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Data availability
The NCBI Gene Expression Omnibus accession number for the RNA-seq experiment reported in this paper is GSE215115.
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Acknowledgements
We thank the staff at the NIH Tetramer Core Facility for providing flow tetramers; the staff at the Bloomberg~Kimmel Institute for Cancer Immunotherapy Flow Cytometry and Human Immunology Technology Center for providing cell sorting. This work was supported by the National Institutes of Health (R01CA226765, R01CA229451, R01AI155602, R01AI07761 and P41EB028239-01 to J.D.P.) and The Bloomberg~Kimmel Institute for Cancer Immunotherapy.
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W.X. and J.D.P. designed and oversaw the study. W.X., C.H.P., J.A., L.Z., I.-H.S., M.-H.O., I.-M.S., R.L.B. and A.J.T. performed experiments and data analysis. C.H.P., I.-H.S. and M.-H.O. provided expertise in experimental design and data interpretation. J.W. helped with mouse genotyping and colony maintenance. W.X. and J.D.P. wrote the manuscript.
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J.D.P. is a cofounder and equity holder of Dracen Pharmaceuticals. C.H.P. and J.D.P. are current employees of Calico. The other authors declare no competing interests.
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Extended data figures and tables
Extended Data Fig. 1 GOT1 knockout did not affect T cell development and TH17 cell activation, slightly delayed the proliferation of TH17 cells; acute GOT1 deletion using CRISPR promoted TH17 while inhibited FOXP3 expression.
(a) Immunoblot measurement of GOT1 expression in isolated naive WT and GOT1−/− CD4+ T cells. β-actin served as the loading control. (b) Gating strategy to sort naive CD4+ T cells (CD4+CD44−CD62L+CD25-) for in vitro TH17 and iTreg cell differentiation experiments. For general flow cytometry analysis, lymphocytes, single cells, live cells and CD4+ T cells were gated similarly before further analysing. (c-f) Flow cytometry analysis of T cell compartments from thymus, spleen and lymph nodes from WT and T cell conditional GOT1−/− mice. (c) Percentages of CD4+ and CD8+ T cells (representative flow plots on the left and statistical analysis on the right). P values (left to right): ns = 0.9979, ns = 0.1946, *P = 0.0275 (upper panel, CD4+); ns = 0.9943, ns = 0.6661, *P = 0.0382 (bottom panel, CD8+). (d-e) Representative flow plots (left) and statistical analysis (right) of CD44 and CD62L expression of CD4+ T cells (d) or CD8+ T cells (e). P values (left to right): ns = 0.8454, ns = 0.8790 (CD44+CD62L+, CD4+); ns = 0.4353, ns = 0.6607 (CD44−CD62L+, CD4+); ns = 0.3799, ns = 0.6228 (CD44+CD62L+, CD8+); ns = 0.9993, ns = 0.9941 (CD44-CD62L+, CD8+). (f) Representative flow plots (left) and statistical analysis (right) of FOXP3 expression of CD4+ T cells. P values (left to right): ns = 0.3227, ns = 0.9706. (g) Flow cytometry analysis of CD69 and CD44 expression of WT and GOT1−/− TH17 cells at indicated time points. (h) Flow cytometry analysis of cell proliferation as indicated by CTV dilution of WT and GOT1−/− TH17 cells at indicated time points. (i-m) WT naive CD4+ T cells were electroporated with control (Ctrl) or GOT1 guide RNAs (g1, g2, g3) complexed with Cas9 protein, rested in IL-7 for 48 h and then differentiated into TH17 cells. (i) Immunoblot measurement of GOT1 expression. Tubulin served as the loading control. (j) Flow cytometry analysis of IL17A production upon PMA/Ionomycin stimulation and FOXP3 expression. Representative flow plots of IL17A (top) and FOXP3 (bottom) on the left, statistical analysis on the right. ****P < 0.0001. (k) Flow cytometry analysis of IL17A geometric mean fluorescence intensity (gMFI) of IL17A+ cells upon PMA/Ionomycin stimulation. Representative flow plot on the left, statistical analysis on the right. ****P < 0.0001. (l) ELISA measurement of IL17A upon anti-CD3 (3 μg ml−1) and anti-CD28 stimulation. ****P < 0.0001, **P = 0.0021, ***P = 0.0002. (m) Real-time PCR analysis of Il17a and Foxp3 mRNA levels. ****P < 0.0001, ***P = 0.0003. Two-way ANOVA with Sidak’s multiple comparisons test (c-f, j, m), one-way ANOVA with Dunnett’s multiple comparisons test (k, l). Mean ± s.e.m. values were shown. Representative data from n = 2 (a-h) or n = 4 (i-m) independent experiments with similar results. In each biological repeat, n = 6 mice were used in each group (c-f).
Extended Data Fig. 2 AOA chemically reacted with keto-acids.
(a-b) Targeted metabolomics analysis of WT, AOA (250 µM) treated WT or GOT1−/− TH17 cells. (a) Principal component analysis (PCA) plot. (b) Heatmap showing top 30 differentially expressed metabolites. (c-d) WT and GOT1−/− naive CD4+ T cells were differentiated into TH17 cells. (c) MS measurements of aspartate and glutamate levels. ***P = 0.0004, **P = 0.0012. (d) Pyrosequencing analysis of Foxp3 CNS2 region CpG methylation status. (e) WT naive CD4+ T cells were differentiated into TH17 cells without treatment (NT), or with AOA (250 µM) or AOA together with 2 mM dimethyl-ketoglutarate (DMK). Flow cytometry analysis of IL17A production upon PMA/Ionomycin stimulation and FOXP3 expression were shown. Representative flow plots of IL17A (top) and FOXP3 (bottom) on the left and statistical analysis on the right. ****P < 0.0001, ***P = 0.0003. (f-i) AOA (300 μM) was left alone or co-incubated with (f) pyruvate (Pyr), (g) oxaloacetate (OAA), (h) α-ketobutyrate (αKB) or (i) dimethyl-ketoglutarate (DMK) at indicated concentrations in PBS overnight. MS analysis of AOA and adducts formed between AOA and keto-acids were shown (left). Statistical analysis (right). ****P < 0.0001, ***P = 0.0003 (AOA vs. AOA + 100 µM DMK, AOA group), ns = 0.2885 (AOA vs. AOA + 100 µM DMK, AOA∙DMK group), ***P = 0.0001 (AOA vs. AOA + 200 µM DMK, AOA∙DMK group). (j) RNA sequencing analysis of WT and GOT1−/− TH17 cells. Gene set enrichment analysis (GSEA) plots of glycolysis/gluconeogenesis (top), Oxidative Phosphorylation (middle) and fatty acid metabolism (bottom) genes. Normalized enrichment scores in the gene set were shown. Unpaired t test, two-tailed (c), two-way ANOVA with Sidak’s multiple comparisons test (e), one-way ANOVA with Dunnett’s multiple comparisons test (f-i). Mean ± s.e.m. values were shown. Representative data from n = 3 (a-c, e-i) or n = 2 (d) or n = 1 (j) independent experiment(s) with similar results.
Extended Data Fig. 3 GOT1 restrains TH17 generation in vivo.
(a-f) WT and GOT1−/− mice were immunized with Complete Freuds Adjuvant (CFA)-gp66 peptide. Draining lymph nodes were collected on day 11 post immunization for analysis. (a) Frequency of CD44+ of CD4+ T cells. P value: ns = 0.3463. (b) Gating strategy for RORγt and FOXP3 expression of CD44+CD4+ T cells (left), and statistical analysis of RORγt and FOXP3 expression of CD44+CD4+ T cells (right). ***P = 0.0004 (FOXP3+%), ****P < 0.0001, ns = 0.0588, **P = 0.0026, ***P = 0.0002 (RORγt+%). (c) Frequency of gp66 tetramer positive T cells of CD44+CD4+ T cells. P value: ns = 0.8584. (d) Gating strategy for RORγt and FOXP3 expression of gp66 tetramer positive CD4+ T cells (left), and statistical analysis of RORγt expression of gp66 tetramer positive CD4+ T cells (right). **P = 0.0034. (e-f) Flow cytometry analysis of IL17A and IFNγ production upon (e) PMA/Ionomycin or (f) gp66 peptide stimulation. P values: **P = 0.0018, ns = 0.1993 (PMA/Ionomycin group); **P = 0.0021, ns = 0.8843 (peptide group). Mann-Whitney t test, two-tailed (a-f). Mean ± s.e.m. values were shown. Representative data from n = 2 independent experiments with similar results. In each biological repeat, WT group contains n = 10 mice, GOT1−/− group contains n = 12 mice.
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The uncropped blots for Extended Data Fig. 1a,h.
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Xu, W., Patel, C.H., Alt, J. et al. GOT1 constrains TH17 cell differentiation, while promoting iTreg cell differentiation. Nature 614, E1–E11 (2023). https://doi.org/10.1038/s41586-022-05602-3
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DOI: https://doi.org/10.1038/s41586-022-05602-3
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