Cell-Substrate Interactions in Orthopaedic Tissue Engineering


The cells of orthopaedic tissues such as articular cartilage and the intervertebral disc (IVD) are known to adjust their behavior in response to mechanical features in their local environment. An example of such a mechanism is called durotaxis [1].  One associated phenomenon is that cells seeded on a non-uniform substrate move along the gradient of increasing substrate stiffness.  Another occurs on substrates of uniform elastic stiffness, where cell-substrate attachments are favored over cell-cell attachments as the elastic modulus of the substrate is increased.  On soft substrates, it is also believed that individual cells may be capable of mechanosensing the presence of neighboring cells through coordinated mechanical interactions with the substrate. In cartilage tissue engineering applications, cells are seeded into three-dimensional biomaterial scaffolds that eventually degrade as new extracellular matrix is synthesized.  The spatial distribution and patterning of cells in the scaffold matrix are known to strongly influence key functional outcomes in the engineered tissue construct.


In this project, we will develop models of cell-cell and cell-substrate mechanical interactions using a lattice-based computational framework [2].  In this approach, each point of the lattice is associated with a specific constituent of the system at a particular time.  Evolution of the constituents on the lattice is determined via minimization of an energy constructed from the states of the lattice constituents at any given time. Models with interacting mechanisms are constructed via a total energy written as the sum of energies accounting for each mechanism under consideration. Applications of the models to be considered include the optimal arrangement of immature cells in the nucleus pulposus of the IVD and the effects of scaffold stiffness on seeding of chondrocytes in cartilage tissue engineering.


[1] CM Lo, HB Wang, M Dembo and Y Wang (2000) Cell movement is guided by the rigidity of the substrate, Biophysical Journal, 79:144-152


[2] ARA Anderson, MAJ Chaplain and KA Rejniak (2007) Single Cell-Based Models in Biology and Medicine, Birkhauser, Boston