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Development of a quantitative COVID-19 multiplex assay and its use for serological surveillance in a low SARS-CoV-2 incidence community

  • Cassandra Guarino,

    Roles Data curation, Formal analysis, Investigation, Methodology, Validation, Writing – original draft, Writing – review & editing

    Affiliation Department of Population Medicine and Diagnostic Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY, United States of America

  • Elisabeth Larson,

    Roles Investigation, Writing – original draft, Writing – review & editing

    Affiliation Department of Population Medicine and Diagnostic Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY, United States of America

  • Susanna Babasyan,

    Roles Methodology, Writing – review & editing

    Affiliation Department of Population Medicine and Diagnostic Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY, United States of America

  • Alicia Rollins,

    Roles Methodology, Writing – review & editing

    Affiliation Department of Population Medicine and Diagnostic Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY, United States of America

  • Lok R. Joshi,

    Roles Methodology, Writing – review & editing

    Affiliation Department of Population Medicine and Diagnostic Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY, United States of America

  • Melissa Laverack,

    Roles Methodology, Writing – review & editing

    Affiliation Department of Population Medicine and Diagnostic Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY, United States of America

  • Lara Parrilla,

    Roles Resources, Writing – review & editing

    Affiliation Cayuga Medical Center, Ithaca, NY, United States of America

  • Elizabeth Plocharczyk,

    Roles Resources, Writing – review & editing

    Affiliation Cayuga Medical Center, Ithaca, NY, United States of America

  • Diego G. Diel,

    Roles Funding acquisition, Methodology, Supervision, Writing – review & editing

    Affiliation Department of Population Medicine and Diagnostic Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY, United States of America

  • Bettina Wagner

    Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Writing – review & editing

    Affiliation Department of Population Medicine and Diagnostic Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY, United States of America


A serological COVID-19 Multiplex Assay was developed and validated using serum samples from convalescent patients and those collected prior to the 2020 pandemic. After initial testing of multiple potential antigens, the SARS-CoV-2 nucleocapsid protein (NP) and receptor-binding domain (RBD) of the spike protein were selected for the human COVID-19 Multiplex Assay. A comparison of synthesized and mammalian expressed RBD proteins revealed clear advantages of mammalian expression. Antibodies directed against NP strongly correlated with SARS-CoV-2 virus neutralization assay titers (rsp = 0.726), while anti-RBD correlation was moderate (rsp = 0.436). Pan-Ig, IgG, IgA, and IgM against NP and RBD antigens were evaluated on the validation sample sets. Detection of NP and RBD specific IgG and IgA had outstanding performance (AUC > 0.90) for distinguishing patients from controls, but the dynamic range of the IgG assay was substantially greater. The COVID-19 Multiplex Assay was utilized to identify seroprevalence to SARS-CoV-2 in people living in a low-incidence community in Ithaca, NY. Samples were taken from a cohort of healthy volunteers (n = 332) in early June 2020. Only two volunteers had a positive result on a COVID-19 PCR test performed prior to serum sampling. Serological testing revealed an exposure rate of at least 1.2% (NP) or as high as 5.7% (RBD), higher than the measured incidence rate of 0.16% in the county at that time. This highly sensitive and quantitative assay can be used for monitoring community exposure rates and duration of immune response following both infection and vaccination.


The community of Ithaca, NY (in Tompkins county) responded swiftly and decisively to the impending threat of SARS-CoV-2, closing public and private schools, most child daycare centers, as well as the local Colleges and University in March 2020. In addition, the community followed New York State guidance on the closure of non-essential businesses, and many individuals quickly adapted practices on social distancing, mask wearing and travel restrictions. As a result, the community spread of SARS-CoV-2 in Ithaca was greatly limited, while a severe outbreak occurred simultaneously in New York City, the initial epicenter of COVID-19 in the US, and its surrounding regions. From March 13 to June 30, the number of daily new cases in New York City reached 6364 (April 6, 2020), while in Tompkins county, daily case numbers peaked at 16 (March 27, 2020). During the first week of June, the duration of the seroprevalence study described here, New York City had a 7-day rolling average of 450 new cases/day, while the 7-day rolling average in Tompkins county was <1 new case/day [1, 2]. The availability of testing to identify active infections was crucial but limited in the first weeks and months of the pandemic. In addition, assays that could detect prior exposure to the SARS-CoV-2 virus, the causative agent of COVID-19 were initially not available.

Since our work on a serologic COVID-19 assay began, large research and development undertakings around the world have led to the development of a variety of different, but related, serologic assays. These serologic assays, many of which have received USA FDA Emergency Use Authorization, have been recently reviewed [35], and information on newly developed tests is available through multiple websites [68]. Each assay measures different components of the host immune response against SARS-CoV-2. For example, the different assays detect IgG [923], IgM [11, 13, 1522], IgA [10, 13], or pan-Ig [24] specific for different recombinant SARS-CoV-2 antigens: full length spike protein (S) [15, 19, 22, 25], subunit 1 of S (aa14-685, S1) [10, 12, 13, 23], subunit 2 of S (aa686-1273, S2) [13, 23], the receptor binding domain (aa319-541, RBD) [12, 13, 21, 25], nucleocapsid protein (full length protein, NP) [9, 1113, 15, 16, 19, 24, 25], and/or membrane protein (M) [13]. These assays utilize different techniques, including ELISA [10, 11, 16, 21, 2528], rapid detection lateral flow qualitative assays [14, 17, 20, 22], singleplex chemiluminescent microparticle immunoassays [9, 15, 19, 23, 24, 29], or multiplex bead-based Luminex assays [12, 13, 3038].

Community-wide seroprevalence analyses provide valuable insight into the breadth of community exposure to the virus in regions with rapidly increasing COVID-19 related hospitalizations. These studies have identified that approximately 0.1–6% [9, 14, 17, 18, 28, 29, 36, 3945], and as high as 17–22.7% [20, 37, 46], of individuals in communities with rapidly increasing cases present SARS-CoV-2 specific IgG antibodies. However, many studies compared multiple assays on the same sample set [3, 12, 25, 4761], and showed discrepancies in detection rate between tests. For example, one study compared six different assays on convalescent PCR-confirmed COVID-19 patients in Germany. The different assays detected specific antibodies in 66.7–89% of the samples, depending on the assay used [48]. Accurate detection of SARS-CoV-2 specific antibodies presents specific challenges in communities with low case incidence due to the decreased positive predictive value. For example, a comparison of three different assays on serum samples from a region of Japan with no identified SARS-CoV-2 outbreaks at the time testing was performed resulted in inconsistent seroprevalence values ranging from 0–3.3%, depending on which test was used [54]. This highlights the importance for high sensitivity and specificity in order to accurately detect rare seropositive cases amongst the broad population.

Here, we describe the development of a COVID-19 Multiplex Assay to simultaneously quantify antibodies directed against three SARS-CoV-2 antigens, NP, RBD, and S1, as indicators of previous SARS-CoV-2 exposure. We demonstrate the importance of the antigen expression methodology for assay performance, compare assay results to virus neutralization, and evaluate the detection of different antibody isotypes. Finally, we utilized this assay to perform surveillance of the non-diagnosed exposure rate in the Cornell University community residing in Ithaca, NY in early June 2020.

Materials and methods

Samples for assay validation

De-identified serum samples (n = 78) from a previous serologic study conducted in 2019, collected in Binghamton, NY prior to SARS-CoV-2 being introduced in the United States, were used as control serum samples (pre-COVID-19) to investigate non-specific reactivity of assay components–all samples were from participants that indicated willingness to have their samples used for future research. All samples for this control group originated from people living in upstate NY in 2019 and included participants 20–75 years of age (median: 55.5 years), including 18.3% male and 61.7% female volunteers.

De-identified convalescent human serum samples from PCR confirmed SARS-CoV-2 infected individuals (n = 20) were obtained from Cayuga Medical Center (CMC, IRB protocol 0420EP), including samples from 10 non-hospitalized patients in the Cayuga Health System, with three serial samples from two patients, and two serial samples from six patients. Individuals were 16–72 years of age (median: 40 years) and were 70% male and 30% female. ROC curve analysis, described below, used only the first sample from individuals contributing multiple samples. Details of clinical history, sampling dates, and diagnostic criteria were not provided with these samples. One additional de-identified convalescent sample from a PCR confirmed SARS-CoV-2 infected individual was provided by Cornell Weill Medicine (WMC). Additional unique de-identified convalescence serum samples (n = 30), >21 days post SARS-CoV-2 PCR positive nasopharyngeal swab result, were obtained from the NYS Department of Health (NYSDOH), Wadsworth Center. These samples were from individuals residing in NYS, and additional demographic information was not provided.

Virus neutralization assay

A virus neutralization assay [62, 63] was performed to assess the levels of neutralizing antibodies in serum. All serum samples were heat inactivated at 56°C for 30 minutes prior to the virus neutralization assay. Each sample was serially diluted (2-fold dilutions, 1:8 to 1:1024) and incubated with 100 TCID50 of SARS-CoV-2 Hu-WA-1 strain (GenBank: MN985325.1) for 1h at 37°C. Following incubation, 100 μl of a cell suspension of Vero CCL-81 cells was added to each well of the 96-well plate and incubated for 72h at 37°C with 5% CO2. Virus neutralization assays were read under an inverted microscope using SARS-COV-2 cytopathic effects as an indicator. Neutralizing antibody titers were expressed as the reciprocal of the highest dilution of serum capable of completely inhibiting SARS-CoV-2 infection/replication. Negative and positive human control sera were included in all assays. All samples were tested in duplicate and the endpoint titer determined based on the highest dilution of serum that presented 100% neutralization against SARS-CoV-2. The reciprocal titer of the highest serum dilution with 100% neutralization is presented.

SARS-CoV-2 antigens

A synthetic peptide of the RBD region of the Spike protein (synthetic RBD) was a commercially available (LifeTein LLC, Somerset, NJ, product number LT5587). This 74 amino acids peptide (aa 433 to 506, YP_009724390) was composed of the following sequence: NH2- VIAWNSNNLDSKVGGNYNYL YRLFRKSNLKPFERDISTEI YQAGSTPCNGVEGFNCYFPL QSYGFQPTNGVGYQ- CONH2, including a disulfide bridge: Cys480-Cys488.

NP, RBD and S1 SARS-CoV-2 antigens expressed from mammalian cell culture were produced using a previously described IL-4 fusion protein expression system [64]. The SARS-CoV-2 antigens were cloned from SARS-CoV-2 RNA derived from Vero cell cultures infected with SARS-CoV-2 strain Hu-WA-1. cDNA was synthesized using the SuperScript III Reverse Transcriptase (Life Technologies) and oligo dT and six hexamer random primers following the manufacturer’s recommendations. The cDNA was used as template to amplify and clone nucleotide sequences, corresponding to the partial N-terminal domain of the S1 subunit without the signal peptide (aa 16 to 264, YP_009724390), RBD (aa 319 to 529, YP_009724390) of the Spike protein, and the whole NP antigen (aa 1–419, YP_009724397). Platinum SuperFi DNA Polymerase was used for amplification as per manufacturer’s instructions (ThermoFisher Scientific, Waltham, MA, USA). The primer sequences are summarized in Table 1. The PCR products were cloned into the multiple cloning site of mammalian expression vector pcDNA3.1 (ThermoFisher Scientific, Waltham, MA, USA) 3’ of the horse IL-4 sequence, as described previously [64].

Table 1. Primer sequences for expression cloning SARS-CoV-2 antigens.

The sequences of RBD and NP were identical to Spike protein and nucleocapsid protein sequences, respectively, of Wuhan-Hu-1 isolate (NC_045512), as verified by Sanger sequencing. S1 had a deletion of 10 amino acids, position 67–77 and was identical to the sequence of GenBank entry, accession number MT772569.

CHO-K1 cells were transiently transfected with recombinant expression constructs. Geneporter II transfection reagent was used per manufacturer’s instructions (Genlantis, San Diego, CA, USA). F12 medium (Gibco, Gaithersburg, MD), supplemented with 10% Fetal bovine serum (Atlanta Biologicals, Flowery Branch, GA) was used as growth medium. Expression and secretion of the recombinant SARS-CoV-2 antigen fusion proteins by CHO transfectants was confirmed using the IL-4 tag by flow cytometric analysis and ELISA, respectively, as previously described [64]. After 24–30 hours of incubation, the supernatants were harvested for fluorescent bead-based multiplex assays.

Fluorescent bead-based assays

Fluorescent beads (MicroPlex®, Luminex Corp., Austin, TX, USA) were coupled as previously described [65]. Briefly, the SARS-CoV-2 proteins expressed as IL-4 fusion proteins were bound to the beads through an anti-IL-4 antibody, clone 25 (RRID: AB_2737308) by incubating the anti-IL-4 coupled beads with the fusion protein supernatant solution for 30 minutes at room temperature, followed by a wash step. The synthetic RBD peptide was directly coupled to beads. The multiplex assay was performed as previously described [66], with a few modifications. Briefly, beads were incubated with serum samples diluted 1:10, 1:50, or 1:100, and bound serum antibodies were detected with biotinylated anti-human IgG (H+L), ‘pan-Ig’ (RRID: AB_2337628), diluted 1:10,000. Alternatively, the assay was detected with one of the following biotinylated antibodies for isotype detection: anti-human IgG, Fcɣ fragment specific, ‘IgG’ (RRID: AB_2337630), anti-human IgM, Fc5μ specific, ‘IgM’ (RRID: AB_2337632), or anti-human serum IgA, α-chain specific, ‘IgA’ (RRID: AB_2337624). All isotype detection reagents were diluted 1:10,000. A serum dilution of 1:100 was found to be optimal. The Luminex platform allows for quantification over a large range, from approximately 100–25,000 MFI. While the MFI values do not provide an absolute antibody concentration, the MFI values reflect the quantity of antigens-specific antibody in the sample, with a dynamic range that exceeds that of a typical ELISA.

Samples for serologic surveillance

Samples for serologic surveillance were collected at Cornell University at a ‘COVID-19 Healthy Volunteer Clinic’ (COVID-19 HVC) performed during the first week of June 2020. Eligible volunteers were non-pregnant healthy adults, 18–78 years of age, >110lbs, and members of the Cornell University community in Ithaca, NY, including faculty, staff, and students, or their direct family members. Volunteers answered a brief survey, including travel and health history since January 2020, and donated samples of blood and saliva. This project was approved by the Institutional Review Board for Human Participants at Cornell University, Protocol ID# 2004009584.

Statistical analysis

Confidence intervals for sensitivity and specificity were calculated as “exact” Clopper-Pearson confidence intervals. Spearmen nonparametric correlation coefficients, rsp, were calculated with one-tailed p values. One-way ANOVAs were performed with Dunnett’s multiple comparison tests. Data were considered significant if p values were < 0.05. Statistical analyses, including ROC curve analysis, were performed using Prism GraphPad version 6.0.


Antigen selection

With the goal to identify the best antigens for the COVID-19 Multiplex assay, different proteins of SARS-CoV-2 were evaluated and compared as antigen targets for a serological multiplex assay using a pan-Ig detection antibody. Initially, a commercially available synthetic RBD peptide of the Spike protein and the full-length RBD expressed in mammalian cells as an IL-4 fusion protein were compared using a sample set of pre-COVID-19 negative serum samples as ‘controls’ (n = 78) and convalescent samples from CMC and WCM as ‘patients’ (n = 21). The assay based on synthetic RBD resulted in an area under the ROC curve (AUC) of 0.6496 (95% CI: 0.5256–0.7735), indicating poor discrimination between patients and controls. The AUC for IL-4/RBD evaluated on the same sample set was 0.9945 (95% CI: 0.9830–1.006), indicating excellent discrimination between patients and controls. The IL-4/RBD assay also generated a wider dynamic range of pan-Ig MFI results in comparison to the assay with synthetic RBD antigen (Fig 1). These results supported the use of the mammalian expressed IL-4/RBD antigen for serological assay development.

Fig 1. Comparison between fluorescent bead COVID-19 assays using synthetic RBD or mammalian expressed IL-4/RBD fusion protein as antigens for serologic testing.

Negative serum samples (n = 78) were taken in 2019 prior to the COVID-19 pandemic. Convalescent serum samples (n = 21) were obtained from COVID-19 patients (n = 11). The plots represent pan-Ig median fluorescence intensity (MFI) values.

Additional SARS-CoV-2 antigens expressed in the mammalian cells as IL-4 fusion proteins included S1, NP, M and E proteins. Each antigen was first screened in individual assays with a subset of convalescent serum samples and negative samples for pan-Ig (S1 Fig). The IL-4/NP and IL-4/S1 antigens together with IL-4/RBD were selected for further evaluation.

Correlation to virus neutralization

Serum samples from pre-COVID-19 controls (n = 7), from healthy people collected in the first week of June 2020 (COVID-19 HVC, n = 50), and from convalescent patients (n = 50) were evaluated for antibodies (pan-Ig) directed against NP, RBD and S1 in the COVID-19 Multiplex Assay. Each of these serum samples was also tested for neutralizing antibodies. Pan-Ig directed against NP highly correlated with neutralizing antibodies (rsp = 0.726; p < 0.0001). RBD antibodies correlated moderately (rsp = 0.436, p < 0.0001), while those directed against S1, where the version of S1 expressed contained a 10 amino acid deletion, did not correlate with neutralizing antibodies (rsp = 0.055, p = 0.2852) (Fig 2).

Fig 2. Correlation of virus neutralization titers with COVID-19 multiplex results using NP, RBD and S1 antigens.

The SARS-CoV-2 antigens were expressed in mammalian cells as IL-4 fusion proteins, and the three antigens were multiplexed. Serum samples included samples taken pre-COVID-19 (n = 7), obtained from healthy people in the first week of June 2020 (COVID-19 HVC, n = 50), and from convalescent patients (n = 51). The correlation coefficients, rsp, for NP, RBD and S1 were 0.726, 0.436, and -0.055, respectively.

Overall, serum neutralizing antibodies in convalescent patient samples were low and not reaching titers above 64. All convalescent samples from CMC (n = 20) had neutralizing antibody titers between 12 and 64. Convalescent serum samples taken >21 days after a positive PCR result (n = 30) generated variable virus neutralization results: thirteen had titers ranging from 16 to 64, six had a titer of 8, and the remaining eleven did not neutralize virus (<8). Of the 50 serum samples from the COVID-19 HVC, 41 serum samples did not neutralize virus, six had a neutralizing antibody titer of 8, and one, from an individual reporting a positive SARS-CoV-2 PCR result, had a titer of 32.

SARS-CoV-2 specific antibody isotypes

Convalescent serum samples (n = 41) and pre-COVID-19 control serum (n = 78) used above for the pan-Ig measurement were also tested for IgG, IgM, and IgA isotypes in COVID-19 Multiplex assays. ROC curve analyses were performed on all data. The NP antigen resulted in outstanding discrimination between the convalescent patient and control groups, with AUCs above 0.90, on pan-Ig and all isotypes tested (Table 2). RBD yielded outstanding performance (AUC >0.90) with IgG and IgA, while the S1 assay showed only moderate performance with any isotype tested, leading to the exclusion of the S1 assay in the final COVID-19 Multiplex Assay. At a 1:100 serum dilution, the dynamic MFI range was greatest with NP for all isotypes tested. Detection with pan-Ig and IgG reagents produced a substantially greater dynamic range of results (50 to 24000 MFI) than with anti-IgM and IgA (Fig 3 and S2 Fig). The upper range of IgM and IgA values did not exceed 3,000 MFI on any antigen at a 1:100 serum dilution, limiting the value of these detection antibodies for low positive samples. Based on the comparison of three SARS-COV-2 antigens and four detection antibodies, the NP and RBD antigens in combination with the IgG detection reagent were selected for the final COVID-19 Multiplex assay.

Fig 3. Comparison of antibody isotypes.

The SARS-CoV-2 antigens, NP, RBD, and S1, were multiplexed in each assay run. Serum samples included samples taken pre-COVID-19, ‘Neg.’, (n = 78), and samples from convalescent patients, ‘Conv.’ (n = 41). The assays were detected with antibodies against either pan-Ig, IgG, IgM or IgA. Dashed lines represent the positive (upper line) and negative (lower line) cut-off values for RBD and NP IgG MFI. Values between the lines are considered ‘equivocal’.

Table 2. Area under the ROC curve (AUC) for each SARS-CoV-2 antigens and detection antibodies in the COVID-19 multiplex assay a.

Assay sensitivity and specificity of the COVID-19 multiplex assay

The sensitivity and specificity were determined for the optimized COVID-19 IgG assay based on the ROC analysis of convalescent serum samples from 41 individual patients and control serum samples from 78 pre-COVID-19 study participants. The assay’s lower and upper cut-off values, respectively, resulted in diagnostic sensitivity of >98%, and specificity of >95% for both antigens (Table 3). Sample results between the small lower and upper cut-off value ranges are considered equivocal and describe either high negative or low positive serum samples. Overall, IgG antibody measurement provides a wide dynamic range above the upper cut-offs for both antigens, allowing for optimal quantification of SARS-CoV-2 antibodies in positive samples (Fig 3).

Table 3. Sensitivity and specificity for the IgG COVID-19 multiplex assay a.

Community exposure rate

By June 1st 2020, a total of 160 SARS-CoV-2 infection cases were reported in Tompkins County since the beginning of the pandemic, comprising approximately 0.16% of the county population [1]. Serum samples from 332 volunteers were taken during a clinic (COVID-19 HVC) between June 1–5, 2020 and were tested for IgG antibodies against NP and RBD in the COVID-19 Multiplex Assay. Serum samples from four individuals (1.2%) were positive on both NP and RBD, indicating evidence of previous infection with SARS-CoV-2 (Table 4). Of those four NP and RBD positive samples, only one individual was previously diagnosed by a COVID-19 positive PCR test. A second participant reported a positive PCR result prior to the COVID-19 HVC but did not have antibodies by the time the serum sample was taken. An additional 15 samples were positive on the RBD antigen only, but equivocal (n = 10) or negative (n = 5) on the NP antigen assay. By considering a positive result on one or both antigens as an indicator of previous infection with SARS-CoV-2, a total of 19 participants (5.7%) were identified as ‘seropositive’.

Table 4. Serum samples from healthy volunteers (n = 332) were tested for NP and RBD-specific IgG antibodies using the COVID-19 multiplex assay.

Self-reported illness history from the preceding 6 months was provided by each COVID-19 HVC participant and included dry cough (n = 77), fever (n = 54), GI upset (diarrhea) (n = 52), and loss of sense of smell or taste (n = 15). There was no significant difference between serum IgG values for either antigen for each reported illness history group, as compared to those who did not report any illness (Table 5).

Table 5. Comparison of NP and RBD-specific serum IgG antibodies in healthy volunteers by illness and travel history between January and May 2020.

Self-reported travel history from the preceding 6 months was also provided by each COVID-19 HVC participants and included travel to NYC (n = 49), domestic travel outside of NYS (n = 103), and international travel (n = 26). NP-specific IgG values in serum between groups with different travel history were similar to those without travel history. RBD-specific IgG values were significantly increased in the group with international travel history as compared to those who did not report any travel history (p < 0.05) (Table 5).


Development of a SARS-CoV-2 specific serological assay that can accurately quantify virus-specific antibodies in high and low COVID-19 incidence communities is crucial for assessing exposure rates to the virus, immune responses to vaccination, and the longevity of antibodies after infection or vaccination. Here, we described the validation of a new COVID-19 Multiplex Assay based on the SARS-CoV-2 RBD and NP antigens with excellent accuracy of detection, sensitivity and specificity, and a broad quantification range. In addition, the assay was used to detect undiagnosed prior infection with SARS-CoV-2 in individuals with no or mild disease in a low incidence community in Ithaca, NY.

Antibody responses against viral pathogens are polyclonal and typically directed against several immunogenic structures including conformational and linear epitopes on these antigens. The choice, quality and conformation of an antigen highly influences specificity, sensitivity, and the overall performance of the serological assay. Here, we compared several SARS-CoV-2 antigens to identify the optimal antigens for a sensitive fluorescent bead-based multiplex assay, including two different RBD antigens. One was a synthetic, commercially available peptide. The second RBD antigen was expressed in mammalian cells, resulting in the closest homolog to expression of the natural viral protein after infection of a human host. The serological assay based on mammalian RBD antigen resulted in excellent sensitivity and specificity and a wide linear quantification range for antibodies in serum, while the assay based on the synthetic RBD peptide had a narrow quantification range and a poor ability to distinguish pre-COVID-19 sera without antibodies against SARS-CoV-2 from COVID-19 patient sera. The serological results suggest that the synthetic RBD peptide had a low structural homology to the natural viral RBD protein. In addition, the commercial peptide was truncated (74 aa) compared to the 210 aa mammalian expressed RBD antigen, possibly leading to missing antigenic epitopes of the synthetic peptide.

For the final COVID-19 Multiplex Assay both antigens, NP and RBD, were thus produced in mammalian cells. Antibodies against NP highly correlated with neutralizing antibodies against the SARS-CoV-2 strain Hu-WA-1. Testing of pre-COVID-19 sera that were collected before the pandemic reached the US, confirmed that these samples had no reactivity with the NP antigen assay. Antibodies against SARS-CoV-2 NP in convalescent patient serum illustrated the wide dynamic quantification range of the NP assay. Overall, the NP assay had an outstanding diagnostic sensitivity and specificity of 97.6% and 100%, respectively. For comparison, the EUROIMMUN SARS-CoV-2 anti-spike S1 ELISA, a widely distributed pre-existing serologic assay for SARS-CoV-2, resulted in sensitivity values ranging from 67.0–97.0% and specificity values ranging from 96.0–100% [6, 10, 27, 28, 4850, 55]. The USA Food and Drug Administration has independently evaluated many of the current COVID-19 serologic assays together on the same sample set, allowing a useful comparison of test accuracies [67]. Most of the current serologic assays for SARS-CoV-2 antibodies are validated with blood samples collected in the first 2–7 weeks after symptom onset [9, 10, 19, 2125, 2729, 39, 47, 50, 52, 53, 55, 59].

Two sets of convalescent sera were used for validation of the COVID-19 Multiplex Assay described here and included samples collected in Ithaca, NY within the first 4–6 weeks after clinical cases were first confirmed in the region (n = 11), and samples obtained from the NYS DOH from patients >21 days after a positive SARS-CoV-2 PCR result from a nasopharyngeal swab (n = 30). Other patient information, including duration and onset of symptoms and severity of disease was not available for these sample sets. It has been suggested that the magnitude of SARS-CoV-2-specific antibodies in serum is positively correlated with disease severity [68, 69] and antibodies wane rapidly, possibly within as little as three months after virus clearance [7072]. Therefore, sensitivity may have been overestimated in assays that were validated using only early convalescent sera from hospitalized patients. Within our sample set, patients who had mild illness, or patients who were infected many months prior to testing may have had low serum antibody at the time the sample was taken, but SARS-CoV-2 specific antibodies could still be detected by the COVID-19 Multiplex Assay above the lower cut-off values.

Most serological COVID-19 assays described in the literature identified IgG or IgM antibodies against SARS-CoV-2 in patient serum, and a few have also investigated IgA antibodies [73, 74]. Here, we compared serum pan-Ig, IgG, IgM and IgA antibodies on the same assay platform indicating that measurement of IgG antibodies against SARS-CoV-2 most effectively differentiated convalescent patient serum from pre-COVID-19 serum. Measurement of NP- and RBD-specific serum IgA antibodies also distinguished known positive and negative sera, however serum IgA measurements were limited in magnitude and dynamic range. The ability of the COVID-19 Multiplex Assay to measure both IgG and IgA isotypes will enable further study of the immune response to SARS-CoV-2, including the quantification of antibody responses after vaccination. Furthermore, the COVID-19 Multiplex Assays for IgG and IgA will be valuable tools for measuring mucosal antibody responses due to the improved analytical sensitivity of the bead-based platform compared to conventional ELISA [75] and as shown previously for other respiratory viral pathogens [65, 76, 77].

We next used the COVID-19 Multiplex Assay to evaluate seroprevalence in healthy people in Ithaca, NY in June 2020. The confirmed COVID-19 incidence rate in the community at that time was low (0.16%). Out of 332 COVID-19 HVC participants a total of 19 (5.7%) had IgG antibodies against SARS-CoV-2 NP and/or RBD antigens. Based on the self-reported clinical COVID-19-like symptoms that the majority of the participants experienced since January 2020, it can be assumed that at least some of these individuals were infected with SARS-CoV-2 sometime earlier in the year. Many of the participants also travelled in the first 2.5 months in 2020 either internationally or to NYC which was the initial hot-spot of the COVID-19 pandemic in the US. Nevertheless, the severity of their symptoms did not advance to COVID-19 PCR testing or hospitalization and it can be assumed that several participants of the COVID-19 HVC did mount low and short-lasting antibody responses against the virus which were overall low again in June 2020. At the time of antibody testing, there was only an increased prevalence of RBD antibodies in serum from individuals with international travel history during the early months of the pandemic. Overall, the 5.7% seroprevalence rate was substantially higher than the confirmed infection rate of 0.16% suggesting that undiagnosed infections were prevalent in this community in the early months of the pandemic.

This highly sensitive and specific assay is a valuable tool for monitoring immune response to SARS-CoV-2 infection in both individuals and at the population level, however there are several limitations to the use of this serological assay. One potential limitation of this assay is the possibility for cross-reactivity with other known coronaviruses, in particular NP, which has moderate sequence homology with the nucleocapsid proteins of other human coronaviruses [78]. However, non-specific reactions against this antigen were not detected in our control group. Another potential limitation is that, in populations with low disease prevalence, as in the case of the population surveyed here, the positive predictive value of individual results will be low.

In conclusion, the use of the quantitative serological COVID-19 Multiplex Assay, for monitoring community exposure rates and obtaining more information on antibody magnitude and longevity after SARS-CoV-2 infection and vaccination, will help to assess infection risks in populations and individuals.

Supporting information

S1 Fig. Representative pan-Ig antibody values directed against NP, RBD, envelope protein (E) or membrane protein (M) of SARS-CoV-2 in the pools produced for internal assay standards.

These pools included Negative (N), Low Positive (L), and High Positive (H) pooled samples.


S2 Fig. IgA antibody values against NP and RBD for negative (“-“, n = 8) and positive (“+”, n = 15) serum samples measured at three different serum dilutions, 1:10, 1:50, or 1:100.



We would like to thank Dr. Hon Ip, USGS National Wildlife Health Center, Madison WI, for kindly providing the SARS-CoV-2 virus, strain Hu-WA-1, and the associated SARS-CoV-2 RNA derived from Vero cell cultures infected with this strain. We would also like to thank Dr. Brad Jones, Weill Cornell Medicine, and Dr. William Lee, NYS Department of Health, Wadsworth Center, for kindly providing additional convalescent samples, and Eric Hoffman, Marissa Barbieri, Kanneboyina Nagaraju, and Yetrib Hathout for providing the control sera taken in 2019 for our COVID-19 Multiplex assay validation and verification analysis. We further thank Paul Jannette, Andrew Brooks, Diane Kilts, Renee Anderson, Rebecca Tallmadge, Patrick Mitchell, Brittany Cronk, Dana Williams and her phlebotomist team, Dr. Erica Behling-Kelly, and Erica Bender for their help in organizing and running the COVID-19 Healthy Volunteer Clinic in June 2020, as well as Cornell Health and the IRB and IBC Committee members in enabling the Clinic at Cornell University.


  1. 1. 2020. “Tompkins County COVID-19 Data.” Tompkins County.
  2. 2. 2020. “COVID-19: Data.” NYC Health.
  3. 3. Ward S, Lindsley A, Courter J, Assa’ad A. Clinical testing for COVID-19. J Allergy Clin Immunol. 2020;146: 23–34. pmid:32445839
  4. 4. Cheng MP, Papenburg J, Desjardins M, Kanjilal S, Quach C, Libman M, et al. Diagnostic Testing for Severe Acute Respiratory Syndrome–Related Coronavirus-2. Ann Intern Med. 2020 [cited 24 Jul 2020]. pmid:32282894
  5. 5. Espejo AP, Akgun Y, Al Mana AF, Tjendra Y, Millan NC, Gomez-Fernandez C, et al. Review of Current Advances in Serologic Testing for COVID-19. Am J Clin Pathol. [cited 24 Jul 2020]. pmid:32583852
  6. 6. 2020. “EUA Authorized Serology Test Performance.” US Food and Drug Administration.
  7. 7. 2020. “Serology-based tests for COVID-19.” Johns Hopkins Center for Health Security.
  8. 8. 2020. “SARS-CoV-2 diagnostic pipeline.” Foundation for Innovative New Diagnostics.
  9. 9. Bryan A, Pepper G, Wener MH, Fink SL, Morishima C, Chaudhary A, et al. Performance Characteristics of the Abbott Architect SARS-CoV-2 IgG Assay and Seroprevalence in Boise, Idaho. Journal of Clinical Microbiology. 2020;58. pmid:32381641
  10. 10. Beavis KG, Matushek SM, Abeleda APF, Bethel C, Hunt C, Gillen S, et al. Evaluation of the EUROIMMUN Anti-SARS-CoV-2 ELISA Assay for detection of IgA and IgG antibodies. J Clin Virol. 2020;129: 104468. pmid:32485620
  11. 11. Bundschuh C, Egger M, Wiesinger K, Gabriel C, Clodi M, Mueller T, et al. Evaluation of the EDI enzyme linked immunosorbent assays for the detection of SARS-CoV-2 IgM and IgG antibodies in human plasma. Clin Chim Acta. 2020;509: 79–82. pmid:32526218
  12. 12. Chia WN, Tan CW, Foo R, Kang AEZ, Peng Y, Sivalingam V, et al. Serological differentiation between COVID-19 and SARS infections. Emerging Microbes & Infections. 2020;9: 1497–1505. pmid:32529906
  13. 13. Dobaño C, Vidal M, Santano R, Jiménez A, Chi J, Barrios D, et al. Highly Sensitive and Specific Multiplex Antibody Assays To Quantify Immunoglobulins M, A, and G against SARS-CoV-2 Antigens. Journal of Clinical Microbiology. 2021;59. pmid:33127841
  14. 14. Doi A, Iwata K, Kuroda H, Hasuike T, Nasu S, Kanda A, et al. Estimation of seroprevalence of novel coronavirus disease (COVID-19) using preserved serum at an outpatient setting in Kobe, Japan: A cross-sectional study. medRxiv. 2020; 2020.04.26.20079822.
  15. 15. Jin Y, Wang M, Zuo Z, Fan C, Ye F, Cai Z, et al. Diagnostic value and dynamic variance of serum antibody in coronavirus disease 2019. Int J Infect Dis. 2020;94: 49–52. pmid:32251798
  16. 16. Tan W, Lu Y, Zhang J, Wang J, Dan Y, Tan Z, et al. Viral Kinetics and Antibody Responses in Patients with COVID-19. medRxiv. 2020; 2020.03.24.20042382.
  17. 17. Erikstrup C, Hother CE, Pedersen OBV, Mølbak K, Skov RL, Holm DK, et al. Estimation of SARS-CoV-2 infection fatality rate by real-time antibody screening of blood donors. Clin Infect Dis. [cited 24 Jul 2020]. pmid:33501969
  18. 18. Ling R, Yu Y, He J, Zhang J, Xu S, Sun R, et al. Seroprevalence and epidemiological characteristics of immunoglobulin M and G antibodies against SARS-CoV-2 in asymptomatic people in Wuhan, China. medRxiv. 2020; 2020.06.16.20132423.
  19. 19. Suhandynata RT, Hoffman MA, Kelner MJ, McLawhon RW, Reed SL, Fitzgerald RL. Longitudinal Monitoring of SARS-CoV-2 IgM and IgG Seropositivity to Detect COVID-19. J Appl Lab Med. [cited 24 Jul 2020]. pmid:32428207
  20. 20. Torres JP, Piñera C, De La Maza V, Lagomarcino AJ, Simian D, Torres B, et al. SARS-CoV-2 antibody prevalence in blood in a large school community subject to a Covid-19 outbreak: a cross-sectional study. Clinical Infectious Diseases. 2020; ciaa955. pmid:32649743
  21. 21. Zhao J, Yuan Q, Wang H, Liu W, Liao X, Su Y, et al. Antibody responses to SARS-CoV-2 in patients of novel coronavirus disease 2019. Clin Infect Dis. [cited 24 Jul 2020]. pmid:32221519
  22. 22. Candel González FJ, Viñuela-Prieto JM, González del Castillo J, Barreiro García P, Fragiel Saavedra M, Hernández Píriz A, et al. Utility of lateral flow tests in SARS-CoV-2 infection monitorization. Rev Esp Quimioter. 2020 [cited 1 Aug 2020]. pmid:32492991
  23. 23. Bonelli F, Sarasini A, Zierold C, Calleri M, Bonetti A, Vismara C, et al. Clinical and Analytical Performance of an Automated Serological Test That Identifies S1/S2-Neutralizing IgG in COVID-19 Patients Semiquantitatively. Journal of Clinical Microbiology. 2020;58. pmid:32580948
  24. 24. Favresse J, Eucher C, Elsen M, Tré-Hardy M, Dogné J-M, Douxfils J. Clinical Performance of the Elecsys Electrochemiluminescent Immunoassay for the Detection of SARS-CoV-2 Total Antibodies. Clin Chem. [cited 24 Jul 2020]. pmid:32484887
  25. 25. Steiner DJ, Cognetti JS, Luta EP, Klose AM, Bucukovski J, Bryan MR, et al. Array-based analysis of SARS-CoV-2, other coronaviruses, and influenza antibodies in convalescent COVID-19 patients. Biosensors and Bioelectronics. 2020;169: 112643. pmid:33007615
  26. 26. Jääskeläinen A, Kuivanen S, Kekäläinen E, Ahava M, Loginov R, Kallio-Kokko H, et al. Performance of six SARS-CoV-2 immunoassays in comparison with microneutralisation. Journal of Clinical Virology. 2020;129: 104512. pmid:32563180
  27. 27. Meyer B, Torriani G, Yerly S, Mazza L, Calame A, Arm-Vernez I, et al. Validation of a commercially available SARS-CoV-2 serological immunoassay. Clinical Microbiology and Infection. 2020;26: 1386–1394. pmid:32603801
  28. 28. Stringhini S, Wisniak A, Piumatti G, Azman AS, Lauer SA, Baysson H, et al. Seroprevalence of anti-SARS-CoV-2 IgG antibodies in Geneva, Switzerland (SEROCoV-POP): a population-based study. The Lancet. 2020;396: 313–319. pmid:32534626
  29. 29. Ng DL, Goldgof GM, Shy BR, Levine AG, Balcerek J, Bapat SP, et al. SARS-CoV-2 seroprevalence and neutralizing activity in donor and patient blood. Nature Communications. 2020;11: 4698. pmid:32943630
  30. 30. Rosenberg ES, Tesoriero JM, Rosenthal EM, Chung R, Barranco MA, Styer LM, et al. Cumulative incidence and diagnosis of SARS-CoV-2 infection in New York. Ann Epidemiol. 2020 [cited 24 Jul 2020]. pmid:32648546
  31. 31. Cameron A, Porterfield CA, Byron LD, Wang J, Pearson Z, Bohrhunter JL, et al. A Multiplex Microsphere IgG Assay for SARS-CoV-2 Using ACE2-Mediated Inhibition as a Surrogate for Neutralization. Journal of Clinical Microbiology. 2021;59. pmid:33139422
  32. 32. den Hartog G, Schepp RM, Kuijer M, GeurtsvanKessel C, van Beek J, Rots N, et al. SARS-CoV-2–Specific Antibody Detection for Seroepidemiology: A Multiplex Analysis Approach Accounting for Accurate Seroprevalence. J Infect Dis. 2020;222: 1452–1461. pmid:32766833
  33. 33. Shrock E, Fujimura E, Kula T, Timms RT, Lee I-H, Leng Y, et al. Viral epitope profiling of COVID-19 patients reveals cross-reactivity and correlates of severity. Science. 2020 [cited 12 Oct 2020]. pmid:32994364
  34. 34. Pisanic N, Randad PR, Kruczynski K, Manabe YC, Thomas DL, Pekosz A, et al. COVID-19 Serology at Population Scale: SARS-CoV-2-Specific Antibody Responses in Saliva. Journal of Clinical Microbiology. 2020;59. pmid:33067270
  35. 35. Yonker LM, Neilan AM, Bartsch Y, Patel AB, Regan J, Arya P, et al. Pediatric Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2): Clinical Presentation, Infectivity, and Immune Responses. The Journal of Pediatrics. 2020; S0022347620310234. pmid:32827525
  36. 36. Fotis CF, Meimetis N, Tsolakos N, Politou M, Akinosoglou K, Pliaka V, et al. Accurate SARS-CoV-2 seroprevalence surveys require robust multi-antigen assays. medRxiv. 2020; 2020.09.09.20191122.
  37. 37. Rudberg A-S, Havervall S, Månberg A, Jernbom Falk A, Aguilera K, Ng H, et al. SARS-CoV-2 exposure, symptoms and seroprevalence in healthcare workers in Sweden. Nature Communications. 2020;11: 5064. pmid:33033249
  38. 38. 2020. “xMAP® SARS-CoV-2 Antibody Testing.” Luminex Corporation.
  39. 39. Xu X, Sun J, Nie S, Li H, Kong Y, Liang M, et al. Seroprevalence of immunoglobulin M and G antibodies against SARS-CoV-2 in China. Nat Med. 2020 [cited 24 Jul 2020]. pmid:32504052
  40. 40. Naranbhai V, Chang CC, Beltran WFG, Miller TE, Astudillo MG, Villalba JA, et al. High seroprevalence of anti-SARS-CoV-2 antibodies in Chelsea, Massachusetts. J Infect Dis. 2020. pmid:32906151
  41. 41. Fischer B, Knabbe C, Vollmer T. SARS-CoV-2 IgG seroprevalence in blood donors located in three different federal states, Germany, March to June 2020. Euro Surveill. 2020;25. pmid:32700672
  42. 42. Dacosta-Urbieta A, Rivero-Calle I, Pardo-Seco J, Redondo-Collazo L, Salas A, Gómez-Rial J, et al. Seroprevalence of SARS-CoV-2 Among Pediatric Healthcare Workers in Spain. Front Pediatr. 2020;8: 547. pmid:33042908
  43. 43. Pan Y, Li X, Yang G, Fan J, Tang Y, Hong X, et al. Seroprevalence of SARS-CoV-2 immunoglobulin antibodies in Wuhan, China: part of the city-wide massive testing campaign. Clin Microbiol Infect. 2020 [cited 12 Oct 2020]. pmid:33035672
  44. 44. Barzin A, Schmitz JL, Rosin S, Sirpal R, Almond M, Robinette C, et al. SARS-CoV-2 Seroprevalence among a Southern U.S. Population Indicates Limited Asymptomatic Spread under Physical Distancing Measures. mBio. 2020;11. pmid:32994333
  45. 45. Murhekar MV, Bhatnagar T, Selvaraju S, Rade K, Saravanakumar V, Vivian Thangaraj JW, et al. Prevalence of SARS-CoV-2 infection in India: Findings from the national serosurvey, May-June 2020. Indian J Med Res. 2020;152: 48–60. pmid:32952144
  46. 46. McLaughlin CC, Doll MK, Morrison KT, McLaughlin WL, O’Connor T, Sholukh AM, et al. High Community SARS-CoV-2 Antibody Seroprevalence in a Ski Resort Community, Blaine County, Idaho, US. Preliminary Results. medRxiv. 2020. pmid:32743610
  47. 47. Egger M, Bundschuh C, Wiesinger K, Gabriel C, Clodi M, Mueller T, et al. Comparison of the Elecsys® Anti-SARS-CoV-2 immunoassay with the EDITM enzyme linked immunosorbent assays for the detection of SARS-CoV-2 antibodies in human plasma. Clin Chim Acta. 2020;509: 18–21. pmid:32485155
  48. 48. Kohmer N, Westhaus S, Rühl C, Ciesek S, Rabenau HF. Brief clinical evaluation of six high-throughput SARS-CoV-2 IgG antibody assays. Journal of Clinical Virology. 2020;129: 104480. pmid:32505777
  49. 49. Krüttgen A, Cornelissen CG, Dreher M, Hornef M, Imöhl M, Kleines M. Comparison of four new commercial serologic assays for determination of SARS-CoV-2 IgG. Journal of Clinical Virology. 2020;128: 104394. pmid:32416599
  50. 50. Lassaunière R, Frische A, Harboe ZB, Nielsen AC, Fomsgaard A, Krogfelt KA, et al. Evaluation of nine commercial SARS-CoV-2 immunoassays. medRxiv. 2020; 2020.04.09.20056325.
  51. 51. Lippi G, Salvagno GL, Pegoraro M, Militello V, Caloi C, Peretti A, et al. Assessment of immune response to SARS-CoV-2 with fully automated MAGLUMI 2019-nCoV IgG and IgM chemiluminescence immunoassays. Clinical Chemistry and Laboratory Medicine (CCLM). 2020;58: 1156–1159. pmid:32301750
  52. 52. Meschi S, Colavita F, Bordi L, Matusali G, Lapa D, Amendola A, et al. Performance evaluation of Abbott ARCHITECT SARS-CoV-2 IgG immunoassay in comparison with indirect immunofluorescence and virus microneutralization test. J Clin Virol. 2020;129: 104539. pmid:32679298
  53. 53. Montesinos I, Gruson D, Kabamba B, Dahma H, Van den Wijngaert S, Reza S, et al. Evaluation of two automated and three rapid lateral flow immunoassays for the detection of anti-SARS-CoV-2 antibodies. J Clin Virol. 2020;128: 104413. pmid:32403010
  54. 54. Nakamura A, Sato R, Ando S, Oana N, Nozaki E, Endo H, et al. Seroprevalence of Antibodies to SARS-CoV-2 in Healthcare Workers in Non-epidemic Region: A Hospital Report in Iwate Prefecture, Japan. medRxiv. 2020 [cited 24 Jul 2020].
  55. 55. Nicol T, Lefeuvre C, Serri O, Pivert A, Joubaud F, Dubée V, et al. Assessment of SARS-CoV-2 serological tests for the diagnosis of COVID-19 through the evaluation of three immunoassays: Two automated immunoassays (Euroimmun and Abbott) and one rapid lateral flow immunoassay (NG Biotech). Journal of Clinical Virology. 2020;129: 104511. pmid:32593133
  56. 56. Okba NMA, Müller MA, Li W, Wang C, GeurtsvanKessel CH, Corman VM, et al. Severe Acute Respiratory Syndrome Coronavirus 2-Specific Antibody Responses in Coronavirus Disease Patients. Emerging Infect Dis. 2020;26: 1478–1488. pmid:32267220
  57. 57. Plebani M, Padoan A, Negrini D, Carpinteri B, Sciacovelli L. Diagnostic performances and thresholds: The key to harmonization in serological SARS-CoV-2 assays? Clin Chim Acta. 2020;509: 1–7. pmid:32485157
  58. 58. Tré-Hardy M, Wilmet A, Beukinga I, Dogné J-M, Douxfils J, Blairon L. Validation of a chemiluminescent assay for specific SARS-CoV-2 antibody. Clin Chem Lab Med. 2020;58: 1357–1364. pmid:32447328
  59. 59. Tang MS, Hock KG, Logsdon NM, Hayes JE, Gronowski AM, Anderson NW, et al. Clinical Performance of Two SARS-CoV-2 Serologic Assays. Clin Chem. [cited 24 Jul 2020]. pmid:32402061
  60. 60. Lin D, Liu L, Zhang M, Hu Y, Yang Q, Guo J, et al. Evaluations of the serological test in the diagnosis of 2019 novel coronavirus (SARS-CoV-2) infections during the COVID-19 outbreak. Eur J Clin Microbiol Infect Dis. 2020 [cited 12 Oct 2020]. pmid:32681308
  61. 61. Luchsinger LL, Ransegnola B, Jin D, Muecksch F, Weisblum Y, Bao W, et al. Serological Assays Estimate Highly Variable SARS-CoV-2 Neutralizing Antibody Activity in Recovered COVID19 Patients. Journal of Clinical Microbiology. 2020 [cited 12 Oct 2020]. pmid:32577675
  62. 62. McAloose D, Laverack M, Wang L, Killian ML, Caserta LC, Yuan F, et al. From People to Panthera: Natural SARS-CoV-2 Infection in Tigers and Lions at the Bronx Zoo. mBio. 2020;11. pmid:33051368
  63. 63. Palmer MV, Martins M, Falkenberg S, Buckley A, Caserta LC, Mitchell PK, et al. Susceptibility of white-tailed deer (Odocoileus virginianus) to SARS-CoV-2. bioRxiv. 2021; 2021.01.13.426628.
  64. 64. Wagner B, Hillegas JM, Babasyan S. Monoclonal antibodies to equine CD23 identify the low-affinity receptor for IgE on subpopulations of IgM+ and IgG1+ B-cells in horses. Veterinary Immunology and Immunopathology. 2012;146: 125–134. pmid:22405681
  65. 65. Wimer CL, Schnabel CL, Perkins G, Babasyan S, Freer H, Stout AE, et al. The deletion of the ORF1 and ORF71 genes reduces virulence of the neuropathogenic EHV-1 strain Ab4 without compromising host immunity in horses. PLOS ONE. 2018;13: e0206679. pmid:30440016
  66. 66. Wagner B, Freer H, Rollins A, Erb HN. A fluorescent bead-based multiplex assay for the simultaneous detection of antibodies to B. burgdorferi outer surface proteins in canine serum. Veterinary Immunology and Immunopathology. 2011;140: 190–198. pmid:21208663
  67. 67. 2020 “Independent Evaluations of COVID-19 Serological Tests.” US Food and Drug Administration.
  68. 68. Long Q-X, Tang X-J, Shi Q-L, Li Q, Deng H-J, Yuan J, et al. Clinical and immunological assessment of asymptomatic SARS-CoV-2 infections. Nature Medicine. 2020; 1–5. pmid:32555424
  69. 69. Faustini SE, Jossi SE, Perez-Toledo M, Shields AM, Allen JD, Watanabe Y, et al. Detection of antibodies to the SARS-CoV-2 spike glycoprotein in both serum and saliva enhances detection of infection. medRxiv. 2020 [cited 15 Oct 2020]. pmid:32588002
  70. 70. Seow J, Graham C, Merrick B, Acors S, Pickering S, Steel KJA, et al. Longitudinal observation and decline of neutralizing antibody responses in the three months following SARS-CoV-2 infection in humans. Nature Microbiology. 2020;5: 1598–1607. pmid:33106674
  71. 71. Beaudoin-Bussières G, Laumaea A, Anand SP, Prévost J, Gasser R, Goyette G, et al. Decline of Humoral Responses against SARS-CoV-2 Spike in Convalescent Individuals. mBio. 2020;11. pmid:33067385
  72. 72. Crawford KHD, Dingens AS, Eguia R, Wolf CR, Wilcox N, Logue JK, et al. Dynamics of neutralizing antibody titers in the months after SARS-CoV-2 infection. J Infect Dis. 2020. pmid:33535236
  73. 73. Padoan A, Sciacovelli L, Basso D, Negrini D, Zuin S, Cosma C, et al. IgA-Ab response to spike glycoprotein of SARS-CoV-2 in patients with COVID-19: A longitudinal study. Clinica Chimica Acta. 2020;507: 164–166. pmid:32343948
  74. 74. Guo L, Ren L, Yang S, Xiao M, Chang D, Yang F, et al. Profiling Early Humoral Response to Diagnose Novel Coronavirus Disease (COVID-19). Clin Infect Dis. 2020;71: 778–785. pmid:32198501
  75. 75. Wagner B, Freer H. Development of a bead-based multiplex assay for simultaneous quantification of cytokines in horses. Veterinary Immunology and Immunopathology. 2009;127: 242–248. pmid:19027964
  76. 76. Perkins G, Babasyan S, Stout AE, Freer H, Rollins A, Wimer CL, et al. Intranasal IgG4/7 antibody responses protect horses against equid herpesvirus-1 (EHV-1) infection including nasal virus shedding and cell-associated viremia. Virology. 2019;531: 219–232. pmid:30928700
  77. 77. Schnabel CL, Babasyan S, Rollins A, Freer H, Wimer CL, Perkins GA, et al. An Equine Herpesvirus Type 1 (EHV-1) Ab4 Open Reading Frame 2 Deletion Mutant Provides Immunity and Protection from EHV-1 Infection and Disease. Journal of Virology. 2019;93. pmid:31462575
  78. 78. Dobaño C, Santano R, Jiménez A, Vidal M, Chi J, Rodrigo Melero N, et al. Immunogenicity and crossreactivity of antibodies to the nucleocapsid protein of SARS-CoV-2: utility and limitations in seroprevalence and immunity studies. Translational Research. 2021;232: 60–74. pmid:33582244