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Exit from dormancy provokes DNA-damage-induced attrition in haematopoietic stem cells

Nature volume 520, pages 549–552 (2015)Cite this article

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Abstract

Haematopoietic stem cells (HSCs) are responsible for the lifelong production of blood cells. The accumulation of DNA damage in HSCs is a hallmark of ageing and is probably a major contributing factor in age-related tissue degeneration and malignant transformation1. A number of accelerated ageing syndromes are associated with defective DNA repair and genomic instability, including the most common inherited bone marrow failure syndrome, Fanconi anaemia2,3. However, the physiological source of DNA damage in HSCs from both normal and diseased individuals remains unclear. Here we show in mice that DNA damage is a direct consequence of inducing HSCs to exit their homeostatic quiescent state in response to conditions that model physiological stress, such as infection or chronic blood loss. Repeated activation of HSCs out of their dormant state provoked the attrition of normal HSCs and, in the case of mice with a non-functional Fanconi anaemia DNA repair pathway, led to a complete collapse of the haematopoietic system, which phenocopied the highly penetrant bone marrow failure seen in Fanconi anaemia patients. Our findings establish a novel link between physiological stress and DNA damage in normal HSCs and provide a mechanistic explanation for the universal accumulation of DNA damage in HSCs during ageing and the accelerated failure of the haematopoietic system in Fanconi anaemia patients.

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Figure 1: pI:pC induces proliferation-induced DNA damage in LT-HSCs.
Figure 2: Metabolic ROS induce DNA damage in cycling LT-HSCs.
Figure 3: The Fanconi anaemia pathway is involved in resolving in vivo proliferative stress in LT-HSCs.
Figure 4: Chronic stress leads to LT-HSC depletion and bone marrow failure in Fanca−/− mice.

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Acknowledgements

We thank R. Gliniorz, S. Blaszkiewicz, V. Vogel and B. Schoell for technical assistance, B. Walter for help with figures and S. Fröhling, M. Sprick and T. Oskarsson for critical proofreading of this manuscript. We also acknowledge support from the Animal Laboratory Services Deutsches Krebsforschungszentrum (DKFZ) core facility and S. Schmitt, A. Atzberger, J. Hartwig and K. Hexel from the Imaging and Cytometry DKFZ core facility. We are grateful to K. J. Patel for anti-mouse FANCD2 antibody and T. Southgate for the SF-CS-I-G retroviral vector. D.W., A.L., M.A.G.E., A.T. and M.D.M. were supported by the BioRN Leading-Edge Cluster “Cell-Based and Molecular Medicine” funded by the German Federal Ministry of Education and Research, and the Dietmar Hopp Foundation. M.A.R. was supported by the LOEWE Center for Cell and Gene Therapy Frankfurt, Hessisches Ministerium für Wissenschaft und Kunst (III L 4- 518/17.004 (2014)). A.T. and M.A.G.E. were also supported by the SFB873 funded by the Deutsche Forschungsgemeinschaft. A.G. and P.K. are funded by a fellowship from the Helmholtz International Graduate School and S.W.L. received support from the Leukemia Foundation of Australia, Cure Cancer Australia Foundation and the National Health and Medical Research Foundation of Australia.

Author information

Author notes

  1. Dagmar Walter and Amelie Lier: These authors contributed equally to this work.

Authors and Affiliations

  1. Heidelberg Institute for Stem Cell Technology and Experimental Medicine gGmbH (HI-STEM), 69120 Heidelberg, Germany,

    Dagmar Walter, Amelie Lier, Sina Huntscha, Corinna Klein, Marieke A. G. Essers, Andreas Trumpp & Michael D. Milsom

  2. Division of Stem Cells and Cancer, Deutsches Krebsforschungszentrum (DKFZ), Experimental Hematology Group, 69120 Heidelberg, Germany,

    Anja Geiselhart, David Brocks, Irem Bayindir, Paul Kaschutnig & Michael D. Milsom

  3. LOEWE Center for Cell and Gene Therapy and Department of Hematology/Oncology, Goethe University Frankfurt, 60595 Frankfurt am Main, Germany,

    Frederic B. Thalheimer & Michael A. Rieger

  4. Division of Redox Regulation, Deutsches Krebsforschungszentrum (DKFZ), DKFZ-ZMBH Alliance, 69120 Heidelberg, Germany,

    Mirko C. Sobotta & Tobias P. Dick

  5. Institute for Molecular Medicine, Stem Cells and Aging, Ulm University, 89081 Ulm, Germany,

    Bettina Moehrle & Hartmut Geiger

  6. Division of Stem Cells and Cancer, Deutsches Krebsforschungszentrum (DKFZ), 69120 Heidelberg, Germany,

    Katja Muedder & Andreas Trumpp

  7. Institute of Human Genetics, University of Heidelberg, 69120 Heidelberg, Germany,

    Anna Jauch

  8. Department of Biosystems Science and Engineering, ETH Zurich, 4058 Basel, Switzerland,

    Timm Schroeder

  9. Division of Experimental Hematology and Cancer Biology, Cincinnati Children’s Hospital Medical Center, Cincinnati, 45229, Ohio, USA

    Hartmut Geiger

  10. Division of Biostatistics, Deutsches Krebsforschungszentrum (DKFZ), 69120 Heidelberg, Germany,

    Tim Holland-Letz

  11. Division of Epigenomics and Cancer Risk Factors, Deutsches Krebsforschungszentrum (DKFZ), 69120 Heidelberg, Germany,

    Peter Schmezer

  12. QIMR Berghofer Medical Research Institute, University of Queensland, Brisbane 4006, Australia,

    Steven W. Lane

  13. Division of Stem Cells and Cancer, Deutsches Krebsforschungszentrum (DKFZ), Hematopoietic Stem Cells and Stress Group, 69120 Heidelberg, Germany,

    Marieke A. G. Essers

  14. Boston Children’s Hospital, Boston, 02115, Massachusetts, USA

    David A. Williams

  15. Dana-Faber Cancer Institute, Boston, 02115, Massachusetts, USA

    David A. Williams

  16. Harvard Stem Cell Institute, Boston, 02138, Massachusetts, USA

    David A. Williams

  17. Harvard Medical School, Boston, 02115, Massachusetts, USA

    David A. Williams

Authors
  1. Dagmar Walter
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Contributions

D.W., A.L., P.S., S.W.L., A.J., T.S., H.G., T.P.D., M.A.R., M.A.G.E., D.A.W., A.T. and M.D.M. designed experiments and analysed experimental data. D.W., A.L., A.G., F.B.T., M.C.S., B.M., S.H., D.B., I.B., P.K., K.M., P.S., C.K. and M.D.M. performed experiments. T.H.-L. performed statistical analysis on experimental data and S.W.L. provided interpretation of mouse histology samples. D.W., A.L., S.W.L., M.A.G.E., P.S., T.P.D., M.A.R., D.A.W., A.T. and M.D.M. wrote the manuscript.

Corresponding author

Correspondence to Michael D. Milsom.

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The authors declare no competing financial interests.

Extended data figures and tables

Extended Data Figure 1 HSCs exit quiescence in vivo following challenge of mice with a double-stranded RNA mimetic.

a, Schematic outline of pI:pC time course experiments. b, Schematic of the flow cytometry scheme used to identify and/or prospectively purify LT-HSCs, short-term (ST)-HSCs or MPPs from murine bone marrow. Ctrl, control. c, Representative FACS plot of Sca-1 expression of lineage (Lin)-negative, c-Kit-positive bone marrow cells 24 h after the indicated treatment. d, Limiting dilution analysis of HSC frequency after acute IFN-α treatment shows that the LT-HSC marker panel still prospectively isolates functional HSCs. Mice were injected twice with IFN-α or with PBS on consecutive days and bone marrow cells were harvested a further 24 h later. LT-HSCs were purified by FACS sorting as shown in b and lethally irradiated recipient mice were injected intra-femorally with a mixture of 1.5 × 105 supporting total bone marrow cells and either 3, 10, 30 or 100 of these sorted cells. At 20 weeks after transplantation, peripheral blood was analysed to determine whether donor HSCs had engrafted, which was defined as at least 1% donor chimaerism in both the lymphoid and myeloid lineages. HSC frequency was estimated using ELDA software (http://bioinf.wehi.edu.au/software/elda/). n = 5 mice (30 and 100 LT-HSCs), n = 10 mice (3 and 10 LT-HSCs). e, Representative FACS analysis of cell cycle distribution in LT-HSCs at 24 or 120 h after pI:pC treatment. f, Cell cycle analysis of LT-HSCs harvested from wild-type mice at the indicated time points after pI:pC injection. Mean ± s.d. is shown, n = 9 mice (96 h, 120 h); n = 10 mice (48 h, 72 h); n = 11 mice (control, 24 h). g, Composite analysis of the percentage of LT-HSCs that have: entered into active cell cycle (red); acquired five or more γH2AX foci per cell (grey); or acquired five or more FANCD2 foci per cell (blue), at the indicated time points after injection with pI:pC. Mean ± s.d. is shown. For cell cycle analysis, n = 8 mice (96 h); n = 9 mice (72 h, 120 h); n = 10 mice (48 h); n = 11 mice (control, 24 h). For γH2AX analysis, n = 3 biological repeats (control, 24 h, 48 h, 72 h, 96 h); n = 4 biological repeats (120 h). For FANCD2 foci analysis, n = 3 biological repeats (120 h); n = 4 biological repeats (control, 24 h, 48 h, 72 h, 96 h). h, Schematic representation of mechanism via which pI:pC induces cell cycle entry of HSCs in vivo and the effect of loss of function of IFNAR or Sca-1 (in red). D.C., dendritic cell. i, Cell cycle analysis of LT-HSCs harvested from wild-type (WT), Ifnar−/− or Sca1−/− mice 24 h after treatment. Mean ± s.d., n = 6 mice (Sca-1−/− pI:pC); n = 9 mice (wild-type control/pI:pC, Ifnar−/− control, Sca-1−/− control); n = 10 mice (Ifnar−/− pI:pC), two-way analysis of variance (ANOVA). j, Quantitative polymerase chain reaction with reverse transcription (qRT–PCR) analysis of expression levels of representative IFN target genes in Sca-1+/+ and Sca-1−/− LT-HSCs 48 h after pI:pC. Mean ± s.d., n = 3 independent biological repeats.

Source data

Extended Data Figure 2 Metabolic reactive oxygen species induce DNA damage in HSCs in vivo.

a, Representative cell cycle analysis of LT-HSCs isolated from wild-type mice injected with the indicated agonist or serially bled at 24 h after treatment. Ctrl, control. b, Percentage of LT-HSCs in active cycle (G1/S/G2/M) 24 h after the indicated treatment. Data are mean ± s.d., n = 5 mice (IFN-α, G-CSF); n = 6 mice (Bleed); n = 8 mice (control, pI:pC, TPO). c, Representative FACS plots of LT-HSCs stained with Mitotracker Red CMXRos or anti-8-Oxo-dG antibody. d, Change in LT-HSC CMXRos signal 24 h after pI:pC, TPO or serial bleeding treatment. Data are mean ± s.d., n = 7 mice (control); n = 8 mice (pI:pC, TPO, Bleed). e, Schematic of γ-retroviral vectors SF-Grx1-roGFP2, SF-Mito-Grx1-roGFP2, SF-roGFP2-Orp1, SF-Mito-roGFP2-Orp1, SF-IRES-eGFP (SF-I-G) and SF-Cat/SOD2-IRES-eGFP (SF-CS-I-G). Ψ, packaging signal; 2A, FMDV 2A peptide; eGFP, enhanced green fluorescent protein; GRX1, human glutaredoxin-1; IRES, internal ribosome entry site; Mito, mitochondrial; Orp1, yeast thiol peroxidase Gpx3; Pre, post-transcriptional regulatory element; roGFP2, redox-sensitive green fluorescent protein 2; SF, SFFV LTR enhancer/promoter. f, Schematic overview of retroviral rescue experiments. LSK, lineage−, Sca-1+, c-Kit+ bone marrow cells. g, Representative FACS plots of dithiothreitol (DTT)- or diamide-treated bone marrow cells transduced with SF-Grx1-roGFP2, SF-Mito-Grx1-roGFP2, SF-roGFP2-Orp1 or SF-Mito-roGFP2-Orp1. Boxes denote fluorescent ratios corresponding to the fully oxidized or fully reduced probe redox states as mediated by treatment with diamide or DTT, respectively. h, Representative FACS plots showing the percentage of LT-HSCs in a predominantly oxidized or reduced redox state for H2O2 redox probes 24 h after pI:pC treatment. i, j, Western blot analysis of catalase (i) or MnSOD (j) expression in SF-I-G- or SF-CS-I-G-transduced LSK cells. 1 = SF-I-G; 2 = SF-CS-I-G; 3 = SF-I-G; 4 = SF-CS-I-G. Bands corresponding to catalase or MnSOD are indicated. k, Cell cycle analysis of LT-HSCs transduced with either catalase/SOD2 (SF-CS-I-G)-overexpressing retroviral vector or control vector (SF-I-G) 24 h after pI:pC treatment. Data are mean ± s.d., n = 7 mice (SF-I-G pI:pC, SF-CS-I-G control/pI:pC); n = 9 mice (SF-I-G control). l, Catalase and MnSOD overexpression is sufficient to protect LSK cells from excessive levels of H2O2-induced apoptosis. Percentage of early (annexin V+, 7AAD−) or late (annexin V+, 7AAD+) apoptotic SF-I-G- or SF-CS-I-G-transduced LSK cells 24 h after treatment with 1 mM hydrogen peroxide. Data are mean ± s.d., n = 4 independent biological repeats.

Source data

Extended Data Figure 3 Characterization of in vivo stress response of hematopoietic progenitors versus HSCs.

a, Percentage of LK progenitor cells (lineage−, c-Kit+ and Sca-1−) in active cycle (G1/S/G2/M) at various time points after pI:pC treatment. Data are mean ± s.d. n = 5 mice (96 h and 120 h); n = 7 mice (24 h, 48 h and 72 h); n = 8 mice (control). Ctrl, control b, Colony-forming unit assay using total bone marrow cells isolated 48 h after pI:pC treatment. Data are mean ± s.d. n = 6 mice per group. c, Comparison of percentage of LT-HSCs and LKs having ≥5 γH2AX foci per cell 48 h after pI:pC treatment. Data are mean ± s.d., n = 3 biological repeats. d, Comparison of percentage of LT-HSCs and LKs having ≥5 53BP1 foci per cell 48 h after pI:pC treatment. Data are mean ± s.d., n = 3 biological repeats. e, Percentage of LT-HSCs and LKs having ≥5 RAD51 foci per cell 48 h after pI:pC treatment. Data are mean ± s.d., n = 3 biological repeats. f, LOG10 fold change in levels of 8-Oxo-dG lesions within LT-HSCs and LKs 24 h after pI:pC compared to control LT-HSCs. Data are mean ± s.d., n = 7 mice (pI:pC group) and n = 8 mice (control group). g, Percentage of LT-HSCs and LKs having ≥5 FANCD2 foci per cell 48 h after pI:pC treatment. Data are mean ± s.d., n = 3 biological repeats (LT-HSC pI:pC, LK control and pI:pC), n = 4 biological repeats (LT-HSC control). It is possible that the comparatively high baseline levels of DNA damage in the haematopoietic progenitor compartment may limit the lifespan of these cells.

Source data

Extended Data Figure 4 Involvement of the Fanconi anaemia DNA repair pathway in the in vivo response to stress.

a–c, Peripheral blood cell analysis of a Fanconi anaemia patient treated with IFN-α showing pre-treatment and nadir levels of peripheral blood parameters for total white blood cell count (WBC; a); haemoglobin level (Hb; b); and platelets (PLT; c). d, Schematic representation of the Fanconi anaemia signalling pathway highlighting FANCA (red), FANCD2 (blue) and FANCI (pink). e, Expression of Fanca, Fancd2 and Fanci in LT-HSCs, ST-HSCs and MPPs as determined by qRT–PCR. Data are mean ± s.d., n = 3 biological repeats (Fanca in ST-HSCs); n = 4 biological repeats (all remaining groups). f, Expression of Fanca, Fancd2 and Fanci in LT-HSCs at the indicated time points after treatment as determined by qRT–PCR. Ctrl, control. Data are mean ± s.d., n = 3 biological repeats. g, Percentage of LT-HSCs having ≥5 FANCD2 foci after the indicated treatment (pI:pC, IFN-α, TPO 48 h after treatment; G-CSF 36 h after treatment). Data are mean ± s.d., n = 3 biological repeats (pI:pC, IFN-α); n = 4 biological repeats (control, TPO, G-CSF). h, Cell cycle analysis of LT-HSCs isolated from wild-type (WT) and Fanca−/− mice 24 h after pI:pC. Data are mean ± s.d., n = 11 mice per condition. i, Percentage of LT-HSCs with ≥5 53BP1 foci per cell 48 h after pI:pC. Data are mean ± s.d., n = 3 biological repeats (Fanca−/−); n = 4 biological repeats (wild type). j–m, DNA damage analysis of wild-type LT-HSCs performed directly after isolation or after 36 h of in vitro culture. j, LT-HSC mitochondrial membrane potential. Data are mean ± s.d., n = 5 mice. k, Percentage of LT-HSCs with ≥5 γH2AX foci per cell either directly following harvest or after 36 h in culture. Data are mean ± s.d., n = 3 biological repeats. l, Percentage of LT-HSCs with ≥5 53BP1 or RAD51 foci per cell. Data are mean ± s.d., n = 3 biological repeats. m, Relative levels of 8-Oxo-dG lesions in LT-HSCs. Data are mean ± s.d., n = 5 mice. n, Representative pedigrees showing cell fate outcomes for individual wild-type and Fanca−/− LT-HSCs during in vitro culture as determined by videomicroscopy-based cell tracking. Horizontal bars indicate cell division and X indicates cell death. o, Videomicroscopy-based cell tracking of LT-HSCs during in vitro culture. The cumulative incidence of cell death after the second division is shown for wild-type and Fanca−/− LT-HSCs. n = 218 cells tracked (wild type); n = 263 cells tracked (Fanca−/−) across three independent biological repeats.

Source data

Extended Data Figure 5 HSC defects in Fanca−/− mice exposed to chronic stress.

a, Schematic representation of the 8-week serial treatment schedule. Mice were injected with either pI:pC or PBS eight times during the first 4 weeks of the schedule, as indicated. After a further 4-week recovery period, the mice were then euthanized and bone marrow was isolated for cell cycle analysis and competitive repopulation assays. b, Cell cycle analysis of LT-HSCs isolated from wild-type (WT) or Fanca−/− mice at the end of the serial treatment schedule depicted in a. Ctrl, control. Mean ± s.d. is shown, n = 6 mice per group. c, Schematic representation of the in vivo label retention assay used to assess long-term cycling behaviour of LT-HSCs. Wild-type or Fanca−/− mice harbouring both the Scl-tTa and H2B-GFP transgenes were serially treated with PBS or pI:pC according to the schedule illustrated in a. At the end of the schedule, drinking water was supplemented with doxycycline (DOX) to prevent de novo labelling of HSCs with GFP. Mice were euthanized after 70 days of DOX treatment and bone marrow was harvested for FACS analysis. d, Absolute levels of engraftment of CD45.1+ cells in the peripheral blood of recipient mice at 6 months (24 weeks) after transplantation. Mice were transplanted with a competitive chimaera, with the test population consisting of bone marrow from PBS- or pI:pC-treated wild-type or Fanca−/− mice as described in Fig. 4b. Each point denotes an individual recipient mouse, which received bone marrow from a single treated mouse. The mean ± s.d. is indicated with bars; n = 17 mice (Fanca−/−); n = 18 mice (wild type). e, Relative composition of the peripheral blood in wild-type or Fanca−/− mice at the end of the treatment schedule depicted in a. Mean ± s.d. is shown, n = 11 mice (Fanca−/− mice); n = 17 mice (wild-type control); n = 18 mice (wild-type pI:pC). f, Absolute frequency of LT-HSCs, MPPs and committed progenitors in the bone marrow of wild-type or Fanca−/− mice at the end of the treatment schedule depicted in a. CLP, common lymphoid progenitor; CMP, common myeloid progenitor; GMP, granulocyte–macrophage progenitor; MEP, megakaryocyte–erythroid progenitor. Mean ± s.d. is shown, n = 9 mice (wild-type control CLP, CMP, GMP, MEP); n = 11 (Fanca−/− control); n = 12 mice (wild-type control LT-HSCs, MPP, Fanca−/− pI:pC). g–i, Peripheral blood cell parameters for wild-type or Fanca−/− mice at the end of the treatment schedule depicted in a. g–i, Total white blood cell count (WBC; g), haemoglobin level (Hb; h) and platelet count (PLT; i) are shown for individual mice. Mean ± s.d. is shown, n = 6 (control group); n = 12 (pI:pC group).

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Extended Data Figure 6 Severe aplastic anemia in Fanca−/− mice exposed to chronic stress.

a, Schematic representation of the extended treatment schedule that mice were subjected to in the survival study described in Fig. 4c. Each 8-week round of treatment depicted here is referred to as a single cycle. b–i, H&E-stained sections of tibiae isolated from moribund pI:pC-treated Fanca−/− mice. Individual mice are numbered 1–10. k, Frequency of c-Kit+ CD41+ megakaryocytes within the bone marrow (BM) of moribund Fanca−/− mice treated with pI:pC versus age-matched PBS-treated Fanca−/− mice (control (Ctrl)). n = 6 (control); n = 8 (pI:pC). l, m, Reticulin-stained bone marrow sections from either an age-matched PBS-treated Fanca−/− mouse (l) or a moribund Fanca−/− mouse treated with pI:pC (m).

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Extended Data Figure 7 Model depicting a putative mechanism for how stress-induced activation of dormant HSCs leads to de novo DNA damage and eventual bone marrow failure.

a, Under homeostatic conditions, LT-HSCs reside in a quiescent state within the bone marrow niche. They rarely replicate their DNA and their energy demands are low, and this correlates with minimal use of the mitochondrial electron transport chain and accompanying low levels of ROS. b, Quiescent HSCs are induced into the cell cycle during times of stress to replenish the supply of mature cells that have been depleted during infection or following blood loss. As HSCs enter the cycle, they coordinately initiate DNA replication and upregulate energy production via oxidative phosphorylation within the mitochondria. Increased use of the mitochondrial electron transport chain correlates with elevated levels of intracellular ROS. c, Mitochondrial ROS may either directly form adducts on genomic DNA or, alternatively, may indirectly precipitate these lesions via activation of signal transduction pathways or secondary chemical entities. Increased levels of ROS-induced lesions coupled with elevated DNA replication increases the likelihood of the DNA replication fork colliding with repair intermediates. This reflects a condition of high replicative stress and would result in the induction of many stalled replication forks. d, The Fanconi anaemia repair pathway can resolve the stalled replication fork by coordinating the regression of the replicative machinery followed by translesion synthesis and homologous recombination repair. This mechanism of repair is of high fidelity and does not compromise HSC function by introducing deleterious mutations. e, At the site of some lesions, the replication fork will collapse, resulting in a DNA DSB, which will in turn provoke a locus-specific phosphorylation of γH2AX. Inefficient repair of this DSB will result in the loss of this cell from the HSC pool, or the survival of the HSC with the addition of DNA mutations. For each round of activation, only a small percentage of HSCs will be subject to inefficient repair of proliferative DNA damage and be depleted from the HSC pool. However, over the lifetime of an organism, HSCs will pass through this cycle many times. Eventually the gradual depletion of HSCs will become evident as the remaining stem cells are unable to sustain the ongoing demand for more mature blood cells. The lack of a functional Fanconi anaemia pathway will favour error-prone repair of stress-induced DNA damage, leading to a higher rate of HSC attrition per round of activation and hence the accelerated ageing of the haematopoietic system.

Supplementary information

Supplementary Information

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Live cell imaging video illustrating the behaviour of a single tracked WT LT-HSC over two rounds of cell division in vitro.

Individual tracked cells are numbered 1-7, with 1 being the parent LT-HSC, 2 and 3 being the second generation progeny and 4-7 being the third generation progeny. Time in culture is indicated in days, hours, minutes and seconds. (MP4 8578 kb)

Live cell imaging video illustrating the behaviour of a single tracked Fanca-/- LT-HSC over one round of cell division and subsequent cell death in vitro.

Individual tracked cells are numbered 1-3, with 1 being the parent LT-HSC and 2 and 3 being the second generation progeny. Time in culture is indicated in days, hours, minutes and seconds. (MP4 8522 kb)

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Walter, D., Lier, A., Geiselhart, A. et al. Exit from dormancy provokes DNA-damage-induced attrition in haematopoietic stem cells. Nature 520, 549–552 (2015). https://doi.org/10.1038/nature14131

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