Patterns of Epistasis between Beneficial Mutations in an Antibiotic Resistance Gene

Abstract

Understanding epistasis is central to biology. For instance, epistatic interactions determine the topography of the fitness landscape and affect the dynamics and determinism of adaptation. However, few empirical data are available, and comparing results is complicated by confounding variation in the system and the type of mutations used. Here, we take a systematic approach by quantifying epistasis in two sets of four beneficial mutations in the antibiotic resistance enzyme TEM-1 β-lactamase. Mutations in these sets have either large or small effects on cefotaxime resistance when present as single mutations. By quantifying the epistasis and ruggedness in both landscapes, we find two general patterns. First, resistance is maximal for combinations of two mutations in both fitness landscapes and declines when more mutations are added due to abundant sign epistasis and a pattern of diminishing returns with genotype resistance. Second, large-effect mutations interact more strongly than small-effect mutations, suggesting that the effect size of mutations may be an organizing principle in understanding patterns of epistasis. By fitting the data to simple phenotype resistance models, we show that this pattern may be explained by the nonlinear dependence of resistance on enzyme stability and an unknown phenotype when mutations have antagonistically pleiotropic effects. The comparison to a previously published set of mutations in the same gene with a joint benefit further shows that the enzyme's fitness landscape is locally rugged but does contain adaptive pathways that lead to high resistance.

Bypass of genetic constraints during mutator evolution to antibiotic resistance

“…Several reports have documented both inter- [4,5,56] and intralocus [27,57,58] sign epistasis in different model systems. These observations promoted the idea that genetic constraints could be prevalent and hence adaptation could proceed through very few mutational paths to optimal genotypes [8,11].…”

A tortoise–hare pattern seen in adapting structured and unstructured populations suggests a rugged fitness landscape in bacteria

“…Fig. 1 shows a network representation of the landscape (2)(3)(4)(5) in which nodes are genotypes and edges connect genotypes differing by a single substitution. This network is embedded in two dimensions, where genotypes are grouped along the abscissa by their mutational distance from a common genotype and along the ordinate by their fitness.…”

“…This network is embedded in two dimensions, where genotypes are grouped along the abscissa by their mutational distance from a common genotype and along the ordinate by their fitness. Under assumptions of strong selection and weak mutation (2,3), adaptive evolution of a population involves a series of steps across edges from lower to higher nodes. A genetic network without epistasis (Fig.…”

Scaling properties of evolutionary paths in a biophysical model of protein adaptation

“…However, we see that the landscape is largely free of sign epistasis except near E f = 0, where there is a higher probability of multiple local fitness maxima (figure 2b). Overall, this suggests that the scaling relations from the non-epistatic Mount Fuji model may provide a reasonable approximation for this model of protein adaptation; the approximately additive nature of protein traits as in (14) has led to applications of the Mount Fuji model to proteins previously [7,31,39,40].…”

“…Let s be the total selection coefficient between the minimum and maximum fitness points on the landscape; this corresponds to the actual selection strength between two distinct biological genotypes. For example, the minimum and maximum fitnesses might correspond to wild-type and antibiotic-resistant genotypes in bacteria [9,31], or to one protein sequence that does not bind a target ligand and one that does [17]. As we coarse-grain the sequence space into smaller L and k, we must therefore hold fixed this true overall selection strength.…”