Post-Synapse Model Cell for Synaptic Glutamate Receptor (GluR)-Based Biosensing: Strategy and Engineering to Maximize Ligand-Gated Ion-Flux Achieving High Signal-to-Noise Ratio

Abstract

Cell-based biosensing is a “smart” way to obtain efficacy-information on the effect of applied chemical on cellular biological cascade. We have proposed an engineered post-synapse model cell-based biosensors to investigate the effects of chemicals on ionotropic glutamate receptor (GluR), which is a focus of attention as a molecular target for clinical neural drug discovery. The engineered model cell has several advantages over native cells, including improved ease of handling and better reproducibility in the application of cell-based biosensors. However, in general, cell-based biosensors often have low signal-to-noise (S/N) ratios due to the low level of cellular responses. In order to obtain a higher S/N ratio in model cells, we have attempted to design a tactic model cell with elevated cellular response. We have revealed that the increase GluR expression level is not directly connected to the amplification of cellular responses because the saturation of surface expression of GluR, leading to a limit on the total ion influx. Furthermore, coexpression of GluR with a voltage-gated potassium channel increased Ca2+ ion influx beyond levels obtained with saturating amounts of GluR alone. The construction of model cells based on strategy of amplifying ion flux per individual receptors can be used to perform smart cell-based biosensing with an improved S/N ratio.

Keywords

• cell-based biosensors
• high through-put analysis (HTA)
• organ function model
• post-synapse model cell
• cell engineering
• ionotropic glutamate receptor
• signal-to-noise ratio