Next Generation Strain Engineering via OptKnock

描述(由申请人提供)： 代谢工程在工业和医学生物技术中都具有重要意义，用于合成包括小分子代谢物和其他抗生素在内的各种产品。然而，由于缺乏合理和系统的代谢工程方法，菌株开发的时间和成本可能很大，有时对许多产品来说是令人望而却步的。这项建议通过实施建模和模拟技术来设计实际目标的细胞代谢网络，从而解决了对更合理方法的需求。两级编程框架OptKnock尤其侧重于确定多个基因缺失策略，以迫使在实验室适应性进化后进行生长耦合生化生产。具体而言，基因敲除的选择方式是，由于化学计量学的原因，向必要生长资源(即生物质成分、氧化还原潜力和能量)的流失必须伴随着所需化学产品的生产。第一阶段SBIR的总体目标是完成一项综合的计算和实验研究，旨在证明利用OptKnock方法推动应变工程工作的技术可行性。在大肠杆菌中生产琥珀酸酯将成为实现这一目标的示范案例研究。这项应用的最初目标是列举导致生长耦合琥珀酸酯生产的多组基因缺失，并将这三种最有希望的基因整合到大肠杆菌中。然后，这三个独特设计的菌株将进行适应性进化，以提高它们的生长速度，从而间接优化琥珀酸生产的耦合目标。最后，我们将使实验结果与最初的预测相一致，以衡量组合建模/实验平台的总体成功。在该项目的后续阶段，我们将针对几种具有生物技术和生物医学重要性的化合物，目标是产生至少一种具有工业竞争力的生产菌株。这项计划将导致开发代谢工程的系统方法，利用基因组信息和大量实验数据来合理设计生产宿主。所开发的技术将大大加快并降低菌株开发的成本，以生产大量具有治疗价值的化合物。

DESCRIPTION (provided by applicant): Metabolic engineering has gained significance in both industrial and medical biotechnology for the synthesis of a wide variety of products including small metabolites and other antibiotics. However, due to the lack of rational and systematic approaches to metabolic engineering the timelines and cost for strain development can be large and at times prohibitive for many products. This proposal addresses this need for more rational approaches through the implementation of modeling and simulation technologies to design cellular metabolic networks for practical objectives. The bilevel programming framework OptKnock, in particular, focuses on identifying multiple gene deletion strategies for forcing growth-coupled biochemical production following laboratory adaptive evolution. Specifically, knockouts are selected in such a way that the drain towards necessary growth resources (i.e., biomass components, redox potential and energy) must be accompanied, due to stoichiometry, by the production of the desired chemical product. The overall goal of this Phase I SBIR is the completion of an integrated computational and experimental study aimed at demonstrating the technical feasibility of utilizing the OptKnock approach to drive strain engineering efforts. The production of succinate in Escherichia coli will serve as an exemplary case study towards this end. The initial aims of this application are to enumerate sets of multiple gene deletions leading to growth-coupled succinate production and incorporate the three most promising into E. coli. The three unique designed strains will then be subjected to adaptive evolution to enhance their rates of growth, and thus the coupled objective of succinate production will be indirectly optimized. Finally, we will reconcile the experimental findings with the original predictions to gauge the overall success of the combined modeling/experimental platform. In subsequent phases of the project, we will target several compounds of biotechnological and biomedical importance with the goal of generating at least one industrially competitive production strain. This program will lead to the development of a systematic approach to metabolic engineering that leverages genomic information and a host of experimental data for the rational design of production hosts. The developed technology will significantly expedite and lesson the cost of strain development for the production of a plethora of compounds with therapeutic value.