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Metagenomic analysis of the lung microbiome in pulmonary tuberculosis - a pilot study

The lung microbiome plays an important role in the pathophysiological processes associated with pulmonary tuberculosis (PTB). However, only a few studies using 16S rDNA amplicon sequencing have been reported, and the interactions between Mycobacterium tuberculosis (MTB) and the lung microbiome remai...

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Autores principales: Hu, Yongfeng, Cheng, Min, Liu, Bo, Dong, Jie, Sun, Lilian, Yang, Jian, Yang, Fan, Chen, Xinchun, Jin, Qi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7473061/
https://www.ncbi.nlm.nih.gov/pubmed/32552447
http://dx.doi.org/10.1080/22221751.2020.1783188
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author Hu, Yongfeng
Cheng, Min
Liu, Bo
Dong, Jie
Sun, Lilian
Yang, Jian
Yang, Fan
Chen, Xinchun
Jin, Qi
author_facet Hu, Yongfeng
Cheng, Min
Liu, Bo
Dong, Jie
Sun, Lilian
Yang, Jian
Yang, Fan
Chen, Xinchun
Jin, Qi
author_sort Hu, Yongfeng
collection PubMed
description The lung microbiome plays an important role in the pathophysiological processes associated with pulmonary tuberculosis (PTB). However, only a few studies using 16S rDNA amplicon sequencing have been reported, and the interactions between Mycobacterium tuberculosis (MTB) and the lung microbiome remain poorly understood. Patients with respiratory symptoms and imaging abnormalities compatible with tuberculosis (TB) were enrolled. We analyzed the lung microbiome in bronchoalveolar lavage (BAL) samples from 30 MTB-positive (MTB+) subjects and 30 MTB negative (MTB-) subjects by shotgun metagenomic sequencing. Alpha diversity tended to be lower in the MTB+ group than in the MTB- group. There was a significant difference in beta diversity between the MTB+ and MTB- subjects. MTB+ lung samples were dominated by MTB, while MTB- samples were enriched with Streptococcus, Prevotella, Nesseria, Selenomonas and Bifidobacterium, which more closely resemble the microbial composition of a healthy lung. Network analysis suggested that MTB could greatly impact the microbial community structure. MTB+ and MTB- communities showed distinct functional signatures. Fungal communities were also found to be associated with the presence or absence of MTB. Furthermore, it was confirmed that 16S rDNA amplicon sequencing underrepresents Mycobacterium. This pilot study is the first to explore the interplay between MTB and the host microbiome by using metagenomic sequencing. MTB dominates the lung microbiome of MTB+ subjects, while MTB- subjects have a Streptococcus-enriched microbiome. The 16S approach underrepresents Mycobacterium and is not the best way to study the TB-associated microbiome.
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spelling pubmed-74730612020-09-15 Metagenomic analysis of the lung microbiome in pulmonary tuberculosis - a pilot study Hu, Yongfeng Cheng, Min Liu, Bo Dong, Jie Sun, Lilian Yang, Jian Yang, Fan Chen, Xinchun Jin, Qi Emerg Microbes Infect Articles The lung microbiome plays an important role in the pathophysiological processes associated with pulmonary tuberculosis (PTB). However, only a few studies using 16S rDNA amplicon sequencing have been reported, and the interactions between Mycobacterium tuberculosis (MTB) and the lung microbiome remain poorly understood. Patients with respiratory symptoms and imaging abnormalities compatible with tuberculosis (TB) were enrolled. We analyzed the lung microbiome in bronchoalveolar lavage (BAL) samples from 30 MTB-positive (MTB+) subjects and 30 MTB negative (MTB-) subjects by shotgun metagenomic sequencing. Alpha diversity tended to be lower in the MTB+ group than in the MTB- group. There was a significant difference in beta diversity between the MTB+ and MTB- subjects. MTB+ lung samples were dominated by MTB, while MTB- samples were enriched with Streptococcus, Prevotella, Nesseria, Selenomonas and Bifidobacterium, which more closely resemble the microbial composition of a healthy lung. Network analysis suggested that MTB could greatly impact the microbial community structure. MTB+ and MTB- communities showed distinct functional signatures. Fungal communities were also found to be associated with the presence or absence of MTB. Furthermore, it was confirmed that 16S rDNA amplicon sequencing underrepresents Mycobacterium. This pilot study is the first to explore the interplay between MTB and the host microbiome by using metagenomic sequencing. MTB dominates the lung microbiome of MTB+ subjects, while MTB- subjects have a Streptococcus-enriched microbiome. The 16S approach underrepresents Mycobacterium and is not the best way to study the TB-associated microbiome. Taylor & Francis 2020-07-02 /pmc/articles/PMC7473061/ /pubmed/32552447 http://dx.doi.org/10.1080/22221751.2020.1783188 Text en © 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group, on behalf of Shanghai Shangyixun Cultural Communication Co., Ltd https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Articles
Hu, Yongfeng
Cheng, Min
Liu, Bo
Dong, Jie
Sun, Lilian
Yang, Jian
Yang, Fan
Chen, Xinchun
Jin, Qi
Metagenomic analysis of the lung microbiome in pulmonary tuberculosis - a pilot study
title Metagenomic analysis of the lung microbiome in pulmonary tuberculosis - a pilot study
title_full Metagenomic analysis of the lung microbiome in pulmonary tuberculosis - a pilot study
title_fullStr Metagenomic analysis of the lung microbiome in pulmonary tuberculosis - a pilot study
title_full_unstemmed Metagenomic analysis of the lung microbiome in pulmonary tuberculosis - a pilot study
title_short Metagenomic analysis of the lung microbiome in pulmonary tuberculosis - a pilot study
title_sort metagenomic analysis of the lung microbiome in pulmonary tuberculosis - a pilot study
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7473061/
https://www.ncbi.nlm.nih.gov/pubmed/32552447
http://dx.doi.org/10.1080/22221751.2020.1783188
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