Controlling mitochondrial dynamics: population genetics and networks

Mitochondria form an essential component of nearly all eukaryotic cells, are implicated in numerous diseases and may play important roles in ageing. Mitochondrial populations are dynamic, controlled and heterogeneous, with different types -- both mutant and wildtype -- potentially coexisting in single cells. This thesis will study the dynamics of both mitochondria and their genetic material (mtDNA) to improve our understanding of the role of these dynamics in pathology and ageing. This study suggests, as well as critically evaluates, reasons for the existence of complex continuous mitochondrial networks using coarse-grained mathematical models, underlining a nonlinear relation between functionality and network structure. Understanding the link between morphology and function is important as disruption of the former is directly implicated in cellular dysfunction. We perform experiments in which we measure the influence of mitochondrial fusion and division events on integrated mitochondrial membrane potential, an indicator of functionality, and find evidence for its conservation. The cellular homeostatic control acting on a mitochondrial population is poorly understood; to address this, we study the influence of general feedback control strategies on mutant and wildtype mtDNA dynamics. We introduce a simple linear control mechanism that captures a wide variety of biologically observed dynamics, and study optimal parameterisations through the construction of an energy-based mitochondrial cost function. Not only cellular control, but also gene-therapeutic control of mtDNA is studied, allowing us to investigate optimal treatment strategies to reduce mutant loads. The cellular proportion of mutant mtDNA molecules, known as heteroplasmy, is crucial in mitochondrial disease and we study the influence of cellular mtDNA exchange on heteroplasmy dynamics and mutant expansion during ageing. We find that this exchange of genetic material can induce preferential mutant expansion during ageing (even in the face of selection against mutants) through a stochastically driven increase in cellular mean heteroplasmy levels.Open Acces

Stochastic survival of the densest and mitochondrial DNA clonal expansion in aging.

The expansion of mitochondrial DNA molecules with deletions has been associated with aging, particularly in skeletal muscle fibers; its mechanism has remained unclear for three decades. Previous accounts have assigned a replicative advantage (RA) to mitochondrial DNA containing deletion mutations, but there is also evidence that cells can selectively remove defective mitochondrial DNA. Here we present a spatial model that, without an RA, but instead through a combination of enhanced density for mutants and noise, produces a wave of expanding mutations with speeds consistent with experimental data. A standard model based on RA yields waves that are too fast. We provide a formula that predicts that wave speed drops with copy number, consonant with experimental data. Crucially, our model yields traveling waves of mutants even if mutants are preferentially eliminated. Additionally, we predict that mutant loads observed in single-cell experiments can be produced by de novo mutation rates that are drastically lower than previously thought for neutral models. Given this exemplar of how spatial structure (multiple linked mtDNA populations), noise, and density affect muscle cell aging, we introduce the mechanism of stochastic survival of the densest (SSD), an alternative to RA, that may underpin other evolutionary phenomena

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, 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.Comment: Main text: 14 pages, 5 figures; Supplement: 17 pages, 4 figures; Total: 31 pages, 9 figure

Cellular allometry of mitochondrial functionality establishes the optimal cell size

Eukaryotic cells attempt to maintain an optimal size, resulting in size homeostasis. While cellular content scales isometrically with cell size, allometric laws indicate that metabolism per mass unit should decline with increasing size. Here we use elutriation and single-cell flow cytometry to analyze mitochondrial scaling with cell size. While mitochondrial content increases linearly, mitochondrial membrane potential and oxidative phosphorylation are highest at intermediate cell sizes. Thus, mitochondrial content and functional scaling are uncoupled. The nonlinearity of mitochondrial functionality is cell size, not cell cycle, dependent, and it results in an optimal cell size whereby cellular fitness and proliferative capacity are maximized. While optimal cell size is controlled by growth factor signaling, its establishment and maintenance requires mitochondrial dynamics, which can be controlled by the mevalonate pathway. Thus, optimization of cellular fitness and functionality through mitochondria can explain the requirement for size control, as well as provide means for its maintenance

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

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