A comprehensive biophysical description of pairwise epistasis throughout an entire protein domain

By C. A. Olson, Nicholas C. Wu, Ren Sun. 2014

347 citations recorded by the source corpus.

SUMMARY Background Non-additivity in fitness effects from two or more mutations, termed epistasis, can result in compensation of deleterious mutations or negation of beneficial mutations. Recent evidence shows the importance of epistasis in individual evolutionary pathways. However, an unresolved question in molecular evolution is how often and how significantly fitness effects change in alternative genetic backgrounds. Results To answer this question we quantified the effects of all single mutations and double mutations between all positions in the IgG-binding domain of protein G (GB1). By observing the first two steps of all possible evolutionary pathways, this fitness profile enabled the characterization of the extent and magnitude of pairwise epistasis throughout an entire protein molecule. Furthermore, we developed a novel approach to quantitatively determine the effects of single mutations on structural stability (ΔΔGU). This enabled determination of the importance of stability effects in functional epistasis. Conclusions Our results illustrate common biophysical mechanisms for occurrences of positive and negative epistasis. Our results show pervasive positive epistasis within a conformationally dynamic network of residues. The stability analysis shows that significant negative epistasis, which is more common than positive epistasis, mostly occurs between combinations of destabilizing mutations. Furthermore, we show that although significant positive epistasis is rare, many deleterious mutations are beneficial in at least one alternative mutational background. The distribution of conditionally beneficial mutations throughout the domain demonstrates that the functional portion of sequence space can be significantly expanded by epistasis.

Subfields: Genetics, Molecular Biology

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Citations in the corpus

Evolution-Based Functional Decomposition of Proteins (2015, positive): “However, the sparsity of the constraints between amino acids observed both statistically (6; 10) and experimentally (33–35) eﬀectively reduces the dimensionality of the solution, enabling practical approaches.”
Adaptation in protein fitness landscapes is facilitated by indirect paths (2016, methodology): “The sequence of the WT template consisted of a T7 promoter, 5’ UTR, the coding sequence of Protein GB1, 3’ poly-GS linkers, and a FLAG-tag (Figure 1— figure supplement 1B) ([Olson et al., 2014).”
The genetic landscape of a physical interaction (2018, background): “Thus, as observed in other systems (Araya et al., 2012; Olson et al., 2014), genetic interactions make an important contribution to the outcome of double mutations.”
Epistasis in protein evolution (2016, background): “In GB1, most mutations that are deleterious have at least one or more interacting mutations elsewhere in the protein that make it beneficial or neutral.(34) Positive epistasis can open mutational trajectories to combinations of substitutions that would otherwise have been inaccessible.”
Inferring the shape of global epistasis (2018, methodology): “(37) targeted 55 sites for mutation and measured the binding to an immunoglobulin fragment (IgGFC) for all single– amino-acid substitutions (1,045) and 95% of all double substitutions (509,693) (37).”
Coevolution-based inference of amino acid interactions underlying protein function (2018, methodology): “The same distribution shapes are found in all the individual PDZ 141 homologs tested (Figure 2 and Figure 2 – figure supplements 1-4), the average over homologs (Figure 3), 142 and even for DCS in an unrelated protein (GB1, Figure 2 – figure supplement 5 (Olson et al., 2014)).”