Understanding the Role of Mechanical Boundary Conditions on Tissue Assembly and Repair in 3D Fibrous Microtissues

Trustees Of Boston University, Boston

Investigators

Abstract

This award will support research that will generate new knowledge about biological tissue assembly and repair. This work will both promote the progress of science and advance national health. Tissue assembly and repair are the fundamental mechanisms that underly wound healing. It is known that mechanical forces control tissue assembly. However, the mechanisms by which forces regulate new tissue formation and its organization remain poorly understood. Essentially, changing the mechanical forces on a tissue can either promote or suppress wound healing. However, the direct relationship between mechanical forces and wound healing outcomes are largely unknown. This award supports the fundamental research to provide knowledge about how mechanical forces will influence tissue assembly and repair in a tightly controlled laboratory setting. Through establishing a combined experimental and computational platform for measuring the interplay between mechanical, chemical, and biological cues, this research will directly advance the design of engineered devices and therapeutics to promote would healing. Thus, results from this research will benefit the U.S. national health, economy, and society as impaired wound healing is a significant medical problem. Finally, this work will include community outreach at the middle school level to educate students about the exciting field of mechanobiology. The objective of this project is to understand how domain boundary conditions (i.e., the boundary restraints that control emergent ECM alignment and tissue geometry) control local tissue repair (i.e., healing through matrix contractility and matrix deposition) via the induced spatially heterogeneous mechanical microenvironment (i.e., self-assembled fiber alignment, tissue strain, and tissue stress). This work tightly integrates in vitro experiments and computational modeling, where the in vitro experiments build on a previously developed three-dimensional in vitro biomimetic gap closure model of tissue assembly and repair. This work will first establish a mechanistic computational model to predict the heterogeneous stresses and strains of microtissue formed around different micropost configurations. Then, it will integrate the mechanistic computational model with timelapse image based experimental data to form a combined mechanistic and data-driven framework to predict the gap closure process. Finally, this framework will be used to define the transition regime between “gap closure” and “gap closure failure” for this in vitro experimental system. In addition to the knowledge gained about biological tissue assembly and repair, this work will establish a generalizable methodology for integrating mechanistic and data driven computational models for mechanobiological systems. 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.