Rapid Identification of Drug-Resistant Tuberculosis Using Nanopore Targeted Next-Generation Sequencing from Sputum and Culture Isolates: Accuracy and Limitations

Purpose: Drug-resistant tuberculosis (DR-TB) complicates treatment and requires diagnostic approaches capable of comprehensive resistance profiling of Mycobacterium tuberculosis (MTB). This study evaluated the diagnostic performance of the Oxford Nanopore Technologies (ONT) custom TB-DR sequencing assay, a targeted Next-Generation Sequencing (tNGS) using Nanopore sequencing technology, in sputum and culture isolates. The assay targets resistance-associated variants across 24 genes covering 13 anti-tuberculosis drugs and integrates the hsp65 gene and direct repeat (DR) region for species identification and lineage determination. Methods: DNA was extracted from 88 clinical samples, comprising 30 uncultured sputum specimens (10 MTB-positive, 10 non-tuberculous mycobacteria, and 10 mycobacteria-negative controls) to evaluate species identification, and 58 MTB culture isolates. The culture isolates represented diverse phenotypic resistance profiles, including mono-drug resistant, multidrug-resistant, and pre-extensively drug-resistant strains. tNGS profiles were compared with pDST to evaluate diagnostic performance for drug-resistance profiling, including sensitivity, specificity, and test agreement. Results: Profiling success in sputum samples was dependent on mycobacterial load. Among MTB-positive sputum specimens, 6 (60%) produced results, including 2 complete resistance profiles and 4 partial profiles limited to species identification; the remaining specimens failed due to low mycobacterial load (smear-negative and high Ct values). All NTM samples were correctly identified, and all mycobacteria-negative controls tested negative. In contrast, 57 of 58 (98.3%) culture isolates yielded complete resistance profiles. Compared with pDST, sensitivity and specificity exceeded 90% for most drugs (except streptomycin, 85.7% sensitivity), with very strong agreement (κ > 0.8). Conclusion: The ONT custom TB-DR sequencing assay provides comprehensive resistance profiling with high concordance to pDST in samples yielding complete sequencing profiles and enables species and lineage identification with a shorter analytical turnaround time compared with phenotypic testing. Performance in sputum specimens was influenced by mycobacterial load. Further studies involving larger and more diverse cohorts are needed to validate clinical applicability. Keywords: Mycobacterium tuberculosis , Nanopore sequencing, tNGS, drug-resistant tuberculosis, rapid diagnostics

Authors

Institutions

Publication Details

Journal
Infection and Drug Resistance
Published
2026-02-01
DOI
https://doi.org/10.2147/idr.s571825
Primary Topic
Tuberculosis Research and Epidemiology
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Rapid Identification of Drug-Resistant Tuberculosis Using Nanopore Targeted Next-Generation Sequencing from Sputum and Culture Isolates: Accuracy and Limitations

Thanadon Dokrungkoon, Kamol Suwannakarn, Popchai Ngamskulrungroj, Tawatchai Chumponsuk et al.
Infection and Drug Resistance
Tuberculosis Research and Epidemiology
article

Rapid Identification of Drug-Resistant Tuberculosis Using Nanopore Targeted Next-Generation Sequencing from Sputum and Culture Isolates: Accuracy and Limitations

Thanadon Dokrungkoon, Kamol Suwannakarn, Popchai Ngamskulrungroj, Tawatchai Chumponsuk, Orapan Sripichai
article en

Abstract

Purpose: Drug-resistant tuberculosis (DR-TB) complicates treatment and requires diagnostic approaches capable of comprehensive resistance profiling of Mycobacterium tuberculosis (MTB). This study evaluated the diagnostic performance of the Oxford Nanopore Technologies (ONT) custom TB-DR sequencing assay, a targeted Next-Generation Sequencing (tNGS) using Nanopore sequencing technology, in sputum and culture isolates. The assay targets resistance-associated variants across 24 genes covering 13 anti-tuberculosis drugs and integrates the hsp65 gene and direct repeat (DR) region for species identification and lineage determination. Methods: DNA was extracted from 88 clinical samples, comprising 30 uncultured sputum specimens (10 MTB-positive, 10 non-tuberculous mycobacteria, and 10 mycobacteria-negative controls) to evaluate species identification, and 58 MTB culture isolates. The culture isolates represented diverse phenotypic resistance profiles, including mono-drug resistant, multidrug-resistant, and pre-extensively drug-resistant strains. tNGS profiles were compared with pDST to evaluate diagnostic performance for drug-resistance profiling, including sensitivity, specificity, and test agreement. Results: Profiling success in sputum samples was dependent on mycobacterial load. Among MTB-positive sputum specimens, 6 (60%) produced results, including 2 complete resistance profiles and 4 partial profiles limited to species identification; the remaining specimens failed due to low mycobacterial load (smear-negative and high Ct values). All NTM samples were correctly identified, and all mycobacteria-negative controls tested negative. In contrast, 57 of 58 (98.3%) culture isolates yielded complete resistance profiles. Compared with pDST, sensitivity and specificity exceeded 90% for most drugs (except streptomycin, 85.7% sensitivity), with very strong agreement (κ > 0.8). Conclusion: The ONT custom TB-DR sequencing assay provides comprehensive resistance profiling with high concordance to pDST in samples yielding complete sequencing profiles and enables species and lineage identification with a shorter analytical turnaround time compared with phenotypic testing. Performance in sputum specimens was influenced by mycobacterial load. Further studies involving larger and more diverse cohorts are needed to validate clinical applicability. Keywords: Mycobacterium tuberculosis , Nanopore sequencing, tNGS, drug-resistant tuberculosis, rapid diagnostics

Infection and Drug ResistanceVol. Volume 19
Ministry of Public Health (TH), Siriraj Hospital (TH), Mahidol University (TH), Department of Medical Sciences (TH)
Department of Science and Technology, Ministry of Science and Technology, India, Mahidol University, Faculty of Medicine Siriraj Hospital, Mahidol University
Openalex Percentile: Top 67%
Tuberculosis Research and Epidemiology
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.