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. Author manuscript; available in PMC: 2023 Sep 15.
Published in final edited form as: Neuropharmacology. 2022 Jun 27;216:109173. doi: 10.1016/j.neuropharm.2022.109173

Coffee and cigarettes: modulation of high and low sensitivity α4β2 nicotinic acetylcholine receptors by n-MP, a biomarker of coffee consumption

Roger L Papke a, Madison Karaffa a, Nicole A Horenstein b, Clare Stokes a
PMCID: PMC9524580  NIHMSID: NIHMS1838670  PMID: 35772522

Abstract

Smokers report particular appreciation for coffee with their first cigarettes of the day. We investigated with voltage-clamp experiments, effects of aqueous extracts (coffees) of unroasted and roasted coffee beans on the activity of human brain nicotinic acetylcholine receptor (nAChR) subtypes expressed in Xenopus oocytes, looking at complex brews, low molecular weight (LMW) fractions, and specific compounds present in coffee. When co-applied with PNU-120596, a positive allosteric modulator (PAM), the coffees stimulated currents from cells expressing α7 nAChR that were larger than ACh controls. The PAM-dependent responses to green bean coffee were three-fold greater than those to dark roasted coffee, consistent with α7 receptor activation by choline, a component of coffee that is partially degraded in the roasting process. Coffees were tested on both high sensitivity (HS) and low sensitivity (LS) forms of α4β2 nAChR, which are associated with nicotine addiction. To varying degrees, these receptors were both activated and inhibited by the coffees and LMW extracts. We also examined the activity of nine small molecules present in coffee. Only two compounds, 1-methylpyridinium and 1-1-dimethylpiperidium, produced during the process of roasting coffee beans, showed significant effects on nAChR. The compounds were competitive antagonists of the HS α4β2 receptors, but were PAMs for LS α4β2 receptors. HS receptors in smokers are likely to progressively desensitize through a day of smoking but may be hypersensitive in the mornings when brain nicotine levels are low. A smoker’s first cup of coffee may therefore balance the effects of the day’s first cigarette in the brain.

Keywords: coffee, nicotine, addiction, electrophysiology, neuromodulation

1. Introduction

1.1. Historical aspects of caffeine and nicotine use

Alcohol, nicotine, and caffeine constitute the triad of addictive substances commonly used in modern American and European societies. It is interesting that the same nicotine-dependent smoker will associate their smoking with coffee in the morning and with alcohol in the evening. Coffee and cigarettes for breakfast is sometimes referred to as “the breakfast of champions”, a “French”, or a “Bohemian” breakfast. While there is a substantial literature examining the effects of ethanol on nicotinic acetylcholine receptors (nAChR) (Rahman et al., 2016), interactions between nAChR and coffee have been less well studied.

Coffee is more than caffeine, but caffeine is an important active component. Caffeine is a central nervous system stimulant, and the antagonism of adenosine receptors is responsible for the ability of coffee to make the user feel awake and alert. Although caffeine is acknowledged to be addictive, producing at least a mild dependency (Hasin et al., 2013), the generally pleasant psychotropic effects and low levels of adverse effects have led to unregulated and widespread use of coffee and other caffeinated beverages (Chou, 1992).

Nicotine addiction, particularly in the form of cigarette smoking, is a huge problem worldwide. The addictive properties of tobacco make it incredibly difficult for the user to stop once they have started using tobacco. For many users smoking begins before full adulthood, and then they find themselves with a lifetime addiction to tobacco. This lifetime addiction then contributes to numerous health issues, making cigarette smoking the largest preventable cause of death in the United States and many other countries.

1.2. Concomitant use of caffeine and nicotine

A cigarette smoker will indulge their habit throughout the day, while coffee, perhaps the most popular caffeinated beverage, is consumed mainly in the morning and for a smoker will be associated with their first cigarettes of each day. In contrast, smoking may later be paired with alcohol in the evenings. Therefore, for the smoker, both coffee and alcohol may provide cues for their smoking behavior but are differentially tied to their daily cycle of nicotine intake.

When the smoker wakes up, their brain likely craves a cigarette because they have been deprived of nicotine all night, and likewise they may be craving caffeine, so that when these drugs are used together in the morning, a habitual association is likely to form. We wished to investigate the hypothesis that common use of coffee and cigarettes is reinforced by complementary effects associated with the daily cycle nicotine effects on brain function. Chronic nicotine use leads to the upregulation of α4β2 nAChRs, the main nicotinic acetylcholine receptor subtype promoting addiction (Papke et al., 2020), producing an important difference in brain activity between smokers and non-smokers. Is there a difference in nAChR availability among smokers who are also heavy caffeine consumers and smokers who are not? Findings have suggested that there is greater upregulation of the nAChRs in the brainstem, prefrontal cortex, and thalamus in smokers using caffeine than in smokers without (Brody et al., 2016), leading us to focus on α4β2 receptors for some of our experiments.

The receptors containing α4 and β2 subunits are the most abundant nAChRs in the brain, and there are two distinct isoforms of the α4β2 nAChR, based on subunit stoichiometry. Receptors that contain three α4 and two β2 subunits α4(3)β2(2) are considered the low sensitivity (LS) receptors, while high sensitivity (HS) α4(2)β2(3) receptors, will activate with lower concentrations of ACh or nicotine but are more sensitive to desensitization (Kuryatov et al., 2008).

1.3. Goals of the study

One of our primary objectives was to investigate the effects of coffee on the α4β2 nAChR of the brain. However, it was also of interest to see if there are interactions between coffee and the other main nAChR subtype of the brain, homomeric α7 (Papke and Horenstein, 2021). These receptors have been implicated in cognitive function and, more recently, in control of inflammatory disease and pain via a cholinergic anti-inflammatory pathway (CAP) and the stimulation of α7 nAChR on cells of the immune system (Bagdas et al., 2018).

For our experiments, we used a single source for coffee beans that that could be obtained both roasted, as is typical for preparing the beverage, and as unroasted green beans, which allowed us to identify the activities of compounds produced in the roasting process. We examined and compared the activity of the complete complex coffees and low molecular weight (LMW) extracts. We also obtained samples of specific compounds known to be present in coffee, including 1-methylpyridinium (n-MP), a biomarker for coffee consumption known to be produced during the roasting process (Lang et al., 2011).

2. Materials and Methods

2.1. Chemicals and reagents

Acetylcholine chloride (ACh), buffer chemicals, and most test and reference compounds were purchased from Sigma-Aldrich (St. Louis MO). 1-methylpyridinium (n-MP) was purchased from AK Scientific (Union City CA). PNU-120596 and 1,1-dimethylpiperidium (dMP) were synthesized in the Horenstein laboratory by Dr. Kinga Chojnacka following the published procedures (Hurst et al., 2005) and (Papke et al., 2014), respectively. Whole coffee beans, Coffea arabica, roasted and unroasted, were sourced from Peru and purchased from Sweetwater Organic Coffee Co. (Gainesville FL).

2.2. Preparation of coffee and low molecular weight fractions

Whole beans were ground with a coffee grinder or heavy-duty spice grinder. Powder and grinds that passed through a 1/16th inch sieve were weighed and “brewed” with 15 ml Ringer’s (see section 2.5) solution per g of grounds. Dark roasted coffee (DRC) was brought just to a boil while stirring, about 10 minutes, to simulate normal coffee preparation, and the green bean coffee (GBC) was simply stirred for 10 minutes at room temperature in order to avoid conversion of natural compounds by heat. Then the coffees were vacuum filtered, first through coarse P8 or regular consumer coffee filter and then through 0.2 micron nylon filters (Whatman, GE Healthcare, Piscataway NJ) for the “whole brew”. pH was adjusted to 7.2 with NaOH.

For low molecular weight (LMW) fractions, the whole brew was then subjected to ultrafiltration using the Amicon Stirred Cell (EMD Millipore, Billerica MA) apparatus with nitrogen gas pressure successively through 100 kDa, 30 kDa, 10 kDa, 5 kDa, and 1 kDa cutoff regenerated cellulose membranes (EMD Millipore).

2.3. LC-MS analysis of coffee extracts

Mass Spectrometry instrumentation. A ThermoScientific LTQ XL linear quadrupole ion trap mass spectrometer was used for the analyses. The HPLC sysem was a Thermo Scientific Ultimate 3000. The mobile phase elution system used two buffers of 20 mM aqueous NH4OAc (buffer A) and acetonitrile with 0.2 % acetic acid (buffer B). Standard samples of n-MP and dMP were used to confirm elution times.

2.4. Expression in Xenopus oocytes

The human nAChR clones and concatamers were obtained from Jon Lindstrom (University of Pennsylvania, Philadelphia PA). The human resistance-to-cholinesterase 3 (RIC3) clone was obtained from Millet Treinin (Hebrew University, Jerusalem, Israel) and co-injected with α7. The β2−6−α4 concatamer was co-expressed with monomeric α4 or β2 to obtain relative pure populations of LS or HS α4β2 receptor, respectively (Zhou et al., 2003). Subsequent to linearization and purification of the plasmid DNAs, RNAs were prepared using the mMessage mMachine in vitro RNA transcription kit (Ambion, Austin TX).

Oocytes were surgically removed from mature female Xenopus laevis frogs (Nasco, Ft. Atkinson WI) as previously described (Papke and Stokes, 2010). Frogs were maintained in the Animal Care Service facility of the University of Florida, and all procedures were approved by the University of Florida Institutional Animal Care and Use Committee (approval number 202002669).

2.5. Two-electrode voltage clamp electrophysiology

Experiments were conducted using OpusXpress 6000A (Molecular Devices, Union City, CA) as previously described (Papke and Stokes, 2010). Oocytes were voltage-clamped at −60 mV at room temperature (24 °C). The oocytes were bath-perfused with Ringer’s solution (115 mM NaCl, 2.5 mM KCl, 1.8 mM CaCl2, 10 mM HEPES, and 1 μM atropine, pH 7.2) at 4 ml/min for heteromeric nAChR or 2 ml/min for α7 receptors to optimize the measurement of net charge responses (Papke and Papke, 2002). To evaluate the effects of experimental compounds, responses were compared to control ACh-evoked responses, defined as the average of two initial applications of ACh made before test applications. Note that by using the average of two initial controls, we included the effects of the variability of ACh responses into our analyses. ACh control concentrations were 60 μM for α7 receptors, 100 μM for α3β2, α3β4 and LS α4(3)β2(2) receptors, 30 μM for α4β2α6β2β3, and 10 μM for α4(3)β2(2) and α4(2)β2(2)α5 receptors.

The responses were calculated as both peak-current amplitudes and net charge, as previously described (Papke and Papke, 2002). Data reported are the net-charge responses for α7 (Papke and Papke, 2002) and the peak currents for all other subtypes. Data were collected at 50 Hz, filtered at 20 Hz for α7 receptors or filtered at 5 Hz for heteromeric nAChR, and analyzed by Clampfit (Molecular Devices, San Jose CA) and Excel (Microsoft, Redmond WA). Data are expressed as means ± standard deviations (S.D.) from at least five oocytes for each experiment and plotted with Kaleidagraph 4.5.2 (Synergy Software, Reading PA). Multi-cell averages were calculated for comparisons of complex responses. Averages of the normalized data were calculated for each of the 10,322 points in each of the 206.44 s traces (acquired at 50 Hz), as well as the standard errors for those averages.

2.6. Data and statistical analysis

Comparisons of results were made using one-way ANOVA or using t-tests between the pairs of experimental measurements. In cases where multiple comparisons were made, a Bonferroni correction for multiple comparisons (Aickin and Gensler, 1996) was applied. Dunnett’s post hoc analysis was conducted to evaluate changes from initial control responses. A corrected value of p < 0.05 was used to constitute a minimum level of significance. The statistics were calculated using an Excel template provided in Microsoft Office or ANOVA protocols in Kaleidagraph.

3. Results

3.1. Effects of coffee on α7 nAChR

To explore the hypothesis that there might be α7 nAChR agonists in the rich mixture of compounds consumed as coffee, we applied pH-adjusted dark roasted coffee (DRC) made up with the saline components of our Ringer’s solution (see section 2.5) to oocytes expressing human α7 nAChR without or with the α7 positive allosteric modulator (PAM) PNU-120596 (Hurst et al., 2005) (Figure 1). Although coffee alone caused only minimal activation of α7 ion channel currents compared to the 60 μM ACh control responses (see Supplemental Data for ANOVA), the addition of the PAM produced much larger currents (P <0.001). Similar results were obtained with broth made from unroasted “green” coffee beans (GBC). It was notable that the PNU-potentiated responses to GBC, normalized to their internal ACh controls, were significantly larger than the normalized potentiated response to the DRC (p < 0.001).

Figure 1.

Figure 1.

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Responses of α7 receptors to applications of coffees. A) Shown on the left are the averaged normalized raw data of responses of 6 oocytes expressing α7 to applications of 60 μM ACh (the second pre-control), pH and osmotically balanced dark roasted coffee applied alone, and co-applied with 10 μM PNU-120596. The single-cell replicate data for net-charge responses are shown on the right and were used for ANOVA (see Supplemental Data for details). B) On the left are shown the averaged normalized raw data of responses of 7 oocytes expressing α7 to applications of 60 μM ACh (the second pre-control), pH and osmotically balanced “coffee” made from unroasted beans applied alone, and co-applied with 10 μM PNU-120596. Scale bars are based on the average 60 μM ACh responses used for normalization. The single cell replicate data for net charge responses are shown on the right. As noted in the Methods, our normalization of the data was based on the average of two initial controls, and so both sets of control responses were used for these and similar plots.

3.2. PAM-dependent activation of α7 receptors by LMW coffee fractions

Using sequential ultrafiltration, we prepared DRC and GBC fractions that contained only components of 1 kilodalton or less (Methods). The LMW fractions of GBC and DRC were co-applied with 10 μM PNU-120596 to cells expressing α7 nAChR and compared to ACh control responses from the same cells (Figure 2A). While PAM-dependent activity was observed with both preparations, the net-charge responses to LMW DRC plus PNU-120596 were not larger than the ACh controls (see Supplemental Data for ANOVA). This suggests that there may have been additional silent agonists in the HMW DRC that were lost in the size fractionation, based on comparison to Figure 1. Potentiated responses to the GBC LMW preparation were larger than to the respective ACh controls and larger than the potentiated DRC LMW responses (p < 0.001). These PAM-dependent responses may be due in large part to the presence of choline in coffee beans (Wei et al., 2012). According to the USDA1, typically 100 g of coffee contains 2.6 g of choline. Of course, this will vary depending on the source of the coffee beans, as well as the roasting and brewing processes. Given those factors, it is reasonable to estimate that our coffee preparation might contain as much as 100–300 μM choline. Choline is an efficacious, though low potency, selective agonist for α7 receptors (Papke et al., 1996). At a concentration of 100 μM, the co-application of choline with 10 μM PNU-120596 (Figure 2B) is more than sufficient to evoke PAM-dependent α7 currents significantly greater (p < 0.0001) than those stimulated by either of the LMW coffee preparations (Figure 2A). A study of the α7 responses to choline, applied alone or co-applied with PNU-120596 indicated EC50 values of approximately 200 μM, consistent with previous reports (Papke and Papke, 2002) and a net charge Imax roughly 100-fold greater with PNU-120596 co-application (Figure 2C). The response to GBC plus 10 μM PNU-120596 was 7.16 ± 0.66 times the ACh control responses, and based on the Hill equation curve-fit parameters, this would correspond to a response to 45 μM choline, consistent with the USDA data. Choline concentrations are reduced in the process of roasting coffee (Li et al., 2020) beans since it is one of the precursors for 1,1-dimethylpiperidium (dMP) (Wermann et al., 2014) and 1-methylpyridinium (n-MP) (Burton et al., 2020), compounds found only in coffee made from roasted beans (see below). Such a reduction in choline content would be consistent with the lower PAM-dependent currents stimulated by DRC compared to GBC (see also Figure 1).

Figure 2.

Figure 2.

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Responses of α7 receptors to applications of LMW coffee fractions. A) Traces on the left are the averaged normalized raw data of responses of 7 oocytes expressing α7 to applications of 60 μM ACh, then pH and osmotically balanced LMW DRC co-applied with 10 μM PNU-120596. Traces on the right are the averaged normalized raw data of responses of 5 oocytes expressing α7 to applications of 60 μM ACh, then pH and osmotically balanced LMW GBC coffee co-applied with 10 μM PNU-120596. B) The averaged normalized raw data of responses of 5 oocytes expressing α7 to applications of 60 μM ACh, then 100 μM choline co-applied with 10 μM PNU-120596. The scale bars are based on the average 60 μM ACh responses used for normalization. C) Concentration response data for a7 responses to choline applied alone (left axis, blue markers) or ca-applied with 10 μM PNU-120596 (right axis, red markers). Data were normalized relative to the control responses to 60 μM ACh obtained from the same cells, and represent the average responses of 7 or 8 cells (± SEM). D) Single replicate data of the net-charge values of the PNU-120596-potentiated currents in A, used for statistical analysis (Supplemental Data). The potentiated responses of LMW GBC and choline were greater than the initial ACh controls (p < 0.05 and p ≤ 0.0001, respectively).

3.3. Tests of roasted, and green bean coffee on α4β2 nAChR

The two coffee preparations were tested on cells expressing human α4β2 nAChR. Using the β2−6−α4 concatamer of the ligand-binding α4β2 dimer (Papke et al., 2013; Zhou et al., 2003) co-expressed with either α4 or β2 monomers, receptors were obtained with the subunit composition of α4(3)β2(2) or α4(2)β2(3), for LS ACh (EC50 ≈ 155 μM) or HS (EC50 ≈ 1.5 μM) forms of α4β2 receptors, respectively. The coffee preparations were applied alone or co-applied with control concentrations of ACh (Figure 3). There were small current responses for each receptor subtype to both preparations, although these were significantly less than the ACh controls (p < 0.0001, see Supplemental Data for ANOVA results). Control responses to ACh of both receptor subtypes were also inhibited by both preparations (p < 0.0001).

Figure 3.

Figure 3.

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Responses of oocytes expressing α4β2 with the two different stoichiometries to applications of coffees. A) The averaged normalized raw data of responses of oocytes expressing α4β2 with the two different stoichiometries to applications of control ACh and pH and osmotically balanced dark roast coffee (DRC) applied alone and co-applied with control ACh. The LS receptor data (left) represent 6 oocytes, and the HS receptor data (right) represent the responses of 7 oocytes. Scale bars are based on the average control ACh responses used for normalization (100 μM for LS and 10 μM for HS). B) Data from single oocytes expressing LS α4β2 receptors compared to the initial ACh controls from the same cells (two applications per cell). The peak current responses to the DRC were smaller than the ACh controls, and the co-application of coffee with ACh reduced the ACh responses (p < 0.0001, see Supplemental Data for ANOVA). C) Data from single cells expressing HS α4β2 receptors to applications of DRC compared to the initial ACh controls from the same cells (two applications per cell). The peak-current responses to the DRC were not statistically different from the ACh controls, although the co-application of coffee with ACh reduced the ACh responses (p < 0.0001, see Supplemental Data for ANOVA). D) Data from single cells expressing LS α4β2 receptors in response to applications of GBC, compared to the initial ACh controls from the same cells (two applications per cell). The peak-current responses to the GBC were smaller than the ACh controls, and the co-application of coffee with ACh reduced the ACh responses (P< 0.0001, see Supplemental Data for ANOVA). E) Data from single cells expressing HS α4β2 receptors to applications of GBC, compared to the initial ACh controls from the same cells (two applications per cell). The peak-current responses to the GBC were smaller than the ACh controls, and the co-application of GBC with ACh reduced the ACh responses (p < 0.0001, see Supplemental Data for ANOVA).

3.4. Low molecular weight (LMW) DRC and GBC on α4β2 nAChR

The LMW preparations were tested on cells expressing LS or HS α4β2 receptors (Figure 4). The activation produced by the LMW fractions appeared less than for the whole-brew preparation, although once corrected for multiple comparisons, the only significant difference was for the DRC preparation on HS receptors (p < 0.0001). While the agonist activity of the LMW preparations was generally decreased compared to the whole-brew preparations, all the preparations were effective at inhibiting the ACh-evoked peak-current responses (Figure 4A–D, p < 0.0001). It was also noted that for both the LMW DRC and LMW GBC, the HS receptors were more inhibited than the LS receptors (p < 0.0001 for the DRC and p < 0.05 for the GBC).

Figure 4.

Figure 4.

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Responses of α4β2 receptors to applications of low molecular weight (LMW) fractions of coffees. A) Data from single cells expressing LS α4β2 receptors to the LMW fraction of DRC compared to the initial ACh controls from the same cells (two applications per cell). The peak-current responses to the LMW DRC were smaller than the ACh controls (p < 0.0001), and the co-application of LMW DRC with ACh reduced the ACh responses (p < 0.0001, see Supplemental Data for ANOVA). B) Data from single cells expressing HS α4β2 receptors to applications of LMW DRC compared to the initial ACh controls from the same cells (two applications per cell). The peak-current responses to the DRC were smaller than the ACh controls, and the co-application of LMW DRC with ACh reduced the ACh responses (p < 0.0001, see Supplemental Data for ANOVA). C) Data from single cells expressing LS α4β2 receptors in response to applications of LMW GBC compared to the initial ACh controls from the same cells (two applications per cell). The peak-current responses to the GBC were smaller than the ACh controls, and the co-application of coffee with ACh reduced the ACh responses (p < 0.0001, see Supplemental Data for ANOVA). D) Data from single cells expressing HS α4β2 receptors to applications of LMW GBC compared to the initial ACh controls from the same cells (two applications per cell). The peak-current responses to the GBC were smaller than the ACh controls, and the co-application of GBC with ACh reduced the ACh responses (p < 0.0001, see Supplemental Data for ANOVA). E) Comparison of the inhibitory effects of the LMW fractions on LS and HS receptors. For each of the preparations, the inhibition of HS receptors was greater than the inhibition of LS receptors (**p < 0.0001 for the LMW DRC and *p < 0.05 for the LMW GBC).

3.5. Evaluations of small molecules identified as present in dark roasted coffee

Compounds shown in Figure 5A are known to be found in coffee, and as many nAChR ligands are charged amines, these were selected for testing since they contain basic or quaternary nitrogens. They include, of course, caffeine (Burton et al., 2020), as well as trigonelline (Perez-Miguez et al., 2019), agmatine (Galgano et al., 2012), spermine (Dias et al., 2012), taurine (Albouchi and Murkovic, 2020), lutidine (Tsegay et al., 2019), 1-(2-aminoethyl)pyrrolidine (Tsegay et al., 2019), 1-methylpyridinium (n-MP) (Burton et al., 2020), and 1,1-dimethylpiperidium (dMP) (Wermann et al., 2014). Of these compounds, it should be noted that dMP was previously identified as an α7-selective agonist (Horenstein et al., 2008), and when applied to cells expressing α7, 100 μM dMP evoked responses comparable to those stimulated by the control application of 60 μM ACh (not shown). None of the other test compounds evoked detectable responses from cells expressing α7 when applied alone at 100 μM. To ascertain whether they might be silent agonists (Papke et al., 2014; Quadri et al., 2016), the compounds shown in Figure 5A were tested at 100 μM co-applied with 10 μM PNU-120596 to cells expressing α7 nAChR (Figure 5B) and the responses compared to PNU-120596 applied alone in Ringer’s solution (Vehicle). As expected, dMP stimulated large responses when co-applied with the PAM, and this was confirmed by ANOVA (Supplemental Data) to be highly significant compared to PNU-120596 applied alone (p < 0.0001), which served as a vehicle control. The only other compound to stimulate PAM-dependent responses was n-MP (Figure 5B). This activity has been reported previously (Papke and Horenstein, 2021). Although in the ten-group ANOVA it did not reach a level of significance, it was confirmed to be significant in a pairwise t-test (p < 0.001, see Supplemental Data).

Figure 5.

Figure 5.

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Small nitrogen-containing molecules identified in coffee. A) Structure of test compounds identified in coffee and abbreviated names. B) Net-charge responses of cells expressing α7 (n = 6–8) to the compounds shown in A co-applied at 100 μM with 10 μM PNU-120596 compared to PNU-120596 applied alone in the standard vehicle (Ringer’s solution). Note that in the ANOVA of the multiple comparisons, only the co-applications of dMP with PNU-120596 indicated a significant difference compared to PNU-120596 applied alone; however, a Student t Test for unpaired data indicated a significant increase with n-MP compared to PNU-120596 applied alone (p < 0.0001, see Supplemental Data).

None of the compounds produced detectable activation of either LS or HS α4β2 receptors when applied at 100 μM (data not shown), and most lacked effect when co-applied with control concentrations of ACh (Figure 6). However, both dMP and n-MP were observed to differentially modulate the ACh-evoked responses of HS and LS α4β2 receptors, decreasing the responses of HS receptors (p < 0.0001) and increasing the responses of LS receptors (p < 0.0001, see Supplemental Data for ANOVA results).

Figure 6.

Figure 6.

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Effects of small nitrogen-containing molecules identified in coffee on ACh peak-current responses on the two types of α4β2 receptors. After the acquisition of control ACh responses, compounds were co-applied at 100 μM with control concentration of ACh, and data were compared to initial ACh controls. n-MP had significant effects (p < 0.05) on both LS and HS α4β2 receptors, increasing the responses of LS receptors and decreasing those of HS receptors. dMP had no significant effect on LS receptors but strongly inhibited HS receptors (p < 0.0001).

3.6. Creation of n-MP and dMP in the roasting process

It has been reported that both n-MP and dMP are produced during the roasting process from the degradation of choline and/or trigonelline (Lang et al., 2013; Wermann et al., 2014). Therefore, we conducted liquid chromatography-mass spectrometry (LC-MS) analysis of our LMW preparations of DRC and GBC to confirm the presence and relative levels of these compounds in our experimental preparations (See Supplemental Data). We did not detect the presence of either n-MP or dMP in GBC. However, both n-MP and dMP were identified in the DRC preparation in a ratio of 183:1 based on their relative peak areas in the LC-MS-ESI data.

Since the LC-MS data indicate that the abundance of dMP in our LMW DRC is only 0.5% that of n-MP, an observation consistent with other studies (Stadler et al., 2002), we focused our remaining experiments on n-MP.

3.7. Mechanistic studies of n-MP effects on α4β2 nAChR

We conducted competition experiments on the effects n-MP on the ACh-evoked responses of HS and LS α4β2 receptors (Figure 7 and Supplemental Figure 1). In order to most effectively understand the effects of n-MP on the α4β2 receptor subtypes, we conducted the analysis in two different ways (See Table 1). In Figure 7 we plot all the data obtained at the various ACh concentrations with or without n-MP. These data were suitable for ANOVA to determine at which concentrations n-MP had significant effects on the responses (indicated in Figure 7, see Supplemental Data for ANOVA). These data were fit to the Hill equation (Table 1). The primary effect of n-MP on LS α4β2 receptors was to decrease the EC50 without a large effect on the Imax. However, the increase of the peak-current responses in the range from 10 to 100 μM ACh (Figure 7A) would be consistent with it working as a PAM at those intermediate concentrations. In contrast, for the HS receptors under both conditions, the ACh-evoked responses (normalized to ACh controls) had an Imax of roughly 1.6 times the ACh control. In the absence of n-MP, the EC50 was 1.109 ± 0.107 μM, while in the presence of 100 μM n-MP, there was a shift in the EC50 to 12.1 ± 4.3 μM (Figure 7B). These results were consistent with n-MP functioning as a competitive antagonist of HS α4β2 ACh-evoked responses.

Figure 7.

Figure 7.

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Effects of 100 μM n-MP on ACh responses of α4β2 receptors. A) Peak-current responses of LS (α4(3)β2(2)) receptors to ACh applied alone (open circles, n = 5) or co-applied with 100 μM n-MP (red-filled circles n = 7). Data are expressed relative to the initial control responses 10 μM ACh. All of the single-cell responses are plotted, and ANOVA indicated that n-MP co-application produced significant increases in the ACh responses at 10 μM (** p < 0.0001) and 30 μM (* p < 0.05). B) Peak-current responses of HS (α4(2)β2(3)) receptors to ACh applied alone (open circles, n = 6) or co-applied with 100 μM n-MP (blue-filled circles n = 6). Data are expressed relative to the initial control responses 10 μM ACh. All of the single-cell responses are plotted, and ANOVA indicated that n-MP co-application produced significant reductions in the ACh responses in the range from 1 μM to 30 μM (** p < 0.0001, * p< 0.05). The data in A and B were fit to the Hill equation, and the Imax and EC50 values are reported in Table 1. Note that the Imax values relative to the respective ACh controls are consistent with those previously reported (Papke et al., 2013). See the discussion in the text and Supplemental Figure 1 for an alternative analysis of these data based on curve fits of the responses of individual cells, also reported in Table 1.

Table 1.

Effect of n-MP on ACh responses

From Figure 7 From replicates, Averages ± S.D.*
Condition Imax EC50 μM Imax EC50 μM
HS ACh alone 1.5365 ± 0.031 1.109 ± 0.107 1.535 ± 0.080 1.128 ± 0.214
HS + n-MP 1.672 ± 0.142 12.090 ± 4.271 1.682 ± 0.317 15.687 ± 12.998
LS ACh alone 2.327 ± 0.395 109.1 ± 103.9 2.290 ± 0.714 114.285 ± 80.165
LS + n-MP 1.824 ± 0.062 5.707 ± 1.125 1.845 ± 0.405 6.545 ± 3.315
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The responses of each single cell were fit to the Hill equation, and then EC50 and Imax values from each replicate were averaged. There were no significant effects of n-MP co-application on the Imax values. However, n-MP increased the EC50 for HS receptors (p < 0.05) and decreased the EC50 for LS receptors (p < 0.01). See Supplemental Data for replicate values. Data were normalized to the ACh control responses (10 μM for HS receptors and 100 μM for LS receptors) obtained from the same cells. Note that the Imax values are therefore relative to the ACh controls and that the HS ACh control responses were 65% the ACh maximum and the HS ACh control responses were 43% the ACh maximum for their respective subtypes.

While this approach was useful for determining n-MP effects and specific concentrations, it did not provide a statistically valid approach for comparing Imax and EC50 values. Therefore, we took advantage of the fact that under each condition we had multiple cells that each responded across the entire concentration range, so we could fit the Hill equation to the data from each single cell (Supplemental Figure 1). We used those data to calculate the average curve fits (± S.D), shown in Table 1. These values were all in very good agreement with single curve fits to the data presented in Figure 7 and additionally allowed us to make statistical comparisons of the effects of n-MP on the Imax and EC50 values confirming the conclusions discussed above.

3.8. Effects of bath-applied n-MP on HS and LS α4β2 receptor ACh responses

We determined baseline response of HS and LS α4β2 receptors to control applications of ACh and then added n-MP at varying concentrations to the bath while continuing to make periodic applications of ACh (co-applied with n-MP at the indicated concentration, Figure 8). We observed a concentration-dependent, and only partially reversible, inhibition of HS α4β2 responses, and a small concentration-dependent increase in the LS α4β2 responses that, in the case of 300 μM n-MP, produced significant increases (p < 0.05) in the ACh responses after n-MP washout. Shown in Figure 8 are the average peak responses (± S.D.), while Supplemental Figure 2 shows the replicate data that were used for ANOVA, comparing each condition to the initial controls.

Figure 8.

Figure 8.

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Effects of bath-applied n-MP on the ACh responses of LS (α4(3)β2(2)) and HS (α4(2)β2(3)) nAChR. Separate sets of cells (n ≥ 5) received two control ACh applications (100 μM ACh for LS receptors and 10 μM ACh for HS receptors), and then the bath solution was switched to one containing n-MP at the indicated concentrations. Cells then received seven additional ACh applications (made up with the bath concentration of n-MP) at four-minute intervals before the bath was switched back to the control Ringer’s solution. As the n-MP was washed out of the bath, cells received three more ACh applications. Data are peak current responses (± S.D.) relative to the average of the first two ACh controls. An alternative presentation of these data is provided in Supplemental Figure 2 with the individual cell responses used for ANOVA, which indicate significant inhibition (**p < 0.001) of HS receptor responses during the bath application, and increased (*p < 0.05) responses of the LS receptors after the 300 μM n-MP bath application.

3.9. n-MP effects on alternative α4-containing receptors and α3 analogs of HS and LS receptors

We evaluated the effects of 100 μM n-MP on α4β2 receptors with the α5 receptor in the accessory subunit position. These receptors are functionally like HS α4β2 receptors, showing similar high sensitivity to ACh and nicotine (Kuryatov et al., 2008; Zhou et al., 2003). We also evaluated the effects of 100 μM n-MP on α4/α6-containing receptors with the subunit composition β3α4β2α6β2 (Kuryatov and Lindstrom, 2011). We determined that 100 μM n-MP was an antagonist of the α4β2α5 responses (p < 0.05) but had no significant effect on the responses of the α6-containing receptors (Figure 9A).

Figure 9.

Figure 9.

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Effects of 100 μM n-MP on the ACh peak-current responses of other heteromeric nAChR. A) ACh responses of alternative α4-containing nAChR. Cells expressing receptors with the stoichiometry of α4(2)β2(2)α5 (n = 6) were prepared by co-expressing the α4β2 concatamer (Zhou et al., 2003) with monomeric α5. After control applications of 10 μM ACh, ACh was co-applied with 100 μM n-MP. Cells expressing receptors with the subunit composition of β3α4β2α6β2 (n = 6) were prepared by expressing the linked subunits as a concatamer (Kuryatov and Lindstrom, 2011). After control applications of 30 μM ACh, ACh was co-applied with 100 μM n-MP. There was significant (*p < 0.05) inhibition of the α4β2α5 receptors and no significant effects on the β3α4β2α6β2 receptors. B) Cells (n ≥ 6) expressing α3 and bias ratios of either β2 or β4 were prepared by injecting the alpha and beta subunit RNA at either a 1:5 or 5:1 ratio. After control applications of 100 μM ACh, ACh was co-applied with 100 μM n-MP. Data are the average responses (± SEM) of the response to the co-application relative to the ACh controls in the same cells. There was significant (*p < 0.05) increase in the responses of the α3β2 receptors with the increased expression of α3, consistent with n-MP effects on LS α4β2 receptors, and no significant effect on the other receptors.

The heteromeric nicotinic receptors of autonomic ganglia primarily contain α3 subunits, variously in combination with β2, β4, or α5 subunits (David et al., 2010; Rassadi et al., 2005). An alternative approach for modulation of the subunit stoichiometry of heteromeric nAChR is to inject RNAs at ratios that will bias receptors to having either three alpha and two beta subunits or the reverse (Zwart et al., 2008). Using cells injected with α3 and β2 or α3 and β4 subunits with alpha:beta ratios of 5:1 or 1:5, we determined that 100 μM n-MP produced significant potentiation of the α3β2 receptors with high levels of α3 (p < 0.05), but had no effect on α3β2 receptors with high levels of β2, nor on either set of α3β4 receptors (Figure 9B).

4. Discussion

Caffeine is consumed by 90% of the adult population in the United States. As noted previously, the primary psychoactive effect of caffeine is as an adenosine receptor antagonist (Nehlig et al., 1992; Ribeiro and Sebastiao, 2010). Adenosine, which acts to slow neuronal activity, builds up during sleep (Chou, 1992). Therefore, as might be expected, most caffeine (70%) is consumed before noon, often at breakfast, and intake decreases progressively over the day (Benson et al., 2019; Lieberman et al., 2019). Approximately 83% of the caffeine users in the United States are coffee drinkers (Loftfield et al., 2016).

Although tobacco use in our society has decreased over the last fifty years (Wittenberg et al., 2020), it still remains the third most commonly used addictive substance in the United States, and higher cigarette consumption has been reported to causally increase coffee intake (Bjorngaard et al., 2017). Therefore, we investigated potential interactions between elements of coffee and nicotinic receptor function.

Coffee is a complex solution containing many components of both high and low molecular weight (Burton et al., 2020; Perez-Miguez et al., 2019). In order to broadly sample these multiple components, in our initial studies we used coffee as it might be consumed to determine if there was α7 nAChR agonist or silent activity in coffee. We define silent agonists as substances that produce little or no ion channel activation but will activate large currents when co-applied with a PAM. In the first phase of our experiments, we determined that there is significant PAM-dependent α7 agonist activity in broths (coffees) made from both dark roasted (DRC) and unroasted (green) coffee beans (GBC). Additionally, these coffees produced slight activation and significant inhibition of α4β2 nAChR, a major class of receptors in brain believed to promote nicotine addiction (Papke et al., 2020). These α4β2 nAChR activities were largely preserved in ultrafiltrated low molecular weight (LMW) solutions that contained only components with molecular mass less than 1 kilodalton. Likewise, the LMW solutions retained the α7 PAM-dependent agonist activity, and the activity of the LMW GBC was greater than that of the LMW DRC, consistent with an effect of choline, which is higher in GBC than DRC.

The first phase of our experiments clearly has relevance to the potential effects of coffee as it is consumed by humans but failed to provide insight into the molecular mechanisms underlying those effects, or to identify other potentially more subtle effects of single components of the complex brew of coffee. Therefore, in the second phase of our studies, we surveyed the activities of a series of compounds known to be found in coffee, focusing on compounds with basic or quaternary nitrogens since many nAChR ligands are charged amines. We confirmed that caffeine lacks significant nAChR activity, and we only saw effects on α7 and α4β2 nAChR with two of the test compounds, n-MP and dMP, both of which are produced during the process of roasting the coffee beans (Lang et al., 2011; Wermann et al., 2014). We then focused our further studies on n-MP, since it is by far the more abundant of the two compounds in coffee (Stadler et al., 2002). However, it should also be noted that although the GBC do not contain n-MP they nonetheless inhibit HS α4β2 receptors, suggesting that there is a component other than n-MP in GBC that inhibits the HS receptors.

Our data suggest that n-MP binds competitively to the ACh binding site of α7 and HS α4β2 receptors and functions as an antagonist or a silent agonist. It has been proposed that LS α4β2 receptors contain a low affinity agonist site at the α4−α4 interface (Lucero et al., 2016), and LS α4β2 PAMs such as (R)-7-bromo-N-(piperidin-3-yl)benzo[b]thiophene-2-carboxamide (Br-PBTC) that bind to that site have been identified (Norleans et al., 2019). It is reasonable to hypothesize that the PAM activity of n-MP may also arise from binding to that same site.

The fact that n-MP can serve as a biomarker of coffee consumption (Bresciani et al., 2020) indicates that it has good bioavailability. Brewed coffee has been reported to contained about 491 μM n-MP. After consumption of 350 mL freshly prepared coffee brew, peak plasma concentrations reached micromolar levels within one hour and remained high for up to three hours (Riedel et al., 2014). It has been suggested that it may be a substrate for the human organic cation transporters 1 (hOCT1) and 3 (hOCT3) (Jinakote et al., 2020), so levels may be concentrated in the brain and potentially reach levels that could modulate nAChR function.

5. Conclusions

It is interesting to speculate whether the differential modulation of HS and LS α4β2 receptors by n-MP may relate to the association between coffee and cigarettes. Data from animal studies suggest that both HS and LS forms of α4β2 receptors exist in the brain (Grady et al., 2010), and the relative abundance of the two forms varies among brain areas (Fasoli et al., 2016). Nicotine has been shown to increase the relative abundance of HS receptors in vitro (Srinivasan et al., 2011). Under normal conditions, the cortex has been reported to have a relatively high basal expression of LS α4β2 receptors, while in the thalamus the expression of HS receptors is higher. It is well known that chronic nicotine increases the overall nAChR expression in the brain (Huang and Winzer-Serhan, 2006; Nashmi et al., 2007), and in the cortex, chronic nicotine selectively increases the expression of HS α4β2 receptors (Fasoli et al., 2016). It should be noted that, while HS receptors respond more sensitively to low levels of nicotine or ACh, they also desensitize more readily than LS receptors and generate smaller currents (Kuryatov et al., 2008; Nelson et al., 2003). The smoker then, during the active part of their day when they are smoking frequently, perpetually delivers nicotine to an elevated population of HS receptors that are limited in their responses to high concentration of nicotine. First thing in the morning, however, after the nicotine of the previous day has largely been metabolized, the HS receptors will be primed for the day’s first dose of the drug. The delivery of n-MP in the breakfast coffee may then tune that response to the first cigarettes of the day, decreasing the response of the upregulated HS receptors and perhaps increasing the activity of the LS receptors that will respond to the full dose of nicotine.

For many people, coffee is the paragon of caffeinated beverages, and while we attribute the property of being addictive to the caffeine, the drug itself is considered safe and its use acceptable. This invites the consideration that the other components of coffee may actually be beneficial and perhaps so too their modulation of nAChR.

Supplementary Material

1

Highlights.

  • Caffeine and nicotine are two of the three most commonly used addictive substances in the world.

  • Caffeine (coffee) and nicotine (cigarettes) are often used together after periods of abstinence.

  • Coffee has direct effects on the two main types of brain nicotine receptors.

  • The choline in coffee affects α7 receptors, and n-MP most affects α4β2 receptors.

  • n-MP inhibits one of the two main types of α4β2 receptors and potentiates the other.

Acknowledgments

This research was supported by the National Institutes of Health Grant, GM57481

Abbreviations

LMW

low molecular weight

n-MP

1-methylpyridinium

dMP

1,1-dimethylpiperidium

PNU-120596

1-(5-chloro-2,4-dimethoxyphenyl)-3-(5-methylisoxazol-3-yl)-urea

TQS

3a,4,5,9b-tetrahydro-4-(1-naphthalenyl)-3H-cyclopentan[c]quinoline-8-sulfonamide

GBC

green coffee beans

DRC

dark roasted coffee

Caf

caffein

Trg

trigonelline

Agm

agmatine

Spr

spermine

Tau

taurine

Lut

lutidine: 2-AP, 1-(2-aminoethyl)pyrrolidine

Footnotes

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The authors have no financial or competing interest in the outcomes of this study.

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