Neuronal alignment on asymmetric textured surfaces

Abstract

Axonal growth and the formation of synaptic connections are key steps in the development of the nervous system. Here, we present experimental and theoretical results on axonal growth and interconnectivity in order to elucidate some of the basic rules that neuronal cells use for functional connections with one another. We demonstrate that a unidirectional nanotextured surface can bias axonal growth. We perform a systematic investigation of neuronal processes on asymmetric surfaces and quantify the role that biomechanical surface cues play in neuronal growth. These results represent an important step towards engineering directed axonal growth for neuro-regeneration studies. These surfaces also provide physical guidance, and chemical support for neuronal cell adherence, axonal extension, network formation, and function. The axons, and in particular their dynamic unit known as the growth cone are able to detect and respond to environmental signals such as functionalization of surfaces with extracellular matrix proteins, biomolecules released by neighboring neurons at extremely low concentrations (molecular level), substrate stiffness and topographical and geometrical cues. 6 Over the past decade, there has been rapid progress in our understanding of the role played by chemical signaling and surface-based biochemical guidance on the growth cone dynamics and axonal elongation. For example, it is known that axonal navigation to their target depends on the precise arrangement of extracellular proteins on the growth surfaces. 2,6,7 It is also now recognized that mechanical interactions between neurons and their environment are playing an essential role in neuronal growth and development. 5,8 However, the neuronal response to mechanical and topographical stimuli, and the details of cell-surface interactions such as adhesion forces and traction stress generated during growth are currently poorly understood. 9,10Directional surfaces composed of asymmetric structures are widely used in nature for wet and dry adhesion.11 Inspired by these surfaces, Demirel et al. synthesized an asymmetric textured surface 12 and reported an engineered nanotextured surface deriving its anisotropic adhesive wetting directly from its asymmetric nanoscale roughness. 13 In an earlier study, Demirel et al. studied the fibroblast adhesion and removal on directional nanofilms, 14 using a fluidic shear stress to remove cells from a microfluidic channel. It has been shown that cells were removed with lower shear stresses when the flow was in the direction of nanorod tilt, compared to flow against the tilt.14 Adhesion and retraction under asymmetric mechanical cues demonstrated unique properties. 15Cell polarization (i.e., response to external cues such as chemical gradients and mechanical deformation) has been studied extensively on textured surfaces to understand cell fate. 16 However, unidirectional polarization in response to surface mechanical cues has not been demonstrated earlier.Here, we report axonal extension and network formation on asymmetri...

Neuronal growth as diffusion in an effective potential

“…In these cases, a model is motivated by a known underlying mechanism, whose validity is then tested against experimental data. Conversely, stochastic models have been recently introduced in order to provide purely phenomenological descriptions of axonal growth in some special cases, such as edge movement of the growth cone [10] or growth on asymmetrical surfaces [19].…”

“…We note that in general, equation (1) could also incorporate drift terms to account for biochemical or mechanical interactions between neurons, or between neurons and the growth substrate. For example, in our previous work we have used a constant velocity drift term to quantify axonal bias imparted by mechanical interactions between the growth cone and asymmetric growth surfaces [19]. The potential V(v) in eqn.…”

“…This time interval was chosen in order to allow enough time for typical axon growth to exceed the precision of our axon measurement (~0.1µm), while being short enough to accurately approximate an instantaneous velocity. The Nikon NIS-Elements Basic Research software [9,19] is used to measure the change in axon length, yielding 3 consecutive values of the 5-minute average axon growth velocity. While Fig.…”

“…After plating, cells were allowed to incubate at 37°C for 8, 15, 19, 26, 33, or 46 hours. Samples are then removed from the incubator, loaded into the BioHeater™ Closed Fluid Cell, and imaged under bright-field using the optical stage of the MFP-3D-BIO Atomic Force Microscope (AFM, Asylum Research) [9,19] (Fig. 1).…”

“…A general description of axonal growth must take into account the inherent stochastic nature of this process due to different chemotactic signals, internal biochemical reactions and the randomness of external signals of various strengths [5,7,[10][11][12][13][14][15][16][17][18][19][20]. Much of the previous work on stochastic effects has focused on describing axonal movement in the context of either intercellular diffusion of known neuron growth factors [5,[11][12][13][14], or intracellular events, such as polymerization of cytoskeletal structures [15][16][17], production of substrate adhesions sites [6], and transmembrane receptor activity [18].…”