scholarly journals immuneSIM: tunable multi-feature simulation of B- and T-cell receptor repertoires for immunoinformatics benchmarking

2019 ◽  
Author(s):  
Cédric R. Weber ◽  
Rahmad Akbar ◽  
Alexander Yermanos ◽  
Milena Pavlović ◽  
Igor Snapkov ◽  
...  
Keyword(s):  
T Cell ◽  
T Cell Receptor ◽  
Network Architecture ◽  
Gene Annotation ◽  
Sequence Similarity ◽  
Cell Receptor ◽  
Germline Gene ◽  
Immune Receptor ◽  
Link Type ◽  
Estimation Sequence

AbstractSummaryB- and T-cell receptor repertoires of the adaptive immune system have become a key target for diagnostics and therapeutics research. Consequently, there is a rapidly growing number of bioinformatics tools for immune repertoire analysis. Benchmarking of such tools is crucial for ensuring reproducible and generalizable computational analyses. Currently, however, it remains challenging to create standardized ground truth immune receptor repertoires for immunoinformatics tool benchmarking. Therefore, we developed immuneSIM, an R package that allows the simulation of native-like and aberrant synthetic full length variable region immune receptor sequences. ImmuneSIM enables the tuning of the immune receptor features: (i) species and chain type (BCR, TCR, single, paired), (ii) germline gene usage, (iii) occurrence of insertions and deletions, (iv) clonal abundance, (v) somatic hypermutation, and (vi) sequence motifs. Each simulated sequence is annotated by the complete set of simulation events that contributed to its in silico generation. immuneSIM permits the benchmarking of key computational tools for immune receptor analysis such as germline gene annotation, diversity and overlap estimation, sequence similarity, network architecture, clustering analysis, and machine learning methods for motif detection.AvailabilityThe package is available via https://github.com/GreiffLab/immuneSIM and will also be available at CRAN (submitted). The documentation is hosted at https://[email protected], [email protected]

scholarly journals immuneSIM: tunable multi-feature simulation of B- and T-cell receptor repertoires for immunoinformatics benchmarking

2020 ◽  
Vol 36 (11) ◽  
pp. 3594-3596 ◽  
Author(s):  
Cédric R Weber ◽  
Rahmad Akbar ◽  
Alexander Yermanos ◽  
Milena Pavlović ◽  
Igor Snapkov ◽  
...  
Keyword(s):  
T Cell ◽  
T Cell Receptor ◽  
Network Architecture ◽  
Gene Annotation ◽  
Sequence Similarity ◽  
Cell Receptor ◽  
Supplementary Information ◽  
Germline Gene ◽  
Immune Receptor ◽  
Estimation Sequence

Abstract Summary B- and T-cell receptor repertoires of the adaptive immune system have become a key target for diagnostics and therapeutics research. Consequently, there is a rapidly growing number of bioinformatics tools for immune repertoire analysis. Benchmarking of such tools is crucial for ensuring reproducible and generalizable computational analyses. Currently, however, it remains challenging to create standardized ground truth immune receptor repertoires for immunoinformatics tool benchmarking. Therefore, we developed immuneSIM, an R package that allows the simulation of native-like and aberrant synthetic full-length variable region immune receptor sequences by tuning the following immune receptor features: (i) species and chain type (BCR, TCR, single and paired), (ii) germline gene usage, (iii) occurrence of insertions and deletions, (iv) clonal abundance, (v) somatic hypermutation and (vi) sequence motifs. Each simulated sequence is annotated by the complete set of simulation events that contributed to its in silico generation. immuneSIM permits the benchmarking of key computational tools for immune receptor analysis, such as germline gene annotation, diversity and overlap estimation, sequence similarity, network architecture, clustering analysis and machine learning methods for motif detection. Availability and implementation The package is available via https://github.com/GreiffLab/immuneSIM and on CRAN at https://cran.r-project.org/web/packages/immuneSIM. The documentation is hosted at https://immuneSIM.readthedocs.io. Contact [email protected] or [email protected] Supplementary information Supplementary data are available at Bioinformatics online.

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

2021 ◽  
Vol 12 ◽  
Author(s):  
Jonathan Crider ◽  
Sylvie M. A. Quiniou ◽  
Kristianna L. Felch ◽  
Kurt Showmaker ◽  
Eva Bengtén ◽  
...  
Keyword(s):  
T Cell ◽  
T Cell Receptor ◽  
Ictalurus Punctatus ◽  
Channel Catfish ◽  
Gene Annotation ◽  
Gene Segment ◽  
Cell Receptor ◽  
Gene Duplications ◽  
The Many ◽  
Segment Database

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.

scholarly journals Staphylococcus aureus Isolated from Skin from Atopic-Dermatitis Patients Produces Staphylococcal Enterotoxin Y, Which Predominantly Induces T-Cell Receptor Vα-Specific Expansion of T Cells

2019 ◽  
Vol 88 (2) ◽  
Author(s):  
Fatkhanuddin Aziz ◽  
Junzo Hisatsune ◽  
Liansheng Yu ◽  
Junko Kajimura ◽  
Yusuke Sato’o ◽  
...  
Keyword(s):  
Staphylococcus Aureus ◽  
T Cells ◽  
Atopic Dermatitis ◽  
T Cell ◽  
T Cell Receptor ◽  
T Cell Activation ◽  
Cell Receptor ◽  
Broth Culture ◽  
Content Type ◽  
Link Type

ABSTRACT While investigating the virulence traits of Staphylococcus aureus adhering to the skin of atopic-dermatitis (AD) patients, we identified a novel open reading frame (ORF) with structural similarity to a superantigen from genome sequence data of an isolate from AD skin. Concurrently, the same ORF was identified in a bovine isolate of S. aureus and designated SElY (H. K. Ono, Y. Sato’o, K. Narita, I. Naito, et al., Appl Environ Microbiol 81:7034–7040, 2015, https://doi.org/10.1128/AEM.01873-15). Recombinant SElYbov had superantigen activity in human peripheral blood mononuclear cells. It further demonstrated emetic activity in a primate animal model, and it was proposed that SElY be renamed SEY (H. K. Ono, S. Hirose, K. Narita, M. Sugiyama, et al., PLoS Pathog 15:e1007803, 2019, https://doi.org/10.1371/journal.ppat.1007803). Here, we investigated the prevalence of the sey gene in 270 human clinical isolates of various origins in Japan. Forty-two strains were positive for the sey gene, and the positive isolates were from patients with the skin diseases atopic dermatitis and impetigo/staphylococcal scalded skin syndrome (SSSS), with a detection rate of ∼17 to 22%. There were three variants of SEY (SEY1, SEY2, and SEY3), and isolates producing SEY variants formed three distinct clusters corresponding to clonal complexes (CCs) 121, 59, and 20, respectively. Most sey+ isolates produced SEY in broth culture. Unlike SEYbov, the three recombinant SEY variants exhibited stability against heat treatment. SEY predominantly activated human T cells with a particular T-cell receptor (TCR) Vα profile, a unique observation since most staphylococcal enterotoxins exert their superantigenic activities through activating T cells with specific TCR Vβ profiles. SEY may act to induce localized inflammation via skin-resident T-cell activation, facilitating the pathogenesis of S. aureus infection in disrupted epithelial barriers.

scholarly journals T-cell Receptor Diversity Estimates for Repertoires (TCRDivER) uses sequence similarity to find signatures of immune response

2021 ◽  
Author(s):  
Milena Vujović ◽  
Paolo Marcatili ◽  
Benny Chain ◽  
Joseph Kaplinsky ◽  
Thomas Lars Andresen
Keyword(s):  
T Cell ◽  
T Cell Receptor ◽  
Sequence Similarity ◽  
Cell Receptor ◽  
Sequence Motifs ◽  
Sequencing Data ◽  
Cell Repertoire ◽  
Specific Sequence ◽  
Clone Size ◽  
Diversity Estimates

AbstractWe propose TCRDivER, a global approach to T-cell repertoire comparison using diversity profiles sensitive to both clone size and sequence similarity. As immunotherapies improve, the long standing biological interest in connecting outcome with T cell receptor (TCR) repertoire status has become more urgent. Here we show that new insights can be extracted from high throughput repertoire sequencing data. Most current efforts focus on identification of immunisation-specific sequence motifs or on monitoring changes in frequency of individual clones. Applying TCRDivER to murine spleen samples shows it characterises an additional dimension of repertoire variation, beyond conventional diversity estimates, allowing distinction between immunised and non-immunised samples. We further apply TCRDivER to repertoires from human blood. In both cases we show characteristic relationships between repertoire features. These reveal biologically interpretable relationships between sequence similarity and clonal expansions. We thereby demonstrate a new tool for investigation in clinical and research applications.

T-Cell receptor constant β germline gene polymorphisms and susceptibility to autoimmune hepatitis

1994 ◽  
Vol 106 (5) ◽  
pp. 1321-1325 ◽  
Author(s):  
Koji Manabe ◽  
Martin L. Hibberd ◽  
Peter T. Donaldson ◽  
James A. Underhill ◽  
Derek G. Doherty ◽  
...  
Keyword(s):  
T Cell ◽  
Autoimmune Hepatitis ◽  
T Cell Receptor ◽  
Gene Polymorphisms ◽  
Cell Receptor ◽  
Germline Gene

T Cell Receptor Germline Gene Segments and HLA Haplotypes Control the Length of the CDR3 of Human T Cell Receptor β Chains

1996 ◽  
Vol 168 (2) ◽  
pp. 235-242 ◽  
Author(s):  
Corinna Kayser ◽  
Inge Waase ◽  
Cornelia M. Weyand ◽  
Jörg J. Goronzy
Keyword(s):  
T Cell ◽  
T Cell Receptor ◽  
Cell Receptor ◽  
Germline Gene ◽  
Human T Cell ◽  
Hla Haplotypes

scholarly journals TCRMatch: Predicting T-Cell Receptor Specificity Based on Sequence Similarity to Previously Characterized Receptors

2021 ◽  
Vol 12 ◽  
Author(s):  
William D. Chronister ◽  
Austin Crinklaw ◽  
Swapnil Mahajan ◽  
Randi Vita ◽  
Zeynep Koşaloğlu-Yalçın ◽  
...  
Keyword(s):  
T Cell ◽  
T Cell Receptor ◽  
High Throughput Sequencing ◽  
Sequence Similarity ◽  
Adaptive Immune System ◽  
Cell Receptor ◽  
Epitope Specificity ◽  
Receptor Repertoire ◽  
Tcr Repertoire ◽  
Specific Receptors

The adaptive immune system in vertebrates has evolved to recognize non-self antigens, such as proteins expressed by infectious agents and mutated cancer cells. T cells play an important role in antigen recognition by expressing a diverse repertoire of antigen-specific receptors, which bind epitopes to mount targeted immune responses. Recent advances in high-throughput sequencing have enabled the routine generation of T-cell receptor (TCR) repertoire data. Identifying the specific epitopes targeted by different TCRs in these data would be valuable. To accomplish that, we took advantage of the ever-increasing number of TCRs with known epitope specificity curated in the Immune Epitope Database (IEDB) since 2004. We compared seven metrics of sequence similarity to determine their power to predict if two TCRs have the same epitope specificity. We found that a comprehensive k-mer matching approach produced the best results, which we have implemented into TCRMatch, an openly accessible tool (http://tools.iedb.org/tcrmatch/) that takes TCR β-chain CDR3 sequences as an input, identifies TCRs with a match in the IEDB, and reports the specificity of each match. We anticipate that this tool will provide new insights into T cell responses captured in receptor repertoire and single cell sequencing experiments and will facilitate the development of new strategies for monitoring and treatment of infectious, allergic, and autoimmune diseases, as well as cancer.

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