Comparative Study on Tuberculosis Drug Resistance and Molecular Detection Methods Among Different Mycobacterium Tuberculosis Lineages

Purpose: This study aims to compare drug resistance and detection efficacy across different Mycobacterium tuberculosis lineages, offering insights for precise treatment and molecular diagnosis. Methods: 161 strains of Mycobacterium tuberculosis (M.tb) were tested for drug resistance using Phenotypic Drug Susceptibility Testing (pDST), High-Resolution Melting analysis (HRM), and Whole Genome Sequencing (WGS) methods. The main focus was on evaluating the accuracy of different methods for detecting resistance to rifampicin (RIF), isoniazid (INH), and streptomycin (SM).Results: Among the 161 strains ofM.tb, 83.85% (135/161) were fully sensitive to RIF, INH, and SM according to pDST, and the rate of multidrug resistance was 4.35% (7/161). The drug resistance rates of lineage 2 M.tb to the three drugs (26/219, 11.87%) were significantly higher than those of non-lineage 2 M.tb (12/264, 4.45%) (P<0.05). Compared with pDST, WGS had a sensitivity of 100%, 94.12%, and 92.31% and a specificity of 100%, 99.31%, and 98.65% for RIF, INH, and SM, respectively, with no significant difference. The sensitivity of HRM for RIF, INH, and SM was 87.50%, 52.94%, and 76.92%, respectively, while the specificity was 96.08%, 99.31%, and 99.32%, respectively. The sensitivity of HRM for detecting INH resistance was significantly lower than that of pDST (P=0.039). Compared with HRM, WGS increased the sensitivity of RIF, INH, and SM by 12.50%, 41.18%, and 15.38%, respectively.Conclusion: There are significant differences in drug resistance rates among different lineages ofM.tb, with lineage 2 having higher rates of RIF, INH, and SM resistance than lineages 3 and 4. The sensitivity of HRM is far lower than that of pDST, and currently, the accuracy of HRM is not sufficient to replace pDST. WGS has no significant difference in detecting drug resistance compared with pDST but can identify new anti-tuberculosis drug-resistant mutations, providing effective guidance for clinical decision-making.