Abstract
How cells respond to myriad stimuli with finite signaling machinery is central to immunology. In naive T cells, the inherent effect of ligand strength on activation pathways and endpoints has remained controversial, confounded by environmental fluctuations and intercellular variability within populations. Here we studied how ligand potency affected the activation of CD8+ T cells in vitro, through the use of genome-wide RNA, multi-dimensional protein and functional measurements in single cells. Our data revealed that strong ligands drove more efficient and uniform activation than did weak ligands, but all activated cells were fully cytolytic. Notably, activation followed the same transcriptional pathways regardless of ligand potency. Thus, stimulation strength did not intrinsically dictate the T cell–activation route or phenotype; instead, it controlled how rapidly and simultaneously the cells initiated activation, allowing limited machinery to elicit wide-ranging responses.
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Acknowledgements
This work was funded by an MRC Skills Development Fellowship (MR/P014178/1 to A.C.R.); the Wellcome Trust (grants [103930] and [100140] to G.M.G.); Cancer Research UK (core funding (A17197) to J.C.M.); EMBL (core funding to J.C.M.); the University of Cambridge; and Hutchison Whampoa Limited. Single-cell collection and analysis were supported through MRC Clinical Research Infrastructure funds for the Cambridge Single Cell Facility (MR/M008975/1). W.W.Y.L. and B.G. were supported by Bloodwise (12029) and Cancer Research UK (C1163/A12765 and C1163/A21762). This research was supported by the CIMR Flow Cytometry Core Facility. We thank R. Schulte and C. Cossetti for their advice and support in cell sorting; the CRUK-CI Flow Cytometry core, particularly M. Strzelecki and R. Grenfell, and Genomics core for their resources and assistance; the Wellcome Trust Sanger Institute Mouse Genetics Project (Sanger MGP) and its funders for the wild-type C57BL/6 mouse line (funding information, https://www.sanger.ac.uk/science/collaboration/mouse-resource-portal); and C. Gawden-Bone, J. Warland, A. Denton and G. Frazer for critical reading of the manuscript.
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A.C.R., J.C.M. and G.M.G. designed the study and wrote the manuscript; A.C.R. carried out the experiments and analyses under the supervision of J.C.M. and G.M.G.; A.T.L.L. designed analytical pipelines and software and advised analyses; W.W.Y.L. and B.G. advised and supervised, respectively, cell sorting and library preparation for scRNA-seq, which were optimized by W.W.Y.L.; and all authors edited and approved the final manuscript.
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Supplementary Figure 1 Single-cell profiling and clustering in early CD8+ T cell activation.
a, OT-I CD8+ T cells were stimulated with high potency ovalbumin peptide (N4) at various concentrations for 4 hours before measuring CD69 and CD25 protein expression by flow cytometry. Results are representative of two independent experiments. b, We hypothesized that heterogeneity among stimulated cells might result from stochastic variation in gene expression in the unstimulated state driving certain cells to more quickly respond to stimulation. We therefore examined highly variable genes within unstimulated cells. Heatmap depicts the top 100 most biologically variable genes detected by scRNA-seq in unstimulated cells (n = 44 cells) clustered by Euclidean distance. Colored bars indicate the pseudotime designation of these cells from Fig. 1c and the experimental batch in which they were processed. No obvious structure was observed in the unstimulated population. c, Histogram of the cell distribution along diffusion pseudotime from Fig. 1d. d, Cells were clustered along diffusion pseudotime using Jenks’ natural breaks classification method. e, The hypergeometric test was used to test for enrichment of transcriptional regulators among transcripts specifically upregulated in the early activation cluster compared to both resting and late activation cells.
Supplementary Figure 2 Costimulation effects and control gene selection in early CD8+ T cell activation.
a, OT-I CD8+ T cells were stimulated as in Fig. 2 with pure peptide in the presence and absence of exogenous murine IL-2. After 6 hours, surface protein expression was examined by flow cytometry. Plots depict results from 3 separate mice; line depicts the mean. Stimulation in the presence of IL-2 primarily affected expression of the high affinity receptor CD25 in the first 6 hours, with minimal impact on other activation readouts. b, Cells were stained with a proliferation dye before stimulation as in a. After 2 days, proliferation was examined by flow cytometry, confirming previous reports that IL-2 is important for proliferation under low potency activation conditions. Results are representative of 3 separate mice. c, The Rpl39 control gene for RNA flow cytometry was identified in single-cell RNA-seq data as having low variance and minimal condition-dependence. Plots show expression in two independent scRNA-seq data sets and ANOVA p values without multiple testing correction; left, n = 46 cells for N4 6h, 47 for T4 6h, 46 for G4 6h, 46 for NP68 6h, 44 for unstimulated, 51 for N4 1h, and 64 for N4 3h; right, n = 45 cells for N4, 44 for T4, 48 for G4, and 47 for NP68. Box plots show the median, boxed interquartile range, and whiskers extending to the most extreme point up to 1.5 x the interquartile range. d, Control gene expression in an RNA flow cytometry experiment as depicted in Fig. 2. Histograms are representative of 3 independent experiments.
Supplementary Figure 3 Transcriptomic activation status correlation with CD69 protein expression and examination of early expression of specific genes.
a, OTI CD8+ T cells were stimulated with peptides of varying affinity for 6 hours before scRNA-seq. Violin plots depict the distribution of surface protein expression measurements in sequenced cells stimulated for 6 hours; n = 46 cells for N4, 47 for T4, 46 for G4, and 46 for NP68. Data is the second independent replicate of that in Fig. 3a. b, CD69 protein FACS measurements are plotted against transcriptional activation status as determined by diffusion pseudotime analysis in Fig. 3b for each of two scRNA-seq experiments. Surface protein measurements were made independently in each experiment; diffusion pseudotime analysis to determine transcriptional activation status was performed using the combined data set of both experiments. r denotes Pearson’s correlation coefficient; n = 184, left; n = 293, right. c-d, Normalized gene expression without regression on activation status for genes depicted in Fig. 2e,f is plotted by stimulation condition. e, Residual expression of Granzyme B (Gzmb) in scRNA-seq data after regression on batch and CD69 expression is plotted by stimulation condition (left). Normalized expression of Gzmb without regression on activation status is plotted by stimulation condition (right). Box plots (c-e) show the median, boxed interquartile range, and whiskers extending to the most extreme point up to 1.5 x the interquartile range. For (c, d, e (right)), n = 44 cells for unstimulated, 64 for N4 3h, 91 for N4 6h, 91 for T4 6h, 94 for G4 6h, 93 for NP68 6h; for (e (left)), n = 155 cells for N4, 91 for T4, 94 for G4.
Supplementary Figure 4 Comparison of alternative antigen presentation strategies for 2-day stimulation of CD8+ T cells.
a, OTI CD8+ T cells activated with peptide-pulsed T-depleted autologous APCs (top) or pure peptide (bottom) for 2 days were examined for death by flow cytometry. Cells were gated on singlet, CD8+, proliferation dye+ cells. Gate denotes the percentage of dead cells in each sample. Direct comparison using T cells from the same mouse is representative of 2 independent experiments. b, OT-I CD8+ T cells activated with pure peptide for 2 days were examined for proliferation and CD44 expression by flow cytometry. Results are representative of 4 separate mice in 3 independent experiments. c, OT-I CD8+ T cells were stimulated as in Fig. 5 except that wild-type splenocytes were used as APCs. After 2 days, proliferation and CD44 expression were measured by flow cytometry. For cell division plotting, cells were additionally gated on proliferation dye+ cells to exclude CD8+ T cells from wild-type splenocyte APCs. d, Protein phenotypes of cells stimulated as in c were examined by flow cytometry. Results (c-d) are representative of 2-3 independent experiments for each condition and measurement.
Supplementary Figure 5 Expression of all proteins measured by mass cytometry in phenotypic hyperspheres that were differentially abundant between stimulation conditions.
Plot as in Fig. 6c is colored by the intensity of each marker measured by mass cytometry. Labels indicate the metal tag, antibody target, and secondary antibody where appropriate.
Supplementary Figure 6 Flow cytometry validation of protein expression phenotypes observed in 2-day stimulation of CD8+ T cells.
a, Co-expression of selected proteins measured by mass cytometry in Fig. 6 was validated by flow cytometry. Each co-expression plot is representative of at least 4 separate mice in at least 3 independent experiments. b, Plots summarize replicate experiments from a quantifying the percentages of cells in each condition expressing the indicated proteins; n = 10 mice in 7 independent experiments for CD44, 9 in 6 for Granzyme B (GZMB), 8 in 5 for CTLA-4, 4 in 3 for CD62L, 4 in 3 for CD25; lines depict the mean. c, GZMB expression in GZMB+ cells is quantified by flow cytometry for 9 separate mice in 6 independent experiments; p values by two-sided Wilcoxon signed rank test. d, GZMB versus proliferation dye dilution for one representative experiment from c. e, Mass cytometry data plot as in Fig. 6b,c is colored by the relative proportion of cells from each stimulus in each hypersphere (i.e. the proportion of the cells in the hypersphere occupied by cells from each condition after normalizing for total cell count in each condition). f, Mass cytometry data were validated by flow cytometry examining the percentage of IFN-γ+ cells in each condition. Plot depicts results from 8 separate mice in 5 independent experiments; line denotes the mean. g, IFN-γ versus proliferation dye dilution for one representative experiment from f.
Supplementary Figure 7 Confirmation and summarization of degranulation phenotypes.
a, OTI CD8+ T cells were activated with pulsed wild-type splenocyte APCs for 2 days as in Supplementary Fig. 4c before assaying degranulation as in Fig. 7a. b-c, Cells in a were gated on their division number (b) or CD44 expression (c) before comparing LAMP1 MFI. We note that there were not sufficient cells that had undergone 4 divisions after G4 primary stimulation to calculate LAMP1 MFI. (a-c) are representative of 3 independent experiments. d, The 8 replicates of the degranulation assay in Fig. 7d (left) challenging day-7 CTLs with ovalbumin peptide (N4)-pulsed EL4 cells. e, As d for the 5 replicates of the degranulation assay in Fig. 7d (right) challenging day-7 CTLs with plate-bound anti-CD3ε. p values (d-e) by two-sided Wilcoxon signed rank test.
Supplementary Figure 8 Flow cytometry gating strategies.
a, Example gating strategy for single-cell sorting: cells were sorted on size, single cells, live cells, CD8+ T cells, and proliferation dye+ cells. b, Example gating strategy for RNA flow cytometry: cells were gated on size, single cells, live cells, and Rpl39+ cells before examining Nr4a1 and Fosb expression; Nr4a1, Fosb and Rpl39 positive gates were set on fluorescence-minus-one stains. c, Example gating strategy for T cell phenotyping by flow cytometry: where included, 123count eBeads were counted and excluded; cells were gated on size, singlets, live cells, CD8+ cells, and proliferation dye+ cells. Cells in each division cycle were quantified. A combination of two separate staining panels was used to examine surface and intracellular proteins. d, Example gating strategy for day-2 degranulation assays: cells were gated on size, singlets, live cells, CD8+ cells, and, where necessary, proliferation dye+ cells; further refinement was achieved by gating cells in each division cycle or CD44hi cells before comparison of LAMP1 staining. e, Gating strategy for day-7 degranulation assays: cells were gated on size, singlets, live cells, and CD8+ cells before comparison of LAMP1 staining.
Supplementary information
Supplementary Figures
Supplementary Figures 1-8
Supplementary Table 1
A differential expression analysis was performed on scRNA-seq data between cells in the early activation cluster and the resting naive T cell cluster, and between cells in the late activation cluster and the resting cluster from Fig. 1. Differentially expressed genes were tested for Gene Ontology (GO) category enrichment. Enriched categories (FDR < 0.05) are reported
Supplementary Table 2
Results from the sc-RNAseq differential expression analysis between cells stimulated with peptides of different potencies (n = 155 cells for N4, 91 for T4, 94 for G4), controlling for activation status by CD69 protein expression depicted in Fig. 4
Supplementary Table 3
A differential expression analysis was performed on scRNA-seq data between peptides of different potencies, controlling for CD69 expression as described in Fig. 4 and Supplementary Table 2. Differentially expressed genes were tested for Gene Ontology (GO) category enrichment. Enriched categories (FDR < 0.05) are reported
Supplementary Table 4
Antibodies used for mass cytometry experiment
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Richard, A.C., Lun, A.T.L., Lau, W.W.Y. et al. T cell cytolytic capacity is independent of initial stimulation strength. Nat Immunol 19, 849–858 (2018). https://doi.org/10.1038/s41590-018-0160-9
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DOI: https://doi.org/10.1038/s41590-018-0160-9