INDI-integrated nanobody database for immunoinformatics.

Nanobodies, a subclass of antibodies found in camelids, are versatile molecular binding scaffolds composed of a single polypeptide chain. The small size of nanobodies bestows multiple therapeutic advantages (stability, tumor penetration) with the first therapeutic approval in 2018 cementing the clinical viability of this format. Structured data and sequence information of nanobodies will enable the accelerated clinical development of nanobody-based therapeutics. Though the nanobody sequence and structure data are deposited in the public domain at an accelerating pace, the heterogeneity of sources and lack of standardization hampers reliable harvesting of nanobody information. We address this issue by creating the Integrated Database of Nanobodies for Immunoinformatics (INDI, http://naturalantibody.com/nanobodies). INDI collates nanobodies from all the major public outlets of biological sequences: patents, GenBank, next-generation sequencing repositories, structures and scientific publications. We equip INDI with powerful nanobody-specific sequence and text search facilitating access to >11 million nanobody sequences. INDI should facilitate development of novel nanobody-specific computational protocols helping to deliver on the therapeutic promise of this drug format.

IMGT® databases, related tools and web resources through three main axes of research and development.

IMGT®, the international ImMunoGeneTics information system®, http://www.imgt.org/, is at the forefront of the immunogenetics and immunoinformatics fields with more than 30 years of experience. IMGT® makes available databases and tools to the scientific community pertaining to the adaptive immune response, based on the IMGT-ONTOLOGY. We focus on the recent features of the IMGT® databases, tools, reference directories and web resources, within the three main axes of IMGT® research and development. Axis I consists in understanding the adaptive immune response, by deciphering the identification and characterization of the immunoglobulin (IG) and T cell receptor (TR) genes in jawed vertebrates. It is the starting point of the two other axes, namely the analysis and exploration of the expressed IG and TR repertoires based on comparison with IMGT reference directories in normal and pathological situations (Axis II) and the analysis of amino acid changes and functions of 2D and 3D structures of antibody and TR engineering (Axis III).

Using the antibody-antigen binding interface to train image-based deep neural networks for antibody-epitope classification.

High-throughput B-cell sequencing has opened up new avenues for investigating complex mechanisms underlying our adaptive immune response. These technological advances drive data generation and the need to mine and analyze the information contained in these large datasets, in particular the identification of therapeutic antibodies (Abs) or those associated with disease exposure and protection. Here, we describe our efforts to use artificial intelligence (AI)-based image-analyses for prospective classification of Abs based solely on sequence information. We hypothesized that Abs recognizing the same part of an antigen share a limited set of features at the binding interface, and that the binding site regions of these Abs share share common structure and physicochemical property patterns that can serve as a "fingerprint" to recognize uncharacterized Abs. We combined large-scale sequence-based protein-structure predictions to generate ensembles of 3-D Ab models, reduced the Ab binding interface to a 2-D image (fingerprint), used pre-trained convolutional neural networks to extract features, and trained deep neural networks (DNNs) to classify Abs. We evaluated this approach using Ab sequences derived from human HIV and Ebola viral infections to differentiate between two Abs, Abs belonging to specific B-cell family lineages, and Abs with different epitope preferences. In addition, we explored a different type of DNN method to detect one class of Abs from a larger pool of Abs. Testing on Ab sets that had been kept aside during model training, we achieved average prediction accuracies ranging from 71-96% depending on the complexity of the classification task. The high level of accuracies reached during these classification tests suggests that the DNN models were able to learn a series of structural patterns shared by Abs belonging to the same class. The developed methodology provides a means to apply AI-based image recognition techniques to analyze high-throughput B-cell sequencing datasets (repertoires) for Ab classification.

Exploiting antibody biology for the treatment of cancer.

Over the last decade, antibodies have become an important component in the arsenal of cancer therapeutics. High-specificity, low off-target effects, desirable pharmacokinetics and high success rate are a few of the many attributes that make antibodies amenable for development as drugs. To design antibodies for successful clinical applications, however, it is critical to have an understanding of their structure, functions, mechanisms of action and pharmacokinetic/pharmacodynamic properties. This review highlights some of these key aspects, as well as certain limitations encountered, with monoclonal antibody therapy. Further, we discuss rational combination therapies for clinical applications, some of which could help overcome the limitations.

Discovery of receptor-ligand interfaces in the immunoglobulin superfamily.

Cell-surface-anchored immunoglobulin superfamily (IgSF) proteins are widespread throughout the human proteome, forming crucial components of diverse biological processes including immunity, cell-cell adhesion, and carcinogenesis. IgSF proteins generally function through protein-protein interactions carried out between extracellular, membrane-bound proteins on adjacent cells, known as trans-binding interfaces. These protein-protein interactions constitute a class of pharmaceutical targets important in the treatment of autoimmune diseases, chronic infections, and cancer. A molecular-level understanding of IgSF protein-protein interactions would greatly benefit further drug development. A critical step toward this goal is the reliable identification of IgSF trans-binding interfaces. We propose a novel combination of structure and sequence information to identify trans-binding interfaces in IgSF proteins. We developed a structure-based binding interface prediction approach that can identify broad regions of the protein surface that encompass the binding interfaces and suggests that IgSF proteins possess binding supersites. These interfaces could theoretically be pinpointed using sequence-based conservation analysis, with performance approaching the theoretical upper limit of binding interface prediction accuracy, but achieving this in practice is limited by the current ability to identify an appropriate multiple sequence alignment for conservation analysis. However, an important contribution of combining the two orthogonal methods is that agreement between these approaches can estimate the reliability of the predictions. This approach was benchmarked on the set of 22 IgSF proteins with experimentally solved structures in complex with their ligands. Additionally, we provide structure-based predictions and reliability scores for the 62 IgSF proteins with known structure but yet uncharacterized binding interfaces.

A Few Key Historical Events in the Antibody Field: The Alacritous Antibody.

We have coined the term "alacrity" to describe the extraordinary diversity of B cell activation potentials, even among cells in a single B cell clone responding to a single antigen. The discovery of methodologies for B cell culture in limiting dilution allowed scientists to identify the source of cellular heterogeneity among cells of the immune system. Analyses of individual B cells set the stage for more detailed descriptions of the factors that diversify B cell functions, some of which will be expanded upon by partner articles in this B cell issue.

Advancing computational biology and bioinformatics research through open innovation competitions.

Open data science and algorithm development competitions offer a unique avenue for rapid discovery of better computational strategies. We highlight three examples in computational biology and bioinformatics research in which the use of competitions has yielded significant performance gains over established algorithms. These include algorithms for antibody clustering, imputing gene expression data, and querying the Connectivity Map (CMap). Performance gains are evaluated quantitatively using realistic, albeit sanitized, data sets. The solutions produced through these competitions are then examined with respect to their utility and the prospects for implementation in the field. We present the decision process and competition design considerations that lead to these successful outcomes as a model for researchers who want to use competitions and non-domain crowds as collaborators to further their research.

[Analysis of irregular antibody screening and antibody identification results in 31 858 cases of inpatients].

Objective To explore clinical significance of transfusion safety by analyzing the results of screening the irregular antibodies and antibody identification. Methods The micro-column gel test cards were used to screen and identify irregular antibodies of 31 858 inpatients. Results Among the 31 858 cases, 31 517 (98.92%) had positive results in RhD detection, and 341 (1.08%) had negative results in RhD detection. The number of patients who had positive results in screening the irregular antibodies was 92 cases and the positive rate was 0.3%. The highest detected rate of positive results in screening the irregular antibodies was obtained in the patients with hematologic diseases at a rate of 2.21% (11/497), closely followed by the pregnant women at a rate of 0.72% (31/4313). The 92 cases had positive results in antibody identification, including 45 cases of anti-E (48.91%), 11 cases of anti-D (11.96%), 10 cases of anti-c (10.87%), 6 cases of anti-Lea (6.52%), 5 cases of anti-Ec (5.44%), 5 cases of anti-M (5.44%), and 10 cases of other antibodies. Conclusion Screening the irregular antibodies and antibody identification before blood transfusion can effectively avoid the adverse reactions of blood transfusion and improve the quality of blood transfusion.

Antibodies: The major participants in maternal-fetal interaction.

The aim of this study is to improve our understanding of the mechanisms involved in maternal-fetal immune tolerance. We searched the related literatures and overviewed the major antibodies associated with pregnancy and described in details their possible roles in mediating maternal-fetal interactions. Antibodies classified into different types based on their functional or structural characteristics were summarized, including immunoglobulin G, blocking antibody, nonprecipitating asymmetric antibody, antiphospholipid antibody, antitrophoblast antibody and antipaternal antibody. The presence and levels of various circulating antibodies in pregnancy may play a crucial role in the occurrence, development and termination of pregnancy.

Antibodies against recombinant alpha-galactosidase A in Fabry disease: Subclass analysis and impact on response to treatment.

BACKGROUND: Treatment of Fabry disease (FD) with recombinant alpha-galactosidase A (r-αGAL A) is complicated by the formation of anti-drug antibodies in the majority of male patients with the classical disease phenotype. Detailed information regarding antibody subtypes, onset and persistence of antibody development and their effect on treatment efficacy is sparse. METHODS: A retrospective study was carried out in 39 male patients with classical FD, treated with either agalsidase-alfa or agalsidase-beta (mean follow up of 10 years). With six to twelve months intervals plasma-induced in vitro inhibition of enzyme activity, lysoglobotriaosylsphingosine (lysoGb3) levels and renal function were assessed. In a subset of 12 patients, additionally anti- r-αGAL A IgM, IgA and IgG1, 2, 3 and 4 levels were analyzed. RESULTS: In 23 out of 39 patients, plasma-induced in vitro inhibition of r-αGAL A activity was observed (inhibition-positive). The inhibition titer was strongly negatively correlated to the decrease in lysoGb3: agalsidase-alfa (FElog10(inhibition) = -10.3, P ≤.001), agalsidase-beta (FElog10(inhibition) = -4.7, P ≤.001). Inhibition-positive patients had an accelerated decline in renal function (FE = 1.21, p = .042). During treatment IgG1 anti-r-αGAL A levels increased only in inhibition-positive patients (p = .0045). IgG4 anti-r-αGAL A antibodies developed in 7 out of 9 inhibition-positive patients. Other antibody subclasses were either not present or too low to quantify. CONCLUSION: Development of inhibiting antibodies against r-αGAL A negatively affects the biochemical response to ERT and resulted in an accelerated decline in renal function. The presence of IgG1 and IgG4 anti-r-αGAL A antibodies is associated with in vitro αGAL A activity inhibition.

MAP1A/BLC3? Now I am really confused.

I routinely see people use incorrect names for MAP1LC3/LC3 isoforms in scientific papers. In fact, it happens often enough that I decided to investigate the reason for the apparent confusion. It turns out that the sources of misinformation are abundant, including UniProt and antibody supplier web sites.

Novel Approaches to Analyze Immunoglobulin Repertoires.

Analysis of immunoglobulin (Ig) repertoires aims to comprehend Ig diversity with the goal of predicting humoral immune responses in the context of infection, vaccination, autoimmunity, and malignancies. The first next-generation sequencing (NGS) analyses of bulk B cell populations dramatically advanced sampling depth over previous low-throughput single-cell-based protocols, albeit at the expense of accuracy and loss of chain-pairing information. In recent years the field has substantially differentiated, with bulk analyses becoming more accurate while single-cell approaches have gained in throughput. Additionally, new platforms striving to combine high throughput and chain pairing have been developed as well as various computational tools for analysis. Here we review the developments of the past 4-5 years and discuss the open challenges.

The Individual and Population Genetics of Antibody Immunity.

Antibodies (Abs) produced by immunoglobulin (IG) genes are the most diverse proteins expressed in humans. While part of this diversity is generated by recombination during B-cell development and mutations during affinity maturation, the germ-line IG loci are also diverse across human populations and ethnicities. Recently, proof-of-concept studies have demonstrated genotype-phenotype correlations between specific IG germ-line variants and the quality of Ab responses during vaccination and disease. However, the functional consequences of IG genetic variation in Ab function and immunological outcomes remain underexplored. In this opinion article, we outline interconnections between IG genomic diversity and Ab-expressed repertoires and structure. We further propose a strategy for integrating IG genotyping with functional Ab profiling data as a means to better predict and optimize humoral responses in genetically diverse human populations, with immediate implications for personalized medicine.

A Simple, Versatile Antibody-Based Barcoding Method for Flow Cytometry.

Barcoding of biological samples is a commonly used strategy to mark or identify individuals within a complex mixture. However, cell barcoding has not yet found wide use in flow cytometry that would benefit greatly from the ability to analyze pooled experimental samples simultaneously. This is due, in part, to technical and practical limitations of current fluorescent dye-based methods. In this study, we describe a simple, versatile barcoding strategy that relies on combinations of a single Ab conjugated to different fluorochromes and thus in principle can be integrated into any flow cytometry application. To demonstrate the efficacy of the approach, we describe the results of a variety of experiments using live cells as well as fixed and permeabilized cells. The results of these studies show that Ab-based barcoding provides a simple, practical method for identifying cells from individual samples pooled for analysis by flow cytometry that has broad applications in immunological research.

Multiple etiologies of equine recurrent uveitis--A natural model for human autoimmune uveitis: A brief review.

Equine recurrent uveitis (ERU) has various etiologies, with Leptospira infection and genetic predisposition being the leading risk factors. Regardless of etiology, expression of ocular proteins associated with maintenance of the blood-ocular barrier is impaired in ERU. The recurring-remitting cycle of ERU repeatedly disrupts the blood-ocular barrier, allowing the previously immune-privileged ocular environment to become the site of a progressive local autoimmune pathology that ultimately results in tissue destruction and vision loss. The immune-mediated process involves humoral and cellular mechanisms. Intraocular antibodies either produced in the eye or that leak through the blood-ocular barrier, are often present at higher levels than in serum and react with antigens in ocular tissue of horses with ERU. Ocular infiltration of auto-aggressive lymphocytes occurs with each uveitis episode and is the most crucial contributor to inflammation and eye damage. Recurring uveitis episodes may be initiated when epitopes of an ocular antigen become visible to the immune system (intramolecular spreading) or another autoantigen (intermolecular spreading), resulting in a new inflammatory reaction.

Immunophenotype of normal vs. myeloma plasma cells: Toward antibody panel specifications for MRD detection in multiple myeloma.

In recent years, several studies on large series of multiple myeloma (MM) patients have demonstrated the clinical utility of flow cytometry monitoring of minimal residual disease (flow-MRD) in bone marrow (BM), for improved assessment of response to therapy and prognostication. However, disturbing levels of variability exist regarding the specific protocols and antibody panels used in individual laboratories. Overall, consensus exists about the utility of combined assessment of CD38 and CD138 for the identification of BM plasma cells (PC); in contrast, more heterogeneous lists of markers are used to further distinguish between normal/reactive PCs and myeloma PCs in the MRD settings. Among the later markers, CD19, CD45, CD27, and CD81, together with CD56, CD117, CD200, and CD307, have emerged as particularly informative; however, no single marker provides enough specificity for clear discrimination between clonal PCs and normal PCs. Accordingly, multivariate analyses of single PCs from large series of normal/reactive vs. myeloma BM samples have shown that combined assessment of CD138 and CD38, together with CD45, CD19, CD56, CD27, CD81, and CD117 would be ideally suited for MRD monitoring in virtually every MM patient. However, the specific antibody clones, fluorochrome conjugates and sources of the individual markers determines its optimal (vs. suboptimal or poor) performance in an eight-color staining. Assessment of clonality, via additional cytoplasmic immunoglobulin (CyIg) κ vs. CyIgλ evaluation, may contribute to further establish the normal/reactive vs. clonal nature of small suspicious PC populations at high sensitivity levels, provided that enough cells are evaluated.

Discovering Molecules That Regulate Efferocytosis Using Primary Human Macrophages and High Content Imaging.

Defective clearance of apoptotic cells can result in sustained inflammation and subsequent autoimmunity. Macrophages, the "professional phagocyte" of the body, are responsible for efficient, non-phlogistic, apoptotic cell clearance. Controlling phagocytosis of apoptotic cells by macrophages is an attractive therapeutic opportunity to ameliorate inflammation. Using high content imaging, we have developed a system for evaluating the effects of antibody treatment on apoptotic cell uptake in primary human macrophages by comparing the Phagocytic Index (PI) for each antibody. Herein we demonstrate the feasibility of evaluating a panel of antibodies of unknown specificities obtained by immunization of mice with primary human macrophages and show that they can be distinguished based on individual PI measurements. In this study ~50% of antibodies obtained enhance phagocytosis of apoptotic cells while approximately 5% of the antibodies in the panel exhibit some inhibition. Though the specificities of the majority of antibodies are unknown, two of the antibodies that improved apoptotic cell uptake recognize recombinant MerTK; a receptor known to function in this capacity in vivo. The agonistic impact of these antibodies on efferocytosis could be demonstrated without addition of either of the MerTK ligands, Gas6 or ProS. These results validate applying the mechanism of this fundamental biological process as a means for identification of modulators that could potentially serve as therapeutics. This strategy for interrogating macrophages to discover molecules regulating apoptotic cell uptake is not limited by access to purified protein thereby increasing the possibility of finding novel apoptotic cell uptake pathways.

Significant Impact of Immunogen Design on the Diversity of Antibodies Generated by Carbohydrate-Based Anticancer Vaccine.

Development of an effective vaccine targeting tumor associated carbohydrate antigens (TACAs) is an appealing approach toward tumor immunotherapy. While much emphasis has been typically placed on generating high antibody titers against the immunizing antigen, the impact of immunogen design on the diversity of TACA-specific antibodies elicited has been overlooked. Herein, we report that the immunogen structure can significantly impact the breadth and the magnitude of humoral responses. Vaccine constructs that induced diverse TACA-binding antibodies provided much stronger recognition of a variety of Tn positive tumor cells. Optimization of the breadth of the antibody response led to a vaccine construct that demonstrated long lasting efficacy in a mouse tumor model. After challenged with the highly aggressive TA3Ha cells, mice immunized with the new construct exhibited a statistically significant improvement in survival relative to controls (0% vs 50% survival; p < 0.0001). Furthermore, the surviving mice developed long-term immunity against TA3Ha. Thus, both the magnitude and the breadth of antibody reactivity should be considered when designing TACA-based antitumor vaccines.

Sequencing the functional antibody repertoire--diagnostic and therapeutic discovery.

The development of high-throughput DNA sequencing technologies has enabled large-scale characterization of functional antibody repertoires, a new method of understanding protective and pathogenic immune responses. Important parameters to consider when sequencing antibody repertoires include the methodology, the B-cell population and clinical characteristics of the individuals analysed, and the bioinformatic analysis. Although focused sequencing of immunoglobulin heavy chains or complement determining regions can be utilized to monitor particular immune responses and B-cell malignancies, high-fidelity analysis of the full-length paired heavy and light chains expressed by individual B cells is critical for characterizing functional antibody repertoires. Bioinformatic identification of clonal antibody families and recombinant expression of representative members produces recombinant antibodies that can be used to identify the antigen targets of functional immune responses and to investigate the mechanisms of their protective or pathogenic functions. Integrated analysis of coexpressed functional genes provides the potential to further pinpoint the most important antibodies and clonal families generated during an immune response. Sequencing antibody repertoires is transforming our understanding of immune responses to autoimmunity, vaccination, infection and cancer. We anticipate that antibody repertoire sequencing will provide next-generation biomarkers, diagnostic tools and therapeutic antibodies for a spectrum of diseases, including rheumatic diseases.

Toward a more accurate view of human B-cell repertoire by next-generation sequencing, unbiased repertoire capture and single-molecule barcoding.

B-cell repertoire analysis using next-generation sequencing has become a valuable tool for interrogating the genetic record of humoral response to infection. However, key obstacles such as low throughput, short read length, high error rate, and undetermined bias of multiplex PCR method have hindered broader application of this technology. In this study, we report several technical advances in antibody repertoire sequencing. We first demonstrated the ability to sequence antibody variable domains using the Ion Torrent PGM platform. As a test case, we analyzed the PGT121 class of antibodies from IAVI donor 17, an HIV-1-infected individual. We then obtained "unbiased" antibody repertoires by sequencing the 5'-RACE PCR products of B-cell transcripts from IAVI donor 17 and two HIV-1-uninfected individuals. We also quantified the bias of previously published gene-specific primers by comparing the repertoires generated by 5'-RACE PCR and multiplex PCR. We further developed a single-molecule barcoding strategy to reduce PCR-based amplification noise. Lastly, we evaluated several new PGM technologies in the context of antibody sequencing. We expect that, based upon long-read and high-fidelity next-generation sequencing technologies, the unbiased analysis will provide a more accurate view of the overall antibody repertoire while the barcoding strategy will facilitate high-resolution analysis of individual antibody families.