Network properties derived from deep sequencing of human B-cell receptor repertoires delineate B-cell populations

Computational estimation of clonal diversity in autoimmunity

Diversity is the cornerstone of the adaptive immune system, crucial for its effectiveness against constantly evolving pathogens that pose threats to higher vertebrates. Accurately measuring and interpreting this diversity presents challenges for immunologists, as changes in diversity and clonotype composition can tip the balance between protective immunity and autoimmunity. In this review, we present the current methods commonly used to measure diversity from single-cell T-cell receptor and B-cell receptor sequencing. We also discuss two case studies where single-cell sequencing and diversity estimations have led to breakthroughs in autoimmune disease discovery and therapeutic innovation, and reflect upon the necessity and importance of accurately defining and measuring lymphocyte diversity in these contexts.

CD4+ CAR T-cell exhaustion associated with early relapse of multiple myeloma after BCMA CAR T-cell therapy

ABSTRACT

Multiple myeloma is characterized by frequent clinical relapses after conventional therapy. Recently, chimeric antigen receptor (CAR) T cells targeting B-cell maturation antigen (BCMA) has been established as a treatment option for patients with relapsed or refractory disease. However, although >70% of patients initially respond to this treatment, clinical relapse and disease progression occur in most cases. Recent studies showed persistent expression of BCMA at the time of relapse, indicating that immune-intrinsic mechanisms may contribute to this resistance. Although there were no preexisting T-cell features associated with clinical outcomes, we found that patients with a durable response to CAR T-cell treatment had greater persistence of their CAR T cells than patients with transient clinical responses. They also possessed a significantly higher proportion of CD8+ T-effector memory cells. In contrast, patients with short-lived responses to treatment have increased frequencies of cytotoxic CD4+ CAR T cells. These cells expand in vivo early after infusion but express exhaustion markers (hepatitis A virus cellular receptor 2 [HAVCR2] and T-cell immunoglobulin and mucin domain-containing-3 [TIGIT]) and remain polyclonal. Finally, we demonstrate that nonclassical monocytes are enriched in the myeloma niche and may induce CAR T-cell dysfunction through mechanisms that include transforming growth factor β. These findings shed new light on the role of cytotoxic CD4+ T cells in disease progression after CAR T-cell therapy.

nf-core/airrflow: An adaptive immune receptor repertoire analysis workflow employing the Immcantation framework

Adaptive Immune Receptor Repertoire sequencing (AIRR-seq) is a valuable experimental tool to study the immune state in health and following immune challenges such as infectious diseases, (auto)immune diseases, and cancer. Several tools have been developed to reconstruct B cell and T cell receptor sequences from AIRR-seq data and infer B and T cell clonal relationships. However, currently available tools offer limited parallelization across samples, scalability or portability to high-performance computing infrastructures. To address this need, we developed nf-core/airrflow, an end-to-end bulk and single-cell AIRR-seq processing workflow which integrates the Immcantation Framework following BCR and TCR sequencing data analysis best practices. The Immcantation Framework is a comprehensive toolset, which allows the processing of bulk and single-cell AIRR-seq data from raw read processing to clonal inference. nf-core/airrflow is written in Nextflow and is part of the nf-core project, which collects community contributed and curated Nextflow workflows for a wide variety of analysis tasks. We assessed the performance of nf-core/airrflow on simulated sequencing data with sequencing errors and show example results with real datasets. To demonstrate the applicability of nf-core/airrflow to the high-throughput processing of large AIRR-seq datasets, we validated and extended previously reported findings of convergent antibody responses to SARS-CoV-2 by analyzing 97 COVID-19 infected individuals and 99 healthy controls, including a mixture of bulk and single-cell sequencing datasets. Using this dataset, we extended the convergence findings to 20 additional subjects, highlighting the applicability of nf-core/airrflow to validate findings in small in-house cohorts with reanalysis of large publicly available AIRR datasets.

Single-cell immune repertoire analysis

Single-cell T cell and B cell antigen receptor-sequencing data analysis can potentially perform in-depth assessments of adaptive immune cells that inform on understanding immune cell development to tracking clonal expansion in disease and therapy. However, it has been extremely challenging to analyze and interpret T cells and B cells and their adaptive immune receptor repertoires at the single-cell level due to not only the complexity of the data but also the underlying biology. In this Review, we delve into the computational breakthroughs that have transformed the analysis of single-cell T cell and B cell antigen receptor-sequencing data.

Systematic evaluation of B-cell clonal family inference approaches

The reconstruction of clonal families (CFs) in B-cell receptor (BCR) repertoire analysis is a crucial step to understand the adaptive immune system and how it responds to antigens. The BCR repertoire of an individual is formed throughout life and is diverse due to several factors such as gene recombination and somatic hypermutation. The use of Adaptive Immune Receptor Repertoire sequencing (AIRR-seq) using next generation sequencing enabled the generation of full BCR repertoires that also include rare CFs. The reconstruction of CFs from AIRR-seq data is challenging and several approaches have been developed to solve this problem. Currently, most methods use the heavy chain (HC) only, as it is more variable than the light chain (LC). CF reconstruction options include the definition of appropriate sequence similarity measures, the use of shared mutations among sequences, and the possibility of reconstruction without preliminary clustering based on V- and J-gene annotation. In this study, we aimed to systematically evaluate different approaches for CF reconstruction and to determine their impact on various outcome measures such as the number of CFs derived, the size of the CFs, and the accuracy of the reconstruction. The methods were compared to each other and to a method that groups sequences based on identical junction sequences and another method that only determines subclones. We found that after accounting for data set variability, in particular sequencing depth and mutation load, the reconstruction approach has an impact on part of the outcome measures, including the number of CFs. Simulations indicate that unique junctions and subclones should not be used as substitutes for CF and that more complex methods do not outperform simpler methods. Also, we conclude that different approaches differ in their ability to correctly reconstruct CFs when not considering the LC and to identify shared CFs. The results showed the effect of different approaches on the reconstruction of CFs and highlighted the importance of choosing an appropriate method.

nf-core/airrflow: an adaptive immune receptor repertoire analysis workflow employing the Immcantation framework

Adaptive Immune Receptor Repertoire sequencing (AIRR-seq) is a valuable experimental tool to study the immune state in health and following immune challenges such as infectious diseases, (auto)immune diseases, and cancer. Several tools have been developed to reconstruct B cell and T cell receptor sequences from AIRR-seq data and infer B and T cell clonal relationships. However, currently available tools offer limited parallelization across samples, scalability or portability to high-performance computing infrastructures. To address this need, we developed nf-core/airrflow, an end-to-end bulk and single-cell AIRR-seq processing workflow which integrates the Immcantation Framework following BCR and TCR sequencing data analysis best practices. The Immcantation Framework is a comprehensive toolset, which allows the processing of bulk and single-cell AIRR-seq data from raw read processing to clonal inference. nf-core/airrflow is written in Nextflow and is part of the nf-core project, which collects community contributed and curated Nextflow workflows for a wide variety of analysis tasks. We assessed the performance of nf-core/airrflow on simulated sequencing data with sequencing errors and show example results with real datasets. To demonstrate the applicability of nf-core/airrflow to the high-throughput processing of large AIRR-seq datasets, we validated and extended previously reported findings of convergent antibody responses to SARS-CoV-2 by analyzing 97 COVID-19 infected individuals and 99 healthy controls, including a mixture of bulk and single-cell sequencing datasets. Using this dataset, we extended the convergence findings to 20 additional subjects, highlighting the applicability of nf-core/airrflow to validate findings in small in-house cohorts with reanalysis of large publicly available AIRR datasets. nf-core/airrflow is available free of charge, under the MIT license on GitHub (https://github.com/nf-core/airrflow). Detailed documentation and example results are available on the nf-core website at (https://nf-co.re/airrflow).

The dengue-specific immune response and antibody identification with machine learning

Dengue virus poses a serious threat to global health and there is no specific therapeutic for it. Broadly neutralizing antibodies recognizing all serotypes may be an effective treatment. High-throughput adaptive immune receptor repertoire sequencing (AIRR-seq) and bioinformatic analysis enable in-depth understanding of the B-cell immune response. Here, we investigate the dengue antibody response with these technologies and apply machine learning to identify rare and underrepresented broadly neutralizing antibody sequences. Dengue immunization elicited the following signatures on the antibody repertoire: (i) an increase of CDR3 and germline gene diversity; (ii) a change in the antibody repertoire architecture by eliciting power-law network distributions and CDR3 enrichment in polar amino acids; (iii) an increase in the expression of JNK/Fos transcription factors and ribosomal proteins. Furthermore, we demonstrate the applicability of computational methods and machine learning to AIRR-seq datasets for neutralizing antibody candidate sequence identification. Antibody expression and functional assays have validated the obtained results.

Scaling Monte-Carlo-Based Inference on Antibody and TCR Repertoires

Previously, it has been shown that maximum-entropy models of immune-repertoire sequence can be used to determine a person's vaccination status. However, this approach has the drawback of requiring a computationally intensive method to compute each model's partition function ( Z ) , the normalization constant required for calculating the probability that the model will generate a given sequence. Specifically, the method required generating approximately 1010 sequences via Monte-Carlo simulations for each model. This is impractical for large numbers of models. Here we propose an alternative method that requires estimating Z this way for only a few models: it then uses these expensive estimates to estimate Z more efficiently for the remaining models. We demonstrate that this new method enables the generation of accurate estimates for 27 models using only three expensive estimates, thereby reducing the computational cost by an order of magnitude. Importantly, this gain in efficiency is achieved with only minimal impact on classification accuracy. Thus, this new method enables larger-scale investigations in computational immunology and represents a useful contribution to energy-based modeling more generally.

Characterizing the dynamics of BCR repertoire from repeated influenza vaccination

Yearly epidemics of seasonal influenza cause an enormous disease burden around the globe. An understanding of the rules behind the immune response with repeated vaccination still presents a significant challenge, which would be helpful for optimizing the vaccination strategy. In this study, 34 healthy volunteers with 16 vaccinated were recruited, and the dynamics of the BCR repertoire for consecutive vaccinations in two seasons were tracked. In terms of diversity, length, network, V and J gene segments usage, somatic hypermutation (SHM) rate and isotype, it was found that the overall changes were stronger in the acute phase of the first vaccination than the second vaccination. However, the V gene segments of IGHV4-39, IGHV3-9, IGHV3-7 and IGHV1-69 were amplified in the acute phase of the first vaccination, with IGHV3-7 dominant. On the other hand, for the second vaccination, the changes were dominated by IGHV1-69, with potential for coding broad neutralizing antibody. Additional analysis indicates that the application of V gene segment for IGHV3-7 in the acute phase of the first vaccination was due to the elevated usage of isotypes IgM and IgG3. While for IGHV1-69 in the second vaccination, it was contributed by isotypes IgG1 and IgG2. Finally, 41 public BCR clusters were identified in the vaccine group, with both IGHV3-7 and IGHV1-69 were involved and representative complementarity determining region 3 (CDR3) motifs were characterized. This study provides insights into the immune response dynamics following repeated influenza vaccination in humans and can inform universal vaccine design and vaccine strategies in the future.

Immunological and clinicopathological features predict HER2-positive breast cancer prognosis in the neoadjuvant NeoALTTO and CALGB 40601 randomized trials

The identification of prognostic markers in patients receiving neoadjuvant therapy is crucial for treatment optimization in HER2-positive breast cancer, with the immune microenvironment being a key factor. Here, we investigate the complexity of B and T cell receptor (BCR and TCR) repertoires in the context of two phase III trials, NeoALTTO and CALGB 40601, evaluating neoadjuvant paclitaxel with trastuzumab and/or lapatinib in women with HER2-positive breast cancer. BCR features, particularly the number of reads and clones, evenness and Gini index, are heterogeneous according to hormone receptor status and PAM50 subtypes. Moreover, BCR measures describing clonal expansion, namely evenness and Gini index, are independent prognostic factors. We present a model developed in NeoALTTO and validated in CALGB 40601 that can predict event-free survival (EFS) by integrating hormone receptor and clinical nodal status, breast pathological complete response (pCR), stromal tumor-infiltrating lymphocyte levels (%) and BCR repertoire evenness. A prognostic score derived from the model and including those variables, HER2-EveNT, allows the identification of patients with 5-year EFS > 90%, and, in those not achieving pCR, of a subgroup of immune-enriched tumors with an excellent outcome despite residual disease.

HIV-1 treatment timing shapes the human intestinal memory B-cell repertoire to commensal bacteria

HIV-1 infection causes severe alterations of gut mucosa, microbiota and immune system, which can be curbed by early antiretroviral therapy. Here, we investigate how treatment timing affects intestinal memory B-cell and plasmablast repertoires of HIV-1-infected humans. We show that only class-switched memory B cells markedly differ between subjects treated during the acute and chronic phases of infection. Intestinal memory B-cell monoclonal antibodies show more prevalent polyreactive and commensal bacteria-reactive clones in late- compared to early-treated individuals. Mirroring this, serum IgA polyreactivity and commensal-reactivity are strongly increased in late-treated individuals and correlate with intestinal permeability and systemic inflammatory markers. Polyreactive blood IgA memory B cells, many of which egressed from the gut, are also substantially enriched in late-treated individuals. Our data establish gut and systemic B-cell polyreactivity to commensal bacteria as hallmarks of chronic HIV-1 infection and suggest that initiating treatment early may limit intestinal B-cell abnormalities compromising HIV-1 humoral response.

Transcriptional immunogenomic analysis reveals distinct immunological clusters in paediatric nervous system tumours

BACKGROUND

Cancer immunotherapies including immune checkpoint inhibitors and Chimeric Antigen Receptor (CAR) T-cell therapy have shown variable response rates in paediatric patients highlighting the need to establish robust biomarkers for patient selection. While the tumour microenvironment in adults has been widely studied to delineate determinants of immune response, the immune composition of paediatric solid tumours remains relatively uncharacterized calling for investigations to identify potential immune biomarkers.

METHODS

To inform immunotherapy approaches in paediatric cancers with embryonal origin, we performed an immunogenomic analysis of RNA-seq data from 925 treatment-naïve paediatric nervous system tumours (pedNST) spanning 12 cancer types from three publicly available data sets.

RESULTS

Within pedNST, we uncovered four broad immune clusters: Paediatric Inflamed (10%), Myeloid Predominant (30%), Immune Neutral (43%) and Immune Desert (17%). We validated these clusters using immunohistochemistry, methylation immune inference and segmentation analysis of tissue images. We report shared biology of these immune clusters within and across cancer types, and characterization of specific immune cell frequencies as well as T- and B-cell repertoires. We found no associations between immune infiltration levels and tumour mutational burden, although molecular cancer entities were enriched within specific immune clusters.

CONCLUSIONS

Given the heterogeneity of immune infiltration within pedNST, our findings suggest personalized immunogenomic profiling is needed to guide selection of immunotherapeutic strategies.

NAIR: Network Analysis of Immune Repertoire

T cells represent a crucial component of the adaptive immune system and mediate anti-tumoral immunity as well as protection against infections, including respiratory viruses such as SARS-CoV-2. Next-generation sequencing of the T-cell receptors (TCRs) can be used to profile the T-cell repertoire. We developed a customized pipeline for Network Analysis of Immune Repertoire (NAIR) with advanced statistical methods to characterize and investigate changes in the landscape of TCR sequences. We first performed network analysis on the TCR sequence data based on sequence similarity. We then quantified the repertoire network by network properties and correlated it with clinical outcomes of interest. In addition, we identified (1) disease-specific/associated clusters and (2) shared clusters across samples based on our customized search algorithms and assessed their relationship with clinical outcomes such as recovery from COVID-19 infection. Furthermore, to identify disease-specific TCRs, we introduced a new metric that incorporates the clonal generation probability and the clonal abundance by using the Bayes factor to filter out the false positives. TCR-seq data from COVID-19 subjects and healthy donors were used to illustrate that the proposed approach to analyzing the network architecture of the immune repertoire can reveal potential disease-specific TCRs responsible for the immune response to infection.

Age-associated B cells predict impaired humoral immunity after COVID-19 vaccination in patients receiving immune checkpoint blockade

Age-associated B cells (ABC) accumulate with age and in individuals with different immunological disorders, including cancer patients treated with immune checkpoint blockade and those with inborn errors of immunity. Here, we investigate whether ABCs from different conditions are similar and how they impact the longitudinal level of the COVID-19 vaccine response. Single-cell RNA sequencing indicates that ABCs with distinct aetiologies have common transcriptional profiles and can be categorised according to their expression of immune genes, such as the autoimmune regulator (AIRE). Furthermore, higher baseline ABC frequency correlates with decreased levels of antigen-specific memory B cells and reduced neutralising capacity against SARS-CoV-2. ABCs express high levels of the inhibitory FcγRIIB receptor and are distinctive in their ability to bind immune complexes, which could contribute to diminish vaccine responses either directly, or indirectly via enhanced clearance of immune complexed-antigen. Expansion of ABCs may, therefore, serve as a biomarker identifying individuals at risk of suboptimal responses to vaccination.

Exploring the impact of clonal definition on B-cell diversity: implications for the analysis of immune repertoires

The adaptive immune system has the extraordinary ability to produce a broad range of immunoglobulins that can bind a wide variety of antigens. During adaptive immune responses, activated B cells duplicate and undergo somatic hypermutation in their B-cell receptor (BCR) genes, resulting in clonal families of diversified B cells that can be related back to a common ancestor. Advances in high-throughput sequencing technologies have enabled the high-throughput characterization of B-cell repertoires, however, the accurate identification of clonally related BCR sequences remains a major challenge. In this study, we compare three different clone identification methods on both simulated and experimental data, and investigate their impact on the characterization of B-cell diversity. We observe that different methods lead to different clonal definitions, which affects the quantification of clonal diversity in repertoire data. Our analyses show that direct comparisons between clonal clusterings and clonal diversity of different repertoires should be avoided if different clone identification methods were used to define the clones. Despite this variability, the diversity indices inferred from the repertoires' clonal characterization across samples show similar patterns of variation regardless of the clonal identification method used. We find the Shannon entropy to be the most robust in terms of the variability of diversity rank across samples. Our analysis also suggests that the traditional germline gene alignment-based method for clonal identification remains the most accurate when the complete information about the sequence is known, but that alignment-free methods may be preferred for shorter sequencing read lengths. We make our implementation freely available as a Python library cdiversity.

Characterization of the tumor-infiltrating immune repertoire in muscle invasive bladder cancer

Introduction

Muscle-invasive bladder cancer (MIBC) is a heterogeneous disease with several taxonomic molecular subtypes showing different genetic, clinical, and epidemiological profiles. It has been suggested that MIBC-subtypes follow different tumorigenesis pathways playing decisive roles at different stages of tumor development, resulting in distinct tumor microenvironment containing both innate and adaptive immune cells (T and B lymphocytes). We aim to characterize the MIBC tumor microenvironment by analyzing the tumor-infiltrating B and T cell repertoire according to the taxonomic molecular subtypes.

Methods

RNAseq data from 396 MIBC samples included in TCGA were considered. The subtype information was collected from the international consensus taxonomic classification describing six subtypes: Basal/Squamous-like (Ba/Sq), Luminal papillary (LumP), Luminal non-Specify (LumNS), Luminal unstable (LumU), Stroma-rich, and Neuroendocrine-like (NE-like). Using MiXCR, we mapped the RNA read sequences to their respective B-cell receptor (BCR) and T-cell receptor (TCR) clonotypes. To evaluate the BCR and TCR differences among subtypes, we compared diversity measures (richness and diversity) using a Wilcoxon test and we performed a network analysis to characterize the clonal expansion. For the survival analysis stratified by subtypes, Cox regression models adjusted for age, region, and pathological stage were performed.

Results

Overall, we found different patterns of tumor-infiltrating immune repertoire among the different MIBC subtypes. Stroma-rich and Ba/Sq tumors showed the highest BCR and TCR infiltration while LumP showed the lowest. In addition, we observed that the Ba/Sq and Stroma-rich tumors were more clonally expanded than the Luminal subtypes. Moreover, higher TCR richness and diversity were significantly associated with better survival in the Stroma-rich and Ba/Sq subtypes.

Discussion

This study provides evidence that MIBC subtypes present differences in the tumor microenvironment, in particular, the Ba/Sq and the Stroma-rich are related with a higher tumoral-infiltrating immune repertoire, which seems to be translated into better survival. Determining the causes of the different tumoral-infiltrating immune repertoire according to the MIBC molecular subtypes will help to improve our understanding of the disease and the distinct responses to immunotherapy of MIBC.

T cell receptor repertoire sequencing reveals chemotherapy-driven clonal expansion in colorectal liver metastases

BACKGROUND

Colorectal liver metastasis (CLM) is a leading cause of colorectal cancer mortality, and the response to immune checkpoint inhibition (ICI) in microsatellite-stable CRC has been disappointing. Administration of cytotoxic chemotherapy may cause increased density of tumor-infiltrating T cells, which has been associated with improved response to ICI. This study aimed to quantify and characterize T-cell infiltration in CLM using T-cell receptor (TCR) repertoire sequencing. Eighty-five resected CLMs from patients included in the Oslo CoMet study were subjected to TCR repertoire sequencing. Thirty-five and 15 patients had received neoadjuvant chemotherapy (NACT) within a short or long interval, respectively, prior to resection, while 35 patients had not been exposed to NACT. T-cell fractions were calculated, repertoire clonality was analyzed based on Hill evenness curves, and TCR sequence convergence was assessed using network analysis.

RESULTS

Increased T-cell fractions (10.6% vs. 6.3%) were detected in CLMs exposed to NACT within a short interval prior to resection, while modestly increased clonality was observed in NACT-exposed tumors independently of the timing of NACT administration and surgery. While private clones made up >90% of detected clones, network connectivity analysis revealed that public clones contributed the majority of TCR sequence convergence.

CONCLUSIONS

TCR repertoire sequencing can be used to quantify T-cell infiltration and clonality in clinical samples. This study provides evidence to support chemotherapy-driven T-cell clonal expansion in CLM in a clinical context.

The Clonal Diversity of Peripheral B Cell Receptor Immune Repertoire Impaired by Residual Malignant B Cells Predicts Treatment Efficacy in B Cell Lymphoma Patients

Germinal center (GC) is the vital locus for the evolution of naïve B cells into memory B and plasma cells, but also a hotbed for the proliferation of malignant B cells. We hypothesized that malignant B cells may locally or globally impact GCs to produce peripheral B cell receptor immune repertoire (BCR IR) with reduced clonal diversity. In this study, we first validated our hypothesis in a novel human in-vitro GC (hiGC) model. The addition of the diffuse large B cell lymphoma (DLBCL) cells to the hiGC culture attenuated the rate of diversity growth. For clinical validation, we collected samples from 17 DLBCL patients at various points during high-dose therapy and autologous stem cell rescue. The elimination and reestablishment of the patients’ lymphatic pool allowed us to unambiguously monitor the impact of tumor cells on the replenishment of the peripheral BCR IR. Compared to the nine patients who did not relapse after treatment, relapsed patients tended to have a slower rate of recovery regarding the clonal diversity of their peripheral BCR IR. Our results suggest a mechanistic and clinical connection between residual tumor cells and abnormal peripheral BCR IR, which may corelate with treatment efficacy in B cell lymphomas.

Gastric DLBCL clonal evolution as function of patient age

Diffuse large B cell lymphoma (DLBCL) is the most common type of NHL, accounting for about 40% of NHL cases, and is one of the most aggressive lymphomas. DLBCL is widespread in individuals aged more than 50 years old, with a maximum incidence in the seventh decade, but it may also occur in younger patients. DLBCL may occur in any immune system tissue, including those around the gastrointestinal tract, and even in the stomach, though gastric DLBCL has yet to be sufficiently investigated. This study aimed to understand changes in gastric Diffuse Large B cell lymphoma (gastric DLBCL) development with age. Immunoglobulin (Ig) heavy chain variable region genes were amplified from sections of nine preserved biopsies, from patients whose age varied between 25 and 89 years, sequenced and analyzed. We show first that identification of the malignant clone based on the biopsies is much less certain than was previously assumed; and second that, contrary to expectations, the repertoire of gastric B cell clones is more diverse among the elderly DLBCL patients than among the young.

Repertoire-scale measures of antigen binding

Antibodies and T cell receptors (TCRs) are the fundamental building blocks of adaptive immunity. Repertoire-scale functionality derives from their epitope-binding properties, just as macroscopic properties like temperature derive from microscopic molecular properties. However, most approaches to repertoire-scale measurement, including sequence diversity and entropy, are not based on antibody or TCR function in this way. Thus, they potentially overlook key features of immunological function. Here we present a framework that describes repertoires in terms of the epitope-binding properties of their constituent antibodies and TCRs, based on analysis of thousands of antibody-antigen and TCR-peptide-major-histocompatibility-complex binding interactions and over 400 high-throughput repertoires. We show that repertoires consist of loose overlapping classes of antibodies and TCRs with similar binding properties. We demonstrate the potential of this framework to distinguish specific responses vs. bystander activation in influenza vaccinees, stratify cytomegalovirus (CMV)-infected cohorts, and identify potential immunological "super-agers." Classes add a valuable dimension to the assessment of immune function.

Reference-based comparison of adaptive immune receptor repertoires

B and T cell receptor (immune) repertoires can represent an individual's immune history. While current repertoire analysis methods aim to discriminate between health and disease states, they are typically based on only a limited number of parameters. Here, we introduce immuneREF: a quantitative multidimensional measure of adaptive immune repertoire (and transcriptome) similarity that allows interpretation of immune repertoire variation by relying on both repertoire features and cross-referencing of simulated and experimental datasets. To quantify immune repertoire similarity landscapes across health and disease, we applied immuneREF to >2,400 datasets from individuals with varying immune states (healthy, [autoimmune] disease, and infection). We discovered, in contrast to the current paradigm, that blood-derived immune repertoires of healthy and diseased individuals are highly similar for certain immune states, suggesting that repertoire changes to immune perturbations are less pronounced than previously thought. In conclusion, immuneREF enables the population-wide study of adaptive immune response similarity across immune states.

Machine Learning Approaches to TCR Repertoire Analysis

Sparked by the development of genome sequencing technology, the quantity and quality of data handled in immunological research have been changing dramatically. Various data and database platforms are now driving the rapid progress of machine learning for immunological data analysis. Of various topics in immunology, T cell receptor repertoire analysis is one of the most important targets of machine learning for assessing the state and abnormalities of immune systems. In this paper, we review recent repertoire analysis methods based on machine learning and deep learning and discuss their prospects.

Development and application of a next-generation sequencing protocol and bioinformatics pipeline for the comprehensive analysis of the canine immunoglobulin repertoire

Profiling the adaptive immune repertoire using next generation sequencing (NGS) has become common in human medicine, showing promise in characterizing clonal expansion of B cell clones through analysis of B cell receptors (BCRs) in patients with lymphoid malignancies. In contrast, most work evaluating BCR repertoires in dogs has employed traditional PCR-based approaches analyzing the IGH locus only. The objectives of this study were to: (1) describe a novel NGS protocol to evaluate canine BCRs; (2) develop a bioinformatics pipeline for processing canine BCR sequencing data; and (3) apply these methods to derive insights into BCR repertoires of healthy dogs and dogs undergoing treatment for B-cell lymphoma. RNA from peripheral blood mononuclear cells of healthy dogs (n = 25) and dogs newly diagnosed with intermediate-to-large B-cell lymphoma (n = 18) with intent to pursue chemotherapy was isolated, converted into cDNA and sequenced by NGS. The BCR repertoires were identified and quantified using a novel analysis pipeline. The IGK repertoires of the healthy dogs were far less diverse compared to IGL which, as with IGH, was highly diverse. Strong biases at key positions within the CDR3 sequence were identified within the healthy dog BCR repertoire. For a subset of the dogs with B-cell lymphoma, clonal expansion of specific IGH sequences pre-treatment and reduction post-treatment was observed. The degree of expansion and reduction correlated with the clinical outcome in this subset. Future studies employing these techniques may improve disease monitoring, provide earlier recognition of disease progression, and ultimately lead to more targeted therapeutics.

Pandemic, Epidemic, Endemic: B Cell Repertoire Analysis Reveals Unique Anti-Viral Responses to SARS-CoV-2, Ebola and Respiratory Syncytial Virus

Immunoglobulin gene heterogeneity reflects the diversity and focus of the humoral immune response towards different infections, enabling inference of B cell development processes. Detailed compositional and lineage analysis of long read IGH repertoire sequencing, combining examples of pandemic, epidemic and endemic viral infections with control and vaccination samples, demonstrates general responses including increased use of IGHV4-39 in both Zaire Ebolavirus (EBOV) and COVID-19 patient cohorts. We also show unique characteristics absent in Respiratory Syncytial Virus or yellow fever vaccine samples: EBOV survivors show unprecedented high levels of class switching events while COVID-19 repertoires from acute disease appear underdeveloped. Despite the high levels of clonal expansion in COVID-19 IgG1 repertoires there is a striking lack of evidence of germinal centre mutation and selection. Given the differences in COVID-19 morbidity and mortality with age, it is also pertinent that we find significant differences in repertoire characteristics between young and old patients. Our data supports the hypothesis that a primary viral challenge can result in a strong but immature humoral response where failures in selection of the repertoire risk off-target effects.

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.

Adaptive Immune Receptor Repertoire (AIRR) Community Guide to Repertoire Analysis

Adaptive immune receptor repertoires (AIRRs) are rich with information that can be mined for insights into the workings of the immune system. Gene usage, CDR3 properties, clonal lineage structure, and sequence diversity are all capable of revealing the dynamic immune response to perturbation by disease, vaccination, or other interventions. Here we focus on a conceptual introduction to the many aspects of repertoire analysis and orient the reader toward the uses and advantages of each. Along the way, we note some of the many software tools that have been developed for these investigations and link the ideas discussed to chapters on methods provided elsewhere in this volume.

Analysis of B cell receptor repertoires reveals key signatures of systemic B cell response after SARS-CoV-2 infection

A comprehensive study of the B cell response against SARS-CoV-2 could be significant for understanding the immune response and developing therapeutical antibodies and vaccines. To define the dynamics and characteristics of the antibody repertoire following SARS-CoV-2 infection, we analyzed the mRNA transcripts of immunoglobulin heavy chain (IgH) repertoires of 24 peripheral blood samples collected between 3 and 111 days after symptom onset from 10 COVID-19 patients. Massive clonal expansion of naive B cells with limited somatic hypermutation (SHM) was observed in the second week after symptom onset. The proportion of low-SHM IgG clones strongly correlated with spike-specific IgG antibody titers, highlighting the significant activation of naive B cells in response to a novel virus infection. The antibody isotype switching landscape showed a transient IgA surge in the first week after symptom onset, followed by a sustained IgG elevation that lasted for at least 3 months. SARS-CoV-2 infection elicited poly-germ line reactive antibody responses. Interestingly, 17 different IGHV germ line genes recombined with IGHJ6 showed significant clonal expansion. By comparing the IgH repertoires that we sequenced with the 774 reported SARS-CoV-2–reactive monoclonal antibodies (MAbs), 13 shared spike-specific IgH clusters were found. These shared spike-specific IgH clusters are derived from the same lineage of several recently published neutralizing MAbs, including CC12.1, CC12.3, C102, REGN10977, and 4A8. Furthermore, identical spike-specific IgH sequences were found in different COVID-19 patients, suggesting a highly convergent antibody response to SARS-CoV-2. Our analysis based on sequencing antibody repertoires from different individuals revealed key signatures of the systemic B cell response induced by SARS-CoV-2 infection.

IMPORTANCE Although the canonical delineation of serum antibody responses following SARS-CoV-2 infection has been well established, the dynamics of antibody repertoire at the mRNA transcriptional level has not been well understood, especially the correlation between serum antibody titers and the antibody mRNA transcripts. In this study, we analyzed the IgH transcripts and characterized the B cell clonal expansion and differentiation, isotype switching, and somatic hypermutation in COVID-19 patients. This study provided insights at the repertoire level for the B cell response after SARS-CoV-2 infection.

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.

Tumor-Infiltrating B- and T-Cell Repertoire in Pancreatic Cancer Associated With Host and Tumor Features

Background

Infiltrating B and T cells have been observed in several tumor tissues, including pancreatic ductal adenocarcinoma (PDAC). The majority known PDAC risk factors point to a chronic inflammatory process leading to different forms of immunological infiltration. Understanding pancreatic tumor infiltration may lead to improved knowledge of this devastating disease.

Methods

We extracted the immunoglobulins (IGs) and T cell receptors (TCRs) from RNA-sequencing of 144 PDAC from TCGA and 180 pancreatic normal tissue from GTEx. We used Shannon entropy to find differences in IG/TCR diversity. We performed a clonotype analysis considering the IG clone definition (same V and J segments, same CDR3 length, and 90% nucleotide identity between CDR3s) to study differences among the tumor samples. Finally, we performed an association analysis to find host and tumor factors associated with the IG/TCR.

Results

PDAC presented a richer and more diverse IG and TCR infiltration than normal pancreatic tissue. A higher IG infiltration was present in heavy smokers and females and it was associated with better overall survival. In addition, specific IG clonotypes classified samples with better prognosis explaining 24% of the prognosis phenotypic variance. On the other hand, a larger TCR infiltration was present in patients with previous history of diabetes and was associated with lower nonantigen load.

Conclusions

Our findings support PDAC subtyping according to its immune repertoire landscape with a potential impact on the understanding of the inflammatory basis of PDAC risk factors as well as the design of treatment options and prognosis monitoring.

Insights From Single Cell RNA Sequencing Into the Immunology of Type 1 Diabetes- Cell Phenotypes and Antigen Specificity

In the past few years, huge advances have been made in techniques to analyse cells at an individual level using RNA sequencing, and many of these have precipitated exciting discoveries in the immunology of type 1 diabetes (T1D). This review will cover the first papers to use scRNAseq to characterise human lymphocyte phenotypes in T1D in the peripheral blood, pancreatic lymph nodes and islets. These have revealed specific genes such as IL-32 that are differentially expressed in islet -specific T cells in T1D. scRNAseq has also revealed wider gene expression patterns that are involved in T1D and can predict its development even predating autoantibody production. Single cell sequencing of TCRs has revealed V genes and CDR3 motifs that are commonly used to target islet autoantigens, although truly public TCRs remain elusive. Little is known about BCR repertoires in T1D, but scRNAseq approaches have revealed that insulin binding BCRs commonly use specific J genes, share motifs between donors and frequently demonstrate poly-reactivity. This review will also summarise new developments in scRNAseq technology, the insights they have given into other diseases and how they could be leveraged to advance research in the type 1 diabetes field to identify novel biomarkers and targets for immunotherapy.

Massive surge of mRNA expression of clonal B-cell receptor in patients with COVID-19

Background

Antibody production is one of the primary mechanisms for recovery from coronavirus disease 2019 (COVID-19). It is speculated that massive clonal expansion of B cells, which can produce clinically meaningful neutralizing antibodies, occurs in patients who recover on the timing of acquiring adaptive immunity.

Methods

To evaluate fluctuations in clonal B cells and the size of the clones, we chronologically assessed the B-cell receptor (BCR) repertoire in three patients with COVID-19 who recovered around 10 days after symptom onset.

Results

We focused on the three dominant clonotypes (top 3) in each individual. The percentage frequencies of the top 3 clonotypes increased rapidly and accounted for 27.8 % on day 9 in patient 1, 10.4 % on day 12 in patient 2, and 10.8 % on day 11 in patient 3, respectively. The frequencies of these top 3 clonotypes rapidly decreased as the patients’ clinical symptoms improved. Furthermore, BCR network analysis revealed that accumulation of clusters composed of similar complementarity-determining region 3 (CDR3) sequences were rapidly formed, grew, and reached their maximum size around 10 days after symptom onset.

Conclusions

BCR repertoire analysis revealed that a massive surge of some unique BCRs occurs during the acquisition of adaptive immunity and recovery. The peaks were more prominent than expected. These results provide insight into the important role of BCRs in the recovery from COVID-19 and raise the possibility of developing neutralizing antibodies as COVID-19 immunotherapy.

SARS-CoV-2 mRNA vaccines induce persistent human germinal centre responses

SARS-CoV-2 mRNA-based vaccines are about 95% effective in preventing COVID-191-5. The dynamics of antibody-secreting plasmablasts and germinal centre B cells induced by these vaccines in humans remain unclear. Here we examined antigen-specific B cell responses in peripheral blood (n = 41) and draining lymph nodes in 14 individuals who had received 2 doses of BNT162b2, an mRNA-based vaccine that encodes the full-length SARS-CoV-2 spike (S) gene1. Circulating IgG- and IgA-secreting plasmablasts that target the S protein peaked one week after the second immunization and then declined, becoming undetectable three weeks later. These plasmablast responses preceded maximal levels of serum anti-S binding and neutralizing antibodies to an early circulating SARS-CoV-2 strain as well as emerging variants, especially in individuals who had previously been infected with SARS-CoV-2 (who produced the most robust serological responses). By examining fine needle aspirates of draining axillary lymph nodes, we identified germinal centre B cells that bound S protein in all participants who were sampled after primary immunization. High frequencies of S-binding germinal centre B cells and plasmablasts were sustained in these draining lymph nodes for at least 12 weeks after the booster immunization. S-binding monoclonal antibodies derived from germinal centre B cells predominantly targeted the receptor-binding domain of the S protein, and fewer clones bound to the N-terminal domain or to epitopes shared with the S proteins of the human betacoronaviruses OC43 and HKU1. These latter cross-reactive B cell clones had higher levels of somatic hypermutation as compared to those that recognized only the SARS-CoV-2 S protein, which suggests a memory B cell origin. Our studies demonstrate that SARS-CoV-2 mRNA-based vaccination of humans induces a persistent germinal centre B cell response, which enables the generation of robust humoral immunity.

Single-cell multi-omics analysis of the immune response in COVID-19

Analysis of human blood immune cells provides insights into the coordinated response to viral infections such as severe acute respiratory syndrome coronavirus 2, which causes coronavirus disease 2019 (COVID-19). We performed single-cell transcriptome, surface proteome and T and B lymphocyte antigen receptor analyses of over 780,000 peripheral blood mononuclear cells from a cross-sectional cohort of 130 patients with varying severities of COVID-19. We identified expansion of nonclassical monocytes expressing complement transcripts (CD16+C1QA/B/C+) that sequester platelets and were predicted to replenish the alveolar macrophage pool in COVID-19. Early, uncommitted CD34+ hematopoietic stem/progenitor cells were primed toward megakaryopoiesis, accompanied by expanded megakaryocyte-committed progenitors and increased platelet activation. Clonally expanded CD8+ T cells and an increased ratio of CD8+ effector T cells to effector memory T cells characterized severe disease, while circulating follicular helper T cells accompanied mild disease. We observed a relative loss of IgA2 in symptomatic disease despite an overall expansion of plasmablasts and plasma cells. Our study highlights the coordinated immune response that contributes to COVID-19 pathogenesis and reveals discrete cellular components that can be targeted for therapy.

Current strategies for detecting functional convergence across B-cell receptor repertoires

Convergence across B-cell receptor (BCR) and antibody repertoires has become instrumental in prioritizing candidates in recent rapid therapeutic antibody discovery campaigns. It has also increased our understanding of the immune system, providing evidence for the preferential selection of BCRs to particular (immunodominant) epitopes post vaccination/infection. These important implications for both drug discovery and immunology mean that it is essential to consider the optimal way to combine experimental and computational technology when probing BCR repertoires for convergence signatures. Here, we discuss the theoretical basis for observing BCR repertoire functional convergence and explore factors of study design that can impact functional signal. We also review the computational arsenal available to detect antibodies with similar functional properties, highlighting opportunities enabled by recent clustering algorithms that exploit structural similarities between BCRs. Finally, we suggest future areas of development that should increase the power of BCR repertoire functional clustering.

Dynamic regulation of hypoxia-inducible factor-1α activity is essential for normal B cell development

B lymphocyte development and selection are central to adaptive immunity and self-tolerance. These processes require B cell receptor (BCR) signaling and occur in bone marrow, an environment with variable hypoxia, but whether hypoxia-inducible factor (HIF) is involved is unknown. We show that HIF activity is high in human and murine bone marrow pro-B and pre-B cells and decreases at the immature B cell stage. This stage-specific HIF suppression is required for normal B cell development because genetic activation of HIF-1α in murine B cells led to reduced repertoire diversity, decreased BCR editing and developmental arrest of immature B cells, resulting in reduced peripheral B cell numbers. HIF-1α activation lowered surface BCR, CD19 and B cell-activating factor receptor and increased expression of proapoptotic BIM. BIM deletion rescued the developmental block. Administration of a HIF activator in clinical use markedly reduced bone marrow and transitional B cells, which has therapeutic implications. Together, our work demonstrates that dynamic regulation of HIF-1α is essential for normal B cell development.

Immune Literacy: Reading, Writing, and Editing Adaptive Immunity

Advances in reading, writing, and editing DNA are providing unprecedented insights into the complexity of immunological systems. This combination of systems and synthetic biology methods is enabling the quantitative and precise understanding of molecular recognition in adaptive immunity, thus providing a framework for reprogramming immune responses for translational medicine. In this review, we will highlight state-of-the-art methods such as immune repertoire sequencing, immunoinformatics, and immunogenomic engineering and their application toward adaptive immunity. We showcase novel and interdisciplinary approaches that have the promise of transforming the design and breadth of molecular and cellular immunotherapies.

Incomplete genetic reconstitution of B cell pools contributes to prolonged immunosuppression after measles

Measles is a disease caused by the highly infectious measles virus (MeV) that results in both viremia and lymphopenia. Lymphocyte counts recover shortly after the disappearance of measles-associated rash, but immunosuppression can persist for months to years after infection, resulting in increased incidence of secondary infections. Animal models and in vitro studies have proposed various immunological factors underlying this prolonged immune impairment, but the precise mechanisms operating in humans are unknown. Using B cell receptor (BCR) sequencing of human peripheral blood lymphocytes before and after MeV infection, we identified two immunological consequences from measles underlying immunosuppression: (i) incomplete reconstitution of the naïve B cell pool leading to immunological immaturity and (ii) compromised immune memory to previously encountered pathogens due to depletion of previously expanded B memory clones. Using a surrogate model of measles in ferrets, we investigated the clinical consequences of morbillivirus infection and demonstrated a depletion of vaccine-acquired immunity to influenza virus, leading to a compromised immune recall response and increased disease severity after secondary influenza virus challenge. Our results show that MeV infection causes changes in naïve and memory B lymphocyte diversity that persist after the resolution of clinical disease and thus contribute to compromised immunity to previous infections or vaccinations. This work highlights the importance of MeV vaccination not only for the control of measles but also for the maintenance of herd immunity to other pathogens, which can be compromised after MeV infection.

Data Integration for Immunology

Over the last several years, next-generation sequencing and its recent push toward single-cell resolution have transformed the landscape of immunology research by revealing novel complexities about all components of the immune system. With the vast amounts of diverse data currently being generated, and with the methods of analyzing and combining diverse data improving as well, integrative systems approaches are becoming more powerful. Previous integrative approaches have combined multiple data types and revealed ways that the immune system, both as a whole and as individual parts, is affected by genetics, the microbiome, and other factors. In this review, we explore the data types that are available for studying immunology with an integrative systems approach, as well as the current strategies and challenges for conducting such analyses.

Ultrasensitive amplicon barcoding for next-generation sequencing facilitating sequence error and amplification-bias correction

The ability to accurately characterize DNA variant proportions using PCR amplification is key to many genetic studies, including studying tumor heterogeneity, 16S microbiome, viral and immune receptor sequencing. We develop a novel generalizable ultrasensitive amplicon barcoding approach that significantly reduces the inflation/deflation of DNA variant proportions due to PCR amplification biases and sequencing errors. This method was applied to immune receptor sequencing, where it significantly improves the quality and estimation of diversity of the resulting library.

Network Organization of Antibody Interactions in Sequence and Structure Space: the RADARS Model

Adaptive immunity in vertebrates is a complex self-organizing network of molecular interactions. While deep sequencing of the immune-receptor repertoire may reveal clonal relationships, functional interpretation of such data is hampered by the inherent limitations of converting sequence to structure to function. In this paper, a novel model of antibody interaction space and network, termed radial adjustment of system resolution, RAdial ADjustment of System Resolution (RADARS), is proposed. The model is based on the radial growth of interaction affinity of antibodies towards an infinity of directions in structure space, each direction corresponding to particular shapes of antigen epitopes. Levels of interaction affinity appear as free energy shells of the system, where hierarchical B-cell development and differentiation takes place. Equilibrium in this immunological thermodynamic system can be described by a power law distribution of antibody-free energies with an ideal network degree exponent of phi square, representing a scale-free fractal network of antibody interactions. Plasma cells are network hubs, memory B cells are nodes with intermediate degrees, and B1 cells function as nodes with minimal degree. Overall, the RADARS model implies that a finite number of antibody structures can interact with an infinite number of antigens by immunologically controlled adjustment of interaction energy distribution. Understanding quantitative network properties of the system should help the organization of sequence-derived predicted structural data.

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.

Genetic modification of primary human B cells to model high-grade lymphoma

Sequencing studies of diffuse large B cell lymphoma (DLBCL) have identified hundreds of recurrently altered genes. However, it remains largely unknown whether and how these mutations may contribute to lymphomagenesis, either individually or in combination. Existing strategies to address this problem predominantly utilize cell lines, which are limited by their initial characteristics and subsequent adaptions to prolonged in vitro culture. Here, we describe a co-culture system that enables the ex vivo expansion and viral transduction of primary human germinal center B cells. Incorporation of CRISPR/Cas9 technology enables high-throughput functional interrogation of genes recurrently mutated in DLBCL. Using a backbone of BCL2 with either BCL6 or MYC, we identify co-operating genetic alterations that promote growth or even full transformation into synthetically engineered DLBCL models. The resulting tumors can be expanded and sequentially transplanted in vivo, providing a scalable platform to test putative cancer genes and to create mutation-directed, bespoke lymphoma models.

Analysis of the B cell receptor repertoire in six immune-mediated diseases

B cells are important in the pathogenesis of many, and perhaps all, immune-mediated diseases (IMDs). Each B cell expresses a single B cell receptor (BCR)¹, with the diverse range of BCRs expressed by an individual’s total B cell population being termed the “BCR repertoire”. Our understanding of the BCR repertoire in the context of IMDs is incomplete, and defining this could reveal new insights into pathogenesis and therapy. We therefore compared the BCR repertoire in systemic lupus erythematosus (SLE), ANCA-associated vasculitis (AAV), Crohn’s disease (CD), Behçet’s disease (BD), eosinophilic granulomatosis with polyangiitis (EGPA) and IgA vasculitis (IgAV), analysing BCR clonality, and immunoglobulin heavy chain gene (IGHV) and, in particular, isotype usage. An IgA-dominated increased clonality in SLE and CD, together with skewed IGHV gene usage in these and other diseases, suggested a microbial contribution to pathogenesis. Different immunosuppressive treatment had specific and distinct impacts on the repertoire; B cells persisting after rituximab were predominately isotype-switched and clonally expanded, the inverse of those persisting after mycophenolate mofetil. A comparative analysis of the BCR repertoire in immune-mediated disease reveals a complex B cell architecture, providing a platform for understanding pathological mechanisms and designing treatment strategies.

The Genomic and Immune Landscapes of Lethal Metastatic Breast Cancer

The detailed molecular characterization of lethal cancers is a prerequisite to understanding resistance to therapy and escape from cancer immunoediting. We performed extensive multi-platform profiling of multi-regional metastases in autopsies from 10 patients with therapy-resistant breast cancer. The integrated genomic and immune landscapes show that metastases propagate and evolve as communities of clones, reveal their predicted neo-antigen landscapes, and show that they can accumulate HLA loss of heterozygosity (LOH). The data further identify variable tumor microenvironments and reveal, through analyses of T cell receptor repertoires, that adaptive immune responses appear to co-evolve with the metastatic genomes. These findings reveal in fine detail the landscapes of lethal metastatic breast cancer.

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.

FcγRIIb differentially regulates pre-immune and germinal center B cell tolerance in mouse and human

Several tolerance checkpoints exist throughout B cell development to control autoreactive B cells and prevent the generation of pathogenic autoantibodies. FcγRIIb is an Fc receptor that inhibits B cell activation and, if defective, is associated with autoimmune disease, yet its impact on specific B cell tolerance checkpoints is unknown. Here we show that reduced expression of FcγRIIb enhances the deletion and anergy of autoreactive immature B cells, but in contrast promotes autoreactive B cell expansion in the germinal center and serum autoantibody production, even in response to exogenous, non-self antigens. Our data thus show that FcγRIIb has opposing effects on pre-immune and post-immune tolerance checkpoints, and suggest that B cell tolerance requires the control of bystander germinal center B cells with low or no affinity for the immunizing antigen.

The inhibitory receptor, FcγRIIb, is reported to limit autoimmune B cell response. Here the authors show that FcγRIIb has a dual role in both human and mouse, with reduced FcγRIIb expression or function associated with enhanced pre-immune B cell tolerance, yet defective control of mature autoreactive B cells in the germinal center.

Characterizing pre-transplant and post-transplant kidney rejection risk by B cell immune repertoire sequencing

Studying immune repertoire in the context of organ transplant provides important information on how adaptive immunity may contribute and modulate graft rejection. Here we characterize the peripheral blood immune repertoire of individuals before and after kidney transplant using B cell receptor sequencing in a longitudinal clinical study. Individuals who develop rejection after transplantation have a more diverse immune repertoire before transplant, suggesting a predisposition for post-transplant rejection risk. Additionally, over 2 years of follow-up, patients who develop rejection demonstrate a specific set of expanded clones that persist after the rejection. While there is an overall reduction of peripheral B cell diversity, likely due to increased general immunosuppression exposure in this cohort, the detection of specific IGHV gene usage across all rejecting patients supports that a common pool of immunogenic antigens may drive post-transplant rejection. Our findings may have clinical implications for the prediction and clinical management of kidney transplant rejection.

Large-scale network analysis reveals the sequence space architecture of antibody repertoires

The architecture of mouse and human antibody repertoires is defined by the sequence similarity networks of the clones that compose them. The major principles that define the architecture of antibody repertoires have remained largely unknown. Here, we establish a high-performance computing platform to construct large-scale networks from comprehensive human and murine antibody repertoire sequencing datasets (>100,000 unique sequences). Leveraging a network-based statistical framework, we identify three fundamental principles of antibody repertoire architecture: reproducibility, robustness and redundancy. Antibody repertoire networks are highly reproducible across individuals despite high antibody sequence dissimilarity. The architecture of antibody repertoires is robust to the removal of up to 50-90% of randomly selected clones, but fragile to the removal of public clones shared among individuals. Finally, repertoire architecture is intrinsically redundant. Our analysis provides guidelines for the large-scale network analysis of immune repertoires and may be used in the future to define disease-associated and synthetic repertoires.

Unraveling the cellular origin and clinical prognostic markers of infant B-cell acute lymphoblastic leukemia using genome-wide analysis

B-cell acute lymphoblastic leukemia is the commonest childhood cancer. In infants, B-cell acute lymphoblastic leukemia remains fatal, especially in patients with t(4;11), present in ~80% of cases. The pathogenesis of t(4;11)/KMT2A-AFF1⁺ (MLL-AF4⁺) infant B-cell acute lymphoblastic leukemia remains difficult to model, and the pathogenic contribution in cancer of the reciprocal fusions resulting from derivative translocated-chromosomes remains obscure. Here, “multi-layered” genome-wide analyses and validation were performed on a total of 124 de novo cases of infant B-cell acute lymphoblastic leukemia uniformly diagnosed and treated according to the Interfant 99/06 protocol. These patients showed the most silent mutational landscape reported so far for any sequenced pediatric cancer. Recurrent mutations were exclusively found in K-RAS and N-RAS, were subclonal and were frequently lost at relapse, despite a larger number of non-recurrent/non-silent mutations. Unlike non-MLL-rearranged B-cell acute lymphoblastic leukemias, B-cell receptor repertoire analysis revealed minor, non-expanded B-cell clones in t(4;11)⁺ infant B-cell acute lymphoblastic leukemia, and RNA-sequencing showed transcriptomic similarities between t(4;11)⁺ infant B-cell acute lymphoblastic leukemias and the most immature human fetal liver hematopoietic stem and progenitor cells, confirming a “pre-VDJ” fetal cellular origin for both t(4;11) and RAS^mut. The reciprocal fusion AF4-MLL was expressed in only 45% (19/43) of the t(4;11)⁺ patients, and HOXA cluster genes are exclusively expressed in AF4-MLL-expressing patients. Importantly, AF4-MLL/HOXA-expressing patients had a significantly better 4-year event-free survival (62.4% vs. 11.7%, P=0.001), and overall survival (73.7 vs. 25.2%, P=0.016). AF4-MLL expression retained its prognostic significance when analyzed in a Cox model adjusting for risk stratification according to the Interfant-06 protocol based on age at diagnosis, white blood cell count and response to prednisone. This study has clinical implications for disease outcome and diagnostic risk-stratification of t(4;11)⁺ infant B-cell acute lymphoblastic leukemia.

Efficient Selection of Antibodies Reactive to Homologous Epitopes on Human and Mouse Hepatocyte Growth Factors by Next-Generation Sequencing-Based Analysis of the B Cell Repertoire

: YYB-101 is a humanized rabbit anti-human hepatocyte growth factor (HGF)-neutralizing antibody currently in clinical trial. To test the effect of HGF neutralization with antibody on anti-cancer T cell immunity, we generated surrogate antibodies that are reactive to the mouse homologue of the epitope targeted by YYB-101. First, we immunized a chicken with human HGF and monitored changes in the B cell repertoire by next-generation sequencing (NGS). We then extracted the VH gene repertoire from the NGS data, clustered it into components by sequence homology, and classified the components by the change in the number of unique VH sequences and the frequencies of the VH sequences within each component following immunization. Those changes should accompany the preferential proliferation and somatic hypermutation or gene conversion of B cells encoding HGF-reactive antibodies. One component showed significant increases in the number and frequencies of unique VH sequences and harbored genes encoding antibodies that were reactive to human HGF and competitive with YYB-101 for HGF binding. Some of the antibodies also reacted to mouse HGF. The selected VH sequences shared 98.3% identity and 98.9% amino acid similarity. It is therefore likely that the antibodies encoded by them all react to the epitope targeted by YYB-101.