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

The effect of mutations in a protein may depend on the presence of others-a phenomenon known as epistasis. Epistasis plays a key role in evolution and complicates predictions of mutational effects, as effects can be context-dependent. Yet, despite its importance, the mechanistic basis of epistasis remains poorly understood. To better characterize epistasis, we focused on an 11-residue α-helix in TEM-1 β-lactamase and constructed a comprehensive library of over 14,000 double mutants. Fitness and minimum inhibitory concentration, two contrasted measure of protein efficiency, reveal consistent widespread epistasis. A non-linear two-state protein stability model in which destabilizing, neutral, or stabilizing mutations contribute additively to the stability phenotype, largely explain the data. Most epistatic effects are consequently predictable from single-mutation effects. However, systematic deviations from the model occur when both mutated residues directly interact in the 3D structure-a fold conserved across distant TEM-1 homologs. We therefore investigated the predictive power of statistical models trained on distant homologous sequences and found that they could partially recover the observed epistatic interactions. Our results, built on a short structural element of a protein, shed light on multiple determinants of the epistatic landscape that have shaped the evolutionary trajectory of β-lactamase proteins over long timescales.

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Journal
Nature Communications
Published
2026-03-17
DOI
https://doi.org/10.1038/s41467-026-70627-5
Primary Topic
Protein Structure and Dynamics
Type
article
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article

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

Simona Cocco, Hervé Jacquier, Olivier Tenaillon, Karine Panigoni et al.
Nature Communications
Protein Structure and Dynamics
article

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

Simona Cocco, Hervé Jacquier, Olivier Tenaillon, Karine Panigoni, Jimmy Mullaert, André Birgy, Clément Roussel, Harry Kemble, Audrey Chapron, Rémi Monasson, Mélanie Magnan
article en

Abstract

The effect of mutations in a protein may depend on the presence of others-a phenomenon known as epistasis. Epistasis plays a key role in evolution and complicates predictions of mutational effects, as effects can be context-dependent. Yet, despite its importance, the mechanistic basis of epistasis remains poorly understood. To better characterize epistasis, we focused on an 11-residue α-helix in TEM-1 β-lactamase and constructed a comprehensive library of over 14,000 double mutants. Fitness and minimum inhibitory concentration, two contrasted measure of protein efficiency, reveal consistent widespread epistasis. A non-linear two-state protein stability model in which destabilizing, neutral, or stabilizing mutations contribute additively to the stability phenotype, largely explain the data. Most epistatic effects are consequently predictable from single-mutation effects. However, systematic deviations from the model occur when both mutated residues directly interact in the 3D structure-a fold conserved across distant TEM-1 homologs. We therefore investigated the predictive power of statistical models trained on distant homologous sequences and found that they could partially recover the observed epistatic interactions. Our results, built on a short structural element of a protein, shed light on multiple determinants of the epistatic landscape that have shaped the evolutionary trajectory of β-lactamase proteins over long timescales.

Nature Communications
Centre National de la Recherche Scientifique (FR), Inserm (FR), Université de Versailles Saint-Quentin-en-Yvelines (FR), Université Paris Cité (FR), Université Paris Sciences et Lettres (FR), Université Paris-Saclay (FR), École Normale Supérieure - PSL (FR), Sorbonne Université (FR), Université Sorbonne Paris Nord (FR), Sorbonne Paris Cité (FR), Assistance Publique – Hôpitaux de Paris (FR), Hôpital Robert-Debré (FR), Hôpitaux Universitaires Henri-Mondor (FR), Institut Cochin (FR), ESPCI Paris (FR)
Openalex Percentile: Top 19%
Protein Structure and Dynamics
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