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Although bisphenol A (BPA) is commonly recognized as an endocrine disruptor, the metabolic consequences of its exposure are still poorly understood. In this study, we present a non-targeted LC-MS based metabolomic analysis in combination with a full-genome, high-throughput RNA sequencing (RNA-Seq) to reveal the metabolic effects and the subjacent regulatory pathways of exposing zebrafish embryos to BPA during the first 120 hours post-fertilization. We applied multivariate data analysis methods to extract biochemical information from the LC-MS and RNA-Seq complex datasets and to perform testable predictions of the phenotypic adverse effects. Metabolomic and transcriptomic data revealed a similar subset of altered pathways, despite the large difference in the number of identified biomarkers (around 50 metabolites and more than 1000 genes). These results suggest that even a moderate coverage of zebrafish metabolome may be representative of the global metabolic changes. These multi-omic responses indicate a specific metabolic disruption by BPA affecting different signaling pathways, such as retinoid and prostaglandin metabolism. The combination of transcriptomic and metabolomic data allowed a dynamic interpretation of the results that could not be drawn from either single dataset. These results illustrate the utility of -omic integrative analyses for characterizing the physiological effects of toxicants beyond the mere indication of the affected pathways.
Fish Proteins, Metabolic disruption, Endocrine Disruptors, Mass Spectrometry, Bisphenol A, Phenols, Metabolome, Animals, Metabolomics, Non-targeted metabolomics, Bisphenol A Compounds, Benzhydryl Compounds, Transcriptomics, Transcriptome, Zebrafish, Chromatography, Liquid
Fish Proteins, Metabolic disruption, Endocrine Disruptors, Mass Spectrometry, Bisphenol A, Phenols, Metabolome, Animals, Metabolomics, Non-targeted metabolomics, Bisphenol A Compounds, Benzhydryl Compounds, Transcriptomics, Transcriptome, Zebrafish, Chromatography, Liquid
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