Examination of the process behavior of productive biofilms

• Applicants: Professor Dr. Roland Ulber; Dr. Andreas Wirsen, since 4/2016
• Subject Area: Biological Process Engineering
• Term: from 2016 to 2020
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 290361961

The scope of this project is a better understanding of productive biofilm processes in terms of product yield. Therefore, flow cells need to be designed and developed so that they allow FRAP online measurements on biofilms. These measurements finally contribute to the identification and validation of a mathematical model for productive biofilms in flow cells. The model intends to describe the dependence of biofilm productivity and supplied nutrients over time. For this reason the models core is a reaction-diffusion system of equations describing the mass transfer of nutrients and products both between media and biofilm on the outer layer of the biofilm and the transport and metabolism within the biofilm over time. Unknown (possibly time-dependent) parameters such as diffusion coefficients and reaction rates will be determined through the evaluation of online measured data with help of mathematical methods for parameter identification respective estimations. Apart from pH measurements primarily confocal laser scanning microscopy (CLSM) will provide the needed data. Using CLSM both the biofilm density and the diffusion coefficients are determined at certain intervals. The latter is done by a two-dimensional variant of the fluorescence recovery after photobleaching (FRAP), which will also be further developed in this project. Nevertheless, to enable this online on intransparent substrata, existing flow cells have to be adapted adequately. Reaction rates (uptake rates of nutrients and release rates of the product) cannot be measured directly and must therefore be calculated using mathematical methods. After all, the mathematical model created can in future be used as a basis for improved cultivation of biofilms as well as online monitoring during the production phase.

• DFG Programme: Research Grants
• Ehemaliger Antragsteller: Dr. Patrick Lang, until 3/2016