Mathematical modelling of metabolic pathways #

Bandar Muidh Alharbi, Jonathan Wattis, Christopher Fallaize, Tim Parr, John Brameld.

11:10 Monday in 3Q68.

Part of the Cell modelling session.

Abstract #

We discuss an ongoing project developing mathematical models to predict and simulate the behaviour of metabolic pathways, particularly those taking place in the cytosol (glycolysis) and mitochondria (TCA cycle) within the muscle cell, which may give insight into predictions about accelerating muscle growth to increase protein mass and decrease fat in animals. Our present aim is to model the effects of mutations in two genes that encode enzymes which accelerate protein production and investigate their effects on the dynamics of the TCA cycle and serine production.

We investigate a deterministic model of the metabolic network that captures the behaviour of 13 metabolites in a muscle cell as a tool for predictions of muscle growth. The model uses coupled nonlinear ordinary differential equations to describe glucose metabolism through glycolysis, the TCA cycle in the mitochondria, and the associated transport processes, particularly the serine synthesis pathway. We use asymptotic analysis to generate approximate solutions to the model at the steady state to gain a better understanding of critical parameter values that switch the system between steady states and divergent behaviour. In addition, we use parameter sensitivity analysis to determine the effects of varying parameters (including enzymatic rates and input rates) on serine production.