Systems Biology to Unlock the Next Level of Cell-Free Synthetic Biology

系统生物学开启无细胞合成生物学的新境界

• 批准号: 10623894
• 负责人: Mark Philip-Walter Styczynski
• 金额: $ 39.55万
• 依托单位: GEORGIA INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-06 至 2028-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10623894
• 关键词: Adoption; Behavior; Biological; Biomedical Engineering; Biosensor; Biotechnology; Cell-Free System; Cells; Complement; Data; Data Analyses; Development; Diagnostic; Engineering; Equipment; Goals; Laboratories; Malnutrition; Masks; Measurement; Metabolic; Metabolism; Modeling; Organism; Productivity; Proteomics; Reaction; Regulation; Research Project Summaries; Residual state; Resource-limited setting; System; Systems Biology; Testing; Therapeutic; Tube; Vision; Work; biological systems; computerized tools; cost; experimental study; improved; in vitro Model; in vivo; insight; metabolic abnormality assessment; metabolomics; synthetic biology; tool

Project Summary Research in the PI’s laboratory focuses on metabolism, with applications in systems and synthetic biology. The lab has two main goals: to study and model metabolic dynamics and regulation, and to develop minimal-equipment biosensors for nutritional deficiencies for deployment to resource- poor environments. The biosensor work has broad potential global utility and impact, and also motivates some of the systems biology analyses they perform. Those metabolic studies lie at the interface of computation and experiment, and are unified via their use of metabolomics. His group uses temporal metabolomics measurements to capture the metabolic dynamics of biological systems, and then uses these data for analysis, understanding, and engineering of those biological systems. In parallel, they develop computational tools to better exploit metabolomics data, with an aim towards applying those data to new metabolic modeling frameworks. In the next five years, the PI will tackle some of the most significant yet understudied challenges in cell-free systems, the group’s current platform of choice for the development of field-deployable biosensors. In the past five years he has been a trailblazer at the interface of systems biology and cell-free synthetic biology, discovering that residual endogenous metabolism in lysate-based cell- free systems is critical in determining the total productivity of a given reaction. He will expand upon that discovery to fully characterize the impacts of endogenous metabolism on cell-free systems, and to move towards solving what is currently the key challenge to broader adoption and use of cell-free systems: early termination of expression in reactions. He will use a host of systems-scale tools, including metabolomics, proteomics, and fluxomics, to create a comprehensive (and the only) systems-scale characterization of metabolism in cell-free systems, and will complement these efforts with metabolic modeling and analysis to gain greater insight into the inner workings of the system. The PI’s overall vision is of a deeper understanding of cell-free systems that allows them to go to the next level in terms of adoption, applications, and impact. He also envisions significant biological insight coming from these cell-derived but cell-free systems, including the ability to discover regulatory interactions that might otherwise be masked by epistatic effects in vivo. He envisions the results of his work being exploited by biologists and bioengineers to enable more effective in vitro models of biological systems as well as biotechnological advances that were previously either scientifically or economically infeasible.

项目摘要 PI实验室的研究重点是新陈代谢，在系统和合成中的应用 生物学该实验室有两个主要目标：研究和模拟代谢动力学和调节， 开发用于营养缺乏的最小设备生物传感器， 恶劣的环境。生物传感器工作具有广泛的潜在全球效用和影响， 激发了他们进行的一些系统生物学分析。这些代谢研究位于 计算和实验的接口，并通过代谢组学的使用统一起来。他的团队 使用时间代谢组学测量来捕获生物的代谢动力学， 系统，然后使用这些数据进行分析，理解和工程的那些 生物系统。同时，他们开发计算工具，以更好地利用代谢组学 数据，旨在将这些数据应用于新的代谢建模框架。 在接下来的五年里，PI将解决一些最重要但研究不足的挑战 在无细胞系统中，该集团目前选择的平台用于开发可现场部署的 生物传感器在过去的五年里，他一直是系统生物学界面的开拓者， 无细胞合成生物学，发现裂解物为基础的细胞中残留的内源性代谢， 自由体系在确定给定反应的总生产率方面是关键的。他将扩大 在该发现的基础上，充分表征内源性代谢对无细胞代谢的影响。 系统，并朝着解决目前更广泛采用的关键挑战迈进 和无细胞系统的使用：在反应中表达的早期终止。他将使用大量的 系统规模的工具，包括代谢组学，蛋白质组学和通量组学，以创建一个 无细胞系统中代谢的全面（和唯一）系统规模表征， 并将通过代谢建模和分析来补充这些努力， 系统的内部运作 PI的总体愿景是更深入地了解无细胞系统，使他们能够 在采用、应用和影响方面达到下一个水平。他还设想了重大的 来自这些细胞衍生但无细胞系统的生物学见解，包括 发现可能被体内上位效应掩盖的调节相互作用。他 设想他的工作成果被生物学家和生物工程师利用， 生物系统的有效体外模型以及生物技术的进步， 以前无论是科学上还是经济上都是不可行的。