Energetic costs of cellular and therapeutic control of stochastic mitochondrial DNA populations

Hanne Hoitzing, Payam A Gammage, Lindsey Van Haute, Michal Minczuk, Iain G Johnston and Nick S Jones

PLOS Computational Biology, 2019, vol. 15, issue 6, 1-27

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.Author summary: Mitochondria, best known for their role in energy production, are crucial to the survival of most of our cells. To respond to energetic demands and mitigate against mutational damage, cells control the mitochondrial populations within them. However, the character of these control mechanisms remains open. As experimental elucidation of these mechanisms is challenging, theoretical approaches can help us understand the general principles of cellular control of mitochondria in physiology and disease. Here, we use stochastic modelling to compare control strategies by studying their impact on the dynamics of mitochondrial DNA (mtDNA) populations as well as their energetic burden to the cell. We identify optimal strategies for the cell to control against mtDNA damage and preserve energy production and use this theory to explore the action of recently developed mitochondrial gene therapies, which reduce the fraction of mutant mtDNA molecules inside cells. We show how treatment efficiency may depend on pre-treatment distributions of mutant and wildtype mtDNA molecules: treatments are less effective for tissues consisting of cells with highly varying mutant levels, and long-term, rather than short intense, gene therapies should be favoured.

Date: 2019
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1007023 (text/html)
https://journals.plos.org/ploscompbiol/article/fil ... 07023&type=printable (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:plo:pcbi00:1007023

DOI: 10.1371/journal.pcbi.1007023

Access Statistics for this article

More articles in PLOS Computational Biology from Public Library of Science
Bibliographic data for series maintained by ploscompbiol ().