Abstract
Stem-cell fate can be influenced by metabolite levels in culture, but it is not known whether physiological variations in metabolite levels in normal tissues regulate stem-cell function in vivo. Here we describe a metabolomics method for the analysis of rare cell populations isolated directly from tissues and use it to compare mouse haematopoietic stem cells (HSCs) to restricted haematopoietic progenitors. Each haematopoietic cell type had a distinct metabolic signature. Human and mouse HSCs had unusually high levels of ascorbate, which decreased with differentiation. Systemic ascorbate depletion in mice increased HSC frequency and function, in part by reducing the function of Tet2, a dioxygenase tumour suppressor. Ascorbate depletion cooperated with Flt3 internal tandem duplication (Flt3ITD) leukaemic mutations to accelerate leukaemogenesis, through cell-autonomous and possibly non-cell-autonomous mechanisms, in a manner that was reversed by dietary ascorbate. Ascorbate acted cell-autonomously to negatively regulate HSC function and myelopoiesis through Tet2-dependent and Tet2-independent mechanisms. Ascorbate therefore accumulates within HSCs to promote Tet activity in vivo, limiting HSC frequency and suppressing leukaemogenesis.
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Acknowledgements
S.J.M. is a Howard Hughes Medical Institute (HHMI) Investigator, the Mary McDermott Cook Chair in Pediatric Genetics, the Kathryn and Gene Bishop Distinguished Chair in Pediatric Research, the director of the Hamon Laboratory for Stem Cells and Cancer, and a Cancer Prevention and Research Institute of Texas Scholar. M.A. was a Royal Commission for the Exhibition of 1851 Research Fellow. We thank F. Harrison for sharing the Slc23a2−/− mice, N. Loof and the Moody Foundation Flow Cytometry Facility for flow cytometry, K. Correll, A. Leach and A. Gross for mouse colony management and BioHPC at UT Southwestern for providing high-performance computing. This work was supported by the Cancer Prevention and Research Institute of Texas and the National Institutes of Health (R37 AG024945 and R01 DK100848).
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M.A. conceived and performed most experiments. C.E.M. performed experiments with Tet2fl and Tet2fl;Flt3ITD mice in Extended Data Figs 5, 8. R.J.B. and E.P. performed the histone methylation analysis. E.P. and Z.Z. performed RNA-sequencing analysis. Z.Z. performed the statistical analyses. G.M.C. assessed haematopathology in Figs 4, 5. E.B. and B.L.C. provided technical assistance. M.M.M. performed collagen staining. W.C. provided human bone marrow specimens. G.J.S. provided some of the data from Slc23a2−/− mice. Z.H., M.A., and R.J.D. developed the metabolomics methods and R.J.D. helped to interpret metabolomics results. M.A. and S.J.M. designed experiments, interpreted results and wrote the manuscript.
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Extended data figures and tables
Extended Data Figure 1 Stability of metabolites during cell isolation.
a, Diagram of the isolation procedure. b–f, Fold changes in the levels of representative metabolites in 20,000 bone marrow cells before and after each step of the cell isolation procedure. Metabolites were extracted before and after bone marrow cells were kept on ice for 7 h (b), centrifuged at 4 °C at 300g for 5 min (c), stained with the antibodies used for HSC isolation (d), cells underwent positive selection with anti-CD45 and anti-Ter119 beads (e) or were sorted by flow cytometry for CD45 and Ter119 (f). G1P, glucose/fructose-1-phosphate; GPC, glycerophosphocholine; GSH, glutathione; NAD, nicotinamide adenine dinucleotide; SAM, S-adenosylmethionine; SMTA, S-methyl-5′-thioadenosine. Although most bone marrow cells are CD45+ or Ter119+, unfractionated samples are different in cellular composition from samples after selection and sorting, perhaps contributing to the changes observed in some metabolites in e and f. Data were normalized to the median metabolite signal intensity of each sample. Statistical significance was assessed with t-tests performed on log2-transformed data. We accounted for multiple comparisons by controlling the false discovery rate. n = 3 mice; *P < 0.05, **P < 0.01, ***P < 0.001. g, Ascorbate levels were compared in whole bone marrow cells from which metabolites were extracted before the cell purification procedure, or after flow cytometric purification (a total of n = 4 mice from two independent experiments). Statistical significance was assessed using a paired t-test. All data represent mean ± s.d. ns, not significant.
Extended Data Figure 2 Differences in metabolite levels among haematopoietic stem and progenitor cell populations in the bone marrow.
a, Types of metabolites detected in 10,000 HSCs. b, Unsupervised clustering of metabolomic data from HSCs, MPPs and CD45+ bone marrow haematopoietic cells isolated from six independent experiments. BM, bone marrow. c, Metabolites that significantly differed between HSCs and CD45+ bone marrow cells (six independent experiments with a total of 6 HSC samples and 16 CD45+ bone marrow samples). GSH, glutathione; IMP, inosine monophosphate. Statistical significance was assessed using t-tests performed on log2-transformed data. We accounted for multiple comparisons by controlling the false discovery rate. All data represent mean ± s.d. d, The metabolites that we measured in stem and progenitor cell populations. The display is autoscaled for each metabolite to illustrate changes across samples. In total, 52 out of 64 metabolites show statistically significant changes among at least some cell populations (one experiment is shown, representative of three independent experiments; *P < 0.05, **P < 0.01, ***P < 0.001) assessed using a one-way ANOVA for each metabolite followed by Fisher’s LSD tests corrected for multiple comparisons by controlling the false discovery rate.
Extended Data Figure 3 The ascorbate content in haematopoietic stem and progenitor cells correlates with ascorbate transporter expression level and the phenotype of ascorbate-depleted Gulo−/− mice.
a, Ascorbate content versus slc23a2 expression in haematopoietic stem and progenitor cell populations. The plotted data are from Fig. 1c, d. b–s, u, Analysis of ascorbate-depleted Gulo−/− mice and littermate controls (a total of n = 5–11 mice per genotype per time point were analysed from 3–6 independent experiments per time point). t, The percentage of cells that incorporated a three-day pulse of 5-bromodeoxyuridine (BrdU) at 7–8 weeks of age (a total of n = 4–6 mice per genotype from three independent experiments). Statistical significance was assessed with a two-way ANOVA followed by Fisher’s LSD tests (b–l) or Mann–Whitney U-tests (p, u). We corrected for multiple comparisons by controlling the false discovery rate. *P < 0.05, **P < 0.01, ***P < 0.001. All data represent mean ± s.d.
Extended Data Figure 4 Ascorbate depletion did not have any detectable effects on global histone methylation, collagen levels, ROS levels, carnitine metabolism or Tet1–Tet3 expression in HSCs or other haematopoietic progenitors.
a, Western blots with antibodies against the indicated histone modifications were performed using haematopoietic cells from eight-week-old ascorbate-depleted Gulo−/− mice and littermate controls (a total of n = 3–6 mice per genotype from three independent experiments). Bar graphs show band intensity relative to the band intensity of the wild-type sample of each cell type. We did not observe an increase in histone methylation for any of the modifications, as would be expected if ascorbate was promoting global histone demethylase activity. We observed reduced H3K27me3 in HPCs (note that the data in Fig. 3e show that the effects of ascorbate depletion on Flt3ITD-driven myelopoiesis were mediated mainly by reduced Tet2 function). For gel source data, see Supplementary Fig. 1. MyP, myeloid progenitor; WBM, whole bone marrow. b, Histochemical staining of collagen with Sirius red (bright field or polarized light) or Masson’s trichrome (blue) of bone sections from 8–16-week-old Gulo−/− mice and littermate controls (photographs are representative of 6–8 mice per genotype from two independent experiments). c, Carnitine and acetylcarnitine levels were measured by LC–MS/MS for the indicated cell populations obtained from 7–8-week-old Gulo−/− and littermate-control mice (a total of n = 4–7 mice per genotype from four independent experiments). Data show carnitine/acetylcarnitine levels relative to the average levels in wild-type whole bone marrow samples. d, ROS levels were measured in 12-week-old Gulo−/− and littermate-control mice using CellRox Deep Red and Enzo Total ROS dyes (a total of n = 3–4 mice per genotype from three independent experiments). Data show ROS levels relative to wild-type whole bone marrow samples. e, Ascorbate levels were measured in the plasma and bone marrow (BM) of 4–6-month-old Gulo−/− mice or controls (a total of n = 12–17 mice per genotype for plasma and n = 5 mice per genotype for bone marrow were analysed from three independent experiments). f, Tet1–Tet3 transcript levels did not change in Gulo−/− versus littermate control mice, suggesting that the effect of ascorbate depletion on Tet activity was not due to reduced Tet1–Tet3 transcription (n = 3 mice). Statistical significance was assessed with two-way ANOVAs (a-d, f) followed by Fisher’s LSD tests or Welch’s tests (e), or Mann–Whitney test (a- H3K36me2-HPC). We corrected for multiple comparisons by controlling the false discovery rate. All data represent mean ± s.d.
Extended Data Figure 5 Tet2 deletion increases HSC frequency and function.
a–g, Mx1-Cre;Tet2fl/fl mice and littermate controls (+/+) were injected with poly(I:C) at 6–8 weeks of age. The frequencies of HSCs and other haematopoietic progenitors were analysed three weeks later (a total of n = 10–24 mice per genotype from 9–14 independent experiments). h, Percentage of donor-derived haematopoietic cells after competitive transplantation of 200,000 donor Tet2+/+, or Tet2Δ/+ or Tet2Δ/Δ bone marrow cells along with 500,000 wild-type recipient competitor cells in irradiated recipient mice (a total of five donors and 15–25 recipients per treatment from five independent experiments). All data represent mean ± s.d. Statistical significance was assessed with Kruskal–Wallis tests (a–g), or a non-parametric mixed model followed by a Kruskal–Wallis test for individual time points (h). We corrected for multiple comparisons by controlling the false discovery rate. *P < 0.05, **P < 0.01, ***P < 0.001.
Extended Data Figure 6 Ascorbate regulates HSC function in vivo and HSC differentiation in culture.
a, Ascorbate levels in sorted cell populations from transplanted recipient mice (a total of n = 2–4 mice per genotype from two independent experiments). b, Percentage of donor cells that are myeloid, B or T cells in wild-type or Gulo−/− recipients 16 weeks after transplantation (a total of n = 13–18 mice per condition were analysed from four independent experiments). c, d, Competitive transplantation of 500,000 donor bone marrow cells from Tet2fl/fl;Mx1-cre mice or littermate controls along with 1,500,000 competitor wild-type cells in irradiated wild-type (ascorbate-replete) or Gulo−/− (ascorbate-depleted) mice (a total of two donor mice and 5–10 recipient mice per treatment from two independent experiments). e, Plasma ascorbate levels in wild-type mice, Gulo−/− mice or Gulo−/− mice fed an ascorbate-supplemented diet (a total of n = 6–17 mice per condition were analysed from four independent experiments). f, Ascorbate content in bone marrow cells from wild-type and Gulo−/− mice fed normal mouse chow or an ascorbate-supplemented diet (a total of n = 3–11 mice per condition were analysed from three independent experiments). g–m, Myeloid and erythroid differentiation were assessed eight days after culturing HSCs in the presence or absence of ascorbate or its more stable derivative, 2-phospho-ascorbate (a total of n = 48 wells for myeloid and 24 wells for erythroid differentiation from two independent experiments). All data represent mean ± s.d. Statistical significance was assessed with Welch’s tests (a, b), Kruskal–Wallis tests (e–m), or a non-parametric mixed model followed by a Kruskal–Wallis test for individual time points (d). We corrected for multiple comparisons by controlling the false discovery rate. *P < 0.05, **P < 0.01, ***P < 0.001.
Extended Data Figure 7 Gene expression changes in HSCs/MPPs from Gulo−/−, Tet2Δ/Δ and Tet2Δ/Δ;Gulo−/− mice relative to control HSCs/MPPs.
a–c, HSCs/MPPs were isolated from 4–5-month-old mice of the indicated genotypes. Mice from all treatments were maintained on low ascorbate water and treated with poly(I:C) to induce Tet2 deletion by Mx1-Cre two months before HSC/MPP isolation. a, Fold-change values for all genes that significantly differed among any combination of genotypes (DESeq2 likelihood ratio tests for differential expression, corrected for multiple comparisons by controlling the false discovery rate). The value for each gene in the control cells was set to one. Red and green indicate increases and decreases in gene expression, respectively. The number of genes in Gulo−/− and Tet2Δ/Δ HSCs/MPPs that changed in expression in the same direction in both genotypes relative to control HSCs/MPPs was significantly higher than would be expected by chance (P = 0.01, binomial test). b, Fold change (log2) for HSCs/MPPs of each genotype relative to control HSCs/MPPs. All genes that changed in the same direction in all three genotypes relative to control are shown and for which the log2 fold change was >0.7 or <−0.7 and fragments per kilobase of transcript per million mapped reads (FPKM) > 1. Negative fold change values indicate that the expression of the indicated gene decreased in the indicated genotypes compared to control and positive values indicate that the expression of the gene increased. c, Gene set enrichment analysis showed that of the top 20 gene sets (based on normalized enrichment score) that were downregulated in Gulo−/− compared to control HSCs/MPPs, 4 were also among the top 20 gene sets downregulated in Tet2Δ/Δ compared to control HSCs/MPPs (n = 3 mice per genotype, except for the Tet2Δ/Δ treatment, for which n = 2).
Extended Data Figure 8 Collaboration between Flt3ITD and either Tet2 deficiency or ascorbate depletion.
a–f, Analysis of the frequencies of haematopoietic stem and progenitor cell populations in the bone marrow of 10–12-week-old Mx1-Cre;Tet2fl/fl;Flt3ITD mice and littermate controls three weeks after poly(I:C) treatment (12–17 independent experiments; the numbers of mice per treatment in a–c are shown across the top of a and for d–f across the top of d). g, Percentage of donor-derived haematopoietic cells after competitive transplantation of 300,000 donor bone marrow cells of the indicated genotypes along with 300,000 competing recipient cells in irradiated recipient mice (a total of 2–5 donor mice and 6–20 recipient mice per treatment from five independent experiments). h, Secondary transplantation of 5 million bone marrow cells from primary Gulo−/− (ascorbate-depleted) recipients of Flt3ITD/+ cells in irradiated wild-type or ascorbate-depleted Gulo−/− recipient mice (a total of three donor mice and 10–18 recipient mice per treatment from three independent experiments). *Comparison to wild type and #comparison to Flt3ITD/+. i, Ascorbate levels in donor cells of the indicated genotypes sorted from transplant recipients (a total of n = 4 mice per condition from 2 independent experiments). 1°, primary transplantation; 2°, secondary transplantation. j, Frequencies of donor cells of the indicated genotypes in the blood of transplant recipients described in Fig. 3f, g. k, Analysis of HSC frequency in the fetal liver of embryonic day (E)17.5 mice of the indicated genotypes (five independent experiments; the numbers of mice per treatment are shown across the top). All data represent mean ± s.d. Statistical significance was assessed with one-way ANOVAs followed by Fisher’s LSD tests (d, k) or Kruskal–Wallis tests (a–c, e). In other cases, we used two-way ANOVAs followed by Fisher’s LSD tests (i), Kruskal–Wallis tests (j) or a non-parametric mixed model followed by Kruskal–Wallis tests for individual time points (g, h). We corrected for multiple comparisons by controlling the false discovery rate. *P < 0.05, **P < 0.01, ***P < 0.001; #P < 0.05, ##P < 0.01, ###P < 0.001; +P < 0.05, ++P < 0.01, +++P < 0.001. *Comparison to the wild-type (+/+) condition, #comparison to the Flt3ITD condition and +comparison to the Tet2Δ/+ or Tet2Δ/Δ conditions. To simplify the representation of statistical significance in g, statistical significance was only noted when both Tet2Δ/+ and Tet2Δ/Δ conditions, or both Tet2Δ/+;Flt3ITD and Tet2Δ/Δ;Flt3ITD conditions, were significantly different from other conditions).
Extended Data Figure 9 Analysis of Tet2Δ/+;Flt3ITD leukaemias.
a–g, Analysis of recipient mice described in Fig. 4a–d. Statistical significance was assessed with one-way ANOVAs followed by Fisher’s LSD tests (f, g) or Kruskal–Wallis tests (e). d, Representative images from the experiments quantified in Fig. 4a. All data represent mean ± s.d. We corrected for multiple comparisons by controlling the false discovery rate. *P < 0.05, **P < 0.01, ***P < 0.001.
Extended Data Figure 10 Analysis of Tet2Δ/+;Flt3ITD and Tet2Δ/Δ;Flt3ITD leukaemias.
a, b, Analysis of recipient mice described in Fig. 4e–j. Statistical significance was assessed with one-way ANOVAs followed by Fisher’s LSD tests (b) or Kruskal–Wallis tests (a). c, Western blots with antibodies against the indicated histone modifications were performed using protein extracted from Tet2Δ/+;Flt3ITD/+ leukaemia cells isolated by flow cytometry from wild-type or ascorbate-depleted Gulo−/− transplant recipients (results are representative of two independent experiments). d, Diff-Quik-stained blood smears from Gulo−/− recipients of Tet2Δ/+;Flt3ITD/+ cells fed with an ascorbate-supplemented diet before and after the engraftment of leukaemia cells (representative images from the experiments described in Fig. 5a and quantified in Fig. 5c). Cells with an immature blast-like morphology were more abundant in the blood of ascorbate-depleted Gulo−/− recipients compared to ascorbate-fed Gulo−/− recipients. e, f, WBCs in recipient mice from the experiment described in Fig. 5a. The statistical significance of differences among treatments was assessed with Kruskal–Wallis tests (a, e, f) or a one-way ANOVA (b) or a two-way ANOVA followed by Fisher’s LSD tests (c). All data represent mean ± s.d. We corrected for multiple comparisons by controlling the false discovery rate. *P < 0.05, **P < 0.01, ***P < 0.001.
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Agathocleous, M., Meacham, C., Burgess, R. et al. Ascorbate regulates haematopoietic stem cell function and leukaemogenesis. Nature 549, 476–481 (2017). https://doi.org/10.1038/nature23876
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DOI: https://doi.org/10.1038/nature23876
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