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log in [Metagenomic samples] - Metagenomic sample information, genetic accession identifiers (NCBI SRA, JGI IMG), and estimated gene copies from Orcas Island coastal waters (2 m depth) in May and June of 2021 (Collaborative Research: Rhythm and Blooms: Deciphering metabolic, functional and taxonomic interactions over the life cycle of a phytoplankton bloom) This dataset contains NCBI Sequence Read Archive (SRA) accession numbers, DOE JGI Integrated Microbial Genomes & Microbiome (IMG/M) IDs, and estimated gene copies for metagenomic samples collected at Orcas Island, WA, USA Coastal Ocean (2m depth) from 5/27/21 to 6/18/21 collected as part of the following study.\n\nStudy abstract:\n\nFloating, single-celled algae, or phytoplankton, form the base of marine food webs. When phytoplankton have sufficient nutrients to grow quickly and generate dense populations, known as blooms, they influence productivity of the entire food web, including rich coastal fisheries. The present research explores how the environment (nutrients) as well as physical and chemical interactions between individual cells in a phytoplankton community and their associated bacteria act to control the timing of bloom events in a dynamic coastal ecosystem. The work reveals key biomolecules within the base of the food web that can inform food web functioning (including fisheries) and be used in global computational models that forecast the impacts of phytoplankton activities on global carbon cycling. A unique set of samples and data collected in 2021 and 2022 that captured phytoplankton and bacterial communities before, during, and after phytoplankton blooms, is analyzed using genomic methods and the results are used to interrogate these communities for biomolecules associated with blooms stages. The team mentors undergraduates, graduate students, and postdoctoral researchers in the fields of biochemical oceanography, genome sciences, and time-series multivariate statistics. University of Washington organized hackathons to develop publicly accessible portals for the simplified interrogation and visualization of 'omics data, accessible to high schoolers and undergraduates. These portals are implemented in investigator-led undergraduate teaching modules in the University of Rhode Island Ocean Classroom. The research team also returns to Orcas Island, WA, where the field sampling takes place, to host a series of annual Science Weekends to foster scientific engagement with the local community.\nPhytoplankton blooms, from initiation to decline, play vital roles in biogeochemical cycling by fueling primary production, influencing nutrient availability, impacting carbon sequestration in aquatic ecosystems, and supporting secondary production. In addition to influences from environmental conditions, the physical and chemical interactions among planktonic microbes can significantly modulate blooms, influencing the growth, maintenance, and senescence of phytoplankton. Recent work in steady-state open ocean ecosystems has shown that important chemicals are transferred amongst plankton on time-dependent metabolic schedules that are related to diel cycles. It is unknown how these metabolic schedules operate in dynamic coastal environments that experience perturbations, such as phytoplankton blooms. Here, the investigators are examining metabolic scheduling using long-term, diel sample sets to reveal how chemical and biological signals associated with the initiation, maintenance, and cessation of phytoplankton blooms are modulated on both short (hrs) and long (days-weeks) time scales. Findings are advancing the ability to predict and manage phytoplankton dynamics, providing crucial insights into ecological stability and future oceanographic sampling strategies. Additionally, outcomes of this study are providing a new foundational understanding of the succession of microbial communities and their chemical interactions across a range of timescales. In the long term, this research has the potential to identify predictors of the timing of phytoplankton blooms, optimize fisheries management, and guide future research on carbon sequestration.\n\ncdm_data_type = Other\nVARIABLES:\nDateID_PT (unitless)\n... (33 more variables)\n BCO-DMO bcodmo_dataset_984169_v1
https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_914399_v1 https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_914399_v1.graph https://erddap.bco-dmo.org/erddap/files/bcodmo_dataset_914399_v1/ public [Microbial eukaryotic diversity: Mid-Cayman Rise SRA dataset] - 18S rRNA amplicon sequencing of microbial eukaryotes from the Mid-Cayman Rise acquired Jan-Feb, 2020 (Probing subseafloor microbial interactions via hydrothermal vent fluids: A focus on protists) Single-celled microbial eukaryotes inhabit deep-sea hydrothermal vent environments and play critical ecological roles in the vent-associated microbial food web. 18S rRNA amplicon sequencing of diffuse venting fluids from two geochemically-distinct hydrothermal vent fields was applied to investigate community diversity patterns among protistan assemblages. Piccard and Von Damm vent fields are situated 20 km apart at the Mid-Cayman Rise in the Caribbean Sea. We describe species diversity patterns with respect to hydrothermal vent field and sample type, identify putative vent endemic microbial eukaryotes, and test how vent fluid geochemistry may influence microbial community diversity. Individual vent fields supported distinct and highly diverse assemblages of protists that included potentially endemic or novel vent-associated strains. This data adds to our growing knowledge of the biogeography of deep-sea microbial eukaryotes.\n\ncdm_data_type = Other\nVARIABLES:\nExperiment_Accession (unitless)\nExperiment_Title (unitless)\nOrganism_Name (unitless)\nInstrument (unitless)\nStudy_Accession (unitless)\nStudy_Title (unitless)\nSample_Accession (unitless)\nTotal_Size_Mb (Mb)\nTotal_Bases (bp)\nLibrary_Name (unitless)\nLibrary_Strategy (unitless)\nLibrary_Source (unitless)\nLibrary_Selection (unitless)\nVent_field (unitless)\nCollection (unitless)\nVent_name (unitless)\nDiveID (unitless)\n https://erddap.bco-dmo.org/erddap/info/bcodmo_dataset_914399_v1/index.htmlTable https://www.bco-dmo.org/dataset/914399 (external link) https://erddap.bco-dmo.org/erddap/rss/bcodmo_dataset_914399_v1.rss https://erddap.bco-dmo.org/erddap/subscriptions/add.html?datasetID=bcodmo_dataset_914399_v1&showErrors=false&email= BCO-DMO bcodmo_dataset_914399_v1

 
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