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. 2017 Oct 10;21(2):366-380.
doi: 10.1016/j.celrep.2017.09.039.

Temporal Tracking of Microglia Activation in Neurodegeneration at Single-Cell Resolution

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Free PMC article

Temporal Tracking of Microglia Activation in Neurodegeneration at Single-Cell Resolution

Hansruedi Mathys et al. Cell Rep. .
Free PMC article

Abstract

Microglia, the tissue-resident macrophages in the brain, are damage sensors that react to nearly any perturbation, including neurodegenerative diseases such as Alzheimer's disease (AD). Here, using single-cell RNA sequencing, we determined the transcriptome of more than 1,600 individual microglia cells isolated from the hippocampus of a mouse model of severe neurodegeneration with AD-like phenotypes and of control mice at multiple time points during progression of neurodegeneration. In this neurodegeneration model, we discovered two molecularly distinct reactive microglia phenotypes that are typified by modules of co-regulated type I and type II interferon response genes, respectively. Furthermore, our work identified previously unobserved heterogeneity in the response of microglia to neurodegeneration, discovered disease stage-specific microglia cell states, revealed the trajectory of cellular reprogramming of microglia in response to neurodegeneration, and uncovered the underlying transcriptional programs.

Keywords: Alzheimer’s disease; microglia; neurodegeneration; single-cell RNA sequencing.

Figures

Figure 1
Figure 1. Single-Cell RNA Sequencing of Microglia Cells Isolated from the Hippocampus of CK-p25 Mice and CK Control Littermates
(A) Workflow diagram for single-cell RNA sequencing of microglia cells isolated from the hippocampus of CK-p25 mice and CK control littermates at four different time points after p25 induction. (B) Quality of single-cell RNA sequencing. Scatterplots compare transcript expression (log10[FPKM+1]) between the average of 95 single-cells and a bulk population of 200 cells. The data from four representative animals are shown. (C) Heatmap showing the expression level of 86 microglia signature genes (yellow), genes preferentially expressed in peripheral immune cells (black), and natural killer cell and T cell signature genes (green) across the 1,685 CD11b- and CD45-positive cells analyzed in this study.
Figure 2
Figure 2. Non-linear Dimensionality Reduction Reveals Multiple Distinct and Disease Stage-Specific Microglia Cell States
(A) Clustering of 1,685 CD11b and CD45 double-positive cells isolated from the hippocampus into eight populations. The t-SNE plot shows a two-dimensional representation of global gene expression profile relationships among 1,685 cells. (B) Pie charts showing the composition of some of the clusters identified in (A). (C) Pie charts showing the distribution of each group of cells indicated across the clusters identified in (A) (excluding cluster 8). Cells are grouped by genotype and time point. (D) t-SNE plots as shown in (A). Cells isolated from CK control mice (at all four time points) and cells from CK-p25 mice 1, 2, and 6 weeks after p25 induction (0wk, 1wk, 2wk, and 6wk, respectively) are highlighted in red in individual panels.
Figure 3
Figure 3. Single-Cell Differential Expression Analysis Reveals Hundreds of Genes Regulated during Cellular Reprogramming of Microglia in Response to Neurodegeneration
(A–C) Bar plots showing the top 5 Gene Ontology (GO) terms (biological processes) associated with genes upregulated in (A) cluster 3 compared with cluster 2, (B) cluster 7 compared with cluster 2, and (C) cluster 6 compared with cluster 2. (D and E) Bar graphs showing the fold change in gene expression of the top upregulated genes associated with the top 10 GO terms in cells of cluster 3 (D) and cluster 7 (E) compared with cells of cluster 2. (F) Bar graph showing the fold change in gene expression of selected genes associated with the top 10 GO terms in cells of cluster 6 compared with cells of cluster 2. For all panels, error bars show the 95% confidence interval.
Figure 4
Figure 4. Temporally Distinct Transcriptional Dynamics among Immune Response-Related Genes during Micro-glia Activation
(A) Scatterplot comparing the fold change in gene expression in early- and late-response microglia for genes significantly differentially expressed. The genes significantly upregulated (with a certainty of 95%) in early- and late-response microglia are shown in orange. All other genes are shown in blue. Definition of early-response microglia: cells of cluster 3 that were isolated from CK-p25 mice 1 week after p25 induction (1wk CK-p25). Definition of late-response microglia: cells of cluster 6. (B and C) t-SNE plots as shown in Figure 2A. Selected genes showing early and consistent upregulation (B) and selected genes exclusively upregulated in the late-response cluster 6 (C) are shown. Data points are colored by the expression levels of the genes indicated.
Figure 5
Figure 5. Heterogeneous Late Response to Neurodegeneration of Microglia Is Typified by Different Modules of Co-regulated Genes
t-SNE plots as shown in Figure 2A. (A) Data points are colored by the expression level of selected antiviral and interferon response genes as indicated. (B) Data points are colored by the expression level of the genes encoding MHC class II components as indicated. (C) Scatterplots showing the correlation of the expression level of MHC class II related genes (H2-Aa, H2-Ab1, Cd74) and of Cd74 and the housekeeping genes Actb, Gapdh, and Rpl13 across the cells of cluster 6.
Figure 6
Figure 6. Two Distinct Reactive Microglia Phenotypes in Late Response to Neurodegeneration
(A and B) Histograms showing the distribution of the weighted fold induction of a module of 132 antiviral and interferon response genes (A) and four MHC class II complex-related genes (B) across the cells of the groups indicated. (C and D) t-SNE plots as shown in Figure 2A. Data points are colored by the weighted fold induction of (C) a module of 132 antiviral and interferon response genes and (D) a module of four MHC class II complex-related genes. (E) Histograms showing the distribution of the weighted fold induction of a module of co-regulated genes mainly containing ribosomal protein-encoding genes across the cells of the groups indicated. (F) Scatterplot showing the correlation between the induction of the antiviral and interferon response module and the MHC class II module across the cells isolated from CK-p25 mice 2 and 6 weeks after p25 induction.
Figure 7
Figure 7. Immunostaining Reveals Heterogeneous Late Response of Microglia to Neurodegeneration
Immunostaining in the dentate gyrus of CK-p25 mice 6 weeks after p25 induction. (A) Immunohistochemistry with anti-CD40 (red) and anti-Iba1 (white) antibodies. Cells indicated with blue and red arrows are shown at higher magnification on the right. (B) Immunohistochemistry with anti-CD69 (red) and anti-Iba1 (white) antibodies. (C–E) Quantification of the CD40 (C), CD69 (D), MHC2 (E), and Iba1 immunostaining. Values are percentages of Iba1-positive cells expressing CD40, CD69, and MHC2, respectively. (F) Immunohistochemistry with anti-GFP (green), anti-CD74 (MHC2, red), and anti-Iba1 (white) antibodies. For all graphs, quantification is based on immunostaining in the dentate gyrus of seven CK mice and four CK-p25 mice, with two sections per animal. Error bars show SEM. **p < 0.01; ***p < 0.001.

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