Identification of Major Dioxin-Like Compounds and Androgen Receptor Antagonist in Acid-Treated Tissue Extracts of High Trophic-Level Animals

Abstract

We evaluated the applicability of combining in vitro bioassays with instrument analyses to identify potential endocrine disrupting pollutants in sulfuric acid-treated extracts of liver and/or blubber of high trophic-level animals. Dioxin-like and androgen receptor (AR) antagonistic activities were observed in Baikal seals, common cormorants, raccoon dogs, and finless porpoises by using a panel of rat and human cell-based chemical-activated luciferase gene expression (CALUX) reporter gene bioassays. On the other hand, no activity was detected in estrogen receptor α (ERα)-, glucocorticoid receptor (GR)-, progesterone receptor (PR)-, and peroxisome proliferator-activated receptor γ2 (PPARγ2)-CALUX assays with the sample amount applied. All individual samples (n = 66) showed dioxin-like activity, with values ranging from 21 to 5500 pg CALUX-2,3,7,8-tetrachlorodibenzo-p-dioxin equivalent (TEQ)/g-lipid. Because dioxins are expected to be strong contributors to CALUX-TEQs, the median theoretical contribution of dioxins calculated from the result of chemical analysis to the experimental CALUX-TEQs was estimated to explain up to 130% for all the tested samples (n = 54). Baikal seal extracts (n = 31), but not other extracts, induced AR antagonistic activities that were 8–150 μg CALUX-flutamide equivalent (FluEQ)/g-lipid. p,p′-DDE was identified as an important causative compound for the activity, and its median theoretical contribution to the experimental CALUX-FluEQs was 59% for the tested Baikal seal tissues (n = 25). Our results demonstrate that combining in vitro CALUX assays with instrument analysis is useful for identifying persistent organic pollutant-like compounds in the tissue of wild animals on the basis of in vitro endocrine disruption toxicity.

Effect-based assessment of persistent organic pollutant and pesticide dumpsite using mammalian CALUX reporter cell lines

“…The (semi-)quantitative nature of the data 3. A reduced risk of underestimation of the actual hazard by directly measuring sum activities instead of focusing the presence of individual compounds that are among the Busual suspects similar approach as the one presented here for soil quality assessment may also be used for other environmental compartments, and other types of samples such as sediments, food and feed, and animal and human tissue (e.g., Suzuki et al 2011;Papadopoulou et al 2013;Porpora et al 2009). …”

Effects‐directed analysis (EDA) and toxicity identification evaluation (TIE): Complementary but different approaches for diagnosing causes of environmental toxicity

“…This type of data is often best achieved with in vitro assays, for example, cellular toxicity tests with endpoints including mutagenicity, genotoxicity, and endocrine disruption (e.g., Thomas et al and Weiss et al ) (Figure ). However, small‐scale whole‐organism toxicity testing (i.e., in vivo) has also been applied in some instances in EDA . As noted earlier, the use of organic solvent extracts in the in vitro assays precludes the EDA from addressing the bioavailability of toxicants (except, possibly, in the case of EDA conducted on exposed biota).…”

Coupling passive sampling with in vitro bioassays and chemical analysis to understand combined effects of bioaccumulative chemicals in blood of marine turtles

“…There was no statistically significant 3. Comparison of (A) AhR-and (B) Nrf2-active chemical burdens in marine wildlife species, including green turtles (this study) and dugongs (Jin et al, 2015) from Australia, Baikal seals from Russia and finless porpoises from Japan (Suzuki et al, 2011), polar bears from East Greenland (Erdmann et al, 2013), North Sea herring from Sweden (Nording et al, 2005) and Atlantic cod from Poland (Dabrowska et al, 2010). Left, middle and right lines represent the minimum, median and maximum values, respectively.…”

“…Facilitated transport of hydrophobic chemicals by biological matrices (e.g., proteins) into passive sampling devices has been observed in many studies (Oomen et al, 2000;Heringa et al, 2006;Kramer et al, 2007). The advantage of PDMS over solvents to extract chemicals is that charged molecules (e.g., proteins) do not diffuse into PDMS and only a small proportion of lipid does, which minimizes co-extraction of complex matrices, thus significantly reducing solvent use and cleanup efforts compared to conventional solvent extraction methods (Simon et al, 2010(Simon et al, , 2011Suzuki et al, 2011). The PDMS-based approach may also offer chemical extraction from biological samples to be performed immediately in situ or in vivo, thus circumventing the logistical need to transport and store samples (Allan et al, 2013).…”