Non-targeted analysis of unexpected food contaminants using LC-HRMS

Toxicity of soil leaching liquor from coking plant in developmental zebrafish embryos/larvae model

The coking industry in China is the largest coke supplier in the world. Contaminated soil in industrial areas poses a serious threat to human and ecosystems. Most of the studies investigated the toxicity of soil from coking plant on soil microorganisms, while the toxic effects of soil leaching liquor on aquatics are limited. In this study, the composition of soil leaching liquor from a coking plant in Taiyuan (TY) was analyzed, and the developmental toxicity on zebrafish was evaluated. The results showed that a total of 91 polycyclic aromatic hydrocarbons were detected in the leaching liquor, followed by phenols and benzene series. The leaching liquor induced developmental impairment in zebrafish larvae, including delayed incubation, deficits in locomotor behavior, vascular and cardiac dysplasia, and impaired neurodevelopment. The results of metabolomics analysis showed that TY soil leaching liquor induced significant metabolic profile disturbances in zebrafish embryos/larvae. The developmental toxicity of the leaching liquor metabolic disorders may be associated with the leaching liquor-induced abnormalities in zebrafish embryonic development. Metabolic pathways were identified by arginine and proline metabolism, phosphotransferase system, starch and sucrose metabolism, steroid biosynthesis, beta-alanine metabolism, and nucleotide metabolism pathways.

A Support Vector Machine-Assisted Metabolomics Approach for Non-Targeted Screening of Multi-Class Pesticides and Veterinary Drugs in Maize

The contamination risks of plant-derived foods due to the co-existence of pesticides and veterinary drugs (P&VDs) have not been fully understood. With an increasing number of unexpected P&VDs illegally added to foods, it is essential to develop a non-targeted screening method for P&VDs for their comprehensive risk assessment. In this study, a modified support vector machine (SVM)-assisted metabolomics approach by screening eligible variables to represent marker compounds of 124 multi-class P&VDs in maize was developed based on the results of high-performance liquid chromatography-tandem mass spectrometry. Principal component analysis and orthogonal partial least squares discriminant analysis indicate the existence of variables with obvious inter-group differences, which were further investigated by S-plot plots, permutation tests, and variable importance in projection to obtain eligible variables. Meanwhile, SVM recursive feature elimination under the radial basis function was employed to obtain the weight-squared values of all the variables ranging from large to small for the screening of eligible variables as well. Pairwise t-tests and fold changes of concentration were further employed to confirm these eligible variables to represent marker compounds. The results indicate that 120 out of 124 P&VDs can be identified by the SVM-assisted metabolomics method, while only 109 P&VDs can be found by the metabolomics method alone, implying that SVM can promote the screening accuracy of the metabolomics method. In addition, the method's practicability was validated by the real contaminated maize samples, which provide a bright application prospect in non-targeted screening of contaminants. The limits of detection for 120 P&VDs in maize samples were calculated to be 0.3~1.5 µg/kg.

Recent advances and challenges in the analysis of natural toxins

Natural toxins (NTs) are poisonous secondary metabolites produced by living organisms developed to ward off predators. Especially low molecular weight NTs (MW<∼1 kDa), such as mycotoxins, phycotoxins, and plant toxins, are considered an important and growing food safety concern. Therefore, accurate risk assessment of food and feed for the presence of NTs is crucial. Currently, the analysis of NTs is predominantly performed with targeted high pressure liquid chromatography tandem mass spectrometry (HPLC-MS/MS) methods. Although these methods are highly sensitive and accurate, they are relatively expensive and time-consuming, while unknown or unexpected NTs will be missed. To overcome this, novel on-site screening methods and non-targeted HPLC high resolution mass spectrometry (HRMS) methods have been developed. On-site screening methods can give non-specialists the possibility for broad "scanning" of potential geographical regions of interest, while also providing sensitive and specific analysis at the point-of-need. Non-targeted chromatography-HRMS methods can detect unexpected as well as unknown NTs and their metabolites in a lab-based approach. The aim of this chapter is to provide an insight in the recent advances, challenges, and perspectives in the field of NTs analysis both from the on-site and the laboratory perspective.

Innovative non-targeted screening approach using High-resolution mass spectrometry for the screening of organic chemicals and identification of specific tracers of soil and dust exposure in children

Environmental contamination through direct contact, ingestion and inhalation are common routes of children's exposure to chemicals, in which through indoor and outdoor activities associated with common hand-to-mouth, touching objects, and behavioral tendencies, children can be susceptible and vulnerable to organic contaminants in the environment. The objectives of this study were the screening and identification of a wide range of organic contaminants in indoor dust, soil, food, drinking water, and urine matrices (N = 439), prioritizing chemicals to assess children's environmental exposure, and selection of unique tracers of soil and dust ingestion in young children by non-targeted analysis (NTA) using Q-Exactive Orbitrap followed data processing by the Compound Discoverer (v3.3, SP2). Chemical features were first prioritized based on their predominant abundance (peak area>500,000), detection frequency (in >50% of the samples), available information on their uses and potential toxicological effects. Specific tracers of soil and dust exposure in children were selected in this study including Tripropyl citrate and 4-Dodecylbenzenesulfonic acid. The criteria for selection of the tracers were based on their higher abundance, detection frequency, unique functional uses, measurable amounts in urine (suitable biomarker), and with information on gastrointestinal absorption, metabolism, and excretion, and were further confirmed by authentic standards. We are proposing for the first time suitable unique tracers for dust ingestion by children.

Improving predictions of compound amenability for liquid chromatography-mass spectrometry to enhance non-targeted analysis

Mass-spectrometry-based non-targeted analysis (NTA), in which mass spectrometric signals are assigned chemical identities based on a systematic collation of evidence, is a growing area of interest for toxicological risk assessment. Successful NTA results in better identification of potentially hazardous pollutants within the environment, facilitating the development of targeted analytical strategies to best characterize risks to human and ecological health. A supporting component of the NTA process involves assessing whether suspected chemicals are amenable to the mass spectrometric method, which is necessary in order to assign an observed signal to the chemical structure. Prior work from this group involved the development of a random forest model for predicting the amenability of 5517 unique chemical structures to liquid chromatography-mass spectrometry (LC-MS). This work improves the interpretability of the group's prior model of the same endpoint, as well as integrating 1348 more data points across negative and positive ionization modes. We enhance interpretability by feature engineering, a machine learning practice that reduces the input dimensionality while attempting to preserve performance statistics. We emphasize the importance of interpretable machine learning models within the context of building confidence in NTA identification. The novel data were curated by the labeling of compounds as amenable or unamenable by expert curators, resulting in an enhanced set of chemical compounds to expand the applicability domain of the prior model. The balanced accuracy benchmark of the newly developed model is comparable to performance previously reported (mean CV BA is 0.84 vs. 0.82 in positive mode, and 0.85 vs. 0.82 in negative mode), while on a novel external set, derived from this work's data, the Matthews correlation coefficients (MCC) for the novel models are 0.66 and 0.68 for positive and negative mode, respectively. Our group's prior published models scored MCC of 0.55 and 0.54 on the same external sets. This demonstrates appreciable improvement over the chemical space captured by the expanded dataset. This work forms part of our ongoing efforts to develop models with higher interpretability and higher performance to support NTA efforts.

Identification of transformation products during Doxylamine chloramination for NDMA mitigation

N-nitrosodimethylamine (NDMA) is a disinfection byproduct that forms at the presence of an organic nitrogen precursor. Doxylamine, an antihistaminic pharmaceutical, is a precursor of NDMA and has been shown to form NDMA in the presence of chloramine. In this study, the effect of Doxylamine as an NDMA precursor has been further studied during chloramination. The end product and byproducts during chloramination were investigated using a high-resolution mass spectrometer by taking samples at different time intervals. Results suggest that NDMA is not the only end product forming during chloramination of Doxylamine and several transformation products that do not end up as NDMA may form. A group of these transformation products have been selected based on their relative amounts during chloramination with time and notated as Focus Tentative Transformation Products (FTTPn). The identification of these byproducts will make it easier to study the conditions during chloramination that may favour these 'known' transformation products with the use of less sophisticated analytical instruments. Then, it might lead to the establishment of chloramination protocols that will minimise the formation of NDMA from its precursors.

Suspect Screening Analysis of Pooled Human Serum Samples Using GC × GC/TOF-MS

Humans interact with thousands of chemicals. This study aims to identify substances of emerging concern and in need of human health risk evaluations. Sixteen pooled human serum samples were constructed from 25 individual samples each from the National Institute of Environmental Health Sciences' Clinical Research Unit. Samples were analyzed using gas chromatography (GC) × GC/time-of-flight (TOF)-mass spectrometry (MS) in a suspect screening analysis, with follow-up confirmation analysis of 19 substances. A standard reference material blood sample was also analyzed through the confirmation process for comparison. The pools were stratified by sex (female and male) and by age (≤45 and >45). Publicly available information on potential exposure sources was aggregated to annotate presence in serum as either endogenous, food/nutrient, drug, commerce, or contaminant. Of the 544 unique substances tentatively identified by spectral matching, 472 were identified in females, while only 271 were identified in males. Surprisingly, 273 of the identified substances were found only in females. It is known that behavior and near-field environments can drive exposures, and this work demonstrates the existence of exposure sources uniquely relevant to females.

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.

Nontargeted Analysis in Tobacco Research: Challenges and Opportunities

Tobacco products are evolving at a pace that has outstripped tobacco control, leading to a high prevalence of tobacco use in the population. Researchers have been tirelessly developing suitable techniques to assess these products' emissions, toxicity, and public health impact. The nonclinical testing of tobacco products to assess the chemical profile of emissions is needed for evidence-based regulations. This testing has largely relied on targeted analytical methods that focus on constituent lists that may fall short in determining the toxicity of newly designed tobacco products. Nontargeted analysis (NTA), or the process of identifying and quantifying compounds within a complex matrix without prior knowledge of its chemical composition, is a promising technique for tobacco regulation, but it is not without challenges. The lack of standardized methods for sample generation, sample preparation, chromatographic separation, compound identification, and data analysis and reporting must be addressed so that the quality and reproducibility of the data generated by NTA can be benchmarked. This review discusses the challenges and highlights the opportunities of NTA in studying tobacco product constituents and emissions.

Critical Assessment of the Chemical Space Covered by LC-HRMS Non-Targeted Analysis

Non-targeted analysis (NTA) has emerged as a valuable approach for the comprehensive monitoring of chemicals of emerging concern (CECs) in the exposome. The NTA approach can theoretically identify compounds with diverse physicochemical properties and sources. Even though they are generic and have a wide scope, non-targeted analysis methods have been shown to have limitations in terms of their coverage of the chemical space, as the number of identified chemicals in each sample is very low (e.g., ≤5%). Investigating the chemical space that is covered by each NTA assay is crucial for understanding the limitations and challenges associated with the workflow, from the experimental methods to the data acquisition and data processing techniques. In this review, we examined recent NTA studies published between 2017 and 2023 that employed liquid chromatography-high-resolution mass spectrometry. The parameters used in each study were documented, and the reported chemicals at confidence levels 1 and 2 were retrieved. The chosen experimental setups and the quality of the reporting were critically evaluated and discussed. Our findings reveal that only around 2% of the estimated chemical space was covered by the NTA studies investigated for this review. Little to no trend was found between the experimental setup and the observed coverage due to the generic and wide scope of the NTA studies. The limited coverage of the chemical space by the reviewed NTA studies highlights the necessity for a more comprehensive approach in the experimental and data processing setups in order to enable the exploration of a broader range of chemical space, with the ultimate goal of protecting human and environmental health. Recommendations for further exploring a wider range of the chemical space are given.

Non-targeted analysis (NTA) and suspect screening analysis (SSA): a review of examining the chemical exposome

Non-targeted analysis (NTA) and suspect screening analysis (SSA) are powerful techniques that rely on high-resolution mass spectrometry (HRMS) and computational tools to detect and identify unknown or suspected chemicals in the exposome. Fully understanding the chemical exposome requires characterization of both environmental media and human specimens. As such, we conducted a review to examine the use of different NTA and SSA methods in various exposure media and human samples, including the results and chemicals detected. The literature review was conducted by searching literature databases, such as PubMed and Web of Science, for keywords, such as "non-targeted analysis", "suspect screening analysis" and the exposure media. Sources of human exposure to environmental chemicals discussed in this review include water, air, soil/sediment, dust, and food and consumer products. The use of NTA for exposure discovery in human biospecimen is also reviewed. The chemical space that has been captured using NTA varies by media analyzed and analytical platform. In each media the chemicals that were frequently detected using NTA were: per- and polyfluoroalkyl substances (PFAS) and pharmaceuticals in water, pesticides and polyaromatic hydrocarbons (PAHs) in soil and sediment, volatile and semi-volatile organic compounds in air, flame retardants in dust, plasticizers in consumer products, and plasticizers, pesticides, and halogenated compounds in human samples. Some studies reviewed herein used both liquid chromatography (LC) and gas chromatography (GC) HRMS to increase the detected chemical space (16%); however, the majority (51%) only used LC-HRMS and fewer used GC-HRMS (32%). Finally, we identify knowledge and technology gaps that must be overcome to fully assess potential chemical exposures using NTA. Understanding the chemical space is essential to identifying and prioritizing gaps in our understanding of exposure sources and prior exposures. IMPACT STATEMENT: This review examines the results and chemicals detected by analyzing exposure media and human samples using high-resolution mass spectrometry based non-targeted analysis (NTA) and suspect screening analysis (SSA).

Evaluating non-targeted analysis methods for chemical characterization of organic contaminants in different matrices to estimate children's exposure

BACKGROUND

Children are vulnerable to environmental exposure of contaminants due to their small size, lack of judgement skills, as well as their proximity to dust, soil, and other environmental sources. A better understanding about the types of contaminants that children are exposed to or how their bodies retain or process these compounds is needed.

OBJECTIVE

In this study, we have implemented and optimized a methodology based on non-targeted analysis (NTA) to characterize chemicals in dust, soil, urine, and in the diet (food and drinking water) of infant populations.

METHODS

To evaluate potential toxicological concerns associated with chemical exposure, families with children between 6 months and 6 years of age from underrepresented groups were recruited in the greater Miami area. Samples of soil, indoor dust, food, water, and urine were provided by the caregivers, prepared by different techniques (involving online SPE, ASE, USE, QuEChERs), and analyzed by liquid chromatography-high resolution mass spectrometry (LC-HRMS). Data post-processing was performed using the small molecule structure identification software, Compound Discoverer (CD) 3.3, and identified features were plotted using Kendrick mass defect plot and Van Krevelen diagrams to show unique patterns in different samples and regions of anthropogenic compound classifications.

RESULTS

The performance of the NTA workflow was evaluated using quality control standards in terms of accuracy, precision, selectivity, and sensitivity, with an average of 98.2%, 20.3%, 98.4% and 71.1%, respectively. Sample preparation was successfully optimized for soil, dust, water, food, and urine. A total of 30, 78, 103, 20 and 265 annotated features were frequently identified (detection frequency >80%) in the food, dust, soil, water, and urine samples, respectively. Common features detected in each matrix were prioritized and classified, providing insight on children's exposure to organic contaminants of concern and their potential toxicities.

IMPACT STATEMENT

Current methods to assess the ingestion of chemicals by children have limitations and are generally restricted by specific classes of targeted organic contaminants of interest. This study offers an innovative approach using non-targeted analysis for the comprehensive screening of organic contaminants that children are exposed to through dust, soil, and diet (drinking water and food).

A Chemical Characterization Workflow for Nontargeted Analysis of Complex Extracts from Polymer Based Medical Device Using High Resolution LC/MS

The chemical characterization of extractables and leachables (E&Ls) is an important aspect of biosafety and biocompatibility assessment in medical device industry. The advent of the body-contact use of medical devices in patient treatment has introduced a potential source for extractables and leachables as these medical devices are comprised of various polymeric materials. Several industry working groups, the FDA and USP, have recognized the guidance for chemical characterizations and nontargeted analysis of medical device extracts, such as ISO 10993-18:2020. The MS application of nontargeted analysis has played a critical role in understanding the E&Ls from medical device extracts. However, there have been very few reports about the MS based workflow with nontargeted analysis for medical device extracts and there is little guidance about the exact methodologies which should be used, even though there is an urgent need for a clearly defined process for the identification of medical device extracts. In this study, we demonstrated an analytical LC/MS (liquid chromatography/mass spectrometry) workflow using high resolution Exploris120 Orbitrap instrument for data acquisition and Compound Discoverer 3.3 intelligent software for data processing to profile the polymer related E&Ls from a balloon dilation catheter device extracted with 40% ethanol. An E&L ID workflow combining LC separation, data-informed MS acquisition strategy, MS information mining (including adduct ions, MS information from both electrospray ionization (ESI) (+) and ESI (-), in-source fragmentation, common fragment ions (CFIs), common neutral losses (CNLs), and in silico MS simulation was described with intelligent software processing and manual data interpretation. The workflow developed in this study was proven to be effective to provide a comprehensive profile of polymer related degradation products, polymer impurities and additives including surfactants, UV curing agent, antioxidants, and plasticizers for the device analyzed. The classification of E&L compounds using CFIs and CNLs was very effective to facilitate the identification of polymer related impurities and extract the polymer related impurities with common structures in a large data result set.

Non-targeted metabolomics of moldy wheat by ultra-performance liquid chromatography - quadrupole time-of-flight mass spectrometry

Introduction

As one of the staple foods for the world's major populations, the safety of wheat is critical in ensuring people's wellbeing. However, mildew is one of the prevalent safety issues that threatens the quality of wheat during growth, production, and storage. Due to the complex nature of the microbial metabolites, the rapid identification of moldy wheat is challenging.

Methods

In this research, identification of moldy wheat samples was studied using ultra-performance liquid chromatography - quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) coupled with chemometrics. The non-targeted PCA model for identifying moldy wheat from normal wheat was established by using previously established compounds database of authentic wheat samples. The partial least squares-discriminant analysis (PLS-DA) was performed.

Results and discussion

By optimizing the model parameters, correct discrimination of the moldy wheat as low as 5% (w/w) adulteration level could be achieved. Differential biomarkers unique to moldy wheat were also extracted to identify between the moldy and authentic wheat samples. The results demonstrated that the chemical information of wheat combined with the existing PCA model could efficiently discriminate between the constructed moldy wheat samples. The study offered an effective method toward screening wheat safety.

Mass Spectrometric Methods for Non-Targeted Screening of Metabolites: A Future Perspective for the Identification of Unknown Compounds in Plant Extracts

Phyto products are widely used in natural products, such as medicines, cosmetics or as so-called “superfoods”. However, the exact metabolite composition of these products is still unknown, due to the time-consuming process of metabolite identification. Non-target screening by LC-HRMS/MS could be a technique to overcome these problems with its capacity to identify compounds based on their retention time, accurate mass and fragmentation pattern. In particular, the use of computational tools, such as deconvolution algorithms, retention time prediction, in silico fragmentation and sophisticated search algorithms, for comparison of spectra similarity with mass spectral databases facilitate researchers to conduct a more exhaustive profiling of metabolic contents. This review aims to provide an overview of various techniques and tools for non-target screening of phyto samples using LC-HRMS/MS.

Rapid and Reliable Data Treatment for the Control of Food Chemical Contaminants by LC-HRMS

Liquid chromatography-high resolution mass spectrometry (LC-HRMS) is considered an unavoidable extension of low-resolution LC-MS/MS that stretches the capabilities of multi-residue analysis of chemical contaminants in food. However, LC-HRMS acquisitions generate a massive amount of information available for data processing with supplier software that still miss critical calculation features and adapted reporting tools. Consequently, routine laboratories are still reluctant to switch from LC-MS/MS to LC-HRMS, the latter is still perceived as a cumbersome and demanding technology. In that context, we propose a four-step LC-HRMS workflow to speed-up data processing in situations of multi-residue multi-matrix analysis with the goal to maximize the time spent on data interpretation rather than on data formatting. The first three steps of the workflow imply specific settings on the Orbitrap HRMS associated software (TraceFinder^TM) while the fourth step is the novelty i.e. a newly coded R-script capable to translate a raw export file into a comprehensive .xlsx report file in a few seconds. As recommended by various international guidelines and in some official methods, standard addition-based applications are fully embedded in this reporting tool whilst still being the main bottleneck of supplier's software. The reporting tool also allows appropriate data formatting, filtering, and color-coding options to provide a clear picture of compounds being detected or not, and those requiring specific attention due to unmet quality control criteria as required by European legislation (European Commission SANTE 11312/2021). It is hoped that additional functionalities compatible with R scripts will be soon fully embedded in the supplier's software for easier data interpretation and reporting.

Metabolomics Approach on Non-Targeted Screening of 50 PPCPs in Lettuce and Maize

The metabolomics approach has proved to be promising in achieving non-targeted screening for those unknown and unexpected (U&U) contaminants in foods, but data analysis is often the bottleneck of the approach. In this study, a novel metabolomics analytical method via seeking marker compounds in 50 pharmaceutical and personal care products (PPCPs) as U&U contaminants spiked into lettuce and maize matrices was developed, based on ultrahigh-performance liquid chromatography-tandem mass spectrometer (UHPLC-MS/MS) output results. Three concentration groups (20, 50 and 100 ng mL-1) to simulate the control and experimental groups applied in the traditional metabolomics analysis were designed to discover marker compounds, for which multivariate and univariate analysis were adopted. In multivariate analysis, each concentration group showed obvious separation from other two groups in principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) plots, providing the possibility to discern marker compounds among groups. Parameters including S-plot, permutation test and variable importance in projection (VIP) in OPLS-DA were used for screening and identification of marker compounds, which further underwent pairwise t-test and fold change judgement for univariate analysis. The results indicate that marker compounds on behalf of 50 PPCPs were all discovered in two plant matrices, proving the excellent practicability of the metabolomics approach on non-targeted screening of various U&U PPCPs in plant-derived foods. The limits of detection (LODs) for 50 PPCPs were calculated to be 0.4~2.0 µg kg-1 and 0.3~2.1 µg kg-1 in lettuce and maize matrices, respectively.

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.

Current Role of Mass Spectrometry in the Determination of Pesticide Residues in Food

The extensive use of pesticides represents a risk to human health. Consequently, legal frameworks have been established to ensure food safety, including control programs for pesticide residues. In this context, the performance of analytical methods acquires special relevance. Such methods are expected to be able to determine the largest number of compounds at trace concentration levels in complex food matrices, which represents a great analytical challenge. Technical advances in mass spectrometry (MS) have led to the development of more efficient analytical methods for the determination of pesticides. This review provides an overview of current analytical strategies applied in pesticide analysis, with a special focus on MS methods. Current targeted MS methods allow the simultaneous determination of hundreds of pesticides, whereas non-targeted MS methods are now applicable to the identification of pesticide metabolites and transformation products. New trends in pesticide analysis are also presented, including approaches for the simultaneous determination of pesticide residues and other food contaminants (i.e., mega-methods), or the recent application of techniques such as ion mobility–mass spectrometry (IM–MS) for this purpose.

Parallel Operation of Electron Ionization and Chemical Ionization for GC-MS Using a Single TOF Mass Analyzer

This work describes a novel mass spectrometer coupled to gas chromatography (GC-MS) that simultaneously displays the mass spectral information of electron (EI)- and chemical ionization (CI)-generated ion populations for a single chromatographic peak. After GC separation, the eluent is equally split and supplied in parallel to an EI and a novel CI source, both operating continuously. Precise switching of the ion optics provides the exact timing to consecutively extract the respective ion population from both sources and transfer them into a time-of-flight (TOF) mass analyzer. This technique enables the acquisition of complementary information from both ion populations (EI and CI) within a single chromatographic run and with sufficient data points to retain the chromatographic fidelity. The carefully designed GC transfer setup, fast ion optical switching, and synchronized TOF data acquisition system provide an automatic and straightforward spectral alignment of two ion populations. With an eluent split ratio of about 50% between the two ion sources, instrument detection limits of <40 fg on the column (octafluoronaphthalene) for the EI and <2 pg (benzophenone) for the CI source were obtained. The system performance and the additional analytical value for compound identification are demonstrated by means of different common GC standard mixtures and a commercial perfume sample of unknown composition.

Chemical Characterization and Non-targeted Analysis of Medical Device Extracts: A Review of Current Approaches, Gaps, and Emerging Practices

The developers of medical devices evaluate the biocompatibility of their device prior to FDA's review and subsequent introduction to the market. Chemical characterization, described in ISO 10993-18:2020, can generate information for toxicological risk assessment and is an alternative approach for addressing some biocompatibility end points (e.g., systemic toxicity, genotoxicity, carcinogenicity, reproductive/developmental toxicity) that can reduce the time and cost of testing and the need for animal testing. Additionally, chemical characterization can be used to determine whether modifications to the materials and manufacturing processes alter the chemistry of a patient-contacting device to an extent that could impact device safety. Extractables testing is one approach to chemical characterization that employs combinations of non-targeted analysis, non-targeted screening, and/or targeted analysis to establish the identities and quantities of the various chemical constituents that can be released from a device. Due to the difficulty in obtaining a priori information on all the constituents in finished devices, information generation strategies in the form of analytical chemistry testing are often used. Identified and quantified extractables are then assessed using toxicological risk assessment approaches to determine if reported quantities are sufficiently low to overcome the need for further chemical analysis, biological evaluation of select end points, or risk control. For extractables studies to be useful as a screening tool, comprehensive and reliable non-targeted methods are needed. Although non-targeted methods have been adopted by many laboratories, they are laboratory-specific and require expensive analytical instruments and advanced technical expertise to perform. In this Perspective, we describe the elements of extractables studies and provide an overview of the current practices, identified gaps, and emerging practices that may be adopted on a wider scale in the future. This Perspective is outlined according to the steps of an extractables study: information gathering, extraction, extract sample processing, system selection, qualification, quantification, and identification.

Pesticide residue intake from fruits and vegetables and alterations in the serum metabolome of women undergoing infertility treatment

BACKGROUND

Pesticide exposure is linked to a myriad of negative health effects; however, the mechanisms underlying these associations are less clear. We utilized metabolomics to describe the alterations in the serum metabolome associated with high and low pesticide residue intake from fruits and vegetables (FVs), the most common route of exposure in humans.

METHODS

This analysis included 171 women undergoing in vitro fertilization who completed a validated food frequency questionnaire and provided a serum sample during controlled ovarian stimulation (2007-2015). FVs were categorized as high or low-to-moderate pesticide residue using a validated method based on pesticide surveillance data from the USDA. We conducted untargeted metabolic profiling using liquid chromatography with high-resolution mass spectrometry and two chromatography columns. We used multivariable generalized linear models to identified metabolic features (p < 0.005) associated with high and low-to-moderate pesticide residue FV intake, followed by enriched pathway analysis.

RESULTS

We identified 50 and 109 significant features associated with high pesticide residue FV intake in the C18 negative and HILIC positive columns, respectively. Additionally, we identified 90 and 62 significant features associated with low-to-moderate pesticide residue FV intake in the two columns, respectively. Four metabolomic pathways were associated with intake of high pesticide residue FVs including those involved in energy, vitamin, and enzyme metabolism. 12 pathways were associated with intake of low-to-moderate pesticide residue FVs including cellular receptor, energy, intercellular signaling, lipid, vitamin, and xenobiotic metabolism. One energy pathway was associated with both high and low-to-moderate pesticide residue FVs.

CONCLUSIONS

We identified limited overlap in the pathways associated with intake of high and low-to-moderate pesticide residue FVs, which supports findings of disparate health effects associated with these two exposures. The identified pathways suggest there is a balance between the dietary antioxidant intake associated with FVs intake and heightened oxidative stress as a result of dietary pesticide exposure.

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.

Evaluation of different extractions for the metabolite identification of malachite green in brook trout and shrimp

Applications of mass spectrometry-based metabolomics in food science have developed fast in the last decade. Sample preparation and data processing are critical in non-target/metabolomic workflows but there is currently no standardized protocol for the development of these methods. The impact of data processing parameters or the inclusion of a different matrix is not often taken into account during the selection of an extraction. Thus, this study aimed to investigate the impact of different extractions, e.g., QuEChERS, and data processing on the determination of malachite green metabolites in two different organisms, brook trout and shrimp. The results obtained confirm the need for a harmonized approach for the validation of non-target workflows, as depending on the comparison criteria, the matrix, the mode of ionization or data processing, a different extraction could be chosen. This study also identified for the first time des-methylated leucomalachite green as another metabolite in the two organisms.

Metabolomics-based non-targeted screening analysis of 34 PPCPs in bovine and piscine muscles

The metabolomics-based analytical strategy has showed superiority on the non-targeted screening of contaminants, especially for unknown and unexpected (U&U) contaminants in the field of food safety, but data analysis is often the bottleneck of the strategy. In this study, a novel metabolomics-based analytical method via searching for marker compounds was developed on the basis of ultrahigh-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) results to accurately, rapidly and comprehensively achieve the non-targeted screening of 34 pharmaceutical and personal care products (PPCPs) as U&U contaminants spiked in bovine and piscine muscle matrices. Three concentration groups (20, 50 and 100 ng mL^-1) were intentionally designed to simulate the control and experimental groups for the discovery of marker compounds, for which multivariate and univariate analyses were adopted. In multivariate analysis, each concentration group was fully separated from the other two groups in PCA and OPLS-DA plots, laying a foundation to distinguish marker compounds among groups. The S-plot, permutation and variable importance in projection (VIP) in OPLS-DA were employed to screen and identify marker compounds, which were further verified by pairwise t-test and fold change judgement in univariate analysis. The results indicate that 34 PPCPs spiked in two muscle matrices were all identified as marker compounds, proving the validity and practicability of this novel metabolomics-based non-targeted screening method, which will exhibit great superiority and broad application prospects, especially in the face of massive PPCPs and various animal matrices in the field of food safety control. In addition, the limits of detection (LODs) for 34 PPCPs were calculated to be 0.2-2.6 μg kg^-1 and 0.3-2.1 μg kg^-1 in bovine and piscine muscle matrices, respectively.

Sample preparation techniques for suspect and non-target screening of emerging contaminants

The progress in sensitivity and resolution in mass spectrometers in recent years provides the possibility to detect a broad range of organic compounds in a single procedure. For this reason, suspect and non-target screening techniques are gaining attention since they enable the detection of hundreds of known and unknown emerging contaminants in various matrices of environmental, food and human sources. Sample preparation is a critical step before analysis as it can significantly affect selectivity, sensitivity and reproducibility. The lack of generic sample preparation protocols is obvious in this fast-growing analytical field, and most studies use those of traditional targeted analysis methods. Among them, solvent extraction and solid phase extraction (SPE) are widely used to extract emerging contaminants from solid and liquid sample types, respectively. Sequential solvent extraction and a combination of different SPE sorbents can cover a broad range of chemicals in the samples. Gel permeation chromatography (GPC) and adsorption chromatography, including acidification, are typically used to remove matrix components such as lipids from complex matrices, but usually at the expense of compound losses. Ideally, the purification of samples intended for non-target analysis should be selective of matrix interferences. Recent studies have suggested quality assurance/quality control measures for suspect and non-target screening, based on expansion and extrapolation of target compound lists, but method validations remain challenging in the absence of analytical standards and harmonized sample preparation approaches.

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.

Rapid determination of pharmaceuticals in wastewater by direct infusion HRMS using target and suspect screening analysis

A wide-scope screening of active pharmaceutical ingredients (APIs) and their transformation products (TPs) in wastewater can yield valuable insights and pinpoint emerging contaminants that have not been previously reported. Such information is relevant to investigate their occurrence and fate in various environmental compartments. In this study, we explored the applicability of direct infusion high resolution mass spectrometry (DI-HRMS) for comprehensive and rapid detection of APIs and their TPs in wastewater samples. The method was developed using a Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) system and incorporated both wide-scope suspect screening and semi-quantitative determination of selected analytes. The identification strategy was based on the following criteria: narrow accurate mass window (±1.25 ppm) for two most abundant full-MS signals, isotopic pattern fit and additional confirmation on the basis of MS² spectra at three fragmentation levels. The tentative identification of suspects and target compounds relied on an in-house database containing more than 500 different APIs and TPs. The measured fragment spectra were matched against experimental MS² patterns obtained from a publicly available spectral library (MassBank of North America) and in-silico generated fragmentation features (from the CFM-ID algorithm). In total, 79 suspects were identified and 24 target compounds were semi-quantified in 72 wastewater samples. The highest detection frequencies in treated wastewater effluents were observed for diclofenac, metoprolol and telmisartan, while hydroxydiclofenac, dextrorphan, and carbamazepine metabolites were the most frequently detected TPs. The obtained API profiles were in accordance with the national consumption statistics and the origin of wastewater samples. The developed method is suitable for rapid screening of APIs in wastewater and can be used as a complementary tool to characterize API emissions from wastewater treatment facilities and to identify problematic compounds that require more rigorous monitoring.

Trends towards Effective Analysis of Fluorinated Compounds Using Inductively Coupled Plasma Mass Spectrometry (ICP-MS)

Increased demand for monitoring and identification of novel and unknown fluorinated compounds (FCs) has demonstrated the need of sensitive fluorine-specific detectors for unknown FCs in both biological and environmental matrices. Inductively coupled plasma mass spectrometry (ICP-MS) is a promising technique for analysis of FCs and has been rated as the most powerful tool in analytical chemistry. However, direct determination of fluorine using this technique is challenged by high ionization potential of fluorine together with spectral and nonspectral interferences which affect the quality of results. To enhance the quality of results, several studies have reported modifications of a conventional ICP-MS analysis procedure on sample preparation, introduction, analysis, and instrument optimization. Therefore, the focus of this study is to discuss different ICP-MS optimizations and future trends towards the effective analysis of FCs using ICP-MS.

An overview of chemical contaminants and other undesirable chemicals in alcoholic beverages and strategies for analysis

The presence of chemical contaminant in alcoholic beverages is a widespread and notable problem with potential implications for human health. With the complexity and wide variation in the raw materials, production processes, and contact materials involved, there are a multitude of opportunities for a diverse host of undesirable compounds to make their way into the final product-some of which may currently remain unidentified and undetected. This review provides an overview of the notable contaminants (including pesticides, environmental contaminants, mycotoxins, process-induced contaminants, residues of food contact material [FCM], and illegal additives) that have been detected in alcoholic products thus far based on prior reviews and findings in the literature, and will additionally consider the potential sources for contamination, and finally discuss and identify gaps in current analytical strategies. The findings of this review highlight a need for further investigation into unwanted substances in alcoholic beverages, particularly concerning chemical migrants from FCMs, as well as a need for comprehensive nontargeted analytical techniques capable of determining unanticipated contaminants.

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.

Effect of home cooking processes on chlordecone content in beef and investigation of its by-products and metabolites by HPLC-HRMS/MS

Chlordecone (CLD) is a toxic organochlorine pesticide frequently used in the French West Indies until 1993, resulting in a contamination of soil and food. This study assessed the behaviour of CLD residues and CLD processing factors (PFs) during four home cooking processes: cooking in a conventional oven ("oven"), frying ("pan"), cooking in a microwave oven ("microwave") and grilling ("grill"). These four processes were applied to six types of naturally contaminated beef (kidney, liver, rib, chuck, top-sirloin and sirloin). Targeted analyses with isotopic dilution were carried out by ID-HPLC-MS/MS to determine CLD concentrations before and after each cooking process and the corresponding processing factors. HPLC-HRMS/MS was used to find potential organochlorine degradation by-products and/or CLD metabolites present in samples by target, suspect and non-target screening. Cooking processes and especially microwave cooking led to a significant decrease in the CLD contained in beef (2% < PF < 17%). Traces of 5b-hydro-CLD and of another mono-hydro-CLD were found in the uncooked liver but no CLD degradation by-product was observed in the cooked liver.

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.

Targeted and non-targeted unexpected food contaminants analysis by LC/HRMS: Feasibility study on rice

A widely applicable analytical LC/HRMS method based on ion source optimization, data treatment optimization on rice matrix was developed. The effects of key parameters of ion source, and their interactions on ESI response were studied on HPLC-QTOF. Compared with center points, 40% and 20% increase of response factors in the positive and negative mode can be achieved by ion source optimization, respectively. Data processing strategies inspired from metabolomics and multi-targeted analysis were compared and developed using case and control rice samples. Highly automated workflow using XCMS achieved highest mass accuracy, highest detection rate of 96% for 5 μg/kg in a non-targeted way. A clear distinction between the control and contaminated samples by PCA and PLS-DA was also achieved by this workflow using XCMS, even for the concentration of 5 μg/kg.

Analytical methods for mixed organic chemical residues and contaminants in food

Developing methods that can analyze multiple categories of organic chemical residues such as pesticides, veterinary drugs, mycotoxins, human drugs, and environmental contaminants in food with a single analytical procedure is a growing trend. These methods for mixed organic chemical residues and contaminants focus on the chemical properties of these analytes rather than how they are used and adulterate the food supply. This paper highlights recently published methods for mixed residue and contaminant methods in food including advances in technology (instrumental hardware, data processing programs, and sample cleanup) that allow for a larger number of compounds to be monitored simultaneously. The factors that determine the scope, or number and type of analytes in a given method, including needs for specific food commodities, complexity of the analytical procedure, and the intended purpose (qualitative vs quantitative analysis) will be examined. Although there are clear advantages to expanding the number of unwanted chemicals being monitored in the global food supply, challenges to developing and implementing mixed organic residue and contaminant methods will also be discussed. Going forward, it will be important to implement these methods to more thoroughly protect the food supply for a wide variety of targeted and non-targeted chemical residues and contaminants while also having the regulatory framework in place to effectively manage the results of these comprehensive analyses. Graphical abstract.

Identification of chemicals in a polyvinyl chloride/polyethylene multilayer film by ultra-high-performance liquid chromatography/quadrupole time-of-flight mass spectrometry and their migration into solution

An ultra-high-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UPLC-QTOF/MS) method was employed for chemical identification in a commercial polyvinyl chloride/polyethylene (PVC/PE) multilayer film. Over 30 chemicals from different layers (PE layer, PVC layer, and adhesive layer) of the film were identified and were classified into 6 groups, including antioxidants, plasticizers, slip agents, antistatic agents, adhesive components, etc. Special attention was placed on the analysis of some non-intentionally added substances and oligomers in adhesive. Based on the identification results, six additives (all from PE layer) were selected and their migration behaviors were investigated via one-sided contact migration test. The migration test was performed by exposing the PE side of the film to different simulating solutions (water, 40% ethanol, and 95% ethanol) at 40°C, as well as recording the migration level as a function of time. No obvious migration was found into water for all additives, while the migration into 40% and 95% ethanol followed Fickian diffusion behavior, and could be described by Fick's diffusion equation. Diffusion coefficients derived from the equation were in a range of 10^-13 to 10^-10 cm²/s and were dependent on the type of additive and solution.

Expanding phytoremediation to the realms of known and unknown organic chemicals of concern

Recent advancements in analytical chemistry and data analyses via high-resolution mass spectrometry (HRMS) are evolving scientific understanding of the potential totality of organic chemical exposure and pollutant risk. This review addresses the importance of HRMS approaches, namely suspect screening and nontarget chemical analyses, to the realm of phytoremediation. These analytical approaches are not without caveats and constraints, but they provide an opportunity to understand in greater totality how plant-based technologies contribute, mitigate, and reduce organic chemical exposure across scales of experimental and system-level studies. These analytical tools can enlighten the complexity and efficacy of plant-contaminant system design and expand our understanding of biogenic and anthropogenic chemicals at work in phytoremediation systems. Advances in data analytics from biological sciences, such as metabolomics, are crucial to HRMS analysis. This review provides an overview of targeted, suspect screening, and nontarget HRMS approaches, summarizes the expanding knowledge of regulated and unregulated organic chemicals in the environment, addresses requisite HRMS instrumentation, analysis cost, uncertainty, and data processing techniques, and offers potential bridges of HRMS analyses to phytoremediation research and application.