Mikhail Shugay

MiXCR: software for comprehensive adaptive immunity profiling

MiXCR: software for comprehensive adaptive immunity profiling. MiXCR: software for comprehensive adaptive immunity profiling. MiXCR: software for comprehensive adaptive immunity profiling. MiXCR: software for comprehensive adaptive immunity profiling.MiXCR: software for comprehensive adaptive immunity profiling.

Towards error-free profiling of immune repertoires

Deep profiling of antibody and T cell–receptor repertoires by means of high-throughput sequencing has become an attractive approach for adaptive immunity studies, but its power is substantially compromised by the accumulation of PCR and sequencing errors. Here we report MIGEC (molecular identifier groups–based error correction), a strategy for high-throughput sequencing data analysis. MIGEC allows for nearly absolute error correction while fully preserving the natural diversity of complex immune repertoires.

Age-Related Decrease in TCR Repertoire Diversity Measured with Deep and Normalized Sequence Profiling

The decrease of TCR diversity with aging has never been studied by direct methods. In this study, we combined high-throughput Illumina sequencing with unique cDNA molecular identifier technology to achieve deep and precisely normalized profiling of TCR β repertoires in 39 healthy donors aged 6–90 y. We demonstrate that TCR β diversity per 106 T cells decreases roughly linearly with age, with significant reduction already apparent by age 40. The percentage of naive T cells showed a strong correlation with measured TCR diversity and decreased linearly up to age 70. Remarkably, the oldest group (average age 82 y) was characterized by a higher percentage of naive CD4+ T cells, lower abundance of expanded clones, and increased TCR diversity compared with the previous age group (average age 62 y), suggesting the influence of age selection and association of these three related parameters with longevity. Interestingly, cross-analysis of individual TCR β repertoires revealed a set >10,000 of the most representative public TCR β clonotypes, whose abundance among the top 100,000 clones correlated with TCR diversity and decreased with aging.

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.

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.

A mechanism for expansion of regulatory T-cell repertoire and its role in self-tolerance

T-cell receptor (TCR) signalling has a key role in determining T-cell fate. Precursor cells expressing TCRs within a certain low-affinity range for complexes of self-peptide and major histocompatibility complex (MHC) undergo positive selection and differentiate into naive T cells expressing a highly diverse self-MHC-restricted TCR repertoire. In contrast, precursors displaying TCRs with a high affinity for ‘self’ are either eliminated through TCR-agonist-induced apoptosis (negative selection) or restrained by regulatory T (Treg) cells, whose differentiation and function are controlled by the X-chromosome-encoded transcription factor Foxp3 (reviewed in ref. 2). Foxp3 is expressed in a fraction of self-reactive T cells that escape negative selection in response to agonist-driven TCR signals combined with interleukin 2 (IL-2) receptor signalling. In addition to Treg cells, TCR-agonist-driven selection results in the generation of several other specialized T-cell lineages such as natural killer T cells and innate mucosal-associated invariant T cells. Although the latter exhibit a restricted TCR repertoire, Treg cells display a highly diverse collection of TCRs. Here we explore in mice whether a specialized mechanism enables agonist-driven selection of Treg cells with a diverse TCR repertoire, and the importance this holds for self-tolerance. We show that the intronic Foxp3 enhancer conserved noncoding sequence 3 (CNS3) acts as an epigenetic switch that confers a poised state to the Foxp3 promoter in precursor cells to make Treg cell lineage commitment responsive to a broad range of TCR stimuli, particularly to suboptimal ones. CNS3-dependent expansion of the TCR repertoire enables Treg cells to control self-reactive T cells effectively, especially when thymic negative selection is genetically impaired. Our findings highlight the complementary roles of these two main mechanisms of self-tolerance.

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.

High-quality full-length immunoglobulin profiling with unique molecular barcoding

High-throughput sequencing analysis of hypermutating immunoglobulin (IG) repertoires remains a challenging task. Here we present a robust protocol for the full-length profiling of human and mouse IG repertoires. This protocol uses unique molecular identifiers (UMIs) introduced in the course of cDNA synthesis to control bottlenecks and to eliminate PCR and sequencing errors. Using asymmetric 400+100-nt paired-end Illumina sequencing and UMI-based assembly with the new version of the MIGEC software, the protocol allows up to 750-nt lengths to be sequenced in an almost error-free manner. This sequencing approach should also be applicable to various tasks beyond immune repertoire studies. In IG profiling, the achieved length of high-quality sequence covers the variable region of even the longest chains, along with the fragment of a constant region carrying information on the antibody isotype. The whole protocol, including preparation of cells and libraries, sequencing and data analysis, takes 5 to 6 d.