Metabolite Profiling of Human Amniotic Fluid by Hyphenated Nuclear Magnetic Resonance Spectroscopy

The metabolic profiling of human amniotic fluid (HAF) is of potential interest for the diagnosis of disorders in the mother or the fetus. In order to build a comprehensive metabolite database for HAF, hyphenated NMR has been used, for the first time, for systematic HAF profiling. Experiments were ca...

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Veröffentlicht in:Analytical chemistry (Washington) 2008-08, Vol.80 (15), p.6085-6092
Hauptverfasser: Graça, Gonçalo, Duarte, Iola F, J. Goodfellow, Brian, Carreira, Isabel M, Couceiro, Ana Bela, Domingues, Maria do Rosário, Spraul, Manfred, Tseng, Li-Hong, Gil, Ana M
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Sprache:eng
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Zusammenfassung:The metabolic profiling of human amniotic fluid (HAF) is of potential interest for the diagnosis of disorders in the mother or the fetus. In order to build a comprehensive metabolite database for HAF, hyphenated NMR has been used, for the first time, for systematic HAF profiling. Experiments were carried out using reverse-phase (RP) and ion-exchange liquid chromatography (LC), in order to detect less and more polar compounds, respectively. RP-LC conditions achieved good separation of amino acids, some sugars, and xanthines. Subsequent NMR and MS analysis enabled the rapid identification of 30 compounds, including 3-methyl-2-oxovalerate and 4-aminohippurate identified in HAF for the first time, to our knowledge. Under ion-exchange LC conditions, a different set of 30 compounds was detected, including sugars, organic acids, several derivatives of organic acids, and amino acids. In this experiment, five compounds were identified for the first time in HAF: d-xylitol, amino acid derivatives (N-acetylalanine, N-acetylglycine, 2-oxoleucine), and isovalerate. The nonendogenous nature of some metabolites (caffeine, paraxanthine, d-xylitol, sorbitol) is discussed. Hyphenated NMR has allowed the rapid detection of ∼60 metabolites in HAF, some of which are not detectable by standard NMR due to low abundance (μM) and signal overlap thus enabling an extended metabolite database to be built for HAF.
ISSN:0003-2700
1520-6882
DOI:10.1021/ac800907f