Triggering Celltype Specific Behaviors with Rationally Designed Nanoenvironments

这个项目的目标是用合理设计的纳米环境触发细胞类型的特定行为。细胞行为严重依赖于细胞微环境，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而普遍的反应。对亚细胞尺度纳米环境的响应可以驱动独特的细胞行为，包括远距离引导，亚细胞精度控制，以及与其他细胞引导线索结合时，在多个尺度上控制细胞行为。该研究将产生定量见解和预测相场模拟，将在实验和模拟之间的反馈中得到验证和改进。这种反馈回路主要依赖于控制细胞实验，具有先进的图像分析，尖端的3D相场建模和机器学习，以将实验和模拟联系起来，并为纳米环境中细胞行为的预测性理解开辟道路。纳米环境对细胞行为的精确控制对于需要精确控制细胞和组织的迁移和行为的广泛生物学和生物医学应用具有很大的前景。该研究项目将允许pi为特定任务设计这种纳米环境制定指导原则，这将使这些材料能够应用于广泛的任务，通过医疗和其他技术对社会有益。这些项目将培训科学家使用即将开发的图像分析和建模软件，这些软件将免费提供。该培训将以为期一周的集训形式提供。私家侦探还将利用研究成果与公众接触。该项目的成果将通过出版物、会议和讲习班向学术界广泛传播。隐性，即纳米形貌对细胞骨架动力学的引导，是pi最近才发现的一种现象。这是哺乳动物细胞中的一种高度保守的现象，它开辟了新的、细胞类型特异性和空间精确控制的机会，但它尚未得到很好的理解。这个项目将导致对隐性的预测性理解，以及如何利用合理设计的纳米环境来利用它。这种理解将通过包括材料设计和制造，通过细胞成像和高级分析验证，以及调整和扩展三维相场模拟的迭代循环来实现。机器学习方法将使研究小组能够确定哪些细胞特征对确定隐层表型最重要，以及将纳米形貌特征与特定的隐层行为联系起来。从3D相场模拟的初步结果开始，显示出与关键实验预测的定性一致，团队希望开发一个定量预测模型，作为第二个目标，也将纳入现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学相关模型中证明细胞类型特异性控制。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。

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.