Aim 3: Gene & Pathway Discovery

Our Gene and Pathway Discovery aim focuses on uncovering the genetic and enzymatic pathways responsible for the biosynthesis of key bioactive compounds. By integrating advanced technologies and AI tools, we aim to map these pathways, enabling further exploration of bioactive compounds for sustainable agriculture.

Research Goals & Approach

1. Annotating Gene-Metabolite Relationships

Our team leverages advanced AI tools like FuncFetch to screen scientific literature for enzyme-metabolite interactions. FuncFetch extracts enzyme activity and sequence data from thousands of manuscripts, providing a rich dataset of enzyme-substrate interactions. By integrating these findings with genomic diversity data such as the Darwin Tree of Life and crop diversity panels, we identify genes and pathways that synthesize prioritized bioactive metabolites. These efforts address the complexities of plant metabolite biosynthesis, which is characterized by regulatory and chemical challenges, enabling the discovery of novel pathways for metabolic engineering.

2. Modeling Gene-Metabolite Networks

We use RNA-seq and LC-MS/MS data to construct Gene Regulatory Networks (GRNs) that link DNA, proteins, and metabolites under specific conditions. By applying advanced methods like mutual rank-based co-expression, DIABLO, and Inferelator 3.0, we integrate multi-omic datasets to identify stress-responsive metabolites and their regulatory elements. This approach enables us to prioritize enzymes and transcription factors that regulate metabolite production, providing targets for engineering pathways that enhance crop resilience and stress tolerance.

3. Characterizing Biosynthetic Gene Clusters (BGCs)

​We investigate unique compounds produced by extremophilic microbes from polar regions, where harsh conditions drive the evolution of specialized metabolites. In collaboration with the Korean Polar Research Institute, we analyze the genomes and metabolomes of approximately 300 microbes isolated from Arctic and Antarctic environments. Using HRMS, we generate detailed metabolomic fingerprints for each species under standard growth conditions. These analyses aim to identify metabolites with potential applications in enhancing crop resilience. Although the direct path to agricultural application may be longer for these microbial-derived compounds, they are crucial for identifying biosynthetic gene clusters and engineering pathways for novel bioactives. This integration of microbial diversity enriches our catalog and provides valuable leads for future research in metabolic engineering and resilience strategies.

4. Developing Visualization Platforms

To facilitate exploration of the multi-omics data generated, we are expanding the Bio-Analytic Resource with advanced visualization tools. These include integration with platforms like CELLxGENE Explorer for single-cell and single-nucleus datasets. These tools enable researchers to visualize metabolite and gene expression networks interactively, integrating findings from the Center to support the design of metabolic engineering strategies and deepen our understanding of complex biosynthetic pathways.

Outcomes & Impact

Our efforts will result in a comprehensive workflow for connecting bioactive compounds with their biosynthetic pathways. By identifying key gene targets, mapping regulatory networks, and characterizing gene clusters, we provide a foundation for pathway engineering and the sustainable production of bioactive metabolites. These advancements support our Center’s broader goals of enhancing crop resilience, driving innovation in sustainable agriculture, and advancing synthetic biology applications.