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Updated: Jul 4, 2025

A Simplified System for Evaluating Cell Mechanosensing and Durotaxis In Vitro
Published on: August 27, 2015
Stiffness assisted cell-matrix remodeling trigger 3D mechanotransduction regulatory programs
Anna L Kersey1, Daniel Y Cheng1, Kaivalya A Deo1
1Department of Biomedical Engineering, College of Engineering, Texas A&M University, College Station, TX 77843, USA.
Abstract:
Engineered matrices provide a valuable platform to understand the impact of biophysical factors on cellular behavior such as migration, proliferation, differentiation, and tissue remodeling, through mechanotransduction. While recent studies have identified some mechanisms of 3D mechanotransduction, there is still a critical knowledge gap in comprehending the interplay between 3D confinement, ECM properties, and cellular behavior. Specifically, the role of matrix stiffness in directing cellular fate in 3D microenvironment, independent of viscoelasticity, microstructure, and ligand density remains poorly understood. To address this gap, we designed a nanoparticle crosslinker to reinforce collagen-based hydrogels without altering their chemical composition, microstructure, viscoelasticity, and density of cell-adhesion ligand and utilized it to understand cellular dynamics. This crosslinking mechanism utilizes nanoparticles as crosslink epicenter, resulting in 10-fold increase in mechanical stiffness, without other changes. Human mesenchymal stem cells (hMSCs) encapsulated in 3D responded to mechanical stiffness by displaying circular morphology on soft hydrogels (5 kPa) and elongated morphology on stiff hydrogels (30 kPa). Stiff hydrogels facilitated the production and remodeling of nascent extracellular matrix (ECM) and activated mechanotransduction cascade. These changes were driven through intracellular PI3AKT signaling, regulation of epigenetic modifiers and activation of YAP/TAZ signaling. Overall, our study introduces a unique biomaterials platform to understand cell-ECM mechanotransduction in 3D for regenerative medicine as well as disease modelling.
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