A scalable serology solution for profiling humoral immune responses to SARS-CoV-2 infection and vaccination.

Objectives: Antibody testing against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been instrumental in detecting previous exposures and analyzing vaccine-elicited immune responses. Here, we describe a scalable solution to detect and quantify SARS-CoV-2 antibodies, discriminate between natural infection- and vaccination-induced responses, and assess antibody-mediated inhibition of the spike-angiotensin converting enzyme 2 (ACE2) interaction. Methods: We developed methods and reagents to detect SARS-CoV-2 antibodies by enzyme-linked immunosorbent assay (ELISA). The main assays focus on the parallel detection of immunoglobulin (Ig)Gs against the spike trimer, its receptor binding domain (RBD) and nucleocapsid (N). We automated a surrogate neutralisation (sn)ELISA that measures inhibition of ACE2-spike or -RBD interactions by antibodies. The assays were calibrated to a World Health Organization reference standard. Results: Our single-point IgG-based ELISAs accurately distinguished non-infected and infected individuals. For seroprevalence assessment (in a non-vaccinated cohort), classifying a sample as positive if antibodies were detected for ≥ 2 of the 3 antigens provided the highest specificity. In vaccinated cohorts, increases in anti-spike and -RBD (but not -N) antibodies are observed. We present detailed protocols for serum/plasma or dried blood spots analysis performed manually and on automated platforms. The snELISA can be performed automatically at single points, increasing its scalability. Conclusions: Measuring antibodies to three viral antigens and identify neutralising antibodies capable of disrupting spike-ACE2 interactions in high-throughput enables large-scale analyses of humoral immune responses to SARS-CoV-2 infection and vaccination. The reagents are available to enable scaling up of standardised serological assays, permitting inter-laboratory data comparison and aggregation.

Comparison of SARS-CoV-2 indirect and direct RT-qPCR detection methods.

BACKGROUND: Sensitive, rapid, and accessible diagnostics continue to be critical to track the COVID-19 pandemic caused by the SARS-CoV-2 virus. RT-qPCR is the gold standard test, and comparison of methodologies and reagents, utilizing patient samples, is important to establish reliable diagnostic pipelines. METHODS: Here, we assessed indirect methods that require RNA extraction with direct RT-qPCR on patient samples. Four different RNA extraction kits (Qiagen, Invitrogen, BGI and Norgen Biotek) were compared. For detection, we assessed two recently developed Taqman-based modules (BGI and Norgen Biotek), a SYBR green-based approach (NEB Luna Universal One-Step Kit) with published and newly-developed primers, and clinical results (Seegene STARMag RNA extraction system and Allplex 2019-nCoV RT-qPCR assay). We also tested and optimized direct, extraction-free detection using these RT-qPCR systems and performed a cost analysis of the different methods evaluated here. RESULTS: Most RNA isolation procedures performed similarly, and while all RT-qPCR modules effectively detected purified viral RNA, the BGI system provided overall superior performance (lower detection limit, lower Ct values and higher sensitivity), generating comparable results to original clinical diagnostic data, and identifying samples ranging from 65 copies to 2.1 × 105 copies of viral genome/µl. However, the BGI detection system is more expensive than other options tested here. With direct RT-qPCR, simply adding an RNase inhibitor greatly improved detection, without the need for any other treatments (e.g. lysis buffers or boiling). The best direct methods detected ~ 10 fold less virus than indirect methods, but this simplified approach reduced sample handling, as well as assay time and cost. CONCLUSIONS: With extracted RNA, the BGI RT-qPCR detection system exhibited superior performance over the Norgen system, matching initial clinical diagnosis with the Seegene Allplex assay. The BGI system was also suitable for direct, extraction-free analysis, providing 78.4% sensitivity. The Norgen system, however, still accurately detected samples with a clinical Ct < 33 from extracted RNA, provided significant cost savings, and was superior to SYBR green assays that exhibited reduced specificity.

A multiplexed, next generation sequencing platform for high-throughput detection of SARS-CoV-2.

Population scale sweeps of viral pathogens, such as SARS-CoV-2, require high intensity testing for effective management. Here, we describe "Systematic Parallel Analysis of RNA coupled to Sequencing for Covid-19 screening" (C19-SPAR-Seq), a multiplexed, scalable, readily automated platform for SARS-CoV-2 detection that is capable of analyzing tens of thousands of patient samples in a single run. To address strict requirements for control of assay parameters and output demanded by clinical diagnostics, we employ a control-based Precision-Recall and Receiver Operator Characteristics (coPR) analysis to assign run-specific quality control metrics. C19-SPAR-Seq coupled to coPR on a trial cohort of several hundred patients performs with a specificity of 100% and sensitivity of 91% on samples with low viral loads, and a sensitivity of >95% on high viral loads associated with disease onset and peak transmissibility. This study establishes the feasibility of employing C19-SPAR-Seq for the large-scale monitoring of SARS-CoV-2 and other pathogens.

Persistence of serum and saliva antibody responses to SARS-CoV-2 spike antigens in COVID-19 patients.

While the antibody response to SARS-CoV-2 has been extensively studied in blood, relatively little is known about the antibody response in saliva and its relationship to systemic antibody levels. Here, we profiled by enzyme-linked immunosorbent assays (ELISAs) IgG, IgA and IgM responses to the SARS-CoV-2 spike protein (full length trimer) and its receptor-binding domain (RBD) in serum and saliva of acute and convalescent patients with laboratory-diagnosed COVID-19 ranging from 3-115 days post-symptom onset (PSO), compared to negative controls. Anti-SARS-CoV-2 antibody responses were readily detected in serum and saliva, with peak IgG levels attained by 16-30 days PSO. Longitudinal analysis revealed that anti-SARS-CoV-2 IgA and IgM antibodies rapidly decayed, while IgG antibodies remained relatively stable up to 105 days PSO in both biofluids. Lastly, IgG, IgM and to a lesser extent IgA responses to spike and RBD in the serum positively correlated with matched saliva samples. This study confirms that serum and saliva IgG antibodies to SARS-CoV-2 are maintained in the majority of COVID-19 patients for at least 3 months PSO. IgG responses in saliva may serve as a surrogate measure of systemic immunity to SARS-CoV-2 based on their correlation with serum IgG responses.

Overexpression of the Severe Acute Respiratory Syndrome Coronavirus-2 Receptor, Angiotensin-Converting Enzyme 2, in Diabetic Kidney Disease: Implications for Kidney Injury in Novel Coronavirus Disease 2019.

OBJECTIVES: Diabetes is associated with adverse outcomes, including death, after coronavirus disease 19 (COVID-19) infection. Beyond the lungs, Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), the etiologic agent of the COVID-19 pandemic, can infect a range of other tissues, including the kidney, potentially contributing to acute kidney injury in those with severe disease. We hypothesized that the renal abundance of angiotensin-converting enzyme (ACE) 2, the cell surface receptor for SARS-CoV-2, may be modulated by diabetes and agents that block the renin-angiotensin-aldosterone system (RAAS). METHODS: The expression of ACE 2 was examined in 49 archival kidney biopsies from patients with diabetic kidney disease and from 12 healthy, potential living allograft donors using next-generation sequencing technology (RNA Seq). RESULTS: Mean ACE 2 messenger RNA was increased approximately 2-fold in diabetes when compared with healthy control subjects (mean ± SD, 13.2±7.9 vs 7.7±3.6 reads per million reads, respectively; p=0.001). No difference in transcript abundance was noted between recipients and nonrecipients of agents that block the RAAS (12.2±6.7 vs 16.2±10.7 reads per million reads, respectively; p=0.25). CONCLUSIONS: Increased ACE 2 messenger RNA in the diabetic kidney may increase the risk and/or severity of kidney infection with SARS-CoV-2 in the setting of COVID-19 disease. Further studies are needed to ascertain whether this diabetes-related overexpression is generalizable to other tissues, most notably the lungs.