Rapid analysis of aminoglycoside antibiotics in bovine tissues using disposable pipette extraction and ultrahigh performance liquid chromatography–tandem mass spectrometry

Journal of Chromatography A, 1313 (2013) 103–112

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Rapid analysis of aminoglycoside antibiotics in bovine tissues using disposable pipette extraction and ultrahigh performance liquid chromatography–tandem mass spectrometry夽 ˜ a, Steven J. Lehotay a,∗ , Katerina Mastovska a,1 , Alan R. Lightfield a , Alberto Nunez b c c Terry Dutko , Chilton Ng , Louis Bluhm a

U.S. Department of Agriculture, Agricultural Research Service, Eastern Regional Research Center, 600 East Mermaid Lane, Wyndmoor, PA 19038, USA US Department of Agriculture, Food Safety and Inspection Service, Midwestern Laboratory, 4300 Goodfellow Boulevard, Building 105D, St. Louis, MO 63120, USA c US Department of Agriculture, Food Safety and Inspection Service, Laboratory Quality Assurance Staff, 950 College Station Road, Athens, GA 30605, USA b

a r t i c l e

i n f o

Article history: Received 22 May 2013 Received in revised form 27 August 2013 Accepted 31 August 2013 Available online 8 September 2013 Keywords: Aminoglycoside antibiotic residues Analysis Ultrahigh performance liquid chromatography Tandem mass spectrometry Bovine tissues

a b s t r a c t A high-throughput qualitative screening and identification method for 9 aminoglycosides of regulatory interest has been developed, validated, and implemented for bovine kidney, liver, and muscle tissues. The method involves extraction at previously validated conditions, cleanup using disposable pipette extraction, and analysis by a 3 min ultrahigh-performance liquid chromatography–tandem mass spectrometry (UHPLC–MS/MS) method. The drug analytes include neomycin, streptomycin, dihydrosptreptomycin, and spectinomycin, which have residue tolerances in bovine in the US, and kanamicin, gentamicin, apramycin, amikacin, and hygromycin, which do not have US tolerances established in bovine tissues. Tobramycin was used as an internal standard. An additional drug, paromomycin also was validated in the method, but it was dropped during implementation due to conversion of neomycin into paromomycin. Proposed fragmentation patterns for the monitored ions of each analyte were elucidated with the aid of high resolution MS using a quadrupole-time-of-flight instrument. Recoveries from spiking experiments at regulatory levels of concern showed that all analytes averaged 70–120% recoveries in all tissues, except hygromycin averaged 61% recovery. Lowest calibrated levels were as low as 0.005 ␮g/g in matrix extracts, which approximately corresponded to the limit of detection for screening purposes. Drug identifications at levels <0.05 ␮g/g were made in spiked and/or real samples for all analytes and tissues tested. Analyses of 60 samples from 20 slaughtered cattle previously screened positive for aminoglycosides showed that this method worked well in practice. The UHPLC–MS/MS method has several advantages compared to the previous microbial inhibition screening assay, especially for distinguishing individual drugs from a mixture and improving identification of gentamicin in tissue samples. Published by Elsevier B.V.

1. Introduction The monitoring of veterinary drug residues in animal-derived foods is routinely conducted in many countries to help ensure food safety and the compliance of approved veterinary medical practices. Microbial resistance to antibiotics also is a notable topic of scientific investigation and regulatory interest [1]. The analytical

夽 Mention of brand or firm name does not constitute an endorsement by the U.S. Department of Agriculture above others of a similar nature not mentioned. This publication is not intended to state Food Safety and Inspection Service (FSIS) regulatory policy; the reader should refer to the FSIS website for guidance (www.fsis.usda.gov). ∗ Corresponding author. Tel.: +1 215 233 6433; fax: +1 215 233 6642. E-mail address: [email protected] (S.J. Lehotay). 1 Current address: Covance Laboratories, Nutritional Chemistry and Food Safety, 3301 Kinsman Boulevard, Madison, WI 53704, USA. 0021-9673/$ – see front matter. Published by Elsevier B.V. http://dx.doi.org/10.1016/j.chroma.2013.08.103

methods used to screen, identify, and quantify drug residues in foods for regulatory enforcement purposes must be validated in accordance with established rules or guidelines, and the quality of the results must meet method acceptability criteria prior to implementation [2,3]. Due to practical factors, routine monitoring methods should be affordable, easy, and safe to conduct and achieve high sample throughput. The greatest laboratory efficiency is most readily attained through the use of the fewest distinct methods to meet analytical needs for the widest possible scope of analytes. In 2012, the US Department of Agriculture’s Food Safety and Inspection Service (USDA-FSIS) implemented a multi-class, multiresidue monitoring method using ultrahigh performance liquid chromatography–tandem mass spectrometry (UHPLC–MS/MS) designed to screen and identify scores of veterinary drugs in food animal tissues [4–6]. However, the new method is not suitable for

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an important class of antibiotics, aminoglycosides, in part due to their highly polar nature, which typically requires chromatographic conditions less suitable for other drug classes [4,7–9]. A couple of reports described multiclass, multiresidue methods that include aminoglycosides [10,11], but an attempt to adapt these approaches was not as successful [4]. Many different screening and analytical methods for aminoglycoside antibiotics in animal tissues have been reported using LC–MS/MS [6,8–17]. The previous laboratory-based screening method used by FSIS involved a 7-plate microbial assay [18] followed by an LC–MS/MS confirmatory method for positive samples [6]. However, the screening method was not able to distinguish different aminoglycosides from each other, which have a wide range of tolerances and levels of interest [19]. Thus, the bioassay was too sensitive for certain aminoglycosides, such as neomycin, which led to an excessive number of follow-up analyses resulting in nonviolative positive samples, or samples which showed residues present but below tolerance levels. Accordingly, it is more efficient to use a rapid UHPLC–MS/MS method devised to screen, identify, and quantify individual aminoglycosides of concern [6]. Those few samples found to be positive above a threshold of interest are then re-analyzed by the official regulatory method for further quantification and confirmation to gain evidence in defense of enforcement actions [3–6]. If the identified drug is not allowed to be used in veterinary practices for the slaughter class, or if there is no established tolerance for the residue, then quantification is of secondary importance, and only confirmation of identity is needed in a second analysis [4,5]. As advances in analytical instrumentation such as UHPLC–MS/MS have resulted in significantly shorter sample analysis times [20], the key to high-throughput screening for drug residues has become efficient and effective sample preparation. This is particularly important in complicated tissue matrices such as kidney, liver, and muscle. Solid-phase extraction (SPE) is one of the most common techniques [21] to reduce matrix co-extractives in a reasonably efficient and cost-effective approach. DispersiveSPE, which involves mixing sorbents with the extracts in centrifuge tubes, is an even easier and less costly approach than the traditional cartridge-based SPE formats, despite that it provides somewhat less effective “chemical filtration” cleanup [4,5,22]. Disposable (or dispersive) pipette extraction (DPX) is another form of SPE [23–26], but which is conducted in a pipette tip rather than a cartridge or centrifuge tube. As opposed to the dispersive-SPE in a tube, which is employed for the chemical filtration clean-up (retention of matrix interferences on the sorbent), the DPX format also can be used for analyte retention and elution by a different solvent. The main potential advantage of DPX, especially when using a simple semi-automated lever-arm apparatus, relates to high-throughput parallel sample processing while still maintaining flexibility of sorbents and procedures. The aim of this work was to develop and validate a highthroughput method to screen, identify, and quantify targeted aminoglycoside antibiotics in bovine kidney, liver, and muscle at concentrations of regulatory interest. For the method to be appropriate for routine use by FSIS, it would have to show advantages over the previous FSIS combination of the 7-plate bioassay [18] and LC–MS/MS approach [6], and meet regulatory validation criteria for implementation by FSIS. DPX and UHPLC–MS/MS were chosen as the techniques to employ for this purpose due to their highthroughput capabilities.

Table 1 Spiking levels (1X) for the aminoglycosides in the different bovine tissues which were equivalent to the US tolerances for each matrix, except a default 1X spiking level of 0.1 ␮g/g was used for those drugs that have no established tolerance.

2. Materials and methods

2.2. Sample preparation

The complete standard operating procedures of the current version of the aminoglycosides method independently validated and

About 1 kg amounts of beef kidney, liver, and muscle (steak) were obtained from organic food suppliers. Many additional frozen

Drug analyte

Kidney (␮g/g)

Liver (␮g/g)

Muscle (␮g/g)

Neomycin B Spectinomycina Dihydrostreptomycin Streptomycin Amikacin Apramycin Gentamicin (sum)c Hygromycin B Kanamycin A

7.2 4 2 2 0.1 0.1 0.1 0.1 0.1

3.6 0.25b 0.5 0.5 0.1 0.1 0.1 0.1 0.1

1.2 0.25 0.5 0.5 0.1 0.1 0.1 0.1 0.1

a Spectinomycin and spectinomycin hydrate were monitored, but only spectinomycin was spiked. b No tolerance has been established for spectinomycin in liver and tolerance in muscle was used. c Gentamicin (sum) consisted of a mixture of gentamicin C1 , C1a , C2 , and C2a .

implemented by FSIS is reported in their Analytical Chemistry Laboratory Guidebook [6]. The work used to create the validated method is described in this report. 2.1. Chemicals and reagents Reference standards were obtained from Sigma (St. Louis, MO, USA) for amikacin, apramycin HCl, gentamicin sulfate, hygromycin B, kanamycin sulfate, neomycin B sulfate, paromomycin sulfate, and tobramycin (internal standard), and from US Pharmacopeia (Rockville, MD, USA) for dihydrostreptomycin sulfate, spectinomycin HCl, and streptomycin sulfate. Individual stock solutions of 1000 ng/␮L in H2 O were prepared and stored in fluoroethylenepropylene bottles. Due to concerns with the aminoglycosides sticking to glass surfaces, all working solutions were stored in polypropylene containers, and glass was not used in the sample preparation method. For the internal standard (tobramycin), a separate 40 ng/␮L aqueous solution was prepared. Mixtures of concentrations relative to spiking levels for each drug analyte relative to the tolerances for the bovine tissue involved in the study were prepared in H2 O. Table 1 lists the 1X spiking levels for the different tissue types, which determined the individual analyte concentrations in the mixed aminoglycoside solutions. When not in use, standard solutions were stored frozen at −18 ◦ C. Methanol (MeOH) was LC-grade from Burdick & Jackson (Muskegon, MI, USA) and acetonitrile (MeCN) was from Sigma–Aldrich. House-deionized water was further purified through a Barnstead E-pure system (Dubuque, IA, USA). Ethylenediaminetetraacetic acid, disodium salt, dihydrate (Na2 EDTA·2H2 O), heptafluorobutyric acid (HFBA), NaCl, NaOH, and trichloroacetic acid (TCA) were from Sigma, and ammonium acetate (NH4 OAc) and HCl was from Mallinkrodt (St. Louis, MO, USA). Formic acid, obtained from Fluka (Sigma–Aldrich), was diluted into a 10% aqueous solution. Individual 1 M HCl and NaOH and 30% (w/v) NaOH solutions in H2 O were used to adjust pH of extracts. The extraction solvent was 10 mM NH4 OAc, 0.4 mM EDTA, 1% NaCl and 2% TCA in H2 O, and mobile phases solutions consisted of 20 mM HFBA solutions prepared in (A) 95/5 (v/v) H2 O/MeCN and (B) MeCN. DPX tips of 5 mL volume containing 50 mg weak cation exchange (WCX) sorbent were obtained from DPX Labs (Columbia, SC, USA). A 20-position manually-operated lever arm extractor from DPX Labs was used for cleanup in DPX. Whatman (Maidstone, Kent, UK) MiniUniPrep syringeless filter vials with 0.2 ␮m PVDF filters served as autosampler vials for final extracts.

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samples of each tissue type were provided by FSIS for evaluation of the method. The pure fatty sections and connective tissues were cut away and disposed. The remaining tissues were cut into ≈5 cm3 portions and placed in the freezer. The samples were partially thawed and finely minced with a knife or chopped with dry ice in a food chopper (RSI 2Y1 from Robotcoupe, Ridgeland, MS, USA). The powdered samples were placed in unclosed ziplock bags in the freezer at −20 ◦ C to allow the dry ice to sublime overnight. The seals were then closed for sample storage until they were partially thawed prior for handling purposes prior to extraction. For extraction, 2.0 ± 0.1 g samples were weighed in 100 mL stomacher bags. In the case of spiked samples, 100 ␮L aliquots of the appropriate spiking solutions were added directly to the blank tissues to yield 0.5X, 1X, 2X, or other stated multiplication factors vs. the spiking levels shown in Table 1. Then, 20 mL of extraction solution described in Section 2.1 was added along with 100 ␮L of the 40 ng/␮L tobracmycin internal standard solution to yield 2 ␮g/g sample equivalent (but the internal standard was not added to blank samples to be used to make matrix-matched calibration standards). Several stomachers from Interscience (Saint Nom, France) and Seward (London, UK) were used to increase sample throughput, and samples were extracted typically in parallel using 2 bags per stomacher for 10 min. The liquid extracts were transferred from the bags to 50 mL polypropylene centrifuge tubes, which were centrifuged at 3700 rcf for 3 min. Floating material, if present, was removed with a spatula, and the extract was decanted into another 50 mL tube. A pH meter was used to check pH as it was adjusted to 6.5 ± 0.1 using 30% NaOH with 1 M HCl and 1 M NaOH used for fine adjustments. The extracts were centrifuged again at 3700 rcf for 3 min, being sure that the tubes of equal weights were balanced across from each other. A 10 mL aliquot of each extract was transferred to 15 mL polypropylene tubes (sample equivalent was ≈0.92 g accounting for the water in the samples). For DPX cleanup, the 5 mL tips (10 per row) containing 50 mg WCX sorbent were placed in the lever arm apparatus, and the lever arm was positioned to give ≈3 mL air in each of the plastic syringes used as individual pumps for each tip in the apparatus. Conditioning was conducted by pumping and dispensing 3 mL MeOH (once) from test tubes in a rack followed by 3 mL H2 O (twice) in another set of tubes in the same rack. The 10 mL extracts were then bubbled with the loose sorbent beds in ≈2.5 mL portions (≈30 s each), and dispensed into a set of 15 mL tubes along another row of the rack until the full 10 mL of each extract had interacted with the sorbents in the tips. To rinse the sorbents, another set of 3 mL volumes of H2 O (once) were pumped into and dispensed from the tips. Lastly, 0.9 mL of 10% formic acid aqueous solution was pumped and dispensed 5 times into the same test tubes. For real and spiked samples, 100 ␮L H2 O was added to each extract, and for matrix-matched standards, 100 ␮L of mixed standard solutions (each containing 20 ng/␮L tobramycin internal standard) were added to sample blank extracts to achieve the desired analyte levels for calibration standards (0.92 g/mL sample equivalent). For preparation of reagent-only calibration standards, 0.9 mL of 10% formic acid aqueous solution was substituted for sample blank extracts in the same procedure otherwise. Then, 0.5 mL of final extracts was transferred to the syringeless filter autosampler vials, which were capped to filter. The vials were placed in the autosampler tray which was kept at 4–7 ◦ C during the analytical sequence. 2.3. Analysis For analysis, a Waters (Milford, MA, USA) UPLC–MS/MS TQD system with MassLynx operating software was employed. The UHPLC column was a Waters BEH C18, 2.1 mm i.d., 50 mm length, 1.7 ␮m particles, coupled with a VanGuard Pre-column BEH C18,

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2.1 × 5 mm, 1.7 ␮m. The injection was 15 ␮L. Mobile phase flow rate was 0.5 mL/min, and the gradient went from 100% A (20 mM HFBA in 95/5 H2 O/MeCN) for 0.5 min, then ramped to 20% B (20 mM HFBA in MeCN) from 0.5 to 1 min, then ramped to 40% B from 1 to 2 min, followed by 90% B from 2 to 2.05 min, where it was held until 2.5 min, and ramped again to 100% B from 2.5 to 2.55 min, where it was held until the end of the run of 3 min total. The divert flow valve was set to waste until 0.8 min and after 2.4 min to reduce source contamination from salts and matrix components. The mobile phase was returned to 100% A after each 3 min run and 1 min given for re-equilibration. As a precaution to help keep the system clean after each sequence, 5–10 min of 100% MeCN was pumped at 0.5 mL/min to flush the column, and the source and gas cones were exchanged for clean ones (two sets were alternately cleaned and re-used). In MS/MS, electrospray positive ionization (ESI+) was used, the source temperature was 150 ◦ C, desolvation temperature was 450 ◦ C, and capillary voltage was 3.0 kV. The Supplementary table lists the individual MS/MS parameters used for each analyte in the method. One of the criteria for MS identification in regulatory enforcement applications is that the ion transitions must make sense structurally, which helps to avoid choice of the wrong ions during method development. In separate experiments to conduct structure elucidation of ions, a Waters Synapt G1 quadrupoletime-of-flight mass spectrometer (Q-ToF) was used in ESI+ mode. The aminoglycosides at 1 ng/␮L were infused individually at 0.030 mL/min in 3:1 H2 O:MeCN containing 0.1% formic acid, and ion fragments from the precursor ion were detected with high resolution ToF (achieving <5 ppm mass accuracy). The molecular formulas of the ions could be discerned from their m/z, which were helpful to define structures of the fragments for qualitative purposes.

3. Results and discussion 3.1. Choice of aminoglycoside analytes, an issue with paromomycin, and stability The list of aminoglycoside analytes for monitoring was provided by FSIS, which were similar as those monitored previously in the FSIS National Residue Program [18,19]. Levels of interest for the different bovine tissues are given in Table 1, which correspond to the 1X spiking level. For those drugs without tolerances, 0.1 ␮g/g was used as the default 1X spiking concentration in light of that being the tolerance for sulfonamides. Paromomycin was added later in validation experiments for possible monitoring by FSIS, but it was uncovered during validation of pork matrices by FSIS that paromomycin was being formed by chemical conversion from neomycin, which also is described in the literature [27,28]. This situation leads to potential mistaken regulatory actions for misuse of paromomycin because the original source of the drug residue could be neomycin. This is not unique in residue analysis, and analytical chemists must be aware of the pitfalls and consequences of overly-simplistic and rigid interpretations of MS results or regulatory guidelines [29,30]. Thus, we chose not to include our paromomycin results in the method tables, but we give its results separately in the text for those who may wish to monitor for it with appropriate precautions to avoid possible false positives from approved uses of neomycin. Stability of matrix-matched (extracts) and reagent-only calibration solutions were demonstrated experimentally over the course of 7 weeks with storage at 4 ◦ C. No losses were observed except possibly for tobramycin, which showed no differences for 27 days, but which gave 10% lower response after 41 days and a −20% difference

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1,2

3 4,5

6 7

8,9 10-13

1,2

3 4,5

6 7

8,9 10-13

A

B

Fig. 1. Total ion chromatograms of the aminoglycosides in (A) reagent-only and (B) matrix-matched calibration standards for kidney equivalent to the 1X spiking levels as shown in Table 1 (tobramycin is 2 ␮g/g). Each peak is normalized to the signal intensities as shown; peak numbers corresponding to the analytes and their parameters appear in Table 2. *The extra peak in the kidney extract at 1.75 min is a matrix component with one of the same transitions as kanamycin.

after 49 days. Gentamicins and apramycin also potentially gave <25% losses, but these differences may have been to experimental variability at the relatively lower concentrations involved. A recent report in the literature also demonstrates that aminoglycosides are very stable in refrigerated solutions [31]. 3.2. UHPLC–MS/MS matrix effects and calibration Aminoglycosides are so polar that they tend to exhibit little or no retention in reversed-phase LC even when using aqueous mobile phase. This is why they typically cannot be monitored at the same chromatographic conditions as other classes of drugs. Instead, normal-phase [32,33], ion-pairing [12,15–17], or hydrophilic interaction liquid chromatography (HILIC) [10,11,13,34] is more commonly needed. Mastovska and Lightfield devised a novel dual column reversed-phase and normal-phase approach for aminoglycosides and other drug classes in which the re-equilibration times in gradient elution were used for alternate analyses [33], but this system has not yet been tested using UHPLC. In this study, we used an MS/MS-amenable ion-pairing reagent, HFBA, under reversed-phase conditions with a standard C18 UHPLC column manufactured for the Waters system. The final mobile phase and gradient were devised to achieve separation of analytes in a short chromatographic runtime of 3 min including the column wash. Total cycle time from injection to injection in a sequence was ≈4 min to provide high-throughput operation. Fig. 1 shows example UHPLC–MS/MS total ion chromatograms (sum of ion signals in each segment) for the 1X level reagent-only and matrix-matched standards for kidney (see Table 1 and the supplementary table for concentrations and ion transitions). The scale for each peak is given on the right to show the large differences in signal intensities due primarily to analyte concentrations and relatively smaller contributions due to matrix effects (mainly from ion suppression) that occur as a result of co-eluting chemical components [5,35,36]. The chromatogram in Fig. 1B shows only one matrix component from kidney (marked with an asterisk at ≈1.8 min), which originated from one of the ion transitions for kanamycin (peak 7). This matrix peak appeared at a much different retention time (tR ) from any analytes, but undetected matrix components may have been

the source of a small tR shift for kanamycin in sample extracts from all 3 matrices. As shown in supplementary information, direct matrix interferences were not appreciably observed for the drug analytes in the blank tissue extracts for bovine kidney, liver, or muscle. The low intensity ions observed in the case of spectinomycin hydrate in the blanks were not matrix interferants, but were likely a result of trace level carry-over and/or slight contamination. The levels of concern for spectinomycin were much higher than observed in the spectinomycin hydrate background responses. The monitoring of spectinomycin and its hydrate are a subject of discussion in Section 3.4. Matrix effects (MEs) were measured in each experiment by calculating the average %differences in the peak areas from the quantifier ions of the matrix-matched vs. reagent-only calibration standards at each level. Ideally, an isotopically labeled internal standard of each analyte would be used to avoid MEs and achieve best quantitative results, but unfortunately, no such standards were available for the aminoglycosides from common commercial sources. A single internal standard for all analytes has been shown to help compensate for MEs if quantification is being conducted using reagent-only standards [37]. In this case, though, the tobramycin internal standard gave no MEs in the 3 tissue types (0 ± 4% ME), thus MEs for the other analytes were essentially the same with or without the use of the internal standard. Table 2 provides average %MEs for the different drugs sorted by tR in the different sample types. Since the %MEs depend on coeluting components, these can be monitored vs. tR , and it becomes apparent from the results that the most severe co-elutions took place at the front of the chromatogram until ≈1.8 min. No ion suppression of note occurred after 1.9 min, including in the case of paromomycin with tR of 1.99 min. Paromomycin averaged 5%, 13%, and 53% MEs for kidney, liver, and muscle, respectively, using the ion transitions shown in supplementary information. Curiously, hygromycin with tR of 1.21 min did not undergo strong MEs as did the other aminoglycosides that eluted from 1 to 1.7 min. Furthermore, the %ME results show that enhancements occurred in different matrices for hygromycin, apramycin, and gentamicin (and paromomycin in muscle). Enhancements in

S.J. Lehotay et al. / J. Chromatogr. A 1313 (2013) 103–112 Table 2 Average matrix effects (%ME) for the analytes in the different bovine matrices with analytes listed in order of tR . Drug analyte

Kidney

Liver

Muscle

Spectinomycin Spectinomycin hydrate Hygromycin B Streptomycin Dihydrostreptomycin Amikacin Kanamycin A Apramycin Tobramycin (int. std.) Gentamicin (sum) Neomycin B

−41 −25 28 −23 −53 8 −49 9 3 2 1

−56 −36 29 −42 −62 −5 −66 27 −6 10 −4

−76 −67 −10 −53 −67 7 −19 35 −2 48 19

the latter part of the chromatograms were observed previously in bovine tissues, which were eliminated by dilution of the extracts [5]. Dilution of the final extracts would provide relief from MEs in this method, but a more sensitive instrument was needed to yield acceptable results for all analytes at levels for regulatory purposes. Although dilution of extracts would have been preferable for neomycin, spectinomycin, streptomycin, and dihydrostreptomycin, we were unable to dilute the extracts further and still meet detection needs for the other analytes (particularly gentamicins). As demonstrated in Fig. 1 and supplemental, the observed enhancements were not necessarily the same for all concentrations. Hygromycin in liver extract gave consistently positive responses vs. concentration, but greater differences in MEs were observed in the other matrices. The likely cause of its more variable MEs were other co-eluting analytes in the calibration standards, some of which had very high concentrations as shown in Table 1 and Fig. 1. This situation also is a contributing factor leading to nonlinear calibration curves (see supplemental). In this study, quantification was conducted using matrixmatched calibrations with normalization to the tobramycin internal standard. A common problem in quantification in trace chemical residue analysis is that regulatory enforcement levels can be very high or very low (theoretically zero in some circumstances) for the same drug in different sample types, depending on the established residue tolerance level or if there is no tolerance established [2,3]. The concentrations were much higher for the 4 drugs with established tolerances than those drugs without tolerances, which led to the situation that the calibration standards did not always fall in the linear dynamic region. Perhaps less intense ions or less optimal conditions to reduce sensitivity for higher concentration analytes could have been used, but this path would

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likely adversely affect quality of results. Also, it is unlikely that this “nonoptimization” approach would reduce analyte–analyte MEs because co-eluting concentration differences would remain very large, which would continue to affect linearity of responses. Thus, we systematically used best-fit quadratic calibration curves as a matter of course in this study, even in cases where the responses were linear. Supplemental shows some examples of reagent-only and matrix-matched calibration curves for different analytes and matrices. The quadratic curves better accounted for low level and high level standards, which also did not necessitate the use of weighting factors in calibration. In real samples, calculated concentrations may be affected by the presence of closely eluting drugs and their levels in extracts and standards alike. Ideally, secondary analysis also should provide accurate quantification and confirmation information for drugs having tolerances to support regulatory enforcement actions. The need for ascertaining analyte concentrations is less important in cases where drugs without tolerances are found in regulatory samples. 3.3. Quantitative method validation Tables 3 and 4 report the recovery and reproducibility results for each of the aminoglycoside antibiotics at different spiking levels in the 3 bovine tissue types. These validation experiments were conducted over 7 days with 132 replicates overall, and the combined tobramycin-normalized results for all 3 tissues at all spiking levels appear in Table 4. Tobramycin results were very consistent, with average %recoveries of 72 ± 4 in kidney (n = 60), 71 ± 5 in liver (n = 36), and 81 ± 5 in muscle (n = 36) with 74 ± 6% recovery overall at the 2 ␮g/g spiking level. As the tables indicate, the average recoveries for each analyte were quite consistent between matrices and spiking levels, and as expected, relative standard deviations (RSDs) decreased as spiking concentrations increased. Despite that the lowest spiking level was 50 ng/g for certain aminoglycoside antibiotics, spiking levels were actually lower for the individual gentamicins, which consisted of a mixture of 4 compounds (C1 , C1a , C2 , and C2a ) of unstated proportions. The latter two forms could not be distinguished by the MS/MS transitions or tR in this approach (even though asymmetric peak shape showed they have slightly different tR ). Supplementary information shows the structures of the different gentamicin components along with the selected ion transitions. The issue with gentamicins will be discussed further in Sections 3.4 and 3.5, but individual concentrations of the lowest component level were <10 ng/g, and half of that at the lowest calibrated level. Thus, it is expected that the individual gentamicins showed higher variability in their recoveries even

Table 3 %Recoveries and relative standard deviations (%RSD) results from a 3-day validation experiment for the aminoglycosides method in bovine kidney. Quantification entailed that peak areas were normalized to the tobramycin internal standard with matrix-matched calibration using quadratic curves. Spiking concentrations shown for 1X levels appear in Table 1. Analyte Amikacin Apramycin Dihydrostreptomycin Gentamicin C1 Gentamicin C1a Gentamicin C2 + C2a Gentamicin (sum) Hygromycin B Kanamycin A Neomycin B Spectinomycin Spectinomycin hydrate Streptomycin

0.25X, n = 6

89 (4) 103 (9) 107 (4)

0.5X, n = 18

1X, n = 18

2X, n = 18

95 (13) 99 (20) 121 (10)a 92 (22) 76 (28) 95 (20) 90 (13) 72 (22) 103 (20) 86 (16) 93 (9)a 94 (10) 97 (12)

88 (12) 95 (12) 115 (11)a 88 (8) 90 (24) 92 (15) 90 (9) 63 (19) 102 (20) 94 (8) 90 (9)a 93 (7) 99 (13)

87 (5) 91 (10) 118 (8)a 83 (10) 94 (18) 88 (11) 87 (8) 61 (16) 93 (14) 97 (14) 86 (10)a 89 (6) 98 (7)

4X, n = 6 81 (2) 95 (4) 123 (10) 78 (2) 74 (15) 80 (2) 78 (3) 67 (3) 82 (10)

7X, n = 6

103(2)

88 (6)

Only spectinomycin hydrate was monitored on day 1; empty cells indicate spiking was not done at those levels for those drugs. a n = 12. b n = 42.

14X, n = 6

93(3)

Overall, n = 60 89 (15) 95 (15) 115 (12) 87 (16) 85 (25) 90 (16) 88 (11) 65 (20) 98 (19) 92 (15) 91 (11)b 93 (9) 97 (11)

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Table 4 %Recoveries and relative standard deviations (%RSD) results from 2-day validation experiments each for the method in bovine liver and muscle. Quantification entailed that peak areas were normalized to the tobramycin internal standard with matrix-matched calibration using quadratic curves. Spiking concentrations shown for 1X levels appear in Table 1. Analyte

Liver

Muscle

0.5X, n = 12 Amikacin Apramycin Dihydrostreptomycin Gentamicin C1 Gentamicin C1a Gentamicin C2 + C2a Gentamicin (sum) Hygromycin B Kanamycin A Neomycin B Spectinomycin Spectinomycin hydrate Streptomycin

79 (14) 91 (20) 90 (7) 90 (18) 92 (30) 91 (25) 92 (19) 56 (32) 76 (39) 91 (6) 73 (9) 77 (9) 72 (13)

1X, n = 12 84 (10) 97 (13) 104 (10) 94 (17) 107 (24) 100 (23) 100 (15) 56 (16) 92 (18) 100 (9) 77 (15) 78 (12) 76 (14)

2X, n = 12 90 (12) 101 (8) 105 (11) 94 (10) 106 (13) 92 (11) 96 (8) 61 (14) 97 (13) 95 (10) 88 (10) 82 (8) 80 (12)

Overall, n = 36 84 (13) 96 (15) 100 (12) 93 (16) 102 (24) 94 (21) 96 (15) 58 (22) 88 (26) 95 (9) 80 (14) 79 (10) 76 (13)

though the individual gentamicin components nearly always averaged 90–100% recoveries. The elution of neomycin at varying high concentrations <5 s away probably contributed to this variability, as well as the ion enhancement factors described in Section 3.2. The sum of the gentamicin peaks greatly improved precision of the results, decreasing overall RSD from 30% for C1a to 14% for the sum. Unfortunately, there is no perfect solution to quantify gentamicin except to analyze each C-form individually using pure standards of each component, but the individual standards do not exist commercially. We believe this summation to be appropriate since the US gentamicin tolerance for swine is established for the total residues of gentamicin, and formulations and standards are only available as mixtures. The concentrations of individual components were unknown, and only the total amounts added to samples and standards were known. Dihydrostreptomycin gave a high bias in results for kidney (n = 60) with 115 ± 14% recovery, but this phenomenon was not observed in the muscle and liver tissues, which gave consistent quantitative (100%) recoveries. This may have been due to its relative average recovery being 15% higher than tobramycin in kidney, but the possible relationship between streptomycin and dihydrostreptomycin also may have been a factor. Streptomycin had 76 ± 10% recovery in liver (n = 36), but its recoveries were 92–97% in kidney and muscle. Otherwise, all recoveries at each 130 120

pH 3.5

pH 4.5

0.5X, n = 12 81 (12) 79 (22) 97 (7) 97 (33) 97 (53) 92 (20) 93 (14) 58 (28) 84 (15) 87 (5) 85 (18) 80 (14) 94 (10)

Tissues overall, n = 132 1X, n = 12 81 (17) 91 (12) 102 (3) 93 (24) 104 (25) 90 (17) 94 (15) 64 (18) 84 (13) 98 (6) 95 (11) 87 (12) 93 (10)

2X, n = 12 83 (7) 93 (13) 97 (10) 91 (16) 107 (27) 89 (12) 93 (13) 64 (12) 90 (9) 98 (12) 85 (10) 86 (9) 89 (8)

Overall, n = 36 82 (13) 88 (17) 99 (8) 94 (26) 102 (36) 90 (17) 93 (14) 62 (22) 86 (13) 94 (10) 89 (14) 85 (13) 92 (10)

86 (13) 93 (16) 106 (13) 90 (20) 94 (30) 91 (18) 91 (14) 62 (22) 92 (21) 94 (12) 88 (14) 87 (13) 90 (15)

level in all matrices averaged between 72 and 105%, except for hygromycin, which rather consistently averaged 62 ± 14% recovery overall. This lower recovery for hygromycin was a trade-off involving pH adjustment prior to DPX clean-up during method development. Fig. 2 shows the results of an experiment designed to optimize pH of the extracts prior to the DPX step. Clearly, using a pH of 6.5 gave the highest recoveries for all aminoglycosides in the DPX step using the WCX sorbent. The lower observed recoveries for hygromycin in the final method could arise from extraction or UHPLC–MS/MS factors, but the lower pKa1 of 7.1 for hygromycin sets it apart from the other drugs with pKa of 8.1–8.8. Perhaps using a pH of 6.0 would have been slightly better, but this was not tested in the final method. The results for paromomycin are not presented in the tables for the reasons stated at the start of Section 3. Validation experiments for n = 6 each at 50, 100, and 200 ng/g in bovine kidney, liver, and muscle gave 93% recovery and 13% RSD overall for paromomycin with no differences in results observed among tissues or the day of analysis. As expected, reproducibility improved as concentrations increased, and % RSDs were 16, 13, and 8 (n = 18 each) for experiments in bovine tissues at 50, 100, and 200 ng/g spiking levels, respectively. All results were compared to quantitative regulatory criteria by the US Food and Drug Administration (FDA) Center for

pH 5.5

pH 6.5

pH 7.5

pH 8.5

DPX recovery (%)

110

100 90 80 70 60 50 40 30

20 10 0

Fig. 2. Recoveries of the aminoglycosides added at 2 ␮g/g each to bovine kidney extracts depending on adjusted pH prior to the DPX step (n = 2 for each pH).

S.J. Lehotay et al. / J. Chromatogr. A 1313 (2013) 103–112

109

Table 5 Averages and standard deviations of qualitative factors used in the identification of the aminoglycoside analytes in the bovine tissues spiked at different levels (n = 114). Ion #1 is the quantification ion listed in Table 2 and ions #2 and #3 are the qualifier ions to yield the given ion ratios for identification purposes. Drug Analyte

tR (min)

Spectinomycin Spectinomycin hydrate Hygromycin B Streptomycin Dihydrostreptomycin Amikacin Kanamycin A Apramycin Tobramycin Gentamicin C1a Gentamicin C2 + C2a Gentamicin C1 Neomycin B

1.078 1.075 1.206 1.257 1.284 1.618 1.682 1.986 2.029 2.091 2.121 2.133 2.162

± ± ± ± ± ± ± ± ± ± ± ± ±

2/1 ratio (%) 0.004 0.005 0.008 0.010 0.009 0.010 0.015 0.006 0.008 0.008 0.007 0.005 0.006

Veterinary Medicine (CVM), which entail 80–110% average recovery and ≤10% RSD for concentrations ≥100 ng/g and 60–110% recoveries and ≤20% RSD for concentrations <100 ng/g [3]. In the wider regulatory arena, 70–120% recoveries are generally considered acceptable with 15–25% RSD depending on concentration [38]. It should be noted that this application primarily serves as a screening approach for FSIS to replace the screening function of the 7-plate bioassay [4–6,18], not as an official drug registration method used for enforcement actions. The official regulatory methods for FDA-approved aminoglycosides currently consist of bioassays developed prior to the conventional acceptance of LC–MS/MS as an analytical tool. Thus, screen positive results above 0.5X levels for drug/tissue pairs are analyzed further to obtain determinative (quantification) and confirmatory information using official regulatory methods. 3.4. Analyte identification and ion fragmentation patterns For enforcement actions, confirmation that analytes are present in the samples must be made by a second analysis. One of the confirmatory methods should involve analyte identification, typically using MS techniques [2,29,30,38,39]. The FSIS LC–MS identification criteria for regulatory purposes involve several factors [4,5,39]: (1) the tR of the detected analyte peak must be within ±5% of the analyte reference standard peak; (2) the different ion transitions for the analyte should co-elute with similar peak shapes; (3) the ratios of peak areas for each ion transition must match the ratios of the reference standard(s) within ±10% absolute for one transition or ±20% absolute for two transitions; (4) reagent and matrix blanks must be shown to be free of carry-over, contamination, and/or interferences above an appreciable level; (5) signal/noise ratios for measured peaks must be >3; (6) the signal must exceed the threshold intensity level as compared to the signal of a suitable reference standard or control encompassing the level of interest; and (7) the ion transitions chosen for identification purposes should make chemical/structural sense. We verified all qualitative aspects, including elucidation of the fragment ion pathways, as shown in supplemental information, which were proposed with the help of Q-ToF analysis as described separately for other veterinary drugs [40]. The high resolution analysis of fragment ions enabled us to resolve previously uncertain proposed pathways reported in the literature, including corrections to schemes for streptomycin, dihydrostreptomycin, gentamicins, and neomycin proposed by Kotretsou [41]. Even though only spectinomycin was added to the samples and standards, it also exists in its hydrate form, which is prominent in aqueous solutions [42]. After initially choosing to only monitor spectinomycin hydrate (as indicated in Table 3) due to its higher ion intensities than spectinomycin, we thereafter chose to monitor both precursor

60 63 95 49 34 21 35 39 34 63 78 77 69

± ± ± ± ± ± ± ± ± ± ± ± ±

9 5 16 3 1 2 8 7 8 29 20 23 4

3/1 ratio (%)

3/2 ratio (%)

55 ± 10 30 ± 2 26 ± 6 26 ± 3 21 ± 1 15 ± 2 23 ± 9 16 ± 5 n/a 31 ± 17 29 ± 10 55 ± 16 35 ± 10

95 ± 22 48 ± 3 28 ± 7 54 ± 5 61 ± 3 74 ± 9 68 ± 26 42 ± 16 n/a 62 ± 70 39 ± 17 77 ± 32 51 ± 13

ions for the same analyte, spectinomycin (m/z 333 precursor) and its hydrate (m/z 351). This gave additional confidence in both the quantitative and qualitative findings for spectinomycin in the method. Tables 3 and 4 show that the quantification is much the same whichever ion is monitored, and if differences are observed between them, the results should be further investigated. In terms of qualitative aspects, 6 ion transitions are being monitored for spectinomycin rather than typically 3 in the case of the other targeted drugs. Table 5 shows the combined results for each analyte obtained from bovine kidney, liver, and muscle samples at different spiking levels. The first consideration in UHPLC–MS/MS identification is tR , and as in previous studies [4,5], the consistencies of tR in UHPLC was demonstrated to be exceptional. The standard deviation of tR was only 0.9 s in the 3 matrices measured over the course of 5 days in the worst case (kanamycin as also shown in Fig. 1). FSIS criteria allow ±5% difference in tR from the contemporaneously-analyzed reference standard, which corresponds to ±3 s when tR = 1 min and ±6 s when tR = 2 min. However, as also discussed previously [4,5], a constant window of ±0.1 min (±6 s) is an appropriate alternative. The tR for all analytes in all experiments were highly consistent in each matrix, and no false negatives occurred in the study due to tR shifts. In the case of the 4 aminoglycosides having established tolerances (spectinomycin, streptomycin, dihydrostreptomycin, and neomycin) spiked in the tissues at higher concentrations (see Table 1), no false negatives occurred in the validation experiments when at least 3 ion transitions were monitored (n = 114). In initial experiments, only 2 ion transitions were monitored, but this led to an undesirably high rate of false negatives for nearly all analytes due to the requirement of ±10% absolute ion ratio acceptability range for identifications based on a single ion ratio. For the 5 drugs without an established tolerance in bovine (amikacin, apramycin, gentamicin, hygromycin, and kanamycin) spiked at lower concentrations in the matrices, false negatives still occurred even when using the more liberal criterion of ±20% absolute ion ratio acceptability range for 2 ion ratios. No false positives were observed in the blanks as shown in supplementary information, or in subsequent testing by FSIS using many replicates from different food animal tissues. The low level background responses for spectinomycin hydrate in each matrix was omnipresent in this study and believed to be an artifact in the analysis. This further demonstrates the value in monitoring for both spectinomycin and its monohydrate to provide greater confidence in identifications. Fig. 3 shows the differing rates of true identifications based on the 2-ions ±20% ratios for the drugs spiked at lower concentrations (%false negatives are the differences from 100%). For paromomycin, tR was 1.986 ± 0.007 min with standard deviations for ion ratios 2/1, 3/1, and 3/2 of 12%, 9%, and 13%, respectively (n = 120). False

110

A

S.J. Lehotay et al. / J. Chromatogr. A 1313 (2013) 103–112

provides strong evidence for the identification of gentamicin. As Fig. 3B shows, no false negatives occurred for gentamicin when taking all 3 peaks into account.

100%

90%

Identifications

80% 70%

3.5. Analysis of real samples

60% 50%

Amikacin

40% 30%

Apramycin

20%

Kanamycin

10%

Hygromycin B

0% 0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

Spiked Concentration (µg/g)

B

100% 90%

Identifications

80% 70% 60% 50% 40%

Gentamicin (sum)

30%

Gentamicin C2+C2a

20%

Gentamicin C1

10%

Gentamicin C1a

0% 0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

Spiked Sum Concentration (µg/g) Fig. 3. Percentage of analyses using the UHPLC–MS/MS method that identification criteria were met for aminoglycosides without US tolerances spiked at different concentrations in bovine kidney, liver, and muscle (n = 36 each level from 0.05 to 0.20 ␮g/g and n = 12 at 0.40 ␮g/g). In Plot B, gentamicin (sum) identification includes detected ion peaks at the correct tR independent of ion ratios for each individual component of the gentamicin mixture.

negatives for paromoycin were 31%, 11%, and 0% at 0.05, 0.10, and 0.20 ␮g/g spiking levels, respectively (n = 36 each). For amikacin and apramycin, the standard deviations in their 2/1 and 3/1 ion ratios were merely 2–7%, and only one false negative occurred (at the 0.05 ␮g/g level) among 240 chances. However, hygromycin gave greater variation of 16% standard deviation in the 2/1 ion ratio, leading to 36% false negatives at the 0.05 ␮g/g spiking level. The 3/2 ion ratio was not used in this evaluation, nor the possibility that one of the 3 ion ratios fell within the ±10% criterion for a single ratio. The use of these caveats would have lowered the rates of false negatives. The situation with gentamicins is different than the other drug analytes because it is actually a mixture of 4 components. In all validation experiments, quantifier ion peaks appeared at the correct tR of all 3 gentamicin peaks even at the lowest spiking levels in all 3 matrices. In only 2 instances out of 1080 combinations (3 ion transitions × 3 peaks × 120 replicates) did a qualifier ion peak fail to appear for an added gentamicin component. Gentamicins are treated as a single analyte in regulatory applications, thus the presence of the 3 chromatographic peaks could be considered as 3 transitions of a single peak to provide qualitative information for identification. The ratios of the peak areas may change depending on the animal metabolism, gentamicin formulation, and reference standard used, thus peak area ratios among the different quantification ions should not be part of the qualitative assessment, but the appearance of the peaks themselves, especially recognizing the unique shape of the combined C2 + C2a peak (see Fig. 1),

FSIS provided 20 each of matched kidney, liver, and muscle samples from bovine carcasses processed at slaughter establishments. The kidneys tested positive in microbial inhibition bioassays used by FSIS in the field, and they were subsequently found to be positive for aminoglycosides in the 7-plate bioassay used in the lab by FSIS. Table 6 gives the UHPLC–MS/MS method results for the samples. Quantification was conducted using matrix-matched calibration standards with lowest calibrated level of 0.005 ␮g/g for each drug. For screening purposes, “indications” [29] in the table refer to quantification ion peaks at the correct tR for the anaytes. No indications were observed in any of the 60 samples for amikacin, apramycin, hygromycin, kanamycin, or streptomycin. If these analyses were conducted for regulatory purposes, only the kidney samples would have been tested first. All results for spectinomycin and dihydrostreptomycin were <0.5X tolerance levels, thus these samples would not have been re-analyzed on account of those drugs. Similarly, all findings for neomycin except in cattle #13–15 would not have triggered a second analysis. The 12 and 13 ␮g/g neomycin concentrations in kidney samples #13 and #15, respectively, would have been above the established tolerance if confirmed to be correct, but the 4.4 ␮g/g result for kidney sample #12 would have been below the established tolerance. Table 6 also shows that several cattle contain residues of multiple drugs, which is not an unusual finding [19,43]. As described previously [4,5], UHPLC–MS/MS possesses several advantages over the 7-plate bioassay, and this ability to distinguish individual drugs at different concentrations in the same sample is probably the most important feature in practice. Significant savings in time, labor, and costs are made by reducing the number of re-analyses. However, all confirmed findings for gentamicin, which was identified in different tissues from cattle #1, #3, #8, and #9, would be considered positive findings independent of concentrations. In practice, much of the discussion about the identification criteria for gentamicin becomes immaterial because estimated concentrations were >5 ␮g/g for the 4 gentamicin presumed positive findings. The gentamicin indications (1–2 peaks for the 3 quantification ions at the correct tR ) for kidneys #2, #4, and #10 (<0.02 ␮g/g in each case) would be candidates for further confirmatory testing. Examination of the ratios of the different gentamicin peaks in the real samples led to interesting findings. In the reference standards, the relative ion peaks for gentamicin C1a :C2 + C2a :C1 averaged 22:46:32 in peak intensities independent of concentration or tissue type, which held true in the spiked samples as well. This leads to accurate quantification results, but quantification of gentamicin by any method involving a mixed standard will be somewhat less accurate if the ratios between the C1 , C1a , C2 , and C2a components are different in the sample than in the standard. In the real samples, the C1a :C2 + C2a :C1 ratios were consistent for each tissue among the different cows, but gave slightly different ratios for each tissue type. For the 4 real-world kidney samples, the C1a :C2 + C2a :C1 ratios closely averaged 35:49:16, but in the liver and muscle samples containing measurable gentamicin, the average ratios were 18:46:36 and 17:57:26, respectively. The samples from FSIS were obtained from different slaughterhouses at different times, thus the gentamicin drug formulations seem to be quite consistent, as evidenced by the highly reproducible peak ratios (particularly in the kidney results). However, the different drug profiles in the liver and muscle samples are indicative of different aspects of animal metabolism, but which leads to surprisingly consistent gentamicin peak ratios within each tissue type.

S.J. Lehotay et al. / J. Chromatogr. A 1313 (2013) 103–112

111

Table 6 Results (␮g/g) for matched tissues from 20 cattle, the kidneys of which had previously tested positive for aminoglycosides by FSIS using the 7-plate bioassay. Values given means identification criteria were met, “+” indicates only the quant. ion peak was present at the correct tR (positive screen result), and “−” is a negative result. #

Spectinomycin Kidney

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 a b

1.7 − − + − + − 0.45 − − − − + − + − − 0.25 − −

Liver 0.082 + − + − + − 0.049 − − − − − − − − − 0.056 − −

Dihydrostreptomycin Muscle 0.013 − − − − − − + − − − − − − − − − − − −

Neomycin

Kidney

Liver

Muscle

0.030 0.15 − 0.93 − 0.32 − 0.019 − − − − 0.095 − − − − − 0.028 −

− 0.010 − 0.064 − 0.038 − − − − − − − − − − − − − −

− − − + − + − − − − − − − − − − − − + −

Kidney 0.010 0.007 <0.005 1.5 <0.005 − − − − 2.1 0.75 0.007 12 4.4 13 0.043 − 0.24 2.1 0.007

Gentamicin Liver 0.006 − − 0.009 − − − − − 0.005 − − 0.12 0.19 0.48 <0.005 − 0.008 <0.005 0.012

Muscle <0.005 − − 0.009 − − − − − 0.013 <0.005 − 0.013 0.008 − − − + <0.005 −

Kidney a

16 + 5.8a + − − − 27a 12a + − − − − − − − − − −

Liver

Muscle

0.40 − 1.5a − − − − 1.8a −b 0.22b − − − − − − − − − −

0.032 − + − − − − 0.038 − − − − − − − − − − − −

Estimated concentrations based on extrapolation. Probable sample mismatch.

Another piece of very useful evidence is the presence of the same drug residues in different tissues from the same animal. Table 6 clearly shows how aminoglycosides occur at highest concentrations in the kidney and recedingly lower concentrations in the liver and muscle tissues. 4. Conclusions This method was designed primarily to be an easy, economical, and effective screening approach with high sample throughput for 9 targeted aminoglycoside antibiotics of US-regulatory importance in bovine tissues. An analyst can complete a batch of 20 samples along with necessary controls in about 5 h. Multiple batches can be combined and completed by an analyst dependent upon necessary equipment available. This high-throughput method serves to complement the multi-class, multi-residue screening method implemented by FSIS covering a broad scope of veterinary drug residues in different food animal tissues [6]. This method for aminoglycosides also was validated by FSIS in several matrix types and implemented for parallel analysis of the same samples by the broader method [6]. The combination of these two UHPLC–MS/MS methods covers substantially more drugs of concern than the previous combination of the 7-plate microbial inhibition assay and unwieldy single-class chemical methods [4,18]. These UHPLC–MS/MS methods provide screening, identification, and (semi-)quantification of many individual drugs that could not be detected or distinguished from each other by previous FSIS screening methods. Paromomycin also was found to provide acceptable results in the bovine tissues validated in this study, but precautions must be taken in practice to be aware of false positives due to its conversion from neomycin. In additional experiments, we tested some of the most polar drug analytes that did not yield good results in the multiclass, multiresidue method [4,5] in this method. Although the UHPLC–MS/MS conditions could be modified (longer tR ) to incorporate the additional drugs into the detection method, analytes such as tulathromycin, sulfanilamide, florfenicol amine, desacetyl cephapirin, and 2-mercapto-1-methylimidazole were not appreciably recovered by the aminoglycosides method in spiked kidney samples.

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