Selection of yeasts with multifunctional features for application as
starters in natural black table olive processing
S. Bonatsou1, A. Benítez2, F. Rodríguez-Gómez2, E.Z. Panagou1, F.N. Arroyo-López2,*
1
Laboratory of Microbiology and Biotechnology of Foods, Department of Food Science
and Human Nutrition, Agricultural University of Athens, Iera Odos 75, Athens, Greece,
GR-11855.
2
Food Biotechnology Department. Instituto de la Grasa (CSIC). Avda\ Padre García
Tejero nº4, 41012, Seville. Spain.
Running title: Olive yeasts as multifunctional starters
Corresponding author: F.N. Arroyo-López, Ph.D. Tel: 0034 954692516 ext 115.
FAX: 0034954691262. e-mail: fnarroyo@cica.es.
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1
Abstract:
2
Yeasts are unicellular eukaryotic microorganisms with a great importance in the
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elaboration on many foods and beverages. In the last years, researches have focused
4
their attention to determine the favourable effects that these microorganisms could
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provide to table olive processing. In this context, the present study assesses, at
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laboratory scale, the potential technological (resistance to salt, lipase, esterase and β-
7
glucosidase activities) and probiotic (phytase activity, survival to gastric and pancreatic
8
digestions) features of 12 yeast strains originally isolated from Greek natural black table
9
olive fermentations. The multivariate classification analysis carried out with all
10
information obtained (a total of 336 quantitative input data), revealed that the most
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promising strains (clearly discriminated from the rest of isolates) were Pichia
12
guilliermondii Y16 (which showed overall the highest resistance to salt and simulated
13
digestions) and Wickerhamomyces anomalus Y18 (with the overall highest
14
technological enzymatic activities), while the rest of strains were grouped together in
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two clearly differentiated clusters. Thus, this work opens the possibility for the
16
evaluation of these two selected yeasts as multifunctional starters, alone or in
17
combination with lactic acid bacteria, in real table olive fermentations.
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Keywords: Enzymatic spectrophotometric assays; Growth modelling; Multifunctional
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starters; Principal component analysis; Table olives; Yeasts.
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1. Introduction
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Table olives are one of the most important and well known fermented vegetables
22
of the food industry, with an estimated worldwide production that currently exceeds 2.5
23
million tons/year (IOC, 2013). The elaboration of this food is closely related to the
24
culture and diet of many Mediterranean countries, with Spain, Turkey, Egypt, Greece
25
and Italy as the main producers. There is also important production in the USA, Peru,
26
Argentina and Australia. Thus, table olive processing is widespread around the world
27
and represents an important economic source for producing countries. The most usual
28
table olive elaborations are: a) alkali-treated green olives (the so-called Spanish style),
29
b) ripe olives by alkaline oxidation (Californian style), and c) naturally black olives
30
(also known as Greek style) (Garrido-Fernández et al., 1997).
31
Microorganisms, especially lactic acid bacteria and yeasts, play an important
32
role during fermentation of the olive fruit determining the safety, quality and flavour of
33
the final product (Garrido-Fernández et al., 1997). For many years, the search for
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starters with application in olive fermentation has been practically focused on the
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activity of lactic acid bacteria. However, in the last years, diverse publications have
36
emphasised the importance of selection of yeasts as starter cultures during table olive
37
processing (Silva et al., 2011; Arroyo-López et al., 2012; Rodriguez-Gómez et al.,
38
2012; Bevilacqua et al., 2012, 2013; Tofalo et al., 2013). Although these
39
microorganisms can cause spoilage of the product due to the production of CO2, bad
40
odours and flavours, clouding of brines or softening of fruits, which is especially
41
harmful in olive packaging or storage, they also show some desirable activities with
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important potential technological and probiotic applications. For this reason, yeasts may
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be exploited in table olive processing as multifunctional starters.
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In this context, several authors have studied, among others, the lipolytic (lipase
45
and esterase) and β-glucosidase activities (technological characteristics) of different
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yeast species related to table olives or oleic ecosystems (Psani and Kotzekidou, 2006;
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Hernández et al., 2007; Bevilacqua et al., 2009, 2012; Aponte et al., 2010; Romo-
48
Sánchez et al., 2010; Bautista-Gallego et al., 2011; Rodriguez-Gómez et al., 2012). It
49
has also been widely proven that many yeast species have excellent aromatic profiles,
50
can improve lactic acid bacteria growth and inhibit undesirable microorganisms (Psani
51
and Kotzekidou, 2006; Querol and Fleet, 2006; Arroyo-López et al., 2012). Recently,
52
the probiotic potential of table olive related yeasts has also begun to be evaluated (Psani
53
and Kotzekidou, 2006; Silva et al., 2011). However, most of the available information
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until now comes only from qualitative tests carried out on agar-assays, which do not
55
facilitate the comparison and selection of the most appropriate yeast starters. On the
56
contrary, spectrophotometric assays have been developed to quantitatively determine
57
the yeast activity levels for several groups of enzymes (lipases, esterases, β-
58
glucosidades and phytases, among others) (Rosi et al., 1994; Haros et al., 2005;
59
Ciafardini et al., 2006; Rodríguez-Gómez et al., 2012) or to determine the resistance of
60
microorganism to salt by mathematical modelling (Romero-Gil et al., 2013). These
61
methods are easily applicable and inexpensive; they do not need complex instruments
62
and offer objective information on yeast reponse for comparison.
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Another additional problem is the application of an appropriate methodology for
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the management of such a large amount of data, necessary when researchers have to
65
analyze several physiological traits (variables) from a considerable number of strains
66
(cases). Multivariate analysis techniques offer an interesting approach to solve this
67
drawback. Principal component analysis (PCA) is a multivariate statistical technique
68
used for data compression, to capture the main features in the multivariate data sets and
4
69
to extract information from them. PCA implies a mathematical procedure that
70
transforms the overall set of original variables into a smaller number of mathematical
71
“constructs”, also called “factors”. Thereby, a new set of axes, called factor axes, is
72
obtained in a lower dimensional space onto which the original space of variables and
73
cases can be projected and classified into categories. Such factors can be viewed as
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linear combinations of the original variables that are uncorrelated (Jackson, 1991). The
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new variables thus generated account for the inherent variation of the data to the
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maximum possible extent.
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In this work, diverse methodologies (growth modelling, spectrophotometric
78
enzymatic assays and in vitro probiotic tests) have been applied to assess the potential
79
technological (resistance to salt, lipase, esterase and β-glucosidase activities) and
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probiotic (phytase activity and resistance to gastric, pancreatic and overall digestions)
81
applications of a considerable number of yeast species never before studied in Greek
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natural black table olive processing. One way ANOVA and multivariate analysis based
83
on PCA were then applied to this quantitative set of data to select the yeast strains with
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the most promising global characteristics for their use as multifunctional starters.
85
2. Material and methods
86
2.1. Yeast strains
87
A total of 12 yeast strains (Pichia guilliermondii Y16, Pichia kluyveri Y17,
88
Wickerhamomyces anomalus Y18, Candida silvae Y19, Metschnikowia pulcherrima
89
Y20, Saccharomyces cerevisiae Y22, Pichia manshurica Y37, Rhodotorula
90
mucilaginosa Y38, Rhodotorula diobovatum Y39, Aereobasidium pullulans Y40,
91
Debaryomyces hansenii Y57 and Pichia membranifaciens Y67), representative of the
5
92
yeast microbiota usually found in Greek natural black table olives, were used in the
93
present study. All of them were previously isolated by Nisiotou et al. (2010) from
94
distinct phases (early, middle and final stages) of the spontaneous fermentation of
95
naturally black cv. Conservolea olives, and were identified at the species level by PCR-
96
restriction fragment length polymorphism (RFLP) of the 5.8S internal transcribed
97
spacer (ITS) region combined with sequence analysis of the D1/D2 domain of 26S
98
gene. The previous mentioned work was focused only on the identification of the
99
succession of yeasts species during the fermentation of natural black olives, and for this
100
reason, only one strain per species was randomly selected and deposited in the
101
microbiological collection of the Laboratory of Microbiology and Biotechnology of
102
Foods of the Agricultural University of Athens (Greece). Their sequences were also
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deposited in the NCBI GenBank data library under accession numbers FJ715430,
104
FJ649188 to FJ649197 and GQ140297 to GQ140301.
105
2.2. Modelling the resistance of yeasts to salt
106
Yeast inocula were prepared by inoculating one single colony of each isolate
107
into 5 mL of YM broth medium (DifcoTM, Becton and Dickinson Company, Sparks,
108
USA). After 48 h of incubation at 30ºC, 1 mL from each tube was centrifuged at 9000 x
109
g for 10 min, the pellets were washed with sterile saline solution (9 g/L), centrifuged
110
and re-suspended again in 0.5 mL of a sterile saline solution to obtain a final
111
concentration of about 7.2 log10 CFU/mL, which was confirmed by surface spread on
112
YM agar. These yeast suspensions were used to inoculate the different modelling
113
experiments.
114
Growth was monitored in a Bioscreen C automated spectrophotometer
115
(Labsystem, Helsinki, Finland) with a wideband filter (420-580 nm). Measurements
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116
were taken every 2 h after a pre-shaking of 5 s. The wells of the microplate were filled
117
with 20 µL of inoculum and 330 µL of medium (according to treatment as described
118
below), always reaching an initial OD of approximately 0.2 (inoculum level above 6
119
log10 CFU/mL). The inocula were always above the detection limit of the apparatus,
120
which was determined by comparison with a previously established calibration curve.
121
Uninoculated wells for each experimental series were also included in the microplate to
122
determine, and consequently subtract, the noise signal. All experiments were carried out
123
in triplicate.
124
Sterilized YM broth was supplemented with NaCl to obtain the following final
125
concentrations of salt in the media: 0, 5, 10, 20, 30, 50, 70, 90, 110, 140, 180, 200 and
126
250 g/L. Thus, a total of 468 growth curves (13 levels NaCl x 12 yeasts x triplicate)
127
were obtained. The use of a well known, standardized synthetic laboratory medium to
128
carry out the experiments was preferred because, in the olive matrix, the presence of
129
diverse components released by fruits such as polyphenols, organic acids, etc., may
130
mask the real inhibitory effect of NaCl.
131
The basis of the technique used for estimating the NIC (non-inhibitory
132
concentration) and MIC (minimum-inhibitory concentration) values of the assayed yeast
133
strains for NaCl was the comparison of the area under the OD/time curve of a positive
134
control (absence of salt, optimal conditions) with the areas of the tests (presence of salt,
135
increasing inhibitory conditions). As the amount of inhibitor in the well increases, the
136
effect on the growth of the organism also increases. This effect on growth is manifested
137
by a reduction in the area under the OD/time curve relative to the positive control at any
138
specified time. The areas under the OD/time curves were calculated by integration using
139
OriginPro 7.5 software (OriginLab Corporation, Northampton, USA). The relative
7
140
amount of growth for each NaCl concentration, denoted as the fractional area (fa), was
141
obtained using the ratios of the test area (areatest) to that of the positive control of the
142
yeast (areacont), according to the following formula:
143
fa = (areatest)/(areacont)
144
The plot of the fa versus the natural logarithm (ln) of the NaCl concentration
145
produced a sigmoid-shape curve that could be well-fitted with a reparameterized
146
modified Gompertz function for decay, which had the following expression:
147
y=exp(-(x/(ln(MIC)/exp(-(ln(ln(NIC)/ln(MIC))/2.71828))))^(-2.71828/(ln(ln(NIC)/ln(MIC)))))
148
where y is the dependent variable (fa), x is the independent variable (ln NaCl g/L), MIC
149
is the minimum NaCl concentration (g/L) above which growth is not observed, and NIC
150
is the NaCl concentration (g/L) above which a inhibitory effect begin to be observed.
151
These parameters were obtained by a non-linear regression procedure, minimizing the
152
sum of squares of the difference between the experimental data and the fitted model,
153
i.e., loss function (observed-predicted)2. This task was accomplished using the non-
154
linear module of the Statistica 7.1 software package (StatSoft Inc, Tulsa, OK, USA) and
155
its Quasi-Newton option. Fit adequacy was checked by the proportion of variance
156
explained by the model (R2) with respect to the experimental data.
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2.3. In vitro gastric and pancreatic digestions
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Simulated gastric digestion (GD) was performed using the protocol initially
159
described by Corcoran et al. (2007) with slight modifications. Briefly, synthetic gastric
160
juice was prepared in a buffer solution at pH 2.0 containing NaCl (2.05 g/L), KH2PO4
161
(0.60 g/L), CaCl2 (0.11 g/L) and KCl (0.37 g/L). It was adjusted to pH 2.0 with 1 M
8
162
HCl and autoclaved at 121 ºC for 15 min. Prior to use, pepsin (0.0133 g/L) and
163
lysozyme (0.01 g/L) were added. All the components were obtained from Sigma-
164
Aldrich (St. Louis, USA). The yeast cultures to be tested were grown to early stationary
165
phase, centrifuged (10,000 x g, 10 min) and the pellet was washed with the buffer (pH
166
2.0) mentioned above. Then, the cells were re-suspended in the synthetic gastric juice to
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a final concentration around 7 log10 CFU/mL and incubated for 2.5 h at 37 ºC in an
168
orbital shaker (~200 rpm) to simulate peristaltic movements. Finally, serial dilutions of
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the cultures were plated onto YM agar medium and counted after incubation at 30 ºC
170
for 2 days.
171
Simulated pancreatic digestion (PD) was formulated using bile (3.0 g/L, Oxoid
172
LTD, Basingstoke, England) and pancreatin (0.1 g/L, Sigma-Aldrich) in a buffer at pH
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8.0 (adjusted with 1M HCl) consisting of 50.81 g/L of sodium phosphate dibasic
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heptahydrate and 8.5 g/L of NaCl. Harvested cells from the previous GD step were
175
washed in saline and re-suspended in the same volume of the simulated pancreatic juice.
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A colony count on YM agar plates at initial time, to know the initial counts in the
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freshly prepared simulated pancreatic juice, was performed by serial dilutions of the
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cultures. After shaking at 200 rpm in an orbital shaker during 3.5 h at 37 ºC, the pellet
179
was washed and then re-suspended in a volume of isotonic solution in order to avoid
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carryover of the buffers to the agar. Serial dilutions were done, and subsequently plated
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onto YM agar. A reference probiotic strain (Lactobacillus rhamnosus GG), was used for
182
comparison of the survival rates after simulated GD and PD, but using MRS (de Man,
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Rogosa and Sharpe) (Oxoid) as culture medium. The use of a bacterium was preferred
184
instead a yeast because they are the most common probiotic microorganisms found in
185
the literature. Overall survival was obtained by comparison of the initial yeast counts
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186
(CFU/mL) at the beginning of the simulated GD and those cells recovered at the end of
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the simulated PD.
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2.4. Assessment of the enzymatic activities
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Before enzymatic tests, the 12 yeast cultures were previously refreshed on YM
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agar. After 48 h of incubation at 30ºC, colonies were picked and directly used to
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inoculate 5 mL of new fresh YM broth. These tubes were then incubated at 30 ºC for 2
192
days and agitated daily for 1 min with a vortex. Then, cells were separated by
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centrifugation at 9,000 x g for 15 min. The supernatant was sterilized through
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microfiltration using a sterile syringe-driven filter unit with 0.2 µm of porosity
195
(Millipore Co., Bedford, Massachusetts, USA) and used as the extracellular fraction. At
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the same time, the cell pellets were washed twice in a sterile 50 mM phosphate buffer
197
(pH 7.0) to remove liquid culture media for lipase and esterase, in a 100 mM citrate-
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phosphate buffer (pH 5.0) for β-glucosidase, or in a buffer sodium acetate-acetic acid
199
0.1M (pH 5.5) for phytase determinations. Finally, cells were re-suspended in a suitable
200
volume of the corresponding sterile buffer solution to reach a population level between
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7 and 8 log10 CFU/mL, according to yeast species. Both supernatant and whole cells
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were used for the enzymatic tests described below.
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β-glucosidase, esterase and lipase activities were quantitatively determined in
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duplicate following procedures already mentioned by several authors (Rosi et al., 1994;
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Ciafardini et al., 2006; Costas et al., 2007; Rodríguez-Gómez et al., 2010, 2012) with
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slight modifications. Briefly, these activities were evaluated by measuring the amount
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of p-nitrophenol liberated from the following chromogenic substrates: p-nitrophenyl
208
stearate (Sigma–Aldrich) and 4-nitrophenyl palmitate (Fluka Chemical, Buchs,
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Switzerland) for lipase determination, p-nitrophenyl butyrate (Sigma-Aldrich) for
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esterase, and p-nitrophenyl-β-D-glucoside (Sigma-Aldrich) for β-glucosidase assays.
211
For lipase and esterase determinations, the corresponding chromogenic
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substrates were dissolved in undecane to reach a final concentration of 1 mM. The
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reactions were carried out in a biphasic system formed by 1 mL of the
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substrate+undecane mix (organic phase) and 1 mL of the extracellular or cellular
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fractions (aqueous phase). For β-glucosidase evaluation, 0.2 mL of the cellular or
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supernatant fraction was mixed with another 0.2 mL of a solution formed by the
217
corresponding chromogenic substrate dissolved in 100 mM of a citrate-phosphate buffer
218
to reach a final concentration of 5 mM. After 24 h of incubation at 30ºC for lipase and
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esterase, or only 1 h at 40°C for β-glucosidase, 0.2 M carbonate buffer (pH 10.2) was
220
added to stop the reaction. The concentration of liberated p-nitrophenol was estimated
221
from the absorbance obtained at 410 (lipase and esterase) or 400 nm (β-glucosidase) in
222
a spectrophotometer model Cary1E UVevis (Varian INC., Palo Alto, CA, USA) using a
223
suitable blank for each case. Results were expressed as the amount of enzyme liberating
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1 nmol of p-nitrophenol per hour and milliliter (nmol h-1 mL-1) under the assay
225
conditions for both extracellular and cellular fractions.
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Phytase activity was determined by measuring the amount of liberated inorganic
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phosphate from sodium phytate using the protocol described by Haros et al. (2005), but
228
with slight modifications. The reaction mixture consisted of 0.5 mL of 0.1 M sodium
229
acetace-acetic acid (pH 5.5), containing 6 mM sodium phytate and 0.5 mL of sample
230
solution. After incubation at 50ºC for 60 min, the reaction was stopped by adding 0.25
231
mL of 20% (w/v) trichloroacetic acid (TCA) solution. The reaction was cooled in ice for
232
15 min and then centrifuged at 9,000 x g for 10 min. Then, 0.9 mL of the aqueous phase
11
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was mixed with 0.96 mL of phosphorus reagent (Mo-Va:5N H2SO4:acetone in 1:1:2
234
proportion). After 10 min of incubation at room temperature, absorbance was measured
235
at 405 nm. One unit of phytase activity was defined as the amount of enzyme liberating
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1 nmol of inorganic phosphorous per hour and milliliter (nmol h-1 mL-1) under the assay
237
conditions for both extracellular and cellular fractions.
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Finally, commercial lipase (from porcine pancreas), esterase (from porcine
239
liver), β-glucosidase (from almonds) and phytase (from wheat) enzymes were purchased
240
from Sigma-Aldrich (references L3126, E3019, G0395 and P1259, respectively), and
241
used in the present study at a final concentration of 5 mg/L as internal control for
242
comparison with the yeast activities.
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2.5. Statistical data analysis
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An analysis of variance was performed by means of the one-way ANOVA module
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of Statistica 7.1 software (Statsoft Inc., Tulsa, USA) to check for significant differences
246
among yeast strains for the different technological and probiotic tests. For this purpose,
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a post-hoc comparison statistical test was applied by means of the Scheffé test, which is
248
considered to be one of the most conservative post-hoc tests (Winer, 1962).
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A total of 336 quantitative input data were then subjected to multivariate analysis.
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PCA was applied to discriminate yeast strains with highly desirable properties, using a
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varimax rotation. For the selection of the number of Principal Components or Factors,
252
the Kaiser criterion (Jolliffe, 1986) was followed and only factors with eigen-values
253
higher than 1.00 were retained. Cases introduced in the analysis were the 12 assayed
254
yeast strains, while explanatory variables were: NIC and MIC values, survival to
255
gastric, pancreatic and overall digestions (GS, PS and OS, respectively), and cellular
12
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lipase (L-C), extracellular lipase (L-E), cellular esterase (E-C), extracellular esterase (E-
257
E), cellular β-glucosidase (B-C), extracellular β-glucosidase (B-E), cellular phytase (P-
258
C) and extracellular phytase (P-E) activities. Statistica software version 7.1 was used for
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data processing and graphic representation.
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3. Results
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3.1. Susceptibility and resistance of the assayed yeasts to salt
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In this survey, a total of 468 OD curves were obtained in synthetic laboratory
263
media to estimate the effect of NaCl concentration on the growth of 12 table olive
264
related yeasts isolated from the fermentation of Greek natural black table olives. Data
265
were fitted using the reparameterized Gompertz equation for decay, with an R2 in many
266
cases above 0.95 (data not shown). As an example, Figure 1 shows the fit for Y40 yeast
267
(A. pullulans), which followed a typical sigmoid decay function. Consequently, yeast
268
response to NaCl was non-linearly dose related. The whole sigmoid-shaped curve for
269
this microorganism could be divided into three sections: i) points corresponding to
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concentrations from zero up to the NIC (concentrations at which no effect of the
271
inhibitor was observed and fa was around 1), ii) concentrations between NIC and MIC
272
values (within which growth inhibition progressively occurred and the fa decreased),
273
and iii) a third section above MIC (where no growth relative to the control was recorded
274
and fa was around 0).
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Table 1 shows the NIC and MIC values obtained for all the yeasts assayed by
276
this methodology. For each species, average values were obtained from three
277
independent experiments. The NIC value, related to salt susceptibility, was widespread
278
among yeast strains and ranged from 20.2 (P. membranifaciens Y67) to 109.9 g/L (P.
13
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guillidermondii Y16), while the MIC value, related to salt resistance, ranged from 123.7
280
(R. mucilaginosa Y39) to 274.4 g/L (S. cerevisiae Y22). Thereby, according to values
281
shown in Table 1, yeasts Y16 and Y22 were the most resistant microorganisms to salt in
282
laboratory medium, with no statistically significant differences between them according
283
to a Scheffé post-hoc comparison test, while yeast Y40 was the less resistant.
284
3.2. Resistance of the assayed yeasts to in vitro digestions
285
Table 2 shows the survival (%) of all assayed yeasts to the simulated in vitro
286
gastric and pancreatic digestions, as well as for the probiotic bacterium (L. rhamnosus
287
GG) used as control. All yeast isolates showed a survival percentage to the gastric
288
digestion higher than the reference probiotic microorganism, which had a survival of
289
only 0.04%. Two strains, P. guillidermondii Y16 and D. hansenii Y57, showed values
290
especially high (492.0% and 90.4%, respectively), indicative that both microorganisms
291
were not affected by the stressed conditions found in the stomach. On the contrary, C.
292
silvae Y19, R. mucilaginosa Y38 and A. pullulans Y40 were the yeasts less resistant to
293
the gastric test, with values close to 30%.
294
After GD, all yeasts were sequentially subjected to the simulated PD. In general,
295
a lower survival frequency in the PD than in the GD was noticed (Table 2). Especially,
296
two strains were considerably affected by this test (A. pullulans Y40 and D. hansenii
297
Y57), which exhibited a high mortality (survival close to 0%). On the contrary, P.
298
guillidermondii Y16, C. silvae Y19 and S. cerevisiae Y22 had values higher than 60%,
299
although only Y22 was statistically different to the probiotic control (14.4% for LGG).
300
The overall yeast survival to the simulated digestive process, comparing the
301
initial CFU/mL with the final population obtained after both gastric and pancreatic
14
302
digestions, is also shown in Table 2. Three yeast strains, P. kluyveri Y17, S. cerevisiae
303
Y22 and R. mucilaginosa Y38, were especially resistant with values around 26% and
304
statistically higher than the probiotic bacterium used as control (0.01%), while the
305
mortality for yeasts Y40 and Y57 was considerable (close to 0% survival).
306
3.3. Enzymatic activities of the assayed yeasts
307
Table 3 shows the average results obtained for the spectrophotometric enzymatic
308
assays. Data were analyzed by means of one-way ANOVA analysis to identify the yeast
309
strains with the highest levels for each enzymatic activity and compared to commercial
310
enzymes. In this way, strain W. anomalus Y18 was the yeast with the highest
311
statistically significant levels (p≤0.05) in four of six enzymatic technological activities
312
(L-C, L-E, E-E and B-C), with also high values for B-E and E-C. However, this
313
microorganism did not show any activity for the phytase tests. It can be observed that
314
the production of lipase enzymes for the majority of yeasts was practically null, except
315
for the above mentioned microorganism that was even above the commercial enzyme.
316
Table 3 also shows that some strains (Y16, Y38 and Y39) did not produce β-glucosidase
317
enzymes under the assayed conditions. However, it is clear that the production of
318
esterases was the most widerspread technological property among the yeasts.
319
Regarding phytase activity, the strain with the highest values for this test was M.
320
pulcherrima Y20 in both cellular and extracellular fractions, while many yeasts (Y18,
321
Y37, Y38, Y39) did not show any levels of activity. The great potential of Y20 to
322
produce phytase enzymes was evidenced when it was compared the commercial enzyme
323
versus the cellular fraction (796 vs 1914 nmol*ml-1*h-1, respectively). Other isolate with
324
high values in both cellular and extracellular fraction was Candida silvae Y19.
15
325
3.4. Multivariate analysis
326
In addition to specific tests, a study which simultaneously considers all of them is of
327
interest for selection of multifunctional starters. For this reason, quantitative data were
328
subjected to PCA in order to condense the information into a reduced number of
329
Factors. PCA led to the identification of four Factors with eigen-values higher than 1
330
(data not shown), indicating that the total number of analyzed variables (13) could be
331
grouped into only four Factors which explained 84.5% of the total variance (37.0% for
332
Factor 1, 22.9% for Factor 2, 16.3% for Factor 3 and 8.8% for Factor 4).
333
The relationship between the two major factors and the original variables can be
334
deduced from Figure 2 (upper panel). In this way, Factor 1 was linearly related (positive
335
correlation in Figure 2) to many of the enzymatic activities (except phytase). Thus, it
336
was re-named as “technological enzymatic activities”. On the contrary, Factor 2 was
337
mainly related (positive correlation) to resistance to digestion (GS, PS and OS) and salt
338
(MIC and NIC) tests, so it was re-named as “resistance to stress”. Figure 2 (upper panel)
339
can also be used to establish relationships among variables. According to this graph,
340
there was no relationship between “stress variables” (GS, PS, OS, NIC and MIC) and
341
“technological enzymatic activities” (L-C, L-E, B-E, E-E, E-C), because they formed an
342
angle close to 90º.
343
The projection of the cases (yeast strains) onto the planes formed by the two major
344
Factors (59.9% of the total variance) led to the segregation of several isolates clearly
345
differentiated from the rest (Figure 2, lower panel). The majority of yeasts were grouped
346
close to the intersection between both factors (one group formed by Y17, Y22, Y38 and
347
Y37, slightly in the positive axis of Factor 2, and other group formed by Y19, Y20,
348
Y39, Y40, Y57 and Y67, slightly in the negative axis of Factor 2), while two cases were
16
349
clearly located outside bouth groups. They were P. guillidermondii Y16 and W.
350
anomalus 18. The former, was characterised by its high resistance to the stress
351
conditions (salt and digestions), while the later was characterized by its considerable
352
high technological enzymatic activities.
353
4. Discussion
354
The presence of yeasts during processing of table olives around the world is very
355
common, particularly species of the genera Candida, Pichia, Rhodotorula,
356
Saccharomyces and Debaryomyces (Garrido-Fernández et al., 1997; Arroyo-López et
357
al., 2012). They can reach population levels above 6 log10 CFU/mL in this fermented
358
vegetable, affecting the organoleptic and nutritional characteristics of the final product
359
(Garrido-Fernández et al., 1997; Rodríguez-Gómez et al., 2010; Arroyo-López et al.,
360
2012). These microorganisms play especially an important role during fermentation of
361
natural black olives, where high salt levels (8-10% or even higher) are used, resulting in
362
a process that is basically dominated by yeasts and occasionally by lactic acid bacteria
363
(Heperkan, 2013). This type of table olive elaboration is very common in Greece,
364
especially at farmers’ level. Modelling data obtained in this work corroborate the high
365
resistance of these microorganisms to NaCl, with strains belonging to species P.
366
guilliermondii, P. kluyveri, S. cerevisiae and R. mucilaginosa as the most resistant
367
yeasts with MIC values above 200 g/L.
368
Today, the attention on microbiology of table olive fermentations has been given
369
almost exclusively focused on lactic acid bacteria, which stand among the most
370
important groups of microorganisms found in olive microbiota (Hurtado et al., 2012).
371
However, recent research has revealed the significant contribution that yeasts may have
372
to this fermented vegetable, and how they could improve the process and the added
17
373
value of the final product (Arroyo-López et al., 2008, 2012; Rodríguez-Gómez et al.,
374
2010). Selection of yeasts as starter cultures is a complex process including a selection
375
step, validation on laboratory scale and finally demonstration at factory level
376
(Bevilacqua et al., 2012). Potential starters must be assessed on the basis of
377
technological as well as functional traits. In this direction, the screening of an
378
appropriate number of strains is critical in successful starter development. It must be
379
noted that in this work only one strain per yeast species was subjected to technological
380
and functional characterisation. However, the information provided is important for the
381
Greek table olive industry as it refers to the most frequently encountered yeast species
382
in natural black olive fermentation and could become a basis for future research on this
383
issue.
384
Esterase and lipase enzymes (globally recognised as lipolytic activity) are
385
desirable in yeasts because they can improve the flavour of olives through the formation
386
of volatile compounds that can be generated by the catabolism of free fatty acids
387
(Hernández et al., 2007; Rodríguez-Gómez et al., 2010, 2012; Bevilacqua et al., 2012).
388
Microorganisms with β-glucosidase activities are also convenient because they can be
389
used to hydrolyze the glucoside oleuropein, removing the natural bitterness present in
390
directly brined olives, without a lye treatment (Psani and Kotzekidou, 2006; Arroyo-
391
López et al., 2012). Unfortunately, very few quantitative studies are available in the
392
literature about the influence and activity of these microorganisms on real table olive
393
fermentations (Rodríguez-Gómez et al., 2010, 2012; Bautista-Gallego et al., 2011). This
394
work offers, for the first time, quantitative information on the potential technological
395
and probiotic applications of diverse yeast species isolated from natural black Greek
396
table olive fermentation, which were then analysed using PCA for the selection and
397
discrimination of species with the most promising characteristics. Especially two
18
398
strains, W. anomalus Y18 and P. guilliermondii Y16, showed desirable features and
399
were clearly differentiated from the rest of isolates. In the last years, many researchers
400
have also used this methodology for the selection of the most promising yeast starters
401
related with table olive processing (Bevilacqua et al., 2009, 2013; Rodriguez-Gómez et
402
al., 2012).
403
The presence of W. anomalus (previously called Pichia anomala) in directly
404
brined olives, and in table olives in general, is very common (Hernández et al., 2007;
405
Bautista-Gallego et al., 2011; Arroyo-López et al., 2012; Doulgeraki et al., 2012). This
406
species is well adapted to grow under the environmental conditions that drive table olive
407
fermentations such as low pH and high NaCl concentrations. Romero-Gil et al. (2013)
408
reported similar MIC values for NaCl (166.9 g/L) for diverse W. anomalus strains
409
isolated from Spanish table olive processing compared to the isolate assayed in this
410
work (163.2 g/L). In a previous study, Hernández et al. (2007) found diverse strains of
411
this species isolated from table olive fermentations with interesting technological
412
applications. Recently, Bautista-Gallego et al. (2011) and Tofalo et al. (2013) have
413
reported the high β-glucosidase activity of this microorganism. All these features make
414
this species one of the best candidates to obtain isolates with technological applications
415
in table olives, as was also reported recently by Rodriguez-Gómez et al. (2012) and
416
Bevilacqua et al. (2013). Data obtained in this work prove again the high potential
417
technological application that this species, and especially the Y18 isolate, may have
418
during table olive processing because of its high lipase, esterase and β-glucosidase
419
activities.
420
P. guilliermondii is another yeast species usually also found in table olive
421
processing (Nisiotou et al., 2010; Tofalo et al., 2012) and according to results obtained
19
422
in this work with the Y16 isolate, showed interesting potential probiotic properties.
423
According to FAO/WHO (2001), probiotics are "live microorganisms which, when
424
administered in adequate amounts, confer a health benefit to the host". They “should be
425
resistant to gastric juices and be able to grow in the presence of bile”. There is a series
426
of in vitro tests such as acid and bile tolerance, although requiring further refinement,
427
that are usually applied as a first approach for the selection of potential probiotic
428
microorganisms (FAO/WHO, 2001). In the specific case of table olives, only Psani and
429
Kotzekidou (2006) and Silva et al. (2011) have started to assess the probiotic potential
430
of yeasts isolated from this fermented vegetable using these tests. The first authors
431
found diverse T. delbrueckii and D. hansenii strains which tolerated high bile salt
432
concentrations and low pH values, while the later authors found diverse P. fermentans
433
and C. oleophila strains with similar properties. It is remarkable to notify how many of
434
the yeast strains assayed in this work showed survival percentages to simulated
435
digestions higher than the probiotic bacterium used as control, which was especially
436
evident in the case of P. guillidermondii Y16.
437
This is the first time that phytase activity has been studied for table olive related
438
yeasts. Phytic acid or phytate is the primary storage form of phosphorous in mature
439
seeds of plants and it is abundant in legumes, oilseeds and many cereal grains. Phytate
440
has antinutritional effects because of the strong chelating capacity of this compound
441
with divalent minerals (calcium, zinc, etc.). Humans lack the required enzymes in the
442
gastrointestinal tract for the degradation of phytate complexes, but yeasts are able to
443
desphosphorylate these antinutritional compounds by the production of phytase
444
enzymes, which release free inorganic phosphate, inositol phosphate esters and
445
minerals. These enzymes are widespread in yeast species such as I. orientalis, S.
446
cerevisiae, T. delbrueckii and K. lactis (Moslehi-Jenabian et al., 2010; Olstorpe et al.,
20
447
2009), many of them usually isolated from diverse table olive processing (Arroyo-
448
López et al., 2012). However, in this work, M. pulcherrima Y20 was the strain with the
449
highest phytase activity levels in both cellular and extracellular fraction in laboratory
450
medium, followed by P. kluyveri Y17 and P. guillidermondii Y16 in the cellular
451
fraction.
452
5. Conclusions
453
The results obtained in this survey have shown that especially two isolates (W.
454
anomalus Y18 and P. guilliermondii Y16) show interesting properties for their use as
455
starters in table olive processing, the former with technological applications and the
456
later as potential probiotic agent. This information provides new perspectives for the
457
industrial sector of natural black olives and enhances the research on the impact of these
458
microorganisms in the characteristics of this fermented vegetable. The selection of the
459
most appropriate strains, in combination with/without lactic acid bacteria, could
460
transform table olives from a traditional food to a novel functional commodity with
461
multiple benefits for the consumers. Thus, the real challenge for the Greek table olive
462
industry is to address this demand of consumers and develop new products with
463
enhanced sensory and functional properties that may have an impact on human health in
464
the long run. However, further studies should be carried out to determine and validate
465
the influence of both microorganisms on industrial scale fermentations.
466
Acknowledgements
467
The research leading to these results has received funding from the Spanish
468
Government (Ramón y Cajal program), and the Junta de Andalucía (through financial
469
support to group AGR-125). S. Bonatsou and F.N. Arroyo-López wish to express
21
470
thanks to the European Erasmus program and Ramón y Cajal postdoctoral research
471
contract (Spanish Government), respectively.
472
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Figure Legends
568
Figure 1. Fit of the fractional areas of Aureobasidium pullulans Y40 as a function of ln
569
NaCl (g/L) using the reparameterized Gompertz equation for decay (see materials and
570
methods) for the estimation of NIC (non-inhibitory concentration) and MIC (minimum
571
inhibitory concentration).
572
573
Figure 2. Projection of the two major factors of the PCA as a function of variables
574
(upper panel) and yeast strains (lower panel). GS: gastric digestion, PS: pancreatic
575
digestion, OS: overall digestion, MIC: minimum inhibitory concentration, NIC: non-
576
inhibitory concentration, L-C: cellular lipase, L-E: extracellular lipase, E-C: cellular
577
esterase, E-E: extracellular esterase, B-C: cellular β-glucosidase, B-E: extracellular β-
578
glucosidase, P-C: cellular phytase, P-E: extracellular phytase.
27