Diabetes affects more than 150 million people worldwide and its incidence is increasing. Glucose-stimulated insulin secretion (GSIS) is an essential homeostatic process for the control of blood glucose levels and takes place in pancreatic β-cells through interplay between glucose metabolism and various signaling cascades leading to a regulated insulin production and secretion. Many details of this interplay are still elusive and pure experimental approaches aiming to unveil such details are inadequate given the complexity of the system. Mathematical modeling can facilitate our understanding of how GSIS works given that pancreatic β-cell dysfunction in one of the leading causes of diabetes. Although many computational dynamic models for GSIS have been constructed, a complete, detailed kinetic model with a large number of enzyme rate equations mimicking the dynamics from the plasma glucose input and leading to the generation of ATP production based on experimental β-cell data has not been developed so far.

In this study, we have constructed a systems level model consisting of the following detailed subsystems: glycolysis, TCA cycle, oxidative phosphorylation and mitochondrial shuttles. The model is constructed based on detailed kinetic and thermodynamic reaction schemes for the biochemical intermediates involved in the pathway. Parameterization and validation of the model involved utilizing a large amount of the available β-cell experimental data. The model provides a relation between blood glucose levels and the amount of ATP generated. Most of the intermediates are minimal at baseline (low) glucose conditions. However, we observe that increasing extracellular glucose concentration with time in a similar fashion to postprandial increase in blood glucose, causes the flux through the glycolytic pathway to increase resulting in matching the β-cell experimental data of the glycolytic intermediates. The model also shows expected behavior in its outputs, including the response of ATP production to starting glucose concentration and the induction of oscillations in the concentration of metabolites in the glycolytic pathway as well as in the concentrations of ATP and ADP.

We further examined the effect of β-cell acidification on insulin secretion as the role of intracellular pH in GSIS is not clearly understood. Also, we investigated in silico the ‘pyruvate paradox' reported in β-cells. The relative effect of the TCA cycle and glycolysis on putative signals (e.g. ATP) was also explored. Results from these studies will be presented. Ongoing efforts focusing on the integration of calcium signaling and insulin exocytosis modules will be discussed. The outcome of this study will facilitate the discovery of novel targets for therapeutic intervention and the identification of new biomarkers of abnormal β-cell function for diagnostic purposes.