Clinical metagenomics analysis of bacterial and fungal microbiota from sputum of patients suspected with tuberculosis infection based on nanopore sequencing

Study information

Needs review

study design

cross-sectional observational, not case-control

Citation

PMID PubMed identifier for scientific articles.

40404683

DOI Digital object identifier for electronic documents.

10.1038/s41598-025-01905-3

URI Uniform resource identifier for web resources.

Authors

Terbtothakun P, Visedthorn S, Klomkliew P, Chanchaem P, Sawaswong V, Sivapornnukul P, Sunantawanit S, Khamwut A, Rotcheewaphan S, Kaewsapsak P, Payungporn S

Journal

Scientific reports

Year

2025

Keywords:

Mycobacterium tuberculosis, 16S rDNA, Internal transcribed spacer (ITS), Metagenomics, Oxford nanopore technologies (ONT)

Tuberculosis (TB) remains a significant global health challenge, demanding rapid and comprehensive diagnostics for effective treatment. Secondary infections further complicate TB infection, worsening outcomes. Conventional diagnostics are hindered by prolonged turnaround times, high costs, and inability to detect co-infections. This study utilizes full-length 16S rDNA and internal transcribed spacer (ITS) amplicon sequencing based on Oxford Nanopore Technologies (ONT) to analyze clinical metagenomics of sputum microbiota from patients suspected with TB Infection. Our findings highlight the potential of ONT for profiling microbial communities associated with TB infection. The MTB group exhibited a significant abundance of Mycobacterium tuberculosis (M. tuberculosis) and Stenotrophomonas maltophilia. In contrast, Prevotella melaninogenica, Veillonella parvula, Corynebacterium striatum and Pseudomonas aeruginosa were more abundant in the negative samples. Fungal analysis revealed Candida orthopsilosis was enriched in MTB samples, while Aureobasidium leucospermi and Wallemia muriae predominated in negative samples. Correlation network analysis revealed M. tuberculosis exhibits positive and negative correlations with other microbial species, suggesting cooperative and competitive interactions that may influence microbial community dynamics and disease progression in TB patients. This study demonstrates the promise of ONT-based clinical metagenomics for rapid, comprehensive detection of bacterial and fungal co-infections, addressing limitations of conventional diagnostics and improving outcomes.

Experiment 1

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Curated date: 2025/07/10

Curator: Nuerteye

Revision editor(s): Nuerteye

Subjects

Location of subjects: Thailand

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: Mycobacterium tuberculosis-negative (non-TB)

Group 1 name Corresponds to the case (exposed) group for case-control studies: Mycobacterium tuberculosis-positive

Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group: Mycobacterium tuberculosis confirmed by standard tests (culture, Xpert, etc.)

Group 0 sample size Number of subjects in the control (unexposed) group: 41

Group 1 sample size Number of subjects in the case (exposed) group: 56

Lab analysis

Sequencing type: 16S

16S variable region One or more hypervariable region(s) of the bacterial 16S gene: V1-V9

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

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: 4

Alpha Diversity

Shannon Estimator of species richness and species evenness: more weight on species richness: unchanged

Chao1 Abundance-based estimator of species richness: unchanged

Simpson Estimator of species richness and species evenness: more weight on species evenness: unchanged

Signature 1

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Curated date: 2025/07/10

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Source: Figure 2B; 4B; S2

Description: Differential abundance analysis was performed using Linear Discriminant Analysis Effect Size (LEfSe) on MTB and negative sputum samples. 2(B) Bar plots display differentially abundant bacterial taxa across various taxonomic ranks. 4(B) Bar plots display differentially abundant fungal taxa across various taxonomic ranks.

Abundance in Group 1: increased abundance in Mycobacterium tuberculosis-positive

NCBI	Quality Control	Links
Stenotrophomonas maltophilia
Mycobacterium tuberculosis
Candida orthopsilosis

Revision editor(s): Nuerteye

Signature 2

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Curated date: 2025/07/10

Curator: Nuerteye

Revision editor(s): Nuerteye

Source: Figure 2B; 4B; S2

Description: Differential abundance analysis was performed using Linear Discriminant Analysis Effect Size (LEfSe) on MTB and negative sputum samples. 2(B) Bar plots display differentially abundant bacterial taxa across various taxonomic ranks. 4(B) Bar plots display differentially abundant fungal taxa across various taxonomic ranks.

Abundance in Group 1: decreased abundance in Mycobacterium tuberculosis-positive

NCBI	Quality Control	Links
Prevotella melaninogenica
Veillonella parvula
Corynebacterium striatum
Pseudomonas aeruginosa
Aureobasidium leucospermiAureobasidium leucospermi
Wallemia muriaeWallemia muriae

Revision editor(s): Nuerteye