Origins and breadth of pairwise epistasis in an α-helix of β-lactamase TEM-1

Abstract

Epistasis affects genome evolution together with our ability to predict individual mutation effects. The mechanistic basis of epistasis remains, however, largely unknown. To quantify and better understand interactions between fitness-affecting mutations, we focus on a 11 amino-acid α-helix of the protein β-lactamase TEM-1, and build a comprehensive library of more than 15,000 double mutants. Analysis of the growth rates of these mutants shows pervasive epistasis, which can be largely explained by a non-linear two-state model, where inactivating, destabilizing, neutral, or stabilizing mutations additively contribute to the phenotype. Hence, most epistatic interactions can be predicted by a non-linear model informed by single-point mutational measurements only. Deviations from the two-state model are consistently found for few pairs of residues, in particular when they are in contact. This result, as well as single-point mutation parameters, can be quantitatively found back through direct-coupling-analysis-based statistical models inferred from homologous sequence data. Our results thus shed light on the existence and the origins of the multiple determinants of the epistatic landscape, even at the level of small structural components of a protein, and suggest that the corresponding constraints shape the entire β-lactamase family.

Minimal epistatic networks from integrated sequence and mutational protein data

“…Recent developments of deep scanning mutagenesis experiments combined with the advances in sequencing technology have nowadays shifted the paradigm from few tested mutations to large mutational scans, eg. by testing almost all single site mutations around a wild type sequence [22, 20, 21, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44], single and double mutations in a small protein region[44], or mutational paths on some chosen sites and amino-acids [45].…”

gUMI-BEAR, a modular, unsupervised population barcoding method to track variants and evolution at high resolution

“…However, how individual adaptations translate into success or failure, or how population dynamics are affected by individual variations and their degree, is not yet clear. A number of studies are beginning to shed light on these questions by employing procedures to quantify a population's clonal makeup [6][7][8][9][10][11][12][13]. Using these methods, multiple lineages within a population can be distinguished by the introduction of DNA barcodes, short segments of DNA inserted into cells' genomes and passed on to their progenies.…”

gUMI-BEAR, a modular, unsupervised population barcoding method to track variants and evolution at high resolution

“…However, how individual adaptations translate into success or failure, or how population dynamics are affected by individual variations, is not yet clear. A number of experiments are beginning to shed light on these questions by employing procedures to quantify a population's clonal makeup [6][7][8][9][10][11][12][13] . Using these methods, multiple lineages can be distinguished by the introduction of DNA barcodes, short segments of DNA inserted into cells' genomes and passed on to their progenies.…”