Mapping the Invisible to Insight with Spatial Metabolome with MALDI Imaging
Sponsored by Bruker
Wednesday 22 October 2025
16.00 BST | 11.00 EST
Sponsor Webinar held on Zoom
Presented by Ramon C. Sun
Understanding how metabolites, lipids, and glycans shape physiology requires spatially resolved analysis across molecular classes. We developed a single-tissue workflow for spatial mass spectrometry imaging that captures the metabolome, lipidome, and glycome in parallel. This pipeline is powered by the Spatial Augmented Multiomics Interface (SAMI), a computational platform for multiomics integration, high-dimensional clustering, spatial annotation, and pathway enrichment. Using SAMI, we mapped metabolic diversity across brain regions and revealed distinct alterations in the Ps19 Alzheimer’s disease mouse model. To extend spatial biology beyond two dimensions, we created MetaVision3D, an AI-guided pipeline that transforms serial 2D MALDI-MS sections into high-resolution 3D spatial metabolomes. By aligning, normalizing, and interpolating tissue sections, MetaVision3D reconstructs tissue-wide metabolite distributions at submesoscale resolution. As proof of principle, we generated a 3D atlas of brain metabolism in normal and diseased mice, available as an interactive online resource. Together, these technologies provide a framework to explore spatial metabolic networks and illuminate biochemical complexity in health and disease.
SPEAKER BIO
Ramon C. Sun
Ramon Sun is a biochemist and molecular biologist specializing in metabolism and spatial biology. He earned his Ph.D. from the Australian National University and completed postdoctoral training at Stanford University. He is currently the Anne and Oscar Lackner Endowed Chair and Associate Professor of Biochemistry and Molecular Biology at the University of Florida College of Medicine. He also founded and directs the UF Center for Advanced Spatial Biomolecule Research (CASBR), a nationally leading facility dedicated to high-resolution spatial metabolomics and imaging mass spectrometry. Dr. Sun’s research focuses on how metabolic pathways influence physiology, signaling, and disease progression, particularly in the brain and cancer. His lab integrates spatial metabolomics with AI-driven analysis to uncover cell- and tissue-specific mechanisms underlying neurological, neoplastic, and age-related disorders.