An Integrated Systems Engineering Approach to the Modeling of Cellular Dynamics and Bioreactors

皮：王，金研究所：奥本大学论文编号：1264861题目：细胞动力学和生物反应器建模的集成系统工程方法由于生物体内固有的复杂调节机制，生物反应器的建模和控制给控制工程师带来了独特的挑战。解决这一挑战的关键是获得一个能够充分描述细胞新陈代谢动力学的模型。PIS计划使用树干酵母菌作为模型系统来回答以下工程和科学问题：1.工程问题：如何有效地对细胞代谢动力学进行建模，进而对生物反应器的动力学进行建模？2.科学问题：什么是调控树干酵母菌从好氧生长向厌氧发酵转变的调控机制？为了回答第一个问题，他们提出了一个称为通量平衡分析引导的动态规划(FBA-DP)的计算框架来对细胞代谢动力学进行建模。对计算组件的补充是实验组件，其中开发了新的设备和实验程序，以获得计算组件所需的动态过程信息。为了回答第二个问题，将通过与托马斯·W·杰弗里斯(UW？Madison)教授的持续合作，使用下一代测序技术获得时间进程转录组测量结果。通过与彼得·何教授(塔斯基吉大学)的合作，将通过新的多变量方法将电子流组的动态细节与体内转录组数据整合起来，以阐明细胞调控机制。o通过将最优控制理论与通量平衡分析相结合，FBA-DP框架应该能够提供整个基因组范围的细胞内动态新陈代谢的细节，而不需要体内的酶动力学信息；o这个项目将产生有史以来第一个关于从需氧条件向无氧条件转变的时间过程转录组数据的数据集。对于对阐明基因调控网络的动态感兴趣的研究人员来说，这样的时间进程数据是非常可取的；O通过将电子流信息中的时间进程与体内转录组信息相结合，PI将能够获得控制树状葡萄球菌细胞从需氧生长到厌氧发酵的各种调控机制的动力学知识。o该框架可用于研究各种微生物和其他活细胞(如癌细胞)的细胞新陈代谢，只要它们的代谢网络模型可用。o有关细胞调控机制的已发现知识将为树状葡萄球菌像大多数其他酵母和真菌一样不能厌氧生长提供有价值的见解，这是一个悬而未决的基本生物学问题。O由于S生物反应器的广泛适用性，这种建模方法不仅有可能改善广泛行业的制造，如生物燃料、生化、食品和制药行业，而且还有可能提高国家的能源安全和可持续发展。o本研究促进了研究生和本科生水平的生物工程和生物技术工程师和科学家的教育。此外，这些项目将积极让少数群体参与，并为他们提供生物技术和可再生能源领域的研究经验。

PI: Wang, Jin Institution: Auburn UniversityProposal Number: 1264861Title: An Integrated Systems Engineering Approach to the Modeling of CellularDynamics and BioreactorsBecause of the inherent complex regulation mechanisms of living organisms, the modeling and control of bioreactors present unique challenges to control engineers. The key to addressing this challenge is to obtain a model that can adequately describe the dynamics of cellular metabolism. The PIs plan to use Scheffersomyces stipitis as the model system to answer the following engineering and scientific questions:1. Engineering question: how to effectively model the dynamics of cellular metabolism and then the dynamics of the bioreactor?2. Scientific question: what are the regulatory mechanisms that govern the transition of S. stipitis from aerobic growth to anaerobic fermentation?To answer the first question, they propose a computational framework named flux balance analysis guided dynamic programming (FBA-DP) to model the dynamics of cellular metabolism. Complementary to the computational component is an experimental component, where new equipment and experimental procedures have been developed to obtain dynamic process information required by the computational component. To answer the second question, the time course transcriptome measurements will be obtained using next-generation sequencing technology through a continuing collaboration with Prof. Thomas W. Jeffries (UW?Madison). Through the collaboration with Prof. Q. Peter He (Tuskegee Univ.), the dynamic in silico fluxome details with the in vivo trancriptome data via novel multivariate approaches to elucidate the cellular regulatory mechanisms will be integrated.Intellectual Merits:o By integrating the optimal control theory with flux balance analysis, the FBA-DP framework should be able to provide genome-wide intracellular details of the dynamic cellular metabolism without requiring in vivo enzyme kinetics information; o This project will produce the first ever data set of the time course transcriptome data on S. stipites during the transition from aerobic to anaerobic condition. Such time course data are highly desirable for researchers who are interested in elucidating the dynamics of the gene regulatory network; o By integrating time course in silico fluxome information with in vivo transcriptome information, the PIs will be able to obtain knowledge on the dynamics of various regulatory mechanisms that govern the cellular transition of S. stipitis from aerobic growth to anaerobic fermentation.Broader Impacts:o This framework can be applied to study cellular metabolism of various microorganisms and other living cells, such as cancer cells, as soon as their metabolic network models are made available.o The discovered knowledge on cellular regulation mechanisms will provide valuable insights on why S. stipitis, like most other yeasts and fungi, cannot grow anaerobically, which is an unsolved fundamental biological question. In addition, such knowledge will enable significant advancement in metabolic engineering for new strain development.o Because of the bioreactor?s wide applicability, this modeling approach has the potential to not only improve manufacturing in a wide range of industries, such as biofuels, biochemical, food and pharmaceutical industries, and but also to improving the nation?s energy security and sustainability.o This research promotes education of engineers and scientists for bioengineering and biotechnology at both graduate and undergraduate levels. In addition, the projects will actively involve minorities and give them research experience in biotechnology and renewable energy areas.