The central question we explored was: When does it make sense for microbes to act antagonistically and when does it become a disadvantage? said Andrea Giometto assistant professor of civil and environmental engineering at Cornell Engineering and co-senior author of the paper. Displaying antagonistic behavior comes at a metabolic cost microbes must use energy to produce toxins. In situations where resources are abundant and microbial populations are still low it may be more beneficial to channel that energy into rapid growth rather than conflict.

Vladimirsky noted that when environmental disturbances occur randomly antagonistic microbes benefit more from selectively producing toxins. In contrast predictable dilution schedules offer less advantage for such selective behavior. This understanding of trade-offs between metabolic cost and competitive gain could guide the development of smarter adaptable probiotics. The findings may even carry broader implications for how all organisms microbes to humans approach competition. As Vladimirsky put it focusing too much on harming others can drain resources better spent on growth and success.

Microbial antagonism where microbes produce toxins to suppress or eliminate competitors can be beneficial by helping microbes colonize environments outcompete rivals and even protect their hosts from harmful pathogens. It also holds promise for humans as these microbial interactions can lead to the discovery of new antimicrobial compounds. 

In stable laboratory environments aggressive or antagonistic microbes typically outcompete their less combative peers. However this dynamic can flip in fluctuating or disrupted settings. For example environments that are generally supportive but subject to sudden disturbances like the gut microbiome after antibiotic treatment or the mouth during routine plaque removal often favor more peaceful microbes.

To replicate these boom-and-bust conditions the researchers conducted a daily cycle experiment using two strains of Saccharomyces cerevisiae (budding yeast): a toxin-producing killer strain and a non-aggressive sensitive strain. Each day they grew both strains diluted the cultures and measured how many cells of each remained then repeated the process over multiple cycles.

To explore further the team turned to computational modeling. This allowed them to simulate scenarios that were difficult to test experimentally such as varying dilution strengths and schedules introducing randomness versus predictability in disturbances and analyzing different toxin-production strategies. Their models also emphasized the role of microbial tactics like quorum sensing where antagonistic microbes respond to environmental or population signals before deploying their toxins highlighting how timing and strategy can influence microbial competition.

Source: https://news.cornell.edu/stories/2025/07/microbes-harsh-environments-its-survival-meekest