Trade-Offs in Biosensor Optimization for Dynamic Pathway Engineering

Recent progress in synthetic biology allows the construction of dynamic control circuits for metabolic engineering. This technology promises to overcome many challenges encountered in traditional pathway engineering, thanks to its ability to self-regulate gene expression in response to bioreactor perturbations. The central components in these control circuits are metabolite biosensors that read out pathway signals and actuate enzyme expression. However, the construction of metabolite biosensors is a major bottleneck for strain design, and a key challenge is to understand the relation between biosensor dose-response curves and pathway performance. Here we employ multiobjective optimization to quantify performance trade-offs that arise in the design of metabolite biosensors. Our approach reveals strategies for tuning dose-response curves along an optimal trade-off between production flux and the cost of an increased expression burden on the host. We explore properties of control architectures built in the literature and identify their advantages and caveats in terms of performance and robustness to growth conditions and leaky promoters. We demonstrate the optimality of a control circuit for glucaric acid production in Escherichia coli, which has been shown to increase the titer by 2.5-fold as compared to static designs. Our results lay the groundwork for the automated design of control circuits for pathway engineering, with applications in the food, energy, and pharmaceutical sectors.

合成生物学（synthetic biology）的近期进展，使得构建用于代谢工程（metabolic engineering）的动态控制回路成为可能。该技术可响应生物反应器（bioreactor）扰动并自主调控基因表达，因此有望克服传统途径工程中遇到的诸多挑战。此类控制回路的核心组件为代谢物生物传感器（metabolite biosensors），能够读取途径信号并调控酶的表达。然而，代谢物生物传感器的构建是菌株设计（strain design）中的一大瓶颈，当前的关键挑战之一在于阐明生物传感器剂量反应曲线与途径性能之间的关联。本研究采用多目标优化（multiobjective optimization）方法，量化了代谢物生物传感器设计过程中存在的性能权衡。我们的方法揭示了在生产通量与宿主表达负担成本之间寻求最优权衡时，调整剂量反应曲线的策略。我们对已有文献中构建的控制架构（control architectures）的特性进行了探索，并从性能、对生长条件的鲁棒性（robustness）以及渗漏启动子（leaky promoters）的影响等方面，分析了各类控制架构的优势与局限。我们以大肠杆菌（Escherichia coli）生产葡萄糖二酸（glucaric acid）为例，验证了该控制回路的最优性——已有研究表明，相较于静态设计，该回路可将产物滴度提升2.5倍。本研究成果为代谢途径工程的控制回路自动化设计奠定了基础，相关应用可覆盖食品、能源与制药等领域。