Genome-Scale Metabolic Networks in Plants
A special issue of Metabolites (ISSN 2218-1989). This special issue belongs to the section "Plant Metabolism".
Deadline for manuscript submissions: 15 June 2025 | Viewed by 5
Special Issue Editors
Interests: abiotic stress; biotic stress; plant; genomics; nitrogen fixation; cereal crop; plant development
Special Issue Information
Dear Colleagues,
Genome-scale Metabolic Network (GSMN) in plants refers to a comprehensive model that maps all the biochemical reactions, metabolites, and genes involved in the metabolism of a plant organism. It integrates genomic data, metabolic pathways, and enzyme functions to provide a system-level view of a plant's metabolism, from primary to secondary metabolism. The model typically represents the flow of metabolites through the network of metabolic reactions, with the reactions governed by the presence of specific enzymes, which are encoded by genes. These metabolic networks are often constructed using data derived from the plant's genome, transcriptome, and other omics approaches. Key features of Genome-Scale Metabolic Networks in plants include a detailed collection of biochemical pathways involved in the plant’s metabolism, such as carbon, nitrogen, sulphur, and lipid metabolism. They link metabolic reactions to specific genes and the proteins they encode, which catalyse these reactions. The network typically includes stoichiometric relationships between metabolites and the constraints governing reaction rates, such as enzyme capacity or thermodynamic feasibility. A computational approach is often used to predict the flow of metabolites through the network, helping to understand metabolic behaviour under different conditions. GSMNs are used in metabolic engineering to design plants with enhanced traits (e.g., improved stress resistance, higher yield, or the production of biofuels or pharmaceuticals). In summary, a Genome-Scale Metabolic Network in plants is a powerful tool to study and manipulate the complex biochemical systems that drive plant growth, development, and response to environmental stimuli.
Dr. Akhilesh Yadav
Dr. Dawei Yan
Guest Editors
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Keywords
- metabolites
- genomics
- transcriptomics
- omics
- pathway
- network
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