Summary of Study ST001834

This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench,, where it has been assigned Project ID PR001158. The data can be accessed directly via it's Project DOI: 10.21228/M8199Q This work is supported by NIH grant, U2C- DK119886.


This study contains a large results data set and is not available in the mwTab file. It is only available for download via FTP as data file(s) here.

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Study IDST001834
Study TitleA metabolomics comparison of plant-based meat and grass-fed meat indicates large nutritional differences despite comparable nutrition facts labels
Study SummaryA new generation of plant-based meat alternatives—formulated to mimic the taste and nutritional composition of red meat—have attracted considerable consumer interest, research attention, and media coverage. This has raised questions of whether plant-based meat alternatives represent proper nutritional replacements to animal meat. Given that food sources have considerable complexity and contain a wide variety of nutrients (e.g., phenols, anti-oxidants, peptides, amino acids, fatty acids, and other carboxylic acids), the majority of which do not appear on nutrition labels, it is important to explore expanded nutrient profiles when determining whether beef and plant-based meat alternatives are nutritionally interchangeable. Important nutritional differences may exist between beef and novel plant-based alternatives, given their materials origin; however, this has not been thoroughly assessed. Given the scientific and commercial interest in plant-based meat alternatives, the goal of our study was to use untargeted metabolomics to provide an in-depth comparison of the metabolite profiles of grass-fed ground beef and a popular plant-based meat alternative.
Duke University
Last Namevan Vliet
First NameStephan
Address300 N Duke Street
Submit Date2021-06-03
Raw Data AvailableYes
Raw Data File Type(s)cdf
Analysis Type DetailGC-MS
Release Date2021-06-24
Release Version1
Stephan van Vliet Stephan van Vliet application/zip

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Combined analysis:

Analysis ID AN002976
Analysis type MS
Chromatography type GC
Chromatography system Agilent 7890B
Column Agilent DB5-MS (15m x 0.25mm,0.25um)
MS Type EI
MS instrument type Single quadrupole
MS instrument name Agilent 5977
Units Log-transformed deconvoluted spectra


MS ID:MS002766
Analysis ID:AN002976
Instrument Name:Agilent 5977
Instrument Type:Single quadrupole
MS Type:EI
MS Comments:Raw data from Agilent's MassHunter software environment were imported into the freeware, Automatic Mass Spectral Deconvolution and Identification Software or AMDIS (version 2.73)—7-9; courtesy of NIST at Peaks were not normalized, with all samples run in a single batch sequence, for which we have found normalization of peak intensities to not be necessary. Deconvoluted spectra were annotated as metabolites using an orthogonal approach that incorporates both retention time (RT) from GC and the fragmentation pattern observed in EI-MS. Peak annotation was based primarily on our own RT-locked spectral library of metabolites (2059 spectra from 1174 unique compounds at the time of analysis; January 2020). Our library is built upon the Fiehn GC/MS Metabolomics RTL Library (a gift from Agilent, their part number G1676-90000; Kind et al. 2009 3. Additional spectra have been gleaned from running pure reagent standards in our lab, from the Golm Metabolome Library10, and from the Wiley 10th-NIST 2014 commercial library (Agilent G1730-64000). Peak alignment and chemometrics of log-base-two-transformed areas of deconvoluted peaks were performed with our own custom macros, written in our lab in Visual Basic (version 6.0) for use in the Excel (Microsoft Office Professional Plus 2019) software environment (both from Microsoft, Redmond, WA)