4.6 Article

Suspect screening and untargeted analysis of veterinary drugs in food by LC-HRMS: Application of background exclusion-dependent acquisition for retrospective analysis of unknown xenobiotics

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ELSEVIER
DOI: 10.1016/j.jpba.2022.114583

Keywords

BE-DDA; PATBS; Veterinary drugs; Xenobiotics fingerprint; Retrospective suspect screening; Untargeted analysis of unknowns

Funding

  1. National Natural Science Foundation of China [U1903119, 82173779]
  2. Pilot Project of Science and Technology of Fujian Province [2020Y0013]
  3. Fundamental Research Funds for the Central Universities [20720200052]
  4. Science and Technology Program of Customs P.R. China [2020HK223]

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This study developed an analytical strategy based on high-resolution mass spectrometry for retrospective analysis of suspect and unknown xenobiotics. Using newly developed BE-DDA and PATBS techniques, accurate identification of 48 veterinary drugs and acquisition of their MS/MS spectra were achieved. Compared to ion intensity-based data-dependent acquisition, this study provided more comprehensive analysis results.
ABSTR A C T The presence of veterinary drug and pesticide residues in food products pose considerable threats to human health. Monitoring of these residues in food is mainly carried out using targeted analysis by triple quad-rupole mass spectrometry. However, these methods are not suitable for suspect screening and untargeted analysis of unknowns. The main objectives of this study were to develop a new high-resolution mass spectrometry (HRMS)-based analytical strategy for retrospective analysis of suspect and unknown xeno-biotics and to evaluate its performance in the tentative identification of 48 veterinary drugs as unknowns spiked in a pork sample. In the analysis, a newly developed background exclusion data-dependent acqui-sition (BE-DDA) technique was employed to trigger the product ion (MS/MS) spectral acquisition of the unknowns, and an in-house precise-and-thorough background-subtraction (PATBS) technique was ap-plied to detect these unknowns. Results showed that untargeted data mining of the acquired LC-MS dataset by PATBS was able to find all the 48 veterinary drugs and 46 of them were triggered by BE-DDA to generate accurate MS/MS spectra. The dataset of recorded accurate full-scan mass and MS/MS spectra of all the xenobiotics of the test pork sample is defined as the xenobiotics profile. Searching the xenobiotic profile of the test pork sample using mass spectral data of selected veterinary drugs (as suspects) from the mzCloud spectral library led to the correct hits. Searching against the mzCloud spectral library using the mass spectral data of selected individual veterinary drugs (as unknowns) from the xenobiotics profile tentatively confirmed their identities. In contrast, analysis of the same sample using ion intensity-data dependent acquisition only recorded the MS/MS spectra for 34 veterinary drugs. In addition, a data in-dependent acquisition method enabled the acquisition of the fragment spectra for 44 veterinary drugs, but their spectral data displayed only one or a few true product ions of individual analytes of interest along with

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