Project description:Epitopes that are conserved among SARS-like coronaviruses are attractive targets for design of cross-reactive vaccines and therapeutics. CR3022 is a SARS-CoV neutralizing antibody to a highly conserved epitope on the receptor binding domain (RBD) on the spike protein that can cross-react with SARS-CoV-2, but with lower affinity. Using x-ray crystallography, mutagenesis, and binding experiments, we illustrate that of four amino acid differences in the CR3022 epitope between SARS-CoV-2 and SARS-CoV, a single mutation P384A fully determines the affinity difference. CR3022 does not neutralize SARS-CoV-2, but the increased affinity to SARS-CoV-2 P384A mutant now enables neutralization with a similar potency to SARS-CoV. We further investigated CR3022 interaction with the SARS-CoV spike protein by negative-stain EM and cryo-EM. Three CR3022 Fabs bind per trimer with the RBD observed in different up-conformations due to considerable flexibility of the RBD. In one of these conformations, quaternary interactions are made by CR3022 to the N-terminal domain (NTD) of an adjacent subunit. Overall, this study provides insights into antigenic variation and potential for cross-neutralizing epitopes on SARS-like viruses.
Project description:Epitopes that are conserved among SARS-like coronaviruses are attractive targets for design of cross-reactive vaccines and therapeutics. CR3022 is a SARS-CoV neutralizing antibody to a highly conserved epitope on the receptor binding domain (RBD) on the spike protein that is able to cross-react with SARS-CoV-2, but with lower affinity. Using x-ray crystallography, mutagenesis, and binding experiments, we illustrate that of four amino acid differences in the CR3022 epitope between SARS-CoV-2 and SARS-CoV, a single mutation P384A fully determines the affinity difference. CR3022 does not neutralize SARS-CoV-2, but the increased affinity to SARS-CoV-2 P384A mutant now enables neutralization with a similar potency to SARS-CoV. We further investigated CR3022 interaction with the SARS-CoV spike protein by negative-stain EM and cryo-EM. Three CR3022 Fabs bind per trimer with the RBD observed in different up-conformations due to considerable flexibility of the RBD. In one of these conformations, quaternary interactions are made by CR3022 to the N-terminal domain (NTD) of an adjacent subunit. Overall, this study provides insights into antigenic variation and potential cross-neutralizing epitopes on SARS-like viruses.
Project description:SARS-CoV-2 is an emerging coronavirus that causes dysfunctions in multiple human cells and tissues. Studies have looked at the entry of SARS-CoV-2 into host cells mediated by the viral spike protein and human receptor ACE2. However, less is known about the cellular immune responses triggered by SARS-CoV-2 viral proteins. Here, we show that the nucleocapsid of SARS-CoV-2 inhibits host pyroptosis by blocking Gasdermin D (GSDMD) cleavage. SARS-CoV-2-infected monocytes show enhanced cellular interleukin 1b (IL-1b) expression, but reduced IL-1b secretion. While SARS-CoV-2 infection promotes activation of the NLRP3 inflammasome and caspase-1, GSDMD cleavage and pyroptosis are inhibited in infected human monocytes. SARS-CoV-2 nucleocapsid protein associates with GSDMD in cells and inhibits GSDMD cleavage in vitro and in vivo. The nucleocapsid binds the GSDMD linker region and hinders GSDMD processing by caspase-1. These insights into how SARS-CoV-2 antagonizes cellular inflammatory responses may open new avenues for treating COVID-19 in the future.
Project description:The capacity of RNA viruses to adapt to new hosts and rapidly escape the host immune system is largely attributable to de novo genetic diversity that emerges through mutations in RNA. Although the molecular spectrum of de novo mutations-the relative rates at which various base substitutions occur-are widely recognized as informative toward understanding the evolution of a viral genome, little attention has been paid to the possibility of using molecular spectra to infer the host origins of a virus. Here, we characterize the molecular spectrum of de novo mutations for SARS-CoV-2 from transcriptomic data obtained from virus-infected cell lines, enabled by the use of sporadic junctions formed during discontinuous transcription as molecular barcodes. We find that de novo mutations are generated in a replication-independent manner, typically on the genomic strand, and highly dependent on mutagenic mechanisms specific to the host cellular environment. De novo mutations will then strongly influence the types of base substitutions accumulated during SARS-CoV-2 evolution, in an asymmetric manner favoring specific mutation types. Consequently, similarities between the mutation spectra of SARS-CoV-2 and the bat coronavirus RaTG13, which have accumulated since their divergence strongly suggest that SARS-CoV-2 evolved in a host cellular environment highly similar to that of bats before its zoonotic transfer into humans. Collectively, our findings provide data-driven support for the natural origin of SARS-CoV-2.
Project description:One year since the first severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was reported in China, several variants of concern (VOC) have appeared around the world, with some variants seeming to pose a greater thread to public health due to enhanced transmissibility or infectivity. This study provides a framework for molecular characterization of novel VOC and investigates the effect of mutations on the binding affinity of the receptor-binding domain (RBD) to human angiotensin-converting enzyme 2 (hACE2) using in silico approach. Notable nonsynonymous mutations in RBD of VOC include the E484K and K417N/T that can be seen in South African and Brazilian variants, and N501Y and D614G that can be seen in all VOC. Phylogenetic analyses demonstrated that although the UK-VOC and the BR-VOC fell in the clade GR, they have different mutation signatures, implying an independent evolutionary pathway. The same is true about SA-VOC and COH-VOC felling in clade GH, but different mutation signatures. Combining molecular interaction modeling and the free energy of binding (FEB) calculations for VOC, it can be assumed that the mutation N501Y has the highest binding affinity in RBD for all VOC, followed by E484K (only for BR-VOC), which favors the formation of a stable complex. However, mutations at the residue K417N/T are shown to reduce the binding affinity. Once vaccination has started, there will be selective pressure that would be in favor of the emergence of novel variants capable of escaping the immune system. Therefore, genomic surveillance should be enhanced to find and monitor new emerging SARS-CoV-2 variants before they become a public health concern.
Project description:Numerous studies demonstrate frequent mutations in the genome of SARS-CoV-2. Our goal was to statistically link mutations to severe disease outcome. We used an automated machine learning approach where 1594 viral genomes with available clinical follow-up data were used as the training set (797 'severe' and 797 'mild'). The best algorithm, based on random forest classification combined with the LASSO feature selection algorithm, was employed to the training set to link mutation signatures and outcome. The performance of the final model was estimated by repeated, stratified, 10-fold cross validation (CV) and then adjusted for multiple testing with Bootstrap Bias Corrected CV. We identified 26 protein and Untranslated Region (UTR) mutations significantly linked to severe outcome. The best classification algorithm uses a mutation signature of 22 mutations as well as the patient's age as the input and shows high classification efficiency with an area under the curve (AUC) of 0.94 [confidence interval (CI): [0.912, 0.962]] and a prediction accuracy of 87% (CI: [0.830, 0.903]). Finally, we established an online platform (https://covidoutcome.com/) that is capable to use a viral sequence and the patient's age as the input and provides a percentage estimation of disease severity. We demonstrate a statistical association between mutation signatures of SARS-CoV-2 and severe outcome of COVID-19. The established analysis platform enables a real-time analysis of new viral genomes.
Project description:SARS-CoV-2 has been emerged in December 2019 in China, causing deadly (5% mortality) pandemic pneumonia, termed COVID-19. More than one host-cell receptor is reported to be recognized by the viral spike protein, among them is the cell-surface Heat Shock Protein A5 (HSPA5), also termed GRP78 or BiP. Upon viral infection, HSPA5 is upregulated, then translocating to the cell membrane where it is subjected to be recognized by the SARS-CoV-2 spike. In this study, some natural product compounds are tested against the HSPA5 substrate-binding domain ? (SBD?), which reported to be the recognition site for the SARS-CoV-2 spike. Molecular docking and molecular dynamics simulations are used to test some natural compounds binding to HSPA5 SBD?. The results show high to a moderate binding affinity for the phytoestrogens (Diadiazin, Genistein, Formontein, and Biochanin A), chlorogenic acid, linolenic acid, palmitic acid, caffeic acid, caffeic acid phenethyl ester, hydroxytyrosol, cis-p-Coumaric acid, cinnamaldehyde, thymoquinone, and some physiological hormones such as estrogens, progesterone, testosterone, and cholesterol to the HSPA5 SBD?. Based on its binding affinities, the phytoestrogens and estrogens are the best in binding HSPA5, hence may interfere with SARS-CoV-2 attachment to the stressed cells. These compounds can be successful as anti-COVID-19 agents for people with a high risk of cell stress like elders, cancer patients, and front-line medical staff.Communicated by Ramaswamy H. Sarma.
Project description:Host-virus protein-protein interactions play key roles in the lifecycle of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We conducted a comprehensive interactome study between the virus and host cells using tandem affinity purification and proximity labeling strategies and identified 437 human proteins as the high-confidence interacting proteins. Further characterization of these interactions and comparison to other large-scale study of cellular responses to SARS-CoV-2 infection elucidated how distinct SARS-CoV-2 viral proteins participate in its lifecycle. With these data mining, we discovered potential drug targets for the treatment of COVID-19. The interactomes of two key SARS-CoV-2-encoded viral proteins, NSP1 and N, were compared with the interactomes of their counterparts in other human coronaviruses. These comparisons not only revealed common host pathways these viruses manipulate for their survival, but also showed divergent protein-protein interactions that may explain differences in disease pathology. This comprehensive interactome of SARS-CoV-2 provides valuable resources for the understanding and treating of this disease.