CD4+ T cells are critical to fighting pathogens, but a comprehensive analysis of human T-cell specificities is hindered by the diversity of HLA alleles (>20,000) and the complexity of many pathogen genomes. We previously described GLIPH, an algorithm to cluster T-cell receptors (TCRs) that recognize the same epitope and to predict their HLA restriction, but this method loses efficiency and accuracy when >10,000 TCRs are analyzed. Here we describe an improved algorithm, GLIPH2, that can process millions of TCR sequences. We used GLIPH2 to analyze 19,044 unique TCRβ sequences from 58 individuals latently infected with Mycobacterium tuberculosis (Mtb) and to group them according to their specificity. To identify the epitopes targeted by clusters of Mtb-specific T cells, we carried out a screen of 3,724 distinct proteins covering 95% of Mtb protein-coding genes using artificial antigen-presenting cells (aAPCs) and reporter T cells. We found that at least five PPE (Pro-Pro-Glu) proteins are targets for T-cell recognition in Mtb.
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The data supporting the findings of this study are available within the paper and in its Supplementary Information files.
Two compiled standalone versions of GLIPH2 (Executable for MacOS ≥ 10.14.14 and Linux server Centos 7) are provided as Supplementary Code. Also, a web tool for GLIPH2 analysis is available at http://18.104.22.168:8080/.
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We would like to thank the Stanford Human Immune Monitoring Center for their high-throughput sequencing support for this project, M. Mindrinos and co-workers at Sirona Genomics for the HLA typing, S. Xue (Department of Immunology, University College London) for providing the Jurkat 76 T-cell line, J. Li for providing HLA-typed PBMCs, L. Chen and S. Chiou for valuable discussions regarding GLIPH2 optimization, H. Mahomed, W. Hanekom and members of the Adolescent Cohort Study (ACS) group for enrolment and follow-up of the Mtb-infected adolescents, R. DiFazio for help making the schematic overview and Y. Chien for constructive criticism of the manuscript, and J. Pavlovitch-Bedzyk for proofreading. This work was supported by the Bill and Melinda Gates Foundation (grant OPP1113682) and the Howard Hughes Medical Institute.
The authors declare no competing interests.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Figures 1–7
Mtb-specific TCR sequences and summary
TCR sequences from VDJdb
TCR specificity groups from GLIPH2 analysis
Gene list of the whole Mtb ORF clone set
Two compiled standalone versions of GLIPH2
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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. Nat Biotechnol (2020). https://doi.org/10.1038/s41587-020-0505-4
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