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Deterministic and stochastic processes generating alternative states of microbiomes

Ibuki Hayashi, Hiroaki Fujita, Hirokazu Toju

2024ISME Communications32 citationsDOIOpen Access PDF

Abstract

The structure of microbiomes is often classified into discrete or semi-discrete types potentially differing in community-scale functional profiles. Elucidating the mechanisms that generate such "alternative states" of microbiome compositions has been one of the major challenges in ecology and microbiology. In a time-series analysis of experimental microbiomes, we here show that both deterministic and stochastic ecological processes drive divergence of alternative microbiome states. We introduced species-rich soil-derived microbiomes into eight types of culture media with 48 replicates, monitoring shifts in community compositions at six time points (8 media × 48 replicates × 6 time points = 2304 community samples). We then confirmed that microbial community structure diverged into a few state types in each of the eight medium conditions as predicted in the presence of both deterministic and stochastic community processes. In other words, microbiome structure was differentiated into a small number of reproducible compositions under the same environment. This fact indicates not only the presence of selective forces leading to specific equilibria of community-scale resource use but also the influence of demographic drift (fluctuations) on the microbiome assembly. A reference-genome-based analysis further suggested that the observed alternative states differed in ecosystem-level functions. These findings will help us examine how microbiome structure and functions can be controlled by changing the "stability landscapes" of ecological community compositions.

Topics & Concepts

MicrobiomeCommunity structureEcologyBiologyScale (ratio)EcosystemDivergence (linguistics)CommunityEvolutionary biologyComputational biologyBioinformaticsGeographyCartographyPhilosophyLinguisticsGut microbiota and healthEvolutionary Game Theory and CooperationEvolution and Genetic Dynamics
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