Speaker
Description
Cell fate decisions are driven by gene regulatory networks (GRNs). While the mutually inhibitory toggle switch effectively models binary fate decisions, fully connected inhibitory networks with more than two nodes fail to capture multi-fate decisions due to the low prevalence of "single-high states", where only a single master regulator is highly expressed. In this study, we use monotone Boolean models to derive structural constraints necessary for an n-node network to support n phenotypes. We find that the only network that maximizes the prevalence of single-high states is completely disconnected. However, since biological networks typically require connectivity, we further investigate the requirements for equipotency, where a network structure supports all single-high states with equal prevalence. Finally, we characterize the requirements for multistability across all single-high states, finding that it is possible only in networks in which each node either has self-activations or inhibitions with every other node. Our findings provide a theoretical framework for understanding the topological design principles required for master regulator networks to support simultaneous differentiation into multiple distinct cell types.
