Beyond model antigens: high-dimensional methods for the analysis of antigen-specific T cells

Abstract

Adaptive immune responses often begin with the formation of a molecular complex between a T-cell receptor (TCR) and a peptide antigen bound to a major histocompatibility complex (MHC) molecule. These complexes are highly variable, however, due to the polymorphism of MHC genes, the random, inexact recombination of TCR gene segments, and the vast array of possible self and pathogen peptide antigens. As a result, it has been very difficult to comprehensively study the TCR repertoire or identify and track more than a few antigen-specific T cells in mice or humans. For mouse studies, this had led to a reliance on model antigens and TCR transgenes. The study of limited human clinical samples, in contrast, requires techniques that can simultaneously survey TCR phenotype and function, and TCR reactivity to many T-cell epitopes. Thanks to recent advances in single-cell and cytometry methodologies, as well as high-throughput sequencing of the TCR repertoire, we now have or will soon have the tools needed to comprehensively analyze T-cell responses in health and disease.

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Figure 1: Antigen recognition by the T-cell receptor and probing antigen specificity with peptide–MHC multimers.
Figure 2: Single-cell analysis can reveal heterogeneity in gene expression among T cells.
Figure 3: Highly multiplexed analysis of T-cell antigen specificity using mass cytometry–based combinatorial peptide–MHC tetramer staining.
Figure 4: Strategies for high-throughput single-cell analysis of TCR sequences and identification of TCR ligands.

References

  1. 1

    Burnet, F.M. A modification of Jerne's theory of antibody production using the concept of clonal selection. Aust. J. Sci. 20, 67–69 (1957).

    Google Scholar 

  2. 2

    Burnet, F.M. The Clonal Selection Theory of Acquired Immunity (Vanderbilt University Press, 1959).

  3. 3

    Hulett, H.R., Bonner, W.A., Barrett, J. & Herzenberg, L.A. Cell sorting: automated separation of mammalian cells as a function of intracellular fluorescence. Science 166, 747–749 (1969).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  4. 4

    Chattopadhyay, P.K. & Roederer, M. Cytometry: today's technology and tomorrow's horizons. Methods 57, 251–258 (2012).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  5. 5

    Han, Q., Bradshaw, E.M., Nilsson, B., Hafler, D.A. & Love, J.C. Multidimensional analysis of the frequencies and rates of cytokine secretion from single cells by quantitative microengraving. Lab Chip 10, 1391–1400 (2010).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  6. 6

    Han, Q. et al. Polyfunctional responses by human T cells result from sequential release of cytokines. Proc. Natl. Acad. Sci. USA 109, 1607–1612 (2012).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  7. 7

    Varadarajan, N. et al. Rapid, efficient functional characterization and recovery of HIV-specific human CD8+ T cells using microengraving. Proc. Natl. Acad. Sci. USA 109, 3885–3890 (2012).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  8. 8

    Betts, M.R. et al. HIV nonprogressors preferentially maintain highly functional HIV-specific CD8+ T cells. Blood 107, 4781–4789 (2006).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  9. 9

    Seder, R.A., Darrah, P.A. & Roederer, M. T-cell quality in memory and protection: implications for vaccine design. Nat. Rev. Immunol. 8, 247–258 (2008).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  10. 10

    Makedonas, G. & Betts, M.R. Living in a house of cards: re-evaluating CD8+ T-cell immune correlates against HIV. Immunol. Rev. 239, 109–124 (2011).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  11. 11

    Yuan, J. et al. CTLA-4 blockade enhances polyfunctional NY-ESO-1 specific T cell responses in metastatic melanoma patients with clinical benefit. Proc. Natl. Acad. Sci. USA 105, 20410–20415 (2008).

    CAS  PubMed  Article  Google Scholar 

  12. 12

    Walker, B.D. & Yu, X.G. Unravelling the mechanisms of durable control of HIV-1. Nat. Rev. Immunol. 13, 487–498 (2013).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  13. 13

    Precopio, M.L. et al. Immunization with vaccinia virus induces polyfunctional and phenotypically distinctive CD8+ T cell responses. J. Exp. Med. 204, 1405–1416 (2007).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  14. 14

    Yamanaka, Y.J., Gierahn, T.M. & Love, J.C. The dynamic lives of T cells: new approaches and themes. Trends Immunol. 34, 59–66 (2013).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  15. 15

    Akram, A. & Inman, R.D. Immunodominance: a pivotal principle in host response to viral infections. Clin. Immunol. 143, 99–115 (2012).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  16. 16

    Kiepiela, P. et al. CD8+ T-cell responses to different HIV proteins have discordant associations with viral load. Nat. Med. 13, 46–53 (2007).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  17. 17

    Pereyra, F. et al. Genetic and immunologic heterogeneity among persons who control HIV infection in the absence of therapy. J. Infect. Dis. 197, 563–571 (2008).

    PubMed  Article  PubMed Central  Google Scholar 

  18. 18

    Bowen, D.G. & Walker, C.M. Adaptive immune responses in acute and chronic hepatitis C virus infection. Nature 436, 946–952 (2005).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  19. 19

    Hislop, A.D., Annels, N.E., Gudgeon, N.H., Leese, A.M. & Rickinson, A.B. Epitope-specific evolution of human CD8+ T cell responses from primary to persistent phases of Epstein-Barr virus infection. J. Exp. Med. 195, 893–905 (2002).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  20. 20

    Newell, E.W. et al. Combinatorial tetramer staining and mass cytometry analysis facilitate T-cell epitope mapping and characterization. Nat. Biotechnol. 31, 623–629 (2013).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  21. 21

    Bendall, S.C. et al. Single-cell mass cytometry of differential immune and drug responses across a human hematopoietic continuum. Science 332, 687–696 (2011).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  22. 22

    Newell, E.W., Sigal, N., Bendall, S.C., Nolan, G.P. & Davis, M.M. Cytometry by time-of-flight shows combinatorial cytokine expression and virus-specific cell niches within a continuum of CD8+ T cell phenotypes. Immunity 36, 142–152 (2012).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  23. 23

    Hadrup, S.R. et al. Parallel detection of antigen-specific T-cell responses by multidimensional encoding of MHC multimers. Nat. Methods 6, 520–526 (2009).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  24. 24

    Newell, E.W., Klein, L.O., Yu, W. & Davis, M.M. Simultaneous detection of many T-cell specificities using combinatorial tetramer staining. Nat. Methods 6, 497–499 (2009).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  25. 25

    Dominguez, M.H. et al. Highly multiplexed quantitation of gene expression on single cells. J. Immunol. Methods 391, 133–145 (2013).

    CAS  PubMed  Article  Google Scholar 

  26. 26

    Shalek, A.K. et al. Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells. Nature 498, 236–240 (2013).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  27. 27

    Warren, E.H., Matsen, F.A.t. & Chou, J. High-throughput sequencing of B- and T-lymphocyte antigen receptors in hematology. Blood 122, 19–22 (2013).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  28. 28

    La Gruta, N.L. & Thomas, P.G. Interrogating the relationship between naive and immune antiviral T cell repertoires. Curr. Opin. Virol. 3, 447–451 (2013).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  29. 29

    Han, A. et al. Dietary gluten triggers concomitant activation of CD4+ and CD8+ alphabeta T cells and gammadelta T cells in celiac disease. Proc. Natl. Acad. Sci. USA 110, 13073–13078 (2013).

    CAS  PubMed  Article  Google Scholar 

  30. 30

    Zhu, J. et al. Immune surveillance by CD8alphaalpha+ skin-resident T cells in human herpes virus infection. Nature 497, 494–497 (2013).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  31. 31

    Emerson, R.O. et al. High-throughput sequencing of T cell receptors reveals a homogeneous repertoire of tumor-infiltrating lymphocytes in ovarian cancer. J. Pathol. 231, 433–440 (2013).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  32. 32

    Adams, J.J. et al. T cell receptor signaling is limited by docking geometry to peptide-major histocompatibility complex. Immunity 35, 681–693 (2011).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  33. 33

    Birnbaum, M.E., Dong, S. & Garcia, K.C. Diversity-oriented approaches for interrogating T-cell receptor repertoire, ligand recognition, and function. Immunol. Rev. 250, 82–101 (2012).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  34. 34

    Davis, M.M. & Bjorkman, P.J. T-cell antigen receptor genes and T-cell recognition. Nature 334, 395–402 (1988).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  35. 35

    Aghaeepour, N. et al. Critical assessment of automated flow cytometry data analysis techniques. Nat. Methods 10, 228–238 (2013).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  36. 36

    Qiu, P. et al. Extracting a cellular hierarchy from high-dimensional cytometry data with SPADE. Nat. Biotechnol. 29, 886–891 (2011).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  37. 37

    Finak, G. et al. Mixture models for single-cell assays with applications to vaccine studies. Biostatistics 15, 87–101 (2014).

    PubMed  Article  PubMed Central  Google Scholar 

  38. 38

    Amir, E.A. et al. viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia. Nat. Biotechnol. 31, 545–552 (2013).

    CAS  Article  Google Scholar 

  39. 39

    Sallusto, F., Lenig, D., Forster, R., Lipp, M. & Lanzavecchia, A. Two subsets of memory T lymphocytes with distinct homing potentials and effector functions. Nature 401, 708–712 (1999).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  40. 40

    Romero, P. et al. Four functionally distinct populations of human effector-memory CD8+ T lymphocytes. J. Immunol. 178, 4112–4119 (2007).

    CAS  PubMed  Article  Google Scholar 

  41. 41

    Gattinoni, L. et al. A human memory T cell subset with stem cell-like properties. Nat. Med. 17, 1290–1297 (2011).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  42. 42

    Kaech, S.M. & Cui, W. Transcriptional control of effector and memory CD8+ T cell differentiation. Nat. Rev. Immunol. 12, 749–761 (2012).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  43. 43

    Masopust, D. & Schenkel, J.M. The integration of T cell migration, differentiation and function. Nat. Rev. Immunol. 13, 309–320 (2013).

    CAS  PubMed  Article  Google Scholar 

  44. 44

    Ornatsky, O., Baranov, V.I., Bandura, D.R., Tanner, S.D. & Dick, J. Multiple cellular antigen detection by ICP-MS. J. Immunol. Methods 308, 68–76 (2006).

    CAS  Article  Google Scholar 

  45. 45

    Bjornson, Z.B., Nolan, G.P. & Fantl, W.J. Single-cell mass cytometry for analysis of immune system functional states. Curr. Opin. Immunol. 25, 484–494 (2013).

    CAS  PubMed  Article  Google Scholar 

  46. 46

    Bodenmiller, B. et al. Multiplexed mass cytometry profiling of cellular states perturbed by small-molecule regulators. Nat. Biotechnol. 30, 858–867 (2012).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  47. 47

    Kidd, B.A., Peters, L.A., Schadt, E.E. & Dudley, J.T. Unifying immunology with informatics and multiscale biology. Nat. Immunol. 15, 118–127 (2014).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  48. 48

    Shapiro, E., Biezuner, T. & Linnarsson, S. Single-cell sequencing-based technologies will revolutionize whole-organism science. Nat. Rev. Genet. 14, 618–630 (2013).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  49. 49

    Flatz, L. et al. Single-cell gene-expression profiling reveals qualitatively distinct CD8 T cells elicited by different gene-based vaccines. Proc. Natl. Acad. Sci. USA 108, 5724–5729 (2011).

    CAS  PubMed  Article  Google Scholar 

  50. 50

    Tang, F. et al. mRNA-Seq whole-transcriptome analysis of a single cell. Nat. Methods 6, 377–382 (2009).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  51. 51

    Brunner, K.T., Mauel, J., Cerottini, J.C. & Chapuis, B. Quantitative assay of the lytic action of immune lymphoid cells on 51-Cr-labelled allogeneic target cells in vitro; inhibition by isoantibody and by drugs. Immunology 14, 181–196 (1968).

    CAS  PubMed  PubMed Central  Google Scholar 

  52. 52

    Peters, P.J. et al. Cytotoxic T lymphocyte granules are secretory lysosomes, containing both perforin and granzymes. J. Exp. Med. 173, 1099–1109 (1991).

    CAS  PubMed  Article  Google Scholar 

  53. 53

    Betts, M.R. et al. Sensitive and viable identification of antigen-specific CD8+ T cells by a flow cytometric assay for degranulation. J. Immunol. Methods 281, 65–78 (2003).

    CAS  PubMed  Article  Google Scholar 

  54. 54

    Waldrop, S.L., Pitcher, C.J., Peterson, D.M., Maino, V.C. & Picker, L.J. Determination of antigen-specific memory/effector CD4+ T cell frequencies by flow cytometry: evidence for a novel, antigen-specific homeostatic mechanism in HIV-associated immunodeficiency. J. Clin. Invest. 99, 1739–1750 (1997).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  55. 55

    De Rosa, S.C. et al. Vaccination in humans generates broad T cell cytokine responses. J. Immunol. 173, 5372–5380 (2004).

    CAS  PubMed  Article  Google Scholar 

  56. 56

    Frentsch, M. et al. Direct access to CD4+ T cells specific for defined antigens according to CD154 expression. Nat. Med. 11, 1118–1124 (2005).

    CAS  PubMed  Article  Google Scholar 

  57. 57

    Altman, J.D. et al. Phenotypic analysis of antigen-specific T lymphocytes. Science 274, 94–96 (1996).

    CAS  Article  Google Scholar 

  58. 58

    Davis, M.M., Altman, J.D. & Newell, E.W. Interrogating the repertoire: broadening the scope of peptide-MHC multimer analysis. Nat. Rev. Immunol. 11, 551–558 (2011).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  59. 59

    Toebes, M. et al. Design and use of conditional MHC class I ligands. Nat. Med. 12, 246–251 (2006).

    CAS  Article  Google Scholar 

  60. 60

    Grotenbreg, G.M. et al. Discovery of CD8+ T cell epitopes in Chlamydia trachomatis infection through use of caged class I MHC tetramers. Proc. Natl. Acad. Sci. USA 105, 3831–3836 (2008).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  61. 61

    Day, C.L. et al. Ex vivo analysis of human memory CD4 T cells specific for hepatitis C virus using MHC class II tetramers. J. Clin. Invest. 112, 831–842 (2003).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  62. 62

    Moon, J.J. et al. Naive CD4+ T cell frequency varies for different epitopes and predicts repertoire diversity and response magnitude. Immunity 27, 203–213 (2007).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  63. 63

    Andersen, R.S. et al. Parallel detection of antigen-specific T cell responses by combinatorial encoding of MHC multimers. Nat. Protoc. 7, 891–902 (2012).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  64. 64

    Chang, C.X. et al. Sources of diversity in T cell epitope discovery. Front. Biosci. (Landmark Ed.) 16, 3014–3035 (2011).

    CAS  Article  Google Scholar 

  65. 65

    Assarsson, E. et al. Immunomic analysis of the repertoire of T-cell specificities for influenza A virus in humans. J. Virol. 82, 12241–12251 (2008).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  66. 66

    Maciel, M. Jr. et al. Comprehensive analysis of T cell epitope discovery strategies using 17DD yellow fever virus structural proteins and BALB/c (H2d) mice model. Virology 378, 105–117 (2008).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  67. 67

    Weiskopf, D. et al. Comprehensive analysis of dengue virus-specific responses supports an HLA-linked protective role for CD8+ T cells. Proc. Natl. Acad. Sci. USA 110, E2046–E2053 (2013).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  68. 68

    Hoof, I. et al. Interdisciplinary analysis of HIV-specific CD8+ T cell responses against variant epitopes reveals restricted TCR promiscuity. J. Immunol. 184, 5383–5391 (2010).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  69. 69

    Lundegaard, C. et al. NetMHC-3.0: accurate web accessible predictions of human, mouse and monkey MHC class I affinities for peptides of length 8–11. Nucleic Acids Res. 36, W509–W512 (2008).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  70. 70

    Wee, L.J., Lim, S.J., Ng, L.F. & Tong, J.C. Immunoinformatics: how in silico methods are re-shaping the investigation of peptide immune specificity. Front. Biosci. (Elite Ed.) 4, 311–319 (2012).

    Article  Google Scholar 

  71. 71

    Rivino, L. et al. Defining CD8+ T cell determinants during human viral infection in populations of Asian ethnicity. J. Immunol. 191, 4010–4019 (2013).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  72. 72

    Yang, J. et al. Multiplex mapping of CD4 T cell epitopes using class II tetramers. Clin. Immunol. 120, 21–32 (2006).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  73. 73

    Heemskerk, B., Kvistborg, P. & Schumacher, T.N. The cancer antigenome. EMBO J. 32, 194–203 (2013).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  74. 74

    van Rooij, N. et al. Tumor exome analysis reveals neoantigen-specific T-cell reactivity in an ipilimumab-responsive melanoma. J. Clin. Oncol. 31, e439–e442 (2013).

    Article  Google Scholar 

  75. 75

    Rotzschke, O. et al. Isolation and analysis of naturally processed viral peptides as recognized by cytotoxic T cells. Nature 348, 252–254 (1990).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  76. 76

    Marrack, P., Ignatowicz, L., Kappler, J.W., Boymel, J. & Freed, J.H. Comparison of peptides bound to spleen and thymus class II. J. Exp. Med. 178, 2173–2183 (1993).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  77. 77

    Fortier, M.H. et al. The MHC class I peptide repertoire is molded by the transcriptome. J. Exp. Med. 205, 595–610 (2008).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  78. 78

    Kasuga, K. Comprehensive analysis of MHC ligands in clinical material by immunoaffinity-mass spectrometry. Methods Mol. Biol. 1023, 203–218 (2013).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  79. 79

    Baker, E.S. et al. Mass spectrometry for translational proteomics: progress and clinical implications. Genome Med. 4, 63 (2012).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  80. 80

    Robins, H.S. et al. Comprehensive assessment of T-cell receptor beta-chain diversity in alphabeta T cells. Blood 114, 4099–4107 (2009).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  81. 81

    Robins, H.S. et al. Overlap and effective size of the human CD8+ T cell receptor repertoire. Sci. Transl. Med. 2, 47ra64 (2010).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  82. 82

    Venturi, V. et al. A mechanism for TCR sharing between T cell subsets and individuals revealed by pyrosequencing. J. Immunol. 186, 4285–4294 (2011).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  83. 83

    Arstila, T.P. et al. A direct estimate of the human alphabeta T cell receptor diversity. Science 286, 958–961 (1999).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  84. 84

    Klarenbeek, P.L. et al. Human T-cell memory consists mainly of unexpanded clones. Immunol. Lett. 133, 42–48 (2010).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  85. 85

    Dziubianau, M. et al. TCR repertoire analysis by next generation sequencing allows complex differential diagnosis of T cell-related pathology. Am. J. Transplant. 13, 2842–2854 (2013).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  86. 86

    Boyd, S.D., Liu, Y., Wang, C., Martin, V. & Dunn-Walters, D.K. Human lymphocyte repertoires in ageing. Curr. Opin. Immunol. 25, 511–515 (2013).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  87. 87

    Wu, D. et al. High-throughput sequencing detects minimal residual disease in acute T lymphoblastic leukemia. Sci. Transl. Med. 4, 134ra163 (2012).

    Article  CAS  Google Scholar 

  88. 88

    DeKosky, B.J. et al. High-throughput sequencing of the paired human immunoglobulin heavy and light chain repertoire. Nat. Biotechnol. 31, 166–169 (2013).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  89. 89

    Turchaninova, M.A. et al. Pairing of T-cell receptor chains via emulsion PCR. Eur. J. Immunol. 43, 2507–2515 (2013).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  90. 90

    Sollid, L.M. & Jabri, B. Triggers and drivers of autoimmunity: lessons from coeliac disease. Nat. Rev. Immunol. 13, 294–302 (2013).

    CAS  PubMed  Article  Google Scholar 

  91. 91

    Reay, P.A., Kantor, R.M. & Davis, M.M. Use of global amino acid replacements to define the requirements for MHC binding and T cell recognition of moth cytochrome c (93–103). J. Immunol. 152, 3946–3957 (1994).

    CAS  PubMed  Google Scholar 

  92. 92

    Garcia, K.C., Teyton, L. & Wilson, I.A. Structural basis of T cell recognition. Annu. Rev. Immunol. 17, 369–397 (1999).

    CAS  PubMed  Article  Google Scholar 

  93. 93

    Wu, L.C., Tuot, D.S., Lyons, D.S., Garcia, K.C. & Davis, M.M. Two-step binding mechanism for T-cell receptor recognition of peptide MHC. Nature 418, 552–556 (2002).

    CAS  PubMed  Article  Google Scholar 

  94. 94

    Janin, J. Protein-protein docking tested in blind predictions: the CAPRI experiment. Mol. Biosyst. 6, 2351–2362 (2010).

    CAS  PubMed  Article  Google Scholar 

  95. 95

    Ritchie, D.W. Recent progress and future directions in protein-protein docking. Curr. Protein Pept. Sci. 9, 1–15 (2008).

    CAS  PubMed  Article  Google Scholar 

  96. 96

    Reiser, J.B. et al. CDR3 loop flexibility contributes to the degeneracy of TCR recognition. Nat. Immunol. 4, 241–247 (2003).

    CAS  PubMed  Article  Google Scholar 

  97. 97

    Su, L.F., Kidd, B.A., Han, A., Kotzin, J.J. & Davis, M.M. Virus-specific CD4+ memory-phenotype T cells are abundant in unexposed adults. Immunity 38, 373–383 (2013).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  98. 98

    Su, L.F. & Davis, M.M. Antiviral memory phenotype T cells in unexposed adults. Immunol. Rev. 255, 95–109 (2013).

    PubMed  Article  CAS  Google Scholar 

  99. 99

    Parameswaran, P. et al. Convergent antibody signatures in human dengue. Cell Host Microbe 13, 691–700 (2013).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  100. 100

    Crawford, F. et al. Use of baculovirus MHC/peptide display libraries to characterize T-cell receptor ligands. Immunol. Rev. 210, 156–170 (2006).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  101. 101

    Stadinski, B.D. et al. Chromogranin A is an autoantigen in type 1 diabetes. Nat. Immunol. 11, 225–231 (2010).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  102. 102

    Wen, F., Esteban, O. & Zhao, H. Rapid identification of CD4+ T-cell epitopes using yeast displaying pathogen-derived peptide library. J. Immunol. Methods 336, 37–44 (2008).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  103. 103

    Harvey, C.J. & Wucherpfennig, K.W. Cracking the code of human T-cell immunity. Nat. Biotechnol. 31, 609–610 (2013).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

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Newell, E., Davis, M. Beyond model antigens: high-dimensional methods for the analysis of antigen-specific T cells. Nat Biotechnol 32, 149–157 (2014). https://doi.org/10.1038/nbt.2783

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