期刊
EXPERIMENTAL CELL RESEARCH
卷 351, 期 2, 页码 150-156出版社
ELSEVIER INC
DOI: 10.1016/j.yexcr.2017.01.007
关键词
Valvular heart disease; Mechanosensing; Cell signaling/signal transduction
资金
- Texas Tech University
Degenerative valvular diseases have been linked to the action of abnormal forces on valve tissues during each cardiac cycle. It is now accepted that the degenerative behavior of valvular cells can be induced mechanically in vitro. This approach of in vitro modeling of valvular cells in culture constitutes a powerful tool to study, characterize, and develop predictors of heart valve degeneration in vivo. Using such in vitro systems, we expect to determine the exact signaling mechanisms that trigger and mediate propagation of degenerative signals. In this study, we aim to uncover the role of mechanosensing proteins on valvular cell membranes. These can be cell receptors and triggers of downstream pathways that are activated upon the action of cyclical tensile strains in pathophysiological conditions. In order to identify mechanosensors of tensile stresses on valvular interstitial cells, we employed biaxial cyclic strain of valvular cells in culture and quantitatively evaluated the expression of cell membrane proteins using a targeted protein array and interactome analyses. This approach yielded a high-throughput screening of all cell surface proteins involved in sensing mechanical stimuli. In this study, we were able to identify the cell membrane proteins which are activated during physiological cyclic tensile stresses of valvular cells. The proteins identified in this study were clustered into four interactomes, which included CC chemokine ligands, thrombospondin (adhesive glycoproteins), growth factors, and interleukins. The expression levels of these proteins generally indicated that cells tend to increase adhesive efforts to counteract the action of mechanical forces. This is the first study of this kind used to comprehensively identify the mechanosensitive proteins in valvular cells.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据