Bond graph modelling of chemoelectrical energy transduction. Issue 5 (1st October 2017)

• Record Type: Journal Article
• Authors: Gawthrop, Peter J.; Siekmann, Ivo; Kameneva, Tatiana; Saha, Susmita; Ibbotson, Michael R.; Crampin, Edmund J.
• Is Part Of: IET systems biology. Volume 11:Issue 5(2017)
• Page Start: 127
• Page End: 138
• Publication Date: 2017-10-01
• Subjects: molecular biophysics -- biochemistry -- bioelectric potentials -- biomembrane transport -- sodium -- neurophysiology -- eye; energy‐based bond graph modelling -- chemoelectrical energy transduction -- biomolecular systems -- integrated thermodynamically compliant modelling -- chemoelectrical systems -- excitable membranes -- membrane action potential -- energy consumption -- healthy neurons -- diseased neurons -- healthy retinal ganglion cells -- degenerative retinal ganglion cells -- Na; Systems biology -- Periodicals; Cell physiology -- Periodicals; Biological systems -- Mathematical models -- Periodicals; Genetics -- Mathematical models -- Periodicals; Computational biology -- Periodicals; 573
• DOI: 10.1049/iet-syb.2017.0006
• Languages: English
• ISSNs: 1751-8849

Abstract

Abstract : Energy‐based bond graph modelling of biomolecular systems is extended to include chemoelectrical transduction thus enabling integrated thermodynamically compliant modelling of chemoelectrical systems in general and excitable membranes in particular. Our general approach is illustrated by recreating a well‐known model of an excitable membrane. This model is used to investigate the energy consumed during a membrane action potential thus contributing to the current debate on the trade‐off between the speed of an action potential event and energy consumption. The influx of N a + is often taken as a proxy for energy consumption; in contrast, this study presents an energy‐based model of action potentials. As the energy‐based approach avoids the assumptions underlying the proxy approach it can be directly used to compute energy consumption in both healthy and diseased neurons. These results are illustrated by comparing the energy consumption of healthy and degenerative retinal ganglion cells using both simulated and in vitro data.