Proteogenomic analysis of Mycobacterium tuberculosis by high resolution mass spectrometry

高分辨率质谱法对结核分枝杆菌进行蛋白质组学分析

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作者:Dhanashree S Kelkar, Dhirendra Kumar, Praveen Kumar, Lavanya Balakrishnan, Babylakshmi Muthusamy, Amit Kumar Yadav, Priyanka Shrivastava, Arivusudar Marimuthu, Sridhar Anand, Hema Sundaram, Reena Kingsbury, H C Harsha, Bipin Nair, T S Keshava Prasad, Devendra Singh Chauhan, Kiran Katoch, Vishwa Moha

Abstract

The genome sequencing of H37Rv strain of Mycobacterium tuberculosis was completed in 1998 followed by the whole genome sequencing of a clinical isolate, CDC1551 in 2002. Since then, the genomic sequences of a number of other strains have become available making it one of the better studied pathogenic bacterial species at the genomic level. However, annotation of its genome remains challenging because of high GC content and dissimilarity to other model prokaryotes. To this end, we carried out an in-depth proteogenomic analysis of the M. tuberculosis H37Rv strain using Fourier transform mass spectrometry with high resolution at both MS and tandem MS levels. In all, we identified 3176 proteins from Mycobacterium tuberculosis representing ~80% of its total predicted gene count. In addition to protein database search, we carried out a genome database search, which led to identification of ~250 novel peptides. Based on these novel genome search-specific peptides, we discovered 41 novel protein coding genes in the H37Rv genome. Using peptide evidence and alternative gene prediction tools, we also corrected 79 gene models. Finally, mass spectrometric data from N terminus-derived peptides confirmed 727 existing annotations for translational start sites while correcting those for 33 proteins. We report creation of a high confidence set of protein coding regions in Mycobacterium tuberculosis genome obtained by high resolution tandem mass-spectrometry at both precursor and fragment detection steps for the first time. This proteogenomic approach should be generally applicable to other organisms whose genomes have already been sequenced for obtaining a more accurate catalogue of protein-coding genes.

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