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. 2022 Apr 30:2022:1817721.
doi: 10.1155/2022/1817721. eCollection 2022.

Single-Cell RNA-Sequencing Analyses Revealed Heterogeneity and Dynamic Changes of Metabolic Pathways in Astrocytes at the Acute Phase of Ischemic Stroke

Hongyu Ma  1 , Yu Zhou  1 , Zifu Li  1 , Luojiang Zhu  1 , He Li  1 , Guanghao Zhang  1 , Jing Wang  1 , Haiyi Gong  2 , Da Xu  3 , Weilong Hua  1 , Pei Liu  1 , Xiaoxi Zhang  1 , Yongxin Zhang  1 , Lei Zhang  1 , Bo Hong  1 , Wang Zhou  1 , Pengfei Yang  1 , Jianmin Liu  1
Affiliations

Single-Cell RNA-Sequencing Analyses Revealed Heterogeneity and Dynamic Changes of Metabolic Pathways in Astrocytes at the Acute Phase of Ischemic Stroke

Hongyu Ma et al. Oxid Med Cell Longev. .

Abstract

Astrocyte plays important roles in the pathogenesis of ischemic stroke and reperfusion injury. They intensively participate in the energy metabolism of the brain, while their heterogeneity and function after ischemic stroke remain controversial. By employing single-cell sequencing of mice cortex at 12 h after transient middle cerebral artery occlusion (tMCAO) and comparing with the similar published datasets of 24h after tMCAO, we uncover the cellular phenotypes and dynamic change of astrocytes at the acute phase of ischemic stroke. In this study, we separately identified 3 major subtypes of astrocytes at the 12 h-tMCAO-system and 24 h-tMCAO-system, indicated the significant differences in the expression of genes and metabolic pathways in the astrocytes between the two time nodes after ischemic stroke, and detected the major change in the energy metabolism. These results provided a comprehensive understanding of the characteristic changes of astrocytes after ischemic stroke and explored the potential astrocytic targets for neuroprotection.

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Conflict of interest statement

The authors declare that there is no conflict of interest regarding the publication of this paper.

Figures

Figure 1
Figure 1
Major brain cell subtypes and genes signature. (a). UMAP plot of 104382 cells to visualize subtypes of brain cells based on the expression of known marker genes. (b). The UMAP plot visualized by sample distribution. (c). Heatmap of the relative expression level of genes across cell types. (d). The proportion of cells that contributed to each cluster by each sample, colored by cell type.
Figure 2
Figure 2
Major brain cell subtypes in the 12 h-tMCAO-system and 24 h-tMCAO-system. (a). UMAP plot to visualize subtypes of brain cells based on the expression of known marker genes (left) and the sample distribution (right) in 12 h-tMCAO-system. (b). UMAP plot to visualize subtypes of brain cells based on the expression of known marker genes (left) and the sample distribution (right) in 24 h-tMCAO-system.
Figure 3
Figure 3
Astrocyte heterogeneities in the 12 h-tMCAO-system. (a). Unsupervised clustering of astrocytes visualized by sample distribution. (b). Visualization of the expression of signature genes of astrocytes. (c). Subpopulation of astrocytes using monocle algorithm visualized by sample distribution. (d). The t-SNE plot for cell differentiation trajectory. (e). Identified subpopulation of astrocytes clustered by monocle algorithm. (f). Visualization of the expression of previously reported signature genes of astrocytes in the t-SNE plot clustered by monocle algorithm. (g). The proportion of cells that contributed to each cluster by control and MCAO. (h). The cell cycle distribution in the three subpopulations. (i). Bubble plots displayed the top 10 signature genes for each subpopulation. (j). Volcano plot to identify the differential genes between AST12_B and AST12_C. (k). Heatmap of the expression regulation by transcription factors of the identified clusters. (l). Gene ontology network based on genes that are highly upregulated.
Figure 4
Figure 4
Astrocyte heterogeneities in the 24 h-tMCAO-system. (a). Unsupervised clustering of astrocytes visualized by sample distribution. (b). Visualization of the expression of signature genes of astrocytes. (c). Subpopulation of astrocytes using monocle algorithm visualized by sample distribution. (d). The t-SNE plot for cell differentiation trajectory. (e). Identified subpopulation of astrocytes clustered by monocle algorithm. (f). Visualization of the expression of previously reported signature genes of astrocytes in the t-SNE plot clustered by monocle algorithm. (g). The proportion of cells that contributed to each cluster by control and MCAO. (h). The cell cycle distribution in the three subpopulations. (i). Bubble plots displayed the top 10 signature genes for each subpopulation. (j). Volcano plot to identify the differential genes between AST24_B and AST24_C. (k). Heatmap of the expression regulation by transcription factors of the identified clusters. (l). Gene ontology network based on genes that are highly upregulated.
Figure 5
Figure 5
Differential expression and relationship between 12 h and 24 h after tMCAO. (a). Genes that were significantly upregulated in four astrocytic subsets are compared using Venn diagram. (b). Volcano plot displayed the differential genes of reactive astrocytes between 12 h and 24 h. (c). Astrocytic gene ontology network showed the highly activated pathways at 12 h and 24 h after MCAO.
Figure 6
Figure 6
Comparison of the major gene expression in energy metabolic pathways in astrocytes at 12 h and 24 h after MCAO. (a). Heatmap of GSVA results indicated major changes in the energy metabolism pathways. (b). Boxplots indicated the changes of expression of genes related to glycolysis. (c). Boxplots indicated the changes of expression of pentose phosphate pathway. (d). Boxplots indicated the changes of expression of the syntheses and transportation of lactate and glucose transporters.
Figure 7
Figure 7
Comparison of the gene expression in energy metabolism. (a). Boxplots indicated the change of expression of genes for the transition between glycolysis and tricarboxylic acid cycle (TCA). (b). Boxplots indicated the change of expression of genes for TCA. (c). Boxplots displayed the change of expression of genes for glycogen metabolism. (d). Boxplots displayed the change of expression of genes for glutamic metabolism.
Figure 8
Figure 8
Comparison of the major gene expression in respiratory chain at 12 h and 24 h after MCAO. (a). Boxplots indicated the change of expression for the complex I in mitochondria. (b). Boxplots indicated the change of expression of genes for the complex II and III. (c). Boxplots displayed the change of expression of genes for the complex IV. (d). Boxplots displayed the change of expression of genes for the complex V and ATP syntheses.
Figure 9
Figure 9
Comparison of the major gene expression in lipid metabolism, reactive oxidative (ROS), and calcium signaling pathways in astrocytes at 12 h and 24 h after MCAO. (a). Boxplots indicated the change of expression of lipid metabolism. (b). Boxplots indicated the change of expression of genes for the ROS. (c). Boxplots displayed the change of expression of genes for calcium signaling pathways.
Figure 10
Figure 10
The immunofluorescence images for the 12 h-tMCAO-system and 24 h-tMCAO-system. Validation of differential expression genes related to glycolysis (PKM, upregulation in 24 h), lactate syntheses (LDH, upregulation in 24 h), glucose transporter (GLUT1, upregulation in 24 h), and glutamate transporter (SLC1A3, no significant differences between 12 h and 24 h).
Figure 11
Figure 11
Comparison of the major gene expression in gliosis, blood-brain barrier, and inflammation pathways in astrocytes at 12 h and 24 h after MCAO. (a). Boxplots indicated the change of expression of gliosis. (b). Boxplots indicated the change of expression of genes for the blood-brain barrier. (c). Boxplots displayed the change of expression of genes for inflammation. (d). Boxplots displayed the change of expression of genes for chemokines.
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