Single-dose ethanol intoxication causes acute and lasting neuronal changes in the brain

Significance

To better understand the changes in the brain that support the transition from sporadic drinking to chronic alcohol abuse, we identified distinct effects of single ethanol exposure on a molecular, cellular, and behavioral level. Similar to learning and memory processes, the idea was to discover lasting changes that could mediate lasting ethanol reward memories. By imaging the brains of acutely exposed mice, we found that ethanol induced lasting changes in synaptic morphology, the axon initial segment, and mitochondrial trafficking. In Drosophila flies, specific knockdown of mitochondrial trafficking abolished positive ethanol reward memories. Together, our data suggest that a single ethanol exposure induces plastic changes which in turn could contribute to the basis of ethanol dependence.

Abstract

Alcohol intoxication at early ages is a risk factor for the development of addictive behavior. To uncover neuronal molecular correlates of acute ethanol intoxication, we used stable-isotope–labeled mice combined with quantitative mass spectrometry to screen more than 2,000 hippocampal proteins, of which 72 changed synaptic abundance up to twofold after ethanol exposure. Among those were mitochondrial proteins and proteins important for neuronal morphology, including MAP6 and ankyrin-G. Based on these candidate proteins, we found acute and lasting molecular, cellular, and behavioral changes following a single intoxication in alcohol-naïve mice. Immunofluorescence analysis revealed a shortening of axon initial segments. Longitudinal two-photon in vivo imaging showed increased synaptic dynamics and mitochondrial trafficking in axons. Knockdown of mitochondrial trafficking in dopaminergic neurons abolished conditioned alcohol preference in Drosophila flies. This study introduces mitochondrial trafficking as a process implicated in reward learning and highlights the potential of high-resolution proteomics to identify cellular mechanisms relevant for addictive behavior.

First alcohol intoxication at an early age is a critical risk factor for later alcohol bingeing and the development of alcohol addiction (1–3). College students who had their first alcohol intoxication prior to age 13 y were more than 3 times more likely to develop alcohol addiction than those with an alcohol intoxication at age 19 y or later (4, 5). The hippocampus is especially susceptible to the intoxicating effect of alcohol during peri-adolescence, and behaviors mediated by the hippocampus have long been known to be sensitive to the acute effects of ethanol (6). Yet most studies have examined the effects of chronic ethanol exposure on the hippocampus and the brain. Consequently, little is known about the acute neuronal correlates of critical risk factors such as first early-age intoxication. Here we set out to discover ethanol-dependent molecular alterations that in turn could form the basis for lasting cellular changes following a single, acute ethanol intoxication. We qualitatively define “lasting” as a plastic, cellular change that persists beyond the original ethanol stimulus. Similar to long-term potentiation (LTP), a plasticity process that experimentally persists for a few hours but is considered to be the basis for learning and memory (7), lasting changes after acute ethanol exposure could be the foundation of associative memories for drug-related rewards. Identification of lasting ethanol-dependent changes is therefore an essential first step in our understanding of how acute drinking can develop into chronic alcohol misuse.

We conducted a screen of synaptic proteomes because synapses are the main sites for neuronal transmission, plasticity, and information storage (8). Ex vivo hippocampal slices from young mice (postnatal day, P30) were used to capture the vulnerable peri-adolescent phase. We found several dozen proteins that significantly changed their synaptic abundance upon a single ethanol stimulus. Among other proteins, the screen identified cytoskeletal and mitochondrial proteins suggesting changes in neuronal morphology and mitochondrial trafficking upon single a ethanol exposure. We found that the results of the screen were robustly recapitulated in the brains of living mice as we could image and characterize changes in morphological and mitochondrial dynamics with two-photon microscopy. Intriguingly, the imaging data implied that mitochondrial trafficking and the lasting effects of ethanol could impact on ethanol-related behavior, which was separately verified in appropriate Drosophila fly and mouse behavioral tests, respectively.

Results

Identification of proteins that change their synaptic abundance upon acute ethanol exposure.

To address whether a single ethanol intoxication is sufficient to cause structural and functional changes, we wanted to identify key protein contributors of acute ethanol intoxication, investigate their influence on relevant neuronal processes, and link these processes to behavior (Fig. 1A). We used quantitative high-resolution mass spectrometry (MS) in combination with acute hippocampal (9) slices derived from stable-isotope labeling in culture (SILAC) mice (10). With SILAC (11), labeled heavy amino acids allow quantitative proteomics by measuring the peaks of the same peptides, from labeled and unlabeled samples, in one MS spectrum. In SILAC mice, all organismal lysines were metabolically replaced by stable-isotope–labeled heavy ¹³C₆-lysine (+6 Da). SILAC ethanol-treated and wild-type (WT) untreated control hippocampal slices (or vice versa) were pooled in a cross-over design (SI Appendix, Fig. S1A) prior to biochemical processing, which eliminated any potential artifacts that might arise from differences in purification efficiencies between the different experimental conditions.

Fig. 1.

Study design and quantitative MS of synaptic proteomes. (A) Study design. (B) Raw MS spectra of WT and SILAC peptides. Reproducible and significant ethanol-dependent changes in peptide abundance of a peptide (FLSDVYPDGFK) unique to PCCA. In all four experiments, ethanol exposure roughly doubled the peak height compared to untreated controls. (C) WB analysis of two candidate proteins. Actin was used as a loading control as MS results showed that the actin protein did not change between ethanol (EtOH) and untreated control (ctrl) conditions. Numbers indicate molecular weight markers. Graphs show quantifications (black dots) of two independent WB experiments for each candidate protein. The ratio of candidate protein/actin under untreated conditions was normalized to 1 for comparison with the ratio of candidate protein/actin after ethanol stimulation.

We first established a small-scale experimental purification protocol for the quantitative MS of highly purified synaptic preparations from acute slices derived from as few as two mouse hippocampi (SI Appendix, Fig. S1B). Applying stringent requirements for MS identification on the data from the ethanol cross-over experiments produced a comprehensive yet conservative estimate of 2,089 pre- and postsynaptic proteins for the hippocampal synaptic proteome (Dataset S1), including Homer, Bassoon, PSD-95, and many synaptic vesicle proteins. The number of detected proteins was in good agreement with previously published results (12).

For the MS experiments, we used 50 mM ethanol, which blocks LTP in acute hippocampal slices (13), interferes with various ion channels, and most importantly leads to intoxication (14). In cross-over experiments, this ethanol concentration (50 mM for 4 h) was administered to acute ex vivo slices from young (P30) mice and compared to control slices. As an example, Fig. 1B shows the spectra of a unique peptide of the propionyl-CoA carboxylase alpha chain (PCCA), a biotin-dependent mitochondrial enzyme, whose intensity increased similarly upon ethanol stimulation independent of whether labeled or unlabeled slices were used. Overall, in the screen we identified 57 proteins that significantly changed their level of abundance upon ethanol exposure (2.7% of 2,089) (SI Appendix, Table S1). We then conducted a second screen in acute hippocampal slices from adult mice (P210) that strongly corroborated the first screen, as more than half of the changing proteins (32 out of 57) were detected again. Both screens thus produced valuable candidate proteins for further validation, but we did not observe compelling molecular differences. In general, ethanol-induced changes that were common to both tended to be more pronounced in young mice, in which we also found more changes overall. This suggested to us that the peri-adolescent susceptibility to ethanol is potentially less a function of individual genes and proteins but more a function of cellular plasticity mechanisms that could be more pronounced in younger rather than older organisms, akin to LTP (15). We therefore shifted our focus to identifying cellular plasticity mechanisms based on the proteomic results with the hope that such mechanisms could begin to explain the development of alcohol dependence.

A total of 72 proteins from P30 and P210 animals were detected whose synaptic abundance changed significantly upon the ethanol stimulus (SI Appendix, Table S1). Western blotting (WB) for one protein that showed an increase (MAP6) and for one protein that showed a decrease (ALIX, or programmed cell death 6-interacting protein) in synaptic abundance confirmed the MS results (Fig. 1C). The values obtained by WB were in good agreement with the MS results for both proteins (MAP6↑: 2.2 [MS]/2.2 [WB]; ALIX↓: 0.76 [MS]/0.55[WB]). A gene ontology (GO) analysis revealed enrichment of adenosine triphosphate synthase and other mitochondrial functions after acute ethanol intoxication (SI Appendix, Fig. S2A).

Among the 72 changing proteins, increases in synaptic abundance ranged from a 1.25- to a 2.65-fold change and decreases ranged from a 0.85- to a 0.57-fold change. In total, 27 of the 72 candidate proteins (∼38%) that changed significantly have been previously linked to ethanol (Ethanol-Related Gene Resource [ERGR] database [16]). Among these were proteins known to be affected by acute ethanol exposure such as malate dehydrogenase (17), monoamine oxidase A (18), GAP-43 (19), and Fyn tyrosine kinase (20). Our MS data suggested that ethanol also reduced the synaptic abundance of the gamma-aminobutyric acid (GABA) reuptake transporter GAT4 (SI Appendix, Fig. S2B) and GABA transaminase (21), which catabolizes GABA. The reduction of both proteins should increase GABA signaling. An annotated, more detailed description of the identified proteins is presented in the SI Appendix. Overall, the identified proteins linked acute alcohol intoxication to alterations in synaptic transmission/plasticity, mitochondrial function, mood, apoptosis, and (neurodegenerative) diseases. In conclusion, the detected proteins support and expand literature knowledge and overlap with the ERGR, confirming the validity of our experimental approach.

We were intrigued to discover that ankyrin-G and MAP6 were among the 72 candidate proteins because both have been reported to affect spine stability (22, 23), and ankyrin-G is also a key protein for the establishment and maintenance of the axon initial segment (AIS) (24). This suggested that acute ethanol exposure may induce detectable changes in neuronal morphology. Other notable candidate proteins included several mitochondrial proteins such as PCCA, which indicated that the synaptic localization and trafficking of intact mitochondria was affected by the ethanol exposure. We therefore set out to visualize acute ethanol-dependent changes of neuronal morphology and mitochondrial trafficking in the brains of living mice by in vivo two-photon microscopy. The different conditions for all subsequent in vivo ethanol experiments are summarized in a separate subsection in the SI Appendix. Notably, we based our research on an extensive body of publications (25, 26) showing that mice have a high ethanol metabolism, which reduces blood and breath alcohol concentrations to negligible levels within 3 to 4 h, including initial ethanol doses of > 3 g/kg (27). Thus, the assumption is that any ethanol-dependent change seen 4 h after injection is reflective of a lasting effect of the initial ethanol dose.

Synaptic protein abundance changes in the primary somatosensory/motor cortex in vivo after ethanol exposure.

In preparation for the in vivo imaging experiments in the cortex, we verified that the protein candidates identified in hippocampal forebrain synapses also showed similar dynamics in cortical forebrain synapses (28). Using immunofluorescence staining, we wanted to validate ethanol-dependent synaptic protein dynamics in a cortical region readily accessible to subsequent in vivo two-photon microscopy. The expectation was that ethanol-dependent synaptic protein dynamics would subserve ethanol-dependent changes of neuronal morphology, which in turn could be detected by imaging. For this, we analyzed ethanol-dependent synaptic abundance changes in the primary somatosensory (S1)/motor (M1) cortex of intoxicated adult mice by quantifying the synaptic abundance of candidate proteins in brain sections. Previous publications also showed that both regions are known to be affected by ethanol (29, 30). We detected ethanol-induced synaptic accumulation of all three proteins that we analyzed: ankyrin-G (Fig. 2 A–D), MAP6 (Fig. 2 E–H), and PCCA (Fig. 2 I–L). Each protein significantly increased its synaptic abundance approximately 4 h after injection (Fig. 2 M–O) (P < 0.0001, Mann–Whitney U test; pooled 1 to 3 h after injection vs 4 to 24 h after injection, 3 mice each) similar to the MS results (∼1.5- to twofold) obtained with acute hippocampal slices.

Fig. 2.

Immunofluorescence detection of ethanol-dependent synaptic protein dynamics in vivo. (A–D) Images for ankyrin-G analysis. (E–H) Images for MAP6 analysis. (I–L) Images for PCCA analysis. (B) Ankyrin-G stain. (F) MAP6 stain. (J) PCCA stain. (A, E, and I) β-actin stain. (C, G, and K) Synapsin stain. Merged images (D, H, and L). Insets: high magnification of synaptic labels (green: β-actin, red: ankyrin-G/MAP6/PCCA, blue: synapsin). (M) Quantification of ankyrin-G/synapsin ratios over time, at 1, 2, 3, 4, 6, or 24 h after 3.5 g/kg ethanol i.p. injection. Each sample point corresponds to a single image as shown in this figure; each time point was based on one mouse. The y axis shows the synaptic ratio of [fluorescence intensity candidate protein]/[fluorescence intensity synapsin]. (N) Quantification of MAP6/synapsin ratios over time. (O) Quantification of PCCA/synapsin ratios over time (Scale bars, A–L, 20 µm; insets, 1 µm).

Analysis of the persistence of synaptic accumulation also showed that the abundance of ankyrin-G exhibited a more transient dynamic (Fig. 2M) compared to PCCA, which remained elevated for at least 24 h after ethanol administration (Fig. 2O) (P = 0.0028, Mann–Whitney U test; pooled 4 to 24 h ankyrin-G vs PCCA, 3 mice) while MAP6 displayed an intermediate time course (Fig. 2N). We conclude that the results obtained from the proteomics screen with ex vivo acute hippocampal slices appear to adequately reflect ethanol-related changes at central nervous system synapses in vivo, at least for those proteins that we further characterized.

Acute ethanol exposure causes changes in cortical spine dynamics in vivo.

As a next step, spine dynamics were analyzed in vivo with longitudinal two-photon time-lapse microscopy by imaging Thy1-GFP mice (31) in cortical layers II/III (32) of the S1/M1 cortex (Fig. 3A). Although we could not detect alterations in spine density at cortical synapses after ethanol administration (SI Appendix, Fig. S2C), there was a significant twofold increase in spine turnover after ethanol administration (Fig. 3B). To rule out that the rapid metabolism of ethanol in vivo diminished its effect on spine density, we blocked the activity of alcohol dehydrogenase by pyrazole in a different experiment and additionally kept the mice in ethanol vapor chambers for 4 h to maintain high blood ethanol concentrations (26). Spine densities were then analyzed in brain sections, but again we could not find any differences in spine density between the control and the ethanol-treated mice (Fig. 3C).

Fig. 3.

Neuronal in vivo ethanol-dependent morphological plasticity. (A) Longitudinal in vivo two-photon imaging of the same dendritic stretches in Thy1-GFP mice identified with stable (blue) and unstable spines (red). (B) Quantification of in vivo spine turnover from longitudinal imaging data (P < 0.05; two-way repeated measures ANOVA with Bonferroni’s multiple comparisons test; n = four mice; error bars, SD). (C) Ethanol intoxication in mice did not induce changes in cortical spine density after 4 to 6 h (six mice for each condition; all mice received pyrazole), n.s., nonsignificant. (D) Immunofluorescence detection of the AIS in layer II/III pyramidal neurons of S1 (green: βIV−spectrin; purple: NeuN) (Scale bar, 10 µm). (E) Change in AIS length over time after a single ethanol i.p. injection (3.5 g/kg ethanol); approximately 100 AIS structures were measured for each data point (P = 0.021; n = seven mice; error bars, SD). *P < 0.05.

We next addressed whether ethanol had an impact on the AIS because ankyrin-G is a key protein for its establishment and maintenance (24). The modulation of both the length and position of the AIS is an important mechanism for the regulation of intrinsic neuronal excitability in response to changes in network activity (33). The quantification of the AIS length in pyramidal neurons of layer II/III in S1 cortices (Fig. 3D) revealed a significant difference between ethanol-treated and control animals (P = 0.021, ordinary 2-way ANOVA) (Fig. 3E). This subtle effect of reduced AIS length compared to controls was seen up to 24 h, much beyond the actual presence of ethanol in the blood (26, 27).

Increased mitochondrial mobility during and after acute ethanol intoxication.

Because of the MS and in vivo immunofluorescence results (Fig. 2 I–L), we decided to image and characterize the effects of ethanol on mitochondria in the cortex by in vivo two-photon time-lapse microscopy (SI Appendix, Fig. S3A). To be able to selectively monitor and analyze mitochondria in axons and boutons, two adeno-associated viruses with mitochondria-targeted GFP (mitoGFP) and a synaptophysin-mCherry (SyPhy-mCherry) construct as a marker for boutons were broadly injected into the thalamus (SI Appendix, Fig. S3B). We chose the thalamus because some of its axons project to the cortex and run parallel to the cortical surface, which allows the visualization of multiple axons within an imaging plane. In addition, the fluorescence signal in the cortex that specifically derived from axonal projections of virally transduced thalamic neurons was sparse and suitable for imaging compared to the dense fluorescence signal at the thalamus injection site itself (SI Appendix, Fig. S3C) (34, 35).

To assess the specificity of the effects of ethanol on mitochondrial transport compared to the transport of other organelles, we also characterized dense-core vesicles (DCVs). We conducted longitudinal in vivo imaging of mitochondria and DCVs in addition to recording high-resolution cortical Z-stacks before, at 4 h, and at 24 h after intraperitoneal (i.p.) injection of either saline or ethanol (2.5 g/kg) (Fig. 4A). Time-lapse movies of 10 min were recorded in planes of layer I of M1, 50 to 100 µm away from the pial surface. The change in organelle trafficking was visualized in kymographs (Fig. 4B).

Fig. 4.

In vivo imaging of mitochondria and presynaptic boutons reveals ethanol-dependent effects. (A) For each mouse, the experiment consisted of four imaging sessions. Baseline imaging (unfilled boxes) was acquired each day. Saline (day 1, light gray arrow) and ethanol (day 3, dark gray arrow) were administered i.p. followed by postinjection imaging (filled boxes). On days 2 and 4, 24 h postinjection images were recorded. Time lapses (10 min mitochondria; 5 min DCVs) were acquired every 30 min. (B) Example of a kymograph before ethanol injection (Top); only one mitochondrion was mobile. Kymograph of the same axonal stretch 180 min after ethanol injection (Bottom). (C) Top, axonal stretch at different time points (y axis, seconds). Bottom, corresponding kymograph. (D) Left, overall mitochondrial mobility. Right, time course of mitochondrial mobility under basal conditions (light gray) and after ethanol injection (dark gray) (n = 11 focal planes from four mice; mean ± SD). (E) Left, overall DCV mobility. Right, time course of DCV mobility under basal conditions (light gray) and after ethanol injection (dark gray) (n = 3 mice; mean ± SD). (F) Bouton turnover at different time points. (G) Loss of unoccupied presynaptic boutons was significantly increased after 4 h and 24 h following ethanol injection (n = 40 axons from four mice, mean ± SD). Saline: light gray, ethanol: dark gray for all graphs. Z = Z-stack, T = time lapse. *P < 0.05, **P < 0.01, ***P < 0.001, ****P <0.0001, ns, P > 0.05, nonsignificant.

Fig. 4C shows an exemplary axonal stretch highlighting diverse aspects of axonal mitochondrial transport such as speed, direction of transport within the axon, and temporary pausing. In general, we could detect a high number of stationary mitochondria that did not move during the time-lapse (Fig. 4C, Bottom, white).

Under baseline conditions in vivo, on average 8.47 ± 4.69% of mitochondria were mobile (Fig. 4D and SI Appendix, Fig. S3D and Movie S1). The mice then received an i.p. injection of saline or ethanol, and we continued to image the same brain regions every 30 min for the following 4 h. We found that over time, ethanol-dependent mitochondrial mobility increased compared to the saline controls (P = 0.0005; 2-way repeated-measures ANOVA; F [1, 10] = 25.55) (Fig. 4D and Movie S2). Acute ethanol intoxication significantly increased mitochondrial mobility after 60 min (P = 0.0221; Bonferroni multiple comparisons test) and peaked at a twofold increase after 180 min (P < 0.0001; Bonferroni multiple comparisons test). This effect remained for at least 4 h but was not present after 24 h. In contrast to mitochondrial mobility, mitochondrial velocity remained unchanged after acute ethanol intoxication (P = 0.4601; 2-way repeated-measures ANOVA; F [9, 63] = 0.9864) (SI Appendix, Fig. S3 E–G).

To investigate whether the increase in mitochondrial transport mobility during ethanol exposure was specific for mitochondria or if it affected microtubule-based transport in general, we analyzed the movement characteristics of DCVs, which, like mitochondria, are predominantly transported via microtubules (36) (Movie S3). In contrast to mitochondrial transport, DCV transport mobility was not affected by ethanol intoxication (P = 0.5489; 2-way repeated-measures ANOVA; F [1, 2] = 0.5109) (Fig. 4E). Similar to mitochondrial velocities, ethanol likewise did not increase DCV velocities (P = 0.6427; 2-way repeated-measures ANOVA; F [1.488, 2.976] = 0.4128) (SI Appendix, Fig. S3 H–J). Analyses of DCV mobility under ethanol thus served as a control to highlight the specific effect of ethanol on mitochondrial mobility.

Effects of higher mitochondrial mobility on occupancy of presynaptic boutons.

Because of the increased dislocation (SI Appendix, Fig. S3K) and higher mobility of mitochondria under ethanol, we next investigated whether these factors affected the dynamics of mitochondria occupancy within presynaptic boutons. In addition, dedicated bouton analyses strengthened our efforts to detect morphological changes after ethanol exposure. Fluorescence colocalization of the mitoGFP signal with SyPhy-mCherry (SI Appendix, Fig. S4A) was extracted from high-resolution Z-stacks at defined time points (Fig. 4A). We found that 80.5 ± 9.1% of the presynaptic boutons on thalamic axons were occupied by mitochondria (SI Appendix, Fig. S4B), whereas other studies reported occupancy numbers between 42 and 60% in axons in other neuron types and regions (37, 38). Four hours after ethanol injection, we detected a small decrease in presynaptic mitochondrial occupancy (SI Appendix, Fig. S4B, Right), which returned to baseline levels within 24 h.

Analyzing the diameter of presynaptic boutons revealed that occupied stable boutons (1.25 ± 0.48 µm SD) were significantly larger (P < 0.0001; Kruskal–Wallis test with Dunn’s multiple comparison test) than unoccupied (0.89 ± 0.3 µm SD) or newly formed occupied boutons (0.91 ± 0.24 µm SD) (SI Appendix, Fig. S4C). We also analyzed mitochondrial shapes and found that ethanol did not affect mitochondrial length (SI Appendix, Fig. S4 D and E). Next, we wanted to see if we could detect ethanol-dependent morphological changes at presynaptic boutons. Because we repeatedly imaged the same axonal stretches, we could clearly designate gained or lost boutons while also being able to identify boutons with gained or lost mitochondria (SI Appendix, Fig. S5 A–C). Bouton turnover was subgrouped into newly gained (appeared during any of the imaging time points) or lost (present during baseline imaging that day but disappeared during later timepoints) presynaptic boutons at different time points (4 h, 24 h) (Fig. 4F; graph to show distribution for each mouse separately in SI Appendix, Fig. S6A). Ethanol specifically and significantly increased the rate of bouton loss after 24 h in the ethanol condition (2-way repeated-measures ANOVA with Bonferroni multiple comparisons test; P = 0.0023 and F [1, 78] = 9.894 for interaction between condition and time; difference between ethanol and saline: P = 0.0508, F [1, 78] = 3.936). In unoccupied boutons, ethanol significantly increased the rate of loss compared with the saline condition (P = 0.007; 2-way repeated-measures ANOVA; F [1, 78] = 7.683) (Fig. 4G; graph to show distribution for each mouse separately in SI Appendix, Fig. S6B). This effect was significantly higher 24 h after ethanol compared to 4 h (P = 0.0011; Bonferroni multiple comparison test) and also different after 24 h between saline- and ethanol-treated animals (P = 0.0027; 2-way repeated-measures ANOVA with Bonferroni multiple comparisons test). In addition, ethanol possibly affected the loss of occupied boutons (P = 0.0072 for difference between 4 and 24 h in the ethanol condition; no difference between groups or interaction of time and group in a 2-way repeated-measures ANOVA with Bonferroni correction for multiple comparisons, F [1, 78] = 0.05087) but not the formation of either unoccupied or occupied boutons (SI Appendix, Fig. S6 C–E). Thus, ethanol exposure induced significant structural plasticity in presynaptic boutons and, analogous to the AIS, lasting morphological changes existed at least up to 24 h after injection.

Because we observed lasting changes beyond 4 h and up to 24 h in the form of molecular (PCCA) and cellular (AIS, boutons, mitochondria trafficking) correlates of acute ethanol intoxication, we wondered if these effects were mirrored by lasting changes in ethanol-related behaviors. For this purpose, we conducted a Go/NoGo task in mice, which is a measure for behavioral control and is strongly affected by acute alcohol intoxication (39). Naïve mice were first trained in a standard Go/NoGo task until they reached a designated performance level. The mice were then i.p. injected with 3.5 g/kg ethanol and their performance was assessed at 4 to 6 h, 24 h, and 48 h following injection. We found that at all time points after intoxication, mice exhibited significantly reduced performances in the correct go, false alarm, efficacy, or performance rate (SI Appendix, Fig. S7 A–D). Taken together, animals showed a postintoxication effect of ethanol on behavioral inhibition, suggesting that one dose of ethanol is sufficient to cause lasting behavioral alterations for at least 48 h.

Mitochondrial trafficking is required to mediate positive rewarding properties of ethanol in dopaminergic neurons in Drosophila flies.

The robust effects of ethanol on mitochondrial trafficking identified this cellular process as potentially relevant to regulate changes of neuronal plasticity underlying ethanol-induced behaviors. Because the dopaminergic reward system is conserved across animals from flies to humans, we took advantage of available genetic tools in Drosophila flies to test whether proper mitochondria trafficking is necessary for mediating the positive reinforcing effect of ethanol in dopaminergic reward neurons. Using the GAL4 transgene expression system (40), we therefore altered mitochondria trafficking in Drosophila melanogaster by knockdown of Miro/milton/kinesin complex proteins required for axonal mitochondria transport (41, 42) and analyzed the consequences on ethanol-mediated reward learning and memory. In adult flies, a subset of dopaminergic neurons targeted by the Tyrosine hydroxylase (TH)-Gal4 driver mediates the positive rewarding properties of ethanol (43). We expressed an RNA interference (RNAi) construct of miro, UAS-dmiro-RNAi^TRiPJF02775 under the control of the dopaminergic neuron-specific TH-Gal4 driver. We then tested the experimental and the respective control groups in an olfactory associative learning and memory paradigm using ethanol as a positive reinforcer (SI Appendix, Fig. S8A).

First, we verified that none of the olfactory stimuli were preferred and that the flies perceived the conditioned stimuli equally (SI Appendix, Table S2). Following the reinforcement conditioning, flies were given a choice in a T-maze between the rewarded odor cue and the nonrewarded odor cue. Consistent with previous results, control-conditioned flies significantly preferred the ethanol associated odor over the nonassociated odor cue. However, RNAi-mediated knockdown of Miro in dopaminergic neurons significantly reduced the positive association between the olfactory stimulus and ethanol (Fig. 5A). RNAi-mediated knockdown of Milton in dopaminergic neurons also resulted in a significant loss of the positive association with ethanol (Fig. 5B). To address whether the observed learning defect is specific to alcohol-associated learning, 2 M sucrose was used instead as a positive reinforcer in control appetitive experiments (44) (SI Appendix, Fig. S8 B and C). We found that knockdown of Miro or Milton in dopaminergic neurons did not change the attraction for the reinforced odorant with either short-term or long-term memory forms. Flies exhibited normal sugar responsiveness in all experimental conditions. We conclude that Milton-/Miro-dependent mitochondrial trafficking is relevant to neuronal plasticity and specifically mediates the positive rewarding properties of ethanol in dopaminergic neurons.

Fig. 5.

The function of ethanol as positive reinforcer in dopaminergic neurons depends on Miro and Milton. (A) The expression of UAS-dmiro-RNAi^TRiPJF02775 under the control of the TH-Gal4 driver resulted in the loss of CPI (conditioned odor preference index). The mean of the CPI was for TH-Gal4/+: 0.22 ± 0.07; UAS-dmiro-RNAi/+: 0.21 ± 0.04 and for the experimental group −0.05 ± 0.07. (B) The expression of the UAS-milton-RNAi^GD8116 and UAS-milton-RNAi^TRiPJF03022 under the control of the TH-Gal4 driver resulted in loss of CPI. The mean of the CPI was for TH-Gal4/+: 0.37 ± 0.08, UAS-milton-RNAi^GD8116/+: 0.31 ± 0.04 and for the experimental group 0.05 ± 0.06 and TH-Gal4/+: 0.32 ± 0.07; for UAS-milton-RNAi^TRiPJF03022/+: 0.19 ± 0.03 and for the experimental group −0.01 ± 0.06. The letter “a” indicates significant differences from random choice as determined with the 1-sample sign test. Differences between groups were determined using ANOVA posthoc Tukey–Kramer HSD (honestly significant difference) (Error bars, SEM).

Discussion

We studied short-term and lasting molecular and cellular correlates of a single intoxicating exposure to ethanol. High-resolution quantitative MS achieved the detection of acute ethanol-dependent synaptic proteome changes, which revealed several dozen proteins including a cluster of mitochondrial proteins and two structural proteins, MAP6 and ankyrin-G, that are important for spine stability and formation of the AIS. For comparison, only a handful of proteins have been identified to date whose synaptic abundance reproducibly increased or decreased following any stimulus, including LTP (45, 46). By comparing the proteomics results of P30 with P210 animals, we hoped to find obvious candidate proteins that could begin to explain the susceptibility of peri-adolescence to alcohol. Instead, the ethanol-dependent changes in synaptic abundance tended to occur more often in slices from P30 animals and tended to be more pronounced compared to P210. We therefore focused on the identification of cellular mechanisms rather than individual genes as possible mediators of ethanol reward memories.

We demonstrated with longitudinal two-photon time-lapse microscopy in vivo 1) a twofold increase in spine turnover and increased elimination of presynaptic boutons after acute ethanol administration, indicative of increased structural plasticity, and 2) a pronounced increase in mitochondrial mobility after acute ethanol intoxication. In addition, ethanol-treated animals exhibited a significantly reduced AIS length compared to controls, a decrease that persisted at least up to 24 h after ethanol injection. Heightened neuronal activity has been reported to decrease AIS length (47). One conceivable interpretation of our AIS data is based on published observations showing that acute ethanol rapidly decreases cortical activity (48, 49). Consequently, the lasting homeostatic AIS changes are possibly reflective of ensuing network hyperactivity because ethanol was rapidly metabolized following the initial ethanol-dependent silencing of neurons. Such a scenario would have to be confirmed by carefully quantifying neuronal activity at different time points in vivo following an ethanol stimulus. Besides the AIS, synapses also showed lasting ethanol-dependent structural remodeling as changes in bouton turnover continued up to 24 h. Although subtle, these observed morphological alterations could thus be interpreted as a lasting, adaptive homeostatic response to a single ethanol stimulus, which has been reported for chronic ethanol exposure as well (50, 51).

Morphological remodeling of neurons is a known substrate for learning and memory, as increased spine and bouton turnover has been found to be associated with memory formation (52, 53). Cellular plasticity mechanisms that are central to learning and memory are likewise considered to be at the core of forming associative memories for drug-related rewards (54). Thus, some of the ethanol-dependent morphological changes we observed could potentially influence ethanol-related memory formation by distorting the synaptic connectivity balance between spines and boutons. Together with the trafficking of mitochondria, which are known to be important for synaptic transmission and plasticity, one may therefore speculate that these ethanol-dependent cellular changes are crucial substrates for the development of addictive behavior. We found that the observed changes were indeed of behavioral relevance. We tested this idea by blocking mitochondrial trafficking in a well-described model of ethanol reward in adult Drosophila. Similar to mice and humans, the formation of positive memories associated with ethanol intake is dependent on dopaminergic neurons in the Drosophila model. Knockdown of either of the two known mitochondrial adaptor proteins, Miro and Milton, in dopaminergic neurons eliminated the preference for odor cues specifically associated with ethanol intoxication. The importance of mitochondrial trafficking in the Drosophila model was suggested by results from in vivo mouse brain imaging. Thus, it is remarkable that there is a cross-species conservation of cellular processes that contribute to such a complex reward behavior and consequently suggests a similar role in humans. In conclusion, we introduce enhanced mitochondrial mobility and dynamics in presynaptic boutons as a key cellular mechanism that underlies alcohol reward learning, and perhaps more important, a possible general cellular process essential for learning and memory (55, 56).

Both observed mechanisms, i.e., lasting homeostatic structural remodeling and mitochondrial trafficking, may account for the observations made in mice that a single exposure to an intoxicating dose of ethanol can increase alcohol consumption and alcohol relapse later in life (57, 58). Similar to the conservation of mitochondrial trafficking, these mechanisms may even be of relevance for the observation in humans that an early age of first alcohol intoxication is a critical risk factor for later alcohol bingeing and the development of alcohol addiction (1–3).

Materials and Methods

A full description of materials and methods is available in the SI Appendix. SILAC mice were generated by adding stable-isotope Lys6 to lysine-free chow. Acute hippocampal slices from SILAC mice and matched controls were exposed to 50 mM ethanol (4 h), and synaptic proteomes were extracted with Triton-X from synaptosomes. MS analyses were performed with an LTQ-Orbitrap and quantification of protein abundance with the MaxQuant software. Following in vivo ethanol exposure, immunofluorescence detection of synaptic protein dynamics and AIS changes were conducted on brain slices of the S1/M1 cortex. Head-fixed longitudinal two-photon imaging was performed under anesthesia after cranial window implantation. Ethanol-dependent changes in spine morphology were assessed with Thy1-GFP mice. Virus-mediated fluorescence labeling of mitochondria and DCVs of thalamic neurons allowed imaging of axonal trafficking in projections to the cortex after ethanol administration. In Drosophila flies, the GAL4 system and RNAi knockdown were used to interfere with mitochondrial trafficking in dopaminergic neurons. Following ethanol-conditioned odor preference training, the odor preference of transgenic flies was assessed in a binary choice T-maze.

Data Availability

MS/proteomics data have been deposited in Heidata (https://heidata.uni-heidelberg.de/privateurl.xhtml?token=f88c8325-6f37-473d-856a-0af8109a2bba) (59).

Change History

July 22, 2022: The article has been updated to include the corresponding author’s main affiliation.