Mapping Differentiation under Mixed Culture Conditions Reveals a Tunable Continuum of T Cell Fates

Cell differentiation is typically directed by external signals that drive opposing regulatory pathways. Studying differentiation under polarizing conditions, with only one input signal provided, is limited in its ability to resolve the logic of interactions between opposing pathways. Dissection of this logic can be facilitated by mapping the system's response to mixtures of input signals, which are expected to occur in vivo, where cells are simultaneously exposed to various signals with potentially opposing effects. Here, we systematically map the response of naïve T cells to mixtures of signals driving differentiation into the Th1 and Th2 lineages. We characterize cell state at the single cell level by measuring levels of the two lineage-specific transcription factors (T-bet and GATA3) and two lineage characteristic cytokines (IFN-γ and IL-4) that are driven by these transcription regulators. We find a continuum of mixed phenotypes in which individual cells co-express the two lineage-specific master regulators at levels that gradually depend on levels of the two input signals. Using mathematical modeling we show that such tunable mixed phenotype arises if autoregulatory positive feedback loops in the gene network regulating this process are gradual and dominant over cross-pathway inhibition. We also find that expression of the lineage-specific cytokines follows two independent stochastic processes that are biased by expression levels of the master regulators. Thus, cytokine expression is highly heterogeneous under mixed conditions, with subpopulations of cells expressing only IFN-γ, only IL-4, both cytokines, or neither. The fraction of cells in each of these subpopulations changes gradually with input conditions, reproducing the continuous internal state at the cell population level. These results suggest a differentiation scheme in which cells reflect uncertainty through a continuously tuneable mixed phenotype combined with a biased stochastic decision rather than a binary phenotype with a deterministic decision

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

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.</jats:p

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

Abstract 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. Disclosures: No relevant conflicts of interest to declare. </jats:sec

Effects of intracellular communication between T helper cells on Th2 differantiation

Cytokines provide a main regulatory mechanism of immune responses, which allows for intercellular communication and enables cells to make collective decisions. Existing evidence for stochastiticity in expression of cytokines and their receptors raises the question: how does cytokine communication performs reliably in the face of noise? We study the effect of heterogeneity in IL4R expression level during Th2 differentiation as a model system. Naïve CD4 T cells were separated into different groups according to their IL4R expression levels and the different groups were cultured separately, under different IL4 concentrations driving their differentiation. Expression levels of Th2 markers, IL4 and GATA3, were measured at the single cell level. Our results reveal differences in the differentiation abilities of the different groups - higher initial receptor levels facilitate faster Th2 differentiation, at lower levels of IL4 as an input. Interestingly, we found that these differences in the differentiation abilities vanish when cells with high and low initial IL4R levels are co-cultured. These results suggest that intercellular interactions can decrease the potential heterogeneity in the population that results from noise in gene expression. These experiments provide an opportunity to evaluate the importance and roles played by intercellular communication in Th cell differentiation, and to assess the effects of stochasticity in protein levels on the differentiation process

Effects of intracellular communication between T helper cells on Th2 differantiation (P1149)

Abstract Cytokines provide a main regulatory mechanism of immune responses, which allows for intercellular communication and enables cells to make collective decisions. Existing evidence for stochastiticity in expression of cytokines and their receptors raises the question: how does cytokine communication performs reliably in the face of noise? We study the effect of heterogeneity in IL4R expression level during Th2 differentiation as a model system. Naïve CD4 T cells were separated into different groups according to their IL4R expression levels and the different groups were cultured separately, under different IL4 concentrations driving their differentiation. Expression levels of Th2 markers, IL4 and GATA3, were measured at the single cell level. Our results reveal differences in the differentiation abilities of the different groups - higher initial receptor levels facilitate faster Th2 differentiation, at lower levels of IL4 as an input. Interestingly, we found that these differences in the differentiation abilities vanish when cells with high and low initial IL4R levels are co-cultured. These results suggest that intercellular interactions can decrease the potential heterogeneity in the population that results from noise in gene expression. These experiments provide an opportunity to evaluate the importance and roles played by intercellular communication in Th cell differentiation, and to assess the effects of stochasticity in protein levels on the differentiation process.</jats:p

Diverse continuum of CD4 ⁺ T-cell states is determined by hierarchical additive integration of cytokine signals

Significance Understanding the logic by which cells respond to complex signal combinations is challenging. We used CD4 + T cells as a model system to study signal integration by systematically mapping their differentiation in response to a large number of cytokine combinations. We find that, in response to varied cytokine mixtures, cells coexpress lineage-specifying proteins at diverse levels, such that the cell population spans a continuum of intermediate states between canonical cell phenotypes. Mathematical modeling explains these results using hierarchical summation of cytokine inputs and correctly predicts population response to new input conditions. These findings suggest that complex cellular responses can be effectively described using relatively simple hierarchical summation rules, providing a framework for prediction of cellular responses to signal combinations. </jats:p