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

Version 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.

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  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

Share this article

https://doi.org/10.7554/eLife.62932

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