Cited by 131Microbial Metabolic Engineering and BioproductionBioinformatics and Genomic NetworksGene Regulatory Network Analysis

Bottom-up Metabolic Reconstruction of Arabidopsis and Its Application to Determining the Metabolic Costs of Enzyme Production

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Arnold, Anne, Nikoloski, Zoran·2014·Plant Physiology

Abstract

Large-scale modeling of plant metabolism provides the possibility to compare and contrast different cellular and environmental scenarios with the ultimate aim of identifying the components underlying the respective plant behavior. The existing models of Arabidopsis (Arabidopsis thaliana) are top-down assembled, whereby the starting point is the annotated genome, in particular, the metabolic genes. Hence, dead-end metabolites and blocked reactions can arise that are subsequently addressed by using gap-filling algorithms in combination with species-unspecific genes. Here, we present a bottom-up-assembled, large-scale model that relies solely on Arabidopsis-specific annotations and results in the inclusion of only manually curated reactions. While the existing models are largely condition unspecific by employing a single biomass reaction, we provide three biomass compositions that pertain to realistic and frequently examined scenarios: carbon-limiting, nitrogen-limiting, and optimal growth conditions. The comparative analysis indicates that the proposed Arabidopsis core model exhibits comparable efficiency in carbon utilization and flexibility to the existing network alternatives. Moreover, the model is utilized to quantify the energy demand of amino acid and enzyme de novo synthesis in photoautotrophic growth conditions. Illustrated by the case of the most abundant protein in the world, Rubisco, we determine its synthesis cost in terms of ATP requirements. This, in turn, allows us to explore the tradeoff between protein synthesis and growth in Arabidopsis. Altogether, the model provides a solid basis for completely species-specific integration of high-throughput data, such as gene expression levels, and for condition-specific investigations of in silico metabolic engineering strategies.

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Crossref · 10.1104/pp.114.235358

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Authors
Arnold, A., & Nikoloski, Z.
Affiliations
Max Planck Institute of Molecular Plant Physiology (DE)
Venue
Plant Physiology
Published
2014-05-07
Volume
165
Issue
3
Pages
1380-1391
ISSN
  • 0032-0889 (ISSN-L)
  • 1532-2548
OpenAlex
W2055280476
Cited by
131
References
62
Citations by year
2026: 5 · 2025: 14 · 2024: 7 · 2023: 18 · 2022: 7 · 2021: 18 · 2020: 11 · 2019: 10 · 2018: 13 · 2017: 5 · 2016: 8 · 2015: 10 · 2014: 5
FWCI
3.83
Type
journal article
Language
en
Open access
Locations
  • PLANT PHYSIOLOGY (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
  • Max Planck Digital Library (submittedVersion)
  • MPG.PuRe (Max Planck Society) (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 › Bioinformatics and Genomic Networks
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
Keywords
Arabidopsis thaliana, biomass composition, carbon limitation, nitrogen limitation, photoautotrophic growth, ATP requirement, metabolic engineering

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