Computational prediction and experimental assessment of secreted/surface proteins from Mycobacterium tuberculosis H37Rv.

ABSTRACT: The mycobacterial cell envelope has been implicated in the pathogenicity of tuberculosis and therefore has been a prime target for the identification and characterization of surface proteins with potential application in drug and vaccine development. In this study, the genome of Mycobacterium tuberculosis H37Rv was screened using Machine Learning tools that included feature-based predictors, general localizers and transmembrane topology predictors to identify proteins that are potentially secreted to the surface of M. tuberculosis, or to the extracellular milieu through different secretory pathways. The subcellular localization of a set of 8 hypothetically secreted/surface candidate proteins was experimentally assessed by cellular fractionation and immunoelectron microscopy (IEM) to determ

SUBMITTER: Vizcaino C 

PROVIDER: S-EPMC2891697 | biostudies-literature | 2010 Jun

REPOSITORIES: biostudies-literature