Human gut microbial dynamics are highly individualized, making it challenging to link microbiota to health and to design universal microbiome therapies. This individuality is typically attributed to variation in host genetics, diets, environments and medications but it could also emerge from fundamental ecological forces that shape microbiota more generally. Here, we leverage extensive gut microbial time series from wild baboons—hosts who experience little interindividual dietary and environmental heterogeneity—to test whether gut microbial dynamics are synchronized across hosts or largely idiosyncratic. Despite their shared lifestyles, baboon microbiota were only weakly synchronized. The strongest synchrony occurred among baboons living in the same social group, probably because group members range over the same habitat and simultaneously encounter the same sources of food and water. However, this synchrony was modest compared to each host’s personalized dynamics. In support, host-specific factors, especially host identity, explained, on average, more than three times the deviance in longitudinal dynamics compared to factors shared with social group members and ten times the deviance of factors shared across the host population. These results contribute to mounting evidence that highly idiosyncratic gut microbiomes are not an artefact of modern human environments and that synchronizing forces in the gut microbiome (for example, shared environments, diets and microbial dispersal) are not strong enough to overwhelm key drivers of microbiome personalization, such as host genetics, priority effects, horizontal gene transfer and functional redundancy.
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Analysed data and code are available on the JRB’s Open Science Framework/GitHub repository at https://doi.org/10.17605/OSF.IO/ERDXA
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We thank J. Altmann for her essential role in stewarding the Amboseli Baboon Project and in collecting and maintaining the faecal samples used in this manuscript. This work was supported by the National Science Foundation (NSF) and the National Institutes of Health (NIH), especially NSF Rules of Life Award DEB1840223 (E.A.A. and J.A.G.) and the National Institute on Aging R21AG055777 (E.A.A. and R.B.) and NIH R01AG053330 (E.A.A.), NIH R01AG071684 (E.A.A.) and NIHR35 GM128716 (R.B.), the Duke University Population Research Institute P2C-HD065563 (pilot to J.T.), the University of Notre Dame’s Eck Institute for Global Health (E.A.A.) and the Notre Dame Environmental Change Initiative (E.A.A.). Since 2000, long-term data collection in Amboseli has been supported by NSF and NIH, including IOS1456832 (S.C.A.), IOS1053461 (E.A.A.), DEB1405308 (J.T.), IOS0919200 (S.C.A.), DEB0846286 (S.C.A.), DEB0846532 (S.C.A.), IBN0322781 (S.C.A.), IBN0322613 (S.C.A.), BCS0323553 (S.C.A.), BCS0323596 (S.C.A.), P01AG031719 (S.C.A.), R21AG049936 (J.T. and S.C.A.), R03AG045459 (J.T. and S.C.A.), R01AG034513 (S.C.A.), R01HD088558 (J.T.) and P30AG024361 (S.C.A.). We also especially thank the members of the Maasai pastoralist communities in the Amboseli-Longido areas. We thank the Kenya Wildlife Service, Kenya’s Wildlife Research & Training Institute, the National Council for Science, Technology and Innovation and the National Environment Management Authority for permission to conduct research and collect biological samples in Kenya. We also thank the University of Nairobi, Institute of Primate Research, National Museums of Kenya, the Enduimet Wildlife Management Area, Ker & Downey Safaris, Air Kenya and Safarilink for their cooperation and assistance in the field. We thank K. Pinc for managing and designing the database. We also thank T. Voyles, A. Dumaine, Y. Zhang, M. Rao, T. Vilgalys, A. Lea, N. Snyder-Mackler, P. Durst, J. Zussman, G. Chavez and R. Debray for contributing to faecal sample processing. Complete acknowledgements for the ABRP can be found online at https://amboselibaboons.nd.edu/acknowledgements/.
The authors declare no competing interests.
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Supplementary Methods and Figs. 1–26.
Animation of home range use by the five original social groups, as defined in Fig. 1. This animation shows the geographical location of each social group over time, with the x axis showing longitude and the y axis latitude. Each dot represents the average monthly longitude and latitude per social group and month. While solid dots represent the groups’ current position in the focal month and hydrological year, the hollow circles show previous locations, thus outlining each social group’s total home range area over time.
Animation of the microbiome PC1 and PC2 for baboons living in the five original social groups, as defined in Fig. 1. To make this animation, we first averaged the PC1 and PC2 sample scores by host and collection date, such that each host only has one value per collection date. We then ‘filled in’ missing collection dates and performed a 30-d sliding window analysis (step size = 1). Each frame (image) in the animation corresponds to one sliding window. The date in the top left corner corresponds to the first date of each window and each dot represents one individual host coloured by its social group.
Supplementary Tables 1–9.
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Björk, J.R., Dasari, M.R., Roche, K. et al. Synchrony and idiosyncrasy in the gut microbiome of wild baboons. Nat Ecol Evol 6, 955–964 (2022). https://doi.org/10.1038/s41559-022-01773-4
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