01 February 2019 : Laboratory Research
Comprehensive Bioinformatics Analysis of the Immune Mechanism of Dendritic Cells Against Measles Virus
Lili Jia1ABCDEFG, Rongqiang Zhang2CDEF*DOI: 10.12659/MSM.912949
Med Sci Monit 2019; 25:903-912
Abstract
BACKGROUND: The purpose of this study was to explore the immune mechanism of dendritic cells (DCs) against measles virus (MV), and to identify potential biomarkers to improve measles prevention and treatment.
MATERIAL AND METHODS: The gene expression profile of GSE980, which comprised 10 DC samples from human blood infected with MV (RNA was isolated at 3, 6, 12, and 24 h post-infection) and 4 normal DC control samples, was obtained from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between the MV-infected DC samples and the control samples were screened using Genevestigator software. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analyses were performed using GenCLip 2.0 and STRING 10.5 software. The protein–protein interaction (PPI) network was established using Cytoscape 3.4.0.
RESULTS: The gene expression profiles of MV-infected DCs were obviously changed. Twenty-six common DEGs (0.9%, MV-infected DCs vs. normal DCs) were identified at 4 different time points, including 14 down-regulated and 12 up-regulated genes (P=0.001). GO analysis showed that DEGs were significantly enriched in defense response to virus, type I interferon signaling pathway, et al. ISG15 and CXCL10 were the key genes in the PPI network of the DEGs, and may interact directly with the type I interferon signaling and defense response to virus signaling.
CONCLUSIONS: The DEGs increased gradually with the duration of MV infection. The type I interferon signaling pathway and the defense response to viral processes can be activated against MV by ISG15 and CXCL10 in DCs. These may provide novel targets for the treatment of MV.
Keywords: Gene Expression Profiling, Measles virus, Neuroimmunomodulation, Computational Biology, gene ontology, Gene Regulatory Networks, Protein Interaction Mapping, Protein Interaction Maps, Software
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