Journal Pre-proofs Application of High Resolution Melting combined with DNA-based markers for quantitative analysis of olive oil authenticity and adulteration Elsa Chedid, Myrto Rizou, Panagiotis Kalaitzis PII: DOI: Reference:
S2590-1575(20)30006-7 https://doi.org/10.1016/j.fochx.2020.100082 FOCHX 100082
To appear in:
Food Chemistry: X
Received Date: Revised Date: Accepted Date:
5 September 2019 18 February 2020 18 February 2020
Please cite this article as: E. Chedid, M. Rizou, P. Kalaitzis, Application of High Resolution Melting combined with DNA-based markers for quantitative analysis of olive oil authenticity and adulteration, Food Chemistry: X (2020), doi: https://doi.org/10.1016/j.fochx.2020.100082
This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
© 2020 Published by Elsevier Ltd.
1
Application of High Resolution Melting combined with DNA-based markers for
2
quantitative analysis of olive oil authenticity and adulteration
3 4
Elsa CHEDID,1 :
[email protected]
5
Myrto RIZOU,1 :
[email protected]
6
Panagiotis KALAITZIS1* :
[email protected]
7
1
8 9
Department of Horticultural Genetics & Biotechnology, Mediterranean Agronomic Institute of Chania, Crete, Greece
*Correspondence: Dr. Panagiotis Kalaitzis, Department of Horticultural Genetics and
10
Biotechnology, Mediterranean Agronomic Institute of Chania (MAICh), Alsyllio
11
Agrokepiou,
12
P.O. Box 85, Chania 73100, Crete, Greece
13
E-mail:
[email protected]
14
Fax: +30-28210-35001
15 16
Abstract
17
A plethora of biotechnological methodologies is used to authenticate quality olive
18
oils. Among the DNA-based approaches, SNPs and SSRs combined with high
19
resolution melting (HRM) provide certain advantages such as speed, simplicity and
20
reliability. SNP-HRM and SSR-HRM were used for the detection of monovarietal
21
olive oils as well as the quantification of varietal composition in olive oil DNA
22
admixtures and olive oil blends of two different cultivars. The SSR-HRM was more
23
efficient in distinguishing monovarietal olive oils while the SNP-HRM assay was
24
more reliable in discriminating olive oil blends. HRM was also used for the detection
25
of adulteration of olive oil with oils of different plant origin by using plastid trnL
1
26
indels and SNPs. The trnL-indels-HRM showed higher discrimination power than the
27
trnL-SNP-HRM in determining adulteration in olive oil. These results indicate that
28
traceability of adulteration might be more reliable than authentication of the varietal
29
origin in olive oil blends.
30 31
Keywords: olive oil, quantitative authentication, high resolution melting, molecular
32
markers, SSRs, SNPs, adulteration, sunflower oil, maize oil
33 34
Highlights
35
The varietal composition of olive oil blends was quantified
36
Quantification of olive oil adulteration with oils of different plant origin
37
The quantitative authentication of olive oil blends has limitations
38
The SNP-HRM showed higher authentication ability for oil blends compared to
39 40
SSR-HRM SNP-HRM indicated a 5% limit of detection for varietal identification of olive oil
41 42
1. Introduction
43
Olive oil is a valuable agricultural commodity of the Mediterranean basin and is
44
considered the major component of the Mediterranean diet not only due to its health
45
benefits but also for its great nutritional value. The olive oil production has a high
46
social-economic impact, especially the extra virgin olive oil (EVOO) which is
47
considered of premium quality and possess higher prices in the market (Kalaitzis &
48
El‐Zein, 2016). The identity of such processed products is practically difficult to be
49
determined because is influenced by several factors; olive cultivars, pedoclimatic
50
conditions, environment, agricultural practices, fruit maturation and methods of 2
51
extraction of olive oil (Avramidou, Doulis, & Petrakis, 2018). Protected designation
52
of origin (PDO) and protected geographical indication (PGI) are important labels
53
referring to the quality and identity of olive oils. Therefore, authenticity and
54
traceability of high quality PDO and PGI monovarietal extra virgin olive oils is a
55
major concern for markets and consumers. A major part of authentication efforts
56
concentrate on the identification of the varietal origin as well as the adulteration with
57
oils of different plant origin.
58
DNA-based approaches are considered complementary to analytical chemistry
59
methodologies for olive oil varietal authentication due to their sensitivity, specificity
60
and reliability (Agrimonti & Marmiroli, 2019; Avramidou, Doulis, & Petrakis, 2018;
61
Lo & Shaw, 2018). In this context, various molecular markers were used for food
62
authenticity and traceability but the single nucleotide polymorphisms (SNPs) and the
63
microsatellites or single sequence repeats (SSRs) became the markers of choice for
64
olive oil traceability purposes (Bazakos, Khanfir, Aoun, Spano, Zein, Chalak, et al.,
65
2016; Montemurro, Miazzi, Pasqualone, Fanelli, Sabetta, & di Rienzo, 2015;
66
Pasqualone, Montemurro, di Rienzo, Summo, Paradiso, & Caponio, 2016). These
67
molecular markers are considered as ideal analytical targets in partially degraded
68
DNA preparations such as those of olive oil since they require the amplification of
69
short length PCR amplicons. Therefore, many studies have used the SSRs for the
70
identification of varietal origin of olive oil with various technological platforms
71
(Alba, Sabetta, Blanco, Pasqualone, & Montemurro, 2009; Ben‐Ayed, Kamoun‐Grati,
72
& Rebai, 2013; Pasqualone, Montemurro, Summo, Sabetta, Caponio, & Blanco,
73
2007).
74
Recent reports explored the potential of SNPs in olive oil varietal discrimination by
75
using various methodologies (Consolandi, Palmieri, Doveri, Maestri, Marmiroli,
3
76
Reale, et al., 2007; Reale, Doveri, Díaz, Angiolillo, Lucentini, Pilla, et al., 2006) such
77
as polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP)
78
combined with capillary electrophoresis (CE) (Bazakos, Dulger, Uncu, Spaniolas,
79
Spano, & Kalaitzis, 2012; Bazakos, et al., 2016). Moreover, a multiplex SNPs assay
80
was also used for the varietal identification of monovarietal olive oils in combination
81
with an innovative approach of fluorescence-encoded microspheres (Kalogianni,
82
Bazakos, Boutsika, Targem, Christopoulos, Kalaitzis, et al., 2015).
83
Plastid markers have also been used for the detection of adulteration of olive oil
84
(Besnard, Hernández, Khadari, Dorado, & Savolainen, 2011; Pérez-Jiménez, Besnard,
85
Dorado, & Hernandez, 2013). One of the analytical targets of extra interest is the
86
plastid trnL (UAA) intron for various reasons. The plastid trnL (UAA) intron has
87
been used as an analyte molecule to identify the identity of specific food crops
88
(Spaniolas, Bazakos, Spano, Zoghby, & Kalaitzis, 2010). It has been used in the past
89
for the identification of plant species (Spaniolas, Bazakos, Spano, Zoghby, &
90
Kalaitzis, 2010). This intron shows acceptable discrimination efficiency since it is
91
sufficiently variable among species and conserved enough within species (Taberlet,
92
Coissac, Pompanon, Gielly, Miquel, Valentini, et al., 2006). Alternatively, a set of 40
93
polymorphic loci were identified after sequencing 8 plastid genomes of olive showing
94
very low variability in olive tree cultivars (Besnard, Hernandez, Khadari, Dorado &
95
Savolainen, 2011). Such loci might be efficiently used for detection of adulteration
96
with oils of different plant origin.
97
The development of methodologies that require minimum manipulation is mandatory
98
when dealing with samples destined for authenticity testing. Therefore, the High
99
resolution melting (HRM) technology might be an approach which allows the
100
genotyping of varieties in a closed-tube reaction, without further analysis, as long as
4
101
the variants have been previously identified (Druml & Cichna-Markl, 2014). The
102
HRM analysis curves can be distinguished on the basis of their shape, due to
103
polymorphisms on single nucleotides and/or amplicon length, even though the PCR
104
products might have similar Tm values (Ganopoulos, Bosmali, Madesis, & Tsaftaris,
105
2012; Pereira, Gomes, Castro, Eiras-Dias, Brazão, Graça, et al., 2017). A barcode-
106
HRM approach was established by Madesis, Ganopoulos, Anagnostis, and Tsaftaris
107
(2012) on chloroplastic DNA to detect Lupinus adulterants present in Glycine max
108
flour. Moreover, the HRM assay combined with molecular markers allowed a quick
109
and high-throughput detection of adulteration of monovarietal olive oils (Ganopoulos,
110
Bazakos, Madesis, Kalaitzis, & Tsaftaris, 2013). In addition, the SSR-HRM approach
111
was reported to efficiently determine the traceability of olive oils (Montemurro,
112
Miazzi, Pasqualone, Fanelli, Sabetta, & di Rienzo, 2015) while recently, the SSR-
113
HRM methodology was proposed as an efficient, fast, simple and reliable approach to
114
authenticate a high number of monovarietal olive oils (Gomes, Breia, Carvalho,
115
Carnide, & Martins‐Lopes, 2018).
116
In this report, a comparative authentication and adulteration of olive oil approach by
117
using SSR- and SNP- based HRM was performed at the quantitative level. Initially,
118
HRM combined with DNA markers was used for the discrimination and quantitative
119
determination of blends of monovarietal olive oils. In this analysis, the discriminatory
120
capacity of SNPs compared to SSRs was found to be higher. Moreover, the efficiency
121
of HRM was also investigated for the detection of adulteration of olive oil with oils of
122
different plant origin. For this approach, plastid trnL (insertions/deletions) indels and
123
SNPs were used and it was found that the indels region is more efficient in the
124
discrimination of adulterants. Overall, our findings suggest that depending on the
5
125
authentication and adulteration objective, one DNA marker might provide advantages
126
over another.
127 128
2. Materials and Methods
129
2.1. Plant tissues and oil samples
130
The leaf tissue of three Greek olive varieties, Koroneiki, Tsounati and Kalamon, was
131
collected from an olive collection maintained at the Mediterranean Agronomic
132
Institute of Chania, Crete, Greece and used for DNA extraction. The monovarietal
133
olive oil samples were provided by Pamako S.A.and Kolympari SA, Chania, Crete
134
and by the Union of Agricultural Cooperatives of Lakonia, Sparta, Peloponnese.
135
Commercial maize and sunflower oils were used for the adulteration experiments.
136
For the authentication of the olive oil DNA admixtures, genomic DNA was extracted
137
from three monovarietal olive oils and diluted to equal concentrations separately.
138
Subsequently, the DNA of Koroneiki with Kalamon and Koroneiki with Tsounati
139
were blended in ratios of 50-50%, 75-25%, 85-15% and 95-5%. Monovarietal olive
140
oil DNA of each variety was also used as positive control. For the authentication of
141
olive oil blends, monovarietal olive oils of Koroneiki and Kalamon as well as
142
Koroneiki and Tsounati were mixed in ratios of 50-50%, 75-25%, 85-15% and 95-5%
143
and then DNA was extracted from the mixtures. In addition, monovarietal olive oils
144
of each variety were also used as positive controls. Finally, for the detection of olive
145
oil adulteration, two different vegetable oils were used, maize and sunflower.
146
Monovarietal Koroneiki olive oil was blended with maize and sunflower oils in ratios
147
of 99-1%, 95-5%, 90-10%, 85-15% and 75-25% and subsequently DNA extraction
148
was performed in the mixtures. The monovarietal olive oil and the 100% maize and
149
sunflower oils were used as positive controls.
6
150
2.2. Isolation of DNA from olive oil
151
Genomic DNA was extracted from leaves of the three olive varieties with a standard
152
CTAB (cetyltrimethylammonium bromide) protocol as described in Woolley, James,
153
and Manning (2001). DNA extraction from olive oil samples was performed using
154
two different methods: the CTAB/hexane/chloroform protocol developed by
155
Giménez, Pistón, Martín, and Atienza (2010) and Norgen’s Olive Oil DNA
156
Isolation Kit (Norgen Biotek co., Canada). DNA quantity and purity were estimated
157
on a Nano photometer (Pearl, Implen GmbH Munich Germany)
158
2.3. PCR amplification from olive oil DNA
159
The amplification of DNA templates comprising the SSR and SNP molecular markers
160
(Supplementary Table 1) was performed by PCR reaction in a DYAD thermocycler
161
(BIORAD) using 5x Phusion HF Buffer, 4 mM dNTP, 10 μM for each primer, 0.4
162
units of Phusion High-Fidelity DNA Polymerase (Applied Biosystems, Foster City,
163
CA) and 20 ng of olive DNA in a final volume of 25 μl. The PCR conditions were 98
164
°C for 30 seconds, followed by 45 cycles of 98 °C for 10 s, Tm of the primers for 30 s
165
and 72 °C for 30s/Kb, with a final extension step at 72 °C for 5 min. The amplicons
166
were run on a 1.5% agarose gel and purified with the QIAquick Gel Extraction Kit
167
(QİAGEN, Germany) according to the manufacturer’s instructions based on the
168
expected lentgh despite the fact that were not visualized.
169
2.4. High Resolution Melting Analysis
170
The purified PCR amplicons and the sets of primers used for their amplification were
171
also used for the subsequent HRM assays. HRM analysis was conducted in a 96-well
172
plate using the CFX Connect™ Real-Time PCR Detection System (Bio-Rad).
173
Duplicates of each sample were prepared in a final volume of 10 μL containing 2x
174
Precision Melt Supermix (Bio-Rad), 0.2 μM of each primer and 20 ng/μL of amplified
7
175
and purified template DNA. A negative control was included in each assay. An initial
176
2 min step at 95 °C was followed by 40 cycles of 95 °C for 10 s, Tm of the primers
177
for 30s and 72 °C for 30 s. The melting curve was obtained in continuous, performed
178
as follow: 95 °C for 30 s, 65 °C for 1min rising 0.2 °C/s, 95 °C for 10 s. During the
179
incremental melting step, fluorescence data were continuously acquired. Precision
180
Melt Analysis™ Software (Bio-Rad) was used to analyze the data. After
181
normalization and temperature shift determination, the different melting curves of the
182
several plots were generated. Three biological replicates were performed for each
183
HRM assay.
184 185
3. Results
186
3.1. Detection of monovarietal olive oils using SSR- and SNP-HRM analysis
187
The major bottleneck of the DNA-based approaches for the identification of the
188
varietal origin of olive oil as well as the detection of adulteration with oils of different
189
plant origin is the isolation of adequate quality DNA for PCR amplification from the
190
oil samples. Therefore, two different methodologies were initially tested, the
191
CTAB/hexane/chloroform protocol (Giménez, Pistón, Martín, & Atienza, 2010) and
192
the Norgen kit for olive oil (Norgen Biotek, Thorold, Canada) using 600 µl (Bazakos,
193
et al., 2016) and 500 µl of olive oil sample, respectively. The Norgen DNA extraction
194
procedure required less time compared to the CTAB protocol and was considered
195
more reliable in providing olive oil DNA isolates which were more consistently
196
leading to successful PCR amplifications. Therefore, the Norgen kit was used for the
197
isolation of DNA from the monovarietal olive oils as well as their blends in order to
198
be PCR amplified and purified after fractionation in agarose gel electrophoresis.
199
Although the visualization of the PCR amplicons was not possible in the agarose gel,
8
200
the PCR products were purified as gel fragments according to their expected length
201
(Supplementary Figure 1). These purified PCR products were successfully re-
202
amplified and used for HRM analysis (Supplementary Figure 1). The same set of
203
primers was used for the initial and the additional PCR amplification for the HRM
204
analysis.
205
The olive SSR loci ssrOe-DCA3, ssrOe-DCA9, ssrOe-DCA16 and ssrOe-DCA18
206
(Sefc, Lopes, Mendonça, Santos, Machado, & Machado, 2000) were selected among
207
several others such as ssrDCA5, ssrEMO90 and ssrGAPU71 (Carriero, Fontanazza,
208
Cellini, & Giorio, 2002) because they were more consistent in the PCR amplification
209
of the SSR marker fragments. The nucleotide sequence of the SSR amplicons was
210
determined in order to validate amplification of the selected SSR loci. Representative
211
sequences of ssrOe-DCA3 and ssrOe-DCA18 which were amplified from the
212
Kalamon, Koroneiki and Tsounati are shown in Supplementary Figure 2. The HRM
213
difference plot with the ssrOe-DCA18 showed three different melting profiles of
214
various shapes, one for every variety, allowing their discrimination (Figure 1A).
215
Moreover, the HRM assay with the ssrOe-DCA3 generated two different melting
216
profiles of similar shape distinguishing the Kalamon (Tm=70.40 ˚C) from Koroneiki
217
and Tsounati both with a Tm of 70.20˚C (Figure 1B). Leaf DNA of Koroneiki was
218
used as a positive control template (Figure 1A, B).
219
The SNP1, SNP2 and SNP3 were successfully used for the determination of the
220
varietal origin of Kalamon, Koroneiki and Tsounati as was previously reported after
221
validation by sequencing of the PCR amplicons comprising these SNPs (Bazakos et
222
al., 2012; Bazakos et al., 2016).
223
The use of SNPs for HRM analysis generated two melting plots per SNP, as expected.
224
Specifically, the SNP1 and SNP3 (Bazakos, et al., 2016) discriminated Tsounati from
9
225
Koroneiki and Kalamon and Kalamon from Koroneiki and Tsounati, respectively
226
(Figure 1C, D).
227
3.2. Authentication of Olive Oil DNA admixtures using SSR- and SNP-HRM
228
analysis
229
Genomic DNA was extracted from three monovarietal olive oils and diluted to equal
230
concentrations for admixtures preparations as described in materials and methods.
231
The admixtures and the positive control samples were used for PCR amplification in
232
order to generate the templates for HRM analysis.
233
Three SSRs and three SNPs markers were used for the discrimination of the two sets
234
of admixtures in a preliminary, comparative study to determine which DNA marker
235
might be more suitable for authentication of olive oil admixtures.
236
The ssrOe-DCA18 and ssrOe-DCA16 exhibited 5 different HRM melting profiles out
237
of 6 samples for the DNA mixtures of Koroneiki-Tsounati (Figure 2A, B). The
238
melting curves of 95-5% and 85-15% ratios showed overlapping profiles and could
239
not be discriminated (Figure 2A, B). Although, curves of variable shapes were
240
generated for some ratios compared to others, the discrimination of all ratios was not
241
possible (Figure 2A, B). The SNP1 and SNP2 (Bazakos, et al., 2016) generated six
242
different melting profiles distinguishing the four ratios and the two monovarietal
243
samples generating curves of similar shape (Figure 2C, D).
244
The ssrOe-DCA9 and ssrOe-DCA18 showed 5 different HRM melting profiles out of
245
6 samples for the Koroneiki-Kalamon blends (Figure 3). The melting curves of 95-5%
246
and 85-15% ratios also showed overlapping curves and could not be discriminated
247
(Figure 3A, B). However, the SNP2 and SNP3 (Bazakos, et al., 2016) resulted in six
248
different melting profiles distinguishing the four ratios and the two monovarietal
249
samples generating curves of similar, though, distinct shapes (Figure 3).
10
250
These results indicate higher discriminatory capacity of SNPs compared to SSRs in
251
DNA admixtures. Although the monovarietal DNA samples exhibited melting curves
252
of similar shape, they were distinguished based on the Tm differences (Figure 2,
253
Figure 3). However, the discrimination of the ratios was mainly based on the shape of
254
the visualized melting profiles (Figure 2, Figure 3).
255
Moreover, the limit of detection for both DNA markers was determined at the levels
256
of 5% since the 95-5% ratios of both blends were discriminated efficiently and
257
reliably (Figure 2, Figure 3).
258
3.3. Authentication of Olive oil blends
259
Olive oil blends were prepared and DNA extraction was performed as described in
260
detail in Materials & Methods. The two-cultivar blends at four different ratios and
261
their two monovarietal oils were used for SSR- and SNP-HRM analysis.
262
Initially the ssrOe-DCA16, ssrOe-DCA18 and ssrOe-DCA9, ssrOe-DCA18 pair of
263
markers were used with blends of Koroneiki, Tsounati and Koroneiki, Kalamon,
264
respectively (Figure 4, Figure 5). The blends of 95-5% and 85-15% and those of 75-
265
25% and 50-50% showed overlapping melting profiles and therefore could not be
266
discriminated (Figure 4, Figure 5). These results indicate that blends with ratios in the
267
range between 95 to 85% and between 75 to 50% could not be distinguished by using
268
these specific pairs of SSR markers (Figure 4, Figure 5).
269
Moreover, the SNP1, SNP2 and the SNP2, SNP3 pair of markers were used with
270
blends of Koroneiki, Tsounati and Koroneiki, Kalamon, respectively (Figure 4, Figure
271
5). The blends of 95-5% and 50-50% showed distinct melting profiles and therefore
272
could be discriminated by these combinations of SNP markers (Figure 4, Figure 5).
273
However, the blends of 85-15% and 75-25% showed overlapping melting profiles and
274
therefore could not be discriminated (Figure 4, Figure 5). These results indicate that
11
275
blends with ratios in the range between 85 to 75% could not be distinguished with
276
these specific pair of SNP markers (Figure 4). Overall, the SNPs showed higher
277
capacity to distinguish olive oil blends compared to the SSR markers.
278
Representative amplification plots for the ssrOe-DCA18 and the SNP2 indicate
279
differences in the amplification efficiency but not in the shape of the plot which might
280
be attributed to the quality of the DNA template of the olive oil samples and their
281
blends considering that the same primers and similar HRM reaction conditions were
282
used for each SSR and SNP marker (Supplementary Figure 3).
283
3.4 Detection of maize and sunflower oil adulteration in extra virgin olive oil
284
Two different polymorphic molecular markers of the same chloroplastic trnL intron
285
region were used for the detection of adulteration (Spaniolas, Bazakos, Spano,
286
Zoghby, & Kalaitzis, 2010). The trnL-indels and the trnL-SNPs primers were
287
designed to amplify two different regions of this intron which can discriminate
288
between different species based on length polymorphisms and single nucleotide
289
polymorphisms, respectively (Supplementary Table 1). The trnL-SNPs amplicon was
290
comprising two SNPs (Spaniolas, Bazakos, Spano, Zoghby, & Kalaitzis, 2010).
291
DNA was extracted from the five blends for each adulterant and from the three
292
different plant species oil, and then used as a template for the amplification and the
293
HRM analysis of the two DNA markers, trnL-indels and trnL-SNPs.
294
The HRM-trnL-indels difference plots of Koroneiki with maize and sunflower
295
adulteration mixtures exhibited discrimination of all seven samples, four ratios and
296
three 100% oil samples (Figure 6). The shape of the melting profiles was similar in all
297
blends regardless of the botanical origin of the adulterant and the percentage of
298
adulteration (Figure 6 A, B).
12
299
However, the HRM- trnL-SNPs difference plots of the same samples detected five out
300
of seven samples (Figure 6C, D). The ratios of 99-1% with 95-5% and of 90-10%
301
with 85-15% showed overlapping melting profiles indicating the higher
302
discriminatory capacity of the trnL-indels marker compared to the trnL-SNPs (Figure
303
6C, D). The shape of the melting curves was different in the maize adulterant plot
304
compared to the sunflower plot (Figure 6 C, D). Moreover, in the sunflower
305
difference plot the profiles of 100% and 25% sunflower oil exhibited different shape
306
compared to the profiles of the other samples (Figure 6 C, D).
307
According to these results, the limit of detection for the HRM-trnL-indels analysis
308
was determined at the levels of 1%. For the HRM-trnL-SNPs limit of detection was
309
set at the range of 1-5% due to the overlapping curves of 99-1% and 95-5% blends
310
(Figure 6).
311
Representative amplification plots indicate differences in the efficiency of
312
amplification but not in the shape of the plots which might be explained by
313
differences in the quality of the DNA templates (Supplementary Figure 3).
314 315
4. Discussion
316
Three monovarietal olive oils were selected for varietal authentication by using SSR-
317
HRM and SNP-HRM analysis not only at the monovarietal level but also at the
318
admixtures level of various ratios between two varieties each time. Moreover, this
319
comparative study between SSRs and SNPs suggested possible advantages of one
320
DNA marker over the other depending on the authentication objective.
321
Many studies revealed the efficiency of SSR-HRM analysis for the identification and
322
differentiation of cultivars and closely related species (Bosmali, Ganopoulos,
323
Madesis, & Tsaftaris, 2012; Distefano, Caruso, La Malfa, Gentile, & Wu, 2012;
13
324
Gomes, Breia, Carvalho, Carnide, & Martins‐Lopes, 2018; Li, Xiong, He, Lu, Zhang,
325
Chen, et al., 2018; Mackay, Wright, & Bonfiglioli, 2008). In this study, one SSR
326
locus was adequate to discriminate the three olive varieties while two SNP loci were
327
required to distinguish among them. Usually more SNP loci are required in order to
328
acquire the same level of discriminatory power compared to SSRs (Avramidou,
329
Doulis, & Petrakis, 2018). Therefore, the SSR-HRM might be considered the
330
molecular marker of choice combined with HRM analysis if the objective is to
331
distinguish a higher number of monovarietal olive oils.
332
Blends of specific varieties grown in certain regions are considered premium olive
333
oils of higher value. Therefore there is a pressing need for reliable identification of the
334
genetic identity of premium quality olive oils (Kalaitzis & El‐Zein, 2016). In the
335
current study, the limit of detection of artificial DNA admixtures of two olive oil
336
cultivars was determined down to 5% for the SNP-HRM assays while for the SSR-
337
HRM assays the limit of detection ranged between 5 and 15%. This is an
338
improvement considering that Bazakos, et al. (2016) determined the limit of detection
339
of olive oil blends at the levels of 10% by using a SNP-based PCR-RFLP approach.
340
Significant differences in the discrimination accuracy of HRM analysis was detected
341
between DNA mixtures and monovarietal olive oil mixtures. The SSR-HRM assay of
342
olive oil admixtures of Koroneiki-Kalamon and Koroneiki-Tsounati revealed similar
343
results; the HRM profiles of blends of 5% and 15% ratios were overlapping as well as
344
the blends of 25% and 50% ratios indicating that there are limits in the discriminatory
345
power of the SSR markers. However, the SNP-HRM assay distinguished all ratios
346
except the 5% and 15% indicating that this analytical approach might be more
347
efficient in olive oil traceability and authenticity efforts with strong commercial
348
application potential as was previously described by Reed and Wittwer (2004). 14
349
The greatest challenges one faces while using DNA technology is the low quality and
350
highly degraded DNA recovered from the fatty matrices and the impact of oil
351
extraction processing on the size of the recovered DNA (Enferadi & Rabiei, 2013).
352
The critical steps of the extraction process that affects the most the DNA, are the
353
malaxation and separation steps where oil might be exposed to high temperatures
354
causing higher degradation of DNA. This can result in variable quality DNA isolates.
355
In these cases, a blend comprised of differentially processed monovarietal olive oils
356
might result in DNA isolates which might not be representative of the blend ratios.
357
Consequently, false estimation of DNA isolate for each variety from the blend might
358
be obtained. Thus, this might be a limiting factor for olive oil authenticity at the
359
quantitative level potentially leading to inconclusive results.
360
Various qualities of isolated DNA from monovarietal olive oils or blends might lead
361
to significant variation in the amplification plots in the HRM reactions. In addition,
362
there is the possibility that the presence of contaminants might interfere with the PCR
363
amplification leading to a reduction in the amplification efficiency (Scollo, Egea,
364
Gentile, La Malfa, Dorado & Hernandez, 2016). However, the difference plots
365
provided by the HRM software represent the melting kinetics of each PCR amplicon
366
which is affected by the SNP- or SSR-based polymorphic nature of the sequence of
367
the amplicon and is not related to the amplification plots which are affected by the
368
DNA templates per se.
369
The low quality and partially degraded DNA in olive oil samples make the
370
traceability more challenging and less accurate due to the mostly short DNA
371
templates present in the extracts. In this context, the amplicon length is important in
372
determining the outcome of PCR-based amplification of DNA templates. Therefore,
373
the shorter the amplicon is, the higher the probability of successful amplification
15
374
(Spaniolas, Bazakos, Ntourou, Bihmidine, Georgousakis, & Kalaitzis, 2008).
375
Therefore, it is suggested that the SNP-HRM might be considered the molecular
376
marker of choice compared to the SSR-HRM for authentication of olive and vegetable
377
oil blends due to the requirement for relatively shorter DNA templates.
378
DNA mixtures extracted from adequately high quality olive oil DNA samples might
379
result in the detection of the ratios of two varieties and distinguish among 5%, 15%,
380
25% and 50% by using SNP-HRM assays. However, it was suggested that CE
381
electrophoretograms are more suitable for large data sets due to many samples
382
compared to SNP-HRM because it is easier to digitalize and quantify peaks than
383
melting curves (Lian & Zeng, 2017).
384
It was demonstrated that the discrimination of various percentages of olive oil
385
mixtures is possible at limits of detection set at 5% by using this efficient, closed tube
386
HRM approach. However, mixtures which differ in the range of 10 to 25% might not
387
be possible to be discriminated regardless of high or low ratio percentages neither by
388
SSR-HRM nor by SNPs-HRM.
389
The use of plastidial trnL (UAA) intron as an analytical target to discriminate among
390
oils of different botanical origin by using HRM analysis proved to be an accurate and
391
effective approach. The various polymorphisms in this plastid DNA region among
392
different plant oils were previously reported by Spaniolas, Bazakos, Awad, and
393
Kalaitzis (2008) and Spaniolas, Bazakos, Spano, Zoghby, and Kalaitzis (2010) using a
394
CE assay indicating thus the potential use of this intron in the detection of adulteration
395
of olive oil.
396
Moreover, the HRM assay with trnL-indels locus and trnL-SNPs locus revealed a
397
limit of detection of 1% (v/v) of plant oil adulterant in olive oil. Similar results were
398
obtained by Ganopoulos, Bazakos, Madesis, Kalaitzis, and Tsaftaris (2013) which
16
399
reported a barcode-HRM analysis with an rbcL marker determining the limit of
400
detection at 1% of canola oil in olive oil. In addition, they were able to distinguish
401
different ratio admixtures of olive oil and canola.
402
In this preliminary, comparative report it was demonstrated that the trnL-indels locus
403
revealed better discrimination power than the trnL-SNPs locus, distinguishing all
404
mixture ratios, even though it requires a longer DNA template.
405
The fact that HRM analysis of DNA mixtures is more accurate compared to olive oil
406
mixtures indicates that the quantitative determination of the varietal origin of olive
407
oils has limitations which are directly related to the olive oil production process
408
and/or storage conditions. However, the SNP-based HRM approach might be
409
considered of higher discriminatory potential compared to SSR-based approaches for
410
quantitative authentication purposes.
411
The use of trnL intel-HRM analysis showed higher discrimination power than the
412
trnL SNP-HRM determining all mixture ratios of adulteration with maize oil as well
413
as sunflower oil indicating that traceability of adulteration might be more reliable
414
compared to authentication of the varietal origin of olive oil blends.
415 416
5. Conclusion
417
The authentication, traceability and adulteration of olive oil are of major importance
418
in order to monitor for fraudulent practices. The SSR-HRM and SNP-HRM assays
419
were both efficiently determined the varietal origin of monovarietal olive oils. In two
420
cultivar admixtures, SNP-HRM showed higher efficiency to discriminate olive oil
421
blends of various ratios except those of 95-5% and 85-15%. Moreover, the limit of
422
detection was determined at the level of 5% only for the SNP-HRM assay. The HRM-
423
based comparative quantitative determination of adulteration of olive oil with oils of
17
424
different plant origin indicated that the indels within the trnL region were more
425
efficient compared to trnL SNPs. The limit of detection for adulteration was
426
determined at the level of 1% in accordance with previous reports. These results
427
indicate that the quantitative validation of the varietal composition of olive oil blends
428
might be possible, though not always reliable due to variations in the processing
429
and/or storage of olive oil samples. However, the quantitative detection of
430
adulteration might be considered more efficient despite the heavily processed nature
431
of oils of plant origin.
432 433
Acknowledgements
434
This research has been financed by Greek national funds through the Public
435
Investments Program (PIP) of General Secretariat for Research & Technology
436
(GSRT), under the Emblematic Αction "The Οlive Road" (project code:
437
2018ΣΕ01300000)
438 439
Conflict of Interest Statement
440
The authors declare that there is no conflict of interest.
441 442
References
443
Agrimonti, C., & Marmiroli, N. (2019). Food Genomics for the Characterization of
444
PDO and PGI Virgin Olive Oils. European Journal of Lipid Science and Technology,
445
121(3), e1800132.
446
Alba, V., Sabetta, W., Blanco, A., Pasqualone, A., & Montemurro, C.
447
(2009).Microsatellite markers to identify specific alleles in DNA extracted from
18
448
monovarietal virgin olive oils. European food research and technology = Zeitschrift
449
fur Lebensmittel-Untersuchung und -Forschung. A, 229(3), 375-382.
450
Avramidou, E. V., Doulis, A. G., & Petrakis, P. V. (2018). Chemometrical and
451
molecular methods in olive oil analysis: A review. Journal of food processing and
452
preservation, 42(11), e13770.
453
Bazakos, C., Dulger, A. O., Uncu, A. T., Spaniolas, S., Spano, T., & Kalaitzis, P.
454
(2012). A SNP-based PCR–RFLP capillary electrophoresis analysis for the
455
identification of the varietal origin of olive oils. Food chemistry, 134(4), 2411-2418.
456
Bazakos, C., Khanfir, E., Aoun, M., Spano, T., Zein, Z. E., Chalak, L., Riachy, M. E.,
457
Abou‐Sleymane, G., Ali, S. B., & Grati Kammoun, N. (2016). The potential of
458
SNP‐based PCR‐RFLP capillary electrophoresis analysis to authenticate and detect
459
admixtures of Mediterranean olive oils. Electrophoresis, 37(13), 1881-1890.
460
Ben‐Ayed, R., Kamoun‐Grati, N., & Rebai, A. (2013). An overview of the
461
authentication of olive tree and oil. Comprehensive Reviews in Food Science and
462
Food Safety, 12(2), 218-227.
463
Besnard, G., Hernández, P., Khadari, B., Dorado, G., & Savolainen, V. (2011).
464
Genomic profiling of plastid DNA variation in the Mediterranean olive tree. BMC
465
plant biology, 11(1), 80.
466
Bosmali, I., Ganopoulos, I., Madesis, P., & Tsaftaris, A. (2012). Microsatellite and
467
DNA-barcode regions typing combined with High Resolution Melting (HRM)
468
analysis for food forensic uses: A case study on lentils (Lens culinaris). Food
469
Research International, 46(1), 141-147.
470
Carriero, F., Fontanazza, G., Cellini, F., & Giorio, G. (2002). Identification of simple
471
sequence repeats (SSRs) in olive (Olea europaea L.). Theoretical and Applied
472
Genetics, 104(2-3), 301-307. 19
473
Chen, Y., Wang, Y., Ge, Y., & Xu, B. (2005). Degradation of endogenous and
474
exogenous genes of Roundup-Ready soybean during food processing. J Agric Food
475
Chem, 53(26), 10239-10243.
476
Consolandi, C., Palmieri, L., Doveri, S., Maestri, E., Marmiroli, N., Reale, S., Lee, D.,
477
Baldoni, L., Tosti, N., & Severgnini, M. (2007). Olive variety identification by
478
ligation detection reaction in a universal array format. Journal of biotechnology,
479
129(3), 565-574.
480
Distefano, G., Caruso, M., La Malfa, S., Gentile, A., & Wu, S.-B. (2012). High
481
resolution melting analysis is a more sensitive and effective alternative to gel-based
482
platforms in analysis of SSR–an example in citrus. PloS one, 7(8), e44202.
483
Druml, B., & Cichna-Markl, M. (2014). High resolution melting (HRM) analysis of
484
DNA–Its role and potential in food analysis. Food chemistry, 158, 245-254.
485
Enferadi, S. T., & Rabiei, Z. (2013). Challenges for Genetic Identification of Olive
486
Oil. The Mediterranean Genetic Code: Grapevine and Olive, 201.
487
Ganopoulos, I., Bazakos, C., Madesis, P., Kalaitzis, P., & Tsaftaris, A. (2013).
488
Barcode DNA high‐resolution melting (Bar‐HRM) analysis as a novel close‐tubed
489
and accurate tool for olive oil forensic use. Journal of the Science of Food and
490
Agriculture, 93(9), 2281-2286.
491
Ganopoulos, I., Bosmali, I., Madesis, P., & Tsaftaris, A. (2012). Microsatellite
492
genotyping with HRM (High Resolution Melting) analysis for identification of the
493
PGI common bean variety Plake Megalosperma Prespon. European Food Research
494
and Technology, 234(3), 501-508.
495
Giménez, M. J., Pistón, F., Martín, A., & Atienza, S. G. (2010). Application of real-
496
time PCR on the development of molecular markers and to evaluate critical aspects
497
for olive oil authentication. Food chemistry, 118(2), 482-487.
20
498
Gomes, S., Breia, R., Carvalho, T., Carnide, V., & Martins‐Lopes, P. (2018).
499
Microsatellite High‐Resolution Melting (SSR‐HRM) to Track Olive Genotypes: From
500
Field to Olive Oil. Journal of food science, 83(10), 2415-2423.
501
Kalaitzis, P., & El‐Zein, Z. (2016). Olive oil authentication, traceability and
502
adulteration detection using DNA‐based approaches. Lipid Technology, 28(10-11),
503
173-176.
504
Kalogianni, D. P., Bazakos, C., Boutsika, L. M., Targem, M. B., Christopoulos, T. K.,
505
Kalaitzis, P., & Ioannou, P. C. (2015). Olive oil DNA fingerprinting by multiplex
506
SNP genotyping on fluorescent microspheres. J Agric Food Chem, 63(12), 3121-
507
3128.
508
Li, J., Xiong, C., He, X., Lu, Z., Zhang, X., Chen, X., & Sun, W. (2018). Using SSR-
509
HRM to Identify Closely Related Species in Herbal Medicine Products: A Case Study
510
on Licorice. Frontiers in pharmacology, 9, 407.
511
Lian, D. S., & Zeng, H. S. (2017). Capillary Electrophoresis Based on Nucleic Acid
512
Detection as Used in Food Analysis. Comprehensive Reviews in Food Science and
513
Food Safety, 16(6), 1281-1295.
514
Lo, Y.-T., & Shaw, P.-C. (2018). DNA-based techniques for authentication of
515
processed food and food supplements. Food chemistry, 240, 767-774.
516
Mackay, J. F., Wright, C. D., & Bonfiglioli, R. G. (2008). A new approach to varietal
517
identification in plants by microsatellite high resolution melting analysis: application
518
to the verification of grapevine and olive cultivars. Plant Methods, 4(1), 8.
519
Madesis, P., Ganopoulos, I., Anagnostis, A., & Tsaftaris, A. (2012). The application
520
of Bar-HRM (Barcode DNA-High Resolution Melting) analysis for authenticity
521
testing and quantitative detection of bean crops (Leguminosae) without prior DNA
522
purification. Food Control, 25(2), 576-582. 21
523
McDade, L. A., Daniel, T. F., Kiel, C. A., & Vollesen, K. (2005). Phylogenetic
524
relationships among Acantheae (Acanthaceae): major lineages present contrasting
525
patterns of molecular evolution and morphological differentiation. Systematic Botany,
526
30(4), 834-862.
527
Montemurro, C., Miazzi, M. M., Pasqualone, A., Fanelli, V., Sabetta, W., & di
528
Rienzo, V. (2015). Traceability of PDO olive oil “Terra di Bari” using high resolution
529
melting. Journal of Chemistry, 2015.
530
Pasqualone, A., Montemurro, C., di Rienzo, V., Summo, C., Paradiso, V. M., &
531
Caponio, F. (2016). Evolution and perspectives of cultivar identification and
532
traceability from tree to oil and table olives by means of DNA markers. Journal of the
533
Science of Food and Agriculture, 96(11), 3642-3657.
534
Pasqualone, A., Montemurro, C., Summo, C., Sabetta, W., Caponio, F., & Blanco, A.
535
(2007). Effectiveness of microsatellite DNA markers in checking the identity of
536
protected designation of origin extra virgin olive oil. J Agric Food Chem, 55(10),
537
3857-3862.
538
Pereira, L., Gomes, S., Castro, C., Eiras-Dias, J. E., Brazão, J., Graça, A., Fernandes,
539
J. R., & Martins-Lopes, P. (2017). High Resolution Melting (HRM) applied to wine
540
authenticity. Food chemistry, 216, 80-86.
541
Pérez-Jiménez, M., Besnard, G., Dorado, G., & Hernandez, P. (2013). Varietal tracing
542
of virgin olive oils based on plastid DNA variation profiling. PloS one, 8(8), e70507.
543
Reale, S., Doveri, S., Díaz, A., Angiolillo, A., Lucentini, L., Pilla, F., Martin, A.,
544
Donini, P., & Lee, D. (2006). SNP-based markers for discriminating olive (Olea
545
europaea L.) cultivars. Genome, 49(9), 1193-1205.
22
546
Reed, G. H., & Wittwer, C. T. (2004). Sensitivity and specificity of single-nucleotide
547
polymorphism scanning by high-resolution melting analysis. Clinical chemistry,
548
50(10), 1748-1754.
549
Scollo, F., Egea, A.L., Gentile, A., La Malfa, S., Dorado, G., Hernandez, P. (2016).
550
Absolute quantification of olive oil DNA by droplet digital-PCR (ddPCR):
551
Comparison of isolation and amplification methodologies. Food Chemistry, 213, 388-
552
394.
553
Sefc, K., Lopes, M., Mendonça, D., Santos, M. R. D., Machado, M. L. D. C., &
554
Machado, A. D. C. (2000). Identification of microsatellite loci in olive (Olea
555
europaea) and their characterization in Italian and Iberian olive trees. Molecular
556
Ecology, 9(8), 1171-1173.
557
Spaniolas, S., Bazakos, C., Awad, M., & Kalaitzis, P. (2008). Exploitation of the
558
chloroplast trn L (UAA) intron polymorphisms for the authentication of plant oils by
559
means of a Lab-on-a-Chip capillary electrophoresis system. J Agric Food Chem,
560
56(16), 6886-6891.
561
Spaniolas, S., Bazakos, C., Ntourou, T., Bihmidine, S., Georgousakis, A., & Kalaitzis,
562
P. (2008). Use of lambda DNA as a marker to assess DNA stability in olive oil during
563
storage. European Food Research and Technology, 227(1), 175-179.
564
Spaniolas, S., Bazakos, C., Spano, T., Zoghby, C., & Kalaitzis, P. (2010). The
565
potential of plastid trnL (UAA) intron polymorphisms for the identification of the
566
botanical origin of plant oils. Food chemistry, 122(3), 850-856.
567
Taberlet, P., Coissac, E., Pompanon, F., Gielly, L., Miquel, C., Valentini, A., Vermat,
568
T., Corthier, G., Brochmann, C., & Willerslev, E. (2006). Power and limitations of the
569
chloroplast trn L (UAA) intron for plant DNA barcoding. Nucleic acids research,
570
35(3), e14-e14.
23
571
Woolley, L. C., James, D. J., & Manning, K. (2001). Purification and properties of an
572
endo-β-1, 4-glucanase from strawberry and down-regulation of the corresponding
573
gene, cel1. Planta, 214(1), 11-21. CRediT author statement
574 575 576
Elsa Chedid: Investigation, Validation, Writing - Original Draft
577
Myrto Rizou: Investigation, Validation, Writing - Original Draft, Writing - Review
578
& Editing,
579
Panagiotis Kalaitzis: Conceptualization, Methodology, Supervision, Writing -
580
Original Draft, Writing - Review & Editing,
581 582 583 584
Declaration of interests
585 586 587
☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
588 589 590 591
☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:
592 593 594 24
595 596 597
Highlights
598
The varietal composition of olive oil blends was quantified
599
Quantification of olive oil adulteration with oils of different plant origin
600
The quantitative authentication of olive oil blends has limitations
601
The SNP-HRM showed higher authentication ability for oil blends compared to
602 603
SSR-HRM SNP-HRM indicated a 5% limit of detection for varietal identification of olive oil
604 605
25