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Modeling Dysplastic and Functional Lung Alveolar Repair after Influenza Infection
Published on: September 19, 2025
MicroRNA expression profiles and networks in mouse lung infected with H1N1 influenza virus
Yanyan Bao1, Yingjie Gao1, Yahong Jin1
1Biosafety Laboratory, Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, 100700, China.
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.
Insights
This study identifies 17 key microRNAs (miRNAs) involved in H1N1 influenza A virus infection, revealing crucial regulatory networks in lung tissue. These findings advance understanding of influenza pathogenesis and potential therapeutic targets.
Area of Science:
- Virology
- Molecular Biology
- Genomics
Background:
- Influenza A viruses are significant global health threats, causing widespread illness and death.
- The molecular mechanisms of influenza A virus infection in lung tissue, particularly involving microRNAs (miRNAs), are not fully understood.
- miRNAs play critical roles in various biological processes and are known to be altered during influenza infection.
Purpose of the Study:
- To identify key microRNAs (miRNAs) associated with H1N1 influenza A virus infection.
- To explore the cellular regulatory mechanisms underlying influenza A virus infection by constructing miRNA-gene, miRNA-GO, and miRNA-pathway networks.
- To pinpoint specific miRNAs crucial for the influenza A pathway.
Main Methods:
- Gene chip technology was used to measure miRNA and mRNA expression in H1N1-infected lung tissue.
- Bioinformatic analyses, including Series Test of Cluster (STC), gene ontology (GO), and KEGG pathway analysis, were employed.
- Network construction and subgraph extraction were performed to visualize miRNA-gene, miRNA-GO, and miRNA-pathway interactions.
Main Results:
- Differential expression analysis revealed 82 miRNAs and 3371 mRNAs affected by H1N1 infection.
- Network analysis identified 719 intersection genes, 241 GOs, and 76 pathways significantly associated with differentially expressed miRNAs.
- Seventeen specific miRNAs were identified as being closely related to the influenza A pathway.
Conclusions:
- This study presents comprehensive miRNAome profiles and detailed regulatory networks for H1N1 influenza A virus infection.
- The identification of 17 key miRNAs provides significant insights into the molecular pathogenesis of influenza A.
- These findings lay the groundwork for further research into influenza A virus biology and potential therapeutic strategies, utilizing mouse models.
