Dynamic regulation of hypoxia-inducible factor-1α activity is essential for normal B cell development


B lymphocyte development and selection are central to adaptive immunity and self-tolerance. These processes require B cell receptor (BCR) signaling and occur in bone marrow, an environment with variable hypoxia, but whether hypoxia-inducible factor (HIF) is involved is unknown. We show that HIF activity is high in human and murine bone marrow pro-B and pre-B cells and decreases at the immature B cell stage. This stage-specific HIF suppression is required for normal B cell development because genetic activation of HIF-1α in murine B cells led to reduced repertoire diversity, decreased BCR editing and developmental arrest of immature B cells, resulting in reduced peripheral B cell numbers. HIF-1α activation lowered surface BCR, CD19 and B cell–activating factor receptor and increased expression of proapoptotic BIM. BIM deletion rescued the developmental block. Administration of a HIF activator in clinical use markedly reduced bone marrow and transitional B cells, which has therapeutic implications. Together, our work demonstrates that dynamic regulation of HIF-1α is essential for normal B cell development.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Fig. 1: Disruption of dynamic HIF regulation leads to severe peripheral B cell lymphopenia.
Fig. 2: Hif1a deletion in Vhl−/−Mb1-cre mice rescues peripheral B cell loss, indicating a HIF-1α-dependent effect.
Fig. 3: Regulated HIF-1α activity is required for the generation and diversification of the pre-immune B cell repertoire.
Fig. 4: Defects in development linked to BCR signaling.
Fig. 5: Developmental block linked to BIM-dependent survival.
Fig. 6: Regulated HIF-1α activity is required for BCR editing.
Fig. 7: Developing B cells are reduced in daprodustat-treated mice.

Data availability

Data are available from the corresponding author upon request. Uncropped immunoblots for Supplementary Figs. 3a–c and 8h are provided as Supplementary Data. The BCR-seq data generated in the present study are available at the SRA database (https://www.ncbi.nlm.nih.gov/sra), BioProject accession codes PRJNA574931, PRJNA574906 and PRJNA574628. The RNA-seq and microarray datasets generated in this study are available at the GEO database (https://www.ncbi.nlm.nih.gov/geo/), GEO accession codes GSE129513 and GSE152960. Data in the present study that were obtained from publically available sources can be accessed at: (1) Tabula Muris scRNA-seq data (https://tabula-muris.ds.czbiohub.org); data names: 10X_P7_2 and 10X_P7_3; and (2) Human Cell Atlas scRNA-seq data (https://data.humancellatlas.org/explore/projects/cc95ff89-2e68-4a08-a234-480eca21ce79); data name: MantonBM1.

Code availability

Customized scripts for the analysis of BCR repertoire differences are available at: Immune_receptor_NETWORK-GENERATION (https://github.com/rbr1/Immune_receptor_NETWORK-GENERATION).


  1. 1.

    Nemazee, D. Mechanisms of central tolerance for B cells. Nat. Rev. Immunol. 17, 281–294 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  2. 2.

    Sun, A. et al. VH replacement in primary immunoglobulin repertoire diversification. Proc. Natl Acad. Sci. USA 112, E458–E466 (2015).

    CAS  PubMed  Google Scholar 

  3. 3.

    Kouskoff, V., Lacaud, G., Pape, K., Retter, M. & Nemazee, D. B cell receptor expression level determines the fate of developing B lymphocytes: receptor editing versus selection. Proc. Natl Acad. Sci. USA 97, 7435–7439 (2000).

    CAS  PubMed  Google Scholar 

  4. 4.

    Nemazee, D. A. & Bürki, K. Clonal deletion of B lymphocytes in a transgenic mouse bearing anti-MHC class I antibody genes. Nature 337, 562–566 (1989).

    CAS  PubMed  Google Scholar 

  5. 5.

    Tussiwand, R., Rauch, M., Fluck, L. A. & Rolink, A. G. BAFF-R expression correlates with positive selection of immature B cells. Eur. J. Immunol. 42, 206–216 (2012).

    CAS  PubMed  Google Scholar 

  6. 6.

    Loder, F. et al. B cell development in the spleen takes place in discrete steps and is determined by the quality of B cell receptor-derived signals. J. Exp. Med. 190, 75–89 (1999).

    CAS  PubMed  PubMed Central  Google Scholar 

  7. 7.

    Abbott, R. K. et al. Germinal center hypoxia potentiates immunoglobulin class switch recombination. J. Immunol. 197, 4014–4020 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  8. 8.

    Cho, S. H. et al. Germinal centre hypoxia and regulation of antibody qualities by a hypoxia response system. Nature 537, 234–238 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  9. 9.

    Meng, X. Y. et al. Hypoxia-inducible factor-1α is a critical transcription factor for IL-10-producing B cells in autoimmune disease. Nat. Commun. 9, 251 (2018).

    PubMed  PubMed Central  Google Scholar 

  10. 10.

    Grüneboom, A. et al. A network of trans-cortical capillaries as mainstay for blood circulation in long bones. Nat. Metab. 1, 236–250 (2019).

    PubMed  PubMed Central  Google Scholar 

  11. 11.

    Spencer, J. A. et al. Direct measurement of local oxygen concentration in the bone marrow of live animals. Nature 508, 269–273 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  12. 12.

    Maxwell, P. H. et al. The tumour suppressor protein VHL targets hypoxia-inducible factors for oxygen-dependent proteolysis. Nature 399, 271–275 (1999).

    CAS  PubMed  PubMed Central  Google Scholar 

  13. 13.

    Jaakkola, P. et al. Targeting of HIF-α to the von Hippel–Lindau ubiquitylation complex by O2-regulated prolyl hydroxylation. Science 292, 468–472 (2001).

    CAS  PubMed  Google Scholar 

  14. 14.

    Haase, V. H., Glickman, J. N., Socolovsky, M. & Jaenisch, R. Vascular tumors in livers with targeted inactivation of the von Hippel–Lindau tumor suppressor. Proc. Natl Acad. Sci. USA 98, 1583–1588 (2001).

    CAS  PubMed  Google Scholar 

  15. 15.

    Hobeika, E. et al. Testing gene function early in the B cell lineage in mb1-cre mice. Proc. Natl Acad. Sci. USA 103, 13789–13794 (2006).

    CAS  PubMed  Google Scholar 

  16. 16.

    Hardy, R. R. & Hayakawa, K. B cell development pathways. Annu. Rev. Immunol. 19, 595–621 (2001).

    CAS  PubMed  Google Scholar 

  17. 17.

    Gaspar, H. B. & Conley, M. E. Early B cell defects. Clin. Exp. Immunol. 119, 383–389 (2000).

    CAS  PubMed  PubMed Central  Google Scholar 

  18. 18.

    Kreuzaler, M. et al. Soluble BAFF levels inversely correlate with peripheral B cell numbers and the expression of BAFF receptors. J. Immunol. 188, 497–503 (2012).

    CAS  PubMed  Google Scholar 

  19. 19.

    Ryan, H. E. et al. Hypoxia-inducible factor-1α is a positive factor in solid tumor growth. Cancer Res. 60, 4010–4015 (2000).

    CAS  PubMed  Google Scholar 

  20. 20.

    Gruber, M. et al. Acute postnatal ablation of Hif-2α results in anemia. Proc. Natl Acad. Sci. USA 104, 2301–2306 (2007).

    CAS  PubMed  Google Scholar 

  21. 21.

    Ngo, V. N., Cornall, R. J. & Cyster, J. G. Splenic T zone development is B cell dependent. J. Exp. Med. 194, 1649–1660 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  22. 22.

    Bashford-Rogers, R. J. M. et al. Network properties derived from deep sequencing of human B-cell receptor repertoires delineate B-cell populations. Genome Res. 23, 1874–1884 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  23. 23.

    Bashford-Rogers, R. J. M. et al. Eye on the B-ALL: B-cell receptor repertoires reveal persistence of numerous B-lymphoblastic leukemia subclones from diagnosis to relapse. Leukemia 30, 2312–2321 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  24. 24.

    Bristow, R. G. & Hill, R. P. Hypoxia, DNA repair and genetic instability. Nat. Rev. Cancer 8, 180–192 (2008).

    CAS  PubMed  Google Scholar 

  25. 25.

    Goodnow, C. C. et al. Altered immunoglobulin expression and functional silencing of self-reactive B lymphocytes in transgenic mice. Nature 334, 676–682 (1988).

    CAS  PubMed  Google Scholar 

  26. 26.

    Aiba, Y., Kameyama, M., Yamazaki, T., Tedder, T. F. & Kurosaki, T. Regulation of B-cell development by BCAP and CD19 through their binding to phosphoinositide 3-kinase. Blood 111, 1497–1503 (2008).

    CAS  PubMed  Google Scholar 

  27. 27.

    Amin, R. H. & Schlissel, M. S. Foxo1 directly regulates the transcription of recombination-activating genes during B cell development. Nat. Immunol. 9, 613–622 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  28. 28.

    Yang, Y. et al. Acetylation of FoxO1 activates Bim expression to induce apoptosis in response to histone deacetylase inhibitor depsipeptide treatment. Neoplasia 11, 313–315 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  29. 29.

    Otero, D. C. & Rickert, R. C. CD19 function in early and late B cell development. II. CD19 facilitates pro-B/pre-B transit. J. Immunol. 171, 5921–5930 (2003).

    CAS  PubMed  Google Scholar 

  30. 30.

    Bouillet, P. et al. Proapoptotic Bcl-2 relative Bim required for certain apoptotic responses, leukocyte homeostasis, and to preclude autoimmunity. Science 286, 1735–1738 (1999).

    CAS  PubMed  Google Scholar 

  31. 31.

    Kojima, H. et al. Abnormal B lymphocyte development and autoimmunity in hypoxia-inducible factor 1α-deficient chimeric mice. Proc. Natl Acad. Sci. USA 99, 2170–2174 (2002).

    CAS  PubMed  Google Scholar 

  32. 32.

    Vela, J. L., Ait-Azzouzene, D., Duong, B. H., Ota, T. & Nemazee, D. Rearrangement of mouse immunoglobulin kappa deleting element recombining sequence promotes immune tolerance and lambda B cell production. Immunity 28, 161–170 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  33. 33.

    Maxwell, P. H. & Eckardt, K. U. HIF prolyl hydroxylase inhibitors for the treatment of renal anaemia and beyond. Nat. Rev. Nephrol. 12, 157–168 (2016).

    CAS  PubMed  Google Scholar 

  34. 34.

    Cornall, R. J. et al. Polygenic autoimmune traits: Lyn, CD22, and SHP-1 are limiting elements of a biochemical pathway regulating BCR signaling and selection. Immunity 8, 497–508 (1998).

    CAS  PubMed  Google Scholar 

  35. 35.

    Christodoulou, C. et al. Live-animal imaging of native haematopoietic stem and progenitor cells. Nature 578, 278–283 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  36. 36.

    Kojima, H. et al. Differentiation stage-specific requirement in hypoxia-inducible factor-1α-regulated glycolytic pathway during murine B cell development in bone marrow. J. Immunol. 184, 154–163 (2010).

    CAS  PubMed  Google Scholar 

  37. 37.

    Wolock, S. L., Lopez, R. & Klein, A. M. Scrublet: computational identification of cell doublets in single-cell transcriptomic data. Cell Syst. 8, 281–291 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  38. 38.

    Wolf, F. A., Angerer, P. & Theis, F. J. SCANPY: large-scale single-cell gene expression data analysis. Genome Biol. 19, 15 (2018).

    PubMed  PubMed Central  Google Scholar 

  39. 39.

    Wolf, F. A. et al. PAGA: graph abstraction reconciles clustering with trajectory inference through a topology preserving map of single cells. Genome Biol. 20, 59 (2019).

    PubMed  PubMed Central  Google Scholar 

  40. 40.

    Schaum, N. et al. Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris. Nature 562, 367–372 (2018).

    PubMed Central  Google Scholar 

  41. 41.

    Street, K. et al. Slingshot: cell lineage and pseudotime inference for single-cell transcriptomics. BMC Genomics 19, 477 (2018).

    PubMed  PubMed Central  Google Scholar 

  42. 42.

    Young, M. D. et al. Single-cell transcriptomes from human kidneys reveal the cellular identity of renal tumors. Science 361, 594–599 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  43. 43.

    Tirosh, I. et al. Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq. Science 352, 189–196 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  44. 44.

    Kitamura, D., Roes, J., Kuhn, R. & Rajewsky, K. A B-cell-deficient mouse by targeted disruption of the membrane exon of the immunoglobulin μ chain gene. Nature 350, 423–426 (1991).

    CAS  PubMed  Google Scholar 

  45. 45.

    Janowska-Wieczorek, A. et al. Platelet-derived microparticles bind to hematopoietic stem/progenitor cells and enhance their engraftment. Blood 98, 3143–3149 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  46. 46.

    Watson, S. J. et al. Viral population analysis and minority-variant detection using short read next-generation sequencing. Phil. Trans. R. Soc. B Biol. Sci. 368, 20120205 (2013).

    Google Scholar 

  47. 47.

    Lefranc, M. P. IMGT unique numbering for the variable (V), constant (C), and groove (G) domains of IG, TR, MH, IgSF, and MhSF. Cold Spring Harb. Protoc. 2011, 633–642 (2011).

    PubMed  Google Scholar 

  48. 48.

    Altschul, S. F., Gish, W., Miller, W., Myers, E. W. & Lipman, D. J. Basic local alignment search tool. J. Mol. Biol. 215, 403–410 (1990).

    CAS  Google Scholar 

  49. 49.

    Kim, D., Landmead, B. & Salzberg, S. L. HISAT: a fast spliced aligner with low memory requirements. Nat. Methods 12, 357–360 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  50. 50.

    Wang, L., Wang, S. & Li, W. RSeQC: quality control of RNA-seq experiments. Bioinformatics 28, 2184–2185 (2012).

    CAS  PubMed  Google Scholar 

  51. 51.

    Liao, Y., Smyth, G. K. & Shi, W. The Subread aligner: fast, accurate and scalable read mapping by seed-and-vote. Nucleic Acids Res. 41, e108 (2013).

    PubMed  PubMed Central  Google Scholar 

  52. 52.

    Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).

    PubMed  PubMed Central  Google Scholar 

  53. 53.

    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  PubMed Central  Google Scholar 

Download references


This work was funded by the Wellcome Trust (no. 19710), a Cambridge National Institute for Health Research (NIHR) senior investigator award (no. NF-SI-0514-10122) and the Rosetrees Trust (no. G102721) to P.H.M., supporting N.B., V.J.B., A.P. and J.E.G.S. R.J.M.B.-R. was supported by the Wellcome Trust (no. WT106068AIA). B.J.S. was supported by a Wellcome Clinical PhD fellowship (216366/Z/19/Z). T.M.C. was supported by a MRC Clinic Research Training Fellowship (G0802266, ID 89800). S.S. was supported by a summer studentship award from the Lister Institute of Preventive Medicine. M.G.B.T. was supported by a NIHR grant (no. CL-2006-14-006). M.R.C. was supported by a Chan-Zuckerberg Initiative Human Cell Atlas technology development grant, a Versus Arthritis Cure Challenge Research Grant (no. 21777) and an NIHR Research Professorship (no. RP-2017-08-ST2-002). The CIMR core facilities were supported by a Wellcome Trust/MRC grant (no. 097922/Z/11/Z) and a Wellcome Trust strategic award (no. 100140). We thank R. Schulte, C. Cossetti, M. Maj and G. Grondys-Kotarba (CIMR Flow Cytometry Core Facility), and M. Gratian and M. Bowen (CIMR microscopy core facility) for their help and support; Y. Umrania for bioinformatics support; M. Reth (University of Freiburg, Germany) and M. Turner (Babraham Institute, Cambridge) for providing the Mb1-cre mice; and R. Johnson (Karolinska Institutet, Sweden) for providing Hif1a−/− mice. We thank J. Sale and M. Ashcroft for useful discussions and T. Wilson, K. Scott and D. Gale for experimental and technical support.

Author information




N.B. led the research design, performed experiments, analyzed data, maintained the mouse lines and wrote the paper. R.J.M.B.-R. performed BCR amplification, sequencing and analysis, and wrote the paper. V.J.B. performed experiments and bioinformatics analyses. A.P., J.E.G.S. and T.M.C. performed experiments and maintained the mouse lines. J.R.F., B.J.S., L.B., G.G. and E.P. performed bioinformatics analyses. M.D.−L. helped with experimental and technical design. A.I., S.S. and M.G.B.T. performed experiments. P.A.L. helped with the design of RNA-seq experiments. M.E., K.G.C.S. and B.J.P.H. contributed to research design. R.J.C. contributed to research and experimental design and provided guidance on manuscript preparation. M.R.C. contributed to research and experimental design and wrote the paper. P.H.M. supervised the project and wrote the paper.

Corresponding author

Correspondence to Natalie Burrows.

Ethics declarations

Competing interests

P.H.M. is a scientific founder and equity holder of ReOx and has received speaker honoraria from Fibrogen, which both aim to develop PHD inhibitors as therapies. R.J.M.B-R. is a cofounder and consultant for Alchemab Therapeutics Ltd, which maps antibody repertoires to develop therapeutics for patients with hard-to-treat diseases, and is a consultant for Imperial College London and VHSquared, which develops Vorabodies (oral domain antibodies). R.J.C. is a scientific founder and equity holder of MIROBIO, which aims to develop new therapies to treat a range of autoimmune diseases. All other authors declare no competing interests.

Additional information

Peer review information Peer reviewer reports are available. Zoltan Fehervari 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.

Supplementary information

Supplementary Information

Supplementary Figs. 1–9 and Supplementary Tables 1–3.

Reporting Summary

Peer Review Information

Supplementary Data 1

Uncropped immunoblots.

Supplementary Data 2

Uncropped immunoblots.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Burrows, N., Bashford-Rogers, R.J.M., Bhute, V.J. et al. Dynamic regulation of hypoxia-inducible factor-1α activity is essential for normal B cell development. Nat Immunol 21, 1408–1420 (2020). https://doi.org/10.1038/s41590-020-0772-8

Download citation


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