PLANT PHYSIOLOGY · 2014 · 207 citations · 41 references
Life SciencesPlant BiologyPlant SciencesMetabolismPhotosynthesisPlant EcophysiologyFlux Balance AnalysisLeaf PhysiologyPhotosynthesis BiochemistryPhotosynthesis ModelingPhotosynthetic MetabolismPlant MetabolismDiel MetabolismDynamic Photosynthesis ModelsFacultative Crassulacean Acid MetabolismLeaf Photosynthesis ModelingMetabolic Flux Balance AnalysisMetabolic Flux PartitioningMetabolic Flux RegulationPhotosynthesis-light Response
Abstract Although leaves have to accommodate markedly different metabolic flux patterns in the light and the dark, models of leaf metabolism based on flux-balance analysis (FBA) have so far been confined to consideration of the network under continuous light. An FBA framework is presented that solves the two phases of the diel cycle as a single optimization problem and, thus, provides a more representative model of leaf metabolism. The requirement to support continued export of sugar and amino acids from the leaf during the night and to meet overnight cellular maintenance costs forces the model to set aside stores of both carbon and nitrogen during the day. With only minimal constraints, the model successfully captures many of the known features of C3 leaf metabolism, including the recently discovered role of citrate synthesis and accumulation in the night as a precursor for the provision of carbon skeletons for amino acid synthesis during the day. The diel FBA model can be applied to other temporal separations, such as that which occurs in Crassulacean acid metabolism (CAM) photosynthesis, allowing a system-level analysis of the energetics of CAM. The diel model predicts that there is no overall energetic advantage to CAM, despite the potential for suppression of photorespiration through CO2 concentration. Moreover, any savings in enzyme machinery costs through suppression of photorespiration are likely to be offset by the higher flux demand of the CAM cycle. It is concluded that energetic or nitrogen use considerations are unlikely to be evolutionary drivers for CAM photosynthesis.
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