High-throughput screening of 756 chemical contaminants in aquaculture products using liquid chromatography/quadrupole time-of-flight mass spectrometry

Target and suspect screening approaches for the identification of emerging and other contaminants in fish feeds using high resolution mass spectrometry

Fish feed is essential in aquaculture fish production because, along with beneficial nutrients and components, many suspected compounds can be transferred to fish and ultimately to humans. In this context, a comprehensive analysis was conducted to monitor various pesticides and pharmaceutical compounds in aquaculture fish feed through target analysis and many other groups of chemicals via suspect screening approaches. In this study, the QuEChERS extraction method was optimized, validated, and applied to fifty-four fish feed samples collected from different production batches. This was followed by liquid chromatography-high-resolution linear ion trap/Orbitrap mass spectrometry (LC-HR-IT/Orbitrap-MS) for targeted and suspect screening purposes. In general, pesticides provided satisfactory recoveries (70-105.5 %), with quantification limits lower than 5 ng g-1, whereas pharmaceuticals displayed recoveries ranging from 70.5 to 120.2 %, with quantification limits below 25 ng g-1. In addition, the matrix effects and measurement uncertainty were assessed to provide more accurate and high-confidence results. Pirimiphos-methyl was detected and quantified in 20 of 54 fish feed samples (37 %) at concentrations <77 ng g-1. Finally, suspect screening revealed the occurrence of 10 mycotoxins (e.g., citrinin, aflatoxin G2, zearalenone, and alternariol), two pesticides excluding the target pesticides (tebuconazole and fenazaquin), perfluorooctane sulfonic acid (PFOS) in almost 2 % of the samples, and ethoxyquin (antioxidant), with 12 of its Transformation Products (TPs). Finally, suspect analysis incorporated in routine analyses have proven to have great potential for complete monitoring.

Analysis of chemical contaminants in fish using high resolution mass spectrometry - A review

High resolution mass spectrometry (HRMS) has become an important tool in environmental and food safety analysis. This review highlights how HRMS has been used to analyze chemical contaminants in fish. Measuring and documenting chemical contaminants in fish serves not only as an indicator of environmental conditions but can also monitor the health of these animals and help protect an important source of human food. The incidence and significance of contaminants including veterinary drugs, human drugs and personal care products, pesticides, persistent organic pollutants, per- and poly fluorinated substances, and marine toxins will be reviewed. The advantage of HRMS over traditional MS is its ability to expand the number of compounds that can be detected and identified. This is true whether HRMS is used for targeted analytes, or more broadly for suspect screening and nontargeted analyses. The classes of compounds, types of fish or seafood, options for data acquisition and analysis, and reports of unexpected findings from recent HMRS methods for chemical contaminants in fish are summarized.

Screening and identification of unknown chemical contaminants in food based on liquid chromatography-high-resolution mass spectrometry and machine learning

Unknown or unexpected chemical contaminants and/or their transformation products in food that may be harmful to humans need to be discovered for comprehensive safety evaluation. Liquid chromatography-high-resolution mass spectrometry (LC-HRMS) is a powerful tool for detecting chemical contaminants in food samples. However, identifying all of peaks in LC-HRMS is not possible, but if class information is known in advance, further identification will become easier. In this work, a novel MS2 spectra classification-driven screening strategy was constructed based on LC-HRMS and machine learning. First, the classification model was developed based on machine learning algorithm using class information and experimental MS2 data of chemical contaminants and other non-contaminants. By using the developed artificial neural network classification model, in total 32 classes of pesticides, veterinary drugs and mycotoxins were classified with good prediction accuracy and low false-positive rate. Based on the classification model, a screening procedure was developed in which the classes of unknown features in LC-HRMS were first predicted through the classification model, and then their structures were identified under the guidance of class information. Finally, the developed strategy was tentatively applied to the analysis of pork and aquatic products, and 8 chemical contaminants and 11 transformation products belonging to 8 classes were found. This strategy enables screening of unknown chemical contaminants and transformation products in complex food matrices.

Structure-based virtual screening and fragment replacement to design novel inhibitors of Coxsackievirus A16 (CVA16)

Numerous studies have shown that hand, foot and mouth disease (HFMD) pathogen Coxsackievirus A16 (CVA16) can also cause severe neurological complications and even death. Currently, there is no effective drugs and vaccines for CVA16. Therefore, developing a drug against CVA16 has become critical. In this study, we conducted two strategies-virtual screening (VS) and fragment replacement to obtain better candidates than the known drug GPP3. Through VS, 37 candidate drugs were screened (exhibiting a lower binding energy than GPP3). After toxicity evaluations, we obtained five candidates, analysed their binding modes and found that four candidates could enter the binding pocket of the GPP3. In another strategy, we analysed the four positions in GPP3 structures by the FragRep webserver and obtained a large number of candidates after replacing different functional groups, we obtained eight candidates (that target the four positions above) with the combined binding score and synthetic accessibility evaluations. AMDock software was uniformly utilized to perform molecular docking evaluation of the candidates with binding activity superior to that of GPP3. Finally, the selected top three molecules (Lapatinib, B001 and C001) and its interaction with CAV16 were validated by molecular dynamics (MD) simulation. The results indicated that all three molecules retain inside the pocket of CAV16 receptor throughout the simulation process, and he binding energy calculated from the MD simulation trajectories also support the strong affinity of the top three molecules towards the CVA16. These results will provide new ideas and technical guidance for designing and applying CVA16 therapeutics.Communicated by Ramaswamy H. Sarma.

Wide-scope screening of multi-class contaminants in seafood using a novel sample preparation (QuEChUP) procedure coupled with UHPLC-Q-TOF-MS: Application for semi-quantitation of real seafood samples

A high-resolution mass spectrometry screening method was developed and validated based on EU SANTE/11312/2021 guidelines for the analysis of 850 multi-class contaminants in commercial seafood samples. Samples were extracted using a novel sequential QuEChUP preparation method that combines the QuEChERS and QuPPe procedures. The screening detection limits (SDLs) and limits of identification (LOIs) were equal to or lower than 0.01 mg·kg^-1 for 92% and 78% of contaminants, respectively. This screening procedure was ultimately applied for a target screening analysis of 24 seafood samples. The concentrations of identified contaminants were assessed using semi-quantitative approach. Two identified contaminants, diuron and diclofenac, showed the highest estimated average concentrations: 0.076 and 0.068 mg·kg^-1 respectively in mussel samples. Suspect screening was also performed. Target and suspect screening led to the identification of mixtures of contaminants (pesticides, veterinary products, industrial chemicals and personal care products) and the assessment of their frequencies of appearance (FoA).