Convergent antibody signatures in human dengue

Human TCR repertoire in cancer

BACKGROUND

T cells, the "superstar" of the immune system, play a crucial role in antitumor immunity. T-cell receptors (TCR) are crucial molecules that enable T cells to identify antigens and start immunological responses. The body has evolved a unique method for rearrangement, resulting in a vast diversity of TCR repertoires. A healthy TCR repertoire is essential for the particular identification of antigens by T cells.

METHODS

In this article, we systematically summarized the TCR creation mechanisms and analysis methodologies, particularly focusing on the application of next-generation sequencing (NGS) technology. We explore the TCR repertoire in health and cancer, and discuss the implications of TCR repertoire analysis in understanding carcinogenesis, cancer progression, and treatment.

RESULTS

The TCR repertoire analysis has enormous potential for monitoring the emergence and progression of malignancies, as well as assessing therapy response and prognosis. The application of NGS has dramatically accelerated our comprehension of TCR diversity and its role in cancer immunity.

CONCLUSIONS

To substantiate the significance of TCR repertoires as biomarkers, more thorough and exhaustive research should be conducted. The TCR repertoire analysis, enabled by advanced sequencing technologies, is poised to become a crucial tool in the future of cancer diagnosis, monitoring, and therapy evaluation.

Antibodies utilizing VL6-57 light chains target a convergent cryptic epitope on SARS-CoV-2 spike protein and potentially drive the genesis of Omicron variants

Continued evolution of SARS-CoV-2 generates variants to challenge antibody immunity established by infection and vaccination. A connection between population immunity and genesis of virus variants has long been suggested but its molecular basis remains poorly understood. Here, we identify a class of SARS-CoV-2 neutralizing public antibodies defined by their shared usage of VL6-57 light chains. Although heavy chains of diverse genotypes are utilized, convergent HCDR3 rearrangements have been observed among these public antibodies to cooperate with germline VL6-57 LCDRs to target a convergent epitope defined by RBD residues S371-S373-S375. Antibody repertoire analysis identifies that this class of VL6-57 antibodies is present in SARS-CoV-2-naive individuals and is clonally expanded in most COVID-19 patients. We confirm that Omicron-specific substitutions at S371, S373 and S375 mediate escape of antibodies of the VL6-57 class. These findings support that this class of public antibodies constitutes a potential immune pressure promoting the introduction of S371L/F-S373P-S375F in Omicron variants. The results provide further molecular evidence to support that antigenic evolution of SARS-CoV-2 is driven by antibody mediated population immunity.

High throughput long-read sequencing of circulating lymphocytes of the evolutionarily distant sea lamprey reveals diversity and common elements of the variable lymphocyte receptor B (VLRB) repertoire

The leucine-rich repeat-based variable lymphocyte receptor B (VLRB) antibody system of jawless vertebrates is capable of generating an antibody repertoire equal to or exceeding the diversity of antibody repertoires of jawed vertebrates. Unlike immunoglobulin-based immune repertoires, the VLRB repertoire diversity is characterized by variable lengths of VLRB encoding transcripts, rendering conventional immunoreceptor repertoire sequencing approaches unsuitable for VLRB repertoire sequencing. Here we demonstrate that long-read single-molecule real-time (SMRT) sequencing (PacBio) approaches permit the efficient large-scale assessment of the VLRB repertoire. We present a computational pipeline for sequence data processing and provide the first repertoire-based analysis of VLRB protein characteristics including properties of its subunits and regions of diversity within each structural leucine-rich repeat subunit. Our study provides a template to explore changes in the VLRB repertoire during immune responses and to establish large scale VLRB repertoire databases for computational approaches aimed at isolating monoclonal VLRB reagents for biomedical research and clinical applications.

Antigen-driven Convergent Evolution of Polysaccharide-specific "DH-less" B Cells in Glycoconjugate Immunized Mice

Glycoconjugate vaccines elicit robust anti-polysaccharide Ab response by recruiting T-cell help. Multiple doses of glycoconjugate vaccine are required to induce long-lasting immunity. The characteristics of anti-polysaccharide Ab response have been reported previously. However, the effect of glycoconjugate booster immunization on anti-polysaccharide and anti-carrier protein Ab repertoire remains poorly understood. In this study, we used clinically relevant pneumococcal capsular polysaccharide type 14 (PCP14) conjugated with cross-reactive material 197 (CRM197) as a model glycoconjugate Ag (PCP14-CRM197). We performed a comprehensive sequence analysis of mouse mAbs generated against PCP14 and CRM197 following immunization with one or three doses of PCP14-CRM197. Analysis of the paired Ig H and L chain transcripts revealed that anti-PCP14 Ab repertoire is extremely restricted. The reoccurrence of five replacement mutations at identical positions in anti-polysaccharide mAbs generated from different mice provided evidence for Ag-driven selection in PCP14-specific B cells. Convergent evolution was observed wherein distinct V(D)J rearrangements resulted in identical or nearly identical CDR3 in anti-PCP14 mAbs. Abs that lacked DH encoded amino acids dominated the anti-PCP14 Ab response. In contrast, anti-CRM197 Ab response was quite diverse, with fewer mutations compared with the anti-PCP14 mAbs, suggesting that conjugation of the polysaccharide to a carrier protein interferes with the development of carrier protein-specific Ab responses. Our findings provide molecular insights into the maturation of Ab responses driven by booster doses of glycoconjugate. This has fundamental implications for the design of glycoconjugate vaccines, especially where the development of Ab response against the carrier protein is also crucial.

Machine-learning-assisted high-throughput identification of potent and stable neutralizing antibodies against all four dengue virus serotypes

Several computational methods have been developed to identify neutralizing antibodies (NAbs) covering four dengue virus serotypes (DENV-1 to DENV-4); however, limitations of the dataset and the resulting performance remain. Here, we developed a new computational framework to predict potent and stable NAbs against DENV-1 to DENV-4 using only antibody (CDR-H3) and epitope sequences as input. Specifically, our proposed computational framework employed sequence-based ML and molecular dynamic simulation (MD) methods to achieve more accurate identification. First, we built a novel dataset (n = 1108) by compiling the interactions of CDR-H3 and epitope sequences with the half maximum inhibitory concentration (IC50) values, which represent neutralizing activities. Second, we achieved an accurately predictive ML model that showed high AUC values of 0.879 and 0.885 by tenfold cross-validation and independent tests, respectively. Finally, our computational framework could be applied to filter approximately 2.5 million unseen antibodies into two final candidates that showed strong and stable binding to all four serotypes. In addition, the most potent and stable candidate (1B3B9_V21) was evaluated for its development potential as a therapeutic agent by molecular docking and MD simulations. This study provides an antibody computational approach to facilitate the high-throughput identification of NAbs and accelerate the development of therapeutic antibodies.

Computational mining of B cell receptor repertoires reveals antigen-specific and convergent responses to Ebola vaccination

Outbreaks of Ebolaviruses, such as Sudanvirus (SUDV) in Uganda in 2022, demonstrate that species other than the Zaire ebolavirus (EBOV), which is currently the sole virus represented in current licensed vaccines, remain a major threat to global health. There is a pressing need to develop effective pan-species vaccines and novel monoclonal antibody-based therapeutics for Ebolavirus disease. In response to recent outbreaks, the two dose, heterologous Ad26.ZEBOV/MVA-BN-Filo vaccine regimen was developed and was tested in a large phase II clinical trial (EBL2001) as part of the EBOVAC2 consortium. Here, we perform bulk sequencing of the variable heavy chain (VH) of B cell receptors (BCR) in forty participants from the EBL2001 trial in order to characterize the BCR repertoire in response to vaccination with Ad26.ZEBOV/MVA-BN-Filo. We develop a comprehensive database, EBOV-AbDab, of publicly available Ebolavirus-specific antibody sequences. We then use our database to predict the antigen-specific component of the vaccinee repertoires. Our results show striking convergence in VH germline gene usage across participants following the MVA-BN-Filo dose, and provide further evidence of the role of IGHV3-15 and IGHV3-13 antibodies in the B cell response to Ebolavirus glycoprotein. Furthermore, we found that previously described Ebola-specific mAb sequences present in EBOV-AbDab were sufficient to describe at least one of the ten most expanded BCR clonotypes in more than two thirds of our cohort of vaccinees following the boost, providing proof of principle for the utility of computational mining of immune repertoires.

nf-core/airrflow: An adaptive immune receptor repertoire analysis workflow employing the Immcantation framework

Adaptive Immune Receptor Repertoire sequencing (AIRR-seq) is a valuable experimental tool to study the immune state in health and following immune challenges such as infectious diseases, (auto)immune diseases, and cancer. Several tools have been developed to reconstruct B cell and T cell receptor sequences from AIRR-seq data and infer B and T cell clonal relationships. However, currently available tools offer limited parallelization across samples, scalability or portability to high-performance computing infrastructures. To address this need, we developed nf-core/airrflow, an end-to-end bulk and single-cell AIRR-seq processing workflow which integrates the Immcantation Framework following BCR and TCR sequencing data analysis best practices. The Immcantation Framework is a comprehensive toolset, which allows the processing of bulk and single-cell AIRR-seq data from raw read processing to clonal inference. nf-core/airrflow is written in Nextflow and is part of the nf-core project, which collects community contributed and curated Nextflow workflows for a wide variety of analysis tasks. We assessed the performance of nf-core/airrflow on simulated sequencing data with sequencing errors and show example results with real datasets. To demonstrate the applicability of nf-core/airrflow to the high-throughput processing of large AIRR-seq datasets, we validated and extended previously reported findings of convergent antibody responses to SARS-CoV-2 by analyzing 97 COVID-19 infected individuals and 99 healthy controls, including a mixture of bulk and single-cell sequencing datasets. Using this dataset, we extended the convergence findings to 20 additional subjects, highlighting the applicability of nf-core/airrflow to validate findings in small in-house cohorts with reanalysis of large publicly available AIRR datasets.

Prior dengue virus serotype 3 infection modulates subsequent plasmablast responses to Zika virus infection in rhesus macaques

Immunodominant and highly conserved flavivirus envelope proteins can trigger cross-reactive IgG antibodies against related flaviviruses, which shapes subsequent protection or disease severity. This study examined how prior dengue serotype 3 (DENV-3) infection affects subsequent Zika virus (ZIKV) plasmablast responses in rhesus macaques (n = 4). We found that prior DENV-3 infection was not associated with diminished ZIKV-neutralizing antibodies or magnitude of plasmablast activation. Rather, characterization of 363 plasmablasts and their derivative 177 monoclonal antibody supernatants from acute ZIKV infection revealed that prior DENV-3 infection was associated with a differential isotype distribution toward IgG, lower somatic hypermutation, and lesser B cell receptor variable gene diversity as compared with repeat ZIKV challenge. We did not find long-lasting DENV-3 cross-reactive IgG after a ZIKV infection but did find persistent ZIKV-binding cross-reactive IgG after a DENV-3 infection, suggesting non-reciprocal cross-reactive immunity. Infection with ZIKV after DENV-3 boosted pre-existing DENV-3-neutralizing antibodies by two- to threefold, demonstrating immune imprinting. These findings suggest that the order of DENV and ZIKV infections has impact on the quality of early B cell immunity which has implications for optimal immunization strategies.

IMPORTANCE

The Zika virus epidemic of 2015-2016 in the Americas revealed that this mosquito-transmitted virus could be congenitally transmitted during pregnancy and cause birth defects in newborns. Currently, there are no interventions to mitigate this disease and Zika virus is likely to re-emerge. Understanding how protective antibody responses are generated against Zika virus can help in the development of a safe and effective vaccine. One main challenge is that Zika virus co-circulates with related viruses like dengue, such that prior exposure to one can generate cross-reactive antibodies against the other which may enhance infection and disease from the second virus. In this study, we sought to understand how prior dengue virus infection impacts subsequent immunity to Zika virus by single-cell sequencing of antibody producing cells in a second Zika virus infection. Identifying specific qualities of Zika virus immunity that are modulated by prior dengue virus immunity will enable optimal immunization strategies.

nf-core/airrflow: an adaptive immune receptor repertoire analysis workflow employing the Immcantation framework

Adaptive Immune Receptor Repertoire sequencing (AIRR-seq) is a valuable experimental tool to study the immune state in health and following immune challenges such as infectious diseases, (auto)immune diseases, and cancer. Several tools have been developed to reconstruct B cell and T cell receptor sequences from AIRR-seq data and infer B and T cell clonal relationships. However, currently available tools offer limited parallelization across samples, scalability or portability to high-performance computing infrastructures. To address this need, we developed nf-core/airrflow, an end-to-end bulk and single-cell AIRR-seq processing workflow which integrates the Immcantation Framework following BCR and TCR sequencing data analysis best practices. The Immcantation Framework is a comprehensive toolset, which allows the processing of bulk and single-cell AIRR-seq data from raw read processing to clonal inference. nf-core/airrflow is written in Nextflow and is part of the nf-core project, which collects community contributed and curated Nextflow workflows for a wide variety of analysis tasks. We assessed the performance of nf-core/airrflow on simulated sequencing data with sequencing errors and show example results with real datasets. To demonstrate the applicability of nf-core/airrflow to the high-throughput processing of large AIRR-seq datasets, we validated and extended previously reported findings of convergent antibody responses to SARS-CoV-2 by analyzing 97 COVID-19 infected individuals and 99 healthy controls, including a mixture of bulk and single-cell sequencing datasets. Using this dataset, we extended the convergence findings to 20 additional subjects, highlighting the applicability of nf-core/airrflow to validate findings in small in-house cohorts with reanalysis of large publicly available AIRR datasets. nf-core/airrflow is available free of charge, under the MIT license on GitHub (https://github.com/nf-core/airrflow). Detailed documentation and example results are available on the nf-core website at (https://nf-co.re/airrflow).

The multilevel extensive diversity across the cynomolgus macaque captured by ultra-deep adaptive immune receptor repertoire sequencing

The extent to which AIRRs differ among and within individuals remains elusive. Via ultra-deep repertoire sequencing of 22 and 25 tissues in three cynomolgus macaques, respectively, we identified 84 and 114 novel IGHV and TRBV alleles, confirming 72 (85.71%) and 100 (87.72%) of them. The heterogeneous V gene usage patterns were influenced, in turn, by genetics, isotype (for BCRs only), tissue group, and tissue. A higher proportion of intragroup shared clones in the intestinal tissues than those in other tissues suggests a close intra-intestinal adaptive immunity network. Significantly higher mutation burdens in the public clones and the inter-tissue shared IgM and IgD clones indicate that they might target the shared antigens. This study reveals the extensive heterogeneity of the AIRRs at various levels and has broad fundamental and clinical implications. The data generated here will serve as an invaluable resource for future studies on adaptive immunity in health and diseases.

The dengue-specific immune response and antibody identification with machine learning

Dengue virus poses a serious threat to global health and there is no specific therapeutic for it. Broadly neutralizing antibodies recognizing all serotypes may be an effective treatment. High-throughput adaptive immune receptor repertoire sequencing (AIRR-seq) and bioinformatic analysis enable in-depth understanding of the B-cell immune response. Here, we investigate the dengue antibody response with these technologies and apply machine learning to identify rare and underrepresented broadly neutralizing antibody sequences. Dengue immunization elicited the following signatures on the antibody repertoire: (i) an increase of CDR3 and germline gene diversity; (ii) a change in the antibody repertoire architecture by eliciting power-law network distributions and CDR3 enrichment in polar amino acids; (iii) an increase in the expression of JNK/Fos transcription factors and ribosomal proteins. Furthermore, we demonstrate the applicability of computational methods and machine learning to AIRR-seq datasets for neutralizing antibody candidate sequence identification. Antibody expression and functional assays have validated the obtained results.

mRNA COVID-19 vaccine elicits potent adaptive immune response without the persistent inflammation seen in SARS-CoV-2 infection

SARS-CoV-2 infection and vaccination elicit potent immune responses. Our study presents a comprehensive multimodal single-cell dataset of peripheral blood of patients with acute COVID-19 and of healthy volunteers before and after receiving the SARS-CoV-2 mRNA vaccine and booster. We compared host immune responses to the virus and vaccine using transcriptional profiling, coupled with B/T cell receptor repertoire reconstruction. COVID-19 patients displayed an enhanced interferon signature and cytotoxic gene upregulation, absent in vaccine recipients. These findings were validated in an independent dataset. Analysis of B and T cell repertoires revealed that, while the majority of clonal lymphocytes in COVID-19 patients were effector cells, clonal expansion was more evident among circulating memory cells in vaccine recipients. Furthermore, while clonal αβ T cell responses were observed in both COVID-19 patients and vaccine recipients, dramatic expansion of clonal γδT cells was found only in infected individuals. Our dataset enables comparative analyses of immune responses to infection versus vaccination, including clonal B and T cell responses. Integrating our data with publicly available datasets allowed us to validate our findings in larger cohorts. To our knowledge, this is the first dataset to include comprehensive profiling of longitudinal samples from healthy volunteers pre/post SARS-CoV-2 vaccine and booster.

Germline-encoded specificities and the predictability of the B cell response

Antibodies result from the competition of B cell lineages evolving under selection for improved antigen recognition, a process known as affinity maturation. High-affinity antibodies to pathogens such as HIV, influenza, and SARS-CoV-2 are frequently reported to arise from B cells whose receptors, the precursors to antibodies, are encoded by particular immunoglobulin alleles. This raises the possibility that the presence of particular germline alleles in the B cell repertoire is a major determinant of the quality of the antibody response. Alternatively, initial differences in germline alleles' propensities to form high-affinity receptors might be overcome by chance events during affinity maturation. We first investigate these scenarios in simulations: when germline-encoded fitness differences are large relative to the rate and effect size variation of somatic mutations, the same germline alleles persistently dominate the response of different individuals. In contrast, if germline-encoded advantages can be easily overcome by subsequent mutations, allele usage becomes increasingly divergent over time, a pattern we then observe in mice experimentally infected with influenza virus. We investigated whether affinity maturation might nonetheless strongly select for particular amino acid motifs across diverse genetic backgrounds, but we found no evidence of convergence to similar CDR3 sequences or amino acid substitutions. These results suggest that although germline-encoded specificities can lead to similar immune responses between individuals, diverse evolutionary routes to high affinity limit the genetic predictability of responses to infection and vaccination.

Molecular basis of SARS-CoV-2 Omicron variant evasion from shared neutralizing antibody response

Understanding the molecular features of neutralizing epitopes is important for developing vaccines/therapeutics against emerging SARS-CoV-2 variants. We describe three monoclonal antibodies (mAbs) generated from COVID-19 recovered individuals during the first wave of the pandemic in India. These mAbs had publicly shared near germline gene usage and potently neutralized Alpha and Delta, poorly neutralized Beta, and failed to neutralize Omicron BA.1 SARS-CoV-2 variants. Structural analysis of these mAbs in complex with trimeric spike protein showed that all three mAbs bivalently bind spike with two mAbs targeting class 1 and one targeting a class 4 receptor binding domain epitope. The immunogenetic makeup, structure, and function of these mAbs revealed specific molecular interactions associated with the potent multi-variant binding/neutralization efficacy. This knowledge shows how mutational combinations can affect the binding or neutralization of an antibody, which in turn relates to the efficacy of immune responses to emerging SARS-CoV-2 escape variants.

Clonal evolution and stereotyped sequences of human IgE lineages in aeroallergen-specific immunotherapy

BACKGROUND

Allergic disease reflects specific inflammatory processes initiated by interaction between allergen and allergen-specific IgE. Specific immunotherapy (SIT) is an effective long-term treatment option, but the mechanisms by which SIT provides desensitization are not well understood.

OBJECTIVE

Our aim was to characterize IgE sequences expressed by allergen-specific B cells over a 3-year longitudinal study of patients with aeroallergies who were undergoing SIT.

METHODS

Allergen-specific IgE-expressing clones were identified by using combinatorial single-chain variable fragment libraries and tracked in PBMCs and nasal biopsy samples over a 3-year period with antibody gene repertoire sequencing. The characteristics of private IgE-expressing clones were compared with those of stereotyped or "public" IgE responses to the grass pollen allergen Phleum pratense (Phl p) 2.

RESULT

Members of the same allergen-specific IgE lineages were observed in nasal biopsy samples and blood, and lineages detected at baseline persisted in blood and nasal biopsy samples after 3 years of SIT, including B cells that express IgE. Evidence of progressive class switch recombination to IgG subclasses was observed after 3 years of SIT. A common stereotyped Phl p 2-specific antibody heavy chain sequence was detected in multiple donors. The amino acid residues enriched in IgE-stereotyped sequences from seropositive donors were analyzed with machine learning and k-mer motif discovery. Stereotyped IgE sequences had lower overall rates of somatic hypermutation and antigen selection than did single-chain variable fragment-derived allergen-specific sequences or IgE sequences of unknown specificity.

CONCLUSION

Longitudinal tracking of rare circulating and tissue-resident allergen-specific IgE+ clones demonstrates persistence of allergen-specific IgE+ clones, progressive class switch recombination to IgG subtypes, and distinct maturation of a stereotyped Phl p 2 clonotype.

Structural and immunological basis of cross-reactivity between dengue and Zika infections: Implications in serosurveillance in endemic regions

Dengue and Zika are arthropod-borne viral diseases present in more than 100 countries around the world. In the past decade, Zika emerged causing widespread outbreaks in new regions, where dengue has been endemic-epidemic for a long period. The wide and extensive dissemination of the mosquito vectors, Aedes aegypti, and Ae. albopictus, favor the co-existence of both infections in the same regions. Together with an important proportion of asymptomatic infections, similar clinical manifestations, and a short time window for acute infection confirmatory tests, it is difficult to differentially estimate both dengue and Zika incidence and prevalence. DENV and ZIKV flavivirus share high structural similarity, inducing a cross-reactive immune response that leads to false positives in serological tests particularly in secondary infections. This results in overestimation of recent Zika outbreaks seroprevalence in dengue endemic regions. In this review, we address the biological basis underlying DENV and ZIKV structural homology; the structural and cellular basis of immunological cross reactivity; and the resulting difficulties in measuring dengue and Zika seroprevalence. Finally, we offer a perspective about the need for more research to improve serological tests performance.

Modeling and predicting the overlap of B- and T-cell receptor repertoires in healthy and SARS-CoV-2 infected individuals

Adaptive immunity's success relies on the extraordinary diversity of protein receptors on B and T cell membranes. Despite this diversity, the existence of public receptors shared by many individuals gives hope for developing population-wide vaccines and therapeutics. Using probabilistic modeling, we show many of these public receptors are shared by chance in healthy individuals. This predictable overlap is driven not only by biases in the random generation process of receptors, as previously reported, but also by their common functional selection. However, the model underestimates sharing between repertoires of individuals infected with SARS-CoV-2, suggesting strong specific antigen-driven convergent selection. We exploit this discrepancy to identify COVID-associated receptors, which we validate against datasets of receptors with known viral specificity. We study their properties in terms of sequence features and network organization, and use them to design an accurate diagnostic tool for predicting SARS-CoV-2 status from repertoire data.

Molecular basis for antiviral activity of two pediatric neutralizing antibodies targeting SARS-CoV-2 Spike RBD

Neutralizing antibodies (NAbs) hold great promise for clinical interventions against SARS-CoV-2 variants of concern (VOCs). Understanding NAb epitope-dependent antiviral mechanisms is crucial for developing vaccines and therapeutics against VOCs. Here we characterized two potent NAbs, EH3 and EH8, isolated from an unvaccinated pediatric patient with exceptional plasma neutralization activity. EH3 and EH8 cross-neutralize the early VOCs and mediate strong Fc-dependent effector activity in vitro. Structural analyses of EH3 and EH8 in complex with the receptor-binding domain (RBD) revealed the molecular determinants of the epitope-driven protection and VOC evasion. While EH3 represents the prevalent IGHV3-53 NAb whose epitope substantially overlaps with the ACE2 binding site, EH8 recognizes a narrow epitope exposed in both RBD-up and RBD-down conformations. When tested in vivo, a single-dose prophylactic administration of EH3 fully protected stringent K18-hACE2 mice from lethal challenge with Delta VOC. Our study demonstrates that protective NAbs responses converge in pediatric and adult SARS-CoV-2 patients.

The evolutionary and functional significance of germline immunoglobulin gene variation

The recombination between immunoglobulin (IG) gene segments determines an individual's naïve antibody repertoire and, consequently, (auto)antigen recognition. Emerging evidence suggests that mammalian IG germline variation impacts humoral immune responses associated with vaccination, infection, and autoimmunity - from the molecular level of epitope specificity, up to profound changes in the architecture of antibody repertoires. These links between IG germline variants and immunophenotype raise the question on the evolutionary causes and consequences of diversity within IG loci. We discuss why the extreme diversity in IG loci remains a mystery, why resolving this is important for the design of more effective vaccines and therapeutics, and how recent evidence from multiple lines of inquiry may help us do so.

Comparative global B cell receptor repertoire difference induced by SARS-CoV-2 infection or vaccination via single-cell V(D)J sequencing

Dynamic changes of the paired heavy and light chain B cell receptor (BCR) repertoire provide an essential insight into understanding the humoral immune response post-SARS-CoV-2 infection and vaccination. However, differences between the endogenous paired BCR repertoire kinetics in SARS-CoV-2 infection and previously recovered/naïve subjects treated with the inactivated vaccine remain largely unknown. We performed single-cell V(D)J sequencing of B cells from six healthy donors with three shots of inactivated SARS-CoV-2 vaccine (BBIBP-CorV), five people who received the BBIBP-CorV vaccine after having recovered from COVID-19, five unvaccinated COVID-19 recovered patients and then integrated with public data of B cells from four SARS-CoV-2-infected subjects. We discovered that BCR variable (V) genes were more prominently used in the SARS-CoV-2 exposed groups (both in the group with active infection and in the group that had recovered) than in the vaccinated groups. The VH gene that expanded the most after SARS-CoV-2 infection was IGHV3-33, while IGHV3-23 in the vaccinated groups. SARS-CoV-2-infected group enhanced more BCR clonal expansion and somatic hypermutation than the vaccinated healthy group. A small proportion of public clonotypes were shared between the SARS-CoV-2 infected, vaccinated healthy, and recovered groups. Moreover, several public antibodies had been identified against SARS-CoV-2 spike protein. We comprehensively characterize the paired heavy and light chain BCR repertoire from SARS-CoV-2 infection to vaccination, providing further guidance for the development of the next-generation precision vaccine.

Functional antibodies exhibit light chain coherence

The vertebrate adaptive immune system modifies the genome of individual B cells to encode antibodies that bind particular antigens1. In most mammals, antibodies are composed of heavy and light chains that are generated sequentially by recombination of V, D (for heavy chains), J and C gene segments. Each chain contains three complementarity-determining regions (CDR1-CDR3), which contribute to antigen specificity. Certain heavy and light chains are preferred for particular antigens2-22. Here we consider pairs of B cells that share the same heavy chain V gene and CDRH3 amino acid sequence and were isolated from different donors, also known as public clonotypes23,24. We show that for naive antibodies (those not yet adapted to antigens), the probability that they use the same light chain V gene is around 10%, whereas for memory (functional) antibodies, it is around 80%, even if only one cell per clonotype is used. This property of functional antibodies is a phenomenon that we call light chain coherence. We also observe this phenomenon when similar heavy chains recur within a donor. Thus, although naive antibodies seem to recur by chance, the recurrence of functional antibodies reveals surprising constraint and determinism in the processes of V(D)J recombination and immune selection. For most functional antibodies, the heavy chain determines the light chain.

Molecular basis of SARS-CoV-2 Omicron variant evasion from shared neutralizing antibody response

A detailed understanding of the molecular features of the neutralizing epitopes developed by viral escape mutants is important for predicting and developing vaccines or therapeutic antibodies against continuously emerging SARS-CoV-2 variants. Here, we report three human monoclonal antibodies (mAbs) generated from COVID-19 recovered individuals during first wave of pandemic in India. These mAbs had publicly shared near germline gene usage and potently neutralized Alpha and Delta, but poorly neutralized Beta and completely failed to neutralize Omicron BA.1 SARS-CoV-2 variants. Structural analysis of these three mAbs in complex with trimeric spike protein showed that all three mAbs are involved in bivalent spike binding with two mAbs targeting class-1 and one targeting class-4 Receptor Binding Domain (RBD) epitope. Comparison of immunogenetic makeup, structure, and function of these three mAbs with our recently reported class-3 RBD binding mAb that potently neutralized all SARS-CoV-2 variants revealed precise antibody footprint, specific molecular interactions associated with the most potent multi-variant binding / neutralization efficacy. This knowledge has timely significance for understanding how a combination of certain mutations affect the binding or neutralization of an antibody and thus have implications for predicting structural features of emerging SARS-CoV-2 escape variants and to develop vaccines or therapeutic antibodies against these.

Molecular basis of SARS-CoV-2 Omicron variant evasion from shared neutralizing antibody response

A detailed understanding of the molecular features of the neutralizing epitopes developed by viral escape mutants is important for predicting and developing vaccines or therapeutic antibodies against continuously emerging SARS-CoV-2 variants. Here, we report three human monoclonal antibodies (mAbs) generated from COVID-19 recovered individuals during first wave of pandemic in India. These mAbs had publicly shared near germline gene usage and potently neutralized Alpha and Delta, but poorly neutralized Beta and completely failed to neutralize Omicron BA.1 SARS-CoV-2 variants. Structural analysis of these three mAbs in complex with trimeric spike protein showed that all three mAbs are involved in bivalent spike binding with two mAbs targeting class-1 and one targeting class-4 Receptor Binding Domain (RBD) epitope. Comparison of immunogenetic makeup, structure, and function of these three mAbs with our recently reported class-3 RBD binding mAb that potently neutralized all SARS-CoV-2 variants revealed precise antibody footprint, specific molecular interactions associated with the most potent multi-variant binding / neutralization efficacy. This knowledge has timely significance for understanding how a combination of certain mutations affect the binding or neutralization of an antibody and thus have implications for predicting structural features of emerging SARS-CoV-2 escape variants and to develop vaccines or therapeutic antibodies against these.

AIRRscape: An interactive tool for exploring B-cell receptor repertoires and antibody responses

The sequencing of antibody repertoires of B-cells at increasing coverage and depth has led to the identification of vast numbers of immunoglobulin heavy and light chains. However, the size and complexity of these Adaptive Immune Receptor Repertoire sequencing (AIRR-seq) datasets makes it difficult to perform exploratory analyses. To aid in data exploration, we have developed AIRRscape, an R Shiny-based interactive web browser application that enables B-cell receptor (BCR) and antibody feature discovery through comparisons among multiple repertoires. Using AIRR-seq data as input, AIRRscape starts by aggregating and sorting repertoires into interactive and explorable bins of germline V-gene, germline J-gene, and CDR3 length, providing a high-level view of the entire repertoire. Interesting subsets of repertoires can be quickly identified and selected, and then network topologies of CDR3 motifs can be generated for further exploration. Here we demonstrate AIRRscape using patient BCR repertoires and sequences of published monoclonal antibodies to investigate patterns of humoral immunity to three viral pathogens: SARS-CoV-2, HIV-1, and DENV (dengue virus). AIRRscape reveals convergent antibody sequences among datasets for all three pathogens, although HIV-1 antibody datasets display limited convergence and idiosyncratic responses. We have made AIRRscape available as a web-based Shiny application, along with code on GitHub to encourage its open development and use by immuno-informaticians, virologists, immunologists, vaccine developers, and other scientists that are interested in exploring and comparing multiple immune receptor repertoires.

Association of B cell profile and receptor repertoire with the progression of Alzheimer's disease

Alzheimer's disease (AD) is the most prevalent type of dementia. Reports have revealed that the peripheral immune system is linked to neuropathology; however, little is known about the contribution of B lymphocytes in AD. For this longitudinal study, 133 participants are included at baseline and second-year follow-up. Also, we analyze B cell receptor (BCR) repertoire data generated from a public dataset of three normal and 10 AD samples and perform BCR repertoire profiling and pairwise sharing analysis. As a result, longitudinal increase in B lymphocytes is associated with increased cerebral amyloid deposition and hyperactivates induced pluripotent stem cell-derived microglia with loss-of-function for beta-amyloid clearance. Patients with AD share similar class-switched BCR sequences with identical isotypes, despite the high somatic hypermutation rate. Thus, BCR repertoire profiling can lead to the development of individualized immune-based therapeutics and treatment. We provide evidence of both quantitative and qualitative changes in B lymphocytes during AD pathogenesis.

Repertoire-scale measures of antigen binding

Antibodies and T cell receptors (TCRs) are the fundamental building blocks of adaptive immunity. Repertoire-scale functionality derives from their epitope-binding properties, just as macroscopic properties like temperature derive from microscopic molecular properties. However, most approaches to repertoire-scale measurement, including sequence diversity and entropy, are not based on antibody or TCR function in this way. Thus, they potentially overlook key features of immunological function. Here we present a framework that describes repertoires in terms of the epitope-binding properties of their constituent antibodies and TCRs, based on analysis of thousands of antibody-antigen and TCR-peptide-major-histocompatibility-complex binding interactions and over 400 high-throughput repertoires. We show that repertoires consist of loose overlapping classes of antibodies and TCRs with similar binding properties. We demonstrate the potential of this framework to distinguish specific responses vs. bystander activation in influenza vaccinees, stratify cytomegalovirus (CMV)-infected cohorts, and identify potential immunological "super-agers." Classes add a valuable dimension to the assessment of immune function.

Clonal structure, stability and dynamics of human memory B cells and circulating plasmablasts

Memory B cells persist for a lifetime and rapidly differentiate into antibody-producing plasmablasts and plasma cells upon antigen re-encounter. The clonal relationship and evolution of memory B cells and circulating plasmablasts is not well understood. Using single-cell sequencing combined with isolation of specific antibodies, we found that in two healthy donors, the memory B cell repertoire was dominated by large IgM, IgA and IgG2 clonal families, whereas IgG1 families, including those specific for recall antigens, were of small size. Analysis of multiyear samples demonstrated stability of memory B cell clonal families and revealed that a large fraction of recently generated plasmablasts was derived from long-term memory B cell families and was found recurrently. Collectively, this study provides a systematic description of the structure, stability and dynamics of the human memory B cell pool and suggests that memory B cells may be active at any time point in the generation of plasmablasts.

Peptide Biomarkers for the Diagnosis of Dengue Infection

In a world with an increasing population at risk of exposure to arthropod-borne flaviviruses, access to timely and accurate diagnostic tests would impact profoundly on the management of cases. Twenty peptides previously identified using a flavivirus proteome-wide microarray were evaluated to determine their discriminatory potential to detect dengue virus (DENV) infection. This included nine peptides recognized by IgM antibodies (PM peptides) and 11 peptides recognized by IgG antibodies (PG peptides). A bead-based multiplex peptide immunoassay (MPIA) using the Luminex technology was set-up to determine Ab binding levels to each of these peptides in a panel of 323 carefully selected human serum samples. Sera are derived from individuals either infected with different viruses, namely, the four DENV serotypes, Zika virus (ZIKV), yellow fever virus (YFV), chikungunya virus (CHIKV), West Nile virus (WNV) and Human immunodeficiency virus (HIV), or receiving vaccination against YFV, tick-borne encephalitis (TBEV), and Japanese encephalitis virus (JEV). Additionally, a set of healthy controls were included. We targeted a minimum specificity of 80% for all the analysis. The PG-9 peptide had the best sensitivity (73%) when testing DENV sera from acute patients (A-DENV; <8 days since symptom onset). With sera from convalescent DENV patients (C-DENV; >10 days since symptom onset) the FPG-1 peptide was the best seromarker with a sensitivity of 86%. When combining all A-DENV and C-DENV samples, peptides PM-22 and FPG-1 had the best-diagnostic performance with a sensitivity of 60 and 61.1%, and areas under the curve (AUC) of 0.7865 and 0.8131, respectively. A Random forest (RF) algorithm was used to select the best combination of peptides to classify DENV infection at a targeted specificity >80%. The best RF model for PM peptides that included A-DENV and C-DENV samples, reached a sensitivity of 72.3%, while for PG peptides, the best RF models for A-DENV only, C-DENV only and A-DENV + C-DENV reached a sensitivity of 88.9%, 89.1%, and 88.3%, respectively. In conclusion, the combination of multiple peptides constitutes a founding set of seromarkers for the discrimination of DENV infected individuals from other flavivirus infections.

Sequence and functional characterization of a public HIV-specific antibody clonotype

Public antibody clonotypes shared among multiple individuals have been identified for several pathogens. However, little is known about the determinants of antibody "publicness". Here, we characterize the sequence and functional properties of antibodies from a public clonotype targeting the CD4 binding site on HIV-1 Env. Our results showed that HIV-1 specificity for the public antibodies studied here, comprising sequences from three individuals, was modulated by the VH, but not VL, germline gene. Non-native pairing of public heavy and light chains from different individuals suggested functional complementation of sequences within this public antibody clonotype. The strength of antigen recognition appeared to be dependent on the specific antibody light chain used, but not on other sequence features such as native-antibody or germline sequence identity. Understanding the determinants of antibody clonotype "publicness" can provide insights into the fundamental rules of host-pathogen interactions at the population level, with implications for clonotype-specific vaccine development.

Dual UMIs and Dual Barcodes With Minimal PCR Amplification Removes Artifacts and Acquires Accurate Antibody Repertoire

Antibody repertoire sequencing (Rep-seq) has been widely used to reveal repertoire dynamics and to interrogate antibodies of interest at single nucleotide-level resolution. However, polymerase chain reaction (PCR) amplification introduces extensive artifacts including chimeras and nucleotide errors, leading to false discovery of antibodies and incorrect assessment of somatic hypermutations (SHMs) which subsequently mislead downstream investigations. Here, a novel approach named DUMPArts, which improves the accuracy of antibody repertoires by labeling each sample with dual barcodes and each molecule with dual unique molecular identifiers (UMIs) via minimal PCR amplification to remove artifacts, is developed. Tested by ultra-deep Rep-seq data, DUMPArts removed inter-sample chimeras, which cause artifactual shared clones and constitute approximately 15% of reads in the library, as well as intra-sample chimeras with erroneous SHMs and constituting approximately 20% of the reads, and corrected base errors and amplification biases by consensus building. The removal of these artifacts will provide an accurate assessment of antibody repertoires and benefit related studies, especially mAb discovery and antibody-guided vaccine design.

Analysis of B cell receptor repertoires reveals key signatures of systemic B cell response after SARS-CoV-2 infection

A comprehensive study of the B cell response against SARS-CoV-2 could be significant for understanding the immune response and developing therapeutical antibodies and vaccines. To define the dynamics and characteristics of the antibody repertoire following SARS-CoV-2 infection, we analyzed the mRNA transcripts of immunoglobulin heavy chain (IgH) repertoires of 24 peripheral blood samples collected between 3 and 111 days after symptom onset from 10 COVID-19 patients. Massive clonal expansion of naive B cells with limited somatic hypermutation (SHM) was observed in the second week after symptom onset. The proportion of low-SHM IgG clones strongly correlated with spike-specific IgG antibody titers, highlighting the significant activation of naive B cells in response to a novel virus infection. The antibody isotype switching landscape showed a transient IgA surge in the first week after symptom onset, followed by a sustained IgG elevation that lasted for at least 3 months. SARS-CoV-2 infection elicited poly-germ line reactive antibody responses. Interestingly, 17 different IGHV germ line genes recombined with IGHJ6 showed significant clonal expansion. By comparing the IgH repertoires that we sequenced with the 774 reported SARS-CoV-2–reactive monoclonal antibodies (MAbs), 13 shared spike-specific IgH clusters were found. These shared spike-specific IgH clusters are derived from the same lineage of several recently published neutralizing MAbs, including CC12.1, CC12.3, C102, REGN10977, and 4A8. Furthermore, identical spike-specific IgH sequences were found in different COVID-19 patients, suggesting a highly convergent antibody response to SARS-CoV-2. Our analysis based on sequencing antibody repertoires from different individuals revealed key signatures of the systemic B cell response induced by SARS-CoV-2 infection.

IMPORTANCE Although the canonical delineation of serum antibody responses following SARS-CoV-2 infection has been well established, the dynamics of antibody repertoire at the mRNA transcriptional level has not been well understood, especially the correlation between serum antibody titers and the antibody mRNA transcripts. In this study, we analyzed the IgH transcripts and characterized the B cell clonal expansion and differentiation, isotype switching, and somatic hypermutation in COVID-19 patients. This study provided insights at the repertoire level for the B cell response after SARS-CoV-2 infection.

Landscapes and dynamic diversifications of B-cell receptor repertoires in COVID-19 patients

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused the pandemic of coronavirus disease 2019 (COVID-19). Great international efforts have been put into the development of prophylactic vaccines and neutralizing antibodies. However, the knowledge about the B cell immune response induced by the SARS-CoV-2 virus is still limited. Here, we report a comprehensive characterization of the dynamics of immunoglobin heavy chain (IGH) repertoire in COVID-19 patients. By using next-generation sequencing technology, we examined the temporal changes in the landscape of the patient's immunological status and found dramatic changes in the IGH within the patient's immune system after the onset of COVID-19 symptoms. Although different patients have distinct immune responses to SARS-CoV-2 infection, by employing clonotype overlap, lineage expansion, and clonotype network analyses, we observed a higher clonotype overlap and substantial lineage expansion of B cell clones 2-3 weeks after the onset of illness, which is of great importance to B-cell immune responses. Meanwhile, for preferences of V gene usage during SARS-CoV-2 infection, IGHV3-74 and IGHV4-34, and IGHV4-39 in COVID-19 patients were more abundant than those of healthy controls. Overall, we present an immunological resource for SARS-CoV-2 that could promote both therapeutic development as well as mechanistic research.

Machine Learning Detects Anti-DENV Signatures in Antibody Repertoire Sequences

Dengue infection is a global threat. As of today, there is no universal dengue fever treatment or vaccines unreservedly recommended by the World Health Organization. The investigation of the specific immune response to dengue virus would support antibody discovery as therapeutics for passive immunization and vaccine design. High-throughput sequencing enables the identification of the multitude of antibodies elicited in response to dengue infection at the sequence level. Artificial intelligence can mine the complex data generated and has the potential to uncover patterns in entire antibody repertoires and detect signatures distinctive of single virus-binding antibodies. However, these machine learning have not been harnessed to determine the immune response to dengue virus. In order to enable the application of machine learning, we have benchmarked existing methods for encoding biological and chemical knowledge as inputs and have investigated novel encoding techniques. We have applied different machine learning methods such as neural networks, random forests, and support vector machines and have investigated the parameter space to determine best performing algorithms for the detection and prediction of antibody patterns at the repertoire and antibody sequence levels in dengue-infected individuals. Our results show that immune response signatures to dengue are detectable both at the antibody repertoire and at the antibody sequence levels. By combining machine learning with phylogenies and network analysis, we generated novel sequences that present dengue-binding specific signatures. These results might aid further antibody discovery and support vaccine design.

Current Trends and Limitations in Dengue Antiviral Research

Dengue is the most prevalent arthropod-borne viral disease worldwide and affects approximately 2.5 billion people living in over 100 countries. Increasing geographic expansion of Aedes aegypti mosquitoes (which transmit the virus) has made dengue a global health concern. There are currently no approved antivirals available to treat dengue, and the only approved vaccine used in some countries is limited to seropositive patients. Treatment of dengue, therefore, remains largely supportive to date; hence, research efforts are being intensified for the development of antivirals. The nonstructural proteins, 3 and 5 (NS3 and NS5), have been the major targets for dengue antiviral development due to their indispensable enzymatic and biological functions in the viral replication process. NS5 is the largest and most conserved nonstructural protein encoded by flaviviruses. Its multifunctionality makes it an attractive target for antiviral development, but research efforts have, this far, not resulted in the successful development of an antiviral targeting NS5. Increase in structural insights into the dengue NS5 protein will accelerate drug discovery efforts focused on NS5 as an antiviral target. In this review, we will give an overview of the current state of therapeutic development, with a focus on NS5 as a therapeutic target against dengue.

Cutting Edge: Neutralizing Public Antibody Responses Are an Ancient Form of Defense Conserved in Fish and Mammals

The repertoire of Abs is generated by genomic rearrangements during B cell differentiation. Although V(D)J rearrangements lead to repertoires mostly different between individuals, recent studies have shown that they contain a substantial fraction of overrepresented and shared "public" clones. We previously reported a strong public IgHμ clonotypic response against the rhabdovirus viral hemorrhagic septicemia virus in a teleost fish. In this study, we identified an IgL chain associated with this public response that allowed us to characterize its functionality. We show that this public Ab response has a potent neutralizing capacity that is typically associated with host protection during rhabdovirus infections. We also demonstrate that the public response is not restricted to a particular trout isogenic line but expressed in multiple genetic backgrounds and may be used as a marker of successful vaccination. Our work reveals that public B cell responses producing generic Abs constitute a mechanism of protection against infection conserved across vertebrates.

Potent and protective IGHV3-53/3-66 public antibodies and their shared escape mutant on the spike of SARS-CoV-2

Neutralizing antibodies (nAbs) to SARS-CoV-2 hold powerful potentials for clinical interventions against COVID-19 disease. However, their common genetic and biologic features remain elusive. Here we interrogate a total of 165 antibodies from eight COVID-19 patients, and find that potent nAbs from different patients have disproportionally high representation of IGHV3-53/3-66 usage, and therefore termed as public antibodies. Crystal structural comparison of these antibodies reveals they share similar angle of approach to RBD, overlap in buried surface and binding residues on RBD, and have substantial spatial clash with receptor angiotensin-converting enzyme-2 (ACE2) in binding to RBD. Site-directed mutagenesis confirms these common binding features although some minor differences are found. One representative antibody, P5A-3C8, demonstrates extraordinarily protective efficacy in a golden Syrian hamster model against SARS-CoV-2 infection. However, virus escape analysis identifies a single natural mutation in RBD, namely K417N found in B.1.351 variant from South Africa, abolished the neutralizing activity of these public antibodies. The discovery of public antibodies and shared escape mutation highlight the intricate relationship between antibody response and SARS-CoV-2, and provide critical reference for the development of antibody and vaccine strategies to overcome the antigenic variation of SARS-CoV-2.

Sequence signatures of two public antibody clonotypes that bind SARS-CoV-2 receptor binding domain

Since the COVID-19 pandemic onset, the antibody response to SARS-CoV-2 has been extensively characterized. Antibodies to the receptor binding domain (RBD) on the spike protein are frequently encoded by IGHV3-53/3-66 with a short complementarity-determining region (CDR) H3. Germline-encoded sequence motifs in heavy chain CDRs H1 and H2 have a major function, but whether any common motifs are present in CDR H3, which is often critical for binding specificity, is not clear. Here, we identify two public clonotypes of IGHV3-53/3-66 RBD antibodies with a 9-residue CDR H3 that pair with different light chains. Distinct sequence motifs on CDR H3 are present in the two public clonotypes that seem to be related to differential light chain pairing. Additionally, we show that Y58F is a common somatic hypermutation that results in increased binding affinity of IGHV3-53/3-66 RBD antibodies with a short CDR H3. These results advance understanding of the antibody response to SARS-CoV-2.

Prospective Artificial Intelligence to Dissect the Dengue Immune Response and Discover Therapeutics

Dengue virus (DENV) poses a serious threat to global health as the causative agent of dengue fever. The virus is endemic in more than 128 countries resulting in approximately 390 million infection cases each year. Currently, there is no approved therapeutic for treatment nor a fully efficacious vaccine. The development of therapeutics is confounded and hampered by the complexity of the immune response to DENV, in particular to sequential infection with different DENV serotypes (DENV1-5). Researchers have shown that the DENV envelope (E) antigen is primarily responsible for the interaction and subsequent invasion of host cells for all serotypes and can elicit neutralizing antibodies in humans. The advent of high-throughput sequencing and the rapid advancements in computational analysis of complex data, has provided tools for the deconvolution of the DENV immune response. Several types of complex statistical analyses, machine learning models and complex visualizations can be applied to begin answering questions about the B- and T-cell immune responses to multiple infections, antibody-dependent enhancement, identification of novel therapeutics and advance vaccine research.

Cross-Reactive SARS-CoV-2 Neutralizing Antibodies From Deep Mining of Early Patient Responses

Passive immunization using monoclonal antibodies will play a vital role in the fight against COVID-19. The recent emergence of viral variants with reduced sensitivity to some current antibodies and vaccines highlights the importance of broad cross-reactivity. This study describes deep-mining of the antibody repertoires of hospitalized COVID-19 patients using phage display technology and B cell receptor (BCR) repertoire sequencing to isolate neutralizing antibodies and gain insights into the early antibody response. This comprehensive discovery approach has yielded a panel of potent neutralizing antibodies which bind distinct viral epitopes including epitopes conserved in SARS-CoV-1. Structural determination of a non-ACE2 receptor blocking antibody reveals a previously undescribed binding epitope, which is unlikely to be affected by the mutations in any of the recently reported major viral variants including B.1.1.7 (from the UK), B.1.351 (from South Africa) and B.1.1.28 (from Brazil). Finally, by combining sequences of the RBD binding and neutralizing antibodies with the B cell receptor repertoire sequencing, we also describe a highly convergent early antibody response. Similar IgM-derived sequences occur within this study group and also within patient responses described by multiple independent studies published previously.

Antibody heavy chain CDR3 length-dependent usage of human IGHJ4 and IGHJ6 germline genes

Therapeutic antibody discovery using synthetic diversity has been proved productive, especially for target proteins not suitable for traditional animal immunization-based antibody discovery approaches. Recently, many lines of evidences suggest that the quality of synthetic diversity design limits the development success of synthetic antibody hits. The aim of our study is to understand the quality limitation and to properly address the challenges with a better design. Using VH3–23 as a model framework, we observed and quantitatively mapped CDR-H3 loop length-dependent usage of human IGHJ4 and IGHJ6 germline genes in the natural human immune repertoire. Skewed usage of DH2-JH6 and DH3-JH6 rearrangements was quantitatively determined in a CDR-H3 length-dependent manner in natural human antibodies with long CDR-H3 loops. Structural modeling suggests choices of JH help to stabilize antibody CDR-H3 loop and JH only partially contributes to the paratope. Our observations shed light on the design of next-generation synthetic diversity with improved probability of success.

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.

Structural and genetic convergence of HIV-1 neutralizing antibodies in vaccinated non-human primates

A primary goal of HIV-1 vaccine development is the consistent elicitation of protective, neutralizing antibodies. While highly similar neutralizing antibodies (nAbs) have been isolated from multiple HIV-infected individuals, it is unclear whether vaccination can consistently elicit highly similar nAbs in genetically diverse primates. Here, we show in three outbred rhesus macaques that immunization with Env elicits a genotypically and phenotypically conserved nAb response. From these vaccinated macaques, we isolated four antibody lineages that had commonalities in immunoglobulin variable, diversity, and joining gene segment usage. Atomic-level structures of the antigen binding fragments of the two most similar antibodies showed nearly identical paratopes. The Env binding modes of each of the four vaccine-induced nAbs were distinct from previously known monoclonal HIV-1 neutralizing antibodies, but were nearly identical to each other. The similarities of these antibodies show that the immune system in outbred primates can respond to HIV-1 Env vaccination with a similar structural and genotypic solution for recognizing a particular neutralizing epitope. These results support rational vaccine design for HIV-1 that aims to reproducibly elicit, in genetically diverse primates, nAbs with specific paratope structures capable of binding conserved epitopes.

Trace Reconstruction Problems in Computational Biology

The problem of reconstructing a string from its error-prone copies, the trace reconstruction problem, was introduced by Vladimir Levenshtein two decades ago. While there has been considerable theoretical work on trace reconstruction, practical solutions have only recently started to emerge in the context of two rapidly developing research areas: immunogenomics and DNA data storage. In immunogenomics, traces correspond to mutated copies of genes, with mutations generated naturally by the adaptive immune system. In DNA data storage, traces correspond to noisy copies of DNA molecules that encode digital data, with errors being artifacts of the data retrieval process. In this paper, we introduce several new trace generation models and open questions relevant to trace reconstruction for immunogenomics and DNA data storage, survey theoretical results on trace reconstruction, and highlight their connections to computational biology. Throughout, we discuss the applicability and shortcomings of known solutions and suggest future research directions.

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.

Signatures of B Cell Receptor Repertoire Following Pneumocystis Infection

B cells play vital roles in host defense against Pneumocystis infection. However, the features of the B cell receptor (BCR) repertoire in disease progression remain unclear. Here, we integrated single-cell RNA sequencing and single-cell BCR sequencing of immune cells from mouse lungs in an uninfected state and 1–4 weeks post-infection in order to illustrate the dynamic nature of B cell responses during Pneumocystis infection. We identified continuously increased plasma cells and an elevated ratio of (IgA + IgG) to (IgD + IgM) after infection. Moreover, Pneumocystis infection was associated with an increasing naïve B subset characterized by elevated expression of the transcription factor ATF3. The proportion of clonal expanded cells progressively increased, while BCR diversity decreased. Plasma cells exhibited higher levels of somatic hypermutation than naïve B cells. Biased usage of V(D)J genes was observed, and the usage frequency of IGHV9-3 rose. Overall, these results present a detailed atlas of B cell transcriptional changes and BCR repertoire features in the context of Pneumocystis infection, which provides valuable information for finding diagnostic biomarkers and developing potential immunotherapeutic targets.

Rapid isolation and immune profiling of SARS-CoV-2 specific memory B cell in convalescent COVID-19 patients via LIBRA-seq

B cell response plays a critical role against SARS-CoV-2 infection. However, little is known about the diversity and frequency of the paired SARS-CoV-2 antigen-specific BCR repertoire after SARS-CoV-2 infection. Here, we performed single-cell RNA sequencing and VDJ sequencing using the memory and plasma B cells isolated from five convalescent COVID-19 patients, and analyzed the spectrum and transcriptional heterogeneity of antibody immune responses. Via linking BCR to antigen specificity through sequencing (LIBRA-seq), we identified a distinct activated memory B cell subgroup (CD11c^high CD95^high) had a higher proportion of SARS-CoV-2 antigen-labeled cells compared with memory B cells. Our results revealed the diversity of paired BCR repertoire and the non-stochastic pairing of SARS-CoV-2 antigen-specific immunoglobulin heavy and light chains after SARS-CoV-2 infection. The public antibody clonotypes were shared by distinct convalescent individuals. Moreover, several antibodies isolated by LIBRA-seq showed high binding affinity against SARS-CoV-2 receptor-binding domain (RBD) or nucleoprotein (NP) via ELISA assay. Two RBD-reactive antibodies C14646P3S and C2767P3S isolated by LIBRA-seq exhibited high neutralizing activities against both pseudotyped and authentic SARS-CoV-2 viruses in vitro. Our study provides fundamental insights into B cell response following SARS-CoV-2 infection at the single-cell level.

Diverse immunoglobulin gene usage and convergent epitope targeting in neutralizing antibody responses to SARS-CoV-2

It is unclear whether individuals with enormous diversity in B cell receptor repertoires are consistently able to mount effective antibody responses against SARS-CoV-2. We analyzed antibody responses in a cohort of 55 convalescent patients and isolated 54 potent neutralizing monoclonal antibodies (mAbs). While most of the mAbs target the angiotensin-converting enzyme 2 (ACE2) binding surface on the receptor binding domain (RBD) of SARS-CoV-2 spike protein, mAb 47D1 binds only to one side of the receptor binding surface on the RBD. Neutralization by 47D1 is achieved independent of interfering RBD-ACE2 binding. A crystal structure of the mAb-RBD complex shows that the IF motif at the tip of 47D1 CDR H2 interacts with a hydrophobic pocket in the RBD. Diverse immunoglobulin gene usage and convergent epitope targeting characterize neutralizing antibody responses to SARS-CoV-2, suggesting that vaccines that effectively present the receptor binding site on the RBD will likely elicit neutralizing antibody responses in a large fraction of the population.

From Structural Studies to HCV Vaccine Design

Hepatitis C virus (HCV) is a serious and growing public health problem despite recent developments of antiviral therapeutics. To achieve global elimination of HCV, an effective cross-genotype vaccine is needed. The failure of previous vaccination trials to elicit an effective cross-reactive immune response demands better vaccine antigens to induce a potent cross-neutralizing response to improve vaccine efficacy. HCV E1 and E2 envelope (Env) glycoproteins are the main targets for neutralizing antibodies (nAbs), which aid in HCV clearance and protection. Therefore, a molecular-level understanding of the nAb responses against HCV is imperative for the rational design of cross-genotype vaccine antigens. Here we summarize the recent advances in structural studies of HCV Env and Env-nAb complexes and how they improve our understanding of immune recognition of HCV. We review the structural data defining HCV neutralization epitopes and conformational plasticity of the Env proteins, and the knowledge applicable to rational vaccine design.

Overcoming Immunological Challenges Limiting Capsid-Mediated Gene Therapy With Machine Learning

A key hurdle to making adeno-associated virus (AAV) capsid mediated gene therapy broadly beneficial to all patients is overcoming pre-existing and therapy-induced immune responses to these vectors. Recent advances in high-throughput DNA synthesis, multiplexing and sequencing technologies have accelerated engineering of improved capsid properties such as production yield, packaging efficiency, biodistribution and transduction efficiency. Here we outline how machine learning, advances in viral immunology, and high-throughput measurements can enable engineering of a new generation of de-immunized capsids beyond the antigenic landscape of natural AAVs, towards expanding the therapeutic reach of gene therapy.