Multistability in cellular differentiation enabled by three and four node mutually repressive regulatory networks: A case study of CD4+ T-cell decision making

Abstract

Cellular differentiation is controlled by the complex dynamics of gene regulatory networks (GRNs), often featuring multistability, where multiple stable states represent different phenotypes. A common example is the toggle switch, a two-node network where transcription factors mutually inhibit each other, leading to two exclusive states. However, progenitor cells can differentiate into more than two states, as seen in naïve CD4+ T-helper cells, which can become Th1, Th2, Th17, and other phenotypes.

We studied the dynamics of these differentiation processes by analysing a toggle triad involving three nodes (T-bet, GATA3, RORγt), which are key regulators of Th1, Th2 and Th17 respectively. Using both the deterministic and stochastic versions of RACIPE tool, we identified experimentally reported three prevalent ‘single-positive’ phenotypes – Th1, Th2 and Th17, three less frequent ‘double-positive’ (hybrid) phenotypes – Th1/2, Th2/17, and Th17/1, and observed noise-induced phenotypic switching among them.

We then considered the impact of epigenetic changes on state-switching among Th1, Th2, and Th17 cell populations. We incorporated epigenetic and transcriptional regulations into a single phenomenological model. Our model suggested that the strength and duration of epigenetic repression influence the plasticity of these cell types, thus potentially providing an explanation for the experimentally observed higher plasticity of Th17.

Expanding our model to include a fourth node (FOXP3) revealed the dynamics of differentiation into regulatory T cells (Treg) alongside Th1, Th2, and Th17 cells. The four-node network predominantly exhibited six double-positive states, corresponding to various hybrid T-cell phenotypes, confirmed by experimental observations. Stochastic simulations demonstrated phenotypic plasticity among these states.

These findings provide insights into the design principles for the mutually repressive network motifs and inferences about regulations present in the CD4+ T cell differentiation. This work explains how a common progenitor can differentiate into multiple phenotypes through stable intermediate states and highlights the role of network topology and epigenetic factors in cellular decision-making.