Extraction of the CDRH3 sequence of the mouse antibody repertoire selected upon influenza virus infection by subtraction of the background antibody repertoire

Historically, antibody reactivity to pathogens and vaccine antigens has been evaluated using serological measurements of antigen-specific antibodies. However, it is difficult to evaluate all antibodies that contribute to various functions in a single assay, such as the measurement of the neutralizing antibody titer. Bulk antibody repertoire analysis using next-generation sequencing is a comprehensive method for analyzing the overall antibody response; however, it is unreliable for estimating antigen-specific antibodies due to individual variation. To address this issue, we propose a method to subtract the background signal from the repertoire of data of interest. In this study, we analyzed changes in antibody diversity and inferred the heavy-chain complementarity-determining region 3 (CDRH3) sequences of antibody clones that were selected upon influenza virus infection in a mouse model using bulk repertoire analysis. A decrease in the diversity of the antibody repertoire was observed upon viral infection, along with an increase in neutralizing antibody titers. Using kernel density estimation of sequences in a high-dimensional sequence space with background signal subtraction, we identified several clusters of CDRH3 sequences induced upon influenza virus infection. Most of these repertoires were detected more frequently in infected mice than in uninfected control mice, suggesting that infection-specific antibody sequences can be extracted using this method. Such an accurate extraction of antigen- or infection-specific repertoire information will be a useful tool for vaccine evaluation in the future.

IMPORTANCE

As specific interactions between antigens and cell-surface antibodies trigger the proliferation of B-cell clones, the frequency of each antibody sequence in the samples reflects the size of each clonal population. Nevertheless, it is extremely difficult to extract antigen-specific antibody sequences from the comprehensive bulk antibody sequences obtained from blood samples due to repertoire bias influenced by exposure to dietary antigens and other infectious agents. This issue can be addressed by subtracting the background noise from the post-immunization or post-infection repertoire data. In the present study, we propose a method to quantify repertoire data from comprehensive repertoire data. This method allowed subtraction of the background repertoire, resulting in more accurate extraction of expanded antibody repertoires upon influenza virus infection. This accurate extraction of antigen- or infection-specific repertoire information is a useful tool for vaccine evaluation.

A CSF-1R-blocking antibody/IL-10 fusion protein increases anti-tumor immunity by effectuating tumor-resident CD8+ T cells

Strategies to increase intratumoral concentrations of an anticancer agent are desirable to optimize its therapeutic potential when said agent is efficacious primarily within a tumor but also have significant systemic side effects. Here, we generate a bifunctional protein by fusing interleukin-10 (IL-10) to a colony-stimulating factor-1 receptor (CSF-1R)-blocking antibody. The fusion protein demonstrates significant antitumor activity in multiple cancer models, especially head and neck cancer. Moreover, this bifunctional protein not only leads to the anticipated reduction in tumor-associated macrophages but also triggers proliferation, activation, and metabolic reprogramming of CD8+ T cells. Furthermore, it extends the clonotype diversity of tumor-infiltrated T cells and shifts the tumor microenvironment (TME) to an immune-active state. This study suggests an efficient strategy for designing immunotherapeutic agents by fusing a potent immunostimulatory molecule to an antibody targeting TME-enriched factors.

Rigorous benchmarking of T-cell receptor repertoire profiling methods for cancer RNA sequencing

The ability to identify and track T-cell receptor (TCR) sequences from patient samples is becoming central to the field of cancer research and immunotherapy. Tracking genetically engineered T cells expressing TCRs that target specific tumor antigens is important to determine the persistence of these cells and quantify tumor responses. The available high-throughput method to profile TCR repertoires is generally referred to as TCR sequencing (TCR-Seq). However, the available TCR-Seq data are limited compared with RNA sequencing (RNA-Seq). In this paper, we have benchmarked the ability of RNA-Seq-based methods to profile TCR repertoires by examining 19 bulk RNA-Seq samples across 4 cancer cohorts including both T-cell-rich and T-cell-poor tissue types. We have performed a comprehensive evaluation of the existing RNA-Seq-based repertoire profiling methods using targeted TCR-Seq as the gold standard. We also highlighted scenarios under which the RNA-Seq approach is suitable and can provide comparable accuracy to the TCR-Seq approach. Our results show that RNA-Seq-based methods are able to effectively capture the clonotypes and estimate the diversity of TCR repertoires, as well as provide relative frequencies of clonotypes in T-cell-rich tissues and low-diversity repertoires. However, RNA-Seq-based TCR profiling methods have limited power in T-cell-poor tissues, especially in highly diverse repertoires of T-cell-poor tissues. The results of our benchmarking provide an additional appealing argument to incorporate RNA-Seq into the immune repertoire screening of cancer patients as it offers broader knowledge into the transcriptomic changes that exceed the limited information provided by TCR-Seq.

Abalign: a comprehensive multiple sequence alignment platform for B-cell receptor immune repertoires

The utilization of high-throughput sequencing (HTS) for B-cell receptor (BCR) immune repertoire analysis has become widespread in the fields of adaptive immunity and antibody drug development. However, the sheer volume of sequences generated by these experiments presents a challenge in data processing. Specifically, multiple sequence alignment (MSA), a critical aspect of BCR analysis, remains inadequate for handling massive BCR sequencing data and lacks the ability to provide immunoglobulin-specific information. To address this gap, we introduce Abalign, a standalone program specifically designed for ultrafast MSA of BCR/antibody sequences. Benchmark tests demonstrate that Abalign achieves comparable or even better accuracy than state-of-the-art MSA tools, and shows remarkable advantages in terms of speed and memory consumption, reducing the time required for high-throughput analysis from weeks to hours. In addition to its alignment capabilities, Abalign offers a broad range of BCR analysis features, including extracting BCRs, constructing lineage trees, assigning VJ genes, analyzing clonotypes, profiling mutations, and comparing BCR immune repertoires. With its user-friendly graphic interface, Abalign can be easily run on personal computers instead of computing clusters. Overall, Abalign is an easy-to-use and effective tool that enables researchers to analyze massive BCR/antibody sequences, leading to new discoveries in the field of immunoinformatics. The software is freely available at http://cao.labshare.cn/abalign/.

Antigen specificity and cross-reactivity drive functionally diverse anti-Aspergillus fumigatus T cell responses in cystic fibrosis

BACKGROUNDThe fungus Aspergillus fumigatus causes a variety of clinical phenotypes in patients with cystic fibrosis (pwCF). Th cells orchestrate immune responses against fungi, but the types of A. fumigatus-specific Th cells in pwCF and their contribution to protective immunity or inflammation remain poorly characterized.METHODSWe used antigen-reactive T cell enrichment (ARTE) to investigate fungus-reactive Th cells in peripheral blood of pwCF and healthy controls.RESULTSWe show that clonally expanded, high-avidity A. fumigatus-specific effector Th cells, which were absent in healthy donors, developed in pwCF. Individual patients were characterized by distinct Th1-, Th2-, or Th17-dominated responses that remained stable over several years. These different Th subsets target different A. fumigatus proteins, indicating that differential antigen uptake and presentation directs Th cell subset development. Patients with allergic bronchopulmonary aspergillosis (ABPA) are characterized by high frequencies of Th2 cells that cross-recognize various filamentous fungi.CONCLUSIONOur data highlight the development of heterogenous Th responses targeting different protein fractions of a single fungal pathogen and identify the development of multispecies cross-reactive Th2 cells as a potential risk factor for ABPA.FUNDINGGerman Research Foundation (DFG), under Germany's Excellence Strategy (EXC 2167-390884018 "Precision Medicine in Chronic Inflammation" and EXC 2051-390713860 "Balance of the Microverse"); Oskar Helene Heim Stiftung; Christiane Herzog Stiftung; Mukoviszidose Institut gGmb; German Cystic Fibrosis Association Mukoviszidose e.V; German Federal Ministry of Education and Science (BMBF) InfectControl 2020 Projects AnDiPath (BMBF 03ZZ0838A+B).

Single-cell clonal tracking of persistent T-cells in allogeneic hematopoietic stem cell transplantation

The critical balance between intended and adverse effects in allogeneic hematopoietic stem cell transplantation (alloHSCT) depends on the fate of individual donor T-cells. To this end, we tracked αβT-cell clonotypes during stem cell mobilization treatment with granulocyte-colony stimulating factor (G-CSF) in healthy donors and for six months during immune reconstitution after transfer to transplant recipients. More than 250 αβT-cell clonotypes were tracked from donor to recipient. These clonotypes consisted almost exclusively of CD8⁺ effector memory T cells (CD8TEM), which exhibited a different transcriptional signature with enhanced effector and cytotoxic functions compared to other CD8TEM. Importantly, these distinct and persisting clonotypes could already be delineated in the donor. We confirmed these phenotypes on the protein level and their potential for selection from the graft. Thus, we identified a transcriptional signature associated with persistence and expansion of donor T-cell clonotypes after alloHSCT that may be exploited for personalized graft manipulation strategies in future studies.

IL7 and IL7 Flt3L co-expressing CAR T cells improve therapeutic efficacy in mouse EGFRvIII heterogeneous glioblastoma

Chimeric antigen receptor (CAR) T cell therapy in glioblastoma faces many challenges including insufficient CAR T cell abundance and antigen-negative tumor cells evading targeting. Unfortunately, preclinical studies evaluating CAR T cells in glioblastoma focus on tumor models that express a single antigen, use immunocompromised animals, and/or pre-treat with lymphodepleting agents. While lymphodepletion enhances CAR T cell efficacy, it diminishes the endogenous immune system that has the potential for tumor eradication. Here, we engineered CAR T cells to express IL7 and/or Flt3L in 50% EGFRvIII-positive and -negative orthotopic tumors pre-conditioned with non-lymphodepleting irradiation. IL7 and IL7 Flt3L CAR T cells increased intratumoral CAR T cell abundance seven days after treatment. IL7 co-expression with Flt3L modestly increased conventional dendritic cells as well as the CD103+XCR1+ population known to have migratory and antigen cross-presenting capabilities. Treatment with IL7 or IL7 Flt3L CAR T cells improved overall survival to 67% and 50%, respectively, compared to 9% survival with conventional or Flt3L CAR T cells. We concluded that CAR T cells modified to express IL7 enhanced CAR T cell abundance and improved overall survival in EGFRvIII heterogeneous tumors pre-conditioned with non-lymphodepleting irradiation. Potentially IL7 or IL7 Flt3L CAR T cells can provide new opportunities to combine CAR T cells with other immunotherapies for the treatment of glioblastoma.

T-cell repertoire diversity: friend or foe for protective antitumor response?

Profiling the T-Cell Receptor (TCR) repertoire is establishing as a potent approach to investigate autologous and treatment-induced antitumor immune response. Technical and computational breakthroughs, including high throughput next-generation sequencing (NGS) approaches and spatial transcriptomics, are providing unprecedented insight into the mechanisms underlying antitumor immunity. A precise spatiotemporal variation of T-cell repertoire, which dynamically mirrors the functional state of the evolving host-cancer interaction, allows the tracking of the T-cell populations at play, and may identify the key cells responsible for tumor eradication, the evaluation of minimal residual disease and the identification of biomarkers of response to immunotherapy. In this review we will discuss the relationship between global metrics characterizing the TCR repertoire such as T-cell clonality and diversity and the resultant functional responses. In particular, we will explore how specific TCR repertoires in cancer patients can be predictive of prognosis or response to therapy and in particular how a given TCR re-arrangement, following immunotherapy, can predict a specific clinical outcome. Finally, we will examine current improvements in terms of T-cell sequencing, discussing advantages and challenges of current methodologies.

In vitro and in vivo evidence that the switch from calcineurin to mTOR inhibitors may be a strategy for immunosuppression in Epstein-Barr virus-associated post-transplant lymphoproliferative disorder

Post-transplant lymphoproliferative disorder is a life-threatening complication of immunosuppression following transplantation mediated by failure of T cells to control Epstein-Barr virus (EBV)-infected and transformed B cells. Typically, a modification or reduction of immunosuppression is recommended, but insufficiently defined thus far. In order to help delineate this, we characterized EBV-antigen-specific T cells and lymphoblastoid cell lines from healthy donors and in patients with a kidney transplant in the absence or presence of the standard immunosuppressants tacrolimus, cyclosporin A, prednisolone, rapamycin, and mycophenolic acid. Phenotypes of lymphoblastoid cell-lines and T cells, T cell-receptor-repertoire diversity, and T-cell reactivity upon co-culture with autologous lymphoblastoid cell lines were analyzed. Rapamycin and mycophenolic acid inhibited lymphoblastoid cell-line proliferation. T cells treated with prednisolone and rapamycin showed nearly normal cytokine production. Proliferation and the viability of T cells were decreased by mycophenolic acid, while tacrolimus and cyclosporin A were strong suppressors of T-cell function including their killing activity. Overall, our study provides a basis for the clinical decision for the modification and reduction of immunosuppression and adds information to the complex balance of maintaining anti-viral immunity while preventing acute rejection. Thus, an immunosuppressive regime based on mTOR inhibition and reduced or withdrawn calcineurin inhibitors could be a promising strategy for patients with increased risk of or manifested EBV-associated post-transplant lymphoproliferative disorder.

Purpose-Built Immunoinformatics for BcR IG/TR Repertoire Data Analysis

The study of antigen receptor gene repertoires using next-generation sequencing (NGS) technologies has disclosed an unprecedented depth of complexity, requiring novel computational and analytical solutions. Several bioinformatics workflows have been developed to this end, including the T-cell receptor/immunoglobulin profiler (TRIP), a web application implemented in R shiny, specifically designed for the purposes of comprehensive repertoire analysis, which is the focus of this chapter. TRIP has the potential to perform robust immunoprofiling analysis through the extraction and processing of the IMGT/HighV-Quest output, via a series of functions, ensuring the analysis of high-quality, biologically relevant data through a multilevel process of data filtering. Subsequently, it provides in-depth analysis of antigen receptor gene rearrangements, including (a) clonality assessment; (b) extraction of variable (V), diversity (D), and joining (J) gene repertoires; (c) CDR3 characterization at both the nucleotide and amino acid level; and (d) somatic hypermutation analysis, in the case of immunoglobulin gene rearrangements. Relevant to mention, TRIP enables a high level of customization through the integration of various options in key aspects of the analysis, such as clonotype definition and computation, hence allowing for flexibility without compromising on accuracy.

Adaptive Immune Receptor Repertoire (AIRR) Community Guide to TR and IG Gene Annotation

High-throughput sequencing of adaptive immune receptor repertoires (AIRR, i.e., IG and TR) has revolutionized the ability to carry out large-scale experiments to study the adaptive immune response. Since the method was first introduced in 2009, AIRR sequencing (AIRR-Seq) has been applied to survey the immune state of individuals, identify antigen-specific or immune-state-associated signatures of immune responses, study the development of the antibody immune response, and guide the development of vaccines and antibody therapies. Recent advancements in the technology include sequencing at the single-cell level and in parallel with gene expression, which allows the introduction of multi-omics approaches to understand in detail the adaptive immune response. Analyzing AIRR-seq data can prove challenging even with high-quality sequencing, in part due to the many steps involved and the need to parameterize each step. In this chapter, we outline key factors to consider when preprocessing raw AIRR-Seq data and annotating the genetic origins of the rearranged receptors. We also highlight a number of common difficulties with common AIRR-seq data processing and provide strategies to address them.

A Comprehensive Annotation of the Channel Catfish (Ictalurus punctatus) T Cell Receptor Alpha/Delta, Beta, and Gamma Loci

The complete germline repertoires of the channel catfish, Ictalurus punctatus, T cell receptor (TR) loci, TRAD, TRB, and TRG were obtained by analyzing genomic data from PacBio sequencing. The catfish TRB locus spans 214 kb, and contains 112 TRBV genes, a single TRBD gene, 31 TRBJ genes and two TRBC genes. In contrast, the TRAD locus is very large, at 1,285 kb. It consists of four TRDD genes, one TRDJ gene followed by the exons for TRDC, 125 TRAJ genes and the exons encoding the TRAC. Downstream of the TRAC, are 140 TRADV genes, and all of them are in the opposite transcriptional orientation. The catfish TRGC locus spans 151 kb and consists of four diverse V-J-C cassettes. Altogether, this locus contains 15 TRGV genes and 10 TRGJ genes. To place our data into context, we also analyzed the zebrafish TR germline gene repertoires. Overall, our findings demonstrated that catfish possesses a more restricted repertoire compared to the zebrafish. For example, the 140 TRADV genes in catfish form eight subgroups based on members sharing 75% nucleotide identity. However, the 149 TRAD genes in zebrafish form 53 subgroups. This difference in subgroup numbers between catfish and zebrafish is best explained by expansions of catfish TRADV subgroups, which likely occurred through multiple, relatively recent gene duplications. Similarly, 112 catfish TRBV genes form 30 subgroups, while the 51 zebrafish TRBV genes are placed into 36 subgroups. Notably, several catfish and zebrafish TRB subgroups share ancestor nodes. In addition, the complete catfish TR gene annotation was used to compile a TR gene segment database, which was applied in clonotype analysis of an available gynogenetic channel catfish transcriptome. Combined, the TR annotation and clonotype analysis suggested that the expressed TRA, TRB, and TRD repertoires were generated by different mechanisms. The diversity of the TRB repertoire depends on the number of TRBV subgroups and TRBJ genes, while TRA diversity relies on the many different TRAJ genes, which appear to be only minimally trimmed. In contrast, TRD diversity relies on nucleotide additions and the utilization of up to four TRDD segments.

Next Generation Sequencing of Cerebrospinal Fluid B Cell Repertoires in Multiple Sclerosis and Other Neuro-Inflammatory Diseases-A Comprehensive Review

During the last few decades, the role of B cells has been well established and redefined in neuro-inflammatory diseases, including multiple sclerosis and autoantibody-associated diseases. In particular, B cell maturation and trafficking across the blood–brain barrier (BBB) has recently been deciphered with the development of next-generation sequencing (NGS) approaches, which allow the assessment of representative cerebrospinal fluid (CSF) and peripheral blood B cell repertoires. In this review, we perform literature research focusing on NGS studies that allow further insights into B cell pathophysiology during neuro-inflammation. Besides the analysis of CSF B cells, the paralleled assessment of peripheral blood B cell repertoire provides deep insights into not only the CSF compartment, but also in B cell trafficking patterns across the BBB. In multiple sclerosis, CSF-specific B cell maturation, in combination with a bidirectional exchange of B cells across the BBB, is consistently detectable. These data suggest that B cells most likely encounter antigen(s) within the CSF and migrate across the BBB, with further maturation also taking place in the periphery. Autoantibody-mediated diseases, such as neuromyelitis optica spectrum disorder and LGI1 / NMDAR encephalitis, also show features of a CSF-specific B cell maturation and clonal connectivity with peripheral blood. In conclusion, these data suggest an intense exchange of B cells across the BBB, possibly feeding autoimmune circuits. Further developments in sequencing technologies will help to dissect the exact pathophysiologic mechanisms of B cells during neuro-inflammation.

Tools for fundamental analysis functions of TCR repertoires: a systematic comparison

The full set of T cell receptors (TCRs) in an individual is known as his or her TCR repertoire. Defining TCR repertoires under physiological conditions and in response to a disease or vaccine may lead to a better understanding of adaptive immunity and thus has great biological and clinical value. In the past decade, several high-throughput sequencing-based tools have been developed to assign TCRs to germline genes and to extract complementarity-determining region 3 (CDR3) sequences using different algorithms. Although these tools claim to be able to perform the full range of fundamental TCR repertoire analyses, there is no clear consensus of which tool is best suited to particular projects. Here, we present a systematic analysis of 12 available TCR repertoire analysis tools using simulated data, with an emphasis on fundamental analysis functions. Our results shed light on the detailed functions of TCR repertoire analysis tools and may therefore help researchers in the field to choose the right tools for their particular experimental design.

Using DNA sequencing data to quantify T cell fraction and therapy response

The immune microenvironment influences tumour evolution and can be both prognostic and predict response to immunotherapy1,2. However, measurements of tumour infiltrating lymphocytes (TILs) are limited by a shortage of appropriate data. Whole-exome sequencing (WES) of DNA is frequently performed to calculate tumour mutational burden and identify actionable mutations. Here we develop T cell exome TREC tool (T cell ExTRECT), a method for estimation of T cell fraction from WES samples using a signal from T cell receptor excision circle (TREC) loss during V(D)J recombination of the T cell receptor-α gene (TCRA (also known as TRA)). TCRA T cell fraction correlates with orthogonal TIL estimates and is agnostic to sample type. Blood TCRA T cell fraction is higher in females than in males and correlates with both tumour immune infiltrate and presence of bacterial sequencing reads. Tumour TCRA T cell fraction is prognostic in lung adenocarcinoma. Using a meta-analysis of tumours treated with immunotherapy, we show that tumour TCRA T cell fraction predicts immunotherapy response, providing value beyond measuring tumour mutational burden. Applying T cell ExTRECT to a multi-sample pan-cancer cohort reveals a high diversity of the degree of immune infiltration within tumours. Subclonal loss of 12q24.31-32, encompassing SPPL3, is associated with reduced TCRA T cell fraction. T cell ExTRECT provides a cost-effective technique to characterize immune infiltrate alongside somatic changes.

The intratumoral CXCR3 chemokine system is predictive of chemotherapy response in human bladder cancer

Chemotherapy has direct toxic effects on cancer cells; however, long-term cancer control and complete remission are likely to involve CD8⁺ T cell immune responses. To study the role of CD8⁺ T cell infiltration in the success of chemotherapy, we examined patients with muscle invasive bladder cancer (MIBC) who were categorized on the basis of the response to neoadjuvant chemotherapy (NAC). We identified the intratumoral CXCR3 chemokine system (ligands and receptor splice variants) as a critical component for tumor eradication upon NAC in MIBC. Through characterization of CD8⁺ T cells, we found that stem-like T cell subpopulations with abundant CXCR3alt, a variant form of the CXCL11 receptor, responded to CXCL11 in culture as demonstrated by migration and enhanced effector function. In tumor biopsies of patients with MIBC accessed before treatment, CXCL11 abundance correlated with high numbers of tumor-infiltrating T cells and response to NAC. The presence of CXCR3alt and CXCL11 was associated with improved overall survival in MIBC. Evaluation of both CXCR3alt and CXCL11 enabled discrimination between responder and nonresponder patients with MIBC before treatment. We validated the prognostic role of the CXCR3-CXCL11 chemokine system in an independent cohort of chemotherapy-treated and chemotherapy-naïve patients with MIBC from data in TCGA. In summary, our data revealed stimulatory activity of the CXCR3alt-CXCL11 chemokine system on CD8⁺ T cells that is predictive of chemotherapy responsiveness in MIBC. This may offer immunotherapeutic options for targeted activation of intratumoral stem-like T cells in solid tumors.

Phase I/II clinical trial of adoptive cell transfer of sorted specific T cells for metastatic melanoma patients

Adoptive cell transfer (ACT) of tumor-specific T lymphocytes represents a relevant therapeutic strategy to treat metastatic melanoma patients. Ideal T-cells should combine tumor specificity and reactivity with survival in vivo, while avoiding autoimmune side effects. Here we report results from a Phase I/II clinical trial (NCT02424916, performed between 2015 and 2018) in which 6 metastatic HLA-A2 melanoma patients received autologous antigen-specific T-cells produced from PBMC, after peptide stimulation in vitro, followed by sorting with HLA-peptide multimers and amplification. Each patient received a combination of Melan-A and MELOE-1 polyclonal specific T-cells, whose specificity and anti-tumor reactivity were checked prior to injection, with subcutaneous IL-2. Transferred T-cells were also characterized in terms of functional avidity, diversity and phenotype and their blood persistence was evaluated. An increase in specific T-cells was detected in the blood of all patients at day 1 and progressively disappeared from day 7 onwards. No serious adverse events occurred after this ACT. Clinically, five patients progressed and one patient experienced a partial response following therapy. Melan-A and MELOE-1 specific T-cells infused to this patient were diverse, of high avidity, with a high proportion of T lymphocytes co-expressing PD-1 and TIGIT but few other exhaustion markers. In conclusion, we demonstrated the feasibility and safety of ACT with multimer-sorted Melan-A and MELOE-1 specific T cells to metastatic melanoma patients. The clinical efficacy of such therapeutic strategy could be further enhanced by the selection of highly reactive T-cells, based on PD-1 and TIGIT co-expression, and a combination with ICI, such as anti-PD-1.

Rapid T cell receptor interaction grouping with ting

MOTIVATION

Clustering T cell receptor repertoire (TCRR) sequences according to antigen specificity is challenging. The previously published tool GLIPH needs several days to weeks for clustering large repertoires, making its use impractical in larger studies. In addition, the methodology used in GLIPH suffers from shortcomings, including non-determinism, potential loss of significant antigen-specific sequences or inclusion of too many unspecific sequences.

RESULTS

We present an algorithm for clustering TCRR sequences that scales efficiently to large repertoires. We clustered 36 real datasets with up to 62 000 unique CDR3β sequences using both an implementation of our method called ting, GLIPH and its successsor GLIPH2. While GLIPH required multiple weeks, ting only needed about one minute for the same task. GLIPH2 is comparably fast, but uses a different grouping paradigm. In addition, we found that in naïve repertoires, where no or very few antigen-specific CDR3 sequences or clusters should exist, our method indeed selects much fewer motifs and produces smaller clusters.

AVAILABILITY

Our method has been implemented in Python as a tool called ting. It is available from GitHub (https://github.com/FelixMoelder/ting) or PyPI under the MIT license.

Durable Suppression of Acquired MEK Inhibitor Resistance in Cancer by Sequestering MEK from ERK and Promoting Antitumor T-cell Immunity

MAPK targeting in cancer often fails due to MAPK reactivation. MEK inhibitor (MEKi) monotherapy provides limited clinical benefits but may serve as a foundation for combination therapies. Here, we showed that combining a type II RAF inhibitor (RAFi) with an allosteric MEKi durably prevents and overcomes acquired resistance among cancers with KRAS, NRAS, NF1, BRAF non-V600, and BRAF V600 mutations. Tumor cell-intrinsically, type II RAFi plus MEKi sequester MEK in RAF complexes, reduce MEK/MEK dimerization, and uncouple MEK from ERK in acquired-resistant tumor subpopulations. Immunologically, this combination expands memory and activated/exhausted CD8+ T cells, and durable tumor regression elicited by this combination requires CD8+ T cells, which can be reinvigorated by anti-PD-L1 therapy. Whereas MEKi reduces dominant intratumoral T-cell clones, type II RAFi cotreatment reverses this effect and promotes T-cell clonotypic expansion. These findings rationalize the clinical development of type II RAFi plus MEKi and their further combination with PD-1/L1-targeted therapy. SIGNIFICANCE: Type I RAFi + MEKi are indicated only in certain BRAF V600MUT cancers. In contrast, type II RAFi + MEKi are durably active against acquired MEKi resistance across broad cancer indications, which reveals exquisite MAPK addiction. Allosteric modulation of MAPK protein/protein interactions and temporal preservation of intratumoral CD8+ T cells are mechanisms that may be further exploited.This article is highlighted in the In This Issue feature, p. 521.

An ultra-sensitive T-cell receptor detection method for TCR-Seq and RNA-Seq data

MOTIVATION

T-cell receptors (TCRs) function to recognize antigens and play vital roles in T-cell immunology. Surveying TCR repertoires by characterizing complementarity-determining region 3 (CDR3) is a key issue. Due to the high diversity of CDR3 and technological limitation, accurate characterization of CDR3 repertoires remains a great challenge.

RESULTS

We propose a computational method named CATT for ultra-sensitive and precise TCR CDR3 sequences detection. CATT can be applied on TCR sequencing, RNA-Seq and single-cell TCR(RNA)-Seq data to characterize CDR3 repertoires. CATT integrated de Bruijn graph-based micro-assembly algorithm, data-driven error correction model and Bayesian inference algorithm, to self-adaptively and ultra-sensitively characterize CDR3 repertoires with high performance. Benchmark results of datasets from in silico and experimental data demonstrated that CATT showed superior recall and precision compared with existing tools, especially for data with short read length and small size and single-cell sequencing data. Thus, CATT will be a useful tool for TCR analysis in researches of cancer and immunology.

AVAILABILITY AND IMPLEMENTATION

http://bioinfo.life.hust.edu.cn/CATT or https://github.com/GuoBioinfoLab/CATT.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

TCRdb: a comprehensive database for T-cell receptor sequences with powerful search function

T cells and the T-cell receptor (TCR) repertoire play pivotal roles in immune response and immunotherapy. TCR sequencing (TCR-Seq) technology has enabled accurate profiling TCR repertoire and currently a large number of TCR-Seq data are available in public. Based on the urgent need to effectively re-use these data, we developed TCRdb, a comprehensive human TCR sequences database, by a uniform pipeline to characterize TCR sequences on TCR-Seq data. TCRdb contains more than 277 million highly reliable TCR sequences from over 8265 TCR-Seq samples across hundreds of tissues/clinical conditions/cell types. The unique features of TCRdb include: (i) comprehensive and reliable sequences for TCR repertoire in different samples generated by a strict and uniform pipeline of TCRdb; (ii) powerful search function, allowing users to identify their interested TCR sequences in different conditions; (iii) categorized sample metadata, enabling comparison of TCRs in different sample types; (iv) interactive data visualization charts, describing the TCR repertoire in TCR diversity, length distribution and V-J gene utilization. The TCRdb database is freely available at http://bioinfo.life.hust.edu.cn/TCRdb/ and will be a useful resource in the research and application community of T cell immunology.

Tumor-infiltrating mast cells are associated with resistance to anti-PD-1 therapy

Anti-PD-1 therapy is used as a front-line treatment for many cancers, but mechanistic insight into this therapy resistance is still lacking. Here we generate a humanized (Hu)-mouse melanoma model by injecting fetal liver-derived CD34⁺ cells and implanting autologous thymus in immune-deficient NOD-scid IL2Rγ^null (NSG) mice. Reconstituted Hu-mice are challenged with HLA-matched melanomas and treated with anti-PD-1, which results in restricted tumor growth but not complete regression. Tumor RNA-seq, multiplexed imaging and immunohistology staining show high expression of chemokines, as well as recruitment of FOXP3⁺ Treg and mast cells, in selective tumor regions. Reduced HLA-class I expression and CD8⁺/Granz B⁺ T cells homeostasis are observed in tumor regions where FOXP3⁺ Treg and mast cells co-localize, with such features associated with resistance to anti-PD-1 treatment. Combining anti-PD-1 with sunitinib or imatinib results in the depletion of mast cells and complete regression of tumors. Our results thus implicate mast cell depletion for improving the efficacy of anti-PD-1 therapy.

Immune checkpoint therapies (ICT) are promising for treating various cancers, but response rates vary. Here the authors show, in mouse models, that tumor-infiltrating mast cells colocalize with regulatory T cells, coincide with local reduction of MHC-I and CD8 T cells, and is associated with resistance to ICT, which can be reversed by c-kit inhibitor treatment.

SLAMF7 and IL-6R define distinct cytotoxic versus helper memory CD8+ T cells

The prevailing ‘division of labor’ concept in cellular immunity is that CD8⁺ T cells primarily utilize cytotoxic functions to kill target cells, while CD4⁺ T cells exert helper/inducer functions. Multiple subsets of CD4⁺ memory T cells have been characterized by distinct chemokine receptor expression. Here, we demonstrate that analogous CD8⁺ memory T-cell subsets exist, characterized by identical chemokine receptor expression signatures and controlled by similar generic programs. Among them, Tc2, Tc17 and Tc22 cells, in contrast to Tc1 and Tc17 + 1 cells, express IL-6R but not SLAMF7, completely lack cytotoxicity and instead display helper functions including CD40L expression. CD8⁺ helper T cells exhibit a unique TCR repertoire, express genes related to skin resident memory T cells (T_RM) and are altered in the inflammatory skin disease psoriasis. Our findings reveal that the conventional view of CD4⁺ and CD8⁺ T cell capabilities and functions in human health and disease needs to be revised.

We classically consider the T cell compartment divided into cytotoxic CD8⁺ T cells and multiple, different helper CD4⁺ T cell subsets. Here the authors demonstrate that distinct memory CD8⁺ T cell subsets phenotypically inhabit CD4⁺ T cell like populations including some with helper-like characteristics.

TRIP - T cell receptor/immunoglobulin profiler

Background

Antigen receptors are characterized by an extreme diversity of specificities, which poses major computational and analytical challenges, particularly in the era of high-throughput immunoprofiling by next generation sequencing (NGS). The T cell Receptor/Immunoglobulin Profiler (TRIP) tool offers the opportunity for an in-depth analysis based on the processing of the output files of the IMGT/HighV-Quest tool, a standard in NGS immunoprofiling, through a number of interoperable modules. These provide detailed information about antigen receptor gene rearrangements, including variable (V), diversity (D) and joining (J) gene usage, CDR3 amino acid and nucleotide composition and clonality of both T cell receptors (TR) and B cell receptor immunoglobulins (BcR IG), and characteristics of the somatic hypermutation within the BcR IG genes. TRIP is a web application implemented in R shiny.

Results

Two sets of experiments have been performed in order to evaluate the efficiency and performance of the TRIP tool. The first used a number of synthetic datasets, ranging from 250k to 1M sequences, and established the linear response time of the tool (about 6 h for 1M sequences processed through the entire BcR IG data pipeline). The reproducibility of the tool was tested comparing the results produced by the main TRIP workflow with the results from a previous pipeline used on the Galaxy platform. As expected, no significant differences were noted between the two tools; although the preselection process seems to be stricter within the TRIP pipeline, about 0.1% more rearrangements were filtered out, with no impact on the final results.

Conclusions

TRIP is a software framework that provides analytical services on antigen receptor gene sequence data. It is accurate and contains functions for data wrangling, cleaning, analysis and visualization, enabling the user to build a pipeline tailored to their needs. TRIP is publicly available at https://bio.tools/TRIP_-_T-cell_Receptor_Immunoglobulin_Profiler.

Computational approaches to therapeutic antibody design: established methods and emerging trends

Antibodies are proteins that recognize the molecular surfaces of potentially noxious molecules to mount an adaptive immune response or, in the case of autoimmune diseases, molecules that are part of healthy cells and tissues. Due to their binding versatility, antibodies are currently the largest class of biotherapeutics, with five monoclonal antibodies ranked in the top 10 blockbuster drugs. Computational advances in protein modelling and design can have a tangible impact on antibody-based therapeutic development. Antibody-specific computational protocols currently benefit from an increasing volume of data provided by next generation sequencing and application to related drug modalities based on traditional antibodies, such as nanobodies. Here we present a structured overview of available databases, methods and emerging trends in computational antibody analysis and contextualize them towards the engineering of candidate antibody therapeutics.

Detecting pathogenic variants in autoimmune diseases using high-throughput sequencing

Sequencing the first human genome in 2003 took 15 years and cost $2.7 billion. Advances in sequencing technologies have since decreased costs to the point where it is now feasible to resequence a whole human genome for $1000 in a single day. These advances have allowed the generation of huge volumes of high‐quality human sequence data used to construct increasingly large catalogs of both population‐level and disease‐causing variation. The existence of such databases, coupled with a high‐quality human reference genome, means we are able to interrogate and annotate all types of genetic variation and identify pathogenic variants for many diseases. Increasingly, sequencing‐based approaches are being used to elucidate the underlying genetic cause of autoimmune diseases, a group of roughly 80 polygenic diseases characterized by abnormal immune responses where healthy tissue is attacked. Although sequence data generation has become routine and affordable, significant challenges remain with no gold‐standard methodology to identify pathogenic variants currently available. This review examines the latest methodologies used to identify pathogenic variants in autoimmune diseases and considers available sequencing options and subsequent bioinformatic methodologies and strategies. The development of reliable and robust sequencing and analytic workflows to detect pathogenic variants is critical to realize the potential of precision medicine programs where patient variant information is used to inform clinical practice.

VisTCR: An Interactive Software for T Cell Repertoire Sequencing Data Analysis

Recent progress in high throughput sequencing technologies has provided an opportunity to probe T cell receptor (TCR) repertoire, bringing about an explosion of TCR sequencing data and analysis tools. For easier and more heuristic analysis TCR sequencing data, we developed a client-based HTML program (VisTCR). It has a data storage module and a data analysis module that integrate multiple cutting-edge analysis algorithms in a hierarchical fashion. Researchers can group and re-group samples for different analysis purposes by customized "Experiment Design File." Moreover, the VisTCR provides a user-friendly interactive interface, by all the TCR analysis methods and visualization results can be accessed and saved as tables or graphs in the process of analysis. The source code is freely available at https://github.com/qingshanni/VisTCR.

Nuclear antigen-reactive CD4+ T cells expand in active systemic lupus erythematosus, produce effector cytokines, and invade the kidneys

Systemic lupus erythematosus is a systemic and chronic autoimmune disease characterized by loss of tolerance towards nuclear antigens with autoreactive CD4⁺ T cells implicated in disease pathogenesis. However, very little is known about their receptor specificity since the detection of human autoantigen specific CD4⁺ T cells has been extremely challenging. Here we present an analysis of CD4⁺ T cells reactive to nuclear antigens using two complementary methods: T cell libraries and antigen-reactive T cell enrichment. The frequencies of nuclear antigen specific CD4⁺ T cells correlated with disease severity. These autoreactive T cells produce effector cytokines such as interferon-γ, interleukin-17, and interleukin-10. Compared to blood, these cells were enriched in the urine of patients with active lupus nephritis, suggesting an infiltration of the inflamed kidneys. Thus, these previously unrecognized characteristics support a role for nuclear antigen-specific CD4⁺ T cells in systemic lupus erythematosus.

Profiling immunoglobulin repertoires across multiple human tissues using RNA sequencing

Profiling immunoglobulin (Ig) receptor repertoires with specialized assays can be cost-ineffective and time-consuming. Here we report ImReP, a computational method for rapid and accurate profiling of the Ig repertoire, including the complementary-determining region 3 (CDR3), using regular RNA sequencing data such as those from 8,555 samples across 53 tissues types from 544 individuals in the Genotype-Tissue Expression (GTEx v6) project. Using ImReP and GTEx v6 data, we generate a collection of 3.6 million Ig sequences, termed the atlas of immunoglobulin repertoires (TAIR), across a broad range of tissue types that often do not have reported Ig repertoires information. Moreover, the flow of Ig clonotypes and inter-tissue repertoire similarities across immune-related tissues are also evaluated. In summary, TAIR is one of the largest collections of CDR3 sequences and tissue types, and should serve as an important resource for studying immunological diseases.

Information on immune receptor repertoire provides important insights on disease progression and therapy development, but can be expensive and time-consuming to obtain. Here the authors report ImReP, a computational method that can extract detailed immune repertoire information from existing tissue-specific RNA sequencing data.

The Identity Card of T Cells-Clinical Utility of T-cell Receptor Repertoire Analysis in Transplantation

There is a clear medical need to change the current strategy of "one-size-fits-all" immunosuppression for controlling transplant rejection to precision medicine and targeted immune intervention. As T cells play a key role in both undesired graft rejection and protection, a better understanding of the fate and function of both alloreactive graft-deteriorating T cells and those protecting to infections is required. The T-cell receptor (TCR) is the individual identity card of each T cell clone and can help to follow single specificities. In this context, tracking of lymphocytes with certain specificity in blood and tissue in clinical follow up is of especial importance. After overcoming technical limitations of the past, novel molecular technologies opened new avenues of diagnostics. Using advantages of next generation sequencing, a method was established for T-cell tracing by detection of variable TCR region as identifiers of individual lymphocyte clones. The current review describes principles of laboratory and computational methods of TCR repertoire analysis, and gives an overview on applications for the basic understanding of transplant biology and immune monitoring. The review also delineates methodological pitfalls and challenges. With the outlook on prediction of antigens in immune-mediated processes including those of unknown causative pathogens, monitoring the fate and function of individual T cell clones, and the adoptive transfer of protective effector or regulatory T cells, this review highlights the current and future capability of TCR repertoire analysis.

Association between Subcutaneous Adipose Tissue Inflammation, Insulin Resistance, and Calorie Restriction in Obese Females

The worldwide epidemic of overweight and obesity has led to an increase in associated metabolic comorbidities. Obesity induces chronic low-grade inflammation in white adipose tissue (WAT). However, the function and regulation of both innate and adaptive immune cells in human WAT under conditions of obesity and calorie restriction (CR) is not fully understood yet. Using a randomized interventional design, we investigated postmenopausal overweight or obese female subjects who either underwent CR for 3 mo followed by a 4-wk phase of weight maintenance or had to maintain a stable weight over the whole study period. A comprehensive immune phenotyping protocol was conducted using validated multiparameter flow cytometry analysis in blood and s.c. WAT (SAT). The TCR repertoire was analyzed by next-generation sequencing and cytokine levels were determined in SAT. Metabolic parameters were determined by hyperinsulinemic-euglycemic clamp. We found that insulin resistance correlates significantly with a shift toward the memory T cell compartment in SAT. TCR analysis revealed a diverse repertoire in SAT of overweight or obese individuals. Additionally, whereas weight loss improved systemic insulin sensitivity in the intervention group, SAT displayed no significant improvement of inflammatory parameters (cytokine levels and leukocyte subpopulations) compared with the control group. Our data demonstrate the accumulation of effector memory T cells in obese SAT and an association between systemic glucose homeostasis and inflammatory parameters in obese females. The long-standing effect of obesity-induced changes in SAT was demonstrated by preserved immune cell composition after short-term CR-induced weight loss.

Molecular T-Cell Repertoire Analysis as Source of Prognostic and Predictive Biomarkers for Checkpoint Blockade Immunotherapy

The T cells are key players of the response to checkpoint blockade immunotherapy (CBI) and monitoring the strength and specificity of antitumor T-cell reactivity remains a crucial but elusive component of precision immunotherapy. The entire assembly of T-cell receptor (TCR) sequences accounts for antigen specificity and strength of the T-cell immune response. The TCR repertoire hence represents a “footprint” of the conditions faced by T cells that dynamically evolves according to the challenges that arise for the immune system, such as tumor neo-antigenic load. Hence, TCR repertoire analysis is becoming increasingly important to comprehensively understand the nature of a successful antitumor T-cell response, and to improve the success and safety of current CBI.

Adaptive immune receptor repertoires, an overview of this exciting field

The adaptive immune response in jawed vertebrates relies on the huge diversity and specificity of the B cell and T cell antigen receptors, the immunoglobulins (IG) or antibodies and the T cell receptors (TR), respectively. The high level of diversity has represented a barrier to a comprehensive analysis of the adaptive immune response before the emergence of high-throughput sequencing (HTS) technologies. The size and complexity of HTS data requires the generation of novel computational and analytical approaches, which are transforming how the adaptive immune responses are deciphered to understand the clonal dynamics and properties of antigen-specific B and T cells in response to different kind of antigens. This exciting and rapidly evolving field is not only impacting human and clinical immunology but also comparative immunology. We are now closer to understanding the evolution of adaptive immune response in jawed vertebrates. This review provides an overview about classical and current strategies developed to assess the IG/TR diversity and their applications in basic and clinical immunology.

Systematic comparative study of computational methods for T-cell receptor sequencing data analysis

High-throughput sequencing technologies have exposed the possibilities for the in-depth evaluation of T-cell receptor (TCR) repertoires. These studies are highly relevant to gain insights into human adaptive immunity and to decipher the composition and diversity of antigen receptors in physiological and disease conditions. The major objective of TCR sequencing data analysis is the identification of V, D and J gene segments, complementarity-determining region 3 (CDR3) sequence extraction and clonality analysis. With the advancement in sequencing technologies, new TCR analysis approaches and programs have been developed. However, there is still a deficit of systematic comparative studies to assist in the selection of an optimal analysis approach. Here, we present a detailed comparison of 10 state-of-the-art TCR analysis tools on samples with different complexities by taking into account many aspects such as clonotype detection [unique V(D)J combination], CDR3 identification or accuracy in error correction. We used our in silico and experimental data sets with known clonalities enabling the identification of potential tool biases. We also established a new strategy, named clonal plane, which allows quantifying and comparing the clonality of multiple samples. Our results provide new insights into the effect of method selection on analysis results, and it will assist users in the selection of an appropriate analysis method.

Bioinformatic methods for cancer neoantigen prediction

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

Killer-like receptors and GPR56 progressive expression defines cytokine production of human CD4+ memory T cells

All memory T cells mount an accelerated response on antigen reencounter, but significant functional heterogeneity is present within the respective memory T-cell subsets as defined by CCR7 and CD45RA expression, thereby warranting further stratification. Here we show that several surface markers, including KLRB1, KLRG1, GPR56, and KLRF1, help define low, high, or exhausted cytokine producers within human peripheral and intrahepatic CD4⁺ memory T-cell populations. Highest simultaneous production of TNF and IFN-γ is observed in KLRB1⁺KLRG1⁺GPR56⁺ CD4 T cells. By contrast, KLRF1 expression is associated with T-cell exhaustion and reduced TNF/IFN-γ production. Lastly, TCRβ repertoire analysis and in vitro differentiation support a regulated, progressive expression for these markers during CD4⁺ memory T-cell differentiation. Our results thus help refine the classification of human memory T cells to provide insights on inflammatory disease progression and immunotherapy development.

Despite the current human CD4 memory T cell stratification by CD45RA/CCR7, functional heterogeneities still exist within the respective subsets. Here the authors show that several surface markers, including KLRB1, KLRG1, GPR56 and KLRF1, help to further refine the subsetting of human CD4 memory T cells and provide insights for their differentiation.

The Pipeline Repertoire for Ig-Seq Analysis

With the advent of high-throughput sequencing of immunoglobulin genes (Ig-Seq), the understanding of antibody repertoires and their dynamics among individuals and populations has become an exciting area of research. There is an increasing number of computational tools that aid in every step of the immune repertoire characterization. However, since not all tools function identically, every pipeline has its unique rationale and capabilities, creating a rich blend of useful features that may appear intimidating for newcomer laboratories with the desire to plunge into immune repertoire analysis to expand and improve their research; hence, all pipeline strengths and differences may not seem evident. In this review we provide a practical and organized list of the current set of computational tools, focusing on their most attractive features and differences in order to carry out the characterization of antibody repertoires so that the reader better decides a strategic approach for the experimental design, and computational pathways for the analyses of immune repertoires.

BKV Clearance Time Correlates With Exhaustion State and T-Cell Receptor Repertoire Shape of BKV-Specific T-Cells in Renal Transplant Patients

Reactivation of the BK polyomavirus is known to lead to severe complications in kidney transplant patients. The current treatment strategy relies on decreasing the immunosuppression to allow the immune system to clear the virus. Recently, we demonstrated a clear association between the resolution of BKV reactivation and reconstitution of BKV-specific CD4⁺ T-cells. However, which factors determine the duration of viral infection clearance remains so far unclear. Here we apply a combination of in-depth multi-parametric flow cytometry and NGS-based CDR3 beta chain receptor repertoire analysis of BKV-specific T-cells to a cohort of 7 kidney transplant patients during the clinical course of BKV reactivation. This way we followed TCR repertoires at single clone levels and functional activity of BKV-specific T-cells during the resolution of BKV infection. The duration of BKV clearance did not depend on the number of peripheral blood BKV-specific T-cells nor on a few immunodominant BKV-specific T-cell clones. Rather, the T-cell receptor repertoire diversity and exhaustion status of BKV-specific T-cells affected the duration of viral clearance: high clonotype diversity and lack of PD1 and TIM3 exhaustion markers on BKV-specific T-cells was associated with short clearance time. Our data thus demonstrate how the diversity and the exhaustion state of the T-cells can determine the clinical course of BKV infection.

The Role of Pre-existing Cross-Reactive Central Memory CD4 T-Cells in Vaccination With Previously Unseen Influenza Strains

Influenza vaccination is a common approach to prevent seasonal and pandemic influenza. Pre-existing antibodies against close viral strains might impair antibody formation against previously unseen strains-a process called original antigenic sin. The role of this pre-existing cellular immunity in this process is, despite some hints from animal models, not clear. Here, we analyzed cellular and humoral immunity in healthy individuals before and after vaccination with seasonal influenza vaccine. Based on influenza-specific hemagglutination inhibiting (HI) titers, vaccinees were grouped into HI-negative and -positive cohorts followed by in-depth cytometric and TCR repertoire analysis. Both serological groups revealed cross-reactive T-cell memory to the vaccine strains at baseline that gave rise to the majority of vaccine-specific T-cells post vaccination. On the contrary, very limited number of vaccine-specific T-cell clones was recruited from the naive pool. Furthermore, baseline quantity of vaccine-specific central memory helper T-cells and clonotype richness of this population directly correlated with the vaccination efficacy. Our findings suggest that the deliberate recruitment of pre-existing cross-reactive cellular memory might help to improve vaccination outcome.

Diagnosis of fusion genes using targeted RNA sequencing

Fusion genes are a major cause of cancer. Their rapid and accurate diagnosis can inform clinical action, but current molecular diagnostic assays are restricted in resolution and throughput. Here, we show that targeted RNA sequencing (RNAseq) can overcome these limitations. First, we establish that fusion gene detection with targeted RNAseq is both sensitive and quantitative by optimising laboratory and bioinformatic variables using spike-in standards and cell lines. Next, we analyse a clinical patient cohort and improve the overall fusion gene diagnostic rate from 63% with conventional approaches to 76% with targeted RNAseq while demonstrating high concordance for patient samples with previous diagnoses. Finally, we show that targeted RNAseq offers additional advantages by simultaneously measuring gene expression levels and profiling the immune-receptor repertoire. We anticipate that targeted RNAseq will improve clinical fusion gene detection, and its increasing use will provide a deeper understanding of fusion gene biology.

Rapid and accurate detection of fusion genes is important in cancer diagnostics. Here, the authors demonstrate that targeted RNA sequencing provides fast, sensitive and quantitative gene fusion detection and overcomes the limitations of approaches currently in clinical use.

Human Anti-fungal Th17 Immunity and Pathology Rely on Cross-Reactivity against Candida albicans

Th17 cells provide protection at barrier tissues but may also contribute to immune pathology. The relevance and induction mechanisms of pathologic Th17 responses in humans are poorly understood. Here, we identify the mucocutaneous pathobiont Candida albicans as the major direct inducer of human anti-fungal Th17 cells. Th17 cells directed against other fungi are induced by cross-reactivity to C. albicans. Intestinal inflammation expands total C. albicans and cross-reactive Th17 cells. Strikingly, Th17 cells cross-reactive to the airborne fungus Aspergillus fumigatus are selectively activated and expanded in patients with airway inflammation, especially during acute allergic bronchopulmonary aspergillosis. This indicates a direct link between protective intestinal Th17 responses against C. albicans and lung inflammation caused by airborne fungi. We identify heterologous immunity to a single, ubiquitous member of the microbiota as a central mechanism for systemic induction of human anti-fungal Th17 responses and as a potential risk factor for pulmonary inflammatory diseases.

Filtering Next-Generation Sequencing of the Ig Gene Repertoire Data Using Antibody Structural Information

Next-generation sequencing of the Ig gene repertoire (Ig-seq) produces large volumes of information at the nucleotide sequence level. Such data have improved our understanding of immune systems across numerous species and have already been successfully applied in vaccine development and drug discovery. However, the high-throughput nature of Ig-seq means that it is afflicted by high error rates. This has led to the development of error-correction approaches. Computational error-correction methods use sequence information alone, primarily designating sequences as likely to be correct if they are observed frequently. In this work, we describe an orthogonal method for filtering Ig-seq data, which considers the structural viability of each sequence. A typical natural Ab structure requires the presence of a disulfide bridge within each of its variable chains to maintain the fold. Our Ab Sequence Selector (ABOSS) uses the presence/absence of this bridge as a way of both identifying structurally viable sequences and estimating the sequencing error rate. On simulated Ig-seq datasets, ABOSS is able to identify more than 99% of structurally viable sequences. Applying our method to six independent Ig-seq datasets (one mouse and five human), we show that our error calculations are in line with previous experimental and computational error estimates. We also show how ABOSS is able to identify structurally impossible sequences missed by other error-correction methods.

TCR Analyses of Two Vast and Shared Melanoma Antigen-Specific T Cell Repertoires: Common and Specific Features

Among Immunotherapeutic approaches for cancer treatment, the adoptive transfer of antigen specific T cells is still a relevant approach, that could have higher efficacy when further combined with immune check-point blockade. A high number of adoptive transfer trials have been performed in metastatic melanoma, due to its high immunogenic potential, either with polyclonal TIL or antigen-specific polyclonal populations. In this setting, the extensive characterization of T cell functions and receptor diversity of infused polyclonal T cells is required, notably for monitoring purposes. We developed a clinical grade procedure for the selection and amplification of polyclonal CD8 T cells, specific for two shared and widely expressed melanoma antigens: Melan-A and MELOE-1. This procedure is currently used in a clinical trial for HLA-A2 metastatic melanoma patients. In this study, we characterized the T-cell diversity (T-cell repertoire) of such T cell populations using a new RNAseq strategy. We first assessed the added-value of TCR receptor sequencing, in terms of sensitivity and specificity, by direct comparison with cytometry analysis of the T cell populations labeled with anti-Vß-specific antibodies. Results from these analyzes also confirmed specific features already reported for Melan-A and MELOE-1 specific T cell repertoires in terms of V-alpha recurrence usage, on a very high number of T cell clonotypes. Furthermore, these analyses also revealed undescribed features, such as the recurrence of a specific motif in the CDR3α region for MELOE-1 specific T cell repertoire. Finally, the analysis of a large number of T cell clonotypes originating from various patients revealed the existence of public CDR3α and ß clonotypes for Melan-A and MELOE-1 specific T cells. In conclusion, this method of high throughput TCR sequencing is a reliable and powerful approach to deeply characterize polyclonal T cell repertoires, and to reveal specific features of a given TCR repertoire, that would be useful for immune follow-up of cancer patients treated by immunotherapeutic approaches.

High-throughput sequencing of the T-cell receptor repertoire: pitfalls and opportunities

T-cell specificity is determined by the T-cell receptor, a heterodimeric protein coded for by an extremely diverse set of genes produced by imprecise somatic gene recombination. Massively parallel high-throughput sequencing allows millions of different T-cell receptor genes to be characterized from a single sample of blood or tissue. However, the extraordinary heterogeneity of the immune repertoire poses significant challenges for subsequent analysis of the data. We outline the major steps in processing of repertoire data, considering low-level processing of raw sequence files and high-level algorithms, which seek to extract biological or pathological information. The latest generation of bioinformatics tools allows millions of DNA sequences to be accurately and rapidly assigned to their respective variable V and J gene segments, and to reconstruct an almost error-free representation of the non-templated additions and deletions that occur. High-level processing can measure the diversity of the repertoire in different samples, quantify V and J usage and identify private and public T-cell receptors. Finally, we discuss the major challenge of linking T-cell receptor sequence to function, and specifically to antigen recognition. Sophisticated machine learning algorithms are being developed that can combine the paradoxical degeneracy and cross-reactivity of individual T-cell receptors with the specificity of the overall T-cell immune response. Computational analysis will provide the key to unlock the potential of the T-cell receptor repertoire to give insight into the fundamental biology of the adaptive immune system and to provide powerful biomarkers of disease.

IRProfiler - a software toolbox for high throughput immune receptor profiling

Background

The study of the huge diversity of immune receptors, often referred to as immune repertoire profiling, is a prerequisite for diagnosis, prognostication and monitoring of hematological disorders. In the era of high-throughput sequencing (HTS), the abundance of immunogenetic data has revealed unprecedented opportunities for the thorough profiling of T-cell receptors (TR) and B-cell receptors (BcR). However, the volume of the data to be analyzed mandates for efficient and ease-to-use immune repertoire profiling software applications.

Results

This work introduces Immune Repertoire Profiler (IRProfiler), a novel software pipeline that delivers a number of core receptor repertoire quantification and comparison functionalities on high-throughput TR and BcR sequencing data. Adopting 5 alternative clonotype definitions, IRProfiler implements a series of algorithms for 1) data filtering, 2) calculation of clonotype diversity and expression, 3) calculation of gene usage for the V and J subgroups, 4) detection of shared and exclusive clonotypes among multiple repertoires, and 5) comparison of gene usage for V and J subgroups among multiple repertoires. IRProfiler has been implemented as a toolbox of the Galaxy bioinformatics platform, comprising 6 tools. Theoretical and experimental evaluation has shown that the tools of IRProfiler are able to scale well with respect to the size of input dataset(s). IRProfiler has been utilized by a number of recently published studies concerning hematological disorders.

Conclusion

IRProfiler is made freely available via 3 distribution channels, including the Galaxy Tool Shed. Despite being a new entry in a crowded ecosystem of immune repertoire profiling software, IRProfiler founds its added value on its support for alternative clonotype definitions in conjunction with a combination of properties stemming from its user-centric design, namely ease-of-use, ease-of-access, exploitability of the output data, and analysis flexibility.

Baseline IL-2 and the AIH score can predict the response to standard therapy in paediatric autoimmune hepatitis

Although autoimmune hepatitis (AIH) can be treated with corticosteroid-based first-line therapy, incomplete remission is associated with progressive liver fibrosis. So far accepted predictors of the subsequent treatment response of AIH patients are lacking. Therefore, we analysed baseline parameters, including iron homeostasis and cytokine levels, in 60 children with paediatric AIH (pAIH). In contrast to adults, elevated serum markers indicating iron overload were not commonly found in children. Therefore, ferritin was not predictive of the treatment response in pAIH. Although baseline immunoglobulins were lower in pAIH children with subsequent complete biochemical remission (BR) upon standard first-line therapy, only lower AIH scores (≤16 points) could predict BR upon standard therapy in our training and validation cohorts. Additionally, higher baseline IL-2 and MCP-1/CCL2 levels were associated with BR in a sub-cohort. A combined score of IL-2 level and a simplified AIH score predicted treatment response more precisely than both parameter alone in this sub-cohort. In conclusion, the baseline AIH score could be validated as a predictor of treatment response in pAIH. Additionally, low baseline IL-2 may help identify children who need salvage therapy. This could be important because the use of low-dose IL-2 therapies is being tested in various autoimmune diseases.

VDJPipe: a pipelined tool for pre-processing immune repertoire sequencing data

Background

Pre-processing of high-throughput sequencing data for immune repertoire profiling is essential to insure high quality input for downstream analysis. VDJPipe is a flexible, high-performance tool that can perform multiple pre-processing tasks with just a single pass over the data files.

Results

Processing tasks provided by VDJPipe include base composition statistics calculation, read quality statistics calculation, quality filtering, homopolymer filtering, length and nucleotide filtering, paired-read merging, barcode demultiplexing, 5′ and 3′ PCR primer matching, and duplicate reads collapsing. VDJPipe utilizes a pipeline approach whereby multiple processing steps are performed in a sequential workflow, with the output of each step passed as input to the next step automatically. The workflow is flexible enough to handle the complex barcoding schemes used in many immunosequencing experiments. Because VDJPipe is designed for computational efficiency, we evaluated this by comparing execution times with those of pRESTO, a widely-used pre-processing tool for immune repertoire sequencing data. We found that VDJPipe requires <10% of the run time required by pRESTO.

Conclusions

VDJPipe is a high-performance tool that is optimized for pre-processing large immune repertoire sequencing data sets.

T Cell Receptor Profiling in Type 1 Diabetes

PURPOSE OF REVIEW

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

RECENT FINDINGS

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

Reconstructing Antibody Repertoires from Error-Prone Immunosequencing Reads

Transforming error-prone immunosequencing datasets into Ab repertoires is a fundamental problem in immunogenomics, and a prerequisite for studies of immune responses. Although various repertoire reconstruction algorithms were released in the last 3 y, it remains unclear how to benchmark them and how to assess the accuracy of the reconstructed repertoires. We describe an accurate IgReC algorithm for constructing Ab repertoires from high-throughput immunosequencing datasets and a new framework for assessing the quality of reconstructed repertoires. Surprisingly, Ab repertoires constructed by IgReC from barcoded immunosequencing datasets in the blind mode (without using information about unique molecular identifiers) improved upon the repertoires constructed by the state-of-the-art tools that use barcoding. This finding suggests that IgReC may alleviate the need to generate repertoires using the barcoding technology (the workhorse of current immunogenomics efforts) because our computational approach to error correction of immunosequencing data is nearly as powerful as the experimental approach based on barcoding.