摘要
目的：对急性心肌缺血血瘀证大鼠模型差异microRNAs进行筛选和靶基因的预测,并对相关差异靶基因进行生物信息学分析。方法：采用冠状动脉结扎法结合血液流变学指标制备大鼠急性心肌缺血血瘀证模型,应用表达谱芯片检测病变组织miRNA的差异表达,运用miRNA靶基因数据库筛选靶基因,通过DAVID数据库和GO数据库对筛选出的靶基因进行搜索及注释,并通过VISANT、SPRING数据库进行蛋白相互作用分析。结果：共筛选出27个与急性心肌缺血血瘀证大鼠模型相关的差异miRNAs。初步预测其调控的靶基因数量为46个。差异microRNAs的靶基因主要参与19种生物学过程、9种细胞组分和8类分子途径,发现节点97个,路径映射15个,节点的功能种类包括12类。结论：急性心肌缺血血瘀证大鼠模型差异microRNAs靶基因的功能及相互作用主要体现在信号转导、炎症反应、癌症转录、代谢等方面。急性心肌缺血血瘀证是多环节、多位点、多种生物学进程协同作用的复杂病理反应,利用生物信息学技术可从＂整体＂、＂联系＂的角度对中医证侯的机制作出预测。
Objective： To screen the differential microRNAs of rat model for acute myocardial ischemia with blood stasis syndrome and predict the target gene of the differential microRNAs by applying bioinformatics analysis. Methods： The models of rat for acute myocardial ischemia with blood stasis syndrome were constructed by the peg method and hemorheology index. The differential expressions of tissue-miRNA were detected by the expression spectrum chip. The target gene was screened by using the miRNA target gene database. The genes were forecasted by miRNA target gene database.The screened target genes were searched and annotated through DAVID database and GO database,and an analysis was made in order to search their protein interaction through VISANT and SPRING database. Results： The author in total screened 27 differential miRNAs relating to the rat model for acute myocardial ischemia with blood stasis syndrome. It can be found that there were 46 controlled target genes. Those target genes mainly involved in 19 biological processes,9 cellular components and 8 molecular pathways. In this study,97 nodal points and 15 path mappings were found,and nodal points had 12 types of function. Conclusion： The function and interaction of microRNAs target genes in acute myocardial ischemia rats with blood stasis syndrome are mainly involved in signal transduction,inflammatory response,transcription,metabolism and so on. Acute myocardial ischemia with blood stasis syndrome is a complex pathological reaction of multiple links,multiple points and multiple biological processes. The mechanism of TCM syndrome can be predicted from the perspective of ＂holistic＂and ＂linkage＂by using bioinformatics technology.
作者
罗蔚
郑景辉
陈建军
黄金龙
莫云秋
朱梓铭
伍燕宏
LUO Wei1, ZHENG Jinghui2, CHEN Jianjun2, HUANG Jinlong2, MO Yunqiu2, ZHU Ziming1, WU Yanhong1(1. Graduate School of Guangxi University of Chinese Medicine, Nanning, 530001, Guangxi, China ; 2. Ruikang Hospital Affiliated to Guangxi University of Chinese Medicine, Nanning, 530011, Guangxi, Chin)
出处
《中华中医药学刊》
CAS
北大核心
2018年第5期1142-1146,I0011,I0012,共7页
Chinese Archives of Traditional Chinese Medicine
基金
国家自然科学基金项目(81360535)
广西科学研究与技术开发计划项目(桂科攻1598012-55)
