GCR: Collaborative Research: Micro-bio-genetics for Programmable Organoid Formation

GCR：合作研究：用于可编程类器官形成的微生物遗传学

• 批准号: 2219101
• 负责人: Calin Belta
• 金额: $ 90万
• 依托单位: Trustees of Boston University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-10-01 至 2027-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2219101&HistoricalAwards=false
• 关键词: GCR; Collaborative; Research; Micro; bio

This project aims at defining a new area of dynamically-controlled, robot-assisted biological design. A convergent research team consisting of experts in microrobotics, machine learning, and synthetic biology will focus on developing a radically new approach towards analyzing and replicating intricate cellular patterning in mammalian tissues. Not only will this research result in new biological rules, synthetic biology tools, and microrobotics that can be applied in numerous disciplines, it will also create a new in vitro native-like liver organoid for biological and medical research. The work will open the door for research into the creation and repair of other synthetic human organs.The research team will generate multiscale, multicellular patterns and synthesize 3D patterns with vasculature to produce native-like organs. To enable mapping of pattern design problems to optimization problems, the researchers will define novel machine learning techniques to classify and quantify cellular patterns. To enable control of bio-compatible robots that guide cell organization and differentiation processes, they plan to develop novel technologies that leverage and far exceed current microrobotics. This will enable insights into fundamental scientific questions about cell differentiation and connections between spatial organization and function.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目旨在定义一个新的动态控制，机器人辅助生物学设计的领域。由微型机构，机器学习和合成生物学专家组成的收敛研究团队将着重于开发一种新的新方法来分析和复制哺乳动物组织中复杂的细胞模式。这项研究不仅会导致新的生物学规则，合成生物学工具和可用于众多学科的微生物学，而且还将创建一种新的体外本地肝脏器官，用于生物学和医学研究。这项工作将为研究和修复其他合成人体器官的创建和修复打开大门。研究团队将生成多尺度，多细胞模式，并与脉管系统合成3D模式，以产生类似天然的器官。为了将模式设计问题映射到优化问题，研究人员将定义新型的机器学习技术来对细胞模式进行分类和量化。为了控制指导细胞组织和分化过程的生物兼容机器人，他们计划开发利用并远远超过当前微型物质的新技术。这将使您能够深入了解有关细胞分化和空间组织和功能之间联系的基本科学问题。该奖项反映了NSF的法定任务，并使用基金会的智力优点和更广泛的影响审查标准，被认为值得通过评估来提供支持。