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dc.contributor.authorBurgos, Asdrubal
dc.contributor.authorMiranda, Enoc
dc.contributor.authorVilaprinyo Terré, Ester
dc.contributor.authorMeza Canales, Iván David
dc.contributor.authorAlves, Rui
dc.description.abstractThe evolution of Crassulacean acid metabolism (CAM) by plants has been one of the most successful strategies in response to aridity. On the onset of climate change, expanding the use of water efficient crops and engineering higher water use efficiency into C3 and C4 crops constitute a plausible solution for the problems of agriculture in hotter and drier environments. A firm understanding of CAM is thus crucial for the development of agricultural responses to climate change. Computational models on CAM can contribute significantly to this understanding. Two types of models have been used so far. Early CAM models based on ordinary differential equations (ODE) reproduced the typical diel CAM features with a minimal set of components and investigated endogenous day/night rhythmicity. This line of research brought to light the preponderant role of vacuolar malate accumulation in diel rhythms. A second wave of CAM models used flux balance analysis (FBA) to better understand the role of CO2 uptake in flux distribution. They showed that flux distributions resembling CAM metabolism emerge upon constraining CO2 uptake by the system. We discuss the evolutionary implications of this and also how CAM components from unrelated pathways could have integrated along evolution.ca_ES
dc.publisherFrontiers Mediaca_ES
dc.relation.isformatofReproducció del document publicat a :
dc.relation.ispartofFrontiers in Plant Science, 2022, vol. 13ca_ES
dc.rightscc-by (c) Burgos, Miranda, Vilaprinyo, Meza-Canales and Alves, 2022ca_ES
dc.subjectCAM evolutionca_ES
dc.subjectODE modelsca_ES
dc.subjectFBA modelsca_ES
dc.subjectCarbon concentration mechanismca_ES
dc.titleCAM Models: Lessons and Implications for CAM Evolutionca_ES

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cc-by (c) Burgos, Miranda, Vilaprinyo, Meza-Canales and Alves, 2022
Except where otherwise noted, this item's license is described as cc-by (c) Burgos, Miranda, Vilaprinyo, Meza-Canales and Alves, 2022