IEEE Trans Biomed Circuits Syst. 2019 Feb;13(1):248-258. doi: 10.1109/TBCAS.2018.2883350. Epub 2018 Nov 26.
Feedback control is ubiquitous in biological systems. It can also play a crucial role in the design of synthetic circuits implementing novel functions in living systems, to achieve self-regulation of gene expression, noise reduction, rise time decrease, or adaptive pathway control. Despite in vitro, in vivo, and ex vivo implementations have been successfully reported, the design of biological close-loop systems with quantitatively predictable behavior is still a major challenge. In this work, we tested a model-based bottom-up design of a synthetic close-loop controller in engineered Escherichia coli, aimed to automatically regulate the concentration of an extracellular molecule, N-(3-oxohexanoyl)-L-homoserine lactone (HSL), by rewiring the elements of heterologous quorum sensing/quenching networks. The synthetic controller was successfully constructed and experimentally validated. Relying on mathematical model and experimental characterization of individual regulatory parts and enzymes, we evaluated the predictability of the interconnected system behavior in vivo. The culture was able to reach an HSL steady-state level of 72 nM, accurately predicted by the model, and showed superior capabilities in terms of robustness against cell density variation and disturbance rejection, compared with a corresponding open-loop circuit. This engineering-inspired design approach may be adopted for the implementation of other close-loop circuits for different applications and contribute to decreasing trial-and-error steps.
反馈控制在生物系统中无处不在。它还可以在设计合成电路中发挥关键作用,在活系统中实现新功能,如基因表达的自我调节、降低噪声、减少上升时间或适应途径控制。尽管已经成功报道了体外、体内和离体的实施,但具有定量可预测行为的生物闭环系统的设计仍然是一个主要挑战。在这项工作中,我们测试了一种基于模型的自上而下的设计方法,用于工程大肠杆菌中的合成闭环控制器,旨在通过重新布线异源群体感应/淬灭网络的元件,自动调节细胞外分子 N-(3-氧代己酰基)-L-同型丝氨酸内酯 (HSL) 的浓度。成功构建并实验验证了合成控制器。依赖于数学模型和对单个调节元件和酶的实验特性的描述,我们评估了体内互连系统行为的可预测性。该培养物能够达到 72 nM 的 HSL 稳态水平,这被模型准确预测,并且与相应的开环电路相比,在抵抗细胞密度变化和干扰抑制方面具有更好的性能。这种受工程启发的设计方法可用于实现其他用于不同应用的闭环电路,并有助于减少反复试验的步骤。