Approaches for assessing performance of high-resolution mass spectrometry-based non-targeted analysis methods

Chemical safety screening of products - better proactive

The increasing pressure to ensure product safety in a global market comes up against the current practice of targeting only known hazardous compounds in product safety analysis. However, product safety refers not only to known but also to unknown or hidden hazards that are very important to know and avoid. Shortcomings and limitations of currently used technologies seem to cause an obvious discrepancy between intended and actual consumer protection. Products are not as safe as claimed by stakeholders. An existing but overlooked proactive safety screening with a prioritization strategy is brought into focus as it offers a unique solution. It can handle the complexity of a product with thousands of compounds of unknown identity and unknown toxicity and can figure out the important hazardous compounds, both known and unknown. Using hardly any sample preparation and the effect detection at an early position in the workflow is a game changer not to overlook hazardous compounds. All analytical technologies are needed, but the key is the re-arrangement of the instrument order, i.e. firstly hazard-related screening (effect first) and secondly, focus on identification of prioritized hazardous compounds. Such a proactive safety screening revealed previously unknown hazardous compounds in products on the market claimed to be safe. The highly sustainable, affordable, and all-in-one 2LabsToGo-Eco with easy-to-use planar bioassays empowers stakeholders to implement proactive safety screening and dynamic risk management. The transition to greater efficacy in consumer protection needs incentives and the critical review aims to stimulate a debate.

Pharmaceutical residues and chemicals in landfill leachate from a sanitary landfill in Malaysia: non-target analysis and records of health and environmental hazards

Pharmaceutical residues (PRs) and pharmaceutical chemicals (PCs) have been detected in landfill leachate though landfill sites have no direct role in managing pharmaceutical wastes. However, their detailed exploration is still challenging in leachate samples due to their vast array of metabolites and complex interactions. The present study is aimed to perform a non-target analysis of PRs and PCs in leachate from a sanitary landfill in Malaysia. Cross-sectional study of total 28 samples was conducted at Jeram Sanitary Landfill at Selangor, Malaysia, from July 2023 to October 2023. Grab sample of fresh untreated leachate was collected in a borosilicate glass bottle near leachate collection pond. The centrifuged supernatant liquid was analyzed with LCMS-QTOF system. The chromatographic profiles were analyzed based on mass data, and the compounds were annotated using METLIN database. A total of 7125 PRs and PCs were detected, out of which 1,288 were PRs (mean ± SD 46.00 ± 35.70) and 5837 were PCs (mean ± SD 208.46 ± 102.38). There were 1862 (25.6%) cases of health hazards, and 212 (3.0%) cases of environmental hazards caused by various PRs. Similarly, leachate was laden with various PCs that could cause 2417 (33.7%) cases of health hazards, and 312 (4.4%) cases of environmental hazards. These health hazards were caused by various mechanisms such as toxicity, hypersensitivity, neurotoxicity, carcinogenicity and other. Similarly, environmental hazards were mediated by ecotoxicity, persistence and biomagnification. The results showed the dire scenario of PRs and chemicals in leachate. This implies that urgent interventions be instituted in waste segregation and disposal of people and healthcare facilities to restrict entry of pharmaceutical products and chemicals into non-hazardous waste landfill without prior stabilization.

Nontargeted Urinary Profiling Strategy for Endocrine-Disrupting Chemicals in Women with Ovarian Malignancies

Endocrine-disrupting chemicals (EDCs), including known and unknown parent compounds, their metabolites, and transformation products, are pervasive in daily life, posing increasing risks to human health and the environment. This study employed a high-resolution mass spectrometry-based nontargeted screening approach, integrating polar (HILIC) and reversed-phase separations to expand the chemical space coverage and, supported by open-science tools and resources, evaluated urinary chemical profiles to assess internal EDC exposure. Among 106 annotated biomarkers of exposure, six exhibited significantly higher normalized intensities in patients with ovarian malignancies compared to healthy controls (p < 0.05). This suggests their greater exposure to phthalates (diethylhexyl phthalate and diethyl phthalate), pesticides (metolachlor metabolite and 4-nitrophenol), a UV filter (benzophenone-1), and an industrial byproduct (4-methyl-2-nitrophenol). These compounds may interfere with hormonal regulation, potentially contributing to cancer development. While these findings highlight potential differences in internal EDC exposure, the study primarily demonstrates the applicability of nontargeted urinary profiling for chemical exposure assessment. By providing new insights into EDCs burden and its pathological implications, this work contributes to advancing next-generation chemical risk assessment within the European Partnership for the Assessment of Risks from Chemicals initiative and supports the development of preventive strategies to mitigate environmental cancer risks.

Strategy to improve the confidence level of qualitative screening by high resolution mass spectrometry: A case study of mycotoxins in maize

Targeted, suspect and non-targeted screening by high-resolution mass spectrometry (HRMS) is developing rapidly. In this study, a qualitative screening method was established using HPLC-HRMS on data dependent acquisition for the analysis of mycotoxins in maize. To ensure the sensitivity and applicability of the method, 41 mycotoxin standards were applied for method optimization. A quantitative structure-retention relationships (QSRR) model was developed for retention time prediction and projection using machine learning, providing supplementary evidence for molecule annotation. The predicted errors were all below 0.5 min, contributing to improve the confidence level of suspect and non-targeted screening for mycotoxins. Thresholds affecting the accuracy of screening results were also investigated systematically. Performance metrics including Accuracy, F1 score, Matthew's correlation coefficient (MCC) were introduced to evaluate the qualitative screening method. The developed method was applied in the qualitative screening of collected maize samples, where 11 mycotoxins were screened at high confidence level.

The application of PTR-MS and non-targeted analysis to characterize VOCs emitted from a plastic recycling facility fire

BACKGROUND

On April 11th, 2023, the My Way Trading (MWT) recycling facility in Richmond, Indiana caught fire, mandating the evacuation of local residents and necessitating the U.S. Environmental Protection Agency (EPA) to conduct air monitoring. The EPA detected elevated levels of plastic combustion-related air pollutants, including hydrogen cyanide and benzene.

OBJECTIVE

We aimed to identify these and other volatile organic compounds (VOCs) present as well as to identify the potential hazard of each compound for various human health effects.

METHODS

To identify the VOCs, we conducted air monitoring at sites within and bordering the evacuation zone using proton transfer reaction mass spectrometry (PTR-MS) and non-targeted analysis (NTA). To facilitate risk assessment of the emitted VOCs, we used the EPA Hazard Comparison Dashboard.

RESULTS

We identified 46 VOCs, within and outside the evacuation zone, with average detection levels above local background levels measured in Middletown, OH. Levels of hydrogen cyanide and 4 other VOCs were at least 1.8-fold higher near the incidence site in comparison to background levels and displayed unique temporal and spatial patterns. The 46 VOCs identified had the highest hazardous potential for eye and skin irritation, with approximately 45% and 39%, respectively, of the VOCs classified as high and very high hazards for these endpoints. Notably, all detected VOC levels were below the hazard thresholds set for single VOC exposures; however, hazard thresholds for exposure to VOC mixtures are currently unclear.

IMPACT

This study serves as a proof-of-concept that PTR-MS coupled with NTA can facilitate rapid identification and hazard assessment of VOCs emitted following anthropogenic disasters. Furthermore, it demonstrates that this approach may augment future disaster responses to quantify additional VOCs present in complex combustion mixtures.

Combining non-targeted high resolution mass spectrometry with effect-directed analysis to identify contaminants of emerging concern in the field of ecotoxicology: A systematic quantitative literature review

Methods for measuring environmental toxicity and identifying chemical toxicity drivers using non-targeted analysis (NTA) were reviewed in this systematic quantitative literature review. Effect-directed analysis (EDA) was used to assess sample toxicity and prioritise NTA sample analysis. The most common bioassays performed were estrogen, androgen and aryl hydrocarbon receptor assays, with many studies using test batteries. Across the 95 studies in this review, the toxicity could be explained (>75 %) for eight studies, four studies had toxicity endpoints explained and unexplained, and 38 studies had unexplained (<75 %) toxicity. The addition of NTA allowed for toxicity to be explained with a median of 47 % for TOXnon-target studies and 34 % for TOXtarget+non-target, far higher than the 13 % median for TOXtarget studies within this review. The outcomes of identification were affected by method factors including sample extraction, chromatography method, data acquisition and data processing. Method factors with the biggest potential to introduce selection bias were sample extraction and chromatography technique. These factors were characterised by a high representation of reverse phase liquid chromatography contributing to the selective exclusion of polar, highly polar and ionic compounds from sample analysis. This reduces compound identification and excludes unknown chemical contaminants from analysis. Not all studies reported the explained toxicity contribution of identified compounds, however it was evident that many compound features could not be identified using NTA processing software. There were severe limitations for liquid chromatography data compared to gas chromatography data with insufficient spectral library databases for spectra matching. This bottleneck is partially solved through the rise in in silico and retention time prediction software. Future work, including increasing spectral databases for liquid chromatography, use of less biased chromatography and sample preparation techniques and inclusion of EDA-NTA into risk assessment frameworks, will allow for better toxicity assessment of emerging contaminants.

Automated QA/QC reporting for non-targeted analysis: a demonstration of "INTERPRET NTA" with de facto water reuse data

The US Environmental Protection Agency (EPA) uses non-targeted analysis (NTA) to characterize potential risks associated with environmental pollutants and anthropogenic materials. NTA is used throughout EPA's Office of Research and Development (ORD) to support the needs of states, tribes, EPA regions, EPA program offices, and other outside partners. NTA methods are complex and conducted via myriad instrumental platforms and software products. Comprehensive standards do not yet exist to guide NTA quality assurance/quality control (QA/QC) procedures. Furthermore, no single software tool meets EPA's needs for QA/QC review and documentation. Considering these factors, ORD developed "INTERPRET NTA" (Interface for Processing, Reviewing, and Translating NTA data) to support liquid chromatography (LC) high-resolution mass spectrometry (HRMS) NTA experiments. For purposes of NTA QA/QC, INTERPRET NTA (1) calculates data quality statistics related to accuracy, precision, and reproducibility; (2) produces interactive visualizations to facilitate quality threshold optimization; and (3) outputs comprehensive documentation for inclusion in official reports and research publications. INTERPRET NTA has additional functionality to facilitate rapid chemical identification and risk-based prioritization. The current article describes only the QA/QC elements of INTERPRET NTA's MS1 workflow, which are demonstrated using published data from a de facto water reuse study. INTERPRET NTA, in its current form, exists primarily to meet the needs of EPA and its partners, but a public release is planned. Workflows, terminology, and outputs of INTERPRET NTA provide a focal point for necessary discussions on the harmonization of NTA QA/QC practices.

Community Needs and Proposed Solutions for a Broadly Applicable Standard/QC Mixture for High-Resolution Mass Spectrometry-Based Non-Targeted Analysis

Non-targeted analysis (NTA) using high-resolution mass spectrometry (HRMS) is a global chemical screening approach that generates information-rich data which can be used to detect and identify unknown chemicals. NTA is a powerful approach which is increasingly being used for a variety of sample types, research fields, and goals. However, there are challenges associated with accurate assessments of data quality and method performance, comparability across laboratories/instruments/methods, and communication of results/confidence. A standard mixture containing a sufficient number and diversity of chemicals would help address these needs, but is not yet commercially available. Thus, we conducted a survey of 146 NTA researchers to examine desired requirements for the broad fields, studies, and goals where NTA can be applied. We also compare this feedback to previously published in-house standard mixtures, which, we argue, are models for a standard that can be adjusted to fit the NTA community's needs and possibly commercialized. Reversed-phase liquid chromatography HRMS is one of the most common methods used for NTA; therefore, this survey is focused on characteristics necessary for these types of methods. We intend this information to communicate the need for an interdisciplinary NTA standard mixture, the importance of implementing standards, and to lower the barriers for chemical vendor standard mixture development and distribution.

Communicating with Stakeholders to Identify High-Impact Research Directions for Non-Targeted Analysis

Non-targeted analysis (NTA) using high-resolution mass spectrometry without defined chemical targets has the potential to expand and improve chemical monitoring in many fields. Despite rapid advancements within the research community, NTA methods and data remain underutilized by many potential beneficiaries. To better understand barriers toward widespread adoption, the Best Practices for Non-Targeted Analysis (BP4NTA) working group conducted focus group meetings and follow-up surveys with scientists (n = 61) from various sectors (e.g., drinking water utilities, epidemiologists, n = 9) where NTA is expected to provide future value. Meeting participants included producers and end-users of NTA data with a wide range of familiarity with NTA methods and outputs. Discussions focused on identifying specific barriers that limit adoption and on setting NTA product development priorities. Stated priorities fell into four major categories: 1) education and training materials; 2) QA/QC frameworks and study design guidance; 3) accessible compound databases and libraries; and 4) NTA data linkages with chemical fate and toxicity information. Based on participant feedback, this manuscript proposes research directions, such as standardization of training materials, that BP4NTA and other institutions can pursue to expand NTA use in various application scenarios and decision contexts.

Updated Guidance for Communicating PFAS Identification Confidence with Ion Mobility Spectrometry

Over the last decade, global contamination from per- and polyfluoroalkyl substances (PFAS) has become apparent due to their detection in countless matrices worldwide, from consumer products to human blood to drinking water. As researchers implement non-targeted analyses (NTA) to more fully understand the PFAS present in the environment and human bodies, clear guidance is needed for consistent and objective reporting of the identified molecules. While confidence levels for small molecules analyzed and identified with high-resolution mass spectrometry (HRMS) have existed since 2014, unification and automation of these levels is needed due to inconsistencies in reporting and continuing innovations in analytical methods. Here, we (i) investigate current practices for confidence level reporting of PFAS identified with liquid chromatography (LC), gas chromatography (GC), and/or ion mobility spectrometry (IMS) coupled with high resolution mass spectrometry (HRMS) and (ii) propose a simple, unified confidence level guidance that incorporates both PFAS-specific attributes and IMS collision cross section (CCS) values.

Comprehensive screening and analysis of pharmaceuticals and pharmaceutically active chemicals in wastewater: health and environmental hazards and removal efficiency of wastewater treatment plant in Malaysia

Wastewater treatment plant (WWTP) is a sustainable technique for making wastewater reusable for non-potable purposes. However, in developing countries, most conventional WWTPs are not equipped to trap all pharmaceutical residues (PRs) and pharmaceutically active chemicals (PhACs). This study aims to perform non-target screening of these contaminants in wastewater and explore health and environmental hazards and the removal efficiency of a WWTP in Malaysia. At Indah Water WWTP, a total of 28 wastewater samples (i.e., 2 L each of 14 influent and 14 effluent) were collected every day for a week from February to April 2023. The supernatant of the centrifuged sample was analyzed with the LCMS-QTOF system. Chromatographic profiles were analyzed, and the compounds were annotated using the METLIN database. Categorical data were statistically analyzed with SPSS 29.0 using a chi-square test and continuous variables using paired t-test and multiple regression. PRs like micronutrient (9, 2.3%) and PhACs like lipid (83, 20.8%) were more frequent. Detection frequencies of PRs and PhACs were 72 (18%) and 328 (82%), respectively. Efficiency of WWTP was 36.4 to 100% for PRs removal (mean ± SD: 65.85 ± 56.43%) and 20 to 100% for PhACs removal (mean ± SD: 49.30 ± 55.94%). A total of 943 (mean ± SD: 67.36 ± 43.28) and 400 (mean ± SD: 28.57 ± 32.44) unique PRs and PhACs were recorded. A total of 40 (10%) PRs and PhACs had the potential to irritate eyes, skin, and respiratory tract, and 46 (11.5%) chemicals needed to be avoided from being discharged into the environment. Though WWTP was 98.0% compliant with environmental standards, its efficiency should still be increased to remove the full range of PRs and PhACs. The research has implications for SDGs 6 and 14.

Development and application of a non-targeted analysis method using GC-MS and LC-MS for identifying chemical contaminants in drinking water via point-of-use filters

While many chemicals are regulated and routinely monitored in drinking water, they represent just a portion of all contaminants that may be present. Typical drinking water analyses involve sampling one liter or less of water, which could lead to trace level contaminants going undetected. In this study, a method was developed for using point-of-use activated carbon block drinking water filters as sampling devices. The filters were extracted to remove chemicals that were collected, and then analyzed by non-targeted analysis via liquid chromatography and gas chromatography high-resolution mass spectrometry. Extraction efficiencies were assessed by spiking and recovery experiments to better understand the chemical space coverage. To test the method's applicability to real-world samples, filters from a small-scale pilot study were collected from individuals in New York, NY and Atlanta, GA and analyzed. Twenty tentatively identified chemical candidates were confirmed by comparison to chemical standards. Principal components analysis was performed on the full set of filtered chemical features to explore how geographic and temporal differences in samples impact drinking water composition. Product use categories for confirmed chemicals were explored to determine potential sources of contaminants.

Prioritization before dereplication, an effective strategy to target new metabolites in whole extracts: ghosalin from Murraya paniculata root

Re-discovery of known metabolites is a common challenge in natural product-based drug discovery, and to avoid re-discovery, dereplication has been proposed for identifying known metabolites at the early stage of isolation. A majority of methods use LCMS to profile the extract and ignore the known mass. LC-HRMS profiling may generate a long mass list of metabolites. The identification of a new metabolite is difficult within the mass list. To overcome this, it was hypothesized that identifying a 'new metabolite' in the whole metabolome is more difficult than identifying it within the class of metabolites. A prioritization strategy was proposed to focus on the elimination of unknown and uncommon metabolites first using the designed bias filters and to prioritize the known secondary metabolites. The study employed Murraya paniculata root for the identification of new metabolites. The LC-HRMS-generated mass list of 509 metabolites was subjected to various filters, which resulted in 93 metabolites. Subsequently, it was subjected to regular dereplication, resulting in 10 coumarins, among which 3 were identified as new. Further, chromatographic efforts led to the isolation of a new coumarin, named ghosalin (1). The structure of the new compound was established through 2D NMR and X-ray crystallography. Cytotoxicity studies revealed that ghosalin has significant cytotoxicity against cancer cell lines. The proposed prioritization strategy demonstrates an alternative way for the rapid annotation of a particular set of metabolites to isolate a new metabolite from the whole metabolome of a plant extract.

Prioritization, Identification, and Quantification of Emerging Contaminants in Recycled Textiles Using Non-Targeted and Suspect Screening Workflows by LC-ESI-HRMS

Recycled textiles are becoming widely available to consumers as manufacturers adopt circular economy principles to reduce the negative impact of garment production. Still, the quality of the source material directly impacts the final product, where the presence of harmful chemicals is of utmost concern. Here, we develop a risk-based suspect and non-targeted screening workflow for the detection, identification, and prioritization of the chemicals present in consumer-based recycled textile products after manufacture and transport. We apply the workflow to characterize 13 recycled textile products from major retail outlets in Sweden. Samples were extracted and analyzed by liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS). In positive and negative ionization mode, 20,119 LC-HRMS features were detected and screened against persistent, mobile, and toxic (PMT) as well as other textile-related chemicals. Six substances were matched with PMT substances that are regulated in the European Union (EU) with a Level 2/3 confidence. Forty-three substances were confidently matched with textile-related chemicals reported for use in Sweden. For estimating the relative priority score, aquatic toxicity and concentrations were predicted for 7416 features with tandem mass spectra (MS2) and used to rank the non-targeted features. The top 10 substances were evaluated due to elevated environmental risk linked to the recycling process and potential release at end-of-life.

Fingerprinting of emerging contaminants in L'Albufera natural park (Valencia, Spain): Implications for wetland ecosystem health

Wetlands are crucial ecosystems that are increasingly threatened by anthropogenic activities. L'Albufera Natural Park, the second-largest coastal wetland in Spain, faces significant pressures from surrounding agricultural lands, industrial activities, human settlements, and associated infrastructures, including treated wastewater inputs. This study aimed at (i) establishing pathways of emerging pollutants entering the natural wetland using both target and non-target screening (NTS) for management purposes, (ii) distinguishing specific contamination hotspots through Geographic Information System (GIS) and (iii) performing basic ecological risk assessment to evaluate ecosystem health. Two sampling campaigns were conducted in the spring and summer of 2019, coinciding with the start and end of the rice cultivation season, the region's primary agricultural activity. Each campaign involved the collection of 51 samples. High-resolution mass spectrometry (HRMS) was employed, using a simultaneous NTS approach with optimized gradients for pesticides and moderately polar compounds, along with complementary NTS methods for polar compounds, to identify additional contaminants of emerging concern (CECs). Quantitative analysis revealed that fungicides comprised a substantial portion of detected CECs, constituting approximately 50% of the total quantified pesticides. Tebuconazole emerged as the predominant fungicide, with the highest mean concentration (>16.9 μg L-1), followed by azoxystrobin and tricyclazole. NTS tentatively identified 16 pesticides, 43 pharmaceuticals and personal care products (PPCPs), 24 industrial compounds, and 12 other CECs with high confidence levels. Spatial distribution analysis demonstrated significant contamination predominantly in the southwestern region of the park, gradually diminishing towards the north-eastern outlet. The composition of contaminants varied between water and sediment samples, with pharmaceuticals predominating in water and industrial compounds in sediments. Risk assessment, evaluated through risk quotient calculations based on parent compound concentrations, revealed a decreasing trend towards the outlet, suggesting wetland degradation capacity. However, significant risk levels persist throughout much of the Natural Park, highlighting the urgent need for mitigation measures to safeguard the integrity of this vital ecosystem.

High-Resolution Mass Spectrometry for Human Exposomics: Expanding Chemical Space Coverage

In the modern "omics" era, measurement of the human exposome is a critical missing link between genetic drivers and disease outcomes. High-resolution mass spectrometry (HRMS), routinely used in proteomics and metabolomics, has emerged as a leading technology to broadly profile chemical exposure agents and related biomolecules for accurate mass measurement, high sensitivity, rapid data acquisition, and increased resolution of chemical space. Non-targeted approaches are increasingly accessible, supporting a shift from conventional hypothesis-driven, quantitation-centric targeted analyses toward data-driven, hypothesis-generating chemical exposome-wide profiling. However, HRMS-based exposomics encounters unique challenges. New analytical and computational infrastructures are needed to expand the analysis coverage through streamlined, scalable, and harmonized workflows and data pipelines that permit longitudinal chemical exposome tracking, retrospective validation, and multi-omics integration for meaningful health-oriented inferences. In this article, we survey the literature on state-of-the-art HRMS-based technologies, review current analytical workflows and informatic pipelines, and provide an up-to-date reference on exposomic approaches for chemists, toxicologists, epidemiologists, care providers, and stakeholders in health sciences and medicine. We propose efforts to benchmark fit-for-purpose platforms for expanding coverage of chemical space, including gas/liquid chromatography-HRMS (GC-HRMS and LC-HRMS), and discuss opportunities, challenges, and strategies to advance the burgeoning field of the exposome.

Identification and quantification of medical device extractables and leachables via non-target analysis (NTA); Analytical uncertainty

Leachables are substances that are leached from a medical device during its clinical use and are important due to the patient health-related effects they may have. Thus, medical devices are profiled for leachables (and/or extractables as probable leachables) to assess their potential impact on patient health and safety. This profiling is accomplished by screening extracts or leachates of the medical device for released organic substances via non-targeted analysis (NTA) employing chromatographic methods coupled with mass spectrometric detection. Chromatographic mass spectral response factors (RFs) for extractables and leachables vary significantly from compound to compound, complicating the quantitation of these compounds and the application of assessment strategies such as the Analytical Evaluation Threshold (AET). The analytical uncertainty resulting from response factor variation can be expressed in terms of an uncertainty factor (UF), which estimates the magnitude of response factor variation. This manuscript discusses the concept and impact of analytical uncertainty and provides best practice recommendations for the calculation and use of the uncertainty factor, UF.

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.

Non-target screening in water analysis: recent trends of data evaluation, quality assurance, and their future perspectives

This trend article provides an overview of recent advancements in Non-Target Screening (NTS) for water quality assessment, focusing on new methods in data evaluation, qualification, quantification, and quality assurance (QA/QC). It highlights the evolution in NTS data processing, where open-source platforms address challenges in result comparability and data complexity. Advanced chemometrics and machine learning (ML) are pivotal for trend identification and correlation analysis, with a growing emphasis on automated workflows and robust classification models. The article also discusses the rigorous QA/QC measures essential in NTS, such as internal standards, batch effect monitoring, and matrix effect assessment. It examines the progress in quantitative NTS (qNTS), noting advancements in ionization efficiency-based quantification and predictive modeling despite challenges in sample variability and analytical standards. Selected studies illustrate NTS's role in water analysis, combining high-resolution mass spectrometry with chromatographic techniques for enhanced chemical exposure assessment. The article addresses chemical identification and prioritization challenges, highlighting the integration of database searches and computational tools for efficiency. Finally, the article outlines the future research needs in NTS, including establishing comprehensive guidelines, improving QA/QC measures, and reporting results. It underscores the potential to integrate multivariate chemometrics, AI/ML tools, and multi-way methods into NTS workflows and combine various data sources to understand ecosystem health and protection comprehensively.

Online and Offline Prioritization of Chemicals of Interest in Suspect Screening and Non-targeted Screening with High-Resolution Mass Spectrometry

Recent advances in high-resolution mass spectrometry (HRMS) have enabled the detection of thousands of chemicals from a single sample, while computational methods have improved the identification and quantification of these chemicals in the absence of reference standards typically required in targeted analysis. However, to determine the presence of chemicals of interest that may pose an overall impact on ecological and human health, prioritization strategies must be used to effectively and efficiently highlight chemicals for further investigation. Prioritization can be based on a chemical's physicochemical properties, structure, exposure, and toxicity, in addition to its regulatory status. This Perspective aims to provide a framework for the strategies used for chemical prioritization that can be implemented to facilitate high-quality research and communication of results. These strategies are categorized as either "online" or "offline" prioritization techniques. Online prioritization techniques trigger the isolation and fragmentation of ions from the low-energy mass spectra in real time, with user-defined parameters. Offline prioritization techniques, in contrast, highlight chemicals of interest after the data has been acquired; detected features can be filtered and ranked based on the relative abundance or the predicted structure, toxicity, and concentration imputed from the tandem mass spectrum (MS2). Here we provide an overview of these prioritization techniques and how they have been successfully implemented and reported in the literature to find chemicals of elevated risk to human and ecological environments. A complete list of software and tools is available from https://nontargetedanalysis.org/.

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.

Establishing performance metrics for quantitative non-targeted analysis: a demonstration using per- and polyfluoroalkyl substances

Non-targeted analysis (NTA) is an increasingly popular technique for characterizing undefined chemical analytes. Generating quantitative NTA (qNTA) concentration estimates requires the use of training data from calibration "surrogates," which can yield diminished predictive performance relative to targeted analysis. To evaluate performance differences between targeted and qNTA approaches, we defined new metrics that convey predictive accuracy, uncertainty (using 95% inverse confidence intervals), and reliability (the extent to which confidence intervals contain true values). We calculated and examined these newly defined metrics across five quantitative approaches applied to a mixture of 29 per- and polyfluoroalkyl substances (PFAS). The quantitative approaches spanned a traditional targeted design using chemical-specific calibration curves to a generalizable qNTA design using bootstrap-sampled calibration values from "global" chemical surrogates. As expected, the targeted approaches performed best, with major benefits realized from matched calibration curves and internal standard correction. In comparison to the benchmark targeted approach, the most generalizable qNTA approach (using "global" surrogates) showed a decrease in accuracy by a factor of ~4, an increase in uncertainty by a factor of ~1000, and a decrease in reliability by ~5%, on average. Using "expert-selected" surrogates (n = 3) instead of "global" surrogates (n = 25) for qNTA yielded improvements in predictive accuracy (by ~1.5×) and uncertainty (by ~70×) but at the cost of further-reduced reliability (by ~5%). Overall, our results illustrate the utility of qNTA approaches for a subclass of emerging contaminants and present a framework on which to develop new approaches for more complex use cases.

Quantification of chemicals in non-targeted analysis without analytical standards - Understanding the mechanism of electrospray ionization and making predictions

The constant creation and release of new chemicals to the environment is forming an ever-widening gap between available analytical standards and known chemicals. Developing non-targeted analysis (NTA) methods that have the ability to detect a broad spectrum of compounds is critical for research and analysis of emerging contaminants. There is a need to develop methods that make it possible to identify compound structures from their MS and MS/MS information and quantify them without analytical standards. Method refinements that utilize machine learning algorithms and chemical descriptors to estimate the instrument response of particular compounds have made progress in recent years. This narrative review seeks to summarize the current state of the field of non-targeted analysis (NTA) toward quantification of unknowns without the use of analytical standards. Despite the limited accumulation of validation studies on real samples, the ongoing enhancement in data processing and refinement of machine learning tools could lead to more comprehensive chemical coverage of NTA and validated quantitative NTA methods, thus boosting confidence in their usage and enhancing the utility of quantitative NTA.

A targeted and non-targeted discovery screening approach for poly-and per-fluoroalkyl substances in model environmental biota samples

A comprehensive analytical approach for targeted and non-targeted discovery screening of per- and polyfluoroalkyl substances (PFAS) was developed and applied to model complex environmental biotic samples. Samples were extracted by formic acid-acetonitrile solution and cleaned up and fractionated by SPE (WAX). Target PFAS quantification was performed by ultra-high performance liquid chromatography interfaced with a triple quadrupole mass spectrometer (UPLC-QqQ-MS/MS). Non-targeted analysis (NTA) PFAS screening was performed with UPLC coupled with a quadrupole-Exactive orbitrap high resolution mass spectrometer (UPLC-Q-Exactive-HRMS). An iterative exclusion (IE) approach was applied to data acquisition for NTA suspect screening to increase the potential for unknown PFAS discovery with MS/MS. A complex workflow in Compound Discoverer was set up to automate data processing of the PFAS suspects search. New mass lists and MS/MS databases, which included a large number of PFAS, were set up and introduced into the search for high-throughput structure identification using HRMS techniques. The integrated targeted-NTA method successfully analyzed for legacy and alternative PFAS in model environmental biota samples, namely polar bear liver and bird egg samples. Targeted analysis provided unequivocal identification of well known/established PFAS (mainly perfluoroalkyl acids) with quantification at very low levels. The NTA suspect screening was able to determine a broader range of PFAS. The data analysis method offered high-confidence annotations for PFAS despite lacking available authentic standards. Overall, the analytical coverage of PFAS was greater and elucidated other PFAS present in these model apex predators.

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.

An integrated non-targeted and targeted analysis approach for identification of semi-volatile organic compounds in indoor dust

Household dust contains a wide variety of semi-volatile organic compounds (SVOCs) that may pose health risks. We developed a method integrating non-targeted analysis (NTA) and targeted analysis (TA) to identify SVOCs in indoor dust. Based on a combined use of gas and liquid chromatography with high-resolution mass spectrometry, an automated, time-efficient NTA workflow was developed, and high accuracy was observed. A total of 128 compounds were identified at confidence level 1 or 2 in NIST standard reference material dust (SRM 2585). Among them, 113 compounds had not been reported previously, and this suggested the value of NTA in characterizing contaminants in dust. Additionally, TA was done to avoid the loss of trace compounds. By integrating data obtained from the NTA and TA approaches, SVOCs in SRM 2585 were prioritized based on exposure and chemical toxicity. Six of the top 20 compounds have never been reported in SRM 2585, including melamine, dinonyl phthalate, oxybenzone, diheptyl phthalate, drometrizole, and 2-phenylphenol. Additionally, significant influences of analytical instruments and sample preparation on NTA results were observed. Overall, the developed method provided a powerful tool for identifying SVOCs in indoor dust, which is necessary to obtain a more complete understanding of chemical exposures and risks in indoor environments.

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.

Cutting-edge computational chemical exposure research at the U.S. Environmental Protection Agency

Exposure science is evolving from its traditional "after the fact" and "one chemical at a time" approach to forecasting chemical exposures rapidly enough to keep pace with the constantly expanding landscape of chemicals and exposures. In this article, we provide an overview of the approaches, accomplishments, and plans for advancing computational exposure science within the U.S. Environmental Protection Agency's Office of Research and Development (EPA/ORD). First, to characterize the universe of chemicals in commerce and the environment, a carefully curated, web-accessible chemical resource has been created. This DSSTox database unambiguously identifies >1.2 million unique substances reflecting potential environmental and human exposures and includes computationally accessible links to each compound's corresponding data resources. Next, EPA is developing, applying, and evaluating predictive exposure models. These models increasingly rely on data, computational tools like quantitative structure activity relationship (QSAR) models, and machine learning/artificial intelligence to provide timely and efficient prediction of chemical exposure (and associated uncertainty) for thousands of chemicals at a time. Integral to this modeling effort, EPA is developing data resources across the exposure continuum that includes application of high-resolution mass spectrometry (HRMS) non-targeted analysis (NTA) methods providing measurement capability at scale with the number of chemicals in commerce. These research efforts are integrated and well-tailored to support population exposure assessment to prioritize chemicals for exposure as a critical input to risk management. In addition, the exposure forecasts will allow a wide variety of stakeholders to explore sustainable initiatives like green chemistry to achieve economic, social, and environmental prosperity and protection of future generations.

Practical application guide for the discovery of novel PFAS in environmental samples using high resolution mass spectrometry

BACKGROUND

The intersection of the topics of high-resolution mass spectrometry (HRMS) and per- and polyfluoroalkyl substances (PFAS) bring together two disparate and complex subjects. Recently non-targeted analysis (NTA) for the discovery of novel PFAS in environmental and biological media has been shown to be valuable in multiple applications. Classical targeted analysis for PFAS using LC-MS/MS, though growing in compound coverage, is still unable to inform a holistic understanding of the PFAS burden in most samples. NTA fills at least a portion of this data gap.

OBJECTIVES

Entrance into the study of novel PFAS discovery requires identification techniques such as HRMS (e.g., QTOF and Orbitrap) instrumentation. This requires practical knowledge of best approaches depending on the purpose of the analyses. The utility of HRMS applications for PFAS discovery is unquestioned and will likely play a significant role in many future environmental and human exposure studies.

METHODS/RESULTS

PFAS have some characteristics that make them standout from most other chemicals present in samples. Through a series of tell-tale PFAS characteristics (e.g., characteristic mass defect range, homologous series and characteristic fragmentation patterns), and case studies different approaches and remaining challenges are demonstrated.

IMPACT STATEMENT

The identification of novel PFAS via non-targeted analysis using high resolution mass spectrometry is an important and difficult endeavor. This synopsis document will hopefully make current and future efforts on this topic easier to perform for novice and experienced alike. The typical time devoted to NTA PFAS investigations (weeks to months or more) may benefit from these practical steps employed.

Non-targeted analysis for the screening and semi-quantitative estimates of per-and polyfluoroalkyl substances in water samples from South Florida environments

Per- and polyfluoroalkyl substances (PFAS) are a group of anthropogenic pollutants that are found ubiquitously in surface and drinking water supplies. Due to their persistent nature, bioaccumulative potential, and significant adverse health effects associated with low concentrations, they pose a concern for human and environmental exposure. With the advances in high-resolution mass spectrometry (HRMS) methods, there has been an increasing number of non-targeted analysis (NTA) approaches that allow for a more comprehensive characterization of total PFAS present in environmental samples. In this study, we have developed and compared NTA workflows based on an online solid phase extraction- liquid chromatography high resolution mass spectrometry (online SPE-LC-HRMS) method followed by data processing using Compound Discoverer and FluoroMatch for the screening of PFAS in drinking waters from populated counties in South Florida, as well as in surface waters from Biscayne Bay, Key west, and Everglades canals. Tap water showed the highest number of PFAS features, indicating a poor removal of these chemicals by water treatment or perhaps the breakdown of PFAS precursors. The high number of PFAS features identified only by CD and FluoroMatch emphasizes the complementary aspects of these data processing methods. A Semi-quantitation method for NTA (qNTA) was proposed using a global calibration curve based on existing native standards and internal standards, in which concentration estimates were determined by a regression-based model and internal standard (IS) response factors. NTA play a crucial role in the identification and prioritization of non-traditionally monitored PFAS, needed for the understanding of the toxicological and environmental impact, which are largely underestimated due to the lack of such information for many PFAS.

Untargeted lipidomic profiling of grapes highlights the importance of modified lipid species beyond the traditional compound classes

The aim of this paper is to provide a detailed characterisation of grape lipidome. To achieve this objective, it starts by describing a pipeline implemented in R software to allow the semi-automatic annotation of the detected lipid species. It also provides an extensive description of the different properties of each molecule (such as retention time dependencies, mass accuracy, adduct formation and fragmentation patterns), which allowed the annotations to be made more accurately. Most annotated lipids in the grape samples were (lyso)glycerophospholipids and glycerolipids, although a few free fatty acids, hydroxyceramides and sitosterol esters were also observed. The proposed pipeline also allowed the identification of a series of methylated glycerophosphates never previously observed in grapes. The current results highlight the importance of expanding chemical analyses beyond the classical lipid categories.

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).

Influence of data acquisition modes and data analysis approaches on non-targeted analysis of phthalate metabolites in human urine

Humans are often exposed to phthalates and their alternatives, on account of their widespread use in PVC as plasticizers, which are associated with harmful human effects. While targeted biomonitoring provides quantitative information for exposure assessment, only a small portion of phthalate metabolites has been targeted. This results in a knowledge gap in human exposure to other unknown phthalate compounds and their metabolites. Although the non-targeted analysis (NTA) approach is capable of screening a broad spectrum of chemicals, there is a lack of harmonized workflow in NTA to generate reproducible data within and between different laboratories. The objective of this study was to compare two different NTA data acquisition modes, the data-dependent (DDA) and independent (DIA) acquisition (DDA), as well as two data analysis approaches, based on diagnostic ions and Compound Discoverer software for the prioritization of candidate precursors and identification of unknown compounds in human urine. Liquid chromatography coupled to high-resolution mass spectrometry was used for sample analysis. The combination of three-diagnostic-ion extraction and DDA data acquisition was able to improve data filtering and data analysis for prioritizing phthalate metabolites. With DIA, 25 molecular features were identified in human urine, while 32 molecular features were identified in the same urine samples using DDA data. The number of molecular features identified with level 1 confidence was 11 and 9 using DIA and DDA data, respectively. The study demonstrated that besides sample preparation, the impact of data acquisition must be taken into account when developing a NTA method and a consistent protocol for evaluating such an impact is necessary.