Abstract
BACKGROUND: Gray leaf spot is a devastating disease caused by Stemphylium lycopersici that threatens tomato-growing areas worldwide. Typically, many pathogenesis-related and unrelated secreted proteins can be predicted in genomes using bioinformatics and computer-based prediction algorithms, which help to elucidate the molecular mechanisms of pathogen-plant interactions. RESULTS: S. lycopersici-secreted proteins were predicted from 8997 proteins using a set of internet-based programs, including SignalP v4.1 TMHMM v2.0, big-PI Fungal Predictor, ProtComp V9.0 and TargetP v1.1. Analysis showed that 511 proteins are predicted to be secreted. These proteins vary from 51 to 600 residues in length, with signal peptides ranging from 14 to 30 residues in length. Functional analysis of differentially expressed proteins was performed using Blast2GO. Gene ontology analysis of 305 proteins classified them into 8 groups in biological process (BP), 6 groups in molecular function (MF), and 10 groups in cellular component (CC). Pathogen-host interaction (PHI) partners were predicted by performing BLASTp analysis of the predicted secreted proteins against the PHI database. In total, 159 secreted proteins in S. lycopersici might be involved in pathogenicity and virulence pathways. Scanning S. lycopersici-secreted proteins for the presence of carbohydrate-active enzyme (CAZyme)-coding gene homologs resulted in the prediction of 259 proteins. In addition, 12 of the 511 proteins predicted to be secreted are small cysteine-rich proteins (SCRPs). CONCLUSIONS: S. lycopersici secretory proteins have not yet been studied. The study of S. lycopersici genes predicted to encode secreted proteins is highly significant for research aimed at understanding the hypothesized roles of these proteins in host penetration, tissue necrosis, immune subversion and the identification of new targets for fungicides.