Abstract

Evidence currently suggests that as a species Mycobacterium tuberculosis exhibits very little genomic sequence diversity. Despite limited genetic variability, members of the M. tuberculosis complex (MTBC) have been shown to exhibit vast discrepancies in phenotypic presentation in terms of virulence, elicited immune response and transmissibility. Here, we used qualitative and quantitative mass spectrometry tools to investigate the proteomes of seven clinically-relevant mycobacterial strains—four M. tuberculosis strains, M. bovis, M. bovis BCG, and M. avium—that show varying degrees of pathogenicity and virulence, in an effort to rationalize the observed phenotypic differences. Following protein preparation, liquid chromatography mass spectrometry (LC MS/MS) and data capture were carried out using an LTQ Orbitrap Velos. Data analysis was carried out using a novel bioinformatics strategy, which yielded high protein coverage and was based on high confidence peptides. Through this approach, we directly identified a total of 3788 unique M. tuberculosis proteins out of a theoretical proteome of 4023 proteins and identified an average of 3290 unique proteins for each of the MTBC organisms (representing 82% of the theoretical proteomes), as well as 4250 unique M. avium proteins (80% of the theoretical proteome). Data analysis showed that all major classes of proteins are represented in every strain, but that there are significant quantitative differences between strains. Targeted selected reaction monitoring (SRM) assays were used to quantify the observed differential expression of a subset of 23 proteins identified by comparison to gene expression data as being of particular relevance to virulence. This analysis revealed differences in relative protein abundance between strains for proteins which may promote bacterial fitness in the more virulent W. Beijing strain. These differences may contribute to this strain's capacity for surviving within the host and resisting treatment, which has contributed to its rapid spread. Through this approach, we have begun to describe the proteomic portrait of a successful mycobacterial pathogen. Data are available via ProteomeXchange with identifier PXD004165.

Highlights

  • Tuberculosis disease is caused by the bacterium Mycobacterium tuberculosis, and remains one of the leading causes of death by a single pathogen worldwide

  • The exact mode by which increased pathogenicity is conferred in this lineage remains undetermined and is likely to be a combination of factors (Ribeiro et al, 2014), some proposed mechanisms include enhanced stress response, drug resistance and altered host-pathogen interactions, as has been reviewed previously (Hanekom et al, 2011; Warner et al, 2015)

  • The M. avium strain was obtained from the National Health Laboratory Services (NHLS) laboratory and was verified using line probe assays

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Summary

Introduction

Tuberculosis disease is caused by the bacterium Mycobacterium tuberculosis, and remains one of the leading causes of death by a single pathogen worldwide. According to whole-genome analysis, members of the M. tuberculosis complex (MTBC) exhibit the greatest degree of genetic conservation above all other pathogenic bacteria (99.9%). This strict level of observed genetic homogeneity initially led to the assumption that genetic variety amongst different strains would not be of any clinical significance (Homolka et al, 2008). The exact mode by which increased pathogenicity is conferred in this lineage remains undetermined and is likely to be a combination of factors (Ribeiro et al, 2014), some proposed mechanisms include enhanced stress response, drug resistance and altered host-pathogen interactions, as has been reviewed previously (Hanekom et al, 2011; Warner et al, 2015). Some closely related strains in the M. tuberculosis complex (MTBC) have attenuated virulence in humans (such as the vaccine strain BCG), or are not typically human pathogens and will only opportunistically infect immunocompromised humans (Desforges and Horsburgh, 1991; Wang and Behr, 2014; Halstrom et al, 2015)

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