Metabolic modeling identifies determinants of thermal growth responses in Arabidopsis thaliana Article Swipe

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Philipp Wendering , Gregory M. Andreou , Roosa A. E. Laitinen , Zoran Nikoloski ·

YOU? · · 2025 · Open Access · · DOI: https://doi.org/10.1111/nph.20420

Summary Temperature is a critical environmental factor affecting nearly all plant processes, including growth, development, and yield. Yet, despite decades of research, we lack the ability to predict plant performance at different temperatures, limiting the development of climate‐resilient crops. Further, there is a pressing need to bridge the gap between the prediction of physiological and molecular traits to improve our understanding and manipulation of plant temperature responses. Here, we developed the first enzyme‐constrained model of Arabidopsis thaliana 's metabolism, facilitating predictions of growth‐related phenotypes at different temperatures. We showed that the model can be employed for in silico identification of genes that affect plant growth at suboptimal growth temperature. Using mutant lines, we validated the genes predicted to affect plant growth, demonstrating the potential of metabolic modeling in accurately predicting plant thermal responses. The temperature‐dependent enzyme‐constrained metabolic model provides a template that can be used for developing sophisticated strategies to engineer climate‐resilient crops.

Related Topics

Arabidopsis Thaliana

In Silico

Biology

Computational Biology

Mechanical Engineering

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Arabidopsis thaliana In silico Arabidopsis Biology Computational biology Limiting Plant growth Phenotype Mutant Gene Biotechnology Biochemical engineering Genetics Botany Engineering Mechanical engineering

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Type: article
Language: en
Landing Page: https://doi.org/10.1111/nph.20420
OA Status: hybrid
Cited By: 7
References: 59
Related Works: 10
OpenAlex ID: https://openalex.org/W4406786657

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OpenAlex ID: https://openalex.org/W4406786657

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DOI: https://doi.org/10.1111/nph.20420

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Title: Metabolic modeling identifies determinants of thermal growth responses in Arabidopsis thaliana

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Type: article

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Language: en

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Publication year: 2025

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Publication date: 2025-01-24

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Authors: Philipp Wendering, Gregory M. Andreou, Roosa A. E. Laitinen, Zoran Nikoloski

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Landing page: https://doi.org/10.1111/nph.20420

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Open access: Yes

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OA status: hybrid

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OA URL: https://doi.org/10.1111/nph.20420

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Concepts: Arabidopsis thaliana, In silico, Arabidopsis, Biology, Computational biology, Limiting, Plant growth, Phenotype, Mutant, Gene, Biotechnology, Biochemical engineering, Genetics, Botany, Engineering, Mechanical engineering

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Cited by: 7

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References (count): 59

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Related works (count): 10

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