Characterizing immune repertoires by high throughput sequencing: strategies and applications

Seven-chain adaptive immune receptor repertoire analysis in rheumatoid arthritis reveals novel features associated with disease and clinically relevant phenotypes

BACKGROUND

In rheumatoid arthritis (RA), the activation of T and B cell clones specific for self-antigens leads to the chronic inflammation of the synovium. Here, we perform an in-depth quantitative analysis of the seven chains that comprise the adaptive immune receptor repertoire (AIRR) in RA.

RESULTS

In comparison to controls, we show that RA patients have multiple and strong differences in the B cell receptor repertoire including reduced diversity as well as altered isotype, chain, and segment frequencies. We demonstrate that therapeutic tumor necrosis factor inhibition partially restores this alteration but find a profound difference in the underlying biochemical reactivities between responders and non-responders. Combining the AIRR with HLA typing, we identify the specific T cell receptor repertoire associated with disease risk variants. Integrating these features, we further develop a molecular classifier that shows the utility of the AIRR as a diagnostic tool.

CONCLUSIONS

Simultaneous sequencing of the seven chains of the human AIRR reveals novel features associated with the disease and clinically relevant phenotypes, including response to therapy. These findings show the unique potential of AIRR to address precision medicine in immune-related diseases.

Toolkit for mapping the clonal landscape of tumor-infiltrating B cells

Our current understanding of whether B cell involvement in the tumor microenvironment benefits the patient or the tumor - in distinct cancers, subcohorts and individual patients - is quite limited. Both statements are probably true in most cases: certain clonal B cell populations contribute to the antitumor response, while others steer the immune response away from the desired mechanics. To step up to a new level of understanding and managing B cell behaviors in the tumor microenvironment, we need to rationally discern these roles, which are cumulatively defined by B cell clonal functional programs, specificities of their B cell receptors, specificities and isotypes of the antibodies they produce, and their spatial interactions within the tumor environment. Comprehensive analysis of these characteristics of clonal B cell populations is now becoming feasible with the development of a whole arsenal of advanced technical approaches, which include (1) methods of single-cell and spatial transcriptomics, genomics, and proteomics; (2) methods of massive identification of B cell specificities; (3) methods of deep error-free profiling of B cell receptor repertoires. Here we overview existing techniques, summarize their current application for B cells studies and propose promising future directions in advancing B cells exploration.

Current advancements in B-cell receptor sequencing fast-track the development of synthetic antibodies

Synthetic antibodies (Abs) are a class of engineered proteins designed to mimic the functions of natural Abs. These are produced entirely in vitro, eliminating the need for an immune response. As such, synthetic Abs have transformed the traditional methods of raising Abs. Likewise, deep sequencing technologies have revolutionized genomics and molecular biology. These enable the rapid and cost-effective sequencing of DNA and RNA molecules. They have allowed for accurate and inexpensive analysis of entire genomes and transcriptomes. Notably, via deep sequencing it is now possible to sequence a person's entire B-cell receptor immune repertoire, termed BCR sequencing. This procedure allows for big data explorations of natural Abs associated with an immune response. Importantly, the identified sequences have the ability to improve the design and engineering of synthetic Abs by offering an initial sequence framework for downstream optimizations. Additionally, machine learning algorithms can be introduced to leverage the vast amount of BCR sequencing datasets to rapidly identify patterns hidden in big data to effectively make in silico predictions of antigen selective synthetic Abs. Thus, the convergence of BCR sequencing, machine learning, and synthetic Ab development has effectively promoted a new era in Ab therapeutics. The combination of these technologies is driving rapid advances in precision medicine, diagnostics, and personalized treatments.

Immunological and clinicopathological features predict HER2-positive breast cancer prognosis in the neoadjuvant NeoALTTO and CALGB 40601 randomized trials

The identification of prognostic markers in patients receiving neoadjuvant therapy is crucial for treatment optimization in HER2-positive breast cancer, with the immune microenvironment being a key factor. Here, we investigate the complexity of B and T cell receptor (BCR and TCR) repertoires in the context of two phase III trials, NeoALTTO and CALGB 40601, evaluating neoadjuvant paclitaxel with trastuzumab and/or lapatinib in women with HER2-positive breast cancer. BCR features, particularly the number of reads and clones, evenness and Gini index, are heterogeneous according to hormone receptor status and PAM50 subtypes. Moreover, BCR measures describing clonal expansion, namely evenness and Gini index, are independent prognostic factors. We present a model developed in NeoALTTO and validated in CALGB 40601 that can predict event-free survival (EFS) by integrating hormone receptor and clinical nodal status, breast pathological complete response (pCR), stromal tumor-infiltrating lymphocyte levels (%) and BCR repertoire evenness. A prognostic score derived from the model and including those variables, HER2-EveNT, allows the identification of patients with 5-year EFS > 90%, and, in those not achieving pCR, of a subgroup of immune-enriched tumors with an excellent outcome despite residual disease.

B cell abnormalities and autoantibody production in patients with partial RAG deficiency

Mutations in the recombination activating gene 1 (RAG1) and RAG2 in humans are associated with a broad spectrum of clinical phenotypes, from severe combined immunodeficiency to immune dysregulation. Partial (hypomorphic) RAG deficiency (pRD) in particular, frequently leads to hyperinflammation and autoimmunity, with several underlying intrinsic and extrinsic mechanisms causing a break in tolerance centrally and peripherally during T and B cell development. However, the relative contributions of these processes to immune dysregulation remain unclear. In this review, we specifically focus on the recently described tolerance break and B cell abnormalities, as well as consequent molecular and cellular mechanisms of autoantibody production in patients with pRD.

An open protocol for modeling T Cell Clonotype repertoires using TCRβ CDR3 sequences

T cell receptor repertoires can be profiled using next generation sequencing (NGS) to measure and monitor adaptive dynamical changes in response to disease and other perturbations. Genomic DNA-based bulk sequencing is cost-effective but necessitates multiplex target amplification using multiple primer pairs with highly variable amplification efficiencies. Here, we utilize an equimolar primer mixture and propose a single statistical normalization step that efficiently corrects for amplification bias post sequencing. Using samples analyzed by both our open protocol and a commercial solution, we show high concordance between bulk clonality metrics. This approach is an inexpensive and open-source alternative to commercial solutions.

Genotype-phenotype landscapes for immune-pathogen coevolution

Our immune systems constantly coevolve with the pathogens that challenge them, as pathogens adapt to evade our defense responses, with our immune repertoires shifting in turn. These coevolutionary dynamics take place across a vast and high-dimensional landscape of potential pathogen and immune receptor sequence variants. Mapping the relationship between these genotypes and the phenotypes that determine immune-pathogen interactions is crucial for understanding, predicting, and controlling disease. Here, we review recent developments applying high-throughput methods to create large libraries of immune receptor and pathogen protein sequence variants and measure relevant phenotypes. We describe several approaches that probe different regions of the high-dimensional sequence space and comment on how combinations of these methods may offer novel insight into immune-pathogen coevolution.

Entropic analysis of antigen-specific CDR3 domains identifies essential binding motifs shared by CDR3s with different antigen specificities

Antigen-specific T cell receptor (TCR) sequences can have prognostic, predictive, and therapeutic value, but decoding the specificity of TCR recognition remains challenging. Unlike DNA strands that base pair, TCRs bind to their targets with different orientations and different lengths, which complicates comparisons. We present scanning parametrized by normalized TCR length (SPAN-TCR) to analyze antigen-specific TCR CDR3 sequences and identify patterns driving TCR-pMHC specificity. Using entropic analysis, SPAN-TCR identifies 2-mer motifs that decrease the diversity (entropy) of CDR3s. These motifs are the most common patterns that can predict CDR3 composition, and we identify "essential" motifs that decrease entropy in the same CDR3 α or β chain containing the 2-mer, and "super-essential" motifs that decrease entropy in both chains. Molecular dynamics analysis further suggests that these motifs may play important roles in binding. We then employ SPAN-TCR to resolve similarities in TCR repertoires against different antigens using public databases of TCR sequences.

Signatures of T cell immunity revealed using sequence similarity with TCRDivER algorithm

Changes in the T cell receptor (TCR) repertoires have become important markers for monitoring disease or therapy progression. With the rise of immunotherapy usage in cancer, infectious and autoimmune disease, accurate assessment and comparison of the "state" of the TCR repertoire has become paramount. One important driver of change within the repertoire is T cell proliferation following immunisation. A way of monitoring this is by investigating large clones of individual T cells believed to bind epitopes connected to the disease. However, as a single target can be bound by many different TCRs, monitoring individual clones cannot fully account for T cell cross-reactivity. Moreover, T cells responding to the same target often exhibit higher sequence similarity, which highlights the importance of accounting for TCR similarity within the repertoire. This complexity of binding relationships between a TCR and its target convolutes comparison of immune responses between individuals or comparisons of TCR repertoires at different timepoints. Here we propose TCRDivER algorithm (T cell Receptor Diversity Estimates for Repertoires), a global method of T cell repertoire comparison using diversity profiles sensitive to both clone size and sequence similarity. This approach allowed for distinction between spleen TCR repertoires of immunised and non-immunised mice, showing the need for including both facets of repertoire changes simultaneously. The analysis revealed biologically interpretable relationships between sequence similarity and clonality. These aid in understanding differences and separation of repertoires stemming from different biological context. With the rise of availability of sequencing data we expect our tool to find broad usage in clinical and research applications.

Understanding repertoire sequencing data through a multiscale computational model of the germinal center

Sequencing of B-cell and T-cell immune receptor repertoires helps us to understand the adaptive immune response, although it only provides information about the clonotypes (lineages) and their frequencies and not about, for example, their affinity or antigen (Ag) specificity. To further characterize the identified clones, usually with special attention to the particularly abundant ones (dominant), additional time-consuming or expensive experiments are generally required. Here, we present an extension of a multiscale model of the germinal center (GC) that we previously developed to gain more insight in B-cell repertoires. We compare the extent that these simulated repertoires deviate from experimental repertoires established from single GCs, blood, or tissue. Our simulations show that there is a limited correlation between clonal abundance and affinity and that there is large affinity variability among same-ancestor (same-clone) subclones. Our simulations suggest that low-abundance clones and subclones, might also be of interest since they may have high affinity for the Ag. We show that the fraction of plasma cells (PCs) with high B-cell receptor (BcR) mRNA content in the GC does not significantly affect the number of dominant clones derived from single GCs by sequencing BcR mRNAs. Results from these simulations guide data interpretation and the design of follow-up experiments.

Exploring the sheep (Ovis aries) immunoglobulin repertoire by next generation sequencing

Next-generation sequencing (NGS) has revolutionized the way we determine the antibody repertoires encoded by B cells in the blood or lymphoid organs and transformed our understanding of adaptive immune responses in many species. Sheep (Ovis aries) have been widely used as a host for therapeutic antibody production since the early 1980s, however, little is known about their immune repertoires or immunological processes affecting the antibody generation. The objective of this study was to employ NGS for a comprehensive analysis of immunoglobulin heavy and light chain repertoires in four healthy sheep. We obtained > 90 % complete antibody sequences and nearly 130,000, 48,000 and 218,000 unique CDR3 reads for the heavy chain (IGH), kappa chain (IGK), and lambda chain (IGL) loci, respectively. Consistent with other species, we observed biased usage of germline variable (V), diversity (D) and joining (J) genes in the heavy and kappa loci, but not in the lambda loci. Moreover, the enormous diversity of CDR3 sequences was observed through sequence clustering and convergent recombination. These data will build a foundation for future studies investigating immune repertoires in health and disease as well as contribute to further refinement of ovine-derived therapeutic antibody drugs.

An open protocol for modeling T Cell Clonotype repertoires using TCRβ CDR3 sequences

T cell receptor repertoires can be profiled using next generation sequencing (NGS) to measure and monitor adaptive dynamical changes in response to disease and other perturbations. Genomic DNA-based bulk sequencing is cost-effective but necessitates multiplex target amplification using multiple primer pairs with highly variable amplification efficiencies. Here, we utilize an equimolar primer mixture and propose a single statistical normalization step that efficiently corrects for amplification bias post sequencing. Using samples analyzed by both our open protocol and a commercial solution, we show high concordance between bulk clonality metrics. This approach is an inexpensive and open-source alternative to commercial solutions.

Cetuximab Responses in Patients with HNSCC Correlate to Clonal Expansion Feature of Peripheral and Tumor-Infiltrating T Cells with Top T-Cell Receptor Clonotypes

PURPOSE

Cetuximab is a standard-of-care treatment for head and neck squamous cell carcinoma (HNSCC). Well-defined correlative markers of therapeutic responses are still lacking. Characterizing dynamic changes of T-cell receptor (TCR) repertoire in peripheral blood and tumor tissue may facilitate developing markers for cetuximab response in HNSCCs.

EXPERIMENTAL DESIGN

We analyzed high-throughput TCRβ sequencing data generated with ImmunoSEQ platform using peripheral blood mononuclear cells (PBMC) and tumor-infiltrating lymphocytes (TIL) from patients with HNSCC before and after cetuximab treatment (pre-/post-PBMC vs. pre-/post-TIL). Multiple analytic approaches were employed to normalize sequencing data.

RESULTS

Normalized TCR richness was significantly lower in post-TIL than pre-TIL, suggesting that cetuximab reduced TCR diversity and promoted TCR expansion in TIL samples, regardless of response status. The magnitude of clonal expansion (defined as expansion rate) in top 20 TCR clonotypes was significantly higher in responder PBMC with or without normalization, and in responder TIL upon normalization, than nonresponder ones. Notably, the expanded top 20 or top 50 TCR clonotypes overlapped between PBMC and TIL samples, which occurred significantly more frequently in responders than nonresponders.

CONCLUSIONS

Patients with cetuximab-treated HNSCC harbor dynamic changes of TCR repertoires correlative to therapeutic responses. The expansion rate of top TCR clonotypes in peripheral blood may serve as a minimally invasive, readily accessible, and feasible marker for predicting cetuximab responses in HNSCCs and beyond, and the expansion rate of top TCR clonotypes in TILs and their overlapping probability between PBMC and TIL may serve as additional predictive markers. Our study also highlights the importance of data normalization for TCR repertoire analysis.

Analyzing Antibody Repertoire Using Next-Generation Sequencing and Machine Learning

Advances in high-throughput sequencing technologies have enabled comprehensive sequencing of the immune repertoire. Since repertoire analysis can help to explain the relationship between the immune system and diseases, several methods have been developed for repertoire analysis. Here, using simulated and real-world datasets, we describe how to use DeepRC, a method that applies cutting-edge machine learning techniques.

Immune repertoire profiling for disease pathobiology

Lymphocytes consist of highly heterogeneous populations, each expressing a specific cell surface receptor corresponding to a particular antigen. Lymphocytes are both the cause and regulator of various diseases, including autoimmune/allergic diseases, lifestyle diseases, neurodegenerative diseases, and cancers. Recently, immune repertoire sequencing has attracted much attention because it helps obtain global profiles of the immune receptor sequences of infiltrating T and B cells in specimens. Immune repertoire sequencing not only helps deepen our understanding of the molecular mechanisms of immune-related pathology but also assists in discovering novel therapeutic modalities for diseases, thereby shedding colorful light on otherwise tiny monotonous cells when observed under a microscope. In this review article, we introduce and detail the background and methodology of immune repertoire sequencing and summarize recent scientific achievements in association with human diseases. Future perspectives on this genetic technique in the field of histopathological research will also be discussed.

simAIRR: simulation of adaptive immune repertoires with realistic receptor sequence sharing for benchmarking of immune state prediction methods

BACKGROUND

Machine learning (ML) has gained significant attention for classifying immune states in adaptive immune receptor repertoires (AIRRs) to support the advancement of immunodiagnostics and therapeutics. Simulated data are crucial for the rigorous benchmarking of AIRR-ML methods. Existing approaches to generating synthetic benchmarking datasets result in the generation of naive repertoires missing the key feature of many shared receptor sequences (selected for common antigens) found in antigen-experienced repertoires.

RESULTS

We demonstrate that a common approach to generating simulated AIRR benchmark datasets can introduce biases, which may be exploited for undesired shortcut learning by certain ML methods. To mitigate undesirable access to true signals in simulated AIRR datasets, we devised a simulation strategy (simAIRR) that constructs antigen-experienced-like repertoires with a realistic overlap of receptor sequences. simAIRR can be used for constructing AIRR-level benchmarks based on a range of assumptions (or experimental data sources) for what constitutes receptor-level immune signals. This includes the possibility of making or not making any prior assumptions regarding the similarity or commonality of immune state-associated sequences that will be used as true signals. We demonstrate the real-world realism of our proposed simulation approach by showing that basic ML strategies perform similarly on simAIRR-generated and real-world experimental AIRR datasets.

CONCLUSIONS

This study sheds light on the potential shortcut learning opportunities for ML methods that can arise with the state-of-the-art way of simulating AIRR datasets. simAIRR is available as a Python package: https://github.com/KanduriC/simAIRR.

T cell Repertoire Profiling and the Mechanism by which HLA-B27 Causes Ankylosing Spondylitis

Purpose of Review

Ankylosing spondylitis (AS) is strongly associated with the HLA-B27 gene. The canonical function of HLA-B27 is to present antigenic peptides to CD8 lymphocytes, leading to adaptive immune responses. The ‘arthritogenic peptide’ theory as to the mechanism by which HLA-B27 induces ankylosing spondylitis proposes that HLA-B27 presents peptides derived from exogenous sources such as bacteria to CD8 lymphocytes, which subsequently cross-react with antigens at the site of inflammation of the disease, causing inflammation. This review describes findings of studies in AS involving profiling of T cell expansions and discusses future research opportunities based on these findings.

Recent Findings

Consistent with this theory, there is an expanding body of data showing that expansion of a restricted pool of CD8 lymphocytes is found in most AS patients yet only in a small proportion of healthy HLA-B27 carriers.

Summary

These exciting findings strongly support the theory that AS is driven by presentation of antigenic peptides to the adaptive immune system by HLA-B27. They point to new potential approaches to identify the exogenous and endogenous antigens involved and to potential therapies for the disease.

Evaluation and comparison of adaptive immunity through analyzing the diversities and clonalities of T-cell receptor repertoires in the peripheral blood

The adaptive immune system plays an important role in defending against different kinds of diseases, including infection and cancer. There has been a longtime need for a simple method to quantitatively evaluate the potency of adaptive immunity in our bodies. The tremendously diversified T-cell receptor (TCR) repertoires are the foundation of the adaptive immune system. In this study, we analyzed the expressed TCRβ repertoires in the peripheral blood of 582 healthy donors and 60 cancer patients. The TCR repertoire in each individual is different, with different usages of TCR Vβ and Jβ genes. Importantly, the TCR diversity and clonality change along with age and disease situation. Most elder individuals and cancer patients have elevated numbers of large TCRβ clones and reduced numbers of shared common clones, and thus, they have very low TCR diversity index (D₅₀) values. These results reveal the alteration of the expressed TCRβ repertoire with aging and oncogenesis, and thus, we hypothesize that the TCR diversity and clonality in the peripheral blood might be used to evaluate and compare the adaptive immunities among different individuals in clinical practice.

T-Cell Receptor Repertoire Sequencing and Its Applications: Focus on Infectious Diseases and Cancer

The immune system is a dynamic feature of each individual and a footprint of our unique internal and external exposures. Indeed, the type and level of exposure to physical and biological agents shape the development and behavior of this complex and diffuse system. Many pathological conditions depend on how our immune system responds or does not respond to a pathogen or a disease or on how the regulation of immunity is altered by the disease itself. T-cells are important players in adaptive immunity and, together with B-cells, define specificity and monitor the internal and external signals that our organism perceives through its specific receptors, TCRs and BCRs, respectively. Today, high-throughput sequencing (HTS) applied to the TCR repertoire has opened a window of opportunity to disclose T-cell repertoire development and behavior down to the clonal level. Although TCR repertoire sequencing is easily accessible today, it is important to deeply understand the available technologies for choosing the best fit for the specific experimental needs and questions. Here, we provide an updated overview of TCR repertoire sequencing strategies, providers and applications to infectious diseases and cancer to guide researchers’ choice through the multitude of available options. The possibility of extending the TCR repertoire to HLA characterization will be of pivotal importance in the near future to understand how specific HLA genes shape T-cell responses in different pathological contexts and will add a level of comprehension that was unthinkable just a few years ago.

Exploring the Immunomodulatory Aspect of Mesenchymal Stem Cells for Treatment of Severe Coronavirus Disease 19

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is an enveloped, positive sense, single stranded RNA (+ssRNA) virus, belonging to the genus Betacoronavirus and family Coronaviridae. It is primarily transmitted from infected persons to healthy ones through inhalation of virus-laden respiratory droplets. After an average incubation period of 2–14 days, the majority of infected individuals remain asymptomatic and/or mildly symptomatic, whereas the remaining individuals manifest a myriad of clinical symptoms, including fever, sore throat, dry cough, fatigue, chest pain, and breathlessness. SARS-CoV-2 exploits the angiotensin converting enzyme 2 (ACE-2) receptor for cellular invasion, and lungs are amongst the most adversely affected organs in the body. Thereupon, immune responses are elicited, which may devolve into a cytokine storm characterized by enhanced secretion of multitude of inflammatory cytokines/chemokines and growth factors, such as interleukin (IL)-2, IL-6, IL-7, IL-8, IL-9, tumor necrosis factor alpha (TNF-α), granulocyte colony-stimulating factor (GCSF), basic fibroblast growth factor 2 (bFGF2), monocyte chemotactic protein-1 (MCP1), interferon-inducible protein 10 (IP10), macrophage inflammatory protein 1A (MIP1A), platelet-derived growth factor subunit B (PDGFB), and vascular endothelial factor (VEGF)-A. The systemic persistence of inflammatory molecules causes widespread histological injury, leading to functional deterioration of the infected organ(s). Although multiple treatment modalities with varying effectiveness are being employed, nevertheless, there is no curative COVID-19 therapy available to date. In this regard, one plausible supportive therapeutic modality may involve administration of mesenchymal stem cells (MSCs) and/or MSC-derived bioactive factors-based secretome to critically ill COVID-19 patients with the intention of accomplishing better clinical outcome owing to their empirically established beneficial effects. MSCs are well established adult stem cells (ASCs) with respect to their immunomodulatory, anti-inflammatory, anti-oxidative, anti-apoptotic, pro-angiogenic, and pro-regenerative properties. The immunomodulatory capabilities of MSCs are not constitutive but rather are highly dependent on a holistic niche. Following intravenous infusion, MSCs are known to undergo considerable histological trapping in the lungs and, therefore, become well positioned to directly engage with lung infiltrating immune cells, and thereby mitigate excessive inflammation and reverse/regenerate damaged alveolar epithelial cells and associated tissue post SARS-CoV-2 infection. Considering the myriad of abovementioned biologically beneficial properties and emerging translational insights, MSCs may be used as potential supportive therapy to counteract cytokine storms and reduce disease severity, thereby facilitating speedy recovery and health restoration.

Profiling the baseline performance and limits of machine learning models for adaptive immune receptor repertoire classification

BACKGROUND

Machine learning (ML) methodology development for the classification of immune states in adaptive immune receptor repertoires (AIRRs) has seen a recent surge of interest. However, so far, there does not exist a systematic evaluation of scenarios where classical ML methods (such as penalized logistic regression) already perform adequately for AIRR classification. This hinders investigative reorientation to those scenarios where method development of more sophisticated ML approaches may be required.

RESULTS

To identify those scenarios where a baseline ML method is able to perform well for AIRR classification, we generated a collection of synthetic AIRR benchmark data sets encompassing a wide range of data set architecture-associated and immune state-associated sequence patterns (signal) complexity. We trained ≈1,700 ML models with varying assumptions regarding immune signal on ≈1,000 data sets with a total of ≈250,000 AIRRs containing ≈46 billion TCRβ CDR3 amino acid sequences, thereby surpassing the sample sizes of current state-of-the-art AIRR-ML setups by two orders of magnitude. We found that L1-penalized logistic regression achieved high prediction accuracy even when the immune signal occurs only in 1 out of 50,000 AIR sequences.

CONCLUSIONS

We provide a reference benchmark to guide new AIRR-ML classification methodology by (i) identifying those scenarios characterized by immune signal and data set complexity, where baseline methods already achieve high prediction accuracy, and (ii) facilitating realistic expectations of the performance of AIRR-ML models given training data set properties and assumptions. Our study serves as a template for defining specialized AIRR benchmark data sets for comprehensive benchmarking of AIRR-ML methods.

Differences in SARS-CoV-2 Vaccine Response Dynamics Between Class-I- and Class-II-Specific T-Cell Receptors in Inflammatory Bowel Disease

T-cells specifically bind antigens to induce adaptive immune responses using highly specific molecular recognition, and a diverse T-cell repertoire with expansion of antigen-specific clones can indicate robust immune responses after infection or vaccination. For patients with inflammatory bowel disease (IBD), a spectrum of chronic intestinal inflammatory diseases usually requiring immunomodulatory treatment, the T-cell response has not been well characterized. Understanding the patient factors that result in strong vaccination responses is critical to guiding vaccination schedules and identifying mechanisms of T-cell responses in IBD and other immune-mediated conditions. Here we used T-cell receptor sequencing to show that T-cell responses in an IBD cohort were influenced by demographic and immune factors, relative to a control cohort of health care workers (HCWs). Subjects were sampled at the time of SARS-CoV-2 vaccination, and longitudinally afterwards; TCR Vβ gene repertoires were sequenced and analyzed for COVID-19-specific clones. We observed significant differences in the overall strength of the T-cell response by age and vaccine type. We further stratified the T-cell response into Class-I- and Class-II-specific responses, showing that Ad26.COV2.S vector vaccine induced Class-I-biased T-cell responses, whereas mRNA vaccine types led to different responses, with mRNA-1273 vaccine inducing a more Class-I-deficient T-cell response compared to BNT162b2. Finally, we showed that these T-cell patterns were consistent with antibody levels from the same patients. Our results account for the surprising success of vaccination in nominally immuno-compromised IBD patients, while suggesting that a subset of IBD patients prone to deficiencies in T-cell response may warrant enhanced booster protocols.

Longitudinal High-Throughput Sequencing of the T-Cell Receptor Repertoire Reveals Dynamic Change and Prognostic Significance of Peripheral Blood TCR Diversity in Metastatic Colorectal Cancer During Chemotherapy

Colorectal cancer (CRC) is a major cause of cancer mortality and morbidity. Despite advances in chemotherapy and targeted therapy, unsustainable clinical benefit was noted due to recurrence and therapy resistance. The immune status of the cancer patient may affect the effectiveness of disease treatments. The dynamic change in the T-cell receptor (TCR) repertoire might be a clinical parameter for monitoring treatment responses. In this study, we aimed to determine the characteristics and clinical significance of the TCR repertoire in patients with unresectable metastatic colorectal cancer (mCRC). Herein, we comprehensively profile 103 peripheral blood samples from 20 healthy controls and 16 CRC patients with a follow-up of 98 to 452 days to identify hypervariable rearrangements of the TCRα and TCRβ repertoires using high-throughput sequencing. We found that TCRα repertoires, TCRβ repertoires, and CDR3 clonotypes were altered in mCRC patients compared with healthy controls. The diversity of TCR repertoires and CDR3 clonotypes decreased in most mCRC patients after therapy. Furthermore, compared with baseline TCR diversity, patients whose TCR diversity dropped considerably during therapy had better treatment responses, including lower CEA and CA19-9 levels and smaller tumor sizes. TCR baseline diversity was also significantly associated with partial response (PR) status (odds ratio: 5.29, p = 0.04). In conclusion, the present study demonstrated the association between dynamic changes in TCR diversity during chemotherapy and clinical outcomes as well as the potential utility of the TCR repertoire in predicting the prognosis of cancer treatment.

Rapid development of analytical methods for evaluating pandemic vaccines: a COVID-19 perspective

Vaccines are key in charting a path out of the COVID-19 pandemic. However, development of new vaccines is highly dependent on availability of analytical methods for their design and evaluation. This paper highlights the challenges presented in having to rapidly develop vaccine analytical tools during an ongoing pandemic, including the need to address progressive virus mutation and adaptation which can render initial assays unreliable or redundant. It also discusses the potential of new computational modeling techniques to model and analyze key viral proteins and their attributes to assist vaccine production and assay design. It then reviews the current range of analytical tools available for COVID-19 vaccine application, ranging from in vitro assays for immunogen characterization to assays to measure vaccine responses in vivo. Finally, it provides a future perspective for COVID-19 vaccine analytical tools and attempts to predict how the field might evolve over the next 5-10 years.

Advances in Lymphoma Molecular Diagnostics

Lymphomas encompass a diverse group of malignant lymphoid neoplasms. Over recent years much scientific effort has been undertaken to identify and understand molecular changes in lymphomas, resulting in a wide range of genetic alterations that have been reported across all types of lymphomas. As many of these changes are now incorporated into the World Health Organization’s defined criteria for the diagnostic evaluation of patients with lymphoid neoplasms, their accurate identification is crucial. Even if many alterations are not routinely evaluated in daily clinical practice, they may still have implications in risk stratification, treatment, prognosis or disease monitoring. Moreover, some alterations can be used for targeted treatment. Therefore, these advances in lymphoma molecular diagnostics in some cases have led to changes in treatment algorithms. Here, we give an overview of and discuss advances in molecular techniques in current clinical practice, as well as highlight some of them in a clinical context.

The Value of Flow Cytometry Clonality in Large Granular Lymphocyte Leukemia

Simple Summary

Large granular lymphocyte (LGL) leukemia, a lymphoproliferative disease, is characterized by an increased frequency of large-sized lymphocytes with typical expression of T-cell receptor (TCR) αβ, CD3, CD8, CD16, CD45RA, and CD57, and with the expansion of one to three subfamilies of the TCR variable β chain reflecting gene rearrangements. Molecular analysis remains the gold standard for confirmation of TCR clonality; however, flow cytometry is time and labor saving, and can be associated with simultaneous investigation of other surface markers. Moreover, Vβ usage by flow cytometry can be employed for monitoring clonal kinetics during treatment and follow-up of LGL leukemia patients.

Abstract

Large granular lymphocyte (LGL) leukemia is a lymphoproliferative disorder of mature T or NK cells frequently associated with autoimmune disorders and other hematological conditions, such as myelodysplastic syndromes. Immunophenotype of LGL cells is similar to that of effector memory CD8⁺ T cells with T-cell receptor (TCR) clonality defined by molecular and/or flow cytometric analysis. Vβ usage by flow cytometry can identify clonal TCR rearrangements at the protein level, and is fast, sensitive, and almost always available in every Hematology Center. Moreover, Vβ usage can be associated with immunophenotypic characterization of LGL clone in a multiparametric staining, and clonal kinetics can be easily monitored during treatment and follow-up. Finally, Vβ usage by flow cytometry might identify LGL clones silently underlying other hematological conditions, and routine characterization of Vβ skewing might identify recurrent TCR rearrangements that might trigger aberrant immune responses during hematological or autoimmune conditions.

The methods and advances of adaptive immune receptors repertoire sequencing

The adaptive immune response is a powerful tool, capable of recognizing, binding to, and neutralizing a vast number of internal and external threats via T or B lymphatic receptors with widespread sets of antigen specificities. The emergence of high-throughput sequencing technology and bioinformatics provides opportunities for research in the fields of life sciences and medicine. The analysis and annotation for immune repertoire data can reveal biologically meaningful information, including immune prediction, target antigens, and effective evaluation. Continuous improvements of the immunological repertoire sequencing methods and analysis tools will help to minimize the experimental and calculation errors and realize the immunological information to meet the clinical requirements. That said, the clinical application of adaptive immune repertoire sequencing requires appropriate experimental methods and standard analytical tools. At the population cell level, we can acquire the overview of cell groups, but the information about a single cell is not obtained accurately. The information that is ignored may be crucial for understanding the heterogeneity of each cell, gene expression and drug response. The combination of high-throughput sequencing and single-cell technology allows us to obtain single-cell information with low-cost and high-throughput. In this review, we summarized the current methods and progress in this area.

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

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

Associations between T cell infiltration, T cell receptor clonality, histology and recurrence in renal cell carcinoma

Renal cell carcinoma (RCC) is comprised of clear-cell (ccRCC) and non-clear-cell (nccRCC) tumors. Despite definitive surgical resection in localized disease, recurrence often occurs. A commercial method based on a multiplex polymerase chain reaction (PCR) assay exclusively targets rearranged T cell receptor (TCR) genes to generate high-throughput sequencing-based data, allowing characterization of the immune repertoire within tumors. In this study we performed a retrospective analysis on archived tumor samples from patients with recurring versus non-recurring T3 ccRCC and on samples from early nccRCC versus ccRCC. Following genomic DNA extraction and multiplex PCR, the fraction of T cells within tumors, the number of unique receptors ('richness') and their relative abundances ('clonality') were calculated. Statistical significance and correlations were calculated using Student's t-test and Spearman's rho, respectively. Average fraction and clonality of T cells in tumors from non-recurring patients was 2.5- and 4.3-fold higher than in recurring patients (P = 0.025 and P = 0.043, respectively). A significant positive correlation was found between T cell fraction and clonality (Spearman's rho = 0.78, P = 0.008). The average fraction of T cells in ccRCC tumors was 2.8-fold higher than in nccRCC tumors (P = 0.015). Clonality and estimated richness were similar between ccRCC and nccRCC tumors. In summary, recurrence of ccRCC is associated with a lower fraction and clonality of T cells within tumors; nccRCC tumors are more 'deserted' than ccRCC, but similar in their ability to generate a clonal T cell repertoire. Our work suggests associations between the characteristics of T cell infiltrate, histology and tumor recurrence.

Biological controls for standardization and interpretation of adaptive immune receptor repertoire profiling

Use of adaptive immune receptor repertoire sequencing (AIRR-seq) has become widespread, providing new insights into the immune system with potential broad clinical and diagnostic applications. However, like many high-throughput technologies, it comes with several problems, and the AIRR Community was established to understand and help solve them. We, the AIRR Community’s Biological Resources Working Group, have surveyed scientists about the need for standards and controls in generating and annotating AIRR-seq data. Here, we review the current status of AIRR-seq, provide the results of our survey, and based on them, offer recommendations for developing AIRR-seq standards and controls, including future work.

T cell receptor beta locus sequencing early post-allogeneic stem cell transplant identifies patients at risk of initial and recurrent cytomegalovirus infection

Identification of patients at risk of initial & recurrent cytomegalovirus (CMV) reactivation following allogeneic stem cell transplant (alloSCT) may help guide prophylactic strategies. T-cell receptor beta (TRB) deep sequencing was used to identify and enumerate the T-cell repertoire harbouring TRB sequences with annotated specificity to CMV (pubCMVrep), as well as the overall T-cell receptor (TCR) repertoire diversity at day +30 & day +60 post-alloSCT for 65 patients. T-cells harbouring TRB sequences with annotated specificity for CMV were identifiable in all patients. 56% of patients required CMV treatment and 23% of the cohort developed recurrent CMV. PubCMVrep size at day +30 was not associated with reactivation, however amongst patients with antecedent CMV viremia a low day +60 pubCMVrep was associated with a greater incidence of recurrent CMV (75% vs. 21%, HR 6.16, 95% CI 1.29-29.40, P = 0.0008). Moreover, patients with high pubCMVrep only developed recurrent CMV in the setting of GVHD. Low TCR diversity at day +30 was associated with a greater incidence of initial CMV reactivation (71% vs. 22%, HR 5.39, 95% CI 1.70-17.09, p = 0.0002). pubCMVrep and TCR diversity are promising biomarkers to identify patients at risk of initial & recurrent CMV who may benefit from novel prophylactic strategies.

Select Antitumor Cytotoxic CD8+ T Clonotypes Expand in Patients with Chronic Lymphocytic Leukemia Treated with Ibrutinib

PURPOSE

In chronic lymphocytic leukemia (CLL), the T-cell receptor (TCR) repertoire is skewed and tumor-derived antigens are hypothesized as drivers of oligoclonal expansion. Ibrutinib, a standard treatment for CLL, inhibits not only Bruton tyrosine kinase of the B-cell receptor signaling pathway, but also IL2-inducible kinase of the TCR signaling pathway. T-cell polarization and activation are affected by ibrutinib, but it is unknown whether T cells contribute to clinical response.

EXPERIMENTAL DESIGN

High-throughput TCRβ sequencing was performed in 77 longitudinal samples from 26 patients with CLL treated with ibrutinib. TCRβ usage in CD4⁺ and CD8⁺ T cells and granzyme B expression were assessed by flow cytometric analysis. Antitumor cytotoxicity of T cells expanded with autologous CLL cells or with antigen-independent anti-CD3/CD28/CD137 beads was tested.

RESULTS

The clonality of the TCR repertoire increased at the time of response. With extended treatment, TCR clonality remained stable in patients with sustained remission and decreased in patients with disease progression. Expanded clonotypes were rarely shared between patients, indicating specificity for private antigens. Flow cytometry demonstrated a predominance of CD8⁺ cells among expanded clonotypes. Importantly, bulk T cells from responding patients were cytotoxic against autologous CLL cells in vitro and selective depletion of major expanded clonotypes reduced CLL cell killing.

CONCLUSIONS

In patients with CLL, established T-cell responses directed against tumor are suppressed by disease and reactivated by ibrutinib.See related commentary by Zent, p. 4465.

TCRMatch: Predicting T-Cell Receptor Specificity Based on Sequence Similarity to Previously Characterized Receptors

The adaptive immune system in vertebrates has evolved to recognize non-self antigens, such as proteins expressed by infectious agents and mutated cancer cells. T cells play an important role in antigen recognition by expressing a diverse repertoire of antigen-specific receptors, which bind epitopes to mount targeted immune responses. Recent advances in high-throughput sequencing have enabled the routine generation of T-cell receptor (TCR) repertoire data. Identifying the specific epitopes targeted by different TCRs in these data would be valuable. To accomplish that, we took advantage of the ever-increasing number of TCRs with known epitope specificity curated in the Immune Epitope Database (IEDB) since 2004. We compared seven metrics of sequence similarity to determine their power to predict if two TCRs have the same epitope specificity. We found that a comprehensive k-mer matching approach produced the best results, which we have implemented into TCRMatch, an openly accessible tool (http://tools.iedb.org/tcrmatch/) that takes TCR β-chain CDR3 sequences as an input, identifies TCRs with a match in the IEDB, and reports the specificity of each match. We anticipate that this tool will provide new insights into T cell responses captured in receptor repertoire and single cell sequencing experiments and will facilitate the development of new strategies for monitoring and treatment of infectious, allergic, and autoimmune diseases, as well as cancer.

Dynamic blood single-cell immune responses in patients with COVID-19

The 2019 coronavirus disease (COVID-19) outbreak caused by the SARS-CoV-2 virus is an ongoing global health emergency. However, the virus’ pathogenesis remains unclear, and there is no cure for the disease. We investigated the dynamic changes of blood immune response in patients with COVID-19 at different stages by using 5’ gene expression, T cell receptor (TCR), and B cell receptors (BCR) V(D)J transcriptome analysis at a single-cell resolution. We obtained single-cell mRNA sequencing (scRNA-seq) data of 341,420 peripheral blood mononuclear cells (PBMCs) and 185,430 clonotypic T cells and 28,802 clonotypic B cells from 25 samples of 16 patients with COVID-19 for dynamic studies. In addition, we used three control samples. We found expansion of dendritic cells (DCs), CD14+ monocytes, and megakaryocytes progenitor cells (MP)/platelets and a reduction of naïve CD4+ T lymphocytes in patients with COVID-19, along with a significant decrease of CD8+ T lymphocytes, and natural killer cells (NKs) in patients in critical condition. The type I interferon (IFN-I), mitogen-activated protein kinase (MAPK), and ferroptosis pathways were activated while the disease was active, and recovered gradually after patient conditions improved. Consistent with this finding, the mRNA level of IFN-I signal-induced gene IFI27 was significantly increased in patients with COVID-19 compared with that of the controls in a validation cohort that included 38 patients and 35 controls. The concentration of interferon-α (IFN-α) in the serum of patients with COVID-19 increased significantly compared with that of the controls in an additional cohort of 215 patients with COVID-19 and 106 controls, further suggesting the important role of the IFN-I pathway in the immune response of COVID-19. TCR and BCR sequences analyses indicated that patients with COVID-19 developed specific immune responses against SARS-CoV-2 antigens. Our study reveals a dynamic landscape of human blood immune responses to SARS-CoV-2 infection, providing clues for therapeutic potentials in treating COVID-19.

A new clustering method identifies multiple sclerosis-specific T-cell receptors

OBJECTIVE

To characterize T-cell receptors (TCRs) and identify target epitopes in multiple sclerosis (MS).

METHODS

Peripheral blood mononuclear cells were obtained from 39 MS patients and 19 healthy controls (HCs). TCR repertoires for α/β/δ/γ chains, TCR diversity, and V/J usage were determined by next-generation sequencing. TCR β chain repertoires were compared with affectation status using a novel clustering method, Grouping of Lymphocyte Interactions by Paratope Hotspots (GLIPH). Cytomegalovirus (CMV)-IgG was measured in an additional 113 MS patients and 93 HCs. Regulatory T cells (Tregs) were measured by flow cytometry.

RESULTS

TCR diversity for all four chains decreased with age. TCRα and TCRβ diversity was higher in MS patients (P = 0.0015 and 0.024, respectively), even after age correction. TRAJ56 and TRBV4-3 were more prevalent in MS patients than in HCs (p^corr  = 0.027 and 0.040, respectively). GLIPH consolidated 208,674 TCR clones from MS patients into 1,294 clusters, among which two candidate clusters were identified. The TRBV4-3 cluster was shared by HLA-DRB1*04:05-positive patients (87.5%) and predicted to recognize CMV peptides (CMV-TCR). MS Severity Score (MSSS) was lower in patients with CMV-TCR than in those without (P = 0.037). CMV-IgG-positivity was associated with lower MSSS in HLA-DRB1*04:05 carriers (P = 0.0053). HLA-DRB1*04:05-positive individuals demonstrated higher CMV-IgG titers than HLA-DRB1*04:05-negative individuals (P = 0.017). CMV-IgG-positive patients had more Tregs than CMV-IgG-negative patients (P = 0.054).

INTERPRETATION

High TCRα/TCRβ diversity, regardless of age, is characteristic of MS. Association of a CMV-recognizing TCR with mild disability indicates CMV's protective role in HLA-DRB1*04:05-positive MS.

Gut Microbiome Contributes to Liver Fibrosis Impact on T Cell Receptor Immune Repertoire

Gut microbiota (GM) modifies the intrahepatic immune microenvironment, but the underlying mechanisms remain poorly understood. Liver fibrosis-associated imprinting is predicted to be reflected in GM. This study investigated the link between GM and the intrahepatic T cell receptor (TCR) immune repertoire (IR), and whether GM modulates the intrahepatic immune microenvironment via TCR IR during liver fibrosis. We analyzed the correlation between GM and TCR IR during liver fibrogenesis. Accordingly, 16S rRNA gene sequencing (16S-seq) and bulk immune repertoire sequencing (IR-seq) were performed to characterize GM and intrahepatic TCR IR. Fecal microbial transplant (FMT) and TCRβ knockout (Tcrb^KO) mouse models were employed to determine the biological link between GM and TCR IR in liver fibrosis. We found that GM and intrahepatic TCR IR are highly correlated, with both showing reduced diversity and centralized distribution during liver fibrosis. The restoration of normal intestinal microbiota may reshape intrahepatic TCR IR and delay liver fibrosis. Interestingly, TCR IR ablation abrogated the impact of GM on liver fibrogenesis. Furthermore, GM modulated hepatic stellate cell (HSC) activation via TCR IR-mediated intrahepatic immune milieu. Our study demonstrates that GM, which exhibits cross-talk with the intrahepatic TCR IR, influences the intrahepatic immune microenvironment and liver fibrosis progression.

The head and neck cancer genome in the era of immunotherapy

The recent success of immunotherapy in head and neck squamous cell carcinoma (HNSCC) has necessitated a new perspective on the cancer genome. Here we review recent advances in the carcinogenesis and molecular genetics of HNSCC with an eye on their implications for cancer immunity. Newer sequencing technologies have recently facilitated dissection of the complex interaction between the HPV virus, tumor, host factors, and the tumor microenvironment (TME) that help shed light on how the immune system interacts with head and neck malignancies.

Probing infectious disease by single-cell RNA sequencing: Progresses and perspectives

The increasing application of single-cell RNA sequencing (scRNA-seq) technology in life science and biomedical research has significantly increased our understanding of the cellular heterogeneities in immunology, oncology and developmental biology. This review will summarize the development of various scRNA-seq technologies; primarily discussing the application of scRNA-seq on infectious diseases, and exploring the current development, challenges, and potential applications of scRNA-seq technology in the future.

GLaMST: grow lineages along minimum spanning tree for b cell receptor sequencing data

Background

B cell affinity maturation enables B cells to generate high-affinity antibodies. This process involves somatic hypermutation of B cell immunoglobulin receptor (BCR) genes and selection by their ability to bind antigens. Lineage trees are used to describe this microevolution of B cell immunoglobulin genes. In a lineage tree, each node is one BCR sequence that mutated from the germinal center and each directed edge represents a single base mutation, insertion or deletion. In BCR sequencing data, the observed data only contains a subset of BCR sequences in this microevolution process. Therefore, reconstructing the lineage tree from experimental data requires algorithms to build the tree based on partially observed tree nodes.

Results

We developed a new algorithm named Grow Lineages along Minimum Spanning Tree (GLaMST), which efficiently reconstruct the lineage tree given observed BCR sequences that correspond to a subset of the tree nodes. Through comparison using simulated and real data, GLaMST outperforms existing algorithms in simulations with high rates of mutation, insertion and deletion, and generates lineage trees with smaller size and closer to ground truth according to tree features that highly correlated with selection pressure.

Conclusions

GLaMST outperforms state-of-art in reconstruction of the BCR lineage tree in both efficiency and accuracy. Integrating it into existing BCR sequencing analysis frameworks can significant improve lineage tree reconstruction aspect of the analysis.

Long-term robustness of a T-cell system emerging from somatic rescue of a genetic block in T-cell development

BACKGOUND

The potential of a single progenitor cell to establish and maintain long-term protective T-cell immunity in humans is unknown. For genetic disorders disabling T-cell immunity, somatic reversion was shown to support limited T-cell development attenuating the clinical phenotype. However, the cases reported so far deteriorated over time leaving unanswered the important question of long-term activity of revertant precursors and the robustness of the resulting T-cell system.

METHODS

We applied TCRβ-CDR3 sequencing and mass cytometry on serial samples of a now 18 year-old SCIDX1 patient with somatic reversion to analyse the longitudinal diversification and stability of a T-cell system emerging from somatic gene rescue.

FINDINGS

We detected close to 105 individual CDR3β sequences in the patient. Blood samples of equal size contained about 10-fold fewer unique CDR3β sequences compared to healthy donors, indicating a surprisingly broad repertoire. Despite dramatic expansions and contractions of individual clonotypes representing up to 30% of the repertoire, stable diversity indices revealed that these transient clonal distortions did not cause long-term repertoire imbalance. Phenotypically, the T-cell system did not show evidence for progressive exhaustion. Combined with immunoglobulin substitution, the limited T-cell system in this patient supported an unremarkable clinical course over 18 years.

INTERPRETATION

Genetic correction in the appropriate cell type, in our patient most likely in a T-cell biased self-renewing hematopoietic progenitor, can yield a diverse T-cell system that provides long-term repertoire stability, does not show evidence for progressive exhaustion and is capable of providing protective and regulated T-cell immunity for at least two decades.

FUNDING

DFG EH 145/9-1, DFG SCHW 432/4-1 and the German Research Foundation under Germany's Excellence Strategy-EXC-2189-Project ID: 390939984.

Dissecting efficiency of a 5' rapid amplification of cDNA ends (5'-RACE) approach for profiling T-cell receptor beta repertoire

Deep sequencing of T-cell receptor (TCR) genes is powerful at profiling immune repertoire. To prepare a TCR sequencing library, multiplex polymerase chain reaction (mPCR) is widely applied and is highly efficient. That is, most mPCR products contain the region critical for antigen recognition, which also indicates regular V(D)J recombination. Multiplex PCR, however, may suffer from primer bias. A promising alternative is 5'-RACE, which avoids primer bias by applying only one primer pair. In 5'-RACE data, however, non-regular V(D)J recombination (e.g., TCR sequences without a V gene segment) has been observed and the frequency varies (30-80%) between studies. This suggests that the cause of or how to reduce non-regular TCR sequences is not yet well known by the science community. Although it is possible to speculate the cause by comparing the 5'-RACE protocols, careful experimental confirmation is needed and such a systematic study is still not available. Here, we examined the 5'-RACE protocol of a commercial kit and demonstrated how a modification increased the fraction of regular TCR-β sequences to >85%. We also found a strong linear correlation between the fraction of short DNA fragments and the percentage of non-regular TCR-β sequences, indicating that the presence of short DNA fragments in the library was the main cause of non-regular TCR-β sequences. Therefore, thorough removal of short DNA fragments from a 5'-RACE library is the key to high data efficiency. We highly recommend conducting a fragment length analysis before sequencing, and the fraction of short DNA fragments can be used to estimate the percentage of non-regular TCR sequences. As deep sequencing of TCR genes is still relatively expensive, good quality control should be valuable.

Methods for sequence and structural analysis of B and T cell receptor repertoires

B cell receptors (BCRs) and T cell receptors (TCRs) make up an essential network of defense molecules that, collectively, can distinguish self from non-self and facilitate destruction of antigen-bearing cells such as pathogens or tumors. The analysis of BCR and TCR repertoires plays an important role in both basic immunology as well as in biotechnology. Because the repertoires are highly diverse, specialized software methods are needed to extract meaningful information from BCR and TCR sequence data. Here, we review recent developments in bioinformatics tools for analysis of BCR and TCR repertoires, with an emphasis on those that incorporate structural features. After describing the recent sequencing technologies for immune receptor repertoires, we survey structural modeling methods for BCR and TCRs, along with methods for clustering such models. We review downstream analyses, including BCR and TCR epitope prediction, antibody-antigen docking and TCR-peptide-MHC Modeling. We also briefly discuss molecular dynamics in this context.

Next-Generation Neuroimmunology: New Technologies to Understand Central Nervous System Autoimmunity

Understanding neuroimmunological disorders is essential for developing new diagnostic and therapeutic strategies. Rodent models have provided valuable insights, but are sometimes equated with their human counterparts. Here, we summarize how novel technologies may enable an improved human-focused view of immune mechanisms. Recent studies have applied these new technologies to the brain parenchyma, its surrounding cerebrospinal fluid, and peripheral immune compartments. Therapeutic interventions have also facilitated translational understanding in a reverse way. However, with improved technology, access to patient samples remains a rate-limiting step in translational research. We anticipate that next-generation neuroimmunology is likely to integrate, in the immediate future, diverse technical tools for optimal diagnosis, prognosis, and treatment of neuroimmunological disorders.

An analysis of abnormalities in the B cell receptor repertoire in patients with systemic sclerosis using high-throughput sequencing

Systemic sclerosis is a chronic multisystem autoimmune disease that is associated with polyclonal B cell hyperreactivity. The CDR3 of BCRs is the major site of antigen recognition. Therefore, we analyzed the BCR repertoire of patients with SSc. The BCR repertoires in 12 subjects including eight SSc patients and four healthy controls were characterized by high-throughput sequencing, and bioinformatics analysis were studied. The average CDR3 length in the SSc group was significantly shorter. The SSc patient displayed more diverse BCR. Moreover, SSc patients with mild skin sclerosis, anti-Scl70, interstitial lung disease or female sex were more diversified. B cells from the SSc patients showed a differential V and J gene usage. SSc patients had distinct BCR repertoires.These findings reflected the differences of BCR repertoires between SSc patients and controls. The higher-usage genes for the BCR sequence might be potential biomarkers of B cell-targeted therapies or diagnosis for SSc.

Single-Cell Sequencing of T cell Receptors: A Perspective on the Technological Development and Translational Application

T cells recognize peptides bound to major histocompatibility complex (MHC) class I and class II molecules at the cell surface. This recognition is accomplished by the expression of T cell receptors (TCR) which are required to be diverse and adaptable in order to accommodate the various and vast number of antigens presented on the MHCs. Thus, determining TCR repertoires of effector T cells is necessary to understand the immunological process in responding to cancer progression, infection, and autoimmune development. Furthermore, understanding the TCR repertoires will provide a solid framework to predict and test the antigen which is more critical in autoimmunity. However, it has been a technical challenge to sequence the TCRs and provide a conceptual context in correlation to the vast number of TCR repertoires in the immunological system. The exploding field of single-cell sequencing has changed how the repertoires are being investigated and analyzed. In this review, we focus on the biology of TCRs, TCR signaling and its implication in autoimmunity. We discuss important methods in bulk sequencing of many cells. Lastly, we explore the most pertinent platforms in single-cell sequencing and its application in autoimmunity.

Innate and adaptive immune responses in Parkinson's disease

Parkinson's disease (PD) has classically been defined as a movement disorder, in which motor symptoms are explained by the aggregation of alpha-synuclein (α-syn) and subsequent death of dopaminergic neurons of the substantia nigra pars compacta (SNpc). More recently, the multisystem effects of the disease have been investigated, with the immune system being implicated in a number of these processes in the brain, the blood, and the gut. In this review, we highlight the dysfunctional immune system found in both human PD and animal models of the disease, and discuss how genetic risk factors and risk modifiers are associated with pro-inflammatory immune responses. Finally, we emphasize evidence that the immune response drives the pathogenesis and progression of PD, and discuss key questions that remain to be investigated in order to identify immunomodulatory therapies in PD.

Immunoglobulin profiling identifies unique signatures in patients with Kawasaki disease during intravenous immunoglobulin treatment

Identifying the causes of high fever syndromes such as Kawasaki disease (KD) remains challenging. To investigate pathogen exposure signatures in suspected pathogen-mediated diseases such as KD, we performed immunoglobulin (Ig) profiling using a next-generation sequencing method. After intravenous Ig (IVIG) treatment, we observed disappearance of clonally expanded IgM clonotypes, which were dominantly observed in acute-phase patients. The complementary-determining region 3 (CDR3) sequences of dominant IgM clonotypes in acute-phase patients were commonly observed in other Ig isotypes. In acute-phase KD patients, we identified 32 unique IgM CDR3 clonotypes shared in three or more cases. Furthermore, before the IVIG treatment, the sums of dominant IgM clonotypes in IVIG-resistant KD patients were significantly higher than those of IVIG-sensitive KD patients. Collectively, we demonstrate a novel approach for identifying certain Ig clonotypes for potentially interacting with pathogens involved in KD; this approach could be applied for a wide variety of fever-causing diseases of unknown origin.

Deep sequencing of B cell receptor repertoire

Immune repertoire is a collection of enormously diverse adaptive immune cells within an individual. As the repertoire shapes and represents immunological conditions, identification of clones and characterization of diversity are critical for understanding how to protect ourselves against various illness such as infectious diseases and cancers. Over the past several years, fast growing technologies for high throughput sequencing have facilitated rapid advancement of repertoire research, enabling us to observe the diversity of repertoire at an unprecedented level. Here, we focus on B cell receptor (BCR) repertoire and review approaches to B cell isolation and sequencing library construction. These experiments should be carefully designed according to BCR regions to be interrogated, such as heavy chain full length, complementarity determining regions, and isotypes. We also highlight preprocessing steps to remove sequencing and PCR errors with unique molecular index and bioinformatics techniques. Due to the nature of massive sequence variation in BCR, caution is warranted when interpreting repertoire diversity from error-prone sequencing data. Furthermore, we provide a summary of statistical frameworks and bioinformatics tools for clonal evolution and diversity. Finally, we discuss limitations of current BCR-seq technologies and future perspectives on advances in repertoire sequencing.