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感染H1N1流感病毒的小鼠肺部中的微小RNA表达谱及网络

MicroRNA expression profiles and networks in mouse lung infected with H1N1 influenza virus.

作者信息

Bao Yanyan, Gao Yingjie, Jin Yahong, Cong Weihong, Pan Xin, Cui Xiaolan

机构信息

Biosafety Laboratory, Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, 100700, China.

Laboratory of Cardiovascular Diseases, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, 100091, China.

出版信息

Mol Genet Genomics. 2015 Oct;290(5):1885-97. doi: 10.1007/s00438-015-1047-1. Epub 2015 Apr 18.

Abstract

Influenza A viruses can cause localized outbreaks and worldwide pandemics, owing to their high transmissibility and wide host range. As such, they are among the major diseases that cause human death. However, the molecular changes induced by influenza A virus infection in lung tissue are not entirely clear. Changes in microRNA (miRNA) expression occur in many pathological and physiological processes, and influenza A virus infection has been shown to alter miRNA expression in cultured cells and animal models. In this study, we mined key miRNAs closely related to influenza A virus infection and explored cellular regulatory mechanisms against influenza A virus infection, by building networks among miRNAs and genes, gene ontologies (GOs), and pathways. In this study, miRNAs and mRNAs induced by H1N1 influenza virus infection were measured by gene chips, and we found that 82 miRNAs and 3371 mRNAs were differentially expressed. The 82 miRNAs were further analyzed with the series test of cluster (STC) analysis. Three of the 16 cluster profiles identified by STC, which include 46 miRNAs in the three profiles, changed significantly. Using potential target genes of the 46 miRNAs, we looked for intersections of these genes with 3371 differentially expressed mRNAs; 719 intersection genes were identified. Based on the GO or KEGG databases, we attained GOs or pathways for all of the above intersection genes. Fisher's and χ (2) test were used to calculate p value and false discovery rate (FDR), and according to the standard of p < 0.001, 241 GOs and 76 pathways were filtered. Based on these data, miRNA-gene, miRNA-GO, and miRNA-pathway networks were built. We then extracted three classes of GOs (related to inflammatory and immune response, cell cycle, proliferation and apoptosis, and signal transduction) to build three subgraphs, and pathways strictly related with H1N1 influenza virus infection were filtered to extract a subgraph of the miRNA-pathway network. Last, according to the pathway analysis and miRNA-pathway network analysis, 17 miRNAs were found to be associated with the "influenza A" pathway. This study provides the most complete miRNAome profiles, and the most detailed miRNA regulatory networks to date, and is the first to report the most important 17 miRNAs closely related with the pathway of influenza A. These results are a prelude to advancements in mouse H1N1 influenza virus infection biology and the use of mice as a model for human H1N1 influenza virus infection studies.

摘要

甲型流感病毒因其高传播性和广泛的宿主范围,可引发局部疫情和全球大流行。因此,它们是导致人类死亡的主要疾病之一。然而,甲型流感病毒感染在肺组织中引发的分子变化尚不完全清楚。微小RNA(miRNA)表达的变化发生在许多病理和生理过程中,并且已证明甲型流感病毒感染会改变培养细胞和动物模型中的miRNA表达。在本研究中,我们通过构建miRNA与基因、基因本体(GO)和通路之间的网络,挖掘与甲型流感病毒感染密切相关的关键miRNA,并探索针对甲型流感病毒感染的细胞调控机制。在本研究中,通过基因芯片检测H1N1流感病毒感染诱导的miRNA和mRNA,我们发现82个miRNA和3371个mRNA存在差异表达。对这82个miRNA进一步进行成组序列检验(STC)分析。STC鉴定出的16个聚类图谱中有3个图谱发生了显著变化,这3个图谱包含46个miRNA。利用这46个miRNA的潜在靶基因,我们寻找这些基因与3371个差异表达mRNA的交集;共鉴定出719个交集基因。基于GO或KEGG数据库,我们获得了上述所有交集基因的GO或通路。使用Fisher检验和χ²检验计算P值和错误发现率(FDR),根据P < 0.001的标准,筛选出241个GO和76条通路。基于这些数据,构建了miRNA - 基因、miRNA - GO和miRNA - 通路网络。然后,我们提取了三类GO(与炎症和免疫反应、细胞周期、增殖和凋亡以及信号转导相关)来构建三个子图,并筛选出与H1N1流感病毒感染严格相关的通路,以提取miRNA - 通路网络的一个子图。最后,根据通路分析和miRNA - 通路网络分析,发现17个miRNA与“甲型流感”通路相关。本研究提供了迄今为止最完整的miRNA组图谱和最详细的miRNA调控网络,并且首次报道了与甲型流感通路密切相关的最重要的17个miRNA。这些结果是小鼠H1N1流感病毒感染生物学进展以及将小鼠用作人类H1N1流感病毒感染研究模型的前奏。

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