Biology subjects

Poelwijk, F. J.

Publications and source records attributed to Poelwijk, F. J..

4 recordsLinked to original sources

bioRxiv2019

Evolutionary constraints in regulatory networks defined by partial order between phenotypes

Gene regulation networks allow organisms to adapt to diverse environmental niches. However, the constraints underlying the evolution of regulatory phenotypes remain ill-defined both theoretically and experimentally. Here, we show that the concept of partial order identifies such constraints, and test the predictions by experimentally evolving an engineered signal-integrating network in multiple environments. We find that populations: 1) expand in fitness space along the Pareto-optimal front predicted by conflicts in regulatory demands, by fine-tuning binding affinities within the network, 2) expand beyond this constraint by changes in the network structure, thus allowing access to new fitness domains. Strikingly, the constraint predictions are based on whether the network output increases or decreases in response to the different signals, and do not require information on the network architecture or underlying genetics. Overall, our findings show that limited knowledge on current regulatory phenotypes can provide predictions on future evolutionary constraints.

evolutionary biology↗

bioRxiv2019

Protein structure from experimental evolution

Natural evolution encodes rich information about the structure and function of biomolecules in the genetic record. Previously, statistical analysis of co-variation patterns in natural protein families has enabled the accurate computation of 3D structures. Here, we explored whether similar information can be generated by laboratory evolution, starting from a single gene and performing multiple cycles of mutagenesis and functional selection. We evolved two bacterial antibiotic resistance proteins, {beta}-lactamase PSE1 and acetyltransferase AAC6, and obtained hundreds of thousands of diverse functional sequences. Using evolutionary coupling analysis, we inferred residue interactions in good agreement with contacts in the crystal structures, confirming genetic encoding of structural constraints in the selected sequences. Computational protein folding with contact constraints yielded 3D structures with the same fold as that of natural relatives. Evolution experiments combined with inference of residue interactions from sequence information opens the door to a new experimental method for the determination of protein structures.

evolutionary biology↗

bioRxiv2018

3D protein structure from genetic epistasis experiments

High-throughput experimental techniques have made possible the systematic sampling of the single mutation landscape for many proteins, defined as the change in protein fitness as the result of point mutation sequence changes. In a more limited number of cases, and for small proteins only, we also have nearly full coverage of all possible double mutants. By comparing the phenotypic effect of two simultaneous mutations with that of the individual amino acid changes, we can evaluate epistatic effects that reflect non-additive cooperative processes. The observation that epistatic residue pairs often are in contact in the 3D structure led to the hypothesis that a systematic epistatic screen contains sufficient information to identify the 3D fold of a protein. To test this hypothesis, we examined experimental double mutants for evidence of epistasis and identified residue contacts at 86% accuracy, including secondary structure elements and evidence for an alternative all--helical conformation. Positively epistatic contacts - corresponding to compensatory mutations, restoring fitness - were the most informative. Folded models generated from top-ranked epistatic pairs, when compared with the known structure, were accurate within 2.4 [A] over 53 residues, indicating the possibility that 3D protein folds can be determined experimentally with good accuracy from functional assays of mutant libraries, at least for small proteins. These results suggest a new experimental approach for determining protein structure.

systems biology↗

bioRxiv2017

Learning the pattern of epistasis linking genotype and phenotype in a protein

Understanding the pattern of epistasis - the non-independence of mutations - is critical for relating genotype and phenotype in biological systems. However, the complexity of potential epistatic interactions has limited approaches to this problem at any level. To develop practical strategies, we carried out a comprehensive experimental study of epistasis between all mutations that link two phenotypically distinct variants of the Entacmaea quadricolor fluorescent protein. The data demonstrate significant high-order epistatic interactions between mutations, but also reveals extraordinary sparsity, enabling novel experimental strategies and sequence-based statistical methods for learning the relevant epistasis. The sequence space linking the parental fluorescent proteins is functionally connected through paths of single mutations; thus, high-order epistasis in proteins is consistent with evolution through stepwise variation and selection. This work initiates a path towards characterizing epistasis in proteins in general.

systems biology↗