Beneš David, Sosík Petr, Rodríguez-Patón Alfonso
Silesian University in Opava.
Silesian University in OpavaUniversidad Politécnica de Madrid.
Artif Life. 2015 Spring;21(2):247-60. doi: 10.1162/ARTL_a_00160. Epub 2015 Jan 26.
Success in synthetic biology depends on the efficient construction of robust genetic circuitry. However, even the direct engineering of the simplest genetic elements (switches, logic gates) is a challenge and involves intense lab work. As the complexity of biological circuits grows, it becomes more complicated and less fruitful to rely on the rational design paradigm, because it demands many time-consuming trial-and-error cycles. One of the reasons is the context-dependent behavior of small assembly parts (like BioBricks), which in a complex environment often interact in an unpredictable way. Therefore, the idea of evolutionary engineering (artificial directed in vivo evolution) based on screening and selection of randomized combinatorial genetic circuit libraries became popular. In this article we build on the so-called dual selection technique. We propose a plasmid-based framework using toxin-antitoxin pairs together with the relaxase conjugative protein, enabling an efficient autonomous in vivo evolutionary selection of simple Boolean circuits in bacteria (E. coli was chosen for demonstration). Unlike previously reported protocols, both on and off selection steps can run simultaneously in various cells in the same environment without human intervention; and good circuits not only survive the selection process but are also horizontally transferred by conjugation to the neighbor cells to accelerate the convergence rate of the selection process. Our directed evolution strategy combines a new dual selection method with fluorescence-based screening to increase the robustness of the technique against mutations. As there are more orthogonal toxin-antitoxin pairs in E. coli, the approach is likely to be scalable to more complex functions. In silico experiments based on empirical data confirm the high search and selection capability of the protocol.
合成生物学的成功取决于强大遗传电路的高效构建。然而,即使是对最简单的遗传元件(开关、逻辑门)进行直接工程设计也是一项挑战,且需要大量的实验室工作。随着生物电路复杂性的增加,依赖理性设计范式变得更加复杂且成效降低,因为这需要许多耗时的反复试验周期。原因之一是小装配部件(如生物砖)的上下文相关行为,在复杂环境中它们常常以不可预测的方式相互作用。因此,基于对随机组合遗传电路文库进行筛选和选择的进化工程(人工定向体内进化)理念变得流行起来。在本文中,我们基于所谓的双重选择技术展开研究。我们提出了一种基于质粒的框架,该框架使用毒素 - 抗毒素对以及松弛酶接合蛋白,能够在细菌(选择大肠杆菌进行演示)中对简单布尔电路进行高效的自主体内进化选择。与先前报道的方案不同,正向和负向选择步骤可以在同一环境中的各种细胞中同时运行,无需人工干预;而且优良的电路不仅能在选择过程中存活下来,还会通过接合作用水平转移到邻近细胞,以加快选择过程的收敛速度。我们的定向进化策略将一种新的双重选择方法与基于荧光的筛选相结合,以提高该技术对突变的鲁棒性。由于大肠杆菌中有更多正交的毒素 - 抗毒素对,该方法可能可扩展到更复杂的功能。基于经验数据的计算机模拟实验证实了该方案具有很高的搜索和选择能力。