Geometric control of Myosin-II orientation during axis elongation

  1. Matthew F Lefebvre
  2. Nikolas H Claussen
  3. Noah P Mitchell
  4. Hannah J Gustafson
  5. Sebastian J Streichan  Is a corresponding author
  1. University of California, Santa Barbara, United States

Abstract

The actomyosin cytoskeleton is a crucial driver of morphogenesis. Yet how the behavior of largescale cytoskeletal patterns in deforming tissues emerges from the interplay of geometry, genetics, and mechanics remains incompletely understood. Convergent extension in D. melanogaster embryos provides the opportunity to establish a quantitative understanding of the dynamics of anisotropic non-muscle myosin II. Cell-scale analysis of protein localization in fixed embryos suggests that gene expression patterns govern myosin anisotropy via complex rules. However, technical limitations have impeded quantitative and dynamic studies of this process at the whole embryo level, leaving the role of geometry open. Here we combine in toto live imaging with quantitative analysis of molecular dynamics to characterize the distribution of myosin anisotropy and the corresponding genetic patterning. We found pair rule gene expression continuously deformed, flowing with the tissue frame. In contrast, myosin anisotropy orientation remained approximately static, and was only weakly deflected from the stationary dorsal-ventral axis of the embryo. We propose that myosin is recruited by a geometrically defined static source, potentially related to the embryoscale epithelial tension, and account for transient deflections by cytoskeletal turnover and junction reorientation by flow. With only one parameter, this model quantitatively accounts for the time course of myosin anisotropy orientation in wild-type, twist, and even-skipped embryos as well as embryos with perturbed egg geometry. Geometric patterning of the cytoskeleton suggests a simple physical strategy to ensure a robust flow and formation of shape.

Data availability

All data for this article is available publicly without any restrictions. In our article, we make use of two datasets: (1) confocal microscopy data of FRAP experiments, which is available on the Dryad data repository https://doi.org/10.25349/D94C8M. (2) Lightsheet microscopy data of entire embryos. The data we use in the current publication is a subset of a larger dataset, the 'Morphodynamic atlas of Drosophila development', which is publicly available on the Dryad data repository https://doi.org/10.25349/D9WW43. This collection is indexed by the fly genotype and fluorescent marker imaged, so that the movies and images used in the current publication can be found easily. Lightsheet microscopy integrates microscopy and computational processing and its computational pipeline creates intermediate, 'raw' data files, which are of very large size (TBs for a single movie). This raw data is available upon request from the corresponding author without restriction or need for a specific research proposal. The analysis code used is available on GitHub https://github.com/nikolas-claussen/Geometric-control-of-Myosin-II-orientation-during-axis-elongation.

The following data sets were generated

Article and author information

Author details

  1. Matthew F Lefebvre

    Department of Physics, University of California, Santa Barbara, Santa Barbara, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Nikolas H Claussen

    Department of Physics, University of California, Santa Barbara, Santa Barbara, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Noah P Mitchell

    Department of Physics, University of California, Santa Barbara, Santa Barbara, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Hannah J Gustafson

    Department of Physics, University of California, Santa Barbara, Santa Barbara, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Sebastian J Streichan

    Department of Physics, University of California, Santa Barbara, Santa Barbara, United States
    For correspondence
    streicha@ucsb.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6105-9087

Funding

National Institutes of Health (5 R35 GM138203)

  • Sebastian J Streichan

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

Copyright

© 2023, Lefebvre 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.

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. Matthew F Lefebvre
  2. Nikolas H Claussen
  3. Noah P Mitchell
  4. Hannah J Gustafson
  5. Sebastian J Streichan
(2023)
Geometric control of Myosin-II orientation during axis elongation
eLife 12:e78787.
https://doi.org/10.7554/eLife.78787

Share this article

https://doi.org/10.7554/eLife.78787

Further reading

    1. Physics of Living Systems
    Ning Liu, Wenan Qiang ... Huanyu Qiao
    Research Article

    Chromosome structure is complex, and many aspects of chromosome organization are still not understood. Measuring the stiffness of chromosomes offers valuable insight into their structural properties. In this study, we analyzed the stiffness of chromosomes from metaphase I (MI) and metaphase II (MII) oocytes. Our results revealed a tenfold increase in stiffness (Young’s modulus) of MI chromosomes compared to somatic chromosomes. Furthermore, the stiffness of MII chromosomes was found to be lower than that of MI chromosomes. We examined the role of meiosis-specific cohesin complexes in regulating chromosome stiffness. Surprisingly, the stiffness of chromosomes from three meiosis-specific cohesin mutants did not significantly differ from that of wild-type chromosomes, indicating that these cohesins may not be primary determinants of chromosome stiffness. Additionally, our findings revealed an age-related increase of chromosome stiffness for MI oocytes. Since aging is associated with elevated levels of DNA damage, we investigated the impact of etoposide-induced DNA damage on chromosome stiffness and found that it led to a reduction in stiffness in MI oocytes. Overall, our study underscores the dynamic and cyclical nature of chromosome stiffness, modulated by both the cell cycle and age-related factors.

    1. Cancer Biology
    2. Physics of Living Systems
    Joseph Ackermann, Chiara Bernard ... Martine D Ben Amar
    Research Article

    The tumor stroma consists mainly of extracellular matrix, fibroblasts, immune cells, and vasculature. Its structure and functions are altered during malignancy: tumor cells transform fibroblasts into cancer-associated fibroblasts, which exhibit immunosuppressive activities on which growth and metastasis depend. These include exclusion of immune cells from the tumor nest, cancer progression, and inhibition of T-cell-based immunotherapy. To understand these complex interactions, we measure the density of different cell types in the stroma using immunohistochemistry techniques on tumor samples from lung cancer patients. We incorporate these data into a minimal dynamical system, explore the variety of outcomes, and finally establish a spatio-temporal model that explains the cell distribution. We reproduce that cancer-associated fibroblasts act as a barrier to tumor expansion, but also reduce the efficiency of the immune response. Our conclusion is that the final outcome depends on the parameter values for each patient and leads to either tumor invasion, persistence, or eradication as a result of the interplay between cancer cell growth, T-cell cytotoxicity, and fibroblast activity. However, despite the existence of a wide range of scenarios, distinct trajectories, and patterns allow quantitative predictions that may help in the selection of new therapies and personalized protocols.