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The fitness of beta-lactamase mutants depends nonlinearly on resistance level at sublethal antibiotic concentrations

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Farr,  Andrew D.
Department Microbial Population Biology, Max Planck Institute for Evolutionary Biology, Max Planck Society;

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Citation

Farr, A. D., Pesce, D., Das, S. G., Zwart, M. P., & de Visser, J. A. G. M. (2023). The fitness of beta-lactamase mutants depends nonlinearly on resistance level at sublethal antibiotic concentrations. mBio, 14(3): e00098-23. doi:10.1128/mbio.00098-23.


Cite as: https://hdl.handle.net/21.11116/0000-000D-4D31-6
Abstract
Adaptive evolutionary processes are constrained by the availability of mutations which cause a fitness benefit and together make up the fitness landscape, which maps genotype space onto fitness under specified conditions. Experimentally derived fitness landscapes have demonstrated a predictability to evolution by identifying limited “mutational routes” that evolution by natural selection may take between low and high-fitness genotypes. However, such studies often utilize indirect measures to determine fitness. We estimated the competitive fitness of mutants relative to all single-mutation neighbors to describe the fitness landscape of three mutations in a β-lactamase enzyme. Fitness assays were performed at sublethal concentrations of the antibiotic cefotaxime in a structured and unstructured environment. In the unstructured environment, the antibiotic selected for higher-resistance types—but with an equivalent fitness for a subset of mutants, despite substantial variation in resistance—resulting in a stratified fitness landscape. In contrast, in a structured environment with a low antibiotic concentration, antibiotic-susceptible genotypes had a relative fitness advantage, which was associated with antibiotic-induced filamentation. These results cast doubt that highly resistant genotypes have a unique selective advantage in environments with subinhibitory concentrations of antibiotics and demonstrate that direct fitness measures are required for meaningful predictions of the accessibility of evolutionary routes.