Erasmia Rouka1, Chrissi Hatzoglou2, Konstantinos I Gourgoulianis3, Sotirios G Zarogiannis4. 1. Department of Transfusion Medicine, Faculty of Medicine, University of Thessaly, BIOPOLIS, 41334, Larissa, Greece; Department of Physiology, Faculty of Medicine, University of Thessaly, BIOPOLIS, 41500, Larissa, Greece. Electronic address: errouka@med.uth.gr. 2. Department of Physiology, Faculty of Medicine, University of Thessaly, BIOPOLIS, 41500, Larissa, Greece; Department of Respiratory Medicine, Faculty of Medicine, University of Thessaly, BIOPOLIS, 41334, Larissa, Greece. Electronic address: chatz@med.uth.gr. 3. Department of Respiratory Medicine, Faculty of Medicine, University of Thessaly, BIOPOLIS, 41334, Larissa, Greece. Electronic address: kgourg@med.uth.gr. 4. Department of Physiology, Faculty of Medicine, University of Thessaly, BIOPOLIS, 41500, Larissa, Greece; Department of Respiratory Medicine, Faculty of Medicine, University of Thessaly, BIOPOLIS, 41334, Larissa, Greece. Electronic address: szarog@med.uth.gr.
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.
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.