单细胞测序分析脊髓损伤修复的关键基因和细胞通讯  

Single-cell transcriptome reveals features of key factors and cellular communication in spinal cord injury

作　　者：安岩 朱祥 王博 张琳 于世炎 An Yan;Zhu Xiang;Wang Bo;Zhang Lin;Yu Shiyan(Department of Spine Surgery,Beijing Jishuitan Hospital,Beijing 100035,China;Department of Oncology,Army No.82 Group Military Hospital,Baoding 071000,China;Air Force 986 Hospital,Xi'an 710054,China)

机构地区：[1]首都医科大学附属北京积水潭医院脊柱外科,北京100035 [2]陆军第82集团军医院肿瘤科,保定071000 [3]空军第九八六医院第十门诊部,西安710054

出　　处：《中华骨科杂志》2025年第5期302-309,共8页Chinese Journal of Orthopaedics

基　　金：北京积水潭医院学科新星(XKXX202105);北京积水潭医院院级科研基金(ZR202203)。

摘　　要：目的通过转录组测序和单细胞测序分析揭示脊髓损伤修复过程中的关键基因和细胞通讯。方法通过基因表达综合数据库(Gene Expression Omnibus,GEO)下载2个脊髓损伤相关的转录组测序数据集和1个单细胞测序数据集。使用R软件中的limma包分析2个转录组测序数据集的差异基因,进行交叉分析鉴定共同的差异基因;利用the Database for Annotation,Visualization and Integrated Discovery(DAVID)数据库对差异基因进行基因本体论(Gene Ontology,GO)和京都基因与基因组百科全书数据库(Kyoto Encyclopedia of Genes and Genomes,KEGG)功能富集分析;采用cyto Scape软件中cytoHubba插件鉴定蛋白互作网络中的核心基因。使用R软件中Seurat包分析单细胞测序数据集,主成分分析(principal components analysis,PCA)对数据降维,t分布随机近邻嵌入(t-distributed stochastic neighbor embedding,t-SNE)对单细胞数据进行可视化。使用R软件中的cellChat包分析不同细胞群之间的细胞通讯。结果脊髓损伤相关转录组测序数据差异分析获得了98个共同的差异基因。GO和KEGG功能富集分析鉴定了损伤修复、巨噬细胞活化、免疫反应细胞活化等生物学过程。蛋白互作网络预测了其中10个核心基因:ITGAM、TGFB1、CCL2、ICAM1、CD44、FN1、TIMP1、TLR2、ITGB2、LGALS3。单细胞测序数据集可视化为星形胶质细胞、神经元、内皮细胞、单核细胞、成纤维细胞、B细胞6个细胞群。细胞通讯分析揭示细胞群之间的细胞通讯方式包括SPP1-(ITGAV+ITGB1)、SPP1-(ITGA5+ITGB1)、TNF-TNFRSF1A传递途径等。结论脊髓损伤修复过程中星形胶质细胞通过SPP1传递途径接受成纤维细胞、单核细胞、神经元的信号,星形胶质细胞和神经元通过TNF传递途径接受单核细胞的信号,为深入研究脊髓损伤修复分子机制提供了有效信息。ObjectiveTo investigate key genes and cellular communication involved in spinal cord injury(SCI)repair using transcriptome sequencing and single-cell sequencing analysis.MethodsTwo transcriptome sequencing datasets related to SCI and one single-cell sequencing dataset were obtained from the Gene Expression Omnibus(GEO)database.Differentially expressed genes(DEGs)in the two transcriptome sequencing datasets were analyzed using the limma package in R,followed by cross-analysis to identify common DEGs.Functional enrichment analysis of DEGs was performed using the DAVID database for Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathways.Hub genes in the protein-protein interaction(PPI)network were identified using the cytoHubba plugin in Cytoscape.Single-cell sequencing data were analyzed using the Seurat package in R.Principal Component Analysis(PCA)was applied for dimensionality reduction,and t-distributed Stochastic Neighbor Embedding(t-SNE)was used for visualization.Cellular communication between different cell groups was analyzed using the CellChat package.ResultsDifferential analysis of transcriptome sequencing data identified 98 common DEGs.GO and KEGG enrichment analysis highlighted biological processes such as wound healing,macrophage activation,and immune response-related cell activation.The PPI network predicted 10 hub genes:ITGAM,TGFB1,CCL2,ICAM1,CD44,FN1,TIMP1,TLR2,ITGB2,and LGALS3.Single-cell sequencing analysis identified six distinct cell populations,including astrocytes,neurons,and fibroblasts.Cellular communication analysis revealed key signaling pathways between cell subpopulations,including SPP1-(ITGAV+ITGB1),SPP1-(ITGA5+ITGB1),TNF-TNFRSF1A transmission pathway,etc.ConclusionsDuring SCI repair,astrocytes receive signals from fibroblasts,monocytes,and neurons via the SPP1 pathway,while astrocytes and neurons receive signals from monocytes through the TNF pathway.These findings provide critical insights into the molecular mechanisms underlying SCI repair and offer a foundation fo

关 键 词：脊髓损伤 基因 转录组测序 高通量核苷酸序列分析 细胞间通讯 

分 类 号：R651.2[医药卫生—外科学]