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The transcription factor LRF promotes integrin β7 expression by and gut homing of CD8αα+ intraepithelial lymphocyte precursors

Nature Immunology volume 23, pages 594–604 (2022)Cite this article

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Abstract

While T cell receptor (TCR) αβ+CD8α+CD8β– intraepithelial lymphocytes (CD8αα+ IELs) differentiate from thymic IEL precursors (IELps) and contribute to gut homeostasis, the transcriptional control of their development remains poorly understood. In the present study we showed that mouse thymocytes deficient for the transcription factor leukemia/lymphoma-related factor (LRF) failed to generate TCRαβ+CD8αα+ IELs and their CD8β-expressing counterparts, despite giving rise to thymus and spleen CD8αβ+ T cells. LRF-deficient IELps failed to migrate to the intestine and to protect against T cell-induced colitis, and had impaired expression of the gut-homing integrin α4β7. Single-cell RNA-sequencing found that LRF was necessary for the expression of genes characteristic of the most mature IELps, including Itgb7, encoding the β7 subunit of α4β7. Chromatin immunoprecipitation and gene-regulatory network analyses both defined Itgb7 as an LRF target. Our study identifies LRF as an essential transcriptional regulator of IELp maturation in the thymus and subsequent migration to the intestinal epithelium.

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Fig. 1: LRF is needed for IEL development.
Fig. 2: LRF is required for IELp immunoregulatory functions.
Fig. 3: LRF is required for IELp gut homing.
Fig. 4: LRF is required for α4β7 expression on IELp.
Fig. 5: Impact of LRF on the IELp transcriptome.
Fig. 6: LRF binds the Itgb7 locus.
Fig. 7: LRF is needed for acquisition of the mature IEL transcriptome.

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Data availability

All sequence data reported in the present study are publicly available on the Gene Expression Omnibus, at accession nos. GSE149993, GSE149943, GSE149985, GSE186164 and GSE186291 for LRF ChIP–seq, RNA-seq, scRNA-seq and scATAC-seq, respectively. All datasets generated and/or analyzed during the present study are presented in this published article. Source data are provided with this paper. All the other relevant data are available upon request.

Code availability

No customized code was developed in the present study. Flow cytometry, statistical and bioinformatics analyses were performed using publicly available software packages, as indicated in Methods.

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Acknowledgements

We thank P. Subramanian (Office of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases (NIAID)) for assistance with microbiome analyses, the Center for Cancer Research (CCR) Flow Cytometry Core, the NIH high-performance computing cluster and the NIAID microbiome program for assistance, and W. J. Chen, J. Brenchley and M. S. Vacchio for critical reading of the manuscript. This work was supported by the Intramural Research Program of the NCI, CCR, NIH and the Intramural Research Programs of the NIAID and NINDS. The CCR Single Cell Analysis Facility is funded by the Frederick National Laboratory for Cancer Research (contract no. 75N91019D00024). Sequencing was performed using the CCR Genomics Core.

Author information

Author notes

  1. Andrea C. Carpenter

    Present address: Inflammation and Innate Immunity Unit, Laboratory of Clinical Immunology and Microbiology, National Institute of Allergy and Infectious Disease, NIH, Bethesda, MD, USA

  2. Thomas Ciucci

    Present address: David H. Smith Center for Vaccine Biology and Immunology, Department of Microbiology and Immunology, University of Rochester Medical Center, Rochester, NY, USA

  3. These authors contributed equally: Andrea C. Carpenter, Laura B. Chopp.

Authors and Affiliations

  1. Laboratory of Immune Cell Biology, Center for Cancer Research, National Cancer Institute, National Institutes of Health (NIH), Bethesda, MD, USA

    Jia Nie, Andrea C. Carpenter, Laura B. Chopp, Ting Chen, Mariah Balmaceno-Criss, Thomas Ciucci, Qi Xiao & Rémy Bosselut

  2. Immunology Graduate Group, University of Pennsylvania Medical School, Philadelphia, PA, USA

    Laura B. Chopp

  3. CCR Single Analysis Facility, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Bethesda, MD, USA

    Michael C. Kelly

  4. Viral Immunology and Intravital Imaging Section, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD, USA

    Dorian B. McGavern

  5. Metaorganism Immunology Section, Laboratory of Immune System Biology, Bethesda, MD, USA

    Yasmine Belkaid

  6. Microbiome core, National Institute of Allergy and Infectious Disease, NIH, Bethesda, MD, USA

    Yasmine Belkaid

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Contributions

J.N. and R.B. conceived the research and designed experiments with contributions from A.C., D.B.M., M.K. and Y.B. J.N. and A.C. performed experiments, with assistance from X.Q. They also analyzed the data. J.N., L.C. and T. Chen performed bioinformatics analyses with contributions from T. Ciucci, J.N. and M.B.-C. R.B. wrote the manuscript with input from other co-authors and supervised the research.

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Correspondence to Rémy Bosselut.

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Extended data

Extended Data Fig. 1 Characterization of LRF KO mice.

(a) LRF expression (MFI) of indicated cells in Fig. 1a relative to LRF MFI in LRF-KO CD8+ splenocytes, set to 1. Data summarizes two independent experiments with a total of three mice. (b) (left) CD8α vs. CD4 expression on TCRβ+ cells in thymus, spleen, and mLN from Ctrl and LRF KO mice.(right) Number (bottom) and percentage (among TCRαβ+ cells) of CD4–CD8α+ T cells. Data summarizes five independent experiments with a total of 4 (thymus), 16 (spleen), and 9 (mLN) mice of each genotype. (c) Serum concentration of soluble CD14 (sCD14) in Ctrl (n = 5) and LRF KO (n = 5) mice. Data summarizes two independent experiments. (d) Microbial communities in the small intestine luminal contents and mucosal-associated fraction from Ctrl (n = 5) and LRF KO (n = 5) mice. Data are from one experiment representative of two (the other being shown in Fig. 1d), each column representing one mouse. Color code as in Fig. 1d. (e) Expression of intra-cellular LRF in indicated IEL from Ctrl and LRF KO mice. (f, g) (left) Expression of CD45.2 vs. CD45.1 in TCRβ+ CD4+ CD8α– and CD4+ CD8α+ IEL (f), and CD4–CD8α+ splenocytes (g) from bone marrow chimera analyzed in Fig. 1e. (right) Tester/competitor ratios in indicated subsets, normalized to tester/competitor ratio of B220+ splenocytes. Data summarizes two independent experiments with a total of 6 mice per group. In (f), tester-competitor ratios (average ± SEM) were 0.78 ± 0.082 (Ctrl) and 0.33 ± 0.031 (KO) for CD4+CD8α– IEL, and 0.54 ± 0.043 (Ctrl) and 0.09 ± 0.008 (KO) for CD4+CD8α+ IEL. (h) (left) CD8α vs. CD4 expression on lamina propria TCRβ+ cells from Ctrl and LRF KO mice. (right) Percentage (top) and absolute number (bottom) of CD4+ and CD8+ cells among TCRβ+ cells. Data summarizes four independent experiments with a total of 4 mice per genotype. Error bars indicate standard error of the mean (SEM). P values are from two-tailed unpaired t-test (b, c, d, f, g and h). (a-d, f-h): Each symbol represents one mouse.

Source data

Extended Data Fig. 2 Development of LRF KO IELp.

(a) LRF expression in indicated subsets from Cd4cre+ Thpokfl/fl mice (to exclude cross reactive staining of Thpok by the LRF antibody). LRF KO TCRβ+ CD4–CD8+ splenocytes are shown as a control (grey-shaded). Data are from one experiment representative of two with 4 mice total. Graph (right) summarizes LRF expression (MFI) of indicated cells relative to that in wild-type IELp (analyzed as reference in each experiment), set to 1. (b) CD45.2 vs. CD45.1 expression in IELp from bone marrow chimera analyzed in Fig. 1e. Graphs (right) show tester/competitor ratios in IELp normalized to tester/competitor ratio of B220+ splenocytes and summarize two independent experiments totaling 6 mice per group. (c) Overlaid expression of Bim (left) and Bcl2 (right) in gated Ctrl and LRF KO IELp. Graphs (right) show the indicated protein expression (MFI) in IELp relative to that in IELp from wild type mice, set at 100 in each experiment. Data summarizes two independent experiments totaling 3 Ctrl and 4 LRF KO mice. (d) Contour plots show cleaved Caspase3 levels vs. FSC in wild-type CD4+CD8α+ or immature Bim+ CD4+ SP (Bim+ CD4+ CD8– CD69+ MHC-I–) thymocytes, and in Ctrl and LRF KO IELp. Data are from one experiment representative of two with a total of 3 Ctrl mice and 4 LRF KO mice. (e, f) Staining for extra-cellular annexin V and cell viability (L/D) on Ctrl and LRF KO IELp after in vitro culture for 0 h, 2 h or 4 h (e). Graph (f) summarizes the percent of L/D–Annexin V+ cells among IELp, from 4 Ctrl and 5 LRF KO mice analyzed in two independent experiments. (g, h) Total numbers of (g), and CD8α vs. CD8β expression by (h, left), Ctrl and LRF KO IELp after 4−day in vitro culture with the indicated IL-15 concentration. Right graph in (h) shows numbers of CD8αα and CD8αβ cells. Data is from three determinations for each genotype, acquired in two independent experiments Error bars indicate standard error of the mean (SEM). P values are from two-tailed unpaired t-test (b, c) or two-way ANOVA (g, h). (a-c, f-h) Each symbol in graphs represents one mouse.

Source data

Extended Data Fig. 3 Impact of LRF on IELp homing.

(a) Graph shows the absolute number of the indicated TCRβ+ tester cells (Ctrl or LRF KO) among IEL or spleen T cells analyzed in Fig. 3ab. Data are from one experiment (5 mice per group) representative of two. (b) CD8α vs. CD8β expression on TCRαβ+ CD8α+ splenocytes from bone marrow chimera analyzed in Fig. 1e. Graph (right) shows the percentage of CD8αα cells among TCRαβ+ CD8α+ splenocytes. Data pooled from two independent experiments with a total of 6 mice per group. Each symbol represents one mouse. (c-e) NSG host mice were adoptively transferred with a 1:1 mixture of CD45.2+ tester (either Ctrl or LRF KO) and CD45.1+CD45.2+ competitor CD8αβ splenocytes, and analyzed one week after transfer. Data are from one experiment (5 Ctrl and 4 KO mice) representative of two. (c) Schematic of the experiment (d, e) Top contour plots show CD45.2 vs. CD45.1 expression in TCRβ+ CD45.2+ splenocytes (d) and IEL (e). Colored boxes define Ctrl (blue) and KO (red) testers populations assessed for CD8α vs. CD8β expression in bottom contour plots. Top right graphs show tester/competitor ratios in each organ. Each symbol represents one mouse. Bottom right panel in (e) shows CD8α vs. CD8β expression on CD8α+ IEL from an unmanipulated C57BL/6 (WT) mouse. Error bars indicate standard error of the mean (SEM). P values (a, b, d, e) are from two-tailed unpaired t-test.

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Extended Data Fig. 4 Effect of LRF on thymocyte α4β7 expression.

(a) Histogram overlays show the expression of α4β7 on wild-type IELp and conventional CD8+ SP thymocytes cells. Gray-shaded histogram (Bkgd) shows background of PE fluorochrome signal in IELp from Ctrl mice for which the primary α4β7 antibody was omitted from the staining mix. Right graphs show protein expression (MFI), computed on cells expressing each protein (left plot bracket). (b) Histogram (left) shows the expression of α4β7 on TCRβhiCD8α+ SP thymocytes from Ctrl or LRF KO mice, displayed as in (a). Graph (right) shows the percentage of α4β7+ cells among TCRβhi CD8α+ SP thymocytes. (c) Expression of α4β7 on Ctrl (solid line) and LRF KO (dashed line) TCRβhiCD4+ SP thymocytes, displayed as in (a). (a-c) Data are from one experiment (4 mice per group) representative of two. Each symbol in summary graphs represents one mouse. Error bars indicate standard error of the mean (SEM). P values (a, b) are from two-tailed unpaired t-test.

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Extended Data Fig. 5 Control of IELp gene expression by LRF.

(a-b) Population RNAseq of thymic IELp. (a) Scatter plots compare gene expression (Log2 values, full gene set) in Ctrl vs. KO IELp. Genes with two-fold or greater differential expression between genotypes (and FDR < 0.01) are shown in blue or red. (b) RNAseq expression levels (counts per million) of Itgb7 and Itga4 genes in IELp from Ctrl and KO mice. Error bars indicate SEM. P values are from two-tailed unpaired t-test. (c-f) ScRNAseq of thymic IELp from Ctrl and KO mice. (c) UMAP analysis of IELp, performed as in Fig. 5a, displayed separately for each experiment and color-coded by genotype. (d) Bar plots indicate the Ctrl (gray) vs. LRF KO (red) genotype distribution of IELp clusters referred to in Fig. 5a,b. (e) Violin plot shows the expression of Lrf in indicated clusters from Ctrl IELp. (f) Volcano plot showing differentially expressed genes (FDR < 0.05, |Log2FC | >0.25) between Ctrl T4 (mature) and LRF KO T2 (intermediate) IELp clusters. Blue and red symbols indicate genes preferentially expressed in KO and Ctrl IELp, respectively.

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Extended Data Fig. 6 Control of IEL gene expression by LRF.

(a-d) scRNAseq of CD8αα IEL from Ctrl and CD8αα splenocytes from KO mice. (a) Top plots show sorting strategy for CD8αα splenocytes and CD8αα IEL purification. Bottom graphs show the purity of indicated sorted subsets used for scRNAseq analyses (Fig. 7c-f). (b) UMAP plot of Ctrl CD8αα IEL and KO CD8αα splenocytes, as in Fig. 7c, displayed separately for each experiment and color-coded by genotype. (c) Bar plots indicate the Ctrl (gray) vs. LRF KO (red) genotype distribution of CD8αα clusters referred to in Fig. 7c-f. (d) Heatmap shows row-standardized expression of selected genes among triplicate RNAseq samples from the indicated populations (color scale at right).

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Nie, J., Carpenter, A.C., Chopp, L.B. et al. The transcription factor LRF promotes integrin β7 expression by and gut homing of CD8αα+ intraepithelial lymphocyte precursors. Nat Immunol 23, 594–604 (2022). https://doi.org/10.1038/s41590-022-01161-x

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