Nonylphenol Toxicity Evaluation and Discovery of Biomarkers in Rat Urine by a Metabolomics Strategy through HPLC-QTOF-MS

Yan-Xin Zhang, Xin Yang, Pan Zou, Peng-Fei Du, Jing Wang, Fen Jin, Mao-Jun Jin and Yong-Xin She
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Yan-Xin Zhang: School of Chemistry and Chemical Engineering, Harbin Institute of Technology, Harbin 150090, China
Xin Yang: School of Chemistry and Chemical Engineering, Harbin Institute of Technology, Harbin 150090, China
Pan Zou: School of Chemistry and Chemical Engineering, Harbin Institute of Technology, Harbin 150090, China
Peng-Fei Du: Key Laboratory of Agro-Product Quality and Safety, Institute of Quality Standard & Testing Technology for Agro-Product, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Jing Wang: Key Laboratory of Agro-Product Quality and Safety, Institute of Quality Standard & Testing Technology for Agro-Product, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Fen Jin: Key Laboratory of Agro-Product Quality and Safety, Institute of Quality Standard & Testing Technology for Agro-Product, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Mao-Jun Jin: Key Laboratory of Agro-Product Quality and Safety, Institute of Quality Standard & Testing Technology for Agro-Product, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Yong-Xin She: Key Laboratory of Agro-Product Quality and Safety, Institute of Quality Standard & Testing Technology for Agro-Product, Chinese Academy of Agricultural Sciences, Beijing 100081, China

IJERPH, 2016, vol. 13, issue 5, 1-17

Abstract: Nonylphenol (NP) was quantified using liquid chromatography tandem mass spectrometry (LC-MS/MS) in the urine and plasma of rats treated with 0, 50, and 250 mg/kg/day of NP for four consecutive days. A urinary metabolomic strategy was originally implemented by high performance liquid chromatography time of flight mass spectrometry (HPLC-QTOF-MS) to explore the toxicological effects of NP and determine the overall alterations in the metabolite profiles so as to find potential biomarkers. It is essential to point out that from the observation, the metabolic data were clearly clustered and separated for the three groups. To further identify differentiated metabolites, multivariate analysis, including principal component analysis (PCA), orthogonal partial least-squares discriminant analysis (OPLS-DA), high-resolution MS/MS analysis, as well as searches of Metlin and Massbank databases, were conducted on a series of metabolites between the control and dose groups. Finally, five metabolites, including glycine, glycerophosphocholine, 5-hydroxytryptamine, malonaldehyde (showing an upward trend), and tryptophan (showing a downward trend), were identified as the potential urinary biomarkers of NP-induced toxicity. In order to validate the reliability of these potential biomarkers, an independent validation was performed by using the multiple reaction monitoring (MRM)-based targeted approach. The oxidative stress reflected by urinary 8-oxo-deoxyguanosine (8-oxodG) levels was elevated in individuals highly exposed to NP, supporting the hypothesis that mitochondrial dysfunction was a result of xenoestrogen accumulation. This study reveals a promising approach to find biomarkers to assist researchers in monitoring NP.

Keywords: nonylphenol; metabolomics; exposure; HPLC-QTOF-MS; biomarker (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2016
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