Quantitative measurement of antibiotic resistance in Mycobacterium tuberculosis reveals genetic determinants of resistance and susceptibility in a target gene approach
Barilar I., Battaglia S., Borroni E., Brandao AP., Brankin A., Cabibbe AM., Carter J., Chetty D., Cirillo DM., Claxton P., Clifton DA., Cohen T., Coronel J., Crook DW., Dreyer V., Earle SG., Escuyer V., Ferrazoli L., Fowler PW., Gao GF., Gardy J., Gharbia S., Ghisi KT., Ghodousi A., Gibertoni Cruz AL., Grandjean L., Grazian C., Groenheit R., Guthrie JL., He W., Hoffmann H., Hoosdally SJ., Hunt M., Iqbal Z., Ismail NA., Jarrett L., Joseph L., Jou R., Kambli P., Khot R., Knaggs J., Koch A., Kohlerschmidt D., Kouchaki S., Lachapelle AS., Lalvani A., Lapierre SG., Laurenson IF., Letcher B., Lin W-H., Liu C., Liu D., Malone KM., Mandal A., Mansjö M., Calisto Matias DVL., Meintjes G., de Freitas Mendes F., Merker M., Mihalic M., Millard J., Miotto P., Mistry N., Moore D., Musser KA., Ngcamu D., Nhung HN., Niemann S., Nilgiriwala KS., Nimmo C., O’Donnell M., Okozi N., Oliveira RS., Omar SV., Paton N., Peto TEA., Pinhata JMW., Plesnik S., Puyen ZM., Rabodoarivelo MS., Rakotosamimanana N., Rancoita PMV., Rathod P., Robinson ER., Rodger G., Rodrigues C., Rodwell TC., Roohi A., Santos-Lazaro D., Shah S., Smith G., Kohl TA., Solano W., Spitaleri A., Steyn AJC., Supply P., Surve U., Tahseen S., Thuong NTT., Thwaites G., Todt K., Trovato A., Utpatel C., Van Rie A., Vijay S., Walker AS., Walker TM., Warren R., Werngren J., Wijkander M., Wilkinson RJ., Wilson DJ., Wintringer P., Xiao Y-X., Yang Y., Yanlin Z., Yao S-Y., Zhu B.
AbstractThe World Health Organization has a goal of universal drug susceptibility testing for patients with tuberculosis. However, molecular diagnostics to date have focused largely on first-line drugs and predicting susceptibilities in a binary manner (classifying strains as either susceptible or resistant). Here, we used a multivariable linear mixed model alongside whole genome sequencing and a quantitative microtiter plate assay to relate genomic mutations to minimum inhibitory concentration (MIC) in 15,211 Mycobacterium tuberculosis clinical isolates from 23 countries across five continents. We identified 492 unique MIC-elevating variants across 13 drugs, as well as 91 mutations likely linked to hypersensitivity. Our results advance genetics-based diagnostics for tuberculosis and serve as a curated training/testing dataset for development of drug resistance prediction algorithms.