Fig. 4

Cell-type analysis of proteins identified by in vivo glycocapture though comparison to single-cell RNAseq data. A For each in vivo glycocapture dataset, the identified proteins were aligned to the genes that were detected by single-cell RNAseq in individual cell clusters using data from the Allen Brain Atlas. The percent of genes detected by scRNAseq (with a read count > 0) in each cell count that were identified in the glycocapture dataset are shown. Statistical analysis comparing all cell types was performed to identify cell types that are outliers. These outlier cell types are labelled and include endothelial cells (Endo), smooth muscle cells-pericytes (SMC-Peri), vascular lepotomeningeal cells (VLMC), micro-perivascular macrophages (Micro-PVM), and astrocytes (Astro), oligodendrocytes (Oligo), and Cajal-Retzius cells (CR). B The same analysis described in panel A was repeated using the brain lysate glycocapture datasets. None of the cell types were tagged as outliers. A few cell types showing trends towards over or under representation are labelled. C The percentage of identified signature genes associated with each cell type in the listed proteomic dataset: in vivo glycocapture (light green bar), in vivo glycocapture with a vessel enrichment score > 1000 (dark green bar), or brain lysate glycocapture (brown bar). Combined species data was used for the analysis and only cell types that had at least 5% identified signature genes in at least one dataset were included in the graph. D The difference in percent identified signature genes between the in vivo glycocapture dataset and the brain lysate glycocapture dataset for all identified in vivo glycocapture proteins and identified in vivo glycocapture proteins with a vessel enrichment score > 1000, for the cell types listed in panel C