@article{GawPanRaj25,
author = {Gawthrop, Peter J. and Pan, Michael and Rajagopal, Vijay },
title = {Energy-based modelling of single actin filament polymerization using bond graphs},
journal = {Journal of The Royal Society Interface},
volume = 22,
number = 222,
pages = 20240404,
year = 2025,
doi = {10.1098/rsif.2024.0404},
abstract = { Bond graphs provide an energy-based methodology for modelling complex systems hierarchically; at the moment, the method allows biological systems with both chemical and electrical subsystems to be modelled. Herein, the bond graph approach is extended to include chemomechanical transduction thus extending the range of biological systems to be modelled. Actin filament polymerization and force generation is used as an example of chemomechanical transduction, and it is shown that the TF (transformer) bond graph component provides a practical, and conceptually simple, alternative to the Brownian ratchet approach of Peskin, Odell, Oster and Mogilner. Furthermore, it is shown that the bond graph approach leads to the same equation as the Brownian ratchet approach in the simplest case. The approach is illustrated by showing that flexibility and non-normal incidence can be modelled by simply adding additional bond graph components and that compliance leads to non-convexity of the force–velocity curve. Energy flows are fundamental to life; for this reason, the energy-based approach is utilized to investigate the power transmission by the actin filament and its corresponding efficiency. The bond graph model is fitted to experimental data by adjusting the model physical parameters. }
}
@article{GawPan25,
author = {Gawthrop, Peter and Pan, Michael },
title = {Energy-based analysis of biochemical oscillators using bond graphs and linear control theory},
journal = {Royal Society Open Science},
volume = 12,
number = 4,
pages = 241791,
year = 2025,
doi = {10.1098/rsos.241791},
abstract = { The bond graph approach has been recognized as a useful conceptual basis for understanding the behaviour of living entities modelled as a system with hierarchical interacting parts exchanging energy. One such behaviour is oscillation, which underpins many essential biological functions. In this paper, energy-based modelling of biochemical systems using the bond graph approach is combined with classical feedback control theory to give a novel approach to the analysis, and potentially synthesis, of biochemical oscillators. It is shown that oscillation is dependent on the interplay between active and passive feedback and this interplay is formalized using classical frequency-response analysis of feedback systems. In particular, the phase margin is suggested as a simple scalar indicator of the presence or absence of oscillations; it is shown how this indicator can be used to investigate the effect of both the structure and parameters of biochemical system on oscillation. It follows that the combination of classical feedback control theory and the bond graph approach to systems biology gives a novel analysis and design methodology for biochemical oscillators. The approach is illustrated using an introductory example similar to the Goodwin oscillator, the Sel’kov model of glycolytic oscillations and the repressilator. }
}
@article{PanGawFar25,
author = {Pan, Michael and Gawthrop, Peter J. and Faria, Matthew and Johnston, Stuart T. },
title = {Thermodynamically consistent, reduced models of gene regulatory networks},
journal = {Royal Society Open Science},
volume = 12,
number = 7,
pages = 241725,
year = 2025,
doi = {10.1098/rsos.241725},
abstract = { Synthetic biology aims to engineer novel functionalities
into biological systems. While the approach has been
predominantly applied to single cells, a richer set
of biological phenomena can be engineered by
applying synthetic biology to cell populations. To
rationally design cell populations, we require
mathematical models that link between intracellular
biochemistry and intercellular interactions. In this
study, we develop a kinetic model of gene expression
that is suitable for incorporation into agent-based
models of cell populations. To be scalable to large
cell populations, models of gene expression should
be both computationally efficient and compliant with
the laws of physics. We satisfy the first
requirement by applying a model reduction scheme to
translation and the second requirement by
formulating models using bond graphs, a modelling
approach that ensures thermodynamic consistency. Our
reduced model is significantly faster to simulate
than the full model and reproduces important
behaviours of the full model. We couple separate
models of gene expression to build models of the
toggle switch and repressilator. With these models,
we explore the effects of resource availability and
cell-to-cell heterogeneity on circuit behaviour. The
modelling approaches developed here are a bridge
towards engineering collective cell behaviours such
as synchronization and division of labour.
}
}
@article{MalGugHun25,
author = {Malecki, Cassandra and Guglielmi, Giovanni and Hunter, Benjamin and Harney, Dylan and Koay, Yen Chin and Don, Anthony. S. and Han, Oscar and Khor, Jasmine and Nguyen, Lisa and Pan, Michael and Gawthrop, Peter and Isles, Nathan and Chung, Joshua and Hume, Robert. D. and Taper, Matthew and Wang, XiaoSuo and Larance, Mark and Spill, Fabian and Rajagopal, Vijay and O’Sullivan, John F. and Lal, Sean},
title = {The Human Cardiac “Age-OME”: Age-Specific Changes in Myocardial Molecular Expression},
journal = {Aging Cell},
volume = {n/a},
number = {n/a},
year = 2025,
pages = {e70219},
keywords = {ageing, age-OME, excitation-contraction coupling, human heart, metabolism, omics},
doi = {https://doi.org/10.1111/acel.70219},
note = {e70219 ACE-24-1128-RAr},
abstract = {Ageing is one of the most significant risk factors for heart disease; however, it is still not clear how the human heart changes with age. Taking advantage of a unique set of pre-mortem, cryopreserved, non-diseased human hearts, we performed omics analyses (transcriptomics, proteomics, metabolomics, and lipidomics), coupled with biologically informed computational modelling in younger (<25~years~old) and older hearts (>50~years~old) to describe the molecular landscape of human cardiac ageing. In older hearts, we observed a downregulation of proteins involved in calcium signalling and the contractile apparatus. Furthermore, we found a potential dysregulation of central carbon generation of fuel, glycolysis, and fatty acids oxidation, along with an increase in long-chain fatty acids. This study presents and analyses the first molecular data set of normal human cardiac ageing, which has relevant implications for understanding the human cardiac ageing process and the development of age-related heart disease.}
}
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