Liquid Chromatography/ Mass Spectrometry

A P P L I C A T I O N N O T E

Authors:

Abir KhaledJanusz Pawliszyn

Department of Chemistry, University of Waterloo 200 University Avenue West Waterloo, Ontario, N2L 3G1, Canada

Jingcun WuFeng Qin

PerkinElmer Inc. Woodbridge, Ontario, Canada

IntroductionThe use of veterinary drugs in modern day intensive farming of food-producing animals is essential to prevent and treat animal diseases.1,2 However, improper dosage or failure to keep the

specified withdrawal period of approved drugs may lead to excessive levels of drug residues in the edible tissues of treated animals, posing a potential risk to human health. Moreover, the overuse of antimicrobials in food-producing animals has been closely linked to the emergence of antibiotic-resistant bacteria.3–9

Aiming to safeguard human health, many countries have established extensive regulatory measures to prevent veterinary drug exploitation in the food-animal industry.10,11 In Canada, Health Canada establishes maximum residue limits (MRL) for veterinary drugs through the Veterinary Drugs Directorate (VDD).12 Likewise, in the USA, the Food and Drug Administration (FDA) sets regulatory tolerances of registered veterinary drugs through the Center for Veterinary Medicine (CVM).13 Accordingly, monitoring of veterinary drug residues in food products of animal origin is necessary to ensure the safety of meat products, and that maximum residue limits are not breached. Owing to the large number of samples to be analyzed and the wide array of residual drugs, there is increasing demand for high-throughput multi-class, multi-residue methods (MMM) that are capable of simultaneously detecting a wide variety of analytes in a single analytical run.7,14

Automated High Throughput Multi-class Multi-residue Method for Analysis of Veterinary Drugs in Chicken by SPME-UHPLC/MS/MS

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Analysis of veterinary drug residues in animal tissue samples can be a challenging task owing to the high protein, fat and phospholipid content of biological samples.15 Improper sample preparation and clean-up can lead to the presence of matrix interferences, which might adversely affect the signal and compromise the analytical outcome.14,16,17 Conventional sample preparation procedures to reduce matrix effects often include solvent extraction (SE) followed by either solid phase extraction (SPE) or dispersive SPE (d-SPE) for additional extract clean-up.14,15,18,19 These sample preparation techniques often involve time-consuming procedures owing to the lack of automation and high-throughput capabilities. In addition, they often involve the use of large amounts of toxic organic solvents.

Solid phase microextraction (SPME) is a solvent-less, effective and versatile sample preparation technique, which has been widely used in environmental and other applications.20-22 Recently, with the development of new extraction phases and devices, SPME has found increased applicability to food analysis.22

In this work, we present a robust, high-throughput quantification method for the analysis of 73 veterinary drugs (belonging to more than 12 classes of drug compounds) in chicken tissue by using a fully automated solid phase micro-extraction (SPME) sample preparation technique and a QSight® UHPLC/MS/MS. The method offers an efficient and environmentally friendly alternative for the analysis of veterinary drug residues in animal tissue. In addition, it offers improved precision and accuracy as compared to traditional sampling procedures.

Experimental

Selection of Target Analytes and Target Levels in Chicken Tissue SamplesThe target analytes were selected from the list of priority veterinary drugs specified in the official United States Department of Agriculture method for the confirmation and screening of drug residues in animal tissues (CLG-MRM1.08).23 We aimed to include as many analytes from the list as possible to represent at least 12 drug classes, and to cover a wide range of polarities. The target levels were based on the Canadian MRLs and U.S. regulatory tolerances.24,25 In general, Canadian MRLs are either equal to or less than U.S. tolerances; however, in the case of ketoprofen and morantel, where Canadian MRLs were higher than U.S. tolerances, the U.S. regulatory tolerances were selected.

Materials and Supplies LC-MS grade acetonitrile (MeCN), methanol (MeOH), water, and formic acid (FA) were purchased from Fisher Scientific (Mississauga, ON, Canada). Polyacrylonitrile (PAN) and 1 mL and 2 mL Nunc U96 Deep Well plates made of polypropylene were purchased from VWR International (Mississauga, ON, Canada). Polypropylene inserts (600 mL) for the 1 mL plates were purchased from Analytical Sales and Services (NJ, USA). Desethylene ciprofloxacin HCl, hydroxy dimetridazole, and pirlimycin HCl were obtained from Toronto Research Chemicals (Toronto, ON, Canada). Haloxon was purchased from Cedarlane (Burlington, ON, Canada). All other veterinary drugs, internal standard (IS) flunixin-d3, and other reagents were purchased

from Sigma-Aldrich (Oakville, ON, Canada). SPME pins, shown in Figure 1, were manufactured using high-tolerance 304 stainless steel rods (1/16" diameter) purchased from McMaster-Carr (Aurora, OH, USA). The pins were cut to a length of 50 mm at the University of Waterloo's Science Technical Services (UW-STC), and coated with a slurry of HLB particles suspended in PAN as a binder at a thickness of 60 μm and a length of 2 cm, as previously described.26

Stock solutions of each veterinary drug and the deuterated internal standard were prepared separately by accurately weighing about 5 mg of each individual standard, and dissolving it in 5 mL of either acetonitrile (ACN), methanol (MeOH), water, or 10% dimethyl sulfoxide, depending on the solubility of each compound. An internal standard (IS) solution containing flunixin-d3, at 10 μg/mL, was prepared by appropriate dilution of IS stock solution in ACN. A composite solution containing β-Lactams/cephalosporins was prepared in water at a concentration of 200X (where X is the MRL). All other analytes were mixed in a composite solution and diluted to 100X with ACN. All stock and composite solutions were stored at -30 °C. Spiking solutions were prepared and used in the validation experiments within a week of preparation. Calibration standards were prepared by diluting the spiking solutions each day during validation and analysis. All standard solutions were stored in amber glass vials and closed with fitted PTFE, except for Lactams/cephalosporins solutions which were stored in plastic vials.

Organic chicken muscle tissue samples were purchased from three different local grocery stores in Waterloo, ON, Canada to serve as a pooled blank matrix. Five distinct samples of non-organic chicken were purchased from different local grocery stores for analysis of market samples.

Instruments and Conditions Chromatographic separation of veterinary drugs was conducted utilizing a PerkinElmer UHPLC system, with analyte determination achieved using a PerkinElmer QSight 220 triple quadrupole mass detector with dual ionization source. As the mass detector is capable of fast polarity switching, both positive and negative ionization modes were used. All instrument control, data acquisition, and data processing were performed using Simplicity 3Q™ software.

The optimized LC method and MS source parameters are shown in Table 1. The multiple reaction monitoring mode (MRM) transitions of the veterinary drugs under study are shown in Table 2. Two MRM transitions were monitored for each analyte for improved selectivity,27 whereas only one transition was needed for the IS. MS/MS analyte transitions and conditions were optimized via the software by direct infusion from methanolic and acetonitrile standards. Source conditions were optimized by flow injection (FIA) method. Based on the optimized conditions, the acquisition MS method is generated automatically by selecting the veterinary drugs of interest from the built-in compound library in the time-managed-MRM module of the Simplicity software, including both positive and negative analytes.

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Sample Preparation ProcedureChicken samples were homogenized with dry ice using a Vitamix blender to obtain a uniform powder. Organic chicken samples were then combined in equal weights and mixed to produce a pooled blank matrix. The homogenized chicken samples were first kept at -30 °C overnight to allow sublimation of residual dry ice, and then stored at -80 °C until analysis. Spiked chicken samples were prepared by adding 100 µL of the working solution, containing all analytes under study at their respective designated

concentrations, and 30 µL of the internal standard working solution to 2.0 g of homogenized pooled chicken blank matrix. Samples were vortexed manually for one minute, then placed on a benchtop agitator for one hour. Samples were then stored at 4 °C overnight, so as to allow for binding equilibria between matrix and analytes to be established. Following overnight refrigeration, the chicken samples were placed on the benchtop agitator for one hour prior to extraction to allow samples to reach room temperature. Next, 6 mL of water was added to each individual spiked chicken sample. Samples were then vortexed for one minute to attain a homogeneous consistency suitable for volumetric dispensing of 1500 μL of the diluted chicken samples into 96 well-plates.

Automated SPME ProcedureThe Concept 96 robotic sample preparation station (Professional Analytical System (PAS) Technology, Magdala, Germany) used in this work for SPME sample preparation, as shown in Figure 1, is a fully automated, software-operated, off-line bench-top station that executes all steps of the SPME protocol.28 The robotic arm of the Concept 96 is fitted with an SPME brush made of 96 SPME pins which are compatible with standard commercial 96-well-plates, thus allowing high throughput extraction of 96 samples simultaneously. The automated SPME workflow used in this method consisted of the following steps: (1) conditioning of the SPME coating for 30 minutes with MeOH:H2O (50:50, v/v); (2) static extraction for 60 minutes from 1.5 mL of diluted chicken tissue samples spiked with the target compounds; (3) rinsing of coating in water for 10 seconds so as to remove any loosely attached matrix constituents; and (4) solvent desorption in 400 μL of MeOH:MeCN:H2O (37.5:37.5:25, v/v/v) for 20 minutes. The final extracts from Step 4 were then transferred to the LC/MS/MS autosampler for injection and further analysis.

Table 1. LC Method and MS Source Conditions.

LC Conditions

LC Column Acquity UPLC HSS T3, 100 X 2.1 mm, 1.8 µm

Mobile Phase A 0.1% Formic Acid in Water

Mobile Phase B0.1% Formic Acid and 10 % Methanol in Acetonitrile

Mobile Phase Gradient

Start at 3% Mobile Phase B and Hold it for 1 Min, Then Increase B to 100% in 11 Min, and Keep at 100% B For 2 Mins. Finally Equilibrate The Column at Initial Condition for 3 Min.

Column Oven Temperature 40 °C

Auto Sampler Temperature 4 °C

Injection Volume 3.0 µl

MS Source ConditionsESI Voltage (Positive) 5000 V

ESI Voltage (Negative) -4000V

Drying Gas 120

Nebulizer Gas 200

Source Temperature 400 °C

HSID Temperature 320 °C

Detection Mode Time-managed MRM™

Figure 1. Concept 96-SPME device equipped with 96 SPME pins. Optimized conditions (time, agitation, solvent, and volume) for conditioning, extraction, rinsing, and desorption steps are shown, respectively, under each agitator-station.

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Table 2. MRM Transitions.

Compound Name Polarity Precursor Ion Product Ions CE EV CCL2

2-Amino-flubendazole Positive 256 123, 133 -35, -50 48 -60, -88

5-Hydroxy-thiabendazole Positive 217 191, 147 -33, -43 46 -36, -36

6-Phenyl-2-thiouracil Positive 205 188, 146 -23, -25 30 -36, -42

Acetopromazine Positive 327 86, 222 -25, -50 30 -65, -115

Albendazole (ALBZ) Positive 266 234, 191 -26, -44 33 -45, -75

ALBZ 2-aminosulfone Positive 240 133, 198 -38, -27 25 -63, -53

ALBZ sulfone Positive 297 159, 266 -50, -27 35 -70, -39

ALBZ sulfoxide Positive 282 240, 208 -19, -31 22 -89, -89

Betamethasone Positive 393 373, 355 -12, -18 15 -48, -58

Carazolol Positive 299 116, 222 -25, -25 31 -72, -37

Chlorpromazine Positive 319 86, 246 -26, -31 25 -60, -135

Clenbuterol Positive 276 203, 132 -20, -45 11 -144, -61

Clindamycin Positive 425 126, 377 -38, -30 12 -80, -40

Cloxacillin Positive 437 278, 160 -19, -25 17 -116, -176

Desethylene ciprofloxacin Positive 306 288, 268 -25, -35 10 -90, -90

Diclofenac Positive 296 215, 250 -25, -15 28 -122, -134

Dicloxacillin Positive 470 160, 311 -28, -20 17 -72, -126

Difloxacin Positive 400 356, 299 -26, -38 36 -60, -92

Doxycycline Positive 445 428, 267 -24, -47 16 -68, -112

Emamectin Positive 886 158, 302 -48, -40 30 -140, -144

Enrofloxacin Positive 360 316, 245 -27, -35 38 -52, -47

Fenbendazole Positive 300 268, 159 -28, -47 34 -64, -86

Fenbendazole sulfone Positive 332 300, 159 -29, -52 35 -54, -94

Florfenicol amine Positive 248 230, 130 -17, -29 16 -50, -50

Flubendazole Positive 314 282, 123 -30, -49 15 -44, -94

Flunixin Positive 297 279, 236 -29, -55 30 -50, -150

Flunixin-d3 Positive 300 282 -29 35 -35

Haloperidol Positive 376 165, 123 -32, -50 25 -68, -86

Haloxon Positive 415 211, 353 -46, -29 42 -98, -64

Hydroxy-dimetridazole Positive 158 140, 112 -17, -25 10 -56, -88

Hydroxy-ipronidazole Positive 186 168, 121 -16, -36 26 -24, -20

Ipronidazole Positive 170 109, 123 -33, -33 25 -55, -55

Ketoprofen Positive 255 177, 194 -26, -33 25 -104, -104

Levamisole Positive 205 178, 91 -27, -49 31 -30, -42

Lincomycin Positive 407 126, 359 -36, -24 18 -56, -52

Mebendazole Positive 296 264, 105 -29, -52 30 -110, -106

Melengestrol acetate Positive 397 337, 279 -18, -26 25 -54, -62

Morantel Positive 221 123, 150 -46, -38 28 -74, -68

Nafcillin Positive 415 199, 171 -26, -49 25 -54, -78

Niclosamide Negative 325 171, 289 31, 24 -25 60, 60

Nitroxynil Negative 288 127, 162 32, 25 -24 70, 60

Orbifloxacin Positive 396 295, 352 -32, -25 10 -75, -40

Oxacillin Positive 402 160, 243 -27, -20 19 -78, -108

Oxfendazole Positive 315 191, 284 -29, -25 36 -90, -33

Oxyclozanide Negative 400 364, 202 24, 35 -10 90, 70

Oxyphenylbutazone Positive 325 204, 120 -22, -29 12 -48, -44

Oxytetracycline Positive 461 426, 201 -24, -50 10 -100, 128

Phenylbutazone Positive 309 120, 188 -25, -20 10 -42, -40

Pirlimycin Positive 411 112, 363 -35, -23 28 -92, -36

Prednisone Positive 359 147, 171 -40, -45 12 -62, -68

Promethazine Positive 285 86, 198 -17, -33 25 -94, -94

Propionylpromazine Positive 341 86, 236 -25, -50 25 -52, -102

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Table 2. continued.

Compound Name Polarity Precursor Ion Product Ions CE EV CCL2

Sarafloxacin Positive 386 342, 299 -26, -38 36 -76, -98

Sulfachloropyridazine Positive 285 156, 92 -21, -45 25 -95, -62

Sulfadimethoxine Positive 311 156, 92 -27, -48 28 -76, -64

Sulfadoxine Positive 311 92, 108 -49, -37 21 -60, -60

Sulfaethoxypyridazine Positive 295 156, 92 -25, -47 25 -50, -66

Sulfamerazine Positive 265 108, 172 -38, -22 28 -53, -37

Sulfamethazine Positive 279 186, 124 -23, -36 10 -42, -44

Sulfamethizole Positive 271 156, 92 -19,-41 30 -102, -69

Sulfamethoxazole Positive 254 92, 108 -38, -39 30 -60, -70

Sulfamethoxypyridazine Positive 281 92, 108 -47, -35 10 -68, -72

Sulfaquinoxaline Positive 301 156, 108 -22, -38 30 -48, -48

Sulfathiazole Positive 256 156, 108 -19, -36 10 -34, -50

Tetracycline Positive 445 154, 410 -35, -23 19 -96, -44

Tilmicosin Positive 435 174, 696 -31, -23 35 -94, -94

Tolfenamic acid Positive 262 244, 209 -22, -37 12 -44, -70

Triclabendazole Positive 359 344, 274 -34, -48 25 -92, -96

Triclabendazole Sulfoxide Positive 375 360, 313 -30, -35 25 -72, -156

Triflupromazine Positive 353 86, 248 -27, -55 10 -52, -122

Virginiamycin Positive 526 355, 337 -23, -29 21 -78, -76

Xylazine Positive 221 164, 90 -35, -29 25 -46, -44

Results and Discussion

UHPLC/MS/MS Method OptimizationIn this study, different columns and mobile phase conditions were evaluated to achieve better separation and sensitivity for the target compounds. It was found that three columns produced similar results with slightly different retention time profiles, and can thus be used for the separation of the compounds. The columns are: Waters Acquity C18 UPLC HSS T3 (1.8 µm, 2.1 x 100 mm), PerkinElmer Brownlee SPP Phenyl-Hexyl (2.7 µm, 2.1 x 100 mm), and Restek Raptor Biphenyl (2.7 µm, 2.1 x 100 mm). It was also found that utilizing 10% methanol in acetonitrile as the organic mobile phase provided the best overall performance in terms of analyte peak shape, retention and mass signal intensity. In particular, signal intensity was improved for the late-eluting compounds when 10% methanol was present in the organic mobile phase.

Traditional MRM method development is not suitable for the analysis of a large number of analytes, such as 73 drug residues, in a single run. It is both time-consuming and labor intensive to input all the mass transitions into a method manually. More importantly, the advanced time-managed-MRM acquisition method can intelligently utilize the retention time of a chromatographic peak, and automatically optimize the residence time of the MRM to achieve the best quantitative data. Therefore, a time-managed-MRM is applied for method development in this study to improve efficiency, data quality and method performance. The fast polarity switching capability of the mass spectrometer also provided high detectability for both positive and negative ions in a single analytical run.

Matrix EffectsMatrix effects (MEs) are a major concern in bioanalytical method development and validation using LC/MS/MS. As a result of the complexity of animal tissue composition, interferences from

co-eluting matrix components can alter the ionization efficiency of target analytes, leading to either suppression or enhancement of signals.29,30 These matrix effects can dramatically influence the qualitative and quantitative performance of the method. To overcome MEs, several approaches can be used, such as sample dilution, intensive sample clean-up, using alternative ionization sources, as well as the use of matrix matched calibration curves and isotopically labeled internal standards. While, the ideal internal standard for each analyte is a stable isotope labeled form of the target analyte, using stable isotopically labeled internal standards (IS) for each analyte is not practical in multiresidue methods owing to aspects of availability, cost, and convenience. Therefore, one of the best approaches to reduce MEs is to employ a sample preparation technique that allows isolation and enrichment of a wide range of analytes, while at the same time, delivering a high degree of sample clean-up. In this regard, SPME has consistently demonstrated its ability to isolate and enrich a wide variety of analytes with minimal coextraction of matrix macromolecules.31–33

Figure 2. Matrix effects (%) for target analytes in chicken tissue plotted vs. retention time.

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In this study, MEs were evaluated by comparing the slopes of calibration curves obtained from reagent-only (RO) samples, with slopes obtained from matrix matched standards. MEs (%) for each analyte were calculated by the equation:

ME% = (slope of matrix-matched calibration curve − slope of RO calibration curve) × 100%/slope of RO calibration curve.

When the percentage difference is positive, there is a signal enhancement effect, whereas a negative value indicates signal suppression effect. As shown in Figure 2 and Table 3, matrix effect values for the majority of compounds were less than 20%. Only florfenicol amine and closantel displayed significant signal suppression (23% and 22% respectively), while desethylene ciprofloxacin and betamethasone displayed significant ion enhancement (23% and 30% respectively). The minimal matrix effects achieved in this study confirm that SPME provides an excellent sample clean-up. These results can be mainly attributed to the biocompatible PAN layer, which prevents interfering matrix components, such as proteins and lipids, from adsorbing to the SPME coating while still allowing target analytes to adsorb on the HLB coating.

Selectivity, Linearity, and Limit of QuantificationThe selectivity of the proposed method was evaluated by analyzing 10 blank chicken samples. No background peaks above a signal-to-

noise ratio of three were present at the same elution time as the target analytes, showing that the method is free of interferences. Analyte confirmations were evaluated by comparing the retention time and MRM chromatograms of each compound in the chicken samples with those of reference standards. At least two MRM ion pairs were used in the method to meet the regulatory requirements. The example MRM chromatograms of some veterinary drugs in a pooled chicken sample are illustrated in Figure 3.

Linearity was assessed for each analyte using matrix-matched calibration curves at seven concentration levels in the range of 0.1–3X, with three replicates at each level. Despite the use of only one internal standard, determination coefficient (R2) were higher than 0.99 for 95% of the analytes. Figure 4 shows typical examples of calibration curves obtained. The estimated limit of quantification (LOQ) for the method was established as the lowest point of the matrix-matched calibration curve that produced a response that is both accurate when compared to the expected value (calculated via linear regression), within a 70−120% range of the true concentrations, as well as precise (≤25% RSD). All analytes under study achieved LOQs that are below the ½ X, which is low enough to meet both U.S. regulatory tolerances and Canadian MRLs. These results demonstrated that the developed method can be applied for fast screening and quantification of multi-class veterinary drug residues in chicken samples at the regulatory levels.

Figure 3. Example MRM chromatograms of veterinary drugs in the pooled chicken sample spiked at 0.3X.

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Figure 4. Calibration curves for representative compounds, 5-hydroxy-thiabendazole, orbifloxacin, sulfaquinoxaline and tetracycline obtained from matrix-matched samples (analyte concentrations range from 0.1X to 3X).

Accuracy and PrecisionThe accuracy and precision of the method, with respect to intraday repeatability, were evaluated by analyzing pooled matrix blanks that were spiked at three validation levels- low, mid, and high (0.3X, 0.9X and 2.5X)- using six replicates per concentration. Accuracy was calculated based on estimated concentration values obtained from the linear regression equation of the matrix-matched calibration curve. As shown in Table 3, all analytes fell within the 70–120% range of the true concentrations of compounds, with RSD values ≤ 20% at the 0.3X, 0.9X and 2.5X validation levels, indicating that these

compounds can be quantitatively determined by the proposed method except for 6-Phenyl-2-thiouracil and haloxon. Despite the use of only one internal standard, these excellent accuracy and precision results demonstrate the effective sample clean-up offered by the method, as evidenced by the minimal matrix effects. The overlapped total ion chromatograms (TIC) shown in Figure 5 were generated from the six replicate chicken samples prepared by SPME at a low 0.3X spiking level, demonstrating good detectability and precision of the method.

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Table 3. Results of retention time, linearity, accuracy, intraday repeatability (%RSD), and % matrix effects (%ME) for target analytes in chicken tissue.

Compound Class MRL (ng g-1)

tR (min) R2

Accuracy (%RSD)% ME

0.3X 0.9X 2.5X

2-Aminoflubendazole Anthelmintics 10 6.24 0.9964 94 (8) 100 (4) 99 (4) -0.2

5-Hydroxythiabendazole Anthelmintics 100 4.68 0.9996 100 (5) 106 (9) 96 (2) -7.6

6-Phenyl-2-thiouracil Thyreostats 400 6.07 0.9988 97 (8) 101 (7) 145 (8) 3.1

Acetopromazine Tranquilizers 10 7.36 0.9946 101 (6) 104 (10) 108 (5) -9.5

Albendazole (ALBZ) Anthelmintics 50 7.44 0.9954 97 (3) 109 (4) 117 (2) -9.2

ALBZ 2-Aminosulfone Anthelmintics 100 4.91 0.9995 98 (11) 99 (5) 95 (2) -3.3

ALBZ Sulfone Anthelmintics 50 6.46 0.9966 97 (2) 103 (2) 98 (3) -2.4

ALBZ Sulfoxide Anthelmintics 50 5.69 0.9993 97 (3) 99 (3) 94 (4) -3.4

Betamethasone Anti-inflammatories 100 7.87 0.9968 98 (6) 100 (8) 98 (11) 30.0

Bithionol Anthelmintics 10 11.33 0.9978 98 (8) 107 (5) 104 (2) 5.2

Carazolol Tranquilizers 10 6.42 0.9910 101 (6) 104 (6) 106 (8) -6.9

Chlorpromazine Tranquilizers 10 8.10 0.9993 102 (10) 108 (10) 111 (9) -4.4

Clenbuterol β-Agonists 10 5.89 0.9928 100 (11) 102 (11) 101 (3) -9.7

Clindamycin Macrolides/Lincosamides 100 6.33 0.9942 101 (5) 102 (3) 100 (3) -4.7

Closantel Anthelmintics 50 12.73 0.9850 101 (10) 98 (9) 94 (4) -21.6

Cloxacillin β-Lactams/Cephalosporins 100 8.71 0.9995 104 (9) 100 (6) 95 (9) 4.1

Desethylene Ciprofloxacin Fluoroquinolones 100 5.12 0.9958 98 (10) 103 (10) 107 (7) 22.5

Diclofenac Anti-inflammatories 200 9.83 0.9986 97 (5) 100 (3) 98 (5) -5.0

Dicloxacillin β-Lactams/Cephalosporins 100 9.03 0.9969 99 (10) 103 (7) 98 (4) -1.0

Difloxacin Fluoroquinolones 50 5.91 0.9987 97 (8) 100 (2) 101 (3) 0.8

Doxycycline Tetracyclines 100 6.41 0.9973 97 (11) 96 (9) 98 (9) 9.1

Emamectin Anthelmintics 10 10.27 0.9977 113 (18) 111 (5) 111 (6) 2.1

Enrofloxacin Fluoroquinolones 20 5.56 0.9970 91 (12) 98 (9) 103 (8) 5.0

Fenbendazole Anthelmintics 100 8.32 0.9956 97 (4) 105 (2) 101 (1) -16.6

Fenbendazole Sulfone Anthelmintics 400 7.26 0.9912 97 (3) 104 (2) 98 (3) -17.4

Florfenicol Amine Phenicols 100 0.90 0.9982 102 (12) 106 (6) 97 (9) -23.2

Flubendazole Anthelmintics 10 7.69 0.9985 98 (5) 103 (4) 98 (1) -0.3

Flunixin Anti-inflammatories 20 9.05 0.9982 98 (1) 102 (1) 101 (1) 2.8

Haloperidol Tranquilizers 10 7.32 0.9950 100 (10) 105 (12) 108 (4) -5.8

Haloxon Anthelmintics 100 9.42 0.9977 112 (2) 66 (25) 80 (15) 3.8

Hydroxy-dimetridazole Coccidiostats 50 4.11 0.9964 92 (9) 97 (14) 97 (9) 0.2

Hydroxy-ipronidazole Coccidiostats 10 5.82 0.9982 100 (12) 104 (5) 102 (5) -2.7

Ipronidazole Coccidiostats 10 6.75 0.9988 96 (7) 102 (4) 102 (7) -1.1

Ketoprofen Anti-inflammatories 10 8.72 0.9976 98 (11) 102 (8) 96 (8) -1.7

Levamisole Anthelmintics 100 4.90 0.9973 97 (3) 99 (4) 93 (5) -1.2

Lincomycin Macrolides/Lincosamides 100 4.88 0.9953 108 (3) 101 (3) 97 (6) -5.9

Mebendazole Anthelmintics 10 7.41 0.9970 98 (14) 97 (13) 93 (8) -7.5

Melengestrol acetate Miscellaneous 25 10.67 0.9995 107 (7) 103 (3) 99 (1) -1.0

Morantel Anthelmintics 150 6.03 0.9995 98 (5) 101 (7) 105 (6) -3.4

Nafcillin β-Lactams/Cephalosporins 100 8.72 0.9995 99 (6) 100 (5) 99 (6) -0.4

Niclosamide Anthelmintics 10 10.66 0.9948 93 (9) 105 (6) 106 (4) -0.6

Nitroxynil Anthelmintics 50 8.19 0.9390 100 (5) 101 (5) 100 (4) -14.9

Orbifloxacin Fluoroquinolones 50 5.67 0.9995 94 (4) 101 (6) 103 (5) -6.3

Oxacillin β-Lactams/Cephalosporins 100 8.20 0.9997 99 (3) 102 (4) 100 (4) 0.6

Oxfendazole Anthelmintics 800 6.45 0.9720 99 (2) 106 (3) 98 (3) -14.0

Oxyclozanide Anthelmintics 10 10.44 0.9959 104 (7) 103 (5) 106 (5) -0.9

Oxyphenylbutazone Anti-inflammatories 100 8.75 0.9917 103 (8) 104 (5) 104 (7) -8.7

Oxytetracycline Tetracyclines 200 5.33 0.9956 100 (5) 103 (4) 104 (7) 18.4

Phenylbutazone Anti-inflammatories 100 10.17 0.9995 100 (5) 105 (3) 106 (3) -3.0

Pirlimycin Macrolides/Lincosamides 300 6.13 0.9923 103 (5) 99 (5) 98 (6) 10.1

Prednisone Anti-inflammatories 100 7.24 0.9959 97 (4) 102 (4) 97 (4) -3.0

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Table 3. continued.

Compound Class MRL (ng g-1)

tR (min) R2

Accuracy (%RSD)% ME

0.3X 0.9X 2.5X

Promethazine Tranquilizers 10 7.41 0.9957 98 (9) 102 (11) 110 (5) -4.5

Propionylpromazine Tranquilizers 10 7.90 0.9989 99 (8) 107 (5) 108 (8) 1.0

Sarafloxacin Fluoroquinolones 50 5.85 0.9953 104 (4) 98 (9) 101 (8) 4.0

Sulfachloropyridazine Sulfonamides 100 6.21 0.9937 101 (4) 103 (2) 101 (4) -6.4

Sulfadimethoxine Sulfonamides 100 7.05 0.9925 96 (2) 101 (2) 98 (4) -8.7

Sulfadoxine Sulfonamides 100 6.42 0.9780 101 (4) 105 (2) 98 (3) -9.1

Sulfaethoxypyridazine Sulfonamides 100 6.50 0.9900 96 (2) 102 (3) 99 (3) -1.8

Sulfamerazine Sulfonamides 100 5.30 0.9957 99 (7) 103 (6) 102 (4) -8.3

Sulfamethazine Sulfonamides 100 5.70 0.9924 98 (2) 103 (3) 99 (5) -8.5

Sulfamethizole Sulfonamides 100 5.65 0.9954 97 (3) 99 (4) 100 (7) 1.9

Sulfamethoxazole Sulfonamides 100 6.42 0.9911 100 (2) 104 (2) 99 (4) -4.7

Sulfamethoxypyridazine Sulfonamides 100 5.73 0.9916 97 (5) 103 (3) 100 (5) -11.2

Sulfaquinoxaline Sulfonamides 100 7.06 0.9998 97 (5) 102 (3) 98 (5) -11.5

Sulfathiazole Sulfonamides 100 4.96 0.9919 102 (4) 103 (5) 97 (4) -3.1

Tetracycline Tetracyclines 200 5.54 0.9952 96 (9) 94 (5) 101 (5) 16.1

Tilmicosin Macrolides/lincosamides 100 6.58 0.9962 106 (8) 103 (10) 106 (9) 9.6

Tolfenamic Acid Anti-inflammatories 200 10.70 0.9973 96 (4) 103 (3) 101 (3) -0.8

Triclabendazole Anthelmintics 50 9.62 0.9995 99 (7) 103 (2) 104 (2) 0.6

Triclabendazole Sulfoxide Anthelmintics 50 10.38 0.9962 93 (10) 97 (5) 103 (4) -8.9

Triflupromazine Tranquilizers 10 8.43 0.9989 95 (8) 108 (6) 108 (7) -5.1

Virginiamycin Miscellaneous 100 8.44 0.9959 103 (5) 105 (4) 99 (2) -1.7

Xylazine Tranquilizers 10 6.02 0.9979 106 (6) 104 (4) 102 (5) 4.8

Market Sample AnalysisThe developed method was applied for the analysis of veterinary drugs in five chicken samples fortified with internal standards. None of the studied drugs were detected in the samples based on the retention time and mass spectra information (two MRM transitions) in comparison with the corresponding reference standards.

Figure 5. The overlapped TIC of the six replicate chicken samples prepared by SPME at 0.3X spiking level.

1010

Conclusions

Analytical method development for multiresidue veterinary drugs in animal tissues is highly challenging owing to the complexity of the matrix, the large number of analytes to be monitored, the wide variation in their physico-chemical properties, and the often very low concentration levels that the method must be able to detect. Therefore, investigations related to the safety of food products of animal origin requires the use of powerful qualitative and quantitative analytical instrumentation that allows trace quantification and identification of drug residues. In addition to powerful instrumentation, sample preparation and clean-up are critical in relation to sample turnaround and the reliability of the analytical outcome. With the growing public concern regarding the safety of food products of animal origin, the demand for reliable automated and high-throughput analytical procedures has become an unmet need around the globe.

In this study, a high-throughput MMM for veterinary drug analysis in chicken was developed by using a fully automated SPME method, and coupling a UHPLC system to a QSight 220 triple-quad mass spectrometer. The validation results, and the minimal matrix effects achieved in this work, demonstrate that the proposed method can be successfully applied for the fast screening as well as quantitative analysis of more than 70 veterinary drugs in chicken tissue, with LOQs well below regulatory levels.

References

1. Biselli, S.; Schwalb, U.; Meyer, A.; Hartig, L. A Multi-Class, Multi-Analyte Method for Routine Analysis of 84 Veterinary Drugs in Chicken Muscle Using Simple Extraction and LC-MS/MS. Food Addit. Contam. - Part A Chem. Anal. Control. Expo. Risk Assess. 2013, 30 (6), 921–939.

2. Wang, J.; Leung, D.; Chow, W.; Chang, J.; Wong, J. W. Development and Validation of a Multiclass Method for Analysis of Veterinary Drug Residues in Milk Using Ultrahigh Performance Liquid Chromatography Electrospray Ionization Quadrupole Orbitrap Mass Spectrometry. J. Agric. Food Chem. 2015, 63 (41), 9175–9187.

3. Dasenaki, M. E.; Thomaidis, N. S. Multi-Residue Determination of 115 Veterinary Drugs and Pharmaceutical Residues in Milk Powder , Butter , Fi Sh Tissue and Eggs Using Liquid Chromatography – Tandem Mass Spectrometry. Anal. Chim. Acta 2015, 880, 103–121.

4. Rocca, L. M.; Gentili, A.; Pérez-Fernández, V.; Tomai, P. Veterinary Drugs Residues: A Review of the Latest Analytical Research on Sample Preparation and LC-MS Based Methods. 2017.

5. Reeves, T. .; Wang, J.; Macneil, J. D.; Kay, J. F.; Reeves, P. T. Chemical Analysis of Antibiotic Residues in Food; John Wiley and Sons, 2011; Vol. 199.

6. Su, Y.; Ma, X.; Ouyang, Z. Rapid Screening of Multi-Class Antimicrobial Residues in Food of Animal Origin by Paper Spray Mass Spectrometry. Int. J. Mass Spectrom. 2018, 434, 233–239.

7. Casado, N.; Morante-Zarcero, S.; Pérez-Quintanilla, D.; Sierra, I. Application of a Hybrid Ordered Mesoporous Silica as Sorbent for Solid-Phase Multi-Residue Extraction of Veterinary Drugs in Meat by Ultra-High-Performance Liquid Chromatography Coupled to Ion-Trap Tandem Mass Spectrometry. J. Chromatogr. A 2016, 1459, 24–37.

8. Greenlees, K. J.; Friedlander, L. G.; Boxall, A. Antibiotic Residues in Food and Drinking Water, and Food Safety Regulations. In Chemical Analysis of Antibiotic Residues in Food; John Wiley and Sons, 2011; pp 111–123.

9. Gros, M.; Rodríguez-Mozaz, S.; Barceló, D. Fast and Comprehensive Multi-Residue Analysis of a Broad Range of Human and Veterinary Pharmaceuticals and Some of Their Metabolites in Surface and Treated Waters by Ultra-High-Performance Liquid Chromatography Coupled to Quadrupole-Linear Ion Trap Tandem Mass Spectrometry. J. Chromatogr. A 2012, 1248, 104–121.

10. Geis-Asteggiante, L.; Lehotay, S. J.; Lightfield, A. R.; Dutko, T.; Ng, C.; Bluhm, L. Ruggedness Testing and Validation of a Practical Analytical Method for >100 Veterinary Drug Residues in Bovine Muscle by Ultrahigh Performance Liquid Chromatography- Tandem Mass Spectrometry. J. Chromatogr. A 2012, 1258, 43–54.

11. Bessaire, T.; Mujahid, C.; Beck, A.; Tarres, A.; Savoy, M. C.; Woo, P. M.; Mottier, P.; Desmarchelier, A. Screening of 23 β-Lactams in Foodstuffs by LC–MS/MS Using an Alkaline QuEChERS-like Extraction. Food Addit. Contam. - Part A Chem. Anal. Control. Expo. Risk Assess. 2018, 35 (4), 1–13.

12. Setting Standards for Maximum Residue Limits (MRLs) of Veterinary Drugs Used in Food-Producing Animals - Canada.ca https://www.canada.ca/en/health-canada/services/drugs-health-products/veterinary-drugs/maximum-residue-limits-mrls/setting-standards-maximum-residue-limits-mrls-veterinary-drugs-used-food-producing-animals.html (accessed Jan 13, 2020).

13. Lehotay, S. J.; Lightfield, A. R.; Geis-Asteggiante, L.; Schneider, M. J.; Dutko, T.; Ng, C.; Bluhm, L.; Mastovska, K. Development and Validation of a Streamlined Method Designed to Detect Residues of 62 Veterinary Drugs in Bovine Kidney Using Ultra-High Performance Liquid Chromatography - Tandem Mass Spectrometry. Drug Test. Anal. 2012, 4 (SUPPL.1), 75–90.

14. Alcántara-Durán, J.; Moreno-González, D.; Gilbert-López, B.; Molina-Díaz, A.; García-Reyes, J. F. Matrix-Effect Free Multi-Residue Analysis of Veterinary Drugs in Food Samples of Animal Origin by Nanoflow Liquid Chromatography High Resolution Mass Spectrometry. Food Chem. 2018, 245, 29–38.

15. Andersen, W. C.; Turnipseed, S. B.; Lohne, J. J. Emerging Techniques in Sample Extraction and Rapid Analysis. In Chemical Analysis of Non-antimicrobial Veterinary Drug Residues in Food; John Wiley & Sons, Inc.: Hoboken, NJ, USA, NJ, USA, 2016; pp 27–92.

11

16. Balizs, G.; Hewitt, A. Determination of Veterinary Drug Residues by Liquid Chromatography and Tandem Mass Spectrometry. Analytica Chimica Acta. Elsevier September 15, 2003, pp 105–131.

17. Stolker, A. A. M.; Danaher, M. Sample Preparation: Extraction and Clean-Up. In Chemical Analysis of Antibiotic Residues in Food; Wang, J., MacNeil, J. D., Kay, J. F., Eds.; Wiley Online Library, 2011; pp 125–152.

18. Stolker, A. A. M. M.; Danaher, M.; Martin, D. Sample Preparation: Extraction and Clean-Up. In Chemical Analysis of Antibiotic Residues in Food; Wang, J., MacNeil, J. D., Kay, J. F., Eds.; Wiley Online Library, 2011; pp 125–152.

19. Burns, L. E.; Borts, D. J. Rapid Untargeted Screening for Drug Residues in Animal Tissues with Liquid Microjunction Surface Sampling Probe Mass Spectrometry. Anal. Chim. Acta 2019, 1063, 75–81.

20. Souza-Silva E.A., Jiang R., Rodríguez-Lafuente A.,Gionfriddo E.,Pawliszyn J., Trends Analyt. Chem. 2015, 71, 224.

21. Xu C.H., Chen G.S., Xiong Z.H.,Fan X.H.,Wang X.C., Liu Y., Trends Analyt. Chem. 2016, 80, 12.

22. Souza-Silva E.A., Gionfriddo E., Pawliszyn J., Trends Analyt. Chem. 2015, 71, 236-248.

23. FSIS-USDA. CLG-MRM1.07. Screening and Confirmation of Animal Drug Residues by UHPLC-MS-MS https://www.fsis.usda.gov/wps/wcm/connect/b9d45c8b-74d4-4e99-8eda-5453812eb237/CLG-MRM1.pdf?MOD=AJPERES (accessed Dec 27, 2019).

24. Lehotay, S. J.; Lightfield, A. R. Simultaneous Analysis of Aminoglycosides with Many Other Classes of Drug Residues in Bovine Tissues by Ultrahigh-Performance Liquid Chromatography–Tandem Mass Spectrometry Using an Ion-Pairing Reagent Added to Final Extracts. Anal. Bioanal. Chem. 2018, 410 (3), 1095–1109.

25. Health Canada. List of Maximum Residue Limits (MRLs) for Veterinary Drugs in Foods https://www.canada.ca/content/dam/hc-sc/migration/hc-sc/dhp-mps/alt_formats/pdf/vet/mrl-lmr/mrl-lmr_versus_new-nouveau-20170802-eng.pdf (accessed Dec 3, 2018).

26. Khaled, A.; Gionfriddo, E.; Acquaro, V.; Singh, V.; Pawliszyn, J. Development and Validation of a Fully Automated Solid Phase Microextraction High Throughput Method for Quantitative Analysis of Multiresidue Veterinary Drugs in Chicken Tissue. Anal. Chim. Acta 2019, 1056, 34–46.

27. Berendsen, B. J. A.; Meijer, T.; Wegh, R.; Mol, H. G. J.; Smyth, W. G.; Armstrong Hewitt, S.; van Ginkel, L.; Nielen, M. W. F. A Critical Assessment of the Performance Criteria in Confirmatory Analysis for Veterinary Drug Residue Analysis Using Mass Spectrometric Detection in Selected Reaction Monitoring Mode. Drug Test. Anal. 2016, 8 (5–6), 477–490.

28. Vuckovic, D.; Cudjoe, E.; Musteata, F. M.; Pawliszyn, J. Automated Solid-Phase Microextraction and Thin-Film Microextraction for High-Throughput Analysis of Biological Fluids and Ligand-Receptor Binding Studies. Nat. Protoc. 2010, 5 (1), 140–161.

29. Stahnke, H.; Kittlaus, S.; Kempe, G.; Alder, L. Reduction of Matrix Effects in Liquid Chromatography–Electrospray Ionization–Mass Spectrometry by Dilution of the Sample Extracts: How Much Dilution Is Needed? Anal. Chem. 2012, 84 (3), 1474–1482.

30. Marazuela, M. D.; Bogialli, S. Determination of Veterinary Drug Residues in Foods by Liquid Chromatography–Mass Spectrometry: Basic and Cutting-Edge Applications. Liq. Chromatogr. 2013, 455–476.

31. Khaled, A.; Singh, V.; Pawliszyn, J. Comparison of Solid-Phase Microextraction to Solvent Extraction and QuEChERS for Quantitative Analysis of Veterinary Drug Residues in Chicken and Beef Matrices. J. Agric. Food Chem. 2019, 67, 12663–12669.

32. Musteata, M. L.; Musteata, F. M.; Pawliszyn, J. Biocompatible Solid-Phase Microextraction Coatings Based on Polyacrylonitrile and Solid-Phase Extraction Phases. Anal. Chem. 2007, 79 (18), 6903–6911.

33. Reyes-Garcés, N.; Gionfriddo, E.; Gómez-Ríos, G. A.; Alam, M. N.; Boyacl, E.; Bojko, B.; Singh, V.; Grandy, J.; Pawliszyn, J.; Augusto Gómez-Ríos, G.; et al. Advances in Solid Phase Microextraction and Perspective on Future Directions. Anal. Chem. 2018, 90 (1), 302–360.

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