Cell-fate decisions are driven by complex regulatory networks. Despite their complexity, these networks often exhibit low-dimensional dynamics and allow only a limited number of phenotypes. What design principles in network topology allows for these salient features remains unclear. Previously, we demonstrated that networks driving epithelial-mesenchymal transition (EMT) were comprised of two well-coordinated teams of nodes engaged in mutual antagonism; one team drove an epithelial phentoype, while the one reinforced a mesenchymal one, thus canalizing cell-fate decisions. However, it remains elusive whether teams can drive low-dimensional dynamics of such networks. Here, we investigate networks acrosss diverse biological scenarios (EMT, small cell lung cancer, pluripotency, gonadal cell-fate) and show that they all comprise of two teams of nodes which can be identified without simulations, and drive two mutually exclusive phenotypes. Moreover, a stronger team strength associates with low dimensionality in the emergent phenotypic space. Our analysis elucidates how the presence of teams may be a fundamental design principle in networks driving cellular decision-making.

Understanding the dynamical hallmarks of network motifs is one of the fundamental aspects of systems biology. Positive feedback loops constituting one or two nodes, self-activation, toggle switch, and double activation loops, are commonly observed motifs in regulatory networks underlying cell-fate decision systems. Their individual dynamics are well-studied; they are capable of exhibiting bistability. However, studies across various biological systems suggest that such positive feedback loops are interconnected with one another, and design principles of coupled bistable motifs remain unclear. We wanted to ask what happens to bistability or multistability traits and the phenotypic space (collection of phenotypes exhibited by a system) due to the couplings. In this study, we explore a set of such interactions using discrete and continuous simulation methods. Our results suggest that couplings that do not connect the bistable switches in a way that contradicts the connections within individual bistable switches lead to a steady state space that is strictly a subset of the set of possible combinations of steady states of bistable switches. Furthermore, adding direct and indirect self-activations to these coupled networks can increase the frequency of multistability. Thus, our observations reveal specific dynamical traits exhibited by various coupled bistable motifs.

Elucidating the design principles of regulatory networks driving cellular decision-making has important implications for understanding cell differentiation and guiding the design of synthetic circuits. Mutually repressing feedback loops between ‘master regulators’ of cell fates can exhibit multistable dynamics enabling “single-positive” phenotypes: (high A, low B) and (low A, high B) for a toggle switch, and (high A, low B, low C), (low A, high B, low C) and (low A, low B, high C) for a toggle triad. However, the dynamics of these two motifs have been interrogated in isolation in silico, but in vitro and in vivo, they often operate while embedded in larger regulatory networks. Here, we embed these motifs in complex larger networks of varying sizes and connectivity to identify hallmarks under which these motifs maintain their canonical dynamical behavior. We show that an increased number of incoming edges onto a motif leads to a decay in their canonical stand-alone behaviors. We also show that this decay can be exacerbated by adding self-inhibition but not self-activation loops on the ‘master regulators’. These observations offer insights into the design principles of biological networks containing these motifs and can help devise optimal strategies for the integration of these motifs into larger synthetic networks.

Understanding the dynamical hallmarks of network motifs is one of the fundamental aspects of systems biology. Positive feedback loops constituting one or two nodes -self-activation, toggle switch, and double activation loops -are the commonly observed motifs in regulatory networks underlying cell-fate decision systems. Their individual dynamics are well studied; they are capable of exhibiting bistability. However, studies across various biological systems suggest that such positive feedback loops are interconnected with one another, and design principles of coupled bistable motifs remain unclear. What happens to the bistability or multistability traits and the phenotypic space (collection of phenotypes exhibited by a system) due to the couplings? In this study, we explore a set of such interactions using discrete and continuous simulation methods. Our results suggest that the most frequent states in coupled networks follow the 'rules' within a motif (double activation, toggle switch) and those across the two motifs in terms of how the two motifs have been coupled. Moreover, 'hybrid' states can be observed, too, where one of the above-mentioned 'rules' can be compromised, leading to a more diverse phenotypic repertoire. Furthermore, adding direct and indirect selfactivations to these coupled networks can increase the frequency of multistability. Thus, our observations revealed specific dynamical traits exhibited by various coupled bistable motifs.