SusChEM: Metabolic Analysis and Optimization of Biofuel Production during light-dark cycles in Synechocystis

主要研究者：皮布尔斯，Christie方案编号：1336236机构：科罗拉多州立大学题目：SusChEM：集胞藻在光暗周期中生物燃料生产的代谢分析和优化本项目的总体目标是开发所需的计算工具，以指导蓝藻生物燃料生产的代谢工程工作。蓝细菌经历由昼夜节律驱动的动态细胞环境。该环境对蓝藻生物燃料生产的影响知之甚少，该项目旨在通过计算和实验技术更好地了解这种不断变化的细胞环境。蓝藻是一个有吸引力的生产平台，因为它们能够利用太阳能和固定大气中的碳。 此外，它们表现出快速的倍增时间，并具有既定的分子生物学工具箱。与他们的异养同行，很少有工作集中在开发代谢模型的全球代谢光合生物，准确地描述了光：暗周期期间经历的动态。这些生物体表现出独特的细胞条件和挑战，可以显著改变产生的分子的总体滴度。 在光合平台的光照条件下，氧化还原电位和循环电子流条件更有利于异源燃料的产生。该项目计划通过开发动态通量平衡分析（FBA）代谢模型来解决这些缺陷，该模型捕获了光暗周期下经历的动态变化。该动态FBA模型将利用包括代谢组学、转录组学和蛋白质组学在内的实验方法生成。这将是第一个为光合生物开发的动态FBA模型。然后，该模型将用于生成可验证的假设，以确定将提高生物燃料生产率的关键遗传修饰。这项工作将有助于全面了解光合生物的细胞代谢，并可应用于其他感兴趣的光合生物。从这些研究中产生的菌株将直接导致光合先进的生物燃料生产，具有经济和环境可持续性的潜力。该菌株将作为未来研究生物燃料升级战略和生物化学生产战略的平台。该项目将为本科生和研究生提供跨学科培训，并作出重大努力，将代表性不足的群体的成员包括在内。学生将获得代谢，代谢工程，合成生物学和光合生物的微生物细胞培养的数学建模的经验。这些经验将使学生处于合成生物学和光合生物生物燃料生产研究的最前沿。该项目还将为K-12学生的研究提供指导机会。

PI: Peebles, ChristieProposal Number: 1336236Institution: Colorado State UniversityTitle: SusChEM: Metabolic Analysis and Optimization of Biofuel Production during light-dark cycles in SynechocystisThe overall goal of this project is to develop the computational tools needed to guide metabolic engineering efforts in cyanobacteria for biofuel production. Cyanobacteria experience a dynamic cellular environment that is driven by circadian rhythms. The impacts of this environment on biofuel production in cyanobacteria are poorly understood, and this projects aims to better understand this changing cellular environment through computational and experimental techniques.Cyanobacteria are an attractive production platform due to their ability to utilize solar energy and fix atmospheric carbon. In addition, they exhibit rapid doubling times and have an established molecular biology toolbox. Unlike their heterotrophic counterparts, little work has focused on developing metabolic models of global metabolism in photosynthetic organisms that accurately describe the dynamics experienced during light:dark cycles. These organisms exhibit unique cellular conditions and challenges that can substantially alter overall titers of molecules produced. During light conditions in a photosynthetic platform, redox potential and cyclic electron flow conditions are much more favorable for heterologous fuel production. This project plans to address these deficiencies by developing a dynamic flux balance analysis (FBA) model of metabolism that captures the changing dynamics experienced under light:dark cycles. This dynamic FBA model will be generated utilizing experimental methods that include metabolomics, transcriptomics, and proteomics. This will be the first dynamic FBA model developed for a photosynthetic organism. This model will then be utilized to generate testable hypothesis to identify key genetic modifications that will increase biofuel productivity. This work will contribute to an overall understanding of cellular metabolism in a photosynthetic organism and can be applied to other photosynthetic organisms of interest.The strain created from these studies will lead directly to photosynthetic advanced biofuel production with the potential to be economically and environmentally sustainable. This strain will serve as a platform for future research on biofuel upgrading strategies and on biochemical production strategies. The project will provide interdisciplinary training for undergraduate and graduate students, with significant efforts being made to include members of underrepresented groups. Students will gain experience in mathematical modeling of metabolism, metabolic engineering, synthetic biology, and microbial cell cultivation of photosynthetic organisms. These experiences will place the students at the forefront of research in synthetic biology and biofuel production in photosynthetic organisms. The project will also provide opportunities for mentoring of K-12 students in research.