title: A database for Mycobacterium secretome analysis: 'MycoSec' to accelerate global health research.
abstract: Abstract Members of the genus Mycobacterium are notorious for their pathogenesis. Investigations from various perspectives have identified the pathogenic strategies employed by these lethal pathogens. Secretomes are believed to play crucial roles in host cell recognition and cross-talks, in cellular attachment, and in triggering other functions related to host pathogen interactions. However, a proper idea of the mycobacterial secretomes and their mechanism of functionality still remains elusive. In the present study, we have developed a comprehensive database of potential mycobacterial secretomes (MycoSec) using pre-existing algorithms for secretome prediction for researchers interested in this particular field. The database provides a platform for retrieval and analysis of identified secretomes in all finished genomes of the family Mycobacteriaceae. The database contains valuable information regarding secretory signal peptides (Sec type), lipoprotein signal peptides (Lipo type), and Twin arginine (RR/KR) signal peptides (TAT type), prevalent in mycobacteria. Information pertaining to COG analysis, codon usage, and gene expression of the predicted secretomes has also been incorporated in the database. MycoSec promises to be a useful repertoire providing a plethora of information regarding mycobacterial secretomes and may well be a platform to speed global health research. MycoSec is freely accessible at http://www.bicnbu.in/mycosec .
authors: 1 Bioinformatics Facility, Department of Botany, University of North Bengal , Siliguri, India .
authors: Ayan
authors: A
authors: Roy
authors: Sanghati
authors: S
authors: Bhattacharya
authors: Asim K
authors: AK
authors: Bothra
authors: Arnab
authors: A
authors: Sen
mesh_terms: D001426:Bacterial Proteins / Q000737:chemistry* / Q000378:metabolism; D019295:Computational Biology; D030562:Databases, Protein; D014943:Global Health; D006801:Humans; D009161:Mycobacterium / Q000235:genetics / Q000378:metabolism*; D021382:Protein Sorting Signals; D020543:Proteome / Q000737:chemistry* / Q000378:metabolism
chemical_list: D001426:Bacterial Proteins; D021382:Protein Sorting Signals; D020543:Proteome