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      AraGEM, a genome-scale reconstruction of the primary metabolic network in Arabidopsis.

      Plant physiology
      Arabidopsis, genetics, metabolism, Computational Biology, methods, Computer Simulation, Genome, Plant, Metabolic Networks and Pathways, Models, Genetic

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          Genome-scale metabolic network models have been successfully used to describe metabolism in a variety of microbial organisms as well as specific mammalian cell types and organelles. This systems-based framework enables the exploration of global phenotypic effects of gene knockouts, gene insertion, and up-regulation of gene expression. We have developed a genome-scale metabolic network model (AraGEM) covering primary metabolism for a compartmentalized plant cell based on the Arabidopsis (Arabidopsis thaliana) genome. AraGEM is a comprehensive literature-based, genome-scale metabolic reconstruction that accounts for the functions of 1,419 unique open reading frames, 1,748 metabolites, 5,253 gene-enzyme reaction-association entries, and 1,567 unique reactions compartmentalized into the cytoplasm, mitochondrion, plastid, peroxisome, and vacuole. The curation process identified 75 essential reactions with respective enzyme associations not assigned to any particular gene in the Kyoto Encyclopedia of Genes and Genomes or AraCyc. With the addition of these reactions, AraGEM describes a functional primary metabolism of Arabidopsis. The reconstructed network was transformed into an in silico metabolic flux model of plant metabolism and validated through the simulation of plant metabolic functions inferred from the literature. Using efficient resource utilization as the optimality criterion, AraGEM predicted the classical photorespiratory cycle as well as known key differences between redox metabolism in photosynthetic and nonphotosynthetic plant cells. AraGEM is a viable framework for in silico functional analysis and can be used to derive new, nontrivial hypotheses for exploring plant metabolism.

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          Arabidopsis,genetics,metabolism,Computational Biology,methods,Computer Simulation,Genome, Plant,Metabolic Networks and Pathways,Models, Genetic


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