A systematic survey of an intragenic epistatic landscape

Abstract

Mutations are the source of evolutionary variation. The interactions of multiple mutations can have important effects on fitness and evolutionary trajectories. We have recently described the distribution of fitness effects of all single mutations for a nine-amino-acid region of yeast Hsp90 (Hsp82) implicated in substrate binding. Here, we report and discuss the distribution of intragenic epistatic effects within this region in seven Hsp90 point mutant backgrounds of neutral to slightly deleterious effect, resulting in an analysis of more than 1,000 double mutants. We find negative epistasis between substitutions to be common, and positive epistasis to be rare-resulting in a pattern that indicates a drastic change in the distribution of fitness effects one step away from the wild type. This can be well explained by a concave relationship between phenotype and genotype (i.e., a concave shape of the local fitness landscape), suggesting mutational robustness intrinsic to the local sequence space. Structural analyses indicate that, in this region, epistatic effects are most pronounced when a solvent-inaccessible position is involved in the interaction. In contrast, all 18 observations of positive epistasis involved at least one mutation at a solvent-exposed position. By combining the analysis of evolutionary and biophysical properties of an epistatic landscape, these results contribute to a more detailed understanding of the complexity of protein evolution.

On the (un)predictability of a large intragenic fitness landscape

“…Based on previous screenings of fitness effects in different environments (26) and on different genetic backgrounds (20), and on expectations of their biophysical role, 13 amino acid-changing point mutations at 6 sites were chosen for the fitness landscape presented here (Fig. 1).…”

Physical epistatic landscape of antibody binding affinity

“…This analysis showed that almost all of the variance unexplained by additivity (∼ 40%) could be attributed to epistasis, making its contribution to the phenotype comparable to that of single mutations. A large fraction of that epistasis was beneficial, in contrast with previous reports of mostly negative epistasis owing to the concavity of the scale [24,29,49], which we here circumvent by directly considering the free energy.…”

“…This analysis showed that almost all of the variance unexplained by additivity (∼ 40%) could be attributed to epistasis, making its contribution to the phenotype comparable to that of single mutations. A large fraction of that epistasis was beneficial, in contrast with previous reports of mostly negative epistasis owing to the concavity of the scale [24,29,49], which we here circumvent by directly considering the free energy.Epistasis is key to understanding the predictability and reproducibility of evolutionary paths [18,51]. Our results show how it could constrain the space of possible hypermutation trajectories during affinity maturation, with important consequences for antibody and vaccine design, as the importance of eliciting responses of antibodies that are not just strongly binding but also evolvable is being increasingly recognized [52].…”

“…For instance, protein stability, which often determines fitness, is a nonlinear function of the folding free energy difference, which is expected to be roughly additive [12,[27][28][29][48][49][50]. This leads to both a law of diminishing returns [29] and robustness to mutations when the protein is very stable [48]. To disentangle these potential artifacts, we defined our PWM on the binding free energy, which we expect to be additive in sequence content, and we checked that this parametrization was close to minimizing epistasis.…”

“…† Corresponding authors: awalczak@lpt.ens.fr, tmora@lps.ens. fr effects on sequence background [21], and statistical covariation of residues in large sequence datasets [22,23].Intragenic epistasis has mostly been studied either by measuring the fitness of all possible mutational intermediates between two variants [10,[24][25][26][27], or by comparing the effect of mutations in different backgrounds [21,28,29]. Many such studies rely on a particular measure of fitness rather than a well-defined physical phenotype.…”