Genome-scale metabolic models in plant stress physiology: implications for future climate resilience
Global climate change will result in plants being subjected to abiotic stresses with greater frequency and intensity. Such stresses necessarily impact the metabolic network in terms of both its structure and fluxes. The construction and analysis of genome-scale metabolic models (GEMs) have proved to be useful for both the prediction of the effects of climate change on metabolism and identification of targets for breeding increased resilience. In this review, we first explain how such GEMs are constructed and how fluxes can be predicted, providing a detailed account of how models can be developed to capture metabolic variations across both space and time. Although GEMs are a growing field, the number of plant GEMs is lower than that of other taxa; here we discuss the reasons behind this disparity and propose solutions. We then highlight studies that have investigated the effects of changing CO2 concentrations, drought, and high temperature on metabolism, making use of innovations in the construction of context-specific and multi-organ models. CAM and C4 are also discussed as types of photosynthesis that are typically associated with tolerance of high temperatures and low water availability. Overall, we aim to demonstrate that plant GEMs can be a useful addition to the physiologist's toolkit and can generate important insights and testable hypotheses regarding plant responses to stress.
Authors
- Thomas Christopher Rhys Williams (ORCID: https://orcid.org/0000-0003-1954-2961)
- Eduardo Luís Menezes de Almeida
- Érica Mangaravite (ORCID: https://orcid.org/0000-0001-8129-778X)
- Christina Cleo Vinson (ORCID: https://orcid.org/0000-0001-8779-8075)
Institutions
- Universidade Federal de Viçosa (BR)
- Universidade de Brasília (BR)
- Universidade Federal do Pará (BR)
Publication Details
- Journal
- PLANT PHYSIOLOGY
- Published
- 2025-09-18
- DOI
- https://doi.org/10.1093/plphys/kiaf406
- Citations
- 2
- Primary Topic
- Microbial Metabolic Engineering and Bioproduction
- Type
- article
- Field-Weighted Citation Impact
- 1.61