The analysis of clonal expansions in normal and autoimmune B cell repertoires

Evaluating methods for B-cell clonal family assignment

The adaptive immune response relies on a diverse repertoire of B-cell receptors, each of which is characterized by a distinct sequence resulting from VDJ-recombination. Upon binding to an antigen, B-cells undergo clonal expansion and in a process unique to B-cells the overall binding affinity of the repertoire is further enhanced by somatic hypermutations in the receptor sequence. For B-cell repertoires it is therefore particularly important to analyze the dynamics of clonal expansion and patterns of somatic hypermutations and thus it is necessary to group the sequences into distinct clones to determine the number and identity of expanding clonal families responding to an antigen. Multiple methods are currently used to identify clones from sequences, employing distinct approaches to the problem. Until now there has not been an extensive comparison of how well these methods perform under the same conditions. Furthermore, since this is fundamentally a phylogenetics problem, we speculated that the mPTP method, which delimits species based on an analysis of changes in the underlying process of diversification, might perform as well as or better than existing methods. Here we conducted extensive simulations of B-cell repertoires under a diverse set of conditions and studied errors in clonal assignment and in downstream ancestral state reconstruction. We demonstrated that SCOPer-H consistently yielded superior results across parameters. However, this approach relies on a good reference assembly for the germline immunoglobulin genes which is lacking for many species. Using mPTP had lower error rates than tailor-made immunogenetic methods and should therefore be considered by researchers studying antibody evolution in non-model organisms without a reference genome.

Benchmarking antibody clustering methods using sequence, structural, and machine learning similarity measures for antibody discovery applications

Antibodies are proteins produced by our immune system that have been harnessed as biotherapeutics. The discovery of antibody-based therapeutics relies on analyzing large volumes of diverse sequences coming from phage display or animal immunizations. Identification of suitable therapeutic candidates is achieved by grouping the sequences by their similarity and subsequent selection of a diverse set of antibodies for further tests. Such groupings are typically created using sequence-similarity measures alone. Maximizing diversity in selected candidates is crucial to reducing the number of tests of molecules with near-identical properties. With the advances in structural modeling and machine learning, antibodies can now be grouped across other diversity dimensions, such as predicted paratopes or three-dimensional structures. Here we benchmarked antibody grouping methods using clonotype, sequence, paratope prediction, structure prediction, and embedding information. The results were benchmarked on two tasks: binder detection and epitope mapping. We demonstrate that on binder detection no method appears to outperform the others, while on epitope mapping, clonotype, paratope, and embedding clusterings are top performers. Most importantly, all the methods propose orthogonal groupings, offering more diverse pools of candidates when using multiple methods than any single method alone. To facilitate exploring the diversity of antibodies using different methods, we have created an online tool-CLAP-available at (clap.naturalantibody.com) that allows users to group, contrast, and visualize antibodies using the different grouping methods.

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.

Computational Analysis of B-Cell Receptor (BCR) Immune Repertoires with Abalign

The widespread application of high-throughput sequencing technology has generated massive sequences of B-cell receptor (BCR) immune repertoires. Computational analysis of these data has gained significant attention due to the increasing importance of immunotherapy and precision medicine. It not only reveals the diversity and dynamic changes in immune responses, contributing to the study of associated diseases, but also provides valuable information for immunodiagnostics and drug development. Recently, we introduced a BCR-specific multiple sequence alignment (MSA) method along with a comprehensive platform software called Abalign, which stands out as an excellent choice for analyzing BCR immune repertoires due to its unique high-throughput processing capability. It offers ultra-fast MSA functionality and a wide range of analytical features, including BCR/antibody extraction, clonal grouping, lineage tree construction, mutation profiling, diversity statistics, VJ gene assignment, antibody humanization, and more. Importantly, users can perform these analyses using the graphical user interface without any programming skills or scripts. In this article, we present a series of protocols that integrate Abalign's analysis modules into a cohesive workflow. This step-by-step workflow provides detailed instructions for software installation, data preparation, and comprehensive analysis of BCR immune repertoires. This workflow facilitates the efficient acquisition of comprehensive results in profiling BCR immune repertoires, offering insights into the impacts of infectious diseases, allergies, autoimmune disorders, tumor immunology, and antibody drugs. Abalign is freely available at http://cao.labshare.cn/abalign/. © 2024 Wiley Periodicals LLC. Basic Protocol 1: Resource preparation Basic Protocol 2: Analyzing BCR immune repertoires Support Protocol 1: Aiding antibody humanization Support Protocol 2: Constructing B-cell lineage trees Alternate Protocol: Running with Linux command line Basic Protocol 3: Comparing BCR immune repertoires.

Anchor Clustering for million-scale immune repertoire sequencing data

BACKGROUND

The clustering of immune repertoire data is challenging due to the computational cost associated with a very large number of pairwise sequence comparisons. To overcome this limitation, we developed Anchor Clustering, an unsupervised clustering method designed to identify similar sequences from millions of antigen receptor gene sequences. First, a Point Packing algorithm is used to identify a set of maximally spaced anchor sequences. Then, the genetic distance of the remaining sequences to all anchor sequences is calculated and transformed into distance vectors. Finally, distance vectors are clustered using unsupervised clustering. This process is repeated iteratively until the resulting clusters are small enough so that pairwise distance comparisons can be performed.

RESULTS

Our results demonstrate that Anchor Clustering is faster than existing pairwise comparison clustering methods while providing similar clustering quality. With its flexible, memory-saving strategy, Anchor Clustering is capable of clustering millions of antigen receptor gene sequences in just a few minutes.

CONCLUSIONS

This method enables the meta-analysis of immune-repertoire data from different studies and could contribute to a more comprehensive understanding of the immune repertoire data space.

Atypical B cells consist of subsets with distinct functional profiles

Atypical B cells are a population of activated B cells that are commonly enriched in individuals with chronic immune activation but are also part of a normal immune response to infection or vaccination. To better define the role of atypical B cells in the human adaptive immune response, we performed single-cell sequencing of transcriptomes, cell surface markers, and B cell receptors in individuals with chronic exposure to the malaria parasite Plasmodium falciparum, a condition known to lead to accumulation of circulating atypical B cells. We identified three previously uncharacterized populations of atypical B cells with distinct transcriptional and functional profiles and observed marked differences among these three subsets in their ability to produce immunoglobulin G upon T-cell-dependent activation. Our findings help explain the conflicting observations in prior studies regarding the function of atypical B cells and highlight their different roles in the adaptive immune response in chronic inflammatory conditions.

Yclon: Ultrafast clustering of B cell clones from high-throughput immunoglobulin repertoire sequencing data

MOTIVATION

The next-generation sequencing technologies have transformed our understanding of immunoglobulin (Ig) profiles in various immune states. Clonotyping, which groups Ig sequences into B cell clones, is crucial in investigating the diversity of repertoires and changes in antigen exposure. Despite its importance, there is no widely accepted method for clonotyping, and existing methods are computationally intensive for large sequencing datasets.

RESULTS

To address this challenge, we introduce YClon, a fast and efficient approach for clonotyping Ig repertoire data. YClon uses a hierarchical clustering approach, similar to other methods, to group Ig sequences into B cell clones in a highly sensitive and specific manner. Notably, our approach outperforms other methods by being more than 30 to 5000 times faster in processing the repertoires analyzed. Astonishingly, YClon can effortlessly handle up to 2 million Ig sequences on a standard laptop computer. This enables in-depth analysis of large and numerous antibody repertoires.

AVAILABILITY AND IMPLEMENTATION

YClon was implemented in Python3 and is freely available on GitHub.

Fast clonal family inference from large-scale B cell repertoire sequencing data

Advances in high-throughput sequencing technologies have facilitated the large-scale characterization of B cell receptor (BCR) repertoires. However, the vast amount and high diversity of the BCR sequences pose challenges for efficient and biologically meaningful analysis. Here, we introduce fastBCR, an efficient computational approach for inferring B cell clonal families from massive BCR heavy chain sequences. We demonstrate that fastBCR substantially reduces the running time while ensuring high accuracy on simulated datasets with diverse numbers of B cell lineages and varying mutation rates. We apply fastBCR to real BCR sequencing data from peripheral blood samples of COVID-19 patients, showing that the inferred clonal families display disease-associated features, as well as corresponding antigen-binding specificity and affinity. Overall, our results demonstrate the advantages of fastBCR for analyzing BCR repertoire data, which will facilitate the identification of disease-associated antibodies and improve our understanding of the B cell immune response.

Redefining serological diagnostics with immunoaffinity proteomics

Serological diagnostics is generally defined as the detection of specific human immunoglobulins developed against viral, bacterial, or parasitic diseases. Serological tests facilitate the detection of past infections, evaluate immune status, and provide prognostic information. Serological assays were traditionally implemented as indirect immunoassays, and their design has not changed for decades. The advantages of straightforward setup and manufacturing, analytical sensitivity and specificity, affordability, and high-throughput measurements were accompanied by limitations such as semi-quantitative measurements, lack of universal reference standards, potential cross-reactivity, and challenges with multiplexing the complete panel of human immunoglobulin isotypes and subclasses. Redesign of conventional serological tests to include multiplex quantification of immunoglobulin isotypes and subclasses, utilize universal reference standards, and minimize cross-reactivity and non-specific binding will facilitate the development of assays with higher diagnostic specificity. Improved serological assays with higher diagnostic specificity will enable screenings of asymptomatic populations and may provide earlier detection of infectious diseases, autoimmune disorders, and cancer. In this review, we present the major clinical needs for serological diagnostics, overview conventional immunoassay detection techniques, present the emerging immunoassay detection technologies, and discuss in detail the advantages and limitations of mass spectrometry and immunoaffinity proteomics for serological diagnostics. Finally, we explore the design of novel immunoaffinity-proteomic assays to evaluate cell-mediated immunity and advance the sequencing of clinically relevant immunoglobulins.

Single-cell analysis of human nasal mucosal IgE antibody secreting cells reveals a newly minted phenotype

Immunoglobulin (Ig) E is central to the pathogenesis of allergic conditions, including allergic fungal rhinosinusitis. However, little is known about IgE antibody secreting cells (ASCs). We performed single-cell RNA sequencing from cluster of differentiation (CD)19+ and CD19- ASCs of nasal polyps from patients with allergic fungal rhinosinusitis (n = 3). Nasal polyps were highly enriched in CD19+ ASCs. Class-switched IgG and IgA ASCs were dominant (95.8%), whereas IgE ASCs were rare (2%) and found only in the CD19+ compartment. Through Ig gene repertoire analysis, IgE ASCs shared clones with IgD-CD27- "double-negative" B cells, IgD+CD27+ unswitched memory B cells, and IgD-CD27+ switched memory B cells, suggesting ontogeny from both IgD+ and memory B cells. Transcriptionally, mucosal IgE ASCs upregulate pathways related to antigen presentation, chemotaxis, B cell receptor stimulation, and survival compared with non-IgE ASCs. Additionally, IgE ASCs have a higher expression of genes encoding lysosomal-associated protein transmembrane 5 (LAPTM5) and CD23, as well as upregulation of CD74 (receptor for macrophage inhibitory factor), store-operated Calcium entry-associated regulatory factor (SARAF), and B cell activating factor receptor (BAFFR), which resemble an early minted ASC phenotype. Overall, these findings reinforce the paradigm that human ex vivo mucosal IgE ASCs have a more immature plasma cell phenotype than other class-switched mucosal ASCs and suggest unique functional roles for mucosal IgE ASCs in concert with Ig secretion.

Abalign: a comprehensive multiple sequence alignment platform for B-cell receptor immune repertoires

The utilization of high-throughput sequencing (HTS) for B-cell receptor (BCR) immune repertoire analysis has become widespread in the fields of adaptive immunity and antibody drug development. However, the sheer volume of sequences generated by these experiments presents a challenge in data processing. Specifically, multiple sequence alignment (MSA), a critical aspect of BCR analysis, remains inadequate for handling massive BCR sequencing data and lacks the ability to provide immunoglobulin-specific information. To address this gap, we introduce Abalign, a standalone program specifically designed for ultrafast MSA of BCR/antibody sequences. Benchmark tests demonstrate that Abalign achieves comparable or even better accuracy than state-of-the-art MSA tools, and shows remarkable advantages in terms of speed and memory consumption, reducing the time required for high-throughput analysis from weeks to hours. In addition to its alignment capabilities, Abalign offers a broad range of BCR analysis features, including extracting BCRs, constructing lineage trees, assigning VJ genes, analyzing clonotypes, profiling mutations, and comparing BCR immune repertoires. With its user-friendly graphic interface, Abalign can be easily run on personal computers instead of computing clusters. Overall, Abalign is an easy-to-use and effective tool that enables researchers to analyze massive BCR/antibody sequences, leading to new discoveries in the field of immunoinformatics. The software is freely available at http://cao.labshare.cn/abalign/.

Analysis of CDR3 Sequences from T-Cell Receptor β in Acute Respiratory Distress Syndrome

Acute Respiratory Distress Syndrome (ARDS) is an illness that typically develops in people who are significantly ill or have serious injuries. ARDS is characterized by fluid build-up that occurs in the alveoli. T-cells are implicated as playing a role in the modulation of the aberrant response leading to excessive tissue damage and, eventually, ARDS. Complementarity Determining Region 3 (CDR3) sequences derived from T-cells are key players in the adaptive immune response. This response is governed by an elaborate specificity for distinct molecules and the ability to recognize and vigorously respond to repeated exposures to the same molecules. Most of the diversity in T-cell receptors (TCRs) is contained in the CDR3 regions of the heterodimeric cell-surface receptors. For this study, we employed the novel technology of immune sequencing to assess lung edema fluid. Our goal was to explore the landscape of CDR3 clonal sequences found within these samples. We obtained more than 3615 CDR3 sequences across samples in the study. Our data demonstrate that: (1) CDR3 sequences from lung edema fluid exhibit distinct clonal populations, and (2) CDR3 sequences can be further characterized based on biochemical features. Analysis of these CDR3 sequences offers insight into the CDR3-driven T-cell repertoire of ARDS. These findings represent the first step towards applications of this technology with these types of biological samples in the context of ARDS.

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.

Evolution within the body: the rise and fall of somatic Darwinism in the late nineteenth century

Originating in the work of Ernst Haeckel and Wilhelm Preyer, and advanced by a Prussian embryologist, Wilhelm Roux, the idea of struggle for existence between body parts helped to establish a framework, in which population cell dynamics rather than a predefined harmony guides adaptive changes in an organism. Intended to provide a causal-mechanical view of functional adjustments in body parts, this framework was also embraced later by early pioneers of immunology to address the question of vaccine effectiveness and pathogen resistance. As an extension of these early efforts, Elie Metchnikoff established an evolutionary vision of immunity, development, pathology, and senescence, in which phagocyte-driven selection and struggle promote adaptive changes in an organism. Despite its promising start, the idea of somatic evolution lost its appeal at the turn of the twentieth century giving way to a vision, in which an organism operates as a genetically uniform, harmonious entity.

Cancer immunotherapies: A hope for the uncurable?

The use of cancer immunotherapies is not novel but has been used over the decades in the clinic. Only recently have we found the true potential of stimulating an anti-tumor response after the breakthrough of checkpoint inhibitors. Cancer immunotherapies have become the first line treatment for many malignancies at various stages. Nevertheless, the clinical results in terms of overall survival and progression free survival were not as anticipated. Majority of cancer patients do not respond to immunotherapies and the reasons differ. Hence, further improvements for cancer immunotherapies are crucially needed. In the review, we will discuss various forms of cancer immunotherapies that are being tested or already in the clinic. Moreover, we also highlight future directions to improve such therapies.

Lineage Reconstruction of In Vitro Identified Antigen-Specific Autoreactive B Cells from Adaptive Immune Receptor Repertoires

The emergence, survival, growth and maintenance of autoreactive (AR) B-cell clones, the hallmark of humoral autoimmunity, leave their footprints in B-cell receptor repertoires. Collecting IgH sequences related to polyreactive (PR) ones from adaptive immune receptor repertoire (AIRR) datasets make the reconstruction and analysis of PR/AR B-cell lineages possible. We developed a computational approach, named ImmChainTracer, to extract members and to visualize clonal relationships of such B-cell lineages. Our approach was successfully applied on the IgH repertoires of patients suffering from monogenic hypomorphic RAG1 and 2 deficiency (pRD) or polygenic systemic lupus erythematosus (SLE) autoimmune diseases to identify relatives of AR IgH sequences and to track their fate in AIRRs. Signs of clonal expansion, affinity maturation and class-switching events in PR/AR and non-PR/AR B-cell lineages were revealed. An extension of our method towards B-cell expansion caused by any trigger (e.g., infection, vaccination or antibody development) may provide deeper insight into antigen specific B-lymphogenesis.

Pregnancy Loss and Cardiovascular Diseases in Women: Recent Findings and Potential Mechanisms

PURPOSE OF REVIEW

Pregnancy loss (PL) has been acknowledged by the American Heart Association as a risk factor for cardiovascular diseases (CVD) later in life. This review aims to sum up recent findings (< ~ 5 years), concerning the link between PL and CVD.

RECENT FINDINGS

The association between PL and risk of CVD increased with increasing number of PLs and is inversely correlated to maternal age, indicating that the association concerns euploid PLs. Likely mechanisms leading to PL and an increased risk of CVD include endothelial dysfunction, a pro-inflammatory state, antiphospholipid syndrome, autoimmunity, and genetic predisposition. PL as an independent risk factor for CVD constitutes an obvious gateway for a more targeted approach to future research, prevention, and treatment. Future research should clarify the following questions to which the answers are still unknown: whether PL is (a) directly causing the increased risk of CVD or (b) sharing pathophysiological mechanisms also leading to CVD.

Update in Molecular Testing for Intraocular Lymphoma

The diagnosis of primary vitreoretinal lymphoma and central nervous system lymphoma is challenging. In cases with intraocular involvement, vitreous biopsy plays a pivotal role. Several diagnostic tests are employed to confirm a diagnosis and include cytologic evaluation, immunohistochemistry, flow cytometry, and cytokine analysis. The limitations of these conventional diagnostic tests stem from the often paucicellular nature of vitreous biopsy specimens and the fragility of malignant cells ex vivo. Several emerging molecular techniques show promise in improving the diagnostic yield of intraocular biopsy, possibly enabling more accurate and timely diagnoses. This article will review existing diagnostic modalities for intraocular lymphoma, with an emphasis on currently available molecular tests.

Accurate measurement of microsatellite length by disrupting its tandem repeat structure

Tandem repeats of simple sequence motifs, also known as microsatellites, are abundant in the genome. Because their repeat structure makes replication error-prone, variant microsatellite lengths are often generated during germline and other somatic expansions. As such, microsatellite length variations can serve as markers for cancer. However, accurate error-free measurement of microsatellite lengths is difficult with current methods precisely because of this high error rate during amplification. We have solved this problem by using partial mutagenesis to disrupt enough of the repeat structure of initial templates so that their sequence lengths replicate faithfully. In this work, we use bisulfite mutagenesis to convert a C to a U, later read as T. Compared to untreated templates, we achieve three orders of magnitude reduction in the error rate per round of replication. By requiring agreement from two independent first copies of an initial template, we reach error rates below one in a million. We apply this method to a thousand microsatellite loci from the human genome, revealing microsatellite length distributions not observable without mutagenesis.

A multi-objective based clustering for inferring BCR clonal lineages from high-throughput B cell repertoire data

The adaptive B cell response is driven by the expansion, somatic hypermutation, and selection of B cell clonal lineages. A high number of clonal lineages in a B cell population indicates a highly diverse repertoire, while clonal size distribution and sequence diversity reflect antigen selective pressure. Identifying clonal lineages is fundamental to many repertoire studies, including repertoire comparisons, clonal tracking, and statistical analysis. Several methods have been developed to group sequences from high-throughput B cell repertoire data. Current methods use clustering algorithms to group clonally-related sequences based on their similarities or distances. Such approaches create groups by optimizing a single objective that typically minimizes intra-clonal distances. However, optimizing several objective functions can be advantageous and boost the algorithm convergence rate. Here we propose MobiLLe, a new method based on multi-objective clustering. Our approach requires V(D)J annotations to obtain the initial groups and iteratively applies two objective functions that optimize cohesion and separation within clonal lineages simultaneously. We show that our method greatly improves clonal lineage grouping on simulated benchmarks with varied mutation rates compared to other tools. When applied to experimental repertoires generated from high-throughput sequencing, its clustering results are comparable to the most performing tools and can reproduce the results of previous publications. The method based on multi-objective clustering can accurately identify clonally-related antibody sequences and presents the lowest running time among state-of-art tools. All these features constitute an attractive option for repertoire analysis, particularly in the clinical context. MobiLLe can potentially help unravel the mechanisms involved in developing and evolving B cell malignancies.

High-throughput sequencing can produce a large set of sequences and has profoundly changed our ability to study immune repertoires, particularly B cell receptor sequences. An important application is the analysis of the clonal lineage composition of B cell populations; it is the starting point of many immune repertoire studies, for instance, to differentiate between healthy individuals and those with lymphoid malignancies or other diseases. Several computational methods have been developed to identify clonal lineages from a set of B cell receptor sequences. Most of them apply clustering algorithms and optimize a single objective function that typically minimizes intra-clonal distances. However, optimizing several objective functions in parallel can benefit and increase the clustering performance and efficiency. We propose MobiLLe, the first multi-objective clonal lineage grouping method, which simultaneously optimizes two objective functions for minimizing intra-clonal diversity and maximizing inter-clonal differences. Our approach greatly improved clonal grouping on simulated benchmarks and performed comparably to the most powerful and recent methods on experimental samples. MobiLLe is computationally more efficient than existing tools and does not require any training process or hyper-parameter optimization. It can easily manage large-scale experimental repertoires, providing useful plots to help researchers detect clonally-related sequences in high-throughput B cell repertoire data.

Exploring the Diversity of the B-Cell Receptor Repertoire Through High-Throughput Sequencing

Repertoire sequencing of B cells is the high-throughput profiling of B cell receptors (BCR) expressed on the surface of B cells and of immunoglobulins (Ig) expressed by antibody secreting cells. Each BCR/Ig transcript has a unique complementarity-determining region 3 (CDR3) sequence that can be used to identify and track individual B cell lymphocytes over time and throughout different compartments of the human body. B cell differentiation can be further tracked by assessing the point mutations acquired during affinity maturation via somatic hypermutation (SHM). Here we describe a method for high-throughput sequencing of the variable region of Ig heavy-chain transcripts for repertoire analysis of human B cells on the Illumina Miseq platform.

ImmunoDataAnalyzer: a bioinformatics pipeline for processing barcoded and UMI tagged immunological NGS data

Background

Next-generation sequencing (NGS) is nowadays the most used high-throughput technology for DNA sequencing. Among others NGS enables the in-depth analysis of immune repertoires. Research in the field of T cell receptor (TCR) and immunoglobulin (IG) repertoires aids in understanding immunological diseases. A main objective is the analysis of the V(D)J recombination defining the structure and specificity of the immune repertoire. Accurate processing, evaluation and visualization of immune repertoire NGS data is important for better understanding immune responses and immunological behavior.

Results

ImmunoDataAnalyzer (IMDA) is a pipeline we have developed for automatizing the analysis of immunological NGS data. IMDA unites the functionality from carefully selected immune repertoire analysis software tools and covers the whole spectrum from initial quality control up to the comparison of multiple immune repertoires. It provides methods for automated pre-processing of barcoded and UMI tagged immune repertoire NGS data, facilitates the assembly of clonotypes and calculates key figures for describing the immune repertoire. These include commonly used clonality and diversity measures, as well as indicators for V(D)J gene segment usage and between sample similarity. IMDA reports all relevant information in a compact summary containing visualizations, calculations, and sample details, all of which serve for a more detailed overview. IMDA further generates an output file including key figures for all samples, designed to serve as input for machine learning frameworks to find models for differentiating between specific traits of samples.

Conclusions

IMDA constructs TCR and IG repertoire data from raw NGS reads and facilitates descriptive data analysis and comparison of immune repertoires. The IMDA workflow focus on quality control and ease of use for non-computer scientists. The provided output directly facilitates the interpretation of input data and includes information about clonality, diversity, clonotype overlap as well as similarity, and V(D)J gene segment usage. IMDA further supports the detection of sample swaps and cross-sample contamination that potentially occurred during sample preparation. In summary, IMDA reduces the effort usually required for immune repertoire data analysis by providing an automated workflow for processing raw NGS data into immune repertoires and subsequent analysis. The implementation is open-source and available on https://bioinformatics.fh-hagenberg.at/immunoanalyzer/.

The role of endometrial B cells in normal endometrium and benign female reproductive pathologies: a systematic review

STUDY QUESTION

What are the similarities and differences in endometrial B cells in the normal human endometrium and benign reproductive pathologies?

SUMMARY ANSWER

Endometrial B cells typically constitute <5% of total endometrial CD45+ lymphocytes, and no more than 2% of total cells in the normal endometrium, and while their relative abundance and phenotypes vary in benign gynaecological conditions, current evidence is inconsistent.

WHAT IS KNOWN ALREADY

B cells are vitally important in the mucosal immune environment and have been extensively characterized in secondary lymphoid organs and tertiary lymphoid structures (TLSs), with the associated microenvironment germinal centre. However, in the endometrium, B cells are largely overlooked, despite the crucial link between autoimmunity and reproductive pathologies and the fact that B cells are present in normal endometrium and benign female reproductive pathologies, scattered or in the form of lymphoid aggregates (LAs). A comprehensive summary of current data investigating B cells will facilitate our understanding of endometrial B cells in the endometrial mucosal immune environment.

STUDY DESIGN SIZE DURATION

This systematic review retrieved relevant studies from four databases (MEDLINE, EMBASE, Web of Science Core Collection and CINAHL) from database inception until November 2021.

PARTICIPANTS/MATERIALS SETTING METHODS

The search strategy combined the use of subject headings and relevant text words related to 'endometrium', 'B cells' and B-cell derivatives, such as 'antibody' and 'immunoglobulin'. Non-benign diseases were excluded using cancer-related free-text terms, and searches were limited to the English language and human subjects. Only peer-reviewed research papers were included. Each paper was graded as 'Good', 'Fair' or 'Poor' quality based on the NEWCASTLE-OTTAWA quality assessment scale. Only 'Good' quality papers were included.

MAIN RESULTS AND THE ROLE OF CHANCE

Twenty-seven studies met the selection criteria and were included in this review: 10 cross-sectional studies investigated B cells in the normal endometrium; and 17 case-control studies compared the characteristics of endometrial B cells in control and benign female reproductive pathologies including endometritis, endometriosis, infertility, abnormal uterine bleeding, endometrial polyps and uterine fibroids. In all studies, B cells were present in the endometrium, scattered or in the form of LAs. CD20+ B cells were more abundant in patients with endometritis, but the data were inconsistent as to whether B-cell numbers were increased in endometriosis and patients with reproductive pathologies.

LIMITATIONS REASONS FOR CAUTION

Although only 'good' quality papers were included in this systematic review, there were variations in patients' age, diagnostic criteria for different diseases and sample collection time among included studies. Additionally, a large number of the included studies only used immunohistochemistry as the identification method for endometrial B cells, which may fail to provide an accurate representation of the numbers of endometrial B cells.

WIDER IMPLICATIONS OF THE FINDINGS

Histological studies found that endometrial B cells are either scattered or surrounded by T cells in LAs: the latter structure seems to be under hormonal control throughout the menstrual cycle and resembles TLSs that have been observed in other tissues. Further characterization of endometrial B cells and LAs could offer insights to endometrial B-cell function, particularly in the context of autoimmune-associated pathologies, such as endometriosis. Additionally, clinicians should be aware of the limited value of diagnosing plasma cell infiltration using only CD138.

STUDY FUNDING/COMPETING INTERESTS

This study was funded by Finox Biotech. The authors have no conflicts of interest to declare.

PROSPERO REGISTRATION NUMBER

This systematic review was registered in PROSPERO in January 2020 (PROSPERO ID: CRD42020152915).

Longitudinal analysis of FcRL5 expression and clonal relationships among classical and atypical memory B cells following malaria

BACKGROUND

Chronic and frequently recurring infectious diseases, such as malaria, are associated with expanded populations of atypical memory B cells (MBCs). These cells are different from classical MBCs by the lack of surface markers CD21 and CD27 and increased expression of inhibitory receptors, such as FcRL5. While the phenotype and conditions leading to neogenesis of atypical MBCs in malaria-experienced individuals have been studied extensively, the origin of these cells remains equivocal. Functional similarities between FcRL5+ atypical MBCs and FcRL5+ classical MBCs have been reported, suggesting that these cells may be developmentally related.

METHODS

Here, a longitudinal analysis of FcRL5 expression in various B cell subsets was performed in two children from a high transmission region in Uganda over a 6-month period in which both children experienced a malaria episode. Using B-cell receptor (BCR)-sequencing to track clonally related cells, the connections between IgM+ and IgG+ atypical MBCs and other B cell subsets were studied.

RESULTS

The highest expression of FcRL5 was found among IgG+ atypical MBCs, but FcRL5+ cells were present in all MBC subsets. Following malaria, FcRL5 expression increased in all IgM+ MBC subsets analysed here: classical, activated, and atypical MBCs, while results for IgG+ MBC subsets were inconclusive. IgM+ atypical MBCs showed few connections with other B cell subsets, higher turnover than IgG+ atypical MBCs, and were predominantly derived from naïve B cells and FcRL5- IgM+ classical MBCs. In contrast, IgG+ atypical MBCs were clonally expanded and connected with classical MBCs. IgG+ atypical MBCs present after a malaria episode mainly originated from FcRL5+ IgG+ classical MBCs.

CONCLUSIONS

Collectively, these results suggest fundamental differences between unswitched and class-switched B cell populations and provide clues about the primary developmental pathways of atypical MBCs in malaria-experienced individuals.

Struggle within: evolution and ecology of somatic cell populations

The extent to which normal (nonmalignant) cells of the body can evolve through mutation and selection during the lifetime of the organism has been a major unresolved issue in evolutionary and developmental studies. On the one hand, stable multicellular individuality seems to depend on genetic homogeneity and suppression of evolutionary conflicts at the cellular level. On the other hand, the example of clonal selection of lymphocytes indicates that certain forms of somatic mutation and selection are concordant with the organism-level fitness. Recent DNA sequencing and tissue physiology studies suggest that in addition to adaptive immune cells also neurons, epithelial cells, epidermal cells, hematopoietic stem cells and functional cells in solid bodily organs are subject to evolutionary forces during the lifetime of an organism. Here we refer to these recent studies and suggest that the expanding list of somatically evolving cells modifies idealized views of biological individuals as radically different from collectives.

Isolation of monoclonal antibodies from anti-synthetase syndrome patients and affinity maturation by recombination of independent somatic variants

The autoimmune disease known as Jo-1 positive anti-synthetase syndrome (ASS) is characterized by circulating antibody titers to histidyl-tRNA synthetase (HARS), which may play a role in modulating the non-canonical functions of HARS. Monoclonal antibodies to HARS were isolated by single-cell screening and sequencing from three Jo-1 positive ASS patients and shown to be of high affinity, covering diverse epitope space. The immune response was further characterized by repertoire sequencing from the most productive of the donor samples. In line with previous studies of autoimmune repertoires, these antibodies tended to have long complementarity-determining region H3 sequences with more positive-charged residues than average. Clones of interest were clustered into groups with related sequences, allowing us to observe different somatic mutations in related clones. We postulated that these had found alternate structural solutions for high affinity binding, but that mutations might be transferable between clones to further enhance binding affinity. Transfer of somatic mutations between antibodies within the same clonal group was able to enhance binding affinity in a number of cases, including beneficial transfer of a mutation from a lower affinity clone into one of higher affinity. Affinity enhancement was seen with mutation transfer both between related single-cell clones, and directly from related repertoire sequences. To our knowledge, this is the first demonstration of somatic hypermutation transfer from repertoire sequences to further mature in vivo derived antibodies, and represents an additional tool to aid in affinity maturation for the development of antibodies.

Progress and challenges in mass spectrometry-based analysis of antibody repertoires

Humoral immunity is divided into the cellular B cell and protein-level antibody responses. High-throughput sequencing has advanced our understanding of both these fundamental aspects of B cell immunology as well as aspects pertaining to vaccine and therapeutics biotechnology. Although the protein-level serum and mucosal antibody repertoire make major contributions to humoral protection, the sequence composition and dynamics of antibody repertoires remain underexplored. This limits insight into important immunological and biotechnological parameters such as the number of antigen-specific antibodies, which are for example, relevant for pathogen neutralization, microbiota regulation, severity of autoimmunity, and therapeutic efficacy. High-resolution mass spectrometry (MS) has allowed initial insights into the antibody repertoire. We outline current challenges in MS-based sequence analysis of antibody repertoires and propose strategies for their resolution.

Skewing of the B cell receptor repertoire in myalgic encephalomyelitis/chronic fatigue syndrome

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a debilitating condition characterized by fatigue and post-exertional malaise, accompanied by various signs of neurological and autonomic dysfunction. ME/CFS is often triggered by an infectious episode and associated with an aberrant immune system. Here we report that ME/CFS is a disorder characterized by skewed B cell receptor gene usage. By applying a next-generation sequencing to determine the clone-based IGHV/IGHD/IGHJ repertoires, we revealed a biased usage of several IGHV genes in peripheral blood B cells from ME/CFS patients. Results of receiver operating characteristic (ROC) analysis further indicated a possibility of distinguishing patients from healthy controls, based on the skewed B cell repertoire. Meanwhile, B cell clones using IGHV3-30 and IGHV3-30-3 genes were more frequent in patients with an obvious infection-related episode at onset, and correlated to expression levels of interferon response genes in plasmablasts. Collectively, these results imply that B cell responses in ME/CFS are directed against an infectious agents or priming antigens induced before disease onset.

Motifier: An IgOme Profiler Based on Peptide Motifs Using Machine Learning

Antibodies provide a comprehensive record of the encounters with threats and insults to the immune system. The ability to examine the repertoire of antibodies in serum and discover those that best represent "discriminating features" characteristic of various clinical situations, is potentially very useful. Recently, phage display technologies combined with Next-Generation Sequencing (NGS) produced a powerful experimental methodology, coined "Deep-Panning", in which the spectrum of serum antibodies is probed. In order to extract meaningful biological insights from the tens of millions of affinity-selected peptides generated by Deep-Panning, advanced bioinformatics algorithms are a must. In this study, we describe Motifier, a computational pipeline comprised of a set of algorithms that systematically generates discriminatory peptide motifs based on the affinity-selected peptides identified by Deep-Panning. These motifs are shown to effectively characterize antibody binding activities and through the implementation of machine-learning protocols are shown to accurately classify complex antibody mixtures representing various biological conditions.

IgV somatic mutation of human anti-SARS-CoV-2 monoclonal antibodies governs neutralization and breadth of reactivity

Abs that neutralize SARS-CoV-2 are thought to provide the most immediate and effective treatment for those severely afflicted by this virus. Because coronavirus potentially diversifies by mutation, broadly neutralizing Abs are especially sought. Here, we report a possibly novel approach to rapid generation of potent broadly neutralizing human anti-SARS-CoV-2 Abs. We isolated SARS-CoV-2 spike protein-specific memory B cells by panning from the blood of convalescent subjects after infection with SARS-CoV-2 and sequenced and expressed Ig genes from individual B cells as human mAbs. All of 43 human mAbs generated in this way neutralized SARS-CoV-2. Eighteen of the forty-three human mAbs exhibited half-maximal inhibitory concentrations (IC50) of 6.7 × 10-12 M to 6.7 × 10-15 M for spike-pseudotyped virus. Seven of the human mAbs also neutralized (with IC50 < 6.7 × 10-12 M) viruses pseudotyped with mutant spike proteins (including receptor-binding domain mutants and the S1 C-terminal D614G mutant). Neutralization of the Wuhan Hu-1 founder strain and of some variants decreased when coding sequences were reverted to germline, suggesting that potency of neutralization was acquired by somatic hypermutation and selection of B cells. These results indicate that infection with SARS-CoV-2 evokes high-affinity B cell responses, some products of which are broadly neutralizing and others highly strain specific. We also identify variants that would potentially resist immunity evoked by infection with the Wuhan Hu-1 founder strain or by vaccines developed with products of that strain, suggesting evolutionary courses that SARS-CoV-2 could take.

Characterization of Plasmacytoid Dendritic Cells, Microbial Sequences, and Identification of a Candidate Public T-Cell Clone in Kikuchi-Fujimoto Disease

OBJECTIVES

Kikuchi-Fujimoto disease (KFD) is a self-limited lymphadenitis of unclear etiology. We aimed to further characterize this disease in pediatric patients, including evaluation of the CD123 immunohistochemical (IHC) staining and investigation of potential immunologic and infectious causes.

METHODS

Seventeen KFD cases and 12 controls were retrospectively identified, and the histologic and clinical features were evaluated. CD123 IHC staining was quantified by digital image analysis. Next generation sequencing was employed for comparative microbial analysis via RNAseq (5 KFD cases) and to evaluate the immune repertoire (9 KFD cases).

RESULTS

In cases of lymphadenitis with necrosis, >0.85% CD123+ cells by IHC was found to be six times more likely in cases with a final diagnosis of KFD (sensitivity 75%, specificity 87.5%). RNAseq based comparative microbial analysis did not detect novel or known pathogen sequences in KFD. A shared complementarity determining region 3 (CDR3) sequence and use of the same T-cell receptor beta variable region family was identified in KFD LNs but not controls, and was not identified in available databases.

CONCLUSIONS

Digital quantification of CD123 IHC can distinguish KFD from other necrotizing lymphadenitides. The presence of a unique shared CDR3 sequence suggests that a shared antigen underlies KFD pathogenesis.

Atlas of breast cancer infiltrated B-lymphocytes revealed by paired single-cell RNA-sequencing and antigen receptor profiling

To gain mechanistic insights into the functions and developmental dynamics of tumor-infiltrated immune cells, especially B-lymphocytes, here we combine single-cell RNA-sequencing and antigen receptor lineage analysis to characterize a large number of triple-negative breast cancer infiltrated immune cells and report a comprehensive atlas of tumor-infiltrated B-lymphocytes. The single-cell transcriptional profiles reveal significant heterogeneity in tumor-infiltrated B-cell subgroups. The single-cell antigen receptor analyses demonstrate that compared with those in peripheral blood, tumor-infiltrated B-cells have more mature and memory B-cell characteristics, higher clonality, more class switching recombination and somatic hypermutations. Combined analyses suggest local differentiation of infiltrated memory B-cells within breast tumors. The B-cell signatures based on the single-cell RNA-sequencing results are significantly associated with improved survival in breast tumor patients. Functional analyses of tumor-infiltrated B-cell populations suggest that mechanistically, B-cell subgroups may contribute to immunosurveillance through various pathways. Further dissection of tumor-infiltrated B-cell populations will provide valuable clues for tumor immunotherapy.

Immune cells infiltrating the tumour microenvironment play critical roles in disease pathogenesis and the immune response. Here the authors present the characterisation of infiltrating B cells in breast tumours by the formation of an atlas created from paired RNA sequence and antigen receptor profiling.

The Future of Blood Testing Is the Immunome

It is increasingly clear that an extraordinarily diverse range of clinically important conditions—including infections, vaccinations, autoimmune diseases, transplants, transfusion reactions, aging, and cancers—leave telltale signatures in the millions of V(D)J-rearranged antibody and T cell receptor [TR per the Human Genome Organization (HUGO) nomenclature but more commonly known as TCR] genes collectively expressed by a person’s B cells (antibodies) and T cells. We refer to these as the immunome. Because of its diversity and complexity, the immunome provides singular opportunities for advancing personalized medicine by serving as the substrate for a highly multiplexed, near-universal blood test. Here we discuss some of these opportunities, the current state of immunome-based diagnostics, and highlight some of the challenges involved. We conclude with a call to clinicians, researchers, and others to join efforts with the Adaptive Immune Receptor Repertoire Community (AIRR-C) to realize the diagnostic potential of the immunome.

Alignment free identification of clones in B cell receptor repertoires

Following antigenic challenge, activated B cells rapidly expand and undergo somatic hypermutation, yielding groups of clonally related B cells with diversified immunoglobulin receptors. Inference of clonal relationships based on the receptor sequence is an essential step in many adaptive immune receptor repertoire sequencing studies. These relationships are typically identified by a multi-step process that involves: (i) grouping sequences based on shared V and J gene assignments, and junction lengths and (ii) clustering these sequences using a junction-based distance. However, this approach is sensitive to the initial gene assignments, which are error-prone, and fails to identify clonal relatives whose junction length has changed through accumulation of indels. Through defining a translation-invariant feature space in which we cluster the sequences, we develop an alignment free clonal identification method that does not require gene assignments and is not restricted to a fixed junction length. This alignment free approach has higher sensitivity compared to a typical junction-based distance method without loss of specificity and PPV. While the alignment free procedure identifies clones that are broadly consistent with the junction-based distance method, it also identifies clones with characteristics (multiple V or J gene assignments or junction lengths) that are not detectable with the junction-based distance method.

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.

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

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

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

Identification of a unique anti-Ro60 subset with restricted serological and molecular profiles

Anti-Ro60 is one of the most common and clinically important serum autoantibodies that has a number of diagnostic and predictive capabilities. Most diagnostic laboratories report this simply as a qualitative positive/negative result. The objective of this study was to examine the clinical and serological relevance of a novel subset of anti-Ro60 in patients who display low levels of anti-Ro60 (anti-Ro60low ). We retrospectively identified anti-Ro60 sera during a 12-month period at a major immunopathology diagnostic laboratory in Australia. These all were anti-Ro60-precipitin-positive on the diagnostic gold standard counter-immuno-electrophoresis (CIEP). Lineblot immunoassay was used to stratify patients into either anti-Ro60low or anti-Ro60high subsets. We compared the medical and laboratory parameters associated with each group. Enzyme-linked immunosorbent assay (ELISA) and mass spectrometry techniques were used to analyse the serological and molecular basis behind the two subsets. Anti-Ro60low patients displayed less serological activity than anti-Ro60high patients with less intermolecular spreading, hypergammaglobulinaemia and less tendency to undergo anti-Ro60 isotype-switching than anti-Ro60high patients. Mass spectrometric typing of the anti-Ro60low subset showed restricted variable heavy chain subfamily usage and amino acid point mutations. This subset also displayed clinical relevance, being present in a number of patients with systemic autoimmune rheumatic diseases (SARD). We identify a novel anti-Ro60low patient subset that is distinct from anti-Ro60high patients serologically and molecularly. It is not clear whether they arise from common or separate origins; however, they probably have different developmental pathways to account for the stark difference in immunological maturity. We hence demonstrate significance to anti-Ro60low and justify accurate detection in the diagnostic laboratory.

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.

Benchmarking immunoinformatic tools for the analysis of antibody repertoire sequences

Summary

Antibody repertoires reveal insights into the biology of the adaptive immune system and empower diagnostics and therapeutics. There are currently multiple tools available for the annotation of antibody sequences. All downstream analyses such as choosing lead drug candidates depend on the correct annotation of these sequences; however, a thorough comparison of the performance of these tools has not been investigated. Here, we benchmark the performance of commonly used immunoinformatic tools, i.e. IMGT/HighV-QUEST, IgBLAST and MiXCR, in terms of reproducibility of annotation output, accuracy and speed using simulated and experimental high-throughput sequencing datasets.

We analyzed changes in IMGT reference germline database in the last 10 years in order to assess the reproducibility of the annotation output. We found that only 73/183 (40%) V, D and J human genes were shared between the reference germline sets used by the tools. We found that the annotation results differed between tools. In terms of alignment accuracy, MiXCR had the highest average frequency of gene mishits, 0.02 mishit frequency and IgBLAST the lowest, 0.004 mishit frequency. Reproducibility in the output of complementarity determining three regions (CDR3 amino acids) ranged from 4.3% to 77.6% with preprocessed data. In addition, run time of the tools was assessed: MiXCR was the fastest tool for number of sequences processed per unit of time. These results indicate that immunoinformatic analyses greatly depend on the choice of bioinformatics tool. Our results support informed decision-making to immunoinformaticians based on repertoire composition and sequencing platforms.

Availability and implementation

All tools utilized in the paper are free for academic use.

Supplementary information

Supplementary data are available at Bioinformatics online.

Genomic Stress Responses Drive Lymphocyte Evolvability: An Ancient and Ubiquitous Mechanism

Somatic diversification of antigen receptor genes depends on the activity of enzymes whose homologs participate in a mutagenic DNA repair in unicellular species. Indeed, by engaging error-prone polymerases, gap filling molecules and altered mismatch repair pathways, lymphocytes utilize conserved components of genomic stress response systems, which can already be found in bacteria and archaea. These ancient systems of mutagenesis and repair act to increase phenotypic diversity of microbial cell populations and operate to enhance their ability to produce fit variants during stress. Coopted by lymphocytes, the ancient mutagenic processing systems retained their diversification functions instilling the adaptive immune cells with enhanced evolvability and defensive capacity to resist infection and damage. As reviewed here, the ubiquity and conserved character of specialized variation-generating mechanisms from bacteria to lymphocytes highlight the importance of these mechanisms for evolution of life in general.

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.

Somatic hypermutation analysis for improved identification of B cell clonal families from next-generation sequencing data

Adaptive immune receptor repertoire sequencing (AIRR-Seq) offers the possibility of identifying and tracking B cell clonal expansions during adaptive immune responses. Members of a B cell clone are descended from a common ancestor and share the same initial V(D)J rearrangement, but their B cell receptor (BCR) sequence may differ due to the accumulation of somatic hypermutations (SHMs). Clonal relationships are learned from AIRR-seq data by analyzing the BCR sequence, with the most common methods focused on the highly diverse junction region. However, clonally related cells often share SHMs which have been accumulated during affinity maturation. Here, we investigate whether shared SHMs in the V and J segments of the BCR can be leveraged along with the junction sequence to improve the ability to identify clonally related sequences. We develop independent distance functions that capture junction similarity and shared mutations, and combine these in a spectral clustering framework to infer the BCR clonal relationships. Using both simulated and experimental data, we show that this model improves both the sensitivity and specificity for identifying B cell clones. Source code for this method is freely available in the SCOPer (Spectral Clustering for clOne Partitioning) R package (version 0.2 or newer) in the Immcantation framework: www.immcantation.org under the AGPLv3 license.

Gammaherpesvirus-infected germinal center cells express a distinct immunoglobulin repertoire

Germinal center B cells infected with gammaherpesvirus display altered repertoire with biased usage of lambda light chain and skewed utilization of IGHV genes.

The gammaherpesviruses (γHVs), human Kaposi sarcoma-associated herpesvirus (KSHV), EBV, and murine γHV68 are prevalent infections associated with lymphocyte pathologies. After primary infection, EBV and γHV68 undergo latent expansion in germinal center (GC) B cells and persists in memory cells. The GC reaction evolves and selects antigen-specific B cells for memory development but whether γHV passively transients or manipulates this process in vivo is unknown. Using the γHV68 infection model, we analyzed the Ig repertoire of infected and uninfected GC cells from individual mice. We found that infected cells displayed the hallmarks of affinity maturation, hypermutation, and isotype switching but underwent clonal expansion. Strikingly, infected cells displayed distinct repertoire, not found in uninfected cells, with recurrent utilization of certain Ig heavy V segments including Ighv10-1. In a manner observed with KSHV, γHV68 infected cells also displayed lambda light chain bias. Thus, γHV68 subverts GC selection to expand in a specific B cell subset during the process that develops long-lived immunologic memory.

Autoreactive IgG and IgA B Cells Evolve through Distinct Subclass Switch Pathways in the Autoimmune Disease Pemphigus Vulgaris

Lineage analysis of autoreactive B cells can reveal the origins of autoimmunity. In the autoimmune disease pemphigus vulgaris (PV), desmoglein 3 (DSG3) and DSG1 autoantibodies are predominantly of the IgG4 subclass and less frequently of IgG1 and IgA subclasses, prompting us to investigate whether anti-DSG IgG4 B cells share lineages with IgG1, IgA1, and IgA2. Combining subclass-specific B cell deep sequencing with high-throughput antibody screening, we identified 80 DSG-reactive lineages from 4 PV patients. Most anti-DSG IgG4 B cells lacked clonal relationships to other subclasses and preferentially targeted DSG adhesion domains, whereas anti-DSG IgA frequently evolved from or to other subclasses and recognized a broader range of epitopes. Our findings suggest that anti-DSG IgG4 B cells predominantly evolve independently or diverge early from other subclasses and that IgA is most often not the origin of IgG autoreactivity in PV. These data provide insight into how autoreactivity diversifies across B cell subclasses.

Ellebrecht et al. use next-generation sequencing to identify clonal relationships among antigen-specific B cells in the autoimmune disease pemphigus vulgaris. They find that autoreactive IgG4 B cells are largely clonally distinct from autoreactive IgG1 and IgA, thus elucidating the class-switch pathways that diversify and modify an autoimmune response in humans.

Understanding the human antibody repertoire

The origins of the various elements in the human antibody repertoire have been and still are subject to considerable uncertainty. Uncertainty in respect of whether the various elements have always served a specific defense function or whether they were co-opted from other organismal roles to form a crude naïve repertoire that then became more complex as combinatorial mechanisms were added. Estimates of the current size of the human antibody naïve repertoire are also widely debated with numbers anywhere from 10 million members, based on experimentally derived numbers, to in excess of one thousand trillion members or more, based on the different sequences derived from theoretical combinatorial calculations. There are questions that are relevant at both ends of this number spectrum. At the lower bound it could be questioned whether this is an insufficient repertoire size to counter all the potential antigen-bearing pathogens. At the upper bound the question is rather simpler: How can any individual interrogate such an astronomical number of antibody-bearing B cells in a timeframe that is meaningful? This review evaluates the evolutionary aspects of the adaptive immune system, the calculations that lead to the large repertoire estimates, some of the experimental evidence pointing to a more restricted repertoire whose variation appears to derive from convergent 'structure and specificity features', and includes a theoretical model that seems to support it. Finally, a solution that may reconcile the size difference anomaly, which is still a hot subject of debate, is suggested.

A spectral clustering-based method for identifying clones from high-throughput B cell repertoire sequencing data

Motivation

B cells derive their antigen-specificity through the expression of Immunoglobulin (Ig) receptors on their surface. These receptors are initially generated stochastically by somatic re-arrangement of the DNA and further diversified following antigen-activation by a process of somatic hypermutation, which introduces mainly point substitutions into the receptor DNA at a high rate. Recent advances in next-generation sequencing have enabled large-scale profiling of the B cell Ig repertoire from blood and tissue samples. A key computational challenge in the analysis of these data is partitioning the sequences to identify descendants of a common B cell (i.e. a clone). Current methods group sequences using a fixed distance threshold, or a likelihood calculation that is computationally-intensive. Here, we propose a new method based on spectral clustering with an adaptive threshold to determine the local sequence neighborhood. Validation using simulated and experimental datasets demonstrates that this method has high sensitivity and specificity compared to a fixed threshold that is optimized for these measures. In addition, this method works on datasets where choosing an optimal fixed threshold is difficult and is more computationally efficient in all cases. The ability to quickly and accurately identify members of a clone from repertoire sequencing data will greatly improve downstream analyses. Clonally-related sequences cannot be treated independently in statistical models, and clonal partitions are used as the basis for the calculation of diversity metrics, lineage reconstruction and selection analysis. Thus, the spectral clustering-based method here represents an important contribution to repertoire analysis.

Availability and implementation

Source code for this method is freely available in the SCOPe (Spectral Clustering for clOne Partitioning) R package in the Immcantation framework: www.immcantation.org under the CC BY-SA 4.0 license.

Supplementary information

Supplementary data are available at Bioinformatics online.

Cutting Edge: Ig H Chains Are Sufficient to Determine Most B Cell Clonal Relationships

B cell clonal expansion is vital for adaptive immunity. High-throughput BCR sequencing enables investigating this process but requires computational inference to identify clonal relationships. This inference usually relies on only the BCR H chain, as most current protocols do not preserve H:L chain pairing. The extent to which paired L chains aids inference is unknown. Using human single-cell paired BCR datasets, we assessed the ability of H chain-based clonal clustering to identify clones. Of the expanded clones identified, <20% grouped cells expressing inconsistent L chains. H chains from these misclustered clones contained more distant junction sequences and shared fewer V segment mutations than the accurate clones. This suggests that additional H chain information could be leveraged to refine clonal relationships. Conversely, L chains were insufficient to refine H chain-based clonal clusters. Overall, the BCR H chain alone is sufficient to identify clonal relationships with confidence.