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Reconstructing Dynamic Promoter Activity Profiles from Reporter Gene Data
ACS Synthetic Biology ( IF 3.7 ) Pub Date : 2018-02-19 00:00:00 , DOI: 10.1021/acssynbio.7b00223
Soumya Kannan 1 , Thomas Sams 2 , Jérôme Maury 3 , Christopher T. Workman 1
Affiliation  

Accurate characterization of promoter activity is important when designing expression systems for systems biology and metabolic engineering applications. Promoters that respond to changes in the environment enable the dynamic control of gene expression without the necessity of inducer compounds, for example. However, the dynamic nature of these processes poses challenges for estimating promoter activity. Most experimental approaches utilize reporter gene expression to estimate promoter activity. Typically the reporter gene encodes a fluorescent protein that is used to infer a constant promoter activity despite the fact that the observed output may be dynamic and is a number of steps away from the transcription process. In fact, some promoters that are often thought of as constitutive can show changes in activity when growth conditions change. For these reasons, we have developed a system of ordinary differential equations for estimating dynamic promoter activity for promoters that change their activity in response to the environment that is robust to noise and changes in growth rate. Our approach, inference of dynamic promoter activity (PromAct), improves on existing methods by more accurately inferring known promoter activity profiles. This method is also capable of estimating the correct scale of promoter activity and can be applied to quantitative data sets to estimate quantitative rates.

中文翻译:

从报告基因数据重建动态启动子活性谱

当设计用于系统生物学和代谢工程应用的表达系统时,启动子活性的准确表征很重要。例如,响应环境变化的启动子可以动态控制基因表达,而无需诱导剂化合物。然而,这些过程的动态性质对估计启动子活性提出了挑战。大多数实验方法利用报道基因表达来估计启动子活性。通常,报道基因编码一种荧光蛋白,尽管观察到的输出可能是动态的并且距离转录过程有许多步骤,但该荧光蛋白用于推断恒定的启动子活性。实际上,当生长条件改变时,一些通常被认为是组成型的启动子可以显示出活性的变化。由于这些原因,我们已经开发了一个常微分方程组,用于估计启动子的动态启动子活性,这些启动子响应于对噪声和增长率变化具有鲁棒性的环境而改变其活性。我们的方法,即动态启动子活性的推断(PromAct),通过更准确地推断已知的启动子活性谱来改进现有方法。该方法还能够估计启动子活性的正确规模,并且可以应用于定量数据集以估计定量速率。动态启动子活性的推断(PromAct)通过更准确地推断已知的启动子活性谱对现有方法进行了改进。该方法还能够估计启动子活性的正确规模,并且可以应用于定量数据集以估计定量速率。动态启动子活性的推断(PromAct)通过更准确地推断已知的启动子活性谱对现有方法进行了改进。该方法还能够估计启动子活性的正确规模,并且可以应用于定量数据集以估计定量速率。
更新日期:2018-02-19
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