All-optical multimodal mapping of single-cell-type-specific metabolic activities via REDCAT.

Abstract

Metabolism is fundamental to cell function, yet its activities vary across tissue environments. Resolving these processes in situ at single-cell resolution is crucial for understanding physiology in health and disease. However, existing methods lack biochemical specificity or direct linkage to cell identity. Here we report a method, Raman Enhanced Delineation of Cell Atlases in Tissues (REDCAT), an all-optical platform integrating Raman scattering microscopy and high-plex immunofluorescence to co-map metabolism and cell types. REDCAT achieves subcellular profiling of protein, lipid, nuclear metabolites and redox metabolism in human tissues. In lymph nodes, it revealed cell-type-specific metabolic specialization. In lymphoma, REDCAT uncovered profound reprogramming and transitional states during tumor transformation. In the liver, it resolved zonation-dependent metabolic gradients. By linking cell identity to spatial metabolic states, REDCAT provides a framework for studying immunity and cancer, offering a path to deciphering the metabolic basis of disease.