A Consensus Model of Glucose-Stimulated Insulin Secretion in the Pancreaticβ-Cell

Abstract

The pancreas plays a critical role in maintaining glucose homeostasis through the secretion of hormones from the islets of Langerhans. Glucose-stimulated insulin secretion (GSIS) by the pancreatic beta-cell is the main mechanism for reducing elevated plasma glucose. Here we present a systematic modeling workflow for the development of kinetic pathway models using the Systems Biology Markup Language (SBML). Steps include retrieval of information from databases, curation of experimental and clinical data for model calibration and validation, integration of heterogeneous data including absolute and relative measurements, unit normalization, data normalization, and model annotation. An important factor was the reproducibility and exchangeability of the model, which allowed the use of various existing tools. The workflow was applied to construct the first consensus model of GSIS in the pancreatic beta-cell based on experimental and clinical data from 39 studies spanning 50 years of pancreatic, islet, and beta-cell research in humans, rats, mice, and cell lines. The model consists of detailed glycolysis and equations for insulin secretion coupled to cellular energy state (ATP/ADP ratio). Key findings of our work are that in GSIS there is a glucose-dependent increase in almost all intermediates of glycolysis. This increase in glycolytic metabolites is accompanied by an increase in energy metabolites, especially ATP and NADH. One of the few decreasing metabolites is ADP, which, in combination with the increase in ATP, results in a large increase in ATP/ADP ratios in the beta-cell with increasing glucose. Insulin secretion is dependent on ATP/ADP, resulting in glucose-stimulated insulin secretion. The observed glucose-dependent increase in glycolytic intermediates and the resulting change in ATP/ADP ratios and insulin secretion is a robust phenomenon observed across data sets, experimental systems and species. Model predictions of the glucose-dependent response of glycolytic intermediates and insulin secretion are in good agreement with experimental measurements. Our model predicts that factors affecting ATP consumption, ATP formation, hexokinase, phosphofructokinase, and ATP/ADP-dependent insulin secretion have a major effect on GSIS. In conclusion, we have developed and applied a systematic modeling workflow for pathway models that allowed us to gain insight into key mechanisms in GSIS in the pancreatic beta-cell.

A pathway model of glucose-stimulated insulin secretion in the pancreatic β-cell

“…The model is available in SBML ( 33 , 128 ) under a CC-BY 4.0 license from https://github.com/matthiaskoenig/pancreas-model . In this study, version 0.9.6 of the model is presented ( 108 , 109 ).…”

A more expressive spline representation for SBML models improves code generation performance in AMICI

“…However, such tools require the data to be interpolated to be numeric. While very useful for interpolating data series [12], they cannot be used for parameter inference on functions. We have thus added to the AMICI Python library some convenience functions to generate the above mentioned assignment rules, containing both the AMICI-specific compact representation and the usual MathML formula, also covering the case where the spline values at the nodes (or its derivatives) depend on the model parameters.…”

New-Generation Glucokinase Activators: Potential Game-Changers in Type 2 Diabetes Treatment

“…In the pancreas, GK serves as a glucose sensor in -cells, directly regulating insulin secretion [21]. As blood glucose levels rise, the increased kinetic activity of GK mediates G6P production, subsequently stimulating insulin release and maintaining glucose homeostasis [22]. In pancreatic -cells, GK regulates glucagon secretion [23].…”