Brenton D. Hoffman

Scholar: 2013

Awarded Institution
Assistant Professor
Duke University
Department of Biomedical Engineering


Research Interests

Physiology and patho-physiology are largely manipulated through biochemical means; when we get sick, we typically get a pill. However, cells exist in a complex mechanical environment that is a source of applied forces and a means of mechanical support. Cells respond to mechanical signals through a poorly understood process called mechanotransduction. Furthermore, a commonality amongst many diseases lacking effective treatments is the importance of mechanical variables. For instance, atherosclerosis, also known as hardening of the arteries, is preferentially found in areas of the vasculature with disturbed flow, and cancer metastasis is thought to be associated with enhanced tissue stiffness. Thus, disturbed mechanical variables perturb cell signaling pathways to exacerbate disease states. Further progress has been challenging, as the tools commonly used to probe signaling pathways are based on the principles of solution biochemistry and are ill-suited for mechanotransduction studies.

A main goal of our research is to develop new tools and techniques capable of determining the mechanisms mediating the ability of cells to detect mechanical forces. We focus on the structures cells utilize to adhere to the environment, called focal adhesions. Recently, we developed a light-based sensor that allows visualization of forces across proteins in living cells. Here we focus on using this sensor to identify a portion of the signaling network in focal adhesions that is affected by mechanical forces.

To accomplish this goal, we use a combination of protein engineering, molecular biology, live-cell imaging, automated image analysis, and mathematical model. First, potential mediators of mechanotransduction will be identified as proteins that localize to areas of high molecular tension. Live-cell imaging will be used to determine the temporal relationships among these mediators during the assembly of mechanosensitive sub-cellular structures, such as focal adhesions. Mathematical modeling and other systems biology techniques will then be used to determine the regulatory interactions between these proteins that are consistent with the observed temporal relationships. This approach will add molecular detail to the current understanding of mechanotransduction as well as identify proteins likely to have important, but currently unappreciated, roles in mechanosensitive disease.