Metagenomic analysis of the lung microbiome in pulmonary tuberculosis - a pilot study.
Yongfeng HuMin ChengBo LiuJie DongLilian SunJian YangFan YangXinchun ChenQi JinPublished in: Emerging microbes & infections (2021)
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.
Keyphrases
- mycobacterium tuberculosis
- pulmonary tuberculosis
- single cell
- high resolution
- emergency department
- hepatitis c virus
- pseudomonas aeruginosa
- physical activity
- network analysis
- dna methylation
- staphylococcus aureus
- candida albicans
- antiretroviral therapy
- human immunodeficiency virus
- antibiotic resistance genes
- photodynamic therapy
- fluorescence imaging