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Genomic evolution of antibiotic resistance is contingent on genetic background following a long-term experiment with Escherichia coli

dataset
posted on 2024-06-11, 06:24 authored by Michigan State University
Antibiotic resistance is a growing health concern. Efforts to control resistance would benefit from an improved ability to forecast when and how it will evolve. Epistatic interactions between mutations can promote divergent evolutionary trajectories, which complicates our ability to predict evolution. We recently showed that differences between genetic backgrounds can lead to idiosyncratic responses in the evolvability of phenotypic resistance, even among closely related Escherichia coli strains. In this study, we examined whether a strain's genetic background also influences the genotypic evolution of resistance. Do lineages founded by different genotypes take parallel or divergent mutational paths to achieve their evolved resistance states? We addressed this question by sequencing the complete genomes of antibiotic-resistant clones that evolved from several different genetic starting points during our earlier experiments. We first validated our statistical approach by quantifying the specificity of genomic evolution with respect to antibiotic treatment. As expected, mutations in particular genes were strongly associated with each drug. Then, we determined that replicate lines evolved from the same founding genotypes had more parallel mutations at the gene level than lines evolved from different founding genotypes, although these effects were more subtle than those showing antibiotic specificity. Taken together with our previous work, we conclude that historical contingency can alter both genotypic and phenotypic pathways to antibiotic resistance.

Funding

National Science Foundation, DBI-0939454

National Science Foundation, DEB-1951307

U.S. Department of Agriculture, MICL02253

History

Data contact name

BioProject Curation Staff

Publisher

National Center for Biotechnology Information

Temporal Extent Start Date

2020-07-28

Theme

  • Non-geospatial

ISO Topic Category

  • biota

National Agricultural Library Thesaurus terms

sequence analysis

Pending citation

  • No

Public Access Level

  • Public

Accession Number

PRJNA649277

Preferred dataset citation

It is recommended to cite the accession numbers that are assigned to data submissions, e.g. the GenBank, WGS or SRA accession numbers. If individual BioProjects need to be referenced, state that "The data have been deposited with links to BioProject accession number PRJNA649277 in the NCBI BioProject database (https://www.ncbi.nlm.nih.gov/bioproject/)."

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