Why can we sometimes, but not always, predict the future from short term competition assays - Dataset

Résumé fourni par la source

To predict long-term population dynamics, short-term competition assays are often conducted to determine whether novel community members can invade and persist in an established population. Post hoc we know this approach is sometimes accurate, but sometimes inaccurate. Knowing its effectiveness a priori would prove highly beneficial. To approach a general framework, we combine theory and a model experimental system of human fungal pathogens, Candida albicans and Candida glabrata. We establish conditions where predictions from short-term frequency-dependent competitions accurately describe long-term dynamics. However, introducing fluconazole causes long-term outcomes to diverge from short-term predictions. Mathematical modelling and experiments demonstrate this breakdown is caused by persisting physiological changes from enduring antimicrobial exposure that alter competitive interactions. This temporal dependency we term dynamic frequency dependence. We show that micro-experimental details matter, such as pregrowth conditions, and provide a mechanistic explanation about the inconsistency of extrapolating predictions from short-term competitions into long-term outcomes.

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