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B8 Metabolic process analysis and optimization of bacterial cultivations (Bacillus megaterium)

(Franco-Lara)

The new project B8 (Franco-Lara) focuses on the Bacillus megaterium cultivations especially regarding the in vivo control mechanisms of metabolic fluxes. In close cooperation with project B5 (Deckwer; Interim management: Hempel/Jahn/Franco-Lara), the main topic of the project is the analysis of the bacterial metabolism and its posterior utilization for protein production optimization.
The aim of project B8 is to estimate intracellular concentrations of intracellular metabolites and to elucidate the essential metabolic pathways (metabolic profiling) in Bacillus megaterium. This will allow a quantitative understanding of microbial growth, and production processes. Because intracellular intermediates (metabolites) have a regulatory effect on metabolism, the analysis of changes in their concentration and fluxes may help to identify possible bottle-necks (in expression of a desired protein) at the production or secretion level.

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In cooperation with project B6 (Zeng) potential metabolic networks reconstructed from annotated genome data will be integrated to experimental measurements at the extra cellular level and used to evaluate metabolic resources management. Exemplified at the production of recombinant biocatalysts (project A1 Jahn and project A3, Buchholz/Hofer), the experience and developed methods will be transferred to the production and analysis of recombinant antibodies (project A6, Dübel).
The major goal of the new project B8 (Franco-Lara) is to reach an optimal cost-benefit ratio by using modern control strategies with regard to several process parameters such as temperature, pH-value, time point of induction and feeding strategies. One challenge of this optimization is to achieve the maximum possible production levels of secreted product (heterologous or native protein) by appropriate process controlling. A major barrier to achieve this is the existence of competing components in the production pathway. For example, the enhancement of productivity stables a problem to the optimized growth conditions of the microorganism since both, product and cell, struggle for the same primary resources (intracellular metabolites). In such cases there is no a single optimal solution, but instead a set of efficient solutions (tradeoffs) must be employed. This multi-criterion optimization problem can be overcome by conducting well-planed experiments with varying process parameters. In order to find the best solution for the problem in a cost and time effective manner, model-based methods will be used to reduce the experimental effort.


Main objectives:

  • Characterization of in vivo kinetics
  • Metabolic flux analysis under induction stress
  • Elementary Flux Modes
  • Estimation of bacterial „trade-off“ behavior under induction stress
  • Model-based media formulation (ANNSGA = Artificial Neural Network Supported Genetic Algorithm)
  • Analysis of the influence of temperature and pH on bacterial growth and protein production
  • Development of alternative feed strategies for high cell density cultivation
  • Investigation of the influence of induction time and inductor concentration on protein production


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