bioRxiv Science⌕ Search

Biology subjects

Toledano, G.

Publications and source records attributed to Toledano, G..

2 recordsLinked to original sources

Evolution in microbial microcosms is highly parallel regardless of the presence of interacting species

During laboratory evolution, replicate bacterial populations often follow similar trajectories, thus their evolution is potentially predictable. However, predicting the evolution of natural populations, which are commonly embedded in multispecies communities, would prove extremely difficult if adaptations are contingent on the identity of the interacting species. The extent to which adaptations typically depend on coevolving partners remains poorly understood, since coevolution is commonly studied using small-scale experiments involving few species, making it challenging to extract general trends. To address this knowledge gap, we study the adaptations that occurred in strains of each of 11 species that were either evolved in monoculture or in multiple pairwise co-cultures. While we detect slight but significant partner-specific effects we find that the majority of evolutionary changes that occur are robust across strains that evolved with different partners; species growth abilities increase by a similar factor regardless of partners identity, shifts in community compositions and interactions are similar between pairs of coevolved and separately evolved strains, and the majority of parallelly mutated genes were detected in multiple biotic conditions. We hypothesized that these results might arise from the fact that ancestral strains are maladapted to the abiotic environment, thus having a pool of adaptations that are beneficial regardless of the biotic partners. Therefore, we conducted a second experiment with strains that were pre-adapted to the abiotic conditions before being co-cultured. We find that even after [~]400 generations of pre-adaptation, evolution is surprisingly non-partner-specific. Further work is required in order to elucidate the factors that influence partner-specificity of coevolution, but our results suggest that selection imposed by the biotic environment may play a secondary role to that imposed by abiotic conditions, making predictions regarding coevolutionary dynamics less challenging than previously thought.

evolutionary biology↗

Interactions between culturable bacteria are predicted by individual species' growth

Predicting interspecies interactions is a key challenge in microbial ecology, as such interactions shape the composition and functioning of microbial communities. However, predicting microbial interactions is challenging since they can vary considerably depending on species metabolic capabilities and environmental conditions. Here, we employ machine learning models to predict pairwise interactions between culturable bacteria based on their phylogeny, monoculture growth capabilities, and interactions with other species. We trained our models on one of the largest available pairwise interactions dataset containing over 7500 interactions between 20 species from 2 taxonomic groups that were cocultured in 40 different carbon environments. Our models accurately predicted both the sign (accuracy of 88%) and the strength of effects (R2 of 0.87) species had on each others growth. Encouragingly, predictions with comparable accuracy could be made even when not relying on information about interactions with other species, which are often hard to measure. However, species monoculture growth was essential to the model, as predictions based solely on species phylogeny and inferred metabolic capabilities were significantly less accurate. These results bring us a step closer to a predictive understanding of microbial communities, which is essential for engineering beneficial microbial consortia.

microbiology↗