Parameter identification with optimal experimental design for engineering biology

工程生物学优化实验设计的参数识别

• 批准号: EP/Y00342X/1
• 负责人: Alexander Darlington
• 金额: $ 20.86万
• 依托单位: University of Warwick
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FY00342X%2F1
• 关键词: Parameter; identification; optimal; experimental; design; Parameter; identification; optimal; experimental; design

Engineering biology has the potential to generate new disruptive products and to revolutionise our approach to many societal problems. However, at present, the engineering of these products is complicated by interactions between the host microbe's (chassis') natural biology and the engineered genetic system or metabolic pathway. This results in poor performance which can range from differences in expected behaviour, poor host growth or even complete failure of the engineered function. Recently, mathematical models and computer aided design tools have been produced which enable these interactions to be accounted for during the project design phase. These approaches are termed "host-aware" and enable synthetic biologists and biotechnologists to produce "host-friendly" designs. To date, these approaches have only been developed for the academic lab workhorse E. coli which limits their application in industry who use a variety of microbes due to other beneficial biological properties. Extending these frameworks to other industrially relevant organisms is challenging due to the lack of available data and the lack of experimental protocols which enable efficient data generation. This pilot project establishes an interdisciplinary global research team to solve this problem. First the team will carry out a rigorous analysis of the host-aware design framework which is composed of complex nonlinear ordinary differential equation models and establish new accurate and efficient tools to enable robust parametrisation of complex microbial growth models from sparse data. Working closely with industrial partners, the team will then develop an optimal experimental design approach which enables scientists to determine what experiments need to be conducted to enable these host-aware design frameworks to be developed for industrially relevant microbes. This project will enable the future generation of new industrially relevant "host-aware" computer aided design tools needed for fast and efficient engineering of microbial cells factories.

工程生物学有可能产生新的破坏性产品，并彻底改变我们解决许多社会问题的方法。但是，目前，这些产品的工程化因宿主微生物（底盘）自然生物学与工程遗传系统或代谢途径之间的相互作用而变得复杂。这会导致性能差，这可能包括预期行为的差异，宿主增长差甚至是工程功能的完全失败。最近，已经生产了数学模型和计算机辅助设计工具，使这些交互在项目设计阶段可以考虑。这些方法被称为“宿主意识”，并使合成生物学家和生物技术学家能够生产“宿主友好”的设计。迄今为止，仅针对学术实验室的大肠杆菌开发了这些方法，该方法限制了由于其他有益的生物学特性而使用各种微生物的行业应用。将这些框架扩展到其他与工业相关的生物，这是由于缺乏可用数据以及缺乏实现有效数据生成的实验协议而具有挑战性的。这个试点项目建立了一个跨学科的全球研究团队来解决这个问题。首先，团队将对宿主感知的设计框架进行严格的分析，该框架由复杂的非线性普通微分方程模型组成，并建立了新的准确和有效的工具，以从稀疏数据中启用复杂的微生物增长模型的鲁棒参数化。团队将与工业合作伙伴紧密合作，然后开发一种最佳的实验设计方法，使科学家能够确定需要进行哪些实验，以使这些宿主感知的设计框架能够为工业相关的微生物开发。该项目将使未来的新型工业相关的“宿主意识”计算机辅助设计工具，用于快速有效的微生物细胞工程工程。