The impact of anti-tuberculosis treatment on respiratory tract microbiome in pulmonary tuberculosis

Study information

Needs review

study design

case-control

Citation

PMID PubMed identifier for scientific articles.

39428055

DOI Digital object identifier for electronic documents.

10.1016/j.micinf.2024.105432

URI Uniform resource identifier for web resources.

Authors

Hazra D, Chawla K, S M F, Sintchenko V, Magazine R, Martinez E, Pandey A

Journal

Microbes and infection

Year

2025

Keywords:

16S metagenomics, Anti-tuberculosis treatment, Respiratory microbiome, Sputum, Tuberculosis

The growing evidence has underscored the significance of interactions between the host and microbiota in respiratory health, presenting a novel perspective on disease management. Yet, comprehension of the respiratory microbiome shifts before and after anti-tuberculosis treatment is limited. This study compares respiratory microbiome profiles in untreated tuberculosis (UTB) and completed TB treatment (CTB) cases with healthy controls, using 16S rRNA sequencing on sputum samples. Significant reduction in sputum microbial alpha diversity was observed in both TB groups when compared to healthy controls (P < 0.05). Beta diversity analysis showed distinct clustering (P < 0.05). Linear discriminant analysis revealed an abundance of potentially pathogenic bacterial genera like Haemophilus, Pseudomonas, and Mycobacterium in the UTB group, while Streptococcus, Rothia, and Neisseria dominated in CTB samples. Healthy sputum microbiomes were enriched with Prevotella, Fusobacterium, Porphyromonadaceae_unclassified,andPeptostreptococcus. Moreover, predicted bacterial functional pathways showed significant differences among the three groups, mainly related to nutrient metabolism. These findings indicated significant microbial dysbiosis in sputum samples recovered from patients with pulmonary TB with an elevated presence of potentially pathogenic bacteria, depletion of beneficial genera, and downregulation of several essential metabolic pathways. Further exploration of respiratory microbiome-based diagnostic biomarkers and their role in targeted treatment strategies in tuberculosis is warranted.

Experiment 1

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Needs review

Curated date: 2025/06/21

Curator: Nuerteye

Revision editor(s): Nuerteye

Subjects

Location of subjects: India

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: Sputum Expectoration,Sputum,sputum

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: Healthy controls

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

Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group: Newly diagnosed, Xpert MTB/RIF Ultra+ and sputum AFB+; no prior ATT

Group 0 sample size Number of subjects in the control (unexposed) group: 16

Group 1 sample size Number of subjects in the case (exposed) group: 50

Antibiotics exclusion Number of days without antibiotics usage (if applicable) and other antibiotics-related criteria used to exclude participants (if any): No antibiotics or corticosteroids in 4 weeks before sampling.

Lab analysis

Sequencing type: 16S

16S variable region One or more hypervariable region(s) of the bacterial 16S gene: V3-V4

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: Kruskall-Wallis; LEfSe

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

MHT correction Have statistical tests be corrected for multiple hypothesis testing (MHT)?: Yes

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

Matched on Factors on which subjects have been matched on in a case-control study: age, sex, Matched on: "BMI" is not in the list (abnormal glucose tolerance, acetaldehyde, acute graft vs. host disease, acute lymphoblastic leukemia, acute myeloid leukemia, adenoma, age, AIDS, alcohol consumption measurement, alcohol drinking, ...) of allowed values.BMI

Confounders controlled for Confounding factors that have been accounted for by stratification or model adjustment: Confounders controlled for: "HIV status" is not in the list (abnormal glucose tolerance, acetaldehyde, acute graft vs. host disease, acute lymphoblastic leukemia, acute myeloid leukemia, adenoma, age, AIDS, alcohol consumption measurement, alcohol drinking, ...) of allowed values.HIV status, Confounders controlled for: "chronic disease" is not in the list (abnormal glucose tolerance, acetaldehyde, acute graft vs. host disease, acute lymphoblastic leukemia, acute myeloid leukemia, adenoma, age, AIDS, alcohol consumption measurement, alcohol drinking, ...) of allowed values.chronic disease, Confounders controlled for: "pregnancy" is not in the list (abnormal glucose tolerance, acetaldehyde, acute graft vs. host disease, acute lymphoblastic leukemia, acute myeloid leukemia, adenoma, age, AIDS, alcohol consumption measurement, alcohol drinking, ...) of allowed values.pregnancy, Confounders controlled for: "prior TB history" is not in the list (abnormal glucose tolerance, acetaldehyde, acute graft vs. host disease, acute lymphoblastic leukemia, acute myeloid leukemia, adenoma, age, AIDS, alcohol consumption measurement, alcohol drinking, ...) of allowed values.prior TB history