Metabarcoding of bacterial and foraminifera communities
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB32436 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR3309080_1.fastq.gz | Fastqsanger.gz | |||
| ERR3309080_2.fastq.gz | Fastqsanger.gz | |||
| ERR3309090_1.fastq.gz | Fastqsanger.gz | |||
| ERR3309090_2.fastq.gz | Fastqsanger.gz | |||
| ERR3309730_1.fastq.gz | Fastqsanger.gz |
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Project description:Foraminifera are ubiquitous marine protists with an important role in the benthic carbon cycle. However, morphological observations often fail to resolve their exact taxonomic placement and there is a lack of field studies on their particular trophic preferences. Here, we propose the application of metabarcoding as a tool for the elucidation of the in situ feeding behavior of benthic foraminifera, while also allowing the correct taxonomic assignment of the feeder, using the V9 region of the 18S (small subunit; SSU) rRNA gene. Living foraminiferal specimens were collected from two intertidal mudflats of the Wadden Sea and DNA was extracted from foraminiferal individuals and from the surrounding sediments. Molecular analysis allowed us to confirm that our foraminiferal specimens belong to three genetic types: Ammonia sp. T6, Elphidium sp. S5 and Haynesina sp. S16. Foraminiferal intracellular eukaryote communities reflected to an extent those of the surrounding sediments but at different relative abundances. Unlike sediment eukaryote communities, which were largely determined by the sampling site, foraminiferal intracellular eukaryote communities were driven by foraminiferal species, followed by sediment depth. Our data suggests that Ammonia sp. T6 can predate on metazoan classes, whereas Elphidium sp. S5 and Haynesina sp. S16 are more likely to ingest diatoms. These observations, alongside the use of metabarcoding in similar ecological studies, significantly contribute to our overall understanding of the ecological roles of these protists in intertidal benthic environments and their position and function in the benthic food webs.
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Project description:Foraminifera are unicellular eukaryotes that are an integral part of benthic fauna in many marine ecosystems, including the deep sea, with direct impacts on benthic biogeochemical cycles. In these systems, different foraminiferal species are known to have a distinct vertical distribution, i.e., microhabitat preference, which is tightly linked to the physico-chemical zonation of the sediment. Hence, foraminifera are well-adapted to thrive in various conditions, even under anoxia. However, despite the ecological and biogeochemical significance of foraminifera, their ecology remains poorly understood. This is especially true in terms of the composition and diversity of their microbiome, although foraminifera are known to harbor diverse endobionts, which may have a significant meaning to each species' survival strategy. In this study, we used 16S rRNA gene metabarcoding to investigate the microbiomes of five different deep-sea benthic foraminiferal species representing differing microhabitat preferences. The microbiomes of these species were compared intra- and inter-specifically, as well as with the surrounding sediment bacterial community. Our analysis indicated that each species was characterized with a distinct, statistically different microbiome that also differed from the surrounding sediment community in terms of diversity and dominant bacterial groups. We were also able to distinguish specific bacterial groups that seemed to be strongly associated with particular foraminiferal species, such as the family Marinilabiliaceae for Chilostomella ovoidea and the family Hyphomicrobiaceae for Bulimina subornata and Bulimina striata. The presence of bacterial groups that are tightly associated to a certain foraminiferal species implies that there may exist unique, potentially symbiotic relationships between foraminifera and bacteria that have been previously overlooked. Furthermore, the foraminifera contained chloroplast reads originating from different sources, likely reflecting trophic preferences and ecological characteristics of the different species. This study demonstrates the potential of 16S rRNA gene metabarcoding in resolving the microbiome composition and diversity of eukaryotic unicellular organisms, providing unique in situ insights into enigmatic deep-sea ecosystems.
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Project description:Traditional biomarkers for hydrocarbon exposure are not induced by all petroleum substances. The objective of this study was to determine if exposure to a crude oil and different refined oils would generate a common hydrocarbon-specific response in gene expression profiles that could be used as generic biomarkers of hydrocarbon exposure. Juvenile rainbow trout (Oncorhynchus mykiss) were exposed to the water accommodated fraction (WAF) of either kerosene, gas oil, heavy fuel oil, or crude oil for 96 hours. Tissue was collected for RNA extraction and microarray analysis. Exposure to each WAF resulted in a different list of differentially regulated genes, with few genes in common across treatments. Exposure to crude oil WAF changed the expression of genes including CYP1A and GST with known roles in detoxification pathways. These gene expression profiles were compared to others from previous experiments which used a diverse suite of toxicants. Clustering algorithms successfully i dentified gene expression profiles resulting from hydrocarbon exposure. These preliminary analyses highlight the difficulties of using single genes as diagnostic of petroleum hydrocarbon exposures. Further work is needed to determine if multivariate transcriptomic-based biomarkers may be a more effective tool than single gene studies for exposure monitoring of different oils.
2009-12-15 | GSE19483 | GEO
Project description:Traditional biomarkers for hydrocarbon exposure are not induced by all petroleum substances. The objective of this study was to determine if exposure to a crude oil and different refined oils would generate a common hydrocarbon-specific response in gene expression profiles that could be used as generic biomarkers of hydrocarbon exposure. Juvenile rainbow trout (Oncorhynchus mykiss) were exposed to the water accommodated fraction (WAF) of either kerosene, gas oil, heavy fuel oil, or crude oil for 96 hours. Tissue was collected for RNA extraction and microarray analysis. Exposure to each WAF resulted in a different list of differentially regulated genes, with few genes in common across treatments. Exposure to crude oil WAF changed the expression of genes including CYP1A and GST with known roles in detoxification pathways. These gene expression profiles were compared to others from previous experiments which used a diverse suite of toxicants. Clustering algorithms successfully i dentified gene expression profiles resulting from hydrocarbon exposure. These preliminary analyses highlight the difficulties of using single genes as diagnostic of petroleum hydrocarbon exposures. Further work is needed to determine if multivariate transcriptomic-based biomarkers may be a more effective tool than single gene studies for exposure monitoring of different oils. Two channel experiment; control versus exposed (samples were time matched). 3 biological replicates, three technical replicates for both exposed and control fish. Samples were paired at random. One replicate per array
2010-05-18 | E-GEOD-19483 | biostudies-arrayexpress
Project description:Since the advent of DNA metabarcoding surveys, the planktonic realm is considered a treasure trove of diversity, inhabited by a small number of abundant taxa, and a hugely diverse and taxonomically uncharacterized consortium of rare species. Here we assess if the apparent underestimation of plankton diversity applies universally. We target planktonic foraminifera, a group of protists whose known morphological diversity is limited, taxonomically resolved and linked to ribosomal DNA barcodes. We generated a pyrosequencing dataset of ~100,000 partial 18S rRNA foraminiferal sequences from 32 size fractioned photic-zone plankton samples collected at 8 stations in the Indian and Atlantic Oceans during the Tara Oceans expedition (2009-2012). We identified 69 genetic types belonging to 41 morphotaxa in our metabarcoding dataset. The diversity saturated at local and regional scale as well as in the three size fractions and the two depths sampled indicating that the diversity of foraminifera is modest and finite. The large majority of the newly discovered lineages occur in the small size fraction, neglected by classical taxonomy. These unknown lineages dominate the bulk [>0.8?µm] size fraction, implying that a considerable part of the planktonic foraminifera community biomass has its origin in unknown lineages.
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