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.

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.

The Effects of Long-term, Low-dose β-N-methylamino-L-alanine (BMAA) Exposures in Adult SOD Transgenic Zebrafish.

β-N-Methylamino-L-alanine (BMAA) is a non-proteinogenic amino acid produced by cyanobacteria, which has been implicated in several neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS). It is postulated that chronic exposure to BMAA can lead to formation of protein aggregates, oxidative stress, and/or excitotoxicity, which are mechanisms involved in the etiology of ALS. While specific genetic mutations are identified in some instances of ALS, it is likely that a combination of genetic and environmental factors, such as exposure to the neurotoxin BMAA, contributes to disease.

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

The continual introduction of new chemicals into the market necessitates fast, efficient testing strategies for evaluating their toxicity. Ideally, these high-throughput screening (HTS) methods should capture the entirety of biological complexity while minimizing reliance on expensive resources that are required to assess diverse phenotypic endpoints. In recent years, the zebrafish () has become a preferred vertebrate model to conduct rapid toxicity tests.

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.