Correlating metabolites, lipids, and N-glycans in murine kidney microstructures via integrative mass spectrometry imaging

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Understanding how metabolites, lipids and glycans interact within tissues at the same cellular layer is key to uncovering their roles in health and disease. Herein, we present an integrative multi-omic mass spectrometry imaging (MSI) approach correlating metabolites, lipids and N-glycans, including their linkage-specific sialic acid information, in a single renal tissue section. Our protocol enables the sequential detection of hundreds of metabolites and lipids species alongside diverse glycosylation traits in small cell clusters across the kidney. Importantly, our pixel-to-pixel co-registration and clustering correlates glycans (recorded in positive mode MS), metabolites, and lipids (both in negative mode MS) across kidney microstructures. This analysis reveals strong association between taurine, TCA metabolites, sulfatides, and polyunsaturated phospholipids, and specific sialic acid linkages on N-glycans in the thick ascending limb and collecting ducts. The robust strategy maximizes molecular insights from scarcely available samples and offers a powerful tool for exploring tissue complexity in both normal and disease states. Authors provide a method to map metabolites, lipids and glycans from a single tissue section using mass spectrometry imaging. Applied on murine kidney, the method reveals how molecules across classes correlate in kidney microstructures.

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