A network pharmacology for predicting the key targets and potential mechanism of Paxlovid in treating COVID-19 (preprint)

Background: Paxlovid has been widely used to treat COVID-19 in global pandemics. The aim of this study is to discover the main targets of SARS-CoV-2 and to explore therapeutic mechanism of Paxlovid. Methods: The targets of Paxlovid were predicted by SwissTargetPrediction. Meanwhile, COVID-19 related targets were collected from GeneCards and OMIM. Then, PPI networks, GO and KEGG enrichment analysis were constructed to discover the potential mechanism by STRING, Cytoscape and DAVID. Finally, AutoDock Vina and Pymol were performed to visualize the interactions between Paxlovid and targets. Results: A total of 22 Paxlovid-related targets of were collected, and 1191 remained therapeutic genes for COVID-19. 23 targets were retained for the further study by PPI network and data integration. The GO and KEGG indicated that 23 targets were significantly enriched to inflammatory response, immune response and so forth. Paxlovid was successfully docked to the active of ALB, CXCL8, HLA-A, IL1B, IL6, KNG1, TNF, VEGFA, CD8A and CTSL. In addition, Paxlovid easily bind with the active pocket of3CLpro and PLpro. Conclusions: Paxlovid could directly target 3CLproand PLpro, and also regulate the immune system. Meanwhile, it may affect the interaction between spike protein RBD and ACE2.

Specific pupylation as IDEntity reporter (SPIDER) for the identification of protein-biomolecule interactions.

Protein-biomolecule interactions play pivotal roles in almost all biological processes. For a biomolecule of interest, the identification of the interacting protein(s) is essential. For this need, although many assays are available, highly robust and reliable methods are always desired. By combining a substrate-based proximity labeling activity from the pupylation pathway of Mycobacterium tuberculosis and the streptavidin (SA)-biotin system, we developed the Specific Pupylation as IDEntity Reporter (SPIDER) method for identifying protein-biomolecule interactions. Using SPIDER, we validated the interactions between the known binding proteins of protein, DNA, RNA, and small molecule. We successfully applied SPIDER to construct the global protein interactome for m6A and mRNA, identified a variety of uncharacterized m6A binding proteins, and validated SRSF7 as a potential m6A reader. We globally identified the binding proteins for lenalidomide and CobB. Moreover, we identified SARS-CoV-2-specific receptors on the cell membrane. Overall, SPIDER is powerful and highly accessible for the study of protein-biomolecule interactions.

[Impacts of Emission and Meteorological Conditions on Air Pollutants at Various Sites Around the COVID-19 Lockdown in Wuhan].

The random forest algorithm was used to separate the mass concentrations of six air pollutants (SO2, NO2, CO, PM10, PM2.5, and O3) contributed by emissions and meteorological conditions. Their variations for five types of sites including Wuhan's central urban, suburb, industrial, the third ring road traffic, and urban background sites were investigated. The results showed that the values of PM2.5/CO, PM10/CO, and NO2/CO during the lockdown period decreased by 10.8-21.7, 9.34-24.7, and 14.4-22.1 times compared with the period before the lockdown, indicating that the contributions of emissions to PM2.5, PM10, and NO2 were reduced. O3/CO increased by 50.1-61.5 times, implying that the secondary formation increased obviously. The contributions of emissions to various types of pollutants all increased after the lockdown. During the lockdown period, affected by the operation of some uninterrupted industrial processes, PM2.5 concentrations in industrial areas dropped the least (20.5%). Compared with the lockdown period, residential activities, transportation, and industrial production were basically restored after the lockdown, resulting in the alleviation of the reduction in PM2.5 emission-related concentrations. The increase in emission-related O3 concentrations could be associated with the decreased NO and PM2.5 concentrations during the lockdown period. The elevated O3 partially offset the improved air quality brought by the reduced NO2and PM2.5 concentrations. After the lockdown, ρ(O3) related with meteorology at the suburban and urban background sites increased by 16.2 µg·m-3 and 16.1 µg·m-3, respectively, which could be attributed to the increased ambient temperature and decreased relative humidity. The decrease in PM2.5 and increase in O3 concentrations caused by reduced traffic and industrial emissions at the third ring road traffic and central urban regions can provide reference for the current coordinated and precise control of PM2.5 and O3 in subregions.

Longitudinal neutralization activities on authentic Omicron variant provided by three doses of BBIBP-CorV vaccination during one year.

The majority of people in China have been immunized with the inactivated viral vaccine BBIBP-CorV. The emergence of the Omicron variant raised the concerns about protection efficacy of the inactivated viral vaccine in China. However, longitudinal neutralization data describing protection efficacy against Omicron variant is still lacking. Here we present one-year longitudinal neutralization data of BBIBP-CorV on authentic Omicron, Delta, and wild-type strains using 224 sera collected from 14 volunteers who have finished three doses BBIBP-CorV. The sera were also subjected for monitoring the SARS-CoV-2 specific IgG, IgA, and IgM responses on protein and peptide microarrays. The neutralization titers showed different protection efficacies against the three strains. By incorporating IgG and IgA signals of proteins and Spike protein derived peptide on microarray, panels as potential surrogate biomarkers for rapid estimation of neutralization titers were established. These data support the necessity of the 3rd dose of BBIBP-CorV vaccination. After further validation and assay development, the panels could be used for reliable, convenient and fast evaluation of the efficacy of vaccination.

Pre-existing anti-HCoV-OC43 immunity influences the durability and cross-reactivity of humoral response to SARS-CoV-2 vaccination.

Purpose: This study was conducted in order to properly understand whether prior seasonal human coronavirus (HCoV) immunity could impact the potential cross-reactivity of humoral responses induced by SARS-CoV-2 vaccine, thereby devising universal coronavirus vaccines for future outbreaks. Methods: We performed enzyme-linked immunosorbent assay (ELISA) to quantify the immunoglobulin G (IgG) antibody levels to spike (S) protein and S1 subunit of HCoVs (HCoV-OC43, HCoV-HKU1, HCoV-NL63, and HCoV-229E), and ELISA [anti-RBD and anti-nucleoprotein (N)], chemiluminescence immunoassay assays (anti-RBD), pseudovirus neutralization test, and authentic viral neutralization test to detect the binding and neutralizing antibodies to SARS-CoV-2 in the vaccinees. Results: We found that the antibody of seasonal HCoVs did exist before vaccination and could be boosted by SARS-CoV-2 vaccine. A further analysis demonstrated that the prior S and S1 IgG antibodies of HCoV-OC43 were positively correlated with anti-RBD and neutralization antibodies to SARS-CoV-2 at 12 and 24 weeks after the second vaccination, and the correlation is more statistically significant at 24 weeks. The persistent antibody levels of SARS-CoV-2 were observed in vaccinees with higher pre-existing HCoV-OC43 antibodies. Conclusion: Our data indicate that inactivated SARS-CoV-2 vaccination may confer cross-protection against seasonal coronaviruses in most individuals, and more importantly, the pre-existing HCoV-OC43 antibody was associated with protective immunity to SARS-CoV-2, supporting the development of a pan-coronavirus vaccine.

Pre-existing anti-HCoV-OC43 immunity influences the durability and cross-reactivity of humoral response to SARS-CoV-2 vaccination

Purpose This study was conducted in order to properly understand whether prior seasonal human coronavirus (HCoV) immunity could impact the potential cross-reactivity of humoral responses induced by SARS-CoV-2 vaccine, thereby devising universal coronavirus vaccines for future outbreaks. Methods We performed enzyme-linked immunosorbent assay (ELISA) to quantify the immunoglobulin G (IgG) antibody levels to spike (S) protein and S1 subunit of HCoVs (HCoV-OC43, HCoV-HKU1, HCoV-NL63, and HCoV-229E), and ELISA [anti-RBD and anti-nucleoprotein (N)], chemiluminescence immunoassay assays (anti-RBD), pseudovirus neutralization test, and authentic viral neutralization test to detect the binding and neutralizing antibodies to SARS-CoV-2 in the vaccinees. Results We found that the antibody of seasonal HCoVs did exist before vaccination and could be boosted by SARS-CoV-2 vaccine. A further analysis demonstrated that the prior S and S1 IgG antibodies of HCoV-OC43 were positively correlated with anti-RBD and neutralization antibodies to SARS-CoV-2 at 12 and 24 weeks after the second vaccination, and the correlation is more statistically significant at 24 weeks. The persistent antibody levels of SARS-CoV-2 were observed in vaccinees with higher pre-existing HCoV-OC43 antibodies. Conclusion Our data indicate that inactivated SARS-CoV-2 vaccination may confer cross-protection against seasonal coronaviruses in most individuals, and more importantly, the pre-existing HCoV-OC43 antibody was associated with protective immunity to SARS-CoV-2, supporting the development of a pan-coronavirus vaccine.

Ultrasensitive monitoring of SARS-CoV-2-specific antibody responses based on a digital approach reveals one week of IgG seroconversion.

COVID-19 is still unfolding, while many people have been vaccinated. In comparison to nucleic acid testing (NAT), antibody-based immunoassays are faster and more convenient. However, its application has been hampered by its lower sensitivity and the existing fact that by traditional immunoassays, the measurable seroconversion time of pathogen-specific antibodies, such as IgM or IgG, lags far behind that of nucleic acids. Herein, by combining the single molecule array platform (Simoa), RBD, and a previously identified SARS-CoV-2 S2 protein derivatized 12-aa peptide (S2-78), we developed and optimized an ultrasensitive assay (UIM-COVID-19 assay). Sera collected from three sources were tested, i.e., convalescents, inactivated virus vaccine-immunized donors and wild-type authentic SARS-CoV-2-infected rhesus monkeys. The sensitivities of UIM-COVID-19 assays are 100-10,000 times higher than those of conventional flow cytometry, which is a relatively sensitive detection method at present. For the established UIM-COVID-19 assay using RBD as a probe, the IgG and IgM seroconversion times after vaccination were 7.5 and 8.6 days vs. 21.4 and 24 days for the flow cytometry assay, respectively. In addition, using S2-78 as a probe, the UIM-COVID-19 assay could differentiate COVID-19 patients (convalescents) from healthy people and patients with other diseases, with AUCs ranging from 0.85-0.95. In summary, the UIM-COVID-19 we developed here is a promising ultrasensitive biodetection strategy that has the potential to be applied for both immunological studies and diagnostics.

SARS-CoV-2 proteome microarray for COVID-19 patient sera profiling.

The immunogenicity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) proteome is largely unknown. Here we describe a protocol for analyzing sera samples with SARS-CoV-2 proteome microarray. The proteins were expressed by either E. coli expression system or eukaryotic cell expression systems and obtained by affinity purification. The protocol includes microarray fabricating and sera profiling, which will be used to build an antibody response landscape for IgG and IgM. The protocol may help to facilitate a deeper understanding of immunity related to SARS-CoV-2. For complete details on the use and execution of this protocol, please refer to Li et al. (2021c).

Anti-SARS-CoV-2 IgG responses are powerful predicting signatures for the outcome of COVID-19 patients.

Introduction: The COVID-19 global pandemic is far from ending. There is an urgent need to identify applicable biomarkers for early predicting the outcome of COVID-19. Growing evidences have revealed that SARS-CoV-2 specific antibodies evolved with disease progression and severity in COIVD-19 patients. Objectives: We assumed that antibodies may serve as biomarkers for predicting the clinical outcome of hospitalized COVID-19 patients on admission. Methods: By taking advantage of a newly developed SARS-CoV-2 proteome microarray, we surveyed IgG responses against 20 proteins of SARS-CoV-2 in 1034 hospitalized COVID-19 patients on admission and followed till 66 days. The microarray results were further correlated with clinical information, laboratory test results and patient outcomes. Cox proportional hazards model was used to explore the association between SARS-CoV-2 specific antibodies and COVID-19 mortality. Results: Nonsurvivors (n = 955) induced higher levels of IgG responses against most of non-structural proteins than survivors (n = 79) on admission. In particular, the magnitude of IgG antibodies against 8 non-structural proteins (NSP1, NSP4, NSP7, NSP8, NSP9, NSP10, RdRp, and NSP14) and 2 accessory proteins (ORF3b and ORF9b) possessed significant predictive power for patient death, even after further adjustments for demographics, comorbidities, and common laboratory biomarkers for disease severity (all with p trend < 0.05). Additionally, IgG responses to all of these 10 non-structural/accessory proteins were also associated with the severity of disease, and differential kinetics and serum positive rate of these IgG responses were confirmed in COVID-19 patients of varying severities within 20 days after symptoms onset. The area under curves (AUCs) for these IgG responses, determined by computational cross-validations, were between 0.62 and 0.71. Conclusions: Our findings might have important implications for improving clinical management of COVID-19 patients.

COVID-ONE-hi: The One-stop Database for COVID-19-specific Humoral Immunity and Clinical Parameters.

Coronavirus disease 2019 (COVID-19), which is caused by SARS-CoV-2, varies with regard to symptoms and mortality rates among populations. Humoral immunity plays critical roles in SARS-CoV-2 infection and recovery from COVID-19. However, differences in immune responses and clinical features among COVID-19 patients remain largely unknown. Here, we report a database for COVID-19-specific IgG/IgM immune responses and clinical parameters (named COVID-ONE-hi). COVID-ONE-hi is based on the data that contain the IgG/IgM responses to 24 full-length/truncated proteins corresponding to 20 of 28 known SARS-CoV-2 proteins and 199 spike protein peptides against 2360 serum samples collected from 783 COVID-19 patients. In addition, 96 clinical parameters for the 2360 serum samples and basic information for the 783 patients are integrated into the database. Furthermore, COVID-ONE-hi provides a dashboard for defining samples and a one-click analysis pipeline for a single group or paired groups. A set of samples of interest is easily defined by adjusting the scale bars of a variety of parameters. After the "START" button is clicked, one can readily obtain a comprehensive analysis report for further interpretation. COVID-ONE-hi is freely available at www.COVID-ONE.cn.

Systematic profiling of SARS-CoV-2-specific IgG responses elicited by an inactivated virus vaccine identifies peptides and proteins for predicting vaccination efficacy.

One of the best ways to control COVID-19 is vaccination. Among the various SARS-CoV-2 vaccines, inactivated virus vaccines have been widely applied in China and many other countries. To understand the underlying protective mechanism of these vaccines, it is necessary to systematically analyze the humoral responses that are triggered. By utilizing a SARS-CoV-2 microarray with 21 proteins and 197 peptides that fully cover the spike protein, antibody response profiles of 59 serum samples collected from 32 volunteers immunized with the inactivated virus vaccine BBIBP-CorV were generated. For this set of samples, the microarray results correlated with the neutralization titers of the authentic virus, and two peptides (S1-5 and S2-22) were identified as potential biomarkers for assessing the effectiveness of vaccination. Moreover, by comparing immunized volunteers to convalescent and hospitalized COVID-19 patients, the N protein, NSP7, and S2-78 were identified as potential biomarkers for differentiating COVID-19 patients from individuals vaccinated with the inactivated SARS-CoV-2 vaccine. The comprehensive profile of humoral responses against the inactivated SARS-CoV-2 vaccine will facilitate a deeper understanding of the vaccine and provide potential biomarkers for inactivated virus vaccine-related applications.

Antibody landscape against SARS-CoV-2 reveals significant differences between non-structural/accessory and structural proteins.

The immunogenicity of the SARS-CoV-2 proteome is largely unknown, especially for non-structural proteins and accessory proteins. In this study, we collect 2,360 COVID-19 sera and 601 control sera. We analyze these sera on a protein microarray with 20 proteins of SARS-CoV-2, building an antibody response landscape for immunoglobulin (Ig)G and IgM. Non-structural proteins and accessory proteins NSP1, NSP7, NSP8, RdRp, ORF3b, and ORF9b elicit prevalent IgG responses. The IgG patterns and dynamics of non-structural/accessory proteins are different from those of the S and N proteins. The IgG responses against these six proteins are associated with disease severity and clinical outcome, and they decline sharply about 20 days after symptom onset. In non-survivors, a sharp decrease of IgG antibodies against S1 and N proteins before death is observed. The global antibody responses to non-structural/accessory proteins revealed here may facilitate a deeper understanding of SARS-CoV-2 immunology.

Nsp2 has the potential to be a drug target revealed by global identification of SARS-CoV-2 Nsp2-interacting proteins.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a global health threat since December 2019, and there is still no highly effective drug to control the pandemic. To facilitate drug target identification for drug development, studies on molecular mechanisms, such as SARS-CoV-2 protein interactions, are urgently needed. In this study, we focused on Nsp2, a non-structural protein with largely unknown function and mechanism. The interactome of Nsp2 was revealed through the combination of affinity purification mass spectrometry (AP-MS) and stable isotope labeling by amino acids in cell culture (SILAC), and 84 proteins of high-confidence were identified. Gene ontology analysis demonstrated that Nsp2-interacting proteins are involved in several biological processes such as endosome transport and translation. Network analysis generated two clusters, including ribosome assembly and vesicular transport. Bio-layer interferometry (BLI) assay confirmed the bindings between Nsp2- and 4-interacting proteins, i.e. STAU2 (Staufen2), HNRNPLL, ATP6V1B2, and RAP1GDS1 (SmgGDS), which were randomly selected from the list of 84 proteins. Our findings provide insights into the Nsp2-host interplay and indicate that Nsp2 may play important roles in SARS-CoV-2 infection and serve as a potential drug target for anti-SARS-CoV-2 drug development.

Psychological Factors Affecting Risk Perception of COVID-19: Evidence from Peru and China.

COVID-19 has spread around the world, causing a global pandemic, and to date is impacting in various ways in both developed and developing countries. We know that the spread of this virus is through people's behavior despite the perceived risks. Risk perception plays an important role in decision-making to prevent infection. Using data from the online survey of participants in Peru and China (N = 1594), data were collected between 8 July 31 and August 2020. We found that levels of risk perception are relatively moderate, but higher in Peru compared to China. In both countries, anxiety, threat perception, self-confidence, and sex were found to be significant predictors of risk perception; however, trust in the information received by government and experts was significant only in Peru, whereas self-confidence had a significant negative effect only for China. Risk communication should be implemented through information programs aimed at reducing anxiety and improving self-confidence, taking into consideration gender differences. In addition, the information generated by the government should be based on empirical sources. Finally, the implications for effective risk communication and its impacts on the health field are discussed.

Antibody dynamics to SARS-CoV-2 in asymptomatic COVID-19 infections.

BACKGROUND: The missing asymptomatic COVID-19 infections have been overlooked because of the imperfect sensitivity of the nucleic acid testing (NAT). Globally understanding the humoral immunity in asymptomatic carriers will provide scientific knowledge for developing serological tests, improving early identification, and implementing more rational control strategies against the pandemic. MEASURE: Utilizing both NAT and commercial kits for serum IgM and IgG antibodies, we extensively screened 11 766 epidemiologically suspected individuals on enrollment and 63 asymptomatic individuals were detected and recruited. Sixty-three healthy individuals and 51 mild patients without any preexisting conditions were set as controls. Serum IgM and IgG profiles were further probed using a SARS-CoV-2 proteome microarray, and neutralizing antibody was detected by a pseudotyped virus neutralization assay system. The dynamics of antibodies were analyzed with exposure time or symptoms onset. RESULTS: A combination test of NAT and serological testing for IgM antibody discovered 55.5% of the total of 63 asymptomatic infections, which significantly raises the detection sensitivity when compared with the NAT alone (19%). Serum proteome microarray analysis demonstrated that asymptomatics mainly produced IgM and IgG antibodies against S1 and N proteins out of 20 proteins of SARS-CoV-2. Different from strong and persistent N-specific antibodies, S1-specific IgM responses, which evolved in asymptomatic individuals as early as the seventh day after exposure, peaked on days from 17 days to 25 days, and then disappeared in two months, might be used as an early diagnostic biomarker. 11.8% (6/51) mild patients and 38.1% (24/63) asymptomatic individuals did not produce neutralizing antibody. In particular, neutralizing antibody in asymptomatics gradually vanished in two months. CONCLUSION: Our findings might have important implications for the definition of asymptomatic COVID-19 infections, diagnosis, serological survey, public health, and immunization strategies.

Linear epitope landscape of the SARS-CoV-2 Spike protein constructed from 1,051 COVID-19 patients.

To fully decipher the immunogenicity of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Spike protein, it is essential to assess which part is highly immunogenic in a systematic way. We generate a linear epitope landscape of the Spike protein by analyzing the serum immunoglobulin G (IgG) response of 1,051 coronavirus disease 2019 (COVID-19) patients with a peptide microarray. We reveal two regions rich in linear epitopes, i.e., C-terminal domain (CTD) and a region close to the S2' cleavage site and fusion peptide. Unexpectedly, we find that the receptor binding domain (RBD) lacks linear epitope. We reveal that the number of responsive peptides is highly variable among patients and correlates with disease severity. Some peptides are moderately associated with severity and clinical outcome. By immunizing mice, we obtain linear-epitope-specific antibodies; however, no significant neutralizing activity against the authentic virus is observed for these antibodies. This landscape will facilitate our understanding of SARS-CoV-2-specific humoral responses and might be useful for vaccine refinement.