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Lymph nodes fuel KLF2-dependent effector CD8+ T cell differentiation during chronic infection and checkpoint blockade

Nature Immunology volume 26, pages 1752–1765 (2025)Cite this article

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Abstract

Exhausted CD8+ T (TEX) cell responses are maintained by precursors of exhausted T (TPEX) cells that possess high self-renewal and developmental potential. TPEX cells also drive the proliferative burst of effector T cells upon therapeutic immune checkpoint blockade (ICB). However, the spatial context and signals that regulate their differentiation and function are not well defined. Here we identify developmental and functional compartmentalization of TPEX and TEX cells across secondary lymphoid organs during chronic infection. We show that stem-like CD62L+ TPEX and effector-like CX3CR1+ TEX cells constitute a distinct developmental lineage that is promoted by the lymph node (LN) microenvironment and dependent on the transcription factor KLF2. LNs act as a niche in which migratory dendritic cells provide antigen and costimulatory signals to maintain the proliferative fitness of CD62L+ TPEX cells and generation of CX3CR1+ TEX cells. Moreover, LNs exclusively drive the proliferative burst and systemic dissemination of CX3CR1+ TEX cells during ICB. Thus, our findings identify a unique role for LNs in the maintenance of T cell differentiation and function during systemic chronic infection and ICB therapy.

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Fig. 1: LNs preserve the stemness, proliferative fitness and polyfunctionality of T cells.
Fig. 2: LNs support de novo generation of CX3CR1+ T cells in chronic infection.
Fig. 3: A precursor–progeny relationship defines the differentiation of CD62L+ TPEX to CX3CR1+ TEX cells.
Fig. 4: The transcription factor KLF2 instructs the lineage development of CD62L+ TPEX and CX3CR1+ TEX cells in LNs.
Fig. 5: CCR7 and S1PR1 are required for optimal development of CD62L+ TPEX and CX3CR1+ TEX cells.
Fig. 6: Migratory DCs provide a functional niche in LNs to promote T cell fitness.
Fig. 7: LNs drive the generation of TEFF cells in response to ICB.

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Data availability

The scRNA-seq data have been deposited in the Gene Expression Omnibus under accession no. GSE268824. All other data are available in the article and Supplementary Information.

Code availability

All analyses can be assessed at https://gitlab.dzne.de/ag-beyer/klf2_lcmv.git. Correcting for ambient genes and GOEA was performed on the docker image alefrol94/scrnaseq.analysis:reticulate using the package scrnaseq.analysis v.0.01. Any additional packages installed were tracked with the renv package v.0.14.0. Trajectory analysis with Palantir and CellRank was performed on the docker image wollmilchsau/scanpy_sccoda:latest (from 4 November 2021). The conda environments used for the analysis have been saved as YAML files.

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Acknowledgements

We thank the Melbourne Cytometry Platform and Walter and Eliza Hall Institute of Medical Research (WEHI) Cytometry Facility for providing flow cytometry services and the Doherty Institute Biological Resource Facility for animal husbandry and management. We thank the WEHI Centre for Dynamic Imaging for providing image acquisition and analysis services and the Molecular Genomics Core facility of the Peter MacCallum Cancer Centre for providing sequencing services. We thank members of the Kallies laboratory for critical reading of the manuscript and for providing feedback. This work was supported by the National Health and Medical Research Council of Australia (Investigator grant no. APP1194779 to D.T.U., Ideas grant no. 2028921 to C.T. and L.R.), the Australian Research Council Discovery Early Career Research Award (no. DE240100827 to C.T.). L.R. is supported by a Deutsche Forschungsgemeinschaft (DFG) (German Research Foundation) Postdoctoral Fellowship. L.H., L.W., C.G.d.G., D.M. and S.K.W. are supported by a Melbourne Research Scholarship. L.W. is supported by a China Scholarship Council-University of Melbourne PhD scholarship. M.D.B. is supported by the Helmholtz Association and the DFG (SFB1454 project no. 432325352, IGK2168/2 project no. 272482170). M.D.B. is a member of the excellence cluster ImmunoSensation2 (EXC2151 project no. 390873048). Z.A. was supported by the DFG through IRTG2168 no. 272482170 and EXC2151 no. 390873048.

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Author notes

  1. These authors contributed equally: Carlson Tsui, Leonie Heyden.

Authors and Affiliations

  1. Department of Microbiology and Immunology, The Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, Victoria, Australia

    Carlson Tsui, Leonie Heyden, Lifen Wen, Catarina Gago da Graça, Nikita Potemkin, Aleksej Frolov, Daniel Rawlinson, Lei Qin, Darya Malko, Chun-Hsi Su, Sining Li, Kayla R. Wilson, Helena Horvatic, Sharanya K. Wijesinghe, Marcela L. Moreira, Lachlan Dryburgh, Dominik Schienstock, Lisa Rausch, Daniel T. Utzschneider, Scott N. Mueller, Sammy Bedoui, Jan Schröder & Axel Kallies

  2. Institute of Molecular Medicine & Experimental Immunology, University Hospital Bonn, Bonn, Germany

    Leonie Heyden, Helena Horvatic, Zeinab Abdullah & Axel Kallies

  3. Immunogenomics & Neurodegeneration, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany

    Aleksej Frolov, Darya Malko & Marc D. Beyer

  4. The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia

    Verena C. Wimmer & Marjan Hadian-Jazi

  5. Monash Biomedicine Discovery Institute, Department of Biochemistry and Molecular Biology, Monash University, Melbourne, Victoria, Australia

    Marjan Hadian-Jazi

  6. Institute of Pharmaceutical Sciences, ETH Zürich, Zürich, Switzerland

    Cornelia Halin

  7. Systems Medicine, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany

    Marc D. Beyer

  8. Platform for Single Cell Genomics and Epigenomics at the German Center for Neurodegenerative Diseases (DZNE) and University of Bonn and West German Genome Center, Bonn, Germany

    Marc D. Beyer

Authors
  1. Carlson Tsui
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  2. Leonie Heyden
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  21. Daniel T. Utzschneider
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Contributions

C.T. and A.K. conceived, designed and supervised the study, and wrote the manuscript. C.T. and L.H., supported by L.W., C.G.d.G., V.C.W., D.M., C.-H.S., H.H., S.L., K.R.W., S.K.W., M.L.M., D.S. and L.R., performed all the experimental work. N.P., A.F., L.Q., D.R., M.H.-J., L.D. and J.S. performed the computational analyses. D.T.U., C.H., S.N.M., M.D.B., S.B. and Z.A. provided biological and technical resources and contributed to student supervision.

Corresponding authors

Correspondence to Carlson Tsui or Axel Kallies.

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Competing interests

A.K. has received research support from Pfizer. The other authors declare no competing interests.

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Nature Immunology thanks Stephen Jameson and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: Nick Bernard in collaboration with the rest of the Nature Immunology editorial team. Peer reviewer reports are available.

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Extended data

Extended Data Fig. 1 Lymph nodes preserve stemness, proliferative and metabolic fitness, and polyfunctionality of CD8+ T cells.

(a–e) Naïve congenically marked (CD45.1+) P14 CD8+ T cells were adoptively transferred into naïve wildtype (CD45.2+) mice, which were subsequently infected with LCMV-Docile. On d25 post-infection (p.i.) CD8+ T cells from spleens and pooled inguinal, brachial, axillary, cervical and mandibular lymph nodes (LN) were analysed using flow cytometry. (a) Quantification showing IL-2 production by P14 TPEX cells (n = 7). (b) Flow cytometry plots and quantification showing IFN-γ and TNF production in CD62L+ and CD62L− TPEX cells from spleen and LN after incubation with gp33 peptide (n = 11). (c) Flow cytometry plots and quantification of Ki67+ cells among the P14 TEX cells (n = 21). (d) Quantification showing ex vivo puromycin uptake in splenic and LN TEX cells. (e) Flow cytometry plots and quantification showing IFN-γ and TNF production in P14 TEX cells from spleen and LN after incubation with gp33 peptide (n = 10). (f–k) Naïve wildtype mice were infected with LCMV-Docile. On d25 p.i. CD8+ T cells from spleen and pooled LN were analysed using flow cytometry. (f) Flow cytometry plots and quantification showing the expression of PD-1 and TOX in endogenous polyclonal antigen-responsive CD8+ T cells in spleen and LN in comparison to naïve CD8+ T cells (n = 10). (g) Flow cytometry plots and quantification of TPEX cells among endogenous PD-1+CD8+ T cells in spleen and LN (n = 10). (h) Flow cytometry plots and quantification of CD62L+ cells among endogenous TPEX cells in spleen and LN (n = 20). (i) Flow cytometry plots and quantification showing the frequencies of Ki67+ cells among endogenous TPEX and TEX cells (n = 12). (j) Quantification showing ex vivo puromycin uptake of spleen and LN-derived endogenous antigen-responsive CD8+ T cells (n = 8). (k) Flow cytometry plots and quantification showing IFN-γ and TNF production in endogenous PD-1+CD8+ T cells from spleen and LN after stimulation in the presence or absence of gp33 peptide (n = 26). Flow cytometry plots are representative. Dots in graphs (a–k) represent individual mice; bars represent median. Quantification and statistics derive from unpaired two-tailed t tests (a, c, e, g–i, k) and one-way ANOVA (b, d, f) and are based on all data points across at least two independent experiments.

Extended Data Fig. 2 Functional superiority of endogenous antigen-responsive CD8+ T cells residing in lymph nodes.

(a, b) P14 T cells expressing IRF4-tdTomato were analysed using flow cytometry on d25 p.i. with chronic LCMV. The expression of IRF4 in TPEX and TEX subsets in the spleen and LN was quantified. (a) Flow cytometry plots and (b) quantification showing the expression of IRF4 in exhausted T cell subsets (n = 8). (c–h) Naïve wildtype mice were infected with LCMV-Docile. On d26 p.i., CD8+ T cells from spleen and pooled inguinal, brachial, axillary, cervical and mandibular lymph nodes (LN) were analysed using flow cytometry. (c, d) Flow cytometry plots and quantification showing the frequencies of (c) CX3CR1+ (n = 21) and (d) CD101+ cells (n = 15) among endogenous TEX cells (gated as TCF1−). (e, f) Flow cytometry plots and quantification showing expression of (e) CXCR6 (n = 9) and (f) Ly108 (n = 9) among endogenous CX3CR1+ TEX cells in the spleen and LN. (g) Flow cytometry plots and corresponding quantification showing the frequencies of Ki67+ among Ly108intCX3CR1+ and Ly108loCX3CR1+ TEX cells in spleen and LN (n = 14). (h) Flow cytometry plots and corresponding quantification showing the frequencies of Ki67+CX3CR1+ cells among endogenous PD-1+CD8+ T cells in spleen and LN (n = 8). (i–n) Naïve congenically marked (CD45.1+) P14 CD8+ T cells were adoptively transferred into naïve wildtype (CD45.2+) mice, which were subsequently infected with LCMV-cl13. On d32 p.i., P14 T cells in the spleen and pooled LN were analysed using flow cytometry. (i, j) Flow cytometry plots and quantification showing the frequencies of (i) TPEX cells among P14 cells (n = 9) and (j) CD62L+ cells among TPEX cells (n = 9). (k) Flow cytometry plots and quantification showing the frequencies of CD101+ cells among P14 TEX cells (n = 12). (l) Flow cytometry plots and quantification showing the frequencies of Ki67+CX3CR1+ cells among P14 cells in spleen and LN (n = 10). (m, n) Flow cytometry plots and quantification showing the frequencies of Ly108intCX3CR1+ cells among (m) P14 cells (n = 23) and (n) endogenous antigen-responsive CD8+PD-1+ cells (n = 9). Flow cytometry plots are representative. Dots in graphs (b–n) represent individual mice; bars represent median. Quantification and statistics derive from unpaired two-tailed t tests (c–f, h–n) and one-way ANOVA (a, g) and based on all data points across at two (f, h, i–l, n) or three (b–e, g, m) independent experiments.

Extended Data Fig. 3 CX3CR1+ TEX cells develop in lymph nodes.

(a–d) Naïve congenically marked (CD45.1+) P14 CD8+ T cells were adoptively transferred into naïve wildtype (CD45.2+) mice, which were subsequently infected with LCMV-Docile. On d26 p.i., mice were subjected to daily FTY720 treatment for 4 days. On d30 p.i., P14 T cells from the spleen and lymph nodes (LN) were analysed using flow cytometry. (a, b) Quantification showing the (a) frequencies and (b) numbers of P14 TPEX and TEX cells in the presence and absence of FTY720 in the spleen and LN (n = 10). (c) Representative flow cytometry plots and corresponding quantification showing the frequencies of Ly108intCX3CR1+ cells among endogenous antigen-responsive PD-1+CD8+ T cells (n = 10). (d) Quantification showing the absolute numbers of endogenous TPEX and TEX cells in the presence and absence of FTY720 in the spleen and LN (n = 10). (e–i) Naïve congenically marked (CD45.1+) P14 CD8+ T cells were adoptively transferred into naïve wildtype (CD45.2+) mice, which were subsequently infected with LCMV-Docile. P14 cells in the spleen and LN were harvested on d30 p.i. and subjected to scRNA-seq. (e) Normalised gene expression of key identity genes of exhausted T cell populations projected onto the UMAPs. (f) Heatmap showing the expression of cluster signature genes for each cluster from across all cell populations as annotated in Fig. 3a. (g) Annotated UMAP plot of single P14 T cells from spleen and LN of LCMV-Docile infected mice showing expression of the stem-like TPEX cell transcriptional signature22. (h) Box plot showing transcriptional diversity scores (CytoTRACE)33 among splenic and LN-derived TPEX (Spleen: n = 2175; LN: n = 995) and TEX cells (Spleen: n = 2266; LN: n = 1346). (i) Annotated volcano plots showing differentially expressed (DE) genes between splenic and LN total Cx3cr1+ TEX cells (left) and between Cx3cr1+S1pr5+ TEX and Cx3cr1+ TEX cells independent of tissue of origin (right). Dots in graphs (b–d) represent individual mice; bars represent median or mean. Box plot in (h) defines range (maxima and minima), interquartile range and median of the dataset. Quantification and statistics derive from two-tailed t tests (h) and one-way ANOVA (a–d) and based on all data points across at least two independent experiments (a–d).

Extended Data Fig. 4 The development of CX3CR1+ TEX cells is defined by KLF2 expression.

(a) Diffusion maps showing all annotated cell clusters (as per Fig. 3a) and cluster distribution according to origin, spleen and LN. (b) UMAP representations (as per Fig. 3a) showing enrichment of transcriptional signatures for Trajectory 1 (Cx3cr1+ TEX cells, top 50 genes) and Trajectory 2 (Cd101+ TEX cells, top 50 genes), with reciprocal enrichments of these signatures in TPEX cells bordered. (c) Box plots showing enrichment scores of Trajectory 1 and Trajectory 2 signatures among Sell+ and Sell− TPEX cell clusters. (d) Diffusion maps (as per Fig. 3e) showing the expressions of selected Traj. 2 genes that were also expressed in some TPEX cells. (e–g) UMAP representation after correction using muVI single cell trajectory analysis using Palantir and CellRank of P14 cells scRNA-seq data showing (e) cell differentiation originating from Tcf7+ TPEX cells and (f) progressing into either Cx3cr1+ (Traj. 1; upper) or Cd101+ (Traj. 2; lower) TEX cells. (g) Box plot showing fate probabilities towards Traj. 1 among Sell+ and Sell− TPEX cell clusters. (h–o) Naïve congenically marked (CD45.1+) P14 CD8+ T cells were adoptively transferred into naïve wildtype (CD45.2+) mice, which were subsequently infected with LCMV-Docile or LCMV-cl13. On d28 p.i. CD8+ T cells from spleen and pooled inguinal, brachial, axillary, cervical and mandibular lymph nodes (LN) were analysed using flow cytometry. (h, i) Flow cytometry plots showing the expression of (h) KLF2 and CD69, and (i) CD69 and CD62L expression among KLF2+ and KLF2− TPEX cells in the spleen and LN. (j) Quantification showing the frequency of CD69-expressing TPEX cells stratified by KLF2 expression (n = 9). (k, l) Flow cytometry plots showing the expression of (k) KLF2 and CD69, and (l) CD69 and CD101 among KLF2+ and KLF2− TEX cells in the spleen and LN. (m) Quantification showing the frequencies of CD69-expressing TEX cells stratified by KLF2 expression (n = 9). (n, o) Flow cytometry plots and corresponding quantification showing the frequencies KLF2+ cells among (n) TPEX (n = 6) and (o) TEX cell subsets (n = 6) in the spleen and LN. Dots in graphs (j, m–o) represent individual mice; bars represent median. Flow cytometry plots are representative. Box plots in (c, g) define ranges (maxima and minima), interquartile ranges and medians of the datasets. Quantification and statistics derive from unpaired two-tailed t tests (c, g) and one-way ANOVA (j, m–o) and based on all analysed mice across at least two independent experiments.

Extended Data Fig. 5 KLF2 drives the differentiation of CD62L+ TPEX and CX3CR1+ TEX cells in chronic LCMV infection.

(a–h) Naïve congenically marked KLF2-deficient (Klf2Δ) and control P14 CD8+ T cells were adoptively co-transferred at a 1:1 ratio into naïve wildtype mice, which were subsequently infected with chronic LCMV-cl13 and analysed on d28 p.i. (a) Flow cytometry plots and quantification showing the expression of KLF2 protein in control and Klf2Δ P14 cells in spleen and LN (n = 6). (b) Quantification showing the absolute counts of TPEX and TEX cells in the spleen and LN on d28 p.i. (n = 13). (c) Flow cytometry plots and quantification showing the frequencies of control and Klf2Δ CD62L+ and CD62L− TPEX cells in the LN (n = 10). (d) Quantification showing the accumulation of control and Klf2Δ P14 cells in different tissues (n = 7). (e) Flow cytometry plots and quantification showing the lack of CD62L+ and CX3CR1+ cells among Klf2Δ P14 cells in different tissues (n = 6). (f) Flow cytometry plots and quantification showing the frequencies of control and Klf2Δ CX3CR1+ and CD101+ TEX cells in LN (n = 10). (g) Flow cytometry plots and quantification showing the expression of CD69 among control and Klf2Δ P14 cells in the spleen (n = 10). (h) Quantification of PD-1 and TOX expression in control and KLF2-deficient P14 cells in the spleen (n = 8). (i–n) Naïve congenically marked KLF2-deficient (Klf2Δ) and control P14 CD8+ T cells were adoptively co-transferred at a 1:1 ratio into naïve wildtype mice, which were subsequently infected with chronic LCMV-Docile and analysed on d24 p.i. (i) Schematic of experimental setup. (j) Flow cytometry plots and quantification showing the expression of KLF2 protein in control and Klf2Δ P14 cells in spleen and LN (n = 9). (k) Quantification showing the relative accumulation of control and Klf2Δ TPEX and TEX cells in the spleen and LN on d24 p.i. (n = 10). (l) Quantification showing the frequencies of control and Klf2Δ CD62L+ and CD62L− TPEX cells in the spleen and LN (n = 10). (m) Quantification showing the frequencies of control and Klf2Δ CX3CR1+ TEX cells in the spleen and LN (n = 10). (n) Quantification showing the expression of CD69 among control and Klf2Δ P14 cells in the spleen and LN (n = 10). Flow cytometry plots are representative. Dots in graphs (b–f, j–n) represent individual mice; bars represent median. Quantification and statistics derive from two-tailed t tests (g, k) and one-way ANOVA (a–f, h, j, l–n) and are based on all data points across at least two independent experiments.

Extended Data Fig. 6 The KLF2-instructed differentiation program involves molecules associated with lymph node trafficking, including CCR7 and S1PR1, which contribute to CX3CR1+ TEX cell differentiation.

(a) Enrichment of a transcriptional signature for stem-like Sell+ TPEX cells (ref. 22) in control versus Klf2Δ TPEX cells. (b) Annotated UMAP plot showing single P14 T cells in spleen and LN. (c, d) Enrichment of transcriptional signatures projected onto a UMAP plot among genes (c) upregulated and (d) down-regulated comparing control and Klf2Δ TPEX cells, showing enrichment in Cx3cr1+ TEX cells and Cd101+ TEX cells, respectively. (e) Enrichment of transcriptional signatures among single P14 T cells derived from spleen and LN based on upregulated and down-regulated genes between control and Klf2Δ TPEX cells, showing reciprocal enrichment in splenic and LN P14 cells, respectively (Spleen TPEX: n = 2175; LN TPEX: n = 995; Spleen TEX: n = 2266; LN TEX: n = 1346). (f–h) Naïve congenically marked control and CCR7-deficient (Ccr7Δ) P14 CD8+ T cells were generated using CRISPR-Cas9-mediated editing. Control and Ccr7Δ P14 cells were cultured in the presence of IL7 for 2 days in vitro and surface expression of CCR7 were analysed using flow cytometry. (f) Schematic of in vitro experimental setup. (g) Flow cytometry plot and quantification of CCR7 expression in control and Ccr7Δ P14 cells (n = 10). (h) Quantification showing the absolute numbers of control and Ccr7Δ TEX cell subsets in the spleen and LN on d26 p.i. (n = 10). (i–l) Naïve congenically marked control and S1pr1Δ P14 CD8+ T cells co-transferred at a 1:1 ratio into naïve wildtype mice, which were subsequently infected with chronic LCMV-cl13 and analysed on d7 and d26 p.i. (i) Flow cytometry plots and quantification showing the expression of CD69 among control and S1pr1Δ P14 cells in the blood at the specified time points (n = 9). (j) Flow cytometry plots and quantification showing the expression of CD69 among control and S1pr1Δ P14 cells in the spleen and LN on d26 p.i. (n = 9). (k) Quantification showing the relative accumulation of control and S1pr1Δ TPEX and TEX cells in the spleen and LN on d7 (n = 8) and d26 p.i. (n = 13). (l) Flow cytometry plots and corresponding quantification showing the frequencies of Ki67+CX3CR1+ cells among control and S1pr1Δ P14 cells in spleen and LN (n = 9). Results in (g) represent four independent experiments. Flow cytometry plots are representative. Dots in graphs (h–l) represent individual mice; bars represent median. Box plots in (d, e) define ranges (maxima and minima), interquartile ranges and medians of the datasets. Quantification and statistics derive from two-tailed t tests (e, g) and one-way ANOVA (d, h–l) and based on all data points across at least two independent experiments (h–l).

Extended Data Fig. 7 LCMV induces influx of migratory cDC1 that express high levels immunostimulatory molecules.

(a–c) Naïve wildtype mice were infected with chronic LCMV-Docile. The spleens and pooled inguinal, brachial, axillary, cervical and mandibular lymph nodes (LN) were harvested on d30 p.i. and enriched for the CD11c+MHCII+ cells by flow cytometric sorting. The samples were then subjected to scRNA-seq. (a) Normalised expression of myeloid/DC marker genes projected onto the UMAPs. (b) Bubble plot comparing the transcript expression of genes related to DC activation among the main DC subsets obtained from the spleen and LN. (c) Annotated bubble plot showing predicted cell-cell interaction classes between different myeloid/DC subsets (senders) and TPEX cells (receivers). (d–h) Naïve wildtype mice were infected with chronic LCMV-Docile. The spleens and pooled LN were harvested on d25 p.i., and DC subsets were analysed using flow cytometry. (d) Schematic of the experimental setup. (e) Representative flow cytometry plots and quantification showing the frequencies of CCR7+ cells among CD11c+MHCII+ cells in the spleen and LN on d25 p.i. (n = 13). (f, g) Representative flow cytometry plots and quantification showing the frequencies of migratory DC defined by (f) CD8αneg (Uninfected: n = 10; LCMV: n = 21) and (g) MHCIIhi (Uninfected: n = 10; LCMV: n = 11) among all LN-derived cDC1 (XCR1+) in infected and uninfected mice. (h) Representative flow cytometry plots and (i) quantification showing the expression of MHCII, CD40, CD86, CD80 and IL-12 among splenic and LN cDC1 subsets on d25 p.i. (n = 6). Dots in graphs (e–g, i) represent individual mice; bars represent median. Quantification and statistics derive from two-tailed t tests (e, f) and one-way ANOVA (g, l) and based on all data points across at least two independent experiments.

Extended Data Fig. 8 TPEX cells interact with cDC1 in the paracortical T cell zones of lymph nodes.

(a–f) Naïve P14 CD8+ T cells, which ubiquitously express tdTomato (ref. 71) were adoptively transferred into naïve Xcr1Venus reporter mice (ref. 72), which were subsequently infected with LCMV-Docile. Lymph nodes (LN) were harvested on d25 p.i., fixed and imaged using confocal microscopy. (a) Representative confocal micrograph and quantification showing the distribution of B220+, TCF1+, CD11c+ CD68+ and P14 cells. (b) Analysis and (c) quantification showing the spatial distribution of TPEX (tdTomato+TCF1+) and TEX (tdTomato+TCF1−) cells within different anatomical regions of a LN (Follicular areas: n = 10; Paracortical TCZ: n = 9; Medullary regions: n = 7). (d) Representative confocal micrograph and (e) quantification showing the distribution of XCR1+ dendritic cells within different regions of the LN (Follicular areas: n = 10; Paracortical TCZ: n = 9; Medullary regions: n = 7). (f) Representative confocal micrographs and quantification showing the expression of CD11c in XCR1+ dendritic cells found within different anatomical regions of the LN (TCZ: n = 40; non-TCZ: n = 59). (g–j) Mixed bone marrow chimeric mice containing Ccr7−/− and Xcr1DTR (ref. 72) haematopoietic cells were infected with LCMV-Docile before the administering of Diphtheria toxin (DTX) starting on d18 p.i. P14 cells in the spleen and LN were analysed using flow cytometry on d25 p.i. (g) Representative flow cytometry plots and (h) quantification showing the frequencies of XCR1+ cells in spleen and LN in untreated or DTX treated mice (n = 8). (i) Quantification showing absolute numbers of P14 TPEX and TEX cell subsets in the presence and absence of cDC1 depletion in the spleen and LN (n = 9). (j) Representative flow cytometry plots and corresponding quantification showing the frequencies of Ly108intCX3CR1+ cells among P14 cells in the presence and absence of cDC1 depletion in the spleen and LN (n = 9). Dots in graphs represent (b, e) individual manually defined regions of interest, (f) individual cells, or individual mice (h–j), and bars represent median, and bars represent median. Quantification and statistics derive from unpaired two-tailed t tests (f) and one-way ANOVA (c, e, h–j) and based on all data points across at least two independent experiments.

Extended Data Fig. 9 CD28 signalling promotes exhausted T cell fitness in lymph nodes.

(a–e) Naïve congenically marked (CD45.1+) P14 cells were adoptively transferred into wildtype (CD45.2+) mice, which were then infected with LCMV-Docile and subjected to B7 blockade using anti-CD80/86 antibodies treatment starting on d18 p.i. Endogenous antigen-responsive PD-1+ as well as P14 cells were analysed on d25 p.i. using flow cytometry. (a) Flow cytometry plots and quantification showing the frequencies of Ki67+ cells among endogenous TPEX cells in the spleen and lymph nodes (LN) on d25 p.i. (n = 15). (b) Flow cytometry plots and quantification showing IFN-γ and TNF production of from spleen and LN-derived P14 cells after incubation with gp33 peptide ex vivo (Untreated: n = 20; Anti-B7: n = 16). (c) Flow cytometry plots and quantification showing the frequencies of intermediate Ly108intCX3CR1+ cells among P14 T cells in the spleen and LN on d25 p.i. (Untreated: n = 20; Anti-B7: n = 12). (d) Flow cytometry plots and quantification showing the frequencies of Ki67+CX3CR1+ cells among endogenous antigen-responsive CD8+ T cells in the spleen and LN on d25 p.i. (n = 15). (e) Flow cytometry plots and quantification showing the frequencies of intermediate Ly108intCX3CR1+ cells among endogenous antigen-responsive CD8+ T cells in the spleen and LN on d25 p.i. (n = 18). (f) Flow cytometry plots and quantification showing the surface expression of CD28 among P14 TPEX and TEX cells in the spleen and LN on d25 p.i. (n = 8). Flow cytometry plots are representative. Dots in graphs (a–f) represent individual mice; bars represent median. Quantification and statistics derive from one-way ANOVA (a–f) and based on all data points across at least two (f) or three (a–e) independent experiments.

Extended Data Fig. 10 Immune checkpoint blockade induces TPEX and CX3CR1+ TEX cell proliferation and egress from lymph nodes.

(a) Naïve congenically marked (CD45.1+) P14 CD8+ T cells were adoptively transferred to naïve wildtype (CD45.2+) mice, which were subsequently infected with LCMV-Docile. A single dose of anti-PD-L1 was given on d26 p.i. with or without subsequent daily FTY720 treatment. CD8+ T cells were analysed using flow cytometry on d30 p.i. (a) Representative flow cytometry plots and quantification of Ki67+ cells among the P14 TPEX cells in the spleen and lymph nodes (LN) (Ctrl: n = 17; ICB/FTY720: n = 24). (b–e) Naïve wildtype mice were infected with LCMV-Docile. A single dose of anti-PD-L1 was given on d26 p.i. with or without subsequent daily FTY720 treatment. Endogenous CD8+ T cells in the blood, spleen and pooled LN were analysed using flow cytometry on d30 p.i. (b) Schematic of the experimental setup. (c) Quantification showing the numbers of endogenous CX3CR1+ and CX3CR1− TEX cells (Ctrl: n = 10; ICB: n = 14; ICB/FTY720: n = 18) in 100 µL of peripheral blood on d30 p.i. (d) Representative flow cytometry plots and (e) quantification showing the frequencies of endogenous CX3CR1+ (left – Ctrl: n = 24; ICB: n = 14; ICB/FTY720: n = 24) and proliferating CX3CR1+ (right – Ctrl: n = 19; ICB: n = 9; ICB/FTY720: n = 18) cells in the spleen and LN on d30 p.i. (f, g) Naïve congenically marked (CD45.1+) P14 CD8+ T cells were adoptively transferred to naïve wildtype (CD45.2+) mice, which were subsequently infected with LCMV-Docile. A single dose of anti-PD-L1 was given on d26 p.i. with or without subsequent daily FTY720 treatment. CD8+ T cells were analysed using flow cytometry on d30 p.i. (f) Representative flow cytometry plots and (g) quantification showing the numbers of P14 and endogenous TPEX cells in peripheral blood (Ctrl: n = 10; ICB: n = 14; ICB/FTY720: n = 16). Dots in graphs (a, c, e, g) represent individual mice; bars represent median. Quantification and statistics derive from multiple t tests (b) and one-way ANOVA (c, e, g) and based on all data points across at least two (c, g) or three (a, e) independent experiments.

Supplementary information

Supplementary Information

Supplementary Figs. 1 and 2 and Tables 1–7.

Reporting Summary

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Supplementary Table 1

T cell markers.

Supplementary Table 2

Trajectory 1 versus trajectory 2 markers.

Supplementary Table 3

KLF2 (KO versus WT) T cell markers.

Supplementary Table 4

KLF2 TPEX (KO versus WT) DE genes.

Supplementary Table 5

Overlapping genes: ChIP versus TPEX DE genes.

Supplementary Table 6

DC/myeloid markers.

Supplementary Table 7

Intercellular communication.

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Tsui, C., Heyden, L., Wen, L. et al. Lymph nodes fuel KLF2-dependent effector CD8+ T cell differentiation during chronic infection and checkpoint blockade. Nat Immunol 26, 1752–1765 (2025). https://doi.org/10.1038/s41590-025-02276-7

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