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Science of the Total Environment 773 (2021) 145602 Contents lists available at ScienceDirect Science of the Total Environment j ourna l homepage: www.e lsev ie r .com/ locate /sc i totenv Mapping multiple endocrine disrupting activities in Virginia rivers using effect-based assays Diana A. Stavreva a,⁎,1, Michael Collins b,1, Andrew McGowana, Lyuba Varticovski a, Razi Raziuddin a, David Owen Brody a,c, Jerry Zhao a,c, Johnna Lee a,c, Riley Kuehn a,c, Elisabeth Dehareng a,c, Nicholas Mazza a,c, Gianluca Pegoraro a, Gordon L. Hager a,⁎ a Laboratory of Receptor Biology and Gene Expression, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, United States b Center for Natural Capital, PO Box 901, Orange, VA, United States c Walt Whitman High School, 7100 Whittier Blvd, Bethesda, MD 20817, United States H I G H L I G H T S G R A P H I C A L A B S T R A C T • A novel imaging-based assay enables characterization of individual and mix- tures of endocrine disrupting activities. • Four classes of bioactivitieswere assessed in river water from the state of Virginia. • Androgenic and aryl hydrocarbon activi- ties were most prevalent. • Glucocorticoid and thyroid activities were less common. • Multiple endocrine disrupting activities were present at many tested sites. Abbreviations:AR, androgen receptor; GR, glucocortico L-thyronine sodium salt powder; CAY, CAY 10465 aryl hy ⁎ Corresponding authors. E-mail addresses: stavrevd@mail.nih.gov (D.A. Stavrev 1 Co-first authors. https://doi.org/10.1016/j.scitotenv.2021.145602 0048-9697/Published by Elsevier B.V. a b s t r a c t a r t i c l e i n f o Article history: Received 9 October 2020 Received in revised form 23 January 2021 Accepted 29 January 2021 Available online 4 February 2021 Editor: Henner Hollert Keywords: Biological activity Hormones Endocrine disrupting compounds River water Water sources are frequently contaminated with natural and anthropogenic substances having known or suspected endocrine disrupting activities; however, these activities are not routinely measured and monitored. Phenotypic bioassays are a promising new approach for detection and quantitation of endocrine disrupting chemicals (EDCs). We developed cell lines expressing fluorescent chimeric constructs capable of detecting envi- ronmental contaminants which interact with multiple nuclear receptors. Using these assays, we tested water samples collected in the summers of 2016, 2017 and 2018 from twomajor Virginia rivers. Samples were concen- trated 200× and screened for contaminants interacting with the androgen (AR), glucocorticoid (GR), aryl hydro- carbon (AhR) and thyroid receptors. Among 45 tested sites, over 70% had AR activity and 60% had AhR activity. Many sites were also positive for GR and TRβ activation (22% and 42%, respectively). Multiple sites were positive for more than one type of contaminants, indicating presence of complex mixtures. These activities may nega- tively impact river ecosystems and consequently human health. Published by Elsevier B.V. id receptor; AhR, aryl hydrocarbon receptor; TR, thyroid receptor; Dex, dexamethasone; Testo, Testosterone; T3, 3,3′,5-Triiodo- drocarbon receptor agonist; DMSO, dimethyl sulfoxide. a), hagerg@exchange.nih.gov (G.L. Hager). http://crossmark.crossref.org/dialog/?doi=10.1016/j.scitotenv.2021.145602&domain=pdf https://doi.org/10.1016/j.scitotenv.2021.145602 mailto:stavrevd@mail.nih.gov mailto:hagerg@exchange.nih.gov Journal logo https://doi.org/10.1016/j.scitotenv.2021.145602 Unlabelled image http://www.sciencedirect.com/science/journal/00489697 www.elsevier.com/locate/scitotenv D.A. Stavreva, M. Collins, A. McGowan et al. Science of the Total Environment 773 (2021) 145602 1. Introduction Endocrine disruption by natural and synthetic compounds is amajor concern for the health of aquatic ecosystems (Kolpin et al., 2002).More- over, the presence of these chemicals in the environment and water sources could also affect human health (Kabir et al., 2015; Schug et al., 2016). Most EDCs are manmade compounds and include pharmaceuti- cals, pesticides, industrial chemicals and personal care products (Frye et al., 2012). Synthetic hormones used as contraceptives and treatment of hormone-responsive diseases are also potential EDCs, which can easily reach water sources by natural excretion (Fent et al., 2006). In addition, synthetic androgens such as trenbolone, used to accelerate livestock growth, can contaminatewater sources and affected sex deter- mination and fecundity in fish (Ankley et al., 2003; Morthorst et al., 2010; Stephany, 2010). Steroid hormones are among the most potent EDCs and can substantially affect aquatic life (Christen et al., 2010; Jobling et al., 2006; Lange et al., 2001; Pawlowski et al., 2004; Sumpter and Johnson, 2005). They bind to evolutionary conserved receptors at very low levels and exposure to EDCs can impact the physiology of most vertebrates, including humans (Christen et al., 2010). Epidemio- logical studies demonstrated that EDCs can affect prenatal growth and development, thyroid function, puberty, fertility, glucose metabolism, obesity, and are linked to the development of malignancies in humans (Ho et al., 2017; Street et al., 2018). Standard single-analyte chemical approaches such as High-Pressure Liquid Chromatography combined with Gas Chromatography and Tan- demMass Spectrometry have been used to identify EDCs in the environ- ment, specifically in the water (Bussy et al., 2016; Petrovic et al., 2002). However, structural changes induced by environmental biological and chemical processes, which transform the initial contaminants and their chemical structures, can complicate structural analysis. For exam- ple, in a recent study that screened stream water at 35 sites from 24 states in theUS and Puerto Rico by both, the in vitro assays and chemical analysis concluded that estrogen receptor activity correlated with the concentrations of steroidal estrogens detected by chemical approaches; however, AR and GR activities did not correlate with chemical analyses. Furthermore, no known GR-active compounds were identified from the target-chemical analyte list (Conley et al., 2017). Similarly, a study from our laboratory failed to identify any known glucocorticoid compounds in a sample with high activity measured by GR translocation and gene expression assays (Stavreva et al., 2012). These results argue for the wider use of effect-based assays to detect endocrine disrupting poten- tial of environmental contaminants. Moreover, water sources may con- tain a complex mixture of contaminants having endocrine disrupting potential which might be difficult to anticipate using single chemical identification methods (Kolpin et al., 2002). Earlier studies successfully utilized in vitro assays to screen for rele- vant biological activities. Those include screening for contaminants interacting with multiple nuclear receptors (NR) including AR (Brand et al., 2013; Cavallin et al., 2014; Mehinto et al., 2015; Roberts et al., 2015), AhR (Eichbaum et al., 2014; Escher et al., 2014) and GR (Brand et al., 2013; Cavallin et al., 2014; Mehinto et al., 2015; Roberts et al., 2015) and TR (Escher et al., 2014; Jia et al., 2015). Most of these studies were performed by transcription-based assays which are very sensitive, specific, and effect-based. However, they are time-consuming and require a 2-step validation to determine the full spectrumof endocrinedisrupting activities in each sample: afirst screen is performed in an agonist mode and an additional screen needs to be performed in the antagonist mode. To account for the entire spectrum of receptor-interacting contaminants in a single screen, we developed and validated a low- cost, high-throughput imaging-based assay for quantitative imaging of translocation from the cytoplasm to the nucleus of fluorescently labeled NR chimeric constructs in mammalian cells. This transloca- tion occurs in response to agonists or antagonists,thus reporting an unbiased endocrine disruptive activity of the tested sample in a 2 single step (Jones et al., 2020; Stavreva et al., 2012; Stavreva et al., 2016). Wide screening for endocrine disrupting activities in the environ- ment is important, it does not require identification of knownhormones or specific chemical structures. Thus, we employed ourmammalian-cell based bioassays to screen samples from several major rivers in Virginia, some of which also supply drinking water. We assessed bioactivity of these samples across four major classes of EDCs (androgenic, glucocor- ticoid, aryl hydrocarbon and thyroid) and demonstrate that these rivers are frequently positive formultiple activities. The persistent presence of low-level hormonal activities may negatively affect fish and other aquatic organisms and may also indirectly affect human health. 2. Materials and methods 2.1. Chemicals Testosterone, Dexamethasone, 3,3′,5-Triiodo-L-thyronine sodium salt powder (T3) and the organic solvent DMSO were purchased from Sigma (catalog Nu: T1500, D1756, T6397, and D2650, respectively). CAY10465 (catalog Nu: 10006546) was purchased from Cayman Chemical. 2.2. River water samples collection and processing Water samples were collected as part of the ongoing StreamSweepers Program at the Center for Natural Capital (CNC), Orange VA. They were collected between 2016 and 2018 from different geographic locations (Fig. 1 and Supplemental Table 1) and included two replicas of grab water samples which were processed and concentrated according to a previously published protocol (Ciparis et al., 2012). Briefly,water samples were collected in glass bottles and stored at 4 °C until processing. The water sampleswere filtered through a GF/F filter (0.7 μm) using a solvent rinsed all-glass apparatus. Filters were rinsed with 1 ml of methanol to liberate soluble compounds from the retained suspended solids. Filtered samples and blanks were subjected to solid phase extraction (SPE) using OASIS® HLB (200 mg) glass cartridges (Waters Corporation, Milford, MA). Cartridges were sequentially pre-conditioned, and the filtered samples were loaded onto the cartridge at a flow rate of 5–6 ml/min (continuous vacuum). Analytes were eluted from the car- tridge with 100% methanol and concentrated by evaporation. For bio- logical testing, samples were reconstituted in DMSO and diluted in growth media to a final 1000× concentration from the original water volume and added to cells at 200× concentration. Multiple samples were collected alongside the same river basin on the same day to exam- ine the effect of the site location on the presence of contamination. 2.3. Cell treatment and imaging The method for quantitative imaging of AR, GR, TR and AhR have been described previously (Gonsioroski et al., 2020; Jones et al., 2020; Stavreva et al., 2012; Stavreva et al., 2016). Briefly, all cell lines were maintained at 37 °C in tetracycline -containingmedia (DMEMmedium, supplemented with 10% fetal bovine serum (Sigma, St. Louis, MO), Pen/ strep, and glutamine (both from Invitrogen, Carlsbad, CA) supple- mented with 5 μg/ml of Tetracycline (Sigma, St. Louis, MO) dissolved at 1000× in EtOH) to suppress expression of the constructs prior to test- ing, and were not cultured for more than 3–4 weeks. Cells expressing the green fluorescent protein (GFP)-tagged AR, GR, and AhR constructs were plated in 384well plates (Matrical, CatalogNumberMGB101–1-2- LG-L) at 5000 cells per well without tetracycline in DMEM containing 10% charcoal stripped serum (Hyclone, Logan, UT) and grown at 37 °C overnight to allow expression of the GFP-tagged constructs. As GFP- GR-TRβ expressing MCF cells require longer time to express the con- struct, these cells were first cultured for 24 h without tetracycline in DMEM medium containing 10% charcoal stripped serum and then plated in 384 well plates at 7000 cells per well in the same media for Fig. 1.Map showing overall and focused locations of the collected samples. D.A. Stavreva, M. Collins, A. McGowan et al. Science of the Total Environment 773 (2021) 145602 additional 24 h. Concentrated water samples (at 200× concentration), vehicle controls (1% DMSO), as well as the positive controls Dex or tes- tosterone, respectively, were added to cells at various concentrations (up to 100nM) for 30minwhen screening for GR and AR.When screen- ing for AhR and TR samples and vehicle controls were added for 3 h using CAY 10465 (up to 2.5 μM) or T3 (up to 100 nM) as positive con- trols, respectively. Blanks, solvent controls, and positive controls hor- mones were included in each batch and four replicates of each sample were analyzed. Cells were then fixed with 4% paraformaldehyde in PBS for 10 min, washed 3× with PBS, stained with 4′,6-diamidino-2- phenylindole (DAPI) for 10 min and after 3 final washes with PBS were imaged using the Perkin Elmer Opera QEHS Image Screening System or the Yokogawa CV7000S high-throughput Imaging System. Alternatively, the plates were sealed and kept in PBS at 4 °C for later imaging. 2.4. Automated imaging and analysis A PerkinElmer (Waltham, MA) Opera QEHSHigh-Content Screening platform was used for fully automated confocal collection of images. This system employed a 40× water immersion objective lens, laser 3 illuminated dual Nipkow spinning disk, and cooled charge-coupled de- vice cameras to digitally capture high-resolution confocal fluorescence micrographs (323 nm pixel size with 2 × 2 camera pixel binning). Additional imaging experiments were carried out using Yokogawa CV7000S high-throughput dual spinning disk confocal microscope. Im- ages were acquired with a 40× Olympus PlanApoChromat air objective (NA 0.9) and two sCMOS cameras (2560 × 2160 pixels) using camera binning of 2 × 2 (Pixel size 325 nm). Samples were sequentially imaged using 488 nm and 405 nm excitation lasers and a 405/488/561/640 nm excitation dichroic mirror. Fluorescent signals were collected using the 561 nm emission dichroic mirror and BP525/50 and BP445/45 mirrors in front of the two sCMOS cameras, respectively. 2.5. Theory/calculation An image analysis pipelinewas customized using the Columbus soft- ware (Perkin Elmer) to segment automatically the nucleus using the DAPI channel and then construct a ring region (cytoplasm) around the nucleus mask for each cell in the digital micrograph. The pipeline auto- matically calculated the mean GFP intensity in both compartments using the GFP channel and translocation was calculated as a ratio of Image of Fig. 1 D.A. Stavreva, M. Collins, A. McGowan et al. Science of the Total Environment 773 (2021) 145602 these intensities. Each value was further normalized to a control (DMSO) sample on the same plate. Data were analyzed using SigmaPlot v. 11 (SPSS Inc., Chicago, IL) as previously described (Stavreva et al., 2012; Stavreva et al., 2016). Briefly, the mean was computed across four replicates of each sample, and one-way ANOVAs compared activity of all tested samples to the negative controls following Holm-Sidak cor- rection for multiple comparisons. The frequency for hormonal activities was based on double testing of the samples (two grab samples were tested from most locations, see Supplemental Table 1 for details). We scored any site being positive when at least one of the samples tested positive. Translocation responses to known concentration of activating hormones were applied to generate standard curves, that were used to estimate equivalent concentrations (in nM) of contaminants in the screenedwater samples. For a better comparisonwith the existing pub- lished data, in some cases, these were further converted to ng/l. 3. Results and discussion 3.1. Samples distribution and collection The water samples were collected over the span of 3 years at 45 lo- cations alongmajor water supplies in the state of Virginia (Fig. 1). Sam- ples were from the Rappahannock river and its tributaries, and the Mattaponi river (see Supplemental Table 1 for details). The Rappahan-nock River is the longest river in Virginia flowing from the Blue Ridge Mountains to Chesapeake Bay. The Mattaponi River is the second major watershed in Virginia and joins the York River which also flows into the Chesapeake Bay. The Mattaponi river is an excellent spawning andnursery habitat for several species of anadromousmigratoryfish in- cluding river herring, shad, and striped bass. In addition to beingwidely used for recreational activities, both rivers support key agricultural ac- tivities in Virginia, and provide water for livestock, irrigating crops, and other industries including blue crab, oyster, and fisheries. To assure the current and future health of these river ecosystems it is important to Fig. 2.Representativemicrographs showing translocation of theGFP-tagged chimeric construct for GFP-AR, GFP-GR and GFP-GR-TRβ, respectively and 2500 nM CAY 19465 for the GFP-AhR-e 4 screen and monitor these river sources for the presence of emerging contaminants with endocrine disrupting potential. 3.2. Detection of androgen receptor-interacting contaminants Androgen receptor at uninduced state resides in the cytoplasm and moves to the nucleus in response to binding by antagonists or agonists (Fig. 2A). Nuclear AR acts as a transcription factor (Dasgupta et al., 2014) and is responsible for the physiological effects of testosterone and its more active metabolite, 5α-dihydrotestosterone (DHT). In mammals, testosterone is mainly produced by the testis in males and the ovary in females. In addition tomale sexuality and reproductive health, andro- gens are also critical for the female reproductive system. Many synthetic compounds potentially released into the environ- ment have been studied for their endocrine disrupting potential. Some exhibit cross-reactivity with AR. For example, potent estro- genic compounds, such as α-zearalanol (α-ZA) and its derivatives, pesticide metabolites M2 compound and DDE, cosmetics such as benzophenone 2, and bisphenols, such as chlorinated BPA and BPC, are also anti-androgens, with affinities in the sub-to micromolar range (reviewed in Toporova and Balaguer, 2020). To test for pres- ence of AR-interacting contaminants, GFP-AR translocation to the nucleus in response to water samples was compared to the negative control (DMSO) and the activity quantified based on translocation induced by testosterone, the natural hormone (Figs. 2A and 3A). Sur- prisingly, most tested sites (70%) were positive for AR-interacting contaminants (red color in Figs. 4, 5). Using the translocation re- sponse to known concentrations of testosterone, a standard curve was generated (Fig. 3C) and the adjusted concentration of contami- nants in the most positive sample (M1-17_R1, Fig. 3A and B) was es- timated as 1.04 ± 0.04 ng of testosterone equivalent (TestoEq)/l (N = 4, ±SEM). This is in the lower range of previously reported levels of AR-agonist for water sources in US, estimated in the range of 1.6 to 4.8 ng DHTEq/l (Conley et al., 2017); s in the present of their respective ligands (100 nMof Testosterone, Dexamethasone and T3 xpressing cells). Scale bar 20 μm. Image of Fig. 2 Fig. 3. Screening of water samples for AR-interacting contaminants. A) GFP-AR translocation induced by the 200× concentrated samples. B) Representative micrographs showing translocation of the GFP-AR from two positive samples (marked orange in A). Scale bar 20 μm. C) Linear response of the GFP-AR translocation to low levels (up to 0.5 nM) of Testosteronewas used to estimate Testosterone equivalent (TestoEq) in the screenedwater samples. D) Calculated nMTestoEq in 1× samples based on the standard curve presented in (C). D.A. Stavreva, M. Collins, A. McGowan et al. Science of the Total Environment 773 (2021) 145602 In the last two decades, many studies revealed an increasing fre- quency of worldwide contamination of the water, soil and other envi- ronmental sources with agonists and antagonists of androgen alone or in combination with compounds which mimic other hormones, such Fig. 4. Detection of four classes of EDCs at different locations along Rappahannock river and its AhR (yellow) and TR (green). 5 as estrogen, thyroid and/or progesterone (Hotchkiss et al., 2008; Schug et al., 2016; Soto et al., 2004). Monitoring environmental androgenic activities has been challeng- ing because most efforts have been directed to identification of precise tributaries, Hughes, Robinson, and Rapidan rivers. Color indication for AR (red), GR (blue), Image of Fig. 3 Image of Fig. 4 Fig. 5. Detection of four classes of EDCs at different locations along Mattaponi River. Color indication for AR (red), GR (blue), AhR (yellow) and TR (green). D.A. Stavreva, M. Collins, A. McGowan et al. Science of the Total Environment 773 (2021) 145602 chemical structure for the various compounds which are present in small amounts in environmental samples (Backe et al., 2011; Chang et al., 2008) reviewed in Scholz et al. (2013). Recent studies have shifted to functional detection of agonist and antagonist effects using cell-based yeast and mammalian cells reporter assays or whole organisms (am- phibians and fish) (Hoffmann and Kloas, 2016; Liu et al., 2009; Scholz et al., 2013). These are important changes in providing meaningful in- formation that can be used to establish limits for hormonal activities in the water, soil and other environmental samples. Considering the widespread presence of AR-interacting contaminants detected in most of the locations tested in our study, future studies are needed to deter- mine whether these contaminations pose a risk for the health of the ecosystems and, thus indirectly to humans. 3.3. Detection of glucocorticoid receptor-interacting contaminants Glucocorticoid receptor (GR) is expressed in most vertebrate tissues andmediates the actions of glucocorticoid hormones, a family of steroids involved in many critical physiological processes in mammals (Kadmiel and Cidlowski, 2013; Odermatt and Gumy, 2008). Previous experiments (Baxter and Tomkins, 1970; Sibley and Tomkins, 1974) revealed that nu- clear localization of the receptor-steroid complex follows steroid bind- ing. Translocation of the GR from the cytoplasm to the nucleus (Fig. 2B) was visualized using immunohistochemistry (Papamichail et al., 1980). Subsequently, two distinct nuclear localization signals (NL1 and NL2) re- sponsible for this translocation were defined (Picard and Yamamoto, 1987). Upon nuclear translocation, GR binds to chromatin targets to reg- ulate gene expression (Voss and Hager, 2014). Using a previously described highly sensitive mammalian cell line that expresses GFP-tagged GR (Walker et al., 1999), we detected gluco- corticoid receptor-interacting activity in 22% of 45 locations tested which are marked in Figs. 4 and 5 (blue color) and detailed in Supple- mental Table 1 and Figure Supplemental Figure 1. The highest activity was detected in sample M1–11_R1 and was estimated at 2.34 ± 6 0.15 ng DexEq/l (N = 4, ±SEM). A recent screen in US and Puerto Rico waters reported GR agonism in a range of 6.0 to 43 ng DexEq/l (Conley et al., 2017). These levelsmay be capable of inducing physiolog- ical effects in aquatic organisms. For example, exposure to cortisol at 16 ng/l was shown to decrease the locomotor activities of fish embryos (Zhao et al., 2018). Moreover, fludrocortisone acetate at environmental relevant concentrations decreased blood leukocyte number and altered gene expression and circadian rhythm in zebrafish (Zhao et al., 2016). Glucocorticoids are among the most widely prescribed drugs due to their anti-inflammatory action (Barnes, 2011; Barnes and Adcock, 2009). Thus, their presence in the environment and especially in water is not surprising. Indeed, a study in the Netherlands found such activity inwastewater effluents and surface water in all tested samples (Van der Linden et al., 2008). Glucocorticoid activitywas also found in riverwater, as well as in treated or untreated wastewater in the US, Switzerland, CzechRepublic, and China (Berninger et al., 2019; Conley et al., 2017; Jia et al., 2016; Jones et al., 2020; Macikova et al., 2014; Stavreva et al., 2012). In addition, activities were detected in extracts of agricultural soil in China combined with contaminations interacting with estrogen receptor (ER), AR, progesterone receptor (PR), andmineralocorticoid re- ceptor (MR) (Zhang et al., 2018). A growing body of literature implicates many environmental contaminants (e.g. metals, metalloids, pesticides, bisphenol analogues, plasticizers, flame retardants and pharmaceuti- cals) and chemicals in disrupting GR (Zhang et al., 2019). The presence of GR-interacting contaminants in the environment is of increasing interest because dysregulated GR signaling is associated with immune diseases, allergies, mood and cognitive disorders, meta- bolic disorders, cardiovascular disease, and cancers (Carnahan and Goldstein, 2000; Odermatt and Gumy, 2008). 3.4. Detection of aryl hydrocarbon receptor-interacting contaminants The aryl hydrocarbon receptor (AhR) is a nuclear receptor that reg- ulates transcription through binding to DNA following activation by Image of Fig. 5 D.A. Stavreva, M. Collins, A. McGowan et al. Science of the Total Environment 773 (2021) 145602 exogenous and endogenous ligands. Similarly to AR andGR, AhR resides in the cytoplasm in an uninduced state and translocates to the nucleus in the presence of specific ligands (Fig. 2C). Initially named “dioxin” re- ceptor for its discovery using radiolabeled TCDD in the 1970s, AhR has since been found to interact with many natural and man-made com- pounds (Hale et al., 2017). While first identified as the mediator of dioxin-induced toxicity, the AhR has been implicated in numerous pro- cesses including cell proliferation, adhesion andmigration, birth defects, immune system function, neurotoxicity, lethality, tumor promotion, and changing enzymatic functions (e.g., CYP1A1/2 and CYP1B1) induc- tion (Kolluri et al., 2017; Larigot et al., 2018; Xie et al., 2016). We used a cell line expressing GFP-tagged AhR to test for pres- ence of AhR-interacting activities (Jones et al., 2020). In the current study, we detected abundant AhR activity in Virginia river samples in 60% of tested locations (indicated by yellow color in Figs. 4 and 5). Based on standard curve generated by using CAY19465 as a stan- dard for AhR activation, activity in the most positive sample (M2- 1_R2) was estimated to be 1342.56 ± 48.96 ng CAY 19465 Eq/l (N = 4, ±SEM) (see Figure Supplemental Figure 2 for details). These high levels are a result of a relatively low translocation efficiency in response of GFP-AhR to CAY 19465whichwas detected at concentra- tions above 150 nM CAY 19465 and plateaued at 2500 nM (data not shown). We refrained from using dioxin as AhR ligand because it is highly toxic and represents a human and environmental hazard. The presence of chemicalswith known affinity to the AhR in environ- mental water samples have been documented since themid-1900s, and many of these chemicals persistent as contaminants today (Dyke et al., 1997; Zgheib et al., 2018). The most prevalent strategies for detecting AhR activity in water samples have been similar to those used for other hormone receptors. These include gas or liquid chromatography- tandem mass spectrometry (GC-/LC-MS), cell-based reporter gene as- says, or in vivo models measuring physiological endpoints (Otarola et al., 2018). Detection of AhR-mediated activities in waterways has been well documented in the past decade (Brack et al., 2007; Chou et al., 2006; Dagnino et al., 2010). Most known AhR ligands are hydrophobic compounds that enter the waterways through fuel combustion, waste incineration, and runoff or leaching from landfills (Brack et al., 2007). Pesticides also represent a major source of contamination. A screen of 200 pesticides identified 11 (acifluorfen-methyl, bifenox, chlorpyrifos, isoxathion, quinalphos, chlorpropham, di-ethofencarb, propanil, diuron, linuron, and prochloraz) as AhR ligands (Kjaerstad et al., 2010). In addi- tion, many plant- and organism-derived polyphenols also modulate AhR activity, such as the isoflavone resveratrol in red wine (Nguyen et al., 2015), the flavonoid curcumin in turmeric (Ciolino et al., 1998; Nishiumi et al., 2007), and epigallocatechin in green tea (Palermo et al., 2003). Interestingly, these molecules act as AhR antagonists, which may be beneficial (Choi et al., 2008). However, the notion that AhR agonists are toxic and antagonists are therapeutically beneficial seem simplistic in light of recent information. For example, indigo naturalis, an AhR agonist, promotes restoration and intestinal integ- rity in inflammatory bowel disease (Mizoguchi et al., 2018). In sum, dioxins and dioxin-like EDCs exert their biological and toxi- cological activities through activation of AhR and these compounds can have biological effects even at low levels of exposure (Furue and Tsuji, 2019). Based on current information, the detected widespread contam- ination of Virginia rivers with AhR-interacting compounds and their possible consequences on fish and river ecosystems should be exam- ined further. 3.5. Detection of thyroid receptor beta-interacting contaminants Thyroid hormones (THs) are iodine-containing hormones in- dispensable for normal development, growth, and metabolism of most cells and tissues. The predominant TH secreted by the thy- roid gland is 3,3′,5,5′-tetraiodothyronine (thyroxine, T4), which 7 is the precursor for the active T3 (3,3′,5-triiodothyronine) pro- duced by partial deiodination in peripheral tissues. THs exert their action primarily by activation of thyroid hormone receptors (TR α and β) expressed in most tissues with a specific pattern during development, depending on their function (Cheng et al., 2010; Tancevski et al., 2011; Zoeller et al., 2002). TRs, similar to other NR, are ligand-dependent transcription factors that regulate gene expression by interaction with thyroid hormone response elements (TREs) in the promoter/enhancers DNA loci (Sap et al., 1986; Weinberger et al., 1986). Due to their wide expression, TRs regulate many processes in human physiology from metabolism, bone formation and cardiac output, to neuronal development (Cioffi et al., 2018; Duncan Bassett and Williams, 2018; Gilbert et al., 2012; Williams, 2008; Yen, 2001; Zoeller et al., 2007). We tested TRβ translocation to the nucleus using a GFP-GR-TRβ con- struct which renders the receptor cytoplasmic in the absence of a ligand Fig. 2D, see also inset in Figure Supplemental Figure 3A (Stavreva et al., 2016)]. Using this strategy, we have previously identified novel TRβ an- tagonists from the Tox21 chemical library (Paul-Friedmanet al., 2019) as well as TRβ-interacting environmental contaminants (Jones et al., 2020; Stavreva et al., 2012; Stavreva et al., 2016). In the present study, we de- tected TRβ interacting contaminants in 42% of river samples from 45 tested locations (indicated by green color in Figs. 4 and 5 see also Figure Supplemental Figure 3 for details). The highest TR activitywas de- tected in sample M1-18_R1, estimated to be 5.73 ± 0.6 ng T3 Eq/l (N= 4, ±SEM). Using the TR antagonist amiodarone hydrochloride (AH) as a standard, amuch higher TR (antagonistic) activity in the range of 21.2 to 313.9 μg AH Eq/l were reported in water samples in China (Li et al., 2014). Studies of disrupted thyroid function have included efforts to iden- tify specific ECDs in environmental samples (Fini et al., 2007; Grimaldi et al., 2015; Scholz et al., 2013; Steinberg, 2013). However, thee critical issue is the detection of environmental TR-interacting compoundswith- out the need for costly and time-consuming characterization of their molecular structures. Previous in vitro approaches used several nuclear TR transactivation assays (Murk et al., 2013). Based on an extensive review, the panel recommended a battery of methods to classify chemicals of lesser or higher concern for furtherhazard and risk assess- ment. Considering that the disruption of thyroid hormone signaling in a multicellular organism may trigger complex adverse outcomes, addi- tional approaches to assess the disruption are being currently evaluated (Noyes et al., 2019). Addressing the central issue of TR activation, the GFP-GR-TRβ translocation assay is an alternative in vivo, activity-based method for detecting both, TRβ agonists and antagonists. Because thyroid function is particularly critical during early development, detec- tion of TR-interacting activities in thewater of major Virginia rivers is of great concern. Although the sources of such contaminants are un- known, some medications frequently used for hypothyroidism, such as Synthroid, could be present in the rivers. The sources of this contam- ination should be investigated further. 4. Conclusions Exposures to EDCs are very costly by increasing disease and disability (Kassotis et al., 2020). Identification of substances having endocrine-disrupting potential and their regulation is carried out in EU, where substantial efforts are directed into developing comprehensive effect-based methods. At present, 205 substances, of which 16 are also endocrine disruptors, are included in the EU list of substances of very high concern (SVHC) and are subject to increased regulatory scrutiny and higher reporting standards. Moreover, ambitious multifaceted pro- jects, such as the SOLUTIONS Project (https://www.solutions-project. eu/), coordinate efforts to develop methods for detection and monitor of EDCs as well as efficient policies to reduce potential human exposure. In the USA, regulations are strictly risk-based and pre-marketing testing is usually not required. In addition, most screening and testing efforts https://www.solutions-project.eu/ https://www.solutions-project.eu/ D.A. Stavreva, M. Collins, A. McGowan et al. Science of the Total Environment 773 (2021) 145602 focus on estrogenic contaminants. Less is known about contamination with other classes of EDCs. The data presented here reveals contamina- tion of riverswith four classes of EDCs.Multiple endocrine disrupting ac- tivitieswere detected inwater samples collected from45 locations along Virginia rivers. Many locations were positive for multiple activities, and 40% of samples were positive for at least three of the four tested activi- ties. These findings suggest the presence of complex mixtures of EDCs, where individual biological activities could influence each other. Future studies are needed to address the possible effects of these activities on fish and wildlife in the screened locations. An important next step will be to also evaluate endocrine disrupting activities in samples of drinking water in the same areas to identify and characterize possible human exposure. Supplementary data to this article can be found online at https://doi. org/10.1016/j.scitotenv.2021.145602. Funding This work was supported by the Intramural Research Program, NCI, NIH, Project ZIA BC 010308 "In vivo Imaging Analysis of Steroid/Nuclear Receptor Function" CRediT authorship contribution statement Diana A. Stavreva: Conceptualization, Data curation, Formal analy- sis, Funding acquisition, Investigation, Project administration, Supervi- sion, Validation, Writing – original draft, Writing – review & editing. Michael Collins: Conceptualization, Writing – review & editing. Andrew McGowan: Data curation, Visualization, Writing – original draft,Writing– review& editing. LyubaVarticovski: Conceptualization, Project administration, Writing – original draft, Writing – review & editing. Razi Raziuddin: Data curation, Writing – original draft, Writing – review & editing. David Owen Brody: Funding acquisition, Investigation, Writing – review & editing. Jerry Zhao: Formal analy- sis, Writing – review & editing. Johnna Lee: Funding acquisition, In- vestigation, Writing – review & editing. Riley Kuehn: Funding acquisition, Investigation, Writing – review & editing. Elisabeth Dehareng: Funding acquisition, Investigation, Writing – review & editing. Nicholas Mazza: Funding acquisition, Investigation, Writing – review & editing. Gianluca Pegoraro: Formal analysis, Methodology, Resources, Software,Writing – review& editing.Gordon L. Hager: Con- ceptualization, Project administration, Supervision, Writing – review & editing. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influ- ence the work reported in this paper. Acknowledgements We thank all participants in the StreamSweepers Program at the Center for Natural Capital, Orange, VA for water sample collection. We also thank Mr. Kelly W. Garton and Ms. Melanie Hudock, current and former coordinators of the Science Internship Program at Whitman High School, Bethesda, MD. References Ankley, G.T., Jensen, K.M., Makynen, E.A., Kahl, M.D., Korte, J.J., Hornung, M.W., ... Gray, L.E., 2003. 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Introduction 2. Materials and methods 2.1. Chemicals 2.2. River water samples collection and processing 2.3. Cell treatment and imaging 2.4. Automated imaging and analysis 2.5. Theory/calculation 3. Results and discussion 3.1. Samples distribution and collection 3.2. Detection of androgen receptor-interacting contaminants 3.3. Detection of glucocorticoid receptor-interacting contaminants 3.4. Detection of aryl hydrocarbon receptor-interacting contaminants 3.5. Detection of thyroid receptor beta-interacting contaminants 4. Conclusions Funding CRediT authorship contribution statement Declaration of competing interest Acknowledgements References
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