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Eutypa dieback is a vascular disease that may severely affect vineyards throughout the world. In the present work, microarrays were made in order (i) to improve our knowledge of grapevine (Vitis vinifera cv. Cabernet-Sauvignon) responses to Eutypa lata, the causal agent of Eutypa dieback; and (ii) to identify genes that may prevent symptom development. Qiagen/Operon grapevine microarrays comprising 14500 probes were used to compare, under three experimental conditions (in vitro, in the greenhouse, and in the vineyard), foliar material of infected symptomatic plants (S+R+), infected asymptomatic plants (S–R+), and healthy plants (S–R–). These plants were characterized by symptom notation after natural (vineyard) or experimental (in vitro and greenhouse) infection, re-isolation of the fungus located in the lignified parts, and the formal identification of E. lata mycelium by PCR. Semi-quantitative real-time PCR experiments were run to confirm the expression of some genes of interest in response to E. lata. Their expression profiles were also studied in response to other grapevine pathogens (Erysiphe necator, Plasmopara viticola, and Botrytis cinerea). (i) Five functional categories of genes, that is those involved in metabolism, defence reactions, interaction with the environment, transport, and transcription, were up-regulated in S+R+ plants compared with S–R– plants. These genes, which cannot prevent infection and symptom development, are not specific since they were also up-regulated after infection by powdery mildew, downy mildew, and black rot. (ii) Most of the genes that may prevent symptom development are associated with the light phase of photosynthesis. This finding is discussed in the context of previous data on the mode of action of eutypin and the polypeptide fraction secreted by Eutypa.
Eutypa dieback is a wood decay disease found in all grape-growing areas, which can be very damaging (Munkvold et al., 1994; Wicks et al., 1999; Creaser et al., 2001). Eutypa dieback is caused by the vascular ascomycete fungus Eutypa lata (Moller and Kasimatis, 1978). After initial infection by the fungus, a lag phase of several years is often observed before the appearance of symptoms (Duthie et al., 1991; Tey-Ruhl et al., 1991) whose intensity on a given plant may vary with each year (Creaser et al., 2001). Symptoms of Eutypa dieback include stunting of growing shoots after bud break, with small, cupped, chlorotic, and tattered leaves, reduced development of fruit clusters, and characteristic dark, wedge-shaped necrosis of the trunk and cordons (Lecomte et al., 2000; Mahoney et al., 2003). Leaf symptoms are due both to toxins (Mauro et al., 1988; Tey Rulh et al., 1991; Deswarte et al., 1996; Molyneux et al., 2002; Mahoney et al., 2003; Smith et al., 2003) and to cell wall-degrading enzymes (English and Davis, 1978; Elghazali et al., 1992; Schmidt et al., 1999; Rolshausen et al., 2008) produced by the fungus in the wood (Bernard and Mur, 1986). Variations of disease expression may also depend on cultivar susceptibility (Péros and Berger, 1994; Sosnowski et al., 2007). Among the most cultivated grapevine cultivars, Cabernet-Sauvignon is particularly susceptible to Eutypa dieback (Peros and Berger, 1994). There is no known resistant cultivar (Boubals, 1986; Mauro et al., 1988; Munkvold and Marois, 1995; Peros and Berger, 1994; Chapuis et al., 1998; Sosnowski et al., 2007), and neither efficient treatment nor non-destructive diagnostic tools are available for this disease. Thus, in cases of contamination, infected plants die within a few years (Pascoe, 1999). Finally, except for some microscopic and toxicological studies (Philippe et al., 1993; Deswartes et al., 1994, 1996; Amborabé et al., 2001; Kim et al., 2004; Octave et al., 2006b), grapevine responses to E. lata are still poorly described.
The present work describes a trancriptomic study of grapevine (Vitis vinifera cv. Cabernet-Sauvignon) response after infection by the vascular ascomycete fungus E. lata. The aims of this work are to (i) characterize grapevine responses to E. lata infection and (ii) to identify genes more specifically associated with a lack of symptoms. For these purposes, leaves of infected symptomatic plants (S+R+), infected asymptomatic plants (S–R+), and healthy plants (S–R–), from vineyard (natural infection), greenhouse (experimental infection), and in vitro (experimental infection) material were compared.
Two conditions were used for the production of infected and healthy Cabernet-Sauvignon grapevines: the vineyard (natural infection) and the greenhouse (experimental infection).
Vineyard samples were collected in an INRA experimental plot (Chateau Cruzeaux) located close to Bordeaux. In this vineyard, which is naturally infected by E. lata, Eutypa dieback symptoms were monitored every year between 2002 and 2006. Healthy grapevines were selected among those that did not show disease symptoms during this time. Infected grapevines showing apparent Eutypa dieback symptoms every year from 2002 to 2006 were also selected. Leaf samples were collected in June when symptoms were most visible, immediately frozen in liquid nitrogen, and stored at –80°C. Absence of infection by other fungal pathogens (Botrytis cinerea, Erysiphe necator, and Plasmopra viticola) was visually checked during sampling.
Two-node Cabernet-Sauvignon cuttings were rooted 2 months before infection and grown in a greenhouse (Chapuis, 1995). The temperature was maintained between 20°C and 32°C. Plants were watered for 5min, twice per day, using 0.5l h−1 emitters via a drip system. They received, on average, 18h of light per day from both ambient and supplemental lighting. These rooted cuttings were experimentally infected with the E. lata strain BX1-10, which has been characterized as a very aggressive strain (Péros and Berger, 1999). Infections were carried out as described by Chapuis (1995). A hole (2mm diameter, 5mm deep) was drilled 2cm below the upper bud. After 10–15d of culture at 23°C in darkness, E. lata mycelium was collected by scraping the surface of the PDA (potato dextrose agar, Difco) culture medium with a scalpel, and suspended in sterile water with strong agitation. A 20μl aliquot of this suspension was injected into the hole in the cutting and the inoculation site was immediately covered with paraffin. Non-inoculated control vines treated with 20μl of sterile water were included in the experiment. Cuttings were maintained in the greenhouse until eutypiosis symptoms appeared the following year. An average of 10 leaves were randomly collected from each grapevine, immediately frozen in liquid nitrogen, and stored at –80°C. All samples were collected at the same time.
In the vineyard, Eutypa symptoms were followed between 2002 and 2006 according to the guidelines provided by Darrieutort and Lecomte (2007). In the greenhouse, leaf symptoms were evaluated for each cutting 1 year after the experimental infection and categorized as not visible (S–) or visible symptoms (S+) (for severe, moderate, or mild symptoms), as suggested by Péros and Berger (1994).
For both vineyard and greenhouse plants, cross-sections were made in woody parts to look for brown lesions characteristic of Eutypa dieback as described by Lecomte et al. (2000). After surface sterilization by rapid flaming, a wood fragment was sampled along the margin of the lesion (between healthy and infected wood), using pruning shears. This segment was then split into wood chips (3×5×5mm) for culture of E. lata. Chips were surface sterilized by soaking in 3% calcium hypochlorite solution. They were placed in sterile conditions onto Petri dishes containing malt (15g l−1), agar (20g l−1) medium supplemented with chloramphenicol (50mg l−1). Petri plates with both greenhouse and vineyard samples were assessed visually for the presence of E. lata, after 10d of incubation in the dark at 22°C. When the samples were for positive E. lata, a white cottony mycelium growth originating from the sample was observed.
PCR identification of E. lata was carried out as described previously (Lardner et al., 2005). After rapid DNA extraction from re-isolated mycelium, amplification was performed using the SCAR primer pair Eut02 F3 (TGGTGGACGGGTAGGGTTAG) and Eut02 R2 (GGCCTTACCGAAATAGACCAA). This indirect and destructive PCR allowed a clear identication of the presence of E. lata in infected plants. Rapid DNA extraction from the mycelium was carried out according to Hamelin et al. (2000). Briefly, a small amount of mycelium was removed from the surface of actively growing cultures on PDA using a 200μl pipette tip, incubated for 7min at 95°C in 100μl of extraction buffer (0.5M TRIS-HCl, pH 9. 0.1% Triton X-100), then cooled on ice for 5min. PCRs were conducted with 1μl aliquots of fungal DNA extract (~30ng of template) in a total volume of 25μl. Each reaction also contained 0.2 vol. of 5× green buffer (Promega), 2mM MgCl2, 200μM each of dATP, dCTP, dGTP, and dTTP (Roche diagnosis), 0.2μM of each primer (Operon technologies), and 1U of GoTaq DNA polymerase (Promega). An initial denaturation step of 2min at 94°C was followed by 37 cycles of 30s at 94°C, 30s at 58°C, and 1min at 72°C, with a final extension of 10min at 72°C. Before migration, 0.2 vol. of loading buffer (30% glycerol, 0.25% bromophenol blue, 0.25% xylene cyanol) was added to the samples. Amplification products, which have an expected size of 643bp, were separated by electrophoresis in 2% agarose gels using a 0.5× TAE buffer (20mM TRIS-HCl, 0.5mM EDTA, 2.5mM Na acetate), stained with 100μg l−1 ethidium bromide (Biorad), and visualized under UV illumination ‘GEL DOC 2000’ (Biorad).
Eutypa lata isolation and PCR enabled the determination of whether the non-inoculated control or the selected vineyard grapevines that seemed to be healthy were indeed axenic (negative isolation), and to separate the experimentally inoculated samples that became infected (positive recovery and PCR test) from those that did not (negative re-isolation). R+ samples correspond to positive recovery and positive PCR, whereas samples were rated R– in the case of negative isolation.
In order to determine whether key changes in gene expression in leaves infected with E. lata (identified by transcriptomic studies) were specific to this pathogen, they were also profiled by real-time PCR (RT-PCR) in vine leaves infected with other fungal pathogens.
Healthy leaves were sampled just before infection from Cabernet-Sauvignon vines grown in the greenhouse. They were placed upper face down in a Petri dish. Half of them were infected with 15μl droplets of a P. viticola spore suspension (5000 spores ml−1, counted with a Malassez cell) deposited on the lower face of the leaf, the other half were left as the non-infected control. The leaves were maintained in a growth chamber at 22°C under a photoperiod of 16h light/8h darkness. Leaves infected with various strains of P. viticola (PAV 32, FEM 03, PIC 59, MIC 128, EAU 14, and FET 03) were collected 12, 14, and 16d after infection. At each time of infection, leaves infected by these different strains were pooled together. Healthy leaves were also collected after 12, 14, and 16d in a Petri dish. These samples were deep-frozen in liquid nitrogen and used later for RT-PCR studies on candidate genes.
Mature leaves from Cabernet-Sauvignon vines grown in the greenhouse were collected and, after sterilization in calcium hypochlorite (50g l−1) for 10min, they were placed in a Petri dish containing solid medium (15g l−1 agar with 30mg l−1 benzimidazole, upper face upwards). The fungal conidia were detached from a pre-inoculated sporulating leaf by an air stream, and inoculated by gravity under dry conditions on the selected leaves.
Chardonnay grapevine plantlets grown in vitro on MacCown medium were transferred to aeroponic conditions when the fourth leaf was developing and the roots were 4–5cm long. The plantlets were placed in a container where the nutrient solution was sprayed as a mist. The container was maintained in a growth cabinet under a sodium bulb, with constant temperature (23°C) and humidity (75%). The 916 T B. cinerea strain was grown on malt agar (10g l−1; 15g l−1) and induced to sporulate by continuous light for 5–10d. A conidial suspension was prepared with sterile distilled water and maintained on ice until inoculation. Infection was carried out by deposition of 8.5μl (~1000 conidia) of this suspension onto the leaf. Several healthy leaves (0h) or infected leaves were collected 24, 48, and 72h after infection.
RNA isolation was carried out as described previously by Reid et al. (2006). To prepare the fluorescent targets, total RNA was amplified using the Amino Allyl MessageAmp II aRNA Amplification Kit (Ambion, TX, USA) following the manufacturer's instructions. The first-strand cDNA was synthesized from 2μg of total RNA with ArrayScript and T7 oligo(dT) primer, after incubation for 2h at 42°C. The cDNA then underwent second-strand synthesis (2 h at 16°C) and was cleaned-up with the same kit to become a template for in vitro transcription with T7 RNA polymerase. During transcription (14h at 37°C) a modified nucleotide, amino allyl UTP, is incorporated into the aRNA. Amino allyl UTP contains a reactive primary amino group that can be chemically coupled to NHS ester dyes. A 25μg aliquot of amino allyl aRNA was used for this subsequent indirect labelling with the fluorescent cyanine dyes Cy3-dCTP and Cy5-dCTP (Amersham Biosciences, USA).
In order to characterize grapevine response to E. lata infection, gene expression was profiled in infected plants with symptoms (S+R+), infected plants without symptoms (S–R+), and healthy plants (S–R–) produced in two experimental conditions: the greenhouse and the vineyard. Fluorescent targets prepared with RNA extracted from leaves of these plants (S+R+, S–R+, and S–R–) were hybridized to 70mer oligonucleotide microarrays, allowing simultaneous monitoring of the expression of ~ 15000 grapevine genes. Microarrays were used to perform three different comparisons (Fig. 4): for the first comparison (S+R+/S–R–), three biological replicates were used in vineyard condition and two biological replicates were used for the greenhouse material. For the second comparison (S–R+/S–R–), three and two biological replicates were used, respectively, in greenhouse and vineyard conditions. For the last comparison (S+R+/S–R+), two biological replicates were made in the greenhouse condition and one biological replicate was made in the vineyard condition. At least two technical replicates (dye swap) were made for each comparison. The data are available in ArrayEpress (http://www.ebi.ac.uk/arrayExpress) under the accession number E-MEXP-2337.
Greenhouse and vineyard microarray data were combined with microarray data that we obtained previously with in vitro plantlets experimentally infected by E. lata, and that were used to test the Mapman software presently being adapted for grapevine (Rotter et al., 2009). These in vitro microarray data can be found under the accession number E-MEXP-2102 in Array Express.
For microarray production, the Array-Ready Oligo Set™ for the grape (V. vinifera) genome Version 1.0 designed by Operon was used. This set contains 14562 probes of 70mer representing 14562 transcripts from The Institute for Genomic Research (TIGR) Grape Gene Index (VvGI), release 3. Oligonucleotide probes were mapped to the grapevine genome (Jaillon et al., 2007) and to the most recent release of the DFCI Grape Gene Index (version 6.0). Genome transcripts have been annotated automatically against the Swissprot database. Manual annotation has been done for differentially expressed genes using Uniprot's Uniref100 database. Probes were synthesized by Qiagen and spotted onto epoxy mirror slides (Amersham) at the Montpellier Languedoc Roussillon Genopole, Institut de Génomique Fonctionnelle, at a concentration of 5μM and a spot size of 150–160μm. Just before hybridization, oligonucleotides were fixed onto the slide by UV (254nm) radiation of 120mJ in a UV Stratalinker 2400-cross-linker (Stratagene, USA). The slides were then washed with up and down gentle movement, twice in 0.2% SDS for 1min and twice in distilled water for 5min. Air-dried slides were positioned in the hybridization chambers.
For each hybridization, 600pmol (~4μg) of Cy3 and Cy5 aRNA targets were mixed. Fragmentation was carried out for 15min at 70°C with an RNA fragmentation reagent kit (Ambion). The final volume of the target solution was then adjusted to 100μl with hybridization solution: 50% formamide, 5× Denhardt's solution, 1× SSC, 0.05% SDS, and 1μg ml−1 denatured salmon sperm DNA (Stratagene, USA). This target solution was finally denaturated for 2min at 95°C, cooled on ice for 2min, and stabilized at 37°C until injection (maximum 5min). During injection, denatured target solution (600pi of Cy3- and Cy5-labelled aRNA) was introduced into the hybridization chamber containing the microarrays slide (14562 grapevine oligo probes). Hybridization was then conducted for 16h at 37°C, with moderate agitation, in the automated microarray station HS4800 Mastersystem (Tecan). Slides were washed sequentially at 30°C in 1× SSC/0.2% SDS for 20min in 0.1× SSC/0.2% SDS for 10min, twice; and finally in 0.1× SSC for 10min. The washed arrays were quickly dried with 2.7 bars of nitrogen gas and immediately scanned.
The microarrays were scanned with a Genepix 4000B fluorescence reader (Axon Instruments, Canada) using GenePix 4.0 image acquisition software. It simultaneously scans array slides at two wavelengths using a dual-laser scanning system. These wavelengths (532nm and 635nm) are used to excite the fluorophores Cy3 and Cy5, respectively. A pair of photomultiplier tubes (PMTs) is used to detect the emitted fluorescent light. Sensitivity of detection can be adjusted by changing the voltage applied to the PMT. PMT voltages were adjusted to 400V for Cy3 (532nm) and 460V for Cy5 (635nm) in order to obtain maximal signal intensities and low saturation <1%.
The microarray images obtained with the GenePix 4000B scanner were quantified with the Maia tool version 2.75 (Novikov and Barillot, 2007). A full version of the software is freely available to non-commercial users upon request from the authors. Maia 2.75 allowed an automatic processing of the two-colour microarray images including: localization of spots with different morphological characteristics, quantification, and quality control. Flagged and saturated (intensity >50000) spots were filtered out and excluded from further analysis.
Array normalization was carried out using a modified version of the Goulphar script version 1.1.2 (Lemoine et al., 2006) to take into account input data in the MAIA format. Median intensity data without background subtraction were normalized by a global lowess method followed by a print-tip median method. The lowess function enables the correction of global intensity artefacts due to the difference in incorporation between the two dyes. The print-tip method allows the correction of the spatial intensity artefacts due to the print-tips.
Differentially expressed genes were identified with the R/Bioconductor package Limma (Smyth, 2004, 2005) using linear models and by taking into account technical and biological replicates. Genes with a P-value ≤0.05 and an expression ratio ≥1.4 were deemed potentially significant and selected for further study. For convenience and clarity of the text, although what was actually measured were transcript amounts, and not transcriptional activities, reference is made to ‘up’- or ‘down-regulation’, and to ‘over-’ and ‘underexpression’.
The expression profiles of candidate genes were studied by semi-quantitative RT-PCR in response to E. lata and other grapevine pathogens (E. necator, P. viticola, and B. cinerea).
TC sequences (Grape Gene Index Version 6) or grapevine predicted gene genomic sequences (Jaillon et al. 2007), revealing 100% homology to the microarray 70mer oligonucleotides, were used to design gene-specific primers located in the 3′-untranslated region and in the penultimate exon with Primer 3 and NetPrimer software. These primers were than synthesized by Operon. Primer sequences and predicted product size are given in Supplementary Table S1 available at JXB online.
About 2μg of total RNA were reverse transcribed in a total volume of 25μl with M-MLV reverse transcriptase (Promega). RNA was mixed with 3μl of 10μM oligo(dT), and adjusted to a final volume of 15μl. The mixture was incubated at 75°C for 10min and snap-cooled on ice. The following preparation (10μl) was then added to the RNA mixture: 5μl of M-MLV reverse transcriptase reaction buffer (5×; Promega), 2μl of deoxynucleoside triphosphate (10mM each) mix, 1μl of dithiothreitol (DTT; 100mM), 1μl of RNasin RNase inhibitor (40U μl−1; Promega), and 1μl of M-MLV reverse transcriptase (200U μl−1; Promega). Incubation was at 42°C for 1h and final denaturation at 100°C for 5min. The cDNA solution was diluted with 100μl of water.
PCRs were conducted in triplicate in a total volume of 25μl containing: 2.5μl of diluted cDNA solution, 12.5μl of GoTaq Green Master Mix 2X (Promega), and 1.25μl of each primer (10μM). GoTaq Green Master Mix (Promega) is a pre-mixed ready-to-use solution containing Taq DNA polymerase, dNTPs, MgCl2, and reaction buffers at optimal concentrations for efficient amplification of DNA templates by PCR. DNA amplification was performed on a programmable thermal cycler (Progene, Techne, Cambridge, UK) with the following parameters: 95°C for 5min followed by 25–30 cycles of 95°C for 30s, 30s at the specific primer pair annealing temperature, and 72°C for 45s, with a final cycle at 72°C for 5min.
One hundred and fifty Cabernet-Sauvignon cuttings grown in greenhouse conditions were infected through a stem drill with the BX1-10 E. lata strain. Control cuttings were maintained under the same greenhouse conditions. One year after infection, the symptoms were evaluated and ranked as severe, moderate, mild, or absent (Fig. 1). Among the 150 infected plants, 50% showed symptoms. Thirty-two cuttings exhibited severe symptoms, 21 cuttings showed moderate symptoms, and mild symptoms were found on seven plants. None of the 20 control plants showed symptoms. Eutypa lata recovery tests were conducted on 15 infected cuttings showing symptoms (five with severe, five with moderate, and five with mild symptoms), on 20 infected cuttings which did not develop symptoms, and on 10 control cuttings (Table 1). For the re-isolation of fungal hyphae, the cutting was split longitudinally, and the zone adjacent to the necrosis was cut into 20 small pieces that were briefly surface-sterilized in a 3% sodium hypochlorite solution. These pieces were then placed onto culture medium. Eutypa lata was successfully re-isolated from all the infected plants showing symptoms, whereas no fungal growth was observed for nine out of 10 uninfected plants. Eutypa lata was also successfully re-isolated from most of the infected plants that did not show any symptoms (Table 1). The nine control plants that did not show any fungal growth and the infected plants for which at least nine fragments out of 20 gave a positive re-isolation result were selected for further analysis (Table 1).
Eutypa dieback symptoms were studied every year between 2002 and 2006 in the Châteaux Cruzeaux vineyard (Table 2). This allowed identification of 12 plants which showed symptoms of varying severity every year and 15 plants which did not show any symptoms during this period. The infected plants exhibited typical symptoms of eutypiosis including dwarf shoots, bushy phenotype with small chlorotic leaves, and marginal necrosis (Fig. 2). The area close to the zone of necrosis was cut into sections and 20 fragments per plant were incubated on culture medium. Positive re-isolation was considered to have occurred when fungal growth was seen 10d after the beginning of incubation. Table 2 gives, for each plant, the number of fragments for which fungal growth was obtained. Fungal infection (positive E. lata re-isolation) was confirmed for the 12 plants which showed symptoms every year of the survey. Among the 15 plants that never exhibited symptoms, seven never showed any fungal growth, whereas eight were contaminated. Other fungi (i.e. Botryosphaeria obtusa, Phaeomoniella chlamydospora, Phaeoacremonium aleophilum, and Trichoderma sp.) were also visually identified after re-isolation. Four plants for which the number of ‘positive’ fragments was ≥50% and devoid of infection by other fungi were selected and called S+R+ (symptoms+ re-isolation+). Four plants among those that did not yield growth of E. lata, P. chlamydospora, P. aleophilum, and Trichoderma sp. were considered as healthy plants and selected. These S–R– plants allowed some re-isolation of Botryosphaeria; this was also the case for two of the plants that were selected as S+R+. Thus, because it is present in both samples it can be assumed that the genes that were differentially expressed between S+R+ and S–R– samples are not due to interaction with Botryosphaeria.
Formal identification of E. lata in the re-isolation samples collected from infected greenhouse and vineyard plants was successfully achieved by the protocol of Lardner et al. (2005). This protocol is based on DNA extraction from the re-isolated mycelium, followed by PCR with the Eut02F3 and Eut02R2 primers. It allowed characterization of E. lata in all infected samples (S–R+ and S+R+) selected from greenhouse and vineyard plants (Fig. 3). A DNA fragment of the expected size (643bp) was amplified from the mycelium growing from all the infected fragments, and a pure E. lata strain (BX1-10, NE85-1). This extensive characterization of plant material either prepared in the greenhouse or collected in the vineyard allowed identification of three series of plants: healthy plants with no symptoms and no re-isolation of E. lata (S–R–), infected plants from which the fungus was successfully re-isolated but that did not show Eutypa dieback symptoms (S–R+), and infected plants (with successful re-isolation of E. lata) exhibiting eutypiosis symptoms (S+R+). RNA was extracted from leaves of S–R–, S+R+, and S–R+ plants, and used for hybridization with the 15 K Qiagen/operon microarray.
Analysis of the microarrays was conducted from infected plants with symptoms (S+R+), infected plants without symptoms (S–R+), and healthy plants (S–R–).
The microarray data were first used to identify genes that were differentially expressed between infected plants with symptoms (S+R+) and healthy (S–R–) plants. In order to increase the stringency of the differentially expressed genes and to identify the most interesting genes that characterize grapevine response to E. lata, the microarray data produced from greenhouse and vineyard (S+R+) and (S–R–) material described herein were combined with microarray data that we obtained previously with in vitro plantlets experimentally infected by E. lata (accession number E-MEXP-2102 in Array Express; Rotter et al., 2009).
The microarray data were also used to identify genes that may be involved in the lack of symptoms, and thus may play some role in the tolerance to E. lata. For this, comparisons were made between S–R+/S+R+ plants, and between S–R+/S–R– plants produced in both greenhouse and vineyard conditions. An overview of the microarray experimental design is presented in Fig. 4.
Genes differentially expressed between S+R+ and S–R– plants were identified in three experimental conditions in vitro, in the greenhouse, and in the vineyard. Only a few genes were differentially expressed if thresholds of 2 for up-regulation and 0.5 for down-regulation were set, with a P-value <0.05. The numbers of up- and down-regulated genes were 25, 70, and 131, and 1, 35, and 45, respectively, in in vitro, greenhouse, and vineyard conditions. These low figures may be due to the fact that the major impact of the vascular fungus Eutypa on xylem tissue is diluted when whole leaf samples are analysed. However, it was technically impossible to extract RNA from the xylem of lignified stems. For this reason, and to make sure any gene that may be differentially expressed was not missed, thresholds of 1.5 for up-regulation and 0.66 for down-regulation, with a P-value <0.05, were used. With a threshold of 1.5 for up-regulation and 0.66 for down-regulation, and a P-value <0.05 the numbers of overexpressed or down-regulated genes in S+R+ plants compared with S–R– plants were 64, 222, and 420, and 6, 131, and 195, respectively, under in vitro, greenhouse, and vineyard conditions. Venn diagrams were constructed to identify genes that exhibited the same behaviour for in vitro, greenhouse, and vineyard plants (Fig. 5). Twenty-six genes were overexpressed in in vitro, greenhouse, and vineyard S+R+ plants compared with the corresponding S–R– plants. No down-regulated genes were found in common between in vitro, greenhouse, and vineyard plants. Sixty-three genes were up-regulated both in S+R+ greenhouse and vineyard plants compared with the corresponding healthy plants, and 13 down-regulated genes were found both in greenhouse and vineyard plants with symptoms (S+R+) compared with healthy plants. In in vitro and greenhouse conditions, 15 common genes were up-regulated in S+R+ plants. Only two differentially expressed genes (one up- and one down-regulated) were shared between in vitro and vineyard conditions (Fig. 5). A total of 105 genes were up-regulated for at least two conditions in S+R+ compared with S–R– plants, and a total of 14 genes were down-regulated for at least two conditions. The number of up-regulated genes was thus much higher than the number of down-regulated genes.
Among the 119 genes which were differentially expressed in S+R+ plants for at least two conditions, 68 (57 up-regulated and 11 down-regulated) can be identified by mapping the probes to the Vitis vinifera Gene Index (http://compbio.dfci.harvard.edu/tgi/cgi-bin/tgi/gimain.pl?gudb=grape) or the Pinot noir grapevine genome (Jaillon at al., 2007) and show a good homology with known genes. Classification of these genes in functional categories indicates that 12 categories were represented in overexpressed genes, whereas underexpression concerns only three categories (Fig. 6). Five categories are abundant for overexpressed genes: metabolism, defence reactions, interaction with the environment, transport, and transcription. Repressed genes belong to lipid metabolism, cell wall metabolism, and defence reactions.
The complete list of genes that were differentially affected is given in Table 3. Genes involved in carbon metabolism, amino acid, or phenylpropanoid metabolism were up-regulated in symptomatic infected plants. In contrast, several genes involved in lipid metabolism were down-regulated in these plants. Genes that are involved in defence reactions were quite numerous and most of them were up-regulated in infected plants with eutypiosis symptoms. They include osmotin, PR10 and PR1, arachidonic acid-induced DEA 1, harpin-induced protein Hin1, class IV chitinase and endochitinase, thaumatin, disease resistance proteins, and anionic peroxidase. Several genes encoding enzymes of cell wall metabolism or extracellular metabolism were also up-regulated. These include proline-rich protein, hydroxyproline-rich glycoprotein, and β-glucanase. In contrast, a few genes involved in plant cell wall metabolism were down-regulated, including those encoding an arabinogalactan, an expansin, a xyloglucan endotransglycosylase, a pectin methylesterase inhibitor, and a germin-like protein. Several genes involved in the interaction with the environment were up-regulated. They are particularly associated with hormonal metabolism and response. These genes include those encoding enzymes of the ethylene biosynthetic pathway (ACC oxidase), auxin-repressed proteins, and a gibberellin receptor. Other up-regulated genes encode transcription factors (dehydration-responsive element-binding protein, WRKY, Zn-finger, and NAC transcription factors) and protein regulating factors (tumour-related protein and serine/threonine kinase). One plasma membrane aquaporin and several ion and metabolite transporters are up-regulated in infected plants.
In order to identify genes that may prevent symptom development, comparisons were made (i) between infected plants without or with eutypiosis symptoms (S–R+/S+R+) and (ii) between infected plants without symptoms and healthy plants (S–R+/S–R–). Because both types of plants are infected by E. lata, the first comparison (S–R+/S+R+) identifies genes that prevent symptom development and genes associated with symptom externalization. The second comparison (S–R+/S–R–) identifies genes that prevent symptom development and genes associated with response to infection by E. lata. Genes that prevent symptom development (even though the fungus is present in the plant) must be common between both comparisons (S–R+/S+R+) and (S–R+/S–R–). A total of 32 and 59 genes specifically involved in the absence of symptoms have been highlighted in greenhouse and vineyard conditions, respectively. Expression ratios obtained for the three comparisons (S+R+/S–R–, S–R+/S+R+, and S–R+/S–R–) allow the establishment of an expected expression profile between the different kinds of plants: S–R+, S+R+, and S–R–. For greenhouse plants, 26 genes were overexpressed and six genes were down-regulated in S–R+ plants compared with S+R+ and S–R– plants; for vineyard plants, 49 genes were overexpressed and 10 genes were repressed in S–R+ plants compared with S+R+ and S–R– plants.
The genes that may be involved in the absence of symptom development in greenhouse or vineyard conditions, which exhibited good homology with genes of known function, are listed in Table 4, and arranged by functional categories (Fig. 7). Among the genes that may be assigned to functional categories (34 up-regulated genes and five down-regulated genes in total), the most abundant belong to the category of energy metabolism, and more precisely to the light phase of photosynthesis. All those genes were up-regulated (Fig. 7). Four of them encode subunits of NADH-plastoquinone oxidoreductase, four encode other membrane proteins of the photosynthetic apparatus (oxygen-evolving enhancer protein 2, cytochrome b6, PSI chlorophyll a/b-binding protein, and PSII CP47 chlorophyll apoprotein), and three encode soluble proteins (RBCX, phosphoribulokinase, and thioredoxin) (Table 4). Besides energy metabolism (photosynthesis), other functional categories seemed to be linked to lack of symptom development. They included phenylpropanoid metabolism, carbon metabolism, protein synthesis or regulation, defence reactions, and cell wall metabolism.
Of the 26 genes that were up-regulated in S+R+ plants, eight were selected to study their expression by RT-PCR. These genes code for osmotin (Vv-10010885: GSVIVG00001106001), PR10 protein (Vv-10003874: GSVIVG00033089001), chitinase (Vv-10000136: GSVIVG00034644001), tumour-related protein (Vv-10001691: GSVIVG00007741001), disease resistance response protein (Vv-10010268: GSVIVG00024743001), harpin-induced protein (Vv-10009597: GSVIVG00021517001), legumin (TC72587), and a small proline-rich protein (GSVIVG00034255001). The elongation factor EF1 was used as a constitutive control. The transcripts of the eight selected genes were more abundant in infected symptomatic plants (S+R+) than in healthy plants (S−R−). To check the specificity of the response of these genes, their expression was also studied in plants infected by either downy mildew, powdery mildew, or black rot (Fig. 8 B). All the genes were also up-regulated upon infection by these three fungi, indicating that they are general markers of fungal infection which are not specific for E. lata.
Very few studies have been devoted to the interaction between a plant and a vascular pathogenic fungus (Dowd et al., 2004; Robb et al., 2007). To our knowledge, this paper provides the first transcriptomic analysis of the interaction of grapevine with the causal agent of Eutypa dieback, a major vascular disease.
In the vineyard, Eutypa symptoms appear several years after infection (Duthie et al., 1991; Tey-Rulh et al., 1991), and for a given plant the symptoms are variable from one year to the next, even after the symptoms have appeared for the first time. This makes this disease very hard to study. For these reasons, transcriptomic analyses were carried out with plants that were carefully characterized after symptom notation and fungus isolation, in order to distinguish infected plants with typical Eutypa symptoms (S+R+), infected plants without visible symptoms (S–R+), and healthy plants (S–R–). The symptoms observed 1 year after inoculation of greenhouse cuttings, which included stunting of new shoots, with small, cupped, chlorotic, and tattered leaves, were also observed in several other greenhouse studies: 14 months after infection of rooted grapevine cutting inoculated with E. lata ascospores (Pezoldt et al., 1981), 4–8 weeks after inoculation of unrooted cuttings maintained in moist rockwool with an E. lata mycelium plug (Peros et al., 1994, 1999), or 8 months after infection of rooted cuttings with an E. lata mycelium plug (Sosnowski et al., 2007). Isolation of the fungus present in woody tissues and PCR identification of E. lata were also carried out to characterize the plant material. Numerous DNA-based markers are available to identify E. lata (Lecomte et al., 2000; Rolshausen et al., 2004; Lardner et al., 2005; Catal et al., 2007). The SCAR primer pair Eut02 F3/Eut02 R2 (Lardner et al., 2005) was used in the present study. The development of E. lata PCR primers is very interesting because it allows a formal E. lata diagnosis test. However, this is a destructive assay requiring the use of perennial grapevine wood tissues. The different tests made allowed checks to be made to determine whether the uninoculated control or the grapevines that seemed to be healthy were indeed axenic, and to separate the experimentally inoculated samples that became infected from those that did not.
Eutypiosis is also hard to study because each possible experimental model (in vitro, greenhouse, or vineyard) has specific advantages and disadvantages. Vineyard plants infected with E. lata obviously represent the closest material to natural conditions, but the infection process and the environment are not controlled. In this study, the status of naturally infected vineyard plants was monitored for several years. Greenhouse and in vitro plants can be experimentally infected. In this study, greenhouse and in vitro plants were inoculated with a characterized E. lata strain under a controlled environment. Eutypa symptoms appeared after 1 year for greenhouse plants and after only 7 weeks for in vitro plants. However, greenhouse cuttings are a simplified model and in vitro plants do not differentiate much woody tissue, which makes this material less close to natural conditions. Furthermore, although it is thought that grapevine infection by E. lata occurs through wounds in natural conditions (Carter, 1960, 1965; Moller et al., 1978), infection via a cut stem or a stem hole may not completely reflect the natural sequence of events. Notwithstanding this, great care was taken to check the physiological status of each series of plants.
It is because each experimental condition presents specific advantages and disadvantages that transcriptomic analyses were carried out on the three experimental conditions (in vitro, greenhouse, and vineyard) and that the data were combined in order to determine only the most significant genes.
Due to the impossibility of RNA isolation from lignified vascular tissues, it was decided to analyse leaf samples, because RNA can be easily extracted from leaves and because leaves exhibit dramatic symptoms in the case of infection. The ratios observed for differential expression were rather low and led to low thresholds being used in most cases. Possible reasons for this are the dilution of infected zones of leaves with healthy leaf parts, the choice of leaf samples while the first invaded tissue is the xylem, and the long times chosen for sampling.
The number of up- and down-regulated genes in infected plants with symptoms compared with healthy plants increased from in vitro to greenhouse and vineyard conditions. Part of this observation might be explained by the kinetics of infection. Indeed, the contact between the grapevine and E. lata lasts 7 weeks in vitro, 1 year in the greenhouse, and 5 years in the vineyard. The material produced in vitro and in the greenhouse corresponds to earlier steps of infection than that in the vineyard. Microarray studies conducted on other plant pathogen systems also revealed that the number of genes differentially expressed increased during infection kinetics (Moy et al., 2004; Zhao et al., 2007; Fung et al., 2008). Another explanation may be that the environment is less controlled and stable between in vitro, greenhouse, and vineyard conditions.
The number of up-regulated genes was much higher than the number of repressed genes. The same trend was observed after infection of tomato plants with Verticillium dahliae (Robb et al., 2007) or after treatment of tomato leaves with fusicoccin, a toxin secreted by Fusicoccum amygdali (Frick et al., 2002). The response of the plant to fungal infection is therefore oriented more towards the stimulation of specific metabolic pathways than to the cessation of given processes.
According to the literature or to the pathoplant database (http://www.pathoplant.de/microarray. php), 44% (30/66 up-regulated, 4/11 down-regulated) of the genes differentially expressed in infected plants showing symptoms in at least two experimental conditions (Table 3) are already known to be involved in plant–fungus interaction. This result confirms the validity of the present approach. The gene BIG8.1 (Vv_10008453: GSVIVG00032646001) encoding a serine hydrolase (AAN77692) was cloned after differential screening of transcripts expressed in grape leaves infected by B. cinerea, and its up-regulation by infection was confirmed by RT-PCR (Bezier et al., 2002). The gene CYP82H1 (Vv_10007334: GSVIVG00036466001) encoding the cytochrome P450 protein (Q6QNI1) is expressed more after elicitation by fungal extracts, and is thus probably involved in defence response (Larbart, 2006). The genes GSVIVG00002773001 (Vv_10001736) and GSVIVG00027001001 (Vv_10001880) are associated with the transcription factors CaWRKY-b (AY743433) and VaWRKY 30 (AY509152). Both these transcription factors are overexpressed in V. vinifera leaves of a susceptible cultivar infected with E. necator compared with healthy grapevine leaves (Fung et al., 2007). Both GSVIVG00001107001 (Vv_10003617) and GSVIVG00001106001 (Vv_10010885) are highly homologous to a V. vinifera gene encoding an osmotin (P93621). This protein has a strong antifungal activity in vitro and stops the mycelial growth of Phomopsis viticola and B. cinerea. It inhibits spore germination and germ tube growth of E. necator, P. viticola, and B. cinerea. Both gene expression and protein production are induced in grapevine leaves and berries infected by E. necator or P. viticola (Monteiro et al., 2003). Following leaf infection by E. necator, this gene is strongly induced in the resistant grapevine cultivar Regent compared with the susceptible variety Chardonnay (Leocir Welter, personal communication). VvPR10-1 (Vv_10003874: GSVIVG00033089001) encodes a pathogenesis-related protein PR10 (Q9FS42) which is induced in the leaves of the grapevine cultivar Riesling and Glory infected with the fungus P. viticola or P. cubensis (Kortekamp, 2006). This gene is also overexpressed in the Régent cultivar during the incompatible interaction between grapevine and E. necator (Leocir Welter, personal communication). VvCHIT4c (Vv_10002903: GSVIVG00034623001) encoding a class IV chitinase (Q7XB39), VvPIN (Vv_10008543: GSVIVG00029889001) encoding a protease inhibitor (Q6YEY6), and the gene (Vv_10010418: GSVIVG00033125001) coding for a β-1,3-glucanase (Q9M563) are all induced in elicited grapevine leaves or cells, and this treatment promotes resistance to the fungi B. cinerea, E. necator, and P. viticola (Aziz et al., 2003, 2004; Belhadj et al., 2006). GSVIVG00025341001 (Vv_10002068) and GSVIVG00025340001 (Vv_10000389) are associated with a second β-1,3-glucanase (Q9M3U4) whose transcripts are accumulated in the susceptible variety ‘Gloire de Montpellier’ after infection with P. viticola (Kortekamp, 2006).
All these responses tend to strenghten the plant cell wall (anionic peroxidase, proline-rich and hydroxyproline-rich proteins), to maintain the osmotic balance (osmotin, DEA1), to destroy the fungal cell walls (chitinase, endochitinase, β-glucanase), and react to pathogen infection (PR). Induction of genes of secondary metabolism (PAL, flavanone-3-hydroxylase) and of aquaporins, ions, and metabolite transporters also follows these trends. In the present experiments, all those genes were unable to prevent infection and appearance of symptoms, because they are expressed too late, and/or at too low level, and/or are not appropriate. In order to identify tolerance/resistance genes, it will be interesting to compare results obtained here (in a susceptible cultivar) and other microarray analyses conducted with a more resistant cultivar.
The expression profile of selected genes obtained by RT-PCR confirmed the microarray expression profile (Fig. 8). These genes were up-regulated in S+R+ compared with S–R– plants in all the conditions tested. They were also up-regulated in Cabernet-Sauvignon leaves infected by E. necator, P. viticola, and B. cinerea (Fig. 8). This result was expected for genes involved in general defence mechanisms such as osmotin, PR10, chitinase, tumour-related protein, and legumin. The RT-PCR profiles obtained for some genes are in agreement with literature data. Thus, the GSVIVG00001106001 (Vv_10010885) associated with an osmotin gene is up-regulated by infection with E. necator and P. viticola as observed by Monteiro et al. (2003). VvPR10-1 (Vv_10003874: GSVIVG00033089001) is up-regulated by P. viticola, as observed by Kortekamp (2006), and by E. necator (Leocir Welter, personal communication). To our knowledge, the other genes tested have not been shown to be involved in the response to infection by E. necator, P. viticola, or B. cinerea before this work.
All the transcripts that were differentially expressed in the greenhouse or vineyard for both of the comparisons (S–R+/S+R+ and S–R–/S–R–) were considered together in order to identify genes that may prevent the development of the fungus and/or the symptoms (Fig. 7, Table 4).
Among the 91 genes whose differential expression correlated with lack of symptoms, 40 could be categorized into functional categories (Table 4). Out of these 40 genes, 10 were involved in light capture and electron transport in the chloroplast. This result may be related to the mode of action of E. lata’s toxins at the cellular level. Indeed, eutypine and the toxic polypeptide fraction secreted by E. lata behaved like protonophores that affect both structure and function of mitochondrial (Deswarte et al., 1996), plastidial (Deswarte et al., 1994), and plasma membranes (Amborabé et al., 2001; Octave et al., 2006a). Ultrastructural observations depicting a chloroplast swelling with a thylakoid dilatation (Deswarte et al., 1994) showed that eutypine also inhibits photosynthesis and interacts with the thylakoid membranes. Eutypine also uncouples mitochondrial oxidative phosphorylation in grapevine and potato cells (Deswarte et al., 1996). The toxic effect of the polypeptide fraction and eutypin was also studied with plasma membrane vesicles (Amborabé et al., 2001; Octave et al., 2006a). These toxins induced transmembrane potential variation and changes in transmembrane proton fluxes, and inhibited proton-coupled uptake of nutrients (Amborabé et al., 2001; Octave et al., 2006a). These experiments suggested that the polypeptide fraction alters proton flux both by inhibiting the plasma membrane proton-pumping activity and by increasing plasma membrane proton conductance (Octave et al., 2006a). However, the impact of the polypeptide fraction is not restricted to the plasma membrane since respiration and photosynthesis of grapevine leaf tissues were also inhibited by the polypeptide fraction (Octave et al., 2006a). Part of the toxin's inhibitory effect is due to progressive reduction of the energetic charge of the cells by uncoupling and inhibition of photosynthesis and respiration (Amborabé et al., 2001). Therefore, a decreased energy charge may lead to dramatic metabolic starvation subsequent to decreased assimilate uptake in the cell. This may explain the dwarfed shoots and leaves observed on diseased plants (Octave et al., 2006a). Coordinated up-regulation of several genes involved in photosynthetic electron transport may help the cell to circumvent these effects at the chloroplast level. Although no such effect could be detected for the mitochondrial transporters, restoration of chloroplast function may provide enough energy to prevent the appearance of symptoms.
The present observations may also be related to a recent work of Valtaud et al. (2009) who showed that Esca, another major vascular disease of grapevine, modified glutathione metabolism in a systemic way. Glutathione is a major compound for maintenance of the redox balance. In the present work, the up-regulation of genes encoding proteins of the thylakoid electron transport chain, and of the chloroplast thioredoxin M-type (B9GTN8) suggests that the plant may efficiently prevent the appearance of eutypiosis symptoms by restoring chloroplast electron transport and redox balance. This is further confirmed by the up-regulation of three other genes involved in redox balance: peroxiredoxin (B9MT31), thioredoxin peroxidase (B3TLV1), and glutaredoxin (B9MYC1) (Table 4).
The response of grapevine to E. lata was studied by microarray analysis with: (i) foliar material distant from the infection point; (ii) the susceptible cultivar Cabernet-Sauvignon; (iii) aggressive E. lata strains BX1-10 and NE85-1; and (iv) at the symptom externalization time point. Although many genes involved in defence reactions are up-regulated in infected plants with symptoms, those genes do not seem efficient in preventing the detrimental effect of the fungus. Lack of symptoms is associated mainly with up-regulation of genes encoding proteins involved in photosynthetic electron transport and in the maintenance of redox balance. The data and these genes may give some clues about strategies aiming to prevent or to fight eutypiosis.
Supplementary data are available at JXB online.
Table S1. Sequences and melting temperatures of primers used for semi-quantitative RT-PCR of candidate genes selected after microarray analysis. The expected size of the amplified products is indicated in bp.
Table S2. Grapevine genome identifier (G8X ID), DFCI grape gene index version 6 identifier (VvGI6 ID), and the protein ID associated with the sequences differentially expressed between S+R+ and S–R– plants, for at least two conditions: in vitro (I), greenhouse (G), vineyard (V).
Table S3. Grapevine genome identifier (G8X ID), DFCI grape gene index version 6 identifier (VvGI6 ID), and the protein ID of the sequences associated with absence of symptoms.
We thank the Comité Interprofessionnel du Vin de Bordeaux (CIVB) for the PhD grant allocated to CC and for partial funding of the research expenses. The authors also thank David Lafarge and Philippe Cartolaro (UMR Santé Végétale, INRA-ENITA Bordeaux, France) for providing leaves infected by P. viticola and E. necator, Damien Afoufa-Bastien (FRE CNRS 3091, University of Poitiers, France) for providing leaf samples infected by B. cinerea, Jean Pierre Péros (UMR Diversité et génomes des plantes cultivées, INRA Montpellier, France) for providing E. lata strains, Jean Michel Liminana (UMR Santé Végétale, INRA-ENITA Bordeaux, France) for his technical assistance during the production and characterization of greenhouse and vineyard material, and Chateau Cruzeaux (INRA Bordeaux) for the kind permission to collect vine samples. The authors also thank Yohann Petit (UMR Biologie du Fruit, INRA Bordeaux, France), Romain Fouquet, and Sabine Guillaumie (UMR EGFV, ISVV, INRA Bordeaux, France) for their help during microarray technical improvements. The authors would like to express their gratitude to Julie Scholes (Department of Animal and Plant Sciences, University of Sheffield, UK) for her critical reading and comments on the manuscript.