Evidence map›Paper›PMID 42387366›Full record

ArticleBMC microbiology2026

Differential analysis of the lower respiratory tract microbiota between patients with non-tuberculous mycobacterial pulmonary disease and pulmonary tuberculosis.

Jie Mi, Ying Dong, Zongyi Xu, Yan Liang, Xueqiong Wu, Jianqin Liang

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Article in BMC microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

6 authors.

Jie Mi *Senior Department of Tuberculosis, the Chinese PLA General Hospital, 17# Heishanhu Road, Haidian District, Beijing, 100091, China.
Ying Dong *Chinese PLA Medical School, Beijing, 100039, China.
Zongyi XuEmergency Medicine Department, the 8th Medical Center of PLA General Hospital, Beijing, 100091, China.
Yan LiangSenior Department of Tuberculosis, the Chinese PLA General Hospital, 17# Heishanhu Road, Haidian District, Beijing, 100091, China. amy5919@sina.com.
Xueqiong WuSenior Department of Tuberculosis, the Chinese PLA General Hospital, 17# Heishanhu Road, Haidian District, Beijing, 100091, China. xueqiongwu@139.com.
Jianqin LiangSenior Department of Tuberculosis, the Chinese PLA General Hospital, 17# Heishanhu Road, Haidian District, Beijing, 100091, China. ljqbj309@163.com.

Funding

Capitals Funds for Health Improvement and Research 2024-2-5094
6 · The paper itself

Abstract

backgroundNon-tuberculous mycobacterial pulmonary disease (NTM-PD) poses significant diagnostic challenges due to its clinical similarity to pulmonary tuberculosis (PTB). This study aimed to compare the clinical characteristics, immune status and lower respiratory tract microbiome profiles of NTM-PD and PTB patients.

methodsA total of 113 NTM-PD patients and 105 PTB patients were enrolled. The clinical features, laboratory parameters, and comorbidity profiles were analyzed. Bronchoalveolar lavage fluid (BALF) samples were subjected to bacterial culture and targeted next-generation sequencing (tNGS) for microbiome characterization. Microbiome distributions were then compared across disease groups, host characteristics, immune cell subsets, and NTM species.

resultsCompared with PTB patients, NTM-PD patients were older and exhibited lower rates of smoking, alcohol use, interferon-gamma release assay (IGRA) positivity, red blood cell (RBC) count, hemoglobin (Hb) and albumin levels, but a higher erythrocyte sedimentation rate (ESR). Hemoptysis, bronchiectasis, and chronic obstructive pulmonary disease (COPD) were more common among NTM-PD patients, while lymphadenopathy and diabetes were more frequent among PTB patients. BALF microbiome analysis revealed distinct profiles: Pseudomonas aeruginosa and Aspergillus spp. were more frequently detected in NTM-PD patients, while Neisseria spp. and Streptococcus viridans predominated in PTB patients. Reduced CD4⁺ T cell counts were associated with a higher detection rate of Pseudomonas aeruginosa and Candida spp. in NTM-PD patients. The most prevalent NTM species were the M. avium complex (MAC) (62.37%) and the M. abscessus complex (MABC) (27.96%).

conclusionsThe lower respiratory tract microbiome in NTM-PD differs from that in PTB and is characterized by a high prevalence of Aspergillus spp. and Pseudomonas aeruginosa. These differences are likely influenced by underlying structural lung disease, host immune status, and the NTM species themselves. Our findings provide new insights for the precise diagnosis and treatment of NTM-PD.

Indexed as

BacteriaMicrobiotaMycobacterium Infections, NontuberculousRespiratory SystemTuberculosis, PulmonaryAdultAgedBronchoalveolar Lavage FluidFemaleHigh-Throughput Nucleotide SequencingHumansMaleMiddle AgedNontuberculous MycobacteriaBronchoalveolar lavage fluidMicrobiomeNon-tuberculous mycobacterial pulmonary diseasePulmonary tuberculosisTargeted next-generation sequencing

Identifiers

PMID42387366
PMCPMC13591713

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.