Leibniz MMS Days 2020 - Abstract
CD4 T cell differentiation is a key element of the adaptive immune system driving appropriate immune responses by selective differentiation into highly specialized effector subsets such as Th1, Th2 and Tfh-like cells. The decision to differentiate into specific Th cell subtypes is mediated by a complex network of interacting immune cells through the release and uptake of cytokines. Here, employing response-time modeling (Thurley et al. 2018, Cell Systems 6:355), we developed and analyzed data-driven models of T cell differentiation and proliferation. Using our framework, we tested cell-decision scenarios as well as homeostatic control mechanisms such as autocrine cytokine secretion and density-independent timing of cell quiescence. We envision using response-time modeling to derive large-scale data-driven models of cell-cell communication circuits in autoimmune diseases, to elucidate decision-making processes and to derive testable predictions regarding therapeutic opportunities.