Abstract
T cell differentiation requires Notch1 signaling. In the present study, we show that an enhancer upstream of Notch1 active in double-negative (DN) mouse thymocytes is responsible for raising Notch1 signaling intrathymically. This enhancer is required to expand multipotent progenitors intrathymically while delaying early differentiation until lineage restrictions have been established. Early thymic progenitors lacking the enhancer show accelerated differentiation through the DN stages and increased frequency of B, innate lymphoid (IL) and natural killer (NK) cell differentiation. Transcription regulators for T cell lineage restriction and commitment are expressed normally, but IL and NK cell gene expression persists after T cell lineage commitment and T cell receptor β VDJ recombination, Cd3 expression and β-selection have been impaired. This Notch1 enhancer is inactive in double-positive (DP) thymocytes. Its aberrant reactivation at this stage in Ikaros mutants is required for leukemogenesis. Thus, the DN-specific Notch1 enhancer harnesses the regulatory architecture of DN and DP thymocytes to achieve carefully orchestrated changes in Notch1 signaling required for early lineage restrictions and normal T cell differentiation.
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Data availability
All data that support the findings of the present study are available from the corresponding authors upon request. ChIP–seq and RNA-seq datasets generated during the present study have been deposited in the Gene Expression Omnibus (GEO) under accession nos. GSE186764 and GSE211079. The publicly available NGS datasets used during the present study can be found in the GEO or PRJNA, under accession nos.: GSE60103, GSE73143, GSE61149, GSE115742, GSE33679, GSE32311, GSE77695, GSE183056, GSE109125, GSE15330, GSE128964, GSE95337, GSE33513, GSE154304, GSE93755, GSE115744, PRJNA487507, GSE79422, GSE89848, GSE19923, PRJNA451505, GSE99159, GSE100738, GSE31233, GSE103953, GSE93572, GSE30518, GSE162292, GSE89847, GSE90958, GSE79422; they are listed in Supplementary Table 6. Source data are provided with this paper.
References
Yu, V. W. et al. Specific bone cells produce DLL4 to generate thymus-seeding progenitors from bone marrow. J. Exp. Med. 212, 759–774 (2015).
Tikhonova, A. N. et al. The bone marrow microenvironment at single-cell resolution. Nature 569, 222–228 (2019).
Chen, E. L. Y., Thompson, P. K. & Zuniga-Pflucker, J. C. RBPJ-dependent Notch signaling initiates the T cell program in a subset of thymus-seeding progenitors. Nat. Immunol. 20, 1456–1468 (2019).
Tan, J. B., Visan, I., Yuan, J. S. & Guidos, C. J. Requirement for Notch1 signals at sequential early stages of intrathymic T cell development. Nat. Immunol. 6, 671–679 (2005).
Sambandam, A. et al. Notch signaling controls the generation and differentiation of early T lineage progenitors. Nat. Immunol. 6, 663–670 (2005).
Radtke, F. et al. Deficient T cell fate specification in mice with an induced inactivation of Notch1. Immunity 10, 547–558 (1999).
Wilson, A., MacDonald, H. R. & Radtke, F. Notch 1-deficient common lymphoid precursors adopt a B cell fate in the thymus. J. Exp. Med. 194, 1003–1012 (2001).
Feyerabend, T. B. et al. Deletion of Notch1 converts pro-T cells to dendritic cells and promotes thymic B cells by cell-extrinsic and cell-intrinsic mechanisms. Immunity 30, 67–79 (2009).
Hozumi, K. et al. Delta-like 4 is indispensable in thymic environment specific for T cell development. J. Exp. Med. 205, 2507–2513 (2008).
Koch, U. et al. Delta-like 4 is the essential, nonredundant ligand for Notch1 during thymic T cell lineage commitment. J. Exp. Med. 205, 2515–2523 (2008).
Han, H. et al. Inducible gene knockout of transcription factor recombination signal binding protein-J reveals its essential role in T versus B lineage decision. Int. Immunol. 14, 637–645 (2002).
Pui, J. C. et al. Notch1 expression in early lymphopoiesis influences B versus T lineage determination. Immunity 11, 299–308 (1999).
Dorsch, M. et al. Ectopic expression of Delta4 impairs hematopoietic development and leads to lymphoproliferative disease. Blood 100, 2046–2055 (2002).
Yan, X. Q. et al. A novel Notch ligand, Dll4, induces T-cell leukemia/lymphoma when overexpressed in mice by retroviral-mediated gene transfer. Blood 98, 3793–3799 (2001).
Yui, M. A. & Rothenberg, E. V. Developmental gene networks: a triathlon on the course to T cell identity. Nat. Rev. Immunol. 14, 529–545 (2014).
Rothenberg, E. V., Ungerback, J. & Champhekar, A. Forging T-lymphocyte identity: intersecting networks of transcriptional control. Adv. Immunol. 129, 109–174 (2016).
Hosokawa, H. et al. Bcl11b sets pro-T cell fate by site-specific cofactor recruitment and by repressing Id2 and Zbtb16. Nat. Immunol. 19, 1427–1440 (2018).
Wakabayashi, Y. et al. Bcl11b is required for differentiation and survival of alphabeta T lymphocytes. Nat. Immunol. 4, 533–539 (2003).
Wolfer, A., Wilson, A., Nemir, M., MacDonald, H. R. & Radtke, F. Inactivation of Notch1 impairs VDJbeta rearrangement and allows pre-TCR-independent survival of early alpha beta lineage thymocytes. Immunity 16, 869–879 (2002).
Tanigaki, K. et al. Regulation of alphabeta/gammadelta T cell lineage commitment and peripheral T cell responses by Notch/RBP-J signaling. Immunity 20, 611–622 (2004).
Schmitt, T. M., Ciofani, M., Petrie, H. T. & Zuniga-Pflucker, J. C. Maintenance of T cell specification and differentiation requires recurrent notch receptor-ligand interactions. J. Exp. Med. 200, 469–479 (2004).
Ciofani, M. et al. Obligatory role for cooperative signaling by pre-TCR and Notch during thymocyte differentiation. J. Immunol. 172, 5230–5239 (2004).
Ciofani, M. & Zuniga-Pflucker, J. C. Notch promotes survival of pre-T cells at the beta-selection checkpoint by regulating cellular metabolism. Nat. Immunol. 6, 881–888 (2005).
Maillard, I. et al. The requirement for Notch signaling at the beta-selection checkpoint in vivo is absolute and independent of the pre-T cell receptor. J. Exp. Med. 203, 2239–2245 (2006).
Taghon, T., Yui, M. A., Pant, R., Diamond, R. A. & Rothenberg, E. V. Developmental and molecular characterization of emerging beta- and gammadelta-selected pre-T cells in the adult mouse thymus. Immunity 24, 53–64 (2006).
Yashiro-Ohtani, Y. et al. Pre-TCR signaling inactivates Notch1 transcription by antagonizing E2A. Genes Dev. 23, 1665–1676 (2009).
Gomez-del Arco, P. et al. Alternative promoter usage at the Notch1 locus supports ligand-independent signaling in T cell development and leukemogenesis. Immunity 33, 685–698 (2010).
Ashworth, T. D. et al. Deletion-based mechanisms of Notch1 activation in T-ALL: key roles for RAG recombinase and a conserved internal translational start site in Notch1. Blood 116, 5455–5464 (2010).
Jeannet, R. et al. Oncogenic activation of the Notch1 gene by deletion of its promoter in Ikaros-deficient T-ALL. Blood 116, 5443–5454 (2010).
Li, X., Gounari, F., Protopopov, A., Khazaie, K. & von Boehmer, H. Oncogenesis of T-ALL and nonmalignant consequences of overexpressing intracellular NOTCH1. J. Exp. Med. 205, 2851–2861 (2008).
Mingueneau, M. et al. The transcriptional landscape of alphabeta T cell differentiation. Nat. Immunol. 14, 619–632 (2013).
Tsuji, H., Ishii-Ohba, H., Ukai, H., Katsube, T. & Ogiu, T. Radiation-induced deletions in the 5′ end region of Notch1 lead to the formation of truncated proteins and are involved in the development of mouse thymic lymphomas. Carcinogenesis 24, 1257–1268 (2003).
Mumm, J. S. & Kopan, R. Notch signaling: from the outside. Dev. Biol. 228, 151–165 (2000).
Yoshida, T., Ng, S. Y. & Georgopoulos, K. Awakening lineage potential by Ikaros-mediated transcriptional priming. Curr. Opin. Immunol. 22, 154–160 (2010).
Hu, G. et al. Transformation of accessible chromatin and 3D nucleome underlies lineage commitment of early T cells. Immunity 48, 227–242.e228 (2018).
Kaul, A., Bhattacharyya, S. & Ay, F. Identifying statistically significant chromatin contacts from Hi-C data with FitHiC2. Nat. Protoc. 15, 991–1012 (2020).
Porritt, H. E. et al. Heterogeneity among DN1 prothymocytes reveals multiple progenitors with different capacities to generate T cell and non-T cell lineages. Immunity 20, 735–745 (2004).
Zhou, W. et al. Single-cell analysis reveals regulatory gene expression dynamics leading to lineage commitment in early T cell development. Cell Syst. 9, 321–337.e329 (2019).
Ramond, C. et al. Two waves of distinct hematopoietic progenitor cells colonize the fetal thymus. Nat. Immunol. 15, 27–35 (2014).
Suliman, S. et al. Notch3 is dispensable for thymocyte beta-selection and Notch1-induced T cell leukemogenesis. PLoS ONE 6, e24937 (2011).
Georgopoulos, K., van den Elsen, P., Bier, E., Maxam, A. & Terhorst, C. A T cell-specific enhancer is located in a DNase I-hypersensitive area at the 3′ end of the CD3-delta gene. EMBO J. 7, 2401–2407 (1988).
Clevers, H. et al. Characterization and expression of the murine CD3-epsilon gene. Proc. Natl Acad. Sci. USA 85, 8623–8627 (1988).
Satoh-Takayama, N. et al. IL-7 and IL-15 independently program the differentiation of intestinal CD3−NKp46+ cell subsets from Id2-dependent precursors. J. Exp. Med. 207, 273–280 (2010).
Yokota, Y. et al. Development of peripheral lymphoid organs and natural killer cells depends on the helix–loop–helix inhibitor Id2. Nature 397, 702–706 (1999).
Zook, E.C. et al. Transcription factor ID2 prevents E proteins from enforcing a naive T lymphocyte gene program during NK cell development. Sci. Immunol. 3, eaao2139 (2018).
Seillet, C. et al. Deciphering the innate lymphoid cell transcriptional program. Cell Rep. 17, 436–447 (2016).
Ng, S. Y., Yoshida, T., Zhang, J. & Georgopoulos, K. Genome-wide lineage-specific transcriptional networks underscore Ikaros-dependent lymphoid priming in hematopoietic stem cells. Immunity 30, 493–507 (2009).
Miyazaki, M. et al. The E–Id protein axis specifies adaptive lymphoid cell identity and suppresses thymic innate lymphoid cell development. Immunity 46, 818–834.e814 (2017).
Joshi, I. et al. Loss of Ikaros DNA-binding function confers integrin-dependent survival on pre-B cells and progression to acute lymphoblastic leukemia. Nat. Immunol. 15, 294–304 (2014).
Inlay, M. A. et al. Ly6d marks the earliest stage of B-cell specification and identifies the branchpoint between B-cell and T-cell development. Genes Dev. 23, 2376–2381 (2009).
Georgopoulos, K. et al. The Ikaros gene is required for the development of all lymphoid lineages. Cell 79, 143–156 (1994).
de Boer, J. et al. Transgenic mice with hematopoietic and lymphoid specific expression of Cre. Eur. J. Immunol. 33, 314–325 (2003).
Kuhn, R., Schwenk, F., Aguet, M. & Rajewsky, K. Inducible gene targeting in mice. Science 269, 1427–1429 (1995).
Hu, Y. et al. Superenhancer reprogramming drives a B-cell–epithelial transition and high-risk leukemia. Genes Dev. 30, 1971–1990 (2016).
Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).
Heinz, S. et al. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol. Cell 38, 576–589 (2010).
Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).
Robinson, M. D., McCarthy, D. J. & Smyth, G. K. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26, 139–140 (2010).
Ramirez, F., Dundar, F., Diehl, S., Gruning, B. A. & Manke, T. deepTools: a flexible platform for exploring deep-sequencing data. Nucleic Acids Res. 42, W187–W191 (2014).
Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA 102, 15545–15550 (2005).
Mootha, V. K. et al. PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes. Nat. Genet. 34, 267–273 (2003).
Servant, N. et al. HiC-Pro: an optimized and flexible pipeline for Hi-C data processing. Genome Biol. 16, 259 (2015).
Hao, Y. et al. Integrated analysis of multimodal single-cell data. Cell 184, 3573–3587.e3529 (2021).
La Manno, G. et al. RNA velocity of single cells. Nature 560, 494–498 (2018).
Bergen, V., Lange, M., Peidli, S., Wolf, F. A. & Theis, F. J. Generalizing RNA velocity to transient cell states through dynamical modeling. Nat. Biotechnol. 38, 1408–1414 (2020).
Yoshida, T., Ng, S. Y., Zuniga-Pflucker, J. C. & Georgopoulos, K. Early hematopoietic lineage restrictions directed by Ikaros. Nat. Immunol. 7, 382–391 (2006).
Mohtashami, M., Zarin, P. & Zuniga-Pflucker, J. C. Induction of T cell development in vitro by delta-like (Dll)-expressing stromal cells. Methods Mol. Biol. 1323, 159–167 (2016).
Hu, Y. & Smyth, G. K. ELDA: extreme limiting dilution analysis for comparing depleted and enriched populations in stem cell and other assays. J. Immunol. Methods 347, 70–78 (2009).
Acknowledgements
We thank H. Petrie at the Scripps Research Institute for providing us sorted ex vivo T cell progenitors. We thank K. White, J. M. Park and F. Gounari for critical review of the manuscript and E. Wu and R. Czyzewski for mouse husbandry. Research was supported by the National Institutes of Health (grant nos. R01HL140622 and R01CA158006 to K.G., R21AR074748 to B.A.M. and R35GM128938 to F.A.). Gene targeting was performed at the Cutaneous Biology Research Center (CBRC) and at the targeting core at the University of Chicago. Cell sorting was performed at the Flow and Mass Cytometry Core/Massachusetts General Hospital and at CBRC. High-throughput RNA-seq was performed at the Bauer Center for Genomic research at Harvard University and at CBRC.
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M.K. designed and performed the experiments, and analyzed and interpreted the data. B.A.M. and K.G. supervised the study. D.S.F. and F.A. performed RNA velocity and Hi-C analysis. M.K., B.A.M. and K.G. wrote the manuscript.
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Extended data
Extended Data Fig. 1 Generation of mice with deletion of the DNS region and effects of the DNS and Notch1 deletions on gene expression in DN3 thymocytes.
(a) Strategy to generate a conditional deletion of the DNS region. A 4.6 kb region containing the DNS promoter and a region enriched for transcription factor binding sites (TF BS) were flanked by loxP sites (black arrowhead). The Neo marker was flanked by Frt sites (white arrowhead). Flp recombinase excises the Neo gene from the targeting construct and generates the DNS floxed allele. CD2-Cre or Mx-Cre recombinase were used to induce deletion of the DNS region in T cell progenitors or in all hematopoietic cells and progenitors, respectively. DNS1 exons (red square) and DNS2 and DNS3 exons (blue square) and TF BS (yellow square) are shown. (b, c) Genome browser tracks of normalized RNAseq reads at Notch1 ((-) strand), DNS1 ((-) strand), and DNS2 and DNS3 ((+) strand) genes in WT, ΔDNSCD2cre, and ΔN1cCD2cre DN3 thymocytes are shown. Complete loss of Notch1 exon1 (E1) was detected in ΔN1cCD2cre DN3 (b, c). Splicing events in ΔN1cCD2cre are drawn by angled lines (c). (d) Expression of DNS1-3 RNAs in DN3 is shown (mean+/– SEM). Data shown for WT DN3 is also used in Fig. 1g. (e) Number of RNA-seq reads that span splicing junctions are shown for two independent ΔN1cCD2cre DN3 data sets. (f) K-means clustering of genes significantly up-or down- regulated in ΔN1cCD2cre vs WT (log2FC > 0 or <0, adj.p < 0.05) in WT, ΔDNSCD2cre, and ΔN1cCD2cre DN3 cells is shown. A similar trend of up- and down-regulated genes was seen with ΔDNSCD2cre and ΔN1cCD2cre DN3 cells relative to WT DN3 cells although gene expression changes observed in ΔDNSCD2cre were smaller than those seen in ΔN1cCD2cre DN3. (g) GO Pathway analyses of up- or down-regulated genes in ΔN1cCD2cre vs WT. Data shown were generated from two (ΔDNSCD2cre DN3 and ΔN1cCD2cre DN3) and three (WT DN3) independent experimental groups with pooled samples from at least two biological replicates.
Extended Data Fig. 2 Generation of mice with deletion of the DNS enhancer and interaction of the DNS enhancer with the canonical Notch1 and DNS promoters.
(a) Strategy to generate the DNS enhancer mutant allele. A 600 bp region containing the conserved TF BS were deleted by CRISPR-Cas9-mediated gene editing. DNS1 (red square) and DNS2 and 3 (blue square) exons, and TF BS (yellow square) are shown by respectively colored squares. (b) Statistically significant (FDR < 0.01) long distance interactions at Notch1 locus identified by HiC at 10kb resolution in DN2 thymocytes are shown together with histone modifications and chromatin accessibility. HiC data shown in (b) was downloaded publicly available data (GSE90958).
Extended Data Fig. 3 Characterization of ΔDNSe mutant thymus.
(a) FACS profiles of total thymocytes with markers for, DN, DP, and SP stages of αβT and B cells are shown. (b) Absolute cell numbers for αβT cell subsets in the WT and ΔDNSe thymi at different ages are shown. Unpaired t-test (two-tailed) was used for statistical analysis. N.S., not significant. (c) FACS profiles of γδT cells are shown. Data shown in (a) were representative FACS profiles from one experiment with 28-day-old WT (N = 3) and ΔDNSe (N = 3) mice, in (b) were generated from 4 independent experiments with mice at different age groups (WT N = 13, ΔDNSe N = 12), in (c) were representative FACS profiles from 3 independent experiments with WT (N = 8) and ΔDNSe (N = 8) mice.
Extended Data Fig. 4 scRNAseq analysis with replicate 2 samples.
(a) Integrated analysis and UMAP visualization of WT ETPs (3341 cells) and ΔDNSe ETPs (2952 cells), is shown in 12 colored sub-clusters. Absolute cell number in each cluster is shown in parenthesis. (b) Heatmap of the top 20 enriched genes in each sub-cluster ordered by approximate developmental progression based on gene expression and connectivity in the UMAP display is shown. (c) ETP subcluster composition in WT and ΔDNSe ETPs are shown by bar graph. (d) Independent visualization of WT and ΔDNSe ETP subclusters and expression of Flt3 (a vETP marker), Spi1 (a marker for multipotentETP and innate cells), Bcl11b (a marker for proT), Id2 (a marker for ILC/NK), and Gata2 (a marker for Ery/Meg) in the UMAP defined clusters are shown. (e) Expression of genes that define ETP subsets and downstream stages of T cell differentiation as well as genes representative of ILC/NK, GN, Ery/Meg, DC, and B cell differentiation are shown. Color intensity is proportional to the average gene expression across cells in the indicated clusters. The size of circles is proportional to the percent of cells expressing the indicated genes.
Extended Data Fig. 5 Deducing lineage affiliation of cells in ETP sub-clusters (replicate 1).
(a) Previously established gene expression data sets from HSC, early lineage progenitors and thymic DC were used to define the cell type affiliation of ETP cluster-defining gene markers. The list of markers is summarized in Supplementary Table 1. (b) Expression of Hoxa9, Cd34, and Spi1 in the UMAP defined clusters are shown. (c) Expression of genes that define ETP subsets and downstream stages of T cell differentiation as well as genes representative of ILC/NK, GN, Ery/Meg, DC, and B cell differentiation are shown. Color intensity is proportional to the average gene expression across cells in the indicated clusters. The size of circles is proportional to the percent of cells expressing the indicated genes. Two replicates of HSC, MPP, CLP, ILC2p, NKp, and thymic DC were obtained from published datasets (GEO: GSE77695, GSE183056). ETP, DN2, DN3, proB, La.preB, Sm.preB, and thymic B data sets were generated in this study (as described in Fig. 1 and Fig. 2).
Extended Data Fig. 6 Analysis of RNA velocity (replicate 1).
(a) Velocity streams of scRNA analysis for WT and ΔDNSe ETPs are shown separately. Stream arrows represent relative transition probabilities based on un-spliced over spliced transcript ratio calculations. The vector calculation was performed with (top) or without (bottom) 1248 cell-cycle-associated genes that belonged to either GO term: GO:0022402 or Reactome Pathway ID: R-MMU-1640170. (b) Selected genes contributing to velocities of each cluster is shown. Genes were classified as 1) common to WT and ΔDNSe, 2) only in WT, 3) only in ΔDNSe. Genes added to or excluded from the list after exclusion of cell-cycle associated genes are also shown.
Extended Data Fig. 7 Gene expression profiling for cultured WT and ΔDNSe DN3 cells.
(a) Hierarchical clustering of genes expressed in cultured DN3, ex vivo T cell progenitors and innate lymphoid progenitors is shown. Genes with > 50 reads in at least one data set were clustered. (b) Enrichment of ΔDNSe deregulated genes in the Notch Signaling (Hallmark Notch Signaling) and Myc (Hallmark Myc target V1) pathways are shown by GSEA. Genes ranked from most upregulated (left end) to most downregulated (right end) in ΔDNSe relative to WT DN3 cells are plotted on the X axis. Enrichment profiles of genes are plotted on Y axis and calculated enrichment score (ES) and FDR are shown. (c) The full expression panel for Trbv, Trbc, Trbd and Trbj genes in cultured DN3 cells as determined by RNAseq is shown (mean + /– SEM. * adj. p < 0.01 Expression data for Trbv genes is also shown in Fig. 6e. Reduction in expression of genes encoding Vβ region (Trbv) were detected in ΔDNSe relative to WT DN3 with the exception of Trbv12-2 and Trbv13-2. Expression of genes encoding Cβ, Dβ and Jβ regions (Trbc, Trbd, and Trbj) were similar or even higher in ΔDNSe DN3, suggesting that ΔDNSe DN3 have already undergone D-J rearrangement. (d) Heatmaps based on significance of functional pathway enrichment (-log10(pval)) are shown for down-regulated genes classified as a DN3 and ΔDNSe-dwn signatures as shown in Fig. 6c. (e) Expression of genes related to innate lymphoid lineages in cultured DN3 cells as determined by RNAseq is shown (mean + /– SEM). * adj. p < 0.01. Data for cultured DN3 cells were generated from three independent experimental groups for each genotype. Data for ex vivo ETP, DN2 and DN3 were generated in this study as in Fig. 1. Data for ILC2p and NKp were obtained from published datasets (GEO: GSE77695) as in Fig. 6 and Extended Data Fig. 5.
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Kashiwagi, M., Figueroa, D.S., Ay, F. et al. A double-negative thymocyte-specific enhancer augments Notch1 signaling to direct early T cell progenitor expansion, lineage restriction and β-selection. Nat Immunol 23, 1628–1643 (2022). https://doi.org/10.1038/s41590-022-01322-y
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DOI: https://doi.org/10.1038/s41590-022-01322-y
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