Developing a Maize Metabolic Model to Study Root Microbiome Interactions
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Authors
Melton, Trey
Date of Issue
2025-04-25
Type
Presentation
Language
en_US
Subject Keywords
Other Titles
Abstract
Microbiomes are an essential part of the biological functions of many complex organisms. The microbes that comprise these microbiomes work in tandem with their host by exchanging metabolites for mutual survival. As such, metabolic models, which contain a system of reactions that represent the metabolic pathways in an individual organism or a community of organisms, can provide insight into how microbiomes function. A synthetic subset of the maize root-associated microbiome has been previously studied, providing a baseline for understanding the assembly and composition of this community. Whereas previous work for this system has focused on bacterial models, both individually and as a community, this study specifically aimed to construct a metabolic model of the key carbon pathways of the maize plant as whole (including roots and shoots). The biochemical reactions were assembled and organized in Google Sheets by exporting reactions from metabolic databases and tools, including KBase, MetaCyc, and KEGG, and subsequently converted to SBML files in MATLAB. The model was then analyzed in CNApy using flux balance analysis (FBA), a linear programming algorithm that optimizes the metabolic processes for a specific objective such as biomass production. Altogether, this work provided a model of plant metabolism that can intersect with the previously developed bacterial models for more holistic simulations. Collaborators at North Carolina State University are using the models to improve the design of experimental trials and discover metabolic drivers of plant-microbe interactions. Improved understanding of the interaction between the microbial community and the plant can benefit agricultural production efficiency.