Transport Phenomena in Biofilms
Biofilms provide interesting applications, e.g., as biocatalysts in the field of industrial biotechnology. The high robustness of the cells towards non-physiological conditions and the fact that the immobilizing compounds are produced by the cells themselves, spares the addition of an activity affecting artificial hazardous compound for the immobilization procedure . However, the robustness of biofilms is detrimental if they occur on medical devices like implants, catheters, and/or membranes. The efficiency of biocatalytic processes is strongly correlated with the mass transfer of substrates as well as products to avoid a limitation of the reaction. Therefore, a deeper knowledge of substrate transfer, consumption, generation of the product, and mass transfer of products is required to enable an economic application of biofilms for production of bulk and fine chemicals. Furthermore, the dynamics of the biomass are of interest for the description of the process. The mentioned characteristics are as well of interest with respect to baneful biofilms on medical devices, since the models for mass transfer and cell mobility/growth can also be exploited to derive conditions to reduce growth and metabolism of such “negative” biofilms.
A common procedure for determination of mass transfer in biofilms is to combine fluorescence recovery after photobleaching (done with a confocal laser scanning microscope) with balancing equations. However, the commonly applied approaches reduce the mass transfer to two-dimensional diffusion and furthermore they do not consider the mobility and growth of the cells in the biofilm matrix. In our project we want to establish novel more appropriate models for description of mass transfer in biofilms which actually include the biomass dynamics. They rely on reaction-diffusion-transport equations for the cell population density, the substrate and the product concentrations, possibly coupled with mass kinetics for processes on the (sub-)cellular level. The outcome are multiscale PDE-ODE settings. Moreover, stochastic model concepts are developed and validated with experimental data, allowing to correspondingly adapt the mathematical settings. At the same time the mathematical modelling can also suggest new experimental approaches.