Estrogenic activity of surface waters using zebrafish- and human-based in vitro assays: The Danube as a case-study

Abstract

Most in vitro reporter gene assays used to assess estrogenic contamination are based on human estrogen receptor α (hERα) activation. However, fish bioassays can have distinct response to estrogenic chemicals and mixtures, questioning the relevance of human-based bioassays for assessing risk to this species. In this study, zebrafish liver cells stably expressing zebrafish ERβ2 (ZELHβ2) and human breast cancer cells expressing hERα (MELN) were used to quantify the estrogenic activity of 25 surface water samples of the Danube River, for which chemicals have been previously quantified. Most samples had a low estrogenic activity below 0.1 ng/L 17β-estradiol-equivalents that was more often detected by MELN cells, while ZELHβ2 response tend to be lower than predicted based on the chemicals identified.Nevertheless, both bioassays quantified well a higher estrogenic activity at two sites, which was confirmed in vivo using a transgenic zebrafish assay. The results are discussed considering the effect-based trigger values proposed for water quality monitoring.

Monitoring of emerging contaminants of concern in the aquatic environment: a review of studies showing the application of effect-based measures

“…However, there are no details on what type of bioassays must be used to determine such endpoints. In general, bioassays are reporter gene based as seen in the CALUX system, DR/ER-LUC, MDA-kb2, MELN, MVLN or H4IIE-luc systems, [89][90][91][92][93][94][95][96][97][98][99][100][101][102] where genes specic to the endpoint such as estrogen receptor for estrogenicity, and a response element for that receptor are engineered in a plasmid vector located upstream of a luciferase enzyme. Activation of the receptor by the ligand, which in this case is the chemical contaminant, results in activation of the receptor and binding with the response element.…”

“…The limit of detection of estrogenicity varies between all these studies and even at this, estrogenic activities is more likely to be detected than any other mode of actions, although some studies reported no detection of estrogenic activities is some of the sampled locations. 93,107 This may be attributed to the chemical properties of the analytes in the collected samples. For short and long term exposure, EEQ values <0.5 ng of E2 L À1 is considered to be the safe level.…”

Effect-Based Trigger Values Are Essential for the Uptake of Effect-Based Methods in Water Safety Planning

“…Assays indicative of receptor‐mediated effects, such as activation of the estrogen receptor (ER; Leusch et al, 2010; Serra et al, 2020), activation of the glucocorticoid receptor (GR; Jia et al, 2016), and photosynthesis inhibition (Bengtson Nash et al, 2006; Tang & Escher, 2014), are highly specific bioassays, and almost all of the detected effects can typically be explained by a small number of known and potent chemicals. For example, >90% of the estrogenic activity in most water samples is caused by natural hormones (such as 17β‐estradiol and estrone) and synthetic hormones (such as 17α‐ethinylestradiol), with industrial xenoestrogens, such as alkylphenols, only having a minor contribution (Korner et al, 2001; Ra et al, 2011).…”

Bioanalytical and chemical characterization of organic micropollutant mixtures in long-term exposed passive samplers from the Joint Danube Survey 4: Setting a baseline for water quality monitoring

“…Effect-based water quality monitoring using several in vitro assays was implemented next to chemical analyses to screen mixture effects for the first time in the previous Joint Danube Survey (JDS3) in 2013 ( König et al, 2017 , Neale et al, 2015 , Novák et al, 2018 ). The results pointed to various relevant biological activities, namely activation of aryl hydrocarbon receptor (AhR), peroxisome proliferator-activated receptor isoform gamma (PPARɣ), estrogen receptor isoform alpha (ERα), androgen receptor (AR), glucocorticoid receptor (GR), induction of adaptive stress response to oxidative stress (AREc32), and antagonism to AR ( Alygizakis et al, 2019 , König et al, 2017 , Neale et al, 2015 , Novák et al, 2018 , Serra et al, 2020 , Toušová et al, 2019 ). Nevertheless, the studies from the previous JDS campaigns analyzed only short term-collected samples that included grab samples ( Loos et al, 2010 ), mobile passive sampling ( Novák et al, 2018 ) and active large-volume solid-phase extraction (LVSPE) samples ( König et al, 2017 , Neale et al, 2017b ).…”