Receptor dimerization enables ligand discrimination through tunable response heterogeneity

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.Author summary: Cells constantly exchange messages to coordinate their behavior, during both development and in maintaining health. Many of these messages, proteins called ligands, use the same cellular machinery but nevertheless lead to very different outcomes. Most research has focused on how single cells can distinguish these messages. In this study, we asked a different question: can ligand identity be encoded in how varied the responses are across an entire population of cells? Controlling population variability can strongly influence the collective behavior of a tissue. Using mathematical models of receptor–ligand interactions, we found that the architecture of the receptor complex itself plays a key role. Simple one-part receptors respond proportionally to the different ligands, so population variability cannot be tuned by the signal. In contrast, receptors built from two parts, especially when the parts differ as in pathways like type I interferon or TGF-β/BMP, allow ligand identity and relative amount to shape the spread of responses across cells without changing the average level. This population-level “fingerprint” could influence immune defense, tissue development, or drug responses, and suggests new ways to design therapies or synthetic systems that harness variability rather than simply suppressing it.