Development of receptor binding domain-based double-antigen sandwich lateral flow immunoassay for the detection and evaluation of SARS-CoV-2 neutralizing antibody in clinical sera samples compared with the conventional virus neutralization test.

Vaccination is an effective strategy to fight COVID-19. However, the effectiveness of the vaccine varies among different populations in varying immune effects. Neutralizing antibody (NAb) level is an important indicator to evaluate the protective effect of immune response after vaccination. Lateral flow immunoassay (LFIA) is a rapid, safe and sensitivity detection method, which has great potential in the detection of SARS-CoV-2 NAb. In this study, a fluorescent beads-based lateral flow immunoassay (FBs-LFIA) and a latex beads-based LFIA (LBs-LFIA) using double antigen sandwich (DAS) strategy were established to detect NAbs in the serum of vaccinated people. The limit of detection (LoD) of the FBs-LFIA was 1.13 ng mL- 1 and the LBs-LFIA was 7.11 ng mL- 1. The two LFIAs were no cross-reactive with sera infected by other pathogenic bacteria. Furthermore, the two LFIAs showed a good performance in testing clinical samples. The sensitivity of FBs-LFIA and LBs-LFIA were 97.44% (95%CI: 93.15%-99.18%) and 98.29% (95%CI: 95.84%-99.37%), and the specificity were 98.28% (95%CI: 95.37%-99.45%) and 97.70% (95%CI: 94.82%-99.06%) compared with the conventional virus neutralization test (cVNT), respectively. Notably, the LBs-LFIA was also suitable for whole blood sample, requiring only 3 µL of whole blood, which provided the possibility to detect NAbs at home. To sum up, the two LFIAs based on double antigen sandwich established by us can rapidly, safely, sensitively and accurately detect SARS-CoV-2 NAb in human serum.

T-Cell Repertoire Characteristics of Asymptomatic and Re-Detectable Positive COVID-19 Patients.

The prevention of the COVID-19 pandemic is highly complicated by the prevalence of asymptomatic and recurrent infection. Many previous immunological studies have focused on symptomatic and convalescent patients, while the immune responses in asymptomatic patients and re-detectable positive cases remain unclear. Here we comprehensively analyzed the peripheral T-cell receptor (TCR) repertoire of 54 COVID-19 patients in different courses, including asymptomatic, symptomatic, convalescent, and re-detectable positive cases. We identified a set of V-J gene combinations characterizing the upward immune responses through asymptomatic and symptomatic courses. Furthermore, some of these V-J combinations could be awakened in the re-detectable positive cases, which may help predict the risk of recurrent infection. Therefore, TCR repertoire examination has the potential to strengthen the clinical surveillance and the immunotherapy development for COVID-19.

Differential Antibody Response to Inactivated COVID-19 Vaccines in Healthy Subjects.

The appearance and magnitude of the immune response and the related factors correlated with SARS-CoV-2 vaccination need to be defined. Here, we enrolled a prospective cohort of 52 participants who received two doses of inactivated vaccines (BBIBP-CorV). Their serial plasma samples (n = 260) over 2 months were collected at five timepoints. We measured antibody responses (NAb, S-IgG and S-IgM) and routine blood parameter. NAb seroconversion occurred in 90.7% of vaccinated individuals and four typical NAb kinetic curves were observed. All of the participants who seroconverted after the first dose were females and had relatively high prevaccine estradiol levels. Moreover, those without seroconversion tended to have lower lymphocyte counts and higher serum SAA levels than those who experienced seroconversion. The NAb titers in young vaccine recipients had a significantly higher peak than those in elderly recipients. S-IgG and S-IgM dynamics were accompanied by similar trends in NAb. Here, we gained insight into the dynamic changes in NAbs and preliminarily explored the prevaccine blood parameters related to the kinetic subclasses, providing a reference for vaccination strategies.

Quantitative Detection of Anti-SARS-CoV-2 Antibodies Using Indirect ELISA.

OBJECTIVE: Real-time reverse transcription-polymerase chain reaction is the gold standard for the diagnosis of COVID-19, but it is necessary to utilize other tests to determine the burden of the disease and the spread of the outbreak such as IgG-, IgM-, and IgA-based antibody detection using enzyme-linked immunosorbent assay (ELISA). MATERIALS AND METHODS: We developed an indirect ELISA assay to quantitatively measure the amount of COVID-19 IgG, IgM, and IgA antibodies present in patient serum, dried blood, and plasma. RESULTS: The population cutoff values for positivity were determined by receiver operating characteristic curves to be 1.23 U/mL, 23.09 U/mL, and 6.36 U/mL for IgG, IgM, and IgA, respectively. After albumin subtraction, the specificity remained >98% and the sensitivity was 95.72%, 83.47%, and 82.60%, respectively, for IgG, IgM, and IgA antibodies to the combined spike subunit 1 receptor binding domain and N proteins in serum. Plasma and dried blood spot specimens were also validated on this assay. CONCLUSION: This assay may be used for determining the seroprevalence of SARS-CoV-2 in a population exposed to the virus or in vaccinated individuals.

Transcriptome Analysis of Peripheral Blood Mononuclear Cells Reveals Distinct Immune Response in Asymptomatic and Re-Detectable Positive COVID-19 Patients.

The existence of asymptomatic and re-detectable positive coronavirus disease 2019 (COVID-19) patients presents the disease control challenges of COVID-19. Most studies on immune responses in COVID-19 have focused on moderately or severely symptomatic patients; however, little is known about the immune response in asymptomatic and re-detectable positive (RP) patients. Here we performed a comprehensive analysis of the transcriptomic profiles of peripheral blood mononuclear cells (PBMCs) from 48 COVID-19 patients which included 8 asymptomatic, 13 symptomatic, 15 recovered and 12 RP patients. The weighted gene co-expression network analysis (WGCNA) identified six co-expression modules, of which the turquoise module was positively correlated with the asymptomatic, symptomatic, and recovered COVID-19 patients. The red module positively correlated with symptomatic patients only and the blue and brown modules positively correlated with the RP patients. The analysis by single sample gene set enrichment analysis (ssGSEA) revealed a lower level of IFN response and complement activation in the asymptomatic patients compared with the symptomatic, indicating a weaker immune response of the PBMCs in the asymptomatic patients. In addition, gene set enrichment analysis (GSEA) analysis showed the enrichment of TNFα/NF-κB and influenza infection in the RP patients compared with the recovered patients, indicating a hyper-inflammatory immune response in the PBMC of RP patients. Thus our findings could extend our understanding of host immune response during the progression of COVID-19 disease and assist clinical management and the immunotherapy development for COVID-19.

Comprehensive Profiling of Inflammatory Factors Revealed That Growth Differentiation Factor-15 Is an Indicator of Disease Severity in COVID-19 Patients.

To systematically explore potential biomarkers which can predict disease severity in COVID-19 patients and prevent the occurrence or development of severe COVID-19, the levels of 440 factors were analyzed in patients categorized according to COVID-19 disease severity; including asymptomatic, mild, moderate, severe, convalescent and healthy control groups. Factor candidates were validated by ELISA and functional relevance was uncovered by bioinformatics analysis. To identify potential biomarkers of occurrence or development of COVID-19, patient sera from three different severity groups (moderate, severe, and critical) at three time points (admission, remission, and discharge) and the expression levels of candidate biomarkers were measured. Eleven differential factors associated with disease severity were pinpointed from 440 factors across 111 patients of differing disease severity. The dynamic changes of GDF15 reflect the progression of the disease, while the other differential factors include TRAIL R1, IGFBP-1, IGFBP-4, VCAM-1, sFRP-3, FABP2, Transferrin, GDF15, IL-1F7, IL-5Rα, and CD200. Elevation of white blood cell count, neutrophil count, neutrophil-lymphocyte ratio (NLR), Alanine aminotransferase and Aspartate aminotransferase, low lymphocyte and eosinophil counts in the severe group were associated with the severity of COVID-19. GDF15 levels were observed to be associated with the severity of COVID-19 and the dynamic change of GDF15 levels was closely associated with the COVID-19 disease progression. Therefore, GDF15 might serve as an indicator of disease severity in COVID-19 patients.

Stigma, Discrimination, and Hate Crimes in Chinese-Speaking World amid Covid-19 Pandemic.

The Covid-19 pandemic has given rise to stigma, discrimination, and even hate crimes against various populations in the Chinese language-speaking world. Using interview data with victims, online observation, and the data mining of media reports, this paper investigated the changing targets of stigma from the outbreak of Covid-19 to early April 2020 when China had largely contained the first wave of Covid-19 within its border. We found that at the early stage of the pandemic, stigma was inflicted by some non-Hubei Chinese population onto Wuhan and Hubei residents, by some Hong Kong and Taiwan residents onto mainland Chinese, and by some Westerners towards overseas Chinese. With the number of cases outside China surpassing that in China, stigmatization was imposed by some Chinese onto Africans in China. We further explore how various factors, such as the fear of infection, food and mask culture, political ideology, and racism, affected the stigmatization of different victim groups. This study not only improved our understanding of how stigmatization happened in the Chinese-speaking world amid Covid-19 but also contributes to the literature of how sociopolitical factors may affect the production of hate crimes.

Network pharmacology and molecular docking analysis on molecular targets and mechanisms of Huashi Baidu formula in the treatment of COVID-19.

PURPOSE: Huashi Baidu formula (HSBDF) was developed to treat the patients with severe COVID-19 in China. The purpose of this study was to explore its active compounds and demonstrate its mechanisms against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) through network pharmacology and molecular docking. METHODS: All the components of HSBDF were retrieved from the pharmacology database of TCM system. The genes corresponding to the targets were retrieved using UniProt and GeneCards database. The herb-compound-target network was constructed by Cytoscape. The target protein-protein interaction network was built using STRING database. The core targets of HSBDF were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). The main active compounds of HSBDF were docked with SARS-CoV-2 and angiotensin converting enzyme II (ACE2). RESULTS: Compound-target network mainly contained 178 compounds and 272 corresponding targets. Key targets contained MAPK3, MAPK8, TP53, CASP3, IL6, TNF, MAPK1, CCL2, PTGS2, etc. There were 522 GO items in GO enrichment analysis (p < .05) and 168 signaling pathways (p < .05) in KEGG, mainly including TNF signaling pathway, PI3K-Akt signaling pathway, NOD-like receptor signaling pathway, MAPK signaling pathway, and HIF-1 signaling pathway. The results of molecular docking showed that baicalein and quercetin were the top two compounds of HSBDF, which had high affinity with ACE2. CONCLUSION: Baicalein and quercetin in HSBDF may regulate multiple signaling pathways through ACE2, which might play a therapeutic role on COVID-19.

[Effect of heat inactivation of blood samples on the efficacy of three detection methods of SARS-CoV-2 antibodies].

OBJECTIVE: To evaluate the effects of heat inactivation of blood samples at 56℃ for 30 min on the results of SARS-CoV-2 antibody detection using different methods. METHODS: This retrospective study was conducted in 11 patients with established diagnosis of COVID-19 and 10 patients with diseases other than COVID- 19 in our hospital. We collected samples of serum, plasma and whole blood from each patient between February, 12 and 18, 2020, and with a double- blind design, the samples were examined for SARS-CoV-2 antibodies before and after heat inactivation at 56 ℃ for 30 min. In all the samples, the total SARS-CoV-2 antibodies were detected using immunochromatography, and the IgM antibodies were detected using fluorescence immunochromatography; the IgM and IgG antibodies in the serum and plasma samples detected with chemiluminescence immunoassay. We compared the detection results and analyzed the correlation of semi-quantitative detection results of IgM and IgG antibodies before and after heat inactivation of the samples. RESULTS: With immuno-chromatography, the coincidence rate of the total SARS-CoV-2 antibody detection before and after heat inactivation of the serum and plasma samples was 90.0% in COVID-19 cases and 100.0% in the negative cases, resulting in a total coincidence rate 95.2%; for the whole blood samples, the total coincidence rates of the total SARS-CoV-2 antibodies were 100.0%. For detection of IgM antibodies in the serum, plasma and whole blood samples using fluorescence immunochromatography, the coincidence rates in SARS-CoV-2-positive and negative cases and the total coincidence rate before and after inactivation were 100.0%, 0 and 47.6%, respectively. For detection of serum IgM and IgG antibodies and plasma IgG antibodies with chemiluminescence immunoassay, the coincidence rates in SARS-CoV-2-positive and negative cases and the total coincidence rate before and after inactivation were all 100.0%, and the total coincidence rate of plasma IgM antibodies was 95.2%. Pearson correlation analysis of the semi-quantitative results of IgM and IgG detection in the serum and plasma samples showed a correlation coefficient of 0.9999 (95%CI: 0.9998-1.000, P < 0.001) between the results before and after sample inactivation. CONCLUSIONS: Heat inactivation of blood samples at 56 ℃ for 30 min does not obviously affect the results of immunochromatography and chemiluminescent immunoassay for detection of SARS-COV-2 antibodies but can reduce the risk of infection for the operators. Heat-inactivated samples can not be used in fluorescence immunochromatography for SARS-CoV-2 antibody detection.