Freshwater metagenome
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA257094 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR873436.fastq.gz | Fastqsanger.gz |
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To collect the metabolite profile, sterile monocultures of the 31 phytoplankton strains were grown under identical conditions. When each strain reached carrying capacity, the culture was filtered through a 0.22um filter, removing all phytoplankton cells. This filtrate was then acidified to a pH of 2.5 and stored at 4C for 2-29 hours, until it could be processed through the solid phase extraction column. To prep the column, 1 cartridge volume (1mL) of 100% methanol was passed through the column. Once the column was prepped, 50mL of cell-free, acidified culture was passed through the column to collect the organic material. The column was cleaned with 2 cartridge volume of 0.01M HCl and air dried for 5 minutes. The sample was eluted into a deep-well plate over dry ice with 1mL of 100% methanol. The plates were stored at -80C until ready for processing.
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2014-03-11 | PXD000206 | Pride
Project description:The spring bloom in the North Atlantic develops over a few weeks in response to the physical stabilization of the nutrient replete water column and is one of the biggest biological signals on earth. The composition of the phytoplankton assemblage during the spring bloom of 2008 was evaluated, using a microarray, on the basis of functional genes that encode key enzymes in nitrogen and carbon assimilation in eukaryotic and prokaryotic phytoplankton. Oligonucleotide archetype probes representing RuBisCO, nitrate reductase and nitrate transporter genes from major phytoplankton classes detected a diverse assemblage. For RuBisCO, the archetypes with strongest signals represented known phytoplankton groups, but for the nitrate related genes, the major signals were not closely related to any known phytoplankton sequences. Most of the assemblage's components exhibited consistent temporal/spatial patterns. Yet, the strongest archetype signals often showed quite different patterns, indicating different ecological responses by the main players. The most abundant phytoplankton genera identified previously by microscopy, however, were not well represented on the microarray. The lack of sequence data for well-studied species, and the inability to identify organisms associated with functional gene sequences in the environment, still limits our understanding of phytoplankton ecology even in this relatively well-studied system.
2016-05-11 | GSE81262 | GEO
Project description:Seasonal changes in nitrogen assimilation have been studied in the western English Channel by sampling at approximately weekly intervals for 12 months. Nitrate concentrations showed strong seasonal variations. Available nitrogen in the winter was dominated by nitrate but this was close to limit of detection from May to September, after the spring phytoplankton bloom. 15N uptake experiments showed that nitrate was the nitrogen source for the spring phytoplankton bloom but regenerated nitrogen supported phytoplankton productivity throughout the summer. The average annual f ratio was 0.35, which demonstrated the importance of ammonia regeneration in this dynamic temperate region. Nitrogen uptake rate measurements were related to the phytoplankton responsible by assessing the relative abundance of nitrate reductase (NR) genes and the expression of NR among eukaryotic phytoplankton. Strong signals were detected from NR sequences that are not associated with known phylotypes or cultures. NR sequences from the diatom Phaeodactylum tricornutum were highly represented in gene abundance and expression, and were significantly correlated with f ratio. The results demonstrate that analysis of functional genes provides additional information, and may be able to give better indications of which phytoplankton species are responsible for the observed seasonal changes in f ratio than microscopic phytoplankton identification.
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Project description:Emiliania huxleyi: Cellular cascades induced by bacterial algicides Interactions between phytoplankton and bacteria play a central role in mediating oceanic biogeochemical cycling and microbial trophic structure in the ocean. The intricate relationships between these two domains of life are mediated via excreted molecules that facilitate communication and determine competitive outcomes. Yet, despite their predicted importance, identifying these secreted compounds and understanding their ecological significance has remained a challenge. Research in the Whalen Lab endeavors to (i) identify those bacterially-derived chemical signaling compounds (i.e. infochemicals) that mediate phytoplankton population dynamics, and (ii) determine the underlying physiological processes that contribute to phytoplankton tolerance or susceptibility to these compounds. Recently, the Whalen lab isolated an alkylquinolone-signaling molecule with known quorum sensing function from the globally distributed marine γ-proteobacteria, Pseudoalteromonas sp. capable of inducing species-specific phytoplankton mortality. This research was the first to suggest quorum sensing compounds have expanded and previously unrecognized ecological roles in regulating primary production and phytoplankton bloom dynamics. We are now investigating in how this alkylquinolone induces phytoplankton mortality via transcriptomic profiling and diagnostic biochemical analysis. Complementary to this transcriptomic examination, we will complete whole-cell proteomic approach to identify those phytoplankton proteins crucial in competitive interactions with bacterial infochemicals, but whose functions may not yet be known. With this proteomic approach in parallel to our transcriptomic investigation, we can establish a better understanding of the eukaryotic macromolecular targets and cellular cascades induced in response to bacterial algicides like alkylquinolones. With the knowledge gained from both approaches we can begin to address how these ?keystone molecules? influence population dynamics and community composition of phytoplankton and bacteria in field-based experiments with the goal of defining a new mechanistic framework for how bacterially derived signaling molecules influence biogeochemical cycles. D= DMSO - control treatment L= low 1 nm HHG additions M= medium 10 nm HHG additions H= high 100 nm HHG additions Each treatment had 4 biological replicates A-D
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