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

T-cell immunity induced and reshaped by an anti-HPV immuno-oncotherapeutic lentiviral vector

We recently developed an immuno-oncotherapy against human papillomavirus (HPV)-induced tumors based on a lentiviral vector encoding the Early E6 and E7 oncoproteins of HPV16 and HPV18 genotypes, namely "Lenti-HPV-07". The robust and long-lasting anti-tumor efficacy of Lenti-HPV-07 is dependent on CD8+ T-cell induction and remodeling of the tumor microenvironment. Here, we first established that anti-vector immunity induced by Lenti-HPV-07 prime has no impact on the efficacy of a homologous boost to amplify anti-HPV T-cell immunity. To longitudinally monitor the evolution of the T-cell repertoire generated after the prime, homologous or heterologous boost with Lenti-HPV-07, we tracked T-cell clonotypes by deep sequencing of T-Cell Receptor (TCR) variable β and α chain mRNA, applied to whole peripheral blood cells (PBL) and a T cell population specific of an immunodominant E7HPV16 epitope. We observed a hyper-expansion of clonotypes post prime, accompanied by increased frequencies of HPV-07-specific T cells. Additionally, there was a notable diversification of clonotypes post boost in whole PBL, but not in the E7HPV16-specific T cells. We then demonstrated that the effector functions of such Lenti-HPV-07-induced T cells synergize with anti-checkpoint inhibitory treatments by systemic administration of anti-TIM3 or anti-NKG2A monoclonal antibodies. While Lenti-HPV-07 is about to enter a Phase I/IIa clinical trial, these results will help better elucidate its mode of action in immunotherapy against established HPV-mediated malignancies.

Detecting T-cell clonal expansions and quantifying clone survival using deep profiling of immune repertoires

An individual's T-cell repertoire constantly changes under the influence of external and internal factors. Cells that do not receive a stimulatory signal die, while those that encounter and recognize a pathogen or receive a co-stimulatory signal divide, resulting in clonal expansions. T-cell clones can be traced by monitoring the presence of their unique T-cell receptor (TCR) sequence, which is assembled de novo through a process known as V(D)J rearrangement. Tracking T cells can provide valuable insights into the survival of cells after hematopoietic stem cell transplantation (HSCT) or cancer treatment response and can indicate the induction of protective immunity by vaccination. In this study, we report a bioinformatic method for quantifying the T-cell repertoire dynamics from TCR sequencing data. We demonstrate its utility by measuring the T-cell repertoire stability in healthy donors, by quantifying the effect of donor lymphocyte infusion (DLI), and by tracking the fate of the different T-cell subsets in HSCT patients and the expansion of pathogen-specific clones in vaccinated individuals.

Characterizing the T Cell Repertoire in the Proximal Airway in Health and Disease

OBJECTIVES

Recent translational scientific efforts in subglottic stenosis (SGS) support a disease model where epithelial alterations facilitate microbiome displacement, dysregulated immune activation, and localized fibrosis. Given the observed immune cell infiltrate in SGS, we sought to test the hypothesis that SGS cases possessed a low diversity (highly clonal) adaptive immune response when compared with healthy controls.

METHODS

Single cell RNA sequencing (scRNA-seq) of subglottic mucosal scar in iSGS (n = 24), iLTS (n = 8), and healthy controls (n = 7) was performed. T cell receptor (TCR) sequences were extracted, analyzed, and used to construct repertoire structure, compare diversity, interrogate overlap, and define antigenic targets using the Immunarch bioinformatics pipeline.

RESULTS

The proximal airway mucosa in health and disease are equally diverse via Hill framework quantitation (iSGS vs. iLTS vs. Control, p > 0.05). Repertoires do not significantly overlap between individuals (Morisita <0.02). Among iSGS patients, clonality of the TCR repertoire is driven by CD8+ T cells, and iSGS patients possess numerous TCRs targeting viral and intercellular pathogens. High frequency clonotypes do not map to known targets in public datasets.

CONCLUSION

SGS cases do not possess a lower diversity adaptive immune infiltrate when compared with healthy controls. Interestingly, the TCR repertoire in both health and disease contains a restricted number of high frequency clonotypes that do not significantly overlap between individuals. The target of the high frequency clonotypes in health and disease remain unresolved.

LEVEL OF EVIDENCE

NA Laryngoscope, 134:1757-1764, 2024.

Repeated mRNA vaccination sequentially boosts SARS-CoV-2-specific CD8+ T cells in persons with previous COVID-19

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) hybrid immunity is more protective than vaccination or previous infection alone. To investigate the kinetics of spike-reactive T (TS) cells from SARS-CoV-2 infection through messenger RNA vaccination in persons with hybrid immunity, we identified the T cell receptor (TCR) sequences of thousands of index TS cells and tracked their frequency in bulk TCRβ repertoires sampled longitudinally from the peripheral blood of persons who had recovered from coronavirus disease 2019 (COVID-19). Vaccinations led to large expansions in memory TS cell clonotypes, most of which were CD8+ T cells, while also eliciting diverse TS cell clonotypes not observed before vaccination. TCR sequence similarity clustering identified public CD8+ and CD4+ TCR motifs associated with spike (S) specificity. Synthesis of longitudinal bulk ex vivo single-chain TCRβ repertoires and paired-chain TCRɑβ sequences from droplet sequencing of TS cells provides a roadmap for the rapid assessment of T cell responses to vaccines and emerging pathogens.

Altered T-cell receptor β repertoire in adults with SARS CoV-2 inactivated vaccine of BBIBP-CorV

OBJECTIVE

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused the prolonged and widespread epidemic of coronavirus disease 2019 (COVID-19). The inactivated BBIBP-CorV vaccine has shown safety, efficacy and immunogenicity against COVID-19 in in-vitro studies and clinical trials. However, the characteristics changes of the TCRβ repertoire in patients receiving BBIBP-CorV remain unclear.

METHODS

TCRβ repertoire difference were analyzed between 54 uninfected subjects who received a third dose of the enhanced BBIBP-CorV vaccine and the 16 healthy donors who did not receive the vaccine and 44 COVID-19 patients with different courses of disease (asymptomatic, symptomatic and convalescent). Furthermore, antibody response, anti-inflammatory and pro-inflammatory cytokines also were examined.

RESULTS

We found that the third dose inactivated coronavirus vaccine induced widespread changes including the increased TCRβ repertoire diversity, a much shorter CDR3 length and high usage of V-J genes segments. Meanwhile, the vaccine-responding clones were also predicted. The results of the antibody response showed that 90.7 % of the vaccinated individuals were positive for NAb seroconversion and 88.9 % for IgG antibody about 60 days after the third dose. The concentration of IL-2 increased significantly compared to baseline inoculation.

CONCLUSION

Altered TCRβ repertoire in adults with SARS CoV-2 inactivated vaccine of BBIBP-CorV clarified the specific immunity induced by inactivated vaccines. Our research provides insights into the adaptive immune response induced by the new inactivated SARS-CoV-2 vaccine and strengthens the development of immunotherapy.

An integrated approach to the characterization of immune repertoires using AIMS: An Automated Immune Molecule Separator

The adaptive immune system employs an array of receptors designed to respond with high specificity to pathogens or molecular aberrations faced by the host organism. Binding of these receptors to molecular fragments-collectively referred to as antigens-initiates immune responses. These antigenic targets are recognized in their native state on the surfaces of pathogens by antibodies, whereas T cell receptors (TCR) recognize processed antigens as short peptides, presented on major histocompatibility complex (MHC) molecules. Recent research has led to a wealth of immune repertoire data that are key to interrogating the nature of these molecular interactions. However, existing tools for the analysis of these large datasets typically focus on molecular sets of a single type, forcing researchers to separately analyze strongly coupled sequences of interacting molecules. Here, we introduce a software package for the integrated analysis of immune repertoire data, capable of identifying distinct biophysical differences in isolated TCR, MHC, peptide, antibody, and antigen sequence data. This integrated analytical approach allows for direct comparisons across immune repertoire subsets and provides a starting point for the identification of key interaction hotspots in complementary receptor-antigen pairs. The software (AIMS-Automated Immune Molecule Separator) is freely available as an open access package in GUI or command-line form.

mRNA vaccination boosts S-specific T cell memory and promotes expansion of CD45RAint TEMRA-like CD8+ T cells in COVID-19 recovered individuals

SARS-CoV-2 infection and mRNA vaccination both elicit spike (S)-specific T cell responses. To analyze how T cell memory from prior infection influences T cell responses to vaccination, we evaluated functional T cell responses in naive and previously infected vaccine recipients. Pre-vaccine S-specific responses are predictive of subsequent CD8+ T cell vaccine-response magnitudes. Comparing baseline with post-vaccination TCRβ repertoires, we observed large clonotypic expansions correlated with the frequency of spike-specific T cells. Epitope mapping the largest CD8+ T cell responses confirms that an HLA-A∗03:01 epitope was highly immunodominant. Peptide-MHC tetramer staining together with mass cytometry and single-cell sequencing permit detailed phenotyping and clonotypic tracking of these S-specific CD8+ T cells. Our results demonstrate that infection-induced S-specific CD8+ T cell memory plays a significant role in shaping the magnitude and clonal composition of the circulating T cell repertoire after vaccination, with mRNA vaccination promoting CD8+ memory T cells to a TEMRA-like phenotype.

BERTrand-peptide:TCR binding prediction using Bidirectional Encoder Representations from Transformers augmented with random TCR pairing

MOTIVATION

The advent of T-cell receptor (TCR) sequencing experiments allowed for a significant increase in the amount of peptide:TCR binding data available and a number of machine-learning models appeared in recent years. High-quality prediction models for a fixed epitope sequence are feasible, provided enough known binding TCR sequences are available. However, their performance drops significantly for previously unseen peptides.

RESULTS

We prepare the dataset of known peptide:TCR binders and augment it with negative decoys created using healthy donors' T-cell repertoires. We employ deep learning methods commonly applied in Natural Language Processing to train part a peptide:TCR binding model with a degree of cross-peptide generalization (0.69 AUROC). We demonstrate that BERTrand outperforms the published methods when evaluated on peptide sequences not used during model training.

AVAILABILITY AND IMPLEMENTATION

The datasets and the code for model training are available at https://github.com/SFGLab/bertrand.

TCR Sequencing in Mouse Models of Allorecognition Unveils the Features of Directly and Indirectly Activated Clonotypes

Allorecognition is known to involve a large number of lymphocytes carrying diverse T-cell receptor repertoire. Thus, one way to understand allorecognition and rejection mechanisms is via high-throughput sequencing of T-cell receptors. In this study, in order to explore and systematize the properties of the alloreactive T-cell receptor repertoire, we modeled direct and indirect allorecognition pathways using material from inbred mice in vitro and in vivo. Decoding of the obtained T-cell receptor genes using high-throughput sequencing revealed some features of the alloreactive repertoires. Thus, alloreactive T-cell receptor repertoires were characterized by specific V-gene usage patterns, changes in CDR3 loop length, and some amino acid occurrence probabilities in the CDR3 loop. Particularly pronounced changes were observed for directly alloreactive clonotypes. We also revealed a clustering of directly and indirectly alloreactive clonotypes by their ability to bind a single antigen; amino acid patterns of the CDR3 loop of alloreactive clonotypes; and the presence in alloreactive repertoires of clonotypes also associated with infectious, autoimmune, and tumor diseases. The obtained results were determined by the modeling of the simplified allorecognition reaction in inbred mice in which stimulation was performed with a single MHCII molecule. We suppose that the decomposition of the diverse alloreactive TCR repertoire observed in humans with transplants into such simple reactions will help to find alloreactive repertoire features; e.g., a dominant clonotype or V-gene usage pattern, which may be targeted to correct the entire rejection reaction in patients. In this work, we propose several technical ways for such decomposition analysis, including separate modeling of the indirect alloreaction pathway and clustering of alloreactive clonotypes according to their ability to bind a single antigen, among others.

Creating an Innovative Artificial Intelligence-Based Technology (TCRact) for Designing and Optimizing T Cell Receptors for Use in Cancer Immunotherapies: Protocol for an Observational Trial

BACKGROUND

Cancer continues to be the leading cause of mortality in high-income countries, necessitating the development of more precise and effective treatment modalities. Immunotherapy, specifically adoptive cell transfer of T cell receptor (TCR)-engineered T cells (TCR-T therapy), has shown promise in engaging the immune system for cancer treatment. One of the biggest challenges in the development of TCR-T therapies is the proper prediction of the pairing between TCRs and peptide-human leukocyte antigen (pHLAs). Modern computational immunology, using artificial intelligence (AI)-based platforms, provides the means to optimize the speed and accuracy of TCR screening and discovery.

OBJECTIVE

This study proposes an observational clinical trial protocol to collect patient samples and generate a database of pHLA:TCR sequences to aid the development of an AI-based platform for efficient selection of specific TCRs.

METHODS

The multicenter observational study, involving 8 participating hospitals, aims to enroll patients diagnosed with stage II, III, or IV colorectal cancer adenocarcinoma.

RESULTS

Patient recruitment has recently been completed, with 100 participants enrolled. Primary tumor tissue and peripheral blood samples have been obtained, and peripheral blood mononuclear cells have been isolated and cryopreserved. Nucleic acid extraction (DNA and RNA) has been performed in 86 cases. Additionally, 57 samples underwent whole exome sequencing to determine the presence of somatic mutations and RNA sequencing for gene expression profiling.

CONCLUSIONS

The results of this study may have a significant impact on the treatment of patients with colorectal cancer. The comprehensive database of pHLA:TCR sequences generated through this observational clinical trial will facilitate the development of the AI-based platform for TCR selection. The results obtained thus far demonstrate successful patient recruitment and sample collection, laying the foundation for further analysis and the development of an innovative tool to expedite and enhance TCR selection for precision cancer treatments.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04994093; https://clinicaltrials.gov/ct2/show/NCT04994093.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/45872.

On the feasibility of using TCR sequencing to follow a vaccination response - lessons learned

T cells recognize pathogens by their highly specific T-cell receptor (TCR), which can bind small fragments of an antigen presented on the Major Histocompatibility Complex (MHC). Antigens that are provided through vaccination cause specific T cells to respond by expanding and forming specific memory to combat a future infection. Quantification of this T-cell response could improve vaccine monitoring or identify individuals with a reduced ability to respond to a vaccination. In this proof-of-concept study we use longitudinal sequencing of the TCRβ repertoire to quantify the response in the CD4+ memory T-cell pool upon pneumococcal conjugate vaccination. This comes with several challenges owing to the enormous size and diversity of the T-cell pool, the limited frequency of vaccine-specific TCRs in the total repertoire, and the variation in sample size and quality. We defined quantitative requirements to classify T-cell expansions and identified critical parameters that aid in reliable analysis of the data. In the context of pneumococcal conjugate vaccination, we were able to detect robust T-cell expansions in a minority of the donors, which suggests that the T-cell response against the conjugate in the pneumococcal vaccine is small and/or very broad. These results indicate that there is still a long way to go before TCR sequencing can be reliably used as a personal biomarker for vaccine-induced protection. Nevertheless, this study highlights the importance of having multiple samples containing sufficient T-cell numbers, which will support future studies that characterize T-cell responses using longitudinal TCR sequencing.

Large clones of pre-existing T cells drive early immunity against SARS-COV-2 and LCMV infection

T cell responses precede antibody and may provide early control of infection. We analyzed the clonal basis of this rapid response following SARS-COV-2 infection. We applied T cell receptor (TCR) sequencing to define the trajectories of individual T cell clones immediately. In SARS-COV-2 PCR+ individuals, a wave of TCRs strongly but transiently expand, frequently peaking the same week as the first positive PCR test. These expanding TCR CDR3s were enriched for sequences functionally annotated as SARS-COV-2 specific. Epitopes recognized by the expanding TCRs were highly conserved between SARS-COV-2 strains but not with circulating human coronaviruses. Many expanding CDR3s were present at high frequency in pre-pandemic repertoires. Early response TCRs specific for lymphocytic choriomeningitis virus epitopes were also found at high frequency in the preinfection naive repertoire. High-frequency naive precursors may allow the T cell response to respond rapidly during the crucial early phases of acute viral infection.

A multispecies framework for modeling adaptive immunity and immunotherapy in cancer

Predator-prey theory is commonly used to describe tumor growth in the presence of selective pressure from the adaptive immune system. These interactions are mediated by the tumor immunopeptidome (what the tumor "shows" the body) and the T-cell receptor (TCR) repertoire (how well the body "sees" cancer cells). The tumor immunopeptidome comprises neoantigens which can be gained and lost throughout tumorigenesis and treatment. Heterogeneity in the immunopeptidome is predictive of poor response to immunotherapy in some tumor types, suggesting that the TCR repertoire is unable to support a fully polyclonal response against every neoantigen. Importantly, while tumor and T-cell populations are known to compete with each other for intratumoral resources, whether between-lineage competition among peripheral T cells influences the TCR repertoire is unknown and difficult to interrogate experimentally. Computational models may offer a way to investigate these phenomena and deepen our understanding of the tumor-immune axis. Here, we construct a predator-prey-like model and calibrate it to preclinical and clinical data to describe tumor growth and immunopeptidome diversification. Simultaneously, we model the expansion of antigen-specific T-cell lineages and their consumption of both lineage-specific antigenic resources and lineage-agnostic, shared resources. This predator-prey-like framework accurately described clinically observed immunopeptidomes; recapitulated response-associated effects of immunotherapy, including immunoediting; and allowed exploration of treatment of tumors with varying growth and mutation rates.

Anti-tumor memory CD4 and CD8 T-cells quantified by bulk T-cell receptor (TCR) clonal analysis

Simple, reliable methods to detect anti-tumor memory T-cells are necessary to develop a clinical tumor vaccination program. A mouse model of curative viral onco-immunotherapy found that peritoneal tumor challenge following cure identified an oligoclonal anti-tumor memory CD4 and CD8 T-cell response. Clonotypes differed among the challenged animals but were congruent in blood, spleen and peritoneal cells (PC) of the same animal. Adoptive transfer demonstrated that the high-frequency responding T-cells were tumor specific. Tetramer analysis confirmed that clonotype frequency determined by T-cell receptor (TCR)- chain (TRB) analysis closely approximated cell clone frequency. The mean frequency of resting anti-tumor memory CD4 T-cells in unchallenged spleen was 0.028% and of memory CD8 T-cells was 0.11% which was not high enough to distinguish them from background. Stimulation produced a mean ~10-fold increase in splenic and 100-fold increase in peritoneal anti-tumor memory T-cell clonotypes. This methodology can be developed to use blood and tissue sampling to rapidly quantify the effectiveness of a tumor vaccine or any vaccine generating therapeutic T-cells.

Applicability of T cell receptor repertoire sequencing analysis to unbalanced clinical samples - comparing the T cell receptor repertoire of GATA2 deficient patients and healthy controls

T cell receptor repertoire sequencing (TCRseq) has become one of the major omic tools to study the immune system in health and disease. Multiple commercial solutions are currently available, greatly facilitating the implementation of this complex method into translational studies. However, the flexibility of these methods to react to suboptimal sample material is still limited. In a clinical research context, limited sample availability and/or unbalanced sample material can negatively impact the feasibility and quality of such analyses. We sequenced the T cell receptor repertoires of three healthy controls and four patients with GATA2 deficiency using a commercially available TCRseq kit and thereby (1) assessed the impact of suboptimal sample quality and (2) implemented a subsampling strategy to react to biased sample input quantity. Applying these strategies, we did not find significant differences in the global T cell receptor repertoire characteristics such as V and J gene usage, CDR3 junction length and repertoire diversity of GATA2-deficient patients compared with healthy control samples. Our results prove the adaptability of this TCRseq protocol to the analysis of unbalanced sample material and provide encouraging evidence for use of this method in future studies despite suboptimal patient samples.

Post-transplant cyclophosphamide prevents xenogeneic graft-versus-host disease while depleting proliferating regulatory T cells

Graft-versus-host disease (GVHD) remains a serious limitation of allogeneic hematopoietic cell transplantation (allo-HCT). While post-transplant administration of cyclophosphamide (PTCy) is increasingly used as GVHD prophylaxis, its precise mechanisms of action and its impact on graft-versus-leukemia effects have remained debated. Here, we studied the mechanisms of xenogeneic GVHD (xGVHD) prevention by PTCy in different humanized mouse models. We observed that PTCy attenuated xGVHD. Using flow cytometry and single-cell RNA-sequencing, we demonstrated that PTCy depleted proliferative CD8⁺ and conventional CD4⁺ T cells but also proliferative regulatory T cells (Treg). Further, T-cell receptor β variable region sequencing (TCRVB) analyses demonstrated that highly xenoreactive T-cell clones were depleted by PTCy. Although Treg frequencies were significantly higher in PTCy-treated than in control mice on day 21, xGVHD attenuation by PTCy was not abrogated by Treg depletion. Finally, we observed that PTCy did not abrogate graft-versus-leukemia effects.

Inferring the T cell repertoire dynamics of healthy individuals

The adaptive immune system is a diverse ecosystem that responds to pathogens by selecting cells with specific receptors. While clonal expansion in response to particular immune challenges has been extensively studied, we do not know the neutral dynamics that drive the immune system in the absence of strong stimuli. Here, we learn the parameters that underlie the clonal dynamics of the T cell repertoire in healthy individuals of different ages, by applying Bayesian inference to longitudinal immune repertoire sequencing (RepSeq) data. Quantifying the experimental noise accurately for a given RepSeq technique allows us to disentangle real changes in clonal frequencies from noise. We find that the data are consistent with clone sizes following a geometric Brownian motion and show that its predicted steady state is in quantitative agreement with the observed power-law behavior of the clone-size distribution. The inferred turnover time scale of the repertoire increases with patient age and depends on the clone size in some individuals.

The use of non-functional clonotypes as a natural calibrator for quantitative bias correction in adaptive immune receptor repertoire profiling

High-throughput sequencing of adaptive immune receptor repertoires is a valuable tool for receiving insights in adaptive immunity studies. Several powerful TCR/BCR repertoire reconstruction and analysis methods have been developed in the past decade. However, detecting and correcting the discrepancy between real and experimentally observed lymphocyte clone frequencies are still challenging. Here, we discovered a hallmark anomaly in the ratio between read count and clone count-based frequencies of non-functional clonotypes in multiplex PCR-based immune repertoires. Calculating this anomaly, we formulated a quantitative measure of V- and J-genes frequency bias driven by multiplex PCR during library preparation called Over Amplification Rate (OAR). Based on the OAR concept, we developed an original software for multiplex PCR-specific bias evaluation and correction named iROAR: immune Repertoire Over Amplification Removal (https://github.com/smiranast/iROAR). The iROAR algorithm was successfully tested on previously published TCR repertoires obtained using both 5' RACE (Rapid Amplification of cDNA Ends)-based and multiplex PCR-based approaches and compared with a biological spike-in-based method for PCR bias evaluation. The developed approach can increase the accuracy and consistency of repertoires reconstructed by different methods making them more applicable for comparative analysis.

Distinguishing between monozygotic twins' blood samples through immune repertoire sequencing

Monozygotic (MZ) twins with highly similar genomic DNA sequences can not be distinguished by conventional forensic DNA testing. The immune repertoire (IR) reflects an individual's immune history, which is unique between individuals, has been applied to individualized treatment in precision medicine. However, the application of IR in forensic genetics has not been reported to date. In this study, the diversity in the complementary determining region 3 (CDR3) of both the T-cell receptor β chain (TCRβ) and B-cell receptor heavy chain (also known as immunoglobulin heavy chain, IGH) in four pairs of MZ twins were analyzed. The results showed that the amino acid sequences length distribution frequency of TCRβ CDR3 had 4-10 differences, and the nucleic acid sequences length distribution frequency of TCRβ CDR3 had 2-7 differences between MZ twins. The shared difference of four pairs of MZ twins focused on the length distribution frequency of 34 bp nucleotide sequences in TCRβ. By analyzing the usage frequency of V and J genes in TCRβ and IGH CDR3 DNA sequence rearrangements, we also found that there were biases between each pair of MZ twins, and the usage frequency of TRBJ2-3 showed common differences between each pair of MZ twins. Furthermore, each pair of MZ twins had its own unique V-J genes combination mode in TCRβ and IGH CDR3 DNA sequences. This study, for the first time, suggested that IR can be used as a potential biological marker to distinguish MZ twins.

Clustering and Annotation of T Cell Receptor Repertoires

Immunological protection against a wide variety of pathogens is largely mediated by the diverse and dynamic T cell receptor (TCR) repertoire, a crucial component of the adaptive immune system. An encounter with infectious agents stimulates specific T cells to initiate a direct immune response to combat intruders. Hence, the TCR repertoire may conceal crucial information regarding current and past infections and might assist in the development and monitoring of vaccines. To unlock its knowledge, we describe a computational workflow involving both supervised and unsupervised machine learning techniques to analyze and annotate full TCR repertoire data. The method is explained using data from a published yellow fever virus (YFV) vaccination study in healthy individuals. The TCR repertoire of one individual is studied before and 2 weeks after vaccination, using an efficient clustering method and identification of YFV-specific TCRs.

A somatic hypermutation-based machine learning model stratifies individuals with Crohn's disease and controls

Crohn's disease (CD) is a chronic relapsing-remitting inflammatory disorder of the gastrointestinal tract that is characterized by altered innate and adaptive immune function. Although massively parallel sequencing studies of the T cell receptor repertoire identified oligoclonal expansion of unique clones, much less is known about the B cell receptor (BCR) repertoire in CD. Here, we present a novel BCR repertoire sequencing data set from ileal biopsies from pediatric patients with CD and controls, and identify CD-specific somatic hypermutation (SHM) patterns, revealed by a machine learning (ML) algorithm trained on BCR repertoire sequences. Moreover, ML classification of a different data set from blood samples of adults with CD versus controls identified that V gene usage, clusters, or mutation frequencies yielded excellent results in classifying the disease (F1 > 90%). In summary, we show that an ML algorithm enables the classification of CD based on unique BCR repertoire features with high accuracy.

Comparing T cell receptor repertoires using optimal transport

The complexity of entire T cell receptor (TCR) repertoires makes their comparison a difficult but important task. Current methods of TCR repertoire comparison can incur a high loss of distributional information by considering overly simplistic sequence- or repertoire-level characteristics. Optimal transport methods form a suitable approach for such comparison given some distance or metric between values in the sample space, with appealing theoretical and computational properties. In this paper we introduce a nonparametric approach to comparing empirical TCR repertoires that applies the Sinkhorn distance, a fast, contemporary optimal transport method, and a recently-created distance between TCRs called TCRdist. We show that our methods identify meaningful differences between samples from distinct TCR distributions for several case studies, and compete with more complicated methods despite minimal modeling assumptions and a simpler pipeline.

TCR repertoire profiling revealed antigen-driven CD8+ T cell clonal groups shared in synovial fluid of patients with spondyloarthritis

Spondyloarthritis (SpA) comprises a number of inflammatory rheumatic diseases with overlapping clinical manifestations. Strong association with several HLA-I alleles and T cell infiltration into an inflamed joint suggest involvement of T cells in SpA pathogenesis. In this study, we performed high-throughput T cell repertoire profiling of synovial fluid (SF) and peripheral blood (PB) samples collected from a large cohort of SpA patients. We showed that synovial fluid is enriched with expanded T cell clones that are shared between patients with similar HLA genotypes and persist during recurrent synovitis. Using an algorithm for identification of TCRs involved in immune response we discovered several antigen-driven CD8+ clonal groups associated with risk HLA-B*27 or HLA-B*38 alleles. We further show that these clonal groups were enriched in SF and had higher frequency in PB of SpA patients vs healthy donors, implying their relevance to SpA pathogenesis. Several of the groups were shared among patients with different SpAs that suggests a common immunopathological mechanism of the diseases. In summary, our results provide evidence for the role of specific CD8+ T cell clones in pathogenesis of SpA.

NoisET: Noise Learning and Expansion Detection of T-Cell Receptors

High-throughput sequencing of T- and B-cell receptors makes it possible to track immune repertoires across time, in different tissues, in acute and chronic diseases and in healthy individuals. However, quantitative comparison between repertoires is confounded by variability in the read count of each receptor clonotype due to sampling, library preparation, and expression noise. We review methods for accounting for both biological and experimental noise and present an easy-to-use python package NoisET that implements and generalizes a previously developed Bayesian method. It can be used to learn experimental noise models for repertoire sequencing from replicates, and to detect responding clones following a stimulus. We test the package on different repertoire sequencing technologies and data sets. We review how such approaches have been used to identify responding clonotypes in vaccination and disease data. Availability: NoisET is freely available to use with source code at github.com/statbiophys/NoisET.

Inactivated tick-borne encephalitis vaccine elicits several overlapping waves of T cell response

The development and implementation of vaccines have been growing exponentially, remaining one of the major successes of healthcare over the last century. Nowadays, active regular immunizations prevent epidemics of many viral diseases, including tick-borne encephalitis (TBE). Along with the generation of virus-specific antibodies, a highly effective vaccine should induce T cell responses providing long-term immune defense. In this study, we performed longitudinal high-throughput T cell receptor (TCR) sequencing to characterize changes in individual T cell repertoires of 11 donors immunized with an inactivated TBE vaccine. After two-step immunization, we found significant clonal expansion of both CD4⁺ and CD8⁺ T cells, ranging from 302 to 1706 vaccine-associated TCRβ clonotypes in different donors. We detected several waves of T cell clonal expansion generated by distinct groups of vaccine-responding clones. Both CD4⁺ and CD8⁺ vaccine-responding T cell clones formed 17 motifs in TCRβ sequences shared by donors with identical HLA alleles. Our results indicate that TBE vaccination leads to a robust T cell response due to the production of a variety of T cell clones with a memory phenotype, which recognize a large set of epitopes.

Two types of human TCR differentially regulate reactivity to self and non-self antigens

Based on analyses of TCR sequences from over 1,000 individuals, we report that the TCR repertoire is composed of two ontogenically and functionally distinct types of TCRs. Their production is regulated by variations in thymic output and terminal deoxynucleotidyl transferase (TDT) activity. Neonatal TCRs derived from TDT-negative progenitors persist throughout life, are highly shared among subjects, and are reported as disease-associated. Thus, 10%–30% of most frequent cord blood TCRs are associated with common pathogens and autoantigens. TDT-dependent TCRs present distinct structural features and are less shared among subjects. TDT-dependent TCRs are produced in maximal numbers during infancy when thymic output and TDT activity reach a summit, are more abundant in subjects with AIRE mutations, and seem to play a dominant role in graft-versus-host disease. Factors decreasing thymic output (age, male sex) negatively impact TCR diversity. Males compensate for their lower repertoire diversity via hyperexpansion of selected TCR clonotypes.

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Over 10⁸ TCR CDR3 sequences from ∼10³ individuals and 7 cohorts were analyzed

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The TCR repertoire is composed of two layers: neonatal and TDT-dependent layer

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∼70% of frequent cord blood TCRs are associated with common pathogens

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Acute graft-vs-host disease correlates with a high proportion of TDT-dependent TCRs

A hierarchy of selection pressures determines the organization of the T cell receptor repertoire

We systematically examine the receptor repertoire in T cell subsets in young, adult, and LCMV-infected mice. Somatic recombination generates diversity, resulting in the limited overlap between nucleotide sequences of different repertoires even within the same individual. However, statistical features of the repertoire, quantified by the V gene and CDR3 k-mer frequency distributions, are highly conserved. A hierarchy of immunological processes drives the evolution of this structure. Intra-thymic divergence of CD4+ and CD8+ lineages imposes subtle but dominant differences observed across repertoires of all subpopulations in both young and adult mice. Differentiation from naive through memory to effector phenotype imposes an additional gradient of repertoire diversification, which is further influenced by age in a complex and lineage-dependent manner. The distinct repertoire of CD4+ regulatory T cells is more similar to naive cells in young mice and to effectors in adults. Finally, we describe divergent (naive and memory) and convergent (CD8+ effector) evolution of the repertoire following acute infection with LCMV. This study presents a quantitative framework that captures the structure of the repertoire in terms of its fundamental statistical properties and describes how this structure evolves as individual T cells differentiate, migrate and mature in response to antigen exposure.

Machine Learning Approaches to TCR Repertoire Analysis

Sparked by the development of genome sequencing technology, the quantity and quality of data handled in immunological research have been changing dramatically. Various data and database platforms are now driving the rapid progress of machine learning for immunological data analysis. Of various topics in immunology, T cell receptor repertoire analysis is one of the most important targets of machine learning for assessing the state and abnormalities of immune systems. In this paper, we review recent repertoire analysis methods based on machine learning and deep learning and discuss their prospects.

Divergent Characteristics of T-Cell Receptor Repertoire Between Essential Hypertension and Aldosterone-Producing Adenoma

Aldosterone-producing adenoma (APA) is a benign adrenal tumor that results in persistent hyperaldosteronism. As one major subtype of primary aldosteronism, APA leads to secondary hypertension that is associated with immune dysregulation. However, how the adaptive immune system, particularly the T-cell population, is altered in APA patients remains largely unknown. Here, we performed TCR sequencing to characterize the TCR repertoire between two age-matched groups of patients: one with APA and the other one with essential hypertension (EH). Strikingly, we found a significant reduction of TCR repertoire diversity in the APA group. Analyses on TCR clustering and antigen annotation further showed that the APA group possessed lower diversity in TCR clonotypes with non-common antigen-specific features, compared with the EH group. In addition, our results indicated that the strength of correlation between generation probabilities and frequencies of TCR clonotypes was significantly higher in the APA group than that in the EH group. Finally, we observed that clinical features, including plasma aldosterone level, aldosterone–renin ratio, and blood sodium level, were positively associated with the strength of correlation between generation and abundance of TCR clonotypes in the APA group. Our findings unveiled the correlation between T-cell immune repertoire and APA, suggesting a critical role of such adrenal adenoma in the T-cell immunity of patients with hypertension.

Pinpointing the tumor-specific T-cells via TCR clusters

Adoptive cell transfer (ACT) is a promising approach to cancer immunotherapy, but its efficiency fundamentally depends on the extent of tumor-specific T cell enrichment within the graft. This can be estimated via activation with identifiable neoantigens, tumor-associated antigens (TAAs), or living or lysed tumor cells, but these approaches remain laborious, time-consuming, and functionally limited, hampering clinical development of ACT. Here, we demonstrate that homology cluster analysis of T cell receptor (TCR) repertoires efficiently identifies tumor-reactive TCRs allowing to: (1) detect their presence within the pool of tumor-infiltrating lymphocytes (TILs); (2) optimize TIL culturing conditions, with IL-2_low/IL-21/anti-PD-1 combination showing increased efficiency; (3) investigate surface marker-based enrichment for tumor-targeting T cells in freshly isolated TILs (enrichment confirmed for CD4⁺ and CD8⁺ PD-1⁺/CD39⁺ subsets), or re-stimulated TILs (informs on enrichment in 4-1BB-sorted cells). We believe that this approach to the rapid assessment of tumor-specific TCR enrichment should accelerate T cell therapy development.

Analysis of T cell receptor clonotypes in tumor microenvironment identifies shared cancer-type-specific signatures

Despite the conventional view that a truly random V(D)J recombination process should generate a highly diverse immune repertoire, emerging reports suggest that there is a certain bias toward the generation of shared/public immune receptor chains. These studies were performed in viral diseases where public T cell receptors (TCR) appear to confer better protective responses. Selective pressures generating common TCR clonotypes are currently not well understood, but it is believed that they confer a growth advantage. As very little is known about public TCR clonotypes in cancer, here we set out to determine the extent of shared TCR clonotypes in the intra-tumor microenvironments of virus- and non-virus-driven head and neck cancers using TCR sequencing. We report that tumor-infiltrating T cell clonotypes were indeed shared across individuals with the same cancer type, where the majority of shared sequences were specific to the cancer type (i.e., viral versus non-viral). These shared clonotypes were not particularly enriched in EBV-associated nasopharynx cancer but, in both cancers, exhibited distinct characteristics, namely shorter CDR3 lengths, restricted V- and J-gene usages, and also demonstrated convergent V(D)J recombination. Many of these shared TCRs were expressed in patients with a shared HLA background. Pattern recognition of CDR3 amino acid sequences revealed strong convergence to specific pattern motifs, and these motifs were uniquely found to each cancer type. This suggests that they may be enriched for specificity to common antigens found in the tumor microenvironment of different cancers. The identification of shared TCRs in infiltrating tumor T cells not only adds to our understanding of the tumor-adaptive immune recognition but could also serve as disease-specific biomarkers and guide the development of future immunotherapies.

Combining genotypes and T cell receptor distributions to infer genetic loci determining V(D)J recombination probabilities

Every T cell receptor (TCR) repertoire is shaped by a complex probabilistic tangle of genetically determined biases and immune exposures. T cells combine a random V(D)J recombination process with a selection process to generate highly diverse and functional TCRs. The extent to which an individual’s genetic background is associated with their resulting TCR repertoire diversity has yet to be fully explored. Using a previously published repertoire sequencing dataset paired with high-resolution genome-wide genotyping from a large human cohort, we infer specific genetic loci associated with V(D)J recombination probabilities using genome-wide association inference. We show that V(D)J gene usage profiles are associated with variation in the TCRB locus and, specifically for the functional TCR repertoire, variation in the major histocompatibility complex locus. Further, we identify specific variations in the genes encoding the Artemis protein and the TdT protein to be associated with biasing junctional nucleotide deletion and N-insertion, respectively. These results refine our understanding of genetically-determined TCR repertoire biases by confirming and extending previous studies on the genetic determinants of V(D)J gene usage and providing the first examples of trans genetic variants which are associated with modifying junctional diversity. Together, these insights lay the groundwork for further explorations into how immune responses vary between individuals.

Identification and Tracking of Alloreactive T Cell Clones in Rhesus Macaques Through the RM-scTCR-Seq Platform

T cell receptor (TCR) clonotype tracking is a powerful tool for interrogating T cell mediated immune processes. New methods to pair a single cell's transcriptional program with its TCR identity allow monitoring of T cell clonotype-specific transcriptional dynamics. While these technologies have been available for human and mouse T cells studies, they have not been developed for Rhesus Macaques (RM), a critical translational organism for autoimmune diseases, vaccine development and transplantation. We describe a new pipeline, 'RM-scTCR-Seq', which, for the first time, enables RM specific single cell TCR amplification, reconstruction and pairing of RM TCR's with their transcriptional profiles. We apply this method to a RM model of GVHD, and identify and track in vitro detected alloreactive clonotypes in GVHD target organs and explore their GVHD driven cytotoxic T cell signature. This novel, state-of-the-art platform fundamentally advances the utility of RM to study protective and pathogenic T cell responses.

Preexisting memory CD4 T cells in naïve individuals confer robust immunity upon hepatitis B vaccination

Antigen recognition through the T cell receptor (TCR) αβ heterodimer is one of the primary determinants of the adaptive immune response. Vaccines activate naïve T cells with high specificity to expand and differentiate into memory T cells. However, antigen-specific memory CD4 T cells exist in unexposed antigen-naïve hosts. In this study, we use high-throughput sequencing of memory CD4 TCRβ repertoire and machine learning to show that individuals with preexisting vaccine-reactive memory CD4 T cell clonotypes elicited earlier and higher antibody titers and mounted a more robust CD4 T cell response to hepatitis B vaccine. In addition, integration of TCRβ sequence patterns into a hepatitis B epitope-specific annotation model can predict which individuals will have an early and more vigorous vaccine-elicited immunity. Thus, the presence of preexisting memory T cell clonotypes has a significant impact on immunity and can be used to predict immune responses to vaccination.

Immune cells called CD4 T cells help the body build immunity to infections caused by bacteria and viruses, or after vaccination. Receptor proteins on the outside of the cells recognize pathogens, foreign molecules called antigens, or vaccine antigens. Vaccine antigens are usually inactivated bacteria or viruses, or fragments of these pathogens. After recognizing an antigen, CD4 T cells develop into memory CD4 T cells ready to defend against future infections with the pathogen.

People who have never been exposed to a pathogen, or have never been vaccinated against it, may nevertheless have preexisting memory cells ready to defend against it. This happens because CD4 T cells can recognize multiple targets, which enables the immune system to be ready to defend against both new and familiar pathogens.

Elias, Meysman, Bartholomeus et al. wanted to find out whether having preexisting memory CD4 T cells confers an advantage for vaccine-induced immunity. Thirty-four people who were never exposed to hepatitis B or vaccinated against it participated in the study. These individuals provided blood samples before vaccination, with 2 doses of the hepatitis B vaccine, and at 3 time points afterward. Using next generation immune sequencing and machine learning techniques, Elias et al. analyzed the individuals’ memory CD4 T cells before and after vaccination.

The experiments showed that preexisting memory CD4 T cells may determine vaccination outcomes, and people with more preexisting memory cells develop quicker and stronger immunity after vaccination against hepatitis B. This information may help scientists to better understand how people develop immunity to pathogens. It may guide them develop better vaccines or predict who will develop immunity after vaccination.

Adaptive Immune Receptor Repertoire (AIRR) Community Guide to Repertoire Analysis

Adaptive immune receptor repertoires (AIRRs) are rich with information that can be mined for insights into the workings of the immune system. Gene usage, CDR3 properties, clonal lineage structure, and sequence diversity are all capable of revealing the dynamic immune response to perturbation by disease, vaccination, or other interventions. Here we focus on a conceptual introduction to the many aspects of repertoire analysis and orient the reader toward the uses and advantages of each. Along the way, we note some of the many software tools that have been developed for these investigations and link the ideas discussed to chapters on methods provided elsewhere in this volume.

Prospective Tracking of Donor-Reactive T-Cell Clones in the Circulation and Rejecting Human Kidney Allografts

Background

Antigen recognition of allo-peptides and HLA molecules leads to the activation of donor-reactive T-cells following transplantation, potentially causing T-cell-mediated rejection (TCMR). Sequencing of the T-cell receptor (TCR) repertoire can be used to track the donor-reactive repertoire in blood and tissue of patients after kidney transplantation.

Methods/Design

In this prospective cohort study, 117 non-sensitized kidney transplant recipients with anti-CD25 induction were included. Peripheral mononuclear cells (PBMCs) were sampled pre-transplant and at the time of protocol or indication biopsies together with graft tissue. Next-generation sequencing (NGS) of the CDR3 region of the TCRbeta chain was performed after donor stimulation in mixed lymphocyte reactions to define the donor-reactive TCR repertoire. Blood and tissue of six patients experiencing a TCMR and six patients without rejection on protocol biopsies were interrogated for these TCRs. To elucidate common features of T-cell clonotypes, a network analysis of the TCR repertoires was performed.

Results

After transplantation, the frequency of circulating donor-reactive CD4 T-cells increased significantly from 0.86 ± 0.40% to 2.06 ± 0.40% of all CD4 cells (p < 0.001, mean dif.: -1.197, CI: -1.802, -0.593). The number of circulating donor-reactive CD4 clonotypes increased from 0.72 ± 0.33% to 1.89 ± 0.33% (p < 0.001, mean dif.: -1.168, CI: -1.724, -0.612). No difference in the percentage of donor-reactive T-cells in the circulation at transplant biopsy was found between subjects experiencing a TCMR and the control group [p = 0.64 (CD4⁺), p = 0.52 (CD8⁺)]. Graft-infiltrating T-cells showed an up to six-fold increase of donor-reactive T-cell clonotypes compared to the blood at the same time (3.7 vs. 0.6% and 2.4 vs. 1.5%), but the infiltrating TCR repertoire was not reflected by the composition of the circulating TCR repertoire despite some overlap. Network analysis showed a distinct segregation of the donor-reactive repertoire with higher modularity than the overall TCR repertoire in the blood. These findings indicate an unchoreographed process of diverse T-cell clones directed against numerous non-self antigens found in the allograft.

Conclusion

Donor-reactive T-cells are enriched in the kidney allograft during a TCMR episode, and dominant tissue clones are also found in the blood.

Trial Registration

Clinicaltrials.gov: NCT: 03422224 (https://clinicaltrials.gov/ct2/show/NCT03422224).

Impact of HLA type, age and chronic viral infection on peripheral T-cell receptor sharing between unrelated individuals

The human adaptive immune system must generate extraordinary diversity to be able to respond to all possible pathogens. The T-cell repertoire derives this high diversity through somatic recombination of the T-cell receptor (TCR) locus, a random process that results in repertoires that are largely private to each individual. However, factors such as thymic selection and T-cell proliferation upon antigen exposure can affect TCR sharing among individuals. By immunosequencing the TCRβ variable region of 426 healthy individuals, we find that, on average, fewer than 1% of TCRβ clones are shared between individuals, consistent with largely private TCRβ repertoires. However, we detect a significant correlation between increased HLA allele sharing and increased number of shared TCRβ clones, with each additional shared HLA allele contributing to an increase in ~0.01% of the total shared TCRβ clones, supporting a key role for HLA type in shaping the immune repertoire. Surprisingly, we find that shared antigen exposure to CMV leads to fewer shared TCRβ clones, even after controlling for HLA, indicative of a largely private response to major viral antigenic exposure. Consistent with this hypothesis, we find that increased age is correlated with decreased overall TCRβ clone sharing, indicating that the pattern of private TCRβ clonal expansion is a general feature of the T-cell response to other infectious antigens as well. However, increased age also correlates with increased sharing among the lowest frequency clones, consistent with decreased repertoire diversity in older individuals. Together, all of these factors contribute to shaping the TCRβ repertoire, and understanding their interplay has important implications for the use of T cells for therapeutics and diagnostics.

Expansion of Unique Hepatitis C Virus-Specific Public CD8+ T Cell Clonotypes during Acute Infection and Reinfection

Hepatitis C virus (HCV) infection resolves spontaneously in ∼25% of acutely infected humans where viral clearance is mediated primarily by virus-specific CD8⁺ T cells. Previous cross-sectional analysis of the CD8⁺ TCR repertoire targeting two immunodominant HCV epitopes reported widespread use of public TCRs shared by different subjects, irrespective of infection outcome. However, little is known about the evolution of the public TCR repertoire during acute HCV and whether cross-reactivity to other Ags can influence infectious outcome. In this article, we analyzed the CD8⁺ TCR repertoire specific to the immunodominant and cross-reactive HLA-A2-restricted nonstructural 3-1073 epitope during acute HCV in humans progressing to either spontaneous resolution or chronic infection and at ∼1 y after viral clearance. TCR repertoire diversity was comparable among all groups with preferential usage of the TCR-β V04 and V06 gene families. We identified a set of 13 public clonotypes in HCV-infected humans independent of infection outcome. Six public clonotypes used the V04 gene family. Several public clonotypes were long-lived in resolvers and expanded on reinfection. By mining publicly available data, we identified several low-frequency CDR3 sequences in the HCV-specific repertoire matching human TCRs specific for other HLA-A2-restricted epitopes from melanoma, CMV, influenza A, EBV, and yellow fever viruses, but they were of low frequency and limited cross-reactivity. In conclusion, we identified 13 new public human CD8⁺ TCR clonotypes unique to HCV that expanded during acute infection and reinfection. The low frequency of cross-reactive TCRs suggests that they are not major determinants of infectious outcome.

Autoencoder based local T cell repertoire density can be used to classify samples and T cell receptors

Recent advances in T cell repertoire (TCR) sequencing allow for the characterization of repertoire properties, as well as the frequency and sharing of specific TCR. However, there is no efficient measure for the local density of a given TCR. TCRs are often described either through their Complementary Determining region 3 (CDR3) sequences, or theirV/J usage, or their clone size. We here show that the local repertoire density can be estimated using a combined representation of these components through distance conserving autoencoders and Kernel Density Estimates (KDE). We present ELATE-an Encoder-based LocAl Tcr dEnsity and show that the resulting density of a sample can be used as a novel measure to study repertoire properties. The cross-density between two samples can be used as a similarity matrix to fully characterize samples from the same host. Finally, the same projection in combination with machine learning algorithms can be used to predict TCR-peptide binding through the local density of known TCRs binding a specific target.

Predictive Markers of Immunogenicity and Efficacy for Human Vaccines

Vaccines represent one of the major advances of modern medicine. Despite the many successes of vaccination, continuous efforts to design new vaccines are needed to fight "old" pandemics, such as tuberculosis and malaria, as well as emerging pathogens, such as Zika virus and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Vaccination aims at reaching sterilizing immunity, however assessing vaccine efficacy is still challenging and underscores the need for a better understanding of immune protective responses. Identifying reliable predictive markers of immunogenicity can help to select and develop promising vaccine candidates during early preclinical studies and can lead to improved, personalized, vaccination strategies. A systems biology approach is increasingly being adopted to address these major challenges using multiple high-dimensional technologies combined with in silico models. Although the goal is to develop predictive models of vaccine efficacy in humans, applying this approach to animal models empowers basic and translational vaccine research. In this review, we provide an overview of vaccine immune signatures in preclinical models, as well as in target human populations. We also discuss high-throughput technologies used to probe vaccine-induced responses, along with data analysis and computational methodologies applied to the predictive modeling of vaccine efficacy.

Dynamics of B cell repertoires and emergence of cross-reactive responses in patients with different severities of COVID-19

Individuals with the 2019 coronavirus disease (COVID-19) show varying severity of the disease, ranging from asymptomatic to requiring intensive care. Although monoclonal antibodies specific to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been identified, we still lack an understanding of the overall landscape of B cell receptor (BCR) repertoires in individuals with COVID-19. We use high-throughput sequencing of bulk and plasma B cells collected at multiple time points during infection to characterize signatures of the B cell response to SARS-CoV-2 in 19 individuals. Using principled statistical approaches, we associate differential features of BCRs with different disease severity. We identify 38 significantly expanded clonal lineages shared among individuals as candidates for responses specific to SARS-CoV-2. Using single-cell sequencing, we verify the reactivity of BCRs shared among individuals to SARS-CoV-2 epitopes. Moreover, we identify the natural emergence of a BCR with cross-reactivity to SARS-CoV-1 and SARS-CoV-2 in some individuals. Our results provide insights important for development of rational therapies and vaccines against COVID-19.

Profiling of T Cell Repertoire in SARS-CoV-2-Infected COVID-19 Patients Between Mild Disease and Pneumonia

The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become a public health emergency. The most common symptoms of COVID-19 are fever, cough, and fatigue. While most patients with COVID-19 present with mild illness, some patients develop pneumonia, an important risk factor for mortality, at early stage of viral infection, putting these patients at increased risk of death. So far, little has been known about differences in the T cell repertoires between COVID-19 patients with and without pneumonia during SARS-CoV-2 infection. Herein, we aimed to investigate T cell receptor (TCR) repertoire profiles and patient-specific SARS-CoV-2-associated TCR clusters between COVID-19 patients with mild disease (no sign of pneumonia) and pneumonia. The TCR sequencing was conducted to characterize the peripheral TCR repertoire profile and diversity. The TCR clustering and CDR3 annotation were exploited to further discover groups of patient-specific TCR clonotypes with potential SARS-CoV-2 antigen specificities. Our study indicated a slight decrease in the TCR repertoire diversity and a skewed CDR3 length usage in patients with pneumonia compared to those with mild disease. The SARS-CoV-2-associated TCR clusters enriched in patients with mild disease exhibited significantly higher TCR generation probabilities and most of which were highly shared among patients, compared with those from pneumonia patients. Importantly, using similarity network-based clustering followed by the sequence conservation analysis, we found different patterns of CDR3 sequence motifs between mild disease- and pneumonia-specific SARS-CoV-2-associated public TCR clusters. Our results showed that characteristics of overall TCR repertoire and SARS-CoV-2-associated TCR clusters/clonotypes were divergent between COVID-19 patients with mild disease and patients with pneumonia. These findings provide important insights into the correlation between the TCR repertoire and disease severity in COVID-19 patients.

High Frequency of Shared Clonotypes in Human T Cell Receptor Repertoires

The collection of T cell receptors (TCRs) generated by somatic recombination is large but unknown. We generate large TCR repertoire datasets as a resource to facilitate detailed studies of the role of TCR clonotypes and repertoires in health and disease. We estimate the size of individual human recombined and expressed TCRs by sequence analysis and determine the extent of sharing between individual repertoires. Our experiments reveal that each blood sample contains between 5 million and 21 million TCR clonotypes. Three individuals share 8% of TCRβ- or 11% of TCRα-chain clonotypes. Sorting by T cell phenotypes in four individuals shows that 5% of naive CD4+ and 3.5% of naive CD8+ subsets share their TCRβ clonotypes, whereas memory CD4+ and CD8+ subsets share 2.3% and 0.4% of their clonotypes, respectively. We identify the sequences of these shared TCR clonotypes that are of interest for studies of human T cell biology.

Soto et al. examine the extent to which five healthy adults share their T cell receptor (TCR) repertoire. Using sequencing and bioinformatics, they show a high prevalence of shared clonotypes even considering different T cell phenotypes. Possible functions for some clonotypes are inferred based on homology with TCRs in GenBank.

Dynamics of B-cell repertoires and emergence of cross-reactive responses in COVID-19 patients with different disease severity

COVID-19 patients show varying severity of the disease ranging from asymptomatic to requiring intensive care. Although a number of SARS-CoV-2 specific monoclonal antibodies have been identified, we still lack an understanding of the overall landscape of B-cell receptor (BCR) repertoires in COVID-19 patients. Here, we used high-throughput sequencing of bulk and plasma B-cells collected over multiple time points during infection to characterize signatures of B-cell response to SARS-CoV-2 in 19 patients. Using principled statistical approaches, we determined differential features of BCRs associated with different disease severity. We identified 38 significantly expanded clonal lineages shared among patients as candidates for specific responses to SARS-CoV-2. Using single-cell sequencing, we verified reactivity of BCRs shared among individuals to SARS-CoV-2 epitopes. Moreover, we identified natural emergence of a BCR with cross-reactivity to SARS-CoV-1 and SARS-CoV-2 in a number of patients. Our results provide important insights for development of rational therapies and vaccines against COVID-19.

Clustering based approach for population level identification of condition-associated T-cell receptor β-chain CDR3 sequences

BACKGROUND

Deep immune receptor sequencing, RepSeq, provides unprecedented opportunities for identifying and studying condition-associated T-cell clonotypes, represented by T-cell receptor (TCR) CDR3 sequences. However, due to the immense diversity of the immune repertoire, identification of condition relevant TCR CDR3s from total repertoires has mostly been limited to either "public" CDR3 sequences or to comparisons of CDR3 frequencies observed in a single individual. A methodology for the identification of condition-associated TCR CDR3s by direct population level comparison of RepSeq samples is currently lacking.

RESULTS

We present a method for direct population level comparison of RepSeq samples using immune repertoire sub-units (or sub-repertoires) that are shared across individuals. The method first performs unsupervised clustering of CDR3s within each sample. It then finds matching clusters across samples, called immune sub-repertoires, and performs statistical differential abundance testing at the level of the identified sub-repertoires. It finally ranks CDR3s in differentially abundant sub-repertoires for relevance to the condition. We applied the method on total TCR CDR3β RepSeq datasets of celiac disease patients, as well as on public datasets of yellow fever vaccination. The method successfully identified celiac disease associated CDR3β sequences, as evidenced by considerable agreement of TRBV-gene and positional amino acid usage patterns in the detected CDR3β sequences with previously known CDR3βs specific to gluten in celiac disease. It also successfully recovered significantly high numbers of previously known CDR3β sequences relevant to each condition than would be expected by chance.

CONCLUSION

We conclude that immune sub-repertoires of similar immuno-genomic features shared across unrelated individuals can serve as viable units of immune repertoire comparison, serving as proxy for identification of condition-associated CDR3s.

VJ Segment Usage of TCR-Beta Repertoire in Monozygotic Cystic Fibrosis Twins

Sixteen monozygotic cystic fibrosis (CF) twin pairs of whom 14 pairs were homozygous for the most common p.Phe508del CFTR mutation were selected from the European Cystic Fibrosis Twin and Sibling Study Cohort. The monozygotic twins were examined in their T cell receptor (TCR) repertoire in peripheral blood by amplicon sequencing of the CDR3 variable region of the ß-chain. The recruitment of TCR J and V genes for recombination and selection in the thymus showed a strong genetic influence in the CF twin cohort as indicated by the shortest Jensen-Shannon distance to the twin individual. Exceptions were the clinically most discordant and/or most severely affected twin pairs where clonal expansion probably caused by recurrent pulmonary infections overshadowed the impact of the identical genomic blueprint. In general the Simpson clonality was low indicating that the population of TCRß clonotypes of the CF twins was dominated by the naïve T-cell repertoire. Intrapair sharing of clonotypes was significantly more frequent among monozygotic CF twins than among pairs of unrelated CF patients. Complete nucleotide sequence identity was observed in about 0.11% of CDR3 sequences which partially should represent persisting fetal clones derived from the same progenitor T cells. Complete amino acid sequence identity was noted in 0.59% of clonotypes. Of the nearly 40,000 frequent amino acid clonotypes shared by at least two twin siblings 99.8% were already known within the immuneACCESS database and only 73 had yet not been detected indicating that the CDR3ß repertoire of CF children and adolescents does not carry a disease-specific signature but rather shares public clones with that of the non-CF community. Clonotypes shared within twin pairs and between unrelated CF siblings were highly abundant among healthy non-CF people, less represented in individuals with infectious disease and uncommon in patients with cancer. This subset of shared CF clonotypes defines CDR3 amino acid sequences that are more common in health than in disease.

Dynamics of thymus function and T cell receptor repertoire breadth in health and disease

T cell recognition of unknown antigens relies on the tremendous diversity of the T cell receptor (TCR) repertoire; generation of which can only occur in the thymus. TCR repertoire breadth is thus critical for not only coordinating the adaptive response against pathogens but also for mounting a response against malignancies. However, thymic function is exquisitely sensitive to negative stimuli, which can come in the form of acute insult, such as that caused by stress, infection, or common cancer therapies; or chronic damage such as the progressive decline in thymic function with age. Whether it be prolonged T cell deficiency after hematopoietic cell transplantation (HCT) or constriction in the breadth of the peripheral TCR repertoire with age; these insults result in poor adaptive immune responses. In this review, we will discuss the importance of thymic function for generation of the TCR repertoire and how acute and chronic thymic damage influences immune health. We will also discuss methods that are used to measure thymic function in patients and strategies that have been developed to boost thymic function.

Benchmarking of T cell receptor repertoire profiling methods reveals large systematic biases

Monitoring the T cell receptor (TCR) repertoire in health and disease can provide key insights into adaptive immune responses, but the accuracy of current TCR sequencing (TCRseq) methods is unclear. In this study, we systematically compared the results of nine commercial and academic TCRseq methods, including six rapid amplification of complementary DNA ends (RACE)-polymerase chain reaction (PCR) and three multiplex-PCR approaches, when applied to the same T cell sample. We found marked differences in accuracy and intra- and inter-method reproducibility for T cell receptor α (TRA) and T cell receptor β (TRB) TCR chains. Most methods showed a lower ability to capture TRA than TRB diversity. Low RNA input generated non-representative repertoires. Results from the 5' RACE-PCR methods were consistent among themselves but differed from the RNA-based multiplex-PCR results. Using an in silico meta-repertoire generated from 108 replicates, we found that one genomic DNA-based method and two non-unique molecular identifier (UMI) RNA-based methods were more sensitive than UMI methods in detecting rare clonotypes, despite the better clonotype quantification accuracy of the latter.

The clonal structure and dynamics of the human T cell response to an organic chemical hapten

Diphenylcyclopropenone (DPC) is an organic chemical hapten which induces allergic contact dermatitis and is used in the treatment of warts, melanoma, and alopecia areata. This therapeutic setting therefore provided an opportunity to study T cell receptor (TCR) repertoire changes in response to hapten sensitization in humans. Repeated exposure to DPC induced highly dynamic transient expansions of a polyclonal diverse T cell population. The number of TCRs expanded early after sensitization varies between individuals and predicts the magnitude of the allergic reaction. The expanded TCRs show preferential TCR V and J gene usage and consist of clusters of TCRs with similar sequences, two characteristic features of antigen-driven responses. The expanded TCRs share subtle sequence motifs that can be captured using a dynamic Bayesian network. These observations suggest the response to DPC is mediated by a polyclonal population of T cells recognizing a small number of dominant antigens.