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Extracellular matrix anisotropy is determined by TFAP2C-dependent regulation of cell collisions

Nature Materials volume 19, pages 227–238 (2020)Cite this article

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Abstract

The isotropic or anisotropic organization of biological extracellular matrices has important consequences for tissue function. We study emergent anisotropy using fibroblasts that generate varying degrees of matrix alignment from uniform starting conditions. This reveals that the early migratory paths of fibroblasts are correlated with subsequent matrix organization. Combined experimentation and adaptation of Vicsek modelling demonstrates that the reorientation of cells relative to each other following collision plays a role in generating matrix anisotropy. We term this behaviour ‘cell collision guidance’. The transcription factor TFAP2C regulates cell collision guidance in part by controlling the expression of RND3. RND3 localizes to cell–cell collision zones where it downregulates actomyosin activity. Cell collision guidance fails without this mechanism in place, leading to isotropic matrix generation. The cross-referencing of alignment and TFAP2C gene expression signatures against existing datasets enables the identification and validation of several classes of pharmacological agents that disrupt matrix anisotropy.

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Fig. 1: ECM anisotropy instructs cancer cell migration and enables the global coordination of force.
Fig. 2: Aligned fibroblasts demonstrate higher intrinsic polarity and migratory persistence, but this is insufficient to drive alignment.
Fig. 3: Aligned fibroblasts show supressed contact inhibition of locomotion and elevated collision guidance.
Fig. 4: Collision guidance entails the suppression of actomyosin contractility at cell–cell contacts.
Fig. 5: TFAP2C acts through RND3 to facilitate collision guidance and alignment.
Fig. 6: Predicting pharmacological perturbation of alignment.

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Data availability

Primary accession data files are deposited at the NCBI Gene Expression Omnibus under GSE121536. The data that support the findings of this study are available from the corresponding author on reasonable request.

Code availability

The code for the computational model continues to be developed and is available via the following link: https://github.com/wershofe/FibroblastMatrixModel. The version pertaining to this manuscript is called cellCellModel.

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Acknowledgements

We are indebted to Bioinformatics and Biostatistics, Light Microscopy (in particular D. Barry), Advanced Sequencing Facilities, Cell Services and the Biological Research Facility at the Francis Crick Institute for scientific and technical support throughout the project. We thank C. Mein (Barts and the London School of Medicine and Dentistry) for support and advice with RNA sequencing. E.S., D.P., P.A.B. and E.W. were funded by the Francis Crick Institute, which receives its core funding from Cancer Research UK (FC001144, FC001003), the UK Medical Research Council (FC001003, FC001144) and the Wellcome Trust (FC001003, FC001144). E.S. and D.P. also received funding from Breast Cancer Now (2013NovPR182). X.T. received funding from by the Spanish Ministry of Science and Innovation (Severo Ochoa Award), the Generalitat de Catalunya (Cerca Program), the European Research Council (CoG-616480), the European Commission (FET Proactive 731957) and Obra Social ‘La Caixa’. A.L. received financial support through the Junior Leader Postdoctoral Fellowship Programme from ‘La Caixa’ Banking Foundation.

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Authors and Affiliations

  1. Tumour Cell Biology Laboratory, The Francis Crick Institute, London, UK

    Danielle Park, Esther Wershof, Robert P. Jenkins, Samantha George & Erik Sahai

  2. Biomolecular Modelling Laboratory, The Francis Crick Institute, London, UK

    Esther Wershof & Paul A. Bates

  3. Bioinformatics Laboratory, The Francis Crick Institute, London, UK

    Stefan Boeing

  4. Institute for Bioengineering of Catalonia, The Barcelona Institute for Science and Technology, Barcelona, Spain

    Anna Labernadie & Xavier Trepat

  5. Institució Catalana de Recerca i Estudis Avançats, Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, University of Barcelona, Barcelona, Spain

    Xavier Trepat

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Contributions

D.P., E.W. and E.S. conceived and developed the project. D.P. performed the experiments and analysed the data. E.W. and P.A.B. developed the computational model and analysed the data. S.B. performed the bioinformatic analysis of RNASeq and LINCS data. A.L. performed the traction force microscopy and analysis in Figs. 1f and 4e. R.P.J. wrote the code for analysis of fibre alignment. S.G. performed the tracking of some cell collision data. D.P. and E.S. wrote the manuscript with assistance from E.W., A.L., R.P.J., X.T. and P.A.B.

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Correspondence to Erik Sahai.

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Supplementary information

Supplementary Information

Supplementary Figs. 1–6 and Tables 1 and 2.

Reporting Summary

Supplementary Video 1

Alignment emerges prior to confluence and early migration paths predict final organization.

Supplementary Video 2

Actomyosin is supressed at cell contacts during collision guidance.

Supplementary Video 3

Actomyosin is concentrated at cell contacts during CIL.

Supplementary Video 4

Myosin is supressed at cell contacts during nematic gliding.

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Park, D., Wershof, E., Boeing, S. et al. Extracellular matrix anisotropy is determined by TFAP2C-dependent regulation of cell collisions. Nat. Mater. 19, 227–238 (2020). https://doi.org/10.1038/s41563-019-0504-3

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