Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Adaptive response to inflammation contributes to sustained myelopoiesis and confers a competitive advantage in myelodysplastic syndrome HSCs

Abstract

Despite evidence of chronic inflammation in myelodysplastic syndrome (MDS) and cell-intrinsic dysregulation of Toll-like receptor (TLR) signaling in MDS hematopoietic stem and progenitor cells (HSPCs), the mechanisms responsible for the competitive advantage of MDS HSPCs in an inflammatory milieu over normal HSPCs remain poorly defined. Here, we found that chronic inflammation was a determinant for the competitive advantage of MDS HSPCs and for disease progression. The cell-intrinsic response of MDS HSPCs, which involves signaling through the noncanonical NF-κB pathway, protected these cells from chronic inflammation as compared to normal HSPCs. In response to inflammation, MDS HSPCs switched from canonical to noncanonical NF-κB signaling, a process that was dependent on TLR-TRAF6-mediated activation of A20. The competitive advantage of TLR-TRAF6-primed HSPCs could be restored by deletion of A20 or inhibition of the noncanonical NF-κB pathway. These findings uncover the mechanistic basis for the clonal dominance of MDS HSPCs and indicate that interfering with noncanonical NF-κB signaling could prevent MDS progression.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: MDS HSPC are associated with inflammatory states.
Fig. 2: TLR-TRAF6-primed HSPCs outcompete WT HSPCs with LD-LPS.
Fig. 3: Overexpression of TRAF6 alters the response of hematopoietic cells to LD-LPS.
Fig. 4: LD-LPS stimulation of TLR-TRAF6-primed HSPC results in noncanonical NF-κB signaling.
Fig. 5: Noncanonical NF-κB activation correlates with A20 expression in TLR-TRAF6 primed HSPCs.
Fig. 6: A20 expression and noncanonical NF-κB activation occurs in TET2-deficient HSPC.
Fig. 7: Deletion of A20 prevents noncanonical NF-κB signaling and rescues the competitive advantage of TLR-TRAF6-primed HSPCs during LD-LPS.

Data availability

The data that support the findings of this study are available from the corresponding author upon request. All gene expression data are available at GSE142560, GSE19429, GSE58831 and GSE88949. Source data for Figs. 2–7 and Extended Data Figs. 1, 3, 5 and 8 are presented with the paper.

References

  1. 1.

    Nimer, S. D. Myelodysplastic syndromes. Blood 111, 4841–4851 (2008).

    CAS  PubMed  Google Scholar 

  2. 2.

    Nilsson, L. et al. Involvement and functional impairment of the CD34+CD38Thy-1+ hematopoietic stem cell pool in myelodysplastic syndromes with trisomy 8. Blood 100, 259–267 (2002).

    CAS  PubMed  Google Scholar 

  3. 3.

    Nilsson, L. et al. Isolation and characterization of hematopoietic progenitor/stem cells in 5q-deleted myelodysplastic syndromes: evidence for involvement at the hematopoietic stem cell level. Blood. 96, 2012–2021 (2000).

    CAS  PubMed  Google Scholar 

  4. 4.

    Muto, T. et al. Concurrent loss of Ezh2 and Tet2 cooperates in the pathogenesis of myelodysplastic disorders. J. Exp. Med. 210, 2627–2639 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  5. 5.

    Fang, J. et al. Ubiquitination of hnRNPA1 by TRAF6 links chronic innate immune signaling with myelodysplasia. Nat. Immunol. 18, 236–245 (2017).

    CAS  PubMed  Google Scholar 

  6. 6.

    Thanopoulou, E. et al. Engraftment of NOD/SCID-β2 microglobulin null mice with multilineage neoplastic cells from patients with myelodysplastic syndrome. Blood 103, 4285–4293 (2004).

    CAS  PubMed  Google Scholar 

  7. 7.

    Oishi, Y. & Manabe, I. Macrophages in age-related chronic inflammatory diseases. NPJ Aging Mech. Disease 2, 16018 (2016).

    Google Scholar 

  8. 8.

    Pietras, E. M. Inflammation: a key regulator of hematopoietic stem cell fate in health and disease. Blood 130, 1693–1698 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  9. 9.

    Barreyro, L., Chlon, T. M. & Starczynowski, D. T. Chronic immune response dysregulation in MDS pathogenesis. Blood 132, 1553–1560 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  10. 10.

    Varney, M. E. et al. Loss of Tifab, a del(5q) MDS gene, alters hematopoiesis through derepression of Toll-like receptor–TRAF6 signaling. J. Exp. Med. 212, 1967–1985 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  11. 11.

    Starczynowski, D. T. et al. Identification of miR-145 and miR-146a as mediators of the 5q- syndrome phenotype. Nat. Med. 16, 49–58 (2010).

    CAS  PubMed  Google Scholar 

  12. 12.

    Starczynowski, D. T. et al. Genome-wide identification of human microRNAs located in leukemia-associated genomic alterations. Blood 117, 595–607 (2011).

    CAS  PubMed  Google Scholar 

  13. 13.

    Rhyasen, G. W. et al. Targeting IRAK1 as a therapeutic approach for myelodysplastic syndrome. Cancer Cell 24, 90–104 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  14. 14.

    Fang, J. et al. TRAF6 mediates basal activation of NF-κB necessary for hematopoietic stem cell homeostasis. Cell Rep. 22, 1250–1262 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  15. 15.

    Varney, M. E. et al. Epistasis between TIFAB and miR-146a: neighboring genes in del(5q) myelodysplastic syndrome. Leukemia 31, 491–495 (2017).

    CAS  PubMed  Google Scholar 

  16. 16.

    Sato, S. et al. Toll/IL-1 receptor domain-containing adaptor inducing IFN-β (TRIF) associates with TNF receptor-associated factor 6 and TANK-binding kinase 1, and activates two distinct transcription factors, NF-κB and IFN-regulatory factor-3, in the Toll-like receptor signaling. J. Immunol. 171, 4304–4310 (2003).

    CAS  PubMed  Google Scholar 

  17. 17.

    Gohda, J., Matsumura, T. & Inoue, J. Cutting edge: TNFR-associated factor (TRAF) 6 is essential for MyD88-dependent pathway but not Toll/IL-1 receptor domain-containing adaptor-inducing IFN-β (TRIF)-dependent pathway in TLR signaling. J Immunol. 173, 2913–2917 (2004).

    CAS  PubMed  Google Scholar 

  18. 18.

    Schuettpelz, L. G. & Link, D. C. Regulation of hematopoietic stem cell activity by inflammation. Front. Immunol. 4, 204 (2013).

    PubMed  PubMed Central  Google Scholar 

  19. 19.

    Zhao, J. L. et al. NF-κB dysregulation in microRNA-146a-deficient mice drives the development of myeloid malignancies. Proc. Natl Acad. Sci. USA 108, 9184–9189 (2011).

    CAS  PubMed  Google Scholar 

  20. 20.

    Takizawa, H. et al. Pathogen-Induced TLR4-TRIF Innate Immune Signaling in Hematopoietic Stem Cells Promotes Proliferation but Reduces Competitive Fitness. Cell Stem Cell 21, 225–240.e5 (2017).

    CAS  PubMed  Google Scholar 

  21. 21.

    Zhang, H. et al. Sepsis induces hematopoietic stem cell exhaustion and myelosuppression through distinct contributions of TRIF and MYD88. Stem Cell Rep. 6, 940–956 (2016).

    CAS  Google Scholar 

  22. 22.

    Esplin, B. L. et al. Chronic exposure to a TLR ligand injures hematopoietic stem cells. J. Immunol. 186, 5367–5375 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  23. 23.

    Liu, A. et al. Cutting edge: hematopoietic stem cell expansion and common lymphoid progenitor depletion require hematopoietic-derived, cell-autonomous TLR4 in a model of chronic endotoxin. J. Immunol. 195, 2524–2528 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  24. 24.

    Chavakis, T., Mitroulis, I. & Hajishengallis, G. Hematopoietic progenitor cells as integrative hubs for adaptation to and fine-tuning of inflammation. Nat. Immunol. 20, 802–811 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  25. 25.

    Waterstrat, A., Liang, Y., Swiderski, C. F., Shelton, B. J. & Van Zant, G. Congenic interval of CD45/Ly-5 congenic mice contains multiple genes that may influence hematopoietic stem cell engraftment. Blood 115, 408–417 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  26. 26.

    Fang, J. et al. Myeloid malignancies with chromosome 5q deletions acquire a dependency on an intrachromosomal NF-κB gene network. Cell Rep. 8, 1328–1338 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. 27.

    Sanz, C., Richard, C., Prosper, F. & Fernandez-Luna, J. L. Nuclear factor κ B is activated in myelodysplastic bone marrow cells. Haematologica 87, 1005–1006 (2002).

    CAS  PubMed  Google Scholar 

  28. 28.

    Wei, Y. et al. Global H3K4me3 genome mapping reveals alterations of innate immunity signaling and overexpression of JMJD3 in human myelodysplastic syndrome CD34+ cells. Leukemia 27, 2177–2186 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  29. 29.

    Magness, S. T. et al. In vivo pattern of lipopolysaccharide and anti-CD3-induced NF-κB activation using a novel gene-targeted enhanced GFP reporter gene mouse. J. Immunol. 173, 1561–1570 (2004).

    CAS  PubMed  Google Scholar 

  30. 30.

    Sun, S. C. The non-canonical NF-κB pathway in immunity and inflammation. Nat. Rev. Immunol. 17, 545–558 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  31. 31.

    Yamaguchi, N., Oyama, M., Kozuka-Hata, H. & Inoue, J. Involvement of A20 in the molecular switch that activates the non-canonical NF-κB pathway. Sci. Rep. 3, 2568 (2013).

    PubMed  PubMed Central  Google Scholar 

  32. 32.

    Wertz, I. E. et al. De-ubiquitination and ubiquitin ligase domains of A20 downregulate NF-κB signalling. Nature 430, 694–699 (2004).

    CAS  PubMed  Google Scholar 

  33. 33.

    Lee, E. G. et al. Failure to regulate TNF-induced NF-κB and cell death responses in A20-deficient mice. Science 289, 2350–2354 (2000).

    CAS  PubMed  PubMed Central  Google Scholar 

  34. 34.

    Bird, L. TET2: the terminator. Nat. Rev. Immunol. 15, 598 (2015).

    CAS  PubMed  Google Scholar 

  35. 35.

    Zhang, Q. et al. Tet2 is required to resolve inflammation by recruiting Hdac2 to specifically repress IL-6. Nature. 525, 389–393 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  36. 36.

    Cai, Z. et al. Inhibition of inflammatory signaling in Tet2 mutant preleukemic cells mitigates stress-induced abnormalities and clonal hematopoiesis. Cell Stem Cell 23, 833–849 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  37. 37.

    Rhyasen, G. W. et al. An MDS xenograft model utilizing a patient-derived cell line. Leukemia 28, 1142–1145 (2014).

    CAS  PubMed  Google Scholar 

  38. 38.

    Kumar, M. S. et al. Coordinate loss of a microRNA and protein-coding gene cooperate in the pathogenesis of 5q-syndrome. Blood 118, 4666–4673 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  39. 39.

    Nakagawa, M. M., Thummar, K., Mandelbaum, J., Pasqualucci, L. & Rathinam, C. V. Lack of the ubiquitin-editing enzyme A20 results in loss of hematopoietic stem cell quiescence. J. Exp. Med. 212, 203–216 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  40. 40.

    Cull, A. H., Snetsinger, B., Buckstein, R., Wells, R. A. & Rauh, M. J. Tet2 restrains inflammatory gene expression in macrophages. Exp. Hematol. 55, 56–70.e13 (2017).

    CAS  PubMed  Google Scholar 

  41. 41.

    Ma, S. et al. Epigenetic regulator CXXC5 recruits DNA demethylase Tet2 to regulate TLR7/9-elicited IFN response in pDCs. J. Exp. Med. 214, 1471–1491 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  42. 42.

    Leoni, C. et al. Dnmt3a restrains mast cell inflammatory responses. Proc. Natl Acad. Sci. USA 114, E1490–E1499 (2017).

    CAS  PubMed  Google Scholar 

  43. 43.

    Li, X. et al. Methyltransferase Dnmt3a upregulates HDAC9 to deacetylate the kinase TBK1 for activation of antiviral innate immunity. Nat. Immunol. 17, 806–815 (2016).

    CAS  PubMed  Google Scholar 

  44. 44.

    Lee, S. C. et al. Synthetic lethal and convergent biological effects of cancer-associated spliceosomal gene mutations. Cancer Cell 34, 225–241.e8 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  45. 45.

    Smith, M. A. et al. U2AF1 mutations induce oncogenic IRAK4 isoforms and activate innate immune pathways in myeloid malignancies. Nat. Cell Biol. 21, 640–650 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  46. 46.

    Pollyea, D. A. et al. Myelodysplastic syndrome-associated spliceosome gene mutations enhance innate immune signaling. Haematologica 104, e388–e392 (2019).

    PubMed  PubMed Central  Google Scholar 

  47. 47.

    Ulas, T. et al. S100-alarmin-induced innate immune programming protects newborn infants from sepsis. Nat. Immunol. 18, 622–632 (2017).

    CAS  PubMed  Google Scholar 

  48. 48.

    Shi, H. et al. Chemokine (C-X-C motif) ligand 1 and CXCL2 produced by tumor promote the generation of monocytic myeloid-derived suppressor cells. Cancer Sci. 109, 3826–3839 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  49. 49.

    Tavares, R. M. et al. The ubiquitin modifying enzyme A20 restricts B cell survival and prevents autoimmunity. Immunity 33, 181–191 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  50. 50.

    Fang, J. et al. A calcium- and calpain-dependent pathway determines the response to lenalidomide in myelodysplastic syndromes. Nat. Med. 22, 727–734 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  51. 51.

    Haeussler, M. et al. Evaluation of off-target and on-target scoring algorithms and integration into the guide RNA selection tool CRISPOR. Genome Biol. 17, 148 (2016).

    PubMed  PubMed Central  Google Scholar 

  52. 52.

    Choi, K. & Ratner, N. iGEAK: an interactive gene expression analysis kit for seamless workflow using the R/shiny platform. BMC Genomics 20, 177 (2019).

    PubMed  PubMed Central  Google Scholar 

  53. 53.

    Pellagatti, A. et al. Deregulated gene expression pathways in myelodysplastic syndrome hematopoietic stem cells. Leukemia 24, 756–764 (2010).

    CAS  PubMed  Google Scholar 

  54. 54.

    Gerstung, M. et al. Combining gene mutation with gene expression data improves outcome prediction in myelodysplastic syndromes. Nat. Commun. 6, 5901 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  55. 55.

    Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA 102, 15545–15550 (2005).

    CAS  PubMed  Google Scholar 

Download references

Acknowledgements

This work was supported in parts by the National Institutes of Health (grant nos. R35HL135787, R01DK102759, R01DK113639 to D.T.S.), Cancer Free Kids (D.T.S.), Cincinnati Children’s Hospital Research Foundation (D.T.S.), The Uehara Memorial Foundation (T.M.), The Waksman Foundation of Japan (T.M.), The Mochida Memorial Foundation for Medical and Pharmaceutical Research (T.M.), Japan Society for the Promotion of Science (T.M.) and Ohio State University Comprehensive Cancer Center (T.M.). T.M. is a Leukemia and Lymphoma Society Special Fellow. D.T.S. is a Leukemia and Lymphoma Society Scholar. We thank J. Bailey and V. Summey for assistance with transplantations (Comprehensive Mouse and Cancer Core at CCHMC), and M.-D. Filippi, D. Lucas, D. Reynaud and the Starczynowski laboratory for insightful suggestions and feedback.

Author information

Affiliations

Authors

Contributions

T.M. and D.T.S. contributed to study conception and design. T.M., C.S.W., K.C., K.H. and M.S. acquired, analyzed and interpreted data. Z.G. and G.G.-M. provided samples. A.M. and Y.Z. provided reagents. T.M. and D.T.S. wrote and revised the manuscript.

Corresponding author

Correspondence to Daniel T. Starczynowski.

Ethics declarations

Competing interests

D.T.S. serves on the scientific advisory board at Kurome Therapeutics. All other authors declare no competing interests.

Additional information

Peer review information Ioana Visan was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Inflammatory and immune pathway activation in MDS cells.

a, Survival analysis of MDS patients based on TRAF6 expression (probe: 227264_at) in CD34+ cells (GSE58831). Patients were stratified based on TRAF6 mRNA expression (top 20%, n = 28; bottom 20%, n = 26). Log-rank (Mantel-Cox) test. b, Overview of experimental design to examine inflammatory states in MDS and human TLR-TRAF6 primed HSPC. c, Human miR-146a deficient (miR146a-/-) and control (WT) CD34+ BM cells generated from healthy CD34+ BM using CRISPR-Cas9 gene editing or Vav-TRAF6 and WT LSK BM cells were stimulated in vitro for 90 min with 1 µg/mL of LPS (or PBS) (n = 3 each per group) and then examined for differential gene expression by RNA-sequencing. The inflammatory state for each group was determined using the GSEA. NES, normalized enrichment score. d, Expression of miR-146a in miR-146a deficient (miR146a-/-) and control (sg-CTL) CD34+ BM cells gene edited using CRISPR-Cas9. Results are presented as mean ± s.e.m. for n = 3 technical replicate samples. e, Immunoblot analysis of TRAF6 and IRAK1, two miR-146a targets, in miR146a-/- and control (sg-CTL) CD34+ BM cells gene edited using CRISPR-Cas9. Shown is an immunoblot from a single biological replicate.

Extended Data Fig. 2 Evaluation of Vav-TRAF6-YFP and WT-YFP versus WT BM cell competition with LD-LPS.

a, Overview of experimental design to directly measure hematopoietic cell competition in the presence of low-dose chronic inflammation. Vav-TRAF6 CD45.2 BM cells (co-expressing a YFP transgene referred to as Vav-TRAF6-YFP) and WT CD45.2 BM cells were transplanted in equal proportions into lethally irradiated recipient mice. Two months after transplantation, chimeric mice were treated with LD-LPS (1 µg/g) or vehicle twice a week for 30 days and then examined for hematopoietic contribution of Vav-TRAF6-YFP and WT cells in the PB and BM. After the last LPS treatment, BM cells were serially transplanted into lethally irradiated recipient mice. b, Overview of experimental design to directly measure hematopoietic cell competition in the presence of low-dose chronic inflammation. Wild-type (WT) CD45.2 BM cells (co-expressing a YFP transgene) and WT CD45.2 BM cells were transplanted in equal proportions into lethally irradiated recipient mice. Two months after transplantation, chimeric mice were treated with LD-LPS (1 µg/g) or vehicle twice a week for 4 weeks and then examined for hematopoietic contribution of WT-YFP and WT cells in the BM. c, Representative flow cytometric profiles and gating strategy of YFP+ (WT-YFP) cells in the BM of chimeric mice after LPS or vehicle (PBS) treatment. d, The proportion of YFP+ (WT-YFP) cells in LSK populations 4 weeks after treatment with LPS or vehicle (PBS). Data represent the mean ± s.e.m., n = 6 mice per group.

Extended Data Fig. 3 Overexpression of TRAF6 alters the response of hematopoietic progenitor cells to LD-LPS.

a, Overview of experimental design to examine the long-term effects of low-dose chronic inflammation on hematopoiesis. Vav-TRAF6 (T6) CD45.2 BM cells or WT CD45.2 BM cells were isolated from mice treated with LD-LPS (1 µg/g) or vehicle twice a week for 30 days and then transplanted with a ratio of 10:1 of CD45.1 competitor BM cells into lethally irradiated recipient mice. Three months after transplantation, BM cells were serially transplanted into lethally irradiated recipient mice. b, The proportion of donor-derived CD45.2+ cells in MPP2 (Flk2-CD150+CD48+LSK), MPP3 (Flk2-CD150-CD48+LSK), and MPP4 (Flk2+CD150-CD48+LSK) after tertiary transplantation. Results are presented as mean ± s.e.m. for n = 3 mice per group. Statistical analysis was performed by a two-tailed Student’s t-test. *, P < 0.05. Source data

Extended Data Fig. 4 TLR-TRAF6 primed HSPC exhibit expression of non-canonical NF-κB gene signatures.

a, Normalized enrichment scores (NES) and P value of gene signatures established from WT and Vav-TRAF6 LSK stimulated with LPS evaluated in constitutively active (ca) NIK expressing LSK (GSE88949). b, GSEA plots established from caNIK LSK were evaluated in miR-146a deficient (miR146a-/-) CD34+ BM cells gene edited using CRISPR-Cas9 and then stimulated with 1 µg/mL of LPS (or PBS) for 90 min. The gene expression profiles are relative to unstimulated miR-146a-/- CD34+ BM and control (sg-CTL) (+/− LPS). (c) Capillary immunoassay of CD34+ cells isolated from healthy controls or MDS BM visualized by chemiluminescence using ProteinSimple. Shown is an immunoassay from a single biological replicate.

Extended Data Fig. 5 TET2 deficiency in hematopoietic cells results in increased myeloid-biased hematopoiesis without affecting the proportions of HSC after LD-LPS.

a, Overview of experimental design to examine the effects of low-dose chronic inflammation on hematopoiesis. Tet2f/f VavCre CD45.2 BM cells (Tet2-/-) or Tet2f/f (WT) CD45.2 BM cells were isolated from mice treated with LD-LPS (1 µg/g) or vehicle twice a week for 4 weeks and then transplanted into lethally irradiated recipient mice (along with CD45.1 competitor BM cells). One month after transplantation, PB and BM cells were evaluated by flow cytometry. b, The proportion of donor-derived CD45.2+ myeloid (CD11b+) and lymphoid (B220+ and CD3+) cells in the PB (n = 6 mice per group). * P = 0.02. c, The proportion of donor-derived CD45.2+ LSK and LT-HSC in the BM of mice after treatment with LD-LPS. Results are presented as mean ± s.e.m., n = 6 for all groups; n = 3 for WT LPS treated group. * P = 0.03. Statistical analysis in b was performed by a two-tailed Student’s t-test. Statistical analysis in c was performed by a one-tailed Student’s t-test. Source data

Extended Data Fig. 6 Generation of Traf6- and Tet2-deficient mice.

Genotyping analysis of Tet2-/- VavCre and Traf6-/- Tet2-/- VavCre mice.

Extended Data Fig. 7 Generation of Vav-TRAF6 and A20-deficient mice.

Genotyping analysis of Vav-TRAF6 RosaCreER and A20-/- Vav-TRAF6 RosaCreER mice. A20 floxed allele recombination is shown after Tamoxifen treatment.

Extended Data Fig. 8 A20 knockdown impairs MDSL and THP1 cell function.

a, Immunoblotting of MDSL cells expressing independent shRNAs targeting A20 (shA20) or non-targeting shRNA (shControl). Shown is an immunoblot from a single biological replicate. b, Colony forming potential of MDSL cells expressing shRNAs targeting A20 (shA20) or non-targeting shRNA (shControl) in methylcellulose. Results are presented as mean ± s.e.m., for n = 3 independent biological replicates. * P = 0.006, ** P = 0.0004. c, Immunoblotting of THP1 cells expressing an shRNA targeting A20 (shA20) or non-targeting shRNA (shControl). Shown is an immunoblot from a single biological replicate. d, Colony forming potential of THP1 cells expressing shRNAs targeting A20 or non-targeting shRNA (shControl) in methylcellulose. Results are presented as mean ± s.e.m., for n = 3 independent biological replicates. *, P = 0.0001. Statistical analysis in b,d was performed by a two-tailed Student’s t-test. Source data

Supplementary information

Reporting Summary

Supplementary Tables

Supplementary Tables 1–11.

Source data

Source Data Fig. 2

Statistical Source Data for Fig. 2

Source Data Fig. 3

Statistical Source Data for Fig. 3

Source Data Fig. 4

Statistical Source Data for Fig. 4

Source Data Fig. 5

Statistical Source Data for Fig. 5

Source Data Fig. 6

Statistical Source Data for Fig. 6

Source Data Fig. 7

Statistical Source Data for Fig. 7

Source Data Extended Data Fig. 3

Statistical Source Data for ED Fig. 3

Source Data Extended Data Fig. 5

Statistical Source Data for ED Fig. 5

Source Data Extended Data Fig. 8

Statistical Source Data for ED Fig. 8

Source Data Fig. 4

Unprocessed western blots

Source Data Fig. 5

Unprocessed western blots

Source Data Fig. 6

Unprocessed western blots

Source Data Fig. 7

Unprocessed western blots

Source Data Extended Data Fig. 1

Unprocessed western blots

Source Data Extended Data Fig. 8

Unprocessed western blots

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Muto, T., Walker, C.S., Choi, K. et al. Adaptive response to inflammation contributes to sustained myelopoiesis and confers a competitive advantage in myelodysplastic syndrome HSCs. Nat Immunol 21, 535–545 (2020). https://doi.org/10.1038/s41590-020-0663-z

Download citation

Further reading

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing