Development and application of nbLIBRA-seq for high-throughput discovery of antigen-specific nanobodies
Leonard, S. E.; Wasdin, P. T.; Webb, K. E.; Amlashi, P. B.; Rathmell, J. C.; Spiller, B. W.; Wadzinski, B. E.; Georgiev, I. S.; Voss, K.
Show abstract
Nanobodies are of high interest in many fields of medicine and biotechnology due to their high stability, tissue penetration, and engineering adaptability compared to monoclonal antibodies. However, nanobody discovery has been limited by technologies that rely on laborious library generation, panning, and clone screening techniques. Here, we demonstrate the successful adaptation of Linking B-Cell Receptor to Antigen Specificity through Sequencing (LIBRA-seq) to immunized alpacas for the rapid identification of antigen-specific nanobodies, derived from heavy-chain antibodies. We validated for nanobody discovery (nbLIBRA-seq) in two different disease settings. First, we identified over 300 antigen-specific heavy chain antibodies against human Transferrin Receptor (TfR1), also known as CD71, from a single alpaca blood sample. Experimental validation showed nbLIBRA-seq was able to identify nanobodies that exhibit specific binding to CD71, with two nanobodies also showing receptor internalization on human T cells. In a separate experiment, we tested the ability of nbLIBRA-seq to perform nanobody discovery with multiple antigens in the antigen screening library. Using fusion glycoproteins from the related respiratory syncytial virus (RSV) and human metapneumovirus (hMPV), 1,125 antigen-specific heavy-chain expressing B cells were recovered via nbLIBRA-seq. A subset of these nanobodies was validated experimentally to possess the target antigen specificity. Together, our results illustrate the potential of nbLIBRA-seq to rapidly identify antigen-specific heavy chain antibodies for a range of diverse targets, a capability that will be of critical significance for the effective and efficient development of novel nanobody-based therapeutics against targets of biomedical significance.
Matching journals
The top 8 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Development of an improved blood-stage malaria vaccine targeting the essential RH5-CyRPA-RIPR invasion complex 95%
- CD8 + T-cell landscape in Indigenous and non-Indigenous people restricted by influenza mortality-associated HLA-A*24:02 allomorph 95%
- Single-Cell Profiling of the Antigen-Specific Response to BNT162b2 SARS-CoV-2 RNA Vaccine 95%
Similar papers in this journal
- Deep repertoire mining uncovers ultra-broad coronavirus neutralizing antibodies targeting multiple epitopes 95%
- Crimean-Congo Hemorrhagic Fever Survivors Elicit Protective Non-Neutralizing Antibodies that Target 11 Overlapping Regions on Viral Glycoprotein GP38 95%
- Pre-existing immunity modulates responses to mRNA boosters 95%
Similar papers in this journal
Similar papers in this journal
- Immunofocusing on the conserved fusion peptide of HIV envelope glycoprotein in rhesus macaques 96%
- Vaccine genetics of IGHV1-2 VRC01-class broadly neutralizing antibody precursor naive human B cells 95%
- Targeting HIV Env immunogens to B cell follicles in non-human primates through immune complex or protein nanoparticle formulations 95%
Similar papers in this journal
- Comprehensive characterization of the antibody responses to SARS-CoV-2 Spike protein after infection and/or vaccination 95%
- Modular DNA Barcoding of Nanobodies Enables Multiplexed in situ Protein Imaging and High-throughput Biomolecule Detection 94%
- Cross-reactive antibodies after SARS-CoV-2 infection and vaccination 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.