Ultrasensitive allele inference from immune repertoire sequencing data with MiXCR.

Allelic variability in the adaptive immune receptor loci, which harbor the gene segments that encode B cell and T cell receptors (BCR/TCR), is of critical importance for immune responses to pathogens and vaccines. Adaptive immune receptor repertoire sequencing (AIRR-seq) has become widespread in immunology research making it the most readily available source of information about allelic diversity in immunoglobulin (IG) and T cell receptor (TR) loci. Here we present a novel algorithm for extra-sensitive and specific variable (V) and joining (J) gene allele inference, allowing reconstruction of individual high-quality gene segment libraries. The approach can be applied for inferring allelic variants from peripheral blood lymphocyte BCR and TCR repertoire sequencing data, including hypermutated isotype-switched BCR sequences, thus allowing high-throughput novel allele discovery from a wide variety of existing datasets. The developed algorithm is a part of the MiXCR software. We demonstrate the accuracy of this approach using AIRR-seq paired with long-read genomic sequencing data, comparing it to a widely used algorithm, TIgGER. We applied the algorithm to a large set of IG heavy chain (IGH) AIRR-seq data from 450 donors of ancestrally diverse population groups, and to the largest reported full-length TCR alpha and beta chain (TRA; TRB) AIRR-seq dataset, representing 134 individuals. This allowed us to assess the genetic diversity within the IGH, TRA and TRB loci in different populations and to establish a database of alleles of V and J genes inferred from AIRR-seq data and their population frequencies with free public access through an online database.

Comment on 'rigorous benchmarking of T cell receptor repertoire profiling methods for cancer RNA sequencing'.

Transcriptome sequencing has become common in cancer research, resulting in the generation of a substantial volume of RNA sequencing (RNA-Seq) data. The ability to extract immune repertoires from these data is crucial for obtaining information on infiltrating T- and B-lymphocyte clones when dedicated amplicon T-cell/B-cell receptors sequencing (TCR-Seq/BCR-Seq) methods are unavailable. In response to this demand, several dedicated computational methods have been developed, including MiXCR, TRUST and ImRep. In the recent publication in Briefings in Bioinformatics, Peng et al. have conducted an intensive, systematic comparison of the three previously mentioned tools. Although their effort is commendable, we do have a few constructive critiques regarding technical elements of their analysis.

Local fitness landscape of the green fluorescent protein.

Fitness landscapes depict how genotypes manifest at the phenotypic level and form the basis of our understanding of many areas of biology, yet their properties remain elusive. Previous studies have analysed specific genes, often using their function as a proxy for fitness, experimentally assessing the effect on function of single mutations and their combinations in a specific sequence or in different sequences. However, systematic high-throughput studies of the local fitness landscape of an entire protein have not yet been reported. Here we visualize an extensive region of the local fitness landscape of the green fluorescent protein from Aequorea victoria (avGFP) by measuring the native function (fluorescence) of tens of thousands of derivative genotypes of avGFP. We show that the fitness landscape of avGFP is narrow, with 3/4 of the derivatives with a single mutation showing reduced fluorescence and half of the derivatives with four mutations being completely non-fluorescent. The narrowness is enhanced by epistasis, which was detected in up to 30% of genotypes with multiple mutations and mostly occurred through the cumulative effect of slightly deleterious mutations causing a threshold-like decrease in protein stability and a concomitant loss of fluorescence. A model of orthologous sequence divergence spanning hundreds of millions of years predicted the extent of epistasis in our data, indicating congruence between the fitness landscape properties at the local and global scales. The characterization of the local fitness landscape of avGFP has important implications for several fields including molecular evolution, population genetics and protein design.

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

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 ß J segments. These findings provide a deeper insight into the mechanism of TCR repertoire generation.

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

BACKGROUND: The 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. RESULTS: Here 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. CONCLUSIONS: tcR 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.

Convergence, plasticity, and tissue residence of regulatory T cell response via TCR repertoire prism.

Suppressive function of regulatory T cells (Treg) is dependent on signaling of their antigen receptors triggered by cognate self, dietary, or microbial peptides presented on MHC II. However, it remains largely unknown whether distinct or shared repertoires of Treg TCRs are mobilized in response to different challenges in the same tissue or the same challenge in different tissues. Here we use a fixed TCRß chain FoxP3-GFP mouse model to analyze conventional (eCD4) and regulatory (eTreg) effector TCRα repertoires in response to six distinct antigenic challenges to the lung and skin. This model shows highly 'digital' repertoire behavior with easy-to-track challenge-specific TCRα CDR3 clusters. For both eCD4 and eTreg subsets, we observe challenge-specific clonal expansions yielding homologous TCRα clusters within and across animals and exposure sites, which are also reflected in the draining lymph nodes but not systemically. Some CDR3 clusters are shared across cancer challenges, suggesting a response to common tumor-associated antigens. For most challenges, eCD4 and eTreg clonal response does not overlap. Such overlap is exclusively observed at the sites of certain tumor challenges, and not systematically, suggesting transient and local tumor-induced eCD4=>eTreg plasticity. This transition includes a dominant tumor-responding eCD4 CDR3 motif, as well as characteristic iNKT TCRα CDR3. In addition, we examine the homeostatic tissue residency of clonal eTreg populations by excluding the site of challenge from our analysis. We demonstrate that distinct CDR3 motifs are characteristic of eTreg cells residing in particular lymphatic tissues, regardless of the challenge. This observation reveals the tissue-resident, antigen-specific clonal Treg populations.

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.

Can we see PIP(3) and hydrogen peroxide with a single probe?

A genetically encoded sensor for parallel measurements of phosphatidylinositol 3-kinase activity and hydrogen peroxide (H(2)O(2)) levels (termed PIP-SHOW) was developed. Upon elevation of local phosphatidylinositol 3,4,5-trisphosphate (PIP(3)) concentration, the sensor translocates from the cytosol to the plasma membrane, while a ratiometric excitation change rapidly and simultaneously reports changes in the concentration of H(2)O(2). The dynamics of PIP(3) and H(2)O(2) generation were monitored in platelet-derived growth factor-stimulated fibroblasts and in T-lymphocytes after formation of an immunological synapse. We suggest that PIP-SHOW can serve as a prototype for many fluorescent sensors with combined readouts.