Metabolic fingerprinting of high-fat plasma samples processed by centrifugation- and filtration-based protein precipitation delineates significant differences in metabolite information coverage
Abstract
Metabolomics and metabolic fingerprinting are being extensively employed for improved understanding of biological changes induced by endogenous or exogenous factors. Blood serum or plasma samples are often employed for metabolomics studies. Plasma protein precipitation (PPP) is currently performed in most laboratories before LC-MS analysis. However, the impact of fat content in plasma samples on metabolite coverage has not previously been investigated. Here, we have studied whether PPP procedures influence coverage of plasma metabolites from high-fat plasma samples. An optimized UPLC-QTOF/MS metabolic fingerprinting approach and multivariate modeling (PCA and OPLS-DA) were utilized for finding characteristic metabolite changes induced by two PPP procedures; centrifugation and filtration. We used 12-h fasting samples and postprandial samples collected at 2h after a standardized high-fat protein-rich meal in obese non-diabetic subjects recruited in a dietary intervention. The two PPP procedures as well as external and internal standards (ISs) were used to track errors in response normalization and quantification. Remarkably and sometimes uniquely, the fPPP, but not the cPPP approach, recovered not only high molecular weight (HMW) lipophilic metabolites, but also small molecular weight (SMW) relatively polar metabolites. Characteristic SMW markers of postprandial samples were aromatic and branched-chain amino acids that were elevated (p<0.001) as a consequence of the protein challenge. In contrast, some HMW lipophilic species, e.g. acylcarnitines, were moderately lower (p<0.001) in postprandial samples. LysoPCs were largely unaffected. In conclusion, the fPPP procedure is recommended for processing high-fat plasma samples in metabolomics studies. While method improvements presented here were clear, use of several ISs revealed substantial challenges to untargeted metabolomics due to large and variable matrix effects.
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Variables affecting the final data set include sample preparation mode, chromatography method, detection mode, and choice of data reduction methods.
“These include the mode of sample preparation, method of chromatography, mode of detection, and the choice of data reduction methods (116, 117).”
From The food metabolome: a window over dietary exposure (2014) · cites this paper as [116]
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The food metabolome: a window over dietary exposure
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- Authors
- Barri, T., Holmer-Jensen, J., Hermansen, K., & Dragsted, L. O.
- Affiliations
- University of Copenhagen (DK)
- Aarhus University Hospital (DK)
- Corresponding author
- Barri, Thaer
- Venue
- Analytica Chimica Acta
- Publisher
- Elsevier BV
- Published
- 2012-03
- Volume
- 718
- Pages
- 47-57
- ISSN
- 0003-2670 (ISSN-L)
- OpenAlex
- W2069313484
- Cited by
- 57
- References
- 30
- Citations by year
- 2026: 2 · 2025: 4 · 2024: 1 · 2023: 3 · 2022: 2 · 2021: 7 · 2020: 5 · 2019: 5 · 2018: 1 · 2017: 1 · 2016: 2 · 2015: 2 · 2014: 9 · 2013: 10 · 2012: 3
- FWCI
- 3.08
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Analytica Chimica Acta (publishedVersion)
- PubMed (publishedVersion)
- Research at the University of Copenhagen (University of Copenhagen) (submittedVersion)
- Funders
- Arla Foods Ingredients Group
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolomics and Mass Spectrometry Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Clinical Biochemistry › Metabolism and Genetic Disorders
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diet, Metabolism, and Disease
- Keywords
- plasma protein precipitation, metabolic fingerprinting, postprandial metabolism, branched-chain amino acids, aromatic amino acids, acylcarnitines, lysophosphatidylcholine, matrix effects, internal standard, UPLC-Q-TOF-MS, dietary intervention
- MeSH terms
- Blood Proteins, Centrifugation, Fasting, Fats, Female, Filtration, Humans, Male, Plasma, Chemical Precipitation, Postprandial Period, Metabolomics
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