Abstract
Influenza A virus belonged to RNA viruses that genetic materials were high variability. One of the subtypes, H1N1 has caused several world-wide and seasonal influenza pandemics. After influenza virus infected human, the infection caused acute respiratory and lung diseases. The infection often led to other complications, and even severe death cases. Influenza A viruses are still threats of human health. However, the mechanism of influenza A virus infects human is still unclear. In this thesis, the interactions between influenza virus and human host were research topics. In order to understand the relationships between the different influenza virus and host cell materials (such as proteins, and miRNAs), the research selected the three strains influenza virus with pathogenic differences. The three 1918, 2007 and 2009 seasonal influenza virus strains were respectively research materials. This thesis provided two dimensions to study the influenza A (H1N1) virus. In the first dimension, the functional domains of the influenza virus were used to predict human affected proteins. In the process, domain interactions for ten influenza virus proteins were constructed out with the combination of existing biological databases (Pfam, DOMINE, KEGG etc.). This result was found the three influenza viruses affected the overlapping human proteins. The domain-domain path constructions were from three influenza virus to affected human proteins, and explained the affected process of the virus on the human proteins. Some human proteins were speculated that affected by influenza, and the predictions were referable with some literatures. Although the three strains influenza virus had genetic variability with each other, the impacts of the human proteins revealed that they were similar. These results indicated that the three strains influenza virus went through the influence of human-specific protein populations, and caused pathogenic phenomena. With the advances of computing technology, bioinformatics tools gradually applied to the predicted experiment auxiliaries. The human small molecules, miRNAs, regulated many effect roles in vivo. In addition, some literatures showed that miRNAs had impacts on influenza virus. In the second dimension, the bioinformatics software (miRanda) was in use to predict human miRNAs targeted affairs on three different toxicity influenza viruses, and built the researching process about influenza virus and human miRNAs interactions. In this process, the human miRNAs expression levels within the related organizations were consulted, particularly in major incidence of infected organizations. This study found that the infected tissues had common and high expression miRNA molecules which also had some targeted results with influenza viral genomes. However, the binding sites differed with the other strains. The predicted miR-143, miR-145, and miR-150 etc. were mentioned that had regulations of the immune cells in recorded literatures. The results in this part showed the selected miRNAs were expected to be in certain relationships with influenza virus. Through two aspects of domain-domain interactions and the miRNA-genome relations between human and influenza virus, these interactions inferred the mechanisms are manifold and associated with both. Some forecasts were associated with virus epidemiology, and provided more in-depth knowledge. The current predictions provided further experimental verification of biological related research team.