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基因组规模代谢网络建模的结果是最小的干预,这些干预共同促使碳通量向丙二酰辅酶 A 方向流动。

Genome-scale metabolic network modeling results in minimal interventions that cooperatively force carbon flux towards malonyl-CoA.

机构信息

Department of Chemical and Biological Engineering, Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, NY 12180, USA.

出版信息

Metab Eng. 2011 Sep;13(5):578-87. doi: 10.1016/j.ymben.2011.06.008. Epub 2011 Jul 13.

Abstract

Malonyl-coenzyme A is an important precursor metabolite for the biosynthesis of polyketides, flavonoids and biofuels. However, malonyl-CoA naturally synthesized in microorganisms is consumed for the production of fatty acids and phospholipids leaving only a small amount available for the production of other metabolic targets in recombinant biosynthesis. Here we present an integrated computational and experimental approach aimed at improving the intracellular availability of malonyl-CoA in Escherichia coli. We used a customized version of the recently developed OptForce methodology to predict a minimal set of genetic interventions that guarantee a prespecified yield of malonyl-CoA in E. coli strain BL21 Star™. In order to validate the model predictions, we have successfully constructed an E. coli recombinant strain that exhibits a 4-fold increase in the levels of intracellular malonyl-CoA compared to the wild type strain. Furthermore, we demonstrate the potential of this E. coli strain for the production of plant-specific secondary metabolites naringenin (474mg/L) with the highest yield ever achieved in a lab-scale fermentation process. Combined effect of the genetic interventions was found to be synergistic based on a developed analysis method that correlates genetic modification to cell phenotype, specifically the identified knockout targets (ΔfumC and ΔsucC) and overexpression targets (ACC, PGK, GAPD and PDH) can cooperatively force carbon flux towards malonyl-CoA. The presented strategy can also be readily expanded for the production of other malonyl-CoA-derived compounds like polyketides and biofuels.

摘要

丙二酰辅酶 A 是聚酮类化合物、类黄酮和生物燃料生物合成的重要前体代谢物。然而,微生物中天然合成的丙二酰辅酶 A 被用于脂肪酸和磷脂的生产,只有少量可用于重组生物合成中其他代谢靶标的生产。在这里,我们提出了一种综合计算和实验方法,旨在提高大肠杆菌中丙二酰辅酶 A 的细胞内可用性。我们使用了最近开发的 OptForce 方法的定制版本,来预测一组最小的遗传干预措施,以保证大肠杆菌 BL21 Star™ 菌株中丙二酰辅酶 A 的规定产量。为了验证模型预测,我们成功构建了一个大肠杆菌重组菌株,与野生型菌株相比,细胞内丙二酰辅酶 A 的水平提高了 4 倍。此外,我们还展示了该大肠杆菌菌株在植物特异性次生代谢物柚皮素(474mg/L)生产中的潜力,这是在实验室规模发酵过程中达到的最高产量。根据一种开发的分析方法,遗传干预的综合效应被发现是协同的,该方法将遗传修饰与细胞表型相关联,特别是鉴定的敲除靶标(Δ fumC 和 Δ sucC)和过表达靶标(ACC、PGK、GAPD 和 PDH)可以协同地将碳通量推向丙二酰辅酶 A。所提出的策略也可以很容易地扩展到其他丙二酰辅酶 A 衍生化合物的生产,如聚酮类化合物和生物燃料。

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