Abstract Sifter: a comprehensive front-end system to PubMed

Leveraging integrative toxicogenomic approach towards development of stressor-centric adverse outcome pathway networks for plastic additives

Plastics are widespread pollutants found in atmospheric, terrestrial and aquatic ecosystems due to their extensive usage and environmental persistence. Plastic additives, that are intentionally added to achieve specific functionality in plastics, leach into the environment upon plastic degradation and pose considerable risk to ecological and human health. Limited knowledge concerning the presence of plastic additives throughout plastic life cycle has hindered their effective regulation, thereby posing risks to product safety. In this study, we leveraged the adverse outcome pathway (AOP) framework to understand the mechanisms underlying plastic additives-induced toxicities. We first identified an exhaustive list of 6470 plastic additives from chemicals documented in plastics. Next, we leveraged heterogenous toxicogenomics and biological endpoints data from five exposome-relevant resources, and identified associations between 1287 plastic additives and 322 complete and high quality AOPs within AOP-Wiki. Based on these plastic additive-AOP associations, we constructed a stressor-centric AOP network, wherein the stressors are categorized into ten priority use sectors and AOPs are linked to 27 disease categories. We visualized the plastic additives-AOP network for each of the 1287 plastic additives and made them available in a dedicated website: https://cb.imsc.res.in/saopadditives/ . Finally, we showed the utility of the constructed plastic additives-AOP network by identifying highly relevant AOPs associated with benzo[a]pyrene (B[a]P), bisphenol A (BPA), and bis(2-ethylhexyl) phthalate (DEHP) and thereafter, explored the associated toxicity pathways in humans and aquatic species. Overall, the constructed plastic additives-AOP network will assist regulatory risk assessment of plastic additives, thereby contributing towards a toxic-free circular economy for plastics.

Optimizing cryopreservation strategies for scalable cell therapies: A comprehensive review with insights from iPSC-derived therapies

Off-the-shelf cell therapies hold significant curative potential for conditions, such as Parkinson's disease and heart failure. However, these therapies face unique cryopreservation challenges, especially when novel routes of administration, such as intracerebral or epicardial injection, require cryopreservation media that are safe for direct post-thaw administration. Current practices often involve post-thaw washing to remove dimethyl sulfoxide (Me2SO), a cytotoxic cryoprotective agent, which complicates the development and clinical translation of off-the-shelf therapies. To overcome these obstacles, there is a critical need to explore Me2SO-free cryopreservation methods. While such methods typically yield suboptimal post-thaw viability with conventional slow-freeze protocols, optimizing freezing profiles offers a promising strategy to enhance their performance. This comprehensive review examines the latest advancements in cryopreservation techniques across various cell therapy platforms, with a specific case study of iPSC-derived therapies used to illustrate the scalability challenges. By identifying key thermodynamic and biochemical phenomena that occur during freezing, this review aims to identify cell-type independent approaches to improve the efficiency and efficacy of cryopreservation strategies, thereby supporting the widespread adoption and clinical success of off-the-shelf cell therapies.

Engineering a computable epiblast for in silico modeling of developmental toxicity

Developmental hazard evaluation is an important part of assessing chemical risks during pregnancy. Toxicological outcomes from prenatal testing in pregnant animals result from complex chemical-biological interactions, and while New Approach Methods (NAMs) based on in vitro bioactivity profiles of human cells offer promising alternatives to animal testing, most of these assays lack cellular positional information, physical constraints, and regional organization of the intact embryo. Here, we engineered a fully computable model of the embryonic disc in the CompuCell3D.org modeling environment to simulate epithelial-mesenchymal transition (EMT) of epiblast cells and self-organization of mesodermal domains (chordamesoderm, paraxial, lateral plate, posterior/extraembryonic). Mesodermal fate is modeled by synthetic activity of the BMP4-NODAL-WNT signaling axis. Cell position in the epiblast determines timing with respect to EMT for 988 computational cells in the computer model. An autonomous homeobox (Hox) clock hidden in the epiblast is driven by WNT-FGF4-CDX signaling. Executing the model renders a quantitative cell-level computation of mesodermal fate and consequences of perturbation based on known biology. For example, synthetic perturbation of the control network rendered altered phenotypes (cybermorphs) mirroring some aspects of experimental mouse embryology, with electronic knockouts, under-activation (hypermorphs) or over-activation (hypermorphs) particularly affecting the size and specification of the posterior mesoderm. This foundational model is trained on embryology but capable of performing a wide variety of toxicological tasks conversing through anatomical simulation to integrate in vitro chemical bioactivity data with known embryology. It is amenable to quantitative simulation for probabilistic prediction of early developmental toxicity.

Community-Engaged Research and the Use of Open Access ToxVal/ToxRef In Vivo Databases and New Approach Methodologies (NAM) to Address Human Health Risks From Environmental Contaminants

BACKGROUND

The paper analyzes opportunities for integrating Open access resources (Abstract Sifter, US EPA and NTP Toxicity Value and Toxicity Reference [ToxVal/ToxRefDB]) and New Approach Methodologies (NAM) integration into Community Engaged Research (CEnR).

METHODS

CompTox Chemicals Dashboard and Integrated Chemical Environment with in vivo ToxVal/ToxRef and NAMs (in vitro) databases are presented in three case studies to show how these resources could be used in Pilot Projects involving Community Engaged Research (CEnR) from the University of California, Davis, Environmental Health Sciences Center.

RESULTS

Case #1 developed a novel assay methodology for testing pesticide toxicity. Case #2 involved detection of water contaminants from wildfire ash and Case #3 involved contaminants on Tribal Lands. Abstract Sifter/ToxVal/ToxRefDB regulatory data and NAMs could be used to screen/prioritize risks from exposure to metals, PAHs and PFAS from wildfire ash leached into water and to investigate activities of environmental toxins (e.g., pesticides) on Tribal lands. Open access NAMs and computational tools can apply to detection of sensitive biological activities in potential or known adverse outcome pathways to predict points of departure (POD) for comparison with regulatory values for hazard identification. Open access Systematic Empirical Evaluation of Models or biomonitoring exposures are available for human subpopulations and can be used to determine bioactivity (POD) to exposure ratio to facilitate mitigation.

CONCLUSIONS

These resources help prioritize chemical toxicity and facilitate regulatory decisions and health protective policies that can aid stakeholders in deciding on needed research. Insights into exposure risks can aid environmental justice and health equity advocates.

Modeling the human placenta: in vitro applications in developmental and reproductive toxicology

During its temporary tenure, the placenta has extensive and specialized functions that are critical for pre- and post-natal development. The consequences of chemical exposure in utero can have profound effects on the structure and function of pregnancy-associated tissues and the life-long health of the birthing person and their offspring. However, the toxicological importance and critical functions of the placenta to embryonic and fetal development and maturation have been understudied. This narrative will review early placental development in humans and highlight some in vitro models currently in use that are or can be applied to better understand placental processes underlying developmental toxicity due to in utero environmental exposures.

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.

An integrative data-centric approach to derivation and characterization of an adverse outcome pathway network for cadmium-induced toxicity

Cadmium is a prominent toxic heavy metal that contaminates both terrestrial and aquatic environments. Owing to its high biological half-life and low excretion rates, cadmium causes a variety of adverse biological outcomes. Adverse outcome pathway (AOP) networks were envisioned to systematically capture toxicological information to enable risk assessment and chemical regulation. Here, we leveraged AOP-Wiki and integrated heterogeneous data from four other exposome-relevant resources to build the first AOP network relevant for inorganic cadmium-induced toxicity. From AOP-Wiki, we filtered 309 high confidence AOPs, identified 312 key events (KEs) associated with inorganic cadmium from five exposome-relevant databases using a data-centric approach, and thereafter, curated 30 cadmium relevant AOPs (cadmium-AOPs). By constructing the undirected AOP network, we identified a large connected component of 18 cadmium-AOPs. Further, we analyzed the directed network of 59 KEs and 82 key event relationships (KERs) in the largest component using graph-theoretic approaches. Subsequently, we mined published literature using artificial intelligence-based tools to provide auxiliary evidence of cadmium association for all KEs in the largest component. Finally, we performed case studies to verify the rationality of cadmium-induced toxicity in humans and aquatic species. Overall, cadmium-AOP network constructed in this study will aid ongoing research in systems toxicology and chemical exposome.

Perfluorooctanoic acid induces transcriptomic alterations in second trimester human cytotrophoblasts

Poly- and perfluroroalkylated substances (PFAS) are a major class of surfactants used in industry applications and consumer products. Despite efforts to reduce the usage of PFAS due to their environmental persistence, compounds such as perfluorooctanoic acid (PFOA) are widely detected in human blood and tissue. Although growing evidence supports that prenatal exposures to PFOA and other PFAS are linked to adverse pregnancy outcomes, the target organs and pathways remain unclear. Recent investigations in mouse and human cell lines suggest that PFAS may impact the placenta and impair trophoblast function. In this study, we investigated the effects of PFOA on cytotoxicity and the transcriptome in cultured second trimester human cytotrophoblasts (CTBs). We show that PFOA significantly reduces viability and induces cell death at 24 h, in a concentration-dependent manner. At subcytotoxic concentrations, PFOA impacted expression of hundreds of genes, including several molecules (CRH, IFIT1, and TNFSF10) linked with lipid metabolism and innate immune response pathways. Furthermore, in silico analyses suggested that regulatory factors such as peroxisome proliferator-activated receptor-mediated pathways may be especially important in response to PFOA. In summary, this study provides evidence that PFOA alters primary human CTB viability and gene pathways that could contribute to placental dysfunction and disease.

AOP Report: Aryl Hydrocarbon Receptor Activation Leads to Early-Life Stage Mortality via Sox9 Repression-Induced Craniofacial and Cardiac Malformations

The aryl hydrocarbon receptors (Ahrs) are evolutionarily conserved ligand-dependent transcription factors that are activated by structurally diverse endogenous compounds as well as environmental chemicals such as polycyclic aromatic hydrocarbons and halogenated aromatic hydrocarbons. Activation of the Ahr leads to several transcriptional changes that can cause developmental toxicity resulting in mortality. Evidence was assembled and evaluated for two novel adverse outcome pathways (AOPs) which describe how Ahr activation (molecular initiating event) can lead to early-life stage mortality (adverse outcome), via either SOX9-mediated craniofacial malformations (AOP 455) or cardiovascular toxicity (AOP 456). Using a key event relationship (KER)-by-KER approach, we collected evidence using both a narrative search and a systematic review based on detailed search terms. Weight of evidence for each KER was assessed to inform overall confidence of the AOPs. The AOPs link to previous descriptions of Ahr activation and connect them to two novel key events (KEs), increase in slincR expression, a newly characterized long noncoding RNA with regulatory functions, and suppression of SOX9, a critical transcription factor implicated in chondrogenesis and cardiac development. In general, confidence levels for KERs ranged between medium and strong, with few inconsistencies, as well as several opportunities for future research identified. While the majority of KEs have only been demonstrated in zebrafish with 2,3,7,8-tetrachlorodibenzo-p-dioxin as an Ahr activator, evidence suggests that the two AOPs likely apply to most vertebrates and many Ahr-activating chemicals. Addition of the AOPs into the AOP-Wiki (https://aopwiki.org/) helps expand the growing Ahr-related AOP network to 19 individual AOPs, of which six are endorsed or in progress and the remaining 13 relatively underdeveloped. Environ Toxicol Chem 2023;42:2063-2077. © 2023 SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Identifying a causal link between prolactin signaling pathways and COVID-19 vaccine-induced menstrual changes

COVID-19 vaccines have been instrumental tools in the fight against SARS-CoV-2 helping to reduce disease severity and mortality. At the same time, just like any other therapeutic, COVID-19 vaccines were associated with adverse events. Women have reported menstrual cycle irregularity after receiving COVID-19 vaccines, and this led to renewed fears concerning COVID-19 vaccines and their effects on fertility. Herein we devised an informatics workflow to explore the causal drivers of menstrual cycle irregularity in response to vaccination with mRNA COVID-19 vaccine BNT162b2. Our methods relied on gene expression analysis in response to vaccination, followed by network biology analysis to derive testable hypotheses regarding the causal links between BNT162b2 and menstrual cycle irregularity. Five high-confidence transcription factors were identified as causal drivers of BNT162b2-induced menstrual irregularity, namely: IRF1, STAT1, RelA (p65 NF-kB subunit), STAT2 and IRF3. Furthermore, some biomarkers of menstrual irregularity, including TNF, IL6R, IL6ST, LIF, BIRC3, FGF2, ARHGDIB, RPS3, RHOU, MIF, were identified as topological genes and predicted as causal drivers of menstrual irregularity. Our network-based mechanism reconstruction results indicated that BNT162b2 exerted biological effects similar to those resulting from prolactin signaling. However, these effects were short-lived and didn't raise concerns about long-term infertility issues. This approach can be applied to interrogate the functional links between drugs/vaccines and other side effects.

Cross-species applicability of an adverse outcome pathway network for thyroid hormone system disruption

Thyroid hormone system disrupting compounds are considered potential threats for human and environmental health. Multiple adverse outcome pathways (AOPs) for thyroid hormone system disruption (THSD) are being developed in different taxa. Combining these AOPs results in a cross-species AOP network for THSD which may provide an evidence-based foundation for extrapolating THSD data across vertebrate species and bridging the gap between human and environmental health. This review aimed to advance the description of the taxonomic domain of applicability (tDOA) in the network to improve its utility for cross-species extrapolation. We focused on the molecular initiating events (MIEs) and adverse outcomes (AOs) and evaluated both their plausible domain of applicability (taxa they are likely applicable to) and empirical domain of applicability (where evidence for applicability to various taxa exists) in a THSD context. The evaluation showed that all MIEs in the AOP network are applicable to mammals. With some exceptions, there was evidence of structural conservation across vertebrate taxa and especially for fish and amphibians, and to a lesser extent for birds, empirical evidence was found. Current evidence supports the applicability of impaired neurodevelopment, neurosensory development (eg, vision) and reproduction across vertebrate taxa. The results of this tDOA evaluation are summarized in a conceptual AOP network that helps prioritize (parts of) AOPs for a more detailed evaluation. In conclusion, this review advances the tDOA description of an existing THSD AOP network and serves as a catalog summarizing plausible and empirical evidence on which future cross-species AOP development and tDOA assessment could build.

Effects of Corsi-Rosenthal boxes on indoor air contaminants: non-targeted analysis using high resolution mass spectrometry

BACKGROUND

In response to COVID-19, attention was drawn to indoor air quality and interventions to mitigate airborne COVID-19 transmission. Of developed interventions, Corsi-Rosenthal (CR) boxes, a do-it-yourself indoor air filter, may have potential co-benefits of reducing indoor air contaminant levels.

OBJECTIVE

We employed non-targeted and suspect screening analysis (NTA and SSA) to detect and identify volatile and semi-volatile organic contaminants (VOCs and SVOCs) that decreased in indoor air following installation of CR boxes.

METHODS

Using a natural experiment, we sampled indoor air before and during installation of CR boxes in 17 rooms inside an occupied office building. We measured VOCs and SVOCs using gas chromatography (GC) high resolution mass spectrometry (HRMS) with electron ionization (EI) and liquid chromatography (LC) HRMS in negative and positive electrospray ionization (ESI). We examined area count changes during vs. before operation of the CR boxes using linear mixed models.

RESULTS

Transformed (log2) area counts of 71 features significantly decreased by 50-100% after CR boxes were installed (False Discovery Rate (FDR) p-value < 0.2). Of the significantly decreased features, four chemicals were identified with Level 1 confidence, 45 were putatively identified with Level 2-4 confidence, and 22 could not be identified (Level 5). Identified and putatively identified features (Level ≥4) that declined included disinfectants (n = 1), fragrance and/or food chemicals (n = 9), nitrogen-containing heterocyclic compounds (n = 4), organophosphate esters (n = 1), polycyclic aromatic hydrocarbons (n = 8), polychlorinated biphenyls (n = 1), pesticides/herbicides/insecticides (n = 18), per- and polyfluorinated alkyl substances (n = 2), phthalates (n = 3), and plasticizers (n = 2).

IMPACT STATEMENT

We used SSA and NTA to demonstrate that do-it-yourself Corsi-Rosenthal boxes are an effective means for improving indoor air quality by reducing a wide range of volatile and semi-volatile organic contaminants.

Review of DDT, DDE, DDD, DDMU and DDMS Toxicity Data for Organisms Used in Estuarine and Marine Sediment Toxicity Tests

The open literature was searched for laboratory toxicity data for marine/estuarine organisms exposed to dichlorodiphenyltrichloroethane (DDT) and its degradation products of dichlorodiphenyldichloroethylene (DDE), dichlorodiphenyldichloroethane (DDD), dichlorodiphenylchloroethylene (DDMU), and dichlorodiphenylchloroethane (DDMS). The goal of the review was to determine water-column toxicity values that could be used for porewater-based assessment of sediment toxicity. Data for individual compounds (and isomers thereof) in this group were very limited; most available data were for mixtures of multiple compounds, some defined and others undefined. Further, the majority of relevant studies involved exposure to spiked or field-contaminated sediment (rather than waterborne exposure), which requires inferring concentration in porewater from bulk sediment. Comparing data on the basis of effect concentrations for water or inferred concentration in sediment pore water, the lower reported effect concentrations were in the range of 0.05 to 0.1 µg/L, generally in studies of longer duration and/or evaluating sub-lethal effects. Because field exposures are generally to mixtures of these compounds in varied proportions, additional data on chemical-specific toxicity would aid in pore-water based toxicity assessment for marine/estuarine sediments contaminated with DDT-related chemicals.

AOP-helpFinder 2.0: Integration of an event-event searches module

To support the use of alternative methods in regulatory assessment of chemical risks, the concept of adverse outcome pathway (AOP) constitutes an important toxicological tool. AOP represents a structured representation of existing knowledge, linking molecular initiating event (MIE) initiated by a prototypical stressor that leads to a cascade of biological key event (KE) to an adverse outcome (AO). Biological information to develop such AOP is very dispersed in various data sources. To increase the chance of capturing relevant existing data to develop a new AOP, the AOP-helpFinder tool was recently implemented to assist researchers to design new AOP. Here, an updated version of AOP-helpFinder proposes novel functionalities. The main one being the implementation of an automatic screening of the abstracts from the PubMed database to identify and extract event-event associations. In addition, a new scoring system was created to classify the identified co-occurred terms (stressor-event or event-event (which represent key event relationships) to help prioritization and support the weight of evidence approach, allowing a global assessment of the strength and reliability of the AOP. Moreover, to facilitate interpretation of the results, visualization options are also proposed. The AOP-helpFinder source code are fully accessible via GitHub, and searches can be performed via a web interface at http://aop-helpfinder-v2.u-paris-sciences.fr/.

Inconsistencies in variable reporting and methods in larval zebrafish behavioral assays

New approaches in developmental neurotoxicity (DNT) screening are needed due to the tens of thousands of chemicals requiring hazard assessments. Zebrafish (Danio rerio) are an alternative vertebrate model for DNT testing, but without a standardized protocol for larval behavioral assays, comparison of results among laboratories is challenging. To evaluate the congruence of protocols across laboratories, we conducted a literature review of DNT studies focusing on larval zebrafish behavior assays and cataloged experimental design consistencies. Our review focused on 51 unique method variables in publications where chemical exposure occurred in early development and subsequent larval locomotor evaluation focused on assays that included a light/dark photoperiod transition. We initially identified 94 publications, but only 31 exclusively met our inclusion criteria which focused on parameters that are important to an assay employed by our laboratory. No publication reported 100% of the targeted variables; only 51 to 86% of those variables were reported in the reviewed publications, with some aspects of the experimental design consistent among laboratories. However, no protocol was exactly the same for any two publications. Many of these variables had more than one parameter/design reported, highlighting the inconsistencies among methods. Overall, there is not only a strong need for the development of a standardized testing protocol for larval zebrafish locomotor assays, but there is also a need for a standardized protocol for reporting experimental variables in the literature. Here we include an extensive guideline checklist for conducting larval zebrafish developmental behavior assays.

Identifying xenobiotic metabolites with in silico prediction tools and LCMS suspect screening analysis

Understanding the metabolic fate of a xenobiotic substance can help inform its potential health risks and allow for the identification of signature metabolites associated with exposure. The need to characterize metabolites of poorly studied or novel substances has shifted exposure studies towards non-targeted analysis (NTA), which often aims to profile many compounds within a sample using high-resolution liquid-chromatography mass-spectrometry (LCMS). Here we evaluate the suitability of suspect screening analysis (SSA) liquid-chromatography mass-spectrometry to inform xenobiotic chemical metabolism. Given a lack of knowledge of true metabolites for most chemicals, predictive tools were used to generate potential metabolites as suspect screening lists to guide the identification of selected xenobiotic substances and their associated metabolites. Thirty-three substances were selected to represent a diverse array of pharmaceutical, agrochemical, and industrial chemicals from Environmental Protection Agency's ToxCast chemical library. The compounds were incubated in a metabolically-active in vitro assay using primary hepatocytes and the resulting supernatant and lysate fractions were analyzed with high-resolution LCMS. Metabolites were simulated for each compound structure using software and then combined to serve as the suspect screening list. The exact masses of the predicted metabolites were then used to select LCMS features for fragmentation via tandem mass spectrometry (MS/MS). Of the starting chemicals, 12 were measured in at least one sample in either positive or negative ion mode and a subset of these were used to develop the analysis workflow. We implemented a screening level workflow for background subtraction and the incorporation of time-varying kinetics into the identification of likely metabolites. We used haloperidol as a case study to perform an in-depth analysis, which resulted in identifying five known metabolites and five molecular features that represent potential novel metabolites, two of which were assigned discrete structures based on in silico predictions. This workflow was applied to five additional test chemicals, and 15 molecular features were selected as either reported metabolites, predicted metabolites, or potential metabolites without a structural assignment. This study demonstrates that in some-but not all-cases, suspect screening analysis methods provide a means to rapidly identify and characterize metabolites of xenobiotic chemicals.

Application of AOPs to assist regulatory assessment of chemical risks - Case studies, needs and recommendations

While human regulatory risk assessment (RA) still largely relies on animal studies, new approach methodologies (NAMs) based on in vitro, in silico or non-mammalian alternative models are increasingly used to evaluate chemical hazards. Moreover, human epidemiological studies with biomarkers of effect (BoE) also play an invaluable role in identifying health effects associated with chemical exposures. To move towards the next generation risk assessment (NGRA), it is therefore crucial to establish bridges between NAMs and standard approaches, and to establish processes for increasing mechanistically-based biological plausibility in human studies. The Adverse Outcome Pathway (AOP) framework constitutes an important tool to address these needs but, despite a significant increase in knowledge and awareness, the use of AOPs in chemical RA remains limited. The objective of this paper is to address issues related to using AOPs in a regulatory context from various perspectives as it was discussed in a workshop organized within the European Union partnerships HBM4EU and PARC in spring 2022. The paper presents examples where the AOP framework has been proven useful for the human RA process, particularly in hazard prioritization and characterization, in integrated approaches to testing and assessment (IATA), and in the identification and validation of BoE in epidemiological studies. Nevertheless, several limitations were identified that hinder the optimal usability and acceptance of AOPs by the regulatory community including the lack of quantitative information on response-response relationships and of efficient ways to map chemical data (exposure and toxicity) onto AOPs. The paper summarizes suggestions, ongoing initiatives and third-party tools that may help to overcome these obstacles and thus assure better implementation of AOPs in the NGRA.

Environmental mixtures and breast cancer: identifying co-exposure patterns between understudied vs breast cancer-associated chemicals using chemical inventory informatics

BACKGROUND

Although evidence linking environmental chemicals to breast cancer is growing, mixtures-based exposure evaluations are lacking.

OBJECTIVE

This study aimed to identify environmental chemicals in use inventories that co-occur and share properties with chemicals that have association with breast cancer, highlighting exposure combinations that may alter disease risk.

METHODS

The occurrence of chemicals within chemical use categories was characterized using the Chemical and Products Database. Co-exposure patterns were evaluated for chemicals that have an association with breast cancer (BC), no known association (NBC), and understudied chemicals (UC) identified through query of the Silent Spring Institute's Mammary Carcinogens Review Database and the U.S. Environmental Protection Agency's Toxicity Reference Database. UCs were ranked based on structure and physicochemical similarities and co-occurrence patterns with BCs within environmentally relevant exposure sources.

RESULTS

A total of 6793 chemicals had data available for exposure source occurrence analyses. 50 top-ranking UCs spanning five clusters of co-occurring chemicals were prioritized, based on shared properties with co-occuring BCs, including chemicals used in food production and consumer/personal care products, as well as potential endocrine system modulators.

SIGNIFICANCE

Results highlight important co-exposure conditions that are likely prevalent within our everyday environments that warrant further evaluation for possible breast cancer risk.

IMPACT STATEMENT

Most environmental studies on breast cancer have focused on evaluating relationships between individual, well-known chemicals and breast cancer risk. This study set out to expand this research field by identifying understudied chemicals and mixtures that may occur in everyday environments due to their patterns of commercial use. Analyses focused on those that co-occur alongside chemicals associated with breast cancer, based upon in silico chemical database querying and analysis. Particularly in instances when understudied chemicals share physicochemical properties and structural features with carcinogens, these chemical mixtures represent conditions that should be studied in future clinical, epidemiological, and toxicological studies.

Environmental mixtures and breast cancer: identifying co-exposure patterns between understudied vs breast cancer-associated chemicals using chemical inventory informatics

BACKGROUND

Although evidence linking environmental chemicals to breast cancer is growing, mixtures-based exposure evaluations are lacking.

OBJECTIVE

This study aimed to identify environmental chemicals in use inventories that co-occur and share properties with chemicals that have association with breast cancer, highlighting exposure combinations that may alter disease risk.

METHODS

The occurrence of chemicals within chemical use categories was characterized using the Chemical and Products Database. Co-exposure patterns were evaluated for chemicals that have an association with breast cancer (BC), no known association (NBC), and understudied chemicals (UC) identified through query of the Silent Spring Institute's Mammary Carcinogens Review Database and the U.S. Environmental Protection Agency's Toxicity Reference Database. UCs were ranked based on structure and physicochemical similarities and co-occurrence patterns with BCs within environmentally relevant exposure sources.

RESULTS

A total of 6793 chemicals had data available for exposure source occurrence analyses. 50 top-ranking UCs spanning five clusters of co-occurring chemicals were prioritized, based on shared properties with co-occuring BCs, including chemicals used in food production and consumer/personal care products, as well as potential endocrine system modulators.

SIGNIFICANCE

Results highlight important co-exposure conditions that are likely prevalent within our everyday environments that warrant further evaluation for possible breast cancer risk.

IMPACT STATEMENT

Most environmental studies on breast cancer have focused on evaluating relationships between individual, well-known chemicals and breast cancer risk. This study set out to expand this research field by identifying understudied chemicals and mixtures that may occur in everyday environments due to their patterns of commercial use. Analyses focused on those that co-occur alongside chemicals associated with breast cancer, based upon in silico chemical database querying and analysis. Particularly in instances when understudied chemicals share physicochemical properties and structural features with carcinogens, these chemical mixtures represent conditions that should be studied in future clinical, epidemiological, and toxicological studies.

Computational model for fetal skeletal defects potentially linked to disruption of retinoic acid signaling

All-trans retinoic acid (ATRA) gradients determine skeletal patterning morphogenesis and can be disrupted by diverse genetic or environmental factors during pregnancy, leading to fetal skeleton defects. Adverse Outcome Pathway (AOP) frameworks for ATRA metabolism, signaling, and homeostasis allow for the development of new approach methods (NAMs) for predictive toxicology with less reliance on animal testing. Here, a data-driven model was constructed to identify chemicals associated with both ATRA pathway bioactivity and prenatal skeletal defects. The phenotype data was culled from ToxRefDB prenatal developmental toxicity studies and produced a list of 363 ToxRefDB chemicals with altered skeletal observations. Defects were classified regionally as cranial, post-cranial axial, appendicular, and other (unspecified) features based on ToxRefDB descriptors. To build a multivariate statistical model, high-throughput screening bioactivity data from >8,070 chemicals in ToxCast/Tox21 across 10 in vitro assays relevant to the retinoid signaling system were evaluated and compared to literature-based candidate reference chemicals in the dataset. There were 48 chemicals identified for effects on both in vivo skeletal defects and in vitro ATRA pathway targets for computational modeling. The list included 28 chemicals with prior evidence of skeletal defects linked to retinoid toxicity and 20 chemicals without prior evidence. The combination of thoracic cage defects and DR5 (direct repeats of 5 nucleotides for RAR/RXR transactivation) disruption was the most frequently occurring phenotypic and target disturbance, respectively. This data model provides valuable AOP elucidation and validates current mechanistic understanding. These findings also shed light on potential avenues for new mechanistic discoveries related to ATRA pathway disruption and associated skeletal dysmorphogenesis due to environmental exposures.

“In Litero” Screening: Retrospective Evaluation of Clinical Evidence to Establish a Reference List of Human Chemical Respiratory Sensitizers

Despite decades of investigation, test methods to identify respiratory sensitizers remain an unmet regulatory need. In order to support the evaluation of New Approach Methodologies in development, we sought to establish a reference set of low molecular weight respiratory sensitizers based on case reports of occupational asthma. In this context, we have developed an “in litero” approach to identify cases of low molecular weight chemical exposures leading to respiratory sensitization in clinical literature. We utilized the EPA-developed Abstract Sifter literature review tool to maximize the retrieval of publications relevant to respiratory effects in humans for each chemical in a list of chemicals suspected of inducing respiratory sensitization. The literature retrieved for each of these candidate chemicals was sifted to identify relevant case reports and studies, and then evaluated by applying defined selection criteria. Clinical diagnostic criteria were defined around exposure history, respiratory effects, and specific immune response to conclusively demonstrate occupational asthma as a result of sensitization, rather than irritation. This approach successfully identified 28 chemicals that can be considered as human respiratory sensitizers and used to evaluate the performance of NAMs as part of a weight of evidence approach to identify novel respiratory sensitizers. Further, these results have immediate implications for the development and refinement of predictive tools to distinguish between skin and respiratory sensitizers. A comparison of the protein binding mechanisms of our identified “in litero” clinical respiratory sensitizers shows that acylation is a prevalent protein binding mechanism, in contrast to Michael addition and Schiff base formation common to skin sensitizers. Overall, this approach provides an exemplary method to evaluate and apply human data as part of the weight of evidence when establishing reference chemical lists.

Identifying candidate reference chemicals for in vitro testing of the retinoid pathway for predictive developmental toxicity

Evaluating chemicals for potential in vivo toxicity based on their in vitro bioactivity profile is an important step toward animal- free testing. A compendium of reference chemicals and data describing their bioactivity on specific molecular targets, cellular pathways, and biological processes is needed to bolster confidence in the predictive value of in vitro hazard detection. Endogenous signaling by all-trans retinoic acid (ATRA) is an important pathway in developmental processes and toxicities. Employing data extraction methods and advanced literature extraction tools, we assembled a set of candidate reference chemicals with demonstrated activity on ten protein family targets in the retinoid system. The compendium was culled from Protein Data Bank, ChEMBL, ToxCast/Tox21, and the biomedical literature in PubMed. Finally, we performed a case study on one chemical in our collection, citral, an inhibitor of endogenous ATRA production, to determine whether the literature supports an adverse outcome pathway explaining the compound’s developmental toxicity initiated by disruption of the retinoid pathway. We also deliver an updated Abstract Sifter tool populated with these reference compounds and complex search terms designed to query the literature for the downstream consequences to support concordance with targeted retinoid pathway disruption.

Development of a Flame Retardant and an Organohalogen Flame Retardant Chemical Inventory

There have been many attempts to compile comprehensive lists of flame retardants. However, this goal has proven challenging due to the heterogeneity of compounds that can be used as flame retardants coupled with changes in formulation chemistry over time. Flame retardants have been the focus of many recent existing hazard, exposure, and risk assessments. These assessments have been class-based or for individual chemical substances. Here, diverse sets of publicly available data sources from governmental organizations and the open literature were compiled to develop an inventory of chemicals used as flame retardants and organohalogen flame retardants. The chemical substances from these data sources were mapped to appropriate chemical identifiers via manual curation and deduplicated. Despite different data sources containing a large number of overlapping chemical substances, compiling information from multiple data sources was found to increase the breadth of potential flame retardant chemistries. The flame retardant and organohalogen flame retardant inventories were developed as a resource for scientists interested in better understanding properties of flame retardant and organohalogen flame retardant classes.

Measurement(s)	chemical use information
Technology Type(s)	manual and automated literature collection

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

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

Developmental Neurotoxicity and Behavioral Screening in Larval Zebrafish with a Comparison to Other Published Results

With the abundance of chemicals in the environment that could potentially cause neurodevelopmental deficits, there is a need for rapid testing and chemical screening assays. This study evaluated the developmental toxicity and behavioral effects of 61 chemicals in zebrafish (Danio rerio) larvae using a behavioral Light/Dark assay. Larvae (n = 16-24 per concentration) were exposed to each chemical (0.0001-120 μM) during development and locomotor activity was assessed. Approximately half of the chemicals (n = 30) did not show any gross developmental toxicity (i.e., mortality, dysmorphology or non-hatching) at the highest concentration tested. Twelve of the 31 chemicals that did elicit developmental toxicity were toxic at the highest concentration only, and thirteen chemicals were developmentally toxic at concentrations of 10 µM or lower. Eleven chemicals caused behavioral effects; four chemicals (6-aminonicotinamide, cyclophosphamide, paraquat, phenobarbital) altered behavior in the absence of developmental toxicity. In addition to screening a library of chemicals for developmental neurotoxicity, we also compared our findings with previously published results for those chemicals. Our comparison revealed a general lack of standardized reporting of experimental details, and it also helped identify some chemicals that appear to be consistent positives and negatives across multiple laboratories.

Pluripotent stem cell assays: Modalities and applications for predictive developmental toxicity

This manuscript provides a review focused on embryonic stem cell-based models and their place within the landscape of alternative developmental toxicity assays. Against the background of the principles of developmental toxicology, the wide diversity of alternative methods using pluripotent stem cells developed in this area over the past half century is reviewed. In order to provide an overview of available models, a systematic scoping review was conducted following a published protocol with inclusion criteria, which were applied to select the assays. Critical aspects including biological domain, readout endpoint, availability of standardized protocols, chemical domain, reproducibility and predictive power of each assay are described in detail, in order to review the applicability and limitations of the platform in general and progress moving forward to implementation. The horizon of innovative routes of promoting regulatory implementation of alternative methods is scanned, and recommendations for further work are given.

Chemical Mixtures in Household Environments: In Silico Predictions and In Vitro Testing of Potential Joint Action on PPARγ in Human Liver Cells

There are thousands of chemicals that humans can be exposed to in their everyday environments, the majority of which are currently understudied and lack substantial testing for potential exposure and toxicity. This study aimed to implement in silico methods to characterize the chemicals that co-occur across chemical and product uses in our everyday household environments that also target a common molecular mediator, thus representing understudied mixtures that may exacerbate toxicity in humans. To detail, the Chemical and Products Database (CPDat) was queried to identify which chemicals co-occur across common exposure sources. Chemicals were preselected to include those that target an important mediator of cell health and toxicity, the peroxisome proliferator activated receptor gamma (PPARγ), in liver cells that were identified through query of the ToxCast/Tox21 database. These co-occurring chemicals were thus hypothesized to exert potential joint effects on PPARγ. To test this hypothesis, five commonly co-occurring chemicals (namely, benzyl cinnamate, butyl paraben, decanoic acid, eugenol, and sodium dodecyl sulfate) were tested individually and in combination for changes in the expression of PPARγ and its downstream target, insulin receptor (INSR), in human liver HepG2 cells. Results showed that these likely co-occurring chemicals in household environments increased both PPARγ and INSR expression more significantly when the exposures occurred as mixtures vs. as individual chemicals. Future studies will evaluate such chemical combinations across more doses, allowing for further quantification of the types of joint action while leveraging this method of chemical combination prioritization. This study demonstrates the utility of in silico-based methods to identify chemicals that co-occur in the environment for mixtures toxicity testing and highlights relationships between understudied chemicals and changes in PPARγ-associated signaling.

Beyond AOPs: A Mechanistic Evaluation of NAMs in DART Testing

New Approach Methodologies (NAMs) promise to offer a unique opportunity to enable human-relevant safety decisions to be made without the need for animal testing in the context of exposure-driven Next Generation Risk Assessment (NGRA). Protecting human health against the potential effects a chemical may have on embryo-foetal development and/or aspects of reproductive biology using NGRA is particularly challenging. These are not single endpoint or health effects and risk assessments have traditionally relied on data from Developmental and Reproductive Toxicity (DART) tests in animals. There are numerous Adverse Outcome Pathways (AOPs) that can lead to DART, which means defining and developing strict testing strategies for every AOP, to predict apical outcomes, is neither a tenable goal nor a necessity to ensure NAM-based safety assessments are fit-for-purpose. Instead, a pragmatic approach is needed that uses the available knowledge and data to ensure NAM-based exposure-led safety assessments are sufficiently protective. To this end, the mechanistic and biological coverage of existing NAMs for DART were assessed and gaps to be addressed were identified, allowing the development of an approach that relies on generating data relevant to the overall mechanisms involved in human reproduction and embryo-foetal development. Using the knowledge of cellular processes and signalling pathways underlying the key stages in reproduction and development, we have developed a broad outline of endpoints informative of DART. When the existing NAMs were compared against this outline to determine whether they provide comprehensive coverage when integrated in a framework, we found them to generally cover the reproductive and developmental processes underlying the traditionally evaluated apical endpoint studies. The application of this safety assessment framework is illustrated using an exposure-led case study.

Comparing the performance and coverage of selected in silico (liver) metabolism tools relative to reported studies in the literature to inform analogue selection in read-across: A case study

Changes in the regulatory landscape of chemical safety assessment call for the use of New Approach Methodologies (NAMs) including read-across to fill data gaps. One critical aspect of analogue evaluation is the extent to which target and source analogues are metabolically similar. In this study, a set of 37 structurally diverse chemicals were compiled from the EPA ToxCast inventory to compare and contrast a selection of metabolism in silico tools, in terms of their coverage and performance relative to metabolism information reported in the literature. The aim was to build understanding of the scope and capabilities of these tools and how they could be utilised in a read-across assessment. The tools were Systematic Generation of Metabolites (SyGMa), Meteor Nexus, BioTransformer, Tissue Metabolism Simulator (TIMES), OECD Toolbox, and Chemical Transformation Simulator (CTS). Performance was characterised by sensitivity and precision determined by comparing predictions against literature reported metabolites (from 44 publications). A coverage score was derived to provide a relative quantitative comparison between the tools. Meteor, TIMES, Toolbox, and CTS predictions were run in batch mode, using default settings. SyGMa and BioTransformer were run with user-defined settings, (two passes of phase I and one pass of phase II). Hierarchical clustering revealed high similarity between TIMES and Toolbox. SyGMa had the highest coverage, matching an average of 38.63% of predictions generated by the other tools though was prone to significant overprediction. It generated 5,125 metabolites, which represented 54.67% of all predictions. Precision and sensitivity values ranged from 1.1-29% and 14.7-28.3% respectively. The Toolbox had the highest performance overall. A case study was presented for 3,4-Toluenediamine (3,4-TDA), assessed for the derivation of screening-level Provisional Peer Reviewed Toxicity Values (PPRTVs), was used to demonstrate the practical role in silico metabolism information can play in analogue evaluation as part of a read-across approach.

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

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

AOP-helpFinder webserver: a tool for comprehensive analysis of the literature to support adverse outcome pathways development

MOTIVATION

Adverse outcome pathways (AOPs) are a conceptual framework developed to support the use of alternative toxicology approaches in the risk assessment. AOPs are structured linear organizations of existing knowledge illustrating causal pathways from the initial molecular perturbation triggered by various stressors, through key events (KEs) at different levels of biology, to the ultimate health or ecotoxicological adverse outcome.

RESULTS

Artificial intelligence can be used to systematically explore available toxicological data that can be parsed in the scientific literature. Recently, a tool called AOP-helpFinder was developed to identify associations between stressors and KEs supporting thus documentation of AOPs. To facilitate the utilization of this advanced bioinformatics tool by the scientific and the regulatory community, a webserver was created. The proposed AOP-helpFinder webserver uses better performing version of the tool which reduces the need for manual curation of the obtained results. As an example, the server was successfully applied to explore relationships of a set of endocrine disruptors with metabolic-related events. The AOP-helpFinder webserver assists in a rapid evaluation of existing knowledge stored in the PubMed database, a global resource of scientific information, to build AOPs and Adverse Outcome Networks supporting the chemical risk assessment.

AVAILABILITY AND IMPLEMENTATION

AOP-helpFinder is available at http://aop-helpfinder.u-paris-sciences.fr/index.php.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Sourcing data on chemical properties and hazard data from the US-EPA CompTox Chemicals Dashboard: A practical guide for human risk assessment

For the past six decades, human health risk assessment of chemicals has relied on in vivo data from human epidemiological and experimental animal toxicological studies to inform the derivation of non-cancer toxicity values. The ongoing evolution of this risk assessment paradigm in an environmental landscape of data-poor chemicals has highlighted the need to develop and implement non-testing methods, so-called New Approach Methodologies (NAMs). NAMs include a growing number of in silico and in vitro data streams designed to inform hazard properties of chemicals, including kinetics and dynamics at different levels of biological organization, environmental fate and transport, and exposure. NAMs provide a fit-for-purpose science-basis for human hazard and risk characterization of chemicals ranging from data-gap filling applications to broad evidence-based decision-making. Systematic assembly and delivery of empirical and predicted data for chemicals are paramount to advancing chemical evaluation, and software tools serve an essential role in delivering these data to the scientific community. The CompTox Chemicals Dashboard (from here on referred to as the "Dashboard") is one such tool and is a publicly available web-based application developed by the US Environmental Protection Agency to provide access to chemistry, toxicity and exposure information for ~900,000 chemicals. The Dashboard is increasingly becoming a valuable resource for assessors tasked with the evaluation of potential human health risks associated with chemical exposures. In this context, the significant amount of information present in the Dashboard facilitates: 1) assembly of information on physicochemical properties and environmental fate and transport and exposure parameters and metrics; 2) identification of cancer and non-cancer health effects from extant human and experimental animal studies in the public domain and/or information not available in the public domain (i.e., "grey literature"); 3) systematic literature searching and review for developing cancer and non-cancer hazard evidence bases; and 4) access to mechanistic information that can aid or augment the analysis of traditional toxicology evidence bases, or potentially, serve as the primary basis for informing hazard identification and dose-response when traditional bioassay data are lacking. Finally, in silico predictive tools developed to conduct structure-activity or read-across analyses are also available within the Dashboard. This practical tutorial is intended to address key questions from the human health risk assessment community dealing with chemicals in both food and in the environment. Perspectives for future development or refinement of the Dashboard highlight foreseen activities to further support the research and risk assessment community in cancer and non-cancer chemical evaluations.

Chlorpyrifos and Δ9 Tetrahydrocannabinol exposure and effects on parameters associated with the endocannabinoid system and risk factors for obesity

Marilyn Silva. Retired from a career in toxicology and risk assessment. Increased childhood and adult obesity are associated with chlorpyrifos (CPF), an organophosphate pesticide. Cannabis (Δ9Tetrahydrocannabinol: Δ9THC) use has increased globally with legalization. CPF applications on cannabis crops lacks federally regulated tolerances and may pose health risks through exposure during development and in adulthood. Both CPF and Δ9THC affect the endocannabinoid system (eCBS), a regulator of appetite, energy balance, and gut microbiota, which, if disrupted, increases risk for obesity and related diseases. CPF inhibits eCB metabolism and Δ9THC is a partial agonist/antagonist at the cannabinoid receptor (CB1R). Effects of each on obesogenic parameters were examined via literature search. Male rodents with CPF exposure showed increased body weights, dysbiosis, inflammation and oxidative stress, potentially associated with increased eCBs acting through the gut-microbiota-adipose-brain regulatory loop. Δ9THC generally decreased body weights via partial agonism at the CB1R, lowering levels of eCBs. Dysbiosis and/or oxidative stress associated inflammation occurred with CPF, but these parameters were not tested with Δ9THC. Database deficiencies included limited endpoints to compare between chemicals/age-groups, inter-study variables (dose ranges, dosing vehicle, rodent strain, treatment duration, etc.). CPF and Δ9THC were not tested together, but human co-chemical effects would depend on exposure ratio, subject age, exposure duration, and health status, among others. An overriding concern is that both chemicals are well-documented developmental neurotoxins in addition to their low dose effects on energy balance. A co-exposure risk assessment is warranted with increased use and lack of federal CPF regulation on cannabis.

Using the US EPA CompTox Chemicals Dashboard to interpret targeted and non-targeted GC-MS analyses from human breath and other biological media

The U.S. EPA CompTox Chemicals Dashboard is a freely available web-based application providing access to chemistry, toxicity, and exposure data for ∼900 000 chemicals. Data, search functionality, and prediction models within the Dashboard can help identify chemicals found in environmental analyses and human biomonitoring. It was designed to deliver data generated to support computational toxicology to reduce chemical testing on animals and provide access to new approach methodologies including prediction models. The inclusion of mass and formula-based searches, together with relevant ranking approaches, allows for the identification and prioritization of exogenous (environmental) chemicals from high resolution mass spectrometry in need of further evaluation. The Dashboard includes chemicals that can be detected by liquid chromatography, gas chromatography-mass spectrometry (GC-MS) and direct-MS analyses, and chemical lists have been added that highlight breath-borne volatile and semi-volatile organic compounds. The Dashboard can be searched using various chemical identifiers (e.g. chemical synonyms, CASRN and InChIKeys), chemical formula, MS-ready formulae monoisotopic mass, consumer product categories and assays/genes associated with high-throughput screening data. An integrated search at a chemical level performs searches against PubMed to identify relevant published literature. This article describes specific procedures using the Dashboard as a first-stop tool for exploring both targeted and non-targeted results from GC-MS analyses of chemicals found in breath, exhaled breath condensate, and associated aerosols.

Evaluation of Fetal Exposures to Metals and Metalloids through Meconium Analyses: A Review

This paper surveys the existing scientific literature on metals concentrations in meconium. We examine some 32 papers that analyzed meconium for aluminum, arsenic, barium, calcium, chromium, copper, iron, lithium, magnesium, manganese, zinc, lead, mercury, manganese, molybdenum, nickel, phosphorus, lead, antimony, selenium, tin, vanadium, and zinc. Because of the lack of detail in the statistics it is not possible to do a rigorous meta-analysis. What stands out is that almost every study had subjects with seemingly large amounts of at least one of the metals. The significance of metals in meconium is not clear beyond an indication of exposure although some studies have correlated metals in meconium to a number of adverse outcomes. A number of outstanding questions have been identified that, if resolved, would greatly increase the utility of meconium analysis for assessment of long-term gestational metals exposures. Among these are questions of the developmental and long-term significance of metals detected in meconium, the kinetics and interactions among metals in maternal and fetal compartments and questions on best methods for meconium analyses.

Enabling High-Throughput Searches for Multiple Chemical Data Using the U.S.-EPA CompTox Chemicals Dashboard

The core goal of cheminformatics is to efficiently store robust and accurate chemical information and make it accessible for drug discovery, environmental analysis, and the development of prediction models including quantitative structure-activity relationships (QSAR). The U.S. Environmental Protection Agency (EPA) has developed a web-based application, the CompTox Chemicals Dashboard, which provides access to a compilation of data generated within the agency and sourced from public databases and literature and to utilities for real-time QSAR prediction and chemical read-across. While the vast majority of online tools only allow interrogation of chemicals one at a time, the Dashboard provides a batch search feature that allows for the sourcing of data based on thousands of chemical inputs at one time, by chemical identifier (e.g., names, Chemical Abstract Service registry numbers, or InChIKeys), or by mass or molecular formulas. Chemical information that can then be sourced via the batch search includes chemical identifiers and structures; intrinsic, physicochemical and fate and transport properties; in vitro and in vivo toxicity data; and the presence in environmentally relevant lists. We outline how to use the batch search feature and provide an overview regarding the type of information that can be sourced by considering a series of typical-use questions.

Retinoid signaling in skeletal development: Scoping the system for predictive toxicology

All-trans retinoic acid (ATRA), the biologically active form of vitamin A, is instrumental in regulating the patterning and specification of the vertebrate embryo. Various animal models demonstrate adverse developmental phenotypes following experimental retinoid depletion or excess during pregnancy. Windows of vulnerability for altered skeletal patterning coincide with early specification of the body plan (gastrulation) and regional specification of precursor cell populations forming the facial skeleton (cranial neural crest), vertebral column (somites), and limbs (lateral plate mesoderm) during organogenesis. A common theme in physiological roles of ATRA signaling is mutual antagonism with FGF signaling. Consequences of genetic errors or environmental disruption of retinoid signaling include stage- and region-specific homeotic transformations to severe deficiencies for various skeletal elements. This review derives from an annex in Detailed Review Paper (DRP) of the OECD Test Guidelines Programme (Project 4.97) to support recommendations regarding assay development for the retinoid system and the use of resulting data in a regulatory context for developmental and reproductive toxicity (DART) testing.

Computational Biology and in silico Toxicodynamics

New approach methodologies (NAMs) refer to any non-animal technology, methodology, approach, or combination thereof that can be used to provide information on chemical hazard and risk assessment that avoids the use of intact animals. A spectrum of in silico models is needed for the integrated analysis of various domains in toxicology to improve predictivity and reduce animal testing. This review focuses on in silico approaches, computer models, and computational intelligence for developmental and reproductive toxicity (predictive DART), providing a means to measure toxicodynamics in simulated systems for quantitative prediction of adverse outcomes phenotypes.

Computational identification of preservatives with potential neuronal cytotoxicity

Preservatives play a vital role in cosmetics by preventing microbiological contamination for keeping products safe to use. However, a few commonly used preservatives have been suggested to be neurotoxic. Cytotoxicity to neuronal cells is commonly used as the first-tier assay for assessing chemical-induced neurotoxicity. Given the time and resources required for chemical screening, computational methods are attractive alternatives over experimental approaches in prioritizing chemicals prior to further experimental evaluations. In this study, we developed a Quantitative Structure-Activity Relationships (QSAR) model for the identification of potential neurotoxicants. A set of 681 chemicals was utilized to construct a robust prediction model using oversampling and Random Forest algorithms. Within a defined applicability domain, the independent test on 452 chemicals showed a high accuracy of 87.7%. The application of the model to 157 preservatives identified 15 chemicals potentially toxic to neuronal cells. Three of them were further validated by in vitro experiments. The results suggested that further experiments are desirable for assessing the neurotoxicity of the identified preservatives with potential neuronal cytotoxicity.

An ontology for developmental processes and toxicities of neural tube closure

In recent years, the development and implementation of animal-free approaches to chemical and pharmaceutical hazard and risk assessment has taken off. Alternative approaches are being developed starting from the perspective of human biology and physiology. Neural tube closure is a vital step that occurs early in human development. Correct closure of the neural tube depends on a complex interplay between proteins along a number of protein concentration gradients. The sensitivity of neural tube closure to chemical disturbance of signalling pathways such as the retinoid pathway, is well known. To map the pathways underlying neural tube closure, literature data on the molecular regulation of neural tube closure were collected. As the process of neural tube closure is highly conserved in vertebrates, the extensive literature available for the mouse was used whilst considering its relevance for humans. Thus, important cell compartments, regulatory pathways, and protein interactions essential for neural tube closure under physiological circumstances were identified and mapped. An understanding of aberrant processes leading to neural tube defects (NTDs) requires detailed maps of neural tube embryology, including the complex genetic signals and responses underlying critical cellular dynamical and biomechanical processes. The retinoid signaling pathway serves as a case study for this ontology because of well-defined crosstalk with the genetic control of neural tube patterning and morphogenesis. It is a known target for mechanistically-diverse chemical structures that disrupt neural tube closure The data presented in this manuscript will set the stage for constructing mathematical models and computer simulation of neural tube closure for human-relevant AOPs and predictive toxicology.

Endocrine-disrupting chemicals rapidly affect intercellular signaling in Leydig cells

A decline in male fertility possibly caused by environmental contaminants, namely endocrine-disrupting chemicals (EDCs), is a topic of public concern and scientific interest. This study addresses a specific role of testicular gap junctional intercellular communication (GJIC) between adjacent prepubertal Leydig cells in endocrine disruption and male reproductive toxicity. Organochlorine pesticides (lindane, methoxychlor, DDT), industrial chemicals (PCB153, bisphenol A, nonylphenol and octylphenol) as well as personal care product components (triclosan, triclocarban) rapidly dysregulated GJIC in murine Leydig TM3 cells. The selected GJIC-inhibiting EDCs (methoxychlor, triclosan, triclocarban, lindane, DDT) caused the immediate GJIC disruption by the relocation of gap junctional protein connexin 43 (Cx43) from the plasma membrane and the alternation of Cx43 phosphorylation pattern (Ser368, Ser279, Ser282) of its full-length and two N-truncated isoforms. After more prolonged exposure (24 h), EDCs decreased steady-state levels of full-length Cx43 protein and its two N-truncated isoforms, and eventually (triclosan, triclocarban) also tight junction protein Tjp-1. The disturbance of GJIC was accompanied by altered activity of mitogen-activated protein kinases MAPK-Erk1/2 and MAPK-p38, and a decrease in stimulated progesterone production. Our results indicate that EDCs might disrupt testicular homeostasis and development via disruption of testicular GJIC, a dysregulation of junctional and non-junctional functions of Cx43, activation of MAPKs, and disruption of an early stage of steroidogenesis in prepubertal Leydig cells. These critical disturbances of Leydig cell development and functions during a prepubertal period might be contributing to impaired male reproduction health later on.

Respirometric Screening and Characterization of Mitochondrial Toxicants Within the ToxCast Phase I and II Chemical Libraries

Mitochondrial toxicity drives several adverse health outcomes. Current high-throughput screening assays for chemically induced mitochondrial toxicity typically measure changes to mitochondrial structure and may not detect known mitochondrial toxicants. We adapted a respirometric screening assay (RSA) measuring mitochondrial function to screen ToxCast chemicals in HepG2 cells using a tiered testing strategy. Of 1042 chemicals initially screened at a singlemaximal concentration, 243 actives were identified and rescreened at 7 concentrations. Concentration-response data for 3 respiration phases confirmed activity and indicated a mechanism for 193 mitochondrial toxicants: 149 electron transport chain inhibitors (ETCi), 15 uncouplers and 29 adenosine triphosphate synthase inhibitors. Subsequently, an electron flow assay was used to identify the target complex for 84 of the 149 ETCi. Sixty reference chemicals were used to compare the RSA to existing ToxCast and Tox21 mitochondrial toxicity assays. The RSA was most predictive (accuracy = 90%) of mitochondrial toxicity. The Tox21 mitochondrial membrane potential assay was also highly predictive (accuracy = 87%) of bioactivity but underestimated the potency of well-known ETCi and provided no mechanistic information. The tiered RSA approach accurately identifies and characterizes mitochondrial toxicants acting through diverse mechanisms and at a throughput sufficient to screen large chemical inventories. The electron flow assay provides additional confirmation and detailed mechanistic understanding for ETCi, the most common type of mitochondrial toxicants among ToxCast chemicals. The mitochondrial toxicity screening approach described herein may inform hazard assessment and the in vitro bioactive concentrations used to derive relevant doses for screening level chemical assessment using new approach methodologies.

EPA's DSSTox database: History of development of a curated chemistry resource supporting computational toxicology research

The US Environmental Protection Agency's (EPA) Distributed Structure-Searchable Toxicity (DSSTox) database, launched publicly in 2004, currently exceeds 875 K substances spanning hundreds of lists of interest to EPA and environmental researchers. From its inception, DSSTox has focused curation efforts on resolving chemical identifier errors and conflicts in the public domain towards the goal of assigning accurate chemical structures to data and lists of importance to the environmental research and regulatory community. Accurate structure-data associations, in turn, are necessary inputs to structure-based predictive models supporting hazard and risk assessments. In 2014, the legacy, manually curated DSSTox_V1 content was migrated to a MySQL data model, with modern cheminformatics tools supporting both manual and automated curation processes to increase efficiencies. This was followed by sequential auto-loads of filtered portions of three public datasets: EPA's Substance Registry Services (SRS), the National Library of Medicine's ChemID, and PubChem. This process was constrained by a key requirement of uniquely mapped identifiers (i.e., CAS RN, name and structure) for each substance, rejecting content where any two identifiers were conflicted either within or across datasets. This rejected content highlighted the degree of conflicting, inaccurate substance-structure ID mappings in the public domain, ranging from 12% (within EPA SRS) to 49% (across ChemID and PubChem). Substances successfully added to DSSTox from each auto-load were assigned to one of five qc_levels, conveying curator confidence in each dataset. This process enabled a significant expansion of DSSTox content to provide better coverage of the chemical landscape of interest to environmental scientists, while retaining focus on the accuracy of substance-structure-data associations. Currently, DSSTox serves as the core foundation of EPA's CompTox Chemicals Dashboard [https://comptox.epa.gov/dashboard], which provides public access to DSSTox content in support of a broad range of modeling and research activities within EPA and, increasingly, across the field of computational toxicology.

Progress in data interoperability to support computational toxicology and chemical safety evaluation

New approach methodologies (NAMs) in chemical safety evaluation are being explored to address the current public health implications of human environmental exposures to chemicals with limited or no data for assessment. For over a decade since a push toward "Toxicity Testing in the 21st Century," the field has focused on massive data generation efforts to inform computational approaches for preliminary hazard identification, adverse outcome pathways that link molecular initiating events and key events to apical outcomes, and high-throughput approaches to risk-based ratios of bioactivity and exposure to inform relative priority and safety assessment. Projects like the interagency Tox21 program and the US EPA ToxCast program have generated dose-response information on thousands of chemicals, identified and aggregated information from legacy systems, and created tools for access and analysis. The resulting information has been used to develop computational models as viable options for regulatory applications. This progress has introduced challenges in data management that are new, but not unique, to toxicology. Some of the key questions require critical thinking and solutions to promote semantic interoperability, including: (1) identification of bioactivity information from NAMs that might be related to a biological process; (2) identification of legacy hazard information that might be related to a key event or apical outcomes of interest; and, (3) integration of these NAM and traditional data for computational modeling and prediction of complex apical outcomes such as carcinogenesis. This work reviews a number of toxicology-related efforts specifically related to bioactivity and toxicological data interoperability based on the goals established by Findable, Accessible, Interoperable, and Reusable (FAIR) Data Principles. These efforts are essential to enable better integration of NAM and traditional toxicology information to support data-driven toxicology applications.

Characterizing cleft palate toxicants using ToxCast data, chemical structure, and the biomedical literature

Cleft palate has been linked to both genetic and environmental factors that perturb key events during palatal morphogenesis. As a developmental outcome, it presents a challenging, mechanistically complex endpoint for predictive modeling. A data set of 500 chemicals evaluated for their ability to induce cleft palate in animal prenatal developmental studies was compiled from Toxicity Reference Database and the biomedical literature, which included 63 cleft palate active and 437 inactive chemicals. To characterize the potential molecular targets for chemical-induced cleft palate, we mined the ToxCast high-throughput screening database for patterns and linkages in bioactivity profiles and chemical structural descriptors. ToxCast assay results were filtered for cytotoxicity and grouped by target gene activity to produce a "gene score." Following unsuccessful attempts to derive a global prediction model using structural and gene score descriptors, hierarchical clustering was applied to the set of 63 cleft palate positives to extract local structure-bioactivity clusters for follow-up study. Patterns of enrichment were confirmed on the complete data set, that is, including cleft palate inactives, and putative molecular initiating events identified. The clusters corresponded to ToxCast assays for cytochrome P450s, G-protein coupled receptors, retinoic acid receptors, the glucocorticoid receptor, and tyrosine kinases/phosphatases. These patterns and linkages were organized into preliminary decision trees and the resulting inferences were mapped to a putative adverse outcome pathway framework for cleft palate supported by literature evidence of current mechanistic understanding. This general data-driven approach offers a promising avenue for mining chemical-bioassay drivers of complex developmental endpoints where data are often limited.

Microbiota alter metabolism and mediate neurodevelopmental toxicity of 17β-estradiol

Estrogenic chemicals are widespread environmental contaminants associated with diverse health and ecological effects. During early vertebrate development, estrogen receptor signaling is critical for many different physiologic responses, including nervous system function. Recently, host-associated microbiota have been shown to influence neurodevelopment. Here, we hypothesized that microbiota may biotransform exogenous 17-βestradiol (E2) and modify E2 effects on swimming behavior. Colonized zebrafish were continuously exposed to non-teratogenic E2 concentrations from 1 to 10 days post-fertilization (dpf). Changes in microbial composition and predicted metagenomic function were evaluated. Locomotor activity was assessed in colonized and axenic (microbe-free) zebrafish exposed to E2 using a standard light/dark behavioral assay. Zebrafish tissue was collected for chemistry analyses. While E2 exposure did not alter microbial composition or putative function, colonized E2-exposed larvae showed reduced locomotor activity in the light, in contrast to axenic E2-exposed larvae, which exhibited normal behavior. Measured E2 concentrations were significantly higher in axenic relative to colonized zebrafish. Integrated peak area for putative sulfonated and glucuronidated E2 metabolites showed a similar trend. These data demonstrate that E2 locomotor effects in the light phase are dependent on the presence of microbiota and suggest that microbiota influence chemical E2 toxicokinetics. More broadly, this work supports the concept that microbial colonization status may influence chemical toxicity.

Workflow for defining reference chemicals for assessing performance of in vitro assays

Instilling confidence in use of in vitro assays for predictive toxicology requires evaluation of assay performance. Performance is typically assessed using reference chemicals--compounds with defined activity against the test system target. However, developing reference chemical lists has historically been very resource-intensive. We developed a semi-automated process for selecting and annotating reference chemicals across many targets in a standardized format and demonstrate the workflow here. A series of required fields defines the potential reference chemical: the in vitro molecular target, pathway, or phenotype affected; and the chemical's mode (e.g. agonist, antagonist, inhibitor). Activity information was computationally extracted into a database from multiple public sources including non-curated scientific literature and curated chemical-biological databases, resulting in the identification of chemical activity in 2995 biological targets. Sample data from literature sources covering 54 molecular targets ranging from data-poor to data-rich was manually checked for accuracy. Precision rates were 82.7% from curated data sources and 39.5% from automated literature extraction. We applied the final reference chemical lists to evaluating performance of EPA's ToxCast program in vitro bioassays. The level of support, i.e. the number of independent reports in the database linking a chemical to a target, was found to strongly correlate with likelihood of positive results in the ToxCast assays, although individual assay performance had considerable variation. This overall approach allows rapid development of candidate reference chemical lists for a wide variety of targets that can facilitate performance evaluation of in vitro assays as a critical step in imparting confidence in alternative approaches.

An ecotoxicological view on neurotoxicity assessment

The numbers of potential neurotoxicants in the environment are raising and pose a great risk for humans and the environment. Currently neurotoxicity assessment is mostly performed to predict and prevent harm to human populations. Despite all the efforts invested in the last years in developing novel in vitro or in silico test systems, in vivo tests with rodents are still the only accepted test for neurotoxicity risk assessment in Europe. Despite an increasing number of reports of species showing altered behaviour, neurotoxicity assessment for species in the environment is not required and therefore mostly not performed. Considering the increasing numbers of environmental contaminants with potential neurotoxic potential, eco-neurotoxicity should be also considered in risk assessment. In order to do so novel test systems are needed that can cope with species differences within ecosystems. In the field, online-biomonitoring systems using behavioural information could be used to detect neurotoxic effects and effect-directed analyses could be applied to identify the neurotoxicants causing the effect. Additionally, toxic pressure calculations in combination with mixture modelling could use environmental chemical monitoring data to predict adverse effects and prioritize pollutants for laboratory testing. Cheminformatics based on computational toxicological data from in vitro and in vivo studies could help to identify potential neurotoxicants. An array of in vitro assays covering different modes of action could be applied to screen compounds for neurotoxicity. The selection of in vitro assays could be guided by AOPs relevant for eco-neurotoxicity. In order to be able to perform risk assessment for eco-neurotoxicity, methods need to focus on the most sensitive species in an ecosystem. A test battery using species from different trophic levels might be the best approach. To implement eco-neurotoxicity assessment into European risk assessment, cheminformatics and in vitro screening tests could be used as first approach to identify eco-neurotoxic pollutants. In a second step, a small species test battery could be applied to assess the risks of ecosystems.