Metabolic flux quantification in plants is instrumental in the detailed understanding of metabolism but is difficult to perform on a systemic level. Toward this aim, we report the development and application of a computer-aided metabolic flux analysis tool that enables the concurrent evaluation of fluxes in several primary metabolic pathways. Labeling experiments were performed by feeding a mixture of U-13 C Suc, naturally abundant Suc, and Gln to developing soybean (Glycine max) embryos. Two-dimensional [ 13 C, 1 H] NMR spectra of seed storage protein and starch hydrolysates were acquired and yielded a labeling data set consisting of 155 13 C isotopomer abundances. We developed a computer program to automatically calculate fluxes from this data. This program accepts a user-defined metabolic network model and incorporates recent mathematical advances toward accurate and efficient flux evaluation. Fluxes were calculated and statistical analysis was performed to obtain SDs. A high flux was found through the oxidative pentose phosphate pathway (19.99 6 4.39 mmol d 21 cotyledon 21 , or 104.2 carbon mol 6 23.0 carbon mol per 100 carbon mol of Suc uptake). Separate transketolase and transaldolase fluxes could be distinguished in the plastid and the cytosol, and those in the plastid were found to be at least 6-fold higher. The backflux from triose to hexose phosphate was also found to be substantial in the plastid (21.72 6 5.00 mmol d 21 cotyledon
21, or 113.2 carbon mol 626.0 carbon mol per 100 carbon mol of Suc uptake). Forward and backward directions of anaplerotic fluxes could be distinguished. The glyoxylate shunt flux was found to be negligible. Such a generic flux analysis tool can serve as a quantitative tool for metabolic studies and phenotype comparisons and can be extended to other plant systems.
Single-gene disorders with "simple" Mendelian inheritance do not always imply that there will be an easy prediction of the phenotype from the genotype, which has been shown for a number of metabolic disorders. We propose that moonlighting enzymes (i.e., metabolic enzymes with additional functional activities) could contribute to the complexity of such disorders. The lack of knowledge about the additional functional activities of proteins could result in a lack of correlation between genotype and phenotype. In this review, we highlight some notable and recent examples of moonlighting enzymes and their possible contributions to human disease. Because knowledge and cataloging of the moonlighting activities of proteins are essential for the study of cellular function and human physiology, we also review recently reported and recommended methods for the discovery of moonlighting activities.
Glycerol kinase has several diverse activities in mammalian cells. Glycerol kinase deficiency is a complex, single-gene, inborn error of metabolism wherein no genotype-phenotype correlation has been established. Since glycerol kinase has been suggested to exhibit additional activities than glycerol phosphorylation, expression level perturbation in this enzyme may affect cellular physiology globally. To investigate this possibility, we conducted metabolic investigations of wild type and two glycerol kinase-overexpressing H4IIE rat hepatoma cell lines constructed in this study. The glycerol kinase-overexpressing cell lines exhibited a significantly higher consumption of carbon sources per cell, suggesting excess carbon expenditure. Furthermore, we quantified intracellular metabolic fluxes by employing stable isotope ( 13 C) labeling with a mathematically designed substrate mixture, gas chromatography-mass spectrometry, and comprehensive isotopomer balancing. This flux analysis revealed that the pentose phosphate pathway flux in the glycerol kinase-overexpressing cell lines was two-fold higher than that in the wild type, in addition to subtler flux changes in other pathways of carbohydrate metabolism. Furthermore, the activity and transcript level of the lipogenic enzyme glucose-6-phosphate dehydrogenase, the rate-limiting enzyme of the pentose phosphate pathway, were also about two-fold higher than that of the wild type; these data corroborate the flux analysis results. This study shows that glycerol kinase affects carbon metabolism globally, possibly through its additional functions, and highlights glycerol kinase's multifaceted role in cellular physiology.
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