High-Throughput Neutralization and Serology Assays Reveal Correlated but Highly Variable Humoral Immune Responses in a Large Population of Individuals Infected with SARS-CoV-2 in the US between March and August 2020

Abstract

The ability to measure neutralizing antibodies on large scale can be important for understanding features of the natural history and epidemiology of infection, as well as an aid in determining the efficacy of interventions, particularly in outbreaks such as the current severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. Because of the assay's rapid scalability and high efficiency, serology measurements that quantify the presence rather than function of serum antibodies often serve as proxies of immune protection. Here, we report the development of a high-throughput, automated fluorescence-based neutralization assay using SARS-CoV-2 virus to quantify neutralizing antibody activity in patient specimens. We performed large-scale testing of over 19,000 COVID-19 convalescent plasma (CCP) samples from patients who had been infected with SARS-CoV-2 between March and August 2020 across the United States. The neutralization capacity of the samples was moderately correlated with serological measurements of anti-receptor-binding domain (RBD) IgG levels. The neutralizing antibody levels within these convalescent-phase serum samples were highly variable against the original USA-WA1/2020 strain with almost 10% of individuals who had had PCR-confirmed SARS-CoV-2 infection having no detectable antibodies either by serology or neutralization, and ~1/3 having no or low neutralizing activity. Discordance between neutralization and serology measurements was mainly due to the presence of non-IgG RBD isotypes. Meanwhile, natural infection with the earliest SARS-CoV-2 strain USA-WA1/2020 resulted in weaker neutralization of subsequent B.1.1.7 (alpha) and the B.1.351 (beta) variants, with 88% of samples having no activity against the BA.1 (omicron) variant. IMPORTANCE The ability to directly measure neutralizing antibodies on live SARS-CoV-2 virus in individuals can play an important role in understanding the efficacy of therapeutic interventions or vaccines. In contrast to functional neutralization assays, serological assays only quantify the presence of antibodies as a proxy of immune protection. Here, we have developed a high-throughput, automated neutralization assay for SARS-CoV-2 and measured the neutralizing activity of ~19,000 COVID-19 convalescent plasma (CCP) samples collected across the United States between March and August of 2020. These data were used to support the FDA's interpretation of CCP efficacy in patients with SARS-CoV-2 infection and their issuance of emergency use authorization of CCP in 2020.

Keywords: SARS-CoV-2; neutralizing antibodies; serology.

FIG 1

Workflow and validation of high-throughput fluorescent SARS-CoV-2 neutralization assay. (a) Overview of high-throughput neutralization assay for measuring neutralizing antibody titers against SARS-CoV-2. Patient serum samples are serially diluted and mixed with SARS-CoV-2. VeroE6/TMPRSS2 cells are then infected with the virus/serum mixture. The infected cells are fixed, immunostained and imaged. (b) Representative immunofluorescence images of VeroE6/TMPRSS2 cells infected with SARS-CoV-2 in the absence (left) or presence (right) of a positive neutralizing serum (right), 40 h postinfection. Scale bar, 200 μm. (c) Exemplary sigmoidal dose response curves across a dilution series of 4 different serum samples. The data are presented in mean ± SD (n = 3, technical replicates) of one representative experiment. (d) Correlation between ID₅₀ values of the PRNT and neutralizing assays. The Pearson correlation efficiency R² is shown. (e) Neutralization curves for the anti-RBD human IgG neutralizing monoclonal antibody in PRNT and neutralizing assays. The data are presented in mean ± SD (n = 3, independent experiments).

FIG 2

Workflow and validation of high-throughput anti-RBD and anti-N protein serology assay. (a) Overview of high-throughput serology assay for measuring anti-RBD and anti-N antibodies. Precoated SARS-CoV-2 RBD or nucleocapsid antigens capture IgG antibodies from the patient sample. Secondary anti-IgG antibodies that are conjugated to horseradish peroxidase (HRP) bind to the captured primary IgG antibodies and react with an absorbance-based substrate to generate a signal. (b) Representative standard curves of the anti-SARS-CoV-1-spike control antibody (CR3022) (left) and a patient sample that was previously shown to have a high anti-N IgG level (right) assessed in duplicate. The Pearson correlation efficiency R² values are shown. (c) Day-to-day reproducibility of the anti-RBD (left) and anti-N serology assay (right). Samples from the independent validation set (n = 420) were evaluated on two consecutive days and correlation analysis performed on log-transformed values. Pearson correlation efficiency R² values are shown.

FIG 3

Neutralizing activity and serological analysis of independent validation set (n = 418). (a) Serology of validation set showing proportion and number of samples with positive, indeterminate or negative result for anti-RBD and anti-N IgG antibody. (b) Frequency of samples that are anti-RBD and anti-N IgG antibody positive, indeterminate, and negative among the validation set. (c) Distribution of neutralization ID₅₀ values of the validation set. The left red bar indicates samples with neutralization titers below the limit of detection of the assay (ID₅₀ < 40). Samples with ID₅₀ values that exceeded the last dilution (1:5,120) were plotted as > 5,120. (d) Correlations between the estimated abundance of anti-RBD IgG (left) or Z-score abundance of anti-N IgG (right) and the SARS-CoV-2 neutralization titers, with each point representing an individual sample in the validation set. For visualization purposes, anti-N IgG Z-score abundance values less than or equal to 0 were assigned the value 0.005 in the plot. The nonparametric Spearman correlation coefficients (r_s) are shown. The vertical black dotted lines indicate assay cutoff values for indeterminate and positive samples. The horizontal red dotted line indicates an ID₅₀ value of 40. (e) Neutralization capacity of the validation set against the reference SARS-CoV-2 WA2020/1 strain and three other variants. Each point represents an individual sample in the validation set. Solid lines represent the median titer, and the whiskers show the 95% confidence interval. The red dotted line indicates an ID₅₀ value of 40. **, P < 0.01; ****, P < 0.0001.

FIG 4

Large scale CCP neutralization activity and serological analysis. (a) Serology of 19,729 samples showing proportion and number of samples with positive, indeterminate or negative result for anti-RBD and anti-N IgG antibody. (b) Frequency of samples that are anti-RBD and anti-N IgG antibody positive, indeterminate, and negative among the entire 19,729 CCP sample set. (c) Distribution of neutralization ID₅₀ values of the entire 19,729 CCP sample set. The left red bar indicates samples with neutralization titers below the limit of detection of the assay (ID₅₀ < 40). Samples with ID₅₀ values exceeded the last dilution (1:2,560) were plotted as > 2,560. The black dotted line indicates an ID₅₀ value of 160, which is the FDA recommended cutoff for use in CCP therapy. (d) Correlations between the estimated abundance of anti-RBD IgG (left) or Z-score abundance of anti-N IgG (right) and the SARS-CoV-2 neutralization titers, with each point representing an individual sample in entire 19,729 CCP sample set. For visualization purposes, Z-score abundance of anti-N IgG values less than or equal to 0 were assigned the value 0.005 in the plot. The nonparametric Spearman correlation coefficients (r_s) are shown. The vertical black dotted lines indicate assay cutoff values for indeterminate and positive samples. The horizontal red dotted line indicates an ID₅₀ value of 40. (e) Frequency of samples that are anti-RBD and anti-N IgG antibody positive, indeterminate, and negative among the NA positive samples (ID₅₀ > 40).