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Journal of Central South University Medical Sciences logoLink to Journal of Central South University Medical Sciences
. 2022 Sep 28;47(9):1208–1216. [Article in Chinese] doi: 10.11817/j.issn.1672-7347.2022.210789

MicroRNA在胶原诱导型关节炎大鼠中的异常表达及功能分析

Expression and function analysis of microRNA in collagen-induced arthritis rats

WEN Yuqi 1,2, HE Cailin 1, WANG Yang 1, CHEN Pin 2, XIONG Xingui 1,✉
Editor: 傅 希文
PMCID: PMC10930329  PMID: 36411704

Abstract

Objective

Rheumatoid arthritis is a common autoimmune disease, and microRNAs (miRNAs) are involved in its pathogenesis. This study aims to examine the differentially expressed miRNAs in collagen-induced arthritis (CIA) rats, to analyze the biological functions and the related pathways of the miRNA target genes.

Methods

The total RNA in the synovium of experimental animals was extracted. The miRNA gene profile was obtained by miRNA microarray. Then the differentially expressed miRNAs were screened and the relevant target mRNAs were predicted. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed on the significantly differentially expressed miRNAs.

Results

There were 69 differentially expressed miRNAs including rno-miR-6215 and rno-miR-709 in CIA rats, of which 22 (31.9%) were up-regulated and 47 (68.1%) were down-regulated. GO and KEGG enrichment analysis showed that the up-regulated miRNA target genes were mainly enriched in cellular metabolism, and they were involved in MAPK and Wnt signaling pathways. The down-regulated miRNA target genes were mainly enriched in nervous system development, and they were involved in axon guidance signaling pathway.

Conclusion

There are differentially expressed miRNAs in the CIA rat model, which may be involved in metabolism biological functions and signal pathways such as MAPK and Wnt.

Keywords: rheumatoid arthritis, microRNA, collagen-induced arthritis rats

类风湿性关节炎(rheumatoid arthritis，RA)是一种常见的全身炎症性和自身免疫性疾病，以小关节肿胀疼痛、僵硬及活动障碍等为主要临床表现。RA作为一种慢性进展性疾病，可引起受累关节及周围组织不可逆性损伤，造成患者关节活动功能障碍乃至终身致残[1-2]。然而RA作为一种遗传和环境多因素介导的慢性疾病[3-5]，目前针对RA的基础及临床相关研究均不能完整解释其发病机制，故临床也缺乏特异性的诊断和治疗手段。

近年来，非编码RNA(non-coding RNA，ncRNA)的相关研究正成为揭示RA发病机制的新突破口。微RNA(microRNA，miRNA)为长度在21~23 nt、具有调控功能的ncRNA，具有高度保守性，并与细胞的增殖、分化和凋亡、机体免疫等广泛生物学过程有关[6]。已有研究[7-9]证明miR-155，miR-146和miR-223等miRNA在RA患者的滑膜组织、血清样本、外周血单核细胞中存在不同程度的表达上调。通过miRNA的相关测序和功能分析或可进一步揭示RA的发病机制，并为临床上RA的诊断和治疗研究提供思路。

1. 材料与方法

1.1. 实验动物与分组

胶原诱导型关节炎(collagen-induced arthritis，CIA)大鼠模型复制参考文献[10]，选用7~8周雄性Sprague Dawley(SD)大鼠10只，体重为180~200 g。从1到10对其进行编号，并根据随机数字表法将10只大鼠分为处理组和对照组。

10只大鼠饲养于中南大学湘雅医学院实验动物学部，在相同条件下[温度(21±2) ℃，湿度70%，光照时间为6:00—18:00，自由饮食]适应性饲养7 d。造模选用试剂牛II型胶原(美国Chondrex公司)、完全弗式佐剂(美国Sigma公司)，按1꞉1比例混合。处理组为CIA大鼠造模组，使用混合乳剂于大鼠尾部、足底各注射0.1 mL，1周后足底注射0.1 mL进行增强；对照组为空白对照组，按处理组注射方案注射等剂量生理盐水。饲养周期结束后，参照关节炎指数(arthritis index，AI)对大鼠进行评分[11]。评分合格后，取10只大鼠双腿滑膜组织提取总RNA。

1.2. 测定基因表达谱

使用RNA提取试剂TRIzol(美国Sigma公司)提取样本总RNA。利用琼脂糖凝胶电泳检测总RNA样品的完整性。使用NanoDrop ND-1000型微量核酸蛋白定量仪(美国Thermo Fisher Scientific公司)测定总RNA准确的浓度以及蛋白质污染等情况。通过NEBNext® Poly(A) mRNA磁性分离模块(新英格兰Biolabs公司)提取实验动物滑膜组织样品总RNA中完整的带有poly(A)结构的RNA。按照说明书使用核糖体RNA去除试剂盒(美国RiboZero Magnetic Gold Kit，Epicentre公司)，在保留miRNA调控区的基础上去除样品中多余的rRNA；质检合格后的RNA样品可进行miRNA文库构建。

按照说明使用簇生成和测序试剂盒(TruSeq Rapid SR Cluster Kit，美国Illumina公司)，通过 0.1 mol/L NaOH变性将文库变为单链DNA分子，并在Illumina NextSeq 500测序仪流动池上捕获cDNA，进行原位扩增；再在Illumina NextSeq 500测序仪(美国Illumina公司)上进行51个循环的测序。测序仪产生的原始测序数据经测序质量控制步骤和过滤步骤去除测序片段中的3'接头序列、过短片段和低质量测序片段，获得对比结果良好的测序数据。

1.3. 差异表达miRNA的筛选

通过miRNA芯片数据处理软件mirDeep2将芯片数据与已知的基因组进行对比，获得miRNA的定量表达。MiRNA表达量阈值设定为每组中每百万次读取计数(counts per million reads，CPM)均值≥1(CPM为比对到某基因上的测序片段数目的106乘积与获得的所有基因的总测序片段数目之比)，则视为该miRNA在分组中的表达并对其进行统计分析。设定阈值|logFC|>1(FC为差值倍数，logFC即为两组表达量间以2为底数的对数化的变化倍数)，P<0.05为差异表达的miRNA，使用差异分析软件edgeR对组间miRNAs的差异表达进行筛选和分析。

1.4. 靶基因功能富集分析

基因本体(Gene Ontology，GO)富集分析是一种基因功能分类条目的数据库，包括基因的分子功能(molecular function，MF)、细胞组成(cellular component，CC)、参与的生物学过程(biological process，BP)3个子条目。采用双侧Fisher精确检验和χ2检验对GO类别进行分类，从而可计算错误发现率(false discover rate，FDR)以修正P值，FDR越小，判断P值的误差越小；P值越小则表明该GO条目和输入的基因联系越大[12-13]。

京都基因和基因组数据库(Kyoto Encyclopedia of Genes and Genomes，KEGG)通路富集分析可赋予基因和基因组在分子和更高水平上的功能意义。根据最新的KEGG(http://www.kegg.jp/或http://www.genome.jp/kegg/)数据库中的生物学通路分类条目，采用Fisher精确检验和χ2检验来选择显著路径，显著性阈值由P值和FDR定义，P值越小则表明该通路条目和输入的差异表达miRNA靶基因的联系越大[14]。

1.5. Real-time PCR验证

使用引物设计软件Primer 5.0设计目标miRNA的扩增引物。目标miRNA和内参(U6)分别进行real-time PCR反应。挑选显著差异表达的4个miRNA，大鼠(rno)-miR-299-5p的引物正向5'-CCTGGTTTAC-CGTCCC-3'，反向5'-CAGTGCGTGTCGTGGA-3'；rno-miR-709的引物正向5'-GGGAAAGGAGGCAG-AGGC-3'，反向5'-GTGCGTGTCGTGGAGTCG-3'；rno-miR-3473的引物正向5'-GGGGACTAGGGCTG-GAGAG-3'，反向5'-GTGCGTGTCGTGGAGTCG-3'；rno-miR-6215的引物正向5'-GGGGGTTTAGGGTT-GCAGA-3'，反向5'-GTGCGTGTCGTGGAGTCG-3'；内参U6引物正向5'-GCTTCGGCAGCACATATACT-AAAAT-3'，反向5'-CGCTTCACGAATTTGCGTG-TCAT-3'。数据采用2-ΔΔCt法进行分析：ΔΔCt=[实验组(Ct目的基因-Ct内参基因)-对照组(Ct目的基因-Ct内参基因)]。

2. 结 果

2.1. CIA大鼠模型质量评估

实验参照AI、大鼠四肢外观及HE染色切片对处理组大鼠造模质量进行评估。造模干预后，处理组大鼠体重增长值要低于对照组，AI在行增强后显著增加(均P<0.05)。与对照组大鼠相比，处理组大鼠的四肢外观可见明显发红、肿胀，其评分越高踝关节肿胀越严重(图1，2)。同时，HE染色切片显示：处理组大鼠踝关节切片炎症细胞增多，浸润周围组织，部分细胞增大，包浆内有空泡，细胞核呈不规则改变(图3)。上述结果表明CIA大鼠模型复制成功。

图1.

图1

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对照组和处理组28 d体重增加值及AI指数变化

Figure 1 Weight and AI changes in the control group and the treatment group at 28 days

AI: Arthritis index. *P<0.05 vs the control group.

图2.

图2

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对照组和处理组大鼠足部外观表现

Figure 2 Appearance of feet of rats in the control group and the treatment group

A: Control group; B: Treatment group (2 scores); C: Treatment group (4 scores).

图3.

图3

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对照组和处理组HE染色病理切片

Figure 3 Pathological sections in the control group and the treat group by HE staining

A: Control group; B: Control group; C: Treatment group; D: Treatment group.

2.2. 差异表达的miRNA的结果分析

对对照组和处理组差异表达的全部miRNA进行聚类分析，显示两组之间存在显著上调或下调的miRNA差异表达，即处理组与对照相比存在显著差异表达的miRNA(图4)。根据已定阈值挑选显著差异表达的miRNA，处理组中有69个差异表达的miRNA，包括rno-miR-6215、rno-miR-709、rno-miR-154-3p等；其中有22个(31.9%)上调和47个(68.1%)下调(图5)。其中处理组前10个显著差异表达的上调和下调的miRNA相关信息详见表1。

图4.

图4

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对照组和处理组差异表达的miRNA的聚类热图

Figure 4 Clustering heat map of differentially expressed miRNAs in the control group and the treatment group

Each row represents one miRNA, each column represents one sample, red represents significantly differentially expressed up-regulated miRNAs, and green represents significantly differentially expressed down-regulated miRNAs. C1, C2, C3, C4, and C5 respresent the sample number of the control group; T1, T2, T3, T4, and T5 respresent the sample number of the treatment group.

图5.

图5

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差异表达的miRNA的火山图

Figure 5 Volcano plot of differentially expressed miRNAs

表1.

处理组前10个显著性差异表达的上调和下调的miRNA

Table 1 Top 10 significantly differentially expressed up- and down-regulated miRNAs in the treatment group

成熟miRNA名称 臂 差异倍数对数值 差异倍数 P q
rno-miR-6215 5p 6.41 84.75 2.29E-03 2.27E-02
rno-miR-709 5p 4.56 23.55 7.60E-08 7.14E-06
rno-miR-3473 5p 3.64 12.43 2.24E-05 5.79E-04
rno-miR-365-5p 5p 2.44 5.42 7.66E-08 7.14E-06
rno-miR-128-1-5p 5p 1.78 3.44 5.23E-03 4.06E-02
rno-miR-494-3p 3p -2.34 0.20 1.31E-12 6.11E-10
rno-miR-668 5p -2.47 0.18 6.92E-03 5.05E-02
rno-miR-1193-3p 3p -2.94 0.13 4.09E-10 9.53E-08
rno-miR-299a-5p 5p -3.05 0.12 2.14E-06 8.49E-05
rno-miR-154-3p 3p -3.49 0.09 2.19E-06 8.49E-05
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2.3. MiRNA的靶基因

使用miRNA靶基因在线预测数据库miRBase(http://mirdb.org/miRDB/)预测显著差异表达的miRNA的目标靶基因，并对显著上调或下调差异表达前10的miRNA进行靶基因筛选。基于miRBase靶基因预测数据库，前10个显著差异上调或下调的miRNA的靶基因预测结果详见表2。

表2.

处理组前10个显著性差异上调和下调miRNA的靶基因

Table 2 Top 10 significantly differentially up-regulated and down-regulated miRNA target genes in the treatment group

成熟miRNA名称 目标基因 数据库预测基因数 计数 成熟miRNA名称 目标基因 数据库预测基因数 计数
rno-miR-6215 Plagl1 1 1 rno-miR-494-3p Mphosph6 1 1
rno-miR-709 Erf 1 1 rno-miR-668 Kdm1b 1 1
rno-miR-3473 Taf9b 1 1 rno-miR-1193-3p Nr1d2 1 1
rno-miR-365-5p Zbtb4 1 1 rno-miR-299a-5p Sema3d 1 1
rno-miR-128-1-5p Csk 1 1 rno-miR-154-3p Cyp20a1 1 1
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2.4. GO和KEGG富集分析

GO富集分析结果显示：显著差异表达上调的miRNA靶基因主要富集于细胞代谢过程，结构上属于细胞内区，分子功能上主要与多肽结合；显著差异表达下调的miRNA靶基因主要富集于神经系统发育，结构上属于细胞内区，分子功能上主要与蛋白质结合(图6)。

图6.

图6

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上调、下调的差异表达miRNA靶基因GO富集分析

Figure 6 GO enrichment analysis of up-regulated and down-regulated differentially expressed miRNA target genes

GO enrichment analysis is a classification of gene functions, including three sub-items: molecular function (MF), cellular component (CC), and biological process (BP) of genes. The enrichment score represents the degree to which the members of the set are overexpressed at the top or bottom of the sorted list. The higher the score, the greater the degree of overexpression.

KEGG通路分析结果显示：富集指数前3位的显著差异表达上调的miRNA靶基因中有30个富集于MAPK信号通路，18个富集于Wnt信号通路，13个富集于γ-氨基丁酸突触能信号通路；富集指数较高的显著差异表达下调的miRNA靶基因主要富集于涉及轴突引导、致心律失常性右室心肌病(arrhythmogeic right ventricular cardiomyophathy，ARVC)、转化生长因子-β(transforming growth factor β，TGF-β)信号通路等(图7)。

图7.

图7

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上调、下调的差异表达miRNA靶基因KEGG富集分析

Figure 7 KEGG enrichment analysis of up-regulated and down-regulated differentially expressed miRNA target genes

MAPK: Mitogen-activated protein kinase; Wnt: Wingless-integrated；FOX: Forkhead box protein; ErbB1: Epidermal growth factor receptor; TGF-β: Transforming growth factor beta; Th17: T helper cell 17.

2.5. 新miRNA预测结果

通过数据处理软件Dicer对miRNA前体处理并建立简单模型，miRNA芯片数据处理软件mirDeep2可重现异质性深度测序样品中大部分已知的miRNA，并以高可信度预测新的miRNA。通过miDeep2预测新的miRNA并对其可信度进行预测，发现有chr3-11861、chr14-48256、chr7-27452等可信度较高的新miRNA，其在基因中的位置、序列读数及成熟序列等信息详见表3。

表3.

新RNA预测及相关数据表达

Table 3 New miRNA predictions and related data expression

名称 基因坐标 基因总数 成熟序列
chr3-11861 chr3:11348208..11348268:+ 1 585 687 5'-ACAGUAGUCUGCACAUUGGUU-3'
chr14-48256 chr14:30326667..30326729:- 10 177 5'-UAAUGCCCCUAAAAAUCCUUAU-3'
chr7-27452 chr7:77464141..77464206:+ 7 269 5'-UCUCGGUGGAACCUCCA-3'
chr15-50404 chr15:41961043..41961108:- 3 660 5'-CCAGUAUUGACUGUGCUGCUGAA-3'
chr10-36823 chr10:4763069..4763143:+ 2 945 5'-ACAGAAGUCUGCAUAUUGGUU-3'
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2.6. 部分显著差异表达miRNA的real-time PCR验证

为了进一步验证miRNA芯片的结果，实验选取了部分显著差异表达miRNA进行real-time PCR验证。被选中的4条miRNA中，1条(rno-miR-299a-5p)显著下调；3条(rno-miR-709、rno-miR-3473、rno-miR-6215)显著上调，差异均具有统计学意义(均P<0.05或P<0.01)。经PCR验证的4条miRNA相对表达量与miRNA芯片结果一致，证实了测序结果的可靠性(图8)。

图8.

图8

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部分显著差异表达miRNA(rno-miR-299a-5p、rno-miR-709、rno-miR-3473、rno-miR-6215)的real-time PCR验证

Figure 8 Real-time PCR validation of some significantly differentially expressed miRNAs (rno-miR-299a-5p, rno-miR-709, rno-miR-3473, rno-miR-6215)

*P<0.05, **P<0.01 vs the control group.

3. 讨 论

人体内只有1.5%~2.0%的基因组能够编码蛋白质，体内其余75.0%~90.0%的DNA转录任务则需要由非编码RNA来承担[15]。MiRNA作为非编码RNA的重要成员，可通过与靶基因mRNA的3'非翻译区结合造成mRNA的翻译或抑制调节[16]。1993年人类发现RNA研究史上第一个miRNA，自此便揭开研究miRNA的序幕[17]，此后针对各类新型miRNA的鉴定、结构和功能研究获得了有序的进展。RA作为一种发病机制尚不明确、特异性治疗手段有限的慢性自身免疫性疾病，可在患者体内发现RA特异性表达的miRNA，这或许可从转录学角度解释RA的具体发病机制。

CIA大鼠模型为RA的常用动物模型，存在许多与RA患者相似的病理环节，包括胶原的自身抗体诱导、滑膜增生和炎症细胞浸润等[10,18]。对CIA大鼠和正常大鼠同时测序，发现CIA大鼠模型中有包括rno-miR-6215、rno-miR-709等69个差异表达的miRNA，其中22个(31.9%)上调和47个(68.1%)下调。

本研究中GO及KEGG富集分析发现：显著差异表达上调的miRNA靶基因主要参与机体细胞代谢过程、MAPK及Wnt信号通路。活动期RA患者葡萄糖、乳酸等糖酵解代谢产物增加[19]；血浆中胆固醇等脂类代谢物及丙氨酸、缬氨酸、亮氨酸等氨基酸含量下降[20-21]，均表明RA患者体内代谢水平与健康人相比存在差异。从细胞分子水平来看，RA的主要病理特征之一是侵袭性血管翳的形成，而成纤维样滑膜细胞(fibroblast-like synoviocytes，FLS)作为血管翳的重要组成部分，受到刺激后可持续产生IL-6、前列腺素、基质金属蛋白酶等相关细胞因子，诱导局部滑膜炎症反应及蛋白酶溶解，最终导致软骨破坏[22]。RA-FLSs的增殖、活化及相关趋化因子分泌则需要增加细胞内糖酵解及谷氨酰胺分解以持续供能[19,23]。

从富集分析结果的高相关信号通路来看，Wnt蛋白家族由糖蛋白分泌，其介导的信号通路可在胚胎发育及稳态组织中影响细胞活化、细胞极性及细胞结局[24]。Wnt信号通路的激活可导致β-连环蛋白的增加；β-连环蛋白的激活又可引起RA患者体内FLSs的稳定活化[25]。而RA-FLSs可分泌Wnt的拮抗因子Dickkopf相关蛋白1，该蛋白为RA发病机制内成骨细胞轴-破骨细胞轴失衡的主要调节因子。以上证据均表明Wnt信号通路在RA相关FLS内活化，在成骨细胞活动中受到抑制[26-27]。同时亦有研究[28-29]表明P38 MAPK信号途径可通过调节TNF、IL-1、IL-6等炎症介质而影响机体促炎及抗炎平衡，最终造成RA等慢性炎症性疾病的产生。

显著差异表达rno-miR-128-1-5p的靶基因Csk可影响Src酪氨酸激酶家族及激酶相关细胞内信号通路。Scr激酶可参与调控淋巴细胞的激活及骨质疏松骨吸收。有研究[30]表明：Csk过表达可抑制Scr激酶活性，从而抑制激酶增殖、IL-6产生及破骨细胞活动。亦有研究[31]表明：在RA患者体内Csk表达明显降低。SFKs能够启动并调节T细胞抗原受体和B细胞抗原受体，而抑制Csk可快速增加SFK活性，导致对T细胞中抗原受体的反应增强；抑制Csk亦可抑制B细胞抗原受体介导磷脂酰肌醇3激酶在B细胞中产生，影响B细胞的活化[32]。RA患者滑膜中自发的TNF-α很可能是T细胞依赖性的，T细胞的功能调节对于RA的发病或有关键作用[33]。在自体免疫过程中，B细胞可产生抗体、促炎因子、趋化因子，并充当抗原提呈细胞来影响T细胞活化[34]。本研究发现rno-miR-128-1-5p显著上调，其或可通过抑制靶基因Csk活性、激活Scr激酶相关细胞信号通路而参与RA的自身免疫过程。同时，此次测序发现了chr3-11861、chr14-48256、chr7-27452等可信度较高的新miRNA。

综上，CIA大鼠模型内miRNA呈显著差异表达，其靶基因可能通过影响细胞代谢生物功能及MAPK、Wnt等信号通路参与RA的发病过程。然而其主要作用及相关机制、作用网络尚有待进一步研究。

基金资助

国家自然科学基金(81874407)；湖南省自然科学基金(2019JJ40522)；湖南省中医药科研计划重点项目(C2022024)。

This work was supported by the National Natural Science Foundation (81874407), the Natural Science Foundation of Hunan Province (2019JJ40522), and the Key Program of Hunan Province Traditional Chinese Medicine Research (C2022024), China.

利益冲突声明

作者声称无任何利益冲突。

作者贡献

文宇琪 论文设计、撰写与修改，数据分析；何彩林 数据采集；王杨 论文指导；陈玭 数据分析；熊新贵 论文设计、指导及修改。所有作者阅读并同意最终的文本。

原文网址

http://xbyxb.csu.edu.cn/xbwk/fileup/PDF/2022091208.pdf

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