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Genetic composition and evolution of the prevalent Mycobacterium tuberculosis lineages 2 and 4 in the Chinese and Zhejiang Province populations

BACKGROUND: There are seven human-adaptation lineages of Mycobacterium tuberculosis (Mtb). Tuberculosis (TB) dissemination is strongly influenced by human movements and host genetics. The detailed lineage distribution evolution of Mtb in Zhejiang Province is unknown. We aim to determine how differen...

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Autores principales: Wu, Beibei, Zhu, Wenlong, Wang, Yue, Wang, Qi, Zhou, Lin, Liu, Zhengwei, Bi, Lijun, Barun, Mathema, Kreiswirth, Barry N., Chen, Liang, Chen, Songhua, Wang, Xiaomeng, Wang, Weibing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8379736/
https://www.ncbi.nlm.nih.gov/pubmed/34419157
http://dx.doi.org/10.1186/s13578-021-00673-7
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author Wu, Beibei
Zhu, Wenlong
Wang, Yue
Wang, Qi
Zhou, Lin
Liu, Zhengwei
Bi, Lijun
Barun, Mathema
Kreiswirth, Barry N.
Chen, Liang
Chen, Songhua
Wang, Xiaomeng
Wang, Weibing
author_facet Wu, Beibei
Zhu, Wenlong
Wang, Yue
Wang, Qi
Zhou, Lin
Liu, Zhengwei
Bi, Lijun
Barun, Mathema
Kreiswirth, Barry N.
Chen, Liang
Chen, Songhua
Wang, Xiaomeng
Wang, Weibing
author_sort Wu, Beibei
collection PubMed
description BACKGROUND: There are seven human-adaptation lineages of Mycobacterium tuberculosis (Mtb). Tuberculosis (TB) dissemination is strongly influenced by human movements and host genetics. The detailed lineage distribution evolution of Mtb in Zhejiang Province is unknown. We aim to determine how different sub-lineages are transmitted and distributed within China and Zhejiang Province. METHODS: We analysed whole-genome sequencing data for a worldwide collection of 1154 isolates and a provincial collection of 1296 isolates, constructed the best-scoring maximum likelihood phylogenetic tree. Bayesian evolutionary analysis was used to calculate the latest common ancestor of lineages 2 and 4. The antigenic diversity of human T cell epitopes was evaluated by calculating the pairwise dN/dS ratios. RESULTS: Of the Zhejiang isolates, 964 (74.38%) belonged to lineage 2 and 332 (25.62%) belonged to lineage 4. The distributions of the sub-lineages varied across the geographic regions of Zhejiang Province. L2.2 is the most ancient sub-lineage in Zhejiang, first appearing approximately 6897 years ago (95% highest posterior density interval (HDI): 6513–7298). L4.4 is the most modern sub-lineage, first appearing approximately 2217 years ago (95% HDI: 1864–2581). The dN/dS ratios showed that the epitope and non-epitope regions of lineage 2 strains were significantly (P < 0.001) more conserved than those of lineage 4. CONCLUSIONS: An increase in the frequency of lineage 4 may reflect its successful transmission over the last 20 years. The recent common ancestors of the sub-lineages and their transmission routes are relevant to the entry of humans into China and Zhejiang Province. Diversity in T cell epitopes may prevent Mycobacterium tuberculosis from being recognized by the immune system. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13578-021-00673-7.
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spelling pubmed-83797362021-08-23 Genetic composition and evolution of the prevalent Mycobacterium tuberculosis lineages 2 and 4 in the Chinese and Zhejiang Province populations Wu, Beibei Zhu, Wenlong Wang, Yue Wang, Qi Zhou, Lin Liu, Zhengwei Bi, Lijun Barun, Mathema Kreiswirth, Barry N. Chen, Liang Chen, Songhua Wang, Xiaomeng Wang, Weibing Cell Biosci Research BACKGROUND: There are seven human-adaptation lineages of Mycobacterium tuberculosis (Mtb). Tuberculosis (TB) dissemination is strongly influenced by human movements and host genetics. The detailed lineage distribution evolution of Mtb in Zhejiang Province is unknown. We aim to determine how different sub-lineages are transmitted and distributed within China and Zhejiang Province. METHODS: We analysed whole-genome sequencing data for a worldwide collection of 1154 isolates and a provincial collection of 1296 isolates, constructed the best-scoring maximum likelihood phylogenetic tree. Bayesian evolutionary analysis was used to calculate the latest common ancestor of lineages 2 and 4. The antigenic diversity of human T cell epitopes was evaluated by calculating the pairwise dN/dS ratios. RESULTS: Of the Zhejiang isolates, 964 (74.38%) belonged to lineage 2 and 332 (25.62%) belonged to lineage 4. The distributions of the sub-lineages varied across the geographic regions of Zhejiang Province. L2.2 is the most ancient sub-lineage in Zhejiang, first appearing approximately 6897 years ago (95% highest posterior density interval (HDI): 6513–7298). L4.4 is the most modern sub-lineage, first appearing approximately 2217 years ago (95% HDI: 1864–2581). The dN/dS ratios showed that the epitope and non-epitope regions of lineage 2 strains were significantly (P < 0.001) more conserved than those of lineage 4. CONCLUSIONS: An increase in the frequency of lineage 4 may reflect its successful transmission over the last 20 years. The recent common ancestors of the sub-lineages and their transmission routes are relevant to the entry of humans into China and Zhejiang Province. Diversity in T cell epitopes may prevent Mycobacterium tuberculosis from being recognized by the immune system. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13578-021-00673-7. BioMed Central 2021-08-21 /pmc/articles/PMC8379736/ /pubmed/34419157 http://dx.doi.org/10.1186/s13578-021-00673-7 Text en © The Author(s) 2021, corrected publication 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Wu, Beibei
Zhu, Wenlong
Wang, Yue
Wang, Qi
Zhou, Lin
Liu, Zhengwei
Bi, Lijun
Barun, Mathema
Kreiswirth, Barry N.
Chen, Liang
Chen, Songhua
Wang, Xiaomeng
Wang, Weibing
Genetic composition and evolution of the prevalent Mycobacterium tuberculosis lineages 2 and 4 in the Chinese and Zhejiang Province populations
title Genetic composition and evolution of the prevalent Mycobacterium tuberculosis lineages 2 and 4 in the Chinese and Zhejiang Province populations
title_full Genetic composition and evolution of the prevalent Mycobacterium tuberculosis lineages 2 and 4 in the Chinese and Zhejiang Province populations
title_fullStr Genetic composition and evolution of the prevalent Mycobacterium tuberculosis lineages 2 and 4 in the Chinese and Zhejiang Province populations
title_full_unstemmed Genetic composition and evolution of the prevalent Mycobacterium tuberculosis lineages 2 and 4 in the Chinese and Zhejiang Province populations
title_short Genetic composition and evolution of the prevalent Mycobacterium tuberculosis lineages 2 and 4 in the Chinese and Zhejiang Province populations
title_sort genetic composition and evolution of the prevalent mycobacterium tuberculosis lineages 2 and 4 in the chinese and zhejiang province populations
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8379736/
https://www.ncbi.nlm.nih.gov/pubmed/34419157
http://dx.doi.org/10.1186/s13578-021-00673-7
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