Abstract Global climate change will result in plants being subjected to abiotic stresses with greater frequency and intensity. Such stresses necessarily impact the metabolic network, both in terms of its structure and fluxes. The construction and analysis of Genome-Scale Metabolic Models (GEMs) has proved to be a useful tool 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. Whilst a growing field, the number of plant GEMs is lower than that of other taxa, and 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.
Mangaravite et al. (Fri,) studied this question.
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