Quantification of Cyclin-CDK dissociation constants in living cells using fluorescence cross-correlation spectroscopy with green and near-infrared fluorescent proteins

  1. Aika Toyama
  2. Yuhei Goto
  3. Yuhei Yamauchi
  4. Hironori Sugiyama
  5. Yohei Kondo
  6. Atsushi Mochizuki
  7. Kazuhiro Aoki

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Abstract

The cell cycle is a highly coordinated process governed by cyclin-bound cyclin-dependent kinases (CDKs). While the interaction between cyclin and CDK are well-documented, the dissociation constants (K d ) between specific cyclin-CDK pairs within living cells remain poorly understood. Fluorescence cross-correlation spectroscopy (FCCS) enables the quantification of the K d , but challenges remain in selecting an optimal pair of fluorescent molecules for FCCS in a living cell. In this study, we demonstrate that mNeonGreen and phycocyanobilin-bound miRFP670 represent a suitable pair for FCCS in living cells from the viewpoint of high photostability and low bleed-through. This fluorescent protein pair enables us to measure the K d values of the cyclin-dependent kinase Cdc2 and B-type cyclin Cdc13 in fission yeast cells. Moreover, we conducted a comprehensive analysis of the K d values for 36 cyclin-CDK complexes, formed by 9 distinct cyclins and 4 CDKs, in mammalian cells, including unconventional cyclin-CDK pairs. These findings provide insights into the redundancy of cyclin-CDK binding in cell cycle progression, with potential implications for understanding cell cycle regulation in both fission yeast and higher eukaryotes.

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    Reply to the reviewers

    Manuscript number: RC-2024-02788

    Corresponding author(s): Kazuhiro, Aoki and Yuhei, Goto

    1. General Statements [optional]

    We sincerely thank all reviewers for their insightful comments and constructive suggestions that have substantially improved our manuscript. We provide point-to-point responses to each comment and added detailed explanations in the preliminary revised manuscript. The reviewers' comments are shown in dark blue italics, followed by our responses.

    2. Description of the planned revisions

    Insert here a point-by-point reply that explains what revisions, additional experimentations and analyses are planned to address the points raised by the referees.

    Reviewer #1

    Major Concerns

      • Fig. 3G, Cdc2-miRFP670 levels appear to drop after cell division, which is a surprising observation because Cdc2 is generally considered stable. This could be an imaging artifact because the level recovers quickly after division. The authors should substantiate their findings with a western blot analysis of tagged vs untagged proteins. Additionally, the authors should test whether endogenously tagging Cdc2 and Cdc13 causes any cell cycle phenotypes.* While Cdc2 protein levels are indeed stable in whole cells as you noted, we specifically measured nuclear Cdc2-miRFP670 levels. A previous study has shown that nuclear Cdc2 levels fluctuate throughout the cell cycle, increasing during interphase and decreasing during mitosis (Curran et al., 2022). This known behavior of nuclear Cdc2 is consistent with our observation.

    To address your concerns about potential artifacts from fluorescent protein tagging to endogenous Cdc2 and Cdc13, we will perform two additional experiments:

    1. Compare protein expression levels between wild-type and fluorescently tagged strains for Cdc2 and Cdc13 using western blot analysis.
    2. Examine whether the fluorescent tags affect cell cycle progression by measuring cell cycle duration in tagged versus untagged strains using time-lapse imaging.
    • The authors explore a panel of red-fluorescent proteins to identify those with the best photobleaching properties. Conducting a similar review with a panel of green fluorescent proteins would significantly enhance the manuscript. It would be particularly helpful to test the properties of the new StayGold fluorescent protein.*

    Thank you for this valuable suggestion. We will expand our photobleaching analysis to include green fluorescent proteins, specifically mEGFP and the recently developed mStayGold as well as mNeonGreen. These measurements will be conducted under identical experimental conditions to our red fluorescent protein analysis, allowing for direct comparison of their photostability properties. This additional data will provide a more comprehensive evaluation of fluorescent protein options for FCCS.

    • In both yeast and mammalian experiments, the green fluorophore is consistently fused to the cyclin and the far-red fluorophore to Cdk1. The authors should include an FCCS control reversing the fluorophores in at least one experiment to verify whether comparable Kd values are obtained.*

    We plan to conduct FCCS measurements with reversed fluorophore combinations in HeLa cells to validate our experiments. Specifically, we will compare Kd values between:

    1. cyclin D1-miRFP670 and CDK4-mNG pair versus cyclinD1-mNG and CDK4-miRFP670 pair
    2. cyclin D3-miRFP670 and CDK6-mNG pair versuscyclin D3-mNG and CDK6-miRFP670 pair.
    3. We also plan to do it in fission yeast cells comparing Kd values between: Cdc13-miRFP670 and Cdc2-mNG pair versus Cdc13-mNG and Cdc2-miRFP670 pair Reviewer #2

    SectionA

    Major Comments

    (ii) For the characterisation of the cell cycle dependent expression of Cdc13 and its association with Cdc2, the level of Cdc13 EGFexpression is used to identify cell cycle stage. It would be appropriate to have an independent measure of cell cycle stage (?cell length). In using Cdc13 to identify cell cycle stage, please define the criteria used ie what level of Cdc13-mNG fluorescence intensity was used to define G1 vs S vs G2?

    We would like to thank you for raising these important comments and suggestions about cell cycle stage determination. We agree that using Cdc13-mNG levels alone as a cell cycle marker requires more rigorous validation.We will incorporate cell length measurements as an independent cell cycle stage indicator for FCCS measurements. However, it is important to note that traditional cell cycle stage classification is limited in fission yeast cells due to its unique cell cycle characteristics; a brief G1 phase, continuous S phase during cell separation, and an extended G2 phase. Cdc13 expression keeps at the undetectable level during G1 and S phases, and therefore this inevitably restricts our FCCS measurements to G2 and M phases. G2 and M phase cells can be distinguished by the characteristic relocalization of Cdc2 and Cdc13 to the mitotic spindle during the M phase (Sugiyama et al., 2024). In the revised manuscript, we will demonstrate the FCCS data with both quantitative (cell length) and qualitative (G2 and M phase localization pattern) indicators for more precise cell cycle staging.

    (iii) Include a control experiment to compare the level of Cdc13 expression in untagged wild-type cells vs the Cdc13-mNG, CDK1- miRFP670 expressing cells to confirm that tagging does not affect Cdc13 expression, cell cycle duration or Cdc13 function.

    We agree with the reviewer's comment, which suggests validation of the functionality of tagged proteins. We will perform two key control experiments:

    1. Compare Cdc13 protein expression levels between wild-type cells and cells expressing Cdc13-mNG and Cdc2-miRFP670 using western blot analysis with anti-Cdc13 antibody.
    2. Measure cell cycle duration in both strains through time-lapse microscopy to assess any potential effect of the fluorescent tags on cell cycle progression. Major points

    (ii) Please provide the confidence interval for the data fit for each CDK-cyclin pair. In panel Figure 4I, the results are represented as a heat map to define the Kd for each CDK-cyclin pair. This panel suggests that the technique can sensitively distinguish alternative CDK-cyclin complexes where their Kd values differ in 1 uM increments. The heat map is presented with block colours, but the key to the color coding is a graded color scheme and it is not possible to move between the two. This disconnect has to be addressed. The accompanying text on pages 18 and 19 is a qualitative description of the results, a comparative and quantitative analysis of the data (Kd values with accompanying confidence intervals) has to be included to justify the apparent strength of the technique to discriminate different CDK-cyclin pairs that Figure 4 implies.

    Thank you for highlighting the need for more rigorous statistical analysis. We will calculate and add the confidence intervals for all Kd values of each cyclin-CDK pair.

    (iii) For "low affinity" interactions that are determined to be >10 uM. Please define how this value was calculated. Would it be more appropriate to say a value could not be determined as the data could not be fitted?

    We appreciate the reviewer's valuable comment regarding the determination of low affinity interactions. As mentioned above, we are currently calculating confidence intervals for our curve fitting analyses across all measurements. Based on these statistical analyses, we will carefully evaluate the reliability of the >10 µM designations and revise our descriptions accordingly in the manuscript to ensure accurate representation of the binding parameters.

    3. Description of the revisions that have already been incorporated in the transferred manuscript

    Reviewer #1

    Major Concerns

    • The authors extensively characterize the Kd of cyclin/Cdk pairs using overexpressed proteins. This approach is problematic due to the heterogeneous expression levels associated with transient expression and competition between overexpressed proteins and endogenous proteins. Variable expression levels are a concern because of the limiting rate of T-loop phosphorylation on Cdks (Merrick et al., 2008), which is required to stabilise cyclin/Cdk complexes. While the authors acknowledge the competition between exogenous and endogenous proteins, they do not take into account the cell cycle-dependent fluctuation of cyclin levels. For instance, in cells with low levels of endogenous Cyclin B1 (S-phase), competition with overexpressed Cyclin B1 will have less impact on cross-correlation measurements compared to cells with high endogenous Cyclin B1 (G2-phase).*

    These issues severely affect the relevance of this dataset. Indeed, the reported measurements differ by at least an order of magnitude from the Kd values obtained through biochemical methods or FCCS with endogenously tagged proteins. Moreover, the data partially diverge from the literature; for example, Cdk1 is known to form unconventional complexes with Cyclin Ds and Es.

    We acknowledge the important issues about the limitations of using overexpressed proteins for Kd measurement. Indeed, several factors affect the reliability of our measurements. At first, competition between overexpressed and endogenous proteins varies throughout the cell cycle due to cell cycle-dependent fluctuations in endogenous cyclin levels. Indeed, we had analyzed the effects of the overexpression on in vivo Kd measurements with FCCS (Sadaie, Mol Cell Biol, 2014), showing that not only endogenous proteins but also competitive binding proteins affect Kd values quantified in living cells. Second, variable expression levels from transient transfection may impact T-loop phosphorylation of CDKs, which is known to be rate-limiting (Merrick et al., 2008). We have expanded our discussion to address these limitations and their implications for interpreting the cyclin-CDK binding affinities (page 25, line 16-18). We also note that our overexpression experiments may not fully capture the formation of previously reported unconventional complexes, such as those between CDK1 and D- or E-type of cyclins (Koff et al. 1992; Zhang et al. 1993) (page 26, line 8-10).

    • Fig. S3A, Cyclin E levels are shown to persist into mitosis, whereas endogenous Cyclin E is degraded in late S and G2 phases. This is likely to be caused by over-expression and the authors should comment on this.*

    We agree that the observed persistence of Cyclin E into mitosis differs from the known behavior of endogenous Cyclin E, which is typically degraded during late S and G2 phases. This discrepancy is likely due to our overexpression system overwhelming the normal degradation machinery. In the revised manuscript, we have explicitly acknowledged this limitation and discuss how overexpression may alter the typical cell cycle-dependent regulation of cyclin proteins (page 26, line 12-16). This observation further highlights the importance of considering expression levels when interpreting protein-protein interaction data from overexpression systems.

    Minor Comments

      • The authors should reference relevant studies from Jan Ellenberg's lab on FCS (e.g., Wachsmuth et al., 2015; Cai et al., 2018).* Thank you for your suggestion. We have cited these two papers in introduction (page 6, line 5-8).
    • The statement, "In order to perform FCCS in a reproducible manner, we are trying to find a better fluorescent protein pair that is bright, crosstalk-free, and highly resistant to photobleaching," would be improved by removing the word "better".*

    We removed the word "better".

    • In Fig. 1C, F, G, and H, the colour codes are difficult to read and should be improved.*

    We have changed the color codes to make them easy to distinguish.

    • The paragraph discussing Fig. 3 states: "We used a fission yeast strain that expressed SynPCB2.1 under the control of the adh promoter," raising the question of how emiRFP670 was imaged in earlier experiments.*

    We apologize for the unclear description. All experiments involving miRFP670 imaging, including those in Figure 1, were performed using fission yeast cells expressing SynPCB2.1 under the control of the adh1 promoter. We have clarified these important experimental details in the revised manuscript under the section "miRFP670, a near-infrared fluorescent protein, is suitable for simultaneous imaging with mNeonGreen."

    • The authors estimate the volume of a mammalian cell as approximately 5 pL. This estimate requires a supporting reference or experimental data. Additionally, it would be helpful to specify which cell type was considered and at which cell cycle stage this estimate applies.*

    Our cell volume estimate was based on HeLa cells reported by our previous work (Aoki, PNAS, 2011). In our study, total cell volume was determined using differential interference contrast microscopy, while nuclear volume was measured through Höechst 33258 fluorescence imaging. While we reported average volumes from 20 cells, we acknowledge that the cell cycle stage was not specified in our measurement. We have added these experimental details to the revised manuscript (page 15, line 7-9), noting that cell volumes vary with cell cycle stage.

    • Including page and/or line numbers would facilitate future revisions.*

    We have added page numbers and line numbers throughout the revised manuscript.

    Reviewer #2

    Section A

    Major Comments

    (i) Materials and Methods: Page 10 "The fitting process was constrained by initial estimates and bounded by physically reasonable limits." Please define physically reasonable limits"

    We apologize for not providing sufficient details about the fitting constraints. In the revised Material and Methods section (page 11, line 20-21) and (page 13, line 8-9), we have specified the initial parameter estimates and their boundary conditions used in our fitting process. These have included explicit numerical values for all parameters and the physical reasoning behind each constraint.

    Minor points

    *(i) Figure 1. Panels C, F, G and H. Please improve color palette to distinguish the overlapping traces. It might be helpful to remove the edge grey and broaden the color spectrum for visual inclusion (eg straw/blue vs green/red). Could the statement "As expected, mNG exhibited tolerance to the photobleaching when excited at low laser power (We have changed the color palette to make them easy to distinguish.

    SectionB

    Major points

    (i) In analysing the data, the model assumes that the monomeric CDK and cyclin subunits are either bound to form a binary complex or not. Can the authors discuss whether this can be presumed to be the case when they present the results. Either the labelled proteins are overexpressed to such a level that it can be presumed in the data handling that they are behaving as monomeric proteins and the resulting derived Kds reflect binary CDK-cyclin interactions. However, within the cell, the situation is more complex, and both CDKs and cyclins will mostly likely (and dependent on identity) be variably associated with multiple alternative protein partners. Can such effects be discounted in the analysis presented here and what would be the experimental grounds to do so. The authors make note of this fact in the discussion when they note that the results presented in this manuscript differ by circa an order of magnitude for the CDK1-cyclin B1 pairing reported by Pines et al using endogenously labelled proteins. They suggest that the discrepancy might result in part from competition from endogenously unlabelled proteins. This discrepancy has to be addressed.

    We acknowledge this important point about the complexity of cyclin-CDK interactions in cellular context. Our current analysis, which assumes simple binary interactions between overexpressed proteins, has several limitations as the reviewer suggested:

    1. As demonstrated by Pines laboratory's work with CDK1-cyclin B1 FCCS, dissociation constant can vary throughout the cell cycle, suggesting regulation by additional factors.
    2. Both cyclins and CDKs interact with multiple binding partners in cells, and therefore the analysis with binary interaction does not account for.
    3. Overexpression of exogenous proteins may alter the balance of these interactions. While our previous studies (Sadaie, MCB, 2014; Komatsubara, JBC, 2019) cited in the manuscript have addressed similar considerations, we agree that this aspect requires more thorough explanation. We have expanded our explanation in the results section (page 16, line 26-page17, line 8) and discussion part (page 26, line 7-23).

    (iv) Previous work from the Pines lab using FCS and FCCS to measure the binding of CDK1 to cyclin B1 in RPE-1 cells reported not only a higher affinity for the pair but also that their apparent affinity was dependent on cell cycle stage suggesting that their assembly might be multi-stepped. Both affinity and cell cycle dependency of CDK-cyclin pairings are of great interest to scientists working in the cell cycle field. It could be argued that measurements of the affinities of multiple CDK-cyclin pairs each "averaged out" over the cell cycle will have less impact on the field than a few well-chosen CDK-cyclin pairs characterised in greater depth.

    We acknowledge the limitations of the current approach that averages dissociation constants across the cell cycle. The Pines laboratory's work revealed cell cycle-dependent variations in the dissociation constant for Cyclin B1-CDK1, suggesting complex regulation beyond simple binary interactions. These variations likely reflect both changes in cyclin expression levels and the involvement of additional regulatory factors throughout the cell cycle. While our comprehensive survey of multiple cyclin-CDK pairs provides a useful overview of relative binding preferences, we agree that a more focused analysis of selected pairs across different cell cycle stages would offer deeper mechanistic insights. We have expanded our discussion to address the significance of cell cycle-dependent changes in binding affinities and the potential role of additional regulatory factors as well as the trade-offs between breadth and depth in studying cyclin-CDK interactions (page 26, line 7-23).

    Minor Points

    (i) For both Figures 3 and 4 address red/green color pair choice.

    We have modified the color codes in Figures 3 and 4.

    **Referee cross-commenting**

    I would like to thank the other reviewer for their comments about requirements and possible control experiments for the use of the fluorescent probes.

    We agree that the use of tagged proteins overexpressed in cells to measure Kd values has significant limitations:

    (i) Competition between tagged and endogenous proteins

    (ii) Limiting factors that affect CDK-cyclin complex stability (PTMs and contributions from binding and assembly factors mentioned).

    (iii) Cell cycle dependent protein expression

    Points (ii) and (iii) are not applicable to all protein-protein pairs but are significant when trying to determine CDK-cyclin affinities.

    As mentioned above, we have expanded our discussion to address these limitations and their implications for interpreting the cyclin-CDK binding affinities (page 26, line 7-23).

    Ideally it would be demonstrated that this approach can return the established values for a limited subset of CDK-cyclin pairs in mammalian cells and so extrapolate the results from yeast cells where endogenous labelling was carried out.

    We are sorry, but we could not fully understand what the reviewer wanted to ask.

    We also have shared concerns about the data presentation in Figure 4.

    According to the suggestion, we have modified Figure 4.

    4. Description of analyses that authors prefer not to carry out

    Reviewer #2

    Major Comments

    (iv). Could the authors consider exploiting the tractability of yeast cells to block and release and/or genetic means to establish synchronous populations to improve data acquisition? This approach could also be employed to assess whether CDK1-cyclin B1 affinity changes with cell cycle stage (as was shown by Pines et al in RPE-1 cells) and would demonstrate that their approach is as equally suitable to sensitively distinguish CDK-cyclin pairs in yeast cells.

    We appreciate the suggestion to analyze cell cycle-dependent changes in dissociation constants using synchronized cells. However, we have deliberately chosen not to use cell synchronization methods in fission yeast for several important reasons. During cell cycle arrest, cells continue to grow and synthesize proteins, leading to cell elongation and abnormal accumulation of Cdc13. These unphysiological perturbations are evidenced by the unusually rapid progression through the subsequent cell cycle following release. Such conditions deviate significantly from normal cellular physiology. One of the key advantages of FCCS is its ability to measure protein-protein interactions in individual, asynchronous cells. While traditional biochemical analyses require cell synchronization to obtain population-averaged measurements, they inherently suffer from the artifacts mentioned above.

    Instead, as described in (ii), we will utilize cell length as a natural indicator of cell cycle progression in fission yeast, allowing us to examine the relationship between cell cycle stage and Kd values while maintaining normal cellular physiology.

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    Referee #2

    Evidence, reproducibility and clarity

    Summary

    In the first part of the manuscript the authors present a thorough description of the background and theoretical basis to the identification of a fluorescent pair that permits both FCS and FCCS measurements at the single cell level to enable the determination of Kd values between labelled protein pairs (Figures 1 and 2). The generation of the reagents and subsequent experimental details are thorough and would permit the experiments to be repeated. The first two sections are well argued and appropriately controlled.

    They then tag the endogenous S. pombe cdk1 and cdc13 genes at their 3' ends with sequences that encode miRFP670 (a near infrared fluorescent protein) and mNG (mNeonGreen) respectively and from measurements collected on 13 cells derive a mean Kd value calculated for each of the 13 cells of 0.31{plus minus}0.22 μM. They note that this value agrees with that reported by the Pines lab following labelling of cyclin B1 and CDK1 with genome editing in RPE-1/hTERT cells.

    The final part of the manuscript then extends the technique to a pair-wise analysis of 9 cyclins and 4 CDKs in a human cell line.

    Major Comments

    (i) Materials and Methods: Page 10 "The fitting process was constrained by initial estimates and bounded by physically reasonable limits." Please define physically reasonable limits"

    (ii) For the characterisation of the cell cycle dependent expression of Cdc13 and its association with Cdc2, the level of Cdc13 expression is used to identify cell cycle stage. It would be appropriate to have an independent measure of cell cycle stage (?cell length). In using Cdc13 to identify cell cycle stage, please define the criteria used ie what level of Cdc13-mNG fluorescence intensity was used to define G1 vs S vs G2?

    (iii) Include a control experiment to compare the level of Cdc13 expression in untagged wild-type cells vs the Cdc13-mNG, CDK1- miRFP670 expressing cells to confirm that tagging does not affect Cdc13 expression, cell cycle duration or Cdc13 function.

    (iv). Could the authors consider exploiting the tractability of yeast cells to block and release and/or genetic means to establish synchronous populations to improve data acquisition? This approach could also be employed to assess whether CDK1-cyclin B1 affinity changes with cell cycle stage (as was shown by Pines et al in RPE-1 cells) and would demonstrate that their approach is as equally suitable to sensitively distinguish CDK-cyclin pairs in yeast cells.

    Minor points

    (i) Figure 1. Panels C, F, G and H. Please improve color palette to distinguish the overlapping traces. It might be helpful to remove the edge grey and broaden the color spectrum for visual inclusion (eg straw/blue vs green/red). Could the statement "As expected, mNG exhibited tolerance to the photobleaching when excited at low laser power (< 5%) (Fig. 1C)." be supported by additional labelling on the figure panel.

    The manuscript then goes on to describe the measurement of Kds for 36 CDK-cyclin pairs in HeLa cells by overexpression of labelled CDKs and cyclins following transient overexpression by plasmid co-transfection. This last section of the manuscript requires significant revision.

    Major points

    (i) In analysing the data, the model assumes that the monomeric CDK and cyclin subunits are either bound to form a binary complex or not. Can the authors discuss whether this can be presumed to be the case when they present the results. Either the labelled proteins are overexpressed to such a level that it can be presumed in the data handling that they are behaving as monomeric proteins and the resulting derived Kds reflect binary CDK-cyclin interactions. However, within the cell, the situation is more complex, and both CDKs and cyclins will mostly likely (and dependent on identity) be variably associated with multiple alternative protein partners. Can such effects be discounted in the analysis presented here and what would be the experimental grounds to do so. The authors make note of this fact in the discussion when they note that the results presented in this manuscript differ by circa an order of magnitude for the CDK1-cyclin B1 pairing reported by Pines et al using endogenously labelled proteins. They suggest that the discrepancy might result in part from competition from endogenously unlabelled proteins. This discrepancy has to be addressed.

    (ii) Please provide the confidence interval for the data fit for each CDK-cyclin pair. In panel Figure 4I, the results are represented as a heat map to define the Kd for each CDK-cyclin pair. This panel suggests that the technique can sensitively distinguish alternative CDK-cyclin complexes where their Kd values differ in 1 uM increments. The heat map is presented with block colours, but the key to the color coding is a graded color scheme and it is not possible to move between the two. This disconnect has to be addressed. The accompanying text on pages 18 and 19 is a qualitative description of the results, a comparative and quantitative analysis of the data (Kd values with accompanying confidence intervals) has to be included to justify the apparent strength of the technique to discriminate different CDK-cyclin pairs that Figure 4 implies.

    (iii) For "low affinity" interactions that are determined to be >10 uM. Please define how this value was calculated. Would it be more appropriate to say a value could not be determined as the data could not be fitted?

    (iv) Previous work from the Pines lab using FCS and FCCS to measure the binding of CDK1 to cyclin B1 in RPE-1 cells reported not only a higher affinity for the pair but also that their apparent affinity was dependent on cell cycle stage suggesting that their assembly might be multi-stepped. Both affinity and cell cycle dependency of CDK-cyclin pairings are of great interest to scientists working in the cell cycle field. It could be argued that measurements of the affinities of multiple CDK-cyclin pairs each "averaged out" over the cell cycle will have less impact on the field than a few well-chosen CDK-cyclin pairs characterised in greater depth.

    Minor Points

    (i) For both Figures 3 and 4 address red/green color pair choice.

    Referee cross-commenting

    I would like to thank the other reviewer for their comments about requirements and possible control experiments for the use of the fluorescent probes.

    We agree that the use of tagged proteins overexpressed in cells to measure Kd values has significant limitations:

    (i) Competition between tagged and endogenous proteins

    (ii) Limiting factors that affect CDK-cyclin complex stability (PTMs and contributions from binding and assembly factors mentioned).

    (iii) Cell cycle dependent protein expression

    Points (ii) and (iii) are not applicable to all protein-protein pairs but are significant when trying to determine CDK-cyclin affinities.

    Ideally it would be demonstrated that this approach can return the established values for a limited subset of CDK-cyclin pairs in mammalian cells and so extrapolate the results from yeast cells where endogenous labelling was carried out.

    We also have shared concerns about the data presentation in Figure 4.

    Significance

    Technology: The paper describes a technical advance in identifying a fluorescent probe pair suitable for FCCS in living cells.

    Cell cycle: The ability of CDKs and cyclins to discriminate each other and pair to form complexes that characterise different cell cycle stages and drive progression has long been appreciated. The formation of non-cognate pairings when the cell cycle is perturbed has also been noted and a greater understanding of the in-cell affinities of all possible CDK-cyclin complexes would be a significant advance in our understanding. However, this manuscript currently does not (i) provide statistically validated measures of apparent differences in affinity between different CDK-cyclin pairs and (ii) address whether the measurements are cell cycle dependent. (iii) Interpretation of the results has to take into consideration that both the CDK and cyclin components are transiently over expressed in cells and therefore the values that are measured are difficult to interpret in terms of CDK and cyclin function. These considerations would dampen interest in the findings by cell cycle biologists.

    Expertise: CDKs, cyclin, cell cycle biology.

    Non-expert in technical aspects of fluorescence microscopy

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    Referee #1

    Evidence, reproducibility and clarity

    Major Concerns

    1. Fig. 3G, Cdc2-miRFP670 levels appear to drop after cell division, which is a surprising observation because Cdc2 is generally considered stable. This could be an imaging artifact because the level recovers quickly after division. The authors should substantiate their findings with a western blot analysis of tagged vs untagged proteins. Additionally, the authors should test whether endogenously tagging Cdc2 and Cdc13 causes any cell cycle phenotypes.
    2. The authors explore a panel of red-fluorescent proteins to identify those with the best photobleaching properties. Conducting a similar review with a panel of green fluorescent proteins would significantly enhance the manuscript. It would be particularly helpful to test the properties of the new StayGold fluorescent protein.
    3. In both yeast and mammalian experiments, the green fluorophore is consistently fused to the cyclin and the far-red fluorophore to Cdk1. The authors should include an FCCS control reversing the fluorophores in at least one experiment to verify whether comparable Kd values are obtained.
    4. The authors extensively characterize the Kd of cyclin/Cdk pairs using overexpressed proteins. This approach is problematic due to the heterogeneous expression levels associated with transient expression and competition between overexpressed proteins and endogenous proteins. Variable expression levels are are a concern because of the limiting rate of T-loop phosphorylation on Cdks (Merrick et al., 2008), which is required to stabilise cyclin/Cdk complexes. While the authors acknowledge the competition between exogenous and endogenous proteins, they do not take into account the cell cycle-dependent fluctuation of cyclin levels. For instance, in cells with low levels of endogenous Cyclin B1 (S-phase), competition with overexpressed Cyclin B1 will have less impact on cross-correlation measurements compared to cells with high endogenous Cyclin B1 (G2-phase). These issues severely affect the relevance of this dataset. Indeed, the reported measurements differ by at least an order of magnitude from the Kd values obtained through biochemical methods or FCCS with endogenously tagged proteins. Moreover, the data partially diverge from the literature; for example, Cdk1 is known to form unconventional complexes with Cyclin Ds and Es.
    5. Fig. S3A, Cyclin E levels are shown to persist into mitosis, whereas endogenous Cyclin E is degraded in late S and G2 phases. This is likely to be caused by over-expression and the authors should comment on this.

    Minor Comments

    1. The authors should reference relevant studies from Jan Ellenberg's lab on FCS (e.g., Wachsmuth et al., 2015; Cai et al., 2018).
    2. The statement, "In order to perform FCCS in a reproducible manner, we are trying to find a better fluorescent protein pair that is bright, crosstalk-free, and highly resistant to photobleaching," would be improved by removing the word "better".
    3. In Fig. 1C, F, G, and H, the colour codes are difficult to read and should be improved.
    4. The paragraph discussing Fig. 3 states: "We used a fission yeast strain that expressed SynPCB2.1 under the control of the adh promoter," raising the question of how emiRFP670 was imaged in earlier experiments.
    5. The authors estimate the volume of a mammalian cell as approximately 5 pL. This estimate requires a supporting reference or experimental data. Additionally, it would be helpful to specify which cell type was considered and at which cell cycle stage this estimate applies.
    6. Including page and/or line numbers would facilitate future revisions.
    7. Fig. 4I would benefit from providing actual Kd values alongside the color-coded representation.

    Significance

    In this study, Toyama and colleagues characterize a novel low-bleaching fluorophore pair to detect protein-protein interactions through FCCS. They demonstrate that while red-fluorescent proteins bleach rapidly, NeonGreen and iRFP670 are relatively stable over time and applicable to both yeast and mammalian cells. Furthermore, they apply their system to cyclin-Cdk pairs and describe a clever approach to enhance the brightness of iRFP670 in mammalian cells. The data are clear and the identification of suitable fluors for FCCS will be of value to the field; however, there are several major concerns that need to be addressed before publication.

  4. Version published to 10.1101/2024.11.14.623553v1 on bioRxiv