Predictability of B cell clonal persistence and immunosurveillance in breast cancer

B cells and T cells are important components of the adaptive immune system and mediate anticancer immunity. The T cell landscape in cancer is well characterized, but the contribution of B cells to anticancer immunosurveillance is less well explored. Here we show an integrative analysis of the B cell and T cell receptor repertoire from individuals with metastatic breast cancer and individuals with early breast cancer during neoadjuvant therapy. Using immune receptor, RNA and whole-exome sequencing, we show that both B cell and T cell responses seem to coevolve with the metastatic cancer genomes and mirror tumor mutational and neoantigen architecture. B cell clones associated with metastatic immunosurveillance and temporal persistence were more expanded and distinct from site-specific clones. B cell clonal immunosurveillance and temporal persistence are predictable from the clonal structure, with higher-centrality B cell antigen receptors more likely to be detected across multiple metastases or across time. This predictability was generalizable across other immune-mediated disorders. This work lays a foundation for prioritizing antibody sequences for therapeutic targeting in cancer.

Building Representation Learning Models for Antibody Comprehension

Antibodies are versatile proteins with both the capacity to bind a broad range of targets and a proven track record as some of the most successful therapeutics. However, the development of novel antibody therapeutics is a lengthy and costly process. It is challenging to predict the functional and biophysical properties of antibodies from their amino acid sequence alone, requiring numerous experiments for full characterization. Machine learning, specifically deep representation learning, has emerged as a family of methods that can complement wet lab approaches and accelerate the overall discovery and engineering process. Here, we review advances in antibody sequence representation learning, and how this has improved antibody structure prediction and facilitated antibody optimization. We discuss challenges in the development and implementation of such models, such as the lack of publicly available, well-curated antibody function data and highlight opportunities for improvement. These and future advances in machine learning for antibody sequences have the potential to increase the success rate in developing new therapeutics, resulting in broader access to transformative medicines and improved patient outcomes.

Becoming fluent in proteins

Large language models have emerged as a new compass for navigating the complex landscapes of protein engineering. This issue of Cell Systems features ProGen2 and IgLM-two protein language models (PLMs) that use subtly different approaches to design proteins.

Structural modeling of antibody variable regions using deep learning-progress and perspectives on drug discovery

AlphaFold2 has hallmarked a generational improvement in protein structure prediction. In particular, advances in antibody structure prediction have provided a highly translatable impact on drug discovery. Though AlphaFold2 laid the groundwork for all proteins, antibody-specific applications require adjustments tailored to these molecules, which has resulted in a handful of deep learning antibody structure predictors. Herein, we review the recent advances in antibody structure prediction and relate them to their role in advancing biologics discovery.

Characterisation of the immune repertoire of a humanised transgenic mouse through immunophenotyping and high-throughput sequencing

Immunoglobulin loci-transgenic animals are widely used in antibody discovery and increasingly in vaccine response modelling. In this study, we phenotypically characterised B-cell populations from the Intelliselect® Transgenic mouse (Kymouse) demonstrating full B-cell development competence. Comparison of the naïve B-cell receptor (BCR) repertoires of Kymice BCRs, naïve human, and murine BCR repertoires revealed key differences in germline gene usage and junctional diversification. These differences result in Kymice having CDRH3 length and diversity intermediate between mice and humans. To compare the structural space explored by CDRH3s in each species’ repertoire, we used computational structure prediction to show that Kymouse naïve BCR repertoires are more human-like than mouse-like in their predicted distribution of CDRH3 shape. Our combined sequence and structural analysis indicates that the naïve Kymouse BCR repertoire is diverse with key similarities to human repertoires, while immunophenotyping confirms that selected naïve B-cells are able to go through complete development.

B cell clonal expansion and mutation in the immunoglobulin heavy chain variable domain in response to Pfs230 and Pfs25 malaria vaccines

Malaria transmission-blocking vaccines induce antibodies that target Plasmodium in the mosquito vector. We recently reported that Pfs230 vaccine achieves activity superior to Pfs25 in humans. Here, we describe clonal expansion in the variable region of immunoglobulin heavy chains (VH) of antigen-specific single B cells collected from humans immunised with Pfs230D1-EPA or Pfs25-EPA conjugate vaccines formulated in Alhydrogel®. Based on studies of CD27+ memory B cells following Pfs230 vaccination, clonal expansion and somatic hypermutation was seen in four of five subjects. Pfs25 did not induce sufficient CD27+ cells for sorting; based instead on CD19+ Pfs25-reactive B cells, clonal expansion was only seen in two of five subjects. Clonal expansions and mutations in Pfs230-specific single B cells combined with the enhanced activity of Pfs230 antibodies by complement, might justify the outstanding activity of Pfs230D1 as a TBV candidate.

Deciphering the language of antibodies using self-supervised learning

An individual’s B cell receptor (BCR) repertoire encodes information about past immune responses and potential for future disease protection. Deciphering the information stored in BCR sequence datasets will transform our understanding of disease and enable discovery of novel diagnostics and antibody therapeutics. A key challenge of BCR sequence analysis is the prediction of BCR properties from their amino acid sequence alone. Here, we present an antibody-specific language model, Antibody-specific Bidirectional Encoder Representation from Transformers (AntiBERTa), which provides a contextualized representation of BCR sequences. Following pre-training, we show that AntiBERTa embeddings capture biologically relevant information, generalizable to a range of applications. As a case study, we fine-tune AntiBERTa to predict paratope positions from an antibody sequence, outperforming public tools across multiple metrics. To our knowledge, AntiBERTa is the deepest protein-family-specific language model, providing a rich representation of BCRs. AntiBERTa embeddings are primed for multiple downstream tasks and can improve our understanding of the language of antibodies.

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AntiBERTa is an antibody-specific transformer model for representation learning

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AntiBERTa embeddings capture aspects of antibody function

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Attention maps of AntiBERTa correspond to structural contacts and binding sites

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AntiBERTa can be fine-tuned for state-of-the-art paratope prediction

Understanding antibody function is critical for deciphering the biology of disease and for the discovery of novel therapeutic antibodies. The challenge is the vast diversity of antibody variants compared with the limited labeled data available. We overcome this challenge by using self-supervised learning to train a large antibody-specific language model, followed by transfer learning, to fine-tune the model for predicting information related to antibody function. We initially demonstrate the success of the model by providing leading results in antibody binding site prediction. The model is amenable to further fine-tuning for diverse applications to improve our understanding of antibody function.

Different B cell subpopulations show distinct patterns in their IgH repertoire metrics

Several human B cell subpopulations are recognised in the peripheral blood, which play distinct roles in the humoral immune response. These cells undergo developmental and maturational changes involving VDJ recombination, somatic hypermutation and class switch recombination, altogether shaping their immunoglobulin heavy chain (IgH) repertoire. Here, we sequenced the IgH repertoire of naïve, marginal zone, switched and plasma cells from 10 healthy adults along with matched unsorted and in silico separated CD19⁺ bulk B cells. Using advanced bioinformatic analysis and machine learning, we show that sorted B cell subpopulations are characterised by distinct repertoire characteristics on both the individual sequence and the repertoire level. Sorted subpopulations shared similar repertoire characteristics with their corresponding in silico separated subsets. Furthermore, certain IgH repertoire characteristics correlated with the position of the constant region on the IgH locus. Overall, this study provides unprecedented insight over mechanisms of B cell repertoire control in peripherally circulating B cell subpopulations.

Cross-Reactive SARS-CoV-2 Neutralizing Antibodies From Deep Mining of Early Patient Responses

Passive immunization using monoclonal antibodies will play a vital role in the fight against COVID-19. The recent emergence of viral variants with reduced sensitivity to some current antibodies and vaccines highlights the importance of broad cross-reactivity. This study describes deep-mining of the antibody repertoires of hospitalized COVID-19 patients using phage display technology and B cell receptor (BCR) repertoire sequencing to isolate neutralizing antibodies and gain insights into the early antibody response. This comprehensive discovery approach has yielded a panel of potent neutralizing antibodies which bind distinct viral epitopes including epitopes conserved in SARS-CoV-1. Structural determination of a non-ACE2 receptor blocking antibody reveals a previously undescribed binding epitope, which is unlikely to be affected by the mutations in any of the recently reported major viral variants including B.1.1.7 (from the UK), B.1.351 (from South Africa) and B.1.1.28 (from Brazil). Finally, by combining sequences of the RBD binding and neutralizing antibodies with the B cell receptor repertoire sequencing, we also describe a highly convergent early antibody response. Similar IgM-derived sequences occur within this study group and also within patient responses described by multiple independent studies published previously.

A human monoclonal antibody blocks malaria transmission and defines a highly conserved neutralizing epitope on gametes

Malaria elimination requires tools that interrupt parasite transmission. Here, we characterize B cell receptor responses among Malian adults vaccinated against the first domain of the cysteine-rich 230 kDa gamete surface protein Pfs230, a key protein in sexual stage development of P. falciparum parasites. Among nine Pfs230 human monoclonal antibodies (mAbs) that we generated, one potently blocks transmission to mosquitoes in a complement-dependent manner and reacts to the gamete surface; the other eight show only low or no blocking activity. The structure of the transmission-blocking mAb in complex with vaccine antigen reveals a large discontinuous conformational epitope, specific to domain 1 of Pfs230 and comprising six structural elements in the protein. The epitope is conserved, suggesting the transmission-blocking mAb is broadly functional. This study provides a rational basis to improve malaria vaccines and develop therapeutic antibodies for malaria elimination.

A computational method for immune repertoire mining that identifies novel binders from different clonotypes, demonstrated by identifying anti-pertussis toxoid antibodies

Due to their shared genetic history, antibodies from the same clonotype often bind to the same epitope. This knowledge is used in immune repertoire mining, where known binders are used to search bulk sequencing repertoires to identify new binders. However, current computational methods cannot identify epitope convergence between antibodies from different clonotypes, limiting the sequence diversity of antigen-specific antibodies that can be identified. We describe how the antibody binding site, the paratope, can be used to cluster antibodies with common antigen reactivity from different clonotypes. Our method, paratyping, uses the predicted paratope to identify these novel cross clonotype matches. We experimentally validated our predictions on a pertussis toxoid dataset. Our results show that even the simplest abstraction of the antibody binding site, using only the length of the loops involved and predicted binding residues, is sufficient to group antigen-specific antibodies and provide additional information to conventional clonotype analysis.

Abbreviations: BCR: B-cell receptor; CDR: complementarity-determining region; PTx: pertussis toxoid

Deep Sequencing of B Cell Receptor Repertoires From COVID-19 Patients Reveals Strong Convergent Immune Signatures

Deep sequencing of B cell receptor (BCR) heavy chains from a cohort of 31 COVID-19 patients from the UK reveals a stereotypical naive immune response to SARS-CoV-2 which is consistent across patients. Clonal expansion of the B cell population is also observed and may be the result of memory bystander effects. There was a strong convergent sequence signature across patients, and we identified 1,254 clonotypes convergent between at least four of the COVID-19 patients, but not present in healthy controls or individuals following seasonal influenza vaccination. A subset of the convergent clonotypes were homologous to known SARS and SARS-CoV-2 spike protein neutralizing antibodies. Convergence was also demonstrated across wide geographies by comparison of data sets between patients from UK, USA, and China, further validating the disease association and consistency of the stereotypical immune response even at the sequence level. These convergent clonotypes provide a resource to identify potential therapeutic and prophylactic antibodies and demonstrate the potential of BCR profiling as a tool to help understand patient responses.

Antimalarial antibody repertoire defined by plasma IG proteomics and single B cell IG sequencing

Plasma antimalarial Ab can mediate antiparasite immunity but has not previously been characterized at the molecular level. Here, we develop an innovative strategy to characterize humoral responses by integrating profiles of plasma immunoglobulins (IGs) or Abs with those expressed on B cells as part of the B cell receptor. We applied this strategy to define plasma IG and to determine variable (V) gene usage after vaccination with the Plasmodium falciparum zygote antigen Pfs25. Using proteomic tools coupled with bulk immunosequencing data, we determined human antigen-binding fragment [F(ab')2] peptide sequences from plasma IG of adults who received 4 doses of Pfs25-EPA/Alhydrogel. Specifically, Pfs25 antigen-specific F(ab')2 peptides (Pfs25-IG) were aligned to cDNA sequences of IG heavy (IGH) chain complementarity determining region 3 from a data set generated by total peripheral B cell immunosequencing of the entire vaccinated population. IGHV4 was the most commonly identified IGHV subgroup of Pfs25-IG, a pattern that was corroborated by V heavy/V light chain sequencing of Pfs25-specific single B cells from 5 vaccinees and by matching plasma Pfs25-IG peptides and V-(D)-J sequences of Pfs25-specific single B cells from the same donor. Among 13 recombinant human mAbs generated from IG sequences of Pfs25-specific single B cells, a single IGHV4 mAb displayed strong neutralizing activity, reducing the number of P. falciparum oocysts in infected mosquitoes by more than 80% at 100 μg/mL. Our approach characterizes the human plasma Ab repertoire in response to the Pfs25-EPA/Alhydrogel vaccine and will be useful for studying circulating Abs in response to other vaccines as well as those induced during infections or autoimmune disorders.

Maturation of the Human Immunoglobulin Heavy Chain Repertoire With Age

B cells play a central role in adaptive immune processes, mainly through the production of antibodies. The maturation of the B cell system with age is poorly studied. We extensively investigated age-related alterations of naïve and antigen-experienced immunoglobulin heavy chain (IgH) repertoires. The most significant changes were observed in the first 10 years of life, and were characterized by altered immunoglobulin gene usage and an increased frequency of mutated antibodies structurally diverging from their germline precursors. Older age was associated with an increased usage of downstream IgH constant region genes and fewer antibodies with self-reactive properties. As mutations accumulated with age, the frequency of germline-encoded self-reactive antibodies decreased, indicating a possible beneficial role of self-reactive B cells in the developing immune system. Our results suggest a continuous process of change through childhood across a broad range of parameters characterizing IgH repertoires and stress the importance of using well-selected, age-appropriate controls in IgH studies.

Inferring B cell specificity for vaccines using a Bayesian mixture model

Background

Vaccines have greatly reduced the burden of infectious disease, ranking in their impact on global health second only after clean water. Most vaccines confer protection by the production of antibodies with binding affinity for the antigen, which is the main effector function of B cells. This results in short term changes in the B cell receptor (BCR) repertoire when an immune response is launched, and long term changes when immunity is conferred. Analysis of antibodies in serum is usually used to evaluate vaccine response, however this is limited and therefore the investigation of the BCR repertoire provides far more detail for the analysis of vaccine response.

Results

Here, we introduce a novel Bayesian model to describe the observed distribution of BCR sequences and the pattern of sharing across time and between individuals, with the goal to identify vaccine-specific BCRs. We use data from two studies to assess the model and estimate that we can identify vaccine-specific BCRs with 69% sensitivity.

Conclusion

Our results demonstrate that statistical modelling can capture patterns associated with vaccine response and identify vaccine specific B cells in a range of different data sets. Additionally, the B cells we identify as vaccine specific show greater levels of sequence similarity than expected, suggesting that there are additional signals of vaccine response, not currently considered, which could improve the identification of vaccine specific B cells.

Structurally Mapping Antibody Repertoires

Every human possesses millions of distinct antibodies. It is now possible to analyze this diversity via next-generation sequencing of immunoglobulin genes (Ig-seq). This technique produces large volume sequence snapshots of B-cell receptors that are indicative of the antibody repertoire. In this paper, we enrich these large-scale sequence datasets with structural information. Enriching a sequence with its structural data allows better approximation of many vital features, such as its binding site and specificity. Here, we describe the structural annotation of antibodies pipeline that maps the outputs of large Ig-seq experiments to known antibody structures. We demonstrate the viability of our protocol on five separate Ig-seq datasets covering ca. 35 m unique amino acid sequences from ca. 600 individuals. Despite the great theoretical diversity of antibodies, we find that the majority of sequences coming from such studies can be reliably mapped to an existing structure.

Identification of Antigen-Specific B-Cell Receptor Sequences from the Total B-Cell Repertoire

Advances in next-generation sequencing now allow characterization of the global B-cell receptor (BCR) heavy-chain repertoire at a level that reflects its huge diversity. This technology has provided great insight into the structure of the BCR repertoire and how it responds to specific antigen stimuli. There are numerous potential clinical and research applications of BCR repertoire sequencing, but a major hurdle in the realization of these applications is the identification of the antigen-specific sequences of interest from within the total repertoire. To deconvolute the antigen-specific sequences from total repertoire, either a source of antigen-enriched sequence data is required with which to annotate the total repertoire, or de novo annotation methods must be used based on preconceptions of the features of antigen-specific sequences and their behavior following antigen-specific immune stimulation. We present a review of how these different methods can be applied to identify antigen-specific BCR sequences from the total BCR repertoire.

B-cell receptor repertoire sequencing in patients with primary immunodeficiency: a review

The advent of next-generation sequencing (NGS) now allows a detailed assessment of the adaptive immune system in health and disease. In particular, high-throughput B-cell receptor (BCR) repertoire sequencing provides detailed information about the functionality and abnormalities of the B-cell system. However, it is mostly unknown how the BCR repertoire is altered in the context of primary immunodeficiencies (PID) and whether findings are consistent throughout phenotypes and genotypes. We have performed an extensive literature search of the published work on BCR repertoire sequencing in PID patients, including several forms of predominantly antibody disorders and combined immunodeficiencies. It is somewhat surprising that BCR repertoires, even from severe clinical phenotypes, often show only mild abnormalities and that diversity or immunoglobulin gene segment usage is generally preserved to some extent. Despite the great variety of wet laboratory and analytical methods that were used in the different studies, several findings are common to most investigated PIDs, such as the increased usage of gene segments that are associated with self-reactivity. These findings suggest that BCR repertoire characteristics may be used to assess the functionality of the B-cell compartment irrespective of the underlying defect. With the use of NGS approaches, there is now the opportunity to apply BCR repertoire sequencing to multiple patients and explore the PID BCR repertoire in more detail. Ultimately, using BCR repertoire sequencing in translational research could aid the management of PID patients by improving diagnosis, estimating functionality of the immune system and improving assessment of prognosis.

How B-Cell Receptor Repertoire Sequencing Can Be Enriched with Structural Antibody Data

Next-generation sequencing of immunoglobulin gene repertoires (Ig-seq) allows the investigation of large-scale antibody dynamics at a sequence level. However, structural information, a crucial descriptor of antibody binding capability, is not collected in Ig-seq protocols. Developing systematic relationships between the antibody sequence information gathered from Ig-seq and low-throughput techniques such as X-ray crystallography could radically improve our understanding of antibodies. The mapping of Ig-seq datasets to known antibody structures can indicate structurally, and perhaps functionally, uncharted areas. Furthermore, contrasting naïve and antigenically challenged datasets using structural antibody descriptors should provide insights into antibody maturation. As the number of antibody structures steadily increases and more and more Ig-seq datasets become available, the opportunities that arise from combining the two types of information increase as well. Here, we review how these data types enrich one another and show potential for advancing our knowledge of the immune system and improving antibody engineering.

B-cell repertoire dynamics after sequential hepatitis B vaccination and evidence for cross-reactive B-cell activation

BACKGROUND

A diverse B-cell repertoire is essential for recognition and response to infectious and vaccine antigens. High-throughput sequencing of B-cell receptor (BCR) genes can now be used to study the B-cell repertoire at great depth and may shed more light on B-cell responses than conventional immunological methods. Here, we use high-throughput BCR sequencing to provide novel insight into B-cell dynamics following a primary course of hepatitis B vaccination.

METHODS

Nine vaccine-naïve participants were administered three doses of hepatitis B vaccine (months 0, 1, and 2 or 7). High-throughput Illumina sequencing of the total BCR repertoire was combined with targeted sequencing of sorted vaccine antigen-enriched B cells to analyze the longitudinal response of both the total and vaccine-specific repertoire after each vaccine. ELISpot was used to determine vaccine-specific cell numbers following each vaccine.

RESULTS

Deconvoluting the vaccine-specific from total BCR repertoire showed that vaccine-specific sequence clusters comprised <0.1 % of total sequence clusters, and had certain stereotypic features. The vaccine-specific BCR sequence clusters were expanded after each of the three vaccine doses, despite no vaccine-specific B cells being detected by ELISpot after the first vaccine dose. These vaccine-specific BCR clusters detected after the first vaccine dose had distinct properties compared to those detected after subsequent doses; they were more mutated, present at low frequency even prior to vaccination, and appeared to be derived from more mature B cells.

CONCLUSIONS

These results demonstrate the high-sensitivity of our vaccine-specific BCR analysis approach and suggest an alternative view of the B-cell response to novel antigens. In the response to the first vaccine dose, many vaccine-specific BCR clusters appeared to largely derive from previously activated cross-reactive B cells that have low affinity for the vaccine antigen, and subsequent doses were required to yield higher affinity B cells.

LLT1 and CD161 Expression in Human Germinal Centers Promotes B Cell Activation and CXCR4 Downregulation

Germinal centers (GCs) are microanatomical structures critical for the development of high-affinity Abs and B cell memory. They are organized into two zones, light and dark, with coordinated roles, controlled by local signaling. The innate lectin-like transcript 1 (LLT1) is known to be expressed on B cells, but its functional role in the GC reaction has not been explored. In this study, we report high expression of LLT1 on GC-associated B cells, early plasmablasts, and GC-derived lymphomas. LLT1 expression was readily induced via BCR, CD40, and CpG stimulation on B cells. Unexpectedly, we found high expression of the LLT1 ligand, CD161, on follicular dendritic cells. Triggering of LLT1 supported B cell activation, CD83 upregulation, and CXCR4 downregulation. Overall, these data suggest that LLT1–CD161 interactions play a novel and important role in B cell maturation within the GC in humans.

Analysis of B Cell Repertoire Dynamics Following Hepatitis B Vaccination in Humans, and Enrichment of Vaccine-specific Antibody Sequences

Generating a diverse B cell immunoglobulin repertoire is essential for protection against infection. The repertoire in humans can now be comprehensively measured by high-throughput sequencing. Using hepatitis B vaccination as a model, we determined how the total immunoglobulin sequence repertoire changes following antigen exposure in humans, and compared this to sequences from vaccine-specific sorted cells. Clonal sequence expansions were seen 7 days after vaccination, which correlated with vaccine-specific plasma cell numbers. These expansions caused an increase in mutation, and a decrease in diversity and complementarity-determining region 3 sequence length in the repertoire. We also saw an increase in sequence convergence between participants 14 and 21 days after vaccination, coinciding with an increase of vaccine-specific memory cells. These features allowed development of a model for in silico enrichment of vaccine-specific sequences from the total repertoire. Identifying antigen-specific sequences from total repertoire data could aid our understanding B cell driven immunity, and be used for disease diagnostics and vaccine evaluation.

BCR repertoire sequencing: different patterns of B-cell activation after two Meningococcal vaccines

Next-generation sequencing was used to investigate the B-cell receptor heavy chain transcript repertoire of different B-cell subsets (naive, marginal zone (MZ), immunoglobulin M (IgM) memory and IgG memory) at baseline, and of plasma cells (PCs) 7 days following administration of serogroup ACWY meningococcal polysaccharide and protein-polysaccharide conjugate vaccines. Baseline B-cell subsets could be distinguished from each other using a small number of repertoire properties (clonality, mutation from germline and complementarity-determining region 3 (CDR3) length) that were conserved between individuals. However, analyzing the CDR3 amino-acid sequence (which is particularly important for antigen binding) of the baseline subsets showed few sequences shared between individuals. In contrast, day 7 PCs demonstrated nearly 10-fold greater sequence sharing between individuals than the baseline subsets, consistent with the PCs being induced by the vaccine antigen and sharing specificity for a more limited range of epitopes. By annotating PC sequences based on IgG subclass usage and mutation, and also comparing them with the sequences of the baseline cell subsets, we were able to identify different signatures after the polysaccharide and conjugate vaccines. PCs produced after conjugate vaccination were predominantly IgG1, and most related to IgG memory cells. In contrast, after polysaccharide vaccination, the PCs were predominantly IgG2, less mutated and were equally likely to be related to MZ, IgM memory or IgG memory cells. High-throughput B-cell repertoire sequencing thus provides a unique insight into patterns of B-cell activation not possible from more conventional measures of immunogenicity.

In-Depth Assessment of Within-Individual and Inter-Individual Variation in the B Cell Receptor Repertoire

High-throughput sequencing of the B cell receptor (BCR) repertoire can provide rapid characterization of the B cell response in a wide variety of applications in health, after vaccination and in infectious, inflammatory and immune-driven disease, and is starting to yield clinical applications. However, the interpretation of repertoire data is compromised by a lack of studies to assess the intra and inter-individual variation in the BCR repertoire over time in healthy individuals. We applied a standardized isotype-specific BCR repertoire deep sequencing protocol to a single highly sampled participant, and then evaluated the method in 9 further participants to comprehensively describe such variation. We assessed total repertoire metrics of mutation, diversity, VJ gene usage and isotype subclass usage as well as tracking specific BCR sequence clusters. There was good assay reproducibility (both in PCR amplification and biological replicates), but we detected striking fluctuations in the repertoire over time that we hypothesize may be due to subclinical immune activation. Repertoire properties were unique for each individual, which could partly be explained by a decrease in IgG2 with age, and genetic differences at the immunoglobulin locus. There was a small repertoire of public clusters (0.5, 0.3, and 1.4% of total IgA, IgG, and IgM clusters, respectively), which was enriched for expanded clusters containing sequences with suspected specificity toward antigens that should have been historically encountered by all participants through prior immunization or infection. We thus provide baseline BCR repertoire information that can be used to inform future study design, and aid in interpretation of results from these studies. Furthermore, our results indicate that BCR repertoire studies could be used to track changes in the public repertoire in and between populations that might relate to population immunity against infectious diseases, and identify the characteristics of inflammatory and immunological diseases.

Identification of antigen-specific B cell receptor sequences using public repertoire analysis

High-throughput sequencing allows detailed study of the BCR repertoire postimmunization, but it remains unclear to what extent the de novo identification of Ag-specific sequences from the total BCR repertoire is possible. A conjugate vaccine containing Haemophilus influenzae type b (Hib) and group C meningococcal polysaccharides, as well as tetanus toxoid (TT), was used to investigate the BCR repertoire of adult humans following immunization and to test the hypothesis that public or convergent repertoire analysis could identify Ag-specific sequences. A number of Ag-specific BCR sequences have been reported for Hib and TT, which made a vaccine containing these two Ags an ideal immunological stimulus. Analysis of identical CDR3 amino acid sequences that were shared by individuals in the postvaccine repertoire identified a number of known Hib-specific sequences but only one previously described TT sequence. The extension of this analysis to nonidentical, but highly similar, CDR3 amino acid sequences revealed a number of other TT-related sequences. The anti-Hib avidity index postvaccination strongly correlated with the relative frequency of Hib-specific sequences, indicating that the postvaccination public BCR repertoire may be related to more conventional measures of immunogenicity correlating with disease protection. Analysis of public BCR repertoire provided evidence of convergent BCR evolution in individuals exposed to the same Ags. If this finding is confirmed, the public repertoire could be used for rapid and direct identification of protective Ag-specific BCR sequences from peripheral blood.

Studying the antibody repertoire after vaccination: practical applications

Nearly all licensed vaccines have been developed to confer protection against infectious diseases by stimulating the production of antibodies by B cells, but the nature of a successful antibody response has been difficult to capture. Recent advances in next-generation sequencing (NGS) technology have allowed high-resolution characterization of the antibody repertoire, and of the changes that occur following vaccination. These approaches have yielded important insights into the B cell response, and have raised the possibility of using specific antibody sequences as measures of vaccine immunogenicity. Here, we review recent findings based on antibody repertoire sequencing, and discuss potential applications of these new technologies and of the analyses of the increasing volume of antibody sequence data in the context of vaccine development.