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Community composition of microbial microcosms follows simple assembly rules at evolutionary timescales.

ABSTRACT: Managing and engineering microbial communities relies on the ability to predict their composition. While progress has been made on predicting compositions on short, ecological timescales, there is still little work aimed at predicting compositions on evolutionary timescales. Therefore, it is still unknown for how long communities typically remain stable after reaching ecological equilibrium, and how repeatable and predictable are changes when they occur. Here, we address this knowledge gap by tracking the composition of 87 two- and three-species bacterial communities, with 3-18 replicates each, for ~400 generations. We find that community composition typically changed during evolution, but that the composition of replicate communities remained similar. Furthermore, these changes were predictable in a bottom-up approach-changes in the composition of trios were consistent with those that occurred in pairs during coevolution. Our results demonstrate that simple assembly rules can hold even on evolutionary timescales, suggesting it may be possible to forecast the evolution of microbial communities.

SUBMITTER: Meroz N

PROVIDER: S-EPMC8113234 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Understanding spatiotemporal patterns in microbial community composition is a central goal of microbial ecology. The objective of this study was to better understand the biogeography of activated sludge microbial communities, which are important for the protection of surface water quality. Monthly samples were collected from 20 facilities (25 bioreactors) within 442 km of each other for 1 year. Microbial community composition was characterized by sequencing of PCR-amplified 16S rRNA gene fragments. Statistically significant distance decay of community similarity was observed in these bioreactors independent of clustering method (operational taxonomic units [OTUs] at 97% similarity, genus-level phylotypes) and community dissimilarity metric (Sørensen, Bray-Curtis, and weighted Unifrac). Universal colonizers (i.e., detected in all samples) and ubiquitous genus-level phylotypes (i.e., detected in every facility at least once) also exhibited a significant distance decay relationship. Variation partitioning analysis of community composition showed that environmental characteristics (temperature, influent characteristics, etc.) explained more of the variance in community composition than geographic distance did, suggesting that environmental heterogeneity is more important than dispersal limitation as a mechanism for determining microbial community composition. Distance decay relationships also became stronger with increasing distance between facilities. Seasonal variation in community composition was also observed from selected bioreactors, but there was no clear seasonal pattern in the distance decay relationships. IMPORTANCE Understanding the spatiotemporal patterns of biodiversity is a central goal of ecology. The distance decay of community similarity is one of the spatial scaling patterns observed in many forms of life, including plants, animals, and microbial communities. Municipal wastewater treatment relies on microorganisms to prevent the release of excessive quantities of nutrients and other pollutants, but relatively few studies have explored distance decay relationships in wastewater treatment bioreactors. Our results demonstrate a strong distance decay pattern in wastewater treatment bioreactors, regardless of the sequence clustering method or the community dissimilarity metric. Our results suggest that microbial communities in wastewater treatment bioreactors are not randomly assembled but rather exhibit a statistically significant spatial pattern.

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Community composition of microbial microcosms follows simple assembly rules at evolutionary timescales.

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