Skip to main content
ARS Home » Northeast Area » Wyndmoor, Pennsylvania » Eastern Regional Research Center » Residue Chemistry and Predictive Microbiology Research » Research » Publications at this Location » Publication #335933

Research Project: Development, Evaluation, and Validation of Technologies for the Detection and Characterization of Chemical Contaminants in Foods

Location: Residue Chemistry and Predictive Microbiology Research

Title: Comparison of veterinary drug residue results in animal tissues by ultrahigh-performance liquid chromatography coupled to triple quadrupole ... use of a commercial lipid removal product

Author
item Anumol, Tarun - Agilent Laboratories
item Lehotay, Steven
item Stevens, Joan - Agilent Laboratories
item Zweigenbaum, Jerry - Agilent Laboratories

Submitted to: Analytical and Bioanalytical Chemistry
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/12/2017
Publication Date: 2/21/2017
Publication URL: http://handle.nal.usda.gov/10113/5661757
Citation: Anumol, T., Lehotay, S.J., Stevens, J., Zweigenbaum, J. 2017. Comparison of veterinary drug residue results in animal tissues by ultrahigh-performance liquid chromatography coupled to triple quadrupole ... use of a commercial lipid removal product. Analytical and Bioanalytical Chemistry. 409:2639-2653.

Interpretive Summary: Analysis of veterinary drug residues in food animal tissues is an important application for improved food safety and addressing antimicrobial resistance. Drug residue monitoring is routinely conducted in countless laboratories worldwide for regulatory and other purposes. One of the main challenges in detecting, identifying, and quantifying ultratrace amounts of chemical residues in complex foods is sample cleanup, which involves the isolation of the contaminants from the many matrix components in the samples. In this study, a new commercial product was evaluated for sample cleanup and compared with an existing method used in practice. Results showed both methods to be effective, with advantages and disadvantages of each, but the new material provided greater removal of lipids from the extracts. The new cleanup technique may improve the analysis of chemical residues in food, and ultimately improve monitoring results.

Technical Abstract: Veterinary drug residues in animal-derived foods must be monitored to ensure food safety, verify proper veterinary practices, enforce legal limits in domestic and imported foods, and other purposes. A common goal in drug residue analysis in foods is to achieve acceptable monitoring results for as many analytes as possible, with higher priority given to the drugs of most concern, in an efficient and robust manner. The U.S. Department of Agriculture has implemented a multiclass, multiresidue method based on sample preparation using dispersive solid-phase extraction (d-SPE) for cleanup and ultrahigh-performance liquid chromatography – tandem quadrupole mass spectrometry (UHPLC-QQQ) for analysis of >120 drugs at regulatory levels of concern in animal tissues. Recently, a new cleanup product called “enhanced matrix removal for lipids” (EMR-L) was commercially introduced that uses a unique chemical mechanism to remove lipids from extracts. Furthermore, high resolution quadrupole – time-of-flight (Q/TOF) for (U)HPLC detection often yields higher selectivity than targeted QQQ analyzers while allowing retroactive processing of samples for other contaminants. In this study, the use of both d-SPE and EMR-L sample preparation and UHPLC-QQQ and UHPLC-Q/TOF analysis methods for shared spiked samples of bovine muscle, kidney, and liver were compared. The results showed that the EMR-L method provided cleaner extracts overall and improved results for several anthelmintics and tranquilizers compared to the d-SPE method, but the EMR-L method gave lower recoveries for certain beta-lactam antibiotics. QQQ vs. Q/TOF detection showed similar mixed performance advantages depending on analytes and matrix interferences, with an advantage to Q/TOF for greater possible analytical scope and nontargeted data collection. Either combination of approaches may be used to meet monitoring purposes, with an edge in efficiency to d-SPE, but greater instrument robustness and less matrix effects when analyzing EMR-L extracts.