Mass Spectrometry of Biologically Active Small Molecules Focusing on polyphenols, alkaloids and amino acids

University dissertation from Stockholm : Department of Analytic Chemistry, Stockholm University

Abstract: The foci of this dissertation are on advanced liquid chromatography (LC) separation and mass spectrometry (MS) techniques for the analysis of small bioactive molecules. In addition to discussing general aspects of such techniques the results from analyses of polyphenols (PPs), alkaloids and amino acids published in five appended studies are presented and discussed. High efficiency and well understood principles make LC the method of choice for separating analytes in many kinds of scientific investigations. Moreover, when LC is coupled to an MS instrument, analytes are separated in two stages: firstly they are separated and pre-concentrated in narrow bands using LC and then separated according to their mass-to-charge (m/z) ratios in the MS instrument. Some MS instruments can provide highly accurate molecular weight measurements and mass resolution allowing identification of unknown compounds based purely on MS data, thus making prior separation unnecessary. However, prior separation is essential for analyzing substances in most complex matrices – especially useful is the ultra-high performance LC (UHPLC). The advantages of using UHPLC rather than HPLC for the analysis of PPs in tea and wine were evaluated in one of the studies this thesis is based upon. The phenolic composition of red wine was also examined, using a novel LDI technique, following solid phase extraction (SPE). A class of small aromatic molecules (medicinally important alkaloids) also proved to be amenable to straightforward analysis, by thin layer chromatography (TLC) work-up followed by LDI-MS. Finally, a LC-MS method for monitoring neurotoxins (β-N-methyl-amino-L-alanine and 2,3-diaminobutyric acid) in complex biological matrices was developed and applied. Overall, the studies show that careful attention to the physicochemical properties of analytes can provide insights that can greatly facilitate the development of alternative methods to analyze them, e.g. by LDI.

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