Entry Date:
August 5, 2013

Simulation and Modeling

Principal Investigator Roger Kamm


Computational models aide with data interpretation and experimental design, and simulations can prove insight into biological mechanisms in instances where experiments are not feasible. Modeling and simulation are integral parts to the Mechanobiology Lab, and we have developed models spanning length scales from single molecules to cell populations. Furthermore, these models are not independent; we employ course-graining techniques to allow models developed at small length scales to inform larger scale models. For example, the bulk properties of a material have been estimated by course-graining simulations of the constitutive atoms, providing a quantitative link between the chemical composition and mechanics of biomaterials.

The actin cytoskeleton contributes to the mechanical rigidity of cells, and dynamic reorganization of the intracellular actin network is required for key cellular events such as proliferation and migration. Mechanical force plays a crucial role in governing the dynamics of the actin cytoskeleton, and we have developed a computational model derived from Brownian dynamics simulations to study the mechanical properties of actin networks. The model well captures experimentally observed viscoelastic properties of actin and provides novel insight into the contribution of molecular motors and actin crosslinking proteins to the viscoelastic moduli of actin networks. Recently, we have extended this model to investigate the role of molecular motors in the generation of actin stress fibers, molecular complexes under tension that provide direct mechanical connections to the extracellular environment.

Simulation results from a hybrid continuum-discrete model show similar topology to neovascular networks generated in microfluidic devices (From ref. 3).
In the MIT Mechanobiology Lab, our experiments are tightly coupled with computational models for investigating biological phenomena. The highly controlled cell microenvironment enabled by our microfluidic platforms allows validation of our cell-level models, which in turn, provide insight into the mechanism underlying experimentally observed cellular behavior. We have integrated the microfluidic platform for studying angiogenesis with a hybrid discrete-continuum model to investigate the effects of matrix and growth factors on vascular network topology, and we have explored the link between matrix degrading enzymes and angiogenic sprout structure through control theory. Recently we have developed finite element models for investigating the role of interstitial flow in perturbing the tumor cell microenvironment, and we are adapting these models to aide in the development of patterned synthetic tissues and biological machines.