# Microbiological Follow-Up of Bioreactor-Assisted Must Alcoholic Fermentation by Flow Cytometry
## 4 Discussion  
In the present work we used FCM to examine the growth dynamics of SC in the bioreactor-assisted fermentation of a _Chasselas_ must. The temperature and pressure were kept constant for the duration of the experiment, trying to mimic the conditions typically used in the cell. The FCM data precisely illustrated the classical kinetics of must fermentation, and this was observed in terms of both the percentages and the absolute counts. The agitation in the bioreactor maintained a homogeneous yeast suspension, and this represents ideal conditions for a consistent sampling and downstream FCM analysis. However, the fermenting must is not usually subject to continuous stirring and future experimentation should take this aspect under consideration--for example by stirring only a few minutes before sampling--to avoid any unwanted effects of long-term agitation. It is important to underline that in this study, the FCM results--both counts and percentages--were obtained in a very short time. In fact, it took only half an hour from must sampling to the final acquisition at the analyser, including the transportation of the sample to the laboratory. Indeed, FCM can represent a quasi-online analytical tool. As such,  
Figure 6: Unsupervised analysis and exemplative t-SNE and 2D plots from day 7. **(A)** All FCS files are concatenated in a single file for t-SNE analysis. The results from day 7 are further displayed (see events in the “Identifier” gate). **(B)** Scatter dot plot. **(C)** Dot plot identifying live, dead and damaged cells by CFDA-PI staining. **(D)** The t-SNE transformation plot. Note that the main populations from **(C)** are easily identifiable in the t-SNE plot: blue cluster = live cells, red cluster = dead cells and green cluster = damaged cells. **(E)** The t-SNE plot and gating of two subclusters. **(F–I)** The CFDA-PI and scatter profiles of cells within gates 1 and 2.  
we also applied a method that did not include centrifugation or filtration steps, to keep the sample as pristine as possible and to save time. The choice of a 1:20 dilution was made in the first staining trials at the beginning of fermentation and proved to be effective for FCM acquisition, in order to avoid doublet formation or clumping, as revealed by the SSC-Area (SSC-A) versus SSC-Height (SSC-H) dot plot for doublet discrimination (data not shown). We also applied two protocols that have been widely used in microbiology as well as in oncology. The first protocol contained SYBR Green, a stoichiometric DNA-specific dye applied in oenology to study yeast cell cycle [14]. The second protocol contained a fluorescein derivative, CFDA-AM. Such derivatives have been widely used in FCM to follow both alcoholic and malalactic fermentation [8; 10; 13; 15]. We chose to use CFDA-AM because it can be loaded in the cell at lower concentrations compared to those used with the other derivatives, as the AM group makes the dye more cell permeable. Overlapping yeast growth kinetics in the bioreactor were appreciated in both the SYBR-PI and the CFDA-PI protocols, and this was true for both cell counts and percentages. The results from the method comparison suggested that the two methods are generally in agreement, as almost all the measurements were within the LoA with acceptable bias values. The biggest differences were found when analysing the cell concentrations. However, they did not affect the overall kinetics. Thus, the two methods can be used interchangeably with respect to the experimental design. For future analyses, one possibility could be merging the two methods, changing the type of DNA dye regarding the fluorescence excitation/emission profile. Such configuration would provide a particular benefit in high-background samples, in which DNA dye could help in extracting the specific signal from the background for proper CFDA analysis.