Single-molecule imaging with cell-derived nanovesicles reveals early binding dynamics at a cyclic nucleotide-gated ion channel

  1. Vishal R. Patel
  2. Arturo M. Salinas
  3. Darong Qi
  4. Shipra Gupta
  5. David J. Sidote
  6. Marcel P. Goldschen-Ohm

  • Curated by Biophysics Colab

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    Endorsement statement (30 August 2021)

    The preprint by Patel et al. describes the development of a single molecule approach for studying individual ligand binding events in membrane proteins within native lipid environments. The approach represents an elegant way to investigate the dynamics of ligand binding, and potential relationships with conformational changes, in molecules embedded within physiological membranes. The work makes an important contribution that will be of interest to scientists working on molecular mechanisms in ion channels and other membrane proteins.

    (This endorsement by Biophysics Colab refers to version 2 of this preprint, which has been revised in response to peer review of version 1.)

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Abstract

Ligand binding to membrane proteins is critical for many biological signaling processes. However, individual binding events are rarely directly observed, and their asynchronous dynamics are occluded in ensemble-averaged measures. For membrane proteins, single-molecule approaches that resolve these dynamics are challenged by dysfunction in non-native lipid environments, lack of access to intracellular sites, and costly sample preparation. Here, we introduce an approach combining cell-derived nanovesicles, microfluidics, and single-molecule fluorescence colocalization microscopy to track individual binding events at a cyclic nucleotide-gated TAX-4 ion channel critical for sensory transduction. Our observations reveal dynamics of both nucleotide binding and a subsequent conformational change likely preceding pore opening. Kinetic modeling suggests that binding of the second ligand is either independent of the first ligand or exhibits up to ~10-fold positive binding cooperativity. This approach is broadly applicable to studies of binding dynamics for proteins with extracellular or intracellular domains in native cell membrane.

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  1. Version published to 10.1038/s41467-021-26816-5
  2. Biophysics Colab

    Endorsement statement (30 August 2021)

    The preprint by Patel et al. describes the development of a single molecule approach for studying individual ligand binding events in membrane proteins within native lipid environments. The approach represents an elegant way to investigate the dynamics of ligand binding, and potential relationships with conformational changes, in molecules embedded within physiological membranes. The work makes an important contribution that will be of interest to scientists working on molecular mechanisms in ion channels and other membrane proteins.

    (This endorsement by Biophysics Colab refers to version 2 of this preprint, which has been revised in response to peer review of version 1.)

  3. Biophysics Colab

    Authors' response (6 August 2021)

    GENERAL ASSESSMENT

    This manuscript reports the development of a single molecule (SM) approach for studying individual ligand binding events for a membrane protein in a native lipid membrane environment. The authors express the eukaryotic TAX-4 cyclic nucleotide-gated channel in mammalian cells tagged on their cytoplasmic N-terminus with EGFP, form nanovesicles using nitrogen cavitation, separate the plasma membrane fraction from ER vesicles using gradient ultracentrifugation and then purify the fraction of vesicles containing TAX-4 oriented with its intracellular domains outward using GFP nanobodies immobilized onto cover slips. To visualize binding and unbinding of an agonist at the SM level, the authors utilize low concentrations of the fluorescent cGMP analog fcGMP along with TIRF microscopy. The authors develop the approach in a nuanced and cautious fashion, with nice controls to demonstrate that the preparation works for the TAX-4 channel, but also for a more complex assembly of GABA receptors comprised of alpha1, beta2 and gamma subunits. Adsorption of both TAX-4 and GABA receptors appears to be specific as fluorescent puncta are not observed without the GFP nanobody. In the case of TAX-4, many EGFP-positive puncta are observed that do not bind fcGMP, indicating that not all channels remain functional. fcGMP puncta are also observed that do not contain EGFP fluorescence, indicating that fcGMP can adhere to coverslips non-specifically. However, single binding events of fcGMP to EGFP-positive puncta can be readily observed, they can be competed out using cGMP, and both binding and unbinding events were analyzed quantitatively. The authors demonstrate that bound lifetimes are independent of agonist concentration, whereas unbound lifetimes decrease as agonist concentration increases, as would be expected if they are able to resolve individual binding and unbinding events. Bound lifetimes are poorly described by single exponential functions over a range of fcGMP concentrations, suggesting that TAX-4 channels have at least two distinct bound conformations. The authors explore a range of binding models to account for their results and find that their results are consistent with a model in which the nucleotide binding domain alternates between an open conformation that can bind and unbind agonist, and a closed conformation that hinders both binding and unbinding. The authors hypothesize that the conformational change correspond to an early step in the activation process, agreeing with cryo-EM structures of TAX-4 in the absence and presence of agonist. The modeling and interpretation of results is nuanced and presented in an open and objective fashion, although more details on the modeling would be helpful. The author also study double-bound events and uncover evidence that unbinding of the second ligand is slower than the first, suggesting positive cooperativity between the first and second agonist binding events. Overall, the methodology is well described, and the controls certify the quality of the data shown. The authors explain the limitations of the technique and restrict their focus to the two initial binding event and do not draw conclusions on the nature of the conformational change or whether the conformational change correspond to individual subunits or all subunits at the same time. Despite these limitations, the manuscript beautifully describes an elegant approach for studying ligand binding dynamics at the SM level and the possible relationship with conformational changes while the molecule is embedded in the physiological membrane. The following are suggestions the authors should consider when revising the manuscript.

    RECOMMENDATIONS

    Revisions essential for endorsement:

    • The authors should provide statistics on the number of colocalized spots compared to the number of non-colocalized GFP and fcGMP spots in GABA vs TAX-4. As seen in the GABA negative controls, colocalization does occasionally occur spuriously. It would be ideal to show this type of quantitation for experiments done on different days and with different vesicle preps to give the reader a sense of the frequency of binding competent channel proteins are observed and whether there is day to day variability. 60 hours of binding dynamics is also not a very useful statistic. Please provide the number of traces/replicates/individual vesicle preparations in the figure legends.

    We agree with the reviewers that statistics for overall number of experimental preps and spots vs. colocalized spots would be informative. Number of colocalized single molecules at each concentration in the final dataset: 10 nM: 112, 30 nM: 325, 60 nM: 63, 100 nM: 65, 200 nM: 132. In lieu of including this information in nearly every figure caption, we provide it in the Methods (page 26, line 9). Data were collected from four separate experimental preparations. However, there is also a fair degree of variability in the nonspecific binding observed at different locations even within a single chip. We did some manual selection at low laser power for areas with low background GFP fluorescence to attempt to record from the best spots in a chip, but we did not attempt a thorough search as this would necessarily also bleach GFP molecules needed for bleach step analysis. We attribute this variability to nonuniformity in the pacification PEG layer. In addition to the GABA control, we have also now done controls with a TRP channel containing an intracellular GFP. In these controls far fewer colocalized spots (~7%) were observed than with TAX-4 (30-40%) across all four preps. Although we agree that number of molecules/preps are informative, we disagree that the total recording time is not a useful piece of information. Indeed, for dynamics we would argue that it is one of the most important pieces of information and highlights a strength of our approach in that binding of fresh fcGMP allows long duration 4-7 min. recordings of individual molecules.

    We have merged Supplementary Figs. 4 and 5 (these are now all in Supp. Fig. 4) and added a new Supplementary Fig. 5 comparing colocalization statistics along with exemplar images for vesicles with GFP-TAX-4 and controls for vesicles with a TRPV1 channel containing an intracellular GFP. These data clearly show consistent colocalization only in the presence of TAX-4-GFP.

    • The authors prefer a model wherein a conformation change prevents the binding and unbinding of agonist. The authors explanation of their thinking and the exclusion of model M1.F wasn't always easy to follow. It would helpful if the authors provided a somewhat more complete explanation for why the model with the lower BIC is not the preferred and what constants are significantly lower to make the model M1.F worse than M1.E. This is important because this is used to discard binding and unbinding after the conformational change and support the hypothesized conformational change. Have the authors explored the possibility that the conformational changes detected are intermediate states different to the final state with the four binding sites occupied?

    This is an important point. Regarding M1.E vs M1.F, as expected for a model with an extra degree of freedom the BIC for M1.F is lower. However, it's only marginally lower, suggesting that the additional degree of freedom wasn't hugely beneficial. Furthermore, the binding and unbinding rates following the conformational change in M1.F are an order of magnitude slower than those preceding it, the rates for which match very well with M1.E (see Table S2). Although it is not our intention to completely rule out binding/unbinding after the conformational change, it seems that it is at least inhibited, and thus we opt for the simpler model lacking these transitions. We have added several sentences near the bottom of page 11 to clarify this.

    Additional suggestions for the authors to consider:

    • Do the authors have any additional data to inform on how well gradient ultracentrifugation enriches the PM fraction? Have the authors probed fractions with antibodies against ER resident proteins or those in other intracellular organelles?

    We did not additionally probe for ER proteins as was done previously (Fox-Loe et al., 2017). However, our results for the PM fraction match those in this prior study.

    • Quantifying fcGMP photobleaching rates based on those that are nonspecifically adsorbed to the surface probably isn't the most robust method. Dyes stuck to the surface will likely encounter higher intensities in the evanescent field due to their proximity to the surface and will often also have distorted photophysical properties as is observed in the traces shown. A better method would be to encapsulate fcGMP in vesicles and measure bleaching rates.

    We agree that dyes on the surface are likely to bleach more quickly, if anything, than dyes tracking binding events. However, this makes it a nice extreme limit control. If even these bleach times are long compared to our observed binding events, then it's unlikely that bleaching is grossly altering our observed dynamics. Regarding encapsulating dyes in vesicles, although this could be fruitful it also brings some complications. If the vesicle size is not tightly controlled (and even if it is) then there could be a significant excitation gradient across the vesicle that may lead to longer times to bleaching than would be observed at the binding site.

    • The distribution in individual fcGMP intensities observed could be caused by irregularities in the laser illumination spot or the emission pathway though this is limited in mmTIRF setups generally. The authors should comment on this in the methods.

    Nonuniformities in the optical excitation or emission paths would lead to spatial variation in fcGMP intensities, but not variation at a single site. The laser intensity is stable in time as judged by both background readings away from any identified spot and separate tests with a power meter, so it is unlikely to be due to artifactual fluctuations in laser power. The variability we observe likely requires some sort of dynamics at the site in question involving either a relative motion in the TIRF field gradient or photodynamics of the dyes themselves.

    • Have the authors considered whether it might be possible to do experiments with APT-cGMP or another analog for covalent ligand attachment to two of the CNBDs while the others are activated by fcGMP? This might be a useful way to examine agonist binding steps beyond the first two given the limitation of having to use low agonist concentrations.

    This is a great suggestion that we will investigate. We also have some similar ideas that we are currently pursuing in this regard.

    • The authors don't comment on whether the conformational change can occur in absence of ligand binding, a possibility included in the models. This event cannot be detected with this methodology but are relevant for the relationship of the conformational changes and gating of the channel and can modify the binding kinetics detected but not the unbinding kinetics. It would be helpful if the authors discuss uncertainties created by not knowing the extent to which the conformational change does or does not occur in the absence of agonist.

    Actually, we can detect this with the current methodology: analysis of unbound dwell times suggests multiple components consistent with at least two unbound states. Indeed, our favored single site model M1.E includes such a conformational change. This was also the case for our prior observations in isolated CNBDs from HCN channels. Thus, we do believe that this occurs. However, the rates for the conformational change are much slower in the absence of bound ligand (Table S2). For this reason, and because the models would otherwise have been too complex, we ignored this transition in models of two binding sites. We have amended the text near the top of page 12 to clarify this.

    • The inside-out orientation appears to work robustly for the TAX-4 channel. Can the authors comment in the discussion on potential intracellular mechanisms known to regulate TAX-4 or other cyclic nucleotide-gate channels that might be disrupted in this orientation? Many channels are regulated by PIP2, which would be depleted in the inside-out orientation.

    This is an interesting question, and we acknowledge that despite retaining the channel in the cell membrane, the vesicle preparation is not exactly a native environment. We also acknowledge that we did not control for any intracellular factors such as PIP2 that could regulate the binding dynamics. Intracellular PIPs are known to reduce apparent affinity of CNG channels for cGMP and to inhibit maximal current. Indeed, our approach could potentially provide some insight into which transitions were preferentially affected upon addition of PIP2 if it is largely absent from the vesicle prep, or any other intracellular factor for that matter.

    (This is a response to peer review conducted by Biophysics Colab on version 1 of this preprint.)

  4. Biophysics Colab

    Consolidated peer review report (23 July 2021)

    GENERAL ASSESSMENT

    This manuscript reports the development of a single molecule (SM) approach for studying individual ligand binding events for a membrane protein in a native lipid membrane environment. The authors express the eukaryotic TAX-4 cyclic nucleotide-gated channel in mammalian cells tagged on their cytoplasmic N-terminus with EGFP, form nanovesicles using nitrogen cavitation, separate the plasma membrane fraction from ER vesicles using gradient ultracentrifugation and then purify the fraction of vesicles containing TAX-4 oriented with its intracellular domains outward using GFP nanobodies immobilized onto cover slips. To visualize binding and unbinding of an agonist at the SM level, the authors utilize low concentrations of the fluorescent cGMP analog fcGMP along with TIRF microscopy. The authors develop the approach in a nuanced and cautious fashion, with nice controls to demonstrate that the preparation works for the TAX-4 channel, but also for a more complex assembly of GABA receptors comprised of alpha1, beta2 and gamma subunits. Adsorption of both TAX-4 and GABA receptors appears to be specific as fluorescent puncta are not observed without the GFP nanobody. In the case of TAX-4, many EGFP-positive puncta are observed that do not bind fcGMP, indicating that not all channels remain functional. fcGMP puncta are also observed that do not contain EGFP fluorescence, indicating that fcGMP can adhere to coverslips non-specifically. However, single binding events of fcGMP to EGFP-positive puncta can be readily observed, they can be competed out using cGMP, and both binding and unbinding events were analyzed quantitatively. The authors demonstrate that bound lifetimes are independent of agonist concentration, whereas unbound lifetimes decrease as agonist concentration increases, as would be expected if they are able to resolve individual binding and unbinding events. Bound lifetimes are poorly described by single exponential functions over a range of fcGMP concentrations, suggesting that TAX-4 channels have at least two distinct bound conformations. The authors explore a range of binding models to account for their results and find that their results are consistent with a model in which the nucleotide binding domain alternates between an open conformation that can bind and unbind agonist, and a closed conformation that hinders both binding and unbinding. The authors hypothesize that the conformational change correspond to an early step in the activation process, agreeing with cryo-EM structures of TAX-4 in the absence and presence of agonist. The modeling and interpretation of results is nuanced and presented in an open and objective fashion, although more details on the modeling would be helpful. The authors also study double-bound events and uncover evidence that unbinding of the second ligand is slower than the first, suggesting some positive cooperativity between the first and second agonist binding events. Overall, the methodology is well described, and the controls certify the quality of the data shown. The authors explain the limitations of the technique and restrict their focus to the two initial binding event and do not draw conclusions on the nature of the conformational change or whether the conformational change correspond to individual subunits or all subunits at the same time. Despite these limitations, the manuscript beautifully describes an elegant approach for studying ligand binding dynamics at the SM level and the possible relationship with conformational changes while the molecule is embedded in the physiological membrane. The following are suggestions the authors should consider when revising the manuscript.

    RECOMMENDATIONS

    Revisions essential for endorsement:

    1. The authors should provide statistics on the number of colocalized spots compared to the number of non-colocalized GFP and fcGMP spots in GABA vs TAX-4. As seen in the GABA negative controls, colocalization does occasionally occur spuriously. It would be ideal to show this type of quantitation for experiments done on different days and with different vesicle preps to give the reader a sense of the frequency of binding competent channel proteins are observed and whether there is day to day variability. 60 hours of binding dynamics is also not a very useful statistic. Please provide the number of traces/replicates/individual vesicle preparations in the figure legends.

    2. The authors prefer a model wherein a conformation change prevents the binding and unbinding of agonist. The authors explanation of their thinking and the exclusion of model M1.F wasn’t always easy to follow. It would helpful if the authors provided a somewhat more complete explanation for why the model with the lower BIC is not the preferred and what constants are significantly lower to make the model M1.F worse than M1.E. This is important because this is used to discard binding and unbinding after the conformational change and support the hypothesized conformational change. Have the authors explored the possibility that the conformational changes detected are intermediate states different to the final state with the four binding sites occupied?

    Additional suggestions for the authors to consider:

    1. Do the authors have any additional data to inform on how well gradient ultracentrifugation enriches the PM fraction? Have the authors probed fractions with antibodies against ER resident proteins or those in other intracellular organelles?

    2. Quantifying fcGMP photobleaching rates based on those that are nonspecifically adsorbed to the surface probably isn’t the most robust method. Dyes stuck to the surface will likely encounter higher intensities in the evanescent field due to their proximity to the surface and will often also have distorted photophysical properties as is observed in the traces shown. A better method would be to encapsulate fcGMP in vesicles and measure bleaching rates.

    3. The distribution in individual fcGMP intensities observed could be caused by irregularities in the laser illumination spot or the emission pathway though this is limited in mmTIRF setups generally. The authors should comment on this in the methods.

    4. Have the authors considered whether it might be possible to do experiments with APT-cGMP or another analog for covalent ligand attachment to two of the CNBDs while the others are activated by fcGMP? This might be a useful way to examine agonist binding steps beyond the first two given the limitation of having to use low agonist concentrations.

    5. The authors don’t comment on whether the conformational change can occur in absence of ligand binding, a possibility included in the models. This event cannot be detected with this methodology but are relevant for the relationship of the conformational changes and gating of the channel and can modify the binding kinetics detected but not the unbinding kinetics. It would be helpful if the authors discuss uncertainties created by not knowing the extent to which the conformational change does or does not occur in the absence of agonist.

    6. The inside-out orientation appears to work robustly for the TAX-4 channel. Can the authors comment in the discussion on potential intracellular mechanisms known to regulate TAX-4 or other cyclic nucleotide-gate channels that might be disrupted in this orientation? Many channels are regulated by PIP2, which would be depleted in the inside-out orientation.

    REVIEWING TEAM

    Reviewed by:

    Gabriel Fitzgerald, Postdoctoral Fellow (J.A. Mindell lab, NINDS, USA): membrane protein mechanisms, single molecule spectroscopy

    Pablo Miranda, Staff Scientist (M. Holmgren lab, NINDS, USA): ion channel mechanisms, electrophysiology, fluorescence spectroscopy

    Kenton J. Swartz, Senior Investigator, NINDS, USA: ion channel structure and mechanisms, chemical biology and biophysics, electrophysiology and fluorescence spectroscopy

    Curated by:

    Kenton J. Swartz, Senior Investigator, NINDS, USA

    (This consolidated report is a result of peer review conducted by Biophysics Colab on version 1 of this preprint. Minor corrections and presentational issues have been omitted for brevity.)

  5. Version published to 10.1101/2021.07.05.451181v2 on bioRxiv
  6. Version published to 10.1101/2021.07.05.451181v1 on bioRxiv