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

Facile preparation of hollow covalent organic frameworks as superior and universal matrix clean-up micro-structures for high throughout determination of food hazards

The complicated food matrix seriously limits the one-time test for the potential food hazards in non-targeted analysis. Accordingly, developing advanced sample pretreatment strategy to reduce matrix effects is of great significance. Herein, newly-integrated hollow-structured covalent organic frameworks (HCOFs) with large internal adsorption capacity and target-matched pore size were synthesized via etching the core-shell structured COFs. The as-prepared HCOFs could be directly applied for matrix clean-up of vegetable samples, while further modification of polydopamine (PDA) network facilitated application for animal samples. Both HCOFs and HCOFs@PDA with the comparable sizes to the matrix interference gave excellent adsorption performance to targets, achieving satisfied recoveries (70%-120%) toward 90 pesticides and 44 veterinary drugs in one-test, respectively. This work showed the great potential of the facile-integrated HCOFs with high stability and customized size to remove interference matrix and offered a universal strategy to achieve simultaneous screening of hazards with considerable quantity in high-throughput non-targeted analysis.

Targeted screening of the synergistic components in Artemisia annua L. leading to enhanced antiplasmodial potency of artemisinin based on a "top down" PD-PK approach

ETHNOPHARMACOLOGICAL RELEVANCE

Artemisinin (ART) showed enhanced antimalarial potency in the herb Artemisia annua L. (A. annua), from which ART is isolated. Increased absorption of ART with inhibited metabolism in the plant matrix is an underlying mechanism. Several synergistic components have been reported based on a "bottom-up" approach, i.e., traditional isolation followed by pharmacokinetic and/or pharmacodynamic evaluation.

AIM OF THE STUDY

In this study, we employed a "top-down" approach based on in vivo antimalarial and pharmacokinetic studies to identify synergistic components in A. annua.

MATERIALS AND METHODS

Two A. annua extracts in different chemical composition were obtained by extraction using ethyl acetate (EA) and petroleum ether (PE). The synergistic antimalarial activity of ART in two extracts was compared both in vitro (Plasmodium falciparum) and in vivo (murine Plasmodium yoelii). For the PD-PK correlation analysis, the pharmacokinetic profiles of ART and its major metabolite (ART-M) were investigated in healthy rats after a single oral administration of pure ART (20 mg/kg) or equivalent ART in each A. annua extract. A liquid chromatography-tandem high-resolution mass spectrometry (LC-HRMS)-based analytical strategy was then applied for efficient component classification and structural characterization of the differential components in the targeted extract with a higher antimalarial potency. Major components isolated from the targeted extract were then evaluated for their synergistic effect in the same proportion.

RESULTS

Compared with pure ART (ED50, 5.6 mg/kg), ART showed enhanced antimalarial potency in two extracts in vivo (ED50 of EA, 2.9 mg/kg; ED50 of PE, 1.6 mg/kg), but not in vitro (IC50, 15.0-20.0 nM). A significant increase (1.7-fold) in ART absorption (AUC0-t) was found in rats after a single oral dose of equivalent ART in PE but not in EA; however, no significant change in the metabolic capability (AUCART-M/AUCART) was found for ART in either extract. The differential component analysis of the two extracts showed a higher composition of sesquiterpene compounds, especially component AB (3.0% in PE vs. 0.9% in EA) and component AA (14.1% in PE vs. 5.1% in EA). Two target sesquiterpenes were isolated and identified as arteannuin B (AB) and artemisinic acid (AA). The synergism between ART and AB/AA in the same proportion with PE extract (20:1.6:7.6, mg/kg) was verified by a pharmacokinetic study in rats.

CONCLUSIONS

A "top-down" strategy based on PD-PK studies was successfully employed to identify synergistic components for ART in A. annua. Two sesquiterpene compounds (arteannuin B and artemisinic acid) could enhance the antimalarial potency of ART by increasing its absorption.

Adsorption of clarithromycin on polystyrene nanoplastics surface and its combined adverse effect on serum albumin

Emerging contaminants, such as antibiotics and nanoplastics, have garnered significant attention due to their potential adverse effects on diverse ecosystems. Antibiotic adsorption on the surface of nanoplastics potentially facilitates their long-range transport, leading to the synergistic effects of the complex. This research aims to examine the adsorption behavior of clarithromycin binding with polystyrene nanoplastics surface as well as their interaction between drug adsorbed polystyrene nanoplastics with serum albumin. Different spectroscopic methods were used to find out the interaction between clarithromycin and nanoplastics, under stimulated physiological conditions UV-vis spectroscopy showed a maximum of 22.8% percentage of the drug adsorbed with the polystyrene nanoplastics surface after 6 h of incubation. The fluorescence spectroscopic results demonstrated that the fluorescence intensity of serum albumin was quenched by the clarithromycin-polystyrene nanoplastics (CLA-PSNP) complex through static quenching. We calculated the number of binding stoichiometry, binding constants, and thermodynamic parameters. This study revealed that the CLA-PSNP binds to serum albumin spontaneously and its hydrophobic interactions played a significant role. The conformational changes in the structure of serum albumin were revealed from the findings of synchronous fluorescence spectra, CD spectra, and 3D fluorescence spectra, leading to the disturbance in functional activity. This study focuses valuable insights into the intermolecular interactions between clarithromycin-adsorbed polystyrene nanoplastics and serum albumin and its potential molecular-level biological toxicity.

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.

An integrated approach for studying the metabolic profiling of herbal medicine in mice using high-resolution mass spectrometry and metabolomics data processing tools

Analysis of exposure to traditional Chinese medicine (TCM) in vivo based on mass spectrometry is helpful for the screening of effective ingredients of TCM and the development of new drugs. The method of screening biomarkers through metabolomics technology is a nontargeted research method to explore the differential components between two sets of biological samples. By taking this advantage, this study aims to takes Forsythia suspensa, which is a TCM also known as Lian Qiao (LQ), as the research object and to study its in vivo exposure by using metabolomics technology. By comparing the significant differences between biological samples before and after administration, it could be focused on the components that were significantly upregulated, where a complete set of analysis strategies for nontargeted TCM in vivo exposure mass spectrometry was established. Furthermore, the threshold parameters for peak extraction, parameter selection during statistical data analysis, and sample concentration multiples in this method have also been optimized. More interestingly, by using the established analysis strategy, we found 393 LQ-related chemical components in mice after administration, including 102 prototypes and 291 LQ-related metabolites, and plotted their metabolic profiles in vivo. In short, this study has obtained a complete mass spectrum of LQ exposure in mice in vivo for the first time, which provides a reference for research on the active ingredients of LQ in vivo. More importantly, compared with other methods, the analysis strategy of nontargeted exposure of TCM in vivo-based mass spectrometry, constructed by using this research method, has good universality and does not require self-developed postprocessing software. It is worth mentioning that, for the identification and characterization of trace amounts of metabolites in vivo, this analysis strategy has no discrimination and has a detection capability similar to that of highly exposed components.

Suspect screening for chemical residues in aquacultured shrimp and fish using liquid chromatography-high resolution mass spectrometry: comparison of data evaluation approaches

High-resolution mass spectrometry (HRMS) has become an important tool for monitoring chemical residues in food, but the time and effort required to evaluate the large amount of data generated by HRMS can be a limiting factor in the widespread application of this tool. Suspect screening, i.e., searching HRMS data against large compound databases or mass lists, represents a practical compromise between using HRMS data to only look for target compounds and performing full non-target analysis. Several different approaches for suspect screening using HRMS data were tested using data from shrimp and eel spiked with veterinary drugs and pesticides as well as from imported aquaculture samples. Most of the analytes (>70%) in the spiked samples were detected and identified by searching against compound databases. To query larger databases and on-line resources such as mzCloud, it was necessary to use software capable of differential analysis and selective filtering, such as Compound Discoverer. Using selective filtering, the number of compounds detected in fish sample extracts could be reduced from tens of thousands to a few hundred by subtracting method blanks and comparing to matrix blank extracts. This smaller list of potential compounds could be further evaluated and compared to available databases and libraries. Analysis of imported aquaculture samples resulted in detection of unexpected contaminants including the dewormer levamisole, the insecticide buprofezin, and potentially the plant alkaloid ricinine.

Interaction of antidiabetic formulation with nanoplastics and its binary influence on plasma protein

Nanoplastics exposure to humans becomes inevitable due to its prevalence and permanence. Adsorption of emerging pollutant metformin hydrochloride (Met-HCl) -antidiabetic drug, on polystyrene nanoplastics (PSNPs) and influence on plasma protein binding was investigated. Fluorescence studies were carried out for human serum albumin (HSA) binding. Adsorption follows pseudo-second-order kinetics, intraparticle-diffusion, and Langmuir isotherm, undergoing both physisorption and chemisorption which was validated by FE-SEM, FTIR, and HRMS measurements. Complex, experiences static quenching mechanism by hydrogen bonding and VanderWaals force of attraction to HSA. FTIR confirms the secondary structural alteration of HSA. Since Met-HCl covers the NPs' surface, NPs' affinity for HSA is reduced and they might reach the target organs of Met-HCl, disrupt antidiabetic mechanisms and cause far-reaching implications. Results from molecular docking and simulation studies backed up these results as hydrophobic and hydrogen bonds dominate the binding process of the HSA-Met-HCl-PSNPs complex. This work will aid in understanding of the toxico-kinetics/dynamics of binary contaminants.

Targeted Analysis of Veterinary Drugs in Food Samples by Developing a High-Resolution Tandem Mass Spectral Library

Veterinary drug residues present in foods can pose severe health threats to the population. The present study aims to develop a high-resolution mass spectral library of 158 veterinary drugs of 16 different classes for their rapid identification in food samples through liquid chromatography-high-resolution electrospray ionization-tandem mass spectrometry (LC-HR-ESI-MS/MS). Standard drugs were pooled according to their log P values and exact masses before analysis. Spectra were collected at system automated collision energy, i.e., of 25-60 eV and four predetermined collision energies (10, 20, 30, and 40 eV) for each compound using a schedule precursor list of [M + H]+, [M + Na]+, and [M + NH4]+ ions. The utility of the developed database was checked by analyzing food samples. A total of 17 veterinary drugs based on the reference standard retention times (RTs), HR-MS spectra, and MS/MS spectra were identified in the analyzed samples. Moreover, five veterinary drugs were selected for quantitative analysis, including doxycycline hyclate, lincomycin, sulfasalazine, moxifloxacin, and diphenoxylate, using liquid chromatography-ion trap mass-spectrometry (LC-IT-MS). Concentrations of the drug were obtained to vary from 0.0805 to 0.9731 mg/kg in food samples and were found to be exceeded in most of the cases as per the maximum residue levels described by Food and Agriculture Organization (FAO)/World Health Organization (WHO). The MS data were submitted to the MetaboLights online database (MTBLS2914). This study will help in the high-throughput screening of multiclass veterinary drugs in foodstuffs.

Factors affecting untargeted detection of doping agents in biological samples

Doping control is essential for sports, and untargeted detection of doping agents (UDDA) is the holy grail for anti-doping strategies. The present study examined major factors impacting UDDA with metabolomic data processing, including the use of blank samples, signal-to-noise ratio thresholds, and the minimum chromatographic peak intensity. Contrary to data processing in metabolomics studies, both blank sample use (either blank solvent or plasma) and marking of background compounds were found to be unnecessary for UDDA in biological samples, the first such report to the authors' knowledge. The minimum peak intensity required to detect chromatographic peaks affected the limit of detection (LOD) and data processing time for untargeted detection of 57 drugs spiked into equine plasma. The ratio of the mean (ROM) of the extracted ion chromatographic peak area of a compound in the sample group (SG) to that in the control group (CG) impacted its LOD, and a small ROM value such as 2 is recommended for UDDA. Mathematical modeling of the required signal-to-noise ratio (S/N) for UDDA provided insights into the effect of the number of samples in the SG, the number of positive samples, and the ROM on the required S/N, highlighting the power of mathematics in addressing issues in analytical chemistry. The UDDA method was validated by its successful identification of untargeted doping agents in real-world post-competition equine plasma samples. This advancement in UDDA methodology will be a useful addition to the arsenal of approaches used to combat doping in sports.

Using HRMS fingerprinting to explore micropollutant contamination in soil and vegetables caused by swine wastewater irrigation

Livestock wastewater has been reused for agricultural irrigation to save water and fertilise the soil. However, micropollutants excreted by livestock animals may contaminate the soil and crops through livestock wastewater irrigation. This study employed high-resolution mass spectrometry (HRMS) to facilitate broad-scope suspect screening of soil and vegetables and identify changes in micropollutant fingerprints caused by swine wastewater irrigation. Field trials were performed to simulate the practical cultivation of small leafy vegetables. Soil and pak choi were irrigated with groundwater, a reasonable amount of swine wastewater, and excessive swine wastewater (three times the reasonable amount) and were sampled at three time points. The samples were extracted using organic solvents and analysed with a liquid chromatography-quadrupole-time-of-flight HRMS system. The molecular features were compared to over 3000 micropollutants in commercial libraries. The relative concentrations of suspect micropollutants among the irrigation groups were compared using multivariate and univariate analyses. The marker micropollutants that increased with swine wastewater irrigation were rigorously identified based on the MS/MS spectra. Fifty-three micropollutants were frequently found in the soil (n = 54) and 36 in the pak choi (n = 53). Partial least squares discriminant analysis (PLS-DA) models revealed significant differences in the micropollutant fingerprints in the soil among the three irrigation groups, but not in the pak choi. Eight micropollutants with variable importance in projection scores above 1.0 in the PLS-DA model and significantly higher relative concentrations (p < 0.05) in the soil irrigated with swine wastewater were confirmed as markers. Besides veterinary drugs and their metabolites, cinnamic acid and phenylalanine were the markers relevant to swine feed that were not previously reported. Nevertheless, accumulations of micropollutants in the soil or contamination of the pak choi due to swine wastewater irrigation were not found under the trial conditions.

Strategies for studying in vivo biochemical formation pathways and multilevel distributions of sulfanilamide metabolites in food (2012-2022)

Sulfonamide metabolites are a major source of food pollution worldwide. However, the formation of internal sulfanilamide metabolites has only been investigated for selected compounds. In this paper, the fragmentation mechanism and characteristic ions of sulfonamide metabolites are reviewed using density functional theory and Q-Orbitrap high-resolution mass spectrometry. The result of the protonation site, rearrangement and bond breaking induced fragmentations at C₆H₆NO₂S⁺m/z 156.01138, C₆H₆NO⁺m/z 108.04439, and C₆H₆N⁺m/z 92.04948. Mass shifts are calculated for derivative metabolites, including hydrogenation, acetylation, oxidation, glucosylation, glucosidation, sulfation, deamination, formylation, desulfonation and O-aminomethylation. Given their homologous series, it is demonstrated that similar metabolic reactions occur for all sulfonamides. The suspicious sulfonamide metabolites are confirmed by d-labelling experiments and reference standards. This is the first review of the latest advances in the field of sulfonamide metabolite prediction (2012-2022), and scheme design for metabolite multirresidue screening, as well as the challenges in the mass spectrometry evolution.