Designing Well-Ordered Neural Network on a Microelectrode Array Using Agarose Hydrogel S
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DESIGNING WELL-ORDERED NEURAL NETWORK ON A MICROELECTRODE ARRAY USING AGAROSE HYDROGEL S. Joo, J. Lim and Y. Nam Korea Advanced Institute of Science and Technology, REPUBLIC OF KOREA ABSTRACT We demonstrated an in vitro network chip design technique that produces well-ordered neural networks on a microelectrode array (MEA). To construct predesigned neural network, agarose hydrogel structures were molded using MIMIC (Micromolding in capillaries) on a MEA. Initially, E18 rat hippocampal neurons were positioned at node structures and multi-node networks were formed by guiding neurites through edges. MEA recordings showed that propagating spontaneous electrical activities were generated after 2 weeks in the network, and electrical stimulation of one cluster evoked synaptically transmitted action potentials in the other cluster. The proposed neural network is expected to be a useful in vitro model system for basic neuroscience and cell chip applications. KEYWORDS: Neuron patterning, Microelectrode array, In vitro, Agarose hydrogel, Primary neuron INTRODUCTION Cultured neural networks on planar-type microelectrode array (MEA) system have been used as an experimental model for studying electrophysiological properties of neuronal network about mechanism of learning and memory [1]. To enable efficient investigation about neural mechanisms underlying network dynamics, enhancing efficiency of neuron-electrode coupling and simplification of anatomical structure in the neural network has to be needed. Thus, the cell positioning and neurite outgrowth control have been applied to MEA by advanced microfabrication technologies [2,3]. Here we propose a neuronal network chip design technique that produced a simple but biologically functional network model on MEAs. To construct predesigned neural network composed of circular nodes of 100 µm diameter and edges of 10 µm width, agarose hydrogel structures were molded using MIMIC (Micromolding in capillaries) on a MEA. We also demonstrated that spontaneous activities of the neural network with E18 rat hippocampal neuron were measured by MEA system. Figure 1: (a)The dimension of node-edge structure of agarose hydrogel for designing neuronal network on MEA. (b) Fabrication process of well-ordered neural network on MEA using agarose hydrogel structure. EXPERIMENTAL Figure 1a shows basic node-edge structure of an agarose hydrogel for neuronal network on MEA. Five different patterns were designed and tested (2,3,4-node linear shape, 4-node T-shape, 5-node cross shape). Figure 1b shows a schematic representation of fabrication process of micropatterned cell- 978-0-9798064-7-6/µTAS 2014/$20©14CBMS-0001 503 18th International Conference on Miniaturized Systems for Chemistry and Life Sciences October 26-30, 2014, San Antonio, Texas, USA repulsive agarose hydrogels by the MIMIC. For the construction of agarose structure, a air-plasma treated mold was placed on a PDL(poly-D-lysine)-coated MEA substrate and agarose solution was dropped to fill the mold using capillary forces. Gelation of the agarose solution was performed at 4 °C for 3 hours and the MEA was sealed during gelation. After the gelation and drying of agarose solution, hippocampal neurons from dissected hippocampi of E18 Sprague-Dawley rat were seeded on the cell culture substrate. After 30 min, samples were rinsed with the plating media to remove unattached floating cells. Cultures were maintained in a humidified incubator under 5% CO2, 37 °C condition and culture media. Electrical recording and stimulations were performed by a 60-channel amplifier (MEA1060-Inv-BC, Multi Channel Systems), and a 4-channel stimulus generator (MSC-STG-2004, Multi Channel Systems). RESULTS AND DISCUSSION Figure 2: Patterned neural network with various network forms. (a-c) 2,3,4-node linear networks at 7,12,8 DIV. (d) 4-node T-shape network at 20 DIV. (e) 5-node cross shape network at 20 DIV. Figure 2 shows that neural network were successfully formed following variable pre-designed structure after 1~2 weeks. Especially, large nodes and narrow edge structure were effective in selectively localizing neuronal cell bodies in each node. Also, each nodes were connected by neurites from the cell bodies. Figure 3: (a) Movement of cells in the edge toward node structure. Patterned neural network with various network forms. (b) Networks were categorized as 4 different outcomes according to initial cells. Even though cells were located at edges at early stage of the cultivation, most of the neurons migrated into node areas and edge structures were cell-free after a few days of cultivation (Figure 3a). For the preservation of pre-designed shape of neural network, the average number of neurons on each node at the first time was crucial (Figure 3b). Node area with 7 to 13 cells maintained node-edge structure of the designed networks and each node had un-clustered cells, which was stable for 3 weeks. When there were 14 to 20 cells in the nodes, a small stationary cluster was formed at each node and the cluster remained intact for 2 weeks. Figure 4a shows that the neural network were functionally connected by MEA recording of propagation of spontaneous activities and evoked response in another channel. In the designed neural network, the 504 unidirectional neural signal propagations were observed. The nodes in the 3-node network had the fixed order of spike timing in synchronized bursts. Evoked responses from electrical stimulation were also important feature of the network. Figure 4c shows that six consecutive traces obtained from the recording electrode when electrical stimulation was applied at the stimulation electrode. The biological functionalities of well-ordered neuronal network means that the network could be a powerful tool to study the synaptic plasticity and functional electric stimulations. Figure 4: (a) Synchronized spontaneous activity of 3-node network. (b) Stimulus evoked responses from a 3-node network using specified shaped pulse. CONCLUSION This work developed a simple and reproducible method to design well-ordered neuronal networks on MEAs by controlling the location and growth of neuron using agarose hydrogel structures. The proposed fabrication process was applicable to ready-made MEA chips. Our well-ordered neuronal networks had biological functionalities (spontaneous activity, synchronized bursting, synapse-mediated evoked re- sponses). The presented reliable neuron patterning method in combination with electrical interfaces would also serve as a reduced model system to investigate neural dynamics such as network plasticity and synaptic response. ACKNOWLEDGEMENTS This work was supported by Mid-career Researcher Program through National Research Foundation grant (NRF-2012R1A2A1A01007327), and the Brain Research Program (NRF-2011-0019213) funded by the Ministry of Science, ICT and Future Planning. REFERENCES [1] G. W. Gross, B. K. Rhoades, H. M. Azzazy, E. S. Hung, “The use of neuronal networks on multielectrode arrays as biosensors,” Biosens. Bioelectron, 10, 553-567, 1995. [2] M. B. Sinclair, Y. Nam, D. W. Branch, and B. C. Wheeler, “Epoxy-silane linking of biomolecules is simple and effective for patterning neuronal cultures,” Biosens. Bioelectron, 22, 589-597, 2006. [3] I. Suzuki, Y. Sugio, Y. Jimbo, and K. Yasuda, “Stepwise pattern modification of neuronal network in photo-thermally-etched agarose architecture on multi-electrode array chip for individual-cell-based electrophysiological measurement,” Lab Chip, 5, 241-247, 2005. CONTACT * Y. Nam; phone: +82 42 350 4322; [email protected] 505.