Anesiadis Nikolaos, Kobayashi Hideki, Cluett William R, Mahadevan Radhakrishnan
Department of Chemical Engineering and Applied Chemistry, University of Toronto, Canada, M5S 3E5.
ACS Synth Biol. 2013 Aug 16;2(8):442-52. doi: 10.1021/sb300129j. Epub 2013 Apr 9.
Recent advances in synthetic biology have equipped us with new tools for bioprocess optimization at the genetic level. Previously, we have presented an integrated in silico design for the dynamic control of gene expression based on a density-sensing unit and a genetic toggle switch. In the present paper, analysis of a serine-producing Escherichia coli mutant shows that an instantaneous ON-OFF switch leads to a maximum theoretical productivity improvement of 29.6% compared to the mutant. To further the design, global sensitivity analysis is applied here to a mathematical model of serine production in E. coli coupled with a genetic circuit. The model of the quorum sensing and the toggle switch involves 13 parameters of which 3 are identified as having a significant effect on serine concentration. Simulations conducted in this reduced parameter space further identified the optimal ranges for these 3 key parameters to achieve productivity values close to the maximum theoretical values. This analysis can now be used to guide the experimental implementation of a dynamic metabolic engineering strategy and reduce the time required to design the genetic circuit components.
合成生物学的最新进展为我们提供了在基因水平上优化生物过程的新工具。此前，我们提出了一种基于密度感应单元和基因翻转开关的基因表达动态控制的集成计算机设计。在本文中，对一株产丝氨酸的大肠杆菌突变体的分析表明，与该突变体相比，瞬时开关可使理论生产率提高29.6%。为了进一步优化设计，本文将全局敏感性分析应用于与遗传电路耦合的大肠杆菌丝氨酸生产数学模型。群体感应和翻转开关模型涉及13个参数，其中3个被确定对丝氨酸浓度有显著影响。在这个简化的参数空间中进行的模拟进一步确定了这3个关键参数的最佳范围，以实现接近最大理论值的生产率。该分析现在可用于指导动态代谢工程策略的实验实施，并减少设计遗传电路组件所需的时间。
