BCO-DMO ERDDAP
Accessing BCO-DMO data
log in    
Brought to you by BCO-DMO    

ERDDAP > tabledap > Data Access Form ?

Dataset Title:  Synthesis of publicly-available sequence datasets of the 16S rRNA gene in
environmental DNA extracted from seafloor and subseafloor samples from the
Dorado outcrop, L\u014d'ihi Seamount, North Pond, and Juan de Fuca Ridge flank
Subscribe RSS
Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_789136)
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Files
 
Variable ?   Optional
Constraint #1 ?
Optional
Constraint #2 ?
   Minimum ?
 
   Maximum ?
 
 Plot_Order (unitless) ?          "1"    "not-in-plot_used-i..."
 Sample_Name (unitless) ?          "3830-U1301A-1-MS28..."    "z-6XCC"
 SRA_Run (unitless) ?          "SRR1184143"    "SRX4104088"
 SRA_LibraryName (unitless) ?          "1301A_1A_BAC"    "UN12"
 Study_Nickname (unitless) ?          "JorgensenNP"    "ZinkeDoradoSed"
 Sample_Type (unitless) ?          "Basalt"    "sediment"
 Temp (Temperature, unitless) ?          "cool"    "warm"
 Location (unitless) ?          "Dorado"    "NorthPond"
 depth2 (Depth, unitless) ?          "none"    "subsurface"
 Sequencer_Type (unitless) ?          "454"    "IonTorrent"
 region16S (unitless) ?          "V1-V3"    "V6"
 Primers (unitless) ?          "27F-518R"    "967F-1046R"
 DNAextraction (unitless) ?          "CTABPhenolChloroform"    "TCEPPhenolChloroform"
 DOI (unitless) ?          "10.1038/ismej.2015..."    "doi: 10.3389/fmicb..."
 SRA_Study (unitless) ?          "SRP039455"    "SRP148501"
 
Server-side Functions ?
 distinct() ?
? ("Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.")

File type: (more info)

(Documentation / Bypass this form ? )
 
(Please be patient. It may take a while to get the data.)


 

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  Plot_Order {
    String bcodmo_name "sample";
    String description "Numerical order on the \"Sample\" Axis of invididual samples in Figure 4 of the main text. Values: integers from 1 to 120 for samples included in plot; none, samples from blank DNA extractions used for comparison; not-in-plot_used-in-NMDS, additional sediment comparison samples not included in plots but used in NMDS analysis";
    String long_name "Plot Order";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
    String units "unitless";
  }
  Sample_Name {
    String bcodmo_name "sample";
    String description "Unique name of the sample used in the plot";
    String long_name "Sample Name";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
    String units "unitless";
  }
  SRA_Run {
    String bcodmo_name "accession number";
    String description "Unique Seqence Read Archive (SRA) Accession Number to download fastq-formatted file of sequence data for the Sample_Name from the NCBI Archive";
    String long_name "SRA Run";
    String units "unitless";
  }
  SRA_LibraryName {
    String bcodmo_name "sample_descrip";
    String description "The unique library name given to the Sample_Name by the authors as listed on the NCBI archive";
    String long_name "SRA Library Name";
    String units "unitless";
  }
  Study_Nickname {
    String bcodmo_name "reference_paper";
    String description "Short hand code referencing the first author and location of a given study";
    String long_name "Study Nickname";
    String units "unitless";
  }
  Sample_Type {
    String bcodmo_name "sample_descrip";
    String description "Environmental type that the sample was collected from. Values: Basalt, Seafloor or subseafloor basalt core samle; FLOCS, mineral colonization experiment from an in situ sytem; Fluids,  subsurface crustal fluids collected from a subseafloor observatory; Sediment, sediment core samples; SW, bottom seawater near field sites; blank, DNA extraction blank";
    String long_name "Sample Type";
    String units "unitless";
  }
  Temp {
    String bcodmo_name "sample_descrip";
    String description "Description of the temperature of the sampling environment. Values: cool, 10 degrees C; na, not applicable";
    String long_name "Temperature";
    String units "unitless";
  }
  Location {
    String bcodmo_name "site";
    String description "Descriptive name of field site where Sample_Name originated. Values: NorthPond; Dorado; Loihi; JuanDeFuca";
    String long_name "Location";
    String units "unitless";
  }
  depth2 {
    String bcodmo_name "sample_descrip";
    String description "Descriptive category of the relative position of the Sample_Name in the environment. Values: seafloor, collected from the seafloor; subsurface, below the seafloor; none, not applicable";
    String long_name "Depth";
    String standard_name "depth";
    String units "unitless";
  }
  Sequencer_Type {
    String bcodmo_name "instrument";
    String description "Sequencing platform used to sequence extracted DNA from the Sample_Name. Values: IonTorrent; Illumina; 454";
    String long_name "Sequencer Type";
    String units "unitless";
  }
  region16S {
    String bcodmo_name "sample_descrip";
    String description "Variable region(s) of the 16S rRNA gene that was sequenced from the extracted DNA from the Sample_Name, as desxcribed in the primary literature. Values: V4; V6; V4-V6; V1-V3";
    String long_name "Region16 S";
    String units "unitless";
  }
  Primers {
    String bcodmo_name "sampling_method";
    String description "Primer set used to amplify the 16S rRNA variable region(s) from the DNA prior to sequencing of the Sample_Name, as described in the primary literature. Values: 519F-805R; 515F-806R; 967F-1046R; 518F-1064R; 28F-388R; 27F-518R";
    String long_name "Primers";
    String units "unitless";
  }
  DNAextraction {
    String bcodmo_name "sampling_method";
    String description "Short-hand name for protocol used for extracting DNA from the sample, as described in the primary literature. Values: MPBiomedicalsFastDNA; CTABPhenolChloroform; TCEPPhenolChloroform; MoBioPowerSoil; EnzymePhenolChloroform; SDSPhenolChloroform";
    String long_name "DNAextraction";
    String units "unitless";
  }
  DOI {
    String bcodmo_name "reference_paper";
    String description "Digital Object Identitfyer information for publications that describe the original study for the data used here";
    String long_name "DOI";
    String units "unitless";
  }
  SRA_Study {
    String bcodmo_name "accession number";
    String description "Sequence Read Archive Identifier number for finding original datafiles on the NCBI Archive";
    String long_name "SRA Study";
    String units "unitless";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
    String acquisition_description 
"Analysis of publicly available 16S rRNA gene sequence datasets for taxonomic
profiling
 
To summarize crustal bacterial and archaeal taxa for this review, we
synthesized publicly-available sequence datasets of the 16S rRNA gene in
environmental DNA extracted from seafloor and subseafloor basalts generated
using 454, Illumina and Ion Torrent amplicon platforms. These include seafloor
basalts from the Dorado Outcrop (Lee et al., 2015) and the L\\u014d'ihi
Seamount (Jacobsen Meyers et al., 2014) in the Pacific Ocean and subseafloor
basalts from North Pond on the western flank of the Mid-Atlantic Ridge
(J\\u00f8rgensen & Zhao, 2016) and the Juan de Fuca Ridge flank in the
northeastern Pacific Ocean (LaBont\\u00e9 et al., 2017). Datasets from rock
colonization experiments conducted in the subseafloor at the Juan de Fuca
Ridge flank site (Smith et al., 2016; Ram\\u00edrez et al., 2019) were also
included, as well as microbial community surveys of the subseafloor crustal
fluids from the anoxic Juan de Fuca site (Jungbluth et al., 2016) and the oxic
North Pond site (Tully et al., 2017; Meyer et al., 2016). For comparison, we
included select reference datasets from oxic (Reese et al., 2018; Zinke et
al., 2018) and anoxic sediment (LaBont\\u00e9 et al., 2017) and the overlying
bottom seawater (Lee et al., 2015) from these same study sites.
 
Raw sequence data from the reviewed studies were downloaded from the NCBI
Short Read Archive. Sequencing reads generated using Illumina and Ion Torrent
platforms were quality filtered and processed to unique Amplicon Sequence
Variants (ASVs) using DADA2 (Callahan et al, 2016), with taxonomy determined
by the na\\u00efve Bayesian classifier in DADA2 using a training set from the
SILVA v132 database (Quast et al., 2013; Yilmaz et al., 2014; Gl\\u00f6ckner et
al., 2017). For the 454 GS-FLX sequence datasets, operational taxonomic units
(OTUs) constructed with 97% or greater sequence similarity in the original
analyses were reprocessed in mothur V.1.37.6 (Schloss et al., 2009) against
the same SILVA database. All short read datasets were merged and summarized to
the relative abundance at phylum resolution (or to class level for
Proteobacteria phyla) using Phyloseq v1.24.0 (McMurdie & Holmes, 2013).
Figures were produced using ggplot2 R package version 2.2.1 (Wickham, 2016) in
RStudio (RStudio Team, 2017). Taxonomic grouping in each sample separated taxa
into common (>5% abundance in at least one sample) versus rare (never more
than 5% in any sample). Supplemental Figure S1 shows the breakdown of
Gammaproteobacteria families in the samples presented in Figure 4 of the main
text, and Supplemental Figure S2 highlights the abundance of rare taxa (never
>5% abundance in any sample). The Bray-Curtis distances between samples was
calculated using the same dataset described above, summarized to relative
abundance at the Family taxonomic level using Phyloseq and the Vegan package
(Oksanen et al., 2018). A Non-Metric Multidimensional Scaling (NMDS)
ordination was produced from this distance matrix. It should be noted that
common rules for beta diversity comparisons, such as common library
preparation/sequencing protocols and library-size normalization, were not
performed in this analysis due to the diversity of the datasets being
considered and the resulting NMDS ordination having high-stress (>20%).
Therefore, the results should be viewed as broadly qualitative and not
quantitative.
 
All data processing steps and markdown files are available via github:
[https://github.com/orcuttlab/ocean-crust-
micro](\\\\\"https://github.com/orcuttlab/ocean-crust-micro\\\\\")";
    String awards_0_award_nid "700323";
    String awards_0_award_number "OCE-1737017";
    String awards_0_data_url "https://www.nsf.gov/awardsearch/showAward?AWD_ID=1737017";
    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 
"Metadata for sequence datasets used in ocean crust microbiome survey 
  PI: Beth Orcutt (Bigelow) 
  Co-PI: Timothy D'Angelo (Bigelow) 
  Version date: 04-Feb-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 date_created "2020-02-04T18:08:53Z";
    String date_modified "2020-02-05T16:01:31Z";
    String defaultDataQuery "&time<now";
    String doi "10.1575/1912/bco-dmo.789136.1";
    String history 
"2024-02-28T12:24:20Z (local files)
2024-02-28T12:24:20Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_789136.html";
    String infoUrl "https://www.bco-dmo.org/dataset/789136";
    String institution "BCO-DMO";
    String keywords "bco, bco-dmo, biological, chemical, data, dataset, depth, depth2, dmo, dnaextraction, doi, erddap, library, Location, management, name, nickname, oceanography, office, order, plot, Plot_Order, preliminary, primers, region16, region16S, run, sample, Sample_Name, Sample_Type, sequencer, Sequencer_Type, sra, SRA_LibraryName, SRA_Run, SRA_Study, study, Study_Nickname, Temp, temperature, type";
    String license "https://www.bco-dmo.org/dataset/789136/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/789136";
    String param_mapping "{'789136': {}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/789136/parameters";
    String people_0_affiliation "Bigelow Laboratory for Ocean Sciences";
    String people_0_person_name "Beth N. Orcutt";
    String people_0_person_nid "565799";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "Bigelow Laboratory for Ocean Sciences";
    String people_1_person_name "Timothy D'Angelo";
    String people_1_person_nid "756164";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "Woods Hole Oceanographic Institution";
    String people_2_affiliation_acronym "WHOI BCO-DMO";
    String people_2_person_name "Shannon Rauch";
    String people_2_person_nid "51498";
    String people_2_role "BCO-DMO Data Manager";
    String people_2_role_type "related";
    String project "Slow Life in Crust";
    String projects_0_acronym "Slow Life in Crust";
    String projects_0_description 
"NSF Award Abstract:
The marine deep biosphere is the habitat for life existing under the sea floor. The zone has remarkably low energy sources creating a paradox of how life can persist there. Resolving this energy paradox is a grand challenge in deep biosphere research. The Juan de Fuca Ridge flank off the coast of Washington, USA, is an accessible, low energy environment making it an attractive location for addressing this challenge. A series of experiments will be conducted on the seafloor at the Juan de Fuca Ridge flank, using established subseafloor observatories that access the crustal deep biosphere, to provide the first direct in situ measurement of microbial activity in the crustal subsurface. This project will provide essential information about the ability of life to survive under conditions that we are not able to replicate in the laboratory, but that are increasingly important for understanding microbial community interaction in the environment. This information can then be used in models of global microbial activity for estimating the impact of this biosphere on elemental cycling, transforming our understanding of microbial processes within this vast subseafloor habitat. To communicate these discoveries to the public, the project will include a ship-to-shore outreach program during the cruise. In addition public lectures will be presented, and an interactive display of deep-sea video footage will be set up for the annual public Open House at the Bigelow Laboratory for Ocean Sciences in Maine. Diverse undergraduate students and a postdoctoral researcher will be recruited to participate in the research and public outreach activities.
This project proposes to leverage existing subsurface infrastructure on the eastern flank of the Juan de Fuca Ridge with advances in single-cell based molecular and geochemical approaches to make fundamental new discoveries about the activity of life in the deep crustal biosphere. During a two-week research cruise, the research team will incubate crustal fluids in situ and in the laboratory with labeled substrates for tracking single-cell activity, coupled with radioisotope tracer activity and potentiostat measurements, with the objective of determining in situ and potential rates of activity and cellular physiology. The research will also identify which metabolisms active microorganisms utilize under in situ and laboratory conditions, the rates of these processes, and the microorganisms involved. The results are expected to provide explicit hypothesis testing of microbial activity and in situ microbial growth rates from the crustal deep biosphere to transform understanding of microbial activity in the crustal deep biosphere and generate critical information about the ability of life to survive under low energy conditions.";
    String projects_0_geolocation "Juan de Fuca Ridge flank CORKs, 47N/127W";
    String projects_0_name "Microbial activity in the crustal deep biosphere";
    String projects_0_project_nid "700324";
    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 "To summarize crustal bacterial and archaeal taxa for this review, we synthesized publicly-available sequence datasets of the 16S rRNA gene in environmental DNA extracted from seafloor and subseafloor basalts generated using 454, Illumina and Ion Torrent amplicon platforms. These include seafloor basalts from the Dorado Outcrop and the L\\u014d'ihi Seamount in the Pacific Ocean and subseafloor basalts from North Pond on the western flank of the Mid-Atlantic Ridge and the Juan de Fuca Ridge flank in the northeastern Pacific Ocean. Datasets from rock colonization experiments conducted in the subseafloor at the Juan de Fuca Ridge flank site were also included, as well as microbial community surveys of the subseafloor crustal fluids from the anoxic Juan de Fuca site and the oxic North Pond site.";
    String title "Synthesis of publicly-available sequence datasets of the 16S rRNA gene in environmental DNA extracted from seafloor and subseafloor samples from the Dorado outcrop, L\\u014d'ihi Seamount, North Pond, and Juan de Fuca Ridge flank";
    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
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.


 
ERDDAP, Version 2.02
Disclaimers | Privacy Policy | Contact