Microarray Profiling of Vaccination-Induced Antibody Responses to SARS-CoV-2 Variants of Interest and Concern.

Mutations in surface proteins enable emerging variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to escape a substantial fraction of neutralizing antibodies and may thus weaken vaccine-driven immunity. To compare available vaccines and justify revaccination, rapid evaluation of antibody (Ab) responses to currently circulating SARS-CoV-2 variants of interest (VOI) and concern (VOC) is needed. Here, we developed a multiplex protein microarray-based system for rapid profiling of anti-SARS-CoV-2 Ab levels in human sera. The microarray system was validated using sera samples from SARS-CoV-2-free donors and those diagnosed with COVID-19 based on PCR and enzyme immunoassays. Microarray-based profiling of vaccinated donors revealed a substantial difference in anti-VOC Ab levels elicited by the replication-deficient adenovirus vector-base (Sputnik V) and whole-virion (CoviVac Russia COVID-19) vaccines. Whole-virion vaccine-induced Abs showed minor but statistically significant cross-reactivity with the human blood coagulation factor 1 (fibrinogen) and thrombin. However, their effects on blood clotting were negligible, according to thrombin time tests, providing evidence against the concept of pronounced cross-reactivity-related side effects of the vaccine. Importantly, all samples were collected in the pre-Omicron period but showed noticeable responses to the receptor-binding domain (RBD) of the Omicron spike protein. Thus, using the new express Ab-profiling system, we confirmed the inter-variant cross-reactivity of the anti-SARS-CoV-2 Abs and demonstrated the relative potency of the vaccines against new VOCs.

COVID-BIOCHIP: A Web Tool to Analyse COVID-19 Antigen Microarrays.

During the COVID-19 pandemic, there was a growing need to characterise the disease. A very important aspect is the ability to measure the immunisation extent, which can be achieved using antigen microarrays that quantitively measure the presence of COVID-related antibodies. A significant limitation for these tests was the complexity of manually analysing the results, and the limited availability of software for its analysis. In this paper, we describe the development of COVID-BIOCHIP, an ad-hoc web-based solution for the automatic analysis and visualisation of COVID-19 antigen microarray data results.

Fully Automated Chemiluminescence Microarray Analysis Platform for Rapid and Multiplexed SARS-CoV-2 Serodiagnostics.

Lateral-flow immunoassays and laboratory diagnostic tests like enzyme-linked immunosorbent assays (ELISAs) are powerful diagnostic tools to help fight the COVID-19 pandemic using them as antigen or antibody tests. However, the need emerges for alternative bioanalytical systems that combine their favorable features─simple, rapid, and cost-efficient point-of-care (POC) analysis of lateral-flow immunoassays and higher reliability of laboratory tests─while eliminating their disadvantages (limited sensitivity and specificity of lateral-flow assays and prolonged time and work expenditure of laboratory analysis). An additional need met by only a few tests is multiplexing, allowing for the analysis of several immunorecognition patterns at the same time. We herein present a strategy to combine all desirable attributes of the different test types by means of a flow-based chemiluminescence microarray immunoassay. Laminated polycarbonate microarray chips were developed for easy production and subsequent application in the fully automated microarray analysis platform MCR-R, where a novel flow cell design minimizes the sample volume to 40 µL. This system was capable of detecting IgG antibodies to SARS-CoV-2 with 100% sensitivity and specificity using recombinant antigens for the SARS-CoV-2 spike S1 protein, nucleocapsid protein, and receptor binding domain. The analysis was accomplished within under 4 min from serum, plasma, and whole blood, making it also useful in POC settings. Additionally, we showed the possibility of serosurveillance after infection or vaccination to monitor formerly unnoticed breakthrough infections in the population as well as to detect the need for booster vaccination after the natural decline of the antibody titer below detectable levels. This will help in answering pressing questions on the importance of the antibody response to SARS-CoV-2 that so far remain open. Additionally, even the sequential detection of IgM and IgG antibodies was possible, allowing for statements on the time response of an infection. While our serodiagnostic application focuses on SARS-CoV-2, the same approach is easily adjusted to other diseases, making it a powerful tool for future serological testing.

Dried blood sample analysis by antibody array across the total testing process.

Dried blood samples (DBSs) have many advantages; yet, impediments have limited the clinical utilization of DBSs. We developed a novel volumetric sampling device that collects a precise volume of blood, which overcomes the heterogeneity and hematocrit issues commonly encountered in a traditional DBS card collection as well as allowing for more efficient extraction and processing procedures and thus, more efficient quantitation, by using the entire sample. We also provided a thorough procedure validation using this volumetric DBS collection device with an established quantitative proteomics analysis method, and then analyzed 1000 proteins using this approach in DBSs concomitantly with serum for future consideration of utility in clinical applications. Our data provide a first step in the establishment of a DBS database for the broad application of this sample type for widespread use in clinical proteomic and other analyses applications.

New insights into genetic characteristics between multiple myeloma and COVID-19: An integrative bioinformatics analysis of gene expression omnibus microarray and the cancer genome atlas data.

BACKGROUND: Multiple myeloma (MM) is a hematological malignancy. Coronavirus disease 2019 (COVID-19) infection correlates with MM features. This study aimed to identify MM prognostic biomarkers with potential association with COVID-19. METHODS: Differentially expressed genes (DEGs) in five MM data sets (GSE47552, GSE16558, GSE13591, GSE6477, and GSE39754) with the same expression trends were screened out. Functional enrichment analysis and the protein-protein interaction network were performed for all DEGs. Prognosis-associated DEGs were screened using the stepwise Cox regression analysis in the cancer genome atlas (TCGA) MMRF-CoMMpass cohort and the GSE24080 data set. Prognosis-associated DEGs associated with COVID-19 infection in the GSE164805 data set were also identified. RESULTS: A total of 98 DEGs with the same expression trends in five data sets were identified, and 83 DEGs were included in the protein-protein interaction network. Cox regression analysis identified 16 DEGs were associated with MM prognosis in the TCGA cohort, and only the cytochrome c oxidase subunit 6C (COX6C) gene (HR = 1.717, 95% CI 1.231-2.428, p = .002) and the nucleotide-binding oligomerization domain containing 2 (NOD2) gene (HR = 0.882, 95% CI 0.798-0.975, p = .014) were independent factors related to MM prognosis in the GSE24080 data set. Both of them were downregulated in patients with mild COVID-19 infection compared with controls but were upregulated in patients with severe COVID-19 compared with patients with mild illness. CONCLUSIONS: The NOD2 and COX6C genes might be used as prognostic biomarkers in MM. The two genes might be associated with the development of COVID-19 infection.

A Serological Snapshot of COVID-19 Initial Stages in Israel by a 6-Plex Antigen Array.

The first case of SARS-CoV-2 was discovered in Israel in late February 2020. Three major outbreaks followed, resulting in over 800,000 cases and over 6,000 deaths by April 2021. Our aim was characterization of a serological snapshot of Israeli patients and healthy adults in the early months of the COVID-19 pandemic. Sera from 55 symptomatic COVID-19 patients and 146 healthy subjects (early-pandemic, reverse transcription-quantitative PCR [qRT-PCR]-negative), collected in Israel between March and April 2020, were screened for SARS-CoV-2-specific IgG, IgM, and IgA antibodies, using a 6-plex antigen microarray presenting the whole inactivated virus and five viral antigens: a stabilized version of the spike ectodomain (S2P), spike subunit 1 (S1), receptor-binding-domain (RBD), N-terminal-domain (NTD), and nucleocapsid (NC). COVID-19 patients, 4 to 40 days post symptom onset, presented specific IgG to all of the viral antigens (6/6) in 54 of the 55 samples (98% sensitivity). Specific IgM and IgA antibodies for all six antigens were detected in only 10% (5/55) and 4% (2/55) of the patients, respectively, suggesting that specific IgG is a superior serological marker for COVID-19. None of the qRT-PCR-negative sera reacted with all six viral antigens (100% specificity), and 48% (70/146) were negative throughout the panel. Our findings confirm a low seroprevalence of anti-SARS-CoV-2 antibodies in the Israeli adult population prior to the COVID-19 outbreak. We further suggest that the presence of low-level cross-reacting antibodies in naive individuals calls for a combined, multiantigen analysis for accurate discrimination between naive and exposed individuals. IMPORTANCE A 6-plex protein array presenting the whole inactivated virus and five nucleocapsid and spike-derived SARS-CoV-2 antigens was used to generate a serological snapshot of SARS-CoV-2 seroprevalence and seroconversion in Israel in the early months of the pandemic. Our findings confirm a very low seroprevalence of anti-SARS-CoV-2 antibodies in the Israeli adult population. We further propose that the presence of low-level nonspecific antibodies in naive individuals calls for a combined, multiantigen analysis for accurate discrimination between naive and exposed individuals enabling accurate determination of seroconversion. The developed assay is currently applied to evaluate immune responses to the Israeli vaccine during human phase I/II trials.

An antigen microarray protocol for COVID-19 serological analysis.

The emergence of the coronavirus disease 2019 pandemic increased the interest in analysis of immunoglobulin responses. ELISA and lateral flow assays are widely used but are restricted by a single response value to an antigen or antigen pool. Here, we describe antigen microarrays, an alternative allowing simultaneous assessment of multiple interactions between antigens and the immunoglobulin content of patient sera. The technique requires minimal reagents and sample input and can be adapted to a wide variety of potential antigenic targets of interest.

A glycosaminoglycan microarray identifies the binding of SARS-CoV-2 spike protein to chondroitin sulfate E.

Heparan sulfate (HS), a sulfated glycosaminoglycan (GAG), was reported to be a necessary host attachment factor that promotes SARS-CoV-2 infection. In this study, we developed GAG microarrays based on fluorescence detection for high-sensitivity screening of the GAG-binding specificity of proteins and applied it for the analysis of SARS-CoV-2 spike (S) protein. Among the 20 distinct GAGs, the S protein bound not only to heparin (HEP)/HS but also to chondroitin sulfate E (CSE) in a concentration-dependent manner. We then analyzed the specificity of each subunit of the S protein. While the S1 subunit showed exclusive binding to HEP, the S2 subunit also bound to CSE and HEP/HS. CSE might act as an alternative attachment factor for HS in SARS-CoV-2 infection.

Epitope-specific antibody responses differentiate COVID-19 outcomes and variants of concern.

BACKGROUNDThe role of humoral immunity in COVID-19 is not fully understood, owing, in large part, to the complexity of antibodies produced in response to the SARS-CoV-2 infection. There is a pressing need for serology tests to assess patient-specific antibody response and predict clinical outcome.METHODSUsing SARS-CoV-2 proteome and peptide microarrays, we screened 146 COVID-19 patients' plasma samples to identify antigens and epitopes. This enabled us to develop a master epitope array and an epitope-specific agglutination assay to gauge antibody responses systematically and with high resolution.RESULTSWe identified linear epitopes from the spike (S) and nucleocapsid (N) proteins and showed that the epitopes enabled higher resolution antibody profiling than the S or N protein antigen. Specifically, we found that antibody responses to the S-811-825, S-881-895, and N-156-170 epitopes negatively or positively correlated with clinical severity or patient survival. Moreover, we found that the P681H and S235F mutations associated with the coronavirus variant of concern B.1.1.7 altered the specificity of the corresponding epitopes.CONCLUSIONEpitope-resolved antibody testing not only affords a high-resolution alternative to conventional immunoassays to delineate the complex humoral immunity to SARS-CoV-2 and differentiate between neutralizing and non-neutralizing antibodies, but it also may potentially be used to predict clinical outcome. The epitope peptides can be readily modified to detect antibodies against variants of concern in both the peptide array and latex agglutination formats.FUNDINGOntario Research Fund (ORF) COVID-19 Rapid Research Fund, Toronto COVID-19 Action Fund, Western University, Lawson Health Research Institute, London Health Sciences Foundation, and Academic Medical Organization of Southwestern Ontario (AMOSO) Innovation Fund.

Gene selection using hybrid dragonfly black hole algorithm: A case study on RNA-seq COVID-19 data.

This paper introduces a new hybrid approach (DBH) for solving gene selection problem that incorporates the strengths of two existing metaheuristics: binary dragonfly algorithm (BDF) and binary black hole algorithm (BBHA). This hybridization aims to identify a limited and stable set of discriminative genes without sacrificing classification accuracy, whereas most current methods have encountered challenges in extracting disease-related information from a vast amount of redundant genes. The proposed approach first applies the minimum redundancy maximum relevancy (MRMR) filter method to reduce the dimensionality of feature space and then utilizes the suggested hybrid DBH algorithm to determine a smaller set of significant genes. The proposed approach was evaluated on eight benchmark gene expression datasets, and then, was compared against the latest state-of-art techniques to demonstrate algorithm efficiency. The comparative study shows that the proposed approach achieves a significant improvement as compared with existing methods in terms of classification accuracy and the number of selected genes. Moreover, the performance of the suggested method was examined on real RNA-Seq coronavirus-related gene expression data of asthmatic patients for selecting the most significant genes in order to improve the discriminative accuracy of angiotensin-converting enzyme 2 (ACE2). ACE2, as a coronavirus receptor, is a biomarker that helps to classify infected patients from uninfected in order to identify subgroups at risk for COVID-19. The result denotes that the suggested MRMR-DBH approach represents a very promising framework for finding a new combination of most discriminative genes with high classification accuracy.

Extracellular Vesicles Analysis in the COVID-19 Era: Insights on Serum Inactivation Protocols towards Downstream Isolation and Analysis.

Since the outbreak of the COVID-19 crisis, the handling of biological samples from confirmed or suspected SARS-CoV-2-positive individuals demanded the use of inactivation protocols to ensure laboratory operators' safety. While not standardized, these practices can be roughly divided into two categories, namely heat inactivation and solvent-detergent treatments. These routine procedures should also apply to samples intended for Extracellular Vesicles (EVs) analysis. Assessing the impact of virus-inactivating pre-treatments is therefore of pivotal importance, given the well-known variability introduced by different pre-analytical steps on downstream EVs isolation and analysis. Arguably, shared guidelines on inactivation protocols tailored to best address EVs-specific requirements will be needed among the analytical community, yet deep investigations in this direction have not yet been reported. We here provide insights into SARS-CoV-2 inactivation practices to be adopted prior to serum EVs analysis by comparing solvent/detergent treatment vs. heat inactivation. Our analysis entails the evaluation of EVs recovery and purity along with biochemical, biophysical and biomolecular profiling by means of a set of complementary analytical techniques: Nanoparticle Tracking Analysis, Western Blotting, Atomic Force Microscopy, miRNA content (digital droplet PCR) and tetraspanin assessment by microarrays. Our data suggest an increase in ultracentrifugation (UC) recovery following heat treatment; however, it is accompanied by a marked enrichment in EVs-associated contaminants. On the other hand, solvent/detergent treatment is promising for small EVs (<150 nm range), yet a depletion of larger vesicular entities was detected. This work represents a first step towards the identification of optimal serum inactivation protocols targeted to EVs analysis.

Multiplexed, microscale, microarray-based serological assay for antibodies against all human-relevant coronaviruses.

Rapid, sensitive, and precise multiplexed assays for serological analysis during candidate COVID-19 vaccine development would streamline clinical trials. The VaxArray Coronavirus (CoV) SeroAssay quantifies IgG antibody binding to 9 pandemic, potentially pandemic, and endemic human CoV spike antigens in 2 h with automated results analysis. IgG antibodies in serum bind to the CoV spike protein capture antigens printed in a microarray format and are labeled with a fluorescent anti-species IgG secondary label. The assay demonstrated excellent lower limits of quantification ranging from 0.3 to 2.0 ng/mL and linear dynamic ranges of 76 to 911-fold. Average precision of 11 % CV and accuracy (% recovery) of 92.5 % over all capture antigens were achieved over 216 replicates representing 3 days and 3 microarray lots. Clinical performance on 263 human serum samples (132 SARS-CoV-2 negatives and 131 positives based on donor-matched RT-PCR and/or date of collection) produced 98.5 % PPA and 100 % NPA.

Machine learning-based cytokine microarray digital immunoassay analysis.

Serial measurement of a large panel of protein biomarkers near the bedside could provide a promising pathway to transform the critical care of acutely ill patients. However, attaining the combination of high sensitivity and multiplexity with a short assay turnaround poses a formidable technological challenge. Here, the authors develop a rapid, accurate, and highly multiplexed microfluidic digital immunoassay by incorporating machine learning-based autonomous image analysis. The assay has achieved 12-plexed biomarker detection in sample volume <15 µL at concentrations < 5 pg/mL while only requiring a 5-min assay incubation, allowing for all processes from sampling to result to be completed within 40 min. The assay procedure applies both a spatial-spectral microfluidic encoding scheme and an image data analysis algorithm based on machine learning with a convolutional neural network (CNN) for pre-equilibrated single-molecule protein digital counting. This unique approach remarkably reduces errors facing the high-capacity multiplexing of digital immunoassay at low protein concentrations. Longitudinal data obtained for a panel of 12 serum cytokines in human patients receiving chimeric antigen receptor-T (CAR-T) cell therapy reveals the powerful biomarker profiling capability. The assay could also be deployed for near-real-time immune status monitoring of critically ill COVID-19 patients developing cytokine storm syndrome.

COVID-19: Virology, biology and novel laboratory diagnosis.

BACKGROUND: At the end of December 2019, a novel coronavirus tentatively named SARS-CoV-2 in Wuhan, a central city in China, was announced by the World Health Organization. SARS-CoV-2 is an RNA virus that has become a major public health concern after the outbreak of the Middle East Respiratory Syndrome-CoV (MERS-CoV) and Severe Acute Respiratory Syndrome-CoV (SARS-CoV) in 2002 and 2012, respectively. As of 29 October 2020, the total number of COVID-19 cases had reached over 44 million worldwide, with more than 1.17 million confirmed deaths. DISCUSSION: SARS-CoV-2 infected patients usually present with severe viral pneumonia. Similar to SARS-CoV, the virus enters respiratory tract cells via the angiotensin-converting enzyme receptor 2. The structural proteins play an essential role in budding the virus particles released from different host cells. To date, an approved vaccine or treatment option of a preventive character to avoid severe courses of COVID-19 is still not available. CONCLUSIONS: In the present study, we provide a brief review of the general biological features of CoVs and explain the pathogenesis, clinical symptoms and diagnostic approaches regarding monitoring future infectivity and prevent emerging COVID-19 infections.

Analysis of SARS-CoV-2 antibodies in COVID-19 convalescent blood using a coronavirus antigen microarray.

The current practice for diagnosis of COVID-19, based on SARS-CoV-2 PCR testing of pharyngeal or respiratory specimens in a symptomatic patient at high epidemiologic risk, likely underestimates the true prevalence of infection. Serologic methods can more accurately estimate the disease burden by detecting infections missed by the limited testing performed to date. Here, we describe the validation of a coronavirus antigen microarray containing immunologically significant antigens from SARS-CoV-2, in addition to SARS-CoV, MERS-CoV, common human coronavirus strains, and other common respiratory viruses. A comparison of antibody profiles detected on the array from control sera collected prior to the SARS-CoV-2 pandemic versus convalescent blood specimens from virologically confirmed COVID-19 cases demonstrates near complete discrimination of these two groups, with improved performance from use of antigen combinations that include both spike protein and nucleoprotein. This array can be used as a diagnostic tool, as an epidemiologic tool to more accurately estimate the disease burden of COVID-19, and as a research tool to correlate antibody responses with clinical outcomes.

Increasing host cellular receptor-angiotensin-converting enzyme 2 expression by coronavirus may facilitate 2019-nCoV (or SARS-CoV-2) infection.

The ongoing outbreak of a new coronavirus (2019-nCoV, or severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2]) has caused an epidemic of the acute respiratory syndrome known as coronavirus disease (COVID-19) in humans. SARS-CoV-2 rapidly spread to multiple regions of China and multiple other countries, posing a serious threat to public health. The spike (S) proteins of SARS-CoV-1 and SARS-CoV-2 may use the same host cellular receptor, angiotensin-converting enzyme 2 (ACE2), for entering host cells. The affinity between ACE2 and the SARS-CoV-2 S protein is much higher than that of ACE2 binding to the SARS-CoV S protein, explaining why SARS-CoV-2 seems to be more readily transmitted from human to human. Here, we report that ACE2 can be significantly upregulated after infection of various viruses, including SARS-CoV-1 and SARS-CoV-2, or by the stimulation with inflammatory cytokines such as interferons. We propose that SARS-CoV-2 may positively induce its cellular entry receptor, ACE2, to accelerate its replication and spread; high inflammatory cytokine levels increase ACE2 expression and act as high-risk factors for developing COVID-19, and the infection of other viruses may increase the risk of SARS-CoV-2 infection. Therefore, drugs targeting ACE2 may be developed for the future emerging infectious diseases caused by this cluster of coronaviruses.

Polymer microarrays rapidly identify competitive adsorbents of virus-like particles.

The emergence of SARS-CoV-2 highlights the global need for platform technologies to enable the rapid development of diagnostics, vaccines, treatments, and personal protective equipment (PPE). However, many current technologies require the detailed mechanistic knowledge of specific material-virion interactions before they can be employed, for example, to aid in the purification of vaccine components or in the design of a more effective PPE. Here, we show that an adaption of a polymer microarray method for screening bacterial-surface interactions allows for the screening of polymers for desirable material-virion interactions. Nonpathogenic virus-like particles including fluorophores are exposed to the arrays in an aqueous buffer as a simple model of virions carried to the surface in saliva/sputum. Competitive binding of Lassa and Rubella virus-like particles is measured to probe the relative binding properties of a selection of copolymers. This provides the first step in the development of a method for the discovery of novel materials with promise for viral binding, with the next being development of this method to assess absolute viral adsorption and assessment of the attenuation of the activity of live virus, which we propose would be part of a material scale up step carried out in high containment facilities, alongside the use of more complex media to represent biological fluids.

Recent advances in the nucleic acid-based diagnostic tool for coronavirus.

Recently in China, a novel coronavirus outbreak took place which caused pneumonia-like symptoms. This coronavirus belongs to the family of SARS and MERS and causes respiratory system disease known as COVID-19. At present we use polymerase chain reaction (PCR) based molecular biology methods for the detection of coronavirus. Other than these PCR based methods, some improved methods also exist such as microarray-based techniques, Real time-quantitative PCR, CRISPR-Cas13 based tools but almost all of the available methods have advantages and disadvantages. There are many limitations associated with this method and hence there is a need for a fast, more sensitive, and specific diagnostic tool which can detect a greater number of samples in less time. Here we have summarised currently available nucleic acid-based diagnostic methods for the detection of coronavirus and the need for developing a better technique for a fast and sensitive detection of coronavirus infections. Nucleic acid based detection tool for SARS-CoV-2.

Evaluation of the Quotient® MosaiQ™ COVID-19 antibody microarray for the detection of IgG and IgM antibodies to SARS-CoV-2 virus in humans.

The MosaiQ® COVID-19 Antibody test fulfills the minimal requirements for serological testing according to the French regulation.

A modular microarray imaging system for highly specific COVID-19 antibody testing.

To detect the presence of antibodies in blood against SARS-CoV-2 in a highly sensitive and specific manner, here we describe a robust, inexpensive ($200), 3D-printable portable imaging platform (TinyArray imager) that can be deployed immediately in areas with minimal infrastructure to read coronavirus antigen microarrays (CoVAMs) that contain a panel of antigens from SARS-CoV-2, SARS-1, MERS, and other respiratory viruses. Application includes basic laboratories and makeshift field clinics where a few drops of blood from a finger prick could be rapidly tested in parallel for the presence of antibodies to SARS-CoV-2 with a test turnaround time of only 2-4 h. To evaluate our imaging device, we probed and imaged coronavirus microarrays with COVID-19-positive and negative sera and achieved a performance on par with a commercial microarray reader 100× more expensive than our imaging device. This work will enable large scale serosurveillance, which can play an important role in the months and years to come to implement efficient containment and mitigation measures, as well as help develop therapeutics and vaccines to treat and prevent the spread of COVID-19.