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The clinical phenotype of zoonotic tuberculosis and its contribution to the global burden of disease are poorly understood and probably underestimated. This shortcoming is partly because of the inability of currently available laboratory and in silico tools to accurately identify all subspecies of the Mycobacterium tuberculosis complex (MTBC). We present SNPs to Identify TB (SNP-IT), a single-nucleotide polymorphism-based tool to identify all members of MTBC, including animal clades. By applying SNP-IT to a collection of clinical genomes from a UK reference laboratory, we detected an unexpectedly high number of M. orygis isolates. M. orygis is seen at a similar rate to M. bovis, yet M. orygis cases have not been previously described in the United Kingdom. From an international perspective, it is possible that M. orygis is an underestimated zoonosis. Accurate identification will enable study of the clinical phenotype, host range, and transmission mechanisms of all subspecies of MTBC in greater detail.

Original publication

DOI

10.3201/eid2503.180894

Type

Journal article

Journal

Emerging infectious diseases

Publication Date

03/2019

Volume

25

Pages

482 - 488

Keywords

Animals, Humans, Mycobacterium tuberculosis, Tuberculosis, Zoonoses, DNA, Bacterial, Genetic Markers, Antitubercular Agents, Prevalence, Computational Biology, Phylogeny, Drug Resistance, Bacterial, Polymorphism, Single Nucleotide, Molecular Typing