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Structural dynamics determine voltage and pH gating in human voltage-gated proton channel

Cite this dataset

Wang, Shizhen (2022). Structural dynamics determine voltage and pH gating in human voltage-gated proton channel [Dataset]. Dryad.


Voltage-gated ion channels are key players of electrical signaling in cells. As a unique subfamily, voltage-gated proton (Hv) channels are standalone voltage sensors without separate ion conductive pores. Hv channels are gated by both voltage and transmembrane proton gradient (i.e ∆pH), serving as acid extruders in most cells. Amongst their many functions, Hv channels are known for regulating the intracellular pH of human spermatozoa and compensating for the charge and pH imbalances caused by NADPH oxidases in phagocytes. Like the canonical voltage sensors, Hv channels are a bundle of 4 helices (named S1 through S4), with the S4 segment carrying 3 positively charged Arg residues. Extensive structural and electrophysiological studies on voltage-gated ion channels, in general, agree on an outwards movement of the S4 segment upon activating voltage, but the real-time conformational transitions are still unattainable. With purified human voltage-gated proton (hHv1) channels reconstituted in liposomes, we have examined its conformational dynamics, including the S4 segment at different voltage and pHs using single-molecule fluorescence resonance energy transfer (smFRET). Here, we provide the first glimpse of real-time conformational trajectories of the hHv1 voltage sensor and show that both voltage and pH gradient shift the conformational dynamics of the S4 segment to control channel gating. Our results indicate that the S4 segment transits among 3 major conformational states and kinetic analysis suggest that only the transitions between the inward and outward conformations are highly dependent on voltage and pH changes. Our smFRET studies uncover the stochastic conformational dynamics of S4 and demonstrate how voltage and pH shift its conformational distributions to regulate channel gating. Altogether, we propose a kinetic model that explains the mechanisms underlying voltage and pH gating in Hv channels, which may also serve as a general framework for understanding the voltage sensing and gating in other voltage-gated ion channels.


Liposome fluorescence flux assay

The K+ gradient between inside and outside of the liposomes was established by diluting the liposomes in the extraliposomal buffer containing 20 mM Hepes, 150 mM NMDG, pH7.5. The liposomes were incubated with 2 µM of ACMA fluorescence probes for ~5 min, then ACMA fluorescence was measured using a 96 well plate reader (FluoStar, Ex/Em = 390nm/460nm) for ~5 min. After valinomycin was added at a final concentration of 0.45 µM, the fluorescence measurements were resumed with the same optical setting for ~40 min. Proton-specific ionophore CCCP was used as the positive control, and empty liposomes without hHv1 channels were used as negative controls. The fluorescence liposome flux data were processed following the method of Su et al (32). In brief, the hHv1 channel activities were calculated from the fluorescence readings normalized between 0 and 1 using the following equation:

A = (F0 – Fval)/(F0-Fcccp)

where F0, Fval and Fcccp were the steady-state ACMA fluorescence at initial, after adding valinomycin and CCCP, respectively. The relative activities of the hHv1 channel were normalized against the hHv1 WT proteoliposomes included in every batch of assays.

Single-molecule imaging and data analysis

Flow chambers for smFRET imaging were prepared following the protocol of Joo et al (33). An objective-based TIRF built on a Nikon TE-2000U inverted microscope (TE-2000s) with 100x APO TIRF NA1.49 objective lens, 532 nm and 640 nm lasers, was used for single-molecule imaging. Donor and acceptor emissions were separated by W-view Gemini beam splitter with chromatic aberration correction (Hamamatsu Inc.) carrying the 638 nm long-pass beam splitter, then cleaned by 585/65 nm and 700/75 nm bandwidth filters (Chroma Inc.). The images were collected by an ImagEM X2 EMCCD camera (Hamamatsu Inc.). The liposomes containing fluorophore-labeled hHv1 channels were retained on the PEGlyated surface coated with biotinylated Histag antibodies (1:200 dilution, ThermoFisher). Fluorophores were excited by a 532 nm laser (~1.0 W/cm2) and time-lapse movies were collected at 10 frames per second (i.e, time resolution of 100 ms). The 640 nm laser (~1.0 W/cm2) was only used to confirm the existence of acceptor fluorophores when overall FRET was very low. Typical recording time was ~3 min, with half bleaching time being ~ 1 min. All imaging buffers contained ~3 mM Trolox, 5 mM PCA, and 15 μg/μL of PCD to enhance the photostability of the fluorophores (34, 35). For symmetrical pH conditions, β-escin at a final concentration of 50 µM was used to permeabilize liposomes(36). At least 3 batches of independent smFRET imaging were performed for each sample/condition. The movies were imported into the SPARTAN software directly without any corrections (22). The donor and acceptor channels were aligned using 2D maps generated from TetraSpeck fluorescent beads (T7279, Invitrogen). The molecules were identified as point-spread functions using the threshold method with a window size of 7 pixels. The smFRET traces were extracted and then preselected using the Autotrace function of the SPARTAN software with criteria setting as FRET Lifetime >50 frames, donor/acceptor correlation coefficient between -1.1 and 0.5, Signal-to-Noise ratio >8, background noise level <70, Cy3 blinks <4 and overlap molecules removed (22). The resulting traces were further picked manually following the criteria described in the previous studies (37, 38). The FRET efficiency E was calculated with the following equation:

E = (IA-ID*0.07)/(IA+ID)

Where IA and ID are intensities of the donor and acceptor fluorophores. The cross-talk value is 0.07, determined from a protein sample containing the donor fluorophore only.

Overall, there were ~500 molecules per field of view with ~100 molecules containing both acceptor and donor fluorophores. The bin size of all histograms and contour maps was 0.03 and FRET contour plots were generated from the smFRET data of the first 5s. For kinetic analysis, a kinetic model containing 4 FRET states was used, with one state assigned to bleaching or blinking events as FRET close to 0 (Figure 1F). The FRET peak centers were fixed for all smFRET traces from the same labeling sites, with the K125C-S224C sites as 0.27, 0.6 and 0.9 and the K169C-Q194C site as 0.24, 0.52, and 0.78. These peak centers were determined by Gaussian fit to the FRET histograms from all smFRET traces of the same labeling sites (Figure 1-figure supplement 3B). The smFRET traces were idealized using the Maximum Point Likelihood (MPL) algorithm included in the SPARTAN software, which allows model constraints and directly optimizes rate constants obtained at different experimental conditions (23).

Usage notes

The zip file contains all the data of this paper, including the supplementary figures. The data were sorted by the figure number, panel name, and data type.


National Cancer Institute, Award: 1R15GM137215-01

University of Missouri–Kansas City