A large-scale database of T-cell receptor beta sequences and binding associations from natural and synthetic exposure to SARS-CoV-2
Sean Nolan, Marissa Vignali, Mark Klinger, Jennifer N. Dines, Ian M. Kaplan, Emily Svejnoha, Tracy Craft, Katie Boland, Mitchell W. Pesesky, Rachel M. Gittelman, Thomas M. Snyder, Christopher J. Gooley, Simona Semprini, Claudio Cerchione, Fabio Nicolini, Massimiliano Mazza, Ottavia M. Delmonte, Kerry Dobbs, Gonzalo Carreño‐Tarragona, Santiago Barrio, Vittorio Sambri, Giovanni Martinelli, Jason D. Goldman, James R. Heath, Luigi D. Notarangelo, Joaquín Martínez‐López, Bryan Howie, Jonathan M. Carlson, Harlan Robins
Abstract
We describe the establishment and current content of the ImmuneCODE™ database, which includes hundreds of millions of T-cell Receptor (TCR) sequences from over 1,400 subjects exposed to or infected with the SARS-CoV-2 virus, as well as over 160,000 high-confidence SARS-CoV-2-associated TCRs. This database is made freely available, and the data contained in it can be used to assist with global efforts to understand the immune response to the SARS-CoV-2 virus and develop new interventions.