Ph.D.,South Dakota School of Mines & Technology
Integrative Computational and Biochemical Validation of Microbiome-Derived Metabolites in Neuropsychiatric Disorders
Europsychiatric disorders (NPDs), including major depressive disorder, autism spectrum disorder, schizophrenia, and bipolar disorder, are complex, multifactorial conditions with limited mechanistic treatment options. Growing evidence implicates the gut-brain axis and microbiome-derived metabolites as key modulators of neurochemical and neuroinflammatory pathways underlying these disorders. Building on an SD INBRE-supported 2025-2026 project that identified disease-associated microbial taxa and functional pathways using integrative machine learning approaches, this extension focuses on mechanistic validation of microbiome-derived metabolites using non-human experimental systems.
The proposed research advances prior computational discoveries through three interconnected tasks. First, previously prioritized microbial taxa and pathways will be systematically mapped to specific metabolites using curated pathway databases (e.g. KEGG adn MetaCyc) and targeted literature verification to generate an assay-ready, procurement-defined metabolite panel. Second, selected metabolite-enzyme interactions will be evaluated using molecular docking, molecular dynamics simulations, and pharmacokinetic analysis to assess binding stability, specificity, and blood-brain barrier-related properties. Third, top-ranked candidates will undergo functional validation using cell-free enzyme assays with commercially procured metabolites and purified enzymes to quantify modulation of enzymatic activity under controlled conditions.
This project directly supports the SD INBRE mission by combining innovation, core bioinformatics resource utilization, and undergraduate training. Students will be actively engaged in every stage-from dataset handling and functional assays and result interpretation-gaining hands-on experience in biomedical research. The project will foster a culture of inquiry-driven learning and mentorship while contributing open-access data and workflows for the broader scientific community. Results from this research may pave the way toward microbiome-based diagnostics and personalized interventions for neuropsychiatric disorders.