Volume 11,Issue 2
Clinical Evaluation of Targeted Next-Generation Sequencing for Detecting Rifampicin and Isoniazid Resistance in Mycobacterium tuberculosis
Objective: To evaluate the clinical efficacy of targeted next-generation sequencing (NGS) technology in detecting rifampicin and isoniazid resistance in Mycobacterium tuberculosis (MTB). Methods: Patient specimens from 31 cases of MTB culture-positive and phenotypically drug-resistant (Drug susceptibility test, DST) collected between May 2024 and November 2025 were analyzed. Targeted NGS was used to detect mutations in resistance genes such as rpoB, katG, and inhA. Using DST as the gold standard, the sensitivity of NGS in detecting rifampicin and isoniazid resistance and its mutation spectrum were analyzed and compared with the PCR melting curve method, with a focus on evaluating NGS's ability to re-detect samples missed by PCR. Results: Among 15 rifampicin-resistant samples, NGS detected 13 cases with rifampicin resistance mutations, while 2 cases had no clear rifampicin resistance mutations identified, yielding a sensitivity of 86.67% for detecting resistance, significantly higher than that of the PCR melting curve method. For 17 isoniazid-resistant samples, NGS detected all isoniazid resistance mutations, achieving a sensitivity of 100%, which is also significantly higher than that of PCR. Among the 31 missed resistance mutations by PCR (14 for rifampicin and 17 for isoniazid, with 2 cases missed for both drugs), NGS successfully detected 30, with an overall re-detection sensitivity of 96.77%. NGS also identified various rare mutations and detected multiple heterogeneous resistance samples with mutation frequencies ranging from 0.19 to 0.67, all of which were missed by PCR. Conclusion: NGS demonstrates outstanding re-detection capability for rifampicin and isoniazid resistance samples missed by PCR melting curve method and provides comprehensive resistance spectrum information for multiple drugs in a single test. It offers unique advantages in detecting rare mutations and identifying heterogeneous resistance. For cases with negative PCR results but high clinical suspicion of drug resistance, NGS can serve as an important supplementary verification tool, providing crucial evidence for the precise diagnosis and treatment of complex multidrug-resistant tuberculosis.
[1] Jones RM, Adams KN, Eldesouky HE, et al., 2022, The evolving biology of Mycobacterium tuberculosis drug resistance. Frontiers in Cellular and Infection Microbiology, 12: 1027394.
[2] Datta D, Jamwal S, Jyoti N, et al., 2024, Actionable mechanisms of drug tolerance and resistance in Mycobacterium tuberculosis. FEBS Journal, 291(20): 4433-4452.
[3] Cui K, Zhao X, Liu W, et al., 2025, Global, regional, and national burden and trends of multidrug resistant tuberculosis and extensively drug resistant tuberculosis in adolescents and adults aged 15 49 years from 2010 to 2021: insights from the global burden of disease study 2021. BMC Medicine, 23(1): 445.
[4] Gopalaswamy R, Subbian S, 2026, The power of resistance: mechanisms of antimicrobial resistance in Mycobacterium tuberculosis and its impact on tuberculosis management. Clinical Microbiology Reviews, 39(1): e0019425.
[5] Pillay S, Steingart KR, Davies GR, et al., 2022, Xpert MTB/XDR for detection of pulmonary tuberculosis and resistance to isoniazid, fluoroquinolones, ethionamide, and amikacin. Cochrane Database of Systematic Reviews, 5(5): CD014841.
[6] Rocha DMGC, Magalhães C, Cá B, et al., 2021, Heterogeneous Streptomycin Resistance Level Among Mycobacterium tuberculosis Strains From the Same Transmission Cluster. Frontiers in Microbiology, 12: 659545.
[7] Zhang R, Ou X, Sun X, et al., 2023, Multiplex LNA probe based RAP assay for rapid and highly sensitive detection of rifampicin resistant Mycobacterium tuberculosis. Frontiers in Microbiology, 14: 1141424.
[8] Chang Y, Liu G, Li X, et al., 2025, A novel one tube nested fluorescence melting curve analysis for rapid detection of drug resistant Mycobacterium tuberculosis. BMC Microbiology, 26(1): 72.
[9] Yuqing Ch, Hui T, Jieyuan Zh, et al., 2025, Transforming tuberculosis diagnosis with clinical metagenomics: progress and roadblocks. Journal of Clinical Microbiology, 63(12): e0053725.
[10] Paolo M, Rebecca EC, Andrea MC, et al., 2026, Clinical evaluation of a commercial culture free targeted next generation sequencing test for diagnosis of drug resistant tuberculosis. Microbiology Spectrum, 14(2): e0303525.
[11] Pholwat S, Stroup S, Foongladda S, et al., 2013, Digital PCR to detect and quantify heteroresistance in drug resistant Mycobacterium tuberculosis. PLoS One, 8(2): e57238.
[12] Liebenberg D, Gordhan BG, Kana BD, 2022, Drug resistant tuberculosis: Implications for transmission, diagnosis, and disease management. Frontiers in Cellular and Infection Microbiology, 12: 943545.
[13] Miaoran W, Ying W, Ying X, et al., 2025, Enhanced targeted NGS assay for comprehensive diagnosis in tuberculosis and drug resistant tuberculosis patients. International Journal of Antimicrobial Agents, 66(6): 107598.
[14] Zhenzhen W, Tengfei G, Liyang X, et al., 2025, Analysis of molecular resistance and associated risk factors in tuberculosis. BMC Infectious Diseases, 25(1): 216.
[15] Jae Jin L, Daniel HS, Sun-Kyung L, et al., 2025, Trehalose catalytic shift inherently enhances phenotypic heterogeneity and multidrug resistance in Mycobacterium tuberculosis. Nature Communications, 16(1): 6442.
[16] Nicola MZ, Sanghyuk S Sh, Kefentse AT, et al., 2014, Mixed Mycobacterium tuberculosis complex infections and false negative results for rifampin resistance by GeneXpert MTB/RIF are associated with poor clinical outcomes. Journal of Clinical Microbiology, 52(7): 2422-2429.
[17] Zhang X, Zhao B, Liu L, et al., 2012, Subpopulation analysis of heteroresistance to fluoroquinolone in Mycobacterium tuberculosis isolates from Beijing, China. Journal of Clinical Microbiology, 50(4): 1471-1474.