Modeling Maize Root-Associated Bacterial Interactions
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Authors
Phillip, Henry
Date of Issue
2022
Type
Presentation
Language
en
Subject Keywords
Other Titles
Abstract
A commonly unknown contributor toward plant growth is the microbial community that exists within the soil. The microbial community is composed of bacteria, fungi, protozoa, and archaea. The interaction between members of the microbial community and the associated plant is not clearly understood. In this study, seven key bacteria associated with the maize plant root were used to begin understanding and predicting potential interactions using KBase, a biological computation modeling program. Individual models of the metabolism of each bacterial species were created using their sequenced genome along with a designed nutrient medium, followed by the creation of two and three member community models. Each model was analyzed using flux balance analysis (FBA), a linear programming algorithm that optimizes the bacterial metabolic process for a specific objective such as biomass optimization. FBA simulations developed a complex nutrient exchange (amino acids, carbon sources, and vitamins) prediction that was used to create maps to simplify the interpretation of bacterial interactions. Collaborators at North Carolina State University use the models to improve the design of experimental trials and increase the rate of discovery. Improved understanding of the interaction between the microbial community and the plant can benefit agricultural production efficiency.