High-throughput sequencing of the paired human immunoglobulin heavy and light chain repertoire

Public antibodies: convergent signatures in human humoral immunity against pathogens

The human humoral immune system has evolved to recognize a vast array of pathogenic threats. This ability is primarily driven by the immense diversity of antibodies generated by gene rearrangement during B cell development. However, different people often produce strikingly similar antibodies when exposed to the same antigen-known as public antibodies. Public antibodies not only reflect the immune system's ability to consistently select for optimal B cells but can also serve as signatures of the humoral responses triggered by infection and vaccination. In this Minireview, we examine and compare public antibody identification methods, including the identification criteria used based on V(D)J gene usage and similarity in the complementarity-determining region three sequences, and explore the molecular features of public antibodies elicited against common pathogens, including viruses, protozoa, and bacteria. Finally, we discuss the evolutionary significance and potential applications of public antibodies in informing the design of germline-targeting vaccines, predicting escape mutations in emerging viruses, and providing insights into the process of affinity maturation. The ongoing discovery of public antibodies in response to emerging pathogens holds the potential to improve pandemic preparedness, accelerate vaccine design efforts, and deepen our understanding of human B cell biology.

Enhanced Bioactive Compound Absorption on PMMA Microwell Plates via Fine Controlling Air Plasma Treatment Time for Disease Diagnosis Applications

Microwell plates absorb bioactive compounds and are commonly used for disease prediction, diagnosis, and monitoring. Chemical absorption is more effective than physical absorption for stabilizing these compounds. This study systematically investigates the fundamental mechanisms of air plasma-induced surface modifications in poly(methyl methacrylate) (PMMA), focusing on carboxyl group formation kinetics, morphological evolution, and optical property changes. Air plasma treatment enhances the hydrophilicity and surface roughness of the PMMA plates. Light transmission remains comparable to untreated plates for 10 min treatment durations. Treatment for 3 min significantly increases the large-molecular-weight carboxyl compounds, with minimal loss after wash buffer rinsing. Thus, a 3 min air plasma treatment optimally enhances PMMA microwell plates for effective bioactive compound absorption.

Efficient Identification of Monoclonal Antibodies Against Rift Valley Fever Virus Using High-Throughput Single Lymphocyte Transcriptomics of Immunized Mice

Background: Rift Valley fever virus (RVFV) is a zoonotic virus that poses a significant threat to both livestock and human health and has caused outbreaks in endemic regions. In humans, most patients experience a febrile illness; however, in some patients, RVF disease may result in hemorrhagic fever, retinitis, or encephalitis. While several veterinary vaccines are being utilized in endemic countries, currently, there are no licensed RVF vaccines or therapeutics for human use. Neutralizing antibodies specifically targeting vulnerable pathogen epitopes are promising candidates for prophylactic and therapeutic interventions. In the case of RVFV, the surface glycoproteins Gc and Gn, which harbor neutralizing epitopes, represent the primary targets for vaccine and neutralizing antibody development. Methods: We report the implementation of advanced 10x Genomics technology, enabling high-throughput single-cell analysis for the identification of rare and potent antibodies against RVFV. Following the immunization of mice with live attenuated rMP-12-GFP virus and successive Gc/Gn boosts, memory B cell populations (both general and antigen-specific) were sorted from splenocytes by flow cytometry. Deep sequencing of the antibody repertoire at a single-cell resolution, together with bioinformatic analyses, was applied for BCR pair selection based on their abundance and specificity. Results: Twenty-three recombinant monoclonal antibodies (mAbs) were selected and expressed, and their antigen-binding capacities were characterized. About half of them demonstrated specific binding to their cognate antigen with relatively high binding affinities. Conclusions: These antibodies could be used for the future development of efficacious therapeutics, as well as for studying virus-neutralizing mechanisms. The current study, in which the single-cell sequencing approach was implemented for the development of antibodies targeting the RVFV surface proteins Gc and Gn, demonstrates the effective applicability of this technique for antibody discovery purposes.

Navigating the landscape: A comprehensive overview of computational approaches in therapeutic antibody design and analysis

Immunotherapy, harnessing components like antibodies, cells, and cytokines, has become a cornerstone in treating diseases such as cancer and autoimmune disorders. Therapeutic antibodies, in particular, have transformed modern medicine, providing a targeted approach that destroys disease-causing cells while sparing healthy tissues, thereby reducing the side effects commonly associated with chemotherapy. Beyond oncology, these antibodies also hold promise in addressing chronic infections where conventional therapeutics may fall short. However, antibodies identified through in vivo or in vitro methods often require extensive engineering to enhance their therapeutic potential. This optimization process, aimed at improving affinity, specificity, and reducing immunogenicity, is both challenging and costly, often involving trade-offs between critical properties. Traditional methods of antibody development, such as hybridoma technology and display techniques, are resource-intensive and time-consuming. In contrast, computational approaches offer a faster, more efficient alternative, enabling the precise design and analysis of therapeutic antibodies. These methods include sequence and structural bioinformatics approaches, next-generation sequencing-based data mining, machine learning algorithms, systems biology, immuno-informatics, and integrative approaches. These approaches are advancing the field by providing new insights and enhancing the accuracy of antibody design and analysis. In conclusion, computational approaches are essential in the development of therapeutic antibodies, significantly improving the precision and speed of discovery, optimization, and validation. Integrating these methods with experimental approaches accelerates therapeutic antibody development, paving the way for innovative strategies and treatments for various diseases ranging from cancers to autoimmune and infectious diseases.

Clonal Lineage and Gene Diversity Analysis of Paired Antibody Heavy and Light Chains

Antibodies consist of unique variable heavy (VH) and variable light (VL) chains, and both are required to fully characterize an antibody. Methods to detect paired heavy and light chain variable regions (VH:VL) using high-throughput sequencing (HTS) have recently enabled large-scale analysis of complete functional antibody responses. Here, we describe an HTS computational pipeline to analyze paired VH:VL antibody sequences and obtain a comprehensive profile of immune diversity landscapes, including gene usage, antibody isotypes, and clonal lineage analysis. This protocol uses Illumina MiSeq 2 × 300-bp sequencing data and integrates with several different computational tools for flexible analyses of paired VH:VL gene repertoire data to enable efficient antibody discovery.

Targeted barcoding of variable antibody domains and individual transcriptomes of the human B-cell repertoire using Link-Seq

Here, we present Link-Seq, a highly efficient droplet microfluidic method for combined sequencing of antibody-encoding genes and the transcriptome of individual B cells at large scale. The method is based on 3' barcoding of the transcriptome and subsequent single-molecule PCR in droplets, which freely shift the barcode along specific gene regions, such as the antibody heavy- and light-chain genes. Using the immune repertoire of COVID-19 patients and healthy donors as a model system, we obtain up to 91.7% correctly paired immunoglobulin heavy and light chains. Furthermore, we map the V(D)J usage and obtain sensitivities comparable with the current gold-standard 10× Genomics commercial systems while offering full flexibility in experimental setup and significant cost savings. A further unique feature of Link-Seq is the possibility of barcoding multiple target genes in a site-specific manner. Based on the open character of the platform and its conceptual advantages, we expect Link-Seq to become a versatile tool for single-cell analysis, especially for applications requiring additional processing steps that cannot be implemented on commercially available platforms.

Predicting adaptive immune receptor specificities by machine learning is a data generation problem

Determining the specificity of adaptive immune receptors-B cell receptors (BCRs), their secreted form antibodies, and T cell receptors (TCRs)-is critical for understanding immune responses and advancing immunotherapy and drug discovery. Immune receptors exhibit extensive diversity in their variable domains, enabling them to interact with a plethora of antigens. Despite the significant progress made by AI tools such as AlphaFold in predicting protein structures, challenges remain in accurately modeling the structure and specificity of immune receptors, primarily due to the limited availability of high-quality crystal structures and the complexity of immune receptor-antigen interactions. In this perspective, we highlight recent advancements in sequence-based and structure-based data generation for immune receptors, which are crucial for training machine learning models that predict receptor specificity. We discuss the current bottlenecks and potential future directions in generating and utilizing high-dimensional datasets for predicting and designing the specificity of antibodies and TCRs.

scTrends: A living review of commercial single-cell and spatial 'omic technologies

Understanding the rapidly evolving landscape of single-cell and spatial omic technologies is crucial for advancing biomedical research and drug development. We provide a living review of both mature and emerging commercial platforms, highlighting key methodologies and trends shaping the field. This review spans from foundational single-cell technologies such as microfluidics and plate-based methods to newer approaches like combinatorial indexing; on the spatial side, we consider next-generation sequencing and imaging-based spatial transcriptomics. Finally, we highlight emerging methodologies that may fundamentally expand the scope for data generation within pharmaceutical research, creating opportunities to discover and validate novel drug mechanisms. Overall, this review serves as a critical resource for navigating the commercialization and application of single-cell and spatial omic technologies in pharmaceutical and academic research.

Learning antibody sequence constraints from allelic inclusion

Antibodies and B-cell receptors (BCRs) are produced by B cells, and are built of a heavy chain and a light chain. Although each B cell could express two different heavy chains and four different light chains, usually only a unique pair of heavy chain and light chain is expressed-a phenomenon known as allelic exclusion. However, a small fraction of naive-B cells violate allelic exclusion by expressing two productive light chains, one of which has impaired function; this has been called allelic inclusion. We demonstrate that these B cells can be used to learn constraints on antibody sequence. Using large-scale single-cell sequencing data from humans, we find examples of light chain allelic inclusion in thousands of naive-B cells, which is an order of magnitude larger than existing datasets. We train machine learning models to identify the abnormal sequences in these cells. The resulting models correlate with antibody properties that they were not trained on, including polyreactivity, surface expression, and mutation usage in affinity maturation. These correlations are larger than what is achieved by existing antibody modeling approaches, indicating that allelic inclusion data contains useful new information. We also investigate the impact of similar selection forces on the heavy chain in mouse, and observe that pairing with the surrogate light chain significantly restricts heavy chain diversity.

Antibody sequence determinants of viral antigen specificity

Throughout life, humans experience repeated exposure to viral antigens through infection and vaccination, resulting in the generation of diverse, antigen-specific antibody repertoires. A paramount feature of antibodies that enables their critical contributions in counteracting recurrent and novel pathogens, and consequently fostering their utility as valuable targets for therapeutic and vaccine development, is the exquisite specificity displayed against their target antigens. Yet, there is still limited understanding of the determinants of antibody-antigen specificity, particularly as a function of antibody sequence. In recent years, experimental characterization of antibody repertoires has led to novel insights into fundamental properties of antibody sequences but has been largely decoupled from at-scale antigen specificity analysis. Here, using the LIBRA-seq technology, we generated a large data set mapping antibody sequence to antigen specificity for thousands of B cells, by screening the repertoires of a set of healthy individuals against 20 viral antigens representing diverse pathogens of biomedical significance. Analysis uncovered virus-specific patterns in variable gene usage, gene pairing, somatic hypermutation, as well as the presence of convergent antiviral signatures across multiple individuals, including the presence of public antibody clonotypes. Notably, our results showed that, for B-cell receptors originating from different individuals but leveraging an identical combination of heavy and light chain variable genes, there is a specific CDRH3 identity threshold above which B cells appear to exclusively share the same antigen specificity. This finding provides a quantifiable measure of the relationship between antibody sequence and antigen specificity and further defines experimentally grounded criteria for defining public antibody clonality.IMPORTANCEThe B-cell compartment of the humoral immune system plays a critical role in the generation of antibodies upon new and repeated pathogen exposure. This study provides an unprecedented level of detail on the molecular characteristics of antibody repertoires that are specific to each of the different target pathogens studied here and provides empirical evidence in support of a 70% CDRH3 amino acid identity threshold in pairs of B cells encoded by identical IGHV:IGL(K)V genes, as a means of defining public clonality and therefore predicting B-cell antigen specificity in different individuals. This is of exceptional importance when leveraging public clonality as a method to annotate B-cell receptor data otherwise lacking antigen specificity information. Understanding the fundamental rules of antibody-antigen interactions can lead to transformative new approaches for the development of antibody therapeutics and vaccines against current and emerging viruses.

Single-cell sequencing to multi-omics: technologies and applications

Cells, as the fundamental units of life, contain multidimensional spatiotemporal information. Single-cell RNA sequencing (scRNA-seq) is revolutionizing biomedical science by analyzing cellular state and intercellular heterogeneity. Undoubtedly, single-cell transcriptomics has emerged as one of the most vibrant research fields today. With the optimization and innovation of single-cell sequencing technologies, the intricate multidimensional details concealed within cells are gradually unveiled. The combination of scRNA-seq and other multi-omics is at the forefront of the single-cell field. This involves simultaneously measuring various omics data within individual cells, expanding our understanding across a broader spectrum of dimensions. Single-cell multi-omics precisely captures the multidimensional aspects of single-cell transcriptomes, immune repertoire, spatial information, temporal information, epitopes, and other omics in diverse spatiotemporal contexts. In addition to depicting the cell atlas of normal or diseased tissues, it also provides a cornerstone for studying cell differentiation and development patterns, disease heterogeneity, drug resistance mechanisms, and treatment strategies. Herein, we review traditional single-cell sequencing technologies and outline the latest advancements in single-cell multi-omics. We summarize the current status and challenges of applying single-cell multi-omics technologies to biological research and clinical applications. Finally, we discuss the limitations and challenges of single-cell multi-omics and potential strategies to address them.

Rapid discovery of monoclonal antibodies by microfluidics-enabled FACS of single pathogen-specific antibody-secreting cells

Monoclonal antibodies are increasingly used to prevent and treat viral infections and are pivotal in pandemic response efforts. Antibody-secreting cells (ASCs; plasma cells and plasmablasts) are an excellent source of high-affinity antibodies with therapeutic potential. Current methods to study antigen-specific ASCs either have low throughput, require expensive and labor-intensive screening or are technically demanding and therefore not widely accessible. Here we present a straightforward technology for the rapid discovery of monoclonal antibodies from ASCs. Our approach combines microfluidic encapsulation of single cells into an antibody capture hydrogel with antigen bait sorting by conventional flow cytometry. With our technology, we screened millions of mouse and human ASCs and obtained monoclonal antibodies against severe acute respiratory syndrome coronavirus 2 with high affinity (<1 pM) and neutralizing capacity (<100 ng ml-1) in 2 weeks with a high hit rate (>85% of characterized antibodies bound the target). By facilitating access to the underexplored ASC compartment, the approach enables efficient antibody discovery and immunological studies into the generation of protective antibodies.

Monoclonal Antibody Generation Using Single B Cell Screening for Treating Infectious Diseases

The screening of antigen-specific B cells has been pivotal for biotherapeutic development for over four decades. Conventional antibody discovery strategies, including hybridoma technology and single B cell screening, remain widely used based on their simplicity, accessibility, and proven track record. Technological advances and the urgent demand for infectious disease applications have shifted paradigms in single B cell screening, resulting in increased throughput and decreased time and labor, ultimately enabling the rapid identification of monoclonal antibodies with desired biological and biophysical properties. Herein, we provide an overview of conventional and emergent single B cell screening approaches and highlight their potential strengths and weaknesses. We also detail the impact of innovative technologies-including miniaturization, microfluidics, multiplexing, and deep sequencing-on the recent identification of broadly neutralizing antibodies for infectious disease applications. Overall, the coronavirus disease 2019 (COVID-19) pandemic has reinvigorated efforts to improve the efficiency of monoclonal antibody discovery, resulting in the broad application of innovative antibody discovery methodologies for treating a myriad of infectious diseases and pathological conditions.

Improved detection of tryptic immunoglobulin variable region peptides by chromatographic and gas-phase fractionation techniques

The polyclonal repertoire of circulating antibodies potentially holds valuable information about an individual's humoral immune state. While bottom-up proteomics is well suited for serum proteomics, the vast number of antibodies and dynamic range of serum challenge this analysis. To acquire the serum proteome more comprehensively, we incorporated high-field asymmetric waveform ion-mobility spectrometry (FAIMS) or two-dimensional chromatography into standard trypsin-based bottom-up proteomics. Thereby, the number of variable region (VR)-related spectra increased 1.7-fold with FAIMS and 10-fold with chromatography fractionation. To match antibody VRs to spectra, we combined de novo searching and BLAST alignment. Validation of this approach showed that, as peptide length increased, the de novo accuracy decreased and BLAST performance increased. Through in silico calculations on antibody repository sequences, we determined the uniqueness of tryptic VR peptides and their suitability as antibody surrogate. Approximately one-third of these peptides were unique, and about one-third of all antibodies contained at least one unique peptide.

B-cell receptor immunoglobulin stereotypy in chronic lymphocytic leukemia: Key to understanding disease biology and stratifying patients

Sequence convergence, otherwise stereotypy, of B-cell receptor immunoglobulin (BcR IG) from unrelated patients is a distinctive feature of the IG gene repertoire in chronic lymphocytic leukemia (CLL) whereby patients expressing a particular BcR IG archetype are classified into groups termed stereotyped subsets. From a biological perspective, the fact that a considerable fraction (∼41%) of patients with CLL express (quasi)identical or stereotyped BcR IG underscores the key role of antigen selection in the natural history of CLL. From a clinical perspective, at odds with the pronounced heterogeneity of CLL at large, patients belonging to the same stereotyped subset display consistent clinical presentation and outcome, including response to treatment, likely as a reflection of consistent biological background. Many major stereotyped subsets were recently shown to have satellites, that is, smaller subsets that are immunogenetically similar. Preliminary evidence supports that this similarity extends to shared biological and even clinical features, with important implications for patient stratification. Consequently, BcR IG stereotypy emerges as a powerful tool for dissecting the heterogeneity of CLL toward refined risk stratification and, eventually, more precise therapeutic interventions.

Extraction of the CDRH3 sequence of the mouse antibody repertoire selected upon influenza virus infection by subtraction of the background antibody repertoire

Historically, antibody reactivity to pathogens and vaccine antigens has been evaluated using serological measurements of antigen-specific antibodies. However, it is difficult to evaluate all antibodies that contribute to various functions in a single assay, such as the measurement of the neutralizing antibody titer. Bulk antibody repertoire analysis using next-generation sequencing is a comprehensive method for analyzing the overall antibody response; however, it is unreliable for estimating antigen-specific antibodies due to individual variation. To address this issue, we propose a method to subtract the background signal from the repertoire of data of interest. In this study, we analyzed changes in antibody diversity and inferred the heavy-chain complementarity-determining region 3 (CDRH3) sequences of antibody clones that were selected upon influenza virus infection in a mouse model using bulk repertoire analysis. A decrease in the diversity of the antibody repertoire was observed upon viral infection, along with an increase in neutralizing antibody titers. Using kernel density estimation of sequences in a high-dimensional sequence space with background signal subtraction, we identified several clusters of CDRH3 sequences induced upon influenza virus infection. Most of these repertoires were detected more frequently in infected mice than in uninfected control mice, suggesting that infection-specific antibody sequences can be extracted using this method. Such an accurate extraction of antigen- or infection-specific repertoire information will be a useful tool for vaccine evaluation in the future.

IMPORTANCE

As specific interactions between antigens and cell-surface antibodies trigger the proliferation of B-cell clones, the frequency of each antibody sequence in the samples reflects the size of each clonal population. Nevertheless, it is extremely difficult to extract antigen-specific antibody sequences from the comprehensive bulk antibody sequences obtained from blood samples due to repertoire bias influenced by exposure to dietary antigens and other infectious agents. This issue can be addressed by subtracting the background noise from the post-immunization or post-infection repertoire data. In the present study, we propose a method to quantify repertoire data from comprehensive repertoire data. This method allowed subtraction of the background repertoire, resulting in more accurate extraction of expanded antibody repertoires upon influenza virus infection. This accurate extraction of antigen- or infection-specific repertoire information is a useful tool for vaccine evaluation.

Toolkit for mapping the clonal landscape of tumor-infiltrating B cells

Our current understanding of whether B cell involvement in the tumor microenvironment benefits the patient or the tumor - in distinct cancers, subcohorts and individual patients - is quite limited. Both statements are probably true in most cases: certain clonal B cell populations contribute to the antitumor response, while others steer the immune response away from the desired mechanics. To step up to a new level of understanding and managing B cell behaviors in the tumor microenvironment, we need to rationally discern these roles, which are cumulatively defined by B cell clonal functional programs, specificities of their B cell receptors, specificities and isotypes of the antibodies they produce, and their spatial interactions within the tumor environment. Comprehensive analysis of these characteristics of clonal B cell populations is now becoming feasible with the development of a whole arsenal of advanced technical approaches, which include (1) methods of single-cell and spatial transcriptomics, genomics, and proteomics; (2) methods of massive identification of B cell specificities; (3) methods of deep error-free profiling of B cell receptor repertoires. Here we overview existing techniques, summarize their current application for B cells studies and propose promising future directions in advancing B cells exploration.

Systematic evaluation of B-cell clonal family inference approaches

The reconstruction of clonal families (CFs) in B-cell receptor (BCR) repertoire analysis is a crucial step to understand the adaptive immune system and how it responds to antigens. The BCR repertoire of an individual is formed throughout life and is diverse due to several factors such as gene recombination and somatic hypermutation. The use of Adaptive Immune Receptor Repertoire sequencing (AIRR-seq) using next generation sequencing enabled the generation of full BCR repertoires that also include rare CFs. The reconstruction of CFs from AIRR-seq data is challenging and several approaches have been developed to solve this problem. Currently, most methods use the heavy chain (HC) only, as it is more variable than the light chain (LC). CF reconstruction options include the definition of appropriate sequence similarity measures, the use of shared mutations among sequences, and the possibility of reconstruction without preliminary clustering based on V- and J-gene annotation. In this study, we aimed to systematically evaluate different approaches for CF reconstruction and to determine their impact on various outcome measures such as the number of CFs derived, the size of the CFs, and the accuracy of the reconstruction. The methods were compared to each other and to a method that groups sequences based on identical junction sequences and another method that only determines subclones. We found that after accounting for data set variability, in particular sequencing depth and mutation load, the reconstruction approach has an impact on part of the outcome measures, including the number of CFs. Simulations indicate that unique junctions and subclones should not be used as substitutes for CF and that more complex methods do not outperform simpler methods. Also, we conclude that different approaches differ in their ability to correctly reconstruct CFs when not considering the LC and to identify shared CFs. The results showed the effect of different approaches on the reconstruction of CFs and highlighted the importance of choosing an appropriate method.

Current advancements in B-cell receptor sequencing fast-track the development of synthetic antibodies

Synthetic antibodies (Abs) are a class of engineered proteins designed to mimic the functions of natural Abs. These are produced entirely in vitro, eliminating the need for an immune response. As such, synthetic Abs have transformed the traditional methods of raising Abs. Likewise, deep sequencing technologies have revolutionized genomics and molecular biology. These enable the rapid and cost-effective sequencing of DNA and RNA molecules. They have allowed for accurate and inexpensive analysis of entire genomes and transcriptomes. Notably, via deep sequencing it is now possible to sequence a person's entire B-cell receptor immune repertoire, termed BCR sequencing. This procedure allows for big data explorations of natural Abs associated with an immune response. Importantly, the identified sequences have the ability to improve the design and engineering of synthetic Abs by offering an initial sequence framework for downstream optimizations. Additionally, machine learning algorithms can be introduced to leverage the vast amount of BCR sequencing datasets to rapidly identify patterns hidden in big data to effectively make in silico predictions of antigen selective synthetic Abs. Thus, the convergence of BCR sequencing, machine learning, and synthetic Ab development has effectively promoted a new era in Ab therapeutics. The combination of these technologies is driving rapid advances in precision medicine, diagnostics, and personalized treatments.

Local and Global Variability in Developing Human T-Cell Repertoires

The adaptive immune response relies on T cells that combine phenotypic specialization with diversity of T-cell receptors (TCRs) to recognize a wide range of pathogens. TCRs are acquired and selected during T-cell maturation in the thymus. Characterizing TCR repertoires across individuals and T-cell maturation stages is important for better understanding adaptive immune responses and for developing new diagnostics and therapies. Analyzing a dataset of human TCR repertoires from thymocyte subsets, we find that the variability between individuals generated during the TCR V(D)J recombination is maintained through all stages of T-cell maturation and differentiation. The interindividual variability of repertoires of the same cell type is of comparable magnitude to the variability across cell types within the same individual. To zoom in on smaller scales than whole repertoires, we defined a distance measuring the relative overlap of locally similar sequences in repertoires. We find that the whole repertoire models correctly predict local similarity networks, suggesting a lack of forbidden T-cell receptor sequences. The local measure correlates well with distances calculated using whole repertoire traits and carries information about cell types.

Molecular correlates of vaccine-induced protection against typhoid fever

BACKGROUNDTyphoid fever is caused by the Gram-negative bacterium Salmonella enterica serovar Typhi and poses a substantial public health burden worldwide. Vaccines have been developed based on the surface Vi-capsular polysaccharide of S. Typhi; these include a plain-polysaccharide-based vaccine, ViPS, and a glycoconjugate vaccine, ViTT. To understand immune responses to these vaccines and their vaccine-induced immunological protection, molecular signatures were analyzed using bioinformatic approaches.METHODSBulk RNA-Seq data were generated from blood samples obtained from adult human volunteers enrolled in a vaccine trial, who were then challenged with S. Typhi in a controlled human infection model (CHIM). These data were used to conduct differential gene expression analyses, gene set and modular analyses, B cell repertoire analyses, and time-course analyses at various post-vaccination and post-challenge time points between participants receiving ViTT, ViPS, or a control meningococcal vaccine.RESULTSTranscriptomic responses revealed strong differential molecular signatures between the 2 typhoid vaccines, mostly driven by the upregulation in humoral immune signatures, including selective usage of immunoglobulin heavy chain variable region (IGHV) genes and more polarized clonal expansions. We describe several molecular correlates of protection against S. Typhi infection, including clusters of B cell receptor (BCR) clonotypes associated with protection, with known binders of Vi-polysaccharide among these.CONCLUSIONThe study reports a series of contemporary analyses that reveal the transcriptomic signatures after vaccination and infectious challenge, while identifying molecular correlates of protection that may inform future vaccine design and assessment.TRIAL REGISTRATIONClinicalTrials.gov NCT02324751.

Single-cell profiling in multiple myeloma: insights, problems, and promises

In a short time, single-cell platforms have become the norm in many fields of research, including multiple myeloma (MM). In fact, the large amount of cellular heterogeneity in MM makes single-cell platforms particularly attractive because bulk assessments can miss valuable information about cellular subpopulations and cell-to-cell interactions. The decreasing cost and increasing accessibility of single-cell platform, combined with breakthroughs in obtaining multiomics data for the same cell and innovative computational programs for analyzing data, have allowed single-cell studies to make important insights into MM pathogenesis; yet, there is still much to be done. In this review, we will first focus on the types of single-cell profiling and the considerations for designing a single-cell profiling experiment. Then, we will discuss what have learned from single-cell profiling about myeloma clonal evolution, transcriptional reprogramming, and drug resistance, and about the MM microenvironment during precursor and advanced disease.

Accurate profiling of full-length Fv in highly homologous antibody libraries using UMI tagged short reads

Deep parallel sequencing (NGS) is a viable tool for monitoring scFv and Fab library dynamics in many antibody engineering high-throughput screening efforts. Although very useful, the commonly used Illumina NGS platform cannot handle the entire sequence of scFv or Fab in a single read, usually focusing on specific CDRs or resorting to sequencing VH and VL variable domains separately, thus limiting its utility in comprehensive monitoring of selection dynamics. Here we present a simple and robust method for deep sequencing repertoires of full length scFv, Fab and Fv antibody sequences. This process utilizes standard molecular procedures and unique molecular identifiers (UMI) to pair separately sequenced VH and VL. We show that UMI assisted VH-VL matching allows for a comprehensive and highly accurate mapping of full length Fv clonal dynamics in large highly homologous antibody libraries, as well as identification of rare variants. In addition to its utility in synthetic antibody discovery processes, our method can be instrumental in generating large datasets for machine learning (ML) applications, which in the field of antibody engineering has been hampered by conspicuous paucity of large scale full length Fv data.

A Customizable Suite of Methods to Sequence and Annotate Cattle Antibodies

Studying the antibody response to infection or vaccination is essential for developing more effective vaccines and therapeutics. Advances in high-throughput antibody sequencing technologies and immunoinformatic tools now allow the fast and comprehensive analysis of antibody repertoires at high resolution in any species. Here, we detail a flexible and customizable suite of methods from flow cytometry, single cell sorting, heavy and light chain amplification to antibody sequencing in cattle. These methods were used successfully, including adaptation to the 10x Genomics platform, to isolate native heavy-light chain pairs. When combined with the Ig-Sequence Multi-Species Annotation Tool, this suite represents a powerful toolkit for studying the cattle antibody response with high resolution and precision. Using three workflows, we processed 84, 96, and 8313 cattle B cells from which we sequenced 24, 31, and 4756 antibody heavy-light chain pairs, respectively. Each method has strengths and limitations in terms of the throughput, timeline, specialist equipment, and cost that are each discussed. Moreover, the principles outlined here can be applied to study antibody responses in other mammalian species.

Genomics-driven prophylactic measures to increase streptococcosis resistance in tilapia

Streptococcosis caused by Streptococcus agalactiae and S. iniae is a significant problem that affects the success of tilapia aquaculture industries worldwide. In this critical review, we summarize the applicable practical strategies which may effectively enhance the world tilapia aquaculture development. Recently, the effect of vaccination and selective breeding programmes has been recognized as valuable tools to control the target disease and other consequent negative impacts caused by chemical and drug application. Advances in sequencing and molecular technologies are vital helpful factors with which to develop robust vaccines and increase the selective breeding programme's precision against streptococcosis. The genomic selection for streptococcosis-resistant tilapia strains and crucial genomic application for genomics' contribution to the development of novel Streptococcus vaccine, comparative genomics approach identifying vaccine candidates by reverse vaccinology, and next-generation vaccine design were described. Information from our review is encouraging for practical implementation of the development of vaccination and genomic selection in tilapia for streptococcosis resistance, which may be vital factors to sustain the world tilapia aquaculture industry effectively.

Cell activation-based screening of natively paired human T cell receptor repertoires

Adoptive immune therapies based on the transfer of antigen-specific T cells have been used successfully to treat various cancers and viral infections, but improved techniques are needed to identify optimally protective human T cell receptors (TCRs). Here we present a high-throughput approach to the identification of natively paired human TCRα and TCRβ (TCRα:β) genes encoding heterodimeric TCRs that recognize specific peptide antigens bound to major histocompatibility complex molecules (pMHCs). We first captured and cloned TCRα:β genes from individual cells, ensuring fidelity using a suppression PCR. We then screened TCRα:β libraries expressed in an immortalized cell line using peptide-pulsed antigen-presenting cells and sequenced activated clones to identify the cognate TCRs. Our results validated an experimental pipeline that allows large-scale repertoire datasets to be annotated with functional specificity information, facilitating the discovery of therapeutically relevant TCRs.

Understanding repertoire sequencing data through a multiscale computational model of the germinal center

Sequencing of B-cell and T-cell immune receptor repertoires helps us to understand the adaptive immune response, although it only provides information about the clonotypes (lineages) and their frequencies and not about, for example, their affinity or antigen (Ag) specificity. To further characterize the identified clones, usually with special attention to the particularly abundant ones (dominant), additional time-consuming or expensive experiments are generally required. Here, we present an extension of a multiscale model of the germinal center (GC) that we previously developed to gain more insight in B-cell repertoires. We compare the extent that these simulated repertoires deviate from experimental repertoires established from single GCs, blood, or tissue. Our simulations show that there is a limited correlation between clonal abundance and affinity and that there is large affinity variability among same-ancestor (same-clone) subclones. Our simulations suggest that low-abundance clones and subclones, might also be of interest since they may have high affinity for the Ag. We show that the fraction of plasma cells (PCs) with high B-cell receptor (BcR) mRNA content in the GC does not significantly affect the number of dominant clones derived from single GCs by sequencing BcR mRNAs. Results from these simulations guide data interpretation and the design of follow-up experiments.

Influenza vaccination-induced H3 stalk-reactive memory B-cell clone expansion

Current vaccine formulations elicit a recall immune response against viruses by targeting epitopes on the globular head of hemagglutinin (HA), and stalk-reactive antibodies are rarely found. However, stalk-specific memory B-cell expansion after influenza vaccination is poorly understood. In this study, B cells were isolated from individuals immunized with seasonal tetravalent influenza vaccines at days 0 and 28 for H7N9 stimulation in vitro. Plasma and supernatants were collected for the analysis of anti-HA IgG using ELISA and a Luminex assay. Memory B cells were positively enriched, and total RNA was extracted for B cell receptor (BCR) H-CDR3 sequencing. All subjects displayed increased anti-H3 antibody secretion after vaccination, whereas no increase in cH5/3-reactive IgG levels was detected. The number of shared memory B-cell clones among individuals dropped dramatically from 593 to 37. Four out of 5 subjects displayed enhanced frequencies of the VH3-23 and VH3-30 genes, and one exhibited an increase in the frequency of VH1-18, which are associated with the stalk of HA. An increase in H3 stalk-specific antibodies produced by B cells stimulated with H7N9 viruses was detected after vaccination. These results demonstrated that H3 stalk-specific memory B cells can expand and secrete antibodies that bind to the stalk in vitro, although no increase in serum H3 stalk-reactive antibodies was found after vaccination, indicating potential for developing a universal vaccine strategy.

Generation of a single-cell B cell atlas of antibody repertoires and transcriptomes to identify signatures associated with antigen specificity

Although new genomics-based pipelines have potential to augment antibody discovery, these methods remain in their infancy due to an incomplete understanding of the selection process that governs B cell clonal selection, expansion, and antigen specificity. Furthermore, it remains unknown how factors such as aging and reduction of tolerance influence B cell selection. Here we perform single-cell sequencing of antibody repertoires and transcriptomes of murine B cells following immunizations with a model therapeutic antigen target. We determine the relationship between antibody repertoires, gene expression signatures, and antigen specificity across 100,000 B cells. Recombinant expression and characterization of 227 monoclonal antibodies revealed the existence of clonally expanded and class-switched antigen-specific B cells that were more frequent in young mice. Although integrating multiple repertoire features such as germline gene usage and transcriptional signatures failed to distinguish antigen-specific from nonspecific B cells, other features such as immunoglobulin G (IgG) subtype and sequence composition correlated with antigen specificity.

Bioengineering of Antibody Fragments: Challenges and Opportunities

Antibody fragments are used in the clinic as important therapeutic proteins for treatment of indications where better tissue penetration and less immunogenic molecules are needed. Several expression platforms have been employed for the production of these recombinant proteins, from which E. coli and CHO cell-based systems have emerged as the most promising hosts for higher expression. Because antibody fragments such as Fabs and scFvs are smaller than traditional antibody structures and do not require specific patterns of glycosylation decoration for therapeutic efficacy, it is possible to express them in systems with reduced post-translational modification capacity and high expression yield, for example, in plant and insect cell-based systems. In this review, we describe different bioengineering technologies along with their opportunities and difficulties to manufacture antibody fragments with consideration of stability, efficacy and safety for humans. There is still potential for a new production technology with a view of being simple, fast and cost-effective while maintaining the stability and efficacy of biotherapeutic fragments.

RNA cytometry of single-cells using semi-permeable microcapsules

Analytical tools for gene expression profiling of individual cells are critical for studying complex biological systems. However, the techniques enabling rapid measurements of gene expression on thousands of single-cells are lacking. Here, we report a high-throughput RNA cytometry for digital profiling of single-cells isolated in liquid droplets enveloped by a thin semi-permeable membrane (microcapsules). Due to the selective permeability of the membrane, the desirable enzymes and reagents can be loaded, or replaced, in the microcapsule at any given step by simply changing the reaction buffer in which the microcapsules are dispersed. Therefore, complex molecular biology workflows can be readily adapted to conduct nucleic acid analysis on encapsulated mammalian cells, or other biological species. The microcapsules support sequential multi-step enzymatic reactions and remain intact under different biochemical conditions, freezing, thawing, and thermocycling. Combining microcapsules with conventional FACS provides a high-throughput approach for conducting RNA cytometry of individual cells based on their digital gene expression signature.

Bioinformatic Analysis of Natively Paired VH:VL Antibody Repertoires for Antibody Discovery

Next-generation DNA sequencing (NGS) of human antibody repertoires has been extensively implemented to discover novel antibody drugs, to analyze B-cell developmental features, and to investigate antibody responses to infectious diseases and vaccination. Because the antibody repertoire encoded by human B cells is highly diverse, NGS analyses of antibody genes have provided a new window into understanding antibody responses for basic immunology, biopharmaceutical drug discovery, and immunotherapy. However, many antibody discovery protocols analyze the heavy and light chains separately due to the short-read nature of most NGS technologies, whereas paired heavy and light chain data are required for complete antibody characterization. Here, we describe a computational workflow to process millions of paired antibody heavy and light chain DNA sequence reads using the Illumina MiSeq 2x300 NGS platform. In this workflow, we describe raw NGS read processing and initial quality filtering, the annotation and assembly of antibody clonotypes relating to paired heavy and light chain antibody lineages, and the generation of complete heavy+light consensus sequences for the downstream cloning and expression of human antibody proteins.

Applications of High-Throughput DNA Sequencing to Single-Domain Antibody Discovery and Engineering

Next-generation DNA sequencing (NGS) technologies have made it possible to interrogate antibody repertoires to unprecedented depths, typically via sequencing of cDNAs encoding immunoglobulin variable domains. In the absence of heavy-light chain pairing, the variable domains of heavy chain-only antibodies (HCAbs), referred to as single-domain antibodies (sdAbs), are uniquely amenable to NGS analyses. In this chapter, we provide simple and rapid protocols for producing and sequencing multiplexed immunoglobulin variable domain (VHH, VH, or VL) amplicons derived from a variety of sources using the Illumina MiSeq platform. Generation of such amplicon libraries is relatively inexpensive, requiring no specialized equipment and only a limited set of PCR primers. We also present several applications of NGS to sdAb discovery and engineering, including: (1) evaluation of phage-displayed sdAb library sequence diversity and monitoring of panning experiments; (2) identification of sdAbs of predetermined epitope specificity following competitive elution of phage-displayed sdAb libraries; (3) direct selection of B cells expressing antigen-specific, membrane-bound HCAb using antigen-coupled magnetic beads and identification of antigen-specific sdAbs, and (4) affinity maturation of lead sdAbs using tandem phage display selection and NGS. These methods can easily be adapted to other types of proteins and libraries and expand the utility of in vitro display technology.

Conformation specific antagonistic high affinity antibodies to the RON receptor kinase for imaging and therapy

The RON receptor tyrosine kinase is an exceptionally interesting target in oncology and immunology. It is not only overexpressed in a wide variety of tumors but also has been shown to be expressed on myeloid cells associated with tumor infiltration, where it serves to dampen tumour immune responses and reduce the efficacy of anti-CTLA4 therapy. Potent and selective inhibitory antibodies to RON might therefore both inhibit tumor cell growth and stimulate immune rejection of tumors. We derived cloned and sequenced a new panel of exceptionally avid anti-RON antibodies with picomolar binding affinities that inhibit MSP-induced RON signaling and show remarkable potency in antibody dependent cellular cytotoxicity. Antibody specificity was validated by cloning the antibody genes and creating recombinant antibodies and by the use of RON knock out cell lines. When radiolabeled with 89-Zirconium, the new antibodies 3F8 and 10G1 allow effective immuno-positron emission tomography (immunoPET) imaging of RON-expressing tumors and recognize universally exposed RON epitopes at the cell surface. The 10G1 was further developed into a novel bispecific T cell engager with a 15 pM EC50 in cytotoxic T cell killing assays.

Inference of B cell clonal families using heavy/light chain pairing information

Next generation sequencing of B cell receptor (BCR) repertoires has become a ubiquitous tool for understanding the antibody-mediated immune response: it is now common to have large volumes of sequence data coding for both the heavy and light chain subunits of the BCR. However, until the recent development of high throughput methods of preserving heavy/light chain pairing information, these samples contained no explicit information on which heavy chain sequence pairs with which light chain sequence. One of the first steps in analyzing such BCR repertoire samples is grouping sequences into clonally related families, where each stems from a single rearrangement event. Many methods of accomplishing this have been developed, however, none so far has taken full advantage of the newly-available pairing information. This information can dramatically improve clustering performance, especially for the light chain. The light chain has traditionally been challenging for clonal family inference because of its low diversity and consequent abundance of non-clonal families with indistinguishable naive rearrangements. Here we present a method of incorporating this pairing information into the clustering process in order to arrive at a more accurate partition of the data into clonally related families. We also demonstrate two methods of fixing imperfect pairing information, which may allow for simplified sample preparation and increased sequencing depth. Finally, we describe several other improvements to the partis software package.

Mutational patterns along different evolution paths of follicular lymphoma

Follicular lymphoma (FL) is an indolent disease, characterized by a median life expectancy of 18-20 years and by intermittent periods of relapse and remission. FL frequently transforms into the more aggressive diffuse large B cell lymphoma (t-FL). In previous studies, the analysis of immunoglobulin heavy chain variable region (IgHV) genes in sequential biopsies from the same patient revealed two different patterns of tumor clonal evolution: direct evolution, through acquisition of additional IgHV mutations over time, or divergent evolution, in which lymphoma clones from serial biopsies independently develop from a less-mutated common progenitor cell (CPC). Our goal in this study was to characterize the somatic hypermutation (SHM) patterns of IgHV genes in sequential FL samples from the same patients, and address the question of whether the mutation mechanisms (SHM targeting, DNA repair or both), or selection forces acting on the tumor clones, were different in FL samples compared to healthy control samples, or in late relapsed/transformed FL samples compared to earlier ones. Our analysis revealed differences in the distribution of mutations from each of the nucleotides when tumor and non-tumor clones were compared, while FL and transformed FL (t-FL) tumor clones displayed similar mutation distributions. Lineage tree measurements suggested that either initial clone affinity or selection thresholds were lower in FL samples compared to controls, but similar between FL and t-FL samples. Finally, we observed that both FL and t-FL tumor clones tend to accumulate larger numbers of potential N-glycosylation sites due to the introduction of new SHM. Taken together, these results suggest that transformation into t-FL, in contrast to initial FL development, is not associated with any major changes in DNA targeting or repair, or the selection threshold of the tumor clone.

Advances in antibody discovery from human BCR repertoires

Antibodies make up an important and growing class of compounds used for the diagnosis or treatment of disease. While traditional antibody discovery utilized immunization of animals to generate lead compounds, technological innovations have made it possible to search for antibodies targeting a given antigen within the repertoires of B cells in humans. Here we group these innovations into four broad categories: cell sorting allows the collection of cells enriched in specificity to one or more antigens; BCR sequencing can be performed on bulk mRNA, genomic DNA or on paired (heavy-light) mRNA; BCR repertoire analysis generally involves clustering BCRs into specificity groups or more in-depth modeling of antibody-antigen interactions, such as antibody-specific epitope predictions; validation of antibody-antigen interactions requires expression of antibodies, followed by antigen binding assays or epitope mapping. Together with innovations in Deep learning these technologies will contribute to the future discovery of diagnostic and therapeutic antibodies directly from humans.

Exploration of shared features of B cell receptor and T cell receptor repertoires reveals distinct clonotype clusters

Although B cells and T cells are integral players of the adaptive immune system and act in co-dependent ways to orchestrate immune responses, existing methods to study the immune repertoire have largely focused on separate analyses of B cell receptor (BCR) and T cell receptor (TCR) repertoires. Based on our hypothesis that the shared history of immune exposures and the shared cellular machinery for recombination result in similarities between BCR and TCR repertoires in an individual, we examine any commonalities and interrelationships between BCR and TCR repertoires. We find that the BCR and TCR repertoires have covarying clonal architecture and diversity, and that the pattern of correlations appears to be altered in immune-mediated diseases. Furthermore, hierarchical clustering of public B and T cell clonotypes in both health and disease based on correlation of clonal proportion revealed distinct clusters of B and T cell clonotypes that exhibit increased sequence similarity, share motifs, and have distinct amino acid characteristics. Our findings point to common principles governing memory formation, recombination, and clonal expansion to antigens in B and T cells within an individual. A significant proportion of public BCR and TCR repertoire can be clustered into nonoverlapping and correlated clusters, suggesting a novel way of grouping B and T cell clonotypes.

Peptide mimotopes to emulate carbohydrates

Glycoconjugates on animal cell surfaces are involved in numerous biological functions and diseases, especially the adhesion/metastasis of cancer cells, infection, and the onset of glycan-related diseases. In addition to glycoantigen detection, the regulation of glycan (carbohydrate)-protein interactions is needed to develop therapeutic strategies for glycan-related diseases. Preparation of a diverse range of glycan derivatives requires a massive effort, but the preparation and identification of alternative glycan-mimetic peptide mimotopes may provide a solution to this issue. Peptide mimotopes are recognized by glycan-binding proteins, such as lectins, enzymes, and antibodies, alternative to glycan ligands. Phage-display technology is the first choice in the selection of "glycan (carbohydrate)-mimetic peptide mimotopes" from a large repertoire of library sequences. This tutorial review describes the advantages of peptide mimotopes in comparison to glycan ligands, as well as their structural and functional mimicry. The detailed library design is followed by a description of the strategy used to improve affinity, and finally, an outline of the vaccine application of glycan-mimetic peptides is provided.

Mapping monoclonal anti-SARS-CoV-2 antibody repertoires against diverse coronavirus antigens

Variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have emerged continuously, challenging the effectiveness of vaccines, diagnostics, and treatments. Moreover, the possibility of the appearance of a new betacoronavirus with high transmissibility and high fatality is reason for concern. In this study, we used a natively paired yeast display technology, combined with next-generation sequencing (NGS) and massive bioinformatic analysis to perform a comprehensive study of subdomain specificity of natural human antibodies from two convalescent donors. Using this screening technology, we mapped the cross-reactive responses of antibodies generated by the two donors against SARS-CoV-2 variants and other betacoronaviruses. We tested the neutralization potency of a set of the cross-reactive antibodies generated in this study and observed that most of the antibodies produced by these patients were non-neutralizing. We performed a comparison of the specific and non-specific antibodies by somatic hypermutation in a repertoire-scale for the two individuals and observed that the degree of somatic hypermutation was unique for each patient. The data from this study provide functional insights into cross-reactive antibodies that can assist in the development of strategies against emerging SARS-CoV-2 variants and divergent betacoronaviruses.

Profiling the peripheral blood T cell receptor repertoires of gastric cancer patients

Cancer driven by somatic mutations may express neoantigens that can trigger T-cell immune responses. Since T-cell receptor (TCR) repertoires play critical roles in anti-tumor immune responses for oncology, next-generation sequencing (NGS) was used to profile the hypervariable complementarity-determining region 3 (CDR3) of the TCR-beta chain in peripheral blood samples from 68 gastric cancer patients and 49 healthy controls. We found that most hyper-expanded CDR3 are individual-specific, and the gene usage of TRBV3-1 is more frequent in the tumor group regardless of tumor stage than in the healthy control group. We identified 374 hyper-expanded tumor-specific CDR3, which may play a vital role in anti-tumor immune responses. The patients with stage IV gastric cancer have higher EBV-specific CDR3 abundance than the control. In conclusion, analysis of the peripheral blood TCR repertoires may provide the biomarker for gastric cancer prognosis and guide future immunotherapy.

Suspendable Hydrogel Nanovials for Massively Parallel Single-Cell Functional Analysis and Sorting

Techniques to analyze and sort single cells based on functional outputs, such as secreted products, have the potential to transform our understanding of cellular biology as well as accelerate the development of next-generation cell and antibody therapies. However, secreted molecules rapidly diffuse away from cells, and analysis of these products requires specialized equipment and expertise to compartmentalize individual cells and capture their secretions. Herein, we describe methods to fabricate hydrogel-based chemically functionalized microcontainers, which we call nanovials, and demonstrate their use for sorting single viable cells based on their secreted products at high-throughput using only commonly accessible laboratory infrastructure. These nanovials act as solid supports that facilitate attachment of a variety of adherent and suspension cell types, partition uniform aqueous compartments, and capture secreted proteins. Solutions can be exchanged around nanovials to perform fluorescence immunoassays on secreted proteins. Using this platform and commercial flow sorters, we demonstrate high-throughput screening of stably and transiently transfected producer cells based on relative IgG production. Chinese hamster ovary cells sorted based on IgG production regrew and maintained a high secretion phenotype over at least a week, yielding >40% increase in bulk IgG production rates. We also sorted hybridomas and B lymphocytes based on antigen-specific antibody production. Hybridoma cells secreting an antihen egg lysozyme antibody were recovered from background cells, enriching a population of ∼4% prevalence to >90% following sorting. Leveraging the high-speed sorting capabilities of standard sorters, we sorted >1 million events in <1 h. IgG secreting mouse B cells were also sorted and enriched based on antigen-specific binding. Successful sorting of antibody-secreting B cells combined with the ability to perform single-cell RT-PCR to recover sequence information suggests the potential to perform antibody discovery workflows. The reported nanovials can be easily stored and distributed among researchers, democratizing access to high-throughput functional cell screening.

"Nourish to Flourish": complementary feeding for a healthy infant gut microbiome-a non-randomised pilot feasibility study

Background

The introduction of complementary foods and changes in milk feeding result in modifications to gastrointestinal function. The interplay between indigestible carbohydrates, host physiology, and microbiome, and immune system development are areas of intense research relevant to early and later-life health.

Methods

This 6-month prospective non-randomised feasibility study was conducted in Auckland, New Zealand (NZ), in January 2018. Forty parents/caregivers and their infants were enrolled, with 30 infants allocated to receive a prebiotic NZ kūmara (flesh and skin; a type of sweet potato) prepared as a freeze-dried powder, and ten infants allocated to receive a commercially available probiotic control known to show relevant immune benefits (10⁹ CFU Bifidobacterium lactis BB-12®). The primary outcome was the study feasibility measures which are reported here.

Results

Recruitment, participant retention, and data collection met feasibility targets. Some limitations to biological sample collection were encountered, with difficulties in obtaining sufficient plasma sample volumes for the proposed immune parameter analyses. Acceptability of the kūmara powder was met with no reported adverse events.

Conclusion

This study indicates that recruiting infants before introducing complementary foods is feasible, with acceptable adherence to the food-based intervention. These results will inform the protocol of a full-scale randomised controlled trial (RCT) with adjustments to the collection of biological samples to examine the effect of a prebiotic food on the prevalence of respiratory tract infections during infancy.

Trial registration

Australia New Zealand Clinical Trials Registry ACTRN12618000157279. Prospectively registered on 02/01/2018.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40814-022-01059-3.

High-Throughput B Cell Epitope Determination by Next-Generation Sequencing

Development of novel technologies for the discovery of human monoclonal antibodies has proven invaluable in the fight against infectious diseases. Among the diverse antibody repertoires elicited by infection or vaccination, often only rare antibodies targeting specific epitopes of interest are of potential therapeutic value. Current antibody discovery efforts are capable of identifying B cells specific for a given antigen; however, epitope specificity information is usually only obtained after subsequent monoclonal antibody production and characterization. Here we describe LIBRA-seq with epitope mapping, a next-generation sequencing technology that enables residue-level epitope determination for thousands of single B cells simultaneously. By utilizing an antigen panel of point mutants within the HIV-1 Env glycoprotein, we identified and confirmed antibodies targeting multiple sites of vulnerability on Env, including the CD4-binding site and the V3-glycan site. LIBRA-seq with epitope mapping is an efficient tool for high-throughput identification of antibodies against epitopes of interest on a given antigen target.

Characterization of human IgM and IgG repertoires in individuals with chronic HIV-1 infection

Advancements in high-throughput sequencing (HTS) of antibody repertoires (Ig-Seq) have unprecedentedly improved our ability to characterize the antibody repertoires on a large scale. However, currently, only a few studies explored the influence of chronic HIV-1 infection on human antibody repertoires and many of them reached contradictory conclusions, possibly limited by inadequate sequencing depth and throughput. To better understand how HIV-1 infection would impact humoral immune system, in this study, we systematically analyzed the differences between the IgM (HIV-IgM) and IgG (HIV-IgG) heavy chain repertoires of HIV-1 infected patients, as well as between antibody repertoires of HIV-1 patients and healthy donors (HH). Notably, the public unique clones accounted for only a negligible proportion between the HIV-IgM and HIV-IgG repertoires libraries, and the diversity of unique clones in HIV-IgG remarkably reduced. In aspect of somatic mutation rates of CDR1 and CDR2, the HIV-IgG repertoire was higher than HIV-IgM. Besides, the average length of CDR3 region in HIV-IgM was significant longer than that in the HH repertoire, presumably caused by the great number of novel VDJ rearrangement patterns, especially a massive use of IGHJ6. Moreover, some of the B cell clonotypes had numerous clones, and somatic variants were detected within the clonotype lineage in HIV-IgG, indicating HIV-1 neutralizing activities. The in-depth characterization of HIV-IgG and HIV-IgM repertoires enriches our knowledge in the profound effect of HIV-1 infection on human antibody repertoires and may have practical value for the discovery of therapeutic antibodies.

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Ultra-deep sequencing of both IgM and IgG repertoires in chronic HIV-1 infection.

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VDJ gene rearrangement patterns can be dramatically changed by HIV-1 infection.

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Multiple mechanisms cause the high complexity of HIV-1-experienced antibodies.

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Discovery of promising neutralizing HIV-1 antibodies from antibody repertoires.

Immortalization and functional screening of natively paired human T cell receptor repertoires

Functional analyses of the T cell receptor (TCR) landscape can reveal critical information about protection from disease and molecular responses to vaccines. However, it has proven difficult to combine advanced next-generation sequencing technologies with methods to decode the peptide-major histocompatibility complex (pMHC) specificity of individual TCRs. We developed a new high-throughput approach to enable repertoire-scale functional evaluations of natively paired TCRs. In particular, we leveraged the immortalized nature of physically linked TCRα:β amplicon libraries to analyze binding against multiple recombinant pMHCs on a repertoire scale, and to exemplify the utility of this approach, we also performed affinity-based functional mapping in conjunction with quantitative next-generation sequencing to track antigen-specific TCRs. These data successfully validated a new immortalization and screening platform to facilitate detailed molecular analyses of disease-relevant antigen interactions with human TCRs.

Microfluidic Compartmentalization Platforms for Single Cell Analysis

Many cellular analytical technologies measure only the average response from a cell population with an assumption that a clonal population is homogenous. The ensemble measurement often masks the difference among individual cells that can lead to misinterpretation. The advent of microfluidic technology has revolutionized single-cell analysis through precise manipulation of liquid and compartmentalizing single cells in small volumes (pico- to nano-liter). Due to its advantages from miniaturization, microfluidic systems offer an array of capabilities to study genomics, transcriptomics, and proteomics of a large number of individual cells. In this regard, microfluidic systems have emerged as a powerful technology to uncover cellular heterogeneity and expand the depth and breadth of single-cell analysis. This review will focus on recent developments of three microfluidic compartmentalization platforms (microvalve, microwell, and microdroplets) that target single-cell analysis spanning from proteomics to genomics. We also compare and contrast these three microfluidic platforms and discuss their respective advantages and disadvantages in single-cell analysis.

Reconstruction of full antibody sequences in NGS datasets and accurate VL:VH coupling by cluster coordinate matching of non-overlapping reads

Next-generation sequencing (NGS) is an indispensable tool in antibody discovery projects. However, the limits on NGS read length make it difficult to reconstruct full antibody sequences from the sequencing runs, especially if the six CDRs are randomized. To overcome that, we took advantage of Illumina’s cluster mapping capabilities to pair non-overlapping reads and reconstruct full Fab sequences with accurate V_L:V_H pairings. The method relies on in silico cluster coordinate information, and not on extensive in vitro manipulation, making the protocol easily deployable and less prone to PCR-derived errors. This work maintains the throughput necessary for antibody discovery campaigns, and a high degree of fidelity, which potentiates not only phage-display and synthetic library-based discovery methods, but also the NGS-driven analysis of naïve and immune libraries.

Heavy chain sequence-based classifier for the specificity of human antibodies

Antibodies specifically bind to antigens and are an essential part of the immune system. Hence, antibodies are powerful tools in research and diagnostics. High-throughput sequencing technologies have promoted comprehensive profiling of the immune repertoire, which has resulted in large amounts of antibody sequences that remain to be further analyzed. In this study, antibodies were downloaded from IMGT/LIGM-DB and Sequence Read Archive databases. Contributing features from antibody heavy chains were formulated as numerical inputs and fed into an ensemble machine learning classifier to classify the antigen specificity of six classes of antibodies, namely anti-HIV-1, anti-influenza virus, anti-pneumococcal polysaccharide, anti-citrullinated protein, anti-tetanus toxoid and anti-hepatitis B virus. The classifier was validated using cross-validation and a testing dataset. The ensemble classifier achieved a macro-average area under the receiver operating characteristic curve (AUC) of 0.9246 from the 10-fold cross-validation, and 0.9264 for the testing dataset. Among the contributing features, the contribution of the complementarity-determining regions was 53.1% and that of framework regions was 46.9%, and the amino acid mutation rates occupied the first and second ranks among the top five contributing features. The classifier and insights provided in this study could promote the mechanistic study, isolation and utilization of potential therapeutic antibodies.