Whole genome sequencing-based identification of human tuberculosis caused by animal-lineage Mycobacterium orygis

A recently described member of the complex (MTBC) is , which can cause disease primarily in animals but also in humans. Although has been reported from different geographic regions around the world, due to a lack of proper identification techniques, the contribution of this emerging pathogen to the...

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Veröffentlicht in:Journal of clinical microbiology 2023-11, Vol.61 (11), p.e0026023-e0026023
Hauptverfasser: Islam, Md Rashedul, Sharma, Meenu K, KhunKhun, Rupinder, Shandro, Cary, Sekirov, Inna, Tyrrell, Gregory J, Soualhine, Hafid
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Sprache:eng
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Zusammenfassung:A recently described member of the complex (MTBC) is , which can cause disease primarily in animals but also in humans. Although has been reported from different geographic regions around the world, due to a lack of proper identification techniques, the contribution of this emerging pathogen to the global burden of zoonotic tuberculosis is not fully understood. In the present work, we report single nucleotide polymorphism (SNP) analysis using whole genome sequencing (WGS) that can accurately identify and differentiate it from other members of the MTBC species. WGS-based SNP analysis was performed for 61 isolates from different provinces in Canada that were identified as . A total of 56 . sequences from the public databases were also included in the analysis. Several unique SNPs in the , , , , , and genes were used to determine their effectiveness as genetic markers for the identification of . To the best of our knowledge, five of these SNPs, viz., (A→G), (T→C), (A→T), (T→C), and (C→G), are reported for the first time in this study. Our results also revealed several SNPs specific to other species within MTBC. The phylogenetic analysis shows that the studied genomes were genetically diverse and clustered with sequences of human and animal origin reported from different geographic locations. Therefore, the present study provides a new insight into the high-confidence identification of from MTBC species based on WGS data, which can be useful for reference and diagnostic laboratories.
ISSN:0095-1137
1098-660X
DOI:10.1128/jcm.00260-23