Diagnostic performance of nanopore-targeted sequencing for pulmonary infections in a tuberculosis-endemic setting: A prospective observational study
Year: 2026
Type: article
Study design: Observational Study
Abstract: BACKGROUND: Pulmonary infections in tuberculosis (TB)-endemic settings are heterogeneous and commonly polymicrobial. Nanopore-targeted sequencing (NTS) enables detection of mycobacteria, bacteria, and fungi in a single targeted assay. However, performance across pathogen classes in TB-endemic cohorts remains limited. METHODS: We conducted a prospective study at a specialized TB hospital, enrolling adults with suspected pulmonary infections across five predefined diagnostic categories: pulmonary TB, nontuberculous mycobacterial pulmonary disease, bacterial, fungal, and polymicrobial infection. Respiratory specimens (n = 312) from 305 patients were tested in parallel by conventional microbiological testing (CMT) and NTS. Blinded clinical diagnoses served as the reference standard. RESULTS: Among 283 paired cases, NTS identified the adjudicated pathogens in 263 cases, whereas culture identified them in 185 cases. NTS showed a sensitivity/specificity of 83.0%/99.4% for Mycobacterium tuberculosis, 89.8%/98.2% for nontuberculous mycobacteria, 92.9%/91.1% for fungi, and 97.4%/57.8% for bacteria. In 72 polymicrobial infections, NTS detected all adjudicated pathogens in 77.8% vs 62.5% for CMT, a nonsignificant difference (P = 0.06). Overall, NTS provided a 12.2% incremental diagnostic yield. CONCLUSION: NTS offers sensitive, single-assay detection of diverse pulmonary pathogens in TB-endemic settings. By streamlining workflows and improving detection of fastidious or co-infecting organisms, it may complement conventional methods. However, bacterial NTS findings in nonsterile respiratory specimens require clinical correlation.
Language: English
Subfield: Infectious Diseases
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,900
Awards: G1949779815, G2009726791, G4672982343
OpenAlex ID: W7125485079
