Receptor dimerization enables ligand discrimination through tunable response heterogeneity

Abstract

Signaling pathways enable cells to coordinate collective behaviors by exchanging specific information. Many pathways utilize multiple ligand variants to activate the same intracellular signaling cascade, raising the question of how cells discriminate between these seemingly redundant signals. It has been shown that individual cells can discriminate between signals based on their induced level of activity, temporal dynamics or combinatorial effect. Here, we demonstrate that ligand discrimination could also emerge at the population level. Using mathematical models of ligand-receptor interactions, we examine how response heterogeneity at the population level can encode ligand identity. We introduce a local scaling metric to quantify how variation in pathway components affects the cellular response. Our results reveal that for pathways with dimeric receptors, and more significantly for heterodimeric receptors, biochemical parameters of the ligands control the resulting heterogeneity in the response of a population of cells. Furthermore, we show that the population-level heterogeneity encodes the enzymatic activity of the resulting receptor complex. This suggests a functional advantage for utilizing heterodimeric receptor complexes in pathways acting across a population of cells, such as the type I interferon pathway, which shows several of the characteristics of our model. This contrasts to juxtacrine pathways, such as Notch, that do not act at the population level and use a single component receptor. Overall, our findings highlight a novel mechanism by which receptor architecture enables cells to encode ligand-specific information through population-level heterogeneity, offering insights into immune regulation, tissue development, and synthetic biology. Significance StatementCells often communicate using distinct molecular signals (ligands) that activate the same pathway. Yet, how cells distinguish between these signals remains unclear. This study reveals that ligand discrimination can emerge at the level of entire cell populations, not just individual cells. By analyzing mathematical models, we show that certain receptor architectures, especially those involving heterodimeric receptors, allow signals to control the heterogeneity of the response level across a population. This mechanism enables cell populations to decode specific information about their environment, impacting processes like immune responses and tissue development. Our findings provide new insights into how signals coordinate collective behaviors and suggest strategies for designing synthetic systems to precisely control biological responses.