mlstverse-web: advancing real-time identification of mycobacteria from sputum using targeted sequencing NALC-Seq

The identification of mycobacteria, including Mycobacterium tuberculosis (MTB) and non-tuberculous mycobacteria (NTM), remains a critical challenge in clinical and public health settings due to their pathogenicity and increasing drug resistance. Traditional diagnostic methods, such as PCR and mass spectrometry, are limited by species detectability and prolonged culture requirements. To address these limitations, this study introduces a novel approach, named NALC-Seq, which integrates next-generation sequencing (NGS) and target capture sequencing for the direct and comprehensive identification of mycobacteria from sputum samples. A total of 54 patients were prospectively or retrospectively enrolled between April 6, 2021, and November 8, 2022, and sputum samples were subjected to next generation sequencing. The NALC-Seq methodology utilizes custom-designed RNA probes for targeted enrichment of mycobacterial DNA, coupled with species identification via the mlstverse-web system. This system integrates web, upload, head, and cloud nodes to streamline data management and analysis. Our evaluation demonstrated that NALC-Seq achieved high sensitivity (98.1%) and accuracy (83.3%) in detecting diverse mycobacterial species, including rare and drug-resistant subspecies. There were discrepancies with MGIT-Seq in nine samples. These samples exhibited low smear positivity rates, and the detection of environmental mycobacteria suggested potential contamination. Furthermore, real-time identification using the MinION device significantly reduced the turnaround time from 686 to 19 h.These findings highlight the potential of NALC-Seq and mlstverse-web as an integrated diagnostic solution for overcoming the limitations of current methods. The proposed approach offers a rapid, accurate, and comprehensive strategy for mycobacterial identification, with significant implications for clinical diagnostics and public health surveillance.