2018
DOI: 10.1007/978-1-4939-7643-0_11
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GC-MS Metabolomic Profiling of Protic Metabolites Following Heptafluorobutyl Chloroformate Mediated Dispersive Liquid Microextraction Sample Preparation Protocol

Abstract: A simple analytical workflow is described for gas chromatographic-mass spectrometry (GC-MS)-based metabolomic profiling of protic metabolites, particularly amino-carboxylic species in biological matrices. The sample preparation is carried out directly in aqueous samples and uses simultaneous in situ heptafluorobutyl chloroformate (HFBCF) derivatization and dispersive liquid-liquid microextraction (DLLME), followed by GC-MS analysis in single-ion monitoring (SIM) mode. The protocol involves ten simple pipetting… Show more

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Cited by 5 publications
(1 citation statement)
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“…This places high demands on the relevant analytical technique, which must ensure the simultaneous determination of five different AAs (Val, Leu, Ile, Ala, and Gln) on the large sets of blood plasma samples that are included in the clinical study to ensure its high validity. Since these AAs are nonvolatile water‐soluble substances that provide only a weak signal in direct UV/VIS photometry at 190–210 nm wavelengths [5], the use of HPLC or GC is necessarily associated with complicated sample derivatizations [6–10]. MS is suitable for the identification of unknown substances in complex samples, but it is not an ideal choice for the precise quantification of AAs in complex matrices [11–14].…”
Section: Introductionmentioning
confidence: 99%
“…This places high demands on the relevant analytical technique, which must ensure the simultaneous determination of five different AAs (Val, Leu, Ile, Ala, and Gln) on the large sets of blood plasma samples that are included in the clinical study to ensure its high validity. Since these AAs are nonvolatile water‐soluble substances that provide only a weak signal in direct UV/VIS photometry at 190–210 nm wavelengths [5], the use of HPLC or GC is necessarily associated with complicated sample derivatizations [6–10]. MS is suitable for the identification of unknown substances in complex samples, but it is not an ideal choice for the precise quantification of AAs in complex matrices [11–14].…”
Section: Introductionmentioning
confidence: 99%