School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-2000, United States.
School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-2000, United States.
ACS Synth Biol. 2023 Apr 21;12(4):1094-1108. doi: 10.1021/acssynbio.2c00593. Epub 2023 Mar 19.
Transcriptional programming leverages systems of engineered transcription factors to impart decision-making (, Boolean logic) in chassis cells. The number of components used to construct said decision-making systems is rapidly increasing, making an exhaustive experimental evaluation of iterations of biological circuits impractical. Accordingly, we posited that a predictive tool is needed to guide and accelerate the design of transcriptional programs. The work described here involves the development and experimental characterization of a large collection of network-capable single-INPUT logical operations─, engineered BUFFER (repressor) and engineered NOT (antirepressor) logical operations. Using this single-INPUT data and developed metrology, we were able to model and predict the performances of all fundamental two-INPUT compressed logical operations (, compressed AND gates and compressed NOR gates). In addition, we were able to model and predict the performance of compressed mixed phenotype logical operations (A NIMPLY B gates and complementary B NIMPLY A gates). These results demonstrate that single-INPUT data is sufficient to accurately predict both the qualitative and quantitative performance of a complex circuit. Accordingly, this work has set the stage for the predictive design of transcriptional programs of greater complexity.
转录编程利用工程转录因子系统赋予底盘细胞决策能力（布尔逻辑）。用于构建决策系统的组件数量正在迅速增加，因此对生物电路的迭代进行详尽的实验评估是不切实际的。因此，我们假设需要一个预测工具来指导和加速转录程序的设计。这里描述的工作涉及开发和实验表征大量具有网络功能的单输入逻辑运算——工程 BUFFER（抑制剂）和工程 NOT（反抑制剂）逻辑运算。使用此单输入数据和开发的计量技术，我们能够对所有基本的两输入压缩逻辑运算（压缩 AND 门和压缩 NOR 门）进行建模和预测性能。此外，我们还能够对压缩混合表型逻辑运算（A 蕴涵 B 门和互补 B 蕴涵 A 门）的性能进行建模和预测。这些结果表明，单输入数据足以准确预测复杂电路的定性和定量性能。因此，这项工作为更复杂的转录程序的预测设计奠定了基础。
