How long gtp

This step was repeated twice to ensure complete nucleotide exchange. After the second buffer exchange, this EA tubulin polymerized in the presence of 0.

These microtubules were then transferred to room temperature and stored until use. Single molecule experiments on dynamic microtubules were performed similarly to the dynamic assays Figure 4. We chose wildtype and ED tubulin concentration, at which wildtype and ED microtubules grew at nearly identical growth speeds Figure 4—figure supplement 3.

Samples for steady state bleaching assays were prepared identically to the single molecule experiments for each respective tubulin species wildtype, ED, EA except that only 2. Both beams were rapidly scanned azimuthally using a galvo scanning system iLas2, Gataca Systems, France to provide uniform illumination and reduce interference effects. Both camera relays had a total magnification of 2x.

Time-lapse movies were acquired with 63 ms exposure time at 1 Hz for 10 min. For each sample, an average static background image was created by translating the sample rapidly while acquiring a movie stream, and averaging the resulting image series. The raw iSCAT movie was then divided by the corresponding average background image to produce a pseudo-flat-field corrected, normalized movie. This was then filtered using a mask in Fourier-space, to remove large-scale dynamic interference effects, and a Kalman stack filter to reduce noise.

Exposure times were between 55 ms single molecule imaging and ms nucleation assays. Images were acquired at intervals of every 60 ms single-molecule imaging , 1 s nucleation assays , or ms comet analysis keeping imaging conditions consistent for each set of experiments. For steady-state bleaching, movies were acquired with identical laser illumination powers and exposure times 55 ms , and increasing frame intervals 60, , ms.

Kymographs were generated as described previously Jha et al. After acquisition, movies were corrected for drift when necessary, then individual microtubule growth trajectories were drawn on a maximum intensity projection of the entire movie stack Figure 4—figure supplement 1a.

Kymographs were generated from the movie stack along each trajectory line; subsequently, the microtubule end position was traced manually on each kymograph Figure 4—figure supplement 1b 3.

Periods including overlapping microtubules were excluded from the analysis. Microtubule growth speeds were calculated from the marked end position on the kymographs.

Our iSCAT microscopy setup allowed us to image microtubules consisting entirely of unlabeled recombinant tubulin, but did not produce images of the quality required for automated microtubule end tracking with sub-pixel precision Bohner et al. Therefore, we based our comet and single molecule analysis see below entirely on TIRF microscopy movies of fluorescently labeled EB3. For comet analysis, average spatial mGFP-EB3 intensity profiles comets Figure 3i—j were generated from kymographs as described previously Jha et al.

Each kymograph was straightened and re-centered using the marked microtubule end positions, then aligned and averaged with other straightened kymographs. The intensities were averaged for all time points at each position along the resulting average kymograph, giving a time-averaged spatial intensity profile.

Kinetic rate constants were extracted from an exponentially modified Gaussian fit to the comet profile, as described previously Maurer et al.

To determine the affinity of EB3 for binding to wildtype microtubules, average maximal comet intensities were measured as a function of the mGFP-EB3 concentration Figure 2c. The equilibrium dissociation constant K d was determined from a hyperbolic fit to the data Figure 2d , because EB3 was in large excess over binding sites at microtubule ends in these experiments.

To obtain dwell time distributions for the single molecule mGFP-EB3 experiments Figures 2j, k and 4a—h , kymographs were generated and the microtubule end positions traced, as described above Figure 4—figure supplement 1a—b. Using the traced end position, the corresponding x-y coordinates of the microtubule end in the original movie were calculated for each frame Figure 4—figure supplement 1c.

These coordinates were used to create a binary mask movie that only included points on each microtubule up to the growing end in each frame. The resulting localization positions were filtered in space and time using the binary mask movie, to remove all events not localized on a microtubule Figure 4—figure supplement 1d. The remaining localization events were linked together in space and time throughout the whole movie using specific thresholds: only two events that occurred within a maximum separation of one pixel nm and 30 frames 1.

This allowed for slight movement of the molecules between frames due to e. The linking parameter values were chosen after a careful inspection of the effects of the parameter space on the resulting individual dwell events, for a specific kymograph. The automatically identified binding events agreed well with visually identified events in test subsets of the data Figure 4—figure supplement 1e.

For each molecule, the dwell time was determined by the total time over which events were linked. The position of the molecule in the first frame of the binding event relative to the nearest microtubule end was calculated, creating a list of dwell times with their corresponding distances from the growing microtubule end Figure 4—figure supplement 1f.

For spatially resolved dwell time distributions, binding events were binned at specific distances from the end Figure 4—figure supplement 1g and the dwell time '1 - cumulative distribution function' survival function calculated for each bin. Characteristic dwell times were extracted from these distributions using a mono-exponential fit.

The average dwell time measured for single mGFP-EB3 molecules bound to the growing ends of recombinant human wildtype microtubules was ms Figure 4f , which is comparable to previous reports of EB dwell times being in the range of 50— ms Bieling et al. The longer mean dwell time observed here is probably a consequence of the lower ionic strength buffer used. However, single molecule dwell times on EA microtubules were in the range of our bleaching time and were therefore determined from a steady state bleaching analysis performed at different time intervals Figure 2—figure supplement 1g ; Gebhardt et al.

We assume that molecules bound to the microtubule bleach at a rate k b and unbind at a rate k off. We assume an excess of unbleached EB3 molecules in solution such that at steady-state the binding rate of unbleached molecules is limited by the total unbinding rate.

Solving the resulting differential equations gives a relative unbleached fraction at time t after illumination of. Movies taken at different frame intervals were background corrected using a 50 pixel rolling ball subtraction. The mean intensity over the field of view was calculated for each frame, and normalized to the value in the first frame. Decay curves were fit with the function above, with k off shared globally Figure 2—figure supplement 1g.

All data are available in the manuscript or the supplementary materials. Correspondence regarding data and materials should be addressed to TS. All data generated or analysed during this study are included in the manuscript and supporting files. In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses. This carefully executed in vitro reconstitution study resolves some important questions concerning the nature of the cap that stabilizes growing microtubules.

The study will be of interest to a broad biological audience interested in cytoskeletal regulation. Thank you for submitting your article "The speed of GTP hydrolysis determines GTP cap size and controls microtubule stability" for consideration by eLife. Your article has been reviewed by three peer reviewers, and the evaluation has been overseen by Anna Akhmanova as the Senior and Reviewing Editor.

The reviewers have opted to remain anonymous. The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission. The reviewers agreed that this is a rigorously performed study, which addresses important questions about the relationship between the stabilizing cap at growing microtubule ends, the nucleotide state of tubulin and the tubulin state recognized by End Binding proteins.

The finding that EB3 specifically recognizes the GTP form of tubulin is an important, though perhaps not entirely surprising contribution to the field. Further, all three reviewers agreed that the description of a gradient of EB binding affinity along the microtubule end is the most novel and interesting part of the paper, but also the part that needs to be worked out better.

Specifically, the conformational transition model raised a number of critiques, and these should be addressed by additional experiments and analyses,and possibly also by adjusting the writing of the paper. Since there might be different ways of extending this part of the paper, I include below a summary of the reviewers' discussions and also the full reviews. Could GTP tubulin exist in either the expanded or the compacted state according to a conformational equilibrium?

It should be possible to obtain these data without generating a high resolution structure, perhaps by using TPX2 binding experiments or by a 2D cryo-EM analysis. Further, the conclusions about a conformational gradient are based on a limited set of data, and as, pointed out by the reviewers, alternative explanations of the obtained results are possible.

One could consider performing experiments with a monomeric EB3 protein, because they might help to rule out or provide support for the model proposed by reviewer 1. Another idea raised during the consultation between the reviewers was to use as a binding substrate microtubules grown from mixtures of EA and wild type tubulin at different ratios. Two reviewers questioned the assignment of 'mono exponential' distributions in Figure 4, and this critique should be addressed. Finally, two reviewers found that the split comets deserve some analysis, and the faster growth rate displayed by ED microtubules requires some attention.

Roostalu et al. They make the surprising observation that the dwell time of EB3 molecules changes as you go deeper in the cap. As expected from the Surrey lab, this is a high quality paper addressing a central issue in the microtubule field, namely the role of GTP hydrolysis.

The decrease in dwell times is hypothesized to be caused by a gradual "conformational gradient" that reduces EB3 affinity. The visual representation of this idea is the color gradient from red to yellow in the schematic in Figure 4J. I have an alternative hypothesis for why the dwell times decrease. Consider that EB3 is an "obligatory dimer" Sen et al. At the very end of the microtubule, EB3 is likely to find two adjacent sites where all of the relevant tubulin dimers are in the GTP state.

The site has 4 dimers, but we can leave aside for the moment the question of their relative relevance. These states have different affinities for EB3. EB3 becomes functionally monomeric, hanging on to the microtubule with only one hand. In contrast, EB3 at the very end of the microtubule is holding on with both hands. Note: the EB3 construct they are using appears to be full-length when I trace back through their Materials and methods references. Can this alternative framework explain the decrease in dwell times with depth inside the cap Figure 4C?

More specifically: a gradual transition from dimeric to monomeric affinity conditions, driven by the probabilistic availability to two binding sites with different affinities? Are the measurements precise enough to rule out this hypothesis? The visual representation of this idea would NOT be a color gradient but rather an increased "speckling" of red and yellow blocks.

They divide the microtubules into bins based on distance from the plus-end. The bin size is approximately 0. These bins are relatively small when you consider that: 1 the microtubule end-position is not determined with sub-pixel accuracy, but is determined rather using the "traced end position" from a manual-tracing of a kymograph, which they state has 0. The first two points make me uncertain whether the molecules are being correctly placed into their bins.

The 3rd point is more conceptual: what is the best way to treat a molecule whose bin changes beneath it? They appear to start off linear but then deviate from linearity at, e.

The central argument of the paper hinges on the fact that Figure 4B is not mono-exponential but Figure 4C is mono-exponential. Are the fits really strong enough to support this? The distributions are described as "strikingly mono-exponential". What does strikingly mean in terms of goodness of fit? How often are they observed? How bright are the split comets compared to a full comet, etc. That's fine; the Roll-Mecak lab uses similar constructs. The Materials and methods are clear about the retention of the internal His tag but the main text is not.

I think it's important to be clear throughout. Alternatively, in the concluding paragraph, the authors say that high-resolution structures are on the way. But one doesn't necessarily need a 3. What motivates this hypothesis? Are there data, structures, kinetic measurements, conceptual arguments, etc, that would motivate this idea?

Are there measurements of the GTPase activity with non-human proteins that would provide support for this idea? This is an interesting and well-executed paper that addresses interesting questions about the microtubule's stabilizing cap, how it relates to nucleotide state, and what is the preferred state that EB proteins recognize.

The experiments are performed rigorously and for the most part described clearly, and the work has been done to a high technical standard.

The main findings of the paper are: i that abolishing or at least substantially slowing; EA GTPase results in very stable microtubules akin to GMPCPP microtubules, ii that moderately slowing ED GTPase results in microtubules with longer EB comets that are also more stable, and iii that in these longer comets and also wild-type comets , there appears to be a gradient of EB binding affinity, with the highest affinity being closest to the growing end.

Although it has not been shown directly before using a mutant, I did not find it all surprising that reducing GTPase rate increased microtubule stability, but it is nice to see this in the way that it is shown here. The findings involving EB binding are more interesting: they provide some of the most direct support for the idea of an adaptable microtubule lattice, and they raise questions about what states commonly used GTP analogs are giving.

I think the site-specific EB analysis is probably the most interesting and mechanistic part of the manuscript, and the authors might want to place a little more emphasis there and place less emphasis on some of the obvious-sounding claims.

I don't think new experiments are required, but they may want to go deeper into some of the analysis of the EB binding. Could the authors commend on whether they think the switch in protofilament number or the different conformation of tubulin or both account for the lack of EB3 binding?

I think this should be made more clear. This is unexpected, and the authors really don't say much about it. This is what they measured, of course. Since they know the growth rates, is there anything interesting to learn from plotting the decay against time or just transforming to get the time dependence?

A few more sentences about this might be useful. In particular, while the authors ascribe various deficiencies to nucleotide analogs, they do not seem to consider the possibility that the mutation s they made might also perturb the structure.

This criticism applies to the main text also. Some version of the discussion of induced fit should probably be incorporated into the main text. The study by Roostalu et al. The present study examines the binding of the major plus end tip tracking protein, EB3, and its ability to specifically recognize the GTP form of tubulin.

Here, it is shown, using tubulin mutants that either fail to hydrolyze or hydrolyze slowly, that EB3 specifically recognizes the GTP form of tubulin. This is an important finding for the field, one that is achieved through elegant experimental studies of mutant tubulin and careful quantitative analysis, for which the authors are to be commended. However, in the final analysis, the authors invoke a GDP-Pi intermediate state, without strong evidence to justify it.

Rather, it seems possible that a simpler alternative explanation that only assumes GTP and GDP states, as suggested by their data, is not ruled out. Thus, I am concerned that the study, while making an important contribution to the field, may be misleading in its final interpretation.

The spatially resolved dwell time is interesting, but the two positions that are farther away from the tip appear that they may be bi-exponential. It seems the non-exponential distribution might be expected as the k off jumps when the hydrolysis occurs, which would give spatially varying dwell times and nonexponential distributions as the hydrolysis can occur at random Poisson process during the observation time. To rule this out it will be necessary to do model-convolution to make it convincing that the analysis method is not yielding spurious results.

Even then, the EB binding could be dependent on the local neighborhood of nucleotide state see Seetapun et al. Overall, model-convolution on the microtubule addition-loss-hydrolysis and EB binding-unbinding to assess the model is needed to rule out the simpler GTP-GDP model. Even then the argument for a GDP-Pi state is not compelling. Why is this, and are the in vitro results informative of the tip tracking in living cells? Note: "cap size" is in the title, but it is not estimated, despite a lot of nice quantitation.

These papers should be cited, as previous estimates of cap size. Note: need to account for tubulin concentration, e. Seetapun et al. We thank the reviewers for their overall very positive evaluation of the quality, novelty and importance of our work. We however respectfully disagree with the view that the demonstration of EBs binding GTP microtubules is less significant, because it is perceived as not surprising. The question whether EBs bind to the GTP conformation of microtubules could not be answered with certainty in the past.

Previous studies have used various nucleotide analogs to address questions of the nucleotide state. In our Introduction, we now provide more background and explain these different interpretations that arose from partly contradictory observations. We believe that this helps to provide a better context and highlights the value of our experiments with GTP microtubules. In our view, we present here for the first time evidence that EBs indeed bind the GTP state of microtubules with high affinity, providing clarity concerning a central question about microtubule biochemistry that has remained unsolved and has been a matter of speculation.

We have performed additional analysis going beyond what the reviewers asked which helped us to improve the clarity of the description of the measured affinity gradient. We describe this in detail in our response to the individual points raised by the reviewers and provide an improved description and discussion in the manuscript.

EBs sense the conformation of their binding site. And the conformation of this binding site is affected by the nucleotide state. We make this clear in the revised Discussion. Fluorescence microscopy experiments cannot visualise the degree of lattice 'compaction' or 'expansion' that can be observed by cryo-electron microscopy.

Therefore, we do not make statements about such lattice characteristics. Following a suggestion of a reviewer, we added experiments with a fragment of TPX2 to the manuscript but consider electron microscopy experiments beyond the scope of this already extensive study.

We respectfully disagree with the view that our data set is too limited. Not many labs are currently able to make high quality recombinant tubulin.

Although it cannot be produced in amounts as large as for animal brain tubulin, our single molecule imaging data sets here are larger than previous data sets, even when compared to experiments made with brain tubulin. Otherwise our new spatially resolved dwell time analysis at growing microtubule ends would not have been possible. We consider experiments with monomeric EB and mixed microtubule lattices beyond scope, because they have their own challenges and become easily studies in their own right.

We have addressed the issue of the 'mono-exponential distributions' by additional analysis. This is an interesting point and it turns out that it is important to consider whether EBs diffuse on the microtubule lattice while they are bound:. If they do not diffuse, the reviewer's model is not supported by the data. This would then result in complicated, clearly non-mono-exponential local dwell time distributions, which we do not observe.

However, if EBs can diffuse on the lattice, as reported earlier Lopez and Valentine, , they are expected to have a "mixed" affinity resulting from the various affinities of the binding sites they visit during lattice diffusion, leading again to mono-exponential local dwell time distributions. In our experiments, we observe much less diffusion than reported in Lopez and Valentine possibly due to our lower ionic strength buffer.

Therefore, our data do not allow to distinguish between the reviewer's model of a speckled nucleotide state lattice in the cap of growing microtubule ends and a model in which tubulins hypothetically change their conformation in a concerted manner.

Nevertheless, we clearly observe an affinity gradient for EB binding at growing microtubule ends, as we state in our manuscript. We explain now in our Discussion that the measured affinities are 'average' affinities integrating information of the conformation of several EB binding sites visited by EBs during lattice diffusion.

We also clarify that our colour gradient in the Legend of the schematic figure is intended to illustrate affinity gradient for EB binding. Mis-assignment to incorrect bins due the errors in determining the microtubule end position and the EB position, could lead to incorrectly mixing up different affinities in a bin which would make dwell time distributions less mono-exponential.

However, this is not observed, therefore this is not an issue here. We do observe that total dwell time distributions which include all binding events are clearly less mono-exponential Figure 4B than the local dwell time distributions Figure 4C. Importantly, the measured dwell times of the local dwell time distributions quite obviously change with distance from the microtubule end Figure 4C , demonstrating the existence of an affinity gradient and providing a very simple explanation for the non-mono-exponential nature of the dwell time distribution of all events.

Our main conclusion of the spatially resolved dwell time analysis is that one can measure an affinity gradient for EB binding in the cap at growing microtubule ends. This is demonstrated by a change of the characteristic local dwell times with distance from the microtubule end. This result is independent of the question how well distributions are fitted by a mono-exponential distribution. However, we have demonstrated this now quantitatively: we state in the legend of Figure 4 that a mono-exponential fit to the total dwell time distribution Figure 4B has a reduced chi-squared value two-times larger than that of a global mono-exponential fit to all the distance-binned data Figure 4—figure supplement 2A.

Furthermore, it should be noted that the logarithmic display of the dwell time distributions overemphasizes the small deviations from mono-exponential behaviour in the tail of some distributions — there is remarkably little deviation over the largest decade of data. We found it interesting to report the 'split comets' as previously reported in Portran et al.

This is however not the main point of the manuscript. This could be characterized further in the future combined with structural studies. We agree. We state now in the main text that we use an internal His-tag. This allows normal microtubule growth. We agree that electron microscopy of these mutant microtubules is very interesting, but we consider this beyond the scope of this manuscript. Instead, we have made the suggested TPX2 experiment and include it in the revised version of the manuscript Figure 2—figure supplement 1E.

The idea of a stability gradient is supported by our data of GTPase-dead microtubules EA being extremely stable and nucleating extremely efficiently, and the microtubules with slow GTPase hydrolysis having an intermediate stability and nucleation capacity, in between EA and wildtype microtubules. This allows the hypothesis that a conformational gradient in the GTP cap corresponds to a stability gradient of the lattice as it transforms from the GTP to the GDP state.

We have expanded our Introduction to better explain the conflicting interpretations in the literature with regards to nucleotide state and microtubule stability. We believe that these contradictions necessitate the experiments that we report here with pure GTP microtubules in order to be able to clearly answer a fundamental questions about the nature of the GTP cap.

We think that all our findings and not only the final part of the study provide important new information and clarify unresolved issues about the GTP cap and microtubule dynamics. Although EBs have been shown to promote the formation of protofilament microtubules Vitre et al. There is typically a mixture of microtubules with different protofilament numbers in in vitro experiments.

Maurer et al. Our data do not allow us to decide whether there is a correspondence between nucleotide and lattice state of an individual tubulin. However, we observe a correlation between EB binding affinity and nucleotide state. EB binding probably samples the average lattice state of the area it can diffuse over, as we explain in our new Discussion.

We agree that this is unexpected. We cannot explain this observation at the moment and expect that a combination of careful kinetic and structural experiments will be required to obtain a satisfactory mechanistic explanation.

We consider this a study in itself and a task for the future. The rate of the decay of the dwell times over distance together with the growth speed provides the time scale of the conformational lattice change that causes the EB binding affinity to change. This most likely reflects more or less directly the time scale of GTP hydrolysis, with the caveat that we do not know how fast phosphate is released.

We have re-written the manuscript in a longer format, with a separate Introduction and Discussion. To address the valid concern of the mutation potentially perturbing the microtubule structure, we performed an additional experiment.

These microtubules display strongly reduced EB binding, clearly demonstrating that the EB binding affinity, and hence the conformation of the microtubule, is indeed determined by the presence of the nucleotide and not by the EA mutation itself Figure 2—figure supplement 1D. We thank this reviewer for the overall positive assessment of the manuscript and the acknowledgement of the importance of our findings.

We believe that some of our statements or the final scheme might have caused a misunderstanding. We did not intend to directly draw conclusions about the GDP-Pi intermediate state from our data as presented here but simply aimed to put our new findings about the GTP hydrolysis into the general context of the current knowledge of different nucleotide states at the microtubule end.

We have changed or presentation, expanding our Discussion to clarify this point. We do not intend to conclude that our data are evidence for having detected a GDP-Pi state. We can however also not exclude that a GDP-Pi state contributes to the observed affinity gradient. We believe that the longer version of our revised manuscript helps to prevent this misunderstanding. We agree also here. Our schematic figure might have been misleading. This is because 25 are considered pretest questions and are placed randomly throughout the examination.

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