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.

AHR Dependent Toxicity by Retene Requires Metabolic Competence.

Polycyclic aromatic hydrocarbons (PAHs) are a class of organic compounds frequently detected in the environment with widely varying toxicities. Many PAHs activate the aryl hydrocarbon receptor (AHR), inducing the expression of a battery of genes, including xenobiotic metabolizing enzymes like Cytochrome P450s (CYPs); however, not all PAHs act via this mechanism. We screened several parent and substituted PAHs in in vitro AHR activation assays to classify their unique activity. Retene (1-methyl-7-isopropylphenanthrene) displays Ahr2 dependent teratogenicity in zebrafish, but did not activate human AHR or zebrafish Ahr2, suggesting a retene metabolite activates Ahr2 in zebrafish to induce developmental toxicity. To investigate the role of metabolism in retene toxicity, studies were performed to determine the functional role of cyp1a, cyp1b1, and the microbiome in retene toxicity, identify the zebrafish window of susceptibility, and measure retene uptake, loss, and metabolite formation in vivo. Cyp1a-null fish were generated using CRISPR-Cas9. Cyp1a-null fish showed increased sensitivity to retene toxicity, while Cyp1b1-null fish were less susceptible, and microbiome elimination had no significant effect. Zebrafish required exposure to retene between 24 and 48 hours post fertilization (hpf) to exhibit toxicity. After static exposure, retene concentrations in zebrafish embryos increased until 24 hpf, peaked between 24 and 36 hpf, and decreased rapidly thereafter. We detected retene metabolites at 36 and 48 hpf, indicating metabolic onset preceding toxicity. This study highlights the value of combining molecular and systems biology approaches with mechanistic and predictive toxicology to interrogate the role of biotransformation in AHR-dependent toxicity.

Diverse PFAS produce unique transcriptomic changes linked to developmental toxicity in zebrafish.

Per- and polyfluoroalkyl substances (PFAS) are a widespread and persistent class of contaminants posing significant environmental and human health concerns. Comprehensive understanding of the modes of action underlying toxicity among structurally diverse PFAS is mostly lacking. To address this need, we recently reported on our application of developing zebrafish to evaluate a large library of PFAS for developmental toxicity. In the present study, we prioritized 15 bioactive PFAS that induced significant morphological effects and performed RNA-sequencing to characterize early transcriptional responses at a single timepoint (48 h post fertilization) after early developmental exposures (8 h post fertilization). Internal concentrations of 5 of the 15 PFAS were measured from pooled whole fish samples across multiple timepoints between 24-120 h post fertilization, and additional temporal transcriptomics at several timepoints (48-96 h post fertilization) were conducted for Nafion byproduct 2. A broad range of differentially expressed gene counts were identified across the PFAS exposures. Most PFAS that elicited robust transcriptomic changes affected biological processes of the brain and nervous system development. While PFAS disrupted unique processes, we also found that similarities in some functional head groups of PFAS were associated with the disruption in expression of similar gene sets. Body burdens after early developmental exposures to select sulfonic acid PFAS, including Nafion byproduct 2, increased from the 24-96 h post fertilization sampling timepoints and were greater than those of sulfonamide PFAS of similar chain lengths. In parallel, the Nafion byproduct 2-induced transcriptional responses increased between 48 and 96 h post fertilization. PFAS characteristics based on toxicity, transcriptomic effects, and modes of action will contribute to further prioritization of PFAS structures for testing and informed hazard assessment.

The zebrafish gut microbiome influences benzo[a]pyrene developmental neurobehavioral toxicity.

Early-life exposure to environmental toxicants like Benzo[a]pyrene (BaP) is associated with several health consequences in vertebrates (i.e., impaired or altered neurophysiological and behavioral development). Although toxicant impacts were initially studied relative to host physiology, recent studies suggest that the gut microbiome is a possible target and/or mediator of behavioral responses to chemical exposure in organisms, via the gut-brain axis. However, the connection between BaP exposure, gut microbiota, and developmental neurotoxicity remains understudied. Using a zebrafish model, we determined whether the gut microbiome influences BaP impacts on behavior development. Embryonic zebrafish were treated with increasing concentrations of BaP and allowed to grow to the larval life stage, during which they underwent behavioral testing and intestinal dissection for gut microbiome profiling via high-throughput sequencing. We found that exposure affected larval zebrafish microbiome diversity and composition in a manner tied to behavioral development: increasing concentrations of BaP were associated with increased taxonomic diversity, exposure was associated with unweighted UniFrac distance, and microbiome diversity and exposure predicted larval behavior. Further, a gnotobiotic zebrafish experiment clarified whether microbiome presence was associated with BaP exposure response and behavioral changes. We found that gut microbiome state altered the relationship between BaP exposure concentration and behavioral response. These results support the idea that the zebrafish gut microbiome is a determinant of the developmental neurotoxicity that results from chemical exposure.

The addition of mammalian cell culture medium impacts nanoparticle toxicity in zebrafish.

Engineered nanomaterials (ENMs) are ubiquitous in contemporary applications, yet their environmental and human health impacts remain inadequately understood. This study addresses the challenge of identifying potential risks associated with ENM exposure by highlighting the significant variability in existing research methodologies. Without a systematic collection of toxicological data that encompasses standardized materials, relevant platforms, and assays, the task of identifying potential risks linked to ENM exposure becomes an intricate challenge. In vitro assessments often use media rich in ionic species, such as RPMI and fetal bovine serum (FBS). Zebrafish embryos, known to develop normally in low-ionic environments, were exposed to Cerium Oxide, Zinc Oxide, and Graphene Oxides in different media at varying concentrations. Here, we discovered that zebrafish embryos tolerated a mix of 80 % RPMI, 2 % FBS, and 1 % antibiotic cocktail. The results revealed that adverse effects observed in zebrafish with certain nanomaterials in Ultra-Pure (UP) water were mitigated in cell culture medium, emphasizing the importance of revisiting previously considered non-toxic materials in vitro. The zebrafish results underscore the importance of utilizing a multidimensional in vivo platform to gauge the biological activity of nanomaterials accurately.

PAH bioremediation with Rhodococcus rhodochrous ATCC 21198: Impact of cell immobilization and surfactant use on PAH treatment and post-remediation toxicity.

Polycyclic aromatic hydrocarbons (PAHs) are prevalent environmental contaminants that are harmful to ecological and human health. Bioremediation is a promising technique for remediating PAHs in the environment, however bioremediation often results in the accumulation of toxic PAH metabolites. The objectives of this research were to demonstrate the cometabolic treatment of a mixture of PAHs by a pure bacterial culture, Rhodococcus rhodochrous ATCC 21198, and investigate PAH metabolites and toxicity. Additionally, the surfactant Tween ® 80 and cell immobilization techniques were used to enhance bioremediation. Total PAH removal ranged from 70-95% for fluorene, 44-89% for phenanthrene, 86-97% for anthracene, and 6.5-78% for pyrene. Maximum removal was achieved with immobilized cells in the presence of Tween ® 80. Investigation of PAH metabolites produced by 21198 revealed a complex mixture of hydroxylated compounds, quinones, and ring-fission products. Toxicity appeared to increase after bioremediation, manifesting as mortality and developmental effects in embryonic zebrafish. 21198's ability to rapidly transform PAHs of a variety of molecular structures and sizes suggests that 21198 can be a valuable microorganism for catalyzing PAH remediation. However, implementing further treatment processes to address toxic PAH metabolites should be pursued to help lower post-remediation toxicity in future studies.

Interlaboratory Study on Zebrafish in Toxicology: Systematic Evaluation of the Application of Zebrafish in Toxicology's (SEAZIT's) Evaluation of Developmental Toxicity.

Embryonic zebrafish represent a useful test system to screen substances for their ability to perturb development. The exposure scenarios, endpoints captured, and data analysis vary among the laboratories who conduct screening. A lack of harmonization impedes the comparison of the substance potency and toxicity outcomes across laboratories and may hinder the broader adoption of this model for regulatory use. The Systematic Evaluation of the Application of Zebrafish in Toxicology (SEAZIT) initiative was developed to investigate the sources of variability in toxicity testing. This initiative involved an interlaboratory study to determine whether experimental parameters altered the developmental toxicity of a set of 42 substances (3 tested in duplicate) in three diverse laboratories. An initial dose-range-finding study using in-house protocols was followed by a definitive study using four experimental conditions: chorion-on and chorion-off using both static and static renewal exposures. We observed reasonable agreement across the three laboratories as 33 of 42 test substances (78.6%) had the same activity call. However, the differences in potency seen using variable in-house protocols emphasizes the importance of harmonization of the exposure variables under evaluation in the second phase of this study. The outcome of the Def will facilitate future practical discussions on harmonization within the zebrafish research community.

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

Zebrafish have become an essential tool 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.

3' RNA-seq is superior to standard RNA-seq in cases of sparse data but inferior at identifying toxicity pathways in a model organism.

Introduction: The application of RNA-sequencing has led to numerous breakthroughs related to investigating gene expression levels in complex biological systems. Among these are knowledge of how organisms, such as the vertebrate model organism zebrafish (Danio rerio), respond to toxicant exposure. Recently, the development of 3' RNA-seq has allowed for the determination of gene expression levels with a fraction of the required reads compared to standard RNA-seq. While 3' RNA-seq has many advantages, a comparison to standard RNA-seq has not been performed in the context of whole organism toxicity and sparse data. Methods and results: Here, we examined samples from zebrafish exposed to perfluorobutane sulfonamide (FBSA) with either 3' or standard RNA-seq to determine the advantages of each with regards to the identification of functionally enriched pathways. We found that 3' and standard RNA-seq showed specific advantages when focusing on annotated or unannotated regions of the genome. We also found that standard RNA-seq identified more differentially expressed genes (DEGs), but that this advantage disappeared under conditions of sparse data. We also found that standard RNA-seq had a significant advantage in identifying functionally enriched pathways via analysis of DEG lists but that this advantage was minimal when identifying pathways via gene set enrichment analysis of all genes. Conclusions: These results show that each approach has experimental conditions where they may be advantageous. Our observations can help guide others in the choice of 3' RNA-seq vs standard RNA sequencing to query gene expression levels in a range of biological systems.

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

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