摘要
目的筛选脓毒症大鼠肝组织中与正常组织差异表达的基因并进行初步功能分析。方法雄性Wistar大鼠30只，随机分为模型组和空白对照组，每组15只。参照盲肠结扎穿孔术（CLP）制备大鼠脓毒症模型，采用含有4096个大鼠基因cDNA克隆的表达谱基因芯片，检测并分析脓毒症大鼠肝组织在CLP后24h的基因表达变化，并以计算机软件筛选出差异表达的基因。结果CLP后24h共筛选出522条与空白对照组相比出现差异的基因，占基因芯片总点数的12．7％，其中244条基因表达下调，278条基因表达上调。结论脓毒症导致的多器官功能障碍综合征（MODS），涉及到一系列与细胞周期、调控、细胞凋亡、免疫相关基因、各种基本生物化学物质代谢酶类基因和能量代谢相关基因、血液相关基因、癌基因相关基因、生长因子类基因、应激反应类基因、细胞信号转导相关基因、DNA结合转录和转录调节因子相关基因、DNA复制与修复相关基因、蛋白质翻译与修饰、加工、降解相关基因等相关的基因表达异常；采用基因芯片检测技术有利于全面揭示脓毒症中的基因表达模式，快速高效地发现新的研究目标和基因治疗途径。
Objective To screen differentially expressed genes of liver tissue in rat sepsis model and analyze them in terms of functions. Methods Thirty male Wistar rats were randomly divided into model group and blank control group with 15 rats in each group. Cecal ligation and puncture （CLP） was used to reproduce rat sepsis model, gene expression profile microarray that contains 4 096 rat cDNA clones was used to detect the change in gene expression pattern of rat liver tissue 24 hours after CLP, then differentially expressed genes that high correlated to sepsis were screened, and the functions of these genes were analyzed by means of related computer software. Results Compared to the controls, gene expression of 522 genes in rat sepsis model were changed 24 hours after CLP, accounting for 12.7%, among them 244 gene expression down -regulated, and 278 gene expression up -regulated. Conclusion Multiple organ dysfunction syndrome （MODS） induced by sepsis involves to a series of gene differential expressions, such as cell cycle and control related genes, cell apoptosis genes, immunity related genes, genes concerning energy metabolism, blood system related genes, cancer related genes, growth factor genes, acute stress reaction related genes etc. Gene microarray technique can be used to comprehensively study gene expression profile in rat sepsis model, in order to find new research objectives and gene therapy strategies for sepsis.
出处
《中国危重病急救医学》
CAS
CSCD
北大核心
2007年第3期156-159,I0001,共5页
Chinese Critical Care Medicine
关键词
脓毒症
肝
基因表达
基因芯片
sepsis
liver
gene expression
gene microarray
