J Ind Microbiol Biotechnol (2013) 40:63–73
DOI 10.1007/s10295-012-1200-3
BIOTECHNOLOGY METHODS
Cytofluorometric detection of wine lactic acid bacteria:
application of malolactic fermentation to the monitoring
Mohammad Salma • Sandrine Rousseaux •
Anabelle Sequeira-Le Grand • Hervé Alexandre
Received: 20 July 2012 / Accepted: 15 September 2012 / Published online: 19 October 2012
Ó Society for Industrial Microbiology and Biotechnology 2012
Abstract In this study we report for the first time a rapid,
efficient and cost-effective method for the enumeration of
lactic acid bacteria (LAB) in wine. Indeed, up to now,
detection of LAB in wine, especially red wine, was not
possible. Wines contain debris that cannot be separated
from bacteria using flow cytometry (FCM). Furthermore,
the dyes tested in previous reports did not allow an efficient
staining of bacteria. Using FCM and a combination of
BOX/PI dyes, we were able to count bacteria in wines. The
study was performed in wine inoculated with Oenococcus
oeni (106 CFU ml-1) stained with either FDA or BOX/PI
and analyzed by FCM during the malolactic fermentation
(MLF). The analysis show a strong correlation between the
numbers of BOX/PI-stained cells determined by FCM and
the cell numbers determined by plate counts (red wine:
R2 C 0.97, white wine R2 C 0.965). On the other hand, we
found that the enumeration of O. oeni labeled with FDA
was only possible in white wine (R2 C 0.97). Viable yeast
and LAB populations can be rapidly discriminated and
quantified in simultaneous malolactic-alcoholic wine fermentations using BOX/PI and scatter parameters in a one
single measurement. This rapid procedure is therefore a
suitable method for monitoring O. oeni populations during
winemaking, offers a detection limit of \104 CFU ml-1
M. Salma S. Rousseaux H. Alexandre (&)
UMR 02102 PAM Université de Bourgogne-AgroSup Dijon
Laboratoire VALMIS Institut Universitaire de la Vigne et du Vin
Jules Guyot, Université de Bourgogne, 21078 Dijon Cedex,
France
e-mail: rvalex@u-bourgogne.fr
A. Sequeira-Le Grand
Plateforme de Cytométrie, Structure Fédérative de Recherche
Santé STIC, Fac. Médecine, Université de Bourgogne,
7, Bd Jeanne D’Arc, 21000 Dijon, France
and can be considered a useful method for investigating the
dynamics of microbial growth in wine and applied for
microbiological quality control in wineries.
Keywords Lactic acid bacteria Malolactic fermentation
Flow cytometry Fluorescein diacetate Bis-oxonol
Introduction
Wine is the result of a complex interaction between yeast,
lactic acid bacteria (LAB) and must. Oenococcus oeni is
the main species that carries out malolactic fermentation
(MLF) in wine, and Saccharomyces cerevisiae is the main
yeast species that carries out alcoholic fermentation (AF).
Various bacterial genera such as Lactobacillus, Pediococcus and Leuconostoc can also be found in wine and can
cause spoilage [1].
Real-time microbial analysis during fermentation allows
winemakers to make informed production decisions.
However, accurate microbial analysis of mixed populations
of yeast and bacteria that are constantly changing during
fermentation is a challenging task.
Several methods are available to detect and enumerate
the microorganisms present in wine fermentations. Classical microbiological techniques can be used to detect LAB
in wine samples, but these assays require up to 14 days to
be complete because of the slow growth of some LAB such
as O. oeni. Another disadvantage is the failure of these
methods to detect viable but nonculturable organisms [2].
On the other hand, total microscopic enumeration methods
are relatively fast, but are limited by operator fatigue due to
prolonged microscope use and by low sensitivity [3].
Consequently, several molecular methods have been developed, but most of these methods, such as species-specific
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PCR and nested PCR, require lysis of the microbial cells
and isolation of DNA [4]. Species-specific target sequences
can also be detected in DNA immobilized on a membrane,
DNA in solution or after the DNA has been resolved on
gel, using either radioactive or fluorescent oligonucleotide
probes [4, 5]. Alternatively, qPCR amplification has been
used to detect and identify O. oeni in wine [6]. For all these
methods, primer design requires prior knowledge of
genomic sequences, the cost of the analysis is expensive
[7], and analysis times generally exceed 6 h [6].
Flow cytometry is extremely sensitive, it avoids the
need for culturing or enrichment procedures, and it can be
both qualitative and quantitative [3, 8, 9]. FCM offers
numerous possibilities for the detection and enumeration of
microorganisms in their natural habitat. It also allows the
detection and discrimination of viable cultivable, viable
noncultivable and nonviable organisms by using fluorescent stains or fluorogenic substrates [2, 3, 10–14]. Continuous improvements in the sensitivity and performance of
FCM instruments have resulted in a wide range of applications for characterizing and detecting bacteria, yeast,
fungi and even viruses [8, 13, 15–19].
FCM has been used previously to monitor microbial
populations in wine fermentations and was found to be
suitable for enological applications [20–23]. The method
has also been validated by comparing it with other viability
tests such as plating methods [22–24].
Rodriguez et al. [23] proposed to monitor yeast and
bacteria simultaneously in white wine using flow cytometry with fluorescent antibodies. However, antibodies are
expensive, and the efficiency of this method in red wine
still needs to be demonstrated.
Malacrinò et al. [22] used FCM to directly detect yeasts
and malolactic bacteria in wine using different fluorescent
viability probes, such as rhodamine 123, calcein acetoxymethyl ester and fluorescein diacetate (FDA). FDA was
found to be the most effective marker for labeling O. oeni
because it generates a higher fluorescent signal than the
autofluorescence produced by cells and wine debris [22].
FDA is a lipophilic, uncharged and non-fluorescent substrate
for cellular esterase, which cleaves FDA inside living cells to
release green fluorescent fluorescein (520-nm emission).
FDA can be used to monitor cellular esterase activity and to
determine the viability of cell populations. However, the
fluorescein generated from FDA has been reported to leak
from cells [25]. In addition, natural wine debris can interfere
with O. oeni detection and can cause poor quantification
results [22]. Furthermore, some O. oeni strains are not
stained at all with FDA, which limits the usefulness of this
probe for detecting these bacteria in wine [22].
A number of different fluorescent probes could be
potentially applied to the microbial analysis of wine. The
combination of a cell dye, such as bis-oxonol (BOX), and
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propidium iodide (PI) could be used to distinguish between
intact polarized cytoplasmic membranes (CMs), intact
depolarized CMs and permeabilized membrane cells.
PI is a vital red fluorescent probe (635-nm emission) that
binds to DNA only when the CM is permeabilized [2, 26–
28]. BOX is a lipophilic, non-toxic anionic green fluorescent (525-nm emission) stain that binds to the CM only if it
is depolarized. BOX staining also provides a measure of
the cellular metabolic ‘‘stress’’ level. One advantage of
using BOX is its insensitivity to the efflux pump systems in
the CM [2]. Thus, dual staining with BOX/PI can provide
quantitative and qualitative information about the cell
populations having intact polarized CMs, intact depolarized CMs and permeabilized membrane cells. Use of this
combination of fluorescent dyes for microbial analysis of
wine has not been reported previously.
The first objective of this study was to compare the
efficacy of FDA staining to that of BOX/PI staining in the
detection and quantification of LAB in wine. Our second
objective was to develop a method for a quick and reliable
quantitative FCM assay for LAB in wine. Thereafter, we
applied FCM: (1) to evaluate the viability of different O.
oeni starter ferments during winemaking, and (2) to monitor the changes in the bacterial and yeast populations
during fermentation of musts, inoculated simultaneously
with S. cerevisiae and O. oeni.
Materials and methods
Yeast and bacterial strains; culture media
Saccharomyces cerevisiae strain PB2585 was aerobically
cultured on yeast extract-peptone-dextrose agar medium
[YPD; 10 g l-1 yeast extract (Conda catalog no. 1702,
Madrid, Spain); 20 g l-1 glucose (Sigma G8270, Quentin
Fallavier France), 20 g l-1 bacterial peptone (Conda catalog no. 1616, Madrid, Spain), 20 g l-1 agar (Conda catalog
no. 1805, Madrid, Spain)] at 28 °C. For liquid culture,
yeast cells were grown in YPD broth at 28 °C.
Pediococcus damnosus LMG16740 and O. oeni (DIV
SABO11 and DIV 7.32) were cultured on LAC medium
[78 ml l-1 white commercial grape juice, 33 g l-1 yeast
extract (Conda catalog no. 1702, Madrid, Spain),
0.6 ml l-1 Tween 80 (Sigma P4780, Steinheim Germany),
0.08 g l-1 MnSO4 H2O (Sigma M7634, Quentin Fallavier
France)] containing 1 ml Delvocid 1 % to suppress yeast
growth. The plates were incubated anaerobically at 28 °C
for 10–14 days inside jars using an anaerobic atmosphere
generation system (Anaerogen Kits, Oxoid Ltd). Lactobacillus plantarum WCFS1 was cultured at 30 °C in MRS
medium (Conda, catalog no. 1215, Madrid Spain). For
liquid culture, P. damnosus and O. oeni cells were grown in
J Ind Microbiol Biotechnol (2013) 40:63–73
LAC broth at 28 °C. Lactobacillus plantarum WCFS1 was
precultured at 30 °C in MRS broth (Conda, catalog no.
1215, Madrid Spain).
Two commercial starters of O. oeni, starter I (Inoflore,
Institut Oenologique de Champagne, France) and starter II
(VinifloraÒ—Oenos, Denmark), were used according to the
manufacturer’s rehydration and inoculation instructions.
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side scatter (SSC) using logarithmic scale. After preculture,
bacteria were inoculated in wines at a density of
106 CFU ml-1 and incubated at 20 °C. Commercial starters were directly inoculated according to the manufacturer’s rehydration and inoculation instructions (Fig. 1).
All culture processes were performed in triplicate.
Alcoholic and/or malolactic fermentations
Musts and wines
Musts were collected from the Burgundy area at harvest.
Red (Pinot noir) and white (Chardonnay) wines (pH 3.17
and 3.52, respectively) were also from the Burgundy area.
For some experiments, samples of wine were filtered
through a 0.22-lm-pore membrane (Sartorius). To control
the sterility of filtered wine, 1 ml of wine was aseptically
removed and incubated for 3 days on (YPD) agar medium
at 28 °C to culture yeast or for 14 days on LAC agar
medium at 28 °C in anaerobic conditions to culture bacteria as previously described.
Flow cytometry analysis
Flow cytometry samples were analyzed using a Guava
EasyCyte Plus SSC4C flow cytometer (Guava Technologies, Hayward). This instrument is equipped with a
488-nm, 25-mW laser line, forward scatter (FSC, for cell
size) and side scatter (SSC, for granularity) detectors; green
fluorescence was collected on the FL 1 channel using a
525-nm (±30 nm) band-pass filter; red fluorescence was
collected on the FL 3 channel using a 680-nm (±30 nm)
band-pass filter. This instrument allows determining
accurate cell numbers and population percentages, without
the need for reference beads, as described by the manufacturer using only the Guava Cytosoft data acquisition and
analysis software. For all analyses, a minimum of 5,000
events was acquired, and all samples were collected as
logarithmic signal. Experiments were performed in duplicate and included an unlabeled sample as a control in
96-well plates. Data were analyzed using the Guava Cytosoft data acquisition and analysis software version 5.0
and FlowJo software version 7.6. Hardware compensation
has been applied for adjusting the settings of the two-color
analysis (BOX/PI, Table 1). In parallel, cells were enumerated by plating on YPD and LAC agar media to validate the FCM results.
Analysis of strains and wine debris by scattered light
detection on a flow cytometer
Unfiltered and filtered wines, either inoculated with
microorganisms or not, were analyzed on a flow cytometer
by scattered light detection using forward scatter (FSC) and
Fermentations were carried out in 250-ml flasks containing
200 ml of must or wine. All fermentations were performed
in triplicate.
After preculture, LAB strains were inoculated in wines
at a density of 106 CFU ml-1 and incubated at 20 °C.
Commercial starters were directly inoculated according to
the manufacturer’s rehydration and inoculation instructions
(Fig. 1). MLF was monitored by malic acid degradation
analyzed by an enzymatic assay (OENOSENTEC L-malic
acid kit, Toulouse, France) according to the manufacturer’s
instructions. MLF was considered to be complete when the
malic acid concentration was less than 0.2 g/l.
In cases of co-inoculation, starters and S. cerevisiae
PB2585 were simultaneously inoculated at densities of
106 CFU ml-1 in must and incubated at 20 °C (Fig. 1). AF
was monitored by sugar consumption using the DNS
method [29] and was considered to be complete when the
sugar level was less than 1 g/l.
Detection of strains with fluorescent dyes
We used three fluorescent dyes BOX/PI and FDA to detect
microorganisms by FCM. For the FDA staining procedure,
1 ml of cultured cells from red or white wine was centrifuged (13,000 rpm for 5 min at 25 °C), the pellet was
rinsed twice in PBS (130 mM NaCl, Sigma S9888, Quentin
Fallavier France), 5 mM NaH2PO4 (Sigma S2554, Quentin
Fallavier France) and 5 mM Na2HPO4 (Sigma 255793,
Quentin Fallavier France; pH 7.4). Cells were resuspended
in 1 ml of FDA buffer (0.5 M Na2HPO4 and 0.5 M
NaH2PO4; pH 7) to which 6 ll of FDA at 20 lM in acetone
(Sigma F737, St Louis, MO, USA) was added in order to
reach a final concentration of 0.12 lM, and the cells were
then incubated for 15 min at room temperature in the dark
before being analyzed by FCM. Samples were diluted if
necessary to obtain a final concentration of 106 CFU ml-1.
To stain cells with BOX and PI, 100 ll of cultured cells
from inoculated wine or must was added to 900 ll of PBS
(pH 7.2–7.5), and 4 mM EDTA (Sigma E9894, Steinheim
Germany) was added to facilitate the staining of gramnegative bacteria with BOX by destabilizing the outer
membrane (OM) [30]. Cell concentrations between
5 9 105 and 1 9 106 cells ml-1 are recommended for
counting with FCM; 1 ll of 2 mM PI (final concentration
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2 lM; Sigma, 81845, St Louis, MO, USA, in sterile MilliQ
water) and 3 ll of 2 mM BOX (final concentration 6 lM;
Invitrogen, B-438, USA, in DMSO, Sigma, 472301,
Steinheim, Germany) were added to the resuspended cells
to label dead and viable cells, respectively. The cell suspensions were incubated at room temperature for 15 min in
the dark before being analyzed by FCM.
mercury arc lamp for epifluorescence illumination, a fluorescein isothiocyanate filter set and a 1009 objective lens.
Fluorescence microscopy
Before the quantification of LAB in wine, a threshold level
determination is required. Unfiltered wine with or without
O. oeni cells was analyzed and compared by flow cytometry using only the FSC and SSC parameters (logarithmic
scale). This allowed setting an electronic threshold on FSC
to eliminate instrument noise and background linked to
wine debris smaller than bacteria (data not shown). The
threshold is fixed on FSC and is applied to all the following
analyses (Table 1).
Microscope slides were analyzed with an epifluorescence
microscope (Leica DM LB) equipped with a 12-V, 50-W
halogen lamp for transmitted light illumination, a 50-W
Table 1 Typical cytometer settings used for analysis of bacteria
species
Parameter
Results
Flow cytometer instrument settings
Setting for stain(s) and species
FDA
Box/PI
Measurement of cells versus particles in white wine
FSC
Log A
Log A
SSC
Log A
Log A
FL1 (525 ± 30 nm)
FL3 (680 ± 30 nm)
Log A: 524 V
Log A: 500 V
Log A: 557 V
Log A: 610 V
In a second set of experiments, we assessed whether it was
possible to differentiate O. oeni from white wine debris
(equivalent to bacteria size) based on FSC and SSC
parameters. FCM analysis demonstrated that filtered and
unfiltered white wines, whether inoculated or not with
LAB, were not significantly different from each other in
terms of light scattering (Fig. 2). Thus, it was not possible
to differentiate between LAB and white wine debris by
light scattering; the same results were observed for red
Threshold on FSC (FSC-Hlin)
14 units
14 units
Compensation (RED—%GRN)
NA
15,9
FSC Forward scattered light, SSC side scattered light, FL1 detector
for green fluorescence, FL3 detector for red fluorescence, NA not
npplicable, Log A logaritmic amplification
Fig. 1 Schematic summary of the experiments conducted for this study
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Fig. 2 Forward- (FSC-H) and side-scattering (SSC-H) results from FCM analyses of uninoculated unfiltered white wine (Panel a), uninoculated filtered
red wine (Panel b), and unfiltered (red) and filtered (blue) red wine inoculated with O. oeni (106 CFU ml-1) (panel c) (colour figure online)
wines (data not shown). Moreover, the autofluorescences of
LAB and of wine debris were not significantly different
(data not shown). We therefore investigated whether bacteria in wine could be labeled with fluorescent probes such
as FDA or BOX/PI.
Bacteria staining in white wine
Analysis of O.oeni, inoculated in white wine by FCM
using the BOX/PI, allows us to identify different subpopulations. The PI-negative cells with an intact cytoplasmic membrane (CM), which are considered to be
culturable cells [2, 12, 31–34], are depicted on quadrants
3 and 4 (Fig. 3). PI-positive cells (PI positive) with a
nonintact CM, which were considered to be uncultivable
cells [34, 35], are depicted on quadrants 1 and 2 of Fig. 3.
Quadrant 3 shows PI-negative/BOX-negative cells representing polarized cells with an intact CM, which were
considered to be healthy and viable [34]. Quadrant 4
shows PI-negative/BOX-positive cells representing depolarized cells with an intact CM, which were considered to
be viable but metabolically stressed (with a disrupted
electron transport system across the cell membrane) cells
[34].
As the wine contains different depolarizing factors such
as ethanol, acidic pH (3.5), sulfites and phenol products
[17, 26–28, 36–38], it was hypothesized that viable and
culturable bacteria were mostly present in quadrant 4. In
order to confirm our hypothesis, O. oeni populations during
MLF in white wine inoculated with 106 CFU ml-1 were
monitored by FCM using BOX/PI staining. A strong correlation between the bacteria numbers obtained by FCM
[BOX/PI (quadrant 4), R2 C 0.965] and those determined
by plate counts was found (Fig. 4). This confirms that in
wine most bacteria cells possess a depolarized cytoplasmic
membrane. In white wine, a strong correlation also exists
between the number of FDA-stained bacteria determined
by FCM and plate count (R2 C 0.923, Fig. 4).
We also found that the ratio of fluorescence intensity of
labeled cells (FIL) by BOX/fluorescence intensity of
unlabeled cells (FIU) (r = 30) was higher compared to
cells stained by FDA (r = 6.67, Fig. 5). This difference
allowed a much better separation of BOX-stained cells
from wine debris compared to FDA-stained cells (Fig. 5).
Although both staining methods allowed bacteria
undergoing MLF to be efficiently counted in white wine,
with a detection limit of less than 104 CFU ml-1, it was
necessary to validate our protocol for bacteria in red wine.
Quantification of O. oeni in red wine
We inoculated filtered red wine with O. oeni
(106 CFU ml-1) stained with either FDA or BOX/PI and
analyzed the suspensions by FCM and fluorescence
microscopy (FM). FCM showed that the BOX-labeled cells
were substantially more highly fluorescent than FDAlabeled cells (Fig. 6). The FCM analysis also showed that
the ratio (FIL/FIU) of the BOX-labeled cells (r = 25) was
higher than that of FDA-labeled cells (r = 8.54, Fig. 7).
We next inoculated filtered red wine with O. oeni
(106 CFU ml-1) and then analyzed samples collected
during MLF by FCM (BOX/PI, quadrant 4) and by standard plate counts. We found strong correlations between
the numbers of BOX/PI-stained cells determined by FCM
and the cell numbers determined by plate counts
(R2 C 0.97, Figs. 8, 9). Our results demonstrate that BOX/
PI staining and FCM could be applied to real-time monitoring of LAB numbers in wine undergoing MLF, which is
not possible with plate counts or other available techniques.
On the other hand, we found that the detection and
enumeration of O. oeni labeled with FDA was not efficient
enough in red wine. Indeed, a great proportion of stained
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Fig. 3 FCM analysis of O. oeni cells grown in red wine for 9 days
and stained with BOX/PI. Green fluorescence intensity is shown on
the x-axes, and red fluorescence intensity is shown on the y-axes. Dot
plot a shows the autofluorescence of unstained cells. Dot plot b shows
the fluorescence of cells after staining with BOX/PI. PI-negative cells
are contained in quadrants 3 and 4; PI-positive cells are contained in
quadrants 1 and 2. BOX-positive cells are contained in quadrants 2
and 4; BOX-negative cells are contained in quadrants 1 and 3. PI
fluorescence was measured at 630 nm (emission) and BOX at 525 nm
(emission). Hardware compensation has been applied for adjusting
the settings of the two-color analysis (BOX/PI)
Fig. 4 The correlations between the numbers of O. oeni (starters I
and II) in white wine determined by FCM and by standard plate
counts are linear. The straight lines are the linear regressions
calculated for the plots of the O. oeni counts in wine samples
determined by FCM versus those determined by plate counts. The
relationships produced high correlation coefficients (R2) of 0.923 with
FDA staining and 0.965 with BOX/PI staining (quadrants 4)
cells could not be differentiated from unstained cells
(Fig. 7). We attempted to improve the FDA accessibility of
the cells in red wine using different washing methods (PBS
with and without Triton X-100) but found that it did not
improve staining efficiency (data not shown).
this reason, we assessed whether it was possible to discriminate these two microorganisms by FCM analysis
using the scattering parameters.
Flow cytometry analysis of mixed cultures of malolactic
bacteria and yeasts inoculated in red wine revealed that the
size and the granularity of yeast is different from bacterial
cells and wine debris, allowing yeast to be separated from
bacteria cells and debris into two clearly distinguishable different zones based on light-scattering parameters (Fig. 10).
These differences can be exploited to efficiently gate the
specific cell types, allowing yeast cells and malolactic bacteria
to be counted and separated from wine debris in a single
analysis after they have been labeled with BOX/PI.
Quantification of O. oeni in co-culture
with S. cerevisiae during AF and MLF
MLF traditionally occurs shortly after the end of AF, but in
current winemaking trends yeast and malolactic bacteria
are co-inoculated at the start of AF. In such conditions,
both yeast and bacteria could be stained by BOX/PI. For
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Fig. 5 FCM histograms of O. oeni cells grown in white wine and
stained with FDA or BOX. Green fluorescence intensity (GRN-HLog)
is represented on the x-axis, and cell counts are represented on the yaxis. Panel a shows the fluorescence of O. oeni before (red arrow;
autofluorescence) and after (blue arrow) staining with FDA. Panel
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b shows the fluorescence of O. oeni before (red arrow; autofluorescence) and after (blue arrow) staining with BOX. O. oeni cells stained
with BOX are more highly fluorescent than those stained with FDA
(colour figure online)
Fig. 6 Fluorescence
microscopy of O. oeni cells
stained with FDA (a) and BOX
(b). O. oeni was cultured in red
wine. Magnifications: 9100
We monitored two different co-cultures and compared
the FCM results for S. cerevisiae and O. oeni to those
obtained by standard plate counts. The cell numbers
determined by FCM for both cell types correlated well with
those obtained by plate count methods (R2 C 0.97,
Fig. 11).
After co-inoculation, the S. cerevisiae populations
increased and reached their maxima ([107 cells ml-1)
after 2 days of growth. After day 7, the population
decreased (Fig. 12).
During the growth phase of S. cerevisiae, the O. oeni
populations decreased and stabilized rapidly during the first
days of AF (between 5.105 and 106 CFU ml-1 for days
1–22). After the S. cerevisiae populations decreased (at
sugar concentrations \1 g l-1), the O. oeni populations
increased from day 22 to 8.106 CFU ml-1, and malic acid
degradation signaled the beginning of MLF.
To assess whether O. oeni could be discriminated from
other bacteria present in wine using FCM, we spiked wine
containing O. oeni with either P. damnosus or L. plantarum
and analyzed the light-scattering characteristics of the cell
mixtures by FCM. The results showed that it was not
possible to discriminate between the different types of
bacteria by analyzing the light-scattering properties of the
cells (data not shown).
Discussion
The ability to use a single instrument to rapidly conduct
numerous microbiological assays offers obvious advantages for the wine industry over current methods in which
culturing, microscopy or several dedicated instruments are
needed. While cytometry-based methods exist to monitor
yeast growth and viability during alcoholic fermentation in
wine, there is no fast, efficient and affordable method that
allows counting bacteria in white and red wines. Wine is a
particular medium in that it contains numerous particles
(positive signal by FCM using light-scattering parameters).
Thus, care should be taken in FCM analyses because these
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Fig. 7 FCM histograms of O. oeni cells grown in red wine and stained
with FDA or BOX. Green fluorescence intensity (GRN-HLog) is
represented on the x-axis, and cell counts are represented on the y-axis.
Panel a shows the fluorescence of O. oeni before (red arrow; auto-
Fig. 8 The correlation between the numbers of O. oeni (starters I and
II) in red wine determined by FCM and by standard plate counts is
linear. The straight line is the linear regression calculated for the
plots of the O. oeni counts in red wine samples determined by FCM
(BOX/PI, quadrant 4) versus those determined by plate counts. The
relationship produced a high correlation coefficient (R2) [ 0.97
particles are similar in size and density to bacteria and can
produce misleading signals, especially in unfiltered wine.
However, in this study, experiments were conducted in
sterilized wine, i.e., free of particles, inoculated with yeast
and bacteria. While bacteria could be separated from yeast
in filtered wine because of the difference in their size and
granularity; in the case of unfiltered wine, we found that it
was not possible to discriminate between bacteria and wine
debris by FCM using light-scattering parameters alone. For
this reason, in order to count bacteria, cells need to be
stained.
Malacrinò [22] previously showed that among various
fluorescent dyes—rhodamine, calcein acetoxymethyl
ester,
20 7 0 -bis(carboxyethyl)-5(6)-carboxyfluorescein
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fluorescence) and after (blue arrow) staining with FDA. Panel b shows the
fluorescence of O. oeni before (red arrow; autofluorescence) and after
(blue arrow) staining with BOX. O. oeni cells stained with BOX are more
highly fluorescent than those stained with FDA (colour figure online)
Fig. 9 Malic acid degradation versus growth of O. oeni (starter I) in
red wine analyzed by FCM (BOX/PI, quadrant 4) and by plate count
method. Error bars indicate the SDs of three independent
experiments
Fig. 10 Forward-scatter (FSC-H) and side-scatter (SSC-H) analysis
of S. cerevisiae PB 2585 (M1) and O. oeni (starter I) (M2) in a ratio of
1:1
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Fig. 11 The correlation between the numbers of O. oeni (starters I)
determined by FCM and by standard plate counts is linear. The
straight line is the linear regression calculated for the plots of the O.
oeni counts present in S. cerevisiae determined by FCM (BOX/PI
staining, quadrant 4) versus those determined by plate counts. The
relationship produced a high correlation coefficient (R2) [ 0.97
Fig. 12 Malic acid consumption versus growth of O. oeni (starter I)
and S. cerevisiae. Cell counts were determined by FCM analysis.
Error bars indicate the SDs of three independent experiments
acetoxymethyl ester and fluorescein diacetate—the highest
fluorescence intensity was obtained with FDA. However,
FDA did not stain all strains of O. oeni, which indicated
that the use of this dye alone was unsuitable for enumerating bacteria in wine [22]. In addition, we demonstrate
here that phenolic compounds can hamper bacteria labeling
in red wines, as has been shown for other wine microorganisms [39]. Despite the use of different washing methods
(PBS with and without Triton X-100), we were not able to
efficiently stain bacteria with FDA in red wines. For these
reasons, we investigated BOX/PI labeling, which has proven useful for detecting bacteria in different physiological
states [40]. BOX is a anionic stain that binds to the CM
only if it is depolarized. The good correlation coefficient
between the plate counting and the FCM (quandrant 4)
shows that cells are in a depolarized condition, which is
due to the presence of some wine components such as
ethanol, acidic pH (3.5), sulfites and phenolic compounds
that affect the physical and chemical properties of the
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cytoplasmic membrane of LAB and which affect the
membrane potential [17, 26–28, 36, 38].
We demonstrate that this staining has several advantages
over FDA: (1) a higher fluorescence intensity that allows
clear separation of stained bacteria from debris even in red
wines; (2) this staining allows the labeling of all tested
bacteria; (3) the double staining provides information on
the physiological state of bacteria in wine.
Furthermore, our protocol allows labeling of yeast.
Indeed, yeasts are easily stained with BOX/PI [41]. The
growth kinetics of these yeast and bacteria during coculture agrees with a previous report in which cell numbers were determined by plate counts [42]. This is very
interesting in wine, since yeast and bacteria are naturally
present together in wine during either alcoholic fermentation or malolactic fermentation [43]. Moreover, inoculating grape musts with wine yeast and lactic acid bacteria
(LAB) concurrently in order to induce simultaneous
alcoholic fermentation (AF) and malolactic fermentation
(MLF) is a common trend nowadays [44]. Thus, our
method allows monitoring both yeast and and bacteria in
real-time during alcoholic and malolactic fermentation in
white and red wine. This is a real advantage; if MLF is
found to be sluggish or stuck, re-inoculation may be
needed. Delaying re-inoculation by a week, especially at
low SO2 levels, is detrimental to wine quality. With FCM,
the number of viable O. oeni cells in wine can be determined in 20 min, even in the presence of [108 yeast
cells ml-1. This rapid procedure is therefore a suitable
method for monitoring O. oeni populations during winemaking and offers a detection limit of \104 CFU ml-1. In
contrast to classical microbiology techniques and molecular biology methods, which present constraints in terms
of time and cost, FCM allows the timely application of
corrective measures to regulate bacterial growth and
improve the control of MLF in wine.
Must or wine may also contain acetic acid bacteria or
other LAB such as Pediococcus damnosus or some Lactobacillus plantarum [45]. However, our methods do not
address the presence of other microorganisms that are
found in wine, such as the spoilage bacteria P. damnasus
and some L. plantarum. Despite this disadvantage, our
staining and FCM methods allow O. oeni to be followed in
musts or in wine and can be used to determine the viability
of O. oeni and Saccharomyces cerevisiae populations
during AF and MLF in cases of inoculated or natural fermentations. Unfortunately, in cases of contamination, such
as those encountered in case of stuck fermentation, these
methods cannot be used to distinguish between O. oeni and
the other types of spoilage bacteria. However, this is not a
serious issue during fermentation because normally these
bacteria only cause spoilage of wine during aging in the
cellar and after bottling [1].
123
72
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