Network analysis of inflammatory responses to sepsis by neutrophils and peripheral blood mononuclear cells
Network analysis of inflammatory responses to sepsis by neutrophils and peripheral blood mononuclear cells
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DOI：
10.1371/journal.pone.0201674
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发表时间：
2018-08-07
期刊：
影响因子：
3.7
通讯作者：
Ebrahimie, Esmaeil
中科院分区：
文献类型：
--
作者：
Godini, Rasoul;Fallahi, Hossein;Ebrahimie, Esmaeil
败血症是一种危及生命的综合征，每年在全球范围内导致数千人死亡。脓毒症是感染的结果，可能导致全身炎症反应和器官衰竭。此外，作为免疫系统的主要细胞的血细胞也可能受到脓毒症的影响。在这里，我们使用了不同的网络分析方法，包括加权基因共表达网络分析(WGCNA)、蛋白质-蛋白质相互作用(PPI)和基因调控网络，来剖析主要白细胞对脓毒症的系统水平反应。利用生物信息学的方法，获得了败血症血浆中中性粒细胞(NTS)、树突状细胞(DC)和外周血单核细胞(PBMC)的基因表达谱，并进行了分析。制备了单个基因表达矩阵和差异表达基因(Deg)列表，并用它们构建了几个网络。因此，通过网络分析检测关键调控模块和中枢基因，并通过从David数据库中提取的本体分析对其进行标注。我们的结果表明，脓毒症血浆对NTS、PBMCs的调节网络的影响大于DC的调节网络。DEGS的基因本体论揭示，信号转导和免疫细胞反应是脓毒症最重要的生物学过程。另一方面，网络分析在每种细胞类型中检测到模块和中枢基因。研究发现，参与免疫细胞、信号转导和凋亡过程的通路是脓毒症反应中受影响最大的通路之一。综上所述，我们已经发现了几个可能与脓毒症感染特异反应的HUB基因，包括ADORA3、CD83 CDKN1A、FFAR2、GNAQ、IL1B、LTB、MAPK14、SAMD9L、SOCS1和STAT1。总之，我们的结果揭示了主要白细胞对脓毒症的系统水平反应，并确定了几个具有潜在治疗和诊断应用的HUB基因。
Sepsis is a life-threatening syndrome causing thousands of deaths yearly worldwide. Sepsis is a result of infection and could lead to systemic inflammatory responses and organ failures. Additionally, blood cells, as the main cells in the immune systems, could be also affected by sepsis. Here, we have used different network analysis approaches, including Weighted Gene Co-expression Network Analysis (WGCNA), Protein-Protein Interaction (PPI), and gene regulatory network, to dissect system-level response to sepsis by the main white blood cells. Gene expression profiles of Neutrophils (NTs), Dendritic Cells (DCs), and Peripheral Blood Mononuclear Cells (PBMCs) that were exposed to septic plasma were obtained and analyzed using bioinformatics approaches. Individual gene expression matrices and the list of differentially expressed genes (DEGs) were prepared and used to construct several networks. Consequently, key regulatory modules and hub genes were detected through network analysis and annotated through ontology analysis extracted from DAVID database. Our results showed that septic plasma affected the regulatory networks in NTs, PBMCs more than the network in DCs. Gene ontology of DEGs revealed that signal transduction and immune cells responses are the most important biological processes affected by sepsis. On the other hand, network analysis detected modules and hub genes in each cell types. It was found that pathways involved in immune cells, signal transduction, and apoptotic processes are among the most affected pathways in the responses to sepsis. Altogether, we have found several hub genes including ADORA3, CD83 CDKN1A, FFAR2, GNAQ, IL1B, LTB, MAPK14, SAMD9L, SOCS1, and STAT1, which might specifically respond to sepsis infection. In conclusion, our results uncovered the system-level responses of the main white blood cells to sepsis and identified several hub genes with potential applications for therapeutic and diagnostic purposes.