http://lod.bco-dmo.org/id/dataset/789136
eng; USA
utf8
dataset
Highest level of data collection, from a common set of sensors or instrumentation, usually within the same research project
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
2020-02-04
ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data
ISO 19115-2:2009(E)
Synthesis of publicly-available sequence datasets of the 16S rRNA gene in environmental DNA extracted from seafloor and subseafloor samples from the Dorado outcrop, Lō'ihi Seamount, North Pond, and Juan de Fuca Ridge flank
2020-02-04
publication
2020-02-04
revision
Marine Biological Laboratory/Woods Hole Oceanographic Institution Library (MBLWHOI DLA)
2020-02-05
publication
https://doi.org/10.1575/1912/bco-dmo.789136.1
Beth N. Orcutt
Bigelow Laboratory for Ocean Sciences
principalInvestigator
Timothy D'Angelo
Bigelow Laboratory for Ocean Sciences
principalInvestigator
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
publisher
Cite this dataset as: Orcutt, B., D'Angelo, T. (2020) Synthesis of publicly-available sequence datasets of the 16S rRNA gene in environmental DNA extracted from seafloor and subseafloor samples from the Dorado outcrop, Lō'ihi Seamount, North Pond, and Juan de Fuca Ridge flank. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2020-02-04 [if applicable, indicate subset used]. doi:10.1575/1912/bco-dmo.789136.1 [access date]
Metadata for sequence datasets used in ocean crust microbiome survey Dataset Description: <p>Metadata for sequence datasets used in ocean crust microbiome survey.</p>
<p>This metadata table and supporting PDF document describe data analysis performed for a review chapter to be published in an edited book:</p>
<p>Authors: Beth N. Orcutt, Timothy D'Angelo, Sean P. Jungbluth, Julie&nbsp;A. Huber, Jason B. Sylvan<br />
Chapter Title: Microbial Life in Oceanic Crust<br />
Book title: The Microbiology of the Deep-Sea<br />
Editors: Donato Giovannelli, Costantino Vetriani<br />
Publisher: Springer International Publishing AG</p> Methods and Sampling: <p><em>Analysis of publicly available 16S rRNA gene sequence datasets for taxonomic profiling</em></p>
<p>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 Lō'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 (Jørgensen &amp; Zhao, 2016) and the Juan de Fuca Ridge flank in the northeastern Pacific Ocean (LaBonté et al., 2017). Datasets from rock colonization experiments conducted in the subseafloor at the Juan de Fuca Ridge flank site (Smith et al., 2016; Ramírez 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 (LaBonté et al., 2017) and the overlying bottom seawater (Lee et al., 2015) from these same study sites.</p>
<p>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 naïve Bayesian classifier in DADA2 using a training set from the SILVA v132 database (Quast et al., 2013; Yilmaz et al., 2014; Glöckner 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 &amp; 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 (&gt;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 &gt;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 (&gt;20%). Therefore, the results should be viewed as broadly qualitative and not quantitative.</p>
<p>All data processing steps and markdown files are available via github: <a href="https://github.com/orcuttlab/ocean-crust-micro" target="_blank">https://github.com/orcuttlab/ocean-crust-micro</a></p>
Funding provided by NSF Division of Ocean Sciences (NSF OCE) Award Number: OCE-1737017 Award URL: https://www.nsf.gov/awardsearch/show-award?AWD_ID=1737017
completed
Beth N. Orcutt
Bigelow Laboratory for Ocean Sciences
207-315-2567 ext 312
60 Bigelow Drive PO Box 380
East Boothbay
Maine
04544
USA
borcutt@bigelow.org
pointOfContact
Timothy D'Angelo
Bigelow Laboratory for Ocean Sciences
207-315-2567
60 Bigelow Drive
East Boothbay
ME
04544
USA
tdangelo@bigelow.org
pointOfContact
asNeeded
Dataset Version: 1
Unknown
Plot_Order
Sample_Name
SRA_Run
SRA_LibraryName
Study_Nickname
Sample_Type
Temp
Location
Depth
Sequencer_Type
region16S
Primers
DNAextraction
DOI
SRA_Study
theme
None, User defined
sample identification
accession number
sample description
reference_paper
site
instrument
sampling_method
featureType
BCO-DMO Standard Parameters
otherRestrictions
otherRestrictions
Access Constraints: none. Use Constraints: Please follow guidelines at: http://www.bco-dmo.org/terms-use Distribution liability: Under no circumstances shall BCO-DMO be liable for any direct, incidental, special, consequential, indirect, or punitive damages that result from the use of, or the inability to use, the materials in this data submission. If you are dissatisfied with any materials in this data submission your sole and exclusive remedy is to discontinue use.
Microbial activity in the crustal deep biosphere
https://osprey.bco-dmo.org/project/700324
Microbial activity in the crustal deep biosphere
<p><em>NSF Award Abstract:</em><br />
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.</p>
<p>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.</p>
Slow Life in Crust
largerWorkCitation
project
eng; USA
oceans
-155.27
-46
10
45.62
2014-01-01
2019-12-31
Juan de Fuca Ridge flank CORKs, 47N/127W
0
BCO-DMO catalogue of parameters from Synthesis of publicly-available sequence datasets of the 16S rRNA gene in environmental DNA extracted from seafloor and subseafloor samples from the Dorado outcrop, Lō'ihi Seamount, North Pond, and Juan de Fuca Ridge flank
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
http://lod.bco-dmo.org/id/dataset-parameter/789226.rdf
Name: Plot_Order
Units: unitless
Description: <p>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</p>
http://lod.bco-dmo.org/id/dataset-parameter/789227.rdf
Name: Sample_Name
Units: unitless
Description: <p>Unique name of the sample used in the plot</p>
http://lod.bco-dmo.org/id/dataset-parameter/789228.rdf
Name: SRA_Run
Units: unitless
Description: <p>Unique Seqence Read Archive (SRA) Accession Number to download fastq-formatted file of sequence data for the Sample_Name from the NCBI Archive</p>
http://lod.bco-dmo.org/id/dataset-parameter/789229.rdf
Name: SRA_LibraryName
Units: unitless
Description: <p>The unique library name given to the Sample_Name by the authors as listed on the NCBI archive</p>
http://lod.bco-dmo.org/id/dataset-parameter/789230.rdf
Name: Study_Nickname
Units: unitless
Description: <p>Short hand code referencing the first author and location of a given study</p>
http://lod.bco-dmo.org/id/dataset-parameter/789231.rdf
Name: Sample_Type
Units: unitless
Description: <p>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</p>
http://lod.bco-dmo.org/id/dataset-parameter/789232.rdf
Name: Temp
Units: unitless
Description: <p>Description of the temperature of the sampling environment. Values: cool, <10 degrees C; warm, >10 degrees C; na, not applicable</p>
http://lod.bco-dmo.org/id/dataset-parameter/789233.rdf
Name: Location
Units: unitless
Description: <p>Descriptive name of field site where Sample_Name originated. Values: NorthPond; Dorado; Loihi; JuanDeFuca</p>
http://lod.bco-dmo.org/id/dataset-parameter/789234.rdf
Name: Depth
Units: unitless
Description: <p>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</p>
http://lod.bco-dmo.org/id/dataset-parameter/789235.rdf
Name: Sequencer_Type
Units: unitless
Description: <p>Sequencing platform used to sequence extracted DNA from the Sample_Name. Values: IonTorrent; Illumina; 454</p>
http://lod.bco-dmo.org/id/dataset-parameter/789236.rdf
Name: region16S
Units: unitless
Description: <p>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</p>
http://lod.bco-dmo.org/id/dataset-parameter/789237.rdf
Name: Primers
Units: unitless
Description: <p>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</p>
http://lod.bco-dmo.org/id/dataset-parameter/789238.rdf
Name: DNAextraction
Units: unitless
Description: <p>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</p>
http://lod.bco-dmo.org/id/dataset-parameter/789239.rdf
Name: DOI
Units: unitless
Description: <p>Digital Object Identitfyer information for publications that describe the original study for the data used here</p>
http://lod.bco-dmo.org/id/dataset-parameter/789240.rdf
Name: SRA_Study
Units: unitless
Description: <p>Sequence Read Archive Identifier number for finding original datafiles on the NCBI Archive</p>
GB/NERC/BODC > British Oceanographic Data Centre, Natural Environment Research Council, United Kingdom
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
22720
https://darchive.mblwhoilibrary.org/bitstream/1912/25316/1/dataset-789136_ocean-crust-microbiome-amplicon-metadata__v1.tsv
download
https://doi.org/10.1575/1912/bco-dmo.789136.1
download
onLine
dataset
<p><em>Analysis of publicly available 16S rRNA gene sequence datasets for taxonomic profiling</em></p>
<p>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 Lō'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 (Jørgensen &amp; Zhao, 2016) and the Juan de Fuca Ridge flank in the northeastern Pacific Ocean (LaBonté et al., 2017). Datasets from rock colonization experiments conducted in the subseafloor at the Juan de Fuca Ridge flank site (Smith et al., 2016; Ramírez 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 (LaBonté et al., 2017) and the overlying bottom seawater (Lee et al., 2015) from these same study sites.</p>
<p>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 naïve Bayesian classifier in DADA2 using a training set from the SILVA v132 database (Quast et al., 2013; Yilmaz et al., 2014; Glöckner 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 &amp; 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 (&gt;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 &gt;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 (&gt;20%). Therefore, the results should be viewed as broadly qualitative and not quantitative.</p>
<p>All data processing steps and markdown files are available via github: <a href="https://github.com/orcuttlab/ocean-crust-micro" target="_blank">https://github.com/orcuttlab/ocean-crust-micro</a></p>
Specified by the Principal Investigator(s)
asNeeded
7.x-1.1
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact