Convergent Evolution in Breadth of Two VH6-1-Encoded Influenza Antibody Clonotypes from a Single Donor

Structurally convergent antibodies derived from different vaccine strategies target the influenza virus HA anchor epitope with a subset of VH3 and VK3 genes

H1N1 influenza viruses are responsible for both seasonal and pandemic influenza. The continual antigenic shift and drift of these viruses highlight the urgent need for a universal influenza vaccine to elicit broadly neutralizing antibodies (bnAbs). Identification and characterization of bnAbs elicited in natural infection and immunization to influenza virus hemagglutinin (HA) can provide insights for development of a universal influenza vaccine. Here, we structurally and biophysically characterize four antibodies that bind to a conserved region on the HA membrane-proximal region known as the anchor epitope. Despite some diversity in their VH and VK genes, the antibodies interact with the HA through germline-encoded residues in HCDR2 and LCDR3. Somatic mutations on HCDR3 also contribute hydrophobic interactions with the conserved HA epitope. This convergent binding mode provides extensive neutralization breadth against H1N1 viruses and suggests possible countermeasures against H1N1 viruses.

Computational design and improvement of a broad influenza virus HA stem targeting antibody

Broadly neutralizing antibodies (nAbs) are vital therapeutic tools to counteract both pandemic and seasonal influenza threats. Traditional strategies for optimizing nAbs generally rely on labor-intensive, high-throughput mutagenesis screens. Here, we present an innovative structure-based design framework for the optimization of nAbs, which integrates epitope-paratope analysis, computational modeling, and rational design approaches, complemented by comprehensive experimental assessment. This approach was applied to optimize MEDI8852, a nAb targeting the stalk region of influenza A virus hemagglutinin (HA). The resulting variant, M18.1.2.2, shows a marked enhancement in both affinity and neutralizing efficacy, as demonstrated both in vitro and in vivo. Computational modeling reveals that this improvement can be attributed to the fine-tuning of interactions between the antibody's side-chains and the epitope residues that are highly conserved across the influenza A virus HA stalk. Our dry-wet iterative protocol for nAb optimization presented here yielded a promising candidate for influenza intervention.

Vaccination with different group 2 influenza subtypes alters epitope targeting and breadth of hemagglutinin stem-specific human B cells

The conserved influenza hemagglutinin stem, which is a target of cross-neutralizing antibodies, is now used in vaccine strategies focused on protecting against influenza pandemics. Antibody responses to group 1 stem have been extensively characterized, but little is known about group 2. Here, we characterized the stem-specific repertoire of individuals vaccinated with one of three group 2 influenza subtypes (H3, H7, or H10). Epitope mapping revealed two epitope supersites on the group 2 stem. Antibodies targeting the central epitope were broadly cross-reactive, whereas antibodies targeting the lower epitope had narrower breadth but higher potency against H3 subtypes. The ratio of B cells targeting each of the supersites varied with the vaccine subtype, leading to differences in the cross-reactivity of the B cell response. Our findings suggest that vaccine strategies targeting both group 2 stem epitopes would be complementary, eliciting broader and more potent protection against both seasonal and pandemic influenza strains.

Isolation of anti-Ancylostoma-secreted protein 5 (ASP5) antibody from a naïve antibody phage library

Ancylostoma species are parasitic nematodes that release a multitude of proteins to manipulate host immune responses to facilitate their survival. Among the released proteins, Ancylostoma-secreted protein 5 (ASP5) plays a pivotal role in mediating host-parasite interactions, making it a promising target for interventions against canine hookworm infections caused by Ancylostoma species. Antibody phage display, a widely used method for generating human monoclonal antibodies was employed in this study. A bacterial expression system was used to produce ASP5 for biopanning. A single-chain fragment variable (scFv) monoclonal antibody against ASP5 was generated from the naïve Human AntibodY LibrarY (HAYLY). The resulting scFv antibody was characterized to elucidate its antigen-binding properties. The identified monoclonal antibody showed good specificity and binding characteristics which highlights its potential for diagnostic applications for hookworm infections.

An explainable language model for antibody specificity prediction using curated influenza hemagglutinin antibodies

Despite decades of antibody research, it remains challenging to predict the specificity of an antibody solely based on its sequence. Two major obstacles are the lack of appropriate models and the inaccessibility of datasets for model training. In this study, we curated >5,000 influenza hemagglutinin (HA) antibodies by mining research publications and patents, which revealed many distinct sequence features between antibodies to HA head and stem domains. We then leveraged this dataset to develop a lightweight memory B cell language model (mBLM) for sequence-based antibody specificity prediction. Model explainability analysis showed that mBLM could identify key sequence features of HA stem antibodies. Additionally, by applying mBLM to HA antibodies with unknown epitopes, we discovered and experimentally validated many HA stem antibodies. Overall, this study not only advances our molecular understanding of the antibody response to the influenza virus but also provides a valuable resource for applying deep learning to antibody research.

Rapid synthesis and screening of natively paired antibodies against influenza hemagglutinin stem via oPool+ display

Antibody discovery is crucial for developing therapeutics and vaccines as well as understanding adaptive immunity. However, the lack of approaches to synthesize antibodies with defined sequences in a high-throughput manner represents a major bottleneck in antibody discovery. Here, we presented oPool+ display, which combines oligo pool synthesis and mRNA display to construct and characterize many natively paired antibodies in parallel. As a proof-of-concept, we applied oPool+ display to rapidly screen the binding activity of >300 natively paired influenza hemagglutinin (HA) antibodies against the conserved HA stem domain. Structural analysis of 16.ND.92, one of the identified HA stem antibodies, revealed a unique binding mode distinct from other known broadly neutralizing HA stem antibodies with convergent sequence features. Yet, despite such differences, 16.ND.92 remained broadly reactive and conferred in vivo protection. Overall, this study not only established an experimental platform that can be applied in both research and therapeutics to accelerate antibody discovery, but also provides molecular insights into antibody responses to the influenza HA stem, which is a major target for universal influenza vaccine development.

A library-on-library screen reveals the breadth expansion landscape of a broadly neutralizing betacoronavirus antibody

Broadly neutralizing antibodies (bnAbs) typically evolve cross-reactivity breadth through acquiring somatic hypermutations. While evolution of breadth requires improvement of binding to multiple antigenic variants, most experimental evolution platforms select against only one antigenic variant at a time. In this study, a yeast display library-on-library approach was applied to delineate the affinity maturation of a betacoronavirus bnAb, S2P6, against 27 spike stem helix peptides in a single experiment. Our results revealed that the binding affinity landscape of S2P6 varies among different stem helix peptides. However, somatic hypermutations that confer general improvement in binding affinity across different stem helix peptides could also be identified. We further showed that a key somatic hypermutation for breadth expansion involves long-range interaction. Overall, our work not only provides a proof-of-concept for using a library-on-library approach to analyze the evolution of antibody breadth, but also has important implications for the development of broadly protective vaccines.

Self-adjuvant multiepitope nanovaccine based on ferritin induced long-lasting and effective mucosal immunity against H3N2 and H1N1 viruses in mice

The influenza A virus (IAV) is a ubiquitous and continuously evolving respiratory pathogen. The intranasal vaccination mimicking natural infections is an attractive strategy for controlling IAVs. Multiepitope vaccines accurately targeting multiple conserved domains have the potential to broaden the protective scope of current seasonal influenza vaccines and reduce the risk of generating escape mutants. Here, multiple linear epitopes from the matrix protein 2 ectodomain (M2e) and the hemagglutinin stem domain (HA2) are fused with the Helicobacter pylori ferritin, a self-assembled nanocarrier and mucosal adjuvant, to develop a multiepitope nanovaccine. Through intranasal delivery, the prokaryotically expressed multiepitope nanovaccine elicits long-lasting mucosal immunity, broad humoral immunity, and robust cellular immunity without any adjuvants, and confers complete protection against H3N2 and H1N1 subtypes of IAV in mice. Importantly, this intranasal multiepitope nanovaccine triggers memory B-cell responses, resulting in secretory immunoglobulin A (sIgA) and serum immunoglobulin G (IgG) levels persisting for more than five months post-immunization. Therefore, this intranasal ferritin-based multiepitope nanovaccine represents a promising approach to combating respiratory pathogens.

Widespread impact of immunoglobulin V-gene allelic polymorphisms on antibody reactivity

The ability of the human immune system to generate antibodies to any given antigen can be strongly influenced by immunoglobulin V-gene allelic polymorphisms. However, previous studies have provided only limited examples. Therefore, the prevalence of this phenomenon has been unclear. By analyzing >1,000 publicly available antibody-antigen structures, we show that many V-gene allelic polymorphisms in antibody paratopes are determinants for antibody binding activity. Biolayer interferometry experiments further demonstrate that paratope allelic polymorphisms on both heavy and light chains often abolish antibody binding. We also illustrate the importance of minor V-gene allelic polymorphisms with low frequency in several broadly neutralizing antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza virus. Overall, this study not only highlights the pervasive impact of V-gene allelic polymorphisms on antibody binding but also provides mechanistic insights into the variability of antibody repertoires across individuals, which in turn have important implications for vaccine development and antibody discovery.

An explainable language model for antibody specificity prediction using curated influenza hemagglutinin antibodies

Despite decades of antibody research, it remains challenging to predict the specificity of an antibody solely based on its sequence. Two major obstacles are the lack of appropriate models and inaccessibility of datasets for model training. In this study, we curated a dataset of >5,000 influenza hemagglutinin (HA) antibodies by mining research publications and patents, which revealed many distinct sequence features between antibodies to HA head and stem domains. We then leveraged this dataset to develop a lightweight memory B cell language model (mBLM) for sequence-based antibody specificity prediction. Model explainability analysis showed that mBLM captured key sequence motifs of HA stem antibodies. Additionally, by applying mBLM to HA antibodies with unknown epitopes, we discovered and experimentally validated many HA stem antibodies. Overall, this study not only advances our molecular understanding of antibody response to influenza virus, but also provides an invaluable resource for applying deep learning to antibody research.

Defining and Studying B Cell Receptor and TCR Interactions

BCRs (Abs) and TCRs (or adaptive immune receptors [AIRs]) are the means by which the adaptive immune system recognizes foreign and self-antigens, playing an integral part in host defense, as well as the emergence of autoimmunity. Importantly, the interaction between AIRs and their cognate Ags defies a simple key-in-lock paradigm and is instead a complex many-to-many mapping between an individual's massively diverse AIR repertoire, and a similarly diverse antigenic space. Understanding how adaptive immunity balances specificity with epitopic coverage is a key challenge for the field, and terms such as broad specificity, cross-reactivity, and polyreactivity remain ill-defined and are used inconsistently. In this Immunology Notes and Resources article, a group of experimental, structural, and computational immunologists define commonly used terms associated with AIR binding, describe methodologies to study these binding modes, as well as highlight the implications of these different binding modes for therapeutic design.

Widespread impact of immunoglobulin V gene allelic polymorphisms on antibody reactivity

The ability of human immune system to generate antibodies to any given antigen can be strongly influenced by immunoglobulin V gene (IGV) allelic polymorphisms. However, previous studies have provided only a limited number of examples. Therefore, the prevalence of this phenomenon has been unclear. By analyzing >1,000 publicly available antibody-antigen structures, we show that many IGV allelic polymorphisms in antibody paratopes are determinants for antibody binding activity. Biolayer interferometry experiment further demonstrates that paratope allelic mutations on both heavy and light chain often abolish antibody binding. We also illustrate the importance of minor IGV allelic variants with low frequency in several broadly neutralizing antibodies to SARS-CoV-2 and influenza virus. Overall, this study not only highlights the pervasive impact of IGV allelic polymorphisms on antibody binding, but also provides mechanistic insights into the variability of antibody repertoires across individuals, which in turn have important implications for vaccine development and antibody discovery.

Application of germline antibody features to vaccine development, antibody discovery, antibody optimization and disease diagnosis

Although the efficacy and commercial success of vaccines and therapeutic antibodies have been tremendous, designing and discovering new drug candidates remains a labor-, time- and cost-intensive endeavor with high risks. The main challenges of vaccine development are inducing a strong immune response in broad populations and providing effective prevention against a group of highly variable pathogens. Meanwhile, antibody discovery faces several great obstacles, especially the blindness in antibody screening and the unpredictability of the developability and druggability of antibody drugs. These challenges are largely due to poorly understanding of germline antibodies and the antibody responses to pathogen invasions. Thanks to the recent developments in high-throughput sequencing and structural biology, we have gained insight into the germline immunoglobulin (Ig) genes and germline antibodies and then the germline antibody features associated with antigens and disease manifestation. In this review, we firstly outline the broad associations between germline antibodies and antigens. Moreover, we comprehensively review the recent applications of antigen-specific germline antibody features, physicochemical properties-associated germline antibody features, and disease manifestation-associated germline antibody features on vaccine development, antibody discovery, antibody optimization, and disease diagnosis. Lastly, we discuss the bottlenecks and perspectives of current and potential applications of germline antibody features in the biotechnology field.

Evolution of Indian Influenza A (H1N1) Hemagglutinin Strains: A Comparative Analysis of the Pandemic Californian HA Strain

The need for a vaccine/inhibitor design has become inevitable concerning the emerging epidemic and pandemic viral infections, and the recent outbreak of the influenza A (H1N1) virus is one such example. From 2009 to 2018, India faced severe fatalities due to the outbreak of the influenza A (H1N1) virus. In this study, the potential features of reported Indian H1N1 strains are analyzed in comparison with their evolutionarily closest pandemic strain, A/California/04/2009. The focus is laid on one of its surface proteins, hemagglutinin (HA), which imparts a significant role in attacking the host cell surface and its entry. The extensive analysis performed, in comparison with the A/California/04/2009 strain, revealed significant point mutations in all Indian strains reported from 2009 to 2018. Due to these mutations, all Indian strains disclosed altered features at the sequence and structural levels, which are further presumed to be associated with their functional diversity as well. The mutations observed with the 2018 HA sequence such as S91R, S181T, S200P, I312V, K319T, I419M, and E523D might improve the fitness of the virus in a new host and environment. The higher fitness and decreased sequence similarity of mutated strains may compromise therapeutic efficacy. In particular, the mutations observed commonly, such as serine-to-threonine, alanine-to-threonine, and lysine-to-glutamine at various regions, alter the physico-chemical features of receptor-binding domains, N-glycosylation, and epitope-binding sites when compared with the reference strain. Such mutations render diversity among all Indian strains, and the structural and functional characterization of these strains becomes inevitable. In this study, we observed that mutational drift results in the alteration of the receptor-binding domain, the generation of new variant N-glycosylation along with novel epitope-binding sites, and modifications at the structural level. Eventually, the pressing need to develop potentially distinct next-generation therapeutic inhibitors against the HA strains of the Indian influenza A (H1N1) virus is also highlighted here.

Hierarchical sequence-affinity landscapes shape the evolution of breadth in an anti-influenza receptor binding site antibody

Broadly neutralizing antibodies (bnAbs) that neutralize diverse variants of a particular virus are of considerable therapeutic interest. Recent advances have enabled us to isolate and engineer these antibodies as therapeutics, but eliciting them through vaccination remains challenging, in part due to our limited understanding of how antibodies evolve breadth. Here, we analyze the landscape by which an anti-influenza receptor binding site (RBS) bnAb, CH65, evolved broad affinity to diverse H1 influenza strains. We do this by generating an antibody library of all possible evolutionary intermediates between the unmutated common ancestor (UCA) and the affinity-matured CH65 antibody and measure the affinity of each intermediate to three distinct H1 antigens. We find that affinity to each antigen requires a specific set of mutations - distributed across the variable light and heavy chains - that interact non-additively (i.e., epistatically). These sets of mutations form a hierarchical pattern across the antigens, with increasingly divergent antigens requiring additional epistatic mutations beyond those required to bind less divergent antigens. We investigate the underlying biochemical and structural basis for these hierarchical sets of epistatic mutations and find that epistasis between heavy chain mutations and a mutation in the light chain at the V_H-V_L interface is essential for binding a divergent H1. Collectively, this is the first work to comprehensively characterize epistasis between heavy and light chain mutations and shows that such interactions are both strong and widespread. Together with our previous study analyzing a different class of anti-influenza antibodies, our results implicate epistasis as a general feature of antibody sequence-affinity landscapes that can potentiate and constrain the evolution of breadth.

A large-scale systematic survey reveals recurring molecular features of public antibody responses to SARS-CoV-2

Global research to combat the COVID-19 pandemic has led to the isolation and characterization of thousands of human antibodies to the SARS-CoV-2 spike protein, providing an unprecedented opportunity to study the antibody response to a single antigen. Using the information derived from 88 research publications and 13 patents, we assembled a dataset of ∼8,000 human antibodies to the SARS-CoV-2 spike protein from >200 donors. By analyzing immunoglobulin V and D gene usages, complementarity-determining region H3 sequences, and somatic hypermutations, we demonstrated that the common (public) responses to different domains of the spike protein were quite different. We further used these sequences to train a deep-learning model to accurately distinguish between the human antibodies to SARS-CoV-2 spike protein and those to influenza hemagglutinin protein. Overall, this study provides an informative resource for antibody research and enhances our molecular understanding of public antibody responses.

Structure of an influenza group 2-neutralizing antibody targeting the hemagglutinin stem supersite

Several influenza antibodies with broad group 2 neutralization have recently been isolated. Here, we analyze the structure, class, and binding of one of these antibodies from an H7N9 vaccine trial, 315-19-1D12. The cryo-EM structure of 315-19-1D12 Fab in complex with the hemagglutinin (HA) trimer revealed the antibody to recognize the helix A region of the HA stem, at the supersite of vulnerability recognized by group 1-specific and by cross-group-neutralizing antibodies. 315-19-1D12 was derived from HV1-2 and KV2-28 genes and appeared to form a new antibody class. Bioinformatic analysis indicated its group 2 neutralization specificity to be a consequence of four key residue positions. We specifically tested the impact of the group 1-specific N33 glycan, which decreased but did not abolish group 2 binding of 315-19-1D12. Overall, this study highlights the recognition of a broad group 2-neutralizing antibody, revealing unexpected diversity in neutralization specificity for antibodies that recognize the HA stem supersite.

A large-scale systematic survey of SARS-CoV-2 antibodies reveals recurring molecular features

In the past two years, the global research in combating COVID-19 pandemic has led to isolation and characterization of numerous human antibodies to the SARS-CoV-2 spike. This enormous collection of antibodies provides an unprecedented opportunity to study the antibody response to a single antigen. From mining information derived from 88 research publications and 13 patents, we have assembled a dataset of ∼8,000 human antibodies to the SARS-CoV-2 spike from >200 donors. Analysis of antibody targeting of different domains of the spike protein reveals a number of common (public) responses to SARS-CoV-2, exemplified via recurring IGHV/IGK(L)V pairs, CDR H3 sequences, IGHD usage, and somatic hypermutation. We further present a proof-of-concept for prediction of antigen specificity using deep learning to differentiate sequences of antibodies to SARS-CoV-2 spike and to influenza hemagglutinin. Overall, this study not only provides an informative resource for antibody and vaccine research, but fundamentally advances our molecular understanding of public antibody responses to a viral pathogen.

Germline IGHV3-53-encoded RBD-targeting neutralizing antibodies are commonly present in the antibody repertoires of COVID-19 patients

Monoclonal antibodies (mAbs) encoded by IGHV3-53 (VH3-53) targeting the spike receptor-binding domain (RBD) have been isolated from different COVID-19 patients. However, the existence and prevalence of shared VH3-53-encoded antibodies in the antibody repertoires is not clear. Using antibody repertoire sequencing, we found that the usage of VH3-53 increased after SARS-CoV-2 infection. A highly shared VH3-53-J6 clonotype was identified in 9 out of 13 COVID-19 patients. This clonotype was derived from convergent gene rearrangements with few somatic hypermutations and was evolutionary conserved. We synthesized 34 repertoire-deduced novel VH3-53-J6 heavy chains and paired with a common IGKV1-9 light chain to produce recombinant mAbs. Most of these recombinant mAbs (23/34) possess RBD binding and virus-neutralizing activities, and recognize ACE2 binding site via the same molecular interface. Our computational analysis, validated by laboratory experiments, revealed that VH3-53 antibodies targeting RBD are commonly present in COVID-19 patients’ antibody repertoires, indicating many people have germline-like precursor sequences to rapidly generate SARS-CoV-2 neutralizing antibodies. Moreover, antigen-specific mAbs can be digitally obtained through antibody repertoire sequencing and computational analysis.

Sequence-Signature Optimization Enables Improved Identification of Human HV6-1-Derived Class Antibodies That Neutralize Diverse Influenza A Viruses

Sequence signatures of multidonor broadly neutralizing influenza antibodies can be used to quantify the prevalence of B cells with virus-neutralizing potential to accelerate development of broadly protective vaccine strategies. Antibodies of the same class share similar recognition modes and developmental pathways, and several antibody classes have been identified that neutralize diverse group 1- and group 2-influenza A viruses and have been observed in multiple human donors. One such multidonor antibody class, the HV6-1-derived class, targets the stem region of hemagglutinin with extraordinary neutralization breadth. Here, we use an iterative process to combine informatics, biochemical, and structural analyses to delineate an improved sequence signature for HV6-1-class antibodies. Based on sequence and structure analyses of known HV6-1 class antibodies, we derived a more inclusive signature (version 1), which we used to search for matching B-cell transcripts from published next-generation sequencing datasets of influenza vaccination studies. We expressed selected antibodies, evaluated their function, and identified amino acid-level requirements from which to refine the sequence signature (version 2). The cryo-electron microscopy structure for one of the signature-identified antibodies in complex with hemagglutinin confirmed motif recognition to be similar to known HV6-1-class members, MEDI8852 and 56.a.09, despite differences in recognition-loop length. Threading indicated the refined signature to have increased accuracy, and signature-identified heavy chains, when paired with the light chain of MEDI8852, showed neutralization comparable to the most potent members of the class. Incorporating sequences of additional class members thus enables an improved sequence signature for HV6-1-class antibodies, which can identify class members with increased accuracy.

Grafting Methionine on 1F1 Ab Increases the Broad-Activity on HA Structural-Conserved Residues of H1, H2, and H3 Influenza a Viruses

A high level of mutation enables the influenza A virus to resist antibiotics previously effective against the influenza A virus. A portion of the structure of hemagglutinin HA is assumed to be well-conserved to maintain its role in cellular fusion, and the structure tends to be more conserved than sequence. We designed peptide inhibitors to target the conserved residues on the HA surface, which were identified based on structural alignment. Most of the conserved and strongly similar residues are located in the receptor-binding and esterase regions on the HA1 domain In a later step, fragments of anti-HA antibodies were gathered and screened for the binding ability to the found conserved residues. As a result, Methionine amino acid got the best docking score within the −2.8 Å radius of Van der Waals when it is interacting with Tyrosine, Arginine, and Glutamic acid. Then, the binding affinity and spectrum of the fragments were enhanced by grafting hotspot amino acid into the fragments to form peptide inhibitors. Our peptide inhibitor was able to form in silico contact with a structurally conserved region across H1, H2, and H3 HA, with the binding site at the boundary between HA1 and HA2 domains, spreading across different monomers, suggesting a new target for designing broad-spectrum antibody and vaccine. This research presents an affordable method to design broad-spectrum peptide inhibitors using fragments of an antibody as a scaffold.

Structural Biology of Influenza Hemagglutinin: An Amaranthine Adventure

Hemagglutinin (HA) glycoprotein is an important focus of influenza research due to its role in antigenic drift and shift, as well as its receptor binding and membrane fusion functions, which are indispensable for viral entry. Over the past four decades, X-ray crystallography has greatly facilitated our understanding of HA receptor binding, membrane fusion, and antigenicity. The recent advances in cryo-EM have further deepened our comprehension of HA biology. Since influenza HA constantly evolves in natural circulating strains, there are always new questions to be answered. The incessant accumulation of knowledge on the structural biology of HA over several decades has also facilitated the design and development of novel therapeutics and vaccines. This review describes the current status of the field of HA structural biology, how we got here, and what the next steps might be.