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Building a minimal and generalizable model of transcription factor-based biosensors: Showcasing flavonoids

机译:构建基于转录因子的生物传感器的最小和最广泛的模型:展示黄酮类化合物

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Progress in synthetic biology tools has transformed the way we engineer living cells. Applications of circuit design have reached a new level, offering solutions for metabolic engineering challenges that include developing screening approaches for libraries of pathway variants. The use of transcription-factor-based biosensors for screening has shown promising results, but the quantitative relationship between the sensors and the sensed molecules still needs more rational understanding. Herein, we have successfully developed a novel biosensor to detect pinocembrin based on a transcriptional regulator. The FdeR transcription factor (TF), known to respond to naringenin, was combined with a fluorescent reporter protein. By varying the copy number of its plasmid and the concentration of the biosensor TF through a combinatorial library, different responses have been recorded and modeled. The fitted model provides a tool to understand the impact of these parameters on the biosensor behavior in terms of dose-response and time curves and offers guidelines to build constructs oriented to increased sensitivity and or ability of linear detection at higher titers. Our model, the first to explicitly take into account the impact of plasmid copy number on biosensor sensitivity using Hill-based formalism, is able to explain uncharacterized systems without extensive knowledge of the properties of the TF. Moreover, it can be used to model the response of the biosensor to different compounds (here naringenin and pinocembrin) with minimal parameter refitting.
机译:合成生物学工具的进步改变了我们工程师生活细胞的方式。电路设计的应用达到了新的水平,为代谢工程挑战提供了解决方案,包括开发途径变体图书馆的筛选方法。用于筛选的转录因子的生物传感器已经显示出有前途的结果,但传感器与感测分子之间的定量关系仍然需要更合理的理解。在此,我们已成功开发了一种新的生物传感器,以基于转录调节剂检测泛膜。已知对Naringenin响应荧光报告蛋白的致垃圾转录因子(TF)与荧光报告蛋白组合。通过改变其质粒的拷贝数和通过组合库中的生物传感器TF的浓度,已经记录和建模了不同的响应。该拟合模型提供了一种工具,以了解这些参数在剂量 - 响应和时间曲线方面对生物传感器行为的影响,并提供指南,以构建以提高较高滴度的提高敏感性和线性检测能力的构建体。我们的型号,首先明确考虑了使用基于山的形式主义的体传感器敏感性对生物传感器灵敏度的影响,能够解释无表征系统,而无需广泛了解TF的性质。此外,它可用于将生物传感器的响应模拟到不同的化合物(这里的Naringenin和Pinocembrin),具有最小的参数改装。

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