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Gewählte Publikation:

Publikationstyp: Zeitschriftenaufsatz
Dokumentart: Originalarbeit

Publikationsjahr: 2017

AutorInnen: Zutz, C; Wagener, K; Yankova, D; Eder, S; Möstl, E; Drillich, M; Rychli, K; Wagner, M; Strauss, J

Titel: A robust high-throughput fungal biosensor assay for the detection of estrogen activity.

Quelle: Steroids. 2017; 126:57-65



Autor/innen der Vetmeduni Vienna:

Drillich Marc
Kober-Rychli Kathrin
Möstl Erich
Wagener Karen
Wagner Martin
Zutz Christoph

Beteiligte Vetmed-Organisationseinheiten
Institut für Lebensmittelsicherheit, Lebensmitteltechnologie und öffentliches Gesundheitswesen in der Veterinärmedizin, Abteilung für Lebensmittelmikrobiologie
Institut für Physiologie, Pathophysiologie und Biophysik, Abteilung für Physiologie, Pathophysiologie und experimentelle Endokrinologie
Universitätsklinik für Wiederkäuer, Bestandsbetreuung bei Wiederkäuern


Zugehörige(s) Projekt(e): Förderung der Milchwirtschaft in Österreich (ADDA)


Abstract:
Estrogenic active compounds are present in a variety of sources and may alter biological functions in vertebrates. Therefore, it is crucial to develop innovative analytical systems that allow us to screen a broad spectrum of matrices and deliver fast and reliable results. We present the adaptation and validation of a fungal biosensor for the detection of estrogen activity in cow derived samples and tested the clinical applicability for pregnancy diagnosis in 140 mares and 120 cows. As biosensor we used a previously engineered genetically modified strain of the filamentous fungus Aspergillus nidulans, which contains the human estrogen receptor alpha and a reporter construct, in which β-galactosidase gene expression is controlled by an estrogen-responsive-element. The estrogen response of the fungal biosensor was validated with blood, urine, feces, milk and saliva. All matrices were screened for estrogenic activity prior to and after chemical extraction and the results were compared to an enzyme immunoassay (EIA). The biosensor showed consistent results in milk, urine and feces, which were comparable to those of the EIA. In contrast to the EIA, no sample pre-treatment by chemical extraction was needed. For 17β-estradiol, the biosensor showed a limit of detection of 1ng/L. The validation of the biosensor for pregnancy diagnosis revealed a specificity of 100% and a sensitivity of more than 97%. In conclusion, we developed and validated a highly robust fungal biosensor for detection of estrogen activity, which is highly sensitive and economic as it allows analyzing in high-throughput formats without the necessity for organic solvents.


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