Bioinformatics Analysis of the Effects of Tobacco Smoke on Gene Expression.
Bioinformatics Analysis of the Effects of Tobacco Smoke on Gene Expression.
复制标题
烟草烟雾对基因表达影响的生物信息学分析。
DOI：
10.1371/journal.pone.0143377
复制
发表时间：
2015
期刊：
影响因子：
3.7
通讯作者：
Zou D
中科院分区：
文献类型：
--
作者：
Cao C;Chen J;Lyu C;Yu J;Zhao W;Wang Y;Zou D
本研究旨在通过生物信息学分析探讨烟草烟雾对基因表达的影响。从Gene Expression Omnibus数据库下载基因表达谱GSE 17913。对39例吸烟者和40例非吸烟者口腔颊粘膜组织中的差异表达基因进行了分析。对DEG进行GO和途径富集分析，构建蛋白质-蛋白质相互作用（PPI）网络、转录调控网络和miRNA-靶调控网络。总共鉴定了88个上调的DEG和106个下调的DEG。在这些DEG中，细胞色素P450家族1、亚家族A、多肽1（CYP 1A 1）和CYP 1B 1通过细胞色素P450途径富集在外源性物质的代谢中。在PPI网络中，酪氨酸3-单加氧酶/色氨酸5-单加氧酶激活蛋白zeta（YWHAZ）和CYP 1A 1是枢纽基因。在转录调控网络中，MYC相关因子X（MAX）和上游转录因子1（USF 1）的转录因子调控着许多重叠的DEG。此外，在miRNA-DEG调控网络中，蛋白酪氨酸磷酸酶，受体类型，D（PTPRD）受到多个miRNA的调控。CYP 1A 1、CYP 1B 1、YWHAZ和PTPRD以及MAX和USF 1的TF有可能作为烟草烟雾相关病变的生物标志物和治疗靶点。
This study was designed to explore the effects of tobacco smoke on gene expression through bioinformatics analyses. Gene expression profile GSE17913 was downloaded from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) in buccal mucosa tissues between 39 active smokers and 40 never smokers were identified. Gene Ontology (GO) and pathway enrichment analyses of DEGs were performed, followed by protein-protein interaction (PPI) network, transcriptional regulatory network as well as miRNA-target regulatory network construction. In total, 88 up-regulated DEGs and 106 down-regulated DEGs were identified. Among these DEGs, cytochrome P450, family 1, subfamily A, polypeptide 1 (CYP1A1) and CYP1B1 were enriched in the Metabolism of xenobiotics by cytochrome P450 pathway. In the PPI network, tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein, zeta (YWHAZ), and CYP1A1 were hub genes. In the transcriptional regulatory network, transcription factors of MYC associated factor X (MAX) and upstream transcription factor 1 (USF1) regulated many overlapped DEGs. In addition, protein tyrosine phosphatase, receptor type, D (PTPRD) was regulated by multiple miRNAs in the miRNA-DEG regulatory network. CYP1A1, CYP1B1, YWHAZ and PTPRD, and TF of MAX and USF1 may have the potential to be used as biomarkers and therapeutic targets in tobacco smoke-related pathological changes.