scholarly journals OLGA: fast computation of generation probabilities of B- and T-cell receptor amino acid sequences and motifs

2018 ◽  
Author(s):  
Zachary Sethna ◽  
Yuval Elhanati ◽  
Curtis G. Callan ◽  
Aleksandra M. Walczak ◽  
Thierry Mora
Keyword(s):  
T Cells ◽  
Amino Acid ◽  
T Cell ◽  
High Throughput Sequencing ◽  
Amino Acid Level ◽  
Cell Receptor ◽  
Amino Acid Sequences ◽  
Published Data ◽  
Cell Receptors ◽  
Specific Nucleotide Sequence

MotivationHigh-throughput sequencing of large immune repertoires has enabled the development of methods to predict the probability of generation by V(D)J recombination of T- and B-cell receptors of any specific nucleotide sequence. These generation probabilities are very non-homogeneous, ranging over 20 orders of magnitude in real repertoires. Since the function of a receptor really depends on its protein sequence, it is important to be able to predict this probability of generation at the amino acid level. However, brute-force summation over all the nucleotide sequences with the correct amino acid translation is computationally intractable. The purpose of this paper is to present a solution to this problem.ResultsWe use dynamic programming to construct an efficient and flexible algorithm, called OLGA (Optimized Likelihood estimate of immunoGlobulin Amino-acid sequences), for calculating the probability of generating a given CDR3 amino acid sequence or motif, with or without V/J restriction, as a result of V(D)J recombination in B or T cells. We apply it to databases of epitope-specific T-cell receptors to evaluate the probability that a typical human subject will possess T cells responsive to specific disease-associated epitopes. The model prediction shows an excellent agreement with published data. We suggest that OLGA may be a useful tool to guide vaccine design.AvailabilitySource code is available at https://github.com/zsethna/OLGA

scholarly journals OLGA: fast computation of generation probabilities of B- and T-cell receptor amino acid sequences and motifs

2019 ◽  
Vol 35 (17) ◽  
pp. 2974-2981 ◽  
Author(s):  
Zachary Sethna ◽  
Yuval Elhanati ◽  
Curtis G Callan ◽  
Aleksandra M Walczak ◽  
Thierry Mora
Keyword(s):  
T Cells ◽  
Amino Acid ◽  
T Cell ◽  
High Throughput Sequencing ◽  
Amino Acid Level ◽  
Cell Receptor ◽  
Amino Acid Sequences ◽  
Supplementary Information ◽  
Published Data ◽  
Cell Receptors

Abstract Motivation High-throughput sequencing of large immune repertoires has enabled the development of methods to predict the probability of generation by V(D)J recombination of T- and B-cell receptors of any specific nucleotide sequence. These generation probabilities are very non-homogeneous, ranging over 20 orders of magnitude in real repertoires. Since the function of a receptor really depends on its protein sequence, it is important to be able to predict this probability of generation at the amino acid level. However, brute-force summation over all the nucleotide sequences with the correct amino acid translation is computationally intractable. The purpose of this paper is to present a solution to this problem. Results We use dynamic programming to construct an efficient and flexible algorithm, called OLGA (Optimized Likelihood estimate of immunoGlobulin Amino-acid sequences), for calculating the probability of generating a given CDR3 amino acid sequence or motif, with or without V/J restriction, as a result of V(D)J recombination in B or T cells. We apply it to databases of epitope-specific T-cell receptors to evaluate the probability that a typical human subject will possess T cells responsive to specific disease-associated epitopes. The model prediction shows an excellent agreement with published data. We suggest that OLGA may be a useful tool to guide vaccine design. Availability and implementation Source code is available at https://github.com/zsethna/OLGA. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Localization of a site on bacterial superantigens that determines T cell receptor beta chain specificity.

1993 ◽  
Vol 177 (2) ◽  
pp. 283-293 ◽  
Author(s):  
J A Mollick ◽  
R L McMasters ◽  
D Grossman ◽  
R R Rich
Keyword(s):  
T Cells ◽  
Amino Acid ◽  
T Cell ◽  
T Cell Receptor ◽  
Amino Acid Level ◽  
Cell Receptor ◽  
Class Ii ◽  
Beta Chain ◽  
Functional Sites ◽  
Bacterial Superantigens

A defining characteristic of superantigens is their ability to stimulate T cells based predominantly on the type of variable segment of the T cell receptor (TCR) beta chain (V beta). The V beta specificity of these toxins most likely results from direct contact between the toxin and the TCR, although the low affinity nature of this binding has prevented direct assessment of this interaction. To identify important functional sites on the toxin, we created chimeric enterotoxin genes between staphylococcal enterotoxins A and E (SEA and SEE) and tested the V beta specificity of the chimeric toxins. This approach allowed us to identify three amino acid residues in the extreme COOH terminus of these toxins that are largely responsible for their ability to stimulate either human V beta 5- or V beta 8-bearing T cells, or mouse V beta 3 or V beta 11. We also found that residues in the NH2 terminus were required for wild-type levels of V beta-specific T cell activation, suggesting that the NH2 and COOH ends of these superantigens may come together to form the full TCR V beta contact site. SEA and SEE also differ with respect to their class II binding characteristics. Using the same chimeric molecules, we demonstrate that the first third of the molecule controls the class II binding phenotype. These data lead us to propose that for SEA and SEE, and perhaps for all bacterial-derived superantigens, the COOH and NH2 termini together form the contact sites for the TCR and therefore largely determine the V beta specificity of the toxin, while the NH2 terminus alone binds major histocompatibility complex class II molecules. The predominant role of the COOH terminus of bacterial superantigens in determining V beta specificity resembles current models being proposed for virally encoded superantigens, suggesting that these molecules may demonstrate some structural relationship not seen at the amino acid level.

P134 Amino acid sequences of T cell receptor reacting against multiple myeloma

Blood Reviews ◽  
2007 ◽  
Vol 21 ◽  
pp. S129
Author(s):  
S. Dudova ◽  
L. Kovarova ◽  
R. Horvath ◽  
M. Penka ◽  
R. Hajek ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Amino Acid ◽  
T Cell ◽  
T Cell Receptor ◽  
Cell Receptor ◽  
Amino Acid Sequences

Developing and validating an approach for diagnosing and prognosticating cancer from biochemical motifs in T-cell receptors.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e15260-e15260
Author(s):  
Jared L Ostmeyer ◽  
Lindsay G Cowell ◽  
Scott Christley
Keyword(s):  
Amino Acid ◽  
T Cell ◽  
T Cell Receptor ◽  
T Cell Receptors ◽  
Ovarian Tissue ◽  
Cell Receptor ◽  
Healthy Tissue ◽  
Cervical Lesions ◽  
Cell Receptors ◽  
Biochemical Features

e15260 Background: Immune repertoire deep sequencing allows profiling T-cell populations and enables novel approaches to diagnose and prognosticate cancer by identifying T-cell receptor sequence patterns associated with clinical phenotypes and outcomes. Methods: Our goal is to develop a method to diagnose and prognosticate cancer using sequenced T-cell receptors. To determine how to profile the specificity of a T-cell receptor, we analyze 3D X-ray crystallographic structures of T-cell receptors bound to antigen. We observe a contiguous strip typically 4 amino acid residues in length from the complimentary determining region 3 (CDR3) lying in direct contact with the antigen. Based on this observation, we extract 4 residue long snippets from every receptor’s CDR3 and represent each snippet using biochemical features encoded by its amino acid sequence. The biochemical features are combined with information about the abundance of the snippet or the receptor and scored using a machine learning based approach. Each predictive model is fitted and validated under the requirement that at least one positively labelled snippet appears per tumor and no positively labelled snippets appear in healthy tissue. Results: Using a patient-holdout cross-validation, we fit predictive models to distinguish: 1. colorectal tumors from healthy tissue matched controls with 93% accuracy, 2. breast tumors from healthy tissue matched controls with 94% accuracy, 3. ovarian tumors from non-cancer patient ovarian tissue with 95% accuracy (80% accuracy on a blinded follow-up cohort) 4. and regression of preneoplastic cervical lesions over 1 year in advance with 96% accuracy. Conclusions: Immune repertoires can be used to diagnose and prognosticate cancer.

scholarly journals T Cell Receptor Transfection Shows Non-HLA-Restricted Recognition of Nickel by CD8+ Human T Cells to be Mediated by αβ T Cell Receptors

2003 ◽  
Vol 121 (3) ◽  
pp. 496-501 ◽  
Author(s):  
Corinne Moulon ◽  
Yoanna Choleva ◽  
Hermann-Josef Thierse ◽  
Doris Wild ◽  
Hans Ulrich Weltzien
Keyword(s):  
T Cells ◽  
T Cell ◽  
T Cell Receptor ◽  
T Cell Receptors ◽  
Cell Receptor ◽  
Cell Receptors ◽  
Human T Cells

scholarly journals T Cell Receptor Beta-Chain Profiling of Tumor Tissue, Peripheral Blood and Regional Lymph Nodes From Patients With Papillary Thyroid Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Yizeng Wang ◽  
Yuanchao Liu ◽  
Li Chen ◽  
Zuoyu Chen ◽  
Xiaoning Wang ◽  
...  
Keyword(s):  
Amino Acid ◽  
T Cell ◽  
Papillary Thyroid Carcinoma ◽  
Thyroid Carcinoma ◽  
T Cell Receptor ◽  
Peripheral Blood ◽  
Acid Level ◽  
Amino Acid Level ◽  
Cell Receptor ◽  
Papillary Thyroid

Objective: To study the characteristics of the T cell receptor (TCR) repertoire in cancer tissue, peripheral blood and regional lymph nodes (LNs) from patients with papillary thyroid carcinoma (PTC).Methods: PTC tissue, peripheral blood mononuclear cells (PBMCs) and regional LNs of six patients with papillary thyroid carcinoma were harvested. T cell receptor beta-chain (TCRβ) profiling was performed though high-throughput sequencing (HTS), and IMonitor, MiXCR and VDJtools were used to analyze the characteristics of the TCR repertoire.Results: The results of IMonitor and those of MiXCR and VDJtools were very similar. The unique CDR3 of TCRβ from LNs was higher than that of PBMCs, and the CDR3 of TCRβ from LNs was higher than that of PTC tissue. Shannon's diversity index, D50, inverse Simpson index_mean and normalized Shannon's diversity index_mean of CDR3 from LNs were higher than those of PTCs and PBMCs. The HEC (high expansion clones) rate of CDR3 sequences at the amino acid level in PTC tissue was higher than that of PBMCs, which was higher than that of LNs. The V-J HEC rate of CDR3 was highest in PTC tissue, followed by PBMCs and LNs.Conclusion: TCR CDR3 profiling showed differences among and within the PBMCs, PTC tissues and regional LNs of PTC, including unique CDR3, CDR3 HEC at the amino acid level, CDR3 V-J HEC at the amino acid level, Shannon's diversity index and D50. The TCRβ repertoire of PTC tissue, peripheral blood and regional LNs of PTC provide a reference for further study of immunity mechanisms against PTC.

scholarly journals Repertoire Builder: high-throughput structural modeling of B and T cell receptors

2019 ◽  
Vol 4 (4) ◽  
pp. 761-768 ◽  
Author(s):  
Dimitri Schritt ◽  
Songling Li ◽  
John Rozewicki ◽  
Kazutaka Katoh ◽  
Kazuo Yamashita ◽  
...  
Keyword(s):  
Amino Acid ◽  
T Cell ◽  
High Throughput ◽  
T Cell Receptors ◽  
Three Dimensional ◽  
Amino Acid Sequences ◽  
Atomic Resolution ◽  
B Cell Receptors ◽  
Cell Receptors ◽  
Three Dimensional Models

Repertoire Builder (https://sysimm.org/rep_builder/) is a method for generating atomic-resolution, three-dimensional models of B cell receptors (BCRs) or T cell receptors (TCRs) from their amino acid sequences.

scholarly journals The Single Positive T Cells Found in CD3-ζ/η−/− Mice Overtly React with Self–Major Histocompatibility Complex Molecules upon Restoration of Normal Surface Density of T Cell Receptor–CD3 Complex

1997 ◽  
Vol 185 (4) ◽  
pp. 707-716 ◽  
Author(s):  
Shih-Yao Lin ◽  
Laurence Ardouin ◽  
Anne Gillet ◽  
Marie Malissen ◽  
Bernard Malissen
Keyword(s):  
T Cells ◽  
T Cell ◽  
T Cell Receptor ◽  
T Cell Receptors ◽  
Cell Receptor ◽  
Normal Density ◽  
Cell Receptors ◽  
Peripheral T Cells ◽  
Single Positive ◽  
Deficient Mice

CD3-ζ/η–deficient mice have small thymuses containing cells that show a profound reduction in the surface levels of T cell receptors and terminate their differentiation at the CD4+CD8+ stage. Rather unexpectedly, CD3− or very low single positive T cells accumulate over time in the spleen and lymph nodes of CD3-ζ/η–deficient mice after a process dependent on MHC expression. Fusion of these peripheral T cells with a CD3-ζ–positive derivative of the BW5147 TCR-α−/β− thymoma resulted in hybridomas that do express an heterogeneous set of T cell receptor α/β dimers at their surface and at density comparable to those found in hybridomas derived from wild-type peripheral T cells. We have investigated the specificities of these T cell receptors using spleen cells from congenic and mutant mouse strains, and showed that the majority of them readily recognized self-MHC class I or class II molecules. These results demonstrate that by increasing the density and/or output of the T cell receptors expressed in peripheral T cells, one can confer them with the capacity to respond to normal density of self-MHC molecules.

scholarly journals Functionally Convergent B Cell Receptor Sequences in Transgenic Rats Expressing a Human B Cell Repertoire in Response to Tetanus Toxoid and Measles Antigens

2017 ◽  
Author(s):  
Jean-Philippe Büerckert ◽  
Axel R.S.X. Dubois ◽  
William J. Faison ◽  
Sophie Farinelle ◽  
Emilie Charpentier ◽  
...  
Keyword(s):  
Amino Acid ◽  
B Cell ◽  
Tetanus Toxoid ◽  
Measles Virus ◽  
High Throughput Sequencing ◽  
Cell Receptor ◽  
Amino Acid Sequences ◽  
Transgenic Rats ◽  
Cell Repertoire ◽  
Environmental Carcinogen

AbstractThe identification and tracking of antigen-specific immunoglobulin (Ig) sequences within total Ig repertoires is central to high-throughput sequencing (HTS) studies of infections or vaccinations. In this context, public Ig sequences shared by different individuals exposed to the same antigen could be valuable markers for tracing back infections, measuring vaccine immunogenicity, and perhaps ultimately allow the reconstruction of the immunological history of an individual. Here, we immunized groups of transgenic rats expressing human Ig against tetanus toxoid (TT), Modified Vaccinia virus Ankara (MVA), measles virus hemagglutinin and fusion proteins expressed on MVA and the environmental carcinogen Benzo[a]Pyrene, coupled to TT. We showed that these antigens impose a selective pressure causing the Ig Heavy chain (IgH) repertoires of the rats to converge towards the expression of antibodies with highly similar IgH CDR3 amino acid sequences. We present a computational approach, similar to differential gene expression analysis, that selects for clusters of CDR3s with 80% similarity, significantly overrepresented within the different groups of immunized rats. These IgH clusters represent antigen-induced IgH signatures exhibiting stereotypic amino acid patterns including previously described TT and measles specific IgH sequences. Our data suggest, that with the presented methodology, transgenic Ig rats can be utilized as a model to identify antigen-induced, human IgH signatures to a variety of different antigens.

Natural killer cell receptors regulate responses of HLA-E–restricted T cells

2021 ◽  
Vol 6 (58) ◽  
pp. eabe9057
Author(s):  
Lucy C. Sullivan ◽  
Thi H.O. Nguyen ◽  
Christopher M. Harpur ◽  
Sanda Stankovic ◽  
Abbie R. Kanagarajah ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
Natural Killer Cell ◽  
Natural Killer ◽  
Killer Cell ◽  
Flow Cytometric Analysis ◽  
Human Leukocyte ◽  
Cell Receptor ◽  
Cell Receptors ◽  
Natural Killer Cell Receptors

Human cytomegalovirus (CMV) infection can stimulate robust human leukocyte antigen (HLA)–E–restricted CD8+ T cell responses. These T cells recognize a peptide from UL40, which differs by as little as a single methyl group from self-peptides that also bind HLA-E, challenging their capacity to avoid self-reactivity. Unexpectedly, we showed that the UL40/HLA-E T cell receptor (TCR) repertoire included TCRs that had high affinities for HLA-E/self-peptide. However, paradoxically, lower cytokine responses were observed from UL40/HLA-E T cells bearing TCRs with high affinity for HLA-E. RNA sequencing and flow cytometric analysis revealed that these T cells were marked by the expression of inhibitory natural killer cell receptors (NKRs) KIR2DL1 and KIR2DL2/L3. On the other hand, UL40/HLA-E T cells bearing lower-affinity TCRs expressed the activating receptor NKG2C. Activation of T cells bearing higher-affinity TCRs was regulated by the interaction between KIR2D receptors and HLA-C. These findings identify a role for NKR signaling in regulating self/non-self discrimination by HLA-E–restricted T cells, allowing for antiviral responses while avoiding contemporaneous self-reactivity.

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