Diversity in immunogenomics: the value and the challenge

Omics in allergy and asthma

This review explores the transformative impact of omics technologies on allergy and asthma research in recent years, focusing on advancements in high-throughput technologies related to genomics and transcriptomics. In particular, the rapid spread of single-cell RNA sequencing has markedly advanced our understanding of the molecular pathology of allergic diseases. Furthermore, high-throughput genome sequencing has accelerated the discovery of monogenic disorders that were previously overlooked as ordinary intractable allergic diseases. We also introduce microbiomics, proteomics, lipidomics, and metabolomics, which are quickly growing areas of research interest, although many of their current findings remain inconclusive as solid evidence. By integrating these omics data, we will gain deeper insights into disease mechanisms, leading to the development of precision medicine approaches that promise to enhance treatment outcomes.

RIOT-Rapid Immunoglobulin Overview Tool-annotation of nucleotide and amino acid immunoglobulin sequences using an open germline database

Antibodies are a cornerstone of the immune system, playing a pivotal role in identifying and neutralizing infections caused by bacteria, viruses, and other pathogens. Understanding their structure, and function, can provide insights into both the body's natural defenses and the principles behind many therapeutic interventions, including vaccines and antibody-based drugs. The analysis and annotation of antibody sequences, including the identification of variable, diversity, joining, and constant genes, as well as the delineation of framework regions and complementarity-determining regions, is essential for understanding their structure and function. Currently analyzing large volumes of antibody sequences is routine in antibody discovery, requiring fast and accurate tools. While there are existing tools designed for the annotation and numbering of antibody sequences, they often have limitations such as being restricted to either nucleotide or amino acid sequences; slow execution times; or reliance on germline databases that are closed, frequently changed, or have sparse coverage for some species. Here, we present the Rapid Immunoglobulin Overview Tool (RIOT), a novel open-source solution for antibody numbering that addresses these shortcomings. RIOT handles nucleotide and amino acid sequence processing, comes integrated with an Open Germline Receptor Database, and is computationally efficient. We hope that the tool will facilitate rapid annotation of antibody sequencing outputs for the benefit of understanding antibody biology and discovering novel therapeutics.

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.

Addressing Technical Pitfalls in Pursuit of Molecular Factors That Mediate Immunoglobulin Gene Regulation

The expressed Ab repertoire is a critical determinant of immune-related phenotypes. Ab-encoding transcripts are distinct from other expressed genes because they are transcribed from somatically rearranged gene segments. Human Abs are composed of two identical H and L chain polypeptides derived from genes in IGH locus and one of two L chain loci. The combinatorial diversity that results from Ab gene rearrangement and the pairing of different H and L chains contributes to the immense diversity of the baseline Ab repertoire. During rearrangement, Ab gene selection is mediated by factors that influence chromatin architecture, promoter/enhancer activity, and V(D)J recombination. Interindividual variation in the composition of the Ab repertoire associates with germline variation in IGH, implicating polymorphism in Ab gene regulation. Determining how IGH variants directly mediate gene regulation will require integration of these variants with other functional genomic datasets. In this study, we argue that standard approaches using short reads have limited utility for characterizing regulatory regions in IGH at haplotype resolution. Using simulated and chromatin immunoprecipitation sequencing reads, we define features of IGH that limit use of short reads and a single reference genome, namely 1) the highly duplicated nature of the DNA sequence in IGH and 2) structural polymorphisms that are frequent in the population. We demonstrate that personalized diploid references enhance performance of short-read data for characterizing mappable portions of the locus, while also showing that long-read profiling tools will ultimately be needed to fully resolve functional impacts of IGH germline variation on expressed Ab repertoires.

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.

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.

Spatial transcriptomics of B cell and T cell receptors reveals lymphocyte clonal dynamics

The spatial distribution of lymphocyte clones within tissues is critical to their development, selection, and expansion. We have developed spatial transcriptomics of variable, diversity, and joining (VDJ) sequences (Spatial VDJ), a method that maps B cell and T cell receptor sequences in human tissue sections. Spatial VDJ captures lymphocyte clones that match canonical B and T cell distributions and amplifies clonal sequences confirmed by orthogonal methods. We found spatial congruency between paired receptor chains, developed a computational framework to predict receptor pairs, and linked the expansion of distinct B cell clones to different tumor-associated gene expression programs. Spatial VDJ delineates B cell clonal diversity and lineage trajectories within their anatomical niche. Thus, Spatial VDJ captures lymphocyte spatial clonal architecture across tissues, providing a platform to harness clonal sequences for therapy.

Design and deep learning of synthetic B-cell-specific promoters

Synthetic biology and deep learning synergistically revolutionize our ability for decoding and recoding DNA regulatory grammar. The B-cell-specific transcriptional regulation is intricate, and unlock the potential of B-cell-specific promoters as synthetic elements is important for B-cell engineering. Here, we designed and pooled synthesized 23 640 B-cell-specific promoters that exhibit larger sequence space, B-cell-specific expression, and enable diverse transcriptional patterns in B-cells. By MPRA (Massively parallel reporter assays), we deciphered the sequence features that regulate promoter transcriptional, including motifs and motif syntax (their combination and distance). Finally, we built and trained a deep learning model capable of predicting the transcriptional strength of the immunoglobulin V gene promoter directly from sequence. Prediction of thousands of promoter variants identified in the global human population shows that polymorphisms in promoters influence the transcription of immunoglobulin V genes, which may contribute to individual differences in adaptive humoral immune responses. Our work helps to decipher the transcription mechanism in immunoglobulin genes and offers thousands of non-similar promoters for B-cell engineering.

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.

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).

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.

Integrated Drivers of Basal and Acute Immunity in Diverse Human Populations

Prior studies have identified genetic, infectious, and biological associations with immune competence and disease severity; however, there have been few integrative analyses of these factors and study populations are often limited in demographic diversity. Utilizing samples from 1,705 individuals in 5 countries, we examined putative determinants of immunity, including: single nucleotide polymorphisms, ancestry informative markers, herpesvirus status, age, and sex. In healthy subjects, we found significant differences in cytokine levels, leukocyte phenotypes, and gene expression. Transcriptional responses also varied by cohort, and the most significant determinant was ancestry. In influenza infected subjects, we found two disease severity immunophenotypes, largely driven by age. Additionally, cytokine regression models show each determinant differentially contributes to acute immune variation, with unique and interactive, location-specific herpesvirus effects. These results provide novel insight into the scope of immune heterogeneity across diverse populations, the integrative effects of factors which drive it, and the consequences for illness outcomes.

Archaic humans have contributed to large-scale variation in modern human T cell receptor genes

Human T cell receptors (TCRs) are critical for mediating immune responses to pathogens and tumors and regulating self-antigen recognition. Yet, variations in the genes encoding TCRs remain insufficiently defined. Detailed analysis of expressed TCR alpha, beta, gamma, and delta genes in 45 donors from four human populations-African, East Asian, South Asian, and European-revealed 175 additional TCR variable and junctional alleles. Most of these contained coding changes and were present at widely differing frequencies in the populations, a finding confirmed using DNA samples from the 1000 Genomes Project. Importantly, we identified three Neanderthal-derived, introgressed TCR regions including a highly divergent TRGV4 variant, which mediated altered butyrophilin-like molecule 3 (BTNL3) ligand reactivity and was frequent in all modern Eurasian population groups. Our results demonstrate remarkable variation in TCR genes in both individuals and populations, providing a strong incentive for including allelic variation in studies of TCR function in human biology.

TCR repertoire landscape reveals macrophage-mediated clone deletion in endotoxin tolerance

BACKGROUND

Endotoxin tolerance (ET) is a protective mechanism in the process of sepsis, septic shock, and their sequelae including uncontrolled inflammation. Accumulating evidence has shown that peripheral T cells contribute to the induction of ET. However, what and how T-cell development contributes to ET inductions remain unclear.

METHODS

Mice were intraperitoneally injected with LPS at a concentration of 5 mg/kg to establish an LPS tolerance model and were divided into two groups: a group examined 72 h after LPS injection (72-h group) and a group examined 8 days after LPS injection (8-day group). Injection of PBS was used as a control. We performed high-throughput sequencing to analyze the characteristics and changes of CD4⁺SP TCRβ CDR3 repertoires with respect to V direct to J rearrangement during the ET induction. Moreover, the proportion and proliferation, as well as surface molecules such as CD80 and CD86, of F4/80⁺ macrophages were analyzed using FCM. Furthermore, ACT assay was designed and administered by the tail vein into murine LPS-induced mouse model to evaluate the role of F4/80⁺ macrophages on the development of CD4⁺SP thymocytes in ET condition.

RESULTS

We found that the frequency and characteristics of the TCRβ chain CDR3 changed obviously under condition of ET, indicating the occurrence of TCR rearrangement and thymocyte diversification. Moreover, the absolute numbers of F4/80⁺ macrophages, but not other APCs, were increased in thymic medulla at 72-h group, accompanied by the elevated function-related molecules of F4/80⁺ macrophages. Furthermore, adoptively transferred OVA_332-339 peptide-loaded macrophages into Rag-1^-/- mice induced the clone deletion of OVA-specific CD4⁺SP, thereby ameliorating the pathology in lung tissue in LPS challenge.

CONCLUSIONS

These data reveal that the frequency and characteristics of the TCRβ chain CDR3 undergo dynamic programming under conditions of LPS tolerance. Furthermore, the peripheral macrophages may be a key factor which carry peripheral antigen to thymic medulla and affect the negative selection of T-cell population, thereby contributing to the formation of ET. These results suggest that the clone selection in thymus in ET may confer protection against microbial sepsis.

Analysis of IGH allele content in a sample group of rheumatoid arthritis patients demonstrates unrevealed population heterogeneity

Immunoglobulin heavy chain (IGH) germline gene variations influence the B cell receptor repertoire, with resulting biological consequences such as shaping our response to infections and altering disease susceptibilities. However, the lack of information on polymorphism frequencies in the IGH loci at the population level makes association studies challenging. Here, we genotyped a pilot group of 30 individuals with rheumatoid arthritis (RA) to examine IGH allele content and frequencies in this group. Eight novel IGHV alleles and one novel IGHJ allele were identified in the study. 15 cases were haplotypable using heterozygous IGHJ6 or IGHD anchors. One variant, IGHV4-34*01_S0742, was found in three out of 30 cases and included a single nucleotide change resulting in a non-canonical recombination signal sequence (RSS) heptamer. This variant allele, shown by haplotype analysis to be non-expressed, was also found in three out of 30 healthy controls and matched a single nucleotide polymorphism (SNP) described in the 1000 Genomes Project (1KGP) collection with frequencies that varied between population groups. Our finding of previously unreported alleles in a relatively small group of individuals with RA illustrates the need for baseline information about IG allelic frequencies in targeted study groups in preparation for future analysis of these genes in disease association studies.

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

The human immunoglobulin heavy-chain (IGH) locus is exceptionally polymorphic, with high levels of allelic and structural variation. Thus, germline IGH genotypes are personal, which may influence responses to infection and vaccination. For an improved understanding of inter-individual differences in antibody responses, we isolated SARS-CoV-2 spike-specific monoclonal antibodies from convalescent health care workers, focusing on the IGHV1-69 gene, which has the highest level of allelic variation of all IGHV genes. The IGHV1-69∗20-using CAB-I47 antibody and two similar antibodies isolated from an independent donor were critically dependent on allele usage. Neutralization was retained when reverting the V region to the germline IGHV1-69∗20 allele but lost when reverting to other IGHV1-69 alleles. Structural data confirmed that two germline-encoded polymorphisms, R50 and F55, in the IGHV1-69 gene were required for high-affinity receptor-binding domain interaction. These results demonstrate that polymorphisms in IGH genes can influence the function of SARS-CoV-2 neutralizing antibodies.

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.

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.

Targeted long-read sequencing facilitates phased diploid assembly and genotyping of the human T cell receptor alpha, delta, and beta loci

T cell receptors (TCRs) recognize peptide fragments presented by the major histocompatibility complex (MHC) and are critical to T cell-mediated immunity. Recent data have indicated that genetic diversity within TCR-encoding gene regions is underexplored, limiting understanding of the impact of TCR loci polymorphisms on TCR function in disease, even though TCR repertoire signatures (1) are heritable and (2) associate with disease phenotypes. To address this, we developed a targeted long-read sequencing approach to generate highly accurate haplotype resolved assemblies of the TCR beta (TRB) and alpha/delta (TRA/D) loci, facilitating the genotyping of all variant types, including structural variants. We validate our approach using two mother-father-child trios and 5 unrelated donors representing multiple populations. This resulted in improved genotyping accuracy and the discovery of 84 undocumented V, D, J, and C alleles, demonstrating the utility of this framework for improving our understanding of TCR diversity and function in disease.

Antibody class-switching as a strategy to improve HIV-1 neutralization

Broadly neutralizing antibodies (bNAbs), when administered through passive immunization, are protective against HIV-1 infection. Current HIV-1 vaccine strategies are aimed at guiding the immune system to make bNAbs by mimicking their development during infection. Somatic hypermutation of the variable region is known to be crucial for the development of bNAbs. More recently, however, studies have shown how class-switch recombination (CSR) resulting in the generation of different antibody isotypes may serve as an additional mechanism through which antibodies can gain neutralization breadth and potency. In this review, we discuss the importance of different antibody isotypes for HIV-1 neutralization breadth and potency and how this information can be leveraged to improve passive and active immunization against HIV-1.

Enhanced neutralization potency of an identical HIV neutralizing antibody expressed as different isotypes is achieved through genetically distinct mechanisms

Antibodies with the same variable region can exist as multiple isotypes with varying neutralization potencies, though the mechanism for this is not fully defined. We previously isolated an HIV-directed IgA1 monoclonal antibody (mAb), CAP88-CH06, and showed that IgA1 and IgG3 isotypes of this antibody demonstrated enhanced neutralization compared to IgG1. To explore the mechanism behind this, hinge region and constant heavy chain (CH1) chimeras were constructed between the IgA1, IgG3 and IgG1 mAbs and assessed for neutralization activity, antibody-dependent cellular phagocytosis (ADCP) and antibody-dependent cellular cytotoxicity (ADCC). Hinge chimeras revealed that the increased neutralization potency and phagocytosis of the IgG3 isotype was attributed to its longer hinge region. In contrast, for IgA1, CH1 chimeras showed that this region was responsible both for enhanced neutralization potency and decreased ADCP, though ADCC was not affected. Overall, these data show that the enhanced neutralization potency of CAP88-CH06 IgG3 and IgA1, compared to IgG1, is achieved through distinct mechanisms. Understanding the influence of the hinge and CH1 regions on Fab domain function may provide insights into the engineering of therapeutic antibodies with increased neutralization potency.

Profiling genes encoding the adaptive immune receptor repertoire with gAIRR Suite

Adaptive immune receptor repertoire (AIRR) is encoded by T cell receptor (TR) and immunoglobulin (IG) genes. Profiling these germline genes encoding AIRR (abbreviated as gAIRR) is important in understanding adaptive immune responses but is challenging due to the high genetic complexity. Our gAIRR Suite comprises three modules. gAIRR-seq, a probe capture-based targeted sequencing pipeline, profiles gAIRR from individual DNA samples. gAIRR-call and gAIRR-annotate call alleles from gAIRR-seq reads and annotate whole-genome assemblies, respectively. We gAIRR-seqed TRV and TRJ of seven Genome in a Bottle (GIAB) DNA samples with 100% accuracy and discovered novel alleles. We also gAIRR-seqed and gAIRR-called the TR and IG genes of a subject from both the peripheral blood mononuclear cells (PBMC) and oral mucosal cells. The calling results from these two cell types have a high concordance (99% for all known gAIRR alleles). We gAIRR-annotated 36 genomes to unearth 325 novel TRV alleles and 29 novel TRJ alleles. We could further profile the flanking sequences, including the recombination signal sequence (RSS). We validated two structural variants for HG002 and uncovered substantial differences of gAIRR genes in references GRCh37 and GRCh38. gAIRR Suite serves as a resource to sequence, analyze, and validate germline TR and IG genes to study various immune-related phenotypes.

Addressing IGHV Gene Structural Diversity Enhances Immunoglobulin Repertoire Analysis: Lessons From Rhesus Macaque

The accurate germline gene assignment and assessment of somatic hypermutation in antibodies induced by immunization or infection are important in immunological studies. Here, we illustrate issues specific to the construction of comprehensive immunoglobulin (IG) germline gene reference databases for outbred animal species using rhesus macaques, a frequently used non-human primate model, as a model test case. We demonstrate that the genotypic variation found in macaque germline inference studies is reflected in similar levels of gene diversity in genomic assemblies. We show that the high frequency of IG heavy chain V (IGHV) region structural and gene copy number variation between subjects means that individual animals lack genes that are present in other animals. Therefore, gene databases compiled from a single or too few animals will inevitably result in inaccurate gene assignment and erroneous SHM level assessment for those genes it lacks. We demonstrate this by assigning a test macaque IgG library to the KIMDB, a database compiled of germline IGHV sequences from 27 rhesus macaques, and, alternatively, to the IMGT rhesus macaque database, based on IGHV genes inferred primarily from the genomic sequence of the rheMac10 reference assembly, supplemented with 10 genes from the Mmul_051212 assembly. We found that the use of a gene-restricted database led to overestimations of SHM by up to 5% due to misassignments. The principles described in the current study provide a model for the creation of comprehensive immunoglobulin reference databases from outbred species to ensure accurate gene assignment, lineage tracing and SHM calculations.

COVID-19 Pandemic: Escape of Pathogenic Variants and MHC Evolution

We propose a new hypothesis that explains the maintenance and evolution of MHC polymorphism. It is based on two phenomena: the constitution of the repertoire of naive T lymphocytes and the evolution of the pathogen and its impact on the immune memory of T lymphocytes. Concerning the latter, pathogen evolution will have a different impact on reinfection depending on the MHC allomorph. If a mutation occurs in a given region, in the case of MHC allotypes, which do not recognize the peptide in this region, the mutation will have no impact on the memory repertoire. In the case where the MHC allomorph binds to the ancestral peptides and not to the mutated peptide, that individual will have a higher chance of being reinfected. This difference in fitness will lead to a variation of the allele frequency in the next generation. Data from the SARS-CoV-2 pandemic already support a significant part of this hypothesis and following up on these data may enable it to be confirmed. This hypothesis could explain why some individuals after vaccination respond less well than others to variants and leads to predict the probability of reinfection after a first infection depending upon the variant and the HLA allomorph.

T cell receptor beta germline variability is revealed by inference from repertoire data

BACKGROUND

T and B cell receptor (TCR, BCR) repertoires constitute the foundation of adaptive immunity. Adaptive immune receptor repertoire sequencing (AIRR-seq) is a common approach to study immune system dynamics. Understanding the genetic factors influencing the composition and dynamics of these repertoires is of major scientific and clinical importance. The chromosomal loci encoding for the variable regions of TCRs and BCRs are challenging to decipher due to repetitive elements and undocumented structural variants.

METHODS

To confront this challenge, AIRR-seq-based methods have recently been developed for B cells, enabling genotype and haplotype inference and discovery of undocumented alleles. However, this approach relies on complete coverage of the receptors' variable regions, whereas most T cell studies sequence a small fraction of that region. Here, we adapted a B cell pipeline for undocumented alleles, genotype, and haplotype inference for full and partial AIRR-seq TCR data sets. The pipeline also deals with gene assignment ambiguities, which is especially important in the analysis of data sets of partial sequences.

RESULTS

From the full and partial AIRR-seq TCR data sets, we identified 39 undocumented polymorphisms in T cell receptor Beta V (TRBV) and 31 undocumented 5 ' UTR sequences. A subset of these inferences was also observed using independent genomic approaches. We found that a single nucleotide polymorphism differentiating between the two documented T cell receptor Beta D2 (TRBD2) alleles is strongly associated with dramatic changes in the expressed repertoire.

CONCLUSIONS

We reveal a rich picture of germline variability and demonstrate how a single nucleotide polymorphism dramatically affects the composition of the whole repertoire. Our findings provide a basis for annotation of TCR repertoires for future basic and clinical studies.

A Pan-Cancer Analysis of Tumor-Infiltrating B Cell Repertoires

Tumor-infiltrating B cells can play an important role in anti-tumor responses but their presence is not well understood. In this study, we extracted the B cell receptor repertoires from 9522 tumor and adjacent non-tumor samples across 28 tumor types in the Cancer Genome Atlas project and performed diversity and network analysis. We identified differences in diversity and network statistics across tumor types and subtypes and observed a trend towards increased clonality in primary tumors compared to adjacent non-tumor tissues. We also found significant associations between the repertoire features and mutation load, tumor stage, and age. Our V-gene usage analysis identified similar V-gene usage patterns in colorectal and endometrial cancers. Lastly, we evaluated the prognostic value of the repertoire features and identified significant associations with survival in seven tumor types. This study warrants further research into better understanding the role of tumor-infiltrating B cells across a wide range of tumor types.

OUP accepted manuscript

The study and manipulation of T cell receptors (TCRs) is central to multiple fields across basic and translational immunology research. Produced by V(D)J recombination, TCRs are often only recorded in the literature and data repositories as a combination of their V and J gene symbols, plus their hypervariable CDR3 amino acid sequence. However, numerous applications require full-length coding nucleotide sequences. Here we present Stitchr, a software tool developed to specifically address this limitation. Given minimal V/J/CDR3 information, Stitchr produces complete coding sequences representing a fully spliced TCR cDNA. Due to its modular design, Stitchr can be used for TCR engineering using either published germline or novel/modified variable and constant region sequences. Sequences produced by Stitchr were validated by synthesizing and transducing TCR sequences into Jurkat cells, recapitulating the expected antigen specificity of the parental TCR. Using a companion script, Thimble, we demonstrate that Stitchr can process a million TCRs in under ten minutes using a standard desktop personal computer. By systematizing the production and modification of TCR sequences, we propose that Stitchr will increase the speed, repeatability, and reproducibility of TCR research. Stitchr is available on GitHub.

The role of metadata in reproducible computational research

Reproducible computational research (RCR) is the keystone of the scientific method for in silico analyses, packaging the transformation of raw data to published results. In addition to its role in research integrity, improving the reproducibility of scientific studies can accelerate evaluation and reuse. This potential and wide support for the FAIR principles have motivated interest in metadata standards supporting reproducibility. Metadata provide context and provenance to raw data and methods and are essential to both discovery and validation. Despite this shared connection with scientific data, few studies have explicitly described how metadata enable reproducible computational research. This review employs a functional content analysis to identify metadata standards that support reproducibility across an analytic stack consisting of input data, tools, notebooks, pipelines, and publications. Our review provides background context, explores gaps, and discovers component trends of embeddedness and methodology weight from which we derive recommendations for future work.

Immunoglobulin germline gene variation and its impact on human disease

Immunoglobulins (Ig) play an important role in the immune system both when expressed as antigen receptors on the cell surface of B cells and as antibodies secreted into extracellular fluids. The advent of high-throughput sequencing methods has enabled the investigation of human Ig repertoires at unprecedented depth. This has led to the discovery of many previously unreported germline Ig alleles. Moreover, it is becoming clear that convergent and stereotypic antibody responses are common where different individuals recognise defined antigenic epitopes with the use of the same Ig V genes. Thus, germline V gene variation is increasingly being linked to the differential capacity of generating an effective immune response, which might lead to varying disease susceptibility. Here, we review recent evidence of how germline variation in Ig genes impacts the Ig repertoire and its subsequent effects on the adaptive immune response in vaccination, infection, and autoimmunity.

Withdrawn: Precision Neoantigen Discovery Using Large-scale Immunopeptidomes and Composite Modeling of MHC Peptide Presentation

This article has been withdrawn by the authors. A publication of the manuscript with the correct figures and tables has been approved and the authors state the conclusions of the manuscript remain unaffected. Specifically, errors are in Figure 6A, Supplementary Figure 10B, Supplementary Figure 10C, and Supplementary Table 5. The details of the errors are as follows: the HLA types for one sample were incorrectly assigned because of a tumor/normal mislabeling from the biobank vendor. Due to the differing HLA types between the tumor and normal sample, the sequence analysis established that the HLA alleles for this patient had been deleted (HLA LOH). The authors conclude that this was an artifact caused by the normal sample mislabeling. The corrected version can be accessed (Pyke, R.M., Mellacheruvu, D., Dea, S., Abbott, C.W., Zhang, S.V., Philips, N.A., Harris, J., Bartha, G., Desai, S., McClory, R., West, J., Snyder, M,P., Chen, R., Boyle, S.M. (2022) Precision Neoantigen Discovery Using Large-Scale Immunopeptidomics and Composite Modeling of MHC Peptide Presentation. Mol. Cell. Proteomics 22, 100506

Current strategies for detecting functional convergence across B-cell receptor repertoires

Convergence across B-cell receptor (BCR) and antibody repertoires has become instrumental in prioritizing candidates in recent rapid therapeutic antibody discovery campaigns. It has also increased our understanding of the immune system, providing evidence for the preferential selection of BCRs to particular (immunodominant) epitopes post vaccination/infection. These important implications for both drug discovery and immunology mean that it is essential to consider the optimal way to combine experimental and computational technology when probing BCR repertoires for convergence signatures. Here, we discuss the theoretical basis for observing BCR repertoire functional convergence and explore factors of study design that can impact functional signal. We also review the computational arsenal available to detect antibodies with similar functional properties, highlighting opportunities enabled by recent clustering algorithms that exploit structural similarities between BCRs. Finally, we suggest future areas of development that should increase the power of BCR repertoire functional clustering.