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.
Keywords: Bioinformatics; H1N1; Influenza A virus; MicroRNA; STC analysis.