임현준 (서울대학교)

임현준 (서울대학교)

Recent advances in spatial multi-omics technologies have enabled high-dimensional molecular profiling, offering new opportunities to interrogate complex biological systems. However, most existing spatial multi-omics approaches acquire different molecular layers such as transcriptomics, proteomics, metabolomics, and lipidomics from separate tissue sections. This heterogeneity introduces misalignment between molecular layers, masks true molecular co-localization, and limits accurate cross-omics integration. Here, we present a spatial multi-omics platform that integrates lipidomics and metabolomics using Desorption Electrospray Ionization Mass Spectrometry Imaging (DESI-MSI), transcriptomics using Fluorescence In Situ Hybridization (FISH), and proteomics using Matrix-Assisted Laser Desorption Ionization Mass Spectrometry Imaging (MALDI-MSI) formed within a single tissue. We demonstrated that, in the sequential workflow, preceding modalities do not interfere molecular signals measured by subsequent modalities, and confirmed that signals are preserved across all omics layers. We applied this platform to mouse brain tissue, focusing on myelinated regions where coordinated spatial organization of lipids, metabolites, RNAs, and proteins is essential for rapid neuronal conduction. Compared with analyses performed on adjacent tissue sections, single-section spatial multi-omics resulted in significantly higher Pearson correlation coefficients, improved geometry-based alignment accuracy. These results demonstrate that spatial multi-omics performed on a single tissue section not only improves quantitative accuracy, but also preserves native spatial relationships that are critical for interpreting coordinated molecular function in complex tissues.

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