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Updated: Feb 4, 2026

Spatial Molecular Imaging of the Glycome Using Mass Spectrometry
Published on: November 28, 2025
From Laser Microdissection to Spatial Glycomics: Lectin Microarray Protocols for Tissue Glycome Mapping with High-End
Patcharaporn Boottanun1,2, Sayaka Fuseya1, Atsushi Kuno1
1Cellular and Molecular Biotechnology Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki, Japan.
Abstract:
Formalin-fixed paraffin-embedded (FFPE) tissues offer key advantages such as broad availability, long-term preservation, and retention of tissue architecture, providing the substrate on which laser microdissection (LMD) turns spatial glycomics into practice. Integrating LMD into the lectin microarray workflow (LMD-LMA) enables precise and reproducible glycomic profiling of microscale tissue regions (~0.1 mm2 areas, 5 μm thickness), thereby revealing intra- and inter-tissue-specific glycosylation patterns.Here, we present detailed protocols for LMD-LMA methods optimized with a high-end evanescent-field fluorescence scanner (GSR2300), which improves sensitivity by detecting weak signals while reducing background noise. The workflow can be implemented through three approaches based on the dissection strategy: Method 1, morphology-guided dissection; Method 2, probe-guided dissection on serial sections; and Method 3, direct dissection from probe-stained sections. Regardless of the dissection method, tissue fragments follow a common LMA pipeline comprising protein extraction, Cy3 labeling, lectin-glycoprotein interaction on the array, fluorescence scanning, and data qualification. The resulting "tissue glycome mapping" datasets are shareable via LM-GlycoRepo and visualized through LM-GlycomeAtlas under FAIR (Findable, Accessible, Interoperable, Reusable) principles. Crucially, this protocol is plug-and-play with existing LMD pipelines: Microdissected regions can be mirrored across serial sections for spatial transcriptomics or proteomics, enabling co-registered datasets in which glycan motifs serve as anchors for biological interpretation. We encourage the broader spatial omics community to enrich current workflows with glycan information at minimal overhead.
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