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SNP-IT Tool for Identifying Subspecies and Associated Lineages of Mycobacterium tuberculosis Complex
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 t...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Centers for Disease Control and Prevention
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6390766/ https://www.ncbi.nlm.nih.gov/pubmed/30789126 http://dx.doi.org/10.3201/eid2503.180894 |
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author | Lipworth, Samuel Jajou, Rana de Neeling, Albert Bradley, Phelim van der Hoek, Wim Maphalala, Gugu Bonnet, Maryline Sanchez-Padilla, Elizabeth Diel, Roland Niemann, Stefan Iqbal, Zamin Smith, Grace Peto, Tim Crook, Derrick Walker, Timothy van Soolingen, Dick |
author_facet | Lipworth, Samuel Jajou, Rana de Neeling, Albert Bradley, Phelim van der Hoek, Wim Maphalala, Gugu Bonnet, Maryline Sanchez-Padilla, Elizabeth Diel, Roland Niemann, Stefan Iqbal, Zamin Smith, Grace Peto, Tim Crook, Derrick Walker, Timothy van Soolingen, Dick |
author_sort | Lipworth, Samuel |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6390766 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Centers for Disease Control and Prevention |
record_format | MEDLINE/PubMed |
spelling | pubmed-63907662019-03-06 SNP-IT Tool for Identifying Subspecies and Associated Lineages of Mycobacterium tuberculosis Complex Lipworth, Samuel Jajou, Rana de Neeling, Albert Bradley, Phelim van der Hoek, Wim Maphalala, Gugu Bonnet, Maryline Sanchez-Padilla, Elizabeth Diel, Roland Niemann, Stefan Iqbal, Zamin Smith, Grace Peto, Tim Crook, Derrick Walker, Timothy van Soolingen, Dick Emerg Infect Dis Research 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. Centers for Disease Control and Prevention 2019-03 /pmc/articles/PMC6390766/ /pubmed/30789126 http://dx.doi.org/10.3201/eid2503.180894 Text en https://creativecommons.org/licenses/by/4.0/This is a publication of the U.S. Government. This publication is in the public domain and is therefore without copyright. All text from this work may be reprinted freely. Use of these materials should be properly cited. |
spellingShingle | Research Lipworth, Samuel Jajou, Rana de Neeling, Albert Bradley, Phelim van der Hoek, Wim Maphalala, Gugu Bonnet, Maryline Sanchez-Padilla, Elizabeth Diel, Roland Niemann, Stefan Iqbal, Zamin Smith, Grace Peto, Tim Crook, Derrick Walker, Timothy van Soolingen, Dick SNP-IT Tool for Identifying Subspecies and Associated Lineages of Mycobacterium tuberculosis Complex |
title | SNP-IT Tool for Identifying Subspecies and Associated Lineages of Mycobacterium tuberculosis Complex |
title_full | SNP-IT Tool for Identifying Subspecies and Associated Lineages of Mycobacterium tuberculosis Complex |
title_fullStr | SNP-IT Tool for Identifying Subspecies and Associated Lineages of Mycobacterium tuberculosis Complex |
title_full_unstemmed | SNP-IT Tool for Identifying Subspecies and Associated Lineages of Mycobacterium tuberculosis Complex |
title_short | SNP-IT Tool for Identifying Subspecies and Associated Lineages of Mycobacterium tuberculosis Complex |
title_sort | snp-it tool for identifying subspecies and associated lineages of mycobacterium tuberculosis complex |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6390766/ https://www.ncbi.nlm.nih.gov/pubmed/30789126 http://dx.doi.org/10.3201/eid2503.180894 |
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