Signaling pathways are characterized by crosstalk, feedback and feedforward mechanisms giving rise to highly complex and cell-context specific signaling networks. Dissecting the underlying relations is crucial to predict the impact of targeted perturbations. However, a major challenge in identifying cell-context specific signaling networks is the enormous number of potentially possible interactions. Here, we report a novel hybrid mathematical modeling strategy to systematically unravel hepatocyte growth factor (HGF) stimulated phosphoinositide-3-kinase (PI3K) and mitogen activated protein kinase (MAPK) signaling, which critically contribute to liver regeneration. By combining time-resolved quantitative experimental data generated in primary mouse hepatocytes with interaction graph and ordinary differential equation modeling, we identify and experimentally validate a network structure that represents the experimental data best and indicates specific crosstalk mechanisms. Whereas the identified network is robust against single perturbations, combinatorial inhibition strategies are predicted that result in strong reduction of Akt and ERK activation. Thus, by capitalizing on the advantages of the two modeling approaches, we reduce the high combinatorial complexity and identify cell-context specific signaling networks.

ERK is a member of the MAPK pathway with essential functions in cell proliferation, differentiation, and survival. Complete ERK activation by the kinase MEK requires dual phosphorylation at T and Y within the activation motif TEY. We show that exposure of primary mouse hepatocytes to hepatocyte growth factor (HGF) results in phosphorylation at the activation motif, but not of other residues nearby. To determine the relative abundances of unphosphorylated ERK and the three ERK phospho-forms pT, pY, and pTpY, we employed an extended one-source peptide/phosphopeptide standard method in combination with nanoUPLC-MS. This method enabled us to determine the abundances of phospho-forms with a relative variability of ≤5% (SD). We observed a switch-like preference of ERK phospho-form abundances toward the active, doubly phosphorylated and the inactive, unphosphorylated form. Interestingly, ERK phospho-form profiles were similar upon growth factor and cytokine stimulation. A screening of several murine and human cell systems revealed that the balance between TY- and pTpY-ERK is conserved while the abundances of pT- and pY-ERK are more variable within cell types. We show that the phospho-form profiles do not change by blocking MEK activity suggesting that cellular phosphatases determine the ERK phospho-form distribution. This study provides novel quantitative insights into multisite phosphorylation.