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Whole transcriptome exploration revealed the dysregulated RNAs involved in SARS-CoV-2 spike protein inhibited apoptosis in Calu-3 cells

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NIAID Data Ecosystem2026-05-02 收录
下载链接:
https://www.ncbi.nlm.nih.gov/sra/SRP371755
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SARS-CoV-2 induced COVID-19 has been spreading all over the world since 2020. Although the vaccines have been planted and efficiently suppressed the momentum, it is not fully understood how SARS-CoV-2 infects host cells, especially for the functions of its spike (S) glycoprotein. In this study, we investigated the biological and molecular functions of S protein by infecting the commercial pure S protein into human Calu-3 cells and analyzing apoptotic level change and its regulated transcriptome profile using whole transcriptome sequencing method (RNA-seq). Strikingly, we found S protein alone could significantly inhibit apoptotic level with dose dependent manner in Calu-3 cells, with or without ActD treatment. Higher level of S protein has more effective inhibition on cellular apoptosis. ActD-treated RNA-seq data analysis revealed hundreds of mRNAs, lncRNAs, and circRNAs were differentially expressed at post-transcriptional level. Functional enrichment analysis of DE mRNAs and lncRNAs showed they were highly enriched in inflammatory response, cell adhesion, and apoptotic process pathways. Host genes of circRNAs were enriched in metabolic and lysosome pathways. Finally, we constructed an RNA regulatory network involving these three RNA classes that were dysregulated in this study. RT-qPCR experiment was performed to validate the DE RNAs, which showed a high consistency with RNA-seq data. In conclusion, our study demonstrated the novel functions of SARS-CoV-2 S protein in lung Calu-3 cells, which will be helpful to understand the underlying molecular mechanisms during SARS-CoV-2 infection and the development of drugs and vaccines in future. Overall design: We obtained the purified SARS-CoV-2 S protein and transfected it into human Calu-3 cells, which are frequently used in virus infection experiments. Whole transcriptome sequencing data was utilized to identify its regulated expression pattern of genes, including mRNA, lncRNA, and circRNA genes.
创建时间:
2025-04-22
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