Immunoglobulin germline gene polymorphisms influence the function of SARS-CoV-2 neutralizing antibodies

Construction of a variable fragment (Fv)-immunoglobulin A (IgA) anti-receptor binding domain (RBD) SARS-CoV-2 library based on IgA from Indonesian COVID-19 survivors

Despite entering the post-pandemic phase, SARS-CoV-2 remains a treatment challenge due to evolving mutations and immune evasion, leading to the emergence of antibody-resistant variants. This study aims to computationally construct a human Fv against various emerged variants of SARS-CoV-2 based on IgA sequences from Indonesian COVID-19 survivors. Survivor's saliva and plasma were purified using affinity chromatography to isolate anti-SARS-CoV-2 IgA. The IgA components, heavy and light chains, were isolated using SDS-PAGE and confirmed by Western Blot. They were extracted, digested with trypsin and chymotrypsin, and sequenced using LC MS/MS. Full Fvs were constructed based on IgA sequence obtained and covered with database and reference sequences to generate an Fv Library. The selection of the Fv Library was performed based on modelling, developability, and molecular docking analysis against various RBD variants. The study identified 9 potential Fvs with strong binding affinities to RBD-SARS-CoV-2 across all variants with RMSD values of CDR and Framework of Fv model structures <0.5 Å and developability scores within the safe therapeutic range. FVIGA0289, one of the top candidates, had binding affinities (ΔG) of -17.5, -16.3, -15.6, -16.6, -17.4, and -17.6 kcal/mol for the Wuhan, alpha, beta, gamma, delta, and omicron (XBB.1.5) variants, respectively. In conclusion, the use of antibody information isolated from Indonesian patients has successfully facilitated the computational construction of IgA-based Fv candidates with strong binding to multiple SARS-CoV-2 variants, supported by promising structural models and developability.

Vaccination of nonhuman primates elicits a broadly neutralizing antibody lineage targeting a quaternary epitope on the HIV-1 Env trimer

The elicitation of cross-neutralizing antibodies to the HIV-1 envelope glycoprotein (Env) by vaccination remains a major challenge. Here, we immunized previously Env-immunized nonhuman primates with a series of near-native trimers that possessed N-glycan deletions proximal to the conserved CD4 binding site (CD4bs) to focus B cells to this region. Following heterologous boosting with fully glycosylated trimers, we detected tier 2 cross-neutralizing activity in the serum of several animals. Isolation of 185 matched heavy- and light-chain sequences from Env-binding memory B cells from an early responder identified a broadly neutralizing antibody lineage, LJF-0034, which neutralized nearly 70% of an 84-member HIV-1 global panel. High-resolution cryoelectron microscopy (cryo-EM) structures revealed a bifurcated binding mode that bridged the CD4bs to V3 across the gp120:120 interface on two adjacent protomers, evading the proximal N276 glycan impediment to the CD4bs, allowing neutralization breadth. This quaternary epitope defines a potential target for future HIV-1 vaccine development.

A Broad Survey and Functional Analysis of Immunoglobulin Loci Variation in Rhesus Macaques

Rhesus macaques (RMs) are a vital model for studying human disease and invaluable to pre-clinical vaccine research, particularly for the study of broadly neutralizing antibody responses. Such studies require robust genetic resources for antibody-encoding genes within the immunoglobulin (IG) loci. The complexity of the IG loci has historically made them challenging to characterize accurately. To address this, we developed novel experimental and computational methodologies to generate the largest collection to date of integrated antibody repertoire and long-read genomic sequencing data in 106 Indian origin RMs. We created a comprehensive resource of IG heavy and light chain variable (V), diversity (D), and joining (J) alleles, as well as leader, intronic, and recombination signal sequences (RSSs), including the curation of 1474 novel alleles, unveiling tremendous diversity, and expanding existing IG allele sets by 60%. This publicly available, continually updated resource (https://vdjbase.org/reference_book/Rhesus_Macaque) provides the foundation for advancing RM immunogenomics, vaccine discovery, and translational research.

An allelic atlas of immunoglobulin heavy chain variable regions reveals antibody binding epitope preference resilient to SARS-CoV-2 mutation escape

Background

Although immunoglobulin (Ig) alleles play a pivotal role in the antibody response to pathogens, research to understand their role in the humoral immune response is still limited.

Methods

We retrieved the germline sequences for the IGHV from the IMGT database to illustrate the amino acid polymorphism present within germline sequences of IGHV genes. We aassembled the sequences of IgM and IgD repertoire from 130 people to investigate the genetic variations in the population. A dataset comprising 10,643 SARS-CoV-2 spike-specific antibodies, obtained from COV-AbDab, was compiled to assess the impact of SARS-CoV-2 infection on allelic gene utilization. Binding affinity and neutralizing activity were determined using bio-layer interferometry and pseudovirus neutralization assays. Primary docking was performed using ZDOCK (3.0.2) to generate the initial conformation of the antigen-antibody complex, followed by simulations of the complete conformations using Rosetta SnugDock software. The original and simulated structural conformations were visualized and presented using ChimeraX (v1.5).

Results

We present an allelic atlas of immunoglobulin heavy chain (IgH) variable regions, illustrating the diversity of allelic variants across 33 IGHV family germline sequences by sequencing the IgH repertoire of in the population. Our comprehensive analysis of SARS-CoV-2 spike-specific antibodies revealed the preferential use of specific Ig alleles among these antibodies. We observed an association between Ig alleles and antibody binding epitopes. Different allelic genotypes binding to the same RBD epitope on the spike show different neutralizing potency and breadth. We found that antibodies carrying the IGHV1-69*02 allele tended to bind to the RBD E2.2 epitope. The antibodies carrying G50 and L55 amino acid residues exhibit potential enhancements in binding affinity and neutralizing potency to SARS-CoV-2 variants containing the L452R mutation on RBD, whereas R50 and F55 amino acid residues tend to have reduced binding affinity and neutralizing potency. IGHV2-5*02 antibodies using the D56 allele bind to the RBD D2 epitope with greater binding and neutralizing potency due to the interaction between D56 on HCDR2 and K444 on RBD of most Omicron subvariants. In contrast, IGHV2-5*01 antibodies using the N56 allele show increased binding resistance to the K444T mutation on RBD.

Discussion

This study provides valuable insights into humoral immune responses from the perspective of Ig alleles and population genetics. These findings underscore the importance of Ig alleles in vaccine design and therapeutic antibody development.

Real-time estimation of immunological responses against emerging SARS-CoV-2 variants in the UK: a mathematical modelling study

BACKGROUND

The emergence of SARS-CoV-2 variants and COVID-19 vaccination have resulted in complex exposure histories. Rapid assessment of the effects of these exposures on neutralising antibodies against SARS-CoV-2 infection is crucial for informing vaccine strategy and epidemic management. We aimed to investigate heterogeneity in individual-level and population-level antibody kinetics to emerging variants by previous SARS-CoV-2 exposure history, to examine implications for real-time estimation, and to examine the effects of vaccine-campaign timing.

METHODS

Our Bayesian hierarchical model of antibody kinetics estimated neutralising-antibody trajectories against a panel of SARS-CoV-2 variants quantified with a live virus microneutralisation assay and informed by individual-level COVID-19 vaccination and SARS-CoV-2 infection histories. Antibody titre trajectories were modelled with a piecewise linear function that depended on the key biological quantities of an initial titre value, time the peak titre is reached, set-point time, and corresponding rates of increase and decrease for gradients between two timing parameters. All process parameters were estimated at both the individual level and the population level. We analysed data from participants in the University College London Hospitals-Francis Crick Institute Legacy study cohort (NCT04750356) who underwent surveillance for SARS-CoV-2 either through asymptomatic mandatory occupational health screening once per week between April 1, 2020, and May 31, 2022, or symptom-based testing between April 1, 2020, and Feb 1, 2023. People included in the Legacy study were either Crick employees or health-care workers at three London hospitals, older than 18 years, and gave written informed consent. Legacy excluded people who were unable or unwilling to give informed consent and those not employed by a qualifying institution. We segmented data to include vaccination events occurring up to 150 days before the emergence of three variants of concern: delta, BA.2, and XBB 1.5. We split the data for each wave into two categories: real-time and retrospective. The real-time dataset contained neutralising-antibody titres collected up to the date of emergence in each wave; the retrospective dataset contained all samples until the next SARS-CoV-2 exposure of each individual, whether vaccination or infection.

FINDINGS

We included data from 335 participants in the delta wave analysis, 223 (67%) of whom were female and 112 (33%) of whom were male (median age 40 years, IQR 22-58); data from 385 participants in the BA.2 wave analysis, 271 (70%) of whom were female and 114 (30%) of whom were male (41 years, 22-60); and data from 248 participants in the XBB 1.5 wave analysis, 191 (77%) of whom were female, 56 (23%) of whom were male, and one (<1%) of whom preferred not to say (40 years, 21-59). Overall, we included 968 exposures (vaccinations) across 1895 serum samples in the model. For the delta wave, we estimated peak titre values as 490·0 IC50 (95% credible interval 224·3-1515·9) for people with no previous infection and as 702·4 IC50 (300·8-2322·7) for people with a previous infection before omicron; the delta wave did not include people with a previous omicron infection. For the BA.2 wave, we estimated peak titre values as 858·1 IC50 (689·8-1363·2) for people with no previous infection, 1020·7 IC50 (725·9-1722·6) for people with a previous infection before omicron, and 1422·0 IC50 (679·2-3027·3) for people with a previous omicron infection. For the XBB 1.5 wave, we estimated peak titre values as 703·2 IC50 (415·0-3197·8) for people with no previous infection, 1215·9 IC50 (511·6-7338·7) for people with a previous infection before omicron, and 1556·3 IC50 (757·2-7907·9) for people with a previous omicron infection.

INTERPRETATION

Our study shows the feasibility of real-time estimation of antibody kinetics before SARS-CoV-2 variant emergence. This estimation is valuable for understanding how specific combinations of SARS-CoV-2 exposures influence antibody kinetics and for examining how COVID-19 vaccination-campaign timing could affect population-level immunity to emerging variants.

FUNDING

Wellcome Trust, National Institute for Health Research University College London Hospitals Biomedical Research Centre, UK Research and Innovation, UK Medical Research Council, Francis Crick Institute, and Genotype-to-Phenotype National Virology Consortium.

Ultrasensitive allele inference from immune repertoire sequencing data with MiXCR

Allelic variability in the adaptive immune receptor loci, which harbor the gene segments that encode B cell and T cell receptors (BCR/TCR), is of critical importance for immune responses to pathogens and vaccines. Adaptive immune receptor repertoire sequencing (AIRR-seq) has become widespread in immunology research making it the most readily available source of information about allelic diversity in immunoglobulin (IG) and T cell receptor (TR) loci. Here, we present a novel algorithm for extrasensitive and specific variable (V) and joining (J) gene allele inference, allowing the reconstruction of individual high-quality gene segment libraries. The approach can be applied for inferring allelic variants from peripheral blood lymphocyte BCR and TCR repertoire sequencing data, including hypermutated isotype-switched BCR sequences, thus allowing high-throughput novel allele discovery from a wide variety of existing data sets. The developed algorithm is a part of the MiXCR software. We demonstrate the accuracy of this approach using AIRR-seq paired with long-read genomic sequencing data, comparing it to a widely used algorithm, TIgGER. We applied the algorithm to a large set of IG heavy chain (IGH) AIRR-seq data from 450 donors of ancestrally diverse population groups, and to the largest reported full-length TCR alpha and beta chain (TRA and TRB) AIRR-seq data set, representing 134 individuals. This allowed us to assess the genetic diversity within the IGH, TRA, and TRB loci in different populations and to establish a database of alleles of V and J genes inferred from AIRR-seq data and their population frequencies with free public access through VDJ.online database.

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

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

Scifer: An R/Bioconductor package for large-scale integration of Sanger sequencing and flow cytometry data of index-sorted single cells

Sanger sequencing remains widely used in various experimental contexts, often in combination with flow cytometry for indexing specific cell populations. However, existing software lacks the capability to automate quality control (QC) of raw Sanger sequencing data and integrate it with flow cytometry information on a large scale. Here, we introduce scifer, an R package now available in the latest release of Bioconductor (3.20) showcasing its effectiveness in seamlessly integrating these types of data as demonstrated by analyses of B cell and T cell receptor sequences. Scifer preprocesses raw data from index sorts and immune receptor Sanger sequencing. It identifies high-quality sequences based on selected parameters, such as length, Phred scores, and heavy-chain complementarity-determining region 3 (HCDR3) quality. As a result, the quality of germline assignments is significantly increased and spurious variable gene mutations are reduced. Scifer is automated and can process thousands of sequences in less than an hour. Its output provides quality control reports, FASTA files, summarized tables, and electropherograms for manual inspection. In summary, scifer is a user-friendly software that speeds up the analysis of immune receptor repertoire sequences, offering wide applicability.

An unbiased comparison of immunoglobulin sequence aligners

Adaptive Immune Receptor Repertoire sequencing (AIRR-seq) is critical for our understanding of the adaptive immune system's dynamics in health and disease. Reliable analysis of AIRR-seq data depends on accurate rearranged immunoglobulin (Ig) sequence alignment. Various Ig sequence aligners exist, but there is no unified benchmarking standard representing the complexities of AIRR-seq data, obscuring objective comparisons of aligners across tasks. Here, we introduce GenAIRR, a modular simulation framework for generating Ig sequences alongside their ground truths. GenAIRR realistically simulates the intricacies of V(D)J recombination, somatic hypermutation, and an array of sequence corruptions. We comprehensively assessed prominent Ig sequence aligners across various metrics, unveiling unique performance characteristics for each aligner. The GenAIRR-produced datasets, combined with the proposed rigorous evaluation criteria, establish a solid basis for unbiased benchmarking of immunogenetics computational tools. It sets up the ground for further improving the crucial task of Ig sequence alignment, ultimately enhancing our understanding of adaptive immunity.

The peculiar features, diversity and impact of citrulline-reactive autoantibodies

Since entering the stage 25 years ago as a highly specific serological biomarker for rheumatoid arthritis, anti-citrullinated protein antibodies (ACPAs) have been a topic of extensive research. This hallmark B cell response arises years before disease onset, displays interpatient autoantigen variability, and is associated with poor clinical outcomes. Technological and scientific advances have revealed broad clonal diversity and intriguing features including high levels of somatic hypermutation, variable-domain N-linked glycosylation, hapten-like peptide interactions, and clone-specific multireactivity to citrullinated, carbamylated and acetylated epitopes. ACPAs have been found in different isotypes and subclasses, in both circulation and tissue, and are secreted by both plasmablasts and long-lived plasma cells. Notably, although some disease-promoting features have been reported, results now demonstrate that certain monoclonal ACPAs therapeutically block arthritis and inflammation in mouse models. A wealth of functional studies using patient-derived polyclonal and monoclonal antibodies have provided evidence for pathogenic and protective effects of ACPAs in the context of arthritis. To understand the roles of ACPAs, one needs to consider their immunological properties by incorporating different facets such as rheumatoid arthritis B cell biology, environmental triggers and chronic antigen exposure. The emerging picture points to a complex role of citrulline-reactive autoantibodies, in which the diversity and dynamics of antibody clones could determine clinical progression and manifestations.

Structural basis of broad SARS-CoV-2 cross-neutralization by affinity-matured public antibodies

Descendants of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant now account for almost all SARS-CoV-2 infections. The Omicron variant and its sublineages have spike glycoproteins that are highly diverged from the pandemic founder and first-generation vaccine strain, resulting in significant evasion from monoclonal antibody therapeutics and vaccines. Understanding how commonly elicited antibodies can broaden to cross-neutralize escape variants is crucial. We isolate IGHV3-53, using "public" monoclonal antibodies (mAbs) from an individual 7 months post infection with the ancestral virus and identify antibodies that exhibit potent and broad cross-neutralization, extending to the BA.1, BA.2, and BA.4/BA.5 sublineages of Omicron. Deep mutational scanning reveals these mAbs' high resistance to viral escape. Structural analysis via cryoelectron microscopy of a representative broadly neutralizing antibody, CAB-A17, in complex with the Omicron BA.1 spike highlights the structural underpinnings of this broad neutralization. By reintroducing somatic hypermutations into a germline-reverted CAB-A17, we delineate the role of affinity maturation in the development of cross-neutralization by a public class of antibodies.

Multimodal Mass Spectrometry Identifies a Conserved Protective Epitope in S. pyogenes Streptolysin O

An important element of antibody-guided vaccine design is the use of neutralizing or opsonic monoclonal antibodies to define protective epitopes in their native three-dimensional conformation. Here, we demonstrate a multimodal mass spectrometry-based strategy for in-depth characterization of antigen-antibody complexes to enable the identification of protective epitopes using the cytolytic exotoxin Streptolysin O (SLO) from Streptococcus pyogenes as a showcase. We first discovered a monoclonal antibody with an undisclosed sequence capable of neutralizing SLO-mediated cytolysis. The amino acid sequence of both the antibody light and the heavy chain was determined using mass-spectrometry-based de novo sequencing, followed by chemical cross-linking mass spectrometry to generate distance constraints between the antibody fragment antigen-binding region and SLO. Subsequent integrative computational modeling revealed a discontinuous epitope located in domain 3 of SLO that was experimentally validated by hydrogen-deuterium exchange mass spectrometry and reverse engineering of the targeted epitope. The results show that the antibody inhibits SLO-mediated cytolysis by binding to a discontinuous epitope in domain 3, likely preventing oligomerization and subsequent secondary structure transitions critical for pore-formation. The epitope is highly conserved across >98% of the characterized S. pyogenes isolates, making it an attractive target for antibody-based therapy and vaccine design against severe streptococcal infections.

Adaptive immune receptor germline gene variation

Recognition of antigens by T cell receptors (TCRs) and B cell receptors (BCRs) is a key step in lymphocyte activation. T and B cells mediate adaptive immune responses, which protect us against infections and provide immunological memory, and also, in some instances, drive pathogenic responses in autoimmune diseases. TCRs and BCRs are encoded within loci that are known to be genetically diverse. However, the extent and functional impact of this variation, both in humans and model animals used in immunological research, remain largely unknown. Experimental and genetic evidence has demonstrated that the complementarity determining regions 1 and 2 (HCDR1 and HCDR2), encoded by the variable (V) region of TCRs and BCRs, also often make critical contacts with the targeted antigen. Thus, knowledge about allelic variation in the genes encoding TCRs and BCRs is critically important for understanding adaptive immune responses in outbred populations and to define responder and non-responder phenotypes.

Novel Omicron Variants Enhance Anchored Recognition of TMEM106B: A New Pathway for SARS-CoV-2 Cellular Invasion

The recent discovery that TMEM106B serves as a receptor mediating ACE2-independent SARS-CoV-2 entry into cells deserves attention, especially in the background of the frequent emergence of mutant strains. Here, the structure-dynamic features of this novel pathway are dissected deeply. Our investigation revealed that the large loop (RBD@471-491) could anchor TMEM106B, which was then firmly locked by another loop (RBD@444-451). The novel and widely disseminated Omicron variants (BA.2.86/EG.5.1) affect the anchoring recognition of proteins, with BA.2.86 being more likely to impact cells with limited or undetectable ACE2 expression. The large loop of the EG.5.1 variant captures TMEM106B poorly due to impaired electrostatic complementarity. Furthermore, we emphasize that antibody design against these two loops could enhance the protection of ACE2 low-expressing cells according to the alanine scanning mutagenesis of multiple antibodies. We hope this study will provide a novel perspective for the prevention and treatment against this new viral invasion pathway.

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.

COVID-19-Related Age Profiles for SARS-CoV-2 Variants in England and Wales and States of the USA (2020 to 2022): Impact on All-Cause Mortality

Since 2020, COVID-19 has caused serious mortality around the world. Given the ambiguity in establishing COVID-19 as the direct cause of death, we first investigate the effects of age and sex on all-cause mortality during 2020 and 2021 in England and Wales. Since infectious agents have their own unique age profile for death, we use a 9-year time series and several different methods to adjust single-year-of-age deaths in England and Wales during 2019 (the pre-COVID-19 base year) to a pathogen-neutral single-year-of-age baseline. This adjusted base year is then used to confirm the widely reported higher deaths in males for most ages above 43 in both 2020 and 2021. During 2020 (+COVID-19 but no vaccination), both male and female population-adjusted deaths significantly increased above age 35. A significant reduction in all-cause mortality among both males and females aged 75+ could be demonstrated in 2021 during the widespread COVID-19 vaccination period; however, deaths below age 75 progressively increased. This finding arises from a mix of vaccination coverage and year-of-age profiles of deaths for the different SARS-CoV-2 variants. In addition, specific effects of age around puberty were demonstrated, where females had higher deaths than males. There is evidence that year-of-birth cohorts may also be involved, indicating that immune priming to specific pathogen outbreaks in the past may have led to lower deaths for some birth cohorts. To specifically identify the age profile for the COVID-19 variants from 2020 to 2023, we employ the proportion of total deaths at each age that are potentially due to or 'with' COVID-19. The original Wuhan strain and the Alpha variant show somewhat limited divergence in the age profile, with the Alpha variant shifting to a moderately higher proportion of deaths below age 84. The Delta variant specifically targeted individuals below age 65. The Omicron variants showed a significantly lower proportion of overall mortality, with a markedly higher relative proportion of deaths above age 65, steeply increasing with age to a maximum around 100 years of age. A similar age profile for the variants can be seen in the age-banded deaths in US states, although they are slightly obscured by using age bands rather than single years of age. However, the US data shows that higher male deaths are greatly dependent on age and the COVID variant. Deaths assessed to be 'due to' COVID-19 (as opposed to 'involving' COVID-19) in England and Wales were especially overestimated in 2021 relative to the change in all-cause mortality. This arose as a by-product of an increase in COVID-19 testing capacity in late 2020. Potential structure-function mechanisms for the age-specificity of SARS-CoV-2 variants are discussed, along with potential roles for small noncoding RNAs (miRNAs). Using data from England, it is possible to show that the unvaccinated do indeed have a unique age profile for death from each variant and that vaccination alters the shape of the age profile in a manner dependent on age, sex, and the variant. The question is posed as to whether vaccines based on different variants carry a specific age profile.

SARS-CoV-2 Omicron BA.1 breakthrough infection drives late remodeling of the memory B cell repertoire in vaccinated individuals

How infection by a viral variant showing antigenic drift impacts a preformed mature human memory B cell (MBC) repertoire remains an open question. Here, we studied the MBC response up to 6 months after SARS-CoV-2 Omicron BA.1 breakthrough infection in individuals previously vaccinated with three doses of the COVID-19 mRNA vaccine. Longitudinal analysis, using single-cell multi-omics and functional analysis of monoclonal antibodies from RBD-specific MBCs, revealed that a BA.1 breakthrough infection mostly recruited pre-existing cross-reactive MBCs with limited de novo response against BA.1-restricted epitopes. Reorganization of clonal hierarchy and new rounds of germinal center reactions, however, combined to maintain diversity and induce progressive maturation of the MBC repertoire against common Hu-1 and BA.1, but not BA.5-restricted, SARS-CoV-2 Spike RBD epitopes. Such remodeling was further associated with a marked improvement in overall neutralizing breadth and potency. These findings have fundamental implications for the design of future vaccination booster strategies.

IGHV allele similarity clustering improves genotype inference from adaptive immune receptor repertoire sequencing data

In adaptive immune receptor repertoire analysis, determining the germline variable (V) allele associated with each T- and B-cell receptor sequence is a crucial step. This process is highly impacted by allele annotations. Aligning sequences, assigning them to specific germline alleles, and inferring individual genotypes are challenging when the repertoire is highly mutated, or sequence reads do not cover the whole V region. Here, we propose an alternative naming scheme for the V alleles, as well as a novel method to infer individual genotypes. We demonstrate the strengths of the two by comparing their outcomes to other genotype inference methods. We validate the genotype approach with independent genomic long-read data. The naming scheme is compatible with current annotation tools and pipelines. Analysis results can be converted from the proposed naming scheme to the nomenclature determined by the International Union of Immunological Societies (IUIS). Both the naming scheme and the genotype procedure are implemented in a freely available R package (PIgLET https://bitbucket.org/yaarilab/piglet). To allow researchers to further explore the approach on real data and to adapt it for their uses, we also created an interactive website (https://yaarilab.github.io/IGHV_reference_book).

Challenges and Progress in Designing Broad-Spectrum Vaccines Against Rapidly Mutating Viruses

Viruses evolve to evade prior immunity, causing significant disease burden. Vaccine effectiveness deteriorates as pathogens mutate, requiring redesign. This is a problem that has grown worse due to population increase, global travel, and farming practices. Thus, there is significant interest in developing broad-spectrum vaccines that mitigate disease severity and ideally inhibit disease transmission without requiring frequent updates. Even in cases where vaccines against rapidly mutating pathogens have been somewhat effective, such as seasonal influenza and SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2), designing vaccines that provide broad-spectrum immunity against routinely observed viral variation remains a desirable but not yet achieved goal. This review highlights the key theoretical advances in understanding the interplay between polymorphism and vaccine efficacy, challenges in designing broad-spectrum vaccines, and technology advances and possible avenues forward. We also discuss data-driven approaches for monitoring vaccine efficacy and predicting viral escape from vaccine-induced protection. In each case, we consider illustrative examples in vaccine development from influenza, SARS-CoV-2, and HIV (human immunodeficiency virus)-three examples of highly prevalent rapidly mutating viruses with distinct phylogenetics and unique histories of vaccine technology development.

Differences among epitopes recognized by neutralizing antibodies induced by SARS-CoV-2 infection or COVID-19 vaccination

SARS-CoV-2 has gradually acquired amino acid substitutions in its S protein that reduce the potency of neutralizing antibodies, leading to decreased vaccine efficacy. Here, we attempted to obtain mutant viruses by passaging SARS-CoV-2 in the presence of plasma samples from convalescent patients or vaccinees to determine which amino acid substitutions affect the antigenicity of SARS-CoV-2. Several amino acid substitutions in the S2 region, as well as the N-terminal domain (NTD) and receptor-binding domain (RBD), affected the neutralization potency of plasma samples collected from vaccinees, indicating that amino acid substitutions in the S2 region as well as those in the NTD and RBD affect neutralization by vaccine-induced antibodies. Furthermore, the neutralizing potency of vaccinee plasma samples against mutant viruses we obtained or circulating viruses differed among individuals. These findings suggest that genetic backgrounds of vaccinees influence the recognition of neutralizing epitopes.

Immunoglobulin repertoire restriction characterizes the serological responses of patients with predominantly antibody deficiency

BACKGROUND

Predominantly antibody deficiency (PAD) is the most common category of inborn errors of immunity and is underpinned by impaired generation of appropriate antibody diversity and quantity. In the clinic, responses are interrogated by assessment of vaccination responses, which is central to many PAD diagnoses. However, the composition of the generated antibody repertoire is concealed from traditional quantitative measures of serological responses. Leveraging modern mass spectrometry-based proteomics (MS-proteomics), it is possible to elaborate the molecular features of specific antibody repertoires, which may address current limitations of diagnostic vaccinology.

OBJECTIVES

We sought to evaluate serum antibody responses in patients with PAD following vaccination with a neo-antigen (severe acute respiratory syndrome coronavirus-2 vaccination) using MS-proteomics.

METHODS

Following severe acute respiratory syndrome coronavirus-2 vaccination, serological responses in individuals with PAD and healthy controls (HCs) were assessed by anti-S1 subunit ELISA and neutralization assays. Purified anti-S1 subunit IgG and IgM was profiled by MS-proteomics for IGHV subfamily usage and somatic hypermutation analysis.

RESULTS

Twelve patients with PAD who were vaccine-responsive were recruited with 11 matched vaccinated HCs. Neutralization and end point anti-S1 titers were lower in PAD. All subjects with PAD demonstrated restricted anti-S1 IgG antibody repertoires, with usage of <5 IGHV subfamilies (median: 3; range 2-4), compared to ≥5 for the 11 HC subjects (P < .001). IGHV3-7 utilization was far less common in patients with PAD than in HCs (2 of 12 vs 10 of 11; P = .001). Amino acid substitutions due to somatic hypermutation per subfamily did not differ between groups. Anti-S1 IgM was present in 64% and 50% of HC and PAD cohorts, respectively, and did not differ significantly between HCs and patients with PAD.

CONCLUSIONS

This study demonstrates the breadth of anti-S1 antibodies elicited by vaccination at the proteome level and identifies stereotypical restriction of IGHV utilization in the IgG repertoire in patients with PAD compared with HC subjects. Despite uniformly pauci-clonal antibody repertoires some patients with PAD generated potent serological responses, highlighting a possible limitation of traditional serological techniques. These findings suggest that IgG repertoire restriction is a key feature of antibody repertoires in PAD.

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.

Frequent use of IGHV3-30-3 in SARS-CoV-2 neutralizing antibody responses

The antibody response to SARS-CoV-2 shows biased immunoglobulin heavy chain variable (IGHV) gene usage, allowing definition of genetic signatures for some classes of neutralizing antibodies. We investigated IGHV gene usage frequencies by sorting spike-specific single memory B cells from individuals infected with SARS-CoV-2 early in the pandemic. From two study participants and 703 spike-specific B cells, the most used genes were IGHV1-69, IGHV3-30-3, and IGHV3-30. Here, we focused on the IGHV3-30 group of genes and an IGHV3-30-3-using ultrapotent neutralizing monoclonal antibody, CAB-F52, which displayed broad neutralizing activity also in its germline-reverted form. IGHV3-30-3 is encoded by a region of the IGH locus that is highly variable at both the allelic and structural levels. Using personalized IG genotyping, we found that 4 of 14 study participants lacked the IGHV3-30-3 gene on both chromosomes, raising the question if other, highly similar IGHV genes could substitute for IGHV3-30-3 in persons lacking this gene. In the context of CAB-F52, we found that none of the tested IGHV3-33 alleles, but several IGHV3-30 alleles could substitute for IGHV3-30-3, suggesting functional redundancy between the highly homologous IGHV3-30 and IGHV3-30-3 genes for this antibody.

Adaptive immune receptor genotyping using the corecount program

We present a new Rep-Seq analysis tool called corecount, for analyzing genotypic variation in immunoglobulin (IG) and T cell receptor (TCR) genes. corecount is highly efficient at identifying V alleles, including those that are infrequently used in expressed repertoires and those that contain 3' end variation that are otherwise refractory to reliable identification during germline inference from expressed libraries. Furthermore, corecount facilitates accurate D and J gene genotyping. The output is highly reproducible and facilitates the comparison of genotypes from multiple individuals, such as those from clinical cohorts. Here, we applied corecount to the genotypic analysis of IgM libraries from 16 individuals. To demonstrate the accuracy of corecount, we Sanger sequenced all the heavy chain IG alleles (65 IGHV, 27 IGHD and 7 IGHJ) from one individual from whom we also produced two independent IgM Rep-seq datasets. Genomic analysis revealed that 5 known IGHV and 2 IGHJ sequences are truncated in current reference databases. This dataset of genomically validated alleles and IgM libraries from the same individual provides a useful resource for benchmarking other bioinformatic programs that involve V, D and J assignments and germline inference, and may facilitate the development of AIRR-Seq analysis tools that can take benefit from the availability of more comprehensive reference databases.