Drugs of abuse , stress , and addiction

Drugs of abuse , stress , and addiction

Neuroplasticity, the putative mechanism underlying learning and memory, is modified by drugs of abuse, alcohol and may contribute to the development of the eventual addicted state. Innovative treatments directly targeting these drug-induced changes in brain reward components and circuits may be efficacious in reducing drug use and relapse.

Nicotine promotes glutamatergic synaptic plasticity in dopaminergic (DA) neurons in the ventral tegmental area (VTA), which is thought to be an important mechanism underlying nicotine reward. However, it is unclear whether exposure of nicotine alone to VTA slice is sufficient to increase glutamatergic synaptic strength on DA neurons and which nicotinic acetylcholine receptor (nAChR) subtype mediates this effect. Here, we report that the incubation of rat VTA slices with 500 nM nicotine induces glutamatergic synaptic plasticity in DA neurons. We measure the ratio of AMPA and NMDA receptor-mediated currents (AMPA/NMDA) and compare these ratios between nicotine-treated and -untreated slices. Our results demonstrate that the incubation of VTA slices with 500 nM nicotine for 1 h (but not for 10 min) significantly increases the AMPA/NMDA ratio when compared with controls. Preincubation with 10 nM of the α7-nAChR antagonist, methyllycaconitine (MLA) but not 1 μM α4-containing nAChR antagonist, dihydro-β-erythroidine (DHβE) prevents nicotinic effect, suggesting that α7-nAChRs are mainly mediated this nicotinic effect. This finding is further supported by the disappearance of this nicotinic effect in nAChR α7 knockout (KO) mice. Furthermore, nicotine reduced paired-pulse ratio (PPR) of evoked excitatory postsynaptic potential (eEPSP) in the VTA slices prepared from wild-type (WT) mice but not α7 KO mice. Collectively, these findings suggest that exposure of smoking-relevant concentrations of nicotine to VTA slices is sufficient to increase glutamatergic synaptic strength on DA neurons and that α7-nAChRs likely mediate this nicotinic effect through increasing presynaptic release of glutamate. Synapse, 2011. © 2010 Wiley-Liss, Inc.

Alterations in neuronal activity can elicit long-lasting changes in the strength of synaptic transmission at excitatory synapses and, as a consequence, may underlie many forms of experience-dependent plasticity, including learning and memory. The best-characterized forms of such synaptic plasticity are the long-term depression (LTD) and long-term potentiation (LTP) observed at excitatory synapses in the CA1 region of the hippocampus. It is now well accepted that the trafficking of AMPA receptors to and away from the synaptic plasma membrane plays an essential role in both LTP and LTD, respectively.

In an ever-changing environment, animals must learn new behavioral strategies for the successful procurement of food, sex, and other needs. Synaptic plasticity within the mesolimbic system, a key reward circuit, affords an animal the ability to adapt and perform essential goal-directed behaviors. Ironically, drugs of abuse can also induce synaptic changes within the mesolimbic system, and such changes are hypothesized to promote deleterious drug-seeking behaviors in lieu of healthy, adaptive behaviors. In this review, we will discuss drug-induced neuroadaptations in excitatory transmission in the ventral tegmental area and the nucleus accumbens, two critical regions of the mesolimbic system, and the possible role of dopamine receptors in the development of these neuroadaptations. In particular, we will focus our discussion on recent studies showing changes in AMPA receptor function as a common molecular target of addictive drugs, and the possible behavioral consequences of such neuroadaptations.

The main characteristics of cocaine addiction are compulsive drug use despite adverse consequences and high rates of relapse during periods of abstinence. A current popular hypothesis is that compulsive cocaine use and cocaine relapse is due to drug-induced neuroadaptations in reward-related learning and memory processes, which cause hypersensitivity to cocaine-associated cues, impulsive decision making and abnormal habit-like learned behaviours that are insensitive to adverse consequences. Here, we review results from studies on the effect of cocaine exposure on selected signalling cascades, growth factors and physiological processes previously implicated in neuroplasticity underlying normal learning and memory. These include the extracellular signal-regulated kinase (ERK) signalling pathway, brain-derived neurotrophic factor (BDNF), glutamate transmission, and synaptic plasticity (primarily in the form of long-term potentiation and depression, LTP and LTD). We also discuss the degree to which these cocaine-induced neuroplasticity changes in the mesolimbic dopamine system mediate cocaine psychomotor sensitization and cocaine-seeking behaviours, as assessed in animal models of drug addiction. Finally, we speculate on how these factors may interact to initiate and sustain cocaine psychomotor sensitization and cocaine seeking.

Synaptic plasticity in the ventral tegmental area (VTA) is modulated by drugs of abuse and stress and is hypothesized to contribute to specific aspects of addiction.

Both excitatory and inhibitory synapses on dopamine neurons in the VTA are capable of undergoing long-term changes in synaptic strength. While the strengthening or weakening of excitatory synapses in the VTA has been widely examined, the role of inhibitory synaptic plasticity in brain reward circuitry is less established. Here, we investigated the effects of drugs of abuse, as well as acute stress, on long-term potentiation of GABAergic synapses onto VTA dopamine neurons (LTPGABA). Morphine (10 mg/kg i.p.) reduced the ability of inhibitory synapses in midbrain slices to express LTPGABA both at 2 and 24 h after drug exposure but not after 5 days. Cocaine (15 mg/kg i.p.) impaired LTPGABA 24 h after exposure, but not at 2 h. Nicotine (0.5 mg/kg i.p.) impaired LTPGABA 2 h after exposure, but not after 24 h. Furthermore, LTPGABA was completely blocked 24 h following brief exposure to a stressful stimulus, a forced swim task. Our data suggest that drugs of abuse and stress trigger a common modification to inhibitory plasticity, synergizing with their collective effect at excitatory synapses. Together, the net effect of addictive substances or stress is expected to increase excitability of VTA dopamine neurons, potentially contributing to the early stages of addiction.

What to eat to prevent drug and alcohol negative effects? Dietary Amino Acids

Hypothalamic orexin/hypocretin (orx/hcrt) neurons regulate energy balance, wakefulness, and reward; their loss produces narcolepsy and weight gain. Glucose can lower the activity of orx/hcrt cells, but whether other dietary macronutrients have similar effects is unclear. We show that orx/hcrt cells are stimulated by nutritionally relevant mixtures of amino acids (AAs), both in brain slice patch-clamp experiments, and in c-Fos expression assays following central or peripheral administration of AAs to mice in vivo. Physiological mixtures of AAs electrically excited orx/hcrt cells through a dual mechanism involving inhibition of KATP channels and activation of system-A amino acid transporters. Nonessential AAs were more potent in activating orx/hcrt cells than essential AAs. Moreover, the presence of physiological concentrations of AAs suppressed the glucose responses of orx/hcrt cells. These results suggest a new mechanism of hypothalamic integration of macronutrient signals and imply that orx/hcrt cells sense macronutrient balance, rather than net energy value, in extracellular fluid.

Nutritionally Relevant Mixes of Amino Acids Excite orx/hcrt Neurons In Situ

To test whether the activity of orx/hcrt cells is modulated by dietary amino acids (AAs), we first used a mixture of amino acids (“AA mix”; see Table S1 available online) based on microdialysis samples from the rat hypothalamus (Choi et al., 1999). Whole-cell patch-clamp recording showed that orx/hcrt cells depolarized and increased their firing frequency in response to the AA mix (Figure 1A; all statistics are given in the figure legends unless stated otherwise). The latency of response onset was 66 ± 5 s (n = 25). This response was unaffected by blockers of ionotropic glutamate, GABA, and glycine receptors (Figure 1B), or by blockade of spike-dependent synaptic transmission with tetrodotoxin (Figure 1C). We did not observe such AA responses in neighboring lateral hypothalamic GAD65 neurons (Figures 1D and 1F; see Experimental Procedures), or in cortical pyramidal cells (Figures 1E and 1F).

Highlights

► Brain orexin/hypocretin cells are stimulated by dietary amino acids (AAs) ► AA sensing involves K-ATP channels and system-A transporters ► Nonessential AAs stimulate orexin/hypocretin cells more than essential AAs ► AA presence prevents glucose from blocking orexin/hypocretin cells

 Effects of Physiological Amino Acid Mixes on the Membrane Potential of orx/hcrt and Other Central Neurons

(A) Effect of “AA mix” (see Table S1) on orx/hcrt cells (n = 25). Membrane potential during AA application (−39.4 ± 0.8 mV) was higher than preapplication (−51.8 ± 0.6 mV, p < 0.0001) or postapplication (−51.0 ± 1.1 mV, p < 0.0001).

(B) Same with synaptic blockers (see Experimental Procedures, n = 5). Membrane potential during AA application (−40.1 ± 1.1 mV) was depolarized relative to preapplication (−50.4 ± 0.5 mV, p < 0.002) or postapplication (−48.0 ± 1.6 mV, p < 0.02).

(C) Same as A with tetrodotoxin (0.5 μM, n = 5). Membrane potential during AA application (−42.2 ± 1.4 mV) was higher than preapplication (−53.5 ± 0.8 mV, p < 0.002) or postapplication (−51.2 ± 1.0 mV, p < 0.001).

(D) Effect of “AA mix” on non-orx/hcrt lateral hypothalamic neurons expressing GAD65 (n = 7, see Experimental Procedures). Membrane potential during AA application (−46.6 ± 1.2 mV) was not different from preapplication (−48.8 ± 1.0 mV, p > 0.15) or postapplication (−47.5 ± 1.7 mV, p > 0.6).

(E) Effect of “AA mix” on neurons from secondary somatosensory cortex layer 2-4 (n = 7). Membrane potential during AA application (−49.1 ± 0.8 mV) was not different from preapplication (−49.6 ± 0.6 mV, p > 0.3) or postapplication (−48.8 ± 1.1 mV, p > 0.8).

(F) Depolarization (means ± SEM) caused by the AA mix in different conditions, evoked from the same baseline of −50 mV (∗∗∗ = p < 0.001; n.s. = p = 0.24).

(G) Left, effect of switching from “low AA mix” to “AA mix” (see Table S1) on orx/hcrt cells (n = 6, quantified in F). Right, dose-response (means ± SEM) of AA-induced depolarization. Total concentration of AA mix was changed while proportions of AAs were kept same as in “AA mix” in Table S1. EC50 value (see Experimental Procedures) = 438.2 μM (equivalent to 0.66-fold of “AA mix” in Table S1).

(H) Effects of AAs in cell-attached recording mode (left, frequency histogram; right, raw trace, n = 6). Firing rate was higher in AA (6.6 ± 0.5 Hz) than in low AA (3.0 ± 0.3 Hz, p < 0.001).

Effects of Individual Amino Acids

To explore whether orx/hcrt cells are more sensitive to particular AAs, we first examined their membrane current responses to individual AAs applied at high concentration (5 mM). In this voltage-clamp assay, nonessential AAs elicited large responses, with a relative potency order glycine > aspartate > cysteine > alanine > serine > asparagine > proline > glutamine, while essential AAs were much less effective (Figures 3A and 3B). Because leucine has been suggested previously to be sensed in the hypothalamus (Cota et al., 2006), we investigated its effect across a broad concentration range in comparison with alanine (Figure 3C). Across all concentrations tested, leucine (0.02–10 mM) did not induce any detectable membrane currents, whereas alanine dose-dependently stimulated currents with an EC50 of 3.19 mM (Figure 3C).

Source: http://www.sciencedirect.com/science/article/pii/S0896627311007823

Amino acid Alanine food sources: Good sources of alanine include. Animal sources: meat, seafood, caseinate, dairy products, eggs, fish, gelatin, lactalbumin. Vegetarian sources: beans, nuts, seeds, soy, whey, brewer’s yeast, brown rice, bran, corn, legumes, whole grains.