http://lod.bco-dmo.org/id/dataset/654371
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
2016-08-18
ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data
ISO 19115-2:2009(E)
Potential nitrification rates and ammonia oxidizer gene abundances collected on R/V Endeavor (SQO-Delta) in the San Francisco Bay Delta during September and October 2007
2016-08-18
publication
2016-08-18
revision
Marine Biological Laboratory/Woods Hole Oceanographic Institution Library (MBLWHOI DLA)
2019-05-22
publication
https://doi.org/10.1575/1912/bco-dmo.654371.1
Christopher Francis
Stanford University
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: Francis, C. (2016) Potential nitrification rates and ammonia oxidizer gene abundances collected on R/V Endeavor (SQO-Delta) in the San Francisco Bay Delta during September and October 2007. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2016-08-18 [if applicable, indicate subset used]. doi:10.1575/1912/bco-dmo.654371.1 [access date]
Nitrification rates and ammonia oxidizer gene abundances Dataset Description: <p>Surface sediment samples were collected for potential nitrification rates, using sediment slurries with filtered site water. Ammonia oxidizer gene abundances (AOA and AOB <em>amoA</em>) were quantified using qPCR, and clone libraries for each gene were sequenced using Sanger sequencing.</p>
<p><strong>Related Manuscript: Damasheck <em>et al., </em>2015</strong></p>
<p>&nbsp;</p> Methods and Sampling: <p>Surface sediment was retrieved using a modified Van Veen grab. Duplicate cores were taken from each grab sample using sterile, cut-off 5 mL syringes and immediately placed on dry ice prior to storage at –80 degrees celsius. Bottom water nutrient samples were collected in triplicate using a hand-held Niskin bottle, immediately filtered (0.2 um pore size), and frozen on dry ice prior to storage at –20 degrees celsius. Nutrient (NH4+, NO2-, and NO3-) concentrations were measured using a QuikChem 8000 Flow Injection Analyzer (Lachat Instruments).&nbsp;</p>
<p>Sediment samples for potential nitrification rate measurements were collected in triplicate into the barrels of cut-off 60 mL syringes, which were sealed with parafilm and transported to the laboratory on ice. Potential rates were measured using amended sediment slurries. Slurries included 5 g of sediment (top 1 cm) homogenized in 100 mL of filtered bottom water augmented with NH4+ and phosphate to final additional concentrations of 500 and 100 uM, respectively. Amended slurries were shaken (200 rpm) in the dark for 24 hours at room temperature (about 22 degrees celsius). Aliquots for the determination of NO3- plus NO2- (NOX) were collected at evenly spaced intervals through the incubation period and stored at –20 degrees celsius. Prior to analysis, aliquots were thawed and passed through Whatman No. 42 filter paper, and the filtrate was analyzed for the accumulation of NOx over time, using a SmartChem 200 Discrete Analyzer (Unity Scientific). Rates were determined by linear regression of NOx concentrations over time.</p>
<p>DNA was extracted from approximately 0.5 g of surface sediments by extruding and cutting the top 0.5 cm from frozen cores with a sterile scalpel and immediately proceeding with the FastDNA SPIN Kit for Soil (MP Biomedicals), including a FastPrep bead beating step of 30 s at speed 5.5. AOA and AOB <em>amoA</em> genes were quantified using gene-specific SYBR qPCR assays on a StepOnePlus Real-Time PCR System (Life Technologies). AOA <em>amoA</em> reactions contained iTaq SYBR Green Supermix with ROX (Bio-Rad Laboratories), 0.4 uM primers Arch-amoAF/Arch-amoAR (Francis et al., 2005) and 1 uL template DNA. AOA qPCR program details were identical to previously published protocols (Mosier and Francis, 2008) but with a 10 s detection step at 78.5 degrees celsius. AOB <em>amoA</em> qPCR reactions used primers amoA1F/amoA2R (Rotthauwe et al., 1997), and were set up following Mosier and Francis (2008) but with a 10 s detection step at 83 degress celsius. Each plate included a standard curve (5 to 10^6 copies/reaction) made by serial dilution of linearized plasmids extracted from previously sequenced clones, and negative controls that substituted sterile water for DNA. The diversity of ammonia oxidizing communities was determined by cloning and sequencing of PCR-amplified <em>amoA</em> genes using primers Arch-amoAF/Arch-amoAR (Francis et al., 2005) and amoA1F*/amoA2R (Rotthauwe et al., 1997; Stephen et al., 1999) for AOA and AOB, respectively. Reaction conditions and PCR programs followed previously published protocols (Mosier and Francis, 2008). Triplicate reactions were qualitatively checked by gel electrophoresis, pooled, and purified using the MinElute PCR Purification Kit or MinElute Gel Extraction Kit (Qiagen), following the manufacturer’s instructions. Purified products were cloned using the pGEM-T Vector System II (Promega), and sequenced by Elim Biopharmaceuticals on a 3730xl capillary sequencer (Life Technologies). Sequences were imported into Geneious (version 6.1.6 created by Biomatters, available from http://www.geneious.com) and manually cleaned prior to operational taxonomic unit (OTU) grouping (greater than or equal to 95% sequence similarity) using mothur (Schloss et al., 2009). Rarefaction curves and diversity/richness estimators (Chao1 and Shannon indices) were calculated using mothur. OTUs were aligned with reference sequences using the MUSCLE alignment package within Geneious, using a gap open score of –750. Alignments were manually checked and used to build neighbor-joining bootstrap trees (Jukes-Cantor distance model, 1000 neighbor joining bootstrap replicates) within Geneious. The <em>amoA </em>sequences generated in this study have been deposited into GenBank with accession numbers KM000240 to KM000508 (AOB) and KM000509 to KM000784 (AOA).</p>
<p>Two-tailed Spearman rank correlation coefficients (ρ) were calculated using R (R Core Team, 2014) to determine correlations between variables, using the suggested critical value of 0.786 for 5% significance with a sample size of 7 (Zar, 1972). Principal component and non-metric multidimensional scaling analyses were performed using the vegan package in R (Oksanen, 2013). Environmental variables were z-transformed to standardize across different scales and units by subtracting the population mean from each measurement and dividing by the standard deviation. OTU count data were Hellinger-transformed to standardize to relative abundances (Legendre and Legendre, 2012). Other than unweighted UniFrac distances, which were calculated using the online UniFrac portal (Lozupone et al., 2006), distance/dissimilarity indices were calculated using the vegan package in R. All principle component analyses are presented using scaling 1; therefore, the distance between sites on the biplot represents their Euclidean distance, and the right-angle projection of a site onto a descriptor vector shows the approximate position of that site on the vector (Legendre and Legendre, 2012).&nbsp;</p>
Funding provided by NSF Division of Ocean Sciences (NSF OCE) Award Number: OCE-0847266 Award URL: https://www.nsf.gov/awardsearch/show-award?AWD_ID=0847266
completed
Christopher Francis
Stanford University
650-724-0301
Environmental Earth System Science 473 Via Ortega, Y2E2 Bldg
Stanford
CA
94305-4216
USA
caf@stanford.edu
pointOfContact
asNeeded
Dataset Version: 1
Unknown
station
lat
lon
date
AOA_amoA
AOB_amoA
log_AOAtoAOB
NO2
NO3
NH4
nitrification
SmartChem 200 Discrete Analyzer
QuikChem 8000
Niskin bottle
StepOnePlus Real-Time PCR System
theme
None, User defined
station
latitude
longitude
date
abundance
Nitrite
Nitrate
Ammonium
No BCO-DMO term
featureType
BCO-DMO Standard Parameters
Discrete Analyzer
Flow Injection Analyzer
Niskin bottle
Thermal Cycler
instrument
BCO-DMO Standard Instruments
SQO-Delta
service
Deployment Activity
San Francisco Bay Delta
place
Locations
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.
Spatial and Temporal Dynamics of Nitrogen-Cycling Microbial Communities Across Physicochemical Gradients in the San Francisco Bay Estuary
https://osprey.bco-dmo.org/project/546278
Spatial and Temporal Dynamics of Nitrogen-Cycling Microbial Communities Across Physicochemical Gradients in the San Francisco Bay Estuary
<p><em>Description from the NSF award abstract:</em></p>
<p>This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).</p>
<p>Although nitrogen (N) acts as a limiting nutrient in many marine ecosystems, from estuaries to the open ocean, N in excess can be extremely detrimental. Eutrophication is of particular concern in estuaries, with over half of the estuaries in the United States experiencing its effects. Harmful levels of N in estuaries can be diminished through tightly coupled processes in the microbial nitrogen cycle, including nitrification (chemoautotrophic oxidation of ammonia to nitrite and nitrate) and denitrification (the dissimilatory reduction of nitrate to N2 gas). In fact, coupled nitrification-denitrification can remove up to 50% of external dissolved inorganic nitrogen inputs to estuaries, thereby reducing the risk of eutrophication. Despite the biogeochemical importance of both nitrification and denitrification in estuarine systems, surprisingly little is known regarding the underlying microbial communities responsible for these processes, or how they are influenced by key physical/chemical factors.</p>
<p>The investigators will work in San Francisco Bay - the largest estuary on the west coast of the United States - using molecular, biogeochemical and cultivation approaches to explore how the distribution, diversity, abundance, and activities of key N-cycling communities are influenced by environmental gradients over temporal and spatial scales. Denitrifying communities will be studied using functional genes (nirK and nirS) encoding the key denitrification enzyme nitrite reductase, while genes encoding ammonia monooxygenase subunit A (amoA) will be used to study both ammonia-oxidizing bacteria (AOB) and the recently-discovered ammonia-oxidizing archaea (AOA)- members of one of the most ubiquitous and abundant prokaryotic groups on the planet, the mesophilic Crenarchaeota. Analyzing sediments from sites spanning a range of physical and chemical conditions in the Bay, seasonally over the course of several years, will represent an unprecedented opportunity to examine spatial, physical/chemical, and temporal effects on both denitrifier and ammonia-oxidizer communities in this large, urban estuary. Concurrently, an intensive cultivation effort will also be undertaken, in order to compile a novel culture collection of estuarine denitrifiers and ammonia-oxidizers, for which virtually nothing is currently known. Taken together, these complimentary approaches will help reveal how complex physical/chemical gradients influence the diversity and functioning of key estuarine N-cycling communities over time and space.</p>
N-Cycling Microbial Communities
largerWorkCitation
project
eng; USA
oceans
San Francisco Bay Delta
-121.850917
-121.597033
38.017617
38.167117
2007-09-17
2007-10-10
San Francisco Bay
0
BCO-DMO catalogue of parameters from Potential nitrification rates and ammonia oxidizer gene abundances collected on R/V Endeavor (SQO-Delta) in the San Francisco Bay Delta during September and October 2007
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/654382.rdf
Name: station
Units: unitless
Description: <p>station where sample was taken</p>
http://lod.bco-dmo.org/id/dataset-parameter/654383.rdf
Name: lat
Units: decimal degrees
Description: <p>latitude</p>
http://lod.bco-dmo.org/id/dataset-parameter/654384.rdf
Name: lon
Units: decimal degrees
Description: <p>longitude</p>
http://lod.bco-dmo.org/id/dataset-parameter/654385.rdf
Name: date
Units: unitless
Description: <p>date when sample was taken; mm/dd/yyyy</p>
http://lod.bco-dmo.org/id/dataset-parameter/654386.rdf
Name: AOA_amoA
Units: genes g -1 of wet sediment
Description: <p>abundance of archaeal amoA genes in surface sediments</p>
http://lod.bco-dmo.org/id/dataset-parameter/654387.rdf
Name: AOB_amoA
Units: genes g -1 of wet sediment
Description: <p>abundance of bacterial amoA genes in surface sediments</p>
http://lod.bco-dmo.org/id/dataset-parameter/654388.rdf
Name: log_AOAtoAOB
Units: dimensionless
Description: <p>AOA gene abundances divided by AOB gene abundances, log10 transformed</p>
http://lod.bco-dmo.org/id/dataset-parameter/654389.rdf
Name: NO2
Units: micromoles
Description: <p>nitrite concentrations in bottom water</p>
http://lod.bco-dmo.org/id/dataset-parameter/654390.rdf
Name: NO3
Units: micromoles
Description: <p>nitrate concentrations in bottom water</p>
http://lod.bco-dmo.org/id/dataset-parameter/654391.rdf
Name: NH4
Units: micromoles
Description: <p>ammonium concentrations in bottom water</p>
http://lod.bco-dmo.org/id/dataset-parameter/654392.rdf
Name: nitrification
Units: nmol NOx g-1 h-1
Description: <p>potential nitrification rates in surface sediments</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
685
https://darchive.mblwhoilibrary.org/bitstream/1912/24158/1/dataset-654371_delta-nitrification-study-potential-nitrification-rates__v1.tsv
download
https://doi.org/10.1575/1912/bco-dmo.654371.1
download
onLine
dataset
<p>Surface sediment was retrieved using a modified Van Veen grab. Duplicate cores were taken from each grab sample using sterile, cut-off 5 mL syringes and immediately placed on dry ice prior to storage at –80 degrees celsius. Bottom water nutrient samples were collected in triplicate using a hand-held Niskin bottle, immediately filtered (0.2 um pore size), and frozen on dry ice prior to storage at –20 degrees celsius. Nutrient (NH4+, NO2-, and NO3-) concentrations were measured using a QuikChem 8000 Flow Injection Analyzer (Lachat Instruments).&nbsp;</p>
<p>Sediment samples for potential nitrification rate measurements were collected in triplicate into the barrels of cut-off 60 mL syringes, which were sealed with parafilm and transported to the laboratory on ice. Potential rates were measured using amended sediment slurries. Slurries included 5 g of sediment (top 1 cm) homogenized in 100 mL of filtered bottom water augmented with NH4+ and phosphate to final additional concentrations of 500 and 100 uM, respectively. Amended slurries were shaken (200 rpm) in the dark for 24 hours at room temperature (about 22 degrees celsius). Aliquots for the determination of NO3- plus NO2- (NOX) were collected at evenly spaced intervals through the incubation period and stored at –20 degrees celsius. Prior to analysis, aliquots were thawed and passed through Whatman No. 42 filter paper, and the filtrate was analyzed for the accumulation of NOx over time, using a SmartChem 200 Discrete Analyzer (Unity Scientific). Rates were determined by linear regression of NOx concentrations over time.</p>
<p>DNA was extracted from approximately 0.5 g of surface sediments by extruding and cutting the top 0.5 cm from frozen cores with a sterile scalpel and immediately proceeding with the FastDNA SPIN Kit for Soil (MP Biomedicals), including a FastPrep bead beating step of 30 s at speed 5.5. AOA and AOB <em>amoA</em> genes were quantified using gene-specific SYBR qPCR assays on a StepOnePlus Real-Time PCR System (Life Technologies). AOA <em>amoA</em> reactions contained iTaq SYBR Green Supermix with ROX (Bio-Rad Laboratories), 0.4 uM primers Arch-amoAF/Arch-amoAR (Francis et al., 2005) and 1 uL template DNA. AOA qPCR program details were identical to previously published protocols (Mosier and Francis, 2008) but with a 10 s detection step at 78.5 degrees celsius. AOB <em>amoA</em> qPCR reactions used primers amoA1F/amoA2R (Rotthauwe et al., 1997), and were set up following Mosier and Francis (2008) but with a 10 s detection step at 83 degress celsius. Each plate included a standard curve (5 to 10^6 copies/reaction) made by serial dilution of linearized plasmids extracted from previously sequenced clones, and negative controls that substituted sterile water for DNA. The diversity of ammonia oxidizing communities was determined by cloning and sequencing of PCR-amplified <em>amoA</em> genes using primers Arch-amoAF/Arch-amoAR (Francis et al., 2005) and amoA1F*/amoA2R (Rotthauwe et al., 1997; Stephen et al., 1999) for AOA and AOB, respectively. Reaction conditions and PCR programs followed previously published protocols (Mosier and Francis, 2008). Triplicate reactions were qualitatively checked by gel electrophoresis, pooled, and purified using the MinElute PCR Purification Kit or MinElute Gel Extraction Kit (Qiagen), following the manufacturer’s instructions. Purified products were cloned using the pGEM-T Vector System II (Promega), and sequenced by Elim Biopharmaceuticals on a 3730xl capillary sequencer (Life Technologies). Sequences were imported into Geneious (version 6.1.6 created by Biomatters, available from http://www.geneious.com) and manually cleaned prior to operational taxonomic unit (OTU) grouping (greater than or equal to 95% sequence similarity) using mothur (Schloss et al., 2009). Rarefaction curves and diversity/richness estimators (Chao1 and Shannon indices) were calculated using mothur. OTUs were aligned with reference sequences using the MUSCLE alignment package within Geneious, using a gap open score of –750. Alignments were manually checked and used to build neighbor-joining bootstrap trees (Jukes-Cantor distance model, 1000 neighbor joining bootstrap replicates) within Geneious. The <em>amoA </em>sequences generated in this study have been deposited into GenBank with accession numbers KM000240 to KM000508 (AOB) and KM000509 to KM000784 (AOA).</p>
<p>Two-tailed Spearman rank correlation coefficients (ρ) were calculated using R (R Core Team, 2014) to determine correlations between variables, using the suggested critical value of 0.786 for 5% significance with a sample size of 7 (Zar, 1972). Principal component and non-metric multidimensional scaling analyses were performed using the vegan package in R (Oksanen, 2013). Environmental variables were z-transformed to standardize across different scales and units by subtracting the population mean from each measurement and dividing by the standard deviation. OTU count data were Hellinger-transformed to standardize to relative abundances (Legendre and Legendre, 2012). Other than unweighted UniFrac distances, which were calculated using the online UniFrac portal (Lozupone et al., 2006), distance/dissimilarity indices were calculated using the vegan package in R. All principle component analyses are presented using scaling 1; therefore, the distance between sites on the biplot represents their Euclidean distance, and the right-angle projection of a site onto a descriptor vector shows the approximate position of that site on the vector (Legendre and Legendre, 2012).&nbsp;</p>
Specified by the Principal Investigator(s)
<p><span style="font-size:11px"><strong>DMO Notes:</strong></span></p>
<p><span style="font-size:11px">-created a row for every accession number, they were originally&nbsp;presented by the PI as a range.<br />
-added links for every accession number.<br />
-removed all spaces and replaced with underscores.<br />
-reformatted column names to comply with BCO-DMO standards.<br />
-reorganized the data so that all station numbers were grouped together</span></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
SmartChem 200 Discrete Analyzer
SmartChem 200 Discrete Analyzer
PI Supplied Instrument Name: SmartChem 200 Discrete Analyzer PI Supplied Instrument Description:Filtrate analyzed from the accumulation of NOx over time using this discrete analyzer. Instrument Name: Discrete Analyzer Instrument Short Name:Discrete Analyzer Instrument Description: Discrete analyzers utilize discrete reaction wells to mix and develop the colorimetric reaction, allowing for a wide variety of assays to be performed from one sample. These instruments are ideal for drinking water, wastewater, soil testing, environmental and university or research applications where multiple assays and high throughput are required.
QuikChem 8000
QuikChem 8000
PI Supplied Instrument Name: QuikChem 8000 PI Supplied Instrument Description:Concentrations measured via QuikChem 8000 Flow Injection Analyzer Instrument Name: Flow Injection Analyzer Instrument Short Name:FIA Instrument Description: An instrument that performs flow injection analysis. Flow injection analysis (FIA) is an approach to chemical analysis that is accomplished by injecting a plug of sample into a flowing carrier stream. FIA is an automated method in which a sample is injected into a continuous flow of a carrier solution that mixes with other continuously flowing solutions before reaching a detector. Precision is dramatically increased when FIA is used instead of manual injections and as a result very specific FIA systems have been developed for a wide array of analytical techniques. Community Standard Description: http://vocab.nerc.ac.uk/collection/L05/current/LAB36/
Niskin bottle
Niskin bottle
PI Supplied Instrument Name: Niskin bottle PI Supplied Instrument Description:Hand-held Niskin bottle Instrument Name: Niskin bottle Instrument Short Name:Niskin bottle Instrument 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. Community Standard Description: http://vocab.nerc.ac.uk/collection/L22/current/TOOL0412/
StepOnePlus Real-Time PCR System
StepOnePlus Real-Time PCR System
PI Supplied Instrument Name: StepOnePlus Real-Time PCR System PI Supplied Instrument Description:Genes quantified using gene-specific SYBR qPCR assays Instrument Name: Thermal Cycler Instrument Short Name:Thermal Cycler Instrument Description: A thermal cycler or "thermocycler" is a general term for a type of laboratory apparatus, commonly used for performing polymerase chain reaction (PCR), that is capable of repeatedly altering and maintaining specific temperatures for defined periods of time. The device has a thermal block with holes where tubes with the PCR reaction mixtures can be inserted. The cycler then raises and lowers the temperature of the block in discrete, pre-programmed steps. They can also be used to facilitate other temperature-sensitive reactions, including restriction enzyme digestion or rapid diagnostics.
(adapted from http://serc.carleton.edu/microbelife/research_methods/genomics/pcr.html)
Cruise: SQO-Delta
SQO-Delta
R/V Endeavor
Community Standard Description
International Council for the Exploration of the Sea
R/V Endeavor
vessel
SQO-Delta
http://dmoserv3.bco-dmo.org/data_docs/N_Cycling_Microbial_Communities/cruise_reports/2007-08-21-Sediment.pdf
Report describing SQO-Delta
R/V Endeavor
Community Standard Description
International Council for the Exploration of the Sea
R/V Endeavor
vessel