Simultaneous quantification of energetically important metabolites in various cell types by CZE.

A new CZE method was developed for the determination of 12 purine and pyrimidine nucleotides, two adenine coenzymes and their reduced forms, and acetyl coenzyme A in various cell extracts. As the concentration levels of these metabolites in living cells are low; CZE was combined with field-enhanced sample stacking. As a result, the separation conditions were optimised to achieve a suitable resolution at the relatively high sample volume provided by this on-line pre-concentration technique. The optimum BGE was 150 mM glycine buffer (pH 9.5). Samples were introduced hydrodynamically using a pressure of 35 mbar (3.5 kPa) for 25 s, and data were collected at a detection wavelength of 260 nm. An applied voltage of 30 kV (positive polarity) and capillary temperature of 25°C gave the best separation of these compounds. The optimised method was validated by determining the linearity, sensitivity and repeatability and it was successfully applied for the analysis of extracts from Paracoccus denitrificans bacteria and from stem cells.

Capillary zone electrophoresis with field enhanced sample stacking as a tool for targeted metabolome analysis of adenine nucleotides and coenzymes in Paracoccus denitrificans.

The main aim of this work was to demonstrate the applicability of capillary zone electrophoresis in combination with field enhanced sample stacking in targeted metabolome analyses of adenine nucleotides--AMP, ADP, ATP, coenzymes NAD(+), NADP(+) and their reduced forms in Paracoccus denitrificans. Sodium carbonate/hydrogencarbonate buffer (100 mM, pH 9.6) with the addition of beta-CD at a concentration of 10 mM was found to be an effective BGE for their separation within 20 min. Besides this, special attention was paid to the development of the procedure for the extraction of specific metabolites from the bacterium P. denitrificans. This procedure was not only optimised to achieve the highest metabolite yields but also to obtain a sample that was fully compatible with the online preconcetration strategy used. The developed methodology was finally applied in a study of the bacterium P. denitrificans at various stages of the active respiratory chain.

Nonlinear regression models for determination of nicotinamide adenine dinucleotide content in human embryonic stem cells.

Recent evidence suggests that energy metabolism contributes to molecular mechanisms controlling stem cell identity. For example, human embryonic stem cells (hESCs) receive their metabolic energy mostly via glycolysis rather than mitochondrial oxidative phosphorylation. This suggests a connection of metabolic homeostasis to stemness. Nicotinamide adenine dinucleotide (NAD) is an important cellular redox carrier and a cofactor for various metabolic pathways, including glycolysis. Therefore, accurate determination of NAD cellular levels and dynamics is of growing importance for understanding the physiology of stem cells. Conventional analytic methods for the determination of metabolite levels rely on linear calibration curves. However, in actual practice many two-enzyme cycling assays, such as the assay systems used in this work, display prominently nonlinear behavior. Here we present a diaphorase/lactate dehydrogenase NAD cycling assay optimized for hESCs, together with a mechanism-based, nonlinear regression models for the determination of NAD(+), NADH, and total NAD. We also present experimental data on metabolic homeostasis of hESC under various physiological conditions. We show that NAD(+)/NADH ratio varies considerably with time in culture after routine change of medium, while the total NAD content undergoes relatively minor changes. In addition, we show that the NAD(+)/NADH ratio, as well as the total NAD levels, vary between stem cells and their differentiated counterparts. Importantly, the NAD(+)/NADH ratio was found to be substantially higher in hESC-derived fibroblasts versus hESCs. Overall, our nonlinear mathematical model is applicable to other enzymatic amplification systems.