Glutamate and dopamine (DA) represent two key contributors to striatal functioning, a region of the brain that is essential to motor coordination and motivated behavior. While electroanalytical techniques can be utilized for rapid, spatially resolved detection of DA in the interferent-rich brain environment, glutamate, a nonelectroactive analyte, cannot be directly detected using electroanalytical techniques. However, it can be probed using enzyme-based sensors, which generate an electroactive reporter in the presence of glutamate. The vast majority of glutamate biosensors have relied on amperometric sensing, which is an inherently nonselective detection technique. This approach necessitates the use of complex and performance-limiting modifications to ensure the desired single-analyte specificity. Here, we present a novel glutamate microbiosensor fabricated on a carbon-fiber microelectrode substrate and coupled with fast-scan cyclic voltammetry (FSCV) to enable the simultaneous quantification of glutamate and DA at single recording sites in the brain, which is impossible when using typical amperometric approaches. The glutamate microbiosensors were characterized for sensitivity, stability, and selectivity by using a voltammetric waveform optimized for the simultaneous detection of both species. The applicability of these sensors for the investigation of neural circuits was validated in the rat ventral striatum. Electrically evoked glutamate and DA release were recorded at single-micrometer-scale locations before and after pharmacological manipulation of glutamatergic signaling. Our novel glutamate microbiosensor advances the state of the art by providing a powerful tool for probing coordination between these two species in a way that has previously not been possible.
Simultaneous, Real-Time Detection of Glutamate and Dopamine in Rat Striatum Using Fast-Scan Cyclic Voltammetry
Laney C Kimble,Jack S Twiddy,Jenna M Berger,Alexandra G Forderhase,Gregory S. McCarty,John Meitzen,Leslie A. Sombers
Published 2023 in ACS Sensors
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- Publication year
2023
- Venue
ACS Sensors
- Publication date
2023-11-14
- Fields of study
Medicine, Chemistry
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- Source metadata
Semantic Scholar, PubMed
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