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| Item Type: | Article |
|---|---|
| Title: | Calcium signals driven by single channel noise |
| Creators Name: | Skupin, A. and Kettenmann, H. and Falcke, M. |
| Abstract: | Usually, the occurrence of random cell behavior is appointed to small copy numbers of molecules involved in the stochastic process. Recently, we demonstrated for a variety of cell types that intracellular Ca(2+) oscillations are sequences of random spikes despite the involvement of many molecules in spike generation. This randomness arises from the stochastic state transitions of individual Ca(2+) release channels and does not average out due to the existence of steep concentration gradients. The system is hierarchical due to the structural levels channel - channel cluster - cell and a corresponding strength of coupling. Concentration gradients introduce microdomains which couple channels of a cluster strongly. But they couple clusters only weakly; too weak to establish deterministic behavior on cell level. Here, we present a multi-scale modelling concept for stochastic hierarchical systems. It simulates active molecules individually as Markov chains and their coupling by deterministic diffusion. Thus, we are able to follow the consequences of random single molecule state changes up to the signal on cell level. To demonstrate the potential of the method, we simulate a variety of experiments. Comparisons of simulated and experimental data of spontaneous oscillations in astrocytes emphasize the role of spatial concentration gradients in Ca(2+) signalling. Analysis of extensive simulations indicates that frequency encoding described by the relation between average and standard deviation of interspike intervals is surprisingly robust. This robustness is a property of the random spiking mechanism and not a result of control. |
| Keywords: | Astrocytes, Calcium, Calcium Channels, Calcium Signaling, Computer Simulation, Diffusion, Inositol 1,4,5-Trisphosphate Receptors, Markov Chains, Biological Models , Statistical Models, Animals, Mice, Rats |
| Source: | PLoS Computational Biology |
| ISSN: | 1553-734X |
| Publisher: | Public Library of Science |
| Volume: | 6 |
| Number: | 8 |
| Page Range: | e1000870 |
| Date: | 5 August 2010 |
| Official Publication: | https://doi.org/10.1371/journal.pcbi.1000870 |
| PubMed: | View item in PubMed |
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