文章摘要
刘飞，叶民.基于单细胞测序技术分析缺血性脑卒中的转录图谱与疾病进展的生物信息学分析[J].神经损伤功能重建,2024,(7):385-391
基于单细胞测序技术分析缺血性脑卒中的转录图谱与疾病进展的生物信息学分析
Single-cell RNA Sequencing Analysis and Bioinformatics Analysis of the TranscriptionalProfile of Ischemic Stroke and Disease Progression
  
DOI：
中文关键词: 缺血性脑卒中  单细胞测序  转录图谱全景  生物信息学分析
英文关键词: ischemic stroke  single-cell RNA sequencing  transcriptional profile  bioinformatic analysis
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作者单位
刘飞，叶民 南京明基医院神经 内科 
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中文摘要:
      目的：通过单细胞测序（single-cell RNA sequencing，scRNA-seq）技术刻画缺血性脑卒中（ischemic stroke，IS）的转录图谱并分析特定细胞亚群的特征。方法：从基因表达数据库（gene expression omnibus， GEO）中获取IS小鼠的脑组织和同侧的正常脑组织（Sham）scRNA-seq公共数据集GSE174574，对其中的3 个IS病灶和3个Sham组织分别进行样本整合，完成过滤和质控后通过Harmony法去除批次效应进行下游 分析。通过UMAP进行细胞亚群聚类。通过SingleR软件和手工完成各细胞亚群的注释。接着完成差异 化表达和GSVA功能富集分析。使用Monocle2算法评估细胞的进化状态和发育轨迹。使用Cellchat算法 刻画细胞间的通讯作用。结果：经严格质控后，3个IS样本共有29 920个细胞，经UMAP降维后共获得22 个细胞亚群和10个注释出的亚群。其中内皮细胞和巨噬细胞在IS样本中比例较高。3个Sham样本共有 27 259个细胞，UMAP降维获取18个细胞亚群和9个注释出的亚群。与IS相比，Sham组有明显较高的小胶 质细胞比例，但巨噬细胞、单核细胞、上皮细胞的比例相对偏低。对IS样本进行进一步分析，星形细胞可分 为7个细胞亚群（C0～C6），C0～C3组具有明显正相关关系，C0组发育较早而C4、C5组发育较晚。少突细 胞可被分为6个细胞亚群（C0～C5），C3组的发育较早而C2组的发育较晚。少突胶质细胞间的信号传导主 要在PSAP通路，C0和C1组与其他少突胶质细胞亚组的信号传导更加密切。免疫细胞包括粒细胞、巨噬细 胞、单核细胞和自然杀伤（natural killer，NK）细胞，粒细胞和单核细胞可介导巨噬细胞耐受和抗病毒免疫反 应，NK细胞则对内源性刺激信号不敏感。轨迹分析提示粒细胞和单核细胞处于免疫细胞的发育早期阶段 而NK细胞和巨噬细胞处于发育晚期阶段。细胞间的信号通路包括CCL、SPP1、CXCL等，其中CCL通路占 比最大，单核细胞与其他细胞的互动较多，而NK细胞较少。结论：本研究从单细胞分辨率刻画了IS的转录 图谱和各细胞亚群间的关系，并与Sham样本进行对比，揭示了大脑炎症微环境下星形细胞、少突细胞和各 免疫细胞在IS疾病进展中的具体特征和重要作用。免疫细胞亚群在所有细胞中占有较大比例，具有免疫 调节、抗炎反应和稳态的多种作用。
英文摘要:
      To characterize the transcriptional profile of ischemic stroke (IS) and analyze the characteristics of specific cell subpopulations by single-cell sequencing (scRNA-seq). Methods: The public scRNA-seq dataset GSE174574 of IS mouse brain tissues and ipsilateral hemisphere (sham) tissues was obtained from the Gene Expression Omnibus (GEO) database. Samples of three IS lesions and three sham tissues were integrated respectively. Following filtering and quality control, batch effects were corrected using the Harmony method for downstream analysis. UMAP was used to generate cell subpopulation clusters, with annotations completed by SingleR and manual methods. Differential expression analysis and GSVA functional enrichment analysis were then performed. The Monocle2 algorithm was used to evaluate the evolutionary state and developmental trajectory of the cells. The CellChat algorithm was used to characterize cellular communication. Results: After rigorous quality control, a total of 29 920 cells from three IS samples were included. UMAP dimensionality reduction identified 22 cell subpopulations, of which 10 were annotated. Endothelial cells and macrophages were more prevalent in the IS samples. For the sham group, 27259 cells were included, resulting in 18 cell subpopulations, with 9 annotated. Compared to the IS group, the sham group had a significantly higher proportion of microglia, whereas the proportions of macrophages, monocytes, and epithelial cells were lower. Further analysis of IS samples showed that astrocytes could be divided into seven subpopulations (C0～C6), with a significant positive correlation in C0～C3 group. The C0 group developed earlier, while the C4 and C5 groups developed later. Oligodendrocytes could be divided into six cell subpopulations (C0～C5), with C3 developing earlier and C2 developing later. Signal transduction between oligodendrocytes mainly occurred via the PSAP pathway, with closer interactions between C0 and C1 groups and other oligodendrocyte subgroups. Immune cells included granulocytes, macrophages, monocytes and natural killer (NK) cells. Granulocytes and monocytes mediated macrophage tolerance and antiviral immune responses, while NK cells were less responsive to endogenous stimuli. Trajectory analysis showed that granulocytes and monocytes were in the early stage of immune cell development while NK cells and macrophages were in the later stages. Intercellular signaling pathways included CCL, SPP1, and CXCL pathways, with the CCL pathway being the largest proportion. Monocytes exhibited more interactions with other cells, while NK cells showed fewer interactions. Conclusion: This study characterized the transcriptional profile of IS and the relationships between various cell subpopulations at single-cell resolution. Comparison with sham samples revealed the specific characteristics and important roles of astrocytes, oligodendrocytes, and various immune cells in the progression of IS under the brain's inflammatory microenvironment. Immune cell subpopulations accounted for a large proportion of all cells, exhibiting multiple functions in immune regulation, anti-inflammatory response, and homeostasis.
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