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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.
Laser microdissection combined with lectin microarray (LMD-LMA) precisely profiles spatial glycosylation in formalin-fixed paraffin-embedded tissues. This method enables detailed tissue glycome mapping for enhanced biological interpretation in spatial omics.
Area of Science:
- Biochemistry
- Molecular Biology
- Histology
Background:
- Formalin-fixed paraffin-embedded (FFPE) tissues are widely available and preserve tissue architecture.
- Spatial glycomics requires precise isolation of microscale tissue regions.
- Laser microdissection (LMD) and lectin microarray (LMA) are key technologies for glycomic profiling.
Purpose of the Study:
- To present detailed protocols for integrating LMD with LMA (LMD-LMA) for spatial glycomic profiling.
- To optimize LMD-LMA workflow using an advanced evanescent-field fluorescence scanner.
- To enable precise and reproducible glycomic profiling of microscale tissue regions.
Main Methods:
- Developed three LMD-LMA approaches: morphology-guided, probe-guided on serial sections, and direct dissection from stained sections.
- Optimized workflow with a high-end evanescent-field fluorescence scanner (GSR2300) for enhanced sensitivity and reduced noise.
- Standardized LMA pipeline: protein extraction, Cy3 labeling, lectin-glycoprotein interaction, fluorescence scanning, and data qualification.
Main Results:
- Achieved precise glycomic profiling of microscale tissue regions (~0.1 mm², 5 μm thickness).
- Revealed intra- and inter-tissue-specific glycosylation patterns.
- Generated shareable "tissue glycome mapping" datasets via LM-GlycoRepo and visualized through LM-GlycomeAtlas under FAIR principles.
Conclusions:
- LMD-LMA provides a plug-and-play protocol for spatial glycomics, compatible with existing LMD pipelines.
- Enables co-registered datasets for spatial transcriptomics and proteomics by mirroring microdissected regions.
- Encourages integration of glycan information into broader spatial omics workflows for enhanced biological interpretation.
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