Particulate triacylglycerol lipid data from cruises EN667 in the Gulf of Maine in June 2021, SR2310 along the Oregon Coast in May 2023, and AE2320 in the Sargasso Sea in September 2023 (RIPPLE1, RIPPLE2, and RIPPLE3)

Website: https://www.bco-dmo.org/dataset/997821
Data Type: Cruise Results
Version: 1
Version Date: 2026-05-11

Project
» Production and Fate of Fats in the Upper Ocean (RIPPLE)
ContributorsAffiliationRole
Van Mooy, Benjamin A.S.Woods Hole Oceanographic Institution (WHOI)Principal Investigator
Lowenstein, DanielWoods Hole Oceanographic Institution (WHOI)Student
Rauch, ShannonWoods Hole Oceanographic Institution (WHOI BCO-DMO)BCO-DMO Data Manager

Abstract
This dataset includes particulate triacylglycerol lipid data from samples collected on three research cruises in 2021 and 2023. In the Gulf of Maine, samples were collected on R/V Endeavor (cruise EN667) from 13 June to 21 June, 2021. Off the Oregon Coast, samples were on the R/V Sally Ride (cruise SR2310) from 18 May to 25 May, 2023. In the Sargasso Sea, samples were collected on R/V Atlantic Explorer (cruise AE2320) from 5 September to 11 September, 2023. Lipid samples were collected via CTD rosette, filtered, and analyzed according to Holm et al. (2022). The goal of these cruises was to investigate diel carbon cycling in the surface ocean, led by Chief Scientist Ben Van Mooy.


Coverage

Location: Photic zones of the Gulf of Maine, Oregon Coast, and Sargasso Sea
Spatial Extent: N:44.70316667 E:-64.08516667 S:31.6575 W:-125.276
Temporal Extent: 2021-06-13 - 2023-09-11

Methods & Sampling

Methods on EN667:
One liter (L) samples were collected via CTD rosette for particulate lipid, carbohydrate, and organic carbon samples. Samples were filtered onto 47-millimeter (mm) 0.2-micrometer (um) Durapore filters (lipids, carbs; Millipore) and 25 mm 0.7 um GF/F filters (POC; Whatman), flash frozen in liquid nitrogen, and stored in LN2 headspace until extraction.

Lipid samples were processed and analyzed according to Holm et al. (2022), and quantified via Holm et al. (2024). Per-liter particulate lipid values are reported in peak area and femtomoles per liter. All values for all compounds were blank-corrected using the average of five 1-L filtered seawater blanks collected from the sea surface on EN667.

Methods on SR2320:
One liter samples were collected via CTD rosette for particulate lipid, carbohydrate, and organic carbon samples. Samples were filtered onto 47 mm 0.2 um Durapore filters (lipids, carbs; Millipore) and 25 mm 0.7 um GF/F filters (POC; Whatman), flash frozen in liquid nitrogen, and stored in LN2 headspace until extraction.

Lipid samples were processed and analyzed according to Holm et al. (2022), and quantified via Holm et al. (2024). Per-liter particulate lipid values are reported in peak area and femtomoles per liter. All values for all compounds were blank-corrected using the average of twenty 0.2 um Durapore filters processed and analyzed alongside sample filters.

Methods on AE2320:
Two liter samples were collected via CTD rosette for particulate lipid, carbohydrate, and organic carbon samples. Samples were filtered onto 47 mm 0.2 um Durapore filters (lipids, carbs; Millipore) and 25 mm 0.7 um GF/F filters (POC; Whatman), flash frozen in liquid nitrogen, and stored in LN2 headspace until extraction.

Lipid samples were processed and analyzed according to Holm et al. (2022), and quantified via Holm et al. (2024). Per-liter particulate lipid values are reported in peak area and femtomoles per liter. All values for all compounds were blank-corrected using the average of seven 2-L filtered seawater blanks collected from the surface on AE2320.


Data Processing Description

For data from all cruises:
Lipids were annotated using the LOBSTAHS package in the R-language (Collins et al. 2015), which utilizes the xcms (Tautenham et al. 2008; Smith et al. 2006) and CAMERA (Kuhl et al. 2012) packages.


BCO-DMO Processing Description

- Imported the three original CSV files (AE2320_RIPPLE_3_triacylglycerol_data.csv, SR2310_RIPPLE_2_triacylglycerol_data.csv, EN667_RIPPLE_1_triacylglycerol_data.csv) into the BCO-DMO system.
- Treated "NA" as a missing value (missing values are empty/blank in the final CSV file).
- Concatenated the three files into a single file, adding a column for Cruise_Name."
- Converted the original "Time_UTC" column into ISO_DateTime_UTC (format %Y-%m-%dT%H:%MZ) and renamed it to "ISO_DateTime_UTC".
- Renamed fields to comply with BCO-DMO naming conventions.
- Saved the final file as "997821_v1_lipids_RIPPLE_cruises.csv".


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Related Publications

Collins, J. R., Edwards, B. R., Fredricks, H. F., & Van Mooy, B. A. S. (2016). LOBSTAHS: An Adduct-Based Lipidomics Strategy for Discovery and Identification of Oxidative Stress Biomarkers. Analytical Chemistry, 88(14), 7154–7162. https://doi.org/10.1021/acs.analchem.6b01260
Methods
Holm, H. C., Fredricks, H. F., Bent, S. M., Lowenstein, D. P., Ossolinski, J. E., Becker, K. W., Johnson, W. M., Schrage, K., & Van Mooy, B. A. S. (2022). Global ocean lipidomes show a universal relationship between temperature and lipid unsaturation. Science, 376(6600), 1487–1491. https://doi.org/10.1126/science.abn7455
Methods
Holm, H. C., Fredricks, H. F., Bent, S. M., Lowenstein, D. P., Schrage, K. R., & Van Mooy, B. A. S. (2024). Lipid composition, caloric content, and novel oxidation products from microbial communities within seasonal pack ice cores. Geochimica et Cosmochimica Acta, 368, 12–23. https://doi.org/10.1016/j.gca.2024.01.003
Methods
Kuhl, C., Tautenhahn, R., Böttcher, C., Larson, T. R., & Neumann, S. (2011). CAMERA: An Integrated Strategy for Compound Spectra Extraction and Annotation of Liquid Chromatography/Mass Spectrometry Data Sets. Analytical Chemistry, 84(1), 283–289. doi:10.1021/ac202450g
Methods
Smith, C. A., Want, E. J., O’Maille, G., Abagyan, R., & Siuzdak, G. (2006). XCMS:  Processing Mass Spectrometry Data for Metabolite Profiling Using Nonlinear Peak Alignment, Matching, and Identification. Analytical Chemistry, 78(3), 779–787. doi:10.1021/ac051437y
Methods
Tautenhahn, R., Böttcher, C., & Neumann, S. (2008). Highly sensitive feature detection for high resolution LC/MS. BMC Bioinformatics, 9(1). doi:10.1186/1471-2105-9-504
Methods

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Parameters

ParameterDescriptionUnits
Cruise_ID

Cruise ID

unitless
Cruise_Name

description

units
Lat

Sampling Site Latitude (North is positive)

decimal degrees
Long

Sampling Site Longitude (West is negative)

decimal degrees
ISO_DateTime_UTC

Sampling date and time (UTC) in ISO 8601 format

unitless
Cast

CTD Cast Number

unitless
Depth

Depth

meters
compound_name

compound name

unitless
elem_formula

elemental formula

unitless
LOBdbase_mz

theoretical compound mass:charge ratio in LOBSTAHS lipid database

Atomic Mass Units
lipid_class

lipid class

unitless
species

lipid headgroup species

unitless
FA_total_no_C

fatty acid number of carbon atoms

carbon atoms
FA_total_no_DB

fatty acid number of double bonds

double bonds
degree_oxidation

fatty acid number of peroxidations

additional acyl oxygen atoms
peak_area_per_L

LC-MS peak area per liter

blank corrected LC-MS peak area per liter
fmol_per_L

femtomoles per liter

blank corrected femtomoles per liter


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Instruments

Dataset-specific Instrument Name
Agilent 1100 high performance chromatography system
Generic Instrument Name
High-Performance Liquid Chromatograph
Dataset-specific Description
Lipids were analyzed on Thermo Scientific QExactive Mass spectrometer with Agilent 1100 high performance chromatography system
Generic Instrument Description
A High-performance liquid chromatograph (HPLC) is a type of liquid chromatography used to separate compounds that are dissolved in solution. HPLC instruments consist of a reservoir of the mobile phase, a pump, an injector, a separation column, and a detector. Compounds are separated by high pressure pumping of the sample mixture onto a column packed with microspheres coated with the stationary phase. The different components in the mixture pass through the column at different rates due to differences in their partitioning behavior between the mobile liquid phase and the stationary phase.

Dataset-specific Instrument Name
Thermo Scientific QExactive Mass spectrometer
Generic Instrument Name
Mass Spectrometer
Dataset-specific Description
Lipids were analyzed on Thermo Scientific QExactive Mass spectrometer with Agilent 1100 high performance chromatography system
Generic Instrument Description
General term for instruments used to measure the mass-to-charge ratio of ions; generally used to find the composition of a sample by generating a mass spectrum representing the masses of sample components.


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Deployments

AE2320

Website
Platform
R/V Atlantic Explorer
Start Date
2023-09-04
End Date
2023-09-11
Description
See additional information from R2R: https://www.rvdata.us/search/cruise/AE2320

EN667

Website
Platform
R/V Endeavor
Start Date
2021-06-12
End Date
2021-06-22
Description
See additional information at R2R: https://www.rvdata.us/search/cruise/EN667

SR2310

Website
Platform
R/V Sally Ride
Start Date
2023-05-18
End Date
2023-05-25
Description
See additional information at R2R: https://www.rvdata.us/search/cruise/SR2310


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Project Information

Production and Fate of Fats in the Upper Ocean (RIPPLE)

Coverage: Gulf of Maine, Oregon coast, Sargasso Sea


The Production and Fate of Fats in the Upper Ocean Phytoplankton, microscopic photosynthetic organisms in the ocean, produce a type of fat called triaclyglycerols (TAGs). A recent discovery in the North Pacific Ocean showed that a significant percentage of primary production from phytoplankton is devoted to producing TAGs. This suggests that TAGs may serve as a source of energy for phytoplankton at night, when they are unable to generate energy from photosynthesis. Phytoplankton are the base of the food web in the ocean. Therefore, it is important to understand how they create and store energy. This project will investigate the role of fats in the ocean. Specifically, this research will look at: 1) factors that affect the production and use of TAGs by phytoplankton and 2) how TAGs contribute to the global carbon cycle. This project will support the training and education of graduate students. This project will also provide resources for mentoring high school students, support summer research experiences for high school and undergraduate students, and offer field trips for 7th grade students.

Triacylglycerols (TAGs) are one of the most abundant classes of lipids in the ocean. A new discovery suggests that TAGs are also a very dynamic class of biochemicals. A recent study in the surface waters of the North Pacific subtropical gyre (NPSG) showed that TAGs doubled in concentration between sunrise and sunset daily, accounting for 16 to 42% of net primary production by eukaryotic nanophytoplankton (Becker et al., 2018). These results show that TAGs are an vital component of the physiology of eukaryotic phytoplankton and that TAGs contribute significantly to the carbon cycle of the NPSG. Based on estimates from this study, daytime production of TAGs in the subtropical gyres accounted for 4 to 6 percent of total global primary production. Outside of subtropical gyres, the production rates of TAGs are entirely unknown, particularly in regions where primary production rates are higher and eukaryotic phytoplankton are more dominant. Thus, the contribution of TAGs to the global ocean carbon cycle is almost certainly underestimated. There are major outstanding questions about TAGs. What environmental factors affect rates of net TAG production? What fraction of net TAG production is exported in sinking particles? Do TAGs play a role in the food web of the euphotic zone? How much of the TAGs produced during the day do phytoplankton themselves consume at night? These questions will be answered using state-of-the-art lipidomics, in situ observations, isotope-tracing techniques, incubations, and on-deck experiments. This study will provide significant advances in our understanding of TAG metabolism in phytoplankton, elucidate the roles that TAGs play in the marine carbon cycle, constrain their global importance by studying TAGs in multiple disparate environments, and set the groundwork for future research on these fascinating and vital molecules.

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.



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Funding

Funding SourceAward
NSF Division of Ocean Sciences (NSF OCE)

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