Ke-Ying Fang1,2, Wen-Chao Cao1,2, Tian-Ao Xie1,2, Jie Lv1,2, Jia-Xin Chen1,2, Xun-Jie Cao1,2, Zhong-Wei Li1,2, Shu-Ting Deng1,2, Xu-Guang Guo3,4,5,6. 1. Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510150, China. 2. Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, Guangzhou, 511436, China. 3. Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510150, China. gysygxg@gmail.com. 4. Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, Guangzhou, 511436, China. gysygxg@gmail.com. 5. Key Laboratory for Major Obstetric Diseases of Guangdong Province, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510150, China. gysygxg@gmail.com. 6. Key Laboratory of Reproduction and Genetics of Guangdong Higher Education Institutes, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510150, China. gysygxg@gmail.com.
Abstract
BACKGROUND: In the novel coronavirus pandemic, the high infection rate and high mortality have seriously affected people's health and social order. To better explore the infection mechanism and treatment, the three-dimensional structure of human bronchus has been employed in a better in-depth study on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). METHODS: We downloaded a separate microarray from the Integrated Gene Expression System (GEO) on a human bronchial organoids sample to identify differentially expressed genes (DEGS) and analyzed it with R software. After processing with R software, Gene Ontology (GO) and Kyoto PBMCs of Genes and Genomes (KEGG) were analyzed, while a protein-protein interaction (PPI) network was constructed to show the interactions and influence relationships between these differential genes. Finally, the selected highly connected genes, which are called hub genes, were verified in CytoHubba plug-in. RESULTS: In this study, a total of 966 differentially expressed genes, including 490 upregulated genes and 476 downregulated genes were used. Analysis of GO and KEGG revealed that these differentially expressed genes were significantly enriched in pathways related to immune response and cytokines. We construct protein-protein interaction network and identify 10 hub genes, including IL6, MMP9, IL1B, CXCL8, ICAM1, FGF2, EGF, CXCL10, CCL2, CCL5, CXCL1, and FN1. Finally, with the help of GSE150728, we verified that CXCl1, CXCL8, CXCL10, CCL5, EGF differently expressed before and after SARS-CoV-2 infection in clinical patients. CONCLUSIONS: In this study, we used mRNA expression data from GSE150819 to preliminarily confirm the feasibility of hBO as an in vitro model to further study the pathogenesis and potential treatment of COVID-19. Moreover, based on the mRNA differentiated expression of this model, we found that CXCL8, CXCL10, and EGF are hub genes in the process of SARS-COV-2 infection, and we emphasized their key roles in SARS-CoV-2 infection. And we also suggested that further study of these hub genes may be beneficial to treatment, prognostic prediction of COVID-19.
BACKGROUND: In the novel coronavirus pandemic, the high infection rate and high mortality have seriously affected people's health and social order. To better explore the infection mechanism and treatment, the three-dimensional structure of human bronchus has been employed in a better in-depth study on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). METHODS: We downloaded a separate microarray from the Integrated Gene Expression System (GEO) on a human bronchial organoids sample to identify differentially expressed genes (DEGS) and analyzed it with R software. After processing with R software, Gene Ontology (GO) and Kyoto PBMCs of Genes and Genomes (KEGG) were analyzed, while a protein-protein interaction (PPI) network was constructed to show the interactions and influence relationships between these differential genes. Finally, the selected highly connected genes, which are called hub genes, were verified in CytoHubba plug-in. RESULTS: In this study, a total of 966 differentially expressed genes, including 490 upregulated genes and 476 downregulated genes were used. Analysis of GO and KEGG revealed that these differentially expressed genes were significantly enriched in pathways related to immune response and cytokines. We construct protein-protein interaction network and identify 10 hub genes, including IL6, MMP9, IL1B, CXCL8, ICAM1, FGF2, EGF, CXCL10, CCL2, CCL5, CXCL1, and FN1. Finally, with the help of GSE150728, we verified that CXCl1, CXCL8, CXCL10, CCL5, EGF differently expressed before and after SARS-CoV-2 infection in clinical patients. CONCLUSIONS: In this study, we used mRNA expression data from GSE150819 to preliminarily confirm the feasibility of hBO as an in vitro model to further study the pathogenesis and potential treatment of COVID-19. Moreover, based on the mRNA differentiated expression of this model, we found that CXCL8, CXCL10, and EGF are hub genes in the process of SARS-COV-2 infection, and we emphasized their key roles in SARS-CoV-2 infection. And we also suggested that further study of these hub genes may be beneficial to treatment, prognostic prediction of COVID-19.
Entities:
Keywords:
3D structure model; Bioinformatics analysis; Human bronchial organoids; Immune response; Novel coronavirus infection
Authors: Jie Zhou; Cun Li; Norman Sachs; Man Chun Chiu; Bosco Ho-Yin Wong; Hin Chu; Vincent Kwok-Man Poon; Dong Wang; Xiaoyu Zhao; Lei Wen; Wenjun Song; Shuofeng Yuan; Kenneth Kak-Yuen Wong; Jasper Fuk-Woo Chan; Kelvin Kai-Wang To; Honglin Chen; Hans Clevers; Kwok-Yung Yuen Journal: Proc Natl Acad Sci U S A Date: 2018-06-11 Impact factor: 11.205
Authors: Jéssica F C Cordeiro; Talita M Fernandes; Diana M Toro; Pedro V da Silva-Neto; Vinícius E Pimentel; Malena M Pérez; Jonatan C S de Carvalho; Thais F C Fraga-Silva; Camilla N S Oliveira; Jamille G M Argolo; Augusto M Degiovani; Fátima M Ostini; Enrico F Puginna; João S da Silva; Isabel K F M Santos; Vânia L D Bonato; Cristina R B Cardoso; Marcelo Dias-Baruffi; Lúcia H Faccioli; Eduardo A Donadi; Carlos A Sorgi; Ana P M Fernandes Journal: Int J Mol Sci Date: 2022-08-27 Impact factor: 6.208