SNP-IT tool for identifying subspecies and associated lineages of Mycobacterium tuberculosis complex

Samuel Lipworth; Rana Jajou; Albert De Neeling; Phelim Bradley; Wim Van Der Hoek; Gugu Maphalala; Maryline Bonnet; Elizabeth Sanchez-Padilla; Roland Diel; Stefan Niemann; Zamin Iqbal; Grace Smith; Tim Peto; Derrick Crook; Timothy Walker; Dick Van Soolingen

doi:10.3201/eid2503.180894

SNP-IT tool for identifying subspecies and associated lineages of Mycobacterium tuberculosis complex

Samuel Lipworth^*, Rana Jajou, Albert De Neeling, Phelim Bradley, Wim Van Der Hoek, Gugu Maphalala, Maryline Bonnet, Elizabeth Sanchez-Padilla, Roland Diel, Stefan Niemann, Zamin Iqbal, Grace Smith, Tim Peto, Derrick Crook, Timothy Walker, Dick Van Soolingen

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

45 Citations (Scopus)

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 MTBCin greater detail.

Original language	English
Pages (from-to)	482-488
Number of pages	7
Journal	Emerging Infectious Diseases
Volume	25
Issue number	3
DOIs	https://doi.org/10.3201/eid2503.180894
Publication status	Published - Mar 2019

Bibliographical note

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© 2019, Centers for Disease Control and Prevention (CDC). All rights reserved.

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10.3201/eid2503.180894

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Lipworth, S., Jajou, R., De Neeling, A., Bradley, P., Van Der Hoek, W., Maphalala, G., Bonnet, M., Sanchez-Padilla, E., Diel, R., Niemann, S., Iqbal, Z., Smith, G., Peto, T., Crook, D., Walker, T., & Van Soolingen, D. (2019). SNP-IT tool for identifying subspecies and associated lineages of Mycobacterium tuberculosis complex. Emerging Infectious Diseases, 25(3), 482-488. https://doi.org/10.3201/eid2503.180894

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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 MTBCin greater detail.",

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Lipworth, S, Jajou, R, De Neeling, A, Bradley, P, Van Der Hoek, W, Maphalala, G, Bonnet, M, Sanchez-Padilla, E, Diel, R, Niemann, S, Iqbal, Z, Smith, G, Peto, T, Crook, D, Walker, T & Van Soolingen, D 2019, 'SNP-IT tool for identifying subspecies and associated lineages of Mycobacterium tuberculosis complex', Emerging Infectious Diseases, vol. 25, no. 3, pp. 482-488. https://doi.org/10.3201/eid2503.180894

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AU - Lipworth, Samuel

AU - Jajou, Rana

AU - De Neeling, Albert

AU - Bradley, Phelim

AU - Van Der Hoek, Wim

AU - Maphalala, Gugu

AU - Bonnet, Maryline

AU - Sanchez-Padilla, Elizabeth

AU - Diel, Roland

AU - Niemann, Stefan

AU - Iqbal, Zamin

AU - Smith, Grace

AU - Peto, Tim

AU - Crook, Derrick

AU - Walker, Timothy

AU - Van Soolingen, Dick

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AB - 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 MTBCin greater detail.

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SNP-IT tool for identifying subspecies and associated lineages of Mycobacterium tuberculosis complex

Abstract

Bibliographical note

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