A Hybrid Petri Net Model of the Akt-Wnt-mTOR-p70S6K Signalling Network in Neurons

Abstract

Signalling networks in the mammalian cell are complex systems. Their dynamic properties can often be explained by the interaction of regulatory network motifs. Computational modelling is instrumental in explaining how these systems function. To accomplish this task in this paper, we combine hybrid Petri net modelling and simulation, which produce the individual trajectories of protein concentrations and enable structural analysis of the reaction network. In the end, we generate dynamic graphs to get a system view of the signalling network dynamics. We use this methodology on the regulatory network of the proteins mTOR and p70S6K. In neuronal synaptic plasticity, prolonged activation of these proteins is needed to support an increased protein synthesis. However, biologists wonder how two brief calcium influxes of 1 second each can lead to this long activation downstream. With our computational approach and a new model of the Akt-Wnt-mTOR-p70S6K network, we explore the current biological hypothesis for the response of mTOR: the crosstalk between the Akt and Wnt pathways. Simulation results indicate instead that a feedforward motif between Akt, GSK3 and TSC2 acts as a coincidence detector. From the simulation results, we can also make two predictions that can be tested experimentally and indicate where a molecular regulatory mechanism seems to be missing to completely explain the activity in the signalling network.