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| Dataset Title: | [sea_fan_parasite_growth] - Experimental results on the growth of Aplanochytrium (a sea fan parasite) cells over a temperature gradient conducted at the Harvell lab at Cornell University (Influence of Temperature and Acidification on the Dynamics of Coral Co-Infection and Resistance) 
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| Institution: | BCO-DMO (Dataset ID: bcodmo_dataset_3719) |
| Information: | Summary
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| ISO 19115
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Attributes {
s {
trial {
Byte _FillValue 127;
String _Unsigned "false";
Byte actual_range 1, 2;
String bcodmo_name "exp_id";
String description "Experimental trial number (1 or 2; see Acquisition Description).";
String long_name "Trial";
String units "unitless";
}
temp {
Byte _FillValue 127;
String _Unsigned "false";
Byte actual_range 15, 32;
String bcodmo_name "unknown";
String description "Incubation temperature.";
String long_name "Temperature";
String units "degrees C";
}
count_avg {
Float64 _FillValue NaN;
Float64 actual_range 0.0, 5263333.33;
String bcodmo_name "count";
Float64 colorBarMaximum 100.0;
Float64 colorBarMinimum 0.0;
String description "Average of total cells per temperature.";
String long_name "Count Avg";
String units "# cells (unitless)";
}
count_avg_se {
Float64 _FillValue NaN;
Float64 actual_range 0.0, 663498.42;
String bcodmo_name "unknown";
Float64 colorBarMaximum 100.0;
Float64 colorBarMinimum 0.0;
String description "Standard error of count_avg.";
String long_name "Count Avg Se";
String units "# cells (unitless)";
}
count_log10_avg {
Float64 _FillValue NaN;
Float64 actual_range 0.0, 6.707714392;
String bcodmo_name "count";
Float64 colorBarMaximum 100.0;
Float64 colorBarMinimum 0.0;
String description "Average of log 10 transformed cell counts per temperature.";
String long_name "Count Log10 Avg";
String units "# cells (unitless)";
}
count_log10_avg_se {
Float64 _FillValue NaN;
Float64 actual_range 0.0, 0.14726115;
String bcodmo_name "unknown";
Float64 colorBarMaximum 100.0;
Float64 colorBarMinimum 0.0;
String description "Standard error of count_log10_avg.";
String long_name "Count Log10 Avg Se";
String units "# cells (unitless)";
}
protein_avg {
Float64 _FillValue NaN;
Float64 actual_range 8.56, 11.09937689;
String bcodmo_name "unknown";
String description "Average protein concentration per temperature.";
String long_name "Protein Avg";
String units "mg protein per culture";
}
protein_avg_se {
Float64 _FillValue NaN;
Float64 actual_range 0.50994737, 0.89;
String bcodmo_name "unknown";
String description "Standard error of protein_avg.";
String long_name "Protein Avg Se";
String units "mg protein per culture";
}
protein_log10_avg {
Float64 _FillValue NaN;
Float64 actual_range 0.93, 1.040367223;
String bcodmo_name "unknown";
String description "Average of log 10 transformed protein concentration per temperature.";
String long_name "Protein Log10 Avg";
String units "mg protein per culture";
}
protein_log10_avg_se {
Float64 _FillValue NaN;
Float64 actual_range 0.025478283, 0.05;
String bcodmo_name "unknown";
String description "Standard error of protein_log10_avg.";
String long_name "Protein Log10 Avg Se";
String units "mg protein per culture";
}
rep {
Byte _FillValue 127;
String _Unsigned "false";
Byte actual_range 1, 3;
String bcodmo_name "unknown";
String description "Replicate.";
String long_name "Rep";
String units "unitless";
}
count {
Int32 _FillValue 2147483647;
Int32 actual_range 0, 8670000;
String bcodmo_name "count";
Float64 colorBarMaximum 100.0;
Float64 colorBarMinimum 0.0;
String description "Total number of cells per culture.";
String long_name "Count";
String units "# cells (unitless)";
}
protein {
Float64 _FillValue NaN;
Float64 actual_range 5.839496, 13.382512;
String bcodmo_name "unknown";
String description "Protein concentration measured in milligrams of protein per culture.";
String long_name "Protein";
String units "mg protein per culture";
}
count_log10 {
Float64 _FillValue NaN;
Float64 actual_range 0.0, 6.938019097;
String bcodmo_name "count";
Float64 colorBarMaximum 100.0;
Float64 colorBarMinimum 0.0;
String description "Total cells per culture, log 10 transformed.";
String long_name "Count Log10";
String units "# cells (unitless)";
}
protein_log10 {
Float64 _FillValue NaN;
Float64 actual_range 0.766375365, 1.126537641;
String bcodmo_name "unknown";
String description "Protein concentration, log 10 transformed.";
String long_name "Protein Log10";
String units "mg protein per culture";
}
}
NC_GLOBAL {
String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
String acquisition_description
"Sampling and Analytical Methodology:
In the first trial, a Labyrinthulomycota culture held at 22 degrees C was
divided into 18 sub-cultures that were incubated at 15 degrees C, 20 degrees
C, 25 degrees C, 30 degrees C, and 32 degrees C in triplicate for three days.
Culture temperatures and incubation period were based on previous visual
observations of Labyrinthulomycota growth, where over-growth of culture flasks
occurs after three days at temperatures of 25 degrees C and higher. In the
second trial, nine sub-cultures were incubated at 20 degrees C, 25 degrees C,
and 30 degrees C in triplicate for three days.
In the second trial, total protein was also assessed. After three days, the
media was poured off, rinsed once with 3 mLs of 0.22 um-filtered artificial
sea water, and replaced with 3 mLs of 0.22 um-filtered artificial sea water.
With a sterile wooden dowel, the bottom of each culture was scraped until no
Labyrinthulomycota growth was visible on the bottom of the culture. 700 uL of
each culture was placed in a bead beater and mixed at 300 rpm for 30 sec; 400
uL was set aside for protein assays and 300 uL for cell counts and held on ice
until use.
Prior to counting using a hemocytometer, cells were vortexed for about 20 sec.
In each culture, cells were counted in triplicate.
Total protein was extracted from each sample by adding 400 uL of extraction
buffer (0.15 ug mL-1 DTT in Tris-HCl) to each tube. The contents of the tube
were mixed and lysed for 2 minutes with the Fisherbrand disposable pestle
grinder system, and incubated for 45 minutes on ice for extractions. Protein
was measured using the DC protein kit (Bio-Rad), and read in triplicate using
the Synergy HT multi-Detection microplate reader with KC4 software (Biotek
Instruments, Vermont) at 750 nm.";
String awards_0_award_nid "55012";
String awards_0_award_number "OCE-0849776";
String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0849776";
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
"Growth of Aplanochytrium cells over a temperature gradient
PI: Drew Harvell (Cornell University)
Co-PI: Laura Mydlarz (University of Texas Arlington)
Version: 12 Sept 2012";
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 "2012-09-12T18:15:39Z";
String date_modified "2019-03-01T21:25:08Z";
String defaultDataQuery "&time<now";
String doi "10.1575/1912/bco-dmo.3719.1";
String history
"2024-11-23T07:59:37Z (local files)
2024-11-23T07:59:37Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_3719.html";
String infoUrl "https://www.bco-dmo.org/dataset/3719";
String institution "BCO-DMO";
String keywords "average, bco, bco-dmo, biological, chemical, count, count_avg, count_avg_se, count_log10, count_log10_avg, count_log10_avg_se, data, dataset, dmo, erddap, log10, management, oceanography, office, preliminary, protein, protein_avg, protein_avg_se, protein_log10, protein_log10_avg, protein_log10_avg_se, rep, temperature, trial";
String license "https://www.bco-dmo.org/dataset/3719/license";
String metadata_source "https://www.bco-dmo.org/api/dataset/3719";
String param_mapping "{'3719': {}}";
String parameter_source "https://www.bco-dmo.org/mapserver/dataset/3719/parameters";
String people_0_affiliation "Cornell University";
String people_0_affiliation_acronym "Cornell";
String people_0_person_name "Drew Harvell";
String people_0_person_nid "51556";
String people_0_role "Principal Investigator";
String people_0_role_type "originator";
String people_1_affiliation "University of Texas at Arlington";
String people_1_affiliation_acronym "UT Arlington";
String people_1_person_name "Dr Laura Mydlarz";
String people_1_person_nid "51558";
String people_1_role "Co-Principal Investigator";
String people_1_role_type "originator";
String people_2_affiliation "Cornell University";
String people_2_affiliation_acronym "Cornell";
String people_2_person_name "Dr Colleen Burge";
String people_2_person_nid "51557";
String people_2_role "Contact";
String people_2_role_type "related";
String people_3_affiliation "Woods Hole Oceanographic Institution";
String people_3_affiliation_acronym "WHOI BCO-DMO";
String people_3_person_name "Shannon Rauch";
String people_3_person_nid "51498";
String people_3_role "BCO-DMO Data Manager";
String people_3_role_type "related";
String project "Climate_CoralDisease";
String projects_0_acronym "Climate_CoralDisease";
String projects_0_description
"This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).
Coral reef ecosystems are highly endangered by recent increases in temperature and by projected increases in ocean acidification. Although temperature has been identified as a driver of some coral disease outbreaks, nothing is known about direct effects of acidification on host immunity and pathogen virulence, or the potential for synergism with temperature. Natural coral populations often suffer from simultaneous infection by multiple pathogens that can also influence host immune responses, but co-infection dynamics have not been investigated in invertebrate systems lacking classical adaptive immunity. Changing climate will very likely influence the outcome of single and co-infection.
This project will investigate the influence of environmental stress on co-infection dynamics of the sea fan coral, Gorgonia ventalina, with a fungal pathogen, Aspergillus sydowii and a protist parasite, SPX. The goal is to identify the mechanisms through which multiple infections, temperature and acidification modify host resistance, leading to changes in within- and among-colony rates of disease spread.
The objectives of this project are to:
(1) Identify incidence and co-infection frequency of Aspergillus sydowii and SPX. Detailed field surveys of the two diseases will test the hypothesis that co-infection is significant, provide valuable information about drivers of aspergillosis, and will help to characterize an emerging new sea fan disease.
(2) Investigate how co-infection influences sea fan susceptibility, resistance, and within host disease dynamics. Through manipulative lab inoculation experiments we will test the hypothesis that single infections increase susceptibility to a second pathogen.
(3) Examine the effects of temperature increase and ocean acidification on pathogen virulence, on underlying host resistance, and on the dynamics of single and co-infections.
The hypotheses that acidification will increase pathogen virulence and host susceptibility will be tested in a temperature and pH controlled experimental system. This system will also allow the potential synergistic effects of temperature and acidification on host immunity and co-infection dynamics to be explored. The primary intellectual merit of the proposed work will be a greater understanding of how changing climate mediates co-infection and immunity in a non-model invertebrate. While fungal pathogens are primarily opportunistic, labyrinthulid protozoans are recognized as primary pathogens in shellfish. Even in shellfish, little is known about co-infections involving labyrinthulids, and these protists are entirely unstudied in corals.
Publications associated with this project:
Burge CA, Douglas N, Conti-Jerpe I, Weil E, Roberts S, Friedman CS & CD Harvell. (May 2012) Friend or foe: the association of Labyrinthulomycetes with the Caribbean sea fan, Gorgonia ventalina. Dis Aquat Org. 101:1-12. doi: 10.3354/dao02487
Burge CA, Mouchka, ME, Harvell, CD & S Roberts. (In review) Immune response of the Caribbean sea fan, Gorgonia ventalina exposed to an Aplanochytrium parasite as revealed by transcriptome sequencing.";
String projects_0_end_date "2012-07";
String projects_0_geolocation "Florida Keys & Puerto Rico";
String projects_0_name "Influence of Temperature and Acidification on the Dynamics of Coral Co-Infection and Resistance";
String projects_0_project_nid "2232";
String projects_0_start_date "2009-08";
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 "Experimental results on the growth of Aplanochytrium (a sea fan parasite) cells over a temperature gradient. Two types of assays were used in two trials to quantify Labyrinthulomycota cultures: cell counts using a hemocytometer and total protein concentration.";
String title "[sea_fan_parasite_growth] - Experimental results on the growth of Aplanochytrium (a sea fan parasite) cells over a temperature gradient conducted at the Harvell lab at Cornell University (Influence of Temperature and Acidification on the Dynamics of Coral Co-Infection and Resistance)";
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.