Logical models reveal the complex immune cell phenomena produced by the MISA gene regulatory motif

The immune system is simultaneously life-saving and dangerous. Dysregulation leads to life-threatening conditions such as sepsis and severe cases of Covid-19. Successful responses protect the body from viruses, pathogens, and cellular damage. Regulation of immune responses is accomplished through the decentralized interactions of dynamically shifting cellular populations and chemical signals. Central to this process is the differentiation of progenitor cells into effector cells and the appropriate production of chemical signals called cytokines. Understanding how this regulation is accomplished requires a systems-level understanding of the cellular and molecular mechanisms that integrate stimuli into gene expression decisions. Boolean and Fuzzy-Logic modeling have been instrumental in establishing the MISA (mutually-inhibitory, self-activating) gene-regulatory motif as a fundamental component of immune cell differentiation responses. Here we describe the work of a number of mathematical biologists, reframing the regulatory networks they study, to emphasize the array of biological phenomena that can be produced when the MISA motif is embedded in complex gene regulatory networks. These phenomena include: hierarchical differentiation, dose-dependent decisions, differentiation memory, and the production of heterogeneous cell populations from uniform signaling environments. The perspective provided by this work allows for the formation of new hypotheses about the network structures underlying newly discovered biological phenomena.