南方医科大学学报 ›› 2015, Vol. 35 ›› Issue (12): 1775-.

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差异基因表达谱分析小鼠烧伤早期免疫细胞刺激反应的相关基因靶标

金辉,高艳彬,卢志阳,邹琼,史鹏伟,杨磊   

  • 出版日期:2015-12-20 发布日期:2015-12-20

Screening genes related with leukocyte responses early after burn injury: analysis of
differentially gene expression profiling data in mice

  • Online:2015-12-20 Published:2015-12-20

摘要: 目的利用生物信息学方法对小鼠烧伤早期免疫细胞差异基因表达谱进行分析,筛选烧伤早期应对刺激反应相关基因靶
标。方法从GEO数据库中下载GSE7404数据集,通过配对样本t检验和倍比法筛选差异表达基因,利用DAVID数据库进行
GO功能富集分析筛选刺激反应相关差异表达基因,并进行KEGG通路富集分析,同时应用STRING数据库及Cytoscape软件构
建刺激反应相关基因的蛋白互作网络,运用荧光定量PCR技术验证其中部分基因差异表达。结果(1)在烧伤后第1天共有259
个刺激反应相关差异基因被选出,其中上调基因118个,下调基因141个。KEGG通路富集分析显示差异基因主要富集于免疫
相关通路及细胞生长与死亡相关通路;将259个刺激反应相关差异基因通过STRING数据库及Cytoscape软件进行蛋白互作网
络分析,分析显示Lck、Stat1、Myd88、Stat3和Jun基因同时在蛋白互作网络中具有最大互作关系和在子网络中处于中心位置,可
能是潜在的诊断及治疗靶标;(2)实时荧光定量PCR技术检测显示Lck、Stat1、Myd88、Stat3和Jun基因表达情况与分析结果相一
致。结论通过对小鼠烧伤后第1天全血游离白细胞基因芯片分析我们发现Lck、Stat1、Myd88、Stat3和Jun基因在烧伤早期刺
激反应过程中发挥重要的作用。

Abstract: Objective To screen the genes related with leukocyte responses in mice early after burn injury by bioinformatic
analysis of the gene expression profiling data. Methods Gene expression profiles were obtained from GEO (GSE7404, Mouse
musculus, 25% TBSA, full-thickness) database. After screening of the differentially expressed genes (DEGs) through
paired-sample t-test and fold-change, DAVID online tools were used to select the DEGs related to leukocyte responses to burns
by GO functional enrichment analysis; the interacting genes identified through KEGG pathway enrichment analysis were
transferred to STRING to construct the protein-protein interaction (PPI) network. Biological annotation of the sub-networks
was executed using the software Cytoscape. Real-time PCR was used to verify the DEGs identified in mice. Results Of the 259
leukocyte response-related DEGs screened at 1 day post-burn, 118 were up-regulated and 141 were down-regulated. KEGG
pathway enrichment analysis showed that the pathways were associated with the immune function, cell growth and cell death.
PPI network and module analysis suggested that some of genes (such as Lck, Stat1, Myd88, Stat3, and Jun) play critical roles in
the PPI network post-burn. RT-PCR results were consistent with those of bioinformatic analysis. Conclusion Lck, Stat1, Myd88,
Stat3, and Jun might be critical players in the development of leukocyte response in mice early after burn injury. Our finding
provides new insights into the pathogenesis of leukocyte response to burn injury and identifies several potential biomarkers
for burn treatment.