ATP-driven conformational dynamics reveal hidden intermediates in a heterodimeric ABC transporter

Reviewer #1 (Public review):

Summary:

Pecak et al have deciphered the conformational dynamics of a heterodimeric model ABC transporter, TmrAB, a functional homolog of the human antigen transporter TAP, using single molecule Forster resonance energy and fluorophores attached to residues at either nucleotide binding domains or periplasmic gate. The analysis not only differentiated ATP-free and bound states, but also enabled the real time monitoring of protein conformational changes precisely dissecting transport cycles and resolving transient intermediates. This study is absolutely significant in providing and establishing a general pipeline delineating the conformational dynamics in heterodimeric ABC transporters.

Strengths:

The scientific study is very well documented for experimental design, results and conclusions supported by the experimental data. Authors have determined the conformational dynamics of TmrAB across different ATP concentrations including physiological ones and resolved an outward open state and other conformational states consistent with previous cryoEM and DEER studies. Authors have also mentioned limitations in the study.

Comments on revised version.

Authors have worked on most of the revisions stated in previous feedback and included in the newer version, which has been significantly improved. Other comments have been described to be out of scope from this study.

Reviewer #2 (Public review):

In their manuscript entitled 'ATP-driven conformational dynamics reveal hidden intermediates in a heterodimeric ABC transporter', Pečak et al. use elegant single-molecule FRET experiments in detergent to investigate the heterodimeric ABC transporter TmrAB. By combining simulations of the transporter's accessible volume with elegant trapping strategies, the authors identify an unresolved outward-facing open state and conclude that it is usually obscured by a rapidly interconverting ATP-bound ensemble. Overall, the study demonstrates that smFRET can resolve the short-lived intermediate states of TmrAB and potentially other ABC transporters that are obscured in ensemble measurements.

It is a very interesting study that highlights the power of combining high-resolution structural information with spectroscopic approaches. I had three major concerns with the original version, all of which have been addressed by the authors in this revised version.

Author response:

The following is the authors’ response to the original reviews.

Public Reviews:

Reviewer #1 (Public review):

Summary:

Pecak et al have deciphered the conformational dynamics of a heterodimeric model ABC transporter, TmrAB, a functional homolog of the human antigen transporter TAP, using single-molecule Forster resonance energy and fluorophores attached to residues at either nucleotide binding domains or periplasmic gate. The analysis not only differentiated ATP-free and bound states but also enabled the real-time monitoring of protein conformational changes, precisely dissecting transport cycles and resolving transient intermediates. This study is absolutely significant in providing and establishing a general pipeline delineating the conformational dynamics in heterodimeric ABC transporters.

We thank the reviewer for this accurate and thoughtful summary of our work and its broader significance. We agree that the combination of single-molecule FRET with orthogonal validation approaches enables mechanistic resolution of conformational states and transitions that are not accessible by ensemble measurements. In particular, this framework allows direct discrimination of ATP-free and ATP-bound conformations, real-time tracking of transport cycle progression, and identification of transient intermediates in the heterodimeric ABC transporter TmrAB. We further agree that these capabilities support a generalizable strategy for dissecting conformation dynamics in related ABC transporters.

Strengths:

The scientific study is very well documented for experimental design, results, and conclusions supported by the experimental data. The authors have determined the conformational dynamics of TmrAB across different ATP concentrations, including physiological ones, and resolved an outward open state and other conformational states consistent with previous cryoEM and DEER studies.

Weaknesses:

The scientific study needs a bit of in-depth analysis with respect to consistency in K_d and its implications on the mechanism.

The apparent K_d,ATP values were determined using two complementary approaches that report on different aspects of the system. Ensemble FRET measurements yielded values of 51 ± 38 µM (TmrAB^NBD), 68 ± 25 µM (TmrAB^PG), and 95 ± 26 µM (TmrAB^PG_EQ), which are in good agreement with previously reported biochemical estimates (~100 µM for TmrAB^EQ) (Stefan et al, 2020). The slightly elevated value observed for the E→Q variant may reflect modest perturbation of nucleotide handling in this slow-turnover background. Notably, the close agreement between labeled and unlabeled variants indicates that fluorophore attachment does not measurably affect ATP binding.

In contrast, smFRET-derived K_d,ATP values (13 ± 1 µM for TmrAB^NBD and 2 ± 1 µM for TmrAB^PG) are systematically lower. This difference likely arises from the difficulty of deconvoluting overlapping FRET populations at sub-K_d,ATP concentrations, particularly for TmrAB^PG, where state assignment is less well separated. Despite this quantitative offset, both approaches consistently indicate ATP saturation well below physiological concentrations and therefore support the same mechanistic conclusion that ATP binding drives conformational switching in TmrAB.

Reviewer #2 (Public review):

In their manuscript entitled 'ATP-driven conformational dynamics reveal hidden intermediates in a heterodimeric ABC transporter', Pečak et al. use elegant single-molecule FRET experiments in detergent to investigate the heterodimeric ABC transporter TmrAB. By combining simulations of the transporter's accessible volume with elegant trapping strategies, the authors identify an unresolved outward-facing open state and conclude that it is usually obscured by a rapidly interconverting ATP-bound ensemble. Overall, the study demonstrates that smFRET can resolve the short-lived intermediate states of TmrAB and potentially other ABC transporters that are obscured in ensemble measurements.

It is a very interesting study that highlights the power of combining high-resolution structural information with spectroscopic approaches. I have three major points and a few minor criticisms.

We thank the reviewer for the thoughtful and constructive evaluation of our manuscript and for highlighting the strength of combining structural and single-molecule approaches. We have addressed all major and minor points in detail below and revised the manuscript where appropriate to clarify limitations, justify analysis choices, and improve transparency.

Major points:

(1) The main weakness is that the authors base their conclusions on a very limited set of FRET pairs. While TmrAB has been extensively studied in terms of its structure, the authors should at least acknowledge this limitation more clearly.

We agree that our conclusions are based on a limited number of FRET reporter pairs, and we now explicitly state this limitation in the revised manuscript. The chosen labeling positions were selected to probe two functionally critical regions—the nucleotide-binding domains and the periplasmic gate—based on prior structural and spectroscopic evidence. While this represents sparse sampling of the full conformational space, it is consistent with typical smFRET studies of membrane transporters, where experimental constraints generally limit the number of simultaneously accessible labeling positions (Asher et al, 2021; Asher et al, 2022; Levring et al, 2023; Wang et al, 2020).

Importantly, both independent reporter variants yield consistent ATP-dependent population shifts, supporting the robustness of the observed trends. We further clarify that additional labeling sites could, in principle, resolve finer structural sub-states; however, given the already limited population separation in the current variants, such extensions would likely provide diminishing returns in state resolvability under the present experimental conditions. This trade-off is now explicitly discussed.

(2) Most smFRET distributions were fitted with one, two, or three Gaussians. However, in several cases, additional populations with noticeable amplitudes appear to be present (e.g., Figure 3c at 0.1 mM and 3 mM ATP; Figure 4a, apo; Figure 4c, 0.3 mM R9L). Could the authors clarify why these populations were not included in the analysis?

We thank the reviewer for this careful observation. Low-amplitude sub-populations are occasionally detected in individual histograms; however, they were not included in the quantitative model because they do not meet criteria for reproducibility, amplitude robustness, or structural assignability. Specifically, these features vary between replicates, contribute minimally to total population, and cannot be mapped to structurally or biochemically defined states based on available cryo-EM (Hofmann et al, 2019), DEER/PELDOR (Barth et al, 2018; Barth et al, 2020), or accessible-volume simulations.

Similar minor subpopulations have been reported in smFRET studies and often attributed to photophysical or labeling heterogeneity effects (Asher et al, 2022; Husada et al, 2018). To avoid over-parameterization, we therefore restricted analysis to reproducible, structurally supported states. This rationale is now clarified in the revised manuscript.

(3) Figure 3c (3 mM ATP): Is it truly possible to distinguish the two states in this distribution?

We agree that state separation in the TmrAB^PG variant is limited (ΔE = 0.11), and we now explicitly acknowledge this constraint in the manuscript. To improve robustness under these conditions, we used a constrained fitting strategy in which the apo-state distribution was fixed from nucleotide-free measurement, reducing parameter degeneracy during fitting of ATP-bound datasets.

While single-molecule trajectory-based approaches such as Hidden Markov Modeling would be ideal for resolving dynamic interconversion, this was not feasible due to the low fraction of dynamic traces at the available temporal resolution. We therefore rely on population-level analysis, which remains consistent across replicates and reporter variants.

Notably, independent measurements from two reporter positions (TmrAB^NBD and TmrAB^PG) yield similar ATP-bound population fractions at saturating ATP concentrations (~77% vs. ~80%), supporting the robustness of the inferred state distribution despite partial overlap.

We have revised the manuscript to more clearly articulate methodological limitations, strengthen the justification of our analytical approaches, and improve the clarity of data presentation. These revisions enhance the transparency and robustness of the study and address the reviewer’s concerns.

Recommendations for the authors:

Reviewer #1 (Recommendations for the authors):

Here are a few comments that can help to improve the study.

(1) Line 115: The authors have checked the purity and monodispersity of the protein sample using SDS-Gel and size exclusion chromatography; however, additional characterization using negative stain electron microscopy, which clearly shows the monodispersity, will be useful.

We agree that negative stain EM can provide an additional assessment of sample homogeneity. Given the extensive prior structural characterization (Hofmann et al, 2019; Nocker et al, 2026; Nöll et al, 2017) and the SEC profiles presented here, we believe that additional negative stain EM would unlikely provide substantial new information regarding sample homogeneity. We have clarified this point in the manuscript by explicitly referencing the relevant cryo-EM studies.

(2) Line 116: The authors have mentioned that the enzymatic activity of TmrAB was retained after purification. Although smFRET results showing conformational dynamics of TmrAB confirm its ATPase activity, a comment on the effect of labelling on ATPase activity will be useful.

We appreciate this important point. Previous studies on spin-labeled TmrAB^NBD demonstrated transport activity comparable to wild-type TmrAB, indicating that cysteine substitution and label conjugation do not substantially perturb this variant (Barth et al, 2018). In addition, AV simulations showed that fluorophores at the TmrAB^NBD labeling positions do not interfere with ATP- or substrate-binding sites, supporting the conclusion that FRET labeling does not affect ATP binding, hydrolysis, or transport. For TmrAB^PG, however, equivalent transport data were not available, and AV simulations suggested interference of fluorophores with periplasmic gate dynamics. We therefore directly compared the transport activity of LD555/LD655-labeled TmrAB^PG and unlabeled wild-type TmrAB using a single-liposome transport assay with the fluorescein-labeled peptide C4F (RRYC^FKSTEL) (^F, fluorescein; Fig. 1– Fig. S3a). Both variants showed indistinguishable transport activity, demonstrating that fluorophore conjugation at the periplasmic gate preserves transport function.

(3) Line 117 and Figure S1c. Please add the reference for consistency of ATPase activity with previous studies on TmrAB.

We have added a reference to previous biochemical studies reporting comparable ATPase activity and kinetic parameters for TmrAB to support the consistency of our measurements.

(4) Line 119: It mentions that "Cysteine-maleimide labeling of detergent-solubilized TmrAB achieved site-specific labeling efficiencies exceeding 90%". The legend of Figure S1d mentions about labeling efficiency in the range of 40-50%. A clarification will be helpful for the reader. Also, calculations can be extended to the ratio of LD555 and LD655 labels on the molecule, which can be considered in analyzing results.

We apologize for the lack of clarity. The reported >90% labeling efficiency refers to the site-specific cysteine labeling efficiency per accessible site, as determined by dye incorporation. In contrast, the 40–50% values shown in Fig.1–Fig. S1d reflect the per-site efficiency for donor-lonely and acceptor-only populations respectively, which together account for the >90% overall labeling efficiency. We have revised the main text and figure legend to clearly distinguish between per-cysteine labeling efficiency and the fraction of correctly double-labeled molecules. We also clarify that only complexes with appropriate donor– acceptor stoichiometry were included in the smFRET analysis.

(5) Figure 1: Line 627: This line mentions "For all simulations, TmrA is shown in blue with LD655 (orange) and TmrB in yellow with LD555 (green)." Is it (which label on which subunit) known for the experimental setup?

We thank the reviewer for pointing out this potential source of confusion. In the experimental system, fluorophore attachment occurs stochastically. Therefore, the assignment of donor and acceptor dyes to specific subunits is random. The representation shown in Figure 1 reflects one possible configuration for visualization purposes only. We have clarified this explicitly in the figure legend to avoid misinterpretation.

(6) Figure S1-2a. Tau value can be better represented in a graph for visual readers instead of in the form of a table, and a dotted line with the threshold (~1 ns) will give a better representation of no change. Values can be included in the graph as well.

We appreciate this helpful suggestion. We have revised Figure S1-2a to include a graphical representation of fluorescence life times, including a reference line around ~1 ns to facilitate visual comparison. Numerical values are retained alongside the plot for completeness.

(7) Figure 2a: Each component of the assembly has been pointed with an arrow, which can mix two components and confuse readers. It would be good to make a legend column on the left or right and depict or indicate each component of the assembly clearly.

We have changed the labeling in Figure 2a to improve clarity by separating the components and introducing a clearer legend layout, ensuring that each element of the assembly is unambiguously labeled.

(8) The physiological concentration of ATP can range up to 5-10 mM. A comment on choosing the ATP concentration specifically to be 3 mM would be useful for the readers.

We appreciate this suggestion. While intracellular ATP concentrations can reach up to 5–10 mM, values around 3 mM are commonly used as physiologically relevant conditions in in vitro biochemical and biophysical studies. We selected 3 mM ATP as a representative near physiological concentration that ensures saturation of ATP-dependent conformational transitions while remaining comparable to previous studies on TmrAB (Hofmann et al, 2019; Nocker et al, 2026; Nöll et al, 2017; Stefan et al, 2020). We have clarified this rationale in the manuscript.

(9) Figure 2c is not cited in the text.

We thank the reviewer for noting this oversight. Figure 2c is now explicitly cited in the main text.

(10) Results in Figure 2 and 3 have been analyzed using 2 and 3 Gaussian distributions, respectively. It would be good to explain the rationale for it.

We appreciate that this important point was brought to our attention. The number of Gaussian components was determined based on the minimal model required to describe reproducible and structurally supported populations. For ATP titration experiments (Figure 2 and Figure 3), two populations (apo and ATP-bound) were sufficient and consistent across replicates. In contrast, three populations were required under trapping conditions (Figure 4), where an additional state (OFF^open) becomes kinetically stabilized and clearly resolved. We have clarified this rationale in the manuscript.

(11) Figure 3b: data points do not seem to be saturated with respect to ATP concentration. It needs more points beyond 3 mM. Different K_d at different sites in the structure could represent differential local dynamics over the structure.

Previous structural studies demonstrated that 1 mM ATP is sufficient to saturate both nucleotide-binding sites under trapping conditions (Hofmann et al, 2019), indicating that the concentration range used here is adequate. Consistent with this, both ensemble and smFRET measurements approach saturation by 3 mM ATP, a near-physiological condition commonly used in biochemical studies. While additional data points above 3 mM could further define the plateau, they are unlikely to alter the mechanistic conclusion. We have clarified this point in the manuscript.

(12) Figure 3 and Figure 1 - S1 have two different Kd values with respect to ATP concentration; both of these graphs measure conformational changes using smFRET. A comment specifying these Kd values based on single molecule verses ensemble measurement from will be helpful for readers.

We appreciate this important point and have clarified it in the manuscript and the response to Reviewer #1 above. The K_d,ATP values in Fig. 1–Fig. S1 are derived from ensemble FRET measurements, whereas those in Fig. 3 are obtained from smFRET population analysis. This difference likely arises from the difficulty of deconvoluting overlapping FRET populations at sub-K_d,ATP concentrations, particularly for TmrAB^PG, where state assignment is less well separated. Despite this quantitative offset, both approaches consistently indicate ATP saturation well below physiological concentrations and therefore support the same mechanistic conclusion that ATP binding drives conformational switching in TmrAB. We now explicitly distinguish these methods and their interpretation in the manuscript.

(13) Figure 4: Slow-turnover TmrAB mutant has been employed in cysteine mutant on the PG opening side, but not towards the NBD side. Either experimental data or a comment on not pursuing it would be helpful for the reader. Similarly, experiments in the presence of peptide and in the absence of ATP, which can help to understand the role of substrate in conformational dynamics in the absence of ATP, are not pursued in this study. Along similar lines, experiments with wild type, in the presence of MgADP +/- substrate, are not shown in this study.

We thank the reviewer for these insightful suggestions. The slow-turnover variant was specifically applied to the periplasmic gate reporter (TmrAB^PG) because this construct provides direct sensitivity to outward-facing conformations, which are central to resolving the OF^open state. In contrast, the NBD reporter primarily monitors nucleotide-binding domain (NBD) dimerization and is less suitable for distinguishing periplasmic conformational differences.

Experiments in the absence of ATP but in the presence of peptide, as well as MgADP ± substrate, would indeed be valuable for further dissecting substrate effects. However, these conditions are beyond the scope of the current study, which focuses on ATP-driven conformational dynamics and the identification of kinetically hidden intermediates. We have added a statement in the Discussion to acknowledge these possibilities as directions for future work.

(14) Figure 4, peptide concentration has been varied in the right panel. The result can also be presented as the % of OFopen and OFoccluded state with increasing concentration of peptide.

We thank the reviewer for this suggestion. While such a plot would indeed be informative and could improve our understanding of substrate binding and substrate-induced trans-inhibition, the current dataset does not contain sufficient data points to construct a reliable concentration-dependent curve, particularly given that peptide saturation was not reached in our experiments. The characterization of substrate binding is further complicated by the presence of two distinct substrate-binding sites one in the outward-facing and one in the inward-facing state with likely completely different K_d values and would require a more complex binding model. We have therefore decided against including this plot in the current manuscript. We do acknowledge, however, that future smFRET studies with improved temporal resolution are particularly well suited to investigating substrate binding to TmrAB and its effects on conformational equilibrium, and we have noted this in the Discussion.

Reviewer #2 (Recommendations for the authors):

(1) In all figures, can you please label the transporter schematics with the conformational states they represent?

We thank the reviewer for this suggestion. All transporter schematics in the main and supplementary figures have been updated to include clear labels indicating the corresponding conformational states, thereby improving clarity and consistency.

(2) As a suggestion, it may improve clarity to include the labelling positions (residue numbers) directly in Figure 1a and b, even though they are provided in the legend.

We appreciate this suggestion. Residue numbers corresponding to labeling positions have now been added directly to Figure 1a and b to improve readability and facilitate interpretation.

(3) Lines 183-188: This is a key point. It would be helpful to include a reference line for the expected state (0.63). Interestingly, this value coincides with the shoulder observed in Fig. 3c (0.1 mM ATP). Is there an explanation for this (see also point 2)?

We thank the reviewer for highlighting this point. We considered adding a reference line at 0.63 to the plot; however, we decided against it. While a subpopulation does appear at ~0.63 —consistent with the expected FRET efficiency of the OF^open conformation—it is only present in a single condition (0.1 mM ATP) and is not observed across other ATP concentrations for this TmrAB variant. It more likely reflects a minor non-reproducible subpopulation or photophysical artefact, in line with our response to Point 2 of the public review (Reviewer #2).

(4) The final section of the Results section seems like an afterthought, especially since the heading suggests a broader scope.

We appreciate this comment. We have revised the final section of the Results to improve its structure and ensure that the scope indicated by the heading is fully reflected in the content. This section now more clearly integrates kinetic and thermodynamic aspects of the transport cycle.

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