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Whole-genome sequencing-based analyses of drug-resistant Mycobacterium tuberculosis from Taiwan
Drug-resistant tuberculosis (DR-TB) posed challenges to global TB control. Whole-genome sequencing (WGS) is recommended for predicting drug resistance to guide DR-TB treatment and management. Nevertheless, data are lacking in Taiwan. Phenotypic drug susceptibility testing (DST) of 12 anti-TB drugs w...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9925824/ https://www.ncbi.nlm.nih.gov/pubmed/36781938 http://dx.doi.org/10.1038/s41598-023-29652-3 |
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author | Xiao, Yu-Xin Liu, Kuang-Hung Lin, Wan-Hsuan Chan, Tai-Hua Jou, Ruwen |
author_facet | Xiao, Yu-Xin Liu, Kuang-Hung Lin, Wan-Hsuan Chan, Tai-Hua Jou, Ruwen |
author_sort | Xiao, Yu-Xin |
collection | PubMed |
description | Drug-resistant tuberculosis (DR-TB) posed challenges to global TB control. Whole-genome sequencing (WGS) is recommended for predicting drug resistance to guide DR-TB treatment and management. Nevertheless, data are lacking in Taiwan. Phenotypic drug susceptibility testing (DST) of 12 anti-TB drugs was performed for 200 Mycobacterium tuberculosis isolates. WGS was performed using the Illumina platform. Drug resistance profiles and lineages were predicted in silico using the Total Genotyping Solution for TB (TGS-TB). Using the phenotypic DST results as a reference, WGS-based prediction demonstrated high concordance rates of isoniazid (95.0%), rifampicin (RIF) (98.0%), pyrazinamide (98.5%) and fluoroquinolones (FQs) (99.5%) and 96.0% to 99.5% for second-line injectable drugs (SLIDs); whereas, lower concordance rates of ethambutol (87.5%), streptomycin (88.0%) and ethionamide (84.0%). Furthermore, minimum inhibitory concentrations confirmed that RIF rpoB S450L, FQs gyrA D94G and SLIDs rrs a1401g conferred high resistance levels. Besides, we identified lineage-associated mutations in lineage 1 (rpoB H445Y and fabG1 c-15t) and predominant lineage 2 (rpoB S450L and rpsL K43R). The WGS-based prediction of drug resistance is highly concordant with phenotypic DST results and can provide comprehensive genetic information to guide DR-TB precision therapies in Taiwan. |
format | Online Article Text |
id | pubmed-9925824 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-99258242023-02-15 Whole-genome sequencing-based analyses of drug-resistant Mycobacterium tuberculosis from Taiwan Xiao, Yu-Xin Liu, Kuang-Hung Lin, Wan-Hsuan Chan, Tai-Hua Jou, Ruwen Sci Rep Article Drug-resistant tuberculosis (DR-TB) posed challenges to global TB control. Whole-genome sequencing (WGS) is recommended for predicting drug resistance to guide DR-TB treatment and management. Nevertheless, data are lacking in Taiwan. Phenotypic drug susceptibility testing (DST) of 12 anti-TB drugs was performed for 200 Mycobacterium tuberculosis isolates. WGS was performed using the Illumina platform. Drug resistance profiles and lineages were predicted in silico using the Total Genotyping Solution for TB (TGS-TB). Using the phenotypic DST results as a reference, WGS-based prediction demonstrated high concordance rates of isoniazid (95.0%), rifampicin (RIF) (98.0%), pyrazinamide (98.5%) and fluoroquinolones (FQs) (99.5%) and 96.0% to 99.5% for second-line injectable drugs (SLIDs); whereas, lower concordance rates of ethambutol (87.5%), streptomycin (88.0%) and ethionamide (84.0%). Furthermore, minimum inhibitory concentrations confirmed that RIF rpoB S450L, FQs gyrA D94G and SLIDs rrs a1401g conferred high resistance levels. Besides, we identified lineage-associated mutations in lineage 1 (rpoB H445Y and fabG1 c-15t) and predominant lineage 2 (rpoB S450L and rpsL K43R). The WGS-based prediction of drug resistance is highly concordant with phenotypic DST results and can provide comprehensive genetic information to guide DR-TB precision therapies in Taiwan. Nature Publishing Group UK 2023-02-13 /pmc/articles/PMC9925824/ /pubmed/36781938 http://dx.doi.org/10.1038/s41598-023-29652-3 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Xiao, Yu-Xin Liu, Kuang-Hung Lin, Wan-Hsuan Chan, Tai-Hua Jou, Ruwen Whole-genome sequencing-based analyses of drug-resistant Mycobacterium tuberculosis from Taiwan |
title | Whole-genome sequencing-based analyses of drug-resistant Mycobacterium tuberculosis from Taiwan |
title_full | Whole-genome sequencing-based analyses of drug-resistant Mycobacterium tuberculosis from Taiwan |
title_fullStr | Whole-genome sequencing-based analyses of drug-resistant Mycobacterium tuberculosis from Taiwan |
title_full_unstemmed | Whole-genome sequencing-based analyses of drug-resistant Mycobacterium tuberculosis from Taiwan |
title_short | Whole-genome sequencing-based analyses of drug-resistant Mycobacterium tuberculosis from Taiwan |
title_sort | whole-genome sequencing-based analyses of drug-resistant mycobacterium tuberculosis from taiwan |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9925824/ https://www.ncbi.nlm.nih.gov/pubmed/36781938 http://dx.doi.org/10.1038/s41598-023-29652-3 |
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