Computational Cell Motility Model Educed from Single-Cell and High-Throughput Phenotype Analysis

细胞的机械特性和机械感知对细胞的身份和稳态至关重要。广泛的研究表明，细胞的各种机械特性与其分化、调节基因表达和指导运动的能力之间存在相关性。这些过程在胚胎发育过程中是至关重要的，并且似乎是癌症的核心。虽然在力学测量、生物化学和运动性以及癌症行为之间建立了相关性，但在这些过程中明显缺乏对力学的综合理解。在这个项目中，研究人员开发了一个集成的计算模型，该模型将生物化学、细胞结构和细胞运动动力学行为与通过实验技术测量的计算机械性能的能力结合起来。这将使研究小组首先了解潜在的生物现象，其次，这些工具如何将生物化学和基因组学与细胞力学联系起来。此外，为了充分表征力学在细胞过程中的作用，该项目将为细胞生物物理学带来高通量方法。这将使研究人员能够将基因组学和蛋白质组学与跨越癌症和细胞/组织模型的细胞力学特性联系起来。该项目的结果将为在癌症诊断和制定治疗策略中使用实验工具提供指导。细胞运动模型已经建立了六种主要的生物物理成分/现象：a.板足延伸，b.皮质肌动蛋白流动，c.膜张力，d.牵引，e.由活性凝胶组成的中心区域，f.粘弹性核。最后，细胞感知它们的机械环境和施加在它们身上的力，这些线索可以指导它们的运动。这些现象并不是独立的，对细胞突起前缘的作用的理解必须与细胞后方的细胞收缩、整体形状扭曲、细胞基质力以及细胞中肌动蛋白的整体命运和运输结合起来。目前还没有一种计算模型能够结合这些特征，对运动的主要机制形成自一致的理解。相应地，广泛的细胞生物物理表征技术已经开发出来，包括基于探针的原子力显微镜（AFM）方法，主动和被动基于头的方法，牵引力测量和整体细胞力学方法。理解这些方法所探测的细胞结构和过程依赖于生化干预和建模，该项目采用综合计算模型来解释单细胞或细胞群体的多重力学分析。开发的计算模型将针对选定的癌细胞运动模型进行一系列机械和结构研究，研究人员的实验室同时对单个细胞进行多机械测量，并对细胞群进行高通量机械研究。这种独特的综合计算/实验方法将使细胞力学研究与基因组/蛋白质组学方法相结合。

The mechanical properties and mechanical sensing of cells is critical to the identity and homeostasis of the cell. A wide range of studies have shown correlations between a variety of mechanical properties of cells and their ability to differentiate, to modulate gene expression, and to direct motility. These processes are critical for during the development of the embryo and appear to be central in cancer. While correlations are being established between the mechanical measurements, biochemistry and motility, and cancer behavior, there is a striking lack of integrated understanding of mechanics in these processes. In this project, the investigators develop an integrated computational model that will incorporate biochemistry, cell structure, and cell motility dynamical behavior with the ability to compute mechanical properties as measured by experimental techniques. This will allow the research team to understand first, the underlying biological phenomena, and second, how these tools can connect biochemistry and genomics with cell mechanics. Further, to fully characterize the role of mechanics in cellular processes, this project will bring high-throughput methods to cell biophysics. This will allow the investigators to connect genomics and proteomics to the mechanical properties of cells across the spectrum of cancers and cell/tissue models. The results of this project will provide guidance for the use of experimental tools in diagnosis of cancer and in developing strategies for treatment. Models of cell motility have established six principle biophysical constituents/phenomena: a. lamellipodia extension, b. flow of cortical actin, c. membrane tension, d. traction, e. a central region consisting of an active gel, and f. a viscoelastic nucleus. Finally, cells sense their mechanical environment and forces that are applied to them, and these cues can direct their motility. These phenomena are not independent, and an understanding of the role of the leading edge of cell protrusions have to be combined with cell retraction at the rear, global shape distortions, cell-matrix forces, and the global fate and trafficking of actin in the cell. There is no current computational model that combines these features to develop a self-consistent understanding of the primary mechanisms of motility. Correspondingly, a wide range of cell biophysical characterization techniques have been developed ranging from probe-based methods of atomic force microscopy (AFM), and active and passive bead based methods, traction force measurements and global cell mechanical methods. Understanding the cell structures and processes that are being probed by these methods depends on biochemical interventions and modeling, and this project employs an integrated computational model to interpret multiple mechanical assays on single cells or on cell populations. The computational model that is developed will be tested against a battery of mechanical and structural studies on selected cancer cell motility models, with the investigators' laboratory performing simultaneous multi-mechanical measurements on individual cells, and performing high-throughput mechanical studies on cell populations. This unique integrated computational/experimental approach will allow cell mechanical studies to be integrated with genomic/proteomic methodologies.