癌变·畸变·突变 ›› 2024, Vol. 36 ›› Issue (4): 268-274,280.doi: 10.3969/j.issn.1004-616x.2024.04.004

• 论著 • 上一篇    

二氧化硅暴露对呼吸道上皮细胞基因表达的影响

吴梦宇1,2,3, 德小明1,2, 单婧1,2,3, 李洁1,2, 张映驰1,2,4, 徐海明1,2   

  1. 1. 宁夏医科大学公共卫生学院, 宁夏 银川 750004;
    2. 宁夏回族自治区环境因素与慢性病控制重点实验室, 宁夏 银川 750004;
    3. 西安宝石花长庆医院, 陕西 西安 710201;
    4. 西安市疾病预防控制中心, 陕西 西安 710068
  • 收稿日期:2023-10-17 修回日期:2024-02-25 发布日期:2024-08-06
  • 通讯作者: 徐海明
  • 作者简介:吴梦宇,E-mail:wm28139@163.com。
  • 基金资助:
    2021年自治区卫生健康系统科研课题(2021-NW-001);国家自然科学基金(81660527);宁夏自然科学基金(2022AAC05027)

Effect of silica exposure on gene expression in respiratory epithelium

WU Mengyu1,2,3, DE Xiaoming1,2, SHAN Jing1,2,3, LI Jie1,2, ZHANG Yingchi1,2,4, XU Haiming1,2   

  1. 1. School of Public Health, Ningxia Medical University, Yinchuan 750004;
    2. Ningxia Hui Autonomous Region Key Laboratory of Environmental Factors and Chronic Disease Control, Yinchuan 750004, Ningxia;
    3. Xi'an Gem Flower Changqing Hospital, Xi'an 710201;
    4. Xi'an Center for Disease Control and Prevention, Xi'an 710068, Shaanxi, China
  • Received:2023-10-17 Revised:2024-02-25 Published:2024-08-06

摘要: 目的:采用生物信息学方法探讨人原代支气管上皮NHBE细胞暴露于SiO2后的基因表达变化,筛选关键基因并进行实验验证,从而为硅肺病的诊断和治疗提供新思路。方法:从GEO数据库获取数据集GSE62769,采用R语言3.6.3对基因表达数据矩阵进行差异表达基因(DEGs)筛选、GO功能富集分析及KEGG信号通路分析。同时采用STRING数据库和Cytoscape软件构建蛋白质-蛋白质相互作用(PPI)网络,MCODE插件筛选关键基因。最后以0、50、100、200 μg/mL SiO2暴露于A549细胞24 h,采用逆转录荧光定量PCR(RT-qPCR)法对关键基因表达水平的生信分析结果进行了扩展性验证。结果:生物信息学分析共筛选出48个DEGs。GO和KEGG分析结果显示,DEGs主要参与脂多糖反应、对细菌来源分子的反应等生物学过程,细胞因子-细胞因子受体相互作用等信号通路。11个关键基因为CXCL8CXCL10TLR2JUNICAM1CXCL1MMP1TNFAIP3CCL20CXCL2CXCL3。RT-qPCR实验结果显示,在200 μg/mL SiO2混悬液干预下A549细胞中CXCL8JUNICAM1CXCL1MMP1TNFAIP3CCL20CXCL3基因的mRNA表达均显著上调,与生物信息学分析中暴露于SiO2的NHBE细胞的基因表达趋势一致。结论:基于生物信息学方法和体外实验验证,筛选得到了呼吸系统上皮细胞中11个与SiO2暴露相关的异常表达基因,可为硅肺病的发生机制提供新的科学依据,同时为硅肺病早期诊断和治疗提供了新靶标。

关键词: 硅肺, 上皮细胞, 二氧化硅, 生物信息学, 差异表达基因

Abstract: OBJECTIVE:Bioinformatics method was used to explore changes of gene expression in NHBE cells exposed to SiO2 and key genes were verified by experiments,to provide information for enhanced diagnosis and treatment of silicosis. METHODS:GSE62769,a dataset related to silica,was obtained from GEO database. The differentially expressed genes (DEGs),GO functional enrichment analysis and KEGG signal pathway analysis were carried out with R language 3.6.3. At the same time,the protein-protein interaction (PPI) network was constructed by STRING database and Cytoscape software,and key genes were screened by MCODE plug-in. Finally,A549 cells were exposed to 0,50,100,200 μg/mL SiO2 for 24 h and the bioinformatics analysis results of key gene expression levels were extensively verified by RT-qPCR method. RESULTS:A total of 48 DEGs were screened. The results of GO and KEGG analysis showed that DEGs were mainly involved in biological processes such as lipopolysaccharide reaction and reaction to bacterial molecules,etc.,and signal pathways such as cytokine-cytokine receptor interaction,etc. Eleven key genes of PPI network were selected by MCODE plug-in,which were CXCL8CXCL10TLR2JUNICAM1CXCL1MMP1TNFAIP3CCL20CXCL2 and CXCL3.Results from RT-qPCR analyses showed that expressions of CXCL8JUNICAM1CXCL1MMP1TNFAIP3CCL20 and CXCL3 were significantly up-regulated in the A549 cells treated with 200 μg/mL SiO2 suspension,which was consistent with the trend of gene expression on NHBE cells in bioinformatics analysis. CONCLUSION:Based on bioinformatics and experimental verification methods,11 key DEG related to SiO2 exposed respiratory epithelial cells were screened. Our results provided new information on pathogenesis of silicosis,and identified several possible targets for the early diagnosis and treatment of silicosis.

Key words: silicosis, epithelial cells, silica, bioinformatics, differentially expressed genes

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