Mathematical models can aid the design of genetic circuits, but may yield inaccurate results if individual parts are not modeled at the appropriate resolution. To illustrate the importance of this concept, we study transcriptional cascades consisting of two inducible synthetic transcription factors connected in series. Despite the simplicity of this design, we find that accurate prediction of circuit behavior requires mapping the dose responses of each circuit component along the dimensions of both its expression level and its inducer concentration. Using this multidimensional characterization, we were able to computationally explore the behavior of 16 different circuit designs. We experimentally verified a subset of these predictions and found substantial agreement. This method of biological part characterization enables the use of models to identify (un)desired circuit behaviors prior to experimental implementation, thus shortening the design–build–test cycle for more complex circuits.

中文翻译：

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零件的多维表征提高了遗传电路的建模精度

数学模型可以帮助设计遗传回路，但如果没有以适当的分辨率对各个部分进行建模，则可能会产生不准确的结果。为了说明这一概念的重要性，我们研究了由两个串联连接的诱导型合成转录因子组成的转录级联。尽管这种设计很简单，但我们发现准确预测电路行为需要沿着每个电路组件的表达水平和诱导剂浓度的维度绘制剂量响应。使用这种多维表征，我们能够以计算方式探索 16 种不同电路设计的行为。我们通过实验验证了这些预测的一个子集，并发现了实质性的一致性。