Characterization of protein secretion in Mycobacterium leprae using phoA fusions in Escherichia coli and Mycobacterium smegmatis
Complete sequencing and annotation of the M. leprae genome has provided new information related to proteins constituting its hypothetical proteome. Since M. leprae can not be grown in vitro, novel approaches are needed to determine which proteins are expressed during infection and whether these proteins are related to pathogenesis. Secreted proteins represent a distinct group of protein with respect to their structure and function, contribution to virulence and are of particular importance for vaccine development because they are often immunogenic and have the potential to be recognized early in infection. The objectives of this study were: 1) to identify putatively secreted proteins of M. leprae based on protein sequences homologies with known MT secreted proteins; 2) to apply bioinformatic tools designed to assess proteins for secretion, to proteins selected in objective 1 with the goal of improving the likelihood that selected proteins are secreted by M. leprae, 3) to validate secretion of selected ML proteins through genetic cloning of predicted secreted ML protein genes using surrogate host bacteria, E. coli and M. smegmatis. Bioinformatics identified 24 proteins with high probability for secretion in M. leprae. Fifteen of 24 ML genes showed more than 50% amino acid homology with their M. tuberculosis counterparts and were studied for gene expression and secretion. mRNA analysis identified transcripts for all Sec-dependent pathway proteins of 15 genes predicted to be secreted in M. leprae. PhoA fusion studies in E. coli showed that 5 of 6 (83%) ML proteins (ML0091, ML0097, ML0620, ML1811 and ML1812) were secreted in E. coli and 2 of 7 (29%) proteins (ML0715 and ML2569) were secreted in M. smegmatis. Only lipoproteins were secreted in M. smegmatis suggesting the importance of mycobacterial-related characteristics for secretion of ML lipoproteins. These results suggest that bioinformatic tools are reliable predictors for identifying secreted proteins in M. leprae and support the hypothesis that Sec-dependent secretion exists in M. leprae.
leprosy, secretion, intracellular bacteria, secreted proteins
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Veterinary Medical Sciences - Pathobiological Sciences