High-resolution antibody dynamics of vaccine-induced immune responses

The Assessment of Anti-SARS-CoV-2 Antibodies in Different Vaccine Platforms: A Systematic Review and Meta-Analysis of COVID-19 Vaccine Clinical Trial Studies

BACKGROUND AND OBJECTIVE

The COVID-19 pandemic spread rapidly throughout the world and caused millions of deaths globally. Several vaccines have been developed to control the COVID-19 pandemic and reduce the burden it placed on public health. This study aimed to assess the efficacy of different vaccine platforms in inducing potent antibody responses. Moreover, the seroconversion rate and common side effects of vaccine platforms were evaluated.

METHODS

This meta-analysis included clinical trials of COVID-19 vaccines that met the eligibility criteria. Electronic databases (including PubMed, Scopus, and Web of Science) and Google Scholar search engine were searched for eligible studies. Regarding the methodological heterogeneity between the included studies, we selected a random-effects model. The geometric mean ratio (GMR) was chosen as the effect size for this meta-analysis.

RESULTS

Of the 1838 records identified through screening and after removing duplicate records, the full texts of 1076 records were assessed for eligibility. After the full-text assessment, 56 records were eligible and included in the study. Overall, vaccinated participants had a 150.8-fold increased rate of anti-spike IgG titres compared with the placebo group (GMR = 150.8; 95% CI, 95.9-237.1; I2 = 100%). Moreover, vaccinated participants had a 37.3-fold increased rate of neutralising antibody titres compared with the placebo group (GMR = 37.3; 95% CI, 28.5-48.7; I2 = 99%). The mRNA platform showed a higher rate of anti-spike IgG (GMR = 1263.5; 95% CI, 431.1-3702.8; I2 = 99%), while neutralising antibody titres were higher in the subunit platform (GMR = 53.4; 95% CI, 32.8-87.1; I2 = 99%) than in other platforms. Different vaccine platforms showed different rates of both anti-spike IgG and neutralising antibody titres with interesting results. The seroconversion rate of anti-spike IgG and neutralising antibody titres was more than 98% in the vaccinated participants.

CONCLUSION

Inactivated and subunit vaccines produced a high percentage of neutralising antibodies and had a low common adverse reaction rate compared to other platforms. In this regard, subunit and inactivated vaccines can still be used as the main vaccine platforms for effectively controlling infections with high transmission rates.

An unbiased comparison of immunoglobulin sequence aligners

Adaptive Immune Receptor Repertoire sequencing (AIRR-seq) is critical for our understanding of the adaptive immune system's dynamics in health and disease. Reliable analysis of AIRR-seq data depends on accurate rearranged immunoglobulin (Ig) sequence alignment. Various Ig sequence aligners exist, but there is no unified benchmarking standard representing the complexities of AIRR-seq data, obscuring objective comparisons of aligners across tasks. Here, we introduce GenAIRR, a modular simulation framework for generating Ig sequences alongside their ground truths. GenAIRR realistically simulates the intricacies of V(D)J recombination, somatic hypermutation, and an array of sequence corruptions. We comprehensively assessed prominent Ig sequence aligners across various metrics, unveiling unique performance characteristics for each aligner. The GenAIRR-produced datasets, combined with the proposed rigorous evaluation criteria, establish a solid basis for unbiased benchmarking of immunogenetics computational tools. It sets up the ground for further improving the crucial task of Ig sequence alignment, ultimately enhancing our understanding of adaptive immunity.

Computational detection of antigen-specific B cell receptors following immunization

B cell receptors (BCRs) play a crucial role in recognizing and fighting foreign antigens. High-throughput sequencing enables in-depth sampling of the BCRs repertoire after immunization. However, only a minor fraction of BCRs actively participate in any given infection. To what extent can we accurately identify antigen-specific sequences directly from BCRs repertoires? We present a computational method grounded on sequence similarity, aimed at identifying statistically significant responsive BCRs. This method leverages well-known characteristics of affinity maturation and expected diversity. We validate its effectiveness using longitudinally sampled human immune repertoire data following influenza vaccination and SARS-CoV-2 infections. We show that different lineages converge to the same responding Complementarity Determining Region 3, demonstrating convergent selection within an individual. The outcomes of this method hold promise for application in vaccine development, personalized medicine, and antibody-derived therapeutics.

Investigating the ability of deep learning-based structure prediction to extrapolate and/or enrich the set of antibody CDR canonical forms

Deep learning models have been shown to accurately predict protein structure from sequence, allowing researchers to explore protein space from the structural viewpoint. In this paper we explore whether "novel" features, such as distinct loop conformations can arise from these predictions despite not being present in the training data. Here we have used ABodyBuilder2, a deep learning antibody structure predictor, to predict the structures of ~1.5M paired antibody sequences. We examined the predicted structures of the canonical CDR loops and found that most of these predictions fall into the already described CDR canonical form structural space. We also found a small number of "new" canonical clusters composed of heterogeneous sequences united by a common sequence motif and loop conformation. Analysis of these novel clusters showed their origins to be either shapes seen in the training data at very low frequency or shapes seen at high frequency but at a shorter sequence length. To evaluate explicitly the ability of ABodyBuilder2 to extrapolate, we retrained several models whilst withholding all antibody structures of a specific CDR loop length or canonical form. These "starved" models showed evidence of generalisation across CDRs of different lengths, but they did not extrapolate to loop conformations which were highly distinct from those present in the training data. However, the models were able to accurately predict a canonical form even if only a very small number of examples of that shape were in the training data. Our results suggest that deep learning protein structure prediction methods are unable to make completely out-of-domain predictions for CDR loops. However, in our analysis we also found that even minimal amounts of data of a structural shape allow the method to recover its original predictive abilities. We have made the ~1.5 M predicted structures used in this study available to download at https://doi.org/10.5281/zenodo.10280181.

Current advancements in B-cell receptor sequencing fast-track the development of synthetic antibodies

Synthetic antibodies (Abs) are a class of engineered proteins designed to mimic the functions of natural Abs. These are produced entirely in vitro, eliminating the need for an immune response. As such, synthetic Abs have transformed the traditional methods of raising Abs. Likewise, deep sequencing technologies have revolutionized genomics and molecular biology. These enable the rapid and cost-effective sequencing of DNA and RNA molecules. They have allowed for accurate and inexpensive analysis of entire genomes and transcriptomes. Notably, via deep sequencing it is now possible to sequence a person's entire B-cell receptor immune repertoire, termed BCR sequencing. This procedure allows for big data explorations of natural Abs associated with an immune response. Importantly, the identified sequences have the ability to improve the design and engineering of synthetic Abs by offering an initial sequence framework for downstream optimizations. Additionally, machine learning algorithms can be introduced to leverage the vast amount of BCR sequencing datasets to rapidly identify patterns hidden in big data to effectively make in silico predictions of antigen selective synthetic Abs. Thus, the convergence of BCR sequencing, machine learning, and synthetic Ab development has effectively promoted a new era in Ab therapeutics. The combination of these technologies is driving rapid advances in precision medicine, diagnostics, and personalized treatments.

Prediction of antigen-responding VHH antibodies by tracking the evolution of antibody along the time course of immunization

Antibody maturation is the central function of the adaptive immune response. This process is driven by the repetitive selection of mutations that increase the affinity toward antigens. We hypothesized that a precise observation of this process by high-throughput sequencing along the time course of immunization will enable us to predict the antibodies reacting to the immunized antigen without any additional in vitro screening. An alpaca was immunized with IgG fragments using multiple antigen injections, and the antibody repertoire development was traced via high-throughput sequencing periodically for months. The sequences were processed into clusters, and the antibodies in the 16 most abundant clusters were generated to determine whether the clusters included antigen-binding antibodies. The sequences of most antigen-responsive clusters resembled those of germline cells in the early stages. These sequences were observed to accumulate significant mutations and also showed a continuous sequence turnover throughout the experimental period. The foregoing characteristics gave us >80% successful prediction of clusters composed of antigen-responding VHHs against IgG fragment. Furthermore, when the prediction method was applied to the data from other alpaca immunized with epidermal growth factor receptor, the success rate exceeded 80% as well, confirming the general applicability of the prediction method. Superior to previous studies, we identified the immune-responsive but very rare clusters or sequences from the immunized alpaca without any empirical screening data.

Chimeric vaccine design against the conserved TonB-dependent receptor-like β-barrel domain from the outer membrane tbpA and hpuB proteins of Kingella kingae ATCC 23330

Kingella kingae is a Gram-negative bacterium that primarily causes pediatric infections such as septicemia, endocarditis, and osteoarticular infections. Its virulence is attributed to the outer membrane proteins having implications in bacterial adhesion, invasion, nutrition, and host tissue damage. TonB-dependent receptors (TBDRs) play an important role in nutrition and were previously implicated as vaccine targets in other bacteria. Therefore, we targeted the conserved β-barrel TBDR domain of these proteins for designing a vaccine construct that could elicit humoral and cellular immune responses. We used bioinformatic tools to mine TBDR-containing proteins from K. kingae ATCC 23330 and then predict B- and T-cell epitopes from their conserved β-barrel TDR domain. A chimeric vaccine construct was designed using three antigenic epitopes, covering >98% of the world population and capable of inciting humoral and adaptive immune responses. The final construct elicited a robust immune response. Docking and dynamics simulation showed good binding affinity of the vaccine construct to various receptors of the immune system. Additionally, the vaccine was predicted to be safe and non-allergenic, making it a promising candidate for further development. In conclusion, our study demonstrates the potential of immunoinformatics approaches in designing chimeric vaccines against K. kingae infections. The chimeric vaccine we designed can serve as a blueprint for future experimental studies to develop an effective vaccine against this pathogen, which can serve as a potential strategy to prevent K. kingae infections.

A Customizable Suite of Methods to Sequence and Annotate Cattle Antibodies

Studying the antibody response to infection or vaccination is essential for developing more effective vaccines and therapeutics. Advances in high-throughput antibody sequencing technologies and immunoinformatic tools now allow the fast and comprehensive analysis of antibody repertoires at high resolution in any species. Here, we detail a flexible and customizable suite of methods from flow cytometry, single cell sorting, heavy and light chain amplification to antibody sequencing in cattle. These methods were used successfully, including adaptation to the 10x Genomics platform, to isolate native heavy-light chain pairs. When combined with the Ig-Sequence Multi-Species Annotation Tool, this suite represents a powerful toolkit for studying the cattle antibody response with high resolution and precision. Using three workflows, we processed 84, 96, and 8313 cattle B cells from which we sequenced 24, 31, and 4756 antibody heavy-light chain pairs, respectively. Each method has strengths and limitations in terms of the throughput, timeline, specialist equipment, and cost that are each discussed. Moreover, the principles outlined here can be applied to study antibody responses in other mammalian species.

A somatic hypermutation-based machine learning model stratifies individuals with Crohn's disease and controls

Crohn's disease (CD) is a chronic relapsing-remitting inflammatory disorder of the gastrointestinal tract that is characterized by altered innate and adaptive immune function. Although massively parallel sequencing studies of the T cell receptor repertoire identified oligoclonal expansion of unique clones, much less is known about the B cell receptor (BCR) repertoire in CD. Here, we present a novel BCR repertoire sequencing data set from ileal biopsies from pediatric patients with CD and controls, and identify CD-specific somatic hypermutation (SHM) patterns, revealed by a machine learning (ML) algorithm trained on BCR repertoire sequences. Moreover, ML classification of a different data set from blood samples of adults with CD versus controls identified that V gene usage, clusters, or mutation frequencies yielded excellent results in classifying the disease (F1 > 90%). In summary, we show that an ML algorithm enables the classification of CD based on unique BCR repertoire features with high accuracy.

A scalable model for simulating multi-round antibody evolution and benchmarking of clonal tree reconstruction methods

Affinity maturation (AM) of B cells through somatic hypermutations (SHMs) enables the immune system to evolve to recognize diverse pathogens. The accumulation of SHMs leads to the formation of clonal lineages of antibody-secreting b cells that have evolved from a common naïve B cell. Advances in high-throughput sequencing have enabled deep scans of B cell receptor repertoires, paving the way for reconstructing clonal trees. However, it is not clear if clonal trees, which capture microevolutionary time scales, can be reconstructed using traditional phylogenetic reconstruction methods with adequate accuracy. In fact, several clonal tree reconstruction methods have been developed to fix supposed shortcomings of phylogenetic methods. Nevertheless, no consensus has been reached regarding the relative accuracy of these methods, partially because evaluation is challenging. Benchmarking the performance of existing methods and developing better methods would both benefit from realistic models of clonal lineage evolution specifically designed for emulating B cell evolution. In this paper, we propose a model for modeling B cell clonal lineage evolution and use this model to benchmark several existing clonal tree reconstruction methods. Our model, designed to be extensible, has several features: by evolving the clonal tree and sequences simultaneously, it allows modeling selective pressure due to changes in affinity binding; it enables scalable simulations of large numbers of cells; it enables several rounds of infection by an evolving pathogen; and, it models building of memory. In addition, we also suggest a set of metrics for comparing clonal trees and measuring their properties. Our results show that while maximum likelihood phylogenetic reconstruction methods can fail to capture key features of clonal tree expansion if applied naively, a simple post-processing of their results, where short branches are contracted, leads to inferences that are better than alternative methods.

Antibodies from primary humoral responses modulate the recruitment of naive B cells during secondary responses

Vaccines generate high-affinity antibodies by recruiting antigen-specific B cells to germinal centers (GCs), but the mechanisms governing the recruitment to GCs on secondary challenges remain unclear. Here, using preclinical SARS-CoV and HIV mouse models, we demonstrated that the antibodies elicited during primary humoral responses shaped the naive B cell recruitment to GCs during secondary exposures. The antibodies from primary responses could either enhance or, conversely, restrict the GC participation of naive B cells: broad-binding, low-affinity, and low-titer antibodies enhanced recruitment, whereas, by contrast, the high titers of high-affinity, mono-epitope-specific antibodies attenuated cognate naive B cell recruitment. Thus, the directionality and intensity of that effect was determined by antibody concentration, affinity, and epitope specificity. Circulating antibodies can, therefore, be important determinants of antigen immunogenicity. Future vaccines may need to overcome-or could, alternatively, leverage-the effects of circulating primary antibodies on subsequent naive B cell recruitment.

Memory persistence and differentiation into antibody-secreting cells accompanied by positive selection in longitudinal BCR repertoires

The stability and plasticity of B cell-mediated immune memory ensures the ability to respond to the repeated challenges. We have analyzed the longitudinal dynamics of immunoglobulin heavy chain repertoires from memory B cells, plasmablasts, and plasma cells from the peripheral blood of generally healthy volunteers. We reveal a high degree of clonal persistence in individual memory B cell subsets, with inter-individual convergence in memory and antibody-secreting cells (ASCs). ASC clonotypes demonstrate clonal relatedness to memory B cells, and are transient in peripheral blood. We identify two clusters of expanded clonal lineages with differing prevalence of memory B cells, isotypes, and persistence. Phylogenetic analysis revealed signs of reactivation of persisting memory B cell-enriched clonal lineages, accompanied by new rounds of affinity maturation during proliferation and differentiation into ASCs. Negative selection contributes to both persisting and reactivated lineages, preserving the functionality and specificity of B cell receptors (BCRs) to protect against current and future pathogens.

Phenotypic determinism and stochasticity in antibody repertoires of clonally expanded plasma cells

B cell clonal selection and expansion from a genetically diverse antibody repertoire guides the immune response to a target antigen. It remains unclear if clonal selection and expansion follow any deterministic rules or are stochastic with regards to phenotypic antibody properties such as antigen-binding, affinity, and epitope specificity. We perform the in-depth genotypic and phenotypic characterization of antibody repertoires following immunization in mice. We identify the degree to which clonal expansion is driven by antibody binding, affinity, and epitope specificity and as such may provide greater insight into vaccine-induced immunity.

The capacity of humoral B cell-mediated immunity to effectively respond to and protect against pathogenic infections is largely driven by the presence of a diverse repertoire of polyclonal antibodies in the serum, which are produced by plasma cells (PCs). Recent studies have started to reveal the balance between deterministic mechanisms and stochasticity of antibody repertoires on a genotypic level (i.e., clonal diversity, somatic hypermutation, and germline gene usage). However, it remains unclear if clonal selection and expansion of PCs follow any deterministic rules or are stochastic with regards to phenotypic antibody properties (i.e., antigen-binding, affinity, and epitope specificity). Here, we report on the in-depth genotypic and phenotypic characterization of clonally expanded PC antibody repertoires following protein immunization. We find that clonal expansion drives antigen specificity of the most expanded clones (top ∼10), whereas among the rest of the clonal repertoire antigen specificity is stochastic. Furthermore, we report both on a polyclonal repertoire and clonal lineage level that antibody-antigen binding affinity does not correlate with clonal expansion or somatic hypermutation. Last, we provide evidence for convergence toward targeting dominant epitopes despite clonal sequence diversity among the most expanded clones. Our results highlight the extent to which clonal expansion can be ascribed to antigen binding, affinity, and epitope specificity, and they have implications for the assessment of effective vaccines.

Phylogenetic analysis of migration, differentiation, and class switching in B cells

B cells undergo rapid mutation and selection for antibody binding affinity when producing antibodies capable of neutralizing pathogens. This evolutionary process can be intermixed with migration between tissues, differentiation between cellular subsets, and switching between functional isotypes. B cell receptor (BCR) sequence data has the potential to elucidate important information about these processes. However, there is currently no robust, generalizable framework for making such inferences from BCR sequence data. To address this, we develop three parsimony-based summary statistics to characterize migration, differentiation, and isotype switching along B cell phylogenetic trees. We use simulations to demonstrate the effectiveness of this approach. We then use this framework to infer patterns of cellular differentiation and isotype switching from high throughput BCR sequence datasets obtained from patients in a study of HIV infection and a study of food allergy. These methods are implemented in the R package dowser, available at https://dowser.readthedocs.io.

B cells produce high affinity antibodies through an evolutionary process of mutation and selection during adaptive immune responses. Migration between tissues, differentiation to cellular subtypes, and switching between different antibody isotypes can be important factors in shaping the role B cells play in response to infection, autoimmune disease, and allergies. B cell receptor (BCR) sequence data has the potential to elucidate important information about these processes. However, there is currently no robust, generalizable framework for making such inferences from BCR sequence data. Here, we develop three parsimony-based summary statistics to characterize migration, differentiation, and isotype switching along B cell phylogenetic trees. We confirm the effectiveness of our approach using simulations and further apply our method to data from patients with HIV and allergy. Our methods are released in the R package dowser: https://dowser.readthedocs.io.

Similarity measurements of B cell receptor repertoire in baseline mice showed spectrum convergence of IgM

BACKGROUND

The B cell receptor (BCR) repertoire is highly diverse among individuals. Poor similarity of the spectrum among inbred baseline mice may limit the ability to discriminate true signals from those involving specific experimental factors. The repertoire similarity of the baseline status lacks intensive measurements.

RESULTS

We measured the repertoire similarity of IgH in blood and spleen samples from untreated BALB/c and C57BL/6J mice to investigate the baseline status of the two inbred strains. The antibody pool was stratified by the isotype of IgA, IgG and IgM. Between individuals, the results showed better convergence of CDR3 and clonal lineage profiles in IgM than in IgA and IgG, and better robustness of somatic mutation networks in IgM than in IgA and IgG. It also showed that the CDR3 clonotypes and clonal lineages shared better in the spleen samples than in the blood samples. The animal batch differences were detected in CDR3 evenness, mutated clonotype proportions, and maximal network degrees. A cut-off of 95% identity in the CDR3 nucleotide sequences was suitable for clonal lineage establishment.

CONCLUSIONS

Our findings reveal a natural landscape of BCR repertoire similarities between baseline mice and provide a solid reference for designing studies of mouse BCR repertoires.

Characterization of human IgM and IgG repertoires in individuals with chronic HIV-1 infection

Advancements in high-throughput sequencing (HTS) of antibody repertoires (Ig-Seq) have unprecedentedly improved our ability to characterize the antibody repertoires on a large scale. However, currently, only a few studies explored the influence of chronic HIV-1 infection on human antibody repertoires and many of them reached contradictory conclusions, possibly limited by inadequate sequencing depth and throughput. To better understand how HIV-1 infection would impact humoral immune system, in this study, we systematically analyzed the differences between the IgM (HIV-IgM) and IgG (HIV-IgG) heavy chain repertoires of HIV-1 infected patients, as well as between antibody repertoires of HIV-1 patients and healthy donors (HH). Notably, the public unique clones accounted for only a negligible proportion between the HIV-IgM and HIV-IgG repertoires libraries, and the diversity of unique clones in HIV-IgG remarkably reduced. In aspect of somatic mutation rates of CDR1 and CDR2, the HIV-IgG repertoire was higher than HIV-IgM. Besides, the average length of CDR3 region in HIV-IgM was significant longer than that in the HH repertoire, presumably caused by the great number of novel VDJ rearrangement patterns, especially a massive use of IGHJ6. Moreover, some of the B cell clonotypes had numerous clones, and somatic variants were detected within the clonotype lineage in HIV-IgG, indicating HIV-1 neutralizing activities. The in-depth characterization of HIV-IgG and HIV-IgM repertoires enriches our knowledge in the profound effect of HIV-1 infection on human antibody repertoires and may have practical value for the discovery of therapeutic antibodies.

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Ultra-deep sequencing of both IgM and IgG repertoires in chronic HIV-1 infection.

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VDJ gene rearrangement patterns can be dramatically changed by HIV-1 infection.

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Multiple mechanisms cause the high complexity of HIV-1-experienced antibodies.

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Discovery of promising neutralizing HIV-1 antibodies from antibody repertoires.

A Pan-Cancer Analysis of Tumor-Infiltrating B Cell Repertoires

Tumor-infiltrating B cells can play an important role in anti-tumor responses but their presence is not well understood. In this study, we extracted the B cell receptor repertoires from 9522 tumor and adjacent non-tumor samples across 28 tumor types in the Cancer Genome Atlas project and performed diversity and network analysis. We identified differences in diversity and network statistics across tumor types and subtypes and observed a trend towards increased clonality in primary tumors compared to adjacent non-tumor tissues. We also found significant associations between the repertoire features and mutation load, tumor stage, and age. Our V-gene usage analysis identified similar V-gene usage patterns in colorectal and endometrial cancers. Lastly, we evaluated the prognostic value of the repertoire features and identified significant associations with survival in seven tumor types. This study warrants further research into better understanding the role of tumor-infiltrating B cells across a wide range of tumor types.

Human B cell lineages associated with germinal centers following influenza vaccination are measurably evolving

The poor efficacy of seasonal influenza virus vaccines is often attributed to pre-existing immunity interfering with the persistence and maturation of vaccine-induced B cell responses. We previously showed that a subset of vaccine-induced B cell lineages are recruited into germinal centers (GCs) following vaccination, suggesting that affinity maturation of these lineages against vaccine antigens can occur. However, it remains to be determined whether seasonal influenza vaccination stimulates additional evolution of vaccine-specific lineages, and previous work has found no significant increase in somatic hypermutation among influenza-binding lineages sampled from the blood following seasonal vaccination in humans. Here, we investigate this issue using a phylogenetic test of measurable immunoglobulin sequence evolution. We first validate this test through simulations and survey measurable evolution across multiple conditions. We find significant heterogeneity in measurable B cell evolution across conditions, with enrichment in primary response conditions such as HIV infection and early childhood development. We then show that measurable evolution following influenza vaccination is highly compartmentalized: while lineages in the blood are rarely measurably evolving following influenza vaccination, lineages containing GC B cells are frequently measurably evolving. Many of these lineages appear to derive from memory B cells. We conclude from these findings that seasonal influenza virus vaccination can stimulate additional evolution of responding B cell lineages, and imply that the poor efficacy of seasonal influenza vaccination is not due to a complete inhibition of vaccine-specific B cell evolution.

Landscapes and dynamic diversifications of B-cell receptor repertoires in COVID-19 patients

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused the pandemic of coronavirus disease 2019 (COVID-19). Great international efforts have been put into the development of prophylactic vaccines and neutralizing antibodies. However, the knowledge about the B cell immune response induced by the SARS-CoV-2 virus is still limited. Here, we report a comprehensive characterization of the dynamics of immunoglobin heavy chain (IGH) repertoire in COVID-19 patients. By using next-generation sequencing technology, we examined the temporal changes in the landscape of the patient's immunological status and found dramatic changes in the IGH within the patient's immune system after the onset of COVID-19 symptoms. Although different patients have distinct immune responses to SARS-CoV-2 infection, by employing clonotype overlap, lineage expansion, and clonotype network analyses, we observed a higher clonotype overlap and substantial lineage expansion of B cell clones 2-3 weeks after the onset of illness, which is of great importance to B-cell immune responses. Meanwhile, for preferences of V gene usage during SARS-CoV-2 infection, IGHV3-74 and IGHV4-34, and IGHV4-39 in COVID-19 patients were more abundant than those of healthy controls. Overall, we present an immunological resource for SARS-CoV-2 that could promote both therapeutic development as well as mechanistic research.

An Analysis of the Effects of Spaceflight and Vaccination on Antibody Repertoire Diversity

Ab repertoire diversity plays a critical role in the host's ability to fight pathogens. CDR3 is partially responsible for Ab-Ag binding and is a significant source of diversity in the repertoire. CDR3 diversity is generated during VDJ rearrangement because of gene segment selection, gene segment trimming and splicing, and the addition of nucleotides. We analyzed the Ab repertoire diversity across multiple experiments examining the effects of spaceflight on the Ab repertoire after vaccination. Five datasets from four experiments were analyzed using rank-abundance curves and Shannon indices as measures of diversity. We discovered a trend toward lower diversity as a result of spaceflight but did not find the same decrease in our physiological model of microgravity in either the spleen or bone marrow. However, the bone marrow repertoire showed a reduction in diversity after vaccination. We also detected differences in Shannon indices between experiments and tissues. We did not detect a pattern of CDR3 usage across the experiments. Overall, we were able to find differences in the Ab repertoire diversity across experimental groups and tissues.

Immune2vec: Embedding B/T Cell Receptor Sequences in ℝ N Using Natural Language Processing

The adaptive branch of the immune system learns pathogenic patterns and remembers them for future encounters. It does so through dynamic and diverse repertoires of T- and B- cell receptors (TCR and BCRs, respectively). These huge immune repertoires in each individual present investigators with the challenge of extracting meaningful biological information from multi-dimensional data. The ability to embed these DNA and amino acid textual sequences in a vector-space is an important step towards developing effective analysis methods. Here we present Immune2vec, an adaptation of a natural language processing (NLP)-based embedding technique for BCR repertoire sequencing data. We validate Immune2vec on amino acid 3-gram sequences, continuing to longer BCR sequences, and finally to entire repertoires. Our work demonstrates Immune2vec to be a reliable low-dimensional representation that preserves relevant information of immune sequencing data, such as n-gram properties and IGHV gene family classification. Applying Immune2vec along with machine learning approaches to patient data exemplifies how distinct clinical conditions can be effectively stratified, indicating that the embedding space can be used for feature extraction and exploratory data analysis.

Functional development of a V3/glycan-specific broadly neutralizing antibody isolated from a case of HIV superinfection

Stimulating broadly neutralizing antibodies (bnAbs) directly from germline remains a barrier for HIV vaccines. HIV superinfection elicits bnAbs more frequently than single infection, providing clues of how to elicit such responses. We used longitudinal antibody sequencing and structural studies to characterize bnAb development from a superinfection case. BnAb QA013.2 bound initial and superinfecting viral Env, despite its probable naive progenitor only recognizing the superinfecting strain, suggesting both viruses influenced this lineage. A 4.15 Å cryo-EM structure of QA013.2 bound to native-like trimer showed recognition of V3 signatures (N301/N332 and GDIR). QA013.2 relies less on CDRH3 and more on framework and CDRH1 for affinity and breadth compared to other V3/glycan-specific bnAbs. Antigenic profiling revealed that viral escape was achieved by changes in the structurally-defined epitope and by mutations in V1. These results highlight shared and novel properties of QA013.2 relative to other V3/glycan-specific bnAbs in the setting of sequential, diverse antigens.

Large-scale analysis of 2,152 Ig-seq datasets reveals key features of B cell biology and the antibody repertoire

Antibody repertoire sequencing enables researchers to acquire millions of B cell receptors and investigate these molecules at the single-nucleotide level. This power and resolution in studying humoral responses have led to its wide applications. However, most of these studies were conducted with a limited number of samples. Given the extraordinary diversity, assessment of these key features with a large sample set is demanded. Thus, we collect and systematically analyze 2,152 high-quality heavy-chain antibody repertoires. Our study reveals that 52 core variable genes universally contribute to more than 99% of each individual's repertoire; a distal interspersed preferences characterize V gene recombination; the number of public clones between two repertoires follows a linear model, and the positive selection dominates at RGYW motif in somatic hypermutations. Thus, this population-level analysis resolves some critical features of the antibody repertoire and may have significant value to the large cadre of scientists.

The dynamics and association of B and T cell receptor repertoires upon antibody response to hepatitis B vaccination in healthy adults

The Hepatitis B (HB) vaccine is efficacious in preventing hepatitis B virus infection. However, the association between antibody response to the HB vaccine and dynamic immune repertoire changes in different cell subsets remains unclear. Nine healthy participants were administered three doses of HB vaccine following the 0, 1, 6 month schedule. Peripheral CD4⁺ T, memory B (MB), naïve B (NB), and plasma cells (PCs) were sorted before vaccination and 7 days following each dose. The complementary determining region 3 of T-cell receptor β (TCRβ) chain and B-cell receptor (BCR) heavy chain (IgG, IgM, IgA) repertoires were analyzed by high-throughput sequencing. All nine participants elicited protective antibody titers to the vaccine at the end of immunization. Compared with the baseline, MB cells showed a significant increase in IgG usage and decreased IgM usage and repertoire diversity at the end of vaccination. TCRβ diversity changes were highly correlated with those of the BCR in MB cells in participants with a faster and robust antibody responses. The percentage of shared clonotypes between NB and MB cells, and MB cells and PCs were much higher than that between NB cells and PCs. The more clonotypes sharing the faster and stronger antibody responses were observed after HB vaccination. These results suggest the integral involvement of MB cells in vaccine immunization. Interaction between CD4⁺ T and MB cells and B cell differentiation may improve antibody response to HB vaccine.

Applications of Machine and Deep Learning in Adaptive Immunity

Adaptive immunity is mediated by lymphocyte B and T cells, which respectively express a vast and diverse repertoire of B cell and T cell receptors and, in conjunction with peptide antigen presentation through major histocompatibility complexes (MHCs), can recognize and respond to pathogens and diseased cells. In recent years, advances in deep sequencing have led to a massive increase in the amount of adaptive immune receptor repertoire data; additionally, proteomics techniques have led to a wealth of data on peptide-MHC presentation. These large-scale data sets are now making it possible to train machine and deep learning models, which can be used to identify complex and high-dimensional patterns in immune repertoires. This article introduces adaptive immune repertoires and machine and deep learning related to biological sequence data and then summarizes the many applications in this field, which span from predicting the immunological status of a host to the antigen specificity of individual receptors and the engineering of immunotherapeutics.

The Interplay between CD27dull and CD27bright B Cells Ensures the Flexibility, Stability, and Resilience of Human B Cell Memory

Memory B cells (MBCs) epitomize the adaptation of the immune system to the environment. We identify two MBC subsets in peripheral blood, CD27^dull and CD27^bright MBCs, whose frequency changes with age. Heavy chain variable region (VH) usage, somatic mutation frequency replacement-to-silent ratio, and CDR3 property changes, reflecting consecutive selection of highly antigen-specific, low cross-reactive antibody variants, all demonstrate that CD27^dull and CD27^bright MBCs represent sequential MBC developmental stages, and stringent antigen-driven pressure selects CD27^dull into the CD27^bright MBC pool. Dynamics of human MBCs are exploited in pregnancy, when 50% of maternal MBCs are lost and CD27^dull MBCs transit to the more differentiated CD27^bright stage. In the postpartum period, the maternal MBC pool is replenished by the expansion of persistent CD27^dull clones. Thus, the stability and flexibility of human B cell memory is ensured by CD27^dull MBCs that expand and differentiate in response to change.

Public Baseline and shared response structures support the theory of antibody repertoire functional commonality

The naïve antibody/B-cell receptor (BCR) repertoires of different individuals ought to exhibit significant functional commonality, given that most pathogens trigger an effective antibody response to immunodominant epitopes. Sequence-based repertoire analysis has so far offered little evidence for this phenomenon. For example, a recent study estimated the number of shared ('public') antibody clonotypes in circulating baseline repertoires to be around 0.02% across ten unrelated individuals. However, to engage the same epitope, antibodies only require a similar binding site structure and the presence of key paratope interactions, which can occur even when their sequences are dissimilar. Here, we search for evidence of geometric similarity/convergence across human antibody repertoires. We first structurally profile naïve ('baseline') antibody diversity using snapshots from 41 unrelated individuals, predicting all modellable distinct structures within each repertoire. This analysis uncovers a high (much greater than random) degree of structural commonality. For instance, around 3% of distinct structures are common to the ten most diverse individual samples ('Public Baseline' structures). Our approach is the first computational method to find levels of BCR commonality commensurate with epitope immunodominance and could therefore be harnessed to find more genetically distant antibodies with same-epitope complementarity. We then apply the same structural profiling approach to repertoire snapshots from three individuals before and after flu vaccination, detecting a convergent structural drift indicative of recognising similar epitopes ('Public Response' structures). We show that Antibody Model Libraries derived from Public Baseline and Public Response structures represent a powerful geometric basis set of low-immunogenicity candidates exploitable for general or target-focused therapeutic antibody screening.

Decrease of Clone Diversity in IgM Repertoires of HBV Chronically Infected Individuals With High Level of Viral Replication

High-throughput antibody sequencing allows in-depth insights into human antibody repertoires. To investigate the characteristics of antibody repertoires in patients with chronic HBV infection, we performed Illumina sequencing and IMGT/HighV-QUEST analysis of B lymphocytes from healthy adults and the HBV carriers with high or low level of viral replication. The comparative study revealed high levels of similarity between the IgM and IgG repertoires of the HBV carriers and the healthy adults, including the somatic mutations in V regions, the average CDR3 length, and the occurrence of junctional modifications. Nevertheless, the diversity of the unique clones decreased and some clusters of unique clones expanded in the IgM repertoire of chronic HBV carriers (CHB) compared with healthy adults (HH) and inactive HBV carriers (IHB). Such difference in clone diversity and expansion was not observed in the IgG repertoires of the three populations. More shared antibody clones were found between the IgM repertoires of IHB and HH than that found between CHB and HH (7079 clones vs. 2304 clones). Besides, the biased used IGHD genes were IGHD2-2 and IGHD3-3 in CHB library but were IGHD3-10 and IGHD3-22 in IHB and HH library. In contrast, for IgG repertories, the preferred used VDJ genes were similar in all the three populations. These results indicated that low level of serum HBV might not induce significant changes in BCR repertoires, and high level of HBV replication could have more impacts on IgM repertories than IgG repertoires. Taken together, our findings provide a better understanding of the antibody repertoires of HBV chronically infected individuals.

Development of antibody-dependent cell cytotoxicity function in HIV-1 antibodies

A prerequisite for the design of an HIV vaccine that elicits protective antibodies is understanding the developmental pathways that result in desirable antibody features. The development of antibodies that mediate antibody-dependent cellular cytotoxicity (ADCC) is particularly relevant because such antibodies have been associated with HIV protection in humans. We reconstructed the developmental pathways of six human HIV-specific ADCC antibodies using longitudinal antibody sequencing data. Most of the inferred naive antibodies did not mediate detectable ADCC. Gain of antigen binding and ADCC function typically required mutations in complementarity determining regions of one or both chains. Enhancement of ADCC potency often required additional mutations in framework regions. Antigen binding affinity and ADCC activity were correlated, but affinity alone was not sufficient to predict ADCC potency. Thus, elicitation of broadly active ADCC antibodies may require mutations that enable high-affinity antigen recognition along with mutations that optimize factors contributing to functional ADCC activity.

Deep sequencing reveals the skewed B-cell receptor repertoire in plaques and the association between pathogens and atherosclerosis

The immune/inflammatory responses regulated by B cells are the critical determinants of atherosclerosis. B-cell receptor (BCR) plays pivotal roles in regulating B cell function. However, the composition and molecular characteristics of the BCR repertoire in atherosclerotic patients have not been fully elucidated. Herein we analyzed BCR repertoire in circulation and plaques of atherosclerotic patients by sequencing the BCR heavy chain complement determining region 3 (BCRH CDR3). Our data showed that in plaques, BCR repertoire was dramatically skewed and their combinations and diversity were significantly decreased, while the frequency of public and dominant B-cell clones was markedly increased. Additionally, BCRH CDR3 in plaques had higher positive selection pressure than that in the peripheral blood of normal subjects and atherosclerotic patients. Moreover, the BCRH CDR3 of some B cell clones specifically expanded in plaques were similar to that of antibodies which recognized certain pathogens including Influenza A virus, implying the possibility of the association between pathogens and atherosclerosis. The present study contributed to understand the roles of B cells in atherosclerosis. The design of specific antibodies based on the B cell clones specifically expanded in plaques might yield useful tools to reveal the pathogenesis of atherosclerosis, assess or alleviate the progression of atherosclerosis.

Position-Dependent Differential Targeting of Somatic Hypermutation

Somatic hypermutation (SHM) generates much of the Ab diversity necessary for affinity maturation and effective humoral immunity. The activation-induced cytidine deaminase-induced DNA lesions and error-prone repair that underlie SHM are known to exhibit intrinsic biases when targeting the Ig sequences. Computational models for SHM targeting often model the targeting probability of a nucleotide in a motif-based fashion, assuming that the same DNA motif is equally likely to be targeted regardless of its position along the Ig sequence. The validity of this assumption, however, has not been rigorously studied in vivo. In this study, by analyzing a large collection of 956,157 human Ig sequences while controlling for the confounding influence of selection, we show that the likelihood of a DNA 5-mer motif being targeted by SHM is not the same at different positions in the same Ig sequence. We found position-dependent differential SHM targeting for about three quarters of the 38 and 269 unique motifs from more than half of the 292 and 1912 motif-allele pairs analyzed using productive and nonproductive Ig sequences, respectively. The direction of the differential SHM targeting was largely conserved across individuals with no allele-specific effect within an IgH variable gene family, but was not consistent with general decay of SHM targeting with increasing distance from the transcription start site. However, SHM targeting did correlate positively with the mutability of the wider sequence neighborhood surrounding the motif. These findings provide insights and future directions for computational efforts toward modeling SHM.

Single-cell repertoire tracing identifies rituximab-resistant B cells during myasthenia gravis relapses

Rituximab, a B cell-depleting therapy, is indicated for treating a growing number of autoantibody-mediated autoimmune disorders. However, relapses can occur after treatment, and autoantibody-producing B cell subsets may be found during relapses. It is not understood whether these autoantibody-producing B cell subsets emerge from the failed depletion of preexisting B cells or are generated de novo. To further define the mechanisms that cause postrituximab relapse, we studied patients with autoantibody-mediated muscle-specific kinase (MuSK) myasthenia gravis (MG) who relapsed after treatment. We carried out single-cell transcriptional and B cell receptor profiling on longitudinal B cell samples. We identified clones present before therapy that persisted during relapse. Persistent B cell clones included both antibody-secreting cells and memory B cells characterized by gene expression signatures associated with B cell survival. A subset of persistent antibody-secreting cells and memory B cells were specific for the MuSK autoantigen. These results demonstrate that rituximab is not fully effective at eliminating autoantibody-producing B cells and provide a mechanistic understanding of postrituximab relapse in MuSK MG.

Rapid HIV Progression Is Associated with Extensive Ongoing Somatic Hypermutation

The Ab response to HIV is of great interest, particularly in the context of a protective vaccine and broadly neutralizing Abs, but research is typically geared toward elite controllers because of their ability to successfully control the virus. In this study, we studied the evolution of the Ab repertoire over the first year of HIV infection in people classified as rapid progressors (RP) compared with typical progressors. HIV RPs are an important yet understudied group of HIV patients classified by a rapid decline in CD4 counts and accelerated development of AIDS. We found that the global IgG somatic hypermutation load negatively correlated with disease progression, possibly because of exaggerated isotype switching of unmutated sequences in patients with low CD4 counts. We measured Ab sequence evolution over time using longitudinal samples taken during the early stages of infection and 1 year postinfection. Within clonal lineages spanning both timepoints, visit 2-derived sequences harbored considerably more mutations than their visit 1 relatives. Despite extensive ongoing somatic hypermutation, the initially strong signs of Ag selection pressure observed in visit 1-derived sequences decayed by visit 2. These data suggest that excessive immune activation in RPs leads to a hyperactive B cell response that fails to confer protection.

Inter- and intraspecies comparison of phylogenetic fingerprints and sequence diversity of immunoglobulin variable genes

Protection and neutralization of a vast array of pathogens is accomplished by the tremendous diversity of the B cell receptor (BCR) repertoire. For jawed vertebrates, this diversity is initiated via the somatic recombination of immunoglobulin (Ig) germline elements. While it is clear that the number of these germline segments differs from species to species, the extent of cross-species sequence diversity remains largely uncharacterized. Here we use extensive computational and statistical methods to investigate the sequence diversity and evolutionary relationship between Ig variable (V), diversity (D), and joining (J) germline segments across nine commonly studied species ranging from zebrafish to human. Metrics such as guanine-cytosine (GC) content showed low redundancy across Ig germline genes within a given species. Other comparisons, including amino acid motifs, evolutionary selection, and sequence diversity, revealed species-specific properties. Additionally, we showed that the germline-encoded diversity differs across antibody (recombined V-D-J) repertoires of various B cell subsets. To facilitate future comparative immunogenomics analysis, we created VDJgermlines, an R package that contains the germline sequences from multiple species. Our study informs strategies for the humanization and engineering of therapeutic antibodies.

Dynamics of heavy chain junctional length biases in antibody repertoires

Antibody variable domain sequence diversity is generated by recombination of germline segments. The third complementarity-determining region of the heavy chain (CDR H3) is the region of highest sequence diversity and is formed by the joining of heavy chain V_H, D_H and J_H germline segments combined with random nucleotide trimming and additions between these segments. We show that CDR H3 and junctional segment length distributions are biased in human antibody repertoires as a function of V_H, V_L and J_H germline segment utilization. Most length biases are apparent in the naive and antigen experienced B cell compartments but not in nonproductive recombination products, indicating B cell selection as a major driver of these biases. Our findings reveal biases in the antibody CDR H3 diversity landscape shaped by V_H, V_L, and J_H germline segment use during naive and antigen-experienced repertoire selection.

Sankar et al. investigate the junctional length biases (determining antibody binding potential) as a function of germline gene usage in antibody repertoires. They show that CDR H3 and junction length are biased by V_H, V_L, and J_H germline segment usage and these biases are apparent in both naive and antigen-experienced repertoires but not in non-productive repertoires.

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.

Deep Characterization of the Human Antibody Response to Natural Infection Using Longitudinal Immune Repertoire Sequencing

Human antibody response studies are largely restricted to periods of high immune activity (e.g. vaccination). To comprehensively understand the healthy B cell immune repertoire and how this changes over time and through natural infection, we conducted immune repertoire RNA sequencing on flow cytometry-sorted B cell subsets to profile a single individual's antibodies over 11 months through two periods of natural viral infection. We found that 1) a baseline of healthy variable (V) gene usage in antibodies exists and is stable over time, but antibodies in memory cells consistently have a different usage profile relative to earlier B cell stages; 2) a single complementarity-determining region 3 (CDR3) is potentially generated from more than one VJ gene combination; and 3) IgG and IgA antibody transcripts are found at low levels in early human B cell development, suggesting that class switching may occur earlier than previously realized. These findings provide insight into immune repertoire stability, response to natural infections, and human B cell development.

Fierce Selection and Interference in B-Cell Repertoire Response to Chronic HIV-1

During chronic infection, HIV-1 engages in a rapid coevolutionary arms race with the host's adaptive immune system. While it is clear that HIV exerts strong selection on the adaptive immune system, the characteristics of the somatic evolution that shape the immune response are still unknown. Traditional population genetics methods fail to distinguish chronic immune response from healthy repertoire evolution. Here, we infer the evolutionary modes of B-cell repertoires and identify complex dynamics with a constant production of better B-cell receptor (BCR) mutants that compete, maintaining large clonal diversity and potentially slowing down adaptation. A substantial fraction of mutations that rise to high frequencies in pathogen-engaging CDRs of BCRs are beneficial, in contrast to many such changes in structurally relevant frameworks that are deleterious and circulate by hitchhiking. We identify a pattern where BCRs in patients who experience larger viral expansions undergo stronger selection with a rapid turnover of beneficial mutations due to clonal interference in their CDR3 regions. Using population genetics modeling, we show that the extinction of these beneficial mutations can be attributed to the rise of competing beneficial alleles and clonal interference. The picture is of a dynamic repertoire, where better clones may be outcompeted by new mutants before they fix.

Longitudinal analysis of the antibody repertoire of a Zika virus-infected patient revealed dynamic changes in antibody response

The Zika virus (ZIKV) is a mosquito-borne flavivirus that causes neonatal abnormalities and other disorders. Antibodies to the ZIKV envelope (E) protein can block infection. In this study, next-generation sequencing (NGS) of immunoglobulin heavy chain (IgH) mRNA transcripts was combined with single-cell PCR cloning of E-binding monoclonal antibodies for analysing antibody response in a patient from the early stages of infection to more than one year after the clearance of the virus. The patient's IgH repertoire 14 and 64 days after symptom onset showed dramatic dominant clonal expansion but low clonal diversity. IgH repertoire 6 months after disease-free status had few dominant clones but increased diversity. E-binding antibodies appeared abundantly in the repertoire during the early stages of infection but quickly declined after clearance of the virus. Certain VH genes such as VH5-10-1 and VH4-39 appeared to be preferentially enlisted for a rapid antibody response to ZIKV infection. Most of these antibodies require relatively few somatic hypermutations to acquire the ability to bind to the E protein, pointing to a possible mechanism for rapid defence against ZIKV infection. This study provides a unique and holistic view of the dynamic changes and characteristics of the antibody response to ZIKV infection.

Immune repertoire fingerprinting by principal component analysis reveals shared features in subject groups with common exposures

BACKGROUND

Advances in next-generation sequencing (NGS) of antibody repertoires have led to an explosion in B cell receptor sequence data from donors with many different disease states. These data have the potential to detect patterns of immune response across populations. However, to this point it has been difficult to interpret such patterns of immune response between disease states in the absence of functional data. There is a need for a robust method that can be used to distinguish general patterns of immune responses at the antibody repertoire level.

RESULTS

We developed a method for reducing the complexity of antibody repertoire datasets using principal component analysis (PCA) and refer to our method as "repertoire fingerprinting." We reduce the high dimensional space of an antibody repertoire to just two principal components that explain the majority of variation in those repertoires. We show that repertoires from individuals with a common experience or disease state can be clustered by their repertoire fingerprints to identify common antibody responses.

CONCLUSIONS

Our repertoire fingerprinting method for distinguishing immune repertoires has implications for characterizing an individual disease state. Methods to distinguish disease states based on pattern recognition in the adaptive immune response could be used to develop biomarkers with diagnostic or prognostic utility in patient care. Extending our analysis to larger cohorts of patients in the future should permit us to define more precisely those characteristics of the immune response that result from natural infection or autoimmunity.

A Recombinant Influenza A/H1N1 Carrying A Short Immunogenic Peptide of MERS-CoV as Bivalent Vaccine in BALB/c Mice

Middle East Respiratory Syndrome Coronavirus (MERS-CoV) became a global human health threat since its first documentation in humans in 2012. An efficient vaccine for the prophylaxis of humans in hotspots of the infection (e.g., Saudi Arabia) is necessary but no commercial vaccines are yet approved. In this study, a chimeric DNA construct was designed to encode an influenza A/H1N1 NA protein which is flanking immunogenic amino acids (aa) 736–761 of MERS-CoV spike protein. Using the generated chimeric construct, a novel recombinant vaccine strain against pandemic influenza A virus (H1N1pdm09) and MERS-CoV was generated (chimeric bivalent 5 + 3). The chimeric bivalent 5 + 3 vaccine strain comprises a recombinant PR8-based vaccine, expressing the PB1, HA, and chimeric NA of pandemic 2009 H1N1. Interestingly, an increase in replication efficiency of the generated vaccine strain was observed when compared to the PR8-based 5 + 3 H1N1pdm09 vaccine strain that lacks the MERS-CoV spike peptide insert. In BALB/c mice, the inactivated chimeric bivalent vaccine induced potent and specific neutralizing antibodies against MERS-CoV and H1N1pdm09. This novel approach succeeded in developing a recombinant influenza virus with potential use as a bivalent vaccine against H1N1pdm09 and MERS-CoV. This approach provides a basis for the future development of chimeric influenza-based vaccines against MERS-CoV and other viruses.

Repertoire-wide phylogenetic models of B cell molecular evolution reveal evolutionary signatures of aging and vaccination

In order to produce effective antibodies, B cells undergo rapid somatic hypermutation (SHM) and selection for binding affinity to antigen via a process called affinity maturation. The similarities between this process and evolution by natural selection have led many groups to use phylogenetic methods to characterize the development of immunological memory, vaccination, and other processes that depend on affinity maturation. However, these applications are limited by the fact that most phylogenetic models are designed to be applied to individual lineages comprising genetically diverse sequences, while B cell repertoires often consist of hundreds to thousands of separate low-diversity lineages. Further, several features of affinity maturation violate important assumptions in standard phylogenetic models. Here, we introduce a hierarchical phylogenetic framework that integrates information from all lineages in a repertoire to more precisely estimate model parameters while simultaneously incorporating the unique features of SHM. We demonstrate the power of this repertoire-wide approach by characterizing previously undescribed phenomena in affinity maturation. First, we find evidence consistent with age-related changes in SHM hot-spot targeting. Second, we identify a consistent relationship between increased tree length and signs of increased negative selection, apparent in the repertoires of recently vaccinated subjects and those without any known recent infections or vaccinations. This suggests that B cell lineages shift toward negative selection over time as a general feature of affinity maturation. Our study provides a framework for undertaking repertoire-wide phylogenetic testing of SHM hypotheses and provides a means of characterizing dynamics of mutation and selection during affinity maturation.

sumrep: A Summary Statistic Framework for Immune Receptor Repertoire Comparison and Model Validation

The adaptive immune system generates an incredible diversity of antigen receptors for B and T cells to keep dangerous pathogens at bay. The DNA sequences coding for these receptors arise by a complex recombination process followed by a series of productivity-based filters, as well as affinity maturation for B cells, giving considerable diversity to the circulating pool of receptor sequences. Although these datasets hold considerable promise for medical and public health applications, the complex structure of the resulting adaptive immune receptor repertoire sequencing (AIRR-seq) datasets makes analysis difficult. In this paper we introduce sumrep, an R package that efficiently performs a wide variety of repertoire summaries and comparisons, and show how sumrep can be used to perform model validation. We find that summaries vary in their ability to differentiate between datasets, although many are able to distinguish between covariates such as donor, timepoint, and cell type for BCR and TCR repertoires. We show that deletion and insertion lengths resulting from V(D)J recombination tend to be more discriminative characterizations of a repertoire than summaries that describe the amino acid composition of the CDR3 region. We also find that state-of-the-art generative models excel at recapitulating gene usage and recombination statistics in a given experimental repertoire, but struggle to capture many physiochemical properties of real repertoires.

Genetic background and immunological status influence B cell repertoire diversity in mice

The relationship between the immune repertoire and the physiopathological status of individuals is essential to apprehend the genesis and the evolution of numerous pathologies. Nevertheless, the methodological approaches to understand these complex interactions are challenging. We performed a study evaluating the diversity harbored by different immune repertoires as a function of their physiopathological status. In this study, we base our analysis on a murine scFv library previously described and representing four different immune repertoires: i) healthy and naïve, ii) healthy and immunized, iii) autoimmune prone and naïve, and iv) autoimmune prone and immunized. This library, 2.6 × 109 in size, is submitted to high throughput sequencing (Next Generation Sequencing, NGS) in order to analyze the gene subgroups encoding for immunoglobulins. A comparative study of the distribution of immunoglobulin gene subgroups present in the four libraries has revealed shifts in the B cell repertoire originating from differences in genetic background and immunological status of mice.

Next-generation sequencing analysis of the human T-cell and B-cell receptor repertoire diversity before and after hepatitis B vaccination

The hepatitis B (HB) vaccine effectively prevents the incidence of hepatitis B virus (HBV) infection. However, vaccine failure occurs in 5-10% of the recipients. The precise mechanisms leading to responsiveness to the HB vaccine are poorly understood. High-throughput sequencing (HTS) may help clarify the immune response to the HB vaccine, so we applied this method to investigate whether the HB vaccine induced a specific change in the T-cell receptor (TCR) and B-cell receptor (BCR) repertoires. We conducted HTS of the TCR β chain and BCR IgG heavy (H) chain complementary determining region 3 (CDR3) repertoires in five volunteers before and after the second and third immunizations with the HB vaccine. The HB surface antibody (HBsAb) levels were >10 mIU/ml after the third vaccination in all five participants. The TCR β chain CDR3 repertoire diversity significantly increased, while the BCR IgG H chain CDR3 repertoire diversity significantly decreased after the second vaccination. Although there was no marked inter-individual variation in terms of the numbers of unique reads, it is possible that the TCR β chain and BCR IgG H chain CDR3 repertoires may have changed within the same numbers of unique reads. Our data failed to identify the specific dominant clones that responded to the HB vaccine. In summary, the TCR β chain CDR3 repertoire diversity significantly increased, while the BCR IgG H chain CDR3 repertoire diversity significantly decreased, after the second HB vaccination. These diversity changes might be associated with a better response to the HB vaccine.

Activation Dynamics and Immunoglobulin Evolution of Pre-existing and Newly Generated Human Memory B cell Responses to Influenza Hemagglutinin

Vaccine-induced memory B cell responses to evolving viruses like influenza A involve activation of pre-existing immunity and generation of new responses. To define the contribution of these two types of responses, we analyzed the response to H7N9 vaccination in H7N9-naive adults. We performed comprehensive comparisons at the single-cell level of the kinetics, Ig repertoire, and activation phenotype of established pre-existing memory B cells recognizing conserved epitopes and the newly generated memory B cells directed toward H7 strain-specific epitopes. The recall response to conserved epitopes on H7 HA involved a transient expansion of memory B cells with little observed adaptation. However, the B cell response to newly encountered epitopes was phenotypically distinct and generated a sustained memory population that evolved and affinity matured months after vaccination. These findings establish clear differences between newly generated and pre-existing memory B cells, highlighting the challenges in achieving long-lasting, broad protection against an ever-evolving virus.

Per-sample immunoglobulin germline inference from B cell receptor deep sequencing data

The collection of immunoglobulin genes in an individual's germline, which gives rise to B cell receptors via recombination, is known to vary significantly across individuals. In humans, for example, each individual has only a fraction of the several hundred known V alleles. Furthermore, the currently-accepted set of known V alleles is both incomplete (particularly for non-European samples), and contains a significant number of spurious alleles. The resulting uncertainty as to which immunoglobulin alleles are present in any given sample results in inaccurate B cell receptor sequence annotations, and in particular inaccurate inferred naive ancestors. In this paper we first show that the currently widespread practice of aligning each sequence to its closest match in the full set of IMGT alleles results in a very large number of spurious alleles that are not in the sample's true set of germline V alleles. We then describe a new method for inferring each individual's germline gene set from deep sequencing data, and show that it improves upon existing methods by making a detailed comparison on a variety of simulated and real data samples. This new method has been integrated into the partis annotation and clonal family inference package, available at https://github.com/psathyrella/partis, and is run by default without affecting overall run time.

Functional Enrichment and Analysis of Antigen-Specific Memory B Cell Antibody Repertoires in PBMCs

Phenotypic screening of antigen-specific antibodies in human blood is a common diagnostic test for infectious agents and a correlate of protection after vaccination. In addition to long-lived antibody secreting plasma cells residing in the bone marrow, memory B cells are a latent source of antigen-experienced, long-term immunity that can be found at low frequencies in circulating peripheral blood mononuclear cells (PBMCs). Assessing the genotype, clonal frequency, quality, and function of antibodies resulting from an individual's persistent memory B cell repertoire can help inform the success or failure of immune protection. Using in vitro polyclonal stimulation, we functionally expand the memory repertoire from PBMCs and clonally map monoclonal antibodies from this population. We show that combining deep sequencing of stimulated memory B cell repertoires with retrieving single antigen-specific cells is a promising approach in evaluating the latent, functional B cell memory in PBMCs.

The Pipeline Repertoire for Ig-Seq Analysis

With the advent of high-throughput sequencing of immunoglobulin genes (Ig-Seq), the understanding of antibody repertoires and their dynamics among individuals and populations has become an exciting area of research. There is an increasing number of computational tools that aid in every step of the immune repertoire characterization. However, since not all tools function identically, every pipeline has its unique rationale and capabilities, creating a rich blend of useful features that may appear intimidating for newcomer laboratories with the desire to plunge into immune repertoire analysis to expand and improve their research; hence, all pipeline strengths and differences may not seem evident. In this review we provide a practical and organized list of the current set of computational tools, focusing on their most attractive features and differences in order to carry out the characterization of antibody repertoires so that the reader better decides a strategic approach for the experimental design, and computational pathways for the analyses of immune repertoires.