中国组织工程研究 ›› 2022, Vol. 26 ›› Issue (24): 3908-3913.doi: 10.12307/2022.575

• 干细胞综述 stem cell review • 上一篇    下一篇

脂肪干细胞成骨分化的转录因子-miRNA-mRNA网络分析

余春波,李大玉,范  芳,李长福   

  1. 遵义医科大学基础医学院,贵州省遵义市   563000
  • 收稿日期:2021-08-30 接受日期:2021-10-11 出版日期:2022-08-28 发布日期:2022-01-24
  • 通讯作者: 李长福,硕士,教授,遵义医科大学基础医学院,贵州省遵义市 563000
  • 作者简介:余春波,男,1989年生,贵州省遵义市人,汉族,2019年遵义医科大学毕业,硕士,实验师,主要从事肿瘤分子生物学研究。
  • 基金资助:
    遵义市市校联合基金[遵市科合HZ字(2020)87号],项目负责人:余春波

Transcription factor-miRNA-mRNA network analysis of osteogenic differentiation of adipose-derived stem cells

Yu Chunbo, Li Dayu, Fan Fang, Li Changfu   

  1. School of Basic Medicine, Zunyi Medical University, Zunyi 563000, Guizhou Province, China
  • Received:2021-08-30 Accepted:2021-10-11 Online:2022-08-28 Published:2022-01-24
  • Contact: Li Changfu, Master, Professor, School of Basic Medicine, Zunyi Medical University, Zunyi 563000, Guizhou Province, China
  • About author:Yu Chunbo, Master, Experimentalist, School of Basic Medicine, Zunyi Medical University, Zunyi 563000, Guizhou Province, China
  • Supported by:
    Zunyi City School Joint Fund, No. Zunyi Kehe HZ (2020)87 (to YCB)

摘要:

文题释义:
脂肪干细胞:是一种非常具有发展前景的组织工程细胞类型,可分化为脂肪细胞、成骨细胞、软骨细胞和肌细胞等,有恢复组织细胞、促进细胞再生及有效改善亚健康、早衰、抵抗衰老等作用。
成骨分化:是骨质形成的基础,也骨生成的关键步骤,涉及生长因子、信号通路及调控基因等多种因素,多种信号通路的共同影响下介导和调控干细胞的成骨分化。

背景:脂肪干细胞来源广泛、易于获取,人脂肪组织来源的干细胞进入分化骨细胞涉及基因表达的变化主要受miRNA和转录因子调节,但调节脂肪干细胞成骨分化的转录因子-miRNA-mRNA调控网络尚未建立。
目的:筛选脂肪干细胞成骨分化过程中的差异表达基因、差异表达miRNA及转录因子,探讨脂肪干细胞成骨分化过程中的转录因子-miRNA-mRNA调控网络及其潜在的靶基因、miRNA和转录因子。
方法:从GEO数据库获取3张芯片(GSE37329,GSE63754 mRNA数据芯片2张,GSE72429 miRNA数据芯片1张),筛选差异表达基因和差异表达miRNA;差异表达基因进行PPI网络、GO功能和KEGG信号通路分析;随后差异表达基因预测上游miRNA,差异表达miRNA预测转录因子,通过Cytoscape3.7.1软件构建转录因子-miRNA-mRNA网络图。
结果与结论:筛选出86个差异表达基因(26个上调,60个下调)、16个差异表达miRNA (10个上调,6个下调);PPI网络中蛋白互作共表达的占76.52%,协同定位的占8.69%;GO功能富集分析主要在对经典Wnt信号通路的负调控、软骨发育的负调控等功能相关,KEGG信号通路涉及酪氨酸代谢、脂肪酸降解等信号通路;差异表达基因预测到11 381个miRNA及差异miRNA预测到55个转录因子,构建转录因子-miRNA-mRNA调控网络。脂肪干细胞成骨分化过程中的关键基因可能是PODXL、SEMA3D、ADGRG6、LGR4、LPL、CADM3、GRIA1、GPM6B、RERG、APCDD1和NRCAM,重要的miRNA有hsa-miR-502-3p、hsa-miR-762和hsa-miR-1275,核心转录因子是CTCF、TAL1、STAT2、STAT1和TCF3。结果显示,通过生物信息学技术和数据库挖掘等方法构建的转录因子-miRNA-mRNA调控网络,为脂肪干细胞成骨分化的深入研究提供潜在的治疗靶标。

https://orcid.org/0000-0002-2563-550X (余春波)

中国组织工程研究杂志出版内容重点:干细胞;骨髓干细胞;造血干细胞;脂肪干细胞;肿瘤干细胞;胚胎干细胞;脐带脐血干细胞;干细胞诱导;干细胞分化;组织工程

关键词: 脂肪干细胞, 成骨分化, 转录因子, 生物信息学, miRNA, 差异表达基因

Abstract: BACKGROUND: Adipose stem cells have a wide range of sources and are easy to obtain. The changes in gene expression involved in the entry of human adipose tissue-derived stem cells into differentiated bone cells are mainly regulated by miRNA and transcription factor, but the specific molecular mechanisms that regulate the osteogenic differentiation of adipose stem cells and their potential transcription factor-miRNA-mRNA regulatory network have not yet been established.  
OBJECTIVE: To screen the differentially expressed genes, differentially expressed miRNAs and transcription factors during the osteogenic differentiation of adipose-derived stem cells, and to explore the potential target genes, miRNAs, transcription factors, and transcription factor-miRNA-mRNA regulatory network during the osteogenic differentiation of adipose-derived stem cells.
METHODS:  GEO database was used to acquire three chips (GSE37329, GSE63754 two miRNA gene chips and GSE72429 one miRNA data chip) to screen differentially expressed genes and differential miRNAs. Differentially expressed genes were analyzed for PPI network, GO function, and KEGG signaling pathway. Differentially expressed genes were utilized to predict upstream miRNAs and differential miRNAs pre-transcription factors. Transcription factor-miRNA-mRNA network diagrams were constructed through Cytoscape 3.7.1 software.  
RESULTS AND CONCLUSION: Eighty-six differentially expressed genes (26 up-regulated genes, 60 down-regulated genes) and 16 differential miRNAs (10 up-regulated miRNAs, 6 down-regulated miRNAs) were screened out. There were 76.52% of protein interactions and co-expression and 8.69% of synergistic localization in the PPI network. GO function enrichment analysis was mainly related to the negative regulation of the classical Wnt signaling pathway and the negative regulation of cartilage development. The KEGG signaling pathway involved signaling pathways, such as tyrosine metabolism and fatty acid degradation. Differentially expressed genes predicted 11 381 miRNAs and differential miRNAs predicted 55 transcription factors. Transcription factor-miRNA-mRNA regulatory network was constructed. The key genes in the osteogenic differentiation of adipose-derived stem cells may be PODXL, SEMA3D, ADGRG6, LGR4, LPL, CADM3, GRIA1, GPM6B, RERG, APCDD1, and NRCAM. Important miRNAs were: hsa-miR-762, hsa-miR-502-3p, and hsa-miR-1275. The core transcription factors were CTCF, TAL1, STAT2, STAT1, and TCF3. The results show that the transcription factor-miRNA-mRNA regulatory network constructed through bioinformatics technology and database mining methods provides potential therapeutic targets for the in-depth study of osteogenic differentiation of adipose-derived stem cells.

Key words: adipose-derived stem cells, osteogenic differentiation, transcription factor, bioinformatics, miRNA, differentially expressed genes

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