Concurrent Evaluation of Mortality and Behavioral Responses: A Fast and Efficient Testing Approach for High-Throughput Chemical Hazard Identification

Developmental toxicity of alkylated PAHs and substituted phenanthrenes: Structural nuances drive diverse toxicity and AHR activation

Polycyclic aromatic hydrocarbons (PAHs) are a diverse class of chemicals that occur in complex mixtures including parent and substituted PAHs. To understand the hazard posed by complex environmental PAH mixtures, we must first understand the structural drivers of activity and mode of action of individual PAHs. Understanding the toxicity of alkylated PAHs is important as they often occur in higher abundance in environmental matrices and can be more biologically active than their parent compounds. 104 alkylated PAHs were screened from 11 different parent compounds with emphasis on substituted phenanthrenes and their structurally dependent toxicity differences. Using a high-throughput early life stage zebrafish assay, embryos were exposed to concentrations between 0.1 and 100 μM and assessed for morphological and behavioral outcomes. The aryl hydrocarbon receptor (AHR) is often implicated in the toxicity of PAHs and the induction of cytochrome P4501A (cyp1a) is an excellent biomarker of Ahr activation. Embryos were evaluated for cyp1a induction using a fluorescence reporter line. Alkyl and polar phenanthrene derivatives were further assessed for spatial cyp1a expression and Ahr dependence of morphological effects. In the alkyl PAH screen 35 (33.7%) elicited a morphological or behavioral response and of those 23 (65%) also induced cyp1a. 31 (29.8%) of the chemicals only induced cyp1a. Toxicity varied substantially in response to substitution location, the amount of ring substitutions and alkyl chain length. Cyp1a induction varied by parent compound group and was a poor indicator of morphological or behavioral outcomes. Polar phenanthrenes were more biologically active than alkylated phenanthrene derivatives and their toxicity was not dependent upon the Ahr2, Ahr1a or Ahr1b when tested individually, despite cyp1a induction by 50% of polar phenanthrenes. Our results demonstrated that induction of cyp1a did not always correlate with PAH toxicity or Ahr dependence and that the type and location of phenanthrene substitution determined potency.

Inhibition of Neural Crest Cell Migration by Strobilurin Fungicides and Other Mitochondrial Toxicants

Cell-based test methods with a phenotypic readout are frequently used for toxicity screening. However, guidance on how to validate the hits and how to integrate this information with other data for purposes of risk assessment is missing. We present here such a procedure and exemplify it with a case study on neural crest cell (NCC)-based developmental toxicity of picoxystrobin. A library of potential environmental toxicants was screened in the UKN2 assay, which simultaneously measures migration and cytotoxicity in NCC. Several strobilurin fungicides, known as inhibitors of the mitochondrial respiratory chain complex III, emerged as specific hits. From these, picoxystrobin was chosen to exemplify a roadmap leading from cell-based testing towards toxicological predictions. Following a stringent confirmatory testing, an adverse outcome pathway was developed to provide a testable toxicity hypothesis. Mechanistic studies showed that the oxygen consumption rate was inhibited at sub-µM picoxystrobin concentrations after a 24 h pre-exposure. Migration was inhibited in the 100 nM range, under assay conditions forcing cells to rely on mitochondria. Biokinetic modeling was used to predict intracellular concentrations. Assuming an oral intake of picoxystrobin, consistent with the acceptable daily intake level, physiologically based kinetic modeling suggested that brain concentrations of 0.1-1 µM may be reached. Using this broad array of hazard and toxicokinetics data, we calculated a margin of exposure ≥ 80 between the lowest in vitro point of departure and the highest predicted tissue concentration. Thus, our study exemplifies a hit follow-up strategy and contributes to paving the way to next-generation risk assessment.

Deep autoencoder-based behavioral pattern recognition outperforms standard statistical methods in high-dimensional zebrafish studies

Zebrafish have become an essential model organism in screening for developmental neurotoxic chemicals and their molecular targets. The success of zebrafish as a screening model is partially due to their physical characteristics including their relatively simple nervous system, rapid development, experimental tractability, and genetic diversity combined with technical advantages that allow for the generation of large amounts of high-dimensional behavioral data. These data are complex and require advanced machine learning and statistical techniques to comprehensively analyze and capture spatiotemporal responses. To accomplish this goal, we have trained semi-supervised deep autoencoders using behavior data from unexposed larval zebrafish to extract quintessential "normal" behavior. Following training, our network was evaluated using data from larvae shown to have significant changes in behavior (using a traditional statistical framework) following exposure to toxicants that include nanomaterials, aromatics, per- and polyfluoroalkyl substances (PFAS), and other environmental contaminants. Further, our model identified new chemicals (Perfluoro-n-octadecanoic acid, 8-Chloroperfluorooctylphosphonic acid, and Nonafluoropentanamide) as capable of inducing abnormal behavior at multiple chemical-concentrations pairs not captured using distance moved alone. Leveraging this deep learning model will allow for better characterization of the different exposure-induced behavioral phenotypes, facilitate improved genetic and neurobehavioral analysis in mechanistic determination studies and provide a robust framework for analyzing complex behaviors found in higher-order model systems.

Utilizing a Population-Genetic Framework to Test for Gene-Environment Interactions between Zebrafish Behavior and Chemical Exposure

Individuals within genetically diverse populations display broad susceptibility differences upon chemical exposures. Understanding the role of gene-environment interactions (GxE) in differential susceptibility to an expanding exposome is key to protecting public health. However, a chemical's potential to elicit GxE is often not considered during risk assessment. Previously, we've leveraged high-throughput zebrafish (Danio rerio) morphology screening data to reveal patterns of potential GxE effects. Here, using a population genetics framework, we apportioned variation in larval behavior and gene expression in three different PFHxA environments via mixed-effect modeling to assess significance of GxE term. We estimated the intraclass correlation (ICC) between full siblings from different families using one-way random-effects model. We found a significant GxE effect upon PFHxA exposure in larval behavior, and the ICC of behavioral responses in the PFHxA exposed population at the lower concentration was 43.7%, while that of the control population was 14.6%. Considering global gene expression data, a total of 3746 genes showed statistically significant GxE. By showing evidence that heritable genetics are directly affecting gene expression and behavioral susceptibility of individuals to PFHxA exposure, we demonstrate how standing genetic variation in a heterogeneous population such as ours can be leveraged to test for potential GxE.

Systematic developmental toxicity assessment of a structurally diverse library of PFAS in zebrafish

Per- and polyfluoroalkyl substances (PFAS) are a class of widely used chemicals with limited human health effects data relative to the diversity of structures manufactured. To help fill this data gap, an extensive in vivo developmental toxicity screen was performed on 139 PFAS provided by the US EPA. Dechorionated embryonic zebrafish were exposed to 10 nominal water concentrations of PFAS (0.015-100 µM) from 6 to 120 h post-fertilization (hpf). The embryos were assayed for embryonic photomotor response (EPR), larval photomotor response (LPR), and 13 morphological endpoints. A total of 49 PFAS (35%) were bioactive in one or more assays (11 altered EPR, 25 altered LPR, and 31 altered morphology). Perfluorooctanesulfonamide (FOSA) was the only structure that was bioactive in all 3 assays, while Perfluorodecanoic acid (PFDA) was the most potent teratogen. Low PFAS volatility was associated with developmental toxicity (p < 0.01), but no association was detected between bioactivity and five other physicochemical parameters. The bioactive PFAS were enriched for 6 supergroup chemotypes. The results illustrate the power of a multi-dimensional in vivo platform to assess the developmental (neuro)toxicity of diverse PFAS and in the acceleration of PFAS safety research.