Dataset Information

Diversity in Compartmental Dynamics of Gene Regulatory Networks: The Immune Response in Primary Influenza A Infection in Mice.

ABSTRACT: Current approaches to study transcriptional profiles post influenza infection typically rely on tissue sampling from one or two sites at a few time points, such as spleen and lung in murine models. In this study, we infected female C57/BL6 mice intranasally with mouse-adapted H3N2/Hong Kong/X31 avian influenza A virus, and then analyzed the gene expression profiles in four different compartments (blood, lung, mediastinal lymph nodes, and spleen) over 11 consecutive days post infection. These data were analyzed by an advanced statistical procedure based on ordinary differential equation (ODE) modeling. Vastly different lists of significant genes were identified by the same statistical procedure in each compartment. Only 11 of them are significant in all four compartments. We classified significant genes in each compartment into co-expressed modules based on temporal expression patterns. We then performed functional enrichment analysis on these co-expression modules and identified significant pathway and functional motifs. Finally, we used an ODE based model to reconstruct gene regulatory network (GRN) for each compartment and studied their network properties.

SUBMITTER: Qiu X

PROVIDER: S-EPMC4586376 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Diversity in Compartmental Dynamics of Gene Regulatory Networks: The Immune Response in Primary Influenza A Infection in Mice.

Qiu Xing X Wu Shuang S Hilchey Shannon P SP Thakar Juilee J Liu Zhi-Ping ZP Welle Stephen L SL Henn Alicia D AD Wu Hulin H Zand Martin S MS

PloS one 20150928 9

Current approaches to study transcriptional profiles post influenza infection typically rely on tissue sampling from one or two sites at a few time points, such as spleen and lung in murine models. In this study, we infected female C57/BL6 mice intranasally with mouse-adapted H3N2/Hong Kong/X31 avian influenza A virus, and then analyzed the gene expression profiles in four different compartments (blood, lung, mediastinal lymph nodes, and spleen) over 11 consecutive days post infection. These dat ...[more]

PMID: 26413862

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Project description:H1N1 influenza virus is a major factor in seasonal influenza outbreaks. After the body is infected with the influenza virus, the expression of certain mRNAs, including miRNAs, could be affected. However, the association between these mRNAs and miRNAs remains unclear. This study is aimed at identifying differentially expressed genes (DEGs) and miRNAs (DEmiRs) caused by H1N1 influenza virus infection and constructing a miRNA-mRNA regulatory network. Nine GSE datasets were downloaded from the Gene Expression Omnibus database, of which seven were mRNA data and two were miRNA data. The limma package in R language package was used to analyze array data, and edgeR package was used to analyze high-throughput sequencing data. At the same time, the genes related to H1N1 infection were further screened by WGCNA analysis. DEGs were subjected to Gene Ontology and KEGG pathway enrichment analyses by DAVID database, while the STRING database predicted the protein-protein interaction (PPI) network. The correspondence between miRNA and target mRNA was analyzed by the miRWalk database. Cytoscape software was used to output PPI results, identify hub genes, and construct a miRNA-mRNA regulatory network. 114 DEGs and 37 candidate DEmiRs were identified for subsequent analysis. These DEGs were significantly enriched in response to the virus, cytokine activity, and symbiont-containing vacuole membrane. According to KEGG analysis, DEGs were enriched in PD-L1 expression and PD-1 checkpoint pathway. The key point Cd274 (PD-L1) was highly expressed in the H1N1-infected group. Finally, a potential miRNA-mRNA regulatory network (containing 8 candidate DEmiRs and 69 candidate DEGs) and a PPI network were constructed. After that, three hub genes were identified: Ifit3, Stat2, and Irf7. These hub genes and Cd274 were validated by another independent high-throughput dataset and were highly expressed pattern. This study will help researchers gain insights into the intrinsic effects of H1N1 influenza virus infection on the host and suggest a novel association of H1N1 virus with the host immune system.

Dataset Information

Diversity in Compartmental Dynamics of Gene Regulatory Networks: The Immune Response in Primary Influenza A Infection in Mice.

Publications

Diversity in Compartmental Dynamics of Gene Regulatory Networks: The Immune Response in Primary Influenza A Infection in Mice.

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