Variability in mitochondrial genetics and functionality and its cell physiological effects

Mitochondria are organelles that produce the energy that is necessary for life within our cells. This energy is produced in the form of ATP, a molecule that is used as an energy source in countless cellular processes. The importance of mitochondria in ensuring a sufficient energy supply within organisms means that variability in mitochondrial performance -- and subsequent changes in their capacity to produce ATP -- can have profound consequences for an organism. Many diseases with great societal impact are associated with damage to the protein machinery of mitochondria and subequent decrease in mitochondrial performance, including Alzheimer's, Parkinson's, and a host of inherited diseases. Increasing damage to the mitochondrial system in organisms is postulated to be a key cause of ageing. In addition, differences in the mitochondrial content of cells can affect fundamental biological behaviour, such as how stem cells differentiate into other cell types (a key question in current stem cell research) and how tumour cells respond to anti-cancer drugs.

Despite the importance of mitochondrial variability in these situations of medical and biological interest, and a recent explosion of experimental data showing that mitochondria form a rich physical system within cells, there has been little theoretical work to provide a quantitative understanding of the mitochondrial system. This lack of quantitative understanding makes it very difficult, for example, to make statements of clinical relevance such as the probability of inheriting a mitochondrial disease. This project aims to address this imbalance by producing mathematical and computational models of several key causes and effects of mitochondrial variability. First, damage to the mitochondrial genome -- which encodes the proteins that are responsible for ATP production -- and to the proteins themselves will be explored quantitatively, providing a mathematical foundation to help describe probabilities and time behaviour of mitochondrial damage. Second, the effects of this and other sources of mitochondrial variability -- including uneven inheritance of mitochondria from a parent cell to a daughter cell -- will be incorporated into a model for the variation in ATP levels between cells in a population. Thirdly, the effects of this variability on two key biological phenomena: the differentiation pathways of stem cells, and the response of tumour cells to anti-cancer drugs, will be explored by linking these models with existing approaches in the mathematical biology literature.

This project will address the existing disconnect between experimental and theoretical understanding of mitochondrial systems by using existing and novel statistical modelling approaches to describe sources of mitochondrial variability, and combining this with computational models to explore mitochondrial effects on downstream processes.

A birth-death-mutation model incorporating stochastic partitioning effects will be developed to statistically describe the time evolution of the mitochondrial makeup of cells. A model for oxidative damage, including oxidative phosphorylation and ROS production, mtDNA mutation, cardiolipin and protein damage, will be developed to provide a systems-level view of mitochondrial time behaviour. These models will be parameterised using recent advances in statistical inference for stochastic kinetic systems, notably from approximate Bayesian computation. This part of the project will be the first example of a rigorously parameterised statistical description of mitochondrial damage and quality control, enabling quantitative statements and predictions to be made about damage buildup and subsequent disease onset.

Existing control theory-based models for ATP homeostasis will be examined and adapted with input from new computational models of mitochondria and oxidative phosphorylation to model the effects of mitochondrial variability on the ATP content of cells. Existing inferential techniques for stochastic kinetic models will be adapted to allow the statistical inference of rate parameters that may vary with time, to incorporate the possibility of varying ATP levels in cellular models. Combining these approaches, terms representing mitochondrial variability will be incorporated into existing mathematical models for stem cell differentiation and TRAIL response to explore the implications of mitochondrial variability in these systems of medical interest.

This research will benefit academic communities in the fields of mitochondrial biology, cellular noise, and mathematical biology, as well as applied statistics. Its implications and the models it produces will be of use to medical practitioners concerned with approaches to mitochondrial disease and diseases associated with mitochondrial damage. Through its quantitative approach to this important medical system, clinical approaches to the management of these diseases will be improved, benefitting public health. In addition, public dissemination of the elucidation of causes and effects of stochasticity in cellular biology will help raise the understanding of stochastic biology in the public eye and potentially inform the public about how random effects play a role in medical treatments.

Perhaps the most important result of this research will be a improved quantitative understanding of mitochondrial variability. The current lack of a quantitative foundation in this field has been noted as a significant factor hindering the clinical management of mitochondrial disease. Contributions from this project have the potential to make quantitative predictions about mitochondrial disease inheritance and onset timescales, which will improve medical approaches to managing these diseases. As the number of diseases in which mitochondrial variability is implicated as a causal factor increases -- from those resulting from inherited mtDNA mutations to the more ubiquitous examples of Parkinson's and Alzheimer's -- this quantitative understanding will be invaluable.

The stem cell project within this research also has the potential to increase understanding in a biological system of fundamental medical relevance. With the ongoing development of stem cell therapy, and high level of interest in developmental biology, a quantitative understanding of the influences on differentiation pathways is of profound importance. Advances made in this research will investigate mitochondrial influences on these pathways -- an effect of potentially fundamental importance. The increased understanding resulting from this work will be of immediate relevance to researchers in stem cell biology and development, potentially translating into advantages in stem cell therapy approaches.

The TRAIL response project likewise has the potential to contribute positively to public health. An understanding of the factors that result in different tumour cells responding differently to drug treatment will be of great benefit to the further development and application of this clinical approach.

Academically, the project will be of benefit both in providing a quantitative description of what is at present a qualitatively understood system, and in developing new stochastic models and inferential techniques for the description of stochastic systems in cellular biology (see Academic Beneficiaries).