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

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

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

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

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

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

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

A comparison of unamplified and massively multiplexed PCR amplification for murine antibody repertoire sequencing

Sequencing antibody repertoires has steadily become cheaper and easier. Sequencing methods usually rely on some form of amplification, often a massively multiplexed PCR prior to sequencing. To eliminate potential biases and create a data set that could be used for other studies, our lab compared unamplified sequencing results from the splenic heavy-chain repertoire in the mouse to those processed through two commercial applications. We also compared the use of mRNA vs total RNA, reverse transcriptase, and primer usage for cDNA synthesis and submission. The use of mRNA for cDNA synthesis resulted in higher read counts but reverse transcriptase and primer usage had no statistical effects on read count. Although most of the amplified data sets contained more antibody reads than the unamplified data set, we detected more unique V-gene segments in the unamplified data set. Although unique CDR3 detection was much lower in the unamplified data set, RNASeq detected 98% of the high frequency CDR3s. We have shown that unamplified profiling of the antibody repertoire is possible, detects more V-gene segments, and detects high frequency clones in the repertoire.

Antigen Receptor Sequence Reconstruction and Clonality Inference from scRNA-Seq Data

In this chapter, we describe TraCeR and BraCeR, our computational tools for reconstruction of paired full-length antigen receptor sequences and clonality inference from single-cell RNA-seq (scRNA-seq) data. In brief, TraCeR reconstructs T-cell receptor (TCR) sequences from scRNA-seq data by extracting sequencing reads derived from TCRs by aligning the reads from each cell against synthetic TCR sequences. TCR-derived reads are then assembled into full-length recombined TCR sequences. BraCeR builds on the TraCeR pipeline and accounts for somatic hypermutations (SHM) and isotype switching. Here we discuss experimental design, use of the tools, and interpretation of the results.

A comparison of unamplified and massively multiplexed PCR amplification for murine antibody repertoire sequencing

Sequencing antibody repertoires has steadily become cheaper and easier. Sequencing methods usually rely on some form of amplification, often a massively multiplexed PCR prior to sequencing. To eliminate potential biases and create a data set that could be used for other studies, our laboratory compared unamplified sequencing results from the splenic heavy-chain repertoire in the mouse to those processed through two commercial applications. We also compared the use of mRNA vs total RNA, reverse transcriptase, and primer usage for cDNA synthesis and submission. The use of mRNA for cDNA synthesis resulted in higher read counts but reverse transcriptase and primer usage had no statistical effects on read count. Although most of the amplified data sets contained more antibody reads than the unamplified data set, we detected more unique variable (V)-gene segments in the unamplified data set. Although unique CDR3 detection was much lower in the unamplified data set, RNASeq detected 98% of the high-frequency CDR3s. We have shown that unamplified profiling of the antibody repertoire is possible, detects more V-gene segments, and detects high-frequency clones in the repertoire.

Network Representation of T-Cell Repertoire- A Novel Tool to Analyze Immune Response to Cancer Formation

The T cell repertoire potentially presents complexity compatible, or greater than, that of the human brain. T cell based immune response is involved with practically every part of human physiology, and high-throughput biology needed to follow the T-cell repertoire has made great leaps with the advent of massive parallel sequencing [1]. Nevertheless, tools to handle and observe the dynamics of this complexity have only recently started to emerge [e.g., 2, 3, 4] in parallel with sequencing technologies. Here, we present a network-based view of the dynamics of the T cell repertoire, during the course of mammary tumors development in a mouse model. The transition from the T cell receptor as a feature, to network-based clustering, followed by network-based temporal analyses, provides novel insights to the workings of the system and provides novel tools to observe cancer progression via the perspective of the immune system. The crux of the approach here is at the network-motivated clustering. The purpose of the clustering step is not merely data reduction and exposing structures, but rather to detect hubs, or attractors, within the T cell receptor repertoire that might shed light on the behavior of the immune system as a dynamic network. The Clone-Attractor is in fact an extension of the clone concept, i.e., instead of looking at particular clones we observe the extended clonal network by assigning clusters to graph nodes and edges to adjacent clusters (editing distance metric). Viewing the system as dynamical brings to the fore the notion of an attractors landscape, hence the possibility to chart this space and map the sample state at a given time to a vector in this large space. Based on this representation we applied two different methods to demonstrate its effectiveness in identifying changes in the repertoire that correlate with changes in the phenotype: (1) network analysis of the TCR repertoire in which two measures were calculated and demonstrated the ability to differentiate control from transgenic samples, and, (2) machine learning classifier capable of both stratifying control and trangenic samples, as well as to stratify pre-cancer and cancer samples.

Tracing Antibody Repertoire Evolution by Systems Phylogeny

Antibody evolution studies have been traditionally limited to either tracing a single clonal lineage (B cells derived from a single V-(D)-J recombination) over time or examining bulk functionality changes (e.g., tracing serum polyclonal antibody proteins). Studying a single B cell disregards the majority of the humoral immune response, whereas bulk functional studies lack the necessary resolution to analyze the co-existing clonal diversity. Recent advances in high-throughput sequencing (HTS) technologies and bioinformatics have made it possible to examine multiple co-evolving antibody monoclonal lineages within the context of a single repertoire. A plethora of accompanying methods and tools have been introduced in hopes of better understanding how pathogen presence dictates the global evolution of the antibody repertoire. Here, we provide a comprehensive summary of the tremendous progress of this newly emerging field of systems phylogeny of antibody responses. We present an overview encompassing the historical developments of repertoire phylogenetics, state-of-the-art tools, and an outlook on the future directions of this fast-advancing and promising field.

Observed Antibody Space: A Resource for Data Mining Next-Generation Sequencing of Antibody Repertoires

Abs are immune system proteins that recognize noxious molecules for elimination. Their sequence diversity and binding versatility have made Abs the primary class of biopharmaceuticals. Recently, it has become possible to query their immense natural diversity using next-generation sequencing of Ig gene repertoires (Ig-seq). However, Ig-seq outputs are currently fragmented across repositories and tend to be presented as raw nucleotide reads, which means nontrivial effort is required to reuse the data for analysis. To address this issue, we have collected Ig-seq outputs from 55 studies, covering more than half a billion Ab sequences across diverse immune states, organisms (primarily human and mouse), and individuals. We have sorted, cleaned, annotated, translated, and numbered these sequences and make the data available via our Observed Antibody Space (OAS) resource at http://antibodymap.org The data within OAS will be regularly updated with newly released Ig-seq datasets. We believe OAS will facilitate data mining of immune repertoires for improved understanding of the immune system and development of better biotherapeutics.

Noninvasive Molecular Monitoring in Multiple Myeloma Patients Using Cell-Free Tumor DNA: A Pilot Study

Novel treatments for multiple myeloma (MM) have increased rates of complete response, raising interest in more accurate methods to evaluate residual disease. Cell-free tumor DNA (cfDNA) analysis may represent a minimally invasive approach complementary to multiparameter flow cytometry (MFC) and molecular methods on bone marrow aspirates. A sequencing approach using the Ion Torrent Personal Genome Machine was applied to identify clonal IGH gene rearrangements in tumor plasma cells (PCs) and in serial plasma samples of 25 patients with MM receiving second-line therapy. The same clonal IGH rearrangement identified in tumor PCs was detected in paired plasma samples, and levels of IGH cfDNA correlated with outcome and mirrored tumor dynamics evaluated using conventional laboratory parameters. In addition, IGH cfDNA levels reflected the number of PCs enumerated by MFC immunophenotyping even in the complete response context. Patients determined by MFC to be free of minimal residual disease were characterized by low frequencies of tumor clonotypes in cfDNA and longer survival. This pilot study supports the clinical applicability of the noninvasive monitoring of tumor levels in plasma samples of patients with MM by IGH sequencing.

Combined Influence of B-Cell Receptor Rearrangement and Somatic Hypermutation on B-Cell Class-Switch Fate in Health and in Chronic Lymphocytic Leukemia

A diverse B-cell receptor (BCR) repertoire is required to bind a wide range of antigens. BCRs are generated through genetic recombination and can be diversified through somatic hypermutation (SHM) or class-switch recombination (CSR). Patterns of repertoire diversity can vary substantially between different health conditions. We use isotype-resolved BCR sequencing to compare B-cell evolution and class-switch fate in healthy individuals and in patients with chronic lymphocytic leukemia (CLL). We show that the patterns of SHM and CSR in B-cells from healthy individuals are distinct from CLL. We identify distinct properties of clonal expansion that lead to the generation of antibodies of different classes in healthy, malignant, and non-malignant CLL BCR repertoires. We further demonstrate that BCR diversity is affected by relationships between antibody variable and constant regions leading to isotype-specific signatures of variable gene usage. This study provides powerful insights into the mechanisms underlying the evolution of the adaptive immune responses in health and their aberration during disease.

The era of immunogenomics/immunopharmacogenomics

Although germline alterations and somatic mutations in disease cells have been extensively analyzed, molecular changes in immune cells associated with disease conditions have not been characterized in depth. It is clear that our immune system has a critical role in various biological and pathological conditions, such as infectious diseases, autoimmune diseases, drug-induced skin and liver toxicity, food allergy, and rejection of transplanted organs. The recent development of cancer immunotherapies, particularly drugs modulating the immune checkpoint molecules, has clearly demonstrated the importance of host immune cells in cancer treatments. However, the molecular mechanisms by which these new therapies kill tumor cells are still not fully understood. In this regard, we have begun to explore the role of newly developed tools such as next-generation sequencing in the genetic characterization of both cancer cells and host immune cells, a field that is called immunogenomics/ immunopharmacogenomics. This new field has enormous potential to help us better understand changes in our immune system during the course of various disease conditions. Here we report the potential of deep sequencing of T-cell and B-cell receptors in capturing the molecular contribution of the immune system, which we believe plays critical roles in the pathogenesis of various human diseases.

Analyzing Immunoglobulin Repertoires

Somatic assembly of T cell receptor and B cell receptor (BCR) genes produces a vast diversity of lymphocyte antigen recognition capacity. The advent of efficient high-throughput sequencing of lymphocyte antigen receptor genes has recently generated unprecedented opportunities for exploration of adaptive immune responses. With these opportunities have come significant challenges in understanding the analysis techniques that most accurately reflect underlying biological phenomena. In this regard, sample preparation and sequence analysis techniques, which have largely been borrowed and adapted from other fields, continue to evolve. Here, we review current methods and challenges of library preparation, sequencing and statistical analysis of lymphocyte receptor repertoire studies. We discuss the general steps in the process of immune repertoire generation including sample preparation, platforms available for sequencing, processing of sequencing data, measurable features of the immune repertoire, and the statistical tools that can be used for analysis and interpretation of the data. Because BCR analysis harbors additional complexities, such as immunoglobulin (Ig) (i.e., antibody) gene somatic hypermutation and class switch recombination, the emphasis of this review is on Ig/BCR sequence analysis.

History, applications, and challenges of immune repertoire research

The diversity of T and B cells in terms of their receptor sequences is huge in the vertebrate's immune system and provides broad protection against the vast diversity of pathogens. Immune repertoire is defined as the sum of T cell receptors and B cell receptors (also named immunoglobulin) that makes the organism's adaptive immune system. Before the emergence of high-throughput sequencing, the studies on immune repertoire were limited by the underdeveloped methodologies, since it was impossible to capture the whole picture by the low-throughput tools. The massive paralleled sequencing technology suits perfectly the researches on immune repertoire. In this article, we review the history of immune repertoire studies, in terms of technologies and research applications. Particularly, we discuss several aspects of challenges in this field and highlight the efforts to develop potential solutions, in the era of high-throughput sequencing of the immune repertoire.

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.

IgA Function in Relation to the Intestinal Microbiota

IgA is the dominant immunoglobulin isotype produced in mammals, largely secreted across the intestinal mucosal surface. Although induction of IgA has been a hallmark feature of microbiota colonization following colonization in germ-free animals, until recently appreciation of the function of IgA in host-microbial mutualism has depended mainly on indirect evidence of alterations in microbiota composition or penetration of microbes in the absence of somatic mutations in IgA (or compensatory IgM). Highly parallel sequencing techniques that enable high-resolution analysis of either microbial consortia or IgA sequence diversity are now giving us new perspectives on selective targeting of microbial taxa and the trajectory of IgA diversification according to induction mechanisms, between different individuals and over time. The prospects are to link the range of diversified IgA clonotypes to specific antigenic functions in modulating the microbiota composition, position and metabolism to ensure host mutualism.

Studying Antibody Repertoires with Next-Generation Sequencing

Next-generation sequencing is making it possible to study the antibody repertoire of an organism in unprecedented detail, and, by so doing, to characterize its behavior in the response to infection and in pathological conditions such as autoimmunity and cancer. The polymorphic nature of the repertoire poses unique challenges that rule out the use of many commonly used NGS methods and require tradeoffs to be made when considering experimental design.We outline the main contexts in which antibody repertoire analysis has been used, and summarize the key tools that are available. The humoral immune response to vaccination has been a particular focus of repertoire analyses, and we review the key conclusions and methods used in these studies.

Characterization of the naive murine antibody repertoire using unamplified high-throughput sequencing

Antibody specificity and diversity are generated through the enzymatic splicing of genomic gene segments within each B cell. Antibodies are heterodimers of heavy- and light-chains encoded on separate loci. We studied the antibody repertoire from pooled, splenic tissue of unimmunized, adult female C57BL/6J mice, using high-throughput sequencing (HTS) without amplification of antibody transcripts. We recovered over 90,000 heavy-chain and over 135,000 light-chain immunoglobulin sequences. Individual V-, D-, and J-gene segment usage was uniform among the three mouse pools, particularly in highly abundant gene segments, with low frequency V-gene segments not being detected in all pools. Despite the similar usage of individual gene segments, the repertoire of individual B-cell CDR3 amino acid sequences in each mouse pool was highly varied, affirming the combinatorial diversity in the B-cell pool that has been previously demonstrated. There also was some skewing in the V-gene segments that were detected depending on chromosomal location. This study presents a unique, non-primer biased glimpse of the conventionally housed, unimmunized antibody repertoire of the C57BL6/J mouse.

High-throughput sequencing of the immune repertoire in oncology: Applications for clinical diagnosis, monitoring, and immunotherapies

The diagnostic, monitoring and therapeutic options for cancers currently remain limited. These limitations represent a large threat to human health. Adaptive immunity, which is dependent on diverse repertoires of B cell receptors (BCRs) and T cell receptors (TCRs), plays a critical role in the anti-tumor immune response. Modulation and surveillance of adaptive immunity has become a powerful weapon to combat cancers. Recently, the high-throughput sequencing of immune repertoire (HTS-IR) technology, which provides a robust tool for deep sequencing repertoires of BCRs or TCRs, has been applied in the development of tumor biomarkers and immunotherapeutics for cancers. This review will first provide an overview of the advancement of HTS-IR technology at the population-cell and single-cell levels. It will then provide a current summary of the applications of HTS-IR technology in the diagnosis and monitoring of minimal residual disease (MRD), focusing on immune reconstitution after the treatment of allogeneic hematopoietic stem cell transplantation (allo-HSCT) in B/T-cell malignancies, and the precise detection of tumor-infiltrating lymphocytes (TILs) in non-B/T-cell malignancies. Finally, current advances of HTS-IR technology in cancer immunotherapeutic applications, such as therapeutic antibodies, CAR-T cell based-adoptive immunotherapies, and neoantigen-specific TCR-T cell-based adoptive immunotherapies, will be introduced.

Reproducibility and Reuse of Adaptive Immune Receptor Repertoire Data

High-throughput sequencing (HTS) of immunoglobulin (B-cell receptor, antibody) and T-cell receptor repertoires has increased dramatically since the technique was introduced in 2009 (1–3). This experimental approach explores the maturation of the adaptive immune system and its response to antigens, pathogens, and disease conditions in exquisite detail. It holds significant promise for diagnostic and therapy-guiding applications. New technology often spreads rapidly, sometimes more rapidly than the understanding of how to make the products of that technology reliable, reproducible, or usable by others. As complex technologies have developed, scientific communities have come together to adopt common standards, protocols, and policies for generating and sharing data sets, such as the MIAME protocols developed for microarray experiments. The Adaptive Immune Receptor Repertoire (AIRR) Community formed in 2015 to address similar issues for HTS data of immune repertoires. The purpose of this perspective is to provide an overview of the AIRR Community’s founding principles and present the progress that the AIRR Community has made in developing standards of practice and data sharing protocols. Finally, and most important, we invite all interested parties to join this effort to facilitate sharing and use of these powerful data sets (join@airr-community.org).

Early loss of Crebbp confers malignant stem cell properties on lymphoid progenitors

Loss-of-function mutations of cyclic-AMP response element binding protein, binding protein (CREBBP) are prevalent in lymphoid malignancies. However, the tumour suppressor functions of CREBBP remain unclear. We demonstrate that loss of Crebbp in murine haematopoietic stem and progenitor cells (HSPCs) leads to increased development of B-cell lymphomas. This is preceded by accumulation of hyperproliferative lymphoid progenitors with a defective DNA damage response (DDR) due to a failure to acetylate p53. We identify a premalignant lymphoma stem cell population with decreased H3K27ac, which undergoes transcriptional and genetic evolution due to the altered DDR, resulting in lymphomagenesis. Importantly, when Crebbp is lost later in lymphopoiesis, cellular abnormalities are lost and tumour generation is attenuated. We also document that CREBBP mutations may occur in HSPCs from patients with CREBBP-mutated lymphoma. These data suggest that earlier loss of Crebbp is advantageous for lymphoid transformation and inform the cellular origins and subsequent evolution of lymphoid malignancies.

Heterogeneity of tumor-infiltrating lymphocytes ascribed to local immune status rather than neoantigens by multi-omics analysis of glioblastoma multiforme

Hypothetically, intratumoral genomic heterogeneity has the potential to foster tumor-infiltrating lymphocyte (TIL) diversity; however, no study has directly tested this hypothesis by simultaneously investigating somatic mutations, TIL diversity, and immune response activity. Thus, we performed whole-exome sequencing, immune repertoire sequencing and gene expression on ten spatially separated tumor samples obtained from two tumor masses excised from a glioblastoma multiforme (GBM) patient, and we included peripheral blood as control. We found that although the multi-region samples from one tumor shared more common mutations than those from different tumors, the TIL populations did not. TIL repertoire diversity did not significantly correlate with the number of non-synonymous mutations; however, TIL diversity was highly correlated with local immune activity, as the pathways were all immune-related pathways that highly positive correlated with local TIL diversity. Twenty-three genes with expression largely unaffected by the intratumor heterogeneity were extracted from these pathways. Fifty GBM patients were stratified into two clusters by the expression of these genes with significant difference in prognosis. This finding was validated by The Cancer Genome Atlas (TCGA) GBM dataset, which indicated that despite the heterogeneity of intra-tumor immune status, the overall level of the immune response in GBM could be connected with prognosis.

Next-generation sequencing in chronic lymphocytic leukemia: recent findings and new horizons

The rapid progress in next-generation sequencing technologies has significantly contributed to our knowledge of the genetic events associated with the development, progression and treatment resistance of chronic lymphocytic leukemia patients. Together with the discovery of new driver mutations, next-generation sequencing has revealed an immense degree of both intra- and inter-tumor heterogeneity and enabled us to describe marked clonal evolution. Advances in immunogenetics may be implemented to detect minimal residual disease more sensitively and to track clonal B cell populations, their dynamics and molecular characteristics. The interpretation of these aspects is indispensable to thoroughly examine the genetic background of chronic lymphocytic leukemia. We review and discuss the recent results provided by the different next-generation sequencing techniques used in studying the chronic lymphocytic leukemia genome, as well as future perspectives in the methodologies and applications.

T cell receptor repertoires of mice and humans are clustered in similarity networks around conserved public CDR3 sequences

Diversity of T cell receptor (TCR) repertoires, generated by somatic DNA rearrangements, is central to immune system function. However, the level of sequence similarity of TCR repertoires within and between species has not been characterized. Using network analysis of high-throughput TCR sequencing data, we found that abundant CDR3-TCRβ sequences were clustered within networks generated by sequence similarity. We discovered a substantial number of public CDR3-TCRβ segments that were identical in mice and humans. These conserved public sequences were central within TCR sequence-similarity networks. Annotated TCR sequences, previously associated with self-specificities such as autoimmunity and cancer, were linked to network clusters. Mechanistically, CDR3 networks were promoted by MHC-mediated selection, and were reduced following immunization, immune checkpoint blockade or aging. Our findings provide a new view of T cell repertoire organization and physiology, and suggest that the immune system distributes its TCR sequences unevenly, attending to specific foci of reactivity.

DOI:http://dx.doi.org/10.7554/eLife.22057.001

Dynamic variation of CD5 surface expression levels within individual chronic lymphocytic leukemia clones

Chronic lymphocytic leukemia (CLL) is characterized by the accumulation of clonally derived mature CD5high B cells; however, the cellular origin of CLL is still unknown. Patients with CLL also harbor variable numbers of CD5low B cells, but the clonal relationship of these cells to the bulk disease is unknown and can have important implications for monitoring, treating, and understanding the biology of CLL. Here, we use B-cell receptors (BCRs) as molecular barcodes to first show by single-cell BCR sequencing that the great majority of CD5low B cells in the blood of CLL patients are clonally related to CD5high CLL B cells. We investigate whether CD5 state switching was likely to occur continuously as a common event or as a rare event in CLL by tracking somatic BCR mutations in bulk CLL B cells and using them to reconstruct the phylogenetic relationships and evolutionary history of the CLL in four patients. Using statistical methods, we show that there is no parsimonious route from a single or low number of CD5low switch events to the CD5high population, but rather, large-scale and/or dynamic switching between these CD5 states is the most likely explanation. The overlapping BCR repertoires between CD5high and CD5low cells from CLL patient peripheral blood reveal that CLL exists in a continuum of CD5 expression. The major proportion of CD5low B cells in patients are leukemic, thus identifying CD5low B cells as an important component of CLL, with implications for CLL pathogenesis, clinical monitoring, and the development of anti-CD5-directed therapies.

Reproducibility and Reuse of Adaptive Immune Receptor Repertoire Data

High-throughput sequencing (HTS) of immunoglobulin (B-cell receptor, antibody) and T-cell receptor repertoires has increased dramatically since the technique was introduced in 2009 (1-3). This experimental approach explores the maturation of the adaptive immune system and its response to antigens, pathogens, and disease conditions in exquisite detail. It holds significant promise for diagnostic and therapy-guiding applications. New technology often spreads rapidly, sometimes more rapidly than the understanding of how to make the products of that technology reliable, reproducible, or usable by others. As complex technologies have developed, scientific communities have come together to adopt common standards, protocols, and policies for generating and sharing data sets, such as the MIAME protocols developed for microarray experiments. The Adaptive Immune Receptor Repertoire (AIRR) Community formed in 2015 to address similar issues for HTS data of immune repertoires. The purpose of this perspective is to provide an overview of the AIRR Community's founding principles and present the progress that the AIRR Community has made in developing standards of practice and data sharing protocols. Finally, and most important, we invite all interested parties to join this effort to facilitate sharing and use of these powerful data sets (join@airr-community.org).

Production of individualized V gene databases reveals high levels of immunoglobulin genetic diversity

Comprehensive knowledge of immunoglobulin genetics is required to advance our understanding of B cell biology. Validated immunoglobulin variable (V) gene databases are close to completion only for human and mouse. We present a novel computational approach, IgDiscover, that identifies germline V genes from expressed repertoires to a specificity of 100%. IgDiscover uses a cluster identification process to produce candidate sequences that, once filtered, results in individualized germline V gene databases. IgDiscover was tested in multiple species, validated by genomic cloning and cross library comparisons and produces comprehensive gene databases even where limited genomic sequence is available. IgDiscover analysis of the allelic content of the Indian and Chinese-origin rhesus macaques reveals high levels of immunoglobulin gene diversity in this species. Further, we describe a novel human IGHV3-21 allele and confirm significant gene differences between Balb/c and C57BL6 mouse strains, demonstrating the power of IgDiscover as a germline V gene discovery tool.

Current databases of V genes for antibody repertoire have limitations. Here Corcoran et al. develop a computational approach named IgDiscover that can identify germline V gene sequences from expressed antibody repertoires to high specificity and completeness.

Tissue distribution and clonal diversity of the T and B cell repertoire in type 1 diabetes

The adaptive immune repertoire plays a critical role in type 1 diabetes (T1D) pathogenesis. However, efforts to characterize B cell and T cell receptor (TCR) profiles in T1D subjects have been largely limited to peripheral blood sampling and restricted to known antigens. To address this, we collected pancreatic draining lymph nodes (pLN), "irrelevant" nonpancreatic draining lymph nodes, peripheral blood mononuclear cells (PBMC), and splenocytes from T1D subjects (n = 18) and control donors (n = 9) as well as pancreatic islets from 1 T1D patient; from these tissues, we collected purified CD4⁺ conventional T cells (Tconv), CD4⁺ Treg, CD8⁺ T cells, and B cells. By conducting high-throughput immunosequencing of the TCR β chain (TRB) and B cell receptor (BCR) immunoglobulin heavy chain (IGH) on these samples, we sought to analyze the molecular signature of the lymphocyte populations within these tissues and of T1D. Ultimately, we observed a highly tissue-restricted CD4⁺ repertoire, while up to 24% of CD8⁺ clones were shared among tissues. We surveyed our data set for previously described proinsulin- and glutamic acid decarboxylase 65-reactive (GAD65-reactive) receptors, and interestingly, we observed a TRB with homology to a known GAD65-reactive TCR (clone GAD4.13) present in 7 T1D donors (38.9%), representing >25% of all productive TRB within Tconv isolated from the pLN of 1 T1D subject. These data demonstrate diverse receptor signatures at the nucleotide level and enriched autoreactive clones at the amino acid level, supporting the utility of coupling immunosequencing data with knowledge of characterized autoreactive receptors.

Likelihood-Based Inference of B Cell Clonal Families

The human immune system depends on a highly diverse collection of antibody-making B cells. B cell receptor sequence diversity is generated by a random recombination process called “rearrangement” forming progenitor B cells, then a Darwinian process of lineage diversification and selection called “affinity maturation.” The resulting receptors can be sequenced in high throughput for research and diagnostics. Such a collection of sequences contains a mixture of various lineages, each of which may be quite numerous, or may consist of only a single member. As a step to understanding the process and result of this diversification, one may wish to reconstruct lineage membership, i.e. to cluster sampled sequences according to which came from the same rearrangement events. We call this clustering problem “clonal family inference.” In this paper we describe and validate a likelihood-based framework for clonal family inference based on a multi-hidden Markov Model (multi-HMM) framework for B cell receptor sequences. We describe an agglomerative algorithm to find a maximum likelihood clustering, two approximate algorithms with various trade-offs of speed versus accuracy, and a third, fast algorithm for finding specific lineages. We show that under simulation these algorithms greatly improve upon existing clonal family inference methods, and that they also give significantly different clusters than previous methods when applied to two real data sets.

Antibodies must recognize a great diversity of antigens to protect us from infectious disease. The binding properties of antibodies are determined by the DNA sequences of their corresponding B cell receptors (BCRs). These BCR sequences are created in naive form by VDJ recombination, which randomly selects and trims the ends of V, D, and J genes, then joins the resulting segments together with additional random nucleotides. If they pass initial screening and bind an antigen, these sequences then undergo an evolutionary process of reproduction, mutation, and selection, revising the BCR to improve binding to its cognate antigen. It has recently become possible to determine the BCR sequences resulting from this process in high throughput. Although these sequences implicitly contain a wealth of information about both antigen exposure and the process by which we learn to resist pathogens, this information can only be extracted using computer algorithms. In this paper we describe a likelihood-based statistical method to determine, given a collection of BCR sequences, which of them are derived from the same recombination events. It is based on a hidden Markov model (HMM) of VDJ rearrangement which is able to calculate likelihoods for many sequences at once.

Network Signatures of IgG Immune Repertoires in Hepatitis B Associated Chronic Infection and Vaccination Responses

The repertoire of IgG antibody responses to infection and vaccination varies depending on the characteristics of the immunogen and the ability of the host to mount a protective immune response. Chronic hepatitis B virus (HBV) infections are marked by persistent infection and immune tolerance to vaccination. This disease offers a unique opportunity to discover key repertoire signatures during infection and in response to vaccination. Complementarity determining region 3 of an antibody heavy chain (CDR-H3) has a major impact on the antigenic specificity of an antibody. We used next-generation sequencing to characterize the CDR-H3 sequences in paired siblings of 4 families in which only one member of each pair had chronic HBV infection. Blood samples were obtained before and 2 weeks after HBV vaccination. The analysis revealed a huge network of sequence-related CDR-H3 clones found almost exclusively among carriers. In contrast, vaccination induced significant increases of CDR-H3 cluster diversities among siblings without hepatitis B. Several vaccination-associated clone clusters were identified. Similar findings of vaccination-associated clone networks were observed in healthy adults receiving HBV boosters. These strategies can be used to identify signatures of other infectious diseases and accelerate discoveries of antibody sequences with important biomedical implications.

Eye on the B-ALL: B-cell receptor repertoires reveal persistence of numerous B-lymphoblastic leukemia subclones from diagnosis to relapse

The strongest predictor of relapse in B-cell acute lymphoblastic leukemia (B-ALL) is the level of persistence of tumor cells after initial therapy. The high mutation rate of the B-cell receptor (BCR) locus allows high-resolution tracking of the architecture, evolution and clonal dynamics of B-ALL. Using longitudinal BCR repertoire sequencing, we find that the BCR undergoes an unexpectedly high level of clonal diversification in B-ALL cells through both somatic hypermutation and secondary rearrangements, which can be used for tracking the subclonal composition of the disease and detect minimal residual disease with unprecedented sensitivity. We go on to investigate clonal dynamics of B-ALL using BCR phylogenetic analyses of paired diagnosis-relapse samples and find that large numbers of small leukemic subclones present at diagnosis re-emerge at relapse alongside a dominant clone. Our findings suggest that in all informative relapsed patients, the survival of large numbers of clonogenic cells beyond initial chemotherapy is a surrogate for inherent partial chemoresistance or inadequate therapy, providing an increased opportunity for subsequent emergence of fully resistant clones. These results frame early cytoreduction as an important determinant of long-term outcome.

Epstein-Barr virus nuclear protein EBNA3C directly induces expression of AID and somatic mutations in B cells

Allday and collaborators demonstrate that the EBV transcription factor and oncoprotein EBNA3C directly induces the expression of AID and somatic mutations in B cells, providing a mechanism linking infection and lymphoma induction.

Activation-induced cytidine deaminase (AID), the enzyme responsible for induction of sequence variation in immunoglobulins (Igs) during the process of somatic hypermutation (SHM) and also Ig class switching, can have a potent mutator phenotype in the development of lymphoma. Using various Epstein-Barr virus (EBV) recombinants, we provide definitive evidence that the viral nuclear protein EBNA3C is essential in EBV-infected primary B cells for the induction of AID mRNA and protein. Using lymphoblastoid cell lines (LCLs) established with EBV recombinants conditional for EBNA3C function, this was confirmed, and it was shown that transactivation of the AID gene (AICDA) is associated with EBNA3C binding to highly conserved regulatory elements located proximal to and upstream of the AICDA transcription start site. EBNA3C binding initiated epigenetic changes to chromatin at specific sites across the AICDA locus. Deep sequencing of cDNA corresponding to the IgH V-D-J region from the conditional LCL was used to formally show that SHM is activated by functional EBNA3C and induction of AID. These data, showing the direct targeting and induction of functional AID by EBNA3C, suggest a novel role for EBV in the etiology of B cell cancers, including endemic Burkitt lymphoma.

Clonal deleted latent membrane protein 1 variants of Epstein-Barr virus are predominant in European extranodal NK/T lymphomas and disappear during successful treatment

Extranodal natural killer/T-cell lymphomas (NK/TL), rare in Europe, are Epstein-Barr virus (EBV) associated lymphomas with poor outcomes. Here, we determined the virus type and analyzed the EBV latent membrane protein-1 (LMP1) gene sequence in NK/TL from French patients. Six clones of viral LMP1 were sequenced by Sanger technology in blood from 13 patients before treatment with an l-asparaginase based regimen and, for 8 of them, throughout the treatment. Blood LMP1 sequences from 21 patients without any known malignancy were tested as controls. EBV Type A was identified for 11/13 patients and for all controls. Before treatment, a clonal LMP1 gene containing a 30 bp deletion (del30) was found in 46.1% of NK/TL and only in 4.8% of controls. Treatment was less effective in these patients who died more rapidly than the others. Patients with a deleted strain evolving toward a wild-type strain during treatment reached complete remission. The LMP1 gene was sequenced by highly sensitive next-generation sequencing technology in five NK/TL nasopharyngeal biopsies, two of them originating from the previous patients. Del30 was present in 100% of the biopsies; two viruses at least coexisted in three biopsies. These results suggest that del30 may be associated with poor prognosis NK/TL and that strain evolution could be used as a potential marker to monitor treatment.

Quantifying evolutionary constraints on B-cell affinity maturation

The antibody repertoire of each individual is continuously updated by the evolutionary process of B-cell receptor (BCR) mutation and selection. It has recently become possible to gain detailed information concerning this process through high-throughput sequencing. Here, we develop modern statistical molecular evolution methods for the analysis of B-cell sequence data, and then apply them to a very deep short-read dataset of BCRs. We find that the substitution process is conserved across individuals but varies significantly across gene segments. We investigate selection on BCRs using a novel method that side-steps the difficulties encountered by previous work in differentiating between selection and motif-driven mutation; this is done through stochastic mapping and empirical Bayes estimators that compare the evolution of in-frame and out-of-frame rearrangements. We use this new method to derive a per-residue map of selection, which provides a more nuanced view of the constraints on framework and variable regions.

Dynamics of immunoglobulin sequence diversity in HIV-1 infected individuals

Advances in immunoglobulin (Ig) sequencing technology are leading to new perspectives on immune system dynamics. Much research in this nascent field has focused on resolving immune responses to viral infection. However, the dynamics of B-cell diversity in early HIV infection, and in response to anti-retroviral therapy, are still poorly understood. Here, we investigate these dynamics through bulk Ig sequencing of samples collected over 2 years from a group of eight HIV-1 infected patients, five of whom received anti-retroviral therapy during the first half of the study period. We applied previously published methods for visualizing and quantifying B-cell sequence diversity, including the Gini index, and compared their efficacy to alternative measures. While we found significantly greater clonal structure in HIV-infected patients versus healthy controls, within HIV patients, we observed no significant relationships between statistics of B-cell clonal expansion and clinical variables such as viral load and CD4⁺ count. Although there are many potential explanations for this, we suggest that important factors include poor sampling resolution and complex B-cell dynamics that are difficult to summarize using simple summary statistics. Importantly, we find a significant association between observed Gini indices and sequencing read depth, and we conclude that more robust analytical methods and a closer integration of experimental and theoretical work is needed to further our understanding of B-cell repertoire diversity during viral infection.

Reconstructing and mining the B cell repertoire with ImmunediveRsity

The B cell antigen receptor repertoire is highly diverse and constantly modified by clonal selection. High-throughput DNA sequencing (HTS) of the lymphocyte repertoire (Rep-Seq) represents a promising technology to explore such diversity ex-vivo and assist in the identification of antigen-specific antibodies based on molecular signatures of clonal selection. Therefore, integrative tools for repertoire reconstruction and analysis from antibody sequences are needed. We developed ImmunediveRity, a stand-alone pipeline primarily based in R programming for the integral analysis of B cell repertoire data generated by HTS. The pipeline integrates GNU software and in house scripts to perform quality filtering, sequencing noise correction and repertoire reconstruction based on V, D and J segment assignment, clonal origin and unique heavy chain identification. Post-analysis scripts generate a wealth of repertoire metrics that in conjunction with a rich graphical output facilitates sample comparison and repertoire mining. Its performance was tested with raw and curated human and mouse 454-Roche sequencing benchmarks providing good approximations of repertoire structure. Furthermore, ImmunediveRsity was used to mine the B cell repertoire of immunized mice with a model antigen, allowing the identification of previously validated antigen-specific antibodies, and revealing different and unexpected clonal diversity patterns in the post-immunization IgM and IgG compartments. Although ImmunediveRsity is similar to other recently developed tools, it offers significant advantages that facilitate repertoire analysis and repertoire mining. ImmunediveRsity is open source and free for academic purposes and it runs on 64 bit GNU/Linux and MacOS. Available at: https://bitbucket.org/ImmunediveRsity/immunediversity/

Current status and recent advances of next generation sequencing techniques in immunological repertoire

To ward off a wide variety of pathogens, the human adaptive immune system harbors a vast array of T-cell receptors (TCRs) and B-cell receptors (BCRs), collectively referred to as the immune repertoire. High-throughput sequencing (HTS) of TCR/BCR genes allows in-depth molecular analysis of T/B-cell clones, providing an unprecedented level of detail when examining the T/B-cell repertoire of individuals. It can evaluate TCR/BCR complementarity-determining region 3 (CDR3) diversity and assess the clonal composition, including the size of the repertoire; similarities between repertoires; V(D)J segment use; nucleotide insertions and deletions; CDR3 lengths; and amino acid distributions along the CDR3s at sequence-level resolution. Deep sequencing of B-cell and T-cell repertoires offers the potential for a quantitative understanding of the adaptive immune system in healthy and disease states. Recently, paired sequencing strategies have also been developed, which can provide information about the identity of immune receptor pairs encoded by individual T or B lymphocytes. HTS technology provides a previously unimaginable amount of sequence data, accompanied, however, by numerous challenges associated with error correction and interpretation that remain to be solved. The review details some of the technologies and some of the recent achievements in this field.

The Diversity and Molecular Evolution of B-Cell Receptors during Infection

B-cell receptors (BCRs) are membrane-bound immunoglobulins that recognize and bind foreign proteins (antigens). BCRs are formed through random somatic changes of germline DNA, creating a vast repertoire of unique sequences that enable individuals to recognize a diverse range of antigens. After encountering antigen for the first time, BCRs undergo a process of affinity maturation, whereby cycles of rapid somatic mutation and selection lead to improved antigen binding. This constitutes an accelerated evolutionary process that takes place over days or weeks. Next-generation sequencing of the gene regions that determine BCR binding has begun to reveal the diversity and dynamics of BCR repertoires in unprecedented detail. Although this new type of sequence data has the potential to revolutionize our understanding of infection dynamics, quantitative analysis is complicated by the unique biology and high diversity of BCR sequences. Models and concepts from molecular evolution and phylogenetics that have been applied successfully to rapidly evolving pathogen populations are increasingly being adopted to study BCR diversity and divergence within individuals. However, BCR dynamics may violate key assumptions of many standard evolutionary methods, as they do not descend from a single ancestor, and experience biased mutation. Here, we review the application of evolutionary models to BCR repertoires and discuss the issues we believe need be addressed for this interdisciplinary field to flourish.

Consistency of VDJ Rearrangement and Substitution Parameters Enables Accurate B Cell Receptor Sequence Annotation

VDJ rearrangement and somatic hypermutation work together to produce antibody-coding B cell receptor (BCR) sequences for a remarkable diversity of antigens. It is now possible to sequence these BCRs in high throughput; analysis of these sequences is bringing new insight into how antibodies develop, in particular for broadly-neutralizing antibodies against HIV and influenza. A fundamental step in such sequence analysis is to annotate each base as coming from a specific one of the V, D, or J genes, or from an N-addition (a.k.a. non-templated insertion). Previous work has used simple parametric distributions to model transitions from state to state in a hidden Markov model (HMM) of VDJ recombination, and assumed that mutations occur via the same process across sites. However, codon frame and other effects have been observed to violate these parametric assumptions for such coding sequences, suggesting that a non-parametric approach to modeling the recombination process could be useful. In our paper, we find that indeed large modern data sets suggest a model using parameter-rich per-allele categorical distributions for HMM transition probabilities and per-allele-per-position mutation probabilities, and that using such a model for inference leads to significantly improved results. We present an accurate and efficient BCR sequence annotation software package using a novel HMM "factorization" strategy. This package, called partis (https://github.com/psathyrella/partis/), is built on a new general-purpose HMM compiler that can perform efficient inference given a simple text description of an HMM.

The evolution within us

The B-cell immune response is a remarkable evolutionary system found in jawed vertebrates. B-cell receptors, the membrane-bound form of antibodies, are capable of evolving high affinity to almost any foreign protein. High germline diversity and rapid evolution upon encounter with antigen explain the general adaptability of B-cell populations, but the dynamics of repertoires are less well understood. These dynamics are scientifically and clinically important. After highlighting the remarkable characteristics of naive and experienced B-cell repertoires, especially biased usage of genes encoding the B-cell receptors, we contrast methods of sequence analysis and their attempts to explain patterns of B-cell evolution. These phylogenetic approaches are currently unlinked to explicit models of B-cell competition, which analyse repertoire evolution at the level of phenotype, the affinities and specificities to particular antigenic sites. The models, in turn, suggest how chance, infection history and other factors contribute to different patterns of immunodominance and protection between people. Challenges in rational vaccine design, specifically vaccines to induce broadly neutralizing antibodies to HIV, underscore critical gaps in our understanding of B cells' evolutionary and ecological dynamics.

A bioinformatic framework for immune repertoire diversity profiling enables detection of immunological status

BACKGROUND

Lymphocyte receptor repertoires are continually shaped throughout the lifetime of an individual in response to environmental and pathogenic exposure. Thus, they may serve as a fingerprint of an individual's ongoing immunological status (e.g., healthy, infected, vaccinated), with far-reaching implications for immunodiagnostics applications. The advent of high-throughput immune repertoire sequencing now enables the interrogation of immune repertoire diversity in an unprecedented and quantitative manner. However, steadily increasing sequencing depth has revealed that immune repertoires vary greatly among individuals in their composition; correspondingly, it has been reported that there are few shared sequences indicative of immunological status ('public clones'). Disconcertingly, this means that the wealth of information gained from repertoire sequencing remains largely unused for determining the current status of immune responses, thereby hampering the implementation of immune-repertoire-based diagnostics.

METHODS

Here, we introduce a bioinformatics repertoire-profiling framework that possesses the advantage of capturing the diversity and distribution of entire immune repertoires, as opposed to singular public clones. The framework relies on Hill-based diversity profiles composed of a continuum of single diversity indices, which enable the quantification of the extent of immunological information contained in immune repertoires.

RESULTS

We coupled diversity profiles with unsupervised (hierarchical clustering) and supervised (support vector machine and feature selection) machine learning approaches in order to correlate patients' immunological statuses with their B- and T-cell repertoire data. We could predict with high accuracy (greater than or equal to 80 %) a wide range of immunological statuses such as healthy, transplantation recipient, and lymphoid cancer, suggesting as a proof of principle that diversity profiling can recover a large amount of immunodiagnostic fingerprints from immune repertoire data. Our framework is highly scalable as it easily allowed for the analysis of 1000 simulated immune repertoires; this exceeds the size of published immune repertoire datasets by one to two orders of magnitude.

CONCLUSIONS

Our framework offers the possibility to advance immune-repertoire-based fingerprinting, which may in the future enable a systems immunogenomics approach for vaccine profiling and the accurate and early detection of disease and infection.

Molecular evolution of broadly neutralizing Llama antibodies to the CD4-binding site of HIV-1

To date, no immunization of humans or animals has elicited broadly neutralizing sera able to prevent HIV-1 transmission; however, elicitation of broad and potent heavy chain only antibodies (HCAb) has previously been reported in llamas. In this study, the anti-HIV immune responses in immunized llamas were studied via deep sequencing analysis using broadly neutralizing monoclonal HCAbs as a guides. Distinct neutralizing antibody lineages were identified in each animal, including two defined by novel antibodies (as variable regions called VHH) identified by robotic screening of over 6000 clones. The combined application of five VHH against viruses from clades A, B, C and CRF_AG resulted in neutralization as potent as any of the VHH individually and a predicted 100% coverage with a median IC50 of 0.17 µg/ml for the panel of 60 viruses tested. Molecular analysis of the VHH repertoires of two sets of immunized animals showed that each neutralizing lineage was only observed following immunization, demonstrating that they were elicited de novo. Our results show that immunization can induce potent and broadly neutralizing antibodies in llamas with features similar to human antibodies and provide a framework to analyze the effectiveness of immunization protocols.

Developing a vaccine against HIV-1 is a priority, but it remains unclear whether immunizations in humans can elicit potent broadly neutralizing antibodies able to prevent HIV-1 transmission. Llamas possess heavy chain only antibodies and conventional heavy and light chain antibodies. We previously reported the heavy chain only antibody J3, which potently neutralizes more than 95% of HIV strains, and was induced by immunization. Here we immunized two further llamas and elicited three novel broadly neutralizing heavy chain only antibodies, which were identified by high-throughput screening. These neutralizing llama antibodies target different areas of the CD4-binding site of the virus, therefore breadth and potency are increased when they are used in combination. To gain greater understanding of how the llama immunizations worked, deep sequencing of the HIV binding region of the antibodies was performed. This revealed that the antibodies were matured fully only in response to the protein immunogens. Furthermore, the VHH elicited in different animals, while sharing functional hallmarks, were encoded by distinct sequences and thus could not have been identified by a deep sequencing analysis alone. Our results show that immunization can potentially induce protective antibodies in llamas and provide a method to more extensively evaluate immunization studies.

Quantitative assessment of the robustness of next-generation sequencing of antibody variable gene repertoires from immunized mice

BACKGROUND

Next-generation sequencing (NGS) of antibody variable regions has emerged as a powerful tool in systems immunology by providing quantitative molecular information on polyclonal humoral immune responses. Reproducible and robust information on antibody repertoires is valuable for basic and applied immunology studies: thus, it is essential to establish the reliability of antibody NGS data.

RESULTS

We isolated RNA from antibody-secreting cells (ASCs) from either 1 mouse or a pool of 9 immunized mice in order to simulate both normal and high diversity populations. Next, we prepared three technical replicates of antibody libraries by RT-PCR from each diversity scenario, which were sequenced using the Illumina MiSeq platform resulting in >106 250 bp paired-end reads per replicate. We then assessed the robustness of antibody repertoire data based on clonal identification defined by amino acid sequence of either full-length VDJ region or the complementarity determining region 3 (CDR3). Leveraging modeling approaches adapted from mathematical ecology, we found that in either diversity scenario both CDR3 and VDJ detection nears completeness indicating deep coverage of ASC repertoires. Additionally, we defined reliability thresholds for accurate quantification and ranking of CDR3s and VDJs. Importantly, we show that both factors-(i) replicate sequencing and (ii) sequencing depth-are crucial for robust CDR3 and VDJ detection and ranking.

CONCLUSIONS

In summary, we established widely applicable experimental and computational guidelines for robust antibody NGS and analysis, which will help advance systems immunology studies related to the quantitative profiling of antibody responses following infection and vaccination.

Biased estimates of clonal evolution and subclonal heterogeneity can arise from PCR duplicates in deep sequencing experiments

Accurate allele frequencies are important for measuring subclonal heterogeneity and clonal evolution. Deep-targeted sequencing data can contain PCR duplicates, inflating perceived read depth. Here we adapted the Illumina TruSeq Custom Amplicon kit to include single molecule tagging (SMT) and show that SMT-identified duplicates arise from PCR. We demonstrate that retention of PCR duplicate reads can imply clonal evolution when none exists, while their removal effectively controls the false positive rate. Additionally, PCR duplicates alter estimates of subclonal heterogeneity in tumor samples. Our method simplifies PCR duplicate identification and emphasizes their removal in studies of tumor heterogeneity and clonal evolution.

Capturing needles in haystacks: a comparison of B-cell receptor sequencing methods

BACKGROUND

Deep-sequencing methods are rapidly developing in the field of B-cell receptor (BCR) and T-cell receptor (TCR) diversity. These promise to revolutionise our understanding of adaptive immune dynamics, identify novel antibodies, and allow monitoring of minimal residual disease. However, different methods for BCR and TCR enrichment and amplification have been proposed. Here we perform the first systematic comparison between different methods of enrichment, amplification and sequencing for generating BCR and TCR repertoires using large sample numbers.

RESULTS

Resampling from the same RNA or cDNA pool results in highly correlated and reproducible repertoires, but resampling low frequency clones leads to stochastic variance. Repertoires generated by different sequencing methods (454 Roche and Illumina MiSeq) and amplification methods (multiplex PCR, 5' Rapid amplification of cDNA ends (5'RACE), and RNA-capture) are highly correlated, and resulting IgHV gene frequencies between the different methods were not significantly different. Read length has an impact on captured repertoire structure, and ultimately full-length BCR sequences are most informative for repertoire analysis as diversity outside of the CDR is very useful for phylogenetic analysis. Additionally, we show RNA-based BCR repertoires are more informative than using DNA.

CONCLUSIONS

Repertoires generated by different sequencing and amplification methods are consistent, but we show that read lengths, depths and error profiles should be considered in experimental design, and multiple sampling approaches could be employed to minimise stochastic sampling variation. This detailed investigation of immune repertoire sequencing methods is essential for informing basic and clinical research.

A bioinformatics pipeline for the analyses of viral escape dynamics and host immune responses during an infection

Rapidly mutating viruses, such as hepatitis C virus (HCV) and HIV, have adopted evolutionary strategies that allow escape from the host immune response via genomic mutations. Recent advances in high-throughput sequencing are reshaping the field of immuno-virology of viral infections, as these allow fast and cheap generation of genomic data. However, due to the large volumes of data generated, a thorough understanding of the biological and immunological significance of such information is often difficult. This paper proposes a pipeline that allows visualization and statistical analysis of viral mutations that are associated with immune escape. Taking next generation sequencing data from longitudinal analysis of HCV viral genomes during a single HCV infection, along with antigen specific T-cell responses detected from the same subject, we demonstrate the applicability of these tools in the context of primary HCV infection. We provide a statistical and visual explanation of the relationship between cooccurring mutations on the viral genome and the parallel adaptive immune response against HCV.

Immunoglobulin gene repertoire diversification and selection in the stomach - from gastritis to gastric lymphomas

Chronic gastritis is characterized by gastric mucosal inflammation due to autoimmune responses or infection, frequently with Helicobacter pylori. Gastritis with H. pylori background can cause gastric mucosa-associated lymphoid tissue lymphoma (MALT-L), which sometimes further transforms into diffuse large B-cell lymphoma (DLBCL). However, gastric DLBCL can also be initiated de novo. The mechanisms underlying transformation into DLBCL are not completely understood. We analyzed immunoglobulin repertoires and clonal trees to investigate whether and how immunoglobulin gene repertoires, clonal diversification, and selection in gastritis, gastric MALT-L, and DLBCL differ from each other and from normal responses. The two gastritis types (positive or negative for H. pylori) had similarly diverse repertoires. MALT-L dominant clones (defined as the largest clones in each sample) presented higher diversification and longer mutational histories compared with all other conditions. DLBCL dominant clones displayed lower clonal diversification, suggesting the transforming events are triggered by similar responses in different patients. These results are surprising, as we expected to find similarities between the dominant clones of gastritis and MALT-L and between those of MALT-L and DLBCL.