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Demonstrates integrated spatial multi-omics profiling in mouse brain, indicating insights into biomolecular analysis.
Spatial multi-omics analyzes biomolecules such as the proteome, metabolome, and lipidome within their native spatial context in tissues or cells. Mass spectrometry imaging (MSI) has emerged as a powerful technique for mapping the region-specific molecular distribution in regions of interest (ROIs). Laser capture microdissection coupled with mass spectrometry (LCM-MS) is another well-established workflow, enabling the accurate characterization of biomolecules in ROIs. To advance the current analytical application, we expanded a matrix-assisted laser desorption/ionization (MALDI)-MSI-guided LCM-MS workflow for integrated multi-omics analysis and applied it to mouse brain tissue as a proof-of-principle validation. MALDI-MSI annotated 387 putative metabolites and lipids, revealing distinct molecular distributions between the cortex and hippocampus. Both regions were subsequently isolated as ROIs using LCM and analyzed by LC-MS/MS metabolomics, lipidomics, and proteomics to achieve accurate biomolecular profiling. LC-MS/MS metabolomics and lipidomics annotated 249 compounds, several of which exhibited distinct abundance patterns between the two regions. LC-MS/MS proteomics matched to over 3500 protein groups across the two regions. Biological network analysis revealed strong associations between molecular pathways and known region-specific phenotypes. Overall, this MALDI-MSI-guided LCM-MS workflow enables comprehensive spatial multi-omics profiling and quantitative biomolecular analysis, providing valuable insights into complex biological systems and spatial molecular organization.
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Cho et al. (2026) studied this question.
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