# Technologies for High-Throughput Mapping of Antigen Specificity to B-Cell-Receptor Sequence

> **NIH NIH R01** · VANDERBILT UNIVERSITY MEDICAL CENTER · 2024 · $841,663

## Abstract

Project Summary. The human immune system participates in complex interactions with virtually all other
systems in the body. In particular, the B cell component of the adaptive immune response plays a role in
various disease settings, including infectious disease, cancer, autoimmunity, cardiovascular, hematologic,
neurologic diseases, and others. In addition, antibodies (a product of B cells) are effectively used in
diagnostics, therapy, and prevention. Yet, despite decades of antibody discovery efforts, there is still very
limited data linking human antibody sequence to antigen specificity (the preferential recognition of target
antigens by a given antibody). One of the major reasons for such limited data is the fact that even high-
throughput antibody sequence identification methods such as next-generation sequencing (NGS) of B cell
receptor (BCR) sequences are generally decoupled from the process of antibody functional characterization.
As a result, even though there are typically thousands to millions of antibody sequences within a single NGS
dataset, functional information is obtained only for a handful of antibodies against not more than 2-3 target
antigens at a time. To address these significant challenges for current technologies for B cell characterization
and antibody discovery, our group has been focusing on the development of a single-cell technology that, for a
given sample, enables the mapping of antibody sequence to antigen specificity from a single high-throughput
experiment for a large number of antigens and B cells at a time. The technology, LIBRA-seq (LInking B-cell
Receptor to Antigen specificity through sequencing), involves physically mixing a B cell sample with a
(theoretically unlimited) pool of DNA-barcoded antigens, thus transforming B cell-antigen binding into a
“sequenceable event”. In essence, LIBRA-seq offers all of the following features: (a) Characterization of
thousands to tens of thousands of B cells at a time, at the single-cell level; (b) Screening against a large
number of antigens at a time; (c) For each B cell, determination of the paired heavy-light chain BCR sequence;
(d) For each B cell, generation of a high-resolution antigen specificity map. We initially validated LIBRA-seq in
proof-of-concept studies in the context of HIV-1, and subsequently coronavirus, infection. These initial studies
lay the foundation for generalizing the LIBRA-seq technology for application toward diverse antigen targets,
and highlight areas for technology optimization, which will be the focus of this technology development
proposal. In particular, here we propose to optimize LIBRA-seq for generalized application toward a broad
diversity of antigen targets.
 Ultimately, the LIBRA-seq technology will have a long-lasting impact on both basic and applied
immunology, helping revolutionize our understanding of antibody-antigen interactions and leading to the
discovery of novel antibody therapeutics targeting a large variety of disease a...

## Key facts

- **NIH application ID:** 10844639
- **Project number:** 5R01AI175245-02
- **Recipient organization:** VANDERBILT UNIVERSITY MEDICAL CENTER
- **Principal Investigator:** Ivelin Georgiev
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $841,663
- **Award type:** 5
- **Project period:** 2023-05-19 → 2028-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10844639

## Citation

> US National Institutes of Health, RePORTER application 10844639, Technologies for High-Throughput Mapping of Antigen Specificity to B-Cell-Receptor Sequence (5R01AI175245-02). Retrieved via AI Analytics 2026-07-25 from https://api.ai-analytics.org/grant/nih/10844639. Licensed CC0.

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