Discerning Data Analysis Methods to Clarify Agonistic/Antagonistic Actions on the Ion Flux Assay of Ligand-Gated Ionotropic Glutamate Receptor on Engineered Post-Synapse Model Cells
- *Corresponding Author:
- Prof. Tetsuya Haruyama
Department of Biological Functions and Engineering
Kyushu Institute of Technology
Kitakyushu Science and Research Park
Fukuoka, 808-0196, Japan
Email: [email protected]
Received Date: December 01, 2010; Accepted Date: December 29, 2010; Published Date: December 31, 2010
Citation: Tateishi A, Cauchi M, Tanoue C, Migita S, Coleman SK, et al. (2011) Discerning Data Analysis Methods to Clarify Agonistic/Antagonistic Actions on the Ion Flux Assay of Ligand-Gated Ionotropic Glutamate Receptor on Engineered Post-Synapse Model Cells. J Biosens Bioelectron 2:104. doi: 10.4172/2155-6210.1000104
Copyright: © 2011 Tateishi A, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Cell-based experiments provide the efficacy of chemicals through the biological function. The authors have described post-synapse model cell-based assay based on qualified analysis for neural drug discoveries. However, in general, cell-based assays often include data fluctuation. This may be a barrier preventing the performance for various practical purposes. In this study, we tried discerning data analysis for clarify the chemical action to the ionotoropic glutamate receptor (GluR), whereby an ion-flux assay of post-synapse model cells is performed and are analyzed based on a chemometrics approach. The dynamic behavior of the GluR of post-synapse model cell was assayed with multivariate data analysis methods namely hierarchical cluster analysis (HCA) and principal component analysis (PCA). By using HCA, we can identify and remove the non-responding samples. By using PCA, the effect of chemicals on the dynamic behavior of ion flux through GluR can be recognized clearly; as either agonist or antagonist. As shown in the results, the GluR-based assay by post-synapse model cell with data analysis methods provide a sodium influx profile which is derived by an agonists or antagonists application. By employing the data analysis methods, PCA and HCA, it is possible to develop a smart cellular biosensing system for qualified analysis.