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This computational study uses an agent-based model to demonstrate that cross-feeding relationships in microbial communities can evolve through selection for energy acquisition alone, without requiring special metabolic trade-offs or mechanisms. The model successfully reproduces experimental observations showing that genetically identical microbial populations evolving under identical conditions can develop different cross-feeding patterns across replicate simulations, explaining previously unexplained variability in laboratory evolution experiments.
Why it matters
Understanding how cross-feeding evolves helps explain the structure and stability of microbial ecosystems, from soil bacteria to the human microbiome. This work suggests that metabolic cooperation may arise more readily than previously thought, which could inform strategies for engineering synthetic microbial communities for applications like bioremediation or industrial fermentation.
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⚠️ Preprint – Noch nicht peer-reviewed
Dieser Artikel wurde noch nicht von unabhängigen Experten begutachtet. Die Ergebnisse sind vorläufig und sollten mit Vorsicht interpretiert werden.
Cross-feeding relationships shape the composition of many microbial communities, yet the evolutionary processes that give rise to them remain poorly understood. Most theoretical and experimental work has therefore focused on minimal scenarios, particularly the stable cross-feeding polymorphisms that evolve in asexual populations growing on a single energy source (Helling et al., 1987). Yet replicate experiments do not always produce cross-feeding populations, raising the question of why genetically identical populations evolving under identical conditions can follow di[ff]erent evolutionary trajectories (Treves et al., 1998). Here we present a bare-bones agent-based model of evolution in a chemostat. We show that selection for energy acquisition alone is su[ffi]cient to promote the evolution of cross-feeding, without invoking mechanisms specific to metabolic exchange. The resulting communities nevertheless di[ff]er across replicate simulations, reproducing the qualitative variability observed experimentally.
Source: No Trade-Offs Required: Cross-Feeding From Survival Alone