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

The CRyPTIC Consortium

doi: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

The CRyPTIC Consortium

Stanford University
Research Center Borstel - Leibniz Lung Center
IRCCS San Raffaele Scientific Institute
Instituto Oswaldo Cruz
Instituto Adolfo Lutz
University of Oxford
Africa Health Research Institute
Scottish Mycobacteria Reference Laboratory
Yale School of Public Health
Universidad Peruana Cayetano Heredia
Wadsworth Center for Laboratories and Research
Chinese Center for Disease Control and Prevention
Bill and Melinda Gates Foundation
UK Health Security Agency
Vita-Salute San Raffaele University
University College London
University of New South Wales
Public Health Agency of Sweden
University of British Columbia
Public Health Ontario
SYNLAB Gauting
IMLred
European Molecular Biology Laboratory
National Health Laboratory Services
Taiwan Centers for Disease Control
P.D. Hinduja National Hospital and Medical Research Centre
University of Cape Town
University of Surrey
Imperial College London
University of Montreal
Instituto Nacional de Salud, Lima
The Foundation for Medical Research India
WHO-SRL
London School of Hygiene and Tropical Medicine
German Center for Infection Research (DZIF)
Columbia University
National University of Singapore
Institut Pasteur de Madagascar
FIND
University of California at San Diego
Center for Infection and Immunity of Lille (CIIL)
National TB Control Program
University of Antwerp
University of Edinburgh
Stellenbosch University
Wellcome Centre for Infectious Diseases Research in Africa
Francis Crick Institute
CAS - Institute of Microbiology

Research output: Contribution to journal › Article › peer-review

37 Scopus citations

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.

Original language	English
Article number	488
Journal	Nature Communications
Volume	15
Issue number	1
DOIs	https://doi.org/10.1038/s41467-023-44325-5
State	Published - Dec 2024
Externally published	Yes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

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10.1038/s41467-023-44325-5

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

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.",

author = "\{The CRyPTIC Consortium\} and Ivan Barilar and Simone Battaglia and Emanuele Borroni and Brandao, \{Angela Pires\} and Alice Brankin and Cabibbe, \{Andrea Maurizio\} and Joshua Carter and Darren Chetty and Cirillo, \{Daniela Maria\} and Pauline Claxton and Clifton, \{David A.\} and Ted Cohen and Jorge Coronel and Crook, \{Derrick W.\} and Viola Dreyer and Earle, \{Sarah G.\} and Vincent Escuyer and Lucilaine Ferrazoli and Fowler, \{Philip W.\} and Gao, \{George Fu\} and Jennifer Gardy and Saheer Gharbia and Ghisi, \{Kelen Teixeira\} and Arash Ghodousi and \{Gibertoni Cruz\}, \{Ana Lu{\'i}za\} and Louis Grandjean and Clara Grazian and Ramona Groenheit and Guthrie, \{Jennifer L.\} and Wencong He and Harald Hoffmann and Hoosdally, \{Sarah J.\} and Martin Hunt and Zamin Iqbal and Ismail, \{Nazir Ahmed\} and Lisa Jarrett and Lavania Joseph and Ruwen Jou and Priti Kambli and Rukhsar Khot and Jeff Knaggs and Anastasia Koch and Donna Kohlerschmidt and Samaneh Kouchaki and Lachapelle, \{Alexander S.\} and Ajit Lalvani and Lapierre, \{Simon Grandjean\} and Laurenson, \{Ian F.\} and Brice Letcher and Puyen, \{Zully M.\}",

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AU - Borroni, Emanuele

AU - Brandao, Angela Pires

AU - Brankin, Alice

AU - Cabibbe, Andrea Maurizio

AU - Carter, Joshua

AU - Chetty, Darren

AU - Cirillo, Daniela Maria

AU - Claxton, Pauline

AU - Clifton, David A.

AU - Cohen, Ted

AU - Coronel, Jorge

AU - Crook, Derrick W.

AU - Dreyer, Viola

AU - Earle, Sarah G.

AU - Escuyer, Vincent

AU - Ferrazoli, Lucilaine

AU - Fowler, Philip W.

AU - Gao, George Fu

AU - Gardy, Jennifer

AU - Gharbia, Saheer

AU - Ghisi, Kelen Teixeira

AU - Ghodousi, Arash

AU - Gibertoni Cruz, Ana Luíza

AU - Grandjean, Louis

AU - Grazian, Clara

AU - Groenheit, Ramona

AU - Guthrie, Jennifer L.

AU - He, Wencong

AU - Hoffmann, Harald

AU - Hoosdally, Sarah J.

AU - Hunt, Martin

AU - Iqbal, Zamin

AU - Ismail, Nazir Ahmed

AU - Jarrett, Lisa

AU - Joseph, Lavania

AU - Jou, Ruwen

AU - Kambli, Priti

AU - Khot, Rukhsar

AU - Knaggs, Jeff

AU - Koch, Anastasia

AU - Kohlerschmidt, Donna

AU - Kouchaki, Samaneh

AU - Lachapelle, Alexander S.

AU - Lalvani, Ajit

AU - Lapierre, Simon Grandjean

AU - Laurenson, Ian F.

AU - Letcher, Brice

AU - Puyen, Zully M.

PY - 2024/12

Y1 - 2024/12

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AB - 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.

UR - https://www.scopus.com/pages/publications/85182483279

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DO - 10.1038/s41467-023-44325-5

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AN - SCOPUS:85182483279

SN - 2041-1723

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JO - Nature Communications

JF - Nature Communications

IS - 1

M1 - 488

ER -

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

Abstract

UN SDGs

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