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TCRα-TCRβ pairing controls recognition of CD1d and directs the development of adipose NKT cells

Nature Immunology volume 18, pages 36–44 (2017)Cite this article

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A Corrigendum to this article was published on 19 July 2017

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Abstract

The interaction between the T cell antigen receptor (TCR) expressed by natural killer T cells (NKT cells) and the antigen-presenting molecule CD1d is distinct from interactions between the TCR and major histocompatibility complex (MHC). Our molecular modeling suggested that a hydrophobic patch created after TCRα–TCRβ pairing has a role in maintaining the conformation of the NKT cell TCR. Disruption of this patch ablated recognition of CD1d by the NKT cell TCR but not interactions of the TCR with MHC. Partial disruption of the patch, while permissive to the recognition of CD1d, significantly altered NKT cell development, which resulted in the selective accumulation of adipose-tissue-resident NKT cells. These results indicate that a key component of the TCR is essential for the development of a distinct population of NKT cells.

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Figure 1: Analysis of a hydrophobic 'patch' formed by pairing of the TCR α- and β-chains.
Figure 2: The hydrophobic pocket of the NKT cell TCR heterodimer is essential for the recognition of CD1d.
Figure 3: Disruption of the F108Y hydrophobic patch is permissive for conventional T cell development.
Figure 4: Substitution of TCRβ Phe108 disrupts NKT cell development.
Figure 5: The TCRβ F108Y substitution alters NKT cell development and induces the development of adipose-resident NKT cells.
Figure 6: Thymic NKT cells express adipose-related markers.
Figure 7: NKT cells expressing TCRβ F108Y acquire an adipose-like phenotype in the thymus.
Figure 8: TCR signaling is mediated by the TCRβ F108Y substitution.

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Change history

  • 17 April 2017

    In the version of this article initially published, the symbols in the key for Figure 5f were identified incorrectly. The correct key is open circle for Vβ8.2(F108Y) and red square for Vβ8.2(WT). The error has been corrected in the HTML and PDF versions of the article.

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Acknowledgements

We thank L. Osorio for technical assistance; R. Worth and V. Shapiro for review of the manuscript; A. Roberts for cell sorting; A. Laouar (Rutgers University) for the Rag1−/− mice; the late C. Janeway (Yale University School of Medicine) for the 4G4 cell line; T. Novak (Yale University) for the pMCFR vector; and the US National Institutes of Health Tetramer Core for the CD1d-PBS57 and CD1d-OCH tetramer reagents. Supported by the NIAID of the US National Institutes of Health (R01 AI083988 and AI059739 to D.B.S.), the NIMH of the US National Institutes of Health (MH092906 and NSF BRAIN EAGER MCB-1450895 to D.C.), the New Jersey Commission on Cancer Research Fellowship and Century for the Cure (Fellowship in Translational Immunology to J.A.V.) and by the Robert Wood Johnson Foundation (67038 to the Child Health Institute of New Jersey).

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Authors and Affiliations

  1. Child Health Institute of New Jersey, Rutgers University, New Brunswick, New Jersey, USA

    Joshua A Vieth, Fanomezana M Ranaivoson, Davide Comoletti, Lisa K Denzin & Derek B Sant'Angelo

  2. Rutgers Robert Wood Johnson Medical School, Rutgers University, New Brunswick, New Jersey, USA

    Joshua A Vieth, Fanomezana M Ranaivoson, Davide Comoletti, Lisa K Denzin & Derek B Sant'Angelo

  3. Immunology Program, Sloan-Kettering Institute, Memorial Sloan-Kettering Cancer Center, New York, New York, USA

    Joy Das

  4. Department of Neuroscience and Cell Biology, Rutgers University, New Brunswick, New Jersey, USA

    Davide Comoletti

  5. Rutgers Graduate School of Biomedical Sciences, Rutgers University, New Brunswick, New Jersey, USA

    Lisa K Denzin & Derek B Sant'Angelo

  6. Department of Pediatrics, Rutgers University, New Brunswick, New Jersey, USA

    Lisa K Denzin & Derek B Sant'Angelo

  7. Department of Pharmacology, Rutgers University, New Brunswick, New Jersey, USA

    Lisa K Denzin & Derek B Sant'Angelo

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  1. Joshua A Vieth
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Contributions

J.A.V. and D.B.S. designed the study, interpreted data and wrote the manuscript; J.A.V. performed most of the experiments; J.D. generated the cells transfected to express the Phe108 TCR and performed the initial binding and signaling studies; F.M.R. and D.C. assisted with the modeling of the TCR; L.K.D. assisted with data analysis and interpretation; and D.B.S. developed the Vβ8.2(F108A), Vβ8.2(F108A) mice and Vβ8.2(WT) mice.

Corresponding author

Correspondence to Derek B Sant'Angelo.

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The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 T cells in Vβ8.2(WT), Vβ8.2(F108Y) and Vβ8.2(F108A) mice develop similarly to T cells from wild-type mice.

(a) Representative histogram showing expression of TCR Vβ8 on the surface of CD3hi cells from the thymus and spleen of B6, Vβ8.2(WT), Vβ8.2(F108Y), and Vβ8.2(F108A) mice. Data are representative of at least three individual experiments and three biological replicates. (b) Comparison of T cells from B6, Vβ8.2(WT), Vβ8.2(F108Y), and Vβ8.2(F108A) mice by: expression of CD3 on DAPI- MHC- thymocytes and splenocytes (top row), expression of CD24 on DAPI-MHC II-CD3+ thymocytes and splenocytes (middle row), and expression of CD69 on DAPI-MHC II-CD3hi thymocytes and splenocytes (bottom row). Data shown are representative of three individual experiments representing three biological replicates. 1x104 target cells analyzed per sample. (c) Representative FACS analysis of DAPI-MHC II-CD3+CD4+ cells for CD25+ regulatory T cell populations in splenocytes from B6, Vβ8.2(WT), Vβ8.2(F108Y), and Vβ8.2(F108A) mice. Data are representative of three individual experiments representing a total of three biological replicates. 5x103 cells analyzed per sample.

Supplementary Figure 2 The wild-type TCRβ and mutant TCRβ F108Y and TCRβ F108A TCR Vβ chains dimerize with multiple Vα segments.

Flow cytometry analysis of splenic DAPI-MHC II-CD3+ T cells stained for CD4 and CD8 expression as well as TCRVα3, TCRVα8, TCRVα11, and TCRVα2 antibodies. Data shown for expression of TCRVα chains in CD4+ (left) and CD8+ (right) T cells separately. 1x104 DAPI-MHC II-CD3+ T cells analyzed for each sample, data is representative of three individual experiments assessing a total of three biological replicates.

Supplementary Figure 3 Validation of CD1d-Tet flow cytometry for NKT cell populations.

(a) Representative flow cytometry showing unloaded CD1d tetramer utilized as a negative control to identify background staining in all the thymus, spleen, liver, and adipose tissue of B6 mice. (b) Quantitation of flow cytometry data of the CD3+NK1.1+ total NKT cells in DAPI-MHC II- populations in the thymus, spleen, and liver of B6, Vβ8.2(F108Y), and Vβ8.2(F108A) mice, normalized to B6 control. (n=6 for thymus, spleen, and liver of B6 and Vβ8.2(F108A) mice, thymus and liver of Vβ8.2(F108Y) mice; n=5 for spleen of Vβ8.2(F108Y) mice). **P<0.01,***P<0.001, ****P<0.0001 (Mann-Whitney U test). 1x104 DAPI-MHC II- cells analyzed for each sample. Data derived from three combined experiments representing a total of five (b, Vβ8.2(F108A) splenocytes only) or six biological replicates (mean ±s.e.m. in b).

Supplementary Figure 4 The binding kinetics of NKT cell TCRs from B6, Vβ8.2(WT), Vβ8.2(F108Y) and Vβ8.2(F108A) mice are similar.

(a) DAPI-MHC II- hepatocyte populations from B6, Vβ8.2(F108Y), and Vβ8.2(F108A) mice analyzed by flow cytometry for binding to PBS57-loaded (top row) and OCH-loaded (bottom row) CD1d tetramer. (b) FACS analysis of autoMACS-sorted CD1d:PBS57 tetramer+ hepatocytes incubated with 0μg/ml, 10μg/ml, 100μg/ml and 200μg/ml αVβ8 blocking antibody (F23.1) concentrations for two hours at room temperature then analyzed by flow cytometer for tetramer binding levels. Data shown represents the MFI of CD1d Tet (PE) divided by the MFI of CD3 (AF700) normalized to untreated sample (n= 3). Data derived from three individual experiments analyzing a combined three biological replicates (mean ±s.e.m. in b).

Supplementary Figure 5 Background and preliminary gating strategy for flow cytometry experiments.

Flow cytometry gating strategy for identification of the cell populations discussed in Figures 3,4,5,6,7,8.

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Vieth, J., Das, J., Ranaivoson, F. et al. TCRα-TCRβ pairing controls recognition of CD1d and directs the development of adipose NKT cells. Nat Immunol 18, 36–44 (2017). https://doi.org/10.1038/ni.3622

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