R01AI175245
Project Grant
Overview
Grant Description
Technologies for high-throughput mapping of antigen specificity to B-cell-receptor sequence - 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 areas of biomedical significance.
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 areas of biomedical significance.
Funding Goals
NOT APPLICABLE
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
Nashville,
Tennessee
37203
United States
Geographic Scope
Single Zip Code
Related Opportunity
Analysis Notes
Amendment Since initial award the total obligations have increased 300% from $841,663 to $3,366,652.
Vanderbilt University Medical Center was awarded
High-Throughput Antigen Specificity Mapping with LIBRA-SEQ
Project Grant R01AI175245
worth $3,366,652
from the National Institute of Allergy and Infectious Diseases in May 2023 with work to be completed primarily in Nashville Tennessee United States.
The grant
has a duration of 5 years and
was awarded through assistance program 93.855 Allergy and Infectious Diseases Research.
The Project Grant was awarded through grant opportunity NIH Research Project Grant (Parent R01 Clinical Trial Not Allowed).
Status
(Ongoing)
Last Modified 5/21/26
Period of Performance
5/19/23
Start Date
4/30/28
End Date
Funding Split
$3.4M
Federal Obligation
$0.0
Non-Federal Obligation
$3.4M
Total Obligated
Activity Timeline
Transaction History
Modifications to R01AI175245
Additional Detail
Award ID FAIN
R01AI175245
SAI Number
R01AI175245-846535169
Award ID URI
SAI UNAVAILABLE
Awardee Classifications
Nonprofit With 501(c)(3) IRS Status (Other Than An Institution Of Higher Education)
Awarding Office
75NM00 NIH National Institute of Allergy and Infectious Diseases
Funding Office
75NM00 NIH National Institute of Allergy and Infectious Diseases
Awardee UEI
GYLUH9UXHDX5
Awardee CAGE
7HUA5
Performance District
TN-05
Senators
Marsha Blackburn
Bill Hagerty
Bill Hagerty
Budget Funding
| Federal Account | Budget Subfunction | Object Class | Total | Percentage |
|---|---|---|---|---|
| National Institute of Allergy and Infectious Diseases, National Institutes of Health, Health and Human Services (075-0885) | Health research and training | Grants, subsidies, and contributions (41.0) | $841,663 | 100% |
Modified: 5/21/26