A self-referencing glutamate biosensor for measuring real time neuronal glutamate flux

Abstract

Quantification of neurotransmitter transport dynamics is hindered by a lack of sufficient tools to directly monitor bioactive flux under physiological conditions. Traditional techniques for studying neurotransmitter release/uptake require inferences from non-selective electrical recordings, are invasive/destructive, and/or suffer from poor temporal resolution. Recent advances in electrochemical biosensors have enhanced in vitro and in vivo detection of neurotransmitter concentration under physiological/pathophysiological conditions. The use of enzymatic biosensors with performance enhancing materials (e.g., carbon nanotubes) has been a major focus for many of these advances. However, these techniques are not used as mainstream neuroscience research tools, due to relatively low sensitivity, excessive drift/noise, low signal-to-noise ratio, and inability to quantify rapid neurochemical kinetics during synaptic transmission. A sensing technique known as self-referencing overcomes many of these problems, and allows non-invasive quantification of biophysical transport. This work presents a self-referencing CNT modified glutamate oxidase biosensor for monitoring glutamate flux near neural/neuronal cells. Concentration of basal glutamate was similar to other in vivo and in vitro measurements. The biosensor was used in self-referencing (oscillating) mode to measure net glutamate flux near neural cells during electrical stimulation. Prior to stimulation, the average influx was 33.9±6.4fmolcm−2s−1). Glutamate efflux took place immediately following stimulation, and was always followed by uptake in the 50–150fmolcm−2s−1 range. Uptake was inhibited using threo-β-benzyloxyaspartate, and average surface flux in replicate cells (1.1±7.4fmolcm−2s−1) was significantly lower than uninhibited cells. The technique is extremely valuable for studying neuropathological conditions related to neurotransmission under dynamic physiological conditions.