Robustness of the microtubule network self-organization in epithelia

  1. Aleksandra Z Plochocka
  2. Miguel Ramirez Moreno
  3. Alexander M Davie
  4. Natalia A Bulgakova  Is a corresponding author
  5. Lyubov Chumakova  Is a corresponding author
  1. Flatiron Institute, United States
  2. University of Sheffield, United Kingdom
  3. University of Edinburgh, United Kingdom

Abstract

Robustness of biological systems is crucial for their survival, however, for many systems its origin is an open question. Here we analyze one sub-cellular level system, the microtubule cytoskeleton. Microtubules self-organize into a network, along which cellular components are delivered to their biologically relevant locations. While the dynamics of individual microtubules is sensitive to the organism's environment and genetics, a similar sensitivity of the overall network would result in pathologies. Our large-scale stochastic simulations show that the self-organization of microtubule networks is robust in a wide parameter range in individual cells. We confirm this robustness in vivo on the tissue-scale using genetic manipulations of Drosophila epithelial cells. Finally, our minimal mathematical model shows that the origin of robustness is the separation of time-scales in microtubule dynamics rates. Altogether, we demonstrate that the tissue-scale self-organization of a microtubule network depends only on cell geometry and the distribution of the microtubule minus-ends.

Data availability

At the time of the publication, all the biological data is available on https://datashare.is.ed.ac.uk/handle/10283/3439 (DOI:10.7488/ds/2642) as stated in the supplementary material in the article.

Article and author information

Author details

  1. Aleksandra Z Plochocka

    Center for Computational Biology and Center for Computational Mathematics, Flatiron Institute, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Miguel Ramirez Moreno

    Department of Biomedical Science, University of Sheffield, Sheffield, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  3. Alexander M Davie

    Maxwell Institute for Mathematical Sciences, School of Mathematics, University of Edinburgh, Edinburgh, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  4. Natalia A Bulgakova

    Biomedical Science, University of Sheffield, Sheffield, United Kingdom
    For correspondence
    n.bulgakova@sheffield.ac.uk
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3780-8164
  5. Lyubov Chumakova

    Maxwell Institute for Mathematical Sciences, School of Mathematics, University of Edinburgh, Edinburgh, United Kingdom
    For correspondence
    lchumakova@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2551-3905

Funding

Engineering and Physical Sciences Research Council (The Maxwell Institute Graduate School in Analysis and its Applica- tions,a Centre for Doctoral Trai)

  • Aleksandra Z Plochocka

Royal Society of Edinburgh (personal fellowship)

  • Lyubov Chumakova

Biotechnology and Biological Sciences Research Council (BB/P007503/1)

  • Natalia A Bulgakova

Leverhulme Trust (RPG-2017-249)

  • Natalia A Bulgakova
  • Lyubov Chumakova

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2021, Plochocka et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Aleksandra Z Plochocka
  2. Miguel Ramirez Moreno
  3. Alexander M Davie
  4. Natalia A Bulgakova
  5. Lyubov Chumakova
(2021)
Robustness of the microtubule network self-organization in epithelia
eLife 10:e59529.
https://doi.org/10.7554/eLife.59529

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https://doi.org/10.7554/eLife.59529