Immunosequencing identifies signatures of cytomegalovirus exposure history and HLA-mediated effects on the T cell repertoire

Single T Cell Sequencing Demonstrates the Functional Role of αβ TCR Pairing in Cell Lineage and Antigen Specificity

Although structural studies of individual T cell receptors (TCRs) have revealed important roles for both the α and β chain in directing MHC and antigen recognition, repertoire-level immunogenomic analyses have historically examined the β chain alone. To determine the amount of useful information about TCR repertoire function encoded within αβ pairings, we analyzed paired TCR sequences from nearly 100,000 unique CD4+ and CD8+ T cells captured using two different high-throughput, single-cell sequencing approaches. Our results demonstrate little overlap in the healthy CD4+ and CD8+ repertoires, with shared TCR sequences possessing significantly shorter CDR3 sequences corresponding to higher generation probabilities. We further utilized tools from information theory and machine learning to show that while α and β chains are only weakly associated with lineage, αβ pairings appear to synergistically drive TCR-MHC interactions. Vαβ gene pairings were found to be the TCR feature most informative of T cell lineage, supporting the existence of germline-encoded paired αβ TCR-MHC interaction motifs. Finally, annotating our TCR pairs using a database of sequences with known antigen specificities, we demonstrate that approximately a third of the T cells possess α and β chains that each recognize different known antigens, suggesting that αβ pairing is critical for the accurate inference of repertoire functionality. Together, these findings provide biological insight into the functional implications of αβ pairing and highlight the utility of single-cell sequencing in immunogenomics.

Bioinformatic methods for cancer neoantigen prediction

Tumor cells accumulate aberrations not present in normal cells, leading to presentation of neoantigens on MHC molecules on their surface. These non-self neoantigens distinguish tumor cells from normal cells to the immune system and are thus targets for cancer immunotherapy. The rapid development of molecular profiling platforms, such as next-generation sequencing, has enabled the generation of large datasets characterizing tumor cells. The simultaneous development of algorithms has enabled rapid and accurate processing of these data. Bioinformatic software tools encoding the algorithms can be strung together in a workflow to identify neoantigens. Here, with a focus on high-throughput sequencing, we review state-of-the art bioinformatic tools along with the steps and challenges involved in neoantigen identification and recognition.

Longitudinal immunosequencing in healthy people reveals persistent T cell receptors rich in highly public receptors

Background

The adaptive immune system maintains a diversity of T cells capable of recognizing a broad array of antigens. Each T cell’s specificity for antigens is determined by its T cell receptors (TCRs), which together across all T cells form a repertoire of millions of unique receptors in each individual. Although many studies have examined how TCR repertoires change in response to disease or drugs, few have explored the temporal dynamics of the TCR repertoire in healthy individuals.

Results

Here we report immunosequencing of TCR β chains (TCRβ) from the blood of three healthy individuals at eight time points over one year. TCRβ repertoires of all peripheral-blood T cells and sorted memory T cells clustered clearly by individual, systematically demonstrating that TCRβ repertoires are specific to individuals across time. This individuality was absent from TCRβs from naive T cells, suggesting that the differences resulted from an individual’s antigen exposure history, not genetic background. Many characteristics of the TCRβ repertoire (e.g., diversity, clonality) were stable across time, although we found evidence of T cell expansion dynamics even within healthy individuals. We further identified a subset of “persistent” TCRβs present across all time points. These receptors were rich in clonal and highly public receptors and may play a key role in immune system maintenance.

Conclusions

Our results highlight the importance of longitudinal sampling of the immune system, providing a much-needed baseline for TCRβ dynamics in healthy individuals. Such a baseline will improve interpretation of changes in the TCRβ repertoire during disease or treatment.

Electronic supplementary material

The online version of this article (10.1186/s12865-019-0300-5) contains supplementary material, which is available to authorized users.

Detecting T cell receptors involved in immune responses from single repertoire snapshots

Hypervariable T cell receptors (TCRs) play a key role in adaptive immunity, recognizing a vast diversity of pathogen-derived antigens. Our ability to extract clinically relevant information from large high-throughput sequencing of TCR repertoires (RepSeq) data is limited, because little is known about TCR-disease associations. We present Antigen-specific Lymphocyte Identification by Clustering of Expanded sequences (ALICE), a statistical approach that identifies TCR sequences actively involved in current immune responses from a single RepSeq sample and apply it to repertoires of patients with a variety of disorders - patients with autoimmune disease (ankylosing spondylitis [AS]), under cancer immunotherapy, or subject to an acute infection (live yellow fever [YF] vaccine). We validate the method with independent assays. ALICE requires no longitudinal data collection nor large cohorts, and it is directly applicable to most RepSeq datasets. Its results facilitate the identification of TCR variants associated with diseases and conditions, which can be used for diagnostics and rational vaccine design.

Capturing the differences between humoral immunity in the normal and tumor environments from repertoire-seq of B-cell receptors using supervised machine learning

BACKGROUND

The recent success of immunotherapy in treating tumors has attracted increasing interest in research related to the adaptive immune system in the tumor microenvironment. Recent advances in next-generation sequencing technology enabled the sequencing of whole T-cell receptors (TCRs) and B-cell receptors (BCRs)/immunoglobulins (Igs) in the tumor microenvironment. Since BCRs/Igs in tumor tissues have high affinities for tumor-specific antigens, the patterns of their amino acid sequences and other sequence-independent features such as the number of somatic hypermutations (SHMs) may differ between the normal and tumor microenvironments. However, given the high diversity of BCRs/Igs and the rarity of recurrent sequences among individuals, it is far more difficult to capture such differences in BCR/Ig sequences than in TCR sequences. The aim of this study was to explore the possibility of discriminating BCRs/Igs in tumor and in normal tissues, by capturing these differences using supervised machine learning methods applied to RNA sequences of BCRs/Igs.

RESULTS

RNA sequences of BCRs/Igs were obtained from matched normal and tumor specimens from 90 gastric cancer patients. BCR/Ig-features obtained in Rep-Seq were used to classify individual BCR/Ig sequences into normal or tumor classes. Different machine learning models using various features were constructed as well as gradient boosting machine (GBM) classifier combining these models. The results demonstrated that BCR/Ig sequences between normal and tumor microenvironments exhibit their differences. Next, by using a GBM trained to classify individual BCR/Ig sequences, we tried to classify sets of BCR/Ig sequences into normal or tumor classes. As a result, an area under the curve (AUC) value of 0.826 was achieved, suggesting that BCR/Ig repertoires have distinct sequence-level features in normal and tumor tissues.

CONCLUSIONS

To the best of our knowledge, this is the first study to show that BCR/Ig sequences derived from tumor and normal tissues have globally distinct patterns, and that these tissues can be effectively differentiated using BCR/Ig repertoires.

T cell receptor β repertoires as novel diagnostic markers for systemic lupus erythematosus and rheumatoid arthritis

Objective

T cell receptor (TCR) diversity determines the autoimmune responses in systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA) and is closely associated with autoimmune diseases prognosis and prevention. However, the characteristics of variations in TCR diversity and their clinical significance is still unknown. Large series of patients must be studied in order to elucidate the effects of these variations.

Methods

Peripheral blood from 877 SLE patients, 206 RA patients and 439 healthy controls (HC) were amplified for the TCR repertoire and sequenced using a high-throughput sequencer. We have developed a statistical model to identify disease-associated TCR clones and diagnose autoimmune diseases.

Results

Significant differences were identified in variable (V), joining (J) and V-J pairing between the SLE or RA and HC groups. These differences can be utilised to discriminate the three groups with perfect accuracy (V: area under receiver operating curve > 0.99). One hundred ninety-eight SLE-associated and 53 RA-associated TCRs were identified and used for diseases classification by cross validation with high specificity and sensitivity. Disease-associated clones showed common features and high similarity between both autoimmune diseases. SLE displayed higher TCR heterogeneity than RA with several organ specific properties. Furthermore, the association between clonal expansion and the concentration of disease-associated clones with disease severity were identified, and pathogen-related TCRs were enriched in both diseases.

Conclusions

These characteristics of the TCR repertoire, particularly the disease-associated clones, can potentially serve as biomarkers and provide novel insights for disease status and therapeutical targets in autoimmune diseases.

Differential Effects of Influenza Virus NA, HA Head, and HA Stalk Antibodies on Peripheral Blood Leukocyte Gene Expression during Human Infection

In this study, we examined the relationships between anti-influenza virus serum antibody titers, clinical disease, and peripheral blood leukocyte (PBL) global gene expression during presymptomatic, acute, and convalescent illness in 83 participants infected with 2009 pandemic H1N1 virus in a human influenza challenge model. Using traditional statistical and logistic regression modeling approaches, profiles of differentially expressed genes that correlated with active viral shedding, predicted length of viral shedding, and predicted illness severity were identified. These analyses further demonstrated that challenge participants fell into three peripheral blood leukocyte gene expression phenotypes that significantly correlated with different clinical outcomes and prechallenge serum titers of antibodies specific for the viral neuraminidase, hemagglutinin head, and hemagglutinin stalk. Higher prechallenge serum antibody titers were inversely correlated with leukocyte responsiveness in participants with active disease and could mask expression of peripheral blood markers of clinical disease in some participants, including viral shedding and symptom severity. Consequently, preexisting anti-influenza antibodies may modulate PBL gene expression, and this must be taken into consideration in the development and interpretation of peripheral blood diagnostic and prognostic assays of influenza infection.IMPORTANCE Influenza A viruses are significant human pathogens that caused 83,000 deaths in the United States during 2017 to 2018, and there is need to understand the molecular correlates of illness and to identify prognostic markers of viral infection, symptom severity, and disease course. Preexisting antibodies against viral neuraminidase (NA) and hemagglutinin (HA) proteins play a critical role in lessening disease severity. We performed global gene expression profiling of peripheral blood leukocytes collected during acute and convalescent phases from a large cohort of people infected with A/H1N1pdm virus. Using statistical and machine-learning approaches, populations of genes were identified early in infection that correlated with active viral shedding, predicted length of shedding, or disease severity. Finally, these gene expression responses were differentially affected by increased levels of preexisting influenza antibodies, which could mask detection of these markers of contagiousness and disease severity in people with active clinical disease.

Going Beyond the Sequences: TCR Binding Patterns at the Service of Cancer Detection

Deep sequencing of T-cell receptors enables the comprehensive profiling of lymphocyte populations and the characterization of the repertoire of T-cell responses against tumors, which could be applied to diagnose cancers. Ostmeyer and colleagues introduce a novel approach to characterize TCR patterns correlating with antigen recognition. By projecting the large TCR sequence space into a handful of biophysicochemical descriptors for key residues and seeking TCRs with similar antigen-binding capabilities even in the absence of identical amino acids, this approach presents several advantages over current methods.See related article by Ostmeyer et al., p. 1671.

iReceptor: A platform for querying and analyzing antibody/B-cell and T-cell receptor repertoire data across federated repositories

Next-generation sequencing allows the characterization of the adaptive immune receptor repertoire (AIRR) in exquisite detail. These large-scale AIRR-seq data sets have rapidly become critical to vaccine development, understanding the immune response in autoimmune and infectious disease, and monitoring novel therapeutics against cancer. However, at present there is no easy way to compare these AIRR-seq data sets across studies and institutions. The ability to combine and compare information for different disease conditions will greatly enhance the value of AIRR-seq data for improving biomedical research and patient care. The iReceptor Data Integration Platform (gateway.ireceptor.org) provides one implementation of the AIRR Data Commons envisioned by the AIRR Community (airr-community.org), an initiative that is developing protocols to facilitate sharing and comparing AIRR-seq data. The iReceptor Scientific Gateway links distributed (federated) AIRR-seq repositories, allowing sequence searches or metadata queries across multiple studies at multiple institutions, returning sets of sequences fulfilling specific criteria. We present a review of the development of iReceptor, and how it fits in with the general trend toward sharing genomic and health data, and the development of standards for describing and reporting AIRR-seq data. Researchers interested in integrating their repositories of AIRR-seq data into the iReceptor Platform are invited to contact support@ireceptor.org.

Genetic Basis of Phenotypic Differences Between Chinese Yunling Black Goats and Nubian Goats Revealed by Allele-Specific Expression in Their F1 Hybrids

Chinese Yunling black goats and African Nubian goats are divergent breeds showing significant differences in body size, milk production, and environmental adaptation. However, the genetic mechanisms underlying these phenotypic differences remain to be elucidated. In this report, we provide a detailed portrait of allele-specific expression (ASE) from 54 RNA-Seq analyses across six tissues from nine F1 hybrid offspring generated by crossing the two breeds combined with 13 genomes of the two breeds. We identified a total of 524 genes with ASE, which are involved in bone development, muscle cell differentiation, and the regulation of lipid metabolic processes. We further found that 38 genes with ASE were also under directional selection by comparing 13 genomes of the two breeds; these 38 genes play important roles in metabolism, immune responses, and the adaptation to hot and humid environments. In conclusion, our study shows that the exploration of genes with ASE in F1 hybrids provides an efficient way to understand the genetic basis underlying the phenotypic differences of two diverse goat breeds.

Host Transcriptomics as a Tool to Identify Diagnostic and Mechanistic Immune Signatures of Tuberculosis

Tuberculosis (TB) is a major infectious disease worldwide, and is associated with several challenges for control and eradication. First, more accurate diagnostic tools that better represent the spectrum of infection states are required; in particular, identify the latent TB infected individuals with high risk of developing active TB. Second, we need to better understand, from a mechanistic point of view, why the immune system is unsuccessful in some cases for control and elimination of the pathogen. Host transcriptomics is a powerful approach to identify both diagnostic and mechanistic immune signatures of diseases. We have recently reported that optimal study design for these two purposes should be guided by different sets of criteria. Here, based on already published transcriptomics signatures of tuberculosis, we further develop these guidelines and identify additional factors to consider for obtaining diagnostic vs. mechanistic signatures in terms of cohorts, samples, data generation and analysis. Diagnostic studies should aim to identify small disease signatures with high discriminatory power across all affected populations, and against similar pathologies to TB. Specific focus should be made on improving the diagnosis of infected individuals at risk of developing active disease. Conversely, mechanistic studies should focus on tissues biopsies, immune relevant cell subsets, state of the art transcriptomic techniques and bioinformatics tools to understand the biological meaning of identified gene signatures that could facilitate therapeutic interventions. Finally, investigators should ensure their data are made publicly available along with complete annotations to facilitate metadata and cross-study analyses.

Next Generation Sequencing of the Pig αβ TCR Repertoire Identifies the Porcine Invariant NKT Cell Receptor

Swine represent the only livestock with an established invariant NKT (iNKT) cell-CD1d system. In this study, we exploited the fact that pig iNKT cells can be purified using a mouse CD1d tetramer reagent to establish their TCR repertoire by next generation sequencing. CD1d tetramer-positive pig cells predominantly expressed an invariant Vα-Jα rearrangement, without nontemplate nucleotide diversity, homologous to the Vα24-Jα18 and Vα14-Jα18 rearrangements of human and murine iNKT cells. The coexpressed β-chain used a Vβ segment homologous to the semivariant Vβ11 and Vβ8.2 segments of human and murine iNKT cell receptors. Molecular modeling found that contacts within CD1d and CDR1α that underlie fine specificity differences between mouse and human iNKT cells are conserved between pigs and humans, indicating that the response of porcine and human iNKT cells to CD1d-restricted Ags may be similar. Accordingly, pigs, which are an important species for diverse fields of biomedical research, may be useful for developing human-based iNKT cell therapies for cancer, infectious diseases, and other disorders. Our study also sequenced the expressed TCR repertoire of conventional porcine αβ T cells, which identified 48 Vα, 50 Jα, 18 Vβ, and 18 Jβ sequences, most of which correspond to human gene segments. These findings provide information on the αβ TCR usage of pigs, which is understudied and deserves further attention.

Can We Improve Vaccine Efficacy by Targeting T and B Cell Repertoire Convergence?

Traditional vaccine development builds on the assumption that healthy individuals have virtually unlimited antigen recognition repertoires of receptors in B cells and T cells [the B cell receptor (BCR) and TCR respectively]. However, there are indications that there are "holes" in the breadth of repertoire diversity, where no or few B or T cell are able to bind to a given antigen. Repertoire diversity may in these cases be a limiting factor for vaccine efficacy. Assuming that it is possible to predict which B and T cell receptors will respond to a given immunogen, vaccine strategies could be optimized and personalized. In addition, vaccine testing could be simplified if we could predict responses through sequencing BCR and TCRs. Bulk sequencing has shown putatively specific converging sequences after infection or vaccination. However, only single cell technologies have made it possible to capture the sequence of both heavy and light chains of a BCR or the alpha and beta chains the TCR. This has enabled the cloning of receptors and the functional validation of a predicted specificity. This review summarizes recent evidence of converging sequences in infectious diseases. Current and potential future applications of single cell technology in immune repertoire analysis are then discussed. Finally, possible short- and long- term implications for vaccine research are highlighted.

TCR repertoire evolution during maintenance of CMV-specific T-cell populations

During infections and cancer, the composition of the T-cell receptor (TCR) repertoire of antigen-specific CD8⁺ T cells changes over time. TCR avidity is thought to be a major driver of this process, thereby interacting with several additional regulators of T-cell responses to form a composite immune response architecture. Infections with latent viruses, such as cytomegalovirus (CMV), can lead to large T-cell responses characterized by an oligoclonal TCR repertoire. Here, we review the current status of experimental studies and theoretical models of TCR repertoire evolution during CMV infection. We will particularly discuss the degree to which this process may be determined through structural TCR avidity. As engineered TCR-redirected T cells have moved into the spotlight for providing more effective immunotherapies, it is essential to understand how the key features of a given TCR influence T-cell expansion and maintenance in settings of infection or malignancy. Deeper insights into these mechanisms will improve our basic understanding of T-cell immunology and help to identify optimal TCRs for immunotherapy.

Using T Cell Receptor Repertoires to Understand the Principles of Adaptive Immune Recognition

Adaptive immune recognition is mediated by antigen receptors on B and T cells generated by somatic recombination during lineage development. The high level of diversity resulting from this process posed technical limitations that previously limited the comprehensive analysis of adaptive immune recognition. Advances over the last ten years have produced data and approaches allowing insights into how T cells develop, evolutionary signatures of recombination and selection, and the features of T cell receptors that mediate epitope-specific binding and T cell activation. The size and complexity of these data have necessitated the generation of novel computational and analytical approaches, which are transforming how T cell immunology is conducted. Here we review the development and application of novel biological, theoretical, and computational methods for understanding T cell recognition and discuss the potential for improved models of receptor:antigen interactions.

Biophysicochemical Motifs in T-cell Receptor Sequences Distinguish Repertoires from Tumor-Infiltrating Lymphocyte and Adjacent Healthy Tissue

Immune repertoire deep sequencing allows comprehensive characterization of antigen receptor-encoding genes in a lymphocyte population. We hypothesized that this method could enable a novel approach to diagnose disease by identifying antigen receptor sequence patterns associated with clinical phenotypes. In this study, we developed statistical classifiers of T-cell receptor (TCR) repertoires that distinguish tumor tissue from patient-matched healthy tissue of the same organ. The basis of both classifiers was a biophysicochemical motif in the complementarity determining region 3 (CDR3) of TCRβ chains. To develop each classifier, we extracted 4-mers from every TCRβ CDR3 and represented each 4-mer using biophysicochemical features of its amino acid sequence combined with quantification of 4-mer (or receptor) abundance. This representation was scored using a logistic regression model. Unlike typical logistic regression, the classifier is fitted and validated under the requirement that at least 1 positively labeled 4-mer appears in every tumor repertoire and no positively labeled 4-mers appear in healthy tissue repertoires. We applied our method to publicly available data in which tumor and adjacent healthy tissue were collected from each patient. Using a patient-holdout cross-validation, our method achieved classification accuracy of 93% and 94% for colorectal and breast cancer, respectively. The parameter values for each classifier revealed distinct biophysicochemical properties for tumor-associated 4-mers within each cancer type. We propose that such motifs might be used to develop novel immune-based cancer screening assays. SIGNIFICANCE: This study presents a novel computational approach to identify T-cell repertoire differences between normal and tumor tissue.See related commentary by Zoete and Coukos, p. 1299.

Specific T-cell receptor gene transfer enhances immune response: A potential therapeutic strategy for the control of human cytomegalovirus infection in immunocompromised patients

Human cytomegalovirus (HCMV) infection is a leading cause of morbidity and mortality in immunocompromised patients, but no specific therapeutic strategy is effective clinically, despite recent achievements. HCMV-specific T-cell therapy was thought to be helpful for the management of HCMV infection. To conduct a deep exploration, we investigated the possibility of engineering peripheral blood mononuclear cells (PBMCs) from immunocompetent and immunocompromised subjects with specific T-cell receptor (TCR) genes. CD8-positive T cells that specifically bind to NLV pentamers could be generated by transferring TCR genes to PBMCs from immunocompetent and immunocompromised subjects. The generation of functional T cells varied among transduction of different PBMCs. The numbers of IFN-γ-secreting T cells increased significantly in immunocompetent and immunodeficient PBMCs, but were unchanged in immune-reconstituted PBMCs. TCR gene transfer is a potential therapeutic strategy for controlling HCMV infection in immunocompromised patients. The transfer of TCR genes into immunocompetent and immunodeficient PBMCs would be more meaningful in response to HCMV infection than would the transfer into immune-reconstituted PBMCs.

Antigen-Specific TCR Signatures of Cytomegalovirus Infection

CMV is a prevalent human pathogen. The virus cannot be eliminated from the body, but is kept in check by CMV-specific T cells. Patients with an insufficient T cell response, such as transplant recipients, are at high risk of developing CMV disease. However, the CMV-specific T cell repertoire is complex, and it is not yet clear which T cells protect best against virus reactivation and disease. In this study, we present a highly resolved characterization of CMV-specific human CD8⁺ T cells based on enrichment by specific peptide stimulation and mRNA sequencing of their TCR β-chains (TCRβ). Our analysis included recently identified T cell epitopes restricted through HLA-C, whose presentation is resistant to viral immunomodulation, and well-studied HLA-B-restricted epitopes. In eight healthy virus carriers, we identified a total of 1052 CMV-specific TCRβ sequences. HLA-C-restricted, CMV-specific TCRβ clonotypes dominated the ex vivo T cell response and contributed the highest-frequency clonotype of the entire repertoire in two of eight donors. We analyzed sharing and similarity of CMV-specific TCRβ sequences and identified 63 public or related sequences belonging to 17 public TCRβ families. In our cohort, and in an independent cohort of 352 donors, the cumulative frequency of these public TCRβ family members was a highly discriminatory indicator of carrying both CMV infection and the relevant HLA type. Based on these findings, we propose CMV-specific TCRβ signatures as a biomarker for an antiviral T cell response to identify patients in need of treatment and to guide future development of immunotherapy.

The variations of TRBV genes usages in the peripheral blood of a healthy population are associated with their evolution and single nucleotide polymorphisms

T cell receptors (TCRs) are a class of T cell surface molecules that recognize the antigen-derived peptides presented by the major histocompatibility complex (MHC) and are able to trigger a series of immune responses. TCRs are important members of the adaptive immune system that arose in the jawed fish 500 million years ago. T cell receptor beta variable (TRBV) genes have been widely used to characterize TCR repertoires. Studying the evolution of TRBV may help us to better understand the adaptive immune system. To investigate TRBV evolution and its impacts on the usages of TRBV genes in human populations, we compared the TRBV genes and their homologous sequences among humans, mouse, rhesus and chimpanzee, analyzed the single-nucleotide polymorphisms (SNPs) located at TRBV loci, and sequenced TCR repertoires in the peripheral blood of 97 healthy donors. We found that functional TRBVs are more evolutionarily conserved but possess more SNPs in human populations than do nonfunctional (pseudo) TRBVs. Based on the conservation levels in the four species, we classified the functional TRBVs into 2 groups: old (conserved between mouse and humans) and new (conserved only in primates). The new TRBVs evolve faster and possess more SNPs than the old TRBVs. The variations in TRBV genes frequencies in the peripheral blood of healthy donors are negatively correlated with SNP density. These observations suggest that TRBV usages may be influenced by TCR-MHC co-evolution.

Cytomegalovirus Exposure in the Elderly Does Not Reduce CD8 T Cell Repertoire Diversity

With age, the immune system becomes less effective, causing increased susceptibility to infection. Chronic CMV infection further impairs immune function and is associated with increased mortality in the elderly. CMV exposure elicits massive CD8⁺ T cell clonal expansions and diminishes the cytotoxic T cell response to subsequent infections, leading to the hypothesis that to maintain homeostasis, T cell clones are expelled from the repertoire, reducing T cell repertoire diversity and diminishing the ability to combat new infections. However, in humans, the impact of CMV infection on the structure and diversity of the underlying T cell repertoire remains uncharacterized. Using TCR β-chain immunosequencing, we observed that the proportion of the peripheral blood T cell repertoire composed of the most numerous 0.1% of clones is larger in the CMV seropositive and gradually increases with age. We found that the T cell repertoire in the elderly grows to accommodate CMV-driven clonal expansions while preserving its underlying diversity and clonal structure. Our observations suggest that the maintenance of large CMV-reactive T cell clones throughout life does not compromise the underlying repertoire. Alternatively, we propose that the diminished immunity in elderly individuals with CMV is due to alterations in cellular function rather than a reduction in CD8⁺ T cell repertoire diversity.

Precise tracking of vaccine-responding T cell clones reveals convergent and personalized response in identical twins

T cell receptor (TCR) repertoire data contain information about infections that could be used in disease diagnostics and vaccine development, but extracting that information remains a major challenge. Here we developed a statistical framework to detect TCR clone proliferation and contraction from longitudinal repertoire data. We applied this framework to data from three pairs of identical twins immunized with the yellow fever vaccine. We identified 600 to 1,700 responding TCRs in each donor and validated them using three independent assays. While the responding TCRs were mostly private, albeit with higher overlap between twins, they could be well-predicted using a classifier based on sequence similarity. Our method can also be applied to samples obtained postinfection, making it suitable for systematic discovery of new infection-specific TCRs in the clinic.

Major TCR Repertoire Perturbation by Immunodominant HLA-B*44:03-Restricted CMV-Specific T Cells

Lack of disease during chronic human cytomegalovirus (CMV) infection depends on the maintenance of a high-frequency CMV-specific T cell response. The composition of the T cell receptor (TCR) repertoire underlying this response remains poorly characterised, especially within African populations in which CMV is endemic from infancy. Here we focus on the immunodominant CD8+ T cell response to the immediate-early 2 (IE-2)-derived epitope NEGVKAAW (NW8) restricted by HLA-B^*44:03, a highly prevalent response in African populations, which in some subjects represents >10% of the circulating CD8+ T cells. Using pMHC multimer staining and sorting of NW8-specific T cells, the TCR repertoire raised against NW8 was characterised here using high-throughput sequencing in 20 HLA-B^*44:03 subjects. We found that the CD8+ T cell repertoire raised in response to NW8 was highly skewed and featured preferential use of a restricted set of V and J gene segments. Furthermore, as often seen in immunity against ancient viruses like CMV and Epstein-Barr virus (EBV), the response was strongly dominated by identical TCR sequences shared by multiple individuals, or “public” TCRs. Finally, we describe a pair “superdominant” TCR clonotypes, which were germline or nearly germline-encoded and produced at remarkably high frequencies in certain individuals, with a single CMV-specific clonotype representing up to 17% of all CD8+ T cells. Given the magnitude of the NW8 response, we propose that this major skewing of CMV-specific immunity leads to massive perturbations in the overall TCR repertoire in HLA-B^*44:03 individuals.

Clinical T Cell Receptor Repertoire Deep Sequencing and Analysis: An Application to Monitor Immune Reconstitution Following Cord Blood Transplantation

Spectratyping assays are well recognized as the clinical gold standard for assessing the T cell receptor (TCR) repertoire in haematopoietic stem cell transplant (HSCT) recipients. These assays use length distributions of the hyper variable complementarity-determining region 3 (CDR3) to characterize a patient's T cell immune reconstitution post-transplant. However, whilst useful, TCR spectratyping is notably limited by its resolution, with the technique unable to provide data on the individual clonotypes present in a sample. High-resolution clonotype data are necessary to provide quantitative clinical TCR assessments and to better understand clonotype dynamics during clinically relevant events such as viral infections or GvHD. In this study we developed and applied a CDR3 Next Generation Sequencing (NGS) methodology to assess the TCR repertoire in cord blood transplant (CBT) recipients. Using this, we obtained comprehensive TCR data from 16 CBT patients and 5 control cord samples at Great Ormond Street Hospital (GOSH). These were analyzed to provide a quantitative measurement of the TCR repertoire and its constituents in patients post-CBT. We were able to both recreate and quantify inferences typically drawn from spectratyping data. Additionally, we demonstrate that an NGS approach to TCR assessment can provide novel insights into the recovery of the immune system in these patients. We show that NGS can be used to accurately quantify TCR repertoire diversity and to provide valuable inference on clonotypes detected in a sample. We serially assessed the progress of T cell immune reconstitution demonstrating that there is dramatic variation in TCR diversity immediately following transplantation and that the dynamics of T cell immune reconstitution is perturbed by the presence of GvHD. These findings provide a proof of concept for the adoption of NGS TCR sequencing in clinical practice.

Phase I/II Trial of a Combination of Anti-CD3/CD7 Immunotoxins for Steroid-Refractory Acute Graft-versus-Host Disease

Effective therapies for treating patients with steroid-refractory acute graft-versus-host-disease (SR-aGVHD), particularly strategies that reduce the duration of immunosuppression following remission, are urgently needed. The investigated immunotoxin combination consists of a mixture of anti-CD3 and anti-CD7 antibodies separately conjugated to recombinant ricin A (CD3/CD7-IT), which induces in vivo depletion of T cells and natural killer (NK) cells and suppresses T cell receptor activation. We conducted a phase I/II trial to examine the safety and efficacy of CD3/CD7-IT in 20 patients with SR-aGVHD; 17 of these patients (85%) had severe SR-aGVHD, and all 20 patients had visceral organ involvement, including 18 (90%) with gastrointestinal (GI) involvement and 5 (25%) with liver involvement. A validated 2-biomarker algorithm classified the majority of patients (11 of 20) as high risk. On day 28 after the start of CD3/CD7-IT therapy, the overall response rate was 60% (12 of 20), with 10 patients (50%) achieving a complete response. The 6-month overall survival rate was 60% (12 of 20), including 64% (7 of 11) classified as high risk by biomarkers. The 1-week course of treatment with CD3/CD7-IT caused profound but transient depletion of T cells and NK cells, followed by rapid recovery of the immune system with a diverse TCR Vβ repertoire, and preservation of Epstein-Barr virus- and cytomegalovirus-specific T cell clones. Furthermore, our results indicate that CD3/CD7-IT appeared to be safe and well tolerated, with a relatively low prevalence of manageable and reversible adverse events, primarily worsening of hypoalbuminemia, microangiopathy, and thrombocytopenia. These encouraging results suggest that CD3/CD7-IT may improve patient outcomes in patients with SR-aGVHD.

TCR repertoire profiling of tumors, adjacent normal tissues, and peripheral blood predicts survival in nasopharyngeal carcinoma

The T-cell immune responses in nasopharyngeal carcinoma patients have been extensively investigated recently for designing adoptive immunotherapy or immune checkpoint blockade therapy. However, the distribution characteristics of T cells associated with NPC pathogenesis are largely unknown. We performed deep sequencing for TCR repertoire profiling on matched tumor/adjacent normal tissue from 15 NPC patients and peripheral blood from 39 NPC patients, 39 patients with other nasopharyngeal diseases, and 33 healthy controls. We found that a lower diversity of TCR repertoire in tumors than paired tissues or a low similarity between the paired tissues was associated with a poor prognosis in NPC. A more diverse TCR repertoire was identified in the peripheral blood of NPC patients relative to the controls; this was related to a significant decrease in the proportion of high-frequency TCR clones in NPC. Higher diversity in peripheral blood of NPC patients was associated with a worse prognosis. Due to the peculiarity of the Vβ gene usage patterns in the peripheral blood of NPC patients, 15 Vβ genes were selected to distinguish NPC patients from controls by the least absolute shrinkage and selection operator analysis. We identified 11 clonotypes shared by tumors and peripheral blood samples from different NPC patients, defined as "NPC-associated" that might have value in adoptive immunotherapy. In conclusion, we here report the systematic and overall characteristics of the TCR repertoire in tumors, adjacent normal tissues, and peripheral blood of NPC patients. The data obtained may be relevant to future clinical studies in the setting of immunotherapy for NPC patients.

The landscape and diagnostic potential of T and B cell repertoire in Immunoglobulin A Nephropathy

Immunoglobulin A Nephropathy (IgAN) is the most common glomerulonephritis worldwide. The pathologic hallmark of IgAN is immune complex deposited in glomerular mesangium, which induces inflammation and affects the kidney's normal functions. The exact pathogenesis of IgAN, however, remains obscure. Further, in current clinical practice, the diagnosis relies on needle biopsy of renal tissue. Therefore, a non-invasive method for diagnosis and prognosis surveillance of the disease is highly desirable. To this end, we investigated the T cell receptor beta chain (TCRB) and immunoglobulin heavy chain (IGH) repertoire in circulating lymphocytes and compared them with kidney infiltrating lymphocytes using immune repertoire high throughput sequencing. We found that some features of TCRB and IGH in renal tissues were remarkably different from that in the blood, including decreased repertoire diversity, increased IgA and IgG frequency, and more antigen-experienced B cells. The complementarity-determining region 3 (CDR3) length of circulating TCRB and IGH in IgAN patients was significantly shorter than that in healthy controls, which is the result of both VDJ rearrangement and clonal selection. The IgA1 frequency in the blood of IgAN patients is significantly higher than that in other Nephropathy (NIgAN) patients and healthy control. Importantly we identified a set of TCRB and IGH clones, which can be used to distinguish IgAN from NIgAN and healthy controls with high accuracy. These results indicated that the TCRB and IGH repertoire can potentially serve as non-invasive biomarkers for the diagnosis of IgAN. The characteristics of the kidney infiltrating and circulating lymphocytes repertoires shed light on IgAN detection, treatment and surveillance.

The expanding role of systems immunology in decoding the T cell receptor repertoire

T cells play a crucial role in the immune system's defense against many infectious diseases, including persistent infections for which no effective vaccines currently exist. The T cell component of the adaptive immune system is highly complex involving a constantly evolving landscape of various inter-related T cell populations. These T cell populations are characterized by their phenotypic and functional properties as well as the collection, or repertoire, of T cell receptors (TCR) that mediate T cell recognition of antigenic peptides derived from pathogens. Understanding the various processes and factors that impact the development and evolution of the broader T cell repertoire available to recognize and respond to pathogens and the characteristics of antigen-experienced T cell repertoires associated with effective immune control of pathogens is critical to the rational design of T cell-based vaccines and therapies. In this article we discuss, using examples of recent research, the promise that systems immunology approaches, involving quantitative analysis and mathematical and computational modeling of immunological data, hold for decoding the complex TCR repertoire system in the current era of advancing technologies.

Human T cell receptor occurrence patterns encode immune history, genetic background, and receptor specificity

The T cell receptor (TCR) repertoire encodes immune exposure history through the dynamic formation of immunological memory. Statistical analysis of repertoire sequencing data has the potential to decode disease associations from large cohorts with measured phenotypes. However, the repertoire perturbation induced by a given immunological challenge is conditioned on genetic background via major histocompatibility complex (MHC) polymorphism. We explore associations between MHC alleles, immune exposures, and shared TCRs in a large human cohort. Using a previously published repertoire sequencing dataset augmented with high-resolution MHC genotyping, our analysis reveals rich structure: striking imprints of common pathogens, clusters of co-occurring TCRs that may represent markers of shared immune exposures, and substantial variations in TCR-MHC association strength across MHC loci. Guided by atomic contacts in solved TCR:peptide-MHC structures, we identify sequence covariation between TCR and MHC. These insights and our analysis framework lay the groundwork for further explorations into TCR diversity.

Exploring the pre-immune landscape of antigen-specific T cells

Background

Adaptive immune responses to newly encountered pathogens depend on the mobilization of antigen-specific clonotypes from a vastly diverse pool of naive T cells. Using recent advances in immune repertoire sequencing technologies, models of the immune receptor rearrangement process, and a database of annotated T cell receptor (TCR) sequences with known specificities, we explored the baseline frequencies of T cells specific for defined human leukocyte antigen (HLA) class I-restricted epitopes in healthy individuals.

Methods

We used a database of TCR sequences with known antigen specificities and a probabilistic TCR rearrangement model to estimate the baseline frequencies of TCRs specific to distinct antigens epitopespecificT-cells. We verified our estimates using a publicly available collection of TCR repertoires from healthy individuals. We also interrogated a database of immunogenic and non-immunogenic peptides is used to link baseline T-cell frequencies with epitope immunogenicity.

Results

Our findings revealed a high degree of variability in the prevalence of T cells specific for different antigens that could be explained by the physicochemical properties of the corresponding HLA class I-bound peptides. The occurrence of certain rearrangements was influenced by ancestry and HLA class I restriction, and umbilical cord blood samples contained higher frequencies of common pathogen-specific TCRs. We also identified a quantitative link between specific T cell frequencies and the immunogenicity of cognate epitopes presented by defined HLA class I molecules.

Conclusions

Our results suggest that the population frequencies of specific T cells are strikingly non-uniform across epitopes that are known to elicit immune responses. This inference leads to a new definition of epitope immunogenicity based on specific TCR frequencies, which can be estimated with a high degree of accuracy in silico, thereby providing a novel framework to integrate computational and experimental genomics with basic and translational research efforts in the field of T cell immunology.

Electronic supplementary material

The online version of this article (10.1186/s13073-018-0577-7) contains supplementary material, which is available to authorized users.

Predicting the spectrum of TCR repertoire sharing with a data-driven model of recombination

Despite the extreme diversity of T-cell repertoires, many identical T-cell receptor (TCR) sequences are found in a large number of individual mice and humans. These widely shared sequences, often referred to as "public," have been suggested to be over-represented due to their potential immune functionality or their ease of generation by V(D)J recombination. Here, we show that even for large cohorts, the observed degree of sharing of TCR sequences between individuals is well predicted by a model accounting for the known quantitative statistical biases in the generation process, together with a simple model of thymic selection. Whether a sequence is shared by many individuals is predicted to depend on the number of queried individuals and the sampling depth, as well as on the sequence itself, in agreement with the data. We introduce the degree of publicness conditional on the queried cohort size and the size of the sampled repertoires. Based on these observations, we propose a public/private sequence classifier, "PUBLIC" (Public Universal Binary Likelihood Inference Classifier), based on the generation probability, which performs very well even for small cohort sizes.

The Bayesian optimist's guide to adaptive immune receptor repertoire analysis

Probabilistic modeling is fundamental to the statistical analysis of complex data. In addition to forming a coherent description of the data-generating process, probabilistic models enable parameter inference about given datasets. This procedure is well developed in the Bayesian perspective, in which one infers probability distributions describing to what extent various possible parameters agree with the data. In this paper, we motivate and review probabilistic modeling for adaptive immune receptor repertoire data then describe progress and prospects for future work, from germline haplotyping to adaptive immune system deployment across tissues. The relevant quantities in immune sequence analysis include not only continuous parameters such as gene use frequency but also discrete objects such as B-cell clusters and lineages. Throughout this review, we unravel the many opportunities for probabilistic modeling in adaptive immune receptor analysis, including settings for which the Bayesian approach holds substantial promise (especially if one is optimistic about new computational methods). From our perspective, the greatest prospects for progress in probabilistic modeling for repertoires concern ancestral sequence estimation for B-cell receptor lineages, including uncertainty from germline genotype, rearrangement, and lineage development.

Memory CD4+ T cell receptor repertoire data mining as a tool for identifying cytomegalovirus serostatus

Pathogens of past and current infections have been identified directly by means of PCR or indirectly by measuring a specific immune response (e.g., antibody titration). Using a novel approach, Emerson and colleagues showed that the cytomegalovirus serostatus can also be accurately determined by using a T cell receptor repertoire data mining approach. In this study, we have sequenced the CD4⁺ memory T cell receptor repertoire of a Belgian cohort with known cytomegalovirus serostatus. A random forest classifier was trained on the CMV specific T cell receptor repertoire signature and used to classify individuals in the Belgian cohort. This study shows that the novel approach can be reliably replicated with an equivalent performance as that reported by Emerson and colleagues. Additionally, it provides evidence that the T cell receptor repertoire signature is to a large extent present in the CD4⁺ memory repertoire.

RepSeq Data Representativeness and Robustness Assessment by Shannon Entropy

High-throughput sequencing (HTS) has the potential to decipher the diversity of T cell repertoires and their dynamics during immune responses. Applied to T cell subsets such as T effector and T regulatory cells, it should help identify novel biomarkers of diseases. However, given the extreme diversity of TCR repertoires, understanding how the sequencing conditions, including cell numbers, biological and technical sampling and sequencing depth, impact the experimental outcome is critical to proper use of these data. Here, we assessed the representativeness and robustness of TCR repertoire diversity assessment according to experimental conditions. By comparative analyses of experimental datasets and computer simulations, we found that (i) for small samples, the number of clonotypes recovered is often higher than the number of cells per sample, even after removing the singletons; (ii) high-sequencing depth for small samples alters the clonotype distributions, which can be corrected by filtering the datasets using Shannon entropy as a threshold; and (iii) a single sequencing run at high depth does not ensure a good coverage of the clonotype richness in highly polyclonal populations, which can be better covered using multiple sequencing. Altogether, our results warrant better understanding and awareness of the limitation of TCR diversity analyses by HTS and justify the development of novel computational tools for improved modeling of the highly complex nature of TCR repertoires.

Disease-driving CD4+ T cell clonotypes persist for decades in celiac disease

Little is known about the repertoire dynamics and persistence of pathogenic T cells in HLA-associated disorders. In celiac disease, a disorder with a strong association with certain HLA-DQ allotypes, presumed pathogenic T cells can be visualized and isolated with HLA-DQ:gluten tetramers, thereby enabling further characterization. Single and bulk populations of HLA-DQ:gluten tetramer-sorted CD4+ T cells were analyzed by high-throughput DNA sequencing of rearranged TCR-α and -β genes. Blood and gut biopsy samples from 21 celiac disease patients, taken at various stages of disease and in intervals of weeks to decades apart, were examined. Persistence of the same clonotypes was seen in both compartments over decades, with up to 53% overlap between samples obtained 16 to 28 years apart. Further, we observed that the recall response following oral gluten challenge was dominated by preexisting CD4+ T cell clonotypes. Public features were frequent among gluten-specific T cells, as 10% of TCR-α, TCR-β, or paired TCR-αβ amino acid sequences of total 1813 TCRs generated from 17 patients were observed in 2 or more patients. In established celiac disease, the T cell clonotypes that recognize gluten are persistent for decades, making up fixed repertoires that prevalently exhibit public features. These T cells represent an attractive therapeutic target.

Detailed Characterization of T Cell Receptor Repertoires in Multiple Sclerosis Brain Lesions

The antigen-specific activation of pathogenic T cells is considered essential in the initiation and maintenance of multiple sclerosis (MS). The site of activation, the differential involvement of CD4+, and CD8+ T cells, their functional phenotype, and specificity, are important aspects to understand MS pathogenesis. The analysis of clonal expansions of brain-infiltrating T cells may reveal local antigen-driven activation or specific brain homing and allow the identification of putatively pathogenic T cells. We used high-throughput T cell receptor β-chain variable gene (TRBV) sequencing (-seq) of genomic (g)DNA, which reflects the quantity and diversity of the TRBV repertoire, to characterize three white matter demyelinating lesions with different location and inflammatory activity, and paired peripheral blood memory CD4+ and CD8+ T cell pools from a secondary progressive (SP)MS patient. Our results revealed an important sharing of clonally expanded T cells with identical TRBV sequence (clonotypes) across MS lesions independently of their proximity or inflammatory activity. Comparison with circulating T cells showed that the most frequent brain-infiltrating CD8+, but not CD4+ clonotypes were also those with highest frequency in the peripheral blood, indicating clonal expansion inside the brain or specific brain homing of CD4+ but not CD8+ T cells. Parallel TRBV-seq of complementary (c)DNA that reflects the activation status of the cells, revealed differences between lesions regarding inflammatory activity and appears to facilitate the identification of putatively pathogenic T cells in active lesions. Approaches to identify pathogenic T cells in brain lesions using TRBV-seq may benefit from focusing on lesions with high inflammatory activity and from combining gDNA and cDNA sequencing.

Method for identification of condition-associated public antigen receptor sequences

Diverse repertoires of hypervariable immunoglobulin receptors (TCR and BCR) recognize antigens in the adaptive immune system. The development of immunoglobulin receptor repertoire sequencing methods makes it possible to perform repertoire-wide disease association studies of antigen receptor sequences. We developed a statistical framework for associating receptors to disease from only a small cohort of patients, with no need for a control cohort. Our method successfully identifies previously validated Cytomegalovirus and type one diabetes responsive TCRβ sequences .

History, applications, and challenges of immune repertoire research

The diversity of T and B cells in terms of their receptor sequences is huge in the vertebrate's immune system and provides broad protection against the vast diversity of pathogens. Immune repertoire is defined as the sum of T cell receptors and B cell receptors (also named immunoglobulin) that makes the organism's adaptive immune system. Before the emergence of high-throughput sequencing, the studies on immune repertoire were limited by the underdeveloped methodologies, since it was impossible to capture the whole picture by the low-throughput tools. The massive paralleled sequencing technology suits perfectly the researches on immune repertoire. In this article, we review the history of immune repertoire studies, in terms of technologies and research applications. Particularly, we discuss several aspects of challenges in this field and highlight the efforts to develop potential solutions, in the era of high-throughput sequencing of the immune repertoire.

Computational Strategies for Dissecting the High-Dimensional Complexity of Adaptive Immune Repertoires

The adaptive immune system recognizes antigens via an immense array of antigen-binding antibodies and T-cell receptors, the immune repertoire. The interrogation of immune repertoires is of high relevance for understanding the adaptive immune response in disease and infection (e.g., autoimmunity, cancer, HIV). Adaptive immune receptor repertoire sequencing (AIRR-seq) has driven the quantitative and molecular-level profiling of immune repertoires, thereby revealing the high-dimensional complexity of the immune receptor sequence landscape. Several methods for the computational and statistical analysis of large-scale AIRR-seq data have been developed to resolve immune repertoire complexity and to understand the dynamics of adaptive immunity. Here, we review the current research on (i) diversity, (ii) clustering and network, (iii) phylogenetic, and (iv) machine learning methods applied to dissect, quantify, and compare the architecture, evolution, and specificity of immune repertoires. We summarize outstanding questions in computational immunology and propose future directions for systems immunology toward coupling AIRR-seq with the computational discovery of immunotherapeutics, vaccines, and immunodiagnostics.

Sex bias in MHC I-associated shaping of the adaptive immune system

HLA associations, T cell receptor (TCR) repertoire bias, and sex bias have independently been shown for many diseases. While some immunological differences between the sexes have been described, they do not fully explain bias in men toward many infections/cancers, and toward women in autoimmunity. Next-generation TCR variable beta chain (TCRBV) immunosequencing of 824 individuals was evaluated in a multiparametric analysis including HLA-A -B/MHC class I background, TCRBV usage, sex, age, ethnicity, and TCRBV selection/expansion dynamics. We found that HLA-associated shaping of TCRBV usage differed between the sexes. Furthermore, certain TCRBVs were selected and expanded in unison. Correlations between these TCRBV relationships and biochemical similarities in HLA-binding positions were different in CD8 T cells of patients with autoimmune diseases (multiple sclerosis and rheumatoid arthritis) compared with healthy controls. Within patients, men showed higher TCRBV relationship Spearman's rhos in relation to HLA-binding position similarities compared with women. In line with this, CD8 T cells of men with autoimmune diseases also showed higher degrees of TCRBV perturbation compared with women. Concerted selection and expansion of CD8 T cells in patients with autoimmune diseases, but especially in men, appears to be less dependent on high HLA-binding similarity than in CD4 T cells. These findings are consistent with studies attributing autoimmunity to processes of epitope spreading and expansion of low-avidity T cell clones and may have further implications for the interpretation of pathogenic mechanisms of infectious and autoimmune diseases with known HLA associations. Reanalysis of some HLA association studies, separating the data by sex, could be informative.

High-throughput immune repertoire analysis with IGoR

High-throughput immune repertoire sequencing is promising to lead to new statistical diagnostic tools for medicine and biology. Successful implementations of these methods require a correct characterization, analysis, and interpretation of these data sets. We present IGoR (Inference and Generation Of Repertoires)-a comprehensive tool that takes B or T cell receptor sequence reads and quantitatively characterizes the statistics of receptor generation from both cDNA and gDNA. It probabilistically annotates sequences and its modular structure can be used to investigate models of increasing biological complexity for different organisms. For B cells, IGoR returns the hypermutation statistics, which we use to reveal co-localization of hypermutations along the sequence. We demonstrate that IGoR outperforms existing tools in accuracy and estimate the sample sizes needed for reliable repertoire characterization.

[IGoR: a tool for learning and simulating the random generation of antigen receptors]

Antigen receptors, which form the base of the adaptive immune system, are created stochastically by a DNA editing process called V(D)J recombination. As high-throughput sequencing enables to study the repertoire of these receptors, it is now possible to learn the probabilistic laws of this random process, and to use them to analyse receptors of interest, generate synthetic repertoires to create controls, or aid the identification of receptors that are specific to diseases, with possible applications for medical diagnostics. This article describes how these tasks can be performed using the IGoR software, which can learn statistical models from data, annotate existing sequences, or generate new synthetic ones with the same laws as the recombination process.

IgA Function in Relation to the Intestinal Microbiota

IgA is the dominant immunoglobulin isotype produced in mammals, largely secreted across the intestinal mucosal surface. Although induction of IgA has been a hallmark feature of microbiota colonization following colonization in germ-free animals, until recently appreciation of the function of IgA in host-microbial mutualism has depended mainly on indirect evidence of alterations in microbiota composition or penetration of microbes in the absence of somatic mutations in IgA (or compensatory IgM). Highly parallel sequencing techniques that enable high-resolution analysis of either microbial consortia or IgA sequence diversity are now giving us new perspectives on selective targeting of microbial taxa and the trajectory of IgA diversification according to induction mechanisms, between different individuals and over time. The prospects are to link the range of diversified IgA clonotypes to specific antigenic functions in modulating the microbiota composition, position and metabolism to ensure host mutualism.

T cell receptor sequencing of early-stage breast cancer tumors identifies altered clonal structure of the T cell repertoire

Tumor-infiltrating T cells play an important role in many cancers, and can improve prognosis and yield therapeutic targets. We characterized T cells infiltrating both breast cancer tumors and the surrounding normal breast tissue to identify T cells specific to each, as well as their abundance in peripheral blood. Using immune profiling of the T cell beta-chain repertoire in 16 patients with early-stage breast cancer, we show that the clonal structure of the tumor is significantly different from adjacent breast tissue, with the tumor containing ∼2.5-fold greater density of T cells and higher clonality compared with normal breast. The clonal structure of T cells in blood and normal breast is more similar than between blood and tumor, and could be used to distinguish tumor from normal breast tissue in 14 of 16 patients. Many T cell sequences overlap between tissue and blood from the same patient, including ∼50% of T cells between tumor and normal breast. Both tumor and normal breast contain high-abundance "enriched" sequences that are absent or of low abundance in the other tissue. Many of these T cells are either not detected or detected with very low frequency in the blood, suggesting the existence of separate compartments of T cells in both tumor and normal breast. Enriched T cell sequences are typically unique to each patient, but a subset is shared between many different patients. We show that many of these are commonly generated sequences, and thus unlikely to play an important role in the tumor microenvironment.

T Cell Receptor Profiling in Type 1 Diabetes

PURPOSE OF REVIEW

The genetic susceptibility and dominant protection for type 1 diabetes (T1D) associated with human leukocyte antigen (HLA) haplotypes, along with minor risk variants, have long been thought to shape the T cell receptor (TCR) repertoire and eventual phenotype of autoreactive T cells that mediate β-cell destruction. While autoantibodies provide robust markers of disease progression, early studies tracking autoreactive T cells largely failed to achieve clinical utility.

RECENT FINDINGS

Advances in acquisition of pancreata and islets from T1D organ donors have facilitated studies of T cells isolated from the target tissues. Immunosequencing of TCR α/β-chain complementarity determining regions, along with transcriptional profiling, offers the potential to transform biomarker discovery. Herein, we review recent studies characterizing the autoreactive TCR signature in T1D, emerging technologies, and the challenges and opportunities associated with tracking TCR molecular profiles during the natural history of T1D.

A constant companion: immune recognition and response to cytomegalovirus with aging and implications for immune fitness

Approximately 50% of individuals aged 6-49 years in the United States are infected with cytomegalovirus (CMV), with seroprevalence increasing with age, reaching 85-90% by 75-80 years according to Bate et al. (Clin Infect Dis 50 (11): 1439-1447, 2010) and Pawelec et al. (Curr Opin Immunol 24:507-511, 2012). Following primary infection, CMV establishes lifelong latency with periodic reactivation. Immunocompetent hosts experience largely asymptomatic infection, but CMV can cause serious illness in immunocompromised populations, such as transplant patients and the elderly. Control of CMV requires constant immune surveillance, and recent discoveries suggest this demand alters general features of the immune system in infected individuals. Here, we review recent advances in the understanding of the immune response to CMV and the role of CMV in immune aging and fitness, while highlighting the importance of potential confounding factors that influence CMV studies. Understanding how CMV contributes to shaping "baseline" immunity has important implications for a host's ability to mount effective responses to diverse infections and vaccination.