Organelle-specific single-molecule imaging of α4β2 nicotinic receptors reveals the effect of nicotine on receptor assembly and cell-surface trafficking

Abstract

Nicotinic acetylcholine receptors (nAChRs) assemble in the endoplasmic reticulum (ER) and traffic to the cell surface as pentamers composed of α and β subunits. Many nAChR subtypes can assemble with varying subunit ratios, giving rise to multiple stoichiometries exhibiting different subcellular localization and functional properties. In addition to the endogenous neurotransmitter acetylcholine, nicotine also binds and activates nAChRs and influences their trafficking and expression on the cell surface. Currently, no available technique can specifically elucidate the stoichiometry of nAChRs in the ER versus those in the plasma membrane. Here, we report a method involving single-molecule fluorescence measurements to determine the structural properties of these membrane proteins after isolation in nanoscale vesicles derived from specific organelles. These cell-derived nanovesicles allowed us to separate single membrane receptors while maintaining them in their physiological environment. Sorting the vesicles according to the organelle of origin enabled us to determine localized differences in receptor structural properties, structural influence on transport between organelles, and changes in receptor assembly within intracellular organelles. These organelle-specific nanovesicles revealed that one structural isoform of the α4β2 nAChR was preferentially trafficked to the cell surface. Moreover, nicotine altered nAChR assembly in the ER, resulting in increased production of the receptor isoform that traffics more efficiently to the cell surface. We conclude that the combined effects of the increased assembly of one nAChR stoichiometry and its preferential trafficking likely drive the up-regulation of nAChRs on the cell surface upon nicotine exposure.

Keywords: cell surface receptor; fluorescence; membrane trafficking; nicotinic acetylcholine receptors (nAChR); single-molecule biophysics.

Figure 1.

Schematic showing the generation of organelle-specific nanovesicles containing a single nAChR. Cells expressing fluorescently labeled membrane receptors are expressed throughout the ER and on the plasma membrane. Nitrogen cavitation is used to fragment the cells forming small membrane domains from cellular organelles. These membrane domains spontaneously form nanoscale vesicles. The domains and subsequent vesicles are small enough that there is a low probability of more than one receptor being encapsulated. The resulting vesicles have the same membrane properties as the organelle of origin, thus maintaining a physiological environment. Differences in the densities between the organelle membranes are used to separate them via gradient centrifugation. Vesicles are isolated on glass substrates for TIRF imaging.

Figure 2.

Ligand-induced up-regulation of nAChRs. A and B, schematics showing that TIRF imaging of SEP, a pH-sensitive analog of GFP, is used to determine the expression and distribution of receptors between the ER and plasma membrane. SEP was genetically encoded into the α4 subunit to generate an α4-SEP construct. The α4-SEP β2-wt nicotinic receptors were expressed in N2a cells and imaged under TIRF. A, when the pH of the extracellular solution (ECS) was maintained at 7.4, receptors both in the ER and in the plasma membrane were observable. The observed fluorescence intensity is due to both the ER and plasma membrane receptor populations. B, when the extracellular solution was replaced with a pH 5.4 solution, all SEP on the plasma membrane transition to a non-fluorescent state, and only the receptors within the ER are visible. C, the integrated density of α4β2 on the plasma membrane increased from ∼2.5 × 10⁶ in the absence of any compound to 7 × 10⁶ in the presence of nicotine (Nic) or cytisine (Cyt). Varenicline (Var) and bupropion (Bup) both resulted in a 2-fold increase in the integrated density on the plasma membrane demonstrating ligand-induced up-regulation. D, the percentage of the receptors present on the plasma membrane increased from 21.5% for control cells to 30–40% for all nicotinic receptor ligands, showing a shift in distribution of receptors toward the plasma membrane (n = 61, 47, 42, 38, 51). The data are mean values ± S.D.). ***, p < 0.001. Integrated density (average fluorescence intensity × area) is the total gray values background within a region of interest that encompasses a cell. PMID is obtained by subtracting the integrated density of pH 5 image of a cell from pH 7 image of the same cell.

Figure 3.

Single-molecule photobleaching to determine nAChR stoichiometry. A, representative mouse N2a cell expressing GFP-labeled nicotinic receptors in TIRF. B, representative TIRF image of isolated nanovesicles containing individual GFP-labeled receptors on a glass substrate. C and D, representative time traces of two (C) and three (D) photobleaching steps for GFP-labeled nicotinic receptors, corresponding to two or three GFP-labeled α4 subunits, respectively.

Figure 4.

Whole-cell evaluation of (α4)₂(β2)₃versus (α4)₃(β2)₂ assembly upon exposure smoking cessation agents. Expected distributions of one, two, and three photobleaching steps were obtained by weighting two binomial distributions. A χ² goodness-of-fit test was used to verify expected and observed distributions of two and three GFP-labeled α4 subunits. A, in the absence of a pharmacological agent, the α4β2 population exists as 41% (α4)₂(β2)₃ and 59% (α4)₃(β2)₂. B, 500 nm nicotine alters the ratio of isoforms to 59% (α4)₂(β2)₃ and 41% (α4)₃(β2)₂. C, 500 nm cytisine shifts the stoichiometry to 50% high-sensitivity receptors. D, 500 nm varenicline shifts the distribution to 54% high-sensitivity receptors. E, 500 nm bupropion shifts the stoichiometry to 55% high-sensitivity receptors, (α4)₂(β2)₃. The error bars for the subunit distribution are based on counting events and are calculated as the square root of the counts.

Figure 5.

Western blots verifying separation of ER and plasma membrane–derived nanovesicles. Anti-calnexin was used an ER marker to identify nanovesicles originating from the ER. Anti-PMCA was used to detect nanovesicles formed from the plasma membrane. Calnexin is detected in higher density fractions when vesicles are formed at 250 p.s.i. (A) and at 600 p.s.i. (B). Minimal PMCA is detected at fragmentation of 250 p.s.i. (C) but are localized to lower density fractions upon swelling with a hypotonic solution and higher cavitation pressure of 600 p.s.i. (D). ER-specific nanovesicles are collected from fraction 2 after 250 p.s.i. Plasma membrane–specific nanovesicles are collected from fraction 7 after formation at 600 p.s.i.

Figure 6.

Single-molecule bleaching step analysis shows organelle-specific differences in α4β2 nAChR isoforms. A, the observed ratio of vesicles showing one, two, or three steps was 0.057, 0.43, and 0.51, respectively (blue columns). These observed values were then fit to a 30:70 (high-sensitivity:low-sensitivity) stoichiometry. The fit was verified using a χ² goodness-of-fit analysis. B, the expression of α4β2 nAChRs on the plasma membrane fit binomial distributions weighted for 56% (α4)₂(β2)₃ and 44% (α4)₃(β2)₂. The observed fraction of vesicles showing one, two, or three bleaching steps was 0.12, 0.56, and 0.32, respectively. C, for ER resident receptors in the presence of nicotine, the observed fraction of one, two, and three bleaching steps were 0.086, 0.59, and 0.33, respectively. These observed values were then fit to a 55:45 distribution. D, the observed fraction of vesicles with one, two, or three bleaching steps were 0.11, 0.67, and 0.22, respectively. This was fit to a 70:30 distribution. The error bars for the subunit distribution are based on counting events and are calculated as the square root of the counts.

Figure 7.

Biased transfection of α4β2 to shift assembly toward the high sensitivity ((α4)₂(β2)₃) subtype in both the ER and the plasma membrane. The expected distribution of one, two, and three photobleaching steps was determined by weighting two binomial distributions, and the fit of expected and observed distribution was validated using a χ² goodness-of-fit test. The assigned weights represent the proportion of the high- and low-sensitivity stoichiometries. A, the observed photobleaching distribution of the receptors obtained from the whole-cell homogenate fit with the expected distribution obtained with 73% (α4)₂(β2)₃ and 27% (α4)₃(β2)₂. B, the ER originated receptors exhibited a photobleaching step distribution which agreed with 67% (α4)₂(β2)₃ and 33% (α4)₃(β2)₂ stoichiometries. C, the stoichiometry for receptors from the plasma membrane was 82% (α4)₂(β2)₃ and 18% (α4)₃(β2)₂. The error bars for the subunit distribution are based on counting events and are calculated as the square root of the counts.

Figure 8.

Organelle-specific single-molecule studies reveal a combination of endogenous preferential trafficking, and an intracellular increase in assembly may be responsible for nicotine-induced up-regulation. A, organelle-specific single-molecule photobleaching step studies of stoichiometry show that in the absence of nicotine, α4β2 predominately assembles into the 3α stoichiometry (blue) (70%). B, in the absence of nicotine, the 2α stoichiometry (green) is preferentially trafficked to the cell surface, resulting in a higher proportion of receptors on the cell surface having the 2α stoichiometry. C, in the presence of nicotine, the intracellular assembly of α4β2 is altered to favor the high-sensitivity, 2α isoform (green). D, the increase in availability of the preferentially trafficked stoichiometry, (α4)₂(β2)₃, leads to an even higher proportion of the 2α stoichiometry (green) on the plasma membrane (70%).