Abstract
Antigen-experienced CD8+ T cells form effector and central memory T cells (TEM and TCM cells, respectively); however, the mechanism(s) controlling their lineage plasticity remains incompletely understood. Here we show that the transcription cofactor Tle3 critically regulates TEM and TCM cell fates and lineage stability through dynamic redistribution in antigen-responding CD8+ T cell genome. Genetic ablation of Tle3 promoted CD8+ TCM cell formation at the expense of CD8+ TEM cells. Lineage tracing showed that Tle3-deficient CD8+ TEM cells underwent accelerated conversion into CD8+ TCM cells while retaining robust recall capacity. Tle3 acted as a coactivator for Tbet to increase chromatin opening at CD8+ TEM cell-characteristic sites and to activate CD8+ TEM cell signature gene transcription, while engaging Runx3 and Tcf1 to limit CD8+ TCM cell-characteristic molecular features. Thus, Tle3 integrated functions of multiple transcription factors to guard lineage fidelity of CD8+ TEM cells, and manipulation of Tle3 activity could favor CD8+ TCM cell production.
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Data availability
The Tle3 CUT&RUN, bulk RNA-seq, single-cell RNA-seq and ATAC-seq data in CD8+ T cells are deposited at the GEO under accession number GSE213041. Source data are provided with this paper.
Change history
12 February 2024
A Correction to this paper has been published: https://doi.org/10.1038/s41590-024-01780-6
References
Akondy, R. S. et al. Origin and differentiation of human memory CD8 T cells after vaccination. Nature 552, 362–367 (2017).
Jameson, S. C. & Masopust, D. Understanding subset diversity in T cell memory. Immunity 48, 214–226 (2018).
Martin, M. D. & Badovinac, V. P. Defining memory CD8 T cell. Front Immunol. 9, 2692 (2018).
Sallusto, F., Lenig, D., Forster, R., Lipp, M. & Lanzavecchia, A. Two subsets of memory T lymphocytes with distinct homing potentials and effector functions. Nature 401, 708–712 (1999).
Wherry, E. J. et al. Lineage relationship and protective immunity of memory CD8 T cell subsets. Nat. Immunol. 4, 225–234 (2003).
Kaech, S. M. et al. Selective expression of the interleukin 7 receptor identifies effector CD8 T cells that give rise to long-lived memory cells. Nat. Immunol. 4, 1191–1198 (2003).
Joshi, N. S. et al. Inflammation directs memory precursor and short-lived effector CD8+ T cell fates via the graded expression of T-bet transcription factor. Immunity 27, 281–295 (2007).
Lin, W. W. et al. CD8+ T lymphocyte self-renewal during effector cell determination. Cell Rep. 17, 1773–1782 (2016).
Pais Ferreira, D. et al. Central memory CD8+ T cells derive from stem-like Tcf7hi effector cells in the absence of cytotoxic differentiation. Immunity 53, 985–1000 (2020).
Herndler-Brandstetter D. et al. KLRG1+ effector CD8+ T cells lose KLRG1, differentiate into all memory T cell lineages, and convey enhanced protective immunity. Immunity https://doi.org/10.1016/j.immuni.2018.03.015 (2018).
Chung, H. K., McDonald, B. & Kaech, S. M. The architectural design of CD8+ T cell responses in acute and chronic infection: parallel structures with divergent fates. J. Exp. Med. 218, e20201730 (2021).
Chen, Y., Zander, R., Khatun, A., Schauder, D. M. & Cui, W. Transcriptional and epigenetic regulation of effector and memory CD8 T cell differentiation. Front Immunol. 9, 2826 (2018).
Kallies, A., Xin, A., Belz, G. T. & Nutt, S. L. Blimp-1 transcription factor is required for the differentiation of effector CD8+ T cells and memory responses. Immunity 31, 283–295 (2009).
Gautam, S. et al. The transcription factor c-Myb regulates CD8+ T cell stemness and antitumor immunity. Nat. Immunol. 20, 337–349 (2019).
Zhou, X. et al. Differentiation and persistence of memory CD8+ T cells depend on T cell factor 1. Immunity 33, 229–240 (2010).
Pipkin, M. E. Runx proteins and transcriptional mechanisms that govern memory CD8 T cell development. Immunol. Rev. 300, 100–124 (2021).
Shan, Q. et al. The transcription factor Runx3 guards cytotoxic CD8+ effector T cells against deviation towards follicular helper T cell lineage. Nat. Immunol. 18, 931–939 (2017).
Orian, A. et al. A Myc-Groucho complex integrates EGF and Notch signaling to regulate neural development. Proc. Natl Acad. Sci. USA 104, 15771–15776 (2007).
Ren, B., Chee, K. J., Kim, T. H. & Maniatis, T. PRDI-BF1/Blimp-1 repression is mediated by corepressors of the Groucho family of proteins. Genes Dev. 13, 125–137 (1999).
Zhao, X., Shan, Q. & Xue, H. H. TCF1 in T cell immunity: a broadened frontier. Nat. Rev. Immunol. 22, 147–157 (2022).
Seo, W. & Taniuchi, I. The roles of RUNX family proteins in development of immune cells. Mol. Cells 43, 107–113 (2020).
Turki-Judeh, W. & Courey, A. J. Groucho: a corepressor with instructive roles in development. Curr. Top. Dev. Biol. 98, 65–96 (2012).
Buscarlet, M. & Stifani, S. The ‘Marx’ of Groucho on development and disease. Trends Cell Biol. 17, 353–361 (2007).
Jennings, B. H. & Ish-Horowicz, D. The Groucho/TLE/Grg family of transcriptional co-repressors. Genome Biol. 9, 205 (2008).
Gasperowicz, M. & Otto, F. Mammalian Groucho homologs: redundancy or specificity? J. Cell. Biochem. 95, 670–687 (2005).
Xing, S. et al. Tle corepressors are differentially partitioned to instruct CD8+ T cell lineage choice and identity. J. Exp. Med. 215, 2211–2226 (2018).
Wheat, J. C. et al. The corepressor Tle4 is a novel regulator of murine hematopoiesis and bone development. PLoS ONE 9, e105557 (2014).
Ramasamy, S. et al. Tle1 tumor suppressor negatively regulates inflammation in vivo and modulates NF-κB inflammatory pathway. Proc. Natl Acad. Sci. USA 113, 1871–1876 (2016).
Rutishauser, R. L. et al. Transcriptional repressor Blimp-1 promotes CD8+ T cell terminal differentiation and represses the acquisition of central memory T cell properties. Immunity 31, 296–308 (2009).
Mahajan, V. S. et al. DOCK2 sets the threshold for entry into the virtual memory CD8+ T cell compartment by negatively regulating tonic TCR triggering. J. Immunol. 204, 49–57 (2020).
Cao, J. et al. The single-cell transcriptional landscape of mammalian organogenesis. Nature 566, 496–502 (2019).
Skene, P. J. & Henikoff, S. An efficient targeted nuclease strategy for high-resolution mapping of DNA binding sites. Elife 6, e21856 (2017).
Zhang, Y. et al. Model-based analysis of ChIP–seq (MACS). Genome Biol. 9, R137 (2008).
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).
McLean, C. Y. et al. GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 28, 495–501 (2010).
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).
Levanon, D. et al. Transcriptional repression by AML1 and LEF-1 is mediated by the TLE/Groucho corepressors. Proc. Natl Acad. Sci. USA 95, 11590–11595 (1998).
Chen, G. & Courey, A. J. Groucho/TLE family proteins and transcriptional repression. Gene 249, 1–16 (2000).
Liu, J. et al. CTCF mediates CD8+ effector differentiation through dynamic redistribution and genomic reorganization. J. Exp. Med. 220, e20221288 (2023).
Shan, Q. et al. Tcf1 and Lef1 provide constant supervision to mature CD8+ T cell identity and function by organizing genomic architecture. Nat. Commun. 12, 5863 (2021).
Shan, Q. et al. Tcf1-CTCF cooperativity shapes genomic architecture to promote CD8+ T cell homeostasis. Nat. Immunol. 23, 1222–1235 (2022).
Milner, J. J. et al. Runx3 programs CD8+ T cell residency in non-lymphoid tissues and tumours. Nature 552, 253–257 (2017).
Shan, Q. et al. Ectopic Tcf1 expression instills a stem-like program in exhausted CD8+ T cells to enhance viral and tumor immunity. Cell Mol. Immunol. 18, 1262–1277 (2021).
Wang, D. et al. The transcription factor Runx3 establishes chromatin accessibility of cis-regulatory landscapes that drive memory cytotoxic T lymphocyte formation. Immunity 48, 659–674 (2018).
Sharrocks, A. D. The ETS-domain transcription factor family. Nat. Rev. Mol. Cell Biol. 2, 827–837 (2001).
Anderson, M. K., Hernandez-Hoyos, G., Diamond, R. A. & Rothenberg, E. V. Precise developmental regulation of Ets family transcription factors during specification and commitment to the T cell lineage. Development 126, 3131–3148 (1999).
Villanueva, C. J. et al. TLE3 is a dual-function transcriptional coregulator of adipogenesis. Cell Metab. 13, 413–427 (2011).
Pearson, S. et al. Loss of TLE3 promotes the mitochondrial program in beige adipocytes and improves glucose metabolism. Genes Dev. 33, 747–762 (2019).
Jacob, J. & Baltimore, D. Modelling T-cell memory by genetic marking of memory T cells in vivo. Nature 399, 593–597 (1999).
Guo, K. et al. Disruption of peripheral leptin signaling in mice results in hyperleptinemia without associated metabolic abnormalities. Endocrinology 148, 3987–3997 (2007).
McCausland, M. M. & Crotty, S. Quantitative PCR technique for detecting lymphocytic choriomeningitis virus in vivo. J. Virol. Methods 147, 167–176 (2008).
Sena-Esteves, M., Tebbets, J. C., Steffens, S., Crombleholme, T. & Flake, A. W. Optimized large-scale production of high titer lentivirus vector pseudotypes. J. Virol. Methods 122, 131–139 (2004).
Welsh, R.M. & Seedhom, M.O. Lymphocytic choriomeningitis virus (LCMV): propagation, quantitation, and storage. Curr. Protoc. Microbiol. Chapter 15, unit 15A 11 (2008).
Zhao, X. et al. beta-catenin and gamma-catenin are dispensable for T lymphocytes and AML leukemic stem cells. Elife 9, e55360 (2020).
Zhao, D. M. et al. Constitutive activation of Wnt signaling favors generation of memory CD8 T cells. J. Immunol. 184, 1191–1199 (2010).
Shan, Q. et al. Tcf1 preprograms the mobilization of glycolysis in central memory CD8+T cells during recall responses. Nat. Immunol. 23, 386–398 (2022).
Macosko, E. Z. et al. Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell 161, 1202–1214 (2015).
Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).
Hao, Y. et al. Integrated analysis of multimodal single-cell data. Cell 184, 3573–3587 (2021).
Simon, M., Grandage, V. L., Linch, D. C. & Khwaja, A. Constitutive activation of the Wnt/beta-catenin signalling pathway in acute myeloid leukaemia. Oncogene 24, 2410–2420 (2005).
Meers, M. P., Bryson, T. D., Henikoff, J. G. & Henikoff, S. Improved CUT&RUN chromatin profiling tools. Elife 8, e46314 (2019).
Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).
Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).
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).
Yu, G., Wang, L. G. & He, Q. Y. ChIPseeker: an R/Bioconductor package for ChIP peak annotation, comparison and visualization. Bioinformatics 31, 2382–2383 (2015).
Acknowledgements
We thank the HMH-CDI Flow Cytometry Core facility (M. Poulus and W. Tsao) for cell sorting. We thank J. Wang (Roswell Park Comprehensive Cancer Center), Q. -S. Mi and I. Adrianto (Henry Ford Health) for their input in processing next-generation sequencing data. This study is supported in part by grants from the National Institutes of Health (AI121080, AI139874 and AI112579 to H.-H.X.) and the Veteran Affairs (BX005771 to H.-H.X.). Q.S. is supported by the National Natural Science Foundation of China (32370949), the Natural Science Foundation of Jiangsu Province (BK20231219), the CAMS Innovation Fund for Medical Sciences (2022-I2M-1-024, 2022-I2M-2-004, 2021-I2M-1-047), the Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences (2022-RC310-11) and the Suzhou Municipal Key Laboratory (SZS2023005).
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X.Z., W.H. and Q.S. performed the experiments and analyzed the data; S.R.P., S.Z. and S.S.H. analyzed the next-generation sequencing data, with supervision from C.Z. and W.P.; H.-H.X. conceived and supervised the project, and wrote the paper with Q.S. All authors edited the paper.
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Extended data
Extended Data Fig. 1 Ablating Tle3 shows modest impact on the functions of antigen-responding CD8+ T cells without affecting viral clearance.
a. Experimental design. Naive P14+CD8+ T cells were adoptive transferred into CD45-disparate recipients at 2 × 104 cells/recipient, followed by i.p. infection with LCMV-Arm and characterization of CD8+ T cells at the effector and memory stages. dpi, day post-infection. b. Gating strategy to identify CD45.2+ donor-derived P14+CD8+ T cells in CD45.1+ wild-type recipients. c. Detection of cytokine production in effector CD8+ T cells on 8 dpi. CD45.2+ wild-type or Tle3–/– naive CD8+ T cells were transferred into CD45.1+ wild-type recipients, which were infected with LCMV-Arm the next day, following experimental design in a. GP33-induced production of IFN-γ (top) and TNF-α (bottom) was detected in CD45.2+CD8+ T cells. Representative contour plots (left) are from 2 independent experiments, with values denoting percentages of the gated population. Cumulative data (right) of the percentage of IFN-γ+ population in P14+CD8+ T cells and the percentage of TNF-α+ populations in IFN-γ+ P14+CD8+ T cells are means ± s.d. d. Detection of granzyme B expression in effector CD8+ T cells by intracellular staining on 8 dpi. Representative histographs (left) are from 2 independent experiments, with the values denoting geometric mean fluorescence intensity (gMFI) of granzyme B. Cumulative data (left) are means ± s.d. e–g. Detection of LCMV in recipient sera. The serum samples were collected from recipients of WT or Tle3–/– P14+CD8+ T cells at the indicated time points, and LCMV was detected with either quantitative RT-PCR (e) or plaque assays (f, g). Note that in the plaque assay, sera were serially diluted for the measurement as exemplified for the 4 dpi samples (f), and plaque forming units (PFUs) at 1:10 dilution were plotted for all time points (g). n = 5 each for mice receiving WT and Tle3–/– cells in f; data in e and g are means ± s.d. from two independent experiments. h. Detection of TCM frequency at ≥30 dpi in the spleen (SP) and lymph nodes (LN) of CD45.1+ wild-type recipients where CD45.2+ Tle3–/– and CD45.1+ CD45.2+ WT P14 cells were mixed for co-transfer, followed by LCMV-Arm infection. Donor-derived TM cells were identified firstly by gating on CD45.2+ cells, in which CD45.1+ cells were from WT (black) while CD45.1–GFP+ cells were from Tle3–/– (blue). Bar graphs are cumulative data of frequencies of TCM cells as means ± s.d. from two independent experiments. Statistical significance in c, d, e and h was determined with two-sided Student’s t-test. ns, not statistically significant; *, p < 0.05; ***, p < 0.001.
Extended Data Fig. 2 Targeting Tle3 promotes expression of TCM cell signature genes at the single cell level.
a. Volcano plot showing differential gene expression between TCM and TEM1/2 clusters based on scRNA-seq analysis of WT memory CD8+ T cells. 96 TCM and 53 TEM signature genes were identified by the criteria of ≥1.5 expression changes and FDR < 0.05. b. UMAP plots of WT and Tle3–/– cells displaying TCM and TEM scores for single cells. The scores for each cell were calculated based on the expression of 96 TCM and 53 TEM signature genes defined in a, using Seurat’s ‘AddModuleScore’ function. c. Scatter plots showing TCM and TEM scores for cells in each of the seven clusters as defined in Fig. 2e, with WT and Tle3–/– cells coded in distinct colors.
Extended Data Fig. 3 Targeting Tle3 promotes TCM- but diminishes TEM-chracteristic molecular features.
a. Phenotypic analysis of WT and Tle3–/– memory CD8+ T cells at ≥30 dpi based on select cell surface markers. Based on scRNA-seq analysis, Klrg1 and Cx3cr1 transcripts were preferentially detected in WT TEM compared to WT TCM cells (Fig. 2b, c). While these features were retained in Tle3–/– memory CD8+ T cells, their transcript levels were lower in Tle3–/– TEM cells compared to their WT counterparts (Fig. 2h). These changes were validated on the protein level with flow cytometry analysis. b. Gating strategy for cell sorting of WT and Tle3–/– TCM and TEM cells from the immune mice at ≥30 dpi. The various changes in KLRG1 and CX3CR1 protein expression due to Tle3 deficiency (a) may not accurately reflect the composition changes in Tle3–/– memory CD8+ cell pool. To avoid potentially confounding effects caused by the differential dependence of selected cell surface markers on the expression of Tle3, the CD62L-based classical definition of TCM and TEM cells was used here for cell sorting. c. Key comparisons for analysis of transcriptomic and ChrAcc changes in this study. d. Volcano plots showing DEGs between WT and Tle3–/– TEM cells (left) and those between WT and Tle3–/– TCM cells (right) by the criteria of ≥1.5-fold expression changes, FDR < 0.05, and FPKM ≥ 0.5 in the higher expression condition. Values in the plot denote DEG numbers in each pairwise comparison.
Extended Data Fig. 4 Differential Tle3 binding is associated with immune regulation during CD8+ T cell responses.
a. Volcano plots showing differential ChrAcc sites between WT and Tle3–/– TEM cells (left) and those between WT and Tle3–/– TCM cells (right) by a more stringent criteria of ≥3-fold signal strength changes and FDR < 0.05. Values in the plot denote numbers of differential ChrAcc sites in each pairwise comparison. b. Principal component analysis (PCA) of Tle3 CUT&RUN libraries from WT TN, TEFF, TEM and TCM cells. c. Volcano plots showing differential Tle3 binding sites in comparisons of TEFF, TEM and TCM with TN cells, where stringent criteria (≥3-fold difference in binding strength, adjusted p value < 0.05 using DESeq2) were used to define dynamic Tle3 binding sites. Values in plots denote numbers of dynamic Tle3 binding sites in each comparison. d,f. Functional annotation of dynamic Tle3 binding sites in TleC1 (d) and TleC3 (f) (as defined in Fig. 4d), using GREAT analysis, with GO terms associated with immune regulation highlighted in orange. Values denote Hyper Observed Gene hits. e,g. Tle3 CUT&RUN sequencing tracks showing TleC1 (e) or TleC3 (g) Tle3 binding sites at select genes as displayed on IGV, with the dynamic Tle3 binding sites marked with open bars and subcluster information labeled. IgG CUT&RUN in TN cells was used as a negative control. h. Detection frequency of dynamic Tle3 sites within +/–100 kb of TSS of DEGs in the five expression clusters defined in Fig. 3c. Values denote numbers of DEGs that are associated with dynamic Tle3 sites (w/) and those that are not (w/o). i. Distribution of DEG-associated dynamic Tle3 binding sites in genomic regions. From panel h, the DEGs associated with dynamic Tle3 peaks are divided into three categories, based on Tle3 site locations in promoters, distal regulatory regions, or both; and the values denote DEG numbers in each category.
Extended Data Fig. 5 Tle3 recruitment and stabilized binding require Runx3 and Tbet.
a. Principal component analysis (PCA) of Tle3 CUT&RUN sequencing libraries from WT and TRKO early TEFF cells isolated on 4 dpi. b. Venn diagram showing the overlap of Tle3 binding sites identified in WT and TbetKO TEFF cells. Tle3 CUT&RUN was performed on WT (4 replicates) and TbetKO (in 3 replicates) TEFF cells isolated on 6 dpi. Note that a single Tle3 binding site called in one cell type could overlap with more than one sites in the other, and therefore, the sum of common and uniquely identified Tle3 binding sites in the Venn diagram is not necessarily equal to the total site numbers called in a specific cell type. c. Boxplot showing the ratio of Tle3 binding strength in TbetKO to WT TEFF cells for Tle3 binding sites uniquely detected in each cell type (n = 9,926 for WT only sites, and n = 731 for TbetKO only sites). The box center lines denote the median, box edge denotes interquartile range (IQR), and whiskers denote the most extreme data points that are no more than 1.5 × IQR from the edge. d. Cumulative frequency plot showing differential Tle3 binding strength in WT versus TbetKO TEFF cells at the 3,380 Tbet/Runx-dependent Tle3 binding sites (defined in Fig. 5f). Statistical significance of the observed difference was determined with two-sided paired MWU test. e. Sequencing tracks of Tle3 CUT&RUN in WT and TbetKO TEFF cells. Rectangles with solid lines denote differential Tle3 binding sites with TbetKO cells showing ≥1.25-fold decrease in binding strength with FDR < 0.05, while those with dotted lines denote Tle3 binding sites identified in WT but not TbetKO TEFF cells by the same peak calling criteria.
Extended Data Fig. 6 Tle3 restrains chromatin opening at TCM signature ChrAcc sites via direct and indirect means.
a. De novo motif analysis of ChrAcc clusters 1-5 that overlapped with ‘TEFF-attenuated’ Tle3 binding sites (within blue square in Fig. 4e), with p values determined with DESeq2. b. Venn diagram showing overlap of ‘TEFF-attenuated’ Tle3 binding sites with Tcf1 binding sites in TN and Runx3 binding sites in TEFF cells at Tle3-closed, TCM signature ChrAcc sites (from ChrAccC1-5 with red bars in Fig. 4c). c,d. Sequencing tracks of Tle3 binding (top), Tcf1 and Runx3 binding (bottom), and ChrAcc states (middle) at TCM-characteristic genes as displayed on IGV. Open bars denote colocalized ‘TEFF-attenuated’ Tle3 binding peaks and Tle3-closed ChrAcc sites, with Tle3 binding subcluster information marked on the top. Bars with dotted lines at the Ccr7 (c), Tcf7, Sell and Id3 (d) gene loci mark dynamic Tle3 binding sites where the ChrAcc changes between WT and Tle3–/– TEM cells did not reach the stringent ≥3-fold differences, while bars with grey dotted lines at the Id3 gene locus (d) mark differential ChrAcc sites between WT and Tle3–/– TEM cells, which are associated with Tle3 binding sites that did not show dynamic changes (<3-fold differences) during CD8+ T cell responses. Statistical data in the comparison of the marked ChrAcc sites between WT and Tle3–/– TEM cells are shown for Tcf7, Sell and Id3 (d) genes under the tracks. We posited that Tle3-mediated restraining of TCM cell molecular features might involve at least two non-exclusive mechanisms. The first required direct repression by Tle3-Runx3 complex, as in the downstream region of Ccr7 and intron region of Itgae (c), where Tle3 binding was weakened in TEM compared to TN cells, but was nonetheless necessary to restrain ChrAcc. The second mechanism was likely secondary to elevated Tcf1 expression in Tle3–/– TEM and TCM cells (Fig. 3f). Tcf1 is highly expressed in TN cells, but profoundly down-regulated in TEFF cells. The attenuation of Tle3 binding in TEFF cells can be partly ascribed to downregulation of its partner TF, Tcf1. The prevalent pre-occupancy by Tcf1 at the TCM signature ChrAcc sites in TN cells suggests that these sites were intrinsically accessible by Tcf1 and became more open when Tcf1 became more available in Tle3–/– TEM and TCM cells. This was observed at the TSS and upstream regions of Ccr7 (c), upstream regions of Tcf7 and Id3, and intron regions of Sell (d). e. Tle3-bound, Tle3-closed ChrAcc sites can contribute to positive gene regulation, as observed at the Il2ra gene locus. We posited that these Tle3-bound elements might have the potential to function as silencers, and the Tle3 binding likely maintained their inactive state, allowing their target genes to be expressed/induced in WT cells. Loss of Tle3 resulted in increased ChrAcc at these elements, unleashing the silencer activity and hence leading to target gene downregulation.
Extended Data Fig. 7 Induced deletion of Tle3 at the effector phase promotes TCM cell features without detectably affecting memory CD8+ T cell functions.
a. Experimental design for assessing the impact of induced Tle3 ablation, where CreER+Tle3+/+ and CreER+Tle3FL/FL P14+CD8+ TN cells were used as donor cells (5 × 104 cells/recipient). The recipients were treated with Tamoxifen on 6 and 7 dpi to achieve Tle3 ablation at the effector phase, and treated again on 21 dpi to sustain Tle3 deletion. b–c. Detection of TCM (b) and TEM (c) cell–characteristic proteins with flow cytometry. Two weeks after the last tamoxifen treatment as in a, donor-derived P14+ memory CD8+ T cells in the recipient spleens were analyzed for TCM and TEM cell–characteristic proteins. Half-stacked histograms are representative data from at least 2 independent experiments with values denoting gMFI. Cumulative data for each protein are means ± s.d., with individual data points shown. d. Detection of cytokine production in GP33-stimulated TCM and TEM cells. Representative contour plots (left) are from 2 independent experiments, with values denoting percentages of the gated population. Cumulative data (right) of the percentage of IFN-γ+ population in P14+CD8+ T cells and the percentage of TNF-α+ populations in IFN-γ+ P14+CD8+ T cells are means ± s.d. For all panels, statistical significance for multiple group comparisons was first determined with one-way ANOVA, and Tukey’s test was used as post-hoc correction for indicated pair-wise comparison. *, p < 0.05; **, p < 0.01; ***, p < 0.001; ns, not statistically significant.
Extended Data Fig. 8 Induced deletion of Tle3 promotes TCM cell formation without compromising its recall capacity.
a. Experimental design for investigating the impact of acute deletion of Tle3 in ‘established’ TEM cells. b. RNA-seq tracks at the Tle3 locus showing effective deletion of its floxed exons 3 and 4 in Tle3ΔCreER TEM cells in all three replicates after 48-hr ex vivo treatment with 4-OHT. c–h. Assessment recall response by Tle3-deficient TEM and TCM cells in B16 melanoma model. WT or Tle3ΔCreER TEM, WT or Tle3ΔCreER TCM cells were sort-purified following the study design in Extended Data Fig. 7a, where Tle3 was inducibly deleted at the effector phase. The same number of sort-purified CD45.2+P14+ TN, TCM and TEM cells (5×104 cells/mouse) were transferred into CD45.1+ wild-type B6.SJL mice. One day later, the recepients were subcutaneously inoculated with B16 melanoma cells expressing the LCMV GP33 epitope (B16-GP33) (2 × 105 cells/mouse). Data are from one of two independent experiments with similar results. c. Tracking tumor growth in surviving recipient mice. *, p < 0.05; **, p < 0.01 for comparison between WT and Tle3ΔCreER TCM or WT and Tle3ΔCreER TEM cells, as determined with two-tailed Student’s t-test. Data are means ± s.d., and statistically insignificant time points are unmarked for clarity. Note that all recipients of WT TN cells succumbed by 21 days after inoculation due to uncontrolled tumor growth, the recipients of WT TEM and WT TCM cells showed improved survival and impeded tumor growth, with WT TCM cells exhibiting stronger anti-tumor effect. d. Kaplan-Meier survival curves of recipient mice that received P14+ TN, WT or Tle3ΔCreER TCM and TEM cells. *, p < 0.05; ***, p < 0.001; ns, not statistically significant for indicated pair-wise comparison, as determined with log rank test. e. Tumor size in recipients of WT or Tle3ΔCreER TCM cells that survived till day 33 after tumor inoculation. f–h. Analyses of tumor-infiltrating CD8+ lymphocytes (TILs) derived from WT or Tle3ΔCreER TCM cells in surviving recipients on day 33 after tumor inoculation, including cell counts (f), cell surface detection of Tim3 and PD-1 (g) and intracellular detection of granzyme B (h). Data in e and f are means ± s.d., and p values were determined with two-sided Student’s t-test.
Supplementary information
Supplementary Tables 1–3
Supplementary Table 1. TCM and TEM signature genes based on scRNA-seq analysis of memory CD8+ T cells; Supplementary Table 2. TCM and TEM signature genes based on bulk RNA-seq analysis; Supplementary Table 3. Clusters of DEGs due to Tle3 deficiency.
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Zhao, X., Hu, W., Park, S.R. et al. The transcriptional cofactor Tle3 reciprocally controls effector and central memory CD8+ T cell fates. Nat Immunol 25, 294–306 (2024). https://doi.org/10.1038/s41590-023-01720-w
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DOI: https://doi.org/10.1038/s41590-023-01720-w
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