Agrawal Deepak K, Dolan Elliott M, Hernandez Nancy E, Blacklock Kristin M, Khare Sagar D, Sontag Eduardo D
Department of Bioengineering , Northeastern University , Boston , Massachusetts 02120 , United States.
Department of Electrical and Computer Engineering , Northeastern University , Boston , Massachusetts 02115 , United States.
ACS Synth Biol. 2020 Feb 21;9(2):198-208. doi: 10.1021/acssynbio.9b00279. Epub 2020 Feb 7.
An important goal of synthetic biology is to build biosensors and circuits with well-defined input-output relationships that operate at speeds found in natural biological systems. However, for molecular computation, most commonly used genetic circuit elements typically involve several steps from input detection to output signal production: transcription, translation, and post-translational modifications. These multiple steps together require up to several hours to respond to a single stimulus, and this limits the overall speed and complexity of genetic circuits. To address this gap, molecular frameworks that rely exclusively on post-translational steps to realize reaction networks that can process inputs at a time scale of seconds to minutes have been proposed. Here, we build mathematical models of fast biosensors capable of producing Boolean logic functionality. We employ protease-based chemical and light-induced switches, investigate their operation, and provide selection guidelines for their use as on-off switches. As a proof of concept, we implement a rapamycin-induced switch and demonstrate that its response qualitatively agrees with the predictions from our models. We then use these switches as elementary blocks, developing models for biosensors that can perform OR and XOR Boolean logic computation while using reaction conditions as tuning parameters. We use sensitivity analysis to determine the time-dependent sensitivity of the output to proteolytic and protein-protein binding reaction parameters. These fast protease-based biosensors can be used to implement complex molecular circuits with a capability of processing multiple inputs controllably and algorithmically. Our framework for evaluating and optimizing circuit performance can be applied to other molecular logic circuits.
合成生物学的一个重要目标是构建具有明确输入-输出关系的生物传感器和电路，其运行速度与自然生物系统中的速度相当。然而，对于分子计算而言，最常用的遗传电路元件通常涉及从输入检测到输出信号产生的多个步骤：转录、翻译和翻译后修饰。这些多个步骤加起来对单个刺激的响应需要长达数小时，这限制了遗传电路的整体速度和复杂性。为了弥补这一差距，人们提出了仅依赖翻译后步骤来实现能够在几秒到几分钟的时间尺度上处理输入的反应网络的分子框架。在此，我们构建了能够产生布尔逻辑功能的快速生物传感器的数学模型。我们采用基于蛋白酶的化学和光诱导开关，研究它们的运行情况，并为其用作开关提供选择指南。作为概念验证，我们实现了一种雷帕霉素诱导的开关，并证明其响应在定性上与我们模型的预测一致。然后，我们将这些开关用作基本模块，开发了能够执行“或”和“异或”布尔逻辑计算的生物传感器模型，同时将反应条件用作调节参数。我们使用灵敏度分析来确定输出对蛋白水解和蛋白质-蛋白质结合反应参数的时间依赖性灵敏度。这些基于蛋白酶的快速生物传感器可用于实现能够以可控方式和算法处理多个输入的复杂分子电路。我们评估和优化电路性能的框架可应用于其他分子逻辑电路。
