EST mining and functional expression assays identify extracellular effector proteins from the plant pathogen Phytophthora.
Plant pathogenic microbes have the remarkable ability to manipulate biochemical, physiological, and morphological processes in their host plants. These manipulations are achieved through a diverse array of effector molecules that can either promote infection or trigger defense responses. We describe a general functional genomics approach aimed at identifying extracellular effector proteins from plant pathogenic microorganisms by combining data mining of expressed sequence tags (ESTs) with virus-based high-throughput functional expression assays in plants. PexFinder, an algorithm for automated identification of extracellular proteins from EST data sets, was developed and applied to 2147 ESTs from the oomycete plant pathogen Phytophthora infestans. The program identified 261 ESTs (12.2%) corresponding to a set of 142 nonredundant Pex (Phytophthora extracellular protein) cDNAs. Of these, 78 (55%) Pex cDNAs were novel with no significant matches in public databases. Validation of PexFinder was performed using proteomic analysis of secreted protein of P. infestans. To identify which of the Pex cDNAs encode effector proteins that manipulate plant processes, high-throughput functional expression assays in plants were performed on 63 of the identified cDNAs using an Agrobacterium tumefaciens binary vector carrying the potato virus X (PVX) genome. This led to the discovery of two novel necrosis-inducing cDNAs, crn1 and crn2, encoding extracellular proteins that belong to a large and complex protein family in Phytophthora. Further characterization of the crn genes indicated that they are both expressed in P. infestans during colonization of the host plant tomato and that crn2 induced defense-response genes in tomato. Our results indicate that combining data mining using PexFinder with PVX-based functional assays can facilitate the discovery of novel pathogen effector proteins. In principle, this strategy can be applied to a variety of eukaryotic plant pathogens, including oomycetes, fungi, and nematodes.
Torto
Trudy A
TA
Department of Plant Pathology, The Ohio State University, Ohio Agricultural Research and Development Center, Wooster, Ohio 44691, USA.
Li
Shuang
S
Styer
Allison
A
Huitema
Edgar
E
Testa
Antonino
A
Gow
Neil A R
NA
van West
Pieter
P
Kamoun
Sophien
S
D020418:Algal Proteins / Q000096:biosynthesis / Q000235:genetics* / Q000502:physiology; D000465:Algorithms; D000595:Amino Acid Sequence / Q000235:genetics; D029742:Caenorhabditis elegans Proteins; D018076:DNA, Complementary / Q000096:biosynthesis / Q000235:genetics / Q000502:physiology; D004706:Endodeoxyribonucleases; D020224:Expressed Sequence Tags; D020869:Gene Expression Profiling / Q000379:methods*; D018551:Solanum lycopersicum / Q000235:genetics / Q000382:microbiology; D008969:Molecular Sequence Data; D005810:Multigene Family / Q000235:genetics; D009336:Necrosis; D010641:Phenotype; D010838:Phytophthora / Q000235:genetics* / Q000254:growth & development / Q000472:pathogenicity*; D010935:Plant Diseases / Q000235:genetics / Q000382:microbiology; D040901:Proteomics / Q000379:methods; D012986:Software Validation; D014774:Virulence
D020418:Algal Proteins; D029742:Caenorhabditis elegans Proteins; D018076:DNA, Complementary; C476219:CRN-1 protein, C elegans; D004706:Endodeoxyribonucleases