Metal interference on luciferase activity induced by 2,3,7,8-tetrachlorodibenzo-p-dioxin in bioassays of recombinant mouse hepatoma cells

Chou, I-Cheng; Wu, Ya; Wang, Lin‐Chi; Chang-Chien, Guo-Ping; Lee, Hsinyu

doi:10.1016/j.jhazmat.2008.10.099

Cited by 5 publications

(2 citation statements)

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“…Current reference dioxin detection methods require extraction of all relevant congeners and their individual quantification by capillary gas chromatography-high resolution mass spectrometry (GC-HRMS)) instrumentation. , The concentration of each compound is then adjusted in terms of equivalence to 2,3,7,8-tetrachlorodibenzo- p -dioxin (TCDD) by a toxic equivalence factor (TEF) giving an overall toxic equivalence quotient (TEQ) . Cell-based methods have been devised to screen larger numbers of samples for dioxin-like activity and are based on the ability of dioxins to induce, in a dose-dependent manner, the cytochrome P450 1A1 (CYP1A1) enzyme system in cultured rat liver cells, which is determined using ethoxyresorufin-O-deethylase (EROD) activity or by a dioxin-responsive chemically activated luciferase gene expression (DR-CALUX) assay. − However, such biological-based methods may be subject to interference from environmental pollutants such as heavy metals, pesticides and other organic chemicals as well as endogenous aryl hydrocarbon receptor (AhR) agonists and antagonists …”

Section: Introductionmentioning

confidence: 99%

“…8−13 However, such biological-based methods may be subject to interference from environmental pollutants such as heavy metals, pesticides and other organic chemicals as well as endogenous aryl hydrocarbon receptor (AhR) agonists and antagonists. 14 Human exposure to dioxins occurs primarily through the ingestion of animal-derived food products 17 with dioxins typically entering the food chain through contaminated animal feed sources. Dioxin compounds are typically stable, persistent, lipophilic chemicals, which accumulate readily in the adipose tissues of animals, and contaminated feed materials can easily lead to excess levels in a wide range of primary and processed foodstuffs.…”

Section: ■ Introductionmentioning

confidence: 99%

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Metabolomic Profiling of In Vivo Plasma Responses to Dioxin-Associated Dietary Contaminant Exposure in Rats: Implications for Identification of Sources of Animal and Human Exposure

O'Kane

Chevallier²,

Graham³

et al. 2013

Environ. Sci. Technol.

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Dioxin contamination of the food chain typically occurs when cocktails of combustion residues or polychlorinated biphenyl (PCB) containing oils become incorporated into animal feed. These highly toxic compounds are bioaccumulative with small amounts posing a major health risk. The ability to identify animal exposure to these compounds prior to their entry into the food chain may be an invaluable tool to safeguard public health. Dioxin-like compounds act by a common mode of action and this suggests that markers or patterns of response may facilitate identification of exposed animals. However, secondary co-contaminating compounds present in typical dioxin sources may affect responses to compounds. This study has investigated for the first time the potential of a metabolomics platform to distinguish between animals exposed to different sources of dioxin contamination through their diet. Sprague-Dawley rats were given feed containing dioxin-like toxins from hospital incinerator soot, a common PCB oil standard and pure 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) (normalized at 0.1 μg/kg TEQ) and acquired plasma was subsequently biochemically profiled using ultra high performance liquid chromatography (UPLC) quadropole time-of-flight-mass spectrometry (QTof-MS). An OPLS-DA model was generated from acquired metabolite fingerprints and validated which allowed classification of plasma from individual animals into the four dietary exposure study groups with a level of accuracy of 97-100%. A set of 24 ions of importance to the prediction model, and which had levels significantly altered between feeding groups, were positively identified as deriving from eight identifiable metabolites including lysophosphatidylcholine (16:0) and tyrosine. This study demonstrates the enormous potential of metabolomic-based profiling to provide a powerful and reliable tool for the detection of dioxin exposure in food-producing animals.

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