Construction Of The Regulatory Network For Influenza A(H1N1) And Analysis Of Its Mechanism Of Systems Biology

Influenza viruses cause annual epidemics and recurring pandemics, especially H1N1,which have become a health burden throughout the world.Like all viruses, influenza viruses rely on the host cellular machinery to support their lifecycle. So, it is urgent to comprehensively understand the global host response to influenzavirus infection. The integration of bioinformatics with various evidences from biologicalexperiments provides a new way to gain more insights into the molecular mechanism ofinfluenza.H1N1triggers extensive host differential expression of both miRNAs and mRNAs. Inour study, by analyzing the miRNA and mRNA microarray expression profiles of peripheralblood samples of critically ill H1N1influenza patients, we identified56differentiallyexpressed miRNAs and1359differentially expressed mRNAs. Computational analysesrevealed anti-correlated miRNA-mRNA pairs for several target prediction algorithms used.GO and pathway analysis were performed to annotate and integrate the functions ofdifferentially expressed mRNAs and miRNAs. Up-regulated genes mainly involved in cellcycle, mitosis, metabolic process, inflammatory response, innate immune response;meanwhile, T cell receptor signaling pathway, antigen receptor-mediated signaling pathway,signal transduction, response to stimulus, antigen processing and presentation were observedin down-regulated genes. Then we constructed an interaction network of differentiallyexpressed genes. By topological analysis, the degree distribution of the network revealed apower law distribution, which showed that the network was scale-free. What’s more, weidentified38‘hub’ genes and12functional clusters. Moreover, we constructed a functionalcooperative miRNA-miRNA network via co-regulating functional modules, in which wefound that some clustered miRNAs and miRNAs in the same family tend to have similarexpression pattern and participate in similar biological functions. Finally, by integrating allresults including clusters, miRNAs, transcription factors,‘hub’ genes and virus genes, weobtained a combined network of core information which was found to be related to infectionof H1N1influenza virus.Integrating various sources of data and exploring interactions and functional networkscan pave a new way to gain more insights into the molecular mechanism of diseases at systematic level, and perhaps, to the development of miRNA-based diagnosis andtherapeutics.