Ant microbial endosymbionts and the emergent properties of social groups

EasyChair Preprint 1661

Abstract

In the last fifteen years, research on animal models has provided advances on how gut symbiotic microbes affect behavior and its underlying neurophysiology in animals, including humans. However, most studies on the gut microbiota only take into exam individual behavior without considering social dynamics. Contrarily, animals and humans live in complex societies where they constantly adjust physiology and behavior to social interactions. Therefore, to improve our understanding of how microbes and hosts interact and produce functional individual, social and collective phenotypes, we need to open our experimental approach to the group-level dimension. The ideal models for this purpose are social animals living in stable symbioses with microbes, such as eusocial insects. In our research, we investigate Camponotus carpenter ants and their obligate bacterial symbiont Blochmannia from a behavioral ecology perspective. By suppressing Blochmannia in single individuals using antibiotics, we aim to create ant colonies including differential proportions of bacteria-free individuals; then, using a machine learning-based video tracking system, we plan to study network features and group-level behavior of such experimental colonies.

Keyphrases: Group-Level Behavior, Microbiota-Gut-Brain Axis, Real Time Data Analysis, ants, machine learning, social evolution

@booklet{EasyChair:1661,
  author    = {Alessio Sclocco and Shirlyn Jia Yun Ong and Serafino Teseo},
  title     = {Ant microbial endosymbionts and the emergent properties of social groups},
  howpublished = {EasyChair Preprint 1661},
  year      = {EasyChair, 2019}}