Quantitative modelling explains distinct STAT1 and STAT3 activation dynamics in response to both IFNγ and IL-10 stimuli and predicts emergence of reciprocal signalling at the level of single cells

Abstract Cells use IFNγ-STAT1 and IL-10-STAT3 pathways primarily to elicit pro and anti-inflammatory responses, respectively. However, activation of STAT1 in IL-10 and STAT3 in IFNγ stimulation is also observed. The regulatory processes controlling the amplitude and dynamics of both the STATs in response to the these functionally opposing stimuli remains less understood. Here, we built a model comprising both the pathways and calibrated the model to STAT1 and STAT3(S/1/3) activation dynamics at different doses of both IFNγ and IL-10 stimulus. The model quantitatively captured the dose-dependent dynamics of STAT1 and STAT3(S/1/3) in response both IFNγ and IL-10 stimulations. Since S/1/3 are activated by both the pathways we next predicted a co-stimulation scenario (IL-10 and IFNγ applied simultaneously); in co-stimulation, the model predicts that IL-10 pathway would inhibit IFNγ pathway through strong induction of SOCS1(a negative regulator of IFNγ signalling), which ensured STAT3 activation to remain IL-10 driven. Our experiments subsequently validated the prediction. Next, to understand how protein expression heterogeneity would affect the robustness of STAT3 dynamics in co-stimulation we performed single cell simulations. The simulations show the emergence of two reciprocally responding subpopulations wherein co-stimulation enhances STAT3 and inhibit STAT1 phosphorylation in one subpopulation, and vice versa is observed in the other subpopulation. Analyzing the distribution of protein concentrations in individual cells we identified key proteins whose relative concentration regulates the S/1/3 responses in the subpopulations. Finally, through targeted perturbation of individual cellular states, we could tune S/1/3 responses in desired ways. Taken together, our data-driven modelling at the population level and single cell simulations uncover plausible mechanisms controlling STATs amplitude and dynamics while responding to functionally opposing cues. Therapeutic potential of this study may be explored further.