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

Kyle J. Card; Misty D. Thomas; Joseph L. Graves; Jeffrey E. Barrick; Richard E. Lenski

doi:10.1073/pnas.2016886118

New Research In

Edited by Paul E. Turner, Yale University, New Haven, CT, and approved December 14, 2020 (received for review August 9, 2020)

Significance

A fundamental question in evolution is the repeatability of adaptation. Will independently evolving populations respond similarly when facing the same environmental challenge? This question also has important public-health implications related to the growing problem of antibiotic resistance. For example, efforts to control resistance might benefit from accurately predicting mutational paths to resistance. However, this goal is complicated when a lineage’s prior history alters its subsequent evolution. We recently found that differences between genetic backgrounds can lead to unpredictable responses in phenotypic resistance. Here, we report that genetic background can similarly alter genotypic paths to resistance. This historical contingency underscores the importance of accounting for stochasticity, in the past as well as at present, when designing evolutionarily informed treatment strategies.

Abstract

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.

Footnotes

↵¹To whom correspondence may be addressed. Email: cardkyle{at}msu.edu.

Author contributions: K.J.C. and R.E.L. designed research; K.J.C., M.D.T., J.L.G., J.E.B., and R.E.L. performed research; K.J.C., J.L.G., and R.E.L. analyzed data; and K.J.C., J.E.B., and R.E.L. wrote the paper.
Competing interest statement: J.E.B. is the owner of Evolvomics LLC.
This article is a PNAS Direct Submission.
This article contains supporting information online at https://www.pnas.org/lookup/suppl/doi:10.1073/pnas.2016886118/-/DCSupplemental.

Data Availability.

Analysis code and bioinformatics data have been deposited in GitHub, https://github.com/KyleCard/LTEE-ABR-mutant-sequencing (55). Sequence read data have been deposited in the National Center for Biotechnology Information Sequence Read Archive, https://www.ncbi.nlm.nih.gov/sra (accession no. PRJNA649277) (57).

Published under the PNAS license.

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