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.
Quantitative measurement of antibiotic resistance in Mycobacterium tuberculosis reveals genetic determinants of resistance and susceptibility in a target gene approach / I. Barilar, S. Battaglia, E. Borroni, A.P. Brandao, A. Brankin, A.M. Cabibbe, J. Carter, D. Chetty, D.M. Cirillo, P. Claxton, D.A. Clifton, T. Cohen, J. Coronel, D.W. Crook, V. Dreyer, S.G. Earle, V. Escuyer, L. Ferrazoli, P.W. Fowler, G.F. Gao, J. Gardy, S. Gharbia, K.T. Ghisi, A. Ghodousi, A.L. Gibertoni Cruz, L. Grandjean, C. Grazian, R. Groenheit, J.L. Guthrie, W. He, H. Hoffmann, S.J. Hoosdally, M. Hunt, Z. Iqbal, N.A. Ismail, L. Jarrett, L. Joseph, R. Jou, P. Kambli, R. Khot, J. Knaggs, A. Koch, D. Kohlerschmidt, S. Kouchaki, A.S. Lachapelle, A. Lalvani, S.G. Lapierre, I.F. Laurenson, B. Letcher, W. Lin, C. Liu, D. Liu, K.M. Malone, A. Mandal, M. Mansjö, D.V.L. Calisto Matias, G. Meintjes, F. de Freitas Mendes, M. Merker, M. Mihalic, J. Millard, P. Miotto, N. Mistry, D. Moore, K.A. Musser, D. Ngcamu, H.N. Nhung, S. Niemann, K.S. Nilgiriwala, C. Nimmo, M. O’Donnell, N. Okozi, R.S. Oliveira, S.V. Omar, N. Paton, T.E.A. Peto, J.M.W. Pinhata, S. Plesnik, Z.M. Puyen, M.S. Rabodoarivelo, N. Rakotosamimanana, P.M.V. Rancoita, P. Rathod, E.R. Robinson, G. Rodger, C. Rodrigues, T.C. Rodwell, A. Roohi, D. Santos-Lazaro, S. Shah, G. Smith, T.A. Kohl, W. Solano, A. Spitaleri, A.J.C. Steyn, P. Supply, U. Surve, S. Tahseen, N.T.T. Thuong, G. Thwaites, K. Todt, A. Trovato, C. Utpatel, A. Van Rie, S. Vijay, A.S. Walker, T.M. Walker, R. Warren, J. Werngren, M. Wijkander, R.J. Wilkinson, D.J. Wilson, P. Wintringer, Y. Xiao, Y. Yang, Z. Yanlin, S. Yao, B. Zhu. - In: NATURE COMMUNICATIONS. - ISSN 2041-1723. - 15:1(2024 Jan 12), pp. 488.1-488.13. [10.1038/s41467-023-44325-5]
Quantitative measurement of antibiotic resistance in Mycobacterium tuberculosis reveals genetic determinants of resistance and susceptibility in a target gene approach
A. Spitaleri;
2024
Abstract
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.
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