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Early precursor T cells establish and propagate T cell exhaustion in chronic infection

Nature Immunology volume 21, pages 1256–1266 (2020)Cite this article

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Abstract

CD8+ T cells responding to chronic infections or tumors acquire an ‘exhausted’ state associated with elevated expression of inhibitory receptors, including PD-1, and impaired cytokine production. Exhausted T cells are continuously replenished by T cells with precursor characteristics that self-renew and depend on the transcription factor TCF1; however, their developmental requirements are poorly understood. In the present study, we demonstrate that high antigen load promoted the differentiation of precursor T cells, which acquired hallmarks of exhaustion within days of infection, whereas early effector cells retained polyfunctional features. Early precursor T cells showed epigenetic imprinting characteristic of T cell receptor–dependent transcription factor binding and were restricted to the generation of cells displaying exhaustion characteristics. Transcription factors BACH2 and BATF were key regulators with opposing functions in the generation of early precursor T cells. Overall, we demonstrate that exhaustion manifests first in TCF1+ precursor T cells and is propagated subsequently to the pool of antigen-specific T cells.

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Fig. 1: High amounts of antigen promote the differentiation of early TP cells.
Fig. 2: Early TP cells express high levels of TOX and are impaired in IFN-γ production.
Fig. 3: ID3 demarcates precursor T cells in acute and chronic infections.
Fig. 4: Early TP cells in chronic infection acquire an exhausted phenotype.
Fig. 5: Early TP cells in chronic infection acquire the epigenetic profile of exhausted T cells.
Fig. 6: Early TP cell differentiation in chronic infection is regulated by BACH2 and BATF.
Fig. 7: Early exhausted TP cells retain proliferative potential but are restricted to the generation of exhausted T cells.

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Data availability

All data are available in the main text or the Extended Data materials. All materials used in the present study are available upon request from the lead authors. Sequencing data generated for this study have been deposited in the Gene Expression Omnibus database with accession code GSE142687.

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Acknowledgements

We thank T. Mason for technical support and T. Gebhardt, S. Nutt and members of the Kallies lab for discussions. This work was funded by the National Health and Medical Research Council (project grant no. 1085151 and Senior Research Fellowship no. 1139607 to A.K.), the Swiss National Science Foundation (fellowship nos. P300PA_177907 to D.T.U., P400PM_180807 to S.S.G. and P300PB_177934 to P.M.G.) and the Novartis Foundation for Medical–Biological Research (fellowship to S.S.G.). D.T.U. is a Special Fellow of the Leukemia and Lymphoma Society (fellowship no. 3387-19). W.S .is supported by a WEHI Centenary Fellowship funded by a donation from CSL Ltd. We acknowledge the Melbourne Cytometry Platform for provision of flow cytometry services.

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Author notes

  1. These authors contributed equally: Daniel T. Utzschneider, Sarah S. Gabriel.

Authors and Affiliations

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

    Daniel T. Utzschneider, Sarah S. Gabriel, Renee Gloury, Patrick M. Gubser, Ajithkumar Vasanthakumar & Axel Kallies

  2. Olivia Newton-John Cancer Research Institute, Heidelberg, Australia

    David Chisanga & Wei Shi

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

    David Chisanga, Ajithkumar Vasanthakumar, Wei Shi & Axel Kallies

  4. Department of Medical Biology, University of Melbourne, Melbourne, Australia

    David Chisanga

  5. School of Cancer Medicine, La Trobe University, Heidelberg, Victoria, Australia

    David Chisanga & Wei Shi

  6. School of Computing and Information Systems, University of Melbourne, Melbourne, Australia

    Wei Shi

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Contributions

D.T.U., S.S.G. and A.K. conceived the study, designed experiments, interpreted the results and wrote the manuscript. D.T.U. and S.S.G. performed the experiments with support from R.G. and P.M.G. A.V. generated the BACH2-overexpressing vector. D.C. and W.S. analyzed the sequencing data.

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Correspondence to Daniel T. Utzschneider or Axel Kallies.

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Extended data

Extended Data Fig. 1 High levels of antigen promote precursor T cell generation and PD-1 and TOX expression.

a, Experimental scheme referring to b–d and Fig. 1a, b. Congenically marked P14 T cells were labelled with CellTrace Violet (CTV) and transferred into naïve mice, which were infected with either acute LCMV Armstrong (Arm) or chronic LCMV Docile (Doc). Spleens were analysed 48, 62 and 69 hours post infection (p.i.). For each experiment, all 12 biological replicates (four mice at 3 timepoints) were concatenated into one file in FlowJo. b, Representative FACS plots showing CTV-dilutions of P14 T cells from concatenated samples. c, d, Representative FACS plots showing PD-1 (c) and TOX expression (d) versus CTV-dilution (top). Samples from Docile infected mice are in black and from Armstrong in green. Mean fluorescent intensity (MFI) combined from two experiments (bottom). Data are representative of three individual experiments. Error bars indicate SEM. e–g, P14 T cells were transferred into congenically marked naïve recipient mice, which were infected with either LCMV Armstrong or Docile. e, Gating strategy for identification of P14 T cells. f, g, Representative histograms depicting PD-1 (f) and TOX (g) among TCF1+ precursor (TP, solid line, left) and TIM-3+ effector (TE, dashed line, right) P14 T cells on day 5 p.i. with high dose Docile (black) or Armstrong (green); grey represents host CD8+ T cells. Data are representative of at least three independent experiments with five mice per group.

Extended Data Fig. 2 Memory T cells in acutely-resolved infection express low levels of TOX and high amounts of IFN-γ.

P14 T cells were transferred into congenically marked naïve recipient mice, which were infected with either LCMV Armstrong or Docile and analysed on day 21 p.i. a, TOX expression of TCF1+ precursor (TP, black solid dots) and TIM-3+ effector (TE, black open dots) P14 T cells from Docile compared to memory P14 T cells from Armstrong (green solid dots) infection. b, Frequencies of IFN-γ producing TP and TE P14 T cells from Docile compared to memory P14 T cells from Armstrong after ex vivo re-stimulation with LCMV-derived gp33 peptide. TP and TE cell segregation based on Ly108 and TIM-3 expression. Symbols represent individual mice; lines connect P14 T cells within the same host. Data are representative of at least three independent experiments with at least four mice per group. Statistical analysis was performed with unpaired Student’s t test (two-tailed). ****p < 0.0001; ***p < 0.001.

Extended Data Fig. 3 Phenotypic characterization of ID3+ and ID3- T cells in chronic and acute infection.

Congenically marked Id3GFP P14 T cells were transferred into naïve mice, which were then infected with either LCMV Armstrong or Docile. a, TCF1 versus TIM-3 expression of P14 T cells from spleens on day 5 post LCMV Docile (top, black) or LCMV Armstrong (bottom, green) infection. b, ID3 versus TIM-3 expression of P14 T cells from spleens on day 5 post Docile or Armstrong infection. c, TCF1 versus TIM-3 expression of ID3+ TP and TIM-3+ TE cells from b. d, Expression of Granzyme B (GzmB), 2B4 and CD39 among ID3+ TP and TIM-3+ TE cells on day 5 post Docile or Armstrong infection. Histograms of ID3+TIM-3- TP cells in solid lines, ID3-TIM-3+ TE cells in dashed lines and host CD8+ T cells in grey are shown. Data are representative of at least two individual experiments with at least four mice each.

Extended Data Fig. 4 Transcriptional differences between ID3+ and ID3- P14 T cells in acute and chronic infection.

Congenically marked Id3GFP P14 T cells were transferred into naïve mice, which were then infected with either LCMV Armstrong or Docile. ID3+ and ID3- P14 T cells from Armstrong infected mice were FACS purified for RNAseq analysis as described in Fig. 4. a, b, Volcano plots show differentially expressed (DE) genes between ID3+ and ID3- P14 T cells obtained from Armstrong infected mice on day 5 p.i. (a) and day 21 p.i. (b). c, Number of DE genes in all comparisons including comparisons shown in Fig. 4a, b. Number of genes upregulated in ID3+ compared to ID3- P14 T cells are indicated in red and genes downregulated in ID3+ P14 T cells are indicated in blue.

Extended Data Fig. 5 Generation of a core exhaustion T cell gene signature.

Congenically marked Id3GFP P14 T cells were transferred into naïve mice, which were infected with either LCMV Armstrong or Docile. ID3+ and ID3- P14 T cells were FACS purified for RNAseq analysis as described in Fig. 4. a, b, Volcano plots show genes differentially expressed (DE) between ID3+ (a) and ID3- (b) P14 T cells from day 21 Docile and Armstrong infections. c, Venn diagram shows numbers of DE genes common (core exhaustion signature) or unique to each comparison. Numbers in red highlight genes upregulated in Docile samples and numbers in blue genes downregulated in Docile. d, Heatmap established by unsupervised clustering of all generated samples based on the ‘dysfunctional vs polyfunctional’ signature defined by Alfei et al. 2019 (ref. 11). Black (Docile) and green (Armstrong) boxes on top highlight origin of cells. Dotted squares highlight main two clusters; green square = polyfunctional phenotype, black square = exhausted phenotype. e, Hierarchical tree of unsupervised clustered heatmap. f, Gene set enrichment analysis of Docile derived day 5 TP versus TE cells using the ‘dysfunctional vs polyfunctional’ signature defined by Alfei et al. 2019 (ref. 11). Barcode plots based on ROAST tests including p values from the tests are shown; signature genes upregulated are shown in red and genes downregulated in blue.

Extended Data Fig. 6 The Pdcd1 gene locus displays early enhanced accessibility in T cells responding to LCMV Docile infection.

Congenically marked Id3GFP P14 T cells were transferred into naïve mice, which were then infected with either LCMV Armstrong or Docile. ID3+ and ID3- P14 T cells were FACS purified at days 5 and 21 p.i. and ATAC sequencing was performed. Chromatin accessibility of the Pdcd1 locus is shown. Red arrows highlight regions that are differentially accessible between T cells obtained from Armstrong (green tracks) compared to Docile infected mice (black tracks). ATAC seq analysis was performed with two experimental replicates at each time point. Open chromatin tracks are based on merged replicates.

Extended Data Fig. 7 BACH2 and BATF regulate early precursor T cell differentiation.

a, Congenically marked Id3GFP P14 T cells were transferred into naïve recipient mice, which were then infected with LCMV Docile. 5 days p.i., ID3+ TP and ID3- TE P14 T cells were purified and chromatin accessibility determined by ATAC sequencing. Chromatin accessibility of Bach2 locus of TP and TE cells. Grey box highlights regions that are differentially accessible comparing the two samples. b, c Bach2fl/flCd4Cre (Bach2-/-) and Cd4Cre (Control) mice were infected with Docile and analysed 5 days later. b, Absolute numbers of gp33-tetramer+CD8+ T cells. c, Plots show TCF1 and TIM-3 expression of gp33-tetramer+CD8+ T cells in Bach2-/- and control mice (left), graph shows absolute numbers of TCF1+ TP and TIM-3+ TE cells among gp33-tetramer+CD8+ T cells in spleens (right). d–g, Congenically marked BACH2-deficient (Bach2fl/flCd4Cre, labelled as Bach2-/-) and control P14 T cells (Cd4Cre, labelled as control) (b, c) or Batf-/- and Batf+/+ control P14 T cells (d, e) were co-transferred into naive mice, which were challenged with Armstrong and analysed 5 days later. b, d, TCF1 versus TIM-3 (left) and TCF1+ TP cell frequency (right) in spleens. c, e, Absolute numbers of TCF1+ TP and TIM-3+ TE cells. Numbers indicate fold increase in control compared to Bach2-/- (c) or Batf-/- cells (d). ATAC seq analysis was performed with two experimental replicates at each time point. Open chromatin tracks are based on merged replicates. Symbols in b–e represent individual mice; lines connect P14 T cells within the same host. Data are combined or representative of two independent experiments with at least three mice per group. Statistical analysis was performed with a paired Student’s t test (two-tailed). ****p < 0.0001; ***p < 0.001; **p < 0.01; ns, not significant. MFI, mean fluorescent intensity. Error bars indicate SEM.

Extended Data Fig. 8 Late precursor T cells retain higher levels of TOX and PD-1 after expansion in acute infection.

a, Experimental scheme. Congenically marked Id3GFP P14 T cells were transferred into naïve mice, which were infected with LCMV Docile. 5 or 26 days p.i., ID3+TIM-3- TP and ID3-TIM-3+ TE P14 T cells were FACS sorted and transferred into naïve mice, which were infected with Armstrong. Donor P14 T cells were analysed 7 days post infection. b, Fold expansion of donor T cell populations. c, d, MFI of TOX (c) and PD-1 (d) of donor P14 T cells. Symbols represent individual mice. Data are representative or combined of two experiments with at least 3 mice per group. Statistical analysis was unpaired Student’s t test (two-tailed). ****p < 0.0001; ***p < 0.001; **p < 0.01; ns, not significant.

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Utzschneider, D.T., Gabriel, S.S., Chisanga, D. et al. Early precursor T cells establish and propagate T cell exhaustion in chronic infection. Nat Immunol 21, 1256–1266 (2020). https://doi.org/10.1038/s41590-020-0760-z

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