Optimization of a microfluidic chip design for neuroblastoma cells and their microenvironment studies

Investigating each structural part of a neuron is crucial for clarifying the com plex working mechanism of the nervous system. Isolation of axons from their cell bodies plays an important role in understanding synapse formation, axonal injury and regeneration mechanisms, and the interaction between the neurons and their microenvi ronments. Multi-compartment microfluidic chips are one of the most developed systems used for axon isolation. In this thesis, the optimization of microfluidic chip produc tion has been carried out by changing photoresist types and UV exposure doses, and the effects of these variables on the microgroove width have been observed. For this purpose, two-step photolithography processes have been performed using SU-8 3005, SU-8 3050 SU-8 2005, and SU-8 2050 negative photoresists. Optimum microgroove width (7.3 µm) to isolate axons has been obtained by using SU-8 3005 and applying UV exposure for 3 seconds with a power of 21 mW/cm2 . A similar microgroove width (7.7 µm) has also been achieved by using a different mask alignment system operating outside the cleanroom conditions, and it has been evaluated as promising in terms of reducing microfluidic chip manufacturing costs. SH-SY5Y neuroblastoma cells have been seeded into the microfluidic chips with different microgroove geometries (4.4×10.2 µm, 4.4×7.3 µm, and 4×7.7 µm) through filtered micropipette tips and 8 mm wide reservoirs. The second seeding method has been found more efficient in terms of ap plicability and sustainability. It has also been observed that 4.4×10.2 µm geometry allowed cell migration in both cell culture methods while the other two geometries provided axon isolation. In conclusion, obtained microfluidic chips and improved cell culture method has been considered suitable to investigate the neurite elongation and differentiation of SH-SY5Y cells, and their interaction with their microenvironment. Keywords: Axon isolation, microfluidic neuron chip optimization, photolithography