Abstract
Longitudinal sampling for intestinal microbiota in wild animals is difficult, leading to a lack of information on bacterial dynamics occurring in nature. We studied how the composition of microbiota communities changed temporally in free-ranging small primates, rufous mouse lemurs (Microcebus rufus). We marked and recaptured mouse lemurs during their mating season in Ranomafana National Park in southeastern mountainous rainforests of Madagascar for 2 years and determined the fecal microbiota compositions of these mouse lemurs with MiSeq sequencing. We collected 160 fecal samples from 71 animals and had two or more samples from 39 individuals. We found small, but statistically significant, effects of site and age on microbiota richness and diversity and effects of sex, year, and site on microbiota composition, while the within-year temporal trends were less clear. Within-host microbiota showed pervasive variation in intestinal bacterial community composition, especially during the second study year. We hypothesize that the biological properties of mouse lemurs, including their small body size and fast metabolism, may contribute to the temporal intraindividual-level variation, something that should be testable with more-extensive sampling regimes. IMPORTANCE: While microbiome research has blossomed in recent years, there is a lack of longitudinal studies on microbiome dynamics on free-ranging hosts. To fill this gap, we followed mouse lemurs, which are small heterothermic primates, for 2 years. Most studied animals have shown microbiota to be stable over the life span of host individuals, but some previous research also found ample within-host variation in microbiota composition. Our study used a larger sample size than previous studies and a study setting well suited to track within-host variation in free-ranging mammals. Despite the overall microbiota stability at the population level, the microbiota of individual mouse lemurs can show large-scale changes in composition in time periods as short as 2 days, suggesting caution in inferring individual-level patterns from population-level data.