Summary G protein-coupled receptor (GPCR) signaling is the primary method eukaryotes use to respond to specific cues in their environment. However, the relationship between stimulus and response for each GPCR is difficult to predict due to diversity in natural signal transduction architecture and expression. Using genome engineering in yeast, we constructed an insulated, modular GPCR signal transduction system to study how the response to stimuli can be predictably tuned using synthetic tools. We delineated the contributions of a minimal set of key components via computational and experimental refactoring, identifying simple design principles for rationally tuning the dose response. Using five different GPCRs, we demonstrate how this enables cells and consortia to be engineered to respond to desired concentrations of peptides, metabolites, and hormones relevant to human health. This work enables rational tuning of cell sensing while providing a framework to guide reprogramming of GPCR-based signaling in other systems.
G protein-coupled receptor (GPCR) signaling is the primary method eukaryotes use to respond to specific cues in their environment. However, the relationship between stimulus and response for each GPCR is difficult to predict due to diversity in natural signal transduction architecture and expression.Using genome engineering in yeast, we here constructed an insulated, modular GPCR signal transduction system to study how the response to stimuli can be predictably tuned using synthetic tools. We delineated the contributions of a minimal set of key components via computational and experimental refactoring, identifying simple design principles for rationally tuning the dose-response.Using four different receptors, we demonstrate how this enables cells and consortia to be engineered to respond to desired concentrations of peptides, metabolites and hormones relevant to human health. This work enables rational tuning of cell sensing, while providing a framework to guide reprogramming of GPCR-based signaling in more complex systems.
HighlightsA new ordinary differential equation model for biased agonism dynamics at a G protein-coupled receptor (GPCR) is presented.The model is general in the number of G proteins and active receptor.Numerical simulations reveal new phenomena in active G protein dynamics, including inter-conversion of the observed ligand effect (agonist to inverse agonist).The model recapitulates new experimental data for cells and ligands which are believed to exhibit biased agonism.
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