Protein profiling in the habenula after chronic (–)-menthol exposure in mice

Abstract

The identification of proteins that are altered following nicotine/tobacco exposure can facilitate and positively impact the investigation of related diseases. In this report, we investigated the effects of chronic (–)-menthol exposure in fourteen murine brain regions for changes in total β2 subunit protein levels and changes in epibatidine binding levels using immunoblotting and radioligand binding assays. We identified the habenula as a region of interest due to the region’s marked decreases in β2 subunit and nAChR levels in response to chronic (–)-menthol alone. Thus, we further examined the habenula, a brain region associated with both the reward and withdrawal components of addiction, for additional protein level alterations using mass spectrometry. A total of 552 proteins with altered levels were identified after chronic (–)-menthol exposure. Enriched in the proteins with altered levels after (–)-menthol exposure were proteins associated with signaling, immune systems, RNA regulation, and protein transport. The continuation and expansion of the brain region-specific protein profiling in response to (–)-menthol will provide a better understanding of how this common flavorant in tobacco and e-liquid products may affect addiction and general health.

Graphical Abstract

In this report, we investigated the effects of chronic (–)-menthol in fourteen murine brain regions for changes in total β2 subunit protein levels and changes in epibatidine binding levels using immunoblotting and radioligand binding assays. We identified the habenula as a region of interest due to its marked decreases in β2 subunit and nAChR levels in response to chronic menthol alone. Using mass spectrometry, we further identified 552 proteins with additional protein level alterations in the habenula, a brain region associated with both the reward and withdrawal components of addiction.

Introduction

Nicotinic acetylcholine receptors (nAChRs) are pentameric cation channels expressed in the mammalian central nervous system (CNS), in the peripheral nervous system, and in skeletal muscle. Eleven neuronal nAChR subunits have been identified in mammals (α2–7, α9–10, β2–4), in addition to the five subunits expressed in skeletal muscle (α1, β1, γ, δ and ε). Receptors containing α4β2, α3β4 and α7 nAChR subunits are the most prevalent in the mammalian CNS (Albuquerque et al. 2009). The levels of nAChRs and nAChR subunits upregulate in response to chronic nicotine exposure, and in many cases, this is accompanied by a change in nAChR assembly/stoichiometry. The magnitude of the change and the receptor subunits/subtypes involved are cell-specific and brain region-specific (Marks et al. 2011; Alsharari et al. 2015).

Menthol is a flavor additive in tobacco products, e.g., menthol cigarettes or menthol e-liquids. A previous study demonstrated that human menthol cigarette smokers have elevated β2 nAChR subunit containing nAChRs (β2* nAChRs) in the cortex, brainstem, and corpus callosum compared to non-menthol smokers (Brody et al. 2013). In mouse models, (–)-menthol alone, administered chronically via intraperitoneal injection, increased α4 nAChR subunit levels in the striatum and prefrontal cortex, as well as β2 nAChR subunit levels in the hippocampus, prefrontal cortex, and striatum. When menthol is injected into mice receiving chronic nicotine via osmotic minipumps, β2 nAChR subunit levels are increased in the murine cortex, but not murine striatum or hippocampus, compared to nicotine treatments alone (Alsharari et al. 2015). Receptors containing α4 or α6 nAChR subunits (α4* & α6* nAChRs) with conjugated fluorescent labels upregulate in midbrain dopaminergic neurons, but not GABAergic neurons after chronic (–)-menthol exposure using osmotic minipumps (Henderson et al. 2016).

Chronic nicotine exposure upregulates β2* nAChRs on the subunit, receptor, and functional levels in a region-specific manner (Mulcahy et al. 2020; Marks et al. 2011; Govind et al. 2009). Like the effects of nicotine, the effects of menthol on either receptor or subunit levels are highly CNS region-specific and are stereoisomer specific (i.e. (+)-menthol vs. (–)-menthol) (Henderson et al. 2018; Mulcahy et al. 2020). We previously investigated the effects of chronic nicotine, (±)-menthol, and nicotine plus (±)-menthol co-application administered via osmotic minipump on β2 subunits and total membrane proteins (Mulcahy et al. 2020). Of the nine regions investigated, we identified two brain regions, the cortex and hypothalamus, that had altered β2 subunit levels when nicotine was co-applied with (±)-menthol (a model of mentholated cigarette smoke exposure) compared to nicotine alone (a model of non-mentholated cigarette exposure). The hypothalamus was further protein profiled using mass spectrometry to identify additional proteins with altered expression.

In our present study, we provide a comprehensive investigation of β2 subunit levels, nAChR levels, and region-specific changes in protein levels in response to chronic (–)-menthol exposure. Our present study shares similarities with our previous study of (±)-menthol, but with several key differences. First, we expanded our analysis from nine to fourteen brain regions, with the addition of the inferior colliculus, interpeduncular nucleus (IPN), habenula, olfactory bulbs, and superior colliculus. Second, in addition to measuring β2 subunit levels, we also measured epibatidine binding to determine changes in receptor levels after chronic drug treatments. Several of the regions added to our investigation include high numbers of non-α4β2 nAChRs (habenula, IPN, & superior colliculus). Since receptor subtypes have differential sensitivity to cytisine, cytisine-sensitivity and cytisine-resistance to epibatidine binding was also measured (Whiteaker et al. 2000b). Third, we used quantitative mass spectrometry to identify membrane protein profile changes in the habenula, the only region identified with changes in β2 subunits, cytisine-sensitive epibatidine binding, and cytisine-resistant epibatidine binding. Lastly, with the emergence and medical relevance of electronic nicotine delivery systems (ENDS) and zero-nicotine e-liquids, we not only transitioned from using (±)-menthol to (–)-menthol, but also shifted our paradigm from proteomic changes between nicotine vs. menthol plus nicotine to focus on proteomic changes in response to menthol alone (Figure 1). This multifaceted approach enabled the investigation of nicotinic tone (i.e., nicotinic subunit and assembled nAChR levels) in fourteen brain regions as well as total membrane protein level changes in a select brain region after chronic to (–)-menthol treatment.

Figure 1:

Experimental design. Male C57/Bl6 mice were chronically exposed to vehicle or (−)-menthol for 10 to 12 days using osmotic minipumps. Mice were euthanized using CO₂ inhalation, followed by cervical dislocation, and their brains removed for further dissection into sub-regions. Solubilized membrane protein extracts and purified homogenates were prepared for each region. Protein samples were then queried for changes in protein expression in response to drug treatments using immunoblotting (β2 subunit), radioligand binding (nAChR), or mass spectrometry (proteome).

There is a rich diversity of nAChR subtypes distributed throughout the mammalian CNS. These subtypes are characterized and distinguished by their sensitivity to various ligands, and demonstrate different pharmacology, physiology, and localization throughout the brain. Our goal for this study was to continue to characterize and refine our understanding of how nAChRs respond to chronic administration of drugs of abuse in specific brain regions, such as the habenula. Only by investigating multiple regions can we begin to understand how nAChR subunit and receptor level changes are localized and how they might contribute to various aspects of nicotine and tobacco addiction.

Methods

Study design.

This study was not pre-registered. No randomization was performed to allocate subjects in the study. The experimenters were blinded to the drug administered (vehicle or (–)-menthol) until experiments were complete and data were analyzed. Five menthol-exposed and five vehicle-exposed mice were used for immunoblots and mass spectrometry analysis (n=5). An additional five menthol-exposed and five vehicle-exposed mice were used for radioligand binding (n=5). After experiments were complete, the experimenters were un-blinded by the animal technician who performed the surgical implants. No predetermined sample size calculation was performed. The sample size was based on previous studies of a similar nature (Alsharari et al. 2015; Mulcahy et al. 2020).

Animal care.

All procedures were conducted in accordance with the National Institutes of Health guidelines for care and use of animals, and protocols were approved by the Institutional Animal Care and Use Committee (IACUC) at the California Institute of Technology (protocol 1386–13G). All mice in the study were housed in a dual chamber mouse cage type with 2–3 companions per chamber, with ad libitum access to food and water. Inclusion criteria were the health of the mice and the length of their drug administration. Exclusion criteria were any unanticipated signs of ill health, >15% weight loss, >10% dehydration, lethargy, difficulty ambulating, unalleviated pain or distress, frequent seizure activity, or abnormal behavior. No mice were excluded based on the exclusion criteria and no mice died during experiments.

Drug administration using osmotic minipumps.

Male C57/Bl6 mice (original source Charles River Laboratories), 2.5 to 3.5 months of age and with weights of 20 to 32 grams were used. As an extension of a previous study which used male mice alone, the decision was made to maintain the same gender selection for this study. However, in future studies it would be valuable to investigate the effects and self-administration of menthol in both male and female mice as there is evidence that menthol cigarette usage differs between men and women (Smith et al. 2017). The selected method of (–)-menthol delivery and dose were established as relevant to human intake and described previously (Henderson et al. 2014; Henderson et al. 2016). In brief, osmotic minipumps (Alzet, cat. no. 1002) were implanted under the skin for 10 to 12 days (pre-specified endpoint) to deliver vehicle (60 % ethanol, 40 % saline) or (–)-menthol (2 mg/kg/hr). All subsequent experimentation/analyses were blinded. In accordance with accepted guidelines by IACUC, mice were anesthetized with 1.5 to 2.5% isoflurane via a face mask; 1 mg/kg of bupivacaine and 5 mg/kg of ketoprofen were also administered subcutaneously. For 3 days post operation, mice were given 30 mg/kg of ibuprofen orally to minimize animal suffering. For each experimental group, 10 mice were analyzed (Figure 1).

Mouse brain tissue dissection and collection.

After drug administration, mice were euthanized using CO₂ inhalation in box with a metered dose of 1.5 liters per minute, followed by cervical dislocation. The brains of 20 male C57Bl/6 mice were isolated and immediately dissected on ice. All brains were serially dissected to isolate specific brain regions and frozen at −80°C immediately after dissection.

Mouse brain membrane lysate and membrane protein solubilization.

Dissected mouse brain regions were homogenized in homogenization buffer (50 mM NaCl, 50 mM NaH₂PO₄, 2 mM EDTA, 2 mM EGTA, pH 7.4) on ice with 30 strokes of a Potter-Elvehjem glass homogenizer or disposable polypropylene pestles depending on the size of the region. Membrane fragments were isolated following centrifugation at 21,130 x g for 10 minutes at 4 °C. Membrane pellets were then homogenized in solubilization buffer (50 mM NaCl, 50 mM NaH₂PO₄, 2 mM EDTA, 2 mM EGTA, 2% Triton X-100, pH 7.4) with 40 strokes of a Potter-Elvehjem glass homogenizer or disposable polypropylene pestles and incubated for three hours at 4 °C with agitation to solubilize membrane-bound proteins. Following a second centrifugation at 21,130 x g for 10 minutes at 4 °C, the solubilized membrane fraction was recovered in the supernatant.

All buffers used to isolate the solubilized membrane fraction were supplemented with protease/phosphatase inhibitors (Cell Signaling Technology, cat. no. 5872). Protein content of solubilized membrane fractions was determined using a BCA assay (Thermo Scientific, cat. no. 23225).

Mouse brain purified homogenate preparation.

Dissected mouse brain regions were homogenized in ice cold hypotonic 0.1x KRH buffer (144 mM NaCl, 2.2 mM KCl, 2 mM CaCl₂, 1 mM MgSO₄, and 25 mM HEPES, pH 7.5) with 30 strokes of a Potter-Elvehjem glass homogenizer or disposable polypropylene pestles on ice. Membrane fragments were isolated following centrifugation at 21,130 x g for 10 minutes at 4 °C. Pellets were washed three more times with 0.1x KRH to remove substances that could compete with epibatidine binding.

All buffers were supplemented with protease/phosphatase inhibitors (Cell Signaling Technology, cat. no. 5872). Protein content of the washed homogenates were determined using a BCA assay (Thermo Scientific, cat. no. 23225).

β2 nAChR subunit immunoblotting.

Detergent solubilized membrane preparations (3 μg protein per lane) from each dissected brain region were used for immunoblotting. Samples were incubated at 95 °C for 5 minutes in 1x Laemmli sample buffer and 355 nM β-mercaptoethanol (Bio-Rad, cat. no. 1610747 and 1610710XTU) to reduce disulfide bonds. The pH of each sample was adjusted with 1M Tris base and alkylated using 100 mM iodoacetamide at room temperature for 1 hour in the dark. Proteins were separated by SDS-PAGE (Bio-Rad, cat. no. 4568106) and transferred to Immun-Blot^® low fluorescence polyvinylidene difluoride membranes (Bio-Rad, cat. no. 1620261). Membranes were blocked using Odyssey^® Tris buffered saline (TBS) blocking buffer (Li-Cor, cat. no. 927–50000) for 1 hour at room temperature (20–25 °C). Membranes were incubated with goat anti-β2 subunit antibodies (1:100, RRID:AB_2080867) and rabbit anti-GAPDH antibodies (1:1,000, RRID:AB_307275) diluted in Odyssey^® TBS blocking buffer supplemented with 0.1 % Tween-20^® (Sigma-Aldrich, CAS no. 9005–64-5) (“antibody buffer”) overnight at 4 °C. After washing, the membrane was incubated with anti-goat secondary antibodies (1:5,000, RRID:AB_10956736) and anti-rabbit secondary antibodies (1:15,000, RRID:AB_621848) in antibody buffer. The membrane was then washed, and targeted proteins visualized using an Odyssey^® scanner (Li-Cor, cat. no. 9120).

Radiolabeled epibatidine binding.

Aliquots of tissue homogenates (between 0.2 and 70 μg protein depending on region) were added to wells of 48-well plates containing 400 pM ¹²⁵I-epibatidine or ³H-epibatidine and allowed to bind to equilibrium (2 hrs) (Marks et al. 1998). Cytisine-sensitive binding was assessed with the addition of 150 nM cytisine. Nonspecific binding was determined with 10 μM nicotine in control wells. Samples were aspirated onto a A/E glass filter sheet (PALL) and washed several times with 1.0x KRH buffer using a 48-well head Inotech Cell Harvester (Connectorate AG, model no. 1H-110–96S-501–502-182–174-3). Following washes, the Cell Harvester was used to cut the filter sheet into 48 separate filters and to isolate each sample. Filters were incubated with CytoScintES scintillation fluid (MP Biochemicals, cat. no. 01882453-CF) overnight and measured using a scintillation counter the following day (Beckman Coulter, cat. no. LS 6000SC). For each individual tissue sample, total binding was measured in triplicate, cytisine-sensitive binding in duplicate or triplicate, and nonspecific binding in duplicate. For both conditions, radiolabeled epibatidine binding levels in each brain region were assessed with 5 individual tissue samples (n=5).

Mass spectrometry sample preparation and in-solution trypsin digestion.

To prepare for mass spectrometric analysis, 75 μg protein samples were thawed, and disulfide/sulfhydryl residues were reduced with 50 mM TCEP in 20 mM HEPES, pH 8.0 for 1 h at 60 °C. Samples were alkylated with 100 mM iodoacetamide in 20 mM HEPES, pH 8.0 for 1 h in the dark at room temperature (20–25 °C). Samples were then concentrated and purified via precipitation using a ReadyPrep™ 2-D Cleanup Kit (Bio-Rad, cat. no. 1632130). Precipitated protein was resuspended in 50 mM ammonium bicarbonate, pH 7.8 supplemented with 100 ng trypsin (Promega, cat. no V5280) and digested overnight in-solution at 37 °C. Following digestion, samples were dried and stored at −20 °C until analysis.

Tandem mass tag (TMT) labeling.

TMT labeling and subsequent mass spectrometry analysis was performed using the SL-TMT sample process strategy (Navarrete-Perea et al. 2018). Briefly, TMT reagents (0.8 mg) were dissolved in anhydrous acetonitrile (40 μL) of which 10 μL was added to the peptides (100 μg) along with 30 μL of acetonitrile to achieve a final acetonitrile concentration of approximately 30% (v/v). Following incubation at room temperature for 1 h, the reaction was quenched with hydroxylamine to a final concentration of 0.3% (v/v). The TMT-labeled samples were pooled at a 1:1 ratio across all channels. The sample was vacuum centrifuged to near dryness and subjected to C18 solid-phase extraction (Sep-Pak, Waters, cat. no. WAT036820).

Basic pH reversed-phase (BPRP) fractionation allowed for deep proteome analysis.

A total of 100 μg of peptide from each of the channels were combined, desalted, and fractionated with basic pH reversed-phase (BPRP) chromatography. Following desalting, peptides were resuspended in buffer A (10 mM ammonium bicarbonate, 5% acetonitrile, pH 8) and loaded onto an Agilent 300 Extend C18 column (5 μm particles, 4.6 mm ID and 220 mm in length). The peptide mixture was fractionated with a 60 min linear gradient from 0% to 42% buffer B (10 mM ammonium bicarbonate, 90% acetonitrile, pH 8). A total of 96 fractions were collected and concatenated so that every 24^th fraction was pooled (i.e., samples in wells A1, C1, E1, and G1 were combined) and only alternating pooled fractions (a total of 12) were analyzed (Paulo et al. 2016a).

Liquid chromatography (LC) and tandem mass spectrometry (MS).

The samples were reconstituted in 5% acetonitrile and 5% formic acid for LC-MS/MS processing. Peptides were separated on a 35 cm long, 100 μm inner diameter microcapillary column packed with Accucore (2.6 μm, 150Å) resin (ThermoFisher Scientific, cat. no. 16126). For each analysis, 0.5 μg of the sample was loaded onto a C18 capillary column using a Proxeon NanoLC-1200 UHPLC. Peptides were separated in-line with the mass spectrometer using gradients of 6 to 26% acetonitrile in 0.125% formic acid at a flow rate of ~500 nL/min. Data was collected using the SPS-MS3 method on an Orbitrap Fusion Lumos mass spectrometer (Thermo Scientific, RRID:SCR_020562). Peptides were separated using a 150min gradient of 3 to 25% acetonitrile in 0.125% formic acid with a flow rate of 450 nL/min. Each analysis used an MS3-based TMT method (Ting et al. 2011; McAlister et al. 2014), which has been shown to reduce ion interference compared to MS2 quantification (Paulo et al. 2016b). Prior to starting our analysis, we performed two injections of trifluoroethanol to elute any peptides that may have been bound to the analytical column from prior injections to limit carry over. The scan sequence began with an MS1 spectrum (Orbitrap analysis, resolution 120,000, 350−1400 Th, automatic gain control (AGC) target 5E5, maximum injection time 100 ms). The top ten precursors were then selected for MS2/MS3 analysis. MS2 analysis consisted of: collision-induced dissociation (CID), quadrupole ion trap analysis, AGC 1.8E4, normalized collision energy (NCE) 35, q-value 0.25, maximum injection time 120 ms), and isolation window at 0.7. Following acquisition of each MS2 spectrum, we collected an MS3 spectrum in which multiple MS2 fragment ions are captured in the MS3 precursor population using isolation waveforms with multiple frequency notches. MS3 precursors were fragmented by higher-energy C-trap dissociation and analyzed using the Orbitrap (NCE 65, AGC 1.5E5, maximum injection time 150 ms, resolution was 50,000 at 400 Th). For MS3 analysis, we used charge state-dependent isolation windows: for charge state z=2, the isolation window was set at 1.3 Th, for z=3 at 1 Th, for z=4 at 0.8 Th, and for z=5 at 0.7 Th.

Database searching and TMT quantification analysis.

Mass spectra were processed using a SEQUEST-based software pipeline (Huttlin et al. 2010). Database searching included all entries from the Uniprot mouse database (March 20, 2016). This database was concatenated with one composed of all protein sequences in the reversed order. Searches were performed using a 50 ppm precursor ion tolerance. The product ion tolerance was set to 0.9 Da. These wide mass tolerance windows were chosen to maximize sensitivity in conjunction with SEQUEST searches and linear discriminant analysis (Beausoleil et al. 2006; Huttlin et al. 2010). TMT tags on lysine residues and peptide N termini (+229.163 Da) and carbamidomethylation of cysteine residues (+57.021 Da) were set as static modifications, while oxidation of methionine residues (+15.995 Da) was set as a variable modification.

Peptide-spectrum matches (PSMs) were adjusted to a 1% false discovery rate (FDR) (Elias & Gygi 2010; Elias & Gygi 2007). PSM filtering was performed using a linear discriminant analysis, as described previously (Huttlin et al. 2010), while considering the following parameters: XCorr, ΔCn, missed cleavages, peptide length, charge state, and precursor mass accuracy. For TMT-based reporter ion quantitation, we extracted the signal-to-noise (S:N) ratio for each TMT channel and found the closest matching centroid to the expected mass of the TMT reporter ion. PSMs were identified, quantified, and collapsed to a 1% peptide FDR and then collapsed further to a final protein-level FDR of 1%. Moreover, protein assembly was guided by principles of parsimony to produce the smallest set of proteins necessary to account for all observed peptides.

Peptide intensities were quantified by summing reporter ion counts across all matching PSMs so as to give greater weight to more intense ions (McAlister et al. 2014; McAlister et al. 2012). PSMs with poor quality, MS3 spectra with TMT reporter summed signal-to-noise measurements that were less than 100, or with no MS3 spectra were excluded from quantitation. Isolation specificity of ≥ 0.7 (i.e., peptide purity >70%) was required (McAlister et al. 2012).

Post-search data analysis.

(–)-menthol treated habenula were analyzed with five biological replicates. Samples were split into several groups for TMT labeling and analysis. Changes in specific protein levels after (–)-menthol exposure were normalized to the same vehicle protein levels in each group and then compared to the other group. Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) (v. 11, RRID:SCR_005223) was used to visualize hypothalamic proteomes and the results of the comparisons, and to illustrate known connections between identified interacting proteins (Szklarczyk et al. 2015). All statistically significant protein level differences were evaluated to identify protein enrichments for biological processes (Gene Ontology “GO” terms) or pathways (Reactome pathway analysis).

Statistical analysis.

For immunoblot data, five vehicle and five (–)-menthol treated dissected brain regions were analyzed with five separate blots. One vehicle and one (–)-menthol treated sample for the same brain region were measured in parallel on the same gel, each with three technical replicates per gel. All β2 immunoreactivity signals were normalized to GAPDH. For each blot, the average β2 immunoreactivity was normalized to the average vehicle immunoreactivity. Observed β2 immunoreactivity for all immunoblots was quantified as a percent change from vehicle values. Specificity of the β2 subunit antibody has previously been demonstrated (Mulcahy et al. 2020). A Student’s t-test (two-tailed, two-sample equal variance) was used to identify statistically significant changes between treatment groups for immunoblotting and epibatidine binding experiments (significance level p ≤ 0.05). For analyzing changes in proteins identified by mass spectrometry, vehicle-treated (n=5) or menthol-treated (n=5) habenula were compared. Samples were split into multiple groups for TMT labeling and analysis. Log₂ changes in TMT signals for each protein observed after (–)-menthol exposure tissue were compared to the average TMT signal for vehicle tissue analyzed in that group. Proteins identified were initially sorted by which identifications where all replicates demonstrated a change in the same direction (i.e., the TMT signal for all five replicates was greater than, or less than 0). A Student’s t-test (one-tailed, two-sample equal variance) was used to identify statistically significant changes between treatment groups (significance level p ≤ 0.05). Statistical significance for all analyses was performed using Microsoft Excel (updated July 2021, version 2106). Due to the small sample size typical for animal experiments of this type, no formal tests for normality were performed due to insufficient power to detect deviations from normality. No tests for outliers were performed and no data points were excluded.

Results

The effects of chronic nicotine exposure on nicotinic receptor subunit and assembled nAChR levels in specific regions of the mammalian brain has been extensively studied. Building upon these previous studies, we used immunoblotting and epibatidine binding to quantify proteomic changes in nicotinic subunits and receptors after chronic exposure with (−)-menthol in fourteen brain regions. Assessed with immunoblotting, four brain regions had statistically significant decreases in β2 nAChR subunit levels after chronic (−)-menthol exposure: the cortex, habenula, hippocampus, and hypothalamus (Figure 2). To further articulate changes in cholinergic tone in response to chronic (−)-menthol exposure, changes in assembled receptor levels were also characterized using epibatidine binding.

Figure 2: Effects of (−)-menthol exposure on β2 nAChR subunit levels.

β2 subunit immunoreactivity was assessed in fourteen brain regions: cerebellum (Cb), cortex (CX), habenula (HAB), hindbrain (Hb), hippocampus (HP), hypothalamus (HT), inferior colliculus (IC), interpeduncular nucleus (IPN), ventral midbrain (Mb), olfactory bulbs (OB, superior colliculus (SC), striatum (ST), and thalamus (Th). Four of the fourteen brain regions had statistically significant reductions in β2 subunit levels. All treatments for all regions were measured with tissue from five animals (n=5). Each animal was measured in triplicate. Significance was determined using an unpaired Student’s t-test. “*”: p ≤ 0.05

Ligand binding using radiolabeled epibatidine binding is an accurate method for measuring changes in the number of assembled nAChRs in response to various stimuli. Cytisine-sensitive epibatidine binding is a measure of α4β2 nAChRs, whereas cytisine-resistant epibatidine binding is a measure of non-α4β2 nAChRs (Whiteaker et al. 2000b). Of the fourteen brain regions investigated, the cortex, hindbrain, superior colliculus, and thalamus were analyzed using ³H-epibatidine binding. The remaining ten regions were analyzed using ¹²⁵I-epibatidine. The selection of ligand was based on the abundance of nAChRs, as well as available protein from each brain region. Both preparations of epibatidine have been characterized previously in the literature and there is no marked pharmacological difference between the two ligands (Davila-Garcia et al. 1997).

All observed binding values for vehicle samples were consistent with values in the literature using either ³H- or ¹²⁵I-epibatidine (Whiteaker et al. 2000a). Of the fourteen brain regions investigated, the habenula was selected for further analysis using mass spectrometry because the habenula was the only region to demonstrate decreased β2 nAChR subunit levels, as well as decreased total, cytisine-sensitive, and cytisine-resistant epibatidine binding after (−)-menthol exposure (Table 1).

Table 1:

Changes in radiolabeled epibatidine binding in habenula after chronic (–)-menthol exposure.

		Vehicle		(–)-menthol
Brain Region	Epibatidine Fraction	Fmol/mg	S.E.M.	Fmol/mg	S.E.M.
Habenula (HAB)	Total	306	11	257*	10
	Cytisine-sensitive	213	11	183*	6
	Cytisine-resistant	93	7	75*	4

Of the fourteen brain regions investigated, only the habenula demonstrated statistically significant differences in total, cytisine-sensitive, and cytisine-resistant epibatidine binding after (–)-menthol exposure. Significance was determined using an unpaired, two-tailed Student’s t-test.

^*:p ≤ 0.05.

We identified 7584 total proteins in vehicle treated and/or (–)-menthol treated mice. Identified proteins were sorted similarly to our previous investigation of the hypothalamus (Mulcahy et al. 2020). In brief, protein identifications in (–)-menthol treated tissue were sorted by 1) identifications made using all peptides within a protein group, 2) identifications observed in all 5 replicates with changes in the same direction (i.e., all identifications had TMT signals greater than or less than 0), and 3) whether they were statistically significant from the TMT signals of vehicle treated samples. After sorting, the data identified 552 proteins in the habenula with differential levels after chronic (–)-menthol exposure, 204 proteins with increased levels and 348 proteins with decreased levels. Three notable groups of biological processes and pathways were enriched in the cohort of habenular proteins with increased levels after menthol exposure. These groups were related to 1) neurotransmitter release, 2) immune systems, and 3) protein transport-related proteins (Table 2, Table 3, Table 5, Figure 3).

Table 2:

Select enriched signaling pathways and ontologies for habenular proteins upregulated by chronic (–)-menthol alone.

Description	Analysis	Term	No. of proteins	FDR
Drug metabolic process	GO	17144	17	0.00048
Regulation of neurotransmitter levels	GO	1505	10	0.0122
Regulation of neurotransmitter secretion	GO	46928	4	0.0414
Signaling by EGFR	Reactome	177929	3	0.0156
Neurotransmitter reuptake	GO	98810	2	0.0373
Cellular response to brain-derived neurotrophic factor stimulus	GO	1990416	2	0.0417
GABA synthesis, release, reuptake, and degradation	Reactome	888590	2	0.0377
L-glutamate import	GO	51938	2	0.0466
Progesterone receptor signaling pathway	GO	50847	2	0.0466

Pathway descriptions were provided by Reactome Pathway analysis and ontologies by Gene Ontology (GO) analysis through STRING. The pathway ID or GO term, number of proteins represented in each pathway, and the false discovery rate (FDR) for enrichment are provided.

Table 3:

Immune system related enriched pathways and ontologies for habenular proteins upregulated by chronic (–)-menthol alone.

Description	Pathway/Term	No. of proteins	FDR
Immune System	MMU-168256	38	7.14E-06
Adaptive Immune System	MMU-1280218	24	7.14E-06
Innate Immune System	MMU-168249	21	0.0011
Class I MHC mediated antigen processing & presentation	MMU-983169	16	1.82E-05
Neutrophil degranulation	MMU-6798695	15	0.0011
MHC class II antigen presentation	MMU-2132295	9	9.66E-05
Cytokine Signaling in Immune system	MMU-1280215	9	0.0231
Fc epsilon receptor (FCERI) signaling	MMU-2454202	7	0.0011
FCERI mediated NF-kB activation	MMU-2871837	6	0.0011
CDK-mediated phosphorylation and removal of Cdc6	MMU-69017	6	0.0011
Regulation of APC/C activators between G1/S and early anaphase	MMU-176408	6	0.0013
CLEC7A (Dectin-1) signaling	MMU-5607764	6	0.0014
Interleukin-1 signaling	MMU-9020702	6	0.0015
Signaling by the B Cell Receptor (BCR)	MMU-983705	6	0.0016
Dectin-1 mediated noncanonical NF-kB signaling	MMU-5607761	5	0.0014
NIK-->noncanonical NF-kB signaling	MMU-5676590	5	0.0014
Activation of NF-kappaB in B cells	MMU-1169091	5	0.0017

Pathway descriptions were provided by Reactome Pathway analysis and ontologies by Gene Ontology (GO) analysis through STRING The pathway ID or GO term, number of proteins represented in each pathway, and the false discovery rate (FDR) for enrichment are provided.

Table 5:

Gene Ontology (GO) & Reactome pathway terms for protein transport-related proteins upregulated in the habenula after chronic (–)-menthol treatment.

Description	Analysis	Term	No. of proteins	FDR
Intracellular transport	GO	46907	34	9.47E-08
Vesicle-mediated transport	GO	16192	30	8.51E-06
Intracellular protein transport	GO	6886	21	5.97E-05
ER to Golgi Anterograde Transport	Reactome	199977	9	0.00045
Golgi vesicle transport	GO	48193	11	0.00048
Vacuolar transport	GO	7034	8	0.00075
Lysosomal transport	GO	7041	7	0.0011
COPII-mediated vesicle transport	Reactome	204005	6	0.0011
Lysosome Vesicle Biogenesis	Reactome	432720	4	0.0015
ABC-family proteins mediated transport	Reactome	382556	6	0.0017
Endoplasmic reticulum to Golgi vesicle-mediated transport	GO	6888	6	0.0043
Golgi Associated Vesicle Biogenesis	Reactome	432722	4	0.0043
COPI-independent Golgi-to-ER retrograde traffic	Reactome	6811436	4	0.0051
Clathrin derived vesicle budding	Reactome	421837	4	0.0102
Golgi to vacuole transport	GO	6896	3	0.0109
Regulation of transmembrane transport	GO	34762	14	0.0113
Endosomal transport	GO	16197	7	0.0183
Negative regulation of transmembrane transport	GO	34763	6	0.0218
Cargo recognition for clathrin-mediated endocytosis	Reactome	8856825	4	0.03
Regulation of transport	GO	51049	29	0.031
Regulation of synaptic vesicle transport	GO	1902803	3	0.0384
Negative regulation of ion transmembrane transporter activity	GO	32413	4	0.0414
Golgi to lysosome transport	GO	90160	2	0.0417
Retrograde transport, endosome to Golgi	GO	42147	4	0.0488

Pathway descriptions were provided by Reactome Pathway analysis through STRING. The pathway ID or GO term, number of proteins represented in each pathway, and the false discovery rate (FDR) for enrichment are provided. Data is sorted by FDR values.

Figure 3: STRING analysis of habenular proteins with increased levels after (−)-menthol exposure.

204 proteins were identified with increased levels after (−)-menthol exposure. Proteins were considered only if they were identified in all five biological replicates. Highlighted are the pathway or ontologies. Only interactions with interaction score of ≥0.9 are shown. The following select enriched pathways/ontologies are shown: Adaptive immune response (red), membrane trafficking (blue), and lysosome vesicle biogenesis.

The 348 habenular proteins that were downregulated after chronic (–)-menthol exposure did not include enrichments for signaling, immune system, or protein transport-related proteins terms that were observed in the cohort of proteins with increased levels. Instead, the predominant enriched pathways were those associated with metabolism of RNA and gene expression (Table 4, Figure 4).

Table 4:

Top 10 enriched Reactome pathway terms for habenular proteins downregulated levels after chronic (–)-menthol alone.

Pathway Description	ID	No. of proteins	FDR
Metabolism of RNA	8953854	34	4.24E-11
Post-translational protein modification	597592	33	0.0227
Gene expression (Transcription)	74160	32	0.00086
Processing of Capped Intron-Containing Pre-mRNA	72203	26	2.86E-12
RNA Polymerase II Transcription	73857	25	0.0119
mRNA Splicing - Major Pathway	72163	20	6.68E-10
Generic Transcription Pathway	212436	20	0.0422
Hemostasis	109582	18	0.0176
Platelet activation, signaling and aggregation	76002	11	0.0241
Asparagine N-linked glycosylation	446203	11	0.044

Pathway descriptions were provided by Reactome pathway analysis through STRING. The pathway ID, number of proteins represented in each pathway, and the false discovery rate (FDR) for enrichment are provided.

Figure 4: Reactome analysis of habenular proteins with decreased levels after (−)-menthol exposure.

348 proteins were identified with increased levels after (−)-menthol exposure. Proteins were considered only if they were identified in all five biological replicates. Highlighted are the pathway or ontologies. Only interactions with interaction score of ≥0.9 are shown. Highlighted are the pathways “metabolism of RNA” (red), “post-translational protein modification” (green), and “gene expression (transcription)” (blue).

Discussion

The habenula, menthol, and the downregulation of nAChRs.

Of the fourteen brain regions investigated by immunoblotting and radioligand binding, the habenula was the only brain region to demonstrate statistically significant decreases in β2 nAChR subunit levels and epibatidine binding levels after chronic (–)-menthol exposure. The habenula, along with the IPN, intricately regulate the function of other brain regions, including the VTA (Molas et al. 2017; Antolin-Fontes et al. 2015). The habenula itself comprises two distinct subregions: the lateral habenula (LHb) and medial habenula (MHb) and is involved with both reward (LHb) and withdrawal (MHb) components of addiction (Velasquez et al. 2014). As our dissection did not differentiate between the LHb and MHB, our discussion will consider both subregions.

The Habenula has high levels of nAChR expression and one of the brain regions with the greatest (>30% of total) levels of non-α4β2 nAChRs in the brain (Whiteaker et al. 2000a). These non-α4β2 nAChRs, notably α3*, α5*, and β4* nAChRs, are involved with withdrawal symptoms and nicotine intake, and are highly expressed in the habenula (Velasquez et al. 2014; Elayouby et al. 2021). Several studies have characterized the functional implications of reduced nAChR signaling from the habenula. Knocking out α5 subunit expression in mice increases nicotine consumption and reduces IPN activation, while re-expressing α5 nAChR subunits specifically in the medial habenula prevents an increase in consumption (Fowler et al. 2011). RNAi reduction of habenular CHAT, the enzyme responsible for acetylcholine synthesis, induces anhedonia-like behavior in rats (Han et al. 2017). This is particularly interesting as anhedonia, the inability to feel pleasure, can be considered a component of nicotine withdrawal in humans and is associated with increased probability of relapse (Cook et al. 2015). The reduction of nAChR signaling in the habenula could lead to increase in nicotine consumption and elicit anhedonia-like behavior. Our observations of statistically significant decreases in β2 subunit and epibatidine binding levels observed in the habenula in response to (–)-menthol alone may help provide insight into the observed phenomena, such as the increased difficulty for menthol smokers to quit smoking.

The observed reductions in β2 nicotinic subunits and nAChRs would likely affect the regulation of neurotransmitters in the habenula, which in turn would impact nicotine intake. Furthermore, alterations in nAChR function, either by blockade or genetic deletion, affect the addiction-related withdrawal symptoms that are associated with the habenula-interpeduncular pathway (Salas et al. 2009; Zhao-Shea et al. 2013).

The habenula was not included in the brain regions investigated after (±)-menthol exposure alone in our previous study, though several brain regions demonstrated different responses to the different menthol preparations (Mulcahy et al. 2020). The differences between the effects of (±)-menthol observed previously and the effects of (–)-menthol discussed in this study are of interest as nAChR subunits or receptors may be used as markers not only of menthol exposure, but as markers of specific preparations of menthol. Several scenarios could explain why (±)-menthol and (–)-menthol elicit different effects. One scenario is that (–)-menthol is the sole ligand affecting nAChRs; that α4β2 is the only nAChR affected by menthol, and that differences between menthol preparations are due to administration of half the (–)-menthol dose when menthol is administered in racemic form. A second scenario is that (+)-menthol and (–)-menthol may affect various nAChR subtypes differently. Another scenario is that (+)-menthol is contributing in part to the observed effects, by the same mechanism or a different mechanism. While we have previously reported that (–)-menthol alone is responsible for the upregulation of α4* nAChRs in dopaminergic neurons, we have also demonstrated that (+)-menthol is still bioactive in its ability to modulate other qualities of nAChR function on cell types other than dopaminergic neurons (Henderson et al. 2018). This is illustrated by the observation that (+)-menthol is more potent than (–)-menthol in the positive allosteric modulation of GABA_A receptors (Hall et al. 2004). In this same report, it was revealed that both menthol stereoisomers were equally potent and efficacious as positive modulators of glycine receptors.

These observations illustrate that in addition to having different effects on the function of α4β2 nAChRs, different preparations of menthol (e.g., (±)-menthol or (–)-menthol) may also have brain region-specific differences in regulation of β2 nAChR subunit and nAChR levels. This point is exemplified by our previous observations in the hypothalamus and the results discussed in this study.

Protein upregulation after menthol exposure.

Protein profiling identified numerous ontologies that were enriched after chronic (–)-menthol exposure in the habenula (Figure 3). Several of these ontologies are associated with neurotransmitter regulation, including terms associated with glutamate and gamma aminobutyric acid (GABA) (Table 2). While the MHb preferentially innervates the IPN, there is evidence that axons do project to the LHb as well (Kim & Chang 2005). In addition to potential changes in habenula-interpeduncular pathway signaling to the VTA, changes in nicotinic tone in the MHb could affect the LHb, thereby affecting GABAergic signaling to the VTA and dopamine release. Changes in neurotransmitter regulation in both the MHb and LHb could alter dopamine release in the VTA via decreased nicotinic tone in the habenula-interpeduncular pathway and may contribute to the reduction of nicotine reward-related behavior associated with menthol exposure (Henderson et al. 2016).

In this work, we demonstrate an enrichment of immune system-related protein ontologies following chronic (–)-menthol exposure. The anti-inflammatory effects of (–)-menthol are mediated through MAPK and nuclear factor kappa B pathways, pathways which are corroborated in this study and are enriched in the upregulated proteins identified in the habenula (Table 3) (Shahid et al. 2018). Chemokine induction, reactive oxygen species levels, and intracellular Ca²⁺ levels are greater for cells treated with menthol cigarette smoke extract compared to cells treated with non-menthol cigarette smoke extract (Lin et al. 2017). In addition to known anti-inflammatory qualities, understanding which brain region-specific immune pathways are altered following chronic (–)-menthol exposure in the habenula is of interest for understanding how those pathways may contribute to addiction and withdrawal. Habenular mast cells have been linked to anxiety, a behavior also linked to nicotine withdrawal in the habenula-interpeduncular pathway (McLaughlin et al. 2017; Molas et al. 2017). Henderson et al. reported that the functional effects of menthol on nAChRs were independent of TRPM8, the canonical menthol receptor (Henderson et al. 2016). The changes in immune pathways, coupled with the reduction in nicotinic tone in the habenula, suggest a possible neuroimmune response to chronic (–)-menthol exposure that could affect nicotine consumption.

Protein downregulation after menthol exposure.

The 348 habenular proteins that were downregulated after chronic (–)-menthol exposure did not include enrichments for neither signaling terms nor immune system terms that were observed in the cohort of proteins with increased levels. Instead, the predominant enriched pathways were those associated with metabolism of RNA, post-translational protein modification, and gene expression (Figure 4, Table 4). These enrichments suggest that (–)-menthol exposure may modulate the expression of multiple proteins at the transcript level. The reduction in transcription-related proteins, coupled with the observed statistically significant decreases in β2 subunits and epibatidine binding in the habenula after chronic (–)-menthol, suggest that the nAChR protein decreases observed may in part be a result of transcript level regulation. Habenula transcriptomes following nicotine or menthol exposure have not been reported. It is therefore unclear whether the modulation of transcription-related proteins modulates transcripts of specific proteins or is a global cellular phenomenon. In addition to RNA related pathways, proteins associated with “platelet activation, signaling, and aggregation” were also enriched. Inhibition of platelet aggregation by menthol exposure has previously been reported and is mediated by TRPM8 independent PLC signaling (Kim et al. 2008).

A benefit of analyzing proteins with increased levels separately from those with decreased levels is that it can provide more information about the complexity of the proteomic changes occurring and where these changes are taking place. This is best exemplified with the ontology “asparagine n-linked glycosylation.” This ontology is enriched in the cohort of proteins with increased levels. It is also one of the most enriched ontologies in the cohort of proteins with decreased levels (Table 4). This apparent contradiction is clarified by investigating the function of the proteins in each cohort. Proteins associated with trafficking of proteins modified by asparagine n-linked glycosylation (e.g., sec24c & sec31a) comprise the enriched group in the cohort with increased levels. In the cohort of downregulated proteins, five of the 11 proteins identified are enzymes associated with asparagine n-linked glycosylation. Asparagine n-linked glycosylation is a post-translational modification that has been shown to be required for nAChR assembly and for trafficking between the endoplasmic reticulum (ER) and Golgi apparatus. The reduction of enzymes involved in that pathway observed after (–)-menthol exposure may contribute to the reduction in nAChR levels observed (Wanamaker & Green 2005). The cohort with upregulated proteins was also enriched for proteins associated with membrane trafficking. However, inspection reveals that while ER to Golgi trafficking is enhanced, so is endosomal, vacuolar, and lysosomal transport (Table 5). Golgi to plasma membrane transport pathways are not enriched. Taken together, these data suggest that (–)-menthol exposure leads to dysregulation of nAChR post-translational modifications in the ER or Golgi which may lead to an increase in protein breakdown and lead to the decreases in nicotinic subunit and receptor levels observed by immunoblotting and radioligand binding.

Conclusions

Understanding the biological effects of tobacco and ENDS flavorants, some of which have been associated with addiction, is a key public health concern. While menthol has historically been considered as a tobacco product additive, ENDS can administer menthol alone by vapor in “zero-nicotine” preparations, as in a conventional sickroom vaporizer. This report is the first comprehensive analysis of changes in nAChR subunit and receptor levels after chronic (–)-menthol exposure. Statistically significant decreases in both β2 subunit levels and nAChR levels were only detected in the habenula. The effects of menthol are likely not a result of interacting with one target (i.e., nAChRs) but rather with another target or with a collection of targets. We used mass spectrometry to profile changes in habenular protein expression after chronic (–)-menthol exposure. Profiling demonstrated that, in addition to changes in β2 subunits and nAChR levels, 552 additional membrane-bound proteins also had altered levels of expression. Enriched in the cohort of (–)-menthol-altered proteins were proteins associated with signaling, immune systems, RNA regulation, and protein transport. These changes, particularly those associated with signaling, suggest that in addition to reduced cholinergic signaling, other signaling proteins (e.g., GABA related) are also affected and can have wider implications for signaling to the IPN or to the ventral midbrain. The upregulated and downregulated protein levels identified in (–)-menthol treated habenula enhance our understanding of which pathways are altered with menthol and how they may be involved with withdrawal or reward. Proteins with altered levels following (–)-menthol exposure could identify potential therapeutic targets for the management of addiction and smoking cessation for menthol containing products.

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Abbreviations

AGC

automatic gain control

BPRP

basic pH reversed-phase

BCA

bicinchoninic acid

Cb

cerebellum

CNS

central nervous system

CX

cortex

CID

collision-induced dissociation

ENDS

electronic nicotine delivery systems

ER

endoplasmic reticulum

FDR

false discovery rate

GABA

gamma aminobutyric acid

GAPDH

glyceraldehyde 3-phosphate dehydrogenase

HAB

habenula

Hb

hindbrain

HP

hippocampus

HT

hypothalamus

IACUC

Institutional Care and Use Committee

IC

inferior colliculus

IPN

interpeduncular nucleus

KEGG

Kyoto Encyclopedia of Genes and Genomes

LC

liquid chromatography

LHb

laternal habenula

Mb

ventral midbrain

MHb

medial habenula

MS

mass spectrometry

nAChR

nicotinic acetylcholine receptor

NCE

normalized collision energy

OB

olfactory bulbs

OT

olfactory tubercles

PSM

peptide-spectrum matches

RRID

Research Resource Identifier (see scicrunch.org)

SC

superior colliculus

SNc

substantia nigra compacta

ST

striatum

STRING

Search Tool for the Retrieval of Interacting Genes/Proteins

TMT

tandem mass tag

VTA

ventral tegmental area