Proliferation and Cluster Analysis of Neurons and Glial Cell Organization on Nanocolumnar TiN Sub-Strates.

Abstract

Biomaterials employed for neural stimulation, as well as brain/machine interfaces, offer great perspectives to combat neurodegenerative diseases, while application of lab-on-a-chip devices such as multielectrode arrays is a promising alternative to assess neural function in vitro. For bioelectronic monitoring, nanostructured microelectrodes are required, which exhibit an increased surface area where the detection sensitivity is not reduced by the self-impedance of the electrode. In our study, we investigated the interaction of neurons (SH-SY5Y) and glial cells (U-87 MG) with nanocolumnar titanium nitride (TiN) electrode materials in comparison to TiN with larger surface grains, gold, and indium tin oxide (ITO) substrates. Glial cells showed an enhanced proliferation on TiN materials; however, these cells spread evenly distributed over all the substrate surfaces. By contrast, neurons proliferated fastest on nanocolumnar TiN and formed large cell agglomerations. We implemented a radial autocorrelation function of cellular positions combined with various clustering algorithms. These combined analyses allowed us to quantify the largest cluster on nanocolumnar TiN; however, on ITO and gold, neurons spread more homogeneously across the substrates. As SH-SY5Y cells tend to grow in clusters under physiologic conditions, our study proves nanocolumnar TiN as a potential bioactive material candidate for the application of microelectrodes in contact with neurons. To this end, the employed K-means clustering algorithm together with radial autocorrelation analysis is a valuable tool to quantify cell-surface interaction and cell organization to evaluate biomaterials’ performance in vitro.