On the Application of Metagenomic Next-Generation Sequencing and Real-time PCR with Melting Curve Analysis in the Auxiliary Diagnosis of Mycobacterial Pulmonary Disease

Abstract Objective Rapid and accurate identification of Mycobacteria is of critical importance in clinical practice. With the advancement of molecular diagnostics, techniques such as metagenomic next-generation sequencing ( mNGS ) and real-time PCR with melting curve analysis ( MC-PCR ) are being increasingly employed for the diagnosis of mycobacterial infections. This study aimed to evaluate the diagnostic value of these two methods in the context of pulmonary mycobacterial disease. Methods Bronchoalveolar lavage fluid (BALF) samples from 86 patients suspected of pulmonary mycobacterial infection were analyzed using both mNGS and MC-PCR. The concordance between the results of these two methods was compared. Using a comprehensive clinical diagnosis as the reference standard, the sensitivity, specificity, and agreement of these two molecular techniques, alongside conventional detection methods, were evaluated. Results In the group suspected of Mycobacterium tuberculosis (TB) infection, mNGS and MC-PCR demonstrated substantial agreement (Kappa = 0.667). The sensitivities were 96.67% (29/30) and 83.33% (25/30), respectively. In the group suspected of non-tuberculous mycobacteria (NTM) infection, the two methods showed a high level of agreement (Kappa = 0.824), with sensitivities of 96.77% (30/31) and 93.55% (29/31), respectively. The concordance rate for NTM species identification between the two methods was 90.9% (30/33). Conclusion In the diagnosis of mycobacterial pulmonary infection and the identification of non-tuberculous mycobacteria (NTM) species, both mNGS and MC-PCR exhibited higher sensitivity and superior consistency compared to the other methods evaluated in this study. The combined application of these techniques with conventional detection methods may provide a novel and effective approach for the diagnosis of mycobacterial pulmonary infections.