Aging gut microbiota of wild macaques are equally diverse, less stable, but progressively personalized

Abstract

Background Pronounced heterogeneity of age trajectories has been identified as a hallmark of the gut microbiota in humans and has been explained by marked changes in lifestyle and health condition. Comparatively, age-related personalization of microbiota is understudied in natural systems limiting our comprehension of patterns observed in humans from ecological and evolutionary perspectives. Results Here, we tested age-related changes in the diversity, stability, and composition of the gut bacterial community using 16S rRNA gene sequencing with dense repeated sampling over three seasons in a cross-sectional age sample of adult female Assamese macaques (Macaca assamensis) living in their natural forest habitat. Gut bacterial composition exhibited a personal signature which became less stable as individuals aged. This lack of stability was not explained by differences in microbiota diversity but rather linked to an increase in the relative abundance of rare bacterial taxa. The lack of age-related changes in core taxa or convergence with age to a common state of the community hampered predicting gut bacterial composition of aged individuals. On the contrary, we found increasing personalization of the gut bacterial composition with age, indicating that composition in older individuals was increasingly divergent from the rest of the population. Reduced direct transmission of bacteria resulting from decreasing social activity may contribute to, but not be sufficient to explain, increasing personalization with age. Conclusions Together, our results challenge the assumption of a constant microbiota through adult life in a wild primate. Within the limits of this study, the fact that increasing personalization of the aging microbiota is not restricted to humans suggests the underlying process to be evolved instead of provoked only by modern lifestyle of and health care for the elderly.

Individualized composition or community dynamics? A new statistical approach to assess the individuality of host-associated microbiomes

“…Some of these studies show a large effect of individual identity on the microbiome over a period of two months [1], 1.5 years [2], 2 years [3] or 8 years [4]. However, in two of these cases [2,4], the effects were time dependent. Other longitudinal studies of the microbiome where individuals were repeatedly sampled over long periods of time include individual identity as a random effect in their statistical models to control for individual variation, but do not directly test what proportion of the variation is explained by identity [5][6][7].…”

“…The individuality of the microbiome has been examined previously over various timescales, but primarily using comparisons of within versus between individual similarity. Some of these studies show a large effect of individual identity on the microbiome over a period of two months [1], 1.5 years [2], 2 years [3] or 8 years [4]. However, in two of these cases [2,4], the effects were time dependent.…”

Assessing longitudinal gut microbiome dynamics in relation to age and senescence in a wild animal population

“…Thus, we also tested for greater intra-and inter-individual variation amongst samples taken in older age groups. Such heterogeneity has previously been identi ed in humans [15,46] and wild macaques (Macaca assamensis) [30]. We extended this research by also testing whether GM variation is greatest during the terminal year due to greater instability.…”

“…However, no clear consensus has emerged from this research. Whilst some studies have reported shifts in GM composition [28,29] and greater GM heterogeneity with increasing age [30], others have found that GM dynamics and overall composition remain largely invariable throughout adulthood [31][32][33].…”

Circadian rhythms of hosts and their gut microbiomes: Implications for animal physiology and ecology

“…Although age‐dependent changes to gut microbial composition are known from a variety of wildlife species (Barbosa et al, 2016; Risely et al, 2022; Sadoughi et al, 2022), it remains unknown how changes in composition relate to changes in rhythms. Exploiting systems with high survival rates that have previously been used to model senescence and demography, such as seabirds (Fay et al, 2018; Patrick & Weimerskirch, 2015) or long‐lived mammals (Robinson et al, 2012), may help clarify this question.…”