Upregulation of PD-L1 by SARS-CoV-2 promotes immune evasion.
Hsiang-Chi HuangShih-Han WangGuo-Chen FangWen-Cheng ChouChun-Che LiaoCheng-Pu SunJia-Tsrong JanHsiu-Hua MaHui-Ying KoYi-An KoMing-Tsai ChiangJian-Jong LiangChun-Tse KuoTe-An LeeDiego Morales-ScheihingChen-Yang ShenShih-Yu ChenLouise D McCulloughLu CuiGerlinde WernigMi-Hua TaoYi-Ling LinYao-Ming ChangShu-Ping WangYun-Ju LaiChia-Wei LiPublished in: Journal of medical virology (2023)
Patients with severe COVID-19 often suffer from lymphopenia, which is linked to T cell sequestration, cytokine storm and mortality. However, it remains largely unknown how SARS-CoV-2 induces lymphopenia. Here, we studied the transcriptomic profile and epigenomic alterations involved in cytokine production by SARS-CoV-2-infected cells. We adopted a reverse time-order gene coexpression network (TO-GCN) approach to analyze time-series RNA-sequencing data, revealing epigenetic modifications at the late stage of viral egress. Furthermore, we identified SARS-CoV-2-activated NF-κB and IRF1 pathways contributing to viral infection and COVID-19 severity through epigenetic analysis of H3K4me3 ChIP-sequencing. Cross-referencing our transcriptomic and epigenomic datasets revealed that coupling NF-κB and IRF1 pathways mediate PD-L1 immunosuppressive programs. Interestingly, we observed higher PD-L1 expression in Omicron-infected cells than SARS-CoV-2 infected cells. Blocking PD-L1 at an early stage of virally-infected AAV-hACE2 mice significantly recovered lymphocyte counts and lowered inflammatory cytokine levels. Our findings indicate that targeting the SARS-CoV-2-mediated NF-κB and IRF1-PD-L1 axis may represent an alternative strategy to reduce COVID-19 severity. This article is protected by copyright. All rights reserved.
Keyphrases
- sars cov
- induced apoptosis
- respiratory syndrome coronavirus
- single cell
- signaling pathway
- cell cycle arrest
- early stage
- oxidative stress
- pi k akt
- rna seq
- public health
- gene expression
- dendritic cells
- endoplasmic reticulum stress
- cell proliferation
- cell death
- radiation therapy
- early onset
- genome wide
- poor prognosis
- risk factors
- coronary artery disease
- cardiovascular events
- cardiovascular disease
- long non coding rna
- deep learning
- artificial intelligence
- wild type