Host-age prediction from fecal microbiome composition in laboratory mice

The life-long relationship between microorganisms and hosts has a profound impact on the overall health and physiology of the holobiont. Changes in microbiome composition throughout the lifespan of a host remain, however, largely understudied. In this study, the fecal microbiome of conventionally raised C57BL/6J mice was analyzed throughout almost the entire expected lifespan, from maturing (9 weeks) until very old age (112 weeks). Analysis of alpha and beta diversity suggests that gradual microbiome changes occur throughout the entire murine life but appear to be more pronounced in maturing to middle-aged phases. Phylum-level analysis indicates a shift in the Firmicutes/Bacteroidetes ratio in favor of the Firmicutes in the second year of adulthood. Varying successional patterns throughout life were observed for many Firmicutes OTUs, while relative abundances of Bacteroidetes OTUs varied primarily in the early life phases. Microbiome configurations at given time points were used as training sets in a Bayesian model, which in turn effectively enabled the prediction of host age. The fecal microbiome composition may therefore serve as an accurate biomarker for aging. This study further suggests that age-associated compositional differences may have considerable implications for the interpretation and comparability of animal model-based microbiome studies. ImportanceThe life-long relationship between microorganisms and hosts has a profound impact on the overall physiology of the holobiont. Understanding the extent of gut microbiome compositional changes over the expected mouse lifespan may allow to better understand the interplay of microbiome and the host at the different life stages. In this study, we performed a two-year longitudinal study of murine fecal microbiome. Using fine-scale microbiome profiling we were able to predict the host age from the fecal microbiome composition. Moreover, we observed that the rate of compositional change appears to slow with age. The description of the compositional changes in commonly used C57BL/6J mice can be used to optimize selection of age-associated mouse models and highlights the use of microbiome-profiling as biomarker for aging.