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

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.