Drug-Driven AMPA Receptor Redistribution Mimicked by Selective Dopamine Neuron Stimulation

Addictive drugs have in common that they cause surges in dopamine (DA) concentration in the mesolimbic reward system and elicit synaptic plasticity in DA neurons of the ventral tegmental area (VTA). Cocaine for example drives insertion of GluA2-lacking AMPA receptors (AMPARs) at glutamatergic synapes in DA neurons. However it remains elusive which molecular target of cocaine drives such AMPAR redistribution and whether other addictive drugs (morphine and nicotine) cause similar changes through their effects on the mesolimbic DA system

Expression of ChR2 causes light-activated currents in DA VTA neurons.

<p>(<b>A</b>) Representative whole cell voltage clamp recordings of a DA VTA neuron. Following identification of cell type by the presence of an <i>I</i>_h current (left) responses to light pulses (black lines) at 4 ms (middle) or 100 ms (right) in the presence of TTX were tested (n = 10). (<b>B</b>) Same as in (A) but a representative non-DA VTA neuron (note lack of <i>I</i>_h (left); n = 6). (<b>C</b>) Digital micrograph showing YFP labeling of neurons within the VTA, together with putative GABAergic unlabeled neurons (asterisks).</p

Light pulses are sufficient to mimic burst firing of dopamine (DA) neurons <i>in vivo</i>.

<p>(<b>A</b>) Representative single unit recording (above) and peristimulus time histogram (below, 5 ms bins) of a VTA DA neuron during a single light pulse (black markers; 4 ms, one sweep every 2 s) (n = 7). (<b>B</b>) The same VTA DA neuron as in (A) responding to 5 light pulses at 20 Hz. (<b>C</b>) Light pulses (black markers) are sufficient to drive action potentials, which do not differ in waveform characteristics from spontaneously occurring action potentials (above). Average percentage of action potentials generated by consecutive light pulses (below). Note the decrease in fidelity of action potential firing with increasing numbers of light pulses. (<b>D</b>) A GABAergic VTA neuron, which was recorded in close proximity to light-responsive DA neurons, exhibiting no response to five 4 ms light pulses (n = 7).</p

Addictive drugs cause rectification via AMPAR redistribution.

<p>(<b>A</b>) Representative traces of AMPAR excitatory postsynaptic currents recorded at −70, 0 and +40 mV. Examples are shown from recordings 24 h post injection. (<b>B</b>) Individual and averaged normalized rectification indices (RIs) (mean ± s.e.m) of saline and each drug treatment. RIs of morphine (2.12±0.27), nicotine (2.06±0.23) and cocaine (1.72±0.14) groups were significantly different from the saline (1.12±0.08) control group (F_(3,35) = 4.93, p<0.01, ANOVA. n = 7–15). (<b>C</b>) Representative electron micrographs of VTA sections from saline- or drug-treated animals. Large profiles (arrows) represent tyrosine hydroxylase (TH) immunoreactivity in dendrites (Den) forming asymmetrical synapses with boutons (b), and small profiles (arrowheads) represent GluA2 immunoreactivity. (<b>D</b>) Number of small profiles plotted against the distance from the postsynaptic density. (<b>E</b>) Same as in (C) but staining against PSD 95. (<b>F</b>) Same quantification as in (D) but for PSD 95.</p

Cocaine drives the insertion of GluA2-lacking AMPARs via its effect on the DAT.

<p>(<b>A</b>) Single unit extracellular <i>in vivo</i> recordings (above) and corresponding firing rate plots (below) of VTA neurons during a single i.p. injection of 15 mg/kg cocaine in either WT (left) or DAT_KI (right) mice. Black bar denotes injection time, (a) and (b) denote points from which example traces were taken. (<b>B</b>) The resulting inhibition of neuron firing rate observed in WT mice (38±3.3%) was not present in DAT_KI mice (94.9±1.4%). n = 4–5, t₍₇₎ = 16.5, p<0.0001. (<b>C</b>) Representative AMPAR excitatory postsynaptic currents recorded at −60, 0 and +30 mV (normalized to +40 mV AMPAR component) and RIs (<b>D</b>) of WT and DAT_KI mice 24 h post cocaine injection. Linearity corresponds to and RI of 1. Mean RI = 1.95±0.17 in WT, and 1.12±0.08 in DAT_KI; F_(2–22) = 9.8, p<0.001, n = 5–9). All data are expressed as mean ± sem.</p