Summary of Study ST000983

This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR000672. The data can be accessed directly via it's Project DOI: 10.21228/M8T68F This work is supported by NIH grant, U2C- DK119886.

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Study IDST000983
Study TitleValidating Quantitative Untargeted Lipidomics Across Nine Liquid Chromatography−High-Resolution Mass Spectrometry Platforms (Part I)
Study SummaryLiquid chromatography−mass spectrometry (LC−MS) methods are most often used for untargeted metabolomics and lipidomics. However, methods have not been standardized as accepted “best practice” documents, and reports lack harmonization with respect to quantitative data that enable interstudy comparisons. Researchers use a wide variety of high-resolution mass spectrometers under different operating conditions, and it is unclear if results would yield different biological conclusions depending on the instrument performance. To this end, we used 126 identical human plasma samples and 29 quality control samples from a nutritional intervention study. We investigated lipidomic data acquisitions across nine different MS instruments (1 single TOF, 1 Q/orbital ion trap, and 7 QTOF instruments). Sample preparations, chromatography conditions, and data processing methods were kept identical. Single-point internal standard calibrations were used to estimate absolute concentrations for 307 unique lipids identified by accurate mass, MS/MS spectral match, and retention times. Quantitative results were highly comparable between the LC−MS platforms tested. Using partial least-squares discriminant analysis (PLS-DA) to compare results between platforms, a 92% overlap for the most discriminating lipids based on variable importance in projection (VIP) scores was achieved for all lipids that were detected by at least two instrument platforms. Importantly, even the relative positions of individual samples on the PLS-DA projections were identical. The key for success in harmonizing results was to avoid ion saturation by carefully evaluating linear dynamic ranges using serial dilutions and adjusting the resuspension volume and/or injection volume before running actual study samples.
Institute
University of California, Davis
DepartmentGenome and Biomedical Sciences Facility
LaboratoryWCMC Metabolomics Core
Last NameFiehn
First NameOliver
Address1315 Genome and Biomedical Sciences Facility, 451 Health Sciences Drive, Davis, CA 95616
Emailofiehn@ucdavis.edu
Phone(530) 754-8258
Submit Date2015-12-17
PublicationsDOI: 10.1021/acs.analchem.7b03404
Raw Data AvailableYes
Raw Data File Type(s)d
Analysis Type DetailLC-MS
Release Date2018-07-17
Release Version1
Oliver Fiehn Oliver Fiehn
https://dx.doi.org/10.21228/M8T68F
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

Select appropriate tab below to view additional metadata details:

Project:

Project ID:PR000672
Project DOI:doi: 10.21228/M8T68F
Project Title:Validating Quantitative Untargeted Lipidomics Across Nine Liquid Chromatography−High-Resolution Mass Spectrometry Platforms
Project Summary:Liquid chromatography−mass spectrometry (LC−MS) methods are most often used for untargeted metabolomics and lipidomics. However, methods have not been standardized as accepted “best practice” documents, and reports lack harmonization with respect to quantitative data that enable interstudy comparisons. Researchers use a wide variety of high-resolution mass spectrometers under different operating conditions, and it is unclear if results would yield different biological conclusions depending on the instrument performance. To this end, we used 126 identical human plasma samples and 29 quality control samples from a nutritional intervention study. We investigated lipidomic data acquisitions across nine different MS instruments (1 single TOF, 1 Q/orbital ion trap, and 7 QTOF instruments). Sample preparations, chromatography conditions, and data processing methods were kept identical. Single-point internal standard calibrations were used to estimate absolute concentrations for 307 unique lipids identified by accurate mass, MS/MS spectral match, and retention times. Quantitative results were highly comparable between the LC−MS platforms tested. Using partial least-squares discriminant analysis (PLS-DA) to compare results between platforms, a 92% overlap for the most discriminating lipids based on variable importance in projection (VIP) scores was achieved for all lipids that were detected by at least two instrument platforms. Importantly, even the relative positions of individual samples on the PLS-DA projections were identical. The key for success in harmonizing results was to avoid ion saturation by carefully evaluating linear dynamic ranges using serial dilutions and adjusting the resuspension volume and/or injection volume before running actual study samples.
Institute:University of California, Davis
Department:Genome and Biomedical Sciences Facility
Laboratory:WCMC Metabolomics Core
Last Name:Fiehn
First Name:Oliver
Address:1315 Genome and Biomedical Sciences Facility, 451 Health Sciences Drive, Davis, CA 95616
Email:ofiehn@ucdavis.edu
Phone:5307548258
Publications:DOI: 10.1021/acs.analchem.7b03404

Subject:

Subject ID:SU001022
Subject Type:Human
Subject Species:Homo sapiens
Taxonomy ID:9606
Species Group:Mammals

Factors:

Subject type: Human; Subject species: Homo sapiens (Factor headings shown in green)

mb_sample_id local_sample_id Collection Time (hours) Phenotype
SA060060GLA_AG3_Lipids_SO022_SA024_1001bC10-h CF
SA060061GLA_AG3_Lipids_SO097_SA086_1006cC10-h CF
SA060062GLA_AG3_Lipids_SO025_SA036_1001dC10-h CF
SA060063GLA_AG3_Lipids_SO007_SA037_1000cC10-h CF
SA060064GLA_AG3_Lipids_SO031_SA043_1001fC10-h CF
SA060065GLA_AG3_Lipids_SO076_SA058_1005bC10-h CF
SA060066GLA_AG3_Lipids_SO091_SA061_1006aC10-h CF
SA060067GLA_AG3_Lipids_SO085_SA076_1005fC10-h CF
SA060068GLA_AG3_Lipids_SO082_SA063_1005dC10-h CF
SA060069GLA_AG3_Lipids_SO001_SA042_1000aC10-h CF
SA060070GLA_AG3_Lipids_SO013_SA007_1000eC10-h CF
SA060071GLA_AG3_Lipids_SO109_SA122_1007aC10-h CF
SA060072GLA_AG3_Lipids_SO067_SA098_1003eC10-h CF
SA060073GLA_AG3_Lipids_SO115_SA106_1007cC10-h CF
SA060074GLA_AG3_Lipids_SO055_SA078_1003aC10-h CF
SA060075GLA_AG3_Lipids_SO040_SA029_1002bC10-h CF
SA060076GLA_AG3_Lipids_SO046_SA005_1002dC10-h CF
SA060077GLA_AG3_Lipids_SO061_SA074_1003cC10-h CF
SA060078GLA_AG3_Lipids_SO121_SA105_1007eC10-h CF
SA060079GLA_AG3_Lipids_SO052_SA033_1002fC10-h CF
SA060080GLA_AG3_Lipids_SO016_SA040_1000fG10-h GF
SA060081GLA_AG3_Lipids_SO079_SA070_1005cG10-h GF
SA060082GLA_AG3_Lipids_SO049_SA032_1002eG10-h GF
SA060083GLA_AG3_Lipids_SO043_SA003_1002cG10-h GF
SA060084GLA_AG3_Lipids_SO019_SA014_1001aG10-h GF
SA060085GLA_AG3_Lipids_SO028_SA009_1001eG10-h GF
SA060086GLA_AG3_Lipids_SO034_SA013_1001gG10-h GF
SA060087GLA_AG3_Lipids_SO037_SA048_1002aG10-h GF
SA060088GLA_AG3_Lipids_SO070_SA084_1003fG10-h GF
SA060089GLA_AG3_Lipids_SO073_SA066_1005aG10-h GF
SA060090GLA_AG3_Lipids_SO058_SA099_1003bG10-h GF
SA060091GLA_AG3_Lipids_SO064_SA064_1003dG10-h GF
SA060092GLA_AG3_Lipids_SO010_SA038_1000dG10-h GF
SA060093GLA_AG3_Lipids_SO094_SA085_1006bG10-h GF
SA060094GLA_AG3_Lipids_SO112_SA103_1007bG10-h GF
SA060095GLA_AG3_Lipids_SO106_SA123_1006fG10-h GF
SA060096GLA_AG3_Lipids_SO100_SA118_1006dG10-h GF
SA060097GLA_AG3_Lipids_SO103_SA108_1006eG10-h GF
SA060098GLA_AG3_Lipids_SO088_SA073_1005gG10-h GF
SA060099GLA_AG3_Lipids_SO118_SA110_1007dG10-h GF
SA060100GLA_AG3_Lipids_SO124_SA126_1007fG10-h GF
SA060101GLA_AG3_Lipids_SO004_SA051_1000bG10-h GF
SA060102GLA_AG3_Lipids_SO110_SA100_1007aC22-h CF
SA060103GLA_AG3_Lipids_SO032_SA017_1001fC22-h CF
SA060104GLA_AG3_Lipids_SO047_SA006_1002dC22-h CF
SA060105GLA_AG3_Lipids_SO062_SA055_1003cC22-h CF
SA060106GLA_AG3_Lipids_SO053_SA028_1002fC22-h CF
SA060107GLA_AG3_Lipids_SO041_SA052_1002bC22-h CF
SA060108GLA_AG3_Lipids_SO083_SA069_1005dC22-h CF
SA060109GLA_AG3_Lipids_SO116_SA111_1007cC22-h CF
SA060110GLA_AG3_Lipids_SO122_SA120_1007eC22-h CF
SA060111GLA_AG3_Lipids_SO056_SA057_1003aC22-h CF
SA060112GLA_AG3_Lipids_SO068_SA094_1003eC22-h CF
SA060113GLA_AG3_Lipids_SO077_SA082_1005bC22-h CF
SA060114GLA_AG3_Lipids_SO002_SA044_1000aC22-h CF
SA060115GLA_AG3_Lipids_SO026_SA019_1001dC22-h CF
SA060116GLA_AG3_Lipids_SO098_SA077_1006cC22-h CF
SA060117GLA_AG3_Lipids_SO023_SA012_1001bC22-h CF
SA060118GLA_AG3_Lipids_SO092_SA065_1006aC22-h CF
SA060119GLA_AG3_Lipids_SO008_SA020_1000cC22-h CF
SA060120GLA_AG3_Lipids_SO086_SA095_1005fC22-h CF
SA060121GLA_AG3_Lipids_SO014_SA035_1000eC22-h CF
SA060122GLA_AG3_Lipids_SO080_SA079_1005cG22-h GF
SA060123GLA_AG3_Lipids_SO125_SA117_1007fG22-h GF
SA060124GLA_AG3_Lipids_SO089_SA080_1005gG22-h GF
SA060125GLA_AG3_Lipids_SO119_SA121_1007dG22-h GF
SA060126GLA_AG3_Lipids_SO113_SA113_1007bG22-h GF
SA060127GLA_AG3_Lipids_SO065_SA062_1003dG22-h GF
SA060128GLA_AG3_Lipids_SO104_SA112_1006eG22-h GF
SA060129GLA_AG3_Lipids_SO101_SA104_1006dG22-h GF
SA060130GLA_AG3_Lipids_SO107_SA107_1006fG22-h GF
SA060131GLA_AG3_Lipids_SO071_SA097_1003fG22-h GF
SA060132GLA_AG3_Lipids_SO074_SA089_1005aG22-h GF
SA060133GLA_AG3_Lipids_SO095_SA059_1006bG22-h GF
SA060134GLA_AG3_Lipids_SO059_SA060_1003bG22-h GF
SA060135GLA_AG3_Lipids_SO050_SA027_1002eG22-h GF
SA060136GLA_AG3_Lipids_SO020_SA021_1001aG22-h GF
SA060137GLA_AG3_Lipids_SO035_SA047_1001gG22-h GF
SA060138GLA_AG3_Lipids_SO017_SA018_1000fG22-h GF
SA060139GLA_AG3_Lipids_SO011_SA041_1000dG22-h GF
SA060140GLA_AG3_Lipids_SO005_SA002_1000bG22-h GF
SA060141GLA_AG3_Lipids_SO038_SA008_1002aG22-h GF
SA060142GLA_AG3_Lipids_SO029_SA053_1001eG22-h GF
SA060143GLA_AG3_Lipids_SO044_SA025_1002cG22-h GF
SA060144GLA_AG3_Lipids_SO015_SA004_1000eC34-h CF
SA060145GLA_AG3_Lipids_SO093_SA075_1006aC34-h CF
SA060146GLA_AG3_Lipids_SO123_SA115_1007eC34-h CF
SA060147GLA_AG3_Lipids_SO057_SA071_1003aC34-h CF
SA060148GLA_AG3_Lipids_SO054_SA039_1002fC34-h CF
SA060149GLA_AG3_Lipids_SO078_SA091_1005bC34-h CF
SA060150GLA_AG3_Lipids_SO048_SA128_1002dC34-h CF
SA060151GLA_AG3_Lipids_SO117_SA101_1007cC34-h CF
SA060152GLA_AG3_Lipids_SO084_SA081_1005dC34-h CF
SA060153GLA_AG3_Lipids_SO087_SA056_1005fC34-h CF
SA060154GLA_AG3_Lipids_SO009_SA049_1000cC34-h CF
SA060155GLA_AG3_Lipids_SO024_SA016_1001bC34-h CF
SA060156GLA_AG3_Lipids_SO099_SA096_1006cC34-h CF
SA060157GLA_AG3_Lipids_SO063_SA083_1003cC34-h CF
SA060158GLA_AG3_Lipids_SO042_SA031_1002bC34-h CF
SA060159GLA_AG3_Lipids_SO111_SA102_1007aC34-h CF
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Collection:

Collection ID:CO001016
Collection Summary:We deliberately used samples from a recently published study in order to investigate if statistical and biological conclusions would differ from the published results, depending on the instrumentation used. In a blinded, placebo-controlled, crossover designed study, seven healthy subjects consumed a test meal containing high amounts of gamma-linolenic acid (GLA, 18:3n6) compared to a control meal. Each subject underwent the nutritional test on three separate test days for each test meal, and samples were taken each time over an 8 h period.
Collection Protocol Filename:acs_analchem_7b03404.pdf
Sample Type:Blood (plasma)
Collection Frequency:0, 2, and 4 hours

Treatment:

Treatment ID:TR001036
Treatment Summary:For this study, we used a subset of samples from our recent study focused on nutritional phenotyping in response to a test meal containing gamma-linolenic acid. Briefly, in a single blind, placebo-controlled, crossover design, seven healthy subjects consumed a test meal that consisted of GLA fat (borage oil [denoted GF]) or a control fat (a mixture of corn, safflower, sunflower, and extra-virgin light olive oils [denoted CF]). Compared to the original study, where all subjects were fed on three separate test days for each test meal, a small modification was needed due to sample limitation. Thus, for this study, six subjects were fed on three separate test days for each test meal, while one subject was fed on two separate test days for a control fat meal and four test days for GLA fat (the fourth set was not used in the original study). Plasma samples collected at 0, 2, and 4h in response to the test meals were used for analysis. In total, 126 samples were analyzed out of which 42 were baseline samples (time 0 h), 40 were control fat samples (time 2 and 4 h), and 44 were GLA fat samples (time 2 and 4 h). For quality control, a pool sample consisted of a mixture of nonfasting blood plasma (both control and GLA fat) was used. Also, standard reference material SRM 1950 Metabolites in Frozen Human Plasma (NIST, Gaithersburg, MD) was used.
Treatment Protocol Filename:acs_analchem_7b03404.pdf

Sample Preparation:

Sampleprep ID:SP001029
Sampleprep Summary:Extraction of plasma lipids was carried out using a biphasic solvent system of cold methanol, methyl tertbutyl ether (MTBE), and water with some modifications. In more detail, 300 μL of cold methanol containing a mixture of odd chain and deuterated lipid internal standards [LPE(17:1), LPC(17:0), PC(12:0/13:0), PE(17:0/17:0), PG(17:0/17:0), d7-cholesterol, SM(d18:1/17:0), Cer(d18:1/17:0), sphingosine (d17:1), DG(12:0/12:0/0:0), DG(18:1/2:0/0:0), and d5-TG(17:0/17:1/17:0)] was added to a 40 μL blood plasma aliquot in a 2 mL Eppendorf tube and then vortexed (10 s). Then, 1000 μL of cold MTBE containing CE 22:1 (internal standard) was added, followed by vortexing (10 s) and shaking (6 min) at 4 °C. Phase separation was induced by adding 250 μL of LC−MS grade water followed by centrifugation at 14000 rpm for 2 min.
Sampleprep Protocol Filename:acs_analchem_7b03404.pdf

Combined analysis:

Analysis ID AN001609
Analysis type MS
Chromatography type Reversed phase
Chromatography system Agilent 6530
Column Waters Acquity CSH C18 (100 x 2.1mm,1.7um)
MS Type ESI
MS instrument type QTOF
MS instrument name Agilent 6530 QTOF
Ion Mode POSITIVE
Units nanograms (absolute)

Chromatography:

Chromatography ID:CH001131
Methods Filename:Data_Dictionary_Fiehn_laboratory_CSH_QTOF_lipidomics_05-29-2014.pdf
Instrument Name:Agilent 6530
Column Name:Waters Acquity CSH C18 (100 x 2.1mm,1.7um)
Column Pressure:450-850 bar
Column Temperature:65 C
Flow Gradient:15% B to 99% B
Flow Rate:0.6 mL/min
Injection Temperature:4 C
Internal Standard:See data dictionary
Retention Time:See data dictionary
Sample Injection:1.67 uL
Solvent A:60% acetonitrile/40% water; 10mM formic acid; 10mM ammonium formate
Solvent B:90% isopropanol/10% acetonitrile; 10mM formic acid; 10mM ammonium formate
Analytical Time:13 min
Capillary Voltage:3500 eV
Oven Temperature:50°C for 1 min, then ramped at 20°C/min to 330°C, held constant for 5 min
Time Program:15 min
Washing Buffer:Ethyl Acetate
Weak Wash Solvent Name:Isopropanol
Strong Wash Solvent Name:Isopropanol
Target Sample Temperature:Autosampler temp 4 C
Sample Loop Size:30 m length x 0.25 mm internal diameter
Randomization Order:Excel generated
Chromatography Type:Reversed phase

MS:

MS ID:MS001487
Analysis ID:AN001609
Instrument Name:Agilent 6530 QTOF
Instrument Type:QTOF
MS Type:ESI
Ion Mode:POSITIVE
Capillary Voltage:3500 eV
Collision Energy:25 eV
Collision Gas:Nitrogen
Dry Gas Flow:8L/min
Dry Gas Temp:325 C
Fragment Voltage:120 eV
Fragmentation Method:Auto MS/MS
Ion Source Temperature:325 C
Ion Spray Voltage:1000
Ionization:Pos
Ionization Energy:70eV
Mass Accuracy:Accurate
Reagent Gas:Nitrogen
Source Temperature:325 C
Dataformat:.d
Desolvation Gas Flow:11 L/min
Desolvation Temperature:350 C
Nebulizer:35 psig
Octpole Voltage:750 eV
Resolution Setting:Extended Dyamic Range
Scan Range Moverz:60-1700 Da
Scanning Cycle:2 Hz
Scanning Range:60-1700 Da
Skimmer Voltage:65
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