Triggering Celltype Specific Behaviors with Rationally Designed Nanoenvironments

该项目的目标是通过合理设计的纳米环境来触发特定细胞类型的行为。细胞的行为在很大程度上取决于细胞微环境，即细胞周围物质的物理和(生物)化学性质。PI已经证明，环境中的纳米结构引发了跨细胞类型的独特和普遍的反应。对亚细胞尺度纳米环境的响应可以驱动独特的细胞行为，包括长距离指导，亚细胞精确控制，以及当与其他细胞指导线索结合时，在多个尺度上控制的细胞行为。这项研究将产生定量的见解和预测性的相场模拟，这些将在实验和模拟之间的反馈中得到验证和改进。这一反馈回路主要依靠受控细胞实验、先进的图像分析、尖端的3D相场建模和机器学习，将实验和模拟联系起来，并开辟出一条预测理解纳米环境中细胞行为的途径。纳米环境对细胞行为的精确控制为需要精确控制细胞和组织的迁移和行为的广泛的生物和生物医学应用提供了巨大的希望。该研究项目将使私人投资机构能够为特定任务制定此类纳米环境设计的指导原则，使这些材料能够通过医疗和其他技术应用于对社会有益的广泛任务。PI将培训科学家如何使用将开发的图像分析和建模软件，这些软件将免费提供。这种培训将以为期一周的强化训练营的形式提供。私家侦察亦会利用这项研究接触一般市民。该项目的结果将通过出版物、会议和工作坊广泛传播给学术界。等向性，即通过纳米拓扑学指导细胞骨架动力学的现象，是私营部门最近才发现的现象。这是哺乳动物细胞中的一种高度保守的现象，它打开了新的、特定细胞类型的和空间上精确的控制机会，但它还没有被很好地理解。这个项目将导致对自趋向性的预测性理解，以及如何利用合理设计的纳米环境来利用它。这一理解将通过涉及材料设计和制造、细胞成像和高级分析的验证以及三维相场模拟的调整和扩展的迭代周期来实现。机器学习方法将使团队能够确定哪些细胞特征对确定内立位表型最重要，并将纳米地形特征与特定的内立位行为联系起来。从3D相场模拟的初步结果开始，该团队希望开发一种定量预测模型，作为第二个目标，该模型还将纳入真实的细胞骨架动力学，并能够在多个尺度上同时控制细胞功能。第三个目标是在生物相关的模型中展示特定细胞类型的控制。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The goal of this project is triggering cell-type-specific behaviors with rationally designed nano-environments. Cell behavior critically depends on the cellular microenvironment, i.e. the physical and (bio)chemical properties of the material surrounding the cell. The PIs have demonstrated that nanostructures in the environment elicit a unique and universal response across cell types. The response to subcellular scale nano-environment can drive unique cell behaviors, including guidance over large distances, control with subcellular precision, and, when combined with other cell guidance cues, cell behavior that is controlled on multiple scales. The research will yield quantitative insights and predictive phase-field simulations that will be validated and improved in feedback between experiments and simulations. This feedback loop relies critically on controlled cellular experiments with advanced image analysis, cutting-edge 3D phase-field modeling, and machine learning to link experiments and simulations and forge a path towards predictive understanding of cell behavior in nano-environments. Precise control of cell behavior with nano-environments holds great promise for a broad range of biological and biomedical applications that require precise steering of the migration and behavior of cells and tissues. The research project will allow the PIs to develop guiding principles for the design of such nano-environments for specific tasks, which will enable these materials to be applied to a broad range of tasks that are beneficial to society through medical and other technologies. The PIs will train scientists in the use of the image-analysis and modeling software that will be developed, which will be freely available. This training will be offered in the form of week-long, intensive bootcamps. The PIs will also use the research to reach out to the general public. The results of the project will be broadly disseminated to the academic community through publications, conferences and workshops.Esotaxis, the guidance of cytoskeletal dynamics by nanotopography, is a phenomenon that was discovered only recently by the PIs. It is a highly conserved phenomenon in mammalian cells that opens up novel, cell-type-specific and spatially precise control opportunities, but it is not yet well understood. This project will lead to a predictive understanding of esotaxis and how it can be harnessed with rationally designed nano-environments. This understanding will be achieved through an iterative cycle involving materials design and fabrication, validation through cellular imaging and advanced analysis, and tuning and extension of the three dimensional phase field simulations. Machine learning approaches will allow the team to determine which cellular characteristics are the most important for determining esotactic phenotypes, as well as well as to correlate nano-topographic features with specific esotactic behaviors. Starting with initial results from 3D phase-field simulations that exhibit qualitative agreement with key experimental predictions, the team expects to develop a quantitatively predictive model that, as a second goal, will also incorporate realistic cytoskeletal dynamics, and enable simultaneous control of cell functions on multiple scales. The third goal is to demonstrate cell type specific control in a biologically relevant model.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.