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Stochastic modelling, Bayesian inference, and new in vivo measurements elucidate the debated mtDNA bottleneck mechanism

Dangerous damage to mitochondrial DNA (mtDNA) can be ameliorated during mammalian development through a highly debated mechanism called the mtDNA bottleneck. Uncertainty surrounding this process limits our ability to address inherited mtDNA diseases. We produce a new, physically motivated, generalis...

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Autores principales: Johnston, Iain G, Burgstaller, Joerg P, Havlicek, Vitezslav, Kolbe, Thomas, Rülicke, Thomas, Brem, Gottfried, Poulton, Jo, Jones, Nick S
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4486817/
https://www.ncbi.nlm.nih.gov/pubmed/26035426
http://dx.doi.org/10.7554/eLife.07464
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author Johnston, Iain G
Burgstaller, Joerg P
Havlicek, Vitezslav
Kolbe, Thomas
Rülicke, Thomas
Brem, Gottfried
Poulton, Jo
Jones, Nick S
author_facet Johnston, Iain G
Burgstaller, Joerg P
Havlicek, Vitezslav
Kolbe, Thomas
Rülicke, Thomas
Brem, Gottfried
Poulton, Jo
Jones, Nick S
author_sort Johnston, Iain G
collection PubMed
description Dangerous damage to mitochondrial DNA (mtDNA) can be ameliorated during mammalian development through a highly debated mechanism called the mtDNA bottleneck. Uncertainty surrounding this process limits our ability to address inherited mtDNA diseases. We produce a new, physically motivated, generalisable theoretical model for mtDNA populations during development, allowing the first statistical comparison of proposed bottleneck mechanisms. Using approximate Bayesian computation and mouse data, we find most statistical support for a combination of binomial partitioning of mtDNAs at cell divisions and random mtDNA turnover, meaning that the debated exact magnitude of mtDNA copy number depletion is flexible. New experimental measurements from a wild-derived mtDNA pairing in mice confirm the theoretical predictions of this model. We analytically solve a mathematical description of this mechanism, computing probabilities of mtDNA disease onset, efficacy of clinical sampling strategies, and effects of potential dynamic interventions, thus developing a quantitative and experimentally-supported stochastic theory of the bottleneck. DOI: http://dx.doi.org/10.7554/eLife.07464.001
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spelling pubmed-44868172015-07-02 Stochastic modelling, Bayesian inference, and new in vivo measurements elucidate the debated mtDNA bottleneck mechanism Johnston, Iain G Burgstaller, Joerg P Havlicek, Vitezslav Kolbe, Thomas Rülicke, Thomas Brem, Gottfried Poulton, Jo Jones, Nick S eLife Computational and Systems Biology Dangerous damage to mitochondrial DNA (mtDNA) can be ameliorated during mammalian development through a highly debated mechanism called the mtDNA bottleneck. Uncertainty surrounding this process limits our ability to address inherited mtDNA diseases. We produce a new, physically motivated, generalisable theoretical model for mtDNA populations during development, allowing the first statistical comparison of proposed bottleneck mechanisms. Using approximate Bayesian computation and mouse data, we find most statistical support for a combination of binomial partitioning of mtDNAs at cell divisions and random mtDNA turnover, meaning that the debated exact magnitude of mtDNA copy number depletion is flexible. New experimental measurements from a wild-derived mtDNA pairing in mice confirm the theoretical predictions of this model. We analytically solve a mathematical description of this mechanism, computing probabilities of mtDNA disease onset, efficacy of clinical sampling strategies, and effects of potential dynamic interventions, thus developing a quantitative and experimentally-supported stochastic theory of the bottleneck. DOI: http://dx.doi.org/10.7554/eLife.07464.001 eLife Sciences Publications, Ltd 2015-06-02 /pmc/articles/PMC4486817/ /pubmed/26035426 http://dx.doi.org/10.7554/eLife.07464 Text en © 2015, Johnston et al http://creativecommons.org/licenses/by/4.0/ This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Computational and Systems Biology
Johnston, Iain G
Burgstaller, Joerg P
Havlicek, Vitezslav
Kolbe, Thomas
Rülicke, Thomas
Brem, Gottfried
Poulton, Jo
Jones, Nick S
Stochastic modelling, Bayesian inference, and new in vivo measurements elucidate the debated mtDNA bottleneck mechanism
title Stochastic modelling, Bayesian inference, and new in vivo measurements elucidate the debated mtDNA bottleneck mechanism
title_full Stochastic modelling, Bayesian inference, and new in vivo measurements elucidate the debated mtDNA bottleneck mechanism
title_fullStr Stochastic modelling, Bayesian inference, and new in vivo measurements elucidate the debated mtDNA bottleneck mechanism
title_full_unstemmed Stochastic modelling, Bayesian inference, and new in vivo measurements elucidate the debated mtDNA bottleneck mechanism
title_short Stochastic modelling, Bayesian inference, and new in vivo measurements elucidate the debated mtDNA bottleneck mechanism
title_sort stochastic modelling, bayesian inference, and new in vivo measurements elucidate the debated mtdna bottleneck mechanism
topic Computational and Systems Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4486817/
https://www.ncbi.nlm.nih.gov/pubmed/26035426
http://dx.doi.org/10.7554/eLife.07464
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