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

University Of North Carolina At Chapel Hill, Chapel Hill NC

Investigators

Abstract

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.