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

eLife

Andrew W Murray¹  David R Nelson²  Andrea Giometto³ 

[1] Department of Molecular and Cellular Biology, Harvard University, Cambridge, United States;Department of Physics, Harvard University, Cambridge, United States;Department of Molecular and Cellular Biology, Harvard University, Cambridge, United States;John A Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, United States;School of Civil and Environmental Engineering, Cornell University, Ithaca, United States;Department of Physics, Harvard University, Cambridge, United States;Department of Molecular and Cellular Biology, Harvard University, Cambridge, United States;

关键词: physical biology;    ecology;    evolution;    antagonism;    toxin;    biological interactions;    S. cerevisiae;   

DOI  :  10.7554/eLife.62932

来源: eLife Sciences Publications, Ltd

【 摘 要 】

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 antagonism 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.

【 授权许可】

CC BY