Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Review Article
  • Published:

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.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

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.

Similar content being viewed by others

References

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

  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).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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).

    Article  CAS  PubMed  Google Scholar 

  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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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).

    Article  CAS  PubMed  Google Scholar 

  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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  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).

    Article  CAS  PubMed  Google Scholar 

  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).

    Article  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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).

    Article  CAS  PubMed  Google Scholar 

  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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  PubMed  Google Scholar 

  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).

    Article  CAS  PubMed Central  Google Scholar 

  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).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  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).

    Article  CAS  PubMed  Google Scholar 

  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).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  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).

    Article  CAS  PubMed  Google Scholar 

  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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  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).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  Google Scholar 

  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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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).

    Article  CAS  PubMed  Google Scholar 

  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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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).

    Article  CAS  PubMed  Google Scholar 

  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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  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  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  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).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  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).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  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).

    Article  CAS  PubMed  Google Scholar 

  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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  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).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  PubMed  CAS  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Evan W Newell or Mark M Davis.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Rights and permissions

Reprints and permissions

About this article

Cite this article

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

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nbt.2783

This article is cited by

Search

Quick links

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research