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Integrating standardized whole genome sequence analysis with a global Mycobacterium tuberculosis antibiotic resistance knowledgebase
Drug-resistant tuberculosis poses a persistent public health threat. The ReSeqTB platform is a collaborative, curated knowledgebase, designed to standardize and aggregate global Mycobacterium tuberculosis complex (MTBC) variant data from whole genome sequencing (WGS) with phenotypic drug susceptibil...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6194142/ https://www.ncbi.nlm.nih.gov/pubmed/30337678 http://dx.doi.org/10.1038/s41598-018-33731-1 |
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author | Ezewudo, Matthew Borens, Amanda Chiner-Oms, Álvaro Miotto, Paolo Chindelevitch, Leonid Starks, Angela M. Hanna, Debra Liwski, Richard Zignol, Matteo Gilpin, Christopher Niemann, Stefan Kohl, Thomas Andreas Warren, Robin M. Crook, Derrick Gagneux, Sebastien Hoffner, Sven Rodrigues, Camilla Comas, Iñaki Engelthaler, David M. Alland, David Rigouts, Leen Lange, Christoph Dheda, Keertan Hasan, Rumina McNerney, Ruth Cirillo, Daniela M. Schito, Marco Rodwell, Timothy C. Posey, James |
author_facet | Ezewudo, Matthew Borens, Amanda Chiner-Oms, Álvaro Miotto, Paolo Chindelevitch, Leonid Starks, Angela M. Hanna, Debra Liwski, Richard Zignol, Matteo Gilpin, Christopher Niemann, Stefan Kohl, Thomas Andreas Warren, Robin M. Crook, Derrick Gagneux, Sebastien Hoffner, Sven Rodrigues, Camilla Comas, Iñaki Engelthaler, David M. Alland, David Rigouts, Leen Lange, Christoph Dheda, Keertan Hasan, Rumina McNerney, Ruth Cirillo, Daniela M. Schito, Marco Rodwell, Timothy C. Posey, James |
author_sort | Ezewudo, Matthew |
collection | PubMed |
description | Drug-resistant tuberculosis poses a persistent public health threat. The ReSeqTB platform is a collaborative, curated knowledgebase, designed to standardize and aggregate global Mycobacterium tuberculosis complex (MTBC) variant data from whole genome sequencing (WGS) with phenotypic drug susceptibility testing (DST) and clinical data. We developed a unified analysis variant pipeline (UVP) (https://github.com/CPTR-ReSeqTB/UVP) to identify variants and assign lineage from MTBC sequence data. Stringent thresholds and quality control measures were incorporated in this open source tool. The pipeline was validated using a well-characterized dataset of 90 diverse MTBC isolates with conventional DST and DNA Sanger sequencing data. The UVP exhibited 98.9% agreement with the variants identified using Sanger sequencing and was 100% concordant with conventional methods of assigning lineage. We analyzed 4636 publicly available MTBC isolates in the ReSeqTB platform representing all seven major MTBC lineages. The variants detected have an above 94% accuracy of predicting drug based on the accompanying DST results in the platform. The aggregation of variants over time in the platform will establish confidence-graded mutations statistically associated with phenotypic drug resistance. These tools serve as critical reference standards for future molecular diagnostic assay developers, researchers, public health agencies and clinicians working towards the control of drug-resistant tuberculosis. |
format | Online Article Text |
id | pubmed-6194142 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-61941422018-10-24 Integrating standardized whole genome sequence analysis with a global Mycobacterium tuberculosis antibiotic resistance knowledgebase Ezewudo, Matthew Borens, Amanda Chiner-Oms, Álvaro Miotto, Paolo Chindelevitch, Leonid Starks, Angela M. Hanna, Debra Liwski, Richard Zignol, Matteo Gilpin, Christopher Niemann, Stefan Kohl, Thomas Andreas Warren, Robin M. Crook, Derrick Gagneux, Sebastien Hoffner, Sven Rodrigues, Camilla Comas, Iñaki Engelthaler, David M. Alland, David Rigouts, Leen Lange, Christoph Dheda, Keertan Hasan, Rumina McNerney, Ruth Cirillo, Daniela M. Schito, Marco Rodwell, Timothy C. Posey, James Sci Rep Article Drug-resistant tuberculosis poses a persistent public health threat. The ReSeqTB platform is a collaborative, curated knowledgebase, designed to standardize and aggregate global Mycobacterium tuberculosis complex (MTBC) variant data from whole genome sequencing (WGS) with phenotypic drug susceptibility testing (DST) and clinical data. We developed a unified analysis variant pipeline (UVP) (https://github.com/CPTR-ReSeqTB/UVP) to identify variants and assign lineage from MTBC sequence data. Stringent thresholds and quality control measures were incorporated in this open source tool. The pipeline was validated using a well-characterized dataset of 90 diverse MTBC isolates with conventional DST and DNA Sanger sequencing data. The UVP exhibited 98.9% agreement with the variants identified using Sanger sequencing and was 100% concordant with conventional methods of assigning lineage. We analyzed 4636 publicly available MTBC isolates in the ReSeqTB platform representing all seven major MTBC lineages. The variants detected have an above 94% accuracy of predicting drug based on the accompanying DST results in the platform. The aggregation of variants over time in the platform will establish confidence-graded mutations statistically associated with phenotypic drug resistance. These tools serve as critical reference standards for future molecular diagnostic assay developers, researchers, public health agencies and clinicians working towards the control of drug-resistant tuberculosis. Nature Publishing Group UK 2018-10-18 /pmc/articles/PMC6194142/ /pubmed/30337678 http://dx.doi.org/10.1038/s41598-018-33731-1 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Ezewudo, Matthew Borens, Amanda Chiner-Oms, Álvaro Miotto, Paolo Chindelevitch, Leonid Starks, Angela M. Hanna, Debra Liwski, Richard Zignol, Matteo Gilpin, Christopher Niemann, Stefan Kohl, Thomas Andreas Warren, Robin M. Crook, Derrick Gagneux, Sebastien Hoffner, Sven Rodrigues, Camilla Comas, Iñaki Engelthaler, David M. Alland, David Rigouts, Leen Lange, Christoph Dheda, Keertan Hasan, Rumina McNerney, Ruth Cirillo, Daniela M. Schito, Marco Rodwell, Timothy C. Posey, James Integrating standardized whole genome sequence analysis with a global Mycobacterium tuberculosis antibiotic resistance knowledgebase |
title | Integrating standardized whole genome sequence analysis with a global Mycobacterium tuberculosis antibiotic resistance knowledgebase |
title_full | Integrating standardized whole genome sequence analysis with a global Mycobacterium tuberculosis antibiotic resistance knowledgebase |
title_fullStr | Integrating standardized whole genome sequence analysis with a global Mycobacterium tuberculosis antibiotic resistance knowledgebase |
title_full_unstemmed | Integrating standardized whole genome sequence analysis with a global Mycobacterium tuberculosis antibiotic resistance knowledgebase |
title_short | Integrating standardized whole genome sequence analysis with a global Mycobacterium tuberculosis antibiotic resistance knowledgebase |
title_sort | integrating standardized whole genome sequence analysis with a global mycobacterium tuberculosis antibiotic resistance knowledgebase |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6194142/ https://www.ncbi.nlm.nih.gov/pubmed/30337678 http://dx.doi.org/10.1038/s41598-018-33731-1 |
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