Explaining the ageing of skeletal muscle fibres through a novel evolutionary mechanism

Lead Research Organisation: Imperial College London
Department Name: Dept of Mathematics

Abstract

The expansion of deleted mitochondrial DNA (mtDNA) molecules has been linked to ageing, particularly in muscle fibres, where it leads to sarcopenia. Despite three years of research, the mechanism underlying muscle fibre ageing has remained unclear. Previous accounts have assigned a selective advantage to the deleted mitochondrial DNA, but, in fact, cells can selectively remove disadvantageous mtDNA.

In this project we have been exploring how spatially extended models with a combination of enhanced density for mutants and stochasticity satisfactorily reproduce the expansion and its speed, that we have estimated estimate form experimental data. We have found evidence that the expansion takes place in a wavelike fashion and we have found an empirical formula for the wavespeed. Notably, these models permit a selective disadvantage for the mutants while nonetheless yielding spreading waves. We introduce the mechanism of stochastic survival of the densest, and we are exploring its plausibility as an alternative to conventional evolutionary theory based survival of the fittest. Muscle fibre ageing is thus a candidate exemplar for the role of noise and spatial structure in yielding novel evolutionary phenomena.

Our understanding of muscle ageing, based on the novel mechanism we propose, suggests the relevance of existing drugs for slowing waves of mutants. Based on our empirical formula for the expansion speed, we plan to explore the relevance of possible pharmaceutical interventions that could slow down the spreading of mutants.

The tools used in this project are a combination of analytical and computational techniques. We are using stochastic calculus to gain analytical insight in our model and the Gillespie algorithm to simulate it. Additionally, we use statistical techniques to compare the predictions of ours and competing models to experimental data.

Publications

10 25 50

Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/N509486/1 01/10/2016 31/03/2022
2013975 Studentship EP/N509486/1 01/10/2017 31/03/2021 Ferdinando Insalata