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量。这些收缩力量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，甚至使自己的细胞核变形，滑过微小的空间。已经开发了直接测量这些力量的方法，但这些方法昂贵、具有挑战性，而且有局限性。这个促进工程转型和公平进步的研究想法(BRITE)重新启动项目旨在开发基于成像的方法，以比目前可能的方法更容易和更便宜地估计细胞力。这些方法承诺通过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。本研究将对研究生和本科生进行培训。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、初中和大学生学习科学的辅助工具。该项目将揭示细胞收缩力量和丝状肌动蛋白结构组织之间的关系，并将开发预测肌动蛋白组织力量的工具。收缩力是由细胞骨架施加的，以前的工作导致了一种假设，即通过测量荧光显微镜图像中可见的细胞骨架组织可以预测这些力。这一最重要的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，并将测量马达蛋白对焦点粘连的作用力。将使用机器学习方法来研究细胞骨架组织和力分布之间的关系。细胞将在玻璃表面培养和电镀，并使用活细胞或固定细胞肌动蛋白和DNA染色进行成像。有和没有遗传干扰的细胞骨架结构将被成像，并识别结构上的差异，并与模拟预测进行对比。将测量细胞对局部粘连施加的力，并同时对这些细胞中的细胞骨架结构进行成像。将应用机器学习和高维数据分析方法来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的模拟。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。

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.