title: Mathematical modeling of heterogeneous electrophysiological responses in human β-cells.
abstract: Electrical activity plays a pivotal role in glucose-stimulated insulin secretion from pancreatic β-cells. Recent findings have shown that the electrophysiological characteristics of human β-cells differ from their rodent counterparts. We show that the electrophysiological responses in human β-cells to a range of ion channels antagonists are heterogeneous. In some cells, inhibition of small-conductance potassium currents has no effect on action potential firing, while it increases the firing frequency dramatically in other cells. Sodium channel block can sometimes reduce action potential amplitude, sometimes abolish electrical activity, and in some cells even change spiking electrical activity to rapid bursting. We show that, in contrast to L-type Ca2+-channels, P/Q-type Ca2+-currents are not necessary for action potential generation, and, surprisingly, a P/Q-type Ca2+-channel antagonist even accelerates action potential firing. By including SK-channels and Ca2+ dynamics in a previous mathematical model of electrical activity in human β-cells, we investigate the heterogeneous and nonintuitive electrophysiological responses to ion channel antagonists, and use our findings to obtain insight in previously published insulin secretion measurements. Using our model we also study paracrine signals, and simulate slow oscillations by adding a glycolytic oscillatory component to the electrophysiological model. The heterogenous electrophysiological responses in human β-cells must be taken into account for a deeper understanding of the mechanisms underlying insulin secretion in health and disease, and as shown here, the interdisciplinary combination of experiments and modeling increases our understanding of human β-cell physiology.
authors.affiliation: Department of Information Engineering, University of Padua, Padua, Italy.
authors.forename: Michela
authors.initials: M
authors.lastname: Riz
authors.affiliation: Alberta Diabetes Institute, Department of Pharmacology, University of Alberta, Edmonton, Alberta, Canada.
authors.forename: Matthias
authors.initials: M
authors.lastname: Braun
authors.affiliation: Department of Information Engineering, University of Padua, Padua, Italy.
authors.forename: Morten Gram
authors.initials: MG
authors.lastname: Pedersen
mesh_terms: D000200:Action Potentials; D000465:Algorithms; D000818:Animals; D019295:Computational Biology; D055724:Electrophysiological Phenomena; D005947:Glucose / Q000737:chemistry; D006019:Glycolysis; D006801:Humans; D007328:Insulin / Q000378:metabolism; D000078790:Insulin Secretion; D050417:Insulin-Secreting Cells / Q000166:cytology*; D051379:Mice; D008962:Models, Theoretical; D009991:Oscillometry; D010179:Pancreas / Q000378:metabolism; D011188:Potassium / Q000737:chemistry; D015222:Sodium Channels / Q000737:chemistry; D013779:Tetrodotoxin / Q000737:chemistry
chemical_list: D007328:Insulin; D015222:Sodium Channels; D013779:Tetrodotoxin; D005947:Glucose; D011188:Potassium