Computational analysis of IL-6/IL-22 signaling in liver disease

The cytokines interleukin 6 (IL-6) and interleukin 22 (IL-22) are involved in multiple signaling pathways in a variety of cells, e.g. the activation of the acute-phase response, cell homeostasis and tissue repair. However, high concentrations of IL-6 and IL-22 are associated with worse outcomes for patients with liver pathologies such as cirrhosis and chronic liver failure. Consequently, these pathways are tightly controlled by regulatory proteins. Despite their importance to liver function, the signaling pathways activated by IL-6 and IL-22 have still not been fully understood. We have built a Petri net model of the IL-6 and IL-22 pathways to improve our understanding of cytokine regulation. The model includes cytokines binding to their respective receptors. Following receptor binding, the JAK/STAT pathways can be activated, leading to RNA transcription. This process is regulated by various inhibitors. We analyzed the model for invariants to control for correctness and completeness of the model. We applied in silico knockout experiments to explore how critical different proteins appear for the functioning of the pathways and compared them to previous in vivo experiments from the scientific literature. We used our model to perform asynchronous simulations, which led us to the hypothesis that the higher levels of IL-6 in comparison to IL-22 in some pathologies may compensate for the slower assembly of the IL-6 receptor complex due to its higher structural complexity. We performed stochastic simulations of partial cytokine agonists confirming prior experimental results showing biased phosphorylation of STAT1/3 for lower cytokine receptor-binding dwell times.