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

主要研究者：王金机构：奥本大学提案编号：1264861标题：生物反应器与细胞动力学建模的集成系统工程方法由于生物体固有的复杂调控机制，生物反应器的建模和控制对控制工程师提出了独特的挑战。解决这一挑战的关键是获得一个能够充分描述细胞代谢动力学的模型。PI计划使用Schillosomiastipitis作为模型系统来回答以下工程和科学问题：1。工程问题：如何有效地模拟细胞代谢的动力学，然后模拟生物反应器的动力学？2.科学问题：什么是管理S。树干炎从有氧生长到厌氧发酵？为了回答第一个问题，他们提出了一个名为通量平衡分析指导动态规划（FBA-DP）的计算框架来模拟细胞代谢的动力学。计算部分的补充是一个实验部分，新的设备和实验程序已经开发，以获得所需的计算部分的动态过程信息。为了回答第二个问题，将通过与托马斯W. Jeffries（UW？麦迪逊）。通过与Q教授的合作，Peter He（塔斯基吉大学），智能优点：o通过整合最优控制理论和流量平衡分析，FBA-DP框架应该能够提供动态细胞代谢的全基因组细胞内细节，而不需要体内酶动力学信息; o该项目将产生有史以来第一个关于S.在从有氧到无氧条件的转变过程中的柄。这样的时程数据是非常可取的研究人员谁是有兴趣在阐明基因调控网络的动态; o通过整合时间过程中的硅通量信息与体内转录组信息，PI将能够获得知识的各种调控机制的动态，管理的细胞转变的S。广泛的影响：o一旦代谢网络模型可用，这个框架可以应用于研究各种微生物和其他活细胞（如癌细胞）的细胞代谢。与大多数其他酵母和真菌一样，树干炎不能厌氧生长，这是一个未解决的基本生物学问题。此外，这些知识将使新菌株开发的代谢工程取得重大进展。的广泛适用性，这种建模方法有潜力，不仅提高制造业在广泛的行业，如生物燃料，生物化学，食品和制药行业，而且还提高国家？o这项研究促进了研究生和本科生阶段生物工程和生物技术工程师和科学家的教育。此外，这些项目将积极吸收少数群体参与，并向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.