Characterization of CD8+ T cells in immune-privileged organs of ZIKV-infected Ifnar1-/- mice

Zika virus (ZIKV) infection caused neurological complications and male infertility, leading to the accumulation of antigen-specific immune cells in immune-privileged organs (IPOs). Thus, it is important to understand the immunological responses to ZIKV in IPOs. We extensively investigated the ZIKV-specific T cell immunity in IPOs in Ifnar1-/- mice, based on an immunodominant epitope E294-302 tetramer. The distinct kinetics and functions of virus-specific CD8+ T cells infiltrated into different IPOs were characterized, with late elevation in the brain and spinal cord. Single epitope E294-302-specific T cells can account for 20-60% of the total CD8+ T cells in the brain, spinal cord, and testicle and persist for at least 90 days in the brain and spinal cord. The E294-302-specific TCRαβs within the IPOs are featured with the majority of clonotypes utilizing TRAV9N-3 paired with diverse TRBV chains, but with distinct αβ paired clonotypes in 7 and 30 days post-infection. Specific chemokine receptors, Ccr2 and Ccr5, were selectively expressed in the E294-302-specific CD8+ T cells within the brain and testicle, indicating an IPO-oriented migration of virus-specific CD8+ T cells after infection. Overall, this study adds to the understanding of virus-specific CD8+ T cell responses for controlling and clearing ZIKV infection in IPOs.IMPORTANCEThe immune-privileged organs (IPOs), such as the central nervous system and testicles, presented pathogenicity and inflammation after Zika virus (ZIKV) infection with infiltrated CD8+ T cells. Our data show that CD8+ T cells keep up with virus increases and decreases in immune-privileged organs. Furthermore, our study provides the first ex vivo comparative analyses of the composition and diversity related to TCRα/β clonotypes across anatomical sites and ZIKV infection phases. We show that the vast majority of TCRα/β clonotypes in tissues utilize TRAV9N-3 with conservation. Specific chemokine expression, including Ccr2 and Ccr5, was found to be selectively expressed in the E294-302-specific CD8+ T cells within the brain and testicle, indicating an IPO-oriented migration of the virus-specific CD8+ T cells after the infection. Our study adds insights into the anti-viral immunological characterization and chemotaxis mechanism of virus-specific CD8+ T cells after ZIKV infection in different IPOs.

A virtual memory CD8+ T cell-originated subset causes alopecia areata through innate-like cytotoxicity

Virtual memory T (TVM) cells are a T cell subtype with a memory phenotype but no prior exposure to foreign antigen. Although TVM cells have antiviral and antibacterial functions, whether these cells can be pathogenic effectors of inflammatory disease is unclear. Here we identified a TVM cell-originated CD44super-high(s-hi)CD49dlo CD8+ T cell subset with features of tissue residency. These cells are transcriptionally, phenotypically and functionally distinct from conventional CD8+ TVM cells and can cause alopecia areata. Mechanistically, CD44s-hiCD49dlo CD8+ T cells could be induced from conventional TVM cells by interleukin (IL)-12, IL-15 and IL-18 stimulation. Pathogenic activity of CD44s-hiCD49dlo CD8+ T cells was mediated by NKG2D-dependent innate-like cytotoxicity, which was further augmented by IL-15 stimulation and triggered disease onset. Collectively, these data suggest an immunological mechanism through which TVM cells can cause chronic inflammatory disease by innate-like cytotoxicity.

I-Ag7 β56/57 polymorphisms regulate non-cognate negative selection to CD4+ T cell orchestrators of type 1 diabetes

Genetic susceptibility to type 1 diabetes is associated with homozygous expression of major histocompatibility complex class II alleles that carry specific beta chain polymorphisms. Why heterozygous expression of these major histocompatibility complex class II alleles does not confer a similar predisposition is unresolved. Using a nonobese diabetic mouse model, here we show that heterozygous expression of the type 1 diabetes-protective allele I-Ag7 β56P/57D induces negative selection to the I-Ag7-restricted T cell repertoire, including beta-islet-specific CD4+ T cells. Surprisingly, negative selection occurs despite I-Ag7 β56P/57D having a reduced ability to present beta-islet antigens to CD4+ T cells. Peripheral manifestations of non-cognate negative selection include a near complete loss of beta-islet-specific CXCR6+ CD4+ T cells, an inability to cross-prime islet-specific glucose-6-phosphatase catalytic subunit-related protein and insulin-specific CD8+ T cells and disease arrest at the insulitis stage. These data reveal that negative selection on non-cognate self-antigens in the thymus can promote T cell tolerance and protection from autoimmunity.

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.

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.

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.

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.

Partial recovery of disturbed V-J pairing profiles of T-cell receptor in people living with HIV receiving long-term antiretroviral therapy

Chronic human immunodeficiency virus (HIV) infection not only causes a gradual loss of CD4⁺ T cells but also leads to a disturbance of the T cell receptor (TCR) repertoire. In people living with HIV (PLWH), monitoring TCR repertoire is challenged by the inconsistency of complementarity determining region 3 (CDR3) and limited cell numbers in clinical samples. Thus, a quantitative method is necessary for monitoring the TCR repertoire in PLWH. We characterized the TCR V-J pairing profile of naïve and memory CD4⁺ T cells in healthy donors, HIV-infected antiretroviral therapy (ART)-naïve patients and long-term (over 5 years) ART-experienced patients by performing TCR sequencing. We developed a V-J index with 18 parameters which were subdivided into five categories (expression coverage, cumulative percentage of the top tenth percentile, diversity, intra-individual similarity and inter-individual similarity). In ART-naïve patients, 14 of the 18 parameters were significantly altered. Long-term ART recovered ten parameters. The four unrecovered parameters were related to inter-individual similarity. Therefore, these findings indicate that long-term ART could only partially recover TCR V-J pairs and introduce newly impacted V-J pairs. Moreover, these results provide new insights into the V-J pairing of the TCR and into the disturbance of TCR repertoire in HIV infection.

Myocardial infarction triggers cardioprotective antigen-specific T helper cell responses

T cell autoreactivity is a hallmark of autoimmune diseases but can also benefit self-maintenance and foster tissue repair. Herein, we investigated whether heart-specific T cells exert salutary or detrimental effects in the context of myocardial infarction (MI), the leading cause of death worldwide. After screening more than 150 class-II-restricted epitopes, we found that myosin heavy chain alpha (MYHCA) was a dominant cardiac antigen triggering post-MI CD4+ T cell activation in mice. Transferred MYHCA614-629-specific CD4+ T (TCR-M) cells selectively accumulated in the myocardium and mediastinal lymph nodes (med-LN) of infarcted mice, acquired a Treg phenotype with a distinct pro-healing gene expression profile, and mediated cardioprotection. Myocardial Treg cells were also detected in autopsies from patients who suffered a MI. Noninvasive PET/CT imaging using a CXCR4 radioligand revealed enlarged med-LNs with increased cellularity in MI-patients. Notably, the med-LN alterations observed in MI patients correlated with the infarct size and cardiac function. Taken together, the results obtained in our study provide evidence showing that MI-context induces pro-healing T cell autoimmunity in mice and confirms the existence of an analogous heart/med-LN/T cell axis in MI patients.

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.

A temporal thymic selection switch and ligand binding kinetics constrain neonatal Foxp3+ Treg cell development

The neonatal thymus generates Foxp3⁺ regulatory T (tT_reg) cells that are critical in controlling immune homeostasis and preventing multiorgan autoimmunity. The role of antigen specificity on neonatal tT_reg cell selection is unresolved. Here we identify 17 self-peptides recognized by neonatal tT_reg cells, and reveal ligand specificity patterns that include self-antigens presented in an age- and inflammation-dependent manner. Fate-mapping studies of neonatal peptidyl arginine deiminase type IV (Padi4)-specific thymocytes reveal disparate fate choices. Neonatal thymocytes expressing T cell receptors that engage IA^b-Padi4 with moderate dwell times within a conventional docking orientation are exported as tT_reg cells. In contrast, Padi4-specific T cell receptors with short dwell times are expressed on CD4⁺ T cells, while long dwell times induce negative selection. Temporally, Padi4-specific thymocytes are subject to a developmental stage-specific change in negative selection, which precludes tT_reg cell development. Thus, a temporal switch in negative selection and ligand binding kinetics constrains the neonatal tT_reg selection window.

Evaluation of the capacities of mouse TCR profiling from short read RNA-seq data

Profiling T cell receptor (TCR) repertoire via short read transcriptome sequencing (RNA-Seq) has a unique advantage of probing simultaneously TCRs and the genome-wide RNA expression of other genes. However, compared to targeted amplicon approaches, the shorter read length is more prone to mapping error. In addition, only a small percentage of the genome-wide reads may cover the TCR loci and thus the repertoire could be significantly under-sampled. Although this approach has been applied in a few studies, the utility of transcriptome sequencing in probing TCR repertoires has not been evaluated extensively. Here we present a systematic assessment of RNA-Seq in TCR profiling. We evaluate the power of both Fluidigm C1 full-length single cell RNA-Seq and bulk RNA-Seq in characterizing the repertoires of different diversities under either naïve conditions or after immunogenic challenges. Standard read length and sequencing coverage were employed so that the evaluation was conducted in accord with the current RNA-Seq practices. Despite high sequencing depth in bulk RNA-Seq, we encountered difficulty quantifying TCRs with low transcript abundance (<1%). Nevertheless, top enriched TCRs with an abundance of 1–3% or higher can be faithfully detected and quantified. When top TCR sequences are of interest and transcriptome sequencing is available, it is worthwhile to conduct a TCR profiling using the RNA-Seq data.

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.

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.

High-throughput sequencing in acute lymphoblastic leukemia: Follow-up of minimal residual disease and emergence of new clones

Minimal residual disease (MRD) is known to be an independent prognostic factor in patients with acute lymphoblastic leukemia (ALL). High-throughput sequencing (HTS) is currently used in routine practice for the diagnosis and follow-up of patients with hematological neoplasms. In this retrospective study, we examined the role of immunoglobulin/T-cell receptor-based MRD in patients with ALL by HTS analysis of immunoglobulin H and/or T-cell receptor gamma chain loci in bone marrow samples from 11 patients with ALL, at diagnosis and during follow-up. We assessed the clinical feasibility of using combined HTS and bioinformatics analysis with interactive visualization using Vidjil software. We discuss the advantages and drawbacks of HTS for monitoring MRD. HTS gives a more complete insight of the leukemic population than conventional real-time quantitative PCR (qPCR), and allows identification of new emerging clones at each time point of the monitoring. Thus, HTS monitoring of Ig/TR based MRD is expected to improve the management of patients with ALL.

Vidjil: A Web Platform for Analysis of High-Throughput Repertoire Sequencing

BACKGROUND

The B and T lymphocytes are white blood cells playing a key role in the adaptive immunity. A part of their DNA, called the V(D)J recombinations, is specific to each lymphocyte, and enables recognition of specific antigenes. Today, with new sequencing techniques, one can get billions of DNA sequences from these regions. With dedicated Repertoire Sequencing (RepSeq) methods, it is now possible to picture population of lymphocytes, and to monitor more accurately the immune response as well as pathologies such as leukemia.

METHODS AND RESULTS

Vidjil is an open-source platform for the interactive analysis of high-throughput sequencing data from lymphocyte recombinations. It contains an algorithm gathering reads into clonotypes according to their V(D)J junctions, a web application made of a sample, experiment and patient database and a visualization for the analysis of clonotypes along the time. Vidjil is implemented in C++, Python and Javascript and licensed under the GPLv3 open-source license. Source code, binaries and a public web server are available at http://www.vidjil.org and at http://bioinfo.lille.inria.fr/vidjil. Using the Vidjil web application consists of four steps: 1. uploading a raw sequence file (typically a FASTQ); 2. running RepSeq analysis software; 3. visualizing the results; 4. annotating the results and saving them for future use. For the end-user, the Vidjil web application needs no specific installation and just requires a connection and a modern web browser. Vidjil is used by labs in hematology or immunology for research and clinical applications.

Affinity for self antigen selects Treg cells with distinct functional properties

The manner in which regulatory T cells (Treg cells) control lymphocyte homeostasis is not fully understood. We identified two Treg cell populations with differing degrees of self-reactivity and distinct regulatory functions. We found that GITR(hi)PD-1(hi)CD25(hi) (Triple(hi)) Treg cells were highly self-reactive and controlled lympho-proliferation in peripheral lymph nodes. GITR(lo)PD-1(lo)CD25(lo) (Triple(lo)) Treg cells were less self-reactive and limited the development of colitis by promoting the conversion of CD4(+) Tconv cells into induced Treg cells (iTreg cells). Although Foxp3-deficient (Scurfy) mice lacked Treg cells, they contained Triple(hi)-like and Triple(lo)-like CD4(+) T cells zsuper> T cells infiltrated the skin, whereas Scurfy Triple(lo)CD4(+) T cells induced colitis and wasting disease. These findings indicate that the affinity of the T cell antigen receptor for self antigen drives the differentiation of Treg cells into distinct subsets with non-overlapping regulatory activities.

Hydrophobic CDR3 residues promote the development of self-reactive T cells

Studies of individual T cell antigen receptors (TCRs) have shed some light on structural features that underlie self-reactivity. However, the general rules that can be used to predict whether TCRs are self-reactive have not been fully elucidated. Here we found that the interfacial hydrophobicity of amino acids at positions 6 and 7 of the complementarity-determining region CDR3β robustly promoted the development of self-reactive TCRs. This property was found irrespective of the member of the β-chain variable region (Vβ) family present in the TCR or the length of the CDR3β. An index based on these findings distinguished Vβ2(+), Vβ6(+) and Vβ8.2(+) regulatory T cells from conventional T cells and also distinguished CD4(+) T cells selected by the major histocompatibility complex (MHC) class II molecule I-A(g7) (associated with the development of type 1 diabetes in NOD mice) from those selected by a non-autoimmunity-promoting MHC class II molecule I-A(b). Our results provide a means for distinguishing normal T cell repertoires versus autoimmunity-prone T cell repertoires.

RTCR: a pipeline for complete and accurate recovery of T cell repertoires from high throughput sequencing data

Motivation: High Throughput Sequencing (HTS) has enabled researchers to probe the human T cell receptor (TCR) repertoire, which consists of many rare sequences. Distinguishing between true but rare TCR sequences and variants generated by polymerase chain reaction (PCR) and sequencing errors remains a formidable challenge. The conventional approach to handle errors is to remove low quality reads, and/or rare TCR sequences. Such filtering discards a large number of true and often rare TCR sequences. However, accurate identification and quantification of rare TCR sequences is essential for repertoire diversity estimation.

Results: We devised a pipeline, called Recover TCR (RTCR), that accurately recovers TCR sequences, including rare TCR sequences, from HTS data (including barcoded data) even at low coverage. RTCR employs a data-driven statistical model to rectify PCR and sequencing errors in an adaptive manner. Using simulations, we demonstrate that RTCR can easily adapt to the error profiles of different types of sequencers and exhibits consistently high recall and high precision even at low coverages where other pipelines perform poorly. Using published real data, we show that RTCR accurately resolves sequencing errors and outperforms all other pipelines.

Availability and Implementation: The RTCR pipeline is implemented in Python (v2.7) and C and is freely available at http://uubram.github.io/RTCR/along with documentation and examples of typical usage.

Contact:b.gerritsen@uu.nl

T cell fate and clonality inference from single-cell transcriptomes

We developed TraCeR, a computational method to reconstruct full-length, paired T cell receptor (TCR) sequences from T lymphocyte single-cell RNA sequence data. TraCeR links T cell specificity with functional response by revealing clonal relationships between cells alongside their transcriptional profiles. We found that T cell clonotypes in a mouse Salmonella infection model span early activated CD4(+) T cells as well as mature effector and memory cells.

VDJtools: Unifying Post-analysis of T Cell Receptor Repertoires

Despite the growing number of immune repertoire sequencing studies, the field still lacks software for analysis and comprehension of this high-dimensional data. Here we report VDJtools, a complementary software suite that solves a wide range of T cell receptor (TCR) repertoires post-analysis tasks, provides a detailed tabular output and publication-ready graphics, and is built on top of a flexible API. Using TCR datasets for a large cohort of unrelated healthy donors, twins, and multiple sclerosis patients we demonstrate that VDJtools greatly facilitates the analysis and leads to sound biological conclusions. VDJtools software and documentation are available at https://github.com/mikessh/vdjtools.