Relationships between and formation dynamics of the microbiota of consumers, producers, and the environment in an abalone aquatic system

An ecosystem is a community comprising living and nonliving components of the environment. Microbes are ubiquitous elements in each of these components. The dynamics of microbiota formation in an ecosystem is important to elucidate, because how the different components of a system exchange microbes, and how the microbes control ecological processes remain unresolved. In this study, an abalone, Haliotis diversicolor, seed-nursing pond was used as a model system. We first examined changes in bacterial communities during the seedling cultivation of this herbivorous juvenile aquatic invertebrate animal. Denaturing gradient gel electrophoresis (DGGE) and pyrosequencing were used to analyze bacterial community dynamics and spatio-temporal interactions of different system components: consumers (abalone), producers (algae or a substrate), and the environment (water). DGGE fingerprints revealed that the developmental stages of abalone influences bacterial communities of both the abalone and substrate. Although the communities in water fluctuated daily, they could be divided into two clusters that coincided with abalone stages, reflecting the transition from larva to juvenile at around day 21. Pyrosequencing showed that the microbiota in the abalone and substrate had more operational taxonomic units in common than that of either with water. The Bray-Curtis similarity index was used to quantify the formation dynamics of microbiota among the various components of the system. The bacterial communities in producers and consumers showed similar changes. These communities were unstable at the beginning and then slowly stabilized over time. The environmental bacterial community was more stable than the bacterial communities in consumers and producers, and may have been the basis for stability in the system. Our research provides insights into the dynamics of microbiota formation in various biotic elements of a system that will contribute to predictive systems modeling.