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Dataset Title:  57Fe Wall Loss Experiment data collected as part of a method development study
investigating the precipitation and wall loss of labeled 57Fe when added to M9
Minimal Media
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_732864)
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Subset | Data Access Form | Files
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Things You Can Do With Your Graphs

Well, you can do anything you want with your graphs, of course. But some things you might not have considered are:

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  DATE {
    Int32 _FillValue 2147483647;
    Int32 actual_range 20171113, 20171113;
    String bcodmo_name "date";
    String description "Date (UTC) when media was filtered and experiment initiated (t=0), in format YYYYMMDD";
    String long_name "DATE";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
    String units "unitless";
    String bcodmo_name "sample";
    String description "Sample identifier designated B for un-chelexed, or C for chelexed; 1 for un-spiked with 57FeSO4, 2 for spiked with 10 uM 57FeSO4; D for dissolved (0.2 um filtered) or S for soluble (0.02 um filtered)";
    String long_name "SAMPLE ID";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
    String units "unitless";
    String bcodmo_name "treatment";
    String description "Description of treatment type";
    String long_name "DESCRIPTION";
    String units "unitless";
    String bcodmo_name "treatment";
    String description "Solution was treated with Chelex-100 resin (Yes) or not (No), units in Yes/No";
    String long_name "CHELEX";
    String units "unitless";
  Fe57_SPIKE {
    Byte _FillValue 127;
    Byte actual_range 0, 10;
    String bcodmo_name "treatment";
    String description "57FeSO4 spike concentration as added to the media";
    String long_name "Fe57 SPIKE";
    String units "micromolar (uM)";
    String bcodmo_name "filter_size";
    String description "Pore size used to filter media, using 0.2 um Sterivex PVDF syringe filter or 0.02 um Anatop syringe filter";
    String long_name "FILTER SIZE";
    String units "micrometers (um)";
  DAY {
    Byte _FillValue 127;
    Byte actual_range 0, 7;
    String bcodmo_name "days";
    String description "Time when treatment was sampled, t=n, units in days";
    String long_name "DAY";
    String units "days";
  Fe56 {
    Float32 _FillValue NaN;
    Float32 actual_range 10.73, 738.92;
    String bcodmo_name "Fe";
    String description "Concentration of 56Fe as determined by HR-ICP-MS";
    String long_name "Fe56";
    String units "nanomolar (nM)";
  Fe57 {
    Float32 _FillValue NaN;
    Float32 actual_range 2.13, 10857.82;
    String bcodmo_name "Fe";
    String description "Concentration of 57Fe as determined by HR-ICP-MS";
    String long_name "Fe57";
    String units "nanomolar (nM)";
  Fe57_to_Fe56 {
    Float32 _FillValue NaN;
    Float32 actual_range 2.27, 2459.01;
    String bcodmo_name "Fe";
    String description "Ratio of 57Fe concentration to 56Fe concentration as measured by the HR-ICP-MS, multiplied by 100 (in percentage)";
    String long_name "Fe57 To Fe56";
    String units "unitless (percentage)";
    String bcodmo_name "comment";
    String description "Some samples contaminated by bacterial growth were designated as such";
    String long_name "NOTES";
    String units "unitless";
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
    String acquisition_description 
"Refer to Supplemental File, \\\"57Fe Wall Loss Experiment diagram\\\" for the
steps indicated in bold.
All materials were soaked overnight with heating in 1.5% Citrad Citric Acid
liquid cleaner in deionized water, rinsed in RO water, and soaked in 10% HCl
in Milli-Q ultrapure water for one week (due to time constraints), then rinsed
with MilliQ ultrapure water, let dry in an AirClean 400 work station
overnight, and double-bagged in polyethylene bags (Mellett et al., 2017). M9
Minimal Media for bacterial cultures was made using Milli-Q ultrapure water,
containing final concentrations of 33.7 mM Na\\u2082HPO\\u2084\\u00b72H\\u2082O,
22 mM KH\\u2082PO\\u2084, 8.56 mM NaCl, 18.7 mM NH\\u2084Cl, 0.1 M magnesium
chloride, 0.1 M calcium chloride, 2 mg/ml Thiamine HCl in 70% EtOH, and 20%
Glucose (Kutter & Sulakvelidze, 2004). Half of the media was chelexed using
Chelex-100 resin (Pai et al., 1988) that was not acid-cleaned (C), and half
remained un-chelexed (B). Half of each treatment was spiked with 10 \\u00b5M
labeled \\u2075\\u2077FeSO\\u2084(2) while half remained un-spiked (1). A volume
of 25 ml was then filtered through either a 0.2 \\u00b5m Sterivex PVDF syringe
filter for the dissolved fraction (D), or a 0.02 \\u00b5m Whatman Anatop
syringe filter for the soluble fraction (S) (Gledhill & Buck, 2012). Samples
were directly filtered into trace metal clean polycarbonate Erlenmeyer flasks,
placed in a clean bag with a small opening to vent, and left shaking at 37
\\u00b0C for one week. Samples of each treatment were taken initially, then
after the 1st, 3rd, and 7th days (t= 00, 01, 03, 07). The samples were
diluted, acidified, and analyzed using an ELEMENT XR High Resolution
Inductively Coupled Plasma Mass Spectrometer (HR-ICP-MS). The limit of
detection (LOD) for \\u2075\\u2076Fe and \\u2075\\u2077Fe were 0.3 nM and 0.012
nM, respectively (Shrivastava & Gupta, 2011).
Problem Report:  
 \\u200bThe original measurements of the M9 minimal media \\u2075\\u2076Fe
contamination was high, so in an attempt to lower background contamination the
media was chelexed. However, the Chelex-100 resin was not rinsed with acid, so
was less active for removal of metals. This resulted in higher than expected
background concentrations of metals.
Three samples were contaminated with bacterial growth (as indicated by visual
turbidity and confirmed using SYBR nucleic acid stain and epifluorescence
microscopy) over the course of the week. On t=3, sample B2 was contaminated.
By t=7, sample B1D and B1S were contaminated.";
    String awards_0_award_nid "713366";
    String awards_0_award_number "OCE-1722761";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1722761";
    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 "Michael E. Sieracki";
    String awards_0_program_manager_nid "50446";
    String cdm_data_type "Other";
    String comment 
"57Fe Wall Loss Experiment 
  PIs: Kristen Buck & Mya Breitbart (USF) 
  Co-PIs: Salvatore Caprara & Chelsea Bonnain (USF) 
  Verion: 04 April 2018";
    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 date_created "2018-04-04T17:40:41Z";
    String date_modified "2020-02-11T18:33:18Z";
    String defaultDataQuery "&time<now";
    String doi "10.1575/1912/bco-dmo.732864.1";
    String history 
"2024-04-23T23:03:58Z (local files)
2024-04-23T23:03:58Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_732864.das";
    String infoUrl "https://www.bco-dmo.org/dataset/732864";
    String institution "BCO-DMO";
    String instruments_0_acronym "ICP Mass Spec";
    String instruments_0_dataset_instrument_description "ELEMENT XR High Resolution Inductively Coupled Plasma Mass Spectrometer (HR-ICP-MS)";
    String instruments_0_dataset_instrument_nid "732867";
    String instruments_0_description "An ICP Mass Spec is an instrument that passes nebulized samples into an inductively-coupled gas plasma (8-10000 K) where they are atomized and ionized. Ions of specific mass-to-charge ratios are quantified in a quadrupole mass spectrometer.";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB15/";
    String instruments_0_instrument_name "Inductively Coupled Plasma Mass Spectrometer";
    String instruments_0_instrument_nid "530";
    String instruments_0_supplied_name "ELEMENT XR High Resolution Inductively Coupled Plasma Mass Spectrometer";
    String keywords "bco, bco-dmo, biological, chelex, chemical, data, dataset, date, day, description, dmo, erddap, fe56, fe57, Fe57_SPIKE, Fe57_to_Fe56, filter, FILTER_SIZE, management, notes, oceanography, office, preliminary, sample, SAMPLE_ID, size, spike";
    String license "https://www.bco-dmo.org/dataset/732864/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/732864";
    String param_mapping "{'732864': {}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/732864/parameters";
    String people_0_affiliation "University of South Florida";
    String people_0_affiliation_acronym "USF";
    String people_0_person_name "Mya Breitbart";
    String people_0_person_nid "51740";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "University of South Florida";
    String people_1_affiliation_acronym "USF";
    String people_1_person_name "Kristen N. Buck";
    String people_1_person_nid "51624";
    String people_1_role "Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "University of South Florida";
    String people_2_affiliation_acronym "USF";
    String people_2_person_name "Chelsea Bonnain";
    String people_2_person_nid "732872";
    String people_2_role "Co-Principal Investigator";
    String people_2_role_type "originator";
    String people_3_affiliation "University of South Florida";
    String people_3_affiliation_acronym "USF";
    String people_3_person_name "Salvatore Caprara";
    String people_3_person_nid "732874";
    String people_3_role "Co-Principal Investigator";
    String people_3_role_type "originator";
    String people_4_affiliation "Woods Hole Oceanographic Institution";
    String people_4_affiliation_acronym "WHOI BCO-DMO";
    String people_4_person_name "Shannon Rauch";
    String people_4_person_nid "51498";
    String people_4_role "BCO-DMO Data Manager";
    String people_4_role_type "related";
    String project "Fe-Virus";
    String projects_0_acronym "Fe-Virus";
    String projects_0_description 
"Iron is an essential micronutrient for phytoplankton that is required for photosynthesis and respiration. Insufficient iron has been shown to limit phytoplankton growth in large regions of the surface ocean, and correspondingly, iron cycling is directly linked to carbon cycling in much of the marine environment. Nearly all iron in seawater (>99%) exists as complexes with organic molecules called ligands, which govern the concentration of iron dissolved in the water and the bioavailability of that iron to phytoplankton. However, despite the importance of iron-binding organic ligands, their sources and identities are largely unknown. Viruses, the majority of which are phages (viruses that infect bacteria), are extremely abundant in seawater and are in the same size fraction as dissolved iron. Recent evidence that non-marine phages contain iron as part of their structures has led to the proposal that marine phages may represent a previously overlooked class of organic iron-binding ligands. This project is determining the contribution of marine phages to dissolved iron pools and culture phage-host systems in the laboratory to determine if phages utilize bacterial iron-uptake receptors for infection in the manner of a Trojan horse. As the first study to examine the biogeochemical impact of trace elements contained within the structure of highly abundant marine phage particles, successful completion of the proposed research will be transformative for biological and chemical oceanography and have far-reaching implications for other fields, including human health where iron availability plays an important role in microbial pathogenesis. This project contributes to the multidisciplinary training of a graduate student and postdoctoral researcher. Research results will be disseminated through scientific publications and presentations, and the public will be educated about linkages between viruses and ocean chemistry via a hands-on exhibit for the annual St. Petersburg Science Festival.
Building upon evidence from non-marine model systems demonstrating the presence of iron ions in phage tail proteins and phage utilization of cell surface receptors for siderophore-bound iron, this project combines field and laboratory-based experiments to test the following three hypotheses regarding iron-virus interactions in the oceans: (1) Iron incorporated into phage tails originates from bacterial cell reserves, reducing the amount of iron available for remineralization upon lysis; (2) Phages constitute important iron-binding ligands in the oceans, accounting for a substantial portion of organically complexed colloidal dissolved iron; (3) Marine phages compete with siderophore-bound iron for uptake receptors on the bacterial cell surface and use iron in their tails as a Trojan horse for infection. Initial calculations predict that phages could account for up to 70% of the colloidal fraction of organically complexed dissolved iron in the surface ocean; therefore, this project is critical for advancing knowledge of trace-metal cycling as well as phage-host interactions. Additionally, if a portion of the cellular iron thought to be released from bacterial cells for remineralization following lysis is already incorporated into phage tails, then these findings will have significant implications for oceanic biogeochemical models. Through a combination of laboratory-based culture experiments and field sample measurements, this project could reveal the identity of a ubiquitous component of colloidal organic iron-binding ligands, modify the estimates of iron concentrations and species released through viral lysis, and potentially identify a novel receptor type for marine phage that may compete with the acquisition of siderophore-bound iron by host bacteria.";
    String projects_0_end_date "2019-01";
    String projects_0_name "EAGER: Iron-Virus Interactions in the Ocean";
    String projects_0_project_nid "713367";
    String projects_0_start_date "2017-02";
    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 subsetVariables "DATE";
    String summary "This data was collected as part of a method development study investigating the precipitation and wall loss of labeled \\u2075\\u2077Fe when added to M9 Minimal Media, which is used to grow the model bacterial species Escherichia coli. The bulk media was prepared with the same components and a portion was treated with Chelex-100 to remove metals, while the other portion remained un-chelexed. Half of each treatment was spiked with labeled \\u2075\\u2077Fe and either 0.2 \\u03bcm or 0.02 \\u03bcm filtered for comparison of the dissolved and soluble fractions. The \\u2075\\u2077Fe content was monitored over four time points for one week in a shaking incubator, under the same conditions used to culture E. coli for labeling experiments.";
    String title "57Fe Wall Loss Experiment data collected as part of a method development study investigating the precipitation and wall loss of labeled 57Fe when added to M9 Minimal Media";
    String version "1";
    String xml_source "osprey2erddap.update_xml() v1.3";


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
For example,
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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