ABSTRACT
Microbial transmission is a major benefit of sociality, facilitated by affiliative behaviors such as grooming and communal nesting in group-living animals. The spread of microbial symbionts through these pathways, and their incorporation into host microbiomes, can enhance host health and fitness by contributing to pathogen protection and metabolic flexibility. Are pathways that facilitate microbial transfer across hosts also present in animals that do not form social groups because territoriality limits social interactions and prevents group formation? Here, we addressed this question by combining longitudinal sampling of individual gut microbial communities, demographic data, and dynamic behavioral and spatial measures of territoriality from a non-social, highly territorial small mammal: wild North American red squirrels (Tamiasciurus hudsonicus). As squirrel densities increased, individual gut microbial communities became richer and more phylogenetically diverse, while among-individual differences in composition decreased. This pattern was characterized primarily by increases in obligately anaerobic and non-sporulating taxa with little to no tolerance for oxygen-rich environments, suggesting social rather than environmental routes of transmission. Moreover, territorial intrusions—in which conspecifics were found on within an individual’s territorial space—increased gut microbial diversity among individuals defending larger territorial spaces. Using an intrusion-based social network analysis, we found that that pairs with stronger social association (via intrusions) exhibited higher gut microbial similarity. Taken together, our findings provide some of the first evidence for social microbial transmission in a non-social species, and suggest that increased density and territorial behavior can diversify and homogenize host gut microbial communities despite social isolation.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
Competing interests: The authors declare no competing financial interests.
DATA AVAILABILITY STATEMENT
All data and code associated with this manuscript will be made publicly and freely accessible at the following FigShare repository at the time of publication: https://figshare.com/s/a79d2e1603fe55ac91ce. The code for social network analysis and Bayesian dyadic models can be found from AR’s github page: https://github.com/nuorenarra. Raw sequence data has been submitted to NCBI Sequence Read Archive.