AI Insight
Researchers developed Lectin-IMC, a new imaging technique that maps disease-related sugar modifications (glycans) on proteins within tissue samples while preserving spatial information about cell types and tissue structure. Using a heart disease model, they demonstrated that this method can identify specific glycan patterns associated with fibrotic tissue and link them to particular proteins like periostin and specific cell types such as myofibroblasts. The framework enables stepwise discovery of disease-associated glycan alterations and their spatial validation in tissue microenvironments.
Why it matters
This integrated approach could accelerate the translation of glycan-based discoveries into diagnostic markers and therapeutic targets by providing spatial context that connects sugar modifications to specific proteins, cell types, and disease processes. The method was successfully applied to both animal models and human tissue samples, suggesting broad applicability for studying glycosylation in various diseases.
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⚠️ Preprint – Noch nicht peer-reviewed
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Understanding the pathological significance of protein glycosylation and translating disease-associated glycan alterations into diagnostic and therapeutic opportunities require integrated analysis of glycans, their carrier glycoproteins, and spatial context. Here, we present an expanded multimodal glycoprotein analysis framework incorporating lectin-assisted imaging mass cytometry (Lectin-IMC) for stepwise discovery and spatial validation of disease-associated glyco-niches. Disease-associated glycans identified by laser microdissection-assisted lectin microarray (LMD-LMA) tissue glycome mapping are spatially evaluated by Lectin-IMC in relation to cell types and tissue microenvironments, and candidate carrier glycoproteins identified by MS-based glycoproteomics are subsequently incorporated for higher-order evaluation of glycan-protein-cell type relationships. Multiplex panel design is guided by LMA-based assessment of lectin-lectin interactions and biologically informed probe selection. Using a dilated cardiomyopathy model, we constructed a five-lectin panel centered on Wisteria floribunda agglutinin (WFA), which recognizes fibrosis-associated asialo N-glycans identified previously. Glycan-dependent WFA detection was validated by competitive inhibition and PNGase F treatment, and WFA-reactive glycans were spatially associated with fibrotic regions containing ACTA2VIM myofibroblast-like cells. Among six extracellular matrix glycoprotein candidates identified in WFA-binding fractions, periostin showed the strongest spatial correspondence with WFA-positive regions by pixel-based quantitative analysis and was further associated with ACTA2VIMWFA fibrotic microenvironments. The optimized Lectin-IMC panel was also transferable to a human FFPE cardiomyopathy specimen. Collectively, Lectin-IMC provides intuitive spatial visualization and interpretability of glycan-protein-cell type relationships and serves as an on-tissue spatial validation and prioritization layer within an iterative multimodal framework in which spatially defined glyco-niches can guide subsequent proteomic or glycoproteomic discovery.