Letter | Published:

Diverse and heritable lineage imprinting of early haematopoietic progenitors

Nature volume 496, pages 229232 (11 April 2013) | Download Citation

Abstract

Haematopoietic stem cells (HSCs) and their subsequent progenitors produce blood cells, but the precise nature and kinetics of this production is a contentious issue. In one model, lymphoid and myeloid production branch after the lymphoid-primed multipotent progenitor (LMPP)1, with both branches subsequently producing dendritic cells2. However, this model is based mainly on in vitro clonal assays and population-based tracking in vivo, which could miss in vivo single-cell complexity3,4,5,6,7. Here we avoid these issues by using a new quantitative version of ‘cellular barcoding’8,9,10 to trace the in vivo fate of hundreds of LMPPs and HSCs at the single-cell level. These data demonstrate that LMPPs are highly heterogeneous in the cell types that they produce, separating into combinations of lymphoid-, myeloid- and dendritic-cell-biased producers. Conversely, although we observe a known lineage bias of some HSCs11,12,13,14, most cellular output is derived from a small number of HSCs that each generates all cell types. Crucially, in vivo analysis of the output of sibling cells derived from single LMPPs shows that they often share a similar fate, suggesting that the fate of these progenitors was imprinted. Furthermore, as this imprinting is also observed for dendritic-cell-biased LMPPs, dendritic cells may be considered a distinct lineage on the basis of separate ancestry. These data suggest a ‘graded commitment’ model of haematopoiesis, in which heritable and diverse lineage imprinting occurs earlier than previously thought.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

References

  1. 1.

    et al. Identification of Flt3+ lympho-myeloid stem cells lacking erythro-megakaryocytic potential a revised road map for adult blood lineage commitment. Cell 121, 295–306 (2005)

  2. 2.

    & Steady-state and inflammatory dendritic cell development. Nature Rev. Immunol. 7, 19–30 (2007)

  3. 3.

    et al. Reciprocal activation of GATA-1 and PU.1 marks initial specification of hematopoietic stem cells into myeloerythroid and myelolymphoid lineages. Cell Stem Cell 1, 416–427 (2007)

  4. 4.

    , , , & Transcription from the RAG1 locus marks the earliest lymphocyte progenitors in bone marrow. Immunity 17, 117–130 (2002)

  5. 5.

    Lineage promiscuity and plasticity in hematopoietic development. Ann. NY Acad. Sci. 1044, 125–131 (2005)

  6. 6.

    et al. Development of plasmacytoid and conventional dendritic cell subtypes from single precursor cells derived in vitro and in vivo. Nature Immunol. 8, 1217–1226 (2007)

  7. 7.

    et al. Molecular evidence for hierarchical transcriptional lineage priming in fetal and adult stem cells and multipotent progenitors. Immunity 26, 407–419 (2007)

  8. 8.

    et al. Dissecting T cell lineage relationships by cellular barcoding. J. Exp. Med. 205, 2309–2318 (2008)

  9. 9.

    , & Mapping the life histories of T cells. Nature Rev. Immunol. 10, 621–631 (2010)

  10. 10.

    et al. Recruitment of antigen-specific CD8+ T cells in response to infection is markedly efficient. Science 325, 1265–1269 (2009)

  11. 11.

    et al. Long-term propagation of distinct hematopoietic differentiation programs in vivo. Cell Stem Cell 1, 218–229 (2007)

  12. 12.

    What we have learned from retroviral marking of hematopoietic stem cells. Curr. Top. Microbiol. Immunol. 177, 59–71 (1992)

  13. 13.

    & The GOD of hematopoietic stem cells: a clonal diversity model of the stem cell compartment. Cell Cycle 5, 394–398 (2006)

  14. 14.

    , , & Distinct hematopoietic stem cell subtypes are differentially regulated by TGF-beta1. Cell Stem Cell 6, 265–278 (2010)

  15. 15.

    et al. Cellular barcoding tool for clonal analysis in the hematopoietic system. Blood 115, 2610–2618 (2010)

  16. 16.

    , , & Tracking single hematopoietic stem cells in vivo using high-throughput sequencing in conjunction with viral genetic barcoding. Nature Biotechnol. 29, 928–933 (2011)

  17. 17.

    , , & Long-term lymphohematopoietic reconstitution by a single CD34-low/negative hematopoietic stem cell. Science 273, 242–245 (1996)

  18. 18.

    et al. The hematopoietic stem compartment consists of a limited number of discrete stem cell subsets. Blood 107, 2311–2316 (2006)

  19. 19.

    , , , & New evidence supporting megakaryocyte–erythrocyte potential of flk2/flt3+ multipotent hematopoietic progenitors. Cell 126, 415–426 (2006)

  20. 20.

    et al. SLAM family receptors distinguish hematopoietic stem and progenitor cells and reveal endothelial niches for stem cells. Cell 121, 1109–1121 (2005)

  21. 21.

    et al. Multilineage gene expression precedes commitment in the hemopoietic system. Genes Dev. 11, 774–785 (1997)

  22. 22.

    et al. Myeloid or lymphoid promiscuity as a critical step in hematopoietic lineage commitment. Dev. Cell 3, 137–147 (2002)

  23. 23.

    Demystifying the development of dendritic cell subtypes, a little. Immunol. Cell Biol. 86, 439–452 (2008)

  24. 24.

    Dendritic Cell Development, Lineage Issues and Haematopoiesis at the Single Cell Level. 79–120 (Nova Press, 2009)

  25. 25.

    , & Evolving views on the genealogy of B cells. Nature Rev. Immunol. 8, 95–106 (2008)

  26. 26.

    , & Models of haematopoiesis: seeing the wood for the trees. Nature Rev. Immunol. 9, 293–300 (2009)

  27. 27.

    et al. Novel insights into the relationships between dendritic cell subsets in human and mouse revealed by genome-wide expression profiling. Genome Biol. 9, R17 (2008)

  28. 28.

    et al. Genetic complementation of human muscle cells via directed stem cell fusion. Mol. Ther. 16, 741–748 (2008)

  29. 29.

    , & Survival surgery: removal of the spleen or thymus. Curr. Protoc. Immunol. 2, 1.10.1–1.10.11 (2001)

  30. 30.

    et al. TM4 microarray software suite. Methods Enzymol. 411, 134–193 (2006)

Download references

Acknowledgements

We thank G. Filion, U. Braunschweig, L. Pagie, M. Hauptmann, P. Lio, R. van der Wath and the NKI Genomics Facility for computational assistance; J. van Heijst, J. Rohr and J. Urbanus for useful discussions; http://www.josharris.com for illustrations in Fig. 1a and Supplementary Fig. 1; NKI cytometry and animal facilities; D. Leone, Z. Ping and M. Lodder for technical assistance; and P. Hodgkin, K. Duffy and J. Coquet for critical reading of the manuscript. This work was supported by ERC grant LIFE-HIS-T and HFSP grant RGP0060/2012, S.H.N. was supported by the National Health and Medical Research Council Australia, Marie Curie Incoming International FP6 Fellowship, and the Leukemia and Lymphoma Society; and L.P. was supported by a Marie Curie Intra European FP7 Fellowship and the Bettencourt Schueller Fondation.

Author information

Author notes

    • Shalin H. Naik

    Present address: Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, Victoria 3052, Australia.

Affiliations

  1. Division of Immunology, The Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands

    • Shalin H. Naik
    • , Leïla Perié
    • , Erwin Swart
    • , Carmen Gerlach
    • , Nienke van Rooij
    •  & Ton N. Schumacher
  2. Theoretical Biology and Bioinformatics, Utrecht University, 3584 CH Utrecht, The Netherlands

    • Leïla Perié
    •  & Rob J. de Boer

Authors

  1. Search for Shalin H. Naik in:

  2. Search for Leïla Perié in:

  3. Search for Erwin Swart in:

  4. Search for Carmen Gerlach in:

  5. Search for Nienke van Rooij in:

  6. Search for Rob J. de Boer in:

  7. Search for Ton N. Schumacher in:

Contributions

S.H.N. conceived, developed, executed and analysed experiments; L.P. developed and carried out data analysis, advised by R.J.d.B.; E.S., C.G. and N.v.R. contributed to lineage-tracing technology development. T.N.S. conceived the approach and advised on data analysis and interpretation. All authors discussed results and wrote the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Shalin H. Naik or Ton N. Schumacher.

Supplementary information

PDF files

  1. 1.

    Supplementary Information

    This file contains Supplementary Methods, Supplementary References, Supplementary Tables 1-3 and Supplementary Figures 1-15.

Videos

  1. 1.

    3D Principal Component Analysis of LMPPs by the first 3 principal components

    PCA of the LMPPs was used to identify groups of progenitors, and resulted in 3 distinct groups with some 'intermediate' LMPPs between them. Backgating of LMPPs (i.e. a manual selection of LMPPs by their 3-dimensional coordinates on the principal components, and visualization of their corresponding LMPPs in the clustered heatmap) was done using in-software tools for Supplementary Fig. 7.

About this article

Publication history

Received

Accepted

Published

DOI

https://doi.org/10.1038/nature12013

Further reading

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.