Variation in synonymous evolutionary rates in the SARS-CoV-2 genome.

Introduction: Coronavirus disease 2019 is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Influential variants and mutants of this virus continue to emerge, and more effective virus-related information is urgently required for identifying and predicting new mutants. According to earlier reports, synonymous substitutions were considered phenotypically silent; thus, such mutations were frequently ignored in studies of viral mutations because they did not directly cause amino acid changes. However, recent studies have shown that synonymous substitutions are not completely silent, and their patterns and potential functional correlations should thus be delineated for better control of the pandemic. Methods: In this study, we estimated the synonymous evolutionary rate (SER) across the SARS-CoV-2 genome and used it to infer the relationship between the viral RNA and host protein. We also assessed the patterns of characteristic mutations found in different viral lineages. Results: We found that the SER varies across the genome and that the variation is primarily influenced by codon-related factors. Moreover, the conserved motifs identified based on the SER were found to be related to host RNA transport and regulation. Importantly, the majority of the existing fixed-characteristic mutations for five important virus lineages (Alpha, Beta, Gamma, Delta, and Omicron) were significantly enriched in partially constrained regions. Discussion: Taken together, our results provide unique information on the evolutionary and functional dynamics of SARS-CoV-2 based on synonymous mutations and offer potentially useful information for better control of the SARS-CoV-2 pandemic.

Impact of combination preventative interventions on hospitalization and death under the pandemic of SARS-CoV-2 Omicron variant in China.

With a large population most susceptible to Omicron and emerging SARS-CoV-2 variants, China faces uncertain scenarios if reopening its border. Thus, we aimed to predict the impact of combination preventative interventions on hospitalization and death. An age-stratified susceptible-infectious-quarantined-hospitalized-removed-susceptible (SIQHRS) model based on the new guidelines of COVID-19 diagnosis and treatment (the ninth edition) was constructed to simulate the transmission dynamics of Omicron within 365 days. At baseline, we assumed no interventions other than 60% booster vaccination in individuals aged <=60 years and 80% in individuals aged >60 years, quarantine and hospitalization. Oral antiviral medications for COVID-19 (e.g. BRII-196/BRII-198) and non-pharmaceutical interventions (NPIs) such as social distancing and antigen self-testing were considered in subsequent scenarios. Sensitivity analyses were conducted to reflect different levels of interventions. A total of 0.73 billion cumulative quarantines (95% CI 0.53-0.83), 33.59 million hospitalizations (22.41-39.31), and 0.62 million deaths (0.40-0.75) are expected in 365 days. The case fatality rate with pneumonia symptoms (moderate, severe and critical illness) is expected to be 1.83% (1.68-1.99%) and the infected fatality rate 0.38‰ (0.33-0.42‰). The highest existing hospitalization and ICU occupations are 3.11 (0.30-3.85) and 20.33 (2.01-25.20) times of capacity, respectively. Sensitivity analysis showed that interventions can be adjusted to meet certain conditions to reduce the total number of infections and deaths. In conclusion, after sufficient respiratory and ICU beds are prepared and the relaxed NPIs are in place, the SARS-CoV-2 Omicron variant would not seriously impact the health system. This article is protected by copyright. All rights reserved.

Oridonin Inhibits SARS‐CoV‐2 by Targeting Its 3C‐Like Protease

Oridonin Inhibits SARS‐CoV‐2 Oridonin, a natural product extracted from Rabdosia rubescens, possesses a wide range of pharmacological properties, including anti‐inflammatory, anti‐cancer, anti‐microbial, neuroprotection, immunoregulation, etc. In article number 2100124, Baisen Zhong, Litao Sun, and co‐workers demonstrate that Oridonin targets the SARS‐CoV‐2 3CL protease by covalently binding to cysteine145 in its active pocket to exert an anti‐SARS‐CoV‐2 effect, which provides a novel candidate for the treatment of COVID‐19. © 2022 WILEY‐VCH GmbH

Rational design of AAVrh10-vectored ACE2 functional domain to broadly block the cell entry of SARS-CoV-2 variants.

The frequently emerging SARS-CoV-2 variants have weakened the effectiveness of existing COVID-19 vaccines and neutralizing antibody therapy. Nevertheless, the infections of SARS-CoV-2 variants still depend on angiotensin-converting enzyme 2 (ACE2) receptor-mediated cell entry, and thus the soluble human ACE2 (shACE2) is a potential decoy for broadly blocking SARS-CoV-2 variants. In this study, we firstly generated the recombinant AAVrh10-vectored shACE2 constructs, a kind of adeno-associated virus (AAV) serotype with pulmonary tissue tropism, and then validated its inhibition capacity against SARS-CoV-2 infection. To further optimize the minimized ACE2 functional domain candidates, a comprehensive analysis was performed to clarify the interactions between the ACE2 orthologs from various species and the receptor binding domain (RBD) of SARS-CoV-2 spike (S) protein. Based on the key interface amino acids, we designed a series of truncated ACE2 orthologs, and then assessed their potential affinity to bind to SARS-CoV-2 variants RBD in silico. Of note, we found that the 24-83aa fragment of dog ACE2 (dACE224-83) had a higher affinity to the RBD of SARS-CoV-2 variants than that of human ACE2. Importantly, AAVrh10-vectored shACE2 or dACE224-83 constructs exhibited a broadly blockage breadth against SARS-CoV-2 prototype and variants in vitro and ex vivo. Collectively, these data highlighted a promising therapeutic strategy against SARS-CoV-2 variants.

Oridonin Inhibits SARS-CoV-2 by Targeting Its 3C-Like Protease.

The current COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is an enormous threat to public health. The SARS-CoV-2 3C-like protease (3CLpro), which is critical for viral replication and transcription, has been recognized as an ideal drug target. Herein, it is identified that three herbal compounds, Salvianolic acid A (SAA), (-)-Epigallocatechin gallate (EGCG), and Oridonin, directly inhibit the activity of SARS-CoV-2 3CLpro. Further, blocking SARS-CoV-2 infectivity by Oridonin is confirmed in cell-based experiments. By solving the crystal structure of 3CLpro in complex with Oridonin and comparing it to that of other ligands with 3CLpro, it is identified that Oridonin binds at the 3CLpro catalytic site by forming a C-S covalent bond, which is confirmed by mass spectrometry and kinetic study, blocking substrate binding through a nonpeptidomimetic covalent binding mode. Thus, Oridonin is a novel candidate to develop a new antiviral treatment for COVID-19.

Therapeutic antibodies for COVID-19: is a new age of IgM, IgA and bispecific antibodies coming?

Early humoral immune responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are dominated by IgM and IgA antibodies, which greatly contribute to virus neutralization at mucosal sites. Given the essential roles of IgM and IgA in the control and elimination of SARS-CoV-2 infection, the mucosal immunity could be exploited for therapeutic and prophylactic purposes. However, almost all neutralizing antibodies that are authorized for emergency use and under clinical development are IgG antibodies, and no vaccine has been developed to boost mucosal immunity for SARS-CoV-2 infection. In addition to IgM and IgA, bispecific antibodies (bsAbs) combine specificities of two antibodies in one molecule, representing an important alternative to monoclonal antibody cocktails. Here, we summarize the latest advances in studies on IgM, IgA and bsAbs against SARS-CoV-2. The current challenges and future directions in vaccine design and antibody-based therapeutics are also discussed.

An engineered bispecific human monoclonal antibody against SARS-CoV-2.

The global severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic requires effective therapies against coronavirus disease 2019 (COVID-19), and neutralizing antibodies are a promising therapy. A noncompeting pair of human neutralizing antibodies (B38 and H4) blocking SARS-CoV-2 binding to its receptor, ACE2, have been described previously. Here, we develop bsAb15, a bispecific monoclonal antibody (bsAb) based on B38 and H4. bsAb15 has greater neutralizing efficiency than these parental antibodies, results in less selective pressure and retains neutralizing ability to most SARS-CoV-2 variants of concern (with more potent neutralizing activity against the Delta variant). We also selected for escape mutants of the two parental mAbs, a mAb cocktail and bsAb15, demonstrating that bsAb15 can efficiently neutralize all single-mAb escape mutants. Furthermore, prophylactic and therapeutic application of bsAb15 reduced the viral titer in infected nonhuman primates and human ACE2 transgenic mice. Therefore, this bsAb is a feasible and effective strategy to treat and prevent severe COVID-19.

The Landscape of Aminoacyl-tRNA Synthetases Involved in Severe Acute Respiratory Syndrome Coronavirus 2 Infection.

Aminoacyl-tRNA synthetases (aaRSs) are essential enzymes in translation by linking amino acids onto their cognate tRNAs during protein synthesis. During evolution, aaRSs develop numerous non-canonical functions that expand the roles of aaRSs in eukaryotic organisms. Although aaRSs have been implicated in viral infection, the function of aaRSs during infections with coronaviruses (CoVs) remains unclear. Here, we analyzed the data from transcriptomic and proteomic database on human cytoplasmic (cyto) and mitochondrial (mt) aaRSs across infections with three highly pathogenic human CoVs, with a particular focus on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We found an overall downregulation of aaRSs at mRNA levels, while the protein levels of some mt-aaRSs and the phosphorylation of certain aaRSs were increased in response to SARS-CoV-2 infection. Strikingly, interaction network between SARS-CoV-2 and human aaRSs displayed a strong involvement of mt-aaRSs. Further co-immunoprecipitation (co-IP) experiments confirmed the physical interaction between SARS-CoV-2 M protein and TARS2. In addition, we identified the intermediate nodes and potential pathways involved in SARS-CoV-2 infection. This study provides an unbiased, overarching perspective on the correlation between aaRSs and SARS-CoV-2. More importantly, this work identifies TARS2, HARS2, and EARS2 as potential key factors involved in COVID-19.

The Landscape of Aminoacyl-tRNA Synthetases Involved in Severe Acute Respiratory Syndrome Coronavirus 2 Infection

Aminoacyl-tRNA synthetases (aaRSs) are essential enzymes in translation by linking amino acids onto their cognate tRNAs during protein synthesis. During evolution, aaRSs develop numerous non-canonical functions that expand the roles of aaRSs in eukaryotic organisms. Although aaRSs have been implicated in viral infection, the function of aaRSs during infections with coronaviruses (CoVs) remains unclear. Here, we analyzed the data from transcriptomic and proteomic database on human cytoplasmic (cyto) and mitochondrial (mt) aaRSs across infections with three highly pathogenic human CoVs, with a particular focus on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We found an overall downregulation of aaRSs at mRNA levels, while the protein levels of some mt-aaRSs and the phosphorylation of certain aaRSs were increased in response to SARS-CoV-2 infection. Strikingly, interaction network between SARS-CoV-2 and human aaRSs displayed a strong involvement of mt-aaRSs. Further co-immunoprecipitation (co-IP) experiments confirmed the physical interaction between SARS-CoV-2 M protein and TARS2. In addition, we identified the intermediate nodes and potential pathways involved in SARS-CoV-2 infection. This study provides an unbiased, overarching perspective on the correlation between aaRSs and SARS-CoV-2. More importantly, this work identifies TARS2, HARS2, and EARS2 as potential key factors involved in COVID-19.

A network meta-analysis of secondary attack rates of COVID-19 in different contact environments.

As the corona virus disease 2019 (COVID-19) pandemic continues around the world, understanding the transmission characteristics of COVID-19 is vital for prevention and control. We conducted the first study aiming to estimate and compare the relative risk of secondary attack rates (SARs) of COVID-19 in different contact environments. Until 26 July 2021, epidemiological studies and cluster epidemic reports of COVID-19 were retrieved from SCI, Embase, PubMed, CNKI, Wanfang and CBM in English and Chinese, respectively. Relative risks (RRs) were estimated in pairwise comparisons of SARs between different contact environments using the frequentist NMA framework, and the ranking of risks in these environments was calculated using the surface under the cumulative ranking curve (SUCRA). Subgroup analysis was performed by regions. Thirty-two studies with 68 260 participants were identified. Compared with meal or gathering, transportation (RR 10.55, 95% confidence interval (CI) 1.43-77.85), medical care (RR 11.68, 95% CI 1.58-86.61) and work or study places (RR 10.15, 95% CI 1.40-73.38) had lower risk ratios for SARs. Overall, the SUCRA rankings from the highest to the lowest were household (95.3%), meal or gathering (81.4%), public places (58.9%), daily conversation (50.1%), transportation (30.8%), medical care (18.2%) and work or study places (15.3%). Household SARs were significantly higher than other environments in the subgroup of mainland China and sensitive analysis without small sample studies (<100). In light of the risks, stratified personal protection and public health measures need to be in place accordingly, so as close contacts categorising and management.

Cytokine/Chemokine Expression Is Closely Associated Disease Severity of Human Adenovirus Infections in Immunocompetent Adults and Predicts Disease Progression.

Increasing human Adenovirus (HAdV) infections complicated with acute respiratory distress syndrome (ARDS) even fatal outcome were reported in immunocompetent adolescent and adult patients. Here, we characterized the cytokine/chemokine expression profiles of immunocompetent patients complicated with ARDS during HAdV infection and identified biomarkers for disease severity/progression. Forty-eight cytokines/chemokines in the plasma samples from 19 HAdV-infected immunocompetent adolescent and adult patients (ten complicated with ARDS) were measured and analyzed in combination with clinical indices. Immunocompetent patients with ARDS caused by severe acute respiratory disease coronavirus (SARS-CoV)-2, 2009 pandemic H1N1 (panH1N1) or bacteria were included for comparative analyses. Similar indices of disease course/progression were found in immunocompetent patients with ARDS caused by HAdV, SARS-CoV-2 or panH1N infections, whereas the HAdV-infected group showed a higher prevalence of viremia, as well as increased levels of aspartate aminotransferase (AST), alanine aminotransferase (ALT) and creatine kinase (CK). Expression levels of 33 cytokines/chemokines were increased significantly in HAdV-infected patients with ARDS compared with that in healthy controls, and many of them were also significantly higher than those in SARS-CoV-2-infected and panH1N1-infected patients. Expression of interferon (IFN)-γ, interleukin (IL)-1ß, hepatocyte growth factor (HGF), monokine induced by IFN-γ (MIG), IL-6, macrophage-colony stimulating factor (M-CSF), IL-10, IL-1α and IL-2Ra was significantly higher in HAdV-infected patients with ARDS than that in those without ARDS, and negatively associated with the ratio of the partial pressure of oxygen in arterial blood/fraction of inspired oxygen (PaO2/FiO2). Analyses of the receiver operating characteristic curve (ROC) showed that expression of IL-10, M-CSF, MIG, HGF, IL-1ß, IFN-γ and IL-2Ra could predict the progression of HAdV infection, with the highest area under the curve (AUC) of 0.944 obtained for IL-10. Of note, the AUC value for the combination of IL-10, IFN-γ, and M-CSF reached 1. In conclusion, the "cytokine storm" occurred during HAdV infection in immunocompetent patients, and expression of IL-10, M-CSF, MIG, HGF, IL-1ß, IFN-γ and IL-2Ra was closely associated with disease severity and could predict disease progression.

New framework for recombination and adaptive evolution analysis with application to the novel coronavirus SARS-CoV-2.

The 2019 novel coronavirus (SARS-CoV-2) has spread rapidly worldwide and was declared a pandemic by the WHO in March 2020. The evolution of SARS-CoV-2, either in its natural reservoir or in the human population, is still unclear, but this knowledge is essential for effective prevention and control. We propose a new framework to systematically identify recombination events, excluding those due to noise and convergent evolution. We found that several recombination events occurred for SARS-CoV-2 before its transfer to humans, including a more recent recombination event in the receptor-binding domain. We also constructed a probabilistic mutation network to explore the diversity and evolution of SARS-CoV-2 after human infection. Clustering results show that the novel coronavirus has diverged into several clusters that cocirculate over time in various regions and that several mutations across the genome are fixed during transmission throughout the human population, including D614G in the S gene and two accompanied mutations in ORF1ab. Together, these findings suggest that SARS-CoV-2 experienced a complicated evolution process in the natural environment and point to its continuous adaptation to humans. The new framework proposed in this study can help our understanding of and response to other emerging pathogens.

Impact of Systematic Factors on the Outbreak Outcomes of the Novel COVID-19 Disease in China: Factor Analysis Study.

BACKGROUND: The novel COVID-19 disease has spread worldwide, resulting in a new pandemic. The Chinese government implemented strong intervention measures in the early stage of the epidemic, including strict travel bans and social distancing policies. Prioritizing the analysis of different contributing factors to outbreak outcomes is important for the precise prevention and control of infectious diseases. We proposed a novel framework for resolving this issue and applied it to data from China. OBJECTIVE: This study aimed to systematically identify national-level and city-level contributing factors to the control of COVID-19 in China. METHODS: Daily COVID-19 case data and related multidimensional data, including travel-related, medical, socioeconomic, environmental, and influenza-like illness factors, from 343 cities in China were collected. A correlation analysis and interpretable machine learning algorithm were used to evaluate the quantitative contribution of factors to new cases and COVID-19 growth rates during the epidemic period (ie, January 17 to February 29, 2020). RESULTS: Many factors correlated with the spread of COVID-19 in China. Travel-related population movement was the main contributing factor for new cases and COVID-19 growth rates in China, and its contributions were as high as 77% and 41%, respectively. There was a clear lag effect for travel-related factors (previous vs current week: new cases, 45% vs 32%; COVID-19 growth rates, 21% vs 20%). Travel from non-Wuhan regions was the single factor with the most significant impact on COVID-19 growth rates (contribution: new cases, 12%; COVID-19 growth rate, 26%), and its contribution could not be ignored. City flow, a measure of outbreak control strength, contributed 16% and 7% to new cases and COVID-19 growth rates, respectively. Socioeconomic factors also played important roles in COVID-19 growth rates in China (contribution, 28%). Other factors, including medical, environmental, and influenza-like illness factors, also contributed to new cases and COVID-19 growth rates in China. Based on our analysis of individual cities, compared to Beijing, population flow from Wuhan and internal flow within Wenzhou were driving factors for increasing the number of new cases in Wenzhou. For Chongqing, the main contributing factor for new cases was population flow from Hubei, beyond Wuhan. The high COVID-19 growth rates in Wenzhou were driven by population-related factors. CONCLUSIONS: Many factors contributed to the COVID-19 outbreak outcomes in China. The differential effects of various factors, including specific city-level factors, emphasize the importance of precise, targeted strategies for controlling the COVID-19 outbreak and future infectious disease outbreaks.