Model of central and trimethylammonium metabolism for optimizing L-carnitine production by E. coli.

The application of metabolic engineering principles to the rational design of microbial production processes crucially depends on the ability to make quantitative descriptions of the systemic ability of the central carbon metabolism to redirect fluxes to the product-forming pathways. The aim of this work was to further our understanding of the steps controlling the biotransformation of trimethylammonium compounds into L-carnitine by Escherichia coli. Despite the importance of L-carnitine production processes, development of a model of the central carbon metabolism linked to the secondary carnitine metabolism of E. coli has been severely hampered by the lack of stoichiometric information on the metabolic reactions taking place in the carnitine metabolism. Here we present the design and experimental validation of a model which, for the first time, links the carnitine metabolism with the reactions of glycolysis, the tricarboxylic acid cycle and the pentose-phosphate pathway. The results demonstrate a need for a high production rate of ATP to be devoted to the biotransformation process. The results demonstrate that ATP is used up in a futile cycle, since both trimethylammonium compound carriers CaiT and ProU operate simultaneously. To improve the biotransformation process, resting processes as well as CaiT or ProU knock out mutants would yield a more efficient system for producing L-carnitine from crotonobetaine or D-carnitine.

Metabolic design based on a coupled gene expression-metabolic network model of tryptophan production in Escherichia coli.

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.

Optimal re-design of primary metabolism in Escherichia coli using linlog kinetics.

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.

Dynamic modeling of the central carbon metabolism of Escherichia coli.

Application of metabolic engineering principles to the rational design of microbial production processes crucially depends on the ability to describe quantitatively the systemic behavior of the central carbon metabolism to redirect carbon fluxes to the product-forming pathways. Despite the importance for several production processes, development of an essential dynamic model for central carbon metabolism of Escherichia coli has been severely hampered by the current lack of kinetic information on the dynamics of the metabolic reactions. Here we present the design and experimental validation of such a dynamic model, which, for the first time, links the sugar transport system (i.e., phosphotransferase system [PTS]) with the reactions of glycolysis and the pentose-phosphate pathway. Experimental observations of intracellular concentrations of metabolites and cometabolites at transient conditions are used to validate the structure of the model and to estimate the kinetic parameters. Further analysis of the detailed characteristics of the system offers the possibility of studying important questions regarding the stability and control of metabolic fluxes.