Replaying the tape of ecology to domesticate wild microbiota
preprint
OA: closed
CC-BY-NC-ND-4.0
Abstract
Humanity has benefited from the domestication of nature and there is an increasing need to predict and control ecosystems. Domesticating bacterial communities would be particularly useful. Bacterial communities play key roles in global biogeochemical cycles, in industry (e.g. sewage treatment, fermented food and drink manufacturing), in agriculture (e.g. by fixing nitrogen and suppressing pathogens), and in human health and animal husbandry. There is therefore great interest in understanding bacterial community dynamics so that they can be controlled and engineered to optimise ecosystem services. We assessed the reproducibility and predictability of bacterial community dynamics by creating a frozen archive of hundreds of naturally-occuring bacterial communities that were repeatedly revived and tracked in a standardised, complex environment. Replicate communities followed reproducible trajectories and the community dynamics could be closely mapped to ecosystem functioning. However, even under standardised conditions, the communities exhibited tipping-points, where a small difference in initial community composition created divergent outcomes. We accurately predicted ecosystem outcomes based on initial bacterial community composition, and identified the conditions under which divergent ecosystem outcomes may be expected. In conclusion, we have shown the feasibility of our approach to reproducibly achieve predictable compositions and functions from wild communities. Nonetheless, the predictability of community trajectories, and therefore their utility in domestication, requires detailed knowledge of rugged compositional landscapes where ecosystem properties are not the inevitable result of prevailing environmental conditions but can be tilted toward different outcomes depending on the initial community composition.
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- europepmc
- last seen: 2026-05-19T01:45:01.086888+00:00
- unpaywall
- last seen: 2026-05-22T02:00:06.705733+00:00
License: CC-BY-NC-ND-4.0