Journal
EXPERIMENTAL AND CLINICAL ENDOCRINOLOGY & DIABETES
Volume 119, Issue 2, Pages 86-94Publisher
JOHANN AMBROSIUS BARTH VERLAG MEDIZINVERLAGE HEIDELBERG GMBH
DOI: 10.1055/s-0030-1267239
Keywords
anabolic agents; trenbolone acetate; estradiol; gene expression biomarker; real-time RT-qPCR
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Funding
- Onderstepoort Veterinary Institute, Pretoria, South Africa
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In the European Union the use of anabolic hormones in meat production is forbidden since 1988 and this ban of anabolic agents in animal production is strictly controlled. New hormone cocktails passing the detection systems are attractive for the practice and so new approaches to discover their illegal use have to be developed steadily. Verifying physiological effects caused by anabolic steroids will be a new way to develop potential monitoring systems. One promising matrix in female animals will be vaginal smear containing vaginal epithelial cells, because the vaginal epithelium is a primary steroid hormone responsive organ. In this study we quantified the gene expression in vaginal smear of sexually mature cattle in order to observe physiological effects. Further we aimed to establish a new screening method by testing the effect of a combination of certain anabolic steroid hormones on physiological regulations of mRNA expression of selected genes. In an animal trial Nguni heifers were treated with the anabolic combination trenbolone acetate plus estradiol. Vaginal smear samples were taken at 4 different time points. Gene expression of 27 candidate genes, selected by screening the actual literature for steroidal effects on vaginal epithelial cells, were estimated using quantitative real-time RT-PCR. There were different expression changes observed at different time points. It could be shown that the applied anabolic combination significantly influenced the expression of the steroid receptor ER alpha, the keratinization factor CK8, the proinflammatory interleukins IL-1 alpha and IL-1 beta, the growth factors FGF7, EGF, EGFR, IGF-1R, TGF alpha and LTF, the oncogen c-jun and other factors like actin beta and ubiquitin 3. Using biostatistical tools like principal components analysis or hierarchical cluster analysis, the potential to develop a gene expression pattern for targeting the illegal use of growth promoters could be demonstrated.
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