ABSTRACT
The current pandemic of COVID-19 is fueled by more infectious emergent Omicron variants. Ongoing concerns of emergent variants include possible recombinants, as genome recombination is an important evolutionary mechanism for the emergence and re-emergence of human viral pathogens. Although recombination events among SARS-CoV-1 and MERS-CoV were well-documented, it has been difficult to detect the recombination signatures in SARS-CoV-2 variants due to their high degree of sequence similarity. In this study, we identified diverse recombination events between two Omicron major subvariants (BA.1 and BA.2) and other variants of concern (VOCs) and variants of interest (VOIs), suggesting that co-infection and subsequent genome recombination play important roles in the ongoing evolution of SARS-CoV-2. Through scanning high-quality completed Omicron spike gene sequences, eighteen core mutations of BA.1 variants (frequency >99%) were identified (eight in NTD, five near the S1/S2 cleavage site, and five in S2). BA.2 variants share three additional amino acid deletions with the Alpha variants. BA.1 subvariants share nine common amino acid mutations (three more than BA.2) in the spike protein with most VOCs, suggesting a possible recombination origin of Omicron from these VOCs. There are three more Alpha-related mutations (del69-70, del144) in BA.1 than BA.2, and therefore BA.1 may be phylogenetically closer to the Alpha variant. Revertant mutations are found in some dominant mutations (frequency >95%) in the BA.1 subvariant. Most notably, multiple additional amino acid mutations in the Delta spike protein were also identified in the recently emerged Omicron isolates, which implied possible recombination events occurred between the Omicron and Delta variants during the on-going pandemic. Monitoring the evolving SARS-CoV-2 genomes especially for recombination is critically important for recognition of abrupt changes to viral attributes including its epitopes which may call for vaccine modifications.
Subject(s)
Coinfection , COVID-19ABSTRACT
Cancer patients are more susceptible to SARS-CoV-2 infection and generally have higher mortality rate. Anti-SARS-CoV-2 IgG is an important consideration for the patients in this COVID-19 pandemic. Recent researches suggested the rapid decay of anti-SARS-CoV-2 antibodies in the general population, but the decline rate of the antibodies in cancer patients was unknown. In this observational study, we reported the clinical features of the 53 cancer patients infected by SARS-CoV-2 from two hospitals in Wuhan, China and tracked the presence of anti-SARS-CoV-2 antibodies in the patients for more than 12 months. We found the duration (days) of anti-SARS-CoV-2 IgG in the patients was significant longer in chemotherapy (mean: 175; range: 75 to 315) and radiotherapy groups (mean: 168; range: 85 to 265) than in non-chemo- or radio-therapy group (mean: 58; range:21 to 123) after their recovery from COVID-19. We also used single-cell RNA sequencing to track the immunologic changes in a representative patient infected by COVID-19 for more than one year, and found that CD8 + effective T cells, memory B cells and plasma cells were persistently activated in the patient undergoing chemotherapy. Together, our findings show that chemotherapy and radiotherapy might be beneficial to extend the duration of anti-SARS-CoV-2 IgG.
Subject(s)
COVID-19ABSTRACT
The spread of COVID-19 pandemic and the participation of Internet information are continually changing the public’s positive emotions and risk perception. However, relatively little is known about the underlying mechanism of how the COVID-19 dynamic situation affects the public’s risk perception and emotions. This study uses the social risk amplification framework (SRAF) as the theoretical basis to collect and analyze Hubei Province data from January 20 to April 8, 2020, including the number of newly diagnosed people per day, the proportion of positive emotional posts in Weibo, and the Baidu search index (BSI). The autoregressive integrated moving average (ARIMAbased time-series prediction model is used to analyze the dynamic evolution laws and fluctuation trends of Weibo positive emotions and risk perception during the development of the pandemic. The conclusion of the study is that positive emotions are negatively correlated with risk perception, the severity of the pandemic situation is negatively correlated with positive emotions, and the severity of the pandemic situation is positively correlated with risk perception. The public has a keen response to the dynamics of the pandemic situation and the government’s decision-making behavior, which is manifested by the significant changes in positive emotions and risk perception in the corresponding period. The research results can provide a reference for government departments to guide the public to establish an objective risk perception and maintain positive and stable emotions in similar catastrophes.
ABSTRACT
BACKGROUND: Coronavirus Disease 2019 (COVID-19) has recently become a public emergency and a worldwide pandemic. The clinical symptoms of severe and non-severe patients vary, and the case-fatality rate (CFR) in severe COVID-19 patients is very high. However, the information on the risk factors associated with the severity of COVID-19 and of their prognostic potential is limited. METHODS: In this retrospective study, the clinical characteristics, laboratory findings, treatment and outcome data were collected and analyzed from 223 COVID-19 patients stratified into 125 non-severe patients and 98 severe patients. In addition, a pooled large-scale meta-analysis of 1646 cases was performed. RESULTS: We found that the age, gender and comorbidities are the common risk factors associated with the severity of COVID-19. For the diagnosis markers, we found that the levels of D-dimer, C-reactive protein (CRP), lactate dehydrogenase (LDH), procalcitonin (PCT) were significantly higher in severe group compared with the non-severe group on admission (D-Dimer: 87.3% vs. 35.3%, P<0.001; CRP, 65.1% vs. 13.5%, P<0.001; LDH: 83.9% vs. 22.2%, P<0.001; PCT: 35.1% vs. 2.2%, P<0.001), while the levels of aspartate aminotransferase (ASP) and creatinine kinase (CK) were only mildly increased. We also made a large scale meta-analysis of 1646 cases combined with 4 related literatures, and further confirmed the relationship between the COVID-19 severity and these risk factors. Moreover, we tracked dynamic changes during the process of COVID-19, and found CRP, D-dimer, LDH, PCT kept in high levels in severe patient. Among all these markers, D-dimer increased remarkably in severe patients and mostly related with the case-fatality rate (CFR). We found adjuvant antithrombotic treatment in some severe patients achieved good therapeutic effect in the cohort. CONCLUSIONS: The diagnosis markers CRP, D-dimer, LDH and PCT are associated with severity of COVID-19. Among these markers, D-dimer is sensitive for both severity and CFR of COVID-19. Treatment with heparin or other anticoagulants may be beneficial for COVID-19 patients.
Subject(s)
COVID-19ABSTRACT
The current global pandemic of COVID-19 is caused by a novel coronavirus SARS-CoV-2. The SARS-CoV-2 spike protein receptor-binding domain (RBD) is the critical determinant of viral tropism and infectivity. To investigate whether naturally occurring mutations in the RBD during the early transmission phase have altered the receptor binding affinity and infectivity, firstly we analyzed in silico the binding dynamics between mutated SARS-CoV-2 RBDs and the human ACE2 receptor. Among 32,123 genomes of SARS-CoV-2 isolates (January through March, 2020), 302 non-synonymous RBD mutants were identified and clustered into 96 mutant types. The six dominant mutations were analyzed applying molecular dynamics simulations. The mutant type V367F continuously circulating worldwide displayed higher binding affinity to human ACE2 due to the enhanced structural stabilization of the RBD beta-sheet scaffold. The increased infectivity of V367 mutants was further validated by performing receptor-ligand binding ELISA, surface plasmon resonance, and pseudotyped virus assays. Genome phylogenetic analysis of V367F mutants showed that during the early transmission phase, most V367F mutants clustered more closely with the SARS-CoV-2 prototype strain than the dual-mutation variants (V367F + D614G) which emerged later and formed a distinct sub-cluster. The analysis of critical RBD mutations provides further insights into the evolutionary trajectory of SARS-CoV-2 under negative selection pressure and supports the continuing surveillance of spike mutations to aid in the development of new COVID-19 drugs and vaccines. ImportanceA novel coronavirus SARS-CoV-2 has caused the pandemic of COVID-19. The origin of SARS-CoV-2 was associated with zoonotic infections. The spike protein receptor-binding domain (RBD) is identified as the critical determinant of viral tropism and infectivity. Thus, whether the mutations in the RBD of the circulating SARS-CoV-2 isolates have altered the receptor binding affinity and caused them more infectious, should be paid more attentions to. Given that SARS-CoV-2 is a novel coronavirus, the significance of our research is in identifying and validating the RBD mutant types emerging during the early transmission phase that have increased human ACE2 receptor binding affinity and infectivity. The RBD mutation analysis provides insights into SARS-CoV-2 evolution. The continuous surveillance of RBD mutations with increased human ACE2 affinity in human or other animals is important and necessary, particularly when the direct correlation between the virus variations and vaccine effectiveness is underdetermined during the sustained COVID-19 pandemic.