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Background: To understand the dynamic behavior of cellular systems, mathematical modeling is often necessary and comprises three steps: (1) experimental measurement of participating molecules, (2) assignment of rate laws to each reaction, and (3) parameter calibration with respect to the measurements. In each of these steps the modeler is confronted with a plethora of alternative approaches, e. g., the selection of approximative rate laws in step two as specific equations are often unknown, or the choice of an estimation procedure with its specific settings in step three. This overall process with its numerous choices and the mutual influence between them makes it hard to single out the best modeling approach for a given problem.

The intracellular concentrations of the valine and leucine pathway intermediates in a Corynebacterium glutamicum strain were measured during a transient state. The data were obtained by performing a glucose stimulus-response experiment with the use of a rapid sampling device and advanced mass spectrometry. The glucose stimulus resulted in a 3-fold increase in the intracellular pyruvate concentration within less than a second, demonstrating the very fast interactions in metabolic networks. The samples were taken at subsecond intervals for a time period of 25 s. The time courses of the metabolite concentrations formed the experimental basis of a mathematical model simulating the fluxes and concentrations in the valine/leucine pathway. The implementation of a model selection criterion based on the second law of thermodynamics is demonstrated to be essential for the identification of realistic and unique models. Large differences between the enzyme properties determined in vitro and those determined in vivo by the model were observed with the in vivo maximal rates being almost an order of magnitude larger than the in vitro maximal rates. The transamination of ketoisovalerate (KIV) to valine is carried out mainly by the transaminase B enzyme, with the transaminase C enzyme playing a minor role. The availability of the cofactors NADP and NADPH only has modest influence on the flux through the valine pathway, while the influence of NAD and NADH on the flux through the leucine pathway is negligible.

Microbial bioproduction of the aromatic acid anthranilate (ortho-aminobenzoate) has the potential to replace its current, environmentally demanding production process. The host organism employed for such a process needs to fulfil certain demands to achieve industrially relevant product levels. As anthranilate is toxic for microorganisms, the use of particularly robust production hosts can overcome issues from product inhibition. The microorganisms Corynebacterium glutamicum and Pseudomonas putida are known for high tolerance towards a variety of chemicals and could serve as promising platform strains. In this study, the resistance of both wild-type strains towards anthranilate was assessed. To further enhance their native tolerance, adaptive laboratory evolution (ALE) was applied. Sequential batch fermentation processes were developed, adapted to the cultivation demands for C. glutamicum and P. putida, to enable long-term cultivation in the presence of anthranilate. Isolation and analysis of single mutants revealed phenotypes with improved growth behaviour in the presence of anthranilate for both strains. The characterization and improvement of both potential hosts provide an important basis for further process optimization and will aid the establishment of an industrially competitive method for microbial synthesis of anthranilate.

The enzyme targets for the rational optimization of a Corynebacterium glutamicum strain constructed for valine production are identified by analyzing the control of flux in the valine/leucine pathway. The control analysis is based on measurements of the intracellular metabolite concentrations and on a kinetic model of the reactions in the investigated pathway. Data-driven and model-based methods are used and evaluated against each other. The approach taken gives a quantitative evaluation of the flux control and it is demonstrated how the understanding of flux control is used to reach specific recommendations for strain optimization. The flux control coefficients (FCCs) with respect to the valine excretion rate were calculated, and it was found that the control is distributed mainly between the acetohydroxyacid synthase enzyme (FCC = 0.32), the branched chain amino acid transaminase (FCC = 0.27), and the exporting translocase (FCC = 0.43). The availability of the precursor pyruvate has substantial influence on the valine flux, whereas the cometabolites are less important as demonstrated by the calculation of the respective response coefficients. The model is further used to make in-silico predictions of the change in valine flux following a change in enzyme level. A doubling of the enzyme level of valine translocase will result in an increase in valine flux of 31%. By optimizing the enzyme levels with respect to valine flux it was found that the valine flux can be increased by a factor 2.5 when the optimal enzyme levels are implemented.