Exploration and validation of related hub gene expression during SARS-CoV-2 infection of human bronchial organoids

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.

LncRNAs harbouring regulatory motifs within repeat elements modulate immune response towards COVID‐19 disease severity and clinical outcomes

“…Importantly, downregulation of the RTCA‐AS1 in SARS‐CoV‐2‐infected human bronchial organoids has been reported. 9 Additionally, we found that SOB patients were closer to the mild, while the RS were similar to moderate for their lncRNA expression (Figure 3E ).…”

The Severity of COVID-19 Affects the Plasma Soluble Levels of the Immune Checkpoint HLA-G Molecule

“…Several lines of evidence support the role of HLA-G in COVID-19 pathogenesis, including (i) the increased levels of sHLA-G molecules in patients exhibiting various clinical manifestations of the disease [ 14 , 15 , 16 , 17 , 18 ], (ii) the increased number of immune system cells expressing HLA-G [ 16 , 19 ], (iii) the association of the HLA-G 3′untranslated region polymorphism with susceptibility to the disease [ 18 ], (iv) the increased tissue expression of HLA-G in case reports [ 20 , 21 ], and (v) the induction of the expression of hub genes, including HLA-G , in lung tissue infected by SARS-CoV-2 [ 22 ].…”

Bioinformatics-based investigation on the genetic influence between SARS-CoV-2 infections and idiopathic pulmonary fibrosis (IPF) diseases, and drug repurposing

“…The top five commonly enriched MFs (ubiquitin binding, sequence-specific DNA binding, CCR chemokine receptor binding, chemokine activity) by cHubGs, are significantly associated with both COVID-19 and IPF disease 59,75,76 . Similarly, the association of top four CCs (tertiary granule lumen, early endosome, extracellular space, cytosol, extracellular region) with COVID-19 and IPF disease were supported by the literature review 66,[77][78][79][80][81][82][83] . The top five commonly enriched KEGG pathways (TNF signaling, IL-17 signaling, NF-kappa B signaling, NOD-like receptor signaling and Cytokine-cytokine receptor interaction pathways) are also significantly associated with COVID-19 and IPF diseases 69,[84][85][86][87][88][89][90][91] .…”