Article révisé par les pairs
Résumé : In pancreatic α-cells, intracellular Ca2+ ([Ca2+]i) acts as a trigger for secretion of glucagon, a hormone that plays a key role in blood glucose homeostasis. Intracellular Ca2+ dynamics in these cells are governed by the electrical activity of voltage-gated ion channels, among which ATP-sensitive K+ (KATP) channels play a crucial role. In the majority of α-cells, the global Ca2+ response to lowering external glucose occurs in the form of oscillations that are much slower than electrical activity. These Ca2+ oscillations are highly variable as far as inter-spike intervals, shapes and amplitudes are concerned. Such observations suggest that Ca2+ dynamics in α-cells are much influenced by noise. Actually, each Ca2+ increase corresponds to multiple cycles of opening/closing of voltage gated Ca2+ channels that abruptly become silent, before the occurrence of another burst of activity a few tens of seconds later. The mechanism responsible for this intermittent activity is currently unknown. In this work, we used computational modeling to investigate the mechanism of cytosolic Ca2+ oscillations in α-cells. Given the limited population of KATP channels in this cell type, we hypothesized that the stochastic activity of these channels could play a key role in the sporadic character of the action potentials. To test this assumption, we extended a previously proposed model of the α-cells electrical activity (Diderichsen and Göpel, 2006) to take Ca2+ dynamics into account. Including molecular noise on the basis of a Langevin type description as well as realistic dynamics of opening and closing of KATP channels, we found that stochasticity at the level of the activity of this channel is on its own not able to produce Ca2+ oscillations with a time scale of a few tens of seconds. However, when taking into account the intimate relation between Ca2+ and ATP changes together with the intrinsic noise at the level of the KATP channels, simulations displayed Ca2+ oscillations that are compatible with experimental observations. We analyzed the detailed mechanism and used computational simulations to identify the factors that can affect Ca2+ oscillations in α-cells.