Dynamic Modelling of Mitochondrial Metabolism

Abstract

Mitochondria are cellular organelles that harbour complex biochemical processes ranging from ATP production to calcium signalling, and a purely experimental approach is insufficient to understand the intricate interactions of these processes.In this work, we develop a dynamic model of the mammalian mitochondrial metabolic processes in the form of coupled ordinary differential equations. The model includes the oxidative phosphorylation (OxPhos) complexes, the Krebs cycle, and the metabolites reactions and transport.First, we improved an existing OxPhos model (see Heiske et al. (2017)) by taking into account appropriate enzyme kinetics and thermodynamics, describing each complex by a separate rate equation. These equations are coupled in a mitochondria model context and parameterised using literature data from isolated mitochondria and parameter adjustment of a previous OxPhos data set in Heiske et al. (2017). Then, we coupled the OxPhos model with an adjusted model of metabolites transport and the Krebs cycle similar to Wu et al. (2007).Due to the non-identifiability of some parameters, we propose to use a collinearity-integer optimization workflow presented by Gábor et al. (2017) to find the characteristics of the non-identifiable parameters, thus reformulating and validating the model accordingly.