AUTHOR=Ding Li , Liu Yanmin , Wu Xiaorong , Wu Minhao , Luo Xiaoqing , Ouyang Hui , Xia Jinyu , Liu Xi , Ding Tao TITLE=Pathogen Metagenomics Reveals Distinct Lung Microbiota Signatures Between Bacteriologically Confirmed and Negative Tuberculosis Patients JOURNAL=Frontiers in Cellular and Infection Microbiology VOLUME=11 YEAR=2021 URL=https://www.frontiersin.org/journals/cellular-and-infection-microbiology/articles/10.3389/fcimb.2021.708827 DOI=10.3389/fcimb.2021.708827 ISSN=2235-2988 ABSTRACT=

Understanding the dynamics of lung microbiota in tuberculosis patients, especially those who cannot be confirmed bacteriologically in clinical practice, is imperative for accurate diagnosis and effective treatment. This study aims to characterize the distinct lung microbial features between bacteriologically confirmed and negative tuberculosis patients to understand the influence of microbiota on tuberculosis patients. We collected specimens of bronchoalveolar lavage fluid from 123 tuberculosis patients. Samples were subjected to metagenomic next-generation sequencing to reveal the lung microbial signatures. By combining conventional bacterial detection and metagenomic sequencing, 101/123 (82%) tuberculosis patients were bacteriologically confirmed. In addition to Mycobacterium tuberculosis, Staphylococcus aureus, Kluyveromyces lactis, and Pyricularia pennisetigena were also enriched in the bacteriological confirmation group. In contrast, Haemophilus parainfluenzae was enriched in the bacteriologically negative group. Besides, microbial interaction exhibits a different state between bacteriologically confirmed and negative tuberculosis patients. Mycobacterium tuberculosis was confirmed correlated with clinical characteristics such as albumin and chest cavities. Our study comprehensively demonstrates the correlation between unique features of lung microbial dynamics and the clinical characteristics of tuberculosis patients, suggesting the importance of studying the pulmonary microbiome in tuberculosis disease and providing new insights for future precision diagnosis and treatment.