Universität zu Köln

Machado, Tiago M. ORCID: 0000-0002-8497-9767, Töpfer, Nadine ORCID: 0000-0002-3027-5799 and Soltani, Fatemeh ORCID: 0000-0002-7039-0396 (2025). Metabolic modelling: Insights into the machine room of plant metabolism. Journal of Plant Physiology, 314. pp. 1-12. Elsevier. ISSN 0176-1617

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Abstract

[Artikel-Nr.: 154584] Plant growth, development, and environmental interactions is enabled through the coordinated activity of numerous biochemical reactions that constitute plant metabolic networks. The inherent complexity and inter- connectivity within these networks underscore the importance of investigating plant metabolism from a network perspective. Metabolic modelling provides a holistic in silico representation of plant metabolism, enabling mechanistic insights into network-level processes. In this review, we consolidate recent trends in plant metabolic modelling, highlighting how these approaches can be exploited to study metabolism from subcellular to com- munity and ecosystem levels. We discuss how the scope of plant metabolic modelling has broadened to represent diverse plant species, genotype- and context-specific metabolism as well as specialized metabolic pathways, and to capture spatiotemporal resolution and plant-microbe interactions. Moreover, we review machine learning and deep learning frameworks that assist model reconstruction, parameterization, and analysis, explore hybrid strategies that enhance mechanistic models, and address current challenges and future directions in the field of plant metabolic modelling.

Item Type:	Article
Creators:	Creators Email ORCID ORCID Put Code Machado, Tiago M. UNSPECIFIED https://orcid.org/0000-0002-8497-9767 UNSPECIFIED Töpfer, Nadine UNSPECIFIED https://orcid.org/0000-0002-3027-5799 UNSPECIFIED Soltani, Fatemeh UNSPECIFIED https://orcid.org/0000-0002-7039-0396 UNSPECIFIED
URN:	urn:nbn:de:hbz:38-809235
Identification Number:	10.1016/j.jplph.2025.154584
Journal or Publication Title:	Journal of Plant Physiology
Volume:	314
Page Range:	pp. 1-12
Number of Pages:	12
Date:	November 2025
Publisher:	Elsevier
ISSN:	0176-1617
Language:	English
Faculty:	Faculty of Mathematics and Natural Sciences
Divisions:	CEPLAS - Cluster of Excellence on Plant Sciences
Subjects:	Life sciences
Uncontrolled Keywords:	Keywords Language Plant metabolic modelling ; Constraint-based modelling ; Flux balance analysis ; Spatiotemporal metabolic models ; Plant-microbe interaction ; Multi-scale modelling English
['eprint_fieldname_oa_funders' not defined]:	Publikationsfonds UzK
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/80923