Semi-quantitative non-target analysis of water with liquid chromatography/high-resolution mass spectrometry: How far are we?

Prioritization of monitoring compounds from SNTS identified organic micropollutants in contaminated groundwater using a machine learning optimized ToxPi model

Advanced suspect and non-target screening (SNTS) approach can identify a large number of potential hazardous micropollutants in groundwater, underscoring the need for pinpointing priority pollutants among detected chemicals. This present study therefore demonstrates a novel multi-criteria decision making (MCDM) framework utilizing machine learning (ML) algorithms coupled with toxicological prioritization index tool (i.e., ml_ToxPi) to rank 252 chemicals of interest in groundwater for subsequent targeted analysis. The MCDM framework integrated chemical analysis data (i.e., peak area and detection frequency), toxicity profiles (i.e., bioactivity ratio, human exposure metadata, and carcinogenicity metadata), as well as the environmental fate and transport information (i.e., octanol-water partition coefficient (log Kow), water solubility, biodegradation half-life, and soil adsorption coefficient (Koc)) for ranking the identified pollutants, and the random forest machine learning model was useful for systematically determining the weighting factors of each variable according to their variable importance scores (R2 = 0.808 and 0.778 for training and testing datasets, respectively, while RMSE = 0.042 in both cases). A total of 47 unique high priority compounds (i.e., ml_ToxPi score ≥ 0.55) were identified across the investigated sampling regions, which constituted diverse groups of compounds classified according to their chemical uses, such as alkylated polycyclic aromatic hydrocarbons (alkyl-PAHs), organophosphate flame retardants (OPFRs), parent PAHs, personal care products (PCPs), pesticides, pharmaceuticals, phenols, plasticizers, transformation product (TPs), and other industrial use chemicals. By incorporating relevant variables into the proposed ML-optimized ToxPi MCDM framework, the prioritization approach described here may be adopted in future SNTS assessment of environmental and biological media.

Identification of organic contaminants in water and related matrices using untargeted liquid chromatography high-resolution mass spectrometry screening with MS/MS libraries

Nontargeted and suspect screening with liquid chromatography-high resolution mass spectrometry (LC-HRMS) has become an indispensable tool for quality assessment in the aquatic environment - complementary to targeted analysis of organic (micro)contaminants. An LC-HRMS method is presented, suitable for the analysis of a wide variety of water related matrices: surface water, groundwater, wastewater, sediment and sludge, including extracts from passive samplers and on-site solid phase enrichment, while focusing on the data processing aspect of the method. A field study is included to demonstrate the practical application and versatility of the whole process. HRMS/MS data were recorded following LC separation in both (ESI) positive and negative ionization modes using data dependent as well as data independent acquisition. Two vendor (Agilent's Personal Compound Database and Library and from National Institute of Standards and Technology) and one open (MassBank/EU) tandem mass spectral libraries were utilized for the identification of compounds via mass spectral match. The development of a novel software tool for parsing, grouping and reduction of MS/MS features in data files converted to mascot generic format (MGF) helped to substantially decrease the amount of time and effort needed for MS library search. While applying the method, in the course of the entire field study, 18771 detections (from 870 individual compounds) in total were recorded in 275 samples, resulting in 68.3 identified compounds per sample, on average. Among the top ten most frequently detected contaminants across all samples and sample types were pharmaceutical compounds carbamazepine, 4-acetamidoantipyrine, 4-formylaminoantipyrine, tramadol, lamotrigine and phenazone and industrial contaminants toluene-2-sulfonamide, tolytriazole, tris(2-butoxyethyl) phosphate and benzotriazole. Exploratory data analysis methods and tools enabled us to discover organic pollutant occurrence patterns within the comprehensive sets of qualitative data collected from various projects between the years 2018-2023. The results may be used as valuable inputs for future water quality monitoring programs.

Farmland's silent threat: Comprehensive multimedia assessment of micropollutants through non-targeted screening and targeted analysis in agricultural systems

Intricate agricultural ecosystems markedly influence the dynamics of organic micropollutants, posing substantial threats to aquatic organisms and human health. This study examined the occurrence and distribution of organic micropollutants across soils, ditch sediment, and water within highly intensified farming setups. Using a non-targeted screening method, we identified 405 micropollutants across 10 sampling sites, which mainly included pesticides, pharmaceuticals, industrial chemicals, and personal care products. This inventory comprised emerging contaminants, banned pesticides, and controlled pharmaceuticals that had eluded detection via conventional monitoring. Targeted analysis showed concentrations of 3.99-1021 ng/g in soils, 4.67-2488 ng/g in sediment, and 12.5-9373 ng/L in water, respectively, for Σ40pesticides, Σ8pharmaceuticals, and Σ3industrial chemicals, indicating notable spatial variability. Soil organic carbon content and wastewater discharge were likely responsible for their spatial distribution. Principal component analysis and correlation analysis revealed a potential transfer of micropollutants across the three media. Particularly, a heightened correlation was decerned between soil and sediment micropollutant levels, highlighting the role of sorption processes. Risk quotients surpassed the threshold of 1 for 13-23 micropollutants across the three media, indicating high environmental risks. This study highlights the importance of employing non-targeted and targeted screening in assessing and managing environmental risks associated with micropollutants.

Assessment of emerging and persistent contaminants in an anthropogenic-impacted watershed: Application using targeted, non-targeted, and in vitro bioassay techniques

Emerging and persistent contaminants (EPC) pose a significant challenge to water quality monitoring efforts. Effect-based monitoring (EBM) techniques provide an efficient and systematic approach in water quality monitoring, but they tend to be resource intensive. In this study, we investigated the EPC distribution for various land uses using target analysis (TA) and non-target screening (NTS) and in vitro bioassays, both individually and integrated, in the upper Ping River Catchment, northern Thailand. Our findings of NTS showed that urban areas were the most contaminated of all land use types, although agriculture sites had high unexpected pollution levels. We evaluated the reliability of NTS data by comparing it to TA and observed varying inconsistencies likely due to matrix interferences and isobaric compound interferences. Integrating NTS with in vitro bioassays for a thorough analysis posed challenges, primary due to a scarcity of concentration data for key compounds, and potentially additive or non-additive effects of mixture samples that could not be accounted for. While EBM approaches place emphasis on toxic sites, this study demonstrated the importance of considering non-bioactive sites that contain toxic compounds with antagonistic effects that may go undetected by traditional monitoring approaches. The present work emphasizes the importance of improving NTS workflows and ensuring high-quality EBM analyses in future water quality monitoring programs.

ICP-MS As a Contributing Tool to Nontarget Screening (NTS) Analysis for Environmental Monitoring

Due to the increasing number of chemicals released into the environment, nontarget screening (NTS) analysis is a necessary tool for providing comprehensive chemical analysis of environmental pollutants. However, NTS workflows encounter challenges in detecting both known and unknown pollutants with common chromatography high-resolution mass spectrometry (HRMS) methods. Identification of unknowns is hindered by limited elemental composition information, and quantification without identical reference standards is prone to errors. To address these issues, we propose the use of inductively coupled plasma mass spectrometry (ICP-MS) as an element-specific detector. ICP-MS can enhance the confidence of compound identification and improve quantification in NTS due to its element-specific response and unambiguous chemical composition information. Additionally, mass balance calculations for individual elements (F, Br, Cl, etc.) enable assessment of total recovery of those elements and evaluation of NTS workflows. Despite its benefits, implementing ICP-MS in NTS analysis and environmental regulation requires overcoming certain shortcomings and challenges, which are discussed herein.

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.

Occurrence and risk assessment of pesticides and their transformation products related to olive groves in surface waters of the Guadalquivir river basin

Pesticides are considered one of the main sources of contamination of surface waters, especially in rural areas highly influenced by traditional agricultural practices. The objective of this work was to evaluate the impact caused by pesticides and their transformation products (TPs) related to olive groves in surface waters with strong agricultural pressure. 11 streams were monitored during four sampling campaigns over 2 years. A solid-phase extraction, followed by ultra-high-performance liquid chromatography coupled to tandem mass spectrometry (UHPLC-MS/MS) analysis was used in the quantitative target approach, with more than 70 validated compounds. Target method was combined with a suspect screening strategy involving more than 500 pesticides and TPs, using ultra-high-performance liquid chromatography coupled to high-resolution mass spectrometry (UHPLC-HRMS) to identify additional pesticides and TPs out of the scope of analysis. A total of 43 different compounds were detected with the target method. The herbicide MCPA was present in all samples and at the highest concentration (1260 ng L-1), followed by the fungicide carbendazim (1110 ng L-1), and the herbicide chlorotoluron (706 ng L-1). The suspect screening strategy revealed the presence of 7 compounds out of the target analysis (1 pesticide and 6 TPs). 6 analytes were confirmed with the analytical standards. Semi-quantification results revealed that TPs exhibited higher concentrations than their corresponding parent compounds, indicating higher persistency. Some small streams showed a comparable number of pesticides and concentrations to the most polluted large river. The determined pesticide and TPs concentrations represented an estimated environmental hazard in almost all sampling sites under study. This work underscores the importance of including pesticide TPs and small streams impacted by extensive agricultural activities in water quality monitoring programs.

Gas Phase Reactivity of Isomeric Hydroxylated Polychlorinated Biphenyls

Identification of stereo- and positional isomers detected with high-resolution mass spectrometry (HRMS) is often challenging due to near-identical fragmentation spectra (MS2), similar retention times, and collision cross-section values (CCS). Here we address this challenge on the example of hydroxylated polychlorinated biphenyls (OH-PCBs) with the aim to (1) distinguish between isomers of OH-PCBs using two-dimensional ion mobility spectrometry (2D-IMS) and (2) investigate the structure of the fragments of OH-PCBs and their fragmentation mechanisms by ion mobility spectrometry coupled to high-resolution mass spectrometry (IMS-HRMS). The MS2 spectra as well as CCS values of the deprotonated molecule and fragment ions were measured for 18 OH-PCBs using flow injections coupled to a cyclic IMS-HRMS. The MS2 spectra as well as the CCS values of the parent and fragment ions were similar between parent compound isomers; however, ion mobility separation of the fragment ions is hinting at the formation of isomeric fragments. Different parent compound isomers also yielded different numbers of isomeric fragment mobilogram peaks giving new insights into the fragmentation of these compounds and indicating new possibilities for identification. For spectral interpretation, Gibbs free energies and CCS values for the fragment ions of 4'-OH-CB35, 4'-OH-CB79, 2-OH-CB77 and 4-OH-CB107 were calculated and enabled assignment of structures to the isomeric mobilogram peaks of [M-H-HCl]- fragments. Finally, further fragmentation of the isomeric fragments revealed different fragmentation pathways depending on the isomeric fragment ions.

Tunnel vision in the drinking water research field - Time for non-targeted analysis implementation?

A plethora of compounds can reach our drinking water and possibly affect human health. Still, mostly notorious pollutants like pesticides and disinfection by-products are monitored and regulated. With the increasing availability of high-resolution mass spectrometers (HRMS), non-targeted analyses of environmental samples have become possible. Pilot studies demonstrating the applicability of this approach in the drinking water research field were published. We would like to highlight these studies and appeal to researchers focused on water quality to better exploit the potential of HRMS instruments and broaden the scale of studied pollutants. In addition, the data and experience should be further shared, and the quality standard for the analytical procedures should be set. With advanced knowledge of compounds reaching the drinking water, potential threats would be revealed, and the comprehensive results on water pollution might also act as impulses for associated research branches, including toxicity assessment or development of water treatment technologies, and/or for policy-making.

Reactivity-based identification of oxygen containing functional groups of chemicals applied as potential classifier in non-target analysis

In this work, we developed a reactivity-based strategy to identify functional groups of unknown analytes, which can be applied as classifier in non-target analysis with gas chromatography. The aim of this strategy is to reduce the number of potential candidate structures generated for a molecular formula determined by high resolution mass spectrometry. We selected an example of 18 isomers with the molecular formula C12H10O2 to test the performance of different derivatization reagents, whereas our aim was to select mild and fast reaction conditions. Based on the results for the isomers, we developed a four-step workflow for the identification of functional groups containing oxygen.

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.

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.

Novel nontarget LC-HRMS-based approaches for evaluation of drinking water treatment

A conventional evaluation methodology for drinking water pollution focuses on analysing hundreds of compounds, usually by liquid chromatography-tandem mass spectrometry. High-resolution mass spectrometry allows comprehensive evaluation of all detected signals (compounds) based on their elemental composition, intensity, and numbers. We combined target analysis of 192 emerging micropollutants with nontarget (NT) full-scan/MS/MS methods to describe the impact of treatment steps in detail and assess drinking water treatment efficiency without compound identification. The removal efficiency based on target analytes ranged from - 143 to 97%, depending on the treatment section, technologies, and season. The same effect calculated for all signals detected in raw water by the NT method ranged between 19 and 65%. Ozonation increased the removal of micropollutants from the raw water but simultaneously caused the formation of new compounds. Moreover, ozonation byproducts showed higher persistence than products formed during other types of treatment. We evaluated chlorinated and brominated organics detected by specific isotopic patterns within the developed workflow. These compounds indicated anthropogenic raw water pollution but also potential treatment byproducts. We could match some of these compounds with libraries available in the software. We can conclude that passive sampling combined with nontargeted analysis shows to be a promising approach for water treatment control, especially for long-term monitoring of changes in technology lines because passive sampling dramatically reduces the number of samples and provides time-weighted average information for 2 to 4 weeks.

Characterization of different contaminants and current knowledge for defining chemical mixtures in human milk: A review

Hundreds of xenobiotics, with very diverse origins, have been detected in human milk, including contaminants of emerging concern, personal care products and other current-use substances reflecting lifestyle. The routes of exposure to these chemicals include dermal absorption, ingestion and inhalation. Specific families of chemicals are dominant among human milk monitoring studies (e.g., organochlorine pesticides, bisphenol A, dioxins), even though other understudied families may be equally toxicologically relevant (e.g., food-processing chemicals, current-use plasticizers and flame retardants, mycotoxins). Importantly, the lack of reliable human milk monitoring data for some individual chemicals and, especially, for complex mixtures, is a major factor hindering risk assessment. Non-targeted screening can be used as an effective tool to identify unknown contaminants of concern in human milk. This approach, in combination with novel methods to conduct risk assessments on the chemical mixtures detected in human milk, will assist in elucidating exposures that may have adverse effects on the development of breastfeeding infants.

Identification and semi-quantification of metabolites of new plasticizers in urine collected from flemish adults and children

A suspect screening workflow combined with a semi-quantification method was applied for the investigation of metabolites of the plasticizers di-propylene glycol dibenzoate (DiPGDB) and tri-n-butyl trimellitate (TBTM) in human urine collected from adults and children during winter (W) and summer (S) seasons. Liquid chromatography - quadrupole time of flight mass spectrometry (LC-QTOF-MS) was applied for the analyses. Two direct and one indirect metabolites of DiPGDB were identified: 3-(3-hydroxypropoxy) propyl benzoate (DiPGDB-M194), 3,4,5-trihydroxy-6-[3-(3-hydroxypropoxy) propoxy] oxane-2-carboxylic acid (DiPGDB-M310), hippuric acid (DiPGDB-M179) and one metabolite of TBTM: bis(butoxycarbonyl) benzoyloxy]-3,4,5-trihydroxyoxane-2-carboxylic acid (TBTM-M498). The identified metabolites were reported with levels of confidence (LoC) 2 and 3 and their concentrations were assessed using a semi-quantification approach. The respective concentration ranges for W and S samples were 0.20-42 ng/mL and 0.07-29 ng/mL for DiPGDB-M194, 2.5-1420 ng/mL and 5.0-2320 ng/mL for DiPGDB-M310, 230-10840 ng/mL and 320-8420 ng/mL for DiPGDB-M179, and 0.40-30 ng/mL and 0.65-30 ng/mL for TBTM-M498. The detection frequency order in urine samples was DiPGDB-M310 = DiPGDB-M179 (100%) >TBTM-M498 (44%) > DiPGDB-M194 (28%) for W and DiPGDB-M179 (99%)> DiPGDB-M310 (98%) > TBTM-M498 (57%) > DiPGDB-M194 (30%) for S. The identified metabolites DiPGDB-M310, DiPGDB-M194 and TBTM-M498 are potential biomarkers for the evaluation of human exposure to DiPGDB and TBTM. DiPGDB-M179 cannot be used for the same purpose due to its formation from compounds with multi-source origin. The application of the semi-quantification method could be useful for further studies where analytical standards are not available.

Worst-case ranking of organic chemicals detected in groundwaters and surface waters in England

The Environment Agency has been using Gas Chromatography-Mass Spectrometry (GC-MS) and Accurate-mass Quadrupole Time-of-Flight (Q-TOF) / Liquid Chromatography-Mass Spectrometry (LC-MS) target screen analysis to semi-quantitatively measure organic substances in groundwater and surface water since 2009 for GC-MS and 2014 for LC-MS. Here we use this data to generate a worst-case "risk" ranking of the detected substances. Three sets of hazard values relating to effects on aquatic organisms, namely Water Framework Directive EQSs, NORMAN Network PNECs (hereafter NORMAN PNEC) and chronic Species Sensitivity Distribution (SSD) HC50s from Posthuma et al., (2019) were used for the assessment. These hazard values were compared to the highest measured concentration for each chemical to generate a worst-case hazard quotient (HQ). Calculated HQs for each metric were ranked, averaged and multiplied by rank for detection frequency to generate an overall ordering based on HQ and occurrence. This worst-case approach was then used to generate ranking lists for GC-MS and LC-MS detected substances in groundwater and surface water. Pesticides in the top 30 overall ranked list included more legacy pesticides in groundwater and more current use actives in surface water. Specific uses were linked to some high rankings (e.g. rotenone for invasive species control). A number of industrial and plastics associated chemicals were ranked highly in the groundwater dataset, while more personal care products and pharmaceuticals were highly ranked in surface waters. Perfluoroalkyl and Polyfluoroalkyl Substances (PFAS) compounds were commonly highly ranked in both environmental compartments. The approach confirmed high rankings for some substance (e.g. selected pesticides) from previous prioritization exercises, but also identified novel substance for consideration (e.g. some PFAS compounds and pharmaceuticals). Overall our approach provided a simple approach using readily accessible data to identify substances for further and more detailed assessment.

Standard-Free Quantification of Dicarboxylic Acids: Case Studies with Salt-Rich Effluents and Serum

The present study evaluates the ionization efficiency (IE) of linear and branched C₂-C₁₄ dicarboxylic acids (DCAs) by electrospray ionization (ESI) under different conditions. The influence of the concentration of organic modifier (MeOH); mobile phase additive; and its concentration, pH, and DCA structure on IE values is studied using flow injection analysis. The IE values of DCAs increase with the increase of MeOH concentration but also decrease with an increase of pH. The former is due to the increase in solvent evaporation rates; the latter is caused by an ion-pairing between the diacid and the cation (ammonium), which is confirmed by the study with different amines. The investigation of DCA ionization in the presence of different acidic mobile phase additives showed that a significant improvement in the (-)ESI responses of analytes was achieved in the presence of weak hydrophobic carboxylic acids, such as butyric or propanoic acid. Conversely, the use of strong carboxylic acids, such as trichloroacetic acid, was found to cause signal suppression. The results of the IE studies were used to develop the liquid chromatography-high-resolution mass spectrometry (LC-HRMS) method that provided instrumental limits of detection in the range from 6 to 180 pg. Furthermore, upon applying the nonparametric Gaussian process, a model for the prediction of IE values was developed, which contains the number of carbons in the molecule and MeOH concentration as model parameters. As a case study, dicarboxylic acids are quantified in salt-rich effluent and blood serum samples using the developed LC-HRMS method.

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

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

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

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

Machine Learning for Absolute Quantification of Unidentified Compounds in Non-Targeted LC/HRMS

LC/ESI/HRMS is increasingly employed for monitoring chemical pollutants in water samples, with non-targeted analysis becoming more common. Unfortunately, due to the lack of analytical standards, non-targeted analysis is mostly qualitative. To remedy this, models have been developed to evaluate the response of compounds from their structure, which can then be used for quantification in non-targeted analysis. Still, these models rely on tentatively known structures while for most detected compounds, a list of structural candidates, or sometimes only exact mass and retention time are identified. In this study, a quantification approach was developed, where LC/ESI/HRMS descriptors are used for quantification of compounds even if the structure is unknown. The approach was developed based on 92 compounds analyzed in parallel in both positive and negative ESI mode with mobile phases at pH 2.7, 8.0, and 10.0. The developed approach was compared with two baseline approaches- one assuming equal response factors for all compounds and one using the response factor of the closest eluting standard. The former gave a mean prediction error of a factor of 29, while the latter gave a mean prediction error of a factor of 1300. In the machine learning-based quantification approach developed here, the corresponding prediction error was a factor of 10. Furthermore, the approach was validated by analyzing two blind samples containing 48 compounds spiked into tap water and ultrapure water. The obtained mean prediction error was lower than a factor of 6.0 for both samples. The errors were found to be comparable to approaches using structural information.

An Introduction to the Benchmarking and Publications for Non-Targeted Analysis Working Group

Non-targeted analysis (NTA) encompasses a rapidly evolving set of mass spectrometry techniques aimed at characterizing the chemical composition of complex samples, identifying unknown compounds, and/or classifying samples, without prior knowledge regarding the chemical content of the samples. Recent advances in NTA are the result of improved and more accessible instrumentation for data generation and analysis tools for data evaluation and interpretation. As researchers continue to develop NTA approaches in various scientific fields, there is a growing need to identify, disseminate, and adopt community-wide method reporting guidelines. In 2018, NTA researchers formed the Benchmarking and Publications for Non-Targeted Analysis Working Group (BP4NTA) to address this need. Consisting of participants from around the world and representing fields ranging from environmental science and food chemistry to 'omics and toxicology, BP4NTA provides resources addressing a variety of challenges associated with NTA. Thus far, BP4NTA group members have aimed to establish a consensus on NTA-related terms and concepts and to create consistency in reporting practices by providing resources on a public Web site, including consensus definitions, reference content, and lists of available tools. Moving forward, BP4NTA will provide a setting for NTA researchers to continue discussing emerging challenges and contribute to additional harmonization efforts.

Occurrence of pharmaceuticals in the Eastern Gulf of Finland (Russia)

The presence of substances of emerging concern-pharmaceuticals-in marine environments has been studied to a lesser extent compared to fresh and wastewaters. This is the first study of pharmaceutical distribution in the Russian part of the Baltic Sea. Among 18 pharmaceuticals previously detected in influent waters of Saint-Petersburg WWTPs, 7 compounds (caffeine [81% of samples], carbamazepine [81%], ketoprofen [60%], diclofenac [23 %], ciprofloxacin, trimethoprim, and clarithromycin) were recorded in seawater samples in a range of measured concentrations from 0.1 to 4452 ng L^-1. Antibiotics were presented in trace concentrations. In sediment samples, 6 pharmaceuticals (0.1-66.2 ng g^-1) were detected. The most common was carbamazepine (80%). The remaining compounds were located in decreasing frequency as follows: ketoprofen, trimethoprim, drotaverine, tetracycline, and ciprofloxacin. Some specific features of the Gulf of Finland affecting the distribution of pharmaceutical concentrations were highlighted-among the most important, the megapolis of St. Petersburg with its population over 5 million and freshwater input by the Neva River (high urbanization of the territory with a potent dilution factor). We discussed the suitable set of anthropogenic markers for the Russian part of the Gulf of Finland.

Automated fragment formula annotation for electron ionisation, high resolution mass spectrometry: application to atmospheric measurements of halocarbons

Background

Non-target screening consists in searching a sample for all present substances, suspected or unknown, with very little prior knowledge about the sample. This approach has been introduced more than a decade ago in the field of water analysis, together with dedicated compound identification tools, but is still very scarce for indoor and atmospheric trace gas measurements, despite the clear need for a better understanding of the atmospheric trace gas composition. For a systematic detection of emerging trace gases in the atmosphere, a new and powerful analytical method is gas chromatography (GC) of preconcentrated samples, followed by electron ionisation, high resolution mass spectrometry (EI-HRMS). In this work, we present data analysis tools to enable automated fragment formula annotation for unknown compounds measured by GC-EI-HRMS.

Results

Based on co-eluting mass/charge fragments, we developed an innovative data analysis method to reliably reconstruct the chemical formulae of the fragments, using efficient combinatorics and graph theory. The method does not require the presence of the molecular ion, which is absent in \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\sim$$\end{document}∼40% of EI spectra. Our method has been trained and validated on >50 halocarbons and hydrocarbons, with 3–20 atoms and molar masses of 30–330 g mol\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^{-1}$$\end{document}-1, measured with a mass resolution of approx. 3500. For >90% of the compounds, more than 90% of the annotated fragment formulae are correct. Cases of wrong identification can be attributed to the scarcity of detected fragments per compound or the lack of isotopic constraint (no minor isotopocule detected).

Conclusions

Our method enables to reconstruct most probable chemical formulae independently from spectral databases. Therefore, it demonstrates the suitability of EI-HRMS data for non-target analysis and paves the way for the identification of substances for which no EI mass spectrum is registered in databases. We illustrate the performances of our method for atmospheric trace gases and suggest that it may be well suited for many other types of samples. The L-GPL licenced Python code is released under the name ALPINAC for ALgorithmic Process for Identification of Non-targeted Atmospheric Compounds.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13321-021-00544-w.

Guide to Semi-Quantitative Non-Targeted Screening Using LC/ESI/HRMS

Non-targeted screening (NTS) with reversed phase liquid chromatography electrospray ionization high resolution mass spectrometry (LC/ESI/HRMS) is increasingly employed as an alternative to targeted analysis; however, it is not possible to quantify all compounds found in a sample with analytical standards. As an alternative, semi-quantification strategies are, or at least should be, used to estimate the concentrations of the unknown compounds before final decision making. All steps in the analytical chain, from sample preparation to ionization conditions and data processing can influence the signals obtained, and thus the estimated concentrations. Therefore, each step needs to be considered carefully. Generally, less is more when it comes to choosing sample preparation as well as chromatographic and ionization conditions in NTS. By combining the positive and negative ionization mode, the performance of NTS can be improved, since different compounds ionize better in one or the other mode. Furthermore, NTS gives opportunities for retrospective analysis. In this tutorial, strategies for semi-quantification are described, sources potentially decreasing the signals are identified and possibilities to improve NTS are discussed. Additionally, examples of retrospective analysis are presented. Finally, we present a checklist for carrying out semi-quantitative NTS.

Suitability of High-Resolution Mass Spectrometry for Routine Analysis of Small Molecules in Food, Feed and Water for Safety and Authenticity Purposes: A Review

During the last decade, food, feed and environmental analysis using high-resolution mass spectrometry became increasingly popular. Recent accessibility and technological improvements of this system make it a potential tool for routine laboratory work. However, this kind of instrument is still often considered a research tool. The wide range of potential contaminants and residues that must be monitored, including pesticides, veterinary drugs and natural toxins, is steadily increasing. Thanks to full-scan analysis and the theoretically unlimited number of compounds that can be screened in a single analysis, high-resolution mass spectrometry is particularly well-suited for food, feed and water analysis. This review aims, through a series of relevant selected studies and developed methods dedicated to the different classes of contaminants and residues, to demonstrate that high-resolution mass spectrometry can reach detection levels in compliance with current legislation and is a versatile and appropriate tool for routine testing.

patRoon: open source software platform for environmental mass spectrometry based non-target screening

Mass spectrometry based non-target analysis is increasingly adopted in environmental sciences to screen and identify numerous chemicals simultaneously in highly complex samples. However, current data processing software either lack functionality for environmental sciences, solve only part of the workflow, are not openly available and/or are restricted in input data formats. In this paper we present patRoon, a new R based open-source software platform, which provides comprehensive, fully tailored and straightforward non-target analysis workflows. This platform makes the use, evaluation and mixing of well-tested algorithms seamless by harmonizing various common (primarily open) software tools under a consistent interface. In addition, patRoon offers various functionality and strategies to simplify and perform automated processing of complex (environmental) data effectively. patRoon implements several effective optimization strategies to significantly reduce computational times. The ability of patRoon to perform time-efficient and automated non-target data annotation of environmental samples is demonstrated with a simple and reproducible workflow using open-access data of spiked samples from a drinking water treatment plant study. In addition, the ability to easily use, combine and evaluate different algorithms was demonstrated for three commonly used feature finding algorithms. This article, combined with already published works, demonstrate that patRoon helps make comprehensive (environmental) non-target analysis readily accessible to a wider community of researchers.

Perspectives and challenges associated with the determination of new psychoactive substances in urine and wastewater - A tutorial

New psychoactive substances (NPS), often designed as (legal) substitutes to conventional illicit drugs, are constantly emerging in the drug market and being commercialized in different ways and forms. Their use continues to cause public health problems and is therefore of major concern in many countries. Monitoring NPS use, however, is arduous and different sources of information are required to get more insight of the prevalence and diffusion of NPS use. The determination of NPS in pooled urine and wastewater has shown great potential, adding a different and complementary light on this issue. However, it also presents analytical challenges and limitations that must be taken into account such as the complexity of the matrices, the high sensitivity and selectivity required in the analytical methods as a consequence of the low analyte concentrations as well as the rapid transience of NPS on the drug market creating a scenario with constantly moving analytical targets. Analytical investigation of NPS in pooled urine and wastewater is based on liquid chromatography hyphenated to mass spectrometry and can follow different strategies: target, suspect and non-target analysis. This work aims to discuss the advantages and disadvantages of the different data acquisition workflows and data exploration approaches in mass spectrometry, but also pays attention to new developments such as ion mobility and the use of in-silico prediction tools to improve the identification capabilities in high-complex samples. This tutorial gives an insight into this emerging topic of current concern, and describes the experience gathered within different collaborations and projects supported by key research articles and illustrative practical examples.

Suspect screening and prioritization of chemicals of concern (COCs) in a forest-water reuse system watershed

Much research has assessed organic chemicals of concern (COCs) in municipal wastewater and receiving waters, but few studies have examined COCs in land treatment systems. Many prior studies have implemented targeted methods that quantify a relatively small fraction of COCs present in wastewater and receiving waters. This study used suspect screening to assess chemical features in ground- and surface waters from a watershed where secondary-treated wastewater is irrigated onto 900 ha of temperate forest, offering a more holistic view of chemicals that contribute to the exposome. Chemical features were prioritized by abundance and ToxPi scoring across seasonal sampling events to determine if the forest-water reuse system contributed to the chemical exposome of ground- and surface waters. The number of chemical features detected in wastewater was usually higher than on- and off-site ground- and surface waters; in wastewater, chemical features trended with precipitation in which greater numbers of features were detected in months with low precipitation. The number of chemical features detected in off- and on-site waters was similar. The lower overlap between chemical features found in wastewater and downstream surface waters, along with the similar numbers of features being detected in upstream and downstream surface waters, suggests that though wastewater may be a source of chemicals to ground and surface waters on-site, dissipation of wastewater-derived features (in number and peak area abundance) likely occurs with limited off-site surface water export by the forested land treatment system. Further, the numbers of features detected on site and the overlap between wastewater and surface waters did not increase during periods of low rainfall, counter to our initial expectations. The chemical features tentatively identified in this watershed appear common to features identified in other studies, warranting further examination on the potential for resulting impacts of these on humans and the environment.

The use of fast molecular descriptors and artificial neural networks approach in organochlorine compounds electron ionization mass spectra classification

Developing of theoretical tools can be very helpful for supporting new pollutant detection. Nowadays, a combination of mass spectrometry and chromatographic techniques are the most basic environmental monitoring methods. In this paper, two organochlorine compound mass spectra classification systems were proposed. The classification models were developed within the framework of artificial neural networks (ANNs) and fast 1D and 2D molecular descriptor calculations. Based on the intensities of two characteristic MS peaks, namely, [M] and [M-35], two classification criterions were proposed. According to criterion I, class 1 comprises [M] signals with the intensity higher than 800 NIST units, while class 2 consists of signals with the intensity lower or equal than 800. According to criterion II, class 1 consists of [M-35] signals with the intensity higher than 100, while signals with the intensity lower or equal than 100 belong to class 2. As a result of ANNs learning stage, five models for both classification criterions were generated. The external model validation showed that all ANNs are characterized by high predicting power; however, criterion I-based ANNs are much more accurate and therefore are more suitable for analytical purposes. In order to obtain another confirmation, selected ANNs were tested against additional dataset comprising popular sunscreen agents disinfection by-products reported in previous works.