Wide-Scope Screening Method for Multiclass Veterinary Drug

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Wide-scope screening method for multiclass veterinary drug residues in fish, shrimp and eel using liquid chromatography- quadrupole high resolution mass spectrometry Sherri B. Turnipseed, Joseph M. Storey, Jack J. Lohne, Wendy Cook Andersen, Robert Burger, Aaron S. Johnson, and Mark R. Madson J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.6b04717 • Publication Date (Web): 28 Dec 2016 Downloaded from http://pubs.acs.org on January 4, 2017

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Journal of Agricultural and Food Chemistry

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Wide-scope screening method for multiclass veterinary drug

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residues in fish, shrimp and eel using liquid chromatography-

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quadrupole high resolution mass spectrometry

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Sherri B. Turnipseed1*, Joseph M. Storey1, Jack J. Lohne1, Wendy C. Andersen1, Robert Burger2,

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Aaron S. Johnson2, Mark R. Madson1, 2

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Animal Drugs Research Center, US Food and Drug Administration, Denver, CO 80225

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Denver Laboratory, US Food and Drug Administration, Denver, CO 80225

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* Corresponding author: [email protected]; 303-236-3072

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ACS Paragon Plus Environment


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ABSTRACT

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A screening method for veterinary drug residues in fish, shrimp and eel using LC with a high

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resolution MS instrument has been developed and validated. The method was optimized for over

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70 test compounds representing a variety of veterinary drug classes. Tissues were extracted by

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vortex mixing with acetonitrile acidified with 2% acetic acid and 0.2% p-toluene sulfonic acid.

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A centrifuged portion of the extract was passed through a novel solid phase extraction cartridge

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designed to remove interfering matrix components from tissue extracts. The eluent was then

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evaporated and reconstituted for analysis. Data were collected with a quadrupole- Orbitrap high

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resolution mass spectrometer using both nontargeted and targeted acquisition methods. Residues

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were detected based on the exact mass of the precursor and a product ion along with isotope

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pattern and retention time matching. Semi-quantitative data analysis compared MS1 signal to a

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one-point extracted matrix standard at a target testing level. The test compounds were detected

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and identified in salmon, tilapia, catfish, shrimp, and eel extracts fortified at the target testing

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levels. Fish dosed with selected analytes and aquaculture samples previously found to contain

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residues were also analyzed. The screening method can be expanded to monitor for an additional

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> 260 veterinary drugs based on exact mass measurements and retention times.

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KEYWORDS

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High resolution mass spectrometry, Aquaculture, Veterinary drug residues, Screening methods


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INTRODUCTION

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Aquaculture is a growing industry anticipated to supply approximately 100 million tons or over

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60% of the fish destined for human consumption by 2030. Many types of veterinary drugs may

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be administered to fish in an aquaculture environment to treat disease or proactively prevent

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infection.1, 2 Traditionally, analytical methods were developed to monitor for one residue, or for

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several analytes from a specific class of drugs, in a single species of fish or shellfish. More

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recently, multiclass methods have been developed using liquid chromatography (LC) with

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tandem mass spectrometry (MS),3-5 but these methods are still limited to targeted analytes.

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Using high resolution mass spectrometry (HRMS) instruments, a virtually unlimited

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number of compounds can be simultaneously analyzed because full-scan data are collected rather

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than preselected ion transitions corresponding to specific compounds. Selectivity is achieved by

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taking advantage of the instrument’s ability to provide very accurate mass measurements.

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Residue identification can be based on calculated exact masses of protonated molecules and

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fragment ions, relative isotopic abundances and retention times. This can lead to the

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development of methods that can monitor for a wide scope of residues and contaminants,

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allowing regulatory agencies to be more proactive in discovering possible adulteration of the

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food supply including aquacultured products.

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The use of HRMS technology for detecting drug residues in aquaculture and other foods has

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been reviewed6,

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and includes methods that utilize time-of-flight (ToF)8-11 or orbital ion trap

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(Orbitrap)12-14 HRMS. These methods have demonstrated the ability to detect, identify and

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quantitate an increasing number of analytes. However, some of these early HRMS methods were

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sometimes limited by insufficient mass resolution to accurately measure exact mass in complex

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matrices and a lack of sensitivity to detect residue levels.


The Q-Exactive is a hybrid


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quadrupole-Orbitrap HRMS instrument that has the advantage of operating at increased

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resolution and the ability to collect product ion spectra with or without initial precursor isolation

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using the quadrupole filter.

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Using a MS detector with this capability further enhances the need for the most universal

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extractant and cleanup method possible. Ideally the method should also be simple and quick.

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Although a large number of veterinary drug residue LC-MS methods and cleanup strategies are

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available in the literature for fish and shrimp,5,

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recently been introduced. Removal of lipids is especially important for high fat-containing

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matrices such as salmon and other fish. Fats (specifically phospholipids) can be significant

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HPLC column contaminants and can also contribute to severe matrix suppression in signal

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response for MS detection. New commercially available clean-up techniques are designed to

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eliminate these interferences without severe loss of analyte recovery.16,

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clean-up products were evaluated along with the choice of initial extraction solution to optimize

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a procedure suitable for a wide variety of analytes at residue levels.

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specific lipid cleanup technologies have

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These new sample

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The aim of this research was to be able to screen and identify a wide scope of veterinary

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drug residues in several types of fish matrices. An optimized extraction method was used with an

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LC separation combined with a Q-Exactive (Orbitrap) HRMS.

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according to FDA guidelines18,

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addition to monitoring fish extracts for these test compounds, the full scan HRMS data could be

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compared to a compound database containing about 260 additional (> 330 total) veterinary drugs

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to significantly expand the number of residues that might be detected in any given sample.

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The method was validated

using the representative compounds listed in Table 1. In

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MATERIALS AND METHODS

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Standard Preparation

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Individual stock standards were made in methanol, except for β-lactams, which were dissolved in

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water or acetonitrile/water depending upon solubility. Oxolinic acid was prepared in acetonitrile.

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All stock standard solutions were made at a concentration of approximately 100 µg/mL as the

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free base or acid. Stock standards for the β-lactams were stored at - 25 °C; all others were stored

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at 4 °C. Two different spiking standard mixes (“stable” and “non-stable”) for positive ion

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compounds were made. A 1X target testing level (TTL) spike was made by adding portions (see

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below) of both mixtures to control tissue. The “unstable” analyte spiking mix contained the β-

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lactams, tetracyclines, cephapirin, and dye compounds as listed in Table 1. The unstable standard

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spiking mix was prepared by combining an amount (a volume equal to twenty times the TTL

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level for each compound, corrected for the exact concentration) of each individual stock standard

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and diluting to 20 mL with acetonitrile. To prepare a 1X TTL spike containing all of the unstable

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compounds, 20 µL of this standard mix was added to 2 g of control tissue. This “unstable”

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spiking mix standard is stable for six months at -25 °C. The “stable” standard spiking mix

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consists of all remaining positive ion compounds listed in Table 1. Similarly, the stable analyte

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mix was also prepared by combining an amount (a volume equivalent to 20X the TTL for each

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compound) of each individual stock standard and diluting to 40 mL with acetonitrile. To prepare

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a 1X TTL spike containing all of the stable compounds, 40 µL of this standard mix was added to

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2 g of control tissue. This “stable” spiking mix standard is stable for one year at -25 °C. A

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separate fortification mixture for the negative ion compounds was made in the same manner as

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the stable spiking mix. Samples were fortified with negative ion compounds by adding 40 µL of

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that standard mix to 2 g of control tissue.



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To prepare a solvent standard equivalent to 1X TTL in tissue, 100 µL of the stable

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standard mix and 50 µL of the unstable standard mix were combined and diluted to 5 mL with

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90:10 water: acetonitrile. (This assumes an extraction scheme of 2g→ 10 mL then 2 mL → 0.4

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mL). If an additional acetonitrile injection was needed for salmon, then an equivalent

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acetonitrile solvent standard was additionally prepared by diluting the previous solvent standard

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1:5 with acetonitrile. A negative ion 1X TTL equivalent solvent standard was prepared by

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diluting 100 µL of the negative mixed standard mix to 5 mL with 90:10 water:acetonitrile.

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Sample Extraction

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Homogenized tissue (2.0 ± 0.05 g) was weighed into a 50 mL polypropylene tube, and spiking

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standard mixes were added as appropriate and allowed to mix with the tissue for at least 5 min.

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The tissue was extracted with 8 mL of extraction solution consisting of 0.2% p-toluene sulfonic

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acid (p-TSA) monohydrate (w/v) and 2% glacial acetic acid (v:v) in acetonitrile. The samples

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were vortex mixed for 30 min using a multi-tube vortex mixer at a setting speed of 2500 rpm

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then centrifuged for 7 min (4° C) at minimum of 17,000 RCF (x g). A portion (3 mL) of the

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extract was transferred to an Oasis PRiME HLB 6 cc (200 mg) extraction cartridge with a 15 mL

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polypropylene tube underneath. The samples were allowed to gravity drain (ca. 10 min) through

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the cartridges. The remaining few drops of extractant were gently pushed out through the SPE

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tube with a pipet bulb. (This should give just over 2 mL of liquid at this point). If the tissue was

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salmon, 100 µL of the extract was transferred into an LC vial for an acetonitrile injection. The

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remaining portion of the extract was taken to near dryness under nitrogen stream at 55° C (a drop

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of liquid remaining in the 15 mL tube was acceptable). The extract was then reconstituted with

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400 µL of 10% acetonitrile in water (v:v), mixed, and centrifuged at a minimum of 28,900 RCF

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(x g) for 7 min. Finally, an aliquot of 300 µL was carefully removed from the polypropylene


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tube, leaving particulates behind, and transferred into a LC vial. Overall there was no net

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dilution of concentration of the sample through the extraction procedure. (A sample fortified at

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10 µg/kg = 10 ng/mL in LC vial).

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Incurred Samples

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Incurred fish samples were provided by the Center for Veterinary Medicine Office of Research.

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Two tilapia were dosed with 1 mg/kg body weight of sulfadiazine with 1 day depuration. Two

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other tilapia were dosed with 5 mg/kg body weight of sulfadiazine and 1 mg/kg body weight of

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trimethoprim and were sacrificed at 3 and 4 days. Two catfish were dosed with 5 mg/kg body

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weight of enrofloxacin with a 6 day withdrawal. Control tilapia and catfish were grown and

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harvested concurrently with these dosed animals. Catfish and salmon from an earlier (2014)

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dosing study with triphenylmethane dyes were also tested with this method. These fish were

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exposed to a water bath containing a mixture of 2 µg/L of malachite green, crystal violet, and

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brilliant green for 1 hour followed by 1 hour depuration in clean water.

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Instrument Acquisition Methods

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Instrumentation

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The instrument used was a Thermo Q-Exactive Orbitrap high resolution mass spectrometer

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(HRMS) with a heated electrospray ionization source coupled to a Thermo Ultimate 3000 LC

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system. Thermo XCalibur software (V. 3.0.63) was used for data acquisition and preliminary

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data analysis; data analysis was also performed using TraceFinder software (V 3.2).

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MS Acquisition Programs

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The instrument was calibrated for mass accuracy according to the manufacturer’s

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recommendations at least once a week. The tuning method optimized signals for a majority of

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the test compounds with the LC conditions described below. General MS acquisition parameters



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were as follows: spray voltage, 4kV (positive), 2.5kV (negative); S-Lens RF level, 50; capillary

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temperature, 350 ˚C; auxiliary gas temperature, 325 ˚C; gas flow rate (N2, arbitrary units):

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sheath, 50; auxiliary, 10; sweep, 2. Other general MS parameters include: acquisition time, 0-

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12.5 min; Lock mass, OFF; Chrom peak, 15 s.

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Two different types of acquisition programs were used to analyze the fish extracts. All

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Ion Fragmentation (AIF) was used for initial data acquisition. AIF is a nontargeted method in

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which a full scan MS is followed by a MS2 scan where all precursors are allowed into the high

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collision dissociation (HCD) cell to form product ions simultaneously. The settings for AIF

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were MS1: 70K resolution, 3e6 automatic gain control target, maximum inject time 200 ms, m/z

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150-1000 scan range; MS2: 70K resolution, 3e6 automatic gain control target, maximum inject

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time 200 ms, m/z 80-1000 scan range, normalized collision energies of 10, 30, and 50.

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A second set of data (separate injection of fish extract) was obtained using Data

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Dependent MS2 (DDMS2) data acquisition. With this program, MS2 data were collected when a

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precursor ion from a predefined “inclusion list” was detected (from a full MS1 scan) above a set

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threshold. When that occurred, the quadrupole filtered the precursor ion into the HCD cell using

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a limited m/z window to produce fragment ions related to that compound. The inclusion list for

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positive ion analytes contains approximately 290 of the compounds from the larger database,

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including all test compounds and other analytes for which a retention time was known (1.5 min

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windows were used in the list). Some of the more obscure analytes in the larger compound

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database were not included so the instrument did not waste analysis time triggering spectra for

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those compounds. Analytes can be added to the inclusion list as needed. The DDMS2 inclusion

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list for negative ion compounds was much smaller containing only compounds included in the

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validation (Table 1), although this list can also be expanded as needed. The operating parameters


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for this data acquisition for MS1 are: 70K resolution, 1e5 automatic gain control target, maximum

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inject time 200 ms, m/z 150-1000 scan range. The operating parameters for DDMS2 are: 17.5K

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resolution, 1e5 automatic gain control target, maximum inject time 50 ms, loop count 3, isolation

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width 4 m/z, normalized collision energy 10, 30, 50. Other data dependent settings are: underfill

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ratio 0.5%, calculated intensity threshold 1e4, apex trigger 3-6 s, dynamic exclusion 6 s.

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Negative ion data were collected with separate injections using AIF and DDMS2 acquisition.

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Chromatography

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LC separation was performed using a Supelco Ascentis Express C18 (7.5 cm x 2.1 mm, 2.7 µm)

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fused-core reversed-phase column. The mobile phase consisted of 0.1 % formic acid in water

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(A) and acetonitrile (B) at a flow rate of 0.3 mL/min. The LC gradient program was initialized at

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5% B and held for 1.5 min then ramped to 50% B from 1.5 to 8.5 min, followed by a ramp to

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99% B from 8.5 to 9 min, and then was held at 99% B from 9 to 12 min. The mobile phase was

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returned to 5% B from 12 to 12.5 min and the column was re-equilibrated for an additional 2

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min. The total LC runtime was 14.5 min; MS data were collected for 12.5 min (no divert valve

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was used). The column temperature compartment was kept at 30 ˚C, and the autosampler tray

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temperature was maintained at 10 ˚C. The LC injection volumes were 10 µL or 20 µL for AIF or

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DDMS2 MS acquisition programs, respectively. Multiple injections of a high level dye standard

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may be needed to condition a new column in order to detect low levels of leuco crystal violet and

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leuco malachite green.

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Data Analysis

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Several stages of data analysis were performed. First the AIF data were analyzed to determine if

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the test compounds were identified and present at concentrations above the threshold cutoff level

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(>50% TTL). AIF data could also be compared to the larger veterinary drug compound database



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to determine if additional analytes (beyond the test compounds) were in a sample. The product

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ion spectra from DDMS2 data could also be evaluated. Negative ion data were evaluated using

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the same processes.

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Limit testing and confirmation of identity for test compounds using AIF data

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AIF data from full MS1 scans were used for initial screening of test compounds. A Thermo

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TraceFinder “Quantitative Method” was established to provide data for the test compounds listed

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in Table 1, including a few degradants (e.g., penillic acid and dehydrated erythromycin). The

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test compounds in the “Quantitative Method” were a subset of analytes imported from the larger

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compound database (N > 330) which contains information for retention time and exact masses of

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fragment ions.

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In order to be qualitatively identified, the precursor ions must be present (signal-to-noise

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>3) and match theoretical exact mass within a 5 ppm mass tolerance. The data analysis program

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searched for residues within a time window of 60 s (30 s on each side of specified retention

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time), but a more narrow retention time match (± 0.1 min) to a standard injected the same day

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was typically observed. Fragment detection was also required with at least one fragment ion

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with 500 count minimum intensity threshold within a 10 ppm maximum mass deviation window.

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These criteria are consistent with the FDA guidance.19 The isotope match feature was also

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enabled with a 70% fit threshold, 5 ppm mass deviation, and 10% intensity deviation allowance.

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A sample would be considered presumptive positive for a test compound if the qualitative

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criteria were met and the signal was ≥ 50% as compared to the matrix-extracted standard

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fortified at the TTL.

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Expanded screening for additional veterinary drug residues


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A Thermo TraceFinder “Screening Method” was used to search for additional residues beyond

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the test compounds.

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containing > 330 potential veterinary drug residues, including metabolites and minor

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components. New compounds are continuously being added to the database, and experimental

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data for retention time and fragment ions are included for a majority of these compounds.

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Criteria used in the “Screening Method” were 3 ppm mass tolerance for the precursor ion, greater

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than 100 signal-to-noise ratio, and a signal of greater than 5000 counts for initial detection. In

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order to identify a residue by the screening method, a retention time window match within 60 s

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and a minimum of one fragment ion with intensity threshold of > 500 counts and mass tolerance

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within 10 ppm were required. The retention time and fragment ion criteria could be ignored if

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not defined in the database. The isotope pattern match option was used to filter out false detects.

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Additional qualitative data analysis from DDMS2

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The extracts were analyzed in a separate LC-MS injection using DDMS2 data acquisition. After a

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full MS1 scan, product ion spectra were collected after precursor isolation for analytes in an

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inclusion list if the signal from the MS1 ion met data dependent triggering requirements. Residue

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findings were evaluated for identification criteria using the same data analysis methods described

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above for AIF data. Product ion spectra produced by DDMS2 data acquisition could also be

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manually evaluated using XCalibur QualBrowser software for consistency with solvent and/or

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matrix-extracted standards. Alternatively, spectra could be compared to commercially available

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libraries.

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Validation

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The method was validated according to the FDA Office of Food and Veterinary Medicine

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Guidelines for Chemical Method Validations v 2. for “limit testing”18 with veterinary drugs from

Data collected using AIF were compared to a compound database



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a variety of chemical classes in representative matrices. A summary of the fortification samples

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generated for the validation is included in the supplemental material. Salmon and tilapia were

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used for the initial validation. The majority of the replicates were analyzed at the TTL (1X) to

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generate variance data at that level to set an appropriate threshold cutoff to determine if samples

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should be considered presumptive positive. Fortification samples at 2X, 0.5X, and 0.1X of the

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TTL were also analyzed along with blank matrix samples to determine the lowest minimum

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detectable and confirmation levels, as well as the rates of false positive and false negative results.

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The method was also applied, with fewer overall replicates, to catfish, shrimp and eel in order to

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demonstrate matrix extension to these species. Incurred samples of tilapia (SDZ and SDZ +

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TMP), catfish (ENRO, dyes), and salmon (dyes), as well as regulatory samples that had been

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found to contain residues, were also tested. A second set of validation samples was generated for

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negative ion compounds. Shrimp and salmon were the primary matrices validated for negative

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ion analytes, as these are the species in which phenicol or benzyl urea residues are expected to be

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found, respectively. RESULTS AND DISCUSSION

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Compounds and Testing Levels

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A list of veterinary drug residues of importance in aquacultured species (along with their target

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testing levels) is given in Table 1. The target testing level (TTL) or “1X” is not necessarily

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considered an official tolerance or action level. The majority of these compounds are not

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approved for use in fish in the U.S., so technically any amount found and identified would be

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violative. These values are meant to provide a reasonable concentration at which a residue may

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be expected to be consistently detected and identified using this screening method. For ease of

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sample preparation and data reporting, it is helpful if TTLs for the test compounds are all within

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a practical range (5-50 µg/kg). Some analytes will have TTLs higher (tetracyclines) or lower


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(methyl testosterone and dyes) than that range due to previously established levels of interest. 20

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In addition, for some compounds, such as amoxicillin and the avermectins, the TTLs may be

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>100 µg/kg due to higher detection limits for these analytes in this method. The minimum

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detectable limits for all compounds extracted from fish was determined, and for most compounds

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was found to be considerably lower (0.1X) than the TTL.

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Optimization of Extraction Procedure

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Extraction Solvent

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The list of analytes shown in Table 1 includes triphenylmethane dyes and avermectins. These

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two classes of compounds greatly increase the difficulty of choosing an acceptable sample

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extractant and clean-up procedure. Previous work4 summarizes the difficulty of including dyes in

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a multi-residue method. In addition, it is desirable that any chosen extractant be able to extract

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very polar analytes such as florfenicol amine and metronidazole as well as several non-polar

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compounds. The goal was to develop a simple cleanup procedure to apply to as many of the

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compounds in this list as possible.

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Methanol or acetonitrile as the primary organic component in a meat or fish extractant is

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most widely reported in the literature. Water (with or without buffer salts) is not effective for

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extracting non-polar analytes.

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precipitate proteins in tissue. The use of acetonitrile only (with no other purification steps) as a

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veterinary drug extractant for tissue has been published.21 Acetonitrile has also been used (in

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combination with secondary hexane partitioning) to extract residues from catfish, salmon and

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trout.22 However, when 100% acetonitrile (without acid modifiers) was tried for our list of

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analytes, recoveries for crystal violet and fluoroquinolones were very low (< 10%). Current

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veterinary drug residue methods used by USDA23, 24 for bovine muscle use 4:1 acetonitrile:water

Acetonitrile is usually preferred because of its ability to



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for extraction.

The method has some advantages, including extracting a wide range of

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compounds and allowing very rapid sample throughput. However, although this extractant

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appeared to extract avermectins successfully in bovine muscle, the 80% acetonitrile solution was

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too polar to successfully extract ivermectin from high-fat salmon. In addition, the final extract

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composition described in the USDA method (70% acetonitrile) gave poor peak shape for polar,

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early eluting analytes using the rapid reversed phase chromatographic gradient developed for this

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screening method.

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chromatography, but would sacrifice sensitivity.

Further dilution with water of the final extract would improve

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Our initial investigations focused on using acetonitrile containing acid modifiers as an

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extractant. Acetonitrile with 0.1% acetic acid has been used25 to extract residues from salmon

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and was successful in extracting emamectin and malachite green. Acetonitrile with 1% acetic

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acid has also been used26 for shrimp with similar results. In initial experiments with salmon,

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degradation of several β-lactams was observed when 0.2% or 1% formic acid in acetonitrile was

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used as an extractant. Formic acid in water is known27 to cause rapid degradation of monobasic

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penicillins. Further, formic acid in acetonitrile did not extract avermectins well from salmon and

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had an adverse effect on macrolides. For these reasons, acetic acid was chosen to acidify the

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acetonitrile extractant. By increasing acetic acid from 0.1 to 2% in the acetonitrile extractant, the

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recoveries for fluoroquinolones, avermectins and penicillins doubled. Previous work in our

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laboratory4 showed that the addition of p-TSA improved the recovery of dyes and

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fluoroquinolone compounds so this acid was added to the 2% acetic acid in acetonitrile

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extractant. Provided that acetic acid was also present in the extractant, the p-TSA did not seem

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to appreciably degrade penicillins. The final extraction solvent chosen was acetonitrile with 2%


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acetic acid with 0.2% p-TSA. A comparison of recoveries for representative analytes using

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variable amounts of acid modifiers in tilapia (using Oasis PRiME HLB) is shown in Figure 1.

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Sample Clean-up

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Two new types of cleanup techniques designed specifically for high-fat samples were

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evaluated. Agilent’s EMR® Lipid system is a dispersive SPE technique involving two primary

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sorbents: a water-activated sorbent designed to specifically trap fats containing >5-carbon

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aliphatic chains and a second sorbent containing magnesium sulfate and sodium chloride. A

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published report16 using this technique for the analysis of veterinary drug residues in bovine liver

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was initially evaluated for salmon. Although this procedure worked well for many analytes in

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Table 1, some were not recovered. The 5% formic acid solution used as the extractant in the

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application note did not work well for some penicillins or for the avermectins in salmon. The

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magnesium sulfate sorbent also greatly lowered the recovery of some tetracyclines.

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A Waters Oasis ®PRiME HLB SPE cartridge was also evaluated as a clean-up tool. As

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described in a published method17 for the analysis of veterinary residues in pork tissue, a portion

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of tissue extract is introduced into the SPE cartridge (no conditioning is required) and collected

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by gravity drain. For this method, two changes were made to accommodate the analyte list in

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Table 1. First the extractant of formic acid, acetonitrile and water was changed to the final

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optimized extractant described above. Second, to improve sensitivity, a portion of the extract

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was evaporated (instead of diluted per original method) and reconstituted with 9:1

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water/acetonitrile to allow for successful reversed-phase chromatography. For the newest triple

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quadrupole mass spectrometers, dilution may become less of an issue, but for full scan data

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acquisition obtained using the Orbitrap, a 10 minute evaporation step was included to

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concentrate the extract. The larger 200 mg SPE sorbent size was used to collect a larger volume



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of extractant for evaporation and concentration. Various HPLC filters were evaluated for use in

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filtering the final extract before injection. Although polyvinylidene fluoride filters worked the

335

best (compared to nylon or PTFE), we observed inconsistent or no recovery after filtration in

336

solvent spikes for some analytes. For this reason the final extract was not filtered but was

337

instead centrifuged to help remove any remaining particulates after the evaporation and

338

reconstitution step.

339

For salmon, some compounds (avermectins, brilliant green and crystal violet) were lost

340

when extracts were evaporated and reconstituted most likely because they partitioned into

341

insoluble lipid material.

342

compounds in salmon as described earlier in the experimental section. Because the relevant

343

compounds for the acetonitrile injection elute late in the reversed phase chromatographic system,

344

good peak shapes and consistent retention times are achieved despite the high organic content.

345

This extra injection was also required for nonpolar negative ion compounds (lufenuron,

346

teflubenzuron, toltrazuril) fortified in salmon. A portion of the acetonitrile extract (before

347

drying) was also tested with the other fish matrices. In general, this step was not necessary with

348

the less fatty fish as residues were adequately recovered in the evaporated and reconstituted

349

extract.

350

Method Evaluation

This necessitated a separate acetonitrile injection to detect those

351

Although this method is meant to be used as a screen, some evaluation was made of its

352

quantitative performance (analyte recoveries and method precision). The majority of the test

353

compounds fortified in tilapia had recoveries (as compared to a single solvent standard at the

354

target testing level) of greater than 70%. Recovery values for selected analytes in tilapia are

355

shown in Figure 2. Some compounds such as avermectins gave high recoveries (150-220%)


Page 17 of 46


17

356

compared to a solvent standard, indicating matrix signal enhancement might occur especially

357

when monitoring sodiated molecules. A few compounds (such as penillic acid and erythromycin

358

dehydrate) were formed by decomposition during the acidic extraction process, so their apparent

359

recoveries were quite high as compared to a solvent standard. The compounds with lower

360

recoveries tended to be β-lactams, benzimidazoles, and macrolides. No changes were made to

361

the extraction method to accommodate the negative ion compounds.

362

Strategy for screening using HRMS

363

The strategy for this method development was to optimize and validate sample preparation and

364

MS acquisition methods for representative compounds that are most likely to be used in

365

aquaculture, and then use the full scan HRMS capability along with a compound database of

366

veterinary drugs to screen samples for >260 additional compounds.

367

compound databases with exact mass data for thousands of analytes are commercially available,

368

this method is focused on more limited set of analytes that are likely to be used as veterinary

369

drugs. In addition, a majority of the compounds in this database have been analyzed with this

370

LC-MS method so that relevant retention time data have been obtained. The chromatographic

371

parameters were also designed to accommodate a large number of compounds with very

372

different polarities in a relatively short analysis time. The retention times of the test compounds,

373

along with exact masses of precursor and product ions, are listed in Table 1. Exact mass data for

374

product ions which have been verified as the correct theoretical value are also included.11,

375

Searching against larger commercial databases containing additional compounds such as

376

pesticides, forensic chemicals, and other contaminants can always be performed, but this can

377

lead to a higher percentage of false detects.11


Although very large

28


Page 18 of 46

18

378

Two types of MS acquisition methods were evaluated. Initially, nontargeted AIF was

379

used to analyze the extracts. With AIF data acquisition, all precursor ions (MS1) eluting into the

380

MS at a given time are allowed into the HCD cell to form product ions. This results in a

381

“product ion” spectrum that is a mixture of ions from different analytes and matrix components.

382

However, using the HRMS instrument’s ability to extract data within a narrow mass range, a

383

specific product ion in that spectrum can be detected within the retention time window of the

384

precursor ion to identify the compound.

385

generating screening data as shown below. A more targeted approach, DDMS2, was also used to

386

generate product ions specific to selected precursor ion from compounds on an inclusion list.

387

Data Independent Analysis (which allows subsets of precursors into the HCD cell) was also

388

investigated, but was not found to have any clear advantages over AIF at this time.

389

Results for Validation Samples

390

AIF data

391

With this screening method, data from fortified samples were analyzed to determine if the test

392

compounds could be detected, identified, and measured at a concentration near the TTL. Area

393

counts from extracted ion chromatograms of the precursor ions were compared to those from a

394

matrix-extracted standard fortified at the TTL (1X). Figure 3 shows examples of extracted ion

395

chromatograms of selected positive ion residues in tilapia fortified at the TTL.

AIF proved to be a simple, reliable method of

396

Semi-quantitative limit testing determines if a residue is present at or above the

397

concentration of interest, so it is important to measure the variance of the signals generated from

398

residues present in samples at this concentration. A threshold cutoff value can then be set to

399

determine when to call a sample “presumptive positive”.4, 18 For all matrices tested, 10 replicate

400

samples fortified at the TTL were extracted and analyzed on the same day. One extracted sample


Page 19 of 46


19

401

was assigned as the standard (100% relative recovery) and the relative recoveries of the other

402

replicates were determined by comparison to that single standard (data included as supplemental

403

Table 2). The precision was also determined. For most residues the average recoveries for these

404

data were greater than 90% and standard deviations were less than 15%.

405

cloxacillin (CLOX) in salmon samples fortified at the TTL had an average recovery of 91% with

406

a standard deviation of 6%. The limit threshold cutoff value for that compound in salmon

407

calculates to 80%. This means any salmon sample with a signal for CLOX greater than 80% of

408

the signal in a matrix extracted TTL standard could (with 95% confidence) contain CLOX at a

409

concentration at or above the TTL. For some residues, however, the standard deviations were

410

higher and the threshold cutoff values were therefore lower. In order to avoid false negatives

411

and simplify data analysis by treating all test compounds the same, a threshold cutoff value of

412

≥50% TTL seemed reasonable for all analytes to be considered presumptive positive.

For example,

413

In addition to a residue having the correct exact mass precursor ion (5 ppm) and a signal

414

of ≥50% compared to that analyte in a matrix-extracted standard of the same matrix fortified at

415

the TTL, other criteria for a residue to be presumptive positive for the test compounds include

416

retention time matching and the presence of at least one fragment ion with the correct exact mass

417

(within 10 ppm).19 Isotope matching can also be used for comparison, but is not required in the

418

identification criteria. The allowed retention time window was set fairly wide (30 s each side of

419

specified time) to accommodate drift in the method due to column age or slight changes in

420

mobile phase composition. The measured retention times were generally much tighter than the

421

allowed 30 s (usually within 0.1 min). The data were examined closely to determine if a peak

422

was within the established experimental time when compared to matrix-extracted standards

423

analyzed on the same day. Figure 4 shows selected product ions and the precursor isotope



Page 20 of 46

20

424

pattern for ciprofloxacin in catfish (5 µg/kg). The ciprofloxacin data show that the software is

425

able to isolate and evaluate product ions generated by AIF to determine if the criteria for

426

identification are met.

427

standard), the number of false negatives for samples fortified at the TTL and number of false

428

positives (for the test compounds) in matrix blanks could be determined and are shown in Table

429

2. In general, the performance of these test compounds in this screen was very good using the

430

AIF acquisition program with false positives detected for only one compound and less than 2%

431

false negatives for a majority of the compounds in all matrices. A few compounds (amoxicillin,

432

florfenicol amine, avermectins, and lufenuron) had higher rates (5-20%) of false negatives at the

433

TTL level. Sulfacetamide performed poorly in the screening method with low variable recovery

434

and high background and was removed from the list of validated test compounds.

With these criteria (including signal ≥50% compared to the TTL

435

Since the TTLs are somewhat arbitrary (any amount of a non-approved drug identified

436

could be considered violative), the minimum detectable limits using AIF data were also

437

determined by fortifying samples with the test compounds at lower levels. The same criteria,

438

with the exception of the ≥ 50% of signal compared to TTL, were applied to determine if the

439

residues could be detected and identified. In most cases, analytes were still identified in extracts

440

from fish and shellfish that had been fortified at 0.1X the TTL.

441

Because this method is designed to analyze a wide variety of compounds with very

442

different polarities, the performance for some drugs may not compare well to methods that were

443

developed specifically for those analytes. For example, some of the avermectins do not meet all

444

the criteria for presumptive positive with this screening method below a fortification level of 100

445

µg/kg, even though the current testing level for these compounds at FDA is 10 µg/kg.20 There

446

are several reasons for this including the fact that these compounds are much more nonpolar than


Page 21 of 46


21

447

most veterinary drugs, so extraction efficiency and low solubility may reduce recoveries.

448

Penicillins, on the other hand, are most soluble in water; to extract these compounds

449

simultaneously with avermectins proves difficult. The extraction presented here was the best

450

compromise. In addition, although using the generic acetonitrile/0.1% formic acid LC gradient

451

works well for a majority of the veterinary drugs in the >330 compound database, a buffer

452

containing ammonium formate would have facilitated the formation of ammonium adducts for

453

the avermectins (rather than the sodiated ions which are more difficult to dissociate into product

454

ions). The sodiated precursor ions of ivermectin and doramectin were observed in extracts at

455

levels below 200 µg/kg (0.1 X or 20 µg/kg), meaning the method could potentially be used to

456

detect these residues at lower levels. The incidence of false positives that can occur when only

457

using the measured exact mass of the precursor ion would be less for these compounds because

458

their m/z values (m/z 897, 921) are above those of most background contaminants. However, the

459

absence of product ions prevented confirmation as presumptive positive under the described

460

criteria.

461

detected for this compound at the 0.1X level.

Emamectin, in contrast, forms a protonated molecule, and product ions could be

462

This HRMS screening method was also validated for several negative ion compounds. It

463

was possible to detect chloramphenicol in shrimp and salmon using negative ion AIF data

464

acquisition below the established TTL (0.3 µg/kg); florfenicol and thiamphenicol were detected

465

at 0.1X of the 5 µg/kg TTL. Although the precursor ion of toltrazuril sulfone was detected at

466

low levels, it did not form consistent product ions so could not be considered presumptive

467

positive even at the TTL. The more nonpolar negative ion compounds were detected and

468

identified by AIF at low levels from fortified salmon and catfish in the acetonitrile portion

469

(lufenuron, teflubenzuron), or in the final 10% acetonitrile extract (toltrazuril metabolites) or



Page 22 of 46

22

470

both (diflubenzuron, toltrazuril ). All negative ion compounds could be detected using the

471

extraction procedure in fortified shrimp, tilapia, and eel although the recoveries for lufenuron

472

were variable.

473

DDMS2 data

474

Data Dependent MS2 acquisition, where a narrow range of precursor ions are allowed through

475

the quadrupole into the HCD cell and fragmented, generated product ion spectra more specific to

476

the precursor. These spectra can be used to generate product ion ratios and/or search against

477

library spectra. With this method, DDMS2 worked well for a majority of compounds tested.

478

Figure 5 illustrates how isobaric compounds flumequine and oxolinic acid (FLU and OXO) can

479

be identified on the basis of their difference in precursor ion exact mass, retention times, and

480

unique product ion spectra obtained by DDMS2. Some analytes, however, were missed by

481

DDMS2 data acquisition because the threshold signal level needed to trigger the product ion

482

spectra was not reached.

483

recoveries. The number of false negatives based on DDMS2 acquisition is shown in Table 2.

484

Approximately 20 of the positive ion test compounds had a false negative rate of >10% at the

485

TTL. Many of these analytes did produce product ion spectra using DDMS2 in extracts from fish

486

that had been fortified at a slightly higher level (2X TTL).

487

compounds did not generate DDMS2 product ion spectra at the TTL, even though product ions

488

were detected using AIF. Because AIF data gave more reliable results for the presence of

489

confirmatory product ions, DDMS2 spectra were collected to obtain additional qualitative

490

information but were not required for initial screening and identification.

491

Results for Incurred and Regulatory Fish Samples

492

Test Compounds

Generally this occurred for residues with low TTL and/or poor


Similarly, some negative ion

Page 23 of 46


23

493

In addition to fortified samples, incurred and violative regulatory samples were also tested with

494

this screening method. Initially data from these samples were evaluated to look for the test

495

compounds that had been validated. The results for residues found in incurred and violative

496

samples are shown in Table 3 and 4, respectively. As expected, high levels of sulfadiazine

497

(SDZ) were found in tilapia dosed with that compound. An average of 230 µg/kg SDZ was

498

measured in fish dosed at 1 mg/kg body weight (1 day withdrawal), and up to 650 µg/kg SDZ in

499

fish dosed with 5 mg/kg body weight (3 day withdrawal). However, only low levels (< 1 µg/kg)

500

of trimethoprim were detected in tilapia dosed with a combination of trimethoprim and SDZ, and

501

DDMS2 product ion spectra were only triggered for trimethoprim in one of the two dosed fish.

502

Sulfadiazine was also identified in five regulatory tilapia samples that had previously been found

503

to be violative for that residue. The concentrations of SDZ in these fish estimated using a one-

504

point matrix-extracted TTL standard for comparison were similar to the amounts reported

505

previously using LC-MS/MS methodology.4 Sulfamethoxazole and trimethoprim were identified

506

in another sample of tilapia. Sulfamethazine (SMZ) was found in regulatory eel samples; one

507

sample had levels of SMZ > 100 µg/kg, and the other was below the threshold testing level (
260 additional compounds contains information to

545

match precursor ion and, for many analytes, retention time and fragment ions. When data from

546

the incurred and violative regulatory samples were compared to compounds in the larger

547

database, several other analytes were detected and these results are also shown in Tables 3 and 4.

548

In fish extracts containing high levels of sulfonamides, the N4 acetyl metabolites were also

549

detected. These metabolite products have been described8, and were included in the DDMS2

550

inclusion list so that unique product ion spectra could be obtained.

551

Another additional compound that was found in many of these samples was ethoxyquin

552

dimer, a known by-product of ethoxyquin in fish.32 When these samples were first analyzed, a

553

reference standard for ethoxyquin dimer was not available for comparison, and the compound

554

was detected by matching the exact m/z of the precursor.

555

purchased and it was determined that the retention time and product ions also matched that

556

compound. The metabolite desethylene-enrofloxacin (des-ENRO) that had been found earlier in

557

milk samples from cows dosed with ENRO33 was also found in the catfish dosed with this drug.

558

Thiabendazole was also identified in one regulatory eel sample when the data were compared to

559

the larger veterinary drug database, although the estimated levels were quite low (< 1 µg/kg

560

when compared to a solvent standard). One regulatory eel sample was also analyzed by AIF

561

using negative ion data acquisition, but no compounds were detected.


Subsequently a standard was


Page 26 of 46

26

562

It is worth noting that the rate of false detections increased when the data were compared

563

to more potential analytes in a larger compound database. Searching by exact mass of precursor

564

ion only can lead to a significant number of false hits (40-50) even with the narrower mass

565

window of 3 ppm. Adding criteria for retention time and product ion match greatly reduced the

566

number of potential positives to a reasonable number (< 5). Some compounds were often

567

detected in many samples (including matrix controls) at low abundances (~104 counts) with the

568

correct retention time and fragment ions using the screening data analysis program with AIF

569

data, but DDMS2 spectra could not be obtained. These include small mass compounds with

570

common fragment ions (e.g., lidocaine, benzocaine) and hormones (hydrocortisone,

571

prednisolone, etc.).

572

These results from the analysis of incurred and violative regulatory aquaculture samples

573

demonstrate the ability of the HRMS screening method to confirm the findings of more

574

traditional LC-MS/MS methods for a wide range of veterinary drug residues. In addition, the

575

capability to detect metabolites such as N4 acetyl-sulfonamides, des-ENRO, and ethoxyquin

576

dimer provides verification that the veterinary drugs were administered to the fish and are not an

577

artifact of post-production processing or analysis. The identification of other unexpected drug

578

residues in these samples, even at low levels, also demonstrates the potential for expanding the

579

scope of monitoring for chemical contaminants in aquacultured fish and shellfish using HRMS

580

screening methods.

581

ACKNOWLEDGEMENTS

582

The authors would like to thank Charles Gieseker of the FDA Center for Veterinary Medicine

583

Office of Research for providing the incurred fish tissues.

584


Page 27 of 46


27

SUPPORTING INFORMATION

585 586

The supporting information includes two additional tables of information. The first supporting

587

information table describes the number and type of samples analyzed for method validation. The

588

second supporting table consists of the limit test threshold cutoff values for each residue in the

589

different seafood matrices using the average relative recovery and standard deviation data from

590

replicate extracts fortified at the target testing level. REFERENCES

591 592 593

1. Boison, J. O.; Turnipseed, S. B., A review of aquaculture practices and their impacts on chemical food safety from a regulatory perspective. J. AOAC Int. 2015, 98, 541-549.

594

2.

595 596 597

3. Li, H.; Kijak, P. J.; Turnipseed, S. B.; Cui, W., Analysis of veterinary drug residues in shrimp: a multi-class method by liquid chromatography-quadrupole ion trap mass spectrometry. J. Chromatogr. B 2006, 836, 22-38.

598 599 600 601

4. Storey, J. M.; Clark, S. B.; Johnson, A. S.; Andersen, W. C.; Turnipseed, S. B.; Lohne, J. J.; Burger, R. J.; Ayres, P. R.; Carr, J.; Madson, M. R., Analysis of sulfonamides, trimethoprim, fluoroquinolones, quinolones, triphenylmethane dyes and methyltestosterone in fish and shrimp using liquid chromatography mass spectrometry. J. Chromatogr. B 2014, 972, 38-47.

602 603 604

5. Dasenaki, M. E.; Thomaidis, N. S., Multi-residue determination of 115 veterinary drugs and pharmaceutical residues in milk powder, butter, fish tissue and eggs using liquid chromatography–tandem mass spectrometry. Anal. Chim. Acta 2015, 880, 103-121.

605 606 607

6. Turnipseed, S. B.; Lohne, J. J.; Boison, J. O., Review: Application of high resolution mass spectrometry to monitor veterinary drug residues in aquacultured products. J. AOAC Int. 2015, 98, 550-558.

608 609 610 611 612

7. Verdon, E.; Hurtaud-Pessel, D.; Thota, J. R., A role for high-resolution mass spectrometry in the high-throughput analysis and identification of veterinary medicinal product residues and of their metabolites in foods of animal origin. In High-Throughput Analysis for Food Safety, Wang, P. G.; Vitha, M. F.; Kay, J. F., Eds. John Wiley & Sons, Inc: Hoboken, NJ, 2014.

613 614 615

8. Turnipseed, S. B.; Clark, S. B.; Storey, J. M.; Carr, J. R., Analysis of veterinary drug residues in frog legs and other aquacultured species using liquid chromatography quadrupole time-of-flight mass spectrometry. J. Agric. Food Chem. 2012, 60, 4430-4439.

616 617

9. Dasenaki, M. E.; Bletsoue, A. A.; Koulis, G. A.; Thomaidis, N. S., Qualitative multiresidue screening method for 143 veterinary drugs and pharmaceuticals in milk and fish

World Bank Report, Fish to 2030: Prospects for Fisheries and Aquaculture. 2013.



28

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tissue using liquid chromatography quadrupole-time-of-flight mass spectrometry. J. Agric. Food Chem. 2015, 63, 4493-4508.

620 621 622

10. Boix, C.; Ibanez, M.; Sancho, J. V.; Leon, N.; Yusa, V.; Hernandez, F., Qualitative screening of 116 veterinary drugs in feed by liquid chromatography–high resolution mass spectrometry: Potential application to quantitative analysis. Food Chem. 2014, 160, 313-320.

623 624 625 626

11. Turnipseed, S. B.; Lohne, J. J.; Storey, J. M.; Andersen, W. C.; Young, S. L.; Carr, J.; Madson, M. R., Challenges in implementing a screening method for veterinary drugs in milk using liquid chromatography quadrupole time-of-flight mass spectrometery. J. Agric. Food Chem. 2014, 62, 3660-3674.

627 628 629 630

12. Gomez Perez, M. L.; Romero-Gonzalez, R.; Plaza-Bolanos, P.; Genin, E.; Vidal, J. L.; Frenich, A. G., Wide-scope analysis of pesticide and veterinary drug residues in meat matrices by high resolution MS:detection and identification using Exactive-Orbitrap. J. Mass Spectrom. 2014, 49, 27-36.

631 632 633

13. Wang, X.; Liu, Y.; Su, Y.; Yang, J.; Wang, Z.; He, L., High-throughput screening and confirmation of 22 banned veterinary drugs in feedstuffs using LC-MS/MS and high-resolution orbitrap mass spectrometry. J. Agric. Food Chem. 2014, 62, 516-527.

634 635 636 637

14. 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, 9175-9187.

638 639

15. Samanidou, V.; Bitas, D.; Charitonos, S.; Papadoyannis, I., On the extraction of antibiotics from shrimps prior to chromatographic analysis. Chromatogr. 2016, 3, 8.

640 641

16. Zhao, L.; Lucas, D., Multi-residue analysis of veterinary drugs in bovine liver by LCMS/MS. Agilent Application Note 2015.

642 643

17. Young, M.; Tran, K., Oasis PRiME HLB cartridge for effective cleanup of meat extracts prior to multi-residue veterinary drug UPLC-MS analysis. Waters Application Note 2015.

644 645

18. FDA, Guidelines for the Validation of Chemical Methods for the FDA Foods and Veterinary Medicine Program, 2nd Edition. 2015.

646 647

19. FDA, Acceptance criteria for confirmation of identity of chemical residues using exact mass data for the FDA Foods and Veterinary Medicine Program. 2015.

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20.

649 650 651

21. Robert, C.; Gillard, N.; Brasseur, P.-Y.; Pierret, G.; Ralet, N.; Dubois, M.; Delahaut, P., Rapid multi-residue and multi-class qualitative screening for veterinary drugs in foods of animal origin by UHPLC-MS/MS. Food Addit. Contam. A 2013, 30, 443-457.

652 653 654

22. Smith, S.; Gieseker, C.; Reimschuessel, R.; Decker, C.-S.; Carson, M. C., Simultaneous screening and confirmation of multiple classes of drug residues in fish by liquid chromatography-ion trap mass spectrometry. J. Chromatogr. A 2009, 1216, 8224-8232.

FDA, Chemotherapeutics in Seafood Compliance Program 7304.018. 2016.


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655 656 657 658

23. 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.

659 660 661

24. Schneider, M. J.; Lehotay, S. J.; Lightfield, A. R., Validation of a streamlined multiclass, multiresidue method for determination of veterinary drug residues in bovine muscle by liquid chromatography–tandem mass spectrometry. Anal. Bioanal. Chem. 2015, 407, 4423-4435.

662 663 664

25. Hernando, M. D.; Mezcua, M.; Suárez-Barcena, J. M.; Fernández-Alba, A. R., Liquid chromatography with time-of-flight mass spectrometry for simultaneous determination of chemotherapeutant residues in salmon. Anal. Chim. Acta 2006, 562, 176-184.

665 666 667

26. Villar-Pulido, M.; Gilbert-López, B.; García-Reyes, J. F.; Martos, N. R.; Molina-Díaz, A., Multiclass detection and quantitation of antibiotics and veterinary drugs in shrimps by fast liquid chromatography time-of-flight mass spectrometry. Talanta 2011, 85, 1419-1427.

668 669 670

27. Mastovska, K.; Lightfield, A. R., Streamlining methodology for the multiresidue analysis of beta-lactam antibiotics in bovine kidney using liquid chromatography-tandem mass spectrometry. J. Chromatogr. A 2008, 1202, 118-123.

671 672 673 674

28. Geis-Asteggiante, L.; Nuñez, A.; Lehotay, S. J.; Lightfield, A. R., Structural characterization of product ions by electrospray ionization and quadrupole time-of-flight mass spectrometry to support regulatory analysis of veterinary drug residues in foods. Rapid Commun. Mass Spectrom. 2014, 28, 1061-1081.

675 676 677 678

29. Roybal, J. E.; Walker, C. C.; Pfenning, A. P.; Turnipseed, S. B.; Storey, J. M.; Gonzales, S. A.; Hurlbut, J. A., Concurrent determination of four flouroquinolones in catfish, shrimp, and salmon by liquid chromatography with fluorescence detection. J. AOAC Int. 2002, 85, 12931301.

679 680 681 682

30. Andersen, W. C.; Casey, C. R.; Schneider, M. J.; Turnipseed, S. B., Expansion of scope of AOAC First Action Method 2012.25; Single laboratory validation of triphenylmethane dye and leuco metabolite analysis in shrimp, tilapia, catfish and salmon by LC-MS/MS. J. AOAC Int. 2015, 98, 636-648.

683

31.

684 685 686

32. He, P.; Ackman, R. G., Residues of ethoxyquin and ethoxyquin dimer in ocean-farmed salmonids determined by high-pressure liquid chromatography. J. Food Sci. 2000, 65, 13121314.

687 688 689

33. Turnipseed, S. B.; Storey, J. M.; Clark, S. B.; Miller, K., Analysis of veterinary drugs and metabolites in milk using quadrupole- time of flight liquid chromatography mass spectrometry. J. Agric. Food Chem. 2011, 59, 7569-7581.

FDA, Code of Federal Regulations. Title 21 2015, 573.380 Ethoxyquin in animal feeds.

690 691



30

692

FIGURE CAPTIONS

693

Figure 1. Comparison of selected analyte recoveries in tilapia at 1X TTL with different levels of

694

acid modifiers (normalized to 0.2% p-TSA and 2% acetic acid (AA) recoveries).

695

Figure 2. Recoveries for selected analytes in tilapia fortified at the target testing level (1X) as

696

compared to a 1X solvent standard.

697

Figure 3. Extracted ion chromatograms (5 ppm window) from MS1 AIF data for representative

698

test compounds in tilapia fortified at target testing level

699

Figure 4. AIF product ions (A) and precursor isotope pattern (B) for CIP (5 µg/kg) in catfish

700

extract compared to theoretical values.

701

Figure 5. DDMS2 data for OXO and FLU in shrimp at target testing level (10 µg/kg). (A)

702

Extracted ion chromatograms for MH+ (B) Chromatograms for MS2 of m/z 262 (C) Product ion

703

spectra

704

Figure 6. AIF data for regulatory eel sample #1. (A) Test compounds that were presumptive

705

positive (signal ≥50% target testing level). (B) Test compounds identified, but at concentrations

706

< 50% target testing level. (C) Other compounds identified when compared to larger veterinary

707

drug database.

708

Figure 7. DDMS2 product ion spectra for residues in regulatory eel sample #2. (A) lincomycin

709

(B) ethoxyquin dimer.

710


Page 30 of 46

Page 31 of 46


31

Table 1. Test Compounds Analyte Doramectin (DOR) Emamectin B1a (EMA)

Class Avermectin Avermectin

TTL (µg/kg)

RT (min)

Formula

MH+

Fragment Ions

200

a

11.3

C50H74O14

921.4971

200

a

9.6

C49H75NO13

886.5311

a

Ivermectin B1a (IVER)

Avermectin

200

Amoxicillin (AMOX)

β-lactam

Ampicillin (AMP)

b

b

449.2298

777.4126

82.0651

158.1176

609.3398

753.4184

302.1962

12.0

C48H74O14

897.4971

100

1.9

C16H19N3O5S

366.1118

114.0372

208.0427

349.0853

β-lactam

25

4.2

C16H19N3O4S

350.1169

106.0651

114.0372

160.0427

Aspoxicillin (ASP)

β-lactam

25

2.6

C21H27N5O7S

494.1074

160.0427

250.1186

366.1118

Cloxacillin (CLOX)

β-lactam

25

9.0

C19H18ClN3O5S

436.0729

160.0427

277.0375

Dicloxacillin (DICLOX)

β-lactam

25

9.6

C19H17Cl2N3O5S

470.0339

160.0427

310.9985

Oxacillin (OXAC)

β-lactam

25

8.5

C19H19N3O5S

402.1118

114.0372

160.0427

243.0764

Penicillin G (PEN G)

β-lactam

25

7.5

C16H18N2O4S

335.1060

114.0372

160.0427

176.0706

NA

4.9

C16H18N2O4S

335.1060

128.0528

160.0427

289.0997 234.0696

c

Penillic acid

β-lactam

Albendazole (ALB)

Benzimidazole

50

7.0

C12H15N3O2S

266.0958

159.0427

191.0148

Albendazole sulfoxide (ALB SULF)

Benzimidazole

50

5.0

C12H15N3O3S

282.0907

208.0175

240.0437

Fenbendazole (FEN)

Benzimidazole

50

8.4

C15H13N3O2S

300.0801

159.0427

268.0539

Fenbendazole sulfone (FEN SULF)

Benzimidazole

50

7.3

C15H13N3O4S

332.0700

300.0437

Cephapirin (CEPH)

Cephalosporin

25

3.4

C17H17N3O6S2

424.0632

152.0165

292.0573

Brilliant Green (BG)

Dye

1

9.5

C27H33N2

385.2638 d

297.1386

341.2012

d

251.1543

356.2121

Crystal violet (CV)

Dye

1

9.0

C25H30N3

372.2434

Leucocrystal violet (LCV)

Dye

1

5.6

C25H31N3

374.2591

239.1543

253.1699

358.2278

Leucomalachite green (LMG)

Dye

1

8.2

C23H26N2

331.2169

194.0964

239.1543

315.1856

208.1121

313.1699

d

Malachite green (MG)

Dye

1

8.1

C23H25N2

329.2012

Ciprofloxacin (CIP)

Fluoroquinolone

5

4.6

C17H18FN3O3

332.1405

245.1085

288.1507

Danofloxacin (DANO)

Fluoroquinolone

5

5.0

C19H20FN3O3

358.1562

283.1241

314.1663

Difloxacin (DIFLOX)

Fluoroquinolone

5

5.4

C21H19F2N3O3

400.1467

299.0990

356.1569

Enrofloxacin (ENRO)

Fluoroquinolone

5

5.1

C19H22FN3O3

360.1718

245.1085

316.1820

338.1499 342.1612



Page 32 of 46

32

Analyte

Class

Norfloxacin (NOR)

Fluoroquinolone

TTL (µg/kg)

RT (min)

5

4.7

C16H18FN3O3

320.1405

276.1507

302.1299

Formula

MH+

Fragment Ions

Sarafloxacin (SAR)

Fluoroquinolone

5

5.4

C20H17F2N3O3

386.1311

299.0990

342.1413

Methyl Testosterone (M TET)

Hormone

0.8

9.4

C20H30O2

303.2319

97.0648

109.1011

Lincomycin (LIN)

Lincomycin

50

3.8

C18H34N2O6S

407.2210

126.1277

359.2214

Azithromycin (AZI)

Macrolide

50

5.4

C38H72N2O12

749.5158

158.1176

591.4210

Erythromycin A (ERY)

Macrolide

50

6.6

C37H67NO13

734.4685

83.0491

158.1176

c

Erythromycin dehydrated

Macrolide

NA

7.2

C37H65NO12

716.4580

158.1176

Spiramycin (SPIRO)

Macrolide

50

5.5

C43H74N2O14

843.5213

174.1125

540.3136

174.1125

522.3789

e

Tilmicosin (TIL)

Macrolide

50

6.0

C46H80N2O13

435.2903

Tylosin A (TYL)

Macrolide

50

7.0

C46H77NO17

916.5264

174.1125

Ketoconazole (KETO)

Nitromidazole

10

7.2

C26H28Cl2N4O4

531.1560

82.0525

489.1455

Metronidazole (MNZ)

Nitromidazole

10

2.0

C6H9N3O3

172.0717

82.0525

128.0455

1.33

C10H14FNO3S

248.0751

104.0632

130.0651

4.6

C14H18N4O2

275.1503

123.0665

259.1190

f

Florfenicol Amine (FFA)

Phenicol

50

Ormetoprim (ORM)

Potentiator

10

576.3742

695.460

230.0646

Trimethoprim (TRIMETH)

Potentiator

10

4.3

C14H18N4O3

291.1452

123.0665

230.1162

Ethoxyquin (ETHOX)

Preservative

50

7.7

C14H19NO

218.1539

148.0757

176.1070

Flumequine (FLU)

Quinolone

10

7.82

C14H12FNO3

262.0874

202.0299

244.0768

Nalidixic Acid (NAL)

Quinolone

10

7.6

C12H12N2O3

233.0921

187.0502

215.0815

Oxolinic Acid (OXO)

Quinolone

10

6.5

C13H11NO5

262.0710

216.0291

244.0604

Sulfacetamide (SAA)

Sulfonamide

10

2.2

C8H10N2O3S

215.0485

92.0495

108.0444

156.0114

Sulfachloropyridazine (SCP)

Sulfonamide

10

5.8

C10H9ClN4O2S

285.0208

92.0495

108.0444

156.0114

Sulfaclozine (SULC)

Sulfonamide

10

6.9

C10H9ClN4O2S

285.0208

92.0495

108.0444

156.0114

Sulfadiazine (SDZ)

Sulfonamide

10

2.9

C10H10N4O2S

251.0597

92.0495

108.0444

156.0114

Sulfadimethoxine (SDM)

Sulfonamide

10

7.0

C12H14N4O4S

311.0809

108.0444

156.0114

156.0768

Sulfadoxine (SDX)

Sulfonamide

10

6.1

C12H14N4O4S

311.0809

92.0495

108.0444

156.0114

Sulfaethoxypyridazine (SEP)

Sulfonamide

10

6.2

C12H14N4O3S

295.0859

92.0495

108.0444

156.0114

Sulfamerazine (SMR)

Sulfonamide

10

4.1

C11H12N4O2S

265.0754

92.0495

108.0444

156.0114


Page 33 of 46


33

TTL (µg/kg)

RT (min)

Sulfonamide

10

4.8

C12H14N4O2S

279.0910

Sulfamethoxazole (SMX)

Sulfonamide

10

6.1

C10H11N3O3S

254.0594

92.0495

108.0444

156.0114

Sulfamethoxypyridazine (SMP)

Sulfonamide

10

5.1

C11H12N4O3S

281.0703

108.0444

126.0662

156.0114

Sulfamonomethoxine (SULFMON)

Sulfonamide

10

5.6

C11H12N4O3S

281.0703

92.0495

108.0444

156.0114

Sulfapyridine (SPD)

Sulfonamide

10

4.0

C11H11N3O2S

250.0645

108.0444

156.0114

184.0869

Sulfaquinoxaline (SQX)

Sulfonamide

10

7.1

C14H12N4O2S

301.0754

92.0495

108.0444

156.0114

Sulfathiazole (STZ)

Sulfonamide

10

108.0444

156.0114 428.1340

Analyte

Class

Sulfamethazine (SMZ)

Chlortetracycline (CTC) Doxycycline (DC) Oxytetracycline (OTC)

Tetracycline Tetracycline Tetracycline

Tetracycline (TC)

Tetracycline

Negative Ion Analytes

Class

Chloramphenicol(CAP)

Formula

MH+

Fragment Ions 92.0495

108.0444

3.9

C9H9N3O2S2

256.0209

92.0495

100

g

5.6

C22H23ClN2O8

479.1216

444.0845

100

g

5.9

C22H24N2O8

445.1605

154.0499

410.1234

100

g

4.7

C22H24N2O9

461.1555

154.0499

426.1183

g

4.8

C22H24N2O8

445.1605

154.0499

410.1234

100 TTL (µg/kg)

RT (min)

Phenicol

0.3

Florfenicol (FF)

Phenicol

Thiamphenicol (THIAM)

MH-

6.5

Formula C11H12Cl2N2O5

321.00505

152.0353

176.0353

5

6.0

C12H14Cl2FNO4S

355.99319

185.0278

335.9870

Phenicol

5

4.6

C12H15Cl2NO5S

353.99752

185.0278

290.0259

Toltrazuril (TOLT)

Toltrazuril

50

10

C18H14F3N3O4S

424.05843

316.98132

404.97665

Toltrazuril Sulfone (TOLT SULF)

Toltrazuril

50

9.9

C18H14F3N3O6S

456.04826

Toltrazuril Sulfoxide (TOLT SULFX)

Toltrazuril

50

9.2

C18H14F3N3O5S

440.05335

371.05781

Diflubenzuron (DIFLU)

Benzylurea

50

10

C14H9ClN2O2F2

309.02478

242.98601

289.0184

Lufenuron (LUF)

Benzylurea

50

10.4

C17H8Cl2F8N2O3

508.97115

174.95972

325.9591

Teflubenzuron (TEFLU)

Benzylurea

50

10.3

C14H6Cl2F4N2O2

378.96697

195.95378

338.95451

a

Current FDA program recommends TTL of 10 µg/kg20 b MNa+ c NA= Not applicable (degradant) d M+ e MH22+ f FDA tolerance is 1 mg/kg for FFA as marker residue in aquaculture20 g FDA tolerance is 2 mg/kg for sum of OTC, CTC, and TC in finfish and lobster 2020


156.0114

Fragment Ions 257.0335

None

488.96492


Page 34 of 46

34

Table 2. Screening validation results

Analyte Doramectin Emamectin B1a Ivermectin B1a Amoxicillin Ampicillin Aspoxicillin Cloxacillin Dicloxacillin Oxacillin Penillic acid Albendazole Albendazole sulfoxide Fenbendazole Fenbendazole sulfone Cephapirin Brilliant Green Crystal violet Leucocrystal violet Leucomalachite green Malachite green Ciprofloxacin Danofloxacin

Class Avermectin

β-lactam

Benzimidazole

Cephalosporin Dye

Fluoroquinolone

TTL (µg/kg) 200 a 200 a 200 a 100 25 25 25 25 25 25 b 50 50 50 50 25 1 1 1 1 1 5 5

Lowest level confirmed by AIF (X) 0.5 0.1 0.5 1 0.1 1 0.1 0.5 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.5 0.5 0.5 0.1 0.5 0.5 0.5

Minimum Detectable Concentration (µg/kg) 100 20 100 100 2.5 25 2.5 12.5 2.5 2.5 5 5 5 5 2.5 0.5 0.5 0.5 0.1 0.5 2.5 2.5


% False Neg. at 1X (AIF) N= 77 13 1 5 6 1 0 0 0 0 0 0 0 0 0 0 1 0 3 0 0 0 0

% False Neg. at 1X (DDMS2) N= 77 19 0 57 97 13 32 2 5 31 99 0 0 0 0 0 84 14 73 42 2 10 90

% False Pos. in blanks (AIF) N= 47 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Page 35 of 46


35

Analyte Difloxacin Enrofloxacin Norfloxacin Sarafloxacin Methyl testosterone Lincomycin Azithromycin Erythromycin dehyr Spiramycin Tilmicosin Tylosin A Ketoconazole Metronidazole Florfenicol Amine Ormetoprim Trimethoprim Ethoxyquin Flumequine Nalidixic Acid Oxolinic Acid Sulfacetamide Sulfachloropyridazine Sulfaclozine Sulfadiazine Sulfadimethoxine Sulfadoxine

Class

Hormone Lincomycin Macrolide

Nitromidazole Phenicol Potentiator Preservative Quinolone

Sulfonamide

TTL (µg/kg) 5 5 5 5 0.8 50 50 b 50 50 50 50 10 10 50c 10 10 50 10 10 10 10 10 10 10 10 10

Lowest level confirmed by AIF (X) 0.1 0.1 0.5 0.1 0.5 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 1 0.1 0.1 0.1 0.1 0.1

Minimum Detectable Concentration (µg/kg) 0.5 0.5 2.5 0.5 0.4 1 5 5 2.5 5 5 1 1 5 1 1 5 1 1 1 10 1 1 1 1 1


% False Neg. at 1X (AIF) N= 77 0 0 1 0 0 0 1 0 0 0 0 0 0 9 0 0 10 0 0 0 21 0 0 1 0 0

% False Neg. at 1X (DDMS2) N= 77 0 0 0 0 2 0 12 0 1 0 0 0 13 51 0 0 10 0 0 0 100 8 0 31 0 0

% False Pos. in blanks (AIF) N=47 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0


Page 36 of 46

36

Lowest level confirmed by AIF (X) 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.5 0.1 0.1 0.1 0.1 0.5 0.1 0.1 0.1 > 2e 0.5 0.5 0.5 0.5

Minimum Detectable Concentration (µg/kg) 1 1 1 1 1 1 1 1 5 10 10 10 10 0.15 0.5 0.5 0.5 > 100 25 10 10 10

% False Neg. at 1X (AIF) N= 77 0 1 0 0 0 0 0 0 6 0 0 0 0 0f 0f 0f 0f 100 f 0f 0f 8f 0f

% False Neg. at 1X (DDMS2) N= 77 0 17 14 0 8 0 4 1 16 0 0 0 2 94 f 0f 34 f 77 f 100 f 8f 69 f 34 f 11 f

% False Pos. in blanks (AIF) N=47 0 0 0 0 0 0 0 0 0 0 0 0 0 0f 0f 0f 0f 0f 0f 0f 0f 0f

TTL Analyte Class (µg/kg) Sulfaethoxypyridazine 10 Sulfamerazine 10 Sulfamethazine 10 Sulfamethoxazole 10 Sulfamethoxypyridazine 10 Sulfamonomethoxine 10 Sulfapyridine 10 Sulfaquinoxaline 10 Sulfathiazole 10 Tetracycline Chlortetracycline 100 d Doxycycline 100 d Oxytetracycline 100 d Tetracycline 100 d Chloramphenicol Phenicol 0.3 Florfenicol 5 Thiamphenicol 5 Toltrazuril Toltrazuril 50 Toltrazuril Sulfone 50 Toltrazuril Sulfoxide 50 Benzylurea Diflubenzuron 50 Lufenuron 50 Teflubenzuron 50 a Current FDA program recommends TTL of 10 µg/kg20 b Marker compounds were degradants; amounts were compared to matrix-extracted standard fortified with parent compound at TTL. c FDA tolerance is 1 mg/kg for florfenicol amine as marker residue in aquaculture20 d FDA tolerance is 2 mg/kg for sum of oxytetracycline, chlortetracycline, and tetracycline in finfish and lobster 20 e f No fragments were observed for toltrazuril sulfone For negative ion analytes: N= 35 fortified at 1X and N = 15 blanks


Page 37 of 46


37

Table 3. Screening results for incurred fish samples Incurred sample

Dosing Drug (X) mg/kg body weight SDZ (1)

Depuration Time

N=

Found by QqQ (µg/kg)30

1 day

2

Not analyzed

Test Compounds Presumptive Positive AIF (µg/kg)a SDZ (220)

SDZ (1)

1 day

2

Not analyzed

SDZ (240)

SDZ (5) TRIMETH (1) SDZ (5) TRIMETH (1)

3 days

2

Not analyzed

SDZ (650 )

4 days

2

Not analyzed

SDZ (280)

Catfish Inc#1

ENRO (5 )

6 days

4

Not analyzed

ENRO (620) CIP (30)

Des-ENRO

Catfish Inc#2 CatfishInc#3

ENRO (5 )

6 days

4

Not analyzed

MG (2) c CV (2) BG (2)

1 hr

1

MG (2) c CV (2) BG (2)

1 hr

1

LCV (4.3) MG (3.1) LMG (2.7) BG (1.2) BG (1.8) MG (1.8) LMG (0.8) LCV (0.4)

ENRO (601) CIP (41) LCV (2.7) LMG (0.8)

None

Tilapia Inc#1 Tilapia Inc#2 Tilapia Inc#3 Tilapia Inc#4

SalmonInc#4

Additional compounds found by AIF

Spectra obtained by DDMS2

Comments

N4 acetyl- SDZ ETHOX dimer b N4 acetyl- SDZ ETHOX dimer b N4 acetyl- SDZ ETHOX dimer b N4 acetyl- SDZ

SDZ N4 acetyl- SDZ SDZ N4 acetyl- SDZ SDZ N4 acetyl- SDZ SDZ TRIMETH N4 acetyl- SDZ ENRO, CIP ETHOX

ETHOX found by AIF at < 50% TTL

Des-ENRO

ENRO, CIP ETHOX LCV ETHOX

ETHOX found by AIF at < 50% TTL BG, CV, MG , and ETHOX found by AIF at < 50% TTL

ETHOX dimer c

none

BG and MGs found by AIF at < 50% TTL

TRIMETH found by AIF at < 50% TTL TRIMETH found by AIF at < 50% TTL ETHOX found by AIF at < 50% TTL

a

Average amount calculated as compared to one-point matrix-extracted standard with same matrix at 1X target testing level

b

Ethoxyquin dimer standard was obtained and compound was added to DDMS2 inclusion list after these data were collected

c

Fish were exposed to bath containing 2 µg/L MG, CV, and BG for 1 hr followed by 1 hr in clean water tank



Page 38 of 46

38

Table 4. Screening results for violative regulatory fish samples Regulatory Sample

N=

Found by QqQ (µg/kg) 4

Tilapia Reg#1 Tilapia Reg#2 Tilapia Reg#3 Tilapia Reg#4 Tilapia Reg#5 Tilapia Reg#6

2

SDZ (76)

2

SDZ (77)

Test compounds Presumptive Positive AIF (µg/kg) a ETHOX (105) SDZ (69) SDZ (52)

2

SDZ (9)

SDZ (6)

2

SDZ (4)

SDZ (3)

2

SDZ (5)

SDZ (3)

2

SMX (20) TRIMETH (6)

SMX (15) TRIMETH (6)

N4 acetyl-SMX ETHOX dimer

Catfish Reg#1 Catfish Reg#2 Eel Reg#1

2

LCV (1.1) ENRO (

Wide-Scope Screening Method for Multiclass Veterinary Drug

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