B1_JAK1/STAT3 Signaling

Project Summary:

During the initial phase of hepatocyte regeneration hepatocytes are primed to reenter cell proliferation. The coordinated activation and deactivation of the JAK1-STAT3 and the NFκB signaling cascades in hepatocytes mediates the transition from the priming towards the proliferative state. For the JAK1-STAT3 signaling cascade we have established a data-based mathematical model that revealed rapid nuclearcytoplasmic cycling of STAT3 in primary hepatocytes and thereby confirmed the “remote-sensor” behavior as a general systems property of the JAK-STAT signaling cascade (Swameye et al., PNAS; Klingmüller et al. IEE Systems Biology). To access key mechanisms regulating priming of hepatocytes and subsequent induction of proliferation, we will extend our model to capture in addition modulatory effects of the co-activation of the TNFα stimulated NFκB signaling cascade and the role of STAT3 serine phosphorylation. Possible modes for cross-talk are the induction of autocrine loops such as the successive induction of cytokines or the modulation of phoshporylation of pathway components. Since we observed for the IL-6 receptor that the receptor/signaling pathway interphase critically determines the dynamic behavior of STAT3 activation, we will examine the activation of STAT3 in response to signal transduction through the epidermal growth factor receptor (EGF-R), which plays an important role in the proliferative phase of hepatocyte regeneration. By comparative modeling we will analyze differences and similarities in pathway activation mediated by cytokine receptors such as the IL-6 receptor and receptor tyrosine kinases such as the EGF-R. Furthermore, to incorporate spatial effects we will make use of the Tet-inducible systems developed in Project B5 to express fluorescently labeled STAT3 and compare the kinetic parameters of nuclearcytoplasmic cycling in response to stimulation with IL-6, co-stimulation with IL-6 and TNFα, or EGF. Finally, we will link the time-course of STAT3 activation to the selective activation of target genes and establish a comprehensive model of STAT3 activation to quantitatively predict the outcome of signaling.