Liquid chromatography-bioassay-mass spectrometry for profiling of physiologically active food
Gertrud E Morlock1, Ines Klingelhöfer
1Chair of Food Science, Justus Liebig University Giessen , Interdisciplinary Research Centre (IFZ) and Institute of Nutritional Science, Heinrich-Buff-Ring 26-32, 35392 Giessen, Germany.
Abstract:
Complex samples like food contain thousands of single compounds. In the past, only known target compounds were looked for; however, most bioactive compounds in food are unknown. On the contrary, nontarget analyses face the challenge of determining the thousand peaks' identities, but it remains largely unclear which peaks are bioactive. Here, we show a novel effect-directed food profiling, as food and food supplements can be unknowingly physiologically active. By the combination of planar chromatography, using water-wettable reversed phase high-performance thin-layer chromatography (HPTLC RP18 W) plates, with detection by specific microorganisms, endocrine compounds in food were quantitatively detected as sharp-bounded zones and further characterized by mass spectrometry. This analytical workflow allowed frequent food intakes to be identified as risky with regard to estrogen-effective compounds, in discussion for their potential involvement in foodborne pathogenesis and for use in personalized health care. Using this accelerated workflow with its comprehensive detection potential, unknown endocrine compounds can be discovered. Exemplarily, the discovery of up to six endocrine disrupting compounds was shown in seven propolis samples and in four spices. For example, microorganisms quantitatively detected an estrogen-effective compound in the range of 0.07-0.24% in seven propolis samples, which was assigned to be caffeic acid phenethyl ester by mass spectrometry. This streamlined nontarget analysis detected modes of action, followed by targeted characterization of newly discovered effective compounds. Also, drug discovery or analysis of traditional medicines may profit from this effect-directed profiling of complex samples.
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