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Development and validation of an HPTLC method for apigenin 7-O-glucoside in chamomile flowers and its application for fingerprint discrimination of chamomile-like materials
Accepted Manuscript Title: Development and validation of an HPTLC method for apigenin 7-O-glucoside in chamomile flowers and its application for fingerprint discrimination of chamomile-like materials Author: Etil Guzelmeric Irena Vovk Erdem Yesilada PII: DOI: Reference:
S0731-7085(14)00627-X http://dx.doi.org/doi:10.1016/j.jpba.2014.12.021 PBA 9859
To appear in:
Journal of Pharmaceutical and Biomedical Analysis
Received date: Revised date: Accepted date:
11-11-2014 8-12-2014 14-12-2014
Please cite this article as: E. Guzelmeric, I. Vovk, E. Yesilada, Development and validation of an HPTLC method for apigenin 7-O-glucoside in chamomile flowers and its application for fingerprint discrimination of chamomilelike materials, Journal of Pharmaceutical and Biomedical Analysis (2014), http://dx.doi.org/10.1016/j.jpba.2014.12.021 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. 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.
1 1
Graphical Abstract
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Matricaria recutita L.
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Highlights
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• Chamomile is one of the most popular medicinal plants and used as a safe remedy.
6 7
• Chamomile-like flowers misidentification problem.
8 9
• Apigenin 7-O-glucoside is regarded as an active marker in chamomile flowers.
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• An HPTLC method for quantification of apigenin 7-O-glucoside has been validated.
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• Chamomile was discriminated from chamomile-like species.
consumed
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frequently
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are
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Development and validation of an HPTLC method for apigenin 7-O-
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glucoside in chamomile flowers and its application for fingerprint
16
discrimination of chamomile-like materials
21 22
Phytotherapy, Kayisdagi Cad., Atasehir, 34755, Istanbul, Turkey b
cr
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Yeditepe University, Faculty of Pharmacy, Department of Pharmacognosy and
National Institute of Chemistry, Laboratory for Food Chemistry, Hajdrihova
19., SI-1000 Ljubljana, Slovenia
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a
c
EN-FIST Centre of Excellence, Trg Osvobodilne fronte 13, SI-1000
an
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Etil Guzelmerica, Irena Vovkb,c, Erdem Yesiladaa*
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Ljubljana, Slovenia
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*Corresponding author: Prof. Dr. Erdem Yesilada
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Tel: +90 216 578 00 00 Fax: +90 216 578 00 68
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E-mail address: [email protected]
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1. Introduction The dried flower heads of Matricaria recutita L. (synonym Chamomilla
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recutita (L.) Rauschert) (chamomile) from the family Asteraceae are among
42
the most popular, well-documented and universally recognized herbal drugs
43
[1–3]. In the world market, the annual consumption of chamomile flowers is
44
reported to be several thousands of tons [4]. In fact, daily worldwide
45
consumption of chamomile tea was speculated to be over one million cups [5].
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Brewed tea of chamomile flowers has been extensively utilized for
47
centuries due to either its pleasant and calming taste or medicinal purposes.
48
Bioassay-guided processing of chamomile flowers has revealed that many of
49
its healing benefits such as relieving painful gastrointestinal complaints, mild
50
sleep disorders and inflammatory diseases are highly related with its phenolic
51
content, in particular of apigenin and apigenin 7-O-glucoside (A7G) [6]. In
52
addition to therapeutic activity of A7G, it is one of the major constituents in
53
chamomile flowers [7–11]. Consequently in the European Pharmacopoeia (Ph.
54
Eur.) it is assessed as an active quality marker for M. recutita flowers by high
55
performance liquid chromatography (HPLC) [12].
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A7G and its metabolite apigenin have been shown to possess
57
remarkable
anti-spasmodic,
anti-inflammatory,
antioxidant
and
anti-
58
carcinogenic properties [6]. Recently scientific investigations have been
59
performed focusing on the biological effects of apigenin at cellular and
60
molecular levels i.e. sensitize cancer cells to apoptosis, inhibit cell growth and
61
angiogenesis [13]. Moreover apigenin may provide some additional benefits
62
beyond the available chemotherapeutics in slowing the emergence of
Page 4 of 35
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metastatic diseases by blocking the chemokine signaling pathways, inhibiting
64
cell adhesion molecules and remodeling of the extracellular matrix [14]. On the other hand, the major problem is difficulty in distinguishing the
66
genuine specimen when supplying chamomile, M. recutita, through nature-
67
picking. Consequently flowers of other Asteraceae members resembling to
68
chamomile in appearance, i.e. Anthemis sp., Bellis sp., Chrysanthemum sp.,
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Tanacetum sp., Tripleurospermum sp. etc. may also be gathered from nature by
70
people to be used as home remedy or for marketing in spice shops or bazaars.
71
This problem is solved in several countries by providing bulk chamomile of the
72
official quality from cultivars. However, in many parts of the world, nature-
73
picking raise severe quality problem. One of which is the increased toxicity
74
risk. Although chamomile flowers are known to be safe, there are records of
75
chamomile intoxication cases in the worldwide references due to identification
76
blunder [15]. For example, pyrrolizidine alkaloids in Senecio sp., resembling to
77
chamomile flowers, may induce severe hepatic veno-occlusive disease and
78
even cause of death [16]. The second problem is the concentration of the main
79
active ingredients that is important not only for its therapeutic benefits but also
80
for qualification of chamomile flowers.
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Several qualitative and quantitative methods have been developed for
82
the evaluation of A7G in chamomile flowers. Among these are methods based
83
on HPLC or ultra performance liquid chromatography (UPLC) with ultra-violet
84
(UV) [9,10] or mass (MS) [11,17] or tandem mass (MS2) spectrometric
85
detection
86
electrochromatography [20]. Recently an HPTLC method was developed either
87
for identification or quantification of some flavonoids such as A7G, rutin,
[18],
capillary
electrophoresis
[19]
and
capillary
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chamaemeloside etc. and one coumarin (umbelliferon) in chamomile flowers
89
[21]. In the present study, we first aimed to develop and validate a qualitative
91
and quantitative HPTLC method for A7G in chamomile flowers with the
92
guidance of the HPLC method described in the Ph. Eur. Secondly, the
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validated HPTLC method was practiced to analyze A7G content in wild
94
chamomile flowers and several chamomile-like materials belong to 12 different
95
species i.e. Anthemis spp., Bellis spp., Chrysanthemum sp. and Tanacetum sp.
96
gathered by local people assuming as chamomile. Then, principal component
97
analysis (PCA) based on HPTLC plate images and comparative HPTLC
98
densitograms were used for discrimination of chamomile from chamomile-like
99
species.
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2.1. Chemicals
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HPLC grade acetonitrile and tetrahydrofuran were purchased from J. T.
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Baker (Deventer, the Netherlands) and HiPerSolv Chromanorm (Lutterworth,
104
England). The other solvents were of analytical grade. Ethanol absolute, ethyl
105
acetate, formic acid and acetone were from Sigma-Aldrich (Steinheim,
106
Germany); acetic acid, and 2-propanol were from Riedel-de Haen (Seelze,
107
Germany), o-phosphoric acid and ethyl methyl ketone were from Merck
108
(Darmstadt, Germany); methanol, dichloromethane and n-hexane were from
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Analar Normapur (Muarrie, Australia). 2-aminoethyl diphenylborinate and
110
polyethylene glycol 400 were from Fluka (Steinheim, Germany) and Merck
111
(Hohenbrunn, Germany), respectively. The ultrapure water was obtained from
112
Millipore, Simplicity UV (Darmstadt, Germany).
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Standards of A7G, luteolin 7-O-glucoside (L7G), 5,7-dihydroxy-4-
114
methylcoumarin and the other chemicals which are sodium hydroxide and
115
magnesium
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(Steinheim, Germany).
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2.2. Plant Materials
were
purchased
from
Sigma-Aldrich
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chloride-6-hydrate
Bodegold type M. recutita cultivar used in the HPTLC method
119
development and in the HPLC analysis was obtained from Ataturk Central
120
Horticultural Research Institute (Yalova, Turkey) in May 2011. The
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chamomile-like materials assumed to be M. recutita were gathered from nature
122
by local people from different localities in Turkey. The materials, collection
123
regions and years are listed in Table 1.
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The materials were identified by Prof. Dr. Galip Akaydın (Faculty of
125
Education, Hacettepe University, Ankara, Turkey), Assist. Prof. Dr. Gizem
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Bulut (Faculty of Pharmacy, Marmara University, Istanbul, Turkey), Dr. M.
127
Ufuk Özbek (Faculty of Science, Gazi University, Ankara, Turkey). The
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voucher specimen of materials has been kept in the Herbarium of the
129
Department of Pharmacognosy, Faculty of Pharmacy, Yeditepe University,
130
Turkey.
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All plant materials were kept away from direct sunlight and dried at
132
room temperature for two weeks. The dried materials were stored in a
133
refrigerator at – 25 ºC and ground to powder in a mechanic grinder before the
134
extraction.
135
2.3. Preparation of standard solutions
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2.3.1. Standard solutions for HPLC analysis
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The reference solution A (12.5 µg/mL) and B (10 µg/mL) were
138
prepared according to the described procedure in the Ph. Eur. [12].
139
2.3.2. Standard solutions for HPTLC analysis and method validation A7G and L7G stock solutions (50 µg/mL) were separately prepared in
141
methanol and were used for the preparation of standard mixture (Mix2, 25
142
µg/mL), which was applied for the method development.
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Additional A7G stock solution (250 µg/mL) was prepared in methanol
144
and further diluted with the same solvent to prepare the working solutions 2.5,
145
5 and 10 µg/mL.
146
2.4. Preparation of detection reagents
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Natural Products (NP) and polyethylene glycol 400 (PEG 400) dipping
148
solutions were prepared according to the described procedure by Reich and
149
Schibli [22].
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2.5. Preparation of sample test solutions
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2.5.1. Extraction of M. recutita cultivar according to the Ph. Eur.
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procedure in the Ph. Eur. [12].
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2.5.2. Extraction of M. recutita cultivar for HPTLC analysis
155
Chamomile tea is the most preferred form in folkloric use of
156
chamomile. Therefore, aqueous solvent extraction method was applied to all
157
materials used in this study. Powdered chamomile flowers (2 g) were poured
158
by 100 mL of freshly boiled water and the beaker was then enclosed by watch
159
glass and kept at room temperature for 5 min for brewing (2% infusion). After
160
filtration through a filter paper, the filtrate was cooled and lyophilized (yield:
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32.47%). Then, ten milligrams of lyophilizate was accurately weighed in
Page 8 of 35
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triplicate and extracted with 10 mL of methanol in an ultrasonic bath for 15
163
min. Suspended particles were removed by filtration through a 0.45 µm RC-
164
membrane filter. Finally, the sample test solutions (1 mg/mL) were diluted 2
165
times and used for the method validation.
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2.5.3. Extraction of the plant materials gathered by local people
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The same extraction procedure was performed as described in 2.5.2.
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The extract yields are given in Table 1. Ten milligrams of each lyophilizates
169
was then accurately weighed and extracted as described before. The final
170
concentration of the each sample test solutions was 1 mg/mL.
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2.6. HPLC method
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HPLC system, HP1100 series (Agilents Technologies, Santa Clara,
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California, USA) equipped with a vacuum degasser G1379A, a quaternary
174
pump
175
compartment G1316A, and a diode array detector G1315B, and Chemstation
176
10.01 software was used for the HPLC analysis. The separations were
177
performed on an Agilent Zorbax Eclipse Plus C18 ODS column (5 µm, 250 mm
178
x 4.6 mm, i.d.) according to the method described in the ‘Matricariae flos’
179
monograph in the Ph. Eur. [12].
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2.7. HPTLC method
an
auto-sampler
G1313A,
a
thermo-stated
column
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HPTLC analyses were performed on 20 cm x 10 cm glass HPTLC
182
plates coated with silica gel 60 NH2 F254s (Merck). Sample and standard
183
solutions were applied on the plates as 8 mm bands, 8 mm from the bottom
184
edge and 15 mm from the left edge by means of Linomat V sample applicator
185
(Camag, Muttenz, Switzerland) equipped with a 100 µL syringe (Hamilton,
186
Bonaduz, Switzerland). The plates were pre-conditioned with vapor of the
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developing solvents ethyl acetate-formic acid-acetic acid-water (30:1.5:1.5:3,
188
v/v/v/v) for 10 min and then, developed up to 7 cm in the saturated (20 min)
189
Automatic Developing Chamber 2 (ADC2, Camag). The relative humidity was
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fixed to 33% by a saturated MgCl2.6H2O solution. After development and 5
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min of automatic drying quantitative evaluation of the plates was performed by
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TLC Scanner 3 (Camag) in absorption/reflectance mode at 340 nm, using slit
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dimensions 6 mm x 0.30 mm the scanning speed 20 mm s-1 and the data
194
resolution 100 µm/step. The quantitative evaluations were established through
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peak area via quadratic regression. For the visual documentation, the plates
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were heated at 100˚C on the Camag TLC plate heater for 3 min and dipped into
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NP and PEG 400 solutions, respectively. After derivatization, documentation
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of the plates was performed by the Camag TLC visualizer at 366 nm. All these
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instruments were operated by winCATS program (version 1.4.8, Camag)
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2.8. Statistical analyses
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The applications of each analyzed solutions were performed in
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triplicate. The results were presented as mean ± standard deviation (SD).
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Statistical comparisons of several mean values were done by using one-way
204
analyses of variance (ANOVA), taking the appropriate condition as a single
205
factor. When the ANOVA leads to significant results, Least Significant
206
Difference (LSD) test was performed to identify where the differences occur.
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The evaluation of curve estimation, Lack-of-fit test, and Pearson correlation
208
coefficients (r) calculation were also performed. Statistically significant
209
difference was defined as p < 0.05. The analyses were carried out by SPSS
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Data Editor (version 20.0). The HPTLC images of the plates were processed by
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the Image J processing program. PCA was performed by using MATLAB
212
(version 7.12.0)
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3. Results and discussion
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3.1. HPLC analysis
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Initially, the system suitability was checked by the reference solution B
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for the further analyses. The resolution (Rs) between the standards A7G and
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5,7-dihydroxy-4-methylcoumarin was found as 7.54 ± 0.03 (n = 3), indicated
218
the suitability of the system according to the Ph. Eur. [12].
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The identity of the A7G in the test solution A was verified by
220
comparing the retention time (tR) with the reference solution A at 25ºC and
221
found as 6.50 ± 0.01. Moreover, the percentage content of A7G in M. recutita
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cultivar was found as 0.70% which was higher than the official limit (0.25%)
223
[12]. Eventually, M. recutita cultivar was taken into account as a reference
224
plant material for HPTLC analysis.
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3.2. HPTLC analysis and validation
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3.2.1. Method optimization
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The method optimization is very challenging in plant extracts analyses
228
due to their chemical complexity. The method optimization in thin layer
229
chromatography contains several steps e.g. the type of the stationary phase,
230
composition of the developing solvents, chamber type and saturation,
231
application of the samples, development, derivatization, detection and
232
laboratory conditions [22].
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In this study, Mix2 was used due to similar chemical structures of the
234
standards A7G and L7G (Fig. 1) during the evaluation of the developing
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solvents and these standards assisted for the determination of the optimum
236
separation. The first step was to apply some developing solvent systems reported in
238
the previous studies for the separation of phenolic compounds [21–23]. The
239
second step was to test the combinations of the neat solvents, i.e. 2-propanol,
240
tetrahydrofuran, ethyl acetate, ethyl methyl ketone etc. with formic acid or
241
acetic acid to prevent fronting of the peaks on silica gel plates (firstly used due
242
to ease of availability and low price) and amino plates. The obtained results
243
provided to find various solvent mixtures in different ratios, i.e. acetone-n-
244
hexane-2-propanol-acetic acid (45:15:1:1 v/v/v/v); ethyl methyl ketone-water-
245
acetic acid (49:0.5:0.5 v/v/v); tetrahydrofuran-water-acetic acid-formic acid
246
(42:4:2:2 v/v/v/v) etc. In the all analyses, saturated twin trough chambers were
247
used. Finally, the best separation of the A7G and L7G was achieved using a
248
silica gel 60 NH2 F254s HPTLC glass plate and ethyl acetate-formic acid-acetic
249
acid-water (30:1.5:1.5:3, v/v/v/v) as a developing solvent system (Fig. 1). After
250
assessment of the stationary phase and developing solvent system some
251
modifications have been made, i.e. the plate was pre-conditioned and humidity
252
was controlled (33%) in order to get better resolution.
253
3.2.2. Methodological comparison of developed HPTLC and HPLC
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The separation power of the HPTLC method in this study was
255
compared with the HPLC method in the Ph. Eur. in order to demonstrate the
256
applicability of the developed HPTLC method.
257
Firstly, the test solution A and A7G standard solutions were applied to
258
HPTLC. After development, the zones belong to A7G were marked and
259
scraped from the surface of the plate layer. A7G was extracted from the layer
Page 12 of 35
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by using ethanol 96% and filtered through a 0.45 µm RC-membrane filter and
261
then, solvent was evaporated by rotavapor. The residue was dissolved in 1 mL
262
of ethanol-initial mixture of the mobile phase (1:1 v/v) and applied to both
263
methods. Consequently, a co-existing compound with very low resolution
264
eluted together with A7G in the HPLC method (Figs. 2a and 2b), whereas this
265
compound could not clearly detected in the HPTLC method (Fig. 2c). On the
266
other hand, comparative evaluations of the HPTLC densitogram with that of
267
HPLC chromatogram (Fig. 2d) found at the web address of the European
268
Directorate for the Quality of Medicines & Health Care (EDQM) revealed that
269
this compound was co-eluted with A7G [24]. Consequently, due to the close
270
resolution patterns between HPTLC densitogram and HPLC chromatogram,
271
separation power of the developed HPTLC method was found to be appropriate
272
for further analysis.
273
3.2.3. Validation
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Following the International Committee on Harmonization (ICH)
275
guidelines, the developed HPTLC method was validated for stability,
276
robustness, specificity, limit of detection and quantification, linearity, precision
277
and recovery [25]. Renger et al. [26] have recently summarized the acceptance
278
criteria for complex matrices i.e. plant materials, herbal drugs, foodstuffs etc.
279
for required validation characteristics, therefore found values were compared
280
with the acceptance criteria.
281
3.2.3.1. Stability
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One of the drawbacks of HPTLC is being an open system. During
283
application by Linomat V, application positions are exposed to air and light.
284
Besides, mostly on normal phases due to highly active polar surfaces
Page 13 of 35
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substances may undergo degradation. Therefore, duration of application
286
depends on the number of tracks, application volume, sorbent layer and the
287
effect of the solvent type should be considered during the method optimization.
288
For the evaluation of the stability, the following parameters were tested: the
289
stability of the A7G in methanol at different storing temperatures, the stability
290
of the A7G standard solution on the plate before development, and the stability
291
of the sample solution during the chromatography.
292
3.2.3.1.1. Stability of the A7G in methanol at different storing temperature
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The standard solutions of A7G (0.01 mg/mL) were stored at -80°C, -
294
20°C and 4°C during three weeks. As a result of statistical evaluation by one-
295
way ANOVA, significant changes in mean areas were not established in
296
samples kept at -80°C, -20°C, 4°C and the freshly prepared standard solutions
297
after three weeks, F(3,8) = 0.306, p = 0.821 (Fcrit(3,8) = 4.066).
298
3.2.3.1.1. Stability of the A7G standard on the plate before development
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The A7G standard solution (0.01 mg/mL) was freshly prepared and
300
applied on the plate in 30 min intervals from 0 to 120 min before development.
301
During these intervals the plate was left in an open area, exposed to air and
302
light. Interruptions in time intervals were evaluated by one-way ANOVA. As a
303
result, the mean areas were found to be different across time intervals, F(4,10) =
304
3.989, p = 0.035 (Fcrit(4,10) = 3.478). The LSD multiple comparisons performed
305
at the 0.05 significance level found that the mean area of freshly applied A7G
306
standard solution (M = 587.33, SD = 10.75, n = 3) was significantly different
307
than the average area of the A7G standard solutions, applied in 60 min (M =
308
541.97, SD = 33.45, n = 3), 90 min (M = 534.42, SD = 22.14, n = 3) and 120
309
min (M = 528.48, SD = 23.27, n = 3), but not significantly different than the
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15 310
mean area of the A7G standard solutions, applied in 30 min (M = 576.30, SD =
311
18.82, n = 3).
312
3.2.3.1.3 Stability of the sample during chromatography Stability of the sample during chromatography was investigated by 2-
314
dimensional (2D) development. All components in the sample were detected
315
on the diagonal line connecting the application position and the intersection of
316
the 2 solvent fronts, indicated the stability of the sample.
317
3.2.3.2. Robustness
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The robustness of the method was evaluated by considering the effects
319
of some alterations. The following items were investigated during the testing of
320
robustness: duration of the plate preconditioning time, humidity, plate
321
prewashing and saturation. The ratios of the area of 0.01 mg/mL of standard
322
A7G and 0.5 mg/mL of sample solutions were used during the evaluation of
323
the described variations. The evaluated ratios were compared statistically by
324
using one-way ANOVA. As a result, the mean proportions were not found to
325
be different across variations, F(4, 10) = 0.242, p = 0.908.
326
3.2.3.3. Specificity
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327
The specificity of the method was ascertained by analyzing standard
328
and test solutions. The identity of A7G in the test solution of M. recutita was
329
evaluated by comparison of the retention factor (RF) with the standard solution
330
of A7G, (0.37 ± 0.01) at 22 ± 1°C (Fig. 3). The HPTLC videodensitogram at
331
366 nm and the spectrum of A7G belongs to standards and samples were also
332
used for the confirmation.
333
3.2.3.4. The limits of Detection and Quantification
Page 15 of 35
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0.5 µg/mL, 1 µg/mL and 2 µg/mL of A7G standard solutions were
335
applied on the different plates in triplicate with an increased application
336
volume (2-5 µL) to evaluate the limits of detection (LOD) and the limits of
337
quantification (LOQ). The visual and semi quantitative evaluation of the signal
338
to noise (S/N) ratios 3:1 for the LOD and 10:1 for the LOQ was assisted to
339
found 1.5 ng/spot and 5 ng/spot, respectively.
340
3.2.3.5. Linearity and calibration curve
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To avoid adverse effects of overloading on the application position in
342
HPTLC, starting near the LOQ and selecting the calibration ranges as low as
343
possible are recommended [27]. In this study, 2.5, 5 and 10 µg/mL of the
344
working standard solutions were prepared from freshly prepared 250 µg/mL
345
stock solutions and applied to HPTLC plates to obtain 5, 10, 15, 20, 25 and 50
346
ng/spot.
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The curve estimation option in SPSS was performed to compare linear
348
or quadratic regression models (Table 2), besides plotting the residuals and
349
Lack-of-fit tests were also done to evaluate how well the sets of data in the
350
range of 5-25 ng/spot and 5-50 ng/spot fit either with linear or quadratic
351
models. The high values of F- test for a significant correlation, probability was
352
lower than 0.05 for both models in both ranges, indicated that the variation
353
explained by each model was not due to chance. Secondly, the coefficient of
354
determination, R2 values indicated that there was a strong relationship between
355
both models and ranges. However, quadratic model of the R2 was higher than
356
the linear model in the range of 5-50 ng/spot (Table 2). The scatter plot of
357
residuals by fit values for the linear and quadratic models was the key point for
358
the selection of the model in this study. In the range of 5-50 ng/spot the scatter
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Page 16 of 35
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plot of residuals by fit values for the linear model showed an ‘inverted U’
360
shaped pattern (Fig. 4a), indicated that there was a pattern in the data that was
361
not captured by the linear model, whereas the scatterplot of residuals by fit
362
values for the quadratic model did not show a pattern (Fig. 4b), thus the
363
quadratic model was acceptable in sense the residuals were independent of the
364
fit values. On the other hand, in the range of 5-25 ng/spot the scatter plot of
365
residuals by fit values for the linear and quadratic models also did not show a
366
pattern (Fig. 4c and 4d). In addition, Lack-of-fit test illustrated the probability
367
of the F-test statistic (F(3,10) = 0.844) was p = 0.501, greater than the alpha level
368
of significance of 0.05. These findings also supported that linear regression
369
model was appropriate in the range of 5-25 ng/spot range.
M
an
us
cr
ip t
359
In this study, instead of working in the range of 5-25 ng/spot widening
371
the calibration curve by adding one more standard as 50 ng/spot was decided to
372
be more useful due to the calculations of the recovery results.
373
3.2.3.6. Precision
374
3.2.3.6.1. Repeatability
Ac ce p
te
d
370
375
The intraday precision of the method was performed by replicating the
376
experiment in triplicate with three times freshly prepared samples during the
377
day. The mean of the A7G amount in samples, standard deviations (SD) and
378
relative standard deviations (RSD) was shown in Table 3.
379
3.2.3.6.2. Intermediate Precision
380
The intermediate precision of the method was examined by freshly
381
prepared samples in triplicate on consecutive three days. The determined
382
intermediate precision showed similar deviations as intraday (Table 3).
Page 17 of 35
18
RSD for repeatability and intermediate precision were found in the
384
range of acceptance criteria, RSD should be less than 10% for repeatability and
385
for intermediate precision it should be within the range from 1.3 to 1.7 x RSD
386
of repeatability [26].
387
3.2.3.7. Recovery
ip t
383
Due to impossibility to reconstitute a blank matrix, the accuracy of the
389
proposed method was evaluated as recovery and 2.5, 5, and 10 ng/spot of
390
standard A7G was added to the pre-analyzed sample, respectively. The average
391
percentages of recovery of the added standard A7G shown in Table 3 was
392
found to be in the range of acceptance criteria [26].
393
3.3. Evaluation of chamomile and chamomile-like flowers
M
an
us
cr
388
The chamomile-like flowers assumed to be M. recutita were gathered
395
from nature by local people from 24 different localities in Turkey. The
396
botanical identification of these plant materials have been revealed that they
397
were 13 different species belonging to 5 different types of genus, Matricaria
398
L., Anthemis L., Bellis L., Chrysanthemum L. and Tanacetum L. Surprisingly,
399
among them only 2 materials were identified as M. recutita. In addition to our
400
findings, Joharchi and Amiri [28] also concluded that M. recutita was the most
401
adulterated and substituted plant with other species belonging to the family
402
Asteraceae due to some morphological similarities.
Ac ce p
te
d
394
403
In this study, A7G was determined and quantified in the chamomile-
404
like flowers gathered by people from different localities. That is because; the
405
brewed tea of chamomile-like flowers should contain A7G to meet with the
406
therapeutic expectations of local people. Presence of A7G in the samples was
407
monitored by comparing the RF values and the spectra of the corresponding
Page 18 of 35
19
retention zones with that of the standard A7G. Consequently, A7G was found
409
in the wild M. recutita samples from two different localities along with A.
410
coelopoda var. coelopoda, A. austriaca, A. auriculata, A. cretica, B. perennis
411
and B. sylvestris samples. Subsequently, the amount of A7G was evaluated in
412
these species as shown in Table 1. When the content A7G was compared in
413
wild M. recutita samples, it was found that A7G concentration was quite
414
different in two wild samples collected from different locations; Istanbul (1.90
415
mg) and Canakkale (below LOQ) (Table 1). On the other hand, A7G contents
416
of these wild M. recutita samples were found to be lower than the cultivar
417
sample. This might be due to controlled growth of chamomile under cultivation
418
which eliminates variations in geographical conditions such as rainfall,
419
temperature, soil, altitude, humidity etc. On the other hand, A7G was not
420
identified in A. cotula, A. altissima, A. tinctoria var. discoidea, A. scariosa, C.
421
coronarium and T. parthenium samples.
te
d
M
an
us
cr
ip t
408
It should be underlined that although A7G is an active marker, it should
423
not be considered as a chemotaxonomic marker for discriminating chamomile
424
and chamomile-like flowers. Therefore, PCA processing based on fingerprints
425
obtained from the HPTLC plate images at 366 nm (Fig. 5) and comparative
426
HPTLC densitograms belong to plant materials at 340 nm were used for the
427
interpretation of the results more efficiently during the discrimination of
428
chamomile from chamomile-like flowers.
Ac ce p
422
429
PCA is one of the mostly used techniques in multivariate analysis
430
which classifies samples according to their similarities. The visual
431
documentation of the HPTLC plate images were processed as previously
432
described by Ristivojević et al. [29]. PCA processing has revealed that M.
Page 19 of 35
20
recutita samples from different localities and A. coelopoda. var. coelopada
434
were classified under the same group (Fig. 6), which might be due to the close
435
chemical fingerprinting of these species at 366 nm. However, during the
436
comparison of the densitograms especially the regions from start to RF= 0.40 at
437
340 nm, it was clearly observed that M. recutita possesses a different chemical
438
fingerprint profile than that of A. coelopoda var. coelopada. Consequently, by
439
using PCA processing and comparison of densitograms chamomile was
440
successfully discriminated from the chamomile-like species.
441
4. Conclusion
an
us
cr
ip t
433
The usage of chamomile tea as a remedy has a history of thousands of
443
years in traditional medicine. However, due to difficulty in distinguishing the
444
genuine specimen, the flowers of other Asteraceae members resembling to
445
chamomile in appearance may also be used or marketed. The validated HPTLC
446
method in this study was successfully applied either for quantification of the
447
A7G in chamomile and chamomile-like flowers or discrimination of genuine
448
chamomile from other species from Asteraceae. In addition, HPTLC
449
densitograms belong to M. recutita and 12 different species presented in this
450
study may also be a leading guide for the quality assessment of chamomile tea
451
products on the market.
452
Acknowledgements
Ac ce p
te
d
M
442
453
Etil Guzelmeric would like to state her deep gratitude to the Turkish
454
Scientific and Technical Research Council (TUBITAK) for the scholarship
455
provided during the Ph. D. program. She is also thankful to the CAMAG
456
Laboratory team (Muttenz, Switzerland), Galip Akaydın (Faculty of Education,
457
Hacettepe University, Ankara, Turkey), Gizem Bulut (Faculty of Pharmacy,
Page 20 of 35
21
Marmara University, Istanbul, Turkey), Jelena Trifković (Faculty of
459
Chemistry, University of Belgrade, Belgrade, Serbia), Laboratory for Food
460
Chemistry team (National Institute of Chemistry, Ljubljana, Slovenia), M.
461
Ufuk Özbek (Faculty of Science, Gazi University, Ankara, Turkey), Petar
462
Ristivojević (Innovation Centre of Faculty of Chemistry Ltd., University of
463
Belgrade, Belgrade, Serbia) for their great contributions during the study.
464
References
465
[1] R. Franke, H. Schilcher, Chamomile industrial profiles, first ed., Taylor &
466
Francis Group, Boca Raton, USA, 2005.
467
[2] O. Gacea, M. Hancianu, C. Aprotosoaie, A. Spac, V. Dorneanu, U.
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Stanescu, The pharmaceutical quality of some medicinal teas of Chamomillae
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[3] N. Mulinacci, A. Romani, P. Pinelli, F.F. Vincieri, D. Prucher,
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472
HPLC-DAD analysis, Chromatographia 51(5/6) (2000) 301-307.
473
[4] I. Šalamon, I. Sudimáková, Quality of chamomile teas- Essential oil content
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and its composition, Acta Hort. 749 (2007) 181-186.
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[5] J.K. Srivastava, S. Gupta, Antiproliferative and apoptotic effects of
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chamomile extract in various human cancer cells, J. Agric. Food Chem. 55
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[6] D.L. McKay, J.B. Blumberg, A review of the bioactivity and potential
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health benefits of chamomile tea (Matricaria recutita L.), Phytother. Res. 20
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biological activity of flavonoids isolated from chamomile flowers, Mol. Cell.
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Pharmacol. 1(3) (2009) 138-147.
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[8] J.K. Srivastava, M. Pandey, S. Gupta, Chamomile, a novel and selective
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COX-2 inhibitor with anti-inflammatory activity, Life Sci. 85(19/20) (2009)
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663-669.
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[9] G. Haghi, A. Hatami, A. Safaei, M. Mehran, Analysis of phenolic
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compounds in Matricaria chamomilla and its extracts by UPLC-UV, Res.
489
Pharm. Sci. 9(1) (2014) 31-37.
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[10] M. Repćák, T. Krausová, Phenolic glucosides in the course of ligulate
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flower development in diploid and tetraploid Matricaria chamomilla, Food
492
Chem. 116 (2009) 19-22.
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[11] B. Weber, M. Herrmann, B. Hartmann, H. Joppe, C.O. Schmidt, H.J.
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Bertram, HPLC/MS and HPLC/NMR as hyphenated techniques for accelerated
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characterization of the main constituents in Chamomile (Chamomilla recutita
496
[L.] Rauschert), Eur. Food Res. Technol. 226 (2008) 755-760.
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[12] European pharmacopoeia (Ph. Eur.), Seventh ed., Council of Europe,
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Strasbourg, France, 2010.
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[13] D. Patel, S. Shukla, S. Gupta, Apigenin and cancer chemoprevention:
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progress, potential and promise (review), Int. J. Oncol. 30 (2007) 233-245.
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[14] É.C. Lefort, J. Blay, Apigenin and its impact on gastrointestinal cancers,
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Mol. Nutr. Food Res. 57 (2013) 126-144.
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[15] Z. Chen, J.R. Huo, Hepatic veno-occlusive disease associated with
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toxicity of pyrrolizidine alkaloids in herbal preparations, Neth. J. Med. 68(6)
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(2010) 252-260.
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supplement hepatotoxicity, Aliment. Pharmacol. Ther. 37(1) (2013) 3-17.
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[17] B. Avula, Y.H. Wang, M. Wang, C. Avonto, J. Zhao, T.J. Smillie, D. Rua,
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I.A. Khan, Quantitative determination of phenolic compounds by UHPLC-UV-
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MS and use of partial least-square discriminant analysis to differentiate chemo-
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types of Chamomile/Chrysanthemum flower heads, J. Pharm. Biomed. Anal.
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88 (2014) 278-288.
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[18] L. Z. Lin, J.M. Harnly, LC-PDA-ESI/MS Identification of the phenolic
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components of three Compositae spices: Chamomile, Tarragon, and Mexican
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Arnica, Nat. Prod. Commun. 7(6) (2012) 749-752.
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[19] F.N. Fonseca, M.J. Kato, L. Oliveira Jr., N.P. Neto, M.F.M. Tavares,
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Critical assessment of electrolyte systems for the capillary electrophoresis
518
analysis of phenolic compounds in herbal extracts, J. Microcolumn Sep. 13(6)
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(2001) 227-235.
520
[20]
521
electrochromatography of selected phenolic compounds of Chamomilla
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recutita, J. Chromatogr. A 1154 (2007) 390-399.
523
[21] S. Sagi, B. Avula, Y.H. Wang, J. Zhao, I.A. Khan, Quantitative
524
determination of seven chemical constituents and chemo-type differentiation of
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chamomiles using high-performance thin-layer chromatography, J. Sep. Sci.
526
37(19) (2014) 2797-2804.
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[22] E. Reich, A. Schibli, High Performance Thin Layer Chromatography for
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the Analysis of Medicinal Plants, first ed., Thieme, Stuttgart, New York, 2007.
529
[23] G. Sacchetti, C. Romagnoli, M. Ballero, B. Tosi, F. Poli, Internal secretory
530
structures and preliminary phytochemical investigation on flavonoid and
te Fonseca,
M.F.M.
Tavares,
C.
Horváth,
Capillary
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F.N.
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an
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coumarin content in Santolina insularis (Asteraceae), Phyton 37 (1997) 219-
532
228.
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[24] European Directorate for the Quality of Medicines & Health Care
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(EDQM), Edqm knowledge database – ‘’Matricariae flos’’, 1996.
535
[25] International Conference on Harmonisation (ICH), ICH Harmonised
536
Tripartite
537
Methodology Q2 (R1), 2005.
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[26] B. Renger, Z. Végh, K. Ferenczi-Fodor, Validation of thin layer and high
539
performance thin layer chromatographic methods, J. Chromatogr. A 1218
540
(2011) 2712-2721.
541
[27] S.A. Coran, S. Mulas, N. Mulinacci, Crucial aspects of high performance
542
thin layer chromatography quantitative validation. The case of determination of
543
rosmarinic acid in different matrices, J. Chromatogr. A 1220 (2012) 156-161.
544
[28] M.R. Joharchi, M.S. Amiri, Taxanomic evaluation of misidentification of
545
crude herbal drugs marketed in Iran, Avicenna J. Phytomed. 2(2) (2012) 105-
546
112.
547
[29] P. Ristivojević, F.Lj. Andrić, J.Ð. Trifković, I. Vovk, L.Ž. Stanisavljević,
548
Ž.Lj. Tešić, D.M. Milojković-Opsenica, Pattern recognition methods and
549
multivariate image analysis in HPTLC fingerprinting of propolis extracts, J.
550
Chemometr. 28 (2014) 301-306.
of
Analytical Procedures: Text and
Ac ce p
te
d
M
an
us
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Guideline Validation
ip t
531
551
Page 24 of 35
25 Table 1 Plant materials: Collection region & year, yield, A7G amount and HPTLC densitograms Plant Materials Region & Year A7G (mg)a HPTLC densitogramsb Yield (%) Matricaria recutita L.
Istanbul, June 2012; 17.58%
1.90 ± 0.16
Matricaria recutita L.
Canakkale, May 2012; 20.47%
< LOQ
Anthemis coelopoda Boiss. var. coelopoda Boiss.
Izmir, May 2012; 23.49%
an
us
cr
ip t
551 552
te
d
M
1.72 ± 0.05
Ac ce p
Anthemis austriaca Jacq.
Anthemis auriculata Boiss.
553
554 555
Ankara, July 2011; 19.98%
1.60 ± 0.07
Bursa, June 2011; 13.90%
< LOQ
556
Page 25 of 35
26 557 558
Table 1 Continued Plant
Region & Year Yi ld (%) Istanbul, May 2012; 26.13%
)a < LOQ
(
Istanbul, June 2011; 32.45%
ndt
Anthemis altissima L.
Bursa, June 2012; 16.81%
ndt
te
d
M
an
us
Anthemis cotula L.
cr
ip t
M t i l Anthemis cretica L.
HPTLC densitogramsb
A7G
Istanbul, June 2012; 19.71%
ndt
Anthemis scariosa Banks et Sol.
Adana, June 2012 20.65%
ndt
Ac ce p
Anthemis tinctoria L. var. discoidea (All) D.C
559 560
561
Page 26 of 35
27 562 563
Table 1 Continued Plant
HPTLC densitogramsb
A7G )a < LOQ
(
Amasra, September 2012; 30.60%
< LOQ
Chrysanthemum coronarium L.
Mugla, April 2012; 21.30%
ndt
te
d
M
an
us
Bellis sylvestris Cyr.
cr
ip t
M t i l Bellis perennis L.
Region & Year Yi ld (%) Istanbul, May 2011; 27.08%
Istanbul, June 2011; 20.70%
ndt
Ac ce p
Tanacetum parthenium L.
ndt: A7G not detected; < LOQ: under the limit of quantification a A7G amount in the lyophilized plant materials; Mean ± SD (n = 3) b HPTLC densitograms of plant materials (2 µg/spot) at 340 nm
564 565 566 567 568
569
570
571
572
Page 27 of 35
28
574 575 576
Table 2 Linear and quadratic model comparisons for standard A7G in the range of 5-25 ng/spot and 550 ng/spot Range Model Summary Parameter Estimates (ng/spot) Modelsa R2 F dfb1 dfb2 Sig.c a b c n Linear 0.996 2925.50 1 13 0.00 16.07 33.21 15 5-25 Quadratic 0.996 1620.91 2 12 0.00 37.78 15 10.64 0.15 Linear 0.997 6169.48 1 16 0.00 48.98 30.78 15 5-50 Quadratic 0.999 8065.50 2 15 0.00 -0.93 36.04 18 0.09 a Regression models: Linear equation: y= a + bx; quadratic equation: y= a + bx + cx2 b degree of freedom c p-value
us
583
584
585
586
587
588
M
582
d
Ac ce p
581
an
te
577 578 579 580
cr
ip t
573
589
590
591
592
593
594
595
596
597
598
Page 28 of 35
29
601
602 603 604
Table 3 Repeatability, intermediate precision and recovery results of the developed HPTLC method for A7G Repeatability & intermediate precision Recovery intra A7Ga,b (mg) & Added 1. 2. 3. Found Recover A7Ga,d interA7G prepare prepare prepare A7Ge y (ng/spot) days d d d ( / t) ( / t) (%) intraday6.55 ± 6.41 ± 6.55 ± 1.c 0.22 0.13 0.11 100.5 intraday6.62 ± 6.68 ± 6.42 ± 2.5 2.51 ± 0.33 4 2.c 0.13 0.23 0.19 10.31 ± intraday6.70 ± 6.59 ± 6.54 ± 0.19 3.c 0.22 0.17 0.30
us
cr
ip t
599 600
2.69 2.97 3.05 6.63 ± 6.30 ± 6.54 ± interday 5 0.06 0.30 0.40 6.70 ± 6.59 ± 6.67 ± interday 0.13 0.25 0.42 6.60 ± 6.58 ± 6.55 ± interday 0.27 0.15 0.16 10 RSD (%) 2.37 3.82 4.65 a Mean ± SD, n = 3 b A7G amount in the lyophilized M. recutita cultivar c Applications of the HPTLC method d A7G amount in 1 µg/spot of the test solution of M. recutita cultivar e Mean ± SD, n = 6
102.1 1
10.20 ± 0.50
102.0
te
d
5.11 ± 0.28
Ac ce p
605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620
M
an
RSD (%)
Page 29 of 35
30 620 4'
OH
OH
O 1''
O
O
3'
1'
7
OH
2
OH
4
5 OH
O
L7G
OH
OH
ip t
HO HO
4' O 1'' OH
O
O 2
4
5 OH
A7G
O
te
d
M
an
us
Fig. 1. Chemical structures of L7G & A7G and developed HPTLC method in this study; 1: L7G; 2: A7G; *: remained part of L7G
Ac ce p
621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662
1'
7
cr
HO HO
Page 30 of 35
31
d
an
M d
Ac ce p
667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695
Fig. 2. (a) HPLC chromatogram of scraped A7G in test solution A; (b) HPLC chromatogram of test solution A (4 mg/ml; application: 20 µl) in this study; (c) HPTLC densitogram of scraped A7G in test solution A; (d) HPLC chromatogram of test solution A (4 mg/ml; application: 20 µl) found at the web address of the EDQM **: A7G; * & black arrow: co-existing compound
te
663 664 665 666
us
cr
c
b
ip t
a
Page 31 of 35
32
b
cr us an M d
Ac ce p
698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744
Fig. 3. HPTLC densitograms of (a) standard A7G (10 ng/spot) and (b) M. recutita (1 µg/spot) at 340 nm
te
696 697
ip t
a
Page 32 of 35
33 745
b
c
d
an
us
cr
ip t
a
Fig. 4. The scatter plot of residuals by fit values for the linear and quadratic models using standard A7G; (a) & (b) in the range of 5-50 ng/ spot; (c) & (d) in the range of 5-25 ng/ spot
748
749
750
751
Ac ce p
te
d
M
746 747
752
753
754
755
756
757
758
759
760
761
762
Page 33 of 35
34
us
an M d
Ac ce p
769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808
Fig. 5. HPTLC videodensitogram of standard A7G & plant materials (2 µg/spot) at 366 nm. Derivatization: NP/PEG 400. Applications 1: A7G (5 ng/spot), 2: A7G (25 ng/spot), 3: M. recutita (Istanbul), 4: M. recutita (Canakkale), 5: A. coelopoda var. coelopoda, 6: A. austriaca, 7: A. auriculata, 8: A. cretica, 9: A. cotula, 10: A. altissima, 11: A. tinctoria var. discoidea, 12: A. scariosa, 13: B. perennis, 14: B. sylvestris, 15: C. coronarium, 16: T. parthenium, 17: A7G (50 ng/spot)
te
763 764 765 766 767 768
cr
ip t
Page 34 of 35
35
an
Fig. 6. PCA performed on data sets of fingerprints obtained from the HPTLC plate images. 1 & 2: M. recutita, 3: A. coelopoda var. coelopoda, 4: A. austriaca, 5: A. scariosa, 6: A. cretica, 7: A. cotula, 8: A. altissima, 9: A. tinctoria var. discoidea, 10: A. auriculata, 11: B. perennis, 12: B. sylvestris, 13: C. coronarium, 14: T. parthenium
Ac ce p
te
d
M
810 811 812 813 814 815
us
cr
ip t
809
Page 35 of 35
S0731-7085(14)00627-X http://dx.doi.org/doi:10.1016/j.jpba.2014.12.021 PBA 9859
To appear in:
Journal of Pharmaceutical and Biomedical Analysis
Received date: Revised date: Accepted date:
11-11-2014 8-12-2014 14-12-2014
Please cite this article as: E. Guzelmeric, I. Vovk, E. Yesilada, Development and validation of an HPTLC method for apigenin 7-O-glucoside in chamomile flowers and its application for fingerprint discrimination of chamomilelike materials, Journal of Pharmaceutical and Biomedical Analysis (2014), http://dx.doi.org/10.1016/j.jpba.2014.12.021 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. 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.
1 1
Graphical Abstract
M
2
an
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cr
ip t
Matricaria recutita L.
Ac ce p
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3
Page 1 of 35
2 3
Highlights
4 5
• Chamomile is one of the most popular medicinal plants and used as a safe remedy.
6 7
• Chamomile-like flowers misidentification problem.
8 9
• Apigenin 7-O-glucoside is regarded as an active marker in chamomile flowers.
10 11
• An HPTLC method for quantification of apigenin 7-O-glucoside has been validated.
12
• Chamomile was discriminated from chamomile-like species.
consumed
due
to
us
cr
ip t
frequently
an
13
are
Ac ce p
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14
Page 2 of 35
3 14
Development and validation of an HPTLC method for apigenin 7-O-
15
glucoside in chamomile flowers and its application for fingerprint
16
discrimination of chamomile-like materials
21 22
Phytotherapy, Kayisdagi Cad., Atasehir, 34755, Istanbul, Turkey b
cr
20
Yeditepe University, Faculty of Pharmacy, Department of Pharmacognosy and
National Institute of Chemistry, Laboratory for Food Chemistry, Hajdrihova
19., SI-1000 Ljubljana, Slovenia
us
19
a
c
EN-FIST Centre of Excellence, Trg Osvobodilne fronte 13, SI-1000
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Etil Guzelmerica, Irena Vovkb,c, Erdem Yesiladaa*
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Ljubljana, Slovenia
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*Corresponding author: Prof. Dr. Erdem Yesilada
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Tel: +90 216 578 00 00 Fax: +90 216 578 00 68
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E-mail address: [email protected]
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30 31 32 33 34 35 36 37 38
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4 39
1. Introduction The dried flower heads of Matricaria recutita L. (synonym Chamomilla
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recutita (L.) Rauschert) (chamomile) from the family Asteraceae are among
42
the most popular, well-documented and universally recognized herbal drugs
43
[1–3]. In the world market, the annual consumption of chamomile flowers is
44
reported to be several thousands of tons [4]. In fact, daily worldwide
45
consumption of chamomile tea was speculated to be over one million cups [5].
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Brewed tea of chamomile flowers has been extensively utilized for
47
centuries due to either its pleasant and calming taste or medicinal purposes.
48
Bioassay-guided processing of chamomile flowers has revealed that many of
49
its healing benefits such as relieving painful gastrointestinal complaints, mild
50
sleep disorders and inflammatory diseases are highly related with its phenolic
51
content, in particular of apigenin and apigenin 7-O-glucoside (A7G) [6]. In
52
addition to therapeutic activity of A7G, it is one of the major constituents in
53
chamomile flowers [7–11]. Consequently in the European Pharmacopoeia (Ph.
54
Eur.) it is assessed as an active quality marker for M. recutita flowers by high
55
performance liquid chromatography (HPLC) [12].
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A7G and its metabolite apigenin have been shown to possess
57
remarkable
anti-spasmodic,
anti-inflammatory,
antioxidant
and
anti-
58
carcinogenic properties [6]. Recently scientific investigations have been
59
performed focusing on the biological effects of apigenin at cellular and
60
molecular levels i.e. sensitize cancer cells to apoptosis, inhibit cell growth and
61
angiogenesis [13]. Moreover apigenin may provide some additional benefits
62
beyond the available chemotherapeutics in slowing the emergence of
Page 4 of 35
5 63
metastatic diseases by blocking the chemokine signaling pathways, inhibiting
64
cell adhesion molecules and remodeling of the extracellular matrix [14]. On the other hand, the major problem is difficulty in distinguishing the
66
genuine specimen when supplying chamomile, M. recutita, through nature-
67
picking. Consequently flowers of other Asteraceae members resembling to
68
chamomile in appearance, i.e. Anthemis sp., Bellis sp., Chrysanthemum sp.,
69
Tanacetum sp., Tripleurospermum sp. etc. may also be gathered from nature by
70
people to be used as home remedy or for marketing in spice shops or bazaars.
71
This problem is solved in several countries by providing bulk chamomile of the
72
official quality from cultivars. However, in many parts of the world, nature-
73
picking raise severe quality problem. One of which is the increased toxicity
74
risk. Although chamomile flowers are known to be safe, there are records of
75
chamomile intoxication cases in the worldwide references due to identification
76
blunder [15]. For example, pyrrolizidine alkaloids in Senecio sp., resembling to
77
chamomile flowers, may induce severe hepatic veno-occlusive disease and
78
even cause of death [16]. The second problem is the concentration of the main
79
active ingredients that is important not only for its therapeutic benefits but also
80
for qualification of chamomile flowers.
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Several qualitative and quantitative methods have been developed for
82
the evaluation of A7G in chamomile flowers. Among these are methods based
83
on HPLC or ultra performance liquid chromatography (UPLC) with ultra-violet
84
(UV) [9,10] or mass (MS) [11,17] or tandem mass (MS2) spectrometric
85
detection
86
electrochromatography [20]. Recently an HPTLC method was developed either
87
for identification or quantification of some flavonoids such as A7G, rutin,
[18],
capillary
electrophoresis
[19]
and
capillary
Page 5 of 35
6 88
chamaemeloside etc. and one coumarin (umbelliferon) in chamomile flowers
89
[21]. In the present study, we first aimed to develop and validate a qualitative
91
and quantitative HPTLC method for A7G in chamomile flowers with the
92
guidance of the HPLC method described in the Ph. Eur. Secondly, the
93
validated HPTLC method was practiced to analyze A7G content in wild
94
chamomile flowers and several chamomile-like materials belong to 12 different
95
species i.e. Anthemis spp., Bellis spp., Chrysanthemum sp. and Tanacetum sp.
96
gathered by local people assuming as chamomile. Then, principal component
97
analysis (PCA) based on HPTLC plate images and comparative HPTLC
98
densitograms were used for discrimination of chamomile from chamomile-like
99
species.
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2.1. Chemicals
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HPLC grade acetonitrile and tetrahydrofuran were purchased from J. T.
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Baker (Deventer, the Netherlands) and HiPerSolv Chromanorm (Lutterworth,
104
England). The other solvents were of analytical grade. Ethanol absolute, ethyl
105
acetate, formic acid and acetone were from Sigma-Aldrich (Steinheim,
106
Germany); acetic acid, and 2-propanol were from Riedel-de Haen (Seelze,
107
Germany), o-phosphoric acid and ethyl methyl ketone were from Merck
108
(Darmstadt, Germany); methanol, dichloromethane and n-hexane were from
109
Analar Normapur (Muarrie, Australia). 2-aminoethyl diphenylborinate and
110
polyethylene glycol 400 were from Fluka (Steinheim, Germany) and Merck
111
(Hohenbrunn, Germany), respectively. The ultrapure water was obtained from
112
Millipore, Simplicity UV (Darmstadt, Germany).
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Standards of A7G, luteolin 7-O-glucoside (L7G), 5,7-dihydroxy-4-
114
methylcoumarin and the other chemicals which are sodium hydroxide and
115
magnesium
116
(Steinheim, Germany).
117
2.2. Plant Materials
were
purchased
from
Sigma-Aldrich
ip t
chloride-6-hydrate
Bodegold type M. recutita cultivar used in the HPTLC method
119
development and in the HPLC analysis was obtained from Ataturk Central
120
Horticultural Research Institute (Yalova, Turkey) in May 2011. The
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chamomile-like materials assumed to be M. recutita were gathered from nature
122
by local people from different localities in Turkey. The materials, collection
123
regions and years are listed in Table 1.
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The materials were identified by Prof. Dr. Galip Akaydın (Faculty of
125
Education, Hacettepe University, Ankara, Turkey), Assist. Prof. Dr. Gizem
126
Bulut (Faculty of Pharmacy, Marmara University, Istanbul, Turkey), Dr. M.
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Ufuk Özbek (Faculty of Science, Gazi University, Ankara, Turkey). The
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voucher specimen of materials has been kept in the Herbarium of the
129
Department of Pharmacognosy, Faculty of Pharmacy, Yeditepe University,
130
Turkey.
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All plant materials were kept away from direct sunlight and dried at
132
room temperature for two weeks. The dried materials were stored in a
133
refrigerator at – 25 ºC and ground to powder in a mechanic grinder before the
134
extraction.
135
2.3. Preparation of standard solutions
136
2.3.1. Standard solutions for HPLC analysis
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The reference solution A (12.5 µg/mL) and B (10 µg/mL) were
138
prepared according to the described procedure in the Ph. Eur. [12].
139
2.3.2. Standard solutions for HPTLC analysis and method validation A7G and L7G stock solutions (50 µg/mL) were separately prepared in
141
methanol and were used for the preparation of standard mixture (Mix2, 25
142
µg/mL), which was applied for the method development.
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Additional A7G stock solution (250 µg/mL) was prepared in methanol
144
and further diluted with the same solvent to prepare the working solutions 2.5,
145
5 and 10 µg/mL.
146
2.4. Preparation of detection reagents
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Natural Products (NP) and polyethylene glycol 400 (PEG 400) dipping
148
solutions were prepared according to the described procedure by Reich and
149
Schibli [22].
150
2.5. Preparation of sample test solutions
151
2.5.1. Extraction of M. recutita cultivar according to the Ph. Eur.
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The test solution A (4 mg/mL) was prepared according to the described
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procedure in the Ph. Eur. [12].
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2.5.2. Extraction of M. recutita cultivar for HPTLC analysis
155
Chamomile tea is the most preferred form in folkloric use of
156
chamomile. Therefore, aqueous solvent extraction method was applied to all
157
materials used in this study. Powdered chamomile flowers (2 g) were poured
158
by 100 mL of freshly boiled water and the beaker was then enclosed by watch
159
glass and kept at room temperature for 5 min for brewing (2% infusion). After
160
filtration through a filter paper, the filtrate was cooled and lyophilized (yield:
161
32.47%). Then, ten milligrams of lyophilizate was accurately weighed in
Page 8 of 35
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triplicate and extracted with 10 mL of methanol in an ultrasonic bath for 15
163
min. Suspended particles were removed by filtration through a 0.45 µm RC-
164
membrane filter. Finally, the sample test solutions (1 mg/mL) were diluted 2
165
times and used for the method validation.
166
2.5.3. Extraction of the plant materials gathered by local people
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The same extraction procedure was performed as described in 2.5.2.
168
The extract yields are given in Table 1. Ten milligrams of each lyophilizates
169
was then accurately weighed and extracted as described before. The final
170
concentration of the each sample test solutions was 1 mg/mL.
171
2.6. HPLC method
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HPLC system, HP1100 series (Agilents Technologies, Santa Clara,
173
California, USA) equipped with a vacuum degasser G1379A, a quaternary
174
pump
175
compartment G1316A, and a diode array detector G1315B, and Chemstation
176
10.01 software was used for the HPLC analysis. The separations were
177
performed on an Agilent Zorbax Eclipse Plus C18 ODS column (5 µm, 250 mm
178
x 4.6 mm, i.d.) according to the method described in the ‘Matricariae flos’
179
monograph in the Ph. Eur. [12].
180
2.7. HPTLC method
an
auto-sampler
G1313A,
a
thermo-stated
column
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G1311A,
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181
HPTLC analyses were performed on 20 cm x 10 cm glass HPTLC
182
plates coated with silica gel 60 NH2 F254s (Merck). Sample and standard
183
solutions were applied on the plates as 8 mm bands, 8 mm from the bottom
184
edge and 15 mm from the left edge by means of Linomat V sample applicator
185
(Camag, Muttenz, Switzerland) equipped with a 100 µL syringe (Hamilton,
186
Bonaduz, Switzerland). The plates were pre-conditioned with vapor of the
Page 9 of 35
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developing solvents ethyl acetate-formic acid-acetic acid-water (30:1.5:1.5:3,
188
v/v/v/v) for 10 min and then, developed up to 7 cm in the saturated (20 min)
189
Automatic Developing Chamber 2 (ADC2, Camag). The relative humidity was
190
fixed to 33% by a saturated MgCl2.6H2O solution. After development and 5
191
min of automatic drying quantitative evaluation of the plates was performed by
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TLC Scanner 3 (Camag) in absorption/reflectance mode at 340 nm, using slit
193
dimensions 6 mm x 0.30 mm the scanning speed 20 mm s-1 and the data
194
resolution 100 µm/step. The quantitative evaluations were established through
195
peak area via quadratic regression. For the visual documentation, the plates
196
were heated at 100˚C on the Camag TLC plate heater for 3 min and dipped into
197
NP and PEG 400 solutions, respectively. After derivatization, documentation
198
of the plates was performed by the Camag TLC visualizer at 366 nm. All these
199
instruments were operated by winCATS program (version 1.4.8, Camag)
200
2.8. Statistical analyses
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The applications of each analyzed solutions were performed in
202
triplicate. The results were presented as mean ± standard deviation (SD).
203
Statistical comparisons of several mean values were done by using one-way
204
analyses of variance (ANOVA), taking the appropriate condition as a single
205
factor. When the ANOVA leads to significant results, Least Significant
206
Difference (LSD) test was performed to identify where the differences occur.
207
The evaluation of curve estimation, Lack-of-fit test, and Pearson correlation
208
coefficients (r) calculation were also performed. Statistically significant
209
difference was defined as p < 0.05. The analyses were carried out by SPSS
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Data Editor (version 20.0). The HPTLC images of the plates were processed by
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the Image J processing program. PCA was performed by using MATLAB
212
(version 7.12.0)
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3. Results and discussion
214
3.1. HPLC analysis
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Initially, the system suitability was checked by the reference solution B
216
for the further analyses. The resolution (Rs) between the standards A7G and
217
5,7-dihydroxy-4-methylcoumarin was found as 7.54 ± 0.03 (n = 3), indicated
218
the suitability of the system according to the Ph. Eur. [12].
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The identity of the A7G in the test solution A was verified by
220
comparing the retention time (tR) with the reference solution A at 25ºC and
221
found as 6.50 ± 0.01. Moreover, the percentage content of A7G in M. recutita
222
cultivar was found as 0.70% which was higher than the official limit (0.25%)
223
[12]. Eventually, M. recutita cultivar was taken into account as a reference
224
plant material for HPTLC analysis.
225
3.2. HPTLC analysis and validation
226
3.2.1. Method optimization
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The method optimization is very challenging in plant extracts analyses
228
due to their chemical complexity. The method optimization in thin layer
229
chromatography contains several steps e.g. the type of the stationary phase,
230
composition of the developing solvents, chamber type and saturation,
231
application of the samples, development, derivatization, detection and
232
laboratory conditions [22].
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In this study, Mix2 was used due to similar chemical structures of the
234
standards A7G and L7G (Fig. 1) during the evaluation of the developing
Page 11 of 35
12 235
solvents and these standards assisted for the determination of the optimum
236
separation. The first step was to apply some developing solvent systems reported in
238
the previous studies for the separation of phenolic compounds [21–23]. The
239
second step was to test the combinations of the neat solvents, i.e. 2-propanol,
240
tetrahydrofuran, ethyl acetate, ethyl methyl ketone etc. with formic acid or
241
acetic acid to prevent fronting of the peaks on silica gel plates (firstly used due
242
to ease of availability and low price) and amino plates. The obtained results
243
provided to find various solvent mixtures in different ratios, i.e. acetone-n-
244
hexane-2-propanol-acetic acid (45:15:1:1 v/v/v/v); ethyl methyl ketone-water-
245
acetic acid (49:0.5:0.5 v/v/v); tetrahydrofuran-water-acetic acid-formic acid
246
(42:4:2:2 v/v/v/v) etc. In the all analyses, saturated twin trough chambers were
247
used. Finally, the best separation of the A7G and L7G was achieved using a
248
silica gel 60 NH2 F254s HPTLC glass plate and ethyl acetate-formic acid-acetic
249
acid-water (30:1.5:1.5:3, v/v/v/v) as a developing solvent system (Fig. 1). After
250
assessment of the stationary phase and developing solvent system some
251
modifications have been made, i.e. the plate was pre-conditioned and humidity
252
was controlled (33%) in order to get better resolution.
253
3.2.2. Methodological comparison of developed HPTLC and HPLC
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254
The separation power of the HPTLC method in this study was
255
compared with the HPLC method in the Ph. Eur. in order to demonstrate the
256
applicability of the developed HPTLC method.
257
Firstly, the test solution A and A7G standard solutions were applied to
258
HPTLC. After development, the zones belong to A7G were marked and
259
scraped from the surface of the plate layer. A7G was extracted from the layer
Page 12 of 35
13
by using ethanol 96% and filtered through a 0.45 µm RC-membrane filter and
261
then, solvent was evaporated by rotavapor. The residue was dissolved in 1 mL
262
of ethanol-initial mixture of the mobile phase (1:1 v/v) and applied to both
263
methods. Consequently, a co-existing compound with very low resolution
264
eluted together with A7G in the HPLC method (Figs. 2a and 2b), whereas this
265
compound could not clearly detected in the HPTLC method (Fig. 2c). On the
266
other hand, comparative evaluations of the HPTLC densitogram with that of
267
HPLC chromatogram (Fig. 2d) found at the web address of the European
268
Directorate for the Quality of Medicines & Health Care (EDQM) revealed that
269
this compound was co-eluted with A7G [24]. Consequently, due to the close
270
resolution patterns between HPTLC densitogram and HPLC chromatogram,
271
separation power of the developed HPTLC method was found to be appropriate
272
for further analysis.
273
3.2.3. Validation
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Following the International Committee on Harmonization (ICH)
275
guidelines, the developed HPTLC method was validated for stability,
276
robustness, specificity, limit of detection and quantification, linearity, precision
277
and recovery [25]. Renger et al. [26] have recently summarized the acceptance
278
criteria for complex matrices i.e. plant materials, herbal drugs, foodstuffs etc.
279
for required validation characteristics, therefore found values were compared
280
with the acceptance criteria.
281
3.2.3.1. Stability
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282
One of the drawbacks of HPTLC is being an open system. During
283
application by Linomat V, application positions are exposed to air and light.
284
Besides, mostly on normal phases due to highly active polar surfaces
Page 13 of 35
14
substances may undergo degradation. Therefore, duration of application
286
depends on the number of tracks, application volume, sorbent layer and the
287
effect of the solvent type should be considered during the method optimization.
288
For the evaluation of the stability, the following parameters were tested: the
289
stability of the A7G in methanol at different storing temperatures, the stability
290
of the A7G standard solution on the plate before development, and the stability
291
of the sample solution during the chromatography.
292
3.2.3.1.1. Stability of the A7G in methanol at different storing temperature
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The standard solutions of A7G (0.01 mg/mL) were stored at -80°C, -
294
20°C and 4°C during three weeks. As a result of statistical evaluation by one-
295
way ANOVA, significant changes in mean areas were not established in
296
samples kept at -80°C, -20°C, 4°C and the freshly prepared standard solutions
297
after three weeks, F(3,8) = 0.306, p = 0.821 (Fcrit(3,8) = 4.066).
298
3.2.3.1.1. Stability of the A7G standard on the plate before development
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The A7G standard solution (0.01 mg/mL) was freshly prepared and
300
applied on the plate in 30 min intervals from 0 to 120 min before development.
301
During these intervals the plate was left in an open area, exposed to air and
302
light. Interruptions in time intervals were evaluated by one-way ANOVA. As a
303
result, the mean areas were found to be different across time intervals, F(4,10) =
304
3.989, p = 0.035 (Fcrit(4,10) = 3.478). The LSD multiple comparisons performed
305
at the 0.05 significance level found that the mean area of freshly applied A7G
306
standard solution (M = 587.33, SD = 10.75, n = 3) was significantly different
307
than the average area of the A7G standard solutions, applied in 60 min (M =
308
541.97, SD = 33.45, n = 3), 90 min (M = 534.42, SD = 22.14, n = 3) and 120
309
min (M = 528.48, SD = 23.27, n = 3), but not significantly different than the
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Page 14 of 35
15 310
mean area of the A7G standard solutions, applied in 30 min (M = 576.30, SD =
311
18.82, n = 3).
312
3.2.3.1.3 Stability of the sample during chromatography Stability of the sample during chromatography was investigated by 2-
314
dimensional (2D) development. All components in the sample were detected
315
on the diagonal line connecting the application position and the intersection of
316
the 2 solvent fronts, indicated the stability of the sample.
317
3.2.3.2. Robustness
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The robustness of the method was evaluated by considering the effects
319
of some alterations. The following items were investigated during the testing of
320
robustness: duration of the plate preconditioning time, humidity, plate
321
prewashing and saturation. The ratios of the area of 0.01 mg/mL of standard
322
A7G and 0.5 mg/mL of sample solutions were used during the evaluation of
323
the described variations. The evaluated ratios were compared statistically by
324
using one-way ANOVA. As a result, the mean proportions were not found to
325
be different across variations, F(4, 10) = 0.242, p = 0.908.
326
3.2.3.3. Specificity
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327
The specificity of the method was ascertained by analyzing standard
328
and test solutions. The identity of A7G in the test solution of M. recutita was
329
evaluated by comparison of the retention factor (RF) with the standard solution
330
of A7G, (0.37 ± 0.01) at 22 ± 1°C (Fig. 3). The HPTLC videodensitogram at
331
366 nm and the spectrum of A7G belongs to standards and samples were also
332
used for the confirmation.
333
3.2.3.4. The limits of Detection and Quantification
Page 15 of 35
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0.5 µg/mL, 1 µg/mL and 2 µg/mL of A7G standard solutions were
335
applied on the different plates in triplicate with an increased application
336
volume (2-5 µL) to evaluate the limits of detection (LOD) and the limits of
337
quantification (LOQ). The visual and semi quantitative evaluation of the signal
338
to noise (S/N) ratios 3:1 for the LOD and 10:1 for the LOQ was assisted to
339
found 1.5 ng/spot and 5 ng/spot, respectively.
340
3.2.3.5. Linearity and calibration curve
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To avoid adverse effects of overloading on the application position in
342
HPTLC, starting near the LOQ and selecting the calibration ranges as low as
343
possible are recommended [27]. In this study, 2.5, 5 and 10 µg/mL of the
344
working standard solutions were prepared from freshly prepared 250 µg/mL
345
stock solutions and applied to HPTLC plates to obtain 5, 10, 15, 20, 25 and 50
346
ng/spot.
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The curve estimation option in SPSS was performed to compare linear
348
or quadratic regression models (Table 2), besides plotting the residuals and
349
Lack-of-fit tests were also done to evaluate how well the sets of data in the
350
range of 5-25 ng/spot and 5-50 ng/spot fit either with linear or quadratic
351
models. The high values of F- test for a significant correlation, probability was
352
lower than 0.05 for both models in both ranges, indicated that the variation
353
explained by each model was not due to chance. Secondly, the coefficient of
354
determination, R2 values indicated that there was a strong relationship between
355
both models and ranges. However, quadratic model of the R2 was higher than
356
the linear model in the range of 5-50 ng/spot (Table 2). The scatter plot of
357
residuals by fit values for the linear and quadratic models was the key point for
358
the selection of the model in this study. In the range of 5-50 ng/spot the scatter
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Page 16 of 35
17
plot of residuals by fit values for the linear model showed an ‘inverted U’
360
shaped pattern (Fig. 4a), indicated that there was a pattern in the data that was
361
not captured by the linear model, whereas the scatterplot of residuals by fit
362
values for the quadratic model did not show a pattern (Fig. 4b), thus the
363
quadratic model was acceptable in sense the residuals were independent of the
364
fit values. On the other hand, in the range of 5-25 ng/spot the scatter plot of
365
residuals by fit values for the linear and quadratic models also did not show a
366
pattern (Fig. 4c and 4d). In addition, Lack-of-fit test illustrated the probability
367
of the F-test statistic (F(3,10) = 0.844) was p = 0.501, greater than the alpha level
368
of significance of 0.05. These findings also supported that linear regression
369
model was appropriate in the range of 5-25 ng/spot range.
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359
In this study, instead of working in the range of 5-25 ng/spot widening
371
the calibration curve by adding one more standard as 50 ng/spot was decided to
372
be more useful due to the calculations of the recovery results.
373
3.2.3.6. Precision
374
3.2.3.6.1. Repeatability
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375
The intraday precision of the method was performed by replicating the
376
experiment in triplicate with three times freshly prepared samples during the
377
day. The mean of the A7G amount in samples, standard deviations (SD) and
378
relative standard deviations (RSD) was shown in Table 3.
379
3.2.3.6.2. Intermediate Precision
380
The intermediate precision of the method was examined by freshly
381
prepared samples in triplicate on consecutive three days. The determined
382
intermediate precision showed similar deviations as intraday (Table 3).
Page 17 of 35
18
RSD for repeatability and intermediate precision were found in the
384
range of acceptance criteria, RSD should be less than 10% for repeatability and
385
for intermediate precision it should be within the range from 1.3 to 1.7 x RSD
386
of repeatability [26].
387
3.2.3.7. Recovery
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383
Due to impossibility to reconstitute a blank matrix, the accuracy of the
389
proposed method was evaluated as recovery and 2.5, 5, and 10 ng/spot of
390
standard A7G was added to the pre-analyzed sample, respectively. The average
391
percentages of recovery of the added standard A7G shown in Table 3 was
392
found to be in the range of acceptance criteria [26].
393
3.3. Evaluation of chamomile and chamomile-like flowers
M
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The chamomile-like flowers assumed to be M. recutita were gathered
395
from nature by local people from 24 different localities in Turkey. The
396
botanical identification of these plant materials have been revealed that they
397
were 13 different species belonging to 5 different types of genus, Matricaria
398
L., Anthemis L., Bellis L., Chrysanthemum L. and Tanacetum L. Surprisingly,
399
among them only 2 materials were identified as M. recutita. In addition to our
400
findings, Joharchi and Amiri [28] also concluded that M. recutita was the most
401
adulterated and substituted plant with other species belonging to the family
402
Asteraceae due to some morphological similarities.
Ac ce p
te
d
394
403
In this study, A7G was determined and quantified in the chamomile-
404
like flowers gathered by people from different localities. That is because; the
405
brewed tea of chamomile-like flowers should contain A7G to meet with the
406
therapeutic expectations of local people. Presence of A7G in the samples was
407
monitored by comparing the RF values and the spectra of the corresponding
Page 18 of 35
19
retention zones with that of the standard A7G. Consequently, A7G was found
409
in the wild M. recutita samples from two different localities along with A.
410
coelopoda var. coelopoda, A. austriaca, A. auriculata, A. cretica, B. perennis
411
and B. sylvestris samples. Subsequently, the amount of A7G was evaluated in
412
these species as shown in Table 1. When the content A7G was compared in
413
wild M. recutita samples, it was found that A7G concentration was quite
414
different in two wild samples collected from different locations; Istanbul (1.90
415
mg) and Canakkale (below LOQ) (Table 1). On the other hand, A7G contents
416
of these wild M. recutita samples were found to be lower than the cultivar
417
sample. This might be due to controlled growth of chamomile under cultivation
418
which eliminates variations in geographical conditions such as rainfall,
419
temperature, soil, altitude, humidity etc. On the other hand, A7G was not
420
identified in A. cotula, A. altissima, A. tinctoria var. discoidea, A. scariosa, C.
421
coronarium and T. parthenium samples.
te
d
M
an
us
cr
ip t
408
It should be underlined that although A7G is an active marker, it should
423
not be considered as a chemotaxonomic marker for discriminating chamomile
424
and chamomile-like flowers. Therefore, PCA processing based on fingerprints
425
obtained from the HPTLC plate images at 366 nm (Fig. 5) and comparative
426
HPTLC densitograms belong to plant materials at 340 nm were used for the
427
interpretation of the results more efficiently during the discrimination of
428
chamomile from chamomile-like flowers.
Ac ce p
422
429
PCA is one of the mostly used techniques in multivariate analysis
430
which classifies samples according to their similarities. The visual
431
documentation of the HPTLC plate images were processed as previously
432
described by Ristivojević et al. [29]. PCA processing has revealed that M.
Page 19 of 35
20
recutita samples from different localities and A. coelopoda. var. coelopada
434
were classified under the same group (Fig. 6), which might be due to the close
435
chemical fingerprinting of these species at 366 nm. However, during the
436
comparison of the densitograms especially the regions from start to RF= 0.40 at
437
340 nm, it was clearly observed that M. recutita possesses a different chemical
438
fingerprint profile than that of A. coelopoda var. coelopada. Consequently, by
439
using PCA processing and comparison of densitograms chamomile was
440
successfully discriminated from the chamomile-like species.
441
4. Conclusion
an
us
cr
ip t
433
The usage of chamomile tea as a remedy has a history of thousands of
443
years in traditional medicine. However, due to difficulty in distinguishing the
444
genuine specimen, the flowers of other Asteraceae members resembling to
445
chamomile in appearance may also be used or marketed. The validated HPTLC
446
method in this study was successfully applied either for quantification of the
447
A7G in chamomile and chamomile-like flowers or discrimination of genuine
448
chamomile from other species from Asteraceae. In addition, HPTLC
449
densitograms belong to M. recutita and 12 different species presented in this
450
study may also be a leading guide for the quality assessment of chamomile tea
451
products on the market.
452
Acknowledgements
Ac ce p
te
d
M
442
453
Etil Guzelmeric would like to state her deep gratitude to the Turkish
454
Scientific and Technical Research Council (TUBITAK) for the scholarship
455
provided during the Ph. D. program. She is also thankful to the CAMAG
456
Laboratory team (Muttenz, Switzerland), Galip Akaydın (Faculty of Education,
457
Hacettepe University, Ankara, Turkey), Gizem Bulut (Faculty of Pharmacy,
Page 20 of 35
21
Marmara University, Istanbul, Turkey), Jelena Trifković (Faculty of
459
Chemistry, University of Belgrade, Belgrade, Serbia), Laboratory for Food
460
Chemistry team (National Institute of Chemistry, Ljubljana, Slovenia), M.
461
Ufuk Özbek (Faculty of Science, Gazi University, Ankara, Turkey), Petar
462
Ristivojević (Innovation Centre of Faculty of Chemistry Ltd., University of
463
Belgrade, Belgrade, Serbia) for their great contributions during the study.
464
References
465
[1] R. Franke, H. Schilcher, Chamomile industrial profiles, first ed., Taylor &
466
Francis Group, Boca Raton, USA, 2005.
467
[2] O. Gacea, M. Hancianu, C. Aprotosoaie, A. Spac, V. Dorneanu, U.
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Stanescu, The pharmaceutical quality of some medicinal teas of Chamomillae
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flos, Acta Hort. 749 (2007) 175-179.
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[3] N. Mulinacci, A. Romani, P. Pinelli, F.F. Vincieri, D. Prucher,
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Characterization of Matricaria recutita L. flower extracts by HPLC-MS and
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HPLC-DAD analysis, Chromatographia 51(5/6) (2000) 301-307.
473
[4] I. Šalamon, I. Sudimáková, Quality of chamomile teas- Essential oil content
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and its composition, Acta Hort. 749 (2007) 181-186.
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[5] J.K. Srivastava, S. Gupta, Antiproliferative and apoptotic effects of
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chamomile extract in various human cancer cells, J. Agric. Food Chem. 55
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[6] D.L. McKay, J.B. Blumberg, A review of the bioactivity and potential
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health benefits of chamomile tea (Matricaria recutita L.), Phytother. Res. 20
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biological activity of flavonoids isolated from chamomile flowers, Mol. Cell.
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Pharmacol. 1(3) (2009) 138-147.
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[8] J.K. Srivastava, M. Pandey, S. Gupta, Chamomile, a novel and selective
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COX-2 inhibitor with anti-inflammatory activity, Life Sci. 85(19/20) (2009)
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[9] G. Haghi, A. Hatami, A. Safaei, M. Mehran, Analysis of phenolic
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compounds in Matricaria chamomilla and its extracts by UPLC-UV, Res.
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Pharm. Sci. 9(1) (2014) 31-37.
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[10] M. Repćák, T. Krausová, Phenolic glucosides in the course of ligulate
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flower development in diploid and tetraploid Matricaria chamomilla, Food
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Chem. 116 (2009) 19-22.
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[11] B. Weber, M. Herrmann, B. Hartmann, H. Joppe, C.O. Schmidt, H.J.
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Bertram, HPLC/MS and HPLC/NMR as hyphenated techniques for accelerated
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characterization of the main constituents in Chamomile (Chamomilla recutita
496
[L.] Rauschert), Eur. Food Res. Technol. 226 (2008) 755-760.
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[12] European pharmacopoeia (Ph. Eur.), Seventh ed., Council of Europe,
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Strasbourg, France, 2010.
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[13] D. Patel, S. Shukla, S. Gupta, Apigenin and cancer chemoprevention:
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progress, potential and promise (review), Int. J. Oncol. 30 (2007) 233-245.
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[14] É.C. Lefort, J. Blay, Apigenin and its impact on gastrointestinal cancers,
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Mol. Nutr. Food Res. 57 (2013) 126-144.
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[15] Z. Chen, J.R. Huo, Hepatic veno-occlusive disease associated with
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toxicity of pyrrolizidine alkaloids in herbal preparations, Neth. J. Med. 68(6)
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supplement hepatotoxicity, Aliment. Pharmacol. Ther. 37(1) (2013) 3-17.
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[17] B. Avula, Y.H. Wang, M. Wang, C. Avonto, J. Zhao, T.J. Smillie, D. Rua,
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I.A. Khan, Quantitative determination of phenolic compounds by UHPLC-UV-
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MS and use of partial least-square discriminant analysis to differentiate chemo-
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types of Chamomile/Chrysanthemum flower heads, J. Pharm. Biomed. Anal.
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88 (2014) 278-288.
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[18] L. Z. Lin, J.M. Harnly, LC-PDA-ESI/MS Identification of the phenolic
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components of three Compositae spices: Chamomile, Tarragon, and Mexican
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Arnica, Nat. Prod. Commun. 7(6) (2012) 749-752.
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[19] F.N. Fonseca, M.J. Kato, L. Oliveira Jr., N.P. Neto, M.F.M. Tavares,
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Critical assessment of electrolyte systems for the capillary electrophoresis
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analysis of phenolic compounds in herbal extracts, J. Microcolumn Sep. 13(6)
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(2001) 227-235.
520
[20]
521
electrochromatography of selected phenolic compounds of Chamomilla
522
recutita, J. Chromatogr. A 1154 (2007) 390-399.
523
[21] S. Sagi, B. Avula, Y.H. Wang, J. Zhao, I.A. Khan, Quantitative
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determination of seven chemical constituents and chemo-type differentiation of
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chamomiles using high-performance thin-layer chromatography, J. Sep. Sci.
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37(19) (2014) 2797-2804.
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[22] E. Reich, A. Schibli, High Performance Thin Layer Chromatography for
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the Analysis of Medicinal Plants, first ed., Thieme, Stuttgart, New York, 2007.
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[23] G. Sacchetti, C. Romagnoli, M. Ballero, B. Tosi, F. Poli, Internal secretory
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structures and preliminary phytochemical investigation on flavonoid and
te Fonseca,
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Tavares,
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Horváth,
Capillary
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coumarin content in Santolina insularis (Asteraceae), Phyton 37 (1997) 219-
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228.
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[24] European Directorate for the Quality of Medicines & Health Care
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(EDQM), Edqm knowledge database – ‘’Matricariae flos’’, 1996.
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[25] International Conference on Harmonisation (ICH), ICH Harmonised
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Tripartite
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Methodology Q2 (R1), 2005.
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[26] B. Renger, Z. Végh, K. Ferenczi-Fodor, Validation of thin layer and high
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performance thin layer chromatographic methods, J. Chromatogr. A 1218
540
(2011) 2712-2721.
541
[27] S.A. Coran, S. Mulas, N. Mulinacci, Crucial aspects of high performance
542
thin layer chromatography quantitative validation. The case of determination of
543
rosmarinic acid in different matrices, J. Chromatogr. A 1220 (2012) 156-161.
544
[28] M.R. Joharchi, M.S. Amiri, Taxanomic evaluation of misidentification of
545
crude herbal drugs marketed in Iran, Avicenna J. Phytomed. 2(2) (2012) 105-
546
112.
547
[29] P. Ristivojević, F.Lj. Andrić, J.Ð. Trifković, I. Vovk, L.Ž. Stanisavljević,
548
Ž.Lj. Tešić, D.M. Milojković-Opsenica, Pattern recognition methods and
549
multivariate image analysis in HPTLC fingerprinting of propolis extracts, J.
550
Chemometr. 28 (2014) 301-306.
of
Analytical Procedures: Text and
Ac ce p
te
d
M
an
us
cr
Guideline Validation
ip t
531
551
Page 24 of 35
25 Table 1 Plant materials: Collection region & year, yield, A7G amount and HPTLC densitograms Plant Materials Region & Year A7G (mg)a HPTLC densitogramsb Yield (%) Matricaria recutita L.
Istanbul, June 2012; 17.58%
1.90 ± 0.16
Matricaria recutita L.
Canakkale, May 2012; 20.47%
< LOQ
Anthemis coelopoda Boiss. var. coelopoda Boiss.
Izmir, May 2012; 23.49%
an
us
cr
ip t
551 552
te
d
M
1.72 ± 0.05
Ac ce p
Anthemis austriaca Jacq.
Anthemis auriculata Boiss.
553
554 555
Ankara, July 2011; 19.98%
1.60 ± 0.07
Bursa, June 2011; 13.90%
< LOQ
556
Page 25 of 35
26 557 558
Table 1 Continued Plant
Region & Year Yi ld (%) Istanbul, May 2012; 26.13%
)a < LOQ
(
Istanbul, June 2011; 32.45%
ndt
Anthemis altissima L.
Bursa, June 2012; 16.81%
ndt
te
d
M
an
us
Anthemis cotula L.
cr
ip t
M t i l Anthemis cretica L.
HPTLC densitogramsb
A7G
Istanbul, June 2012; 19.71%
ndt
Anthemis scariosa Banks et Sol.
Adana, June 2012 20.65%
ndt
Ac ce p
Anthemis tinctoria L. var. discoidea (All) D.C
559 560
561
Page 26 of 35
27 562 563
Table 1 Continued Plant
HPTLC densitogramsb
A7G )a < LOQ
(
Amasra, September 2012; 30.60%
< LOQ
Chrysanthemum coronarium L.
Mugla, April 2012; 21.30%
ndt
te
d
M
an
us
Bellis sylvestris Cyr.
cr
ip t
M t i l Bellis perennis L.
Region & Year Yi ld (%) Istanbul, May 2011; 27.08%
Istanbul, June 2011; 20.70%
ndt
Ac ce p
Tanacetum parthenium L.
ndt: A7G not detected; < LOQ: under the limit of quantification a A7G amount in the lyophilized plant materials; Mean ± SD (n = 3) b HPTLC densitograms of plant materials (2 µg/spot) at 340 nm
564 565 566 567 568
569
570
571
572
Page 27 of 35
28
574 575 576
Table 2 Linear and quadratic model comparisons for standard A7G in the range of 5-25 ng/spot and 550 ng/spot Range Model Summary Parameter Estimates (ng/spot) Modelsa R2 F dfb1 dfb2 Sig.c a b c n Linear 0.996 2925.50 1 13 0.00 16.07 33.21 15 5-25 Quadratic 0.996 1620.91 2 12 0.00 37.78 15 10.64 0.15 Linear 0.997 6169.48 1 16 0.00 48.98 30.78 15 5-50 Quadratic 0.999 8065.50 2 15 0.00 -0.93 36.04 18 0.09 a Regression models: Linear equation: y= a + bx; quadratic equation: y= a + bx + cx2 b degree of freedom c p-value
us
583
584
585
586
587
588
M
582
d
Ac ce p
581
an
te
577 578 579 580
cr
ip t
573
589
590
591
592
593
594
595
596
597
598
Page 28 of 35
29
601
602 603 604
Table 3 Repeatability, intermediate precision and recovery results of the developed HPTLC method for A7G Repeatability & intermediate precision Recovery intra A7Ga,b (mg) & Added 1. 2. 3. Found Recover A7Ga,d interA7G prepare prepare prepare A7Ge y (ng/spot) days d d d ( / t) ( / t) (%) intraday6.55 ± 6.41 ± 6.55 ± 1.c 0.22 0.13 0.11 100.5 intraday6.62 ± 6.68 ± 6.42 ± 2.5 2.51 ± 0.33 4 2.c 0.13 0.23 0.19 10.31 ± intraday6.70 ± 6.59 ± 6.54 ± 0.19 3.c 0.22 0.17 0.30
us
cr
ip t
599 600
2.69 2.97 3.05 6.63 ± 6.30 ± 6.54 ± interday 5 0.06 0.30 0.40 6.70 ± 6.59 ± 6.67 ± interday 0.13 0.25 0.42 6.60 ± 6.58 ± 6.55 ± interday 0.27 0.15 0.16 10 RSD (%) 2.37 3.82 4.65 a Mean ± SD, n = 3 b A7G amount in the lyophilized M. recutita cultivar c Applications of the HPTLC method d A7G amount in 1 µg/spot of the test solution of M. recutita cultivar e Mean ± SD, n = 6
102.1 1
10.20 ± 0.50
102.0
te
d
5.11 ± 0.28
Ac ce p
605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620
M
an
RSD (%)
Page 29 of 35
30 620 4'
OH
OH
O 1''
O
O
3'
1'
7
OH
2
OH
4
5 OH
O
L7G
OH
OH
ip t
HO HO
4' O 1'' OH
O
O 2
4
5 OH
A7G
O
te
d
M
an
us
Fig. 1. Chemical structures of L7G & A7G and developed HPTLC method in this study; 1: L7G; 2: A7G; *: remained part of L7G
Ac ce p
621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662
1'
7
cr
HO HO
Page 30 of 35
31
d
an
M d
Ac ce p
667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695
Fig. 2. (a) HPLC chromatogram of scraped A7G in test solution A; (b) HPLC chromatogram of test solution A (4 mg/ml; application: 20 µl) in this study; (c) HPTLC densitogram of scraped A7G in test solution A; (d) HPLC chromatogram of test solution A (4 mg/ml; application: 20 µl) found at the web address of the EDQM **: A7G; * & black arrow: co-existing compound
te
663 664 665 666
us
cr
c
b
ip t
a
Page 31 of 35
32
b
cr us an M d
Ac ce p
698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744
Fig. 3. HPTLC densitograms of (a) standard A7G (10 ng/spot) and (b) M. recutita (1 µg/spot) at 340 nm
te
696 697
ip t
a
Page 32 of 35
33 745
b
c
d
an
us
cr
ip t
a
Fig. 4. The scatter plot of residuals by fit values for the linear and quadratic models using standard A7G; (a) & (b) in the range of 5-50 ng/ spot; (c) & (d) in the range of 5-25 ng/ spot
748
749
750
751
Ac ce p
te
d
M
746 747
752
753
754
755
756
757
758
759
760
761
762
Page 33 of 35
34
us
an M d
Ac ce p
769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808
Fig. 5. HPTLC videodensitogram of standard A7G & plant materials (2 µg/spot) at 366 nm. Derivatization: NP/PEG 400. Applications 1: A7G (5 ng/spot), 2: A7G (25 ng/spot), 3: M. recutita (Istanbul), 4: M. recutita (Canakkale), 5: A. coelopoda var. coelopoda, 6: A. austriaca, 7: A. auriculata, 8: A. cretica, 9: A. cotula, 10: A. altissima, 11: A. tinctoria var. discoidea, 12: A. scariosa, 13: B. perennis, 14: B. sylvestris, 15: C. coronarium, 16: T. parthenium, 17: A7G (50 ng/spot)
te
763 764 765 766 767 768
cr
ip t
Page 34 of 35
35
an
Fig. 6. PCA performed on data sets of fingerprints obtained from the HPTLC plate images. 1 & 2: M. recutita, 3: A. coelopoda var. coelopoda, 4: A. austriaca, 5: A. scariosa, 6: A. cretica, 7: A. cotula, 8: A. altissima, 9: A. tinctoria var. discoidea, 10: A. auriculata, 11: B. perennis, 12: B. sylvestris, 13: C. coronarium, 14: T. parthenium
Ac ce p
te
d
M
810 811 812 813 814 815
us
cr
ip t
809
Page 35 of 35