Protecting P-type plasma membrane H+-ATPases from ROS.

P-type ATPase are ubiquitous transport proteins across all kingdoms of life. These proteins share a common mechanism involving phosphorylation of an invariant aspartate to facilitate movement of substrates from protons to phospholipids across cellular membranes. In this issue of the Biochemical Journal, Welle et al. identify a conserved cysteine near the functionally critical aspartate of P-type plasma membrane H+-ATPases that protects the protein from reactive oxygen species.

Model-guided mechanism discovery and parameter selection for directed evolution.

Directed evolution is frequently applied to identify genetic variants with improvements in a single or multiple properties. When used to improve multiple properties simultaneously, a common strategy is to apply alternating rounds of selection criteria to enrich for variants with each desirable trait. In particular, counterselection, or selection against undesired traits rather than for desired ones, has been successfully employed in many studies. Although the sequence and stringency of alternating selective pressures for different traits are known to be highly consequential for the outcome of the screen, the effects of these parameters have not been systematically evaluated. We developed a method for producing a statistical modeling framework to elucidate these effects. The model uses single-cell fluorescence intensity distributions to estimate the proportions of phenotypic populations within a library and then predicts the changes in these proportions depending on specified positive selective or counterselective pressures. We validated the approach using recently described systems for metabolite-responsive bacterial transcription factors and yeast G-protein-coupled receptors. Finally, we applied the model to identify biological sources that exert undesirable selective pressure on libraries during sorting. Notably, these pressures produce substantial artifacts that, if unaddressed, can lead to failure of the screen. This method for model generation can be applied to FACS-based directed evolution experiments to create a quantitative framework that identifies subtle population effects. Such models can guide the choice of experimental design parameters to better enrich for true positive genetic variants and improve the chance of successful directed evolution.

Modulating and evaluating receptor promiscuity through directed evolution and modeling.

The promiscuity of G-protein-coupled receptors (GPCRs) has broad implications in disease, pharmacology and biosensing. Promiscuity is a particularly crucial consideration for protein engineering, where the ability to modulate and model promiscuity is essential for developing desirable proteins. Here, we present methodologies for (i) modifying GPCR promiscuity using directed evolution and (ii) predicting receptor response and identifying important peptide features using quantitative structure-activity relationship models and grouping-exhaustive feature selection. We apply these methodologies to the yeast pheromone receptor Ste2 and its native ligand α-factor. Using directed evolution, we created Ste2 mutants with altered specificity toward a library of α-factor variants. We then used the  Vectors of Hydrophobic, Steric, and Electronic properties and partial least squares regression to characterize receptor-ligand interactions, identify important ligand positions and properties, and predict receptor response to novel ligands. Together, directed evolution and computational analysis enable the control and evaluation of GPCR promiscuity. These approaches should be broadly useful for the study and engineering of GPCRs and other protein-small molecule interactions.