Bibliographic Details
| Title: |
ReScan, a Multiplex Diagnostic Pipeline, Pans Human Sera for SARS-CoV-2 Antigens |
| Authors: |
Colin R. Zamecnik, Jayant V. Rajan, Kevin A. Yamauchi, Sabrina A. Mann, Rita P. Loudermilk, Gavin M. Sowa, Kelsey C. Zorn, Bonny D. Alvarenga, Christian Gaebler, Marina Caskey, Mars Stone, Philip J. Norris, Wei Gu, Charles Y. Chiu, Dianna Ng, James R. Byrnes, Xin X. Zhou, James A. Wells, Davide F. Robbiani, Michel C. Nussenzweig, Joseph L. DeRisi, Michael R. Wilson |
| Source: |
Cell Reports Medicine, Vol 1, Iss 7, Pp 100123- (2020) |
| Publisher Information: |
Elsevier, 2020. |
| Publication Year: |
2020 |
| Collection: |
LCC:Medicine (General) |
| Subject Terms: |
SARS-CoV-2, serology, phage display, COVID-19, diagnostics, assay development, Medicine (General), R5-920 |
| More Details: |
Summary: Comprehensive understanding of the serological response to SARS-CoV-2 infection is important for both pathophysiologic insight and diagnostic development. Here, we generate a pan-human coronavirus programmable phage display assay to perform proteome-wide profiling of coronavirus antigens enriched by 98 COVID-19 patient sera. Next, we use ReScan, a method to efficiently sequester phage expressing the most immunogenic peptides and print them onto paper-based microarrays using acoustic liquid handling, which isolates and identifies nine candidate antigens, eight of which are derived from the two proteins used for SARS-CoV-2 serologic assays: spike and nucleocapsid proteins. After deployment in a high-throughput assay amenable to clinical lab settings, these antigens show improved specificity over a whole protein panel. This proof-of-concept study demonstrates that ReScan will have broad applicability for other emerging infectious diseases or autoimmune diseases that lack a valid biomarker, enabling a seamless pipeline from antigen discovery to diagnostic using one recombinant protein source. |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
2666-3791 |
| Relation: |
http://www.sciencedirect.com/science/article/pii/S2666379120301658; https://doaj.org/toc/2666-3791 |
| DOI: |
10.1016/j.xcrm.2020.100123 |
| Access URL: |
https://doaj.org/article/fb798e3575304cdbbba3b382901cca64 |
| Accession Number: |
edsdoj.fb798e3575304cdbbba3b382901cca64 |
| Database: |
Directory of Open Access Journals |
