Recombinant protein bioprocess optimization using emerging expression platforms

自1982年第一个重组产品问世以来，生物制药行业在加拿大经历了前所未有的增长，年销售额接近100亿美元。传统的表达许多生物药物（动物细胞系和大肠杆菌）的平台存在一些缺陷。为了缓解这些问题，提出了两种替代的、新兴的重组宿主，即毕赤酵母（一种真核生物）和lividans链霉菌（一种原核生物）的补料分批培养的工程评估和优化，作为研究的模型系统。拟议的研究是建立在申请人在重组蛋白生物过程方面的经验之上的。目的是开发一种基于模型的优化策略来操纵营养饲料和操作条件，以最大限度地提高重组蛋白的产量和浓度。需要结构化的实验方法和数据分析来充分优化该过程。作为第一步，将建立一个基于化学计量学的代谢通量模型来详细描述分解代谢途径、生物合成和基因调控。全通量模型将通过统计方法进行简化和微调。将确定影响最佳表达的潜在瓶颈。反过来，代谢通量模型将被应用，以建立一个平衡的介质，以减少可能导致产品降解的代谢应激。控制程序将开发和优化，以便在批和补料批培养中产生稳健的过程轨迹。实验工作的一个重要方面是确定高密度培养中可能的传质限制，并在必要时采取纠正措施。然后，所得数据将用作使用原位和非原位仪器优化生物过程的基础。

Since the first recombinant product in 1982, the biopharma industry has experienced an unprecedented growth in Canada with sales approaching $10billion annually. The conventional platforms expressing many biopharmaceuticals (animal cell lines and Escherichia coli) have some drawbacks. To alleviate these, the engineering assessment and optimization of fed-batch cultures of two alternate, emerging recombinant hosts, namely Pichia pastoris (a eukaryote) and Streptomyces lividans (a prokaryote) expressing human interleukin-3 (huIl-3) are proposed as model systems for study. The proposed research is built upon the applicant's experience with recombinant protein bioprocesses. The objective is to develop a model-based optimization strategy for manipulating the nutrient feed and operating conditions in order to maximize the recombinant protein productivity and the concentration. A structured experimental approach and data analysis will be required to fully optimize the process. As a first step a stoichiometry-based metabolic flux model will be constructed to detail catabolic pathways, biosynthesis, and gene regulation. The full flux model will be simplified and fine-tuned by statistical methods. Potential bottlenecks affecting optimum expression will be identified. The metabolic flux model will be applied, in turn, to establish a balanced medium to reduce metabolic stress that may lead to product degradation.. Control routines will be developed and optimized so as to produce robust process trajectories in batch and fed-batch culture. An important aspect of the experimental work is to identify probable mass transfer limitations in high density culture and apply corrective measures if necessary. The resulting data will then be used as the basis for optimization of the bioprocesses using both in situ and ex-situ instrumentation.