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Next-generation sequencing of immunoglobulin gene repertoires (Ig-seq) allows the investigation of large-scale antibody dynamics at a sequence level. However, structural information, a crucial descriptor of antibody binding capability, is not collected in Ig-seq protocols. Developing systematic relationships between the antibody sequence information gathered from Ig-seq and low-throughput techniques such as X-ray crystallography could radically improve our understanding of antibodies. The mapping of Ig-seq datasets to known antibody structures can indicate structurally, and perhaps functionally, uncharted areas. Furthermore, contrasting naïve and antigenically challenged datasets using structural antibody descriptors should provide insights into antibody maturation. As the number of antibody structures steadily increases and more and more Ig-seq datasets become available, the opportunities that arise from combining the two types of information increase as well. Here, we review how these data types enrich one another and show potential for advancing our knowledge of the immune system and improving antibody engineering.

Cryopreservation of human B cells is widely employed in clinical and research applications. However, it is still commonly believed that only freshly isolated B cells should be analyzed to accurately evaluate, both quantitatively and qualitatively, the immunoglobulin (Ig) repertoire. In this study, we use next-generation sequencing to investigate how the Ig repertoire reshapes after cryopreservation of B cells, with special focus on the clonotype representation after freeze-thawing, either with and without subsequent restimulation. Our findings indicated that the Ig repertoire was preserved after cell freezing, which might encourage scientists to use cryopreserved, patient-derived B cells in the studies of Ig repertoire, as well as demonstrated potential clinical and experimental applications of monitoring the Ig repertoire of cryopreserved B cells.

With the advent of high-throughput sequencing of immunoglobulin genes (Ig-Seq), the understanding of antibody repertoires and their dynamics among individuals and populations has become an exciting area of research. There is an increasing number of computational tools that aid in every step of the immune repertoire characterization. However, since not all tools function identically, every pipeline has its unique rationale and capabilities, creating a rich blend of useful features that may appear intimidating for newcomer laboratories with the desire to plunge into immune repertoire analysis to expand and improve their research; hence, all pipeline strengths and differences may not seem evident. In this review we provide a practical and organized list of the current set of computational tools, focusing on their most attractive features and differences in order to carry out the characterization of antibody repertoires so that the reader better decides a strategic approach for the experimental design, and computational pathways for the analyses of immune repertoires.

Antibodies are powerful tools for the therapy and diagnosis of various diseases. In addition to conventional hybridoma-based screening, recombinant antibody-based screening has become a common choice; however, its application is hampered by two factors: (1) screening starts after Ig gene cloning and recombinant antibody production only, and (2) the antibody is composed of paired chains, heavy and light, commonly expressed by two independent expression vectors. Here, we introduce a method for the rapid screening of recombinant monoclonal antibodies by establishing a Golden Gate-based dual-expression vector and in-vivo expression of membrane-bound antibodies. Using this system, we demonstrate the rapid isolation of influenza cross-reactive antibodies with high affinity from immunized mice within 7 days. This system is particularly useful for isolating therapeutic or diagnostic antibodies, for example during foreseen pandemics.

Immunoproteomics has emerged as a versatile tool for analyzing the antibody repertoire in various disease contexts. Until recently, characterization of antibody molecules in biological fluids was limited to bulk serology, which identifies clinically relevant features of polyclonal antibody responses. The past decade, however, has seen the rise of mass-spectrometry-enabled proteomics methods that have allowed profiling of the antibody response at the molecular level, with the disease-specific serological repertoire elucidated in unprecedented detail. In this review, we present an up-to-date survey of insights into the disease-specific immunological repertoire by examining how quantitative proteomics-based approaches have shed light on the humoral immune response to infection and vaccination in pathogenic illnesses, the molecular basis of autoimmune disease, and the tumor-specific repertoire in cancer. We address limitations of this technology with a focus on emerging potential solutions and discuss the promise of high-resolution immunoproteomics in therapeutic discovery and novel vaccine design.

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.

Detailed knowledge of the diverse immunoglobulin germline genes is critical for the study of humoral immunity. Hundreds of alleles have been discovered by analyzing antibody repertoire sequencing (Rep-seq or Ig-seq) data via multiple novel allele detection tools (NADTs). However, the performance of these NADTs through antibody sequences with intrinsic somatic hypermutations (SHMs) is unclear. Here, we developed a tool to simulate repertoires by integrating the full spectrum features of an antibody repertoire such as germline gene usage, junctional modification, position-specific SHM and clonal expansion based on 2152 high-quality datasets. We then systematically evaluated these NADTs using both simulated and genuine Ig-seq datasets. Finally, we applied these NADTs to 687 Ig-seq datasets and identified 43 novel allele candidates (NACs) using defined criteria. Twenty-five alleles were validated through findings of other sources. In addition to the NACs detected, our simulation tool, the results of our comparison, and the streamline of this process may benefit further humoral immunity studies via Ig-seq.

The human antibody repertoire is generated by the recombination of different gene segments as well as by processes of somatic mutation. Together these mechanisms result in a tremendous diversity of antibodies that are able to combat various pathogens including viruses and bacteria, or malignant cells. In this review, we summarize the opportunities and challenges that are associated with the analyses of the B cell receptor repertoire and the antigen-specific B cell response. We will discuss how recent advances have increased our understanding of the antibody response and how repertoire analyses can be exploited to inform on vaccine strategies, particularly against HIV-1.

Reproducible and robust data on antibody repertoires are invaluable for basic and applied immunology. Next-generation sequencing (NGS) of antibody variable regions has emerged as a powerful tool in systems immunology, providing quantitative molecular information on antibody polyclonal composition. However, major computational challenges exist when analyzing antibody sequences, from error handling to hypermutation profiles and clonal expansion analyses. In this work, we developed the ASAP (A webserver for Immunoglobulin-Seq Analysis Pipeline) webserver (https://asap.tau.ac.il). The input to ASAP is a paired-end sequence dataset from one or more replicates, with or without unique molecular identifiers. These datasets can be derived from NGS of human or murine antibody variable regions. ASAP first filters and annotates the sequence reads using public or user-provided germline sequence information. The ASAP webserver next performs various calculations, including somatic hypermutation level, CDR3 lengths, V(D)J family assignments, and V(D)J combination distribution. These analyses are repeated for each replicate. ASAP provides additional information by analyzing the commonalities and differences between the repeats (\"joint\" analysis). For example, ASAP examines the shared variable regions and their frequency in each replicate to determine which sequences are less likely to be a result of a sample preparation derived and/or sequencing errors. Moreover, ASAP clusters the data to clones and reports the identity and prevalence of top ranking clones (clonal expansion analysis). ASAP further provides the distribution of synonymous and non-synonymous mutations within the V genes somatic hypermutations. Finally, ASAP provides means to process the data for proteomic analysis of serum/secreted antibodies by generating a variable region database for liquid chromatography high resolution tandem mass spectrometry (LC-MS/MS) interpretation. ASAP is user-friendly, free, and open to all users, with no login requirement. ASAP is applicable for researchers interested in basic questions related to B cell development and differentiation, as well as applied researchers who are interested in vaccine development and monoclonal antibody engineering. By virtue of its user-friendliness, ASAP opens the antibody analysis field to non-expert users who seek to boost their research with immune repertoire analysis.