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Cross-species Global Proteomics Reveals Conserved and Unique Processes in Phytophthora sojae and Phytophthora ramorum

2008; Elsevier BV; Volume: 7; Issue: 8 Linguagem: Inglês

10.1074/mcp.m700431-mcp200

1535-9484

Alon Savidor, Ryan S. Donahoo, Oscar P. Hurtado‐Gonzales, Miriam Land, Manesh Shah, Kurt Lamour, W. Hayes McDonald,

Genomics and Phylogenetic Studies

Phytophthora ramorum and Phytophthora sojae are destructive plant pathogens. P. sojae has a narrow host range, whereas P. ramorum has a wide host range. A global proteomics comparison of the vegetative (mycelium) and infective (germinating cyst) life stages of P. sojae and P. ramorum was conducted to identify candidate proteins involved in host range, early infection, and vegetative growth. Sixty-two candidates for early infection, 26 candidates for vegetative growth, and numerous proteins that may be involved in defining host specificity were identified. In addition, common life stage proteomic trends between the organisms were observed. In mycelia, proteins involved in transport and metabolism of amino acids, carbohydrates, and other small molecules were up-regulated. In the germinating cysts, up-regulated proteins associated with lipid transport and metabolism, cytoskeleton, and protein synthesis were observed. It appears that the germinating cyst catabolizes lipid reserves through the β-oxidation pathway to drive the extensive protein synthesis necessary to produce the germ tube and initiate infection. Once inside the host, the pathogen switches to vegetative growth in which energy is derived from glycolysis and utilized for synthesis of amino acids and other molecules that assist survival in the plant tissue. Phytophthora ramorum and Phytophthora sojae are destructive plant pathogens. P. sojae has a narrow host range, whereas P. ramorum has a wide host range. A global proteomics comparison of the vegetative (mycelium) and infective (germinating cyst) life stages of P. sojae and P. ramorum was conducted to identify candidate proteins involved in host range, early infection, and vegetative growth. Sixty-two candidates for early infection, 26 candidates for vegetative growth, and numerous proteins that may be involved in defining host specificity were identified. In addition, common life stage proteomic trends between the organisms were observed. In mycelia, proteins involved in transport and metabolism of amino acids, carbohydrates, and other small molecules were up-regulated. In the germinating cysts, up-regulated proteins associated with lipid transport and metabolism, cytoskeleton, and protein synthesis were observed. It appears that the germinating cyst catabolizes lipid reserves through the β-oxidation pathway to drive the extensive protein synthesis necessary to produce the germ tube and initiate infection. Once inside the host, the pathogen switches to vegetative growth in which energy is derived from glycolysis and utilized for synthesis of amino acids and other molecules that assist survival in the plant tissue. Organisms of the genus Phytophthora are destructive plant pathogens capable of infecting many agriculturally and ornamentally important crops (1Erwin D.C. Ribeiro O.K. Phytophthora Diseases Worldwide. The American Phytopathological Society, St. Paul, MN1996Google Scholar). To date, there are over 80 recognized species of Phytophthora. Although some Phytophthora species are able to infect a broad range of host plants, others are limited to a single host. Phytophthora ramorum and Phytophthora sojae are examples of each of these groups, respectively. The recently characterized P. ramorum is the causal agent of sudden oak death disease (2Rizzo D.M. Garbelotto M. Davidson J.M. Slaughter G.W. Koike S.T. Phytophthora ramorum as the cause of extensive mortality of Quercus spp. , and Lithocarpus densiflorus in California.Plant Dis. 2002; 86: 205-214Crossref PubMed Scopus (475) Google Scholar, 3Werres S. Marwitz R. Man in't Veld W.A. De Cock A.W.A.M. Bonants P.J.M. De Weerdt M. Themann K. Ilieva E. Baayen R.P. Phytophthora ramorum sp. nov., a new pathogen on Rhododendron and Viburnum.Mycol. Res. 2001; 10: 1166-1175Google Scholar). In addition to its destructive effect on live oak trees, as currently unfolding in forests in California and Oregon, P. ramorum is capable of infecting a wide range of trees and shrubs, such as bay laurel and viburnum (4Rizzo D.M. Garbelotto M. Hansen E.M. Phytophthora ramorum: integrative research and management of an emerging pathogen in California and Oregon forests.Annu. Rev. Phytopathol. 2005; 43: 309-335Crossref PubMed Scopus (343) Google Scholar). On the other hand, P. sojae, the causal agent of soybean root and stem rot, has a very narrow host range. Races of P. sojae are cultivar-specific with certain P. sojae isolates only infecting certain varieties of soybean (1Erwin D.C. Ribeiro O.K. Phytophthora Diseases Worldwide. The American Phytopathological Society, St. Paul, MN1996Google Scholar). The genomes of P. sojae and P. ramorum have been sequenced recently (5Tyler B.M. Tripathy S. Zhang X. Dehal P. Jiang R.H. Aerts A. Arredondo F.D. Baxter L. Bensasson D. Beynon J.L. Chapman J. Damasceno C.M. Dorrance A.E. Dou D. Dickerman A.W. Dubchak I.L. Garbelotto M. Gijzen M. Gordon S.G. Govers F. Grunwald N.J. Huang W. Ivors K.L. Jones R.W. Kamoun S. Krampis K. Lamour K.H. Lee M.K. McDonald W.H. Medina M. Meijer H.J. Nordberg E.K. Maclean D.J. Ospina-Giraldo M.D. Morris P.F. Phuntumart V. Putnam N.H. Rash S. Rose J.K. Sakihama Y. Salamov A.A. Savidor A. Scheuring C.F. Smith B.M. Sobral B.W. Terry A. Torto-Alalibo T.A. Win J. Xu Z. Zhang H. Grigoriev I.V. Rokhsar D.S. Boore J.L. Phytophthora genome sequences uncover evolutionary origins and mechanisms of pathogenesis.Science. 2006; 313: 1261-1266Crossref PubMed Scopus (823) Google Scholar). The genome of P. sojae is 95 Mbp and predicted to encode 19,027 genes, whereas the genome of P. ramorum is 65 Mbp and predicted to encode 15,743 genes. When compared with one another, the two organisms have a high degree of orthology and synteny between their genomes (5Tyler B.M. Tripathy S. Zhang X. Dehal P. Jiang R.H. Aerts A. Arredondo F.D. Baxter L. Bensasson D. Beynon J.L. Chapman J. Damasceno C.M. Dorrance A.E. Dou D. Dickerman A.W. Dubchak I.L. Garbelotto M. Gijzen M. Gordon S.G. Govers F. Grunwald N.J. Huang W. Ivors K.L. Jones R.W. Kamoun S. Krampis K. Lamour K.H. Lee M.K. McDonald W.H. Medina M. Meijer H.J. Nordberg E.K. Maclean D.J. Ospina-Giraldo M.D. Morris P.F. Phuntumart V. Putnam N.H. Rash S. Rose J.K. Sakihama Y. Salamov A.A. Savidor A. Scheuring C.F. Smith B.M. Sobral B.W. Terry A. Torto-Alalibo T.A. Win J. Xu Z. Zhang H. Grigoriev I.V. Rokhsar D.S. Boore J.L. Phytophthora genome sequences uncover evolutionary origins and mechanisms of pathogenesis.Science. 2006; 313: 1261-1266Crossref PubMed Scopus (823) Google Scholar, 6Jiang R.H. Tyler B.M. Govers F. Comparative analysis of Phytophthora genes encoding secreted proteins reveals conserved synteny and lineage-specific gene duplications and deletions.Mol. Plant-Microbe Interact. 2006; 19: 1311-1321Crossref PubMed Scopus (41) Google Scholar). Thus, despite the similarity between the two organisms, there are obviously specific differences that define the organisms in terms of their unique properties. One aim of this study was to identify candidate proteins that might be involved in host range capacity. This was achieved by comparing the expressed proteomes of P. sojae and P. ramorum and identifying differences between them. Phytophthora species are capable of reproducing sexually and asexually. During the sexual life cycle oospores, the sexual spores, are produced. Oospores have thick cell walls and can survive in the soil for years, thus allowing reinfection of their host plant in subsequent growing seasons. However, because the oospores require a dormancy period of several weeks before germination, it is the asexual life cycle that is responsible for rapid propagation and spread of the disease in the field or forest. During the asexual life cycle, the organism is able to differentiate into different life stages including mycelium, sporangium, zoospore, cyst, and germinating cyst (Fig. 1). Infection of a plant can be initiated when a zoospore, a motile kidney-shaped biflagellated cell, interacts with a compatible plant host. Upon contact with the plant host the zoospore sheds its flagella, encysts, and adheres. Shortly after encystment the cyst germinates by producing a germ tube that penetrates the host tissue directly or through wounds or natural openings. Once inside the plant, the pathogen grows and ramifies through the plant tissue as mycelium, the vegetative growth life stage of Phytophthora. In a compatible interaction the initial growth of the mycelium in the plant tissue is biotrophic where the pathogen evades the plant defense responses. Later growth is switched to necrotrophic, and the plant tissue is destroyed. A second aim of this study was to identify candidate proteins involved in initiation of infection. This was achieved by comparing the proteomes of the germinating cyst and the mycelium life stages for both organisms. Proteomics investigation of the mycelium and germinating cyst life stages from P. sojae and P. ramorum was carried out using multidimensional protein identification technology (MudPIT) 1The abbreviations used are: MudPIT, multidimensional protein identification technology; NSAF, normalized spectral abundance factor; GO, Gene Ontology; KOG, Eukaryotic Orthologous Groups; ID, identity; BLAST, Basic Local Alignment Search Tool; EGF, epidermal growth factor; SIG, sexually induced gene; PLD, phospholipase D; CRN, crinkling- and necrosis-inducing protein; CBEL, cellulose-binding elicitor lectin. 1The abbreviations used are: MudPIT, multidimensional protein identification technology; NSAF, normalized spectral abundance factor; GO, Gene Ontology; KOG, Eukaryotic Orthologous Groups; ID, identity; BLAST, Basic Local Alignment Search Tool; EGF, epidermal growth factor; SIG, sexually induced gene; PLD, phospholipase D; CRN, crinkling- and necrosis-inducing protein; CBEL, cellulose-binding elicitor lectin. 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In our case, orthologous proteins that were up-regulated in germinating cyst both in P. sojae and P. ramorum were identified as candidates involved in cyst germination and therefore may be involved in early infection. Orthologous protein pairs that were up-regulated in mycelium were identified as candidates important for vegetative growth. Proteins expressed uniquely in P. ramorum were identified as candidates allowing its broad host range capacity, whereas uniquely expressed P. sojae proteins were identified as candidates for defining its narrow host range. In addition, the methodological approach presented here includes use of orthology and a variety of novel bioinformatics strategies to analyze the data and represents a step forward in the analysis of proteomics data from closely related species. Cell tissue was prepared as described previously (16Savidor A. Donahoo R.S. Hurtado-Gonzales O. Verberkmoes N.C. Shah M.B. Lamour K.H. McDonald W.H. Expressed peptide tags: an additional layer of data for genome annotation.J. Proteome Res. 2006; 5: 3048-3058Crossref PubMed Scopus (31) Google Scholar). Briefly mycelia were generated by growing P. sojae strain P6497 (University of California, Riverside) and P. ramorum strain LT191 (University of California, Riverside) in clarified antibiotic-amended V8 juice broth. Asexual sporangia and zoospores were generated by growing P. sojae and P. ramorum on antibiotic-amended V8 agar plates according to standard protocols (1Erwin D.C. Ribeiro O.K. Phytophthora Diseases Worldwide. The American Phytopathological Society, St. Paul, MN1996Google Scholar). Zoospores were stimulated to encyst by vigorous shaking for 1–2 min and then waiting ∼1 h before harvesting the germinating cysts. The mycelium and germinating cyst were freeze-dried and ground using glass beads. Lysates were fractionated to membrane and soluble fractions by centrifugation, and the soluble fractions were digested with trypsin after denaturation, reduction, and alkylation as described previously (16Savidor A. Donahoo R.S. Hurtado-Gonzales O. Verberkmoes N.C. Shah M.B. Lamour K.H. McDonald W.H. Expressed peptide tags: an additional layer of data for genome annotation.J. Proteome Res. 2006; 5: 3048-3058Crossref PubMed Scopus (31) Google Scholar). Filtered and acidified samples were then loaded off line on a biphasic 150-μm-inner diameter fused silica column containing 3–3.5 cm of C18 reverse phase material followed by 3.5–4 cm of strong cation exchange phase. Loaded columns were placed directly upstream of a 100-μm-inner diameter front column packed with 15 cm of C18 reverse phase material. Samples were analyzed by 11-step MudPIT (LC/LC-MS/MS) on a linear ion trap mass spectrometer (LTQ, ThermoElectron, San Jose, CA) as described previously (16Savidor A. Donahoo R.S. Hurtado-Gonzales O. Verberkmoes N.C. Shah M.B. Lamour K.H. McDonald W.H. Expressed peptide tags: an additional layer of data for genome annotation.J. Proteome Res. 2006; 5: 3048-3058Crossref PubMed Scopus (31) Google Scholar). Flow rate at the tip was ∼200–300 nl/min. MS/MS spectra from RAW files of MudPIT experiments were extracted into MS2 files using Raw2MS2.exe (17McDonald W.H. Tabb D.L. Sadygov R.G. MacCoss M.J. Venable J. Graumann J. Johnson J.R. Cociorva D. Yates J.R. MS1, MS2, and SQT-three unified, compact, and easily parsed file formats for the storage of shotgun proteomic spectra and identifications.Rapid Commun. Mass Spectrom. 2004; 18: 2162-2168Crossref PubMed Scopus (294) Google Scholar, 18Narasimhan C. Tabb D.L. Verberkmoes N.C. Thompson M.R. Hettich R.L. Uberbacher E.C. MASPIC: intensity-based tandem mass spectrometry scoring scheme that improves peptide identification at high confidence.Anal. Chem. 2005; 77: 7581-7593Crossref PubMed Scopus (40) Google Scholar). Spectra were then assigned charge using MS2ZAssign (18Narasimhan C. Tabb D.L. Verberkmoes N.C. Thompson M.R. Hettich R.L. Uberbacher E.C. MASPIC: intensity-based tandem mass spectrometry scoring scheme that improves peptide identification at high confidence.Anal. Chem. 2005; 77: 7581-7593Crossref PubMed Scopus (40) Google Scholar) and searched against the predicted protein databases using the DBDigger algorithm (19Tabb D.L. Narasimhan C. Strader M.B. Hettich R.L. DBDigger: reorganized proteomic database identification that improves flexibility and speed.Anal. Chem. 2005; 77: 2464-2474Crossref PubMed Scopus (45) Google Scholar) in fully tryptic mode with the Multinomial Algorithm for Spectral Profile-based Intensity Comparison (MASPIC) scorer (18Narasimhan C. Tabb D.L. Verberkmoes N.C. Thompson M.R. Hettich R.L. Uberbacher E.C. MASPIC: intensity-based tandem mass spectrometry scoring scheme that improves peptide identification at high confidence.Anal. Chem. 2005; 77: 7581-7593Crossref PubMed Scopus (40) Google Scholar). No limit on missed cleavages was specified. The P. sojae protein database used was Psojae_proteins_VMD_V-1.0, release date July, 29, 2004, and included 19,027 P. sojae proteins as well as 52 common contaminants. The P. ramorum protein database used was Pramorum_proteins_VMD_V-1.0, release date July 29, 2004, and included 15,743 P. ramorum proteins as well as 52 common contaminates. Search results were filtered with the DTASelect algorithm (20Tabb D.L. McDonald W.H. Yates III, J.R. DTASelect and Contrast: tools for assembling and comparing protein identifications from shotgun proteomics.J. Proteome Res. 2002; 1: 21-26Crossref PubMed Scopus (1132) Google Scholar) using filter values allowing a 5% false discovery rate (supplemental Table S1) based on a concatenated reversed protein database search as described previously (16Savidor A. Donahoo R.S. Hurtado-Gonzales O. Verberkmoes N.C. Shah M.B. Lamour K.H. McDonald W.H. Expressed peptide tags: an additional layer of data for genome annotation.J. Proteome Res. 2006; 5: 3048-3058Crossref PubMed Scopus (31) Google Scholar). Briefly spectra from one representative MudPIT experiment for each organism were searched against a protein database containing the respective organism's protein sequences, the contaminants, and the reversed sequences of both proteins and contaminants (essentially representing random entries with the same amino acid composition and length). Filter values allowing one hit to the reverse database for every 19 to the forward database (5% false discovery rate) were determined using the SQTRevPuller algorithm (21Tabb D.L. Shah M.B. Strader M.B. Connelly H.M. Hettich R.L. Hurst G.B. Determination of peptide and protein ion charge states by Fourier transformation of isotope-resolved mass spectra.J. Am. Soc. Mass Spectrom. 2006; 17: 903-915Crossref PubMed Scopus (25) Google Scholar) and applied thereafter to all search results for the same organism. For all searches, a fixed modification of +57 Da on cysteine residues was included as cysteines were considered to be fully carboxamidomethylated. No variable modifications were included. Protein identification required two peptides per protein for identification. Mass tolerance for precursor ions was 3 Da, and mass tolerance for fragment ions was 0.5 Da. Comparison between protein lists was carried out using Microsoft Access and Perl scripts. To make comparisons between life stages, the union of the duplicate MudPIT results of the germinating cyst was compared with the union of the duplicate MudPIT results of the mycelium from the same organism. Spectral count was considered as the total number of MS/MS spectra corresponding to peptides from a given protein. Normalization of spectral counts was done using normalized spectral abundance factors (NSAFs) as described previously (22Florens L. Carozza M.J. Swanson S.K. Fournier M. Coleman M.K. Workman J.L. Washburn M.P. Analyzing chromatin remodeling complexes using shotgun proteomics and normalized spectral abundance factors.Methods. 2006; 40: 303-311Crossref PubMed Scopus (239) Google Scholar). Proteins groups that shared all of their peptides were assigned an NSAF value equal to the NSAF value for the group divided by the number of proteins in the group. A protein was determined to be up-regulated in one life stage versus another if (i) it was identified in both MudPIT duplicates of the up-regulated life stage and (ii) the sum of the normalized spectral counts from both duplicates was at least 5 times higher than the sum of normalized spectral counts in the other life stage duplicates. For statistical significance, a G-test was performed such that for each protein the sums of normalized spectral counts in each life stage were tested against the null hypothesis that they are not different from an expected 1:1 ratio with a two-tailed p value <0.05. Gene Ontology (GO) annotations as well as Eukaryotic Orthologous Groups (KOG) annotations were downloaded from the United States Department of Energy Joint Genome Institute Website into a Microsoft Access relational database and associated with their corresponding protein IDs. Signal peptide assignment was done using a local copy of SignalP (Center for Biological Sequence Analysis, Technical University of Denmark). Orthology was determined by reciprocal BLASTp of the P. sojae and P. ramorum protein databases. A pair of proteins was assigned orthology if both proteins were the best hit on their partner's BLAST results and had an E value <10−50 (supplemental Table S2). Differential expression between orthologous proteins was determined as described above for a protein in different life stages. To make comparisons between the two organisms, the union of the duplicate MudPIT results of each life stage from P. ramorum was compared, based on orthology, with the union of duplicate MudPIT results from the same life stage in P. sojae. For identification of host range-specific candidates, the raw lists of organism-specific proteins (supplemental Tables S3 and S4) were manually examined. Steps that were taken to identify host range-specific candidate from the raw lists included (a) high spectral count for confident protein identification and abundance, (b) observation of KOG and GO annotation, (c) BLASTp against the other organism protein database for identification of homologs with similar expression, (d) BLASTp against the non-redundant protein database for identification of homologs in other species, (e) ClustalW alignment with homologous proteins to confirm homology, (f) Pfam analysis for domain identification, and (g) literature search. All raw data and the supporting analysis are available upon request. Infection of a plant host by Phytophthora can be initiated when a Phytophthora zoospore adheres and encysts on the plant tissue, produces a germ tube, gains access to the plant host, and starts growing vegetatively throughout the plant tissue as mycelium. We investigated the proteomic differences between the germinating cyst and mycelium life stages from P. sojae and P. ramorum by MudPIT to identify candidate proteins that might be involved in early infection. Duplicate MudPIT experiments were carried out on each of the life stages from P. ramorum and P. sojae. Altogether 3897 P. ramorum and 2970 P. sojae proteins were identified. In the germinating cyst 2065 and 2089 P. ramorum proteins were identified in the first and second replicates (supplemental Tables S5 and S6), respectively, with 1293 of them found in both replicates (63% reproducibility). In the P. ramorum mycelium 1966 and 1962 proteins were identified in the first and second replicates (supplemental Tables S5 and S6), respectively, with 1339 of them found in both replicates (68% reproducibility). For P. sojae 1940 and 1779 germinating cyst proteins were identified in the first and second replicates (supplemental Tables S5 and S7), respectively, with 1248 of them found in both replicates (70% reproducibility). In the P. sojae mycelium 1313 and 1216 proteins were identified in the first and second replicates (supplemental Tables S5 and S7), respectively, with 825 of them found in both replicates (68% reproducibility). It should be noted that the major factor in reducing reproducibility comes from identification of low abundance proteins from which two peptides happened to be sampled in one replicate but not the other. For abundant proteins the reproducibility rate was much higher than stated above. One group of proteins that was identified in both life stages of both organisms included superoxide dismutases, catalases, and peroxidases. These enzymes break down reactive oxygen species (23Benov L. Fridovich I. 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