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NK cell receptor NKG2D sets activation threshold for the NCR1 receptor early in NK cell development

Nature Immunology volume 19, pages 1083–1092 (2018)Cite this article

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Abstract

The activation of natural killer (NK) cells depends on a change in the balance of signals from inhibitory and activating receptors. The activation threshold values of NK cells are thought to be set by engagement of inhibitory receptors during development. Here, we found that the activating receptor NKG2D specifically set the activation threshold for the activating receptor NCR1 through a process that required the adaptor DAP12. As a result, NKGD2-deficient (Klrk1−/−) mice controlled tumors and cytomegalovirus infection better than wild-type controls through the NCR1-induced production of the cytokine IFN-γ. Expression of NKG2D before the immature NK cell stage increased expression of the adaptor CD3ζ. Reduced expression of CD3ζ in Klrk1−/− mice was associated with enhanced signal transduction through NCR1, and CD3ζ deficiency resulted in hyper-responsiveness to stimulation via NCR1. Thus, an activating receptor developmentally set the activity of another activating receptor on NK cells and determined NK cell reactivity to cellular threats.

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Fig. 1: Better control of B16 melanoma by Klrk1−/− mice is NK cell and IFNγ mediated.
Fig. 2: Klrk1−/− NK cells show specific hyper-reactivity through NCR1 receptor.
Fig. 3: NKG2D sets an activation threshold for NCR1 early during NK cell development in a process that differs from known mechanisms of NK cell education.
Fig. 4: The NKG2D-DAP12 signaling axis regulates NCR1 activity.
Fig. 5: Klrk1−/− and Tyrobp−/− NK cells have reduced levels of CD3ζ and Zap-70 signaling molecules.
Fig. 6: Hyper-reactivity of Klrk1−/− NK cells in response to NCR1 stimulation is a consequence of reduced expression of CD3ζ.

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Data availability

The data that support the findings of this study are available from the corresponding author upon request. The NCBI SRA accession codes are: SRX4548789, SRX4548788, SRX4548787, SRX4548786, SRX4548785, SRX4548784, SRX4548783, SRX4548782, SRX4548781.

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Acknowledgements

We thank S. Slavić Stupac, M. Samsa, E. Marinović, A. Miše and K. Mikić for technical assistance. We thank S. Jonjić for discussions and overall support to this work. We thank O. Mandelboim (Hebrew University Hadassah Medical School), M. Colonna (Washington University School of Medicine in St. Louis, St. Louis, MO, USA), M. Busslinger (Research Institute of Molecular Pathology, Vienna, Austria), A. Waisman (Institute of Molecular Biology, Mainz, Germany), D.R. Littman (NYU School of Medicine, New York, NY, USA), J. McGlade (University of Toronto, Toronto, Canada) and K. Rajewsky (MDC Center for Molecular Medicine, Berlin, Germany) for providing mouse lines. This work was supported by an EFIS-IL Short-term Fellowship grant to V.J., European Research Council under the European Union’s Seventh Framework Programme (FP/2007–2013)/ERC Grant Agreement no. 311335, Swedish Research Council, Norwegian Research Council, Swedish Foundation for Strategic Research, Wallenberg Foundation, Swedish Cancer Foundation, Swedish Childhood Cancer Foundation, as well as the Stockholm County Council and Karolinska Institutet Center for Innovative Medicine to Y.T.B., Netherlands Organization for Scientific Research (91614029), the European Commission (PCIG14-GA-2013-630827), a University of Rijeka Support grant (865.10.2101) and a Croatian Science Foundation Grant (IP-2016-06-8027) to F.M.W., a European Social Fund grant (HR.3.2.01-0263), University of Rijeka Support grant (803.10.1103) and Croatian Science Foundation grant (IP-2016-06-9306) to B.P. and the grant KK.01.1.1.01.0006, awarded to the Scientific Centre of Excellence for Virus Immunology and Vaccines and co-financed by the European Regional Development Fund.

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Author notes

  1. These authors contributed equally to this work: Marko Šestan, Inga Kavazović.

Authors and Affiliations

  1. Department of Histology and Embryology, Faculty of Medicine, University of Rijeka, Rijeka, Croatia

    Vedrana Jelenčić, Marko Šestan, Inga Kavazović, Maja Lenartić, Sonja Marinović, Berislav Lisnić, Felix M. Wensveen & Bojan Polić

  2. Center for Hematology and Regenerative Medicine, Department of Medicine Huddinge, Karolinska Institutet, Stockholm, Sweden

    Tim D. Holmes & Yenan T. Bryceson

  3. Institute of Pharmacology and Toxicology, Department for Biomedical Sciences, University of Veterinary Medicine Vienna, Vienna, Austria

    Michaela Prchal-Murphy & Veronika Sexl

  4. Broegelmann Laboratory, Department of Clinical Sciences, University of Bergen, Bergen, Norway

    Yenan T. Bryceson

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Contributions

V.J. carried out most of the experiments and analyzed data. M.Š., I.K., M.L., S.M., B.L. and F.M.W. performed and analyzed experiments. B.P. directed the research. B.P., V.J. and F.M.W. designed experiments and wrote the paper. V.S. and M.P. designed and performed qPCR on NK precursors. T.D.H. and Y.T.B. designed and performed RNA-seq experiments.

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Correspondence to Bojan Polić.

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Supplementary Figure 1 Better control of B16 melanoma by Klrk1−/− mice is NK cell and IFNγ mediated.

(a) FACS analysis of indicated organs from C57BL/6J and C57BL/6J RITL mice. (b) NKG2D ligand expression on indicated cells and 3T3-H60 cells as positive control labeled with NKG2D-hIg fusion protein (full line) or irrelevant fusion protein (dashed line). (c,g) Survival curves for C57BL/6J and Klrk1−/− mice after B16 cells i.v. injection without (c) or with CD4+ T cell depletion (g). (d) Representative x-Ray pictures of tumors from C57BL/6J or Klrk1−/− after B16 s.c. injection. (e) NKG2D expression on NKT cells from Klrk1−/− (n = 4), Klrk1fl/fl (n = 7), Klrk1fl/flCD4Cre (n = 6) mice (ANOVA, with Bonferroni’s post-test correction, *** p < 0.001). (f) Survival curves of indicated littermate mice after B16 cells i.v. injection. (h) Killing capacity of NK cells from C57BL/6J and Klrk1−/− mice towards B16-CFSE labeled after 14h at indicated effector to target ratios (n = 3). (i) Ifng mRNA expression normalized to 18S in B16 tumors isolated on 10th day from C57BL/6J and Klrk1−/− mice (data pooled from two experiments). (j) IFN-γ production by NK cells from indicated mice (n = 4) after DNAM-1 stimulation. (k) B16 cells stained with irrelevant fusion protein (dashed line), NCR1-hIg (full line) or NCR1-hIG plus anti NCR1 antibody to prevent binding of fusion protein (red line). c,f and g were analyzed by the Kaplan–Meier model followed by Log-rank (Mantel-Cox) test (n = 10 mice per group). h and j were analyzed using two-tailed unpaired t-test (ns, not significant). e, h-j show mean ± s.e.m. All graphs are representative from two independent experiments.

Supplementary Figure 2 Klrk1−/− mice show better control of both WT and Δm157 mCMV strains.

C57BL/6J and Klrk1−/− mice (n = 6 mice per goup) were infected with mCMV MW97.01 and Δm157 mCMV, which was generated on the backbone of the MW97.01 BAC. On day four after infection, viral titers in spleen were determined by plaque assay. * p > 0.05, ** p > 0.005 (two-sided Mann-Whitney test). Shown are mean ± s.e.m. Graphs are representative from two independent experiments.

Supplementary Figure 3 Deletion of NKG2D expression on NK cells.

(a) NKG2D expression was analyzed on NK cells from Klrk1−/− (n = 7), Klrk1fl/fl (n = 5), Klrk1fl/fl NCR1cre (n = 5) mice. Graph show geometric mean values (ANOVA, with Bonferroni’s post-test correction, shown mean ± s.e.m, *** p < 0.001). (b) Klrk1Δ/Δ mice were generated by crossing Klrk1fl/fl mice with Deletercre. NK cells from Klrk1Δ/Δ (n = 4) and C57BL/6J (n = 5) mice were stimulated through NCR1 and IFN-γ production was analyzed (two-tailed unpaired t-test, shown mean ± s.e.m; *P < 0.05). (c) Rag1CreEYFPStop-FloxiDTR mice were injected with PBS (-DT) or with diphtheria toxin (+DT). After 24h, immune cells in blood were analyzed. Gated is for viable cells. Shown are representative graphs from 3 (a,b) and 2 (c) independent experiments.

Supplementary Figure 4 Characterization of NK cells.

(a) Gating strategy for development of NK cells in BM. First lineage+ cells were excluded using anti CD4, CD8, Gr-1 and Ter119 antibodies. In lineage− population different stages of NK cell development were determined. Stage 1(CD122+NK1.1−CD11b−c-kit−), stage 2 (CD122+NK1.1+NCR1−CD11b−c-kit−), stage 3 (CD122+NK1.1+NCR1+CD11b−c-kit−), stage 4 (CD122+NK1.1+NCR1+CD11b−c-kit+), stage 5 (CD122+NK1.1+NCR1+CD11b+c-kit−/+), stage 6 (CD122+NK1.1+NCR1+CD11b+c-kit−). EYFP+ and EYFP− NK cells from Rag1cre Rosa26-floxed STOP-YFP (EYFPStop-Flox) Klrk1+/+ (n = 4 mice in EYFP+ group and 3 in EYFP− group) (b) or Rag1creEYFPStop-Flox Klrk1−/− (n = 4 mice per group) (c) were analyzed. Graph shows percentages of Klrg1 and CD11b positive NK cells. (d) Graph shows percentage of Ly49I+ NK cells in C57BL/6J (n = 3) and Klrk1−/− (n = 4) littermates. b-d two-tailed unpaired t-test was used; ns, not significant, *P < 0.05, **p < 0.01, *** p < 0.001. b-d shown are mean ± s.e.m.

Supplementary Figure 5 Analysis of NK cells.

(a) NK cells from Tyrobp+/+ and Tyrobp−/− littermates were stimulated through the indicated receptors and IFN-γ production was analyzed by intracellular flow cytometry (n = 5 mice per group). b-c NK cells from Stage 1 and 2 were sorted by FACS Aria using gating strategy described in Supplementary fig. 4a. Using qPCR we analyzed expression of NKG2D-S isoform (b) and DAP12 molecule (c). Graphs show relative expression to Rplp0 (n = 5 mice per group). (d) NK cells from C57BL/6J or Cd247−/− mice were stained for CD3ζ expression and analyzed by flow cytometry. Figure shows representative histograms. (e) NK cells from Tyrobp+/+ and Tyrobp−/− littermates were analyzed for expression of CD3ζ, FcRγ, Zap-70 and Syk expression. Figure shows graphs of geometric mean values for indicated molecules. As controls, isotype stained samples were used (n = 5 mice per group). (f) NK cells from Klrk1−/−, C57BL/6J, Hcst−/− and Tyrobp−/− mice were stimulated through CD16 receptor and IFN-γ production was analyzed (n = 5 mice per group). Representative data (shown are mean ± s.e.m.) from two (a-c, e) or three (d, f) independent experiments. To analyze a-c and e two-tailed unpaired t-test was used (ns, not significant, *P < 0.05, **p < 0.01, *** p < 0.001), for f ANOVA, with Bonferroni’s post-test correction was used (**p < 0.01, *** p < 0.001).

Supplementary Figure 6 Hyper-reactivity of Klrk1−/− NK cells is the consequence of reduced expression of CD3ζ.

(a) Cluster analysis of genes differentially expressed in Klrk1−/− NK cells. mRNA of C57BL/6J and Klrk1−/− NK cells was analyzed by RNAseq. To identify potential interaction partners with CD3ζ and Zap-70, cluster analysis of these molecules and differentially expressed genes was performed. Unconnected nodes were excluded. (b) NK cells from Balb/c or Sla−/− mice were stained for SLAP-1 expression and analyzed by flow cytometry. The figure shows representative histograms. (c) Splenic NK cells from Balb/c (n = 10) and Sla−/− (n = 8) mice were analyzed for expression of NCR1. Figure shows graphs of geometric mean values. d-e NK cells from Tyrobp+/+ and Tyrobp−/− littermates were stimulated through the NCR1 receptor and phosphorylation of Syk (d) and PLC-γ (e) was analyzed (n = 5 mice per group). (f) NCR1 expression was analyzed on NK cells from C57BL/6J (n = 5) and cd247−/− (n = 4) mice. The graph shows geometric mean values. To analyze c-f two-tailed unpaired t-test was used (ns, not significant, *P < 0.05). Shown are mean ± s.e.m.

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Jelenčić, V., Šestan, M., Kavazović, I. et al. NK cell receptor NKG2D sets activation threshold for the NCR1 receptor early in NK cell development. Nat Immunol 19, 1083–1092 (2018). https://doi.org/10.1038/s41590-018-0209-9

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