Replicating community dynamics reveals how initial composition shapes the functional outcomes of bacterial communities

Pascual-García, A ORCID: https://orcid.org/0000-0002-8444-3196, Rivett, DW ORCID: https://orcid.org/0000-0002-1852-6137, Jones, Matt Lloyd ORCID: https://orcid.org/0000-0001-5841-4554 and Bell, T ORCID: https://orcid.org/0000-0002-2615-3932 (2025) Replicating community dynamics reveals how initial composition shapes the functional outcomes of bacterial communities. Nature Communications, 16 (1). 3002. ISSN 2041-1723

Preview	Published Version Available under License Creative Commons Attribution. Download (2MB) | Preview
Preview	Supplemental Material Available under License Creative Commons Attribution. Download (5MB) | Preview

Abstract

Bacterial communities play key roles in global biogeochemical cycles, industry, agriculture, 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 assess the reproducibility and predictability of bacterial community dynamics by creating a frozen archive of hundreds of naturally-occurring bacterial communities that we repeatedly revive and track in a standardised, complex resource environment. Replicate communities follow reproducible trajectories and the community dynamics closely map to ecosystem functioning. However, even under standardised conditions, the communities exhibit tipping-points, where small differences in initial community composition create divergent compositional and functional outcomes. The predictability of community trajectories therefore 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. Our results shed light on the relationship between composition and function, opening new avenues to understand the feasibility and limitations of function prediction in complex microbial communities.