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. 2021 Mar 29:12:639613.
doi: 10.3389/fimmu.2021.639613. eCollection 2021.

Single-Cell Transcriptomics and In Situ Morphological Analyses Reveal Microglia Heterogeneity Across the Nigrostriatal Pathway

Oihane Uriarte Huarte  1   2 , Dimitrios Kyriakis  1 , Tony Heurtaux  2   3 , Yolanda Pires-Afonso  4   5 , Kamil Grzyb  1 , Rashi Halder  1 , Manuel Buttini  1   2 , Alexander Skupin  1   6 , Michel Mittelbronn  1   2   7   8 , Alessandro Michelucci  1   4
Affiliations

Single-Cell Transcriptomics and In Situ Morphological Analyses Reveal Microglia Heterogeneity Across the Nigrostriatal Pathway

Oihane Uriarte Huarte et al. Front Immunol. .

Abstract

Microglia are the resident immune effector cells of the central nervous system (CNS) rapidly reacting to various pathological stimuli to maintain CNS homeostasis. However, microglial reactions in the CNS may also worsen neurological disorders. Hence, the phenotypic analysis of microglia in healthy tissue may identify specific poised subsets ultimately supporting or harming the neuronal network. This is all the more important for the understanding of CNS disorders exhibiting regional-specific and cellular pathological hallmarks, such as many neurodegenerative disorders, including Parkinson's disease (PD). In this context, we aimed to address the heterogeneity of microglial cells in susceptible brain regions for PD, such as the nigrostriatal pathway. Here, we combined single-cell RNA-sequencing with immunofluorescence analyses of the murine nigrostriatal pathway, the most affected brain region in PD. We uncovered a microglia subset, mainly present in the midbrain, displaying an intrinsic transcriptional immune alerted signature sharing features of inflammation-induced microglia. Further, an in situ morphological screening of inferred cellular diversity showed a decreased microglia complexity in the midbrain when compared to striatum. Our study provides a resource for the identification of specific microglia phenotypes within the nigrostriatal pathway, which may be relevant in PD.

Keywords: Parkinson’s disease; cell morphology; cellular heterogeneity; immune alerted; microglia; nigrostriatal pathway; single-cell transcriptomics.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Single-cell transcriptomics identifies cellular diversity of the midbrain and striatum. (A) Schematic representation of the experimental approach. Tissue dissected and dissociated from midbrain (in green) and striatum (in orange) of six months-old C57BL/6J mice (pool of 5 mice) analyzed by Drop-seq. (B) t-SNE projection of 1,337 single cells included in the study showing 480 cells isolated from midbrain (in green) and 857 cells from striatum (in orange). (C) Bar plots of representative cell type-specific markers across nine identified clusters: microglia (P2ry12), astrocytes (Gja1), oligodendrocytes (Plp1), endothelial cells (Ly6c1), hybrid (Scn7a and C1ql1), ependymal cells (Ccdc153), choroid plexus cells (Kcnj13), neurons/neuronal stem cells (Meg3 and Snhg11) and pericytes (Cald1, Vtn, Notch3) clusters. See Figure S1 and Table S1 for additional cell type-specific markers used for cluster annotation. (D) Annotated clusters in the t-SNE map showing nine specific groups identified by differential expression analysis featuring 15,446 total genes (FDR<0.05): microglia (in blue), astrocytes (in red), oligodendrocytes (in green), endothelial cells (in purple), hybrid (orange), ependymal cells (brown), choroid plexus cells (in pink), neurons/neuronal stem cells (in grey) and pericytes (in pale brown). (E) Pie chart depicting the percentage of the identified cell types. (F) Bar plot showing proportion of cell types within midbrain (in green) and striatum (in orange).
Figure 2
Figure 2
Microglia within the nigrostriatal pathway segregate into specific immune subsets. (A) UMAP plot of the re-projected microglia cluster showing four distinct subsets: homeostatic (in grey), intermediate 1 (in pale blue), intermediate 2 (in purple) and immune alerted (in pink). (B) UMAP representation showing 210 microglial cells, with 41 cells from the midbrain (in green) and 169 cells from striatum (in orange). (C) Heatmap showing clustering analysis of single cells, featuring 78 differential expressed genes across the four subsets (q value < 0.05). Color bar represents z-scores (from low z-score in blue to high z-score in red) ( Table S2 ). (D) Cytoscape network analysis of gene ontology terms identified by DAVID analysis (p value < 0.05, node cut off q value < 0.1) of the 78 differentially expressed genes across microglia subsets ( Table S3 ). (E) Top 17 KEGG pathways identified by DAVID resulting from 78 differentially expressed genes ( Table S3 ). (F) Dot plot representing the expression of inflammatory genes across the microglia subsets. Circle diameter denotes percent expression; color code indicates average expression levels. (G) Percentage of CD83+ cells within the CD11b+CD45int population quantified by flow cytometry. Bars represent mean ± SEM (cortex in pale green; striatum in orange; midbrain in green). Unpaired Student t test (n = 3) (*p < 0.05, **p < 0.01). (H–I) Dot plots representing (H) antigen presenting cell markers and (I) homeostatic genes across the microglia subsets. Circle diameter denotes percent expression; color code indicates average expression levels.
Figure 3
Figure 3
Midbrain-enriched immune alerted microglia show transcriptional similarities to inflammation-associated microglia. (A–C) Venn diagrams showing the comparison between 78 differentially expressed genes across midbrain/striatum microglia subsets and 2,148 genes characterizing inflammation-associated microglia (24).
Figure 4
Figure 4
Microglial density and morphology across striatum and midbrain are heterogeneous. (A) Representation of different areas analyzed for microglia density and morphology. TH was employed to identify the brain regions, while IBA1 was used to visualize microglia. Scale bar, 1500 µm (CP, caudoputamen; NA, nucleus accumbens; CRB, cerebellum). (B) Tile pictures showing midbrain sub-regions in sagittal mouse brain. Scale bar, 200 µm (SNr, substantia nigra pars reticulata; SNc; substantia nigra pars compacta; VTA, ventral tegmental area). (C) Quantification of microglial cell density in the different brain areas, cortex (in pale green), cerebellum (in pink), striatum (in orange) and midbrain (in green). Bars represent the mean ± standard error of the mean (SEM) from four independent mice. One-way ANOVA with post-hoc Tukey’s test was used for statistical test (*p < 0.05, **p < 0.01, ***p < 0.005). (D) 3D reconstruction of representative microglial cells across different brain regions. Scale bar, 10 μm (CRB, cerebellum; CP caudoputamen; NA, nucleus accumbens; SNr, substantia nigra pars reticulata; SNc, substantia nigra pars compacta; VTA, ventral tegmental area). (E-G) Quantification of microglial cell complexity across brain regions. Bars represent the mean ± standard error of the mean (SEM) from twelve independent Iba1+ cells. One-way ANOVA with post-hoc Tukey’s test was used for statistical test for process total length, whereas Kruskal-Wallis followed by post-hoc Dunn’s test was used as statistical test for number of branching points and number of segments (NS not significant, *p < 0.05, **p < 0.01, ***p < 0.005) ( Table S5 ). CTX, cortex; CRB, cerebellum; CP caudoputamen; NA, nucleus accumbens; SNr, substantia nigra pars reticulata; SNc, substantia nigra pars compacta; VTA, ventral tegmental area.
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