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. 2023 Mar 30:14:1114663.
doi: 10.3389/fimmu.2023.1114663. eCollection 2023.

Single-cell analyses reveal the dynamic functions of Itgb2+ microglia subclusters at different stages of cerebral ischemia-reperfusion injury in transient middle cerebral occlusion mice model

Fanning Zeng  1   2 , Jun Cao  3 , Zexuan Hong  3 , Yujun Liu  4 , Jie Hao  5 , Zaisheng Qin  2 , Xin Zou  4   6 , Tao Tao  1
Affiliations

Single-cell analyses reveal the dynamic functions of Itgb2+ microglia subclusters at different stages of cerebral ischemia-reperfusion injury in transient middle cerebral occlusion mice model

Fanning Zeng et al. Front Immunol. .

Abstract

Introduction: The underlying pathophysiological mechanisms of cerebral ischemia reperfusion injury (CIRI) is intricate, and current studies suggest that neuron, astrocyte, microglia, endothelial cell, and pericyte all have different phenotypic changes of specific cell types after ischemic stroke. And microglia account for the largest proportion after CIRI. Previous transcriptomic studies of ischemic stroke have typically focused on the 24 hours after CIRI, obscuring the dynamics of cellular subclusters throughout the disease process. Therefore, traditional methods for identifying cell types and their subclusters may not be sufficient to fully unveil the complexity of single-cell transcriptional profile dynamics caused by an ischemic stroke.

Methods: In this study, to explore the dynamic transcriptional profile of single cells after CIRI, we used single-cell State Transition Across-samples of RNA-seq data (scSTAR), a new bioinformatics method, to analyze the single-cell transcriptional profile of day 1, 3, and 7 of transient middle cerebral artery occlusion (tMCAO) mice. Combining our bulk RNA sequences and proteomics data, we found the importance of the integrin beta 2 (Itgb2) gene in post-modeling. And microglia of Itgb2+ and Itgb2- were clustered by the scSTAR method. Finally, the functions of the subpopulations were defined by Matescape, and three different time points after tMCAO were found to exhibit specific functions.

Results: Our analysis revealed a dynamic transcriptional profile of single cells in microglia after tMCAO and explored the important role of Itgb2 contributed to microglia by combined transcriptomics and proteomics analysis after modeling. Our further analysis revealed that the Itgb2+ microglia subcluster was mainly involved in energy metabolism, cell cycle, angiogenesis, neuronal myelin formation, and repair at 1, 3, and 7 days after tMCAO, respectively.

Discussion: Our results suggested that Itgb2+ microglia act as a time-specific multifunctional immunomodulatory subcluster during CIRI, and the underlying mechanisms remain to be further investigated.

Keywords: Itgb2; cerebral ischemia-reperfusion injury; microglia; scSTAR; single cell RNA-seq.

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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
Identification of major brain cell types after tMCAO. (A) Flow chart of the experiment. (B) TTC staining of mouse brain sections after tMCAO. (C) Rotarod test and (D) Neurological Score after tMCAO. **: p < 0.001 (two-way analysis of variance followed by Dunnett's multiple comparisons tests) (E) UMAP graph of single-cell RNA sequencing subpopulations of the brain sample after tMCAO or sham. (F) Cell population ratios at each time point. (G) Heatmap of top 5 genes for each cell population.
Figure 2
Figure 2
Overview of conventional scRNA-seq analysis and scSTAR analysis of microglia (A, B) UMAP of the microglia subcluster and the distribution of cells at time points by the conventional analysis method. (C, D) Trajectory analysis of the microglia subcluster and the distribution of cells at time points by scSTAR. (E) Details of 44 differentially expressed genes co-expressed in RNA-Seq and proteomic. (F) A Venn plot of 44 DEGs was both in RNA-Seq and proteomic differentially expressed genes or proteins. (G) Network Analyzer of 44 shared DEGs.
Figure 3
Figure 3
scSTAR of itgb2+ microglia subclusters in groups on day 1, 3 and 7 after tMCAO (A) Trajectory analysis of the Itgb2+ microglia subcluster by scSTAR. (B) The distribution of cells at time points on trajectory by scSTAR. (C) The trajectory of 6 microglia subclusters by scSTAR. (D) The relationship with Itgb2 expression pattern and subclusters by scSTAR after tMCAO via chord-charts. (E) The relationship with Itgb2 expression pattern and time points after tMCAO via chord-charts.
Figure 4
Figure 4
Functional enrichment of the sc_S5 on day 1 after tMCAO. (A) The top 20 enriched terms of the sc_S5 on day 1 by Metascape, colored by p-values. (B) Protein-protein interaction network and all MCODE components identified of the sc_S5 on day 1. (C–E) Representative MCODEs with correlation to enrichment analysis of the sc_S5.
Figure 5
Figure 5
Functional enrichment of the sc_S4 on day 1 after tMCAO. (A) The top 20 enriched terms of the sc_S4 on day 1 by Metascape, colored by p-values. (B) Protein-protein interaction network and all MCODE components identified of the sc_S4 on day 1. (C, D) Representative MCODEs with correlation to enrichment analysis of the sc_S4.
Figure 6
Figure 6
Functional enrichment of the sc_S1 on day 3 after tMCAO. (A) The top 20 enriched terms of the sc_S1 on day 3 by Metascape, colored by p-values. (B) Protein-protein interaction network and all MCODE components identified of the sc_S1 on day 3. (C, D) Representative MCODEs with correlation to enrichment analysis of the sc_S1.
Figure 7
Figure 7
Functional enrichment of the sc_S3 on day 7 after tMCAO. (A) The top 20 enriched terms of the sc_S3 on day 7 by Metascape, colored by p-values. (B) Protein-protein interaction network and all MCODE components identified of the sc_S3 on day 7. (C–E) Representative MCODEs with correlation to enrichment analysis of the sc_S3.
Figure 8
Figure 8
KEGG analysis of the representative MCODEs together with Itgb2 in sc_S1,3,4,5.
See this image and copyright information in PMC

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