Mapping CD4+ T cell differentiation decision space: Flexibility and heterogeneity under mixed input conditions (P1181)

Abstract

Abstract T helper cell differentiation is influenced by the spectrum of cytokines in the cells' milieu. In-vivo, cells are expected to sense a complex cytokine environment. Therefore, we aimed to study differentiation under mixed input conditions. By exposing cells to varied combinations of cytokines, we mapped the "decision space" of the differentiation process. Naïve CD4+ T cells were exposed to all 64 binary combinations of 6 cytokines, which induce the differentiation of the main T helper subsets: Th1, Th2, Th17 and iTreg. We examined the differentiation outcome in terms of cytokine-production pattern and expression of lineage-specifying transcription factors, by multi-color flow cytometry. Our data indicate that mixed conditions result in mixed phenotypes with cells expressing markers of opposing subsets simultaneously. Clustering and principal component analysis revealed up to eight different Th subsets, some of which are in accordance with known states. We also identified a hierarchical organization of input signals in their influence on driving differentiation into those subsets. Our results demonstrate flexibility and heterogeneity in Th cell differentiation. Under uncertain conditions, rather than following a hard, binary decision, cells reflect uncertainty through a biased stochastic decision process. This strategy allows flexibility and plasticity of the response at the single-cell level, while maintaining an average, possibly optimized response at the population level.