Evaluation and characterization of anti-estrogenic and anti-androgenic activities in soil samples along the Second Songhua River, China

Identification of (anti-)androgenic activities and risks of sludges from industrial and domestic wastewater treatment plants

The annual production of sludges is significant all over the world, and large amounts of sludges have been improperly disposed by random dumping. The contaminants in these sludges may leak into the surrounding soils, surface and groundwater, or be blown into the atmosphere, thereby causing adverse effects to human health. In this study, the (anti-)androgenic activities in organic extracts of sludges produced from both industrial and domestic wastewater treatment plants (WWTPs) were examined using reporter gene assay based on MDA-kb2 cell lines and the potential (anti-)androgenic risks were assessed using hazard index (HI) based on bioassays. Twelve of the 18 samples exhibited androgen receptor (AR) antagonistic activities, with AR antagonistic equivalents ranging from 1.2 × 10² μg flutamide/g sludge to 1.8 × 10⁴ μg flutamide/g sludge; however, no AR agonistic activity was detected in any of the tested samples. These 12 sludges were all from chemical WWTPs; no sludges from domestic WWTPs displayed AR antagonistic activity. Aside from wastewater source, treatment scale and technology could also influence AR antagonistic potencies. The HI values of all the 12 sludges exceeded 1.0, and the highest HI value was above 3.0 × 10³ for children; this indicates that these sludges might cause adverse effects to human health and that children are at a greater risk than adults. The anti-androgenic potencies and risks of the subdivided fractions were also determined, and medium-polar and polar fractions were found to have relatively high detection rates and contribution rates to the AR antagonistic potencies and risks of the raw sample extracts.

Determination of endocrine-disrupting potencies of agricultural soils in China via a battery of steroid receptor bioassays

Pollution of agricultural soils by pesticides, such as organochlorine pesticides (OCPs), can be a significant issue since high detection rates of these compounds were reported in our previous studies. However, more uncertain kinds, quantities and density of pollutants remained in soil samples were unidentified. In this study, the total hormonal activities of complex mixtures of both known and unknown contaminants in agricultural soils in mainland China were measured by applying highly sensitive reporter gene assays for detecting agonists/antagonists for estrogen receptor (ER), androgen receptor (AR), progesterone receptor (PR), glucocorticoid receptor (GR) and mineralocorticoid receptor (MR). High detection rates of estrogenic activities and anti-progestogenic activities were observed among the 123 soil samples, reaching 79% and 73%, respectively. More than half of the soil samples showed obvious antagonistic effects against AR and GR. Approximately a third of tested samples exhibited androgenic, progestogenic and glucocorticoidic effects. A total of 72% and 78% soil extracts had mineralocorticoid-like and anti-mineralocorticoid activities, respectively. Significant positive correlations were observed between estrogenic activity and the concentrations of Σdichlorodiphenyltrichloroethanes (DDTs), Σendosulfans, Σchlordanes, heptachlor and Σdrins, respectively, but not other receptors. As a rapid and convenient pre-caution method, determination of endocrine-disrupting potencies of contaminated soils via bioassay could help to identify and define sites that required further attention for ecological risk assessments.

Extended Virtual Screening Strategies To Link Antiandrogenic Activities and Detected Organic Contaminants in Soils

A tiered screening strategy based on extensive virtual fractionation and elucidation was developed to simplify identification of toxicants in complex environments. In tier1-virtual fractionation, multivariate analysis (MVA) was set up as an alternative of physical fractionation. In tier2-virtual structure elucidation, in-house quantitative structure-retention relationship (QSRR) models and toxicity simulation methods were developed to simplify nontarget identification. The efficiency of the tiered virtual strategy was tentatively verified by soil samples from a chemical park contaminated by antiandrogenic substances. Eight out of 18 sites were detected as antiandrogenic, while none of them exhibited androgenic agonist potencies. Sixty-seven peaks were selected for further identification by MVA, among which over 90% were verified in androgenic fractions in traditional effect-directed analysis (EDA). With 579 tentative structures generated by in silico fragmentation, 74% were elucidated by QSRR and 65% were elucidated by in silico toxicity prediction. All prior peaks were identified at different confidence levels with over 40% of the identified peaks above confidence level 2b, which has been increased over 40% with less than half of the time spent compared to traditional EDA. Such a combination of tiered virtual screening methods provides more efficient and rapid identifications of key toxicants at contaminated sites.

Evaluation and characterization of thyroid-disrupting activities in soil samples along the Second Songhua River, China

In this study, a recombinant thyroid receptor (TR) gene yeast assay combined with Monte Carlo simulation were used to evaluate and characterize soil samples collected from Jilin (China) along the Second Songhua River, for their ant/agonist effect on TR. No TR agonistic activity was found in soils, but many soil samples exhibited TR antagonistic activities, and the bioassay-derived amiodarone hydrochloride equivalents, which was calculated based on Monte Carlo simulation, ranged from not detected (N.D.) to 35.5μg/g. Hydrophilic substance fractions were determined to be the contributors to TR antagonistic activity in these soil samples. Our results indicate that the novel calculation method is effective for the quantification and characterization of TR antagonists in soil samples, and these data could provide useful information for future management and remediation efforts for contaminated soils.