The promise and challenge of high-throughput sequencing of the antibody repertoire

AbCellera's success is unprecedented: what have we learned?

The search for antibody therapeutic candidates is a timely and important challenge well-suited to lab on a chip approaches. Vancouver-based AbCellera Biologics Inc. developed a microfluidic antibody screening platform, ancillary technologies, and a service-based drug discovery business model that has proved a tremendous success. We take the opportunity here to reflect on what enabled this success. We consider the common lab on a chip motivations that were part of their success, and those that were not.

Platypus: an open-access software for integrating lymphocyte single-cell immune repertoires with transcriptomes

High-throughput single-cell sequencing (scSeq) technologies are revolutionizing the ability to molecularly profile B and T lymphocytes by offering the opportunity to simultaneously obtain information on adaptive immune receptor repertoires (VDJ repertoires) and transcriptomes. An integrated quantification of immune repertoire parameters, such as germline gene usage, clonal expansion, somatic hypermutation and transcriptional states opens up new possibilities for the high-resolution analysis of lymphocytes and the inference of antigen-specificity. While multiple tools now exist to investigate gene expression profiles from scSeq of transcriptomes, there is a lack of software dedicated to single-cell immune repertoires. Here, we present Platypus, an open-source software platform providing a user-friendly interface to investigate B-cell receptor and T-cell receptor repertoires from scSeq experiments. Platypus provides a framework to automate and ease the analysis of single-cell immune repertoires while also incorporating transcriptional information involving unsupervised clustering, gene expression and gene ontology. To showcase the capabilities of Platypus, we use it to analyze and visualize single-cell immune repertoires and transcriptomes from B and T cells from convalescent COVID-19 patients, revealing unique insight into the repertoire features and transcriptional profiles of clonally expanded lymphocytes. Platypus will expedite progress by facilitating the analysis of single-cell immune repertoire and transcriptome sequencing.

High-throughput functional screening for next-generation cancer immunotherapy using droplet-based microfluidics

Currently, high-throughput approaches are lacking in the isolation of antibodies with functional readouts beyond simple binding. This situation has impeded the next generation of cancer immunotherapeutics, such as bispecific T cell engager (BiTE) antibodies or agonist antibodies against costimulatory receptors, from reaching their full potential. Here, we developed a highly efficient droplet-based microfluidic platform combining a lentivirus transduction system that enables functional screening of millions of antibodies to identify potential hits with desired functionalities. To showcase the capacity of this system, functional antibodies for CD40 agonism with low frequency (<0.02%) were identified with two rounds of screening. Furthermore, the versatility of the system was demonstrated by combining an anti-Her2 × anti-CD3 BiTE antibody library with functional screening, which enabled efficient identification of active anti-Her2 × anti-CD3 BiTE antibodies. The platform could revolutionize next-generation cancer immunotherapy drug development and advance medical research.

Advances in Electrochemical and Acoustic Aptamer-Based Biosensors and Immunosensors in Diagnostics of Leukemia

Early diagnostics of leukemia is crucial for successful therapy of this disease. Therefore, development of rapid, sensitive, and easy-to-use methods for detection of this disease is of increased interest. Biosensor technology is challenged for this purpose. This review includes a brief description of the methods used in current clinical diagnostics of leukemia and provides recent achievements in sensor technology based on immuno- and DNA aptamer-based electrochemical and acoustic biosensors. The comparative analysis of immuno- and aptamer-based sensors shows a significant advantage of DNA aptasensors over immunosensors in the detection of cancer cells. The acoustic technique is of comparable sensitivity with those based on electrochemical methods; moreover, it is label-free and provides straightforward evaluation of the signal. Several examples of sensor development are provided and discussed.

Biological controls for standardization and interpretation of adaptive immune receptor repertoire profiling

Use of adaptive immune receptor repertoire sequencing (AIRR-seq) has become widespread, providing new insights into the immune system with potential broad clinical and diagnostic applications. However, like many high-throughput technologies, it comes with several problems, and the AIRR Community was established to understand and help solve them. We, the AIRR Community's Biological Resources Working Group, have surveyed scientists about the need for standards and controls in generating and annotating AIRR-seq data. Here, we review the current status of AIRR-seq, provide the results of our survey, and based on them, offer recommendations for developing AIRR-seq standards and controls, including future work.

Dynamics of B cell repertoires and emergence of cross-reactive responses in patients with different severities of COVID-19

Individuals with the 2019 coronavirus disease (COVID-19) show varying severity of the disease, ranging from asymptomatic to requiring intensive care. Although monoclonal antibodies specific to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been identified, we still lack an understanding of the overall landscape of B cell receptor (BCR) repertoires in individuals with COVID-19. We use high-throughput sequencing of bulk and plasma B cells collected at multiple time points during infection to characterize signatures of the B cell response to SARS-CoV-2 in 19 individuals. Using principled statistical approaches, we associate differential features of BCRs with different disease severity. We identify 38 significantly expanded clonal lineages shared among individuals as candidates for responses specific to SARS-CoV-2. Using single-cell sequencing, we verify the reactivity of BCRs shared among individuals to SARS-CoV-2 epitopes. Moreover, we identify the natural emergence of a BCR with cross-reactivity to SARS-CoV-1 and SARS-CoV-2 in some individuals. Our results provide insights important for development of rational therapies and vaccines against COVID-19.

High-efficacy, high-manufacturability human VH domain antibody therapeutics from transgenic sources

Interest in single-domain antibodies (sdAbs) stems from their unique structural/pronounced, hence therapeutically desirable, features. From the outset-as therapeutic modalities-human antibody heavy chain variable domains (VHs) attracted a particular attention compared with 'naturally-occurring' camelid and shark heavy-chain-only antibody variable domains (VHHs and VNARs, respectively) due to their perceived lack of immunogenicity. However, they have not quite lived up to their initial promise as the VH hits, primarily mined from synthetic VH phage display libraries, have too often been plagued with aggregation tendencies, low solubility and low affinity. Largely unexplored, synthetic camelized human VH display libraries appeared to have remediated the aggregation problem, but the low affinity of the VH hits still persisted, requiring undertaking additional, laborious affinity maturation steps to render VHs therapeutically feasible. A wholesome resolution has recently emerged with the development of non-canonical transgenic rodent antibody discovery platforms that appear to facilely and profusely generate high affinity, high solubility and aggregation-resistant human VHs.

Characterization of the B cell receptor repertoire of patients with acute coronary syndrome

BACKGROUND

Acute coronary syndrome (ACS) is a complex cardiovascular disease whose development involves the dysregulation of adaptive immune responses. Though it has been proven that T cells associate with inflammation in the development of ACS, the function of B cells in disease remains unclear.

OBJECTIVE

The aim of this study was to reveal the diversity of the B cell receptor (BCR) repertoire of patients with ACS.

METHODS

We conducted a pilot study to sequence the immune repertoire of peripheral blood mononuclear cells (PBMCs) from patients with ACS, including acute myocardial infarction (AMI) and unstable angina (UA), and quantitatively characterized BCR repertoires by bioinformatics analysis.

RESULTS

We found that patients with AMI and UA had lower BCR repertoire diversity compared with controls with normal coronary arteries (NCA). Lower percentages of productive unique BCR nt sequences and higher percentages of top 200 unique BCR sequences were identified in AMI and UA patients than NCA controls. Patients had various preferential usage of V and J genes from B cell clones in accordance with the disease severity of coronary arteries. AMI patients had distinct CDR3 amino acids, and their frequency differed among patients with ACS.

CONCLUSIONS

Our results indicate that differential BCR signatures represent an imprint of distinct repertoires among ACS patients. This study thereby opens up the prospect of studying disease-relevant B cells to better understand and treat ACS.

Original Antigenic Sin: How Original? How Sinful?

We review the phenomenon of "original antigenic sin" (OAS) in antibody responses to influenza A virus (IAV) infection or vaccination. OAS refers to the preferential induction of antibodies with higher affinity to priming versus boosting immunogens. We emphasize its mechanistic basis and origins in the basic immunobiology of B-cell responses to myriad immunogens. We tabulate 23 studies in animals and humans to show that the magnitude of OAS depends on many variables. We discuss a number of misconceptions about OAS, examine the extent to which OAS is sinful, and argue that OAS is evolutionary selected and not a deleterious by-product of selection for other features of the immune response. We end by raising questions regarding the mechanistic basis of OAS whose answers could contribute to improving influenza virus vaccines on the road to the holy grail of a "universal" influenza vaccine.

Anti-Vascular Cell Adhesion Molecule-1 Nanosystems: A Promising Strategy Against Inflammatory Based Diseases

Inflammation underlays the onset and supports the development of several worldwide diffused pathologies, therefore in the last decades inflammatory markers have attracted a great deal of interest as diagnostic and therapeutic targets. Adhesion molecules are membrane proteins expressed by endotheliocytes and leukocytes, acting as mediators in the process of tethering, rolling, firm adhesion and diapedesis that leads the immune cells to reach an inflamed tissue. Among them, the adhesion molecule VCAM-1 has been investigated as a potential target because of its low constitutive expression and easy accessibility on the endothelium. Moreover, VCAM-1 is involved in the early stages of development of several pathologies like, among others, atherosclerosis, cancer, Alzheimer's and Parkinson's diseases, so a diagnostic or therapeutic tool directed to this protein would allow specific detection and efficacious intervention. The availability of monoclonal antibodies against VCAM-1 has recently fostered the development of various targeting technologies potentially suitable for imaging and drug delivery in VCAM-1 overexpressing pathologies. In this review we initially focus on the structure and functions of VCAM-1, giving also a brief overview of antibodies origin, structure and function; then, we summarize some of the VCAM-1 targeting nanosystems based on antibodies, gathered according to the carrier used, for diagnosis or therapeutic treatment of different inflammatory based pathologies.

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

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

Applications of Machine and Deep Learning in Adaptive Immunity

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

Deep generative selection models of T and B cell receptor repertoires with soNNia

Subclasses of lymphocytes carry different functional roles to work together and produce an immune response and lasting immunity. Additionally to these functional roles, T and B cell lymphocytes rely on the diversity of their receptor chains to recognize different pathogens. The lymphocyte subclasses emerge from common ancestors generated with the same diversity of receptors during selection processes. Here, we leverage biophysical models of receptor generation with machine learning models of selection to identify specific sequence features characteristic of functional lymphocyte repertoires and subrepertoires. Specifically, using only repertoire-level sequence information, we classify CD4+ and CD8+ T cells, find correlations between receptor chains arising during selection, and identify T cell subsets that are targets of pathogenic epitopes. We also show examples of when simple linear classifiers do as well as more complex machine learning methods.

Dynamics of B-cell repertoires and emergence of cross-reactive responses in COVID-19 patients with different disease severity

COVID-19 patients show varying severity of the disease ranging from asymptomatic to requiring intensive care. Although a number of SARS-CoV-2 specific monoclonal antibodies have been identified, we still lack an understanding of the overall landscape of B-cell receptor (BCR) repertoires in COVID-19 patients. Here, we used high-throughput sequencing of bulk and plasma B-cells collected over multiple time points during infection to characterize signatures of B-cell response to SARS-CoV-2 in 19 patients. Using principled statistical approaches, we determined differential features of BCRs associated with different disease severity. We identified 38 significantly expanded clonal lineages shared among patients as candidates for specific responses to SARS-CoV-2. Using single-cell sequencing, we verified reactivity of BCRs shared among individuals to SARS-CoV-2 epitopes. Moreover, we identified natural emergence of a BCR with cross-reactivity to SARS-CoV-1 and SARS-CoV-2 in a number of patients. Our results provide important insights for development of rational therapies and vaccines against COVID-19.

Robustification of RosettaAntibody and Rosetta SnugDock

In recent years, the observed antibody sequence space has grown exponentially due to advances in high-throughput sequencing of immune receptors. The rise in sequences has not been mirrored by a rise in structures, as experimental structure determination techniques have remained low-throughput. Computational modeling, however, has the potential to close the sequence–structure gap. To achieve this goal, computational methods must be robust, fast, easy to use, and accurate. Here we report on the latest advances made in RosettaAntibody and Rosetta SnugDock—methods for antibody structure prediction and antibody–antigen docking. We simplified the user interface, expanded and automated the template database, generalized the kinematics of antibody–antigen docking (which enabled modeling of single-domain antibodies) and incorporated new loop modeling techniques. To evaluate the effects of our updates on modeling accuracy, we developed rigorous tests under a new scientific benchmarking framework within Rosetta. Benchmarking revealed that more structurally similar templates could be identified in the updated database and that SnugDock broadened its applicability without losing accuracy. However, there are further advances to be made, including increasing the accuracy and speed of CDR-H3 loop modeling, before computational approaches can accurately model any antibody.

Covalent Organic Frameworks for Biomedical Applications

Covalent organic frameworks (COFs) are porous organic polymeric materials that are composed of organic elements and linked together by the thermodynamically stable covalent bonds. The applications of COFs in energy sector and drug delivery are afforded because of the desirable properties of COFs, such as high stability, low density, large surface area, multidimensionality, porosity, and high-ordered crystalline structure expanded. In this review COFs are reviewed, from the perspective of different types of reported COFs, different methods for their synthesis, and their potential applications in the biomedical field. The main goal of this review is to introduce COFs as a biomaterial and to identify specific advantages of different types of COFs that can be exploited for specialized biomedical applications, such as immune engineering.

Single-cell immune repertoire and transcriptome sequencing reveals that clonally expanded and transcriptionally distinct lymphocytes populate the aged central nervous system in mice

Neuroinflammation plays a crucial role during ageing and various neurological conditions, including Alzheimer's disease, multiple sclerosis and infection. Technical limitations, however, have prevented an integrative analysis of how lymphocyte immune receptor repertoires and their accompanying transcriptional states change with age in the central nervous system. Here, we leveraged single-cell sequencing to simultaneously profile B cell receptor and T cell receptor repertoires and accompanying gene expression profiles in young and old mouse brains. We observed the presence of clonally expanded B and T cells in the central nervous system of aged male mice. Furthermore, many of these B cells were of the IgM and IgD isotypes, and had low levels of somatic hypermutation. Integrating gene expression information additionally revealed distinct transcriptional profiles of these clonally expanded lymphocytes. Our findings implicate that clonally related T and B cells in the CNS of elderly mice may contribute to neuroinflammation accompanying homeostatic ageing.

Landscape of Monoclonal Antibodies Targeting Zika and Dengue: Therapeutic Solutions and Critical Insights for Vaccine Development

The unprecedented 2015-2016 Zika outbreak in the Americas sparked global concern and drove the rapid deployment of vaccine and therapeutic countermeasures against this re-emerging pathogen. Alongside vaccine development, a number of potent neutralizing antibodies against Zika and related flaviviruses have been identified in recent years. High-throughput antibody isolation approaches have contributed to a better understanding of the B cell responses elicited following infection and/or vaccination. Structure-based approaches have illuminated species-specific and cross-protective epitopes of therapeutic value. This review will highlight previously described monoclonal antibodies with the best therapeutic potential against ZIKV and related flaviviruses, and discuss their implications for the rational design of better vaccine strategies.

Rationalizing Random Walks: Replicating Protective Antibody Trajectories

'Reverse vaccinology 2.0' aims to rationally reproduce template antibody responses, such as broadly neutralizing antibodies against human immunodeficiency virus-1. While observations of antibody convergence across individuals support the assumption that responses may be replicated, the diversity of humoral immunity and the process of antibody selection are rooted in stochasticity. Drawing from experience with in vitro antibody engineering by directed evolution, we consider how antibody selection may be driven, as in germline-targeting vaccine approaches to elicit broadly neutralizing antibodies and illustrate the potential consequences of over-defining a template antibody response. We posit that the prospective definition of template antibody responses and the odds of replicating them must be considered within the randomness of humoral immunity.

PASA: Proteomic analysis of serum antibodies web server

MOTIVATION

A comprehensive characterization of the humoral response towards a specific antigen requires quantification of the B-cell receptor repertoire by next-generation sequencing (BCR-Seq), as well as the analysis of serum antibodies against this antigen, using proteomics. The proteomic analysis is challenging since it necessitates the mapping of antigen-specific peptides to individual B-cell clones.

RESULTS

The PASA web server provides a robust computational platform for the analysis and integration of data obtained from proteomics of serum antibodies. PASA maps peptides derived from antibodies raised against a specific antigen to corresponding antibody sequences. It then analyzes and integrates proteomics and BCR-Seq data, thus providing a comprehensive characterization of the humoral response. The PASA web server is freely available at https://pasa.tau.ac.il and open to all users without a login requirement.

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

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

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

Exploiting next-generation sequencing in antibody selections - a simple PCR method to recover binders

Antibody discovery using invitro display technologies such as phage and/or yeast display has become acornerstone in many research and development projects, including the creation of new drugs for clinical use. Traditionally, after the selection phase, random clones are isolated for binding validation and Sanger sequencing. More recently, next-generation sequencing (NGS) technology has allowed deeper insight into the antibody population after aselection campaign, enabling the identification of many more specific binders. However, this approach only provides the DNA sequences of potential binders, the properties of which need to be fully elucidated by obtaining corresponding clones and expressing them for further validation. Here we present arapid novel method to harvest potential clones identified by NGS that uses asimple PCR and yeast recombination approach. The protocol was tested in selections against three different targets and was able to recover clones at an abundance level that would be impractical to identify using traditional methods.

Development of Therapeutic Antibodies and Modulating the Characteristics of Therapeutic Antibodies to Maximize the Therapeutic Efficacy

Monoclonal antibodies (mAb) have been used as therapeutic agents for various diseases, and immunoglobulin G (IgG) is mainly used among antibody isotypes due to its structural and functional properties. So far, regardless of the purpose of the therapeutic antibody, wildtype IgG has been mainly used, but recently, the engineered antibodies with various strategies according to the role of the therapeutic antibody have been used to maximize the therapeutic efficacy. In this review paper, first, the overall structural features and functional characteristics of antibody IgG, second, the old and new techniques for antibody discovery, and finally, several antibody engineering strategies for maximizing therapeutic efficacy according to the role of a therapeutic antibody will be introduced.

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

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

Proper Read Filtering Method to Adequately Analyze Whole-Transcriptome Sequencing and RNA Based Immune Repertoire Sequencing Data for Tumor Milieu Research

Simple Summary

The recent advancement in high-throughput sequencing has become indispensable for immune-genomics and profiling the T- and B-cell receptor repertoires. Immune repertoire sequencing (IR-seq) and whole transcriptome sequencing (WTS) can be implemented to investigate and quantitatively characterize the complex pattern of the CDR3 region. We conducted T-cell diversity analysis result comparisons of these sequencing methods and suggest an intuitive approach to discriminate reliable TCR sequences and clonotype patterns from capturing errors. Although bulk-RNA sequencing is commonly used for cancer analysis, we confirmed capturing highly enriched TCR transcripts with IR-seq is more reliable for accurate immune repertoire discovery, and singleton read filtering criteria should be applied to capture true clonotypes from error-prone sequencing data. The use of such well-established data and analytical methodologies can broaden understanding of antigen specificity in immunity and enabling efficient therapeutic antibody finding.

Abstract

Analysis of the T-cell receptor (TCR) repertoire is essential to characterize the extensive collections of T-cell populations with recognizing antigens in cancer research, and whole transcriptome sequencing (WTS) and immune repertoire sequencing (IR-seq) are commonly used for this measure. To date, no standard read filtering method for IR measurement has been presented. We assessed the diversity of the TCR repertoire results from the paired WTS and IR-seq data of 31 multiple myeloma (MM) patients. To invent an adequate read filtering strategy for IR analysis, we conducted comparisons with WTS results. First, our analyses for determining an optimal threshold for selecting clonotypes showed that the clonotypes supported by a single read largely affected the shared clonotypes and manifested distinct patterns of mapping qualities, unlike clonotypes with multiple reads. Second, although IR-seq could reflect a wider TCR region with a higher capture rate than WTS, an adequate comparison with the removal of unwanted bias from potential sequencing errors was possible only after applying our read filtering strategy. As a result, we suggest that TCR repertoire analysis be carried out through IR-seq to produce reliable and accurate results, along with the removal of single-read clonotypes, to conduct immune research in cancer using high-throughput sequencing.

Antibody-guided structure-based vaccines

The vaccine field is pursuing diverse approaches to translate the molecular insights from analyses of effective antibodies and their targeted epitopes into immunogens capable of eliciting protective immune responses. Here we review current antibody-guided strategies including conformation-based, epitope-based, and lineage-based vaccine approaches, which are yielding promising vaccine candidates now being evaluated in clinical trials. We summarize directions being employed by the field, including the use of sequencing technologies to monitor and track developing immune responses for understanding and improving antibody-based immunity. We review opportunities and challenges to transform powerful new discoveries into safe and effective vaccines, which are encapsulated by vaccine efforts against a variety of pathogens including HIV-1, influenza A virus, malaria parasites, respiratory syncytial virus, and SARS-CoV-2. Overall, this review summarizes the extensive progress that has been made to realize antibody-guided structure-based vaccines, the considerable challenges faced, and the opportunities afforded by recently developed molecular approaches to vaccine development.

RNase H-dependent PCR enables highly specific amplification of antibody variable domains from single B-cells

Immunization-based antibody discovery platforms require robust and effective protocols for the amplification, cloning, expression, and screening of antibodies from large numbers of B-cells in order to effectively capture the diversity of an experienced Ig-repertoire. Multiplex PCR using a series of forward and reverse primers designed to recover antibodies from a range of different germline sequences is challenging because primer design requires the recovery of full length antibody sequences, low starting template concentrations, and the need for all the primers to function under the same PCR conditions. Here we demonstrate several advantages to incorporating RNase H2-dependent PCR (rh-PCR) into a high-throughput, antibody-discovery platform. Firstly, rh-PCR eliminated primer dimer synthesis to below detectable levels, thereby eliminating clones with a false positive antibody titer. Secondly, by increasing the specificity of PCR, the rh-PCR primers increased the recovery of cognate antibody variable regions from single B-cells, as well as downstream recombinant antibody titers. Finally, we demonstrate that rh-PCR primers provide a more homogeneous sample pool and greater sequence quality in a Next Generation Sequencing-based approach to obtaining DNA sequence information from large numbers of cloned antibody cognate pairs. Furthermore, the higher specificity of the rh-PCR primers allowed for a better match between native antibody germline sequences and the VL/VH fragments amplified from single B-cells.

Deep phenotypic characterization of immunization-induced antibacterial IgG repertoires in mice using a single-antibody bioassay

Antibodies with antibacterial activity need to bind to the bacterial surface with affinity, specificity, and sufficient density to induce efficient elimination. To characterize the anti-bacterial antibody repertoire, we developed an in-droplet bioassay with single-antibody resolution. The assay not only allowed us to identify whether the secreted antibodies recognized a bacterial surface antigen, but also to estimate the apparent dissociation constant (KD app) of the interaction and the density of the recognized epitope on the bacteria. Herein, we found substantial differences within the KD app/epitope density profiles in mice immunized with various species of heat-killed bacteria. The experiments further revealed a high cross-reactivity of the secreted IgG repertoires, binding to even unrelated bacteria with high affinity. This application confirmed the ability to quantify the anti-bacterial antibody repertoire and the utility of the developed bioassay to study the interplay between bacteria and the humoral response.

Towards a Systems Immunology Approach to Unravel Responses to Cancer Immunotherapy

Immunotherapy, particularly immune checkpoint blockade and chimeric antigen receptor (CAR)-T cells, holds a great promise against cancer. These treatments have markedly improved survival in solid as well as in hematologic tumors previously considered incurable. However, durable responses occur in a fraction of patients, and existing biomarkers (e.g. PD-L1) have shown limited prediction power. This scenario highlights the need to dissect the complex interplay between immune and tumor cells to identify reliable biomarkers of response to be used for patients’ selection. In this context, systems immunology represents indeed the new frontier to address important clinical challenges in biomarker discovery. Through the integration of multiple layers of data obtained with several high-throughput approaches, systems immunology may give insights on the vast range of inter-individual differences and on the influences of genes and factors that cooperatively shape the individual immune response to a given treatment. In this Mini Review, we give an overview of the current high-throughput methodologies, including genomics, epigenomics, transcriptomics, metabolomics, proteomics, and multi-parametric phenotyping suitable for systems immunology as well as on the key steps of data integration and biological interpretation. Additionally, we review recent studies in which multi-omics technologies have been used to characterize mechanisms of response and to identify powerful biomarkers of response to checkpoint inhibitors, CAR-T cell therapy, dendritic cell-based and peptide-based cancer vaccines. We also highlight the need of favoring the collaboration of researchers with complementary expertise and of integrating multi-omics data into biological networks with the final goal of developing accurate markers of therapeutic response.

Selectivity over coverage in de novo sequencing of IgGs

Although incredibly diverse in specificity, millions of unique Immunoglobulin G (IgG) molecules in the human antibody repertoire share most of their amino acid sequence. These constant parts of IgG do not yield any useful information in attempts to sequence antibodies de novo. Therefore, methods focusing solely on the variable regions and providing unambiguous sequence reads are strongly advantageous. We report a mass spectrometry-based method that uses electron capture dissociation (ECD) to provide straightforward-to-read sequence ladders for the variable parts of both the light and heavy chains, with a preference for the functionally important CDR3. We optimized this method on the therapeutic antibody Trastuzumab and demonstrate its applicability on two monoclonal quartets of the four IgG subclasses, IgG1, IgG2, IgG3 and IgG4. The method is based on proteolytically separating the variable F(ab')₂ part from the conserved Fc part, whereafter the F(ab')₂ portions are mass-analyzed and fragmented by ECD. Pure ECD, without additional collisional activation, leads to straightforward-to-read sequence tags covering the CDR3 of both the light and heavy chains. Using molecular modelling and structural analysis, we discuss and explain this selective fragmentation behavior and describe how structural features of the different IgG subclasses lead to distinct fragmentation patterns. Overall, we foresee that pure ECD on F(ab')₂ or Fab molecules can become a valuable tool for the de novo sequencing of serum antibodies.

Computational approaches to therapeutic antibody design: established methods and emerging trends

Antibodies are proteins that recognize the molecular surfaces of potentially noxious molecules to mount an adaptive immune response or, in the case of autoimmune diseases, molecules that are part of healthy cells and tissues. Due to their binding versatility, antibodies are currently the largest class of biotherapeutics, with five monoclonal antibodies ranked in the top 10 blockbuster drugs. Computational advances in protein modelling and design can have a tangible impact on antibody-based therapeutic development. Antibody-specific computational protocols currently benefit from an increasing volume of data provided by next generation sequencing and application to related drug modalities based on traditional antibodies, such as nanobodies. Here we present a structured overview of available databases, methods and emerging trends in computational antibody analysis and contextualize them towards the engineering of candidate antibody therapeutics.

Accurate estimation of microbial sequence diversity with Distanced

MOTIVATION

Microbes are the most diverse organisms on the planet. Deep sequencing of ribosomal DNA (rDNA) suggests thousands of different microbes may be present in a single sample. However, errors in sequencing have made any estimate of within-sample (alpha) diversity uncertain.

RESULTS

We developed a tool to estimate alpha diversity of rDNA sequences from microbes (and other sequences). Our tool, Distanced, calculates how different (distant) sequences would be without sequencing errors. It does this using a Bayesian approach. Using this approach, Distanced accurately estimated alpha diversity of rDNA sequences from bacteria and fungi. It had lower root mean square prediction error (RMSPE) than when using no tool (leaving sequencing errors uncorrected). It was also accurate with non-microbial sequences (antibody mRNA). State-of-the-art tools (DADA2 and Deblur) were far less accurate. They often had higher RMSPE than when using no tool. Distanced thus represents an improvement over existing tools. Distanced will be useful to several disciplines, given microbial diversity affects everything from human health to ecosystem function.

AVAILABILITY AND IMPLEMENTATION

Distanced is freely available at https://github.com/thackmann/Distanced.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

PIRD: Pan Immune Repertoire Database

MOTIVATION

T and B cell receptors (TCRs and BCRs) play a pivotal role in the adaptive immune system by recognizing an enormous variety of external and internal antigens. Understanding these receptors is critical for exploring the process of immunoreaction and exploiting potential applications in immunotherapy and antibody drug design. Although a large number of samples have had their TCR and BCR repertoires sequenced using high-throughput sequencing in recent years, very few databases have been constructed to store these kinds of data. To resolve this issue, we developed a database.

RESULTS

We developed a database, the Pan Immune Repertoire Database (PIRD), located in China National GeneBank (CNGBdb), to collect and store annotated TCR and BCR sequencing data, including from Homo sapiens and other species. In addition to data storage, PIRD also provides functions of data visualization and interactive online analysis. Additionally, a manually curated database of TCRs and BCRs targeting known antigens (TBAdb) was also deposited in PIRD.

AVAILABILITY AND IMPLEMENTATION

PIRD can be freely accessed at https://db.cngb.org/pird.

High-throughput sequencing analysis of genes encoding the B-lymphocyte receptor heavy-chain CDR3 in renal and peripheral blood of IgA nephropathy

Aim: IgA nephropathy (IgAN) is one of the most common chronic glomerulonephritis. Its etiology and pathogenesis remain unclear. We thus explored the immune repertoire of the B-cell receptor (BCR) and the heavy-chain complementarity-determining region 3 (CDR3) in renal tissue and peripheral blood of IgAN patients. Method: Total RNAs extracted from renal tissues and peripheral blood of patients and peripheral blood of healthy controls (HCs) were analyzed via high-throughput multiplex PCR sequencing. We amplified and sequenced BCR heavy-chain CDR3 regions to explore repertoire diversity, V/J gene family distribution, CDR3 lengths, BCR heavy-chain variants, consistency between tissue and peripheral blood data, and clones ‘shared’ by these bodily compartments. Results: We identified the renal tissue and peripheral blood BCR heavy-chain CDR3 immune repertoires of 15 IgAN patients. Top1 could be more readily cloned from peripheral blood of patients than from controls (P<0.05), the average CDR3 length was significantly shorter in patients than in HCs (P<0.05), the variant frequency of the gene encoding the BCR heavy chain was higher in patients than in HCs (P<0.05), and the BCR variant frequency was highest in IgAN kidney tissue. Preliminary screening for ‘shared’ clones showed that, in at least 13 patients, the ‘ALYFHNSAY’, ‘ARWGPMYYYMDV’, ‘ARDQGALNA’, and ‘ARVDNPADF’ CDR3 sequences were evident in peripheral blood samples from patients, but not HCs. Conclusions: We found that the ‘ALYFHNSAY’, ‘ARWGPMYYYMDV’, ‘ARDQGALNA’, and ‘ARVDNPADF’ clonal sequences may be useful for noninvasive diagnosis and treatment planning in IgAN.

GLaMST: grow lineages along minimum spanning tree for b cell receptor sequencing data

Background

B cell affinity maturation enables B cells to generate high-affinity antibodies. This process involves somatic hypermutation of B cell immunoglobulin receptor (BCR) genes and selection by their ability to bind antigens. Lineage trees are used to describe this microevolution of B cell immunoglobulin genes. In a lineage tree, each node is one BCR sequence that mutated from the germinal center and each directed edge represents a single base mutation, insertion or deletion. In BCR sequencing data, the observed data only contains a subset of BCR sequences in this microevolution process. Therefore, reconstructing the lineage tree from experimental data requires algorithms to build the tree based on partially observed tree nodes.

Results

We developed a new algorithm named Grow Lineages along Minimum Spanning Tree (GLaMST), which efficiently reconstruct the lineage tree given observed BCR sequences that correspond to a subset of the tree nodes. Through comparison using simulated and real data, GLaMST outperforms existing algorithms in simulations with high rates of mutation, insertion and deletion, and generates lineage trees with smaller size and closer to ground truth according to tree features that highly correlated with selection pressure.

Conclusions

GLaMST outperforms state-of-art in reconstruction of the BCR lineage tree in both efficiency and accuracy. Integrating it into existing BCR sequencing analysis frameworks can significant improve lineage tree reconstruction aspect of the analysis.

FcRn Overexpression Expands Diversity of the Humoral Immune Response in bFcRn Transgenic Mice

The neonatal Fc receptor (FcRn) plays key roles in IgG and albumin homeostasis, maternal IgG transport, and antigen presentation of IgG-opsonized antigens. Previously, we reported that transgenic (Tg) mice that overexpress bovine FcRn (bFcRn) have augmented T-dependent humoral immune response with increased IgG protection, higher level of antigen-specific antibodies, greater number of antigen-specific B cells, and effective immune response even against weakly immunogenic epitopes. In this study we analyzed the diversity of the humoral immune response of bFcRn Tg mice, using a length distribution analysis (spectratyping) and next generation sequencing (NGS) of the immunoglobulin heavy chain variable regions. Our analysis showed that in response to immunization with ovalbumin or transfected cells that expressed a unique membrane protein, our Tg animals developed a more diverse plasma cell repertoire than controls, which manifested in greater numbers of different clones, and clusters with fewer highly expanded large clones, as identified by the variable region (CDR3) of the immunoglobulin heavy chain. The increased antibody diversity in Tg mice after immunization was observed at both IgM and IgG levels, indicating that the increased humoral immune diversity in Tg mice is due to a higher number of both activated, antigen-specific naïve and isotype switched B cells. We thus demonstrated that the BCR repertoire of the immunized bFcRn Tg animals is more diverse compared to wild type mice, which likely makes these Tg mice a better choice for monoclonal antibody production against challenging antigens, including the extracellular regions of cell membrane proteins.

The Molecular Mechanisms That Underlie the Immune Biology of Anti-drug Antibody Formation Following Treatment With Monoclonal Antibodies

Monoclonal antibodies (mAbs) are a crucial asset for human health and modern medicine, however, the repeated administration of mAbs can be highly immunogenic. Drug immunogenicity manifests in the generation of anti-drug antibodies (ADAs), and some mAbs show immunogenicity in up to 70% of patients. ADAs can alter a drug's pharmacokinetic and pharmacodynamic properties, reducing drug efficacy. In more severe cases, ADAs can neutralize the drug's therapeutic effects or cause severe adverse events to the patient. While some contributing factors to ADA formation are known, the molecular mechanisms of how therapeutic mAbs elicit ADAs are not completely clear. Accurate ADA detection is necessary to provide clinicians with sufficient information for patient monitoring and clinical intervention. However, ADA assays present unique challenges because both the analyte and antigen are antibodies, so most assays are cumbersome, costly, time consuming, and lack standardization. This review will discuss aspects related to ADA formation following mAb drug administration. First, we will provide an overview of the prevalence of ADA formation and the available diagnostic tools for their detection. Next, we will review studies that support possible molecular mechanisms causing the formation of ADA. Finally, we will summarize recent approaches used to decrease the propensity of mAbs to induce ADAs.

Coronaviruses pandemics: Can neutralizing antibodies help?

For the first time in Homo sapiens history, possibly, most of human activities is stopped by coronavirus disease 2019 (COVID-19). Nearly eight billion people of this world are facing a great challenge, maybe not "to be or not to be" yet, but unpredictable. What happens to other major pandemics in the past, and how human beings went through these hurdles? The human body is equipped with the immune system that can recognize, respond and fight against pathogens such as viruses. Following the innate response, immune system processes the adaptive response by which each pathogen is encoded and recorded in memory system. The humoral reaction containing cytokines and antibodies is expected to activate when the pathogens come back. Exploiting this nature of body protection, neutralizing antibodies have been investigated. Learning from past, in parallel to SARS-CoV-2, other coronaviruses SARS-CoV and MERS-CoV who caused previous pandemics, are recalled in this review. We here propose insights of origin and characteristics and perspective for the future of antibodies development.

Data Integration for Immunology

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

Nonbifurcating Phylogenetic Tree Inference via the Adaptive LASSO

Phylogenetic tree inference using deep DNA sequencing is reshaping our understanding of rapidly evolving systems, such as the within-host battle between viruses and the immune system. Densely sampled phylogenetic trees can contain special features, including sampled ancestors in which we sequence a genotype along with its direct descendants, and polytomies in which multiple descendants arise simultaneously. These features are apparent after identifying zero-length branches in the tree. However, current maximum-likelihood based approaches are not capable of revealing such zero-length branches. In this paper, we find these zero-length branches by introducing adaptive-LASSO-type regularization estimators for the branch lengths of phylogenetic trees, deriving their properties, and showing regularization to be a practically useful approach for phylogenetics.

Validation of Methods to Assess the Immunoglobulin Gene Repertoire in Tissues Obtained from Mice on the International Space Station

Spaceflight is known to affect immune cell populations. In particular, splenic B-cell numbers decrease during spaceflight and in ground-based physiological models. Although antibody isotype changes have been assessed during and after spaceflight, an extensive characterization of the impact of spaceflight on antibody composition has not been conducted in mice. Next Generation Sequencing and bioinformatic tools are now available to assess antibody repertoires. We can now identify immunoglobulin gene-segment usage, junctional regions, and modifications that contribute to specificity and diversity. Due to limitations on the International Space Station, alternate sample collection and storage methods must be employed. Our group compared Illumina MiSeq® sequencing data from multiple sample preparation methods in normal C57Bl/6J mice to validate that sample preparation and storage would not bias the outcome of antibody repertoire characterization. In this report, we also compared sequencing techniques and a bioinformatic workflow on the data output when we assessed the IgH and Igκ variable gene usage. Our bioinformatic workflow has been optimized for Illumina HiSeq® and MiSeq® datasets, and is designed specifically to reduce bias, capture the most information from Ig sequences, and produce a data set that provides other data mining options.

High-Throughput Screening for Substrate Specificity-Adapted Mutants of the Nisin Dehydratase NisB

Microbial lanthipeptides are formed by a two-step enzymatic introduction of (methyl)lanthionine rings. A dehydratase catalyzes the dehydration of serine and threonine residues, yielding dehydroalanine and dehydrobutyrine, respectively. Cyclase-catalyzed coupling of the formed dehydroresidues to cysteines forms (methyl)lanthionine rings in a peptide. Lanthipeptide biosynthetic systems allow discovery of target-specific, lanthionine-stabilized therapeutic peptides. However, the substrate specificity of existing modification enzymes impose limitations on installing lanthionines in non-natural substrates. The goal of the present study was to obtain a lanthipeptide dehydratase with the capacity to dehydrate substrates that are unsuitable for the nisin dehydratase NisB. We report high-throughput screening for tailored specificity of intracellular, genetically encoded NisB dehydratases. The principle is based on the screening of bacterially displayed lanthionine-constrained streptavidin ligands, which have a much higher affinity for streptavidin than linear ligands. The designed NisC-cyclizable high-affinity ligands can be formed via mutant NisB-catalyzed dehydration but less effectively via wild-type NisB activity. In Lactococcus lactis, a cell surface display precursor was designed comprising DSHPQFC. The Asp residue preceding the serine in this sequence disfavors its dehydration by wild-type NisB. The cell surface display vector was coexpressed with a mutant NisB library and NisTC. Subsequently, mutant NisB-containing bacteria that display cyclized strep ligands on the cell surface were selected via panning rounds with streptavidin-coupled magnetic beads. In this way, a NisB variant with a tailored capacity of dehydration was obtained, which was further evaluated with respect to its capacity to dehydrate nisin mutants. These results demonstrate a powerful method for selecting lanthipeptide modification enzymes with adapted substrate specificity.

Profiling immunoglobulin repertoires across multiple human tissues using RNA sequencing

Profiling immunoglobulin (Ig) receptor repertoires with specialized assays can be cost-ineffective and time-consuming. Here we report ImReP, a computational method for rapid and accurate profiling of the Ig repertoire, including the complementary-determining region 3 (CDR3), using regular RNA sequencing data such as those from 8,555 samples across 53 tissues types from 544 individuals in the Genotype-Tissue Expression (GTEx v6) project. Using ImReP and GTEx v6 data, we generate a collection of 3.6 million Ig sequences, termed the atlas of immunoglobulin repertoires (TAIR), across a broad range of tissue types that often do not have reported Ig repertoires information. Moreover, the flow of Ig clonotypes and inter-tissue repertoire similarities across immune-related tissues are also evaluated. In summary, TAIR is one of the largest collections of CDR3 sequences and tissue types, and should serve as an important resource for studying immunological diseases.

Information on immune receptor repertoire provides important insights on disease progression and therapy development, but can be expensive and time-consuming to obtain. Here the authors report ImReP, a computational method that can extract detailed immune repertoire information from existing tissue-specific RNA sequencing data.

SOS: online probability estimation and generation of T-and B-cell receptors

Summary

Recent advances in modelling VDJ recombination and subsequent selection of T- and B-cell receptors provide useful tools to analyse and compare immune repertoires across time, individuals and tissues. A suite of tools—IGoR, OLGA and SONIA—have been publicly released to the community that allow for the inference of generative and selection models from high-throughput sequencing data. However, using these tools requires some scripting or command-line skills and familiarity with complex datasets. As a result, the application of the above models has not been available to a broad audience. In this application note, we fill this gap by presenting Simple OLGA & SONIA (SOS), a web-based interface where users with no coding skills can compute the generation and post-selection probabilities of their sequences, as well as generate batches of synthetic sequences. The application also functions on mobile phones.

Availability and implementation

SOS is freely available to use at sites.google.com/view/statbiophysens/sos with source code at github.com/statbiophys/sos.

A Protein Epitope Targeted by the Antibody Response to Kawasaki Disease

BACKGROUND

Kawasaki disease (KD) is the leading cause of childhood acquired heart disease in developed nations and can result in coronary artery aneurysms and death. Clinical and epidemiologic features implicate an infectious cause but specific antigenic targets of the disease are unknown. Peripheral blood plasmablasts are normally highly clonally diverse but the antibodies they encode are approximately 70% antigen-specific 1-2 weeks after infection.

METHODS

We isolated single peripheral blood plasmablasts from children with KD 1-3 weeks after onset and prepared 60 monoclonal antibodies (mAbs). We used the mAbs to identify their target antigens and assessed serologic response among KD patients and controls to specific antigen.

RESULTS

Thirty-two mAbs from 9 of 11 patients recognize antigen within intracytoplasmic inclusion bodies in ciliated bronchial epithelial cells of fatal cases. Five of these mAbs, from 3 patients with coronary aneurysms, recognize a specific peptide, which blocks binding to inclusion bodies. Sera from 5/8 KD patients day ≥ 8 after illness onset, compared with 0/17 infant controls (P < .01), recognized the KD peptide antigen.

CONCLUSIONS

These results identify a protein epitope targeted by the antibody response to KD and provide a means to elucidate the pathogenesis of this important worldwide pediatric problem.

IgGeneUsage: differential gene usage in immune repertoires

SUMMARY

Decoding the properties of immune repertoires is key to understanding the adaptive immune response to challenges such as viral infection. One important quantitative property is differential usage of Ig genes between biological conditions. Yet, most analyses for differential Ig gene usage are performed qualitatively or with inadequate statistical methods. Here we introduce IgGeneUsage, a computational tool for the analysis of differential Ig gene usage. IgGeneUsage employs Bayesian inference with hierarchical models to analyze complex gene usage data from high-throughput sequencing experiments of immune repertoires. It quantifies differential Ig gene usage probabilistically and avoids some common problems related to the current practice of null-hypothesis significance testing.

AVAILABILITY AND IMPLEMENTATION

IgGeneUsage is an R-package freely available as part of Bioconductor at: https://bioconductor.org/packages/IgGeneUsage/.

CONTACT

simo.kitanovski@uni-due.de.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Profiling Virus-Specific Tcf1+ T Cell Repertoires During Acute and Chronic Viral Infection

CD8 T cells play a crucial role in providing protection from viral infections. It has recently been established that a subset of CD8 T cells expressing Tcf1 are responsible for sustaining exhausted T cells during chronic lymphocytic choriomeningitis virus (LCMV) infection. Many of these studies, however, have been performed using T cell receptor (TCR) transgenic mice, in which CD8 T cells express a monoclonal TCR specific for the LCMV glycoprotein. To investigate whether the Tcf1+ and Tcf1- repertoires are naturally composed of similar or different clones in wild-type mice exposed to acute or chronic LCMV infection, we performed TCR repertoire sequencing of virus-specific CD8 T cells, including Tcf1+ and Tcf1- populations. Our analysis revealed that the Tcf1+ TCR repertoire is maintained at an equal or higher degree of clonal diversity despite harboring fewer cells. Additionally, within the same animal, there was extensive clonal overlap between the Tcf1+ and Tcf1- repertoires in both chronic and acute LCMV infection. We could further detect these virus-specific clones in longitudinal blood samples earlier in the infection. With respect to common repertoire parameters (clonal overlap, germline gene usage, and clonal expansion), we found minor differences between the virus-specific TCR repertoire of acute and chronic LCMV infection 40 days post infection. Overall, our results indicate that the Tcf1+ population emerging during chronic LCMV infection is not clonally distinct from the Tcf1- population, supporting the notion that the Tcf1+ pool is indeed a fuel for the more exhausted Tcf1- population within the heterogenous repertoire of LCMV-specific CD8 T cells.

IgM Antibody Repertoire Fingerprints in Mice Are Personalized but Robust to Viral Infection Status

Antibody repertoire sequencing provides a molecular fingerprint of current and past pathogens encountered by the immune system. Most repertoire studies in humans require measuring the B cell response in the blood, resulting in a large bias to the IgM isotype. The extent to which the circulating IgM antibody repertoire correlates to lymphoid tissue-resident B cells in the setting of viral infection remains largely uncharacterized. Therefore, we compared the IgM repertoires from both blood and bone marrow (BM) plasma cells (PCs) following acute or chronic lymphocytic choriomeningitis virus (LCMV) infection in mice. Despite previously reported serum alterations between acute and chronic infection, IgM repertoire signatures based on clonal diversity metrics, public clones, network, and phylogenetic analysis were largely unable to distinguish infection cohorts. Our findings, however, revealed mouse-specific repertoire fingerprints between the blood and PC repertoires irrespective of infection status.

OGRDB: a reference database of inferred immune receptor genes

High-throughput sequencing of the adaptive immune receptor repertoire (AIRR-seq) is providing unprecedented insights into the immune response to disease and into the development of immune disorders. The accurate interpretation of AIRR-seq data depends on the existence of comprehensive germline gene reference sets. Current sets are known to be incomplete and unrepresentative of the degree of polymorphism and diversity in human and animal populations. A key issue is the complexity of the genomic regions in which they lie, which, because of the presence of multiple repeats, insertions and deletions, have not proved tractable with short-read whole genome sequencing. Recently, tools and methods for inferring such gene sequences from AIRR-seq datasets have become available, and a community approach has been developed for the expert review and publication of such inferences. Here, we present OGRDB, the Open Germline Receptor Database (https://ogrdb.airr-community.org), a public resource for the submission, review and publication of previously unknown receptor germline sequences together with supporting evidence.