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B10 Systems biotechnology for production of glycosyltransferases with Bacillus megaterium

(Jahn/Franco-Lara)

The recombined production of model proteins in a bioreactor by Bacillus megaterium will be analysed by means of systems biology, modelled and optimised. Flux balance analyses (FBA) are used for predicting the metabolic potential of B. megaterium based on the clarified genome sequence, thus for specific application to the production of glycosyltranferases. In cooperation with subproject B9 (Münch/Schomburg) a bioinformatic approach for determining the respective regulatory network will be applied. Both models are used to predict cellular metabolic processes during protein production. Differential equations combined with neural network approaches, so-called soft sensors, are used for modelling and integration of mass and energy balances for intra- and extracellular process variables. Data for a protein-producing B. megaterium strain at the transcriptome, proteome and metabolome level will be collected by the use of state-of-the-art high-throughput technology to extract sufficient experimental data for validating the model predictions. Identified mRNAs, proteins and metabolites, which are important for the production process, are quantified through real-time PCR, ELISA and metabolomics. The parameters of process control under investigation include C-source, process temperature, oxygen supply and pH value. Existing databases and programmes as well as newly developed bioinformatics tools are used for storing and for automated processing and evaluation of the data. Networks for gene regulation and metabolism are deduced and compared to the predictions of the models. In this approach, the calculated and measured data is employed iteratively to improve the model approaches. Finally, limiting factors occurring during the recombined protein production are identified and used as a basis for specific optimisation.

 

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