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Amplicon-based nanopore sequencing for Mycobacterium spp. identification in clinical isolates and sputum

Journal
International journal of medical microbiology : IJMM (Q1)
Published
10 September 2026
Study design
Unclassified
Evidence level
Level 5, Expert Opinion (CEBM 5)
Authors
Samitanan Sunantawanit, Prangwalai Chanchaem, Pavit Klomkliew, Suthida Visedthorn, Peeraphan Compiro, Pawarisa Terbtothakun, et al.
PMID
42735554
DOI
10.1016/j.ijmm.2026.151733

Why clinicians should know about it

  • Picked for Microbiology (medical) (paper of the day, 17 September 2026): Myco‑ANS nanopore assay for Mycobacterium spp. identification

Abstract

OBJECTIVES: This study developed a mycobacterial amplicon-based nanopore sequencing (Myco-ANS) assay for differentiating eight Mycobacterium spp. and evaluated its diagnostic accuracy in clinical isolates and sputum samples. METHODS: PCR primers targeting the rpoB gene were optimized for sequencing with Oxford Nanopore Technology. Eight American Type Culture Collection (ATCC) reference strains were used for assay development. Clinical isolates and sputum samples were obtained from King Chulalongkorn Memorial Hospital. Results were compared with those from the line probe assay (LPA). RESULTS: A total of 125 clinical isolates and 46 sputum samples were analyzed. Myco-ANS correctly identified eight species: M. tuberculosis, M. bovis BCG, M. abscessus, M. avium, M. fortuitum group, M. kansasii, M. gordonae, and M. intracellulare. For isolates, sensitivity ranged from 89.5 to 100.0%, specificity from 99.2 to 100.0%, and diagnostic accuracy from 98.4 to 100.0%. In sputum, species-level identification showed substantial agreement with LPA (kappa = 0.70). CONCLUSIONS: Myco-ANS provides rapid, accurate identification of clinically relevant mycobacteria from both isolates and sputum. With results available within three days, this assay shortens turnaround time compared to conventional methods, supporting faster treatment decisions and reducing transmission risk.

Abstract as published, via PubMed.

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For healthcare professionals. The summary is generated by AI from the published abstract, and the evidence level is assigned automatically from the study design on the Oxford CEBM hierarchy. Neither is medical advice. Read the full paper before changing practice.