2011
DOI: 10.1021/ac2021823
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Toward Global Metabolomics Analysis with Hydrophilic Interaction Liquid Chromatography–Mass Spectrometry: Improved Metabolite Identification by Retention Time Prediction

Abstract: Metabolomics is an emerging field of postgenomic biology concerned with comprehensive analysis of small molecules in biological systems. However, difficulties associated with the identification of detected metabolites currently limit its application. Here we demonstrate that a retention time prediction model can improve metabolite identification on a hydrophilic interaction chromatography (HILIC)-high-resolution mass spectrometry metabolomics platform. A quantitative structure retention relationship (QSRR) mod… Show more

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Cited by 317 publications
(304 citation statements)
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“…LC-MS analysis utilized hydrophilic interaction chromatography with a ZIC-HILIC column (Sequant) and a formic acid mobile phase and was coupled to high-resolution MS with the Exactive Orbitrap (Thermo) operating in both positive and negative modes with all parameters as previously described (23).…”
Section: Methodsmentioning
confidence: 99%
“…LC-MS analysis utilized hydrophilic interaction chromatography with a ZIC-HILIC column (Sequant) and a formic acid mobile phase and was coupled to high-resolution MS with the Exactive Orbitrap (Thermo) operating in both positive and negative modes with all parameters as previously described (23).…”
Section: Methodsmentioning
confidence: 99%
“…Liquid chromatography separation used a zwitterionic ZIC-hydrophilic interaction liquid chromatography column (Merck Sequant, Watford, UK) with a formic acid gradient, as previously described (Zhang et al, 2012). The method was performed on a Dionex U3000 RSLC (Thermo Fisher, Loughborough, UK) liquid chromatography system coupled to an Exactive Orbitrap (Thermo Fisher) operating at 50,000 resolution in positive and negative mode electrospray ionization (rapid switching), with MS parameters as described (Creek et al, 2011). Metabolomics data were analyzed using the IDEOM application (http:// mzmatch.sourceforge.net/ideom.php) with default parameters .…”
Section: Methodsmentioning
confidence: 99%
“…Metabolomics data were analyzed using the IDEOM application (http:// mzmatch.sourceforge.net/ideom.php) with default parameters . Metabolites were identified by accurate mass and retention time (or predicted retention time where standards were unavailable) according to the IDEOM metabolite database (Creek et al, 2011), with the addition of possible mBBr adducts for common cellular thiols. Molecular formulae for unidentified metabolites were determined based on accurate mass using the IDEOM application.…”
Section: Methodsmentioning
confidence: 99%
“…Other features were putatively annotated (MSI level 2) based on accurate mass and predicted retention time using the IDEOM database (35). The final data set consisted of 460 putatively identified metabolites, from a total of ϳ1,500 unique mass features.…”
Section: Cell Culture and Drug Incubations For Lc-ms Metabolomics Anamentioning
confidence: 99%