**1. Introduction**

*E. coli* is most studied bacteria learned of symbiotic relationships with human for years derived after culturing F Plasmid of a 1922 isolate from a diptheria patient. Production of biopharmaceuticals from *E. coli* is in practice since 1965. Also, the it served for production of biopharmaceuticals such as recombinant proteins, metabolites by several companies namely BPB Bioscience, Agilent technologies, Promega, Takara, Tonbo Biosciences, New England Biolabs, Novagen and Lucigen. They are optimised for expression of challenging proteins difficult to express, purify and folding in native conformation. Moreover, formation of proper disulphide bonds and refolding of membrane proteins is also achieved by using newly commercially

available strains. These strains are suitable for production of metabolites and enzymes in easy to scale-up process development. The cultivation of *E. coli* is facilitated by optimisation of concentrations of tryptone (plant and animal derived), yeast extract, casamino acids. These are divided in three categories carbon, nitrogen and micronutrients, as per sustainable development goals set by united nations for 2030. Innovation for increasing productivity using technology is one of the 17 subject areas, it is need to follow typical strategy, which is usually unique for production of an active compound or protein. The **Table 1**, below describes different strategies to discovered for optimisation of product by utilising model organism *E. coli* (**Table 1**) [57].

Production of Biopharmaceuticals and Biomolecules during fermentation require media formulated using cheap ingredients for supplementation of carbon and nitrogen. The carbon sources are typically glucose, glycerol, molasses (**Table 1**). Nitrogen sources are typically yeast extract and digested proteins by enzymes. The utilisation of carbon by *E. coli* during batch can be inhibited due to accumulation of acetate, formate and succinate. Historically several attempts have been made to design defined or semi-defined media recipes that do not require bio nutrient additives. Traditionally, media developed generally utilise one-factor-at-atime (OFAT) where all but one ingredient (factor) is fixed [58, 59]. This approach guides towards determining individual factors that influence culture growth. Effect of utilisation of amino acids, vitamins and minerals interaction are not possible using OFAT. These interactions can be studied using DoE and multifactorial designs.

DoE is a multifactorial methodology utilising statistical approaches to design and analyse an experimental process by which better outcome and results are obtained. Bacterial growth is the system response impact of "DoE planning" by varying critical parameters and simultaneous factors, such as phosphate, sulphate, vitamin and amino acid concentrations. The full factorial design, DoE is attributed by important principals to allow for robust, valid experimentation. These are known as treatments, replicated, randomised to protect against hidden factors [59]. All treatments must be performed in blocks to control sources of variation. In an experimental process design, all four principles, the statistical approach, conform to regulations and complete exploration of an extensive experimental design process, helps in reducing the number of experiments to get a good outcome [60]. For cultivation using *E. coli*, statistically relevant experimental designs for industrially important proteins (rB-glucosidase, human superoxide dismutase) is studied. A similar approach is applied enzymes, recombinant antibodies and therapeutic proteins(Ranibizumab, Somatropin Certolizumab pegol, PEG interferon alfa-2b, Romiplostim, Interferon-beta 1b, Pegloticase, etc.) [61]. The optimisation of media and critical components is needed for *E. coli* fermentation in batch and fed-batch fermentation is required to achieve a better growth rate, target product per litre of fermentation and reduced cost of production. The cost of various fermentation ingredients for one batch size 10 L of fermentation ranges from 20 to 155 USD (**Table 2**). The cost of media ingredients reduces after scaling up of process for production from 15 to 5000 L.

The DoE with a correct statistical model to understand the effect is needed to be adopted by industrial producers to achieve a robust and high yielding process. The DOE is statistically planned trials for optimising factors associated with increased product output, yield and cost reduction. Typically, DOE experiments are done to screen up to 2–15 elements. Traditionally, using OFAT, the number of experiments needed to determine the effect on yield, the output is numerous. Using the DOE approach, several components, additives and sources of nutrients are compared

*Strategies for Enhancing Product Yield: Design of Experiments (DOE) for* Escherichia coli*… DOI: http://dx.doi.org/10.5772/intechopen.99288*





#### **Table 1.**

*Strategies and optimization parameters and type of fermentation in production of various proteins and small molecules.*

simultaneously, and their impact is evaluated. Based on the response critical factors are ranked. Soon after the response effect by variables are generated, the analysis is successively recorded. Various DoE experiments are studied to understand influencing factors determined by a statistically relevant experimental plan. The difference in factors is measured by Analysis of variance (ANOVA). The results obtained after analysing responses are plotted using contour plots and response surface methodology (RSM). There are several software packages for optimisation of critical factors and parameters Design Expert (Stat-Ease Inc.), GT-SUITE (DOE), DOE ++ (RecCom), MODDE (Umetrics), DoE Fusion PRO (S-Matrix Corp.), STAVEX (Aicos), Minitab (Minitab Inc.), and JMP (SAS) [62].


*Strategies for Enhancing Product Yield: Design of Experiments (DOE) for* Escherichia coli*… DOI: http://dx.doi.org/10.5772/intechopen.99288*

*Amount of component added to the medium listed for purpose mentioned (g/L).*

*a Millilitres of trace elements solution, prepared as described added as 1X to medium or feed solution.*

*b Cost of media components calculated with consumption in fermentation using high grade reagents.*

#### **Table 2.**

*Components of media used to grow E. coli in batch and fed-batch fermentations.*

### **2. Critical fermentation ingredients**

Critical fermentation ingredients are media components which cannot be replaced. These can only be standardised for maximised yield. Typically, buffers and nitrogen sources such as yeast extract, tryptone are not changed. Since *E. coli* is the most studied and highly utilised systems for producing various enzymes, antibodies, and biological products. Bacteria require specific conditions for growth attributed to factors such as oxygen, pH, temperature, and light. Bacterial growth is divided into lag, exponential (log) and stationary phase. During the initial stage, cellular activity in a rich nutrient medium allows cells to synthesise proteins, cells increase in size, but no cell division occurs in the phase. During the exponential phase, metabolic activity is high as DNA, RNA, cell wall components, or machinery needed for division are generated. The stationary phase is triggered due to the accumulation of waste products and depletion of nutrients. During the late log phase, proteins are induced by the addition of allolactose analogue, Isopropyl β-D-1 thiogalactopyranoside (IPTG) [63, 64]. The expression of recombinant products is controlled by promoter systems like T5 and T7 RNA Polymerases. Alternative promoter systems, such as auto-inducible phoA promoter system [13], the saltinducible promoter (proU), arabinose-inducible promoter (pBAD) [65], the heatinducible phage Lamba promoters (pL and pR), the cumate-inducible T5 promoterbased system [66], and the cold-inducible cspA promoter-based system [67] are also valuable for the biologics production. The cost of biologics production is due to the high cost of raw material and fermentation media. In the biologics industry, the more straightforward, cheaper, and reproducible process is highly appreciated.

Fermentation media is a critical component, and a balance of nutrients is needed for increasing productivity. Standardisation of *E. coli* fermentation requires identifying a combination of various media components available, e.g., Yeast extract, Soyabean meal, Bactotryptone, Meat extract and Enzymatic digest of plant and animal protein (Trypic or casein enzymes). There are various carbon sources (glucose, glycerol, sucrose, lactose etc). Additives for fermentation are vitamins, amino acids, and trace elements. Designing a media needs to evaluate the requirement of each of the individual component along with the additives. The design of model using statistical approach having multiple parameters in consideration, followed by validation of defined parameters using fermentation. This is achieved using DoE experimentation (**Figure 1**). Experiments are carried out at Shake flash level with selected nutrients such as carbon and nitrogen sources. Small scale studies are carried out to define as batch or fed-batch fermentation. Next stage is to screen the components available for fermentation of batch/fed batch. Once the components are finalised the possibility of Scale-up is evaluated based on the availability from the source. Finalisation of media components is carried out using shake flask with DOE of media buffer additives and inducers. Evaluation of various product outcome biomass ratio and validation of protein quality is also study with 3 to 5 selected designs. Once the nutrient and components are finalised pilot scale batches setup to study biomass to product ratio. Further optimisation of dissolved oxygen and temperature in fermentation is carried out by the DOE approach. If results are not reproducible with the selected condition, other near possible designs are studied to finalise the medium and process for fermentation (**Figure 1**). The process of selection of components is based on outcome in an experiment calculated by Biomass (OD), product output g L<sup>1</sup> and cost of ingredients. The process is clearly defined in (**Figure 1**).
