AUTHOR=Bajaj Amol O. , Saraswat Suraj , Knuuttila Juha E. A. , Freeke Joanna , Stielow J. Benjamin , Barker Adam P. 

TITLE=Accurate Identification of Closely Related Mycobacterium tuberculosis Complex Species by High Resolution Tandem Mass Spectrometry

JOURNAL=Frontiers in Cellular and Infection Microbiology

VOLUME=11

YEAR=2021

URL=https://www.frontiersin.org/journals/cellular-and-infection-microbiology/articles/10.3389/fcimb.2021.656880

DOI=10.3389/fcimb.2021.656880

ISSN=2235-2988

ABSTRACT=<p>Rapid and accurate differentiation of <italic>Mycobacterium tuberculosis</italic> complex (<italic>MTBC</italic>) species from other mycobacterium is essential for appropriate therapeutic management, timely intervention for infection control and initiation of appropriate health care measures. However, routine clinical characterization methods for <italic>Mycobacterium tuberculosis</italic> (<italic>Mtb</italic>) species remain both, time consuming and labor intensive. In the present study, an innovative liquid Chromatography-Mass Spectrometry method for the identification of clinically most relevant <italic>Mycobacterium tuberculosis</italic> complex species is tested using a model set of mycobacterium strains. The methodology is based on protein profiling of <italic>Mycobacterium tuberculosis</italic> complex isolates, which are used as markers of differentiation. To test the resolving power, speed, and accuracy of the method, four ATCC type strains and 37 recent clinical isolates of closely related species were analyzed using this new approach. Using different deconvolution algorithms, we detected hundreds of individual protein masses, with a subpopulation of these functioning as species-specific markers. This assay identified 216, 260, 222, and 201 proteoforms for <italic>M. tuberculosis</italic> ATCC 27294™, <italic>M. microti</italic> ATCC 19422™, <italic>M. africanum</italic> ATCC 25420™, and <italic>M. bovis</italic> ATCC 19210™ respectively. All clinical strains were identified to the correct species with a mean of 95% accuracy. Our study successfully demonstrates applicability of this novel mass spectrometric approach to identify clinically relevant <italic>Mycobacterium tuberculosis</italic> complex species that are very closely related and difficult to differentiate with currently existing methods. Here, we present the first proof-of-principle study employing a fast mass spectrometry-based method to identify the clinically most prevalent species within the <italic>Mycobacterium tuberculosis</italic> species complex.</p>