BRITE Relaunch: Using Cell Shape and Cytoskeletal Organization for Understanding and Predicting Cellular Force Generation

细胞在许多重要的生理过程中使用拉力或收缩力。这些收缩力驱动细胞分裂和细胞迁移。免疫系统的细胞，以及像转移性癌细胞这样的入侵者，利用这些力量挤压组织，甚至变形自己的细胞核以穿过微小的空间。直接测量这些力的方法已经开发出来，但它们昂贵，具有挑战性，并且有局限性。这个促进工程变革和公平进步的研究理念（BRITE）重新启动项目旨在开发基于成像的方法，以比目前更容易和更便宜地估计细胞力。这些方法有望通过即将采用的理论和实验技术，使这些塑造健康或患病组织的机械力更容易测量。本研究将训练研究生和本科生。此外，将为传统的工程课程开发新的课程材料，使学生能够理解现实世界的问题和社会目标。模拟还将被开发为高中、初中和大学学生学习科学的辅助工具。该项目将揭示细胞收缩力与丝状肌动蛋白结构之间的关系，并将开发用于预测肌动蛋白组织力的工具。收缩力是由细胞骨架施加的，以前的工作已经导致了一种假设，即测量荧光显微镜图像中可见的细胞骨架组织可能允许预测这些力。这一总体假设将通过计算机模拟、实验、成像和人工智能方法进行验证。肌动蛋白细胞骨架将使用专门的细胞骨架模拟软件进行模拟。通过改变参数和初始条件，将产生多种类型的细胞骨架结构，并测量运动蛋白对局灶黏附施加的力。细胞骨架组织和力分布之间的关系将使用机器学习方法进行研究。细胞将被培养并镀在玻璃表面，并使用活细胞或固定细胞肌动蛋白和DNA染色成像。有和没有遗传扰动的细胞骨架结构将被成像，结构的差异被识别并与模拟预测进行对比。将测量细胞对局灶黏附所施加的力，同时对这些细胞的细胞骨架结构进行成像。机器学习和高维数据分析方法将被应用于理解力和细胞骨架组织之间的关系。实验结果将提供反馈和改进模拟。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。

Cells use pulling, or contractile, forces for many important physiological processes. These contractile forces drive cell division and cell migration. Cells of the immune system, as well as invaders like metastatic cancer cells, use these forces to squeeze through tissue and even deform their own nuclei to slip through tiny spaces. Methods to directly measure these forces have been developed, but they are expensive, challenging, and have limitations. This Boosting Research Ideas for Transformative and Equitable Advances in Engineering (BRITE) Relaunch project aims to develop imaging-based methods to estimate cellular forces easier and cheaper than currently possible. The methods promise to make these mechanical forces shaping healthy or diseased tissues more easily measurable through the theoretical and experimental techniques to be employed. Graduate students and undergraduate students will be trained in this research. Additionally, new course material will be developed for traditional engineering courses to enable students to develop an understanding of real-world problems and societal goals. Simulations will also be developed as an aid to learning science for high school, middle school, and college students.This project will uncover the relationship between cellular contractile forces and the organization of the filamentous actin structure and will develop tools for predictive mapping of forces from actin organization. Contractile forces are exerted by the cellular cytoskeleton, and previous work has led to the hypothesis that measuring cytoskeletal organization visible in fluorescence microscopy images may allow for the prediction of these forces. This overarching hypothesis will be tested using computer simulations, experiments, imaging and artificial intelligence methods. The actin cytoskeleton will be simulated using specialized cytoskeletal simulation software. By changing parameters and initial conditions, many types of cytoskeletal structures will be generated, and forces exerted by motor proteins on focal adhesions will be measured. The relation between cytoskeletal organization and force distribution will be investigated using machine learning methods. Cells will be cultured and plated on glass surfaces and imaged using live- or fixed- cell actin and DNA stains. Cytoskeletal structure with and without genetic perturbations will be imaged, and differences in architecture identified and contrasted with simulation predictions. Forces exerted by the cells on focal adhesions will be measured and the cytoskeletal structure in these cells will be simultaneously imaged. Machine learning and high-dimensional data analysis methods will be applied to understand the relation between forces and cytoskeletal organization. Experimental results will provide feedback and improved simulations.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.