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Dataset Title:  [Sulfonates in plankton cultures] - Intracellular sulfonate metabolites
measured in a variety of eukaryotic and prokaryotic phytoplankton and
heterotrophic bacteria using liquid chromatography-mass spectrometry-based
metabolomics (OCE-PRF Track 1 (Broadening Participation): Cryptic Sulfonate
Cycling between Marine Phytoplankton and Heterotrophic Bacterioplankton)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_814713)
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Files | Make a graph
 
Variable ?   Optional
Constraint #1 ?
Optional
Constraint #2 ?
   Minimum ?
 
   Maximum ?
 
 Organism (unitless) ?          "Alexandrium tamare..."    "Thalassospira sp. ..."
 replicate (unitless) ?          "A"    "F"
 cells_filtered (unitless) ?          "101538600"    "9995232000"
 DHPS (amol per cell) ?          88.442    3247.047
 cysteic_acid (amol per cell) ?          1.0E-4    126.71
 sulfolactate (amol per cell) ?          0.002    14.931
 isethionic_acid (amol per cell) ?          8.164    45919.871
 taurine (amol per cell) ?          4.0E-4    15245.64
 
Server-side Functions ?
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File type: (more information)

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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  Organism {
    String bcodmo_name "taxon";
    String description "name and strain number";
    String long_name "Organism";
    String units "unitless";
  }
  replicate {
    String bcodmo_name "replicate";
    String description "biological replicate";
    String long_name "Replicate";
    String units "unitless";
  }
  cells_filtered {
    String bcodmo_name "number";
    String description "number of cells extracted";
    String long_name "Cells Filtered";
    String units "unitless";
  }
  DHPS {
    Float32 _FillValue NaN;
    Float32 actual_range 88.442, 3247.047;
    String bcodmo_name "unknown";
    String description "sulfonate";
    String long_name "DHPS";
    String units "amol per cell";
  }
  cysteic_acid {
    Float32 _FillValue NaN;
    Float32 actual_range 1.0e-4, 126.71;
    String bcodmo_name "unknown";
    String description "sulfonate";
    String long_name "Cysteic Acid";
    String units "amol per cell";
  }
  sulfolactate {
    Float32 _FillValue NaN;
    Float32 actual_range 0.002, 14.931;
    String bcodmo_name "unknown";
    String description "sulfonate";
    String long_name "Sulfolactate";
    String units "amol per cell";
  }
  isethionic_acid {
    Float64 _FillValue NaN;
    Float64 actual_range 8.164, 45919.871;
    String bcodmo_name "unknown";
    String description "sulfonate";
    String long_name "Isethionic Acid";
    String units "amol per cell";
  }
  taurine {
    Float32 _FillValue NaN;
    Float32 actual_range 4.0e-4, 15245.64;
    String bcodmo_name "unknown";
    String description "sulfonate";
    String long_name "Taurine";
    String units "amol per cell";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
    String acquisition_description 
"Pure cultures of bacteria and phytoplankton were grown in artificial seawater
medium, and cells were collected during mid-to-late exponential phase by
gentle filtration onto 0.2 micron Durapore filters. All filters were flash
frozen in liquid nitrogen and stored at -80 degrees Celsius until further
processing. Frozen filters of cells and media blanks were extracted and
analyzed using a targeted liquid chromatography-mass spectrometry-based
metabolomics method according to the protocols in Boysen and Heal et al.,
2018. Briefly, metabolites were extracted using a modified Bligh\\u2013Dyer
extraction using 1:1 methanol/water (aqueous phase) and dichloromethane
(organic phase). Targeted metabolomics data were generated using a Waters Xevo
TQ-S triple quadrupole with both reverse-phase and hydrophilic interaction
liquid chromatography (HILIC). Taurine, isethionate, sulfolactate, and
cysteate were quantified using isotopically-labeled internal standards that
were added prior to extraction. DHPS was quantified by generating standard
addition curves.
 
Instruments: Targeted metabolomics data were generated using a Waters Xevo
TQ-S triple quadrupole (TQS) with electrospray ionization (ESI) in selected
reaction monitoring mode (SRM) with polarity switching. SRM conditions for
each compound (collision energy, cone voltage, precursor, and product ions)
were optimized by infusion of each metabolite standard. For most metabolites,
two SRM transitions were selected based on maximum peak areas. All
chromatographic separations were carried out on a Waters Acquity I-Class UPLC
(Waters Corporation, Milford, MA).";
    String awards_0_award_nid "718130";
    String awards_0_award_number "OCE-1521564";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1521564";
    String awards_0_funder_name "NSF Division of Ocean Sciences";
    String awards_0_funding_acronym "NSF OCE";
    String awards_0_funding_source_nid "355";
    String awards_0_program_manager "Elizabeth L. Rom";
    String awards_0_program_manager_nid "682003";
    String cdm_data_type "Other";
    String comment 
"Sulfonates in plankton cultures 
  PI: Bryndan P. Durham 
  Version date: 10 June 2020";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String creator_email "info@bco-dmo.org";
    String creator_name "BCO-DMO";
    String creator_type "institution";
    String creator_url "https://www.bco-dmo.org/";
    String data_source "extract_data_as_tsv version 2.3  19 Dec 2019";
    String dataset_current_state "Final and no updates";
    String date_created "2020-06-10T14:53:27Z";
    String date_modified "2020-06-10T20:25:53Z";
    String defaultDataQuery "&time<now";
    String doi "10.26008/1912/bco-dmo.814713.1";
    String history 
"2024-11-21T12:12:32Z (local files)
2024-11-21T12:12:32Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_814713.html";
    String infoUrl "https://www.bco-dmo.org/dataset/814713";
    String institution "BCO-DMO";
    String instruments_0_acronym "Mass Spec";
    String instruments_0_dataset_instrument_description "Targeted metabolomics data were generated using a Waters Xevo TQ-S triple quadrupole with both reverse-phase and hydrophilic interaction liquid chromatography (HILIC).";
    String instruments_0_dataset_instrument_nid "814730";
    String instruments_0_description "General term for instruments used to measure the mass-to-charge ratio of ions; generally used to find the composition of a sample by generating a mass spectrum representing the masses of sample components.";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB16/";
    String instruments_0_instrument_name "Mass Spectrometer";
    String instruments_0_instrument_nid "685";
    String instruments_0_supplied_name "Waters Xevo TQ-S triple quadrupole";
    String keywords "acid, bco, bco-dmo, biological, cells, cells_filtered, chemical, cysteic, cysteic_acid, data, dataset, dhps, dmo, erddap, filtered, isethionic, isethionic_acid, management, oceanography, office, organism, preliminary, replicate, sulfolactate, taurine";
    String license "https://www.bco-dmo.org/dataset/814713/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/814713";
    String param_mapping "{'814713': {}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/814713/parameters";
    String people_0_affiliation "University of Washington";
    String people_0_affiliation_acronym "UW";
    String people_0_person_name "Bryndan P. Durham";
    String people_0_person_nid "718133";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "Woods Hole Oceanographic Institution";
    String people_1_affiliation_acronym "WHOI BCO-DMO";
    String people_1_person_name "Shannon Rauch";
    String people_1_person_nid "51498";
    String people_1_role "BCO-DMO Data Manager";
    String people_1_role_type "related";
    String project "Sulfonate Cycling";
    String projects_0_acronym "Sulfonate Cycling";
    String projects_0_description 
"NSF Award Abstract:
Information in the form of chemicals and energy flows constantly through complex networks of marine microbes. In the surface ocean, sunlight and atmospheric carbon dioxide are captured by autotrophic unicellular phytoplankton and transformed into a vast pool of organic matter that microbes use as metabolic currencies and signaling molecules to form the basis for different trading alliances. Several little-known sulfonate compounds have recently been identified as key currencies underlying marine bacterial-phytoplankton mutualisms and appear to be widespread in coastal communities. In this project, the fellow will investigate the prevalence and role of sulfonates in marine microbial interactions and their resulting impact on the Earth's biogeochemistry. With sponsor Dr. E. Virginia Armbrust at the University of Washington, the fellow will advance professionally through interdisciplinary training in microbial ecology and marine biogeochemistry. Broadening participation activities include mentorship of an undergraduate and development of an outreach program for a local minority-serving high school where students will conduct classroom laboratory exercises using microbiological and bioinformatics concepts.
Sulfonates are produced and degraded by several important phytoplankton and heterotrophic bacterial taxa, respectively. Yet, these compounds represent a poorly understood component of the marine organic matter pool. To the extent that sulfonates account for an unquantified flux of carbon and sulfur that supports mutualisms between bacteria and phytoplankton, sulfonates represent cryptic missing links in both carbon and sulfur transformations in the ocean. In this study, the fellow will use laboratory-based approaches to examine physiological and ecological controls on sulfonate production in model phytoplankton species and field-based approaches to examine taxonomically driven dynamics of sulfonate pools in the coastal waters of Puget Sound and surrounding North Pacific. Specifically, the fellow will perform metabolic profiling of model sulfonate-producing phytoplankton taxa (Aim I) and measure spatiotemporal gradients and turnover rates of sulfonates in the ocean environment using targeted in situ metabolite surveys (II) and stable isotope incubations (III), respectively, together with transcriptomics-based identification of marine microbes that control the fate of sulfonate-derived carbon (IV). The planned experiments will provide the first intensive characterization of sulfonates in the environment in terms of their contribution to the marine organic matter pool, their taxonomically driven spatiotemporal dynamics, and their roles in ocean ecosystem interdependencies.";
    String projects_0_end_date "2017-06";
    String projects_0_geolocation "University of Washington";
    String projects_0_name "OCE-PRF Track 1 (Broadening Participation): Cryptic Sulfonate Cycling between Marine Phytoplankton and Heterotrophic Bacterioplankton";
    String projects_0_project_nid "718131";
    String projects_0_start_date "2015-07";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "Intracellular sulfonate metabolites were measured in a variety of eukaryotic and prokaryotic phytoplankton and heterotrophic bacteria using liquid chromatography-mass spectrometry-based metabolomics. These data have been published in Durham et al. (2019). Raw data are available at Metabolomics Workbench under Project ID PR000797.";
    String title "[Sulfonates in plankton cultures] - Intracellular sulfonate metabolites measured in a variety of eukaryotic and prokaryotic phytoplankton and heterotrophic bacteria using liquid chromatography-mass spectrometry-based metabolomics (OCE-PRF Track 1 (Broadening Participation): Cryptic Sulfonate Cycling between Marine Phytoplankton and Heterotrophic Bacterioplankton)";
    String version "1";
    String xml_source "osprey2erddap.update_xml() v1.5";
  }
}

 

Using tabledap to Request Data and Graphs from Tabular Datasets

tabledap lets you request a data subset, a graph, or a map from a tabular dataset (for example, buoy data), via a specially formed URL. tabledap uses the OPeNDAP (external link) Data Access Protocol (DAP) (external link) and its selection constraints (external link).

The URL specifies what you want: the dataset, a description of the graph or the subset of the data, and the file type for the response.

Tabledap request URLs must be in the form
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/datasetID.fileType{?query}
For example,
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/pmelTaoDySst.htmlTable?longitude,latitude,time,station,wmo_platform_code,T_25&time>=2015-05-23T12:00:00Z&time<=2015-05-31T12:00:00Z
Thus, the query is often a comma-separated list of desired variable names, followed by a collection of constraints (e.g., variable<value), each preceded by '&' (which is interpreted as "AND").

For details, see the tabledap Documentation.


 
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