Glyco-PAINT-APP: Subcellular analysis of immune cell-lectin binding enables correlation of glycan binding parameters to receptor biology

Extracting single-molecule glycan binding data from primary cells has not been possible to date. Here, we present Glyco-PAINT-APP (Automated Processing Pipeline), an automated method that enables the extraction of subcellular glycan interaction kinetics using a Points Accumulation for Imaging in Nano-Topography (PAINT)-based approach. This approach leverages an algorithm for precise, high-throughput subcellular analysis of glycan binding dynamics, facilitating the exploration of functional correlations between glycoform binding patterns and immune cell polarization. Using synthetic glycans and glycosylated antigens, we demonstrate the ability of the technique to automatically correlate high glycan binding regions in dendritic cells with increased uptake and cross-presentation efficiency of these antigens. Additionally, we show how the method can uncover subtle differences in glycan binding preferences between resting and polarized macrophages. Taken together, Glyco-PAINT-APP has the potential to enable new insights into the cell-intrinsic heterogeneity of glycan-structure-activity relationships in immune cells.