GCR: Collaborative Research: Fine-grain generation of multiscale patterns in programmable organoids using microrobots

患有疾病或有缺陷的重要器官的人通常需要器官替代来生存，但由于缺乏合适的组织匹配供体以及死后器官退化和免疫排斥等复杂性，替代器官的可用性受到严重限制。这些问题可以通过使用高保真度的人造器官来克服，但要实现这一目标，面临着艰巨而长期的科学和工程挑战，而这个项目的目标是开始迎接这些挑战。该项目将专注于在肝类器官中生成微尺度模式的概念验证，以模仿六边形模式排列的小叶的解剖结构。研究人员将使用微型机器人动态调节三维血管化肝类器官的基因表达，以产生小叶样图案。这个项目的结果将定义一个机器人辅助生物设计的新领域。这项研究将产生新的生物学规则，合成生物学工具和微型机器人，可以应用于许多学科。如果成功，另一个更广泛的影响将是展示一种方法，可用于在体外创造一种新的、类似于生物和医学研究的天然类器官，为研究人造人体器官的创造和修复打开大门。该项目包括研究生和博士后研究人员的研究培训。在体外复制生物模式的传统方法受到多种限制。以往对模式形成的研究主要依赖于在细胞培养中传递全局刺激和研究反应扩散介导的细胞命运模式。这种方法只能产生静态模式，对基因表达和由此产生的生物组织形成既没有精确的空间控制，也没有精确的时间控制。目前的组织工程技术，如3D打印和光遗传学，也无法重现天然类器官中明显的多尺度自组装模式。所提出的方法将能够精确控制微型机器人，以实现对3D生物系统模式的动态控制，从而在该领域创造一个范式转变。概念验证的目标是在工程三维组织结构中调节局部基因表达，以控制多尺度模式的出现。机器学习将用于衍生和表征所需的多尺度模式，合成生物学将赋予干细胞遗传回路，使其能够分化细胞以形成所需的组织结构，微型机器人将改变局部基因表达以形成组织结构中的多尺度模式。特别是，研究人员将开发和控制能够维持和携带工程发送细胞的微型机器人，驱动血管化三维肝类器官内的微型机器人和相关发送细胞到特定位置，并使用微型机器人控制的发送细胞与内皮细胞通信，诱导这些内皮细胞分泌Wnt并产生梯度控制肝小叶分区。这种模式的小叶分区将调节肝脏类器官的代谢活动。该奖项反映了美国国家科学基金会的法定使命，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。

People with diseased or defective vital organs often need organ replacement to survive, but the availability of replacement organs is severely restricted by shortages of suitable tissue-matched donors and complexities such as postmortem organ deterioration and immunological rejection. These problems could be overcome by using high fidelity artificially-grown organs, but achieving that goal faces daunting and long-standing scientific and engineering challenges that this project aims to begin to meet. The project will focus on proof-of-concept generation of microscale patterns in a liver organoid to mimic the anatomical structure of lobules arranged in hexagonal patterns. The researchers will use microrobots to dynamically regulate gene expression in 3D vascularized liver organoids to generate the lobule like patterns. The results of this project will define a new area of robot-assisted biological design. This research will result in new biological rules, synthetic biology tools, and microrobotics that can be applied in numerous disciplines. If successful, another broader impact will be the demonstration of a method that could be used to create a new, in vitro, native-like organoid for biological and medical research, opening the door for research into the creation and repair of synthetic human organs. The project includes research training for graduate students and postdoctoral researchers.Conventional methods of reproducing biological patterns in vitro suffer from multiple limitations. Previous research on pattern formation has largely relied on delivering global stimuli and studying reaction-diffusion mediated patterning of cell fates in the cell culture. Such methods yield only static patterns and give neither precise spatial nor temporal control over gene expression and resulting biological tissue formation. Current tissue engineering capabilities such as 3D printing and optogenetics are also unable to recapitulate the multiscale self-assembled patterns evident in native-like organs. The proposed approach will enable precise control of microrobots to achieve dynamic control over patterning in 3D biological systems, creating a paradigm shift in the field. The proof-of-concept goal is to modulate localized gene expression in engineered 3D tissue constructs to control the emergence of multiscale patterns. Machine learning will be used to derive and characterize desired multiscale patterns, synthetic biology to endow the stem cells with genetic circuits that can differentiate the cells to form desired tissue constructs, and microrobots to alter localized gene expression to form multiscale patterns in tissue constructs. In particular, the researchers will develop and control microrobots capable of sustaining and carrying engineered sender cells, drive the microrobots and associated sender cells within a vascularized 3D liver organoid to specific locations, and use the microrobot controlled sender cells to communicate with endothelial cells, inducing these endothelial cells to secrete Wnt and generate gradients controlling liver lobule zonation. This patterned lobule zonation will regulate the metabolic activity of the liver organoids.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.