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Keywords:

  • filamentous fungus;
  • pathogen;
  • cell wall degradation;
  • microarray;
  • plant biomass;
  • biomass valorization

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results and discussion
  6. Conclusion
  7. Acknowledgements
  8. References
  9. Supporting Information

We report a genome-wide transcriptomic study of Fusarium graminearum grown on four different substrates based on plant cell wall components. About 5% of the genes were differentially expressed in at least one condition. Analysis of upregulated cell wall-degrading enzymes highlights a sharp growth medium-specific adaptation process. In particular, the nature of the polysaccharides available for fungal growth induced a specific transcriptional response aiming at the targeted enzymatic degradation of the given polysaccharides.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results and discussion
  6. Conclusion
  7. Acknowledgements
  8. References
  9. Supporting Information

Fusarium graminearum (teleomorph: Gibberella zeae) is a devastating pathogenic fungus causing regularly worldwide crop losses by pathogenesis or food contamination with mycotoxins (Munkvold, 2003; Legzdina & Buersmayr, 2004). This fungus is able to adapt itself to many different hosts and environmental conditions. It is an important pathogen of cereals such as maize, wheat, or barley, but also of dicotyledons including tobacco and tomato, and was repeatedly isolated from hops (Hatsch et al., 2002; Urban et al., 2002). Several transcriptomics studies focusing mainly on phytopathology, fungal development, or mycotoxins have been reported (Nicolaisen et al., 2005; Qi et al., 2006; Golkari et al., 2007; Stephens et al., 2008). Cell wall-degrading enzymes (CWDE) produced by F. graminearum are key factors for the infection process (Kang & Buchenauer, 2002; Lynd et al., 2008; Phalip et al., 2009), but are also of high economic interest in various industrial fields such as bioplastics or biofuels. Understanding plant/Fusarium interactions could contribute to the development of environmental-friendly solutions to combat fungal pathogens as well as to improve biomass valorization processes.

Here, we report a transcriptomic analysis of F. graminearum grown on four different media containing varying polysaccharides, using a whole-genome microarray covering the totality of the 11 639 predicted genes (febit holding, Germany). The four conditions were minimal M3 medium supplemented with xylan (M3-X), cellulose (M3-CMC), hop cell wall (M3-CW), and glucose (M3-G) as sole carbon sources at 10 g L−1.

Materials and methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results and discussion
  6. Conclusion
  7. Acknowledgements
  8. References
  9. Supporting Information

Raw material

Fusarium graminearum was cultured as previously described (Phalip et al., 2005), and hop cell wall was prepared using the method developed by Sposato et al. (1995).

Microarray experiments

After total RNA extraction and biotin-labeled cRNA synthesis, microarray experiments were achieved with two biological and two technical replicates for each tested condition (Carapito et al., 2008). Results of the microarray experiments were deposited in the GEO database (http://www.ncbi.nlm.nih.gov/geo/), under the accession number (GEO: GSE29973). Raw data were analyzed with the GeneSpring GX software (Agilent Technologies, USA). After informatics processing steps (Carapito et al., 2008), all gene expression data from the M3-X, M3-CMC, and M3-CW conditions were compared with the control condition M3-G. A list of differentially expressed genes was generated by applying a parametric Student's t-test with a P-value cutoff of 0.01 and a false-discovery rate correction of 1% (Benjamini & Hochberg, 1995). Only genes with fold changes > 2 were considered. For functional classification of the proteins corresponding to detected genes, sequences were blasted (NCBI blastp v2.2.10) against the nr database (nonredundant GenBank CDS translations + PDB + SwissProt + PIR + PRF) (Altschul et al., 1997), and the best nonhypothetical hit was analyzed. Genes were classified in following functional categories: CWDE, transporters, oxidoreductases, regulatory genes, proteases, signaling, GABA shunt, cellular architecture, metabolism, stress, toxins, defense/detoxification, iron related, unknown/others. The Functional Catalogue (http://mips.helmholtz-muenchen.de/proj/funcatDB/) was systematically browsed to validate and further examine the putative role of the predicted proteins (Ruepp et al., 2004). When multiple functional categories were proposed, the results were manually refined and the category that was most in accordance with the blast hit was chosen. To determine the targets of the CWDE, each enzyme was searched and analyzed through the carbohydrate-active enzymes classification (http://www.cazy.org/) (Cantarel et al., 2009).

Validation of microarray data

Real-time quantitative RT-PCR was used to validate the microarray data. Reactions were performed as previously described (Carapito et al., 2008). The ΔΔCt quantification method was used to evaluate variations in the tested culture conditions (Livak & Schmittgen, 2001), and the amplicon of the β-tubulin gene (FG09530) was used as an internal control. Selected genes and primers used for their amplification were as follows: 5′-TTGCATTGGTACACTGGTGAGG-3′ and 5′-AGGCAGCTCCTCCTCGTACTCC-3′ for FG09530, 5′-TCACTCAGCACTCTTGCACTGG-3′ and 5′-CCAGATCCAGGACCGTAGAAGG-3′ for FG00571, 5′-CCACTACTCTCCGTTGGTCAGC-3′ and 5′-GAGGAAGACAGTTCGCCAAGG-3′ for FG00721, 5′-GAGCCAGGCAGATATGAGTTCG-3′ and 5′-AATTGAGGTTGGTCGCGTTAGC-3′ for FG01029, 5′-CGAGACTCTCAAGGCGATCTGG-3′ and 5′-TATCGTCTCTCCTGCGTTGTCC-3′ for FG01685, 5′-CCTCTCTCTGTCTACCTCAGCAAGG-3′ and 5′-GACTGGCCGTTCATGTAGTTGG-3′ for FG03968, 5′-TGTCTTCGAGTTCGACACAGAGG-3′ and 5′-CTGTGTTGGCACCAACCATACC-3′ for FG04196, 5′-CCTCGATTCCTCATCAACAAGG-3′ and 5′-GTAGAGCTGTCGGCTGAGATGG-3′ for FG05352, 5′-CTGTCCACAAGCTCGACATTCC-3′ and 5′-AGTGCCATGTGGTCATGATACG-3′ for FG06751.

Results and discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results and discussion
  6. Conclusion
  7. Acknowledgements
  8. References
  9. Supporting Information

Analysis of expression profiles on different media

When comparing expression profiles of F. graminearum grown on M3-X, M3-CMC, and M3-CW with the control condition M3-G, a total of 571 genes were identified as differentially expressed (Supporting Information, Table S1). Among these, 277 genes were up- and 294 genes were downregulated. One hundred and fifty, 124, and 52 genes were upregulated on cellulose, cell wall, and xylan, respectively. For the downregulated genes, 197, 106 and 61 were specific to cellulose, cell wall, and xylan, respectively. Interestingly, even though cellulose displays the simplest molecular structure, M3-CMC was the medium inducing and repressing the highest number of genes (Fig. 1). This could be explained by the fact that glucose – key metabolic compound – is the degradation product of cellulose. The high number of differentially expressed genes on M3-CMC may therefore reveal a complex balanced regulation of cellulose utilization and glucose-induced catabolic repression. Functional categorization of differentially expressed genes (Fig. 2) reveals that the highest number of up- and downregulated genes on M3-CMC belongs to regulatory (49 genes) and metabolic (58 genes) functions, respectively. This observation is consistent with a complex regulation system and metabolization process of a low-complexity sugar.

image

Figure 1. Differentially expressed genes of F. graminearum. The diagram shows the number of genes differentially expressed (P-value < 0.01; fold change > 2) in the three conditions M3-CW, M3-CMC, and M3-X compared with the control M3-G. Gray bars represent the proportion of genes that are differentially expressed with a minimum fold change of 5.

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image

Figure 2. Functional categorization of differentially expressed genes. blastp analyses were used to categorize differentially expressed genes by biological processes. A positive value means more, while a negative value indicates less differentially expressed genes in the tested conditions compared with the control condition M3-G.

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Corroborating previous studies on the protein level (Phalip et al., 2005; Paper et al., 2007), a high number of CWDE aiming at the hydrolysis of polysaccharides were upregulated: 26, 20, and 7 CWDE genes were upregulated on M3-CW, M3-CMC, and M3-X, respectively (Fig. 2). This represents 21, 13, and 13% of the upregulated genes for M3-CW, M3-CMC, and M3-X, respectively, whereas all the CWDE-coding genes represent only 0.5% of the genome. These values reveal a massive mobilization of CWDE by the fungus in presence of different carbon sources to properly degrade them. Fig. 2 also shows significant changes in the regulation of many genes from transporters, regulatory and metabolism categories, which is in line with CWDE expression and indicates a clear metabolic reorientation toward polysaccharides degradation. Detailed lists of genes and functional categories are available as Supporting Information (Table S2).

Functional categorization of CWDE

Proteins corresponding to upregulated CWDE genes were classified on the basis of their predicted target in the cell wall (Fig. 3). The three main polysaccharidic cell wall components being pectin, hemicellulose, and cellulose, the proportions of pectinases, hemicellulases, and cellulases genes were analyzed. The M3-CW medium contained all three polysaccharides, and xylan is the main component of hemicellulose. An equivalent quantity of genes coding for enzymes targeting the three analyzed polysaccharides were upregulated on M3-CW. This means that in the presence of plant cell wall, the fungus implements an enzymatic system which in fine is able to degrade the three major components of the primary cell wall. This result is remarkably in accordance with results found at the proteomic level (Phalip et al., 2005). A majority of cellulases (80%) and hemicellulases (70%) were overexpressed on M3-CMC and M3-X, respectively. Thus, the proportion of genes potentially coding for pectin, hemicellulose, and cellulose-degrading enzymes correlated well with the presence of these polymers in the tested substrates (Fig. 3). This observation reveals a highly specific adaptation of the fungus to its environment. It appears that there is no general transcriptional signature for the presence of plant biomass, but rather several signatures each specific for the different polysaccharides used in this study. Due to the high energy needed for production of extracellular enzymes in large quantities, F. graminearum produces only CWDE that are needed to degrade the polymer on which it is growing.

image

Figure 3. Polysaccharidic targets of upregulated cell wall-degrading enzymes. (a) Structure of the plant cell wall with its major molecular components. (b) Proportion of each upregulated CWDE targeting pectin, cellulose, and hemicellulose after growth in the three conditions.

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Validation of the study

To validate this study, a representative subset of genes was tested through quantitative real-time RT-PCR (Fig. 4). The chosen genes yielded consistent results with the microarray results, indicating that the microarray data have been validated by the qRT-PCR method.

image

Figure 4. Comparison of gene expression profiles across four conditions determined by microarrays and RT-PCR experiments. These eight genes were chosen for RT-PCR analysis because they were differentially expressed with various fold changes in various conditions. The β-tubulin gene (FG09530) was used as reference gene. CT values normalized to the β-tubulin gene [CT(FGxxxx)/CT(FG09530)] are represented on the right axis (plain lines). Microarray data are represented on the left axis (dotted lines): the intensities were normalized per gene to the median of all replicates of the four conditions tested to ensure that the expression value for one gene across the different conditions is centered on 1. Mean of four replicate experiments are shown.

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Conclusion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results and discussion
  6. Conclusion
  7. Acknowledgements
  8. References
  9. Supporting Information

This study provides a significant view of the biology of F. graminearum in the presence of different polysaccharides from primary plant cell wall. Transcriptional responses to tested conditions consolidate previous observations, and the predicted functions are biologically relevant with respect to the different substrates. Altogether, in addition to a better comprehension of plant–fungus interactions, these data should allow to set up new strategies for complete industrial cell wall degradation by a more rational design of growth media capable of fine-tuning the required enzymatic activities. Biofuel and chemical production by biotechnology are the two major fields concerned by the results presented here.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results and discussion
  6. Conclusion
  7. Acknowledgements
  8. References
  9. Supporting Information

This work was funded by the Centre National de la Recherche Scientifique (CNRS, France) and febit holding GmbH (Heidelberg, Germany). Kerstin Ganter is greatly acknowledged for her technical competence. We are very grateful to Cophoudal (France) for supplying the raw hop material.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results and discussion
  6. Conclusion
  7. Acknowledgements
  8. References
  9. Supporting Information

Supporting Information

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results and discussion
  6. Conclusion
  7. Acknowledgements
  8. References
  9. Supporting Information
FilenameFormatSizeDescription
fml12079-sup-0001-TableS1.pdfapplication/PDF1182KTable S1. Overview of the 571 differentially expressed genes classified by expression levels (first part) and by ID (second part).
fml12079-sup-0002-TableS2.pdfapplication/PDF611KTable S2. Functional classification of the differentially expressed genes.

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