Abstract

Background: Phenotypic drug susceptibility testing for prediction of tuberculosis (TB) drug resistance is slow and unreliable, limiting individualized therapy and monitoring of national TB data. Our study evaluated whole genome sequencing (WGS) for its predictive accuracy, use in TB drug-resistance surveillance, and ability to quantify the effects of resistance-associated mutations on minimum inhibitory concentrations (MICs) of anti-TB drugs. Methods: We used WGS to measure the susceptibility of 4880 isolates to ten anti-TB drugs ; for pyrazinamide, we used BACTEC MGIT 960. We determined the accuracy of WGS by comparing the prevalence of resistance, measured by genetic sequencing, with the true prevalence of resistance, determined by phenotypic testing. We used the Student-Newman-Keuls test to confirm MIC differences of mutations. Findings: Resistance to isoniazid, rifampin, and ethambutol were correctly predicted with at least 92·29% sensitivity, resistance to pyrazinamide with 50·52% sensitivity, and resistance to six second-line drugs with 85·05% to 96·01% sensitivity. In addition to the large overlap in estimated drug resistance prevalence by WGS and phenotypic testing, WGS can detect low-level resistant or sub-ECOFF mutations which may be missed by phenotyping. For nearly all drugs, resistance-conferring mutations had varying levels of impact on MICs. Interpretation: WGS can predict phenotypic susceptibility with high accuracy and allow for detection of new escape mutations by rapid molecular tools; as such, it can be a valuable tool in TB drug resistance surveillance and for determining the therapeutic approach. Funding Information: We acknowledge the financial supports of the grants from the Ministry of Science and Technology, the National Science and Technology Major Project (2018ZX10103001) and the National Key Research and Development Plan (No. 2020YFA0907200, 2019YFC0840602). Declaration of Interests: All authors report no conflicts of interest relevant to this article.

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