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Tuning of human MAIT cell activation by commensal bacteria species and MR1-dependent T-cell presentation

Mucosal Immunology (2018) | Download Citation

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Abstract

Human mucosal-associated invariant T (MAIT) cell receptors (TCRs) recognize bacterial riboflavin pathway metabolites through the MHC class 1-related molecule MR1. However, it is unclear whether MAIT cells discriminate between many species of the human microbiota. To address this, we developed an in vitro functional assay through human T cells engineered for MAIT-TCRs (eMAIT-TCRs) stimulated by MR1-expressing antigen-presenting cells (APCs). We then screened 47 microbiota-associated bacterial species from different phyla for their eMAIT-TCR stimulatory capacities. Only bacterial species that encoded the riboflavin pathway were stimulatory for MAIT-TCRs. Most species that were high stimulators belonged to Bacteroidetes and Proteobacteria phyla, whereas low/non-stimulator species were primarily Actinobacteria or Firmicutes. Activation of MAIT cells by high- vs low-stimulating bacteria also correlated with the level of riboflavin they secreted or after bacterial infection of macrophages. Remarkably, we found that human T-cell subsets can also present riboflavin metabolites to MAIT cells in a MR1-restricted fashion. This T–T cell-mediated signaling also induced IFNγ, TNF and granzyme B from MAIT cells, albeit at lower level than professional APC. These findings suggest that MAIT cells can discriminate and categorize complex human microbiota through computation of TCR signals depending on antigen load and presenting cells, and fine-tune their functional responses.

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References

  1. 1.

    Dusseaux, M. et al. Human MAIT cells are xenobiotic-resistant, tissue-targeted, CD161hi IL-17-secreting T cells. Blood 117, 1250–1259 (2011).

  2. 2.

    Martin, E. et al. Stepwise development of MAIT cells in mouse and human. PLoS Biol. 7, e54 (2009).

  3. 3.

    Gold, M. C. et al. Human mucosal associated invariant T cells detect bacterially infected cells. PLoS Biol. 8, e1000407 (2010).

  4. 4.

    Treiner, E. et al. Selection of evolutionarily conserved mucosal-associated invariant T cells by MR1. Nature 422, 164–169 (2003).

  5. 5.

    Le Bourhis, L. et al. Antimicrobial activity of mucosal-associated invariant T cells. Nat. Immunol. 11, 701–708 (2010).

  6. 6.

    Meierovics, A., Yankelevich, W. J. & Cowley, S. C. MAIT cells are critical for optimal mucosal immune responses during in vivo pulmonary bacterial infection. Proc. Natl Acad. Sci. USA 110, E3119–3128 (2013).

  7. 7.

    Chua, W. J. et al. Polyclonal mucosa-associated invariant T cells have unique innate functions in bacterial infection. Infect. Immun. 80, 3256–3267 (2012).

  8. 8.

    Kjer-Nielsen, L. et al. MR1 presents microbial vitamin B metabolites to MAIT cells. Nature 491, 717–723 (2012).

  9. 9.

    Patel, O. et al. Recognition of vitamin B metabolites by mucosal-associated invariant T cells. Nat. Commun. 4, 2142 (2013).

  10. 10.

    Lopez-Sagaseta, J. et al. The molecular basis for Mucosal-Associated Invariant T cell recognition of MR1 proteins. Proc. Natl Acad. Sci. USA 110, E1771–1778 (2013).

  11. 11.

    Corbett, A. J. et al. T-cell activation by transitory neo-antigens derived from distinct microbial pathways. Nature 509, 361–365 (2014).

  12. 12.

    Le Bourhis, L. et al. MAIT cells detect and efficiently lyse bacterially-infected epithelial cells. PLoS Pathog. 9, e1003681 (2013).

  13. 13.

    Kurioka, A. et al. MAIT cells are licensed through granzyme exchange to kill bacterially sensitized targets. Mucosal Immunol. 8, 429–440 (2015).

  14. 14.

    Cui, Y. et al. Mucosal-associated invariant T cell-rich congenic mouse strain allows functional evaluation. J. Clin. Invest. 125, 4171–4185 (2015).

  15. 15.

    Georgel, P., Radosavljevic, M., Macquin, C. & Bahram, S. The non-conventional MHC class I MR1 molecule controls infection by Klebsiella pneumoniae in mice. Mol. Immunol. 48, 769–775 (2011).

  16. 16.

    Ussher, J. E., Klenerman, P. & Willberg, C. B. Mucosal-associated invariant T-cells: new players in anti-bacterial immunity. Front. Immunol. 5, 450 (2014).

  17. 17.

    Liuzzi, A. R. et al. Unconventional human T cells accumulate at the site of infection in response to microbial ligands and induce local tissue remodeling. J. Immunol. 197, 2195–2207 (2016).

  18. 18.

    Jiang, J. et al. Mucosal-associated invariant T-cell function is modulated by programmed death-1 signaling in patients with active tuberculosis. Am. J. Respir. Crit Care Med. 190, 329–339 (2014).

  19. 19.

    Grimaldi, D. et al. Specific MAIT cell behaviour among innate-like T lymphocytes in critically ill patients with severe infections. Intensive Care Med. 40, 192–201 (2014).

  20. 20.

    Smith, D. J., Hill, G. R., Bell, S. C. & Reid, D. W. Reduced mucosal associated invariant T-cells are associated with increased disease severity and Pseudomonas aeruginosa infection in cystic fibrosis. PLoS ONE 9, e109891 (2014).

  21. 21.

    Leung, D. T. et al. Circulating mucosal associated invariant T cells are activated in Vibrio cholerae O1 infection and associated with lipopolysaccharide antibody responses. PLoS Negl. Trop. Dis. 8, e3076 (2014).

  22. 22.

    Booth, J. S. et al. Mucosal-associated invariant T cells in the human gastric mucosa and blood: role in Helicobacter pylori infection. Front. Immunol. 6, 466 (2015).

  23. 23.

    Serriari, N. E. et al. Innate mucosal-associated invariant T (MAIT) cells are activated in inflammatory bowel diseases. Clin. Exp. Immunol. 176, 266–274 (2014).

  24. 24.

    Illes, Z., Shimamura, M., Newcombe, J., Oka, N. & Yamamura, T. Accumulation of Valpha7.2-Jalpha33 invariant T cells in human autoimmune inflammatory lesions in the nervous system. Int. Immunol. 16, 223–230 (2004).

  25. 25.

    Cho, Y. N. et al. Mucosal-associated invariant T cell deficiency in systemic lupus erythematosus. J. Immunol. 193, 3891–3901 (2014).

  26. 26.

    Wright, E. K. et al. Recent advances in characterizing the gastrointestinal microbiome in Crohn’s disease: a systematic review. Inflamm. Bowel Dis. 21, 1219–1228 (2015).

  27. 27.

    Walker, A. W. et al. High-throughput clone library analysis of the mucosa-associated microbiota reveals dysbiosis and differences between inflamed and non-inflamed regions of the intestine in inflammatory bowel disease. BMC Microbiol. 11, 7 (2011).

  28. 28.

    Andoh, A. et al. Comparison of the fecal microbiota profiles between ulcerative colitis and Crohn’s disease using terminal restriction fragment length polymorphism analysis. J. Gastroenterol. 46, 479–486 (2011).

  29. 29.

    Drago, L. et al. Skin microbiota of first cousins affected by psoriasis and atopic dermatitis. Clin. Mol. Allergy 14, 2 (2016).

  30. 30.

    Fahlen, A., Engstrand, L., Baker, B. S., Powles, A. & Fry, L. Comparison of bacterial microbiota in skin biopsies from normal and psoriatic skin. Arch. Dermatol. Res. 304, 15–22 (2012).

  31. 31.

    Cosgrove, C. et al. Early and nonreversible decrease of CD161++ /MAIT cells in HIV infection. Blood 121, 951–961 (2013).

  32. 32.

    Wong, E. B. et al. Low levels of peripheral CD161++CD8+ mucosal associated invariant T (MAIT) cells are found in HIV and HIV/TB co-infection. PLoS ONE 8, e83474 (2013).

  33. 33.

    Eberhard, J. M. et al. CD161+ MAIT cells are severely reduced in peripheral blood and lymph nodes of HIV-infected individuals independently of disease progression. PLoS ONE 9, e111323 (2014).

  34. 34.

    Fernandez, C. S. et al. MAIT cells are depleted early but retain functional cytokine expression in HIV infection. Immunol. Cell Biol. 93, 177–188 (2015).

  35. 35.

    Leeansyah, E. et al. Activation, exhaustion, and persistent decline of the antimicrobial MR1-restricted MAIT-cell population in chronic HIV-1 infection. Blood 121, 1124–1135 (2013).

  36. 36.

    Khaitan, A. et al. HIV-infected children have lower frequencies of CD8+ mucosal-associated invariant T (MAIT) cells that correlate with innate, Th17 and Th22 cell subsets. PLoS ONE 11, e0161786 (2016).

  37. 37.

    Gori, A. et al. Early impairment of gut function and gut flora supporting a role for alteration of gastrointestinal mucosa in human immunodeficiency virus pathogenesis. J. Clin. Microbiol. 46, 757–758 (2008).

  38. 38.

    Round, J. L. & Mazmanian, S. K. The gut microbiota shapes intestinal immune responses during health and disease. Nat. Rev. Immunol. 9, 313–323 (2009).

  39. 39.

    Vujkovic-Cvijin, I. et al. Dysbiosis of the gut microbiota is associated with HIV disease progression and tryptophan catabolism. Sci. Transl. Med. 5, 193ra191 (2013).

  40. 40.

    Lozupone, C. A. et al. Alterations in the gut microbiota associated with HIV-1 infection. Cell Host Microbe 14, 329–339 (2013).

  41. 41.

    Nowak, P. et al. Gut microbiota diversity predicts immune status in HIV-1 infection. AIDS 29, 2409–2418 (2015).

  42. 42.

    Henderson, R. A. et al. HLA-A2.1-associated peptides from a mutant cell line: a second pathway of antigen presentation. Science 255, 1264–1266 (1992).

  43. 43.

    Cohen, C. J., Zhao, Y., Zheng, Z., Rosenberg, S. A. & Morgan, R. A. Enhanced antitumor activity of murine-human hybrid T-cell receptor (TCR) in human lymphocytes is associated with improved pairing and TCR/CD3 stability. Cancer Res. 66, 8878–8886 (2006).

  44. 44.

    Wan, Q. et al. Probing the effector and suppressive functions of human T cell subsets using antigen-specific engineered T cell receptors. PLoS ONE 8, e56302 (2013).

  45. 45.

    Gold, M. C. et al. MR1-restricted MAIT cells display ligand discrimination and pathogen selectivity through distinct T cell receptor usage. J. Exp. Med. 211, 1601–1610 (2014).

  46. 46.

    Gherardin, N. A. et al. Diversity of T cells restricted by the MHC class I-related molecule MR1 facilitates differential antigen recognition. Immunity 44, 32–45 (2016).

  47. 47.

    Lepore, M. et al. Parallel T-cell cloning and deep sequencing of human MAIT cells reveal stable oligoclonal TCRbeta repertoire. Nat. Commun. 5, 3866 (2014).

  48. 48.

    Aldemir, H. Novel MHC class I-related molecule MR1 affects MHC class I expression in 293T cells. Biochem. Biophys. Res. Commun. 366, 328–334 (2008).

  49. 49.

    Yamaguchi, H. & Hashimoto, K. Association of MR1 protein, an MHC class I-related molecule, with beta(2)-microglobulin. Biochem. Biophys. Res. Commun. 290, 722–729 (2002).

  50. 50.

    Soudais, C. et al. In vitro and in vivo analysis of the Gram-negative bacteria-derived riboflavin precursor derivatives activating mouse MAIT cells. J. Immunol. 194, 4641–4649 (2015).

  51. 51.

    Bikard, D. et al. Programmable repression and activation of bacterial gene expression using an engineered CRISPR-Cas system. Nucleic Acids Res. 41, 7429–7437 (2013).

  52. 52.

    Oh, J. et al. The altered landscape of the human skin microbiome in patients with primary immunodeficiencies. Genome Res. 23, 2103–2114 (2013).

  53. 53.

    Human Microbiome Project Consortium. Structure, function and diversity of the healthy human microbiome. Nature 486, 207–214 (2012).

  54. 54.

    McWilliam, H. E. et al. The intracellular pathway for the presentation of vitamin B-related antigens by the antigen-presenting molecule MR1. Nat. Immunol. 17, 531–537 (2016).

  55. 55.

    Sundrud, M. S. et al. Genetic reprogramming of primary human T cells reveals functional plasticity in Th cell differentiation. J. Immunol. 171, 3542–3549 (2003).

  56. 56.

    Mariat, D. et al. The Firmicutes/Bacteroidetes ratio of the human microbiota changes with age. BMC Microbiol. 9, 123 (2009).

  57. 57.

    Urbaniak, C. et al. Effect of chemotherapy on the microbiota and metabolome of human milk, a case report. Microbiome 2, 24 (2014).

  58. 58.

    Chiodini, R. J. et al. Microbial population differentials between mucosal and submucosal intestinal tissues in advanced Crohn’s disease of the ileum. PLoS ONE 10, e0134382 (2015).

  59. 59.

    Mehandru, S., Tenner-Racz, K., Racz, P. & Markowitz, M. The gastrointestinal tract is critical to the pathogenesis of acute HIV-1 infection. J. Allergy Clin. Immunol. 116, 419–422 (2005).

  60. 60.

    Ling, Z. et al. Alterations in the fecal microbiota of patients with HIV-1 infection: an observational study in a Chinese population. Sci. Rep. 6, 30673 (2016).

  61. 61.

    Teunissen, M. B. et al. The IL-17A-producing CD8+ T-cell population in psoriatic lesional skin comprises mucosa-associated invariant T cells and conventional T cells. J. Invest. Dermatol. 134, 2898–2907 (2014).

  62. 62.

    Li, J. et al. The frequency of mucosal-associated invariant T cells is selectively increased in dermatitis herpetiformis. Australas. J. Dermatol. 58, 200–204 (2017).

  63. 63.

    Gao, Z., Tseng, C. H., Strober, B. E., Pei, Z. & Blaser, M. J. Substantial alterations of the cutaneous bacterial biota in psoriatic lesions. PLoS ONE 3, e2719 (2008).

  64. 64.

    Leeming, J. P., Holland, K. T. & Cunliffe, W. J. The microbial ecology of pilosebaceous units isolated from human skin. J. Gen. Microbiol. 130, 803–807 (1984).

  65. 65.

    Kong, H. H. et al. Temporal shifts in the skin microbiome associated with disease flares and treatment in children with atopic dermatitis. Genome Res. 22, 850–859 (2012).

  66. 66.

    Grice, E. A. et al. Topographical and temporal diversity of the human skin microbiome. Science 324, 1190–1192 (2009).

  67. 67.

    Beylot, C. et al. Propionibacterium acnes: an update on its role in the pathogenesis of acne. J. Eur. Acad. Dermatol. Venereol. 28, 271–278 (2014).

  68. 68.

    Leyden, J. J., McGinley, K. J. & Vowels, B. Propionibacterium acnes colonization in acne and nonacne. Dermatology 196, 55–58 (1998).

  69. 69.

    Kistowska, M. et al. Propionibacterium acnes promotes Th17 and Th17/Th1 responses in acne patients. J. Invest. Dermatol. 135, 110–118 (2015).

  70. 70.

    Kelhala, H. L. et al. IL-17/Th17 pathway is activated in acne lesions. PLoS ONE 9, e105238 (2014).

  71. 71.

    Held, K., Beltran, E., Moser, M., Hohlfeld, R. & Dornmair, K. T-cell receptor repertoire of human peripheral CD161hiTRAV1-2+ MAIT cells revealed by next generation sequencing and single cell analysis. Hum. Immunol. 76, 607–614 (2015).

  72. 72.

    Tilloy, F. et al. An invariant T cell receptor alpha chain defines a novel TAP-independent major histocompatibility complex class Ib-restricted alpha/beta T cell subpopulation in mammals. J. Exp. Med. 189, 1907–1921 (1999).

  73. 73.

    Reantragoon, R. et al. Antigen-loaded MR1 tetramers define T cell receptor heterogeneity in mucosal-associated invariant T cells. J. Exp. Med. 210, 2305–2320 (2013).

  74. 74.

    Kitaura, K., Shini, T., Matsutani, T. & Suzuki, R. A new high-throughput sequencing method for determining diversity and similarity of T cell receptor (TCR) alpha and beta repertoires and identifying potential new invariant TCR alpha chains. BMC Immunol. 17, 38 (2016).

  75. 75.

    Eckle, S. B. et al. A molecular basis underpinning the T cell receptor heterogeneity of mucosal-associated invariant T cells. J. Exp. Med. 211, 1585–1600 (2014).

  76. 76.

    Howson, L. J. et al. MAIT cell clonal expansion and TCR repertoire shaping in human volunteers challenged with Salmonella Paratyphi A. Nat. Commun. 9, 253 (2018).

  77. 77.

    Dias, J., Leeansyah, E. & Sandberg, J. K. Multiple layers of heterogeneity and subset diversity in human MAIT cell responses to distinct microorganisms and to innate cytokines. Proc. Natl Acad. Sci. USA 114, E5434–E5443 (2017).

  78. 78.

    Lopez-Sagaseta, J. et al. MAIT recognition of a stimulatory bacterial antigen bound to MR1. J. Immunol. 191, 5268–5277 (2013).

  79. 79.

    Gutierrez-Preciado, A. et al. Extensive identification of bacterial riboflavin transporters and their distribution across bacterial species. PLoS ONE 10, e0126124 (2015).

  80. 80.

    Magnusdottir, S., Ravcheev, D., de Crecy-Lagard, V. & Thiele, I. Systematic genome assessment of B-vitamin biosynthesis suggests co-operation among gut microbes. Front. Genet. 6, 148 (2015).

  81. 81.

    Kurioka, A. et al. Diverse Streptococcus pneumoniae strains drive a mucosal-associated invariant T-cell response through major histocompatibility complex class I-related molecule-dependent and cytokine-driven pathways. J. Infect. Dis. 217, 988–999 (2018).

  82. 82.

    Hartmann, N. et al. Riboflavin metabolism variation among clinical isolates of Streptococcus pneumoniae results in differential activation of mucosal-associated invariant T cells. Am. J. Respir. Cell Mol. Biol. 58, 767–776 (2018).

  83. 83.

    Zheng, Y., Zha, Y. & Gajewski, T. F. Molecular regulation of T-cell anergy. EMBO Rep. 9, 50–55 (2008).

  84. 84.

    Smith, T. R., Verdeil, G., Marquardt, K. & Sherman, L. A. Contribution of TCR signaling strength to CD8+ T cell peripheral tolerance mechanisms. J. Immunol. 193, 3409–3416 (2014).

  85. 85.

    Pamer, E. G. Microbial tuning of the mammalian immune system. Trends Mol. Med. 23, 379–380 (2017).

  86. 86.

    Manel, N. et al. A cryptic sensor for HIV-1 activates antiviral innate immunity in dendritic cells. Nature 467, 214–217 (2010).

  87. 87.

    Sanjana, N. E., Shalem, O. & Zhang, F. Improved vectors and genome-wide libraries for CRISPR screening. Nat. Methods 11, 783–784 (2014).

  88. 88.

    Kanehisa, M. et al. KEGG for linking genomes to life and the environment. Nucleic Acids Res. 36(Database issue), D480–484 (2008).

  89. 89.

    Zhou, K. et al. Novel reference genes for quantifying transcriptional responses of Escherichia coli to protein overexpression by quantitative PCR. BMC Mol. Biol. 12, 18 (2011).

  90. 90.

    Hyatt, D. et al. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinforma. 11, 119 (2010).

  91. 91.

    Edgar, R. C. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26, 2460–2461 (2010).

  92. 92.

    Ciccimaro, E. & Blair, I. A. Stable-isotope dilution LC-MS for quantitative biomarker analysis. Bioanalysis 2, 311–341 (2010).

  93. 93.

    Mani, D. R., Abbatiello, S. E. & Carr, S. A. Statistical characterization of multiple-reaction monitoring mass spectrometry (MRM-MS) assays for quantitative proteomics. BMC Bioinforma. 13(Suppl. 16), S9 (2012).

  94. 94.

    Reantragoon, R. et al. Structural insight into MR1-mediated recognition of the mucosal associated invariant T cell receptor. J. Exp. Med. 209, 761–774 (2012).

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Acknowledgements

We thank Dr. David Mellert (Jackson Laboratory) for critical reading and critiques, Dr. Victor Torres (NYU School of Medicine) and Dr. Bo Shopsin (NYU School of Medicine) for insightful discussions and suggestions, Drs. Victor Torres, Bo Shopsin, Michael Otto (NIH) and George Weinstock (Jackson Laboratory) for several bacteria strains, and NIH tetramer facility for the MR1 tetramers. The research in this study was supported by the National Institute of Health (NIH) grant R01AI121920 to D.U, NIH Grant U54NS105539 to D.U., J.O. and X.Y. and the Jackson Laboratory Director’s Innovation Fund to D.U and J.O.

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Affiliations

  1. Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA

    • Cihan Tastan
    • , Ece Karhan
    • , Wei Zhou
    • , Elizabeth Fleming
    • , Anita Y. Voigt
    • , Meghan Horne
    • , Lindsey Placek
    • , Lina Kozhaya
    • , Julia Oh
    •  & Derya Unutmaz
  2. Department of Microbiology, NYU School of Medicine, New York, NY, 10016, USA

    • Cihan Tastan
  3. Department of Chemistry, University of Connecticut, Storrs, CT, 06269, USA

    • Xudong Yao
    •  & Lei Wang

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Contributions

C.T. designed, performed and analyzed the experiments. W.Z. and J.O. performed bioinformatics studies. A.Y.V. performed CRISPR-repression experiments in E. coli. E.K. helped T–T interaction assays and performed intracellular staining. M.H., L.P., E.K. and L.K. prepared human primary T cells for the experiments. E.F. performed growth of the bacterial species. M.H. and L.K. isolated and prepared healthy human adult PBMCs. X.Y and L.W. performed mass spec analysis of riboflavin in bacteria supernatants. W.Z., A.Y.V, M.H., E.F., L.P., E.K. and L.K. provided helpful discussions in experimental design. C.T., J.O. and D.U. wrote the manuscript. J.O. and D.U. led the investigation and contributed to the design and interpretation of the data.

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The authors declare no competing interests.

Corresponding author

Correspondence to Derya Unutmaz.

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https://doi.org/10.1038/s41385-018-0072-x