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      Comparative Proteomic Analyses of Avirulent, Virulent, and Clinical Strains of Mycobacterium tuberculosis Identify Strain-specific Patterns*

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          Abstract

          Mycobacterium tuberculosis is an adaptable intracellular pathogen, existing in both dormant as well as active disease-causing states. Here, we report systematic proteomic analyses of four strains, H37Ra, H37Rv, and clinical isolates BND and JAL, to determine the differences in protein expression patterns that contribute to their virulence and drug resistance. Resolution of lysates of the four strains by liquid chromatography, coupled to mass spectrometry analysis, identified a total of 2161 protein groups covering ∼54% of the predicted M. tuberculosis proteome. Label-free quantification analysis of the data revealed 257 differentially expressed protein groups. The differentially expressed protein groups could be classified into seven K-means cluster bins, which broadly delineated strain-specific variations. Analysis of the data for possible mechanisms responsible for drug resistance phenotype of JAL suggested that it could be due to a combination of overexpression of proteins implicated in drug resistance and the other factors. Expression pattern analyses of transcription factors and their downstream targets demonstrated substantial differential modulation in JAL, suggesting a complex regulatory mechanism. Results showed distinct variations in the protein expression patterns of Esx and mce1 operon proteins in JAL and BND strains, respectively. Abrogating higher levels of ESAT6, an important Esx protein known to be critical for virulence, in the JAL strain diminished its virulence, although it had marginal impact on the other strains. Taken together, this study reveals that strain-specific variations in protein expression patterns have a meaningful impact on the biology of the pathogen.

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          Most cited references65

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          Genetic requirements for mycobacterial survival during infection.

          Despite the importance of tuberculosis as a public health problem, we know relatively little about the molecular mechanisms used by the causative organism, Mycobacterium tuberculosis, to persist in the host. To define these mechanisms, we have mutated virtually every nonessential gene of M. tuberculosis and determined the effect disrupting each gene on the growth rate of this pathogen during infection. A total of 194 genes that are specifically required for mycobacterial growth in vivo were identified. The behavior of these mutants provides a detailed view of the changing environment that the bacterium encounters as infection proceeds. A surprisingly large fraction of these genes are unique to mycobacteria and closely related species, indicating that many of the strategies used by this unusual group of organisms are fundamentally different from other pathogens
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            The Mycobacterium tuberculosis regulatory network and hypoxia.

            We have taken the first steps towards a complete reconstruction of the Mycobacterium tuberculosis regulatory network based on ChIP-Seq and combined this reconstruction with system-wide profiling of messenger RNAs, proteins, metabolites and lipids during hypoxia and re-aeration. Adaptations to hypoxia are thought to have a prominent role in M. tuberculosis pathogenesis. Using ChIP-Seq combined with expression data from the induction of the same factors, we have reconstructed a draft regulatory network based on 50 transcription factors. This network model revealed a direct interconnection between the hypoxic response, lipid catabolism, lipid anabolism and the production of cell wall lipids. As a validation of this model, in response to oxygen availability we observe substantial alterations in lipid content and changes in gene expression and metabolites in corresponding metabolic pathways. The regulatory network reveals transcription factors underlying these changes, allows us to computationally predict expression changes, and indicates that Rv0081 is a regulatory hub.
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              The One Hour Yeast Proteome*

              We describe the comprehensive analysis of the yeast proteome in just over one hour of optimized analysis. We achieve this expedited proteome characterization with improved sample preparation, chromatographic separations, and by using a new Orbitrap hybrid mass spectrometer equipped with a mass filter, a collision cell, a high-field Orbitrap analyzer, and, finally, a dual cell linear ion trap analyzer (Q-OT-qIT, Orbitrap Fusion). This system offers high MS2 acquisition speed of 20 Hz and detects up to 19 peptide sequences within a single second of operation. Over a 1.3 h chromatographic method, the Q-OT-qIT hybrid collected an average of 13,447 MS1 and 80,460 MS2 scans (per run) to produce 43,400 (x̄) peptide spectral matches and 34,255 (x̄) peptides with unique amino acid sequences (1% false discovery rate (FDR)). On average, each one hour analysis achieved detection of 3,977 proteins (1% FDR). We conclude that further improvements in mass spectrometer scan rate could render comprehensive analysis of the human proteome within a few hours.
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                Author and article information

                Journal
                J Biol Chem
                J. Biol. Chem
                jbc
                jbc
                JBC
                The Journal of Biological Chemistry
                American Society for Biochemistry and Molecular Biology (11200 Rockville Pike, Suite 302, Rockville, MD 20852-3110, U.S.A. )
                0021-9258
                1083-351X
                1 July 2016
                5 May 2016
                5 May 2016
                : 291
                : 27
                : 14257-14273
                Affiliations
                From the []National Institute of Immunology and
                the []Cellular Immunology Group, International Centre for Genetic Engineering and Biotechnology, Aruna Asaf Ali Marg, New Delhi 110067,
                the [§ ]Drug Discovery Research Center, Translational Health Science and Technology Institute, Faridabad, Haryana 121004, and
                the []Institute of Mathematical Sciences, Chennai 600113, India
                Author notes
                [2 ] To whom correspondence should be addressed. Tel.: 91-11-26703789; Fax: 91-11-26742125; E-mail: vinaykn@ 123456nii.ac.in .
                [1]

                Both authors contributed equally to this work.

                Article
                M115.666123
                10.1074/jbc.M115.666123
                4933181
                27151218
                c9f660a0-3e83-4732-b204-a4295461683d
                © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

                Author's Choice—Final version free via Creative Commons CC-BY license.

                History
                : 19 May 2015
                : 17 March 2016
                Funding
                Funded by: Department of Biotechnology, Ministry of Science and Technology http://dx.doi.org/10.13039/501100001407
                Award ID: BT/PR3260/BRB/10/967/2011
                Funded by: Wellcome Trust/DBT India Alliance
                Award ID: Early Career Fellowship 500080-Z-09-Z
                Categories
                Microbiology

                Biochemistry
                mycobacteria,mycobacterium tuberculosis,protein expression,proteomics,virulence factor

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