Cited by 63Microbial Metabolic Engineering and BioproductionPlant biochemistry and biosynthesisPlant nutrient uptake and metabolism

Plant Metabolic Modeling: Achieving New Insight into Metabolism and Metabolic Engineering

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Baghalian, Kambiz, Hajirezaei, Mohammad-Reza, Schreiber, Falk·2014·The Plant Cell

Abstract

Models are used to represent aspects of the real world for specific purposes, and mathematical models have opened up new approaches in studying the behavior and complexity of biological systems. However, modeling is often time-consuming and requires significant computational resources for data development, data analysis, and simulation. Computational modeling has been successfully applied as an aid for metabolic engineering in microorganisms. But such model-based approaches have only recently been extended to plant metabolic engineering, mainly due to greater pathway complexity in plants and their highly compartmentalized cellular structure. Recent progress in plant systems biology and bioinformatics has begun to disentangle this complexity and facilitate the creation of efficient plant metabolic models. This review highlights several aspects of plant metabolic modeling in the context of understanding, predicting and modifying complex plant metabolism. We discuss opportunities for engineering photosynthetic carbon metabolism, sucrose synthesis, and the tricarboxylic acid cycle in leaves and oil synthesis in seeds and the application of metabolic modeling to the study of plant acclimation to the environment. The aim of the review is to offer a current perspective for plant biologists without requiring specialized knowledge of bioinformatics or systems biology.

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Crossref · 10.1105/tpc.114.130328

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  • Kinetic models capture the response of enzymes, transporters, and electron transport chains to their substrates and effectors, and provide a powerful predictive tool for analyzing the response of the system to variable conditions.

    “Kinetic models capture the response of enzymes, transporters, and electron transport chains to their substrates and effectors, and they provide a powerful predictive tool for analyzing the response of the system to variable conditions (Baghalian et al., 2014).”

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Authors
Baghalian, K., Hajirezaei, M.-R., & Schreiber, F.
Affiliations
  • Islamic Azad University, Karaj (IR)
  • Leibniz-Institut für Pflanzengenetik und Kulturpflanzenforschung (IPK) (DE)
  • Monash University (AU)
Venue
The Plant Cell
Published
2014-10
Volume
26
Issue
10
Pages
3847-3866
ISSN
  • 1040-4651 (ISSN-L)
  • 1532-298X
OpenAlex
W2070154722
Cited by
63
References
5
Citations by year
2025: 5 · 2024: 4 · 2023: 4 · 2022: 2 · 2021: 10 · 2020: 4 · 2019: 6 · 2018: 4 · 2017: 9 · 2016: 7 · 2015: 7
FWCI
3.15
Type
journal article
Language
en
Open access
Locations
  • The Plant Cell (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
  • KOPS (University of Konstanz) (submittedVersion)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Microbial Metabolic Engineering and Bioproduction
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Plant biochemistry and biosynthesis
  • Life Sciences › Agricultural and Biological Sciences › Plant Science › Plant nutrient uptake and metabolism
Keywords
plant metabolic engineering, photosynthetic carbon metabolism, sucrose synthesis, TCA cycle, plant acclimation, plant systems biology, compartmentalized metabolism
MeSH terms
Adaptation, Physiological, Computer Simulation, Models, Biological, Plants, Genome, Plant, Computational Biology, Systems Biology, Metabolic Networks and Pathways, Metabolic Engineering

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