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Using Synthetic Biology methods to construct a functional estrogen biosensor based on split Nanoluciferase activity
Journal of Biological Chemistry ; 299(3 Supplement):S135, 2023.
Article in English | EMBASE | ID: covidwho-2314280
ABSTRACT
The presence of estrogenic compounds (endocrine-disruptors, EDCs) in the water supply raises concerns about human and aquatic health. Current methods for detecting estrogen contamination require expensive, time-consuming techniques such as liquid chromatography-mass spectrometry and high-performance liquid chromatography. Previously reported estrogen biosensors required multiple cloning and transformation steps for successful detection in bacteria. Synthetic biology allows for the construction of genetic devises composed of DNA sequences modified to be interchangeable and provide novel functions. New tools and devices are constantly needed to enhance the already extensive list of novel genetic parts. Our approach to the design of an estrogen responsive element uses methodology developed in the Wells lab (Elledge et al, 2021) to detect SARS-CoV-2 antibodies. This methodology takes advantage of the split Nanoluciferase (spLUC) protein divided into two functional domains (designated SmBit and LgBit). Based on rational engineering design we express dimerization dependent LgBit and SmBit fused to the Estrogen Receptor alpha protein (ERalpha) in bacteria cells. These two monomeric proteins will dimerize in the presence of estrogen, reconstitute the split luciferase enzyme and reestablish enzyme activity. Cells can be lysed, and luminescence detected to quantify estrogen present in the sample. We present here the construction strategy and proof of concept data demonstrating the efficiency of this dual-functional biosensor and its effectiveness for detection of estrogenic compounds in contaminated water. NSF-REU-1852150, REU Site A multisite REU in Synthetic Biology, 2019.Copyright © 2023 The American Society for Biochemistry and Molecular Biology, Inc.
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Full text: Available Collection: Databases of international organizations Database: EMBASE Language: English Journal: Journal of Biological Chemistry Year: 2023 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: EMBASE Language: English Journal: Journal of Biological Chemistry Year: 2023 Document Type: Article