Physically asymmetric division of the C. elegans zygote ensures invariably successful embryogenesis

  1. Radek Jankele
  2. Rob Jelier
  3. Pierre Gönczy  Is a corresponding author
  1. Swiss Federal Institute of Technology, Switzerland
  2. Katholieke Universiteit Leuven, Belgium

Abstract

Asymmetric divisions that yield daughter cells of different sizes are frequent during early embryogenesis, but the importance of such a physical difference for successful development remains poorly understood. Here, we investigated this question using the first division of C. elegans embryos, which yields a large AB cell and a small P1 cell. We equalized AB and P1 sizes using acute genetic inactivation or optogenetic manipulation of the spindle positioning protein LIN-5. We uncovered that only some embryos tolerated equalization, and that there was a size asymmetry threshold for viability. Cell lineage analysis of equalized embryos revealed an array of defects, including faster cell cycle progression in P1 descendants, as well as defects in cell positioning, division orientation and cell fate. Moreover, equalized embryos were more susceptible to external compression. Overall, we conclude that unequal first cleavage is essential for invariably successful embryonic development of C. elegans.

Data availability

All data generated or analysed during this study are included in the manuscript and supporting files.Source data files and code have been provided as individual files for: Figure 1 - supplement 1-3, Figures 2, Figure 2 - supplement 1, Figure 5, Figure 5 - supplement 1, and Figure 6 - supplement 1.Further, the lineaging data, as well as the source code used for their analysis, are available from GitHub: https://github.com/UPGON/worm-rules-eLifeThese include code and source data for Figures 3, 4, and 6, and accompanying supplements, as well as for Figure 6 - supplement 2 and 3). Results of the statistical tests are reported in Supplementary File 6

The following data sets were generated

Article and author information

Author details

  1. Radek Jankele

    Swiss Institute for Experimental Cancer Research, School of Life Sciences, Swiss Federal Institute of Technology, Lausanne, Switzerland
    Competing interests
    The authors declare that no competing interests exist.
  2. Rob Jelier

    Centre of Microbial and Plant Genetics, Katholieke Universiteit Leuven, Leuven, Belgium
    Competing interests
    The authors declare that no competing interests exist.
  3. Pierre Gönczy

    Swiss Institute of Experimental Cancer Research, Swiss Federal Institute of Technology, Lausanne, Switzerland
    For correspondence
    pierre.gonczy@epfl.ch
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6305-6883

Funding

Swiss National Science Foundation (31003A_155942)

  • Radek Jankele
  • Pierre Gönczy

Research Foundation Flanders (G055017N)

  • Rob Jelier

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

Reviewing Editor

  1. Michael B Eisen, University of California, Berkeley, United States

Publication history

  1. Received: August 3, 2020
  2. Accepted: February 22, 2021
  3. Accepted Manuscript published: February 23, 2021 (version 1)
  4. Accepted Manuscript updated: February 25, 2021 (version 2)
  5. Version of Record published: March 18, 2021 (version 3)

Copyright

© 2021, Jankele 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.

Metrics

  • 2,287
    Page views
  • 326
    Downloads
  • 5
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Radek Jankele
  2. Rob Jelier
  3. Pierre Gönczy
(2021)
Physically asymmetric division of the C. elegans zygote ensures invariably successful embryogenesis
eLife 10:e61714.
https://doi.org/10.7554/eLife.61714

Further reading

    1. Cell Biology
    Willa Wen-You Yim et al.
    Tools and Resources Updated

    Monitoring autophagic flux is necessary for most autophagy studies. The autophagic flux assays currently available for mammalian cells are generally complicated and do not yield highly quantitative results. Yeast autophagic flux is routinely monitored with the green fluorescence protein (GFP)-based processing assay, whereby the amount of GFP proteolytically released from GFP-containing reporters (e.g. GFP-Atg8), detected by immunoblotting, reflects autophagic flux. However, this simple and effective assay is typically inapplicable to mammalian cells because GFP is efficiently degraded in lysosomes while the more proteolytically resistant red fluorescent protein (RFP) accumulates in lysosomes under basal conditions. Here, we report a HaloTag (Halo)-based reporter processing assay to monitor mammalian autophagic flux. We found that Halo is sensitive to lysosomal proteolysis but becomes resistant upon ligand binding. When delivered into lysosomes by autophagy, pulse-labeled Halo-based reporters (e.g. Halo-LC3 and Halo-GFP) are proteolytically processed to generate Haloligand when delivered into lysosomes by autophagy. Hence, the amount of free Haloligand detected by immunoblotting or in-gel fluorescence imaging reflects autophagic flux. We demonstrate the applications of this assay by monitoring the autophagy pathways, macroautophagy, selective autophagy, and even bulk nonselective autophagy. With the Halo-based processing assay, mammalian autophagic flux and lysosome-mediated degradation can be monitored easily and precisely.

    1. Cell Biology
    2. Computational and Systems Biology
    Théo Aspert et al.
    Tools and Resources

    Automating the extraction of meaningful temporal information from sequences of microscopy images represents a major challenge to characterize dynamical biological processes. So far, strong limitations in the ability to quantitatively analyze single-cell trajectories have prevented large-scale investigations to assess the dynamics of entry into replicative senescence in yeast. Here, we have developed DetecDiv, a microfluidic-based image acquisition platform combined with deep learning-based software for high-throughput single-cell division tracking. We show that DetecDiv can automatically reconstruct cellular replicative lifespans with high accuracy and performs similarly with various imaging platforms and geometries of microfluidic traps. In addition, this methodology provides comprehensive temporal cellular metrics using time-series classification and image semantic segmentation. Last, we show that this method can be further applied to automatically quantify the dynamics of cellular adaptation and real-time cell survival upon exposure to environmental stress. Hence, this methodology provides an all-in-one toolbox for high-throughput phenotyping for cell cycle, stress response, and replicative lifespan assays.