Efficient isolation of rare B cells using next-generation antigen barcoding

Hurtado, Jonathan; Flynn, Claudia; Lee, Jeong Hyun; Salcedo, Eugenia C.; Cottrell, Christopher A.; Skog, Patrick; Nemazee, David; Schief, William R.; Landais, Elise; Sok, Devin; Briney, Bryan

doi:10.1101/2022.06.06.495029

Cited by 5 publications

(3 citation statements)

References 83 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Antigen-selected B cells were then immediately processed on a 10x Genomics Chromium Controller using Next GEM 5’ v2 reagents as previously described. 97 The resulting single cell sequencing libraries (gene expression, feature barcode and VDJ-B) were sequenced on an Illumina NovaSeq 6000 using a 100-cycle SP v1.5 reagent kit. Raw sequencing data was processed with CellRanger 79 and Ab sequences were annotated using the ab[x] toolkit.…”

Section: Methodsmentioning

confidence: 99%

Structural conservation of Lassa virus glycoproteins and recognition by neutralizing antibodies

et al. 2023

View full text Add to dashboard Cite

Section: Methodsmentioning

confidence: 99%

Structural conservation of Lassa virus glycoproteins and recognition by neutralizing antibodies

et al. 2023

View full text Add to dashboard Cite

“…Typically, the frequency of B cells that can be activated by a given immunogen is estimated by FACS analysis of B cells isolated from human donors [31,42]. Cells are selected based on their ability to selectively bind a target immunogen and their BCRs are subsequently identified and characterized.…”

Section: Plos Pathogensmentioning

confidence: 99%

Identification of CDRH3 loops in the B cell receptor repertoire that can be engaged by candidate immunogens

et al. 2023

View full text Add to dashboard Cite

A major goal for the development of vaccines against rapidly mutating viruses, such as influenza or HIV, is to elicit antibodies with broad neutralization capacity. However, B cell precursors capable of maturing into broadly neutralizing antibodies (bnAbs) can be rare in the immune repertoire. Due to the stochastic nature of B cell receptor (BCR) rearrangement, a limited number of third heavy chain complementary determining region (CDRH3) sequences are identical between different individuals. Thus, in order to successfully engage broadly neutralizing antibody precursors that rely on their CDRH3 loop for antigen recognition, immunogens must be able to tolerate sequence diversity in the B cell receptor repertoire across an entire vaccinated population. Here, we present a combined experimental and computational approach to identify BCRs in the human repertoire with CDRH3 loops predicted to be engaged by a target immunogen. For a given antibody/antigen pair, deep mutational scanning was first used to measure the effect of CDRH3 loop substitution on binding. BCR sequences, isolated experimentally or generated in silico, were subsequently evaluated to identify CDRH3 loops expected to be bound by the candidate immunogen. We applied this method to characterize two HIV-1 germline-targeting immunogens and found differences in the frequencies with which they are expected to engage target B cells, thus illustrating how this approach can be used to evaluate candidate immunogens towards B cell precursors engagement and to inform immunogen optimization strategies for more effective vaccine design.

show abstract

“…Over the ensuing decade, next-generation sequencing technology has markedly improved ( Finn and Crowe 2013 ), enabling the first ultra-deep analyses of the human Ab repertoire using billions of sequencing reads ( Briney et al 2019 , Soto et al 2019 ). These increasingly large Ab repertoire datasets have been reused in a variety of novel ways, including mining naturally occurring repertoires for homologs to therapeutic antibodies and uncovering vaccine-targetable precursors of exceptionally broad antiviral antibodies ( Jardine et al 2016 , Krawczyk et al 2019 , Steichen et al 2019 , Hurtado et al 2022 ). One of the most exciting areas of emerging research is the development of sophisticated machine-learning models of antibodies and Ab repertoires.…”

Section: Introductionmentioning

confidence: 99%

AntiRef: reference clusters of human antibody sequences

Briney

2023

Bioinformatics Advances

View full text Add to dashboard Cite

Motivation Genetic biases in the human antibody repertoire result in publicly available antibody sequence datasets that contain many duplicate or highly similar sequences. Available datasets are further skewed by the predominance of studies focused on specific disease states, primarily cancer, autoimmunity, and a small number of infectious diseases that includes HIV, influenza, and SARS-CoV-2. These biases and redundancies are a barrier to rapid similarity searches and reduce the efficiency with which these datasets can be used to train statistical or machine-learning models. Identity-based clustering provides a solution; however, the extremely large size of available antibody sequence datasets makes such clustering operations computationally intensive and potentially out of reach for many scientists and researchers who would benefit from such data. Results Antibody Reference Clusters (AntiRef), which is modeled after UniRef, provides clustered datasets of filtered human antibody sequences. Due to the modular nature of recombined antibody genes, the clustering thresholds used by UniRef for general protein sequences are suboptimal for antibody clustering. Starting with an input dataset of ∼451M full-length, productive human antibody sequences, AntiRef provides reference datasets clustered at a range of antibody-optimized identity thresholds. AntiRef90 is one-third the size of the input dataset and less than half the size of the non-redundant AntiRef100. Availability and implementation AntiRef datasets are available on Zenodo (zenodo.org/record/7474336). All code used to generate AntiRef is available on GitHub (github.com/briney/antiref). The AntiRef versioning scheme (current version: v2022.12.14) refers to the date on which sequences were retrieved from OAS.

show abstract

Efficient isolation of rare B cells using next-generation antigen barcoding

Cited by 5 publications

References 83 publications

Structural conservation of Lassa virus glycoproteins and recognition by neutralizing antibodies

Structural conservation of Lassa virus glycoproteins and recognition by neutralizing antibodies

Identification of CDRH3 loops in the B cell receptor repertoire that can be engaged by candidate immunogens

AntiRef: reference clusters of human antibody sequences

Contact Info

Product

Resources

About