Quantitative live-cell imaging and computational modeling shed new light on endogenous WNT/CTNNB1 signaling dynamics

  1. Saskia MA de Man
  2. Gooitzen Zwanenburg
  3. Tanne van der Wal
  4. Mark A Hink
  5. Renée van Amerongen

  • Curated by eLife

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    Evaluation Summary:

    Wnt signaling plays critical roles in cell fate determination in essentially every tissue in all animals, regulates tissue homeostasis in many adult tissues, and is inappropriately activated in many human cancers. It has been the focus of research for decades, and we have an outline of signal transduction. Remarkably, some of the key questions of Wnt signaling remain controversial. Central among these are questions about the nature of the negative regulatory destruction complex, its mechanism of action and how it is turned down by Wnt signaling. Here Saskia and colleagues take a novel and very exciting approach to these questions, combining innovative quantitative live-cell imaging and computational modelling.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #2 agreed to share their name with the authors.)

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Abstract

WNT/CTNNB1 signaling regulates tissue development and homeostasis in all multicellular animals, but the underlying molecular mechanism remains incompletely understood. Specifically, quantitative insight into endogenous protein behavior is missing. Here, we combine CRISPR/Cas9-mediated genome editing and quantitative live-cell microscopy to measure the dynamics, diffusion characteristics and absolute concentrations of fluorescently tagged, endogenous CTNNB1 in human cells under both physiological and oncogenic conditions. State-of-the-art imaging reveals that a substantial fraction of CTNNB1 resides in slow-diffusing cytoplasmic complexes, irrespective of the activation status of the pathway. This cytoplasmic CTNNB1 complex undergoes a major reduction in size when WNT/CTNNB1 is (hyper)activated. Based on our biophysical measurements, we build a computational model of WNT/CTNNB1 signaling. Our integrated experimental and computational approach reveals that WNT pathway activation regulates the dynamic distribution of free and complexed CTNNB1 across different subcellular compartments through three regulatory nodes: the destruction complex, nucleocytoplasmic shuttling, and nuclear retention.

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  1. eLife

    Author Response (July 26, 2021):

    Reviewer #1 (Public Review):

    The authors have done a great job in carefully labeling the β-catenin with fluorescent protein SGFP2 and quantitatively measuring the β-catenin behavior during Wnt pathway activation with advanced biophysical methods. This is an excellent effort on quantitative biological studies. The knock-in constructs, the cell lines the authors made are great resources for the Wnt field. And the quantification like the β-catenin concentration, β-catenin diffusion coefficient are great knowledge for future studies. The finding that S45F mutation lead to higher fraction of the slow-moving complexes is interesting. Other areas could borrow the research ideas and methods used in this manuscript. My primary concern is the difficulty of interpreting some of the quantitative results in the biological context. The authors have concluded that β-catenin has two major populations: free population and slow-diffusing complexed population. The authors have concluded with FCS that the diffusion coefficient of free β-catenin to be 14.9 um2/s (line 259) and the complexed β-catenin to be 0.17 um2/s (line 327). Similar to the authors' argument in the manuscript, this difference means about a 100-fold change of the complex length scale. If the complex is linear, this means a 100-fold change in molecule size, but if the complex is spherical, this means a one-million-fold increase of the molecule size.

    We thank the reviewer for their positive, yet consistently critical assessment of our work. We share their view that the interpretation of these quantitative results in the biological context remains challenging.

    To clarify the specific point raised by the reviewer: The diffusion coefficient of the cytoplasmic CTNNB1 complex is indeed 14.9/0.17 = 87-fold slower than the free monomeric CTNNB1. And this would indeed be indicative of an 873 change in molecular size if we assume Einstein-Stokes relation. However, the Einstein-Stokes equation is only valid when specific conditions are met (including the assumption that we are dealing with perfectly spherical particles in a homogeneous environment). Therefore, we already noted the following in the material and methods section lines 1104-1112: "It must be noted that, especially for larger protein complexes, the linearity between the radius of the protein and the speed is not ensured, if the shape is not globular, and due to other factors such as molecular crowding in the cell and hindrance from the cytoskeletal network. We therefore did not estimate the exact size of the measured CTNNB1 complexes, but rather compared them to measurements from other FCS studies.”

    In our initial submission we included the following statement “Because a 3.5-fold change in speed would result in 3.53-change in size for a spherical particle (assuming Einstein-Stokes, see equation 7 in the material and methods section for details), this indicates that the size of the cytoplasmic CTNNB1 complex drastically changes when the WNT pathway is activated.” We chose to do so, because in our prior submission of this work (28-05-2020-RA-BX-eLife-59433), Reviewer 1 remarked that “CTNNB1 resides in slow moving complexes that persist upon Wnt but become slightly more mobile”, which we felt was an underappreciation of the significance of this change. We suspect and can understand that Reviewer 1 then applied this logic directly to the speed of the slower SGFP2-CTNNB1 fraction: “Similar to the authors' argument in the manuscript, this difference means about a 100-fold change of the complex length scale. If the complex is linear, this means a 100-fold change in molecule size, but if the complex is spherical, this means a one-million-fold increase of the molecule size.” However, it was never our intention to suggest that we can calculate absolute complex sizes from these diffusion speeds, due to the constraints of the Einstein-Stokes formula explained above For clarification, the 100-fold change is not necessarily in length scale – just in diffusion time which correlates to the radius of a spherical particle. Indeed, a destruction complex with 1003-fold larger mass or volume than a monomeric CTNNB1, is indeed unlikely if not impossible. On the other hand, the diffusion coefficients we observe for the cytoplasmic CTNNB1 complex are equally unlikely to represent a ‘free and monomeric’ version of the destruction complex, as the combined weight of the partners (APC, AXIN, CSNK1A1, GSK3 and SGFP2-CTNNB1, ~600kDa) would be expected to be only ~1.75x slower (assuming Einstein-Stokes). Overall, the most important take home message is not an absolute size estimate of the CTNNB1 complex, but the fact that a larger cytoplasmic CTNNB1 complex is still present after WNT stimulation, although it does undergo a substantial reduction in size (reflected by a 3.5-fold increase in speed upon WNT stimulation), and thus changes its identity. We have modified the statement regarding the relation between diffusion speed and size in the current manuscript, to avoid further confusion on this point. Line 348-352 Because changes in diffusion coefficient are typically indicative of larger changes in protein size (i.e. molecular weight see materials and methods section for details), this indicates that the size of the cytoplasmic CTNNB1 complex drastically changes when the WNT pathway is activated. To the materials and methods, we have added the following Line 1110-1112 However, it is likely that the 3.5-fold change in the second diffusion coefficient of SGFP2-CTNNB1 in response to WNT3A treatment is indicative of a larger than 3.5-change to complex size.

    Furthermore, in the next section, with the N&B method, the authors have suggested that “few, if any, of these complexes contain multiple SGFP2-CTNNB1 molecules” (line 366). When combining the two parts of information, it is hard to imagine a complex that contains one thousand to one million molecules only have one or a few β-catenin subunits. From the biology point of view, APC is the backbone of the destruction complex, which has several β-catenin binding sites by itself. Additionally, APC also contains several Axin1 binding sites where each Axin1 can also recruit one β-catenin. It is unlikely that one APC complex contains only one β-catenin, not mentioning the potential oligomerization of APC. The conclusion that most of the β-catenin containing complexes has only one β-catenin could either be real or due to the misinterpretation of experimental data.

    As elaborated above, it is unlikely that the complex really is 1003 larger than a single free SGFP2-CTNNB1 molecule. At the same time, the diffusion coefficient of the slow fraction of SGFP2-CTNNB1 is still indicative of a very large complex, similar to the 26S proteasome – as discussed in the main text (currently line 344-346: This is indicative of very large complexes containing SGFP2 CTNNB1 that move with diffusion kinetics comparable to those previously observed for the 26S proteasome (Pack et al., 2014).). We were, therefore, equally surprised by the findings from our N&B analysis, which is why we extensively discuss possible explanations in our manuscript. Future follow-up by ourselves and others will reveal in how far our interpretation of these measurements stands the test of time.

    Reviewer #3 (Public Review):

    Wnt signaling plays critical roles in cell fate determination in essentially every tissue in all animals, regulates tissue homeostasis in many adult tissues, and is inappropriately activated in many human cancers. It has been the focus of research for decades, and we have an outline of signal transduction. However, remarkably, key questions remain controversial. Central among these are questions about the nature of the negative regulatory destruction complex, its mechanism of action and how it is turned down by Wnt signaling. Here Saskia and colleagues take a novel and very exciting approach to these questions, combining innovative quantitative live-cell imaging and computational modelling.

    What I can say unequivocally is that there is data in this manuscript that will force a re-evaluation of our current models of Wnt signaling, and also serve as the foundation for future research. Particular notable are: 1) precise measurements of the concentrations of beta-catenin in the cytoplasm and nucleus before and after Wnt signaling and after inhibition of GSK3. 2) Definition of a high MW complex, likely the destruction complex, whose assembly state appears to be regulated by Wnt signaling, and 3) Intriguing evidence that at steady state this complex appears not to contain multiple copies of beta-catenin. These data are exceptionally interesting and timely, as controversy continues about the size/assembly state of the destruction complex.

    We are happy that reviewer 3 evaluates our work so favorably. We are looking forward to contributing to further re-evaluation of the current models of WNT signaling in the future, as well as witnessing further probing and validation of our data by others.

  2. Version published to 10.7554/elife.66440 on eLife
  3. eLife

    Author Response:

    For the reader, we specifically want to highlight the following new data (Figures 7, 8 and accompanying supplements) that were added:

    1. To directly compare physiological (Wntoff/Wnton) and oncogenic (i.e. constitutively active) signaling, we generated a second cell line using CRISPR/Cas9 genome editing, harboring an oncogenic point mutant form of CTNNB1 (SGFP2-CTNNB1S45F).

    2. To further quantify the levels, complex state and multimerization status when WNT/CTNNB1 signaling is hyperactivated, we performed additional FCS and N&B experiments in the new mutant cell line and upon GSK3B inhibition by CHIR99021 treatment (as requested by reviewers 1 and 2).

    3. We use these same perturbations to strengthen the link between our experimental data and the computational model (as suggested by reviewer 2) and provide access to the model in the form of an interactive app (available at https://wntlab.shinyapps.io/WNT_minimal_model/).

    While we are in the process of further revising our manuscript, we do want to take this opportunity to briefly reply to two of the points made by Reviewer #1:

    The authors have concluded with FCS that the diffusion coefficient of free β-catenin to be 14.9 um2/s (line 259) and the complexed β-catenin to be 0.17 um2/s (line 327). Similar to the authors' argument in the manuscript, this difference means about a 100-fold change of the complex length scale. If the complex is linear, this means a 100-fold change in molecule size, but if the complex is spherical, this means a one-million-fold increase of the molecule size.

    To clarify: We indeed measure a 14.9/0.17 = 87-fold change in speed. IF we assume Einstein-Stokes relation, this would be indicative of a 87^3 change in molecular size. However, the Einstein-Stokes equation is only valid when specific conditions are met (including the assumption that we are dealing with perfectly spherical particles in a homogeneous environment). Therefore, we noted the following in the material and methods section: “It must be noted that, especially for larger protein complexes, the linearity between the radius of the protein and the speed is not ensured, if the shape is not globular, and due to other factors such as molecular crowding in the cell and hindrance from the cytoskeletal network. We therefore did not estimate the exact size of the measured CTNNB1 complexes, but rather compared them to measurements from other FCS studies.” Put differently: The most important take home message is not an absolute size estimate of the CTNNB1 complex (which is why were careful not to make that point explicitly, although it is unlikely that this complex only contains one copy of the ‘standard’ destruction complex components APC, AXIN, GSK3 and CK1), but the fact that this complex is still present after WNT stimulation, although it does undergo a substantial reduction in size (a 3.5-fold change in speed upon WNT stimulation), and thus changes its identity. We will take care to ensure that a future revision leaves no room for further confusion on this point.

    From the biology point of view, APC is the backbone of the destruction complex, which has several β-catenin binding sites by itself. Additionally, APC also contains several Axin1 binding sites where each Axin1 can also recruit one β-catenin. It is unlikely that one APC complex contains only one β-catenin, not mentioning the potential oligomerization of APC.

    Here we can only agree with the reviewer: We were equally surprised by the findings from our N&B analysis, which is why we extensively discuss possible explanations in our manuscript. Future follow-up by ourselves and others will reveal in how far our interpretation of these measurements stands the test of time.

  4. eLife

    Reviewer #2 (Public Review):

    Wnt signaling plays critical roles in cell fate determination in essentially every tissue in all animals, regulates tissue homeostasis in many adult tissues, and is inappropriately activated in many human cancers. It has been the focus of research for decades, and we have an outline of signal transduction. However, remarkably, key questions remain controversial. Central among these are questions about the nature of the negative regulatory destruction complex, its mechanism of action and how it is turned down by Wnt signaling. Here Saskia and colleagues take a novel and very exciting approach to these questions, combining innovative quantitative live-cell imaging and computational modelling.

    What I can say unequivocally is that there is data in this manuscript that will force a re-evaluation of our current models of Wnt signaling, and also serve as the foundation for future research. Particular notable are: 1) precise measurements of the concentrations of beta-catenin in the cytoplasm and nucleus before and after Wnt signaling and after inhibition of GSK3. 2) Definition of a high MW complex, likely the destruction complex, whose assembly state appears to be regulated by Wnt signaling, and 3) Intriguing evidence that at steady state this complex appears not to contain multiple copies of beta-catenin. These data are exceptionally interesting and timely, as controversy continues about the size/assembly state of the destruction complex.

  5. eLife

    Reviewer #1 (Public Review):

    The authors have done a great job in carefully labeling the β-catenin with fluorescent protein SGFP2 and quantitatively measuring the β-catenin behavior during Wnt pathway activation with advanced biophysical methods. This is an excellent effort on quantitative biological studies. The knock-in constructs, the cell lines the authors made are great resources for the Wnt field. And the quantification like the β-catenin concentration, β-catenin diffusion coefficient are great knowledge for future studies. The finding that S45F mutation lead to higher fraction of the slow-moving complexes is interesting. Other areas could borrow the research ideas and methods used in this manuscript. My primary concern is the difficulty of interpreting some of the quantitative results in the biological context.

    The authors have concluded that β-catenin has two major populations: free population and slow-diffusing complexed population. The authors have concluded with FCS that the diffusion coefficient of free β-catenin to be 14.9 um2/s (line 259) and the complexed β-catenin to be 0.17 um2/s (line 327). Similar to the authors' argument in the manuscript, this difference means about a 100-fold change of the complex length scale. If the complex is linear, this means a 100-fold change in molecule size, but if the complex is spherical, this means a one-million-fold increase of the molecule size. Furthermore, in the next section, with the N&B method, the authors have suggested that "few, if any, of these complexes contain multiple SGFP2-CTNNB1 molecules" (line 366). When combining the two parts of information, it is hard to imagine a complex that contains one thousand to one million molecules only have one or a few β-catenin subunits. From the biology point of view, APC is the backbone of the destruction complex, which has several β-catenin binding sites by itself. Additionally, APC also contains several Axin1 binding sites where each Axin1 can also recruit one β-catenin. It is unlikely that one APC complex contains only one β-catenin, not mentioning the potential oligomerization of APC. The conclusion that most of the β-catenin containing complexes has only one β-catenin could either be real or due to the misinterpretation of experimental data.

  6. eLife

    Evaluation Summary:

    Wnt signaling plays critical roles in cell fate determination in essentially every tissue in all animals, regulates tissue homeostasis in many adult tissues, and is inappropriately activated in many human cancers. It has been the focus of research for decades, and we have an outline of signal transduction. Remarkably, some of the key questions of Wnt signaling remain controversial. Central among these are questions about the nature of the negative regulatory destruction complex, its mechanism of action and how it is turned down by Wnt signaling. Here Saskia and colleagues take a novel and very exciting approach to these questions, combining innovative quantitative live-cell imaging and computational modelling.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #2 agreed to share their name with the authors.)

  7. Version published to 10.1101/2020.05.28.120543v2 on bioRxiv
  8. eLife

    ###Reviewer #3:

    1. As I state below the paper is carefully done (with a few minor issues) using a difficult and sophisticated biophysical technique, FCS to assess the changes in beta catenin diffusion within the cell following Wnt signaling. So it passes the test on being an original piece of work executed well. However what has been learned is quite limited. A few interactions, such as the slow diffusion in the cytoplasm can be interpreted several ways. It is very helpful to have concentrations in the nucleus and cytoplasm for beta catenin for future modeling. They could have tried to use single cross correlation with labeled APC or axin or the proteasome to derive more important information about the path through the destruction sequence. But that may be too hard to ask for at this stage. They could have combined their measurements with appropriate mutants or knockouts. I come down close to the line, high on the importance of the problem and the methods and execution; lower on the current take home lesson.

    2. The support for the somewhat limited conclusions is strong as it is.

    3. There are some technical issues. There is some concern with the FCS data itself. Figure 5F and 5G are of some concern. The curve doesn't drop to 1 at long correlation time (>100ms) and there are big fluctuations in the region of short correlation times (<0.1 ms). This could be due to the very long time course (120s) used in the experiment. Have the authors tried to image the same spot multiple times in short intervals (etc 10s), or try to analyze 10s sub-trace of the original long trace to see if the conclusions hold? This type of error could influence the calculation of the diffusion coefficient of complexes of CNNTB1. They also affect the quantification of concentration. In line 352-353 the authors mentioned the nuclear concentration of CNNTB1 increases 2.1 fold based on FCS measurement, which is smaller than the fluorescent intensity change. Is this the result of errors such as this.

    For confocal imaging analysis, the description was not clear as to whether there is background subtraction during the intensity quantification. If there is, the authors should mention it in the method explicitly. If not, the background could decrease the fold change estimation.

    In the model description line 877, equation (6), k7x6 should be k7x5

    Line 901 equation (15), there is no unit for the binding affinity

    Normally, a fraction of the fluorescent protein is not bright; the authors may not have a tool to measure the dark component but they should mention how it may affect the quantification in the discussion.

  9. eLife

    ###Reviewer #2:

    The manuscript by S.M.A. de Man et al. presents a study on the cellular response to Wnt activation and on the intracellular kinetics of beta catenin (CTNNB1). The authors have developed cell lines expressing GFP reporters of CTNNB1 using CRISPR CAS9. They present different convincing controls on the specificity of the reporter and decided to analyze the temporal behavior of the best reacting clone. Then, they investigate the temporal evolution of fluorescent signals in the cell cytoplasm and nucleus upon Wnt signaling activation. They quantify the kinetics of the relocalization of CTNNB1 from the cytoplasm to the nucleus upon different strength of activation of the Wnt signaling and GSK3 inhibition. Using FCS, they identify that a dual diffusion model fits better the experimental data than a classical single diffusion model, suggesting the presence of complexes of different sizes. They measure the diffusion parameters and concentrations of the complexes in the nucleus and in the cytoplasm. Using a dynamical model, the authors reveal that, to recapitulate the experimental observations, the regulation of CTNNB1 upon Wnt signaling has to be controlled at three levels, the destruction complex, the nuclear transport and the binding affinity to the chromatin.

    Overall, the study is solid, presenting novel information on the kinetics of CTNNB1 during Wnt signaling. The results are consistent with the classical view on the regulation of beta catenin during Wnt signaling. I have few comments essentially on the methodology.

    Specific comments:

    -The authors have designed a new cell line allowing for tracing the kinetics of beta catenin over time following Wnt signaling activation. They follow the relative changes in concentration in the nucleus and cytoplasm upon activation of Wnt signaling. Normalized changes render difficult to evaluate if the difference in the increase in the cytoplasm and the nucleus is due to a higher increase in the nucleus or simply due the absence of beta catenin in the nucleus at the onset of the process therefore enhancing the quantification. A non-normalized plot showing the increase in grey levels in the nucleus and cytoplasm should be added to complement the quantification and identify the differences between nuclear and cytoplasmic beta catenin. It would also help the reader to compare with the results of concentrations extracted from the FCS.

    -The response in figure 4 upon Wnt signaling activation and GSK3 inhibition are different (with the absence of a plateau in the case of GSK3 inhibition). The explanation of this difference is unclear as it is. I would suggest the authors to detail a bit more their thoughts on the reason for the difference. Could this simply be that Wnt activation clusters just a subset of GSK3 at the membrane and that inhibition can reach a higher level of depletion of GSK3 in the cytoplasm?

    -How GSK3 inhibition treatment affects the FCS measurements, particularly concentrations and different complexes compositions? The differences with Wnt3 activation could provide additional information on the nature of the identified complexes.

    -The dynamical model presented in the paper shows a non-monotonous change in the concentration of beta catenin in the cytoplasm after activation. This seems to be due to the kinetics of nuclear transport and does not seem to be present in the experimental observations. Can the authors comment on this point? Is there a way by modulating parameters associated to transport to suppress this discrepancy?

    -Finally, the model is consistent with the experimental observations but the authors did not check with any type of perturbation how the model would compare with the experiments. For instance, how does the model compare with experiments in the case of GSK3 inhibition, or when nuclear transport is affected. Adding a perturbation case would significantly strengthen the connection between model and experiment and the message of the manuscript.

    -labels of the figure 4 and respective movies are inverted

    -The figure 1 only presents the classical model and no new concept/data. The figure 1 and figure 2 should be merged to my point of view.

    -The labels in the table 1 Wnt (ON -OFF) are inverted.

  10. eLife

    ###Reviewer #1:

    CTNNB1 is a core component of canonical Wnt signalling that is frequently mutated in cancers. A constitutively active destruction complex (degradosome) binds and phosphorylates CTNNB1 earmarking it for proteasomal degradation, this complex is inactivated upon Wnt3a/GSK3β inhibition leading to CTNNB1 stabilisation and nuclear translocation. The authors have successfully employed CRISPR mediated endogenous tagging of CTNNB1 and determined its cellular concentration and diffusion dynamics in HAP1 cells, in both the cytoplasm and nucleus by live-cell imaging and analysis. They provide the relative subcellular CTNNB1 concentration for the nucleus and cytoplasm, like previous studies in other cell lines (Tan et al., 2012) and in Xenopus (Lee et al., 2003). In addition their results suggest CTNNB1 resides in slow moving complexes that persist upon Wnt but become slightly more mobile, these results are intriguing but raise several unanswered questions, such as whether these complexes represent the destruction complex (cytoplasm) or enhanceosome (nucleus). The work has been completed to a high standard but I have several concerns listed below.

    1. The authors acknowledge significant cell-cell heterogeneity. This is particularly noticeable in Fig.4A upon Wnt3a and CHIR99021 treatment. Fig.4B suggests all cells are analysed regardless of heterogeneity and the only exclusion criteria mentioned in the methodology is cells with a cytoplasm of less than 10pixels. Fig.4C/D does not seem to reflect the variation observed in Fig.4A? What is the spread pre-normalisation before and after treatment? How is the relative increase in nuclear/cytoplasmic intensity affected by cell size? Nuclear and cytoplasmic area? This may affect the relative fold increase and the cytoplasmic area seems highly variable at the confluence of cells shown.

    2. Using point FCS the authors determined two diffusion speeds corresponding to monomer and complexed CTNNB1 in both the nucleus and cytoplasm. A modest increase in cytoplasmic diffusion speed of complexed CTNNB1 was observed after Wnt3a (0.461μm2/s-1) but far from the speed of the monomer (14.9μm2/s-1) suggesting it remains complexed upon Wnt3a. In addition the fraction of complexed CTNNB1 (~40%) remains largely unaltered. Is the same true under CHIR299021 treatment? Point FCS samples a very small area of the cell cytoplasm/nucleus and therefore gives a small representation of the subcellular pool (which is likely heterogeneous), only a single point appears to have been analysed per-cell and within the 21 cells analysed clear outliers can be observed (Fig.6A/B), this has not been adequately discussed. What is the variation in diffusion measured at different points within a single cell? Some discussion has been made as to these complexes reflecting the destruction complex/proteasome or the enhanceosome but this really needs to be tested in order to make any conclusions about these observations. Especially as cytoplasmic complexes are maintained under Wnt conditions, this would challenge the notion that CTNNB1 disassociates from the destruction complex upon Wnt. Ideally endogenous tagging of other destruction complex components with a different fluorophore would be done to address this, if these complexes do represent the destruction complex and remain bound after Wnt this would have significant implications for our understanding of complex inactivation and greatly enhance the manuscript.

    3. The N&B analysis averages out monomeric and complexed CTNNB1 intensity across an image stack around a single ROI within each cell. The authors interpret Fig.6C to mean SGFP2-CTNNB1 is present as a monomer whether in a complex or not. This is based on the fact the relative brightness averages at 1.0 similar to a monomeric GFP control. However, the spread of relative brightness is large, and often less than <1 so a relative brightness of 1 cannot refer to a monomeric SGFP2-CTNNB1? Does cellular concentration affect relative brightness? If so transiently expressed monomer and dimer GFP may not be the best controls. Aggregation is spatially homogeneous and limited by the diffusion rate of protein/complexes - which your FCS measurements suggest is consistent with a large complex. Thus a single average may not represent the diversity of protein complexes, eN&B could be used (Cutrale et al., 2019). As mentioned in point 3, like FCS, you are only sampling a small region of the cell, which may or may not contain a destruction complex for example. Super-resolution imaging techniques such a STORM or LLSM may help with visualisation of cell complex heterogeneity and give a different impression of complex occupancy. I don't think the N&B data is sufficient to say complexes don't exist that contain more than one SGFP2-CTNNB1 molecule.

    4. The computational model relies on a number of assumptions determined in other studies that may not reflect the HAP1 cells used in this study. Lee et al., was performed in Xenopus and Tan et al., 2012 found a number of differences in their mammalian cell studies. Important information regarding the concentration of destruction complex components has also been omitted, this information is important for future comparisons of cell-type specific behaviours.

  11. eLife

    ##Preprint Review

    This preprint was reviewed using eLife’s Preprint Review service, which provides public peer reviews of manuscripts posted on bioRxiv for the benefit of the authors, readers, potential readers, and others interested in our assessment of the work. This review applies only to version 1 of the manuscript.

    ###Summary:

    The authors investigate how cells respond to WNT signaling by altering beta catenin (CTNNB1) dynamics. They generated a number of cell lines in which they use different light microscopy techniques –such as FCS and number & brightness (N&B) measurements– to quantitatively investigate the diffusion behavior and complex formation of intracellular CTNNB1. The results are in general well explained, reasoned and technically well-controlled (except for some, which raised concerns that were pointed out by the reviewers). The main finding of the paper is that CTNNB1 seems to reside in slow-moving complexes (that exist both in the presence and absence of WNT) that become slightly more mobile after WNT addition. As pointed out by the reviewers, these results can be interpreted in different ways, and it is not clear whether these complexes represent the destruction complex (cytoplasm) or enhanceosome (nucleus). In summary, yet the work shows some technical proficiency which could address some critical issues in Wnt signaling, the authors would need to identify the issues that could be resolved by the technique and then design experiments to resolve them in the future.

  12. Version published to 10.1101/2020.05.28.120543v1 on bioRxiv