Cargando…

Modeling Cell Energy Metabolism as Weighted Networks of Non-autonomous Oscillators

Networks of oscillating processes are a common occurrence in living systems. This is as true as anywhere in the energy metabolism of individual cells. Exchanges of molecules and common regulation operate throughout the metabolic processes of glycolysis and oxidative phosphorylation, making the consi...

Descripción completa

Detalles Bibliográficos
Autores principales: Rowland Adams, Joe, Stefanovska, Aneta
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7876325/
https://www.ncbi.nlm.nih.gov/pubmed/33584336
http://dx.doi.org/10.3389/fphys.2020.613183
_version_ 1783649949473308672
author Rowland Adams, Joe
Stefanovska, Aneta
author_facet Rowland Adams, Joe
Stefanovska, Aneta
author_sort Rowland Adams, Joe
collection PubMed
description Networks of oscillating processes are a common occurrence in living systems. This is as true as anywhere in the energy metabolism of individual cells. Exchanges of molecules and common regulation operate throughout the metabolic processes of glycolysis and oxidative phosphorylation, making the consideration of each of these as a network a natural step. Oscillations are similarly ubiquitous within these processes, and the frequencies of these oscillations are never truly constant. These features make this system an ideal example with which to discuss an alternative approach to modeling living systems, which focuses on their thermodynamically open, oscillating, non-linear and non-autonomous nature. We implement this approach in developing a model of non-autonomous Kuramoto oscillators in two all-to-all weighted networks coupled to one another, and themselves driven by non-autonomous oscillators. Each component represents a metabolic process, the networks acting as the glycolytic and oxidative phosphorylative processes, and the drivers as glucose and oxygen supply. We analyse the effect of these features on the synchronization dynamics within the model, and present a comparison between this model, experimental data on the glycolysis of HeLa cells, and a comparatively mainstream model of this experiment. In the former, we find that the introduction of oscillator networks significantly increases the proportion of the model's parameter space that features some form of synchronization, indicating a greater ability of the processes to resist external perturbations, a crucial behavior in biological settings. For the latter, we analyse the oscillations of the experiment, finding a characteristic frequency of 0.01–0.02 Hz. We further demonstrate that an output of the model comparable to the measurements of the experiment oscillates in a manner similar to the measured data, achieving this with fewer parameters and greater flexibility than the comparable model.
format Online
Article
Text
id pubmed-7876325
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-78763252021-02-12 Modeling Cell Energy Metabolism as Weighted Networks of Non-autonomous Oscillators Rowland Adams, Joe Stefanovska, Aneta Front Physiol Physiology Networks of oscillating processes are a common occurrence in living systems. This is as true as anywhere in the energy metabolism of individual cells. Exchanges of molecules and common regulation operate throughout the metabolic processes of glycolysis and oxidative phosphorylation, making the consideration of each of these as a network a natural step. Oscillations are similarly ubiquitous within these processes, and the frequencies of these oscillations are never truly constant. These features make this system an ideal example with which to discuss an alternative approach to modeling living systems, which focuses on their thermodynamically open, oscillating, non-linear and non-autonomous nature. We implement this approach in developing a model of non-autonomous Kuramoto oscillators in two all-to-all weighted networks coupled to one another, and themselves driven by non-autonomous oscillators. Each component represents a metabolic process, the networks acting as the glycolytic and oxidative phosphorylative processes, and the drivers as glucose and oxygen supply. We analyse the effect of these features on the synchronization dynamics within the model, and present a comparison between this model, experimental data on the glycolysis of HeLa cells, and a comparatively mainstream model of this experiment. In the former, we find that the introduction of oscillator networks significantly increases the proportion of the model's parameter space that features some form of synchronization, indicating a greater ability of the processes to resist external perturbations, a crucial behavior in biological settings. For the latter, we analyse the oscillations of the experiment, finding a characteristic frequency of 0.01–0.02 Hz. We further demonstrate that an output of the model comparable to the measurements of the experiment oscillates in a manner similar to the measured data, achieving this with fewer parameters and greater flexibility than the comparable model. Frontiers Media S.A. 2021-01-28 /pmc/articles/PMC7876325/ /pubmed/33584336 http://dx.doi.org/10.3389/fphys.2020.613183 Text en Copyright © 2021 Rowland Adams and Stefanovska. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Physiology
Rowland Adams, Joe
Stefanovska, Aneta
Modeling Cell Energy Metabolism as Weighted Networks of Non-autonomous Oscillators
title Modeling Cell Energy Metabolism as Weighted Networks of Non-autonomous Oscillators
title_full Modeling Cell Energy Metabolism as Weighted Networks of Non-autonomous Oscillators
title_fullStr Modeling Cell Energy Metabolism as Weighted Networks of Non-autonomous Oscillators
title_full_unstemmed Modeling Cell Energy Metabolism as Weighted Networks of Non-autonomous Oscillators
title_short Modeling Cell Energy Metabolism as Weighted Networks of Non-autonomous Oscillators
title_sort modeling cell energy metabolism as weighted networks of non-autonomous oscillators
topic Physiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7876325/
https://www.ncbi.nlm.nih.gov/pubmed/33584336
http://dx.doi.org/10.3389/fphys.2020.613183
work_keys_str_mv AT rowlandadamsjoe modelingcellenergymetabolismasweightednetworksofnonautonomousoscillators
AT stefanovskaaneta modelingcellenergymetabolismasweightednetworksofnonautonomousoscillators