Modelling cellular stress during recombinant protein production for improving upstream biomanufacturing processes

模拟重组蛋白生产过程中的细胞应激，以改善上游生物制造工艺

• 批准号: 2321655
• 金额: --
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2321655
• 关键词: Modelling; cellular; stress; during; recombinant

Recombinant proteins are expressed non-endogenously by an organism, and they have wide applications in biotechnology ranging from the biomanufacture of industrially and agriculturally relevant enzymes to therapeutics and the manufacture of biologics. Due to this commercial interest, there is pressure to achieve high yields of high quality protein product by the host cells. However, all biological systems are optimised for their own survival, and not for the production of a heterologous entity, and therefore, the process of heterologous protein expression, particularly in a state of overproduction, creates a huge burden on the cell. The host has difficulty to achieve a high quality product, i.e. a correctly processed protein, under the stress imposed by high production demand. This stress triggers responses within the host to cope with the accumulation of the low quality, and therefore undesirable, product. These responses range from the formation of inclusion bodies by prokaryotic hosts such as bacteria, to the induction of unfolded protein response by eukaryotic hosts such as yeast and mammalian cells. This research will facilitate the development of quantitative models of this stress response and the utilisation of these models in the improvement and optimisation of upstream biomanufacturing processes of recombinant protein production. Within this domain, the research is expected to equip the industry with new research methods and tools, which will help them reduce time in cell and process development and assist the alleviation of costs and risks of product development. The benefits are directly associated with biopharmaceutical and biocatalysis activities, substantial contributors of sustainability, thus the outcomes of the project will benefit the society as a whole. The knowledge and the tools resulting from the project being offered to the service of relevant industries will also strengthen their position in the global markets allowing them to remain competitive in their respective fields of operation.The aim of this research is to develop a formal understanding mammalian and microbial stress mechanisms that have an adverse impact on recombinant protein production capacity via a modelling framework. Its incorporation with data-driven models of upstream biomanufacturing will expand the predictive capability of model-driven analysis. In order to achieve this goal, the following objectives will be met:- Population of a knowledge-base of existing numerical and descriptive data pertaining the stress mechanisms described above- Development of a structured understanding of the existing know-how and identification of missing information creating bottlenecks in formulating a working model- Hypothesis generation on the structure (i.e. the topology) of this mechanism to translate into a formal description- Construction of a structured model of cellular stress in response to heterologous protein production- Model implementation (mathematical + computational framework)- Testing and improving the predictive/descriptive capacity of the model (via simulations or programming) - Incorporation of the model into existing pipelines to improve current practiceNovel approaches in handling and modelling the data will be explored as needed based on the type and the nature of the data accumulating in the knowledge-base. It is expected that stochastic models and elaborate parameter estimation techniques will have to be employed.This research project aligns with EPSRC's research themes of healthcare technologies and manufacturing the future, and with the following research areas: Biological informatics, manufacturing technologies, mathematical biology, and operational research. It also aligns with EPSRC's current research priorities in Digital Manufacturing and Sustainable Industries.No companies or collaborators are currently involved in the project, in the event of any future collaborations, this information will be updated

重组蛋白质由生物体非内源性地表达，并且它们在从工业和农业相关酶的生物制造到治疗和生物制剂的制造的生物技术中具有广泛的应用。由于这种商业利益，存在通过宿主细胞实现高产量的高质量蛋白质产物的压力。然而，所有的生物系统都是为了它们自身的存活而优化的，而不是为了异源实体的产生，因此，异源蛋白质表达的过程，特别是在过度产生的状态下，对细胞造成了巨大的负担。宿主在高生产需求施加的压力下难以获得高质量的产品，即正确加工的蛋白质。这种压力触发宿主内的反应，以科普低质量的积累，因此不受欢迎的产品。这些反应的范围从原核宿主如细菌形成包涵体，到真核宿主如酵母和哺乳动物细胞诱导未折叠蛋白质反应。这项研究将有助于开发这种应激反应的定量模型，并利用这些模型来改进和优化重组蛋白生产的上游生物制造过程。在这一领域内，该研究有望为该行业提供新的研究方法和工具，这将有助于他们减少电池和工艺开发的时间，并有助于减轻产品开发的成本和风险。这些好处与生物制药和生物催化活动直接相关，是可持续发展的重要贡献者，因此该项目的成果将使整个社会受益。该项目为相关行业提供的知识和工具也将加强其在全球市场上的地位，使其能够在各自的业务领域保持竞争力。本研究的目的是通过建模框架，正式了解对重组蛋白生产能力产生不利影响的哺乳动物和微生物应激机制。它与上游生物制造的数据驱动模型的结合将扩大模型驱动分析的预测能力。为实现这一目标，将实现以下目标：- 建立与上述压力机制有关的现有数字和描述性数据的知识库-对现有技术有条理地了解，并确定在制定工作模型时造成瓶颈的缺失信息-生成关于结构的假设- 响应于异源蛋白质产生的细胞应激的结构化模型的构建-模型实施（数学+计算框架）-测试和提高模型的预测/描述能力（通过模拟或编程）-将该模型纳入现有管道，以改进现行做法。将根据需要探索处理和模拟数据的新方法基于知识库中积累的数据的类型和性质。本研究项目与EPSRC的医疗技术和未来制造业的研究主题相一致，并与以下研究领域相一致：生物信息学，制造技术，数学生物学和运筹学。它也符合EPSRC目前在数字制造和可持续工业方面的研究重点。目前没有公司或合作者参与该项目，如果未来有任何合作，此信息将更新