Gene expression in Fusarium graminearum grown on plant cell wall

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Fungal Genetics and Biology 45 (2008) 738–748 www.elsevier.com/locate/yfgbi

Gene expression in Fusarium graminearum grown on plant cell wall Raphae¨l Carapito a, Didier Hatsch b, Sonja Vorwerk c, Elizabet Petkovski d, Jean-Marc Jeltsch a, Vincent Phalip a,* a

U.M.R. 7175, Universite´ Louis Pasteur-CNRS, Ecole Supe´rieure de Biotechnologie de Strasbourg, Boulevard Se´bastien Brant, BP 10413, 67412 Illkirch-Graffenstaden, France b Biogemma S.A.S., 24 Avenue des Landais, Les Ce´zeaux, 63170 Aubie`re, France c febit biotech GmbH, Im Neuhenheimer Feld 519, 69120 Heidelberg, Germany d Institut de Me´decine Le´gale, Universite´ Louis Pasteur, 11 rue Humann 67085 Strasbourg, France Received 14 September 2007; accepted 3 December 2007 Available online 14 January 2008

Abstract Fusarium graminearum is a phytopathogenic filamentous fungus attacking a wide range of plants including Humulus lupulus (hop). Transcriptional analysis of F. graminearum grown on minimal media containing hop cell wall or glucose as the sole carbon source was performed by applying a highly stringent method combining microarrays and a subtracted cDNA library. In addition to genes coding for various cell wall degrading enzymes (CWDE), several metabolic pathways were induced in response to the plant cell wall substrate. Many genes participating in these pathways are probably involved in cellular transport. But the most interesting was that all the genes composing the 4-aminobutyrate-shunt (GABA-shunt) were also up-regulated in the presence of plant cell wall material and were present in the cDNA library. This study provides a description of a part of the fungal gene expression profile when it is in contact with raw biological materials, and helps in understanding the plant cell wall degradation and the infection process.  2007 Elsevier Inc. All rights reserved. Keywords: Gibberella zeae; Filamentous fungi; Humulus lupulus; Microarray; Suppressive subtractive hybridization; Subtracted cDNA library; Cell wall degrading enzymes; GABA-shunt; Transporters; Redox balance

1. Introduction The filamentous fungus Fusarium graminearum (teleomorph: Gibberella zeae) is a devastating phytopathogen with a broad host spectrum. It is one of the most important pathogens of cereals such as maize, wheat and barley, causing worldwide crop losses due to either pathogenesis (Munkvold, 2003) or food spoilage by its mycotoxins (Legzdina and Buersmayr, 2004). Several dicotyledons including Arabidopsis, tobacco, tomato and soybean were described as potential hosts of this fungus (Urban et al., 2002). Furthermore, diseased hop (Humulus lupulus) plants were repeatedly sources of virulent Fusarium species (Hatsch et al., 2002; Phalip et al., 2004). *

Corresponding author. Fax: +33 3 90 24 48 20. E-mail address: [email protected] (V. Phalip). URL: http://phytopathologie.u-strasbg.fr

1087-1845/$ - see front matter  2007 Elsevier Inc. All rights reserved. doi:10.1016/j.fgb.2007.12.002

Besides fundamental interests in host/pathogen interactions, the study of the F. graminearum/H. lupulus pair has various potential economic impacts such as the development of crop protection agents (Copping and Duke, 2007), the improvement of fungal hydrolases used in food, textile, pulp and paper industry (Subramaniyan and Prema, 2002; Polizeli et al., 2005) or biomass conversion for bioethanol production (Lynd et al., 2005; Gusakov et al., 2006; Service, 2007). The recently analyzed exoproteome of the fungus grown on a hop cell wall medium revealed the synthesis and secretion of a very diverse enzymatic arsenal composed of cell wall degrading enzymes (CWDE)1 able to almost completely 1

Abbreviations used: CWDE, cell wall degrading enzyme; GABA, 4aminobutyrate; GABAT, 4-aminobutyrate transaminase; GAD, glutamate decarboxylase; M3-CW, M3 medium with hop cell wall; M3-G, M3 medium with glucose; Orn-T, ornithine aminotransferase; SSADH, semialdehyde dehydrogenase.

R. Carapito et al. / Fungal Genetics and Biology 45 (2008) 738–748

digest the plant cell wall (Phalip et al., 2005). In the same environment, the expression of 30 xylanases, which degrade the highly abundant cell wall component xylan, were demonstrated by quantitative RT-PCR (Hatsch et al., 2006). Moreover, many CWDE activities were identified in supernatants of F. graminearum cultures grown on hop cell wall medium (Phalip et al., unpublished). All together, these results depict the great diversity and flexibility of the fungal enzymes used for the effective degradation of the plant cell wall. Although CWDE play a major role in substrate degradation and infection (Kang and Buchenauer, 2002), other cellular responses are probably induced by the presence of cell wall. In this context, a functional genomic study of F. graminearum grown on hop cell wall would be very informative. Microarrays (Schena et al., 1995) are one of the standard methods for the genome-wide analysis of transcriptional differences under a variety of environmental conditions. The first Fusarium microarray was a spotted chip containing 57 captures oligonucleotides and was used to identify Fusarium species that produce toxic compounds (Nicolaisen et al., 2005). Some microarrays were also designed for the study of sexual development of the teleomorph Gibberella zeae. An array harboring 291 spots was used for the validation of transcriptional alterations in the self sterile mat1-2 strain (Lee et al., 2006). Qi et al. (2006) report a higher density array bearing 2067 spotted cDNA clones corresponding to 1550 predicted Fusarium genes and used for the identification of genes important for perithecium development. With the apparition of the high density Fusarium Genechip from Affymetrix (Guldener et al., 2006), more comprehensive studies of fungal gene expression during sexual development could be done (Hallen et al., 2007). The Genechip technology also enabled the first transcriptional analysis of F. graminearum grown in different environmental conditions. This study provides lists of genes that are present in both the fungus that is grown in different carbon and nitrogen starvation conditions and during infection of barley. Unfortunately, no relative quantification of signal and no biological validation experiment by other methods than microarrays were performed (Guldener et al., 2006). Construction of cDNA libraries is another classical route to discover new sets of genes and to give information on their expression. Kruger et al. (2002) report the identification of F. graminearum pathology-related genes by screening a cDNA library from infected wheat. The major part (98%) of the library was composed of ESTs from the host plant and only 16 ESTs were found to correspond to fungal proteins implicated in pathology. To overcome this methodological bias in the field of pathogenesis, libraries were built from fungus grown on nitrogen and carbon starvation media, which may act as the environmental cue for disease development (Trail et al., 2003). A further improvement was the use of a suppressive subtractive hybridization protocol (Diatchenko et al., 1996), which allows the creation of cDNA libraries containing differentially expressed genes. This protocol was used to identify

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fungal genes expressed in presence of metal ions (Cuero and Ouellet, 2005) and to analyze the sexual development of G. zeae (Lee et al., 2006). The same method was recently applied for the identification of genes involved in pathogenicity (Goswami et al., 2006). The goal of the present study was to analyze the whole transcriptome of F. graminearum grown on hop cell wall in order to elucidate cellular processes induced by plant cell wall. In order to get highly reliable results, the two technical approaches presented above were independently applied. First, F. graminearum whole genome microarrays (febit biotech Biochip, febit biotech GmbH, Germany) experiments were performed to compare gene expression of F. graminearum grown on hop cell wall and on medium containing glucose. Secondly, a suppressive subtractive cDNA library based on Fusarium mRNA grown in the same two conditions was constructed and analyzed. In order to attain a high stringency, only the genes commonly identified with both experiments were analyzed and validated by real-time quantitative RT-PCR. Their roles in cellular response to the presence of plant cell wall are discussed. 2. Materials and methods 2.1. Biological material and culture conditions Fusarium graminearum (G. zeae) was originally isolated from diseased hops and identified by CABI Bioscience (United Kingdom). The method developed on maize by Sposato et al. (1995) was adapted for the preparation of hop cell wall. F. graminearum was cultured at 25 C on M3 medium (Mitchell et al., 1997) with either Glucose (M3-G) or hop cell wall (M3-CW) as sole carbon source at a concentration of 10 g l1. The cultures were prepared as previously described (Phalip et al., 2005; Hatsch et al., 2006) in 10 and 50 ml for the library and microarray experiment, respectively. The Escherichia coli strain TOP10 (F-mcrA D(mrr-hsdRMS-mcrBC) 80lacZDM15 Dlac 74 recA1 araD139 D(araleu) 7697 galU galK rpsL (StrR) endA1 nupG) (Invitrogen, USA) was used for all cloning procedures. 2.2. RNA extraction and sample preparation for microarray hybridization Total RNA extraction was performed with the RNaqueous-4PCR kit (Ambion, USA) according to manufacturer’s instructions. One microgram of RNA was used for biotin labelled cRNA synthesis with the MessageAmp II-Biotin Enhanced Single Round aRNA Amplification Kit (Ambion, USA) according to manufacturer’s instructions. 2.3. Probe and microarray design Oligonucleotide probes were synthesized by light-activated in situ oligonucleotide synthesis inside a Biochip of

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a Geniom instrument (febit biotech GmbH, Germany) (Guimil et al., 2003). The probe set was calculated from the full genome sequence using proprietary software of febit biotech based on a modified Smith–Waterman algorithm (Smith and Waterman, 1981). For each of the 11,639 predicted F. graminearum genes (http://www.broad. mit.edu), a 50mer oligonucleotide likely to hybridize with high specificity and sensitivity was synthesized. The Biochip consists of eight individually accessible micro-channels, each of which contains 6776 features and is referred to as array. The 11,639 probes corresponding to the whole genome were split over two arrays. 2.4. Array hybridization and detection Biotin-labeled cRNA was fragmented in 40 mM Tris (pH 8.1), 30 mM magnesium acetate, 100 mM potassium acetate at 94 C for 35 min. Prior to hybridization, free binding capacities were blocked with 100 mM 2-[N-morpholino]ethanesulfonic acid (MES), 0.9 M NaCl, 20 mM Na2EDTA, 0.01% (v/v) Tween 20, 1% BSA (Sigma– Aldrich, Germany) at room temperature for 15 min. Then 0.5 lg ll1 of fragmented biotin-labelled cRNA was hybridized to each array in the same buffer supplemented with 0.1 mg ml1 herring sperm DNA (Promega, USA). Hybridization was carried out at 55 C for 16 h, followed by a stringent washing step with 0.5 · SSPE (0.5 · 10 mM sodium phosphate buffer (pH 7.4), 150 mM NaCl, 1 mM EDTA) at 45 C. Fluorescence-staining was performed with 5 lg ml1 streptavidin–R-phycoerythrin-conjugate (Invitrogen, USA) in 6 · SSPE at 25 C for 15 min which was followed by a non-stringent wash with 6 · SSPE buffer at 25 C. Signal intensities were amplified by incubating the arrays with 3 lg ml1 biotinylated anti-streptavidin antibody (Vector Laboratories, USA) in 100 mM MES, 0.9 M NaCl, 0.05% Tween 20, 2 mg ml1 BSA, and 0.1 mg ml1 Goat IgG (Sigma–Aldrich, Germany) at 25 C for 15 min, followed by a non-stringent washing step, a SAPE incubation and a non-stringent washing step (conditions as described before). Detection and feature readout were performed using the CCD-based detection system of the Geniom device. 2.5. Microarray data-analysis Raw data were directly imported in the GeneSpring GX software (Agilent Technologies, USA), which was used for all post-processing steps. After background correction, the Robust Multi-Chip Average (RMA) algorithm was used to normalize and summarize probe-level intensities. The normalization used in RMA is quantile normalization (Bolstad et al., 2003). Intensities lower than 0.01 were set to 0.01. In order to be able to compare the expression values for each chip, per chip normalizations were performed by dividing each data set by the 50th percentile of all data sets. The intensities were further normalized per gene to the median of all replicates of both conditions tested to ensure that the

expression value for one gene across the different conditions is centred on 1. Therefore, a gene that is constantly expressed in the tested conditions gets a normalized expression value of 1. A list of differentially expressed genes was created by applying a parametric Student’s t-test with a Pvalue cut-off of 0.02 and a false discovery rate correction of 2% (Benjamini and Hochberg, 1995). The fold changes for the listed genes were then calculated and only those greater than +1.5 were analyzed. 2.6. Data interpretation To identify and characterize the detected proteins, their sequence were blasted (BLASTP) against the nr database (non-redundant GenBank CDS translations + PDB + SwissProt + PIR + PRF) (Altschul et al., 1997). Functional attributions were performed by analyzing the best non-hypothetical blast hit. The FunCat program (http:// mips.gsf.de/projects/funcat) of the Munich Information center for Protein Sequences was used to further examine the putative role of the proteins in the cellular metabolism (Ruepp et al., 2004). When multiple functional categories were proposed, the results were manually refined by choosing the one that was most in accordance with the blast hit. For enzymes, putative EC-numbers were determined using the Enzyme nomenclature database of the Expasy server (http://expasy.org/enzyme/). Each protein supposed to have an activity on carbohydrates was searched and analyzed through the carbohydrate-active enzymes classification (Coutinho and Henrissat, 1999). Finally, probable cellular localizations were predicted with the TargetP program (http://www.cbs.dtu.dk/services/TargetP/). 2.7. Preparation of subtracted library RNA were extracted with the RNeasy kit (Qiagen, Germany), and poly A + RNA were further purified with Oligotex mRNA kit (Qiagen, Germany). The subtracted library was constructed according to the PCR-Select cDNA Subtraction Kit (BD Biosciences, USA). Poly A + RNA extracted from the M3-CW culture was used as tester and poly A + RNA extracted from M3G as driver. The b-tubulin gene (AY303689) was used to estimate the relative enrichment of the library in a standard PCR experiment with the specific primers betatub-5 5 0 TGT TGA TCT CCA AGA TCC GTGAGG-3 0 and betatub-3 5 0 -GGT AGT TCA GGT CGC CGT AAG AGG-3 0 . The subtracted cDNA were cloned into ddTTP tailed HincII digested pUC19 and transformed into E. coli TOP10. 2.8. Sequencing and sequence analysis cDNA clones were purified with the R.E.A.L. prep 96 kit (Qiagen, Germany). Plasmids were sequenced with the BigDye terminator kit v1.1 (Applied Biosystems, USA), sequencing reactions were further purified with Autoseq 96 plate (Amersham Biosciences, USA), separated and

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read on an ABI prism 3100 apparatus (Applied Biosystems, USA). The Phragment assembly program (PHRAP) was used to assemble overlapping or repeated ESTs into contigs and singletons (Ewing et al., 1998). The six-frame translations of the sequences were blasted (BLASTX) against the nr database (non-redundant GenBank CDS translations + PDB + SwissProt + PIR + PRF) (Altschul et al., 1997). Sequences without any blast hit in the database and shorter than 300 bp were enlarged to 300 bp using related genomic sequences (AACM00000000) and blasted again. When no hit was found a larger region up to 4 kb was taken and searched for predicted proteins. If such a protein was identified, the 5 0 or the 3 0 untranslated region was aligned with the starting EST, and if they matched, the corresponding predicted protein sequence was used to identify the EST. The functions of the proteins generated from the EST dataset were attributed according to the F. graminearum predicted protein (Broad Institute) and to the functional assignment also performed by MIPS (http://mips.gsf.de/ genre/proj/Fusarium/). The functions of the ESTs that had not been assigned to any predicted protein were manually determined by BLAST analysis. 2.9. Validation of up-regulated genes through real-time quantitative RT-PCR First-strand cDNA was synthesized from 2 lg of DNase I treated RNA using the iScript cDNA synthesis kit (Bio-

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rad, USA) and following the recommendations of the manufacturer. RNAs used for real-time quantitative RT-PCR were isolated from F. graminearum cultures that were independent from those used in the microarray experiments and in the cDNA library construction. Real-time PCR was performed using a LightCycler instrument (Roche, Switzerland) in a final volume of 10 ll containing 0.2 ll of the reverse transcription reaction and 5 ll of the 2· QuantiTect SYBR Green PCR Master Mix (Qiagen, Germany) together with the specific forward and reverse primers at 0.5 lM (Sigma–Aldrich, USA). Primers were designed for the amplification of gene fragments from 83 to 127 bp (Table 1). Real-time PCR conditions were an initial denaturation at 95 C for 15 min, followed by 45 cycles of denaturing at 95 C for 15 s, annealing at 60 C for 20 s, and extension at 72 C for 20 s. Each cDNA was assayed in triplicate reactions. After amplification, a melting curve analysis was performed to verify the specificity of the reaction. Contamination with genomic DNA was excluded because no amplification could be obtained using a reverse transcriptase free cDNA synthesis reaction as template. The b-tubulin gene (FG09530) was used as an internal reference for calculating the normalized differences in threshold cycles (DDCT) between the two tested conditions, where DDCT = (CT,FGXXXXX  CT,FG09530)M3-CW  (CT,FGXXXXX  CT,FG09530)M3-G (Livak and Schmittgen, 2001). The calculation method was validated by testing the DCT for cDNA preparations diluted over 100-fold range. The slope of the

Table 1 Target-specific primers used for real-time quantitative RT-PCR

a

FG09530 FG01572 FG03247 FG03624 FG03695 FG03725 FG03969 FG04196 FG04431 FG04610 FG05352 FG05546 FG05574 FG06000 FG06452 FG06544 FG06619 FG06744 FG06751 FG07551 FG07631 FG09443 FG10231 FG10483 a b

Length (bp)b

Sequence 5 0 fi 3 0

Target

Forward

Reverse

TTGCATTGGTACACTGGTGAGG GGCCAATACTACCAGCTCATCC AACAAGGCCTACGGATCACTGG CTTCCGGTGCTCAGAAGAAGG GCATCAACCTCAAGGTCACTGG TGGTCGTCAATACCTCTTCATTGG TTTGCCCTAAGGGAACCTCT GCCGGATACTTCTTCTCCAAGG CAAGGATGCTCTCAAGGACTGG CGACCTCTCACCACTGGTATCG TCTTCCTCTGGACCATCACTGG TTGGTAACATGTTCCGTGATGG CTCAACATTCTCGCTCTCATCG GTTGCACGCACTCTATCAATGG GGCTACAAGGTCATCACCAACG CATGGCAGTATCCTTGCTCTGC CTCAGCCTCCTCGATATTCACG CCAAGGCAAGGAGAAGGTACG GTCGCTGGTCTTATCGTTGAGC GGCTCTCTTGGCCAGTACAAGG GATCAACATCAGCAGCAACTGG TGTTGAGGAGAAGACCACCTTCC CCAAGGCCACTGCTACTGATCC CTGTCTACATCGCCGAGATTGC

AGGCAGCTCCTCCTCGTACTCC CGAACGTTCTGACATGATGACG CTGTGCCGTACGTGTTCTTGG CGGACCAGTACTGCTGGAAGG TGCGTAGAGGTTGAAGAGAATGC TACCACCAGCGTTGGTAAGAGG CCTGAAGGGCATTCACACTT CGTAACCGCTCTCCTTGACACC GACAGACATGAGCTGAGCAACC GTAACCACACTTGCCACCAAGG GAAGATACCGAAGATCCAGACAGC CTTGAGGAGCAAGCACAGATCC TGCGAGTGCAGACCTTGTAACC CATCGAGAGCCTCGTCAATATCC GTGTTGACAGTGCTGGCATAGG CATCGGTCTTGTACCACTTGTCG AAGTGAGACGTGCCGATGTAGC TCCTTGCTGATGAGAGGTGAGG AACCAGTCTGGACCTCATCAGC AAGGTGACGTTGTCGATGAAGC GATGGTGAGAGCTTCCTCATGG AGAAGAGCCACCGTTGCTACC CAGATCCTTCCTTGTGGTCTCG AGTGTGGTCGGACATGTTGAGG

b-tubulin reference gene. Length of the amplified gene fragments.

110 115 105 87 127 111 117 126 98 125 124 126 83 127 116 97 122 114 127 126 124 121 115 110

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obtained straight line for the different primers was less than 0.13, indicating that the amplification efficiencies were approximately equal. 3. Results and discussion This study compares the transcriptional activity of F. graminearum grown on minimal media containing glucose (M3-G) or hop cell wall (M3-CW) as the sole carbon source in order to focus on fungal genes specifically responding to the plant cell wall. In the first experimental approach, a high density oligonucleotide Biochip was constructed using the Geniom system (febit biotech GmbH, Germany). The Biochip harboured four replicates of a probe-set representing the whole F. graminearum genome. Each set was split onto two arrays containing 5952 and 5687 oligonucleotides, respectively. Using this Biochip, the transcription levels of the 11,639 F. graminearum genes were analyzed. For each culture condition, two biological and two technical replicates were performed. A significance level of 0.02 was used to discriminate between significantly and non-significantly up-regulated genes. Based on this cut-off value, 143 genes were detected as up-regulated with fold changes greater than +1.5. In the second experimental approach, a differentially expressed cDNA library was created with the suppressive subtractive hybridization technique. The mRNA populations for the subtraction were obtained from F. graminearum grown on M3-G and M3-CW for the driver and tester, respectively. Subtraction efficiency was assessed by comparing the abundance of b-tubulin amplicons in subtracted and unsubtracted populations. A difference of 10 cycles was observed to obtain a similar amplification of the constitutively expressed b-tubulin target (Fig. 1.). This indicates that the enrichment of cDNA sequences resulting from the subtraction process was effective and in accordance with typical result for such experiments (PCRSelect cDNA Subtraction Kit user Manual). The transformation event generated roughly 10,000 transformants. A subset of 1056 randomly selected clones was grown and plasmids were prepared for sequencing. The sequences were trimmed of the vector and primer sequences. 963 sequences were deposited in dbEST

Fig. 1. Subtraction efficiency of the F. graminearum cDNA-library. Amplification of the b-tubulin at 18, 23, 28, and 33 cycles using the substracted and the unsubtracted cDNA population as matrix. The size of specific b-tubulin amplicon is 234 bp (arrow). M: molecular size marker.

(CV827489–CV828451). All the ESTs were found in the F. graminearum genome and analyzed with PHRAP (Ewing et al., 1998) in order to assemble contigs from the repeated and overlapping sequences. A total of 537 unique sequences (124 contigs and 413 singletons) were obtained. The average insert size was 357 ± 169 bp and only 21 sequences exhibited a polyA tail with a mean size of 26 ± 7 bp. The 537 ESTs sequences were blasted (BLASTX) against the nr database (non-redundant GenBank CDS translations + PDB + SwissProt + PIR + PRF). Non-overlapping ESTs could match to the same predicted protein of F. graminearum. This was the case for 169 ESTs corresponding to 73 predicted proteins. Consequently the number of unique mRNAs identified was 441. Array studies allow large screenings for detecting genes putatively involved in a specific function. Because of technological and biological variations of such studies, data validation using other experimental methods has become a general rule. In our case, the microarray assay was combined with the construction of a suppressive subtractive cDNA-library and only the genes commonly identified as up-regulated with both methods were analyzed. By comparing the two methods, a set of 23 predicted genes was detected to be significantly up-regulated in the cell wall condition, compared to the glucose condition. To further validate these data, the 23 genes were tested by real-time quantitative RT-PCR on cDNA synthesized from RNA of independent cultures. All the genes were confirmed to be up-regulated in the presence of plant cell wall material (Fig. 2.). Nevertheless, the magnitudes of expression levels did occasionally differ from those of the microarray experiments (Table 2). These differences could be explained by the position of the gene-specific probe on the mRNA or by hairpins in the biotin-labelled cRNA population, but they do not compromise the qualitative interpretation of the data discussed below. The genes were classified into five categories according to the blast results and the FunCat classification: CWDE, transporters, proteins involved in the GABA-shunt, redox balance enzymes and other proteins. 3.1. CWDE Five identified genes encode enzymes putatively involved in plant cell wall degradation. These putative CWDE are all predicted to be secreted by the TargetP program and show up-regulation factors ranging from 2.11 to 63.80 for FG09443 and FG03624, respectively (Table 2). This set of genes represents a large part of the identifications (22 %) and confirm the proteomic study revealing that when F. graminearum is grown on medium containing hop cell wall, it massively secretes CWDE (Phalip et al., 2005). The predicted CWDE correspond to five different EC numbers enabling to target each of the three main polysaccharide constituents of the cell wall. Predicted exopolygalacturonase (FG07551) and pectin methylesterase (FG09443) are enzymes acting on pectin (note that due

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Fig. 2. Real-time quantitative RT-PCR of 23 up-regulated F. graminearum genes. The b-tubulin gene (FG09530) was used as an internal reference. DDCT values correspond to the normalized differences in threshold cycles between the M3-CW and the M3-G condition. Following formula was used for calculation: DDCT = (CT,FGXXXXX  CT,FG09530)M3-CW  (CT,FGXXXXX  CT,FG09530)M3-G. Mean of three replicate experiments with standard deviations are shown.

to the high expectation value for FG09443 (3E-04), its putative function is less certain than those of the other proteins). Putative endoglucanase (FG03695) and xylanase (FG03624) are targeting cellulose and hemicellulose, respectively. Finally, predicted polysaccharide deacetylase (FG06452) is an enzyme involved in the cleavage of acetyl substituents in various polysaccharide components of the cell wall. Such a mobilization is probably a way of gaining energy through complete degradation of the cell wall. 3.2. Transporters This is the most quantitatively important category with seven predicted transmembrane transporters: FG03725, FG04431, FG04610, FG05352, FG05574, FG06410, and FG07631. Six of them belong to the Major Facilitator Superfamily (MFS). This family represents single polypeptide secondary carriers that are capable of transporting small solutes in response to chemiosmotic ion gradients (Pao et al., 1998). Depending on the system or conditions, such transporters can function by uniport, solute–solute antiport or solute–cation symport. As deduced from the blast hit results, the compounds putatively transported by the seven corresponding proteins are sugars, quinate, amino acids, drugs and nicotinic acid. These predicted transporter genes are highly up-regulated with fold changes ranging from 4.13 to 101.40 (Table 2). The two putative hexose transporters FG05352 and FG07631, which show a 12.21 and 101.40-fold change, respectively, play most likely a role in the internalization of the CWDE enzymes producing C-6 sugars. Maltose is a degradation product of starch, which was reported to be present in hop cell wall medium (Phalip et al.,

2005). The up-regulation of a maltose transporter (FG04610) can therefore be correlated to a probable utilization of this molecule by the fungus. This hypothesis is confirmed by the presence of starch degrading activities in supernatants of F. graminearum cultures on hop cell wall medium (Phalip et al., unpublished). Quinate is used in the aromatic amino acid synthesis pathway and is found in many different plants (Hawkins et al., 1993). As suggested by the 10.21-fold up-regulation of the predicted quinate transporter FG10483, this molecule is most likely used as a supplementary carbon-source by F. graminearum. FG05574 is predicted to be an amino acid permease and its corresponding gene is up-regulated 4.13-fold. This highlights the importance of nitrogen mobilization during grows on hop cell wall. The usefulness of the identified multidrug (FG03725) and nicotinic acid transporter (FG04431), which are 8.46 and 4.99-fold up-regulated, respectively is more elusive. Many secondary metabolites like mycotoxins or antibiotics would be toxic to the microorganisms that produce them if they had no protecting mechanisms. Accordingly, as F. graminearum is a toxin-producing phytopathogenic fungus (Pitt, 2000), it has to protect itself from such compounds too. A possible way of doing that would be comparable to that of Fusarium sporotrichioı¨des which uses an efflux pump to protect itself against trichothecenes (Alexander et al., 1999). Nicotinic acid is a precursor of nicotinamide adenine dinucleotide (NAD+), which holds a key position in metabolism and cellular regulatory events as a major redox carrier and a signalling molecule. Higher availability of NAD+ would be a consequence of the import of nicotinic

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Table 2 Predicted proteins corresponding to the up-regulated genes in F. graminearum grown on hop cell wall medium FG-number

Fold changesa

P-valueb

Blast hits Description

Protein-Acc

e-value

ECc

Cazyd

Cellular localizatione

3.2.1.8

GH11

Sec. Path.

3.2.1.4 3.1.1.58

GH61 CE4

Sec. Path. Sec. Path.

CWDE FG03624

63.80

4.8E-7

Xylanase 15 [Gibberella zeae]

AAT84254.1

1.0E-133

FG03695 FG06452

4.14 4.87

5.1E-7 8.4E-4

XP_001264507.1 XP_751832.1

6.0E-59 1.0E-34

FG07551

46.20

4.3E-6

BAE97056.1

0.0E+0

Polysaccharide metabolism

3.2.1.67

GH28

Sec. Path.

FG09443

2.11

5.1E-4

Endoglucanase [Neosartorya fischeri] Polysaccharide deacetylase family protein [Aspergillus fumigatus] Exopolygalacturonase [Fusarium oxysporum] Pectin methylesterase [Aspergillus fumigatus]

Sugar glucoside polyol and carboxylate metabolism Polysaccharide metabolism Polysaccharide metabolism

XP_747054.1

3.0E-4

n.k.

3.1.1.11

CE8

Sec. Path.

Transporters C-transport FG04610

5.31

3.3E-3

XP_746441.1

0.0E+0

12.21

9.3E-5

XP_001258822.1

0.0E+0

FG07631

101.40

5.5E-4

XP_001258822.1

1.0E-168

FG10483

10.21

1.3E-3

XP_746358.1

0.0E+0

C-compound and carbohydrate transport C-compound and carbohydrate transport C-compound and carbohydrate transport C-compound and carbohydrate transport

Transmbe

FG05352

MFS maltose transporter [Aspergillus fumigatus] MFS hexose transporter [Neosartorya fischeri] MFS hexose transporter [Neosartorya fischeri] MFS quinate transporter [Aspergillus fumigatus]

N-transport FG05574

4.13

1.0E-2

Amino acid permease [Glomus mosseae]

AAX81451.1

0.0E+0

Cellular transport

Transmbe

Others FG03725

8.46

2.8E-6

XP_001268875.1

0.0E+0

Cellular export and secretion

Transmbe

FG04431

4.99

3.6E-3

MFS multidrug transporter [Aspergillus clavatus] MFS nicotinic acid transporter Tna1 [Aspergillus clavatus]

XP_001273552.1

1.0E-112

Cellular import

Transmbe

GABA-shunt FG01572

3.06

2.5E-3

XP_001228383.1

0.0E+0

Stress response

4.1.1.15

n.k.

FG04196

1.55

2.0E-2

XP_001258927.1

0.0E+0

Stress response

1.2.1.16

n.k.

FG05546

6.09

9.5E-3

XP_001240799.1

1.0E-175

n.k.

2.19

1.1E-7

XP_001258998.1

0.0E+0

Nitrogen and sulfur metabolism Secondary metabolism

2.6.1.13

FG06751

Glutamate decarboxylase [Chaetomium globosum] Succinate semialdehyde dehydrogenase [Neosartorya fischeri] Ornithine aminotransferase [Coccidioides immitis RS] 4-aminobutyrate aminotransferase [Neosartorya fischeri]

2.6.1.19

n.k.

Transmbe Transmbe Transmbe

R. Carapito et al. / Fungal Genetics and Biology 45 (2008) 738–748

Funcat

n.k.

3.4E-3 2.2E-3 1.1E-4 7.78 25.84 3.01

3.85

FG03969 FG06000 FG06544

FG06744

1.2E-3

4.2E-5 Other metabolisms FG03247 2.20

3.3. GABA-shunt Abbreviations: n.k., not known; Protein-Acc, protein accession number; e-value, expectation value; Transmbe, transmembrane; Sec. Path., secretory pathway; Mito., mitochondrial. a Microarray measured gene expression fold changes in the M3-CW condition compared to the control condition M3-G. b P-values were determined with a parametric Student’s t-test. c Enzyme classes predicted with the enzyme nomenclature database of the expasy server (http://expasy.org/enzyme/). d Predicted carbohydrate-active enzymes class (Coutinho and Henrissat, 1999). e Probable cellular localization predicted with the TargetP program (http://www.cbs.dtu.dk/services/TargetP/).

3.3.2.10 Detoxification by modification 4.0E-77

0.0E+0 XP_001267704.1

XP_001275970.1

2.0E-26

2.7E-5 2.24 FG10231

EGF repeat molecule [Aedes aegypti] Unknown protein Cystathionine beta-synthase [Aspergillus clavatus] Epoxide hydrolase [Aspergillus clavatus]

EAT40028.1

Nitrogen and sulfur metabolism

4.2.1.22

n.k.

Sec. Path.

n.k. 2.7.1.30

C-compound and carbohydrate metabolism n.k. 0.0E+0 XP_001257963.1

2.6E-4

Glycerol kinase [Neosartorya fischeri]

Mito. 1.6.5.3 Energy 1.0E-112 XP_367376.2

745

acid (FG04431) and could contribute to improve the metabolization of the internalized compounds.

Redox balance FG06619 3.27

NADP-dependent alcohol dehydrogenase VI [Aspergillus terreus] NADH-ubiquinone oxidoreductase 24 kDa subunit [Magnaporthe grisea]

XP_001213912.1

1.0E-132

Energy

1.1.1.2

n.k.

R. Carapito et al. / Fungal Genetics and Biology 45 (2008) 738–748

The four genes coding for proteins FG01572, FG04196, FG05546, and FG06751 constitute the metabolic pathway called GABA-shunt (Balazs et al., 1970). Their respective fold changes are 3.06, 1.55, 6.09, and 2.19 (Table 2). To our knowledge, it is the first time that all the enzymes involved in this pathway are concomitantly identified in response to a specific environmental condition in filamentous fungi. The GABA-shunt is a bypass to the TCA cycle, where 2ketoglutarate is aminated to form glutamate rather than being oxidatively decarboxylated to succinate. Glutamate is then decarboxylated to form 4-aminobutyrate (GABA), which is in turn transaminated to succinate semialdehyde. Finally, the shunt is ended by the oxidation of succinate semialdehyde to succinate. This shunt was first reported by Balazs et al. (1970) in human brain tissue where it represents about 10% of the total flux of the TCA-cycle. Using the present results, a model of the F. graminearum GABA-shunt is proposed in Fig. 3. The predicted enzymes involved in this bypass could be an ornithine aminotransferase (orn-AT, FG05546), a glutamate decarboxylase (GAD, FG01572), a 4-aminobutyrate transaminase (GABAT, FG06751) and a succinate semialdehyde dehydrogenase (SSADH, FG04196). Although the existence of the GABA-shunt is incontestable in filamentous fungi, its function remains unclear in

Fig. 3. GABA-shunt model in F. graminearum Orn-T, ornithine aminotransferase; GAD, glutamate decarboxylase; GABAT, 4-aminobutyrate transaminase; SSADH, semialdehyde dehydrogenase.

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most of the studied fungal systems. Some filamentous fungi are able to utilize GABA as a nutrient source (Kumar and Punekar, 1997). Moreover, GABA was reported to be a major nitrogen source during infection of tomato by Cladosporium fulvum, in the course of which GABAT and SSADH activities are induced (Solomon and Oliver, 2001). As already indicated by the up-regulation of the gene encoding FG05574, it is probable that in the tested condition F. graminearum needs a supplementary nitrogen source to be able to grow. It is known that the activation of the shunt is associated to citrate production in both Aspergillus niger (Kumar et al., 1999) and Fusarium oxyporum (Panagiotou et al., 2005). In plants GAD is activated by acidic pH (Snedden et al., 1995; Snedden et al., 1996) and GABA accumulates in response to cytosolic acidification (Shelp et al., 1999). Another possible role is related to the first described neurotransmitter function in animals, namely the production of GABA as a communication molecule. A few processes involving signalling pathways could be attributed to GABA. In Trichoderma viride, the latter was shown to be involved in sporulation (Strigacova et al., 2001), in yeast, GABA metabolism is a key contributor to the ability of cells to tolerate oxidative stress (Coleman et al., 2001) and in plants it may modulate quorum sensing of infecting bacteria (Chevrot et al., 2006). Considering that the shunt is specifically activated when F. graminearum grows on hop cell wall, GABA may play a signalling role in the induction of fungal enzymes responsible for the degradation of plant cell wall as suggested by Shelp et al. (2006) in the communication between plants and fungi. This hypothesis is confirmed by the fact that in Trichoderma reesei, increased production of cellulases is negatively correlated with the ability to grow on GABA, indicating that GABA is more used as a cellulase producing agent than as a nutrient source (Druzhinina et al., 2006). 3.4. Redox balance FG06619 and FG10231 are two proteins, which coding genes are 3.27- and 2.24-fold more represented on M3-CW than on M3-G, respectively, and are characterized by a high homology with oxidoreductases possibly involved in the maintenance of redox balance (Table 2). Keeping a cytosolic redox balance is a prerequisite for living cells in order to maintain a metabolic activity and enable growth. In this context, the relative concentrations of the redox couples NAD+/NADH and NADP+/ NADPH is primordial. Contrary to glucose, metabolization of the various CWDE products involve more enzymatic reactions and need higher quantities of NAD+ and NADP+. Up-regulation of the genes encoding FG06619 and FG10231 may therefore be a compensating response to the depletion of the reduced forms. Moreover, as an insertion in a gene predicted to code for a NADH:ubiquinone oxidoreductase provoked a reduced virulence of F. graminearum (Seong et al., 2005),

NADH:ubiquinone oxidoreductase may be also related to pathogenesis.

3.5. Others Five functionally unclassified proteins were also identified in both microarrays and cDNA-library experiments. One of them (FG06000) has no known homologue in the sequence databases. FG03247 and FG06544 are predicted to be involved in carbon and nitrogen metabolism, respectively. These metabolisms must be important for the fungus to grow on hop cell wall, but no clear hypothesis can be made on their specific role in the process yet. FG03969 is a putative protein containing epidermal growth factor (EGF) repeats, indicating signalling activities in the fungus. Finally, FG06744 is a protein showing highest homology to an epoxide hydrolase which may be involved in detoxification or in biosynthesis of a metabolite.

4. Conclusion Microarrays and subtractive cDNA-library give a specific insight in the transcriptome of F. graminearum grown on minimal medium containing hop cell wall. Changing the carbon source from glucose to cell wall material caused changes in expression of genes other than those involved in cell wall degradation. Classically nutrient starvation is known to induce gene related to pathogenesis (Trail et al., 2003). The genes identified in this study suggest that when grown on plant cell wall, the fungus switches not only to a metabolism linked to carbon starvation, but also to a growth where several genes associated with other processes like cellular transport, GABA-shunt and redox balance are up-regulated. These events are most likely to happen in F. graminearum during the infection of hop plants. Thus, the use of such a medium to study the fungus by mimicking part of its interaction with a plant should be considered as a valuable tool to characterize the interactions with the host on the pathogen side. Based on the presented gene set, further studies involving specific in vivo deletion will be performed in order to understand better the role of each gene in host/pathogen interactions.

Acknowledgments This work was supported by the Cophoudal (Brumath, France) and the Agence de De´veloppement Agricole et Rural (ADAR). Didier Hatsch was funded by a Ph.D. fellowship from the Region Alsace. Anne Forster is greatly acknowledged for her technical competence. We are very grateful to Julia Klopotek for critical reading of the manuscript. We thank Professor Bertrand Ludes, his team and CODGENE SA. (Strasbourg, France) for great help in the sequencing of the EST library.

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