Mycobacterium tuberculosis mutation rate estimates from different lineages predict substantial differences in the emergence of drug-resistant tuberculosis.
Open accessAbstract
A key question in tuberculosis control is why some strains of M. tuberculosis are preferentially associated with resistance to multiple drugs. We demonstrate that M. tuberculosis strains from lineage 2 (East Asian lineage and Beijing sublineage) acquire drug resistances in vitro more rapidly than M. tuberculosis strains from lineage 4 (Euro-American lineage) and that this higher rate can be attributed to a higher mutation rate. Moreover, the in vitro mutation rate correlates well with the bacterial mutation rate in humans as determined by whole-genome sequencing of clinical isolates. Finally, using a stochastic mathematical model, we demonstrate that the observed differences in mutation rate predict a substantially higher probability that patients infected with a drug-susceptible lineage 2 strain will harbor multidrug-resistant bacteria at the time of diagnosis. These data suggest that interventions to prevent the emergence of drug-resistant tuberculosis should target bacterial as well as treatment-related risk factors.
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In the author's own simulation exploration of the mutant distribution used by Lang and Murray (2008) and by Ford et al. (2013), practical nonidentifiability was a stubborn problem.
“In my own simulation exploration of the mutant distribution used by Lang and Murray (2008) and by Ford et al. (2013), I also found practical nonidentifiability a stubborn problem.”
From rSalvador: An R Package for the Fluctuation Experiment (2017) · cites this paper as Ford et al. (2013)
The Mann-Whitney test is inappropriate for comparing mutation rates from fluctuation assay data.
“Recent investigators turned to the Mann-Whitney test (Ford et al. 2013), which also is inappropriate.”
From rSalvador: An R Package for the Fluctuation Experiment (2017) · cites this paper as Ford et al. 2013
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rSalvador: An R Package for the Fluctuation Experiment
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“In my own simulation exploration of the mutant distribution used by Lang and Murray (2008) and by Ford et al. (2013), I also found practical nonidenti fi ability a stubborn problem.”
BackgroundMethod
- Authors
- Ford, C. B., Shah, R. R., Maeda, M. K., Gagneux, S., Murray, M. B., Cohen, T., Johnston, J. C., Gardy, J., Lipsitch, M., & Fortune, S. M.
- Affiliations
- Harvard University (US)
- Brigham and Women's Hospital (US)
- BC Centre for Disease Control (CA)
- University of British Columbia (CA)
- Broad Institute (US)
- Corresponding author
- Fortune, Sarah M
- ORCID
- Venue
- Nature Genetics
- Published
- 2013-06-09
- Volume
- 45
- Issue
- 7
- Pages
- 784-790
- ISSN
- 1061-4036 (ISSN-L)
- 1546-1718
- PMC
- PMC3777616
- OpenAlex
- W2150600032
- Cited by
- 457
- References
- 75
- Citations by year
- 2026: 12 · 2025: 30 · 2024: 23 · 2023: 35 · 2022: 34 · 2021: 28 · 2020: 42 · 2019: 28 · 2018: 45 · 2017: 54 · 2016: 53 · 2015: 40 · 2014: 26 · 2013: 7
- FWCI
- 30.51
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Genetics (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- Funders
- Howard Hughes Medical Institute
- National Institutes of Health (DP2OD001378)
- National Institute of General Medical Sciences (U54GM088558)
- National Institute of Allergy and Infectious Diseases (U19AI076217, T32AI007638)
- National Center for Chronic Disease Prevention and Health Promotion (DP2-0D001378)
- Topics
- Health Sciences › Medicine › Infectious Diseases › Tuberculosis Research and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
- Health Sciences › Medicine › Surgery › Infectious Diseases and Tuberculosis
- Keywords
- Mycobacterium tuberculosis, drug-resistant tuberculosis, mutation rate, bacterial lineages, lineage 2, lineage 4, multidrug resistance, within-host evolution, stochastic mathematical model, clinical isolates, whole genome sequencing, tuberculosis control
- MeSH terms
- Antibiotics, Antitubercular, Computer Simulation, Humans, Mutation, Mycobacterium tuberculosis, Prognosis, Tuberculosis, Multidrug-Resistant, Communicable Diseases, Emerging, Drug Resistance, Multiple, Bacterial, Genetic Speciation, Biomarkers, Pharmacological, Mutation Rate
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