Impact of mixing imperfections on yeast bioreactor performances: Scale-down reactor concept and related experimental tools

Abstract

A method combining environmental data extracted from the dissolved oxygen profile of a fed-batch bioreactor and a dynamic discrete Markov chain model has been presented in order to give more insight about the glucose and dissolved oxygen fluctuations experienced by the microorganisms during cultivation in heterogeneous bioreactor. The fed-batch cultivation of Saccharomyces cerevisiae has been performed in a well-mixed and a partitioned scale-down reactor (SDR). The analysis of the environmental sequences has shown extended time lengths for the glucose availability and depletion sequences in the case of the SDR under a DO-controlled fed-batch culture. The Markov chain model developed in this work is able to capture the stochastic environmental events, i.e. in our case the environmental states experienced by the microorganisms crossing the tubular part of the SDR. The simulation results show clearly an extension of the starvation periods in the case of the culture performed in the SDR. The simulations have been performed at the single cells level allowing future improvements of our model and notably in the context of the population segregation phenomena occurring in fed-batch cultures. As a perspective, flow cytometry has been presented as a high-throughput analytical tool for the investigation of yeast physiology at the single cell level and in process-related conditions.