Energetic costs of cellular and therapeutic control of stochastic mitochondrial DNA populations
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Published version
Author(s)
Type
Journal Article
Abstract
The dynamics of the cellular proportion of mutant mtDNA molecules is crucial for mitochondrial diseases. Cellular populations of mitochondria are under homeostatic control, but the details of the control mechanisms involved remain elusive. Here, we use stochastic modelling to derive general results for the impact of cellular control on mtDNA populations, the cost to the cell of different mtDNA states, and the optimisation of therapeutic control of mtDNA populations. This formalism yields a wealth of biological results, including that an increasing mtDNA variance can increase the energetic cost of maintaining a tissue, that intermediate levels of heteroplasmy can be more detrimental than homoplasmy even for a dysfunctional mutant, that heteroplasmy distribution (not mean alone) is crucial for the success of gene therapies, and that long-term rather than short intense gene therapies are more likely to beneficially impact mtDNA populations.
Date Issued
2019-06-26
Date Acceptance
2019-04-11
Citation
PLoS Computational Biology, 2019, 15 (6)
ISSN
1553-734X
Publisher
Public Library of Science (PLoS)
Journal / Book Title
PLoS Computational Biology
Volume
15
Issue
6
Copyright Statement
© 2019 Hoitzing et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Sponsor
Engineering & Physical Science Research Council (EPSRC)
The Leverhulme Trust
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/31242175
PII: PCOMPBIOL-D-18-01750
Grant Number
EP/N014529/1
RPG-2019-408
Subjects
Bioinformatics
06 Biological Sciences
08 Information and Computing Sciences
01 Mathematical Sciences
Publication Status
Published
Coverage Spatial
United States
Article Number
e1007023