Cited by 353Microbial Metabolic Engineering and BioproductionBioinformatics and Genomic NetworksGene Regulatory Network Analysis

AraGEM, a Genome-Scale Reconstruction of the Primary Metabolic Network in Arabidopsis

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de Oliveira Dal'Molin, Cristiana Gomes, Quek, Lake-Ee, Palfreyman, Robin William, Brumbley, Stevens Michael, Nielsen, Lars Keld·2010·Plant Physiology

Abstract

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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Authors
de Oliveira Dal'Molin, C. G., Quek, L.-E., Palfreyman, R. W., Brumbley, S. M., & Nielsen, L. K.
Affiliations
  • Australian Institute for Bioengineering and Nanotechnology, University of Queensland, Brisbane, Queensland 4072, Australia
  • The University of Queensland (AU)
Venue
Plant Physiology
Published
2009-12-31
Volume
152
Issue
2
Pages
579-589
ISSN
  • 0032-0889 (ISSN-L)
  • 1532-2548
OpenAlex
W2133556195
Cited by
353
References
1
Citations by year
2026: 13 · 2025: 10 · 2024: 15 · 2023: 13 · 2022: 6 · 2021: 19 · 2020: 21 · 2019: 20 · 2018: 29 · 2017: 22 · 2016: 25 · 2015: 30 · 2014: 24 · 2013: 39 · 2012: 29
FWCI
9.00
Type
journal article
Language
en
Open access
Locations
  • PLANT PHYSIOLOGY (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Microbial Metabolic Engineering and Bioproduction
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
Keywords
genome-scale metabolic networks, Arabidopsis thaliana, primary metabolism, plant metabolism, metabolic flux analysis, photorespiration, redox metabolism, compartmentalized metabolism, metabolic network reconstruction, in silico metabolic modeling
MeSH terms
Computer Simulation, Models, Genetic, Arabidopsis, Genome, Plant, Computational Biology, Metabolic Networks and Pathways

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