Current approaches to fine mapping of antigen-antibody interactions

Solving technical issues in flow cytometry to characterize porcine CD8α/β expressing lymphocytes

The CD8 molecule is a cell surface receptor and well described as co-receptor on T cells, binding directly to the major histocompatibility complex class I on antigen presenting cells. CD8 antigens are comprised of two distinct polypeptide chains, the α and the β chain. In the pig, the CD8 receptor is expressed by several lymphocyte subsets, including Natural Killer cells, γδ T cells and antigen experienced CD4+ αβ T cells. On these cell populations CD8 is expressed as αα homodimers. Porcine cytolytic T cells on the other hand exclusively express CD8 αβ heterodimers. Several monoclonal antibodies (mAbs) for either of the two chains are available and are frequently used in flow cytometry. We observed that distinct combinations of mAb clones for CD8α and CD8β chains can cause troubles in multi-color staining panels. Therefore, we aimed for an in-depth study of the usage of different CD8-specific mAb clones and optimizing co-staining strategies for flow cytometry. We tested mAb clones 11/295/33 and 76-2-11 for the detection of CD8α and mAb clones PPT23 and PG164A for the detection of CD8β. The results indicate that the CD8α clone 11/295/33 should not be used together with either of the two CD8β clones in the same incubation step, as co-staining led to a highly reduced ability of CD8β mAb binding and loss in signal in flow cytometry. This can lead to potential false results in detecting CD8αβ cytolytic T cells. In case of the CD8α mAb clone 76-2-11, no inhibition in binding of either CD8β mAb clones was observed, making it the preferred choice in multi-color staining panels. The obtained data will help in future panel designs for flow cytometry in the pig and therefore improving studies of porcine immune cells.

ParaAntiProt provides paratope prediction using antibody and protein language models

Efficiently predicting the paratope holds immense potential for enhancing antibody design, treating cancers and other serious diseases, and advancing personalized medicine. Although traditional methods are highly accurate, they are often time-consuming, labor-intensive, and reliant on 3D structures, restricting their broader use. On the other hand, machine learning-based methods, besides relying on structural data, entail descriptor computation, consideration of diverse physicochemical properties, and feature engineering. Here, we develop a deep learning-assisted prediction method for paratope identification, relying solely on amino acid sequences and being antigen-agnostic. Built on the ProtTrans architecture, and utilizing pre-trained protein and antibody language models, we extract efficient embeddings for predicting paratope. By incorporating positional encoding for Complementarity Determining Regions, our model gains a deeper structural understanding, achieving remarkable performance with a 0.904 ROC AUC, 0.701 F1-score, and 0.585 MCC on benchmark datasets. In addition to yielding accurate antibody paratope predictions, our method exhibits strong performance in predicting nanobody paratope, achieving a ROC AUC of 0.912 and a PR AUC of 0.665 on the nanobody dataset. Notably, our approach outperforms structure-based prediction methods, boasting a PR AUC of 0.731. Various conducted ablation studies, which elaborate on the impact of each part of the model on the prediction task, show that the improvement in prediction performance by applying CDR positional encoding together with CNNs depends on the specific protein and antibody language models used. These results highlight the potential of our method to advance disease understanding and aid in the discovery of new diagnostics and antibody therapies.

Mapping conformational changes on bispecific antigen-binding biotherapeutic by covalent labeling and mass spectrometry

Biotherapeutic's higher order structure (HOS) is a critical determinant of its functional properties and conformational relevance. Here, we evaluated two covalent labeling methods: diethylpyrocarbonate (DEPC)-labeling and fast photooxidation of proteins (FPOP), in conjunction with mass spectrometry (MS), to investigate structural modifications for the new class of immuno-oncological therapy known as bispecific antigen-binding biotherapeutics (BABB). The evaluated techniques unveiled subtle structural changes occurring at the amino acid residue level within the antigen-binding domain under both native and thermal stress conditions, which cannot be detected by conventional biophysical techniques, e.g., near-ultraviolet circular dichroism (NUV-CD). The determined variations in labeling uptake under native and stress conditions, corroborated by binding assays, shed light on the binding effect, and highlighted the potential of covalent-labeling methods to effectively monitor conformational changes that ultimately influence the product quality. Our study provides a foundation for implementing the developed techniques in elucidating the inherent structural characteristics of novel therapeutics and their conformational stability.

Single-Domain Antibodies-Novel Tools to Study and Treat Allergies

IgE-mediated allergies represent a major health problem in the modern world. Apart from allergen-specific immunotherapy (AIT), the only disease-modifying treatment, researchers focus on biologics that target different key molecules such as allergens, IgE, or type 2 cytokines to ameliorate allergic symptoms. Single-domain antibodies, or nanobodies, are the newcomers in biotherapeutics, and their huge potential is being investigated in various research fields since their discovery 30 years ago. While they are dominantly applied for theranostics of cancer and treatment of infectious diseases, nanobodies have become increasingly substantial in allergology over the last decade. In this review, we discuss the prerequisites that we consider to be important for generating useful nanobody-based drug candidates for treating allergies. We further summarize the available research data on nanobodies used as allergen monitoring and detection probes and for therapeutic approaches. We reflect on the limitations that have to be addressed during the development process, such as in vivo half-life and immunogenicity. Finally, we speculate about novel application formats for allergy treatment that might be available in the future.

Mammalian cell display with automated oligo design and library assembly allows for rapid residue level conformational epitope mapping

Precise epitope determination of therapeutic antibodies is of great value as it allows for further comprehension of mechanism of action, therapeutic responsiveness prediction, avoidance of unwanted cross reactivity, and vaccine design. The golden standard for discontinuous epitope determination is the laborious X-ray crystallography method. Here, we present a combinatorial method for rapid mapping of discontinuous epitopes by mammalian antigen display, eliminating the need for protein expression and purification. The method is facilitated by automated workflows and tailored software for antigen analysis and oligonucleotide design. These oligos are used in automated mutagenesis to generate an antigen receptor library displayed on mammalian cells for direct binding analysis by flow cytometry. Through automated analysis of 33930 primers an optimized single condition cloning reaction was defined allowing for mutation of all surface-exposed residues of the receptor binding domain of SARS-CoV-2. All variants were functionally expressed, and two reference binders validated the method. Furthermore, epitopes of three novel therapeutic antibodies were successfully determined followed by evaluation of binding also towards SARS-CoV-2 Omicron BA.2. We find the method to be highly relevant for rapid construction of antigen libraries and determination of antibody epitopes, especially for the development of therapeutic interventions against novel pathogens.

Binding of Natural Antibodies Generated after COVID-19 and Vaccination with Individual Peptides Corresponding to the SARS-CoV-2 S-Protein

The rapid development of vaccines is a crucial objective in modern biotechnology and molecular pharmacology. In this context, conducting research to expedite the selection of a potent immunogen is imperative. The candidate vaccine should induce the production of antibodies that can recognize the immunogenic epitopes of the target protein, resembling the ones found in recovered patients. One major challenge in vaccine development is the absence of straightforward and reliable techniques to determine the extent to which the spectrum of antibodies produced after vaccination corresponds to antibodies found after recovery. This paper describes a newly developed method to detect antibodies specific to immunogenic epitopes of the target protein in blood plasma and to compare them with antibody spectra generated post vaccination. Comparing the antibody pool generated in the human body after recovering from an infectious disease with the pool formed through vaccination can become a universal method for screening candidate vaccines. This method will enable the identification of candidate vaccines that can induce the production of antibodies similar to those generated in response to a natural infection. Implementing this approach will facilitate the rapid development of new vaccines, even when faced with a pandemic.

Prediction of linear B-cell epitopes based on protein sequence features and BERT embeddings

Linear B-cell epitopes (BCEs) play a key role in the development of peptide vaccines and immunodiagnostic reagents. Therefore, the accurate identification of linear BCEs is of great importance in the prevention of infectious diseases and the diagnosis of related diseases. The experimental methods used to identify BCEs are both expensive and time-consuming and they do not meet the demand for identification of large-scale protein sequence data. As a result, there is a need to develop an efficient and accurate computational method to rapidly identify linear BCE sequences. In this work, we developed the new linear BCE prediction method LBCE-BERT. This method is based on peptide chain sequence information and natural language model BERT embedding information, using an XGBoost classifier. The models were trained on three benchmark datasets. The model was training on three benchmark datasets for hyperparameter selection and was subsequently evaluated on several test datasets. The result indicate that our proposed method outperforms others in terms of AUROC and accuracy. The LBCE-BERT model is publicly available at: https://github.com/Lfang111/LBCE-BERT .

Determination of the epitopic peptides of fig mosaic virus and the single-chain variable fragment antibody by mass spectrometry

The study of antibody-antigen interactions, through epitope mapping, enhances our understanding of antibody neutralization and antigenic determinant recognition. Epitope mapping, employing monoclonal antibodies and mass spectrometry, has emerged as a rapid and precise method to investigate viral antigenic determinants. In this report, we propose an approach to improve the accuracy of epitopic peptide interaction rate recognition. To achieve this, we investigated the interaction between the nucleocapsid protein of fig mosaic virus (FMV-NP) and single-chain variable fragment antibodies (scFv-Ab). These scFv-Ab maintain high specificity similar to whole monoclonal antibodies, but they are smaller in size. We coupled this with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). The experimental design involved using two different enzymes to digest FMV-NP separately. The resulting peptides were then incubated separately with the desired scFv-Ab at different incubation times and antibody concentrations. This allowed us to monitor the relative rate of epitopic peptide interaction with the antibody. The results demonstrated that, at a 1:1 ratio and after 2 h of interaction, the residues 122-136, 148-157, and 265-276 exhibited high-rate epitopic peptide binding, with reductions in peak intensity of 78%, 21%, and 22%, respectively. Conversely, the residues 250-264 showed low-rate binding, with a 15% reduction in peak intensity. This epitope mapping approach, utilizing scFv-Ab, two different enzymes, and various incubation times, offers a precise and dependable analysis for monitoring and recognizing the binding kinetics of antigenic determinants. Furthermore, this method can be applied to study any kind of antigens.

Multi-perspectives and challenges in identifying B-cell epitopes

The identification of B-cell epitopes (BCEs) in antigens is a crucial step in developing recombinant vaccines or immunotherapies for various diseases. Over the past four decades, numerous in silico methods have been developed for predicting BCEs. However, existing reviews have only covered specific aspects, such as the progress in predicting conformational or linear BCEs. Therefore, in this paper, we have undertaken a systematic approach to provide a comprehensive review covering all aspects associated with the identification of BCEs. First, we have covered the experimental techniques developed over the years for identifying linear and conformational epitopes, including the limitations and challenges associated with these techniques. Second, we have briefly described the historical perspectives and resources that maintain experimentally validated information on BCEs. Third, we have extensively reviewed the computational methods developed for predicting conformational BCEs from the structure of the antigen, as well as the methods for predicting conformational epitopes from the sequence. Fourth, we have systematically reviewed the in silico methods developed in the last four decades for predicting linear or continuous BCEs. Finally, we have discussed the overall challenge of identifying continuous or conformational BCEs. In this review, we only listed major computational resources; a complete list with the URL is available from the BCinfo website (https://webs.iiitd.edu.in/raghava/bcinfo/).

Statistical Analysis and Tokenization of Epitopes to Construct Artificial Neoepitope Libraries

Epitopes are specific regions on an antigen's surface that the immune system recognizes. Epitopes are usually protein regions on foreign immune-stimulating entities such as viruses and bacteria, and in some cases, endogenous proteins may act as antigens. Identifying epitopes is crucial for accelerating the development of vaccines and immunotherapies. However, mapping epitopes in pathogen proteomes is challenging using conventional methods. Screening artificial neoepitope libraries against antibodies can overcome this issue. Here, we applied conventional sequence analysis and methods inspired in natural language processing to reveal specific sequence patterns in the linear epitopes deposited in the Immune Epitope Database (www.iedb.org) that can serve as building blocks for the design of universal epitope libraries. Our results reveal that amino acid frequency in annotated linear epitopes differs from that in the human proteome. Aromatic residues are overrepresented, while the presence of cysteines is practically null in epitopes. Byte pair encoding tokenization shows high frequencies of tryptophan in tokens of 5, 6, and 7 amino acids, corroborating the findings of the conventional sequence analysis. These results can be applied to reduce the diversity of linear epitope libraries by orders of magnitude.

Molecular insights into recognition of GUCY2C by T-cell engaging bispecific antibody anti-GUCY2CxCD3

The intestinal epithelial receptor Guanylyl Cyclase C (GUCY2C) is a tumor-associated cell surface antigen expressed across gastrointestinal malignancies that can serve as an efficacious target for colorectal cancer immunotherapy. Here, we describe a yeast surface-display approach combined with an orthogonal peptide-based mapping strategy to identify the GUCY2C binding epitope of a novel anti-GUCY2CxCD3 bispecific antibody (BsAb) that recently advanced into the clinic for the treatment of cancer. The target epitope was localized to the N-terminal helix H2 of human GUCY2C, which enabled the determination of the crystal structure of the minimal GUCY2C epitope in complex with the anti-GUCY2C antibody domain. To understand if this minimal epitope covers the entire antibody binding region and to investigate the impact of epitope position on the antibody's activity, we further determined the structure of this interaction in the context of the full-length extracellular domain (ECD) of GUCY2C. We found that this epitope is positioned on the protruding membrane-distal helical region of GUCY2C and that its specific location on the surface of GUCY2C dictates the close spatial proximity of the two antigen arms in a diabody arrangement essential to the tumor killing activity of GUCY2CxCD3 BsAb.

Bioinformatics and Structural Analysis of Antigenic Variation in the Hemagglutinin Gene of the Influenza A(H1N1)pdm09 Virus Circulating in Shiraz (2013 to 2015)

Circulating influenza A virus provided an excellent opportunity to study the adaptation of the influenza A(H1N1)pdm09 virus to the human host. Particularly, due to the availability of sequences taken from isolates, we could monitor amino acid changes and the stability of mutations that occurred in hemagglutinin (HA). HA is crucial to viral infection because it binds to ciliated cell receptors and mediates the fusion of cells and viral membranes; because antibodies that bind to HA may block virus entry to the cell, this protein is subjected to high selective pressure. In this study, the locations of mutations in the structures of mutant HA were analyzed and the three-dimensional (3D) structures of these mutations were modeled in I-TASSER. Also, the location of these mutations was visualized and studied using Swiss PDB Viewer software and the PyMOL Molecular Graphics System. The crystal structure of the HA from A/California/07/2009 (3LZG) was used for further analysis. The new noncovalent bond formations in mutant luciferases were analyzed via WHAT IF and PIC, and protein stability was evaluated in the iStable server. We identified 33 and 23 mutations in A/Shiraz/106/2015 and A/California/07/2009 isolates, respectively; some mutations are located on the antigenic sites of Sa, Sb, Ca1, Ca2, and Cb HA1 and the fusion peptide of HA2. The results show that with the mutation some interactions are lost and new interactions are formed with other amino acids. The results of the free-energy analysis suggested that these new interactions have a destabilizing effect, which needs confirmation experimentally. IMPORTANCE Due to the fact that the mutations that occurred in the influenza virus HA cause the instability of the protein produced by the virus and antigenic changes and the escape of the virus from the immune system, the mutations that occurred in A/Shiraz/1/2013 were investigated in terms of energy level and stability. The mutations located in a globular portion of the HA are S188T, Q191H, S270P, K285Q, and P299L. On the other hand, the E374K, E46K-B, S124N-B, and I321V mutations are located in the stem portion of the HA (HA2). The change V252L mutation eliminates interactions with Ala181, Phe147, Leu151, and Trp153 and forms new interactions with Gly195, Asn264, Phe161, Met244, Tyr246, Leu165, and Trp167 which can change the stability of the HA structure. The K166Q mutation, which is located within the antigenic site Sa, causes the virus to escape from the immune response.

Epitope Mapping of Lysozyme Using the Chinese Egg-Allergic Sera at Both Pooled and Individual Levels

To accurately map the B-cell linear epitopes of lysozyme (LYS) in eggs, five bioinformatics tools were first used to obtain the mimotopes. Afterward, based on the Chinese egg-allergic sera samples screened by the indirect enzyme-linked immunosorbent, the epitopes possessing the capability of binding to IgG/IgE were mapped at both pooled and individual levels by using overlapping peptides covering the complete amino acid sequence of LYS. Six B-cell linear epitopes and two dominant B-cell linear epitopes that could bind to LYS-sIgG were mapped for the first time. Seven IgE-binding epitopes and three dominant IgE-binding epitopes were also obtained. Furthermore, AA31-34 and AA88-91 were the shared dominant epitopes of LYS-sIgG and LYS-sIgE at pooled and individual levels. Overall, the mapped B-cell linear epitopes filled in the gaps in the study of LYS epitopes, and the results may provide theoretical support for the following immunotherapy of egg allergy.

Determination of Binding Sites on Trastuzumab and Pertuzumab to Selective Affimers Using Hydrogen-Deuterium Exchange Mass Spectrometry

Hydrogen-deuterium exchange mass spectrometry (HDX-MS) is a method to probe the solvent accessibility and conformational dynamics of a protein or a protein-ligand complex with respect to exchangeable amide hydrogens. Here, we present the application of HDX-MS to determine the binding sites of Affimer reagents to the monoclonal antibodies trastuzumab and pertuzumab, respectively. Intact and subunit level HDX-MS analysis of antibody-affimer complexes showed significant protection from HDX in the antibody Fab region upon affimer binding. Bottom-up HDX-MS experiments including online pepsin digestion revealed that the binding sites of the affimer reagents were mainly located in the complementarity-determining region (CDR) 2 of the heavy chain of the respective antibodies. Three-dimensional models of the binding interaction between the affimer reagents and the antibodies were built by homology modeling and molecular docking based on the HDX data.

A modified ELISA assay differentiates CCL20 locked dimers from wild-type monomers

A novel engineered CCL20 locked dimer (CCL20LD) is nearly identical to the naturally occurring chemokine CCL20 but blocks CCR6-mediated chemotaxis and offers a new approach to treat the diseases of psoriasis and psoriatic arthritis. Methods for quantifying CCL20LD serum levels are needed to assess pharmacokinetics parameters and evaluate drug delivery, metabolism, and toxicity. Existing ELISA kits fail to discriminate between CCL20LD and the natural chemokine, CCL20WT (the wild type monomer). Herein, we tested several available CCL20 monoclonal antibodies to be able to identify one clone that can be used both as a capture and a detection antibody (with biotin-labeling) to specifically detect CCL20LD with high specificity. After validation using recombinant proteins, the CCL20LD-selective ELISA was used to analyze blood samples from CCL20LD treated mice, demonstrating the utility of this novel assay for preclinical development of a biopharmaceutical lead compound for psoriatic disease.

Allergenicity of peanut allergens and its dependence on the structure

Food allergies are a global food safety problem. Peanut allergies are common due, in part, to their popular utilization in the food industry. Peanut allergy is typically an immunoglobulin E-mediated reaction, and peanuts contain 17 allergens belonging to different families in peanut. In this review, we first introduce the mechanisms and management of peanut allergy, followed by the basic structures of associated allergens. Subsequently, we summarize methods of epitope localization for peanut allergens. These methods can be instrumental in speeding up the discovery of allergenicity-dependent structures. Many attempts have been made to decrease the allergenicity of peanuts. The structures of hypoallergens, which are manufactured during processing, were analyzed to strengthen the desensitization process and allergen immunotherapy. The identification of conformational epitopes is the bottleneck in both peanut and food allergies. Further, the identification and modification of such epitopes will lead to improved strategies for managing and preventing peanut allergy. Combining traditional wet chemistry research with structure simulation studies will help in the epitopes' localization.

Residue-Level Characterization of Antibody Binding Epitopes Using Carbene Chemical Footprinting

Characterization of antibody binding epitopes is an important factor in therapeutic drug discovery, as the binding site determines and drives antibody pharmacology and pharmacokinetics. Here, we present a novel application of carbene chemical footprinting with mass spectrometry for identification of antibody binding epitopes at the single-residue level. Two different photoactivated diazirine reagents provide complementary labeling information allowing structural refinement of the antibody binding interface. We applied this technique to map the epitopes of multiple MICA and CTLA-4 antibodies and validated the findings with X-ray crystallography and yeast surface display epitope mapping. The characterized epitopes were used to understand biolayer interferometry-derived competitive binding results at the structural level. We show that carbene footprinting provides fast and high-resolution epitope information critical in the antibody selection process and enables mechanistic understanding of function to accelerate the drug discovery process.

Characterization of Phosphorylation-Dependent Antibody Binding to Cancer-Mutated Linkers of C2H2 Zinc Finger Proteins by Intact Transition Epitope Mapping-Thermodynamic Weak-Force Order Analysis

With Intact Transition Epitope Mapping-Thermodynamic Weak-force Order (ITEM-TWO) analysis in combination with molecular modeling, the phosphorylation-dependent molecular recognition motif of the anti-HpTGEKP antibody has been investigated with binary and ternary component mixtures consisting of antibody and (phospho-) peptides. Amino acid sequences have been selected to match either the antibody's recognition motif or the cancer-related zinc finger protein mutations and phosphorylations of the respective amino acid residues. Upon electrospraying of all the components of the mixtures, that is, hexapeptides, antibody, and intact immune complexes, the produced ions were subjected to mass spectrometric mass filtering. The antibody ions as well as the immune complex ions traversed into the mass spectrometer's collision chamber, whereas paths of unbound peptide ions were blocked prior to entering the collision cell. After dissociation of the multiply charged immune complexes in the gas phase, the complex-released peptide ions were recorded after having traversed the second mass filter. Complex-released peptides were unambiguously identified by their masses using mass analysis with isotope resolution. From the results of our studies with seven (phospho-) peptides with distinct amino acid sequences, which resembled either the antibody's binding motif or mutations, we conclude the following: (i) A negatively charged phospho group, located near the peptide's N-terminus is mandatory for antibody binding when placed on the peptide surface at a precise distance to the C-terminally located positively charged ε-amino group of a lysinyl residue. (ii) A bulky amino acid residue, such as the tyrosinyl residue at the N-terminal position of the (phospho-) threoninyl residue, abolishes antibody binding. (iii) Two closely spaced phospho groups negatively interfere with the surface polarity pattern and abolish antibody binding as well. (iv) Non-phosphorylated peptides are not binding partners of the anti-HpTGEKP antibody.

LBCE-XGB: A XGBoost Model for Predicting Linear B-Cell Epitopes Based on BERT Embeddings

Accurately detecting linear B-cell epitopes (BCEs) makes great sense in vaccine design, immunodiagnostic test, antibody production, disease prevention and treatment. Wet-lab experiments for determining linear BCEs are both expensive and laborious, which are not able to meet the recognition needs of modern massive protein sequence data. Instead, computational methods can efficiently identify linear BCEs with low cost. Although several computational methods are available, the performance is still not satisfactory. Thus, we propose a new method, LBCE-XGB, to forecast linear BCEs based on XGBoost algorithm. To represent the biological information concealed in peptide sequences, the embeddings of the residues were obtained from a pre-trained domain-specific BERT model. In addition, the other five types of attributes comprising amino acid composition, amino acid antigenicity scale were also extracted. The best feature combination was determined according to the cross-validation results. Against the models developed by other deep learning and machine learning algorithms, LBCE-XGB achieves the top performance with an AUROC of 0.845 for fivefold cross-validation. The results on the independent test set show that our model attains an AUROC of 0.838 which is substantially higher than other state-of-the-art methods. The outcomes indicate that the representations of BERT could be an effective feature in predicting linear BCEs and we believe that LBCE-XGB could be a useful medium for detecting linear B cell epitopes with high accuracy and low cost.

A high-throughput single-particle imaging platform for antibody characterization and a novel competition assay for therapeutic antibodies

Monoclonal antibodies (mAbs) play an important role in diagnostics and therapy of infectious diseases. Here we utilize a single-particle interferometric reflectance imaging sensor (SP-IRIS) for screening 30 mAbs against Ebola, Sudan, and Lassa viruses (EBOV, SUDV, and LASV) to find out the ideal capture antibodies for whole virus detection using recombinant vesicular stomatitis virus (rVSV) models expressing surface glycoproteins (GPs) of EBOV, SUDV, and LASV. We also make use of the binding properties on SP-IRIS to develop a model for mapping the antibody epitopes on the GP structure. mAbs that bind to mucin-like domain or glycan cap of the EBOV surface GP show the highest signal on SP-IRIS, followed by mAbs that target the GP1-GP2 interface at the base domain. These antibodies were shown to be highly efficacious against EBOV infection in non-human primates in previous studies. For LASV detection, 8.9F antibody showed the best performance on SP-IRIS. This antibody binds to a unique region on the surface GP compared to other 15 mAbs tested. In addition, we demonstrate a novel antibody competition assay using SP-IRIS and rVSV-EBOV models to reveal the competition between mAbs in three successful therapeutic mAb cocktails against EBOV infection. We provide an explanation as to why ZMapp cocktail has higher efficacy compared to the other two cocktails by showing that three mAbs in this cocktail (13C6, 2G4, 4G7) do not compete with each other for binding to EBOV GP. In fact, the binding of 13C6 enhances the binding of 2G4 and 4G7 antibodies. Our results establish SP-IRIS as a versatile tool that can provide high-throughput screening of mAbs, multiplexed and sensitive detection of viruses, and evaluation of therapeutic antibody cocktails.

Recent advances in immunoassay technologies for the detection of human coronavirus infections

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is the seventh coronavirus (CoV) that has spread in humans and has become a global pandemic since late 2019. Efficient and accurate laboratory diagnostic methods are one of the crucial means to control the development of the current pandemic and to prevent potential future outbreaks. Although real-time reverse transcription-polymerase chain reaction (rRT-PCR) is the preferred laboratory method recommended by the World Health Organization (WHO) for diagnosing and screening SARS-CoV-2 infection, the versatile immunoassays still play an important role for pandemic control. They can be used not only as supplemental tools to identify cases missed by rRT-PCR, but also for first-line screening tests in areas with limited medical resources. Moreover, they are also indispensable tools for retrospective epidemiological surveys and the evaluation of the effectiveness of vaccination. In this review, we summarize the mainstream immunoassay methods for human coronaviruses (HCoVs) and address their benefits, limitations, and applications. Then, technical strategies based on bioinformatics and advanced biosensors were proposed to improve the performance of these methods. Finally, future suggestions and possibilities that can lead to higher sensitivity and specificity are provided for further research.

High-Throughput Epitope Mapping by Hydrogen Exchange-Mass Spectrometry

In this paper, we introduce a screening protocol for epitope mapping by hydrogen exchange mass spectrometry (HX-MS) that has higher throughput than a traditional HX-MS epitope mapping. In the screening protocol, three HX labeling times (20, 1000, and 86400 s) are each measured without replicates. The experimental protocol is anchored on a single epitope mapping experiment conducted using the traditional complete protocol (five HX times measured in triplicate) that is used to define HX times and define significance limits. Previously, we reported traditional epitope mapping results on the Borrelia burgdorferi outer surface protein A (OspA) antigen that are in excellent agreement with the X-ray crystallography results. Here, we show that the screening protocol and complete HX-MS identify identical epitopes of OspA but that the screening protocol has a 5-fold higher throughput.

Epitope mapping of monoclonal antibodies: a comprehensive comparison of different technologies

Monoclonal antibodies have become an important class of therapeutics in the last 30 years. Because the mechanism of action of therapeutic antibodies is intimately linked to their binding epitopes, identification of the epitope of an antibody to the antigen plays a central role during antibody drug development. The gold standard of epitope mapping, X-ray crystallography, requires a high degree of proficiency with no guarantee of success. Here, we evaluated six widely used alternative methods for epitope identification (peptide array, alanine scan, domain exchange, hydrogen-deuterium exchange, chemical cross-linking, and hydroxyl radical footprinting) in five antibody-antigen combinations (pembrolizumab+PD1, nivolumab+PD1, ipilimumab+CTLA4, tremelimumab+CTLA4, and MK-5890+CD27). The advantages and disadvantages of each technique are demonstrated by our data and practical advice on when and how to apply specific epitope mapping techniques during the drug development process is provided. Our results suggest chemical cross-linking most accurately identifies the epitope as defined by crystallography.

Unique epitope-antibody interactions in the intrinsically disordered proteoglycan-like domain of human carbonic anhydrase IX defined by high-resolution NMR combined with yeast surface display

Carbonic anhydrase (CA)-IX is an extracellular enzyme that is essential in the adaptation of tumor cells to their increasingly more hypoxic and acidic microenvironment. Within the family of carbonic anhydrases, CA-IX is unique in that it is the only CA with an N-terminal intrinsically disordered region (IDR) containing a proteoglycan (PG)-like domain. This PG-like IDR has been described to be instrumental in CA-IX's enzyme activity, as well as tumor cell motility and invasion. We have characterized the antibody-epitope interactions of two novel and unique antibodies (11H9 and 12H8) that are specific for the human CA-IX's IDR. Binding interactions of these antibodies to the intact IDR were studied by surface plasmon resonance and high-resolution nuclear magnetic resonance (NMR) spectroscopy, while the specific epitopes were determined by both NMR and yeast surface display (YSD). Our data show that 12H8 binds to the N-terminus of CA-IX, while 11H9 has a high affinity for an epitope located in the central region of the IDR containing three GEEDLP repeats in a manner that is different from the previously described M75 antibody. Titration NMR spectroscopy using CA-IX's entire IDR in addition identified a secondary epitope of 11H9 at the beginning of the PG-like domain that remains exposed and available for further binding events after the engagement at its primary epitope at the center of the PG-like domain. Transverse relaxation optimized NMR spectroscopy of 11H9-F(Ab) in complex with the CA-IX IDR outlines structural rigidification of a linear epitope, while the rest of the IDR remains largely unstructured upon complex formation. This study illustrates how high-resolution NMR and YSD are used as complementary tools for a comprehensive characterization of antibody-epitope interactions involving intrinsically unstructured antigen domains with highly repetitive sequences.

Binding epitope for recognition of human TRPM4 channel by monoclonal antibody M4M

Mouse monoclonal antibody M4M was recently designed to block human TRPM4 channel. The polypeptide for generating M4M is composed of peptide A1 between the transmembrane segment 5 (S5) and the pore, and a second peptide A2 between the pore and the transmembrane segment 6 (S6). Using peptide microarray, a 4-amino acid sequence EPGF within the A2 was identified to be the binding epitope for M4M. Substitution of EPGF with other amino acids greatly reduced binding affinity. Structural analysis of human TRPM4 structure indicates that EPGF is located externally to the channel pore. A1 is close to the EPGF binding epitope in space, albeit separated by a 37-amino acid peptide. Electrophysiological study reveals that M4M could block human TRPM4, but with no effect on rodent TRPM4 which shares a different amino acid sequence ERGS for the binding motif. Our results demonstrate that M4M is a specific inhibitor for human TRPM4.

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.

Epitope Fine Mapping by Mass Spectrometry: Investigations of Immune Complexes Consisting of Monoclonal Anti-HpTGEKP Antibody and Zinc Finger Protein Linker Phospho-Hexapeptides

Accurate formation of antibody-antigen complexes has been relied on in both, multitudes of scientific projects and ample therapeutic and diagnostic applications. Mass spectrometrically determined dissociation behavior of immune complexes with the anti-HpTGEKP antibody revealed that the ten most frequently occurring phospho-hexapeptide linker sequences from C2H2 zinc finger proteins could be divided into two classes: orthodox binders, where strong noncovalent interactions developed as anticipated, and unorthodox binders with deviating structures and weaker binding. Phosphorylation of threonine was compulsory for antibody binding in an orthodox manner. Gas phase dissociation energy determinations of seven C2H2 zinc finger protein linker phospho-hexapeptides with orthodox binding properties revealed a bipolar binding motif of the antibody paratope. Epitope peptides, which in addition to the negatively charged phospho-threonine residue were C-terminally flanked by positively charged residues provided stronger binding, i. e. dissociation was endothermic, than peptides with acidic amino acid residues at these positions, for which dissociation was exothermic.

A Promising Tool in Serological Diagnosis: Current Research Progress of Antigenic Epitopes in Infectious Diseases

Infectious diseases, caused by various pathogens in the clinic, threaten the safety of human life, are harmful to physical and mental health, and also increase economic burdens on society. Infections are a complex mechanism of interaction between pathogenic microorganisms and their host. Identification of the causative agent of the infection is vital for the diagnosis and treatment of diseases. Etiological laboratory diagnostic tests are therefore essential to identify pathogens. However, due to its rapidity and automation, the serological diagnostic test is among the methods of great significance for the diagnosis of infections with the basis of detecting antigens or antibodies in body fluids clinically. Epitopes, as a special chemical group that determines the specificity of antigens and the basic unit of inducing immune responses, play an important role in the study of immune responses. Identifying the epitopes of a pathogen may contribute to the development of a vaccine to prevent disease, the diagnosis of the corresponding disease, and the determination of different stages of the disease. Moreover, both the preparation of neutralizing antibodies based on useful epitopes and the assembly of several associated epitopes can be used in the treatment of disease. Epitopes can be divided into B cell epitopes and T cell epitopes; B cell epitopes stimulate the body to produce antibodies and are therefore commonly used as targets for the design of serological diagnostic experiments. Meanwhile, epitopes can fall into two possible categories: linear and conformational. This article reviews the role of B cell epitopes in the clinical diagnosis of infectious diseases.

A Nanobody-Based Immunoassay for Detection of Ustilaginoidins in Rice Samples

Ustilaginoidins are a class of bis-naphtho-γ-pyrone mycotoxins produced by the pathogen Villosiclava virens of rice false smut, which has recently become one of the most devastating diseases in rice-growing regions worldwide. In this research, the nanobody phage display library was established after an alpaca was immunized with the hemiustilaginoidin F-hapten coupled with bovine serum albumin (BSA). Heterologous antigen selection and combing trypsin with competition alternant elution methods were performed for nanobody screening. Two nanobodies, namely, Nb-B15 and Nb–C21, were selected for the establishment of indirect competitive enzyme-linked immunosorbent assays (ic-ELISAs). For Nb–B15 and Nb-C21, their IC₅₀ values were 11.86 μg/mL and 11.22 μg/mL, and the detection ranges were at 3.41–19.98 μg/mL and 1.17–32.13 μg/mL, respectively. Two nanobodies had a broad spectrum to quantify the contents of total ustilaginoidins in rice samples according to cross-reactivity. The recognition mechanisms of Nb-B15 and Nb-C21 against ustilaginoidin A were elucidated by molecular modeling and docking. The key amino acid sites for the binding of Nb–B15 or Nb–C21 to ustilaginoidin A were mainly located in the FR1 and CDR1 regions. As Nb-B15 was superior to Nb–C21 in the aspects of protein expression, ELISA titer, and tolerance to organic solvents, it was selected for application in the detection of actual contaminated rice samples. The total ustilaginoidin contents of rice samples were analyzed by Nb–B15-based ic–ELISA and HPLC-DAD, between which the results were found to be consistent. The developed immunoassay based on the nanobody from the alpaca can be employed as a rapid and effective method for detection of total utilaginoidins in contaminated rice samples.

Prediction of the structural interface between fibroblast growth factor23 and Burosumab using alanine scanning and molecular docking

Burosumab, an FGF23 targeting monoclonal antibody, was approved by the FDA in 2018 for use in children and adults with X-linked hypophosphatemia (or XLH). While several clinical studies have demonstrated the long-term safety and efficacy of Burosumab, the molecular basis of FGF23-Burosumab interaction which underpins its mechanism of action remains unknown. In this study, we employed molecular docking combined with alanine scanning of epitope and paratope to predict a model of FGF23-Burosumab interaction. Then, we used the model to understand the species-species cross-reactivity of Burosumab and to reverse engineer mouse FGF23 with 'back to human' mutations to bind Burosumab. Finally, we redesigned the CDRs with two mutations to engineer an affinity enhanced variant of the antibody. Our study provides insights into the FGF23-Burosumab interaction and demonstrates that alanine-scanning coupled with molecular docking can be used to optimize antibody candidates (e.g., structure-guided affinity maturation) for therapeutic use.

Fine mapping of the antigenic epitopes of the Gc protein of Guertu virus

Guertu virus (GTV), a newly discovered member of the genus Banyangvirus in the family Phenuiviridae, poses a potential health threat to humans and animals. The viral glycoprotein (GP) binds to host cell receptors to induce a neutralizing immune response in the host. Therefore, identification of the B-cell epitopes (BCEs) in the immunodominant region of the GTV Gc protein is important for the elucidation of the virus–host cell interactions and the development of GTV epitope assays and vaccines. In this study, an improved overlapping biosynthetic peptide method and rabbit anti-GTV Gc polyclonal antibodies were used for fine mapping of the minimal motifs of linear BCEs of the GTV Gc protein. Thirteen BCE motifs were identified from eleven positive 16mer-peptides, namely EGc1 (¹⁹KVCATTGRA²⁷), EGc2 (⁵⁸KKINLKCKK⁶⁶), EGc3 (⁶⁸SSYYVPDA⁷⁵), EGc4 (⁷⁵ARSRCTSVRR⁸⁴), EGc5 (⁷⁹CTSVRRCRWA⁸⁸), EGc6 (⁹⁰DCQSGCPS⁹⁷), EGc7 (⁹⁶PSHFTSNS¹⁰³), EGc8 (¹¹⁵AGLGFSG¹²¹), EGc9 (¹⁴⁸ENPHGVI¹⁵⁴), EGc10 (¹⁷⁹KVFHPMS¹⁸⁵), EGc11 (²³⁰QAGMGVVG²³⁷), EGc12 (³⁰³RSHDSQGKIS³¹²), and EGc13 (⁴³⁰DIPRFV⁴³⁵). Of these, 7 could be recognized by GTV IgG-positive sheep sera. Three-dimensional structural analysis revealed that all 13 BCEs were present on the surface of the Gc protein. Sequence alignment of the 13 BCEs against homologous proteins from 10 closely related strains of severe fever with thrombocytopenia syndrome virus from different geographical regions revealed that the amino acid sequences of EGc4, EGc5, EGc8, EGc11, and EGc12 were highly conserved, with 100% similarity. The remaining 8 epitopes (EGc1, EGc2, EGc3, EGc6, EGc7, EGc9, EGc10, and EGc13) showed high sequence similarity in the range of 71.43%–87.50%. These 13 BCEs of the GTV Gc protein provide a molecular foundation for future studies of the immunological properties of GTV glycoproteins and the development of GTV multi-epitope assays and vaccines.

Complementary Structural Information for Antibody-Antigen Complexes from Hydrogen-Deuterium Exchange and Covalent Labeling Mass Spectrometry

Characterizing antibody-antigen interactions is necessary for properly developing therapeutic antibodies, understanding their mechanisms of action, and patenting new drug molecules. Here, we demonstrate that hydrogen-deuterium exchange (HDX) mass spectrometry (MS) measurements together with diethylpyrocarbonate (DEPC) covalent labeling (CL) MS measurements provide higher order structural information about antibody-antigen interactions that is not available from either technique alone. Using the well-characterized model system of tumor necrosis factor α (TNFα) in complex with three different monoclonal antibodies (mAbs), we show that two techniques offer a more complete overall picture of TNFα's structural changes upon binding different mAbs, sometimes providing synergistic information about binding sites and changes in protein dynamics upon binding. Labeling decreases in CL generally occur near the TNFα epitope, whereas decreases in HDX can span the entire protein due to substantial stabilization that occurs when mAbs bind TNFα. Considering both data sets together clarifies the TNFα regions that undergo a decrease in solvent exposure due to mAb binding and that undergo a change in dynamics due to mAb binding. Moreover, the single-residue level resolution of DEPC-CL/MS can clarify HDX/MS data for long peptides. We feel that the two techniques should be used together when studying the mAb-antigen interactions because of the complementary information they provide.

Western blotting: a powerful staple in scientific and biomedical research

Western blotting (WB), also known as immunoblotting, is a well-known molecular biology method that biologists often use to investigate many features of the protein, ranging from basic protein analysis to disease detection. WB is simple, unique, rapid, widely used routine tool with easy interpretation and definite results. It is being used in various fields of science, research and development, diagnostic labs and hospitals. The principle of WB is to accomplish the separation of proteins based on molecular weight and charge. This review addresses in detail the individual steps involved in the WB technique, its troubleshooting, internal loading controls, total protein staining and its diverse applications in scientific research and clinical settings, along with its future perspectives.

A Structure-Based B-cell Epitope Prediction Model Through Combing Local and Global Features

B-cell epitopes (BCEs) are a set of specific sites on the surface of an antigen that binds to an antibody produced by B-cell. The recognition of BCEs is a major challenge for drug design and vaccines development. Compared with experimental methods, computational approaches have strong potential for BCEs prediction at much lower cost. Moreover, most of the currently methods focus on using local information around target residue without taking the global information of the whole antigen sequence into consideration. We propose a novel deep leaning method through combing local features and global features for BCEs prediction. In our model, two parallel modules are built to extract local and global features from the antigen separately. For local features, we use Graph Convolutional Networks (GCNs) to capture information of spatial neighbors of a target residue. For global features, Attention-Based Bidirectional Long Short-Term Memory (Att-BLSTM) networks are applied to extract information from the whole antigen sequence. Then the local and global features are combined to predict BCEs. The experiments show that the proposed method achieves superior performance over the state-of-the-art BCEs prediction methods on benchmark datasets. Also, we compare the performance differences between data with or without global features. The experimental results show that global features play an important role in BCEs prediction. Our detailed case study on the BCEs prediction for SARS-Cov-2 receptor binding domain confirms that our method is effective for predicting and clustering true BCEs.

Antigenicity Alternations of Variant PEDV S Protein Disclosed by Linear B Cell Epitope Mapping

The spike protein (S) plays a crucial role in porcine epidemic diarrhea virus (PEDV) infection and induces neutralizing antibodies. Mutations of the S protein are supposed to provide the main antigenic shift leading to the antigenic escape of PEDVs. It is therefore a significant question how much accumulation of antigenic shift could lead to the antigenic escape of the variant PEDV. To provide an answer in the study, B cell epitopes (BCEs) on the S protein of the PEDV vaccine strain CV777 (S^CV777) and variant strain SD2014 (S^SD2014) were mapped using biosynthetic peptides and rabbit anti-PEDV S serum. Seventy-nine and 68 linear BCEs were identified from S^CV777 and S^SD2014, respectively. While 66.2% of the BCEs of S^SD2014 could be recognized by anti-S^CV777 serum and 67.1% of S^CV777 BCEs could be recognized by anti-S^SD2014 serum, more than 40% of the BCEs identified using anti-S^CV777 serum on S^CV777 could not be recognized by anti-S^SD2014 serum and vice versa. The completely shared BCEs took low percentages of 29.4% and 25.3% for S^SD2014 and S^CV777, respectively. These results indicate a low conservation of antigenicity of the S protein compared to a relatively high amino acid sequence similarity of 92.2% between the two strains. The study provided a BCE shift reference of PEDV antigenic escape and surveillance control.

Mapping immunogenic epitopes of an adhesin-like protein from Methanobrevibacter ruminantium M1 and comparison of empirical data with in silico prediction methods

In silico prediction of epitopes is a potentially time-saving alternative to experimental epitope identification but is often subject to misidentification of epitopes and may not be useful for proteins from archaeal microorganisms. In this study, we mapped B- and T-cell epitopes of a model antigen from the methanogen Methanobrevibacter ruminantium M1, the Big_1 domain (AdLP-D1, amino acids 19-198) of an adhesin-like protein. A series of 17 overlapping 20-mer peptides was selected to cover the Big_1 domain. Peptide-specific antibodies were produced in mice and measured by ELISA, while an in vitro splenocyte re-stimulation assay determined specific T-cell responses. Overall, five peptides of the 17 peptides were shown to be major immunogenic epitopes of AdLP-D1. These immunogenic regions were examined for their localization in a homology-based model of AdLP-D1. Validated epitopes were found in the outside region of the protein, with loop like secondary structures reflecting their flexibility. The empirical data were compared with epitope predictions made by programmes based on a range of algorithms. In general, the epitopes identified by in silico predictions were not comparable to those determined empirically.

Mapping paratopes of nanobodies using native mass spectrometry and ultraviolet photodissociation

Following immense growth and maturity of the field in the past decade, native mass spectrometry has garnered widespread adoption for the structural characterization of macromolecular complexes. Routine analysis of biotherapeutics by this technique has become commonplace to assist in the development and quality control of immunoglobulin antibodies. Concurrently, 193 nm ultraviolet photodissociation (UVPD) has been developed as a structurally sensitive ion activation technique capable of interrogating protein conformational changes. Here, UVPD was applied to probe the paratopes of nanobodies, a class of single-domain antibodies with an expansive set of applications spanning affinity reagents, molecular imaging, and biotherapeutics. Comparing UVPD sequence fragments for the free nanobodies versus nanobody·antigen complexes empowered assignment of nanobody paratopes and intermolecular salt-bridges, elevating the capabilities of UVPD as a new strategy for characterization of nanobodies.

Ultraviolet photodissociation mass spectrometry is used to probe the paratopes of nanobodies, a class of single-domain antibodies, and to determine intersubunit salt-bridges and explore the nanobody·antigen interfaces.

Nanoscale binding site localization by molecular distance estimation on native cell surfaces using topological image averaging

Antibody binding to cell surface proteins plays a crucial role in immunity, and the location of an epitope can altogether determine the immunological outcome of a host-target interaction. Techniques available today for epitope identification are costly, time-consuming, and unsuited for high-throughput analysis. Fast and efficient screening of epitope location can be useful for the development of therapeutic monoclonal antibodies and vaccines. Cellular morphology typically varies, and antibodies often bind heterogeneously across a cell surface, making traditional particle-averaging strategies challenging for accurate native antibody localization. In the present work, we have developed a method, SiteLoc, for imaging-based molecular localization on cellular surface proteins. Nanometer-scale resolution is achieved through localization in one dimension, namely, the distance from a bound ligand to a reference surface. This is done by using topological image averaging. Our results show that this method is well suited for antibody binding site measurements on native cell surface morphology and that it can be applied to other molecular distance estimations as well.

Antibodies play a key role in the immune system. These proteins stick to harmful substances, such as bacteria and other disease-causing pathogens, marking them for destruction or blocking their attack. Antibodies are highly selective, and this ability has been used to target particular molecules in research, diagnostics and therapies.

Typically, antibodies need to stick to a particular segment, or ‘epitope’, on the surface of a cell in order to trigger an immune response. Knowing where these regions are can help explain how these immune proteins work and aid the development of more effective drugs and diagnostic tools.

One way to identify these sites is to measure the nano-distance between antibodies and other features on the cell surface. To do this, researchers take multiple images of the cell the antibody is attached to using light microscopy. Various statistical methods are then applied to create an ‘average image’ that has a higher resolution and can therefore be used to measure the distance between these two points more accurately. While this approach works on fixed shapes, like a perfect circle, it cannot handle human cells and bacteria which are less uniform and have more complex surfaces.

Here, Kumra Ahnlide et al. have developed a new method called SiteLoc which can overcome this barrier. The method involves two fluorescent probes: one attached to a specific site on the cell’s surface, and the other to the antibody or another molecule of interest. These two probes emit different colours when imaged with a fluorescent microscope. To cope with objects that have uneven surfaces, such as cells and bacteria, the two signals are transformed to ‘follow’ the same geometrical shape. The relative distance between them is then measured using statistical methods. Using this approach, Kumra Ahnlide et al. were able to identify epitopes on a bacterium, and measure distances on the surface of human red blood cells.

The SiteLoc system could make it easier to develop antibody-based treatments and diagnostic tools. Furthermore, it could also be beneficial to the wider research community who could use it to probe other questions that require measuring nanoscale distances.

Epitope Mapping with Diethylpyrocarbonate Covalent Labeling-Mass Spectrometry

Antigen-antibody epitope mapping is essential for understanding binding mechanisms and developing new protein therapeutics. In this study, we investigate diethylpyrocarbonate (DEPC) covalent labeling-mass spectrometry as a means of analyzing antigen-antibody interactions using the well-characterized model system of TNFα in complex with three different antibodies. Results show that residues buried in the epitope undergo substantial decreases in labeling, as expected. Interestingly, serine, threonine, and tyrosine residues at the edges of the epitope undergo unexpected increases in labeling. The increased labeling of these weakly nucleophilic residues is caused by the formation of hydrophobic pockets upon antibody binding that presumably increase local DEPC concentrations. Residues that are distant from the epitope generally do not undergo changes in labeling extent; however, some that do change experience variations in their local microenvironment due to side-chain reorganization or stabilization of the TNFα trimer that occurs upon binding. Overall, DEPC labeling of antigen-antibody complexes is found to depend on both changes in solvent exposure and changes to the residue microenvironment.

Epitope screening using Hydrogen/Deuterium Exchange Mass Spectrometry (HDX-MS): An accelerated workflow for evaluation of lead monoclonal antibodies

BACKGROUND

Epitope mapping is an increasingly important aspect of biotherapeutic and vaccine development. Recent advances in therapeutic antibody design and production have enabled candidate mAbs to be identified at a rapidly increasing rate, resulting in a significant bottleneck in the characterization of "structural" epitopes, that are challenging to determine using existing high throughput epitope mapping tools. Here, a Hydrogen/Deuterium Exchange Mass Spectrometry (HDX-MS) epitope screening workflow was introduced that is well suited for accelerated characterization of epitopes with a common antigen.

MAIN METHODS AND MAJOR RESULTS

The method is demonstrated on set of six candidate mAbs targeting Pertactin (PRN). Using this approach, five of the six epitopes were unambiguously determined using two HDX mixing timepoints in 24 h total run time, which is equivalent to the instrument time required to map a single epitope using the conventional workflow.

CONCLUSION

An accelerated HDX-MS epitope screening workflow was developed. The "screening" workflow successfully characterized five (out of six attempted) novel epitopes on the PRN antigen; information that can be used to support vaccine antigenicity assays.

Miniaturized single-cell technologies for monoclonal antibody discovery

Antibodies (Abs) are among the most important class of biologicals, showcasing a high therapeutic and diagnostic value. In the global therapeutic Ab market, fully-human monoclonal Abs (FH-mAbs) are flourishing thanks to their low immunogenicity and high specificity. The rapidly emerging field of single-cell technologies has paved the way to efficiently discover mAbs by facilitating a fast screening of the antigen (Ag)-specificity and functionality of Abs expressed by B cells. This review summarizes the principles and challenges of the four key concepts to discover mAbs using these technologies, being confinement of single cells using either droplet microfluidics or microstructure arrays, identification of the cells of interest, retrieval of those cells and single-cell sequence determination required for mAb production. This review reveals the enormous potential for mix-and-matching of the above-mentioned strategies, which is illustrated by the plethora of established, highly integrated devices. Lastly, an outlook is given on the many opportunities and challenges that still lie ahead to fully exploit miniaturized single-cell technologies for mAb discovery.

Antibody Class(es) Predictor for Epitopes (AbCPE): A Multi-Label Classification Algorithm

Development of vaccines and therapeutic antibodies to deal with infectious and other diseases are the most perceptible scientific interventions that have had huge impact on public health including that in the current Covid-19 pandemic. From inactivation methodologies to reverse vaccinology, vaccine development strategies of 21st century have undergone several transformations and are moving towards rational design approaches. These developments are driven by data as the combinatorials involved in antigenic diversity of pathogens and immune repertoire of hosts are enormous. The computational prediction of epitopes is central to these developments and numerous B-cell epitope prediction methods developed over the years in the field of immunoinformatics have contributed enormously. Most of these methods predict epitopes that could potentially bind to an antibody regardless of its type and only a few account for antibody class specific epitope prediction. Recent studies have provided evidence of more than one class of antibodies being associated with a particular disease. Therefore, it is desirable to predict and prioritize ‘peptidome’ representing B-cell epitopes that can potentially bind to multiple classes of antibodies, as an open problem in immunoinformatics. To address this, AbCPE, a novel algorithm based on multi-label classification approach has been developed for prediction of antibody class(es) to which an epitope can potentially bind. The epitopes binding to one or more antibody classes (IgG, IgE, IgA and IgM) have been used as a knowledgebase to derive features for prediction. Multi-label algorithms, Binary Relevance and Label Powerset were applied along with Random Forest and AdaBoost. Classifier performance was assessed using evaluation measures like Hamming Loss, Precision, Recall and F1 score. The Binary Relevance model based on dipeptide composition, Random Forest and AdaBoost achieved the best results with Hamming Loss of 0.1121 and 0.1074 on training and test sets respectively. The results obtained by AbCPE are promising. To the best of our knowledge, this is the first multi-label method developed for prediction of antibody class(es) for sequential B-cell epitopes and is expected to bring a paradigm shift in the field of immunoinformatics and immunotherapeutic developments in synthetic biology. The AbCPE web server is available at http://bioinfo.unipune.ac.in/AbCPE/Home.html.

In Silico Screening of Putative Corynebacterium pseudotuberculosis Antigens and Serological Diagnosis for Caseous Lymphadenitis in Sheep by Enzyme-Linked Immunosorbent Assay

Corynebacterium pseudotuberculosis is the etiologic agent of Caseous Lymphadenitis (CLA), a disease leading to severe damage in sheep and goats farming due to the lack of serological diagnosis, treatment, and effective prophylaxis. In this context, several strategies in an attempt to discover new antigens to compose diagnosis assays or vaccines are fundamental. Therefore, this study aimed to use bioinformatics software to evaluate the critical chemical characteristics of unknown proteins of C. pseudotuberculosis by selecting them for heterologous expression in Escherichia coli. For this purpose, six protein sequences of ascorbate transporter subunit, UPF protein, MMPL family transporter, Ribonuclease, Iron ABC transporter domain-containing permease, and fimbrial subunit were obtained. In silico analyses were performed using amino acid sequences to access immunodominant epitopes and their antigenic and allergenic potential and physicochemical characterization. The expressed proteins were used as an antigen for serological diagnosis by ELISA. All proteins showed distinct immunodominant epitopes and potential antigenic characteristics. The only proteins expressed were PTS and Ribonuclease. In parallel, we expressed CP40 and all were used with ELISA antigen in 49 CLA positive sera and 26 CLA negative sera. The proteins alone showed 100% sensitivity and 96.2%, 92.3%, and 88.5% specificity for rPTS, rRibonuclease, and rCP40, respectively. When proteins were combined, they showed 100% sensitivity and 84.6%, 92.3%, 88.5%, and 92.3% specificity for rPTS/rCp40, rRibonuclease/rCP40, rPTS/rRibonuclease, and rPTS/rRibonuclease/rCP40, respectively. The results of this study show an excellent correlation of sensitivity and specificity with all proteins. None of the specificity values preclude the potential of rPTS, rRibonuclease, or rCP40 for use in ELISA diagnostic assays since the results of this work are superior to those of other studies on CLA diagnosis described in the literature.

Analysis of binding residues in monoclonal antibody with high affinity for the head domain of the rat P2X4 receptor

P2X4 receptor is known to be involved in neuropathic pain. In order to detect the expression of P2X4 receptor on microglia at the time of onset of neuropathic pain, one approach consists on the preparation of the monoclonal antibodies with both selective binding and high affinity. We have recently established a monoclonal antibody (named 12-10H) which had high affinity to rat P2X4 receptor expressed in 1321N1 cells. The dissociation constants of the complex between the monoclonal antibodies obtained so far and the head domain (HD) in the rat P2X4 receptor were in the nanomolar range. To improve the affinity by rational mutations, we need to know the precious location of the binding site in these monoclonal antibodies. Here, we have analysed and identified the binding residues in the monoclonal antibody (12-10H) with high affinity for the HD of the rat P2X4 receptor by site-directed mutagenesis.

Comparison of Two Strategies to Generate Antigen-Specific Human Monoclonal Antibodies: Which Method to Choose for Which Purpose?

Human monoclonal antibodies (mAbs) are valuable tools to link genetic information with functional features and to provide a platform for conformational epitope mapping. Additionally, combined data on genetic and functional features provide a valuable mosaic for systems immunology approaches. Strategies to generate human mAbs from peripheral blood have been described and used in several studies including single cell sequencing of antigen-binding B cells and the establishment of antigen-specific monoclonal Epstein-Barr Virus (EBV) immortalized lymphoblastoid cell lines (LCLs). However, direct comparisons of these two strategies are scarce. Hence, we sought to set up these two strategies in our laboratory using peanut 2S albumins (allergens) and the autoantigen anti-Rho guanosine diphosphate dissociation inhibitor 2 (RhoGDI2, alternatively 'ARHGDIB') as antigen targets to directly compare these strategies regarding costs, time expenditure, recovery, throughput and complexity. Regarding single cell sequencing, up to 50% of corresponding V(D)J gene transcripts were successfully amplified of which 54% were successfully cloned into expression vectors used for heterologous expression. Seventy-five percent of heterologously expressed mAbs showed specific binding to peanut 2S albumins resulting in an overall recovery of 20.3%, which may be increased to around 29% by ordering gene sequences commercially for antibody cloning. In comparison, the establishment of monoclonal EBV-LCLs showed a lower overall recovery of around 17.6%. Heterologous expression of a mAb carrying the same variable region as its native counterpart showed comparable concentration-dependent binding abilities. By directly comparing those two strategies, single cell sequencing allows a broad examination of antigen-binding mAbs in a moderate-throughput manner, while the establishment of monoclonal EBV-LCLs is a powerful tool to select a small number of highly reactive mAbs restricted to certain B cell subpopulations. Overall, both strategies, initially set-up for peanut 2S albumins, are suitable to obtain human mAbs and they are easily transferrable to other target antigens as shown for ARHGDIB.

Hydrogen/deuterium exchange memory NMR reveals structural epitopes involved in IgE cross-reactivity of allergenic lipid transfer proteins

Identification of antibody-binding epitopes is crucial to understand immunological mechanisms. It is of particular interest for allergenic proteins with high cross-reactivity as observed in the lipid transfer protein (LTP) syndrome, which is characterized by severe allergic reactions. Art v 3, a pollen LTP from mugwort, is frequently involved in this cross-reactivity, but no antibody-binding epitopes have been determined so far. To reveal human IgE-binding regions of Art v 3, we produced three murine high-affinity mAbs, which showed 70-90% coverage of the allergenic epitopes from mugwort pollen-allergic patients. As reliable methods to determine structural epitopes with tightly interacting intact antibodies under native conditions are lacking, we developed a straightforward NMR approach termed hydrogen/deuterium exchange memory (HDXMEM). It relies on the slow exchange between the invisible antigen-mAb complex and the free ¹⁵N-labeled antigen whose ¹H-¹⁵N correlations are detected. Due to a memory effect, changes of NH protection during antibody binding are measured. Differences in H/D exchange rates and analyses of mAb reactivity to homologous LTPs revealed three structural epitopes: two partially cross-reactive regions around α-helices 2 and 4 as well as a novel Art v 3-specific epitope at the C terminus. Protein variants with exchanged epitope residues confirmed the antibody-binding sites and revealed strongly reduced IgE reactivity. Using the novel HDXMEM for NMR epitope mapping allowed identification of the first structural epitopes of an allergenic pollen LTP. This knowledge enables improved cross-reactivity prediction for patients suffering from LTP allergy and facilitates design of therapeutics.

HDX-MS for Epitope Characterization of a Therapeutic ANTIBODY Candidate on the Calcium-Binding Protein Annexin-A1

Annexin-A1 (ANXA1) belongs to a class of highly homologous Ca2+-dependent phospholipid-binding proteins. Its structure consists of a core region composed of four homologous repeats arranged in a compact, hydrolysis-resistant structure and an N-terminal region with a Ca2+-dependent conformation. ANXA1 is involved in several processes, including cell proliferation, apoptosis, metastasis, and the inflammatory response. Therefore, the development of antibodies blocking selected regions on ANXA1 holds great potential for the development of novel therapeutics treating inflammatory and cancer diseases. Here, we report the interaction site between an ANXA1-specific antibody known to inhibit T cell activation without adverse cytotoxic effects and ANXA1 using amide hydrogen-deuterium exchange mass spectrometry (HDX-MS). For the epitope determination, we applied two bottom-up HDX-MS approaches with pepsin digestion in solution and immobilized on beads. Both strategies revealed the interaction region within domain III of ANXA1 in Ca2+-bound conformation. The antibody-binding region correlates with the hydrophobic binding pocket of the N-terminal domain formed in the absence of calcium. This study demonstrates that even cryptic and flexible binding regions can be studied by HDX-MS, allowing a fast and efficient determination of the binding sites of antibodies which will help to define a mode of action profile for their use in therapy.

Identification of critical chemical modifications and paratope mapping by size exclusion chromatography of stressed antibody-target complexes

Therapeutic proteins including antibodies and Fc-fusion proteins undergo a large number of chemical modifications during cell culture, purification, storage and in human circulation. They are also exposed to harsh conditions during stress studies, including elevated temperature, extremes of pH, forced oxidation, physiological pH, UV light to assess the possible degradation pathways and suitability of methods for detecting them. Some of these modifications are located on residues in binding regions, leading to loss of binding and potency and classified as critical quality attributes. Currently, criticality of modifications is assessed by a laborious process of collecting antibody fractions from the soft chromatography techniques ion exchange and hydrophobic interaction chromatography and characterizing the fractions one-by-one for potency and chemical modifications. Here, we describe a method for large-scale, parallel identification of all critical chemical modifications in one experiment. In the first step, the antibody is stressed by one or several stress methods. It is then mixed with target protein and separated by size-exclusion chromatography (SEC) on bound antibody-target complex and unbound antibody. Peptide mapping of fractions and statistical analysis are performed to identify modifications on amino acid residues that affect binding. To identify the modifications leading to slight decreases in binding, competitive SEC of antibody and antigen mixtures was developed and described in a companion study by Shi et al, where target protein is provided at lower level, below the stoichiometry. The newly described method was successfully correlated to crystallography for assessing criticality of chemical modifications and paratope mapping. It is more sensitive to low-level modifications, better streamlined and platform ready.

Antibody Binding Epitope Mapping (AbMap) of Hundred Antibodies in a Single Run

Antibodies play essential roles in both diagnostics and therapeutics. Epitope mapping is essential to understand how an antibody works and to protect intellectual property. Given the millions of antibodies for which epitope information is lacking, there is a need for high-throughput epitope mapping. To address this, we developed a strategy, Antibody binding epitope Mapping (AbMap), by combining a phage displayed peptide library with next-generation sequencing. Using AbMap, profiles of the peptides bound by 202 antibodies were determined in a single test, and linear epitopes were identified for >50% of the antibodies. Using spike protein (S1 and S2)-enriched antibodies from the convalescent serum of one COVID-19 patient as the input, both linear and potentially conformational epitopes of spike protein specific antibodies were identified. We defined peptide-binding profile of an antibody as the binding capacity (BiC). Conceptually, the BiC could serve as a systematic and functional descriptor of any antibody. Requiring at least one order of magnitude less time and money to map linear epitopes than traditional technologies, AbMap allows for high-throughput epitope mapping and creates many possibilities.

Ab-Ligity: identifying sequence-dissimilar antibodies that bind to the same epitope

Solving the structure of an antibody-antigen complex gives atomic level information of the interactions between an antibody and its antigen, but such structures are expensive and hard to obtain. Alternative experimental sources include epitope mapping and binning experiments, which can be used as a surrogate to identify key interacting residues. However, their resolution is usually not sufficient to identify if two antibodies have identical interactions. Computational approaches to this problem have so far been based on the premise that antibodies with similar sequences behave similarly. Such approaches will fail to identify sequence-distant antibodies that target the same epitope. Here, we present Ab-Ligity, a structure-based similarity measure tailored to antibody-antigen interfaces. Using predicted paratopes on model antibody structures, we assessed its ability to identify those antibodies that target highly similar epitopes. Most antibodies adopting similar binding modes can be identified from sequence similarity alone, using methods such as clonotyping. In the challenging subset of antibodies whose sequences differ significantly, Ab-Ligity is still able to predict antibodies that would bind to highly similar epitopes (precision of 0.95 and recall of 0.69). We compared Ab-Ligity's performance to an existing tool for comparing general protein interfaces, InterComp, and showed improved performance on antibody cases achieved in a substantially reduced time. These results suggest that Ab-Ligity will allow the identification of diverse (sequence-dissimilar) antibodies that bind to the same epitopes from large datasets such as immune repertoires. The tool is available at http://opig.stats.ox.ac.uk/resources.