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代谢，并在系统和合成中应用 生物学。实验室有两个主要目标：研究和建模代谢动态和调节，以及 开发最小的设备生物传感器，以用于营养缺陷以部署以进行资源 - 环境差。生物传感器的工作具有广泛的全球实用性和影响力，也具有 激发了他们执行的一些系统生物学分析。这些代谢研究在于 计算和实验的界面，并通过使用代谢组学而统一。他的团队 使用临时代谢组学测量来捕获生物学的代谢动力学 系统，然后使用这些数据进行分析，理解和工程 生物系统。同时，他们开发了计算工具来更好地利用代谢组学 数据，目的是将这些数据应用于新的代谢建模框架。 在接下来的五年中，PI将应对一些最重要的挑战 在无细胞系统中 生物传感器。在过去的五年中，他一直是系统生物学界面和 无细胞合成生物学，发现基于裂解物的细胞中残留的内源性代谢 自由系统对于确定给定反应的总生产率至关重要。他将扩大 在发现后，充分表征了内源代谢对无细胞的影响 系统，并朝着解决当前更广泛采用的主要挑战 和无细胞系统的使用：反应中表达的早期终止。他将使用许多 系统规模的工具，包括代谢组学，蛋白质组学和通量学，以创建一个 无细胞系统中代谢的全面（也是唯一的）系统规模表征， 并将通过代谢建模和分析来完成这些努力，以获得更大的见解 进入系统的内部工作。 PI的整体愿景是对无单元系统的更深入的了解，使他们能够去 在采用，申请和影响方面的下一个级别。他还设想了重要的 来自这些细胞来源但无细胞的系统的生物学见解，包括 发现可能会在体内被上皮效应掩盖的调节相互作用。他 设想生物学家和生物工程探索他的工作的结果 有效的生物系统体外模型以及生物技术进步 以前是科学或经济上不可行的。