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This paper examines the validity of the linlog approach, which was recently developed in our laboratory, by comparison of two different kinetic models for the metabolic network of Escherichia coli. The first model is a complete mechanistic model; the second is an approximative model in which linlog kinetics are applied. The parameters of the linlog model (elasticities) are derived from the mechanistic model. Three different optimization cases are examined. In all cases, the objective is to calculate the enzyme levels that maximize a certain flux while keeping the total amount of enzyme constant and preventing large changes of metabolite concentrations. For an average variation of metabolite levels of 10% and individual changes of a factor 2, the predicted enzyme levels, metabolite concentrations and fluxes of both models are highly similar. This similarity holds for changes in enzyme level of a factor 4-6 and for changes in fluxes up to a factor 6. In all three cases, the predicted optimal enzyme levels could neither have been found by intuition-based approaches, nor on basis of flux control coefficients. This demonstrates that kinetic models are essential tools in Metabolic Engineering. In this respect, the linlog approach is a valuable extension of MCA, since it allows construction of kinetic models, based on MCA parameters, that can be used for constrained optimization problems and are valid for large changes of metabolite and enzyme levels.

The majority of dynamic gene regulatory network (GRN) models are comprised of only a few genes and do not take multiple transcription regulation into account. The models are conceived in this way in order to minimize the number of kinetic parameters. In this paper, we propose a new approach for predicting kinetic parameters from DNA-binding site sequences by correlating the protein–DNA-binding affinities with nucleotide sequence conservation. We present the dynamic modeling of the cra modulon transcription in Escherichia coli during glucose-limited fed-batch cultivation. The concentration of the Cra regulator protein inhibitor, fructose 1,6-bis(phosphate), decreases sharply, eventually leading to the repression of transcription. Total RNA concentration data indicate a strong regulation of transcription through the availability of RNA polymerase. A critical assessment of the results of the model simulations supports this finding. This new approach for the prediction of transcription dynamics may improve the metabolic engineering of gene regulation processes.

The present work is the first to deal with the determination of cholesterol synthesis rates in primary rat hepatocytes using transient (13)C-flux analysis. The effects of statins on cholesterol biosynthesis and central carbon fluxes were quantified at a therapeutic concentration of 50 nM atorvastatin using carbon-labeled glutamine. The flux through the cholesterol pathway decreased from 0.27 to 0.08 mmol/l(cv)h in response to the administration of the hypolipidemic drug. Isotopic steady state was reached within 4h in the central carbon metabolism but not in the cholesterol pathway, regardless of whether atorvastatin was administered or not. Marked channeling was observed for the symmetrical tricarboxylic acid cycle intermediates, succinate and fumarate. Non-stationary (13)C-based flux identification delivers both intracellular fluxes and intermediate levels, which was for the first time utilized for investigating systems-level effects of the administered drug by quantifying the flux control of the 3-hydroxy-3-methylglutaryl-coenzyme A reductase.

The presumably high potential of a holistic design approach for complex biochemical reaction networks is exemplified here for the network of tryptophan biosynthesis from glucose, a system whose components have been investigated thoroughly before. A dynamic model that combines the behavior of the trp operon gene expression with the metabolic network of central carbon metabolism and tryptophan biosynthesis is investigated. This model is analyzed in terms of metabolic fluxes, metabolic control, and nonlinear optimization. We compare two models for a wild-type strain and another model for a tryptophan producer. An integrated optimization of the whole network leads to a significant increase in tryptophan production rate for all systems under study. This enhancement is well above the increase that can be achieved by an optimization of subsystems. A constant ratio of control coefficients on tryptophan synthesis rate has been identified for the models regarding or disregarding trp operon expression. Although we found some examples where flux control coefficients even contradict the trends of enzyme activity changes in an optimized profile, flux control can be used as an indication for enzymes that have to be taken into account in optimization.

This work focuses on the phosphofructokinase-2-system dynamics in Saccharomyces cerevisiae, in vivo. The investigations were dedicated to the development and implementation of appropriate theoretical and experimental methods toward evaluation of a quantitative strategy for the characterization of systemic mechanisms involved in the cAMP/protein kinase-A/phosphofructokinase-2 signal transduction cascade in yeast. Upon glucose pulse experiments, applied to glucose-limited continuous cultures of S. cerevisiae, the system response was determined with respect to alterations of intracellular metabolite concentrations or in vivo enzyme activities. Phosphofructokinase-2, in vivo, was found to be saturated with respect to both its substrates, F6P and ATP. This restriction results in an uncoupling of the enzyme activity and the signal transduction cascade from glycolytic flux, concluding that activation of phosphofructokinase-2 is exclusively a result of phosphorylation by protein kinase-A, which in turn is activated by increasing intracellular cAMP concentration after an extracellular glucose pulse. Signal processing from cAMP versus phosphofructokinase-2 also displays peculiar features implicated in a hysteresis behavior: when increasing cAMP concentration achieves a certain critical value, protein kinase-A switches into an active state. Posterior to this activation, the signal transform maintains autonomy and functional independence of further alterations of the intracellular cAMP concentration. Our observations, finally, allow the establishment of a representative model for the description of the signal transduction process via protein kinase-A in yeast.

A novel approach to construct kinetic models of metabolic pathways, to be used in metabolic engineering, is presented: the tendency modeling approach. This approach greatly facilitates the construction of these models and can easily be applied to complex metabolic networks. The resulting models contain a minimal number of parameters; identification of their values is straightforward. Use of in vitro obtained information in the identification of the kinetic equations is minimized. The tendency modeling approach has been used to derive a dynamic model of primary metabolism for aerobic growth of Saccharomyces cerevisiae on glucose, in which compartmentation is included. Simulation results obtained with the derived model are satisfying for most of the carbon metabolites that have been measured. Compared to a more detailed model, the simulations of our model are less accurate, but taking into account the much smaller number of kinetic parameters (35 instead of 84), the tendency the modeling approach is considered promising.

The in vivo dynamics of the pentose phosphate pathway has been studied with transient experiments in continuous culture of Saccaromyces cerevisiae . Rapid sampling was performed with a special sampling device after disturbing the steady state with a pulse of glucose. The time span of observation was 120 s after the pulse. During this short time period the dynamic effect of protein biosynthesis can be neglected. The metabolites of interest (glu- cose 6-phosphate, NADP, NADPH, 6-phosphogluconate, and MgATP 2− ) we determined with enzymatic assays and HPLC. The experimental observations were then used for the identification of kinetic rate equations and parameters under in vivo conditions. In accordance with results from in vitro studies the in vivo diagnosis supports an ordered Bi-Bi mechanism with noncompetitive inhibition by MgATP 2− for the enzyme glucose-6-phosphate dehydrogenase. In the case of 6-phosphogluconate dehydrogenase an ordered Bi-Ter mechanism with a competitive inhibition by MgATP 2− has been found. Because the MgATP 2− concentration decreases abruptly after the pulse of glucose the inhibitory effect vanishes and the flux through the pentose phosphate pathway increases. This regulation phenomenon guarantees the balance of fluxes through glycolysis and pentose phosphate pathway during the dynamic time period.