Computational model provides insight into the distinct responses of neurons to chemical and topographical cues

Predicting neurite extension for varying extracellular matrix stiffness and topography

Neurite extension is a dynamic process and is dependent on the microenvironment. The mechanical properties of the extracellular matrix (ECM), such as stiffness and topography influence the microenvironment and affects neurite extension; however, the mechanistic basis for this dynamic response of neurite extension remains elusive. In this study, we develop a computational model that predicts neurite extension dynamics process as the stiffness and patterned topography of ECM changes. The model includes the contribution of receptors integrin and neural cellular adhesion molecule toward the growth of neurite tip. We use non-linear finite element analysis (FEA) to model the neuronal cell, neurite, and the ECM, which is then coupled to the force-deformation receptor properties obtained from molecular dynamics simulations. Using an empirical relation, we develop a neurite extension algorithm that simulates the dynamic process of growth cone induced by growth cone extension, receptor density, and rupture. We investigate the dependence of neurite extension on ECM stiffness using three distinct materials, the effect of width and spacing of continuous (cylindrical) and discontinuous (pillar) patterned topography, as well as the topography steepness and stiffness gradient. We find that an increasing stiffness and width of patterned topography results in increased neurite extension, but the magnitude of the increase differs depending on the growth cone extension and receptor density between them. These findings will aid in vitro studies in determining an ECM with appropriate mechanical properties, such as stiffness and topography that will improve neurite extension, thus resulting in the formation of functional neurons.

Regulating the Homogeneity of Thiol-Maleimide Michael-Type Addition-Based Hydrogels Using Amino Biomolecules

Poly(ethylene glycol) (PEG)-based synthetic hydrogels based on Michael-type addition reaction have been widely used for cell culture and tissue engineering. However, recent studies showed that these types of hydrogels were not homogenous as expected since micro domains generated due to the fast reaction kinetics. Here, we demonstrated a new kind of method to prepare homogenous poly(ethylene glycol) hydrogels based on Michael-type addition using the side chain amine-contained short peptides. By introducing such a kind of short peptides, the homogeneity of crosslinking and mechanical property of the hydrogels has been also significantly enhanced. The compressive mechanical and recovery properties of the homogeneous hydrogels prepared in the presence of side chain amine-contained short peptides were more reliable than those of inhomogeneous hydrogels while the excellent biocompatibility remained unchanged. Furthermore, the reaction rate and gelation kinetics of maleimide- and thiol-terminated PEG were proved to be significantly slowed down in the presence of the side chain amine-contained short peptides, thus leading to the improved homogeneity of the hydrogels. We anticipate that this new method can be widely applied to hydrogel preparation and modification based on Michael-type addition gelation.

Numerical study of axonal outgrowth in grooved nerve conduits

Nerve conduits with grooved inner texture, working as a topographical guidance cue, have been experimentally proved to play a significant role in axonal alignment. How grooved conduits guide axonal outgrowth is of particular interest for studying nerve regeneration. A viscoelastic model of axonal outgrowth in a conduit with a defined grooved geometry characterized by its width in the circumferential direction and its height in the radial direction is developed in this work. In this model, the axon is considered as an elastic beam and the axonal deformation and motion, including stretching, bending and torsion, are described using a Cosserat rod theory. The friction between axon and substrate is also considered in this model as well as the tip outgrowth. It is found that the directional outgrowth of the axon can be significantly improved by the grooved texture: when the groove width decreases or the groove height increases, the axonal elongation in the longitudinal direction of the conduit can be increased, which is in good agreement with experimental observations. This work is the first numerical model to study the effect of the substrate geometry on axonal outgrowth.

Engineered in vitro/in silico models to examine neurite target preference

Research on spinal cord injury (SCI) repair focuses on developing mechanisms to allow neurites to grow past an injury site. In this article, we observe that numerous divergent paths (i.e., spinal roots) are present along the spinal column, and hence guidance strategies must be devised to ensure that regrowing neurites reach viable targets. Therefore, we have engineered an in vitro micropatterned model in which cultured E7 dorsal root ganglia (DRG) explants may enter alternate pathways (?roots?) along a branching micropattern. Alongside this in vitro model, we have developed an in silico simulation that we validate by comparison with independent experiments. We find in both in silico and in vitro models that the probability of a neurite entering a given root decreases exponentially with respect to the number of roots away from the DRG; consequently, the likelihood of neurites reaching a distant root can be vanishingly small. This result represents a starting point for future strategies to optimize the likelihood that neurites will reach appropriate targets in the regenerating nervous system, and provides a new computational tool to evaluate the feasibility and expected success of neurite guidance in complex geometries.