Controlling Cellular Fate using Micromachines

使用微型机器控制细胞命运

• 批准号: 10501363
• 负责人: Sambeeta Das
• 金额: $ 40万
• 依托单位: UNIVERSITY OF DELAWARE
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-28 至 2027-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10501363
• 关键词: 3-Dimensional; Automobile Driving; Biological; Biology; Cell Communication; Cell Culture Techniques; Cell Therapy; Cells; Cellular Structures; Complex; Development; Diffusion; Embryo; Engineering; Event; Feedback; Fibrosis; Gene Expression; Genes; In Vitro; Individual; Malignant Neoplasms; Mediating; Methodology; Methods; Mitotic; Noise; Organ; Organoids; Pattern; Pattern Formation; Positioning Attribute; Reaction; Regenerative Medicine; Research; Shapes; Signal Transduction; Signaling Molecule; Stimulus; Surface; System; Technology; Tissues; Work; automated algorithm; behavior change; biological systems; cell behavior; cell type; design; human-in-the-loop; microrobot; morphogens; novel; optogenetics; spatiotemporal

PROJECT SUMMARY Key to multicellularity is the coordinated interaction of the various cells that make up the body. Indeed, patterning of embryos, establishment of cell type diversity, and formation of tissues and organs all rely on cell-to-cell communication. Thus, arguably one of the most important principles of biology involves “one group of cells changing the behavior of an adjacent set of cells, causing them to change their shape, mitotic rate, or fate”. Conventional methods of reproducing biological patterns and cell-fate in vitro suffer from multiple limitations. Previous work on understanding pattern formation has relied on delivering global stimuli and studying reaction- diffusion mediated patterning of cell fates in the cell culture. Another method has been to generate morphogen gradients using signaling molecule patterned surface or optogenetics. However, all current methods produce static patterns and give neither precise spatial nor temporal control over the cell fate. My research group aims to overcome this critical challenge, via a unique and novel cyber-bio system, in which microrobots direct the biological system, in a closed loop approach, to enable position-specific functionality and reduce noise – to direct cellular fate leading to the formation of cellular structures. Inspired by “human-in-the loop” approaches for engineering systems that must interact with complex, living individuals, we propose a “µrobot-in-the-loop” approach in which physical signaling among cells is substituted with microrobot-controlled inputs to afford excellent spatiotemporal precision and feedback control in directing cell behavior. Our efforts in the next five years would focus on designing and fabricating microrobots along with developing control algorithms for automated actuation of the microrobots. We will use these microrobots to deliver morphogens at precise positions in a cellular system which would alter cell fate at those positions only. We would also use this technology for controlling the formation of multilayer cellular structures. We would extend this to three dimensional tissues by interfacing microrobots with organoids. The proposed work is important because it would demonstrate how individual cells in a tissue volume can be spatially and temporally targeted for manipulation. This methodology applies more dynamic control over differentiation factors, which allows for increased understanding of complicated cell fate and differentiation events during cancer, development, or fibrosis as just a few of many applications.

项目总结 多细胞的关键是组成身体的各种细胞的协调相互作用。的确，花纹 胚胎的形成、细胞类型多样性的建立以及组织和器官的形成都依赖于细胞到细胞 沟通。因此，可以说，生物学中最重要的原理之一就是“一组细胞 改变一组相邻细胞的行为，导致它们改变形状、有丝分裂速率或命运“。 在体外复制生物模式和细胞命运的传统方法受到多重限制。 以前关于理解模式形成的工作依赖于传递全局刺激和研究反应- 扩散介导细胞培养中细胞命运的图案化。另一种方法是产生形态生成素 使用信号分子图案化表面或光遗传学的梯度。然而，所有当前的方法都会产生 静态模式，对细胞命运既不提供精确的空间控制，也不提供时间上的精确控制。 我的研究小组的目标是通过一个独特而新颖的网络生物系统来克服这一关键挑战，在这个系统中 微型机器人以闭环方式引导生物系统，以实现特定位置的功能和 减少噪音--引导细胞命运，导致细胞结构的形成。受《人在世界》的启发 对于必须与复杂的、活生生的个体交互的工程系统，我们提出了一种 以微机器人控制取代细胞间物理信号的“微机器人在环”方法 在指导细胞行为方面提供卓越的时空精度和反馈控制的输入。 我们在未来五年的努力将集中在微型机器人的设计和制造上，同时开发 微型机器人自动驱动的控制算法。我们将使用这些微型机器人来交付 在细胞系统中的精确位置上的形态生成物，只会在这些位置上改变细胞的命运。我们 也会使用这种技术来控制多层细胞结构的形成。我们会延长 通过将微型机器人与有机化合物相连接，将其转化为三维组织。 这项拟议的工作很重要，因为它将展示组织体积中的单个细胞如何 在空间和时间上以操纵为目标。此方法应用了更动态的控制 分化因子，从而增加对复杂的细胞命运和分化的理解 在癌症、发育或纤维化过程中发生的事件只是许多应用中的一小部分。