Joachim von Wulffen


Julia Lischke

Project Overview

Large-scale production processes (>10.000 L) in ‘white’ biotechnology are the typical result of optimization strategies following the economy-of-scale principle. In contrast, the development and optimization of production strains and processes is performed in lab-scale fermenters (1–100 L). As a consequence of this scale-up cells experience substrate and oxygen gradients while travelling through the different zones of the reactor causing a large number of underperformances indicating reductions of growth rates, biomass/substrate yields, product titers and productivity in production scale. It is the goal of the project to address the urgent scale-up problem by profound systems biology studies using E. coli as a relevant model strain. Multi-scale systems biology analysis will be performed focusing on the interplay of substrate-gradient based stimuli and the dynamic metabolic and transcriptional response in the cells. Significant metabolites will be measured in scaled-down experiments simulating the gradients of the substantial substrates carbon, nitrogen and oxygen in a reactor coupled with a plug-flow device. Quantitative transcript data, based on next generation sequencing will be gathered using diverse E. coli strains for setting-up data driven metabolic dynamic models. Based on model predictions novel scale-up criteria e.g. taking into account sensitive regulatory relaxation times of the strains will be derived.


  • von Wulffen, J., RecogNice-Team, Sawodny, O., & Feuer, R. (2016). Transition of an Anaerobic Escherichia coli Culture to Aerobiosis: Balancing mRNA and Protein Levels in a Demand-Directed Dynamic Flux Balance Analysis. PloS One, 11(7), e0158711. doi: 10.1371/journal.pone.0158711
  • von Wulffen, J., Buchholz, P., Sawodny, O., & Feuer, R. (2015). Modeling the metabolism of escherichia coli under oxygen gradients with dynamically changing flux bounds. In 2015 IEEE 15th International Conference on Bioinformatics and Bioengineering (BIBE) (pp. 1–6). IEEE. doi: 10.1109/BIBE.2015.7367691


The project is funded by the BMBF.