Marielle Bouix
email: mariellebouix@orange.fr

Sarrah Ghorbal
email: sayfood.sarrah.ghorbal@agroparistech.fr

Daniel Picque
email: sayfood.daniel.picque@inrae.fr

Bruno Perret
email: sayfood.bruno.perret@inrae.fr

Claire Saulou-Berion
email: sayfood.claire.saulou-berion@inrae.fr

A rapid method for the assessment of the vitality of microorganisms using flow cytometry

Keywords: Bacteria, yeast, Physiological state, Cellular state, Vitality, Flow cytometry

Cultivability, viability and vitality make it possible to characterize the behavior of a cellular population. Vitality was assessed using the kinetic parameters of specific metabolisms depending on whether the strains were used, for example, for the acidification of lactic acid bacteria or for CO 2 production in fermenting yeasts. However, these methods are time-consuming. We developed a cytometric descriptor based on the energy-dependent extrusion of carboxyfluorescein from cells, subsequent to carboxyfluorescein diacetate staining, and compared it to the measurements of metabolic activities of various bacteria and yeasts. For all of the microorganisms tested, the cytometric descriptor FI 15 was well correlated with the results of the metabolic measurements and, moreover, has the

-INTRODUCTION

Some microorganisms are used in fermentation processes to produce various biomolecules such as organic acids, aldehydes and alcohols (white biotechnology). Lactic acid bacteria (LAB) and yeasts are widely used in fermented food products (e.g., dairy products, beverages, meats, vegetables).

Regardless of the process, the viability and the activity (also referred to as vitality or dynamics) of the microbial starters must be high in order to quickly colonize the raw materials and avoid the growth of indigenous contaminants. Poor vitality may lead to delays in industrial processes and defects in products.

Cultivability, viability and vitality are three different descriptors that make it possible to characterize the behavior of microorganisms. Cultivability, the best-known property used by microbiologists, is defined as the ability of the cells to reproduce and form colonies on plate agar medium. Viability is defined by membrane integrity, protein synthesis and the energy production necessary to maintain cells (1). Hence, among a viable cell population, there are cultivable as well as non-cultivable cells that remain alive with intact membranes and potential metabolic activity [START_REF] Breeuwer | Characterization of uptake and hydrolysis of fluorescein diacetate and carboxyfluorescein diacetate by intracellular esterases in Saccharomyces cerevisiae, which result in accumulation of fluorescent product[END_REF][START_REF] Quiros | Application of Flow Cytometry to Segregated Kinetic Modeling Based on the Physiological States of Microorganisms[END_REF]. Vitality is defined by the energy yielding capabilities of cells [START_REF] Dinsdale | Yeast vitality during cider fermentation: assessment by energy metabolism[END_REF], by the dynamic behavior of a culture, or by the kinetic parameters of cells including the specific growth rate, the specific metabolite production rate or the specific substrate uptake rate.

In a microbial population, cultivable cells as well as dead cells and viable but non-cultivable cells may be present at the same time. Moreover, due to the heterogeneity of microbial populations, several cellular states with different metabolic activities can be distinguished among viable and cultivable Accepted Article cells. Several authors revealed this heterogeneity using fluorescent probes and flow cytometry (FCM) or epifluorescent microscopy: for lactic acid bacteria in cider [START_REF] Quirós | Taking advantage of the flow cytometry technique for improving malolactic starters production[END_REF], in fermented meat [START_REF] Bonomo | Stress response assessment of Lactobacillus sakei strains selected as potential autochthonous starter cultures by flow cytometry and nucleic acid double-staining analyses[END_REF], in whey (7), and in cheese [START_REF] Mikš-Krajnik | Impact of physiological state of starter culture on ripening and flavour development of Swiss-Dutch-type cheese[END_REF]. It is generally recognized that traditional reference culture-based methods (e.g., plate counts) do not guarantee the physiological state or the dynamics of the microbial population in terms of kinetics and metabolic activities. For example, yeast samples may reveal a low metabolic activity in a product, whereas its cultivability in the laboratory in terms of plate counts was good (9).

The measurement of the viability of microbial cells by FCM is usually based on the dual staining with propidium iodide (PI) (membrane integrity) and with fluorescein diacetate (FDA) or carboxyfluorescein diacetate (cFDA) (intracellular esterase activity). The fluorescent cells stained with FDA or cFDA is reported to correspond to the viable cells that have a metabolic activity and an intact membrane. Some cells lose their ability to reproduce but can still have an intact membrane and be stained by cFDA [START_REF] Breeuwer | Characterization of uptake and hydrolysis of fluorescein diacetate and carboxyfluorescein diacetate by intracellular esterases in Saccharomyces cerevisiae, which result in accumulation of fluorescent product[END_REF]. Dual staining allows the differentiation of three sub-populations on the cytogram: dead cells (PI positive, cFDA negative = red cells), viable cells (cFDA positive, PI negative = green cells) and altered cells (PI positive, cFDA positive = green and red cells) (10,[START_REF] Rault | Multiparametric flow cytometry allows rapid assessment and comparison of lactic acid bacteria viability after freezing and during frozen storage[END_REF]. Viable but non-cultivable cells are among this population of altered cells even if some altered cells may still be cultivable, depending on the ratio of green/red fluorescence intensities [START_REF] El Arbi | Assessment of the dynamics of the physiological states of Lactococcus lactis ssp. cremoris SK11 during growth by flow cytometry: Dynamics of the physiological states of L. lactis ssp. cremoris[END_REF]. The number of viable cells was simply assessed by FCM, which allows cell-by-cell analysis and gives a result in a very short time. However, the final fluorescence intensity of the viable cells depends on membrane integrity, intracellular esterase activity, intracellular pH and loss of fluorescent dye before analysis. Hence, fluorescence intensity alone cannot reflect vitality [START_REF] Breeuwer | Energy-dependent, carrier-mediated extrusion of carboxyfluorescein from Saccharomyces cerevisiae allows rapid assessment of cell viability by flow cytometry[END_REF].

In order to assess the vitality i.e., the kinetic behavior of a microbial population, several methods based on the measurement of a specific activity can be used according to the metabolism of the microorganisms. They involve the determination of the lag phase time with respect to growth, acidifying activity, metabolite production rate and consumption rate. In two microbial populations with the same cellular dry weight or the same number of viable cells (specific activity), the time required to Accepted Article reach a given optical density (OD), a given pH or a given quantity of product may be different according to the vitality of the two microbial populations. These methods provide some results about the whole culture and the overall cell population, but do not consider the heterogeneity within the microbial population. Moreover, they are time-consuming since it is necessary to grow a culture.

The three descriptors -cultivability, viability and vitality -are complementary: in order to ensure a reliable fermentative process, microorganisms must be of high quality, meaning that they must not only produce viable and cultivable cells in Petri dishes, but that they must also present a physiological state that guarantees good vitality. Starter quality has to be quickly assessed just before it is used in industrial processes.

Whereas viability can be quickly assessed by FCM, there is no equivalent method for vitality assessment. The aim of this study is to develop a flow cytometric descriptor that will allow to quickly assess the vitality of microbial cells, regardless of the strains. It is based on the observation that intracellular carboxyfluorescein (cF) is extruded after cFDA staining through an energy-dependent transport system. This phenomenon has been studied by several authors in bacteria and in yeasts: for Lactococcus lactis, the transport system is probably driven by ATP or a related compound, and strictly correlated with ATP concentration [START_REF] Molenaar | The efflux of a fluorescent probe is catalyzed by an ATP-driven extrusion system in Lactococcus lactis[END_REF], and for Saccharomyces cerevisiae, the transport system is driven by membrane potential or proton gradient, depending on the activation of H + -ATPase [START_REF] Breeuwer | Energy-dependent, carrier-mediated extrusion of carboxyfluorescein from Saccharomyces cerevisiae allows rapid assessment of cell viability by flow cytometry[END_REF].

Regardless of the transport system, we hypothesized that the energy status of the stained cells can be assessed by measuring the efflux in standardized conditions. We then proposed to standardize a descriptor to stain cells and to quantify the carboxyfluorescein excreted from the stained cells, and to compare the results to the specific activities measured by different methods according to the types of microorganisms: acidifying rate for LAB (Lactococcus lactis), CO 2 production rate for fermentative yeasts (Saccharomyces cerevisiae), O 2 uptake rate for aerobic yeasts (Yarrowia lipolytica), and growth lag phase or energy charge for other microorganisms (Staphylococcus aureus, Oenococcus oeni).

Accepted Article

-MATERIALS AND METHODS

Microbial strains and cultures

Two strains of Saccharomyces cerevisiae were used: the wine yeast L2056 (Lallemand SA, Blagnac, France), and the industrial ethanol yeast named Ethanol Red® (Lesaffre, Marcq en Baroeul, France).

Yeasts were stored at 4°C on Sabouraud agar (Biokar, Allonne, France). Pre-cultures were performed in Sabouraud broth (Biokar, Allonne, France) for 24 h at 30°C, and cultures were inoculated at 10 6 or 10 7 cells.mL -1 , depending on the assays, in an AF medium containing 180 g.L -1 (or 200 g.L -1 ) of glucose (Univar, Fontenay sous Bois, France), 2.5 g.L -1 of yeast extract, 0.3 g.L -1 of K 2 HPO 4 , 0.5 g.L -1 of KH 2 PO 4 , 2.5 g.L -1 of (NH 4 ) 2 SO 4 , and 0.5 g.L -1 of MgSO 4 (all components from Thermofisher, Strasbourg, France) adjusted to pH 4.0. The temperature was set at 25°C for L2056, and at 30°C for the measurements in alcoholic fermentations with Ethanol Red®.

Yarrowia lipolytica CBS 6124 is a strictly aerobic yeast used in cheese. Pre-culture and culture were performed in 50 mL of Sabouraud broth (Biokar, Allonne, France) in a 250-mL flask, inoculated with 10 6 cells.mL -1 , and placed on an orbital incubator at 100 rpm and 30°C for 24 h. Lactococcus lactis ssp. cremoris SK11 was obtained from the culture collection of the Micalis Institute (https://www.micalis.fr/). Cells were grown at 30°C in 10 mL of M17-lactose (5 g.L -1 ) (Biokar, Allonne, France) for 7 h for pre-culture, before transferring 1 mL to a 100-mL flask of M17-lactose (5 g.L -1 ) for the culture. For the measurement of acidifying activity, the medium was 100 g.L -1 dry skim milk (EPI-Ingredient, Ancenis, France), heat-treated at 110°C for 15 min in 150-mL flasks. The flasks were inoculated to reach a cell concentration of 10 6 cells.mL -1 .

Oenococcus oeni MC1 was isolated from wine by Moet & Chandon. The pre-culture was performed in 10 mL of synthetic medium FT 80 broth (glucose: 5 g.L -1 ; fructose: 5 g.L -1 ; L-malic acid: 5 g.L -1 ; yeast extract: 5 g.L -1 ; beef peptone: 2.5 g.L -1 ; tryptone: 2.5 g.L -1 ; NaH 2 PO 4 ,2H 2 0: 0.5 g.L -1 ; MgCl 2 : 0.05 g.L - 1 ; MnSO 4 ,H 2 0: 0.01 g.L -1 ; KCl: 0.15 g.L -1 ; CaCl 2 : 0.13 g.L -1 ; Tween 80: 1 mL.L -1 , (15) adjusted to pH Accepted Article 5.0 and incubated at 30°C. The cultures were performed in the same conditions except the pH was adjusted to pH 3.2. Cultures were inoculated to reach a cell concentration of 10 6 cells.mL -1 .

Staphylococcus aureus RN4220 (Micalis Institute) was cultivated in Brain Heart Infusion (BHI) (Biokar, Allonne, France) at 37°C. A pre-culture of 7 h was carried out before transferring 1 ml to 50 mL of culture medium.

All of the bacteria were stored in a cryotube at -80°C: an aliquot of 1.5mL of 7-h-old preculture (48-hold preculture for Oenococcus oeni) was poured in the cryotube with 10% glycerol (v/v).

Viable cell counts

The enumeration of viable cells was performed by FCM on the basis of viability staining by cFDA. A quantity of 100 µL of culture containing approximately 10 7 cells.mL -1 was added to 900 µL of McIlvaine's buffer [citric acid (100 mmol (Sigma Aldrich, Saint Quentin Fallavier, France), disodium hydrogen phosphate dihydrate (Na 2 HPO 4 200 mmol, (ThermoFisher, Strasbourg, France)] adjusted to pH4 for yeast and 7.3 for bacteria. A total of 10 μL of Chemchrome V8 (Bio-Mérieux, Craponne, France) diluted to 1/10 (v/v) in acetone (Sigma Aldrich, Saint Quentin Fallavier, France) was added, and the suspension was incubated for 10 min at 40°C before flow analysis.

Cytometric descriptor of vitality

A quantity of 200 µL of culture containing approximately 2.10 7 cells.mL -1 was added to 1.8 mL of Measures of fluorescence intensity FI 0 and FI t were performed on a normalized histogram containing 10,000 cells. The efflux percentage was calculated as follows: ΔFI 15 = 100(FI 0 -FI 15 )/FI 0 .

The development of the method was performed with S. cerevisiae. For that, the incubation time of the second milliliter to promote the efflux of cF, was 30 min or 50 min, and the calculation of the efflux percentage (ΔFI t = 100(FI 0 -FI t )/FI 0 was compared to ΔFI 15 . For one experiment during the development method, yeast cells (S. cerevisiae) were centrifuged and the pellet was placed in osmosed water from 1.5 h to 24 h. The descriptor FI 15 was directly measured after this time on one aliquot, and on a second aliquot after re-suspension in a glucose solution (1.8 g.L -1 in osmosed water) for 20 minutes.

Flow cytometry analyses

Flow cytometry analyses was performed with a CyFlow Space cytometer (Sysmex-Partec, Villepinte, France) equipped with a solid blue laser, emitting at 488 nm, and four optic filters: a forward-angle light scatter (FSC) combined with a diode collector, a side-angle light scatter (SSC) and two fluorescence signals collected with photomultiplier tubes, a 530-nm band-pass filter (515-545) to collect the green fluorescence (FL1 channel) and a 630-nm-long pass filter to collect the red fluorescence (FL2 channel). The signal analysis was performed using logarithmic gains and specific detector settings, adjusted on a sample of unstained cells (first decade for FL1), in order to eliminate cellular autofluorescence. Gating on FSC/SSC was used to discriminate bacteria or yeast cells from the background (R1 region). Data were collected and analyzed with FloMax software (SYSMEX-PARTEC, Villepinte, France) using statistical tables that indicate numbers and percentages of stained cells determined by each detector, as well as the fluorescence intensity of each fluorescent signal and the CV% (dispersion coefficient).

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Comparison of the vitality descriptor FI 15 and the other activity descriptors

To assess and compare the measurements of the vitality of microbial cells between the reference activity method and the cytometric descriptor, the strain (yeast or bacteria) was cultured in appropriate medium. Several samples were taken throughout the growth, from the inoculation to the stationary phase. For each sample, FI 15 was immediately measured by FCM on one aliquot, and a second aliquot was used to measure the activity with the dedicated method described below. Since these methods require culture, the second aliquot was used as an inoculum for these cultures. The values obtained with the two methods were compared.

Energy charge measurement

The energy charge measurement was performed on three bacterial strains: Lactococcus lactis SK11, Oenococcus oeni MC1 and Staphylococcus aureus RN4220. For each strain, seven to ten samples were taken during the culture in the appropriate medium.

For the extraction of nucleotides, 800 L of DMSO and 100 L of 10 mM EDTA were added to 100 L of cell suspension precisely adjusted to 10 6 cells.mL -1 , mixed for 1 min and then centrifuged (14500 g, 5 min). A quantity of 900 L of supernatant was added to 4 mL of 20 mM Tris buffer and stored at -20°C before analysis. For the measurement of nucleotide acids, ADP and AMP were converted to ATP according to [START_REF] Gorman | Measurement of adenine nucleotides in plasma[END_REF]. ATP concentration was measured with an ATP meter (MicroLumat LB 96PEG&G Berthold, Germany). The energy charge was calculated as the ratio: EC = (ATP +1/2 ADP)/(ATP + ADP + AMP). Each data point was the mean of at least three independent cultures.

Lag time of regrowth measurement

Lag phase time for a given number of viable microbial cells depends on the activity of these cells. The shorter the lag phase time is, the higher the activity of cells will be. For this assessment, the continuous Accepted Article measurement of OD at 600 nm was performed with the Bioscreen system (Bioscreen 2400620; Labsystems, Cergy Pontoise, France). This measurement was performed on two bacteria: L. lactis SK11 and S. aureus RN4220. Aliquots of 1.10 6 viable cells.mL -1 (counted by FCM after cFDA staining) were inoculated in wells on a microplate in 200 µL of culture medium dedicated to the bacterial strain and maintained at a set temperature. During growth of L. lactis SK11, the microplate was shaken (by vibration) for 30 seconds at medium intensity before the OD measurement. For S. aureus, which prefers aerobiosis, the microplate was shaken 30 seconds per minute at 37°C. OD was analyzed and registered every 15 minutes by the software (Growth Curves for microbiology reader Bioscreen C, Biolink 5186060A; Labsystems, Cergy Pontoise, France). Five replicates of each sample were poured on the microplate (five wells). Ten wells were filled with the sterile medium without a microbial sample to have a control of potential contamination. For one culture, the result of the OD of a sample during growth was calculated as the mean of the OD of the five replicates of the sample, minus the mean of the five replicates at time zero (i.e. corrected OD). 7 to 10 samples (one per hour) were taken throughout the culture. The lag phase was the time necessary to reach a corrected OD equal to 0.1. Each data point was the mean of at least three independent cultures.

Lag time of the substrate consumption measurement

The continuous measurement of OD with Bioscreen was not possible for Oenococcus oeni because the growth is so slow. Activity was determined by the lag phase of the malolactic fermentation, i.e., the beginning of the substrate (malic acid) consumption. A culture of O. oeni in FT80 medium (100 mL), pH 3.2, was performed, and FI 15 was measured at different times. At each these times, aliquots of 10 8 O. oeni viable cells, counted by FCM after syto9/PI staining [START_REF] Bouix | Rapid enumeration of Oenococcus oeni during malolactic fermentation by flow cytometry[END_REF], were taken from this culture, inoculated in 100 mL of FT80 medium, pH 3.2, and incubated at 30°C. Malic acid was monitored in these sub-cultures once a day (until the beginning of its consumption) using the enzymatic method (Enzytec, Biopharm, Saint Dizier au Mont d'Or, France). The malolactic fermentation lag time was Accepted Article calculated as the time where the initial malic acid concentration (5g.L -1 ) remained constant, before the beginning of its consumption. The shorter the lag time was, the greater the activity of O. oeni cells was [START_REF] Bouix | Rapid assessment of Oenococcus oeni activity by measuring intracellular pH and membrane potential by flow cytometry, and its application to the more effective control of malolactic fermentation[END_REF]. Each data point was the mean of two independent cultures.

Acidifying activity measurement

For acid-producing bacteria, activity assessment was provided by measuring of the acidifying activity, which is done with the CinAc system (Ysebaert, Frépillon, France) [START_REF] Spinnler | Automatic method to quantify starter activity based on pH measurement[END_REF]. The flasks containing milk medium were placed in a water bath at 30°C and inoculated into 10 6 cells.mL -1 (counted by FCM after cFDA staining). The pH is continuously measured, thus allowing the assessment of the acidifying activity by the determination of the time (tpH x ) necessary to reach a given pH [START_REF] Rault | Dynamic analysis of Lactobacillus delbrueckii subsp. bulgaricus CFL1 physiological characteristics during fermentation[END_REF]. Therefore, the smaller the tpH x value (min) is, the higher the acidifying activity will be.

We measured the acidifying activity of nine samples of cells of L. lactis SK11 taken throughout a culture in M17-lactose at 30°C. We measured the time (h) to reach pH=5 (tpH5). FI 15 was measured on each aliquot of the nine samples. Each data point was the mean of three independent cultures.

Gazogen activity measurement

The activity of fermenting yeasts can be measured by the CO 2 production rate in standard conditions during a culture. In the baking industry, this activity of CO 2 production rate, also known as the fermentative strength of yeasts, was determined by measuring the pressure increase due to the expansion of the volume of a dough in standard conditions (temperature, time, flour and yeast quantity) according to the method referred to as the "fermentometer of Burrows" [START_REF] Burrows | Routine method for determination of the activity of baker's yeast[END_REF]. For wine yeasts, the CO 2 production rate was measured by weight loss [START_REF] Sablayrolles | Design of a laboratory automatic system for studying alcoholic fermentations in anisothermal enological conditions[END_REF] or by the volume of CO 2 produced. We used this last method with a new device, the YAMS (Yeast Activity Measurement System), designed and developed by the SayFood unit (AgroParisTech-INRAE, Grignon, France). The flask containing 100 ml of yeast culture, maintained at 25°C with shaking at 100 rpm, is connected to a gas counter

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(Ritter MilliGascounter type MGC-1, SERV'Instrumentation, Irigny, France). The measurement cell consists of two measuring chambers immersed in a solution of HCl (1.8%), which are successively filled with the gas from the flask. When a measuring chamber is filled, the buoyancy of this chamber causes the cell to tip, triggering a pulse by means of a permanent magnet. The second measuring chamber begins to fill and the first one is emptied at the same time. A pulse corresponds to 3 ml of gas.

The system includes ten channels that can be sequentially measured before coming back to the first channel. The set of recorded points makes it possible to draw the CO 2 production curves for each of the ten channels. Using a linear regression on the curves, we can calculate the time necessary to obtain a given amount of CO 2 (from 1 g to 5 g in our case) and to calculate the lag time as the time before the beginning of the increase of the curve of CO 2 production.

To compare the vitality of yeast cells with FI 15 and lag time fermentation, we used the yeast L2056, cultivated in AF medium (glucose 180g.L -1 ). Samples were taken throughout a culture, at 3 h, 5 h, 16h, 24 h, 40 h and 72h. FI 15 was measured on one aliquot, and three flasks containing 100 mL of AF medium was inoculated with another aliquot to reach 10 7 .mL -1 (adjusted by FCM after cFDA staining), and connected to the YAMS. CO 2 production was recorded over 24 h. The lag time (mean of the three flasks) was calculated and correlated with the FI 15 value of each inoculum. Each data point was the mean of three independent cultures.

Respiratory activity measurement

For non-fermenting yeasts, the CO 2 production rate cannot be used, and it is therefore the respiratory activity that must be assessed. The specific oxygen consumption rate was determined in a 7-ml glass reaction chamber (Veral, Colombes, France) [START_REF] Gabier | Intracellular physiological events of yeast Rhodotorula glutinis during storage at +4°C[END_REF], thermostated at 30°C by water circulation. The homogeneity of the cell suspension in the reaction chamber was ensured by magnetic agitation. The concentration of dissolved oxygen in the suspension was measured by an oxygen electrode (Mettler Toledo, InPro 600 series O 2 sensors; Mettler, Paris, France) connected to a unity of regulation (Inceltec

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LH-SGI, Toulouse, France), which was linked to data collection software. The oxygen electrode was calibrated in the McIlvaine buffer, pH 7.3, to 0% and 100% air saturation, by blowing bubbles of nitrogen and air, respectively. Before analysis, 6.5 mL of the McIlvaine buffer containing 1.8g.L -1 of glucose was placed in the reaction chamber, and the P O2 was adjusted to 100% (blowing air bubbles during approximately 15 min). Measurements of FI 15 and the time necessary to reach P O2 =50% were determined on samples taken throughout a culture of Yarrowia lipolytica (samples at 2h, 3h, 5h, 7h, 16h and 24h). A sample was taken, centrifuged, (14500 g, 90s), washed and resuspended in the McIlvaine buffer (pH 7.3) at a concentration adjusted to 1.4.10 8 viable cells.mL -1 (counted by FCM after cFDA staining). A quantity of 500 µL of this cell suspension (containing 7.10 7 viable cells) was poured into the reaction chamber (final concentration in the reaction chamber: 1.10 7 viable cells.mL -1 ).

The analysis began when cell suspension was added in the reaction chamber. The decrease of the P O2 was monitored and recorded. The results were expressed in time (min) to reach P O2 =50%. Two replicates were performed for each sample.

Fermentation activity measurement

All the previous assays allowed to compare FI 15 with the lag time of regrowth or the start up time of metabolisms. This last experiment aimed to compare the vitality descriptor with the activity during fermentation. Alcoholic fermentation was performed with the yeast Ethanol Red® in AF medium (200 g.L -1 of glucose) in a 2-L bioreactor. Temperature and pH were regulated to 36°C and pH=3.2 (addition of 2N NaOH), respectively. Ethanol Red® yeast cells were inoculated to reach 10 6 cells.mL -1 in the bioreactor, from a pre-culture of 24 h. Throughout the culture, viable yeast cells were counted every two hours by FCM after cFDA staining.

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240°C; and oven temperature: 75°C). FI 15 measurements were performed on each sample. On the basis of the results of ethanol concentration and cell concentration, we were able to calculate the ethanol production rate and the specific ethanol production rate throughout the fermentation. All the data were the mean of three fermentations.

-RESULTS

Development of the cytometric descriptor to assess the vitality of microbial cells

Development of the cytometric descriptor with S. cerevisiae L2056

The first development concerned the wine yeast S. cerevisiae L2056. Figure 1a shows the histograms of the fluorescent cells after 0, 15, 30 and 50 min of incubation after staining. The fluorescence intensity FI t decreased when the incubation time t increased because of the cF efflux from the yeast cells. According to the age of culture, these effluxes were quantified with the descriptor FI t : the efflux was faster with young cells than with older ones (Figure 1b). For each culture age, the difference between FI 15 , FI 30 and FI 50 was small, except for the oldest cells. Moreover, the difference between two ages of culture was slightly higher for FI 15 than for the others: FI 15 (6h) -FI 15 (11h) > FI 30 (6h) -FI 30 (11h) > FI 50 (6h) -FI 50 (11h), (Figure 1b). Since the objective was to develop a rapid descriptor to monitor the variation of the efflux out of the cells throughout their growth, FI 15 was chosen since it was more discriminating and rapid to measure.

Figure 1c presents the FI 15 values of yeast cells sampled at 24 h of culture, corresponding to FI 15 time 0, and for the same cells after various durations of storage in water: the FI 15 of yeast cells after water starvation tended to zero. When yeast cells were resuspended in glucose solution before staining, the FI 15 values were restored, confirming that the efflux of cF after staining with cFDA was energydependent, as already shown by other authors in various microbial models ( 14)((13).

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Development of the cytometric descriptor with bacteria

The method developed with S. cerevisiae should be validated with bacteria. Throughout the growth of the lactic acid bacterium Lactococcus lactis ssp. cremoris SK11 and the bacterium S. aureus RN4220, the descriptor FI 15 was measured with the same protocol as for yeast. The FI 15 values increased at the beginning of the exponential growth and then decreased from the middle of the exponential phase of growth to the onset of the stationary phase (Fig. 2a). This change was superimposed on the evolution of the specific growth rate µ (Fig. 2 b andd) with a coefficient of determination (R 2 ) of the linear correlation equal to 0.924 for L. lactis SK11 (Fig. 2 c) and 0.949 for

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Comparison of the vitality descriptor FI 15 with the commonly used descriptors of microbial activity FI 15 and energy charge

Changes in the energy charge of bacterial cells throughout their culture were measured and compared to the variations of the descriptor FI 15 . As displayed in figure 3, the evolution of the energy charge (EC) of L. lactis SK11 throughout its growth showed similar trends to that of FI 15 (determination coefficient of 0.918, see Fig. 3b). This was similarly observed for all the other studied bacteria, namely O. oeni MC1 (R² = 0.981, Fig. 3b) and S. aureus RN4220 (R² = 0.965). For both bacteria, the lag phase duration decreased for the inocula sampled at the beginning of the exponential growth phase, then reached a minimum for the 2-h-old inoculum, and finally increased for all the inocula sampled thereafter until the beginning of the stationary growth phase (6 h). Figure 4a shows that FI 15 measured on each of these inocula of L. lactis SK11increased to a maximum for the 2-h-old inoculum and then decreased: the shorter the lag phase was, the higher the value of FI 15 was. Fig. 4b shows the linear correlation coefficients between the lag phase duration and the FI 15 for the two tested bacteria.

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FI 15 and Lag time of substrate consumption

The growth of O. oeni in FT80, pH3.2, was slow since the fermentation time was 250 h. For inocula taken from a culture aged between 50 and 150 h, FI 15 increased from 28% to 88% and then decreased to 40% for an inoculum sampled at 250h of culture (Fig5a). The duration of the lag phase of the malolactic fermentation of the cultures inoculated with O. oeni cells characterized by these different values of FI 15 followed an inverse evolution: the lag phase was very long for the culture inoculated with cells showing weaker FI 15 cells, (inoculum age between 50 and 100 h), increasingly short with the cells taken at around 150 h of culture showing the highest FI 15 , and then increased up to 120 h for cells of the oldest inoculum (Fig. 5a). The shorter the latency period of malic acid consumption was, the greater the cell activity and the higher the value of the descriptor FI 15 were. The determination coefficient of the linear correlation between FI 15 and the latency period of malic acid consumption was 0.977 (Fig. 5b). The acidifying activity of lactic acid bacteria can be measured by the time needed to reach a given pH value. A difference of about 1,5h for the time to reach a pH value of 5 was observed between the fastest and the slowest aliquots of L. lactis SK11 cells. As shown in Fig. 6a, the cells sampled at the beginning and at the end of the culture required 13.5-14 h to reach a pH of 5, whereas those sampled after 2 h of culture required only 12 h to reach the same pH value. The acidifying activity of bacterial cells was maximum after 2 h of culture, and decreased after this time. The curve of the cytometric descriptor FI 15 showed the inverse evolution: it was maximum for the cells sampled at 2 h of culture and lower before and after this point. FI 15 was negatively correlated to the acidifying activity, with a determination coefficient of 0.97 (Fig. 6b).

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FI 15 and gazogen activity (fermenting yeast)

The YAMS made it possible to record the CO 2 production rate of the cultures inoculated with the samples taken throughout a previous culture (sampling time of A: 3h, B: 5h, C: 16h, D: 24h, E: 40h, and F: 72h; Fig. 7a). The FI 15 values of these samples (= inocula of the cultures) changed from 71.5% to 35%. Depending on the samples, the time to produce 2 g of CO 2 (dashed line on Fig. 7a) changed from 8 h to 18 h. The lag phase (tlag) (i.e., time before the beginning of the increase of the curve of CO 2 production: before the lag time, the CO 2 production was too low to be detected) then varied from

 FI 15 and Respiratory activity

For the strictly aerobic yeast Yarrowia lipolytica, metabolic activity was measured by the oxygen consumption rate. As the experimental device corresponds to a small volume and needs a high cell concentration (10 7 .mL -1 ) to be able to get a measurement, the time to reach 50% of partial dissolved oxygen pressure (P O2 ) was evaluated in minutes. It varied from 5 min to 20 min depending of the age of the inoculum. The vitality descriptor FI 15 changed from 66% to 10%. The coefficient of determination of the linear correlation between the vitality descriptor FI 15 and the time to reach 50% of P O2 (starting to 100% at the beginning of the assay) was equal to 0.99 (Fig. 8). Throughout the alcoholic fermentation performed with the yeast Ethanol Red®, the ethanol concentration increased from 0 to 98 g.L -1 (Fig9a). The cell concentration changed from 10 6 cells.mL -1 at the beginning of the culture to 7.10 7 cells.mL -1 at 40 g.L -1 of ethanol, 8.10 7 .mL -1 at 70 g.L -1 of ethanol, and remained stable until the end of fermentation. The vitality of yeast cells measured by FI 15 decreased when the ethanol concentrations increased. The change in the vitality followed the same profile as the ethanol production rate (Fig9a). The coefficients correlation between FI 15 and ethanol production rate, on the one hand, and between FI 15 and the specific ethanol production rate, on the other hand, were linear (with coefficients of determination of 0.99 and 0.91, respectively (Fig9b, 9c). The lower R² value in the case of the correlation with the specific ethanol production rate may be explained by the accuracy of the measurement of the cellular concentration, which was worse than that of the ethanol concentration.

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-DISCUSSION AND CONCLUSION

As reported by ( 13) and ( 14), we confirmed that after staining with cFDA cleaved by intracellular esterase, yeast cells and bacterial cells extruded cF via an energy-dependent mechanism. The aim of our study was not to clarify the details of the mechanisms, but to quantify the efflux in order to propose an easy-to-handle descriptor of cell vitality on various microorganisms. A 15-min efflux was demonstrated as the most discriminating for cells of different culture ages, and made it possible to have a relevant descriptor of microbial cell vitality that could be assessed in a short time, both for yeast and bacteria. This study confirmed that the vitality of microorganisms measured by the proposed cytometric descriptor changes throughout a culture, following the profile of the specific growth rate and the increase and decrease in the energy charge. All the measurements for an assay were performed with samples at equal cell concentrations, but with different specific activities. This difference of a few hours may be significant in industrial processes, resulting in a more or less quick start-up of culture after inoculation. For example, in cheese-making, the starter must be able to colonize the milk and acidify it as quickly as possible in order to prevent the development of spoilage and pathogenic bacteria. When we inoculated two milk samples with S. aureus RN4220 (10 6 cells.mL -1 ) and with L. lactis SK11 (10 6 cells.mL -1 ), but one with L. lactis characterized by a high FI 15 and the other with L.

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lactis showing a lower FI 15 , we observed that S. aureus grew to 1.6 10 7 cells.mL -1 and then dropped to 2.9 10 6 cells.mL -1 after 7h of culture and to 9.10 5 cells.mL -1 after 24 h of culture in the first sample, but grew to 6.6.10 7 cells.mL -1 and remained at this level after 24 h in the second sample (S. aureus RN4220 alone: 9.5.10 7 cells.mL -1 after 7h of culture) (data not shown). This proved the role of the vitality of the starter L. lactis SK11 independently of the viable count. In addition, a weak vitality of yeasts may explain why, in some cases, wine fermentation remains slow (sluggish fermentation) [START_REF] Rodriguezporrata | Vitality enhancement of the rehydrated active dry wine yeast[END_REF].

To validate the pertinence of the cytometric vitality descriptor, we compared the FI 15 values with the measurements performed with the reference methods for activity assessment suitable for each dedicated metabolism. All FI 15 measurements were well correlated with high determination coefficient to each specific activity tested, both for yeasts and bacteria, regardless of the metabolism, i.e., acidifying activity, CO 2 production or oxygen consumption, lag time of regrowth, substrate consumption or metabolite production.

To our knowledge, there is no other cytometric descriptor to assess the vitality of bacteria as well as yeasts. A review of methods [START_REF] Kwolek-Mirek | Comparison of methods used for assessing the viability and vitality of yeast cells[END_REF] to measure yeast vitality cited the measurement of mitochondrial membrane potential by fluorescence microscopy, after application of an oxidative stress, and not on cells in cultures under natural fermentation conditions. The FI 15 descriptor is therefore the only cytometric descriptor to assess vitality for both bacteria and yeast currently available. This rapid cytometric descriptor proposed in this study included two steps: first, the staining of the cells with cFDA for an incubation of 10 min, then the efflux of cF from the cells for 15 min after centrifugation and re-suspension in a buffer (2 min), followed by the cytometric analysis. It means a total duration of approximately 30 min to assess the cellular concentration (on the same aliquot as the fluorescence intensity FI 0 ) and the microbial cell vitality thanks to the calculation of FI 15 . This time is much shorter than the time necessary to assess the different metabolic activities with the reference methods

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described above since these methods require culture and several hours (or even days). Moreover, this staining and the flow cytometric analysis are easier as no preparation of sterile media in flasks or in microplates is needed. In addition, the width of the histogram makes it possible to visualize the cellular heterogeneity among the microbial population (the narrower it is, the more homogeneous the population will be), in contrast to the measurements of metabolic activities carried out on the whole population. In conclusion, the cytometric descriptor FI 15 is consistent with reference methods of measurement of metabolic activities, gives more information than them, but much faster and is then very useful for assessing the vitality of microorganisms before inoculation in laboratory research or throughout an industrial process.

  McIlvaine's buffer adjusted to pH 4 for yeast and 7.3 for bacteria, and incubated with 10 μL of Chemchrome V8 (Bio-Mérieux, Craponne, France) for 10 min at 40°C. The stained sample was centrifuged (14500 g, 90 s), and the pellet was resuspended in 2 mL of McIlvaine's buffer at pH4 for yeast or 7.3 for bacteria. One milliliter was immediately analyzed by FCM to measure the fluorescence intensity FI 0 . The second milliliter was incubated for 15 min (except for the development) at 40°C to promote the efflux of cF, centrifuged, and the pellet was resuspended Accepted Article in McIlvaine's buffer (pH 4 or 7.3) before FCM analysis to measure the fluorescence intensity FI 15 .

  Ethanol concentration was assessed by GC Head-Space (Agilent Technologies Hewlett Packard, Courtaboeuf Les Ulis, France) equipped with a capillary HP-INNOWax polyethylene glycol (PEG) column (30 m × 530 µm × 1.00 μm) (operating conditions: He flow: 8.4 mL/min; injection temperature: 250°C; detector temperature:

Figure 1 Development

 1 Figure 1

Figure 2

 2 Figure 2 Development of the vitality descriptor for bacteria measured by flow cytometry Growth curve of L. lactis SK11 and S. aureus RN4220 and respective vitality descriptor FI 15 (a); Evolution of vitality descriptor FI 15 and specific growth rate of L. lactis SK11 (b), S. aureus RN4220 (d), and respective linear regression curves (c, e).

Figure 3

 3 Figure 3 Correlation between the energy charge and the cytometric descriptor FI 15 Energy charge (EC) and FI 15 changes throughout a culture of L. Lactis SK11 (a); Linear relation between the EC and the FI 15 descriptor for three different bacterial species (b)

Figure 4

 4 Figure 4 Correlation between the duration of the lag phase of re-growth and the cytometric descriptor FI 15 Evolution of the lag phase duration of re-growth and the values of FI 15 of samples taken throughout a culture of L. lactis SK11 (a); Correlation between lag time and FI 15 for L. lactis SK11 and S. aureus RN4220 (b).

Figure 5

 5 Figure 5 Correlation between the duration of the lag phase of malolactic fermentation by Oenococcus oeni MC1 and the cytometric descriptor FI 15

Figure 6

 6 Figure 6 Correlation between the acidifying activity of lactic acid bacteria and the cytometric descriptor Time to reach a pH value of 5.0 (t pH5 ) of different samples of L. lactis SK11 taken throughout a culture used as inoculum and corresponding FI 15 values of each inoculum (a) Correlation between tpH5 and FI 15 (b).

5. 5 h

 5 Figure 7 Correlation between the CO 2 production rate of the fermenting yeast S. cerevisiae L2056 and FI 15 CO 2 production rate of six cultures with various FI 15 values of the inocula (a); Correlation between the lag time of CO 2 production and the FI 15 values of the inocula (b).

Figure 8

 8 Figure 8 Correlation between the time to reach a partial pressure of dissolved oxygen (P O2) of 50% (starting from 100%) during cultures of Yarrowia lipolytica and FI 15 values of the samples

Figure 9

 9 Figure 9 Correlation between fermenting activity throughout a culture and FI 15 Ethanol production, ethanol production rate and FI 15 (a); Correlation between the ethanol production rate and FI 15 (b); Correlation between the specific ethanol production rate and FI 15 (c).