A Study of Sponge Symbionts from Different Light Habitats

The amount of available light plays a key role in the growth and development of microbial communities. In the present study, we tested to what extent sponge-associated prokaryotic communities differed between specimens of the sponge species Cinachyrella kuekenthali and Xestospongia muta collected in dimly lit (caves and at greater depths) versus illuminated (shallow water) habitats. In addition to this, we also collected samples of water, sediment, and another species of Cinachyrella, C. alloclada. Overall, the biotope (sponge host species, sediment, and seawater) proved the major driver of variation in prokaryotic community composition. The light habitat, however, also proved a predictor of compositional variation in prokaryotic communities of both C. kuekenthali and X. muta. We used an exploratory technique based on machine learning to identify features (classes, orders, and OTUs), which distinguished X. muta specimens sampled in dimly lit versus illuminated habitat. We found that the classes Alphaproteobacteria and Rhodothermia and orders Puniceispirillales, Rhodospirillales, Rhodobacterales, and Thalassobaculales were associated with specimens from illuminated, i.e., shallow water habitat, while the classes Dehalococcoidia, Spirochaetia, Entotheonellia, Nitrospiria, Schekmanbacteria, and Poribacteria, and orders Sneathiellales and Actinomarinales were associated with specimens sampled from dimly lit habitat. There was, however, considerable variation within the different light habitats highlighting the importance of other factors in structuring sponge-associated bacterial communities.

Automated summary

The amount of available light is crucial for the growth and development of microbial communities. This study investigates the differences in prokaryotic communities associated with two sponge species, Cinachyrella kuekenthali and Xestospongia muta, collected from dimly lit and illuminated habitats. The biotope was found to be the major driver of variation in prokaryotic community composition, while the light habitat also influenced the composition of prokaryotic communities in both sponge species. Machine learning was used to identify features that distinguished specimens collected from dimly lit and illuminated habitats.