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CD8+ T cell diversification by asymmetric cell division

Nature Immunology volume 16, pages 891–893 (2015)Cite this article

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To the Editor:

How CD8+ T cells diversify into memory and effector subsets has been a fundamental question of immunology that has practical implications for adoptive T cell therapy. The ongoing controversy about proposed alternative models1,2 suggests that new kinds of data are needed to resolve this question3, and recent single cell–based in vivo approaches have provided steps in this direction4,5.

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Figure 1: Single cell–based analyses of CD8+ T cell diversification support a progressive model of memory and effector fate specification.

References

  1. Restifo, N.P. & Gattinoni, L. Curr. Opin. Immunol. 25, 556–563 (2013).

    Article  CAS  Google Scholar 

  2. Kaech, S.M. & Cui, W. Nat. Rev. Immunol. 12, 749–761 (2012).

    Article  CAS  Google Scholar 

  3. Buchholz, V.R., Gräf, P. & Busch, D.H. Front. Immunol. 4, 31 (2013).

    Article  Google Scholar 

  4. Buchholz, V.R. et al. Science 340, 630–635 (2013).

    Article  CAS  Google Scholar 

  5. Arsenio, J. et al. Nat. Immunol. 15, 365–372 (2014).

    Article  CAS  Google Scholar 

  6. Chang, J.T. et al. Science 315, 1687–1691 (2007).

    Article  CAS  Google Scholar 

  7. Sarkar, S. et al. J. Exp. Med. 205, 625–640 (2008).

    Article  CAS  Google Scholar 

  8. Kalia, V. et al. Immunity 32, 91–103 (2010).

    Article  CAS  Google Scholar 

  9. Trapnell, C. et al. Nat. Biotechnol. 32, 381–386 (2014).

    Article  CAS  Google Scholar 

  10. Newell, E.W., Sigal, N., Bendall, S.C., Nolan, G.P. & Davis, M.M. Immunity 36, 142–152 (2012).

    Article  CAS  Google Scholar 

  11. Hikono, H. et al. J. Exp. Med. 204, 1625–1636 (2007).

    Article  CAS  Google Scholar 

  12. Graef, P. et al. Immunity 41, 116–126 (2014).

    Article  CAS  Google Scholar 

  13. Simons, B. D. & Clevers, H. Cell 145, 851–862 (2011).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

Supported by the German Federal Ministry of Education and Research (BMBF; T-Sys, TIL-REP and SB-Epo) and by the Collaborative Research Centers SFB TR36 (TP-B10/13) and SFB 1054 (TP-B09).

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Authors and Affiliations

  1. Division of Theoretical Systems Biology, German Cancer Research Center (DKFZ), Heidelberg, Germany

    Michael Flossdorf, Jens Rössler & Thomas Höfer

  2. Bioquant Center, University of Heidelberg, Heidelberg, Germany

    Michael Flossdorf, Jens Rössler & Thomas Höfer

  3. Institute for Medical Microbiology, Immunology and Hygiene, Technische Universität München, Munich, Germany

    Veit R Buchholz & Dirk H Busch

  4. Focus Group Clinical Cell Processing and Purification, Institute for Advanced Study, Technische Universität München, Munich, Germany

    Dirk H Busch

  5. Clinical Cooperation Groups Antigen-specific Immunotherapy and Immune-Monitoring, Helmholtz Center Munich, Munich, Germany

    Dirk H Busch

  6. German Center for Infection Research (DZIF), Munich, Germany

    Dirk H Busch

Authors
  1. Michael Flossdorf
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  2. Jens Rössler
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  3. Veit R Buchholz
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  4. Dirk H Busch
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  5. Thomas Höfer
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Contributions

M.F. and J.R. performed mathematical analysis; V.R.B. and D.H.B. provided and analyzed experimental data on single cell–based fate mapping; T.H. supervised the mathematical analyses; all authors discussed the results and wrote the paper.

Corresponding authors

Correspondence to Dirk H Busch or Thomas Höfer.

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The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 A bifurcating model with strictly asymmetric cell divisions of the naïve cells fails to account for the data.

(a) Model scheme of a bifurcating model that assumes strictly asymmetric cell divisions of the naïve cells into one pre-TM and one TSLE cell (dA), followed by proliferation of pre-TM and TSLE cells with subset-specific rates (λ1 and λ2, respectively). (b) Comparison of experimental data derived from single-cell fate mapping (white bars and open dots; same data as in Fig. 1d) with the best-fit of the model depicted in a (blue bars or curve).

Supplementary Figure 2 Model selection criteria favor the progressive over the bifurcating model of T cell subset diversification.

(a) In the bifurcating model (corresponding to Fig. 1a), naïve T cells can divide symmetrically into either two pre-TM cells (dS1) or two TSLE cells (dS2), or divide asymmetrically and give rise to one cell of each of the two phenotypes (dA). The model allows for subset-specific proliferation rates (denoted λ1 for pre-TM and λ2 for TSLE cells). Best-fit values for the five rates of the bifurcating model: λ1=1.18 d−1, λ2=1.38 d−1, dS1=0.74 d−1, dS2=0, dA=0.20 d−1. (b) The progressive model (corresponding to Fig. 1b) assumes a linear diversification pathway with naïve T cells differentiating into pre-TM cells (d0) which in turn give rise to TSLE cells (d1). The nomenclature for the proliferation rates is as in a. Best-fit values for the four rates of the progressive model: λ1=1.35 d−1, λ2=1.53 d−1, d1=0.44 d−1, d2=0.035 d−1. (c) χ2 min over degrees of freedom (defined as the difference between the number of data points and number of estimated parameters) for both models as well as the difference in the (finite sample size corrected) Akaike information criterion between the models.

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Flossdorf, M., Rössler, J., Buchholz, V. et al. CD8+ T cell diversification by asymmetric cell division. Nat Immunol 16, 891–893 (2015). https://doi.org/10.1038/ni.3235

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