A stepwise approach for the reproducible optimization of PAMO expression in Escherichia coli for whole-cell biocatalysis

Background: Baeyer-Villiger monooxygenases (BVMOs) represent a group of enzymes of considerable biotechnological relevance as illustrated by their growing use as biocatalyst in a variety of synthetic applications. However, due to their increased use the reproducible expression of BVMOs and other biotechnologically relevant enzymes has become a pressing matter while knowledge about the factors governing their reproducible expression is scattered. Results: Here, we have used phenylacetone monooxygenase (PAMO) from Thermobifida fusca, a prototype Type I BVMO, as a model enzyme to develop a stepwise strategy to optimize the biotransformation performance of recombinant E. coli expressing PAMO in 96-well microtiter plates in a reproducible fashion. Using this system, the best expression conditions of PAMO were investigated first, including different host strains, temperature as well as time and induction period for PAMO expression. This optimized system was used next to improve biotransformation conditions, the PAMO-catalyzed conversion of phenylacetone, by evaluating the best electron donor, substrate concentration, and the temperature and length of biotransformation. Combining all optimized parameters resulted in a more than four-fold enhancement of the biocatalytic performance and, importantly, this was highly reproducible as indicated by the relative standard deviation of 1% for non-washed cells and 3% for washed cells. Furthermore, the optimized procedure was successfully adapted for activity-based mutant screening. Conclusions: Our optimized procedure, which provides a comprehensive overview of the key factors influencing the reproducible expression and performance of a biocatalyst, is expected to form a rational basis for the optimization of miniaturized biotransformations and for the design of novel activity-based screening procedures suitable for BVMOs and other NAD(P)H-dependent enzymes as well.