Integrated Experimental and Computational Approach to Unveil Mechanisms of Deformation in Fibrous Biological Materials

Human tissues are composed of fibers that deform in response to forces produced by the resident cells. In turn, those deformations provide cues to the cells that trigger regeneration, repair, and progression of disease. For example, in cancer cell invasion, permanent deformations can produce tunnels that cancer cells use to move and spread throughout the human body. Although it is well recognized that permanent deformations occur in biological tissues, the underlying causes are unclear. Furthermore, it is unclear how different chemical connections between the fibers, called crosslinkers, affect permanent deformations. This project will answer these questions using a combination of experiments and computational modeling. The experiments will precisely deform tissue mimics while simultaneously capturing images of the fibers with a microscope, which will identify exactly how the fibers deform relative to each other. The computational model will simulate the physical deformations of each fiber. Computational results will be combined with the experimental data using an artificial intelligence (AI)-based method, which will enable accurate prediction of how tissues permanently deform in response to forces. The predictions will be tested in further experiments that mimic invasion of cancer cells. In addition to providing essential knowledge required to predict and target cancer cell invasion, this project will enhance STEM education and improve the STEM workforce through a combination of a summer computing program for high school students, an exhibit in an annual Engineering Expo, and a Research Experience for Teachers program, in which high school science teachers will participate in the research and build hands-on activities to implement in the classroom. This project will advance understanding of the underlying mechanisms for plastic deformation in the extracellular matrix. The experiments will deform networks of collagen I fibers and simultaneously use confocal microscopy to quantify stretching of individual fibers and relative sliding between fibers. A mechanics-based fiber network model will be closely integrated with the experimental results to infer model parameters and quantify the interplay between fiber stretching and sliding. The experiments and modeling will be repeated for collagen networks in the presence of different crosslinkers, which will identify how the different crosslinkers affect the underlying mechanisms for plastic deformation. Further, model predictions will be tested in a set of experiments in a cancer cell invasion assay, to quantify the effects of fiber density, alignment, and crosslinking on cell-induced plasticity and cell migration. 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.