Experimental analysis and genetic modifications of the bacterial metabolism (Team Bettenbrock)

Biological systems are complex by nature. Even a simple model organism such as the bacterium Escherichia coli are made up of a large number of molecules ranging from simple metabolites to proteins, RNA and DNA. The molecules interact in complex ways to ensure survival and replication under varying conditions. The team of Katja Bettenbrock aims to achieve a holistic and quantitative understanding of these interactions by combining experimental biological research with mathematical modeling and computational methods.

Experimental techniques routinely used in our lab include:

Genetic modifications: Defined genetic modifications are introduced into our model organisms using various genetic and molecular methods. We mainly use recombineering to delete or insert genes into the genome. In addtion, CRISPR-based methods are used e.g. for the introduction of (point) mutations. Heterologous genes are introduced either by plasmid vectors or by integratiion into the genome of the respective host. To achieve controlled gene expression, we use a variety of different sytems, ranging from the well-established lac system to optogenetic tools and CRISPRi.

Cultivation: To characterize strains we perform well-controlled growth assays ranging from shake flasks to batch, fed-batch or continuous cultication in bioreactors. One focus is to vary between aerobic, microaerobic and anaerobic growth conditions. Medium composition is varied according to the specific project.

Analytics: To obtain a holistic view of the physiology of investigated cells, we combine a variety of different analytical methods. We use HPLC, HPLC-MS or enzymatic assays to quantify the uptake of growth substrates, to quantify the different products and to analyze the concentrations of selected intracellular metabolites. In addition, we use real-time PCR or NGS methods to analyse RNA levels in our strains or use reporter genes to analyse gene expression of selected genes. Where appropiate, we also analyze protein levels, activity or modifications.

We apply these techniques in different research projects including:

1) Understanding bacterial metabolism and regulation
Due to their small size and their lifestyle bacteria are subjected to rapid and drastic changes in their environment. To cope with this, each cell must monitor its environment and respond in an appropriate way. This is achieved through a complex network of sensors and regulatory systems. Regulatory systems control gene expression and thereby tune catabolic and anabolic metabolic pathways in catabolism as well as in anabolism. In addition, metabolism is influenced by the control of enzyme activities through modification or allosteric control. A deep understanding of bacterial metabolism and its regulation is vital for engineering bacteria for biotechnological applications. We are therefore investigating the influence of regulatory systems on metabolism under different external conditions in the model bacterium E. coli. A major goal is to use this understanding for the targeted modification of metabolism and regulation in the construction of production strains.

2) Engineering Zymomonas mobilis as workhorse for biotechnological applications
The bacterium Zymomonas mobilis is characterised by a particularly high glucose uptake rate and a high glycolytic flux compared to most other microorganisms. In addition, the glucose taken up by Z. mobilis is almost completely converted into its main fermentation product, ethanol. These characteristics make Z. mobilis a promising workhorse for biotechnology applications. Genetic engineering for targeted modification of the Z. mobilis genome is possible but efficient tools are not yet available. We are developing a genetic toolbox for efficient genetic engineering of Z. mobilis. This toolbox includes various plasmid vectors, different promoter elements for controlled gene expression, a set of ribosome binding sites, as well as tools for genome integration and gene knock out. We use this toolbox to engineer Z. mobilis for the production of other products than ethanol. Model-based analysis predicts promising modifications which are tested in our lab. In addtion, we are aiming to a better understanding of more general aspects of Z. mobilis physiology such as the function and role of its respiratory chain, the mechanisms underlying the uncoupled growth phenotype and ATP metabolism.

3) Dynamic Process Optimization in Biotechnology
The application of biological processes in the production of building blocks is becoming increasingly important. In order to replace petrochemicals, the biological production processes must become more efficient and cheaper. Often the synthesis of the desired product is hampered by slow growth of the cells, reduced substrate uptake rates and/or by the use of the compounds as building blocks for the cells themselves. In order to overcome this obstacle, the application of dynamic process control strategies is promising. In addition to the control of external parameters, also the control of intracellular parameters such as gene expression and protein activity is required. In this project, different targets and strategies for the control of intracellular parameters is evaluated. Most importantly, gene expression systems need to be designed, to allow fine-tuning of gene expression during the production process. Optogenetic tools are suitable for these applications but other tools are also being investigated in our group.

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.