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Biotechnology and bioengineering

Metabolomics for biotransformations: Intracellular redox cofactor analysis and enzyme kinetics offer insight into whole cell processes.


PMID 19489025

Abstract

For redox reactions catalyzed by microbial cells the analysis of involved cofactors is of special interest since the availability of cofactors such as NADH or NADPH is often limiting and crucial for the biotransformation efficiency. The measurement of these cofactors has usually been carried out using spectrophotometric cycling assays. Today LC-MS/MS methods have become a valuable tool for the identification and quantification of intracellular metabolites. This technology has been adapted to measure all four nicotinamide cofactors (NAD, NADP, NADH, and NADPH) during a whole cell biotransformation process catalyzed by recombinant Escherichia coli cells. The cells overexpressing an alcohol dehydrogenase from Lactobacillus brevis were used for the reduction of methyl acetoacetate (MAA) with substrate-coupled cofactor regeneration by oxidation of 2-propanol. To test the reliability of the measurement the data were evaluated using a process model. This model was derived using the measured concentrations of reactants and cofactors for initiation as well as the kinetic constants from in vitro measurements of the isolated enzyme. This model proves to be highly effective in the process development for a whole cell redox biotransformation in predicting both the right concentrations of cofactors and reactants in a batch and in a CSTR process as well as the right in vivo expression level of the enzyme. Moreover, a sensitivity analysis identifies the cofactor regeneration reaction as the limiting step in case for the reduction of MAA to the corresponding product (R)-methyl 3-hydroxybutyrate. Using the combination of in vitro enzyme kinetic measurements, measurements of cofactors and reactants and an adequate model initiated by intracellular concentrations of all involved reactants and cofactors the whole cell biotransformation process can be understood quantitatively.