Environmental selection and epistasis in an empirical phenotype-environment-fitness landscape

Abstract

The fitness landscape, a function that maps genotypic and phenotypic changes to their effects on fitness, is an invaluable concept in evolutionary biochemistry. Though widely discussed, measurements of phenotype-fitness landscapes in proteins remain scarce. Here, we quantify all single mutational effects on fitness and phenotype (antibiotic resistance level) of VIM-2 β-lactamase (5600 variants) across a 64-fold range of ampicillin concentrations by deep mutational scanning. We then construct a phenotype-fitness landscape that takes variations in environmental selection pressure into account (a phenotype-environment-fitness landscape). We found that a simple, empirical landscape accurately models the ~39,000 mutational data points, which suggests the evolution of VIM-2 can be predicted based on the selection environment. Our landscape provides new quantitative knowledge on the evolution of the β-lactamases and proteins in general, particularly their evolutionary dynamics under sub-inhibitory antibiotic concentrations, as well as the mechanisms and environmental dependence of nonspecific epistasis.

Environment by environment interactions (ExE) differ across genetic backgrounds (ExExG)

“…Given their broad utility to biologists, many useful mathematical frameworks exist for quantifying GxG (18), GxE (19) and GxGxE (3,11,20). Further, many experimental frameworks have comprehensively surveyed GxG or GxGxG (15,16,(21)(22)(23), GxE (24)(25)(26)(27), or GxGxE (24,(28)(29)(30)(31). But one type of interaction has remained largely neglected by quantitative geneticists: ExE interactions, or those arising from interactions between environments (Figure 1A).…”