scholarly journals Predicting recognition between T cell receptors and epitopes with TCRGP

2021 ◽  
Vol 17 (3) ◽  
pp. e1008814
Author(s):  
Emmi Jokinen ◽  
Jani Huuhtanen ◽  
Satu Mustjoki ◽  
Markus Heinonen ◽  
Harri Lähdesmäki
Keyword(s):  
T Cell ◽  
T Cell Receptors ◽  
Comprehensive Evaluation ◽  
Adaptive Immune System ◽  
Amino Acid Sequences ◽  
Sequencing Data ◽  
Cell Receptors ◽  
Adaptive Immune ◽  
Complementarity Determining Regions ◽  
Process Method

Adaptive immune system uses T cell receptors (TCRs) to recognize pathogens and to consequently initiate immune responses. TCRs can be sequenced from individuals and methods analyzing the specificity of the TCRs can help us better understand individuals’ immune status in different disorders. For this task, we have developed TCRGP, a novel Gaussian process method that predicts if TCRs recognize specified epitopes. TCRGP can utilize the amino acid sequences of the complementarity determining regions (CDRs) from TCRα and TCRβ chains and learn which CDRs are important in recognizing different epitopes. Our comprehensive evaluation with epitope-specific TCR sequencing data shows that TCRGP achieves on average higher prediction accuracy in terms of AUROC score than existing state-of-the-art methods in epitope-specificity predictions. We also propose a novel analysis approach for combined single-cell RNA and TCRαβ (scRNA+TCRαβ) sequencing data by quantifying epitope-specific TCRs with TCRGP and identify HBV-epitope specific T cells and their transcriptomic states in hepatocellular carcinoma patients.

scholarly journals Determining epitope specificity of T cell receptors with TCRGP

2019 ◽  
Author(s):  
Emmi Jokinen ◽  
Jani Huuhtanen ◽  
Satu Mustjoki ◽  
Markus Heinonen ◽  
Harri Lähdesmäki
Keyword(s):  
T Cell ◽  
Immune Responses ◽  
T Cell Receptors ◽  
Comprehensive Evaluation ◽  
State Of The Art ◽  
Sequencing Data ◽  
Specific Data ◽  
Cell Receptors ◽  
Epitope Specificity ◽  
Process Method

T cell receptors (TCRs) can recognize various pathogens and consequently start immune responses. TCRs can be sequenced from individuals and methods analyzing the specificity of the TCRs can help us better understand individuals’ immune status in different diseases. We have developed TCRGP, a novel Gaussian process method to predict if TCRs recognize certain epitopes. This method can utilize CDR sequences from TCRα and TCRβ chains and learn which CDRs are important in recognizing different epitopes. We have experimented with with epitope-specific data against 29 epitopes and performed a comprehensive evaluation with existing prediction methods. On this data, TCRGP outperforms other state-of-the-art methods in epitope-specificity predictions. We also propose a novel analysis approach for combined single-cell RNA and TCRαβ (scRNA+TCRαβ) sequencing data by quantifying epitope-specific TCRs with TCRGP in phenotypes identified from scRNA-seq data. With this approach, we find HBV-epitope specific T cells and their transcriptomic states in hepatocellular carcinoma patients.

scholarly journals IMGT® Biocuration and Comparative Analysis of Bos taurus and Ovis aries TRA/TRD Loci

Genes ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 30
Author(s):  
Perrine Pégorier ◽  
Morgane Bertignac ◽  
Viviane Nguefack Ngoune ◽  
Géraldine Folch ◽  
Joumana Jabado-Michaloud ◽  
...  
Keyword(s):  
Immune Response ◽  
Comparative Analysis ◽  
T Cell ◽  
T Cell Receptors ◽  
Bos Taurus ◽  
Homo Sapiens ◽  
Adaptive Immune Response ◽  
Ovis Aries ◽  
Cell Receptors ◽  
Adaptive Immune

The adaptive immune response provides the vertebrate immune system with the ability to recognize and remember specific pathogens to generate immunity, and mount stronger attacks each time the pathogen is encountered. T cell receptors are the antigen receptors of the adaptive immune response expressed by T cells, which specifically recognize processed antigens, presented as peptides by the highly polymorphic major histocompatibility (MH) proteins. T cell receptors (TR) are divided into two groups, αβ and γδ, which express distinct TR containing either α and β, or γ and δ chains, respectively. The TRα locus (TRA) and TRδ locus (TRD) of bovine (Bos taurus) and the sheep (Ovis aries) have recently been described and annotated by IMGT® biocurators. The aim of the present study is to present the results of the biocuration and to compare the genes of the TRA/TRD loci among these ruminant species based on the Homo sapiens repertoire. The comparative analysis shows similarities but also differences, including the fact that these two species have a TRA/TRD locus about three times larger than that of humans and therefore have many more genes which may demonstrate duplications and/or deletions during evolution.

scholarly journals Functionally specialized human CD4+ T-cell subsets express physicochemically distinct TCRs

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Sofya A Kasatskaya ◽  
Kristin Ladell ◽  
Evgeniy S Egorov ◽  
Kelly L Miners ◽  
Alexey N Davydov ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
T Cell Receptors ◽  
Adaptive Immune System ◽  
T Cell Subsets ◽  
Effector Memory ◽  
Intrinsic Properties ◽  
Antigen Specificity ◽  
Adaptive Immune ◽  
Transition Pathways

The organizational integrity of the adaptive immune system is determined by functionally discrete subsets of CD4+ T cells, but it has remained unclear to what extent lineage choice is influenced by clonotypically expressed T-cell receptors (TCRs). To address this issue, we used a high-throughput approach to profile the αβ TCR repertoires of human naive and effector/memory CD4+ T-cell subsets, irrespective of antigen specificity. Highly conserved physicochemical and recombinatorial features were encoded on a subset-specific basis in the effector/memory compartment. Clonal tracking further identified forbidden and permitted transition pathways, mapping effector/memory subsets related by interconversion or ontogeny. Public sequences were largely confined to particular effector/memory subsets, including regulatory T cells (Tregs), which also displayed hardwired repertoire features in the naive compartment. Accordingly, these cumulative repertoire portraits establish a link between clonotype fate decisions in the complex world of CD4+ T cells and the intrinsic properties of somatically rearranged TCRs.

scholarly journals SwarmTCR: a computational approach to predict the specificity of T Cell Receptors

2020 ◽  
Author(s):  
Ryan Ehrlich ◽  
Larisa Kamga ◽  
Anna Gil ◽  
Katherine Luzuriaga ◽  
Liisa Selin ◽  
...  
Keyword(s):  
T Cell ◽  
T Cell Receptors ◽  
Nearest Neighbor ◽  
Sequence Data ◽  
Cell Receptor ◽  
Classification Performance ◽  
Sequencing Data ◽  
Cell Receptors ◽  
The Individual ◽  
Cell Data

AbstractMotivationComputationally predicting the specificity of T cell receptors can be a powerful tool to shed light on the immune response against infectious diseases and cancers, autoimmunity, cancer immunotherapy, and immunopathology. With more T cell receptor sequence data becoming available, the need for bioinformatics approaches to tackle this problem is even more pressing. Here we present SwarmTCR, a method that uses labeled sequence data to predict the specificity of T cell receptors using a nearest-neighbor approach. SwarmTCR works by optimizing the weights of the individual CDR regions to maximize classification performance.ResultsWe compared the performance of SwarmTCR against a state-of-the-art method (TCRdist) and showed that SwarmTCR performed significantly better on epitopes EBV-BRLF1300, EBV-BRLF1109, NS4B214–222 with single cell data and epitopes EBV-BRLF1300, EBV-BRLF1109, IAV-M158 with bulk sequencing data (α and β chains). In addition, we show that the weights returned by SwarmTCR are biologically interpretable.AvailabilitySwarmTCR is distributed freely under the terms of the GPL-3 license. The source code and all sequencing data are available at GitHub (https://github.com/thecodingdoc/SwarmTCR)[email protected]

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 TCR3d: The T cell receptor structural repertoire database

2019 ◽  
Vol 35 (24) ◽  
pp. 5323-5325 ◽  
Author(s):  
Ragul Gowthaman ◽  
Brian G Pierce
Keyword(s):  
T Cell ◽  
T Cell Receptors ◽  
Adaptive Immune System ◽  
Cell Receptor ◽  
Binding Mode ◽  
Computational Techniques ◽  
Antigen Specificity ◽  
Cell Receptors ◽  
Gene Usage ◽  
Mechanistic Basis

Abstract Summary T cell receptors (TCRs) are critical molecules of the adaptive immune system, capable of recognizing diverse antigens, including peptides, lipids and small molecules, and represent a rapidly growing class of therapeutics. Determining the structural and mechanistic basis of TCR targeting of antigens is a major challenge, as each individual has a vast and diverse repertoire of TCRs. Despite shared general recognition modes, diversity in TCR sequence and recognition represents a challenge to predictive modeling and computational techniques being developed to predict antigen specificity and mechanistic basis of TCR targeting. To this end, we have developed the TCR3d database, a resource containing all known TCR structures, with a particular focus on antigen recognition. TCR3d provides key information on antigen binding mode, interface features, loop sequences and germline gene usage. Users can interactively view TCR complex structures, search sequences of interest against known structures and sequences, and download curated datasets of structurally characterized TCR complexes. This database is updated on a weekly basis, and can serve the community as a centralized resource for those studying T cell receptors and their recognition. Availability and implementation The TCR3d database is available at https://tcr3d.ibbr.umd.edu/.

scholarly journals Tracking SARS-CoV-2 T cells with epitope-T-cell receptor recognition models

2020 ◽  
Author(s):  
Pieter Meysman ◽  
Anna Postovskaya ◽  
Nicolas De Neuter ◽  
Benson Ogunjimi ◽  
Kris Laukens
Keyword(s):  
T Cells ◽  
T Cell ◽  
T Cell Receptor ◽  
Adaptive Immune Response ◽  
Adaptive Immune System ◽  
Cell Receptor ◽  
Sequencing Data ◽  
Adaptive Immune ◽  
Cell Diversity ◽  
Longitudinal Profiles

Much is still not understood about the human adaptive immune response to SARS-CoV-2, the causative agent of COVID-19. In this paper, we demonstrate the use of machine learning to classify SARS-CoV-2 epitope specific T-cell clonotypes in T-cell receptor (TCR) sequencing data. We apply these models to public TCR data and show how they can be used to study T-cell longitudinal profiles in COVID-19 patients to characterize how the adaptive immune system reacts to the SARS-CoV-2 virus. Our findings confirm prior knowledge that SARS-CoV-2 reactive T-cell diversity increases over the course of disease progression. However our results show a difference between those T cells that react to epitope unique to SARS-CoV-2, which show a more prominent increase, and those T cells that react to epitopes common to other coronaviruses, which begin at a higher baseline.

scholarly journals Pre-T Cell Receptors (Pre-TCRs) Leverage Vβ Complementarity Determining Regions (CDRs) and Hydrophobic Patch in Mechanosensing Thymic Self-ligands

2016 ◽  
Vol 291 (49) ◽  
pp. 25292-25305 ◽  
Author(s):  
Dibyendu Kumar Das ◽  
Robert J. Mallis ◽  
Jonathan S. Duke-Cohan ◽  
Rebecca E. Hussey ◽  
Paul W. Tetteh ◽  
...  
Keyword(s):  
T Cell ◽  
T Cell Receptors ◽  
Cell Receptors ◽  
Hydrophobic Patch ◽  
Complementarity Determining Regions
Sign in / Sign up

Export Citation Format

Share Document