实用医学杂志 ›› 2024, Vol. 40 ›› Issue (15): 2075-2083.doi: 10.3969/j.issn.1006-5725.2024.15.006

• 基础研究 • 上一篇    下一篇

溃疡性结肠炎发病机制的单细胞转录组生物信息学研究

庞雪1,郭建壮2   

  1. 1.山东第一医科大学第一附属医院,肛肠科,(济南 250012 )
    2.山东第一医科大学第一附属医院,检验科,(济南 250012 )
  • 收稿日期:2023-09-27 出版日期:2024-08-10 发布日期:2024-07-30
  • 基金资助:
    国家自然科学基金青年基金项目(82104876);山东省医药卫生科技发展计划(2017WS802);山东省中医药科技发展计划(2019-0379)

Single-cell transcriptomic bioinformatics study of the pathogenesis of ulcerative colitis

Xue PANG1,Jianzhuang. GUO2   

  1. *.Department of Proctology,the First Affiliated Hospital of Shandong First Medical University,Ji′nan 250012,China
  • Received:2023-09-27 Online:2024-08-10 Published:2024-07-30

摘要:

目的 利用单细胞转录组生物信息学方法挖掘溃疡性结肠炎(UC)发病的潜在机制。 方法 从高通量基因表达数据库中下载UC样本的单细胞转录组数据集GSE125527作为研究对象,利用R语言的Seurat数据包对数据进行过滤和标准化,将具有相似特征基因的细胞进行聚类和注释,筛选与UC发病相关的细胞亚群,提取差异表达基因(DEGs),对DEGs进行富集分析,挖掘UC发病的潜在信号通路,对差异最大的细胞亚群进行高维加权基因共表达网络分析(hdWCNA),筛选与UC相关的基因模块;下载GSE36807、GSE42911、GSE65114和GSE6731数据集,筛选DEGs,结合单细胞DEGs和与UC相关的基因模块,筛选UC发病的核心基因,绘制受试者工作特征曲线(ROC)评价核心基因预测UC发病的价值。复制UC模型大鼠验证UC核心基因的表达。 结果 过滤获得UC样本细胞18 642个,正常结肠组织样本细胞4 298个,共聚类成10个亚群,UC样本中B细胞占比高。筛选获得单核细胞相关的差异表达上调基因81个,差异表达下调基因21个。DEGs显著富集于肿瘤坏死因子(TNF)?α、核转录因子(NF)?κB、白细胞介素(IL)?2和信号传导与转录活化因子(STAT)5,以及干扰素(IFN)?α信号通路上。hdWGCNA筛选出2个UC相关基因模块,经筛选并验证,LAPTM5为UC的核心基因。与对照组大鼠相比,UC模型大鼠结肠组织中LAPTM5表达水平显著升高。 结论 UC与正常结肠组织样本细胞分布存在较大差异,B细胞与UC发病密切相关,是预防和治疗UC的潜在靶细胞。LAPTM5是UC发病的潜在核心基因。

关键词: 溃疡性结肠炎, 单细胞转录组, 生物信息学

Abstract:

Objective To explore the underlying mechanisms of ulcerative colitis (UC) pathogenesis using single-cell transcriptomic bioinformatics approaches. Methods Single-cell transcriptome dataset GSE125527, consisting of UC samples, was downloaded from a high-throughput Gene Expression Omnibus for this study. Data filtering and normalization were conducted using the Seurat package in R. Cells with similar gene expression profiles were clustered and annotated. Cell subgroups associated with UC pathogenesis were identified, and differentially expressed genes (DEGs) were extracted. Enrichment analysis of these DEGs was performed to uncover potential signaling pathways involved in UC. High-dimensional weighted gene co-expression network analysis (hdWGCNA) was applied to the cell subgroup with the greatest differences to select UC-related gene modules. Additional datasets, GSE36807, GSE42911, GSE65114, and GSE6731, were downloaded for DEG screening. By integrating single-cell DEGs with UC-related gene modules, core genes involved in UC pathogenesis were identified. Receiver operating characteristic (ROC) curves were plotted to evaluate the predictive value of these core genes for UC pathogenesis. The expression of core genes was validated in a UC rat model. Results After filtering, 18 642 cells from UC samples and 4 298 cells from normal colonic tissue were obtained and clustered into ten subgroups, with a high proportion of B cells in UC samples. Eighty-one upregulated and twenty-one downregulated DEGs related to mononuclear cells were identified. Significant enrichment of DEGs was observed in pathways related to tumor necrosis factor-alpha, nuclear factor Kappa B, interleukin-2, signal transducer and activator of transcription 5, and interferon-alpha. Two UC-related gene modules were identified through hdWGCNA. After screening and validation, LAPTM5 was confirmed as a core gene in UC pathogenesis. Compared to control rats, LAPTM5 expression was significantly higher in the colonic tissues of UC model rats. Conclusions There are significant differences in cell distribution between UC and normal colonic tissues, with B cells closely related to UC pathogenesis, serving as potential targets for prevention and treatment. LAPTM5 is identified as a potential core gene in UC pathogenesis.

Key words: ulcerative colitis, single-cell transcriptome, bioinformatics

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