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Barilar, Ivan; Battaglia, Simone; Borroni, Emanuele; Brandao, Angela Pires; Brankin, Alice; Cabibbe, Andrea Maurizio; Carter, Joshua; Chetty, Darren; Cirillo, Daniela Maria; Claxton, Pauline; Clifton, David A.; Cohen, Ted; Coronel, Jorge; Crook, Derrick W.; Dreyer, Viola; Earle, Sarah G.; Escuyer, Vincent; Ferrazoli, Lucilaine; Fowler, Philip W.; Gao, George Fu; Gardy, Jennifer; Gharbia, Saheer; Ghisi, Kelen Teixeira; Ghodousi, Arash; [...]

Quantitative measurement of antibiotic resistance in Mycobacterium tuberculosis reveals genetic determinants of resistance and susceptibility in a target gene approach

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  • Media type: E-Article
  • Title: Quantitative measurement of antibiotic resistance in Mycobacterium tuberculosis reveals genetic determinants of resistance and susceptibility in a target gene approach
  • Contributor: Barilar, Ivan; Battaglia, Simone; Borroni, Emanuele; Brandao, Angela Pires; Brankin, Alice; Cabibbe, Andrea Maurizio; Carter, Joshua; Chetty, Darren; Cirillo, Daniela Maria; Claxton, Pauline; Clifton, David A.; Cohen, Ted; Coronel, Jorge; Crook, Derrick W.; Dreyer, Viola; Earle, Sarah G.; Escuyer, Vincent; Ferrazoli, Lucilaine; Fowler, Philip W.; Gao, George Fu; Gardy, Jennifer; Gharbia, Saheer; Ghisi, Kelen Teixeira; Ghodousi, Arash; [...]
  • imprint: Springer Science and Business Media LLC, 2024
  • Published in: Nature Communications
  • Language: English
  • DOI: 10.1038/s41467-023-44325-5
  • ISSN: 2041-1723
  • Origination:
  • Footnote:
  • Description: <jats:title>Abstract</jats:title><jats:p>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 <jats:italic>Mycobacterium tuberculosis</jats:italic> 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.</jats:p>
  • Access State: Open Access