Bioprocess optimization
While the first three research areas focus on modeling, characterization and targeted optimization of the microbial metabolism at the molecular level , here we aim to optimize key performance measures (such as volumetric productivity) of bioprocesses at the process level. This includes adjustments of macroscopic process variables (such as medium composition, batch/fed-batch operation, multi-stage processes) or the use of external signals to dynamically modulate the cellular metabolism during the process. Here, we are also interested in optimizing production processes with cell-free enzyme cascades.

Design of two-stage bioprocesses
We are interested in the optimal design of two- or even multi-stage bioprocesses, for example, to separate growth and production phases to maximize the volumetric productivity. Particular aspects of our research include:

• OptMSP: toolbox to identify optimal multi-stage (batch) processes based on given characteristics of the different stages.
• Design of microbial factories for two-stage processes (e.g. how to maintain high metabolic activity during the production phase).
• Switching strategies: e.g. via external oxygen supply, nutrient limitation or/and dynamic metabolic engineering.
• Going beyond static metabolic interventions (such as gene kmockouts): genetic tools for dynamic metabolic engineering, e.g. oxygen-dependent promoters.

Conceptual developments for metabolic cybergentics
Even in dynamic metabolic engineering, the genetic switches follow often a simple on/off logic during the process (e.g., oxygen-dependent promoters induce gene expression if oxygen supply is switched off). The most general case would be to consider gradual increases/decreases of certain metabolic fluxes to maximize process performance. This requires concepts of metabolic cybergenetics, i.e. for optimal dynamic modulation of intracellular fluxes via external signals using mathematical modeling, optimization and computer-aided feedback control. We are developing such concepts with a focus on optogenetic modulation of the expression of metabolic enzymes where light serves as control input. The dynamic manipulation of ATP turnover in the cell to maximize productivity of lactate synthesis by E. coli serves as an application example.

Design and Optimization of Cell-free Production Systems
As an alternative for cell-based production systems, cell-free enzyme cascades are increasingly used for the synthesis of industrially relevant chemicals and biopharmaceuticals. However, implementing efficient enzyme cascades is non-trivial. In collaboration with the BPE group (Reichl, Rexer) we are using model-based strategies to analyze and optimze cell-free enzyme cascades for the production of nucleotide sugars. Important aspects of our research are:

• Use of kinetic models to describe and optimize cell-free enzyme cascades.
• Systematization and formalization of relevant optimization problems.
• Workflow for model-based optimization of enzyme cascades under structural and parametric uncertainty.
• Optimal fed-batch operation of enzyme cascades.
• Application: production of the nucleotide sugars GDP-fucose and UDP-GalNAc.
• Identification of metabolic modules with specified stoichiometric and thermodynamic constraints which can serve as cofactor regeneration modules for cell-free systems.