Selective Growth of Neural Networks on Micro-Patterned Graphene

Abstract

Single crystal graphene is the ideal candidate for next generation of electronic devices and of biosensors. Interfacing graphene with neural cells could be highly advantageous in exploring their electrical behaviour and promising for several biomedical applications, including neural regeneration and artificial retina. Here, we present a straightforward fabrication technique based on laser ablation to obtain patterned substrates promoting ordered neuron growth. Chemical vapor deposition (CVD) single layer graphene (SLG) was machined by means of single pulse UV laser ablation technique at the lowest effective laser fluence in order to minimize laser damage effects (1). The obtained patterned substrates, with alternating micro-sized stripes of ablated and not-ablated SLG, were uniformly coated with poly-D-lysine; primary embryonic hippocampal neurons were cultured on the functionalized substrates. As monitored by time-lapse imaging, neurons adhered on both regions of the pattern, but they spontaneously migrate to the SLG areas and eventually form an ordered interconnected neuron pattern perfectly superimposed to the pattern design. Surface functionalization was then more effective on the SLG, and resulted in notably aligned neural network. The described technique could be considered a valuable candidate to realize a new generation of highly specialized biosensors. To gain further insight into the preferential positioning of neurons onto SLG, the distribution of focal adhesion proteins on the patterned SLG was investigated; Stochastic Optical Reconstruction Microscopy (STORM) was employed in order to localize the cellular components for focal adhesion. Super resolution imaging qualitatively confirms that the distribution of vinculin molecules tagged with Alexa 647 has more affinity towards the SLG regions compared to the ablated ones.1 Lorenzoni et al, Scientific Reports 3:1954, DOI:10.1038/srep01954.