(497c) Minimal Reaction Network for Bistability in the MAPK Signalling Cascade

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. Although the biological responses associated with MAPK signalling are highly varied, the basic structure of the MAPK cascade is well conserved. The cascade always consists of a MAPK kinase kinase (MAPKKK), a MAPK kinase (MAPKK), and a MAPK. MAPKKKs activate MAPKKs by phosphorylation at two conserved serine residues and MAPKKs activate MAPKs by phosphorylation at conserved threonine and tyrosine residues. These signalling pathways are characterized by high levels of structural and parametric uncertainty.

            We used the stoichiometric networks analysis (SNA) to decompose a system involving activation of MAPKKK and first of the two double-phosphorylation cascades (which we call single-phosphorylation cascade model) into irreducible or elementary subnetworks (ESs).  Then we identified those ESs that are potentially sources of nontrivial dynamical instabilities leading to bistability or oscillations. By using the classification system for chemical oscillators we further simplified the topology of the MAPK reaction network into the smallest network which still preserves bistability but does not allow for oscillations. This network can be examined analytically using both convex parametrization employed by the SNA and classical kinetic parameters (i.e., rate coefficients) to determine multiple steady states and their stability. Next we analyze the single-phosphorylation cascade model by using numerical continuation and determine what is the role of various subnetworks in forming the bistability.