Neighborhood enrichment for the identification of antigen-specific T-cell receptors

. 2025 Aug 31 ; 26 (5) : .

Jazyk angličtina Země Velká Británie, Anglie Médium print

Typ dokumentu časopisecké články

Perzistentní odkaz   https://www.medvik.cz/link/pmid40996146

Grantová podpora
075-15-2025-598, June 25, 2025 Ministry of Science and Higher Education of the Russian Federation (the Federal Scientific-technical programme for genetic technologies development for 2019-2030

Understanding T-cell receptor (TCR) specificity is not only essential for fundamental research, but could open up novel avenues for diagnostics, cancer immunotherapy, and the targeted treatment of autoimmune diseases. The immune system responds to challenges through groups of T-cells with similar TCR sequences. In recent years, searching for TCRs with an enrichment of similar sequences - neighbors - in a TCR repertoire has become a standard procedure for antigen-specific TCR identification. This study provides a systematic comparison of computational algorithms-ALICE, TCRNET, GLIPH2, and tcrdist3-that leverage neighborhood enrichment for antigen-specific TCR identification. Using published murine datasets from Lymphocytic choriomeningitis virus (LCMV) infection and novel datasets from Sputnik V vaccination and Mycobacterium tuberculosis (Mtb) infection, we evaluated the performance of these algorithms. To facilitate reproducible analysis, we developed TCRgrapher, an R library that integrates these pipelines into a user-friendly framework. TCRgrapher enables efficient identification of antigen-specific TCRs from single repertoire snapshots and supports flexible parameter customization. Our comparative analysis revealed that ALICE and TCRNET consistently outperformed GLIPH2 and tcrdist3 across most datasets, achieving higher area under precision-recall curve. While murine datasets provide valuable insights into algorithm performance, caution is advised when extrapolating these results to other species or different experimental conditions. TCRgrapher is freely available on GitHub (https://github.com/KseniaMIPT/tcrgrapher), offering researchers a robust tool for investigating TCR specificity and advancing immunological studies.

Zobrazit více v PubMed

Klein  L, Kyewski  B, Allen  PM. et al.  Positive and negative selection of the T-cell repertoire: what thymocytes see (and don’t see). PubMed DOI PMC

Qi  Q, Liu  Y, Cheng  Y. et al.  Diversity and clonal selection in the human T-cell repertoire. PubMed DOI PMC

Bagaev  DV, Vroomans  RMA, Samir  J. et al.  VDJdb in 2019: database extension, new analysis infrastructure and a T-cell receptor motif compendium. DOI

Baulu  E, Gardet  C, Chuvin  N. et al.  TCR-engineered T-cell therapy in solid tumors: state of the art and perspectives. PubMed DOI PMC

Britanova  OV, Lupyr  KR, Staroverov  DB. et al.  Targeted depletion of TRBV9+ T-cells as immunotherapy in a patient with ankylosing spondylitis. PubMed DOI PMC

Uenishi  GI, Repic  M, Yam  JY. et al.  GNTI-122: an autologous antigen-specific engineered Treg cell therapy for type 1 diabetes. DOI

Meysman  P, De Neuter  N, Gielis  S. et al.  On the viability of unsupervised T-cell receptor sequence clustering for epitope preference. PubMed DOI

Venturi  V, Kedzierska  K, Price  DA. et al.  Sharing of T-cell receptors in antigen-specific responses is driven by convergent recombination. PubMed DOI PMC

Huang  H, Wang  C, Rubelt  F. et al.  Analyzing the mycobacterium tuberculosis immune response by T-cell receptor clustering with GLIPH2 and genome-wide antigen screening. PubMed DOI PMC

Zhang  H, Liu  L, Zhang  J. et al.  Investigation of antigen-specific T-cell receptor clusters in human cancers. PubMed DOI

Mayer-Blackwell  K, Schattgen  S, Cohen-Lavi  L. et al.  TCR meta-clonotypes for biomarker discovery with tcrdist3: identification of public, HLA-restricted SARS-CoV-2 associated TCR features. eLife  10:e68605. 10.7554/eLife.68605 DOI

Valkiers  S, Van Houcke  M, Laukens  K. et al.  ClusTCR: a python interface for rapid clustering of large sets of CDR3 sequences with unknown antigen specificity. PubMed DOI

Zhang  H, Zhan  X, Li  B. GIANA allows computationally-efficient TCR clustering and multi-disease repertoire classification by isometric transformation. PubMed DOI PMC

Shlesinger  D, Hong  K-L, Shammas  G. et al.  Single-cell immune repertoire sequencing of B and T-cells in murine models of infection and autoimmunity. PubMed DOI PMC

Khatun  A, Kasmani  MY, Zander  R. et al.  Single-cell lineage mapping of a diverse virus-specific naive CD4 T-cell repertoire. DOI

Tsareva  A, Shelyakin  PV, Shagina  IA. et al.  Aberrant adaptive immune response underlies genetic susceptibility to tuberculosis. PubMed DOI PMC

Pogorelyy  MV, Minervina  AA, Shugay  M. et al.  Detecting T-cell receptors involved in immune responses from single repertoire snapshots. PubMed DOI PMC

Marcou  Q, Mora  T, Walczak  AM. High-throughput immune repertoire analysis with IGoR. PubMed DOI PMC

Sethna  Z, Elhanati  Y, Callan  CG. et al.  OLGA: fast computation of generation probabilities of B- and T-cell receptor amino acid sequences and motifs. PubMed DOI PMC

Sethna Z, Isacchini G, Dupic T, Mora T, Walczak AM. et al. Population variability in the generation and selection of T-cell repertoires. PLOS Computational Biology 2020;16:e1008394. 10.1371/journal.pcbi.1008394 DOI

Pogorelyy  MV, Shugay  M. A framework for annotation of antigen specificities in high-throughput T-cell repertoire sequencing studies. PubMed DOI PMC

Ritvo  P-G, Saadawi  A, Barennes  P. et al.  High-resolution repertoire analysis reveals a major bystander activation of Tfh and Tfr cells. PubMed DOI PMC

Logunov  DY, Dolzhikova  IV, Shcheblyakov  DV. et al.  Safety and efficacy of an rAd26 and rAd5 vector-based heterologous prime-boost COVID-19 vaccine: an interim analysis of a randomised controlled phase 3 trial in Russia. PubMed DOI PMC

Davis  J, Goadrich  M. The relationship between precision-recall and ROC curves. In: Proceedings of the 23rd international conference on Machine learning—ICML ‘06. New York, New York, USA: ACM Press, 2006.   10.1145/1143844.1143874 DOI

Homann  D, Lewicki  H, Brooks  D. et al.  Mapping and restriction of a dominant viral CD4+ T-cell core epitope by both MHC class I and MHC class II. PubMed DOI PMC

Izraelson  M, Nakonechnaya TO, Moltedo  B. et al.  Comparative analysis of murine T-cell receptor repertoires. PubMed DOI PMC

Hudson  D, Fernandes  RA, Basham  M. et al.  Can we predict T-cell specificity with digital biology and machine learning? PubMed DOI PMC

Sabatino  JJ  Jr, Huang  J, Zhu  C. et al.  High prevalence of low affinity peptide-MHC II tetramer-negative effectors during polyclonal CD4+ T-cell responses. PubMed DOI PMC

Lyons  GE, Roszkowski  JJ, Man  S. et al.  T-cell receptor tetramer binding or the lack there of does not necessitate antigen reactivity in T-cell receptor transduced T-cells. PubMed DOI PMC

Zheng G, Terry J, Belgrader P. et al. Massively parallel digital transcriptional profiling of single cells. Nat Commun 2017;8:14049. 10.1038/ncomms14049 DOI

Shugay  M, Britanova  OV, Merzlyak  EM. et al.  Towards error-free profiling of immune repertoires. PubMed DOI

Bolotin  DA, Poslavsky  S, Mitrophanov  I. et al.  MiXCR: software for comprehensive adaptive immunity profiling. PubMed DOI

Shugay  M, Bagaev  DV, Turchaninova  MA. et al.  VDJtools: unifying post-analysis of T-cell receptor repertoires. PubMed DOI PMC

Giudicelli  V, Chaume  D, Lefranc  M-P. IMGT/GENE-DB: a comprehensive database for human and mouse immunoglobulin and T-cell receptor genes. PubMed DOI PMC

Elhanati  Y, Sethna  Z, Callan  CG  Jr. et al.  Predicting the spectrum of TCR repertoire sharing with a data-driven model of recombination. PubMed DOI PMC

Wickham H. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York. 2016. https://ggplot2.tidyverse.org

Saito  T, Rehmsmeier  M. Precrec: fast and accurate precision-recall and ROC curve calculations in R. PubMed DOI PMC

Bastian  M, Heymann  S, Jacomy  M. Gephi: An open source software for exploring and manipulating networks. Proceedings of the International AAAI Conference on Web and Social Media, Vol. 3, pp. 361–2, 2009.   10.1609/icwsm.v3i1.13937 DOI

Najít záznam

Citační ukazatele

Nahrávání dat ...

Možnosti archivace

Nahrávání dat ...