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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

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., Highlights • There is B cell immunoglobulin sequence expansion and mutation 7 days after vaccination. • There is sequence convergence between participants 14 and 21 days after vaccination with a common antigen. • These properties allow de novo identification of vaccine-specific immunoglobulin sequence clusters. The B cell repertoire is a diverse system that adapts in response to infection/vaccination to protect against disease. Next-generation sequencing can be used to study this system at the level of the B cell immunoglobulin sequences, but it is difficult to distinguish the sequences responding to the antigen of interest from background noise. By sequencing both the total and vaccine-specific B cell immunoglobulin repertoire, we show that there are time-limited perturbations in the total repertoire following vaccination. These data were used to develop models for the enrichment of vaccine-specific sequences, which could give insight into the underlying biology of vaccination.

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.