Metabolic disruption of zebrafish (Danio rerio) embryos by bisphenol A. An integrated metabolomic and transcriptomic approach

被引:58
|
作者
Ortiz-Villanueva, Elena [1 ]
Navarro-Martin, Laia [1 ]
Jaumot, Joaquim [1 ]
Benavente, Fernando [2 ]
Sanz-Nebot, Victoria [2 ]
Pina, Benjamin [1 ]
Tauler, Roma [1 ]
机构
[1] IDAEA CS1C, Dept Environm Chem, Jordi Girona 18-26, Barcelona 08034, Spain
[2] Univ Barcelona, Dept Chem Engn & Analyt Chem, Diagonal 645, E-08028 Barcelona, Spain
基金
欧洲研究理事会;
关键词
Bisphenol A; Metabolic disruption; Non-targeted metabolomics; Transcriptomics; Zebrafish; REPRODUCTIVE TOXICITY; HUMAN HEALTH; EXPOSURE; METHYLATION; XENOBIOTICS; RESPONSES; PROFILES; HORMONES; PATTERNS; ENZYMES;
D O I
10.1016/j.envpol.2017.07.095
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:22 / 36
页数:15
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