title: Phantom bursting is highly sensitive to noise and unlikely to account for slow bursting in beta-cells: considerations in favor of metabolically driven oscillations.
abstract: Pancreatic beta-cells show bursting electrical activity with a wide range of burst periods ranging from a few seconds, often seen in isolated cells, over tens of seconds (medium bursting), usually observed in intact islets, to several minutes. The phantom burster model [Bertram, R., Previte, J., Sherman, A., Kinard, T.A., Satin, L.S., 2000. The phantom burster model for pancreatic beta-cells. Biophys. J. 79, 2880-2892] provided a framework, which covered this span, and gave an explanation of how to obtain medium bursting combining two processes operating on different time scales. However, single cells are subjected to stochastic fluctuations in plasma membrane currents, which are likely to disturb the bursting mechanism and transform medium bursters into spikers or very fast bursters. We present a polynomial, minimal, phantom burster model and show that noise modifies the plateau fraction and lowers the burst period dramatically in phantom bursters. It is therefore unlikely that slow bursting in single cells is driven by the slow phantom bursting mechanism, but could instead be driven by oscillations in glycolysis, which we show are stable to random ion channel fluctuations. Moreover, so-called compound bursting can be converted to apparent slow bursting by noise, which could explain why compound bursting and mixed Ca(2+) oscillations are seen mainly in intact islets.
authors.affiliation: Department of Mathematics, Technical University of Denmark, Matematiktorvet 303, DK-2800 Kgs. Lyngby, Denmark. m.g.pedersen@mat.dtu.dk
authors.forename: Morten Gram
authors.initials: MG
authors.lastname: Pedersen
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D000818:Animals; D020013:Calcium Signaling; D006019:Glycolysis; D006801:Humans; D050417:Insulin-Secreting Cells / Q000378:metabolism / Q000502:physiology*; D008954:Models, Biological; D013269:Stochastic Processes