Nontarget Screening with High Resolution Mass Spectrometry in the Environment: Ready to Go?

Network analysis to reveal the most commonly detected compounds in predator-prey pairs in freshwater and marine mammals and fish in Europe

Marine and freshwater mammalian predators and fish samples, retrieved from environmental specimen banks (ESBs), natural history museum (NHMs) and other scientific collections, were analysed by LIFE APEX partners for a wide range of legacy and emerging contaminants (2545 in total). Network analysis was used to visualize the chemical occurrence data and reveal the predominant chemical mixtures for the freshwater and marine environments. For this purpose, a web tool was created to explore these chemical mixtures in predator-prey pairs. Predominant chemicals, defined as the most prevalent substances detected in prey-predator pairs were identified through this innovative approach. The analysis established the most frequently co-occurring substances in chemical mixtures from AP&P in the marine and freshwater environments. Freshwater and marine environments shared 23 chemicals among their top 25 predominant chemicals. Legacy chemical, including perfluorooctanesulfonic acid (PFOS), brominated diphenyl ethers (BDEs), polychlorinated biphenyls (PCBs), hexachlorobenzene and mercury were dominant chemicals in both environments. Furthermore, N-acetylaminoantipyrine was a predominant pharmaceutical in both environments. The LIFE APEX chemical mixture application (https://norman-data.eu/LIFE_APEX_Mixtures) was proven to be useful to establish most prevalent compounds in terms of number of detected counts in prey-predator pairs. Nonetheless, further research is needed to establish food chain associations of the predominant chemicals.

Quantification of additives in beached plastic debris from Aotearoa New Zealand

Plastics have become an essential part of modern society. Their properties can be easily manipulated by incorporating additives to impart desirable attributes, such as colour, flexibility, or stability. However, many additives are classified as hazardous substances. To better understand the risk of plastic pollution within marine ecosystems, the type and concentration of additives in plastic debris needs to be established. We report the quantification of thirty-one common plastic additives (including plasticisers, antioxidants, and UV stabilisers) in beached plastic debris collected across Aotearoa New Zealand. Additives were isolated from the plastic debris by solvent extraction and quantified using high-resolution liquid chromatography-mass spectrometry. Twenty-five of the target additives were detected across 200 items of debris, with plasticisers detected at the highest frequency (99 % detection frequency). Additives were detected in all samples, with a median of four additives per debris item. A significantly higher number of additives were detected per debris item for polyvinyl chloride (median = 7) than polyethylene or polypropylene (median = 4). The additives bis(2-ethylhexyl) phthalate, diisononyl phthalate, diisodecyl phthalate, and antioxidant 702 were detected at the highest concentrations (up to 196,930 μg/g). The sum concentration of additives per debris item (up to 320,325 μg/g) was significantly higher in polyvinyl chloride plastics (median 94,716 μg/g) compared to other plastic types, primarily due to the presence of phthalate plasticisers. Non-target analysis was consistent with the targeted analysis, indicating a higher number and concentration of additives in polyvinyl chloride debris items compared to all other polymer types. Feature identification indicated the presence of more additives than previously detected in the targeted analysis, including plasticisers (phthalate and non-phthalate), processing aids, and nucleating agents. This study highlights phthalates and polyvinyl chloride as key targets for consideration in ecotoxicology and risk assessments, and the development of policies to reduce the impacts of plastic pollution.

Machine learning methods for compound annotation in non-targeted mass spectrometry-A brief overview of fingerprinting, in silico fragmentation and de novo methods

Non-targeted screenings (NTS) are essential tools in different fields, such as forensics, health and environmental sciences. NTSs often employ mass spectrometry (MS) methods due to their high throughput and sensitivity in comparison to, for example, nuclear magnetic resonance-based methods. As the identification of mass spectral signals, called annotation, is labour intensive, it has been used for developing supporting tools based on machine learning (ML). However, both the diversity of mass spectral signals and the sheer quantity of different ML tools developed for compound annotation present a challenge for researchers in maintaining a comprehensive overview of the field. In this work, we illustrate which ML-based methods are available for compound annotation in non-targeted MS experiments and provide a nuanced comparison of the ML models used in MS data analysis, unravelling their unique features and performance metrics. Through this overview we support researchers to judiciously apply these tools in their daily research. This review also offers a detailed exploration of methods and datasets to show gaps in current methods, and promising target areas, offering a starting point for developers intending to improve existing methodologies.

Nontarget and suspect screening reveals the presence of multiple plastic-related compounds in polar bear, killer whale, narwhal and long-finned pilot whale blubber from East Greenland

The monitoring of legacy contaminants in sentinel northern marine mammals has revealed some of the highest concentrations globally. However, investigations into the presence of chemicals of emerging Arctic concern (CEACs) and other lesser-known chemicals are rarely conducted, if at all. Here, we used a nontarget/suspect approach to screen for thousands of different chemicals, including many CEACs and plastic-related compounds (PRCs) in blubber/adipose from killer whales (Orcinus orca), narwhals (Monodon monoceros), long-finned pilot whales (Globicephala melas), and polar bears (Ursus maritimus) in East Greenland. 138 compounds were tentatively identified mostly as PRCs, and four were confirmed using authentic standards: di(2-ethylhexyl) phthalate (DEHP), diethyl phthalate (DEP), di(2-propylheptyl) phthalate (DPHP), and one antioxidant (Irganox 1010). Three other PRCs, a nonylphenol isomer, 2,6-di-tert-butylphenol, and dioctyl sebacate, exhibited fragmentation patterns matching those in library databases. While phthalates were only above detection limits in some polar bear and narwhal, Irganox 1010, nonylphenol, and 2,6-di-tert-butylphenol were detected in >50% of all samples. This study represents the first application of a nontarget/suspect screening approach in Arctic cetaceans, leading to the identification of multiple PRCs in their blubber. Further nontarget analyses are warranted to comprehensively characterize the extent of CEAC and PRC contamination within Arctic marine food webs.

Identification of Key Toxic Substances Considering Metabolic Activation: A Combination of Transcriptome and Nontarget Analysis

There have been numerous studies using effect-directed analysis (EDA) to identify key toxic substances present in source and drinking water, but none of these studies have considered the effects of metabolic activation. This study developed a comprehensive method including a pretreatment process based on an in vitro metabolic activation system, a comprehensive biological effect evaluation based on concentration-dependent transcriptome (CDT), and a chemical feature identification based on nontarget chemical analysis (NTA), to evaluate the changes in the toxic effects and differences in the chemical composition after metabolism. Models for matching metabolites and precursors as well as data-driven identification methods were further constructed to identify toxic metabolites and key toxic precursor substances in drinking water samples from the Yangtze River. After metabolism, the metabolic samples showed a general trend of reduced toxicity in terms of overall biological potency (mean: 3.2-fold). However, metabolic activation led to an increase in some types of toxic effects, including pathways such as excision repair, mismatch repair, protein processing in endoplasmic reticulum, nucleotide excision repair, and DNA replication. Meanwhile, metabolic samples showed a decrease (17.8%) in the number of peaks and average peak area after metabolism, while overall polarity, hydrophilicity, and average molecular weight increased slightly (10.3%). Based on the models for matching of metabolites and precursors and the data-driven identification methods, 32 chemicals were efficiently identified as key toxic substances as main contributors to explain the different transcriptome biological effects such as cellular component, development, and DNA damage related, including 15 industrial compounds, 7 PPCPs, 6 pesticides, and 4 natural products. This study avoids the process of structure elucidation of toxic metabolites and can trace them directly to the precursors based on MS spectra, providing a new idea for the identification of key toxic pollutants of metabolites.

Characterization of the Metabolites of Neonicotinoid Insecticide Imidaclothiz in Mice

As a member of the neonicotinoid group, imidaclothiz has garnered increasing attention due to its possible health risks. This study investigated the metabolism and distribution of imidaclothiz in mice. Seven imidaclothiz metabolites were found, four of which are known, and three are unknown. The metabolic reactions observed were hydroxylation, nitrate ester hydrolysis, methylation, urea formation, and reduction to NO. Precise quantification revealed that after 2 h of oral administration, imidaclothiz rapidly dispersed into various organs and tissues, peaking at 4 h, and was then swiftly eliminated. No propensity for accumulation in the body, particularly in the liver, was observed. Toxicity data from the T.E.S.T prediction indicated that imidaclothiz had moderate toxicity to rats, and a majority of its metabolites were more toxic than the parent compound. These findings complement the existing knowledge of the imidaclothiz environmental fate in mammals and offer a reference point for its application in agriculture and industry.

Screening for compounds with bioaccumulation potential in breast milk using their retention behavior in two-dimensional gas chromatography

Discovery of emerging pollutants in breast milk will be helpful for understanding the hazards to human health. However, it is difficult to identify key compounds among thousands present in complex samples. In this study, a method for screening compounds with bioaccumulation potential was developed. The method can decrease the number of compounds needing structural identification because the partitioning properties of bioaccumulative compounds can be mapped onto GC×GC chromatograms through their retention behaviors. Twenty pooled samples from seven provinces in China were analyzed. 1,286 compounds with bioaccumulation potential were selected from over 3,000 compounds. Sixty-two compounds, including aromatic compounds, phthalates, and phenolics etc., were identified with a high level of confidence and then quantified. Among them, twenty-seven compounds were found for the first time in breast milk. Three phthalate plasticizers and two phenolic antioxidants were found in significantly higher concentrations than other compounds. A toxicological priority index approach was applied to prioritize the compounds considering their concentrations, detection frequencies and eight toxic effects. The prioritization indicated that 13 compounds, including bis(2-ethylhexyl) phthalate, dibutyl phthalate, 1,3-di-tert-butylbenzene, phenanthrene, 2,6-di-tert-butyl-1,4-benzoquinone, 2,4-di-tert-butylphenol, and others, showed higher health risks. Meanwhile, some compounds with high risk for a particular toxic effect, such as benzothiazole and geranylacetone, were still noteworthy. This study is important for assessing the risks of human exposure to organic compounds.

Latest Developments in Direct and Non-Direct LC-MS Methods Based on Liquid Electron Ionization (LEI)

Mass spectrometry (MS) enables precise identification and quantification of molecules, particularly when combined with chromatography. The advent of atmospheric pressure ionization (API) techniques allowed the efficient coupling of liquid chromatography with MS (LC-MS), extending analyses to nonvolatile and thermolabile compounds. API techniques present limitations such as low informative capacity and reproducibility of mass spectra, increasing instrument complexity and costs. Other challenges include analyzing poorly polar molecules and matrix effects (ME), which negatively impact quantitative analyses, necessitating extensive sample purification or using expensive labeled standards. These limitations prompted the exploration of alternative solutions, leading to the development of the Liquid Electron Ionization (LEI) interface. The system has demonstrated excellent robustness and reproducibility. LEI has been employed to analyze various compounds, including pesticides, drugs of abuse, phenols, polycyclic aromatic hydrocarbons (PAHs), phthalates, and many others. Its versatility has been validated with single quadrupole, triple quadrupole, and QToF detectors, operating in electron ionization (EI) or chemical ionization (CI) modes and with both reverse phase liquid chromatography (RPLC) and normal phase liquid chromatography (NPLC). LEI has also been successfully integrated with the Microfluidic Open Interface (MOI), Membrane Introduction Mass Spectrometry (MIMS), and Microfluidic Water-Assisted Trap Focusing (M-WATF), broadening its application scope and consistently demonstrating promising results in terms of sensitivity and identification power. The most recent advancement is the development of Extractive-Liquid Sampling Electron Ionization-Mass Spectrometry (E-LEI-MS), a surface sampling and real-time analysis technique based on the LEI concept. This review article offers a comprehensive and up-to-date picture of the potential of LEI.

Exploring the Chemical Space of the Exposome: How Far Have We Gone?

Around two-thirds of chronic human disease can not be explained by genetics alone. The Lancet Commission on Pollution and Health estimates that 16% of global premature deaths are linked to pollution. Additionally, it is now thought that humankind has surpassed the safe planetary operating space for introducing human-made chemicals into the Earth System. Direct and indirect exposure to a myriad of chemicals, known and unknown, poses a significant threat to biodiversity and human health, from vaccine efficacy to the rise of antimicrobial resistance as well as autoimmune diseases and mental health disorders. The exposome chemical space remains largely uncharted due to the sheer number of possible chemical structures, estimated at over 1060 unique forms. Conventional methods have cataloged only a fraction of the exposome, overlooking transformation products and often yielding uncertain results. In this Perspective, we have reviewed the latest efforts in mapping the exposome chemical space and its subspaces. We also provide our view on how the integration of data-driven approaches might be able to bridge the identified gaps.

Enhancing Molecular Characterization of Dissolved Organic Matter by Integrative Direct Infusion and Liquid Chromatography Nontargeted Workflows

Dissolved organic matter (DOM) in aquatic systems is a highly heterogeneous mixture of water-soluble organic compounds, acting as a major carbon reservoir driving biogeochemical cycles. Understanding DOM molecular composition is thus of vital interest for the health assessment of aquatic ecosystems, yet its characterization poses challenges due to its complex and dynamic chemical profile. Here, we performed a comprehensive chemical analysis of DOM from highly urbanized river and seawater sources and compared it to drinking water. Extensive analyses by nontargeted direct infusion (DI) and liquid chromatography (LC) high-resolution mass spectrometry (HRMS) through Orbitrap were integrated with novel computational workflows to allow molecular- and structural-level characterization of DOM. Across all water samples, over 7000 molecular formulas were calculated using both methods (∼4200 in DI and ∼3600 in LC). While the DI approach was limited to molecular formula calculation, the downstream data processing of MS2 spectral information combining library matching and in silico predictions enabled a comprehensive structural-level characterization of 16% of the molecular space detected by LC-HRMS across all water samples. Both analytical methods proved complementary, covering a broad chemical space that includes more highly polar compounds with DI and more less polar ones with LC. The innovative integration of diverse analytical techniques and computational workflow introduces a robust and largely available framework in the field, providing a widely applicable approach that significantly contributes to understanding the complex molecular composition of DOM.

A stochastic approach for parameter optimization of feature detection algorithms for non-target screening in mass spectrometry

Feature detection plays a crucial role in non-target screening (NTS), requiring careful selection of algorithm parameters to minimize false positive (FP) features. In this study, a stochastic approach was employed to optimize the parameter settings of feature detection algorithms used in processing high-resolution mass spectrometry data. This approach was demonstrated using four open-source algorithms (OpenMS, SAFD, XCMS, and KPIC2) within the patRoon software platform for processing extracts from drinking water samples spiked with 46 per- and polyfluoroalkyl substances (PFAS). The designed method is based on a stochastic strategy involving random sampling from variable space and the use of Pearson correlation to assess the impact of each parameter on the number of detected suspect analytes. Using our approach, the optimized parameters led to improvement in the algorithm performance by increasing suspect hits in case of SAFD and XCMS, and reducing the total number of detected features (i.e., minimizing FP) for OpenMS. These improvements were further validated on three different drinking water samples as test dataset. The optimized parameters resulted in a lower false discovery rate (FDR%) compared to the default parameters, effectively increasing the detection of true positive features. This work also highlights the necessity of algorithm parameter optimization prior to starting the NTS to reduce the complexity of such datasets.

A new approach to monitoring typical organophosphorus compounds (OPs) in environmental media: From database building to suspect screening

Organophosphorus compounds (OPs) are widely used as flame retardants (FRs) and plasticizers, yet strategies for comprehensively screening of suspect OPs in environmental samples are still lacking. In this work, a neoteric, robust, and general suspect screening technique was developed to identify novel chemical exposures by use of ultra-high performance liquid chromatography-Q Exactive hybrid quadrupole-Orbitrap high resolution mass spectrometry (UHPLC-Q-Orbitrap HRMS). We firstly established a suspect chemical database which had 7,922 OPs with 4,686 molecular formulas, and then conducted suspect screening in n = 50 indoor dust samples, n = 76 sediment samples, and n = 111 water samples. By use of scoring criteria such as retention time prediction models, we successfully confirmed five compounds by comparison with their authentic standards, and prioritized three OPs candidates including a nitrogen/fluorine-containing compound, that is dimethyl {1H-indol-3-yl[3-(trifluoromethyl)anilino]methyl} phosphonate (DMITFMAMP). Given that the biodegradation half-life values in water (t1/2,w) of DMITFMAMP calculated by EPI Suite is 180 d, it is considered to be potentially persistent. This strategy shows promising potential in environmental pollution assessment, and can be expected to be widely used in future research.

Emerging contaminants: A One Health perspective

Environmental pollution is escalating due to rapid global development that often prioritizes human needs over planetary health. Despite global efforts to mitigate legacy pollutants, the continuous introduction of new substances remains a major threat to both people and the planet. In response, global initiatives are focusing on risk assessment and regulation of emerging contaminants, as demonstrated by the ongoing efforts to establish the UN's Intergovernmental Science-Policy Panel on Chemicals, Waste, and Pollution Prevention. This review identifies the sources and impacts of emerging contaminants on planetary health, emphasizing the importance of adopting a One Health approach. Strategies for monitoring and addressing these pollutants are discussed, underscoring the need for robust and socially equitable environmental policies at both regional and international levels. Urgent actions are needed to transition toward sustainable pollution management practices to safeguard our planet for future generations.

Plastic additives in the ocean: Use of a comprehensive dataset for meta-analysis and method development

In excess of 13,000 chemicals are added to plastics ('additives') to improve performance, durability, and production of plastic products. They are categorized into numerous chemical classes including flame retardants, light stabilizers, antioxidants, and plasticizers. While research on plastic additives in the marine environment has increased over the past decade, there is a lack of methodological standardization. To direct future measurement of plastic additives, we compiled a first-of-its-kind dataset of literature assessing plastic additives in marine environments, delineated by sample type (plastic debris, seawater, sediment, biota). Using this dataset, we performed a meta-analysis to summarize the state of the science. Currently, our dataset includes 217 publications published between 1978 and May 2023. The majority of publications analyzed plastic additives in biota collected from Europe and Asia. Analyses concentrated on plasticizers, brominated flame retardants, and bisphenols. Common sample preparation techniques included Solvent - Agitation extraction for plastic, sediment, and biota samples, and Solid Phase Extraction for seawater samples with dichloromethane and solvent mixtures including dichloromethane as the organic extraction solvent. Finally, most analyses were performed utilizing gas chromatography/mass spectrometry. There are a variety of data gaps illuminated by this meta-analysis, most notably the small number of compounds that have been targeted for detection compared to the large number of additives used in plastic production. The provided dataset facilitates future investigation of trends in plastic additive concentration data in the marine environment (allowing for comparison to toxicity thresholds) and acts as a starting point for optimizing and harmonizing plastic additive analytical methods.

Effect-directed analysis of androgenic compounds from sewage sludges in China

The safety of municipal sewage sludge has raised great concerns because of the accumulation of large-scale endocrine disrupting chemicals in the sludge during wastewater treatment. The presence of contaminants in sludge can cause secondary pollution owing to inappropriate disposal mechanisms, posing potential risks to the environment and human health. Effect-directed analysis (EDA), involving an androgen receptor (AR) reporter gene bioassay, fractionation, and suspect and nontarget chemical analysis, were applied to identify causal AR agonists in sludge; 20 of the 30 sludge extracts exhibited significant androgenic activity. Among these, the extracts from Yinchuan, Kunming, and Shijiazhuang, which held the most polluted AR agonistic activities were prepared for extensive EDA, with the dihydrotestosterone (DHT)-equivalency of 2.5 - 4.5 ng DHT/g of sludge. Seven androgens, namely boldione, androstenedione, testosterone, megestrol, progesterone, and testosterone isocaproate, were identified in these strongest sludges together, along with testosterone cypionate, first reported in sludge media. These identified androgens together accounted for 55 %, 87 %, and 52 % of the effects on the sludge from Yinchuan, Shijiazhuang, and Kunming, respectively. This study elucidates the causative androgenic compounds in sewage sludge and provides a valuable reference for monitoring and managing androgens in wastewater treatment.

Non-targeted screening and photolysis transformation of tire-related compounds in roadway runoff

Roadway runoff serves as a crucial pathway for transporting contaminants of emerging concern (CECs) from urban environments to receiving water bodies. Tire-related compounds originating from tire wear particles (TWPs) have been frequently detected, posing a potential ecological threat. Yet, the photolysis of tire-related compounds within roadway runoff remains inadequately acknowledged. Addressing this deficit, our study utilized high-resolution mass spectrometry (HRMS) to characterize the chemical profile of roadway runoff across eight strategically selected sites in Guangzhou, China. 219 chemicals were identified or detected within different confidence levels. Among them, 29 tire-related contaminants were validated with reference standards, including hexa(methoxymethyl)melamine (HMMM), 1,3-diphenylguanidine (DPG), dicyclohexylurea (DCU), and N-cyclohexyl-2-benzothiazol-amine (DCMA). HMMM exhibited with the abundance ranging from 2.30 × 104-3.10 × 106, followed by DPG, 1.69 × 104-8.34 × 106. Runoff sample were exposed to irradiation of 500 W mercury lamp for photodegradation experiment. Photolysis results indicated that tire-related compounds with a low photolysis rate, notably DCU, DCMA, and DPG, are more likely to persist within the runoff. The photolytic rates were significantly correlated with the spatial distribution patterns of these contaminants. Our findings underscore TWPs as a significant source of pollution in water bodies, emphasizing the need for enhanced environmental monitoring and assessment strategies.

qPeaks: A Linear Regression-Based Asymmetric Peak Model for Parameter-Free Automatized Detection and Characterization of Chromatographic Peaks in Non-Target Screening Data

We present qPeaks (quality peaks), a novel, user-parameter-free algorithm for peak detection and peak characterization applicable to chromatographic data. The algorithm is based on a linearizable regression model that analyzes asymmetric peaks and estimates the specific uncertainties associated with the peak regression parameters. The uncertainties of the parameters are used to derive a data quality score DQSpeak, rendering low reliability results more transparent during processing and allowing for the prioritization of generated features. High DQSpeak chromatographic peaks have a lower chance of being classified as false-positive and show higher repeatability over multiple measurements. The high efficiency of the algorithm makes it particularly useful for application within processing routines of nontarget screening through chromatography coupled with high-resolution mass spectrometry. qPeaks is integrated into the qAlgorithms nontarget screening processing toolbox and appends a parameter-free chromatographic peak detection and characterization step to it. With qAlgorithms, now high-resolution mass spectra are centroided using the qCentroids algorithms, centroids are clustered to form extracted ion chromatograms (EICs) with the qBinning algorithm, and chromatographic peaks are found on the generated EICs with qPeaks. However, all tools from qAlgorithms can also be used independently.

Should Transformation Products Change the Way We Manage Chemicals?

When chemical pollutants enter the environment, they can undergo diverse transformation processes, forming a wide range of transformation products (TPs), some of them benign and others more harmful than their precursors. To date, the majority of TPs remain largely unrecognized and unregulated, particularly as TPs are generally not part of routine chemical risk or hazard assessment. Since many TPs formed from oxidative processes are more polar than their precursors, they may be especially relevant in the context of persistent, mobile, and toxic (PMT) and very persistent and very mobile (vPvM) substances, which are two new hazard classes that have recently been established on a European level. We highlight herein that as a result, TPs deserve more attention in research, chemicals regulation, and chemicals management. This perspective summarizes the main challenges preventing a better integration of TPs in these areas: (1) the lack of reliable high-throughput TP identification methods, (2) uncertainties in TP prediction, (3) inadequately considered TP formation during (advanced) water treatment, and (4) insufficient integration and harmonization of TPs in most regulatory frameworks. A way forward to tackle these challenges and integrate TPs into chemical management is proposed.

Revealing chemical release from plastic debris in animals' digestive systems using nontarget and suspect screening and simulating digestive fluids

Plastic debris in the environment are not only pollutants but may also be important sources of a variety of contaminants. This work simulated kinetics and potential of chemical leaching from plastic debris in animals' digestive systems by incubating polyvinyl chloride (PVC) cord particles in artificial digestive fluids combined with nontarget and suspect screening based on UHPLC-Orbitrap HRMS. Impacts of particle size, aging, and digestive fluid were investigated to elucidate mechanisms of chemical leaching. Thousands of chemical features were screened in the leachates of PVC cord particles in the artificial digestive fluids, among which >60% were unknown. Bisphenol A (BPA) and bis(2-ethylhexyl) phthalate (DEHP) were the dominant identified CL1 compounds. Finer size and aging of the PVC particles and prolonged incubation time enhanced chemical release, resulting in greater numbers, higher levels, and more complexity in components of the released chemicals. The gastrointestinal fluid was more favorable for chemical leaching than the gastric fluid, with greater numbers and higher levels. Hundreds to thousands of chemical features were screened and filtered in the leachates of consumer plastic products, including food contact products (FCPs) in the artificial bird gastrointestinal fluid. In addition to BPA and DEHP, several novel bisphenol analogues were identified in the leachate of at least one FCP. The results revealed that once plastic debris are ingested by animals, hundreds to thousands of chemicals may be released into animals' digestive tracts in hours, posing potential synergistic risks of plastic debris and chemicals to plastic-ingesting animals. Future research should pay more attentions to identification, ecotoxicities, and environmental fate of vast amounts of unknown chemicals potentially released from plastics in order to gain full pictures of plastic pollution in the environment.

Urban and agricultural influences on the coastal dissolved organic matter pool in the Algoa Bay estuaries

While anthropogenic pollution is a major threat to aquatic ecosystem health, our knowledge of the presence of xenobiotics in coastal Dissolved Organic Matter (DOM) is still relatively poor. This is especially true for water bodies in the Global South with limited information gained mostly from targeted studies that rely on comparison with authentic standards. In recent years, non-targeted tandem mass spectrometry has emerged as a powerful tool to collectively detect and identify pollutants and biogenic DOM components in the environment, but this approach has yet to be widely utilized for monitoring ecologically important aquatic systems. In this study we compared the DOM composition of Algoa Bay, Eastern Cape, South Africa, and its two estuaries. The Swartkops Estuary is highly urbanized and severely impacted by anthropogenic pollution, while the Sundays Estuary is impacted by commercial agriculture in its catchment. We employed solid-phase extraction followed by liquid chromatography tandem mass spectrometry to annotate more than 200 pharmaceuticals, pesticides, urban xenobiotics, and natural products based on spectral matching. The identification with authentic standards confirmed the presence of methamphetamine, carbamazepine, sulfamethoxazole, N-acetylsulfamethoxazole, imazapyr, caffeine and hexa(methoxymethyl)melamine, and allowed semi-quantitative estimations for annotated xenobiotics. The Swartkops Estuary DOM composition was strongly impacted by features annotated as urban pollutants including pharmaceuticals such as melamines and antiretrovirals. By contrast, the Sundays Estuary exhibited significant enrichment of molecules annotated as agrochemicals widely used in the citrus farming industry, with predicted concentrations for some of them exceeding predicted no-effect concentrations. This study provides new insight into anthropogenic impact on the Algoa Bay system and demonstrates the utility of non-targeted tandem mass spectrometry as a sensitive tool for assessing the health of ecologically important coastal ecosystems and will serve as a valuable foundation for strategizing long-term monitoring efforts.

Identification of hazardous organic compounds in e-waste plastic using non-target and suspect screening approaches

End-of-life electric and electronic devices stand as one of the fastest growing wastes in the world and, therefore, a rapidly escalating global concern. A relevant fraction of these wastes corresponds to polymeric materials containing a plethora of chemical additives. Some of those additives fall within the category of hazardous organic compounds (HOCs). Despite the significant advances in the capabilities of analytical methods, the comprehensive characterization of WEEE plastic remains as a challenge. This research strives to identify the primary additives within WEEE polymers by implementing a non-target and suspect screening approach. Gas chromatography coupled to time-of-flight mass spectrometry (GC-QTOF-MS), using electron ionization (EI), was applied for the detection and identification of more than 300 substances in this matrix. A preliminary comparison was carried out with nominal resolution EI-MS spectra contained in the NIST17 library. BPA, flame retardants, UV-filters, PAHs, and preservatives were among the compounds detected. Fifty-one out of 300 compounds were confirmed by comparison with authentic standards. The study establishes a comprehensive database containing m/z ratios and accurate mass spectra of characteristic compounds, encompassing HOCs. Semi-quantification of the predominant additives was conducted across 48 WEEE samples collected from handling and dismantling facilities in Galicia. ABS plastic demonstrated the highest median concentrations, ranging from 0.154 to 4456 μg g-1, being brominated flame retardants and UV filters, the families presenting the highest concentrations. Internet router devices revealed the highest concentrations, containing a myriad of HOCs, such as tetrabromobisphenol A (TBBPA), tribromophenol (TBrP), triphenylphosphate (TPhP), tinuvin P and bisphenol A (BPA), most of which are restricted in Europe.

Adopting Mechanistic Molecular Biology Approaches in Exposome Research for Causal Understanding

Through investigating the combined impact of the environmental exposures experienced by an individual throughout their lifetime, exposome research provides opportunities to understand and mitigate negative health outcomes. While current exposome research is driven by epidemiological studies that identify associations between exposures and effects, new frameworks integrating more substantial population-level metadata, including electronic health and administrative records, will shed further light on characterizing environmental exposure risks. Molecular biology offers methods and concepts to study the biological and health impacts of exposomes in experimental and computational systems. Of particular importance is the growing use of omics readouts in epidemiological and clinical studies. This paper calls for the adoption of mechanistic molecular biology approaches in exposome research as an essential step in understanding the genotype and exposure interactions underlying human phenotypes. A series of recommendations are presented to make the necessary and appropriate steps to move from exposure association to causation, with a huge potential to inform precision medicine and population health. This includes establishing hypothesis-driven laboratory testing within the exposome field, supported by appropriate methods to read across from model systems research to human.

Predicting the Activity of Unidentified Chemicals in Complementary Bioassays from the HRMS Data to Pinpoint Potential Endocrine Disruptors

The majority of chemicals detected via nontarget liquid chromatography high-resolution mass spectrometry (HRMS) in environmental samples remain unidentified, challenging the capability of existing machine learning models to pinpoint potential endocrine disruptors (EDs). Here, we predict the activity of unidentified chemicals across 12 bioassays related to EDs within the Tox21 10K dataset. Single- and multi-output models, utilizing various machine learning algorithms and molecular fingerprint features as an input, were trained for this purpose. To evaluate the models under near real-world conditions, Monte Carlo sampling was implemented for the first time. This technique enables the use of probabilistic fingerprint features derived from the experimental HRMS data with SIRIUS+CSI:FingerID as an input for models trained on true binary fingerprint features. Depending on the bioassay, the lowest false-positive rate at 90% recall ranged from 0.251 (sr.mmp, mitochondrial membrane potential) to 0.824 (nr.ar, androgen receptor), which is consistent with the trends observed in the models' performances submitted for the Tox21 Data Challenge. These findings underscore the informativeness of fingerprint features that can be compiled from HRMS in predicting the endocrine-disrupting activity. Moreover, an in-depth SHapley Additive exPlanations analysis unveiled the models' ability to pinpoint structural patterns linked to the modes of action of active chemicals. Despite the superior performance of the single-output models compared to that of the multi-output models, the latter's potential cannot be disregarded for similar tasks in the field of in silico toxicology. This study presents a significant advancement in identifying potentially toxic chemicals within complex mixtures without unambiguous identification and effectively reducing the workload for postprocessing by up to 75% in nontarget HRMS.

Nontarget screening analysis of organic compounds in river sediments: a case study in the Taipu River of the Yangtze River Delta Region in China

Sediments are the vital fate of organic compounds, and the recognition of organic compounds in sediments is constructive in providing comprehensive and long-term information. In this study, a three-step nontarget screening (NTS) analysis workflow using comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC × GC-TOFMS) revealed the extensive existence of organic compounds in the Taipu River sediment. Organic compounds (705) were detected and divided into four structure-related groups or eight use-related classes. In the Taipu River's mainstream, a significant difference was found in the composition profiles of the identified organic compounds among various sites, demonstrating the organic compounds were more abundant in the midstream and downstream than in the upstream. Meanwhile, the hydrodynamic force was recognized as a potential factor influencing organic compounds' occurrence. Based on multiple statistical analyses, the shipping and textile printing industries were considered the significant contributors to the identified organic compounds. Considering the principles of the priority substances and the current status of the substances, two traditional pollutants and ten emerging organic compounds were recognized as the priority organic compounds for the Taipu River. Conclusively, this study established a workflow for NTS analysis of sediment samples and demonstrated the necessity of NTS analysis to evaluate the impact of terrestrial emissions of organic compounds on the aquatic environment.

Innovative analytical methodologies for characterizing chemical exposure with a view to next-generation risk assessment

The chemical burden on the environment and human population is increasing. Consequently, regulatory risk assessment must keep pace to manage, reduce, and prevent adverse impacts on human and environmental health associated with hazardous chemicals. Surveillance of chemicals of known, emerging, or potential future concern, entering the environment-food-human continuum is needed to document the reality of risks posed by chemicals on ecosystem and human health from a one health perspective, feed into early warning systems and support public policies for exposure mitigation provisions and safe and sustainable by design strategies. The use of less-conventional sampling strategies and integration of full-scan, high-resolution mass spectrometry and effect-directed analysis in environmental and human monitoring programmes have the potential to enhance the screening and identification of a wider range of chemicals of known, emerging or potential future concern. Here, we outline the key needs and recommendations identified within the European Partnership for Assessment of Risks from Chemicals (PARC) project for leveraging these innovative methodologies to support the development of next-generation chemical risk assessment.

Tracking Dynamic Chemical Reactivity Networks with High-Resolution Mass Spectrometry: A Case of Microplastic-Derived Dissolved Organic Carbon

Chemical degradation testing often involves monitoring the loss of a chemical or the evolution of a single diagnostic product through time. Here, we demonstrate a novel approach to tracing complex degradation networks using mass-spectrometry-based methods and open cheminformatics tools. Ester- and ether-based thermoplastic polyurethane (TPU_Ester and TPU_Ether) microplastics (350 μm) and microplastics-derived dissolved organic carbon (MP-DOC) were photoweathered in a simulated marine environment and subsequently analyzed by liquid chromatography coupled to high-resolution mass spectrometry. We formula-annotated 1342 and 2344 unique features in the MP-DOC of TPU_Ester and TPU_Ether, respectively. From these, we extracted 199 and 568 plausible parent-transformation product pairs via matching of features (a) with complementary increasing and decreasing trends (Spearman's correlation coefficient between normalized intensity and time), (b) spectral similarities of at least three accurate mass MS2 fragments, and (c) at least 3 ppm agreement between the theoretical and measured change in m/z between the parent-transformation product formula. Molecular network analysis revealed that both chain scission and cross-linking reactions occur dynamically rather than degradation proceeding in a monotonic progression to smaller or more oxygenated structures. Network nodes with the highest degree of centrality were tentatively identified using in silico fragmentation and can be prioritized for toxicity screening or other physicochemical properties of interest. This work has important implications for chemical transformation tracking in complex mixtures and may someday enable improved elucidation of environmental transformation rules (i.e., structure-reactivity relationships) and fate modeling.

Profiling emerging micropollutants in urban stormwater runoff using suspect and non-target screening via high-resolution mass spectrometry

Urban surface runoff contains chemicals that can negatively affect water quality. Urban runoff studies have determined the transport dynamics of many legacy pollutants. However, less attention has been paid to determining the first-flush effects (FFE) of emerging micropollutants using suspect and non-target screening (SNTS). Therefore, this study employed suspect and non-target analyses using liquid chromatography-high resolution mass spectrometry to detect emerging pollutants in urban receiving waters during stormwater events. Time-interval sampling was used to determine occurrence trends during stormwater events. Suspect screening tentatively identified 65 substances, then, their occurrence trend was grouped using correlation analysis. Non-target peaks were prioritized through hierarchical cluster analysis, focusing on the first flush-concentrated peaks. This approach revealed 38 substances using in silico identification. Simultaneously, substances identified through homologous series observation were evaluated for their observed trends in individual events using network analysis. The results of SNTS were normalized through internal standards to assess the FFE, and the most of tentatively identified substances showed observed FFE. Our findings suggested that diverse pollutants that could not be covered by target screening alone entered urban water through stormwater runoff during the first flush. This study showcases the applicability of the SNTS in evaluating the FFE of urban pollutants, offering insights for first-flush stormwater monitoring and management.

Reproducibility in nontarget screening (NTS) of environmental emerging contaminants: Assessing different HLB SPE cartridges and instruments

Non-targeted screening (NTS) methods are integral in environmental research for detecting emerging contaminants. However, their efficacy can be influenced by variations in hydrophilic-lipophilic balance (HLB) solid phase extraction (SPE) cartridges and high-resolution mass spectrometry (HRMS) instruments across different laboratories. In this study, we scrutinized the influence of five HLB SPE cartridges (Nano, Weiqi, CNW, Waters, and J&K) and four LC-HRMS platforms (Agilent, Waters, Thermo, and AB SCIEX) on the identification of emerging environmental contaminants. Our results demonstrate that 87.6 % of the target compounds and over 59.6 % of the non-target features were consistently detected across all tested HLB cartridges, with an overall 71.2 % universally identified across the four LC-HRMS systems. Discrepancies in detection rates were primarily attributable to variations in retention time stability, mass stability of precursors and fragments, system cleanliness affecting fold change and p-values, and fragment response. These findings confirm the necessity of refining parameter criteria for NTS. Moreover, our study confirms the efficacy of the PyHRMS tool in analyzing and processing data from multiple instrumental platforms, reinforcing its utility for multi-platform NTS. Overall, our findings underscore the reliability and robustness of NTS methods in identifying potential water contaminants, while also highlighting factors that may influence these outcomes.

Unraveling the chemical fingerprint of the Miami River sources: Insights from high-resolution mass spectrometry and nontarget analysis

This study investigated the chemical composition of waters in the heavily urbanized and historically polluted Miami River, Florida. The goal was to assess the different water sources and anthropogenic influence in this managed area using nontarget analysis (NTA) combined with high-resolution mass spectrometry (HRMS). Surface water samples were collected from 10 sites during five sampling events in the wet season of 2021 and 2022. The HRMS data was processed using Compound Discoverer™ version 3.3, and the results were analyzed using techniques including Principal Component Analysis and Kendrick Mass Defect plots. Results showed a gradient change in the chemical composition from the Everglades to Biscayne Bay endmembers. The Seybold Canal, an adjacent canal, was consistently identified as a unique source of contaminants, contributing its own specific set of tracers. Increased presence and intensity of organic contaminants along the waterway was observed, indicating significant anthropogenic influence in the area. The NTA and post-processing were evaluated for reproducibility, demonstrating robustness with a 71.2% average reproducibility for compounds detected in 3 out of 5 sampling trips. A detection frequency of 80% (4 out of 5) was the set criterion for detected compounds suggested as tracers. To prioritize samples, hierarchical cluster analysis was employed, and potential tracers for each water source were determined. Tracers included natural products and agricultural herbicides and insecticides for the Everglades, anthropogenic contaminants for the Seybold Canal, and a lack of unique tracers for Biscayne Bay. Additionally, urban-influenced contaminants such as flame retardants, insect repellents, pharmaceuticals, and non-agricultural herbicides were identified along the river. This study highlights the impact of human activities on the Miami River and demonstrates the effectiveness of NTA in differentiating and tracking water sources. The results emphasize the importance of reproducibility in NTA and provide guidance on implementing monitoring strategies by prioritizing samples based on chemical compositions.

Enhanced efficiency of MS/MS all-ion fragmentation for non-targeted analysis of trace contaminants in surface water using multivariate curve resolution and data fusion

Data-independent acquisition-all-ion fragmentation (DIA-AIF) mode of mass spectrometry can facilitate wide-scope non-target analysis of contaminants in surface water due to comprehensive spectral identification. However, because of the complexity of the resulting MS2 AIF spectra, identifying unknown pollutants remains a significant challenge, with a significant bottleneck in translating non-targeted chemical signatures into environmental impacts. The present study proposes to process fused MS1 and MS2 data sets obtained from LC-HRMS/MS measurements in non-targeted AIF workflows on surface water samples using multivariate curve resolution-alternating least squares (MCR-ALS). This enables straightforward assignment between precursor ions obtained from resolved MS1 spectra and their corresponding MS2 spectra. The method was evaluated for two sets of tap water and surface water contaminated with 14 target chemicals as a proof of concept. The data set of surface water samples consisting of 3506 MS1 and 2170 MS2 AIF mass spectral features was reduced to 81 components via a fused MS1-MS2 MCR model that describes at least 98.8% of the data. Each component summarizes the distinct chromatographic elution of components together with their corresponding MS1 and MS2 spectra. MS2 spectral similarity of more than 82% was obtained for most target chemicals. This highlights the potential of this method for unraveling the composition of MS/MS complex data in a water environment. Ultimately, the developed approach was applied to the retrospective non-target analysis of an independent set of surface water samples.

Molecular formula assignment of dissolved organic matter by ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry using two non-targeted data processing approaches: A case study from recirculating aquaculture systems

BACKGROUND

The accumulation of dissolved organic matter (DOM) poses an issue in the management of the water quality from recirculating aquaculture systems (RAS), but its characterization is often not detailed enough to understand the DOM transformations in RAS. In this study, we investigated the application of two distinct non-targeted data processing approaches using ultra-performance liquid chromatography (UPLC) with quadrupole time-of-flight mass spectrometry (QTOF-MS) and two software with different algorithmic designs: PetroOrg and Progenesis QI to accurately characterize the molecular composition of DOM in RAS by UPLC-QTOF-MS.

RESULTS

The UPLC-QTOF-MS resolution in combination with PetroOrg and Progenesis QI software successfully assigned 912 and 106 unique elemental compositions, respectively, including compounds containing carbon, hydrogen, and oxygen (CHO) and nitrogen-containing CHO compounds (CHON), in the DOM samples from RAS. The results of these two distinct data processing approaches were consistent with the list of DOM formulas from RAS identified by higher resolution mass spectrometry techniques confirming their reliability. PetroOrg approach revealed only compositional information in the DOM samples from RAS, while Progenesis QI in addition to identifying new elemental compositions, increased their chemical space by giving information about their polarity and their possible key structures. DOM samples from RAS were found to be rich in unsaturated CHO compounds, with tentatively key structures of terpenoids with medium polarity indicating natural origins in their composition. The analysis also revealed probable structures of sucrose fatty acid esters and polyethylene glycol, indicating anthropogenic sources.

SIGNIFICANCE AND NOVELTY

The combination of these two non-targeted data processing approaches significantly improves the characterization of the complex mixture of DOM from RAS by UPLC-QTOF-MS reporting for the first time accurate DOM results in terms of its composition, while proposing its key structures. The presented methods can also be used to analyze different DOM samples with other HRMS techniques and software.

Transformation products of antibacterial drugs in environmental water: Identification approaches based on liquid chromatography-high resolution mass spectrometry

In recent years, the presence of antibiotics in the aquatic environment has caused increasing concern for the possible consequences on human health and ecosystems, including the development of antibiotic-resistant bacteria. However, once antibiotics enter the environment, mainly through hospital and municipal discharges and the effluents of wastewater treatment plants, they can be subject to transformation reactions, driven by both biotic (e.g. microorganism and mammalian metabolisms) and abiotic factors (e.g. oxidation, photodegradation, and hydrolysis). The resulting transformation products (TPs) can be less or more active than their parent compounds, therefore the inclusion of TPs in monitoring programs should be mandatory. However, only the reference standards of a few known TPs are available, whereas many other TPs are still unknown, due to the high diversity of possible transformation reactions in the environment. Modern high-resolution mass spectrometry (HRMS) instrumentation is now ready to tackle this problem through suspect and untargeted screening approaches. However, for handling the large amount of data typically encountered in the analysis of environmental samples, these approaches also require suitable processing workflows and accurate tandem mass spectra interpretation. The compilation of a suspect list containing the possible monoisotopic masses of TPs retrieved from the literature and/or from laboratory simulated degradation experiments showed unique advantages. However, the employment of in silico prediction tools could improve the identification reliability. In this review, the most recent strategies relying on liquid chromatography-HRMS for the analysis of environmental TPs of the main antibiotic classes were examined, whereas TPs formed during water treatments or disinfection were not included.

Assessment for the data processing performance of non-target screening analysis based on high-resolution mass spectrometry

Non-target screening (NTS) based on high-resolution mass spectrometry (HRMS) is considered one of the most comprehensive approaches for the characterization of contaminants of emerging concern (CECs) in a complex sample. This study evaluated the performance of NTS in aquatic environments (including peak picking, database matching, product identification, semi-quantification, etc.) based on a self-developed data processing method using 38 glucocorticoids as testing compounds. Data-dependent acquisition (DDA) and data-independent acquisition (DIA) modes were used for obtaining the MS2 information for in-house or online database matching. Results indicate that DDA and DIA mode have their own advantages and can complement each other. The quantification method based on LC-HRMS has shown the potential to provide a fast and acceptable result for testing compounds. Finally, a matrix spike analysis was carried out on 66 CECs across different usage categories in wastewater, surface water, and seawater matrix samples, together with a case study performed for characterizing the whole contaminants in a Pearl River sample, to better illustrate the application potential of NTS workflow and the credibility of NTS outcomes. This study provides a foundation for novel applications of HRMS data by NTS workflow to identify and quantify CECs in complex systems.

A Review of the Occurrence of Metals and Xenobiotics in European Hedgehogs (Erinaceus europaeus)

Monitoring data from several European countries indicate that European hedgehog (Erinaceus europaeus) populations are declining, and research exploring the causes of the decline, including exposure to potentially harmful xenobiotics and metals, may inform conservation initiatives to protect this species in the wild. Hedgehogs are ground-dwelling mammals, feeding on a range of insects, slugs, snails, and earthworms, as well as eggs, live vertebrates, and carrion, including carcasses of apex predator species representing higher levels of the food chain. Consequently, hedgehogs come into close contact with contaminants present in their habitats and prey. This review investigated the studies available on the subject of the occurrence of metals and organic xenobiotics in hedgehogs. This study found that a vast range of different pesticides; persistent organic pollutants (POPs), including organochlorine compounds and brominated flame retardants (BFRs); as well as toxic heavy metals could be detected. Some compounds occurred in lethal concentrations, and some were associated with a potential adverse effect on hedgehog health and survival. Due to their ecology, combined with the opportunity to apply non-invasive sampling techniques using spines as sampling material, we suggest that the European hedgehog is a relevant bioindicator species for monitoring the exposure of terrestrial wildlife to potential toxicants in urban and rural environments.

Bioaccumulative chemicals are either too hard or too soft: Conceptual density functional theory as a screening tool for emerging pollutants

Conceptual density functional theory (CDFT) descriptors were computed to predict the environmental fate of approximately 6,000 widely used industrial chemicals. CDFT descriptors aligned with a molecule's possible bioaccumulation mechanism, i.e., soft chemicals are lipophilic, whereas hard chemicals may bioaccumulate by other mechanisms such as protein binding. The results have provided us with a new "rule of thumb" to guide risk assessment of chemical hazards: suspected persistent organic pollutants are either too hard (η > 0.40 hartree) or too soft (α > 200 Å3). This offers a novel approach to environmental risk assessment using two fundamental properties of a molecule.

Leaching and transformation of chemical additives from weathered plastic deployed in the marine environment

Plastic pollution causes detrimental environmental impacts, which are increasingly attributed to chemical additives. However, the behaviour of plastic additives in the marine environment is poorly understood. We used a marine deployment experiment to examine the impact of weathering on the extractables profile, analysed by liquid chromatography-mass spectrometry, of four plastics at two locations over nine months in Aotearoa/New Zealand. The concentration of additives in polyethylene and oxo-degradable polyethylene were strongly influenced by artificial weathering, with deployment location and time less influential. By comparison, polyamide 6 and polyethylene terephthalate were comparatively inert with minimal change in response to artificial weathering or deployment time. Non-target analysis revealed extensive differentiation between non-aged and aged polyethylene after deployment, concordant with the targeted analysis. These observations highlight the need to consider the impact of leaching and weathering on plastic composition when quantifying the potential impact and risk of plastic pollution within receiving environments.

Non-target analysis for water characterization: wastewater treatment impact and selection of relevant features

Non-target analyses were conducted to characterize and compare the molecular profiles (UHPLC-HRMS fingerprint) of water samples from a wastewater treatment plant (WWTP). Inlet and outlet samples were collected from three campaigns spaced 6 months apart in order to highlight common trends. A significant impact of the treatment on the sample fingerprints was shown, with a 65-70% abatement of the number of features detected in the effluent, and more polar, smaller and less intense molecules found overall compared to those in WWTP influent waters. Multivariate analysis (PCA) associated with variations of the features between inlets and outlets showed that features appearing or increasing were correlated with effluents while those disappearing or decreasing were correlated with influents. Finally, effluent features considered as relevant to a potentially adverse effect on aqueous media (i.e. those which appeared or increased or slightly varied from the influent) were highlighted. Three hundred seventy-five features common with the 3 campaigns were thus selected and further characterized. For most of them, elementary composition was found to be C, H, N, O (42%) and C, H, N, O, P (18%). Considering the MS2 spectra and several reference MS2 databases, annotations were proposed for 35 of these relevant features. They include synthetic products, pharmaceuticals and metabolites.

Discovery and occurrence of organophosphorothioate esters in food contact plastics and foodstuffs from South China: Dietary intake assessment

A recent study revealed the presence of non-pesticide organothiophosphate esters (OTPEs) - precursors to organophosphate esters (OPEs) contaminants - in river water. Since OPEs have demonstrated adverse reproductive outcomes in humans, this accentuates the urgency to explore the prevalence of non-pesticide OTPEs in other potential human exposure matrices. In this study, a nontarget screening method based on high-resolution mass spectrometry was used to identify OTPEs in food contact plastic (FCP) samples collected from South China. O,O,O-triphenyl phosphorothioate (TPhPt) and O,O,O-tris(2,4-di-tert-butylphenyl) phosphorothioate (AO168 = S) were unequivocally identified (Level 1), while O,O-di(di-butylphenyl) O-methyl phosphorothioate (BDBPMPt) was tentatively identified (Level 2b, indicating probable structure based on diagnostic evidence). Among n = 70 FCP samples, AO168 = S emerged with the highest detection frequency and median concentration of 74 % and 111 ng/g, respectively. Significant Pearson correlations were observed in log-transformed peak areas of AO168 = S and TPhPt in FCPs with their respective oxons, respectively. Occurrences of AO168 = S and TPhPt were further investigated in n = 100 foodstuff samples using a market basket method. AO168 = S and TPhPt exhibited detection frequencies of 43 % and 44 % in all food items with mean concentrations of 2.17 ng/g wet weight (ww) (range: <0.53-67.8 ng/g ww) and 0.112 ng/g ww (range: <0.006-2.39 ng/g ww), respectively. The highest mean concentrations for AO168 = S and TPhPt were found in vegetables (4.62 ng/g ww) and oil (3.00 ng/g ww), respectively. The median estimated daily intakes (EDIs) of AO168 = S and TPhPt via diet were calculated as 10.4 and 1.51 ng/kg body weight/day, respectively. For AO168 = S, only meat and vegetables contributed to the median EDI, whereas for TPhPt, oil was identified as the principal contributor to the median EDI. This study for the first time evaluated human exposure to OTPEs via diet, providing new insights to overall human exposure to OPEs.

Evidence of transboundary movement of chemicals from Mexico to the U.S. in Tijuana River Estuary sediments

The Tijuana River Estuary (TRE) has been a public health hazard and point of contention between the United States and Mexico for decades, with sources of pollution on both sides of the border. The goal of our study is to determine the presence and dynamics of chemical contamination in the TRE. We sampled sediment from four TRE locations in the U.S. during stable dry conditions and immediately after a wet weather period. Organic chemicals were initially screened with non-targeted analysis using gas chromatography high-resolution mass spectrometry (GC/HRMS) that tentatively identified 6978 chemicals in the NIST 20 database. These tentative identifications were filtered using the USEPA CompTox database to guide quantitative targeted analysis at detection limits below 1 ng/g dry weight sediment. Quantitative targeted analysis of 152 organic pollutants and 18 inorganic elements via GC/HRMS revealed generally higher concentrations of contaminants in dry weather sediments compared to wet weather sediments. The highest concentrations of all chemical classes were detected at the site closest to the U.S.-Mexico border, followed by an urban area near Imperial Beach, California, U.S. All sites exhibited a mixture of petrogenic and pyrogenic polycyclic aromatic hydrocarbons (PAHs). Current-use pesticides were dominated by pyrethroid insecticides and the thiocarbamate herbicide s-Ethyl dipropylthiocarbamate (EPTC), while the U.S.-banned organochlorine pesticides were dominated by chlordanes, dieldrin, and dichlorodiphenyltrichloroethane (DDT) and its degradation byproducts. Polychlorinated biphenyl (PCB) concentrations were greatest at the site closest to the U.S.-Mexico border but in the low nanogram-per-gram range. Phthalates were only found at the same site, with relatively high concentrations of bis(2-ethylhexyl) phthalate. This study provides positive identification and quantitative concentrations for organic pollutants in TRE sediments. Our data suggest that there are multiple sources of chemical contamination in the estuary, including possible transboundary movement of pollutants from Mexico.

Identification of polar organic chemicals in the aquatic foodweb: Combining high-resolution mass spectrometry and trend analysis

Environmental risk assessment of chemical contaminants requires prioritizing of substances taken up by biota as it is a starting point for potential adverse effects. Although knowledge about the occurrence of known chemical pollutants in aquatic organisms has significantly improved during the last decade, there is still a poor understanding for a broad range of more polar compounds. To tackle this issue, we proposed an approach that identifies bioaccumulative and biomagnifiable polar chemicals using liquid chromatography coupled with electrospray ionization to high resolution tandem mass spectrometry (LC-HRMS/MS) and combine it with trend analysis using hierarchical clustering. As a proof-of-concept, this approach was implemented on various organisms and compartments (sediment, litter leaves, periphytic biofilm, invertebrates and fish) collected from a small urban river. HRMS/MS data measured via data-independent acquisition mode were retrospectively analysed using two analytical strategies: (1) retrospective target and (2) suspect/non-target screening. In the retrospective target analysis, 56 of 361 substances spanning a broad range of contaminant classes were detected (i.e. 26 in fish, 18 in macroinvertebrates, 28 in leaves, 29 in periphyton and 32 in sediments, with only 7 common to all compartments), among which 49 could be quantified using reference standards. The suspect screening approach based on two suspect lists (in-house, Norman SusDat) led to the confirmation of 5 compounds with standards (three xenobiotics at level 1 and two lipids at level 2) and tentative identification of seven industrial or natural chemicals at level 2 and 3 through a mass spectra library match. Overall, this proof-of-concept study provided a more comprehensive picture of the exposure of biota to emerging contaminants (i.e., the internal chemical exposome) and potential bioaccumulation or biomagnification of polar compounds along the trophic chain.

Application of Ion Mobility Spectrometry and the Derived Collision Cross Section in the Analysis of Environmental Organic Micropollutants

Ion mobility spectrometry (IMS) is a rapid gas-phase separation technique, which can distinguish ions on the basis of their size, shape, and charge. The IMS-derived collision cross section (CCS) can serve as additional identification evidence for the screening of environmental organic micropollutants (OMPs). In this work, we summarize the published experimental CCS values of environmental OMPs, introduce the current CCS prediction tools, summarize the use of IMS and CCS in the analysis of environmental OMPs, and finally discussed the benefits of IMS and CCS in environmental analysis. An up-to-date CCS compendium for environmental contaminants was produced by combining CCS databases and data sets of particular types of environmental OMPs, including pesticides, drugs, mycotoxins, steroids, plastic additives, per- and polyfluoroalkyl substances (PFAS), polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), and polybrominated diphenyl ethers (PBDEs), as well as their well-known transformation products. A total of 9407 experimental CCS values from 4170 OMPs were retrieved from 23 publications, which contain both drift tube CCS in nitrogen (DTCCSN2) and traveling wave CCS in nitrogen (TWCCSN2). A selection of publicly accessible and in-house CCS prediction tools were also investigated; the chemical space covered by the training set and the quality of CCS measurements seem to be vital factors affecting the CCS prediction accuracy. Then, the applications of IMS and the derived CCS in the screening of various OMPs were summarized, and the benefits of IMS and CCS, including increased peak capacity, the elimination of interfering ions, the separation of isomers, and the reduction of false positives and false negatives, were discussed in detail. With the improvement of the resolving power of IMS and enhancements of experimental CCS databases, the practicability of IMS in the analysis of environmental OMPs will continue to improve.

Is Nontarget Analysis Ready for Regulatory Application? Influence of Peak-Picking Algorithms on Data Analysis

The use of peak-picking algorithms is an essential step in all nontarget analysis (NTA) workflows. However, algorithm choice may influence reliability and reproducibility of results. Using a real-world data set, the aim of this study was to investigate how different peak-picking algorithms influence NTA results when exploring temporal and/or spatial trends. For this, drinking water catchment monitoring data, using passive samplers collected twice per year across Southeast Queensland, Australia (n = 18 sites) between 2014 and 2019, was investigated. Data were acquired using liquid chromatography coupled to high-resolution mass spectrometry. Peak picking was performed using five different programs/algorithms (SCIEX OS, MSDial, self-adjusting-feature-detection, two algorithms within MarkerView), keeping parameters identical whenever possible. The resulting feature lists revealed low overlap: 7.2% of features were picked by >3 algorithms, while 74% of features were only picked by a single algorithm. Trend evaluation of the data, using principal component analysis, showed significant variability between the approaches, with only one temporal and no spatial trend being identified by all algorithms. Manual evaluation of features of interest (p-value <0.01, log fold change >2) for one sampling site revealed high rates of incorrectly picked peaks (>70%) for three algorithms. Lower rates (<30%) were observed for the other algorithms, but with the caveat of not successfully picking all internal standards used as quality control. The choice is therefore currently between comprehensive and strict peak picking, either resulting in increased noise or missed peaks, respectively. Reproducibility of NTA results remains challenging when applied for regulatory frameworks.

Water, Water Everywhere, but Every Drop Unique: Challenges in the Science to Understand the Role of Contaminants of Emerging Concern in the Management of Drinking Water Supplies

The protection and management of water resources continues to be challenged by multiple and ongoing factors such as shifts in demographic, social, economic, and public health requirements. Physical limitations placed on access to potable supplies include natural and human-caused factors such as aquifer depletion, aging infrastructure, saltwater intrusion, floods, and drought. These factors, although varying in magnitude, spatial extent, and timing, can exacerbate the potential for contaminants of concern (CECs) to be present in sources of drinking water, infrastructure, premise plumbing and associated tap water. This monograph examines how current and emerging scientific efforts and technologies increase our understanding of the range of CECs and drinking water issues facing current and future populations. It is not intended to be read in one sitting, but is instead a starting point for scientists wanting to learn more about the issues surrounding CECs. This text discusses the topical evolution CECs over time (Section 1), improvements in measuring chemical and microbial CECs, through both analysis of concentration and toxicity (Section 2) and modeling CEC exposure and fate (Section 3), forms of treatment effective at removing chemical and microbial CECs (Section 4), and potential for human health impacts from exposure to CECs (Section 5). The paper concludes with how changes to water quantity, both scarcity and surpluses, could affect water quality (Section 6). Taken together, these sections document the past 25 years of CEC research and the regulatory response to these contaminants, the current work to identify and monitor CECs and mitigate exposure, and the challenges facing the future.

Vulnerability of wells in unconfined and confined aquifers to modern contamination from flood events

Groundwater is a primary potable water supply for coastal North Carolina (NC), but the increased intensity of extreme rainfall events and floods may exacerbate surface and subsurface processes that contribute anthropogenic chemicals to wells in the major confined aquifers of this region. We evaluated groundwater for organic chemicals of emerging concern (CEC) and the presence of tritium using flooded and not-flooded wells in the NC Department of Environmental Quality well monitoring network across the NC Coastal Plain. Flooded wells experienced standing water around the well casing at least once during the study period. Tritium concentrations, which indicate modern water presence (water recharged after 1953), were significantly greater in groundwater from flooded wells than not-flooded wells. In confined aquifers, modern water was detected at greater depths in flooded wells (206 m) than not-flooded wells (100 m). Suspect-screening high resolution mass spectrometry (HRMS) analysis of 150 groundwater samples yielded a total of 382 unique organic chemicals. Each groundwater sample contained, on average, 19 tentatively identified chemicals from the NIST 20 mass spectral database (M1) and 9 USEPA ToxCast chemicals. The number of tentatively-identified chemicals per sample was not significantly different among aquifers demonstrating the pervasive presence of the detected CECs in unconfined and confined aquifers. The presence of modern water in groundwater from flooded wells coincided with higher detection frequencies of certain organic contaminant classes, particularly pharmaceuticals, food additives, and regulated aromatic hydrocarbons. These results indicate that wells in both unconfined and confined aquifers are susceptible to modern water contamination during flood events; this finding has critical public health implications for coastal communities.

Deep graph convolutional network for small-molecule retention time prediction

The retention time (RT) is a crucial source of data for liquid chromatography-mass spectrometry (LCMS). A model that can accurately predict the RT for each molecule would empower filtering candidates with similar spectra but differing RT in LCMS-based molecule identification. Recent research shows that graph neural networks (GNNs) outperform traditional machine learning algorithms in RT prediction. However, all of these models use relatively shallow GNNs. This study for the first time investigates how depth affects GNNs' performance on RT prediction. The results demonstrate that a notable improvement can be achieved by pushing the depth of GNNs to 16 layers by the adoption of residual connection. Additionally, we also find that graph convolutional network (GCN) model benefits from the edge information. The developed deep graph convolutional network, DeepGCN-RT, significantly outperforms the previous state-of-the-art method and achieves the lowest mean absolute percentage error (MAPE) of 3.3% and the lowest mean absolute error (MAE) of 26.55 s on the SMRT test set. We also finetune DeepGCN-RT on seven datasets with various chromatographic conditions. The mean MAE of the seven datasets largely decreases 30% compared to previous state-of-the-art method. On the RIKEN-PlaSMA dataset, we also test the effectiveness of DeepGCN-RT in assisting molecular structure identification. By 30% lessening the number of potential structures, DeepGCN-RT is able to improve top-1 accuracy by about 11%.

Machine Learning-Based Hazard-Driven Prioritization of Features in Nontarget Screening of Environmental High-Resolution Mass Spectrometry Data

Nontarget high-resolution mass spectrometry screening (NTS HRMS/MS) can detect thousands of organic substances in environmental samples. However, new strategies are needed to focus time-intensive identification efforts on features with the highest potential to cause adverse effects instead of the most abundant ones. To address this challenge, we developed MLinvitroTox, a machine learning framework that uses molecular fingerprints derived from fragmentation spectra (MS2) for a rapid classification of thousands of unidentified HRMS/MS features as toxic/nontoxic based on nearly 400 target-specific and over 100 cytotoxic endpoints from ToxCast/Tox21. Model development results demonstrated that using customized molecular fingerprints and models, over a quarter of toxic endpoints and the majority of the associated mechanistic targets could be accurately predicted with sensitivities exceeding 0.95. Notably, SIRIUS molecular fingerprints and xboost (Extreme Gradient Boosting) models with SMOTE (Synthetic Minority Oversampling Technique) for handling data imbalance were a universally successful and robust modeling configuration. Validation of MLinvitroTox on MassBank spectra showed that toxicity could be predicted from molecular fingerprints derived from MS2 with an average balanced accuracy of 0.75. By applying MLinvitroTox to environmental HRMS/MS data, we confirmed the experimental results obtained with target analysis and narrowed the analytical focus from tens of thousands of detected signals to 783 features linked to potential toxicity, including 109 spectral matches and 30 compounds with confirmed toxic activity.

Adding open spectral data to MassBank and PubChem using open source tools to support non-targeted exposomics of mixtures

The term "exposome" is defined as a comprehensive study of life-course environmental exposures and the associated biological responses. Humans are exposed to many different chemicals, which can pose a major threat to the well-being of humanity. Targeted or non-targeted mass spectrometry techniques are widely used to identify and characterize various environmental stressors when linking exposures to human health. However, identification remains challenging due to the huge chemical space applicable to exposomics, combined with the lack of sufficient relevant entries in spectral libraries. Addressing these challenges requires cheminformatics tools and database resources to share curated open spectral data on chemicals to improve the identification of chemicals in exposomics studies. This article describes efforts to contribute spectra relevant for exposomics to the open mass spectral library MassBank (https://www.massbank.eu) using various open source software efforts, including the R packages RMassBank and Shinyscreen. The experimental spectra were obtained from ten mixtures containing toxicologically relevant chemicals from the US Environmental Protection Agency (EPA) Non-Targeted Analysis Collaborative Trial (ENTACT). Following processing and curation, 5582 spectra from 783 of the 1268 ENTACT compounds were added to MassBank, and through this to other open spectral libraries (e.g., MoNA, GNPS) for community benefit. Additionally, an automated deposition and annotation workflow was developed with PubChem to enable the display of all MassBank mass spectra in PubChem, which is rerun with each MassBank release. The new spectral records have already been used in several studies to increase the confidence in identification in non-target small molecule identification workflows applied to environmental and exposomics research.

Suspect and Nontarget Screening Reveal the Underestimated Risks of Antibiotic Transformation Products in Wastewater Treatment Plant Effluents

Antibiotics are anthropogenic contaminants with a global presence and of deep concern in aquatic environments, while less is known about the occurrence and risks of their transformation products (TPs). Herein, we developed a comprehensive suspect and nontarget screening workflow based on high-resolution mass spectrometry to identify unknown antibiotic TPs in wastewater treatment plant effluents. We identified 211 compounds (35 parent antibiotics and 176 TPs) at confidence levels of ≥3 and 107 TPs originated from macrolides. TPs were quantified by 17 TPs standards and semiquantified by the predicted response factors and accounted for 55.6-95.1% (76.7% on average) of the total concentrations of parents and TPs. 22.2%, 63.1%, and 18.8% of the identified TPs were estimated to be more persistent, mobile, and toxic than their parent antibiotics, respectively. Further ecological risk assessment based on concentrations and toxicity to aquatic organisms revealed that the cumulative risks of TPs were generally higher than those of parents. Despite the newly formed N-oxide TPs, the tertiary treatment process (mainly ozonation) could decrease the averaged 20.3% of concentrations and 36.2% of the risks of antibiotic-related compounds. This study highlights the necessity to include antibiotic TPs in environmental scrutiny and risk assessment of antibiotics in different aquatic environments.

Per- and Polyfluoroalkyl Substances (PFAS) in PubChem: 7 Million and Growing

Per- and polyfluoroalkyl substances (PFAS) are of high concern, with calls to regulate them as a class. In 2021, the Organisation for Economic Co-operation and Development (OECD) revised the definition of PFAS to include any chemical containing at least one saturated CF2 or CF3 moiety. The consequence is that one of the largest open chemical collections, PubChem, with 116 million compounds, now contains over 7 million PFAS under this revised definition. These numbers are several orders of magnitude higher than previously established PFAS lists (typically thousands of entries) and pose an incredible challenge to researchers and computational workflows alike. This article describes a dynamic, openly accessible effort to navigate and explore the >7 million PFAS and >21 million fluorinated compounds (September 2023) in PubChem by establishing the "PFAS and Fluorinated Compounds in PubChem" Classification Browser (or "PubChem PFAS Tree"). A total of 36500 nodes support browsing of the content according to several categories, including classification, structural properties, regulatory status, or presence in existing PFAS suspect lists. Additional annotation and associated data can be used to create subsets (and thus manageable suspect lists or databases) of interest for a wide range of environmental, regulatory, exposomics, and other applications.

What is in the fish? Collaborative trial in suspect and non-target screening of organic micropollutants using LC- and GC-HRMS

A collaborative trial involving 16 participants from nine European countries was conducted within the NORMAN network in efforts to harmonise suspect and non-target screening of environmental contaminants in whole fish samples of bream (Abramis brama). Participants were provided with freeze-dried, homogenised fish samples from a contaminated and a reference site, extracts (spiked and non-spiked) and reference sample preparation protocols for liquid chromatography (LC) and gas chromatography (GC) coupled to high resolution mass spectrometry (HRMS). Participants extracted fish samples using their in-house sample preparation method and/or the protocol provided. Participants correctly identified 9-69 % of spiked compounds using LC-HRMS and 20-60 % of spiked compounds using GC-HRMS. From the contaminated site, suspect screening with participants' own suspect lists led to putative identification of on average ∼145 and ∼20 unique features per participant using LC-HRMS and GC-HRMS, respectively, while non-target screening identified on average ∼42 and ∼56 unique features per participant using LC-HRMS and GC-HRMS, respectively. Within the same sub-group of sample preparation method, only a few features were identified by at least two participants in suspect screening (16 features using LC-HRMS, 0 features using GC-HRMS) and non-target screening (0 features using LC-HRMS, 2 features using GC-HRMS). The compounds identified had log octanol/water partition coefficient (KOW) values from -9.9 to 16 and mass-to-charge ratios (m/z) of 68 to 761 (LC-HRMS and GC-HRMS). A significant linear trend was found between log KOW and m/z for the GC-HRMS data. Overall, these findings indicate that differences in screening results are mainly due to the data analysis workflows used by different participants. Further work is needed to harmonise the results obtained when applying suspect and non-target screening approaches to environmental biota samples.