Networks and non-autonomous dynamics, with applications to cell energy metabolism

Rowland Adams, Joe and Stefanovska, Aneta and McClintock, Peter and Arridge, Chris (2023) Networks and non-autonomous dynamics, with applications to cell energy metabolism. PhD thesis, Lancaster University.

Text (2023RowlandAdamsPhD)
2023RowlandAdamsPhD.pdf - Published Version
Available under License Creative Commons Attribution.
Download (27MB)

Abstract

Living systems are defined by their thermodynamic openness, by the fact that energy and matter are able to cross their boundaries. Without this capability to interact with their environment, living systems would be unable to support their life-sustaining functions. As a result of this continual interaction with its environment, the interior processes of a living system is forced to operate far from any equilibrium. Indeed, any system that is in equilibrium internally or with its environment could reasonably be characterised as a dead one. The dynamics of systems that are operating far from equilibrium, however, are far from understood. In this thesis, we build on an existing framework for understanding these dynamics, based in the finite-time analysis of non-autonomous oscillatory processes. This approach is motivated by a key consequence of thermodynamic openness — to introduce time-dependence to the open system. We develop an original mathematical model for the energy metabolism of cells using inter-coupled networks of non-autonomous phase oscillators, with intra-network weighted coupling. The effect of each of this model’s components on its dynamics and stability is numerically analysed. Experimental data of the metabolism of HeLa cells is analysed, finding the fundamental frequencies of this process. This analysis is used to demonstrate the capability of the model to reproduce the complex dynamics of the experiment, and this is contrasted to a comparable model of an alternative framework. It is this capacity of non-autonomous oscillations to simply and deterministically produce apparently highly complex dynamics that justifies our application of them to this problem. We demonstrate it further by viewing them through the framework of statistical time-series analysis, finding that even a single non-autonomous oscillator can appear to be 1/fβ noise in a power-spectral density estimation. Autonomous systems are shown to only present as noise when there are many of them, and hence it is the introduction of time-dependence that generates such complexity so readily. We demonstrate that this also occurs for coupled networks of non-autonomous oscillators, and in real experimental data. Analysis tools based in a finite-time framework, however, are shown to detect informative deterministic frequencies and couplings in both the numerical and experimental cases. Overall, this thesis demonstrates that networks of non-autonomous oscillations are physically linked to living systems through the time-dependence introduced by thermodynamic openness. Additionally, it is shown that they are able to reproduce living systems’ complex dynamics in a simple and usable way. Finally, it is established that much greater information about such an open system can be gained when they are analysed with this time-dependent deterministic framework in mind.