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Identification of Thyroid Receptor Ant/Agonists in Water Sources Using Mass Balance Analysis and Monte Carlo Simulation

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  • Wei Shi
  • Si Wei
  • Xin-xin Hu
  • Guan-jiu Hu
  • Cu-lan Chen
  • Xin-ru Wang
  • John P Giesy
  • Hong-xia Yu

Abstract

Some synthetic chemicals, which have been shown to disrupt thyroid hormone (TH) function, have been detected in surface waters and people have the potential to be exposed through water-drinking. Here, the presence of thyroid-active chemicals and their toxic potential in drinking water sources in Yangtze River Delta were investigated by use of instrumental analysis combined with cell-based reporter gene assay. A novel approach was developed to use Monte Carlo simulation, for evaluation of the potential risks of measured concentrations of TH agonists and antagonists and to determine the major contributors to observed thyroid receptor (TR) antagonist potency. None of the extracts exhibited TR agonist potency, while 12 of 14 water samples exhibited TR antagonistic potency. The most probable observed antagonist equivalents ranged from 1.4 to 5.6 µg di-n-butyl phthalate (DNBP)/L, which posed potential risk in water sources. Based on Monte Carlo simulation related mass balance analysis, DNBP accounted for 64.4% for the entire observed antagonist toxic unit in water sources, while diisobutyl phthalate (DIBP), di-n-octyl phthalate (DNOP) and di-2-ethylhexyl phthalate (DEHP) also contributed. The most probable observed equivalent and most probable relative potency (REP) derived from Monte Carlo simulation is useful for potency comparison and responsible chemicals screening.

Suggested Citation

  • Wei Shi & Si Wei & Xin-xin Hu & Guan-jiu Hu & Cu-lan Chen & Xin-ru Wang & John P Giesy & Hong-xia Yu, 2013. "Identification of Thyroid Receptor Ant/Agonists in Water Sources Using Mass Balance Analysis and Monte Carlo Simulation," PLOS ONE, Public Library of Science, vol. 8(10), pages 1-9, October.
    • Handle: RePEc:plo:pone00:0073883
    DOI: 10.1371/journal.pone.0073883
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    References listed on IDEAS

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    1. Martin Hoefling & Nicola Lima & Dominik Haenni & Claus A M Seidel & Benjamin Schuler & Helmut Grubmüller, 2011. "Structural Heterogeneity and Quantitative FRET Efficiency Distributions of Polyprolines through a Hybrid Atomistic Simulation and Monte Carlo Approach," PLOS ONE, Public Library of Science, vol. 6(5), pages 1-19, May.
    2. Qu, C.S. & Chen, W. & Bi, J. & Huang, L. & Li, F.Y., 2011. "Ecological risk assessment of pesticide residues in Taihu Lake wetland, China," Ecological Modelling, Elsevier, vol. 222(2), pages 287-292.
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