Antibody display libraries for precision screening of antibody immune responses to SARS-CoV-2

PROJECT SUMMARY/ABSTRACT This project will determine the antibody-based immune features in COVID-19 patients to accelerate thedevelopment of new medical interventions. SARS-CoV-2 causes asymptomatic or mild disease in manyindividuals, demonstrating that an effective human immune response can fully prevent disease. However, itremains unclear what immune response features are associated with protection from disease. To address thisquestion, here we will analyze comprehensive antibody immune responses in COVID-19 patients and determinehow the molecular features of antibody immunity correlate with COVID-19 symptom severity. First, we will immortalize antibody immune libraries from COVID-19 patient cohorts into yeast display librariesfor comprehensive in vitro functional screening. B cell samples from COVID-19 patients will be isolated andemulsified as single cells for native antibody DNA recovery, and antibody genes will be transformed into a yeastFab display platform for repertoire-scale antibody functional analyses. Antibodies will be screened for binding tothe SARS-CoV-2 spike trimer, a dominant neutralization target, and also for inhibition of ACE2 binding to mapneutralizing antibodies in human immune responses. We will also mine our renewable antibody immune libraries for broader features that may correlate withCOVID-19 disease severity. We will investigate antibodies targeting broad SARS-CoV-2 antigens and epitopes,including multiple epitopes on the spike trimer protein (such as the receptor binding domain, RBD, the N terminaldomain, NTD, and the S1 region) and internal viral proteins (e.g., nucleocapsid protein). We will also map themolecular features of single B cell responses (e.g. affinity, competition-based epitope mapping, and differentialbinding to different spike protein conformations) to comprehensively track anti-SARS-CoV-2 molecular immunityin a human cohort. We will analyze the genetic features of each antibody clone to help elucidate the balance ofneutralizing vs. non-neutralizing antibodies as potential disease correlates. Finally, we will perform large-scale data mining of the antibody repertoires from each patient population toidentify key molecular features that may distinguish mild and severe SARS-CoV-2 infections. These newmolecular-scale correlates and potential biomarkers will improve basic and clinical understanding to advanceCOVID-19 preventions and therapies. We seek to reveal critical immune-based biomarkers of COVID-19diseases severity and identify new potent antibody drug candidates to treat and prevent COVID-19.