Fig. 3

ApoeCh increases disease-associated microglia number in response to plaques. a Representative confocal images of the subiculum stained for dense-core plaques with AmyloGlo (green) and immunolabeled for GFAP (red, a) and IBA1 (red, c) of 12-mo-old WT, ApoeCh, 5xFAD, and 5xFAD;ApoeCh mice. Scale bar = 100 µm. b, d Quantification of total volume of GFAP⁺ cells (b) and IBA1⁺ cells (d). Sex of individual animals is denoted by pink (female) or blue (male) circles. n = 4–6 mice/sex/genotype. Data are represented as mean ± SEM. Two-way ANOVA followed by Tukey’s post hoc tests to examine biologically relevant interactions. Statistical significance is denoted by *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001.e Workflow for targeted 67-plex single-cell spatial proteomics. Fields-of-view (FOVs) are first imaged with GFAP, NEUN, RPS6, and IBA1 markers for cell segmentation. Protein abundance is determined by counting the number of fluorescently-labelled oligos in each cell. Cell types are identified with the CELESTA algorithm, which classifies cells based on marker protein expression. f Cell types in XY space. CELESTA classifies cells into 12 different cell types, which can then be plotted in space to confirm accurate identification. Non-DAM microglia are unable to be identified using CD11b as a marker; only DAM are shown. g Proportions of 5xFAD;ApoeCh, 5xFAD, ApoeCh, and WT cells for each major cell type. h Aggregate expression of the top differentially expressed proteins in DAMs and astrocytes across the four genotypes. i-l Immunofluorescence images of MHCII, CD11c, CD68, and APOE for representative brains of WT, ApoeCh, 5xFAD, and 5xFAD;ApoeCh mice