Effects of Intercellular Communication and Stochasticity in Gene Expression On TH1/TH2 Differentiation.

Abstract 2673

Poster Board II-649

Cytokines provide a main regulatory mechanism of a developing immune response, which allows for intercellular communication. This sharing of information enables cells to make collective decisions based on the state of the system rather than that of a single cell. In our research we focus on several examples of cytokine mediated regulatory mechanisms that function in helper T-cells (Th), whose role is to direct the immune response in the desired course by affecting responses of other cells. To analyze the relative importance of the different components affecting the behavior of the cells we employ mathematical modeling and numerical simulations of specific experimental settings. Quantitative experiments are performed to evaluate unknown parameters and to verify model predictions. We focus on two examples of cytokine mediated regulatory mechanisms that function in the helper T-cell (Th) differentiation. IL-12 and IL-4 direct differentiation into the main fates of Th cells, Th1 and Th2, respectively. By exposing cells to varied combinations of the two cytokines we experimentally map the “decision space” of the differentiation process. We measured, at the single cell level, eight key parameters relating to the state of the cells, from which we can deduce properties of the network describing the system. Our data indicate that under certain mixed conditions, with cells exposed to both IL-12 and IL-4, a new class of Th cells is observed, which secret both IL-4 and IFN-γ upon restimulation. This is preceded by co-expression of the two lineage specific transcription factors T-bet and GATA3 at earlier time points. We incorporate our experimental results and other known data into a cellular automata based simulation. Each cell is simulated as a node on a dynamic network, whose links describe the propagation of intercellular cytokine signals. The intracellular protein network for each node is realized as an automaton with cytokines levels as inputs and their secretion rates as output. By varying model parameters and comparing to experimental results we can gain insight into the significance of the various components driving the differentiation process. We also analyze the roles of heterogeneity in expression levels of cytokine receptors in the differentiation decision. To that end, naïve mice CD4 cells were sorted into separate groups according to their expression level of the IL-4 receptor. The different groups of cells were cultured separately, under “controlled milieu” conditions, at different IL-4 or IL-12 concentrations. Expression levels of key proteins involved in the differentiation process were measured at the single cell level every 24h. This was compared to expression levels of those proteins in a whole population of cells growing together. Our results reveal differences in the differentiation abilities between the sorted, controlled milieu, groups. Additionally, the weighted average of expression levels of the controlled milieu populations is different than that of the full heterogeneous population of cells growing together. These differences are caused by intercellular interactions, as cells secrete cytokines which are involved in and drive the differentiation process (e.g. IL-4, IFN-γ). Thus, these experiments provide an opportunity to evaluate the importance and roles played by intercellular communication in this process, and to asses what are the effects of stochastic levels of a protein (IL-4R in this case) on the following differentiation process.