A kinetic model of Escherichia coli core metabolism satisfying multiple sets of mutant flux data

In contrast to stoichiometric-based models, the development of large-scale kinetic models of metabolism has been hindered by the challenge of identifying kinetic parameter values and kinetic rate laws applicable to a wide range of environmental and/or genetic perturbations. The recently introduced ensemble modeling (EM) procedure provides a promising remedy to address these challenges by decomposing metabolic reactions into elementary reaction steps and incorporating all phenotypic observations, upon perturbation, in its model parameterization scheme. Here, we present a kinetic model of Escherichia coli core metabolism that satisfies the fluxomic data for wild-type and seven mutant strains by making use of the EM concepts. This model encompasses 138 reactions, 93 metabolites and 60 substrate-level regulatory interactions accounting for glycolysis/gluconeogenesis, pentose phosphate pathway, TCA cycle, major pyruvate metabolism, anaplerotic reactions and a number of reactions in other parts of the metabolism. Parameterization is performed using a formal optimization approach that minimizes the discrepancies between model predictions and flux measurements. The predicted fluxes by the model are within the uncertainty range of experimental flux data for 78% of the reactions (with measured fluxes) for both the wild-type and seven mutant strains. The remaining flux predictions are mostly within three standard deviations of reported ranges. Converting the EM-based parameters into a Michaelis–Menten equivalent formalism revealed that 35% of K_m and 77% of k_cat parameters are within uncertainty range of the literature-reported values. The predicted metabolite concentrations by the model are also within uncertainty ranges of metabolomic data for 68% of the metabolites. A leave-one-out cross-validation test to evaluate the flux prediction performance of the model showed that metabolic fluxes for the mutants located in the proximity of mutations used for training the model can be predicted more accurately. The constructed model and the parameterization procedure presented in this study pave the way for the construction of larger-scale kinetic models with more narrowly distributed parameter values as new metabolomic/fluxomic data sets are becoming available for E. coli and other organisms.     

A metabolomics-based method for studying the effect of yfcC gene in Escherichia coli on metabolism

Metabolomics is a potent tool to assist in identifying the function of unknown genes through analysis of metabolite changes in the context of varied genetic backgrounds. However, the availability of a universal unbiased profiling analysis is still a big challenge. In this study, we report an optimized metabolic profiling method based on gas chromatography–mass spectrometry for Escherichia coli. It was found that physiological saline at −80 °C could ensure satisfied metabolic quenching with less metabolite leakage. A solution of methanol/water (21:79, v/v) was proved to be efficient for intracellular metabolite extraction. This method was applied to investigate the metabolome difference among wild-type E. coli, its yfcC deletion, and overexpression mutants. Statistical and bioinformatic analysis of the metabolic profiling data indicated that the expression of yfcC potentially affected the metabolism of glyoxylate shunt. This finding was further validated by real-time quantitative polymerase chain reactions showing that expression of aceA and aceB, the key genes in glyoxylate shunt, was upregulated by yfcC. This study exemplifies the robustness of the proposed metabolic profiling analysis strategy and its potential roles in investigating unknown gene functions in view of metabolome difference.     

Effect of acute ethanol on serine biosynthesis in liver

The effect of an acute intraperitoneal dose of ethanol (1 g/kg), glucose (7.2 g/kg), or the combination of the two on the metabolite pattern of the biosynthetic pathway of l-serine has been determined in rabbit liver in vivo as has the effect of 10 mm ethanol on the glucose-, fructose-, or pyruvate-stimulated accumulation of l-serine in rabbit hepatocytes in vitro. In vivo, the 50% increase in l-serine and 80% increase in l-phosphoserine content of liver following glucose injection was completely prevented by ethanol. In fact, the l-phosphoserine content fell to only 6% of the control value. In spite of these and other significant changes in the metabolite pattern of the pathway of l-serine biosynthesis (d-3-phosphoglycerate dehydrogenase, l-phosphoserine aminotransferase (PSAT), and l-phosphoserine phosphatase), the mass action ratio of the combined reactions of the first two steps remained close to their equilibrium position. As a consequence it is estimated that the tissue content of phosphohydroxypyruvate fell to less than 2% of the control value, to approximately 0.3% of its K_m for the PSAT reaction. The conclusion that acute ethanol blocks l-serine biosynthesis (presumably by redox effects) was supported by the prevention or inhibition of l-serine accumulation in hepatocytes metabolizing glucose, fructose, or pyruvate. Because l-serine is an important source of one-carbon fragments, the inhibition of its biosynthesis may be another mechanism by which ethanol interferes with folate and one-carbon metabolism.     

Novel Key Metabolites Reveal Further Branching of the Roquefortine/Meleagrin Biosynthetic Pathway

Metabolic profiling and structural elucidation of novel secondary metabolites obtained from derived deletion strains of the filamentous fungus Penicillium chrysogenum were used to reassign various previously ascribed synthetase genes of the roquefortine/meleagrin pathway to their corresponding products. Next to the structural characterization of roquefortine F and neoxaline, which are for the first time reported for P. chrysogenum, we identified the novel metabolite roquefortine L, including its degradation products, harboring remarkable chemical structures. Their biosynthesis is discussed, questioning the exclusive role of glandicoline A as key intermediate in the pathway. The results reveal that further enzymes of this pathway are rather unspecific and catalyze more than one reaction, leading to excessive branching in the pathway with meleagrin and neoxaline as end products of two branches.     

Improvement of NADPH bioavailability in Escherichia coli through the use of phosphofructokinase deficient strains

NADPH-dependent reactions play important roles in production of industrially valuable compounds. In this study, we used phosphofructokinase (PFK)-deficient strains to direct fructose-6-phosphate to be oxidized through the pentose phosphate pathway (PPP) to increase NADPH generation. pfkA or pfkB single deletion and double-deletion strains were tested for their ability to produce lycopene. Since lycopene biosynthesis requires many NADPH, levels of lycopene were compared in a set of isogenic strains, with the pfkA single deletion strain showing the highest lycopene yield. Using another NADPH-requiring process, a one-step reduction reaction of 2-chloroacrylate to 2-chloropropionic acid by 2-haloacrylate reductase, the pfkA pfkB double-deletion strain showed the highest yield of 2-chloropropionic acid product. The combined effect of glucose-6-phosphate dehydrogenase overexpression or lactate dehydrogenase deletion with PFK deficiency on NADPH bioavailability was also studied. The results indicated that the flux distribution of fructose-6-phosphate between glycolysis and the pentose phosphate pathway determines the amount of NAPDH available for reductive biosynthesis.     

The N-Reductive System Composed of Mitochondrial Amidoxime Reducing Component (mARC), Cytochrome b5 (CYB5B) and Cytochrome b5 Reductase (CYB5R) Is Regulated by Fasting and High Fat Diet in Mice

The mitochondrial amidoxime reducing component mARC is the fourth mammalian molybdenum enzyme. The protein is capable of reducing N-oxygenated structures, but requires cytochrome b5 and cytochrome b5 reductase for electron transfer to catalyze such reactions. It is well accepted that the enzyme is involved in N-reductive drug metabolism such as the activation of amidoxime prodrugs. However, the endogenous function of the protein is not fully understood. Among other functions, an involvement in lipogenesis is discussed. To study the potential involvement of the protein in energy metabolism, we tested whether the mARC protein and its partners are regulated due to fasting and high fat diet in mice. We used qRT-PCR for expression studies, Western Blot analysis to study protein levels and an N-reductive biotransformation assay to gain activity data. Indeed all proteins of the N-reductive system are regulated by fasting and its activity decreases. To study the potential impact of these changes on prodrug activation in vivo, another mice experiment was conducted. Model compound benzamidoxime was injected to mice that underwent fasting and the resulting metabolite of the N-reductive reaction, benzamidine, was determined. Albeit altered in vitro activity, no changes in the metabolite concentration in vivo were detectable and we can dispel concerns that fasting alters prodrug activation in animal models. With respect to high fat diet, changes in the mARC proteins occur that result in increased N-reductive activity. With this study we provide further evidence that the endogenous function of the mARC protein is linked with lipid metabolism.     

Further developments towards a genome-scale metabolic model of yeast

Background

To date, several genome-scale network reconstructions have been used to describe the metabolism of the yeast Saccharomyces cerevisiae, each differing in scope and content. The recent community-driven reconstruction, while rigorously evidenced and well annotated, under-represented metabolite transport, lipid metabolism and other pathways, and was not amenable to constraint-based analyses because of lack of pathway connectivity.

Results

We have expanded the yeast network reconstruction to incorporate many new reactions from the literature and represented these in a well-annotated and standards-compliant manner. The new reconstruction comprises 1102 unique metabolic reactions involving 924 unique metabolites - significantly larger in scope than any previous reconstruction. The representation of lipid metabolism in particular has improved, with 234 out of 268 enzymes linked to lipid metabolism now present in at least one reaction. Connectivity is emphatically improved, with more than 90% of metabolites now reachable from the growth medium constituents. The present updates allow constraint-based analyses to be performed; viability predictions of single knockouts are comparable to results from in vivo experiments and to those of previous reconstructions.

Conclusions

We report the development of the most complete reconstruction of yeast metabolism to date that is based upon reliable literature evidence and richly annotated according to MIRIAM standards. The reconstruction is available in the Systems Biology Markup Language (SBML) and via a publicly accessible database http://www.comp-sys-bio.org/yeastnet/.