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High-performance liquid chromatography systems were developed to rapidly separate retinol from its esters, analyze the total spectrum of neutral vitamin A compounds, and purify retinyl esters to homogeneity. Chemical ionization mass spectrometric techniques were used to identify vitamin A compounds; these techniques are also applicable to quantification of tissue vitamin A compounds. These methods provide rapid and sensitive techniques for separation and quantification of neutral retinol metabolites. Their utility was demonstrated by analysis of vitamin A metabolites in rat tissues under steady-state conditions. Tissue specificity was noted for the concentrations of retinol and its long-chain fatty acid esters, the ratio of retinol to retinyl esters, and the fatty acid composition of retinyl esters. Quantitatively minor amounts of several neutral polar retinol metabolites were detected, but neither 13-cis-retinol nor 4-hydroxyretinol was observed in vivo as metabolites of retinol in kidney.
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In this work, an integrated modeling approach based on a metabolic signal flow diagram and cellular energetics was used to model the metabolic pathway analysis for the cultivation of yeast on glucose. This approach enables us to make a clear analysis of the flow direction of the carbon fluxes in the metabolic pathways as well as of the degree of activation of a particular pathway for the synthesis of biomaterials for cell growth. The analyses demonstrate that the main metabolic pathways of Saccharomyces cerevisiae change significantly during batch culture. Carbon flow direction is toward glycolysis to satisfy the increase of requirement for precursors and energy. The enzymatic activation of TCA cycle seems to always be at normal level, which may result in the overflow of ethanol due to its limited capacity. The advantage of this approach is that it adopts both virtues of the metabolic signal flow diagram and the simple network analysis method, focusing on the investigation of the flow directions of carbon fluxes and the degree of activation of a particular pathway or reaction loop. All of the variables used in the model equations were determined on-line; the information obtained from the calculated metabolic coefficients may result in a better understanding of cell physiology and help to evaluate the state of the cell culture process.
This study focused on elucidating metabolism of xylose in a Saccharomyces cerevisiae strain that overexpresses xylose reductase and xylitol dehydrogenase from Pichia stipitis, as well as the endogenous xylulokinase. The influence of xylose on overall metabolism was examined supplemented with low glucose levels with emphasis on two potential bottlenecks; cofactor requirements and xylose uptake. Results of metabolic flux analysis in continuous cultivations show changes in central metabolism due to the cofactor imbalance imposed by the two-step oxidoreductase reaction of xylose to xylulose. A comparison between cultivations on 27:3g/L xylose-glucose mixture and 10g/L glucose revealed that the NADPH-generating flux from glucose-6-phosphate to ribulose-5-phosphate was almost tenfold higher on xylose-glucose mixture and due to the loss of carbon in that pathway the total flux to pyruvate was only around 60% of that on glucose. As a consequence also the fluxes in the citric acid cycle were reduced to around 60%. As the glucose level was decreased to 0.1g/L the fluxes to pyruvate and in the citric acid cycle were further reduced to 30% and 20%, respectively. The results from in vitro and in vivo xylose uptake measurements showed that the specific xylose uptake rate was highest at the lowest glucose level, 0.1g/L.
In metabolic pathway analysis, it should be considered that many enzymes operate with low specificity (e.g. nucleoside diphosphokinase, uridine kinase, transketolase, aldolase), so that various substrates and products can be converted. Here, we analyze the effect of enzymes with low substrate specificity on the elementary flux modes (pathways). We also study the benefits of two different approaches to describing multifunctional enzymes. The usual description is in terms of (overall) enzymatic reactions. At a more detailed level, the reaction steps (half-reactions, hemi-reactions) of the formation and conversion of enzyme-substrate complexes are considered. Multifunctional enzymes operate according to various mechanisms. This is illustrated here by the reaction schemes for the different enzyme mechanisms of bifunctional enzymes. For enzymes with two or more functions, it is important to consider only linearly independent functions, because otherwise cyclic elementary modes would occur which do not perform any net transformation. However, the choice of linearly independent functions is not a priori unique. We give a method for making this choice unique by considering the extreme pathways of the hemi-reactions system. A formal application of the algorithm for computing elementary flux modes (pathways) yields the result that the number of such modes sometimes depend on the level of description if some reactions are reversible and the products of the multifunctional enzymes are external metabolites or some multifunctional enzymes partly share the same metabolites. However, this problem can be solved by appropriate interpretation of the definition of elementary modes and the correct choice of independent functions of multifunctional enzymes. The analysis is illustrated by a biochemical example taken from nucleotide metabolism, comparing the two ways of description for nucleoside diphosphokinase and adenylate kinase, and by several smaller examples.
Metabolic control analysis (Kacser & Burns (1973). Symp. Soc. Exp. Biol.27, 65-104; Heinrich & Rapoport (1974). Eur. J. Biochem.42, 89-95) has been extensively used to describe the response of metabolic concentrations and fluxes to small (infinitesimal) changes in enzyme concentrations and effectors. Similarly, metabolic control design (Acerenza (1993). J. theor. Biol.165, 63-85) has been proposed to design small metabolic responses. These approaches have the limitation that they were not devised to deal with large (non-infinitesimal) responses. Here we develop a strategy to design large changes in the metabolic variables. The only assumption made is that, for all the parameter values under consideration, the system has a unique stable steady state. The procedure renders the kinetic parameters of the rate equations that when embedded in the metabolic network produce the pattern of large changes in the steady-state variables that we aim to design. Structural and kinetic constraints impose restrictions on the type of responses that could be designed. We show that these conditions can be transformed into the language of mean-sensitivity coefficients and, as a consequence, a sensitivity analysis of large metabolic responses can be performed after the system has been designed. The mean-sensitivity coefficients fulfil conservation and summation relationships that in the limit reduce to the well-known theorems for infinitesimal changes. Finally, it is shown that the same procedure that was used to design metabolic responses and analyse their sensitivity properties can also be used to determine the values of kinetic parameters of the rate laws operating "in situ".
Metabolic network analysis is a tool for investigating the features that identify the topology of a metabolic network and the relative activities of its individual branches. The pillars of metabolic network analysis are mathematical modeling, allowing for a quantitative analysis, biochemical knowledge of, for example, reaction stoichiometry, and the experimental techniques, providing input for the modeling part. The modeling part includes metabolite balancing, usually the basis for metabolic flux analysis, and isotope balancing. Isotope balancing can be used for both identification of active pathways and for estimation of the relative fluxes through two pathways leading to the same metabolite, aspects that are difficult to investigate using metabolite balancing. The combination of metabolite and isotope balancing is very powerful and constitutes the basis of metabolic network analysis. With the main focus being on investigating the metabolic network structure, this review describes how central metabolic features, for example, pathway identification, flux distribution, and compartmentation, can be addressed using a combination of metabolite balancing and labeling experiments.
A detailed stoichiometric model was developed for growth and penicillin-G production in Penicillium chrysogenum. From an a priori metabolic flux analysis using this model it appeared that penicillin production requires significant changes in fluxes through the primary metabolic pathways. This is brought about by the biosynthesis of carbon precursors for the beta-lactan nucleus and an increased demand for NADPH, mainly for sulfate reduction. As a result, significant changes in flux partitioning occur around four principal nodes in primary metabolism. These are located at: (1) glucose-6-phosphate; (2) 3-phosphoglycerate; (3) mitochondrial pyruvate; and (4) mitochondrial isocitrate. These nodes should be regarded as potential bottlenecks for increased productivity. The flexibility of these principal nodes was investigated by experimental manipulation of the fluxes through the central metabolic pathways using a high-producing strain of P. chrysogenum. Metabolic fluxes were manipulated through growth of the cells on different substrates in carbon-limited chemostat culture. Metabolic flux analysis, based on measured input and output fluxes, was used to calculate the fluxes around the principal nodes. It was found that, for growth on glucose, ethanol, and acetate, the flux partitioning around these nodes differed significantly. However, this had hardly any effect on penicillin productivity, showing that primary carbon metabolism is not likely to contain potential bottlenecks. Further experiments were performed to manipulate the total metabolic demand for the cofactor nicotinamide adenine dinucleotide phosphate (NADPH). NADPH demand was increased stepwise by cultivating the cells on glucose or xylose as the carbon source combined with either ammonia or nitrate as the nitrogen source, which resulted in a stepwise decrease of penicillin production. This clearly shows that, in penicillin fermentation, possible limitations in primary metabolism reside in the supply/regeneration of cofactors (NADPH) rather than in the supply of carbon precursors.
Genetics is a powerful tool for analyzing metabolic regulation in bacteria, permitting definitive identification of key regulatory enzymes, and assignment of cause and effect relationships between molecular mechanisms that control activity of regulatory enzymes and flow of metabolites through the pathways of intermediary metabolism. In homeothermic vertebrates, however, traditional genetic analysis of metabolic regulation is difficult or impossible. Despite an enormous amount of factual information about metabolic pathways in vertebrates, our understanding of regulatory mechanisms is based largely on correlations between regulation of the activity of a purified enzyme by an effector and variations in the intracellular concentration of that effector under conditions that modulate flow of metabolites through the relevant metabolic pathway. Newly developed molecular genetic and gene transfer methods can now be used to study metabolic regulation in vertebrates. Some of these methods will be described in short reviews of the mechanisms by which diet, hormones, and tissue-type regulate transcription of the genes for L-type pyruvate kinase and phosphoenolpyruvate carboxykinase. Application of these techniques to analyses of structure/function in intact cells and animals will be illustrated with recent work on the receptor for low density lipoproteins and cyclic AMP-dependent protein kinases.
This paper considers certain aspects of the analysis of moiety-conserved cycles in terms of metabolic control analysis. Two response coefficients are discussed: the response coefficient with respect to the total number of moles in a cycle (RVT), and the response coefficient with respect to perturbations to the internal state of a pathway (RVS). The relationship between these two different measures is derived and two examples are given to illustrate how the results may be used to simplify the analysis of particular complex pathways. One example considers how metabolite sequestration affects the flux summation theorem for which the analysis confirms the known result that sequestration can depress the value of the summation to below unity. The second example investigates the effect of metabolic channelling on the summation theorems. The analysis indicates that in contrast to metabolite sequestration, metabolic channelling can cause the flux summation theorem to exceed the value of unity. In addition, the maximum value that the summation theorem can reach under these conditions is shown to be equal to 2. Finally, this analysis indicates how one might use control analysis through the use of enzyme titration to determine whether metabolic channelling occurs in real systems or not.
(1) Mammalian serine metabolism is discussed in relation to its synthesis and utilization in proliferating cells, particularly during the nonmalignant proliferation of lymphocytes. (2) An analysis of the control of serine biosynthesis de novo under conditions of high pathway flux has been carried out using metabolic control theory. (3) The important and novel conclusions are that control of pathway flux is localized exclusively at the final step of this biosynthetic pathway, phosphoserine phosphatase. This conclusion challenges the frequently stated maxim that control of biosynthetic pathways is always directed at the first pathway enzyme in a sequence. In the case of phosphoserine phosphatase, the enzyme is inhibited uncompetitively by its product serine, and this feedback control mechanism has the most significant controlling influence on overall pathway flux. Thus, the serine biosynthesis pathway, under these conditions, is controlled by product demand (serine utilization) and not by substrate supply (glycolytic provision of 3-phosphoglycerate), despite the high rate of glycolysis associated with cell proliferation. (4) The control structure of the pathway is not immutable. As has been observed with other pathways analyzed by metabolic control theory, the key points of control in the pathway can shift according to physiological circumstances. At low pathway flux, the control of serine biosynthesis is shared between all the component enzymes of the pathway, and the responsiveness of flux shifts from product demand to substrate supply. (5) Serine utilization has been studied in mitogenically-stimulated human peripheral lymphocytes. Cell proliferation and serine utilization for nucleic acid synthesis have been shown to be responsive to serine concentrations in the normal plasma range. (6) It is concluded that the maintenance of normal plasma serine concentrations is an important factor in the rate of lymphocyte proliferation and hence the effectiveness with which the body can mount an immune response to an antigenic challenge, such as in infection.
Metabolic flux analysis using carbon labeling experiments (CLEs) is an important tool in metabolic engineering where the intracellular fluxes have to be computed from the measured extracellular fluxes and the partially measured distribution of 13C labeling within the intracellular metabolite pools. The relation between unknown fluxes and measurements is described by an isotopomer labeling system (ILS) (see Part I [Math. Biosci. 169 (2001) 173]). Part II deals with the structural flux identifiability of measured ILSs in the steady state. The central question is whether the measured data contains sufficient information to determine the unknown intracellular fluxes. This question has to be decided a priori, i.e. before the CLE is carried out. In structural identifiability analysis the measurements are assumed to be noise-free. A general theory of structural flux identifiability for measured ILSs is presented and several algorithms are developed to solve the identifiability problem. In the particular case of maximal measurement information, a symbolical algorithm is presented that decides the identifiability question by means of linear methods. Several upper bounds of the number of identifiable fluxes are derived, and the influence of the chosen inputs is evaluated. By introducing integer arithmetic this algorithm can even be applied to large networks. For the general case of arbitrary measurement information, identifiability is decided by a local criterion. A new algorithm based on integer arithmetic enables an a priori local identifiability analysis to be performed for networks of arbitrary size. All algorithms have been implemented and flux identifiability is investigated for the network of the central metabolic pathways of a microorganism. Moreover, several small examples are worked out to illustrate the influence of input metabolite labeling and the paradox of information loss due to network simplification.
We used metabolic control analysis to determine the flux control coefficient of phosphorylase on glycogen synthesis in hepatocytes by titration with a specific phosphorylase inhibitor (CP-91149) or by expression of muscle phosphorylase using recombinant adenovirus. The muscle isoform was used because it is catalytically active in the b-state. CP-91149 inactivated phosphorylase with sequential activation of glycogen synthase. It increased glycogen synthesis by 7-fold at 5 mm glucose and by 2-fold at 20 mm glucose with a decrease in the concentration of glucose causing half-maximal rate (S(0.5)) from 26 to 19 mm. Muscle phosphorylase was expressed in hepatocytes mainly in the b-state. Low levels of phosphorylase expression inhibited glycogen synthesis by 50%, with little further inhibition at higher enzyme expression, and caused inactivation of glycogen synthase that was reversed by CP-91149. At endogenous activity, phosphorylase has a very high (greater than unity) negative control coefficient on glycogen synthesis, regardless of whether it is determined by enzyme inactivation or overexpression. This high control is attenuated by glucokinase overexpression, indicating dependence on other enzymes with high control. The high control coefficient of phosphorylase on glycogen synthesis affirms that phosphorylase is a strong candidate target for controlling hyperglycemia in type 2 diabetes in both the absorptive and postabsorptive states.