Antagonism between killer yeast strains as an experimental model for biological nucleation dynamics

  1. Andrea Giometto  Is a corresponding author
  2. David R Nelson
  3. Andrew W Murray
  1. Cornell University, United States
  2. Harvard University, United States

Abstract

Antagonistic interactions are widespread in the microbial world and affect microbial evolutionary dynamics. Natural microbial communities often display spatial structure, which affects biological interactions, but much of what we know about microbial warfare comes from laboratory studies of well-mixed communities. To overcome this limitation, we manipulated two killer strains of the budding yeast Saccharomyces cerevisiae, expressing different toxins, to independently control the rate at which they released their toxins. We developed mathematical models that predict the experimental dynamics of competition between toxin-producing strains in both well-mixed and spatially structured populations. In both situations, we experimentally verified theory's prediction that a stronger antagonist can invade a weaker one only if the initial invading population exceeds a critical frequency or size. Finally, we found that toxin-resistant cells and weaker killers arose in spatially structured competitions between toxin-producing strains, suggesting that adaptive evolution can affect the outcome of microbial antagonism in spatial settings.

Data availability

All data are included in the manuscript and supporting files. All source code that generated figures and numerical results has been uploaded on GitHub at the URL: https://github.com/andreagiometto/Giometto_Nelson_Murray_2020. Source data files have been provided for all Figures displaying data.

Article and author information

Author details

  1. Andrea Giometto

    School of Civil and Environmental Engineering, Cornell University, Ithaca, United States
    For correspondence
    giometto@cornell.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0544-6023
  2. David R Nelson

    Department of Physics, Harvard University, Cambridge, MA, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Andrew W Murray

    Department of Molecular and Cellular Biology, Harvard University, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0868-6604

Funding

Swiss National Science Foundation (P2ELP2_168498)

  • Andrea Giometto

Swiss National Science Foundation (P400PB_180823)

  • Andrea Giometto

Human Frontier Science Program (RGP0041/2014)

  • David R Nelson
  • Andrew W Murray

National Science Foundation (1764269)

  • Andrew W Murray

Simons Foundation (594596)

  • Andrew W Murray

National Science Foundation (DMR1608501)

  • David R Nelson

Harvard Materials Science Research and Engineering Center (DMR-2011754)

  • David R Nelson

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

Reviewing Editor

  1. Naama Barkai, Weizmann Institute of Science, Israel

Publication history

  1. Received: September 9, 2020
  2. Preprint posted: September 10, 2020 (view preprint)
  3. Accepted: November 11, 2021
  4. Accepted Manuscript published: December 6, 2021 (version 1)
  5. Accepted Manuscript updated: December 6, 2021 (version 2)
  6. Version of Record published: January 5, 2022 (version 3)

Copyright

© 2021, Giometto 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

  • 940
    Page views
  • 141
    Downloads
  • 3
    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. Andrea Giometto
  2. David R Nelson
  3. Andrew W Murray
(2021)
Antagonism between killer yeast strains as an experimental model for biological nucleation dynamics
eLife 10:e62932.
https://doi.org/10.7554/eLife.62932
  1. Further reading

Further reading

    1. Physics of Living Systems
    2. Plant Biology
    Lauren Sullivan
    Insight

    Dandelion seeds respond to wet weather by closing their plumes, which reduces dispersal when wind conditions are poor.

    1. Physics of Living Systems
    Matthew F Lefebvre, Nikolas H Claussen ... Sebastian J Streichan
    Research Article

    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.