Transforming tuberculosis diagnosis with clinical metagenomics: progress and roadblocks
Tuberculosis (TB) remains a leading global infectious killer, yet traditional diagnostic methods are inadequate. Acid-fast staining suffers from low sensitivity, and mycobacterial culture requires prolonged incubation because of the slow growth of <i>Mycobacterium tuberculosis</i>. PCR-based molecular assays allow rapid detection, but their capacity for resistance profiling is limited to a narrow set of mutations. Metagenomic next-generation sequencing (mNGS) has emerged as a promising culture-independent tool for TB detection, enabling broad-spectrum pathogen identification and offering added value in complex scenarios including extra-pulmonary disease, mixed infections, and infections in immunocompromised or pediatric populations. Clinical studies indicate that mNGS achieves moderate to high sensitivity and excellent specificity in the diagnosis of tuberculosis. However, its diagnostic performance is often constrained by low mycobacterial read counts, interference from abundant host nucleic acids, and the inability to distinguish active from latent infection. In addition, the accuracy of drug resistance prediction using mNGS remains limited, and the World Health Organization currently endorses targeted NGS as the preferred sequencing-based approach for resistance profiling. Despite these challenges, mNGS has facilitated novel diagnostic strategies that combine pathogen detection with host-response data, thereby broadening its potential clinical utility. Nevertheless, practical barriers such as high cost, complex laboratory workflows, and difficulties in data interpretation continue to restrict widespread adoption in routine practice. Future efforts should prioritize technical optimization, standardized protocols, and integration with conventional diagnostics to establish cost-effective and clinically meaningful roles for mNGS in TB diagnosis and management.
Authors
- Jieyuan Zheng (ORCID: https://orcid.org/0000-0003-3000-3344)
- Hui Tang (ORCID: https://orcid.org/0000-0002-4232-4607)
- Yuqing Chen (ORCID: https://orcid.org/0000-0002-5592-9197)
- Dongsheng Han (ORCID: https://orcid.org/0000-0002-1892-8603)
- Qing Yang (ORCID: https://orcid.org/0000-0003-3744-9402)
Institutions
- Affiliated Hangzhou First People's Hospital, Westlake University, School of Medicine (CN)
- First Affiliated Hospital Zhejiang University (CN)
- Zhejiang University of Technology (CN)
- Zhejiang University (CN)
Publication Details
- Journal
- Journal of Clinical Microbiology
- Published
- 2025-09-19
- DOI
- https://doi.org/10.1128/jcm.00537-25
- Citations
- 1
- Primary Topic
- Tuberculosis Research and Epidemiology
- Type
- article
- Field-Weighted Citation Impact
- 1.40