Genome-wide subcellular localization of putative outer membrane and extracellular proteins in Leptospira interrogans serovar Lai genome using bioinformatics approaches

Abstract

Background: In bacterial pathogens, both cell surface-exposed outer membrane proteins and proteins secreted into the extracellular environment play crucial roles in host-pathogen interaction and pathogenesis. Considerable efforts have been made to identify outer membrane (OM) and extracellular (EX) proteins produced by Leptospira interrogans, which may be used as novel targets for the development of infection markers and leptospirosis vaccines.

Result: In this study we used a novel computational framework based on combined prediction methods with deduction concept to identify putative OM and EX proteins encoded by the Leptospira interrogans genome. The framework consists of the following steps: (1) identifying proteins homologous to known proteins in subcellular localization databases derived from the "consensus vote" of computational predictions, (2) incorporating homology based search and structural information to enhance gene annotation and functional identification to infer the specific structural characters and localizations, and (3) developing a specific classifier for cytoplasmic proteins (CP) and cytoplasmic membrane proteins (CM) using Linear discriminant analysis (LDA). We have identified 114 putative EX and 63 putative OM proteins, of which 41% are conserved or hypothetical proteins containing sequence and/or protein folding structures similar to those of known EX and OM proteins.

Conclusion: Overall results derived from the combined computational analysis correlate with the available experimental evidence. This is the most extensive in silico protein subcellular localization identification to date for Leptospira interrogans serovar Lai genome that may be useful in protein annotation, discovery of novel genes and understanding the biology of Leptospira.

Figure 1

Flow chart of the method used for subcellular localizations of Leptospira interrogans serovar Lai genome. Protein sequences of Leptospira interrogans serovar Lai genome (4,727 ORFs) were analyzed for subcellular localization using PSORTb, ProtCompB, and Proteome analyst (PA) prediction. (a) The consensus vote was obtained from the majority vote type procedure to obtain the result with high prediction accuracy. If all 3 methods agree for localization it was assigned as a consensus vote. The remaining (1 or 2 out of 3 predicted result) was assigned as non-consensus vote. The consensus vote of CP and CM was used as a training set for the development of an LDA-based classifier for CP and CM in the next step. (b) The non-consensus vote results of OM, PP, and EX were further analyzed for sequence and structure homology by DBsubloc and GTD prediction. The non-consensus vote of EX, OM, and PP with significant homology or/and structure information were identified by DBsubloc and GTD prediction. (c) Non-consensus votes of CP, CM and the non predicted data from DBsubloc and GTD predictions were further analyzed for subcellular localization using LDA-based classifier for CP and CM. Significantly predicted results were proteins classified with more than 0.90 probability for CP and CM proteins. The remaining queries that could not be identified in this step were classified as "unknown" results.