A novel biotherapeutic expression platform in bacteria

描述(由申请人提供)：该提案的总体目标是通过利用最近发现的细菌双精氨酸易位(TAT)途径的显著特性来开发一种新的蛋白质表达平台。目前有300多种治疗性蛋白质正处于不同的临床试验阶段，通往更健康未来的道路将需要生产更安全、更便宜的重组蛋白质的新方法。为此，最近发现的双精氨酸转位(TAT)途径将被用作新的重组蛋白在大肠杆菌中的表达平台。为此，第一阶段包括以下具体目标：1)确定细菌TAT转运体的分泌能力；2)通过伴侣共表达策略优化TAT分泌效率；以及3)扩大基于TAT的蛋白质生产过程。这项研究不仅有望开发一种新的细菌蛋白表达平台，还将有助于更深入地了解一个鲜为人知的生物学机制。第二阶段将需要更广泛的努力来研究和提高TAT的运输效率，例如，定向进化策略来设计“高度活跃的”TAT转运体，细胞工程方法来优化TAT表达的宿主，以及前导肽优化研究。此外，我们希望通过优化碳源补料策略，以及温度、溶解氧和pH的优化，充分开发大规模表达TAT的方法。

DESCRIPTION (provided by applicant): The overall objective of the proposal is to develop a novel protein expression platform by capitalizing on the remarkable properties of the recently discovered twin-arginine translocation (Tat) pathway of bacteria. With over 300 therapeutic proteins currently in various stages of clinical trials, the road to a healthier future will require new methods for producing safer and less expensive recombinant proteins. For this purpose, the recently discovered twin-arginine translocation (Tat) pathway will be utilized as a novel recombinant protein expression platform in Escherichia coli. Towards this objective, Phase I encompasses the following specific aims: 1) to define the secretory capacity of the bacterial Tat transporter; 2) to optimize Tat secretion efficiency via chaperone co-expression strategies; and 3) to scale-up the Tat-based protein production process. This research is expected to not only result in the development a novel platform for bacterial protein expression but will also facilitate a deeper understanding of a poorly understood biological mechanism. Phase II will entail a much broader effort to study and improve Tat transport efficiency including, for instance, directed evolution strategies to engineer "hyperactive" Tat transporters, cell engineering methods to optimize the host for Tat expression and leader peptide optimization studies. In addition, we expect to fully develop scale-up methods for large-scale Tat expression by using optimized carbon-source feed strategies, as well as temperature, dissolved oxygen and pH optimization.