Identifying specificity groups in the T cell receptor repertoire
Open accessAbstract
T cell receptor (TCR) sequences are very diverse, with many more possible sequence combinations than T cells in any one individual. Here we define the minimal requirements for TCR antigen specificity, through an analysis of TCR sequences using a panel of peptide and major histocompatibility complex (pMHC)-tetramer-sorted cells and structural data. From this analysis we developed an algorithm that we term GLIPH (grouping of lymphocyte interactions by paratope hotspots) to cluster TCRs with a high probability of sharing specificity owing to both conserved motifs and global similarity of complementarity-determining region 3 (CDR3) sequences. We show that GLIPH can reliably group TCRs of common specificity from different donors, and that conserved CDR3 motifs help to define the TCR clusters that are often contact points with the antigenic peptides. As an independent validation, we analysed 5,711 TCRβ chain sequences from reactive CD4 T cells from 22 individuals with latent Mycobacterium tuberculosis infection. We found 141 TCR specificity groups, including 16 distinct groups containing TCRs from multiple individuals. These TCR groups typically shared HLA alleles, allowing prediction of the likely HLA restriction, and a large number of M. tuberculosis T cell epitopes enabled us to identify pMHC ligands for all five of the groups tested. Mutagenesis and de novo TCR design confirmed that the GLIPH-identified motifs were critical and sufficient for shared-antigen recognition. Thus the GLIPH algorithm can analyse large numbers of TCR sequences and define TCR specificity groups shared by TCRs and individuals, which should greatly accelerate the analysis of T cell responses and expedite the identification of specific ligands.
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The GLIPH algorithm is designed to identify motifs predicted to bind the same MHC/peptide antigen.
“the GLIPH algorithm that is designed to identify motifs predicted to bind the same MHC/peptide antigen 41,42”
From Amphiregulin from regulatory T cells promotes liver fibrosis and insulin resistance in non-alcoholic steatohepatitis (2024) · cites this paper as [41]
AIRs with similar sequences are likely to have common specificity.
“A second approach compares AIRs using distance metrics applied to the CDR3 sequences directly or an embedding of the sequences, as AIRs with similar sequences are likely to have common specificity183.”
From Best practices for single-cell analysis across modalities (2023) · cites this paper as [183]
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- Authors
- Glanville, J., Huang, H., Nau, A., Hatton, O., Wagar, L. E., Rubelt, F., Ji, X., Han, A., Krams, S. M., Pettus, C., Haas, N., Arlehamn, C. S. L., Sette, A., Boyd, S. D., Scriba, T. J., Martinez, O. M., & Davis, M. M.
- Affiliations
- Stanford Medicine (US)
- University of San Francisco (US)
- La Jolla Institute for Immunology (US)
- University of Cape Town (ZA)
- Howard Hughes Medical Institute (US)
- Corresponding author
- Davis, Mark M.
- ORCID
- Venue
- Nature
- Published
- 2017-06-21
- Volume
- 547
- Issue
- 7661
- Pages
- 94-98
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC5794212
- OpenAlex
- W2670890989
- Cited by
- 1,026
- References
- 23
- Citations by year
- 2026: 95 · 2025: 117 · 2024: 130 · 2023: 133 · 2022: 104 · 2021: 133 · 2020: 108 · 2019: 101 · 2018: 77 · 2017: 28
- FWCI
- 35.31
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- National Institutes of Health
- National Institute of Allergy and Infectious Diseases (R37AI022511, U19AI057229, L30 AI113847)
- National Institute of Diabetes and Digestive and Kidney Diseases (K08DK100739, L30 DK089634)
- National Center for Research Resources (S10RR025518)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › vaccines and immunoinformatics approaches
- Life Sciences › Immunology and Microbiology › Immunology › T-cell and B-cell Immunology
- Life Sciences › Immunology and Microbiology › Immunology › Immunotherapy and Immune Responses
- Keywords
- T cell receptor repertoire, TCR specificity, HLA restriction, CDR3 motifs, TCR clustering, latent tuberculosis infection, epitope prediction, CD4+ T cells
- MeSH terms
- Adolescent, Algorithms, Amino Acid Sequence, HLA Antigens, Humans, Ligands, Models, Molecular, Mycobacterium tuberculosis, Receptors, Antigen, T-Cell, Substrate Specificity, Crystallography, X-Ray, Epitopes, T-Lymphocyte
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