Editor's Highlight: Analysis of the Effects of Cell Stress and Cytotoxicity on In Vitro Assay Activity Across a Diverse Chemical and Assay Space

Migration of endocrine and metabolism disrupting chemicals from plastic food packaging

Plastics constitute a vast array of substances, with over 16000 known plastic chemicals, including intentionally and non-intentionally added substances. Thousands of chemicals, including toxic ones, are extractable from plastics, however, the extent to which these compounds migrate from everyday products into food or water remains poorly understood. This study aims to characterize the endocrine and metabolism disrupting activity, as well as the chemical composition of migrates from plastic food contact articles (FCAs) from four countries as significant sources of human exposure. Fourteen plastic FCAs covering seven polymer types with high global market shares were migrated into water and a water-ethanol mixture as food simulants according to European regulations. The migrates were analyzed using reporter gene assays for nuclear receptors relevant to human health and non-target chemical analysis to characterize the chemical composition. Chemicals migrating from each FCA interfered with at least two nuclear receptors, predominantly targeting pregnane X receptor (24/28 migrates). Moreover, peroxisome proliferator receptor gamma was activated by 19 out of 28 migrates, though mostly with lower potencies. Estrogenic and antiandrogenic activity was detected in eight and seven migrates, respectively. Fewer chemicals and less toxicity migrated into water compared to the water-ethanol mixture. However, 73 % of the 15 430 extractable chemical features also transferred into food simulants, and the water-ethanol migrates exhibited a similar toxicity prevalence compared to methanol extracts. The chemical complexity differed largely between FCAs, with 8 to 10631 chemical features migrating into food simulants. Using stepwise partial least squares regressions, we successfully narrowed down the list of potential active chemicals, identified known endocrine disrupting chemicals, such as triphenyl phosphate, and prioritized chemical features for further identification. This study demonstrates the migration of endocrine and metabolism disrupting chemicals from plastic FCAs into food simulants, rendering a migration of these compounds into food and beverages probable.

Exploring BPA alternatives - Environmental levels and toxicity review

Bisphenol A alternatives are manufactured as potentially less harmful substitutes of bisphenol A (BPA) that offer similar functionality. These alternatives are already in the market, entering the environment and thus raising ecological concerns. However, it can be expected that levels of BPA alternatives will dominate in the future, they are limited information on their environmental safety. The EU PARC project highlights BPA alternatives as priority chemicals and consolidates information on BPA alternatives, with a focus on environmental relevance and on the identification of the research gaps. The review highlighted aspects and future perspectives. In brief, an extension of environmental monitoring is crucial, extending it to cover BPA alternatives to track their levels and facilitate the timely implementation of mitigation measures. The biological activity has been studied for BPA alternatives, but in a non-systematic way and prioritized a limited number of chemicals. For several BPA alternatives, the data has already provided substantial evidence regarding their potential harm to the environment. We stress the importance of conducting more comprehensive assessments that go beyond the traditional reproductive studies and focus on overlooked relevant endpoints. Future research should also consider mixture effects, realistic environmental concentrations, and the long-term consequences on biota and ecosystems.

Searching for LINCS to Stress: Using Text Mining to Automate Reference Chemical Curation

Adaptive stress response pathways (SRPs) restore cellular homeostasis following perturbation but may activate terminal outcomes like apoptosis, autophagy, or cellular senescence if disruption exceeds critical thresholds. Because SRPs hold the key to vital cellular tipping points, they are targeted for therapeutic interventions and assessed as biomarkers of toxicity. Hence, we are developing a public database of chemicals that perturb SRPs to enable new data-driven tools to improve public health. Here, we report on the automated text-mining pipeline we used to build and curate the first version of this database. We started with 100 reference SRP chemicals gathered from published biomarker studies to bootstrap the database. Second, we used information retrieval to find co-occurrences of reference chemicals with SRP terms in PubMed abstracts and determined pairwise mutual information thresholds to filter biologically relevant relationships. Third, we applied these thresholds to find 1206 putative SRP perturbagens within thousands of substances in the Library of Integrated Network-Based Cellular Signatures (LINCS). To assign SRP activity to LINCS chemicals, domain experts had to manually review at least three publications for each of 1206 chemicals out of 181,805 total abstracts. To accomplish this efficiently, we implemented a machine learning approach to predict SRP classifications from texts to prioritize abstracts. In 5-fold cross-validation testing with a corpus derived from the 100 reference chemicals, artificial neural networks performed the best (F1-macro = 0.678) and prioritized 2479/181,805 abstracts for expert review, which resulted in 457 chemicals annotated with SRP activities. An independent analysis of enriched mechanisms of action and chemical use class supported the text-mined chemical associations (p < 0.05): heat shock inducers were linked with HSP90 and DNA damage inducers to topoisomerase inhibition. This database will enable novel applications of LINCS data to evaluate SRP activities and to further develop tools for biomedical information extraction from the literature.

A proposed in vitro cytotoxicity test battery to detect and predict hepatotoxicity via multiple mechanisms and pathways: a minireview

The 21st-century toxicity testing program recommends the use of cytotoxicity data from human cells in culture for rapid in vitro screening focusing on biological pathways of potential toxicants to predict in vivo toxicity. Liver is the major organ for both endogenous and exogenous chemical metabolism of xenobiotics. Therefore, this review was undertaken to evaluate side by side five different currently used commercial cytotoxicity assay kits for purpose of rapid predictive screening of potential hepatotoxicants. The test compounds for this review were selected from the NIH LiverTox and FDA Liver Toxicity Knowledge Base (LTKB) databases. Human liver HepG2, HepaRG, and rat liver Clone 9 cell cultures were used as the in vitro liver models. Five commercial assay kits representing different biomarkers or pathways were selected for this review. These kits are Vita-Orange Cell Viability Assay Kit (Sigma-Aldrich), CellTiter-Glo Cell Viability Assay Kit (Promega), CytoTox-ONE Homogeneous Membrane Integrity Assay Kit (Promega), DNA Quantitation Fluorescence Assay Kit (Sigma-Aldrich), and Neutral Red Based In Vitro Toxicology Assay Kit (Sigma-Aldrich). This review found that these kits can all be used for rapid predictive cytotoxicity screening of potential hepatotoxicants in human liver HepG2 and rat liver Clone 9 cells in culture as in vitro liver models without compromising quality and accuracy of endpoint measurements as well as the length of toxicity screening time. Unraveling the structure-activity relationship of potential hepatotoxins would help to classify their hepatotoxic effects. Therefore, in addition to the current regulatory hepatotoxicity testing strategies, development and regulatory approval of hepatotoxins need to be discussed in order to identify potential gaps in the safety assessment. The overall results of our study support the hypothesis that a battery of rapid, simple, and reliable assays is an excellent tool for predicting in vivo effects of suspected liver toxins. The human liver HepaRG cells do not appear to be an ideal in vitro liver model for this purpose.

Marketable 1,3-dimethylamylamine and caffeine-based thermogenic supplements: Regulatory genotoxicity assessment through in vitro and in silico approaches

The consumption of dietary supplements to enhance physical performance has increased significantly in the last century, especially thermogenic pre-workout supplements. Nevertheless, this industry has faced criticism for inadequate safety measures surveillance in regulatory issues regarding their products. The aims of our study were to investigate two pre-workout supplements with respect to (1) mutagenicity utilizing Salmonella/microsome assay; (2) genotoxicity employing cytokinesis-block micronucleus (CBMN) assay protocols; and (3) hepatocytoxicity using WST cell proliferation, activities of lactate dehydrogenase (LDH) and alkaline phosphatase using human liver carcinoma (HepG2) and mouse fibroblast (F C3H) cells. Oxidative stress was determined through glutathione (GSH) measurement and in silico for predictions of pharmacokinetics and toxicity for the most abundant isolated substances present in these supplements. Both supplements induced mutagenicity in all examined bacterial strains, especially in the presence of exogenous metabolism. Further, tested supplements significantly elevated the formation of micronuclei (MN) as well as other cellular phenomena. Concentration- and time-dependent curves were observed for hepatotoxicity in both studied cell lines. In addition, both supplements decreased levels of intracellular and extracellular GSH. In silico predictions showed that the isolated individual compounds failed to induce the observed outcomes. Our findings provide contributions to the molecular mechanisms underlying two pre-workout supplement-induced toxicity and the need for surveillance.

From pixels to phenotypes: Integrating image-based profiling with cell health data as BioMorph features improves interpretability

Cell Painting assays generate morphological profiles that are versatile descriptors of biological systems and have been used to predict in vitro and in vivo drug effects. However, Cell Painting features extracted from classical software such as CellProfiler are based on statistical calculations and often not readily biologically interpretable. In this study, we propose a new feature space, which we call BioMorph, that maps these Cell Painting features with readouts from comprehensive Cell Health assays. We validated that the resulting BioMorph space effectively connected compounds not only with the morphological features associated with their bioactivity but with deeper insights into phenotypic characteristics and cellular processes associated with the given bioactivity. The BioMorph space revealed the mechanism of action for individual compounds, including dual-acting compounds such as emetine, an inhibitor of both protein synthesis and DNA replication. Overall, BioMorph space offers a biologically relevant way to interpret the cell morphological features derived using software such as CellProfiler and to generate hypotheses for experimental validation.

A guide to the use of bioassays in exploration of natural resources

Bioassays are the main tool to decipher bioactivities from natural resources thus their selection and quality are critical for optimal bioprospecting. They are used both in the early stages of compounds isolation/purification/identification, and in later stages to evaluate their safety and efficacy. In this review, we provide a comprehensive overview of the most common bioassays used in the discovery and development of new bioactive compounds with a focus on marine bioresources. We present a comprehensive list of practical considerations for selecting appropriate bioassays and discuss in detail the bioassays typically used to explore antimicrobial, antibiofilm, cytotoxic, antiviral, antioxidant, and anti-ageing potential. The concept of quality control and bioassay validation are introduced, followed by safety considerations, which are critical to advancing bioactive compounds to a higher stage of development. We conclude by providing an application-oriented view focused on the development of pharmaceuticals, food supplements, and cosmetics, the industrial pipelines where currently known marine natural products hold most potential. We highlight the importance of gaining reliable bioassay results, as these serve as a starting point for application-based development and further testing, as well as for consideration by regulatory authorities.

Adverse effects in traditional and alternative toxicity tests

Chemical safety assessment begins with defining the lowest level of chemical that alters one or more measured endpoints. This critical effect level, along with factors to account for uncertainty, is used to derive limits for human exposure. In the absence of data regarding the specific mechanisms or biological pathways affected, non-specific endpoints such as body weight and non-target organ weight changes are used to set critical effect levels. Specific apical endpoints such as impaired reproductive function or altered neurodevelopment have also been used to set chemical safety limits; however, in test guidelines designed for specific apical effect(s), concurrently measured non-specific endpoints may be equally or more sensitive than specific endpoints. This means that rather than predicting a specific toxicological response, animal data are often used to develop protective critical effect levels, without assuming the same change would be observed in humans. This manuscript is intended to encourage a rethinking of how adverse chemical effects are interpreted: non-specific endpoints from in vivo toxicological studies data are often used to derive points of departure for use with safety assessment factors to create recommended exposure levels that are broadly protective but not necessarily target-specific.

Investigating open access new approach methods (NAM) to assess biological points of departure: A case study with 4 neurotoxic pesticides

Open access new approach methods (NAM) in the US EPA ToxCast program and NTP Integrated Chemical Environment (ICE) were used to investigate activities of four neurotoxic pesticides: endosulfan, fipronil, propyzamide and carbaryl. Concordance of in vivo regulatory points of departure (POD) adjusted for interspecies extrapolation (AdjPOD) to modelled human Administered Equivalent Dose (AEDHuman) was assessed using 3-compartment or Adult/Fetal PBTK in vitro to in vivo extrapolation. Model inputs were from Tier 1 (High throughput transcriptomics: HTTr, high throughput phenotypic profiling: HTPP) and Tier 2 (single target: ToxCast) assays. HTTr identified gene expression signatures associated with potential neurotoxicity for endosulfan, propyzamide and carbaryl in non-neuronal MCF-7 and HepaRG cells. The HTPP assay in U-2 OS cells detected potent effects on DNA endpoints for endosulfan and carbaryl, and mitochondria with fipronil (propyzamide was inactive). The most potent ToxCast assays were concordant with specific components of each chemical mode of action (MOA). Predictive adult IVIVE models produced fold differences (FD) < 10 between the AEDHuman and the measured in vivo AdjPOD. The 3-compartment model was concordant (i.e., smallest FD) for endosulfan, fipronil and carbaryl, and PBTK was concordant for propyzamide. The most potent AEDHuman predictions for each chemical showed HTTr, HTPP and ToxCast were mainly concordant with in vivo AdjPODs but assays were less concordant with MOAs. This was likely due to the cell types used for testing and/or lack of metabolic capabilities and pathways available in vivo. The Fetal PBTK model had larger FDs than adult models and was less predictive overall.

Cashmeran as a potential endocrine disrupting chemical: What does the weight-of-the-evidence indicate?

Cashmeran is a fragrance ingredient. Risk assessments are available but have not focused on its endocrine disruptor potential. The objective was to evaluate Cashmeran as a potential endocrine-disrupting chemical (EDC). The assessment was based on data from US EPA's CompTox Chemicals Dashboard, the Danish (Q)SAR Database, in vitro assays, and in vivo studies. ToxCast assays related to estrogen, androgen, thyroid, and steroidogenesis modalities were Inactive at non-cytotoxic concentrations. In vitro assays demonstrated no estrogenic activity in a human cervical epithelioid carcinoma HeLa cell line and indicated only weak agonist estrogenic activity in Chinese Hamster Ovary (CHO)-K1 cells. In the same test, no agonist or antagonist activity was detected for human androgen receptor (hAR) and thyroid hormone receptor β (hTHRβ) binding. The Danish QSAR database didn't indicate any ED potential. There were no adverse endocrine related effects in either a 90-day repeated gavage dosing study or a reproductive and developmental screening study. Regarding ED potential for environment, the data from two limited environmental ED related studies on Cashmeran did not raise any concern. Data from in vitro and in vivo studies were considered for environmental ED concern. Based on the weight-of-the-evidence, Cashmeran is not expected to cause endocrine effects.

Suspect screening and effect evaluation for small-molecule agonists of the antioxidant response element pathway in fine particulate matter

Oxidative stress is an important mechanism by which fine particulate matter (PM2.5) generates toxicity. However, few inducers have been identified, and the combined effects of the contributing chemicals have rarely been examined. In this study, the occurrence of small-molecule agonists of the antioxidant response element (ARE) pathway was explored in 59 PM2.5 samples from urban Beijing over a one-year period via target and suspect screening analysis. In total, 31 chemicals with diverse structures and use categories were identified and quantified, among which polycyclic aromatic hydrocarbons (PAHs), pesticides, and phytochemicals were the most abundant chemical groups in terms of cumulative concentrations. PAHs and organonitrogen pesticides were also prioritized as the predominant contributors to the cumulative effect of ARE pathway activation, accounting for 55 % and 37 %, respectively. A combination of the prioritized chemicals (i.e., benzo[b]fluoranthene, benzo[k]fluoranthene, pyridaben, and acetochlor) was mixed at a fixed dosing ratio according to the measured average concentrations in samples, and synergism was revealed as the mode of mixture interaction. These findings highlight the importance of high-throughput chemical screening for identifying hazardous components in complex environmental samples, and also expand the knowledge regarding the components contributing to PM2.5-induced oxidative stress.

Assessment of bioactive chemicals in wastewater effluents and surface waters using in vitro bioassays in the Nakdong River basin, Korea

Organic micropollutants present in effluents of wastewater treatment plants (WWTPs) can negatively affect the quality of receiving waters or drinking water sources. The present work monitored the concentration of bioactive chemicals using a battery of in vitro bioassays in 14 WWTP effluents, 2 effluent-dominant streams, and 5 river waters in the Nakdong River basin, Korea, for a two-year period. The WWTP effluents showed AR/ERα/TRβ (androgen/estrogen/thyroid hormone) activities at a few to tens ng/L, PAH/PPARγ/p53 (polycyclic-aromatic-hydrocarbon/lipid metabolism/genotoxicity) activities at hundreds ng/L, and PXR/Nrf2 (xenobiotic metabolism/oxidative stress) activities at tens to hundreds μg/L as bioanalytical equivalent concentrations. The concentration level and type of bioactivities were statistically not affected by the source, season, or treatment processes of WWTPs for most endpoints. The effluent-dominant streams showed similar levels of AR/ERα/PAH/PXR/Nrf2 activities compared to the upstream WWTP effluents. The river waters showed lower levels of AR/ERα activities (by factors of 6 or 7) but had only slightly lower PAH/PXR/Nrf2 activities (within factors of 2) than the WWTP effluents when compared based on median concentration. Cytotoxicity was below the quantification limit (0.3 μg/L) in most effluent and river samples. For ERα/PAH/PXR/Nrf2, the median bioactivity levels of the river waters were higher than at least one of the effect-based trigger (EBT) values proposed in the literature. Further monitoring work and reliable/realistic EBT derivation are needed to determine possible ecological risks posed by the observed bioactivities.

Effect-Directed Analysis Combined with Nontarget Screening to Identify Unmonitored Toxic Substances in the Environment

Effect-directed analysis (EDA) combined with nontarget screening (NTS) has established a valuable tool for the identification of unmonitored toxic substances in environmental samples. It consists of three main steps: (1) highly potent fraction identification, (2) toxicant candidate selection, and (3) major toxicant identification. Here, we discuss the methodology, current status, limitations, and future challenges of EDA combined with NTS. This method has been applied successfully to various environmental samples, such as sediments, wastewater treatment plant effluents, and biota. We present several case studies and highlight key results. EDA has undergone significant technological advancements in the past 20 years, with the establishment of its key components: target chemical analysis, bioassays, fractionation, NTS, and data processing. However, it has not been incorporated widely into environmental monitoring programs. We provide suggestions for the application of EDA combined with NTS in environmental monitoring programs and management, with the identification of further research needs.

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

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

Mixture effect assessment applying in vitro bioassays to in-tissue silicone extracts of traditional foods prepared from beluga whale blubber

We complement an earlier study on the nutrient and environmental contaminant levels in Arctic beluga whale traditional foods by mixture effect assessment using in vitro bioassays. Mixtures were extracted by in-tissue sampling of raw blubber and several traditional food preparations including Muktuk and Uqsuq using silicone (polydimethylsiloxane, PDMS) as sampler. PDMS extracts persistent and degradable neutral organic chemicals of a wide range of hydrophobicity with defined lipid-PDMS partition ratios. The solvent extracts of PDMS were dosed in various reporter gene assays based on human cell lines. Cytotoxicity was consistent across all cell lines and was a good indicator of overall chemical burden. No hormone-like effects on the estrogen receptor, the progesterone receptor and the glucocorticoid receptor were observed but a few samples activated the androgen receptor, albeit with low potency. The peroxisome-proliferator activated receptor (PPARγ) was the most sensitive endpoint followed by activation of oxidative stress response and activation of the arylhydrocarbon (AhR) receptor. The detected pollutants only explained a small fraction of the experimental mixture effects, indicating additional bioactive pollutants. The effect levels of the extracted mixtures were higher than those observed in blubber extracts of dugongs living off the shore of Australia. Roasting over an open fire or food preparation near a smokehouse led to increased PAH levels that were reflected in increased oxidative stress response and activation of the AhR. So far in vitro assays have only been used to quantify persistent dioxin-like chemicals in food and feed but this pilot study demonstrates a much broader potential for food safety evaluations complementing chemical analytical monitoring.

Comparison between endocrine activity assessed using ToxCast/Tox21 database and human plasma concentration of sunscreen active ingredients/UV filters

Sunscreen products are composed of ultraviolet (UV) filters and formulated to reduce exposure to sunlight thereby lessening skin damage. Concerns have been raised regarding the toxicity and potential endocrine disrupting (ED) effects of UV filters. The ToxCast/Tox21 program, that is, CompTox, is a high-throughput in vitro screening database of chemicals that identify adverse outcome pathways, key events, and ED potential of chemicals. Using the ToxCast/Tox21 database, octisalate, homosalate, octocrylene, oxybenzone, octinoxate, and avobenzone, 6 commonly used organic UV filters, were found to have been evaluated. These UV filters showed low potency in these bioassays with most activity detected above the range of the cytotoxic burst. The pathways that were most affected were the cell cycle and the nuclear receptor pathways. Most activity was observed in liver and kidney-based bioassays. These organic filters and their metabolites showed relatively weak ED activity when tested in bioassays measuring estrogen receptor (ER), androgen receptor (AR), thyroid receptor, and steroidogenesis activity. Except for oxybenzone, all activity in the endocrine assays occurred at concentrations greater than the cytotoxic burst. Moreover, except for oxybenzone, plasma concentrations (Cmax) measured in humans were at least 100× lower than bioactive (AC50/ACC) concentrations that produced a response in ToxCast/Tox21 assays. These data are consistent with in vivo animal/human studies showing weak or negligible endocrine activity. In sum, when considered as part of a weight-of-evidence assessment and compared with measured plasma concentrations, the results show these organic UV filters have low intrinsic biological activity and risk of toxicity including endocrine disruption in humans.

Assessing utility of thyroid in vitro screening assays through comparisons to observed impacts in vivo

To better understand endocrine disruption, the U.S. Environmental Protection Agency's (USEPA) Endocrine Disruptor Screening Program (EDSP) utilizes a two-tiered approach to investigate the potential of a chemical to interact with the estrogen, androgen, or thyroid systems. As in vivo testing lacks the throughput to address data gaps on endocrine bioactivity for thousands of chemicals, in vitro high-throughput screening (HTS) methods are being developed to screen larger chemical libraries. The primary objective of this work was to investigate for how many of the 52 chemicals with weight-of-evidence (WoE) determinations from EDSP Tier 1 screening there are available in vitro HTS data supporting a thyroid impact. HTS data from the USEPA ToxCast program and the EDSP WoE were collected for this analysis. Considering the complexity of endocrine disruption and interpreting HTS data, concordance between in vitro activity and in vivo effects ranges from 58 to 78%. Based on this evaluation, we conclude that the current suite of HTS assays is beneficial for prioritizing chemicals for further inquiry; however, without a more detailed analysis, one cannot conclude whether HTS results are the primary mode-of-action. Furthermore, development of in vitro assays for additional thyroid-relevant molecular initiating events is required to effectively predict in vivo thyroid impacts.

Exploring the potential of ToxCast™ data for mechanism-based prioritization of chemicals in regulatory context: Case study with priority existing chemicals (PECs) under K-REACH

Recent studies have highlighted the potential of ToxCast™ database to mechanism-based prioritization of chemicals. To explore the applicability of ToxCast data in the context of regulatory inventory chemicals, we screened 510 priority existing chemicals (PECs) regulated under the Act on the Registration and Evaluation of Chemical Substances (K-REACH) using ToxCast bioassays. In our analysis, a hit-call data matrix containing 298984 chemical-gene interactions was computed for 949 bioassays with the intended target genes, which enabled the identification of the putative toxicity mechanisms. Based on the reactivity to the chemicals, we analyzed 412 bioassays whose intended target gene families were cytochrome P450, oxidoreductase, transporter, nuclear receptor, steroid hormone, and DNA-binding. We also identified 141 chemicals based on their reactivity in the bioassays. These chemicals are mainly in consumer products including colorants, preservatives, air fresheners, and detergents. Our analysis revealed that in vitro bioactivities were involved in the relevant mechanisms inducing in vivo toxicity; however, this was not sufficient to predict more hazardous chemicals. Overall, the current results point to a potential and limitation in using ToxCast data for chemical prioritization in regulatory context in the absence of suitable in vivo data.

Impact of a megacity on the water quality of a tropical estuary assessed by a combination of chemical analysis and in-vitro bioassays

Tropical estuaries are threatened by rapid urbanization, which leads to the spread of thousands of micropollutants and poses an environmental risk to such sensitive aqueous ecosystems. In the present study, a combination of chemical and bioanalytical water characterization was applied to investigate the impact of Ho Chi Minh megacity (HCMC, 9.2 million inhabitants in 2021) on the Saigon River and its estuary and provide a comprehensive water quality assessment. Water samples were collected along a 140-km stretch integrating the river-estuary continuum from upstream HCMC down to the estuary mouth in the East Sea. Additional water samples were collected at the mouth of the four main canals of the city center. Chemical analysis was performed targeting up to 217 micropollutants (pharmaceuticals, plasticizers, PFASs, flame retardants, hormones, pesticides). Bioanalysis was performed using six in-vitro bioassays for hormone receptor-mediated effects, xenobiotic metabolism pathways and oxidative stress response, respectively, all accompanied by cytotoxicity measurement. A total of 120 micropollutants were detected and displayed high variability along the river continuum with total concentration ranging from 0.25 to 78 μg L^-1. Among them, 59 micropollutants were ubiquitous (detection frequency ≥ 80 %). An attenuation was observed in concentration and effect profiles towards the estuary. The urban canals were identified as major sources of micropollutants and bioactivity to the river, and one canal (Bến Nghé) exceeded the effect-based trigger values derived for estrogenicity and xenobiotic metabolism. Iceberg modelling apportioned the contribution of the quantified and the unknown chemicals to the measured effects. Diuron, metolachlor, chlorpyrifos, daidzein, genistein, climbazole, mebendazole and telmisartan were identified as main risk drivers of the oxidative stress response and xenobiotic metabolism pathway activation. Our study reinforced the need for improved wastewater management and deeper evaluations of the occurrence and fate of micropollutants in urbanized tropical estuarine environments.

Development, scrutiny, and modulation of transient reporter gene assays of the xenobiotic metabolism pathway in zebrafish hepatocytes

The "toxicology in the twenty-first century" paradigm shift demands the development of alternative in vitro test systems. Especially in the field of ecotoxicology, coverage of aquatic species-specific assays is relatively scarce. Transient reporter gene assays could be a quick, economical, and reliable bridging technology. However, the user should be aware of potential pitfalls that are influenced by reporter vector geometry. Here, we report the development of an AhR-responsive transient reporter-gene assay in the permanent zebrafish hepatocytes cell line (ZFL). Additionally, we disclose how viral, constitutive promoters within reporter-gene assay cassettes induce squelching of the primary signal. To counter this, we designed a novel normalization vector, bearing an endogenous zebrafish-derived genomic promoter (zfEF1aPro), which rescues the squelching-delimited system, thus, giving new insights into the modulation of transient reporter systems under xenobiotic stress. Finally, we uncovered how the ubiquitously used ligand BNF promiscuously activates multiple toxicity pathways of the xenobiotic metabolism and cellular stress response in an orchestral manner, presumably leading to a concentration-related inhibition of the AhR/ARNT/XRE-toxicity pathway and non-monotonous concentration-response curves. We named such a multi-level inhibitory mechanism that might mask effects as "maisonette squelching." A transient reporter gene assay in zebrafish cell lines utilizing endogenous regulatory gene elements shows increased in vitro toxicity testing performance. Synthetic and constitutive promotors interfere with signal transduction ("squelching") and might increase cellular stress (cytotoxicity). The squelching phenomenon might occur on multiple levels (toxicity pathway crosstalk and normalization vector), leading to a complete silencing of the reporter signal.

A single cell transcriptomic fingerprint of stressed premature, imbalanced differentiation of embryonic stem cells

Cultured naïve pluripotent ESC differentiate into first lineage, XEN or second lineage, formative pluripotency. Hyperosmotic stress (sorbitol), like retinoic acid, decreases naive pluripotency and increases XEN in two ESC lines, as reported by bulk and scRNAseq, analyzed by UMAP. Sorbitol overrides pluripotency in two ESC lines as reported by bulk and scRNAseq, analyzed by UMAP. UMAP analyzed the effects of 5 stimuli - three stressed (200-300mM sorbitol with leukemia inhibitory factor +LIF) and two unstressed (+LIF, normal stemness-NS and -LIF, normal differentiation-ND). Sorbitol and RA decrease naive pluripotency and increase subpopulations of 2-cell embryo-like and XEN sub-lineages; primitive, parietal, and visceral endoderm (VE). Between the naïve pluripotency and primitive endoderm clusters is a stress-induced cluster with transient intermediate cells with higher LIF receptor signaling, with increased Stat3, Klf4, and Tbx3 expression. Sorbitol, like RA, also suppresses formative pluripotency, increasing lineage imbalance. Although bulk RNAseq and gene ontology group analyses suggest that stress induces head organizer and placental markers, scRNAseq reveals few cells. But VE and placental markers/cells were in adjacent clusters, like recent reports. UMAPs show that dose-dependent stress overrides stemness to force premature lineage imbalance. Hyperosmotic stress induces lineage imbalance, and other toxicological stresses, like drugs with RA, may cause lineage imbalance, resulting in miscarriages or birth defects.

From vision toward best practices: Evaluating in vitro transcriptomic points of departure for application in risk assessment using a uniform workflow

The growing number of chemicals in the current consumer and industrial markets presents a major challenge for regulatory programs faced with the need to assess the potential risks they pose to human and ecological health. The increasing demand for hazard and risk assessment of chemicals currently exceeds the capacity to produce the toxicity data necessary for regulatory decision making, and the applied data is commonly generated using traditional approaches with animal models that have limited context in terms of human relevance. This scenario provides the opportunity to implement novel, more efficient strategies for risk assessment purposes. This study aims to increase confidence in the implementation of new approach methods in a risk assessment context by using a parallel analysis to identify data gaps in current experimental designs, reveal the limitations of common approaches deriving transcriptomic points of departure, and demonstrate the strengths in using high-throughput transcriptomics (HTTr) to derive practical endpoints. A uniform workflow was applied across six curated gene expression datasets from concentration-response studies containing 117 diverse chemicals, three cell types, and a range of exposure durations, to determine tPODs based on gene expression profiles. After benchmark concentration modeling, a range of approaches was used to determine consistent and reliable tPODs. High-throughput toxicokinetics were employed to translate in vitro tPODs (µM) to human-relevant administered equivalent doses (AEDs, mg/kg-bw/day). The tPODs from most chemicals had AEDs that were lower (i.e., more conservative) than apical PODs in the US EPA CompTox chemical dashboard, suggesting in vitro tPODs would be protective of potential effects on human health. An assessment of multiple data points for single chemicals revealed that longer exposure duration and varied cell culture systems (e.g., 3D vs. 2D) lead to a decreased tPOD value that indicated increased chemical potency. Seven chemicals were flagged as outliers when comparing the ratio of tPOD to traditional POD, thus indicating they require further assessment to better understand their hazard potential. Our findings build confidence in the use of tPODs but also reveal data gaps that must be addressed prior to their adoption to support risk assessment applications.

Advanced Methods for Natural Products Discovery: Bioactivity Screening, Dereplication, Metabolomics Profiling, Genomic Sequencing, Databases and Informatic Tools, and Structure Elucidation

Natural Products (NP) are essential for the discovery of novel drugs and products for numerous biotechnological applications. The NP discovery process is expensive and time-consuming, having as major hurdles dereplication (early identification of known compounds) and structure elucidation, particularly the determination of the absolute configuration of metabolites with stereogenic centers. This review comprehensively focuses on recent technological and instrumental advances, highlighting the development of methods that alleviate these obstacles, paving the way for accelerating NP discovery towards biotechnological applications. Herein, we emphasize the most innovative high-throughput tools and methods for advancing bioactivity screening, NP chemical analysis, dereplication, metabolite profiling, metabolomics, genome sequencing and/or genomics approaches, databases, bioinformatics, chemoinformatics, and three-dimensional NP structure elucidation.

Hazards of current concentration-setting practices in environmental toxicology studies

The setting of concentrations for testing substances in ecotoxicological studies is often based on fractions of the concentrations that cause 50% mortality (LC50 or LD50) rather than environmentally relevant levels. This practice can result in exposures to animals at test concentrations that are magnitudes of order greater than those experienced in the environment. Often, such unrealistically high concentrations may cause non-specific biochemical or morphologic changes that primarily reflect the near-lethal health condition of the animal subjects, as opposed to effects characteristic of the particular test compound. Meanwhile, it is recognized that for many chemicals, the toxicologic mode of action (MOA) responsible for lethality may differ entirely from the MOAs that cause various sublethal effects. One argument for employing excessively high exposure concentrations in sublethal studies is to ensure the generation of positive toxicological effects, which can then be used to establish safety thresholds; however, it is possible that the pressure to produce exposure-related effects may also contribute to false positive outcomes. The purpose of this paper is to explore issues involving some current usages of acute LC50 data in ecotoxicology testing, and to propose an alternative strategy for performing this type of research moving forward. Toward those ends, a brief literature survey was conducted to gain an appreciation of methods that are currently being used to set test concentrations for sublethal definitive studies.

Using membrane-water partition coefficients in a critical membrane burden approach to aid the identification of neutral and ionizable chemicals that induce acute toxicity below narcosis levels

The risk assessment of thousands of chemicals used in our society benefits from adequate grouping of chemicals based on the mode and mechanism of toxic action (MoA). We measure the phospholipid membrane-water distribution ratio (D_MLW) using a chromatographic assay (IAM-HPLC) for 121 neutral and ionized organic chemicals and screen other methods to derive D_MLW. We use IAM-HPLC based D_MLW as a chemical property to distinguish between baseline narcosis and specific MoA, for reported acute toxicity endpoints on two separate sets of chemicals. The first set comprised 94 chemicals of US EPA's acute fish toxicity database: 47 categorized as narcosis MoA, 27 with specific MoA, and 20 predominantly ionic chemicals with mostly unknown MoA. The narcosis MoA chemicals clustered around the median narcosis critical membrane burden (CMB_narc) of 140 mmol kg^-1 lipid, with a lower limit of 14 mmol kg^-1 lipid, including all chemicals labelled Narcosis_I and Narcosis_II. This maximum 'toxic ratio' (TR) between CMB_narc and the lower limit narcosis endpoint is thus 10. For 23/28 specific MoA chemicals a TR >10 was derived, indicative of a specific adverse effect pathway related to acute toxicity. For 10/12 cations categorized as "unsure amines", the TR <10 suggests that these affect fish via narcosis MoA. The second set comprised 29 herbicides, including 17 dissociated acids, and evaluated the TR for acute toxic effect concentrations to likely sensitive aquatic plant species (green algae and macrophytes Lemna and Myriophyllum), and non-target animal species (invertebrates and fish). For 21/29 herbicides, a TR >10 indicated a specific toxic mode of action other than narcosis for at least one of these aquatic primary producers. Fish and invertebrate TRs were mostly <10, particularly for neutral herbicides, but for acidic herbicides a TR >10 indicated specific adverse effects in non-target animals. The established critical membrane approach to derive the TR provides for useful contribution to the weight of evidence to bin a chemical as having a narcosis MoA or less likely to have acute toxicity caused by a more specific adverse effect pathway. After proper calibration, the chromatographic assay provides consistent and efficient experimental input for both neutral and ionizable chemicals to this approach.

Use of computational toxicology models to predict toxicological points of departure: A case study with triazine herbicides

BACKGROUND

Atrazine simazine and propazine, widely used triazine herbicides on food crops and in residential areas, disrupt the neuroendocrine system raising human health concerns. USEPA developed a PBPK model based on triazine common Mode of Action (MOA)-suppression of luteinizing hormone surge in female rats-to generate human regulatory points of departure (POD: mg/kg/day). We compared triazine Human Administered Equivalent Dose (AED_Human mg/kg/day) predictions from open access computational tools to the PBPK PODs to assess concordance.

METHODS

Computational tools were the following: ToxCast/Tox21 in vitro assays; Toxicogenomic databases to assess concordance with ToxCast/Tox21 targets; integrated chemical environment (ICE) models with ToxCast/Tox21 inputs to predict AED_Human PODs and population-based age-refined high throughput toxicokinetics (HTTK-Pop) to compare to age-related PBPK PODs.

RESULTS

ToxCast/Tox21 assays identified critical targets in the triazine common MOA and gene databases; ICE AED_Human predictions were mainly concordant with the USEPA PBPK PODs quantitatively. Low fold-differences between PBPK POD and ICE AED_Human predictions indicated that the ICE models are health-protective. HTTK-Pop age-refinements were within 10-fold of the USEPA PBPK PODs.

CONCLUSIONS

CompTox tools were used to identify assay targets in the MOA and identify potential molecular initiating targets in the adverse outcome pathway for potential use in risk assessment.

Reference compounds for characterizing cellular injury in high-content cellular morphology assays

Robust, generalizable approaches to identify compounds efficiently with undesirable mechanisms of action in complex cellular assays remain elusive. Such a process would be useful for hit triage during high-throughput screening and, ultimately, predictive toxicology during drug development. Here we generate cell painting and cellular health profiles for 218 prototypical cytotoxic and nuisance compounds in U-2 OS cells in a concentration-response format. A diversity of compounds that cause cellular damage produces bioactive cell painting morphologies, including cytoskeletal poisons, genotoxins, nonspecific electrophiles, and redox-active compounds. Further, we show that lower quality lysine acetyltransferase inhibitors and nonspecific electrophiles can be distinguished from more selective counterparts. We propose that the purposeful inclusion of cytotoxic and nuisance reference compounds such as those profiled in this resource will help with assay optimization and compound prioritization in complex cellular assays like cell painting.

In vitro transcriptomic analyses reveal pathway perturbations, estrogenic activities, and potencies of data-poor BPA alternative chemicals

Since initial regulatory action in 2010 in Canada, bisphenol A (BPA) has been progressively replaced by structurally related alternative chemicals. Unfortunately, many of these chemicals are data-poor, limiting toxicological risk assessment. We used high-throughput transcriptomics to evaluate potential hazards and compare potencies of BPA and 15 BPA alternative chemicals in cultured breast cancer cells. MCF-7 cells were exposed to BPA and 15 alternative chemicals (0.0005-100 µM) for 48 h. TempO-Seq (BioSpyder Inc) was used to examine global transcriptomic changes and estrogen receptor alpha (ERα)-associated transcriptional changes. Benchmark concentration (BMC) analysis was conducted to identify 2 global transcriptomic points of departure: (1) the lowest pathway median gene BMC and (2) the 25th lowest rank-ordered gene BMC. ERα activation was evaluated using a published transcriptomic biomarker and an ERα-specific transcriptomic point of departure was derived. Genes fitting BMC models were subjected to upstream regulator and canonical pathway analysis in Ingenuity Pathway Analysis. Biomarker analysis identified BPA and 8 alternative chemicals as ERα active. Global and ERα transcriptomic points of departure produced highly similar potency rankings with bisphenol AF as the most potent chemical tested, followed by BPA and bisphenol C. Further, BPA and transcriptionally active alternative chemicals enriched similar gene sets associated with increased cell division and cancer-related processes. These data provide support for future read-across applications of transcriptomic profiling for risk assessment of data-poor chemicals and suggest that several BPA alternative chemicals may cause hazards at similar concentrations to BPA.

In vitro bioanalytical assessment of the occurrence and removal of bioactive chemicals in municipal wastewater treatment plants in Korea

Effluents of wastewater treatment plants (WWTPs) contain various organic micropollutants, some of which can exert negative effects on the quality of receiving waters or drinking water sources. This study monitored two full-scale WWTPs in Korea for the occurrence and removal of bioactive chemicals for a one-year period using a battery of in vitro bioassays as a complementary approach to chemical analysis. Bioassays covering different endpoints were employed, such as hormone receptor activation (AR and ERα), xenobiotic metabolism (PAH and PXR), oxidative stress response (Nrf2), and cytotoxicity. The WWTP influents showed AR, ERα, and PAH activities at ng/L - μg/L and PXR and Nrf2 activities at μg/L - mg/L as bioanalytical equivalent concentrations of a reference compound for each bioassay. These bioactivities decreased along with the WWTP treatment train, with significant removals achieved by the secondary biological treatment processes. Cytotoxicity was observed only for some municipal wastewater (M-WWTP) influents but was below the limit of quantification for most cases. The influent and effluent bioactivities observed in this study were mostly comparable to those reported in other WWTPs in the literature. Comparison of the bioactivities with the effect-based trigger (EBT) values indicates that the impact of WWTP effluents on receiving water quality was low for most endpoints. For Nrf2, however, further investigation is required to evaluate the observed high bioactivities compared with the current EBT. The observed ERα activity could partly be explained by the presence of some steroid estrogens. Overall, our results contribute to an important database for the concentrations and removal efficiencies of bioactive chemicals in WWTPs and demonstrate bioassays as a useful tool for urban water quality monitoring.

Complementary biological and computational approaches identify distinct mechanisms of chlorpyrifos versus chlorpyrifos-oxon-induced dopaminergic neurotoxicity

Organophosphate (OP) pesticides are widely used in agriculture. While acute cholinergic toxicity has been extensively studied, chronic effects on other neurons are less understood. Here, we demonstrated that the OP pesticide chlorpyrifos (CPF) and its oxon metabolite are dopaminergic neurotoxicants in Caenorhabditis elegans. CPF treatment led to inhibition of mitochondrial complex II, II + III, and V in rat liver mitochondria, while CPF-oxon did not (complex II + III and IV inhibition observed only at high doses). While the effect on C. elegans cholinergic behavior was mostly reversible with toxicant washout, dopamine-associated deficits persisted, suggesting dopaminergic neurotoxicity was irreversible. CPF reduced the mitochondrial content in a dose-dependent manner and the fat modulatory genes cyp-35A2 and cyp-35A3 were found to have a key role in CPF neurotoxicity. These findings were consistent with in vitro effects of CPF and CPF-oxon on nuclear receptor signaling and fatty acid/steroid metabolism observed in ToxCast assays. Two-way hierarchical analysis revealed in vitro effects on estrogen receptor, pregnane X receptor, and peroxisome proliferator-activated receptor gamma pathways as well as neurotoxicity of CPF, malathion, and diazinon, whereas these effects were not detected in malaoxon and diazoxon. Taken together, our study suggests that mitochondrial toxicity and metabolic effects of CPF, but not CPF-oxon, have a key role of CPF neurotoxicity in the low-dose, chronic exposure. Further mechanistic studies are needed to examine mitochondria as a common target for all OP pesticide parent compounds, because this has important implications on cumulative pesticide risk assessment.

Integrating Physiologically Based Pharmacokinetic Modeling-Based Forward Dosimetry and in Vitro Bioassays to Improve the Risk Assessment of Organophosphate Esters on Human Health

The ability to accurately assess the health risks of contaminants is limited by the shortcomings of toxicological standards. Using organophosphate esters (OPEs) as an example, this study attempted to integrate physiologically based pharmacokinetic (PBPK)-based forward dosimetry and in vitro bioassays to assess the likelihood of contaminants inducing biological effects in humans. The total exposure level of OPEs for Chinese residents was 19.5 ± 8.71 ng/kg/day with inhalation being the main exposure pathway. Then, human PBPK models were developed for individual OPEs to predict their steady-state concentrations in human tissues, and the predicted median levels in blood were close to the measurements. The reference doses (RfDs) of OPEs based on in vitro bioassays were comparable to in vivo animal-derived RfDs, demonstrating the reliability of in vitro bioassays. Therefore, the likelihood of OPEs inducing bioactivities in humans (RQ_in-vitro) was calculated using in vitro toxicity data and OPE levels in human tissues. The RQ_in-vitros of tris(2-chloroisopropyl) phosphate, tris(1,3-dichloropropyl) phosphate, and triphenyl phosphate (7.68 × 10^-5-3.18 × 10^-3) were comparable to the risks assessed using traditional RfDs (5.22 × 10^-5-1.94 × 10^-3), indicating the credibility of the method proposed in this study. This study establishes a new framework to improve the health risk assessment of contaminants without sufficient toxicity data and minimize the need for animal experimentation.

Leveraging ToxCast data and protein sequence conservation to complement aquatic life criteria derivation

The USEPA's 1985 guidelines for the derivation of aquatic life criteria (ALC) are robust but data-intensive. For many chemicals, the extensive in vivo data sets required for ALC derivation are not available. Thus, alternative analyses and processes that can provide provisional values to guide states, tribes, and other stakeholders while data accumulate and more rigorous criteria are derived would be beneficial. The overarching purpose of this study was to assess the feasibility of using data from new approach methodologies (NAMs) like ToxCast to derive first-pass, provisional values to guide chemical prioritization and resource management as a complement to traditional ALC derivation. To address this goal, the study objectives were to (1) estimate chemical potency using data from NAMs for nine compounds with available aquatic benchmarks, (2) evaluate the utility of using NAM data to elucidate potential mechanisms of toxicity to guide problem formulation, and (3) determine the species relevance of toxicity pathways for compounds with clearly defined mechanisms of action as a means to evaluate whether minimum data requirements could potentially be waived when deriving a more formal ALC. Points of departure were derived from ToxCast data based on the fifth percentile of the distribution of activity concentration above cutoff values falling below the cytotoxic burst. Mechanistic inferences were made based on active target hits in ToxCast and, where applicable, assessed for taxonomic conservation using SeqAPASS. ToxCast-based point-of-departure aligned relatively closely (six of nine test chemicals within a factor of 10; eight of nine within a factor of 100) with aquatic benchmarks from the USEPA and US Department of Energy (DOE). Moreover, pathways of toxicity gleaned from NAM data were reflective of in vivo-based findings from the literature. These results, while preliminary, and based on a limited number of substances, support the potential application of NAM data to complement traditional ALC derivation approaches and prioritization. Integr Environ Assess Manag 2023;19:224-238. © 2022 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.

Establishment of a human cell-based in vitro battery to assess developmental neurotoxicity hazard of chemicals

Developmental neurotoxicity (DNT) is a major safety concern for all chemicals of the human exposome. However, DNT data from animal studies are available for only a small percentage of manufactured compounds. Test methods with a higher throughput than current regulatory guideline methods, and with improved human relevance are urgently needed. We therefore explored the feasibility of DNT hazard assessment based on new approach methods (NAMs). An in vitro battery (IVB) was assembled from ten individual NAMs that had been developed during the past years to probe effects of chemicals on various fundamental neurodevelopmental processes. All assays used human neural cells at different developmental stages. This allowed us to assess disturbances of: (i) proliferation of neural progenitor cells (NPC); (ii) migration of neural crest cells, radial glia cells, neurons and oligodendrocytes; (iii) differentiation of NPC into neurons and oligodendrocytes; and (iv) neurite outgrowth of peripheral and central neurons. In parallel, cytotoxicity measures were obtained. The feasibility of concentration-dependent screening and of a reliable biostatistical processing of the complex multi-dimensional data was explored with a set of 120 test compounds, containing subsets of pre-defined positive and negative DNT compounds. The battery provided alerts (hit or borderline) for 24 of 28 known toxicants (82% sensitivity), and for none of the 17 negative controls. Based on the results from this screen project, strategies were developed on how IVB data may be used in the context of risk assessment scenarios employing integrated approaches for testing and assessment (IATA).

Predicting Endocrine Disruption Using Conformal Prediction - A Prioritization Strategy to Identify Hazardous Chemicals with Confidence

Receptor-mediated molecular initiating events (MIEs) and their relevance in endocrine activity (EA) have been highlighted in literature. More than 15 receptors have been associated with neurodevelopmental adversity and metabolic disruption. MIEs describe chemical interactions with defined biological outcomes, a relationship that could be described with quantitative structure-activity relationship (QSAR) models. QSAR uncertainty can be assessed using the conformal prediction (CP) framework, which provides similarity (i.e., nonconformity) scores relative to the defined classes per prediction. CP calibration can indirectly mitigate data imbalance during model development, and the nonconformity scores serve as intrinsic measures of chemical applicability domain assessment during screening. The focus of this work was to propose an in silico predictive strategy for EA. First, 23 QSAR models for MIEs associated with EA were developed using high-throughput data for 14 receptors. To handle the data imbalance, five protocols were compared, and CP provided the most balanced class definition. Second, the developed QSAR models were applied to a large data set (∼55,000 chemicals), comprising chemicals representative of potential risk for human exposure. Using CP, it was possible to assess the uncertainty of the screening results and identify model strengths and out of domain chemicals. Last, two clustering methods, t-distributed stochastic neighbor embedding and Tanimoto similarity, were used to identify compounds with potential EA using known endocrine disruptors as reference. The cluster overlap between methods produced 23 chemicals with suspected or demonstrated EA potential. The presented models could be utilized for first-tier screening and identification of compounds with potential biological activity across the studied MIEs.

Effects of Class Imbalance and Data Scarcity on the Performance of Binary Classification Machine Learning Models Developed Based on ToxCast/Tox21 Assay Data

The development of toxicity classification models using the ToxCast database has been extensively studied. Machine learning approaches are effective in identifying the bioactivity of untested chemicals. However, ToxCast assays differ in the amount of data and degree of class imbalance (CI). Therefore, the resampling algorithm employed should vary depending on the data distribution to achieve optimal classification performance. In this study, the effects of CI and data scarcity (DS) on the performance of binary classification models were investigated using ToxCast bioassay data. An assay matrix based on CI and DS was prepared for 335 assays with biologically intended target information, and 28 CI assays and 3 DS assays were selected. Thirty models established by combining five molecular fingerprints (i.e., Morgan, MACCS, RDKit, Pattern, and Layered) and six algorithms [i.e., gradient boosting tree, random forest (RF), multi-layered perceptron, k-nearest neighbor, logistic regression, and naive Bayes] were trained using the selected assay data set. Of the 30 trained models, MACCS-RF showed the best performance and thus was selected for analyses of the effects of CI and DS. Results showed that recall and F1 were significantly lower when training with the CI assays than with the DS assays. In addition, hyperparameter tuning of the RF algorithm significantly improved F1 on CI assays. This study provided a basis for developing a toxicity classification model with improved performance by evaluating the effects of data set characteristics. This study also emphasized the importance of using appropriate evaluation metrics and tuning hyperparameters in model development.

Characterizing Variability and Uncertainty Associated with Transcriptomic Dose-Response Modeling

Transcriptomics dose-response analysis (TDRA) has emerged as a promising approach for integrating toxicogenomics data into a risk assessment context; however, variability and uncertainty associated with experimental design are not well understood. Here, we evaluated n = 55 RNA-seq profiles derived from Japanese quail liver tissue following exposure to chlorpyrifos (0, 0.04, 0.1, 0.2, 0.4, 1, 2, 4, 10, 20, and 40 μg/g; n = 5 replicates per group) via egg injection. The full dataset was subsampled 637 times to generate smaller datasets with different dose ranges and spacing (designs A-E) and number of replicates (n = 2-5). TDRA of the 637 datasets revealed substantial variability in the gene and pathway benchmark doses, but relative stability in overall transcriptomic point-of-departure (tPOD) values when tPODs were calculated with the "pathway" and "mode" methods. Further, we found that tPOD values were more dependent on the dose range and spacing than on the number of replicates, suggesting that optimal experimental designs should use fewer replicates (n = 2 or 3) and more dose groups to reduce uncertainty in the results. Finally, tPOD values ranged by over ten times for all surveyed experimental designs and tPOD types, suggesting that tPODs should be interpreted as order-of-magnitude estimates.

Application of ToxCast/Tox21 data for toxicity mechanism-based evaluation and prioritization of environmental chemicals: Perspective and limitations

In response to the need to minimize the use of experimental animals, new approach methodologies (NAMs) using advanced technology have emerged in the 21st century. ToxCast/Tox21 aims to evaluate the adverse effects of chemicals quickly and efficiently using a high-throughput screening and to transform the paradigm of toxicity assessment into mechanism-based toxicity prediction. The ToxCast/Tox21 database, which contains extensive data from over 1400 assays with numerous biological targets and activity data for over 9000 chemicals, can be used for various purposes in the field of chemical prioritization and toxicity prediction. In this study, an overview of the database was explored to aid mechanism-based chemical prioritization and toxicity prediction. Implications for the utilization of the ToxCast/Tox21 database in chemical prioritization and toxicity prediction were derived. The research trends in ToxCast/Tox21 assay data were reviewed in the context of toxicity mechanism identification, chemical priority, environmental monitoring, assay development, and toxicity prediction. Finally, the potential applications and limitations of using ToxCast/Tox21 assay data in chemical risk assessment were discussed. The analysis of the toxicity mechanism-based assays of ToxCast/Tox21 will help in chemical prioritization and regulatory applications without the use of laboratory animals.

In vitro evaluation of the inhalation toxicity of the cosmetic ingredient aluminum chlorohydrate

Aluminum chlorohydrate (ACH) is a major aerosol component frequently used as the active ingredient in antiperspirants, and in vivo studies have raised a concern about its inhalation toxicity. Still, few studies have addressed its effects on the human respiratory tract. Therefore, we developed a study on ACH inhalation toxicity using an in vitro human alveolar cell model (A549 cells) with molecular and cellular markers of oxidative stress, immunotoxicity, and epigenetic changes. The chemical characterization of ACH suspensions indicated particle instability and aggregation; however, side-scatter analysis demonstrated significant particle uptake in cells exposed to ACH. Exposure of A549 cells to non-cytotoxic concentrations of ACH (0.25, 0.5, and 1 mg/ml) showed that ACH induced reactive oxygen species. Moreover, ACH upregulated TNF, IL6, IL8, and IL1A genes, but not the lncRNAs NEAT1 and MALAT1. Finally, no alterations on the global DNA methylation pattern (5-methylcytosine and 5-hydroxymethylcytosine) or the phosphorylation of histone H2AX (γ-H2AX) were observed. Our data suggest that ACH may induce oxidative stress and inflammation on alveolar cells, and A549 cells may be useful to identify cellular and molecular events that may be associated with adverse effects on the lungs. Still, further research is needed to ensure the inhalation safety of ACH.

Optimisation of an automated high-throughput micronucleus (HiTMiN) assay to measure genotoxicity of environmental contaminants

Anthropogenic contaminants can have a variety of adverse effects on exposed organisms, including genotoxicity in the form of DNA damage. One of the most commonly used methods to evaluate genotoxicity in exposed organisms is the micronucleus (MN) assay. It provides an efficient assessment of chromosomal impairment due to either chromosomal rupture or mis-segregation during mitosis. However, evaluating chromosomal damage in the MN assay through manual microscopy is a highly time-consuming and somewhat subjective process. High-throughput evaluation with automated image analysis could reduce subjectivity and increase accuracy and throughput. In this study, we optimised and streamlined the HiTMiN assay, adapting the MN assay to a miniaturised, 96-well plate format with reduced steps, and applied it to both primary cells from green turtle fibroblasts (GT12s-p) and a freshwater fish hepatoma cell line (PLHC-1). Image analysis using both commercial (Columbus) and freely available (CellProfiler) software automated the scoring of MN, with improved precision and drastically reduced time compared to manual scoring and other available protocols. The assay was validated through exposure to two inorganic (chromium and cobalt) and one organic (the herbicide metolachlor) compounds, which are genotoxicants of concern in the marine environment. All compounds tested induced MN formation below cytotoxic concentrations. The HiTMiN assay presented here greatly increases the suitability of the MN assay as a quick, affordable, sensitive and accurate assay to measure genotoxicity of environmental samples in different cell lines.

Chemical and biological assessments of environmental mixtures: A review of current trends, advances, and future perspectives

Considering the chemical complexity and toxicity data gaps of environmental mixtures, most studies evaluate the chemical risk individually. However, humans are usually exposed to a cocktail of chemicals in real life. Mixture health assessment remains to be a research area having significant knowledge gaps. Characterization of chemical composition and bioactivity/toxicity are the two critical aspects of mixture health assessments. This review seeks to introduce the recent progress and tools for the chemical and biological characterization of environmental mixtures. The state-of-the-art techniques include the sampling, extraction, rapid detection methods, and the in vitro, in vivo, and in silico approaches to generate the toxicity data of an environmental mixture. Application of these novel methods, or new approach methodologies (NAMs), has increased the throughput of generating chemical and toxicity data for mixtures and thus refined the mixture health assessment. Combined with computational methods, the chemical and biological information would shed light on identifying the bioactive/toxic components in an environmental mixture.

IVIVE: Facilitating the Use of In Vitro Toxicity Data in Risk Assessment and Decision Making

During the past few decades, the science of toxicology has been undergoing a transformation from observational to predictive science. New approach methodologies (NAMs), including in vitro assays, in silico models, read-across, and in vitro to in vivo extrapolation (IVIVE), are being developed to reduce, refine, or replace whole animal testing, encouraging the judicious use of time and resources. Some of these methods have advanced past the exploratory research stage and are beginning to gain acceptance for the risk assessment of chemicals. A review of the recent literature reveals a burst of IVIVE publications over the past decade. In this review, we propose operational definitions for IVIVE, present literature examples for several common toxicity endpoints, and highlight their implications in decision-making processes across various federal agencies, as well as international organizations, including those in the European Union (EU). The current challenges and future needs are also summarized for IVIVE. In addition to refining and reducing the number of animals in traditional toxicity testing protocols and being used for prioritizing chemical testing, the goal to use IVIVE to facilitate the replacement of animal models can be achieved through their continued evolution and development, including a strategic plan to qualify IVIVE methods for regulatory acceptance.

On the Utility of ToxCast-Based Predictive Models to Evaluate Potential Metabolic Disruption by Environmental Chemicals

BACKGROUND

Research suggests environmental contaminants can impact metabolic health; however, high costs prohibit in vivo screening of putative metabolic disruptors. High-throughput screening programs, such as ToxCast, hold promise to reduce testing gaps and prioritize higher-order (in vivo) testing.

OBJECTIVES

We sought to a) examine the concordance of in vitro testing in 3T3-L1 cells to a targeted literature review for 38 semivolatile environmental chemicals, and b) assess the predictive utility of various expert models using ToxCast data against the set of 38 reference chemicals.

METHODS

Using a set of 38 chemicals with previously published results in 3T3-L1 cells, we performed a metabolism-targeted literature review to determine consensus activity determinations. To assess ToxCast predictive utility, we used two published ToxPi models: a) the 8-Slice model published by Janesick et al. (2016) and b) the 5-Slice model published by Auerbach et al. (2016). We examined the performance of the two models against the Janesick in vitro results and our own 38-chemical reference set. We further evaluated the predictive performance of various modifications to these models using cytotoxicity filtering approaches and validated our best-performing model with new chemical testing in 3T3-L1 cells.

RESULTS

The literature review revealed relevant publications for 30 out of the 38 chemicals (the remaining 8 chemicals were only examined in our previous 3T3-L1 testing). We observed a balanced accuracy (average of sensitivity and specificity) of 0.86 comparing our previous in vitro results to the literature-derived calls. ToxPi models provided balanced accuracies ranging from 0.55 to 0.88, depending on the model specifications and reference set. Validation chemical testing correctly predicted 29 of 30 chemicals as per 3T3-L1 testing, suggesting good adipogenic prediction performance for our best adapted model.

DISCUSSION

Using the most recent ToxCast data and an updated ToxPi model, we found ToxCast performed similarly to that of our own 3T3-L1 testing in predicting consensus calls. Furthermore, we provide the full ranked list of largely untested chemicals with ToxPi scores that predict adipogenic activity and that require further investigation. https://doi.org/10.1289/EHP6779.

Current status and future directions for a neurotoxicity hazard assessment framework that integrates in silico approaches

Neurotoxicology is the study of adverse effects on the structure or function of the developing or mature adult nervous system following exposure to chemical, biological, or physical agents. The development of more informative alternative methods to assess developmental (DNT) and adult (NT) neurotoxicity induced by xenobiotics is critically needed. The use of such alternative methods including in silico approaches that predict DNT or NT from chemical structure (e.g., statistical-based and expert rule-based systems) is ideally based on a comprehensive understanding of the relevant biological mechanisms. This paper discusses known mechanisms alongside the current state of the art in DNT/NT testing. In silico approaches available today that support the assessment of neurotoxicity based on knowledge of chemical structure are reviewed, and a conceptual framework for the integration of in silico methods with experimental information is presented. Establishing this framework is essential for the development of protocols, namely standardized approaches, to ensure that assessments of NT and DNT based on chemical structures are generated in a transparent, consistent, and defendable manner.

Towards regulation of Endocrine Disrupting chemicals (EDCs) in water resources using bioassays - A guide to developing a testing strategy

Endocrine disrupting chemicals (EDCs) are found in every environmental medium and are chemically diverse. Their presence in water resources can negatively impact the health of both human and wildlife. Currently, there are no mandatory screening mandates or regulations for EDC levels in complex water samples globally. Bioassays, which allow quantifying in vivo or in vitro biological effects of chemicals are used commonly to assess acute toxicity in water. The existing OECD framework to identify single-compound EDCs offers a set of bioassays that are validated for the Estrogen-, Androgen-, and Thyroid hormones, and for Steroidogenesis pathways (EATS). In this review, we discussed bioassays that could be potentially used to screen EDCs in water resources, including in vivo and in vitro bioassays using invertebrates, fish, amphibians, and/or mammalians species. Strengths and weaknesses of samples preparation for complex water samples are discussed. We also review how to calculate the Effect-Based Trigger values, which could serve as thresholds to determine if a given water sample poses a risk based on existing quality standards. This work aims to assist governments and regulatory agencies in developing a testing strategy towards regulation of EDCs in water resources worldwide. The main recommendations include 1) opting for internationally validated cell reporter in vitro bioassays to reduce animal use & cost; 2) testing for cell viability (a critical parameter) when using in vitro bioassays; and 3) evaluating the recovery of the water sample preparation method selected. This review also highlights future research avenues for the EDC screening revolution (e.g., 3D tissue culture, transgenic animals, OMICs, and Adverse Outcome Pathways (AOPs)).

Latent Variables Capture Pathway-Level Points of Departure in High-Throughput Toxicogenomic Data

Estimation of points of departure (PoDs) from high-throughput transcriptomic data (HTTr) represents a key step in the development of next-generation risk assessment (NGRA). Current approaches mainly rely on single key gene targets, which are constrained by the information currently available in the knowledge base and make interpretation challenging as scientists need to interpret PoDs for thousands of genes or hundreds of pathways. In this work, we aimed to address these issues by developing a computational workflow to investigate the pathway concentration–response relationships in a way that is not fully constrained by known biology and also facilitates interpretation. We employed the Pathway-Level Information ExtractoR (PLIER) to identify latent variables (LVs) describing biological activity and then investigated in vitro LVs’ concentration–response relationships using the ToxCast pipeline. We applied this methodology to a published transcriptomic concentration–response data set for 44 chemicals in MCF-7 cells and showed that our workflow can capture known biological activity and discriminate between estrogenic and antiestrogenic compounds as well as activity not aligning with the existing knowledge base, which may be relevant in a risk assessment scenario. Moreover, we were able to identify the known estrogen activity in compounds that are not well-established ER agonists/antagonists supporting the use of the workflow in read-across. Next, we transferred its application to chemical compounds tested in HepG2, HepaRG, and MCF-7 cells and showed that PoD estimates are in strong agreement with those estimated using a recently developed Bayesian approach (cor = 0.89) and in weak agreement with those estimated using a well-established approach such as BMDExpress2 (cor = 0.57). These results demonstrate the effectiveness of using PLIER in a concentration–response scenario to investigate pathway activity in a way that is not fully constrained by the knowledge base and to ease the biological interpretation and support the development of an NGRA framework with the ability to improve current risk assessment strategies for chemicals using new approach methodologies.

Mapping Mechanistic Pathways of Acute Oral Systemic Toxicity Using Chemical Structure and Bioactivity Measurements

Regulatory agencies around the world have committed to reducing or eliminating animal testing for establishing chemical safety. Adverse outcome pathways can facilitate replacement by providing a mechanistic framework for identifying the appropriate non-animal methods and connecting them to apical adverse outcomes. This study separated 11,992 chemicals with curated rat oral acute toxicity information into clusters of structurally similar compounds. Each cluster was then assigned one or more ToxCast/Tox21 assays by looking for the minimum number of assays required to record at least one positive hit call below cytotoxicity for all acutely toxic chemicals in the cluster. When structural information is used to select assays for testing, none of the chemicals required more than four assays and 98% required two assays or less. Both the structure-based clusters and activity from the associated assays were significantly associated with the GHS toxicity classification of the chemicals, which suggests that a combination of bioactivity and structural information could be as reproducible as traditional in vivo studies. Predictivity is improved when the in vitro assay directly corresponds to the mechanism of toxicity, but many indirect assays showed promise as well. Given the lower cost of in vitro testing, a small assay battery including both general cytotoxicity assays and two or more orthogonal assays targeting the toxicological mechanism could be used to improve performance further. This approach illustrates the promise of combining existing in silico approaches, such as the Collaborative Acute Toxicity Modeling Suite (CATMoS), with structure-based bioactivity information as part of an efficient tiered testing strategy that can reduce or eliminate animal testing for acute oral toxicity.

Grouping of chemicals into mode of action classes by automated effect pattern analysis using the zebrafish embryo toxicity test

A central element of high throughput screens for chemical effect assessment using zebrafish is the assessment and quantification of phenotypic changes. By application of an automated and more unbiased analysis of these changes using image analysis, patterns of phenotypes may be associated with the mode of action (MoA) of the exposure chemical. The aim of our study was to explore to what extent compounds can be grouped according to their anticipated toxicological or pharmacological mode of action using an automated quantitative multi-endpoint zebrafish test. Chemical-response signatures for 30 endpoints, covering phenotypic and functional features, were generated for 25 chemicals assigned to 8 broad MoA classes. Unsupervised clustering of the profiling data demonstrated that chemicals were partially grouped by their main MoA. Analysis with a supervised clustering technique such as a partial least squares discriminant analysis (PLS-DA) allowed to identify markers with a strong potential to discriminate between MoAs such as mandibular arch malformation observed for compounds interfering with retinoic acid signaling. The capacity for discriminating MoAs was also benchmarked to an available battery of in vitro toxicity data obtained from ToxCast library indicating a partially similar performance. Further, we discussed to which extent the collected dataset indicated indeed differences for compounds with presumably similar MoA or whether other factors such as toxicokinetic differences could have an important impact on the determined response patterns.

Assessing Fish Immunotoxicity by Means of In Vitro Assays: Are We There Yet?

There is growing awareness that a range of environmental chemicals target the immune system of fish and may compromise the resistance towards infectious pathogens. Existing concepts to assess chemical hazards to fish, however, do not consider immunotoxicity. Over recent years, the application of in vitro assays for ecotoxicological hazard assessment has gained momentum, what leads to the question whether in vitro assays using piscine immune cells might be suitable to evaluate immunotoxic potentials of environmental chemicals to fish. In vitro systems using primary immune cells or immune cells lines have been established from a wide array of fish species and basically from all immune tissues, and in principal these assays should be able to detect chemical impacts on diverse immune functions. In fact, in vitro assays were found to be a valuable tool in investigating the mechanisms and modes of action through which environmental agents interfere with immune cell functions. However, at the current state of knowledge the usefulness of these assays for immunotoxicity screening in the context of chemical hazard assessment appears questionable. This is mainly due to a lack of assay standardization, and an insufficient knowledge of assay performance with respect to false positive or false negative signals for the different toxicant groups and different immune functions. Also the predictivity of the in vitro immunotoxicity assays for the in vivo immunotoxic response of fishes is uncertain. In conclusion, the currently available database is too limited to support the routine application of piscine in vitro assays as screening tool for assessing immunotoxic potentials of environmental chemicals to fish.