Article Dans Une Revue PLoS Computational Biology Année : 2025

Multi-physics modeling for ion homeostasis in multi-compartment plant cells using an energy function

Résumé

Plant cells control their volume by regulating the osmotic potential of their cytoplasm and vacuole. Water is attracted into the cell as the result of a cascade of solute exchanges between the cell subcompartments and the cell surroundings, which are governed by chemical, electrostatic and mechanical forces. Due to this multi-physics aspect and to couplings between volume changes and chemical effects, modeling these exchanges remains a challenge that has only been partially addressed. As interest for multi-compartment models grows in the plant cell community, this challenge calls for new modeling strategies. In this paper, we introduce an energy-based approach to couple chemical, electrical and mechanical processes taking place between several subcompartments of a plant cell. The contributions of all physical effects are gathered in an energy function, which allows us to derive the equations satisfied by each variable in a systematic way. We illustrate the properties of this modular, unified approach on the modeling of ion and water transport in a guard cell during stoma opening. We represent the stoma opening process as a quasi-static evolution driven by hydrogen pumps in the plasma and vacuolar membranes, and we show that the new formalism explains why the system varies in a particular direction in response to perturbations. Additional numerical simulations allow us to investigate the role of each hydrogen pump in this process. Altogether, we show that this energy-based approach highlights a hierarchy between the forces involved in the system, and to dissect the role of each physical effect in the complex behavior of the system.

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Dates et versions

hal-04901993 , version 1 (01-02-2025)
hal-04901993 , version 2 (16-07-2025)

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Guillaume Mestdagh, Alexis de Angeli, Christophe Godin. Multi-physics modeling for ion homeostasis in multi-compartment plant cells using an energy function. PLoS Computational Biology, 2025, 21 (11), pp.e1013474. ⟨10.1371/journal.pcbi.1013474⟩. ⟨hal-04901993v2⟩
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