Jianguo (Jeff) Xia

Our health and disease outcomes result from complex interactions between genetics and environmental factors, including pathogens, parasites, microbiome, diet, and chemical exposures. My research integrates computational, analytical, and experimental approaches to understand these gene-environment interactions for translational applications.

Computational: We develop scalable, user-friendly bioinformatics platforms to address big data challenges in metabolomics, microbiomics, transcriptomics, and multi-omics integration. Our suite of omics tools democratize omics analytics and serves approximately 1 million researchers worldwide.

Analytical: We develop high-throughput analytical workflows for global untargeted metabolomics based on our Q-Exactive Orbitrap systems. We have established robust protocols for analyzing complex biological samples including blood, milk, fecal samples, and cell cultures, supporting collaborations in microbiome research, nutrition studies, infectious diseases, cancer, diabetes, and autoimmune diseases. We joined The Metabolomics Innovation Center (TMIC) network in 2023.

Experimental: We use C. elegans and its native microbiome as a model system for aging and neurodegenerative diseases like Parkinson's disease. Through integrated RNAseq, metabolomics, and phenotypic screening, we have demonstrated that specific microbiome members significantly extend C. elegans lifespan through distinct metabolic pathways. We are developing stable isotope labeling metabolomics combined with genome-scale metabolic modeling to provide mechanistic insights.