Multiplex assays for the identification of serological signatures of SARS-CoV-2 infection: an antibody-based diagnostic and machine learning study

Evaluation of oral health status and immunological parameters of hospitalized COVID-19 patients during acute and recovery phases: A randomized clinical trial

Background/purpose

It is known that COVID-19 patients show many clinical oral symptoms due to the immunological mechanisms triggered by the virus. Aim of this study is to analyze the antibody response to SARS-CoV-2, and to evaluate the oral health status of hospitalized patients.

Materials and methods

160 patients with COVID-19 confirmed by SARS-CoV-2-specific RT-PCR testing and 160 healthy volunteers (HI) with similar age, gender and systemic status were included to compare the bio-chemical and oral manifestations. Oropharyngeal swab specimens were collected to evaluate the salivary interleukins (IL-1, IL-6, IL-10) and immunoglobulins (sIgA, sIgG, sIgM). Oral findings (DMFT, plaque index, salivary flow rate), socio-demographic information and systemic conditions were also recorded. Chi-square, Mann-Whitney U and Spearman's ratio tests were applied to determine the possible correlations between the factors (P = 0.05).

Results

The mean DMFT scores of COVID-19 patients (12.71 ± 7.3) were significantly higher than the HI (7.39 ± 2.8), whereas cases of total or partial edentulism were more common among COVID-19 patients (P < 0.05). While plaque index scores were similar for both groups (P > 0.05), salivary parameters were found statistically different (P < 0.05). Severe and moderate cases showed higher proinflammatory interleukin levels (IL-1 = 68.74 pg/ml, IL-6 = 53.31 pg/ml) amongst all (P < 0.05). While secretory immunoglobulins were almost depleted at baseline, (sIgA = 0.11 mg/ml, sIgG = 0.21 mg/ml, sIgM = 0.08 mg/ml) they reached to threshold levels after 4 weeks.

Conclusion

Higher proinflammatory interleukin levels indicated that traces of ongoing "Cytokine Storm" in COVID-19 patients which can also be observed in oral environment. Poor oral hygiene and malnutrition due to edentulism can pave the way for having a severe COVID-19 infection.

Titers of IgG and IgA against SARS-CoV-2 proteins and their association with symptoms in mild COVID-19 infection

Humoral immunity in COVID-19 includes antibodies (Abs) targeting spike (S) and nucleocapsid (N) SARS-CoV-2 proteins. Antibody levels are known to correlate with disease severity, but titers are poorly reported in mild or asymptomatic cases. Here, we analyzed the titers of IgA and IgG against SARS-CoV-2 proteins in samples from 200 unvaccinated Hospital Workers (HWs) with mild COVID-19 at two time points after infection. We analyzed the relationship between Ab titers and patient characteristics, clinical features, and evolution over time. Significant differences in IgG and IgA titers against N, S1 and S2 proteins were found when samples were segregated according to time T1 after infection, seroprevalence at T1, sex and age of HWs and symptoms at infection. We found that IgM + samples had higher titers of IgG against N antigen and IgA against S1 and S2 antigens than IgM - samples. There were significant correlations between anti-S1 and S2 Abs. Interestingly, IgM + patients with dyspnea had lower titers of IgG and IgA against N, S1 and S2 than those without dyspnea. Comparing T1 and T2, we found that IgA against N, S1 and S2 but only IgG against certain Ag decreased significantly. In conclusion, an association was established between Ab titers and the development of infection symptoms.

A seroprevalence study of SARS-CoV-2 and seasonal coronaviruses after the first SARS-CoV-2 circulation in New Caledonia, Pacific region

Objectives

This study aimed to determine the seroprevalence of immunoglobulin G antibodies targeting SARS-CoV-2 and other human coronaviruses after the first circulation of SARS-CoV-2 in New Caledonia, Pacific region.

Methods

Blood samples were collected to detect the presence of SARS-CoV-2 immunoglobulin G antibodies. The sampling took place between July 2021 and July 2022 but was interrupted after the first circulation of SARS-CoV-2 (September 2021-March 2022) in New Caledonia. Data on ethnicity, age, gender, main residence, and anteriority of COVID-19 and vaccination were collected and analyzed.

Results

A total of 747 participants, representative of New Caledonia's adult population, were included in the study. We found that 81% of the population had antibody responses to SARS-CoV-2 at the end of July 2022. The vaccination rate was 75%, whereas infections had affected 40% of the population. Individuals aged >45 years were significantly more vaccinated than those aged 18-44 years (80%, 95% confidence interval 74-84%). Oceanians were the most infected (50%, 95% confidence interval 42-57%).

Conclusion

In New Caledonia, we show a high immunity rate (81%) after the first waves of SARS-CoV-2 circulation and the vaccination campaign. The analyses showed spatial heterogeneities in the infection rate across the territory and revealed that Oceanians were the most infected. Our study also highlighted high exposure of New Caledonia's population to other human coronaviruses.

Microfluidic Diffusional Sizing (MDS) Measurements of Secretory Neutralizing Antibody Affinity Against SARS-CoV-2

SARS-CoV-2 has rampantly spread around the globe and continues to cause unprecedented loss through ongoing waves of (re)infection. Increasing our understanding of the protection against infection with SARS-CoV-2 is critical to ending the pandemic. Serological assays have been widely used to assess immune responses, but secretory antibodies, the essential first line of defense, have been studied to only a limited extent. Of particular interest and importance are neutralizing antibodies, which block the binding of the spike protein of SARS-CoV-2 to the human receptor angiotensin-converting enzyme-2 (ACE2) and thus are essential for immune defense. Here, we employed Microfluidic Diffusional Sizing (MDS), an immobilization-free technology, to characterize neutralizing antibody affinity to SARS-CoV-2 spike receptor-binding domain (RBD) and spike trimer in saliva. Affinity measurement was obtained through a contrived sample and buffer using recombinant SARS-CoV-2 RBD and monoclonal antibody. Limited saliva samples demonstrated that MDS applies to saliva neutralizing antibody measurement. The ability to disrupt a complex of ACE2-Fc and spike trimer is shown. Using a quantitative assay on the patient sample, we determined the affinity and binding site concentration of the neutralizing antibodies.

The Impact of Artificial Intelligence on Microbial Diagnosis

Traditional microbial diagnostic methods face many obstacles such as sample handling, culture difficulties, misidentification, and delays in determining susceptibility. The advent of artificial intelligence (AI) has markedly transformed microbial diagnostics with rapid and precise analyses. Nonetheless, ethical considerations accompany AI adoption, necessitating measures to uphold patient privacy, mitigate biases, and ensure data integrity. This review examines conventional diagnostic hurdles, stressing the significance of standardized procedures in sample processing. It underscores AI's significant impact, particularly through machine learning (ML), in microbial diagnostics. Recent progressions in AI, particularly ML methodologies, are explored, showcasing their influence on microbial categorization, comprehension of microorganism interactions, and augmentation of microscopy capabilities. This review furnishes a comprehensive evaluation of AI's utility in microbial diagnostics, addressing both advantages and challenges. A few case studies including SARS-CoV-2, malaria, and mycobacteria serve to illustrate AI's potential for swift and precise diagnosis. Utilization of convolutional neural networks (CNNs) in digital pathology, automated bacterial classification, and colony counting further underscores AI's versatility. Additionally, AI improves antimicrobial susceptibility assessment and contributes to disease surveillance, outbreak forecasting, and real-time monitoring. Despite a few limitations, integration of AI in diagnostic microbiology presents robust solutions, user-friendly algorithms, and comprehensive training, promising paradigm-shifting advancements in healthcare.

Validation and Suitability Assessment of Multiplex Mesoscale Discovery Immunogenicity Assay for Establishing Serological Signatures Using Vaccinated, Non-Vaccinated and Breakthrough SARS-CoV-2 Infected Cases

Antibody responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are multi-targeted and variable over time. Multiplex quantitative serological assays are needed to provide accurate and robust seropositivity data for the establishment of serological signatures during vaccination and or infection. We describe here the validation and evaluation of an electro-chemiluminescence (ECL)-based Mesoscale Discovery assay (MSD) for estimation of total and functional IgG relative to SARS-CoV-2 spike, nucleocapsid and receptor binding (RBD) proteins in human serum samples to establish serological signatures of SARS-CoV-2 natural infection and breakthrough cases. The 9-PLEX assay was validated as per ICH, EMA, and US FDA guidelines using a panel of sera samples, including the NIBSC/WHO reference panel (20/268). The assay demonstrated high specificity and selectivity in inhibition assays, wherein the homologous inhibition was more than 85% and heterologous inhibition was below 10%. The assay also met predetermined acceptance criteria for precision (CV < 20%), accuracy (70-130%) and dilutional linearity. The method's applicability to serological signatures was demonstrated using sera samples (n = 45) representing vaccinated, infected and breakthrough cases. The method was able to establish distinct serological signatures and thus provide a potential tool for seroprevalence of SARS-CoV-2 during vaccination or infection.

Harnessing of Artificial Intelligence for the Diagnosis and Prevention of Hospital-Acquired Infections: A Systematic Review

Healthcare-associated infections (HAIs) are the most common adverse events in healthcare and constitute a major global public health concern. Surveillance represents the foundation for the effective prevention and control of HAIs, yet conventional surveillance is costly and labor intensive. Artificial intelligence (AI) and machine learning (ML) have the potential to support the development of HAI surveillance algorithms for the understanding of HAI risk factors, the improvement of patient risk stratification as well as the prediction and timely detection and prevention of infections. AI-supported systems have so far been explored for clinical laboratory testing and imaging diagnosis, antimicrobial resistance profiling, antibiotic discovery and prediction-based clinical decision support tools in terms of HAIs. This review aims to provide a comprehensive summary of the current literature on AI applications in the field of HAIs and discuss the future potentials of this emerging technology in infection practice. Following the PRISMA guidelines, this study examined the articles in databases including PubMed and Scopus until November 2023, which were screened based on the inclusion and exclusion criteria, resulting in 162 included articles. By elucidating the advancements in the field, we aim to highlight the potential applications of AI in the field, report related issues and shortcomings and discuss the future directions.

SARS-CoV-2 seroprevalence and associated factors of infection before and after the Delta wave in French Polynesia: a cross-sectional study

BACKGROUND

French Polynesia (FP) comprises 75 inhabited islands scattered across five archipelagos. Between July and October 2021, the SARS-CoV-2 Delta variant triggered a much stronger second epidemic wave in FP than the original Wuhan strain, which was dominant from August 2020 to March 2021. Although previous seroprevalence surveys made it possible to determine the proportion of the population infected by SARS-CoV-2 on the two most populated islands (Tahiti and Moorea) after the first (20.6% in Tahiti and 9.4% in Moorea) and second (57.7% in Tahiti) epidemic waves, no data are available for more remote islands. We used blood samples and personal data collected before, during, and after the second wave from inhabitants of several islands within the five archipelagos to assess the prevalence of SARS-CoV-2 infections and identify associated factors.

METHODS

Blood samples and personal data were collected between April and December 2021 as part of the MATAEA study, a cross-sectional survey conducted on a random sample of the adult population representative of the five FP archipelagos and stratified by age and gender. IgG antibodies targeting the SARS-CoV-2 nucleocapsid (N) protein were detected using a recombinant antigen-based microsphere immunoassay. Factors associated with anti-SARS-CoV-2-N seropositivity were identified using logistic regression models.

RESULTS

Of 1,120 participants, 503 (44.9%) tested positive for anti-SARS-CoV-2-N antibodies, corresponding to a weighted prevalence of 56.8% for the FP population aged 18-69 years. The seroprevalence increased from 21.9% to 62.1% before and during/after the Delta wave. Of these infections, only 28.4% had been diagnosed by health professionals. The odds of being seropositive were lower in males, participants recruited before the Delta wave, those who had never been married, those with a diagnosed respiratory allergy, smokers, and those vaccinated against COVID-19.

CONCLUSIONS

Our results confirm the high impact of the Delta wave in FP. By the end of 2021, 56.8% of the FP population aged 18-69 years had been infected by SARS-CoV-2; the majority of these infections went undetected. Individuals with respiratory allergies were found to be less susceptible to SARS-CoV-2 infection.

A bead-based multiplex assay covering all coronaviruses pathogenic for humans for sensitive and specific surveillance of SARS-CoV-2 humoral immunity

Serological assays measuring antibodies against SARS-CoV-2 are key to describe the epidemiology, pathobiology or induction of immunity after infection or vaccination. Of those, multiplex assays targeting multiple antigens are especially helpful as closely related coronaviruses or other antigens can be analysed simultaneously from small sample volumes, hereby shedding light on patterns in the immune response that would otherwise remain undetected. We established a bead-based 17-plex assay detecting antibodies targeting antigens from all coronaviruses pathogenic for humans: SARS-CoV-2, SARS-CoV, MERS-CoV, HCoV strains 229E, OC43, HKU1, and NL63. The assay was validated against five commercial serological immunoassays, a commercial surrogate virus neutralisation test, and a virus neutralisation assay, all targeting SARS-CoV-2. It was found to be highly versatile as shown by antibody detection from both serum and dried blot spots and as shown in three case studies. First, we followed seroconversion for all four endemic HCoV strains and SARS-CoV-2 in an outbreak study in day-care centres for children. Second, we were able to link a more severe clinical course to a stronger IgG response with this 17-plex-assay, which was IgG1 and IgG3 dominated. Finally, our assay was able to discriminate recent from previous SARS-CoV-2 infections by calculating the IgG/IgM ratio on the N antigen targeting antibodies. In conclusion, due to the comprehensive method comparison, thorough validation, and the proven versatility, our multiplex assay is a valuable tool for studies on coronavirus serology.

Raman-Based Techniques in Medical Applications for Diagnostic Tasks: A Review

Raman spectroscopy is a widely developing approach for noninvasive analysis that can provide information on chemical composition and molecular structure. High chemical specificity calls for developing different medical diagnostic applications based on Raman spectroscopy. This review focuses on the Raman-based techniques used in medical diagnostics and provides an overview of such techniques, possible areas of their application, and current limitations. We have reviewed recent studies proposing conventional Raman spectroscopy and surface-enhanced Raman spectroscopy for rapid measuring of specific biomarkers of such diseases as cardiovascular disease, cancer, neurogenerative disease, and coronavirus disease (COVID-19). As a result, we have discovered several most promising Raman-based applications to identify affected persons by detecting some significant spectral features. We have analyzed these approaches in terms of their potentially diagnostic power and highlighted the remaining challenges and limitations preventing their translation into clinical settings.

Performance evaluation of in-house developed Covid-19 IgG/IgM antibody rapid diagnostic kit

In the interest of preventing the Coronavirus Disease 2019 (COVID-19) pandemic from spreading, it is crucial to promptly identify and confine afflicted patients. Serological antibody testing is a significant diagnostic technique that is increasingly employed in clinics, however its clinical use is still being investigated. The present study was carried out to scrutinize how well Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) antibody testing using in-house developed rapid antibody assay worked against the chemiluminescence (CLIA) assay. Either IgG positive (IgG + IgM-) or IgM positive (IgM + IgG-); both IgG and IgM positive (IgM + IgG+); and negatives (IgM- IgG-) have been evaluated. A total of 300 samples with diverse age and sexual identity data were included. The combined sensitivities for IgG + IgM+, IgM + IgG-, IgG + IgM- and IgG-IgM- were evaluated. More accurate diagnostic results may be obtained using molecular diagnostic tools. The Antibody Rapid Diagnostic kit's (in-house developed) performance was satisfactory for determining the presence of Covid-19 infection with IgG and IgM positivity. The IgG and IgM positivity helped evaluate the immune response in the individual for the COVID-19 infection. These results lend support to the additional utilisation of serological antibody tests in the COVID-19 diagnosis.

Analytical approaches for antimalarial antibody responses to confirm historical and recent malaria transmission: an example from the Philippines

Background

Assessing the status of malaria transmission in endemic areas becomes increasingly challenging as countries approach elimination. Serology can provide robust estimates of malaria transmission intensities, and multiplex serological assays allow for simultaneous assessment of markers of recent and historical malaria exposure.

Methods

Here, we evaluated different statistical and machine learning methods for analyzing multiplex malaria-specific antibody response data to classify recent and historical exposure to Plasmodium falciparum and Plasmodium vivax. To assess these methods, we utilized samples from a health-facility based survey (n = 9132) in the Philippines, where we quantified antibody responses against 8 P. falciparum and 6 P. vivax-specific antigens from 3 sites with varying transmission intensity.

Findings

Measurements of antibody responses and seroprevalence were consistent with the 3 sites' known endemicity status. Among the models tested, a machine learning (ML) approach (Random Forest model) using 4 serological markers (PfGLURP R2, Etramp5.Ag1, GEXP18, and PfMSP119) gave better predictions for P. falciparum recent infection in Palawan (AUC: 0.9591, CI 0.9497-0.9684) than individual antigen seropositivity. Although the ML approach did not improve P. vivax infection predictions, ML classifications confirmed the absence of recent exposure to P. falciparum and P. vivax in both Occidental Mindoro and Bataan. For predicting historical P. falciparum and P. vivax transmission, seroprevalence and seroconversion rates based on cumulative exposure markers AMA1 and MSP119 showed reliable trends in the 3 sites.

Interpretation

Our study emphasizes the utility of serological markers in predicting recent and historical exposure in a sub-national elimination setting, and also highlights the potential use of machine learning models using multiplex antibody responses to improve assessment of the malaria transmission status of countries aiming for elimination. This work also provides baseline antibody data for monitoring risk in malaria-endemic areas in the Philippines.

Funding

Newton Fund, Philippine Council for Health Research and Development, UK Medical Research Council.

Seroepidemiology of the Seasonal Human Coronaviruses NL63, 229E, OC43 and HKU1 in France

Background

The seasonal human coronaviruses (HCoV) NL63, 229E, OC43, and HKU1 are globally endemic, yet the majority of HCoV infections remain undiagnosed.

Methods

In a cross-sectional study, 2389 serum samples were collected from children and adults in France in 2020. In a longitudinal cohort study, 2520 samples were collected from 898 French individuals followed up between 2020 and 2021. Antibodies to HCoVs were measured using a bead-based multiplex assay.

Results

The rate of waning of anti-HCoV spike immunoglobulin G antibodies was estimated as 0.22-0.47 year^-1 for children, and 0.13-0.27 year^-1 for adults. Seroreversion was estimated as 0.31-1.37 year^-1 in children and 0.19-0.72 year^-1 in adults. The estimated seroconversion rate in children was consistent with 20%-39% of children being infected every year with each HCoV.

Conclusions

The high force of infection in children indicates that HCoVs may be responsible for a substantial proportion of fever episodes experienced by children.

Estimated protection against COVID-19 based on predicted neutralisation titres from multiple antibody measurements in a longitudinal cohort, France, April 2020 to November 2021

BackgroundThe risk of SARS-CoV-2 (re-)infection remains present given waning of vaccine-induced and infection-acquired immunity, and ongoing circulation of new variants.AimTo develop a method that predicts virus neutralisation and disease protection based on variant-specific antibody measurements to SARS-CoV-2 antigens.MethodsTo correlate antibody and neutralisation titres, we collected 304 serum samples from individuals with either vaccine-induced or infection-acquired SARS-CoV-2 immunity. Using the association between antibody and neutralisation titres, we developed a prediction model for SARS-CoV-2-specific neutralisation titres. From predicted neutralising titres, we inferred protection estimates to symptomatic and severe COVID-19 using previously described relationships between neutralisation titres and protection estimates. We estimated population immunity in a French longitudinal cohort of 905 individuals followed from April 2020 to November 2021.ResultsWe demonstrated a strong correlation between anti-SARS-CoV-2 antibodies measured using a low cost high-throughput assay and antibody response capacity to neutralise live virus. Participants with a single vaccination or immunity caused by infection were especially vulnerable to symptomatic or severe COVID-19. While the median reduced risk of COVID-19 from Delta variant infection in participants with three vaccinations was 96% (IQR: 94-98), median reduced risk among participants with infection-acquired immunity was only 42% (IQR: 22-66).ConclusionOur results are consistent with data from vaccine effectiveness studies, indicating the robustness of our approach. Our multiplex serological assay can be readily adapted to study new variants and provides a framework for development of an assay that would include protection estimates.

Antiviral activities of sotrovimab against BQ.1.1 and XBB.1.5 in sera of treated patients

Background

Monoclonal antibodies (mAbs) targeting the spike of SARS-CoV-2 prevent severe COVID-19. Omicron subvariants BQ.1.1 and XBB.1.5 evade neutralization of therapeutic mAbs, leading to recommendations against their use. Yet, the antiviral activities of mAbs in treated patients remain ill-defined.

Methods

We investigated neutralization and antibody-dependent cellular cytotoxicity (ADCC) of D614G, BQ.1.1 and XBB.1.5 in 320 sera from 80 immunocompromised patients with mild-to-moderate COVID-19 prospectively treated with mAbs (sotrovimab, n=29; imdevimab/casirivimab, n=34; cilgavimab/tixagevimab, n=4) or anti-protease (nirmatrelvir/ritonavir, n=13). We measured live-virus neutralization titers and quantified ADCC with a reporter assay.

Findings

Only Sotrovimab elicits serum neutralization and ADCC against BQ.1.1 and XBB.1.5. As compared to D614G, sotrovimab neutralization titers of BQ.1.1 and XBB.1.5 are reduced (71- and 58-fold, respectively), but ADCC levels are only slightly decreased (1.4- and 1-fold, for BQ.1.1 and XBB.1.5, respectively).

Interpretation

Our results show that sotrovimab is active against BQ.1.1 and XBB.1.5 in treated individuals, suggesting that it may be a valuable therapeutic option.

Dynamic antibody response in SARS-CoV-2 infected patients and COVID-19 vaccine recipients alongside vaccine effectiveness in comorbid and multimorbid groups

Objectives

Underlying medical conditions are critical risk factors for COVID-19 susceptibility and its rapid clinical manifestation. Therefore, the preexisting burden of non-communicable diseases (NCDs) makes the preparedness for COVID-19 more challenging for low- and middle-income countries (LMICs). These countries have relied on vaccination campaigns as an effective measure to tackle COVID-19. In this study, we investigated the impact of comorbidities on humoral antibody responses against the specific receptor-binding domain (RBD) of SARS-CoV2.

Methods

A total of 1005 patients were selected for the SARS-CoV-2 specific immunoglobulin G (IgG1, IgG2, IgG3, and IgG4 subclasses) and total antibody (TAb) tests (IgG and IgM), of which 912 serum samples were ultimately selected based on the specimen cutoff analyte value. Patients with multimorbidity (N = 60) were recruited for follow-up studies from the initial cohort, and their immune response (IgG and TAb) was measured at multiple time points after the second dose of vaccination. Siemens Dimension Vista SARS-CoV-2 IgG (CV2G) and SARS-CoV-2 TAb assay (CV2T) were used to carry out the serology test.

Results

Out of a total of 912 participants, vaccinated individuals (N = 711) had detectable antibody responses up to 7-8 months. The synergistic effect of natural infection and vaccine response was also studied. Participants with breakthrough infections (N = 49) mounted a greater antibody response compared to individuals with normal vaccination response (N = 397) and those who were naturally infected before receiving the second dose of vaccine (N = 132). Investigation of the impact of comorbidities revealed that diabetes mellitus (DM) (N = 117) and kidney disease (N = 50) had a significant negative impact on the decline of the humoral antibody response against SARS-CoV-2. IgG and TAb declined more rapidly in diabetic and kidney disease patients compared to the other four comorbid groups. Follow-up studies demonstrated that antibody response rapidly declined within 4 months after receiving the second dose.

Conclusion

The generalized immunization schedule for COVID-19 needs to be adjusted for high-risk comorbid groups, and a booster dose must be administered early within 4 months after receiving the second dose.

Development, Validation, and Utilization of a Luminex-Based SARS-CoV-2 Multiplex Serology Assay

SARS-CoV-2 antibody testing is important for seroprevalence studies and for evaluating vaccine immune responses. We developed and validated a Luminex bead-based multiplex serology assay for measuring IgG levels of anti-SARS-CoV-2 antibodies against full-length spike (S), nucleocapsid (N), and receptor-binding domains (RBDs) of wild-type, RBD N501Y mutant, RBD E484K mutant, RBD triple mutant SARS-CoV-2 proteins, Sars-CoV-1, MERS-CoV, and common human coronaviruses, including SARS-CoV-2, OC43, 229E, HKU1, and NL63. Assay cutoff values, sensitivity, and specificity were determined using samples from 160 negative controls and 60 PCR-confirmed, SARS-CoV-2-infected individuals. The assay demonstrated sensitivities of 98.3%, 95%, and 100% and specificities of 100%, 99.4%, and 98.8% for anti-(S), -N, and -RBD, respectively. Results are expressed as IgG antibody concentrations in BAU/mL, using the WHO international standard (NIBSC code 20/136) for anti-SARS-CoV-2 IgG antibodies. When the multiplex assay was performed and compared with singleplex assays, the IgG antibody measurement geometric mean ratios were between 0.895 and 1.122, and no evidence of interference was observed between antigens. Lower and upper IgG concentration limits, based on accuracy (between 80% and 120%), precision (percent relative standard deviation, ≤25%), and sample dilutional linearity (between 75% and 125%), were used to establish the assay range. Precision was established by evaluating 24 individual human serum samples obtained from vaccinated and SARS-CoV-2-infected individuals. The assay provided reproducible, consistent results with typical coefficients of variation of ≤20% for all assays, irrespective of the run, day, or analyst. Results indicate the assay has high sensitivity and specificity and thus is appropriate for use in measuring SARS-CoV-2 IgG antibodies in infected and vaccinated individuals. IMPORTANCE The SARS-CoV-2 pandemic resulted in the development and validation of multiple serology tests with variable performance. While there are multiple SARS-CoV-2 serology tests to detect SARS-CoV-2 antibodies, the focus is usually either on only one antigen at a time or multiple proteins from only one SARS-CoV-2 variant. These tests usually do not evaluate antibodies against viral proteins from different SARS-CoV-2 variants or from other coronaviruses. Here, we evaluated a multiplex serology test based on Luminex technology, where antibodies against multiple domains of SARS-CoV-2 wild type, SARS-CoV-2 mutants, and common coronavirus antibodies are detected simultaneously in a single assay. This Luminex-based multiplex serology assay can enhance our understanding of the immune response to SARS-CoV-2 infection and vaccination.

Evaluation and deployment of isotype-specific salivary antibody assays for detecting previous SARS-CoV-2 infection in children and adults

BACKGROUND

Saliva is easily obtainable non-invasively and potentially suitable for detecting both current and previous SARS-CoV-2 infection, but there is limited evidence on the utility of salivary antibody testing for community surveillance.

METHODS

We established 6 ELISAs detecting IgA and IgG antibodies to whole SARS-CoV-2 spike protein, to its receptor binding domain region and to nucleocapsid protein in saliva. We evaluated diagnostic performance, and using paired saliva and serum samples, correlated mucosal and systemic antibody responses. The best-performing assays were field-tested in 20 household outbreaks.

RESULTS

We demonstrate in test accuracy (N = 320), spike IgG (ROC AUC: 95.0%, 92.8-97.3%) and spike IgA (ROC AUC: 89.9%, 86.5-93.2%) assays to discriminate best between pre-pandemic and post COVID-19 saliva samples. Specificity was 100% in younger age groups (0-19 years) for spike IgA and IgG. However, sensitivity was low for the best-performing assay (spike IgG: 50.6%, 39.8-61.4%). Using machine learning, diagnostic performance was improved when a combination of tests was used. As expected, salivary IgA was poorly correlated with serum, indicating an oral mucosal response whereas salivary IgG responses were predictive of those in serum. When deployed to household outbreaks, antibody responses were heterogeneous but remained a reliable indicator of recent infection. Intriguingly, unvaccinated children without confirmed infection showed evidence of exposure almost exclusively through specific IgA responses.

CONCLUSIONS

Through robust standardisation, evaluation and field-testing, this work provides a platform for further studies investigating SARS-CoV-2 transmission and mucosal immunity with the potential for expanding salivo-surveillance to other respiratory infections in hard-to-reach settings.

The race to understand immunopathology in COVID-19: Perspectives on the impact of quantitative approaches to understand within-host interactions

The COVID-19 pandemic has revealed the need for the increased integration of modelling and data analysis to public health, experimental, and clinical studies. Throughout the first two years of the pandemic, there has been a concerted effort to improve our understanding of the within-host immune response to the SARS-CoV-2 virus to provide better predictions of COVID-19 severity, treatment and vaccine development questions, and insights into viral evolution and the impacts of variants on immunopathology. Here we provide perspectives on what has been accomplished using quantitative methods, including predictive modelling, population genetics, machine learning, and dimensionality reduction techniques, in the first 26 months of the COVID-19 pandemic approaches, and where we go from here to improve our responses to this and future pandemics.

Analysis of Antibodies Induced after SARS-CoV-2 Vaccination Using Antigen Coded Bead Array Luminex Technology

Objectives. Since the outbreak of SARS-CoV-2 in late 2019, nearly 12.2 billion doses of the COVID-19 vaccine have been administered worldwide; however, the humoral immune responses induced by different types of vaccines are yet to be fully validated. Methods. We analyzed antibody levels in 100 serum samples after vaccination with different types of COVID-19 vaccines and their reactivity against the RBD antigen of Delta and Omicron variants using a bead-based microarray. Results. Elevated levels of anti-wild-type (WT)-RBD IgG and anti-WT-NP IgG were detected in participants who received two doses of the inactivated vaccines (CoronaVac or BBIBP-CorV) and three doses of the recombinant spike protein vaccine (ZF2001), indicating that antibody responses to SARS-CoV-2 were generated regardless of the vaccine administered. We found highly correlated levels of serum anti-RBD IgG and anti-NP IgG (r = 0.432, p < 0.001). We observed that the antibodies produced in vivo after COVID-19 vaccination still reacted with variants of SARS-CoV-2 (p < 0.0001). Conclusions. Our results show that high levels of specific antibodies can be produced after completion of COVID-19 vaccination (two doses of the inactivated vaccines or three doses of ZF2001), with some degree of cross-reactivity to the RBD antigen of Delta and Omicron variants, and provide an accessible and practical experimental method for post-vaccination antibody detection.

Governing AI during a pandemic crisis: Initiatives at the EU level

After the outbreak of Covid-19, the European Commission (EC) promptly took the initiative to lead and coordinate a common European response. The actions unfolded in several directions, paving the way to the uptake of AI-related solutions and placing hope in these tools to face crises, namely of a public health and global nature. In this article, we focus on initiatives for the uptake of AI-related solutions from the experimental level towards implementation. The Repository of AI and Robotics solutions, launched in 2020, is an example of an initiative put forth to leverage and disseminate knowledge on AI, expanding the fields of application and fostering the development and adaptation of cutting-edge technologies to explore how they can assist in tackling specific tasks during a public health crisis. Using this database, the article outlines the promise of AI as a hope for handling specific needs and tasks and how the uptake of such technologies was accelerated during the Covid-19 pandemic. In extension, we frame initiatives for the uptake of AI-enabled solutions from a governance perspective, focusing on the establishment of frameworks for ethical and trustworthy AI by defining principles and standards that aim to protect the underlying values deemed fundamental.

Comparison of one single-antigen assay and three multi-antigen SARS-CoV-2 IgG assays in Nigeria

Objectives

Determining an accurate estimate of SARS-CoV-2 seroprevalence has been challenging in African countries where malaria and other pathogens are endemic. We compared the performance of one single-antigen assay and three multi-antigen SARS-CoV-2 IgG assays in a Nigerian population endemic for malaria.

Methods

De-identified plasma specimens from SARS-CoV-2 RT-PCR positive, dried blood spot (DBS) SARS-CoV-2 RT-PCR positive, and pre-pandemic negatives were used to evaluate the performance of the four SARS-CoV-2 assays (Tetracore, SARS2MBA, RightSign, xMAP).

Results

Results showed higher sensitivity with the multi-antigen (81% (Tetracore), 96% (SARS2MBA), 85% (xMAP)) versus the single-antigen (RightSign (64%)) SARS-CoV-2 assay. The overall specificities were 98% (Tetracore), 100% (SARS2MBA and RightSign), and 99% (xMAP). When stratified based on <15 days to ≥15 days post-RT-PCR confirmation, the sensitivities increased from 75% to 88.2% for Tetracore; from 93% to 100% for the SARS2MBA; from 58% to 73% for RightSign; and from 83% to 88% for xMAP. With DBS, there was no positive increase after 15-28 days for the three assays (Tetracore, SARS2MBA, and xMAP).

Conclusion

Multi-antigen assays performed well in Nigeria, even with samples with known malaria reactivity, and might provide more accurate measures of COVID-19 seroprevalence and vaccine efficacy.

In Silico Identification of Anti-SARS-CoV-2 Medicinal Plants Using Cheminformatics and Machine Learning

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative pathogen of COVID-19, is spreading rapidly and has caused hundreds of millions of infections and millions of deaths worldwide. Due to the lack of specific vaccines and effective treatments for COVID-19, there is an urgent need to identify effective drugs. Traditional Chinese medicine (TCM) is a valuable resource for identifying novel anti-SARS-CoV-2 drugs based on the important contribution of TCM and its potential benefits in COVID-19 treatment. Herein, we aimed to discover novel anti-SARS-CoV-2 compounds and medicinal plants from TCM by establishing a prediction method of anti-SARS-CoV-2 activity using machine learning methods. We first constructed a benchmark dataset from anti-SARS-CoV-2 bioactivity data collected from the ChEMBL database. Then, we established random forest (RF) and support vector machine (SVM) models that both achieved satisfactory predictive performance with AUC values of 0.90. By using this method, a total of 1011 active anti-SARS-CoV-2 compounds were predicted from the TCMSP database. Among these compounds, six compounds with highly potent activity were confirmed in the anti-SARS-CoV-2 experiments. The molecular fingerprint similarity analysis revealed that only 24 of the 1011 compounds have high similarity to the FDA-approved antiviral drugs, indicating that most of the compounds were structurally novel. Based on the predicted anti-SARS-CoV-2 compounds, we identified 74 anti-SARS-CoV-2 medicinal plants through enrichment analysis. The 74 plants are widely distributed in 68 genera and 43 families, 14 of which belong to antipyretic detoxicate plants. In summary, this study provided several medicinal plants with potential anti-SARS-CoV-2 activity, which offer an attractive starting point and a broader scope to mine for potentially novel anti-SARS-CoV-2 drugs.

Supervised Machine Learning Models to Identify Early-Stage Symptoms of SARS-CoV-2

The coronavirus disease (COVID-19) pandemic was caused by the SARS-CoV-2 virus and began in December 2019. The virus was first reported in the Wuhan region of China. It is a new strain of coronavirus that until then had not been isolated in humans. In severe cases, pneumonia, acute respiratory distress syndrome, multiple organ failure or even death may occur. Now, the existence of vaccines, antiviral drugs and the appropriate treatment are allies in the confrontation of the disease. In the present research work, we utilized supervised Machine Learning (ML) models to determine early-stage symptoms of SARS-CoV-2 occurrence. For this purpose, we experimented with several ML models, and the results showed that the ensemble model, namely Stacking, outperformed the others, achieving an Accuracy, Precision, Recall and F-Measure equal to 90.9% and an Area Under Curve (AUC) of 96.4%.

Identifying Recent Cholera Infections Using a Multiplex Bead Serological Assay

Estimates of incidence based on medically attended cholera can be severely biased. Vibrio cholerae O1 leaves a lasting antibody signal and recent advances showed that these can be used to estimate infection incidence rates from cross-sectional serologic data. Current laboratory methods are resource intensive and challenging to standardize across laboratories. A multiplex bead assay (MBA) could efficiently expand the breadth of measured antibody responses and improve seroincidence accuracy. We tested 305 serum samples from confirmed cholera cases (4 to 1083 d postinfection) and uninfected contacts in Bangladesh using an MBA (IgG/IgA/IgM for 7 Vibrio cholerae O1-specific antigens) as well as traditional vibriocidal and enzyme-linked immunosorbent assays (2 antigens, IgG, and IgA). While postinfection vibriocidal responses were larger than other markers, several MBA-measured antibodies demonstrated robust responses with similar half-lives. Random forest models combining all MBA antibody measures allowed for accurate identification of recent cholera infections (e.g., past 200 days) including a cross-validated area under the curve (cvAUC200) of 92%, with simpler 3 IgG antibody models having similar accuracy. Across infection windows between 45 and 300 days, the accuracy of models trained on MBA measurements was non-inferior to models based on traditional assays. Our results illustrated a scalable cholera serosurveillance tool that can be incorporated into multipathogen serosurveillance platforms. IMPORTANCE Reliable estimates of cholera incidence are challenged by poor clinical surveillance and health-seeking behavior biases. We showed that cross-sectional serologic profiles measured with a high-throughput multiplex bead assay can lead to accurate identification of those infected with pandemic Vibrio cholerae O1, thus allowing for estimates of seroincidence. This provides a new avenue for understanding the epidemiology of cholera, identifying priority areas for cholera prevention/control investments, and tracking progress in the global fight against this ancient disease.

Combined monitoring of IgG and IgA anti-Spike and anti-Receptor binding domain long term responses following BNT162b2 mRNA vaccination in Greek healthcare workers

Studies on the humoral response to homologous BNT162b2 mRNA-vaccination focus mainly on IgG antibody dynamics, while long-term IgA kinetics are understudied. Herein, kinetics of IgG and IgA levels against trimeric-Spike (S) and Receptor-Binding-Domain (RBD) were evaluated by in-house ELISAs in 146 two-dose vaccinated Greek healthcare workers (HCWs) in a 9-month period at six time points (up to 270 days after the first dose). The effect of a homologous booster third dose was also studied and evaluated. The peak of immune response was observed 21 days after the second dose; 100% seroconversion rate for anti-S and anti-RBD IgG, and 99.7% and 96.3% respectively for IgA. IgG antibody levels displayed higher increase compared to IgA. Declining but persistent anti-SARS-CoV-2 antibody levels were detected 9 months after vaccination; IgG and IgA anti-S levels approached those after the first dose, while a more rapid reduction rate for anti-RBD antibodies led to significantly lower levels for both classes, supporting the need for a booster dose. Indeed, a homologous booster third dose resulted in enhanced levels of anti-S of both classes, whereas anti-RBD didn't exceed the peak levels after the second dose. Previous SARS-CoV-2 infection, flu vaccination, BMI<35 and the occurrence of an adverse event upon vaccination, were associated with higher IgG antibody levels over time, which however were negatively affected by age increase and the presence of chronic diseases. Overall, after concurrently using the S and RBD target-antigens in in-house ELISAs, we report in addition to IgG, long-term persistence of IgA antibodies. Regarding antibody levels, homologous mRNA vaccination gives rise to an effective anti-viral protection up to 9 months negatively correlated to age. Considering that COVID-19 is still a matter of public concern, booster vaccine doses remain critical to vulnerable individuals.

Performance and validation of an adaptable multiplex assay for detection of serologic response to SARS-CoV-2 infection or vaccination

Measurement of quantitative antibody responses are increasingly important in evaluating the immune response to infection and vaccination. In this study we describe the validation of a quantitative, multiplex serologic assay utilising an electrochemiluminescence platform, which measures IgG against the receptor binding domain (RBD), spike S1 and S2 subunits and nucleocapsid antigens of SARS-CoV-2. The assay displayed a sensitivity ranging from 73 to 91% and specificity from 90 to 96% in detecting previous infection with SARS-CoV-2 depending on antigenic target and time since infection, and this assay highly correlated with commercially available assays. The within-plate coefficient of variation ranged from 3.8-3.9% and the inter-plate coefficient of variation from 11 to 13% for each antigen.

Building an integrated serosurveillance platform to inform public health interventions: Insights from an experts' meeting on serum biomarkers

The use of biomarkers to measure immune responses in serum is crucial for understanding population-level exposure and susceptibility to human pathogens. Advances in sample collection, multiplex testing, and computational modeling are transforming serosurveillance into a powerful tool for public health program design and response to infectious threats. In July 2018, 70 scientists from 16 countries met to perform a landscape analysis of approaches that support an integrated serosurveillance platform, including the consideration of issues for successful implementation. Here, we summarize the group's insights and proposed roadmap for implementation, including objectives, technical requirements, ethical issues, logistical considerations, and monitoring and evaluation.

Neutralising antibody responses to SARS-CoV-2 omicron among elderly nursing home residents following a booster dose of BNT162b2 vaccine: A community-based, prospective, longitudinal cohort study

BACKGROUND

The protective immunity against omicron following a BNT162b2 Pfizer booster dose among elderly individuals (ie, those aged >65 years) is not well characterised.

METHODS

In a community-based, prospective, longitudinal cohort study taking place in France in which 75 residents from three nursing homes were enrolled, we selected 38 residents who had received a two-dose regimen of mRNA vaccine and a booster dose of Pfizer BNT162b2 vaccine. We excluded individuals that did not receive three vaccine doses or did not have available sera samples. We measured anti-S IgG antibodies and neutralisation capacity in sera taken 56 (28-68) and 55 (48-64) days (median (range)) after the 2^nd and 3^rd vaccine doses, respectively. Antibodies targeting the SARS-CoV-2 Spike protein were measured with the S-Flow assay as binding antibody units per milliliter (BAU/mL). Neutralising activities in sera were measured as effective dilution 50% (ED50) with the S-Fuse assay using authentic isolates of delta and omicron BA.1.

FINDINGS

Among the 38 elderly individuals recruited to the cohort study between November 23^rd, 2020 and April 29^th, 2021, with median age of 88 (range 72-101) years, 30 (78.95%) had been previously infected with SARS-CoV-2. After three vaccine doses, serum neutralising activity was lower against omicron BA.1 (median ED50 of 774.5, range 15.0-34660.0) than the delta variant (median ED50 of 4972.0, range 213.7-66340.0), and higher among previously infected (ie, convalescent; median ED50 against omicron: 1088.0, range 32.6-34660.0) compared with infection-naive residents (median ED50 against omicron: 188.4, range 15.0-8918.0). During the French omicron wave in December 2021-January 2022, 75% (6/8) of naive residents were infected, compared to 25% (7/30) of convalescent residents (P=0.0114). Anti-Spike antibody levels and neutralising activity against omicron BA.1 after a third BNT162b2 booster dose were lower in those with breakthrough BA.1 infection (n=13) compared with those without (n=25), with a median of 1429.9 (range 670.9-3818.3) BAU/mL vs 2528.3 (range 695.4-8832.0) BAU/mL (P=0.029) and a median ED50 of 281.1 (range 15.0-2136.0) vs 1376.0 (range 32.6-34660.0) (P=0.0013), respectively.

INTERPRETATION

This study shows that elderly individuals who received three vaccine doses elicit neutralising antibodies against the omicron BA.1 variant of SARS-CoV-2. Elderly individuals who had also been previously infected showed higher neutralising activity compared with naive individuals. Yet, breakthrough infections with omicron occurred. Individuals with breakthrough infections had significantly lower neutralising titers compared to individuals without breakthrough infection. Thus, a fourth dose of vaccine may be useful in the elderly population to increase the level of neutralising antibodies and compensate for waning immunity.

FUNDING

Institut Pasteur, Fondation pour la Recherche Médicale (FRM), European Health Emergency Preparedness and Response Authority (HERA), Agence nationale de recherches sur le sida et les hépatites virales - Maladies Infectieuses Emergentes (ANRS-MIE), Agence nationale de la recherche (ANR), Assistance Publique des Hôpitaux de Paris (AP-HP) and Fondation de France.

Seroprevalence of SARS-CoV-2 on health professionals via Bayesian estimation: a Brazilian case study before and after vaccines

The increasing number of COVID-19 infections brought by the current pandemic has encouraged the scientific community to analyze the seroprevalence in populations to support health policies. In this context, accurate estimations of SARS-CoV-2 antibodies based on antibody tests metrics (e.g., specificity and sensitivity) and the study of population characteristics are essential. Here, we propose a Bayesian analysis using IgA and IgG antibody levels through multiple scenarios regarding data availability from different information sources to estimate the seroprevalence of health professionals in a Northeastern Brazilian city: no data available, data only related to the test performance, data from other regions. The study population comprises 432 subjects with more than 620 collections analyzed via IgA/IgG ELISA tests. We conducted the study in pre- and post-vaccination campaigns started in Brazil. We discuss the importance of aggregating available data from various sources to create informative prior knowledge. Considering prior information from the USA and Europe, the pre-vaccine seroprevalence means are 8.04% and 10.09% for IgG and 7.40% and 9.11% for IgA. For the post-vaccination campaign and considering local informative prior, the median is 84.83% for IgG, which confirms a sharp increase in the seroprevalence after vaccination. Additionally, stratification considering differences in sex, age (younger than 30 years, between 30 and 49 years, and older than 49 years), and presence of comorbidities are provided for all scenarios.

Performance of SARS-CoV-2 Antigens in a Multiplex Bead Assay for Integrated Serological Surveillance of Neglected Tropical and Other Diseases

Serosurveillance can provide estimates of population-level exposure to infectious pathogens and has been used extensively during the COVID-19 pandemic. Simultaneous, serological testing for multiple pathogens can be done using bead-based immunoassays to add value to disease-specific serosurveys. We conducted a validation of four SARS-CoV-2 antigens-full-length spike protein, two receptor binding domain proteins, and the nucleocapsid protein-on our existing multiplex bead assay (MBA) for enteric diseases, malaria, and vaccine preventable diseases. After determining the optimal conditions for coupling the antigens to microsphere beads, the sensitivity and specificity of the assay were determined on two instruments (Luminex-200 and MAGPIX) when testing singly (monoplex) versus combined (multiplex). Sensitivity was assessed using plasma from 87 real-time reverse transcription polymerase chain reaction (rRT-PCR) positive persons collected in March-May of 2020 and ranged from 94.3% to 96.6% for the different testing conditions. Specificity was assessed using 98 plasma specimens collected prior to December 2019 and plasma from 19 rRT-PCR negative persons and ranged from 97.4% to 100%. The positive percent agreement was 93.8% to 97.9% using 48 specimens collected > 21 days post-symptom onset, while the negative percent agreement was ≥ 99% for all antigens. Test performance was similar using monoplex or multiplex testing. Integrating SARS-CoV-2 serology with other diseases of public health interest could add significant value to public health programs that have suffered severe programmatic setbacks during the COVID-19 pandemic.

Serology as a Tool to Assess Infectious Disease Landscapes and Guide Public Health Policy

Understanding the local burden and epidemiology of infectious diseases is crucial to guide public health policy and prioritize interventions. Typically, infectious disease surveillance relies on capturing clinical cases within a healthcare system, classifying cases by etiology and enumerating cases over a period of time. Disease burden is often then extrapolated to the general population. Serology (i.e., examining serum for the presence of pathogen-specific antibodies) has long been used to inform about individuals past exposure and immunity to specific pathogens. However, it has been underutilized as a tool to evaluate the infectious disease burden landscape at the population level and guide public health decisions. In this review, we outline how serology provides a powerful tool to complement case-based surveillance for determining disease burden and epidemiology of infectious diseases, highlighting its benefits and limitations. We describe the current serology-based technologies and illustrate their use with examples from both the pre- and post- COVID-19-pandemic context. In particular, we review the challenges to and opportunities in implementing serological surveillance in low- and middle-income countries (LMICs), which bear the brunt of the global infectious disease burden. Finally, we discuss the relevance of serology data for public health decision-making and describe scenarios in which this data could be used, either independently or in conjunction with case-based surveillance. We conclude that public health systems would greatly benefit from the inclusion of serology to supplement and strengthen existing case-based infectious disease surveillance strategies.

Prediction of coronavirus 3C-like protease cleavage sites using machine-learning algorithms

The coronavirus 3C-like (3CL) protease, a cysteine protease, plays an important role in viral infection and immune escape. However, there is still a lack of effective tools for determining the cleavage sites of the 3CL protease. This study systematically investigated the diversity of the cleavage sites of the coronavirus 3CL protease on the viral polyprotein, and found that the cleavage motif were highly conserved for viruses in the genera of Alphacoronavirus, Betacoronavirus and Gammacoronavirus. Strong residue preferences were observed at the neighboring positions of the cleavage sites. A random forest (RF) model was built to predict the cleavage sites of the coronavirus 3CL protease based on the representation of residues in cleavage motifs by amino acid indexes, and the model achieved an AUC of 0.96 in cross-validations. The RF model was further tested on an independent test dataset which were composed of cleavage sites on 99 proteins from multiple coronavirus hosts. It achieved an AUC of 0.95 and predicted correctly 80% of the cleavage sites. Then, 1,352 human proteins were predicted to be cleaved by the 3CL protease by the RF model. These proteins were enriched in several GO terms related to the cytoskeleton, such as the microtubule, actin and tubulin. Finally, a webserver named 3CLP was built to predict the cleavage sites of the coronavirus 3CL protease based on the RF model. Overall, the study provides an effective tool for identifying cleavage sites of the 3CL protease and provides insights into the molecular mechanism underlying the pathogenicity of coronaviruses.

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A view of the diversity of the cleavage sites by the coronavirus 3CL protease.

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An accurate RF model for predicting the cleavage of coronavirus 3CL protease.

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A web-server named 3CLP for predicting the cleavage of coronavirus 3CL protease.

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The 3CLP is available at http://www.computationalbiology.cn/3CLPHost/home.html.

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1352 human proteins were predicted to be cleaved by the coronavirus 3CL protease.

Bi-ECDAQ: An electrochemical dual-immuno-biosensor accompanied by a customized bi-potentiostat for clinical detection of SARS-CoV-2 Nucleocapsid proteins

Multiplex electrochemical biosensors have been used for eliminating the matrix effect in complex bodily fluids or enabling the detection of two or more bioanalytes, overall resulting in more sensitive assays and accurate diagnostics. Many electrochemical biosensors lack reliable and low-cost multiplexing to meet the requirements of point-of-care detection due to either limited functional biosensors for multi-electrode detection or incompatible readout systems. We developed a new dual electrochemical biosensing unit accompanied by a customized potentiostat to address the unmet need for point-of-care multi-electrode electrochemical biosensing. The two-working electrode system was developed using screen-printing of a carboxyl-rich nanomaterial containing ink, with both working electrodes offering active sites for recognition of bioanalytes. The low-cost bi-potentiostat system (∼$80) was developed and customized specifically to the bi-electrode design and used for rapid, repeatable, and accurate measurement of electrochemical impedance spectroscopy signals from the dual biosensor. This binary electrochemical data acquisition (Bi-ECDAQ) system accurately and selectively detected SARS-CoV-2 Nucleocapsid protein (N-protein) in both spiked samples and clinical nasopharyngeal swab samples of COVID-19 patients within 30 min. The two working electrodes offered the limit of detection of 116 fg/mL and 150 fg/mL, respectively, with the dynamic detection range of 1-10,000 pg/mL and the sensitivity range of 2744-2936 Ω mL/pg.mm² for the detection of N-protein. The potentiostat performed comparable or better than commercial Autolab potentiostats while it is significantly lower cost. The open-source Bi-ECDAQ presents a customizable and flexible approach towards addressing the need for rapid and accurate point-of-care electrochemical biosensors for the rapid detection of various diseases.

Validation of xMAP SARS-CoV-2 Multi-Antigen IgG assay in Nigeria

Objective

There is a need for reliable serological assays to determine accurate estimates of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seroprevalence. Most single target antigen assays have shown some limitations in Africa. To assess the performance of a multi-antigen assay, we evaluated a commercially available SARS-CoV-2 Multi-Antigen IgG assay for human coronavirus disease 2019 (COVID-19) in Nigeria.

Methods

Validation of the xMAP SARS-CoV-2 Multi-Antigen IgG assay was carried out using well-characterized SARS-CoV-2 reverse transcription polymerase chain reactive positive (97) and pre-COVID-19 pandemic (86) plasma panels. Cross-reactivity was assessed using pre-COVID-19 pandemic plasma specimens (213) from the 2018 Nigeria HIV/AIDS Indicator and Impact Survey (NAIIS).

Results

The overall sensitivity of the xMAP SARS-CoV-2 Multi-Antigen IgG assay was 75.3% [95% CI: 65.8%– 82.8%] and specificity was 99.0% [95% CI: 96.8%– 99.7%]. The sensitivity estimate increased to 83.3% [95% CI: 70.4%– 91.3%] for specimens >14 days post-confirmation of diagnosis. However, using the NAIIS pre-pandemic specimens, the false positivity rate was 1.4% (3/213).

Conclusions

Our results showed overall lower sensitivity and a comparable specificity with the manufacturer’s validation. There appears to be less cross-reactivity with NAIIS pre-pandemic COVID-19 specimens using the xMAP SARS-CoV-2 Multi-Antigen IgG assay. In-country SARS-CoV-2 serology assay validation can help guide the best choice of assays in Africa.

SerumCovid database: Description and preliminary analysis of serological COVID-19 diagnosis in healthcare workers

Serological databases represent an important source of information to perceive COVID-19 impact on health professionals involved in combating the disease. This paper describes SerumCovid, a COVID-19 serological database focused on the diagnosis of health professionals, providing a preliminary analysis to contribute to the understanding of the antibody response to the SARS-CoV-2. The study population comprises 321 samples from 236 healthcare and frontline workers fighting COVID-19 in Vitória de Santo Antão, Brazil. Samples were collected from at least six days of symptoms to more than 100 days. The used immunoenzymatic assays were Euroimmun Anti-SARS-CoV-2 ELISA IgG and IgA. The most common gender in SerumCovid is female, while the most common age group is between 30 and 39 years old. However, no statistical differences were observed in either genders or age categories. The most reported symptoms were fatigue, headaches, and myalgia. Still, some subjects presented positive results for IgA after 130 days. Based on a temporal analysis, we have not identified general patterns as subjects presented high and low values of IgA and IgG with different evolution trends. Unexpectedly, for subjects with both serological tests, the outcome of IgA and IgG tests were the same (either positive or negative) for more than 80% of the samples. Therefore, SerumCovid helps better understand how COVID-19 affected healthcare and frontline workers, which increases knowledge about the infection and enables direct prevention actions.

Seropositivity to Nucleoprotein to detect mild and asymptomatic SARS-CoV-2 infections: A complementary tool to detect breakthrough infections after COVID-19 vaccination?

Background

Methods

Results

Conclusions

Assessment of S-Specific IgG and IgM Positive Rates in Healthy Hospital Staff Members Vaccinated with the Inactivated SARS-CoV-2 Vaccine

Widespread vaccination of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine makes the assessment of antibodies' positive rates essential. In this study, a total of 378 hospital staff members vaccinated with the vaccine were selected as research subjects. Serum-specific IgG and IgM against the SARS-CoV-2 spike protein (S) were detected, and S-specific IgG and IgM positive rates were analyzed in different age and sex groups, as was the serological pattern of IgG/IgM. The positive rates of IgG and IgM were 92.06% and 44.44%, respectively. The percentage of both IgG and IgM positive (IgG⁺IgM⁺) was 43.92%. A total of 182 vaccinees (46.90%) were IgG positive and IgM negative (IgG⁺IgM^-), and 28 vaccinees (7.41%) were negative for both IgG and IgM (IgG^-IgM^-); 2 participants were positive for IgM alone (IgG^-IgM⁺). In sex subgroups, the rate of IgM positivity was significantly higher in the male group than in the female group (p = 0.027). In different age subgroups, positive rates for IgG in the young group were significantly higher than those in the other group (p = 0.035). Furthermore, ratios of sample values to cutoff values (S/CO values) for IgG in vaccinees who were S-specific IgG positive were compared, and the S/CO values of IgG were significantly higher in the younger group than in the other group (p < 0.001). When comparing the influence of sex on two specific serological patterns (IgG⁺IgM^- and IgG⁺IgM⁺), a significant difference in positivity rates was detected (p = 0.011). Male vaccinees were more likely than females to have an IgG⁺IgM⁺ pattern.

Peptide Biomarkers for the Diagnosis of Dengue Infection

In a world with an increasing population at risk of exposure to arthropod-borne flaviviruses, access to timely and accurate diagnostic tests would impact profoundly on the management of cases. Twenty peptides previously identified using a flavivirus proteome-wide microarray were evaluated to determine their discriminatory potential to detect dengue virus (DENV) infection. This included nine peptides recognized by IgM antibodies (PM peptides) and 11 peptides recognized by IgG antibodies (PG peptides). A bead-based multiplex peptide immunoassay (MPIA) using the Luminex technology was set-up to determine Ab binding levels to each of these peptides in a panel of 323 carefully selected human serum samples. Sera are derived from individuals either infected with different viruses, namely, the four DENV serotypes, Zika virus (ZIKV), yellow fever virus (YFV), chikungunya virus (CHIKV), West Nile virus (WNV) and Human immunodeficiency virus (HIV), or receiving vaccination against YFV, tick-borne encephalitis (TBEV), and Japanese encephalitis virus (JEV). Additionally, a set of healthy controls were included. We targeted a minimum specificity of 80% for all the analysis. The PG-9 peptide had the best sensitivity (73%) when testing DENV sera from acute patients (A-DENV; <8 days since symptom onset). With sera from convalescent DENV patients (C-DENV; >10 days since symptom onset) the FPG-1 peptide was the best seromarker with a sensitivity of 86%. When combining all A-DENV and C-DENV samples, peptides PM-22 and FPG-1 had the best-diagnostic performance with a sensitivity of 60 and 61.1%, and areas under the curve (AUC) of 0.7865 and 0.8131, respectively. A Random forest (RF) algorithm was used to select the best combination of peptides to classify DENV infection at a targeted specificity >80%. The best RF model for PM peptides that included A-DENV and C-DENV samples, reached a sensitivity of 72.3%, while for PG peptides, the best RF models for A-DENV only, C-DENV only and A-DENV + C-DENV reached a sensitivity of 88.9%, 89.1%, and 88.3%, respectively. In conclusion, the combination of multiple peptides constitutes a founding set of seromarkers for the discrimination of DENV infected individuals from other flavivirus infections.

Combining antibody markers for serosurveillance of SARS-CoV-2 to estimate seroprevalence and time-since-infection

Serosurveillance is an important epidemiologic tool for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), used to estimate infection rates and the degree of population immunity. There is no general agreement on which antibody biomarker(s) should be used, especially with the rollout of vaccines globally. Here, we used random forest models to demonstrate that a single spike or receptor-binding domain (RBD) antibody was adequate for classifying prior infection, while a combination of two antibody biomarkers performed better than any single marker for estimating time-since-infection. Nucleocapsid antibodies performed worse than spike or RBD antibodies for classification, but can be useful for estimating time-since-infection, and in distinguishing infection-induced from vaccine-induced responses. Our analysis has the potential to inform the design of serosurveys for SARS-CoV-2, including decisions regarding a number of antibody biomarkers measured.

Microarray-Based Detection of Antibodies against SARS-CoV-2 Proteins, Common Respiratory Viruses and Type I Interferons

A microarray-based assay to detect IgG and IgM antibodies against betacoronaviruses (SARS-CoV-2, SARS, MERS, OC43, and HKU1), other respiratory viruses and type I interferons (IFN-Is) was developed. This multiplex assay was applied to track antibody cross-reactivity due to previous contact with similar viruses and to identify antibodies against IFN-Is as the markers for severe COVID-19. In total, 278 serum samples from convalescent plasma donors, COVID-19 patients in the intensive care unit (ICU) and patients who recovered from mild/moderate COVID-19, vaccine recipients, prepandemic and pandemic patients with autoimmune endocrine disorders, and a heterogeneous prepandemic cohort including healthy individuals and chronically ill patients were analyzed. The anti-SARS-CoV-2 microarray results agreed well with the ELISA results. Regarding ICU patients, autoantibodies against IFN-Is were detected in 10.5% of samples, and 10.5% of samples were found to simultaneously contain IgM antibodies against more than two different viruses. Cross-reactivity between IgG against the SARS-CoV-2 nucleocapsid and IgG against the OC43 and HKU1 spike proteins was observed, resulting in positive signals for the SARS-CoV-2 nucleocapsid in prepandemic samples from patients with autoimmune endocrine disorders. The presence of IgG against the SARS-CoV-2 nucleocapsid in the absence of IgG against the SARS-CoV-2 spike RBD should be interpreted with caution.

Kinetics of the Severe Acute Respiratory Syndrome Coronavirus 2 Antibody Response and Serological Estimation of Time Since Infection

BACKGROUND

Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) induces a complex antibody response that varies by orders of magnitude between individuals and over time.

METHODS

We developed a multiplex serological test for measuring antibodies to 5 SARS-CoV-2 antigens and the spike proteins of seasonal coronaviruses. We measured antibody responses in cohorts of hospitalized patients and healthcare workers followed for up to 11 months after symptoms. A mathematical model of antibody kinetics was used to quantify the duration of antibody responses. Antibody response data were used to train algorithms for estimating time since infection.

RESULTS

One year after symptoms, we estimate that 36% (95% range, 11%-94%) of anti-Spike immunoglobulin G (IgG) remains, 31% (95% range, 9%-89%) anti-RBD IgG remains, and 7% (1%-31%) of anti-nucleocapsid IgG remains. The multiplex assay classified previous infections into time intervals of 0-3 months, 3-6 months, and 6-12 months. This method was validated using data from a seroprevalence survey in France, demonstrating that historical SARS-CoV-2 transmission can be reconstructed using samples from a single survey.

CONCLUSIONS

In addition to diagnosing previous SARS-CoV-2 infection, multiplex serological assays can estimate the time since infection, which can be used to reconstruct past epidemics.

Infection induced SARS-CoV-2 seroprevalence and heterogeneity of antibody responses in a general population cohort study in Catalonia Spain

Sparse data exist on the complex natural immunity to SARS-CoV-2 at the population level. We applied a well-validated multiplex serology test in 5000 participants of a general population study in Catalonia in blood samples collected from end June to mid November 2020. Based on responses to fifteen isotype-antigen combinations, we detected a seroprevalence of 18.1% in adults (n = 4740), and modeled extrapolation to the general population of Catalonia indicated a 15.3% seroprevalence. Antibodies persisted up to 9 months after infection. Immune profiling of infected individuals revealed that with increasing severity of infection (asymptomatic, 1-3 symptoms, ≥ 4 symptoms, admitted to hospital/ICU), seroresponses were more robust and rich with a shift towards IgG over IgA and anti-spike over anti-nucleocapsid responses. Among seropositive participants, lower antibody levels were observed for those ≥ 60 years vs < 60 years old and smokers vs non-smokers. Overweight/obese participants vs normal weight had higher antibody levels. Adolescents (13-15 years old) (n = 260) showed a seroprevalence of 11.5%, were less likely to be tested seropositive compared to their parents and had dominant anti-spike rather than anti-nucleocapsid IgG responses. Our study provides an unbiased estimate of SARS-CoV-2 seroprevalence in Catalonia and new evidence on the durability and heterogeneity of post-infection immunity.

A systematic review and meta-analysis of the sensitivity of antibody tests for the laboratory confirmation of COVID-19

Aim: The aim of this study was to investigate the utility of serological tests for the diagnosis of COVID-19 during the first week of symptom onset in patients confirmed with the real-time RT-PCR. Materials & methods: A systematic review and meta-analysis of 58 publications were performed using data obtained from Academic Search Ultimate, Africa-wide, Scopus, Web of Science and MEDLINE. Results: We found that the highest pooled sensitivities were obtained with ELISA IgM-IgG and chemiluminescence immunoassay IgM tests. Conclusion: Serological tests have low sensitivity within the first week of symptom onset and cannot replace nucleic acid amplification tests. However, serological assays can be used to support nucleic acid amplification tests.

Serology for Plasmodium vivax surveillance: A novel approach to accelerate towards elimination

Plasmodium vivax is the most widespread causative agent of human malaria in the world. Despite the ongoing implementation of malaria control programs, the rate of case reduction has declined over the last 5 years. Hence, surveillance of malaria transmission should be in place to identify and monitor areas that require intensified malaria control interventions. Serological tools may offer additional insights into transmission intensity over parasite and entomological measures, especially as transmission levels decline. Antibodies can be detected in the host system for months to even years after parasite infections have been cleared from the blood, enabling malaria exposure history to be captured. Because the Plasmodium parasite expresses more than 5000 proteins, it is important to a) understand antibody longevity following infection and b) measure antibodies to more than one antigen in order to accurately inform on the exposure and/or immune status of populations. This review summarises current practices for surveillance of P. vivax malaria, the current state of research into serological exposure markers and their potential role for accelerating malaria elimination, and discusses further studies that need to be undertaken to see such technology implemented in malaria-endemic areas.

SARS-CoV-2 Multi-Antigen Serology Assay

Serology tests are extremely useful for assessing whether a person has been infected with a pathogen. Since the onset of the COVID-19 pandemic, measurement of anti-SARS-CoV-2-specific antibodies has been considered an essential tool in identifying seropositive individuals and thereby understanding the extent of transmission in communities. The Luminex system is a bead-based technology that has the capacity to assess multiple antigens simultaneously using very low sample volumes and is ideal for high-throughput studies. We have adapted this technology to develop a COVID-19 multi-antigen serological assay. This protocol described here carefully outlines recommended steps to optimize and establish this method for COVID-19-specific antibody measurement in plasma and in saliva. However, the protocol can easily be customized and thus the assay is broadly applicable to measure antibodies to other pathogens.

Assessing the effects of non-pharmaceutical interventions on SARS-CoV-2 transmission in Belgium by means of an extended SEIQRD model and public mobility data

We present a compartmental extended SEIQRD metapopulation model for SARS-CoV-2 spread in Belgium. We demonstrate the robustness of the calibration procedure by calibrating the model using incrementally larger datasets and dissect the model results by computing the effective reproduction number at home, in workplaces, in schools, and during leisure activities. We find that schools and home contacts are important transmission pathways for SARS-CoV-2 under lockdown measures. School reopening has the potential to increase the effective reproduction number from Re=0.66±0.04 (95 % CI) to Re=1.09±0.05 (95 % CI) under lockdown measures. The model accounts for the main characteristics of SARS-CoV-2 transmission and COVID-19 disease and features a detailed representation of hospitals with parameters derived from a dataset consisting of 22 136 hospitalized patients. Social contact during the pandemic is modeled by scaling pre-pandemic contact matrices with Google Community Mobility data and with effectivity-of-contact parameters inferred from hospitalization data. The calibrated social contact model with its publically available mobility data, although coarse-grained, is a cheap and readily available alternative to social–epidemiological contact studies under lockdown measures, which were not available at the start of the pandemic.

Antibody landscapes of SARS-CoV-2 can reveal novel vaccine and diagnostic targets

SARS-CoV-2 virions are composed of structural proteins, but during virus infection, an additional 30 proteins could be expressed according to putative open reading frames (ORFs) of the viral genome. Some of these additional proteins modulate cellular processes through direct interactions, their truncations can affect disease pathogenesis and they can also serve as antigenic targets for more specific serology. In addition to structural proteins, the ORF1a/b polyprotein and accessory proteins can stimulate antibody responses during infection. Antibodies that target non-structural proteins can impact viral infection, through Fc mediated effector functions, through interactions during virus entry, fusion, replication and egress within infected cells. Characterization of the serological responses to additional proteins, provides a snapshot of the 'antibody landscape', which includes the antibody magnitude, antigenic specificity and informs the biological relevance of SARS-CoV-2 proteins.

Dye-Loaded Polymersome-Based Lateral Flow Assay: Rational Design of a COVID-19 Testing Platform by Repurposing SARS-CoV-2 Antibody Cocktail and Antigens Obtained from Positive Human Samples

The global pandemic of COVID-19 continues to be an important threat, especially with the fast transmission rate observed after the discovery of novel mutations. In this perspective, prompt diagnosis requires massive economical and human resources to mitigate the disease. The current study proposes a rational design of a colorimetric lateral flow immunoassay (LFA) based on the repurposing of human samples to produce COVID-19-specific antigens and antibodies in combination with a novel dye-loaded polymersome for naked-eye detection. A group of 121 human samples (61 serums and 60 nasal swabs) were obtained and analyzed by RT-PCR and ELISA. Pooled samples were used to purify antibodies using affinity chromatography, while antigens were purified via magnetic nanoparticles-based affinity. The purified proteins were confirmed for their specificity to COVID-19 via commercial LFA, ELISA, and electrochemical tests in addition to sodium dodecyl sulfate-polyacrylamide gel electrophoresis analysis. Polymersomes were prepared using methoxy polyethylene glycol-b-polycaprolactone (mPEG-b-PCL) diblock copolymers and loaded with a Coomassie Blue dye. The polymersomes were then functionalized with the purified antibodies and applied for the preparation of two types of LFA (antigen test and antibody test). Overall, the proposed diagnostic tests demonstrated 93 and 92.2% sensitivity for antigen and antibody tests, respectively. The repeatability (92-94%) and reproducibility (96-98%) of the tests highlight the potential of the proposed LFA. The LFA test was also analyzed for stability, and after 4 weeks, 91-97% correct diagnosis was observed. The current LFA platform is a valuable assay that has great economical and analytical potential for widespread applications.