Jeffrey S. Denny

Comparison of relative binding affinities of endocrine active compounds to fathead minnow and rainbow trout estrogen receptors

Twelve chemicals were tested for binding affinity to rainbow trout liver estrogen receptor (rbtER) and fathead minnow liver ER (fhmER). The chemicals included estradiol (E2), diethylstilbestrol (DES), ethinylestradiol (EE2), estrone (El), estriol, tamoxifen (TAM), genistein (GEN), p-nonylphenol (PNP), p-tert-octylphenol (PTOP), methoxychlor (MXC), testosterone, and methyltestosterone (MT). Relative binding affinity (RBA) was calculated for each chemical as a function of E2 binding to the receptor. The estrogens DES, EE2, and E1 bound with high affinity to both receptors, with respective RBAs of 583, 166, and 28% (fathead minnow) and 179, 89, and 5% (rainbow trout). Relative binding affinity of E3, TAM, and GEN for both fhmER and rbtER were moderate, with values between 0.3 and 5%. The alkylphenols had weak affinity for the ERs with RBAs for the fhmER of 0.1 and 0.01 for PNP and PTOP, respectively. Corresponding values for the rbtER are 0.027 and 0.009. Estradiol ([3H]E2) only partially was displaced from both the fhmER and the rbtER by MXC, T, and MT. Comparison of RBAs of the chemicals tested for fhmER and rbtER indicates that the rank order of RBAs essentially are the same for both species.

Optimization of a precision-cut trout liver tissue slice assay as a screen for vitellogenin induction: comparison of slice incubation techniques

An in vitro male rainbow trout liver slice assay has been developed for long-term incubation of precision-cut slices for the detection of vitellogenin (VTG) protein induction in response to xenobiotic chemicals. The assay was optimized to allow 72 h of incubation of slices to maximize detection of VTG, while maintaining slice viability. Two methods of incubation frequently used with rat liver slices were compared: (1) slices were submerged in media (11 degrees C) and cultured in 12-well plates (PL) with continuous shaking; or (2) slices were floated onto titanium screens, placed into glass vials, and held under dynamic organ culture (DOC) conditions (11 degrees C). Slices (200 µm) in modified L-15 media were exposed to 1.0 µM 17beta-estradiol (E2) or diethylstilbestrol (DES). Protein from media and slice was sampled for Western blot analysis, using a polyclonal antibody to detect appearance of VTG protein. Maximum VTG was seen at 72 h, with detectable protein at 24 and 48 h in slices and media following PL incubation. In contrast, slices incubated in DOC showed little detectable VTG above background levels after 72 h. This difference was not attributable to protein loss to vial or plate surfaces. Standard viability assays did not reveal any differences between slices incubated in PL or DOC. However, histopathological examination revealed earlier and more severe vacuolization in slices incubated in DOC. Significantly more E2 uptake and conversion to water-soluble metabolites was noted in PL, compared with DOC, as well as more production of VTG in response to DES and E2, correlated with less histologic change. The in vitro assay described allows tissue-level assessment of estrogenicity in aquatic organisms, and will be useful for assessing not only comparative species receptor binding and transactivation, but also the role of tissue-specific activation factors in the estrogenic response of fish.

Effects-based chemical category approach for prioritization of low affinity estrogenic chemicals

Regulatory agencies are charged with addressing the endocrine disrupting potential of large numbers of chemicals for which there is often little or no data on which to make decisions. Prioritizing the chemicals of greatest concern for further screening for potential hazard to humans and wildlife is an initial step in the process. This paper presents the collection of in vitro data using assays optimized to detect low affinity estrogen receptor (ER) binding chemicals and the use of that data to build effects-based chemical categories following QSAR approaches and principles pioneered by Gilman Veith and colleagues for application to environmental regulatory challenges. Effects-based chemical categories were built using these QSAR principles focused on the types of chemicals in the specific regulatory domain of concern, i.e. non-steroidal industrial chemicals, and based upon a mechanistic hypothesis of how these non-steroidal chemicals of seemingly dissimilar structure to 17ß-estradiol (E2) could interact with the ER via two distinct binding types. Chemicals were also tested to solubility thereby minimizing false negatives and providing confidence in determination of chemicals as inactive. The high-quality data collected in this manner were used to build an ER expert system for chemical prioritization described in a companion article in this journal.

A rule-based expert system for chemical prioritization using effects-based chemical categories

A rule-based expert system (ES) was developed to predict chemical binding to the estrogen receptor (ER) patterned on the research approaches championed by Gilman Veith to whom this article and journal issue are dedicated. The ERES was built to be mechanistically transparent and meet the needs of a specific application, i.e. predict for all chemicals within two well-defined inventories (industrial chemicals used as pesticide inerts and antimicrobial pesticides). These chemicals all lack structural features associated with high affinity binders and thus any binding should be low affinity. Similar to the high-quality fathead minnow database upon which Veith QSARs were built, the ERES was derived from what has been termed gold standard data, systematically collected in assays optimized to detect even low affinity binding and maximizing confidence in the negatives determinations. The resultant logic-based decision tree ERES, determined to be a robust model, contains seven major nodes with multiple effects-based chemicals categories within each. Predicted results are presented in the context of empirical data within local chemical structural groups facilitating informed decision-making. Even using optimized detection assays, the ERES applied to two inventories of >600 chemicals resulted in only ~5% of the chemicals predicted to bind ER.

Screening the ToxCast Phase 1 Chemical Library for Inhibition of Deiodinase Type 1 Activity

Thyroid hormone (TH) homeostasis is dependent upon coordination of multiple key events including iodide uptake, hormone synthesis, metabolism, and elimination, to maintain proper TH signaling. Deiodinase enzymes catalyze iodide release from THs to interconvert THs between active and inactive forms, and are integral to hormone metabolism. The activity of deiodinases has been identified as an important endpoint to include in the context of screening chemicals for TH disruption. To begin to address the potential for chemicals to inhibit these enzymes an adenovirus expression system was used to produce human deiodinase type 1 (DIO1) enzyme, established robust assay parameters for nonradioactive determination of iodide release by the Sandell-Kolthoff method, and employed a 96-well plate format for screening chemical libraries. An initial set of 18 chemicals was used to establish the assay, along with the known DIO1 inhibitor 6-propylthiouracil as a positive control. An additional 292 unique chemicals from the EPAs ToxCast phase 1_v2 chemical library were screened. Chemicals were initially screened at a single high concentration of 200 µM to identify potential DIO1 inhibitors. There were 50 chemicals, or 17% of the TCp1_v2 chemicals tested, that produced >20% inhibition of DIO1 activity. Eighteen of these inhibited DIO1 activity >50% and were further tested in concentration-response mode to determine IC50s. This work presents an initial effort toward identifying chemicals with potential for affecting THs via inhibition of deiodinases and sets the foundation for further testing of large chemical libraries against DIO1 and the other deiodinase enzymes involved in TH function.