Quantitative live-cell imaging and computational modelling shed new light on endogenous WNT/CTNNB1 signaling dynamics

  1. Saskia M A de Man
  2. Gooitzen Zwanenburg  Is a corresponding author
  3. Tanne van der Wal
  4. Mark Hink  Is a corresponding author
  5. Renee van Amerongen  Is a corresponding author
  1. Swammerdam Institute for Life Sciences, University of Amsterdam, Netherlands
  2. Universiteit van Amsterdam, Netherlands

Abstract

WNT/CTNNB1 signaling regulates tissue development and homeostasis in all multicellular animals, but the underlying molecular mechanism remains incompletely understood. Specifically, quantitative insight into endogenous protein behavior is missing. Here we combine CRISPR/Cas9-mediated genome editing and quantitative live-cell microscopy to measure the dynamics, diffusion characteristics and absolute concentrations of fluorescently tagged, endogenous CTNNB1 in human cells under both physiological and oncogenic conditions. State-of-the-art imaging reveals that a substantial fraction of CTNNB1 resides in slow-diffusing cytoplasmic complexes, irrespective of the activation status of the pathway. This cytoplasmic CTNNB1 complex undergoes a major reduction in size when WNT/CTNNB1 is (hyper)activated. Based on our biophysical measurements we build a computational model of WNT/CTNNB1 signaling. Our integrated experimental and computational approach reveals that WNT pathway activation regulates the dynamic distribution of free and complexed CTNNB1 across different subcellular compartments through three regulatory nodes: the destruction complex, nucleocytoplasmic shuttling and nuclear retention.

Data availability

Source data: for numerical data points in Figures 2-5,7-8 are attached to this article. In addition a comprehensive overview of all numerical data (summary statistics; median, mean and 95% CI's) for the FCS and N&B experiments depicted in Figures 5, 7, 8 plus accompanying supplements and in Tables 1, 2 and 3) is provided in summary tables as Supplementary File 1.Raw data: Original FACS data (.fcs), Western blot data (.tif), confocal images (.tif), FCS data (.ptu- and .oif reference images), N&B data (.ptu/.tif and .oif reference images) have been provided on Open Science Framework (https://osf.io/dczx8/).Source code: scripts for the following have been made publicly available on Open Science Framework (https://osf.io/dczx8/), as referenced in the materials and methods section: Cell profiler segmentation pipeline (Figure 3), R script based on PlotsOfDifference to generate Figure 3 supplement 2 and supplementary movies 4-6, ImageJ N&B analysis script (Figures 5,7 and 8), R source code for the computational model (Figure 6)

The following data sets were generated

Article and author information

Author details

  1. Saskia M A de Man

    Developmental, Stem Cell and Cancer Biology, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, Netherlands
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0906-5276
  2. Gooitzen Zwanenburg

    Biosystems Data Analysis, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, Netherlands
    For correspondence
    Gooitzen.zwanenburg@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
  3. Tanne van der Wal

    Developmental, Stem Cell and Cancer Biology, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, Netherlands
    Competing interests
    The authors declare that no competing interests exist.
  4. Mark Hink

    Universiteit van Amsterdam, Amsterdam, Netherlands
    For correspondence
    m.a.hink@uva.nl
    Competing interests
    The authors declare that no competing interests exist.
  5. Renee van Amerongen

    Developmental, Stem Cell and Cancer Biology, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, Netherlands
    For correspondence
    r.vanamerongen@uva.nl
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8808-2092

Funding

University of Amsterdam (MacGillavry fellowship)

  • Renee van Amerongen

KWF Kankerbestrijding (ANW 2013-6057)

  • Renee van Amerongen

KWF Kankerbestrijding (2015-8014)

  • Renee van Amerongen

Nederlandse Organisatie voor Wetenschappelijk Onderzoek (864.13.002)

  • Renee van Amerongen

Nederlandse Organisatie voor Wetenschappelijk Onderzoek (OCENW.KLEIN.169)

  • Renee van Amerongen

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

Reviewing Editor

  1. Felix Campelo, The Barcelona Institute of Science and Technology, Spain

Version history

  1. Received: January 11, 2021
  2. Accepted: June 29, 2021
  3. Accepted Manuscript published: June 30, 2021 (version 1)
  4. Version of Record published: August 5, 2021 (version 2)

Copyright

© 2021, de Man 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. Saskia M A de Man
  2. Gooitzen Zwanenburg
  3. Tanne van der Wal
  4. Mark Hink
  5. Renee van Amerongen
(2021)
Quantitative live-cell imaging and computational modelling shed new light on endogenous WNT/CTNNB1 signaling dynamics
eLife 10:e66440.
https://doi.org/10.7554/eLife.66440

Share this article

https://doi.org/10.7554/eLife.66440

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