1. Computational and Systems Biology
  2. Immunology and Inflammation

TCR meta-clonotypes for biomarker discovery with tcrdist3 enabled identification of public, HLA-restricted clusters of SARS-CoV-2 TCRs

  1. Koshlan Mayer-Blackwell
  2. Stefan Schattgen
  3. Liel Cohen-Lavi
  4. Jeremy C Crawford
  5. Aisha Souquette
  6. Jessica A Gaevert
  7. Tomer Hertz
  8. Paul G Thomas
  9. Philip G Bradley
  10. Andrew Fiore-Gartland  Is a corresponding author
  1. Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, United States
  2. Department of Immunology, St Jude Children's Research Hospital, United States
  3. Department of Industrial Engineering and Management, Ben-Gurion University of the Negev, Israel
  4. St Jude Children's Research Hospital, United States
  5. Shraga Segal Department of Microbiology and Immunology, Ben-Gurion University of the Negev, United States
  6. Fred Hutchinson Cancer Research Center, United States
https://doi.org/10.7554/eLife.68605
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Cite this article
  1. Koshlan Mayer-Blackwell
  2. Stefan Schattgen
  3. Liel Cohen-Lavi
  4. Jeremy C Crawford
  5. Aisha Souquette
  6. Jessica A Gaevert
  7. Tomer Hertz
  8. Paul G Thomas
  9. Philip G Bradley
  10. Andrew Fiore-Gartland
(2021)
TCR meta-clonotypes for biomarker discovery with tcrdist3 enabled identification of public, HLA-restricted clusters of SARS-CoV-2 TCRs
eLife 10:e68605.
https://doi.org/10.7554/eLife.68605
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13 figures, 1 table and 2 additional files

Figures

Figure 1
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T-cell receptor (TCR) meta-clonotypes.

(A) Defining meta-clonotypes from antigen-associated TCRs. Sets of antigen-associated TCRs were used together with synthetic background repertoires to engineer TCR meta-clonotypes that define …

Figure 2
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TCRdist compared to edit distance.

(A) Correspondence between edit distance (x-axis) and TCRdist (y-axis) for MIRA55 T-cell receptors (TCRs) with matching TRBV genes. The grayscale colormap shows the percentage of TCRs with a given …

Figure 3
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Experimental enrichment of antigen-associated T-cell receptors (TCRs) increases neighbor density.

(A) TCR repertoire subsets obtained by single-cell sorting with peptide–major histocompatibility complex (MHC) tetramers (green), MIRA peptide stimulation enrichment (MIRA55, MIRA48; purple), or …

Figure 4
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T-cell receptor (TCR) neighborhoods have higher density among TCRs that have been experimentally enriched for antigen-specific T cells compare to unenriched repertoires.

TCR β-chains from (A) a peptide–major histocompatibility complex (MHC) tetramer-enriched subrepertoire (n = 247), (B) a MIRA peptide stimulation-enriched subrepertoire (n = 497), or (C) an umbilical …

Figure 5
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Radius-defined neighborhood densities within an antigen-associated and a synthetic background repertoire.

(A) Each T-cell receptor (TCR) (one line, n = 497) in the MIRA55 antigen-associated set acts as the centroid of a neighborhood and an empirical cumulative distribution function (ECDF) is estimated …

Figure 6
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Publicity analysis in MIRA participants of CD8+ T-cell receptor (TCR) β-chain features activated by SARS-CoV-2 peptide ORF1ab (MIRA55) predicted to bind HLA-A*01.

The grid shows all features that were present in two or more MIRA participants. TCR feature publicity across individuals was assessed using two methods: (1) tcrdist3 meta-clonotypes (rectangles) – …

Figure 7
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Sensitivity of optimized meta-clonotype radius to background size and specification.

(A) Radius estimates for MIRA55 T-cell receptors (TCRs) using different synthetic backgrounds: (i) randomly generated TCRs from Optimized Likelihood estimate of Immunoglobulin Amino acid sequences …

Figure 8
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HLA restriction of T-cell receptor (TCR) clonotypes and meta-clonotypes in bulk-sequenced TCRβ repertoires of COVID-19 patients.

(A) Percentage of TCR features with a statistically significant (false discovery rate [FDR] <0.01) association with a restricting HLA allele. We tested for associations between patients’ inferred …

Figure 9
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Associations of T-cell receptor (TCR) features with participant age, days postdiagnosis, HLA genotype, and sex in TCR β-chain repertoires of COVID-19 patients (n = 694).

(A) Beta-binomial regression coefficient estimates (x-axis) and negative log10 false discovery rates (y-axis) for features developed from CD8+ TCRs activated by SARS-CoV-2 MIRA55 ORF1ab amino acids …

Figure 10
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Meta-clonotypes provide opportunities to investigate basis of antigen specificity.

Logo plots of T-cell receptors (TCRs) from bulk repertoires of acute and convalescent COVID-19 patients (n = 694) within 20 TCRdist units of MIRA-identified TCR β-chain meta-clonotype M_55_1E6+ …

Figure 11
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Publicity and breadth analysis of CD8+ T-cell receptor (TCR) β-chain features activated by SARS-CoV-2 peptide ORF1ab (MIRA55) using tcrdist3 and GLIPH2.

TCR feature publicity was determined using two methods for clustering similar TCR sequences: (A) tcrdist3-identified meta-clonotypes and (B) GLIPH2 specificity groups, sets of TCRs with a shared …

Figure 12
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Associations between HLA genotypes in COVID-19 patients and abundance of epitope-specific complementarity determining region (CDR)3 k-mers or meta-clonotypes.

(A) Beta-binomial regression coefficient estimates (x-axis) for participant genotype matching a hypothesized restricting HLA allele and negative log10 false discovery rates (FDRs; y-axis) for …

Figure 13
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Detectable HLA association and complementarity determining region (CDR)3 probability of generation.

We evaluated 1831 meta-clonotypes from 17 MIRA sets in a cohort of 694 COVID-19 patients for their association with predicted HLA-restricting alleles. Statistical evidence of the HLA association for …

Tables

Key resources table
Reagent type (species) or resourceDesignationSource or referenceIdentifiersAdditional information
Software, algorithmPython3,Numpy,Pandas,Python Programming Language, RRID:SCR_008394NumPy, RRID:SCR_00863Pandas, RRID:SCR_01821
Software, algorithmR, ggplot2R Project for Statistical Computing, RRID:SCR_001905ggplot2, RRID:SCR_014601
Software, algorithmtcrdist3This studytcrdist3 0.2.0https://github.com/kmayerb/tcrdist3
Software, algorithmpwseqdistThis studypwseqdist 0.5https://github.com/agartland/pwseqdist
Script, algorithmhla3This studyversion 0.1.0https://github.com/kmayerb/hla3
Software, algorithmcorncobMartin et al., 2020 doi:10.1214/19-aoas1283https://github.com/bryandmartin/corncob (Martin, 2021)
Software, algorithmOLGASethna et al., 201910.1093/bioinformatics/btz035https://github.com/statbiophys/OLGA(Isacchini, 2021) See slight modifications in: https://github.com/kmayerb/tcrdist3/blob/master/tcrdist/olga_directed.py
Software, algorithmGLIPH2Huang et al., 202010.1038/s41587-020-0505-4version 2http://50.255.35.37:8,080

Additional files

Transparent reporting form
https://cdn.elifesciences.org/articles/68605/elife-68605-transrepform1-v1.pdf
Supplementary file 1

Supporting data and analysis results.

https://cdn.elifesciences.org/articles/68605/elife-68605-supp1-v1.xlsx

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