Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1174886 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Prokaryote community associated to sponges (16S1)
| PRJEB60091 | ENA
Project description:microbial community associated to Homoscleromorpha sponges
| PRJEB50148 | ENA
Project description:Marine sponges (phylum Porifera) are leading organisms for the discovery of bioactive compounds from nature. Their often rich and species-specific microbiota is hypothesised to be producing many of these compounds. Yet, environmental influences on the sponge-associated microbiota and bioactive compound production remain elusive. Here, we investigated the changes of microbiota and metabolomes in sponges along a depth range of 1232 m. Using 16S rRNA gene amplicon sequencing and untargeted metabolomics, we assessed prokaryotic and chemical diversities in three deep-sea sponge species: Geodia barretti, Stryphnus fortis, and Weberella bursa. Both prokaryotic communities and metabolome varied significantly with depth, which we hypothesized to be the effect of different water masses. Up to 35.5% of microbial ASVs (amplicon sequence variants) showed significant changes with depth while phylum-level composition of host microbiome remained unchanged. The metabolome varied with depth, with relative quantities of known bioactive compounds increasing or decreasing strongly. Other metabolites varying with depth were compatible solutes regulating osmolarity of the cells. Correlations between prokaryotic community and the bioactive compounds in G. barretti suggested members of Acidobacteria, Proteobacteria, Chloroflexi, or an unclassified prokaryote as potential producers.
2023-05-12 | MTBLS1388 | MetaboLights
Project description:Characterization of the microbial community associated to Homoscleromorpha sponges
| PRJEB44409 | ENA
Project description:Bacteriophage – host dynamics and interactions are important for microbial community composition and ecosystem function. Nonetheless, empirical evidence in engineered environment is scarce. Here, we examined phage and prokaryotic community composition of four anaerobic digestors in full-scale wastewater treatment plants (WWTPs) across China. Despite relatively stable process performance in biogas production, both phage and prokaryotic groups fluctuated monthly over a year of study period. Nonetheless, there were significant correlations in their α- and β-diversities between phage and prokaryotes. Phages explained 40.6% of total prokaryotic community composition, much higher than the explainable power by abiotic factors (14.5%). Consequently, phages were significantly (P<0.010) linked to parameters related to process performance including biogas production and volatile solid concentrations. Association network analyses showed that phage-prokaryote pairs were deeply rooted, and two network modules were exclusively comprised of phages, suggesting a possibility of co-infection. Those results collectively demonstrate phages as a major biotic factor in controlling bacterial composition. Therefore, phages may play a larger role in shaping prokaryotic dynamics and process performance of WWTPs than currently appreciated, enabling reliable prediction of microbial communities across time and space.
2016-12-29 | GSE92978 | GEO
Project description:The interaction of animals with microbes relies on the specific recognition of microbial-derived molecules by receptors of the immune system. Sponges (phylum Porifera), as sister group of the Eumetazoa, provide insights into conserved mechanisms for animal-microbe crosstalk, but empirical data is limited. Here we aimed to characterize the immune response of sponges upon microbial stimuli by RNA-Seq. Two sponges species from the Mediterranean Sea, Aplysina aerophoba and Dysidea avara, were challenged with microbial-associated molecular patterns (lipopolysaccharide and peptidoglycan) or sterile artificial seawater (control) in aquarium experiments. Sponge tissue samples were collected 1h, 3h, and 5h after treatment. The response of the sponges to the treatments was assessed by differential gene expression analysis of RNA-Seq data. For each species, we compared the transcriptomic profiles of the samples in MAMP treatment to control within each time point.
2018-11-26 | E-MTAB-6757 | biostudies-arrayexpress