Multiclass Multiresidue Veterinary Drug Analysis in Beef Using Agilent Captiva EMR—Lipid Cartridge Cleanup and LC/MS/MS
Applications | 2017 | Agilent TechnologiesInstrumentation
Analysis of veterinary drug residues in beef is essential for food safety, regulatory compliance, and public health. Complex matrices like muscle tissue require effective sample preparation to achieve reliable quantitation of a wide range of drug classes.
This study assesses a streamlined workflow combining two-step extraction and Agilent Captiva EMR–Lipid cartridge cleanup for the determination of 39 multiclass veterinary drugs in beef. Key goals include evaluating matrix cleanup efficiency, analyte recovery, reproducibility, and comparison to alternative pass-through cleanup cartridges.
The optimized sample preparation entails:
Chromatographic separation was achieved on a C18 UHPLC column with gradient elution, coupled to a triple quadrupole MS with JetStream electrospray ionization for sensitive MRM detection.
• Gravimetric tests showed 48 % reduction of co-extractive residue with EMR–Lipid cleanup versus 18–23 % for other cartridges.
• Post-column infusion experiments demonstrated markedly reduced matrix suppression after EMR–Lipid cleanup.
• Cartridge recovery studies revealed consistent >60 % recoveries for hydrophobic analytes using EMR–Lipid sorbent, whereas alternative hydrophobic sorbents caused significant losses (often <10 %).
• Method validation yielded linear calibration (R² > 0.98), recoveries within 60–120 % for 94 % of analytes, and RSD < 10 % for most compounds across low, mid, and high levels.
Emerging directions include integration of EMR sorbents into automated platforms, extension to other complex matrices (dairy, eggs, aquaculture), development of sorbents targeting additional interferences (e.g., phospholipids), and coupling with high-resolution MS for non-target screening.
The two-step extraction combined with Agilent Captiva EMR–Lipid cartridge cleanup delivers superior matrix removal, high recovery, and robust quantitation of multiclass veterinary drugs in beef, meeting stringent regulatory and analytical quality requirements.
1. FDA/USDA. A Description of the U.S. Food Safety System. 2000.
2. EC Decision 2002/657, Official Journal L122. 2002.
3. Mastovska K., Lightfield A.R. J. Chromatogr. A 2008, 1202, 118–123.
4. Geis-Asteggiante L. et al. J. Chromatogr. A 2012, 1258, 43–54.
5. Schneider M.J., Lehotay S.J., Lightfield A.R. Anal. Bioanal. Chem. 2015, 407, 4423–4435.
6. Han L. et al. J. Chromatogr. A 2016, 1449, 17–29.
7. López-Blanco R. et al. J. Chromatogr. A 2016, 1456, 89–104.
Sample Preparation, Consumables, LC/MS, LC/MS/MS, LC/QQQ
IndustriesFood & Agriculture
ManufacturerAgilent Technologies
Summary
Importance of Topic
Analysis of veterinary drug residues in beef is essential for food safety, regulatory compliance, and public health. Complex matrices like muscle tissue require effective sample preparation to achieve reliable quantitation of a wide range of drug classes.
Study Objectives and Overview
This study assesses a streamlined workflow combining two-step extraction and Agilent Captiva EMR–Lipid cartridge cleanup for the determination of 39 multiclass veterinary drugs in beef. Key goals include evaluating matrix cleanup efficiency, analyte recovery, reproducibility, and comparison to alternative pass-through cleanup cartridges.
Methodology and Instrumentation
The optimized sample preparation entails:
- Aqueous extraction with 0.1 M EDTA to stabilize polar and chelating drugs.
- Organic extraction using acetonitrile fortified with 2 % formic acid and 2 % DMSO to improve recovery of hydrophobic compounds.
- Combination of extracts and gravity-driven cleanup on Captiva EMR–Lipid cartridges, followed by a secondary elution with 80:20 ACN/water.
Chromatographic separation was achieved on a C18 UHPLC column with gradient elution, coupled to a triple quadrupole MS with JetStream electrospray ionization for sensitive MRM detection.
Instrumentation Used
- Agilent 1290 Infinity UHPLC system (binary pump, autosampler, column compartment)
- Agilent G6490 Triple Quadrupole LC/MS with JetStream ESI
- Agilent InfinityLab Poroshell 120 EC-C18 column (150 × 2.1 mm, 2.7 µm)
- Sample prep: Geno/Grinder, refrigerated centrifuge, vortex/shaker, Vac Elut manifold, Captiva EMR–Lipid cartridges
Key Results and Discussion
• Gravimetric tests showed 48 % reduction of co-extractive residue with EMR–Lipid cleanup versus 18–23 % for other cartridges.
• Post-column infusion experiments demonstrated markedly reduced matrix suppression after EMR–Lipid cleanup.
• Cartridge recovery studies revealed consistent >60 % recoveries for hydrophobic analytes using EMR–Lipid sorbent, whereas alternative hydrophobic sorbents caused significant losses (often <10 %).
• Method validation yielded linear calibration (R² > 0.98), recoveries within 60–120 % for 94 % of analytes, and RSD < 10 % for most compounds across low, mid, and high levels.
Benefits and Practical Applications
- Hands-free, gravity-driven cleanup without vacuum or pressure control
- Highly selective lipid removal preserving analyte recovery, even for very hydrophobic drugs
- Minimal method development due to pass-through SPE format
- Improved laboratory throughput and instrument robustness for food safety testing
Future Trends and Opportunities
Emerging directions include integration of EMR sorbents into automated platforms, extension to other complex matrices (dairy, eggs, aquaculture), development of sorbents targeting additional interferences (e.g., phospholipids), and coupling with high-resolution MS for non-target screening.
Conclusion
The two-step extraction combined with Agilent Captiva EMR–Lipid cartridge cleanup delivers superior matrix removal, high recovery, and robust quantitation of multiclass veterinary drugs in beef, meeting stringent regulatory and analytical quality requirements.
References
1. FDA/USDA. A Description of the U.S. Food Safety System. 2000.
2. EC Decision 2002/657, Official Journal L122. 2002.
3. Mastovska K., Lightfield A.R. J. Chromatogr. A 2008, 1202, 118–123.
4. Geis-Asteggiante L. et al. J. Chromatogr. A 2012, 1258, 43–54.
5. Schneider M.J., Lehotay S.J., Lightfield A.R. Anal. Bioanal. Chem. 2015, 407, 4423–4435.
6. Han L. et al. J. Chromatogr. A 2016, 1449, 17–29.
7. López-Blanco R. et al. J. Chromatogr. A 2016, 1456, 89–104.
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