We report that two-stage dynamic control improves bioprocess robustness as a result of the dynamic deregulation of central metabolism. Dynamic control is implemented during stationary phase using combinations of CRISPR interference and controlled proteolysis to reduce levels of central metabolic enzymes. Reducing the levels of key enzymes alters metabolite pools resulting in deregulation of the metabolic network. Deregulated networks are less sensitive to environmental conditions improving process robustness. Process robustness in turn leads to predictable scalability, minimizing the need for traditional process optimization. We validate process robustness and scalability of strains and bioprocesses synthesizing the important industrial chemicals alanine, citramalate and xylitol. Predictive high throughput approaches that translate to larger scales are critical for metabolic engineering programs to truly take advantage of the rapidly increasing throughput and decreasing costs of synthetic biology.

我们报告说，由于中央代谢的动态失调，两阶段动态控制提高了生物过程的稳健性。在固定阶段使用 CRISPR 干扰和受控蛋白水解的组合实施动态控制，以降低中心代谢酶的水平。降低关键酶的水平会改变代谢物库，导致代谢网络失调。解除管制的网络对环境条件不太敏感，从而提高了过程的稳健性。流程稳健性反过来会导致可预测的可扩展性，最大限度地减少对传统流程优化的需求。我们验证了合成重要工业化学品丙氨酸、柠檬酸和木糖醇的菌株和生物过程的过程稳健性和可扩展性。