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A revised SNP-based barcoding scheme for typing Mycobacterium tuberculosis complex isolates

Authors :
Egor Shitikov
Dmitry Bespiatykh
Source :
mSphere, Vol 8, Iss 4 (2023)
Publication Year :
2023
Publisher :
American Society for Microbiology, 2023.

Abstract

ABSTRACT The development of whole-genome sequencing technologies is gradually leading to a more detailed description of the population structure of the Mycobacterium tuberculosis complex (MTBC). In this study, we correlated previously published classifications on a collection of more than 10,000 genomes and proposed a new, comprehensive nomenclature that unifies the existing ones. In total, we identified 169 lineages and sublineages of M. tuberculosis/M. africanum and 9 animal-adapted species. For the purpose of organizing these genotypes in a more streamlined manner, we stratified them into five hierarchical levels. To represent the classification and compare it with the reference, we compiled a confirmatory data set of 670 high-quality isolates, which includes all genotypes and species of MTBC, and this confirmatory data set can serve as a basis for further studies. We proposed a set of 213 robust barcoding single-nucleotide polymorphisms and a suitable workflow for reliable differentiation of genotypes and species within the complex. This work integrates the results of all the major systematized studies to date to provide an understanding of the global diversity of the MTBC population structure. The results of this work may ultimately help to reliably determine the pathogen genotype and associate it with traits that reflect its prevalence, virulence, vaccination, and treatment efficiency, as well as to reliably find natural features revealed during its spread. IMPORTANCE Through years of research into the Mycobacterium tuberculosis complex (MTBC), a number of ambiguous phylogenetic classifications have emerged, which often overlap with one another. In the present study, we have combined all major studies on MTBC classification and inferred a unified, most complete to date classification and accompanying SNP barcodes.

Details

Language :
English
ISSN :
23795042
Volume :
8
Issue :
4
Database :
Directory of Open Access Journals
Journal :
mSphere
Publication Type :
Academic Journal
Accession number :
edsdoj.666567c91704f4ba97cafac6f8e8522
Document Type :
article
Full Text :
https://doi.org/10.1128/msphere.00169-23