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Simultaneous determination of food-related biogenic amines and precursor amino acids using in situ derivatization ultrasoundassisted dispersive liquid-liquid microextraction by ultra high performance liquid chromatography tandem mass spectrometry Yongrui He, Xian-En Zhao, Renjun Wang, Na Wei, Jing Sun, Jun Dang, Guang Chen, Zhiqiang Liu, Shuyun Zhu, and Jin-Mao You J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.6b03536 • Publication Date (Web): 14 Oct 2016 Downloaded from http://pubs.acs.org on October 16, 2016
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Journal of Agricultural and Food Chemistry
Simultaneous determination of food-related biogenic amines and precursor amino acids using in situ derivatization ultrasound-assisted dispersive liquid-liquid microextraction by ultra high performance liquid chromatography tandem mass spectrometry Yongrui Hea, Xian-En Zhaoa*, Renjun Wanga, Na Weia, Jing Sunb, Jun Dangb, Guang Chena, Zhiqiang Liuc, Shuyun Zhua*, Jinmao Youa,b* a
Shandong Provincial Key Laboratory of Life-Organic Analysis & Key Laboratory of
Pharmaceutical Intermediates and Analysis of Natural Medicine, College of Chemistry and Chemical Engineering, Qufu Normal University, Qufu 273165, Shandong, P. R. China; b
Qinghai Key Laboratory of Qinghai-Tibet Plateau Biological Resources & Key Laboratory of
Tibetan Medicine Research, Northwest Institute of Plateau Biology, Chinese Academy of Science, Xining 810001, Qinghai, P. R. China; c
National Center for Mass Spectrometry in Changchun & Key Laboratory for Traditional Chinese
Medicine Chemistry and Mass Spectrometry of Jilin Province, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, 5625 Renmin Street, Changchun 130022, P. R. China
*Corresponding author: Dr. Xian-En Zhao, E-mail:
[email protected] (Zhao XE), Dr. Shuyun Zhu,
E-mail:
[email protected] (Zhu
SY),
and
Prof.
Jinmao
[email protected] (You JM), Tel: +86-537-4458501, Fax: +86-537-4456305.
1
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You,
E-mail:
Journal of Agricultural and Food Chemistry
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ABSTRACT
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A simple, rapid, sensitive, selective and environmentally friendly method, based on in situ
3
derivatization ultrasound-assisted dispersive liquid-liquid microextraction (in situ DUADLLME)
4
coupled with ultra high performance liquid chromatography tandem mass spectrometry
5
(UHPLC-MS/MS) using multiple reaction monitoring (MRM) mode has been developed for the
6
simultaneous determination of food-related biogenic amines and amino acids. A new mass
7
spectrometry sensitive derivatization reagent 4’-carbonyl chloride rosamine (CCR) was designed,
8
synthesized and firstly reported. Parameters and conditions of in situ DUADLLME and
9
UHPLC-MS/MS were optimized in detail. Under the optimized conditions, the in situ
10
DUADLLME was completed speedily (within 1 min) with high derivatization efficiencies (≥
11
98.5%). With the clean-up and concentration of microextraction step, good analytical performance
12
was obtained for the analytes. The results showed that this method was accurate and practical for
13
quantification of biogenic amines and amino acids in common food samples (red wine, beer, wine,
14
cheese, sausage and fish).
15 16
KEYWORDS:
17
microextraction, amino acids, biogenic amines, UHPLC-MS/MS (MRM).
in
situ
derivatization,
ultrasound-assisted
18 19 20 21 22 23 2
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dispersive
liquid-liquid
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INTRODUCTION
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Amino acids (AAs) and biogenic amines (BAs) are natural compounds which occur in kinds of
26
foods, such as drinks,1-3 fish,2,4,5 cheese,6,7 and meatproducts,2,8 and many of them have powerful
27
physiological effects and important biological activities.9,10 Based on the number of amines, BAs
28
are commonly divided into monoamines, such as histamine (HIM), tyramine (TYM), tryptamine
29
(TRM), 2-phenylethylamine (PEA), and diamines or polyamines such as putrescine (PUT),
30
cadaverine (CAD), and agmatine (AGM). BAs are usually comes from the decarboxylation of AAs
31
in foods. The BAs above are formed from histidine (His), tyrosine (Tyr), tryptophan (Try),
32
2-phenylethylalanine (Phe), ornithine (Orn), lysine (Lys) and arginine (Arg) respectively. Ornithine
33
(Orn) and citrulline (Cit) can arise from arginine (Arg) and polyamines such as spermidine (SPD),
34
and spermine (SPM) arise from PUT. The biosynthesis pathways of AAs and BAs are demonstrated
35
in Figure 1.
36
It has been suggested that the dietary intake of low levels of biogenic amines has several health
37
benefits.9,11 However, when take in excessive amounts, they may cause with physiological
38
functions which are classified as psychoactive and vasoactive amines based on their physiological
39
impacts on humans. Vasoactive amines such as TYM, TRM and PEA impact on the vascular
40
system, and the amines act on psychology such as HIM, PUT, and CAD.10 Maximum limit of HIM
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has been strictly limited by the EU and USA. According to the toxic dose of HIM, it could be
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divided into slight poisoning (8-40 mg/kg); intermediate poisoning (40-100 mg/kg) and intensive
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poisoning (100 mg/kg or higher).10 And in fermented foods the acceptable levels of HIM, TYM,
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and PEA were 50-100 mg/kg, 100-800 mg/kg, and 30 mg/kg, respectively.12 The rapid and reliable
45
analysis methods of the AAs and BAs contents in foods are important to human health and food
46
safety evaluation. 3
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In order to monitor AAs and BAs levels, a variety of analytical techniques have been used to
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determine AAs and BAs in different kind of foods10 include capillary electrophoresis (CE), gas
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chromatography (GC) and most commonly liquid-chromatography (LC), in combination with
50
several detectors2,13-20 are widely used for separation purposes of foodstuffs. Among these methods,
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ultra high-performance liquid chromatography coupled with tandem mass spectrometry
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(UHPLC-MS/MS) using multiple reactions monitoring (MRM) detection has been acted as a
53
powerful technique for its speediness, high sensitivity and selectivity, and applicability.
54
However, most UHPLC-MS/MS methods for determination of AAs and BAs still lack sufficient
55
retention time and separation, and there are some difficulties during the simultaneous analysis of
56
AAs and BAs in food and biological with complex matrices. In turn, chemical derivatization by
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introducing a functional group into the analyte molecules is an efficient way to solve these
58
problems.21,22 The most common derivatization reagents including ethoxymethylenemalonate
59
(DEEMM),3,6
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6-aminoquinolyl-N-hydroxy succinimidyl carbamate (AQC),23 2,6-Dimethyl-4-quinolinecarboxylic
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acid N-hydroxysuccinimide ester (DMQC-OSu),16 diethyl dansyl chloride (DNS-Cl),7,8,17
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benzoylchloride,21
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9-fluorenylmethyl chloroformate (FMOC).26 A derivatization step facilitates the retentions,
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enhances ionization efficiency, decreases endogenous interference, increases sensitivity and
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selectivity, and now greener derivatization in analytical chemistry has been emphasized which have
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been reported by Feng et al.10,22,27 However, there are some limitations of these pre-column
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derivatization reagents during when to use such as low sensitivity, operational inconvenience, poor
68
stability, difficult synthesis, or serious interferences in chromatogram.10,28 A novel MS sensitive
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derivatization reagent 4’-carbonyl chloride rosamine (CCR) which has a permanent positive
dansyl
chloride,8
2-chloro-1,3-dinitro-5-(trifluoromethyl)-benzene(CNBF),1,12
o-phthaldialdehyde
(OPA),24
1,2-naphthoquinone-4-sulfonate
4
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charged moiety, was firstly designed, synthesized and applied in this work for AAs and BAs
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determination.
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However, the derivatization step may bring in mass matrix interference, which comes from
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excess derivatization reagent and catalyst, for the following UHPLC-MS/MS detection. Therefore,
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in order to obtain accurate determination results a pretreatment step for cleansing is necessary. A
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variety of methods have been developed, such as solid-phase extraction,6,20,29 hollow fibre
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liquid-phase microextraction30 or more recently dispersive liquid liquid microextraction
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(DLLME).15,16,19,26 The advantages of DLLME technique are obvious such as speediness, good
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recovery, high sensitivity and selectivity, simplicity to operate, and low cost. Recently, a variety of
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modifications of the primary DLLME have been reported such as ionic liquid-based DLLME,
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ultrasound-assisted DLLME, low-toxicity DLLME, dual DLLME and novel automated
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DLLME.31-33
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In this work, a low toxic in situ derivatization ultrasound-assisted dispersive liquid-liquid
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microextraction (in situ DUADLLME) has been established for the simultaneous determination of
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8 AAs and 9 BAs by UHPLC-MS/MS (MRM). A schematic of in situ DUADLLME procedure of
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this work was shown in the abstract graphic. The derivatization and microextraction of these
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compounds were performed in a single step, allowing the simplification of the procedure and a
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decrease in the time of sample handling.21,30,34-36 Various factors affecting DUADLLME and
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UHPLC-MS/MS conditions were evaluated and optimized. The aim of this work is to establish an
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efficient, simple, quick, and sensitive analytical scheme for the simultaneous determination of a
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range of AAs and BAs in several food samples.
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MATERIALS AND METHODS 5
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Chemicals and Reagents. Standards of AAs and BAs (purity > 99.9%) and 1,7-diaminoheptane
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(internal standard, IS) were purchased from Sigma-Aldrich (St. Louis, MO, USA). Chloroform,
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tetrachloromethane, 1-bromo-3-methylbutane, bromocyclohexane, bromobenzene, 1-bromooctane,
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methanol, acetone, ethanol and acetonitrile were purchased from Shanghai Chemical Reagent
97
(Shanghai, China). HPLC grade acetonitrile (ACN) was purchased from Sigma (St. Louis, MO,
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USA). High-purity, deionized water was purified from a Millipore Milli-Q Water system (Bedford,
99
MA, USA). Other reagents were of HPLC grade of analytical grade obtained commercially.
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Preparation of CCR. The synthesis reaction schematic of CCR is shown in Figure 2.
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Synthesis of 4’-carboxy-substituted rosamine (CSR) was described in our previously reported.36 In
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this work, derivatization reagent CCR was synthesized for the first time as follows: 0.922 g of CSR,
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30.0 mL of thionyl chloride and 0.1 mL of N,N-dimethyl formamide were added into a 100 mL of
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single-necked flask. After stirring at 80 °C for 6 h, the solution was concentrated by a rotary
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evaporator to yield a purple residue. The crude product was recrystallized from diethyl ether to give
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the purple crystal 0.42 g (CCR, yield 45.5%). The ESI-MS molecular ion of the derivative of
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CCR-phenylamine was at m/z 518.3 ([M+H]+). The absorption maximum was at 558 nm in ethanol.
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1
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CH2), 6.93 (d, J = 2.4 Hz, 2 H, 4-H and 5-H), 7.01 (dd, J = 9.6, 2.4 Hz, 2 H, 2-H and 7-H), 7.39 (d,
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J = 9.6 Hz, 2 H, 1-H and 8-H), 7.45 (d, J = 8.4 Hz, 2 H, 2’-H and 6’-H), 8.10 (d, J = 8.4Hz, 2 H,
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3’-H and 5’-H) ppm.
HNMR (400 MHz, CD3Cl): δ = 1.32 (t, J =7.2 Hz, 12 H, 4 × CH3), 3.68 (q, J = 7.2 Hz, 8 H, 4 ×
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Preparation of Standard Solutions and Derivatization Reagent. Stock solutions
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(1g/L) of AAs and BAs were prepared by accurately weighing of each analyte standard and
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dissolving in acetonitrile/water mixed solution (v/v, 1:1, containing 0.1 M hydrochloric acid) of 10
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mL. A multicompound working standard solution (1 mg/L) of each compound was prepared by 6
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appropriate diluting and stored at 4 °C. All the calibration and working solutions were prepared by
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sequentially diluting of the stock solutions in appropriate linear range with spiked internal standard
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on the day of analysis. The IS solution was prepared at 1 mg/L and diluted to 0.01 mg/L with
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acetonitrile during sample analysis.
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The derivatization reagent solution at the concentration of 50 mM was prepared by dissolving
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230.6 mg of CCR with 10 mL acetonitrile. Hydrochloric acid (HCl, 0.1 M); NaHCO3-Na2CO3
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buffer of pH 9.2 (0.1 M) was prepared and adjusted the pH to 9.2 using sodium hydroxide solution.
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Sample Preparation. The method was applied for the determination of AAs and BAs in red
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wine, beer, wine, cheese, sausage and fish which were collected from various local markets (Qufu
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city, Shandong province, China). The red wine, beer and wine samples were homogenized for 30
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min in an ultrasound bath and filtered through 0.22 µm nylon filter before in situ DUADLLME.
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The samples of cheese, sausage and fish were prepared according to previously described
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procedure 7 with some minor modifications. Two g of cheese, sausage or fish were prepared by
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weighing accurately and then homogenized respectively with the ultrasound bath for 30 min,
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respectively. The finely homogenate was transferred into a 50 mL centrifuge tube, and then 20 mL
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of 0.1 M HCl was added into. After centrifugation (10,000 rpm, 5 min), 20 µL of sample solution
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were used for the following in situ DUADLLME and then determined under the optimum
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UHPLC-MS/MS (MRM) conditions.
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In situ DUADLLME Procedure. A volume of 20 µL of working solution or food sample
135
solution and 20 µL of IS solution was placed in a 1.5 mL tube, and then 1 mL of NaHCO3-Na2CO3
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buffer (pH 9.2) was added. After that, 200 µL of CCR derivatization reagent solution of acetonitrile
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(as dispersant) and 90 µL of bromobenzene (extractant) was rapidly injected using syringe. The
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tube was capped and then shaken vigorously for 10 s to mix the phases. The resultant cloudy 7
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solution was then placed in an ultrasound bath for simultaneous derivatization and microextraction
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for 1 min (ultrasound frequency 40 KHz). After centrifuging, the fine droplets of extractant were
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sedimented at the bottom of the centrifuge tube. Then the droplets was withdrawn by using a digital
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graduated syringe and subsequently stored in an insert vial, which was diluted to 50 µL with
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acetonitrile for automated injection. The synthesized reaction of CCR and derivatization reaction
144
schematic of CCR and PEA were shown in Figure 2. Finally, 2 µL of sample was finally injected
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into UHPLC-MS/MS (MRM) for analysis.
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Optimization of in situ DUADLLME conditions. To obtain the best derivatization
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and microextraction efficiencies, the parameters related to DUADLLME parameters were
148
optimized. The effect of buffer solution pH on DUADLLME was studied in the pH range of
149
7.5-10.5. The effects of temperature and ultrasound time were evaluated in the range of 15-50 °C
150
and 0-3 min respectively. The volume of derivatization reagent and the type, and volume of
151
dispersant and extractant were also studied. Parameters which showed the highest responses were
152
applied during the following experiments.
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Instrumental Analysis. An Agilent 1290 series UHPLC system (Agilent, USA) coupled
154
with an Agilent 6460 Triple Quadrupole MS/MS system (Agilent, USA). The chromatographic
155
separation was carried out with 2.0 µL injections with a flow rate of 0.2 mL/min. An Agilent SB
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C18 column (2.1 mm × 50 mm, 1.8 µm) was used at 30 °C. Eluent A was 0.1% formic acid in 5%
157
acetonitrile/water and B was 0.1% formic acid in acetonitrile. The gradient elution program was as
158
follows: 0-6 min, 80% A+20% B; 6-8.5 min, 35% A+65% B; 8.5-10 min, 5% A+95% B, before the
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next run.
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In order to protect the MS/MS system from potential contaminations during the first 1 min after
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injection, the flow was diverted to waste. The mass spectrometer was employed in the positive ion 8
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electrospray mode with MRM. The optimal ESI source conditions were as follows: gas temperature
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300 °C; gas flow rate 10 L/min; nebulizer 40 psi; sheath gas temperature 300 °C; sheath gas flow
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10 L/min and capillary voltage 4.0 kV. The MRM transitions, CEs and FVs of the target
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compounds were summarized in Table 1.
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Method Validation. QC samples were prepared by giving low, medium, and high three
167
analyte concentrations. In order to evaluate linearity, seven calibration solutions were prepared by
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spiking with 10 µL (0.01 mg/L) of the IS solution and 10 µL of working solutions to generate
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calibration levels covering a range of 0.01-20 mg/L for each compound in red wine. Different
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calibration levels were established for different real sample. Limits of detection (LODs) were
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determined as signal-to-noise ratio > 3 and the limits of quantitation (LOQs) were calculated at
172
signal-to-noise ratio > 10, respectively. Three acetonitrile blanks were injected to confirm that there
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were no memory effects before the LODs determination.
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To evaluate accuracy and precision, intra- and inter-day repeatability were carried out at three
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different concentrations (low, medium and high) within one day and on three separate validation
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days, respectively. Accuracies were calculated by the deviation percentage between nominal and
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calculated concentrations. The relative standard deviation (RSD%, n = 6) were calculated and the
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precisions were expressed on this basis. The derivatization efficiency was determined by dividing
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the peak areas of underivatized AAs and BAs after derivatization with equal amount of AAs and
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BAs standards without derivatization, the ratio was then subtracted from 100%. Matrix effect (ME)
181
was defined by comparing the response of spiked AAs and BAs using in situ DUADLLME
182
procedure to those of equivalent amount in standard solution. The recovery was expressed as
183
(increased concentration/spiked concentration) × 100%. The stability of the analytes was defined
184
by analyzing the extract of 0.1 mg/L standard solution at 0, 1, 2, 6, 24, 48, 96 and 120 h after the in 9
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situ DUADLLME procedure. During this period, extracts were located at room temperature.
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Methods Comparison. The sensitivity (expressed by LODs) in this work was compared with
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the analytes reacted with other derivatization reagents or without derivatization coupled with
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LC-MS methods reported before and also compared with CCR derivatization or UADLLME alone
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(without derivatization). The recovery caused by sample pretreatment DUADLLME was also
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depicted by comparing with the methods above.
191 192
RESULTS AND DISCUSSION
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Optimization of the UHPLC-MS/MS Parameters. The chromatographic separation
194
conditions were optimized in order to obtain good peak shapes and short retention time for
195
CCR-AA or CCR-BA derivatives. Among several different columns tested (Agilent SB C18,
196
Agilent Eclipse Plus C18, Acquity BEH C18, Acquity BEH Shield RP18), best performances in
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terms of retention and separation were achieved when employing Agilent SB C18 column
198
(theoretical plate numbers approached 12000), a full end-capped C18 column with a mobile phase
199
composed by water and acetonitrile with 0.1% formic acid. Shallow gradients had better
200
separations results over isocratic conditions. Flow rate and column temperature were also
201
optimized, respectively. The flow rate and column temperature were set at 0.2 mL/min and 30 ºC,
202
respectively. Under the optimized conditions, representative MRM chromatograms of CCR-AA,
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CCR-BA derivatives of standard solution and 1,7-diaminoheptane (IS) derivatives (each 0.5 mg/L)
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were shown in Figure 3A. The peak areas under the two curves of each analyte were assigned to
205
the quantitative production ion (high) and the qualitative production ion (low) of their MRM
206
transitions, respectively.
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MS conditions were also studied. All of the derivatives showed intense [M]+ ions in ESI source, 10
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which can be monitored in the positive ion mode, and made it easy to add the target compounds in
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tandem mass measurements. The molecular mass [M]+ of AA or BA-derivates were defined as
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precursor ion. All precursor ions of CCR-AA, -BA and -IS derivatives regularly fragmented to
211
generate specific and stable product ions at 398.1 and 441.2 Da as shown in Figure 3B, respectively.
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With acidic aqueous acetonitrile, these two specific product ions contained a permanent positive
213
charge through ESI-MS/MS, which resulted in enhanced sensitivity by increasing ionization
214
efficiency. The collision energies (CEs) and fragmentor voltages (FVs) were shown in Table 1.
215
Optimization of in situ DUADLLME. Effect conditions for derivatization. In
216
order to obtain the optimal derivatization conditions for preparing the CCR derivatives of the AAs
217
and
218
derivatization/microextraction and the volume of derivatization reagent CCR.
BAs,
the
variables
studied
were
as
follows:
pH,
time,
temperature
of
the
219
In order to achieve the optimized conditions, different experiments were carried out within the
220
pH range of 7.5-10.5 as shown in Figure S1A. It was expected that at pH < 7.0 no derivatization
221
reaction occurred and the peak area increased with the pH increasing from 7.5 to 9.2 and then
222
decreased. At pH 9.5 and higher, the peak area decreased significantly. It can be attributed to the
223
hydrolysis of the derivatization agent and derivatives at highly alkaline pH. The optimal
224
derivatization and extraction efficiencies would be obtained at pH 9.2. The maximum peak areas of
225
the CCR-derivatives were achieved at the buffer volume of 1 mL. Thus, 1 mL of NaHCO3-Na2CO3
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buffer (pH 9.2, 0.1 M) was selected during in situ DUADLLME. The effects of temperature and
227
time on derivatization/microextraction were evaluated from 15 to 50 °C (Figure S1B) and 0-3 min
228
(Figure S1C), respectively, while the other experimental conditions kept constant. Maximal and
229
constant peak areas were achieved when AAs and BAs standards were derivatized at 25-30 °C for 1
230
min. Volume of CCR was optimized over the range of 50-300 µL. The results indicated that the 11
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optimal volume of CCR was 200 µL, as shown in Figure S1D. The maximum peak area of
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CCR-AA, -BA was obtained when the volume of acetonitrile was at 200 µL. More than or equal to
233
200 µL of CCR solution was significantly excess and ensured the complete derivatization of
234
analytes with derivatization efficiencies (≥ 98.5%, determination and calculation methods reported
235
in our previous papers).37,38 The excess CCR was cleansed by the simultaneous DLLME. The
236
solvent of derivatization reagent was designed to be used as the dispersant for in situ DUADLLME.
237
Therefore, the selection of solvent of CCR was also one of the important factors. Four generally
238
used solvents viz., acetone, methanol, acetonitrile and ethanol were selected for the study.
239
Acetonitrile as solvent showed the maximum derivatization efficiencies and selected for further
240
experiments. Additionally, the acetonitrile showed comparable or occasionally better dispersive
241
ability for DUADLLME efficiencies compared with the other three solvents for most of the
242
analytes. Therefore, the acetonitrile was conveniently worked as a dual role of solvent of CCR and
243
dispersant of DUADLLME.
244
Effects of extractant and its volume. It is important to select a suitable extractant to
245
achieve good recovery with high enrichment factors. In the previous study, chlorosolvents in the
246
UADLLME method were usually chosen as extractant and good extraction results were obtained.
247
However, chlorosolvents had potential toxicity. In this work, low toxic bromosolvents were chosen
248
potential extractant. Extraction performances were compared in chloroform, tetrachloromethane,
249
1-bromo-3-methylbutane, bromocyclohexane, bromobenzene and 1-bromooctane. The results
250
showed that these bromosolvents obtained comparable or higher extraction efficiencies than the
251
above mentioned chlorosolvents. Among the bromosolvents, bromobenzene exhibited the highest
252
extraction efficiency as shown in Figure S2A. The amount of extractant should be selected for in
253
situ DUADLLME. This study aimed at employing the minimum volume of extractant to obtain the 12
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highest extraction efficiency for the proposed technique. The peak areas of CCR derivatives
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increased when the volumes of bromobenzene increased during the range of 50-150 µL (Figure
256
S2B) and tended to decrease when the volume was above 90 µL. Therefore, 90 µL of
257
bromobenzene was eventually selected as the optimized extractant.
258
Effects of in situ DUADLLME time. In DUADLLME, ultrasound agitation facilitates
259
emulsification and the mass of analyte transfer. In order to obtain two distinguishable phases in the
260
extraction tubes by using centrifugation. The effect of in situ DUADLLME time on the extraction
261
efficiency has also been tested. The effect of ultrasound assistance (ultrasound frequency 40KHz)
262
was investigated by changing ultrasound-assisted time from 0 to 3 min (Figure S1C). All of the
263
extraction performances were found reach the optimum when the solution was ultrasound at
264
frequency 40 KHz for 1 min. As a result, the In DUADLLME could be completed very quickly, so
265
1 min was chosen as the optimal time.
266
Method validation. In order to evaluate the applicability of the in situ DUADLLME,
267
linearity range of internal standard curve method, LODs and LOQs, precision, accuracy,
268
derivatization efficiencies, matrix effect (ME), recovery and stability were also studied under the
269
optimized conditions. All CCR-AA, -BA derivatives gave excellent linear responses in their linear
270
ranges with correlation coefficients above 0.99. Derivatization brought high sensitivity of AAs and
271
BAs. The results in Table 2 showed the sensitivity of representative samples in this work was
272
satisfying with LODs (S/N > 3) for red wine in the range of 0.3-0.7 and LOQs (S/N > 10) in the
273
range of 2.0-4.0 µg/L, respectively, and while the LODs for cheese in the range of 0.9-6.0 and
274
LOQs (S/N > 10) in the range of 10-30 µg/kg, respectively. LODs and LOQs of other samples were
275
within the ranges of the above results of two representative samples.
276
The results for accuracy, precision, recovery, stability, derivatization efficiencies and matrix 13
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effect of two representative samples (red wine and cheese) were listed in Table 2, and those results
278
of other food samples (beer, wine, sausage and fish, not shown) were within the ranges of the
279
above two representative samples. Precisions ranged from 4.2 to 13.4%, and accuracy varied
280
between 85 and 108% from the actual QC concentration. High derivatization efficiencies were
281
achieved with more than 99%. The intra- and inter-day accuracy and precision were all within 15%
282
according to FDA. The mean recoveries of the analytes varied from 83% to 111% at different
283
concentration levels. The matrix effects of the analytes ranged from 83% to 112% at three
284
concentration levels. The evaluation of stability for CCR-AA, -BA derivatives were within 3.8 and
285
8.1% at room temperature for 120 h. The stability of the analyte was satisfactory for accurate and
286
sensitive method to determine AAs and BAs by routine UHPLC-MS/MS analysis. Under the
287
optimum conditions above, results of EFs in this study were in the range of 120 to 286 for all
288
analytes.
289
Comparison of the Proposed Method with Other Methods. Although LC equipped
290
with different detectors could directly determine AAs and BAs derived from different food samples,
291
but their signal intensities were usually very weak. Therefore, this method was compared with
292
other derivatization methods, CCR derivatization alone (without microextraction pretreatment) and
293
UADLLME alone (without derivatization), respectively (shown in Table 3). Under the optimized
294
conditions, LODs of UADLLME alone were above 2 orders of magnitude higher than those of the
295
proposed method. The LODs of this work were considerably decreased 1-3 orders of magnitude
296
than those of CNBF,1 DNS-Cl,7 NQS,25 derivatization methods. Moreover, the total pretreatment
297
time of this work was shorten by 2-56 times than above methods.1,5,7,20,21,25,29 The UHPLC-MS/MS
298
sensitivity for AAs and BAs was greatly enhanced due to the introduction of CCR into the AAs and
299
BAs molecules. 14
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As shown in Table 3, recoveries of this method varied from 83% to 114%, and those of the other
301
methods1,5,7,21,25 were in the range of 47-147%. The good recovery results resulted from the
302
clean-up step of UADLLME and specific product ions of the introduction of CCR into the AAs and
303
BAs molecules. Compared with other derivatization methods,1,7,21,25 the product ions of the this
304
method had more specific and larger mass-to-charge ratio values. The results above proved that in
305
situ DUADLLME method could be time-saving and simple, and offered good recovery results for
306
simultaneous determination and quantitation of AAs and BAs in food samples.
307
Application in Real Samples. The developed analytical method was successfully applied to
308
simultaneous determination of 8 AAs and 9 BAs in 6 samples obtained from the local market (red
309
wine, beer, wine, cheese, sausage and fish). The red wine has always been studied for its complex
310
matrix, MRM chromatograms of CCR-AA, CCR-BA derivatives in red wine were shown in Figure
311
4, and AAs and BAs contents were summarized in Table 4. Tyr, His, Phe, Try, Lys, PUT and Arg
312
were found in all samples. The results also indicated that the contents variations in different
313
samples were significant. In general, it was found that His and PUT were the most abundant AA
314
and BA in these red wines with concentrations ranging from 6.0 to 10.4 mg/L. While, in beer His
315
and Phe were present at high contents. Wines contained detectable amounts of His, Phe, Try, PUT,
316
Arg, CAD, Orn and TYM was observed (see Table 4). BAs were measured in sausage substantially
317
higher amounts than in the cheese. The prevalence of AAs and BAs in cheese and sausage was also
318
recently reported, and our data were very close to the concentrations reported in the literature.7 The
319
target compounds except for PEA, Cit were detected in the fish samples varied from 0.32 to 7.52
320
mg/kg.
321
In conclusion, a simple, green, rapid, efficient and sensitive in situ DUADLLME method
322
combined with UHPLC-MS/MS (MRM) has been established and validated for the simultaneous 15
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323
determining AAs and BAs in complex matrix. In comparison with the existing methods, the
324
developed method was highly sensitive and selective for the determination of AAs and BAs by
325
derivatization, and the total analysis time of analytes was greatly reduced. Low matrix effect
326
(85-116%) and satisfactory recoveries (79-126%) of the proposed method made it widely
327
applicable for the analysis of AAs and BAs in a variety of complex food samples. The results
328
described in this work suggest that the proposed method can be a potential useful method to
329
quantitatively analyze each of these analytes and serves as a promising alternative to existing
330
determination methodology for AAs and BAs in foods.
331
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332
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22. Qi, B. L.; L, P.; Wang, Q. Y.; Cai, W. J.; Yuan, B. F.; Feng, Y. Q. Derivatization for liquid
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Compounds in Tuna by Matrix Solid-Phase Dispersion followed by HPLC-Orbitrap Mass
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33. Ocana-Gonzalez, JA.; Fernandez-Torres, R.; Bello-Lopez, M.A.; Ramos-Payan, M. New
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35. Plotka-Wasylka, J. M.; Morrison, C.; Biziuk, M.; Namiesnik, J. Chemical Derivatization
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36. Zhao, X.-E.; Lv, T.; Zhu, S. Y.; Qu, F.; Chen, G.; He, Y. R.; Wei, N.; Li, G. L.; Xia, L. ; Sun, Z.
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W.; Zhang, S. J.; You, J. M.; Liu, S.; Liu, Z. G. ; Sun, J.; Liu, S. Y. Dual ultrasonic-assisted
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dispersive liquid-liquid microextraction coupled with microwave-assisted derivatization for 20
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simultaneous determination of 20(S)-protopanaxadiol and 20(S)-protopanaxatriol by ultra high
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performance liquid chromatography-tandem mass spectrometry. J. Chromatogr. A 2016, 1437,
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49-57.
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37. He, Y. R.; Zhao, X.-E.; Zhu, S. Y.; Wei, N.; Sun, J.; Zhou, Y. B.; Liu, S.; Liu, Z. Q.; Chen, G.;
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Suo, Y. R.; You J. M. In situ derivatization-ultrasound-assisted dispersive liquid-liquid
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microextraction for the determination of neurotransmitters in Parkinson’s rat brain microdialysates
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by ultra high performance liquid chromatography-tandem mass spectrometry. J. Chromatogr. A
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2016, 1458, 70-81.
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38. Wei, N.; Zhao, X.-E.; Zhu, S. Y.; He, Y. R.; Zheng, L. F.; Chen, G.; You, J. M.; Liu, S.; Liu, Z.
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Q. Determination of dopamine, serotonin, biosynthesis precursors and metabolites in rat brain
448
microdialysates
449
microextraction coupled with UHPLC-MS/MS. Talanta 2016, 161, 253-264.
450
Supporting Information.
451
Figure S1. Optimization of in situ DUADLLME conditions (n=5), (A) pH, (B) temperature, (C)
452
time, and (D) volume of CCR.
453
Figure S2. Optimization of parameters of in situ DUADLLME: (A) type of extractant, (B) volume
454
of extractant.
455
Acknowledgement
456
The authors acknowledge the financial support from the National Natural Science Foundation of
457
China (81303179, 31200400, 81403051, 21475074 and 21405094), the Natural Science Foundation
458
of Shandong Province (ZR2013BQ018), the Open Funds of the State Key Laboratory of
459
Electroanalytical Chemistry (No. SKLEAC201506), the Development Project of Qinghai Key
460
Laboratory of Qinghai-Tibet Plateau Biological Resources (No. 2014-Z-Y3), the Open Projects
by
ultrasonic-assisted
in
situ
derivatization–dispersive
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liquid–liquid
Journal of Agricultural and Food Chemistry
461
Program of the Key Laboratory of Tibetan Medicine Research, Chinese Academy of Sciences, and
462
the Foundation of Qufu Normal University (BSQD2012019 and 2012023).
463
Notes
464
The authors declare that they have no conflict of interest.
465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 22
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FIGURE CAPTIONS
485
Figure 1. Schematic of the biosynthesis pathways of amino acids (AAs) and biogenic amines
486
(BAs).
487
Figure 2. The synthesized reaction of CCR, and derivatization reaction of CCR with
488
β-phenylethylamine (PEA).
489
Figure 3. (A) Representative MRM chromatograms of the CCR-derivatives of standard mixture
490
and internal standard, here, the peak areas under the two curves of each analyte corresponding to
491
the quantitative (high) and the qualitative (low) production ion of MRM transition, and (B) product
492
ion spectrum and proposed fragmentation pathways of CCR-PEA derivative.
493
Figure 4. Typical MRM chromatograms of the CCR derivatives of amino acids and biogenic
494
amines in red wine.
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Tables Table 1. Parameters of CCR Derivatives of Amino Acids, Biogenic Amines and Internal Standard in Mass Spectrometric MRM Analysis. Compounds
Fragmentor (V)
Quantitation transition (m/z)
Collision energy (eV)
Confirmation transition (m/z)
Collision energy (eV)
Tyr
240
1031.52 > 398.10
58
1031.52 > 441.20
60
TYM
240
987.53 > 398.10
55
987.53 > 441.20
55
His
240
1005.32 > 398.10
58
1005.32 > 441.20
58
HIM
210
961.53 > 398.10
52
961.53 > 441.20
52
Phe
220
590.30 > 398.10
50
590.30 > 441.20
50
PEA
220
546.31 > 398.10
50
546.31 > 441.20
50
Try
240
631.33 > 398.10
52
631.33 > 441.20
52
TRM
240
587.34 > 398.10
52
587.34 > 441.20
52
Lys
240
996.55 > 398.10
58
996.55 > 441.20
58
CAD
240
952.56 > 398.10
60
952.56 > 441.20
60
Orn
220
986.57 > 398.10
55
986.57 > 441.20
55
PUT
220
938.55 > 398.10
58
938.55 > 441.20
58
Arg
220
600.32 > 398.10
52
600.32 > 441.20
52
Cit
240
600.32 > 398.10
55
600.32 > 441.20
55
AGM
240
980.57 > 398.10
58
980.57 > 441.20
58
SPD
240
1421.83 > 398.10
58
1421.83 > 441.20
58
SPM
240
1904.11 > 398.10
62
1904.11 > 441.20
62
IS
220
980.59 > 398.10
58
980.59 > 441.20
58
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Table 2. Analytical Performance of the In Situ DUADLLME Coupled with UHPLC-MS/MS Method, Containing Linearity, LODs, LOQs, Intra- and Inter-Day Accuracy (RE%), Precision (RSD%), Matrix Effect (ME% ) and Recovery (Rec%) of Amino Acids and Biogenic Amines in Representative Samples (Red Wine and Cheese) (n=6). Red wine
Linear range (mg/L)
LODs (µg/L)
LOQs (µg/L)
R
Tyr
0.01-20
0.7
4.0
0.996
TYM
0.01-20
0.5
3.0
0.997
His
0.01-20
0.6
3.0
0.995
HIM
0.01-20
0.4
4.0
0.996
Phe
0.01-20
0.7
5.0
0.995
PEA
0.01-20
0.3
2.0
0.997
Try
0.01-20
0.5
4.0
0.996
Analytes
Cheese
spiked level (mg/L)
Intra- and Inter-day precision (RSD%)
Intraand Interday RE (%)
ME (%)
Rec (%)
0.05 0.5 5 0.05 0.5 5 0.05 0.5 5 0.05 0.5 5 0.05 0.5 5 0.05 0.5 5 0.05 0.5 5
6.7 9.1 5.2 8.5 6.8 4.6 7.6 10.4 9.8 8.6 11.2 6.9 7.9 11.3 5.9 6.1 13.4 4.2 8.3 10.2 6.2
99 102 98 94 97 108 98 103 105 96 95 105 97 92 103 98 104 96 89 94 103
98 102 106 91 88 105 89 93 94 93 95 100 95 94 105 85 88 95 88 95 102
90 101 109 95 97 104 85 92 109 96 102 101 99 93 102 90 96 110 96 93 101
Linear range (mg/kg)
LODs (µg/kg)
LOQs (µg/kg)
R
0.1-250
6.0
20
0.995
0.05-100
1.5
10
0.994
0.05-100
3.0
20
0.994
0.05-100
0.9
10
0.996
0.1-250
6.0
30
0.997
0.05-100
0.9
10
0.998
0.05-100
2.5
15
0.995
25
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spiked level (mg/kg)
Intra- and Inter-day precision (RSD%)
Intraand Interday RE (%)
ME (%)
Rec (%)
0.5 5 50 0.5 5 50 0.5 5 50 0.5 5 50 0.5 5 50 0.5 5 50 0.5 5 50
8.1 10.2 5.3 7.2 14.4 6.3 5.1 10.7 4.3 6.1 15.4 3.9 5.2 13.3 4.6 7.6 13.7 5.9 5.9 11.7 4.3
85 98 95 91 97 109 97 94 102 92 98 102 90 94 103 99 100 102 91 87 103
91 94 106 88 107 103 98 105 107 92 96 101 92 102 105 95 101 103 87 109 103
83 97 108 99 94 105 101 86 107 97 103 104 85 89 114 89 94 108 88 93 103
Journal of Agricultural and Food Chemistry
TRM
0.01-20
0.4
3.0
0.995
Lys
0.01-20
0.6
3.0
0.994
CAD
0.01-20
0.7
4.0
0.996
Orn
0.01-20
0.6
4.0
0.995
PUT
0.01-20
0.4
3.5
0.993
Arg
0.01-20
0.6
3.0
0.996
Cit
0.01-20
0.7
4.0
0.995
AGM
0.01-20
0.5
4.0
0.993
SPD
0.01-20
0.5
3.0
0.994
SPM
0.01-20
0.5
3.0
0.994
0.05 0.5 5 0.05 0.5 5 0.05 0.5 5 0.05 0.5 5 0.05 0.5 5 0.05 0.5 5 0.05 0.5 5 0.05 0.5
7.3 9.6 6.3 8.6 9.3 5.8 4.9 10.7 3.8 5.2 8.9 4.6 7.3 8.9 6.2 8.8 7.6 10.8 6.9 10.3 9.2 5.6 9.3
97 87 101 91 97 107 97 101 102 96 98 101 88 103 93 95 96 102 97 104 105 94 99
94 96 102 98 96 112 91 99 102 95 96 103 96 97 102 95 102 103 90 93 104 100 98
98 99 106 83 102 105 83 102 99 96 93 102 99 93 102 91 97 102 83 96 108 97 104
0.05 0.5 5 0.05 0.5 5
4.1 9.8 4.7 6.5 13.1 5.3
93 103 105 90 99 107
84 91 102 88 101 107
89 96 104 91 88 103
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0.05-100
2.5
15
0.994
0.1-250
6.0
20
0.997
0.05-100
2.5
15
0.996
0.05-100
4.0
20
0.995
0.05-100
2.5
15
0.997
0.05-100
2.5
15
0.995
0.05-100
4.0
15
0.995
0.05-100
2.5
15
0.997
0.05-100
2.5
15
0.996
0.05-100
2.5
15
0.994
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0.5 5 50 0.5 5 50 0.5 5 50 0.5 5 50 0.5 5 50 0.5 5 50 0.5 5 50 0.5 5
5.2 12.1 6.6 7.3 13.2 4.9 5.6 11.3 7.1 8.5 11.7 5.7 8.6 9.3 5.8 7.6 10.4 9.8 10.6 7.4 9.1 8.1 13.4
96 97 106 95 102 102 97 99 103 96 99 104 99 94 102 93 97 106 89 98 105 98 102
94 91 110 91 96 107 88 97 110 90 84 106 88 103 93 96 98 100 95 100 101 96 97
102 109 104 97 103 103 93 97 101 90 93 105 97 98 105 89 102 106 86 93 103 87 96
0.5 5 50 0.5 5 50
8.7 14.9 8.9 11.3 9.6 6.3
100 97 104 97 94 101
95 90 102 85 88 105
89 93 100 91 94 108
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Table 3. Comparisons of Sample Pretreatment, Sensitivity and Recovery of This Work with Other Methods. Sample preparation Samples
Analytes
fish
SPD, SPM, CAD, PUT, HIM, TYM, PEA, TRM
meat tuna wine beer, cheese, sausage wine red wine
SPD, SPM, CAD, PUT, HIM, AGM, TYM, PEA, TRM PUT, CAD, HIM, TRM, TRM, AGM, PEA HIM, TYM,TRM, PEA Cit, Try, Phe, Orn, Lys, His, Yyr, TRM, PEA, PUT, CAD, HIM, TYM, SPD HIM, PUT, CAD, TRM, PEA, TYM Tyr, His, Phe, Try, Lys, Orn, Arg, Cit, TYM, HIM, PEA, TRM, CAD, PUT, AGM, SPD, SPM
Extraction method
Total Detection modes Derivatization pretreatment time reagents (min)
LODs
Recovery (%)
Refs
SPE
-
-
LC-MS/MS
20-250 (µg/kg)
71-93
[5]
SPE
-
-
HPLC-MS/MS
2-100 (µg/L)
47-127
[20]
SPE
-
-
UHPLC-MS
20-2580 (µg/L)
83-113
[29]
Centrifuge
CNBF
170
LC–QTOFMS
20-30 (µg/L)
97-102
[1]
Centrifuge
DNS-Cl
93
LC–QTOFMS
5-400 (µg/L)
80-120
[7]
-
NQS
5
HPLC-MS
88-206 (µg/L)
83-110
[25]
In situ DUADLLME
CCR
3
UHPLC-MS/MS
0.3-0.7 (µg/L)
85-110 This work
red wine
Tyr, His, Phe, Try, Lys, Orn, Arg, Cit, TYM, HIM, PEA, TRM, CAD, PUT, AGM, SPD, SPM
-
CCR
3
UHPLC-MS/MS
1.5-7(µg/L)
78-114
red wine
Tyr, His, Phe, Try, Lys, Orn, Arg, Cit, TYM, HIM, PEA, TRM, CAD, PUT, AGM, SPD, SPM
UADLLME
-
3
UHPLC-MS/MS
5-60 (µg/L)
60-106
In this work for comparis on In this work for comparis on
CNBF = 2-chloro-1,3-dinitro-5-(trifluoromethyl)-benzene; DNS-Cl = dansyl chloride; NQS = 1,2-naphthoquinone-4-sulfonate; SPE = solid phase extraction; CCR= 4’-carbonyl chloride rosamine
UADLLME = ultrasound-assisted dispersive liquid–liquid microextraction; DLLME-SFO = dispersive liquid-liquid microextraction based on solidification.
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Table 4. Concentrations of Amino Acids and Biogenic Amines in Food Samples. Compound
red wine (mg /L)
beer (mg /L)
wine (mg/L)
cheese (mg/kg)
sausage (mg/kg)
fish (mg/kg)
Tyr
6.56 ± 1.5
0.14 ± 0.05
8.15 ±1.5
120.03 ± 28.9
25.03 ± 3.5
5.23 ± 1.1
TYM
1.05 ± 0.4
0.52 ± 0.09
1.35 ± 0.2
nd
0.26 ± 2.1
0.32 ± 0.8
His
10.39 ± 2.3
24.54 ± 4.9
6.59 ± 1.1
56.57 ± 13.2
19.46 ± 3.6
0.44 ± 0.06
HIM
2.21 ± 0.6
nd
0.28 ± 0.08
nd
15.15 ± 2.0
0.4 ± 0.09
Phe
5.87 ± 1.06
25.25 ± 5.6
7.35 ± 1.9
192.67 ± 35.9
30.63 ± 3.1
0.84 ± 0.01
PEA
0.31 ± 0.08
nd
nd
nd
nd
nd
Try
4.25 ± 1.4
15.72 ± 3.2
2.39 ± 0.7
14.18 ± 1.2
5.04 ± 1.4
0.86 ± 0.09
TRM
0.84 ± 0.05
nd
nd
nd
nd
0.56 ± 0.06
Lys
5.01 ± 0.8
20.01 ± 2.3
15.42 ± 3.4
190.89 ± 36.0
30.16 ± 3.1
0.71 ± 0.05
CAD
0.45 ± 0.07
0.23 ± 0.02
0.22 ± 0.06
nd
1.68 ± 0.6
3.62 ± 0.9
Orn
3.05 ± 0.9
1.02 ± 0.1
3.61 ± 0.5
28.56 ± 2.3
nd
1.53 ± 0.4
PUT
6.01 ±1.2
1.14 ± 0.4
6.11 ± 1.5
2.58 ± 0.7
1.44 ± 0.5
7.52 ± 1.5
Arg
10.23 ± 2.4
7.35 ± 2.5
15.40 ± 3.9
62.93 ± 16.8
8.93 ± 2.3
2.69 ± 0.8
Cit
nd
4.06 ± 1.7
9.23 ± 2.2
9.05 ± 1.2
5.12 ± 1.5
nd
AGM
0.83 ± 0.1
1.58 ± 0.7
nd
28.56 ± 7.3
2.16 ± 0.9
0.82 ± 0.08
SPD
0.76 ± 0.06
0.40 ± 0.08
0.52 ± 0.03
nd
0.66 ± 0.7
1.56 ± 0.8
SPM
0.11 ± 0.03
0.26 ± 0.03
0.18 ± 0.05
nd
0.94 ± 0.03
2.67 ± 0.6
nd, not detected.
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Figure 1
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Figure 4
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