ABSTRACT
Dysfunctional immune response in the COVID-19 patients is a recurrent theme impacting symptoms and mortality, yet the detailed understanding of pertinent immune cells is not complete. We applied single-cell RNA sequencing to 284 samples from 205 COVID-19 patients and controls to create a comprehensive immune landscape. Lymphopenia and active T and B cell responses were found to coexist and associated with age, sex and their interactions with COVID-19. Diverse epithelial and immune cell types were observed to be virus-positive and showed dramatic transcriptomic changes. Elevation of ANXA1 and S100A9 in virus-positive squamous epithelial cells may enable the initiation of neutrophil and macrophage responses via the ANXA1-FPR1 and S100A8/9-TLR4 axes. Systemic up-regulation of S100A8/A9, mainly by megakaryocytes and monocytes in the peripheral blood, may contribute to the cytokine storms frequently observed in severe patients. Our data provide a rich resource for understanding the pathogenesis and designing effective therapeutic strategies for COVID-19.
Subject(s)
Carcinoma, Squamous Cell , Lymphopenia , COVID-19ABSTRACT
The recent COVID-19 pandemic has brought about a surge of crowd-sourced initiatives aimed at simulating the proteins of the SARS-CoV-2 virus. A bottleneck currently exists in translating these simulations into tangible predictions that can be leveraged for pharmacological studies. Here we report on extensive electrostatic calculations done on an exascale simulation of the opening of the SARS-CoV-2 spike protein, performed by the Folding@home initiative. We compute the electric potential as the solution of the non-linear Poisson-Boltzmann equation using a parallel sharp numerical solver. The inherent multiple length scales present in the geometry and solution are reproduced using highly adaptive Octree grids. We analyze our results focusing on the electro-geometric properties of the receptor-binding domain and its vicinity. This work paves the way for a new class of hybrid computational and data-enabled approaches, where molecular dynamics simulations are combined with continuum modeling to produce high-fidelity computational measurements serving as a basis for protein bio-mechanism investigations.
Subject(s)
COVID-19ABSTRACT
Objective: To investigate the mechanism of Qingkailing Injection in the treatment of coronavirus disease 2019 (COVID-19). Methods: The active components and target proteins of Gardeniae Fructus, Isatidis Radix, Lonicerae Japonicae Flos, and other materials in Qingkailing Injection were obtained by means of literature search and TCMSP. Uniprot database was used to search the target genes corresponding to the active ingredients, and Cytoscape 3.7.2 was used to construct the drug-compound-target network. The enrichment analysis of KEGG pathway was carried out with the help of DAVID database to predict its mechanism. Core active components and potential targets of anti-COVID-19 drugs were verified by molecular docking. Results: The drug-compound- target network consisted of five drugs, 62 compounds and 70 targets. The KEGG pathway enrichment analysis included 41 signaling pathways (P < 0.05), which were mainly involved in cell apoptosis, Fc epsilon RI signaling pathway, TNF signaling pathway, etc. Molecular docking results showed that acacetin and syrigin had strong affinity with potential targets of anti-COVID-19 drugs. Conclusion: In this study, the effect of Qingkailing Injection has the characteristics of multiple components, multiple targets and multiple pathways. The active component, acacetin, can regulate the apoptosis pathway and TNF pathway by acting on CASP3, CASP8, FASLG, and other targets, so as to realize the potential therapeutic effect on COVID-19.