Abstract

Mechanobiology requires precise quantitative information on processes taking place in specific 3D microenvironments. Connecting the abundance of microscopical, molecular, biochemical and cell mechanical data with defined topologies has turned out to be extremely difficult. Establishing such structural and functional 3D maps needed for biophysical modeling is a particular challenge for the cytoskeleton, which consists of long and interwoven filamentous polymers coordinating subcellular processes and interactions of cells with their environment. To date, useful tools are available for the segmentation and modeling of actin filaments and microtubules but comprehensive tools for the mapping of intermediate filament organization are still lacking. In this work, we describe a workflow to model and examine the complete 3D arrangement of the keratin intermediate filament cytoskeleton in canine, murine and human epithelial cells both, in vitro and in vivo. Numerical models are derived from confocal Airyscan high resolution 3D imaging of fluorescence-tagged keratin filaments. They are interrogated and annotated at different length scales using different modes of visualization including immersive virtual reality. In this way, information is provided on network organization at the subcellular level including mesh arrangement, density and isotropic configuration as well as details on filament morphology such as bundling, curvature and orientation. We show that the comparison of these parameters helps to identify, in quantitative terms, similarities and differences of keratin network organization in epithelial cell types defining subcellular domains, notably basal, apical, lateral and perinuclear systems. The described approach and the presented data are pivotal for generating mechanobiological models that can be experimentally tested.

Data availability

Software, original and processed data are available athttp://kernet.rwth-aachen.de/andhttps://github.com/VRGroupRWTH/Zytoskelett

The following data sets were generated

Article and author information

Author details

  1. Reinhard Windoffer

    Institute of Molecular and Cellular Anatomy, RWTH Aachen University, Aachen, Germany
    For correspondence
    rwindoffer@ukaachen.de
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1403-5880
  2. Nicole Schwarz

    Institute of Molecular and Cellular Anatomy, RWTH Aachen University, Aachen, Germany
    Competing interests
    The authors declare that no competing interests exist.
  3. Sungjun Yoon

    Institute of Molecular and Cellular Anatomy, RWTH Aachen University, Aachen, Germany
    Competing interests
    The authors declare that no competing interests exist.
  4. Teodora Piskova

    Institute of Molecular and Cellular Anatomy, RWTH Aachen University, Aachen, Germany
    Competing interests
    The authors declare that no competing interests exist.
  5. Michael Scholkemper

    Department of Computer Science, RWTH Aachen University, Aachen, Germany
    Competing interests
    The authors declare that no competing interests exist.
  6. Johannes Stegmaier

    Institute of Imaging and Computer Vision, RWTH Aachen University, Aachen, Germany
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4072-3759
  7. Andrea Bönsch

    Visual Computing Institute, RWTH Aachen University, Aachen, Germany
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5077-3675
  8. Jacopo Di Russo

    Interdisciplinary Centre for Clinical Research, RWTH Aachen University, Aachen, Germany
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6731-9612
  9. Rudolf Leube

    Institute of Molecular and Cellular Anatomy, RWTH Aachen University, Aachen, Germany
    For correspondence
    rleube@ukaachen.de
    Competing interests
    The authors declare that no competing interests exist.

Funding

Deutsche Forschungsgemeinschaft (WI173/8-2)

  • Reinhard Windoffer

Deutsche Forschungsgemeinschaft (LE566/18-2)

  • Rudolf Leube

Deutsche Forschungsgemeinschaft (GRK2415/363055819)

  • Reinhard Windoffer
  • Nicole Schwarz
  • Sungjun Yoon
  • Teodora Piskova
  • Rudolf Leube

RWTH Aachen University (rwth0452)

  • Reinhard Windoffer

Medizinische Fakultät, RWTH Aachen University (IZKF)

  • Teodora Piskova
  • Jacopo Di Russo

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

Ethics

Animal experimentation: All animal experiments were conducted in accordance with the guidelines for the care and use of laboratory animals and were approved by the Landesamt für Natur, Umwelt und Verbraucherschutz Nordrhein-Westfalen (LANUV; reference number 84-02.04.2015.A190 and approvals according to {section sign}4 of the German Animal Welfare Act).

Reviewing Editor

  1. Pierre Coulombe

Publication history

  1. Received: November 26, 2021
  2. Preprint posted: December 9, 2021 (view preprint)
  3. Accepted: February 15, 2022
  4. Accepted Manuscript published: February 18, 2022 (version 1)
  5. Accepted Manuscript updated: February 23, 2022 (version 2)
  6. Version of Record published: April 4, 2022 (version 3)

Copyright

© 2022, Windoffer 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. Reinhard Windoffer
  2. Nicole Schwarz
  3. Sungjun Yoon
  4. Teodora Piskova
  5. Michael Scholkemper
  6. Johannes Stegmaier
  7. Andrea Bönsch
  8. Jacopo Di Russo
  9. Rudolf Leube
(2022)
Quantitative mapping of keratin networks in 3D
eLife 11:e75894.
https://doi.org/10.7554/eLife.75894

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