Development of metabolomic technologies for identification and quantification of intracellular metabolites.

Abstract

Technologies developed for the detection, identification and quantification of endogenous metabolites are described. The identification and quantification of large scale (hundreds) small molecules will offer deeper insight into function of biochemical pathways. A better understanding of the biochemical composition is of great interest as it holds the promise of unlocking keys to unknown pathophysiologies and gene functions particularly to those areas which undergo specific metabolic perturbations. Detection of these large scale metabolites was undertaken using mass spectrometry and separation systems (capillary liquid chromatography and capillary electrophoresis) coupled to mass spectrometry. Negative mode matrix assisted laser desorption ionization (MALDI) time of flight mass spectrometry was used to analyze metabolites from prokaryotes and eukaryotes, yielding 60 and 44 metabolites respectively. Metabolite changes were quantified using a ratio metric method for islets of Langerhans. Capillary electrophoresis mass spectrometry employed a sheathless interface in negative mode yielding 118 metabolites from <italic>Escherichia coli</italic>. For a more robust approach, capillary liquid chromatography mass spectrometry was used to investigate metabolites from prokaryotes detecting 99 metabolites. To augment capillary LC, two dimensional capillary chromatography employed strong anion exchange and reverse phase chromatography, increasing efficacy of system. Increasing resolution of the separation system allowed for a 42% and 102% increase in number of metabolites detected in <italic>E. coli</italic> and islets respectively. Tentative identification of metabolites was made using mass as determined by mass spectrometry. MALDI-TOF-MS yielded higher mass accuracy, 50 ppm, than separations coupled to quadrupole ion trap with &sim;300 ppm mass accuracy. To improve identification, tandem mass spectrometry was used with separation based systems resulting in increased confidence of identification. To further augment identification, isotope labeling was examined in prokaryotes. Complete carbon-13 labeling allowed identification based on mass, carbon number, fragmentation and carbon number of each fragment. Using this method, 46 compounds could be identified and the previously unidentified metabolite 5-mercapto-orotate was uncovered. Ratiometric quantitation was undertaken for the isotope labeled prokaryotic metabolome. By stimulating an unlabeled sample and ratioing its change to an unstimulated standard, 47 metabolite levels were detected to change significantly with p < 0.05. These changes were then related to biochemical pathways including the tricarboxylic acid cycle and biosynthesis of pyrimidines to gain a further understanding of metabolic networks.