Comparisons of whole-genome sequencing and phenotypic drug susceptibility testing for Mycobacterium tuberculosis causing MDR-TB and XDR-TB in Thailand

Abstract

© 2019 Elsevier B.V. and International Society of Chemotherapy Drug-resistant tuberculosis (TB) is a major public health problem. There is little information regarding the genotypic–phenotypic association of anti-TB drugs, especially for second-line drugs. This study compared phenotypic drug susceptibility testing (DST) with predictions based on whole-genome sequencing (WGS) data for 266 Mycobacterium tuberculosis isolates. Phenotypic DST used the standard proportional method. Clinical isolates of M. tuberculosis collected in Thailand between 1998 and 2013 comprised 51 drug-sensitive strains, six mono-resistant strains, two multiple-resistant strains, 88 multi-drug-resistant strains, 95 pre-extensively drug-resistant strains and 24 extensively drug-resistant strains. WGS analysis was performed using the computer programs PhyResSE and TB-Profiler. TB-Profiler had higher average concordance with phenotypic DST than PhyResSE for both first-line (91.96% vs. 91.4%) and second-line (79.67% vs. 78.20%) anti-TB drugs. The average sensitivity for all anti-TB drugs was also higher (83.13% vs. 72.08%) with slightly lower specificity (83.50% vs. 86.68%). Regardless of the program used, isoniazid, rifampicin and amikacin had the highest concordance with phenotypic DST (96.2%, 93.5% and 95.6%, respectively). Ethambutol, ethionamide and fluoroquinolones had the lowest concordance (87.34%, 81.44% and 73.85%, respectively). Concordance rates of ofloxacin (a second-generation fluoroquinolone), levofloxacin, moxifloxacin and gatifloxacin (third- and fourth-generation fluoroquinolones) were 91.79%, 76.62%, 72.64% and 57.35%, respectively. Discordance between phenotypic and WGS-based DSTs may be due, in part, to the choice of critical concentration and variable reproducibility of the phenotypic tests. It may also be due to limitations of the mutation databases (especially for the second-line drugs) and the analysis program used. Mutations related to fluoroquinolone resistance, especially the later generations, need to be identified.