Literature DB >> 27018734

Enhanced Dopamine Release by Dopamine Transport Inhibitors Described by a Restricted Diffusion Model and Fast-Scan Cyclic Voltammetry.

Alexander F Hoffman1, Charles E Spivak1, Carl R Lupica1.   

Abstract

Fast-scan cyclic voltammetry (FSCV) using carbon fiber electrodes is widely used to rapidly monitor changes in dopamine (DA) levels in vitro and in vivo. Current analytical approaches utilize parameters such as peak oxidation current amplitude and decay times to estimate release and uptake processes, respectively. However, peak amplitude changes are often observed with uptake inhibitors, thereby confounding the interpretation of these parameters. To overcome this limitation, we demonstrate that a simple five-parameter, two-compartment model mathematically describes DA signals as a balance of release (r/ke) and uptake (ku), summed with adsorption (kads and kdes) of DA to the carbon electrode surface. Using nonlinear regression, we demonstrate that our model precisely describes measured DA signals obtained in brain slice recordings. The parameters extracted from these curves were then validated using pharmacological manipulations that selectively alter vesicular release or DA transporter (DAT)-mediated uptake. Manipulation of DA release through altering the Ca(2+)/Mg(2+) ratio or adding tetrodotoxin reduced the release parameter with no effect on the uptake parameter. DAT inhibitors methylenedioxypyrovalerone, cocaine, and nomifensine significantly reduced uptake and increased vesicular DA release. In contrast, a low concentration of amphetamine reduced uptake but had no effect on DA release. Finally, the kappa opioid receptor agonist U50,488 significantly reduced vesicular DA release but had no effect on uptake. Together, these data demonstrate a novel analytical approach to distinguish the effects of manipulations on DA release or uptake that can be used to interpret FSCV data.

Entities:  

Keywords:  Voltammetry; brain slice; cathinones; dopamine transporter; drug abuse; kinetics

Mesh:

Substances:

Year:  2016        PMID: 27018734      PMCID: PMC4909544          DOI: 10.1021/acschemneuro.5b00277

Source DB:  PubMed          Journal:  ACS Chem Neurosci        ISSN: 1948-7193            Impact factor:   4.418


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