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Keywords:

  • alcohol drinking;
  • dopamine;
  • GABA;
  • neurotransmitter turnover rates;
  • norepinephrine;
  • serotonin

Abstract

  1. Top of page
  2. Abstract
  3. Experimental procedures
  4. Results
  5. Discussion
  6. Conclusions
  7. Acknowledgements
  8. References

This research was initiated to assess the turnover rates (TORs) of dopamine (DA), norepinephrine (NA), serotonin (5-HT), aspartate, glutamate, and GABA in brain regions during rodent ethanol/sucrose (EtOH) and sucrose (SUC) drinking and in animals with a history of EtOH or SUC drinking to further characterize the neuronal systems that underlie compulsive consumption. Groups of five male rats were used, with two trained to drink EtOH solutions, two to drink SUC and one to serve as a non-drinking control. When stable drinking patterns were obtained, rats were pulse labeled intravenously and killed 60 or 90 min later and the TORs of DA, norepinephrine, 5-HT, aspartate, glutamate, and GABA determined in brain regions. Changes in the TOR of 5-HT, DA, and NA were detected specific to EtOH drinking, SUC drinking or a history of EtOH or SUC drinking. An acute EtOH deprivation effect was detected that was mostly reversed with EtOH drinking. These results suggest that binge-like drinking of moderate amounts of EtOH produces a deficit in neuronal function that could set the stage for the alleviation of anhedonic stimuli with further EtOH intake that strengthen EtOH seeking behaviors which may contribute to increased EtOH use in at risk individuals.

Abbreviations used
5-HIAA

5-hydroxyindole acetic acid

5-HT

serotonin

aCC

anterior cingulate cortex

AMYG

amygdala

Asp

aspartate

ATC

auditory temporal cortex

BS

brainstem

COL

colliculi

CP

caudate nucleus putamen

DA

dopamine

DB-PO

diagonal band of Broca-pre-optic area

DOPAC

dihydroxyphenyl acetic acid

DRN

dorsal raphe nuclei

E-SC

entorhinal subicular cortex

EtOH

ethanol

Glu

glutamate

GP

globus pallidus

HIPP

hippocampus

lHYP

lateral hypothalamus

lTH

lateral thalamus

MC

motor cortex

mHYP

medial hypothalamus

mTH

medial thalamus

NAc

nucleus accumbens

NE

norepinephrine

OT

olfactory tubercle

pCC

posterior cingulate cortex

PFC

prefrontal cortex

PYC

pyriform cortex

SEP

septum

SN

substantia nigra

SSC

somatosensory cortex

SUC

sucrose

TOR

turnover rate

VC

visual cortex

VP-ST

ventral pallidum-stria terminalis

VTA

ventral tegmental area

Alcohol abuse and alcoholism is a biopsychosocial disorder that has complex neurobiological substrates. A vigorous research program over the last two decades has resulted in significant progress toward understanding the basic mechanisms underlying the effects of ethanol (EtOH) on the brain and the resulting behavioral changes. These findings have led to an understanding of the actions of EtOH on specific neuronal systems – NMDA, glutamatergic, GABAA, μ and δ opioid, and serotonergic and dopaminergic neurons. Although these neuronal systems are significantly impacted by EtOH, their role in the control of EtOH intake is not clearly defined. This research project was initiated to further characterize the neuronal systems that underlie the compulsive intake of EtOH by simultaneously assessing the turnover rates (TORs) of dopamine (DA), norepinephrine (NE), serotonin (5-HT), aspartate (Asp), glutamate (Glu), and GABA in small brain regions as a measure of neuronal activity during rodent EtOH/sucrose (EtOH) and sucrose (SUC) consumption and in animals with a history of such consumption.

It is generally believed that chemical substances subject to abuse activate neuronal systems that are responsible for the mediation of the hedonic properties for naturalistic reinforcers that evolved through natural selection prior to the exposure of the ancestors of Homosapiens to many of the chemical stimuli currently present in the environment. A number of hypotheses have been set forth over the last 40 years that have attempted to define the neurobiological mechanisms underlying hedonic processes. The most current and widely accepted hypothesis evolved from studies of psychostimulants or of direct intracranial electrical brain self-stimulation and concluded that increased activity in mesolimbic and mesocortical dopaminergic neurons was responsible for positive hedonic perceptions (Wise 1978). Although data is not in total agreement, dopaminergic neurons appear to participate in the neuronal processes underlying the reinforcing properties of EtOH (Koob et al. 1998; McBride and Li 1998). However, the neuronal circuits underlying drug reinforcement appear to be complex networks that involve interactions of multiple neuronal systems (Smith and Lane 1983; Koob 1992; Koob et al. 1998).

A number of methods have been developed to assess the involvement of pre-and post-synaptic neuronal activity for subsets of identified neurons in brain function. These have included in situ autoradiography to identify changes in receptor densities (Lodge and Lawrence 2003; Beadles-Bohling and Wiren 2005; Short et al. 2006), in situ hybridization (Chen et al. 1998; Beadles-Bohling and Wiren 2005; Short et al. 2006) and immunohistochemistry (Bachtell et al. 2004) to identify densities of specific proteins, microdialysis (Doyon et al. 2004) and in vivo voltametry (Budygin et al. 2001; Jones et al. 2006) to identify extracellular fluid levels of neurohumors, 2-deoxyglucose autoradiography to identify cell groups showing changes in glucose metabolism (Eckardt et al. 1992; Porrino et al. 1998), c-Fos expression to identify cell groups having immediate early gene activation (Ryabinin et al. 2003; Wedzony et al. 2003) and neurotransmitter TOR procedures to identify changes in the activity of discrete subsets of cell groups by measuring the dynamics of the functional pool of neurotransmitters (Milio and Hadfield 1992; Bailey et al. 2000; Smith et al. 2003). This latter technology was chosen for the present study.

Brain neurotransmitters exist in multiple pools with a functional pool, often only a small portion of the total, which likely meets response demands that are within normal physiological limits, while extraordinary demands result in the utilization of additional more firmly bound pools. This circumstance has provided significant challenges for investigation of the role of pre-synaptic processes of specific neurotransmitter systems in behaviors that primarily involve utilization of the functional pool. Neurotransmitter TOR measures were developed as a mechanism for investigating the role of the functional pool as an index of pre-synaptic neuronal activity. This has become even more challenging since recent data showing that the less labor intensive TOR measurement procedure using metabolite/neurotransmitter ratios appears to be inaccurate and apparently represents only changes in the concentration of the metabolites (Smith et al. 2003). The experiment described here used radioactive pulse labeling techniques to measure the TORs of DA, NE, 5-HT, GABA, Glu, and Asp in small brain regions of rats drinking EtOH to assess the role of neurons releasing these neurotransmitters in the processes that underlie this behavior. In addition, the TORs of DA and 5-HT were also calculated using metabolite/neurotransmitter content ratios to further evaluate the concordance of TORs calculated by these two methods.

Experimental procedures

  1. Top of page
  2. Abstract
  3. Experimental procedures
  4. Results
  5. Discussion
  6. Conclusions
  7. Acknowledgements
  8. References

Animals

Sixty-five adult male Wistar 90- to 150-day-old rats (Harlan, Indianapolis, IN, USA) were used in groups of five. Each group was housed in a temperature controlled environment with unlimited access to food and water on a reversed 12 h light–dark cycle (lights on 17:00 to 05:00). Experiments were conducted during the dark cycle and in accordance with the National Institutes of Health Guide for the Care and Use of Laboratory Animals (NIH Publication No. 80–23) revised in 1996 and approved by the Wake Forest University Health Sciences Animal Care and Use Committee.

Ethanol/SUC and SUC drinking

In each group of five rats, two were trained to drink EtOH/SUC solutions, two to drink SUC and one did not drink any solution. Rats were placed in metabolic chambers with drinking solutions in graduated drinking tubes (except for the non-drinking control) for determination of the amount of solution taken during the 90 min session. The four rats drinking in each group started with a 10% SUC solution which was gradually decreased to 5%. Two percentage EtOH was introduced to the two animals in each group drinking EtOH/SUC during the 10% SUC phase and gradually increased to a final solution of 10% EtOH/5% SUC. The doses for these two rats in each group were: [(%EtOH/% SUC) 0/10, 2/10, 5/10, 5/5, and final solution 10/5; volume/volume]. The same SUC dose changes were made for the two rats in each group drinking SUC only. The drinking sessions were 90 min in duration 5 days per week with the volumes of solutions recorded 15, 30, and 60 min after the animals were placed in the chamber and an additional final volume at the end of the 90 min session. The rats had total access to water in the home cage and were not water deprived during these drinking sessions. After stable EtOH/SUC drinking was obtained, each group of five animals was implanted with intravenous catheters for pulse labeling.

Surgical techniques

Rats were anesthetized with pentobarbital (50 mg/kg, i.p.; Abbott Laboratories, North Chicago, IL, USA) after pre-treatment with atropine methyl nitrate (10 mg/kg, i.p.; Sigma, St. Louis, MO, USA) and Penicillin G procaine (75 000 U, i.m.; Wyeth Laboratories, Philadelphia, PA, USA) and implanted with venous catheters placed in the right jugular vein using previously described methods (Weeks 1962, 1972; Pickens and Dougherty 1972). The catheter (a small piece of polyvinyl-chloride tubing) was inserted into the right posterior facial vein, guided into the right jugular vein until it terminated just outside the right atrium and anchored to muscle in the area of the vein. The other end of the catheter continued subcutaneously to the back where it exited between the scapulae through a polyethylene shoulder harness. The harness provided a point of attachment for an aluminum backpack to prevent damage to the catheter. The catheters were flushed weekly and the patency checked periodically by delivering an intravenous infusion of methohexital (10 mg/kg; Eli Lilly, Indianapolis, IN, USA) and determining latency for loss of stability or consciousness which occurs within 1–2 s. Catheter patency was checked the day before the pulse label session.

Pulse label procedure

When stable EtOH/SUC intake was again obtained after catheter implantation, each group of five rats was pulse labeled with radioactive precursors for the biogenic monoamine and amino acid putative neurotransmitters immediately before the drinking session. On the pulse label, one of the EtOH/SUC and SUC drinking rats per group were exposed to the drinking session while the other two remained in their home cages as drinking history controls. Fifty microliters of saline containing 0.4 mCi of d-glucose [U-14C] (specific activity 251 mCi per mmol; I.C.N., Irvine, CA, USA), 1.0 mCi of l-[G-3H] tryptophan (specific activity 39.4 Ci per mmol; Amersham, Arlington Heights, IL, USA), and 2.0 mCi l-[2,3,5,6-3H-tyrosine (specific activity 110 Ci per mmol; Amersham) were administered 60 (n = 7 groups of five) or 90 (n = 6 groups of five) minutes prior to killing through the jugular catheters. These time points were chosen since they have been demonstrated to be on the log-linear portion of the decay in radioactivity curve for DA, NE, 5-HT (Co et al. 1982), Asp, Glu, and GABA (Freeman et al. 1983) which is necessary for determining rate constants and TOR values.

Tissue preparation

Rats were immediately killed by immersion in liquid nitrogen until totally frozen (7 min) at 60 and 90 min into the session. The heads were separated and allowed to warm to −20°C and the brains removed. Trunk blood was collected from the EtOH/SUC drinking group and stored at −80°C for blood alcohol level determination. The brains were sectioned in the coronal plane in a cryostat at −18°C into 750-μm serial sections. The brain sections were microdissected with the aid of a stereomicroscope into 26 areas of interest [prefrontal cortex (PFC), pyriform cortex (PYC), motor cortex (MC), somatosensory cortex (SSC), anterior cingulate cortex (aCC), posterior cingulate cortex (pCC), entorhinal subicular cortex (E-SC), visual cortex (VC) and auditory temporal cortex (ATC), olfactory tubercle (OT), nucleus accumbens (NAc), caudate nucleus putamen (CP), diagonal band of Broca-pre-optic area (DB-PO), ventral pallidum-stria terminalis (VP-ST), amygdala (AMYG), septum (SEP), globus pallidus (GP), hippocampus (HIPP), substantia nigra (SN), ventral tegmental area (VTA), medial hypothalamus (mHYP), lateral hypothalamus (lHYP), medial thalamus (mTH), lateral thalamus (lTH), colliculi (COL), and the remaining brainstem (BS)] and the samples stored at −80°C until analyzed. The frozen tissue samples were individually pulverized at −20°C in liquid nitrogen with a stainless steel mortar cooled on dry ice. Frozen tissue powder from each sample was transferred to two tubes, one for extraction of the biogenic monoamines and the other for extraction of the amino acids. As the VTA had less than 20 mg of tissue only the amino acids were assessed.

Neurochemical procedures

Biogenic monoamines

Biogenic monoamines and metabolites were extracted from 15 to 50 mg of pulverized tissue powder with 0.4 mL ice-cold 1 N formic acid/acetone (v/v: 15/85) and lipids removed with a heptane/chloroform wash (v/v: 8/1). 3,4-dihydroxybenzylamine was added to the tissue powder/extraction buffer slurry for each sample as an internal standard to correct for recovery. The aqueous layer was taken to dryness under N2 and stored at −20°C until analyzed. The content and specific radioactivity of DA, NE, and 5-HT were concurrently measured with HPLC with electrochemical detection and the peaks collected and radioactivity determined with liquid scintillation spectrometry using a previously reported procedure (Co et al. 1982; Smith et al. 2003). The content of metabolites [dihydroxyphenyl acetic acid (DOPAC), 5-hydroxyindole acetic acid (5-HIAA), and homovanillic acid] was also measured.

The samples were reconstituted in the mobile phase [0.05 M citrate-phosphate, pH 3.7, containing 0.4 mM sodium octylsulfate (Fisher Scientific, Atlanta, GA, USA) and 10% methanol] and injected into a C18 reverse phase column (0.46 × 25 cm, 5 μm, Grace's Corp. Columbia, MD, USA). The biogenic monoamines and metabolites were eluted over 20 min with the isocratic mobile phase at a 1.0 mL/min flow rate. Retention times in minutes were: NE 4.7; 3,4-dihydroxybenzylamine 6.6; DOPAC 7.0; DA 9.3; 5-HIAA 10.0; homovanillic acid 16.7; and 5-HT 20.2. Individual peaks for DA, NE, and 5-HT were collected and radioactivity determined using liquid scintillation spectrometer. Proteins were measured in the pellets (Lowry et al. 1951) and the content (pmol/mg protein) of the biogenic monoamines determined from internal standards after correction for recovery and the specific radioactivity (dpm/pmol) calculated for each sample.

Amino acids

The amino acid neurotransmitters were assayed for content and specific radioactivity using a modification (Smith et al. 2003) of a previously reported procedure (Jones and Gilligan 1983) with HPLC and fluorescence detection. Amino acids were extracted from 10 to 15 mg of frozen tissue powder with 0.4 mL 4°C methanol and homoserine added as an internal standard. The extracts were dried at 37°C under a stream of dry nitrogen and stored at −20°C until assay. The samples were reconstituted in methanol and reacted with O-pthaldialdehyde reagent (100 mg O-pthaldialdehyde in 0.5 mL methanol and 100 μL 2-mercaptoethanol in 1.9 mL of 0.4 M borate, pH 9.5) for 2 min and injected into a gradient HPLC system (Gilson Model 201, Gilson, Middleton, WI, USA) using an auto injector (Gilson 401 and 231). A C18 reversed phase column (0.46 × 15 cm, 5 μm) was used with fluorometric detection (Gilson 121) (excitation 305–395 nm and emission 430–470 nm). The mobile phase was 0.1 M sodium acetate, pH 6.2, containing 0.1 mM EDTA and increasing concentrations of methanol (15–50%) with a 1.3 mL/min flow rate. Retention times in minutes were: Asp 2.4, Glu 4.0, and GABA 20.4. Individual amino acid peaks were collected with a fraction collector (Gilson Model 202 with controller) and the radioactivity in each determined with liquid scintillation spectrometry. Proteins were measured in the pellets (Lowry et al. 1951), content (nmol/mg protein) determined from the internal standards after correction for recovery and the specific radioactivity (dpm/nmol) calculated for each sample.

Turnover rate calculation

Radioactive pulse label procedure

Turnover rates were determined with previously reported methods (Co et al. 1982; Smith et al. 1982, 2003; Freeman et al. 1983) with the assumption that radiolabel was disappearing from a single open pool (Zilversmit 1960), as there is no acceptable method for determining CNS intraneuronal compartmentation in vivo. Turnover rates = k × content, where the apparent fractional rate constant (k) was calculated as: k = ln2/t½ and the t½ was extrapolated from a semi-logarithmic plot of the specific radioactivities (dpm/pmol or dpm/nmol) obtained at the two pulse times on the linear portion of the decay in the radioactivity curve for each neurotransmitter. The apparent fractional rate constants and TORs were determined by comparing each animal at the 60 min pulse time with all six animals at the 90 min pulse time. A mean of these measures was calculated and used to represent one turnover measure. Thus, for each of the seven animals in each of the five treatment conditions at the short pulse time, up to seven TORs were calculated and these values for each of the five treatment conditions were then used to determine significance of differences in TORs. This procedure was used to obtain an accurate error estimate that would represent both the variation in content measurements as well as in specific radioactivities. The TOR was expressed as pmol/mg protein/h (DA, NE, and 5-HT) or nmol/mg protein/h (Asp, Glu, and GABA) and was the product of each rate constant (per hour) and each content value (pmol/mg protein or nmol/mg protein). If negative values resulted when the specific radioactivity at the short pulse point was lower than the long pulse point, then these values were not included in the calculations. This occurred most often in brain regions where the particular neurotransmitter had low content which resulted in greater variation in the specific radioactivity or in regions where there was low turnover so that specific radioactivities were similar at the two pulse times (70 out of 2625 specific radioactivities or for 2.7% of the values).

Metabolite – neurotransmitter content ratios procedure

Turnover rates for DA and 5-HT were also calculated from DOPAC/DA and 5-HIAA/5-HT ratios for direct comparisons with the pulse label technique as these are often used as a measure of the turnover of these two neurotransmitters (Frink et al. 1996; Takeo et al. 1997; Bailey et al. 2000).

Blood EtOH measurement

Blood EtOH levels were quantified using an ethanol assay kit (Diagnostic Chemicals Ltd., Charlottetown, PE, Canada).

Statistical analysis

The individual TORs calculated as outlined above were tested for significance of differences with a two-way anova (solution × drinking) to identify TORs that were altered by EtOH/SUC or SUC or by the opportunity to drink on the pulse label day. This was followed by pre-planned post hoc analysis of differences between mean using Bonferroni t-tests for multiple comparisons. The significance of differences between mean included comparison of the EtOH/SUC drinking with the SUC drinking animals (designated as the EtOH drinking effect) (see Table 1). The SUC drinking was compared with the SUC drinking history control (designated as the SUC drinking effect). The EtOH drinking history rats were compared with the SUC drinking history rats (designated as the acute EtOH deprivation effect). The effects of a history of SUC drinking (SUC drinking history control compared with the non-drinking control) was analyzed separately using a one-way anova followed by pre-planned post hoc analysis of differences between mean using Bonferroni t-tests. The reversal of the acute EtOH deprivation effect was assessed by comparing the EtOH drinking rats with the EtOH drinking history group.

Table 1.   Dopamine, norepinephrine, serotonin, aspartate, glutamate, and GABA content in brain regions of rats drinking ethanol/sucrose and sucrose and ethanol or sucrose drinking history and non-drinking controls
AreaDrinkingContent (pmol/mg protein)Content (nmol/mg protein)
SerotoninDopamineNorepinephrineGlutamateGABAAspartate
  1. The grand mean and standard error for all conditions are presented when there were no significant changes between treatments. In brain regions where significant changes were identified a grand mean ± error values is presented on the top line with the mean ± error values for the conditions with significant changes below. EtOH, ethanol drinking; EtOH hist, ethanol drinking history; SUC, sucrose drinking; SUC hist, sucrose drinking history. Values are mean ± SEM. Symbols used represent the following significant comparisons: aSucrose drinking versus EtOH drinking; bEtOH drinking history versus EtOH drinking; cSucrose drinking history versus sucrose drinking; dSucrose drinking history versus EtOH drinking history; eSucrose drinking history versus control. Significance of differences are *< 0.05; < 0.01; < 0.001.

Prefrontal cortex 40.88 ± 1.038.46 ± 0.4228.92 ± 0.6289.32 ± 2.3122.56 ± 0.8317.26 ± 0.61
Olfactory tubercle 46.37 ± 0.99210.35 ± 7.0623.61 ± 0.51119.45 ± 2.7344.61 ± 0.8923.36 ± 0.51
EtOH40.79 ± 2.70    
Sucrose49.89 ± 1.95a,†  114.32 ± 6.25  
EtOH hist48.08 ± 1.64b,*  113.41 ± 4.55d,*  
Suc hist  134.11 ± 5.44c,*  
Control  109.34 ± 5.75e,*  
Pyriform cortex 37.01 ± 0.7020.49 ± 1.3748.50 ± 2.17194.56 ± 2.6446.65 ± 1.1733.83 ± 0.70
EtOH32.10 ± 1.15     
Sucrose39.38 ± 1.89a,†     
EtOH hist37.73 ± 1.54b,*     
Nucleus accumbens 29.40 ± 0.68548.93 ± 8.4218.71 ± 0.78153.44 ± 4.4045.75 ± 1.5124.57 ± 0.64
Motor cortex 14.70 ± 0.3410.53 ± 0.6036.37 ± 0.89120.58 ± 1.6620.82 ± 0.5121.30 ± 0.41
EtOH   127.23 ± 3.35  
EtOH hist   113.42 ± 2.77a,*  
Somatosensory cortex 20.91 ± 0.4110.63 ± 0.5338.67 ± 0.99178.36 ± 2.3344.48 ± 0.8133.95 ± 0.52
Caudate–putamen 36.02 ± 0.80763.91 ± 15.569.44 ± 0.46132.12 ± 3.5553.63 ± 1.6920.20 ± 0.62
Anterior cingulate cortex 20.28 ± 0.4413.39 ± 0.6023.44 ± 1.00102.44 ± 1.0616.49 ± 0.2817.21 ± 0.17
EtOH   105.61 ± 2.53  
Sucrose   98.25 ± 1.95a,*  
Septum 35.62 ± 1.0475.28 ± 3.2549.80 ± 4.29116.79 ± 1.5661.89 ± 1.1627.30 ± 0.44
Diagonal band pre-optic 61.33 ± 1.28103.45 ± 5.05101.43 ± 1.8782.09 ± 0.8869.28 ± 1.2020.83 ± 0.32
Ventral pallidum stria terminalis 57.77 ± 1.48166.58 ± 9.45114.34 ± 2.71118.37 ± 4.61140.74 ± 6.1828.99 ± 1.07
Globus pallidus 31.08 ± 0.9920.14 ± 1.1459.02 ± 2.8874.63 ± 1.25109.36 ± 2.8120.45 ± 0.43
EtOH   80.51 ± 1.73  
Sucrose   66.67 ± 3.03a,‡  
EtOH hist   70.39 ± 1.74b,d,*,†  
Suc hist   77.36 ± 2.91c,†  
Amygdala 73.43 ± 1.8237.80 ± 1.3480.20 ± 4.09131.31 ± 2.4357.15 ± 1.3722.93 ± 0.56
EtOH  63.35 ± 5.72   
EtOH hist  96.60 ± 10.83b,†   
Hippocampus 25.70 ± 0.474.60 ± 0.3056.77 ± 2.00159.97 ± 1.7844.03 ± 0.7120.33 ± 0.29
Medial thalamus 37.91 ± 0.824.55 ± 0.1163.32 ± 2.4498.58 ± 0.9528.80 ± 0.5719.22 ± 0.26
Lateral thalamus 35.18 ± 1.156.21 ± 0.2454.99 ± 2.03112.32 ± 1.3431.74 ± 0.6621.00 ± 0.35
Medial hypothalamus 54.22 ± 0.8819.85 ± 0.41154.19 ± 2.70101.91 ± 1.2789.19 ± 1.7326.53 ± 0.46
EtOH48.63 ± 2.09     
Sucrose56.36 ± 1.24a,†     
EtOH hist59.37 ± 1.51b,‡     
Suc hist54.20 ± 1.63d,*     
Lateral hypothalamus 65.49 ± 1.0025.43 ± 0.67108.34 ± 1.9382.65 ± 1.0581.30 ± 1.9221.11 ± 0.39
Sucrose  106.85 ± 3.30c,*   
EtOH hist  101.97 ± 2.89d,†   
Suc hist  119.00 ± 4.50    
Posterior cingulate cortex 15.30 ± 0.441.99 ± 0.1953.13 ± 2.77112.82 ± 2.7420.37 ± 0.5327.63 ± 0.70
Entorhinal subicular cortex 29.25 ± 0.561.84 ± 0.0732.68 ± 0.76202.58 ± 6.7550.70 ± 1.9934.54 ± 1.01
Substantia nigra 57.34 ± 0.8939.91 ± 0.9942.84 ± 1.6068.95 ± 1.21117.28 ± 2.9221.37 ± 0.35
Ventral tegmental area 98.50 ± 1.1472.98 ± 1.6027.24 ± 0.53
Brainstem 31.57 ± 0.556.22 ± 0.2533.08 ± 0.5875.51 ± 0.7842.50 ± 1.0820.58 ± 0.33
EtOH29.26 ± 0.96     
Sucrose33.19 ± 1.14a,*     
EtOH hist32.90 ± 1.68b,*     
Visual cortex 15.73 ± 0.410.60 ± 0.0228.12 ± 0.90174.33 ± 3.5635.55 ± 0.9127.25 ± 0.62
Auditory temporal cortex 14.94 ± 0.301.17 ± 0.0416.84 ± 0.58144.83 ± 2.2724.07 ± 0.6127.15 ± 0.57
Colliculi 38.57 ± 0.773.76 ± 0.0722.02 ± 0.4588.14 ± 0.8357.94 ± 0.8023.42 ± 0.36

Results

  1. Top of page
  2. Abstract
  3. Experimental procedures
  4. Results
  5. Discussion
  6. Conclusions
  7. Acknowledgements
  8. References

EtOH drinking

Animals acquired EtOH drinking within the first five sessions. The number of sessions of exposure prior to pulse labeling was 50.3 ± 8.8 days for all groups (all values presented are mean ± standard deviations unless otherwise specified). The average EtOH intake for the EtOH drinking rats in the 13 groups for the 10 sessions prior to the pulse labeling was 1.04 g/kg ± 0.2 per session while the average intake for the EtOH drinking history group was 1.00 ± 0.16 g/kg per session. The amount of EtOH intake during the pulse label interval did not differ for the two different pulse times [60 min (1.12 ± 0.25 g/kg) or 90 min (1.11 ± 0.33 g/kg)] and the total average EtOH consumed in the last 10 days prior to pulse labeling did not differ between the two groups from the two pulse intervals [60 min (1.13 ± 0.16 g/kg) and 90 min (1.04 ± 0.26 g/kg)]. The bulk of EtOH drinking occurred in the first 30 min (93% of session intake) with less than 7% occurring in the 30–90 min segment (Fig. 1). The blood EtOH levels assessed on the pulse label day following the death of the animals were 15.7 ± 4.97 mg/100 mL in the 60 min pulse group and 2.32 ± 1.97 mg/100 mL for the 90 min pulse group.

image

Figure 1.  Average intake of ethanol/sucrose and sucrose for the last 10 sessions assessed at 15, 30, 60, and 90 min after the initiation of 90 min drinking sessions in the ethanol/sucrose (EtOH) and sucrose drinking and drinking history for the 60 and 90 min pulse label groups. Values are mean and error bars ± one standard error of the mean for n = 6 or 7 per group. The patterns of intake were not significantly different for any of the groups.

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In addition, the EtOH intake between the EtOH drinking and EtOH history controls did not differ 10 days prior to pulse labeling (0.93 ± 0.13 g/kg for the latter group) nor did it differ between the 60 and 90 min pulse EtOH history subgroups (0.95 ± 0.18 g/kg, 60 min pulse and 0.91 ± 0.07 g/kg, 90 min pulse).

Sucrose drinking

The pattern of SUC drinking was similar to that of the EtOH drinking group. The average total SUC intake for the SUC drinking rats in the 13 groups for the last 10 days prior to the pulse labeling sessions were 1.58 ± 0.49 g/kg per session which is about 54% more SUC than that consumed by the EtOH drinking group. The amount of SUC intake during the pulse label interval did not differ for the two groups [60 min (1.67 ± 0.37 g/kg) or 90 min (1.48 ± 0.63 g/kg)] and the intake did not differ between the groups during the two pulse label sessions [60 min (1.5 ± 0.3 g/kg) and 90 min (1.79 ± 0.88 g/kg)]. The bulk of SUC drinking also occurred in the first 30 min (77% of session intake) with 23% occurring in the 30–90 min segment (Fig. 1).

Similar to the EtOH and EtOH history groups, the SUC and SUC history groups did not differ in the amount of SUC intake for the last 10 days prior to pulse labeling (1.89 ± 0.91 g/kg for the latter). The intake for the 60 and 90 min SUC history pulse subgroups also did not differ in the 10 days prior to labeling (2.16 ± 0.78 g/kg for the 60 min and 1.58 ± 1.02 for the 90 min).

Neurotransmitter content

Neurotransmitter content was differentially distributed throughout the brain as previously demonstrated. The content values were very similar to those recently reported in cocaine self-administering Fischer 344 rats (Smith et al. 2003). The two-way anova and pre-planned post hoc analysis of differences between mean using Bonferroni t-tests for multiple comparisons found 20 significant changes in content that included nine in 5-HT, nine in Glu, one in NE and Asp, and no changes in DA or GABA (Table 1). The significant differences in the content of 5-HT included an EtOH drinking effect with decreases in the OT, PYC, mHYP, and BS, an EtOH drinking history effect with an increase in the mHYP and an increase in the NAc resulting from a SUC drinking history effect. NE content was decreased in the AMYG in the EtOH drinking rats compared with the EtOH drinking history group. The significant change in Glu content included increases in the MC, aCC, and GP resulting from an EtOH drinking effect, decreases in the OT and GP from a SUC drinking effect, decreases in the OT and GP from an EtOH drinking history effect, an increase in the OT from a SUC drinking history effect and an increase in the GP of the EtOH drinking rats compared with the EtOH drinking history group. A decrease in Asp was also detected in the ATC resulting from a history of SUC drinking. In addition, there were no changes in the content of DOPAC or 5-HIAA in any brain region in any of the groups (see Table 2).

Table 2.   DOPAC, 5-HIAA content, and DOPAC/DA and 5-HIAA/5-HT ratios in brain regions of rats drinking ethanol/sucrose and sucrose, ethanol or sucrose drinking history and non-drinking controls
AreaDrinkingDOPAC content (pmol/mg protein) DOPAC : DA5-HIAA content (pmol/mg protein)5-HT content (pmol/mg protein) 5-HIAA : 5-HT
  1. The grand mean and standard error for all conditions are presented when there were no significant changes between treatments. In brain regions where significant changes were identified a grand mean ± error values is presented on the top line with the mean ± error values for the conditions with significant changes below. Significant changes in ratios were only detected between the ethanol/sucrose drinking and the ethanol/sucrose drinking history control groups. Values are mean ± SEM. Significance of difference: *< 0.05; p < 0.01. EtOH, ethanol drinking; EtOH hist, ethanol drinking history; DOPAC, dihydroxyphenyl acetic acid; 5-HIAA, 5-hydroxyindole acetic acid; 5-HT, serotonin; DA, dopamine.

Prefrontal cortex 2.16 ± 0.080.27 ± 0.0147.62 ± 1.3740.88 ± 1.031.22 ± 0.06
EtOH  49.65 ± 2.8438.19 ± 2.011.33 ± 0.07
EtOH hist  49.23 ± 1.9446.64 ± 1.361.07 ± 0.05*
Olfactory tubercle 28.11 ± 1.130.13 ± 0.0046.42 ± 1.0546.37 ± 0.991.01 ± 0.02
EtOH  45.03 ± 3.2140.79 ± 2.701.11 ± 0.06
EtOH hist  43.71 ± 2.3848.08 ± 1.64*0.91 ± 0.04*
Pyriform cortex 5.09 ± 0.240.32 ± 0.0152.28 ± 1.2337.01 ± 0.701.43 ± 0.03
EtOH  50.40 ± 3.2032.11 ± 1.151.58 ± 0.11
EtOH hist  47.96 ± 1.9437.73 ± 1.541.28 ± 0.04*
Nucleus accumbens 89.04 ± 2.080.16 ± 0.0043.81 ± 1.1029.40 ± 0.681.51 ± 0.04
Motor cortex 3.61 ± 0.100.40 ± 0.0223.99 ± 0.7014.70 ± 0.341.64 ± 0.04
EtOH  23.72 ± 2.3613.16 ± 0.971.79 ± 0.10
EtOH hist  20.86 ± 1.1114.28 ± 0.471.47 ± 0.08*
Somatosensory cortex 4.47 ± 0.110.47 ± 0.0233.43 ± 0.6520.91 ± 0.411.63 ± 0.04
EtOH  33.92 ± 1.5618.54 ± 0.661.85 ± 0.10
EtOH hist  31.57 ± 1.1921.13 ± 0.851.51 ± 0.06*
Caudate–putamen 148.12 ± 3.860.20 ± 0.0167.10 ± 1.3536.02 ± 0.801.88 ± 0.03
Anterior cingulate cortex 4.13 ± 0.150.32 ± 0.0230.28 ± 0.6320.28 ± 0.441.51 ± 0.03
Septum 20.30 ± 0.760.29 ± 0.0138.57 ± 1.2635.62 ± 1.041.09 ± 0.03
Diagonal band Pre-Optic 21.60 ± 0.920.21 ± 0.0163.61 ± 1.4761.33 ± 1.281.05 ± 0.02
EtOH  64.71 ± 4.3455.90 ± 3.401.17 ± 0.05
EtOH hist  60.30 ± 3.9063.24 ± 3.200.97 ± 0.06*
Ventral pallidum stria terminalis 30.16 ± 1.330.20 ± 0.0168.85 ± 1.6957.77 ± 1.481.19 ± 0.02
Globus pallidus 12.31 ± 0.340.69 ± 0.0337.28 ± 1.3731.08 ± 0.991.22 ± 0.04
Amygdala 7.74 ± 0.300.22 ± 0.0272.99 ± 2.0073.43 ± 1.821.02 ± 0.04
Hippocampus 2.09 ± 0.140.43 ± 0.0253.41 ± 1.2225.70 ± 0.472.11 ± 0.05
Medial thalamus 50.57 ± 1.2437.91 ± 0.821.35 ± 0.03
EtOH  49.33 ± 3.4532.28 ± 1.481.55 ± 0.11
EtOH hist  50.45 ± 3.4540.16 ± 1.66*1.25 ± 0.05*
Lateral thalamus 1.94 ± 0.150.35 ± 0.0463.50 ± 2.0635.18 ± 1.151.79 ± 0.04
Medial hypothalamus 5.84 ± 0.170.30 ± 0.0164.69 ± 1.3654.22 ± 0.881.21 ± 0.03
EtOH  66.70 ± 4.0848.63 ± 2.091.38 ± 0.08
EtOH hist  66.95 ± 2.7959.38 ± 1.51*1.13 ± 0.05*
Lateral hypothalamus 5.25 ± 0.170.21 ± 0.0197.63 ± 2.0765.49 ± 1.001.49 ± 0.03
Posterior cingulate cortex 18.47 ± 0.4815.30 ± 0.441.22 ± 0.04
Entorhinal subicular 0.56 ± 0.030.30 ± 0.0143.73 ± 0.9429.25 ± 0.561.52 ± 0.04
EtOH  47.47 ± 1.4327.57 ± 0.931.75 ± 0.09
EtOH hist  39.45 ± 1.5929.08 ± 1.121.37 ± 0.06*
Substantia nigra 12.05 ± 0.370.31 ± 0.0157.68 ± 1.2857.34 ± 0.891.00 ± 0.02
Brain stem 2.06 ± 0.060.35 ± 0.0156.17 ± 1.4231.57 ± 0.551.78 ± 0.04
Visual cortex 0.67 ± 0.041.22 ± 0.1025.99 ± 0.8215.73 ± 0.411.66 ± 0.04
EtOH  27.27 ± 1.6214.59 ± 0.891.89 ± 0.09
EtOH hist  22.83 ± 2.2115.66 ± 1.011.43 ± 0.09
Auditory temporal cortex 18.62 ± 0.4014.94 ± 0.301.26 ± 0.03
EtOH  20.08 ± 1.0514.09 ± 0.601.43 ± 0.06
EtOH hist  18.05 ± 0.7415.93 ± 0.701.15 ± 0.05
Colliculi 0.64 ± 0.030.17 ± 0.0142.19 ± 0.8938.57 ± 0.771.11 ± 0.02
EtOH  43.04 ± 2.7035.79 ± 1.781.21 ± 0.05
EtOH hist41.74 ± 2.0041.68 ± 1.251.01 ± 0.05*

The two-way anova also demonstrated several changes in content resulting from exposure to drinking the particular solution (EtOH vs. SUC including the history groups) or to the opportunity to drink (drinking on the pulse label day vs. the drinking history groups) (Table 3). The effects of the solution included decreases in those rats exposed to EtOH in 5-HT content in the MC and HIPP, in DA in the MC, CP, mTH, and lHYP, and increases in the content of Glu in the mTH and GABA in the aCC. The act of drinking showed the drinkers to have lower levels of 5-HT in the PFC, NAc, GP, HIPP, mTH, mHYP, lHYP, and COL, a decrease in NE in the PFC and increase in Asp in the lTH.

Table 3. F-values for two-way anova tests of significance of neurotransmitter content values
AreaNeurotransmitterSolutionDrinkingInteractions
  1. Solution: effects of drinking fluids on neurotransmitter tissue content values (sucrose vs. ethanol); Drinking: effects of drinking during pulse labeling on neurotransmitter content values (actively drinking vs. drinking history). 5-HT, serotonin; NE, norepinephrine; Glu, glutamate; DA, dopamine.

Prefrontal cortex5-HTF(1,48) = 4.92; p = 0.031
NEF(1,47) = 4.58; p = 0.038
Olfactory tubercle5-HTF(1,48) = 8.03; p = 0.007
GluF(1,47) = 8.13; p = 0.006
Pyriform cortex5-HTF(1,48) = 7.61; p = 0.008
Nucleus accumbens5-HTF(1,48) = 4.33; p = 0.043
Motor cortex5-HTF(1,48) = 7.90; p = 0.007
DAF(1,48) = 6.45; p = 0.014
GluF(1,48) = 5.55; p = 0.023
Caudate–putamen DAF(1,47) = 9.67; p = 0.003
Anterior cingulate cortexGluF(1,48) = 5.68; p = 0.021
GABAF(1,48) = 4.16; p = 0.047
Globus pallidus5-HTF(1,48) = 4.97; p = 0.030 
GluF(1,48) = 18.28; < 0.001
AmygdalaNEF(1,48) = 6.45; p = 0.014
Hippocampus5-HTF(1,48) = 5.24; p = 0.027F(1,48) = 5.23; p = 0.027
Medial thalamus5-HTF(1,48) = 15.33; < 0.001
DAF(1,48) = 7.25; p = 0.010
GluF(1,48) = 5.42; p = 0.024
Lateral thalamusAspF(1,48) = 5.11; p = 0.028
Medial hypothalamus5-HTF(1,48) = 6.80; p = 0.012F(1,48) = 15.32; < 0.001
Lateral hypothalamus5-HTF(1,48) = 4.96; p = 0.031
DAF(1,48) = 5.88; p = 0.019
NEF(1,47) = 5.91; p = 0.019
Brainstem5-HTF(1,48) = 4.23; p = 0.045
NEF(1,48) = 6.54; p = 0.014
Auditory temporal cortexGluF(1,47) = 7.32; p = 0.009
Colliculi5-HTF(1,48) = 5.48; p = 0.023

Neurotransmitter turnover rates

Pulse label procedure

The significant changes in neurotransmitter TORs were generally of four types: (i) those that were the result of EtOH drinking and seen in the EtOH drinking rats and not in the SUC drinking group (designated as the ‘EtOH drinking effect’); (ii) those that were the result from a history of EtOH drinking seen in the EtOH drinking history group but not in the SUC drinking history group (designated as the ‘acute EtOH deprivation effect’); (iii) those that were the result of SUC drinking and seen in the SUC drinking group but not in the SUC drinking history group (designated as the ‘SUC drinking effect’); and (iv) those resulting from a history of SUC drinking and seen in the SUC drinking history group but not in the non-drinking control group (designated as the ‘SUC drinking history effect’).

Serotonin

The two-way anova analysis demonstrated that EtOH consumption in most brain regions lowered the TOR of 5-HT, but in some regions it resulted in a significant increase in TOR. Some of these effects were from the act of drinking (when SUC drinking and EtOH drinking both went in the same direction). However, there were several regions where significant effects of EtOH drinking were not related to the act of drinking which is illustrated by significant interactions when EtOH drinking and SUC drinking did not parallel each other (Table 4). Regions where these interactions showed EtOH drinking to have a unique effect on 5-HT TOR included the NAc, VP-ST, GP, AMYG, HIPP, lTH, mHYP, SN, PYC, SSC, aCC, COL, and BS. Thus, in these 13 brain regions EtOH drinking affected the TOR uniquely which included both changes in the opposite direction than SUC drinking, or in the same direction that was significantly quantitatively different than with SUC drinking. In 12 regions, the effect was an elevation of turnover and one region a decrease (NAc). In these 13 regions, it is likely that EtOH drinking, rather than simply the act of drinking, caused the TOR of 5-HT to increase or decrease.

Table 4. F values for two-way anova tests of significance of neurotransmitter turnover rate values
AreaNeurotransmitterSolutionDrinkingInteractions
  1. Solution: effects of drinking fluids on neurotransmitter TORs (sucrose vs. ethanol); Drinking: effects of drinking during pulse labeling on neurotransmitter TORs (actively drinking vs. drinking history). 5-HT, serotonin; NE, norepinephrine; Glu, glutamate; DA, dopamine.

Prefrontal cortex5-HTF(1,21) = 9.63; p = 0.005
NEF(1,20) = 11.91; p = 0.003
Olfactory tubercle5-HTF(1,24) = 6.40; p = 0.018
DAF(1,21) = 26.35; < 0.001F(1,21) = 19.30; < 0.001F(1,21) = 28.78; < 0.001
GluF(1,23) = 13.15; < 0.001
Pyriform cortex5-HTF(1,21) = 59.28; < 0.001F(1,21) = 5.01; p = 0.036F(1,21) = 11.60; p = 0.003
DAF(1,18) = 15.12; p = 0.001
NEF(1,24) = 4.71; p = 0.040
Nucleus accumbens5-HTF(1,22) = 30.85; < 0.001F(1,22) = 6.20; p = 0.021
DAF(1,19) = 12.83; p = 0.002F(1,19) = 18.30; < 0.001F(1,19) = 17.01; < 0.001
NEF(1,24) = 18.04; < 0.001F(1,24) = 4.38; p = 0.047F(1,24) = 9.15; p = 0.006
Motor cortex5-HTF(1,22) = 148.88; < 0.001F(1,22) = 14.80; < 0.001
NEF(1,22) = 15.47; < 0.001F(1,22) = 8.41; p = 0.008
Somatosensory cortex5-HTF(1,24) = 38.97; < 0.001F(1,24) = 6.07; p = 0.021F(1,24) = 8.87; p = 0.007
DAF(1,21) = 4.93; p = 0.038F(1,21) = 13.05; p = 0.002
GABAF(1,23) = 4.32; p = 0.049
Caudate–putamen5-HTF(1,24) = 47.27; < 0.001F(1,24) = 9.07; p = 0.006
DAF(1,21) = 27.99; < 0.001F(1,21) = 21.99; < 0.001F(1,21) = 8.92; p = 0.007
NEF(1,23) = 6.72; p = 0.016F(1,23) = 5.11; p = 0.034
Anterior cingulate cortex5-HTF(1,24) = 6.55; p = 0.017
DAF(1,21) = 21.68; < 0.001
NEF(1,19) = 24.79; < 0.001F(1,19) = 19.15; < 0.001
Septum5-HTF(1,22) = 34.62; < 0.001
NE  F(1,22) = 7.04; p = 0.015
Diagonal band5-HTF(1,24) = 108.12; < 0.001F(1,24) = 10.97; p = 0.003
DAF(1,22) = 76.93; < 0.001
NEF(1,19) = 7.59; p = 0.013F(1,19) = 26.78; < 0.001
AspF(1,22) = 6.65; p = 0.017
Ventral pallidum5-HTF(1,24) = 69.90; < 0.001F(1,24) = 8.26; p = 0.008F(1,24) = 10.51; p = 0.003
DAF(1,22) = 22.78; < 0.001F(1,22) = 7.72; p = 0.011F(1,22) = 15.89; < 0.001
NEF(1,21) = 25.58; < 0.001F(1,21) = 6.04; p = 0.023
GABAF(1,23) = 5.77; p = 0.025
Globus pallidus5-HTF(1,19) = 28.51; < 0.001
DAF(1,20) = 25.17; < 0.001F(1,20) = 9.94; p = 0.005
NEF(1,23) = 7.81; p = 0.10
AspF(1,23) = 5.92; p = 0.023
Amygdala5-HTF(1,22) = 4.63; p = 0.043F(1,22) = 9.85; p = 0.005F(1,22) = 5.95; p = 0.023
DAF(1,20) = 22.05; < 0.001F(1,20) = 28.14; < 0.001F(1,20) = 8.01; p = 0.010
NEF(1,18) = 43.23; < 0.001F(1,18) = 20.11; < 0.001F(1,18) = 209.02; < 0.001
Hippocampus5-HTF(1,23) = 107.95; < 0.001F(1,23) = 12.22; p = 0.002
DAF(1,20) = 7.60; p = 0.012F(1,20) = 73.07; < 0.001
NEF(1,22) = 13.61; p = 0.001
AspF(1,23) = 5.92; p = 0.023
Medial thalamus5-HTF(1,23) = 118.64; < 0.001F(1,23) = 9.36; p = 0.006
DAF(1,23) = 13.88; p = 0.001
NEF(1,23) = 6.09; p = 0.021F(1,23) = 16.77; < 0.001
Lateral thalamus5-HTF(1,23) = 44.36; < 0.001F(1,23) = 16.26; < 0.001F(1,23) = 27.09; < 0.001
DAF(1,22) = 22.97; < 0.001
NEF(1,23) = 7.70; p = 0.011F(1,23) = 9.68; p = 0.005
Medial hypothalamus5-HTF(1,24) = 68.10; < 0.001F(1,24) = 8.36; p = 0.008F(1,24) = 11.85; p = 0.002
DAF(1,22) = 16.75; < 0.001F(1,22) = 5.79; p = 0.025
Lateral hypothalamus5-HTF(1,23) = 50.09; < 0.001F(1,23) = 7.03; p = 0.014
DAF(1,20) = 25.34; < 0.001F(1,20) = 39.36; < 0.001F(1,20) = 17.27; < 0.001
NEF(1,22) = 23.53; < 0.001
 AspF(1,22) = 6.63; p = 0.017
 GluF(1,22) = 4.36; p = 0.049
Posterior cingulate cortex5-HTF(1,23) = 50.94; < 0.001F(1,23) = 10.12; p = 0.004
DAF(1,16) = 8.73; p = 0.009F(1,16) = 21.42; < 0.001
NEF(1,24) = 65.73; < 0.001
GluF(1,22) = 5.97; p = 0.023
Entorhinal subicular cortex5-HTF(1,21) = 35.46; < 0.001F(1,21) = 5.90; p = 0.024
DAF(1,22) = 36.87; < 0.001
GABAF(1,23) = 6.68; p = 0.017
Substantia nigra5-HTF(1,21) = 35.39; < 0.001F(1,21) = 65.99; < 0.001F(1,21) = 5.64; p = 0.027
DAF(1,22) = 49.76; < 0.001F(1,22) = 37.62; < 0.001
NEF(1,23) = 4.60; p = 0.043
Brainstem5-HTF(1,22) = 52.59; < 0.001F(1,22) = 23.08; < 0.001
DAF(1,17) = 18.59; < 0.001F(1,17) = 4.98; p = 0.039F(1,17) = 16.97; < 0.001
NEF(1,23) = 8.11; p = 0.009
AspF(1,23) = 4.47; p = 0.046
GluF(1,22) = 4.46; p = 0.046 
Visual cortex5-HTF(1,24) = 17.27; < 0.001
DAF(1,24) = 17.27; < 0.001F(1,24) = 5.43; p = 0.029
GABAF(1,23) = 6.64; p = 0.017
Auditory temporal cortex5-HTF(1,24) = 31.53; < 0.001
DAF(1,24) = 10.94; p = 0.003
GABAF(1,23) = 5.59; p = 0.027F(1,23) = 24.89; < 0.001F(1,23) = 6.23; p = 0.020
Colliculi5-HTF(1,23) = 77.43; < 0.001F(1,23) = 20.12; < 0.001
DAF(1,22) = 62.99; < 0.001
NEF(1,23) = 31.06; < 0.001
GluF(1,23) = 4.66; p = 0.042

The pre-planned post hoc analysis of differences between mean using Bonferroni t-tests for multiple comparisons demonstrated 5-HT to have the largest number of significant changes in TORs (Fig. 2). Sixty-four changes in turnover were seen with 20 the result of EtOH drinking, 23 from a history of EtOH drinking, 14 from SUC drinking and seven from a history of SUC drinking. Seventeen of the changes resulting from EtOH drinking were decreases (OT, PYC, MC, SSC, pCC, E-SC, ATC, VC, CP, SEP, DB-PO, VP-ST, mTH, mHYP, lHYP, HIPP, COL, and SN) and two were increases (PFC and GP). A history of EtOH drinking resulted in all decreases in turnover in 23 brain regions (PYC, aCC, pCC, MC, SSC, E-SC, ATC, VC, NAc, CP, SEP, DB-PO, VP-ST, GP, AMYG, mTH, lTH, lHYP, mHYP, HIPP, COL, SN, and BS). In addition, SUC drinking resulted in 10 decreases in 5-HT turnover (PYC, SSC, NAc, VP-ST, GP, HIPP, mTH, lTH, COL, and BS) and four increases (PFC, MC, DB-PO, and SN). A history of SUC drinking resulted in seven changes in 5-HT turnover that included five increases (NAc, MC, mTH, lTH, and COL) and two decreases (PFC and AMYG).

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Figure 2.  Significant changes in serotonin turnover rates in brain regions determined with the pulse label method resulting from ethanol/sucrose drinking (upper left panel), sucrose drinking (upper right panel), a history of ethanol drinking (lower left panel), and a history of sucrose drinking (lower right panel). Values represent mean and the error bars standard errors of the mean for an n = 13. Differences between mean were determined following a two-way anova with pre-planned post hoc analysis using Bonferroni t-tests for multiple comparisons.

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Dopamine

The two-way anova analysis also demonstrated that EtOH consumption in a number of brain regions lowered the TOR of DA, but in some regions it resulted in a significant increase in TOR. Similar to what was seen with 5-HT above some of these effects were from the act of drinking, but there were several regions where significant effects were not related to the act of drinking which is illustrated by significant interactions when EtOH drinking and SUC drinking did not parallel each other. Regions where these interaction showed EtOH drinking to have a unique effect on DA TOR included the OT, NAc, VP-ST, CP, GP, AMYG, lTH, mHYP, lHYP, HIPP, E-SC, pCC, and BS. Thus, in these 13 brain regions, EtOH drinking affected the TOR uniquely which included both changes in the opposite direction than SUC drinking, or in the same direction that was significantly quantitatively different than with SUC drinking. In 11 of the 13 regions, the effect was an elevation of turnover and in two regions a decrease. In these 13 regions, it is likely that EtOH drinking, rather than simply the act of drinking, caused TOR of DA innervations of these regions to increase or decrease.

The pre-planned post hoc analysis of differences between mean using Bonferroni t-tests for multiple comparisons identified 48 significant changes in DA turnover with 11 resulting from EtOH drinking, 14 from a history of EtOH drinking, 12 from SUC drinking, and 11 from a history of SUC drinking. The changes with EtOH drinking included nine decreases (DB-PO, GP, AMYG, lHYP, E-SC, SN, VC, ATC, and COL) and an increase in the lTH and HIPP (Fig. 3) while a history of EtOH drinking resulted in 12 decreases in DA turnover (pCC, VC, OT, NAc, CP, DB-PO, VP-ST, HIPP, mHYP, lTH, SN, and COL) and an increase in the E-SC and BS. SUC drinking resulted in 12 changes in DA turnover that included six increases (aCC, E-SC, GP, AMYG, lHYP, and SN) and six decreases (PYC, pCC, SSC, HIPP, mTH, and lTH,). A history of SUC drinking resulted in 11 changes in DA turnover with eight decreases (PYC, MC, aCC, GP, AMYG, lHYP, SN, and BS) and increases in the pCC, HIPP, and VC.

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Figure 3.  Significant changes in dopamine turnover rates in brain regions determined with the pulse label method resulting from ethanol/sucrose drinking (upper left panel), sucrose drinking (upper right panel), a history of ethanol drinking (lower left panel), and a history of sucrose drinking (lower right panel). Values represent mean and the error bars standard errors of the mean for an n = 13. Differences between mean were determined following a two-way anova with pre-planned post hoc analysis using Bonferroni t-tests for multiple comparisons.

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Norepinepherine

The two-way anova analysis demonstrated that EtOH consumption in some brain regions changed NE TOR. Some of these effects were from the act of drinking and some were significant effects of EtOH drinking not related to the act of drinking when EtOH drinking and SUC drinking did not parallel each other (significant interaction effects). Regions where these interaction showed EtOH drinking to have a unique effect included the NAc, CP, SEP, VP-ST, DB-PO, AMYG, aCC, and pCC. Thus, in these eight brain regions EtOH drinking affected NE TOR uniquely and included both changes in the opposite direction than SUC drinking, or in the same direction that was significantly quantitatively different than with SUC drinking. In all eight regions, the effect was either an elevation or decrease in turnover. In these eight regions, it is likely that EtOH drinking, rather than simply the act of drinking, caused TOR of NE innervations of these regions to increase or decrease.

The pre-planned post hoc analysis of differences between mean using Bonferroni t-tests for multiple comparisons showed 39 changes in NE turnover that included nine resulting from EtOH drinking, 10 from SUC drinking, 12 from a history of EtOH drinking and eight from a history of SUC drinking. The nine changes resulting from EtOH drinking included eight decreases (PFC, aCC, NAc, SEP, DB-PO, AMYG, lHYP, and COL) and an increase in the pCC (Fig. 4). SUC drinking alone resulted in four increases in TOR (NAc, CP, DB-PO, and AMYG) and six decreases (mTH, lTH, lHYP, pCC, MC, and COL). A history of EtOH drinking resulted in nine decreases (pCC, MC, VP-ST, GP, HIPP, lTH, lHYP, COL, and BS) and an increase in the aCC, DB-PO, and AMYG. A history of SUC drinking resulted in three increases in NE TOR (PFC, aCC, and mTH) and five decreases (PYC, NAc, SEP, DB-PO, and AMYG).

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Figure 4.  Significant changes in norepinephrine turnover rates in brain regions determined with the pulse label method resulting from ethanol/sucrose drinking (upper left panel), sucrose drinking (upper right panel), a history of ethanol drinking (lower left panel), and a history of sucrose drinking (lower right panel). Values represent mean and the error bars standard errors of the mean for an n = 13. Differences between mean were determined following a two-way anova with pre-planned post hoc analysis using Bonferroni t-tests for multiple comparisons.

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GABA

Four changes in GABA TORs were detected (Fig. 5) that included a decrease in the ATC as a result of EtOH drinking and an increase in the ATC and SSC resulting from SUC drinking. In addition, a history of SUC drinking resulted in a decrease in the ATC.

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Figure 5.  Significant changes in glutamate, GABA, and aspartate turnover rates in brain regions determined with the pulse label method resulting from ethanol/sucrose drinking (upper left panel), sucrose drinking (upper right panel), a history of ethanol drinking (lower left panel), and a history of sucrose drinking (lower right panel). Values represent mean and the error bars standard errors of the mean for an n = 13. Differences between mean were determined following a two-way anova with pre-planned post hoc analysis using Bonferroni t-tests for multiple comparisons. Significance of differences are *< 0.05; p < 0.01; < 0.001.

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Glutamate

Four changes in Glu TOR were detected (Fig. 5) that included an increase in the OT in the EtOH drinking rats, an increase in the COL and a decrease in the OT of SUC drinking rats and a decrease in the OT resulting from a history of EtOH drinking.

Aspartate

Five significant changes in Asp TOR were detected (Fig. 5). These included decreases in the BS of the EtOH drinking rats compared with the SUC drinking group, increases in the DB-PO and HIPP of the SUC drinking rats compared with the SUC drinking history rats and increases in the DB-PO and lHYP in the EtOH drinking history rats compared with the SUC drinking history group.

DOPAC/DA and 5-HIAA/5-HT ratio procedure

No significant differences in DA turnover calculated from DOPAC/DA ratios were found in any of the 26 brain regions (Table 2). In contrast, 12 changes in 5-HT TOR were calculated from 5-HIAA/5-HT ratios that included all increases in the EtOH/SUC drinking versus the EtOH/SUC drinking history group (PFC, OT, PYC, MC, SSC, DB-PO, mTH, mHYP, E-SC, VC, ATC, and COL) (Table 2).

Discussion

  1. Top of page
  2. Abstract
  3. Experimental procedures
  4. Results
  5. Discussion
  6. Conclusions
  7. Acknowledgements
  8. References

This experiment demonstrates that rats with a history of binge-like drinking of moderate amounts of EtOH came to the drinking session with significant deficits in the activity of 5-HT, DA, and NE neurons throughout the brain. The NAc, VP-ST, and AMYG likely have a major role in the effects of EtOH drinking as all three regions showed significant interactions in the two-way anova. Many of the decreases in TOR seen in the EtOH/SUC drinking history group were reversed with EtOH drinking. A neuronal circuit is proposed that may be responsible for reversal of the deficits seen in the EtOH drinking history group and partially underlying EtOH drinking. The data also demonstrate that an acute alcohol deprivation effect likely occurs with moderate amounts of EtOH consumed in a drinking binge that creates the opportunity for negative reinforcement to further strengthen related EtOH seeking behaviors through an alleviation of anhedonic stimuli. In addition, this experiment demonstrates a major role for the biogenic monoamine releasing neurons and a lesser role for GABA and Glu releasing neurons in rat EtOH drinking as 92% (151) of the 164 significant TOR changes detected were in DA, NE, and 5-HT with 13 in Asp, GABA, and Glu. Although EtOH has been shown to have a significant action on GABA and Glu receptors, these data suggest that some of the effects of these amino acid neurotransmitter systems either occur post-synaptically, or through subtle modulations without affecting overall rates of synthesis or perhaps through a balance of increased and decreased turnover in subpopulations of neurons releasing these neurotransmitters within the brain regions that were evaluated. In addition, these amino acids have functions other than that of neurotransmission which can make identification of a subset of roles difficult while biogenic monoamines have a more focused neurotransmission function. There are clearly multiple pools of these amino acids which make the identification of synaptic function challenging. However, the moderate effects seen here would indicate that the consequences of EtOH drinking on these amino acid releasing neurons is different than the self-administration of morphine (Smith et al. 1982) or cocaine (Smith et al. 2003) where a number of significant changes in the TORs of these neurotransmitters were detected in similar brain regions. This experiment also identified DA, 5-HT, and NE innervations of the forebrain that appear to be involved in the process of drinking identified by comparing the drinking rats (both SUC and EtOH) with the drinking history rats. The significant changes in content of the neurotransmitters when they did occur did not seem to correlate with the direction of significant TOR changes. Only eight of the 14 content changes in the biogenic monoamine neurotransmitters occurred where TOR changes were also present with four going in the same direction and four going in the opposite direction. Similarly, only two of the eight changes in the content of the amino acid neurotransmitters occurred where TOR changes were seen and these both went in the same direction. Thus, neurotransmitter content changes do not appear to predict changes in TOR. In addition, the lack of concordance between TORs calculated by the metabolite/neurotransmitter content ratio method and the radioactive pulse label technique calculated from the same data set was further demonstrated, questioning the utility of these ratios as sensitive and accurate measures of neurotransmitter turnover (Smith et al. 2003).

The definition of binge alcohol drinking in animal models is still somewhat unclear. For humans, one definition of binge drinking is five drinks or more in 2 h for a male. For a 170 pound (79 kg) male, this would be approximately 1.25 oz of 40% EtOH per drink which is equivalent to 11.1 g of EtOH per drink and 55.5 g in five drinks. Thus, binge drinking would be considered the consumption of 0.7 g/kg of EtOH in 2 h or 0.35 g/kg/h. Others have defined a binge as a drinking pattern that brings blood alcohol concentration to 80 mg% (0.8 g/kg) or above. Rats metabolize EtOH two to four times faster than humans, so the 1 g/kg intake of the rats in 15 min in this study could be in this range. Blood EtOH levels were measured after tissue fixation in liquid nitrogen at 45 and 75 min after the completion of 93% of the intake of 1 g/kg in 15 min. The blood EtOH levels in the 60 and 90 min pulse labeled rats would fit literature values (Roberts et al. 1999) and project back to a peak level of approximately 30 mg % at the end of the 15 min binge which would not be above the legal limit for humans. This level of intake in rats is considered by researchers to be in the moderate range, thus the binge-like drinking in this study is labeled as moderate intake.

Acute EtOH deprivation effect

This experiment demonstrated that a history of moderate binge-like EtOH drinking produced a significant neurobiological acute EtOH deprivation effect evidenced by a profound general decrease in biogenic monoamine neurotransmitter TOR throughout the brain. Even though the EtOH drinking history rats did not demonstrate gross outward signs of EtOH dependence, it appears that the activity of neuronal systems in a number of brain regions changed in a subdependence state or an ‘acute’ alcohol deprivation effect that could produce negative effect and create an opportunity for strengthening EtOH drinking through negative reinforcement. An alcohol deprivation effect has been previously demonstrated in rats that did not show outward signs of physical dependence (Sinclair and Senter 1967; McKinzie et al. 1998). However, negative affect is suggested here by the decreases in the TORs of DA in the NAc, VP, mHYP, OT, and the pCC and by the increase in NE TOR in the AMYG. Forty-four of 51 significant changes in TOR in the EtOH drinking history group compared with the SUC drinking history group were decreases (Figs 2–5). Over 50% (23) of these TOR decreases were in 5-HT which is generally decreased throughout the brain. These decreases were seen in cortical, limbic and integrative brain regions important to behavior. NE TOR was decreased in several brain regions and increased in the AMYG, aCC, and DB-PO. In addition, DA TOR was decreased in limbic regions and increased in the E-SC and BS. Asp TOR was increased in the DB-PO and lHYP and Glu was decreased in the OT. It is interesting that the TORs of 5-HT, NE, and DA decreased in the VP-ST, pCC, HIPP, lTH, and COL as a result of the acute EtOH deprivation effect which suggests an important role for these areas in the action of EtOH. The levels of NAc DA in the alcohol preferring and high alcohol drinking lines previously have been shown to be decreased compared with the alcohol non-preferring and low alcohol drinking counterparts (Murphy et al. 1987; Gongwer et al. 1989) which is indirectly supported by decreased NAc DA TOR in the EtOH drinking history group. TORs of two of the three biogenic monoamine neurotransmitters were also decreased in the NAc, CP, GP, DB-PO, mHYP and lHYP, and SN as a result of the acute EtOH deprivation effect. The involvement of these regions (pCC, NAc, VP-ST, and lHYP) in the acute EtOH deprivation effect is not surprising as the NAc, basal ganglia, paraventricular nucleus of the HYP, cingulate cortex, VP-ST, and SN have all been identified as brain regions activated in EtOH withdrawal in mice and rats (Eckardt et al. 1992; Kozell et al. 2005). The decreases in DA TOR in forebrain regions also is consistent with electrophysiological data showing decreases in the spontaneous activity and firing rates of DA neurons in the VTA during withdrawal that is reversed by EtOH administration (Diana et al. 1993; Shen and Chiodo 1993). In addition, decreased extracellular DA has been seen in the NAc and CP during withdrawal that is reversed by a challenge dose of EtOH (Rossetti et al. 1992a; Diana et al. 1993; Weiss et al. 1996). The increases in NE TOR in the AMYG are consistent with observations during EtOH withdrawal (Merlo et al. 1995), increased stress (Cecchi et al. 2002) and with the hypothesis recently set forth on the role of A1/A2 noradrenergic neurons in the drug deprivation effects that are proposed to be involved in the elevated anxiety that produce a negative reinforcement opportunity that can strengthen drug self-administration behavior (Aston-Jones and Harris 2004). The decrease in 5-HT TOR in the HIPP may also be indicative of changes that precede the occurrence of physical dependence and the seizures seen during withdrawal that correlate with increased NMDA receptor densities in this region (Gulya et al. 1991).

Ethanol drinking effect

The EtOH drinking rats came to the drinking session with significant decrements in the activity of 5-HT, NE, DA, Asp, Glu, and GABA neurons in a number of brain regions as demonstrated in the EtOH history group (Figs 2–5). The drinking of EtOH returned many of these decreases to or toward that seen in the SUC drinking and non-drinking control groups (Fig. 6). EtOH drinking returned DA TORs in the aCC, pCC, VP-ST, HIPP, lTH, and mHYP to that of SUC or non-drinking control levels and increased 5-HT TOR in the aCC, pCC, SEP, CP, GP, AMYG, lHYP, mHYP, E-SC, SN, and BS in a similar fashion. EtOH drinking returned NE TORs in the VP-ST and pCC to that of SUC or the non-drinking control. EtOH drinking also reversed the decrement in Glu TOR in the OT seen in the EtOH/SUC drinking history group. In addition, GABA TOR was increased in the ATC and Asp TOR was decreased in the BS. As mentioned above, the NAc, VP-ST, and AMYG likely have a significant role as interactions were seen with the two-way anova in the TOR of all three biogenic monoamines in these brain regions. The aCC, pCC, GP, HIPP, lTH, mHYP, and BS are also likely important as similar interactions were seen in two of the three biogenic monoamines in these brain regions.

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Figure 6.  Significant changes in serotonin and dopamine turnover rates in brain regions determined with the pulse label method resulting from a history of ethanol drinking reversed by the opportunity to drink ethanol. Values are mean and error bars standard errors of the mean for an n = 13. The significant differences represent comparisons between the ethanol drinking and the ethanol drinking history group. Differences between mean were determined following a two-way anova with pre-planned post hoc analysis using Bonferroni t-tests for multiple comparisons.

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The increase in 5-HT TOR in the AMYG in the EtOH drinking rats compared with the EtOH history group (Fig. 6) is consistent with prior data showing an increase in extracellular fluid levels of 5-HT after EtOH administration (Yoshimoto et al. 2000). In addition, the increase in NE TOR in the AMYG in the EtOH history rats was also reversed in the EtOH drinking group compared with the EtOH history group suggesting a decrease in stress level and the increase in DA TOR in the NAc with EtOH drinking which is consistent with the alleviation of the acute alcohol deprivation effect and with the suggested optimal level of DA stimulation to produce a reinforcing stimulus (Tupala and Tiihonen 2004).

Even though most of the acute EtOH deprivation effect was alleviated by EtOH drinking, when the EtOH drinking group was compared with the SUC drinking group, the TORs for 5-HT, DA, NE, Asp, and GABA were generally lower (Figs 2–5). The DB-PO had significantly lower levels of TOR of all three biogenic monoamine neurotransmitters and the AMYG, lHYP, pCC, and E-SC regions had decreases in two of the three resulting from EtOH drinking suggesting an elevated level of involvement. Although there was no change in Glu or GABA TOR detected in the VTA, an increase in VTA DA output to the OT, NAc, VP-ST, CP, mHYP, and SN suggest a major role for modulation by these amino acid neurotransmitters in overcoming the decrements seen in the EtOH/SUC drinking history group prior to the drinking session. The increased TOR of 5-HT in the PFC is the opposite of what was seen with SUC drinking or a history of SUC drinking and is hypothesized to have a major role in reversing the EtOH history deficits as described below. The increase in NE TOR in the pCC may also be important to the processes underlying EtOH consumption and the decrease in NE TOR in the PFC is consistent with data showing an acute dose of EtOH (2.0 g/kg) to decrease the release of NE in the frontal cortex (Rossetti et al. 1992b). The TOR of all three biogenic amine neurotransmitters was decreased in the DB-PO region suggesting that a modulation of the major cholinergic efferents from this region to the diencephalon and telencephalon may occur with EtOH drinking.

Proposed neuronal circuit underlying the alleviation of the EtOH deprivation effect and components of EtOH drinking

A neuronal circuit is proposed that may underlie the reversal of the deficits in biogenic amine neurotransmitter tone in the forebrain of rats with a history of moderate EtOH binge-like drinking that may be part of the neurobiological substrates that underlie EtOH drinking. This includes 5-HT innervations of the PFC (evidenced by increased TOR) that modulate the activity of descending Glu and GABA systems innervating the VTA and SN resulting in an increase in the activity of DA neurons in mesolimbic-mesocortical and nigrostriatal pathways which further activate 5-HT neurons in the dorsolateral raphe nuclei resulting in an activation of discrete forebrain DA and 5-HT innervations (Fig. 7). The increased activity of 5-HT innervations of the PFC in the EtOH drinking group likely resulted in an increase output of Glu and/or GABA neurons innervating VTA DA neurons resulting in increased DA tone in the OT, NAc, VP-ST, CP, aCC, and pCC overcoming the decrements seen prior to the drinking session (evidenced in the EtOH drinking history group). Increases in the activity of DA innervations of the dorsal raphe nuclei (DRN) result in the activation of 5-HT innervations of the mHYP, AMYG, CP, aCC and pCC reversing those decrements as well.

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Figure 7.  Neuronal circuits mediating the reversal of the acute ethanol deprivation effect. Activation of 5-HT2A receptors in the prefrontal cortex (PFC) in the ethanol drinking rats demonstrated by increased turnover rates (TORs) for 5-HT activates cortical pyramidal Glu or GABA releasing neurons that innervate the ventral tegmental area (VTA) and substantia nigra (SN) that in turn activate DA releasing neurons that innervate the dorsal raphe nuclei (DRN), amygdala (AMYG), medial hypothalamus (mHYP), ventral pallidum-pre-optic region (VP-PO), olfactory tubercle (OT), nucleus accumbens (NAc), caudate–putamen (CP), and anterior and posterior cingulate cortex (aCC and pCC). The activation of the DRN results in increased 5-HT activity in the AMYG, mHYP, CP, aCC, and pCC.

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This circuit is consistent with data showing the VTA to receive dense innervations from the PFC which upon stimulation results in short latency excitation in VTA DA neurons (Carr and Sesack 2000). The PFC contains 5-HT2A receptors (Amargós-Bosch et al. 2004) that activate pyramidal neurons innervating the VTA resulting in increased activity of VTA DA neurons (Puig et al. 2003; Bortolozzi et al. 2005). In addition, DA neurons innervate the DRN from both the VTA and SN (Decavel et al. 1987; Kalen et al. 1988; Peyron et al. 1995; Kitahama et al. 2000). Although DA TOR was not assessed in the DRN, the increase in 5-HT TOR in these forebrain regions clearly indicates that these nuclei were activated in the EtOH/SUC drinking rats. These rodent data are consistent with the activation of the PFC seen in human alcoholics to alcohol specific cues (George et al. 2001). Further evidence supporting the increase in activity of NAc DA input with EtOH/SUC drinking is consistent with the increases in extracellular fluid levels of DA ([DA]e) in microdialysates of the NAc during EtOH self-administration (Weiss et al. 1993).

Sucrose drinking effect

Although SUC self-administration has been shown to not alter 2-deoxyglucose uptake compared with water drinking controls (Porrino et al. 1998), biogenic monoamine neurotransmitter TORs did differ from home cage and SUC history controls (Fig. 8). However, SUC drinking resulted in significantly less changes and a different pattern of change compared with the EtOH drinking group. While EtOH drinking had the largest impact upon 5-HT TOR, SUC drinking resulted in almost equivalent numbers of changes in DA, 5-HT and NE TORs and two changes each in GABA, Asp, and Glu TOR. SUC drinking increased DA TORs in the aCC, GP, AMYG, lHYP, E-SC, and SN and decreased in the PYC and HIPP while 5-HT TORs were increased in the DB-PO and decreased in the PFC, NAc, SSC, VP-ST, GP, lTH, and COL. Noradrenergic TORs were increased in the NAc, CP, DB-PO, and AMYG and decreased in the MC, lTH, and pCC. SUC drinking increased GABA TOR in the SSC and ATC, Asp in the HIPP and DB-PO and increased Glu TOR in the COL but decreased it in the OT. Although increased NAc [DA]e have been reported after SUC consumption (Doyon et al. 2004) and in rats with gastric fistulas in response to the taste of SUC (Avena et al. 2006), no changes in DA TOR were seen in this region. Actually no changes in the TOR of DA, Asp, Glu, or GABA were seen in the NAc in response to SUC or EtOH drinking. The increases in DA TOR in the lHYP are somewhat in contrast with the decreases in c-Fos expression in this region reported in mice drinking SUC (Ryabinin et al. 2003). However, DA interaction with D2 receptors in this structure would likely be inhibitory and result in a decrease in c-Fos expression. Although there were no changes in Glu or GABA TORs detected in the VTA of the SUC drinking rats, forebrain regions indicate that subsets of VTA DA neurons were activated.

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Figure 8.  Significant changes in serotonin, dopamine and norepinephrine turnover rates in brain regions determined with the pulse label method resulting from a history of sucrose drinking reversed by the opportunity to drink sucrose. Values are mean and error bars standard errors of the mean for an n = 13. The significant differences represent comparisons between the sucrose drinking and the sucrose drinking history group. Differences between mean were determined following a two-way anova with pre-planned post hoc analysis using Bonferroni t-tests for multiple comparisons.

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Sucrose drinking history effect

A history of SUC drinking (SUC history compared with control) resulted in 27 significant changes in 5-HT, NE, DA, and GABA TOR (Figs 2–5) with 10 being increases and 17 being decreases. SUC drinking reversed some of the changes in TOR seen in the SUC history group in a manner similar to what was seen between the EtOH drinking and EtOH history groups outlined above. Why would the SUC history group be so different from the home cage controls? The pulse labeling procedure did not involve the handling of the animals, so the changes are not likely anticipatory or the stress of not being allowed to drink SUC, as the start of the daily sessions did vary up to 60 min during the drinking phase. Fifteen of the 27 significant changes in TOR in this group were reversed toward the non-drinking control by the opportunity to drink SUC (Figs 2–5). These included an increase in PFC 5-HT TOR which could similarly activate VTA and SN DA neurons through the same mechanisms as outlined for EtOH drinking in Fig. 6. The increases in DA TOR in the aCC, GP, AMYG, lHYP, and SN with SUC drinking are also reversals of decreases toward the non-drinking control. Six of the 11 changes in DA TOR and three of seven in each of 5-HT and NE TOR were reversed in the SUC drinking group (Fig. 8).

In the comparisons between the SUC history and the non-drinking groups, 10 of the TOR changes were in cortical regions that included four increases (DA in the pCC and VC, 5-HT in the MC, and NE in the PFC) and six decreases (DA in the PYC, MC and aCC, 5-HT in the PFC, NE in the PYC, and GABA in the ATC). The TORs of all three biogenic amines were decreased in the AMYG including NE which would argue for this condition not being stressful. In addition, 5-HT TOR increased in the NAc, mTH, lTH, and COL and NE TOR increased in the mTH while DA TOR was increased in the HIPP. The increases in 5-HT TOR in the lTH and the COL were the opposite of what was seen with the acute EtOH deprivation effect. DA TOR was decreased in the GP, lHYP, BS, and SN with the latter being the same as the acute EtOH deprivation effect while NE TOR also decreased in the PYC, NAc, SEP, DB-PO, and AMYG. The SUC history and acute EtOH deprivation effects appear to have very different neurobiological underpinnings. Commonalities include the changes in the activity of 5-HT and NE innervations of the AMYG and in DA in the SN. However, there are widespread differences in the effects of a history of EtOH and SUC drinking upon DA, NE, and 5-HT neuronal activity with the EtOH history effect having almost twice the number of changes in TORs and, in general, a larger magnitude of effect.

Drinking effect

Are the ‘compensatory’ changes seen in the alleviation of the deficits in DA, 5-HT, NE, and GABA TOR in the EtOH history group the result of EtOH drinking or of the opportunity to drink? If it were the opportunity to drink, then it should be present in the SUC drinking animals and apparent with the comparisons of that group with the SUC drinking history controls. However, significant increases in TOR of DA in the aCC, AMYG, lHYP, E-SC, and SN, in 5-HT in the PFC, MC, DB-PO, COL, SN, and BS, and in GABA in the ATC were also seen in the SUC drinking and not in the SUC drinking history group (Figs 2 and 3) suggesting that these may be more general changes resulting from the opportunity to drink, while the remaining changes are more likely to be the result of EtOH drinking. The experimental design actually permitted assessment of the effects of drinking in general on neurotransmitter TORs by comparing the drinking rats (both SUC and EtOH) with the history rats. Although 43 changes in TOR were seen, 20 of those were the result of a reversal of the effects of the decrements seen with a history of EtOH/SUC drinking while 23 were unique. The unique changes included increases in the TOR of DA in the aCC and GP, in 5-HT in the PFC, in NE in the CP and DB-PO, in Glu in the pCC and BS while decreases in TOR were seen in DA in the PYC, SSC, HIPP, and mTH, in 5-HT in the PYC, NAc, SSC, VP-ST, and mTH and lTH, in NE in the MC, aCC and mTH and lTH and GABA in the ATC. The mTH, PYC, aCC, SSC, and lTH appear to be the brain regions most involved as two to three TOR changes were identified in each. However, the act of drinking in both the EtOH/SUC and SUC drinking groups included the intake of fluids with a caloric value which likely may also have neurochemical consequences on the TORs of these neurotransmitters. For these reasons, the systems identified as modified with the act of drinking must be critically evaluated and would require follow up studies to demonstrate selective involvement in this behavior.

Differences in the ratio and pulse label TORs

Radioactive pulse labeling TOR methodologies have been used sparingly in the last two decades which likely results partially from the significant effort involved and from the controversy as to what are the acceptable methodologies to be employed. Over the last two decades, neurotransmitter metabolite content and neurotransmitter content ratios evolved as measures of turnover which are substantially easier to obtain and generally have been accepted as measures of neurotransmitter utilization. There had not been a direct comparison of TORs determined with these ratios with those obtained by an alternative method but calculated from the same database until recently (Smith et al. 2003) with that result being generally replicated here. Neurotransmitter metabolite/content ratios for DA and 5-HT were compared with pulse labeling measures of turnover from the same database and found to not be in agreement and be solely the result of changes in the content of the metabolites (Smith et al. 2003). In addition, the ratios did not detect changes that have been previously demonstrated or expected. Similar comparisons were made in this current study with the same result. Discrepancies were found between TORs calculated with the pulse label technique and metabolite/neurotransmitter ratios. Although these TORs were calculated from the same samples only three values obtained with ratios is in agreement with data obtained with the pulse label techniques (increases in TOR in the mHYP MC and E-SC in the EtOH/SUC drinking vs. the EtOH/SUC drinking history group).

Neurotransmitter TORs determined with radioactive pulse labeling were developed to estimate the involvement of the functional pool of biogenic monoamine neurotransmitters in brain function. The functional pool was defined as that portion that is immediately available to meet the requirements of the neuron to transmit information. This pool is believed to be the most recently synthesized neurotransmitter, so that a ‘most recently synthesized, first out’ principle was hypothesized to predominate. Radioactive pulse labeling techniques selectively label this functional pool so that the TOR values are generally thought to reflect activity in this pool. The pulse label procedure detected 112 significant changes in TOR of 5-HT and DA and the metabolite/neurotransmitter ratio procedure detected 10. The pulse label technique detected 64 changes in 5-HT TOR between these groups and the 5-HIAA/5-HT ratio detected 12. Of these 12 significant changes, nine were not seen with that technique. In addition, three of the significant ratio changes resulted from decreases in the content of 5-HT (OT, PFC, and mHYP in the EtOH/SUC drinking history group). The pulse label technique detected 48 changes in DA TOR between these five treatment conditions, while the DOPAC/DA ratio procedure detected no differences. In addition, the magnitude of the differences in TOR detected with the pulse label technique demonstrates the sensitivity of the technology. Although the dynamics of tissue neurotransmitter metabolite content may be partially the result of the rate of degradation of the neurotransmitter, other unrelated factors can also be responsible (transport mechanisms, enzymatic processes responsible for removal, blood flow, and CSF dynamics). Tissue content of neurotransmitters or metabolites is a questionable measure of the activity of neurons that utilize it for transmission. These discrepant results determined in the same animals with two different procedures shown previously (Smith et al. 2003) and further demonstrated here, raise further questions of the utility of metabolite/neurotransmitter ratios as sensitive measures of the utilization of a neurotransmitter and provide further support for the use of pulse label procedures in investigations of neurotransmitter utilization as biological substrates of behavior.

Conclusions

  1. Top of page
  2. Abstract
  3. Experimental procedures
  4. Results
  5. Discussion
  6. Conclusions
  7. Acknowledgements
  8. References

A history of moderate binge-like EtOH consumption causes decreases in DA, 5-HT, and NE neurotransmitter turnover (utilization) in a number of forebrain regions that have been associated with hedonic, emotion, and integrative higher order functions. These changes likely underlie the behavior changes (anhedonia, anxiety, and impulsive behaviors) known to occur following bouts of binge drinking. The large deficits in DA, NE, and 5-HT TOR resulting from the acute EtOH deprivation effect that were attenuated with further binge-like intake of moderate amounts of EtOH suggests a discrete neuronal circuit responsible for this action. The increases in PFC 5-HT TOR and the likely activation of 5-HT2A receptors in this brain region likely have a major role in the alleviation of the acute EtOH deprivation effect producing an activation of VTA and SN DA releasing neurons an subsequent further activation of 5-HT DRN projections to other parts of the forebrain. The experimental results also provide neurobiological evidence for the hypothesis that has been previously proposed that the anhedonia that occurs with moderate levels of EtOH binge drinking that is reversed by further EtOH intake produces an opportunity for negative reinforcement to further strengthen EtOH seeking behaviors. These processes could be central to the events that occur with binge drinking in humans which often escalates to abuse, dependence, and alcoholism and clearly warrant further investigation.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Experimental procedures
  4. Results
  5. Discussion
  6. Conclusions
  7. Acknowledgements
  8. References

This study was supported in part by USPHS Grants AA11661, AA11272, AA00279, and DA00114.

References

  1. Top of page
  2. Abstract
  3. Experimental procedures
  4. Results
  5. Discussion
  6. Conclusions
  7. Acknowledgements
  8. References
  • Amargós-Bosch M., Bortolozzi A., Puig M. V., Serrats J., Adell A., Celeda P., Toth M., Mengod G. and Artigas F. (2004) Co-expression and in vivo interaction of 5-HT1A and -HT2A receptors in pyramidal neurons of prefrontal cortex. Cereb. Cortex 14, 281299.
  • Aston-Jones G. and Harris G. C. (2004) Brain substrates for increased drug seeking during protracted withdrawal. Neuropsychopharmacology 47, 167179.
  • Avena N. M., Rada P., Moise N. and Hoebel B. G. (2006) Sucrose sham feeding on a binge schedule releases accumbens dopamine repeatedly and eliminates the acetylcholine satiety response. Neuroscience 139, 813820.
  • Bachtell R. K., Weitemier A. Z. and Ryabinin A. E. (2004) Lesions of the Edinger-Westphal nucleus in C57BL/6J mice disrupt ethanol-induced hypothermia and ethanol consumption. Eur. J. Neurosci. 20, 16131623.
  • Bailey C. P., Andrews N., McKnight A. T., Hughes J. and Little H. J. (2000) Prolonged changes in neurochemistry of dopamine neurons after chronic ethanol consumption. Pharmacol. Biochem. Behav. 66, 153161.
  • Beadles-Bohling A. S. and Wiren K. M. (2005) Alteration in kappa-opioid receptor system expression in distinct brain regions of a genetic model of enhanced ethanol withdrawal severity. Brain Res. 1046, 7789.
  • Bortolozzi A., Díaz-Mataix L., Scorza M. C., Celada P. and Artigas F. (2005) The activation of 5-HT2A receptors in prefrontal cortex enhances dopaminergic activity. J. Neurochem. 95, 15971607.
  • Budygin E. A., Phillips P. E., Robinson D. L., Kennedy A. P., Gainetdinov R. R. and Wightman R. M. (2001) Effect of acute ethanol on striatal dopamine neurotransmission in ambulatory rats. J. Pharmacol. Exp. Ther. 297, 2734.
  • Carr D. B. and Sesack S. R. (2000) Projections from the rat prefrontal cortex to the ventral tegmental area: target specificity in the synaptic associations with mesoaccumbens and mesocortical neurons. J. Neurosci. 20, 38643873.
  • Cecchi M., Khoshbouei H. and Morilak D. A. (2002) Modulatory effects of norepinephrine acting through α1-receptors in the central nucleus of the amygdala, on behavioral and neuroendocrine responses to acute immobilization stress. Neuroscience 43, 11391147.
  • Chen F., Rezvani A., Jarrott B. and Lawrence A. J. (1998) Distribution of GABAA receptors in the limbic system of alcohol-preferring and non-preferring rats: in situ hybridization histochemistry and receptor autoradiography. Neurochem. Int. 32, 143151.
  • Co C., Smith J. E. and Lane J. D. (1982) Use of a single compartment LCEC cell in the determinations of biogenic amine content and turnover. Pharmacol. Biochem. Behav. 16, 641646.
  • Decavel C., Lescaudron L., Mons N. and Calas A. (1987) First visualization of dopaminergic neurons with a monoclonal antibody to dopamine: a light and electron microscopic study. J. Histochem.Cytochem. 35, 12451251.
  • Diana M., Pistis M., Carboni S., Gessa G. L. and Rossetti Z. L. (1993) Profound decrement of dopaminergic neuronal activity during ethanol withdrawal syndrome in rats: electrophysiological and biochemical evidence. Proc. Natl Acad. Sci. USA 90, 79667969.
  • Doyon W. M., Ramachandra V., Samson H. H., Czachowski C. L. and Gonzales R. A. (2004) Accumbal dopamine concentration during operant self-administration of a sucrose or a novel sucrose with ethanol solution. Alcohol 34, 261271.
  • Eckardt M. J., Campbell G. A., Marietta C. A., Majchrowicz E., Rawlings R. R. and Weight F. F. (1992) Ethanol dependence and withdrawal selectively alter localized cerebral glucose utilization. Brain Res. 584, 244250.
  • Freeman M. D., Lane J. D. and Smith J. E. (1983) Turnover rates of amino acid neurotransmitters in regions of rat cerebellum. J. Neurochem. 40, 14411447.
  • Frink M. C., Hennies H. H., Englberger W., Haurand M. and Wilffert B. (1996) Influence of tramadol on neurotransmitter systems of the rat brain. Arzneimittelforschung 46, 10291036.
  • George M. S., Anton R. F., Bloomer C., Teneback C., Drobes D. J., Lorberbaum J. P., Nahas Z. and Vincent D. J. (2001) Activation of prefrontal cortex and anterior thalamus in alcoholic subjects on exposure to alcohol-specific cues. Arch. Gen. Psychiat. 58, 345352.
  • Gongwer M. A., Murphy J. M., McBride W. J., Lumeng L. and Li T.-K. (1989) Regional brain contents of serotonin, dopamine and their metabolites in the selectively bred high- and low-alcohol drinking lines of rats. Alcohol 6, 317320.
  • Gulya K., Grant K. A., Valverius P., Hoffman P. L. and Tabakoff B. (1991) Brain regional specificity and time-course of changes in the NMDA receptor-ionophore complex during ethanol withdrawal. Brain Res. 547, 129134.
  • Jones B. N. and Gilligan J. P. (1983) O-phthaldialdehyde precolumn derivatization and reversed-phase high-performance liquid chromatography of polypeptide hydrolysates and physiological fluids. J. Chromatog. 266, 471482.
  • Jones S. R., Mathews T. A. and Budygin E. A. (2006) Effect of moderate ethanol dose on dopamine uptake in rat nucleus accumbens in vivo. Synapse 60, 251255.
  • Kalen P., Skagerberg G. and Lindvall O. (1988) Projections from the ventral tegmental area and mesencephalic raphe to the dorsal raphe nucleus in the rat. Exp. Brain Res. 73, 6977.
  • Kitahama K., Nagatsu I., Geffard M. and Maeda T. (2000) Distribution of dopamine-immunoreactive fibers in the rat brainstem. J. Chem. Neuroanat. 18, 19.
  • Koob G. F. (1992) Drugs of abuse: anatomy, pharmacology and function of reward pathways. Trends Pharmacol. Sci. 13, 177184.
  • Koob G. F., Sanna P. P. and Bloom F. E. (1998) Neuroscience of addiction. Neuron 21, 467476.
  • Kozell L. B., Hitzemann R. and Buck K. J. (2005) Acute alcohol withdrawal is associated with c-Fos expression in the basal ganglia and associated circuitry: C57BL/6J and DBA/2J inbred mouse strain analyses. Alcohol. Clin. Exp. Res. 29, 19391948.
  • Lodge D. J. and Lawrence A. J. (2003) The effect of isolation rearing on volitional ethanol consumption and central CCK/dopamine systems in Fawn-Hooded rats. Behav. Brain Res. 141, 113122.
  • Lowry O. H., Rosenbrough N. J., Farr A. L. and Randall R. J. (1951) Protein measurements with the Folin phenol reagent. J. Biol. Chem. 193, 265275.
  • McBride W. J. and Li T. K. (1998) Animal models of alcoholism: neurobiology of high alcohol-drinking behavior in rodents. Crit. Rev. Neurobiol. 12, 339369.
  • McKinzie D. L., Nowak K. L., Yorger L., McBride W. J. and Murphy J. M. (1998) The alcohol deprivation effect in the alcohol preferring P rat under free drinking and operant access conditions. Alc. Clin. Exp. Res. 22, 11701176.
  • Merlo P. E., Lorang M., Yeganeh M., Rodriguez D. F., Raber J. and Koob G. F. (1995) Increase of extracellular corticotropin-releasing factor-like immunoreactivity levels in the amygdala of awake rats during restraint stress and ethanol withdrawal as measured by microdialysis. J. Neurosci. 15, 54395447.
  • Milio C. and Hadfield M. G. (1992) Ethanol alters monoamines in specific mouse brain regions. Brain Res. Bull. 29, 500603.
  • Murphy J. M., McBride W. J., Lumeng L. and Li T.-K. (1987) Contents of monoamines in forebrain regions of alcohol-preferring (P) and non-preferring (NP) lines of rats. Pharmacol. Biochem. Behav. 26, 389392.
  • Peyron C., Luppi P. H., Kitahama K., Fort P., Herman D. M. and Jouvet M. (1995) Origin of the dopaminergic innervation of the rat dorsal raphe nucleus. Neuroreport 6, 25272531.
  • Pickens R. and Dougherty J.(1972) A method for chronic intravenous infusion of fluids into unrestrained rats. Reports from Res. Labs, No. PR-72-1. Department of Psychiatry, University of Minnesota, Minnesota.
  • Porrino L. J., Williams-Hemby L., Whitlow C., Bowen C. and Samson H. H. (1998) Metabolic mapping of the effects of oral alcohol self-administration in rats. Alc. Clin. Exp. Res. 22, 176182.
  • Puig M. V., Celada P., Díaz-Mataix L. and Artigas F. (2003) In vivo modulation of the activity of pyramidal neurons in the rat medial prefrontal cortex by 5-HT2A receptors: relationship of thalamocortical afferents. Cereb. Cortex 13, 870882.
  • Roberts A. J., Heyser C. J. and Koob G. F. (1999) Operant self-administration of sweetened versus unsweetened ethanol: effects on blood alcohol levels. Alc. Clin. Exp. Res. 23, 11511157.
  • Rossetti Z. L., Hmaidan Y. and Gessa G. L. (1992a) Marked inhibition of mesolimbic doapmine release: a common feature of ethanol, morphine, cocaine and amphetamine abstinence in rats. Eur. J. Pharmacol. 221, 227234.
  • Rossetti Z. L., Longu G., Mercuro G., Hmaidan Y. and Gessa G. L. (1992b) Biphasic effect of ethanol onnorepinephrinerelease in the frontal cortex of awake rats. Alcohol 27, 477480.
  • Ryabinin A. E., Galvan-Rosas A., Bachtell R. K. and Risinger F. O. (2003) High alcohol/sucrose consumption during dark circadian phase in C57BL/6J mice: involvement of hippocampus, lateral septum and urocortin-positive cells of the Edinger-Westphal nucleus. Psychopharmacology 165, 296305.
  • Shen R.-Y. and Chiodo L. A. (1993) Acute withdrawal after repeated ethanol treatment reduces the number of spontaneously active dopaminergic neurons in the ventral tegmental area. Brain Res. 622, 289293.
  • Short J. L., Drago J. and Lawrence A. J. (2006) Comparison of ethanol preference and neurochemical measures of mesolimbic dopamine and adenosine systems across different strains of mice. Alc. Clin. Exp. Res. 30, 606620.
  • Sinclair J. D. and Senter R. J. (1967) Increased preference for ethanol in rats following deprivation. Psychon. Sci. 8, 1112.
  • Smith J. E. and Lane J. D. (1983) Brain neurotransmitter turnover correlated with morphine self-administration, in The Neurobiology of Opiate Reward Processes (Smith J. E. and Lane J. D., eds), pp. 361402. Elsevier, Amsterdam.
  • Smith J. E., Co C., Freeman M. E. and Lane J. D. (1982) Brain neurotransmitter turnover correlated with morphine-seeking behavior in rats. Pharmacol. Biochem. Behav. 16, 509519.
  • Smith J. E., Koves T. R. and Co C. (2003) Brain neurotransmitter turnover rates during rat intravenous cocaine self-administration. Neuroscience 117, 461475.
  • Takeo S., Hayashi H., Miyake K., Takagi K., Tadokoro M., Takagi N. and Oshikawa S. (1997) Effects of delayed treatment with nebracetam on neurotransmitters in brain regions after microsphere embolism in rats. Br. J. Pharmocol. 121, 477484.
  • Tupala E. and Tiihonen J. (2004) Dopamine and alcoholism: neurobiological basis of ethanol abuse. Prog. Neuropsychopharamcol. Biol. Psychiatry 28, 12211247.
  • Wedzony K., Koros E., Czyrak A., Chocyk A., Czepiel K., Fijal K., Mackowiak M., Rogowski A., Kostowski W. and Bienkowski P. (2003) Different pattern of brain c-Fos expression following re-exposure to ethanol or sucrose self-administration environment. Naunyn Schmiedebergs Arch. Pharmacol. 368, 331341.
  • Weeks J. R. (1962) Experimental morphine addiction: method for automatic intravenous injections in unrestrained rats. Science 138, 143144.
  • Weeks J. R. (1972) Long-term intravenous infusions, in Methods in Psychobiology, Vol. 2 (Myers R. D., ed.), pp. 155168. Academic Press, New York.
  • Weiss F., Lorang M. T., Bloom F. E. and Koob G. F. (1993) Oral alcohol self-administration stimulates dopamine release in the rat nucleus accumbens: genetic and motivational determinants. J. Pharmacol. Exp. Ther. 267, 250258.
  • Weiss F., Parsons L. H., Schulteis G., Hyytiä P., Lorang M. T., Bloom F. E. and Koob G. F. (1996) Ethanol self-administration restores withdrawal-associated deficiencies in accumbal dopamine and 5-hydroxytryptamine release in dependent rats. J. Neurosci. 16, 34743485.
  • Wise R. A. (1978) Catecholamine theories of reward: a critical review. Brain Res. 152, 215247.
  • Yoshimoto K., Ueda S., Kato B., Takeuchi Y., Kawai Y., Noritake K. and Yasuhara M. (2000) Alcohol enhances characteristic release of dopamine and serotonin in the central nucleus of the amygdala. Neurochem. Int. 37, 369376.
  • Zilversmit D. B. (1960) The design analysis of isotope experiments. Am. J. Med. 29, 832848.