中国组织工程研究

中国组织工程研究 ›› 2011, Vol. 15 ›› Issue (1): 78-81.doi: 10.3969/j.issn.1673-8225.2011. 01.017

• 干细胞因子及调控因子 stem cell factors and regulatory factors • 上一篇    下一篇

胚胎干细胞核心转录因子靶基因集蛋白互作网络特征分析

左长清1，汪宗桂2，吴  铁1，崔  燎1   

  1. 广东医学院，1药理学教研室， 2生物化学教研室，广东省东莞市  523808
  • 收稿日期:2010-07-12 修回日期:2010-09-29 出版日期:2011-01-01 发布日期:2011-01-01
  • 作者简介:左长清☆，男，1977年生，湖南省湘乡市人，汉族，2009年南方医科大学毕业，博士，讲师，主要从事干细胞生物特性和分化调控，生物信息学研究。 chqz77@163.com
  • 基金资助:

    广东医学院博士启动基金(XB1002)。

Analysis of protein interaction networks related to core transcription factors target genes in embryonic stem cells

Zuo Chang-qing1, Wang Zong-gui2, Wu Tie1, Cui Liao1   

  1. 1Department of Pharmacology, 2Department of Biochemistry, Guangdong Medical College, Dongguan  523808, Guangdong Province, China
  • Received:2010-07-12 Revised:2010-09-29 Online:2011-01-01 Published:2011-01-01
  • About author:Zuo Chang-qing☆, Doctor, Lecturer, Department of Pharmacology, Guangdong Medical College, Dongguan 523808, Guangdong Province, China chqz77@163.com
  • Supported by:

    the Doctor Priming Foundation of Guangdong Medical College, No. XB1002

PDF

515

被引次数

1

摘要：

背景：外源性核心转录因子导入终末分化细胞能产生具有与胚胎干细胞特性相似的诱导多潜能干细胞，其复杂机制目前尚未完全阐明。
目的：分析核心转录因子靶基因集蛋白互作网络特征，获得其影响“干性”特征的调控机制。
方法：去除BioGRID数据库中的冗余数据，获得非冗余蛋白互作数据库。perl程序搜索靶基因集组成的蛋白互作对，广度优先算法搜索非冗余蛋白互作数据库，获得靶基因集组成的最大连续蛋白互作网络，同时进行1 000次随机抽样网络分析。通过Cytoscape软件对网络进行可视化分析。复杂无标度网络Barabasi-Albert模型分析网络特征。
结果与结论：核心转录因子靶基因集形成更多的蛋白互作对，最大连续蛋白网络与随机蛋白网络相比具有明显的统计学差异，且核心转录因子靶基因集形成更大的互作网络。网络具有复杂网络无标度特性。该研究通过蛋白互作网络分析证明：靶基因集通过紧密相互作用，形成网络模块方式协调调控胚胎干细胞分子特性。

关键词: 胚胎干细胞, 蛋白相互作用, 生物信息学, 核心转录因子, 网络

Abstract:

BACKGROUND: It is sufficient to reprogram somatic cells, through transduction of some core transcription factors, into pluripotent stem cells (iPS) that exhibit the essential characteristics of embryonic stem (ES) cells. At present, the complex mechanism is not yet fully understood.
OBJECTIVE: To study the protein interaction networks related to core transcription factors target genes in embryonic stem cells and to obtain regulatory mechanism controlled “stemness”.
METHODS: Non-redundant protein interaction data (NRPD) were obtained after removal of redundant data in BioGRID database. Protein interaction pairs, formed by the target genes, were extracted by perl program and the largest continuous protein interaction networks were obtained through searching NRPD using breadth-first search algorithm. At the same time, 1 000 random networks were analyzed and compared. At last, network visualization was analyzed through the Cytoscape software and network characteristics were explained using complex scale-free network model of Barabasi-Albert.
RESULTS AND CONCLUSION: More protein interaction pairs and larger continuous protein network, statistically significant difference compared with random genes, were formed by core transcription factor target genes. The continuous protein network is scale-free characteristics of complex networks. This study has suggested that target genes may regulate synergistically “stemness” characteristics of embryonic stem cells through close interaction and forming a network module.

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