Application evaluation of whole genome sequencing in predicting drug resistance to fluoroquinolones of Mycobacterium tuberculosis
10.3760/cma.j.cn114452-20240306-00111
- VernacularTitle:全基因组测序预测结核分枝杆菌对氟喹诺酮类药物耐药性的应用价值研究
- Author:
Wencong HE
1
;
Yunhong TAN
;
Binbin LIU
;
Yanlin ZHAO
;
Xiangyi LIU
Author Information
1. 首都医科大学附属北京同仁医院检验科，北京100730
- Keywords:
Mycobacterium tuberculosis;
Fluoroquinolones;
Drug resistance;
Genes;
Whole genome sequencing
- From:
Chinese Journal of Laboratory Medicine
2024;47(11):1299-1305
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To assess the utility of whole-genome sequencing (WGS) in predicting Mycobacterium tuberculosis resistance to fluoroquinolones (FQs) and to establish a quantitative relationship between resistant gene mutations and resistance levels. Methods:A total of 296 drug-resistant tuberculosis surveillance strains with various resistance profiles, preserved by the National Tuberculosis Reference Laboratory of the Tuberculosis Prevention and Control Center at the Chinese Center for Disease Control and Prevention between 2013 and 2020, were included as study subjects. The Sensititre? MYCOTBI microplate method and WGS were used to assess the phenotypic and genotypic drug sensitivity of Mycobacterium tuberculosis to ofloxacin and moxifloxacin. Sensitivity, specificity, and concordance (Kappa value) of WGS in predicting fluoroquinolone sensitivity were calculated using phenotypic drug susceptibility testing (DST) results as the gold standard. A summary analysis was conducted on the distribution of drug resistance mutation sites and resistance levels. The paired χ 2 test was used to compare the detection rates between the two methods, with P<0.05 indicating statistical significance. Results:Among the 296 Mycobacterium tuberculosis strains with different resistance profiles, 196 were rifampicin-resistant, 50 were resistant to other drugs, and 50 were fully sensitive. WGS identified 81 strains carrying FQs resistance-related mutations, primarily at gyrA codons 94, 90, and 91. Sensitivity, specificity, and consistency (Kappa value) of WGS in predicting ofloxacin resistance were 86.5%, 98.1%, and 0.87, respectively. For moxifloxacin resistance prediction, these values were 80.0%, 99.5%, and 0.83, respectively. There was no statistically significant difference between the phenotypic DST and WGS detection rates for ofloxacin resistance (30.1% vs 27.4%, χ 2=3.06, P=0.08). However, the phenotypic DST detection rate for moxifloxacin resistance (33.8%, 100/296) was significantly higher than that of WGS (27.4%, 81/296) (χ 2=15.43, P<0.01). Analysis of the distribution of resistance mutation sites and resistance levels showed that different mutation sites corresponded to different minimum inhibitory concentrations (MICs). Multiple mutation combinations, including gyrA_D94G, gyrA_D94Y, and gyrA_D94N were mainly associated with high-level resistance, while gyrA_D94A, gyrA_A90V, and gyrA_S91P were primarily linked to low-level resistance. Conclusion:WGS demonstrates favorable sensitivity, specificity, and consistency in predicting FQs resistance and can partially predict resistance levels.
