SARS-CoV-2 Antibody Binding and Neutralization in Dried Blood Spot Eluates and Paired Plasma
Year: 2021
Type: article
Abstract: ABSTRACT Widescale assessment of SARS-CoV-2-specific antibodies is critical to understanding population seroprevalence, correlates of protection, and the longevity of vaccine-elicited responses. Most SARS-CoV-2 studies characterize antibody responses in plasma/sera. While reliable and broadly used, these samples pose several logistical restrictions such as requiring venipuncture for collection and cold chain for transportation and storage. Dried blood spots (DBS) overcome these barriers as they can be self-collected by fingerstick and mailed and stored at ambient temperature. Here, we evaluate the suitability of DBS for SARS-CoV-2 antibody assays by comparing several antibody responses between paired plasma and DBS from SARS-CoV-2 convalescent and vaccinated individuals. We found that DBS not only reflected plasma antibody binding by ELISA and epitope profiles using phage-display, but also yielded SARS-CoV-2 neutralization titers that highly correlated with paired plasma. Neutralization measurement was further streamlined by adapting assays to a high-throughput 384-well format. This study supports the adoption of DBS for numerous SARS-CoV-2 binding and neutralization assays.
Source: Microbiology Spectrum
Institutions: University of Washington, Fred Hutch Cancer Center
Language: English
Subfield: Infectious Diseases
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,500
Funders: Howard Hughes Medical Institute, Bill and Melinda Gates Foundation, Simons Foundation, Fred Hutchinson Cancer Research Center, National Institutes of Health, National Institute of General Medical Sciences, National Institute of Allergy and Infectious Diseases, Division of Graduate Education, Office of Research Infrastructure Programs, National Institutes of Health
Awards: High-Performance Compute Cluster for Comprehensive Cancer and Infectious Diseases Research, G4681072085, G5514976981, Training in Cellular and Molecular Biology, Characterizing the broad antibody response to HIV superinfection, Blending deep learning with probabilistic mechanistic models to predict and understand the evolution and function of adaptive immune receptors, Host Defense Training in Allergy and Infectious Diseases
OpenAlex ID: W3205703631
