dc.creator | Rouka E., Hatzoglou C., Gourgoulianis K.I., Zarogiannis S.G. | en |
dc.date.accessioned | 2023-01-31T09:51:53Z | |
dc.date.available | 2023-01-31T09:51:53Z | |
dc.date.issued | 2020 | |
dc.identifier | 10.1016/j.micpath.2020.104000 | |
dc.identifier.issn | 08824010 | |
dc.identifier.uri | http://hdl.handle.net/11615/78564 | |
dc.description.abstract | Background and objectives: Human respiratory syncytial virus (HRSV) and human metapneumovirus (HMPV) are leading causes of upper and lower respiratory tract infections in non-immunocompetent subjects, yet the mechanisms by which they induce their pathogenicity differ significantly and remain elusive. In this study we aimed at identifying the gene interaction networks between the HRSV, HMPV respiratory pathogens and their host along with the different cell-signaling pathways associated with the above interactomes. Materials and methods: The Viruses STRING database (http://viruses.string-db.org/) was used for the identification of the host-viruses interaction networks. The two lists of the predicted functional partners were entered in the FunRich tool (http://www.funrich.org) for the construction of the Venn diagram and the comparative Funcional Enrichment Analysis (FEA) with respect to biological pathways. The sets of the common and unique human genes identified in the two networks were also analyzed. The computational predictions regarding the shared human genes in the host-HRSV and the host-HMPV interactomes were further evaluated via the analysis of the GSE111732 dataset. miRNA transcriptomics data were mapped to gene targets using the miRNomics pipeline of the GeneTrail2 database (https://genetrail2.bioinf.uni-sb.de/). Results: Eleven out of twenty predicted human genes were common in the two interactomes (TLR4, SOCS3, SFXN1, AKT1, SFXN3, LY96, SFXN2, SOCS7, CISH, SOCS6, SOCS1). FEA of these common genes identified the kit receptor and the GH receptor signaling pathways as the most significantly enriched annotations. The remaining nine genes of the host-HRSV and the host-HMPV interaction networks were the IFIH1, DDX58, NCL, IRF3, STAT2, HSPA4, CD209, KLF6, CHKA and the MYD88, SOCS4, SOCS2, SOCS5 AKT2, AKT3, SFXN4, SFXN5 and TLR3 respectively. Distinct cell-signaling pathways were enriched per interactome. The comparative FEA highlighted the association of the host-HRSV functional partners with the negative regulation of RIG-I/MDA5 signaling. The analysis with respect to miRNAs mapping to gene targets of the GSE111732 dataset indicated that nine out of the eleven common host genes are either enriched or depleted in the sample sets (HRSV or HMPV infected) as compared with the reference set (non-infected), although with no significant scores. Conclusions: We have identified both shared and unique host genes as members of the HRSV and HMPV interaction networks. The disparate human genes likely contribute to distinct responses in airway epithelial cells. © 2020 Elsevier Ltd | en |
dc.language.iso | en | en |
dc.source | Microbial Pathogenesis | en |
dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079364867&doi=10.1016%2fj.micpath.2020.104000&partnerID=40&md5=bc01044da0f386085b472d98a5ebd861 | |
dc.subject | carrier protein | en |
dc.subject | CD209 antigen | en |
dc.subject | choline kinase | en |
dc.subject | growth hormone receptor | en |
dc.subject | heat shock protein | en |
dc.subject | interferon regulatory factor 3 | en |
dc.subject | kruppel like factor 6 | en |
dc.subject | microRNA | en |
dc.subject | nucleolin | en |
dc.subject | retinoic acid inducible protein I | en |
dc.subject | sideroflexin 2 | en |
dc.subject | sideroflexin 3 | en |
dc.subject | STAT2 protein | en |
dc.subject | stem cell factor receptor | en |
dc.subject | suppressor of cytokine signaling | en |
dc.subject | suppressor of cytokine signaling 1 | en |
dc.subject | suppressor of cytokine signaling 3 | en |
dc.subject | suppressor of cytokine signaling 6 | en |
dc.subject | suppressor of cytokine signaling 7 | en |
dc.subject | toll like receptor 4 | en |
dc.subject | unclassified drug | en |
dc.subject | airway epithelium cell | en |
dc.subject | AKT1 gene | en |
dc.subject | AKT2 gene | en |
dc.subject | AKT3 gene | en |
dc.subject | Article | en |
dc.subject | CD209 gene | en |
dc.subject | CHKA gene | en |
dc.subject | CISH gene | en |
dc.subject | computer model | en |
dc.subject | DDX58 gemne | en |
dc.subject | gene | en |
dc.subject | gene identification | en |
dc.subject | gene interaction | en |
dc.subject | gene mapping | en |
dc.subject | gene targeting | en |
dc.subject | genetic analysis | en |
dc.subject | genetic database | en |
dc.subject | HSPA4 gene | en |
dc.subject | human | en |
dc.subject | Human metapneumovirus | en |
dc.subject | Human respiratory syncytial virus | en |
dc.subject | IFIH1 gene | en |
dc.subject | IRF3 gene | en |
dc.subject | KLF6 gene | en |
dc.subject | LY96 gene | en |
dc.subject | MYD88 gene | en |
dc.subject | NCL gene | en |
dc.subject | nonhuman | en |
dc.subject | prediction | en |
dc.subject | priority journal | en |
dc.subject | SFXN1 gene | en |
dc.subject | SFXN2 gene | en |
dc.subject | SFXN3 gene | en |
dc.subject | SFXN4 gene | en |
dc.subject | SFXN5 gene | en |
dc.subject | signal transduction | en |
dc.subject | SOCS1 gene | en |
dc.subject | SOCS3 gene | en |
dc.subject | SOCS4 gene | en |
dc.subject | SOCS5 gene | en |
dc.subject | SOCS6 gene | en |
dc.subject | SOCS7 gene | en |
dc.subject | STAT2 gene | en |
dc.subject | TLR3 gene | en |
dc.subject | TLR4 gene | en |
dc.subject | transcriptomics | en |
dc.subject | virus cell interaction | en |
dc.subject | computer simulation | en |
dc.subject | cytology | en |
dc.subject | epithelium cell | en |
dc.subject | gene regulatory network | en |
dc.subject | genetics | en |
dc.subject | Human respiratory syncytial virus | en |
dc.subject | Metapneumovirus | en |
dc.subject | organismal interaction | en |
dc.subject | respiratory syncytial virus infection | en |
dc.subject | respiratory system | en |
dc.subject | respiratory tract infection | en |
dc.subject | virology | en |
dc.subject | Computer Simulation | en |
dc.subject | Epithelial Cells | en |
dc.subject | Gene Regulatory Networks | en |
dc.subject | Host Microbial Interactions | en |
dc.subject | Humans | en |
dc.subject | Metapneumovirus | en |
dc.subject | Microbial Interactions | en |
dc.subject | Respiratory Syncytial Virus Infections | en |
dc.subject | Respiratory Syncytial Virus, Human | en |
dc.subject | Respiratory System | en |
dc.subject | Respiratory Tract Infections | en |
dc.subject | Signal Transduction | en |
dc.subject | Academic Press | en |
dc.title | Interactome networks between the human respiratory syncytial virus (HRSV), the human metapneumovirus (ΗMPV), and their host: In silico investigation and comparative functional enrichment analysis | en |
dc.type | journalArticle | en |