Mechanical induction of gene expression in connective tissue cells.

The extracellular matrices of mammals undergo coordinated synthesis and degradation, dynamic remodeling processes that enable tissue adaptations to a broad range of environmental factors, including applied mechanical forces. The soft and mineralized connective tissues of mammals also exhibit a wide repertoire of mechanical properties, which enable their tissue-specific functions and modulate cellular responses to forces. The expression of genes in response to applied forces are important for maintaining the support, attachment, and function of various organs including kidney, heart, liver, lung, joint, and periodontium. Several high-prevalence diseases of extracellular matrices including arthritis, heart failure, and periodontal diseases involve pathological levels of mechanical forces that impact the gene expression repertoires and function of bone, cartilage, and soft connective tissues. Recent work on the application of mechanical forces to cultured connective tissue cells and various in vivo force models have enabled study of the regulatory networks that control mechanically induced gene expression in connective tissue cells. In addition to the influence of mechanical forces on the expression of type 1 collagen, which is the most abundant protein of mammals, new work has shown that the expression of a wide range of matrix, signaling, and cytoskeletal proteins are regulated by exogenous mechanical forces and by the forces generated by cells themselves. In this chapter, we first discuss the fundamental nature of the extracellular matrix in health and the impact of mechanical forces. Next we consider the utilization of several, widely employed model systems for mechanical stimulation of cells. Finally, we consider in detail how application of tensile forces to cultured cardiac fibroblasts can be used for the characterization of the signaling systems by which mechanical forces regulate myofibroblast differentiation that is seen in cardiac pressure overload. Copyright (c) 2010 Elsevier Inc. All rights reserved.