Carroll College

Awards Issued Prior to January 20, 2025, Were Funded Under Previous Administrations and May Not Reflect the Priorities and Policies of the Current Administration. Microbial Communities Play a Crucial Role in Plant Health and Resilience to Both Abiotic and Biotic Environmental Stresses. to Address Rising Global Food Security Concerns, It Is Critical to Gain a More Comprehensive and Integrated Understanding of Plant-microbe Systems. Maize Is an Essential National and Global Agricultural Product Used to Satisfy Food as Well as Biofuel Needs, and the Impact of Both Abiotic and Biotic Stressors Significantly Undercuts Productivity. Although We Now Have the Ability to Well Characterize Microbial Community Composition, There Is Still a Critical Knowledge Gap in Our Understanding of the Interspecies Interactions That Influence Plant Growth and Resilience, as Well as How the Environment Can Alter These Interactions. the Proposed Research Seeks to Build a Predictive Model of Plant Root-microbe Interactions in Maize and Understand How They Are Impacted by Nutrient Limitations in Soil. to Accomplish This Goal, Computational Modeling of Metabolism Will Be Integrated With Controlled Laboratory Experiments. Metabolic Networks Will Be Constructed for Maize Root Cells and Seven Common Bacterial Root Colonizers to Form a Community Metabolic Model. the Model Will Be Analyzed Computationally to Simulate Possible Pathways Through the Network Converting Nutrients to Biomass and Byproducts. Simulated Pathways Will Be Analyzed for Their Ecological Efficiency to Predict Pathways Used Under Nutrient-limited Conditions and the Interactions Mediating Those Pathways. Experiments Will Complement the Model by Providing Community Abundance Data and Profiling Different Cellular Expression Levels (rna, Proteins, and Metabolites) on a Community Level, Which Will Be Used as Constraints to Experimentally Validate the Model Predictions.the Proposed Program Will Transform Our Ability to Predict, Understand, and Quantify Plant-microbe Nutrient Exchange in Response to Variable Environmental Conditions in Maize, Extending Computational Methods to Plant-microbe Systems and Creating a Structure to Harness the Power of Large Molecular Data Sets and Interpret Them in the Context of Microbial Community Functionality. This Will Improve Our Understanding of Maize Response to Nutrient Stress Conditions and the Role That Microbial Communities Play. Moreover, This Project Will Provide New Knowledge About the Interplay Between Different Levels of Cellular Expression (rna Transcripts, Protein Synthesis, Metabolite Abundance) by Collecting Extensive Corresponding Data Sets on a Single System to Better Understand the Patterns Between Different Levels of Cellular Expression and Activity. a Well-validated Model for Root-associated Microbiota Can Also Be Applied to Design Microbial Amendments or Biofertilizers to Improve Plant Health in Nutrient-poor Soils With High Likelihood of Establishment and Long-term Efficacy. Ultimately, the Methods and Concepts Will Be Translatable to Other Crop Systems and Will Contribute to Developing Microbial Strategies for Improving,growth and Managing Susceptibility to Pests and Pathogens in Sustainable Agricultural Practices.