4.6 Article

Mathematical Modeling of Heterogeneous Electrophysiological Responses in Human beta-Cells

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PLOS COMPUTATIONAL BIOLOGY
卷 10, 期 1, 页码 -

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PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pcbi.1003389

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资金

  1. Lundbeck Foundation
  2. EU via a Marie Curie Intra-European Fellowship
  3. Sanofi AG Frankfurt, Germany
  4. CIHR [MOP-106435]
  5. CFI

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Electrical activity plays a pivotal role in glucose-stimulated insulin secretion from pancreatic beta-cells. Recent findings have shown that the electrophysiological characteristics of human beta-cells differ from their rodent counterparts. We show that the electrophysiological responses in human beta-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 beta-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 beta-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 beta-cell physiology.

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