Premium
Development of a suspect and non‐target screening approach to detect veterinary antibiotic residues in a complex biological matrix using liquid chromatography/high‐resolution mass spectrometry
Author(s) -
Solliec Morgan,
RoyLachapelle Audrey,
Sauvé Sébastien
Publication year - 2015
Publication title -
rapid communications in mass spectrometry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.528
H-Index - 136
eISSN - 1097-0231
pISSN - 0951-4198
DOI - 10.1002/rcm.7405
Subject(s) - chemistry , antibiotics , manure , veterinary drug , chromatography , veterinary drugs , complex matrix , liquid chromatography–mass spectrometry , matrix (chemical analysis) , ciprofloxacin , high resolution , mass spectrometry , veterinary medicine , microbiology and biotechnology , biology , medicine , ecology , biochemistry , remote sensing , geology
Rationale Swine manure can contain a wide range of veterinary antibiotics, which could enter the environment via manure spreading on agricultural fields. A suspect and non‐target screening method was applied to swine manure samples to attempt to identify veterinary antibiotics and pharmaceutical compounds for a future targeted analysis method. Methods A combination of suspect and non‐target screening method was developed to identify various veterinary antibiotic families using liquid chromatography coupled with high‐resolution mass spectrometry (LC/HRMS). The sample preparation was based on the physicochemical parameters of antibiotics for the wide scope extraction of polar compounds prior to LC/HRMS analysis. The amount of data produced was processed by applying restrictive thresholds and filters to significantly reduce the number of compounds found and eliminate matrix components. Results The suspect and non‐target screening was applied on swine manure samples and revealed the presence of seven common veterinary antibiotics and some of their relative metabolites, including tetracyclines, β‐lactams, sulfonamides and lincosamides. However, one steroid and one analgesic were also identified. The occurrence of the identified compounds was validated by comparing their retention times, isotopic abundance patterns and fragmentation patterns with certified standards. Conclusions This identification method could be very useful as an initial step to screen for and identify emerging contaminants such as veterinary antibiotics and pharmaceuticals in environmental and biological matrices prior to quantification. Copyright © 2015 John Wiley & Sons, Ltd.