Assessing Toxicogenomics Effects of a Synthetic Androgen on Japanese Quail and the Development of an Avian Vitellogenesis Model

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The Challenge: Endocrine active chemicals (EAC) are known to interfere with hormonally regulated physiological processes, thereby affecting signaling in the hypothalamic-pituitary-gonadal-liver (HPGL) axis and commonly resulting in reproductive dysfunction. Computational models that relate hormonal and genomic biomarkers within the HPGL axis to the reproductive cycle and ecologically relevant endpoints have been developed for fish; however, no similar model is available for birds. These models are very useful for evaluating how EAC-induced changes in physiological systems enhance or inhibit embryonic development, reproduction, and growth.

The Science: Previous studies at PWRC investigating the effects of the synthetic anabolic steroid 17β-Trenbolone (17βT) across multiple generations in Japanese quail found genomic, endocrine and reproductive effects. Different levels of response were evident based on the timing (e.g., stage of development), the route (e.g., dietary vs. in ovo) and length of exposure (e.g., adult only vs hatch through sexual maturation). In the initial studies, however, genomic and biochemical responses were collected on mature adults after 8 or more weeks of exposure. No data were generated on endocrine related effects at the onset of EAC exposure, a period critical for determining whether or not the birds can compensate for exogenous endocrine stress and maintain normal reproductive capacity.

The Future: Building upon this earlier work, JQ were sampled over 21 days following the start of 17βT exposure to identify and link changes in key endocrine-related gene expression and biochemical responses along the HPGL axis to changes in egg laying. Additionally, a novel double dye technique was applied to a subset of these quail to determine how impaired vitellogenesis relates to altered egg yolk development. Data collected from this research will parameterize a computational model and provide researchers with a tool that incorporates molecular and biochemical endpoints to predict effects on egg production in birds exposed to EACs. This model will facilitate the interpretation of field-measured data by creating a data link between biomarkers and ecologically relevant bioindicators such as species productivity, critical for natural resource management and risk assessment.