Back

A defined community of core gut microbiota members promotes cognitive performance in honey bees

Cabirol, A.; Schafer, J.; Neuschwander, N.; Kesner, L.; Liberti, J.; Engel, P.

2023-01-04 animal behavior and cognition
10.1101/2023.01.03.522593 bioRxiv
Show abstract

The composition of the gut microbiota has recently been identified as a cause of cognitive variability in humans and animals. Germ-free individuals and individuals exposed to an antibiotic treatment show severe alteration of their learning and memory performance measured in various cognitive tasks. While different species of bacteria are known to interact in the gut, their cumulative or synergistic effects on cognitive performance remain elusive. Here we established a defined bacterial community - composed of core members of the corbiculate bee microbiota - which enhances honey bees cognitive capacities. Honey bees colonized with this reconstituted community discriminated better two odours based on the presence or absence of a sucrose reward compared to germ-free individuals. They also memorized better these odour-food associations in the short-term. These cognitive improvements seem to constitute an emergent property of the community, because they could not be recapitulated by any of the community members when mono-associated in gnotobiotic bees and they were not explained by the total biomass in the gut. The identification of this community and its effect on bees open new avenues of research in neuroscience, microbiology, and ecology. Future research should help understanding how interactions between bacterial species in the community promote the hosts associative learning and memory performance.

Published in Proceedings of the National Academy of Sciences (predicted rank #14) · training set

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.