High-throughput screening and environmental risk assessment: State of the science and emerging applications

Advancing toxicity studies of per- and poly-fluoroalkyl substances (pfass) through machine learning: Models, mechanisms, and future directions

Perfluorinated and perfluoroalkyl substances (PFASs), encompassing a vast array of isomeric chemicals, are recognized as typical emerging contaminants with direct or potential impacts on human health and the ecological environment. With the complex and elusive toxicological profiles of PFASs, machine learning (ML) has been increasingly employed in their toxicity studies due to its proficiency in prediction and data analytics. This integration is poised to become a predominant trend in environmental toxicology, propelled by the swift advancements in computational technology. This review diligently examines the literature to encapsulate the varied objectives of employing ML in the toxicity studies of PFASs: (1) Utilizing ML to establish Quantitative Structure-Activity Relationship (QSAR) models for PFASs with diverse toxicity endpoints, facilitating the targeted toxicity prediction of unidentified PFASs; (2) Investigating and substantiating the Adverse Outcome Pathway (AOP) through the synergy of ML and traditional toxicological methods, with this refining the toxicity assessment framework for PFASs; (3) Dissecting and elucidating the features of established ML models to advance Open Research into the toxicity of PFASs, with a primary focus on determinants and mechanisms. The discourse extends to an in-depth examination of ML studies, segregating findings based on their distinct application trajectories. Given that ML represents a nascent paradigm within PFASs research, this review delineates the collective challenges encountered in the ML-mediated study of PFAS toxicity and proffers strategic guidance for ensuing investigations.

Screening 800 putative endocrine disrupting chemicals in a representative mammal, bird, and fish using a neurochemical cell-free testing platform

There is global demand for novel ecotoxicity testing tools that are based on alternative to animal models, have high throughput potential, and may be applicable to a wide diversity of taxa. Here we scaled up a microplate-based cell-free neurochemical testing platform to screen 800 putative endocrine disrupting chemicals from the U.S. Environmental Protection Agency's ToxCast e1k library against the glutamate (NMDA), muscarinic acetylcholine (mACh), and dopamine (D2) receptors. Each assay was tested in cellular membranes isolated from brain tissues from a representative bird (zebra finch = Taeniopygia castanotis), mammal (mink = Neogale vison), and fish (rainbow trout = Oncorhynchus mykiss). The primary objective of this short communication was to make the results database accessible, while also summarising key attributes of assay performance and presenting some initial observations. In total, 7200 species-chemical-assay combinations were tested, of which 453 combinations were classified as a hit (radioligand binding changed by at least 3 standard deviations). There were some differences across species, and most hits were found for the D2 and NMDA receptors. The most active chemical was C.I. Solvent Yellow 14 followed by Diphenhydramine hydrochloride, Gentian Violet, SR271425, and Zamifenacin. Nine chemicals were tested across multiple plates with a mean relative standard deviation of the specific radioligand binding data being 24.6%. The results demonstrate that cell-free assays may serve as screening tools for large chemical libraries especially for ecological species not easily studied using traditional methods.

Grouping strategies for assessing and managing persistent and mobile substances

Background

Persistent, mobile and toxic (PMT), or very persistent and very mobile (vPvM) substances are a wide class of chemicals that are recalcitrant to degradation, easily transported, and potentially harmful to humans and the environment. Due to their persistence and mobility, these substances are often widespread in the environment once emitted, particularly in water resources, causing increased challenges during water treatment processes. Some PMT/vPvM substances such as GenX and perfluorobutane sulfonic acid have been identified as substances of very high concern (SVHCs) under the European Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH) regulation. With hundreds to thousands of potential PMT/vPvM substances yet to be assessed and managed, effective and efficient approaches that avoid a case-by-case assessment and prevent regrettable substitution are necessary to achieve the European Union's zero-pollution goal for a non-toxic environment by 2050.

Main

Substance grouping has helped global regulation of some highly hazardous chemicals, e.g., through the Montreal Protocol and the Stockholm Convention. This article explores the potential of grouping strategies for identifying, assessing and managing PMT/vPvM substances. The aim is to facilitate early identification of lesser-known or new substances that potentially meet PMT/vPvM criteria, prompt additional testing, avoid regrettable use or substitution, and integrate into existing risk management strategies. Thus, this article provides an overview of PMT/vPvM substances and reviews the definition of PMT/vPvM criteria and various lists of PMT/vPvM substances available. It covers the current definition of groups, compares the use of substance grouping for hazard assessment and regulation, and discusses the advantages and disadvantages of grouping substances for regulation. The article then explores strategies for grouping PMT/vPvM substances, including read-across, structural similarity and commonly retained moieties, as well as the potential application of these strategies using cheminformatics to predict P, M and T properties for selected examples.

Conclusions

Effective substance grouping can accelerate the assessment and management of PMT/vPvM substances, especially for substances that lack information. Advances to read-across methods and cheminformatics tools are needed to support efficient and effective chemical management, preventing broad entry of hazardous chemicals into the global market and favouring safer and more sustainable alternatives.

Improving wastewater-based epidemiology for new psychoactive substance surveillance by combining a high-throughput in vitro metabolism assay and LC-HRMS metabolite identification

One of the primary criteria for a suitable drug biomarker for wastewater-based epidemiology (WBE) is having a unique source representing human metabolism. For WBE studies, this means it is important to identify and monitor metabolites rather than parent drugs, to capture consumption of drugs and not fractions that could be directly disposed. In this study, a high-throughput workflow based on a human liver S9 fraction in vitro metabolism assay was developed to identify human transformation products of new chemicals, using α-pyrrolidino-2-phenylacetophenone (α-D2PV) as a case study. Analysis by liquid chromatography coupled to high resolution mass spectrometry identified four metabolites. Subsequently, a targeted liquid chromatography - tandem mass spectrometry method was developed for their analysis in wastewater samples collected from a music festival in Australia. The successful application of this workflow opens the door for future work to better understand the metabolism of chemicals and their detection and application for wastewater-based epidemiology.

EcoGenoRisk: Developing a computational ecological risk assessment tool for synthetic biology

The expanding field of synthetic biology (synbio) supports new opportunities in the design of targeted bioproducts or modified microorganisms. However, this rapid development of synbio products raises concerns surrounding the potential risks of modified microorganisms contaminating unintended environments. These potential invasion risks require new bioinformatic tools to inform the design phase. EcoGenoRisk is a newly constructed computational risk assessment tool for invasiveness that aims to predict where synbio microorganisms may establish a population by screening for habitats of genetically similar microorganisms. The first module of the tool identifies genetically similar microorganisms and potential ecological relationships such as competition, mutualism, and inhibition. In total, 520 archaeal and 32,828 bacterial complete assembly genomes were analyzed to test the specificity and accuracy of the tool as well as to characterize the enzymatic profiles of different taxonomic lineages. Additionally, ecological relationships were analyzed to determine which would result in the greatest potential overlap between shared functional profiles. Notably, competition displayed the significantly highest overlap of shared functions between compared genomes. Overall, EcoGenoRisk is a flexible software pipeline that assists environmental risk assessors to query large databases of known microorganisms and prioritize follow-up bench scale studies.

Transcriptomics-Based Points of Departure for Daphnia magna Exposed to 18 Per- and Polyfluoroalkyl Substances

Per- and polyfluoroalkyl substances (PFAS) represent a large group of contaminants of concern based on their widespread use, environmental persistence, and potential toxicity. Many traditional models for estimating toxicity, bioaccumulation, and other toxicological properties are not well suited for PFAS. Consequently, there is a need to generate hazard information for PFAS in an efficient and cost-effective manner. In the present study, Daphnia magna were exposed to multiple concentrations of 22 different PFAS for 24 h in a 96-well plate format. Following exposure, whole-body RNA was extracted and extracts, each representing five exposed individuals, were subjected to RNA sequencing. Following analytical measurements to verify PFAS exposure concentrations and quality control on processed cDNA libraries for sequencing, concentration-response modeling was applied to the data sets for 18 of the tested compounds, and the concentration at which a concerted molecular response occurred (transcriptomic point of departure; tPOD) was calculated. The tPODs, based on measured concentrations of PFAS, generally ranged from 0.03 to 0.58 µM (9.9-350 µg/L; interquartile range). In most cases, these concentrations were two orders of magnitude lower than similarly calculated tPODs for human cell lines exposed to PFAS. They were also lower than apical effect concentrations reported for seven PFAS for which some crustacean or invertebrate toxicity data were available, although there were a few exceptions. Despite being lower than most other available hazard benchmarks, D. magna tPODs were, on average, four orders of magnitude greater than the maximum aqueous concentrations of PFAS measured in Great Lakes tributaries. Overall, this high-throughput transcriptomics assay with D. magna holds promise as a component of a tiered hazard evaluation strategy employing new approach methodologies. Environ Toxicol Chem 2024;00:1-16. © 2024 SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Linking Mechanistic Effects of Pharmaceuticals and Personal Care Products to Ecologically Relevant Outcomes: A Decade of Progress

There are insufficient toxicity data to assess the ecological risks of many pharmaceuticals and personal care products (PPCPs). While data limitations are not uncommon for contaminants of environmental concern, PPCPs are somewhat unique in that an a priori understanding of their biological activities in conjunction with measurements of molecular, biochemical, or histological responses could provide a foundation for understanding mode(s) of action and predicting potential adverse apical effects. Over the past decade significant progress has been made in the development of new approach methodologies (NAMs) to efficiently quantify these types of endpoints using computational models and pathway-based in vitro and in vivo assays. The availability of open-access knowledgebases to curate biological response (including NAM) data and sophisticated bioinformatics tools to help interpret the information also has significantly increased. Finally, advances in the development and implementation of the adverse outcome pathway framework provide the critical conceptual underpinnings needed to translate NAM data into predictions of the ecologically relevant outcomes required by risk assessors and managers. The evolution and convergence of these various data streams, tools, and concepts provides the basis for a fundamental change in how ecological risks of PPCPs can be pragmatically assessed. Environ Toxicol Chem 2024;43:537-548. © 2022 SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Handling concentration data below the analytical limit in environmental mixture risk assessment: A case-study on pesticide river monitoring

Aquatic organisms are exposed to ever-changing complex mixtures of chemicals throughout their lifetime. Component-Based Mixture Risk Assessment (CBMRA) is a well-established methodology for water contaminant-mixture management, the use of which is growing due to improved access to reference ecotoxicity data and extensive monitoring datasets. It enables the translation of measured exposure concentrations of chemicals into biological effect values, and thus to quantitatively estimate the risk of the whole water sample (i.e., as a mixture). However, many factors can bias the final risk decision by impacting the risk metric components; thus, a careful design of the CBMRA is needed, taking into primary consideration the specific features of the dataset and mixture risk assessment assignments. This study systematically addressed the effects of the most common approaches used for handling the concentrations of chemicals below the limit of detection/quantification (LOD/LOQ) in CBMRA. The main results included: i) an informed CBMRA procedure that enables the tracking of the risk decisions triggered by substances below LOD/LOQ, ii) a conceptual map and guidance criteria to support the selection of the most suitable approach for specific scenarios and related interpretation; iii) a guided implementation of the informed CBMRA on dataset of pesticide concentrations in Italian rivers in 2020 (702,097 records).

Assessing Contaminants of Emerging Concern in the Great Lakes Ecosystem: A Decade of Method Development and Practical Application

Assessing the ecological risk of contaminants in the field typically involves consideration of a complex mixture of compounds which may or may not be detected via instrumental analyses. Further, there are insufficient data to predict the potential biological effects of many detected compounds, leading to their being characterized as contaminants of emerging concern (CECs). Over the past several years, advances in chemistry, toxicology, and bioinformatics have resulted in a variety of concepts and tools that can enhance the pragmatic assessment of the ecological risk of CECs. The present Focus article describes a 10+- year multiagency effort supported through the U.S. Great Lakes Restoration Initiative to assess the occurrence and implications of CECs in the North American Great Lakes. State-of-the-science methods and models were used to evaluate more than 700 sites in about approximately 200 tributaries across lakes Ontario, Erie, Huron, Michigan, and Superior, sometimes on multiple occasions. Studies featured measurement of up to 500 different target analytes in different environmental matrices, coupled with evaluation of biological effects in resident species, animals from in situ and laboratory exposures, and in vitro systems. Experimental taxa included birds, fish, and a variety of invertebrates, and measured endpoints ranged from molecular to apical responses. Data were integrated and evaluated using a diversity of curated knowledgebases and models with the goal of producing actionable insights for risk assessors and managers charged with evaluating and mitigating the effects of CECs in the Great Lakes. This overview is based on research and data captured in approximately about 90 peer-reviewed journal articles and reports, including approximately about 30 appearing in a virtual issue comprised of highlighted papers published in Environmental Toxicology and Chemistry or Integrated Environmental Assessment and Management. Environ Toxicol Chem 2023;42:2506-2518. © 2023 SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Quantitative Integration of Mode of Action Information in Dose-Response Modeling and POD Estimation for Nonmutagenic Carcinogens: A Case Study of TCDD

BACKGROUND

Traditional dose-response assessment applies different low-dose extrapolation methods for cancer and noncancer effects and assumes that all carcinogens are mutagenic unless strong evidence suggests otherwise. Additionally, primarily focusing on one critical effect, dose-response modeling utilizes limited mode of action (MOA) data to inform low-dose risk.

OBJECTIVE

We aimed to build a dose-response modeling framework that continuously extends the curve into the low-dose region via a quantitative integration of MOA information and to estimate MOA-based points of departure (PODs) for nonmutagenic carcinogens.

METHODS

2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) was used as an example to demonstrate the new dose-response modeling framework. There were three major steps included: a) identifying and extracting key quantifiable events (KQEs), b) calculating essential doses that sequentially activate KQEs using the benchmark dose (BMD) methodology, and c) characterizing pathway dose-response relationship for MOA-based POD estimation.

RESULTS

We identified and extracted six KQEs and corresponding essential events composing the MOA of TCDD-induced liver tumors. With the essential doses estimated from the BMD method using various settings, three link functions were applied to model the pathway dose-response relationship. Given a toxicologically plausible definition of adversity, an MOA-based POD was derived from the pathway dose-response curve. The estimated MOA-based PODs were generally comparable with traditional PODs and can be further used to calculate reference doses (RfDs).

CONCLUSIONS

The proposed framework quantitatively integrated mechanistic information in the modeling process and provided a promising strategy to harmonize cancer and noncancer dose-response assessment through pathway dose-response modeling. However, the framework can also be limited by data availability and the understanding of the underlying mechanism. https://doi.org/10.1289/EHP12677.

A mode of action-based probabilistic framework of dose-response assessment for nonmutagenic liver carcinogens: a case study of PCB-126

A main function of dose-response assessment is to estimate a "safe" dose in the target population to support chemical risk assessment. Typically, a "safe" dose is developed differently for cancer and noncancer effects based on a 2-step procedure, ie, point of departure (POD) derivation and low-dose extrapolation. However, the current dose-response assessment framework is criticized for its dichotomized strategy without integrating the mode of action (MOA) information. The objective of this study was, based on our previous work, to develop a MOA-based probabilistic dose-response framework that quantitatively synthesizes a biological pathway in a dose-response modeling process to estimate the risk of chemicals that have carcinogenic potential. 3,3',4,4',5-Pentachlorobiphenyl (PCB-126) was exemplified to demonstrate our proposed approach. There were 4 major steps in the new modeling framework, including (1) key quantifiable events (KQEs) identification and extraction, (2) essential dose calculation, (3) MOA-based POD derivation, and (4) MOA-based probabilistic reference dose (RfD) estimation. Compared with reported PODs and traditional RfDs, the MOA-based estimates derived from our approach were comparable and plausible. One key feature of our approach was the use of overall MOA information to build the dose-response relationship on the entire dose continuum including the low-dose region. On the other hand, by adjusting uncertainty and variability in a probabilistic manner, the MOA-based probabilistic RfDs can provide useful insights of health protection for the specific proportion of population. Moreover, the proposed framework had important potential to be generalized to assess different types of chemicals other than nonmutagenic carcinogens, highlighting its utility to improve current chemical risk assessment.

Comparative analysis between zebrafish and an automated live-cell assay to classify developmental neurotoxicant chemicals

Modern toxicology's throughput has dramatically increased due to alternative models, laboratory automation, and machine learning. This has enabled comparative studies across species and assays to prioritize chemical hazard potential and to understand how different model systems might complement one another. However, such comparative studies of high-throughput data are still in their infancy, with more groundwork needed to firmly establish the approach. Therefore, this study aimed to compare the bioactivity of the NIEHS Division of Translational Toxicology's (DTT) 87-compound developmental neurotoxicant (DNT) library in zebrafish and an in vitro high-throughput cell culture system. The early life-stage zebrafish provided a whole animal approach to developmental toxicity assessment. Chemical hits for abnormalities in embryonic zebrafish morphology, mortality, and behavior (ZBEscreen™) were compared with chemicals classified as high-risk by the Cell Health Index (CHI™), which is an outcome class probability from a machine learning classifier using 12 parameters from the SYSTEMETRIC® Cell Health Screen (CHS). The CHS was developed to assess human toxicity risk using supervised machine learning to classify acute cell stress phenotypes in a human leukemia cell line (HL60 cells) following a 4-h exposure to a chemical of interest. Due to the design of the screen, the zebrafish assays were more exhaustive, yielding 86 total bioactive hits, whereas the SYSTEMETRIC® CHS focusing on acute toxicity identified 20 chemicals as potentially toxic. The zebrafish embryonic and larval photomotor response assays (EPR and LPR, respectively) detected 40 of the 47 chemicals not found by the zebrafish morphological screen and CHS. Collectively, these results illustrate the advantages of using two alternative models in tandem for rapid hazard assessment and chemical prioritization and the effectiveness of CHI™ in identifying toxicity within a single multiparametric assay.

Comparison of in silico, in vitro, and in vivo toxicity benchmarks suggests a role for ToxCast data in ecological hazard assessment

Large repositories of in vitro bioactivity data such as US EPA's Toxicity Forecaster (ToxCast) provide a wealth of publicly accessible toxicity information for thousands of chemicals. These data can be used to calculate point-of-departure (POD) estimates via concentration-response modeling that may serve as lower bound, protective estimates of in vivo effects. However, the data are predominantly based on mammalian models and discussions to date about their utility have largely focused on potential integration into human hazard assessment, rather than application to ecological risk assessment. The goal of the present study was to compare PODs based on (1) quantitative structure-activity relationships (QSARs), (2) the 5th centile of the activity concentration at cutoff (ACC), and (3) lower-bound cytotoxic burst (LCB) from ToxCast, with the distribution of in vivo PODs compiled in the Ecotoxicology Knowledgebase (ECOTOX). While overall correlation between ToxCast ACC5 and ECOTOX PODs for 649 chemicals was weak, there were significant associations among PODs based on LCB and ECOTOX, LCB and QSARs, and ECOTOX and QSARs. Certain classes of compounds showed moderate correlation across datasets (eg, antimicrobials/disinfectants), while others, such as organophosphate insecticides, did not. Unsurprisingly, more precise classifications of the data based on ECOTOX effect and endpoint type (eg, apical vs biochemical; acute vs chronic) had a significant effect on overall relationships. Results of this research help to define appropriate roles for data from new approach methodologies in chemical prioritization and screening of ecological hazards.

Identification and Prioritization of Environmental Organic Pollutants: From an Analytical and Toxicological Perspective

Exposure to environmental organic pollutants has triggered significant ecological impacts and adverse health outcomes, which have been received substantial and increasing attention. The contribution of unidentified chemical components is considered as the most significant knowledge gap in understanding the combined effects of pollutant mixtures. To address this issue, remarkable analytical breakthroughs have recently been made. In this review, the basic principles on recognition of environmental organic pollutants are overviewed. Complementary analytical methodologies (i.e., quantitative structure-activity relationship prediction, mass spectrometric nontarget screening, and effect-directed analysis) and experimental platforms are briefly described. The stages of technique development and/or essential parts of the analytical workflow for each of the methodologies are then reviewed. Finally, plausible technique paths and applications of the future nontarget screening methods, interdisciplinary techniques for achieving toxicant identification, and burgeoning strategies on risk assessment of chemical cocktails are discussed.

A framework for prioritizing contaminants in retrospective ecological assessments: Application in the Milwaukee Estuary (Milwaukee, WI)

Watersheds are subjected to diverse anthropogenic inputs, exposing aquatic biota to a wide range of chemicals. Detection of multiple, different chemicals can challenge natural resource managers who often have to determine where to allocate potentially limited resources. Here, we describe a weight-of-evidence framework for retrospectively prioritizing aquatic contaminants. To demonstrate framework utility, we used data from 96-h caged fish studies to prioritize chemicals detected in the Milwaukee Estuary (WI, USA; 2017-2018). Across study years, 77/178 targeted chemicals were detected. Chemicals were assigned prioritization scores based on spatial and temporal detection frequency, environmental distribution, environmental fate, ecotoxicological potential, and effect prediction. Chemicals were sorted into priority bins based on the intersection of prioritization score and data availability. Data-limited chemicals represented those that did not have sufficient data to adequately evaluate ecotoxicological potential or environmental fate. Seven compounds (fluoranthene, benzo[a]pyrene, pyrene, atrazine, metolachlor, phenanthrene, and DEET) were identified as high or medium priority and data sufficient and flagged as candidates for further effects-based monitoring studies. Twenty-one compounds were identified as high or medium priority and data limited and flagged as candidates for further ecotoxicological research. Fifteen chemicals were flagged as the lowest priority in the watershed. One of these chemicals (2-methylnaphthalene) displayed no data limitations and was flagged as a definitively low-priority chemical. The remaining chemicals displayed some data limitations and were considered lower-priority compounds (contingent on further ecotoxicological and environmental fate assessments). The remaining 34 compounds were flagged as low or medium priority. Altogether, this prioritization provided a screening-level (non-definitive) assessment that could be used to focus further resource management and risk assessment activities in the Milwaukee Estuary. Furthermore, by providing detailed methodology and a practical example with real experimental data, we demonstrated that the proposed framework represents a transparent and adaptable approach for prioritizing contaminants in freshwater environments. Integr Environ Assess Manag 2023;19:1276-1296. © 2022 SETAC.

Frameworks for screening and risk management of chemicals and advanced materials: A critical review

Despite the evolution over the last half century of regulatory programs and frameworks developed for the evaluation of safety and management of risks associated with chemicals and materials, new and emerging contaminant issues continue to be identified. These recurring issues suggest a need for review and reflection on current approaches and strategies for ensuring the safety of chemicals and materials. Twelve existing frameworks relating to the evaluation and management of chemical or material risk were reviewed to identify potential process improvements for facilitating early identification of potentially problematic substances and better inform risk management strategies (e.g., prohibition, restricted use, or selection of safer alternatives). The frameworks were selected to represent a broad spectrum of regional, national, and international authorities and purposes, including preproduction evaluation of new substances, classification and hazard communication, identification of persistent pollutants, and identification of safer alternatives. Elements common to the frameworks were identified, as well as features unique to select frameworks. A comparative evaluation was performed, and potential new strategies and approaches were identified to inform process improvement recommendations. These recommendations include requiring validated analytical procedures to enable measurement in environmental media, improved data transparency and accessibility, flexibility to incorporate advances into the state of the practice (e.g., new approach methodologies and high-throughput assessment tools), and incorporation of monitoring and adaptive management strategies to enable more timely intervention. Process improvement recommendations are discussed and summarized in a conceptual risk management framework. Integr Environ Assess Manag 2023;19:1192-1206. © 2022 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC). This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Experimental exposure assessment for in vitro cell-based bioassays in 96- and 384-well plates

In vitro cell-based bioassays have great potential for applications in the human health risk assessment of chemicals. The quantification of freely dissolved concentrations (C free) in in vitro assays is essential to generate reliable data for in vitro-to-in vivo extrapolation. Existing methods for the quantification of C free are limited to low-throughput microtiter plates. The present study is a proof of principle for the applicability of a solid-phase microextraction (SPME) method for the determination of C free in the peroxisome proliferator-activated receptor gamma (PPARγ) bioassay run in 384-well plates with 80 µL medium per well. The effect concentrations obtained from 384-well plates were compared with those obtained from 96-well plates in a previous study. Nominal effect concentrations obtained using 96- and 384-well plates agreed with each other within a factor of three, and freely dissolved effect concentrations agreed within a factor of 6.5. The good degree of agreement in the results from both plate formats proves the general applicability of the SPME method for the determination of C free for bioassays in 384-well plates, making the present study a first step toward exposure assessment in high-throughput bioassays.

Toxicity identification evaluation for hydraulic fracturing flowback and produced water during shale gas exploitation in China: Evidence from tissue residues and gene expression

Hydraulic fracturing flowback and produced water (HF-FPW) from shale gas extraction processes is a highly complex medium with potential threats to the environment. Current research on ecological risks of FPW in China is limited, and the link between major components of FPW and their toxicological effects on freshwater organisms is largely unknown. By integrating chemical and biological analyses, toxicity identification evaluation (TIE) was used to reveal causality between toxicity and contaminants, potentially disentangling the complex toxicological nature of FPW. Here, FPW from different shale gas wells, treated FPW effluent, and a leachate from HF sludge were collected from southwest China, and TIE was applied to obtain a comprehensive toxicity evaluation in freshwater organisms. Our results showed that FPW from the same geographic zone could cause significantly different toxicity. Salinity, solid phase particulates, and organic contaminants were identified as the main contributors to the toxicity of FPW. In addition to water chemistry, internal alkanes, PAHs, and HF additives (e.g., biocides and surfactants) were quantified in exposed embryonic fish by target and non-target tissue analyses. The treated FPW failed to mitigate the toxicity associated with organic contaminants. Transcriptomic results illustrated that organic compounds induced toxicity pathways in FPW-exposed embryonic zebrafish. Similar zebrafish gene ontologies were affected between treated and untreated FPW, again confirming that sewage treatment did not effectively remove organic chemicals from FPW. Thus, zebrafish transcriptome analyses revealed organic toxicant-induced adverse outcome pathways and served as evidence for TIE confirmation in complex mixtures under data-poor scenarios.

Evaluation of in vitro toxicity information for zebrafish as a promising alternative for chemical hazard and risk assessment

In vitro assays are widely proposed as a test alternative to traditional in vivo standard acute and chronic toxicity tests. However, whether toxicity information derived from in vitro assays instead of in vivo tests could provide sufficient protection (e.g., 95 % of protection) for chemical risks remain evaluated. To investigate the feasibility of zebrafish (Danio rerio) cell-based in vitro test method as a test alternative, we comprehensively compared sensitivity differences among endpoints, among test methods (in vitro, FET and in vivo), and between zebrafish and rat (Rattus norvegicus), respectively using chemical toxicity distribution (CTD) approach. For each test method involved, sublethal endpoints were more sensitive than lethal endpoints for both zebrafish and rat, respectively. Biochemistry (zebrafish in vitro), development (zebrafish in vivo and FET), physiology (rat in vitro) and development (rat in vivo) were the most sensitive endpoints for each test method. Nonetheless, zebrafish FET test was the least sensitive one compared to its in vivo and in vitro tests for either lethal or sublethal responses. Comparatively, rat in vitro tests considering cell viability and physiology endpoints were more sensitive than rat in vivo test. Zebrafish was found to be more sensitive than rat regardless of in vivo or in vitro tests for each pairwise endpoint of concern. Those findings indicate that zebrafish in vitro test is a feasible test alternative to zebrafish in vivo and FET test and traditional mammalian test. It is suggesting that zebrafish in vitro test can be optimized by choosing more sensitive endpoints, such as biochemistry to provide sufficient protection for zebrafish in vivo test and to establish applications of zebrafish in vitro test in future risk assessment. Our findings are vital for evaluating and further application of in vitro toxicity toxicity information as an alternative for chemical hazard and risk assessment.

Building the Environmental Chemical-Protein Interaction Network (eCPIN): An Exposome-Wide Strategy for Bioactive Chemical Contaminant Identification

Although advancements in nontargeted analysis have made it possible to detect hundreds of chemical contaminants in a single run, the current environmental toxicology approaches lag behind, precluding the transition from analytical chemistry efforts to health risk assessment. We herein highlighted a recently developed "top-down" bioanalytical method, protein Affinity Purification with Nontargeted Analysis (APNA), to screen for bioactive chemical contaminants at the "exposome-wide" level. To achieve this, a tagged functional protein is employed as a "bait" to directly isolate bioactive chemical contaminants from environmental mixtures, which are further identified by nontargeted analysis. Advantages of this protein-guided approach, including the discovery of new bioactive ligands as well as new protein targets for known chemical contaminants, were highlighted by several case studies. Encouraged by these successful applications, we further proposed a framework, i.e., the environmental Chemical-Protein Interaction Network (eCPIN), to construct a complete map of the 7 billion binary interactions between all chemical contaminants (>350,000) and human proteins (∼20,000) via APNA. The eCPIN could be established in three stages through strategically prioritizing the ∼20,000 human proteins, such as focusing on the 48 nuclear receptors (e.g., thyroid hormone receptors) in the first stage. The eCPIN will provide an unprecedented throughput for screening bioactive chemical contaminants at the exposome-wide level and facilitate the identification of molecular initiating events at the proteome-wide level.

Pesticide Prioritization by Potential Biological Effects in Tributaries of the Laurentian Great Lakes

Watersheds of the Great Lakes Basin (USA/Canada) are highly modified and impacted by human activities including pesticide use. Despite labeling restrictions intended to minimize risks to nontarget organisms, concerns remain that environmental exposures to pesticides may be occurring at levels negatively impacting nontarget organisms. We used a combination of organismal-level toxicity estimates (in vivo aquatic life benchmarks) and data from high-throughput screening (HTS) assays (in vitro benchmarks) to prioritize pesticides and sites of concern in streams at 16 tributaries to the Great Lakes Basin. In vivo or in vitro benchmark values were exceeded at 15 sites, 10 of which had exceedances throughout the year. Pesticides had the greatest potential biological impact at the site with the greatest proportion of agricultural land use in its basin (the Maumee River, Toledo, OH, USA), with 72 parent compounds or transformation products being detected, 47 of which exceeded at least one benchmark value. Our risk-based screening approach identified multiple pesticide parent compounds of concern in tributaries of the Great Lakes; these compounds included: eight herbicides (metolachlor, acetochlor, 2,4-dichlorophenoxyacetic acid, diuron, atrazine, alachlor, triclopyr, and simazine), three fungicides (chlorothalonil, propiconazole, and carbendazim), and four insecticides (diazinon, fipronil, imidacloprid, and clothianidin). We present methods for reducing the volume and complexity of potential biological effects data that result from combining contaminant surveillance with HTS (in vitro) and traditional (in vivo) toxicity estimates. Environ Toxicol Chem 2023;42:367-384. Published 2022. This article is a U.S. Government work and is in the public domain in the USA. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Targeted Per- and Polyfluoroalkyl substances (PFAS) assessments for high throughput screening: Analytical and testing considerations to inform a PFAS stock quality evaluation framework

Per- and polyfluoroalkyl substances (PFAS) represent a large chemical class lacking hazard, toxicokinetic, and exposure information. To accelerate PFAS hazard evaluation, new approach methodologies (NAMs) comprised of in vitro high-throughput toxicity screening, toxicokinetic data, and computational modeling are being employed in read across strategies to evaluate the larger PFAS landscape. A critical consideration to ensure robust evaluations is a parallel assessment of the quality of the screening stock solutions, where dimethyl sulfoxide (DMSO) is often the diluent of choice. Challenged by the lack of commercially available reference standards for many of the selected PFAS and reliance on mass spectrometry approaches for such an evaluation, we developed a high-throughput framework to evaluate the quality of screening stocks for 205 PFAS selected for these NAM efforts. Using mass spectrometry coupled with either liquid or gas chromatography, a quality scoring system was developed that incorporated observations during mass spectral examination to provide a simple pass or fail notation. Informational flags were used to further describe findings regarding parent analyte presence through accurate mass identification, evidence of contaminants and/or degradation, or further describe characteristics such as isomer presence. Across the PFAS-DMSO stocks tested, 148 unique PFAS received passing quality scores to allow for further in vitro testing whereas 57 received a failing score primarily due to detection issues or confounding effects of DMSO. Principle component analysis indicated vapor pressure and Henry's Law Constant as top indicators for a failed quality score for those analyzed by gas chromatography. Three PFAS in the hexafluoropropylene oxide family failed due to degradation in DMSO. As the PFAS evaluated spanned over 20 different structural categories, additional commentary describes analytical observations across specific groups related to PFAS stock composition, detection, stability, and methodologic considerations that will be useful for informing future analytical assessment and downstream HTS efforts. The high-throughput stock quality scoring workflow presented holds value as a tool to evaluate chemical presence and quality efficiently and for informing data inclusion in PFAS or other NAM screening efforts.

Three perspectives on the prediction of chemical effects in ecosystems

The increasing production, use and emission of synthetic chemicals into the environment represents a major driver of global change. The large number of synthetic chemicals, limited knowledge on exposure patterns and effects in organisms and their interaction with other global change drivers hamper the prediction of effects in ecosystems. However, recent advances in biomolecular and computational methods are promising to improve our capacity for prediction. We delineate three idealised perspectives for the prediction of chemical effects: the suborganismal, organismal and ecological perspective, which are currently largely separated. Each of the outlined perspectives includes essential and complementary theories and tools for prediction but captures only part of the phenomenon of chemical effects. Links between the perspectives may foster predictive modelling of chemical effects in ecosystems and extrapolation between species. A major challenge for the linkage is the lack of data sets simultaneously covering different levels of biological organisation (here referred to as biological levels) as well as varying temporal and spatial scales. Synthesising the three perspectives, some central aspects and associated types of data seem particularly necessary to improve prediction. First, suborganism- and organism-level responses to chemicals need to be recorded and tested for relationships with chemical groups and organism traits. Second, metrics that are measurable at many biological levels, such as energy, need to be scrutinised for their potential to integrate across levels. Third, experimental data on the simultaneous response over multiple biological levels and spatiotemporal scales are required. These could be collected in nested and interconnected micro- and mesocosm experiments. Lastly, prioritisation of processes involved in the prediction framework needs to find a balance between simplification and capturing the essential complexity of a system. For example, in some cases, eco-evolutionary dynamics and interactions may need stronger consideration. Prediction needs to move from a static to a real-world eco-evolutionary view.

Pilot testing and optimization of a larval fathead minnow high throughput transcriptomics assay

Concentrations at which global gene expression profiles in cells or animals exposed to a test substance start to differ significantly from those of controls have been proposed as an alternative point of departure for use in screening level hazard assessment. The present study describes pilot testing of a high throughput compatible transcriptomics assay with larval fathead minnows. One day post hatch fathead minnows were exposed to eleven different concentrations of three metals, three selective serotonin reuptake inhibitors, and four neonicotinoid-like compounds for 24 h and concentration response modeling was applied to whole body gene expression data. Transcriptomics-based points of departure (tPODs) were consistently lower than effect concentrations reported in apical endpoint studies in fish. However, larval fathead minnow-based tPODs were not always lower than concentrations reported to elicit apical toxicity in other aquatic organisms like crustaceans or insects. Random in silico subsampling of data from the pilot assays was used to evaluate various assay design and acceptance considerations such as transcriptome coverage, number of replicate individuals to sequence per treatment, and minimum number of differentially expressed genes to produce a reliable tPOD estimate. Results showed a strong association between the total number of genes for which a concentration response relationship could be derived and the overall variability in the resulting tPOD estimates. We conclude that, for our current assay design and analysis pipeline, tPODs based on fewer than 15 differentially expressed genes are likely to be unreliable for screening and that interindividual variability in gene expression profiles appears to be a more significant driver of tPOD variability than sample size alone. Results represent initial steps toward developing high throughput transcriptomics assays for use in ecological hazard screening.

A Nanomedicine Structure-Activity Framework for Research, Development, and Regulation of Future Cancer Therapies

Despite their clinical success in drug delivery applications, the potential of theranostic nanomedicines is hampered by mechanistic uncertainty and a lack of science-informed regulatory guidance. Both the therapeutic efficacy and the toxicity of nanoformulations are tightly controlled by the complex interplay of the nanoparticle's physicochemical properties and the individual patient/tumor biology; however, it can be difficult to correlate such information with observed outcomes. Additionally, as nanomedicine research attempts to gradually move away from large-scale animal testing, the need for computer-assisted solutions for evaluation will increase. Such models will depend on a clear understanding of structure-activity relationships. This review provides a comprehensive overview of the field of cancer nanomedicine and provides a knowledge framework and foundational interaction maps that can facilitate future research, assessments, and regulation. By forming three complementary maps profiling nanobio interactions and pathways at different levels of biological complexity, a clear picture of a nanoparticle's journey through the body and the therapeutic and adverse consequences of each potential interaction are presented.

Tox21-Based Comparative Analyses for the Identification of Potential Toxic Effects of Environmental Pollutants

Chemical pollution has become a prominent environmental problem. In recent years, quantitative high-throughput screening (qHTS) assays have been developed for the fast assessment of chemicals' toxic effects. Toxicology in the 21st Century (Tox21) is a well-known and continuously developing qHTS project. Recent reports utilizing Tox21 data have mainly focused on setting up mathematical models for in vivo toxicity predictions, with less attention to intuitive qHTS data visualization. In this study, we attempted to reveal and summarize the toxic effects of environmental pollutants by analyzing and visualizing Tox21 qHTS data. Via PubMed text mining, toxicity/structure clustering, and manual classification, we detected a total of 158 chemicals of environmental concern (COECs) from the Tox21 library that we classified into 13 COEC groups based on structure and activity similarities. By visualizing these COEC groups' bioactivities, we demonstrated that COECs frequently displayed androgen and progesterone antagonistic effects, xenobiotic receptor agonistic roles, and mitochondrial toxicity. We also revealed many other potential targets of the 13 COEC groups, which were not well illustrated yet, and that current Tox21 assays may not correctly classify known teratogens. In conclusion, we provide a feasible method to intuitively understand qHTS data.

Cross-species comparison of chemical inhibition of human and Xenopus iodotyrosine deiodinase

The transition to include in vitro-based data in chemical hazard assessment has resulted in the development and implementation of screening assays to cover a diversity of biological pathways, including recently added assays to interrogate chemical disruption of proteins relevant to thyroid signaling pathways. Iodotyrosine deiodinase (IYD), the iodide recycling enzyme, is one such thyroid-relevant endpoint for which a human-based screening assay has recently been developed and used to screen large libraries of chemicals. Presented here is the development of an amphibian IYD inhibition assay and its implementation to conduct a cross-species comparison between chemical inhibition of mammalian and non-mammalian IYD enzyme activity. The successful development of an amphibian IYD inhibition assay was based on demonstration of sufficient IYD enzyme activity in several tissues collected from larval Xenopus laevis. With this new assay, 154 chemicals were tested in concentration-response to provide a basis for comparison of relative chemical potency to results obtained from the human IYD assay. Most chemicals exhibited similar inhibition in both assays, with less than 25% variation in median inhibition for 120 of 154 chemicals and 85% concordance in categorization of "active" (potential IYD inhibitor) versus "inactive". For chemicals that produced 50% or greater inhibition in both assays, rank-order potency was similar, with the majority of the IC50s varying by less than 2-fold (and all within an order of magnitude). Most differences resulted from greater maximum inhibition or higher chemical potency observed with human IYD. This strong cross-species agreement suggests that results from the human-based assay would be conservatively predictive of chemical effects on amphibian IYD.

SETApp: A machine learning and image analysis based application to automate the sea urchin embryo test

Since countless xenobiotic compounds are being found in the environment, ecotoxicology faces an astounding challenge in identifying toxicants. The combination of high-throughput in vivo/in vitro bioassays with high-resolution chemical analysis is an effective way to elucidate the cause-effect relationship. However, these combined strategies imply an enormous workload that can hinder their implementation in routine analysis. The purpose of this study was to develop a new high throughput screening method that could be used as a predictive expert system that automatically quantifies the size increase and malformation of the larvae and, thus, eases the application of the sea urchin embryo test in complex toxicant identification pipelines such as effect-directed analysis. For this task, a training set of 242 images was used to calibrate the size-increase and malformation level of the larvae. Two classification models based on partial least squares discriminant analysis (PLS-DA) were built and compared. Moreover, Hierarchical PLS-DA shows a high proficiency in classifying the larvae, achieving a prediction accuracy of 84 % in validation. The scripts built along the work were compiled in a user-friendly standalone app (SETApp) freely accessible at https://github.com/UPV-EHU-IBeA/SETApp. The SETApp was tested in a real case scenario to fulfill the tedious requirements of a WWTP effect-directed analysis.

The ECOTOXicology Knowledgebase: A Curated Database of Ecologically Relevant Toxicity Tests to Support Environmental Research and Risk Assessment

The need for assembled existing and new toxicity data has accelerated as the amount of chemicals introduced into commerce continues to grow and regulatory mandates require safety assessments for a greater number of chemicals. To address this evolving need, the ECOTOXicology Knowledgebase (ECOTOX) was developed starting in the 1980s and is currently the world's largest compilation of curated ecotoxicity data, providing support for assessments of chemical safety and ecological research through systematic and transparent literature review procedures. The recently released version of ECOTOX (Ver 5, www.epa.gov/ecotox) provides single-chemical ecotoxicity data for over 12,000 chemicals and ecological species with over one million test results from over 50,000 references. Presented is an overview of ECOTOX, detailing the literature review and data curation processes within the context of current systematic review practices and discussing how recent updates improve the accessibility and reusability of data to support the assessment, management, and research of environmental chemicals. Relevant and acceptable toxicity results are identified from studies in the scientific literature, with pertinent methodological details and results extracted following well-established controlled vocabularies and newly extracted toxicity data added quarterly to the public website. Release of ECOTOX, Ver 5, included an entirely redesigned user interface with enhanced data queries and retrieval options, visualizations to aid in data exploration, customizable outputs for export and use in external applications, and interoperability with chemical and toxicity databases and tools. This is a reliable source of curated ecological toxicity data for chemical assessments and research and continues to evolve with accessible and transparent state-of-the-art practices in literature data curation and increased interoperability to other relevant resources. Environ Toxicol Chem 2022;41:1520-1539. © 2022 SETAC. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

Aryl hydrocarbon reporter gene bioassay for screening polyhalogenated dibenzo-p-dioxins/furans and dioxin-like polychlorinated biphenyls in hydrochar and sewage sludge

The suitability of the AhR reporter gene bioassays to screen the presence of polychlorinated dibenzo-p-dioxins/furans (PCDD/Fs) and dioxin-like polychlorinated biphenyls (dl-PCBs) in sewage sludge (SL) and related hydrochar (HC) was here investigated. Samples of SL obtained from six WWTPs were processed by hydrothermal carbonization to obtain the resultant HCs and both tested with DR-CALUX® bioassay. Levels of PCDD/Fs and dl-PCBs were also determined analytically in the same samples by GC-MS/MS. Bioanalytical Toxicity Equivalent values (BEQ) resulted in one order of magnitude higher in HC compared to SL samples and those obtained from the dl-PCBs fraction higher than those from PCDD/Fs. BEQ and TEQ_WHO values, the latter obtained by GC-MS/MS analysis on the same matrices, were highly correlated showing also a similar trend in the six WWTPs (R_S= 0.8252, p < 0.001; Pearson's R R_P =0.8029, p < 0.01). The suitability of AhR bioassays and in particular of the DR-CALUX® to screen the presence and biological activity of legacy organohalogen compounds in both SL and HC matrices was demonstrated for the first time which support their usage for the assessment of potential risks associated with their further environmental applications.

High-Throughput Assessment of the Abiotic Stability of Test Chemicals in In Vitro Bioassays

Abiotic stability of chemicals is not routinely tested prior to performing in vitro bioassays, although abiotic degradation can reduce the concentration of test chemicals leading to the formation of active or inactive transformation products, which may lead to misinterpretation of bioassay results. A high-throughput workflow was developed to measure the abiotic stability of 22 test chemicals in protein-rich aqueous media under typical bioassay conditions at 37 °C for 48 h. These test chemicals were degradable in the environment according to a literature review. The chemicals were extracted from the exposure media at different time points using a novel 96-pin solid-phase microextraction. The conditions were varied to differentiate between various reaction mechanisms. For most hydrolyzable chemicals, pH-dependent degradation in phosphate-buffered saline indicated that acid-catalyzed hydrolysis was less important than reactions with hydroxide ions. Reactions with proteins were mainly responsible for the depletion of the test chemicals in the media, which was simulated by bovine serum albumin (BSA) and glutathione (GSH). 1,2-Benzisothiazol-3(2H)-one, 2-methyl-4-isothiazolinone, and l-sulforaphane reacted almost instantaneously with GSH but not with BSA, indicating that GSH is a good proxy for reactivity with electrophilic amino acids but may overestimate the actual reaction with three-dimensional proteins. Chemicals such as hydroquinones or polyunsaturated chemicals are prone to autoxidation, but this reaction is difficult to differentiate from hydrolysis and could not be simulated by the oxidant N-bromosuccinimide. Photodegradation played a minor role because cells are exposed in incubators in the dark and simulations with high light intensities did not yield realistic degradation. Stability predictions from various in silico prediction models for environmental conditions can give initial indications of the stability but were not always consistent with the experimental stability in bioassays. As the presented workflow can be performed in high throughput under realistic bioassay conditions, it can be used to provide an experimental database for developing bioassay-specific stability prediction models.

Altered Larval Yellow Perch Swimming Behavior Due to Methylmercury and PCB126 Detected Using Hidden Markov Chain Models

Fish swimming behavior is a commonly measured response in aquatic ecotoxicology because behavior is considered a whole organism-level effect that integrates many sensory systems. Recent advancements in animal behavior models, such as hidden Markov chain models (HMM), suggest an improved analytical approach for toxicology. Using both new and traditional approaches, we examined the sublethal effects of PCB126 and methylmercury on yellow perch (YP) larvae (Perca flavescens) using three doses. Both approaches indicate larvae increase activity after exposure to either chemical. The middle methylmercury-dosed larvae showed multiple altered behavior patterns. First, larvae had a general increase in activity, typically performing more behavior states, more time swimming, and more swimming bouts per second. Second, when larvae were in a slow or medium swimming state, these larvae tended to switch between these states more often. Third, larvae swam slower during the swimming bouts. The upper PCB126-dosed larvae exhibited a higher proportion and a fast swimming state, but the total time spent swimming fast decreased. The middle PCB126-dosed larvae transitioned from fast to slow swimming states less often than the control larvae. These results indicate that developmental exposure to very low doses of these neurotoxicants alters YP larvae overall swimming behaviors, suggesting neurodevelopment alteration.

Emerging concepts and opportunities for endocrine disruptor screening of the non-EATS modalities

Endocrine disrupting chemicals (EDCs) are ubiquitous in the environment and involve diverse chemical-receptor interactions that can perturb hormone signaling. The Organization for Economic Co-operation and Development has validated several EDC-receptor bioassays to detect endocrine active chemicals and has established guidelines for regulatory testing of EDCs. Focus on testing over the past decade has been initially directed to EATS modalities (estrogen, androgen, thyroid, and steroidogenesis) and validated tests for chemicals that exert effects through non-EATS modalities are less established. Due to recognition that EDCs are vast in their mechanisms of action, novel bioassays are needed to capture the full scope of activity. Here, we highlight the need for validated assays that detect non-EATS modalities and discuss major international efforts underway to develop such tools for regulatory purposes, focusing on non-EATS modalities of high concern (i.e., retinoic acid, aryl hydrocarbon receptor, peroxisome proliferator-activated receptor, and glucocorticoid signaling). Two case studies are presented with strong evidence amongst animals and human studies for non-EATS disruption and associations with wildlife and human disease. This includes metabolic syndrome and insulin signaling (case study 1) and chemicals that impact the cardiovascular system (case study 2). This is relevant as obesity and cardiovascular disease represent two of the most significant health-related crises of our time. Lastly, emerging topics related to EDCs are discussed, including recognition of crosstalk between the EATS and non-EATS axis, complex mixtures containing a variety of EDCs, adverse outcome pathways for chemicals acting through non-EATS mechanisms, and novel models for testing chemicals. Recommendations and considerations for evaluating non-EATS modalities are proposed. Moving forward, improved understanding of the non-EATS modalities will lead to integrated testing strategies that can be used in regulatory bodies to protect environmental, animal, and human health from harmful environmental chemicals.

Machine learning-based biomarkers identification from toxicogenomics - Bridging to regulatory relevant phenotypic endpoints

One of the major challenges in realization and implementations of the Tox21 vision is the urgent need to establish quantitative link between in-vitro assay molecular endpoint and in-vivo regulatory-relevant phenotypic toxicity endpoint. Current toxicomics approach still mostly rely on large number of redundant markers without pre-selection or ranking, therefore, selection of relevant biomarkers with minimal redundancy would reduce the number of markers to be monitored and reduce the cost, time, and complexity of the toxicity screening and risk monitoring. Here, we demonstrated that, using time series toxicomics in-vitro assay along with machine learning-based feature selection (maximum relevance and minimum redundancy (MRMR)) and classification method (support vector machine (SVM)), an "optimal" number of biomarkers with minimum redundancy can be identified for prediction of phenotypic toxicity endpoints with good accuracy. We included two case studies for in-vivo carcinogenicity and Ames genotoxicity prediction, using 20 selected chemicals including model genotoxic chemicals and negative controls, respectively. The results suggested that, employing the adverse outcome pathway (AOP) concept, molecular endpoints based on a relatively small number of properly selected biomarker-ensemble involved in the conserved DNA-damage and repair pathways among eukaryotes, were able to predict both Ames genotoxicity endpoints and in-vivo carcinogenicity in rats. A prediction accuracy of 76% with AUC = 0.81 was achieved while predicting in-vivo carcinogenicity with the top-ranked five biomarkers. For Ames genotoxicity prediction, the top-ranked five biomarkers were able to achieve prediction accuracy of 70% with AUC = 0.75. However, the specific biomarkers identified as the top-ranked five biomarkers are different for the two different phenotypic genotoxicity assays. The top-ranked biomarkers for the in-vivo carcinogenicity prediction mainly focused on double strand break repair and DNA recombination, whereas the selected top-ranked biomarkers for Ames genotoxicity prediction are associated with base- and nucleotide-excision repair The method developed in this study will help to fill in the knowledge gap in phenotypic anchoring and predictive toxicology, and contribute to the progress in the implementation of tox 21 vision for environmental and health applications.

Towards a qAOP framework for predictive toxicology - Linking data to decisions

The adverse outcome pathway (AOP) is a conceptual construct that facilitates organisation and interpretation of mechanistic data representing multiple biological levels and deriving from a range of methodological approaches including in silico, in vitro and in vivo assays. AOPs are playing an increasingly important role in the chemical safety assessment paradigm and quantification of AOPs is an important step towards a more reliable prediction of chemically induced adverse effects. Modelling methodologies require the identification, extraction and use of reliable data and information to support the inclusion of quantitative considerations in AOP development. An extensive and growing range of digital resources are available to support the modelling of quantitative AOPs, providing a wide range of information, but also requiring guidance for their practical application. A framework for qAOP development is proposed based on feedback from a group of experts and three qAOP case studies. The proposed framework provides a harmonised approach for both regulators and scientists working in this area.

Integrating in vitro metabolomics with a 96-well high-throughput screening platform

INTRODUCTION

High-throughput screening (HTS) is emerging as an approach to support decision-making in chemical safety assessments. In parallel, in vitro metabolomics is a promising approach that can help accelerate the transition from animal models to high-throughput cell-based models in toxicity testing.

OBJECTIVE

In this study we establish and evaluate a high-throughput metabolomics workflow that is compatible with a 96-well HTS platform employing 50,000 hepatocytes of HepaRG per well.

METHODS

Low biomass cell samples were extracted for metabolomics analyses using a newly established semi-automated protocol, and the intracellular metabolites were analysed using a high-resolution spectral-stitching nanoelectrospray direct infusion mass spectrometry (nESI-DIMS) method that was modified for low sample biomass.

RESULTS

The method was assessed with respect to sensitivity and repeatability of the entire workflow from cell culturing and sampling to measurement of the metabolic phenotype, demonstrating sufficient sensitivity (> 3000 features in hepatocyte extracts) and intra- and inter-plate repeatability for polar nESI-DIMS assays (median relative standard deviation < 30%). The assays were employed for a proof-of-principle toxicological study with a model toxicant, cadmium chloride, revealing changes in the metabolome across five sampling times in the 48-h exposure period. To allow the option for lipidomics analyses, the solvent system was extended by establishing separate extraction methods for polar metabolites and lipids.

CONCLUSIONS

Experimental, analytical and informatics workflows reported here met pre-defined criteria in terms of sensitivity, repeatability and ability to detect metabolome changes induced by a toxicant and are ready for application in metabolomics-driven toxicity testing to complement HTS assays.

The use of in vitro methods in assessing human health risks associated with short-chain perfluoroalkyl and polyfluoroalkyl substances (PFAS)

Perfluoroalkyl and polyfluoroalkyl substances (PFAS) are a large class of industrial chemicals with a ubiquitous and persistent presence in the environment. Of the thousands of PFAS used by consumers and industry, very few have been thoroughly characterized for potential adverse effects. This is especially true for the novel short-chain (C < 8) alternatives that replaced legacy PFAS. Perfluoroalkyl and polyfluoroalkyl substances have revealed inconsistencies in the toxicokinetics predicted by animal models and empirical findings in humans. To adequately assess the possible health effects of short-chain PFAS, there is a need for robust aggregated data sets on the mechanistic underpinnings and physiochemical properties of these alternatives. Acquiring relevant data on the health effects of short-chain PFAS can be achieved through high-throughput methods supported by in vitro human cell-based models. This review briefly summarizes some of the toxicity data obtained using human cells in vitro, discusses the advantages and limitations of cell-based models, and provides insights on potential solutions to challenges presented with the use of these methods for use in safety assessments.

An in vitro-based hazard assessment of liquid smoke food flavourings

Liquid smoke products are widely used as a food additive to create a desired smoke flavour. These products may contain hazardous chemicals generated during the wood-burning process. However, the toxic effects of these types of hazardous chemicals constituting in the commercially available products are largely unknown. Therefore, a test battery of cell-based in vitro methods, covering different modes of actions of high relevance to human health, was applied to study liquid smoke products. Ten liquid smoke flavourings were tested as non-extracted and extracted. To assess the potential drivers of toxicity, we used two different solvents. The battery of in vitro methods covered estrogenicity, androgenicity, oxidative stress, aryl hydrocarbon receptor activity and genotoxicity. The non-extracted samples were tested at concentrations 0.002 to 1 μL liquid smoke flavouring/mL culture medium, while extracted samples were tested from 0.003 to 200 μL/mL. Genotoxicity was observed for nearly all non-extracted and all hexane-extracted samples, in which the former had higher potency. No genotoxicity was observed for ethyl acetate-extracted samples. Oxidative stress was activated by almost all extracted and non-extracted samples, while approximately half of the samples had aryl hydrocarbon receptor and estrogen receptor activities. This study used effect-based methods to evaluate the complex mixtures of liquid smoke flavourings. The increased bioactivities seen upon extractions indicate that non-polar chemicals are driving the genotoxicity, while polar substances are increasing oxidative stress and cytotoxic responses. The differences in responses indicate that non-extracted products contain chemicals that are able to antagonize toxic effects, and upon extraction, the protective substances are lost.

(Eco)toxicological tests for assessing impacts of chemical stress to aquatic ecosystems: Facts, challenges, and future

Monitoring of chemicals in the aquatic environment by chemical analysis alone cannot completely assess and predict the effects of chemicals on aquatic species and ecosystems. This is primarily because of the increasing number of (unknown) chemical stressors and mixture effects present in the environment. In addition, the ability of ecological indices to identify underlying stressors causing negative ecological effects is limited. Therefore, additional complementary methods are needed that can address the biological effects in a direct manner and provide a link to chemical exposure, i.e. (eco)toxicological tests. (Eco)toxicological tests are defined as test systems that expose biological components (cells, individuals, populations, communities) to (environmental mixtures of) chemicals to register biological effects. These tests measure responses at the sub-organismal (biomarkers and in vitro bioassays), whole-organismal, population, or community level. We performed a literature search to obtain a state-of-the-art overview of ecotoxicological tests available for assessing impacts of chemicals to aquatic biota and to reveal datagaps. In total, we included 509 biomarkers, 207 in vitro bioassays, 422 tests measuring biological effects at the whole-organismal level, and 78 tests at the population- community- and ecosystem-level. Tests at the whole-organismal level and biomarkers were most abundant for invertebrates and fish, whilst in vitro bioassays are mostly based on mammalian cell lines. Tests at the community- and ecosystem-level were almost missing for organisms other than microorganisms and algae. In addition, we provide an overview of the various extrapolation challenges faced in using data from these tests and suggest some forward looking perspectives. Although extrapolating the measured responses to relevant protection goals remains challenging, the combination of ecotoxicological experiments and models is key for a more comprehensive assessment of the effects of chemical stressors to aquatic ecosystems.

The Weight-of-Evidence Approach and the Need for Greater International Acceptance of Its Use in Tackling Questions of Chemical Harm to the Environment

As we attempt to manage chemicals in the environment we need to be sure that our research efforts are being directed at the substances of greatest threat. All too often we focus on a chemical of concern and then cast around for evidence of its effects in an unstructured way. Risk assessment based on laboratory ecotoxicity studies, combined with field chemical measurements, can only take us so far. Uncertainty about the range and sufficiency of evidence required to take restorative action often puts policymakers in a difficult situation. We review this conundrum and reflect on how the "Hill criteria," used widely by epidemiologists, have been applied to a weight-of-evidence approach (a term sometimes used interchangeably with ecoepidemiology) to build a case for causation. While using a set of such criteria to address sites of local environmental distress has been embraced by the US Environmental Protection Agency, we urge a wider adoption of weight-of-evidence approaches by policymakers, regulators, and scientists worldwide. A simplified series of criteria is offered. Progress will require a sustained commitment to long-term wildlife and chemical monitoring over a sufficient geographic spread. Development of a comprehensive monitoring network, coupled with assembling evidence of harm in a structured manner, should be the foundation for protecting our ecosystems and human health. This will enable us to not only judge the success or failure of our efforts but also diagnose underlying causes. Environ Toxicol Chem 2021;40:2968-2977. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Key Characteristics of Cardiovascular Toxicants

BACKGROUND

The concept of chemical agents having properties that confer potential hazard called key characteristics (KCs) was first developed to identify carcinogenic hazards. Identification of KCs of cardiovascular (CV) toxicants could facilitate the systematic assessment of CV hazards and understanding of assay and data gaps associated with current approaches.

OBJECTIVES

We sought to develop a consensus-based synthesis of scientific evidence on the KCs of chemical and nonchemical agents known to cause CV toxicity along with methods to measure them.

METHODS

An expert working group was convened to discuss mechanisms associated with CV toxicity.

RESULTS

The group identified 12 KCs of CV toxicants, defined as exogenous agents that adversely interfere with function of the CV system. The KCs were organized into those primarily affecting cardiac tissue (numbers 1-4 below), the vascular system (5-7), or both (8-12), as follows: 1) impairs regulation of cardiac excitability, 2) impairs cardiac contractility and relaxation, 3) induces cardiomyocyte injury and death, 4) induces proliferation of valve stroma, 5) impacts endothelial and vascular function, 6) alters hemostasis, 7) causes dyslipidemia, 8) impairs mitochondrial function, 9) modifies autonomic nervous system activity, 10) induces oxidative stress, 11) causes inflammation, and 12) alters hormone signaling.

DISCUSSION

These 12 KCs can be used to help identify pharmaceuticals and environmental pollutants as CV toxicants, as well as to better understand the mechanistic underpinnings of their toxicity. For example, evidence exists that fine particulate matter [PM ≤2.5μm in aerodynamic diameter (PM2.5)] air pollution, arsenic, anthracycline drugs, and other exogenous chemicals possess one or more of the described KCs. In conclusion, the KCs could be used to identify potential CV toxicants and to define a set of test methods to evaluate CV toxicity in a more comprehensive and standardized manner than current approaches. https://doi.org/10.1289/EHP9321.

High-throughput analyses and Bayesian network modeling highlight novel epigenetic Adverse Outcome Pathway networks of DNA methyltransferase inhibitor mediated transgenerational effects

A number of epigenetic modulating chemicals are known to affect multiple generations of a population from a single ancestral exposure, thus posing transgenerational hazards. The present study aimed to establish a high-throughput (HT) analytical workflow for cost-efficient concentration-response analysis of epigenetic and phenotypic effects, and to support the development of novel Adverse Outcome Pathway (AOP) networks for DNA methyltransferase (DNMT) inhibitor-mediated transgenerational effects on aquatic organisms. The model DNMT inhibitor 5-azacytidine (5AC) and the model freshwater crustacean Daphnia magna were used to generate new experimental data and served as prototypes to construct AOPs for aquatic organisms. Targeted HT bioassays (DNMT ELISA, MS-HRM and qPCR) in combination with multigenerational ecotoxicity tests revealed concentration-dependent transgenerational (F0-F3) effects of 5AC on total DNMT activity, DNA promoter methylation, gene body methylation, gene transcription and reproduction. Top sensitive toxicity pathways related to 5AC exposure, such as apoptosis and DNA damage responses were identified in both F0 and F3 using Gaussian Bayesian network modeling. Two novel epigenetic AOP networks on DNMT inhibitor mediated one-generational and transgenerational effects were developed for aquatic organisms and assessed for the weight of evidence. The new HT analytical workflow and AOPs can facilitate future ecological hazard assessment of epigenetic modulating chemicals.

Xenopus laevis and human type 3 iodothyronine deiodinase enzyme cross-species sensitivity to inhibition by ToxCast chemicals

Deiodinase enzymes are critical for tissue-specific and temporal control of activation or inactivation of thyroid hormones during vertebrate development, including amphibian metamorphosis. We previously screened ToxCast chemicals for inhibitory activity toward human recombinant Type 3 iodothyronine deiodinase enzyme (hDIO3) and subsequently produced Xenopus laevis recombinant dio3 enzyme (Xldio3) with the goals to identify specific chemical inhibitors of Xldio3, to evaluate cross-species sensitivity and explore whether the human assay results are predictive of the amphibian. We identified a subset of 356 chemicals screened against hDIO3 to test against Xldio3, initially at a single concentration (200 μM), and further tested 79 in concentration-response mode. Most chemicals had IC₅₀ values lower for hDIO3 than for Xldio3 and many had steep Hill slopes (a potential indication of non-specific inhibition). However, eight of the most potent chemicals are likely specific inhibitors, with IC₅₀ values of 14 μM or less, Hill slopes near -1 and curves not significantly different between species likely due to conservation of catalytically active amino acids. Controlling for assay conditions, human in vitro screening results can be predictive of activity in the amphibian assay. This study lays the groundwork for future studies using recombinant non-mammalian proteins to test cross-species sensitivity to chemicals. DISCLAIMER: The views expressed in this paper are those of the authors and do not necessarily reflect the views or policies of the U.S. Environmental Protection Agency. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.

Assessing the Ecological Risks of Per- and Polyfluoroalkyl Substances: Current State-of-the Science and a Proposed Path Forward

Per- and poly-fluoroalkyl substances (PFAS) encompass a large, heterogenous group of chemicals of potential concern to human health and the environment. Based on information for a few relatively well-understood PFAS such as perfluorooctane sulfonate and perfluorooctanoate, there is ample basis to suspect that at least a subset can be considered persistent, bioaccumulative, and/or toxic. However, data suitable for determining risks in either prospective or retrospective assessments are lacking for the majority of PFAS. In August 2019, the Society of Environmental Toxicology and Chemistry sponsored a workshop that focused on the state-of-the-science supporting risk assessment of PFAS. The present review summarizes discussions concerning the ecotoxicology and ecological risks of PFAS. First, we summarize currently available information relevant to problem formulation/prioritization, exposure, and hazard/effects of PFAS in the context of regulatory and ecological risk assessment activities from around the world. We then describe critical gaps and uncertainties relative to ecological risk assessments for PFAS and propose approaches to address these needs. Recommendations include the development of more comprehensive monitoring programs to support exposure assessment, an emphasis on research to support the formulation of predictive models for bioaccumulation, and the development of in silico, in vitro, and in vivo methods to efficiently assess biological effects for potentially sensitive species/endpoints. Addressing needs associated with assessing the ecological risk of PFAS will require cross-disciplinary approaches that employ both conventional and new methods in an integrated, resource-effective manner. Environ Toxicol Chem 2021;40:564-605. © 2020 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

4,5,6,7-Tetrabromo-2,3-dihydro-1,1,3-trimethyl-3-(2,3,4,5-tetrabromophenyl)-1H-indene (OBTMPI): Levels in humans and in silico toxicological profiles

Limited human exposure and toxicity data are currently available for 4,5,6,7-Tetrabromo-2,3-dihydro-1,1,3-trimethyl-3-(2,3,4,5-tetrabromophenyl)-1H-indene (OBTMPI), a flame retardant often used for high temperature application of various polymer materials. Levels of OBTMPI in a cohort population that includes children and their co-residing parents (n = 217) in Canada were determined. Detection frequency of OBTMPI in the samples was 22.6%. OBTMPI levels were in general at sub-to low ng/g lipid weight level with a 95th percentile at 15.6 ng/g lipid weight. Compared to an earlier study conducted in 2008-2009 in the same region, results from this study show an increase in both detection frequency and concentration of OBTMPI. In silico toxicity predictions using Multicase CaseUltra and Leadscope Model Applier suggested that OBTMPI, and its possible metabolites in humans, while unlikely to be carcinogenic or mutagenic, exhibit some estrogen antagonist, androgen antagonist and estrogen binding capability reflective of possible endocrine disrupting properties.

Modeling Bioavailable Concentrations in Zebrafish Cell Lines and Embryos Increases the Correlation of Toxicity Potencies across Test Systems

Linking cellular toxicity to low-tier animal toxicity and beyond is crucial within the adverse outcome pathway concept and the 3R framework. This study aimed to determine and compare the bioavailable effect concentrations in zebrafish cell lines and embryos. Acute, short-term toxicity (48 h) of eight veterinary pharmaceuticals was measured in two zebrafish cell lines (hepatocytes, fibroblasts) and zebrafish embryos. Seven endpoints of cytotoxicity were recorded. The fish embryo acute toxicity test was modified by adding sublethal endpoints. Chemical distribution modeling (mass balance) was applied to compute the bioavailable compound concentrations in cells (Cfree) and embryos (Cint;aq) based on nominal effect concentrations (Cnom). Effect concentration ratios were calculated (cell effects/embryo effects). A low correlation was observed between cytotoxicity and embryo toxicity when nominal concentrations were used. Modeled bioavailable effect concentrations strongly increased correlations and placed regression lines close to the line of unity and axis origin. Cytotoxicity endpoints showed differences in sensitivity and predictability. The hepatocyte cell line depicted closer proximity to the embryo data. Conclusively, the high positive correlation between the cell- and embryo-based test systems emphasizes the appropriate modulation of toxicity when linked to bioavailable concentrations. Furthermore, it highlights the potential of fish cell lines to be utilized in integrated testing strategies.

Parameterization of Microsomal and Cytosolic Scaling Factors: Methodological and Biological Considerations for Scalar Derivation and Validation

Mathematical models that can predict the kinetics of compounds have been increasingly adopted for drug development and risk assessment. Data for these models may be generated from in vitro experimental systems containing enzymes contributing to metabolic clearance, such as subcellular tissue fractions including microsomes and cytosol. Extrapolation from these systems is facilitated by common scaling factors, known as microsomal protein per gram (MPPG) and cytosolic protein per gram (CPPG). Historically, parameterization of MPPG and CPPG has employed the use of recovery factors, commonly benchmarked to cytochromes P450 which work well in some contexts, but could be problematic for other enzymes. Here, we propose absolute quantification of protein content and supplementary assays to evaluate microsomal/cytosolic purity that should be employed. Examples include calculation of microsomal latency by mannose-6-phosphatase activity and immunoblotting of subcellular fractions with fraction-specific markers. Further considerations include tissue source, as disease states can affect enzyme expression and activity, and the methodology used for scalar parameterization. Regional- and organ-specific expression of enzymes, in addition to differences in organ physiology, is another important consideration. Because most efforts have focused on the liver that is, for the most part, homogeneous, derived scalars may not capture the heterogeneity of other major tissues contributing to xenobiotic metabolism including the kidneys and small intestine. Better understanding of these scalars, and how to appropriately derive them from extrahepatic tissues can provide support to the inferences made with physiologically based pharmacokinetic modeling, increase its accuracy in characterizing in vivo drug pharmacokinetics, and improve confidence in go-no-go decisions for clinical trials.

Bioavailable Environmental Pollutant Patterns in Sediments from Passive Equilibrium Sampling

Sediment-associated risks depend on the bioavailable fraction of organic chemicals and cannot be comprehended by their total concentrations. The present study investigated contamination patterns of bioavailable chemicals in sediments from various sites around the globe by using passive equilibrium sampling. The extracts had been characterized previously for mixture effects by in vitro reporter gene assays and were in this study analyzed using gas chromatography-high resolution mass spectrometry for 121 chemicals including both legacy and emerging contaminants. The spatial distribution of the detected chemicals revealed distinct contamination patterns among sampling sites. We identified compounds in common at the different sites but most contaminant mixtures were site-specific. The mixture effects of the detected chemicals were predicted with a mixture toxicity model from effect concentrations of bioactive single chemicals and detected concentrations, applying a joint model for concentration addition and independent action. The predicted mixture effects were dominated by polycyclic aromatic hydrocarbons, and among the chemicals with available effect data, 17% elicited oxidative stress response and 18% activated the arylhydrocarbon receptor. Except for two sites in Sweden, where 11 and 38% of the observed oxidative stress response were explained by the detected chemicals, less than 10% of effects in both biological end points were explained. These results provide a comprehensive investigation of bioavailable contamination patterns of sediments and may serve as an example of employing passive equilibrium sampling as a monitoring technique to integrate the risk of bioavailable sediment-associated chemicals in aquatic environments.

Advancements in effect-based surface water quality assessment

Legally-prescribed chemical monitoring is unfit for determining the pollution status of surface waters, and there is a need for improved assessment methods that consider the aggregated risk of all bioavailable micropollutants present in the aquatic environment. Therefore, the present study aimed to advance effect-based water quality assessment by implementing methodological improvements and to gain insight into contamination source-specific bioanalytical responses. Passive sampling of non-polar and polar organic compounds and metals was applied at 14 surface water locations that were characterized by two major anthropogenic contamination sources, agriculture and wastewater treatment plant (WWTP) effluent, as well as reference locations with a low expected impact from micropollutants. Departing from the experience gained in previous studies, a battery of 20 in vivo and in vitro bioassays was composed and subsequently exposed to the passive sampler extracts. Next, the bioanalytical responses were divided by their respective effect-based trigger values to obtain effect-based risk quotients, which were summed per location. These cumulative ecotoxicological risks were lowest for reference locations (4.3-10.9), followed by agriculture locations (11.3-27.2) and the highest for WWTP locations (12.8-47.7), and were mainly driven by polar organic contaminants. The bioanalytical assessment of the joint risks of metals and (non-)polar organic compounds resulted in the successful identification of pollution source-specific ecotoxicological risk profiles: none of the bioassays were significantly associated with reference locations nor with multiple location types, while horticulture locations were significantly characterized by anti-AR and anti-PR activity and cytotoxicity, and WWTP sites by ERα activity and toxicity in the in vivo bioassays. It is concluded that the presently employed advanced effect-based methods can readily be applied in surface water quality assessment and that the integration of chemical- and effect-based monitoring approaches will foster future-proof water quality assessment strategies on the road to a non-toxic environment.

Investigating (anti)estrogenic activities within South African wastewater and receiving surface waters: Implication for reliable monitoring

Natural and synthetic steroid hormones and many persistent organic pollutants are of concern for their endocrine-disrupting activities observed in receiving surface waters. Apart from the demonstrated presence of estrogen- and estrogen-mimicking compounds in surface waters, antagonistic (anti-estrogenic) responses originating from wastewater effluent have been reported but are less known. Estrogenicity and anti-estrogenicity were assessed using recombinant yeast estrogen receptor binding assays (YES/YAES) at ten South African wastewater treatment works (WWTWs) and receiving rivers in two separate sampling campaigns during the summer- and winter periods in the area. Four WWTWs were then further investigated to show daily variation in estrogenic endocrine-disrupting activities during the treatment process. Although estrogenicity was notably reduced at most of the WWTWs, some treated effluent and river water samples were shown to be above effect-based trigger values posing an endocrine-disrupting risk for aquatic life and potential health risks for humans. Furthermore, estrogenicity recorded in samples collected upstream from some WWTW discharge points also exceeded some calculated risk trigger values, which highlights the impact of alternative pollution sources contributing towards endocrine disrupting contaminants (EDCs) in the environment. The YAES further showed variable anti-estrogenic activities in treated wastewater. The current study highlights a variety of factors that may affect bioassay outcomes and conclusions drawn from the results for risk decision-making. For example, mismatches were found between estrogenic and anti-estrogenic activity, which suggests a potential masking effect in WWTW effluents and highlights the complexity of environmental samples containing chemical mixtures having variable endocrine-disrupting modes of action. Although the recombinant yeast assay is not without its limitations to show endocrine-disrupting modulation in test water systems, it serves as a cost-effective tier-1 scoping assay for further risk characterisation and intervention.