http://lod.bco-dmo.org/id/dataset/928203
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
2024-05-21
ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data
ISO 19115-2:2009(E)
Thalassiosira pseudonana CCMP1335 endometabolite uptake by Ruegeria pomeroyi DSS-3
2025-03-06
publication
2025-03-06
revision
Marine Biological Laboratory/Woods Hole Oceanographic Institution Library (MBLWHOI DLA)
2025-03-07
publication
https://doi.org/10.26008/1912/bco-dmo.928203.1
Mary Ann Moran
University of Georgia
principalInvestigator
Malin Olofsson
University of Georgia
principalInvestigator
Mario Uchimiya
University of Georgia
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: Olofsson, M., Uchimiya, M., Smith, C., Moran, M. A. (2025) Thalassiosira pseudonana CCMP1335 endometabolite uptake by Ruegeria pomeroyi DSS-3. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2025-03-06 [if applicable, indicate subset used]. doi:10.26008/1912/bco-dmo.928203.1 [access date]
endometabolite uptake by Ruegeria pomeroyi DSS-3 Dataset Description: <p>All the raw spectra, NMRPipe scripts for spectrum processing, and MATLAB scripts for data analysis are deposited in Metabolomics Workbench under Project ID PR001837 (see related datasets).</p>
<div>&nbsp;</div> Methods and Sampling: <p>Temperature experiment: Axenic cultures of the diatom Thalassiosira pseudonana CCMP1335 (National Center for Marine Algae) were acclimated to three temperature conditions (below optimal: 14°C, optimal: 20°C, and above optimal: 28°C) for three months with weekly transfers (approximately 120 generations) in L1 medium with 35 ppt artificial seawater under 120 µmol photons m-2 s-1 (ULM-500 Light Meter, Walz) and a 16:8 h light:dark cycle. Diatom cultures were stepwise limited by B12 through three transfers. Ruegeria pomeroyi DSS-3&nbsp; was grown overnight in ½ YTSS medium, harvested in exponential growth phase, washed five times in sterile artificial seawater at 6,000 RCF, and&nbsp; inoculated into diatom flasks with 4 replicates per acclimation temperature. Flasks were harvested at late exponential growth phase on days 3 (28°C), 4 (20°C), and 6 (14°C), with sampling occurring 7 h into the light cycle.</p>
<p>From axenic and inoculated flasks, cultures were sequentially filtered through 2.0 µm-pore-size Isopore filters (Millipore, Burlington, MA) and 0.2 µm-pore-size Supor filters (PALL, Port Washington, NY) to collect 600 ml for diatom endometabolits analysis,&nbsp; bacterial cells for RNA extraction. RNA filters were immediately flash-frozen in liquid nitrogen and stored at -80°C until processing.&nbsp; RNA was subsequently extracted from filters using the ZymoBIOMICS RNA Miniprep Kit (Zymo Research, Irvine, CA, USA) according to the manufacturer’s protocol.</p>
<p>Stranded RNASeq libraries were prepared by the Joint Genome Institute (JGI) and sequenced on an Illumina NovaSeq.</p>
<p>Metabolites were analyzed by NMR spectroscopy using a 600 MHz AVANCE III HD instrument (Bruker) equipped with a 5 mm TCI cryoprobe and pulse programs of 1H-13C heteronuclear single quantum correlation (HSQC, hsqcetgpprsisp2.2 by Bruker nomenclature) and 1H-13C HSQC-total correlation spectroscopy (HSQC-TOCSY, hsqcdietgpsisp.2). TopSpin (Bruker) version 3.5 was used for NMR operation. Data were processed by NMRPipe.</p>
<p>Peak intensity was extracted by rNMR version 1.11 and data were analyzed by MATLAB (MathWorks) version R2023b. Peak intensity was normalized by biovolume and auto-scaled. Metabolites were annotated based on chemical shift (HSQC) and correlation information (HSQC-TOCSY). Chemical shift values for candidate peaks were obtained from the Biological Magnetic Resonance Data Bank and the Human Metabolome Database, and raw reference spectra from BMRB were used for validation.</p>
<p>Draw down experiment: Thalassiosira pseudonana CCMP1335 cells harvested from axenic flasks were rinsed from thawed filters into 10 ml sterile L1 medium, sonicated to lyse cells, and passed through a pre-combusted GF/F filter. Ruegeria pomeroyi DSS-3 was inoculated into a 2.7 ml aliquot of concentrated endometabolomes and grown for 10 h in 96-well plates with shaking at 30°C in dark conditions. Subsamples of 1 ml were collected at inoculation and at the end of the experiment for metabolite quantification. From these subsamples, 540 µl were mixed with 60 µL of the phosphate buffer and transferred to NMR tubes. Metabolites were analyzed by NMR spectroscopy using a 600 MHz AVANCE III HD instrument (Bruker) equipped with a 5 mm TCI cryoprobe and pulse programs of 1H-13C heteronuclear single quantum correlation (HSQC, hsqcetgpprsisp2.2 by Bruker nomenclature) and 1H-13C HSQC-total correlation spectroscopy (HSQC-TOCSY, hsqcdietgpsisp.2). TopSpin (Bruker) version 3.6.4 was used for NMR operation.</p>
<p>Data were processed by NMRPipe. Peak intensity was extracted by rNMR version 1.11 and data were analyzed by MATLAB (MathWorks) version R2023b. Peak intensity was normalized by biovolume and auto-scaled. Metabolites were annotated based on chemical shift (HSQC) and correlation information (HSQC-TOCSY). Chemical shift values for candidate peaks were obtained from the Biological Magnetic Resonance Data Bank and the Human Metabolome Database, and raw reference spectra from BMRB were used for validation.</p>
Funding provided by NSF Division of Ocean Sciences (NSF OCE) Award Number: OCE-1948104 Award URL: https://www.nsf.gov/awardsearch/show-award?AWD_ID=1948104
completed
Mary Ann Moran
University of Georgia
706-542-6481
Department of Marine Sciences
Athens
GA
30602
USA
mmoran@uga.edu
pointOfContact
Malin Olofsson
University of Georgia
Uppsala
Sweden
malin.olofsson@slu.se
pointOfContact
Mario Uchimiya
University of Georgia
Complex Carbohydrate Research Center University of George
Athens
GA
USA
30602
mario.uchimiya@uga.edu
pointOfContact
asNeeded
Dataset Version: 1
Unknown
Experiment
Sample_ID
Metabolomics_Workbench_Project_ID
Metabolomics_Workbench_Study_ID
Metabolomics_Workbench_Sample_ID
Number
Temperature
Replicate
Culture
JGI_Sample_ID
Time_Point_h
Bacteria_presence
Glycine_Betaine
Proline
DHPS
DMSP
Homarine
Beta_1_3_glucan
Glycine
Glutamate
Glutamine
Alanine
Aspartate
Leucine
Lysine
Choline
Glycerol_3_Phosphate
Isoleucine
Illumina NovaSeq
Bruker 600 MHz AVANCE III HD
theme
None, User defined
experiment type
sample identification
accession number
number
temperature of sample or a generic measurement (not in-situ water temp)
replicate
sample description
sample time
presence_absence
Intensity (relative ion abundance)
featureType
BCO-DMO Standard Parameters
Automated DNA Sequencer
Nuclear Magnetic Resonance Spectrometers
instrument
BCO-DMO Standard Instruments
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.
Effects of Climate Change Variables on Microbial Autotroph-Heterotroph Carbon Flux
https://osprey.bco-dmo.org/project/787536
Effects of Climate Change Variables on Microbial Autotroph-Heterotroph Carbon Flux
<p><em>NSF Award Abstract:</em><br />
Phytoplankton in the surface ocean are responsible for roughly half of all photosynthesis on the planet. Much of the organic material created by these photosynthetic organisms is ultimately consumed by diverse marine bacteria with differing preferences for specific types of chemical compounds. This project investigates how climate change (temperature and CO2) might alter the types and amounts of organic compounds produced by different species of marine phytoplankton and the types and amounts of compounds transferred from phytoplankton to marine bacteria. Shifts in organic compounds transferred to bacteria could alter the distribution of bacterial species in the ocean, their growth rates and efficiencies, and flows of energy through the global ocean. This project helps scientists better understand the effects of climate change on marine ecosystems. Two graduate students and a postdoctoral researcher are supported by the project, receiving interdisciplinary training in biology, chemistry, and ocean sciences. Summer research internships in the PIs' laboratories are offered to AP Biology students enrolled at Cedar Shoals High School in Athens, GA, a school that serves a diverse social and economic community.</p>
<p>Much of the bacterial secondary production in the surface ocean is supported by rapid uptake of labile metabolites released from phytoplankton, either directly through excretion and diffusion or indirectly through lysis and predation. This project investigates the effects of two climate change variables (temperature and CO2) on the metabolite pools produced and released by three model phytoplankton species (a diatom, a coccolithophore, and a cyanobacterium) and assesses changes in the composition and fate of metabolites transferred to bacteria. Phytoplankton species are being grown axenically at two different temperatures and CO2 concentrations in a factorial design and endo- and exometabolite composition is determined using NMR. A suite of phytoplankton physiological characteristics is measured and evaluated in the context of metabolite composition. Experiments with heterotrophic bacteria (either model bacteria or natural bacterial communities) are being conducted to assess the effects of climate change variables on metabolite transfer from phytoplankton to marine bacteria. In the first experiment type, bacteria are co-cultured with the phytoplankton at different temperatures and CO2 concentrations, and changes in bacterial gene expression and metabolite concentrations are used to assess shifts in the composition of metabolites transferred. In the second type, bacteria are grown on phytoplankton metabolite pools produced at different temperatures and CO2 concentrations in high-throughput bioassays, and changes in bacterial traits (growth rate, carrying capacity, growth efficiency) resulting from the different climate scenarios are used to indicate changes in metabolite quality. Knowledge of how the heterotrophic processing of phytoplankton metabolites might shift in response to climate change allows better prediction of Earth's future carbon cycle.</p>
<p>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.</p>
CC_Auto_Hetero_Fluxes
largerWorkCitation
project
eng; USA
oceans
2025-03-06
Laboratory in Athens, GA, USA, and waters around Sapelo Island, GA, USA
0
BCO-DMO catalogue of parameters from Thalassiosira pseudonana CCMP1335 endometabolite uptake by Ruegeria pomeroyi DSS-3
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/955442.rdf
Name: Experiment
Units: unitless
Description: <p>Experiment (Temperature or Draw Down)</p>
http://lod.bco-dmo.org/id/dataset-parameter/955443.rdf
Name: Sample_ID
Units: unitless
Description: <p>Sample ID</p>
http://lod.bco-dmo.org/id/dataset-parameter/955444.rdf
Name: Metabolomics_Workbench_Project_ID
Units: unitless
Description: <p>Metabolomics Workbench - Project ID</p>
http://lod.bco-dmo.org/id/dataset-parameter/955445.rdf
Name: Metabolomics_Workbench_Study_ID
Units: unitless
Description: <p>Metabolomics Workbench - Study ID</p>
http://lod.bco-dmo.org/id/dataset-parameter/955446.rdf
Name: Metabolomics_Workbench_Sample_ID
Units: unitless
Description: <p>Metabolomics Workbench - Sample ID</p>
http://lod.bco-dmo.org/id/dataset-parameter/955447.rdf
Name: Number
Units: unitless
Description: <p>Consecutive number per experiment</p>
http://lod.bco-dmo.org/id/dataset-parameter/955448.rdf
Name: Temperature
Units: degrees Celsius (°C)
Description: <p>Temperature condition of sample</p>
http://lod.bco-dmo.org/id/dataset-parameter/955449.rdf
Name: Replicate
Units: unitless
Description: <p>Replicate number</p>
http://lod.bco-dmo.org/id/dataset-parameter/955450.rdf
Name: Culture
Units: unitless
Description: <p>For temperature experiment: Co-culture or Axenic</p>
http://lod.bco-dmo.org/id/dataset-parameter/955451.rdf
Name: JGI_Sample_ID
Units: unitless
Description: <p>For temperature experiment: Joint Genome Institute Sample ID</p>
http://lod.bco-dmo.org/id/dataset-parameter/955452.rdf
Name: Time_Point_h
Units: hours (h)
Description: <p>For Draw Down experiment: Time of sampling in experiment</p>
http://lod.bco-dmo.org/id/dataset-parameter/955453.rdf
Name: Bacteria_presence
Units: unitless
Description: <p>For Draw Down experiment: Bacteria presence (0 or 1)</p>
http://lod.bco-dmo.org/id/dataset-parameter/955454.rdf
Name: Glycine_Betaine
Units: NMR peak intensity per biovolume
Description: <p>C5H11NO2; amino acid derivative</p>
http://lod.bco-dmo.org/id/dataset-parameter/955455.rdf
Name: Proline
Units: NMR peak intensity per biovolume
Description: <p>C5H9NO2; amino acid</p>
http://lod.bco-dmo.org/id/dataset-parameter/955456.rdf
Name: DHPS
Units: NMR peak intensity per biovolume
Description: <p>2,3-dihydroxypropane-1-sulfonate; C3H7O5S-; organosulfur compound</p>
http://lod.bco-dmo.org/id/dataset-parameter/955457.rdf
Name: DMSP
Units: NMR peak intensity per biovolume
Description: <p>3-dimethylsulfoniopropanoate; C5H10O2S; organosulfur compand</p>
http://lod.bco-dmo.org/id/dataset-parameter/955458.rdf
Name: Homarine
Units: NMR peak intensity per biovolume
Description: <p>C7H7NO2; amino acid derivative</p>
http://lod.bco-dmo.org/id/dataset-parameter/955459.rdf
Name: Beta_1_3_glucan
Units: NMR peak intensity per biovolume
Description: <p>Laminarin; C18H32O16; carbohydrate</p>
http://lod.bco-dmo.org/id/dataset-parameter/955460.rdf
Name: Glycine
Units: NMR peak intensity per biovolume
Description: <p>C2H5NO2; amino acid</p>
http://lod.bco-dmo.org/id/dataset-parameter/955461.rdf
Name: Glutamate
Units: NMR peak intensity per biovolume
Description: <p>C5H9NO4; amino acid</p>
http://lod.bco-dmo.org/id/dataset-parameter/955462.rdf
Name: Glutamine
Units: NMR peak intensity per biovolume
Description: <p>C5H10N2O3; amino acid</p>
http://lod.bco-dmo.org/id/dataset-parameter/955463.rdf
Name: Alanine
Units: NMR peak intensity per biovolume
Description: <p>C3H7NO2; amino acid</p>
http://lod.bco-dmo.org/id/dataset-parameter/955464.rdf
Name: Aspartate
Units: NMR peak intensity per biovolume
Description: <p>C4H7NO4; amino acid</p>
http://lod.bco-dmo.org/id/dataset-parameter/955465.rdf
Name: Leucine
Units: NMR peak intensity per biovolume
Description: <p>C6H13NO2; amino acid</p>
http://lod.bco-dmo.org/id/dataset-parameter/955466.rdf
Name: Lysine
Units: NMR peak intensity per biovolume
Description: <p>C6H14N2O2; amino acid </p>
http://lod.bco-dmo.org/id/dataset-parameter/955467.rdf
Name: Choline
Units: NMR peak intensity per biovolume
Description: <p>C5H14NO+; quaternary amine</p>
http://lod.bco-dmo.org/id/dataset-parameter/955468.rdf
Name: Glycerol_3_Phosphate
Units: NMR peak intensity per biovolume
Description: <p>2,3-dihydroxypropyl dihydrogen phosphate; C3H9O6P; glycerol derivative</p>
http://lod.bco-dmo.org/id/dataset-parameter/955469.rdf
Name: Isoleucine
Units: NMR peak intensity per biovolume
Description: <p>C6H13NO2; amino acid</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
13787
https://darchive.mblwhoilibrary.org/server/api/core/bitstreams/763b37dd-1491-43d7-8dd8-8de2f61477cf/content
download
https://doi.org/10.26008/1912/bco-dmo.928203.1
download
onLine
dataset
<p>Temperature experiment: Axenic cultures of the diatom Thalassiosira pseudonana CCMP1335 (National Center for Marine Algae) were acclimated to three temperature conditions (below optimal: 14°C, optimal: 20°C, and above optimal: 28°C) for three months with weekly transfers (approximately 120 generations) in L1 medium with 35 ppt artificial seawater under 120 µmol photons m-2 s-1 (ULM-500 Light Meter, Walz) and a 16:8 h light:dark cycle. Diatom cultures were stepwise limited by B12 through three transfers. Ruegeria pomeroyi DSS-3&nbsp; was grown overnight in ½ YTSS medium, harvested in exponential growth phase, washed five times in sterile artificial seawater at 6,000 RCF, and&nbsp; inoculated into diatom flasks with 4 replicates per acclimation temperature. Flasks were harvested at late exponential growth phase on days 3 (28°C), 4 (20°C), and 6 (14°C), with sampling occurring 7 h into the light cycle.</p>
<p>From axenic and inoculated flasks, cultures were sequentially filtered through 2.0 µm-pore-size Isopore filters (Millipore, Burlington, MA) and 0.2 µm-pore-size Supor filters (PALL, Port Washington, NY) to collect 600 ml for diatom endometabolits analysis,&nbsp; bacterial cells for RNA extraction. RNA filters were immediately flash-frozen in liquid nitrogen and stored at -80°C until processing.&nbsp; RNA was subsequently extracted from filters using the ZymoBIOMICS RNA Miniprep Kit (Zymo Research, Irvine, CA, USA) according to the manufacturer’s protocol.</p>
<p>Stranded RNASeq libraries were prepared by the Joint Genome Institute (JGI) and sequenced on an Illumina NovaSeq.</p>
<p>Metabolites were analyzed by NMR spectroscopy using a 600 MHz AVANCE III HD instrument (Bruker) equipped with a 5 mm TCI cryoprobe and pulse programs of 1H-13C heteronuclear single quantum correlation (HSQC, hsqcetgpprsisp2.2 by Bruker nomenclature) and 1H-13C HSQC-total correlation spectroscopy (HSQC-TOCSY, hsqcdietgpsisp.2). TopSpin (Bruker) version 3.5 was used for NMR operation. Data were processed by NMRPipe.</p>
<p>Peak intensity was extracted by rNMR version 1.11 and data were analyzed by MATLAB (MathWorks) version R2023b. Peak intensity was normalized by biovolume and auto-scaled. Metabolites were annotated based on chemical shift (HSQC) and correlation information (HSQC-TOCSY). Chemical shift values for candidate peaks were obtained from the Biological Magnetic Resonance Data Bank and the Human Metabolome Database, and raw reference spectra from BMRB were used for validation.</p>
<p>Draw down experiment: Thalassiosira pseudonana CCMP1335 cells harvested from axenic flasks were rinsed from thawed filters into 10 ml sterile L1 medium, sonicated to lyse cells, and passed through a pre-combusted GF/F filter. Ruegeria pomeroyi DSS-3 was inoculated into a 2.7 ml aliquot of concentrated endometabolomes and grown for 10 h in 96-well plates with shaking at 30°C in dark conditions. Subsamples of 1 ml were collected at inoculation and at the end of the experiment for metabolite quantification. From these subsamples, 540 µl were mixed with 60 µL of the phosphate buffer and transferred to NMR tubes. Metabolites were analyzed by NMR spectroscopy using a 600 MHz AVANCE III HD instrument (Bruker) equipped with a 5 mm TCI cryoprobe and pulse programs of 1H-13C heteronuclear single quantum correlation (HSQC, hsqcetgpprsisp2.2 by Bruker nomenclature) and 1H-13C HSQC-total correlation spectroscopy (HSQC-TOCSY, hsqcdietgpsisp.2). TopSpin (Bruker) version 3.6.4 was used for NMR operation.</p>
<p>Data were processed by NMRPipe. Peak intensity was extracted by rNMR version 1.11 and data were analyzed by MATLAB (MathWorks) version R2023b. Peak intensity was normalized by biovolume and auto-scaled. Metabolites were annotated based on chemical shift (HSQC) and correlation information (HSQC-TOCSY). Chemical shift values for candidate peaks were obtained from the Biological Magnetic Resonance Data Bank and the Human Metabolome Database, and raw reference spectra from BMRB were used for validation.</p>
Specified by the Principal Investigator(s)
<p>Reads were filtered and trimmed using the JGI QC pipeline, followed by evaluation of artifact sequences by kmer matching (kmer=25) using BBDuk, allowing one mismatch; detected artifacts were trimmed from the 3´end of the reads. Quality trimming was performed using the phred trimming method set at Q6 and reads under the minimum length of 25 bases or 1/3 of the original read length were removed. Filtered reads from each library were aligned to the reference genome using HISAT2 version 2.2.0 and strand-specific coverage bigwig files were generated using deepTools v3.1. FeatureCounts was used to generate the raw gene counts, and DESeq2 (version 1.28.1) was used to determine relative expression differences between pairs of conditions. <em>T. pseudonana</em> gene annotations and biosynthesis pathways were based on Biocyc and PhyloDB. <em>R. pomeroyi </em>annotations were based on Roseobase (http://roseobase.org)</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
Illumina NovaSeq
Illumina NovaSeq
PI Supplied Instrument Name: Illumina NovaSeq PI Supplied Instrument Description:Illumina NovaSeq was used for transcriptome sequencing Instrument Name: Automated DNA Sequencer Instrument Short Name:Automated Sequencer Instrument Description: A DNA sequencer is an instrument that determines the order of deoxynucleotides in deoxyribonucleic acid sequences.
Bruker 600 MHz AVANCE III HD
Bruker 600 MHz AVANCE III HD
PI Supplied Instrument Name: Bruker 600 MHz AVANCE III HD PI Supplied Instrument Description:Bruker 600 MHz AVANCE III HD instrument was used for NMR spectroscopy Instrument Name: Nuclear Magnetic Resonance Spectrometers Instrument Short Name:NMR Instrument Description: Instruments that identify and quantify magnetically active chemical entities by subjecting a sample to orthogonal magnetic and electrical fields. Community Standard Description: http://vocab.nerc.ac.uk/collection/L05/current/LAB18/