A coarse-grained^M modelling approach for applications in Metabolic Engineering

为了改进生物技术过程，数学模型开始发挥作用，以便更好地了解细胞的内部工作原理。尽管有各种建模方法可用，并出版了大量模型，但对细胞过程的定量和动态描述的需求仍然很高，并不是所有的方法都能满足这一要求。此外，现在可以获得不同细胞水平的定量数据，如蛋白质组、转录组和代谢组，这些数据应该整合到这些模型中。该提案的总体目标是开发粗粒度模型，即具有非常通用的模块化结构的动态粗粒度模型的框架，以便能够快速地应用于不同的蜂窝系统和工艺设计。在本提案的上下文中，模块化意味着，从粗粒度模型的简单结构开始，定义功能模块，这些功能模块根据问题的形成指定整个网络的部分。为了建立这些模型，将使用基于基本原理的建模和具有机器学习工具的经典元素的数据驱动方法相结合的方法。介绍了其在代谢工程中的应用，如副产物形成和异源蛋白质生产。此外，还考虑了定义的混合培养，其中两个菌株变种相互链接，以有效地生产有趣的产品。

To improve biotechnological processes, mathematical models come into play for a better understanding of the inner workings of cells. Although various modelling approaches are available and a high number of models are published, the demand for a quantitative and a dynamic description of cellular processes is still high and not met by all approaches. Also, quantitative data is now available for different cellular levels like proteome, transcriptome, and metabolome that should be integrated into these models. The proposal's overall aim is to develop coarse-grainedM, that is, a framework for dynamic coarse-grained models with a modular structure in a very general form, such that applications to different cellular systems and process designs can be made quickly. Modularity in the context of the proposal means that, starting from a simple structure of a coarse-grained model, functional modules are defined that specify parts of the overall network depending on the problem formulation. To set up these models, a combined approach with modelling based on first principles and a data driven approach with classical elements of machine learning tools will be used. Applications in Metabolic Engineering are addressed such as by-product formation, and heterologous protein production. In addition, also defined mixed cultures are considered where two strain variants are mutual linked for an efficient production of an interesting product.