Affiliation:
1. Center for Applied Mathematics
2. Cornell University
3. Department of Mathematics and Center for Applied Mathematics
4. School of Civil and Environmental Engineering
Abstract
Antagonistic interactions are critical determinants of microbial community stability and composition, offering host benefits such as pathogen protection and providing avenues for antimicrobial control. While the ability to eliminate competitors confers an advantage to antagonistic microbes, it often incurs a fitness cost. Consequently, many microbes only produce toxins or engage in antagonistic behavior in response to specific cues like quorum sensing molecules or environmental stress. In laboratory settings, antagonistic microbes typically dominate over sensitive ones, raising the question of why both antagonistic and nonantagonistic microbes are found in natural environments and host microbiomes. Here, using both theoretical models and experiments with killer strains of
Saccharomyces cerevisiae
, we show that “boom-and-bust” dynamics—periods of rapid growth punctuated by episodic mortality events—caused by temporal environmental fluctuations can favor nonantagonistic microbes that do not incur the growth rate cost of toxin production. Additionally, using control theory, we derive bounds on the competitive performance and identify optimal regulatory toxin-production strategies in various boom-and-bust environments where population dilutions occur either deterministically or stochastically over time. Our mathematical investigation reveals that optimal toxin regulation is much more beneficial to killers in stochastic, rather than deterministic, boom-and-bust environments. Overall, our findings show how both antagonistic and nonantagonistic microbes can thrive under varying environmental conditions.
Funder
HHS | NIH | National Institute of General Medical Sciences
National Science Foundation
DOD | AF | AMC | AFRL | Air Force Office of Scientific Research
Publisher
Proceedings of the National Academy of Sciences