ArticleScientific reports2025
Clinical metagenomics analysis of bacterial and fungal microbiota from sputum of patients suspected with tuberculosis infection based on nanopore sequencing.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Gut-lung axis and microbiome alterations in mycobacterial infections: from pathogenesis to therapeutic potential.Gut microbes · 2026Review
- The Pathogenesis, Clinical Features, and Treatment ofMicroorganisms · 2026Review
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
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.
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