dc.description.abstract
This thesis deals with tools for optimization of biocatalytical transformations. The optimization of biocatalysis should be performed on different levels: on the catalyst level, on the fermentation/cultivation level, and on the process level as well as the downstream processing (DSP) level. All levels contribute to the enhancement of productivity and examples for their optimization are given in the following theses. In the first chapter, the optimization was performed on all the levels mentioned above. The development of a biocatalytic process on the multi-dozen gram scale for the synthesis of a precursor to Nylon-9, a specialty polyamide, was established. Such materials are growing in demand, but their corresponding monomers are often difficult to synthesize, giving rise to biocatalytic approaches. Here,the cyclopentadecanone monooxygenase as an Escherichia coli (E. coli) whole-cell biocatalyst was chosen as a catalytic entity and produced in a stable expressing system (biocatalyst level) in a defined medium, which was optimized prior to upscaling (cultivation level). Together with the implementation of a substrate feeding-product removal concept, an DSP was established (process/DSP level). A previously described hazardous peracid-mediated oxidation was thus replaced with a safe and scalable protocol, using aerial oxygen as oxidant and water as reaction solvent. The engineered process converted 42 g (0.28 mol) starting material ketone to the corresponding lactone with an isolated yield of 70 % (33 g), after highly efficient DSP with 95 % recovery of the converted material, translating to a volumetric yield of 8 g pure product per liter. Subsequently, the possibility of optimization on whole-cell biocatalyst level was investigated. A kinetic model for the simulation and optimization of an in vivo redox cascade in E. coli, using a combination of an alcohol dehydrogenase, an enoate reductase, and a Baeyer-Villiger monooxygenase (CHMO) for the synthesis of lactones was developed. The model was used to estimate the concentrations of active enzyme in the sequential biotransformations to identify bottlenecks together with their reasons and how to overcome them. The adapted Michaelis-Menten parameters from in vitro experiments with isolated enzymes were estimated, and these values were used to simulate the change in concentrations of intermediates and products during the in vivo cascade reactions. The model indicated the CHMO, the fastest enzyme, to be rate-determining due to the low concentration of the active form, opening up reversible reaction channels towards side products. Substantial experimental evidence was provided, that a low intracellular concentration of flavin and nicotinamide cofactors drastically throttled the performance of the in vivo cascade. As a next step, the performance of the CHMO in a whole-cell catalyst was investigated to obtain knowledge about its poor performance in vivo and to propose optimization strategies (catalyst level). The measurement of in vivo activity and stability of the CHMO in the recombinant host E. coli was performed. This enzyme was often described as poorly stable in vitro, and has recently been found to deactivate rapidly in the absence of its essential cofactors and of anti-oxidants. Additionally, it was identified as the rate limiting step of an enzymatic cascade in the previous chapter. Its stability in vivo was scarcely studied, so far. The activity and stability of CHMO in E. coli during common conditions for over-expression was measured, and the ability of the host to support these properties by metabolomics analyses was investigated. The results showed that E. coli failed to provide the intracellular levels of cofactors required to functionally stabilize CHMO, although the biocatalyst was produced in high concentration, and was invariably detectable after protein synthesis had stopped. Biotechnological applications in this host possibly relied on a residual activity of approx. 5 %. Other microorganisms might thus offer a more efficient solution for recombinant production of CHMO, and related enzymes. As the last optimization step on the catalyst and cultivation level, an in vivo characterization of dihydroxyacetone kinase (DhaK) expressed in E. coli was presented with regard to physiological and metabolical changes compared to E. coli wt strain. This enzyme can facilitate aldol reactions in vivo by increasing intracellular dihydroxyacetone phosphate (DHAP, aldol donor molecule) concentrations. The DhaK phosphorylates dihydroxyacetone (DHA) to DHAP by consuming ATP. Overall, despite the metabolic burden of plasmid maintenance and protein expression, the DhaK strain showed similar physiological behavior compared to the wt strain. In contrast to E. coli wt, the DhaK strain took up DHA during the exponential growth phase and showed higher intracellular concentrations of DHAP. Metabolomics analysis also indicated that the pool of ATP, which is needed for the enzymatic phosphorylation of DHA, was too low under non-growing conditions, so that the reaction could only proceed during exponential growth. Modeling both strains revealed the possibility of bypassing the upper glycolysis by expressing DhaK and feeding DHA, which needs to be investigated further with carbon source 13C labeling by dynamic metabolomics approaches. In summary, the presented system was modeled together with an aldol producing enzymatic cascade in E. coli and was found to be of benefit for DHAP-dependent aldol reactions in silico. The combination of the different levels of optimization applied in this theses - accompanied by the methods modeling, metabolomics and optimizational tools for reaction design - were successfully applied to facilitate biotransformations in living systems.
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