Dataset Information

SNP-IT Tool for Identifying Subspecies and Associated Lineages of Mycobacterium tuberculosis Complex.

ABSTRACT: 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.

SUBMITTER: Lipworth S

PROVIDER: S-EPMC6390766 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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SNP-IT Tool for Identifying Subspecies and Associated Lineages of Mycobacterium tuberculosis Complex.

Lipworth Samuel S Jajou Rana R de Neeling Albert A Bradley Phelim P van der Hoek Wim W Maphalala Gugu G Bonnet Maryline M Sanchez-Padilla Elizabeth E Diel Roland R Niemann Stefan S Iqbal Zamin Z Smith Grace G Peto Tim T Crook Derrick D Walker Timothy T van Soolingen Dick D

Emerging infectious diseases 20190301 3

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 ...[more]

PMID: 30789126

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Project description:There is increasing evidence that strain variation in Mycobacterium tuberculosis complex (MTBC) might influence the outcome of tuberculosis infection and disease. To assess genotype-phenotype associations, phylogenetically robust molecular markers and appropriate genotyping tools are required. Most current genotyping methods for MTBC are based on mobile or repetitive DNA elements. Because these elements are prone to convergent evolution, the corresponding genotyping techniques are suboptimal for phylogenetic studies and strain classification. By contrast, single nucleotide polymorphisms (SNP) are ideal markers for classifying MTBC into phylogenetic lineages, as they exhibit very low degrees of homoplasy. In this study, we developed two complementary SNP-based genotyping methods to classify strains into the six main human-associated lineages of MTBC, the "Beijing" sublineage, and the clade comprising Mycobacterium bovis and Mycobacterium caprae. Phylogenetically informative SNPs were obtained from 22 MTBC whole-genome sequences. The first assay, referred to as MOL-PCR, is a ligation-dependent PCR with signal detection by fluorescent microspheres and a Luminex flow cytometer, which simultaneously interrogates eight SNPs. The second assay is based on six individual TaqMan real-time PCR assays for singleplex SNP-typing. We compared MOL-PCR and TaqMan results in two panels of clinical MTBC isolates. Both methods agreed fully when assigning 36 well-characterized strains into the main phylogenetic lineages. The sensitivity in allele-calling was 98.6% and 98.8% for MOL-PCR and TaqMan, respectively. Typing of an additional panel of 78 unknown clinical isolates revealed 99.2% and 100% sensitivity in allele-calling, respectively, and 100% agreement in lineage assignment between both methods. While MOL-PCR and TaqMan are both highly sensitive and specific, MOL-PCR is ideal for classification of isolates with no previous information, whereas TaqMan is faster for confirmation. Furthermore, both methods are rapid, flexible and comparably inexpensive.

Project description:Bovine tuberculosis (bTB), traditionally associated with Mycobacterium bovis, presents significant public health and economic challenges worldwide. This study investigated the causative agents of bTB in slaughtered cattle and buffalo in Lahore, Pakistan. Of the 3,581 animals screened, 34 were identified with gross TB-like lesions. The lesions were processed for culture, PCR, and Sanger sequencing to identify the causative agents of the disease. The results identified 10 Mycobacterium orygis and 8 Mycobacterium tuberculosis sensu stricto isolates. Whole-genome sequencing was performed on two M. orygis isolates, and the sequences were phylogenetically compared to 93 publicly available M. orygis sequences. The results also demonstrated that the JB21 and JB22 primers, which have been previously commonly applied to detect M. bovis in Pakistan, are unable to distinguish between M. tuberculosis complex subspecies. The identification of M. orygis and M. tuberculosis as causative agents of bTB in this slaughterhouse in Punjab may have important implications in identifying cases of zoonotic TB in humans and applying appropriate molecular tools to identify the prevalence of the disease. The data from this study align with recent findings suggesting M. orygis is the predominant cause of bTB in South Asia.IMPORTANCEThe study findings hold significant relevance to the Journal of Clinical Microbiology, as they directly impact the field. The first-time identification of Mycobacterium orygis and Mycobacterium tuberculosis as the predominant causative agents of bovine tuberculosis in Lahore, Pakistan underscores the urgent need for enhanced diagnostic methods. The study emphasizes the importance of improved assays for the accurate detection and differentiation of Mycobacterium subspecies. Additionally, the research addresses zoonotic risk assessment and public health implications, advocating for a multidisciplinary approach that integrates clinical microbiology with veterinary and human health sectors. These insights contribute to clinical microbiology knowledge, shaping effective strategies for disease prevention, surveillance, and control. The study's potential to advance the field makes it well suited for publication in the Microbiology Spectrum journal.

Dataset Information

SNP-IT Tool for Identifying Subspecies and Associated Lineages of Mycobacterium tuberculosis Complex.

Publications

SNP-IT Tool for Identifying Subspecies and Associated Lineages of Mycobacterium tuberculosis Complex.

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