Novel Approaches to Analyze Immunoglobulin Repertoires

Antibody-secreting cell repertoires hold high-affinity anti-rocuronium specificities that can induce anaphylaxis in vivo

BACKGROUND

Neuromuscular blocking agents (NMBAs) are muscle relaxants used to assist mechanical ventilation but lead in 1 per 10,000 anesthesia cases to severe acute hypersensitivity reactions-that is, anaphylaxis. Incidences vary between types of NMBAs. Rocuronium, a widely used nondepolarizing aminosteroid NMBA, induces among the highest anaphylaxis rates. Rocuronium-induced anaphylaxis is proposed to rely on preexisting rocuronium-binding antibodies, but no such antibodies have ever been identified.

OBJECTIVES

We sought to identify rocuronium-specific antibody repertoires from plasma cells or plasmablasts of rocuronium-immunized mice to determine the affinities, structures, and anaphylactogenic potential of these antibodies for rocuronium.

METHODS

We engrafted rocuronium onto carrier proteins allowing immunization of mice against rocuronium, screening for rocuronium-specific antibody responses, and sorting of rocuronium-specific plasma cells using droplet microfluids coupled to single-cell antibody gene (variable heavy chain [VH] and variable light chain [VL]) sequencing.

RESULTS

The 2 different repertoires of >500 VH-VL pairs were oligoclonal, comprised 3 major clonal families, and displayed convergence. Expressed as human IgG1, these antibodies demonstrated subnanomolar affinities for rocuronium with families either monospecific for rocuronium or cross-reactive only for closely related NMBAs. Expressed as human IgE, they triggered human mast cell and basophil activation, and severe passive systemic anaphylaxis in mice humanized for the IgE receptor FcεRI. Cocrystal structures between rocuronium and antibody representatives of 3 different VH-VL families revealed distinct interaction modes, with the ammonium group involved systematically in the binding interface.

CONCLUSIONS

This work identifies the epitopes of antibody reactivity to rocuronium, demonstrates anaphylactogenic potential of anti-rocuronium IgE, and establishes the first mouse model of NMBA anaphylaxis.

Efficient De Novo Assembly of 100 kb-Scale Human Functional Immunoglobulin Heavy Variable (IGHV) Gene Fragments In Vitro

Synthetic biology provides a powerful approach to functional studies of viral and microbial genomes. However, in vitro, efficient and scarless DNA manipulation on large and complex human genomes remains an inevitable challenge. Here, we de novo design and successfully assemble human functional immunoglobulin heavy variable (IGHV) gene fragments up to hundred-kilobase (kb)-sized, using an iterative in vitro assembly via Escherichia coli (E. coli) based on Gibson isothermal assembly. We describe an efficient method for "scarless" (without leaving any non-native sequences) engineering of the assembled ordered functional IGHV gene fragments, which contain complex and highly repetitive regions. Our method provides a suitable way to construct bacterial artificial chromosomes (BACs) (30-100 kb) with common materials, easy manipulations, and low cost. The construction of ordered functional IGHV gene BACs expands the synthetic biologist's chassis repertoire. It is essential for the adaptive immune response and constructing immunity humanized animal models.

Antigen-driven T cell responses in rheumatic diseases: insights from T cell receptor repertoire studies

Advances in T cell receptor (TCR) profiling techniques have substantially improved our ability to investigate T cell responses to antigens that are presented on HLA class I and class II molecules and associations between autoimmune T cells and rheumatic diseases. Early-stage studies in axial spondyloarthritis (axSpA) identified disease-associated T cell clonotypes, benefiting from the relative genetic homogeneity of the disease. However, both the genetic and the T cell immunological landscape are more complex in other rheumatic diseases. The diversity or redundancy in the TCR repertoire, epitope spreading over disease duration, genetic heterogeneity of HLA genes or other loci, and the diversity of epitopes contributing to disease pathogenesis and persistent inflammation are all likely to contribute to this complexity. TCR profiling holds promise for identifying key antigenic drivers and phenotypic T cell states that sustain autoimmunity in rheumatic diseases. Here, we review key findings from TCR repertoire studies in axSpA and other chronic inflammatory rheumatic diseases including psoriatic arthritis, rheumatoid arthritis, systemic lupus erythematosus and Sjögren syndrome. We explore how TCR profiling technologies, if applied to better controlled studies focused on early disease stages and genetically homogeneous subsets, can facilitate disease monitoring and the development of therapeutics targeting autoimmune T cells, their cognate antigens, or their underlying biology.

Expression Cloning of Antibodies from Single Human B Cells

The majority of lymphomas originate from B cells at the germinal center stage. Preferential selection of B-cell clones by a limited set of antigens has been suggested to drive lymphoma development. While recent studies in B-cell chronic lymphocytic leukemia (CLL) have shown that self-reactive B-cell receptors (BCR) can generate cell-autonomous signaling and proliferation, our knowledge about the role of BCRs for the development or survival of other lymphomas remains limited. Here, we describe a strategy to characterize the antibody reactivity of human B cells. The approach allows for unbiased characterization of the human antibody repertoire on single-cell level through the generation of recombinant monoclonal antibodies from primary human B cells of defined origin. This protocol offers a detailed description of the method starting from the flow cytometric isolation of single human B cells to the RT-PCR-based amplification of the expressed immunoglobulin (Ig) transcripts (IGH, IGK, and IGL) and their subsequent cloning into expression vectors for the in vitro production of recombinant monoclonal antibodies. The strategy may be used to obtain information about the clonal evolution of B-cell lymphomas by single-cell sequencing of Ig transcripts and on the antibody reactivity of human lymphoma B cells.

Agnostic B cell selection approach identifies antibodies against K. pneumoniae that synergistically drive complement activation

Antibody-dependent complement activation plays a key role in the natural human immune response to infections. Currently, the understanding of which antibody-antigen combinations drive a potent complement response on bacteria is limited. Here, we develop an antigen-agnostic approach to stain and single-cell sort human IgG memory B cells recognizing intact bacterial cells, keeping surface antigens in their natural context. With this method we successfully identified 29 antibodies against K. pneumoniae, a dominant cause of hospital-acquired infections with increasing antibiotic resistance. Combining genetic tools and functional analyses, we reveal that the capacity of antibodies to activate complement on K. pneumoniae critically depends on their antigenic target. Furthermore, we find that antibody combinations can synergistically activate complement on K. pneumoniae by strengthening each other's binding in an Fc-independent manner. Understanding the molecular basis of effective complement activation by antibody combinations to mimic a polyclonal response could accelerate the development of antibody-based therapies against problematic infections.

AbLEF: antibody language ensemble fusion for thermodynamically empowered property predictions

MOTIVATION

Pre-trained protein language and/or structural models are often fine-tuned on drug development properties (i.e. developability properties) to accelerate drug discovery initiatives. However, these models generally rely on a single structural conformation and/or a single sequence as a molecular representation. We present a physics-based model, whereby 3D conformational ensemble representations are fused by a transformer-based architecture and concatenated to a language representation to predict antibody protein properties. Antibody language ensemble fusion enables the direct infusion of thermodynamic information into latent space and this enhances property prediction by explicitly infusing dynamic molecular behavior that occurs during experimental measurement.

RESULTS

We showcase the antibody language ensemble fusion model on two developability properties: hydrophobic interaction chromatography retention time and temperature of aggregation (Tagg). We find that (i) 3D conformational ensembles that are generated from molecular simulation can further improve antibody property prediction for small datasets, (ii) the performance benefit from 3D conformational ensembles matches shallow machine learning methods in the small data regime, and (iii) fine-tuned large protein language models can match smaller antibody-specific language models at predicting antibody properties.

AVAILABILITY AND IMPLEMENTATION

AbLEF codebase is available at https://github.com/merck/AbLEF.

The rise of big data: deep sequencing-driven computational methods are transforming the landscape of synthetic antibody design

Synthetic antibodies (Abs) represent a category of artificial proteins capable of closely emulating the functions of natural Abs. Their in vitro production eliminates the need for an immunological response, streamlining the process of Ab discovery, engineering, and development. These artificially engineered Abs offer novel approaches to antigen recognition, paratope site manipulation, and biochemical/biophysical enhancements. As a result, synthetic Abs are fundamentally reshaping conventional methods of Ab production. This mirrors the revolution observed in molecular biology and genomics as a result of deep sequencing, which allows for the swift and cost-effective sequencing of DNA and RNA molecules at scale. Within this framework, deep sequencing has enabled the exploration of whole genomes and transcriptomes, including particular gene segments of interest. Notably, the fusion of synthetic Ab discovery with advanced deep sequencing technologies is redefining the current approaches to Ab design and development. Such combination offers opportunity to exhaustively explore Ab repertoires, fast-tracking the Ab discovery process, and enhancing synthetic Ab engineering. Moreover, advanced computational algorithms have the capacity to effectively mine big data, helping to identify Ab sequence patterns/features hidden within deep sequencing Ab datasets. In this context, these methods can be utilized to predict novel sequence features thereby enabling the successful generation of de novo Ab molecules. Hence, the merging of synthetic Ab design, deep sequencing technologies, and advanced computational models heralds a new chapter in Ab discovery, broadening our comprehension of immunology and streamlining the advancement of biological therapeutics.

Structural basis for breadth development in the HIV-1 V3-glycan targeting DH270 antibody clonal lineage

Antibody affinity maturation enables adaptive immune responses to a wide range of pathogens. In some individuals broadly neutralizing antibodies develop to recognize rapidly mutating pathogens with extensive sequence diversity. Vaccine design for pathogens such as HIV-1 and influenza has therefore focused on recapitulating the natural affinity maturation process. Here, we determine structures of antibodies in complex with HIV-1 Envelope for all observed members and ancestral states of the broadly neutralizing HIV-1 V3-glycan targeting DH270 antibody clonal B cell lineage. These structures track the development of neutralization breadth from the unmutated common ancestor and define affinity maturation at high spatial resolution. By elucidating contacts mediated by key mutations at different stages of antibody development we identified sites on the epitope-paratope interface that are the focus of affinity optimization. Thus, our results identify bottlenecks on the path to natural affinity maturation and reveal solutions for these that will inform immunogen design aimed at eliciting a broadly neutralizing immune response by vaccination.

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.

Unconstrained generation of synthetic antibody-antigen structures to guide machine learning methodology for antibody specificity prediction

Machine learning (ML) is a key technology for accurate prediction of antibody-antigen binding. Two orthogonal problems hinder the application of ML to antibody-specificity prediction and the benchmarking thereof: the lack of a unified ML formalization of immunological antibody-specificity prediction problems and the unavailability of large-scale synthetic datasets to benchmark real-world relevant ML methods and dataset design. Here we developed the Absolut! software suite that enables parameter-based unconstrained generation of synthetic lattice-based three-dimensional antibody-antigen-binding structures with ground-truth access to conformational paratope, epitope and affinity. We formalized common immunological antibody-specificity prediction problems as ML tasks and confirmed that for both sequence- and structure-based tasks, accuracy-based rankings of ML methods trained on experimental data hold for ML methods trained on Absolut!-generated data. The Absolut! framework has the potential to enable real-world relevant development and benchmarking of ML strategies for biotherapeutics design.

T cell Repertoire Profiling and the Mechanism by which HLA-B27 Causes Ankylosing Spondylitis

Purpose of Review

Ankylosing spondylitis (AS) is strongly associated with the HLA-B27 gene. The canonical function of HLA-B27 is to present antigenic peptides to CD8 lymphocytes, leading to adaptive immune responses. The ‘arthritogenic peptide’ theory as to the mechanism by which HLA-B27 induces ankylosing spondylitis proposes that HLA-B27 presents peptides derived from exogenous sources such as bacteria to CD8 lymphocytes, which subsequently cross-react with antigens at the site of inflammation of the disease, causing inflammation. This review describes findings of studies in AS involving profiling of T cell expansions and discusses future research opportunities based on these findings.

Recent Findings

Consistent with this theory, there is an expanding body of data showing that expansion of a restricted pool of CD8 lymphocytes is found in most AS patients yet only in a small proportion of healthy HLA-B27 carriers.

Summary

These exciting findings strongly support the theory that AS is driven by presentation of antigenic peptides to the adaptive immune system by HLA-B27. They point to new potential approaches to identify the exogenous and endogenous antigens involved and to potential therapies for the disease.

AIRRscape: An interactive tool for exploring B-cell receptor repertoires and antibody responses

The sequencing of antibody repertoires of B-cells at increasing coverage and depth has led to the identification of vast numbers of immunoglobulin heavy and light chains. However, the size and complexity of these Adaptive Immune Receptor Repertoire sequencing (AIRR-seq) datasets makes it difficult to perform exploratory analyses. To aid in data exploration, we have developed AIRRscape, an R Shiny-based interactive web browser application that enables B-cell receptor (BCR) and antibody feature discovery through comparisons among multiple repertoires. Using AIRR-seq data as input, AIRRscape starts by aggregating and sorting repertoires into interactive and explorable bins of germline V-gene, germline J-gene, and CDR3 length, providing a high-level view of the entire repertoire. Interesting subsets of repertoires can be quickly identified and selected, and then network topologies of CDR3 motifs can be generated for further exploration. Here we demonstrate AIRRscape using patient BCR repertoires and sequences of published monoclonal antibodies to investigate patterns of humoral immunity to three viral pathogens: SARS-CoV-2, HIV-1, and DENV (dengue virus). AIRRscape reveals convergent antibody sequences among datasets for all three pathogens, although HIV-1 antibody datasets display limited convergence and idiosyncratic responses. We have made AIRRscape available as a web-based Shiny application, along with code on GitHub to encourage its open development and use by immuno-informaticians, virologists, immunologists, vaccine developers, and other scientists that are interested in exploring and comparing multiple immune receptor repertoires.

Single-Cell Analysis and Tracking of Antigen-Specific T Cells: Integrating Paired Chain AIRR-Seq and Transcriptome Sequencing: A Method by the AIRR Community

Single-cell adaptive immune receptor repertoire sequencing (scAIRR-seq) offers the possibility to access the nucleotide sequences of paired receptor chains from T-cell receptors (TCR) or B-cell receptors (BCR ). Here we describe two protocols and the downstream bioinformatic approaches that facilitate the integrated analysis of paired T-cell receptor (TR ) alpha/beta (TRA /TRB ) AIRR-seq, RNA sequencing (RNAseq), immunophenotyping, and antigen-binding information. To illustrate the methodologies with a use case, we describe how to identify, characterize, and track SARS-CoV-2-specific T cells over multiple time points following infection with the virus. The first method allows the analysis of pools of memory CD8⁺ cells, identifying expansions and contractions of clones of interest. The second method allows the study of rare or antigen-specific cells and allows studying their changes over time.

Computational epitope binning reveals functional equivalence of sequence-divergent paratopes

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Epitope binning groups target-specific protein binders recognizing the same binding region.

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The “Epibin” method utilizes docking models to computationally predict competition and identify bins.

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Epibin recapitulated binding competition of repebody variants as determined by immunoassays.

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In addition, Epibin enabled identification of ‘paratope-equivalent’ residues in sequence-dissimilar variants.

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Computational epitope binning can scale to allow characterization of entire antigen-specific antibody repertoires.

The therapeutic efficacy of a protein binder largely depends on two factors: its binding site and its binding affinity. Advances in in vitro library display screening and next-generation sequencing have enabled accelerated development of strong binders, yet identifying their binding sites still remains a major challenge. The differentiation, or “binning”, of binders into different groups that recognize distinct binding sites on their target is a promising approach that facilitates high-throughput screening of binders that may show different biological activity. Here we study the extent to which the information contained in the amino acid sequences comprising a set of target-specific binders can be leveraged to bin them, inferring functional equivalence of their binding regions, or paratopes, based directly on comparison of the sequences, their modeled structures, or their modeled interactions. Using a leucine-rich repeat binding scaffold known as a “repebody” as the source of diversity in recognition against interleukin-6 (IL-6), we show that the “Epibin” approach introduced here effectively utilized structural modelling and docking to extract specificity information encoded in the repebody amino acid sequences and thereby successfully recapitulate IL-6 binding competition observed in immunoassays. Furthermore, our computational binning provided a basis for designing in vitro mutagenesis experiments to pinpoint specificity-determining residues. Finally, we demonstrate that the Epibin approach can extend to antibodies, retrospectively comparing its predictions to results from antigen-specific antibody competition studies. The study thus demonstrates the utility of modeling structure and binding from the amino acid sequences of different binders against the same target, and paves the way for larger-scale binning and analysis of entire repertoires.

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.

Access to ultra-long IgG CDRH3 bovine antibody sequences using short read sequencing technology

The advances in high-throughput DNA sequencing and recombinant antibody technologies has presented new methods for characterizing antibody repertoires and significantly increased our understanding on the functional role of antibodies in immunity and their use in diagnostics, vaccine antigen design and as biological therapeutics. A subset of Bos taurus antibodies possesses unique ultra-long third complementary-determining region of the heavy chain (CDRH3) and are of special interest because they are thought to have unique functional abilities of broadly neutralizing properties - a functional role that has not been fully explored in vaccine development. Next generation sequencing technologies that are widely used to profile immunoglobulin (Ig) repertoires are based on short-read methods such as the Illumina technology. Although this technology has worked well in sequencing Ig V-D-J regions of most jawed vertebrates, it has faced serious technical challenges with sequencing regions in bovine Ig bearing ultra-long CDRH3 sequences, which are longer than 120 bp. To overcome this limitation, we have developed a sequencing strategy based on nested PCR products that allows sequence assembly of full-length bovine Ig heavy-chain (IgH) V-D-J regions. We have used this strategy to sequence IgH V-D-J regions of two Bos indicus breeds, Ankole and Boran. We confirm the presence of ultra-long CDRH3 sequences in IgG transcripts in both African cattle breeds, and provide preliminary evidence for differences and preferences in germline V_H, D_H and J_H allele gene usage as well as differences in the length of the VH region in the two bovine breeds. Our method provides tools that should allow more robust analyses of ultra-long CDRH3 sequences aiding antibody and epitope discovery in different cattle breeds and their role in mediating immunity.

Rarely Recognized Antibody Diversification in Covid-19 Evolution to Counteract Advanced SARS-CoV-2 Evasion Strategies, and Implications for Prophylactic Treatment

The ongoing Covid-19 pandemic underscores the importance of finding effective and safe ways to combat the virus, and to optimally understand the immune response elicited upon natural infection. This likely involves all components of the immune system, both innate and adaptive. The impetus for the rapid development of prophylactic treatment options has led to an intense focus on neutralizing antibodies (Abs), and many novel and specialized platforms have been designed to achieve that goal. B-cell immunity relies on the generation of a diverse repertoire of Abs. Their structural variation is defined in terms of amino acid composition that is encoded in the genome or acquired through somatic mutations. Yet, key examples of frequently neglected antibody diversification mechanisms involving post-translational modifications such as N- or O-linked glycosylation are present in significant portions of the population. During the last few years, these and other beyond gene sequence determined humoral immune response mechanisms have in some specific cases revealed their potent immunomodulatory effects. Nonetheless, such more unusual mechanisms have not received much attention in the context of SARS-CoV-2. Thus, with specific focus on the latter, this paper presents, (1) the rationale for considering beyond sequence determined strategies, (2) evidence for their possible involvement in Covid-19 disease evolution, (3) consequences for vaccine design exemplified by one of the vaccine candidates that is currently undergoing trial, and (4) more general implications. Based on a critical interpretation of published literature, the hypotheses developed in this study point to a crucial role of non-genetic antibody diversification mechanisms in disease evolution to counteract unique immunogenicity determinants of SARS-CoV-2 infection. The involvement of post translational mechanisms may also help explain the widely varied immune response observed, not only among different patient groups, but also in terms of their observed incompatibility with SARS-CoV-2 infection in several human cell types. The article highlights potentials and challenges of these refined humoral immune response mechanisms to most optimally target non-genetic viral evasion strategies.

Antigen discovery tools for adaptive immune receptor repertoire research

The adaptive immune system has evolved to recognize with incredible precision a large diversity of molecules. Innovations in high-throughput sequencing and bioinformatics have accelerated large-scale immune repertoire analyses and given us important insights into the behavior of the adaptive immune system. However, establishing a connection between receptor sequence and its antigen-specificity remains a challenge despite its central role in determining T and B cell fate. We discuss recent large-scale antigen discovery technologies which can be combined with adaptive immune receptor repertoire (AIRR) studies. We highlight important discoveries made using repertoire analyses in the field of host-microbe interactions.

A consideration of convalescent plasma and plasma derivatives in the care of Severely-ill patients with COVID-19

The pathogenesis and immunopathological damage of severe forms of COVID-19 resemble acute autoimmune disease sparked by SARS-CoV-2, including an early systemic overproduction of proinflammatory cytokines. Such immunopathological features provide a rationale for the use of passive immunotherapy with convalescent plasma as a source of neutralizing anti-viral antibodies and of anti-inflammatory plasma components. While convalescent plasma therapy is now being evaluated in prospective clinical trials, we further consider the therapeutic potential of human hyper immune globulins, and of heterologous, engineered and monoclonal neutralizing antibodies as anti-viral agents to treat COVID-19. Good medical practice procedures are still needed and is why we also discuss the potential use of polyclonal polyspecific immunoglobulins (IVIG), a therapeutic plasma derivative, with potent anti-inflammatory activity, in severe forms of Covid-19.

A facile technology for the high-throughput sequencing of the paired VH:VL and TCRβ:TCRα repertoires

Natively paired sequencing (NPS) of B cell receptors [variable heavy (VH) and light (VL)] and T cell receptors (TCRb and TCRa) is essential for the understanding of adaptive immunity in health and disease. Despite many recent technical advances, determining the VH:VL or TCRb:a repertoire with high accuracy and throughput remains challenging. We discovered that the recently engineered xenopolymerase, RTX, is exceptionally resistant to cell lysate inhibition in single-cell emulsion droplets. We capitalized on the characteristics of this enzyme to develop a simple, rapid, and inexpensive in-droplet overlap extension reverse transcription polymerase chain reaction method for NPS not requiring microfluidics or other specialized equipment. Using this technique, we obtained high yields (5000 to >20,000 per sample) of paired VH:VL or TCRb:a clonotypes at low cost. As a demonstration, we performed NPS on peripheral blood plasmablasts and T follicular helper cells following seasonal influenza vaccination and discovered high-affinity influenza-specific antibodies and TCRb:a.

Deep sequencing of B cell receptor repertoire

Immune repertoire is a collection of enormously diverse adaptive immune cells within an individual. As the repertoire shapes and represents immunological conditions, identification of clones and characterization of diversity are critical for understanding how to protect ourselves against various illness such as infectious diseases and cancers. Over the past several years, fast growing technologies for high throughput sequencing have facilitated rapid advancement of repertoire research, enabling us to observe the diversity of repertoire at an unprecedented level. Here, we focus on B cell receptor (BCR) repertoire and review approaches to B cell isolation and sequencing library construction. These experiments should be carefully designed according to BCR regions to be interrogated, such as heavy chain full length, complementarity determining regions, and isotypes. We also highlight preprocessing steps to remove sequencing and PCR errors with unique molecular index and bioinformatics techniques. Due to the nature of massive sequence variation in BCR, caution is warranted when interpreting repertoire diversity from error-prone sequencing data. Furthermore, we provide a summary of statistical frameworks and bioinformatics tools for clonal evolution and diversity. Finally, we discuss limitations of current BCR-seq technologies and future perspectives on advances in repertoire sequencing.

Trends in therapeutic antibody affinity maturation: From in-vitro towards next-generation sequencing approaches

Current advances in antibody engineering driving the strongest growth area in biotherapeutic agents development. Affinity improvement that is mainly important for biological activity and clinical efficacy of therapeutic antibodies, has still remained a challenging task. In the human body, during a course of immune response affinity maturation increase antibody activity by several rounds of somatic hypermutation and clonal selection in the germinal center. The final outputs are antibodies representing higher affinity and specificity against a particular antigen. In the realm of biotechnology, exploring of mutations which improve antibody affinity while preserving its specificity and stability is an extremely time-consuming and laborious process. Recent advances in computational algorithms and DNA sequencing technologies help researchers to redesign antibody structure to achieve desired properties such as improved binding affinity. In this review, we briefly described the principle of affinity maturation and different corresponding in vitro techniques. Also, we recapitulated the most recent advancements in the field of antibody affinity maturation including computational approaches and next-generation sequencing (NGS).

High-throughput single-cell sequencing of paired TCRα and TCRβ genes for the direct expression-cloning and functional analysis of murine T-cell receptors

Precise clonal and functional assessments of the T cell receptor (TCR) repertoire diversity require paired TCRα and TCRβ gene sequence information at monoclonal level. However, available single‐cell strategies are typically limited in throughput and often do not provide full‐length DNA templates for direct gene cloning. Here, we describe a high‐throughput strategy for the unbiased amplification and automated sequence analysis of paired TCRα and TCRβ genes from primary mouse T cells. The platform links cell phenotype and TCR gene sequence information at single‐cell level. Furthermore, it enables direct functional analyses through the efficient cloning of both genes and the generation of stable TCR expressing cell lines. This highly efficient workflow is a powerful tool to determine the diversity and quality of the murine T‐cell repertoire in various settings, for example in vaccine development, infectious diseases, autoimmunity, or cancer.

High-Quality Library Preparation for NGS-Based Immunoglobulin Germline Gene Inference and Repertoire Expression Analysis

Next generation sequencing (NGS) of immunoglobulin (Ig) repertoires (Rep-seq) enables examination of the adaptive immune system at an unprecedented level. Applications include studies of expressed repertoires, gene usage, somatic hypermutation levels, Ig lineage tracing and identification of genetic variation within the Ig loci through inference methods. All these applications require starting libraries that allow the generation of sequence data with low error rate and optimal representation of the expressed repertoire. Here, we provide detailed protocols for the production of libraries suitable for human Ig germline gene inference and Ig repertoire studies. Various parameters used in the process were tested in order to demonstrate factors that are critical to obtain high quality libraries. We demonstrate an improved 5'RACE technique that reduces the length constraints of Illumina MiSeq based Rep-seq analysis but allows for the acquisition of sequences upstream of Ig V genes, useful for primer design. We then describe a 5' multiplex method for library preparation, which yields full length V(D)J sequences suitable for genotype identification and novel gene inference. We provide comprehensive sets of primers targeting IGHV, IGKV, and IGLV genes. Using the optimized protocol, we produced IgM, IgG, IgK, and IgL libraries and analyzed them using the germline inference tool IgDiscover to identify expressed germline V alleles. This process additionally uncovered three IGHV, one IGKV, and six IGLV novel alleles in a single individual, which are absent from the IMGT reference database, highlighting the need for further study of Ig genetic variation. The library generation protocols presented here enable a robust means of analyzing expressed Ig repertoires, identifying novel alleles and producing individualized germline gene databases from humans.

Inferred Allelic Variants of Immunoglobulin Receptor Genes: A System for Their Evaluation, Documentation, and Naming

Immunoglobulins or antibodies are the main effector molecules of the B-cell lineage and are encoded by hundreds of variable (V), diversity (D), and joining (J) germline genes, which recombine to generate enormous IG diversity. Recently, high-throughput adaptive immune receptor repertoire sequencing (AIRR-seq) of recombined V-(D)-J genes has offered unprecedented insights into the dynamics of IG repertoires in health and disease. Faithful biological interpretation of AIRR-seq studies depends upon the annotation of raw AIRR-seq data, using reference germline gene databases to identify the germline genes within each rearrangement. Existing reference databases are incomplete, as shown by recent AIRR-seq studies that have inferred the existence of many previously unreported polymorphisms. Completing the documentation of genetic variation in germline gene databases is therefore of crucial importance. Lymphocyte receptor genes and alleles are currently assigned by the Immunoglobulins, T cell Receptors and Major Histocompatibility Nomenclature Subcommittee of the International Union of Immunological Societies (IUIS) and managed in IMGT®, the international ImMunoGeneTics information system® (IMGT). In 2017, the IMGT Group reached agreement with a group of AIRR-seq researchers on the principles of a streamlined process for identifying and naming inferred allelic sequences, for their incorporation into IMGT®. These researchers represented the AIRR Community, a network of over 300 researchers whose objective is to promote all aspects of immunoglobulin and T-cell receptor repertoire studies, including the standardization of experimental and computational aspects of AIRR-seq data generation and analysis. The Inferred Allele Review Committee (IARC) was established by the AIRR Community to devise policies, criteria, and procedures to perform this function. Formalized evaluations of novel inferred sequences have now begun and submissions are invited via a new dedicated portal (https://ogrdb.airr-community.org). Here, we summarize recommendations developed by the IARC-focusing, to begin with, on human IGHV genes-with the goal of facilitating the acceptance of inferred allelic variants of germline IGHV genes. We believe that this initiative will improve the quality of AIRR-seq studies by facilitating the description of human IG germline gene variation, and that in time, it will expand to the documentation of TR and IG genes in many vertebrate species.

Mosaic deletion patterns of the human antibody heavy chain gene locus shown by Bayesian haplotyping

Analysis of antibody repertoires by high-throughput sequencing is of major importance in understanding adaptive immune responses. Our knowledge of variations in the genomic loci encoding immunoglobulin genes is incomplete, resulting in conflicting VDJ gene assignments and biased genotype and haplotype inference. Haplotypes can be inferred using IGHJ6 heterozygosity, observed in one third of the people. Here, we propose a robust novel method for determining VDJ haplotypes by adapting a Bayesian framework. Our method extends haplotype inference to IGHD- and IGHV-based analysis, enabling inference of deletions and copy number variations in the entire population. To test this method, we generated a multi-individual data set of naive B-cell repertoires, and found allele usage bias, as well as a mosaic, tiled pattern of deleted IGHD and IGHV genes. The inferred haplotypes may have clinical implications for genetic disease predispositions. Our findings expand the knowledge that can be extracted from antibody repertoire sequencing data.

Expression Cloning of Antibodies from Single Human B Cells

The majority of lymphomas originate from B cells at the germinal center stage. Preferential selection of B-cell clones by a limited set of antigens has been suggested to drive lymphoma development. While recent studies in chronic lymphocytic leukemia have shown that self-reactive B-cell receptors (BCR) can generate cell-autonomous signaling and proliferation, our knowledge about the role of BCRs for the development or survival of other lymphomas remains limited. Here, we describe a strategy to characterize the antibody reactivity of human B cells. The approach allows the unbiased characterization of the human antibody repertoire at single-cell level through the generation of recombinant monoclonal antibodies from single primary human B cells of defined origin. This protocol offers a detailed description of the method starting from the flow-cytometric isolation of single human B cells to the reverse transcription-polymerase chain reaction (RT-PCR)-based amplification of the expressed immunoglobulin (Ig) transcripts (IGH, IGK, and IGL) and their subsequent cloning into expression vectors for the in vitro production of recombinant monoclonal antibodies. The strategy may be used to obtain information on the clonal evolution of B-cell lymphomas by single-cell sequencing of Ig transcripts and on the antibody reactivity of human lymphoma B cells.

Large-Scale Screening of HCMV-Seropositive Blood Donors Indicates that HCMV Effectively Escapes from Antibodies by Cell-Associated Spread

Immunoglobulins are only moderately effective for the treatment of human cytomegalovirus (HCMV) infections, possibly due to ineffectiveness against cell-associated virus spread. To overcome this limitation, we aimed to identify individuals with exceptional antibodies in their plasma that can efficiently block the cell-associated spread of HCMV. A Gaussia luciferase-secreting mutant of the cell-associated HCMV strain Merlin was generated, and luciferase activity evaluated as a readout for the extent of cell-associated focal spread. This reporter virus-based assay was then applied to screen plasma samples from 8400 HCMV-seropositive individuals for their inhibitory effect, including direct-acting antiviral drugs as positive controls. None of the plasmas reduced virus spread to the level of these controls. Even the top-scoring samples that partially reduced luciferase activity in the screening assay failed to inhibit focal growth when reevaluated with a more accurate, immunofluorescence-based assay. Selected sera with high neutralizing capacity against free viruses were analyzed separately, and none of them prevented the focal spread of three recent clinical HCMV isolates nor reduced the number of particles transmitted, as demonstrated with a fluorescent Merlin mutant. We concluded that donors with cell-to-cell-spread-inhibiting plasma are nonexistent or extremely rare, emphasizing cell-associated spread as a highly efficient immune escape mechanism of HCMV.

Using High-Throughput Sequencing to Characterize the Development of the Antibody Repertoire During Infections: A Case Study of HIV-1

High throughput sequencing (HTS) approaches have only recently been applied to describing the antibody/B-cell repertoire in fine detail, but these data sets have already become critical to the design of vaccines and therapeutics, and monitoring of cancer immunotherapy. As a case study, we describe the potential and present limitations of HTS studies of the Ab repertoire during infection with HIV-1. Most of the present studies restrict their analyses to lineages of specific bnAbs. We discuss future initiatives to expand this type of analysis to more complete repertoires and to improve comparing and sharing of these Ab repertoire data across studies and institutions.

Unbiased quantification of immunoglobulin diversity at the DNA level with VDJ-seq

For high-throughput sequencing and quantification of immunoglobulin repertoires, most methodologies use RNA. However, output varies enormously between recombined genes due to different promoter strengths and differential activation of lymphocyte subsets, precluding quantitation of recombinants on a per-cell basis. To date, DNA-based approaches have used V gene primer cocktails, with substantial inherent biases. Here, we describe VDJ sequencing (VDJ-seq), which accurately quantitates immunoglobulin diversity at the DNA level in an unbiased manner. This is accomplished with a single primer-extension step using biotinylated J gene primers. By addition of unique molecular identifiers (UMIs) before primer extension, we reliably remove duplicate sequences and correct for sequencing and PCR errors. Furthermore, VDJ-seq captures productive and nonproductive VDJ and DJ recombination events on a per-cell basis. Library preparation takes 3 d, with 2 d of sequencing and 1 d of data processing and analysis.

Computational Strategies for Dissecting the High-Dimensional Complexity of Adaptive Immune Repertoires

The adaptive immune system recognizes antigens via an immense array of antigen-binding antibodies and T-cell receptors, the immune repertoire. The interrogation of immune repertoires is of high relevance for understanding the adaptive immune response in disease and infection (e.g., autoimmunity, cancer, HIV). Adaptive immune receptor repertoire sequencing (AIRR-seq) has driven the quantitative and molecular-level profiling of immune repertoires, thereby revealing the high-dimensional complexity of the immune receptor sequence landscape. Several methods for the computational and statistical analysis of large-scale AIRR-seq data have been developed to resolve immune repertoire complexity and to understand the dynamics of adaptive immunity. Here, we review the current research on (i) diversity, (ii) clustering and network, (iii) phylogenetic, and (iv) machine learning methods applied to dissect, quantify, and compare the architecture, evolution, and specificity of immune repertoires. We summarize outstanding questions in computational immunology and propose future directions for systems immunology toward coupling AIRR-seq with the computational discovery of immunotherapeutics, vaccines, and immunodiagnostics.

Insights into the Structural Basis of Antibody Affinity Maturation from Next-Generation Sequencing

Affinity maturation is the process whereby the immune system generates antibodies of higher affinities during a response to antigen. It is unique in being the only evolutionary mechanism known to operate on a molecule in an organism's own body. Deciphering the structural mechanisms through which somatic mutations in antibody genes increase affinity is critical to understanding the evolution of immune repertoires. Next-generation sequencing (NGS) has allowed the reconstruction of antibody clonal lineages in response to viral pathogens, such as HIV-1, which was not possible in earlier studies of affinity maturation. Crystal structures of antibodies from these lineages bound to their target antigens have revealed, at the atomic level, how antibodies evolve to penetrate the glycan shield of envelope glycoproteins, and how viruses in turn evolve to escape neutralization. Collectively, structural studies of affinity maturation have shown that increased antibody affinity can arise from any one or any combination of multiple diverse mechanisms, including improved shape complementarity at the interface with antigen, increased buried surface area upon complex formation, additional interfacial polar or hydrophobic interactions, and preorganization or rigidification of the antigen-binding site.

Effects of spaceflight on the immunoglobulin repertoire of unimmunized C57BL/6 mice

Spaceflight has been shown to suppress the adaptive immune response, altering the distribution and function of lymphocyte populations. B lymphocytes express highly specific and highly diversified receptors, known as immunoglobulins (Ig), that directly bind and neutralize pathogens. Ig diversity is achieved through the enzymatic splicing of gene segments within the genomic DNA of each B cell in a host. The collection of Ig specificities within a host, or Ig repertoire, has been increasingly characterized in both basic research and clinical settings using high-throughput sequencing technology (HTS). We utilized HTS to test the hypothesis that spaceflight affects the B-cell repertoire. To test this hypothesis, we characterized the impact of spaceflight on the unimmunized Ig repertoire of C57BL/6 mice that were flown aboard the International Space Station (ISS) during the Rodent Research One validation flight in comparison to ground controls. Individual gene segment usage was similar between ground control and flight animals, however, gene segment combinations and the junctions in which gene segments combine was varied among animals within and between treatment groups. We also found that spontaneous somatic mutations in the IgH and Igκ gene loci were not increased. These data suggest that space flight did not affect the B cell repertoire of mice flown and housed on the ISS over a short period of time.

Adaptive Immune Receptor Repertoire Community recommendations for sharing immune-repertoire sequencing data

High-throughput sequencing of B and T cell receptors is routinely being applied in studies of adaptive immunity. The Adaptive Immune Receptor Repertoire (AIRR) Community was formed in 2015 to address issues in AIRR sequencing studies, including the development of reporting standards for the sharing of data sets.