Nontargeted screening of chemical contaminants and illegal additives in food based on liquid chromatography–high resolution mass spectrometry

Research advances in detection of food adulteration and application of MALDI-TOF MS: A review

Food adulteration and illegal supplementations have always been one of the major problems in the world. The threat of food adulteration to the health of consumers cannot be ignored. Food of questionable origin causes economic losses to consumers, but the potential health risks cannot be ignored. However, the traditional detection methods are time-consuming and complex. This review mainly discusses the types of adulteration and technologies used to detect adulteration. Matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS) is also emphasized in the detection of adulteration and authenticity of origin analysis of various types of food (milk, meat, edible oil, etc.), and the future application direction and feasibility of this technology are analyzed. On this basis, MALDI-TOF MS was compared with other detection methods, highlighting the advantages of this technology in the detection of food adulteration. The future development prospect and direction of this technology are also emphasized.

Fragmentation characteristics-based nontargeted screening method of exogenous chemical residues in animal-derived foods using reversed-phase and hydrophilic interaction liquid chromatography-high-resolution mass spectrometry

Fragmentation characteristics are crucial for nontargeted screening to discover and identify unknown exogenous chemical residues in animal-derived foods. In this study, first, fragmentation characteristics of 51 classes of exogenous chemical residues were summarized based on experimental mass spectra of standards in reversed-phase and hydrophilic interaction liquid chromatography-high-resolution mass spectrometry (MS) and mass spectra from the MassBank of North America (MoNA) library. According to the proportion of fragmentation characteristics to the total number of chemical residues in each class, four screening levels were defined to classify 51 classes of chemical residues. Then, a nontargeted screening method was developed based on the fragmentation characteristics. The evaluation results of 82 standards indicated that more than 90 % of the chemical residues with MS/MS spectra can be identified at concentrations of 100 and 500 μg/kg, and about 80 % can be identified at 10 μg/kg. Finally, the nontargeted screening method was applied to 16 meat samples and 21 egg samples as examples. As a result, eight chemical residues and transformation products (TPs) of 5 classes in the exemplary samples were found and identified, in which 3 TPs of azithromycin were identified by fragmentation characteristics-assisted structure interpretation. The results demonstrated the practicability of the nontargeted screening method for routine risk screening of food safety.

Recent advances in metal oxide nanozyme-based optical biosensors for food safety assays

Metal oxide nanozymes are emerging as promising materials for food safety detection, offering several advantages over natural enzymes, including superior stability, cost-effectiveness, large-scale production capability, customisable functionality, design options, and ease of modification. Optical biosensors based on metal oxide nanozymes have significantly accelerated the advancement of analytical research, facilitating the rapid, effortless, efficient, and precise detection and characterisation of contaminants in food. However, few reviews have focused on the application of optical biosensors based on metal oxide nanozymes for food safety detection. In this review, the catalytic mechanisms of the catalase, oxidase, peroxidase, and superoxide dismutase activities of metal oxide nanozymes are characterized. Research developments in optical biosensors based on metal oxide nanozymes, including colorimetric, fluorescent, chemiluminescent, and surface-enhanced Raman scattering biosensors, are comprehensively summarized. The application of metal oxide nanozyme-based biosensors for the detection of nitrites, sulphites, metal ions, pesticides, antibiotics, antioxidants, foodborne pathogens, toxins, and other food contaminants has been highlighted. Furthermore, the challenges and future development prospects of metal oxide nanozymes for sensing applications are discussed. This review offers insights and inspiration for further investigations on optical biosensors based on metal oxide nanozymes for food safety detection.

A proof-of-concept study on the versatility of liquid chromatography coupled to high-resolution mass spectrometry to screen for various contaminants and highlight markers of floral and geographical origin for different honeys

The high-resolution mass spectrometry is a powerful analytical tool for improving food safety and authenticity, but still underused in official control laboratories. The present work is a proof-of-concept study overviewing how liquid-chromatography coupled to high-resolution mass spectrometry could be used simultaneously for large-scale screening of contaminants and differentiation of honey samples. Within this study, the samples were extracted using all-in-one QuEChERS-based protocol that allowed for analysis of various anthropogenic contaminants and endogenous compounds. First, targeted-analysis of 52 honey samples led to unequivocal identification of 23 chemicals, including neonicotinoids, triazole fungicides and synergist. Then, suspect-screening using MSDial software allowed for tentative identification of 30 chemicals including plasticizers, flame-retardants and additives. Suspect-screening also made it possible to highlight tentative markers of chestnut honey (deoxyvasicinone, 2-quinolone, indoleacrylic acid and kynurenic acid) and citrus honey (caffeine, 2-oxindole and indole-3-carbinol). Lastly, non-targeted analysis enabled to separate honeys by their type, floral and geographical origins.

(Non)targeted Chemical Analysis and Risk Assessment of Organic Contaminants in Darkibor Kale Grown at Rural and Urban Farms

This study investigated the presence and human hazards associated with pesticides and other anthropogenic chemicals identified in kale grown in urban and rural environments. Pesticides and related compounds (i.e., surfactants and metabolites) in kale samples were evaluated using a nontargeted data acquisition for targeted analysis method which utilized a pesticide mixture containing >1,000 compounds for suspect screening and quantification. We modeled population-level exposures and assessed noncancer hazards to DEET, piperonyl butoxide, prometon, secbumeton, terbumeton, and spinosyn A using nationally representative estimates of kale consumption across life stages in the US. Our findings indicate even sensitive populations (e.g., pregnant women and children) are not likely to experience hazards from these select compounds were they to consume kale from this study. However, a strictly nontargeted chemical analytical approach identified a total of 1,822 features across all samples, and principal component analysis revealed that the kale chemical composition may have been impacted by agricultural growing practices and environmental factors. Confidence level 2 compounds that were ≥5 times more abundant in the urban samples than in rural samples (p < 0.05) included chemicals categorized as "flavoring and nutrients" and "surfactants" in the EPA's Chemicals and Products Database. Using the US-EPA's Cheminformatics Hazard Module, we identified that many of the nontarget compounds have predicted toxicity scores of "very high" for several end points related to human health. These aspects would have been overlooked using traditional targeted analysis methods, although more information is needed to ascertain whether the compounds identified through nontargeted analysis are of environmental or human health concern. As such, our approach enabled the identification of potentially hazardous compounds that, based on their hazard assessment score, merit follow-up investigations.

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.

Surface-enhanced Raman scattering using flower-like Ag/ZnO as active substrates for the label-free and sensitive detection of rhodamine 6G and melamine

The reliable and accurate detection of unauthorized additives in food is significant to prevent health risks. In recent years, surface-enhanced Raman spectroscopy (SERS) with fast, simple, and sensitive capabilities has been widely used for food safety analysis. In order to detect illegally added dye molecule rhodamine 6G and small molecule melamine in food, we have proposed a fast, convenient, and label-free SERS detection technology using flower-like Ag/ZnO as the SERS substrate. The structure and morphology of the flower-like Ag/ZnO were characterized by scanning electron microscopy, energy dispersive spectrometery, transmission electron microscopy, and X-ray diffraction analysis. We investigated the SERS effect and sensitivity of flower-like Ag/ZnO toward rhodamine 6G and melamine. The synergistic effect of flower-like Ag/ZnO provides high SERS activity for the detection of rhodamine 6G and melamine at the lowest detection concentrations of 0.5 ng mL-1 and 1.0 ng mL-1, respectively. Therefore, flower-like Ag/ZnO with good sensitivity and uniformity has potential for improving the detection of illegal food additives.

Suspect and nontarget screening of per- and polyfluoroalkyl substances based on ion mobility mass spectrometry and machine learning techniques

High-resolution mass spectrometry (HRMS)-based suspect and nontarget screening techniques are powerful tools for the comprehensive identification of per- and polyfluoroalkyl substances (PFASs), but the interference of complex matrices (especially for wastewater) pose an analytical challenge. This study explored the potential of combining ion mobility spectrometry (IMS) with HRMS and machine learning techniques to achieve the rapid and accurate suspect and nontarget screening of PFAS in wastewater. There were fewer interfering peaks and a clearer spectrum in the data acquired by IMS-HRMS than conventional HRMS. The introduction of collision cross section (CCS) in PFAS homologous series search could filter out 63% of false positive results. Retention time and CCS prediction models were helpful in improving the confidence for PFAS qualitative identification and the random forest algorithm combined with RDKit descriptor performed best for CCS prediction. With the inclusion of extra dimensional information, this study also proposed a comprehensive and concise confidence assignment criterion to better convey the certainty of the qualitative identification of PFAS. Finally, a total of 56 potential PFASs were identified in the wastewater sample using the newly developed method and 45 of them were identified outside reference standards, emphasizing the importance of suspect and nontarget screening for PFAS.

Recent Advances in Nanozyme-Mediated Strategies for Pathogen Detection and Control

Pathogen detection and control have long presented formidable challenges in the domains of medicine and public health. This review paper underscores the potential of nanozymes as emerging bio-mimetic enzymes that hold promise in effectively tackling these challenges. The key features and advantages of nanozymes are introduced, encompassing their comparable catalytic activity to natural enzymes, enhanced stability and reliability, cost effectiveness, and straightforward preparation methods. Subsequently, the paper delves into the detailed utilization of nanozymes for pathogen detection. This includes their application as biosensors, facilitating rapid and sensitive identification of diverse pathogens, including bacteria, viruses, and plasmodium. Furthermore, the paper explores strategies employing nanozymes for pathogen control, such as the regulation of reactive oxygen species (ROS), HOBr/Cl regulation, and clearance of extracellular DNA to impede pathogen growth and transmission. The review underscores the vast potential of nanozymes in pathogen detection and control through numerous specific examples and case studies. The authors highlight the efficiency, rapidity, and specificity of pathogen detection achieved with nanozymes, employing various strategies. They also demonstrate the feasibility of nanozymes in hindering pathogen growth and transmission. These innovative approaches employing nanozymes are projected to provide novel options for early disease diagnoses, treatment, and prevention. Through a comprehensive discourse on the characteristics and advantages of nanozymes, as well as diverse application approaches, this paper serves as a crucial reference and guide for further research and development in nanozyme technology. The expectation is that such advancements will significantly contribute to enhancing disease control measures and improving public health outcomes.

Using UHPLC-HRMS-based comprehensive strategy to efficiently and accurately screen and identify illegal additives in health-care foods

Accurately and high-thoroughly screening illegal additives in health-care foods continues to be a challenging task in routine analysis for the ultrahigh performance liquid chromatography-high resolution mass spectrometry based techniques. In this work, we proposed a new strategy to identify additives in complex food matrices, which consists of both experimental design and advanced chemometric data analysis. At first, reliable features in the analyzed samples were screened based on a simple but efficient sample weighting design, and those related to illegal additives were screened with robust statistical analysis. After the MS¹ in-source fragment ion identification, both MS¹ and MS/MS spectra were constructed for each underlying compound, based on which illegal additives can be precisely identified. The performance of the developed strategy was demonstrated by using mixture and synthetic sample datasets, indicating an improvement of data analysis efficiency up to 70.3 %. Finally, the developed strategy was applied for the screening of unknown additives in 21 batches of commercially available health-care foods. Results indicated that at least 80 % of false-positive results can be reduced and 4 additives were screened and confirmed.

Easily operated COF-based monolithic sponges as matrix clean-up materials for non-targeted analysis of chemical hazards in oil-rich foods

Non-targeted analysis of chemical hazards in foods plays a crucial role in controlling food safety. However, because it brings forward high demand for sample pretreatment, materials suitable for the pretreatment of foods, especially animal foods, are rare. Herein, covalent organic frameworks (COF)-based monolithic materials were constructed by three successive steps: preparation of polydimethylsiloxane (PDMS) sponge using sugar cube as a sacrificial template, loading of a heteroporous COF on PDMS sponge via ultrasonic or in-situ growth method, coating of the obtained PDMS@COF by polydopamine (PDA) network. As-prepared PDMS@COF@PDA sponges were demonstrated to work well in sample pretreatment of animal foods for non-targeted analysis of chemical hazards. After a simple vortex treatment for about 2 min, more than 98% triglycerides, the main interfering matrix components in animal foods, could be removed from lard and pork samples, accompanied by "full recovery" (recovery efficiencies: ≥63%) of 44 chemical hazards with different physicochemical properties. Besides providing promising sample pretreatment materials for non-targeted food safety analysis, this work also paves a feasible way to improve COF-based monolithic materials and thus promote their practical applications, because we found that the introduction of PDA network on COF-based monolithic material surface could play a role in "killing three birds with one stone": enhancing the stability of the materials by overcoming the detachment of COF during operations; controllably adjusting hydrophobic and hydrogen-bonding interactions on the material surface to promote the removal of triglycerides; weakening the hydrophobic and π-π interactions between COF and chemical hazards to increase the recoveries of chemical hazards.

Determination Methods of the Risk Factors in Food Based on Nanozymes: A Review

Food safety issues caused by foodborne pathogens, chemical pollutants, and heavy metals have aroused widespread concern because they are closely related to human health. Nanozyme-based biosensors have excellent characteristics such as high sensitivity, selectivity, and cost-effectiveness and have been used to detect the risk factors in foods. In this work, the common detection methods for pathogenic microorganisms, toxins, heavy metals, pesticide residues, veterinary drugs, and illegal additives are firstly reviewed. Then, the principles and applications of immunosensors based on various nanozymes are reviewed and explained. Applying nanozymes to the detection of pathogenic bacteria holds great potential for real-time evaluation and detection protocols for food risk factors.

A Novel Strategy Based on Permanent Protein Modifications Induced by Formaldehyde for Food Safety Analysis

The illegal additions of chemicals in food products are serious incidents threatening current public safety. To date, ideal methods to determine permanent traces of prohibited chemicals in foods are still lacking. For example, formaldehyde (FA) can be added illegally as a food preservative. However, most current methods that are dependent on the direct detection of FA are not able to determine if FA has ever been added once food products are rinsed completely. Herein, we present a novel approach relying upon protein modifications induced by FA (PMIF) to examine FA in foods. We reveal the entire catalog of PMIFs in food products by combining mass spectrometry analysis with unrestrictive identification of protein modifications. Consequently, four obvious PMIFs were identified and confirmed as markers to discriminate the addition of FA in foods. Our study demonstrates that the approach based on PMIFs enables detecting the imprinted trace of FA even if the food products have been washed thoroughly. Our work presents a novel strategy for analysis of chemical additives, offering broad potential applications in protein analysis and food safety.

Rapid and simultaneous detection of multiple illegal additives in feed and food by SERS with reusable Cu2O-Ag/AF-C3N4 substrate

Illegal additives can bring the economic benefit, resulting in the continuous irregularities in the use of illegal additives. In this study, a method for rapid, sensitive, and simultaneous detection of multiple illegal additives including enrofloxacin, malachite green, nitrofurazone, and Sudan Ⅰ in feed and food samples by surface-enhanced Raman spectroscopy (SERS) with Cu₂O-Ag/AF-C₃N₄ composite substrate was developed. A Cu₂O-Ag/AF-C₃N₄ composite substrate was prepared by reacting Cu₂O modified by AF-C₃N₄ nanosheets with AgNO₃ solution. The substrate has a limit of detection (LOD) of 1.29 × 10^-6 mg/L, a good linear relationship of between 10^-6 and 10^-2 mg/L, and an R² value of 0.95 for Rhodamine B detection. Furthermore, the substrate showed high uniformity and reproducibility, with relative standard deviations (RSD) of 6.74% and 4.85%, respectively. Adding AF-C₃N₄ nanosheets not only increased the enhancement effect of the substrate, which was 4.4 times of that before addition, but also endowed it with good self-cleaning characteristics owing to its excellent photocatalytic activity. The substrate can be reused, with over 80% of the original Raman signal strength remaining after four repeat uses. The SERS based on the above substrate was used to detect the illegal additives, the LOD of enrofloxacin, malachite green, nitrofurazone, and Sudan Ⅰ can reach 4.67 × 10^-4 mg/L, 2.57 × 10^-5 mg/L, 5.7 × 10^-7 mg/L and 6.92 × 10^-5 mg/L. The results reveal that this substrate has great application potential in feed and food safety.

Non-target and suspect-screening analyses of hydroponic soybeans and passive samplers exposed to different watershed irrigation sources

Water scarcity increases the likelihood of irrigating food crops with municipal wastewater that may pose potential dietary risks of regulated and non-regulated organic chemical uptake to edible plant tissues. Only a few studies have used high resolution mass spectrometry (HRMS) to assess the uptake of chemicals of concern into food crops. This study used non-target and suspect-screening analyses to compare total chemical features, tentatively identified chemicals (TICs), and EPA ToxCast chemicals in soybean plants and passive samplers exposed to five different irrigation sources that were collected from an agricultural watershed during mild drought conditions. Secondary-treated municipal wastewater effluent, two surface waters, two ground waters, and deionized municipal tap water were used for two hydroponic experiments: soybean roots and shoots and Composite Integrative Passive Samplers (CIPS) harvested after fourteen days of exposure and soybeans after fifty-six days. CIPS were sealed in separate glass amber jars to evaluate their efficacy to mimic chemical features, TICs, and ToxCast chemical uptake in plant roots, shoots, and beans. Total soybean biomass and water use were greatest for tap water, municipal wastewater, and surface water downstream of the municipal wastewater facility relative to groundwater samples and surface water collected upstream of the wastewater facility. ToxCast chemicals were ubiquitous across watershed irrigation sources in abundance, chemical use category, and number. Wastewater-exposed soybeans had the fewest extractable TICs in plant tissues of all irrigation sources. More ToxCast chemicals were identified in CIPS than extracted from irrigation sources by solid phase extraction. ToxCast chemicals in beans and CIPS were similar in number, chemical use category, and log Kow range. CIPS appear to serve as a useful surrogate for ToxCast chemical uptake in beans, the edible food product.

Non-targeted analysis with liquid chromatography - high resolution mass spectrometry for the identification of food packaging migrants

Potential contamination of food with chemicals migrating from food packaging is an important, yet under-investigated area of food safety. In this study, we examined chemicals migrating from common paper-based food packaging: pizza boxes and pizza box liners, butcher paper and liquid egg containers. Migration tests were conducted with a food simulant for 10 days, and migrated chemicals were identified with liquid chromatography (LC) - high resolution mass spectrometry (HRMS) with mass error < 3 ppm. HRMS identification was based on spectra and/or structure matching against commercial databases (MzCloud, ChemSpider, and Extractable and Leachable high resolution accurate mass (HRAM) database). Following HRMS identification, orthogonal LC retention information was utilized to further refine the data and reduce false positive findings. A model for calculating retention times (t_R) based on octanol-water partition coefficient (log K_ow) values was evaluated and applied for HRMS data refining. Using this approach, 153 migrated chemicals were identified, of which five were further confirmed with reference analytical standards. Additionally, amounts of bisphenol A and bisphenol S, the chemicals of toxicological concerns, were measured at the levels below the established regulatory limits for migration, indicating no/low risk to consumer's health. This study demonstrated the utility of LC-HRMS for confident identification of food packaging migrants.

Nontargeted screening method for veterinary drugs and their metabolites based on fragmentation characteristics from ultrahigh-performance liquid chromatography-high-resolution mass spectrometry

Nontargeted screening of both veterinary drugs and their metabolites is important for comprehensive safety evaluation of animal-derived foods. In this study, a novel nontargeted screening strategy was developed for veterinary drugs and their metabolites based on fragmentation characteristics from ultrahigh-performance liquid chromatography-high-resolution mass spectrometry. First, an in-house database of mass spectra including 3,710 veterinary drugs and their metabolites was constructed. Second, fragmentation characteristics of parent drugs and their metabolites in mass spectrometry were investigated and summarized. Then, a nontargeted screening procedure was established based on fragmentation characteristics to screen unknown parent drugs and their metabolites. Finally, the strategy was applied to 33 egg samples, and four veterinary drugs and three drug metabolites were determined and identified. These results showed that the developed strategy can realize suspect and nontargeted screening of veterinary drugs and their metabolites, and can also be applied to other animal-derived foods.

Recent Progress on Single-Molecule Detection Technologies for Food Safety

Rapid and sensitive detection technologies for food contaminants play vital roles in food safety. Due to the complexity of the food matrix and the trace amount distribution, traditional methods often suffer from unsatisfying accuracy, sensitivity, or specificity. In past decades, single-molecule detection (SMD) has emerged as a way to realize the rapid and ultrasensitive measurement with low sample consumption, showing a great potential in food contaminants detection. For instance, based on the nanopore technique, simple and effective methods for single-molecule analysis of food contaminants have been developed. To our knowledge, there has been a rare review that focuses on SMD techniques for food safety. The present review attempts to cover some typical SMD methods in food safety, including electrochemistry, optical spectrum, and atom force microscopy. Then, recent applications of these techniques for detecting food contaminants such as biotoxins, pesticides, heavy metals, and illegal additives are reviewed. Finally, existing research challenges and future trends of SMD in food safety are also tentatively proposed.

Is Our Natural Food Our Homeostasis? Array of a Thousand Effect-Directed Profiles of 68 Herbs and Spices

The beneficial effects of plant-rich diets and traditional medicines are increasingly recognized in the treatment of civilization diseases due to the abundance and diversity of bioactive substances therein. However, the important active portion of natural food or plant-based medicine is presently not under control. Hence, a paradigm shift from quality control based on marker compounds to effect-directed profiling is postulated. We investigated 68 powdered plant extracts (botanicals) which are added to food products in food industry. Among them are many plants that are used as traditional medicines, herbs and spices. A generic strategy was developed to evaluate the bioactivity profile of each botanical as completely as possible and to straightforwardly assign the most potent bioactive compounds. It is an 8-dimensional hyphenation of normal-phase high-performance thin-layer chromatography with multi-imaging by ultraviolet, visible and fluorescence light detection as well as effect-directed assay and heart-cut of the bioactive zone to orthogonal reversed-phase high-performance liquid chromato-graphy-photodiode array detection-heated electrospray ionization mass spectrometry. In the non-target, effect-directed screening via 16 different on-surface assays, we tentatively assigned more than 60 important bioactive compounds in the studied botanicals. These were antibacterials, estrogens, antiestrogens, androgens, and antiandrogens, as well as acetylcholinesterase, butyrylcholinesterase, α-amylase, α-glucosidase, β-glucosidase, β-glucuronidase, and tyrosinase inhibitors, which were on-surface heart-cut eluted from the bioautogram or enzyme inhibition autogram to the next dimension for further targeted characterization. This biological-physicochemical hyphenation is able to detect and control active mechanisms of traditional medicines or botanicals as well as the essentials of plant-based food. The array of 1,292 profiles (68 samples × 19 detections) showed the versatile bioactivity potential of natural food. It reveals how efficiently and powerful our natural food contributes to our homeostasis.

Application of non-target analysis to study the thermal transformation of malachite and leucomalachite green in brook trout and shrimp

The fate of malachite green and its main metabolite leucomalachite green during thermal treatment was examined in seafood (brook trout and white shrimp) using non-target analysis. Samples were extracted using QuEChERS and analyzed using liquid chromatography coupled with quadruple time of flight mass spectrometry. Malachite green levels were reduced in meat during boiling (∼40%), microwaving (64%), and canning (96%). Only microwaving was successful in significantly decreasing leucomalachite green levels in brook trout. The reduction percentages of the two target analytes were not significantly different in shrimp (mean fat content = 0.8 ± 0.3%) and in brook trout (mean fat content = 3.5 ± 1.7%), suggesting that a higher fat content may not affect the reduction of the more lipophilic leucomalachite green in these two matrices. Three transformation products were tentatively identified in the cooked tissues, resulting from the cleavage of the conjugated structure or through demethylation. Further research is needed to determine possible adverse health effects. The findings of this study show how non-target analysis can complement targeted methodologies in identifying and evaluating risks to human health.

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Non-target analysis was applied to study the fate of malachite/leucomalachite green.

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Thermal processing significantly reduced malachite green in seafood by up to 96%.

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Leucomalachite green levels were significantly reduced only after microwaving.

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Three transformation products were tentatively identified.

Data analysis strategies for the characterization of chemical contaminant mixtures. Fish as a case study

Thousands of chemicals are potentially contaminating the environment and food resources, covering a wide spectrum of molecular structures, physico-chemical properties, sources, environmental behavior and toxic profiles. Beyond the description of the individual chemicals, characterizing contaminant mixtures in related matrices has become a major challenge in ecological and human health risk assessments. Continuous analytical developments, in the fields of targeted (TA) and non-targeted analysis (NTA), have resulted in ever larger sets of data on associated chemical profiles. More than ever, the implementation of advanced data analysis strategies is essential to elucidate profiles and extract new knowledge from these large data sets. Specifically focusing on the data analysis step, this review summarizes the recent progress in integrating data analysis tools into TA and NTA workflows to address the challenging characterization of chemical mixtures in environmental and food matrices. As fish matrices are relevant in both aquatic pollution and consumer exposure perspectives, fish was chosen as the main theme to illustrate this review, although the present document is equally relevant to other food and environmental matrices. The key features of TA and NTA data sets were reviewed to illustrate the challenges associated with their analysis. Advanced filtering strategies to mine NTA data sets are presented, with a particular focus on chemical filters and discriminant analysis. Further, the applications of supervised and unsupervised multivariate analysis methods to characterize exposure to chemical mixtures, and their associated challenges, is discussed.

Chemical contaminants in canned food and can-packaged food: a review

Canning, as a preservation technique, is widely used to extend the shelf life as well as to maintain the quality of perishable foods. During the canning process, most of the microorganisms are killed, reducing their impact on food quality and safety. However, the presence of a range of undesirable chemical contaminants has been reported in canned foods and in relation to the canning process. The present review provides an overview of these chemical contaminants, including metals, polymeric contaminants and biogenic amine contaminants. They have various origins, including migration from the can materials, formation during the canning process, or contamination during steps required prior to canning (e.g. the disinfection step). Some other can-packaged foods (e.g. beverages or milk powder), which are not canned foods by definition, were also discussed in this review, as they have been frequently studied simultaneously with canned foods in terms of contamination. The occurrence of these contaminants, the analytical techniques involved, and the factors influencing the presence of these contaminants in canned food and can-packaged food are summarized and discussed.

Prediction of pesticide retention time in reversed-phase liquid chromatography using quantitative-structure retention relationship models: A comparative study of seven molecular descriptors datasets

Predicting chromatographic retention times of pesticides has become more and more important for suspect and non-target screening. Indeed, high-resolution mass spectrometry hyphenated (HRMS) to liquid chromatography (LC) are of growing interest for research and monitoring of pesticides, their metabolites and transformation products. The development of quantitative structure-retention relationship models require selecting the most adequate and best set of molecular descriptors and the best machine-learning algorithm. Here, we used seven molecular descriptor sets extracted from four well-known studies and applied them to roughly 800 pesticides and their chromatographic reversed-phase retention times. We used and optimized five different machine-learning algorithms with these descriptor sets to carry out predictions. Our results show that a support-vector machine regression algorithm with only eight molecular descriptors gave the best compromise between the number of molecular descriptors, processing time and model complexity to optimize prediction performance for this specific gradient LC method.

Identification of Erythromycin and Clarithromycin Metabolites Formed in Chicken Liver Microsomes Using Liquid Chromatography-High-Resolution Mass Spectrometry

Nontargeted analysis can be used for the rapid screening and confirmatory analysis of veterinary drugs and their metabolites, which are important for the comprehensive safety evaluation of animal-derived foods. Here, a novel nontargeted screening approach based on liquid chromatography coupled with electrospray ionization-high-resolution mass spectrometry (LC/ESI-HR-MS) was developed to determine erythromycin, clarithromycin, and their metabolites in chicken liver microsomes. Erythromycin and clarithromycin were incubated in vitro in the presence of NADPH for 60 min to generate metabolites in chicken liver microsomes. After the incubation, the supernatant was extracted using ultrasonic shaking, orbital shaking, and centrifugation before analysis using LC/ESI-HR-MS in positive ion mode on an Agilent Eclipse Plus C18 column (100 mm × 2.1 mm; i.d. 3.5 µm) with 0.1 percent formic acid-water and acetonitrile as the mobile phases for gradient elution at 0.4 mL/min. The results show that erythromycin can produce N-desmethyl-erythromycin A in chicken liver microsomes, but clarithromycin cannot produce N-desmethyl-clarithromycin in chicken liver microsomes. The N-desmethyl-erythromycin A and N-desmethyl-clarithromycin were tentatively identified in chicken liver microsomes using the established quick analytic method, which will provide a theoretical foundation for future research on pharmacokinetics and drug elimination in poultry.

Efficient Matrix Cleanup of Soft-Gel-Type Dietary Supplements for Rapid Screening of 92 Illegal Adulterants Using EMR-Lipid dSPE and UHPLC-Q/TOF-MS

An efficient matrix cleanup method was developed for the rapid screening of 92 illegal adulterants (25 erectile dysfunction drugs, 15 steroids, seven anabolic steroids, 12 antihistamines, 12 nonsteroidal anti-inflammatory drugs (NSAIDs), four diuretics, and 17 weight-loss drugs) in soft-gel-type supplements by ultra-high performance liquid chromatography-quadrupole/time of flight-mass spectrometry (UHPLC-Q/TOF-MS). As representative green chemistry methods, three sample preparation methods (dispersive liquid-liquid microextraction (DLLME), “quick, easy, cheap, effective, rugged, and safe” dispersive solid-phase extraction (QuEChERS-dSPE), and enhanced matrix removal-lipid (EMR-Lipid) dSPE) were evaluated for matrix removal efficiency, recovery rate, and matrix effect. In this study, EMR-Lipid dSPE was shown to effectively remove complicated matrix contents in soft-gels, compared to DLLME and QuEChERS-dSPE. For the rapid screening of a wide range of adulterants, extracted common ion chromatogram (ECIC) and neutral loss scan (NLS) based on specific common MS/MS fragments were applied to randomly collected soft-gel-type dietary supplement samples using UHPLC-Q/TOF-MS. Both ECICs and NLSs enabled rapid and simple screening of multi-class adulterants and could be an alternative to the multiple reaction monitoring (MRM) method. The developed method was validated in terms of limit of detection (LOD), precision, accuracy, recovery, and matrix effects. The range of LODs was 0.1–16 ng/g. The overall precision values were within 0.09–14.65%. The accuracy ranged from 81.6% to 116.6%. The recoveries and matrix effects of 92 illegal adulterants ranged within 16.9–119.4% and 69.8–114.8%, respectively. The established method was successfully applied to screen and identify 92 illegal adulterants in soft-gels. This method can be a promising tool for the high-throughput screening of various adulterants in dietary supplements and could be used as a more environmentally friendly routine analytical method for screening dietary supplements illegally adulterated with multi-class drug substances.

An Automated Methodology for Non-targeted Compositional Analysis of Small Molecules in High Complexity Environmental Matrices Using Coupled Ultra Performance Liquid Chromatography Orbitrap Mass Spectrometry

The life-critical matrices of air and water are among the most complex chemical mixtures that are ever encountered. Ultrahigh-resolution mass spectrometers, such as the Orbitrap, provide unprecedented analytical capabilities to probe the molecular composition of such matrices, but the extraction of non-targeted chemical information is impractical to perform via manual data processing. Automated non-targeted tools rapidly extract the chemical information of all detected compounds within a sample dataset. However, these methods have not been exploited in the environmental sciences. Here, we provide an automated and (for the first time) rigorously tested methodology for the non-targeted compositional analysis of environmental matrices using coupled liquid chromatography-mass spectrometric data. First, the robustness and reproducibility was tested using authentic standards, evaluating performance as a function of concentration, ionization potential, and sample complexity. The method was then used for the compositional analysis of particulate matter and surface waters collected from worldwide locations. The method detected >9600 compounds in the individual environmental samples, arising from critical pollutant sources, including carcinogenic industrial chemicals, pesticides, and pharmaceuticals among others. This methodology offers considerable advances in the environmental sciences, providing a more complete assessment of sample compositions while significantly increasing throughput.

Non-target bioanalytical eight-dimensional hyphenation including bioassay, heart-cut trapping, online desalting, orthogonal separations and mass spectrometry

It is still a challenge to discover and identify individual bioactive compounds directly in multicomponent mixtures. Current workflows are too tedious for routine use. Hence, the hyphenation of separation and detection techniques is a powerful tool to maximize the information obtained by a single sample run. A robust eight-dimensional (8D) hyphenation was developed. Orthogonal separations, biological assay detection, analyte trapping, desalting, and physico-chemical detections were arranged in the following order, i.e. 1) normal phase high-performance thin-layer chromatography (NP-HPTLC) separation, 2) Vis detection, 3) UV detection, 4) fluorescence detection (FLD), 5) bioassay for effect-directed analysis (EDA), 6) heart-cut trapping/desalting/elution to reversed phase high-performance liquid chromatography (RP-HPLC) separation, 7) photodiode array (PDA) and 8) mass spectrometry (MS) detection. For the first time, the hyphenation exploited online analyte trapping to desalt the eluted bioactive zone from the plate containing highly salted bioassay media. Subsequent valve switching guided the trapped analyte(s) to the main column, followed by multiple detection. As proof-of-principle, cinnamon samples were analyzed by NP-HPTLC-UV/Vis/FLD-EDA-RP-HPLC-PDA-MS, whereby a bioactive zone was separated into two distinct peaks detected by PDA and MS to be 2-methoxy cinnamaldehyde and cinnamaldehyde. The developed 8D hyphenation is applicable for routine, allowing the non-target high-throughput screening of complex samples for individual bioactive compounds.

Rapid screening of 70 colorants in dyeable foods by using ultra-high-performance liquid chromatography-hybrid quadrupole-Orbitrap mass spectrometry with customized accurate-mass database and mass spectral library

A rapid screening method of 70 colorants for regulatory control in dyeable foods was established using ultra-high-performance liquid chromatography-hybrid quadrupole-Orbitrap mass spectrometry (UHPLC-Q/Orbitrap MS) with customized accurate-mass database and mass spectral library. A rapid, high-throughput, and simple sample pretreatment condition with low reagent consumption and high recovery was developed on the basis of ultrasound-assisted extraction and dispersion solid-phase extraction. Rapid screening was conducted by comparing the experimentally measured exact mass of the parent and fragment ions, the isotope pattern, and the retention time with the accurate-mass database and by matching the acquired MS/MS spectra against the mass spectral library. The performance of the method was evaluated in terms of linearity, limits of detection, limits of quantitation, recovery, repeatability, reproducibility, and matrix effect. The proposed method was applied for simultaneous analysis of 70 colorants in seven kinds of dyeable foods, and it exhibited great potential for broad, sensitive, and reliable.

One-pot label-free dual-aptasensor as a chemiluminescent tool kit simultaneously detect adenosine triphosphate and chloramphenicol in foods

The chemiluminescence (CL) analysis based on label-free dual-aptasensor was developed for simultaneous detection of adenosine triphosphate (ATP) and chloramphenicol (CAP) in food. Magnetic microspheres and polystyrene microspheres used as separating and immobilizing carriers which immobilized the two different captured DNA, respectively. Then these carriers were put in the mixture of ATPs, CAPs, ATP-binding aptamers and CAP-binding aptamers to make one-pot label-free recognized interaction. The more ATP or CAP molecules binding their aptamers, the less aptamers left on the surface of carriers reducing the CL signals. The proposed aptasensor exhibited high selectivity and sensitivity for ATP and CAP with the limits of detection of 3.76 × 10^-8 moL/L and 2.48 × 10^-8 moL/L, respectively. Finally, this method is further validated by measuring the recovery of ATP/CAP spiked in three different food samples.

Nontargeted identification and predicted toxicity of new byproducts generated from UV treatment of water containing micropollutant 2-mercaptobenzothiazole

Comprehensive identification of byproducts including intermediate transformation products (TPs) of micropollutants in source water is challenging and paramount for assessment of drinking water quality and treatment technologies. Here, we have developed a nontargeted analysis strategy coupled with computational toxicity assessment to identify indistinguishable TPs including isomers with large differences in toxicity. The new strategy was applied to study the UV treatment of water containing micropollutant 2-mercaptobenzothiazole (2-MBT), and it enabled successful identification of a total of 22 organic TPs. Particularly, the structures of nine new TPs were identified for the first time; in addition, three isomers (P2, P3, and P4) were distinguished from the toxic contaminant 2-hydroxybenzothiazole (2-OH-BT). Computational assessments indicate that estrogenic activity of the three isomers (P2-P4) is higher than that of 2-OH-BT. Mass balance study shows that the 22 organic products accounted for 70% of the 2-MBT degraded, while 30% may degrade to inorganic products. Most TPs are resistant to UV photolysis. Computational toxicity assessment predicted the TPs to increase inhibition of human thyroperoxidase activity although they have lower aquatic toxicity compared to original 2-MBT. This study emphasizes the importance of monitoring the 2-MBT photodegradation products and the overall toxicity of finished water whose production included a UV light-based treatment process.

Strategies for data reduction in non-targeted screening analysis: The impact of sample variability for food safety applications

While analytical methods targeting specific compounds are critical for food safety, analytes excluded from the targeted list will not be identified. Non-targeted analyses (NTA) using LC/HR-MS complement these approaches by producing information-rich data sets where molecular formula can be generated for each detected compound; however, data mining can be labor intensive. Thus, we examined different NTA approaches to reduce the number of compounds needing further investigation, without relying on a suspect list or MS/MS database, both in single ingredient foods (i.e., oats) and more complex, oat-containing samples. We investigated inherent sample variability and utilized this information to build in-house databases for removing food compounds from sample data. While food databases were useful for data reduction, differential analysis was the most promising approach for single ingredient foods because it substantially reduced the number of features while retaining spiked QC compounds; however, a combination of approaches was necessary with greater sample complexity.

Untargeted Screening in a Case Control Study Using Apples as a Matrix

Untargeted screening using high resolution mass spectrometry (HRMS) is a promising approach for screening the food supply for contaminants, but the sheer amount of information inherent to the HRMS data set presents analytical challenges. Red apples, collected during the U.S. FDA's Total Diet Study, were studied to determine whether bioinformatic software can be used to distinguish spiked model compounds from those native to apples. A workflow was created, in which initial data sets of over 44,000 features in each of the two spiked samples were reduced by several orders of magnitude to a scale suitable for visual inspection. After visual inspection to address degeneracy and data quality, the final data sets contained 30 and 2 suspect compounds, respectively. To the best of our knowledge, this is the largest scale case-control study on food matrices to date and the first use of market basket samples as references in an untargeted screening study.

Technical Overview of Orbitrap High Resolution Mass Spectrometry and Its Application to the Detection of Small Molecules in Food (Update Since 2012)

Food safety and quality issues are becoming increasingly important and attract much attention, requiring the development of better analytical platforms. For example, high-resolution (especially Orbitrap) mass spectrometry simultaneously offers versatile functions such as targeted/non-targeted screening while providing qualitative and quantitative information on an almost unlimited number of analytes to facilitate routine analysis and even allows for official surveillance in the food field. This review covers the current state of Orbitrap mass spectrometry (OMS) usage in food analysis based on research reported in 2012-2019, particularly highlighting the technical aspects of OMS application and the achievement of OMS-based screening and quantitative analysis in the food field. The gained insights enhance our understanding of state-of-the-art high-resolution mass spectrometry and highlight the challenges and directions of future research.

Miniaturized liquid chromatography applied to the analysis of residues and contaminants in food: A review

The humankind is pretty dependent on food to control several biological processes into the organism. As the world population increases, the demand for foodstuffs follows the same trend claiming for a high food production situation. For this reason, a substantial amount of chemicals is used in agriculture and livestock husbandries every year, enhancing the likelihood of contaminated foodstuffs being commercialized. This outlook becomes a public health concern; thus, the governmental regulatory agencies impose laws to control the residues and contaminants in food matrices. Currently, one of the most important analytical techniques to perform it is LC. Despite its already recognized effectiveness, it is often time consuming and requires significant volumes of reagents, which are transformed into toxic waste. In this context, miniaturized LC modes emerge as a greener and more effective analytical technique. They have remarkable advantages, including higher sensitivity, lower sample amount, solvent and stationary phase requirements, and more natural coupling to MS. In this review, most of the critical characteristics of them are discussed, focusing on the benchtop instruments and their related analytical columns. Additionally, a discussion regarding the last 10 years of publications reporting miniaturized LC application for the analysis of natural and industrial food samples is categorized. The main chemical classes as applied in the crops are highlighted, including pesticides, veterinary drugs, and mycotoxins.

Preliminary Study to Develop an Alternative Method for the Non-targeted Determination of Xenobiotics in Food by Means of Ultra High Performance Liquid Chromatography Coupled to High Resolution and Accuracy Mass Spectrometry

This preliminary study describes the use of high resolution and accuracy mass spectrometry techniques combined with new generation chemical software products for detecting and identifying contaminants in food commodities. As a first step, the extracts of routine target analysis samples (obtained in our official laboratory responsible for food residues control) were acquired and processed with this method in order to search unknown and non-targeted contaminants in food. In order to verify the feasibility of the presented method, the research has been firstly addressed to untargeted pesticides and their metabolites in stone fruits commodities and tomatoes. The differential analysis carried with Compound Discoverer 2.0 between the investigated unknown sample and the blank matrix sample allowed to remove all the matrix molecular components; Aggregated Computational Toxicology Resource (ACToR) helped to understand and predict chemical interpretation of substances. The acquisition in FullScan-AIF and FullScan-ddMS2 allowed the clear detection and identification of isobaric compounds such as quinalphos and phoxim. In order to verify that the proposed method is suitable to the scope of application, the main points of SANTE/11813/2017 Document have been followed. The results demonstrate that no false positives and no false negatives have been detected from the analysis of samples spiked with 55 pesticides at 0.010 and 0.10 mg kg−1. This preliminary study has been also tested with a Proficiency Test (EUPT-FV-SM08) and, according to EUPT-FV-SM08 Final Report, our laboratory has been included in the 67% (56) that clearly detected over 70% pesticides. Finally, this method has been extended to other matrices and contaminants.