Author
Listed:
- Joshua L Payne
- Fabrizio Menardo
- Andrej Trauner
- Sonia Borrell
- Sebastian M Gygli
- Chloe Loiseau
- Sebastien Gagneux
- Alex R Hall
Abstract
Transition bias, an overabundance of transitions relative to transversions, has been widely reported among studies of the rates and spectra of spontaneous mutations. However, demonstrating the role of transition bias in adaptive evolution remains challenging. In particular, it is unclear whether such biases direct the evolution of bacterial pathogens adapting to treatment. We addressed this challenge by analyzing adaptive antibiotic-resistance mutations in the major human pathogen Mycobacterium tuberculosis (MTB). We found strong evidence for transition bias in two independently curated data sets comprising 152 and 208 antibiotic-resistance mutations. This was true at the level of mutational paths (distinct adaptive DNA sequence changes) and events (individual instances of the adaptive DNA sequence changes) and across different genes and gene promoters conferring resistance to a diversity of antibiotics. It was also true for mutations that do not code for amino acid changes (in gene promoters and the 16S ribosomal RNA gene rrs) and for mutations that are synonymous to each other and are therefore likely to have similar fitness effects, suggesting that transition bias can be caused by a bias in mutation supply. These results point to a central role for transition bias in determining which mutations drive adaptive antibiotic resistance evolution in a key pathogen.Some types of mutations occur more frequently than expected. This study shows that such bias —an excess of transitions over transversions—influences the evolution of antibiotic resistance in a key global pathogen, Mycobacterium tuberculosis.
Suggested Citation
Joshua L Payne & Fabrizio Menardo & Andrej Trauner & Sonia Borrell & Sebastian M Gygli & Chloe Loiseau & Sebastien Gagneux & Alex R Hall, 2019.
"Transition bias influences the evolution of antibiotic resistance in Mycobacterium tuberculosis,"
PLOS Biology, Public Library of Science, vol. 17(5), pages 1-23, May.
Handle:
RePEc:plo:pbio00:3000265
DOI: 10.1371/journal.pbio.3000265
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