Postdoctoral Researcher University of California San Diego, United States
Introduction: : Metabolism dictates a range of physiological functions in human health and disease. Metabolic activities vary substantially in different cell types and are influenced by local tissue environments. Despite latest advent in spatial omics to map cellular heterogeneity and neighborhoods, it is yet to connect cell type or state to metabolic function, ideally, cell-by-cell in same tissue section to unveil metabolic mechanisms in a cell-type-specific manner in complex tissue.
Materials and
Methods: : Here we present Raman Enhanced Delineation of Cell Atlases in Tissues (REDCAT) for spatially co-profiling metabolic activities and cell types via integration of all-optical multi-modal chemical imaging with high-plex immunofluorescence imaging on the same tissue section.Application to human normal and malignant lymphoid tissues maps metabolic processes including protein, nucleic acid, and lipid metabolism as well as intra-cellular lipid droplet (LD) diversity to all cell types and unveils metabolic reprogramming in lymphoma development and progression.
Results, Conclusions, and Discussions:: his platform allows us to spatially profile single-cell redox status and lipid metabolites. REDCAT not only tracks metabolic reprogramming during normal immune cell activation but also accurately delineates the metabolic features of tumor development and progression. Our study indicates that the important lipid species are still preserved in deparaffinized FFPE tissues, likely due to the compact cellular structure that retains small molecules during formalin fixation. Although such samples may not well suited for high coverage mass spec lipidomics, SRS allows for in situ imaging of major lipid metabolic processes such as lipid unsaturation, accumulation, LD formation, and spatial location. The capability of REDCAT to spatially explore lipid biology in FFPE tissues holds transformative potential for clinical histopathology research.
