首页|期刊导航|环境与职业医学|二氧化硅诱导小鼠肺纤维化进程中miRNA-mRNA调控网络的构建与分析

二氧化硅诱导小鼠肺纤维化进程中miRNA-mRNA调控网络的构建与分析OA

Construction and analysis of miRNA-mRNA regulatory network during progression of silica-in-duced pulmonary fibrosis in mice

中文摘要英文摘要

[背景]肺纤维化进程中涉及微 RNA(miRNA)与信使 RNA(mRNA)的调控,这类调控可促进或抑制肺纤维化的发展. [目的]基于 mRNA测序和 miRNA测序,探究二氧化硅(SiO2)暴露下小鼠肺纤维化进程中的miRNA-mRNA调控网络. [方法]通过动式染尘法建立小鼠肺纤维化模型.实验设置空白对照组、SiO2 处理 7、14、28、56 d组,每组各 10只小鼠.通过 HE染色和 Masson染色处理肺组织切片,评估肺组织病理变化,检测羟脯氨酸(HYP)及关键纤维化相关细胞因子[成纤维细胞生长因子(FGF)、白细胞介素-6(IL-6)、转化生长因子-β(TGF-β)、肿瘤坏死因子-α(TNF-α)]的表达水平,确定模型构建成功.对各组小鼠肺组织进行测序,利用 Mfuzz 进行时间序列基因聚类分析探究肺纤维化进程中各阶段的变化模式.利用 DESeq2筛选差异表达基因(DEGs)和差异表达 miRNA.对DEGs进行富集分析,识别肺纤维化进程中的关键信号通路与生物学过程;对筛选出的 4个关键 miRNA进行实时荧光定量 PCR(RT-qPCR)表达验证,采用 miRBase、starBase、miRTar-Base综合预测关键miRNA的靶基因mRNA,构建并分析miRNA-mRNA调控网络及其潜在功能. [结果]SiO2 暴露组随着染尘时间越长,小鼠肺部纤维沉积越多,纤维化程度越深.与 NT组比较,各暴露组 HYP含量均有所上升(P<0.01);4种肺纤维化关键细胞因子表达水平上升(P<0.01),且呈现随染尘时间延长而上升的趋势.Mfuzz时间序列基因聚类分析揭示了肺纤维化各阶段的特征.与对照组相比,7、14、28、56 d SiO2 暴露组分别筛选到 231、662、448和1 020个 DEGs.富集分析表明,这些 DEGs主要参与免疫相关反应及趋化因子相关通路.在7 d(急性炎症与纤维化启动期)和 28 d(慢性炎症与纤维化形成期)2个肺纤维化关键时期,共鉴定出 18个差异表达 miRNA,其中 mmu-miR-135b-5p在 7 d和 28 d均显著差异表达.4个关键 miRNA,即 mmu-miR-135b-5p、mmu-miR-708-5p、mmu-miR-21a-3p、mmu-miR-205-5p的表达趋势与测序结果一致.数据库预测结果显示,mmu-miR-135b-5p与靶基因 Meis1、mmu-miR-708-5p与靶基因 Mmp25、mmu-miR-21a-3p与靶基因 Cacna1d、mmu-miR-205-5p与靶基因 Ereg的调控关系对,与炎症反应、细胞外基质沉积及成纤维细胞活化密切相关,成功构建miRNA-mRNA调控网络. [结论]肺纤维化进程伴随着关键 miRNA-mRNA调控网络的动态变化,鉴定出的关键 miRNA可能通过靶向重要 mRNA(mmu-miR-135b-5p与 Meis1、mmu-miR-708-5p与 Mmp25、mmu-miR-21a-3p与 Cacna1d、mmu-miR-205-5p与 Ereg),在肺纤维化进程中发挥重要作用,为探索肺纤维化的潜在治疗靶点提供了重要线索.

[Background]Regulatory interactions between microRNAs(miRNAs)and messenger RNAs(mRNAs)are involved in the progression of pulmonary fibrosis,which can either promote or inhibit the development of this disease. [Objective]To explore the miRNA-mRNA regulatory network during the progression of silica(SiO2)-induced pulmonary fibrosis in mice using integrated mRNA-seq and miRNA-seq analysis. [Methods]A mouse model of pulmonary fibrosis was established by dynamic SiO2 dust exposure.The experimental design included a blank control group and four SiO2-exposed groups(7,14,28,and 56 d,n=10 per group).Successful model induction was confirmed by histopathological analysis(HE and Masson staining),hydroxyproline(HYP)quantification,and expression of key fibrosis-related cytokines[fibroblast growth factor(FGF),interleukin-6(IL-6),transforming growth factor-β(TGF-β),and tumor necrosis factor-α(TNF-α)].Lung tissues from mice in each group were subjected to sequencing,and Mfuzz was used for time-series gene clustering to identify dynamic progression patterns.DESeq2 was utilized to identify differentially expressed genes(DEGs)and differentially expressed miRNAs.Enrichment analysis of DEGs was performed to identify critical signaling pathways and biological processes underlying pulmonary fibrosis progression.Expres-sion of four selected miRNAs was subsequently validated by real-time quantitative polymerase chain reaction(RT-qPCR).The target mRNAs of key miRNAs were comprehensively predicted by integrating miRBase,starBase,and miRTarBase to construct the regulatory networks and investigate potential functions. [Results]SiO2 exposure led to time-dependent aggravation of pulmonary fibrosis in mice,evidenced by increased fibrous deposition,ele-vated HYP levels(P<0.01),and up-regulation of four kinds of pro-fibrotic cytokines(P<0.01)compared with the NT group.Mfuzz clustering revealed the stage-specific characteristics.Compared to controls,231,662,448,and 1 020 DEGs were identified after SiO2 exposure at 7,14,28,and 56 d,respectively,primarily enriched in immune responses and chemokine signaling.During critical fibrotic phases—7 d(acute inflammation and initiation)and 28 d(chronic inflammation and establishment)—18 differentially expressed miRNAs were identified;notably mmu-miR-135b-5p was significantly dysregulated at both time points.The expression trends of the four key miRNAs(mmu-miR-135b-5p,mmu-miR-708-5p,mmu-miR-21a-3p,and mmu-miR-205-5p)were consistent with the sequencing results.Further-more,bioinformatics databases were used to predict the target mRNAs of key miRNAs.The constructed network highlighted critical miR-NA-mRNA pairs—including mmu-miR-135b-5p and Meis1,mmu-miR-708-5p and Mmp25,mmu-miR-21a-3p and Cacna1d,mmu-miR-205-5p and Ereg which were closely associated with inflammatory response,extracellular matrix deposition,and fibroblast activation. [Conclusion]The progression of pulmonary fibrosis is accompanied by dynamic changes in miRNA-mRNA regulatory networks.The iden-tified miRNA-target axes(e.g.,miR-135b-5p and Meis1,mmu-miR-708-5p and Mmp25,mmu-miR-21a-3p and Cacna1d,and mmu-miR-205-5p and Ereg—)may play important roles in fibrogenesis and provide potential therapeutic targets for pulmonary fibrosis.

安昕;吕达;任雪培;刘春城;刘国君;赵宏宇;蔡禄

内蒙古科技大学生命科学与技术学院,内蒙古 包头 014010乌海市市场监督管理局,内蒙古 乌海 016000内蒙古科技大学生命科学与技术学院,内蒙古 包头 014010内蒙古科技大学生命科学与技术学院,内蒙古 包头 014010内蒙古科技大学生命科学与技术学院,内蒙古 包头 014010内蒙古自治区生命健康与生物信息学重点实验室,内蒙古 包头 014010内蒙古科技大学生命科学与技术学院,内蒙古 包头 014010

医药卫生

二氧化硅肺纤维化mRNA测序miRNA测序miRNA-mRNA调控网络

silicapulmonary fibrosismRNA sequencingmiRNA sequencingmiRNA-mRNA regulatory network

《环境与职业医学》 2026 (5)

565-574,10

国家自然科学基金项目(62261043,62231013,62401300)内蒙古自治区自然科学基金项目(2025MS03093)2025年内蒙古生命健康与生物信息学重点实验室项目(2025KYPT0135)

10.11836/JEOM25480

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