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Interaction network of SARS-CoV-2 with host receptome through spike protein
Preprint
in En
| PREPRINT-BIORXIV
| ID: ppbiorxiv-287508
ABSTRACT
Host cellular receptors are key determinants of virus tropism and pathogenesis. Virus utilizes multiple receptors for attachment, entry, or specific host responses. However, other than ACE2, little is known about SARS-CoV-2 receptors. Furthermore, ACE2 cannot easily interpret the multi-organ tropisms of SARS-CoV-2 nor the clinical differences between SARS-CoV-2 and SARS-CoV. To identify host cell receptors involved in SARS-CoV-2 interactions, we performed genomic receptor profiling to screen almost all human membrane proteins, with SARS-CoV-2 capsid spike (S) protein as the target. Twelve receptors were identified, including ACE2. Most receptors bind at least two domains on S protein, the receptor-binding-domain (RBD) and the N-terminal-domain (NTD), suggesting both are critical for virus-host interaction. Ectopic expression of ASGR1 or KREMEN1 is sufficient to enable entry of SARS-CoV-2, but not SARS-CoV and MERS-CoV. Analyzing single-cell transcriptome profiles from COVID-19 patients revealed that virus susceptibility in airway epithelial ciliated and secretory cells and immune macrophages highly correlates with expression of ACE2, KREMEN1 and ASGR1 respectively, and ACE2/ASGR1/KREMEN1 (ASK) together displayed a much better correlation than any individual receptor. Based on modeling of systemic SARS-CoV-2 host interactions through S receptors, we revealed ASK correlation with SARS-CoV-2 multi-organ tropism and provided potential explanations for various COVID-19 symptoms. Our study identified a panel of SARS-CoV-2 receptors with diverse binding properties, biological functions, and clinical correlations or implications, including ASGR1 and KREMEN1 as the alternative entry receptors, providing insights into critical interactions of SARS-CoV-2 with host, as well as a useful resource and potential drug targets for COVID-19 investigation.
cc_by_nd
Full text:
1
Collection:
09-preprints
Database:
PREPRINT-BIORXIV
Type of study:
Prognostic_studies
Language:
En
Year:
2020
Document type:
Preprint