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Reciprocal transcription factor networks govern tissue-resident ILC3 subset function and identity

Nature Immunology volume 22, pages 1245–1255 (2021)Cite this article

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Abstract

Innate lymphoid cells (ILCs) are guardians of mucosal immunity, yet the transcriptional networks that support their function remain poorly understood. We used inducible combinatorial deletion of key transcription factors (TFs) required for ILC development (RORγt, RORα and T-bet) to determine their necessity in maintaining ILC3 identity and function. Both RORγt and RORα were required to preserve optimum effector functions; however, RORα was sufficient to support robust interleukin-22 production among the lymphoid tissue inducer (LTi)-like ILC3 subset, but not natural cytotoxicity receptor (NCR)+ ILC3s. Lymphoid tissue inducer-like ILC3s persisted with only selective loss of phenotype and effector functions even after the loss of both TFs. In contrast, continued RORγt expression was essential to restrain transcriptional networks associated with type 1 immunity within NCR+ ILC3s, which coexpress T-bet. Full differentiation to an ILC1-like population required the additional loss of RORα. Together, these data demonstrate how TF networks integrate within mature ILCs after development to sustain effector functions, imprint phenotype and restrict alternative differentiation programs.

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Fig. 1: RORα and RORγt combine to preserve functions in NCR+, but not LTi-like, ILC3 subsets.
Fig. 2: NCR+ ILCs undergo extensive transcriptomic changes upon TF deletion.
Fig. 3: Loss of both RORγt and RORα expression within NCR+ ILCs drives full differentiation to a mature ILC1-like phenotype.
Fig. 4: Ex-ILC3s and ILC1s exhibit a comparable spectrum of phenotypes within the SILP.
Fig. 5: RORα expression is sufficient to preserve IL-23-mediated expression of IL-22 by non-LTi-like ILC3s in the absence of RORγt and T-bet.

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Data availability

scRNA-seq data on ‘understanding transcriptional identity in ILCs’ are available in the ArrayExpress database under accession no. E-MTAB-9795. ATAC–seq data are available in NCBI’s Gene Expression Omnibus60 under accession number GSE163149. Further information and requests for resources should be directed to and will be fulfilled by the corresponding authors. Source data are provided with this paper.

Code availability

The custom code used did not differ significantly from the intended implementation that we referenced nor did it contain any new math. The custom R code was used only for visualization in this study.

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Acknowledgements

We thank A. Ptasinska (Institute of Cancer and Genomic Sciences, University of Birmingham), for advice and help with ATAC–seq experiments, Genomics Birmingham, the genomic and sequencing facility of the University of Birmingham, and the University of Birmingham Flow Cytometry Platform. We thank G. Howell and the University of Manchester flow cytometry core, and A. Hayes and C. Morrisroe in the University of Manchester Genomic Technologies core facility for their help with scRNA-seq. We thank G. Frankel (Imperial College, London), for the provision of C. rodentium ICC169. We thank the following for their kind provision of mice: D. Littman (Howard Hughes Medical Institute, New York; Rorccre mice), A. McKenzie (MRC-LMB, Cambridge; Rorafl/fl mice), B. Stockinger (The Francis Crick Institute, London; Il17acre mice), S. Reiner (Columbia University, New York; Tbx21fl/fl mice) and J. Fehling (Ulm University, Germany; Rosa26tdRFP mice). We thank C. Stehle and C. Romagnani (Charité University Medicine Berlin, Germany) for critical discussion of data and the manuscript. This work was supported by a Senior Research Fellowship from the Wellcome Trust to D.R.W. (110199/Z/15/Z) and by a Royal Society and Wellcome Trust Sir Henry Dale Fellowship (105644/Z/14/Z) and a Lister Institute of Preventative Medicine Prize to M.R.H. This work was also supported by a Wellcome Trust ISSF funding award (105610/Z/14/Z) to M.R.H. C.M.F. was supported by a Wellcome Investigator award (106898/A/15/Z) to J. E. Allen.

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Author notes

  1. These authors contributed equally: Matthew R. Hepworth, David R. Withers.

Authors and Affiliations

  1. Institute of Immunology and Immunotherapy, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK

    Rémi Fiancette, Claire Willis, Sky T. H. Ng & David R. Withers

  2. Lydia Becker Institute of Immunology and Inflammation, Division of Infection, Immunity and Respiratory Medicine, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK

    Conor M. Finlay, Syed Murtuza Baker & Matthew R. Hepworth

  3. Institute of Cancer and Genomic Sciences, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK

    Sarah L. Bevington & Jake Soley

  4. Division of Informatics, Imaging & Data Science, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK

    Syed Murtuza Baker

  5. Bioinformatics Group, The Babraham Institute, Cambridge, UK

    Simon Andrews

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Contributions

R.F. designed and performed experiments, analyzed data and contributed to writing the manuscript. C.M.F. analyzed sequencing data and performed in silico experiments. C.W., S.L.B. and J.S. performed and assisted with experiments. S.T.H.N., S.M.B. and S.A. analyzed sequencing data and provided extensive bioinformatics support. M.R.H. designed and performed experiments, analyzed data and wrote the manuscript. D.R.W. designed experiments, analyzed data and wrote the manuscript.

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Correspondence to Matthew R. Hepworth or David R. Withers.

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Peer review information Nature Immunology thanks the anonymous reviewers for their contribution to the peer review of this work. Peer reviewer reports are available. 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 ILC3 subset-specific deletion of TFs reveals that LTi-like cells express normal levels of IL-22 in the absence of both RORγt and RORα.

Il-17acre mice were used to enable ILC3 subset specific targeting of TF-deletion. a Gating strategy for identification of tdRFP+ ILCs from SILP of Il17acre mice. b Expression of RORγt versus NKp46 by tdRFP− and tdRFP+ ILCs from SILP of Il17acre mice. c Proportion of ILCs in the SILP of Il17acre mice that express tdRFP at different ages (wks) post birth. d Representative CCR6, CD4, c-Kit, NK1.1 and NKp46 expression by tdRFP+ ILCs from SILP of Il17acre mice. e Proportion of tdRFP+ ILCs from SILP of Il17acre mice expressing molecules assessed in ‘d’. f Representative expression of RORγt versus CD127 by tdRFP− and tdRFP+ ILCs from SILP of Il17acre, Il17aΔRORγt and Il17aΔRORγt/RORα mice. g Percentage of tdRFP− and tdRFP+ ILCs expressing RORγt (Il17acre: n = 12; Il17aΔRORγt: n = 11; from 4 independent experiments). h Representative expression of RORγt versus IL-17A and IL-22 by tdRFP+ ILCs from SILP of Il17acre, Il17aΔRORγt and Il17aΔRORγt/RORα mice. i Total number of tdRFP+ ILCs from SILP of Il17acre, Il17aΔRORγt and Il17aΔRORγt/RORα mice expressing IL-17A (top) and IL-22 (bottom) (Il17acre: n = 19; Il17aΔRORγt: n = 14; Il17aΔRORγt/RORα: n = 19; from 6 independent experiments). Each data point on graphs is a mouse, horizontal bars denote the median. Statistical significance in ‘g’ was tested using unpaired two-tailed Student’s t tests, and in ‘i’ an ordinary one-way ANOVA with Tukey’s test for multiple comparisons. ns = not significant, **P ≤ 0.01, ****P ≤ 0.0001. Exact P values are provided in the source data.

Source data

Extended Data Fig. 2 Efficient inducible deletion of targeted transcription factors in Id2creERT2, Id2iΔRORγt, Id2iΔRORγt/RORα and Id2iΔRORγt/Tbet mice.

a Representative histograms showing expression of RORγt (upper row) and T-bet (lower row) by tdRFP+KLRG1- ILCs from SILP of Id2creERT2, Id2iΔRORγt, Id2iΔRORγt/RORα and Id2iΔRORγt/Tbet mice, dotted line denotes positive/negative staining. b Proportion of tdRFP+KLRG1- ILCs expressing RORγt and T-bet in Id2creERT2 (n=20), Id2iΔRORγt (n=13), Id2iΔRORγt/RORα (n=8) and Id2iΔRORγt/Tbet (n=17) mice (Data are representative of 7 independent experiments). c Schematics of Rorc and Rora cDNA showing exons, the location of LoxP sites and the qPCR primer annealing sites, floxed exons removed by cre-mediated deletion are in light grey. Relative expression of transcripts for the exon3-exon4, exon7-exon8 and exon8-exon9 junctions of the Rorc locus (d) and for the exon3-exon4, exon7-exon8 and exon9-exon10 junctions of the Rora locus (e) as depicted in ‘c’, determined by qPCR analysis of cDNA prepared from tdRFP+ ILCs sorted from SILP of Id2creERT2 (n=5), Id2iΔRORγt (n=7), Id2iΔRORγt/RORα (n=4) and Id2iΔRORγt/Tbet (n=2) mice (Data are representative of 3 independent experiments). f Mapping of the reads detected by scRNA-seq along the Rorc locus in tdRFP+ ILCs from SILP of Id2creERT2, Id2iΔRORγt, Id2iΔRORγt/RORα and Id2iΔRORγt/Tbet mice. The localisation of LoxP-flanked exons is depicted by a grey box. Each data point on graphs is a mouse, horizontal bars in ‘b’ denote the median, bars in ‘d’ and ‘e’ denote the mean, with error bars denoting the SEM. Statistical significance in ‘b’ was tested using an ordinary one-way ANOVA with Dunnett’s test for multiple comparisons. ****P ≤ 0.0001.

Source data

Extended Data Fig. 3 Expression of key genes associated with ILC superclusters.

a t-SNE plot showing ILC superclusters within all samples (Id2creERT2, Id2iΔRORγt, Id2iΔRORγt/RORα and Id2iΔRORγt/Tbet mice). b Gene expression (ALRA-imputed values) of core ILC genes unique and shared amongst ILC superclusters.

Extended Data Fig. 4 Binary regulon activity within ILC clusters.

a t-SNE plots generated from transcriptome (normalised and log-transformed counts) and b binary regulon activity (On/Off) generated via SCENIC analysis of cells within the 4 samples. c Heatmap of the mean binary regulon activity for all cells within each of the 11 transcriptomically-defined clusters. Regulons were filtered to exclude those which were rarely (< 4%) or constitutively (> 60%) active across all cells in the dataset. d Regulon specificity score for each of the 5 superclusters generated from regulon enrichment scores in each cell calculated using AUCell step of the SCENIC pipeline. Top 8 most specific regulons in each supercluster, relative to the entire dataset, are highlighted in red. e Gata3, Rorc and Tbx21 mRNA expression (ALRA-imputed values, top) and binary regulon activity (bottom).

Extended Data Fig. 5 RORγt and RORα combine to regulate the chromatin landscape of ILC3s.

To further investigate how transcriptomic changes after TF deletion might be influenced by alterations to the chromatin landscape, FACS-isolated tdRFP+ KLRG1- ILCs from Id2creERT2, Id2iΔRORγt, Id2iΔRORγt/RORα and Id2iΔRORγt/Tbet mice were assessed by ATAC-seq. a Principal component analysis of all samples using merged MACS2 broad peaks quantitated with size factor normalized reads per million (RPM). b Heat map showing all initial comparison of 10,910 significant changes in areas of open chromatin. c Primary genomic location of peaks and relative peak abundance around transcription start sites. d Heatmap of differentially enriched peaks between all knockouts (n = 2306) based on median centered size factor normalized log2RPM values, also showing the abundance of ROR response elements (RORE) and TBX21 motifs. Groups A to E refer to the distinct patterns of changes to open chromatin across the mouse models. e UCSC genome browser display of mouse Id2, Il17a/Il17f and Il22 loci with average traces from ILCs from Id2creERT2 (blue), Id2iΔRORγt (yellow), Id2iΔRORγt/RORα (red) and Id2iΔRORγt/Tbet (green) mice, alongside RORγt (49) and T-bet (50) ChIP-seq data, with RORE and TBX21 motifs marked.

Extended Data Fig. 6 Altered metabolism profile in LTi-like ILC3s lacking RORγt and RORα.

a Relative expression (z-score) of key genes associated with LTi-like ILC3 identification and function in clusters 2-4 (LTi-like supercluster) versus clusters 5 (NCR+ ILC3) and 9 (ILC1-like cells enriched in Id2iΔRORγt/RORα mice). b Representative expression of CCR6, c-Kit and NRP1 by NCR- ILC3s, identified as tdRFP+KLRG1-NKp46- cells from SILP of Id2creERT2, Id2iΔRORγt and Id2iΔRORγt/RORα mice, grey shaded histograms show expression by NCR+ ILC3s as a control. c Representative contour plots showing expression of MHCII by NCR- ILC3s from the SILP of Id2creERT2, Id2iΔRORγt and Id2iΔRORγt/RORα mice. d Heatmap (z-score) of differentially expressed genes identified via a three way comparison of LTi-like ILC3 cells (clusters 2-4 combined) derived from Id2creERT2, Id2iΔRORγt and Id2iΔRORγt/RORα mice and selected on the basis of a mean expression ≥0.1 fpkm, False Discovery Rate ≤0.001 and Fold Change in cluster average Z-score > +/− 0.4 . e Relative expression (z-score) of selected metabolism associated genes in total LTi-like ILC3 cells (cluster 2-4 combined) derived from Id2creERT2, Id2iΔRORγt and Id2iΔRORγt/RORα mice. f Representative protein expression of ARG1 in tdRFP+ LTi-like ILC3s from SILP of Id2creERT2, Id2iΔRORγt and Id2iΔRORγt/RORα mice. g Enumeration of % ARG1+ LTi-like ILCs and of the mean fluorescence intensity (MFI) of ARG1 expression assessed in ‘f’ (Id2cre: n=3; Id2iΔRORγt: n=3; Id2iΔRORγt/RORα: n=2. Data from one representative experiment out of two independent experiments). Each data point on the graph is a mouse, horizontal bars denote the median. Statistical significance was tested using an ordinary one-way ANOVA with Tukey’s test for multiple comparisons. ns = not significant, *P ≤ 0.05, **P ≤ 0.01, ***P ≤ 0.001, ****P ≤ 0.0001. Exact P values are provided in the source data.

Source data

Extended Data Fig. 7 Continued RORα expression maintains optimum Arg1 expression by ILC2s.

a Differentially expressed genes amongst ILC2 clusters in Id2creERT2 and Id2iΔRORγt/RORα. Log fold change ≥1.0, mean expression ≥0.1 fpkm, False Discovery Rate ≤0.02. Core ILC2 genes (no significant change) included for comparison. b Violin plots showing Arg1 expression (normalised and log-transformed counts) within the ILC2 cluster identified in Id2creERT2, Id2iΔRORγt, Id2iΔRORγt/RORα and Id2iΔRORγt/Tbet samples. c Representative protein expression of ARG1 in tdRFP+ ILC2s (KLRG1+ ILCs) from SILP of control Id2creERT2 and Id2iΔRORγt/RORα mice. d Percentage of ARG1+ ILC2s (tdRFP+ KLRG1+ ILCs) and MFI of ARG1 expression by ARG1+ ILC2s isolated from the SILP of control Id2creERT2 and Id2iΔRORγt/RORα mice (Id2creERT2: n = 5; Id2iΔRORγt/RORα: n = 3). Each data point on graphs is a mouse, horizontal bars denote the median. Statistical significance was tested using unpaired two-tailed Student’s t tests, *P ≤ 0.05. Exact P values are provided in the source data.

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Extended Data Fig. 8 Validation of transcriptomic changes induced by deletion of RORγt and RORα.

Relative expression of S100a4 (a) and Xcl1 (b) transcripts determined by qPCR analysis of cDNA prepared from tdRFP+ ILCs sorted from SILP of Id2creERT2 (n = 5), Id2iΔRORγt (n = 7), Id2iΔRORγt/RORα (n = 4) and Id2iΔRORγt/Tbet (n = 2) mice (Data are representative of 3 independent experiments). c Representative expression of CD94, NKG2, CD244 and NKp46, versus NK1.1, by tdRFP+ ILCs from SILP of Id2creERT2, Id2iΔRORγt, Id2iΔRORγt/RORα and Id2iΔRORγt/Tbet mice. d UCSC genome browser display of mouse Klrc1, Klrd1, Gzma and Ccl3/4 loci with average traces from ILCs from Id2creERT2 (blue), Id2iΔRORγt (yellow), Id2iΔRORγt/RORα (red) and Id2iΔRORγt/Tbet (green) mice, alongside RORγt (49) and T-bet (50) ChIP-seq data, with RORE and TBX21 motifs marked. e Violin plots of Ikzf1 and Ikzf3 expression across clusters 1-11. f Representative expression of Aiolos by ILC2s, NCR+ ILC3s, ILC1s/ex-ILC3s, DN ILC3s and LTi-like ILC3s using flow cytometry. g Percentage of ILC2s, NCR+ ILC3s, ILC1s/ex-ILC3s, DN ILC3s and LTi-like ILC3s expressing Aiolos (n = 4 for each ILC group/subset, data are representative of two independent experiments). Each data point on graphs is a mouse, horizontal bars in ‘a’ and ‘b’ denote the mean, with error bars denoting the SEM; horizontal bars in ‘g’ denote the median. Statistical significance in ‘g’ was tested using an ordinary one-way ANOVA with Tukey’s test for multiple comparisons. ns = not significant, **P ≤ 0.01, ****P ≤ 0.0001. Exact P values are provided in the source data.

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Extended Data Fig. 9 Id2iΔRORγt/Tbet mice are able to control and clear Citrobacter rodentium infection.

To functionally test whether protective intestinal mechanisms were maintained in Id2iΔRORγt/Tbet mice, infection with Citrobacter rodentium was used. a C. rodentium counts expressed as CFU/g feces over the time course of infection in Id2iΔRORγt (n = 4) and Id2iΔRORγt/Tbet (n = 5 or 6 depending on the time point) mice versus littermate ‘no cre’ controls (n = 8; to ensure comparable microbiome). b Relative expression of RegIIIb and RegIIIg in Id2iΔRORγt and Id2iΔRORγt/Tbet mice versus littermate ‘no cre’ controls at 21 dpi with C. rodentium (no cre control: n = 8; Id2iΔRORγt: n = 4; Id2iΔRORγt/Tbet: n = 6). c Histological analysis of colon isolated from Id2creERT2, Id2iΔRORγt and Id2iΔRORγt/Tbet mice at 15 dpi with C. rodentium (n = 3 for each strain, one representative picture from one representative animal per strain). Each data point on graphs is a mouse, bars denote the mean with error bars denoting the SEM. Statistical significance was tested using a one-sided Kruskal-Wallis test with a Dunn’s test for multiple comparisons. *P ≤ 0.05. Exact P values are provided in the source data.

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Supplementary information

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Source Data Fig. 1

Detail of all individual raw data used in graphs in Fig. 1, and exact P values for statistical analyses.

Source Data Fig. 4

Detail of all individual raw data used in graphs in Fig. 4.

Source Data Fig. 5

Detail of all individual raw data used in graphs in Fig. 5, and exact P values for statistical analyses.

Source Data Extended Data Fig. 1

Detail of all individual raw data used in graphs in Extended Data Fig. 1, and exact P values for statistical analyses.

Source Data Extended Data Fig. 2

Detail of all individual raw data used in graphs in Extended Data Fig. 2, and exact P values for statistical analyses.

Source Data Extended Data Fig. 6

Detail of all individual raw data used in graphs in Extended Data Fig. 6, and exact P values for statistical analyses.

Source Data Extended Data Fig. 7

Detail of all individual raw data used in graphs in Extended Data Fig. 7, and exact P values for statistical analyses.

Source Data Extended Data Fig. 8

Detail of all individual raw data used in graphs in Extended Data Fig. 8, and exact P values for statistical analyses.

Source Data Extended Data Fig. 9

Detail of all individual raw data used in graphs in Extended Data Fig. 9, and exact P values for statistical analyses.

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Fiancette, R., Finlay, C.M., Willis, C. et al. Reciprocal transcription factor networks govern tissue-resident ILC3 subset function and identity. Nat Immunol 22, 1245–1255 (2021). https://doi.org/10.1038/s41590-021-01024-x

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