{"title":"用生物信息学分析鉴定地奎特和百草枯中毒的差异表达基因和途径","authors":"C. Miao, Dandan Fan","doi":"10.1080/15376516.2022.2063095","DOIUrl":null,"url":null,"abstract":"Abstract Objective In this study, differentially expressed genes (DEGs) and signaling pathways involved in diquat (DQ) and paraquat (PQ) poisoning were identified via bioinformatics analysis, in order to inform the development of novel clinical treatments. Methods Raw data from GSE153959 were downloaded from the Gene Expression Omnibus database. DEGs of the DQ vs. control (CON) and PQ vs. CON comparison groups were identified using R, and DEGs shared by the two groups were identified using TBtools. Subsequently, the shared DEGs were searched in the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases, using the Database for Annotation, Visualization, and Integrated Discovery. A protein–protein interaction (PPI) network was constructed, and hub genes were identified using the cytoHubba plug-in in Cytoscape software. Finally, circos and contrast plots showing the DEGs shared between mouse and human chromosomes were constructed using TBtools. Results Thirty-one DEGs shared by the DQ and PQ groups were identified. Enriched biological process terms included positive regulation of cell proliferation and translation. Enriched cellular component terms included extracellular region, intracellular membrane-bounded organelle and mitochondrion. Enriched molecular function terms included transcription factor activity and sequence-specific double-stranded DNA binding. Enriched KEGG pathways included the interleukin-17 signaling pathway, tumor necrosis factor signaling pathway, and human T-cell leukemia virus 1 infection. The top 10 hub genes in the PPI network were prostaglandin-endoperoxide synthase 2 (Ptgs2), chemokine (C-X-C motif) ligand 2 (Cxcl2), colony-stimulating factor 2 (granulocyte-macrophage) (Csf2), matrix metallopeptidase 13 (Mmp13), amphiregulin (Areg), plasminogen activator, urokinase receptor (Plaur), fos-like antigen 1 (Fosl1), epiregulin (Ereg), activating transcription factor 3 (Atf3), and transferrin receptor (Tfrc). Cxcl2, Csf2, and Atf3 played important roles in the mitogen-activated protein kinase (MAPK) signaling pathway. Conclusions These pathways and DEGs may serve as targets for gene therapy.","PeriodicalId":49117,"journal":{"name":"Toxicology Mechanisms and Methods","volume":"32 1","pages":"678 - 685"},"PeriodicalIF":2.8000,"publicationDate":"2022-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Identification of differentially expressed genes and pathways in diquat and paraquat poisoning using bioinformatics analysis\",\"authors\":\"C. Miao, Dandan Fan\",\"doi\":\"10.1080/15376516.2022.2063095\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract Objective In this study, differentially expressed genes (DEGs) and signaling pathways involved in diquat (DQ) and paraquat (PQ) poisoning were identified via bioinformatics analysis, in order to inform the development of novel clinical treatments. Methods Raw data from GSE153959 were downloaded from the Gene Expression Omnibus database. DEGs of the DQ vs. control (CON) and PQ vs. CON comparison groups were identified using R, and DEGs shared by the two groups were identified using TBtools. Subsequently, the shared DEGs were searched in the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases, using the Database for Annotation, Visualization, and Integrated Discovery. A protein–protein interaction (PPI) network was constructed, and hub genes were identified using the cytoHubba plug-in in Cytoscape software. Finally, circos and contrast plots showing the DEGs shared between mouse and human chromosomes were constructed using TBtools. Results Thirty-one DEGs shared by the DQ and PQ groups were identified. Enriched biological process terms included positive regulation of cell proliferation and translation. Enriched cellular component terms included extracellular region, intracellular membrane-bounded organelle and mitochondrion. Enriched molecular function terms included transcription factor activity and sequence-specific double-stranded DNA binding. Enriched KEGG pathways included the interleukin-17 signaling pathway, tumor necrosis factor signaling pathway, and human T-cell leukemia virus 1 infection. The top 10 hub genes in the PPI network were prostaglandin-endoperoxide synthase 2 (Ptgs2), chemokine (C-X-C motif) ligand 2 (Cxcl2), colony-stimulating factor 2 (granulocyte-macrophage) (Csf2), matrix metallopeptidase 13 (Mmp13), amphiregulin (Areg), plasminogen activator, urokinase receptor (Plaur), fos-like antigen 1 (Fosl1), epiregulin (Ereg), activating transcription factor 3 (Atf3), and transferrin receptor (Tfrc). Cxcl2, Csf2, and Atf3 played important roles in the mitogen-activated protein kinase (MAPK) signaling pathway. Conclusions These pathways and DEGs may serve as targets for gene therapy.\",\"PeriodicalId\":49117,\"journal\":{\"name\":\"Toxicology Mechanisms and Methods\",\"volume\":\"32 1\",\"pages\":\"678 - 685\"},\"PeriodicalIF\":2.8000,\"publicationDate\":\"2022-04-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Toxicology Mechanisms and Methods\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1080/15376516.2022.2063095\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"TOXICOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Toxicology Mechanisms and Methods","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/15376516.2022.2063095","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"TOXICOLOGY","Score":null,"Total":0}
引用次数: 4
摘要
【摘要】目的通过生物信息学分析,鉴定双甘菊(diquat, DQ)和百草枯(paraquat, PQ)中毒相关的差异表达基因(DEGs)和信号通路,为开发新的临床治疗方法提供依据。方法从Gene Expression Omnibus数据库下载GSE153959的原始数据。DQ组与对照组(CON)和PQ组与CON组的deg使用R进行鉴定,两组共有的deg使用TBtools进行鉴定。随后,使用Database for Annotation, Visualization, and Integrated Discovery在Gene Ontology和Kyoto Encyclopedia of Genes and Genomes (KEGG)数据库中检索共享的deg。构建蛋白-蛋白相互作用(PPI)网络,利用Cytoscape软件中的cytoHubba插件对枢纽基因进行鉴定。最后,使用TBtools构建显示小鼠和人类染色体之间共享的deg的环状图和对比图。结果DQ组和PQ组共鉴定出31个deg。丰富的生物过程术语包括细胞增殖和翻译的正调控。丰富的细胞成分包括胞外区、胞内膜结合细胞器和线粒体。富集的分子功能项包括转录因子活性和序列特异性双链DNA结合。富集的KEGG通路包括白细胞介素-17信号通路、肿瘤坏死因子信号通路和人t细胞白血病病毒1感染。PPI网络中排名前10位的枢纽基因分别是前列腺素内过氧化物合成酶2 (Ptgs2)、趋化因子(C-X-C基序)配体2 (Cxcl2)、集落刺激因子2(粒细胞-巨噬细胞)(Csf2)、基质金属肽酶13 (Mmp13)、双调节蛋白(Areg)、纤溶酶原激活剂、尿激酶受体(Plaur)、fos样抗原1 (Fosl1)、表调节蛋白(Ereg)、激活转录因子3 (Atf3)和转铁蛋白受体(Tfrc)。Cxcl2、Csf2和Atf3在丝裂原活化蛋白激酶(MAPK)信号通路中发挥重要作用。结论这些通路和deg可作为基因治疗的靶点。
Identification of differentially expressed genes and pathways in diquat and paraquat poisoning using bioinformatics analysis
Abstract Objective In this study, differentially expressed genes (DEGs) and signaling pathways involved in diquat (DQ) and paraquat (PQ) poisoning were identified via bioinformatics analysis, in order to inform the development of novel clinical treatments. Methods Raw data from GSE153959 were downloaded from the Gene Expression Omnibus database. DEGs of the DQ vs. control (CON) and PQ vs. CON comparison groups were identified using R, and DEGs shared by the two groups were identified using TBtools. Subsequently, the shared DEGs were searched in the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases, using the Database for Annotation, Visualization, and Integrated Discovery. A protein–protein interaction (PPI) network was constructed, and hub genes were identified using the cytoHubba plug-in in Cytoscape software. Finally, circos and contrast plots showing the DEGs shared between mouse and human chromosomes were constructed using TBtools. Results Thirty-one DEGs shared by the DQ and PQ groups were identified. Enriched biological process terms included positive regulation of cell proliferation and translation. Enriched cellular component terms included extracellular region, intracellular membrane-bounded organelle and mitochondrion. Enriched molecular function terms included transcription factor activity and sequence-specific double-stranded DNA binding. Enriched KEGG pathways included the interleukin-17 signaling pathway, tumor necrosis factor signaling pathway, and human T-cell leukemia virus 1 infection. The top 10 hub genes in the PPI network were prostaglandin-endoperoxide synthase 2 (Ptgs2), chemokine (C-X-C motif) ligand 2 (Cxcl2), colony-stimulating factor 2 (granulocyte-macrophage) (Csf2), matrix metallopeptidase 13 (Mmp13), amphiregulin (Areg), plasminogen activator, urokinase receptor (Plaur), fos-like antigen 1 (Fosl1), epiregulin (Ereg), activating transcription factor 3 (Atf3), and transferrin receptor (Tfrc). Cxcl2, Csf2, and Atf3 played important roles in the mitogen-activated protein kinase (MAPK) signaling pathway. Conclusions These pathways and DEGs may serve as targets for gene therapy.
期刊介绍:
Toxicology Mechanisms and Methods is a peer-reviewed journal whose aim is twofold. Firstly, the journal contains original research on subjects dealing with the mechanisms by which foreign chemicals cause toxic tissue injury. Chemical substances of interest include industrial compounds, environmental pollutants, hazardous wastes, drugs, pesticides, and chemical warfare agents. The scope of the journal spans from molecular and cellular mechanisms of action to the consideration of mechanistic evidence in establishing regulatory policy.
Secondly, the journal addresses aspects of the development, validation, and application of new and existing laboratory methods, techniques, and equipment. A variety of research methods are discussed, including:
In vivo studies with standard and alternative species
In vitro studies and alternative methodologies
Molecular, biochemical, and cellular techniques
Pharmacokinetics and pharmacodynamics
Mathematical modeling and computer programs
Forensic analyses
Risk assessment
Data collection and analysis.