was named because contains serine, alanine, leucine, threonine, valine and 2,4-diaminobutyric acid, isolated from *P. polymyxa*), jolipeptin (*B. polymyxa*), cerexins (*B. cereus*, *B. mycoides*), tridecaptins (*P. terrae*). All exhibit antibacterial

Due to the nature of the endophytic life style, endophytic microbes establish a long-lasting stable relationship with the plant. In this symbiotic association, the plant provides nutrients and shelter for the microbes and, in turn, the endophyte benefits plants by imparting biotic and abiotic stress tolerance and promoting its growth. Some endophytes are known to produce anti-pest compounds. These bioactive secondary metabolites can be either directly involved in antibiosis and/or triggering induced systemic resistance (ISR). There have been published some reports of the production of LPs by endophytic bacteria that may explain the antifungal

roots and protects germinating seedlings in soil infected with plant pathogen [24].

activity against Gram-negative and Gram-positive bacteria.

**2.2. Endophytic bacteria as lipopeptide-producers**

perspective, a disadvantage associated with iturins is their haemolytic activity.

tions due their milder haemolytic activity.

204 Fermentation Processes

#### **2.3. Lipopeptide production by fermentation process: culture conditions and operational conditions**

In order to incorporate LPs into industrial processes and for medical, pharmaceutical and agricultural uses, it is required their production by fermentation and their posterior downstream. It is clear that one of the main limitations for commercial applications of LPs are the high production costs and the low yield. To overcome these barriers, many efforts have been focused in improving the fermentation process, which represents a fundamental stage in the global production. Lipopeptides have been reported as growth-associated metabolites. In contrast to other bacterial secondary metabolites, production of LPs is induced when the cells have exhausted one or more essential nutrients, in example, surfactin production is induced in actively growing cells during the transition from exponential to stationary phase (SP); fengycin synthesis is related to the early SP, and iturins only accumulate in the later SP [1].

The production of LPs can be achieved by liquid fermentation (LF) or solid-state fermentation (SSF) and now, both methods have been proposed for scale up their industrial production. The LF is an advantageous and typical process used for LPs production in controlled bioreactors, while SSF is still in evolution but has gained attention owing its priority to LF, including lower investment for production, less time and higher secondary metabolite yields.

A critical factor into industrial LP production is media optimization. In fact, the nature of the carbon substrate, N, P, Na, Mg, Fe, Zn and Mn ions concentration in the medium, have been shown to influence enormously the nature and quantity of the LP produced by several bacterial strains. An orderly and planned statistical procedure to screen the effect of each component of the media is very useful. For example, a Plackett-Burman procedure was applied to find that glucose, K2HPO4, and urea concentrations had the most influence into LPs production by *Bacillus subtilis* of 11 tested variables (glucose, urea, ammonium sulfate, NaCl, MgSO4, KH2PO4, K2HPO4, MnSO4, FeSO4, ZnSO4). After, a Central Composite Design was conducted to optimize the three selected factors, finding a maximum biosurfactant concentration of 3.1 g/L when using 15 g/L glucose, 6 g/L urea and 1 g/L K2HPO4, keeping the other parameters at their minimum values [26]. A similar statistical procedure was also applied to determine the effect of sucrose, ammonium nitrate, NaH2PO4, K2HPO4, MgSO4, MnCl2, extract yeast as components of culture media to growth *Bacillus amyloliquefaciens*, using the Plackett-Burman design in the production of C15-surfactin, indicated a significant effect of sucrose, ammonium nitrate and NaH2PO4. The optimum values of the tested variables were 21.17 g/L sucrose, 2.50 g/L ammonium nitrate and 11.56 g/L NaH2PO4 with a production of 134.2 mg/L LP [27]. In a third case, a five-level four-factor Central Composite Design was employed to determine the maximum LP yield by *Bacillus subtilis* testing sucrose, ammonium chloride, ferrous sulphate and zinc sulphate. Optimum fermentation components were 22.431 g/L of sucrose, 2.781 g/L of ammonium chloride, 6.7879 mM of FeSO4 and 0.0377 mM of ZnSO4 to produce 1.712 g/L of LP. Only the ammonium chloride had no significant effect [28].

#### *2.3.1. Carbon sources to optimize lipopeptide production*

It is clear the importance of carbon source in any fermentation process due to its impact in the bacterial metabolism as well as in production costs. The nature and quantity of the carbon source are the most important factors that would affect LPs production. Structural and compositional diversity of LPs is substrate dependent. For example, *Bacillus amyloliquefaciens* was grown in a minimal salt medium with different carbon sources (sucrose, dextrose, maltose, lactose, glycerol and sorbitol) where a C:N ratio remained constant at 15.55. The surfactin, iturin and fengycin were detected when dextrose, sucrose and glycerol were used as carbon source. However, in the presence of maltose, lactose and sorbitol only iturin was produced. Also, these carbon sources significantly influenced the antifungal activity of the molecules. Those bacteria grown in media supplemented with dextrose or sucrose produced LPs with the higher antifungal activity. The maximum biosurfactant activity was observed when the growing minimal salt medium was supplemented with sucrose [29]. In a similar study, it was reported that among several carbon sources: glucose, sucrose, galactose, maltose, sucrose, glycerol, mannitol, soluble starch and dextrin, evaluated for C15-surfactin production, sucrose was the best carbon source [27].

#### *2.3.2. Nitrogen sources*

in actively growing cells during the transition from exponential to stationary phase (SP); fengycin synthesis is related to the early SP, and iturins only accumulate in the later SP [1].

The production of LPs can be achieved by liquid fermentation (LF) or solid-state fermentation (SSF) and now, both methods have been proposed for scale up their industrial production. The LF is an advantageous and typical process used for LPs production in controlled bioreactors, while SSF is still in evolution but has gained attention owing its priority to LF, including lower

A critical factor into industrial LP production is media optimization. In fact, the nature of the carbon substrate, N, P, Na, Mg, Fe, Zn and Mn ions concentration in the medium, have been shown to influence enormously the nature and quantity of the LP produced by several bacterial strains. An orderly and planned statistical procedure to screen the effect of each component of the media is very useful. For example, a Plackett-Burman procedure was applied to find that glucose, K2HPO4, and urea concentrations had the most influence into LPs production by *Bacillus subtilis* of 11 tested variables (glucose, urea, ammonium sulfate, NaCl, MgSO4, KH2PO4, K2HPO4, MnSO4, FeSO4, ZnSO4). After, a Central Composite Design was conducted to optimize the three selected factors, finding a maximum biosurfactant concentration of 3.1 g/L when using 15 g/L glucose, 6 g/L urea and 1 g/L K2HPO4, keeping the other parameters at their minimum values [26]. A similar statistical procedure was also applied to determine the effect of sucrose, ammonium nitrate, NaH2PO4, K2HPO4, MgSO4, MnCl2, extract yeast as components of culture media to growth *Bacillus amyloliquefaciens*, using the Plackett-Burman design in the production of C15-surfactin, indicated a significant effect of sucrose, ammonium nitrate and NaH2PO4. The optimum values of the tested variables were 21.17 g/L sucrose, 2.50 g/L ammonium nitrate and 11.56 g/L NaH2PO4 with a production of 134.2 mg/L LP [27]. In a third case, a five-level four-factor Central Composite Design was employed to determine the maximum LP yield by *Bacillus subtilis* testing sucrose, ammonium chloride, ferrous sulphate and zinc sulphate. Optimum fermentation components were 22.431 g/L of sucrose, 2.781 g/L of ammonium chloride, 6.7879 mM of FeSO4 and 0.0377 mM of ZnSO4 to produce 1.712 g/L of

It is clear the importance of carbon source in any fermentation process due to its impact in the bacterial metabolism as well as in production costs. The nature and quantity of the carbon source are the most important factors that would affect LPs production. Structural and compositional diversity of LPs is substrate dependent. For example, *Bacillus amyloliquefaciens* was grown in a minimal salt medium with different carbon sources (sucrose, dextrose, maltose, lactose, glycerol and sorbitol) where a C:N ratio remained constant at 15.55. The surfactin, iturin and fengycin were detected when dextrose, sucrose and glycerol were used as carbon source. However, in the presence of maltose, lactose and sorbitol only iturin was produced. Also, these carbon sources significantly influenced the antifungal activity of the molecules. Those bacteria grown in media supplemented with dextrose or sucrose produced LPs with the higher antifungal activity. The maximum biosurfactant activity was observed when the growing minimal salt medium was supplemented with sucrose [29]. In a similar study, it was

investment for production, less time and higher secondary metabolite yields.

206 Fermentation Processes

LP. Only the ammonium chloride had no significant effect [28].

*2.3.1. Carbon sources to optimize lipopeptide production*

Several inorganic nitrogen compounds have been tested in LP production trials, i.e. ammonium nitrate, ammonium sulphate, sodium nitrate, urea and glutamic sodium. And looking for cheaper raw materials, complex compounds such as soybean flour, peptone and casein acid hydrolysate have been assayed too [27]. When using organic nitrogen sources it was observed that tryptone enhances the lipopeptide production because it contains several homologous Lamino acids to those found in LPs [30]. A similar behavior was reported in the modified Landy medium, where l-glutamic acid was replaced with various L-α-amino acids at the same concentration (5 g/L). Cottonseed-derived medium (Pharmamedia) proved to be a suitable substrate for the production of 220 mg/L of surfactin from *Bacillus subtilis*; this medium is suitable to achieve high production yields at low cost, which in turn makes it profitable for large scale usage. Moreover, supplementing Pharmamedia with Fe2+ (4.0 mM) and sucrose (2 g/L) leads to a maximum production of about (300 mg/L) [31]. Other interesting nitrogen source is rapeseed meal, a low-cost material that was used to synthetize iturin A by *Bacillus subtilis*. The maximum iturin A concentration was 0.60 g/L after 70 h of incubation, which was 20% and 8.0 times higher than that achieved with peptone and ammonium nitrate media, respectively [32].

#### *2.3.3. Divalent ions*

To optimize the trace element composition of culture media the use of statistical experimental designs is preferred. Such is the case, where was doubled surfactin concentration when was applied the statistical method Taguchi to determine cation effect of culture medium [33]. The role of Fe2+ in the synthesis of LPs is crucial; there are some reports where the supplementation of this cation enhanced the yield of biosurfactants [31,33]. The addition of Fe2+ into fermentation medium was utilized to optimize surfactin production from *Bacillus subtilis*, reaching yields up to 3 g/L into minimal salt medium; the optimal Fe2+ dosage (4.0 mM) leading to 8-fold and 10-fold increments in cell concentration and surfactin yield, respectively, as compared to those media without Fe2+ [34]. *Bacillus amyloliquefaciens* in a culture medium supplemented with 0.2 mM of iron was able to produce 92.78 mg/L of iturin after 5 days with no pH control in the culture. Moreover, if the starting pH at 6.64 and 0.2 mM of ferrous sulphate, an iturin A production of 121.28 mg/L was obtained [35].

#### *2.3.4. Operational conditions*

The pH, temperature, dissolved oxygen concentration and degree of aeration affect cellular growth, and consequently, biosurfactant production. Optimal operational conditions vary from strain to strain, and the better growing condition for each particular strain must be determined experimentally. For example, surfactin synthesis by *Bacillus subtilis* can be achieved at temperatures ranging from 25 to 37°C; the optimal temperature for the surfactin production by *Bacillus subtilis* DSM 3256 was 37.4°C. In contrast, for thermophilic *Bacillus* spp. surfactins were produced at temperatures above 40°C without detriment on their activity [36]. Regarding pH, a greater LP activity was observed when the pH was adjusted to between 3.0 and 8.0.

Statistical tools had been used to optimize LP biosynthesis considering operational conditions. The response surface methodology has been used to determine the maximum LP production varying the temperature, initial pH and culture cycle. Another important condition to be controlled is the dissolved oxygen. The oxygen acted at different levels, suggesting a complex system for regulating the synthesis of LP in B. *subtilis* ATCC6633. So, the oxygen transfer is one of the critical parameters for process optimization and scaling-up of production of surfactin [36]. Varying the oxygen transfer conditions, the synthesis could be oriented to mixed production or to surfactin monoproduction. The fraction of surfactin towards total LPs produced and the maximal surfactin production both increased with *k*La increase (surfactin concentration about 2 g/L at *k*La = 0.04–0.08 s−1), while the maximal fengycin production (fengycin concentration about 0.3 g/L) was obtained at moderate oxygen supply (*k*La = 0.01 s−1). The production of LP represents a challenge due to its surface properties. Foam causes a severe decrease of oxygen transfer. A significant decrease of *k*La (up to 27%) was measured during fermentation process reduces LP biosynthesis [37].

Classical bioreactors aerated by gas bubbling are not suitable for production of LP biosurfactants due to excessive foaming. The use of antifoam agents is not appropriate because it can affect the bacterial physiology and downstream processing. The alternatives are bioreactor with foam collector, rotating discs biofilm reactor [38], bubbleless membrane aerated bioreactor [39] and three-phase inverse fluidized bed bioreactor [40]. Another alternative to foam control is the use of a strictly anaerobic bioreactor cultivation to produce surfactin. Most interesting, the product yields exceeded classical aerobic fermentations, in which foam fractionation was applied. Additionally, values for specific production rate surfactin (0.005 g/ (g h)) and product yield per consumed substrate (*Y*P/S = 0.033 g/g) surpass results of comparable foam-free processes [41]. The bioreactor design is still a challenge to get better productivities in industrial processes; the LPs synthesis is not an exception.

#### **2.4. Solid-state fermentation (SSF)**

Solid-state fermentation (SSF) is an alternative technology for the production of high-value molecules. The SSF could be an alternative method for the LPs production. The SSF uses agroindustrial wastes as substrates, which contributes to reduce the production costs. The productivity of LPs synthetized by SSF depends on initial moisture content, incubation temperature, fermentation time, substrates used and supplementary nutrients such as mineral salts. The temperature is an important parameter for both bacterial growth and LP production. Within a range from 25 to 40°C, the optimal temperature for growth was found to be 30°C, but the biosynthesis of LPs is favored at 37°C. At the beginning, in the firsts 24 h, temperature should be maintained at 30°C, then shifted up to 37°C to enhance LP production [42].

The selection of raw materials to formulate a culture medium, as the previously described, requires experimental tests. Savings in time and resources can be achieved using statistical tion by *Bacillus subtilis* DSM 3256 was 37.4°C. In contrast, for thermophilic *Bacillus* spp. surfactins were produced at temperatures above 40°C without detriment on their activity [36]. Regarding pH, a greater LP activity was observed when the pH was adjusted to between 3.0

Statistical tools had been used to optimize LP biosynthesis considering operational conditions. The response surface methodology has been used to determine the maximum LP production varying the temperature, initial pH and culture cycle. Another important condition to be controlled is the dissolved oxygen. The oxygen acted at different levels, suggesting a complex system for regulating the synthesis of LP in B. *subtilis* ATCC6633. So, the oxygen transfer is one of the critical parameters for process optimization and scaling-up of production of surfactin [36]. Varying the oxygen transfer conditions, the synthesis could be oriented to mixed production or to surfactin monoproduction. The fraction of surfactin towards total LPs produced and the maximal surfactin production both increased with *k*La increase (surfactin concentration about 2 g/L at *k*La = 0.04–0.08 s−1), while the maximal fengycin production (fengycin concentration about 0.3 g/L) was obtained at moderate oxygen supply (*k*La = 0.01 s−1). The production of LP represents a challenge due to its surface properties. Foam causes a severe decrease of oxygen transfer. A significant decrease of *k*La (up to 27%) was measured during

Classical bioreactors aerated by gas bubbling are not suitable for production of LP biosurfactants due to excessive foaming. The use of antifoam agents is not appropriate because it can affect the bacterial physiology and downstream processing. The alternatives are bioreactor with foam collector, rotating discs biofilm reactor [38], bubbleless membrane aerated bioreactor [39] and three-phase inverse fluidized bed bioreactor [40]. Another alternative to foam control is the use of a strictly anaerobic bioreactor cultivation to produce surfactin. Most interesting, the product yields exceeded classical aerobic fermentations, in which foam fractionation was applied. Additionally, values for specific production rate surfactin (0.005 g/ (g h)) and product yield per consumed substrate (*Y*P/S = 0.033 g/g) surpass results of comparable foam-free processes [41]. The bioreactor design is still a challenge to get better productivities

Solid-state fermentation (SSF) is an alternative technology for the production of high-value molecules. The SSF could be an alternative method for the LPs production. The SSF uses agroindustrial wastes as substrates, which contributes to reduce the production costs. The productivity of LPs synthetized by SSF depends on initial moisture content, incubation temperature, fermentation time, substrates used and supplementary nutrients such as mineral salts. The temperature is an important parameter for both bacterial growth and LP production. Within a range from 25 to 40°C, the optimal temperature for growth was found to be 30°C, but the biosynthesis of LPs is favored at 37°C. At the beginning, in the firsts 24 h, temperature

should be maintained at 30°C, then shifted up to 37°C to enhance LP production [42].

The selection of raw materials to formulate a culture medium, as the previously described, requires experimental tests. Savings in time and resources can be achieved using statistical

fermentation process reduces LP biosynthesis [37].

in industrial processes; the LPs synthesis is not an exception.

**2.4. Solid-state fermentation (SSF)**

and 8.0.

208 Fermentation Processes

methods, which help in optimizing components and concentrations in the formulation of a culture medium. The optimal composition of culture medium in solid-state fermentation to get the highest LP production had been determined using a 'Central Composite Design'. First, a screen to select the major solid substrates was performed, where rapeseed meal, corn flour, soybean flour, bean cake, wheat bran, rice hull and rice straw were considered as candidates to support bacterial growth and biosurfactant production. For the election, a quantity of each solid substrate was supplemented with 1.0 ml of mineral solution with initial pH 7.5 and moisture content 55%. To increase the porosity of the substrates and improve its availability, each of them was mixed with an inert substrate (perlite, vermiculite, beads). After that, both easily digestible carbon sources (glucose, sucrose, starch, l-glutamic, maltose, glycerol, dgalactose) and nitrogen sources (tryptone, peptone, yeast extract, urea, NH4NO3, NH4Cl, (NH4)2SO4 at 2% (w/w) were added. The substrates selected to the optimization of the medium composition for LP production by 'Response Surface Methodology' were soybean flour, rice straw, starch and yeast extract. The optimal conditions were 1.79% starch and 1.91% yeast extract by employing 5.58 g soybean flour and 3.67 g rice straw as the solid substrate with initial pH 7.5, moisture content 55% and a 10% inoculum level at 30°C for 2 days. Under these conditions, the experimental yield of LPs reached 50.01 mg/gram of dry substrates [43]. SSF many times is compared with submerged fermentation. By this reason, a comparative study was performed to determine the compositions and properties of LP products purified and the transcription values of LP genes under submerged fermentation and SSF. Results revealed no significant differences in the polarity and structure of the two LP products. But, LP obtained by submerged fermentation possessed higher amino acid proportions, better emulsification activity and antagonistic activity than that from solid-state fermentation. For solid-state fermentation, the transcription accumulation levels of the LP synthetic genes srfA and sfp were higher than for submerged fermentation at the same stage. Transcripts for ituD and lpa-14 remained elevated for a longer period of time under solid-state fermentation conditions, accounting for differences in the production and fermentation periods between both fermentation techniques [44].

#### **2.5. Downstream processing: isolation and purification of lipopeptides from fermentation process**

Due to different applications of LPs, we need different levels of purity. Crude LPs can straightaway be used in bioremediation related applications, where the overall economy of the process is the most important concern. On the other hand, partially purified fractions (about 60–80% pure) can suit applications in microemulsion based nanoparticle synthesis, laundry and food industry. However, the requirement for ultrahigh pure product is indispensable, if the LPs are to be considered for pharmaceuticals and human healthcare [45]. As we mentioned before, the intense foaming produced during aerobic liquid fermentation is a big obstacle for the commercialization making their recovery and purification difficult. A great deal of monetary input will be required for purification, this account 60% of the total production cost. Different techniques have been developed to extract and purify LPs. Among the most used techniques to extract are acid precipitation (HCl 6N), solvent extraction (chloroform, ethyl acetate, dichloromethane or mixtures of chloroform-methanol), ammonium sulphate precipitation with dialysis to remove small molecules and salts, and foam fractionation (utilized for continuous retention process and high purity). For purification normally have been used membrane ultrafiltration techniques, ionic exchange chromatography and adsorptiondesorption on resins (XAD-4, XAD-7 HP, HP-2MG, HP-20) or activated carbon. The High Performance Liquid Chromatography(HPLC) (an excellent method for separation of this class of molecules) uses a reverse phase with C18 columns. The LPs separated can be detected using ultraviolet absorbance or diode arrays detectors and each peak separated is collected using a fraction collector for further analysis of their structure.

#### *2.5.1. Example of techniques used for lipopeptide recovery, purification and identification*

**Membrane ultrafiltration.** This technique serves essentially as an intermediate process for the recovery and purification of LPs. The separation of LPs by membrane filtration depends on their molecular aggregation behavior and on their ability to form micelles, since a process become economic feasible when a high MWCO (molecular weight cut-off) membranes were used. In general, the use of low MWCO membranes requires high maintenance due to low permeate fluxes through smaller pores that get easily plugged by monomers and progressive reduction in flux caused by the mechanism of concentration polarization [45].

A two-step ultrafiltration process using large pore size membranes (up to MWCO = 300 kDa) was investigated to separation of LPs aggregated in single and mixed solutions from fermentation culture. In single solutions of LP both surfactin and mycosubtilin formed micelles of different size depending on their concentration. However when the LPs were in the same solution, they formed mixed micelles of different size and probably conformation to that formed by the individual LPs, this prevents their separation according to size. An effective rejection in the first ultrafiltration step was achieved by membranes with MCWO= 10–100 kDa but poor rejection by the 300 KDa membrane [46]. The rejection is a measure of retention capacity of a membrane. However, some properties of LP micelles such as poor stability and non-uniform size distribution limit the use of readily scalable high MWCO membranes for the purification of LP, as smaller sized micelles and monomers can easily pass through the pores of these membranes. An addition of Ca2+ ions causes the structural transformation of surfactin monomers to larger micellar aggregates, showing excellent features such as compact structure, narrow size distribution, and improved stability [45].

**Chromatographic technique for daptomycin.** Daptomycin was purified from clarified fermentation broth using anion exchange chromatography and reverse phase chromatography. The anion resin was a highly cross-linked agarose with dextran surface extender. Daptomycin was eluted from the anion exchange column with a NaCl gradient from 0.2 to 1.0 M in water. The semi-purified daptomycin was then added to a reversed phase column and was washed with water containing 15% of alcohol. The reverse phase resin was a mono-sized, porous resin made of polystyrene and divinyl benzene (source: RPC 30). After, daptomycin was eluted with 40–70% of ethanol. Two reverse phase columns were involved to improve the purity of the final product at different pH. The first column was run at pH 7.5–8.0, while the second one was eluted at pH 3.0–3.1. The purified daptomycin is then filtered and lyophilized under standard conditions with at least 95% of purity [47].

**Resins.** Macroporous adsorption resin (MAR) chromatography has been successfully used for separation of bioactive molecules on the basis of hydrophobic/hydrophilic interactions between solute and resin surface. MAR has been resolved problems related with low efficiency to separate LP mixtures into individual families employing a simple stepwise solvent gradient elution under optimal conditions. The adsorption and desorption of solutes on MARs depend upon the properties of the resins such as particle size, pore diameter, surface area and polarity. An example is the performance of a non-polar resin (HP-20) that combine features such as higher surface area, pore size and appropriate polarity, allowing it to have a superior adsorption capacity over other resins. Dual gradient MAR was applied to a cell free broth diluted until its total crude LP concentration was 3 g/L, then it was pumped at a flow rate of 1 ml/min into the column pre-packed with HP-20 resin (15 g) until breakthrough point. After one run of adsorption and desorption, the three LP families were successfully enriched in separate fractions and the recovery yields were 79.5% for iturin, 94.4% for fengycin and 89.4% for surfactin. Their purities in the enriched fractions were found to be 68.3, 77.6 and 91.6%, respectively. This process represents a basis for *in situ* recovery of LPs from the culture broth in continuous mode [48].

#### *2.5.2. HLPC-MALDI-TOF*

with dialysis to remove small molecules and salts, and foam fractionation (utilized for continuous retention process and high purity). For purification normally have been used membrane ultrafiltration techniques, ionic exchange chromatography and adsorptiondesorption on resins (XAD-4, XAD-7 HP, HP-2MG, HP-20) or activated carbon. The High Performance Liquid Chromatography(HPLC) (an excellent method for separation of this class of molecules) uses a reverse phase with C18 columns. The LPs separated can be detected using ultraviolet absorbance or diode arrays detectors and each peak separated is collected using a

**Membrane ultrafiltration.** This technique serves essentially as an intermediate process for the recovery and purification of LPs. The separation of LPs by membrane filtration depends on their molecular aggregation behavior and on their ability to form micelles, since a process become economic feasible when a high MWCO (molecular weight cut-off) membranes were used. In general, the use of low MWCO membranes requires high maintenance due to low permeate fluxes through smaller pores that get easily plugged by monomers and progressive

A two-step ultrafiltration process using large pore size membranes (up to MWCO = 300 kDa) was investigated to separation of LPs aggregated in single and mixed solutions from fermentation culture. In single solutions of LP both surfactin and mycosubtilin formed micelles of different size depending on their concentration. However when the LPs were in the same solution, they formed mixed micelles of different size and probably conformation to that formed by the individual LPs, this prevents their separation according to size. An effective rejection in the first ultrafiltration step was achieved by membranes with MCWO= 10–100 kDa but poor rejection by the 300 KDa membrane [46]. The rejection is a measure of retention capacity of a membrane. However, some properties of LP micelles such as poor stability and non-uniform size distribution limit the use of readily scalable high MWCO membranes for the purification of LP, as smaller sized micelles and monomers can easily pass through the pores of these membranes. An addition of Ca2+ ions causes the structural transformation of surfactin monomers to larger micellar aggregates, showing excellent features such as compact structure,

**Chromatographic technique for daptomycin.** Daptomycin was purified from clarified fermentation broth using anion exchange chromatography and reverse phase chromatography. The anion resin was a highly cross-linked agarose with dextran surface extender. Daptomycin was eluted from the anion exchange column with a NaCl gradient from 0.2 to 1.0 M in water. The semi-purified daptomycin was then added to a reversed phase column and was washed with water containing 15% of alcohol. The reverse phase resin was a mono-sized, porous resin made of polystyrene and divinyl benzene (source: RPC 30). After, daptomycin was eluted with 40–70% of ethanol. Two reverse phase columns were involved to improve the purity of the final product at different pH. The first column was run at pH 7.5–8.0, while the second one was eluted at pH 3.0–3.1. The purified daptomycin is then filtered and lyophilized

*2.5.1. Example of techniques used for lipopeptide recovery, purification and identification*

reduction in flux caused by the mechanism of concentration polarization [45].

fraction collector for further analysis of their structure.

210 Fermentation Processes

narrow size distribution, and improved stability [45].

under standard conditions with at least 95% of purity [47].

HPLC is an excellent method for the separation of individual LP separation. The most employed technique is reverse phase chromatography, due to this method can separate this metabolite based on its polarity. The separated products are detected by UV absorbance detection and each individual peak can be collected for further analysis of their structure. Also, use of a diode array detector is recommended. This detector can measure simultaneous wavelengths in a range of 200–600 nm, this means that we can detect LPs as they are eluted from the column in several wavelengths. For mobile phases reported, the methanol:water (80:20) is the most commonly employed, due this phase can elute several LPs as fengicins and iturins. Also, another mobile phase used is acetonitrile:water, as the methanol:water phase, this mobile phase can elute LPs as surfactins. The proportions for a acetonitrile:water can change depending on the LP that you want to separate. The typical column for LP's separation is a C-18 column, the length can vary from 150 to 250 mm, and this depends on the resolution and separation desired. In terms of particle size, 5 μm is the most adequate for the stationary phase. **Table 3A** shows some conditions of HPLC most widely used for separation as well as quantification of LPs derived from a fermentative process [49,50].

MALDI-TOF (matrix-assisted laser desorption/ionization-time of flight) is a mass spectrometry technique that allows the identification of intact compounds. Samples to be analyzed are mixed with a matrix and dried on a stainless steel plate, onto which a laser with various degrees of energy is fired to forming gaseous ions, which can be separated in a time of flight (TOF) analyzer and detected. Now, MALDI-TOF-MS has come to be regarded as a very fast and reliable tool for identification of LPs when compared to the conventional methods like culturing and purifying the LPs. The MALDI-TOF-MS for the identification of LPs has been previously reported [51, 52]. For LP identification, we can use CHCA (α-cyano-4-hydroxycinnamic acid), SA (sinapic acid) and DHB (2,5-dihydroxybenzoic acid). To the best of our knowledge, DHB matrix is better than CHCA, because we obtain a good quality spectra with intensities above 2E4 and LP isomers can be observed. In **Table 3B** are shown relevant information of the mass range for specific LPs identification derived from MALDI-TOF analysis.


Production of Lipopeptides by Fermentation Processes: Endophytic Bacteria, Fermentation Strategies and Easy... http://dx.doi.org/10.5772/64236 213


knowledge, DHB matrix is better than CHCA, because we obtain a good quality spectra with intensities above 2E4 and LP isomers can be observed. In **Table 3B** are shown relevant information of the mass range for specific LPs identification derived from MALDI-TOF

> 250mm length, size particle 5μm

3-10 min iturin 10-16 min fengycin 16-25 min surfactin 28.5 min amphisin 29 min lokisin 29.2 min hodersin 29.9 min tensin 31.6 min vicosinamide

278, 285nm), diode

**LIPOPEPTIDE**

BACILLOMYCIN

FENGYCIN

ITURIN A

array.

(80:20), Acetonitile:water (80:20 and 40:60), acetonitrile: acetic acid (68:32)

*SEPARATED*

ITURIN, FENGYCIN SURFACTIN AMPHISIN LOKISIN HODERSIN, TENSIN VICOSINAMIDE DAPTOMYCIN VISCONSIN MASSETOLIDE ENTOLYSIN

*TECHNIQUE CONDITIONS LIPOPEPTIDE*

MOBILE PHASE Methanol: water

DETECTORS UV-VIS (205, 235,

**PEAKS (***m/z***) IDENTIFICATED**

**(A) HPLC** COLUMN C-18, 150mm–

RETENTION TIMES

**1001.42**, 1029.42; 1016.56, 1030.58, 1044.59, 1058.61, 1072.62; 1030.64, 1044.65, **1058.66**, 1072.67

**1052.63**,1094.45, 1122.47, 1136.55; **1052.64**, 1066.57; **1052.62**, 1066.60, 1080.59

1435.58, 1449.63, **1463.68** , 1477.66; 1421.61, 1435.66, 1459.69, **1463.71**, 1477.72; 1421.75, 1435.76, 1449.77, **1463.79**, 1477.60,

analysis.

212 Fermentation Processes

**(B) MASS SPECTROMETRY** **Table 3.** HPLC strategies and conditions (A) used for lipopeptides separation from extracts of culture filtrate and (B) ranges of m/z of typical peaks obtained by MALDI-TOF analysis. In bold, the reference peaks for lipopeptide identification.

#### **2.6. Discovery of endophyte-producers of lipopeptides: combining molecular biology and chromatographic- mass spectrometry methods**

To search for endophytic bacteria in nature that can produce LPs, researchers must optimize their screening and identification times. Actually, the strategies for the selection of endophytic microorganisms as candidates for biocontrol or lipopeptide-producers combines antifungalantibacterial screenings, a molecular analysis of the genes involved in the LP synthesis and then an analysis of the extracts obtained from the culture medium by HPLC and mass spectrometry.

In practice, after endophyte isolation, we identify the purified strain by MALDI-TOF and confirm its identity by 16s rDNA sequencing. Once identified, we select the strain as a function of its antagonistic ability against plant pathogenic strains. For screening antifungal activity of the isolates, we use a dual culture test against fungal strains collected from plants and previously identified. Normally, the plates are incubated for 3–5 days to observe inhibition of the fungal mycelium (**Figure 2**). For screening the presence of LP product biosynthetic gene clusters present in the antifungal isolate, PCR-based screening methods are used for different genes involved. In **Table 4**, we show the summarized sequences and methods for PCR analysis most used for some lipopeptide-genes, then each amplification product is analyzed by agarose gel electrophoresis to compare the predicted base-pair number (**Figure 3**). The sequence data obtained must be analyzed by BLAST and detailed *in silico* phylogenetic analysis to confirm the PCR product.

**Figure 2.** Antagonism of endophytic *Bacillus subtilis (Bs), B. amyloliquefaciens (Ba) and B. tequilensis (Bt), Kocuria marina (Km)* and *Lysinibacillus fusiformis (Lf)* isolated from agave, banana and maize against *Rhizotocnia* sp. and Colletotrichum sp. incubated by 5 days. It is noted that *Bacillus* strains used are the only ones that have antifungal activity, so the other strains should be discarded for identification analysis.


+PCR: PCR PRODUCT SIZE EXPECTED (bp).

**Table 4.** PCR primers commonly used for amplification of lipopeptide genes.

The crude extracts obtained from culture media must be subject to HPLC separation and their collection for mass identification. The chromatographic profile of acidic methanol extracts and MALDI-TOF spectra of LPs from endophytic *Bacillus amyloliquefaciens* and *B. tequilensis shown* the presence of LPs groups iturins, fengycins and surfactin (**Figure 3**). Mass ranges (*m/z*) are 1001.42–1072 for iturin, 1471–75–1513.79, 1488.70–1516.62 for K and Na adducts of fengycin respectively and 1000–1100 for surfactin.

obtained must be analyzed by BLAST and detailed *in silico* phylogenetic analysis to confirm

**Figure 2.** Antagonism of endophytic *Bacillus subtilis (Bs), B. amyloliquefaciens (Ba) and B. tequilensis (Bt), Kocuria marina (Km)* and *Lysinibacillus fusiformis (Lf)* isolated from agave, banana and maize against *Rhizotocnia* sp. and Colletotrichum sp. incubated by 5 days. It is noted that *Bacillus* strains used are the only ones that have antifungal activity, so the other

**LIPOPEPTIDES GENES PRIMERS PRIMERS SECUENCES (5′–3′) AT\* PCR++**

55 55 55

55 52 43 482 594 647

626 675 428

58 1029

TTGAAYGTCAGYGCSCCTTT TGCGMAAATAATGGSGTCGT CCCCCTCGGTCAAGTGAATA TTGGTTAAGCCCTGATGCTC GATGCGATCTCCTTGGATGT ATCGTCATGTGCTGCTTGAG

AGAGCACATTGAGCGTTACAAA CAGCATCTCGTTCAACTTTCAC ATGAAGATTTACGGAATTTA TTATAAAAGCTCTTCGTACG CGCGGMTACCGVATYGAGC ATBCCTTTBTWDGAATGTCCGCC

AGMCAGCKSGCMASATCMCC GCKATWWTGAARRCCGGCGG

CAKCARGTSAAAATYCGMG CCDASATCAAARAADTTATC 45 419

GAATAYMTCGGMCGTMTKGA GCTTTWADKGAATSBCCGCC 45 452

the PCR product.

214 Fermentation Processes

Iturin ituD

Surfactin srfA

ituC ituA

srfP srf/Ich

Mycosubtilin Myc/itu Am1-F

Fengycin fen Af2-F

Piplastin pps Ap1-F

\*AT: ANNEALING TEMPERATURE (°C). +PCR: PCR PRODUCT SIZE EXPECTED (bp).

strains should be discarded for identification analysis.

ITUD-F1 ITUD-R1 ITUC-F1 ITUC-R1 ITUD1F ITUD1R

SRFA-F1 SRFA-R1 SFP-F1 SFP-R1 As1-F Ts2-R

Tm1-R

Tf1-R

Tp1-R

**Table 4.** PCR primers commonly used for amplification of lipopeptide genes.

**Figure 3.** Agarose gel electrophoresis of PCR products of Bacillus endophytes (Below left) and separation and identification of the antifungal lipopeptides from acidic methanol extract by using reversed-phase HPLC(Above left) and MALDI-TOF MS analysis (Right) Section 2: PCR detection of lipopeptide and biosynthesis genes from Bacillus amyloliquefaciens (A), B. tequilensis (B), B. subtilis (C). M DNA ladder, Lane 1 Subtilosin, Lane 2 Sublancin, Lane 3 Plipastatin, Lane 4 Iturin D, Lane 5 Iturin C, Lane 6 Iturin A, lane 7 Surfactin A, Lane 8 Surfactin F, Lane 9 Mycosubtilin, Lane 10 Fengycin, lane 11 Subtilin A Lane 12 Ericin and Lane 13 Surfactin P. Chromatogram profile and MALDI-TOF mass spectrum of B. *amyloliquefaciens* (A) and B. *tequilensis* (B). The chromatograms were obtained under the following conditions: 0-3min: 45%-50% acetonitrile; 3-8min: 50%-80% acetonitrile; 8-25min: 80-100% acetonitrile, temperature of 38°C and a C-18 column (5μm particle size, 250 mm). Mass spectra were obtained with a RP 700-3500 Da, DHB as matrix. In section 1 (**A1** and **B1**), we can observe the mass spectrum of the HPLC fraction collected (within 4 min for A1 and 5 min for **B1**) that represent iturin (Section 3: with mass of 1016.68m/z and surfactin (1065.06 m/z) indicated that both strains produce this lipopeptides. In **A2** and **B2** we observe fengycin, in both cases the mass spectrum contains the representative mass of fengycin (1477 m/z) in section 3.

#### **2.7. Quorum sensing in fermentative processes and lipopeptide production**

Quorum sensing (QS) is a form of cell-cell communication by which bacteria communicate by secreting signaling molecules called autoinducers that help regulate gene expression. The QS molecule as N-acylhomoserine lactones in Gram-negatives or AIP in Gram-positives regulates different bacterial functions such as antibiotic biosynthesis, production of virulence factor, bacterial swarming, sporulation, competence and transition to the stationary growth phase.

How are LP production and quorum sensing associated? Surfactin a LP widely mentioned in this chapter book was proposed as a quorum-sensing molecule that activates the process of sporulation and production of biofilm [53]. For regulation of surfactin production by a cell density-responsive mechanism *B. subtilis* utilized a peptide pheromone Com X. Com X accumulates in the growth medium. So, the QS control the *srf* operon expression via Com X. However, few studies have been reported relating QS with fermentative processes. The production of putisolvins, also cyclic lipopeptides, in *Pseudomonas putida* occur at the end of the exponential growth phase, which indicates that the production of putisolvins is mediated through a quorum sensing-mechanism [54,55]. Another example that links QS with LP production is rhamnolipid a glycolipid biosurfactant produced also by *Pseudomonas spp*. The *rhl* quorum sensing system in *P. aeruginosa* regulates the production of rhamnolipid type biosurfactants. RhlA, a rhamnosyltransferase, catalyses the synthesis of fatty acid dimers that subsequently serve as the precursor for RhlB to form monorhamnolipids and dirhamnolipids catalyzed by RhlC. The genes (*rhlA*, *rhlB* and *rhlC*) for these catalyses are under the control of QS. Other studies link rhamnolipids synthesis to nutritional conditions, such as nitrogen exhaustion and the alternative sigma factor σ54 for nitrogen limitation. Schmidberger et al. [56], reports an interesting study of *P. aeruginosa* and rhamnolipid synthesis. Using PCRq, gene expression was monitored over entire course of fermentation. They observed until late deceleration phase (or ending log phase), an increase in relative gene expression of the *las*, *rhl* and *pqs* quorum-sensing regulon under nitrogen limitation.

Fermentation processes in terms of batch fermentation constituted a molecular black box in regards to transcriptional activity of the genes of LP synthesis circuitry in both Gram-positive and Gram-negative bacteria. More studies of the molecular biology during fermentation of LPs are needed. Monitoring gene expression of LPs over the entire time course of the fermentation process provides information about regulatory events linked or not to QS. QS is a variable that has largely been ignored in fermentative process studies. It is likely that information on QS in fermentation will help optimize bioreactor conditions, nutrient limitations or perhaps the use of signal molecules of QS to improve production yields of LPs and other microbial products.

#### **3. Conclusions**

The examples discussed so briefly in this chapter are by no means exhaustive. Hopefully they serve to illustrate the potential use of bacterial LPs and highlight potential applications in fields of biomedicine and agriculture. We also emphasize the potential of endophytic bacteria as lipopeptide-producers, opening research opportunities to understand some of the mechanisms involved in the biological control that occurs in niches they inhabit as endophytes. Knowledge of this and other topics, will promote the implementation of new molecules that are harmless to humans when we cannot directly apply bacteria in agricultural fields. It is clear that for widespread use of microbial LPs, more research is required focused on production with higher yields and at lower cost, where solid-state fermentation emerges as an important area of study in fermentation processes. This field is very much in its early stages, and progress will come from a combination of ecological, physiological, structural, genetic and fermentative process approaches.

### **Acknowledgements**

How are LP production and quorum sensing associated? Surfactin a LP widely mentioned in this chapter book was proposed as a quorum-sensing molecule that activates the process of sporulation and production of biofilm [53]. For regulation of surfactin production by a cell density-responsive mechanism *B. subtilis* utilized a peptide pheromone Com X. Com X accumulates in the growth medium. So, the QS control the *srf* operon expression via Com X. However, few studies have been reported relating QS with fermentative processes. The production of putisolvins, also cyclic lipopeptides, in *Pseudomonas putida* occur at the end of the exponential growth phase, which indicates that the production of putisolvins is mediated through a quorum sensing-mechanism [54,55]. Another example that links QS with LP production is rhamnolipid a glycolipid biosurfactant produced also by *Pseudomonas spp*. The *rhl* quorum sensing system in *P. aeruginosa* regulates the production of rhamnolipid type biosurfactants. RhlA, a rhamnosyltransferase, catalyses the synthesis of fatty acid dimers that subsequently serve as the precursor for RhlB to form monorhamnolipids and dirhamnolipids catalyzed by RhlC. The genes (*rhlA*, *rhlB* and *rhlC*) for these catalyses are under the control of QS. Other studies link rhamnolipids synthesis to nutritional conditions, such as nitrogen exhaustion and the alternative sigma factor σ54 for nitrogen limitation. Schmidberger et al. [56], reports an interesting study of *P. aeruginosa* and rhamnolipid synthesis. Using PCRq, gene expression was monitored over entire course of fermentation. They observed until late deceleration phase (or ending log phase), an increase in relative gene expression of the *las*, *rhl*

Fermentation processes in terms of batch fermentation constituted a molecular black box in regards to transcriptional activity of the genes of LP synthesis circuitry in both Gram-positive and Gram-negative bacteria. More studies of the molecular biology during fermentation of LPs are needed. Monitoring gene expression of LPs over the entire time course of the fermentation process provides information about regulatory events linked or not to QS. QS is a variable that has largely been ignored in fermentative process studies. It is likely that information on QS in fermentation will help optimize bioreactor conditions, nutrient limitations or perhaps the use of signal molecules of QS to improve production yields of LPs and other

The examples discussed so briefly in this chapter are by no means exhaustive. Hopefully they serve to illustrate the potential use of bacterial LPs and highlight potential applications in fields of biomedicine and agriculture. We also emphasize the potential of endophytic bacteria as lipopeptide-producers, opening research opportunities to understand some of the mechanisms involved in the biological control that occurs in niches they inhabit as endophytes. Knowledge of this and other topics, will promote the implementation of new molecules that are harmless to humans when we cannot directly apply bacteria in agricultural fields. It is clear that for widespread use of microbial LPs, more research is required focused on production with higher yields and at lower cost, where solid-state fermentation emerges as an important area of study in fermentation processes. This field is very much in its early stages, and progress

and *pqs* quorum-sensing regulon under nitrogen limitation.

microbial products.

216 Fermentation Processes

**3. Conclusions**

TThe authors gratefully acknowledge the financial support from CONACYT: Proyectos de Desarrollo Cientifico para atender Problemas Nacionales (CONACYT 212875) and Project 207400 of Bilateral Cooperation Mexico-Brazil funded by CONACYT and CNPq (Brazil, No. 490440/2013-4). FAPESP (Fundação de Amparo à Pesquisa do Estado de São Paulo; No. 2012/12663-1; CEPID Redoxoma (FAPESP; No. 2013/07937-8)), Universidade de São Paulo NAP Redoxoma (PRPUSP; No. 2011.1.9352.1.8) .G M-R, thanks CONACYT for PhD fellowship #256660. EB-G, AM-R and YY C-C thanks to Universidad Autonoma de Guadalajara for their scholarships. Finally we thanks to Professor James F. White Jr. from RUTGERS University for providing valuable suggestions and English revision of manuscript.

To the memory of Professor Tetsuya Ogura who passed away recently, whose works and gentle encouragement have had the most profound influence on my scientific career.

#### **Author details**

Esteban Beltran-Gracia1 , Gloria Macedo-Raygoza2 , Juan Villafaña-Rojas3 , America Martinez-Rodriguez4 , Yur Yenova Chavez-Castrillon3 , Froylan M. Espinosa-Escalante1 , Paolo Di Mascio5 , Tetsuya Ogura1 and Miguel J. Beltran-Garcia1\*

\*Address all correspondence to: jbeltran@edu.uag.mx

1 Department of Chemistry, Autonomous University of Guadalajara, Zapopan, Jalisco, México

2 Engineering Institute, The Autonomous University of Baja California, Mexicali, México

3 Chemistry Faculty, Autonomous University of Guadalajara, Zapopan, Jalisco, México

4 Biology School, Autonomous University of Guadalajara, Zapopan, Jalisco, México

5 Department of Biochemistry, Chemistry Institute, University of São Paulo, Sao Paulo, Brazil

#### **References**

[1] Ongena M, Jacques P. *Bacillus* lipopeptides: versatile weapons for plant disease biocontrol. Trends Microbiol. 2007;16(3):115–125. DOI: 10.1016/j.tim.2007.12.009.


[13] Zhang, T, Muraih JK, MacCormick B, Silverman J, Palmer M. Daptomycin forms catiónand size-selective pores in model membranes. Biochim Biophys Acta. 2014;1838(10): 2425–2430. DOI: 10.1016/j.bbamem.2014.05.014

[2] Van Der Voort M, Meijer HJ, Schmidt Y, Watrous J, Dekkers E, Mendes R, Dorrestein PC, Gross H, Raaijmakers JM. Genome mining and metabolic profiling of the rhizosphere bacterium *Pseudomonas* sp. SH-C52 for antimicrobial compounds. Front

[3] Singh LS, Sharma H, Talukdar NC. Production of potent antimicrobial agent by actinomycete *Streptomyces sannaensis* strain SU118 isolate from phoomdi in Loktak Lake of Manipur, India. BMC Microbiol. 2014;14:278. DOI: 10.1186/

[4] Li L, Ma T, Liu Q, Huang Y, Hu C, Liao G. Improvement of daptomycin production in *Streptomyces roseosporus* through the acquisition of pleuromutilin resistance. BioMed

[5] Meca G, Sospedra I, Valero MA, Mañes J, Font G, Ruiz MJ. Antibacterial activity of the enniatin B, produced by *Fusarium tricictum* in liquid culture, and cytotoxic

[6] Li Yi-M, Haddad NIA, Yang S-Z, Mu B-Z. Variants of lipopeptides produced by *Bacillus licheniformis* HSN221 in different medium components evaluated by a rapid method ESI-MS. Int J Pept Res Ther. 2008;14(3):229–235. DOI: 10.1007/

[7] Wei Y-H, Chu I-M. Mn2+ improves surfactin production by *Bacillus subtilis*. Biotechnol

[8] Abdel-Mawgoud AM, Aboulwafa MM, Abdel-Haleem HN. Optimization of surfactin production by *Bacillus subtilis* isolate BS5. Appl Biochem Biotechnol. 2008;150(3):305–

[9] Plaza G, Chojniak J, Rudnicka K, Paraszkiewicz, BP. Detection of biosurfactants in *Bacillus* species: genes and products identification. J Appl Microbiol. 2015;119(4):1023–

[10] Roonsawang N, Washio K, Morikawa M. Diversity of nonribosomal peptide synthetases involved in the biosynthesis of lipopeptide biosurfactants. Int J Mol Sci. 2010;12(1):

[11] Duitman EH, Hamoen LW, Rembold M, Venema G, Seitz H, Saenger W, Bernhard F, Reinhardt R, Schmidt M, Ullrich C, Stein T, Leenders F, Vater J. The mycosubtilin synthetase of *Bacillus subtilis* ATCC6633: a multifunctional hybrid between a peptide synthetase, an amino transferase, and a fatty acid synthase. Proc Natl Acad Sci U S A.

[12] Bayer AS, Schneider T, Sahl, HS. Mechanisms of daptomycin resistance in *Staphylococcus aureus*: role of the cell membrane and cell wall. Ann N Y Acad Sci. 2013;1277:139–

effects on Caco-2 cells. Toxicol Mech Methods. 2011;21(7):503-512. DOI:

Microbiol. 2015;6:693. DOI: 10.3389/fmicb.2015.00693.

Res Int. 2013;2013:479742. DOI: 10.1155/2013/479742

Lett. 2002;24(6):479–482. DOI: 10.1023/A:1014534021276

1999;96(23):13294–13299. DOI: 10.1073/pnas.96.23.13294.

s12866-014-0278-3

218 Fermentation Processes

s10989-008-9137-0.

10.3109/15376516.2011.556202

325. DOI: 10.1007/s12010-008-8155-x.

141–172. DOI: 10.3390/ijms12010141.

158. DOI.10.1111/j.1749-6632.2012.06819.x.

1034. DOI: 10.1111/jam.12893.


*monas fluorescens* SBW25 aids spreading motility and plant growth promotion. Environ Microbiol. 2014;16(7):2267–2281. DOI: 10.1111/1462-2920.12469.


[36] Chen W-C, Juang R-S, Wei Y-H. Applications of a lipopeptide biosurfactant, surfactin, produced by microorganisms. Biochem Eng J. 2015;103:158–169. DOI: 10.1016/j.bej. 2015.07.009.

*monas fluorescens* SBW25 aids spreading motility and plant growth promotion. Environ

[25] Gond SK, Bergen MS, Torres MS, White JF. Endophytic *Bacillus* spp. produce antifungal lipopeptides and induce host defence gene expression in maize. Microbiol Res.

[26] Mnif I, Chaabouni-Ellouze S, Ghribi D. (2012) Optimization of the nutritional parameters for enhanced production of *B. subtilis* SPB1 biosurfactant in submerged culture using response surface methodology. Biotechnol Res Int. 2012;2012:795430. DOI:

[27] Liu X, Ren B, Gao H, Liu M, Dai H, Song F, Yu Z, Wang S, Hu J, Kokare CR, Zhang L. Optimization for the production of surfactin with a new synergistic antifungal activity.

[28] Gu X-B, Zheng Z-M, Yu H-Q, Wang J, Liang F-L, Liu R-L. Optimization of medium constituents for a novel lipopeptide production by *Bacillus subtilis* MO-01 by a response surface method. Process Biochem. 2005;40:3196–3201. DOI: 10.1016/j.procbio.

[29] Singh AK, Rautela R, Cameotra SS. Substrate dependent *in vitro* antifungal activity of *Bacillus* sp strain AR2. Microb Cell Fact. 2014;13:67. DOI: 10.1186/1475-2859-13-67. [30] Zhao P, Quan C, Jin L, Wang L, Wang J, Fan S. Effects of critical medium components on the production of antifungal lipopeptides from *Bacillus amyloliquefaciens* Q-426 exhibiting excellent biosurfactant properties. World J Microbiol Biotechnol.

[31] Al-Ajlani MM, Sheikh MA, Ahmad Z, Hasnain S. Production of surfactin from *Bacillus subtilis* MZ-7 grown on pharmamedia commercial medium. Microb Cell Fact. 2007;6:17.

[32] Jin H, Zhang X, Li K, Niu Y, Guo M, Hu C, Wan X, Gong Y, Huang F. Direct bioutilization of untreated rapeseed meal for effective iturin A production by *Bacillus subtilis* in submerged fermentation. PLoS One. 2014;9(10):e111171. DOI: 10.1371/

[33] Wei Y-H, Lai C-C, Chang J-S. Using Taguchi experimental design methods to optimize trace element composition for enhanced surfactin production by *Bacillus subtilis* ATCC

[34] Wei Y-H, Wang L-F, Chang J-S. Optimizing iron supplement strategies for enhanced surfactin production with *Bacillus subtilis*. Biotechnol Progr. 2004;20:979–983. DOI:

[35] Lin H-Y, Rao YK, Wu W-S, Tzeng Y-M. Ferrous ion enhanced lipopeptide antibiotic iturin A production from *Bacillus amyloliquefaciens* B128. Int J Appl Sci Eng. 2007;5(2):

21332. Process Biochem. 2007;42:40–45. DOI: 10.1016/j.procbio.2006.07.025.

Microbiol. 2014;16(7):2267–2281. DOI: 10.1111/1462-2920.12469.

PLoS One. 2012;7(5):e34430. DOI: 10.1371/journal.pone.0034430.

2015;172:79–87 DOI: 10.1016/j.micres.2014.11.004

2013;29:401–409. DOI: 10.1007/s11274-012-1180-5.

DOI: 10.1186/1475-2859-6-17.

journal.pone.0111171.

10.1021/bp030051a.

123–132.

10.1155/2012/795430.

220 Fermentation Processes

2005.02.011.


#### **Lactic Acid Bacteria and Fermentation of Cereals and Pseudocereals Lactic Acid Bacteria and Fermentation of Cereals and Pseudocereals**

Denisa Liptáková, Zuzana Matejčeková and Ľubomír Valík Denisa Liptáková, Zuzana Matejčeková and Ľubomír Valík

Additional information is available at the end of the chapter Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/65459

#### **Abstract**

[48] Dhanarajan G, Rangarajan V, Sen R. Dual gradient macroporous resin column chromatography for concurrent separation and purification of three families of marine bacterial lipopeptides from cell free broth. Sep Pur Technol. 2015;143:72–79. DOI:

[49] Yang H, Li X, Li X, Yu H, Shen Z. Identification of lipopeptide isoforms by MALDI-TOF-MS/MS based on the simultaneous purification of iturin, fengycin, and surfactin by RP-HPLC. Anal Bioanal Chem. 2015;407:2529–2542. DOI: 10.1007/

[50] Torres MJ, Brandan CP, Petroselli G, Erra-Balsells R, Audisio MC. Antagonistic effects of *Bacillus subtilis* subsp. *subtilis* and *B. amyloliquefaciens* against *Macrophomina phaseolina*: SEM study of fungal changes and UV-MALDI-TOF MS analysis of their bioactive

compounds. Microbiol Res. 2016;182:31–39. DOI: 10.1016/j.micres.2015.09.005.

J Chromatogr A. 2016;1438:76–83. DOI: 10.1016/j.chroma.2016.02.013.

MS and RT-PCR. Curr Microbiol. 2016. DOI: 10.1007/s00284-016-1025-9.

[51] Urajová P, Hájek J, Wahlsten M, Jokela J, Galica T, Fewer D, Kust A, Zapomelová-Kozlíková E, Delawská K, Sivonen K, Kopecký J, Hrouzek PA. Liquid chromatographymass spectrometric method for the detection of cyclic β-amino fatty acid lipopeptides.

[52] Sajitha KL, Dev SA, Florence EJM. Identification and characterization of lipopeptides from *Bacillus subtilis* B1 against Sapstain fungus of rubberwood through MALDI-TOF-

[53] Lopez D, Vlamankish H, Losick R, Kolter R. Cannibalism enhances biofilm development in Bacillus subtilis. Mol Microbiol. 2009;74:609–618. DOI: 10.1111/j.

[54] Dubern JF, Lugtenberg BJJ, Bloemberg GV. The ppuI-rsaL-ppuR Quorum sensing system regulates biofilm formation of *Pseudomonas putida* PCL1445 by controlling biosynthesis of the cyclic lipopetides putisolvin I and II. J Bacteriol. 2006;188:2898–2906.

[55] Das P, Mukherjee S, Sen R. Genetic regulations of the biosynthesis of microbial surfactants: an overview. Biotech Genet Eng Rev. 2008;25:165–186 DOI: 10.5661/

[56] Schmidberger A, Henkel M, Hausmann R, Schwartz T. Expression of genes involved in rhamnolipid synthesis in *Pseudomonas aeruginosa* PAO1 in a bioreactor cultivation. Appl

Microbiol Biotechnol. 2013;97:5779–5791. DOI: 10.1007/s00253-013-4891-0

10.1016/j.seppur.2015.01.025.

s00216-015-8486-8.

222 Fermentation Processes

1365-2958.2009.06882.x.

bger-25-165.

DOI: 10.1128/JB.188.8.2898-2906.2006.

The usage of lactic acid bacteria (LAB) in food as starters in fermentation technologies has a long tradition. Although the theorized idea of host‐friendly bacteria found in yoghurt has been formulated only over a century ago, both groups are widely used nowadays. Lactic acid bacteria alone or with special adjunct probiotic strains are inevitable for the preparation of various specific fermented and probiotic foods. Moreover, because of their growth and metabolism, the final products are preserved for a certain time. Growth dynamics of probiotic LAB and Fresco DVS 1010 in milk‐ and water‐based maize mashes with sucrose or flavours (chocolate, caramel and vanilla) were evaluated in this study. Although milk is typical growth medium for the LAB growth, observed strains showed sufficient growth in each of prepared mashes as well as they were able to maintain their content above 106 CFU ml‐1 during storage period (6°C/21 d). Designed flavoured mashes were acceptable from the microbiological point of view, but according to the sensory evaluation they were provided with an attractive overall acceptability and are adequate alternative for celiac patients, people suffering from milk protein allergies or lactose intolerance.

**Keywords:** lactic acid bacteria, fermentation, biopreservation, probiotics, functional products

#### **1. Introduction**

For centuries, human civilization had used different approaches to preserve different types of food products. If we look back in history, we can find the preparation of different types of foods, for example, alcoholic beverages by ancient Egyptians, the preparation of yoghurt and kefir by

© 2017 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2017 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

the nomadic people from central Asia, fermentation of meat by the Germanic tribes and fish by the Eskimos, preparation of boza by the ancient Persians or fermenting maize by the native tribes in pre‐Columbian America [1]. The earliest records about fermentation process were dated back to 6000 BC, and thus fermentation represents one of the oldest food preservation methods [2, 3]. The ancient people probably did not have any knowledge of microbiology, but in the middle of the nineteenth century, Louis Pasteur significantly contributed to the understanding of the fermentation process itself. He established the role of microorganisms and proved that there are many different kinds of fermentation [3]. The original and primary purpose of fermentation was a preservation effect. Subsequently, with the development of many available preservation technologies, plenty of fermented foods were therefore manufactured because of their unique flavours, aromas and textures much appreciated to a consumer [4, 5]. Fermentation process created plenty of traditional food products, such as milk products (cheese, butter and yoghurt), fermented meat, plants and fruits (sausages, silage, sauerkraut, olives and grapes) and finally fermented cereal products such as bread and beer [6]. Fermented food and beverages are defined as those that have been subjected to the effect of microbial enzymes, particularly amylases, proteases and lipases that cause biochemical transformation of polysaccharides, proteins and lipids to non‐toxic variety of desirable products with tastes, aromas and textures attractive to a consumer [4, 7].

In food fermentations, conditions of treatment and storage create an environment in which certain types of organism can flourish and these have a benign effect on the food rather than spoiling it. The majority of fermented foods is produced by the activity of lactic acid bacteria (LAB) and fungi, principally yeasts but also, to a lesser extent, moulds. Both groups of organisms share a common ecological niche, are able to grow under conditions of low pH and reduced water activity, although only lactic acid bacteria and facultative yeasts will prosper under anaerobic conditions. They frequently occur together in fermented products, dairy and non‐dairy, but in some cases, they play the role of a spoilage agent [8].

Microorganisms responsible for the fermentation process may be presented naturally in the substrate, or may be added as a starter and adjunct cultures [9].

#### **2. Lactic acid bacteria**

Lactic acid bacteria (LAB) represent an ubiquitous and heterogeneous species with common feature of lactic acid production as a result of sugar metabolism which leads to an acidification of the environment down to a pH of 3.5 [10]. The monograph by Orla‐Jensen (1919) formed the basis of the present classification of LAB that take into account the cellular morphology, mode of glucose fermentation, growth temperature and sugar utilization possibilities [11]. Taxonomically, LAB are divided into two distinct phyla: *Firmicutes* and *Actinobacteria*. Within the *Firmicutes* phylum genera such as *Lactobacillus*, *Lactococcus*, *Leuconostoc*, *Oenococcus*, *Pediococcus*, *Streptococcus*, *Enterococcus*, *Tetragenococcus*, *Aerococcus*, *Carnobacterium*, *Weissella*, *Alloiococcus*, *Symbiobacterium* and *Vagococcus* belong. Within the *Actinobacteria* phylum, lactic acid bacteria belong to the *Atopobium* and *Bifidobacterium* genera [12].

Lactic acid bacteria are Gram‐positive, non‐sporulating, non‐pigmented and non‐motile rods and cocci, most of which are non‐respiring but aerotolerant anaerobes. They lack cytochromes and porphyrins and are therefore catalase‐ and oxidase‐negative. LAB tend to be nutritionally fastidious, often requiring specific amino acids, B‐vitamins and other growth factors. Some do take up oxygen through the mediation of flavoprotein oxidases, thus producing hydrogen peroxide and/or re‐oxidizing NADH during dehydrogenation of sugars. The cellular energy is derived from the fermentation of carbohydrates to produce major lactic acid. They use one of two different pathways and this provides a useful diagnostic feature in their classification. Since many species of lactic acid bacteria (LAB) and other food‐associated bacteria had a long historical association with human foods, they are recognized as generally regarded as safe (GRAS) bacteria. Infections by LAB are characterized as opportunistic that rely on host factors rather than on intrinsic pathogenicity. Only rare cases of clinical infections have been reported in humans, for example, in patients with endocarditis or with immune deficiency [8, 12–15].

Homofermentative organisms produce only lactic acid from the glucose fermentation during the Embden‐Meyerhof‐Parnas glycolytic pathway. Heterofermenters produce roughly equimolar concentration of lactate, ethanol/acetate and carbon dioxide from glucose (**Table 1**).


**Table 1.** Principal genera of the lactic acid bacteria [8].

the nomadic people from central Asia, fermentation of meat by the Germanic tribes and fish by the Eskimos, preparation of boza by the ancient Persians or fermenting maize by the native tribes in pre‐Columbian America [1]. The earliest records about fermentation process were dated back to 6000 BC, and thus fermentation represents one of the oldest food preservation methods [2, 3]. The ancient people probably did not have any knowledge of microbiology, but in the middle of the nineteenth century, Louis Pasteur significantly contributed to the understanding of the fermentation process itself. He established the role of microorganisms and proved that there are many different kinds of fermentation [3]. The original and primary purpose of fermentation was a preservation effect. Subsequently, with the development of many available preservation technologies, plenty of fermented foods were therefore manufactured because of their unique flavours, aromas and textures much appreciated to a consumer [4, 5]. Fermentation process created plenty of traditional food products, such as milk products (cheese, butter and yoghurt), fermented meat, plants and fruits (sausages, silage, sauerkraut, olives and grapes) and finally fermented cereal products such as bread and beer [6]. Fermented food and beverages are defined as those that have been subjected to the effect of microbial enzymes, particularly amylases, proteases and lipases that cause biochemical transformation of polysaccharides, proteins and lipids to non‐toxic variety of desirable products with tastes, aromas and textures attractive to a

In food fermentations, conditions of treatment and storage create an environment in which certain types of organism can flourish and these have a benign effect on the food rather than spoiling it. The majority of fermented foods is produced by the activity of lactic acid bacteria (LAB) and fungi, principally yeasts but also, to a lesser extent, moulds. Both groups of organisms share a common ecological niche, are able to grow under conditions of low pH and reduced water activity, although only lactic acid bacteria and facultative yeasts will prosper under anaerobic conditions. They frequently occur together in fermented products, dairy and

Microorganisms responsible for the fermentation process may be presented naturally in the

Lactic acid bacteria (LAB) represent an ubiquitous and heterogeneous species with common feature of lactic acid production as a result of sugar metabolism which leads to an acidification of the environment down to a pH of 3.5 [10]. The monograph by Orla‐Jensen (1919) formed the basis of the present classification of LAB that take into account the cellular morphology, mode of glucose fermentation, growth temperature and sugar utilization possibilities [11]. Taxonomically, LAB are divided into two distinct phyla: *Firmicutes* and *Actinobacteria*. Within the *Firmicutes* phylum genera such as *Lactobacillus*, *Lactococcus*, *Leuconostoc*, *Oenococcus*, *Pediococcus*, *Streptococcus*, *Enterococcus*, *Tetragenococcus*, *Aerococcus*, *Carnobacterium*, *Weissella*, *Alloiococcus*, *Symbiobacterium* and *Vagococcus* belong. Within the *Actinobacteria* phylum, lactic

non‐dairy, but in some cases, they play the role of a spoilage agent [8].

acid bacteria belong to the *Atopobium* and *Bifidobacterium* genera [12].

substrate, or may be added as a starter and adjunct cultures [9].

consumer [4, 7].

224 Fermentation Processes

**2. Lactic acid bacteria**

#### **2.1. Starters used in lactic acid fermentation**

Genera *Lactobacillus* is recognized as being phylogenetically very heterogeneous and this is evidenced from broad interval of % G‐C content. They are in general characterized as Gram‐ positive, microaerophilic, non‐spore‐forming and non‐flagellated rods or coccobacilli. They are commonly found in a diversity of environments, in dairy and meat‐fermented products, in fermented and pickled vegetables, adhered on human‐mucosal surfaces (in the gastroin‐ testinal and vaginal tract) as well as in soil and plants [16, 17]. Intestinal lactobacilli (*Lb. rhamnosus*, *Lb. acidophilus*, *Lb. reuteri*, *Lb. plantarum* and *Lb. paracasei*) interact with the host and have been linked with numerous health benefits [18–20]. *Lb. reuteri* is one of the most probiotic bacteria, which are added to infant dried milk formula for babies with lactose intolerance or for realimentation after diarrhoea [21]. Lactobacilli are naturally presented in breast milk, especially species of *Lb. fermentum*, *Lb. rhamnosus*, *Lb. gasseri* and *Lb. salivarius* [18, 22–25]. Liptáková and co‐workers [26] identified frequently *Lb. plantarum* from breast milk of healthy mothers.

*Lactobacillus* species are divided into three groups based on fermentation end products: obligate homofermenters, facultative heterofermenters and obligate heterofermenters [17, 27]. Obligate homofermenters ferment hexoses almost exclusively to lactate but are unable to ferment pentoses or gluconate (*Lb. helveticus*, *Lb. acidophilus*, *Lb. delbrueckii* and others). *Lb. acidophilus* strains are the best known of the health‐promoting lactobacilli and it is a part of human gut microflora. As probiotic strain is added to dairy foods for its physiological benefits. The facultative heterofermenters ferment hexoses via the EMP pathway and pentoses due to phosphoketolase activity to lactate, acetate, formic acid and ethanol (*Lb. plantarum* and *Lb. casei*). Obligate heterofermenters such as *Lb. brevis*, *Lb. reuteri*, *Lb. fermentum* or *Lb. kefir* use the phosphoketolase pathway for hexoses and pentoses fermentation and the main products of fermentation are lactic and acetic acid (or ethanol), and carbon dioxide [13, 15, 28].

Genera *Lactococcus* contains the major mesophilic microorganisms used for lactic acid pro‐ duction especially in dairy fermentations (sour milk and cream, lactic butter, fresh, soft and hard cheeses of artisanal and commercial origin). Some of them are suitable for cereal and pseudocereal fermentations [29, 30]. Joseph Lister made the first reported isolation of micro‐ organism responsible for milk fermentation in 1873. He named the culture *Bacterium lactis* that was changed to *S. lactis* later. Orla‐Jensen in 1919 differentiated mesophilic lactic streptococci into *S. lactis* and *S. cremoris*, which were included in Group N *Streptococci* [29]. On the present, the genus *Lactococcus* comprises nine species: *L. lactis* (including the subspecies *lactis*, *cremoris* and *hordniae*), *L. garvieae*, *L. piscium*, *L. plantarum*, *L. raffinolactis*, *L. chungangensis*, *L. fujiensis*, *L. formosensis* and *L. taiwanensis* [31, 32]. *L. cremoris* is unable to ferment maltose and ribose, to grow at 4% of salt and to hydrolyse arginine in comparison with *L. lactis*. *L. lactis* subsp. *lactis* var. *diacetylactis* converts citrate to diacetyl, carbon dioxide and acetone responsible for a creamy and buttery aroma in fermented milks, cream and butter and in Camembert, Emmental and Cheddar type of cheeses [13, 15, 33].

Many strains of *L. lactis* produce bacteriocins, which have antimicrobial activity especially against a narrow spectrum of *Lactococci;* however, nisin and lacticin 3147 have much broader activity against a wider range of Gram‐positive bacteria. Nisin has been accepted as a food additive to control contaminating microbiota [11, 29]. Sadiq et al. [34] isolated three bacterio‐ cinogenic strains *L. lactis* described as TI‐4, CE‐2 and PI‐2 that were effective against *B. subtilis* and *S. aureus* and the maximum of bacteriocins (nisin A and nisin Z) were produced at 25 and 30°C and at pH 5 and 8, respectively.

Leuconostocs (predominantly *Ln. mesenteroides* subsp. *cremoris*) are the most commonly used heterofermentative dairy lactic acid bacteria that are flavour‐producers in a number of fermented dairy products and cheeses. The fermentation of citrate is important in diacetyl and carbon dioxide formation in some types of cheeses. The genus *Leuconostoc* consists of 12 species isolated from plant, fermented foods (meats and vegetables or dairy products), vacuum‐ packaged, cold‐stored meat, honey, Ethiopian coffee fermentation, kimchi, palm wine, cane juice and human clinical sources: *Ln. mesenteroides*, *Ln. pseudomesenteroides*, *Ln. carnosum*, *Ln. citreum*, *Ln. fallax*, *Ln. gasicomitatum*, *Ln. gelidum*, *Ln. holzapfelii*, *Ln. inhae*, *Ln. kimchii*, *Ln. lactis*, *Ln. palmae* [35–38].

Twelve species of genera *Pediococcus* are currently recognized: *P. acidilactici*, *P. pentosaceus*, *P. argentinicus*, *P. cellicola*, *P. claussenii*, *P. damnosus*, *P. ethanolidurans*, *P. inopinatus*, *P. lolii*, *P. parvulus*, *P. siamensis* and *P. stilesii*. In contrast to other cocci in the LAB, pediococci usually do not form chains of cells [35, 39]. Pediococci are associated with dairy products and dairy environment and have potential impact on texture due to exopolysaccharides production. Garai‐Ibabe et al. isolated two strains of *P. parvulus* (CUPV1 and CUPV22) that enable to produce high concentration of 2‐substituted (1,3)‐β‐d‐glucan increasing viscosity of the growth media [40]. Pediococci are often found in a large number of several fermented meat and fish products, fermented beans, cereals, olives or sauerkraut. Some strains are proposed to have probiotic activity due to their ability to survive and adhere to the gastrointestinal tract and due to reported immune modulation capability [13, 39, 41].

*Lactobacillus* species are divided into three groups based on fermentation end products: obligate homofermenters, facultative heterofermenters and obligate heterofermenters [17, 27]. Obligate homofermenters ferment hexoses almost exclusively to lactate but are unable to ferment pentoses or gluconate (*Lb. helveticus*, *Lb. acidophilus*, *Lb. delbrueckii* and others). *Lb. acidophilus* strains are the best known of the health‐promoting lactobacilli and it is a part of human gut microflora. As probiotic strain is added to dairy foods for its physiological benefits. The facultative heterofermenters ferment hexoses via the EMP pathway and pentoses due to phosphoketolase activity to lactate, acetate, formic acid and ethanol (*Lb. plantarum* and *Lb. casei*). Obligate heterofermenters such as *Lb. brevis*, *Lb. reuteri*, *Lb. fermentum* or *Lb. kefir* use the phosphoketolase pathway for hexoses and pentoses fermentation and the main products of

fermentation are lactic and acetic acid (or ethanol), and carbon dioxide [13, 15, 28].

and Cheddar type of cheeses [13, 15, 33].

30°C and at pH 5 and 8, respectively.

*Ln. palmae* [35–38].

226 Fermentation Processes

Genera *Lactococcus* contains the major mesophilic microorganisms used for lactic acid pro‐ duction especially in dairy fermentations (sour milk and cream, lactic butter, fresh, soft and hard cheeses of artisanal and commercial origin). Some of them are suitable for cereal and pseudocereal fermentations [29, 30]. Joseph Lister made the first reported isolation of micro‐ organism responsible for milk fermentation in 1873. He named the culture *Bacterium lactis* that was changed to *S. lactis* later. Orla‐Jensen in 1919 differentiated mesophilic lactic streptococci into *S. lactis* and *S. cremoris*, which were included in Group N *Streptococci* [29]. On the present, the genus *Lactococcus* comprises nine species: *L. lactis* (including the subspecies *lactis*, *cremoris* and *hordniae*), *L. garvieae*, *L. piscium*, *L. plantarum*, *L. raffinolactis*, *L. chungangensis*, *L. fujiensis*, *L. formosensis* and *L. taiwanensis* [31, 32]. *L. cremoris* is unable to ferment maltose and ribose, to grow at 4% of salt and to hydrolyse arginine in comparison with *L. lactis*. *L. lactis* subsp. *lactis* var. *diacetylactis* converts citrate to diacetyl, carbon dioxide and acetone responsible for a creamy and buttery aroma in fermented milks, cream and butter and in Camembert, Emmental

Many strains of *L. lactis* produce bacteriocins, which have antimicrobial activity especially against a narrow spectrum of *Lactococci;* however, nisin and lacticin 3147 have much broader activity against a wider range of Gram‐positive bacteria. Nisin has been accepted as a food additive to control contaminating microbiota [11, 29]. Sadiq et al. [34] isolated three bacterio‐ cinogenic strains *L. lactis* described as TI‐4, CE‐2 and PI‐2 that were effective against *B. subtilis* and *S. aureus* and the maximum of bacteriocins (nisin A and nisin Z) were produced at 25 and

Leuconostocs (predominantly *Ln. mesenteroides* subsp. *cremoris*) are the most commonly used heterofermentative dairy lactic acid bacteria that are flavour‐producers in a number of fermented dairy products and cheeses. The fermentation of citrate is important in diacetyl and carbon dioxide formation in some types of cheeses. The genus *Leuconostoc* consists of 12 species isolated from plant, fermented foods (meats and vegetables or dairy products), vacuum‐ packaged, cold‐stored meat, honey, Ethiopian coffee fermentation, kimchi, palm wine, cane juice and human clinical sources: *Ln. mesenteroides*, *Ln. pseudomesenteroides*, *Ln. carnosum*, *Ln. citreum*, *Ln. fallax*, *Ln. gasicomitatum*, *Ln. gelidum*, *Ln. holzapfelii*, *Ln. inhae*, *Ln. kimchii*, *Ln. lactis*, *Streptococcus* derives from the Greek 'streptos'—easily twisted like a chain—and 'kokkos' grain/seed and the term was firstly used in 1874 by Billroth as a descriptor for the chain‐ forming, coccoid‐shaped bacteria. Rosenbach (1884) firstly applied the generic name *Strepto‐ coccus* when describing *S. pyogenes,* the chain‐forming coccus isolated from suppurative abscess in human. In 1906, Andrewes and Horder examined 1200 streptococci isolated from human, air and milk sources, and on the basis of sugar metabolism, reduction of neutral red and growth characteristics in milk, they distinguished eight groups. Sherman in 1937 produced the first comprehensive systematic classification of streptococcal isolates from environmental, com‐ mensal and hospital sources. He excluded from the genus *Streptococcus* all strictly anaerobic cocci and pneumococci because of their extreme sensitivity to bile and introduced four primary divisions: pyogenic, enterococcus, lactic and viridans group [42]. The results of molecular taxonomic studies allowed the major changes in the classification of *Streptococcus* spp.: the 'lactic' streptococci now constitute the genus *Lactococcus* and some members from Sherman's 'enterococcus' division became foundation members of the genus *Enterococcus* [43]. The subdivision of *Streptococci* into seven groups is based on 16S rRNA gene sequence data correlated well with the results of DNA‐DNA re‐association experiments and numerical taxonomic studies [44–46].

The only *Streptococcus* sp. useful in milk fermentation (production of yoghurt and Swiss‐ or Italian‐type cooked cheeses such as Grana Padano, Gorgonzola, Mozzarella or Fontina) is *S. thermophilus* var. *salivarius*. It has the status of GRAS in the USA and a Qualified Presump‐ tion of Safety in European Union due to its long history of safe use in food manufacture. The end products of lactose fermentation are lactate, acetaldehyde and diacetyl. Some strains are able to produce thermophilins, proteinaceous compounds that are inhibitory against listeria and clostridia, especially thermophilin 13 and 1277 have a broad inhibitory spectrum [15, 27, 28, 47–50].

Species from the genus *Bifidobacterium* were originally identified from stool samples of breast‐ fed infants as bacteria with a strange and characteristic Y shape in 1899 by Tissier and named *B. bifidus*. In 1924, Orla‐Jensen recognized the existence of the genus *Bifidobacterium* as a separate taxon but due to the similarities of bifidobacteria with the genus *Lactobacillus* they were included in this genus. In 1957, Dehnart realized the existence of multiple biotypes of *Bifidobacterium* and proposed a scheme for the differentiation of these bacteria based on their hexose fermentation pathway [51].

The most frequently found strains in the human gastrointestinal tract include *B. adolescentis*, *B. bifidum*, *B. breve*, *B. catenulatum*, *B. pseudocatenulatum*, *B. longum* subsp. *infantis*, *B. longum* subsp. *longum*, *B*. *dentium* and *B. angulatum* [52]. Bifidobacteria represent up to 25% of the cultivation faecal microbiota in adults and 80% in infants [53]. According to Matsukiand and co‐workers [54], the most often isolated bifidobacteria from adult intestinal tract are *B. catenulatum*, *B. longum* and *B. adolescentis,* whereas *B. breve*, *B. infantis* and *B. longum* predom‐ inate in the infant intestine.

The most important species of *Bifidobacterium* for probiotic application are *B. longum*, *B. bifidum* and *B. animalis*. Children receiving *Bifidobacterium*‐supplemented milk‐based formula (*B. lactis* Bb‐12 strain) were protected against symptomatic rotavirus infection. Daily consumption of three cups/day of *B. longum* yoghurts decreased erythromycin‐associated gastrointestinal disorders. *B. bifidum* NCFB 1454 was found to be active against certain species of *Listeria*, *Bacillus*, *Enterococcus*, *Pediococcus* and *Leuconostoc* due to bifidocin B production [15, 16, 28, 51, 53, 55, 56].

#### **3. Antimicrobial compounds produced by lactic acid bacteria**

Lactic acid bacteria may produce substances and thus create conditions harmful for undesired bacteria, yeasts and moulds which lead to the increase of food shelf life [57]. Temperature and incubation period are the main factors modulating production of antimicrobial substances. Sathe et al. [58] in their study evaluated the impact of the growth phase on antimicrobial activity of *Lb. plantarum* at 30°C. The evaluated strain showed maximal antimicrobial activity at the end of exponential phase of growth, and in stationary phase after 48 h of cultivation, decline in antimicrobial activity was observed. These results are consistent with the study of Batish et al. [59] who observed maximal antimicrobial activity of the same strain after 48 h of incubation at 30°C. The main product of fermentation by lactic acid bacteria is mostly lactic acid. However, under aerobic conditions, carbon dioxide and acetic acid are created as a result of oxidative dissimilation, while hydrogen peroxide as an intermediate product is formed [27]. Most of the isolated and identified antimicrobial substances produced by lactic acid bacteria are with low‐molecular weight composed of organic acids, reuterin, hydrogen peroxide, hydroxyl fatty acids, phenolic and proteinaceous compounds [60].

When lactic acid is produced, the pH decreases and consequently the organic acids or small fatty acids (SFAs) become undissociated and represent the main antimicrobial activity of the LAB [61]. It has been shown that organic acids penetrate bacterial membrane of the target microorganism and inhibit transport mechanism in the cell by reducing pH values [62]. The effect of acids depends not only in combination with lowering pH and reduction of redox potential but also on the type and concentration of acid presented in the environment [63]. Acetic acid in comparison to lactic acid was described as being more effective, and is able to inhibit growth of moulds, yeasts and bacteria [5]. Propionic acid inhibits moulds and selected Gram‐positive microorganism [62]. Phenyllactic acid and pyroglutamic acid are able to inhibit growth of *Aspergillus niger*, *A. flavus* and *Penicillium expansum*, and both were isolated from cell‐free extract of *L. plantarum* and *Lb. rhamnosus* GG (LGG) [60, 64]. Liptáková et al. [64] mathematically predicted the inhibitory effect of *Lb. rhamnosus* GG (LGG) on the growth dynamics of *Candida maltosa* YP1 and *Geotrichum candidum* yeasts. At 18°C, growth rates of the yeasts in mixed cultures decreased about 50% compared with rates of its pure cultures. The effectiveness of growth inhibition of *C. maltosa* was dependent on initial LGG concentration; the most antagonistic activity of lactobacilli was determined at log 4 and log 6 initial concen‐ tration (**Figure 1**). Greifová et al. [65] described the inhibitory effect of D, L‐phenyllactic acid on moulds such as *Alternaria alternata*, *A. flavus*, *Cladosporium herbarum*, *Fusarium nivale*, *Mucor racemosus* and *P. funiculosum*.

*Bifidobacterium* and proposed a scheme for the differentiation of these bacteria based on their

The most frequently found strains in the human gastrointestinal tract include *B. adolescentis*, *B. bifidum*, *B. breve*, *B. catenulatum*, *B. pseudocatenulatum*, *B. longum* subsp. *infantis*, *B. longum* subsp. *longum*, *B*. *dentium* and *B. angulatum* [52]. Bifidobacteria represent up to 25% of the cultivation faecal microbiota in adults and 80% in infants [53]. According to Matsukiand and co‐workers [54], the most often isolated bifidobacteria from adult intestinal tract are *B. catenulatum*, *B. longum* and *B. adolescentis,* whereas *B. breve*, *B. infantis* and *B. longum* predom‐

The most important species of *Bifidobacterium* for probiotic application are *B. longum*, *B. bifidum* and *B. animalis*. Children receiving *Bifidobacterium*‐supplemented milk‐based formula (*B. lactis* Bb‐12 strain) were protected against symptomatic rotavirus infection. Daily consumption of three cups/day of *B. longum* yoghurts decreased erythromycin‐associated gastrointestinal disorders. *B. bifidum* NCFB 1454 was found to be active against certain species of *Listeria*, *Bacillus*, *Enterococcus*, *Pediococcus* and *Leuconostoc* due to bifidocin B production [15, 16, 28, 51,

Lactic acid bacteria may produce substances and thus create conditions harmful for undesired bacteria, yeasts and moulds which lead to the increase of food shelf life [57]. Temperature and incubation period are the main factors modulating production of antimicrobial substances. Sathe et al. [58] in their study evaluated the impact of the growth phase on antimicrobial activity of *Lb. plantarum* at 30°C. The evaluated strain showed maximal antimicrobial activity at the end of exponential phase of growth, and in stationary phase after 48 h of cultivation, decline in antimicrobial activity was observed. These results are consistent with the study of Batish et al. [59] who observed maximal antimicrobial activity of the same strain after 48 h of incubation at 30°C. The main product of fermentation by lactic acid bacteria is mostly lactic acid. However, under aerobic conditions, carbon dioxide and acetic acid are created as a result of oxidative dissimilation, while hydrogen peroxide as an intermediate product is formed [27]. Most of the isolated and identified antimicrobial substances produced by lactic acid bacteria are with low‐molecular weight composed of organic acids, reuterin, hydrogen peroxide,

When lactic acid is produced, the pH decreases and consequently the organic acids or small fatty acids (SFAs) become undissociated and represent the main antimicrobial activity of the LAB [61]. It has been shown that organic acids penetrate bacterial membrane of the target microorganism and inhibit transport mechanism in the cell by reducing pH values [62]. The effect of acids depends not only in combination with lowering pH and reduction of redox potential but also on the type and concentration of acid presented in the environment [63]. Acetic acid in comparison to lactic acid was described as being more effective, and is able to inhibit growth of moulds, yeasts and bacteria [5]. Propionic acid inhibits moulds and selected

**3. Antimicrobial compounds produced by lactic acid bacteria**

hydroxyl fatty acids, phenolic and proteinaceous compounds [60].

hexose fermentation pathway [51].

228 Fermentation Processes

inate in the infant intestine.

53, 55, 56].

Liptáková and co‐workers [66] focused on the growth of yoghurt contaminant *C. maltosa* YP1 in milk as influenced with initial different numbers of *Lb. rhamnosus* VT1 (ranged from 1 to 15% v/v) and temperature. The growth parameters of yeast in dependence on the lactobacilli counts at 17°C are summarized in **Table 2**. The antagonistic relationship between *C. maltosa* YP1 and *Lb. rhamnosus* VT1 was based not only on the lactic acid but it was consequence of the other antimicrobial, non‐proteinaceous and non‐saccharidic substances, identified by Plock‐ ová et al. [67] and also pyroglutamic acid, later identified by Liptáková et al. [64].

**Figure 1.** Growth dynamics of *C. maltosa* YP1 in co‐culture with *Lb. rhamnosus* GG at 18°C in dependence on various initial lactobacilli concentration (♦ without LGG addition, △ 2 log LGG initial counts, ⋇ 4 log LGG initial counts, ■ 6 LGG initial counts).


**Table 2.** Values of growth rate (Gr) and lag time (λ) of *C. maltosa* YP1 in milk in dependence of initial numbers of *Lb. rhamnosus* VT1 at 17 ± 0.5°C.

#### **3.1. Hydrogen peroxide**

Most lactic acid bacteria produce hydrogen peroxide in the presence of oxygen. After its accumulation, inhibitory effect is mediated through oxidizing effect on membrane lipids and cell proteins of targeted microorganism. The antimicrobial activity of the compound in lower concentrations mostly in food is enhanced by treatment with the formation of hypothiocyanite catalysed by lactoperoxidase system [68]. Fitzsimmons and Berry [69] reported in their study the inhibitory effect of hydrogen peroxide on the growth of *C. albicans*. The minimum inhibi‐ tory concentration is less than 0.025% [60].

#### **3.2. Carbon dioxide**

Carbon dioxide at low concentrations may stimulate the growth of selected bacteria. Creating an anaerobic environment may be toxic to some aerobic food microorganisms through its action on cell membranes and its ability to reduce internal and external pH values [5].

#### **3.3. Bacteriocins**

Bacteriocins are ribosomally synthesized antimicrobial group of heterogeneous peptides with antimicrobial effect that kill or inhibit the growth of other bacterial strains. Typically, LAB bacteriocins have a narrow antibacterial spectrum, but some strains may also produce bacteriocins with a broad antibacterial spectrum. Selected lactic acid bacteria may inhibit the growth of Gram‐positive pathogenic and spoilage bacteria, as well as yeasts. It has been reported that bacteriocins also inhibit the growth of some Gram‐negative species. Lozo et al. [70] showed the production of bacteriocin 217 (Bac 217) by the strain *Lb. paracasei* subsp. *paracasei* BGBUK2‐16 isolated from traditional home cheese that shows inhibitory effect against *Staphylococcus aureus*. Strains of *Lb. fermentum*, *Lb. pentosus*, *Lb. paracasei* and *Lb. rhamnosus* isolated from traditional corn drink made of wheat have produced active bacteriocins against *Escherichia coli*, *P. aeruginosa* and *E. faecalis* [71]. Valdés‐Stauber and Scherer [72] isolated and characterized Linocin M18, bacteriocin produced by B. linens M18 in stationary growth phase. This bacteriocin was able to inhibit *Listeria* spp., especially *L. monocytogenes*, *L. innocua*, *L.* *ivanovii* and several coryneforms, Gram‐negative bacteria were insensitive. Corsetti et al. [73] in their study described the antimicrobial substances in sourdough and identified them as a bacteriocins‐like inhibitory substance. Some leuconostocs, especially *Ln. mesenteroides* subsp. *mesenteroides* Y105 and UL5, are able to produce bacteriocins with antilisterial activity [37, 74]. Some strains of *Pediococcus* spp. may have antimicrobial effect by the production of pediocins against undesirable and pathogenic microorganisms, for example, *Listeria* spp. and *Clostridium perfringens* [75]. Gurira and Buys [76] isolated *P. acidilactici* and *P. pentosaceus* from Bouquet and Gouda cheeses as non‐starter lactic acid bacteria which had inhibitory potential against *L. monocytogenes* ATCC 7644 and *B. cereus* ATCC 1178 through the action of pediocins. Altuntas et al. [77] confirmed the antilisterial effect of pediocin producing strain *P. acidilactici* 13 in their study.

#### *3.3.1. Reuterin*

**Initial inoculation of** *Lb. rhamnosus* **VT1 (% v/v) Growth rate (log CFU ml‐1 h‐1) Lag‐phase duration (h)**

**Table 2.** Values of growth rate (Gr) and lag time (λ) of *C. maltosa* YP1 in milk in dependence of initial numbers of *Lb.*

Most lactic acid bacteria produce hydrogen peroxide in the presence of oxygen. After its accumulation, inhibitory effect is mediated through oxidizing effect on membrane lipids and cell proteins of targeted microorganism. The antimicrobial activity of the compound in lower concentrations mostly in food is enhanced by treatment with the formation of hypothiocyanite catalysed by lactoperoxidase system [68]. Fitzsimmons and Berry [69] reported in their study the inhibitory effect of hydrogen peroxide on the growth of *C. albicans*. The minimum inhibi‐

Carbon dioxide at low concentrations may stimulate the growth of selected bacteria. Creating an anaerobic environment may be toxic to some aerobic food microorganisms through its action on cell membranes and its ability to reduce internal and external pH values [5].

Bacteriocins are ribosomally synthesized antimicrobial group of heterogeneous peptides with antimicrobial effect that kill or inhibit the growth of other bacterial strains. Typically, LAB bacteriocins have a narrow antibacterial spectrum, but some strains may also produce bacteriocins with a broad antibacterial spectrum. Selected lactic acid bacteria may inhibit the growth of Gram‐positive pathogenic and spoilage bacteria, as well as yeasts. It has been reported that bacteriocins also inhibit the growth of some Gram‐negative species. Lozo et al. [70] showed the production of bacteriocin 217 (Bac 217) by the strain *Lb. paracasei* subsp. *paracasei* BGBUK2‐16 isolated from traditional home cheese that shows inhibitory effect against *Staphylococcus aureus*. Strains of *Lb. fermentum*, *Lb. pentosus*, *Lb. paracasei* and *Lb. rhamnosus* isolated from traditional corn drink made of wheat have produced active bacteriocins against *Escherichia coli*, *P. aeruginosa* and *E. faecalis* [71]. Valdés‐Stauber and Scherer [72] isolated and characterized Linocin M18, bacteriocin produced by B. linens M18 in stationary growth phase. This bacteriocin was able to inhibit *Listeria* spp., especially *L. monocytogenes*, *L. innocua*, *L.*

0.064 0.1

0.052 8.1

0.046 74.2

0.043 73.1

1.0 0.062 0.1

5.0 0.055 5.5

10.0 0.046 72.9

15.0 0.041 76.4

*rhamnosus* VT1 at 17 ± 0.5°C.

230 Fermentation Processes

**3.1. Hydrogen peroxide**

**3.2. Carbon dioxide**

**3.3. Bacteriocins**

tory concentration is less than 0.025% [60].

Reuterin is a product of glycerol fermentation produced during stationary phase by *Lb. reu‐ teri*, *Lb. brevis*, *Lb. buchneri*, *Lb. collinoides* and *Lb. coryniformis* under anaerobic conditions, which enables to suppress ribonuclease activity [60]. Reuterin has a wide inhibitory spec‐ trum against Gram‐negative and Gram‐positive bacteria, yeasts, fungi and protozoa: *Salmo‐ nella*, *Shigella*, *Clostridium*, *Staphylococcus*, *Listeria*, *Candida* and *Trypanosoma* [78]. An inhibitory effect on the growth of genus *Aspergillus* and *Fusarium* has been reported. The addition of glycerol to the media containing lactic acid bacteria producing reuterin in‐ creased its antifungal activity [60].

#### **4. Probiotics and functional foods**

#### **4.1. Probiotics**

The word probiotic originated from Greek meaning 'for life'. The first definition of probiotics was described by Vergin, 1954, as the opposite to antibiotics, and 1 year later Kolb proposed that the microbial imbalance in the human body as a result of antibiotic therapy could be restored by probiotics. Parker in 1974 defined the probiotics as organisms and substances that contribute to gut‐microbial balance. Most frequently cited definition is that of Fuller's (1992), who defined them as 'a live microbial feed supplement, which beneficially affects the host animal by improving its intestinal microbial balance'. According to the recommendations of a Food and Agriculture Organization/World Health Organization (FAO/WHO)‐working group on probiotics suggested definition describes probiotics as live microorganisms that when administered in adequate amounts confer health benefit on the host (2002). Health benefits must be scientifically established by clinical studies in humans and published in peer‐ reviewed journals [79]. A number of genera and strains of bacteria (*Lactobacillus*, *Bifidobacteri‐ um*, *Lactococcus*, *Leuconostoc*, *Pediococcus*, *S. salivarius* subsp. *thermophilus*, *E. faecium*, *E. faecalis*, *E. coli*, *B. cereus*, *B. subtilis*, *B. clausii*, *B. coagulans*, *B. licheniformis* and *B. polyfermenticus*) and yeast *Saccharomyces boulardii* are used as probiotic mostly in dairy products (milks, yoghurts and probiotic cheeses) but also in non‐dairy food and beverages such as dry sausages, soy milk drink, juices, fermented cereal products Boza, Bushera, Mahewu and Pozol [57, 80–85]. Lee and co‐workers [86] investigated the probiotic potential of *B. polyfermenticus* KU3 isolated from kimchi. The spore suspension was resistant to artificial gastric juice and survived for 24 h in artificial bile acid, adhered strongly to HT‐29 cell line and anti‐carcinogenic activity of *B. polyfermenticus* KU3 was observed. Cell *B. polyfermenticus* strongly inhibited the proliferation of various cancer cell lines such as HeLa, LoVo, HT‐29 and MCF‐7 (percentage of inhibition between 90.5 and 96.9%). Liptáková et al. [87] observed comparable inhibition effect on the proliferation of HeLa and Caco‐2 cells due to the adhesion and metabolism of probiotic *Lb. acidophilus* 145 (95–96%) and *Lb. rhamnosus* GG (68%).

**Figure 2.** *Lactobacillus acidophilus* contents in the fermented milk at the end of shelf life.

The choice of which microbe to use as a probiotic is determined by many factors: probiotics have to be safe, non‐pathogenic and non‐toxic species, survive the passage through the intestinal tract and adhere to the intestinal mucosa and organic acid production, lactic and acetic [57, 79]. According to Tripathi and Giri [85], the viability of probiotics in food is affected by many factors such as pH, water activity, redox potential of foods, presence of salt, sugar, hydrogen peroxide, bacteriocins, aroma and colouring compounds, processing, packaging and storage conditions. Probiotic foods should preferably be stored at a temperature between 4 and 5°C. The highest viability of *Lb. acidophilus* LA‐5 in yoghurt was observed 20 days at 2°C, but for *B. lactis* BB 12 the optimum storage temperature was 8°C [88, 89]. To realize health benefits on host, probiotic microorganisms must be viable and available in a high concentration of about 106 to 107 CFU/ml or g at the end of shelf life of product, so minimum therapeutic daily dose is usually considered as 108 to 109 CFU/ml or g [16]. Liptáková et al. [90] determined the concentration of *Lb. acidophilus* 145 in acidophilus milk at the end of shelf life during storage at 6, 8 and 10°C. The number of probiotic *Lb. acidophilus* 145 ranged from 6 to 7 log counts. Over a period of 5 years (2007–2011), Valík et al. [91] monitored the contents of *Lb. acidophilus* in the fermented milk at the end of shelf life. The average values in log CFU/g ranged in interval from 6.85 to 7.47, respectively. In the years 2007 and 2008, 9.87 and 1.01% of samples contained less than 106 CFU/g of *Lb. acidophilus* at the end of consumption, while in other years they did not find any sample with number lower than 106 CFU/g (**Figure 2**).

The mechanisms of health‐improving properties of probiotics are still not completely under‐ stood, but their anti‐carcinogenic and anti‐mutagenic activity, the suppression of allergies, reduction of serum cholesterol level and reduction in blood pressure are known [12, 80, 92, 93]. *Lb. bulgaricus* and *S. thermophilus* are able to ferment lactose, so they have beneficial effects for people suffering from lactose intolerance [94]. *Lb. rhamnosus* GG, *B. lactis* Bb‐12, *Lb. acidophilus*, *Lb. casei* Shirota or *Lb. reuteri* have beneficial effects against acute diarrhoea caused by rotavirus, in treatment, shortening or preventing of this disease [95–97]. The administration of *S. boulardii* as non‐pathogenic biotherapeutic yeast plays essential role in the treatment or prevention of antibiotic‐associated diarrhoea caused by *C. difficile* [83, 98–101]. Probiotics, especially *Lb. acidophilus*, *Lb. plantarum*, *Lb. rhamnosus* and *Bifidobacterium,* are able to reduce faecal enzyme activity which converts procarcinogens into carcinogens (β‐glucuronidase, azoreductase, urease, nitroreductase and glycocholic acid reductase) due to short‐chain fatty acids production and may thus contribute to a decreasing risk of colorectal carcinoma [79, 102]. Other potential mechanisms for probiotics‐induced anti‐carcinogenic activity are described in the works of Commune et al. [92] and Faghfoori et al. [103], respectively.

#### **4.2. Fermented cereals and pseudocereals functional products**

drink, juices, fermented cereal products Boza, Bushera, Mahewu and Pozol [57, 80–85]. Lee and co‐workers [86] investigated the probiotic potential of *B. polyfermenticus* KU3 isolated from kimchi. The spore suspension was resistant to artificial gastric juice and survived for 24 h in artificial bile acid, adhered strongly to HT‐29 cell line and anti‐carcinogenic activity of *B. polyfermenticus* KU3 was observed. Cell *B. polyfermenticus* strongly inhibited the proliferation of various cancer cell lines such as HeLa, LoVo, HT‐29 and MCF‐7 (percentage of inhibition between 90.5 and 96.9%). Liptáková et al. [87] observed comparable inhibition effect on the proliferation of HeLa and Caco‐2 cells due to the adhesion and metabolism of probiotic *Lb.*

*acidophilus* 145 (95–96%) and *Lb. rhamnosus* GG (68%).

232 Fermentation Processes

**Figure 2.** *Lactobacillus acidophilus* contents in the fermented milk at the end of shelf life.

of about 106

to 107

The choice of which microbe to use as a probiotic is determined by many factors: probiotics have to be safe, non‐pathogenic and non‐toxic species, survive the passage through the intestinal tract and adhere to the intestinal mucosa and organic acid production, lactic and acetic [57, 79]. According to Tripathi and Giri [85], the viability of probiotics in food is affected by many factors such as pH, water activity, redox potential of foods, presence of salt, sugar, hydrogen peroxide, bacteriocins, aroma and colouring compounds, processing, packaging and storage conditions. Probiotic foods should preferably be stored at a temperature between 4 and 5°C. The highest viability of *Lb. acidophilus* LA‐5 in yoghurt was observed 20 days at 2°C, but for *B. lactis* BB 12 the optimum storage temperature was 8°C [88, 89]. To realize health benefits on host, probiotic microorganisms must be viable and available in a high concentration

CFU/ml or g at the end of shelf life of product, so minimum therapeutic

Recently, there is an explosion of consumer's interest in functional foods; therefore, a key priority for food industry is the development of such products with a high quality and safety [104]. The aim of these products is to have beneficial effect on host health affecting gut microbial composition subsequently with reducing the risk of chronic diseases [105]. Cereals have been investigated in recent years regarding their potential use in the production of functional foods [106].

Possible application of cereals in functional food can be summarized as follows:


Cereals have been and still are one of the most important sources of human diet [108] and are grown over 73% of total harvest area [109]. A number of cereals are grown in different countries, including wheat, barley, oat, corn, rye, rice and millet, particularly important from an economical point of view. According to FAO's latest forecast, cereal production in 2015 stands at close to 2525 million tonnes but is still 1.4% below than the record in 2014 [110]. Cereal grains and their derivatives represent an important nutritive component both in developed and in developing countries [111]. They are considered as one of the most important sources of dietary proteins, carbohydrates (starch and fibre), vitamins (B group) and minerals for people all over the world [112].

#### *4.2.1. Nutritional value of cereals*

Cereal grains are primarily a source of carbohydrates, and thus a good source of energy [113]. They form about two‐thirds up to three‐quarters of dry matter [114]. Monosaccharides are the basic components of oligo‐ and polysaccharides and are most represented in the forms of hexoses (fructose, glucose and galactose) and pentoses, arabinose and xylose [115]. Starch, the major component of cereal grains, occurs in starch granules of different sizes in endosperm.

Within common varieties, 25–27% of starch is presented as amylase and 72–75% represents amylopectin. However, in cereals a portion of the presented starch is not digested and absorbed in the small intestine. This is referred to as resistant starch and it appears to act in a similar way to a dietary fibre [113]. A wide variety of biochemical processes occur in cereals during fermentation as a result of lactic acid bacteria. Fermentation process itself may lead to an increase in the content of reducing sugars, which was confirmed also in a study by Marko et al. [116]. Simple carbohydrates are metabolized directly to organic acids and the glucose as a final product of starch metabolism is utilized immediately [116]. Lambo et al. [117] described the decrease in starch content during fermentation of barley with lactobacilli.

Cereals are in general good sources of proteins. The proportions of essential amino acids and their digestibility mainly determine protein nutritional quality. Because of different production systems, environmental factors, as well as genotype, it is difficult to obtain comparative values of protein contents of different cereals. Thus, ranges of 5.8–7.7% of protein on a dry weight have been measured for rice, 8.0–15.0% for barley and 9.0–11.0% for maize. The amount of lysine, which is the limiting amino acid for all cereals, varies between species with the highest values in oat and rice and lowest in wheat and maize [118]. The most represented is glutamic acid in the form of glutamine [119]. Degradation and depolymerization of proteins during fermentation process depend not only on the metabolic activity of presented bacteria but also on enzymes that naturally occurred in cereals. Peptides are converted to amino acids by the activity of lactic acid bacteria by the specific intracellular peptidases that are subsequently converted to the specific products influencing the aroma and taste of final products [120]. Antony and co‐workers [121] in their study pointed out that the fermentation process does not generally significantly change the total protein content of cereals. However, in the case of yeast corn fermentation, Cui et al. [122] found a significant increase (*P* < 0.05) in the total protein content.

Lipids are only a minor component of cereal grains with the amount varying from 1.7 to 7.0% on a dry mass basis, dependent on the type of cereal grain. The germ is the richest source of lipids. In particular, cereals are rich in essential fatty acids and contain only trace amounts of saturated fatty acids [123]. Oxidation of lipids during fermentation process creates volatiles that contribute to the flavour of final products. Linoleic, oleic and linolenic acids are oxidized by lipoxygenases by forming hydroperoxides that are formed to aldehydes [124]. Aldehydes are converted to alcohols by alcohol dehydrogenases during fermentation process [125]. Antony et al. [121] in their study did not record any changes in the total lipid content during the millet fermentation with the endogenous microorganisms.

countries, including wheat, barley, oat, corn, rye, rice and millet, particularly important from an economical point of view. According to FAO's latest forecast, cereal production in 2015 stands at close to 2525 million tonnes but is still 1.4% below than the record in 2014 [110]. Cereal grains and their derivatives represent an important nutritive component both in developed and in developing countries [111]. They are considered as one of the most important sources of dietary proteins, carbohydrates (starch and fibre), vitamins (B group) and minerals for

Cereal grains are primarily a source of carbohydrates, and thus a good source of energy [113]. They form about two‐thirds up to three‐quarters of dry matter [114]. Monosaccharides are the basic components of oligo‐ and polysaccharides and are most represented in the forms of hexoses (fructose, glucose and galactose) and pentoses, arabinose and xylose [115]. Starch, the major component of cereal grains, occurs in starch granules of different sizes in endosperm. Within common varieties, 25–27% of starch is presented as amylase and 72–75% represents amylopectin. However, in cereals a portion of the presented starch is not digested and absorbed in the small intestine. This is referred to as resistant starch and it appears to act in a similar way to a dietary fibre [113]. A wide variety of biochemical processes occur in cereals during fermentation as a result of lactic acid bacteria. Fermentation process itself may lead to an increase in the content of reducing sugars, which was confirmed also in a study by Marko et al. [116]. Simple carbohydrates are metabolized directly to organic acids and the glucose as a final product of starch metabolism is utilized immediately [116]. Lambo et al. [117] described

the decrease in starch content during fermentation of barley with lactobacilli.

Cereals are in general good sources of proteins. The proportions of essential amino acids and their digestibility mainly determine protein nutritional quality. Because of different production systems, environmental factors, as well as genotype, it is difficult to obtain comparative values of protein contents of different cereals. Thus, ranges of 5.8–7.7% of protein on a dry weight have been measured for rice, 8.0–15.0% for barley and 9.0–11.0% for maize. The amount of lysine, which is the limiting amino acid for all cereals, varies between species with the highest values in oat and rice and lowest in wheat and maize [118]. The most represented is glutamic acid in the form of glutamine [119]. Degradation and depolymerization of proteins during fermentation process depend not only on the metabolic activity of presented bacteria but also on enzymes that naturally occurred in cereals. Peptides are converted to amino acids by the activity of lactic acid bacteria by the specific intracellular peptidases that are subsequently converted to the specific products influencing the aroma and taste of final products [120]. Antony and co‐workers [121] in their study pointed out that the fermentation process does not generally significantly change the total protein content of cereals. However, in the case of yeast corn fermentation, Cui et al. [122] found a significant increase (*P* < 0.05) in the total protein

Lipids are only a minor component of cereal grains with the amount varying from 1.7 to 7.0% on a dry mass basis, dependent on the type of cereal grain. The germ is the richest source of lipids. In particular, cereals are rich in essential fatty acids and contain only trace amounts of

people all over the world [112].

234 Fermentation Processes

*4.2.1. Nutritional value of cereals*

content.

Cereals may contribute to vitamin intake due to the presence of most B‐vitamins and appre‐ ciable amounts of vitamin E. Wholegrain cereals also contain considerable amount of calcium, magnesium, iron, zinc, as well as lower levels of many trace elements, for example, selenium. The content of minerals ranges from 1.0 to 2.5% [113, 126]. Cereals contain relatively high levels of phytate (0.2–1.4%), concentrated mostly in the aleurone layer, which can bind minerals and there is an evidence of its decreased absorption in the presence of phytate, so minerals are not available to microorganisms. However, at a pH values less than 5.5, phytates are hydrolysed by endogenous phytases, thus minerals are released from the complex [9]. In our investigation, changes in chemical composition of maize flours before and after expiry date were determined (**Table 3**). The percentage of starch and reducing sugars is one of the most important aspects showing the suitability of the tested substrate in fermentation technologies. A decline in the content of reducing sugars (60.1%) and starch (7.9%) was observed. Matejčeková and co‐ workers [30] recorded a decline of reducing sugars in amaranth flours before and after expiry date of about 31% in their study.

In comparison to milk and dairy products, the nutritional quality of cereals and their products is sometimes inferior, or poor. The reason is the lower protein content in comparison to milk, limitations in the amounts of certain amino acids, notably lysine, and the presence of antinu‐ tritive compounds (phytic acid, tannins and polyphenols) and a coarse nature of grains [7, 127]. Cereals typically undergo a range of processes that change the nutritional content. Milling is the main process associated with cereals; also, extrusion is used to produce a variety of different types of products [128].


Corn flour 1 (before expiry date), corn flour 2 (after expiry date), the results are means ± standard deviation of two determinations.

**Table 3.** Chemical composition of maize flours before and after expiry date (%).

Helland et al. [106] studied the growth and metabolism of four selected probiotic strains in rice‐ or maize‐based puddings with milk or water. All four tested strains showed good growth and survival in cereal‐based puddings.

#### *4.2.2. Fermented cereal and pseudocereal food and beverages*

Fermented food and beverages are defined as those products that have been subjected to the effect of microbial enzymes, particularly amylases, proteases and lipases that causes biochem‐ ical transformation of polysaccharides, proteins and lipids to non‐toxic variety of desirable products with tastes, aromas and textures attractive to a consumer [4, 7]. Microorganisms responsible for the fermentation process may be presented naturally in the substrate, or may be added as a starter culture [9].

Traditional cereal‐ and pseudocereal‐fermented products are made of various kinds of substrates all over the world, mainly widespread in Asia and Africa. Fermentation may have multiple effects on the nutritional value of food [129].

The development of non‐dairy‐fermented products is a challenge to the food industry by producing high‐quality functional products. The main aims of cereal fermentation can be summarized as follows:


Cereal fermentations affected by characteristic variables include the following:


Fermented cereal‐based products are prepared in different parts of the world, mainly in developing countries—Asia and Africa, in combination with legumes to improve overall protein quality of the final fermented products [7]. Petruláková and Valík [133] evaluated the growth and metabolic activity of *Lb. rhamnosus* GG during fermentation of leguminous porridges. Cell density during 21‐day cold storage was stable except whole soybean, yellow pea and red bean. Metabolic activity of observed strain caused decrease in pH values to the final 5.6–6.0 and subsequently during cold storage decreased. Fermented products are usually prepared in the form of beverages, gruels or breakfast meals. Most of the fermented products are made in Asia (soy sauce), India (idli and dosa) and in the Middle East (kishk). In America, as a basic raw material for the production of cereal‐fermented foods, corn is used, in products such as tesgüino (alcoholic beverage of Mexico) or jamin‐bang‐bread made in Brazil [134]. An overview of traditional fermented food and beverages is summarized in **Table 4**.


**Table 4.** Overview of traditional fermented products and beverages [7, 135].

*4.2.2. Fermented cereal and pseudocereal food and beverages*

multiple effects on the nutritional value of food [129].

be added as a starter culture [9].

summarized as follows:

[130];

236 Fermentation Processes

**•** water content;

ides [9, 132].

Fermented food and beverages are defined as those products that have been subjected to the effect of microbial enzymes, particularly amylases, proteases and lipases that causes biochem‐ ical transformation of polysaccharides, proteins and lipids to non‐toxic variety of desirable products with tastes, aromas and textures attractive to a consumer [4, 7]. Microorganisms responsible for the fermentation process may be presented naturally in the substrate, or may

Traditional cereal‐ and pseudocereal‐fermented products are made of various kinds of substrates all over the world, mainly widespread in Asia and Africa. Fermentation may have

The development of non‐dairy‐fermented products is a challenge to the food industry by producing high‐quality functional products. The main aims of cereal fermentation can be

**•** preservation, which relies mainly on acidification (production of lactic, acetic and propionic acid) and/or alcoholic production often in combination with reduction of water activity

**•** improves the nutritional value by removing antinutritive compounds (phytic acid, enzyme inhibitors, tannins and polyphenols) and enhances the bioavailability of components;

**•** reduces the level of carbohydrates as well as non‐digestible poly‐ and oligosaccharides [9].

**•** the type of cereal determining the content of fermentable substrates, growth factors,

**•** sources of amylolytic activity to gain fermentable sugars from starch or other polysacchar‐

Fermented cereal‐based products are prepared in different parts of the world, mainly in developing countries—Asia and Africa, in combination with legumes to improve overall protein quality of the final fermented products [7]. Petruláková and Valík [133] evaluated the growth and metabolic activity of *Lb. rhamnosus* GG during fermentation of leguminous porridges. Cell density during 21‐day cold storage was stable except whole soybean, yellow pea and red bean. Metabolic activity of observed strain caused decrease in pH values to the final 5.6–6.0 and subsequently during cold storage decreased. Fermented products are usually

**•** enhances the safety of final products by the inhibition of pathogens [131];

Cereal fermentations affected by characteristic variables include the following:

**•** affecting sensory properties (taste, aroma, colour and texture);

nutrients, minerals, nitrogen sources and buffering capacity;

**•** additional components (sugars, salt and exposure to oxygen);

**•** duration and temperature of fermentation process;

**Figure 3.** Presumptive counts of the cocci from Fresco DVS 1010 culture and *Lb. rhamnosus* GG (LGG) content in milk‐ based (a) and water‐based (b) maize mashes.

As an example, the growth of Fresco DVS 1010 culture at 37 °C and the survival of probiotic strain *Lb. rhamnosus* GG (6 °C) in milk‐ and water‐based maize mashes with sucrose are demonstrated in **Figure 3** as well as the growth parameters in **Table 5**. In general, the obtained maximal counts of monitored Fresco DVS 1010 culture after 8 h of fermentation process were *N* = 108 –109 CFU ml‐1 from initial *N*0 = 106 –107 CFU ml‐1, which shows the suitability of tested sweet corn mashes for the growth and survival of lactic acid bacteria. During the refrigerated storage at 6°C (**Table 6**), a decline in the number of probiotic strain *Lb. rhamnosus* GG was observed, but not under the levels of 106  CFU ml‐1 necessary from the legislation point of view.


Gr*<sup>f</sup>* , growth rate; *λ*, lag‐phase duration; *k*pH, rate constant for the decrease of pH. The growth data were fitted using DMFit tool, kindly provided by Dr. J. Baranyi.

**Table 5.** Growth parameters of Fresco culture, 8‐h fermentation at 37°C in maize mashes.

In botanical terms, amaranth, quinoa and buckwheat are not true cereals. They are dicotyled‐ onous plants, and thus not cereals (monocotyledonous). Their seeds are in function and composition similar to true cereals, so they are referred as pseudocereals [136, 137]. Gluten‐ free pseudocereals increased attention worldwide, because they represent alternative to conventional gluten‐containing cereals and industrially are used for the production of gluten‐ free products, especially for celiac patients. They enrich the nutrition of health people and contribute to their balanced diet. In comparison to cereals, pseudocereals are characterized by the increased availability of proteins, as well as its higher content. Moreover, pseudocereals are the major source of minerals and vitamins, and in comparison to cereals, the content of essential amino acid lysine is higher [138–141].

Due to its chemical composition, amaranth is considered as one of the most nutritious plants that is easy to grow and over 60 species of amaranth are known worldwide [142]. Grains are characterized with balanced composition of essential amino acids, especially lysine and methionine, higher content of proteins (15–17%) and starch (60–65%) [143, 144]. Compared to other cereals, the fat content is higher, ranging from 7 to 8%. Overall, amaranth is a good source of vitamins (riboflavin, niacin and vitamin E) and minerals such as calcium and magnesium [138]. A growing number of studies have investigated the usage of amaranth in cereal technology not only in the production of nutrient‐rich gluten‐free products but also to enrich diet of health people [145]. Several studies have also reported the possibility to enrich wheat‐ based products with amaranth to improve the quality and overall nutritional value of final products [140]. Matejčeková et al. [146] confirmed in their study the growth of probiotic and potentially probiotic strains (*Lb. acidophilus* 145, *Lb. rhamnosus* GG, *Lb. rhamnosus* VT1 and *Lb. paracasei* subsp. *paracasei*) in water‐ and milk‐based amaranth mashes. The same authors [30] studied the growth and survival of probiotic strain *Lb. rhamnosus* GG in flavoured amaranth mashes, which were acceptable not only from the microbiological point of view but also from the sensory evaluation. Kocková and Valík [147] evaluated the suitability of selected cereals and pseudocereals for the development of new probiotic foods fermented by *Lb. rhamnosus* GG. The highest growth rate was calculated in the case of amaranth flour (0.589 log CFU g‐1 h‐1) and the longest lag phase was observed.

As an example, the growth of Fresco DVS 1010 culture at 37 °C and the survival of probiotic strain *Lb. rhamnosus* GG (6 °C) in milk‐ and water‐based maize mashes with sucrose are demonstrated in **Figure 3** as well as the growth parameters in **Table 5**. In general, the obtained maximal counts of monitored Fresco DVS 1010 culture after 8 h of fermentation process were

sweet corn mashes for the growth and survival of lactic acid bacteria. During the refrigerated storage at 6°C (**Table 6**), a decline in the number of probiotic strain *Lb. rhamnosus* GG was

CFU ml‐1, which shows the suitability of tested

 **(log CFU ml‐1 h‐1) λ (h)** *k***pH (h‐1)**

 CFU ml‐1 necessary from the legislation point of view.

–107

**Fresco DVS 1010** Milk 0.522 – ‐0.231

, growth rate; *λ*, lag‐phase duration; *k*pH, rate constant for the decrease of pH. The growth data were fitted using DMFit

In botanical terms, amaranth, quinoa and buckwheat are not true cereals. They are dicotyled‐ onous plants, and thus not cereals (monocotyledonous). Their seeds are in function and composition similar to true cereals, so they are referred as pseudocereals [136, 137]. Gluten‐ free pseudocereals increased attention worldwide, because they represent alternative to conventional gluten‐containing cereals and industrially are used for the production of gluten‐ free products, especially for celiac patients. They enrich the nutrition of health people and contribute to their balanced diet. In comparison to cereals, pseudocereals are characterized by the increased availability of proteins, as well as its higher content. Moreover, pseudocereals are the major source of minerals and vitamins, and in comparison to cereals, the content of

Due to its chemical composition, amaranth is considered as one of the most nutritious plants that is easy to grow and over 60 species of amaranth are known worldwide [142]. Grains are characterized with balanced composition of essential amino acids, especially lysine and methionine, higher content of proteins (15–17%) and starch (60–65%) [143, 144]. Compared to other cereals, the fat content is higher, ranging from 7 to 8%. Overall, amaranth is a good source of vitamins (riboflavin, niacin and vitamin E) and minerals such as calcium and magnesium [138]. A growing number of studies have investigated the usage of amaranth in cereal technology not only in the production of nutrient‐rich gluten‐free products but also to enrich diet of health people [145]. Several studies have also reported the possibility to enrich wheat‐ based products with amaranth to improve the quality and overall nutritional value of final

**Table 5.** Growth parameters of Fresco culture, 8‐h fermentation at 37°C in maize mashes.

Milk + caramel 0.446 – ‐0.345 Milk + chocolate 0.563 – ‐0.172 Water 0.445 – ‐0.481 Water + caramel 0.508 0.59 ‐0.298 Water + chocolate 0.540 – ‐0.462

*N* = 108

Gr*<sup>f</sup>*

–109

238 Fermentation Processes

CFU ml‐1 from initial *N*0 = 106

**Microorganism Substrate corn flour Gr***<sup>f</sup>*

observed, but not under the levels of 106

tool, kindly provided by Dr. J. Baranyi.

essential amino acid lysine is higher [138–141].


*kd*, rate constant for decrease of the *Lb. rhamnosus* counts; *N*0, initial counts; *N*end, final counts after 14 days of storage period. The growth data were fitted using DMFit tool kindly provided by Dr. J. Baranyi.

**Table 6.** Parameters evaluating the behaviour of *Lb. rhamnosus* GG in fermented maize mashes during storage at 6°C when added after fermentation.


Gr*<sup>f</sup>* , growth rate; *λ*, lag‐phase duration; *N*0, initial counts; *N*max, counts after storage period. The growth data were fitted using DMFit tool kindly provided by Dr. J. Baranyi.

**Table 7.** Growth parameters of *Lb. rhamnosus* GG in fermented buckwheat‐flavoured mashes during fermentation at 37°C.

Together with amaranth, buckwheat and its products are studied in connection with celiac disease. Buckwheat was initially grown mainly in Asia and later has spread to Europe, Australia as well as to USA and Canada. The total carbohydrate content is 67–70%, of which 55% represents starch stored in the endosperm, as in common cereals. Buckwheat has a good content of thiamine, riboflavin and pyridoxine, and also represents a good source of minerals —magnesium, copper and potassium. It is characterized by a unique concentration of phyto‐ chemicals, in particular rutin, which has a positive effect on health especially in the prevention of cardiovascular diseases [148, 149]. Pelikánová et al. [109] evaluated the growth dynamics of *Lactobacillus* spp. in sweet buckwheat gruels. The population density of tested lactobacilli reached counts 108 –109 CFU ml‐1 after 8 (10) h of fermentation, and after a 3‐week‐refrigerated storage period, the number of lactobacilli slightly increased except *Lb. acidophilus* 145. Liptá‐ ková et al. [87] in their study examined the pressed buckwheat products. The most suitable strain for fermentation was *Lb. rhamnosus* GG. Pressed fermented buckwheat water product with vanilla flavour was after 24 h of fermentation and after 5 days of storage evaluated with higher points according to the final evaluation of overall sensory acceptance.


*kd*, rate constant for decrease of the *Lb. rhamnosus* counts; *λ*, lag‐phase duration; *N*end, final counts after 21 days of storage period. The growth data were fitted using DMFit tool kindly provided by Dr. J. Baranyi.

**Table 8.** Parameters of *Lb. rhamnosus* GG in fermented buckwheat‐flavoured mashes during storage at 6°C.

As for the example, growth and fermentative metabolism of probiotic strain *Lb. rhamnosus* GG in buckwheat mashes with caramel/vanilla/chocolate flavour is summarized in **Tables 7** and **8**. Investigated probiotic strain showed sufficient growth and survival in prepared flavoured mashes with the growth rates ranging from 0.251 to 0.641 log CFU ml‐1 h‐1. At the end of cold storage, densities of *Lb. rhamnosus* GG maintained above the minimum limit of 106  CFU ml‐1.

The interest of consumers in fermented cereal‐ or pseudocereal‐based products is growing. The development of non‐dairy‐fermented products including probiotics may lead to enrich‐ ment of the diet in patients suffering from celiac disease, people with allergies, or intolerances, but it may contribute to the balanced diet of healthy subjects [149]. If the cereal or pseudocereal products are presented with an attractive sensory taste, it may represent a suitable option for the development of new probiotic foods. Thus, in our study we evaluate the overall sensory acceptability of maize‐flavoured (chocolate/caramel) mashes (**Figures 4** and **5**). The overall acceptability was evaluated from 2.80 to 3.30 (four‐point scale) that indicated pleasant acceptance except caramel water mash (2.56). Kocková and Valík [135] noted negative effect of a 21‐day storage period on overall acceptability buckwheat product with salt fermented by probiotic strain *Lb. rhamnosus* GG from values 3.31 to 2.44. In our study, no decline of overall acceptance during storage period was observed.

Lactic Acid Bacteria and Fermentation of Cereals and Pseudocereals http://dx.doi.org/10.5772/65459 241

**Figure 4.** Evaluation of overall acceptability maize caramel/chocolate mashes (LGG—*Lactobacillus rhamnosus* GG).

**Figure 5.** Photo‐documentation of flavoured final maize products.

#### **5. Conclusion**

55% represents starch stored in the endosperm, as in common cereals. Buckwheat has a good content of thiamine, riboflavin and pyridoxine, and also represents a good source of minerals —magnesium, copper and potassium. It is characterized by a unique concentration of phyto‐ chemicals, in particular rutin, which has a positive effect on health especially in the prevention of cardiovascular diseases [148, 149]. Pelikánová et al. [109] evaluated the growth dynamics of *Lactobacillus* spp. in sweet buckwheat gruels. The population density of tested lactobacilli

storage period, the number of lactobacilli slightly increased except *Lb. acidophilus* 145. Liptá‐ ková et al. [87] in their study examined the pressed buckwheat products. The most suitable strain for fermentation was *Lb. rhamnosus* GG. Pressed fermented buckwheat water product with vanilla flavour was after 24 h of fermentation and after 5 days of storage evaluated with

*kd*, rate constant for decrease of the *Lb. rhamnosus* counts; *λ*, lag‐phase duration; *N*end, final counts after 21 days of storage

As for the example, growth and fermentative metabolism of probiotic strain *Lb. rhamnosus* GG in buckwheat mashes with caramel/vanilla/chocolate flavour is summarized in **Tables 7** and **8**. Investigated probiotic strain showed sufficient growth and survival in prepared flavoured mashes with the growth rates ranging from 0.251 to 0.641 log CFU ml‐1 h‐1. At the end of cold

The interest of consumers in fermented cereal‐ or pseudocereal‐based products is growing. The development of non‐dairy‐fermented products including probiotics may lead to enrich‐ ment of the diet in patients suffering from celiac disease, people with allergies, or intolerances, but it may contribute to the balanced diet of healthy subjects [149]. If the cereal or pseudocereal products are presented with an attractive sensory taste, it may represent a suitable option for the development of new probiotic foods. Thus, in our study we evaluate the overall sensory acceptability of maize‐flavoured (chocolate/caramel) mashes (**Figures 4** and **5**). The overall acceptability was evaluated from 2.80 to 3.30 (four‐point scale) that indicated pleasant acceptance except caramel water mash (2.56). Kocková and Valík [135] noted negative effect of a 21‐day storage period on overall acceptability buckwheat product with salt fermented by probiotic strain *Lb. rhamnosus* GG from values 3.31 to 2.44. In our study, no decline of overall

 CFU ml‐1.

higher points according to the final evaluation of overall sensory acceptance.

Milk + vanilla 0.0006 – 8.54 Milk + caramel ‐0.0002 – 8.42 Milk + chocolate 0.0009 – 8.89 Water + vanilla 0.0000 – 8.38 Water + caramel ‐0.0002 – 8.41 Water + chocolate 0.0000 – 8.49

period. The growth data were fitted using DMFit tool kindly provided by Dr. J. Baranyi.

acceptance during storage period was observed.

**Substrate buckwheat flour** *kd* **(log CFU ml‐1 h‐1)** *λ* **(h)** *N***end (log CFU ml‐1)**

**Table 8.** Parameters of *Lb. rhamnosus* GG in fermented buckwheat‐flavoured mashes during storage at 6°C.

storage, densities of *Lb. rhamnosus* GG maintained above the minimum limit of 106

–109 CFU ml‐1 after 8 (10) h of fermentation, and after a 3‐week‐refrigerated

reached counts 108

240 Fermentation Processes

Sustainable diets and cultured consumer interests, for example, in personal health, represent the main driving forces for the development of new functional foods in the world. Throughout the world, many fermented foods that are produced cover a wide range of substances and microorganisms. Ensuring high quality and safety for such a product requires deep under‐ standing of fermentation process, types and roles of microorganisms used and specific final product characteristics. Lactic acid bacteria are the alternatives of food biopreservation primarily due to the production of weak organic acids and other inhibitory substances in combination with lowering pH and reduction of redox potential. LAB and their metabolites are able to slow or inhibit the growth of undesirable bacteria, yeasts and toxigenic fungi in food. There is evidence that LAB are also able to reduce the gluten content of cereals that represents increasing problem for 0.5–1% of population worldwide. Many lactic acid bacteria and other microbial strains such as *E. coli* Nissle, *B. cereus*, *B. subtilis* or *S. boulardii* belong to the probiotics with documented positive effects on human health.

The development of fermented cereal‐ or pseudocereal‐based products supplemented with probiotics represents an available alternative to milk products and may lead to enrichment of the diet of people suffering from celiac disease, allergy to milk proteins, lactose intolerance people or otherwise metabolically handicapped consumers, but it may also contribute to a balanced diet of healthy subjects.

#### **Acknowledgements**

The authors would like to thank for the financial contribution from the STU Grant scheme for Support of Young Researchers no. 1617/16.

#### **Author details**

Denisa Liptáková, Zuzana Matejčeková and Ľubomír Valík\*

\*Address all correspondence to: lubomir.valik@stuba.sk

Department of Nutrition and Food Quality Assessment, Faculty of Chemical and Food Technology, Slovak University of Technology in Bratislava, Bratislava, Slovakia

#### **References**


[3] Prajapati JB, Nair BM. The history of fermented foods. In: Farnworth ER, editor. Handbook of Fermented Functional Foods. 2nd ed. London: CRC Press; 2008. p. 1–24.

standing of fermentation process, types and roles of microorganisms used and specific final product characteristics. Lactic acid bacteria are the alternatives of food biopreservation primarily due to the production of weak organic acids and other inhibitory substances in combination with lowering pH and reduction of redox potential. LAB and their metabolites are able to slow or inhibit the growth of undesirable bacteria, yeasts and toxigenic fungi in food. There is evidence that LAB are also able to reduce the gluten content of cereals that represents increasing problem for 0.5–1% of population worldwide. Many lactic acid bacteria and other microbial strains such as *E. coli* Nissle, *B. cereus*, *B. subtilis* or *S. boulardii* belong to

The development of fermented cereal‐ or pseudocereal‐based products supplemented with probiotics represents an available alternative to milk products and may lead to enrichment of the diet of people suffering from celiac disease, allergy to milk proteins, lactose intolerance people or otherwise metabolically handicapped consumers, but it may also contribute to a

The authors would like to thank for the financial contribution from the STU Grant scheme for

Department of Nutrition and Food Quality Assessment, Faculty of Chemical and Food

[1] Todorov SD, Holzapfel WH. Traditional cereal fermented foods as sources of functional microorganism. In: Holzapfel WH, editor. Advances in Fermented Foods and Bever‐ ages. 1st ed. Cambridge: Woodhead Publishing Ltd; 2014. p. 123–153. DOI: 10.1016/

[2] Rivera‐Espinoza Y, Gallardo‐Navaro Y. Non‐dairy probiotic products. Food Microbi‐

Technology, Slovak University of Technology in Bratislava, Bratislava, Slovakia

the probiotics with documented positive effects on human health.

balanced diet of healthy subjects.

Support of Young Researchers no. 1617/16.

B978‐1‐78242‐015‐6.00006‐2

Denisa Liptáková, Zuzana Matejčeková and Ľubomír Valík\*

ology. 2010;27:1–11. DOI:10.1016/j.fm.2008.06.008

\*Address all correspondence to: lubomir.valik@stuba.sk

**Acknowledgements**

242 Fermentation Processes

**Author details**

**References**


[29] Ward LJH, Davey GP, Heap HA, Kelly WJ. *Lactococcus lactis*. In: Roginski H, Fuquay JW, Fox PF, editors. Encyclopedia of Dairy Sciences. 1st ed. Oxford: Academic Press; 2003. p. 1511–1516.

[17] Barrangou R, Lahtinen SJ, Ibrahim F, Ouwehand AC. Genus *Lactobacillus*. In: Lahtinen SJ, Ouwehand AC, Salminen S, von Wright A, editors. Lactic Acid Bacteria. Microbiological and Functional Aspects. 4th ed. Boca Raton: CRC Press;

[18] Albesharat R, Ehrmann MA, Korakli M, Yazaji S, Vogel RF. Phenotypic and genotypic analyses of lactic acid bacteria in local fermented food, breast milk and faeces of mothers and their babies. Systematic and Applied Microbiology.

[19] Solís G, De Los Reyes‐Gavilan CG, Fernández N, Margolles A, Gueimonde M. Estab‐ lishment and development of lactic acid bacteria and bifidobacteria microbiota in breast‐milk and the infant gut. Anaerobe. 2010;16:307–310. DOI: 101016/ j.anaerobe.

[20] Mitsou EK, Kirtzalidou E, Oikonomou I, Liosis G, Kyriacou A. Fecal microflora of Greek healthy neonates. Anaerobe. 2008;14:94–101. DOI: 101016/ j.anaerobe.

[21] Liptáková D, Hornická M, Valík Ľ. Powdered infant formulas fortified with

[22] Fernández L, Langa S, Martín V, Maldonado A, Jiménez E, Martín R, Rodríguez JM. The human milk microbiota: origin and potential roles in health and disease. Pharmacological Research. 2013;69:1–10. DOI: 10.1016/j.phrs.2012.09.001

[23] Martín R, Langa S, Reviriego C, Jiménez E, Marín MA, Olivares M, Boza J, Jiménez J, Fernández L, Xaus J, Rodríguez JM. The commensal microflora of human milk: new perspectives for food bacteriotherapy and probiotics. Trends in Food Science and Technology. 2004;15:121–127. DOI: 101016/ j.tifs.2003.09.010

[24] Martín S, Maldonado‐Baragán A, Moles L, Rodriguez‐Ba'noz M, del Campo R, Fernández L, Rodríguez JM, Jiménez E. Sharing of bacterial strains between breast milk and infant faeces. Journal of Human Lactation. 2012;28:36–44. DOI:

[25] Jost T, Lacroix C, Braegger CP, Rochat F, Chassard C. Vertical mother–neonate transfer of maternal gut microflora. Environmental Microbiology. 2014;16:2891–2904. DOI:

[26] Liptáková D, Koreňová J, Hornická M, Valík Ľ. Microbiological analysis of breast milk.

[27] Görner F, Valík Ľ. Applied food microbiology. 1st ed. Bratislava: Malé Centrum; 2004.

[28] Tamine AY, Robinson's RK. Yoghurt. 3rd ed. Cambridge: Woodhead Publishing in Food

2011;34:148–155. DOI: 101016/ j.syapm.2010.12.001

probiotics. Farmaceutický obzor. 2015; 84:241–245.

2012. p. 77–92.

244 Fermentation Processes

2010.02.004

2007.11.002

10.1177/08903344I I 424729

10.1111/1462‐2920.12238

528 p.

Lekársky obzor. 2016; 65:227–232.

Science, Technology and Nutrition; 2007. 791 p.


producing *Lactobacillus suebicus* and *Pediococcus parvulus* strains with potential utility in the production of functional foods. Bioresource Technology. 2010;101:9254–9263. DOI: 10.1016/j.biortech.2010.07.050


*lactis* GCL2505 on defecation frequency and bifidobacterial microbiota composition in humans. Journal of Bioscience and Bioengineering. 2012;113:587–591. DOI: 10.1016/j.jbiosc.2011.12.016

[53] Picard C, Fioramonti J, Francois A, Robinson T, Neant F, Matuchansky C. Review article: bifidobacteria as probiotic agents – physiological effects and clinical benefits. Alimentary Pharmacology and Therapeutics. 2005;22:495–512. DOI: 0.1111/j.1365‐2036.2005.02615.x

producing *Lactobacillus suebicus* and *Pediococcus parvulus* strains with potential utility in the production of functional foods. Bioresource Technology. 2010;101:9254–9263.

[41] Papagianni M, Anastasiadou S. Encapsulation of *Pediococcus acidilactici* cells in corn and olive oil microcapsules emulsified by peptides and stabilized with xanthan in oil‐in‐ water emulsions: Studies on cell viability under gastro‐intestinal simulating conditions. Enzyme and Microbial Technology. 2009;45:514–522. DOI: 10.1016/j.enzmictec.

[43] Schleifer KH, Killper‐Bälz R. Transfer of *Streptococcus faecalis* and *Streptococcus faecium* to the genus *Enterococcus* nom. rev. as *Enterococcus faecalis* com. nov. and *Enterococcus faecium* comb. nov. International Journal of Systematic Bacteriology. 1984;34:31–34. [44] Bentley RW, Leigh JA, Collins MD. Intrageneric structure of *Streptococcus* based on comparative analysis of small subunit rRNA sequences. International Journal of

[45] Facklam R. What happened to the *Streptococci*: overview of taxonomic and nomencla‐ ture changes. Clinical Microbiology Reviews. 2002;15:613–630. DOI: 10.1128/CMR.

[46] Köhler W. The present state of species within the genera *Streptococcus* and *Enterococ‐ cus*. International Journal of Medical Microbiology. 2007;297:133–150. DOI: 10.1016/

[47] Rossi F, Marzotto M, Cremonese S, Rizzotti L, Torriani S. Diversity of *Streptococcus thermophilus* in bacteriocin production; inhibitory spectrum and occurrence of thermo‐

[48] Tagg JR, Wescombe PA, Burton JP. *Streptococcus*: a brief update on the current taxonomic status of the genus. In: Lahtinen SJ, Ouwehand AC, Salminen S, Von Wright A, editors. Lactic Acid Bacteria. Microbiological and Functional Aspects. 4th ed. Boca Raton: CRC

[49] Kabuki T, Uenishi H, Seto Y, Yoshioka T, Nakajima H. A unique lantibiotic, thermo‐ philin 1277, containing a disulfide bridge and two thioether bridges. Journal of Applied

[50] Erkus O, Okuklu B, Yenidunya AF, Harsa S. High genetic and phenotypic variability of *Streptococcus thermophilus* strains isolated from artisanal Yuruk yoghurts. LWT – Food

[51] Biavati B, Vescovo M, Torriani S, Bottazzi V. *Bifidobacteria*: history, ecology, physiology

[52] Ishizuka A, Tomizuka KI, Aoki R, Nishijima T, Saito Y, Inoue R, Ushida K, Mawatari T, Ikeda T. Effects of administration of *Bifidobacterium animalis* subsp.

Microbiology. 2009;106:853–862. DOI: 10.1111/j.1365‐2672.2008.04059.x

Science and Technology. 2014;58:348–354. DOI: 10.1016/j.lwt.2013.03.007

and applications. Annals of Microbiology. 2000;59:117–131.

philin genes. Food Microbiology. 2013;35:27–33. DOI: 10.1016/j.fm.2013.02.006

[42] Sherman JM. The *Streptococci*. Bacteriological Reviews. 1937;1:3–97.

DOI: 10.1016/j.biortech.2010.07.050

Systematic Bacteriology. 1991;41:487–494.

2009.06.007

246 Fermentation Processes

15.4.613‐630.2002

j.ijmm.2006.11.008

Press; 2012. p. 23–146.


[76] Gurira OZ, Buys EM. Characterization and antimicrobial activity of *Pediococcus* species isolated from South African farm – style cheese. Food Microbiology. 2005;22:159–168. DOI: 10.1016/j.fm.2004.08.001

[64] Liptáková D, Hudecová A, Valík L, Medvedová A. Interaction between dairy yeasts and *Lactobacillus rhamnosus* GG in milk. Journal of Agricultural Science and Technology.

[65] Greifová M, Marunová E, Greif G, Zimanová M. Antifugálna aktivita kyseliny D,L‐

[66] Liptáková D, Valík L, Lauková A, Strompfová V. Characterization of *Lactobacillus rhamnosus* VT1 and its effect on the growth of *Candida maltosa* YP1. Czech Journal of

[67] Plocková M, Stiles J, Chumchalová J, Halfarová R. Control of mould growth by *Lactobacillus rhamnosus* VT1 and *Lactobacillus reuteri* CCM 3625 on milk agar plates.

[68] Schnürer J, Magnusson J. Antifungal lactic acid bacteria as biopreservatives. Trends in Food Science and Technology. 2005;16:70–78. DOI: 10.1016/j.tifs.2004.02.014

[69] Fitzsimmons N, Berry DR. Inhibition of *Candida albicans* by *Lactobacillus acidophilus*: evidence for the involvement of a peroxidase system. Microbios. 1994;80:125–133.

[70] Lozo J, Vukasinovic M, Strahinic I, Topisirovic L. Characterization and antimicrobial activity of bacteriocin 217 produced by natural isolate *Lactobacillus paracasei* subsp.

[71] Güven K, Benlikaya N. Acid pH produced by lactic acid bacteria prevent the growth of *Bacillus cereus* in boza, a traditional fermented Turkish beverage. Journal of Food

[72] Valdés‐Stauber N, Scherer S. Isolation and characterization of linocin M18, a bacteriocin produced by *Brevibacterium linens*. Applied and Environmental Microbiology.

[73] Corsetti A, Settanni L, Van Sinderen D. Characterization of bacteriocin‐like inhibitory substances (BLIS) from sourdough lactic acid bacteria and evaluation of their in vitro and in situ activity. Journal of Applied Microbiology. 2004;96:521–534. DOI: 10.1111/j.

[74] Björkroth KJ, Geisen R, Schillinger U, Weiss N, de Vos P, Holzapfel WH, Korkeala HJ, Vandamme P. Characterization of *Leuconostoc gasicomitatum* sp. nov., associated with spoiled raw tomato‐marinated broiler meat strips packaged under modified atmos‐ phere conditions. Applied and Environmental Microbiology. 2000;66:3764–3772.

[75] Nieto‐Lozano JC, Reguera‐Useros JI, del Peláez‐Martínez M, Sacristián‐Pérez‐Minayo G, Gutíerrez‐Fernández AJ, de la Torre AH. The effect of the pediocin PA – 1 pro‐ duced by *Pediococcus acidilactici* against *Listeria monocytogenes* and *Clostridium perfrin‐ gens* in Spanish dry – fermented sausages and frankfurters. Food Control. 2010;21:679–

*paracasei* BGBUK2‐16. Journal of Food Protection. 2004;67:2727–2734.

Safety. 2005;25:98–108. DOI: 10.1111/j.1745‐4565.2005.00568.x

fenylmliečnej. Mlékařské Listy. 2014;142:6–10.

Czech Journal of Food Sciences. 2001;19:46–50.

Food Sciences. 2007;25:272–282.

1994;60:3809–3814.

1365‐2672.2004.02171.x

685. DOI: 10.1016/j.foodcont.2009.10.007

2010;4:88–95.

248 Fermentation Processes


[102] Cenci G, Rossi J, Throtta F, Caldini G. Lactic acid bacteria isolated from dairy products inhibit genotoxic effect of 4 – nitroquinoline – 1 – oxide in SOS – chromtest. Systematic and Applied Microbiology. 2002;25:483–490.

[89] Mortazavian AM, Razavi SH, Ehsani MR, Sohrabvandi S. Principles and methods of microencapsulation of probiotic microorganisms. Iranian Journal of Biotechnology.

[90] Liptáková D, Valík L, Janovčíková L. *Lactobacillus acidophilus* we can be in daily contact

[91] Valík L, Liptáková D, Medvedová A. Content of probiotic bacteria *L. acidophilus* in fermented milk determined at the end of the recommended "use by date". Farmaceut‐

[92] Commane D, Hughes R, Shortt C, Rowland I. The potential mechanisms involved in the anti – carcinogenic action of probiotics. Mutation Research. 2005;591:276–289. DOI:

[93] Isolauri E, Salminen S, Ouwehand AC. Probiotics. Best Practise and Research Clinical

[94] Liptáková D, Valík L, Görner F. Nutrition and health benefits of yoghurts. Farmaceut‐

[95] Saavedra JM, Bauman NA, Oung I, Perman JA, Yolken RH. Feeding of *Bifidobacterium bifidum* and *Streptococcus thermophilus* to infants in hospital for prevention of diarrhoea

[96] Guandalini S, Pensabene L, Zikri MA, Dias JA, Casali LG. Hoekstra. *Lactobacillus rhamnosus* GG administered in oral rehydration solution to children with acute diarrhea: a multicenter European trial. Journal of Pediatric Gastroenterology and

[97] Zajewska H, Skórka A, Ruszcynski M, Gieruszczak‐Biatek D. Metaanalysis: *Lactobacil‐ lus* GG for treating acute diarrhoea in children. Alimentary and Pharmacology

[98] Gismondo MR, Drago L, Lombardi A. Review of probiotics available to modify gastrointestinal flora. International Journal of Antimicrobial Agents. 1999;12:287–292.

[99] Elmer GW, McFarland LV, Surawicz CM, Danko L, Greenberg RN. Behaviour of *Saccharomyces boulardii* in recurrent *Clostridium difficile* disease patients. Alimentary Pharmacology and Therapeutics. 1999;13:1663–1668. DOI: 10.1046/j.1365‐

[100] Surawicz CM, McFarland LV, Greenberg RN, Rubin M, Fekety R, Mulligan ME, Garcia RJ, Brandmarker S, Bowen K, Borjal D, Elmer GW. The search for a better treatment for recurrent *Clostridium difficile* disease: use of high‐dose vancomycin combined with

[101] Czerucka D, Rampal P. Experimental effects of *Saccharomyces boulardii* on diarrheal

*Saccharomyces boulardii*. Clinical Infectious Diseases. 2000;31:1012–1017.

Gastroenterology. 2004;18:299–313. DOI: 10.1053/ybega.2004.443

and shedding of rotavirus. Lancet. 1994;344:1046–1049.

Therapeutics. 2007;25:871–881. DOI: 10.1111/apt.12403

pathogens. Microbes and Infection. 2002;4:733–739.

with it. Farmaceutický Obzor. 2008b;77:217–221.

2007;5:1–18.

250 Fermentation Processes

ický Obzor. 2012;79:49–53.

10.1016/j.mrfmmm.2005.02.02

ický Obzor. 2006;75:159–162.

Nutrition. 2000;30:214–216.

2036.1999.00666.x


[131] Adams M, Mitchell R. Fermentation and pathogen control: a risk assessment approach. International Journal of Food Microbiology. 2002;79:75–83. DOI: 10.1016/ S0168‐1605(02)00181‐2

[117] Lambo AM, Öste R, Nyman MEGL. Dietary fibre in fermented oat and barley β‐glucan rich concentrates. Food Chemistry. 2005;89:283–293. DOI: 10.1016/j.foodchem.

[118] Shewry PR. Improving the protein content and composition of cereal grain. Journal of

[119] Kadlec P, Melzoch K, Voldřich M. Přehled Tradičních Potravinářských Výrob‐ Techno‐

[120] Gänzle MG. Enzymatic and bacterial conversion during sourdough fermentation. Food

[121] Antony U, Sripriya G, Chandra TS. The effect of fermentation on the primary nutrients in foxtail millet (*Seteria italica*). Food Chemistry. 1996;56:381–384. DOI: 10.1016/0308‐

[122] Cui L, Li D, Liu C. Effect of fermentation on the nutritive value of maize. International Journal of Food Science and Technology. 2012;47:755–760. DOI: 10.1111/j.1365‐

[123] Koehler P, Wieser H. Chemistry of cereal grains. In: Gobbetti M, Gänzle M, editors. Handbook on Sourdough Biotechnology. New York, NY: Springer Science; 2013. p. 11–

[124] Volkov A, Liavonchanka A, Kamneva O, Fiedler T, Goebel C, Kreikemeyer B, Feussner I. Myosin cross‐reactive antigen of *Streptococcus pyogenes* M49 encodes a fatty acid double bond hydratase that plays a role in oleic acid detoxification and bacterial virulence. Journal of Biological Chemistry. 2010;285:10353–10361. DOI: 10.1074/

[125] Belitz HD, Grosch W, Schieberle P. Food Chemistry. 4th ed. Berlin: Springer; 2004. 1070

[126] Poutanen K, Flander L, Katina K. Sourdough and cereal fermentation in a nutritional perspective. Food Microbiology. 2009;26:693–699. DOI: 10.1016/j.fm.2009.07.011

[127] Němečková I, Dragounová H, Pechačová M, Rysová J, Roubal P. Fermentation of vegetable substrates by lactic acid bacteria as a basis of functional foods. Czech Journal

[129] Kohajdová Z, Karovičová J. Fermentation of cereals for specific purpose. Journal of

[130] Ross RP, Morgan S, Hill C. Preservation and fermentation: past, present and future. International Journal of Food Microbiology. 2002;79:3–16. DOI: 10.1016/S0168‐

[128] Keresteš J. et al. Zdravie a Výživa Ludí. Bratislava: CAD Press; 2011. 1040 p.

Cereal Science. 2007;46:239–250. DOI: 10.1016/j.jcs.2007.06.006

logie Potravin. 1st ed. Ostrava: Key Publishing; 2012. 569 p.

Microbiology. 2014;37:2–10. DOI: 10.1016/j.fm.2013.04.007

2004.02.035

252 Fermentation Processes

8146(95)00186‐7

2621.2011.02904.x

jbc.M109.081851

1605(02)00174‐5

p.

45. DOI: 10.1007/978‐1‐4614‐5425‐0

of Food Sciences. 2011;29:42–48.

Food and Nutrition Research. 2007;46:51–57.


#### **Solid-State Culture for Lignocellulases Production Solid-State Culture for Lignocellulases Production**

Ulises Durán Hinojosa, Leticia Soto Vázquez, Isabel de la Luz Membrillo Venegas, Mayola García Rivero, Gabriela Zafra Jiménez, Sergio Esteban Vigueras Carmona and María Aurora Martínez Trujillo Ulises Durán Hinojosa##, Leticia Soto Vázquez##, Isabel de la Luz Membrillo Venegas, Mayola García Rivero, Gabriela Zafra Jiménez, Sergio Esteban Vigueras Carmona and María Aurora Martínez Trujillo

Additional information is available at the end of the chapter Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/64237

#### **Abstract**

[143] Amicarelli V, Camaggio G. *Amaranthus*: A crop to rediscover. Forum Ware Internation‐

[144] Bhat A, Satpathy G, Gupta KR. Evaluation of nutraceutical properties of *Amaranthus hypochondriacus L*. grains and formulation of value added cookies. Journal of Pharma‐

[145] Mlakar GS, Turinek M, Jakop M, Bavec M, Bavec F. Grain amarant as an alternative and perspective crop in temperate climate. Journal for Geography. 2010;5‐1:135–145. [146] Matejčeková Z, Liptáková D, Valík Ľ. Evaluation of the potential of amaranth flour for lactic acid fermentation. Journal of Pharmacy and Nutrition Sciences. 2016;6:1–6. DOI:

[147] Kocková M, Valík Ľ. Suitability of cereal porridges as substrate for probiotic strain *Lactobacillus rhamnosus* GG. Potravinárstvo. 2013;7:22–27. DOI: 10.5219/242

[148] Jubete‐Alvarez L, Arendt EK, Gallagher E. Nutritive value of pseudocereals and their increasing use as functional gluten‐free ingredients. Trends in Food Science and

[149] Kreft I, Fabjan N, Germ M. Rutin in buckwheat – protection of plants and its importance

Technology. 2010;2:106–113. DOI: 10.1016/j.tifs.2009.10.014

for the production of functional food. Fagopyrum. 2003;20:7–11.

al. 2012;2:4–11.

254 Fermentation Processes

cognosy and Phytochemistry. 2015;3:51–54.

10.6000/1927‐5951.2016.06.01.1

*Aspergillus* sp. and *Trametes versicolor* solid-state monocultures produced high titers of xylanases and laccases activities (4617 ± 38 and 2759 ± 30 U/gsubstrate, respectively). Fungal biomass was quantified by estimating the ergosterol content of the mycelium, and by a simple material balance the corresponding residual substrate was obtained. Fungal growth and substrate consumption rates showed different behavior for these monocultures (μ = 0.03 and 0.11 h−1; *rs* = − 0.04 and − 0.0006 gsubstrate/h, respectively). In this case, xylanases production was directly linked to the growth, while laccases were produced during both growth and maintenance phases. Besides xylanases (42% of total *Aspergillus* enzyme), high titers of cellulases (15%), amylases (34%), and invertases (9%), as well as lignin and manganese peroxidases (10 and 24% of the total *Trametes* enzyme), were produced on the corresponding monocultures. When both fungi were used in a coculture mode, xylanases and laccases production decreased (around 85 and 70%), and the proportion of the hydrolases and oxidases changed. This suggested the need for most careful coculture design, in order to produce both enzymatic activities simultaneously even though the enzymatic extracts obtained by mono- or cocultures can be applied in several bioprocesses.

**Keywords:** *Aspergillus*, coculture, laccases, *Trametes versicolor*, xylanases

#### **1. Introduction**

Laccases and xylanases are two of the most important lignocellulases that are employed in several industrial processes. Xylanases (EC 3.2.1.8) are responsible for degrading the xylan, a

© 2017 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2017 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

major polysaccharide in several cereals cell wall, to its constituent monomers. These enzymes are mostly used in textile, pulp and paper, bread making and feed industries, and the production of juice and fruit extracts [1, 2]. Moreover, laccases (EC 1.10.3.2) are multicopper enzymes that catalyze the oxidation of a wide variety of substrates such as mono-, di- and polyphenols, aminophenols, methoxyphenols, aromatic amines, and ascorbic acid. They have several industrial uses: they degrade toxic fungal metabolites and phenolic compounds and also are used in the design of biosensors, the detection of phenols in wastewaters, in the development of biofuel cells, during bleaching and delignification processes in the pulp and paper industry, and for the production of novel paper products [3]. Together, xylanases and laccases can act for boosting bleaching process of several kinds of pulps, generating a cleaner process in which the use of the hazardous chemicals may be considerably reduced [4, 5]. These enzymes can be produced mainly by fungus, either in submerged or in solid-state cultures. The former is the most widely used as it provides a good control of operational parameters, high productivity and easy downstream processing, homogeneity of the culture and pH, and better oxygen supply and agitation speed management [6]. However, solid-state culture could be better for producing this kind of enzymes as it represents the conditions that fungus finds in nature during the invasion of lignocellulosic material. Regarding this, our research group has advanced in optimizing the components of culture media in order to obtain the highest xylanases and laccases activities and yields by *Aspergillus* sp and *Trametes versicolor*, respectively [7]. Both enzymatic activities have been evaluated for pulp pretreatment, achieving good results [8, 9]. However, the behavior of the corresponding optimized cultures has not been analyzed properly although this information can be used for developing a scalable bioprocess.

On the other hand, the joint use of fungi which produce xylanase or laccase for developing a coculture system may be considered in order to obtain a mixed enzyme preparation, which has both xylanase and laccase activities, for being applied in biopulping and biobleaching processes. This kind of procedure will provide economic advantages because of the reduction in the overall cost of production [10].

Therefore, the objective of this work is to characterize solid-state monocultures with respect to growth, substrate consumption, and xylanases or laccases production and to test a coculture for producing both enzymes at the same solid-state fermentation.

#### **2. Methodology**

#### **2.1. Microorganisms**

*Trametes versicolor* CDBB-H-1051 and *Aspergillus* sp were used in these experiments. Stock cultures were maintained on malt-extract agar (malt extract 2%, agar 1.8%) or PDA slants at 4°C with a periodic transfer.

#### **2.2. Culture conditions for solid-state monocultures**

For developing the corresponding monoculture, each microorganism was cultivated in solidstate fermentation (SSF) using 4 g of wheat bran and sugar cane bagasse (1:1 w/w) as support and substrate. For doing this, the support was moistened with water and autoclaved in 250 mL beakers at 121°C for 20 min.

For laccases production monoculture, an appropriate quantity (around 4 mL) of Kirk medium was added to maintain the desired moisture level of the support (50%) for several experimental units. Each beaker was then inoculated with 4 mycelial plugs (50 mm diameter) taken from the periphery if a *T. versicolor* colony grown on malt extract agar at 30°C for 240 h, withdrawing two experimental units every 24 h for quantifying growth, residual substrate content and oxidases activities, and employing the analytical techniques described in the following sections.

Kirk basal medium composition (in g/L) was as follows: sodium tartrate, 0.275; MgSO4·7H2O, 0.55; K2HPO4, 2.2; CaCl2·2H2O, 0.145; (NH4)2SO4, 0.44; Glucose, 8.2; CuSO4·5H2O, 0.28; trace elements, 11 mL (in g/L: MnSO4·H2O, 0.5; NaCl, 1; FeSO4·7H2O, 0.1; CoCl2·6H2O, 0.185; ZnSO4·7H2O, 0.11; Na2MO4·2H2O, 0.011; H3BO3, 0.011). The pH of the medium was adjusted at 5.0 using 1 M HCl before sterilization.

Inoculum from *Aspergillus* sp was obtained from several 5 day old PDA plates incubated at 37°C. The spores in the agar surface were gently scraped and blended in 10 mL sterile saline and used as spore suspension. The spores were enumerated under microscope using a Neubauer chamber. The experimental units used for developing the *Aspergillus* monocultures for obtaining hydrolytic activities were inoculated using 1 × 108 spores/gsubstrate and incubated at 37°C for 96 h. Two experimental units were taken from incubation every 24 h, for quantifying growth, residual substrate content and hydrolytic activities, employing the analytical techniques described further.

Basal medium composition employed for this monoculture (in g/L) was as follows: K2HPO4, 2; KH2PO4, 2; (NH4)2SO4, 5.

#### **2.3. Cocultures developing**

major polysaccharide in several cereals cell wall, to its constituent monomers. These enzymes are mostly used in textile, pulp and paper, bread making and feed industries, and the production of juice and fruit extracts [1, 2]. Moreover, laccases (EC 1.10.3.2) are multicopper enzymes that catalyze the oxidation of a wide variety of substrates such as mono-, di- and polyphenols, aminophenols, methoxyphenols, aromatic amines, and ascorbic acid. They have several industrial uses: they degrade toxic fungal metabolites and phenolic compounds and also are used in the design of biosensors, the detection of phenols in wastewaters, in the development of biofuel cells, during bleaching and delignification processes in the pulp and paper industry, and for the production of novel paper products [3]. Together, xylanases and laccases can act for boosting bleaching process of several kinds of pulps, generating a cleaner process in which the use of the hazardous chemicals may be considerably reduced [4, 5]. These enzymes can be produced mainly by fungus, either in submerged or in solid-state cultures. The former is the most widely used as it provides a good control of operational parameters, high productivity and easy downstream processing, homogeneity of the culture and pH, and better oxygen supply and agitation speed management [6]. However, solid-state culture could be better for producing this kind of enzymes as it represents the conditions that fungus finds in nature during the invasion of lignocellulosic material. Regarding this, our research group has advanced in optimizing the components of culture media in order to obtain the highest xylanases and laccases activities and yields by *Aspergillus* sp and *Trametes versicolor*, respectively [7]. Both enzymatic activities have been evaluated for pulp pretreatment, achieving good results [8, 9]. However, the behavior of the corresponding optimized cultures has not been analyzed properly although this information

On the other hand, the joint use of fungi which produce xylanase or laccase for developing a coculture system may be considered in order to obtain a mixed enzyme preparation, which has both xylanase and laccase activities, for being applied in biopulping and biobleaching processes. This kind of procedure will provide economic advantages because of the reduction

Therefore, the objective of this work is to characterize solid-state monocultures with respect to growth, substrate consumption, and xylanases or laccases production and to test a coculture

*Trametes versicolor* CDBB-H-1051 and *Aspergillus* sp were used in these experiments. Stock cultures were maintained on malt-extract agar (malt extract 2%, agar 1.8%) or PDA slants at

For developing the corresponding monoculture, each microorganism was cultivated in solidstate fermentation (SSF) using 4 g of wheat bran and sugar cane bagasse (1:1 w/w) as support

can be used for developing a scalable bioprocess.

for producing both enzymes at the same solid-state fermentation.

**2.2. Culture conditions for solid-state monocultures**

in the overall cost of production [10].

**2. Methodology**

256 Fermentation Processes

**2.1. Microorganisms**

4°C with a periodic transfer.

For developing the cocultures in solid state, the same support employed for monocultures was used. This was moisturized and sterilized as indicated before. In this case, the support was moisturized with Kirk basal medium, and both inoculums (*T. versicolor* and *As‐ pergillus* sp.) were added, using the same quantities of the corresponding monocultures (see Section 2.2). Several experimental units were subsequently incubated at 30 or 37°C for 240 h. In this case oxidative and hydrolytic activities were quantified for each culture after 240 h.

#### **2.4. Extraction and storage of crude enzymes**

After incubation, 80 mL of 100 mM sodium acetate buffer pH 5 was added to each experimental unit, homogenizing with a Multi Braun® mixer and a posterior constant agitation in an ice bath. Afterwards, the enzymatic extracts were recovered by centrifugation at 4000 rpm and stored at 4°C until analyzed. The solids obtained after centrifugation were used for estimate biomass and residual substrate content, as explained below.

#### **2.5. Enzymatic activities quantification**

Laccase (Lac) activity was determined by measuring the increase in A470 (ε470 nm = 26,600 M −1 cm−1) due to the oxidation of 10 mM guaiacol in 0.1 M Na-acetate buffer (pH 5.0) after incubation with the crude extract at 25°C for 10 min. One unit of laccase activity (U) was defined as the amount of enzyme required to oxidize 1 μmol of guaiacol per minute of reaction [11].

Xylanolytic (Xyl) activity was assayed by incubating at 45°C for 20 min using the crude enzyme with 1% (w/v) xylan dissolved in 100 mM acetate buffer pH 5.0, and the release of reducing sugars as xylose was monitored at 575 nm after stopping the reaction by the addition of DNS. The optical density obtained was compared with a 1 g/L xylose standard curve. One unit of xylanolytic activity was defined as the enzyme necessary for the release of 1 μmol of xylose under the described conditions [12].

Lignin peroxidase (LiP) activity was estimated by incubating at 25 °C for 20 min the crude enzyme with 4 mM veratryl alcohol diluted in 100 mM tartrate buffer pH 3.5 and 0.4 mM H2O2. The formation of veratraldehyde was monitored at 310 nm (ε310 nm = 9.3331 mM−1 cm−1). One unit of lignin peroxidase activity was defined as the enzyme required for oxidize 1 μmol of veratryl alcohol per minute of reaction [13].

Manganese peroxidase (MnP) activity was assayed by Incubating at 25 °C for 5 min the crude enzyme with 0.1 mM MnSO4, 1 mM H2O2, and 1 mM 2,6-dimethoxyphenol (DMP) as substrate diluted in 0.1 M tartrate buffer pH 4.5, measuring the increase in A469 nm (ε469 nm = 27,500 mM −1 cm−1). One unit of manganese peroxidase activity (U) was defined as the amount of enzyme required to oxidize one μmol of DMP per minute of reaction [14].

Glucoamylase (Glcamyl) activity was estimated by incubating at 60 °C for 15 min the crude enzyme with 1% (w/v) starch dissolved in 0.15 M sodium chloride buffer pH 5.0. The released reducing sugars as glucose were monitored at 575 nm after stopping the reaction by the addition of DNS. The optical density obtained was compared with a 1 g/L glucose standard curve. One unit of glucoamylase activity was defined as the enzyme necessary for the release of 1 μmol of glucose under the reaction conditions [15].

α-Amylase (α-amyl) activity was determined by incubating at 37 °C for 20 min the crude enzyme with 1% (w/v) starch dissolved in 0.15 M sodium chloride buffer pH 5. The photometric disappearance of starch was quantified after stopping the reaction by the addition of an iodine (I2/IK) mother solution, and the resultant optical density at 580 nm was registered. One unit of α-amylase activity was defined as the enzyme necessary for hydrolyze 0.1 mg of starch [15].

Invertase (Inv) activity was determined by incubating at 30 °C for 30 min the crude enzyme with 0.1 M sucrose dissolved in 0.15 M acetate buffer pH 5.5. The reducing sugars as fructose were quantified after stopping the reaction with DNS. The optical density obtained was compared with a 1 g/L glucose standard curve. One unit of invertase activity was described as the enzyme necessary for the release of 1 μmol of reducing sugars per minute of reaction [16]. Carboxymethyl cellulase (CMCase) activity was quantified By incubating at 50 °C for 5 min the crude enzyme with (1% w/v) carboxymethyl cellulase low viscosity in 50 mM citrate buffer (pH 5.0). The reducing sugars as glucose were quantified after stopping the reaction with DNS. The optical density obtained was compared with a 1 g/L glucose standard curve. One unit of CMCase activity was described as the enzyme necessary for the release of 1 μmol of reducing sugars per minute of reaction [17].

The total cellulase activity (filter paper activity, FPAse) was assayed by using a 0.5 × 6 cm string of filter paper as the substrate. This was incubated using 100 mM acetate buffer (pH 5.0) and the crude enzyme for 5 min at 45°C, stopping the reaction with DNS. The optical density obtained was compared with a 1 g/L glucose standard curve. One unit of FPAse activity was defined as the amount of enzyme used for the release of 1 μmol of glucose under the assayed conditions [18].

#### **2.6. Biomass quantification**

**2.5. Enzymatic activities quantification**

under the described conditions [12].

of veratryl alcohol per minute of reaction [13].

required to oxidize one μmol of DMP per minute of reaction [14].

of 1 μmol of glucose under the reaction conditions [15].

lyze 0.1 mg of starch [15].

reaction [11].

258 Fermentation Processes

Laccase (Lac) activity was determined by measuring the increase in A470 (ε470 nm = 26,600 M −1 cm−1) due to the oxidation of 10 mM guaiacol in 0.1 M Na-acetate buffer (pH 5.0) after incubation with the crude extract at 25°C for 10 min. One unit of laccase activity (U) was defined as the amount of enzyme required to oxidize 1 μmol of guaiacol per minute of

Xylanolytic (Xyl) activity was assayed by incubating at 45°C for 20 min using the crude enzyme with 1% (w/v) xylan dissolved in 100 mM acetate buffer pH 5.0, and the release of reducing sugars as xylose was monitored at 575 nm after stopping the reaction by the addition of DNS. The optical density obtained was compared with a 1 g/L xylose standard curve. One unit of xylanolytic activity was defined as the enzyme necessary for the release of 1 μmol of xylose

Lignin peroxidase (LiP) activity was estimated by incubating at 25 °C for 20 min the crude enzyme with 4 mM veratryl alcohol diluted in 100 mM tartrate buffer pH 3.5 and 0.4 mM H2O2. The formation of veratraldehyde was monitored at 310 nm (ε310 nm = 9.3331 mM−1 cm−1). One unit of lignin peroxidase activity was defined as the enzyme required for oxidize 1 μmol

Manganese peroxidase (MnP) activity was assayed by Incubating at 25 °C for 5 min the crude enzyme with 0.1 mM MnSO4, 1 mM H2O2, and 1 mM 2,6-dimethoxyphenol (DMP) as substrate diluted in 0.1 M tartrate buffer pH 4.5, measuring the increase in A469 nm (ε469 nm = 27,500 mM −1 cm−1). One unit of manganese peroxidase activity (U) was defined as the amount of enzyme

Glucoamylase (Glcamyl) activity was estimated by incubating at 60 °C for 15 min the crude enzyme with 1% (w/v) starch dissolved in 0.15 M sodium chloride buffer pH 5.0. The released reducing sugars as glucose were monitored at 575 nm after stopping the reaction by the addition of DNS. The optical density obtained was compared with a 1 g/L glucose standard curve. One unit of glucoamylase activity was defined as the enzyme necessary for the release

α-Amylase (α-amyl) activity was determined by incubating at 37 °C for 20 min the crude enzyme with 1% (w/v) starch dissolved in 0.15 M sodium chloride buffer pH 5. The photometric disappearance of starch was quantified after stopping the reaction by the addition of an iodine (I2/IK) mother solution, and the resultant optical density at 580 nm was registered. One unit of α-amylase activity was defined as the enzyme necessary for hydro-

Invertase (Inv) activity was determined by incubating at 30 °C for 30 min the crude enzyme with 0.1 M sucrose dissolved in 0.15 M acetate buffer pH 5.5. The reducing sugars as fructose were quantified after stopping the reaction with DNS. The optical density obtained was compared with a 1 g/L glucose standard curve. One unit of invertase activity was described as the enzyme necessary for the release of 1 μmol of reducing sugars per minute of reaction [16].

The quantification of fungal biomass was made after quantifying ergosterol content of the biomass in each sample. For doing this, the solid content of each experimental unit was resuspended in 10 mL of water by vigorous agitation. From this homogeneous solid suspension, 1 mL was withdrawn and filtered, to recover the solids. To this, 3 mL of an alcoholic basic solution (25% w/v of KOH dissolved in methanol) was added, boiling the resultant mixture for 5 h. Afterwards, 1 mL of distilled water and 5 mL of *n*-heptane were added, for mixing at the vortex for 3 min. The tubes were let to settle until the phase separation (around 1 h), for recording the corresponding optical density at 230 nm (for detecting the presence of 24(28) DHE, an intermediary of ergosterol pathway) and 280 nm (for detecting the ergosterol presence) of the organic phase. Ergosterol content of the biomass was estimated using the following equation:

$$Ergosterool(\%) = \frac{O.D.at280 nm}{290} - \frac{O.D.at230 nm}{518}$$

where 290 and 518 correspond to the molar extinction coefficient (M−1 cm−1) of crystalline ergosterol and 24(28) DHE, respectively. A 10 g/L mycelium (*Aspergillus* sp or *T. versicolor*) standard curve was developed, for correlate g/L of biomass with ergosterol %. In fact, the calculated ergosterol % contained on each sample was compared with this curve in order to estimate biomass content [19].

#### **2.7. Substrate quantification**

The solids obtained from each culture were dried at 60°C for 12 h. The biomass content (estimated as explained before) was subtracted to the corresponding dry weight in order to obtain the real substrate content of each sample.

All the experiments were performed in duplicate, and the results are expressed as the mean of these repetitions and the corresponding standard deviation.

#### **3. Results and discussion**

#### **3.1. Behavior of solid-state fermentation monocultures during enzymes production**

On previous work, we optimized the culture media components in order to obtain high xylanase and laccase productions on solid-state fermentation, using *Aspergillus* sp or *T. versicolor*, respectively [7]. However, these experiments were made at very low volumes, in which only the information of final enzyme production was obtained at 72 or 240 h, respectively. As these enzymes were used successfully for jonote pulp bleaching [8], we decided to increase the volume of the reaction unit, and analyze the behavior of each culture with respect to fungal growth, substrate consumption and xylanase or laccase production. By doing this, we could obtain the basic information to scale up the process for producing both enzymatic activities in large amounts. Also, it could be possible to design an efficient bioprocess in which both enzymatic units can be produced simultaneously.

In this regard, it is worth mentioning that biomass quantification on solid-state cultures is a complicated work. Fungal growth is not easy to quantify because fungus grows as hyphal filaments that cannot be quantified by the usual enumeration techniques, and specifically on cultures in which an insoluble material is used as the only carbon source, complete recovery of fungal biomass from the substrate is very difficult, because the fungal hyphae tend to penetrate into and binds tightly to the solid substrate particles [20]. It is important therefore to have reliable and convenient methods for measuring fungal growth. For this reason, we used the ergosterol content methodology [19] for quantifying biomass evolution along the culture, and employed a simple mass balance for knowing the corresponding residual substrate. Therefore, this is one of the main contributions of the present work.

With respect to monocultures developed with *Aspergillus* sp., growth seemed to start increasing when the culture was among 20 and 40 h, reaching finally 0.7 g of mycelium/g of substrate at the end of culture. In this case, the fungus showed an approximate growth rate of 0.03 h−1. Substrate consumption showed a constant rate during the first 60 h, stopping after that. Almost

**Figure 1.** Fungal growth (♦), substrate consumption (▪), and xylanase production (▴) by *Aspergillus* sp along the solidstate monoculture developed on wheat bran:sugar cane bagasse 1:1 (w/w) as substrate for solid-state fermentation, incubated at 37°C for 96 h.

2.5 g of substrate seems to have been consumed during the culture, at a consumption rate of −0.04 gsubstrate/h. With respect to xylanases production, this started with the same trend as that of fungal growth, and increased constantly, although when the growth stopped xylanolytic activity decreased slightly (**Figure 1**).

**3. Results and discussion**

260 Fermentation Processes

cubated at 37°C for 96 h.

both enzymatic units can be produced simultaneously.

**3.1. Behavior of solid-state fermentation monocultures during enzymes production**

On previous work, we optimized the culture media components in order to obtain high xylanase and laccase productions on solid-state fermentation, using *Aspergillus* sp or *T. versicolor*, respectively [7]. However, these experiments were made at very low volumes, in which only the information of final enzyme production was obtained at 72 or 240 h, respectively. As these enzymes were used successfully for jonote pulp bleaching [8], we decided to increase the volume of the reaction unit, and analyze the behavior of each culture with respect to fungal growth, substrate consumption and xylanase or laccase production. By doing this, we could obtain the basic information to scale up the process for producing both enzymatic activities in large amounts. Also, it could be possible to design an efficient bioprocess in which

In this regard, it is worth mentioning that biomass quantification on solid-state cultures is a complicated work. Fungal growth is not easy to quantify because fungus grows as hyphal filaments that cannot be quantified by the usual enumeration techniques, and specifically on cultures in which an insoluble material is used as the only carbon source, complete recovery of fungal biomass from the substrate is very difficult, because the fungal hyphae tend to penetrate into and binds tightly to the solid substrate particles [20]. It is important therefore to have reliable and convenient methods for measuring fungal growth. For this reason, we used the ergosterol content methodology [19] for quantifying biomass evolution along the culture, and employed a simple mass balance for knowing the corresponding residual

With respect to monocultures developed with *Aspergillus* sp., growth seemed to start increasing when the culture was among 20 and 40 h, reaching finally 0.7 g of mycelium/g of substrate at the end of culture. In this case, the fungus showed an approximate growth rate of 0.03 h−1. Substrate consumption showed a constant rate during the first 60 h, stopping after that. Almost

**Figure 1.** Fungal growth (♦), substrate consumption (▪), and xylanase production (▴) by *Aspergillus* sp along the solidstate monoculture developed on wheat bran:sugar cane bagasse 1:1 (w/w) as substrate for solid-state fermentation, in-

substrate. Therefore, this is one of the main contributions of the present work.

With respect to monocultures developed with *T. versicolor* for laccase production (**Figure 2**), it can be seen that in this case there was an adaptation phase of around 50 h, afterwards the fungus started to grow. In this case, it was obtained about 0.6 gmycelium/gsubstrate, with a constant specific growth rate of 0.11 h−1. However, substrate consumption was really slow (*rs* = −0.0006 gsubstrate/h), and the fungi only consumed approximately 1.5 g along the culture, which represents 40% of the initial substrate. Laccase production and growth started together, increasing at constant rate, but the enzyme production remained even when biomass stopped growing.

Several studies developed on liquid or submerged fermentation have reported that laccases production has a secondary metabolite behavior; it means the activity is produced mainly during the secondary metabolism [21]. On solid-state culture, this relationship is not well known due to the difficulty of quantifying accurately the total biomass grown in the substrate along the culture. However, other studies in which fungal biomass has been quantified by indirect methods, like that used in the present work, have shown that laccases production is growth related, as happened for laccases produced by *Streptomyces psammoticus* on rice straw [22]. And those results are in accordance with the *T. versicolor* profile obtained in the present work.

The titers obtained on each monoculture for xylanases and laccase activities were high. These results show that solid-state culture is a good alternative for producing high oxidative or hydrolytic activities, in order to employ them for several industrial bioprocesses. At this respect, the results obtained in the present work would represent one basis for developing this process on a full- scale. Thereby, for further characterization of the monocultures, in the next section the production profiles of other oxidative or hydrolytic activities obtained were analyzed.

**Figure 2.** Fungal growth (♦), substrate consumption (▪), and laccase production (▴) by *T. versicolor* in monoculture developed on wheat bran:sugar cane bagasse 1:1 (w/w) as support/substrate for solid-state fermentation, incubated at 37°C for 96 h.

#### **3.2. Enzymatic profiles of crude enzymes**

Total enzyme production obtained along *Aspergillus* sp. and *T. versicolor* solid-state monocultures was determined by quantifying different activities: xylanases, oxido-reductases and cellulases, since it is known that these enzymatic families are involved in invasion of lignocellulosic material [23]. Furthermore, due to wheat bran and sugar cane bagasse composition [24], amylase and invertase activities were also measured.

Along *Aspergillus* monoculture, xylanolytic activity was predominant; a peak of this activity was reached after 60 h, followed by a constant level until the end of culture. However, another hydrolases were quantified: cellulases and invertases had maximum titers during the first 20 h, after that their levels remained below 1000 U/g for FPase and 500 U/g for CMCase, while amylases reached their maximum levels after 48 h of cultivation, and these activities were kept until the end of the culture. In this monoculture, no oxidase activities were obtained.

With respect to oxidases, during the first 72 h of monocultures developed with *T. versicolor*, LiP and MnP activities were predominant; from this moment, laccase activity increased continuously to reach a peak around 2700 U/g at the end of process. This activity was almost five times higher than lignin and manganese peroxidases. After 100 h of cultivation, LiP and MnP activities stayed at a level around 250 and 800 U/g, respectively. In this *T. versicolor* monoculture none hydrolytic activity was detected. **Table 1** concentrates final titers of all hydrolase and oxidase activities obtained on each of both monocultures.


ND indicates the enzyme whose activity was not detected in the corresponding monoculture.

**Table 1.** Oxidases and hydrolase activities produced by monocultures developed by *T. versicolor* or *Aspergillus* sp on solid-state monocultures.

Taking into account that enzymatic extracts obtained on solid-state cultures by *Aspergillus* sp. and *T. versicolor* had several hydrolytic or oxidative activities, there could be some other uses for them. In this respect, extracts obtained from *Aspergillus* sp. monoculture could be used for saccharification processes of a number of agro-industrial residues [25], while the extract

obtained from *T. versicolor* monoculture can be proved in color removal of some industrial effluents [26].

#### **3.3. Cocultures for joint production of lignocellulases**

**3.2. Enzymatic profiles of crude enzymes**

262 Fermentation Processes

[24], amylase and invertase activities were also measured.

Total enzyme production obtained along *Aspergillus* sp. and *T. versicolor* solid-state monocultures was determined by quantifying different activities: xylanases, oxido-reductases and cellulases, since it is known that these enzymatic families are involved in invasion of lignocellulosic material [23]. Furthermore, due to wheat bran and sugar cane bagasse composition

Along *Aspergillus* monoculture, xylanolytic activity was predominant; a peak of this activity was reached after 60 h, followed by a constant level until the end of culture. However, another hydrolases were quantified: cellulases and invertases had maximum titers during the first 20 h, after that their levels remained below 1000 U/g for FPase and 500 U/g for CMCase, while amylases reached their maximum levels after 48 h of cultivation, and these activities were kept

With respect to oxidases, during the first 72 h of monocultures developed with *T. versicolor*, LiP and MnP activities were predominant; from this moment, laccase activity increased continuously to reach a peak around 2700 U/g at the end of process. This activity was almost five times higher than lignin and manganese peroxidases. After 100 h of cultivation, LiP and MnP activities stayed at a level around 250 and 800 U/g, respectively. In this *T. versicolor* monoculture none hydrolytic activity was detected. **Table 1** concentrates final titers of all

until the end of the culture. In this monoculture, no oxidase activities were obtained.

hydrolase and oxidase activities obtained on each of both monocultures.

Laccases 2759 ± 30 ND LiP 410 ± 10 ND MnP 996 ± 2 ND Xylanases ND 4617 ± 38 FPAses ND 746 ± 7 Carboximetil-celulases ND 829 ± 34 Glucoamylases ND 1762 ± 4 α-amylases ND 1898 ± 6 Invertases ND 1023 ± 73

ND indicates the enzyme whose activity was not detected in the corresponding monoculture.

solid-state monocultures.

**Table 1.** Oxidases and hydrolase activities produced by monocultures developed by *T. versicolor* or *Aspergillus* sp on

Taking into account that enzymatic extracts obtained on solid-state cultures by *Aspergillus* sp. and *T. versicolor* had several hydrolytic or oxidative activities, there could be some other uses for them. In this respect, extracts obtained from *Aspergillus* sp. monoculture could be used for saccharification processes of a number of agro-industrial residues [25], while the extract

**Enzymatic activities (U/gs)** *Trametes versicolor Aspergillus* **sp**

Solid-state cultures showed high productions of either hydrolase or oxidase activities in the corresponding monocultures. Previous work of this group has shown that bleach boosting of kraft [9] and jonote [8] pulp can be improved with the employment of the combined action of xylanases and laccases, produced by solid-state cultures as those described in the present work. So, a greater enzyme production would be desirable in order to have a more efficient bioprocess. At this respect, it has been suggested that the cocultivation of microbes in fermentation can increase the quantity of the desirable components on a cellulose complex [27]. On the other side, some reports have shown that laccases or xylanases production can increase in a coculture mode, as happens with *P. ostreatus*, which increased fivefold its laccase production in a coculture with *Trichoderma viride* in submerged fermentation [28]. As discussed earlier, it became interesting to probe if a coculture of *Aspergillus* sp and *T. versicolor* was feasible for obtaining higher xylanase and laccase activities at the same time considering that both fungi used wheat bran and sugar cane bagasse as substrate. In addition, this coculture strategy would provide economic advantages because of reduction in overall cost production. This is why both fungi were inoculated at the same time in the support and two incubation temperatures were probed: 30°C (the best for *T. versicolor*) and 37°C (the best for *A. niger*), developing independent experiments. **Figure 3** shows the enzyme proportions obtained in cocultures developed at 30 or 37°C with respect to the control conditions, obtained in the respective monocultures of each fungi.

With respect to hydrolytic activities proportion, it can be seen that while on monocultures xylanase activity was the predominant hydrolytic activity, glucoamylases were in greater proportion for cocultures developed at 30°C, and α-amylases highlighted on cocultures developed at 37°C (**Figure 3 A**).

Comparing both cocultures, one can see that the highest hydrolytic activities were obtained on that developed at 37°C, which means that temperature could be affecting seriously the *Aspergillus* sp. behavior along this culture. On the other hand, invertase and cellulase activity proportions were low on monocultures, but decreased on both cocultures. The diminution of invertase activity production on coculture modes can be due to the presence of glucose in the media, as Kirk medium was used to moisturize the support in these experiments, and this mineral medium contains glucose. A similar diminution on invertase activity production due to glucose presence in solid-state fermentation was reported previously for *A. ochraceus* in similar culture conditions, which employed wheat bran or sugar cane bagasse as substrates [29].

Laccase activities decreased on both cocultures with respect to those values obtained on monocultures. This behavior could be considered unusual, because in general the coculture strategy is used in order to increase these activities. In fact, the addition of soil microorganisms to white rot fungi cultures has increased laccase and other oxidases production [30]. In this case, the diminution on laccase activity can be explained from different points of view. First of all, in the present study both fungi were inoculated at the same time to the support. The decrease in oxidases and hydrolases production could be provoked by problems in fungal growth, considering the differences in specific growth rate of each fungal species. This is because mineral medium used in these cocultures contained glucose, and it has been reported as laccase inductor for *T. versicolor* [31]. So, even when *Aspergillus* grows slower in its respective monoculture, in this case it could be consuming the available glucose of the medium faster than *T. versicolor* could, reducing the ability of *T. versicolor* for producing laccases and the another oxidases. However, to probe this hypothesis, some additional experiments would be necessary.

**Figure 3.** Enzyme proportion of hydrolytic (A) or oxidase (B) activities obtained on monocultures (▪), and cocultures developed at 30°C ( ) or 37°C ( ).

On the other hand, we must remember that enzymes are produced at different rates along the cultures, as described in Section 3.2. In this case, activities analyzed for this experimental phase are those obtained after 10 days, but the enzyme evolution along both cocultures was not registered. This is a great limitation for obtaining valid conclusions. It could be possible that one of these enzymes has been increased at any time during the fermentations, but as we did not quantify the enzyme evolution, we could not know if the reported activity was the highest obtained for the corresponding enzyme in this experiment. So, we can only analyze the enzyme activities at the end of the coculture, and these could not be the highest activities obtained in this case.

Finally, even when some hydrolytic or oxidative enzymes decreased on coculture mode, these extracts can be employed on several processes. Agricultural by-products typically vary in their chemical composition and nutritional value, and sometimes are also higher in low-quality fiber, so a specific enzyme complex is required to break it down in order to be used in ruminant feed. Besides, their nutritional value could be increased by biodegradation methods of fiber in the rumen, through efficient delignification [32]. Therefore, the filtrates obtained on both cocultures could be a good alternative for being employed for using agricultural by-products for ruminant feed.

#### **4. Conclusions**

all, in the present study both fungi were inoculated at the same time to the support. The decrease in oxidases and hydrolases production could be provoked by problems in fungal growth, considering the differences in specific growth rate of each fungal species. This is because mineral medium used in these cocultures contained glucose, and it has been reported as laccase inductor for *T. versicolor* [31]. So, even when *Aspergillus* grows slower in its respective monoculture, in this case it could be consuming the available glucose of the medium faster than *T. versicolor* could, reducing the ability of *T. versicolor* for producing laccases and the another oxidases. However, to probe this hypothesis, some additional experiments would be

**Figure 3.** Enzyme proportion of hydrolytic (A) or oxidase (B) activities obtained on monocultures (▪), and cocultures

On the other hand, we must remember that enzymes are produced at different rates along the cultures, as described in Section 3.2. In this case, activities analyzed for this experimental phase are those obtained after 10 days, but the enzyme evolution along both cocultures was not

necessary.

264 Fermentation Processes

developed at 30°C ( ) or 37°C ( ).

The indirect technique used for the quantification of fungal biomass content was useful, meaning a great contribution for analyzing solid-state cultures. From this, it could be seen that both fungi have different behaviors along the culture, in which *T. versicolor* seems to grow faster than *Aspergillus* sp., and consequently its substrate consumption rate is also higher. However, high xylanases and laccases titers were obtained on the corresponding monocultures. In this case, xylanases production seemed to be growth related, while laccases started to produce since growth phase and continued producing even when fungus stopped growing. In addition, the presence of other hydrolases and oxidases activities showed the potential of the enzymatic extracts for being used in several industrial bioprocesses. Coculture mode caused a decrease in xylanase and laccase production. In this respect, it seems that xylanase production is affected by the incubation temperature, and although *Aspergillus* sp. grows slower it could be consuming the glucose contained in Kirk mineral medium, delaying the laccases production by *T. versicolor*. Some modification in the inoculation methodology is needed in order to increase the production of these enzymes by coculture. Based on this, we can conclude that solid-state fermentation, independent or as coculture, could be a promising green biotechnology for producing several lignocellulosic enzymes from agricultural residues that can be used for different industrial applications at a lower cost.

#### **Acknowledgements**

LSV acknowledges CONACyT for the scholarship 551418. The authors acknowledge Instituto de Ingeniería, from Universidad Nacional Autónoma de México, Tecnológico de Estudios Superiores de Ecatepec and PRODEP, for the economic funding.

### **Author details**

Ulises Durán Hinojosa#1,, Leticia Soto Vázquez#2,, Isabel de la Luz Membrillo Venegas2 , Mayola García Rivero2 , Gabriela Zafra Jiménez2 , Sergio Esteban Vigueras Carmona2 and María Aurora Martínez Trujillo2\*

\*Address all correspondence to: amartinezt@tese.edu.mx

1 Coordination of Environmental Engineering, Institute of Engineering, National Autonomous University of Mexico, Ciudad Universitaria, México D.F

2 Division of Chemical Engineering and Biochemistry, Tecnológico de Estudios Superiores de Ecatepec. Avenida Tecnológico esq. Av. Carlos Hank González, Ecatepec, México
