Predictive endocrine testing in the 21st century using in vitro assays of estrogen receptor signaling responses

Occurrence and distribution of trisiloxane ethoxylates in citrus orchard soils in China: Analytical challenges

Trisiloxane ethoxylates (TSEOn) are widely used as agricultural surfactants due to their significant synergism with the active ingredients of pesticides, generally, including three typical end groups which are hydroxyl (TSEOn-H), methoxy (TSEOn-CH3), and acetoxy (TSEOn-COCH3), respectively. However, the potential ecotoxicological and endocrine-disrupting risks of TSEOn congeners have recently attracted ever-growing concern. Above all, there is limited research on the concentration levels of TSEOn in agroecosystems. This study, simultaneous analysis of 39 TSEOn oligomers in citrus orchard soils in China was implemented by the modified QuEChERS (quick, easy, cheap, effective, rugged, and safe) extraction coupled with ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). The method detection limits (MDLs) and the method quantification limits (MQLs) for TSEOn were 0.003-0.07 μg/kg and 0.01-0.20 μg/kg, respectively. The recoveries for TSEOn oligomers in soils ranged from 81 % ∼ 106 % with related standard deviations (RSDs) < 7 %. This newly developed UPLC-MS/MS method with high sensitivity and stability allows us to successfully trace the occurrence of TSEOn congeners in the citrus orchard soils from 3 provinces and 1 municipality in China. The detected concentrations of TSEOn-H oligomers in the sampled soils ranged from 0.02 to 0.288 μg/kg (dry weight). The congener profiles of TSEOn-H were dominated by TSEOn-H (n = 6- 8) in the soils. Additionally, the total concentrations of TSEOn-H congeners (ΣTSEOn-H) in the soils were in the range of 0.03 to 1.49 μg/kg. A comparison of ΣTSEOn-H distribution among the different citrus orchard soils indicated a higher level of ΣTSEOn-H in the soil samples collected from Zhejiang Province. Notably, TSEOn-CH3 or TSEOn-COCH3 oligomers were not detected in the tested soils. To the best of our knowledge, this is the first report on the occurrence and distribution of TSEOn congeners in agricultural soils.

Trisiloxane Surfactants Negatively Affect Reproductive Behaviors and Enhance Viral Replication in Honey Bees

Trisiloxane surfactants are often applied in formulated adjuvant products to blooming crops, including almonds, exposing the managed honey bees (Apis mellifera) used for pollination of these crops and persisting in colony matrices, such as bee bread. Despite this, little is known regarding the effects of trisiloxane surfactants on important aspects of colony health, such as reproduction. In the present study, we use laboratory assays to examine how exposure to field-relevant concentrations of three trisiloxane surfactants found in commonly used adjuvant formulations affect queen oviposition rates, worker interactions with the queen, and worker susceptibility to endogenous viral pathogens. Trisiloxane surfactants were administered at 5 mg/kg in pollen supplement diet for 14 days. No effects on worker behavior or physiology could be detected, but our results demonstrate that hydroxy-capped trisiloxane surfactants can negatively affect queen oviposition and methyl-capped trisiloxane surfactants cause increased replication of Deformed Wing Virus in workers, suggesting that trisiloxane surfactant use while honey bees are foraging may negatively impact colony longevity and growth. Environ Toxicol Chem 2024;43:222-233. © 2023 SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Identification of nonmonotonic concentration-responses in Tox21 high-throughput screening estrogen receptor assays

Environmental endocrine-disrupting chemicals (EDCs) interfere with the metabolism and actions of endogenous hormones. It has been well documented in numerous in vivo and in vitro studies that EDCs can exhibit nonmonotonic dose response (NMDR) behaviors. Not conforming to the conventional linear or linear-no-threshold response paradigm, these NMDR relationships pose practical challenges to the risk assessment of EDCs. In the meantime, the endocrine signaling pathways and biological mechanisms underpinning NMDR remain incompletely understood. The US Tox21 program has conducted in vitro cell-based high-throughput screening assays for estrogen receptors (ER), androgen receptors, and other nuclear receptors, and screened the 10 K-compound library for potential endocrine activities. Using 15 concentrations across several orders of magnitude of concentration range and run in both agonist and antagonist modes, these Tox21 assay datasets contain valuable quantitative information that can be explored to evaluate the nonlinear effects of EDCs and may infer potential mechanisms. In this study we analyzed the concentration-response curves (CRCs) in all 8 Tox21 ERα and ERβ assays by developing clustering and classification algorithms customized to the datasets to identify various shapes of CRCs. After excluding NMDR curves likely caused by cytotoxicity, luciferase inhibition, or autofluorescence, hundreds of compounds were identified to exhibit Bell or U-shaped CRCs. Bell-shaped CRCs are about 7 times more frequent than U-shaped ones in the Tox21 ER assays. Many compounds exhibit NMDR in at least one assay, and some EDCs well-known for their NMDRs in the literature were also identified, suggesting their nonmonotonic effects may originate at cellular levels involving transcriptional ER signaling. The developed computational methods for NMDR identification in ER assays can be adapted and applied to other high-throughput bioassays.

A plea for the integration of Green Toxicology in sustainable bioeconomy strategies - Biosurfactants and microgel-based pesticide release systems as examples

A key aspect of the transformation of the economic sector towards a sustainable bioeconomy is the development of environmentally friendly alternatives for hitherto used chemicals, which have negative impacts on environmental health. However, the implementation of an ecotoxicological hazard assessment at early steps of product development to elaborate the most promising candidates of lowest harm is scarce in industry practice. The present article introduces the interdisciplinary proof-of-concept project GreenToxiConomy, which shows the successful application of a Green Toxicology strategy for biosurfactants and a novel microgel-based pesticide release system. Both groups are promising candidates for industrial and agricultural applications and the ecotoxicological characterization is yet missing important information. An iterative substance- and application-oriented bioassay battery for acute and mechanism-specific toxicity within aquatic and terrestrial model species is introduced for both potentially hazardous materials getting into contact with humans and ending up in the environment. By applying in silico QSAR-based models on genotoxicity, endocrine disruption, skin sensitization and acute toxicity to algae, daphnids and fish, individual biosurfactants resulted in deviating toxicity, suggesting a pre-ranking of the compounds. Experimental toxicity assessment will further complement the predicted toxicity to elaborate the most promising candidates in an efficient pre-screening of new substances.

A novel chemo-phenotypic method identifies mixtures of salpn, vitamin D3, and pesticides involved in the development of colorectal and pancreatic cancer

Environmental chemical (EC) exposures and our interactions with them has significantly increased in the recent decades. Toxicity associated biological characterization of these chemicals is challenging and inefficient, even with available high-throughput technologies. In this report, we describe a novel computational method for characterizing toxicity, associated biological perturbations and disease outcome, called the Chemo-Phenotypic Based Toxicity Measurement (CPTM). CPTM is used to quantify the EC "toxicity score" (Z_ts), which serves as a holistic metric of potential toxicity and disease outcome. CPTM quantitative toxicity is the measure of chemical features, biological phenotypic effects, and toxicokinetic properties of the ECs. For proof-of-concept, we subject ECs obtained from the Environmental Protection Agency's (EPA) database to the CPTM. We validated the CPTM toxicity predictions by correlating 'Z_ts' scores with known toxicity effects. We also confirmed the CPTM predictions with in-vitro, and in-vivo experiments. In in-vitro and zebrafish models, we showed that, mixtures of the motor oil and food additive 'Salpn' with endogenous nuclear receptor ligands such as Vitamin D3, dysregulated the nuclear receptors and key transcription pathways involved in Colorectal Cancer. Further, in a human patient derived cell organoid model, we found that a mixture of the widely used pesticides 'Tetramethrin' and 'Fenpropathrin' significantly impacts the population of patient derived pancreatic cancer cells and 3D organoid models to support rapid PDAC disease progression. The CPTM method is, to our knowledge, the first comprehensive toxico-physicochemical, and phenotypic bionetwork-based platform for efficient high-throughput screening of environmental chemical toxicity, mechanisms of action, and connection to disease outcomes.

Quality Control for Single Cell Imaging Analytics Using Endocrine Disruptor-Induced Changes in Estrogen Receptor Expression

BACKGROUND

Diverse toxicants and mixtures that affect hormone responsive cells [endocrine disrupting chemicals (EDCs)] are highly pervasive in the environment and are directly linked to human disease. They often target the nuclear receptor family of transcription factors modulating their levels and activity. Many high-throughput assays have been developed to query such toxicants; however, single-cell analysis of EDC effects on endogenous receptors has been missing, in part due to the lack of quality control metrics to reproducibly measure cell-to-cell variability in responses.

OBJECTIVE

We began by developing single-cell imaging and informatic workflows to query whether the single cell distribution of the estrogen receptor-α (ER), used as a model system, can be used to measure effects of EDCs in a sensitive and reproducible manner.

METHODS

We used high-throughput microscopy, coupled with image analytics to measure changes in single cell ER nuclear levels on treatment with ∼100 toxicants, over a large number of biological and technical replicates.

RESULTS

We developed a two-tiered quality control pipeline for single cell analysis and tested it against a large set of biological replicates, and toxicants from the EPA and Agency for Toxic Substances and Disease Registry lists. We also identified a subset of potentially novel EDCs that were active only on the endogenous ER level and activity as measured by single molecule RNA fluorescence in situ hybridization (RNA FISH).

DISCUSSION

We demonstrated that the distribution of ER levels per cell, and the changes upon chemical challenges were remarkably stable features; and importantly, these features could be used for quality control and identification of endocrine disruptor toxicants with high sensitivity. When coupled with orthogonal assays, ER single cell distribution is a valuable resource for high-throughput screening of environmental toxicants. https://doi.org/10.1289/EHP9297.

A Genome-Edited ERα-HiBiT Fusion Reporter Cell Line for the Identification of ERα Modulators Via High-Throughput Screening and CETSA

The estrogen receptor α (ERα) is a target of intense pharmacological intervention and toxicological biomonitoring. Current methods to directly quantify cellular levels of ERα involve antibody-based assays, which are labor-intensive and of limited throughput. In this study, we generated a post-translational reporter cell line, referred to as MCF7-ERα-HiBiT, by fusing a small pro-luminescent nanoluciferase (NLuc) tag (HiBiT) to the C-terminus of endogenous ERα in MCF7 cells. The tag allows the luminescent detection and quantification of endogenous ERα protein by addition of the complementary NLuc enzyme fragment. This MCF7-ERα-HiBiT cell line was optimized for quantitative high-throughput screening (qHTS) to identify compounds that reduce ERα levels. In addition, the same cell line was optimized for a qHTS cellular thermal shift assay to identify compounds that bind and thermally stabilize ERα. Here, we interrogated the MCF7-ERα-HiBiT assay against the NCATS Pharmacological Collection (NPC) of 2,678 approved drugs and identified compounds that potently reduce and thermally stabilize ERα. Our novel post-translational reporter cell line provides a unique opportunity for profiling large pharmacological and toxicological compound libraries for their effect on ERα levels as well as for assessing direct compound binding to the receptor, thus facilitating mechanistic studies by which compounds exert their biological effects on ERα.

Machine Learning: New Ideas and Tools in Environmental Science and Engineering

The rapid increase in both the quantity and complexity of data that are being generated daily in the field of environmental science and engineering (ESE) demands accompanied advancement in data analytics. Advanced data analysis approaches, such as machine learning (ML), have become indispensable tools for revealing hidden patterns or deducing correlations for which conventional analytical methods face limitations or challenges. However, ML concepts and practices have not been widely utilized by researchers in ESE. This feature explores the potential of ML to revolutionize data analysis and modeling in the ESE field, and covers the essential knowledge needed for such applications. First, we use five examples to illustrate how ML addresses complex ESE problems. We then summarize four major types of applications of ML in ESE: making predictions; extracting feature importance; detecting anomalies; and discovering new materials or chemicals. Next, we introduce the essential knowledge required and current shortcomings in ML applications in ESE, with a focus on three important but often overlooked components when applying ML: correct model development, proper model interpretation, and sound applicability analysis. Finally, we discuss challenges and future opportunities in the application of ML tools in ESE to highlight the potential of ML in this field.

SepPCNET: Deeping Learning on a 3D Surface Electrostatic Potential Point Cloud for Enhanced Toxicity Classification and Its Application to Suspected Environmental Estrogens

Deep learning (DL) offers an unprecedented opportunity to revolutionize the landscape of toxicity prediction based on quantitative structure-activity relationship (QSAR) studies in the big data era. However, the structural description in the reported DL-QSAR models is still restricted to the two-dimensional level. Inspired by point clouds, a type of geometric data structure, a novel three-dimensional (3D) molecular surface point cloud with electrostatic potential (SepPC) was proposed to describe chemical structures. Each surface point of a chemical is assigned its 3D coordinate and molecular electrostatic potential. A novel DL architecture SepPCNET was then introduced to directly consume unordered SepPC data for toxicity classification. The SepPCNET model was trained on 1317 chemicals tested in a battery of 18 estrogen receptor-related assays of the ToxCast program. The obtained model recognized the active and inactive chemicals at accuracies of 82.8 and 88.9%, respectively, with a total accuracy of 88.3% on the internal test set and 92.5% on the external test set, which outperformed other up-to-date machine learning models and succeeded in recognizing the difference in the activity of isomers. Additional insights into the toxicity mechanism were also gained by visualizing critical points and extracting data-driven point features of active chemicals.

Development of an objective index, neural activity score (NAS), reveals neural network ontogeny and treatment effects on microelectrode arrays

Microelectrode arrays (MEAs) are valuable tools for electrophysiological analysis, providing assessment of neural network health and development. Analysis can be complex, however, requiring intensive processing of large data sets consisting of many activity parameters, leading to information loss as studies subjectively report relatively few metrics in the interest of simplicity. In screening assays, many groups report simple overall activity (i.e. firing rate) but omit network connectivity changes (e.g. burst characteristics and synchrony) that may not be evident from basic parameters. Our goal was to develop an objective process to capture most of the valuable information gained from MEAs in neural development and toxicity studies. We implemented principal component analysis (PCA) to reduce the high dimensionality of MEA data. Upon analysis, we found the first principal component was strongly correlated to time, representing neural culture development; therefore, factor loadings were used to create a single index score-named neural activity score (NAS)-reflecting neural maturation. For validation, we applied NAS to studies analyzing various treatments. In all cases, NAS accurately recapitulated expected results, suggesting viability of NAS to measure network health and development. This approach may be adopted by other researchers using MEAs to analyze complicated treatment effects and multicellular interactions.

Tris(4-hydroxyphenyl)ethane (THPE), a trisphenol compound, is antiestrogenic and can retard uterine development in CD-1 mice

Tris (4-hydroxyphenyl)ethane (THPE), a trisphenol compound widely used as a branching agent and raw material in plastics, adhesives, and coatings is rarely regarded with concern. However, inspection of in vitro data suggests that THPE is an antagonist of estrogen receptors (ERs). Accordingly, we aimed to evaluate the antiestrogenicity of THPE in vivo and tested its effect via oral gavage on pubertal development in female CD-1 mice. Using uterotrophic assays, we found that THPE either singly, or combined with 17β-estradiol (E₂) (400 μg/kg bw/day) suppressed the uterine weights at low doses (0.1, 0.3, and 1 mg/kg bw/day) in 3-day treatment of weaning mice. When mice were treated with THPE during adolescence (for 10 days beginning on postnatal day 24), their uterine development was significantly retarded at doses of at least 0.1 mg/kg bw/day, manifest as decreased uterine weight, atrophic endometrial stromal cells and thinner columnar epithelial cells. Transcriptome analyses of uteri demonstrated that estrogen-responsive genes were significantly downregulated by THPE. Molecular docking shows that THPE fits well into the antagonist pocket of human ERα. These results indicate that THPE possesses strong antiestrogenicity in vivo and can disrupt normal female development in mice at very low dosages.

The role of fit-for-purpose assays within tiered testing approaches: A case study evaluating prioritized estrogen-active compounds in an in vitro human uterotrophic assay

Chemical risk assessment relies on toxicity tests that require significant numbers of animals, time and costs. For the >30,000 chemicals in commerce, the current scale of animal testing is insufficient to address chemical safety concerns as regulatory and product stewardship considerations evolve to require more comprehensive understanding of potential biological effects, conditions of use, and associated exposures. We demonstrate the use of a multi-level new approach methodology (NAMs) strategy for hazard- and risk-based prioritization to reduce animal testing. A Level 1/2 chemical prioritization based on estrogen receptor (ER) activity and metabolic activation using ToxCast data was used to select 112 chemicals for testing in a Level 3 human uterine cell estrogen response assay (IKA assay). The Level 3 data were coupled with quantitative in vitro to in vivo extrapolation (Q-IVIVE) to support bioactivity determination (as a surrogate for hazard) in a tissue-specific context. Assay AC₅₀s and Q-IVIVE were used to estimate human equivalent doses (HEDs), and HEDs were compared to rodent uterotrophic assay in vivo-derived points of departure (PODs). For substances active both in vitro and in vivo, IKA assay-derived HEDs were lower or equivalent to in vivo PODs for 19/23 compounds (83%). Activity exposure relationships were calculated, and the IKA assay was as or more protective of human health than the rodent uterotrophic assay for all IKA-positive compounds. This study demonstrates the utility of biologically relevant fit-for-purpose assays and supports the use of a multi-level strategy for chemical risk assessment.

Twenty years of transcriptomics, 17alpha-ethinylestradiol, and fish

In aquatic toxicology, perhaps no pharmaceutical has been investigated more intensely than 17alpha-ethinylestradiol (EE2), the active ingredient of the birth control pill. At the turn of the century, the fields of comparative endocrinology and endocrine disruption research witnessed the emergence of omics technologies, which were rapidly adapted to characterize potential hazards associated with exposures to environmental estrogens, such as EE2. Since then, significant advances have been made by the scientific community, and as a result, much has been learned about estrogen receptor signaling in fish from environmental xenoestrogens. Vitellogenin, the egg yolk precursor protein, was identified as a major estrogen-responsive gene, establishing itself as the premier biomarker for estrogenic exposures. Omics studies have identified a plethora of estrogen responsive genes, contributing to a wealth of knowledge on estrogen-mediated regulatory networks in teleosts. There have been ~40 studies that report on transcriptome responses to EE2 in a variety of fish species (e.g., zebrafish, fathead minnows, rainbow trout, pipefish, mummichog, stickleback, cod, and others). Data on the liver and testis transcriptomes dominate in the literature and have been the subject of many EE2 studies, yet there remain knowledge gaps for other tissues, such as the spleen, kidney, and pituitary. Inter-laboratory genomics studies have revealed transcriptional networks altered by EE2 treatment in the liver; networks related to amino acid activation and protein folding are increased by EE2 while those related to xenobiotic metabolism, immune system, circulation, and triglyceride storage are suppressed. EE2-responsive networks in other tissues are not as comprehensively defined which is a knowledge gap as regulated networks are expected to be tissue-specific. On the horizon, omics studies for estrogen-mediated effects in fish include: (1) Establishing conceptual frameworks for incorporating estrogen-responsive networks into environmental monitoring programs; (2) Leveraging in vitro and computational toxicology approaches to identify chemicals associated with estrogen receptor-mediated effects in fish (e.g., male vitellogenin production); (3) Discovering new tissue-specific estrogen receptor signaling pathways in fish; and (4) Developing quantitative adverse outcome pathway predictive models for estrogen signaling. As we look ahead, research into EE2 over the past several decades can serve as a template for the array of hormones and endocrine active substances yet to be fully characterized or discovered.

Measured concentrations of consumer product chemicals in California house dust: Implications for sources, exposure, and toxicity potential

Household dust is a reservoir of various consumer product chemicals. Thus, characterizing comprehensive chemical profiles of house dust may help improve our understanding of residential chemical exposure. We have previously developed a method for detecting a broad spectrum of chemicals in dust by applying a combination of target, suspect screening, and non-target methods with mass spectrometry preceded by liquid chromatography and gas chromatography. Building upon a previous study that detected 271 compounds in 38 dust samples, we presented concentrations of 144 compounds that were confirmed and quantified by standards in the same set of samples. Ten compounds were measured with median concentrations greater than 10 000 ng/g of dust: cis-hexadec-6-enoic acid, squalene, cholesterol, vitamin E, bis(2-ethylhexyl) phthalate, dioctyl terephthalate, linoleic acid, tricaprylin, tris(1-chloroisopropyl) phosphate, and oxybenzone. We also reviewed in vitro toxicity screening data to identify compounds that were not previously detected in indoor dust but have potential for adverse health effects. Among 119 newly detected compounds, 13 had endocrine-disrupting potential and 7 had neurotoxic potential. Toxicity screening data were not available for eight biocides, which may adversely affect health. Our results strive to provide more comprehensive chemical profiles of house dust and identified information gaps for future health studies.

Determination of Endocrine Disruption Potential of Bisphenol A Alternatives in Food Contact Materials Using In Vitro Assays: State of the Art and Future Challenges

Alternatives to bisphenol A (BPA) are developed for food contact materials as a result of increasing evidence of exposure-correlated harmful effects of BPA. In vitro assays provide the fast, affordable, and mechanism insightful ways to screen endocrine disruption (ED), which is a major concern of new BPA alternatives. In this review, we summarize the safety and regulation information on the alternatives to BPA, review the state of the art of in vitro assays for ED evaluation, highlight their advantages and limitations, and discuss the challenges and future research needs. Our review shows that ligand binding, reporter gene, cell proliferation, and steroidogenesis are four commonly used in vitro assays to determine the ED at the response of receptor, gene transcription, and whole cell level. Major challenges are found from in vitro-in vivo translation and identification of ED chemicals in polymers. More studies on these areas are needed in the future.

Identification of Androgen Receptor Modulators in a Prostate Cancer Cell Line Microarray Compendium

High-throughput transcriptomic (HTTr) technologies are increasingly being used to screen environmental chemicals in vitro to identify molecular targets and provide mechanistic context for regulatory testing. Here, we describe the development and validation of a novel gene expression biomarker to identify androgen receptor (AR)-modulating chemicals using a pattern matching method. Androgen receptor biomarker genes were identified by their consistent expression after exposure to 4 AR agonists and 4 AR antagonists and included only those genes that were regulated by AR. The 51 gene biomarker was evaluated as a predictive tool using the fold-change, rank-based Running Fisher algorithm. Using 158 comparisons from cells treated with 95 chemicals, the biomarker gave balanced accuracies for prediction of AR activation or AR suppression of 97% or 98%, respectively. The biomarker correctly classified 16 out of the 17 AR reference antagonists including those that are "weak" and "very weak". Predictions based on microarray profiles from AR-positive LAPC-4 cells treated with 28 chemicals in antagonist mode were compared with those from an AR pathway model which used 11 in vitro HT assays. The balanced accuracy for suppression was 93%. Using our approach, we identified conditions in which AR was modulated in a large collection of microarray profiles from prostate cancer cell lines including (1) constitutively active mutants or knockdown of AR, (2) decreases in availability of androgens by castration or removal from media, and (3) exposure to chemical modulators that work through indirect mechanisms including suppression of AR expression. These results demonstrate that the AR gene expression biomarker could be a useful tool in HTTr to identify AR modulators.

Efficient extraction of estrogen receptor-active compounds from environmental surface water via a receptor-mimic adsorbent, a hydrophilic PEG-based molecularly imprinted polymer

We report an efficient screening procedure for the selective detection of compounds that are actively bound to estrogen receptor (ER) from environmental water samples using a receptor-mimic adsorbent prepared by a molecularly imprinted polymer (MIP). To mimic the recognition ability of ER, we improved the typical MIP preparation procedure using a hydrophilic matrix with a polyethylene glycol (PEG)-based crosslinker and a hydrophobic monomer to imitate the hydrophobic pocket of ER. An optimized MIP prepared with methacrylic acid as an additional functional monomer and estriol (E3), an analogue of 17β-estradiol (E2), exhibited highly selective adsorption for ER-active compounds such as E2 and E3, with significant suppression of non-specific hydrophobic adsorption. The prepared MIP was then applied to the screening of ER-active compounds in sewage samples. The fraction concentrated by the MIP was evaluated by in vitro bioassay using the yeast two-hybrid (Y2H) method and liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-Q-TOFMS). Compared to an authentic adsorbent, styrene-divinylbenzene (SDB)-based resin, the fraction concentrated by the MIP had 120% ER activity in the Y2H assay, and only 25% peak volume was detected in LC-Q-TOFMS. Furthermore, a few ER-active compounds were identified only from the fraction concentrated by the MIP, although they could not be determined in the fraction concentrated by the SDB-based resin due to ion suppression along with high levels of hydrophobic compounds. These results indicated that the newly developed MIP effectively captured ER-active compounds and while allowing most non-ER-active compounds to pass through.

Alkylphenolic compounds and risk of breast and prostate cancer in the MCC-Spain study

BACKGROUND

Alkylphenolic compounds are chemicals with endocrine disrupting properties that have been widely used in industry with important changes in their usage over time. Few epidemiologic studies have evaluated the effect of alkylphenolic compounds on human health.

OBJECTIVES

We investigated whether occupational exposure to alkylphenolic compounds is associated with breast and prostate cancer.

METHODS

We carried out a population-based case-control study including 1513 incident cases of breast cancer, 1095 of prostate cancer, and 3055 controls, frequency matched by sex, age and region. Occupational exposure to alkylphenolic compounds was estimated using a recently developed job-exposure matrix, which considered different scenarios of exposure and different subtypes of alkylphenolic compounds.

RESULTS

History of occupational exposure to alkylphenolic compounds was modestly associated with breast cancer (OR = 1.23; 95% CI = 1.01-1.48). Within the different scenarios, the occupational use of domestic tensioactives was positively associated with breast cancer (OR = 1.28; 95% CI = 1.02-1.60), while occupational exposure in other scenarios showed mostly a suggestion of a similar positive associations. Exposure to nonylphenol ethoxylates was positively associated with breast cancer (OR = 1.21; 95% CI = 1.00-1.47), while exposure to other compounds was uncommon. In general, we did not observe associations between alkylphenolic compounds and prostate cancer, except for a positive association among men occupationally exposed to cosmetic, hair and personal hygiene products.

CONCLUSIONS

Our findings suggest a modest association between breast cancer risk and occupational exposure to alkylphenolic compounds, and no associations between these compounds and prostate cancer risk. These findings warrant further corroboration in other studies.

Copper-Catalyzed Vicinal Chloro-thiolation of Alkynes with Sulfonyl Chlorides

A copper-catalyzed vicinal chloro-thiolation of alkynes with inexpensive and diversified sulfonyl chlorides RSO₂Cl (R = aryl, alkyl) has been developed. This practical and scalable reaction could be used for the construction of a number of unexplored bioactive chlorothiolated alkenes. Internal alkynes could also undergo the chloro-thiolation to provide tetrasubstituted alkynes. Preliminary mechanistic investigations revealed a plausible radical process involving a sulfur-centered radical intermediate via copper-mediated homolysis of the S-Cl bond.

Exploring non-linear distance metrics in the structure-activity space: QSAR models for human estrogen receptor

Background

Quantitative structure-activity relationship (QSAR) models are important tools used in discovering new drug candidates and identifying potentially harmful environmental chemicals. These models often face two fundamental challenges: limited amount of available biological activity data and noise or uncertainty in the activity data themselves. To address these challenges, we introduce and explore a QSAR model based on custom distance metrics in the structure-activity space.

Methods

The model is built on top of the k-nearest neighbor model, incorporating non-linearity not only in the chemical structure space, but also in the biological activity space. The model is tuned and evaluated using activity data for human estrogen receptor from the US EPA ToxCast and Tox21 databases.

Results

The model closely trails the CERAPP consensus model (built on top of 48 individual human estrogen receptor activity models) in agonist activity predictions and consistently outperforms the CERAPP consensus model in antagonist activity predictions.

Discussion

We suggest that incorporating non-linear distance metrics may significantly improve QSAR model performance when the available biological activity data are limited.

Electronic supplementary material

The online version of this article (10.1186/s13321-018-0300-0) contains supplementary material, which is available to authorized users.

Endocrine Disruption: Current approaches for regulatory testing and assessment of plant protection products are fit for purpose

The ongoing debate concerning the regulation of endocrine disruptors, has increasingly led to questions concerning the current testing of chemicals and whether this is adequate for the assessment of potential endocrine disrupting effects. This paper describes the current testing approaches for plant protection product (PPP) active substances in the European Union and the United States and how they relate to the assessment of endocrine disrupting properties for human and environmental health. This includes a discussion of whether the current testing approaches cover modalities other than the estrogen, androgen, thyroid and steroidogenesis (EATS) pathways, sensitive windows of exposure, adequate assessment of human endocrine disorders and wildlife species, and the determination of thresholds for endocrine disruption. It is concluded, that the scope and nature of the core and triggered data requirements for PPP active substances are scientifically robust to address adverse effects mediated through endocrine mode(s) of action and to characterise these effects in terms of dose response.

Comprehensive Analyses and Prioritization of Tox21 10K Chemicals Affecting Mitochondrial Function by in-Depth Mechanistic Studies

BACKGROUND

A central challenge in toxicity testing is the large number of chemicals in commerce that lack toxicological assessment. In response, the Tox21 program is re-focusing toxicity testing from animal studies to less expensive and higher throughput in vitro methods using target/pathway-specific, mechanism-driven assays.

OBJECTIVES

Our objective was to use an in-depth mechanistic study approach to prioritize and characterize the chemicals affecting mitochondrial function.

METHODS

We used a tiered testing approach to prioritize for more extensive testing 622 compounds identified from a primary, quantitative high-throughput screen of 8,300 unique small molecules, including drugs and industrial chemicals, as potential mitochondrial toxicants by their ability to significantly decrease the mitochondrial membrane potential (MMP). Based on results from secondary MMP assays in HepG2 cells and rat hepatocytes, 34 compounds were selected for testing in tertiary assays that included formation of reactive oxygen species (ROS), upregulation of p53 and nuclear erythroid 2-related factor 2/antioxidant response element (Nrf2/ARE), mitochondrial oxygen consumption, cellular Parkin translocation, and larval development and ATP status in the nematode Caenorhabditis elegans.

RESULTS

A group of known mitochondrial complex inhibitors (e.g., rotenone) and uncouplers (e.g., chlorfenapyr), as well as potential novel complex inhibitors and uncouplers, were detected. From this study, we identified four not well-characterized potential mitochondrial toxicants (lasalocid, picoxystrobin, pinacyanol, and triclocarban) that merit additional in vivo characterization.

CONCLUSIONS

The tier-based approach for identifying and mechanistically characterizing mitochondrial toxicants can potentially reduce animal use in toxicological testing. https://doi.org/10.1289/EHP2589.

Effect-based trigger values for in vitro and in vivo bioassays performed on surface water extracts supporting the environmental quality standards (EQS) of the European Water Framework Directive

Effect-based methods including cell-based bioassays, reporter gene assays and whole-organism assays have been applied for decades in water quality monitoring and testing of enriched solid-phase extracts. There is no common EU-wide agreement on what level of bioassay response in water extracts is acceptable. At present, bioassay results are only benchmarked against each other but not against a consented measure of chemical water quality. The EU environmental quality standards (EQS) differentiate between acceptable and unacceptable surface water concentrations for individual chemicals but cannot capture the thousands of chemicals in water and their biological action as mixtures. We developed a method that reads across from existing EQS and includes additional mixture considerations with the goal that the derived effect-based trigger values (EBT) indicate acceptable risk for complex mixtures as they occur in surface water. Advantages and limitations of various approaches to read across from EQS are discussed and distilled to an algorithm that translates EQS into their corresponding bioanalytical equivalent concentrations (BEQ). The proposed EBT derivation method was applied to 48 in vitro bioassays with 32 of them having sufficient information to yield preliminary EBTs. To assess the practicability and robustness of the proposed approach, we compared the tentative EBTs with observed environmental effects. The proposed method only gives guidance on how to derive EBTs but does not propose final EBTs for implementation. The EBTs for some bioassays such as those for estrogenicity are already mature and could be implemented into regulation in the near future, while for others it will still take a few iterations until we can be confident of the power of the proposed EBTs to differentiate good from poor water quality with respect to chemical contamination.

Assessment of the Endocrine-Disrupting Effects of Trichloroethylene and Its Metabolites Using in Vitro and in Silico Approaches

Trichloroethylene (TCE) is a ubiquitous environmental contaminant, which may have effects on both ecosystem and human health. TCE has been reported to cause several toxic effects, but little effort has been made to assess the ecological risks of TCE or its major metabolites: trichloroethanol (TCOH), trichloroacetic acid, and oxalic acid (OA). In this study, the endocrine-disrupting potential of TCE and its metabolites were investigated using in vitro and in silico approaches. We examined alterations in the steroidogenesis pathway using the NCI-H295R cell line and utilized receptor-mediated luciferase reporter cell lines to identify effects on estrogen and androgen receptors. Molecular docking was also used to explore chemical interactions with these receptors. All test chemicals except OA significantly increased 17β-estradiol production which can be attributed to an up-regulation of 17β-hydroxysteroid dehydrogenase. Moreover, TCOH exhibited significant antiestrogenic activity with a RIC20 (20% relative inhibitory concentration) of 3.7 × 10-7 M. Molecular docking simulation supported this finding with lower docking scores for TCOH, indicating that hydrogen bonds may stabilize the interaction between TCOH and the estrogen receptor binding pocket. These findings suggest that TCE contamination poses an endocrine-disrupting threat, which has implications for both ecological and human health.

Contribution of the Endocrine Perspective in the Evaluation of Endocrine Disrupting Chemical Effects: The Case Study of Pubertal Timing

Debate makes science progress. In the field of endocrine disruption, endocrinology has brought up findings that substantiate a specific perspective on the definition of endocrine disrupting chemicals (EDCs), the role of the endocrine system and the endpoints of hormone and EDC actions among other issues. This paper aims at discussing the relevance of the endocrine perspective with regard to EDC effects on pubertal timing. Puberty involves particular sensitivity to environmental conditions. Reports about the advancing onset of puberty in several countries have led to the hypothesis that the increasing burden of EDCs could be an explanation. In fact, pubertal timing currently shows complex changes since advancement of some manifestations of puberty (e.g. breast development) and no change or delay of others (e.g. menarche, pubic hair development) can be observed. In a human setting with exposure to low doses of tenths or hundreds of chemicals since prenatal life, causation is most difficult to demonstrate and justifies a translational approach using animal models. Studies in rodents indicate an exquisite sensitivity of neuroendocrine endpoints to EDCs. Altogether, the data from both human and animal studies support the importance of concepts derived from endocrinology in the evaluation of EDC effects on puberty.

Are organosilicon surfactants safe for bees or humans?

Organosilicon surfactants are the most potent adjuvants available for formulating and applying agricultural pesticides and fertilizers, household cleaning and personal care products, dental impressions and medicines. Risk assessment of pesticides, drugs or personal care products that takes into account only active ingredients without the other formulation ingredients and adjuvants commonly used in their application will miss important toxicity outcomes detrimental to non-target species including pollinators and humans. Over a billion pounds of organosilicon surfactants from all uses are produced globally per year, making this a major component of the chemical landscape to which bees and humans are exposed. These silicones, like most "inerts", are generally recognized as safe, have no mandated tolerances, and their residues are largely unmonitored. Lack of their public disclosure and adequate analytical methods constrains evaluation of their risk. Organosilicon surfactants, the most super-spreading and -penetrating adjuvants available, at relevant exposure levels impair honey bee learning, are acutely toxic, and in combination with bee viruses cause synergistic mortality. Organosilicon surfactants need to be regulated as a separate class of "inerts" from the more common silicones. In turn, impacts of organosilicon surfactant exposures on humans need to be evaluated. Silicones in their great diversity probably represent the single most ubiquitous environmental class of global synthetic pollutants. Do honey bees, a model environmental indicator organism, forewarn of hidden risks to humans of ubiquitous silicone exposures?

Risks and benefits related to alimentary exposure to xenoestrogens

Xenoestrogens are widely diffused in the environment and in food, thus a large portion of human population worldwide is exposed to them. Among alimentary xenoestrogens, phytoestrogens (PhyEs) are increasingly being consumed because of their potential health benefits, although there are also important risks associated to their ingestion. Furthermore, other xenoestrogens that may be present in food are represented by other chemicals possessing estrogenic activities, that are commonly defined as endocrine disrupting chemicals (EDCs). EDCs pose a serious health concern since they may cause a wide range of health problems, starting from pre-birth till adult lifelong exposure. We herein provide an overview of the main classes of xenoestrogens, which are classified on the basis of their origin, their structures and their occurrence in the food chain. Furthermore, their either beneficial or toxic effects on human health are discussed in this review.

Development of estrogen receptor beta binding prediction model using large sets of chemicals

We developed an ER_β binding prediction model to facilitate identification of chemicals specifically bind ER_β or ER_α together with our previously developed ER_α binding model. Decision Forest was used to train ER_β binding prediction model based on a large set of compounds obtained from EADB. Model performance was estimated through 1000 iterations of 5-fold cross validations. Prediction confidence was analyzed using predictions from the cross validations. Informative chemical features for ER_β binding were identified through analysis of the frequency data of chemical descriptors used in the models in the 5-fold cross validations. 1000 permutations were conducted to assess the chance correlation. The average accuracy of 5-fold cross validations was 93.14% with a standard deviation of 0.64%. Prediction confidence analysis indicated that the higher the prediction confidence the more accurate the predictions. Permutation testing results revealed that the prediction model is unlikely generated by chance. Eighteen informative descriptors were identified to be important to ER_β binding prediction. Application of the prediction model to the data from ToxCast project yielded very high sensitivity of 90-92%. Our results demonstrated ER_β binding of chemicals could be accurately predicted using the developed model. Coupling with our previously developed ER_α prediction model, this model could be expected to facilitate drug development through identification of chemicals that specifically bind ER_β or ER_α.

Fixed Bed Modeling of Nonsteroidal Anti-Inflammatory Drug Removal by Ion-Exchange in Synthetic Urine: Mass Removal or Toxicity Reduction?

Ion-exchange removal of nonsteroidal anti-inflammatory drugs (NSAIDs) in synthetic urine can selectively remove pharmaceuticals with minimal coremoval of nutrients to enhance nutrient recovery efforts. However, the effect of endogenous metabolites in urine on ion-exchange removal, and the corresponding reduction in ecotoxicity potential of pharmaceuticals in treated urine entering the environment, is unknown. To assess treatment efficacy, this work paired predicted breakthrough curves determined by the homogeneous surface diffusion model to an in vitro bioassay to evaluate COX-1 inhibition. The presence of endogenous metabolites in urine significantly impacted pharmaceutical removal, by competing for ion-exchange sites on the resin and reducing the resin capacity for pharmaceuticals. This indicates ion-exchange would be ineffective at removing NSAIDs and other negatively charged compounds in urine. Due to hydrolysis of pharmaceutical metabolites back to the parent compound, treatment systems should be designed based on the ultimate pharmaceutical concentration in ureolyzed urine. Mass removal and COX-1 inhibition followed a nonlinear correlation and mixture toxicity followed the generalized concentration addition model. This work demonstrates the importance of evaluating removal of contaminants of emerging concern, such as pharmaceuticals, using a risk-based approach to ecotoxicity end points in conjunction with mass removal.

A novel high throughput screening assay for binding affinities of perfluoroalkyl iodide for estrogen receptor alpha and beta isoforms

Contaminants of emerging concern are continuously increasing, which makes it important to develop high throughput screening techniques for the evaluation of their potential biological effects, especially endocrine disrupting effects, which would directly influence the population dynamics in environment. A novel competitive binding assay based on enzyme fragmentation complementation technology was established to screen the binding affinities of emerging chemicals for estrogen receptor (ER) α or β isoforms. Exogenous compounds could compete with the fragment (ED-ES) of genetically engineered β-galactosidase enzyme (β-gal) for the binding to ERα or β, thus quantitatively altering the formation of enzymatically active β-gal and the hydrolysis of luminescent substrate. According to the monitoring of luminescence curves and the optimization of ERα or β concentrations, it was found that luminescent signals were sustainably emitted for 9h, and 40nM ERα or β in the system would lead to the most sensitive luminescence response. Using 17β-estrodiol (E₂) and genistein as the representative estrogenic hormones, their binding affinities for ERα and β were evaluated. The results were consistent with those determined by traditional methods, which confirmed the reliability of this competitive binding assay based on β-gal. Four polyfluorinated iodine alkanes (PFIs) with specific structural characteristics in iodine substitution and carbon chain length were screened, and the results showed diverse binding affinities and different preferences of these chemicals to ERα or β isoforms. The binding affinities of PFIs for ERα were consistent with the result from MVLN transcriptional reporter assay. Overall, the competitive binding assay presented in this study provided a promising alternative to high throughput screening of emerging chemicals with estrogenic effects, which would be important in explanation of their potential toxicological effects and human exposure risks.

High-Throughput Screening Data Interpretation in the Context of In Vivo Transcriptomic Responses to Oral Cr(VI) Exposure

The toxicity of hexavalent chromium [Cr(VI)] in drinking water has been studied extensively, and available in vivo and in vitro studies provide a robust dataset for application of advanced toxicological tools to inform the mode of action (MOA). This study aimed to contribute to the understanding of Cr(VI) MOA by evaluating high-throughput screening (HTS) data and other in vitro data relevant to Cr(VI), and comparing these findings to robust in vivo data, including transcriptomic profiles in target tissues. Evaluation of Tox21 HTS data for Cr(VI) identified 11 active assay endpoints relevant to the Ten Key Characteristics of Carcinogens (TKCCs) that have been proposed by other investigators. Four of these endpoints were related to TP53 (tumor protein 53) activation mapping to genotoxicity (KCC#2), and four were related to cell death/proliferation (KCC#10). HTS results were consistent with other in vitro data from the Comparative Toxicogenomics Database. In vitro responses were compared to in vivo transcriptomic responses in the most sensitive target tissue, the duodenum, of mice exposed to ≤ 180 ppm Cr(VI) for 7 and 90 days. Pathways that were altered both in vitro and in vivo included those relevant to cell death/proliferation. In contrast, pathways relevant to p53/DNA damage were identified in vitro but not in vivo. Benchmark dose modeling and phenotypic anchoring of in vivo transcriptomic responses strengthened the finding that Cr(VI) causes cell stress/injury followed by proliferation in the mouse duodenum at high doses. These findings contribute to the body of evidence supporting a non-mutagenic MOA for Cr(VI)-induced intestinal cancer.

Real-time cell toxicity profiling of Tox21 10K compounds reveals cytotoxicity dependent toxicity pathway linkage

Cytotoxicity is a commonly used in vitro endpoint for evaluating chemical toxicity. In support of the U.S. Tox21 screening program, the cytotoxicity of ~10K chemicals was interrogated at 0, 8, 16, 24, 32, & 40 hours of exposure in a concentration dependent fashion in two cell lines (HEK293, HepG2) using two multiplexed, real-time assay technologies. One technology measures the metabolic activity of cells (i.e., cell viability, glo) while the other evaluates cell membrane integrity (i.e., cell death, flor). Using glo technology, more actives and greater temporal variations were seen in HEK293 cells, while results for the flor technology were more similar across the two cell types. Chemicals were grouped into classes based on their cytotoxicity kinetics profiles and these classes were evaluated for their associations with activity in the Tox21 nuclear receptor and stress response pathway assays. Some pathways, such as the activation of H2AX, were associated with the fast-responding cytotoxicity classes, while others, such as activation of TP53, were associated with the slow-responding cytotoxicity classes. By clustering pathways based on their degree of association to the different cytotoxicity kinetics labels, we identified clusters of pathways where active chemicals presented similar kinetics of cytotoxicity. Such linkages could be due to shared underlying biological processes between pathways, for example, activation of H2AX and heat shock factor. Others involving nuclear receptor activity are likely due to shared chemical structures rather than pathway level interactions. Based on the linkage between androgen receptor antagonism and Nrf2 activity, we surmise that a subclass of androgen receptor antagonists cause cytotoxicity via oxidative stress that is associated with Nrf2 activation. In summary, the real-time cytotoxicity screen provides informative chemical cytotoxicity kinetics data related to their cytotoxicity mechanisms, and with our analysis, it is possible to formulate mechanism-based hypotheses on the cytotoxic properties of the tested chemicals.

A comprehensive review of regulatory test methods for endocrine adverse health effects

Development of new endocrine disruption-relevant test methods has been the subject of intensive research efforts for the past several decades, prompted in part by mandates in the 1996 Food Quality Protection Act (FQPA). While scientific understanding and test methods have advanced, questions remain on whether current scientific methods are capable of adequately addressing the complexities of the endocrine system for regulatory health and ecological risk assessments. The specific objective of this article is to perform a comprehensive, detailed evaluation of the adequacy of current test methods to inform regulatory risk assessments of whether a substance has the potential to perturb endocrine-related pathways resulting in human adverse effects. To that end,  approximately 42 existing test guidelines (TGs) were considered in the evaluation of coverage for endocrine-related adverse effects. In addition to evaluations of whether test methods are adequate to capture endocrine-related effects, considerations of further enhancements to current test methods, along with the need to develop novel test methods to address existing test method gaps are described. From this specific evaluation, up to 35 test methods are capable of informing whether a chemical substance perturbs known endocrine related biological pathways. Based on these findings, it can be concluded that current validated test methods are adequate to discern substances that may perturb the endocrine system, resulting in an adverse health effect. Together, these test methods predominantly form the core data requirements of a typical food-use pesticide registration submission. It is recognized, however, that the current state of science is rapidly advancing and there is a need to update current test methods to include added enhancements to ensure continued coverage and public health and environmental protection.

Gap Junctional Intercellular Communication: A Functional Biomarker to Assess Adverse Effects of Toxicants and Toxins, and Health Benefits of Natural Products

This protocol describes a scalpel loading-fluorescent dye transfer (SL-DT) technique that measures intercellular communication through gap junction channels, which is a major intercellular process by which tissue homeostasis is maintained. Interruption of gap junctional intercellular communication (GJIC) by toxicants, toxins, drugs, etc. has been linked to numerous adverse health effects. Many genetic-based human diseases have been linked to mutations in gap junction genes. The SL-DT technique is a simple functional assay for the simultaneous assessment of GJIC in a large population of cells. The assay involves pre-loading cells with a fluorescent dye by briefly perturbing the cell membrane with a scalpel blade through a population of cells. The fluorescent dye is then allowed to traverse through gap junction channels to neighboring cells for a designated time. The assay is then terminated by the addition of formalin to the cells. The spread of the fluorescent dye through a population of cells is assessed with an epifluorescence microscope and the images are analyzed with any number of morphometric software packages that are available, including free software packages found on the public domain. This assay has also been adapted for in vivo studies using tissue slices from various organs from treated animals. Overall, the SL-DT assay can serve a broad range of in vitro pharmacological and toxicological needs, and can be potentially adapted for high throughput set-up systems with automated fluorescence microscopy imaging and analysis to elucidate more samples in a shorter time.

Editor's Highlight: Development of an In vitro Assay Measuring Uterine-Specific Estrogenic Responses for Use in Chemical Safety Assessment

A toxicity pathway approach was taken to develop an in vitro assay using human uterine epithelial adenocarcinoma (Ishikawa) cells as a replacement for measuring an in vivo uterotrophic response to estrogens. The Ishikawa cell was determined to be fit for the purpose of recapitulating in vivo uterine response by verifying fidelity of the biological pathway components and the dose-response predictions to women of child-bearing age. Expression of the suite of estrogen receptors that control uterine proliferation (ERα66, ERα46, ERα36, ERβ, G-protein coupled estrogen receptor (GPER)) were confirmed across passages and treatment conditions. Phenotypic responses to ethinyl estradiol (EE) from transcriptional activation of ER-mediated genes, to ALP enzyme induction and cellular proliferation occurred at concentrations consistent with estrogenic activity in adult women (low picomolar). To confirm utility of this model to predict concentration-response for uterine proliferation with xenobiotics, we tested the concentration-response for compounds with known uterine estrogenic activity in humans and compared the results to assays from the ToxCast and Tox21 suite of estrogen assays. The Ishikawa proliferation assay was consistent with in vivo responses and was a more sensitive measure of uterine response. Because this assay was constructed by first mapping the key molecular events for cellular response, and then ensuring that the assay incorporated these events, the resulting cellular assay should be a reliable tool for identifying estrogenic compounds and may provide improved quantitation of chemical concentration response for in vitro-based safety assessments.

A predictive data-driven framework for endocrine prioritization: a triazole fungicide case study

The US Environmental Protection Agency Endocrine Disruptor Screening Program (EDSP) is a tiered screening approach to determine the potential for a chemical to interact with estrogen, androgen, or thyroid hormone systems and/or perturb steroidogenesis. Use of high-throughput screening (HTS) to predict hazard and exposure is shifting the EDSP approach to (1) prioritization of chemicals for further screening; and (2) targeted use of EDSP Tier 1 assays to inform specific data needs. In this work, toxicology data for three triazole fungicides (triadimefon, propiconazole, and myclobutanil) were evaluated, including HTS results, EDSP Tier 1 screening (and other scientifically relevant information), and EPA guideline mammalian toxicology study data. The endocrine-related bioactivity predictions from HTS and information that satisfied the EDSP Tier 1 requirements were qualitatively concordant. Current limitations in the available HTS battery for thyroid and steroidogenesis pathways were mitigated by inclusion of guideline toxicology studies in this analysis. Similar margins (3-5 orders of magnitude) were observed between HTS-predicted human bioactivity and exposure values and between in vivo mammalian bioactivity and EPA chronic human exposure estimates for these products' registered uses. Combined HTS hazard and human exposure predictions suggest low priority for higher-tiered endocrine testing of these triazoles. Comparison with the mammalian toxicology database indicated that this HTS-based prioritization would have been protective for any potential in vivo effects that form the basis of current risk assessment for these chemicals. This example demonstrates an effective, human health protective roadmap for EDSP evaluation of pesticide active ingredients via prioritization using HTS and guideline toxicology information.

Information-dependent enrichment analysis reveals time-dependent transcriptional regulation of the estrogen pathway of toxicity

The twenty-first century vision for toxicology involves a transition away from high-dose animal studies to in vitro and computational models (NRC in Toxicity testing in the 21st century: a vision and a strategy, The National Academies Press, Washington, DC, 2007). This transition requires mapping pathways of toxicity by understanding how in vitro systems respond to chemical perturbation. Uncovering transcription factors/signaling networks responsible for gene expression patterns is essential for defining pathways of toxicity, and ultimately, for determining the chemical modes of action through which a toxicant acts. Traditionally, transcription factor identification is achieved via chromatin immunoprecipitation studies and summarized by calculating which transcription factors are statistically associated with up- and downregulated genes. These lists are commonly determined via statistical or fold-change cutoffs, a procedure that is sensitive to statistical power and may not be as useful for determining transcription factor associations. To move away from an arbitrary statistical or fold-change-based cutoff, we developed, in the context of the Mapping the Human Toxome project, an enrichment paradigm called information-dependent enrichment analysis (IDEA) to guide identification of the transcription factor network. We used a test case of activation in MCF-7 cells by 17β estradiol (E2). Using this new approach, we established a time course for transcriptional and functional responses to E2. ERα and ERβ were associated with short-term transcriptional changes in response to E2. Sustained exposure led to recruitment of additional transcription factors and alteration of cell cycle machinery. TFAP2C and SOX2 were the transcription factors most highly correlated with dose. E2F7, E2F1, and Foxm1, which are involved in cell proliferation, were enriched only at 24 h. IDEA should be useful for identifying candidate pathways of toxicity. IDEA outperforms gene set enrichment analysis (GSEA) and provides similar results to weighted gene correlation network analysis, a platform that helps to identify genes not annotated to pathways.

Evaluation of tetrabromobisphenol A effects on human glucocorticoid and androgen receptors: A comparison of results from human- with yeast-based in vitro assays

The incidence of immune-related diseases increased over the last years in industrialized countries, suggesting a contribution of environmental factors. Impaired glucocorticoid action has been associated with immune disorders. Thus, there is an increasing interest to identify chemicals disrupting glucocorticoid action. The widely used flame retardant tetrabromobisphenol A (TBBPA) was reported earlier to potently inhibit glucocorticoid receptor (GR) and moderately androgen receptor (AR) activity in yeast-based reporter gene assays. To further characterize possible GR disrupting effects of TBBPA, transactivation experiments using a human HEK-293 cell-based reporter gene assay and cell-free receptor binding experiments were performed in the present study. Both, transactivation and GR binding experiments failed to detect any activity of TBBPA on GR function. Molecular docking calculations supported this observation. Additionally, the current study could confirm the antiandrogenic activity of TBBPA seen in the yeast assay, although the effect was an order of magnitude less pronounced in the HEK-293 cell-based system. In conclusion, TBBPA does not directly affect GR function and, considering its rapid metabolism and low concentrations found in humans, it is unlikely to cause adverse effects by acting through AR. This study emphasizes the use of cell-free assays in combination with cell-based assays for the in vitro evaluation of endocrine disrupting chemicals.

On the Utility of ToxCast™ and ToxPi as Methods for Identifying New Obesogens

BACKGROUND

In ToxCast™ Phase I, the U.S. EPA commissioned screening of 320 pesticides, herbicides, fungicides, and other chemicals in a series of high-throughput assays. The agency also developed a toxicological prioritization tool, ToxPi, to facilitate using ToxCast™ assays to predict biological function.

OBJECTIVES

We asked whether top-scoring PPARγ activators identified in ToxCast™ Phase I were genuine PPARγ activators and inducers of adipogenesis. Next, we identified ToxCast™ assays that should predict adipogenesis, developed an adipogenesis ToxPi, and asked how well the ToxPi predicted adipogenic activity.

METHODS

We used transient transfection to test the ability of ToxCast™ chemicals to modulate PPARγ and RXRα, and differentiation assays employing 3T3-L1 preadipocytes and mouse bone marrow-derived mesenchymal stem cells (mBMSCs) to evaluate the adipogenic capacity of ToxCast™ chemicals.

RESULTS

Only 5/21 of the top scoring ToxCast™ PPARγ activators were activators in our assays, 3 were PPARγ antagonists, the remainder were inactive. The bona fide PPARγ activators we identified induced adipogenesis in 3T3-L1 cells and mBMSCs. Only 7 of the 17 chemicals predicted to be active by the ToxPi promoted adipogenesis, 1 inhibited adipogenesis, and 2 of the 7 predicted negatives were also adipogenic. Of these 9 adipogenic chemicals, 3 activated PPARγ, and 1 activated RXRα.

CONCLUSIONS

ToxCast™ PPARγ and RXRα assays do not correlate well with laboratory measurements of PPARγ and RXRα activity. The adipogenesis ToxPi performed poorly, perhaps due to the performance of ToxCast™ assays. We observed a modest predictive value of ToxCast™ for PPARγ and RXRα activation and adipogenesis and it is likely that many obesogenic chemicals remain to be identified.

CITATION

Janesick AS, Dimastrogiovanni G, Vanek L, Boulos C, Chamorro-García R, Tang W, Blumberg B. 2016. On the utility of ToxCast™ and ToxPi as methods for identifying new obesogens. Environ Health Perspect 124:1214-1226; http://dx.doi.org/10.1289/ehp.1510352.

Toxicological Risks of Agrochemical Spray Adjuvants: Organosilicone Surfactants May Not Be Safe

Agrochemical risk assessment that takes into account only pesticide active ingredients without the spray adjuvants commonly used in their application will miss important toxicity outcomes detrimental to non-target species, including humans. Lack of disclosure of adjuvant and formulation ingredients coupled with a lack of adequate analytical methods constrains the assessment of total chemical load on beneficial organisms and the environment. Adjuvants generally enhance the pesticidal efficacy and inadvertently the non-target effects of the active ingredient. Spray adjuvants are largely assumed to be biologically inert and are not registered by the USA EPA, leaving their regulation and monitoring to individual states. Organosilicone surfactants are the most potent adjuvants and super-penetrants available to growers. Based on the data for agrochemical applications to almonds from California Department of Pesticide Regulation, there has been increasing use of adjuvants, particularly organosilicone surfactants, during bloom when two-thirds of USA honey bee colonies are present. Increased tank mixing of these with ergosterol biosynthesis inhibitors and other fungicides and with insect growth regulator insecticides may be associated with recent USA honey bee declines. This database archives every application of a spray tank adjuvant with detail that is unprecedented globally. Organosilicone surfactants are good stand alone pesticides, toxic to bees, and are also present in drug and personal care products, particularly shampoos, and thus represent an important component of the chemical landscape to which pollinators and humans are exposed. This mini review is the first to possibly link spray adjuvant use with declining health of honey bee populations.

A Curated Database of Rodent Uterotrophic Bioactivity

BACKGROUND

Novel in vitro methods are being developed to identify chemicals that may interfere with estrogen receptor (ER) signaling, but the results are difficult to put into biological context because of reliance on reference chemicals established using results from other in vitro assays and because of the lack of high-quality in vivo reference data. The Organisation for Economic Co-operation and Development (OECD)-validated rodent uterotrophic bioassay is considered the "gold standard" for identifying potential ER agonists.

OBJECTIVES

We performed a comprehensive literature review to identify and evaluate data from uterotrophic studies and to analyze study variability.

METHODS

We reviewed 670 articles with results from 2,615 uterotrophic bioassays using 235 unique chemicals. Study descriptors, such as species/strain, route of administration, dosing regimen, lowest effect level, and test outcome, were captured in a database of uterotrophic results. Studies were assessed for adherence to six criteria that were based on uterotrophic regulatory test guidelines. Studies meeting all six criteria (458 bioassays on 118 unique chemicals) were considered guideline-like (GL) and were subsequently analyzed.

RESULTS

The immature rat model was used for 76% of the GL studies. Active outcomes were more prevalent across rat models (74% active) than across mouse models (36% active). Of the 70 chemicals with at least two GL studies, 18 (26%) had discordant outcomes and were classified as both active and inactive. Many discordant results were attributable to differences in study design (e.g., injection vs. oral dosing).

CONCLUSIONS

This uterotrophic database provides a valuable resource for understanding in vivo outcome variability and for evaluating the performance of in vitro assays that measure estrogenic activity.

CITATION

Kleinstreuer NC, Ceger PC, Allen DG, Strickland J, Chang X, Hamm JT, Casey WM. 2016. A curated database of rodent uterotrophic bioactivity. Environ Health Perspect 124:556-562; http://dx.doi.org/10.1289/ehp.1510183.

Moving Toward Integrating Gene Expression Profiling Into High-Throughput Testing: A Gene Expression Biomarker Accurately Predicts Estrogen Receptor α Modulation in a Microarray Compendium

Microarray profiling of chemical-induced effects is being increasingly used in medium- and high-throughput formats. Computational methods are described here to identify molecular targets from whole-genome microarray data using as an example the estrogen receptor α (ERα), often modulated by potential endocrine disrupting chemicals. ERα biomarker genes were identified by their consistent expression after exposure to 7 structurally diverse ERα agonists and 3 ERα antagonists in ERα-positive MCF-7 cells. Most of the biomarker genes were shown to be directly regulated by ERα as determined by ESR1 gene knockdown using siRNA as well as through chromatin immunoprecipitation coupled with DNA sequencing analysis of ERα-DNA interactions. The biomarker was evaluated as a predictive tool using the fold-change rank-based Running Fisher algorithm by comparison to annotated gene expression datasets from experiments using MCF-7 cells, including those evaluating the transcriptional effects of hormones and chemicals. Using 141 comparisons from chemical- and hormone-treated cells, the biomarker gave a balanced accuracy for prediction of ERα activation or suppression of 94% and 93%, respectively. The biomarker was able to correctly classify 18 out of 21 (86%) ER reference chemicals including "very weak" agonists. Importantly, the biomarker predictions accurately replicated predictions based on 18 in vitro high-throughput screening assays that queried different steps in ERα signaling. For 114 chemicals, the balanced accuracies were 95% and 98% for activation or suppression, respectively. These results demonstrate that the ERα gene expression biomarker can accurately identify ERα modulators in large collections of microarray data derived from MCF-7 cells.

Urban Endocrine Disruptors Targeting Breast Cancer Proteins

Humans are exposed to a huge amount of environmental pollutants called endocrine disrupting chemicals (EDCs). These molecules interfere with the homeostasis of the body, usually through mimicking natural hormones leading to activation or blocking of their receptors. Many of these compounds have been associated with a broad range of diseases including the development or increased susceptibility to breast cancer, the most prevalent cancer in women worldwide, according to the World Health Organization. Thus, this article presents a virtual high-throughput screening (vHTS) to evaluate the affinity of proteins related to breast cancer, such as ESR1, ERBB2, PGR, BCRA1, and SHBG, among others, with EDCs from urban sources. A blind docking strategy was employed to screen each protein-ligand pair in triplicate in AutoDock Vina 2.0, using the computed binding affinities as ranking criteria. The three-dimensional structures were previously obtained from EDCs DataBank and Protein Data Bank, prepared and optimized by SYBYL X-2.0. Some of the chemicals that exhibited the best affinity scores for breast cancer proteins in each category were 1,3,7,8-tetrachlorodibenzo-p-dioxin, bisphenol A derivatives, perfluorooctanesulfonic acid, and benzo(a)pyrene, for catalase, several proteins, sex hormone-binding globulin, and cytochrome P450 1A2, respectively. An experimental validation of this approach was performed with a complex that gave a moderate binding affinity in silico, the sex hormone binding globulin (SHBG), and bisphenol A (BPA) complex. The protein was obtained using DNA recombinant technology and the physical interaction with BPA assessed through spectroscopic techniques. BPA binds on the recombinant SHBG, and this results in an increase of its α helix content. In short, this work shows the potential of several EDCs to bind breast cancer associated proteins as a tool to prioritize compounds to perform in vitro analysis to benefit the regulation or exposure prevention by the general population.