**4. Develop of molecular methods for detection and identification of phytophatogenic fungi – Monitoring of the diseases causing by**  *Colletotrichum* **spp.**

Many fungal plant pathogens produce similar symptoms when they develop diseases among different hosts. Currently, the ability to detect, identify and quantify plant pathogens accurately is the cornerstone of plant pathology (Garrido et al., 2011). The reliable identification of the organism(s) responsible for a crop disease is an essential prerequisite to apply the correct disease management strategies and the most appropriate control measures to take. Besides, many pathogens are subjected to special regulation through quarantine programs agreed among producer countries. For all these reasons, pathogen identification is crucial to all aspect of fungal diagnostics and epidemiology in the field of plant pathology, but also in medical science, environmental studies and biological control (Alastair McCartney et al., 2003; Atkins et al., 2003).

Since the 1990's, new methods based on molecular biology have provided new tools for more accurate and reliable detection, identification and quantification of plant pathogens. These methods are based on immunological and DNA/RNA study strategies, including, amongst others: RFLP analyses of mitochondrial DNA (Garrido et al., 2008; Sreenivasaprasad et al., 1992), AFLP, AT-rich analyses (Freeman et al., 2000a, 2000b), RAPD-DNA (Whitelaw-Weckert et al., 2007), genus-specific and species-specific PCR primers (Garrido et al., 2008; Martínez-Culebras et al., 2003; Mills et al., 1992; Sreenivasaprasad et al., 1996), real-time PCR studies (Garrido et al., 2009a), and ELISA assays (Hughes et al., 1997). Diagnosis time can be reduced from a period of weeks, typically experienced with culture plating, to only a few days, thus allowing the appropriate control methods to implemented much sooner and more effectively (Atkins et al., 2003).

Advances in polymerase chain reaction technology have opened alternative approaches to the detection and identification of fungal pathogens. The development of PCR technology relies on three fundamental steps: i) the selection of a specific target region of DNA/RNA to identify the fungus; ii) extraction of total community DNA/RNA from the environmental sample; iii) a method for identifying the presence of the target DNA/RNA region in the sample (Garrido et al., 2011). Our group have optimised a very high sensitive protocol for diagnosis and identification of the fungal genus *Colletotrichum*, and the species *C. acutatum* and *C. gloeosporioides* (Garrido et al., 2009a).

The sensitivity of PCR-based protocols depends mainly on the instrumentation and technique used (i.e. conventional PCR *vs.* real-time PCR), but in a high proportion of cases this sensitivity depends on the quality of the total community DNA/RNA extracted from the environmental samples. Garrido et al. (2009) optimized a DNA extraction protocol that can be used for samples of strawberry plant material directly, or from fungal colonies removed from an agar plate. This method uses sample material physically ground using a grinding machine, in the presence of CTAB lysis buffer. The lysated samples are washed in various chemical products (chloroform, isopropanol, ethanol, etc.) and then the final step involves using Magnesil® beads and GITC lysis buffer (guanidinium thiocyanate buffer) in a Kingfisher robotic processor (Kingfisher ML, Thermo Scientific). The new method was tested with roots, crowns, petioles, leaves and fruits and the extraction methods always showed very high yields of DNA in both quantity and quality. Although, a wide range of

Many fungal plant pathogens produce similar symptoms when they develop diseases among different hosts. Currently, the ability to detect, identify and quantify plant pathogens accurately is the cornerstone of plant pathology (Garrido et al., 2011). The reliable identification of the organism(s) responsible for a crop disease is an essential prerequisite to apply the correct disease management strategies and the most appropriate control measures to take. Besides, many pathogens are subjected to special regulation through quarantine programs agreed among producer countries. For all these reasons, pathogen identification is crucial to all aspect of fungal diagnostics and epidemiology in the field of plant pathology, but also in medical science, environmental studies and biological control (Alastair

Since the 1990's, new methods based on molecular biology have provided new tools for more accurate and reliable detection, identification and quantification of plant pathogens. These methods are based on immunological and DNA/RNA study strategies, including, amongst others: RFLP analyses of mitochondrial DNA (Garrido et al., 2008; Sreenivasaprasad et al., 1992), AFLP, AT-rich analyses (Freeman et al., 2000a, 2000b), RAPD-DNA (Whitelaw-Weckert et al., 2007), genus-specific and species-specific PCR primers (Garrido et al., 2008; Martínez-Culebras et al., 2003; Mills et al., 1992; Sreenivasaprasad et al., 1996), real-time PCR studies (Garrido et al., 2009a), and ELISA assays (Hughes et al., 1997). Diagnosis time can be reduced from a period of weeks, typically experienced with culture plating, to only a few days, thus allowing the appropriate control methods to implemented

Advances in polymerase chain reaction technology have opened alternative approaches to the detection and identification of fungal pathogens. The development of PCR technology relies on three fundamental steps: i) the selection of a specific target region of DNA/RNA to identify the fungus; ii) extraction of total community DNA/RNA from the environmental sample; iii) a method for identifying the presence of the target DNA/RNA region in the sample (Garrido et al., 2011). Our group have optimised a very high sensitive protocol for diagnosis and identification of the fungal genus *Colletotrichum*, and the species *C. acutatum*

The sensitivity of PCR-based protocols depends mainly on the instrumentation and technique used (i.e. conventional PCR *vs.* real-time PCR), but in a high proportion of cases this sensitivity depends on the quality of the total community DNA/RNA extracted from the environmental samples. Garrido et al. (2009) optimized a DNA extraction protocol that can be used for samples of strawberry plant material directly, or from fungal colonies removed from an agar plate. This method uses sample material physically ground using a grinding machine, in the presence of CTAB lysis buffer. The lysated samples are washed in various chemical products (chloroform, isopropanol, ethanol, etc.) and then the final step involves using Magnesil® beads and GITC lysis buffer (guanidinium thiocyanate buffer) in a Kingfisher robotic processor (Kingfisher ML, Thermo Scientific). The new method was tested with roots, crowns, petioles, leaves and fruits and the extraction methods always showed very high yields of DNA in both quantity and quality. Although, a wide range of

**4. Develop of molecular methods for detection and identification of phytophatogenic fungi – Monitoring of the diseases causing by** 

*Colletotrichum* **spp.** 

McCartney et al., 2003; Atkins et al., 2003).

much sooner and more effectively (Atkins et al., 2003).

and *C. gloeosporioides* (Garrido et al., 2009a).

commercial kits are available for extraction of fungal DNA, they can represent a high cost per sample analysed, and they are not always totally reliable in not co-extracting PCR inhibitors, needed a dilution of samples prior to PCR reactions. The optimised protocol did not co-extracted PCR-inhibitors from any samples, and therefore, the sensitivity of the detection protocol is improved using this DNA extraction protocols (Garrido et al., 2011).

To date, conventional PCR has been a fundamental part of fungal molecular diagnosis, but it shows several limitations: i.e. gel-based methods, possibility of quantification, sensitivity, etc. The development of real-time PCR has been a valuable response to these limitations (Garrido et al., 2011). This technology improve the sensitivity, accuracy and it is less timeconsuming that conventional end-point PCR. For development and optimization of *Colletotrichum* diagnosis protocols, the commonly-used ribosomal RNA genes were used, because of the highly variable sequences of the internal transcribed spacers ITS1 and ITS2, which separate the 18S/5,8S and 5,8S/28S ribosomal RNA genes, respectively (Garrido et al., 2009a). Specific genus and species sets of primers and probes were designed for real-time PCR amplifications using TaqMan® chemistry technology. This system consists of a fluorogenic probe specific to the DNA target, which anneals to the target between the PCR primers; TaqMan® tends to be the most sensitive and simply methods for real-time PCR detection (Garrido et al., 2009a, 2011).

The specificity of all assays was tested using DNA from isolates of six species of *Colletotrichum* and from DNA of another nine fungal species commonly found associated with strawberry material. All the new assays were highly specific for *Colletotrichum* spp., *C. acutatum* and *C. gloeosporioides*, no cross-reactions were observed with either related plant pathogens or healthy strawberry plant material. The sensitivity of the new real-time PCR assays was compared with that of previously published conventional PCR assays; they were confirmed to be 100 times more sensitive than the latter. The *C. acutatum*-specific real-time PCR assay was also compared with an existing ELISA assay for the diagnosis of this pathogen. Real-time PCR permitted the detection of the pathogen in samples that gave negative results for *C. acutatum* using ELISA. The real-time PCR assay detected the equivalent of 7.2 conidia per plant inoculated with a serial dilution of *C. acutatum* spores, demonstrating the high degree of sensitivity of the method (Garrido et al., 2009a).

The new protocols were tested for monitoring the development of anthracnose disease in strawberry in the field in the south of Spain. The real-time PCR results showed a progressive increase of target DNA between January and June. The results showed that an increase in lesion development was accompanied by an increase in the amount and incidence of the pathogen as the season progressed. These results showed that new methods are suitable for diagnosis, identification and monitoring of the disease using field samples of strawberry and also, they permitted the detection of the pathogens from artificially infected symptomless plant material. Therefore, the methods described, based on real-time PCR, proved useful for studying the epidemiological routes of these strawberry pathogens in fields and nurseries (Garrido et al., 2009a, 2011).

#### **5. Proteomics approaches of phytopathogenic fungi**

In spite of the advances done by the described techniques above, nowadays proteomics is the most realistic and effective set of tools to unravel complex mixtures of proteins,

Molecular Microbiology Applied to the Study of Phytopathogenic Fungi 151

device. Then, the focused strips are used to load in a polyacrylamide gel, where the proteins are separated by their molecular weight. This system allows the separation of hundreds of proteins from a complex mixture. The gels are visualized with unspecific protein stains (those that stain total proteins, such as Coomassie, Sypro, Silver, etc.), or specific ones (those staining solution prepared to detect specific groups of proteins, mainly post-translationals modifications, i.e. Phospho ProQ diamond). The gels are digitalized and analyzed with specific software to reveal the significant spots. Those spots are identified using mass spectrometry. MALDI TOF/TOF is commonly used for 2DE approaches. The huge list of identified proteins obtained is studied to reveal the biological relevance of each

Unfortunately, the number of papers related to fungal proteomics is still poor compared with the application of this technology to other biological sources. As an example, a simple search in WOK website (web of knowledge, http://www.accesowok.fecyt.es/) get 809 entries when the terms "proteom\*"and "fung\*" are used, whereas 51237 entries are displayed when "proteom\*" is used alone. In spite of the numerical results obtained may vary depending of the used keywords and web resource, the fact is that there is a lot of work to do to bring fungal proteomic information at the same level that is obtained with other biological sources. This lack is mainly caused by (i) the difficulties to obtain proteins with enough quality to 2DE separations and (ii) the lack of protein sequences listed in the databases. Our research group was pioneer solving these problems and preparing the first proteomic approaches to the phytopathogenic fungi *Botrytis cinerea* (Fernández-Acero

Fungi posse strong cell walls. This makes difficult the cell breakage using standard protocols. Moreover, fungal proteins extract are characterised by its high concentration of glycosylated proteins that produces dense extracts, dragging a lot of impurities that disturb protein electrofocusing. We optimized a protocol based on a first phosphate buffer solubilisation followed by a typical TCA/Acetone precipitation. Using this protocol we developed the first proteomic map of *Botrytis cinerea* (Fernández-Acero et al., 2006b). Using this optimized approach we prepared a differential proteomics approach based on 2DE, comparing the proteomes of two *B. cinerea* strains differing in virulence (Fernández-Acero et al., 2007b). In spite of this protocol has been widely cited and used (Cobos et al., 2010; Fernández-Acero et al., 2010, 2011; Michielse et al., 2011; Moreira et al., 2011; Sharma et al., 2010; Yang et al., 2011), our recent data suggest that the phosphate buffer solubilisation produces an artificial enrichment of soluble proteins in our assayed extracts. For this reason, we improved our method using a phenol based protocol preparing a *Botrytis cinerea* map during cellulose degradation (Fernández-Acero et al., 2010). Based on this protocol, adding a previous step of precipitation with DOC, we developed the analysis of the main fungal subproteome, the secretome. We identified 76 secreted proteins from cultures where the virulence was induced with different plant-based elicitors (Fernández-Acero et al., 2010). New projects to unravel proteome content of *Botrytis cinerea* and *Colletotrichum acutatum* are

All the proteomic approaches developed on *B. cinerea* has been facilitated by the availability of fungal genome sequence (Amselem et al., 2011) (http://urgi.versailles.inra.fr/ Species/Botrytis, and http://www.broadinstitute.org/annotation/genome/botrytis\_ cinerea/Home.html). Summarizing all our identified spots, we do not get the 3% of the

identification.

et al. 2006).

running.

describing the current molecular biology age as "post-genomic era". The term proteome was coined in 1995 by Wilkins et al (Wilkins et al., 1995), later the term proteomics appeared by James et al. (James, 1997). Proteome is defined as the complete set of proteins expressed by an organism, in a particular biological state. Proteomics may be introduced as a set of techniques that allow to study and to describe the proteome. The impact of the proteomic approaches is mainly based in a group of widely used techniques such as liquid chromatography or two dimensional gel electrophoresis, to separate complex protein mixtures, defining the proteome. However, the increasing relevance of these studies has been pushed by the improvements done in mass spectrometry system, allowing the analysis of peptides and proteins and/or by the increase number of proteins entries in the databases, making easier protein analysis and identification.

Main proteome characteristic is that it is a high dynamic system. It is even more complex than genomics, due to while the genome of an organism is more or less constant, the number of obtained proteomes from a specific genome is almost infinite. It depends of the assayed cell, tissue, culture conditions, etc. Each change produces a modification in the observed proteome. An additional factor of complexity is that there are changes that occur in proteome that are not encoded in the genome. These changes are mainly based on two sources, (i) the editing of the mRNA and (ii) post-translational modifications (PTMs) that normally serve to modify or modulate the activity, function or location of a protein in different contexts physiological or metabolic. There are more than 200 different described PTMs (phosphorylation, methylation, acetylation, etc.). They transform each single gene into tens or hundreds of different biological functions. Before proteomics achievements, the differential analysis of the genes, that were expressed in different cell types and tissues in different physiological contexts, was done mainly through analysis of mRNA. However, for wine yeast it has been proved that there is no direct correlation between mRNA transcripts and protein content (Rossignol et al., 2006). It is known that mRNA is not always translated into protein, and the amount of protein produced by a given amount of mRNA depends on the physiological state of the cell. Proteomics confirms the presence of the protein and provides a direct measure of its abundance and diversity.

In terms of methodology, proteomics approaches are classified in two groups, (i) gel free systems, based in the use of different chromatography methods, and (ii) gel based methods, using mainly two dimensional polyacrylamide gel electrophoresis (2DE), that will be the core of our discussion. As a schematic summary, the typical workflow of a proteomic experiment begins with the experimental design. It must be deeply studied, and it will delimit the obtained conclusions, even more when comparison between two strains, cultures or physiological stages between others, are done. From an optimal point of view, only one factor must change between the different assayed conditions (Fernández-Acero et al., 2007a, 2007b). It must contain the use of different biological replicates depending of the used strategy, usually from 3 to 5. The next key step is to obtain a protein extract with enough quality to separate the complex mixture of proteins. Usually, the protein extraction is done in sequential steps (Garrido et al., 2010). First, the biological sample is disrupted using mechanical or chemical techniques. Then, proteins are precipitated and cleaned. Most of the protocol use acetone and trichloroacetic acid. During the next step the proteome is defined and visualized using electrophoretic techniques. 2DE has been widely used for this purpose. Using this technique proteins are separated using two different parameters. During the first dimension, proteins are separated by their isoelectric point using an isoelectrofocusing (IEF)

describing the current molecular biology age as "post-genomic era". The term proteome was coined in 1995 by Wilkins et al (Wilkins et al., 1995), later the term proteomics appeared by James et al. (James, 1997). Proteome is defined as the complete set of proteins expressed by an organism, in a particular biological state. Proteomics may be introduced as a set of techniques that allow to study and to describe the proteome. The impact of the proteomic approaches is mainly based in a group of widely used techniques such as liquid chromatography or two dimensional gel electrophoresis, to separate complex protein mixtures, defining the proteome. However, the increasing relevance of these studies has been pushed by the improvements done in mass spectrometry system, allowing the analysis of peptides and proteins and/or by the increase number of proteins entries in the databases,

Main proteome characteristic is that it is a high dynamic system. It is even more complex than genomics, due to while the genome of an organism is more or less constant, the number of obtained proteomes from a specific genome is almost infinite. It depends of the assayed cell, tissue, culture conditions, etc. Each change produces a modification in the observed proteome. An additional factor of complexity is that there are changes that occur in proteome that are not encoded in the genome. These changes are mainly based on two sources, (i) the editing of the mRNA and (ii) post-translational modifications (PTMs) that normally serve to modify or modulate the activity, function or location of a protein in different contexts physiological or metabolic. There are more than 200 different described PTMs (phosphorylation, methylation, acetylation, etc.). They transform each single gene into tens or hundreds of different biological functions. Before proteomics achievements, the differential analysis of the genes, that were expressed in different cell types and tissues in different physiological contexts, was done mainly through analysis of mRNA. However, for wine yeast it has been proved that there is no direct correlation between mRNA transcripts and protein content (Rossignol et al., 2006). It is known that mRNA is not always translated into protein, and the amount of protein produced by a given amount of mRNA depends on the physiological state of the cell. Proteomics confirms the presence of the protein and

In terms of methodology, proteomics approaches are classified in two groups, (i) gel free systems, based in the use of different chromatography methods, and (ii) gel based methods, using mainly two dimensional polyacrylamide gel electrophoresis (2DE), that will be the core of our discussion. As a schematic summary, the typical workflow of a proteomic experiment begins with the experimental design. It must be deeply studied, and it will delimit the obtained conclusions, even more when comparison between two strains, cultures or physiological stages between others, are done. From an optimal point of view, only one factor must change between the different assayed conditions (Fernández-Acero et al., 2007a, 2007b). It must contain the use of different biological replicates depending of the used strategy, usually from 3 to 5. The next key step is to obtain a protein extract with enough quality to separate the complex mixture of proteins. Usually, the protein extraction is done in sequential steps (Garrido et al., 2010). First, the biological sample is disrupted using mechanical or chemical techniques. Then, proteins are precipitated and cleaned. Most of the protocol use acetone and trichloroacetic acid. During the next step the proteome is defined and visualized using electrophoretic techniques. 2DE has been widely used for this purpose. Using this technique proteins are separated using two different parameters. During the first dimension, proteins are separated by their isoelectric point using an isoelectrofocusing (IEF)

making easier protein analysis and identification.

provides a direct measure of its abundance and diversity.

device. Then, the focused strips are used to load in a polyacrylamide gel, where the proteins are separated by their molecular weight. This system allows the separation of hundreds of proteins from a complex mixture. The gels are visualized with unspecific protein stains (those that stain total proteins, such as Coomassie, Sypro, Silver, etc.), or specific ones (those staining solution prepared to detect specific groups of proteins, mainly post-translationals modifications, i.e. Phospho ProQ diamond). The gels are digitalized and analyzed with specific software to reveal the significant spots. Those spots are identified using mass spectrometry. MALDI TOF/TOF is commonly used for 2DE approaches. The huge list of identified proteins obtained is studied to reveal the biological relevance of each identification.

Unfortunately, the number of papers related to fungal proteomics is still poor compared with the application of this technology to other biological sources. As an example, a simple search in WOK website (web of knowledge, http://www.accesowok.fecyt.es/) get 809 entries when the terms "proteom\*"and "fung\*" are used, whereas 51237 entries are displayed when "proteom\*" is used alone. In spite of the numerical results obtained may vary depending of the used keywords and web resource, the fact is that there is a lot of work to do to bring fungal proteomic information at the same level that is obtained with other biological sources. This lack is mainly caused by (i) the difficulties to obtain proteins with enough quality to 2DE separations and (ii) the lack of protein sequences listed in the databases. Our research group was pioneer solving these problems and preparing the first proteomic approaches to the phytopathogenic fungi *Botrytis cinerea* (Fernández-Acero et al. 2006).

Fungi posse strong cell walls. This makes difficult the cell breakage using standard protocols. Moreover, fungal proteins extract are characterised by its high concentration of glycosylated proteins that produces dense extracts, dragging a lot of impurities that disturb protein electrofocusing. We optimized a protocol based on a first phosphate buffer solubilisation followed by a typical TCA/Acetone precipitation. Using this protocol we developed the first proteomic map of *Botrytis cinerea* (Fernández-Acero et al., 2006b). Using this optimized approach we prepared a differential proteomics approach based on 2DE, comparing the proteomes of two *B. cinerea* strains differing in virulence (Fernández-Acero et al., 2007b). In spite of this protocol has been widely cited and used (Cobos et al., 2010; Fernández-Acero et al., 2010, 2011; Michielse et al., 2011; Moreira et al., 2011; Sharma et al., 2010; Yang et al., 2011), our recent data suggest that the phosphate buffer solubilisation produces an artificial enrichment of soluble proteins in our assayed extracts. For this reason, we improved our method using a phenol based protocol preparing a *Botrytis cinerea* map during cellulose degradation (Fernández-Acero et al., 2010). Based on this protocol, adding a previous step of precipitation with DOC, we developed the analysis of the main fungal subproteome, the secretome. We identified 76 secreted proteins from cultures where the virulence was induced with different plant-based elicitors (Fernández-Acero et al., 2010). New projects to unravel proteome content of *Botrytis cinerea* and *Colletotrichum acutatum* are running.

All the proteomic approaches developed on *B. cinerea* has been facilitated by the availability of fungal genome sequence (Amselem et al., 2011) (http://urgi.versailles.inra.fr/ Species/Botrytis, and http://www.broadinstitute.org/annotation/genome/botrytis\_ cinerea/Home.html). Summarizing all our identified spots, we do not get the 3% of the

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predicted genome. The method to capture new fungal proteins, its identification by mass spectrometry and to determine their biological relevance needs to be determined yet. By using our previous experience with *B. cinerea*, we are developing proteomic approaches to *C. acutatum*. Its conidial germination, mycelia dataset and secretome are characterized by 2DE. The key challenge is in our opinion, the use of the collected information to develop new methodologies to fight against plants pathogens. As a future prospect, the development of new environmental friendly proteomics-based fungicides has been discussed (Fernández-Acero et al., 2011).
