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 A.P.; Brankin A.; Cabibbe A.M.; Carter J.; Chetty D.; Cirillo D.M.; Claxton P.; Clifton D.A.; Cohen T.; Coronel J.; Crook D.W.; Dreyer V.; Earle S.G.; Escuyer V.; Ferrazoli L.; Fowler P.W.; Gao G.F.; Gardy J.; Gharbia S.; Ghisi K.T.; Ghodousi A.; Gibertoni Cruz A.L.; Grandjean L.; Grazian C.; Groenheit R.; Guthrie J.L.; He W.; Hoffmann H.; Hoosdally S.J.; Hunt M.; Iqbal Z.; Ismail N.A.; Jarrett L.; Joseph L.; Jou R.; Kambli P.; Khot R.; Knaggs J.; Koch A.; Kohlerschmidt D.; Kouchaki S.; Lachapelle A.S.; Lalvani A.; Lapierre S.G.; Laurenson I.F.; Letcher B.; Lin W.-H.; Liu C.; Liu D.; Malone K.M.; Mandal A.; Mansjö M.; Calisto Matias D.V.L.; Meintjes G.; de Freitas Mendes F.; Merker M.; Mihalic M.; Millard J.; Miotto P.; Mistry N.; Moore D.; Musser K.A.; Ngcamu D.; Nhung H.N.; Niemann S.; Nilgiriwala K.S.; Nimmo C.; O’Donnell M.; Okozi N.; Oliveira R.S.; Omar S.V.; Paton N.; Peto T.E.A.; Pinhata J.M.W.; Plesnik S.; Puyen Z.M.; Rabodoarivelo M.S.; Rakotosamimanana N.; Rancoita P.M.V.; Rathod P.; Robinson E.R.; Rodger G.; Rodrigues C.; Rodwell T.C.; Roohi A.; Santos-Lazaro D.; Shah S.; Smith G.; Kohl T.A.; Solano W.; Spitaleri A.; Steyn A.J.C.; Supply P.; Surve U.; Tahseen S.; Thuong N.T.T.; Thwaites G.; Todt K.; Trovato A.; Utpatel C.; Van Rie A.; Vijay S.; Walker A.S.; Walker T.M.; Warren R.; Werngren J.; Wijkander M.; Wilkinson R.J.; Wilson D.J.; Wintringer P.; Xiao Y.-X.; Yang Y.; Yanlin Z.; Yao S.-Y.; Zhu B. · Nature Communications (2024) · DOI: 10.1038/s41467-023-44325-5

Resumen

The 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.

Instituciones: Universidad Peruana Cayetano Heredia