Ivan V. Zvyagin

Next generation sequencing for TCR repertoire profiling: platform-specific features and correction algorithms.

The TCR repertoire is a mirror of the human immune system that reflects processes caused by infections, cancer, autoimmunity, and aging. Next generation sequencing (NGS) is becoming a powerful tool for deep TCR profiling; yet, questions abound regarding the methodological approaches for sample preparation and correct data interpretation. Accumulated PCR and sequencing errors along with library preparation bottlenecks and uneven PCR efficiencies lead to information loss, biased quantification, and generation of huge artificial TCR diversity. Here, we compare Illumina, 454, and Ion Torrent platforms for individual TCR profiling, evaluate the rate and character of errors, and propose advanced platform‐specific algorithms to correct massive sequencing data. These developments are applicable to a wide variety of next generation sequencing applications. We demonstrate that advanced correction allows the removal of the majority of artificial TCR diversity with concomitant rescue of most of the sequencing information. Thus, this correction enhances the accuracy of clonotype identification and quantification as well as overall TCR diversity measurements.

MiTCR: software for T-cell receptor sequencing data analysis

The approaches MiTCR uses to analyze TCR sequencing data have been shown to be efficient in previous studies5,6. The software performs CDR3 extraction, identifies V, D and J segments, assembles clonotypes, filters out or rescues low-quality reads5 and provides advanced correction of PCR and sequencing errors1,5 using either a predefined or user-specified strategy (Fig. 1a and Supplementary Notes 1–3). Simple command-line parameters, human-readable configuration files and a well-documented application programming interface (API) optimized for use in scripts make the software flexible enough for routine data extraction by immunologists as well as for more advanced analysis and customization by bioinformaticians (Supplementary Note 1 and Supplementary Data 1). We computationally optimized and parallelized the algorithms such that MiTCR can efficiently extract CDR3 information at a speed of more than 50,000 sequencing reads per second (0.3– 0.6 gigabases min–1) on standard PC hardware. For example, Illumina MiSeq run of 10 million reads can be analyzed in ~3 min, and a HiSeq lane of 100 million reads can be analyzed in ~20 min (Supplementary Note 4). Output is provided in a tab-delimited text file that contains exhaustive information regarding TCR clonotype composition, abundance and aggregated sequence quality (Supplementary Data 2). Additionally, we developed MiTCR Viewer software that works with a custom (*.cls) format produced by MiTCR, enabling convenient visualization, filtering and in silico spectratyping of the data (http://mitcr.milaboratory.com/viewer/; Supplementary Data 3). We demonstrated the accuracy and specificity of MiTCR for the analysis of both cDNA-based and genomic DNA–based high-throughput sequencing datasets (Supplementary Tables 1 and 2). To verify software performance with datasets of known clonotype composition, we generated Illumina-like data sets in silico, based on real rates of PCR and sequencing errors (Supplementary Note 5). We determined the efficiency of human TCR-α and TCR-β CDR3 extraction, clonotype generation and error correction for the model data (Fig. 1b,c). Accuracy of V and J segment identif ication was 97–99%. MiTCR efficiency was superior compared to that of existing CDR3extraction packages (Supplementary Note 6, Supplementary Table 3 and Supplementary Fig. 1). MiTCR: software for T-cell receptor sequencing data analysis

Pairing of T-cell receptor chains via emulsion PCR

Our ability to analyze adaptive immunity and engineer its activity has long been constrained by our limited ability to identify native pairs of heavy–light antibody chains and alpha–beta T‐cell receptor (TCR) chains — both of which comprise coupled “halves of a key”, collectively capable of recognizing specific antigens. Here, we report a cell‐based emulsion RT‐PCR approach that allows the selective fusion of the native pairs of amplified TCR alpha and beta chain genes for complex samples. A new type of PCR suppression technique was developed that makes it possible to amplify the fused library with minimal noise for subsequent analysis by high‐throughput paired‐end Illumina sequencing. With this technique, single analysis of a complex blood sample allows identification of multiple native TCR chain pairs. This approach may be extended to identify native antibody chain pairs and, more generally, pairs of mRNA molecules that are coexpressed in the same living 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.

Preparing Unbiased T-Cell Receptor and Antibody cDNA Libraries for the Deep Next Generation Sequencing Profiling

High-throughput sequencing has the power to reveal the nature of adaptive immunity as represented by the full complexity of T-cell receptor (TCR) and antibody (IG) repertoires, but is at present severely compromised by the quantitative bias, bottlenecks, and accumulated errors that inevitably occur in the course of library preparation and sequencing. Here we report an optimized protocol for the unbiased preparation of TCR and IG cDNA libraries for high-throughput sequencing, starting from thousands or millions of live cells in an investigated sample. Critical points to control are revealed, along with tips that allow researchers to minimize quantitative bias, accumulated errors, and cross-sample contamination at each stage, and to enhance the subsequent bioinformatic analysis. The protocol is simple, reliable, and can be performed in 1–2 days.

tcR: an R package for T cell receptor repertoire advanced data analysis

BackgroundThe Immunoglobulins (IG) and the T cell receptors (TR) play the key role in antigen recognition during the adaptive immune response. Recent progress in next-generation sequencing technologies has provided an opportunity for the deep T cell receptor repertoire profiling. However, a specialised software is required for the rational analysis of massive data generated by next-generation sequencing.ResultsHere we introduce tcR, a new R package, representing a platform for the advanced analysis of T cell receptor repertoires, which includes diversity measures, shared T cell receptor sequences identification, gene usage statistics computation and other widely used methods. The tool has proven its utility in recent research studies.ConclusionstcR is an R package for the advanced analysis of T cell receptor repertoires after primary TR sequences extraction from raw sequencing reads. The stable version can be directly installed from The Comprehensive R Archive Network (http://cran.r-project.org/mirrors.html). The source code and development version are available at tcR GitHub (http://imminfo.github.io/tcr/) along with the full documentation and typical usage examples.

Distinctive properties of identical twins' TCR repertoires revealed by high-throughput sequencing

Significance The power of adaptive immunity in humans is realized through the hypervariable molecules: the T-cell receptors (TCRs). Each of those is built from genetically encoded parts with the addition of random nucleotides finally forming individual TCR repertoire. Despite that the individual TCR repertoire potentially can include 1011–1014 different variants, substantially less molecules are found in a single individual. The particular genetic impact on the final set of TCR molecules is still poorly understood. In this study, for the first time to the best of our knowledge, we compare deep TCR repertoires of genetically identical twins. We found that, although TCR repertoires of any pair of individuals have the same amount of identical receptors, twin repertoires share certain specific features. Adaptive immunity in humans is provided by hypervariable Ig-like molecules on the surface of B and T cells. The final set of these molecules in each organism is formed under the influence of two forces: individual genetic traits and the environment, which includes the diverse spectra of alien and self-antigens. Here we assess the impact of individual genetic factors on the formation of the adaptive immunity by analyzing the T-cell receptor (TCR) repertoires of three pairs of monozygous twins by next-generation sequencing. Surprisingly, we found that an overlap between the TCR repertoires of monozygous twins is similar to an overlap between the TCR repertoires of nonrelated individuals. However, the number of identical complementary determining region 3 sequences in two individuals is significantly increased for twin pairs in the fraction of highly abundant TCR molecules, which is enriched by the antigen-experienced T cells. We found that the initial recruitment of particular TCR V genes for recombination and subsequent selection in the thymus is strictly determined by individual genetic factors. J genes of TCRs are selected randomly for recombination; however, the subsequent selection in the thymus gives preference to some α but not β J segments. These findings provide a deeper insight into the mechanism of TCR repertoire generation.

Quantitative tracking of T cell clones after haematopoietic stem cell transplantation

Autologous haematopoietic stem cell transplantation is highly efficient for the treatment of systemic autoimmune diseases, but its consequences for the immune system remain poorly understood. Here, we describe an optimized RNA‐based technology for unbiased amplification of T cell receptor beta‐chain libraries and use it to perform the first detailed, quantitative tracking of T cell clones during 10 months after transplantation. We show that multiple clones survive the procedure, contribute to the immune response to activated infections, and form a new skewed and stable T cell receptor repertoire.

Contribution of functional KIR3DL1 to ankylosing spondylitis

Increasing evidence points to a role for killer immunoglobulin-like receptors (KIRs) in the development of autoimmune diseases. In particular, a positive association of KIR3DS1 (activating receptor) and a negative association of KIR3DL1 (inhibitory receptor) alleles with ankylosing spondylitis (AS) have been reported by several groups. However, none of the studies analyzed these associations in the context of functionality of polymorphic KIR3DL1. To better understand how the KIR3DL1/3DS1 genes determine susceptibility to AS, we analyzed the frequencies of alleles and genotypes encoding functional (KIR3DL1*F) and non-functional (KIR3DL1*004) receptors. We genotyped 83 AS patients and 107 human leukocyte antigen (HLA)-B27-positive healthy controls from the Russian Caucasian population using a two-stage sequence-specific primer PCR, which distinguishes KIR3DS1, KIR3DL1*F and KIR3DL1*004 alleles. For the patients carrying two functional KIR3DL1 alleles, those alleles were additionally genotyped to identify KIR3DL1*005 and KIR3DL1*007 alleles, which are functional but are expressed at low levels. KIR3DL1 was negatively associated with AS at the expense of KIR3DL1*F but not of KIR3DL1*004. This finding indicates that the inhibitory KIR3DL1 receptor protects against the development of AS and is not simply a passive counterpart of the segregating KIR3DS1 allele encoding the activating receptor. However, analysis of genotype frequencies indicates that the presence of KIR3DS1 is a more important factor for AS susceptibility than the absence of KIR3DL1*F. The activation of either natural killer (NK) or T cells via the KIR3DS1 receptor can be one of the critical events in AS development, while the presence of the functional KIR3DL1 receptor has a protective effect. Nevertheless, even individuals with a genotype that carried two inhibitory KIR3DL1 alleles expressed at high levels could develop AS.

VDJdb: a curated database of T-cell receptor sequences with known antigen specificity.

Abstract The ability to decode antigen specificities encapsulated in the sequences of rearranged T-cell receptor (TCR) genes is critical for our understanding of the adaptive immune system and promises significant advances in the field of translational medicine. Recent developments in high-throughput sequencing methods (immune repertoire sequencing technology, or RepSeq) and single-cell RNA sequencing technology have allowed us to obtain huge numbers of TCR sequences from donor samples and link them to T-cell phenotypes. However, our ability to annotate these TCR sequences still lags behind, owing to the enormous diversity of the TCR repertoire and the scarcity of available data on T-cell specificities. In this paper, we present VDJdb, a database that stores and aggregates the results of published T-cell specificity assays and provides a universal platform that couples antigen specificities with TCR sequences. We demonstrate that VDJdb is a versatile instrument for the annotation of TCR repertoire data, enabling a concatenated view of antigen-specific TCR sequence motifs. VDJdb can be accessed at https://vdjdb.cdr3.net and https://github.com/antigenomics/vdjdb-db.