# Antibody display libraries for precision screening of antibody immune responses to SARS-CoV-2 > **NIH NIH DP5** · UNIVERSITY OF KANSAS LAWRENCE · 2020 · $259,300 ## Abstract Project Summary/Abstract This project will develop a new technological approach for the comprehensive analysis of adaptive immune responses, which holds the potential to catalyze new strategies to prevent and treat disease. Here we will apply immune profiling techniques recently invented by the PI to investigate the mechanisms of Epstein-Barr virus (EBV) adaptive immune control in clinical cohorts of infected patients. EBV is a highly prevalent pathogen infecting >90% of the world’s population. Primary EBV infection often causes infectious mononucleosis (IM) and long-term sequelae include numerous malignancies, lymphoproliferative disorders, and a strong association with multiple sclerosis. No EBV vaccine is approved to date, and the molecular mechanisms of immune protection from EBV-associated diseases are unclear. Unfortunately, prior technical barriers in high- throughput immune profiling methods have prevented a comprehensive understanding of adaptive immune protection against EBV diseases. A technological approach that identifies the critical features of EBV immune protection will advance new solutions for vaccine and therapeutic development. Therefore, we developed an experimental pipeline to enable rapid and cost-effective analysis of B- and T-cell responses to EBV that is scalable to dozens of human patients per experiment. We hypothesize that a comprehensive B- and T-cell analysis of carefully selected patient cohorts that either can or cannot suppress symptomatic infection will reveal function-based correlates of EBV control. To test this hypothesis, we will apply quantitative immune profiling technologies to analyze cryopreserved longitudinal samples from recently completed prospective clinical studies of IM. Patient samples in our cohort span pre- and post-infection through convalescence and encompass the full range of clinical IM severity scores (from 0, asymptomatic primary infection, to 6, essentially bedridden with IM). Immune profile data will be used to establish adaptive immune correlates of IM disease severity. In addition, we will analyze immune responses in apparently immunocompetent patients with chronic active EBV (CAEBV) disease, or patients who do not adequately suppress EBV infection, to gain insight regarding adaptive immune function and dysfunction in CAEBV. Finally, we will develop a new computational toolkit to rapidly identify immune correlates from high-throughput datasets. Successful completion of this project will constitute the first comprehensive functional B- and T-cell receptor analysis in a human clinical cohort. Our efforts will provide a repertoire-scale, mechanistic understanding of adaptive immunity to EBV and suggest new strategies for treatment and prevention of EBV-associated diseases. Our long-term goal is to develop human immune profiling techniques as a platform approach to accelerate the rational design of vaccines and therapeutics against pathogens of high public health importance, beginning wit... ## Key facts - **NIH application ID:** 10199286 - **Project number:** 3DP5OD023118-05S1 - **Recipient organization:** UNIVERSITY OF KANSAS LAWRENCE - **Principal Investigator:** Brandon James DeKosky - **Activity code:** DP5 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2020 - **Award amount:** $259,300 - **Award type:** 3 - **Project period:** 2020-09-01 → 2021-08-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10199286 ## Citation > US National Institutes of Health, RePORTER application 10199286, Antibody display libraries for precision screening of antibody immune responses to SARS-CoV-2 (3DP5OD023118-05S1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10199286. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*