Comparative Proteome Analysis of the Strawberry-Fusarium

Mar 15, 2013 - ABSTRACT: Fusarium wilt on strawberry caused by. Fusarium oxysporum f. sp. fragariae (Fof) is a serious threat to commercial strawberry...
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Comparative Proteome Analysis of the Strawberry-Fusarium oxysporum f. sp. fragariae Pathosystem Reveals Early Activation of Defense Responses as a Crucial Determinant of Host Resistance Xiangling Fang,† Ricarda Jost,† Patrick M. Finnegan,†,‡ and Martin J. Barbetti*,†,‡ †

School of Plant Biology, Faculty of Science, The University of Western Australia, 35 Stirling Highway, Crawley, WA 6009, Australia The UWA Institute of Agriculture, Faculty of Science, The University of Western Australia, 35 Stirling Highway, Crawley, WA 6009, Australia

‡

S Supporting Information *

ABSTRACT: Fusarium wilt on strawberry caused by Fusarium oxysporum f. sp. fragariae (Fof) is a serious threat to commercial strawberry production worldwide. However, resistance mechanisms of strawberry against Fof remain unknown. To reveal the defense responses of strawberry against Fof, comparative proteome analyses were conducted to determine temporal changes in root proteomes of the resistant cv. Festival and susceptible cv. Camarosa from 4 to 72 h post inoculation with Fof. Analysis of proteins separated by twodimensional gel electrophoresis revealed 79 Fof-responsive proteins with significant differences in abundance (P < 0.05 and greater than 2-fold) in the resistant and/or susceptible cultivar. The 79 proteins were identified through MALDITOF/TOF MS/MS analysis, and were mainly involved in primary, secondary and protein metabolism, stress and defense responses, antioxidant and detoxification mechanisms, and hormone biosynthesis. Among these, pathogenesis-related proteins and proteins involved in reactive oxygen species detoxification, ethylene/jasmonic acid signaling pathways, secondary metabolite biosynthesis, glycolysis and/or ubiquitin/26S proteasome-mediated protein degradation have great potential in mediating strawberry resistance against Fof. Protein modification may also have an important contribution. This study provides the first insights into strawberry resistance mechanisms against Fof, opening novel avenues to engineer new strawberry cultivars with improved disease resistance and to develop more effective and sustainable disease management strategies. KEYWORDS: Fragaria × ananassa, Fusarium oxysporum, resistance mechanism, compatible interaction, incompatible interaction, root proteome, metabolic process

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INTRODUCTION Strawberry (Fragaria × ananassa) is one of the most economically important berry crops in the world. Global strawberry production reached approximately 4.4 million tons in 2010 and is projected to rise.1 However, Fusarium wilt on strawberry, caused by Fusarium oxysporum f. sp. f ragariae (Fof), is a serious threat to commercial strawberry production worldwide.2−4 Fof penetrates strawberry plants through roots, severely affecting the growth and development of roots and crowns, resulting in the rapid wilting and eventual death of plants.3,5 F. oxysporum is a soilborne fungal species occurring in diverse soil types.6,7 In the absence of a suitable plant host, F. oxysporum grows and persists in affected fields for long periods, particularly on soil organic matter, as dormant chlamydospores.6,7 Plant resistance to F. oxysporum is under complex genetic control.6 Wilt-inducing isolates of F. oxysporum cause severe damage and yield losses across a wide range of plant families, including many economically important crop species. © 2013 American Chemical Society

These isolates have been divided into more than 120 different formae speciales (f. spp.) based on their host specificity.7,8 Fof is a strawberry-specific pathogen. Management of soilborne diseases like Fusarium wilt on strawberry remains reliant on chemical soil fumigation.9−11 However, some broad-spectrum preplanting fumigants, such as methyl bromide, have negative environmental effects and pose risks to human health and consequently have been phased-out in many countries.9−12 The phase-out of these previously effective fumigants has fostered keen interest in developing alternative nonchemical means to manage soil-borne diseases more effectively and sustainably.5,10−14 Development and deployment of resistant cultivars is considered to be the most cost-effective and environmentally sustainable strategy to manage Fusarium wilt.5,7,13−15 However, successful development and deployment of resistant cultivars requires an Received: November 28, 2012 Published: March 15, 2013 1772

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Herbarium, Department of Agriculture and Food Western Australia), highly virulent to strawberry,3,5 was used in this study. For inoculum preparation, pieces of filter paper colonized by Fof WUF-ST-FO51 were subcultured onto fresh potato dextrose agar (PDA) plates and maintained at 22 °C under continuous fluorescent light. After two weeks, spores were harvested from fungal cultures by flooding with 10 mL of sterile DI water and rubbing the agar surface gently with a bent glass rod. The resulting spore suspension was filtered through four layers of Miracloth (Calbiochem, Merck Pty. Ltd., Australia). The Fof conidia in the filtrate were washed three times by centrifugation (11000× g, 20 min) and resuspended in sterile DI water. The spore concentration was adjusted to 1 × 106 conidia/mL with sterile DI water.

understanding of the defense responses of strawberry against Fof. Most components and mechanisms involved in the defense of strawberry against pathogens remain poorly understood.15 Only a few studies have been conducted on the defense mechanisms of strawberry against pathogens, and these mainly involved fruit and/or foliar fungal pathogens.15,16 Proteomic approaches are powerful tools to understand the defense responses of plants against pathogens.17−19 They complement and extend genomic approaches, and are particularly critical as proteins reflect the true biochemical outcome of genetic information and indicate the biochemical pathways that may be involved.20 The at times poor correlation between mRNA transcript levels and protein abundance further necessitates the use of proteomic approaches.21,22 Through comparative proteomic analyses, proteins differentially expressed across the global protein expression profile in response to pathogen infection can be identified. This provides insights into the molecular components and mechanisms underlying the defense responses of plants against pathogens and can reveal the roles of these proteins in mediating disease resistance and susceptibility.17,18 The molecular components and mechanisms that underlie the defense responses occurring in the strawberry−Fof pathosystem remain unexplored. There have been no previous proteomic studies describing molecular changes in strawberry against Fof in relation to either a compatible or incompatible interaction. The identification of highly susceptible and highly resistant cultivars of strawberry5,13 provides the first suitable pathosystems enabling the exploration of compatible and incompatible interactions of strawberry with Fof. In this study, comparative proteome analyses were conducted to determine the temporal changes in root proteomes of the resistant cv. Festival and susceptible cv. Camarosa in response to Fof during the early stages of infection. The potential roles of the identified Fof-responsive proteins are discussed within the context of the strawberry-Fof pathosystem, with special focus on the different functional groups of proteins affected and their potential importance in mediating defense responses of strawberry against Fof.

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Plant Inoculation, Growth and Sampling

Seedlings were inoculated by incubating the roots in the Fof conidial suspension for 10 min (pathogen-inoculated treatment). Control seedlings were mock inoculated in DI water for 10 min (mock-inoculated treatment). Seedlings were then transplanted into plastic pots containing sterile sand watered to free draining with 25%-strength MS. Pots were arranged in a randomized block design and maintained at 22 °C with 60% relative humidity and a 16 h photoperiod. Six seedlings were randomly harvested at 4, 8, 12, 24, and 72 h post inoculation (hpi) and the roots were sampled for protein extraction. Samples were thoroughly washed with sterile DI water, blotted dry, and then flash-frozen in liquid nitrogen and transferred to −80 °C until proteins were extracted. Remaining plants were maintained at the same conditions for final disease assessment. This experiment was repeated to provide three independent biological replicates for each treatment. Disease Assessment

Plants were harvested two weeks post inoculation and shoots scored for disease severity on a 0−5 scale.14 Plants were removed from pots and thoroughly washed under running tap water. Shoots and roots were separated, placed in paper bags and oven-dried at 70 °C for one week before weighing. Fof was reisolated in all experiments from segments of freshly harvested root tissues. These root tissues were superficially disinfected with 1.25% (w/v) sodium hypochlorite for 1 min, and rinsed three times in sterile DI water before culturing on PDA plates to confirm that disease symptoms were in fact caused by Fof. Statistical analyses were conducted using GenStat (14th edition, VSN International Ltd., UK, 2012), with statistically significant differences of means computed at P < 0.001.

MATERIALS AND METHODS

Plant Material and Culture

Strawberry cvs Camarosa and Festival were purchased as certified commercial runners (Toolangi Certified Strawberry Runner Grower’s Co-op Ltd., Victoria, Australia). A tissue culture system was developed to aseptically produce seedlings from the two strawberry cultivars based on methods described by Fang et al.5 Strawberry seedlings were removed from culture tubes after four weeks, washed with deionized (DI) water, and then transplanted to plastic pots containing pasteurized sand watered to free draining with DI water. All pots were maintained in controlled environment rooms at 22 °C with 60% relative humidity and a 16 h photoperiod. Pots were covered with transparent polyethylene bags for the first three days to maintain high humidity post transplanting. All pots were watered with 25%-strength Murashige and Skoog (MS) salts (Sigma-Aldrich Pty. Ltd., Australia) every two days. Seedlings were removed from pots after four weeks and washed with DI water before inoculation.

Protein Extraction

Total proteins were extracted based on methods described by EI-Bebany et al.23 and Kaur et al.24 with some modifications. Root samples (2 g) were ground to a fine powder under liquid nitrogen. Portions (0.2 g) of the powdered tissue were aliquoted into 2 mL tubes and homogenized in 1.5 mL −20 °C acetone containing 20% (w/v) trichloroacetic acid (SigmaAldrich) and 0.2% (w/v) dithiothreitol (DTT; Sigma-Aldrich). Samples were incubated 12 h at −20 °C and precipitated protein collected by centrifugation for 20 min at 30000× g and 4 °C. The pellet was washed four times with 1 mL acetone containing 0.2% (w/v) DTT at −20 °C for 30 min and collected as described above. The final pellet was dried under vacuum (Speed-Vac concentrator, Savant Instruments, Holbrook, NY) and resuspended in rehydration buffer [7 M urea, 2 M thiourea, 1% DTT, 2% 3-[(3-cholamidopropyl)-dimethyl-

Fungal Isolate and Inoculum Preparation

A single-spore isolate of Fof (Fof WUF-ST-FO51, Accession No. WAC13497; Western Australian Culture Collection 1773

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expressed in pixel units (Optical density). The intensity of each spot was normalized by the local regression model of the software to compensate for gel-to-gel variation. The difference in normalized intensity of each spot between pathogeninoculated and mock-inoculated treatments of each cultivar at each time point was determined using the Student’s t-test (P < 0.05). The fold difference in abundance for each protein was calculated as the ratio of the spot intensity of the pathogeninoculated treatment to that of the corresponding mockinoculated treatment. A protein was only considered to be differentially expressed if it showed statistically significant difference at P < 0.05 and with at least a 2-fold difference in abundance between pathogen-inoculated and mock-inoculated treatments at one or more time points or if the protein was reproducibly unique to one cultivar. The molecular mass (Mr) of each protein was estimated by comparison with the standard marker, and the isoelectric point (pI) was determined by the spot position along the IPG strip.

ammonia]-1-propane sulfonate (CHAPS; Sigma-Aldrich), 2 mM phenylmethylsulfonyl fluoride (PMSF; Sigma-Aldrich)]. The samples were mixed for 12 h using a vortex mixer in ‘continuous mode’ at 4 °C. Protein solutions were clarified by centrifugation for 30 min at 30000× g and 22 °C, and repooled into a fresh tube. The protein concentration was determined by a modified Bradford protein assay (Bio-Rad) with BSA as the standard. The protein samples were purified and concentrated using a commercial kit (ReadyPrep 2-D Cleanup Kit, Bio-Rad) according to the manufacturer’s instructions, resuspended in rehydration buffer, and the protein concentrations requantified before being stored at −80 °C. Each protein extraction was conducted independently. Two-dimensional Gel Electrophoresis

For the first dimension, isoelectric focusing (IEF) of proteins was performed based on the method described by Marra et al.25 and Kaur et al.24 with some modifications. The immobilizedpH-gradient (IPG) strips (11 cm, pH 4−7; Bio-Rad) were passively rehydrated with 500 μg protein in 200 μL rehydration buffer containing 0.2% (v/v) ampholytes (Bio-Lyte, Bio-Rad) and 0.002% (w/v) bromophenol blue for 12 h at 22 °C. Proteins on IPG strips were focused (PROTEAN IEF Cell system, Bio-Rad) at 300 V in linear mode for 1 h, at 8 kV in linear model for 3 h, and finally at 8 kV in rapid mode until 35 kVh were reached. Strips were then equilibrated in 4 mL equilibration buffer [6 M urea, 50 mM Tris/HCl pH 8.8, 30% (v/v) glycerol, 2% (w/v) SDS, 0.002% bromophenol blue and 2% (w/v) DTT] with gentle shaking for 15 min followed by a second equilibration in the same buffer containing 2.5% (w/v) iodoacetamide instead of DTT for 15 min. Equilibrated IPG strips were placed on the top of 12.5% polyacrylamide gels. The separation was calibrated using a prestained molecular mass ladder (Precision plus protein all blue standards, Bio-Rad). Gels were run in buffer containing 25 mM Tris, 192 mM glycine and 0.1% (w/v) SDS at 15 mA per gel for 30 min, and then 30 mA per gel until the bromophenol blue reached the gel bottom. The gels were then washed three times in water for 15 min each, and stained for 12 h (BioSafe Coomassie stain, Bio-Rad) with gentle shaking. Stained gels were washed three times in water for 1 h each.

Protein Identification

Proteins excised from 2-D gels were destained and trypsin digested, and the resulting peptides extracted according to Bringans et al.26 Peptides were analyzed by MALDI-TOF/TOF mass spectrometer (5800 Proteomics Analyzer, Applied Biosystem, Foster City, CA). The MS/MS spectra were analyzed automatically to produce peptide sequences (DeNovo Explorer, Version 3.6, Applied Biosystems). All derived peptide sequences were searched against the Fragaria vesca genome database (34809 sequences)27 and the NCBI-LudwigNR Viridiplantae database (Version 20110805; 960 214 sequences) using the Mascot search engine (Version 2.2.1, Matrix Science Ltd., UK) for protein identification. The search parameters were trypsin as the digestion enzyme, one missed cleavage, peptide and MS/MS tolerance of 0.6 kDa each, and carbamidomethyl cysteine and methionine as the fixed and variable modifications, respectively. The ion score automatically calculated by the software was −10 × Log(P) where P is the probability that the observed match is a random event. An individual ion score greater than 29 indicated identity or extensive homology (P < 0.05) to a database entry. Final protein scores were obtained from ion scores as a nonprobabilistic basis for ranking protein hits. The protein identity was assigned as the protein that produced the highest score, had the best coverage of its peptide sequence with at least two matched peptides and good agreement between experimental and theoretical Mr and pI. The best matches were used to query the NCBI protein database using the BLASTP algorithm to verify the matches and to update annotations and identification.

Image analysis

Images of the 2-D gels were acquired (GS-800 calibrated densitometer, Bio-Rad, Berkeley, CA) with a red filter (595− 750 nm) and a resolution of 36.3 × 36.3 μm before analysis (PDQuest software, Version 8.0.1, Bio-Rad). Matched sets of replicate gels were created for each treatment and compared with corresponding matched sets from the other treatments. Each complete match-set included 12 gels for a given time point [three independent biological replicates per treatment for four treatments (resistant pathogen, resistant control, susceptible pathogen, and susceptible control)]. The quality criteria within the software (such as sensitivity, smoothing, streaks etc.) were kept constant for each match-set evaluated for the five time points. The automated spot detection feature was used to detect, match and compare spots. The analysis was manually validated to include missing spots and eliminate artifacts. The group consensus feature was used to manually check the matched spots within the treatment replicates. Only those spots present in all replicate gels were retained in the replicate group of each treatment, such that the correlation coefficient for each individual replicate group was 1.0. The intensity of each spot was determined using the spot quantification tool and

Cluster Analysis and Protein Classification

Hierarchical clustering was performed on the expression profiles of the identified Fof-responsive proteins across cultivars and over a time course (J-Express software, Version 2012; MolMine, Norway).28 Analysis was conducted on the log2transformed fold-difference of each protein using Bray−Curtis as the distance metric and Complete Linkage clustering as the linkage method. The functions of the identified proteins were assigned based on the available literature, Gene Ontology Annotation in the F. vesca genome database27 and/or the UniProt protein database29 to minimize redundancy in functional classifications. The cellular locations of the identified proteins were assigned based on the same databases combined with the SUBA database (Version 2.21).30 1774

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Comparative Proteome Analyses and Differentially Expressed Proteins

RESULTS

Disease Assessment

Temporal changes in root proteomes of the resistant cv. Festival and susceptible cv. Camarosa in response to Fof infection were determined during the early stages of infection from 4 to 72 hpi. Each gel from three biological replicates showed hundreds of proteins separated according to their Mr and pI, providing an overall picture of Fof-induced changes in root proteomes of cv. Camarosa and cv. Festival (Figure 2). Approximately 560 protein spots within the Mr range of 15− 100 kDa and the pI range of 4−7 were detected in all biological replicates. Comparative proteome analyses were focused on the most responsive proteins that showed significant and reproducible differences in abundance (P < 0.05 and at least 2-fold) in response to Fof infection and on those proteins that were unique to one cultivar. A total of 79 Fof-responsive proteins fit these criteria. Among these, four proteins were present only in cv. Festival and one protein was present only in cv. Camarosa (Figure 2; Table S1, Supporting Information). The number of differentially expressed proteins in the root proteome of cv. Festival was greater than that in cv. Camarosa at each time point (Figure 3). This was particularly evident at the early time points from 4 to 12 hpi, where there were about twice as many differentially expressed proteins in cv. Festival than in cv. Camarosa. In cv. Festival, the number of differentially expressed proteins increased in response to Fof infection until 12 hpi, where 52 proteins were differentially expressed, and then decreased at 24 and 72 hpi. In cv. Camarosa, the number of differentially expressed proteins increased in response to Fof infection until 24 hpi, where 26 proteins were differentially expressed, and then decreased at 72 hpi. At each time point, not only was the number of proteins up-regulated by at least 2-fold in cv. Festival greater than that in cv. Camarosa, but the proportion of differentially expressed proteins up-regulated in cv. Festival was also greater.

The effect of Fof on plants of strawberry cvs Camarosa and Festival was assessed at two weeks post inoculation (Figure 1).

Figure 1. Effect of Fusarium oxysporum f. sp. f ragariae (Fof) on plants of strawberry cvs Camarosa and Festival. (A) Disease index of plants mock-inoculated with DI water (control) and plants inoculated with Fof (pathogen) based on a 0−5 rating scale where 0 = well developed plant, no disease symptoms and 5 = dead plant. Asterisks indicate a significant difference (P < 0.001) compared with the Festival-pathogen treatment as determined by Student’s t-test. (B) Shoot dry weight and (C) root dry weight of plants mock-inoculated with DI water (control) and plants inoculated with Fof (pathogen). Asterisks indicate a significant difference (P < 0.001) compared with the control treatment of each cultivar as determined by Student’s t-test. Bars represent standard error (SE) of means (n = 24) from three biologically replicated experiments.

Protein Identification

The identities of the 79 differentially expressed proteins were established through MALDI-TOF/TOF MS/MS analysis (Table 1). These proteins were identified as “significant hits” based on the highest peptide ion scores, at least two matched peptides, and good agreement between the experimental and theoretical Mr and pI. All these identified proteins were matched to proteins in the F. vesca database. Searching against the NCBI-LudwigNR Viridiplantae database matched only three of these proteins to proteins from Fragaria × ananassa, due to the relatively few annotated Fragaria × ananassa proteins in the database. Twenty-five of the 79 identified proteins were located at more than one position in the same gel and were found to be protein isoforms with different experimental Mr and/or pI. Isoforms were detected for succinate dehydrogenase flavoprotein subunit 1 (spots 6903 and 7809), transketolase (spots 5901 and 6901), eukaryotic translation initiation factor 5A-2 (spots 4001 and 5101), protein disulfide-isomerase (spots 1809 and 2801), cysteine proteinase (spots 229 and 1216), ubiquitin (spots 806 and 1805), major latex protein (spots 1106, 2002 and 3101), Fra a allergen (spots 6112, 8103 and 8104), glutathione S-transferase (spots 4203, 6116 and 8101), peroxiredoxin-2F (spots 5107 and 8102), and S-adenosylmethionine synthetase 2 (spots 5507 and 6606).

There was a significant difference (P < 0.001) in disease index between pathogen-inoculated plants of cv. Camarosa and cv. Festival, where plants of cv. Camarosa were severely wilted and/or dead, with a mean disease index of 4.6, while all inoculated plants of cv. Festival were only slightly stunted, with a mean disease index of 1.0 (Figure 1A). In comparison, the mock-inoculated control plants of both cultivars were healthy. Only plants of cv. Camarosa showed a significant reduction (P < 0.001) in shoot dry weight following inoculation with Fof (Figure 1B). Similarly, there was a significant reduction (P < 0.001) in root dry weight only for plants of cv. Camarosa following inoculation with Fof (Figure 1C). 1775

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Figure 2. 2-D reference map of the strawberry root proteome in response to infection by Fusarium oxysporum f. sp. f ragariae (Fof). A representative gel image of the root proteins of (A) resistant cv. Festival and (B) susceptible cv. Camarosa at 12 h post inoculation. Proteins (500 μg each) were separated in the first dimension according to their isoelectric point (pI, 4−7) and in the second dimension according to their molecular mass (Mr, kDa). Differentially expressed proteins (P < 0.05 and greater than 2-fold difference) in response to Fof infection, indicated by numbered squares, were further selected for MS/MS analysis. The spot numbers correspond with those in Table 1.

Clustering of the Expression Profiles of the Fof-responsive Proteins

profiles from the other time points forming another distinct subgroup (Rb; Sb) for each cultivar.

Hierarchical clustering separated the overall expression profiles of the 79 Fof-responsive proteins across cultivars and over a course of infection into three distinct groups (Figure 4). Group I included 17 proteins that were mainly down-regulated in cv. Festival, but mainly up-regulated in cv. Camarosa in response to Fof infection. Group II was the largest group, containing 37 proteins that were mainly up-regulated in cv. Festival, but down-regulated in cv. Camarosa in response to Fof infection. Group III included 25 proteins that were mainly up-regulated in both cultivars in response to Fof infection, but the upregulation in cv. Festival was stronger than that in cv. Camarosa. The dynamic changes in abundance of the 79 Fofresponsive proteins clearly differentiated the two cultivars, as the expression profiles grouped strictly by cultivar (R and S). Furthermore, the expression profiles of the Fof-responsive proteins at the early time points of 4 and 8 hpi formed a distinct subgroup for each cultivar (Ra; Sa), with the expression

Functional Classification and Cellular Localization of the Fof-responsive Proteins

The 79 Fof-responsive proteins were classified into eight major functional groups (Figure 5; Table 1). About 60% of these proteins were involved in primary metabolism, protein metabolism, and stress and defense responses. About 27% of these proteins were associated with the categories antioxidant and detoxification, secondary metabolism, and hormone biosynthesis. The remaining proteins were involved in nucleotide binding or proteins with unclassified/unknown functions. Proteins involved in primary metabolism were further classified into five groups, including those related to glycolysis, tricarboxylic acid (TCA) cycle, pentose phosphate pathway (PPP), amino acid (AA) metabolism or lipid metabolism. Proteins involved in protein metabolism included those involved in protein synthesis, folding and degradation. 1776

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Figure 3. Numbers of differentially expressed proteins (P < 0.05 and greater than 2-fold difference) in the root proteome of resistant cv. Festival (R) and susceptible cv. Camarosa (S) of strawberry in response to infection by Fusarium oxysporum f. sp. f ragariae at 4, 8, 12, 24, and 72 h post inoculation (number following R and S).

regulated only in cv. Festival (Figure 7B, panel c; Figure S1; Table S1). Most Fof-responsive proteins involved in stress and defense responses were strongly up-regulated in cv. Festival (Figure 7C; Figure S1; Table S1, Supporting Information). Among these, three isoforms of major latex protein (MLP; spots 1106, 2002 and 3101) were up-regulated in both cultivars, but they were much more so in cv. Festival at 4 and 8 hpi (3 to 59-fold) than in cv. Camarosa (