Xiao-Yan Zeng, Min Zhang, Si-Jing Liao, Yong Wang, Ying-Bo Ren, Run Li, Tian-Mei Li, An-Qiong Mao, Guang-Zhen Li, Ying Zhang
{"title":"鉴定败血症中与丝裂噬相关的基因","authors":"Xiao-Yan Zeng, Min Zhang, Si-Jing Liao, Yong Wang, Ying-Bo Ren, Run Li, Tian-Mei Li, An-Qiong Mao, Guang-Zhen Li, Ying Zhang","doi":"10.2174/0115748936266722231116050255","DOIUrl":null,"url":null,"abstract":"Background: Numerous studies have shown that mitochondrial damage induces inflammation and activates inflammatory cells, leading to sepsis, while sepsis, a systemic inflammatory response syndrome, also exacerbates mitochondrial damage and hyperactivation. Mitochondrial autophagy eliminates aged, abnormal or damaged mitochondria to reduce intracellular mitochondrial stress and the release of mitochondria-associated molecules, thereby reducing the inflammatory response and cellular damage caused by sepsis. In addition, mitochondrial autophagy may also influence the onset and progression of sepsis, but the exact mechanisms are unclear. background: Sepsis is a critical systemic infection, a syndrome of severe inflammatory response of the organism to various pathogenic microorganisms. Methods: In this study, we mined the available publicly available microarray data in the GEO database (Home - GEO - NCBI (nih.gov)) with the aim of identifying key genes associated with mitochondrial autophagy in sepsis. objective: In this study, we used a bioinformatics approach to integrate multiple microarray data to screen for mitochondrial autophagy-related hub genes associated with sepsis onset and progression in a more scientific and systematic manner. Results: We identified four mitophagy-related genes in sepsis, TOMM20, TOMM22, TOMM40, and MFN1. method: Robust rank aggregation (RRA) Conclusion: This study provides preliminary evidence for the treatment of sepsis and may provide a solid foundation for subsequent biological studies. result: we constructed a PPI network combined with RRA analysis method to finally identify 4 key genes, namely TOMM20, TOMM22, TOMM40, and MFN1. conclusion: In this study, we used a bioinformatics analysis method, RRA, to integrate five gene microarray datasets to identify pivotal genes associated with mitochondrial autophagy in sepsis. Gene ontology (GO) functional annotation results show that these hub genes are mainly enriched in mitochondrial transport and establishment of protein localization to mitochondrion. Finally, we constructed the PPI network with the top 100 genes obtained from the rra method analysis. Based on the RRA results, the PPI results and the mitochondrial autophagy-related genes we found in the Reactome Pathway Database, we finally identified four key genes as TOMM20, TOMM22, TOMM40, and MFN1, respectively.","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2024-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Identification of Mitophagy-Related Genes in Sepsis\",\"authors\":\"Xiao-Yan Zeng, Min Zhang, Si-Jing Liao, Yong Wang, Ying-Bo Ren, Run Li, Tian-Mei Li, An-Qiong Mao, Guang-Zhen Li, Ying Zhang\",\"doi\":\"10.2174/0115748936266722231116050255\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Background: Numerous studies have shown that mitochondrial damage induces inflammation and activates inflammatory cells, leading to sepsis, while sepsis, a systemic inflammatory response syndrome, also exacerbates mitochondrial damage and hyperactivation. Mitochondrial autophagy eliminates aged, abnormal or damaged mitochondria to reduce intracellular mitochondrial stress and the release of mitochondria-associated molecules, thereby reducing the inflammatory response and cellular damage caused by sepsis. In addition, mitochondrial autophagy may also influence the onset and progression of sepsis, but the exact mechanisms are unclear. background: Sepsis is a critical systemic infection, a syndrome of severe inflammatory response of the organism to various pathogenic microorganisms. Methods: In this study, we mined the available publicly available microarray data in the GEO database (Home - GEO - NCBI (nih.gov)) with the aim of identifying key genes associated with mitochondrial autophagy in sepsis. objective: In this study, we used a bioinformatics approach to integrate multiple microarray data to screen for mitochondrial autophagy-related hub genes associated with sepsis onset and progression in a more scientific and systematic manner. Results: We identified four mitophagy-related genes in sepsis, TOMM20, TOMM22, TOMM40, and MFN1. method: Robust rank aggregation (RRA) Conclusion: This study provides preliminary evidence for the treatment of sepsis and may provide a solid foundation for subsequent biological studies. result: we constructed a PPI network combined with RRA analysis method to finally identify 4 key genes, namely TOMM20, TOMM22, TOMM40, and MFN1. conclusion: In this study, we used a bioinformatics analysis method, RRA, to integrate five gene microarray datasets to identify pivotal genes associated with mitochondrial autophagy in sepsis. Gene ontology (GO) functional annotation results show that these hub genes are mainly enriched in mitochondrial transport and establishment of protein localization to mitochondrion. Finally, we constructed the PPI network with the top 100 genes obtained from the rra method analysis. Based on the RRA results, the PPI results and the mitochondrial autophagy-related genes we found in the Reactome Pathway Database, we finally identified four key genes as TOMM20, TOMM22, TOMM40, and MFN1, respectively.\",\"PeriodicalId\":2,\"journal\":{\"name\":\"ACS Applied Bio Materials\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2024-01-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Bio Materials\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.2174/0115748936266722231116050255\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATERIALS SCIENCE, BIOMATERIALS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.2174/0115748936266722231116050255","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
Identification of Mitophagy-Related Genes in Sepsis
Background: Numerous studies have shown that mitochondrial damage induces inflammation and activates inflammatory cells, leading to sepsis, while sepsis, a systemic inflammatory response syndrome, also exacerbates mitochondrial damage and hyperactivation. Mitochondrial autophagy eliminates aged, abnormal or damaged mitochondria to reduce intracellular mitochondrial stress and the release of mitochondria-associated molecules, thereby reducing the inflammatory response and cellular damage caused by sepsis. In addition, mitochondrial autophagy may also influence the onset and progression of sepsis, but the exact mechanisms are unclear. background: Sepsis is a critical systemic infection, a syndrome of severe inflammatory response of the organism to various pathogenic microorganisms. Methods: In this study, we mined the available publicly available microarray data in the GEO database (Home - GEO - NCBI (nih.gov)) with the aim of identifying key genes associated with mitochondrial autophagy in sepsis. objective: In this study, we used a bioinformatics approach to integrate multiple microarray data to screen for mitochondrial autophagy-related hub genes associated with sepsis onset and progression in a more scientific and systematic manner. Results: We identified four mitophagy-related genes in sepsis, TOMM20, TOMM22, TOMM40, and MFN1. method: Robust rank aggregation (RRA) Conclusion: This study provides preliminary evidence for the treatment of sepsis and may provide a solid foundation for subsequent biological studies. result: we constructed a PPI network combined with RRA analysis method to finally identify 4 key genes, namely TOMM20, TOMM22, TOMM40, and MFN1. conclusion: In this study, we used a bioinformatics analysis method, RRA, to integrate five gene microarray datasets to identify pivotal genes associated with mitochondrial autophagy in sepsis. Gene ontology (GO) functional annotation results show that these hub genes are mainly enriched in mitochondrial transport and establishment of protein localization to mitochondrion. Finally, we constructed the PPI network with the top 100 genes obtained from the rra method analysis. Based on the RRA results, the PPI results and the mitochondrial autophagy-related genes we found in the Reactome Pathway Database, we finally identified four key genes as TOMM20, TOMM22, TOMM40, and MFN1, respectively.