Article ; Online: Distinct SARS-CoV-2 sensing pathways in pDCs driving TLR7-antiviral vs. TLR2-immunopathological responses in COVID-19
bioRxiv
Abstract: Understanding the molecular pathways driving the acute antiviral and inflammatory response to SARS-CoV-2 infection is critical for developing treatments for severe COVID-19. Here we show that in COVID-19 patients, circulating plasmacytoid dendritic cells ...
| Abstract | Understanding the molecular pathways driving the acute antiviral and inflammatory response to SARS-CoV-2 infection is critical for developing treatments for severe COVID-19. Here we show that in COVID-19 patients, circulating plasmacytoid dendritic cells (pDCs) decline early after symptom onset and this correlated with COVID-19 disease severity. This transient depletion coincides with decreased expression of antiviral type I IFNα and the systemic inflammatory cytokines CXCL10 and IL-6. Importantly, COVID-19 disease severity correlated with decreased pDC frequency in peripheral blood. Using an in vitro stem cell-based human pDC model, we demonstrate that pDCs directly sense SARS-CoV-2 and in response produce multiple antiviral (IFNα and IFNλ1) and inflammatory (IL-6, IL-8, CXCL10) cytokines. This immune response is sufficient to protect epithelial cells from de novo SARS-CoV-2 infection. Targeted deletion of specific sensing pathways identified TLR7-MyD88 signaling as being crucial for production of the antiviral IFNs, whereas TLR2 is responsible for the inflammatory IL-6 response. Surprisingly, we found that SARS-CoV-2 engages the neuropilin-1 receptor on pDCs to mitigate the antiviral IFNs but not the IL-6 response. These results demonstrate distinct sensing pathways used by pDCs to elicit antiviral vs. immunopathological responses to SARS-CoV-2 and suggest that targeting neuropilin-1 on pDCs may be clinically relevant for mounting TLR7-mediated antiviral protection. |
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| Keywords | covid19 |
| Language | English |
| Publishing date | 2021-11-24 |
| Publisher | Cold Spring Harbor Laboratory |
| Document type | Article ; Online |
| DOI | 10.1101/2021.11.23.469755 |
| Database | COVID19 |
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