Adhesion forces and cortical tension couple cell proliferation and differentiation to drive epidermal stratification

Abstract

To establish and maintain organ structure and function, tissues need to balance stem cell proliferation and differentiation rates and coordinate cell fate with position. By quantifying and modelling tissue stress and deformation in the mammalian epidermis, we find that this balance is coordinated through local mechanical forces generated by cell division and delamination. Proliferation within the basal stem/progenitor layer, which displays features of a jammed, solid-like state, leads to crowding, thereby locally distorting cell shape and stress distribution. The resulting decrease in cortical tension and increased cell–cell adhesion trigger differentiation and subsequent delamination, reinstating basal cell layer density. After delamination, cells establish a high-tension state as they increase myosin II activity and convert to E-cadherin-dominated adhesion, thereby reinforcing the boundary between basal and suprabasal layers. Our results uncover how biomechanical signalling integrates single-cell behaviours to couple proliferation, cell fate and positioning to generate a multilayered tissue.

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Fig. 1: Cell division coincides with cell shape anisotropy, delamination and elevated contractility in stratifying tissue.
Fig. 2: Monolayer crowding state impacts delamination.
Fig. 3: Traction strain anisotropy and cell elongation promote differentiation in crowded cell layers.
Fig. 4: Dynamic changes in cortical tension couple cell fate and position.
Fig. 5: Cell division alters neighbour cell mechanics and increases the probability of delamination.
Fig. 6: Cell–cell adhesion regulates cell mechanics and fate.
Fig. 7: Dynamic changes in tension and cell–cell adhesion forces control stratification.

Change history

  • 06 July 2018

    In the version of this Article originally published, Supplementary Video 1 was incorrectly linked to Supplementary Video 6, Supplementary Video 2 was incorrectly linked to Supplementary Video 1, Supplementary Video 3 was incorrectly linked to Supplementary Video 2, Supplementary Video 4 was incorrectly linked to Supplementary Video 3, Supplementary Video 5 was incorrectly linked to Supplementary Video 4, and Supplementary Video 6 was incorrectly linked to Supplementary Video 5. The files have now been replaced to rectify this.

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Acknowledgements

We thank V. Braga, R. Fässler and P. H. Jones for critical reading of manuscript, R. Fässler for support with micropatterning, E. Bodenschatz for the AFM, R. Wedlich-Söldner for the LifeAct mice, and the FACS & Imaging Core Facility of MPI for Biology of Ageing for support with imaging. The computations were performed on a Bull Cluster at the Center for Information Services and High Performance Computing (ZIH) at TU Dresden. This work was supported by the Max Planck Society, the Max Planck Förderstiftung, the Behrens-Weise Foundation (to S.A.W.) and Deutsche Forschungsgemeinschaft through SFB 829 (to C.M.N. and S.A.W.), through SFB 937 (to N.K. and M.T.), and through SPP1782 (to C.M.N.), by the Whitaker postdoctoral fellowship (to Y.A.M.), and by the BMBF grant INDRA (031A312 to J.G.).

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Contributions

S.A.W. conceived and supervised the study. Y.A.M., D.S., H.Q.L., M.R. and N.B. performed experiments and analysed data. T.T. and J.G. designed, performed and analysed the computer simulations. J.P. assisted with initial design and production of micropatterns. N.K. and M.T. performed cell–cell adhesion force measurements. I.W. and M.B. provided algorithms and analyses of traction force and monolayer flow experiments, C.M.N. designed experiments and analysed data. S.A.W. designed and performed experiments, analysed data and wrote the paper. All authors commented on and edited the manuscript.

Corresponding author

Correspondence to Sara A. Wickström.

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Supplementary information

Supplementary Information

Supplementary Figures and Legends, Supplementary Table Legends, Supplementary Video Legends, References.

Life Sciences Reporting Summary

Supplementary Table 1

Parameter set of the model epidermis.

Supplementary Table 2

Statistics source data.

Videos

Supplementary Video 1

Time-lapse confocal video of LifeAct E15.5 embryo with vectors and smoothed velocity map. Images of back skin of embryos were acquired every 10 mins and subjected to PIV analyses. Motility vectors (left panel) and smoothed velocity maps (right panel) are shown.

Supplementary Video 2

Time-lapse confocal video of LifeAct E15.5 embryo. Images were acquired every 10 mins. Asterisks demarcate a dividing cell and arrowhead a delaminating cell.

Supplementary Video 3

Time-lapse DIC video and smoothed velocity map of EPC monolayers after Ca2+ treatment. Images of EPC monolayers treated with 1.8 mM Ca2+ were acquired every 20 mins and subjected to PIV analyses. Motility vectors (left panel) and smoothed velocity maps (right panel) are shown. Asterisks demarcate examples of 2 dividing cells and arrowhead an example of a delaminating cell.

Supplementary Video 4

Time-lapse DIC video of Ca2+ treated EPCs on a circular micropattern. Images were acquired every 10 mins and the video is shown 1 frame/sec.

Supplementary Video 5

Time-lapse video of a 3D model epidermis simulation. A side view is shown.

Supplementary Video 6

Time-lapse video of a 3D model epidermis simulation. A top view is shown.

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Miroshnikova, Y.A., Le, H.Q., Schneider, D. et al. Adhesion forces and cortical tension couple cell proliferation and differentiation to drive epidermal stratification. Nat Cell Biol 20, 69–80 (2018). https://doi.org/10.1038/s41556-017-0005-z

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