基于微阵列数据的circRNA-miRNA-mRNA竞争性内源RNA网络构建及其与自身免疫性肝炎小鼠模型肝损伤的相关性分析

郭地; 刘莹; 刘杨

doi:10.12449/JCH250513

基于微阵列数据的circRNA-miRNA-mRNA竞争性内源RNA网络构建及其与自身免疫性肝炎小鼠模型肝损伤的相关性分析

DOI: 10.12449/JCH250513

山西中医药大学基础医学院，山西晋中 030619

基金项目:

国家中医药管理局高水平中医药重点学科建设项目 (2024);

中西医结合防治风湿免疫病山西省科技创新人才重点团队 (202204051002033);

山西省科学技术厅山西省重点国别科技合作项目 (202104041101013);

山西省应用基础研究计划青年科学基金项目 (202203021222272);

山西省中医药管理局科研项目 (2024ZYYAD008);

山西中医药大学科技创新团队项目 (2022TD2003);

中西医结合治疗风湿免疫疾病重点实验室 (zyyyjs2024021)

伦理学声明：本研究方案于2024年3月11日经由山西中医药大学实验动物伦理委员会审批，批号：AWE202403147，符合实验室动物管理与使用准则。

利益冲突声明：本文不存在任何利益冲突。

作者贡献声明：郭地负责课题设计，资料分析，撰写论文；刘莹参与数据收集和论文修改；刘杨负责拟定写作思路，指导论文撰写，并最终定稿。

详细信息

通信作者:
刘杨， liuyang1980@sxtcm.edu.cn （ORCID： 0000-0002-6627-5002）

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出版历程
- 收稿日期: 2024-09-13
- 录用日期: 2024-11-27
- 出版日期: 2025-05-25

Construction of a circRNA-miRNA-mRNA competitive endogenous RNA network based on microarray data and its correlation with liver injury in a mouse model of autoimmune hepatitis

College of Basic Medical Sciences，Shanxi University of Chinese Medicine，Jinzhong，Shanxi 030619，China

Research funding:

The Construction Project of High-level Traditional Chinese Medicine Key Discipline of National Administration of Traditional Chinese Medicine （2024） (2024);

Key Team of Scientific and Technological Innovation Talents of Shanxi Province with Integrated Traditional Chinese and Western Medicine for Preventing and Treating Rheumatological Diseases (202204051002033);

Special Project with Important Nations of Scientific and Technological Cooperation and Exchange of Shanxi Province (202104041101013);

Youth Science and Technology Research Fund of Applied Basic Research Program of Shanxi Province (202203021222272);

Scientific Research Project of Administration of Traditional Chinese Medicine in Shanxi Province (2024ZYYAD008);

Science and Technology Innovation Project of Shanxi University of Chinese Medicine (2022TD2003);

Key Laboratory of Rheumatological and Immunological Diseases Treated by Integrated Chinese and Western Medicine (zyyyjs2024021)

More Information

Corresponding author: LIU Yang， liuyang1980@sxtcm.edu.cn （ORCID： 0000-0002-6627-5002）

摘要

摘要: 目的构建环状RNA（circRNA）-微小RNA（miRNA）-信使RNA（mRNA）竞争性内源RNA（ceRNA）网络，探讨其在刀豆蛋白A诱导的自身免疫性肝炎（AIH）小鼠模型中的潜在调控机制，并验证关键基因的表达与肝损伤的关系。方法使用高通量数据筛选差异表达的circRNA、miRNA和mRNA，基于Pearson相关分析和Miranda程序预测miRNA与mRNA及circRNA的配对关系，构建ceRNA网络。对网络中的差异表达基因进行GO和KEGG富集分析。选取SPF级雄性C57BL/6小鼠12只，采用随机数字表法分为对照组和模型组，每组6只，模型组通过尾静脉注射刀豆蛋白A构建AIH小鼠模型，对照组注射生理盐水。通过qRT-PCR和Western Blot方法验证circ_0001577、miR-7055-3p和Akt3的表达。测定血清转氨酶（ALT、AST）和肝组织中丙二醛（MDA）及一氧化氮（NO）含量，并分析其与基因表达的相关性。计量资料两组间比较采用成组t检验。使用Spearman相关分析法分析基因表达与肝损伤指标之间的相关性。结果构建了包含5 795个circRNA-miRNA-mRNA配对的ceRNA网络，发现circ_0001577为中心基因。与对照组小鼠比较，模型组中的circ_0001577和Akt3表达上调，miR-7055-3p下调，差异均有统计学意义（P值均<0.05），且circ_0001577与Akt3呈正相关（r=0.861，P<0.001），miR-7055-3p与两者呈负相关（r值分别为-0.644、-0.855，P值均<0.05）。模型组小鼠肝脏Akt3蛋白表达显著高于对照组（1.04±0.10 vs 0.72±0.06，t=-6.49，P=0.001），并与circ_0001577呈正相关（r=0.579，P=0.048），与miR-7055-3p呈负相关（r=-0.891，P<0.001）。模型组小鼠血清ALT、AST和肝组织MDA、NO含量较对照组均显著增加（P值均<0.05），上述肝损伤指标与circ_0001577、Akt3呈正相关（r值分别为0.849、0.865、0.811、0.801；0.889、0.954、0.938、0.961，P值均<0.05），与miR-7055-3p呈负相关（r值分别为-0.687、-0.818、-0.833、-0.870，P值均<0.05），且与Akt蛋白表达呈正相关（r值分别为0.648、0.796、0.848、0.860，P值均<0.05）。结论 circ_0001577通过竞争性吸附miR-7055-3p，导致Akt3抑制被解除，进而促进Akt3的表达，参与AIH的发生发展。circ_0001577及其相关通路可能成为AIH的潜在治疗靶点。
- 肝炎，自身免疫性 /
- RNA，环状 /
- 微RNAs /
- RNA，信使 /
- 小鼠，近交C57BL
Abstract: Objective To construct a circRNA-miRNA-mRNA competitive endogenous RNA （ceRNA） network， to investigate its potential regulatory mechanism in a mouse model of autoimmune hepatitis （AIH） induced by concanavalin A （ConA）， and to verify the association between the expression of key genes and liver injury. Methods High-throughput data were used to identify differentially expressed circRNAs， miRNAs， and mRNAs， and the Pearson correlation analysis and the Miranda program were used to predict the pairing relationships between miRNAs and mRNAs/circRNAs and construct a ceRNA network. The gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed for the differentially expressed genes in the network. A total of 12 specific pathogen-free male C57BL/6 mice were divided into control group and model group using a random number table， with 6 mice in each group. The mice in the model group were given injection of ConA via the caudal vein to establish a mouse model of AIH， and those in the control group were given injection of normal saline. The methods of qRT-PCR and Western blot were used to validate the expression levels of circ_0001577， miR-7055-3p， and Akt3. The serum levels of alanine aminotransferase （ALT） and aspartate aminotransferase （AST） were measured， as well as the content of malondialdehyde （MDA） and nitric oxide （NO） in liver tissue， and their correlation with gene expression was analyzed. The independent-samples t test was used for comparison of continuous data between two groups， and the Spearman correlation analysis was used to investigate the correlation between gene expression levels and liver injury indicators. Results A ceRNA network containing 5 795 circRNA-miRNA-mRNA pairings was constructed， and circ_0001577 was identified as the central gene. Compared with the control group， the model group had significant increases in the expression levels of circ_0001577 and Akt3 and a significant reduction in the expression of miR-7055-3p （all P<0.05）， and circ_0001577 was positively correlated with Akt3 （r=0.861， P<0.001）， while miR-7055-3p was negatively correlated with circ_0001577 and Akt3 （r=-0.644 and -0.855， both P<0.05）. Compared with the control group， the model group had a significantly higher protein expression level of Akt3 in the liver （1.04±0.10 vs 0.72±0.06， t=-6.49， P=0.001）， which was positively correlated with circ_0001577 （r=0.579， P=0.048） and was negatively correlated with miR-7055-3p （r=-0.891， P<0.001）. Compared with the control group， the model group had significant increases in the serum levels of ALT and AST and the content of MDA and NO in liver tissue （all P<0.05）， and these liver injury indicators were positively correlated with circ_0001577 and Akt3 （r=0.849， 0.865， 0.811， 0.801； 0.889， 0.954， 0.938， and 0.961， all P<0.05） and were negatively correlated with miR-7055-3p （r=-0.687， -0.818， -0.833， and -0.870， all P<0.05）； in addition， they were positively correlated with the protein expression level of Akt3 （r=0.648， 0.796， 0.848， and 0.860， all P<0.05）. Conclusion This study shows that circ_0001577 promotes the expression of Akt3 by competitively adsorbing miR-7055-3p and relieving the inhibition of Akt3， thereby participating in the development and progression of AIH.
- Hepatitis， Autoimmune /
- RNA， Circular /
- MicroRNAs /
- RNA， Messenger /
- Mice， Inbred C57BL

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注： a，ceRNA网络由前200个circRNA-miRNA-mRNA配对组成。绿色菱形、黄色三角形和粉色圆形节点分别代表DEC、DEMi和DEM。蓝色线条表示基因间的调控关系。b，miR-101c、miR-1927、miR-7055-3p、miR-802-5p和miR-877-3p在circ_0001577 序列上的预测结合位点。红色圆圈表示circ_0001577的序列，每条蓝色短线表示目标miRNA的结合位点。

图 1 ceRNA网络的构建

Figure 1. Constructed ceRNA network

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注： a，按P值升序排列的前10个不同类别的GO术语；b，按P值升序排列的所有GO术语中的前30个。

图 2 GO富集分析

Figure 2. GO enrichment analysis

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图 3 KEGG信号通路分析

Figure 3. KEGG signaling pathway analysis

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注： a，circ_0001577、miR-7055-3p和Akt3在两组中的相对表达水平；b～d，miR-7055-3p、circ_0001577和Akt3在转录水平上表达的相关性。

图 4 选择基因的相对表达量及相关性

Figure 4. Relative expression and correlation of the selected genes

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注： C1～6为对照组6只小鼠；M1～6为模型组6只小鼠。

图 5 Akt3蛋白的相对表达

Figure 5. Relative expression of Akt3 protein

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注： a，Akt3蛋白与circ_0001577；b，Akt3蛋白与miR-7055-3p。

图 6 Akt3蛋白表达与circ_0001577、miR-7055-3p之间的相关性

Figure 6. Correlation between expression of Akt3 protein and circ_0001577， miR-7055-3p

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注： a，血清AST和ALT水平；b，肝组织中MDA含量；c，肝组织中NO含量。

图 7 肝损伤指标的比较

Figure 7. Comparison of indicators of liver injury

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注： a，circ_0001577与ALT；b，circ_0001577与AST；c，circ_0001577与MDA；d，circ_0001577与NO。

图 8 circ_0001577表达与肝损伤指标之间的相关性

Figure 8. Correlation between expression of circ_0001577 and liver injury indicators

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注： a，miR-7055-3p与ALT；b，miR-7055-3p与AST；c，miR-7055-3p与MDA；d，miR-7055-3p与NO。

图 9 miR-7055-3p表达与肝损伤指标之间的相关性

Figure 9. Correlation between expression of miR-7055-3p and liver injury indicators

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注： a，Akt3与ALT；b，Akt3与AST；c，Akt3与MDA；d，Akt3与NO。

图 10 Akt3表达与肝损伤指标之间的相关性

Figure 10. Correlation between expression of Akt3 and liver injury indicators

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注： a，Akt3蛋白与ALT；b，Akt3蛋白与AST；c，Akt3蛋白与MDA；d，Akt3蛋白与NO。

图 11 Akt3蛋白表达与肝损伤指标之间的相关性

Figure 11. Correlation between expression of Akt3 protein and liver injury indicators

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表 1 用于qRT-PCR验证的基因特征

Table 1. Gene characteristics for qRT-PCR validation

基因	编号	染色体	FC	P值	调控情况
circ_0001577	无	chr7	2.35	9.04×10^-5	上调
miR-7055-3p	MIMAT0028015	chr7	-6.37	6.83×10^-3	下调
Akt3	XM_006496821.3	chr1	2.31	3.85×10^-4	上调

下载: 导出CSV

表 2 引物序列

Table 2. Primer sequences

基因	引物（5'-3'）	长度（bp）
circ_0001577	F：TGATTATGTCCAGGCCCTTC	141
circ_0001577	R：TATCTCACAGGCACCCTCAAC	141
miR-7055-3p	RT：CTCAACTGGTGTCGTGGAGTCGGCAATTCAGTTGAGCTGGTGGG	21
	F：ACACTCCAGCTGGGTTGCTACTTTGATAC
	R：TGGTGTCGTGGAGTCG
Akt3	F：CATTGCTTTCAGGGCTCTTG	246
Akt3	R：TGCCGTCGTCGTCATACTTT	246
GAPDH	F：GGTTGTCTCCTGCGACTTCA	183
GAPDH	R：TGGTCCAGGGTTTCTTACTCC	183
U6	F：CTCGCTTCGGCAGCACA	96
U6	R：AACGCTTCACGAATTTGCGT	96

下载: 导出CSV

表 3 按ceRNA评分降序排列的前10个ceRNA配对

Table 3. Top 10 ceRNA pairs in descending order of ceRNA Score

mRNA	circRNA	共有miRNA	P值	ceRNA得分
XM_006519062.2	circ_0001577	miR-7055-3p	<0.001	0.017 2
		miR-101c
		miR-877-3p
		miR-1927
		miR-802-5p
XM_017318309.1	circ_0001577	miR-7055-3p	<0.001	0.014 5
		miR-101c
		miR-877-3p
		miR-1927
		miR-802-5p
XM_017314716.1	circ_0001577	miR-877-3p	0.026	0.014 4
		miR-802-5p
		miR-1927
		miR-7055-3p
XM_006495688.3	circ_0001577	miR-877-3p	0.019	0.013 5
		miR-802-5p
		miR-1927
		miR-7055-3p
XM_006495684.3	circ_0001577	miR-877-3p	0.019	0.013 5
		miR-802-5p
		miR-1927
		miR-7055-3p
XM_006495682.2	circ_0001577	miR-877-3p	0.019	0.013 5
		miR-802-5p
		miR-1927
		miR-7055-3p
NM_133833.3	circ_0001577	miR-877-3p	0.019	0.013 5
		miR-802-5p
		miR-1927
		miR-7055-3p
XM_017314712.1	circ_0001577	miR-877-3p	0.019	0.013 5
		miR-802-5p
		miR-1927
		miR-7055-3p
XM_017314794.1	circ_0001577	miR-877-3p	0.014	0.012 5
		miR-802-5p
		miR-1927
		miR-7055-3p
XM_017314741.1	circ_0001577	miR-877-3p	0.014	0.012 5
		miR-802-5p
		miR-1927
		miR-7055-3p

下载: 导出CSV

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