Capturing the mutational landscape of the beta-lactamase TEM-1

Abstract

Adaptation proceeds through the selection of mutations. The distribution of mutant fitness effect and the forces shaping this distribution are therefore keys to predict the evolutionary fate of organisms and their constituents such as enzymes. Here, by producing and sequencing a comprehensive collection of 10,000 mutants, we explore the mutational landscape of one enzyme involved in the spread of antibiotic resistance, the beta-lactamase TEM-1. We measured mutation impact on the enzyme activity through the estimation of amoxicillin minimum inhibitory concentration on a subset of 990 mutants carrying a unique missense mutation, representing 64% of possible amino acid changes in that protein reachable by point mutation. We established that mutation type, solvent accessibility of residues, and the predicted effect of mutations on protein stability primarily determined alone or in combination changes in minimum inhibitory concentration of mutants. Moreover, we were able to capture the drastic modification of the mutational landscape induced by a single stabilizing point mutation (M182T) by a simple model of protein stability. This work thereby provides an integrated framework to study mutation effects and a tool to understand/define better the epistatic interactions.epistasis | adaptive landscape | distribution of fitness effects T he distribution of fitness effects (DFE) of mutations is central in evolutionary biology. It captures the intensity of the selective constraints acting on an organism and therefore how the interplay between mutation, genetic drift, and selection will shape the evolutionary fate of populations (1). For instance, the DFE determines the size of the population required to see fitness increase or decrease (2

Contingency and entrenchment in protein evolution under purifying selection

“…Although the formal validity of their inference has been the topic of debate (91), our simulation results are in accordance with their basic contention and provide a detailed view of the form of epistasis in proteins under purifying selection. Our results are also consistent with the results of both theoretical (60) and empirical studies (6,72) showing that epistatic interactions are in large part governed by underlying biophysical interactions between substitutions.…”

“…Here the selection coefficient, s, denotes the difference in log fitness. This choice of fitness function is thus consistent with experimental data on the distribution of fitness effects of mutants (70)(71)(72)(73).…”

“…S2A. Likewise, in the absence of selection substitutions are more often destabilizing than stabilizing (binomial test, P < 10 −15 ), as expected from empirical studies on the effects of random mutations (61,72,75,76,80).…”

“…Random mutations in a protein-coding sequence typically destabilize the protein structure (26,72,(75)(76)(77)(78)(79)(80). Thus, if protein evolution proceeded solely via random substitutions, without any selection, we would expect a decrease in protein stability over time.…”

Using cellular fitness to map the structure and function of a major facilitator superfamily effluxer

“…Typically, well‐behaved proteins whose function is strongly correlated to organismal fitness are used to study this link as their biochemical properties can be readily measured in vitro . Such model proteins include TEM‐1 β‐lactamase, dihydrofolate reductase, and adenylate kinase (Wang et al , 2002; Couñago et al , 2006; Weinreich et al , 2006; Peña et al , 2010; Jacquier et al , 2013; Rodrigues et al , 2016). These advances have provided a greater understanding into how the physicochemical properties of a protein relate to fitness and allow investigators to explore the role of fitness landscapes in adaptive evolution (Weinreich et al , 2006; Dean & Thornton, 2007; Walkiewicz et al , 2012; Harms & Thornton, 2013; Meini et al , 2015; Palmer et al , 2015).…”