(264d) Minimal Reaction Network for Oscillations in the MAPK Signalling Cascade | AIChE

(264d) Minimal Reaction Network for Oscillations in the MAPK Signalling Cascade

Authors 

Schreiber, I. - Presenter, University of Chemistry and Technology, Prague
Hadac, O., Institute of Chemical Technology, Prague
Pribyl, M., University of Chemistry and Technology

Mitogen Activated Protein Kinases (MAPKs)  belong to serine/threonine-specific protein kinases that respond to extracellular stimuli and modulate cellular activities. The MAPK cascade is one of the most studied signalling biochemical pathways in the eucaryotic cell where proteins transmit a signal from a receptor on the surface of the cell to the DNA in the nucleus of the cell. This biochemical network involves many proteins, including MAPK, which communicate by adding phosphate groups to a neighbouring protein, which in turn acts as an on or off switch. The cascade starts at the MAPK kinase kinase (MAPKKK) that activates the MAPK kinase (MAPKK) by double-phosphorylation at two serine residues, which in turn activates the MAPK by double-phosphorylation at threonine and tyrosine residues.

            Following our earlier analysis of a minimal model for bistability in the MAPK signalling, we use the stoichiometric network analysis (SNA) to decompose a system involving activation of the MAPKKK, the first double-phosphorylation cascade and simultaneously occurring dephosphorylation into irreducible/extreme subnetworks.  We then identify dynamic stability of the subnetworks that are potentially sources of instability leading to oscillations. By using the classification system for chemical oscillators we further reduce the MAPK reaction network into the smallest network which still preserves oscillations. This network differs from the minimal bistability network mainly by including dynamical activation/deactivation of the MAPKKK. Owing to its simplicity, the system can be to certain extent examined analytically using  either directly kinetic parameters (i.e., rate coefficients) or using the convex parametrization introduced via the SNA to determine conditions for a Hopf bifurcation. In addition, we analyze the model by using numerical continuation and determine the role of major subnetworks in forming the oscillatory system.

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