e1004703 Gerber.pdf (1.84 MB)
A thermodynamic model of monovalent cation homeostasis in the yeast Saccharomyces cerevisiae
journal contribution
posted on 2023-05-18, 18:03 authored by Gerber, S, Frohlich, M, Lichtenberg-Frate, H, Sergey ShabalaSergey Shabala, Svetlana ShabalaSvetlana Shabala, Klipp, ECationic and heavy metal toxicity is involved in a substantial number of diseases in mammals and crop plants. Therefore, the understanding of tightly regulated transporter activities, as well as conceiving the interplay of regulatory mechanisms, is of substantial interest. A generalized thermodynamic description is developed for the complex interplay of the plasma membrane ion transporters, membrane potential and the consumption of energy for maintaining and restoring specific intracellular cation concentrations. This concept is applied to the homeostasis of cation concentrations in the yeast cells of S. cerevisiae. The thermodynamic approach allows to model passive ion fluxes driven by the electrochemical potential differences, but also primary or secondary active transport processes driven by the inter- play of different ions (symport, antiport) or by ATP consumption (ATPases). The model - confronted with experimental data - reproduces the experimentally observed potassium and proton fluxes induced by the external stimuli KCl and glucose. The estimated phenomenological constants combine kinetic parameters and transport coefficients. These are in good agreement with the biological understanding of the transporters thus providing a better understanding of the control exerted by the coupled fluxes. The model predicts the flux of additional ion species, like e.g. chloride, as a potential candidate for counterbalancing positive charges. Furthermore, the effect of a second KCl stimulus is simulated, predicting a reduced cellular response for cells that were first exposed to a high KCl stimulus compared to cells pretreated with a mild KCl stimulus. By describing the generalized forces that are responsible for a given flow, the model provides information and suggestions for new experiments. Furthermore, it can be extended to other systems such as e.g. Candida albicans, or selected plant cells.
History
Publication title
PLoS Computational BiologyVolume
12Article number
e1004703Number
e1004703Pagination
1-23ISSN
1553-7358Department/School
Tasmanian Institute of Agriculture (TIA)Publisher
Public Library of SciencePlace of publication
United StatesRights statement
Copyright: © 2016 Gerber et al. Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0) http://creativecommons.org/licenses/by/4.0/Repository Status
- Open