The SARS-CoV-2 accessory factor ORF7a downregulates MHC class I surface expression

biorxiv(2022)

引用 4|浏览9
暂无评分
摘要
The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in over 500 million infections and more than six million deaths worldwide. Although the viral genomes of SARS-CoV-1 and SARS-CoV-2 share high sequence homology, the clinical and pathological features of COVID-19 differ profoundly from those of SARS. It is apparent that changes in viral genes contribute to the increased transmissibility of SARS-CoV-2 and pathology of COVID-19. Cytotoxic T lymphocytes play a key role in the elimination of virus-infected cells, mediated by recognition of virus-derived peptides that are presented on MHC class I molecules. Here, we show that SARS-CoV-2 can interfere with antigen presentation thereby evading immune surveillance. SARS-CoV-2 infection of monkey and human cell lines resulted in reduced cell-surface expression of MHC class I molecules. We identified a single viral gene product, the accessory factor open reading frame 7a (ORF7a), that mediates this effect. ORF7a interacts with HLA class I molecules in the ER, resulting in ER retention or impaired HLA heavy chain (HC) trafficking to the Golgi. Ultimately, these actions result in reduced HLA class I surface expression on infected cells. Whereas ORF7a from SARS-CoV-2 reduces surface HLA class I levels, the homologous ORF7a from the 2002 pandemic SARS-CoV-1 did not, suggesting that SARS-CoV-2 ORF7a acquired the ability to downregulate HLA-I during evolution of the virus. We identified a single amino acid in the SARS-CoV-1 ORF7a luminal domain that, upon mutating to the corresponding SARS-CoV-2 ORF7a sequence, induced a gain-of-function in HLA surface downregulation. By abrogating HLA class I antigen presentation via ORF7a, SARS-CoV-2 may evade host immune responses by inhibiting anti-viral cytotoxic T cell activity, thereby contributing to the pathology of COVID-19. ### Competing Interest Statement The authors have declared no competing interest.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要