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  2. Nontargeted metabolomics-based mapping urinary metabolic fingerprints after exposure to acrylamide

Nontargeted metabolomics-based mapping urinary metabolic fingerprints after exposure to acrylamide

  • Ecotoxicol Environ Saf. 2021 Aug 16;224:112625. doi: 10.1016/j.ecoenv.2021.112625.
Li Zhu 1 Wei Jia 1 Qiao Wang 1 Pan Zhuang 1 Xuzhi Wan 1 Yiping Ren 2 Yu Zhang 3
Affiliations

Affiliations

  • 1 National Engineering Laboratory of Intelligent Food Technology and Equipment, Zhejiang Key Laboratory for Agro-Food Processing, College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, Zhejiang, China.
  • 2 Yangtze Delta Region Institute of Tsinghua University, Jiaxing 314006, Zhejiang, China.
  • 3 National Engineering Laboratory of Intelligent Food Technology and Equipment, Zhejiang Key Laboratory for Agro-Food Processing, College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, Zhejiang, China. Electronic address: y_zhang@zju.edu.cn.
Abstract

Acrylamide classified as a probable carcinogen to humans is a high production volume chemical in industrial applications released to aquatic and environmental ecosystems, and also widely found in the thermal processing of starch-rich foods. To gain insight into the urinary metabolomics that may induce physiological responses stimulated by acrylamide, rats were orally administered with a single dose of 13C3-acrylamide (10 mg/kg bw) in the treatment group and urine samples were continuously collected every 2 h during the first 18 h and every 3 h during the period from 18 h to 36 h. A reliable nontargeted screening method for the analysis of urinary metabolomics in rats was developed using ultra-high performance liquid chromatography coupled to quadrupole-Orbitrap high-resolution mass spectrometry. All metabolites in urine of rats receiving isotope-labeled acrylamide were screened by validated orthogonal partial least squares-discriminant analyses compared to the Animals in the control group, while exposure biomarkers were further confirmed according to the characteristic fragmentation rules and time-dependent profiles. Here we identified 2 new specific exposure biomarkers, named N-acetyl-S-(2-carbamoyl-2-hydroxyethyl)-L-cysteine-sulfoxide and N-acetyl-S-(2-carboxyl)-L-cysteine, compared to 4 currently acknowledged mercapturic acid adducts of acrylamide. In addition, our findings on analysis of acrylamide metabolic pathway and identification of exposure biomarkers confirmed that acrylamide could significantly affect energy metabolism and amino acid metabolism by the Kyoto Encyclopedia of Genes and Genomes pathway analysis for key metabolites. Homocysteine thiolactone and hypoxanthine may be potential biomarkers for the cardiotoxicity, while methionine sulfoxide, hippuric acid and melatonin may be specifically related to the neurotoxicity. Thus, the current study provided new evidence on the identification of emerging exposure biomarkers and specific signature metabolites related to the toxicity of acrylamide, and shed LIGHT on how acrylamide affected energy and amino acid metabolism by further mapping urinary metabolic fingerprints.

Keywords

Acrylamide; Exposure; Fingerprints; Metabolomics; Urinary biomarkers.

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