Polar metabolomics using trichloroacetic acid extraction and porous graphitic carbon stationary phase
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Published:2024-07-16
Issue:4
Volume:20
Page:
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ISSN:1573-3890
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Container-title:Metabolomics
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language:en
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Short-container-title:Metabolomics
Author:
Day Francesca,O’Sullivan Justin,Ramzan Farha,Pook Chris
Abstract
Abstract
Introduction
Accurately identifying and quantifying polar metabolites using untargeted metabolomics has proven challenging in comparison to mid to non-polar metabolites. Hydrophilic interaction chromatography and gas chromatography–mass spectrometry are predominantly used to target polar metabolites.
Objectives
This study aims to demonstrate a simple one-step extraction combined with liquid chromatography–mass spectrometry (LC–MS) that reliably retains polar metabolites.
Methods
The method involves a MilliQ + 10% trichloroacetic acid extraction from 6 healthy individuals serum, combined with porous graphitic carbon liquid chromatography–mass spectrometry (LC–MS). The coefficient of variation (CV) assessed retention reliability of polar metabolites with logP as low as − 9. QreSS (Quantification, Retention, and System Suitability) internal standards determined the method's consistency and recovery efficiency.
Results
The method demonstrated reliable retention (CV < 0.30) of polar metabolites within a logP range of − 9.1 to 5.6. QreSS internal standards confirmed consistent performance (CV < 0.16) and effective recovery (70–130%) of polar to mid-polar metabolites. Quality control dilution series demonstrated that ~ 80% of annotated metabolites could be accurately quantified (Pearson’s correlation coefficient > 0.80) within their concentration range. Repeatability was demonstrated through clustering of repeated extractions from a single sample.
Conclusion
This LC–MS method is better suited to covering the polar segment of the metabolome than current methods, offering a reliable and efficient approach for accurate quantification of polar metabolites in untargeted metabolomics.
Funder
UoA Scholarship High-Value Nutrition Ko Ngā Kai Whai Painga National Science Challenge Shundi Group University of Auckland
Publisher
Springer Science and Business Media LLC
Reference39 articles.
1. Alseekh, S., Aharoni, A., Brotman, Y., Contrepois, K., D’Auria, J., Ewald, J., et al. (2021). Mass spectrometry-based metabolomics: a guide for annotation, quantification and best reporting practices. Nature Methods, 18(7), 747–756. https://doi.org/10.1038/s41592-021-01197-1 2. ASTM International. (2020). Standard Test Method for The Determination of Total Aromatic Hydrocarbons and Total Polynuclear Aromatic Hydrocarbons in Aviation Turbine Fuels and other Kerosene Range Fuels by Supercritical Fluid Chromatography. 3. Bagheri, M., Djazayery, A., Farzadfar, F., Qi, L., Yekaninejad, M. S., Aslibekyan, S., et al. (2019). Plasma metabolomic profiling of amino acids and polar lipids in Iranian obese adults. Lipids in Health and Disease, 18(1), 1–9. https://doi.org/10.1186/S12944-019-1037-0/FIGURES/3 4. Bian, X., Qian, Y., Tan, B., Li, K., Hong, X., Wong, C. C., et al. (2020). In-depth mapping carboxylic acid metabolome reveals the potential biomarkers in colorectal cancer through characteristic fragment ions and metabolic flux. Analytica Chimica Acta, 1128, 62–71. https://doi.org/10.1016/J.ACA.2020.06.064 5. Brodsky, L., Moussaieff, A., Shahaf, N., Aharoni, A., & Rogachev, I. (2010). Evaluation of peak picking quality in LC–MS metabolomics data. Analytical Chemistry, 82(22), 9177–9187. https://doi.org/10.1021/AC101216E/SUPPL_FILE/AC101216E_SI_004.ZIP
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