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Effector differentiation downstream of lineage commitment in ILC1s is driven by Hobit across tissues

Nature Immunology volume 22, pages 1256–1267 (2021)Cite this article

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Abstract

Innate lymphoid cells (ILCs) participate in tissue homeostasis, inflammation, and early immunity against infection. It is unclear how ILCs acquire effector function and whether these mechanisms differ between organs. Through multiplexed single-cell mRNA sequencing, we identified cKit+CD127hiTCF-1hi early differentiation stages of T-bet+ ILC1s. These cells were present across different organs and had the potential to mature toward CD127intTCF-1int and CD127−TCF-1− ILC1s. Paralleling a gradual loss of TCF-1, differentiating ILC1s forfeited their expansion potential while increasing expression of effector molecules, reminiscent of T cell differentiation in secondary lymphoid organs. The transcription factor Hobit was induced in TCF-1hi ILC1s and was required for their effector differentiation. These findings reveal sequential mechanisms of ILC1 lineage commitment and effector differentiation that are conserved across tissues. Our analyses suggest that ILC1s emerge as TCF-1hi cells in the periphery and acquire a spectrum of organ-specific effector phenotypes through a uniform Hobit-dependent differentiation pathway driven by local cues.

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Fig. 1: Differential expression of CD127 identifies helper-like and cytotoxic-like hepatic ILC1s.
Fig. 2: CD127+ ILC1s are precursors of CD127− cytotoxic-like ILC1s.
Fig. 3: TCF-1hi early ILC1s give rise to downstream effector ILC1s.
Fig. 4: Hobit marks lineage-committed ILC1s.
Fig. 5: Hobit drives the effector differentiation of lineage-committed ILC1s.
Fig. 6: Hobit is continuously required to regulate the differentiation of TCF-1hi Gzmlo versus TCF-1lo Gzmhi effector ILC1s.
Fig. 7: Effector differentiation of ILC1s is regulated by Hobit across tissues.
Fig. 8: The developmental potential of ILC1s is conserved across tissues.

Data availability

The sequencing data that were generated for this report have been deposited in Gene Expression Omnibus under the accession number GSE163452. An interactive online resource of single cell sequencing analyses is available on https://go.uniwue.de/hobit. Sequencing data for ILCP analysis was recently published by Harly et al.29.

Source data are provided with this paper in the Supplementary File. Source data are provided with this paper.

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Acknowledgements

We thank C. Romagnani for critically reading the manuscript, and S. Klingler, M. Lian, S. Riedmann, L. Parga-Vidal and the IZKF FACS sorting facility Würzburg for expert technical assistance. We thank E. Vivier (Aix Marseille Univ., CNRS, INSERM, CIML, Marseille, France) and A. Rudensky (Howard Hughes Medical Institute, Immunology Program, and Ludwig Center, Memorial Sloan Kettering Cancer Center, New York, USA) for providing mice. We thank R. Naumann (MPI-CBG, Dresden) for providing Flp deleter mice and for microinjections of HobitKO ES cells. This work was supported by grants through the German Research Foundation (DFG) priority program SPP1937 – Innate lymphoid cells (GA2129/2-2 to G.Gasteiger and GR4980/1-2 to D.G.), through the European Research Council (759176-TissueLymphoContexts to G.Gasteiger, 818846-ImmuNiche to D.G. and 819329- STEP2 to W.K.). G.Gasteiger and D.G. are supported by the Max Planck Society. P.A. acknowledges financial support from Interdisciplinary Center for Clinical Research-IZKF (project Z-6). A.-E.S. is supported by the EMBO Young Investigator program. K.P.J.M.v.G. was funded by a LSBR fellowship from Landsteiner Foundation of Blood Transfusion Research (1629).

Author information

Author notes

  1. These authors contributed equally: Christin Friedrich, Renske L. R. E. Taggenbrock.

  2. These authors jointly supervised this work: Klaas P. J. M. van Gisbergen, Georg Gasteiger.

Authors and Affiliations

  1. Würzburg Institute of Systems Immunology (WüSI), Max Planck Research Group at the Julius-Maximilians-Universität Würzburg, Würzburg, Germany

    Christin Friedrich, Rémi Doucet-Ladevèze, Rebekka Moenius, Mercedes Gomez de Agüero, Wolfgang Kastenmüller, Dominic Grün & Georg Gasteiger

  2. Department of Hematopoiesis, Sanquin Research and Landsteiner Laboratory, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands

    Renske L. R. E. Taggenbrock, Natasja A. M. Kragten & Klaas P. J. M. van Gisbergen

  3. Max Planck Institute of Immunobiology and Epigenetics, Freiburg, Germany

    Gosia Golda & Dominic Grün

  4. Faculty of Biology, University of Freiburg, Freiburg, Germany

    Gosia Golda

  5. International Max Planck Research School for Immunology, Epigenetics and Metabolism (IMPRS-IEM), Freiburg, Germany

    Gosia Golda

  6. Core Unit Systems Medicine, Julius-Maximilians-Universität Würzburg, Würzburg, Germany

    Panagiota Arampatzi

  7. Roche Innovation Center Munich, Oncology Division, Roche Pharmaceutical Research and Early Development, Penzberg, Germany

    Katharina Kreymborg

  8. Helmholtz Institute for RNA-based Infection Research (HIRI), Helmholtz-Center for Infection Research (HZI), Würzburg, Germany

    Antoine-Emmanuel Saliba

  9. Department of Experimental Immunology, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands

    Klaas P. J. M. van Gisbergen

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  1. Christin Friedrich
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Contributions

G.Gasteiger and K.P.J.M.v.G. conceptualized the study, provided funding, and coordinated the project. G.Gasteiger, K.P.J.M.v.G. and C.F. wrote the manuscript with input from all authors. C.F., R.L.R.E.T., R.M. and N.A.M.K. planned and performed experiments and analyzed the data. P.A. and A.-E.S. performed scRNA-seq. R.-D.L., and G.Golda analyzed scRNA-seq experiments. M.G.d.A. and K.K. provided critical reagents. W.K. and D.G. provided intellectual input and conceptual advice.

Corresponding author

Correspondence to Georg Gasteiger.

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Competing interests

K.K. is an employee of Morphosys AG and former employee of the Roche Innovation Center Munich.

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Peer review information Nature Immunology thanks the anonymous reviewers for their contribution to the peer review of this work. L. A. Dempsey was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

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Extended data

Extended Data Fig. 1 Characterization of hepatic group 1 ILCs and gating strategy.

a Representative FACS plots display Lin−NK1.1+ cells of WT and HobitTom/WT mice. Bar graphs indicate absolute numbers of liver ILC1s. Data are pooled from 2 independent experiments with n=2 and 3 mice per group. b Full sorting strategy for liver ILC1 and NK cells from negatively enriched liver lymphocytes of HobitTom/WT mice. c Heat map overview of significantly differentially expressed genes of ILC1 and NK cell clusters from Fig. 1c using Seurat. d, e Gating strategy to identify Lin− NK1.1+ Eomes− CD49a+ liver ILC1 and histograms showing Gata3, RORγt (d) and CD49b (e) protein expression within liver ILC1. Liver and mesenteric lymph nodes are gated on Lin−CD127+ cells to display Gata3 and RORyt expression. Data are representative of 2 individual experiments with n=3 mice. Bar graphs indicate individual mice (symbols) and mean (bar), error bars display means ± SD. Statistical significance was calculated by unpaired two-tailed t-test.

Extended Data Fig. 2 CD127− cytotoxic-like cells are bona-fide ILC1s.

a Dot plot representation of selected ILC1 and NK cell marker gene expression associated with the clusters identified in Fig. 1c. Color indicates z-score of mean expression across clusters and dot size represents fraction of cells in the cluster expressing the respective gene. b, c, f Frequency of liver ILC1s expressing indicated proteins in NKp46Cre versus NKp46Cre Eomesfl/fl mice (b), WT versus Rag1-/- mice (c) and SPF versus germ free mice (f). Data are representative of 2 independent experiments with n=2 and 3 mice per group (b, c, f). d, e Representative FACS analysis of liver ILC1 of RORc-eYFP fate mapper (FM) mice. (d) FACS analysis and bar graph shows frequency of RORc fate map-positive cells within CD127+ and CD127− liver ILC1 and NK cells. Data are representative of 2 independent experiments with n=3 mice per group. (e) FACS plots show marker protein expression of RORc fate mapper-positive (top) and negative (bottom) liver ILC1s. Bar graphs show frequency of Gzmb-positive cells within FM-positive and FM-negative ILC1s. Data are pooled from 2 independent experiments with n=2 mice per group. Bar graphs indicate individual mice (symbols) and mean (bar), error bars display means ± s.d. Statistical significance was calculated by unpaired two-tailed t-test; *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001.

Source data

Extended Data Fig. 3 CD127+ ILC1s give rise to CD127− cytotoxic-like ILC1s in vitro and in vivo.

a, b Sorting strategy for CD127+ and CD127− liver ILC1 and NK cells from WT mice, gated on live CD45+ cells. b Sorting purity. c-f, h, i In vitro cultures of indicated liver ILC1 subsets with IL-2 (c, d, f, h, i) or IL-15 (e) and OP9-DL1 cells (c, e, h, i) or the indicated stromal cell line (d) for 7 days. Representative FACS analysis showing phenotype of NK1.1+ cells. Red quadrants on FACS plots highlight phenotypic differences of CD127+ ILC1 cultured in the presence of IL-2 versus IL-15. d Frequency of Gzma+Gzmb+ cells on day 7. e Absolute numbers on d7. Dashed line indicates number of cells on d0 (input=400 cells). f In vitro proliferation of ILC1 subsets assessed by cell tracer violet dilution analyzed on the indicated days. Data are representative of 2 independent experiments with n=4 and 5 (d), n=2 (e), n=4 (f) replicates per experiment. g In vivo co-transfer of congenically marked CD127+ and CD127− liver ILC1s into sublethally irradiated Rag2-/-γc-/- mice. Representative FACS analysis of liver ILC1s derived from indicated transferred ILC1 subsets on d15. i Isotype control stainings of ILC1s cultured in vitro as in h. Bar graphs indicate replicates (symbols) and mean (bar), error bars display means ± s.d.

Source data

Extended Data Fig. 4 scRNA-seq analysis of hepatic ILC1s from WT and HobitKO mice.

a Schematic representation of the Hobit locus of Hobit KO mice. b Absolute numbers of liver NK cells of WT and HobitKO mice. c Representative FACS analysis displaying Lin−NK1.1+ hepatic ILC1s and NK cells in HobitTom/WT and HobitTom/KO mice. Bar graphs indicate absolute numbers of liver ILC1s. Data in (b) and (c) are pooled from 2 independent experiments with n=3 (b) and n=2 and 3 (c) mice per group. d Representative FACS analysis of liver ILC1s of HobitKO RORc-eYFP fate mapper (FM) mice. Bar graph shows frequency of RORc fate map-positive cells within CD127+ and CD127− liver ILC1s. Data are representative of 2 independent experiments with n=2-3 mice per group. e-g scRNA-seq of hash-tagged liver ILC1 sorted from HobitTom/WT and HobitTom/KO mice. e General QC, low quality cells (feature counts > 1000 and percentage of genes mapped to mitochondrial genome < 8) and cell doublets filtering and demultiplexing of Hashtag (HT) antibodies allows to separate HobitKO/Tom (KO) and HobitTom/WT (WT). Single cell transcriptome visualization using a UMAP color-coded by clusters and the sample WT or KO as indicated by the binary detection of the HT antibodies. f Volcano plot displaying significantly differentially expressed genes between WT and HobitKO ILC1, using Wilcoxon test. Thresholds are displayed at Log2 FC equal 0.5 and Adjusted P value of 0.05. Genes on the right are overexpressed in KO, genes on the left are overexpressed in WT. g Heat map of marker gene expression differentially expressed across liver ILC1s. Cluster number refers to panel (e). h, i Pseudo-temporal ordering of ILC1 single cell transcriptomes with Slingshot. Expression of candidate genes across pseudotime within hash-tagged liver ILC1s sorted from HobitTom/WT and HobitTom/KO mice. Color barcode in (h) indicates cluster identity (as identified in e). Heatmap of expression of selected genes in ILC1 populations along pseudotime (i). Bar graphs indicate individual mice (symbols) and mean (bar), error bars display means ± s.d. Statistical significance was calculated by unpaired two-tailed t-test; **P < 0.01.

Source data

Extended Data Fig. 5 Hobit drives the development and effector maturation of hepatic ILC1s and is expressed in committed ILC1s.

a-c Representative FACS analysis of liver ILC1s in mixed bone marrow chimeric mice containing a congenically marked WT and HobitKO compartment (a). Frequency of liver ILC1 expressing indicated marker (b) and gMFI of CD127, TCF-1 and IL-18R1 expression within the respective marker-positive cells (c). Data are representative of 3 individual experiments with n=4 mice per group (a-c). d-g Analysis of an unbiased ILCP core signature derived from a scRNA-seq dataset of M progenitors generated by Harly et al29. Violin plots display ILCP score calculation and heat maps display individual gene expression across identified clusters (d, f) and in the dataset generated by Harly et al29(e, g). ALP - all-lymphoid progenitors, sEILP - specific early innate lymphoid progenitors, cEILP - committed early innate lymphoid progenitors, ILCP - innate lymphoid progenitors. Bar graphs indicate individual mice (symbols) and mean (bar), error bars display means ± s.d. Statistical significance was calculated by unpaired two-tailed t-test; **P < 0.01, ***P < 0.001, ****P < 0.0001.

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Extended Data Fig. 6 Effector differentiation of ILC1s is regulated by Hobit across tissues.

a Gating strategy identifying ILC1s among live CD45+ cells in the small intestine lamina propria for data depicted in Fig. 7a. To preserve the HobitTom signal, cells were gated without transcription factor staining. ILC1 (1) were enriched as Lin− NKp46+ NK1.1hiCD90int CXCR6+ CD127+ cells, NK cells (2) were gated as Lin− NKp46+ NK1.1hi CD90int CXCR6− CD127− cells, NKp46+ ILC3 were gated as Lin− NKp46+ CD90hi cells. Purity of gating strategy is displayed by analysis of RORγt and Eomes (right). b-q Analysis of ILC1 in salivary glands (b-e), kidneys (f-i), mesenteric lymph nodes (j-m) and small intestine lamina propria (n-q). b, f, j, n Representative FACS analysis of Lin−NK1.1+ cells (left row of FACS plots) and Eomes−CD49a+ ILC1s (middle and right row) of WT and HobitKO mice. b Representative FACS plot identifying ILC1 (Eomes−CD49a+), Eomes+CD49a+NK1.1+ cells (Eomes+CD49a+) and cNK cells (Eomes+CD49a−) within Lin−NK1.1+ cells (left panel). c, g, k, o Bar graphs indicate absolute numbers of ILC1. d, h, l, p Frequency of ILC1s expressing indicated marker proteins. e, i, m, q gMFI of CD127, TCF-1 and IL-18R1 expression within ILC1 that are gated as positive for the respective marker. Data are representative of 3 independent experiments with n=3 (c, e), n=4 (j, l, m, p, q) and n=5 (b, d, f-i, k, o) mice per group. Bar graphs indicate individual mice (symbols) and mean (bar), error bars display means ± s.d. Statistical significance was calculated by unpaired two-tailed t-test; *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001.

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Extended Data Fig. 7 Analysis of ILC1s in mixed bone marrow chimeric mice and upon inducible deletion of Hobit.

Representative FACS analysis of ILC1s in salivary glands (a, b, g, h), kidneys (c, d, i, j) and small intestine lamina propria (e, f) of mixed bone marrow chimeric mice (a-f) or UbiCre-ERT2 Hobitfl/fl mice and littermate controls on d35 after Tamoxifen treatment (g-j). Bar graphs indicate frequency of ILC1s expressing indicated proteins. Data are representative of 2 (e, f) or 3 (a-d, g-j) individual experiments with n=3 (f), n=4 (a-d, g-j) and n=5 (d, h, j) mice per group. Bar graphs indicate individual mice (symbols) and mean (bar), error bars display means ± s.d. Statistical significance was calculated by unpaired two-tailed t-test; *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001.

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Extended Data Fig. 8 Hobit regulates the effector differentiation of Eomes+CD49a+ group 1 ILCs, and phenotype of ILC1s in Treg cell-depleted mice.

a-e FACS analysis of Eomes+CD49a+ tissue-resident NK1.1+ cells in salivary glands of WT and HobitKO mice. a Representative FACS analysis of HobitTom expression within ILC1 (CD49b−CD49a+), Eomes+CD49a+NK1.1+ cells (identified by gating as CD49b+CD49a+, to avoid permeabilization for the analysis of the HobitTom reporter signal) and cNK cells (CD49b+CD49a−) within Lin−NK1.1+ cells. b Absolute numbers of Eomes+CD49a+NK1.1+ cells. c Representative FACS analysis showing indicated marker expression. d Frequency of marker-positive cells. e gMFI of TCF-1 and IL-18R1 expression within marker-positive cells. Data are representative of 3 independent experiments with n=3 mice per group. f Representative FACS plots show expression of indicated proteins of ILC1s in kidneys, mesenteric lymph nodes and small intestine lamina propria of FoxP3DTR mice on d8 of Treg cell depletion (DTx). Data are representative of 2-3 independent experiments with n=4 mice per group. Bar graphs indicate individual mice (symbols) and mean (bar), error bars display means ± s.d. Statistical significance was calculated by unpaired two-tailed t-test; **P < 0.01, ***P < 0.001.

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Friedrich, C., Taggenbrock, R.L.R.E., Doucet-Ladevèze, R. et al. Effector differentiation downstream of lineage commitment in ILC1s is driven by Hobit across tissues. Nat Immunol 22, 1256–1267 (2021). https://doi.org/10.1038/s41590-021-01013-0

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