Targeting population heterogeneity at microscale for robust fermentation processes 
Acronym: POPCORN

Project coordinator

- Dr. Anna Eliasson Lantz – Technical University of Denmark - Denmark

Project leaders

- Prof. Søren  Sørensen – University of Copenhagen – Denmark

- Prof. Jan-Dirk van Elsas – University of Groningen – The Netherlands

- Dr. Ingmar Nopens – Ghent University – Belgium

- Mr. Peter Jensen – Fermenco ApS – Denmark


The overall objective of the proposed project is to establish a platform for more robust fermentation processes and production organism by understanding and controlling heterogeneity. It is essential to optimise fermentation parameters for achieving the most efficient production process. In most research projects on this topic, the microorganism population was considered homogeneous. However, research has shown that a typical population of microorganisms in a fermentation is heterogeneous. Due to continued technological developments in different fields, for example in genetics and molecular biology (reporter systems), flow cytometry and microfluidics (micro-bioreactors), we have now finally reached a phase where the investigation of the effect of cultivation parameters on the heterogeneity of a microorganism population has become possible, and this is precisely what will be done in this project. The central project hypothesis is that there exists an optimum level of heterogeneity leading to a robust fermentation process with sustained high productivity. To investigate this hypothesis, reporter systems for cell growth and productivity will be constructed for industrially relevant model organisms, which will allow to obtain a distribution of these properties for the population, e.g. by using flow cytometry. The effect of cultivation parameters on these properties will be investigated via. Both physiological adaptation to the signals it perceives in the culture, and genetic change allowing selection of optimally adapted forms to conditions in the culture will be researched. Experimental results at microscale will be extrapolated to labscale and pilotscale. This extrapolation will be supported by development of mathematical models, combining computational fluid dynamics with population balance models. In addition to methods for determining the level of heterogeneity both, other outcomes will be: knowledge to obtain more robust strains for biological production, which are more stress tolerant in a production setting; advanced micro-bioreactors and models able to simulate population behavior in large-scale fermenters.