Cell-to-Cell Variability Analysis Dissects the Plasticity of Signaling of Common γ Chain Cytokines in T Cells

Natural variability in the abundance of signaling regulators can lead to divergence in cell fate, even within genetically identical cells that share a common differentiation state. We introduce cell-to-cell variability analysis (CCVA), an experimental and computational methodology that quantifies the correlation between variability in signaling regulator abundance and variation in the sensitivity of cells to stimuli. With CCVA, we investigated the unexpected effects of the interleukin 2 (IL-2) receptor a chain (IL-2R alpha) on the sensitivity of primary mouse T lymphocytes to cytokines that signal through receptors that have the common gamma chain (gamma(c)). Our work showed that increased IL-2R alpha abundance decreased the concentration of IL-2 required for a half-maximal activation (EC50) of the downstream effector signal transducer and activator of transcription 5 (STAT5), but reduced the responsiveness to IL-7 or IL-15, without affecting the EC50 values of other gamma(c) cytokines. To investigate the mechanism of the effect of IL-2R alpha on gamma(c) cytokine signaling, we introduced a Bayesian-inference computational framework that models the formation of receptor signaling complexes with data from previous biophysical measurements. With this framework, we found that a model in which IL-2R alpha drives gamma(c) depletion through the assembly of functional IL-2R complexes was consistent with both the CCVA data and experimental measurements. The combination of CCVA and computational modeling produced quantitative understanding of the crosstalk between gamma(c) cytokine receptor signaling in T lymphocytes.