Simultaneous Determination of Food-Related Biogenic Amines and

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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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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:

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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

41

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

52

(UHPLC-MS/MS) using multiple reactions monitoring (MRM) detection has been acted as a

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powerful technique for its speediness, high sensitivity and selectivity, and applicability.

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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

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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

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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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(NQS),25

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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.

91 92

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.

108

1

109

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 ×

112

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

122

buffer of pH 9.2 (0.1 M) was prepared and adjusted the pH to 9.2 using sodium hydroxide solution.

123

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

132

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

137

(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

143

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

145

into UHPLC-MS/MS (MRM) for analysis.

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Optimization of in situ DUADLLME conditions. To obtain the best derivatization

147

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

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7.5-10.5. The effects of temperature and ultrasound time were evaluated in the range of 15-50 °C

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and 0-3 min respectively. The volume of derivatization reagent and the type, and volume of

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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

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separation was carried out with 2.0 µL injections with a flow rate of 0.2 mL/min. An Agilent SB

156

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

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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

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analyte concentrations. In order to evaluate linearity, seven calibration solutions were prepared by

168

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)

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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

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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

189

(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,

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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

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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

226

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

255

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

REFERENCES

332

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58-66.

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2. Mayr, C. M.; Schieberle, P. Development of Stable Isotope Dilution Assays for the Simultaneous

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Quantitation of Biogenic Amines and Polyamines in Foods by LC-MS/MS. J. Agric. Food Chem.

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8. De Mey, E.; Drabik-Markiewicz, G.; De Maere, H.; Peeters, M.-C.; Derdelinckx, G.; Paelinck, H.;

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9. Oenal, A. A review: Current analytical methods for the determination of biogenic amines in

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11. Önal, A., Tekkeli, S. E. K., Önal, C. A review of the liquid chromatographic methods for the

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12. Tang, T.; Qian, K.; Shi, T. Y.; Wang, F.; Li, J. Q.; Cao, Y. S.; Hu, Q. B. Monitoring the contents

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13. Daniel, D.; Dos Santos, V. B.; Vidal, D. T.; do Lago, C. L. Determination of biogenic amines in

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chromatography-fluorescence detection for sensitive determination of biogenic amines in rice wine

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17. Ramos, R. M.; Valente, I. M.; Rodrigues, J. A. Analysis of biogenic amines in wines by

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21. Jia, S.; Ryu, Y.; Kwon, S. W.; Lee, J. An in situ benzoylation-dispersive liquid-liquid

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microextraction method based on solidification of floating organic droplets for determination of

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biogenic amines by liquid chromatography-ultraviolet analysis. J. Chromatogr. A 2013, 1282, 1-10.

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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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23. Fiechter, G.; Sivec, G.; Mayer, H. K. Application of UHPLC for the simultaneous analysis of

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free amino acids and biogenic amines in ripened acid-curd cheeses. J. Chromatogr. B 2013, 927,

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24. Pereira, V.; Pontes, M.; Câmara, J. S.; Marques, J. C. Simultaneous analysis of free amino acids

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and biogenic amines in honey and wine samples using in loop orthophthalaldeyde derivatization

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procedure. J. Chromatogr. A 2008, 1189, 435-443.

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25. García-Villa, N.; Hernández-Cassou, S.; Saurina, J. Determination of biogenic amines in wines

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26. Donthuan, J.; Yunchalard, S.; Srijaranai, S. Vortex-assisted surfactant-enhanced-emulsification

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liquid-liquid microextraction of biogenic amines in fermented foods before their simultaneous

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analysis by high-performance liquid chromatography. J. Sep. Sci. 2014, 37, 3164-3173.

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27. Lavilla, I.; Romero, V.; Costas, I.; Bendicho, C. Greener derivatization in analytical chemistry.

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28. Zhao, X.-E.; Suo Y.-R. Simultaneous determination of monoamine and amino acid

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neurotransmitters in rat endbrain tissues by pre-column derivatization with high-performance liquid 19

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chromatographic fluorescence detection and mass spectrometric identification. Talanta 2008, 76,

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29. Self, R. L.; Wu, W. H; Marks, H. S. Simultaneous Quantification of Eight Biogenic Amine

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Compounds in Tuna by Matrix Solid-Phase Dispersion followed by HPLC-Orbitrap Mass

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Spectrometry. J. Agric. Food Chem. 2011, 59, 5906-5913.

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30. Saaid, M.; Saad, B.; Ali, A. S.; Saleh, M. I.; Basheer, C.; Lee, H. K. In situ derivatization

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hollow fibre liquid-phase microextraction for the determination of biogenic amines in food samples.

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31. Tang, S.; Zhang, H.; Lee, H. K. Advances in Sample Extraction. Anal. Chem. 2016, 88,

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32. Leong, M.-I; Fuh, M.-R; Huang, S.-D. Beyond dispersive liquid–liquid microextraction. J.

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Chromatogr. A 2014, 1335, 2-14.

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33. Ocana-Gonzalez, JA.; Fernandez-Torres, R.; Bello-Lopez, M.A.; Ramos-Payan, M. New

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developments in microextraction techniques in bioanalysis. A review, Anal. Chim. Acta 2016, 905,

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8-23.

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34. Delgado-Povedano, M.M; de Castro, M.D. Ultrasound-assisted extraction and in situ

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derivatization. J. Chromatogr. A 2013, 1296, 226-234.

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35. Plotka-Wasylka, J. M.; Morrison, C.; Biziuk, M.; Namiesnik, J. Chemical Derivatization

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Processes Applied to Amine Determination in Samples of Different Matrix Composition. Chem.

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Rev. 2015, 115, 4693−4718.

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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

437

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

439

performance liquid chromatography-tandem mass spectrometry. J. Chromatogr. A 2016, 1437,

440

49-57.

441

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

445

2016, 1458, 70-81.

446

38. Wei, N.; Zhao, X.-E.; Zhu, S. Y.; He, Y. R.; Zheng, L. F.; Chen, G.; You, J. M.; Liu, S.; Liu, Z.

447

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

21

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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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484

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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Page 24 of 33

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

Page 26 of 33

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

26

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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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Journal of Agricultural and Food Chemistry

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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Page 28 of 33

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 2

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(B)

Figure 3(A, B) 31

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Figure 4

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Table of Contents Graphic

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