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，机器人辅助生物设计领域。一个由微型机器人、机器学习和合成生物学专家组成的聚合研究团队将专注于开发一种全新的方法，用于分析和复制哺乳动物组织中复杂的细胞模式。这项研究不仅将产生新的生物学规则，合成生物学工具和可应用于众多学科的微型机器人，还将为生物和医学研究创造一种新的体外天然肝脏类器官。这项工作将为研究其他人造人体器官的创造和修复打开大门。研究团队将生成多尺度、多细胞模式，并将3D模式与脉管系统合成，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，研究人员将定义新的机器学习技术来分类和量化细胞模式。为了能够控制引导细胞组织和分化过程的生物相容机器人，他们计划开发利用并远远超过当前微型机器人的新技术。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。