Microbial bioengineering is a growing field for producing plant natural products (PNPs) in recent decades, using heterologous metabolic pathways in host cells. Once heterologous metabolic pathways have been introduced into host cells, traditional metabolic engineering techniques are employed to enhance the productivity and yield of PNP biosynthetic routes, as well as to manage competing pathways. The advent of computational biology has marked the beginning of a novel epoch in strain design through methods. These methods utilize genome-scale metabolic models (GEMs) and flux optimization algorithms to facilitate rational design across the entire cellular metabolic network. However, the implementation of strategies can often result in an uneven distribution of metabolic fluxes due to the rigid knocking out of endogenous genes, which can impede cell growth and ultimately impact the accumulation of target products. In this study, we creatively utilized synthetic biology to refine strain design for efficient PNPs production. OptKnock simulation was performed on the GEM of OA07, an engineered strain for oleanolic acid (OA) bioproduction that has been reported previously. The simulation predicted that the single deletion of , , , , and , or a combined knockout of , and could improve its OA production. Consequently, strains EK1∼EK7 were constructed and cultivated. EK3 (OA07△), EK5 (OA07△), and EK6 (OA07△) had significantly higher OA titers in a batch cultivation compared to the original strain OA07. However, these increases were less pronounced in the fed-batch mode, indicating that gene deletion did not support sustainable OA production. To address this, we designed a negative feedback circuit regulated by malonyl-CoA, a growth-associated intermediate whose synthesis served as a bypass to OA synthesis, at , , and at acetyl-CoA carboxylase-encoding gene , to dynamically and autonomously regulate the expression of these genes in OA07. The constructed strains R_3A, R_5A and R_6A had significantly higher OA titers than the initial strain and the responding gene-knockout mutants in either batch or fed-batch culture modes. Among them, strain R_3A stand out with the highest OA titer reported to date. Its OA titer doubled that of the initial strain in the flask-level fed-batch cultivation, and achieved at 1.23 ± 0.04 g L in 96 h in the fermenter-level fed-batch mode. This indicated that the integration of optimization algorithm and synthetic biology approaches was efficiently rational for PNP-producing strain design.

中文翻译：

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自控计算机基因敲除策略增强酿酒酵母异源萜类化合物的可持续生产


近几十年来，微生物生物工程是利用宿主细胞中的异源代谢途径生产植物天然产物（PNP）的一个不断发展的领域。一旦异源代谢途径被引入宿主细胞，传统的代谢工程技术就被用来提高 PNP 生物合成途径的生产力和产量，并管理竞争途径。计算生物学的出现标志着通过方法进行菌株设计的新纪元的开始。这些方法利用基因组规模代谢模型（GEM）和通量优化算法来促进整个细胞代谢网络的合理设计。然而，由于内源基因的严格敲除，策略的实施往往会导致代谢通量分布不均匀，这会阻碍细胞生长并最终影响目标产物的积累。在这项研究中，我们创造性地利用合成生物学来改进菌株设计，以实现 PNP 的高效生产。 OptKnock 模拟是在 OA07 的 GEM 上进行的，OA07 是之前报道过的齐墩果酸 (OA) 生物生产工程菌株。模拟预测， 、 、 、 和 的单个删除，或 、 的组合敲除， 和 可以提高其 OA 产量。因此，构建并培养了菌株EK1～EK7。与原始菌株OA07相比，EK3（OA07△）、EK5（OA07△）和EK6（OA07△）在分批培养中具有显着更高的OA滴度。然而，这些增加在补料分批模式中不太明显，表明基因删除不支持可持续的 OA 生产。 为了解决这个问题，我们设计了一个由丙二酰辅酶A调节的负反馈电路，丙二酰辅酶A是一种与生长相关的中间体，其合成充当OA合成的旁路，在乙酰辅酶A羧化酶编码基因处，动态地、自主地调节这些基因在 OA07 中的表达。在分批或补料分批培养模式下，构建的菌株R_3A、R_5A和R_6A比初始菌株和响应基因敲除突变体具有显着更高的OA效价。其中，菌株 R_3A 脱颖而出，具有迄今为止报道的最高 OA 滴度。在烧瓶级补料分批培养中，其 OA 滴度是初始菌株的两倍，并且在发酵罐水平补料分批模式下，96 小时内达到 1.23 ± 0.04 g·L。这表明优化算法和合成生物学方法的结合对于 PNP 生产菌株的设计是有效合理的。