Comprehensive Analysis of Pathogen Diversity and Diagnostic Biomarkers in Patients with Suspected Pulmonary Tuberculosis Through Metagenomic Next-Generation Sequencing

Study information

Needs review

study design

case-control

Citation

PMID PubMed identifier for scientific articles.

40337776

DOI Digital object identifier for electronic documents.

10.2147/IDR.S504587

URI Uniform resource identifier for web resources.

Authors

Li Y, Li C, Fang Y, Zhang L, Ying X, Ren R, Zang Y, Ying D, Zhu S, Liu J, Cao X

Journal

Infection and drug resistance

Year

2025

Keywords:

biomarkers, bronchoalveolar lavage fluid, lung microbiome, metagenomic next-generation sequencing, tuberculosis

BACKGROUND: This study aimed to investigate the co-infecting pathogens and lung microbiomes in patients with clinically confirmed pulmonary tuberculosis (TB) and explore potential diagnostic biomarkers to differentiate between varied infection patterns. METHODS: We conducted a retrospective cohort study by analyzing 198 bronchoalveolar lavage fluid (BALF) samples collected from patients with suspected pulmonary TB. All BALF samples were sequenced using metagenomic next-generation sequencing (mNGS). RESULTS: A total of 63 pathogens were detected in all samples. The TB group exhibited a higher diversity of pathogens (n=51) than the Non-TB group (n=37). The analysis revealed that TB patients had significantly higher pathogen counts (P=0.014), and specific microorganisms, such as Mycobacterium tuberculosis complex (MTBC), MTB, Streptococcus infantis, and Campylobacter curvus, were significantly enriched. Furthermore, the abundance of MTBC was negatively correlated with hemoglobin levels (R=-0.17, P=0.015) and positive correlated with C-reactive protein (CRP) levels (R=0.16, P=0.029). The random forest model combined eight differential microbes and five clinical parameters, yielding an area under the curve (AUC) of 0.86 for differentiating TB from Non-TB cohorts, whereas subgroup differentiation yielded an AUC of 0.571, demonstrating the potential for targeted diagnostics in pulmonary infections. CONCLUSION: Our findings highlight the complexity of co-infection patterns in pulmonary TB and emphasize the potential of integrating microbial and clinical markers to improve diagnostic accuracy. This study provides valuable insights into the role of the lung microbiome in TB and informs future research on targeted therapies for this disease.

Experiment 1

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Curated date: 2025/07/01

Curator: Nuerteye

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Subjects

Location of subjects: China

Host species Species from which microbiome was sampled. Contact us to have more species added.: Homo sapiens

Body site Anatomical site where microbial samples were extracted from according to the Uber Anatomy Ontology: Lung Pulmo,Lung,lung

Condition The experimental condition / phenotype studied according to the Experimental Factor Ontology: Pulmonary tuberculosis lung TB,lung tuberculosis,pulmonary TB,pulmonary tuberculosis,Tuberculosis, Pulmonary,Pulmonary tuberculosis

Group 0 name Corresponds to the control (unexposed) group for case-control studies: Non‑Tuberculosis

Group 1 name Corresponds to the case (exposed) group for case-control studies: Tuberculosis (TB)

Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group: Clinical (microbiological) confirmation of pulmonary tuberculosis.

Group 0 sample size Number of subjects in the control (unexposed) group: 111

Group 1 sample size Number of subjects in the case (exposed) group: 87

Lab analysis

Sequencing type: PCR

16S variable region One or more hypervariable region(s) of the bacterial 16S gene: Not specified

Sequencing platform Manufacturer and experimental platform used for quantifying microbial abundance: Illumina

Statistical Analysis

Data transformation Data transformation applied to microbial abundance measurements prior to differential abundance testing (if any).: relative abundances

Statistical test: LEfSe

Significance threshold p-value or FDR threshold used for differential abundance testing (if any): 0.05

LDA Score above Threshold for the linear discriminant analysis (LDA) score for studies using the popular LEfSe tool: 2

Signature 1

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Source: Figure 3A

Description: Microbial species with differential abundance between TB and Non-TB groups identified through LEfSe analysis with the thresholds of log10 LDA score≥2 and P value<0.05.

Abundance in Group 1: increased abundance in Tuberculosis (TB)

NCBI	Quality Control	Links
Streptococcus infantis
Campylobacter curvus
Microbacterium tuberculosisMicrobacterium tuberculosis
Microbacterium tuberculosis complexMicrobacterium tuberculosis complex

Revision editor(s): Nuerteye

Signature 2

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Curated date: 2025/07/01

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Source: Figure 3A

Description: Microbial species with differential abundance between TB and Non-TB groups identified through LEfSe analysis with the thresholds of log10 LDA score≥2 and P value<0.05.

Abundance in Group 1: decreased abundance in Tuberculosis (TB)

NCBI	Quality Control	Links
Corynebacterium striatum
Staphylococcus epidermidis
Ralstonia mannitolilytica
Mycoplasma hominisMycoplasma hominis

Revision editor(s): Nuerteye