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Calcium Regulation of Single Ryanodine Receptor Channel Gating Analyzed Using HMM/MCMC Statistical Methods
Type-II ryanodine receptor channels (RYRs) play a fundamental role in intracellular Ca(2+) dynamics in heart. The processes of activation, inactivation, and regulation of these channels have been the subject of intensive research and the focus of recent debates. Typically, approaches to understand t...
Autores principales: | , , |
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Formato: | Texto |
Lenguaje: | English |
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The Rockefeller University Press
2004
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2234502/ https://www.ncbi.nlm.nih.gov/pubmed/15111644 http://dx.doi.org/10.1085/jgp.200308868 |
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author | Rosales, Rafael A. Fill, Michael Escobar, Ariel L. |
author_facet | Rosales, Rafael A. Fill, Michael Escobar, Ariel L. |
author_sort | Rosales, Rafael A. |
collection | PubMed |
description | Type-II ryanodine receptor channels (RYRs) play a fundamental role in intracellular Ca(2+) dynamics in heart. The processes of activation, inactivation, and regulation of these channels have been the subject of intensive research and the focus of recent debates. Typically, approaches to understand these processes involve statistical analysis of single RYRs, involving signal restoration, model estimation, and selection. These tasks are usually performed by following rather phenomenological criteria that turn models into self-fulfilling prophecies. Here, a thorough statistical treatment is applied by modeling single RYRs using aggregated hidden Markov models. Inferences are made using Bayesian statistics and stochastic search methods known as Markov chain Monte Carlo. These methods allow extension of the temporal resolution of the analysis far beyond the limits of previous approaches and provide a direct measure of the uncertainties associated with every estimation step, together with a direct assessment of why and where a particular model fails. Analyses of single RYRs at several Ca(2+) concentrations are made by considering 16 models, some of them previously reported in the literature. Results clearly show that single RYRs have Ca(2+)-dependent gating modes. Moreover, our results demonstrate that single RYRs responding to a sudden change in Ca(2+) display adaptation kinetics. Interestingly, best ranked models predict microscopic reversibility when monovalent cations are used as the main permeating species. Finally, the extended bandwidth revealed the existence of novel fast buzz-mode at low Ca(2+) concentrations. |
format | Text |
id | pubmed-2234502 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2004 |
publisher | The Rockefeller University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-22345022008-03-21 Calcium Regulation of Single Ryanodine Receptor Channel Gating Analyzed Using HMM/MCMC Statistical Methods Rosales, Rafael A. Fill, Michael Escobar, Ariel L. J Gen Physiol Article Type-II ryanodine receptor channels (RYRs) play a fundamental role in intracellular Ca(2+) dynamics in heart. The processes of activation, inactivation, and regulation of these channels have been the subject of intensive research and the focus of recent debates. Typically, approaches to understand these processes involve statistical analysis of single RYRs, involving signal restoration, model estimation, and selection. These tasks are usually performed by following rather phenomenological criteria that turn models into self-fulfilling prophecies. Here, a thorough statistical treatment is applied by modeling single RYRs using aggregated hidden Markov models. Inferences are made using Bayesian statistics and stochastic search methods known as Markov chain Monte Carlo. These methods allow extension of the temporal resolution of the analysis far beyond the limits of previous approaches and provide a direct measure of the uncertainties associated with every estimation step, together with a direct assessment of why and where a particular model fails. Analyses of single RYRs at several Ca(2+) concentrations are made by considering 16 models, some of them previously reported in the literature. Results clearly show that single RYRs have Ca(2+)-dependent gating modes. Moreover, our results demonstrate that single RYRs responding to a sudden change in Ca(2+) display adaptation kinetics. Interestingly, best ranked models predict microscopic reversibility when monovalent cations are used as the main permeating species. Finally, the extended bandwidth revealed the existence of novel fast buzz-mode at low Ca(2+) concentrations. The Rockefeller University Press 2004-05 /pmc/articles/PMC2234502/ /pubmed/15111644 http://dx.doi.org/10.1085/jgp.200308868 Text en Copyright © 2004, The Rockefeller University Press This article is distributed under the terms of an Attribution–Noncommercial–Share Alike–No Mirror Sites license for the first six months after the publication date (see http://www.rupress.org/terms). After six months it is available under a Creative Commons License (Attribution–Noncommercial–Share Alike 4.0 Unported license, as described at http://creativecommons.org/licenses/by-nc-sa/4.0/). |
spellingShingle | Article Rosales, Rafael A. Fill, Michael Escobar, Ariel L. Calcium Regulation of Single Ryanodine Receptor Channel Gating Analyzed Using HMM/MCMC Statistical Methods |
title | Calcium Regulation of Single Ryanodine Receptor Channel Gating Analyzed Using HMM/MCMC Statistical Methods |
title_full | Calcium Regulation of Single Ryanodine Receptor Channel Gating Analyzed Using HMM/MCMC Statistical Methods |
title_fullStr | Calcium Regulation of Single Ryanodine Receptor Channel Gating Analyzed Using HMM/MCMC Statistical Methods |
title_full_unstemmed | Calcium Regulation of Single Ryanodine Receptor Channel Gating Analyzed Using HMM/MCMC Statistical Methods |
title_short | Calcium Regulation of Single Ryanodine Receptor Channel Gating Analyzed Using HMM/MCMC Statistical Methods |
title_sort | calcium regulation of single ryanodine receptor channel gating analyzed using hmm/mcmc statistical methods |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2234502/ https://www.ncbi.nlm.nih.gov/pubmed/15111644 http://dx.doi.org/10.1085/jgp.200308868 |
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