Petri net model of coupled IL-6 and IL-22 pathways supports the understanding of pharmacological effects of cytokine variants

The pleiotropic cytokines interleukin 6 (IL-6) and interleukin 22 (IL-22) are involved in multiplesignaling pathways in a variety of cells. In hepatocytes, they activate the acute phase response byphosphorylating and activating STAT3 homodimers. Other functions, which involve both STAT1and STAT3 homodimers as well as heterodimers, include 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. Continuous overexpression of these cytokines can prove detrimental to the liver and lead to the formation of tumors. Consequently, these pathways are tightly controlled by regulatory proteins such as SOCS. Despite their importance to liver function in health and disease, the signaling pathways activated by IL-6 and IL-22 have still not been fully described. Cross-talk between both cytokines is similarly enigmatic.We have built a Petri net model of the IL-6 and IL-22 pathways to improve our understandingof cytokine regulation and to produce testable predictions regarding the dynamics of the interactionsbetween the variety of involved agonists and antagonists. The model includes cytokine binding totheir respective receptors. Following receptor binding, the JAK/STAT pathways can be activated,leading to RNA transcription. This process is regulated in our model by various inhibitors and,through negative feedback, SOCS binding to the receptor complexes.We analyzed the model for invariants to control for and eliminate errors and find any relevantsub-pathways in 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 vivoexperiments from the scientific literature. We undertook further analysis using clustering algorithmsto validate the model and find similarities between sub-pathways. We used our model to performasynchronous simulations, which led us to the hypothesis that the higher levels of IL-6 in comparisonto 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, which may help in the discovery of interleukin-related therapeutics.