Accessing BCO-DMO data
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| Dataset Title: | [HHQ Flow Cytometry] - Flow cytometry measurements from HHQ experiments conducted during the MesoHux mesocosm experiment, May 2017, Bergen, Norway (Collaborative Research: Building a framework for the role of bacterial- derived chemical signals in mediating phytoplankton population dynamics) 
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| Institution: | BCO-DMO (Dataset ID: bcodmo_dataset_753431) |
| Information: | Summary
| License
| ISO 19115
| Metadata
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Attributes {
s {
Date {
String bcodmo_name "date";
String description "sampling date formatted as Mon dd yyyy";
String long_name "Date";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
String units "unitless";
}
Sample {
String bcodmo_name "sample";
String description "sample identifier";
String long_name "Sample";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
String units "unitless";
}
Experiment_num {
Byte _FillValue 127;
String _Unsigned "false";
Byte actual_range 1, 8;
String bcodmo_name "exp_id";
String description "experiment number";
String long_name "Experiment Num";
String units "unitless";
}
time2 {
Byte _FillValue 127;
String _Unsigned "false";
Byte actual_range 0, 24;
String bcodmo_name "incubation time";
String description "time since start of experiment";
String long_name "Time";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/AZDRZZ01/";
String units "hours";
}
Replication {
Byte _FillValue 127;
String _Unsigned "false";
Byte actual_range 1, 3;
String bcodmo_name "replicate";
String description "replicate number";
String long_name "Replication";
String units "unitless";
}
Bacteria {
Int32 _FillValue 2147483647;
Int32 actual_range 517817, 2152006;
String bcodmo_name "cell_concentration";
String description "number of bacterial cells";
String long_name "Bacteria";
String units "cells/milliliter";
}
Synechococcus {
Int16 _FillValue 32767;
Int16 actual_range 420, 25704;
String bcodmo_name "cell_concentration";
String description "number of Synechococcus cells";
String long_name "Synechococcus";
String units "cells/milliliter";
}
Picoeukaryotes {
Int32 _FillValue 2147483647;
Int32 actual_range 551, 40121;
String bcodmo_name "cell_concentration";
String description "number of Picoeukaryotes cells";
String long_name "Picoeukaryotes";
String units "cells/milliliter";
}
Nanoeukaryotes {
Int16 _FillValue 32767;
Int16 actual_range 374, 32076;
String bcodmo_name "cell_concentration";
String description "number of Nanoeukaryotes cells";
String long_name "Nanoeukaryotes";
String units "cells/milliliter";
}
Total_Phytoplankton_lt_15um {
Int32 _FillValue 2147483647;
Int32 actual_range 2592, 73204;
String bcodmo_name "cell_concentration";
String description "total number of phytoplankton cells less than 15 microns in diameter";
String long_name "Total Phytoplankton Lt 15um";
String units "cells/milliliter";
}
}
NC_GLOBAL {
String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
String acquisition_description
"Triplicate 5 mL samples were preserved for flow cytometry with 0.5%
glutaraldehyde (final concentration), incubated at 4\\u00b0C for 10 min and
frozen (-80\\u00b0C) until analysis (within 2-3 weeks; Kemp et al. 1993). To
calculate phytoplankton group abundances, 200 \\u00b5l aliquots of fixed sample
were added to a 96-well plate and run on a Guava flow cytometer (Millipore).
Filtered seawater (0.45 \\u00b5m) was run as a blank\\u00a0and instrument-
specific beads were used to calibrate the cytometer. Samples were analyzed at
low flow rate (0.24 \\u00b5l s-1) for 3 min. Three major phytoplankton groups
were distinguishable based on plots of forward scatter vs. orange
(phycoerythrin-containing, Synechococcus spp.) or red (pico- and
nanoeukaryotes) fluorescence signals (Worden and Binder 2003).\\u00a0
Samples for enumerating bacteria were stained prior to running on the Guava in
0.5% v/v SybrGreen I DNA stain for 1 hour at room temperature in the dark.
Mesocosm treatment for all HHQ experiments was as follows:
Redfield: N:P added in a 16:1 ratio during the first 3 days of the
experiment, no shading
HHQ treatments here are as follows:
High HHQ - 100 ng mL-1 (410 uM) added to triplicate 5L bottles.
DMSO control - equivalent (v:v) DMSO added to triplicate 5L bottles.
\\u00a0All bottles were incubated for 24h in a flow-through tank, that was
shaded to mimic in situ conditions. Chlorophyll samples were taken at T0 and
T24 for all experiments.
Data were processed in Excel with statistics run in Excel, R, or Matlab.";
String awards_0_award_nid "709952";
String awards_0_award_number "OCE-1657898";
String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1657898";
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 "David L. Garrison";
String awards_0_program_manager_nid "50534";
String cdm_data_type "Other";
String comment
"HHQ Flow Cytometry
from MesoHux mesocosm experiment, May 2017, Bergen, Norway
PI: E. Harvey (SkIO)
version: 2019-01-23";
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 "2019-01-23T17:23:32Z";
String date_modified "2019-03-14T19:39:56Z";
String defaultDataQuery "&time<now";
String doi "10.1575/1912/bco-dmo.753431.1";
String history
"2024-11-23T16:43:24Z (local files)
2024-11-23T16:43:24Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_753431.html";
String infoUrl "https://www.bco-dmo.org/dataset/753431";
String institution "BCO-DMO";
String instruments_0_acronym "Niskin bottle";
String instruments_0_dataset_instrument_description "Used to collect water samples.";
String instruments_0_dataset_instrument_nid "753438";
String instruments_0_description "A Niskin bottle (a next generation water sampler based on the Nansen bottle) is a cylindrical, non-metallic water collection device with stoppers at both ends. The bottles can be attached individually on a hydrowire or deployed in 12, 24 or 36 bottle Rosette systems mounted on a frame and combined with a CTD. Niskin bottles are used to collect discrete water samples for a range of measurements including pigments, nutrients, plankton, etc.";
String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L22/current/TOOL0412/";
String instruments_0_instrument_name "Niskin bottle";
String instruments_0_instrument_nid "413";
String instruments_0_supplied_name "5 L Niskin";
String instruments_1_acronym "Flow Cytometer";
String instruments_1_dataset_instrument_description "Used for cell counts";
String instruments_1_dataset_instrument_nid "753444";
String instruments_1_description
"Flow cytometers (FC or FCM) are automated instruments that quantitate properties of single cells, one cell at a time. They can measure cell size, cell granularity, the amounts of cell components such as total DNA, newly synthesized DNA, gene expression as the amount messenger RNA for a particular gene, amounts of specific surface receptors, amounts of intracellular proteins, or transient signalling events in living cells.
(from: http://www.bio.umass.edu/micro/immunology/facs542/facswhat.htm)";
String instruments_1_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB37/";
String instruments_1_instrument_name "Flow Cytometer";
String instruments_1_instrument_nid "660";
String instruments_1_supplied_name "Millipore Guava inCyte BG HT flow cytometer";
String keywords "15um, bacteria, bco, bco-dmo, biological, chemical, data, dataset, date, dmo, erddap, experiment, Experiment_num, management, nanoeukaryotes, num, oceanography, office, phytoplankton, picoeukaryotes, preliminary, replication, sample, synechococcus, time, time2, total, Total_Phytoplankton_lt_15um";
String license "https://www.bco-dmo.org/dataset/753431/license";
String metadata_source "https://www.bco-dmo.org/api/dataset/753431";
String param_mapping "{'753431': {}}";
String parameter_source "https://www.bco-dmo.org/mapserver/dataset/753431/parameters";
String people_0_affiliation "Skidaway Institute of Oceanography";
String people_0_affiliation_acronym "SkIO";
String people_0_person_name "Elizabeth Harvey";
String people_0_person_nid "645518";
String people_0_role "Principal Investigator";
String people_0_role_type "originator";
String people_1_affiliation "University of Rhode Island";
String people_1_affiliation_acronym "URI";
String people_1_person_name "Dr David Rowley";
String people_1_person_nid "709954";
String people_1_role "Co-Principal Investigator";
String people_1_role_type "originator";
String people_2_affiliation "Haverford College";
String people_2_affiliation_acronym "Haveford";
String people_2_person_name "Kristen E. Whalen";
String people_2_person_nid "709960";
String people_2_role "Co-Principal Investigator";
String people_2_role_type "originator";
String people_3_affiliation "Woods Hole Oceanographic Institution";
String people_3_affiliation_acronym "WHOI BCO-DMO";
String people_3_person_name "Nancy Copley";
String people_3_person_nid "50396";
String people_3_role "BCO-DMO Data Manager";
String people_3_role_type "related";
String project "HHQSignals";
String projects_0_acronym "HHQSignals";
String projects_0_description
"NSF Abstract:
Bacteria and phytoplankton play a central role in the modification and flow of materials and nutrients through the marine environment. While it has been established that interactions between these two domains are complex, the mechanisms that underpin these interactions remain largely unknown. There is increasing recognition, however, that dissolved chemical cues govern these microbial interactions. This project focuses on establishing a mechanistic framework for how bacterially derived signaling molecules influence interactions between phytoplankton and bacteria. The quorum-sensing (QS) molecule, 2-heptyl-4-quinolone (HHQ) will be used as a model compound for these investigations. Previously published work suggests that exposure to very low levels of HHQ results in phytoplankton mortality. Gaining a mechanistic understanding of these ecologically important interactions will help to inform mathematical models for the accurate prediction of the cycling of material through the marine microbial loop. This work initiates a new, hybrid workshop-internship undergraduate research program in chemical ecology, with a focus
Bacteria and phytoplankton play a central role in the modification and flow of materials and nutrients through the marine environment. While it has been established that interactions between these two domains are complex, the mechanisms that underpin these interactions remain largely unknown. There is increasing recognition, however, that dissolved chemical cues govern these microbial interactions. This project focuses on establishing a mechanistic framework for how bacterially derived signaling molecules influence interactions between phytoplankton and bacteria. The quorum-sensing (QS) molecule, 2-heptyl-4-quinolone (HHQ) will be used as a model compound for these investigations. Previously published work suggests that exposure to very low levels of HHQ results in phytoplankton mortality. Gaining a mechanistic understanding of these ecologically important interactions will help to inform mathematical models for the accurate prediction of the cycling of material through the marine microbial loop. This work initiates a new, hybrid workshop-internship undergraduate research program in chemical ecology, with a focus into bacteria-phytoplankton interactions. Undergraduate students participate in an intense summer learning experience where research and field-based exercises are supplemented with short-lecture based modules. Students return to their home institutions and work closely with the PIs to conduct interdisciplinary research relating to the aims and scope of the summer research. This research also provides training and career development to two graduate students and a postdoctoral scientist.
Interactions between phytoplankton and bacteria play a central role in mediating 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. Despite their predicted importance, identifying these released compounds has remained a challenge. The PIs recently identified a bacterial QS molecule, HHQ, produced by globally distributed marine gamma-proteobacteria, which induces phytoplankton mortality. The PIs therefore hypothesize that bacteria QS signals are critical drivers of phytoplankton population dynamics and, ultimately, biogeochemical fluxes. This project investigates the timing and magnitude of HHQ production, and the physiological and transcriptomic responses of susceptible phytoplankton species to HHQ exposure, and quantifies the influence of HHQ on natural algal and bacterial assemblages. The work connects laboratory and field-based experiments to understand the governance of chemical signaling on marine microbial interactions, and has the potential to yield broadly applicable insights into how microbial interactions influence biogeochemical fluxes in the marine environment.";
String projects_0_end_date "2020-03";
String projects_0_geolocation "Bergen, Norway";
String projects_0_name "Collaborative Research: Building a framework for the role of bacterial-derived chemical signals in mediating phytoplankton population dynamics";
String projects_0_project_nid "709948";
String projects_0_start_date "2017-04";
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 "This dataset includes flow cytometry measurements from HHQ experiments conducted during the MesoHux mesocosm experiment, May 2017, Bergen, Norway. Microbial mesocosms were spiked with 2-heptyl-4-quinolone (HHQ).";
String title "[HHQ Flow Cytometry] - Flow cytometry measurements from HHQ experiments conducted during the MesoHux mesocosm experiment, May 2017, Bergen, Norway (Collaborative Research: Building a framework for the role of bacterial-derived chemical signals in mediating phytoplankton population dynamics)";
String version "1";
String xml_source "osprey2erddap.update_xml() v1.3";
}
}
Data Access Protocol (DAP) and its
selection constraints.
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.