Simultaneous quantification of aminoglycoside antibiotics in milk using the SCIEX Triple Quad™ 3500 LC-MS/MS System
Applications | 2020 | SCIEXInstrumentation
Aminoglycoside antibiotics are widely used in both human and veterinary medicine, but their residues in dairy products pose health risks when exceeding regulatory limits. Monitoring these residues in milk is essential to maintain food safety and comply with international maximum residue levels (MRLs).
This work aimed to establish a robust, sensitive, and high-throughput LC-MS/MS method for simultaneous quantification of spiramycin, kanamycin, and neomycin in milk. The method was aligned with European Commission Directive 2002/657/EC and optimized to detect aminoglycoside levels far below established MRLs.
Sample Preparation:
Chromatography:
Mass Spectrometry:
Data Processing:
Partial validation confirmed linearity (r² ≥ 0.99) for spiramycin (2–150 ppb), kanamycin (3–100 ppb) and neomycin (5–100 ppb) using weighted regression. Limit of quantification (LOQ) was set at 2 ppb for spiramycin and kanamycin, 5 ppb for neomycin. Recovery rates fell between 90–110%, and repeatability (%CV) was below 10% at LOQ. Real-market milk samples showed no detectable residues at analyte retention times.
This streamlined protocol offers:
Advances may include automated sample handling, integration of high-resolution mass spectrometry for non-target screening, and expansion to other antibiotic classes. Machine learning algorithms could enhance data interpretation and further reduce false positives.
The developed LC-MS/MS approach reliably quantifies multiple aminoglycosides in milk with excellent sensitivity, accuracy and compliance to regulatory requirements. Its simplicity and robustness make it ideal for routine surveillance of veterinary drug residues in dairy products.
LC/MS, LC/MS/MS, LC/QQQ
IndustriesFood & Agriculture
ManufacturerSCIEX
Summary
Significance of Topic
Aminoglycoside antibiotics are widely used in both human and veterinary medicine, but their residues in dairy products pose health risks when exceeding regulatory limits. Monitoring these residues in milk is essential to maintain food safety and comply with international maximum residue levels (MRLs).
Study Objectives and Overview
This work aimed to establish a robust, sensitive, and high-throughput LC-MS/MS method for simultaneous quantification of spiramycin, kanamycin, and neomycin in milk. The method was aligned with European Commission Directive 2002/657/EC and optimized to detect aminoglycoside levels far below established MRLs.
Methodology and Instrumentation
Sample Preparation:
- Milk samples (1 mL) were treated with 0.4 mL of 10% trichloroacetic acid, vortexed and centrifuged.
- Supernatant was filtered through a 0.22 μm membrane before analysis.
Chromatography:
- Shimadzu Nexera XR system with Phenomenex Luna C18 column (3.0×150 mm, 3 µm).
- Gradient elution using water + 0.2% HFBA (A) and acetonitrile (B) over 10 minutes at 800 µL/min.
Mass Spectrometry:
- SCIEX Triple Quad 3500 coupled to Turbo V™ Ion Source in positive electrospray ionization mode.
- Multiple reaction monitoring (MRM) with two transitions per analyte for reliable identification.
Data Processing:
- Analyst® Software 1.6.2 for data acquisition.
- MultiQuant™ 3.0.2 for peak integration, calibration curves and automatic ion ratio confirmation.
Results and Discussion
Partial validation confirmed linearity (r² ≥ 0.99) for spiramycin (2–150 ppb), kanamycin (3–100 ppb) and neomycin (5–100 ppb) using weighted regression. Limit of quantification (LOQ) was set at 2 ppb for spiramycin and kanamycin, 5 ppb for neomycin. Recovery rates fell between 90–110%, and repeatability (%CV) was below 10% at LOQ. Real-market milk samples showed no detectable residues at analyte retention times.
Benefits and Practical Applications
This streamlined protocol offers:
- High sensitivity (~100× below MRL).
- Minimal sample preparation without additional cleanup.
- Fast throughput suitable for routine monitoring in QA/QC laboratories.
Future Trends and Opportunities
Advances may include automated sample handling, integration of high-resolution mass spectrometry for non-target screening, and expansion to other antibiotic classes. Machine learning algorithms could enhance data interpretation and further reduce false positives.
Conclusion
The developed LC-MS/MS approach reliably quantifies multiple aminoglycosides in milk with excellent sensitivity, accuracy and compliance to regulatory requirements. Its simplicity and robustness make it ideal for routine surveillance of veterinary drug residues in dairy products.
References
- European Commission Decision 2002/657/EC. Official Journal of the European Communities L221 (2002).
- SANCO/12495/2011: Method Validation and Quality Control Procedures for Pesticide Residues in Food and Feed.
- FSSAI Contaminants, Toxins and Residues Regulation (2011).
- FSSAI Training Program (2018).
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