Author response:
eLife assessment:
This manuscript reports valuable findings on the role of the Srs2 protein in turning off the DNA damage signaling response initiated by Mec1 (human ATR) kinase. The data provide solid evidence that Srs2 interaction with PCNA and ensuing SUMO modification is required for checkpoint downregulation. However, experimental evidence with regard to the model that Srs2 acts at gaps after camptothecin-induced DNA damage is currently lacking. The work will be of interest to cell biologists studying genome integrity but would be strengthened by considering the possible role of Rad51 and its removal.
We appreciate the editors and the reviewers for providing evaluation and helpful comments. As detailed below, we plan to adjust the writing and figures to address the points raised by the reviewers. We believe that these changes will improve the clarity of the work. Below is a summary of our plan to address the two main criticisms.
(1) Regarding the sites of Srs2 action, our data support the conclusion that Srs2 removal of RPA is favored at a subset of ssDNA regions that have proximal PCNA, but not at sites lacking PCNA. A logical supposition for the former types of ssDNA regions includes ssDNA gaps and tails generated during DNA repair or replication, wherein PCNA can be loaded at the ssDNA-dsDNA junction with a 3’ DNA end. Examples of the latter type of ssDNA regions without proximal PCNA can form within negatively supercoiling regions or intact R-loops, both of which lack 3’ DNA end for PCNA loading. While we have stated this conclusion in the text, we highlighted ssDNA gaps as sites of Srs2 action in Discussion and in the model figure, which could be misleading. We will clarify our model, that is, Srs2 distinguishes among different types of ssDNA regions using PCNA proximity as a guide for RPA removal, and state that the precise nature of Srs2 action sites remain to be determined. Regardless, the feature of Srs2 revealed in this work provides a rationale for how it can remove RPA at subsets of ssDNA regions without unnecessary stripping of RPA at other sites.
(2) While Rad51 removal is an important facet of Srs2 functions, it is not relevant to our current study based on the following observations and rationales.
First, we have provided several lines of evidence to support the conclusion that Rad51 removal by Srs2 is separable from the Srs2-RPA antagonism (Dhingra et al., 2021). For example, while rad51∆ rescues the hyper-recombination phenotype of srs2∆ cells, it does not affect the hyper-checkpoint phenotype of srs2∆. Strikingly, rfa1-zm1/zm2 have the opposite effect. The differential effects of rad51∆ and rfa1-zm1/zm2 were also seen for the _srs2-_ATPase dead allele (srs2-K41A). For example, rfa1-zm2 rescued the hyper-checkpoint defect and the CPT sensitivity of srs2-K41A, while rad51∆ had neither effect.
These and other data described in Dhingra et al suggest that Srs2’s effects on checkpoint vs. recombination are separable and that the Srs2-RPA antagonism during the DNA damage checkpoint is independent of Rad51.
Second, our current work addresses which Srs2 features affect the Srs2-RPA antagonism during the DNA damage response and its implications. Given this antagonism is separable from Srs2 removal of Rad51, including Rad51 regulation would be distractive from the main points of this work.
Third, in the current work, we began by examining all known regulatory and protein-protein interaction features of Srs2, including the Rad51 binding domain. Consistent with our conclusion summarized above based on the Dhingra et al study, deleting the Rad51 binding domain in Srs2 (srs2-∆Rad51BD) has no effect on rfa1-zm2 phenotype in CPT (Figure 2D). This is in sharp contrast to mutating the PCNA binding and the sumoylation sites of Srs2, which suppressed rfa1-zm2 for its CPT sensitivity and checkpoint abnormalities (Figure 2C). This data provides yet another evidence that Srs2 regulation of Rad51 is separable from the Srs2-RPA antagonism.
In summary, our work provides a foundation for future examination of how Srs2 regulates RPA and Rad51 in different manners, how these two facets of the Srs2 functions affect genome integrity in different capacity, and whether there is a crosstalk between them during certain DNA metabolism processes.
Public Reviews:
Reviewer #1:
Overall, the data presented in this manuscript is of good quality. Understanding how cells control RPA loading on ssDNA is crucial to understanding DNA damage responses and genome maintenance mechanisms. The authors used genetic approaches to show that disrupting PCNA binding and SUMOylation of Srs2 can rescue the CPT sensitivity of rfa1 mutants with reduced affinity for ssDNA. In addition, the authors find that SUMOylation of Srs2 depends on binding to PCNA and the presence of Mec1. Noted weaknesses include the lack of evidence supporting that Srs2 binding to PCNA and its SUMOylation occur at ssDNA gaps, as proposed by the authors. Also, the mutants of Srs2 with impaired binding to PCNA or impaired SUMOylation showed no clear defects in checkpoint dampening, and in some contexts, even resulted in decreased Rad53 activation. Therefore, key parts of the paper would benefit from further experimentation and/or clarification.
We thank the reviewer for the positive comments on this work and address her/his remark regarding ssDNA gaps below in Major Comment #1. In addition, we detailed below our data and rationale in suggesting that the checkpoint dampening phenotype of srs2-∆PIM and -3KR (deficient for PCNA binding and sumoylation, respectively) is masked by redundant pathways. We further describe our plan to enhance the clarity of both text and model to address these points from the reviewer.
Major Comments
(1) The central model proposed by the authors relies on the loading of PCNA at the 3' junction of an ssDNA gap, which then mediates Srs2 recruitment and RPA removal. While several aspects of the model are consistent with the data, the evidence that it is occurring at ssDNA gaps is not strong. The experiments mainly used CPT, which generates mostly DSBs. The few experiments using MMS, which mostly generates ssDNA gaps, show that Srs2 mutants lead to weaker rescue in this context (Figure S1). How do the authors explain this discrepancy? In the context of DSBs, are the authors proposing that Srs2 is engaging at later steps of HRdriven DSB repair where PCNA gets loaded to promote fill-in synthesis? If so, is RPA removal at that step important for checkpoint dampening? These issues need to be addressed and the final model adjusted.
We appreciate the reviewer’s concern. Our conclusion is that Srs2 can be guided by PCNA to a subset of ssDNA regions for RPA removal, and that this Srs2 action is not favored at ssDNA regions with no proximal PCNA. It is important to note that CPT can produce both types of ssDNA regions. Besides ssDNA generated via DSB-associated recombinational repair, CPT can also lead to ssDNA gap formation upon excision repair and DNA-protein crosslink repair of trapped Top1 (Sun et al., 2020). ssDNA regions generated during these DNA repair processes often contain 3’ DNA end for PCNA loading, thus they can favor Srs2 removal of RPA. Another facet of CPT’s effects (besides DNA lesions) is depleting functional pool of Top1, thus causing topological stress and consequently increased levels of DNA supercoiling and R-loops (Koster et al., 2007, Petermann et al., 2022). ssDNA formed within the negatively supercoiled regions and in R-loops lacks 3’ DNA end unless it is cleaved by nucleases, thus these sites would be disfavored for Srs2 removal of RPA due to lack of PCNA loading. Our conclusion that ssDNA regions with nearby PCNA are preferred sites for Srs2 action provides a rationale for how Srs2 can remove RPA at certain ssDNA regions but minimize unnecessary stripping of RPA from other sites.
We will clarify in Discussion that CPT can generate twp types of ssDNA regions as stated above, and that Srs2 could distinguish among them using PCNA proximity as a guide for RPA removal. While this conclusion was described in the text, we emphasized ssDNA gap as a Srs2 action site in the model. We will clarify that while this is a logical supposition, other types of ssDNAs with proximal PCNA could also be targeted by Srs2 and that our work paves the way to determine the precise nature of ssDNA regions for Srs2’s action.
The reasons for the less potent growth suppression of rfa1 mutants by srs2 alleles in MMS condition compared with CPT condition are unclear, but multiple possibilities should be considered, given that MMS and CPT affect checkpoint responses differently and that RPA and Srs2 affect growth in multiple ways. For example, while CPT only activates the DNA damage checkpoint, MMS additionally induces DNA replication checkpoint (Menin et al., 2018, Redon et al., 2003). It is thus possible that the Srs2-RPA antagonism is relatively more important for the DNA damage checkpoint than the DNA replication checkpoint. Further investigation of this possibility among others will shed light on differential suppressive effects seen in this work. We will include this discussion in the revised text.
(2) The data in Figure 3 showing that Srs2 mutants reduce Rad53 activation in the rfa1-zm2 mutant are confusing, especially given the claim of an anti-checkpoint function for Srs2 (in which case Srs2 mutants should result in increased Rad53 activation). The authors propose that Rad53 is hyperactivated in rfa1-zm2 mutant because of compromised ssDNA protection and consequential DNA lesions, however, the effects sharply contrast with the central model. Are the authors proposing that in the rfa1-zm2 mutant, the compromised protection of ssDNA supersedes the checkpoint-dampening effect? Perhaps a schematic should be included in Figure 3 to depict these complexities and help the reader. The schematic could also include the compensatory dampening mechanisms like Slx4 (on that note, why not move Figure S2 to a main figure?... and even expand experiments to better characterize the compensatory mechanisms, which seem important to help understand the lack of checkpoint dampening effect in the Srs2 mutants)
Genetic interactions that involve partially defective alleles, multi-functional proteins, and redundant pathways are complex to comprehend. For example, a phenotype seen for the null allele may not be seen for partially defective alleles. In the context of this study, while srs2 null increased Rad53 activation (Dhingra et al., 2021), srs2-∆PIM and -3KR did not (Figure 3A-3B). However, srs2-∆PIM enhanced Rad53 activation when combined with another checkpoint dampening mutant slx4RIM, suggesting that defects of srs2-∆PIM can be compensated by Slx4 (Figure S2). Importantly, srs2-∆PIM and -3KR rescued rfa1-zm2’s checkpoint abnormality (Figure 3A3B), suggesting that Srs2 binding to PCNA and its sumoylation contribute to the Srs2-RPA antagonism in the DNA damage checkpoint response.
A partially defective allele that impairs a specific function of a protein can be a powerful genetic tool even when it lacks a particular phenotype on its own. For example, a partially defective allele of the checkpoint protein Rad9 impairing its binding to gamma-H2A (rad9-K1088M) does not affect the G2/M checkpoint nor cause DNA damage sensitivity due to the compensation of other checkpoint factors (Hammet et al., 2007); however_, rad9-K1088M_ rescues the DNA damage sensitivity and persistent G2/M checkpoint of rtt107 and slx4 mutants, providing one of the evidences supporting a role of the Slx4-Rtt107 axis in removal of Rad9 from chromatin (via competing with Rad9 for gamma-H2A binding) (Ohouo et al., 2013).
In order to highlight the checkpoint recovery process, the model in Figure 6 did not depict another consequence of the Srs2-RPA antagonism. In the presence of Srs2, DNA binding rfa1 mutants can lead to increased levels of DNA lesions and checkpoint, and these defects are rescued by lessening Srs2’s ability to strip RPA from DNA (Dhingra et al., 2021). We will modify the model in Figure 6 and its legend to clarify that the model depicts just one of the consequences of the Srs2 and RPA antagonism with a focus on the checkpoint recovery. We will also state these points more clearly in the Discussion. Further, a new schematic in Figure 3 as suggested by the reviewer will be added to outline the genetic relationship and interpretation. We will also follow reviewer’s suggestion to move Figure S2 to the main figures. Better characterizing the compensatory mechanisms among different checkpoint dampening pathways is very interesting but requires substantial amounts of work. While it is beyond the scope of the current study, it could be pursued in the future.
(3) The authors should demarcate the region used for quantifying the G1 population in Figure 3B and explain the following discrepancy: By inspection of the cell cycle graph, all mutants have lower G1 peak height compared to WT (CPT 2h). However, in the quantification bar graph at the bottom, ΔPIM has higher G1 population than the WT.
We have added the description on how the G1 region of the FACS histogram was selected to derive the percentage of G1 cells in Figure 3B. Briefly, for samples collected for a particular strain, the G1 region of the “G1 sample” was used to demarcate the G1 region of the “CPT 2h” sample. Upon re-checking the included FACS profiles, we realized that a mutant panel and its datapoint were mistakenly put in the place for wild-type. We will correct this mistake. The conclusion remains that srs2-∆PIM and srs2-3KR improved rfa1-zm2 cells’ ability to exit G2/M, while they themselves do not show difference from the wild-type control for the percentage of G1 cells after 2hr CPT treatment. We will add statistics in figures to reflect this conclusion and adjust the order of strains shown in panel A and B to be consistent with each other.
Reviewer #2:
This is an interesting paper that delves into the post-translational modifications of the yeast Srs2 helicase and proteins with which it interacts in coping with DNA damage. The authors use mutants in some interaction domains with RPA and Srs2 to argue for a model in which there is a balance between RPA binding to ssDNA and Srs2's removal of RPA. The idea that a checkpoint is being regulated is based on observing Rad53 and Rad9 phosphorylation (so there are the attributes of a checkpoint), but evidence of cell cycle arrest is lacking. The only apparent delay in the cell cycle is the re-entry into the second S phase (but it could be an exit from G2/M); but in any case, the wild-type cells enter the next cell cycle most rapidly. No direct measurement of RPA residence is presented.
We thank the reviewer for the helpful comments. Previous studies have shown that CPT does not induce the DNA replication checkpoint, thus it does not slow down or arrest S phase progression; however, CPT does induce the DNA damage checkpoint, which causes a delay of G2/M cells to re-enter into the second cell cycle (Menin et al., 2018, Redon et al., 2003). Our result is consistent with previous findings, showing that CPT induces G2/M delay but not arrest. We will adjust the text to make this point clearer.
We have previously reported chromatin-bound RPA levels in rfa1-zm2, srs2, and their double mutants, as well as in vitro ssDNA binding by wild-type and mutant RPA complexes (Dhingra et al., 2021). We found that Srs2 loss or its ATPase dead mutant led to 4-6 fold increase of RPA levels on chromatin, which was rescued by rfa1-zm2 (Dhingra et al., 2021). On its own, rfa1-zm2 did not cause defective chromatin association in our assays, despite modestly reducing ssDNA binding in vitro (Dhingra et al., 2021). This discrepancy could be due to a lack of sensitivity of chromatin fractionation assay in revealing moderate changes of RPA residence on DNA. Considering this, we decided to employ functional assays (Figure 2-3) that are more effective in identifying the Srs2 features pertaining to RPA regulation.
Strengths:
Data concern viability assays in the presence of camptothecin and in the post-translational modifications of Srs2 and other proteins.
Weaknesses:
There are a couple of overriding questions about the results, which appear technically excellent. Clearly, there is an Srs2-dependent repair process here, in the presence of camptothecin, but is it a consequence of replication fork stalling or chromosome breakage? Is repair Rad51-dependent, and if so, is Srs2 displacing RPA or removing Rad51 or both? If RPA is removed quickly what takes its place, and will the removal of RPA result in lower DDC1-MEC1 signaling?
While Srs2 can affect both the checkpoint response and DNA repair in CPT conditions, the rfa1-zm2 allele, which affects the former but not the latter, role of Srs2, allows us to gain a deeper understanding of the former role (Dhingra et al., 2021). This role also appears to be critical for cell survival in CPT, since srs2∆ growth on CPT-containing media was greatly improved by rfa1-zm mutants (Dhingra et al., 2021). Building on this understanding, our current study identified two Srs2 features that could afford spatial and temporal regulations of RPA removal from DNA, thus providing a rationale for how cells can properly utilize this beneficial yet also dangerous activity. Study of Srs2-mediated repair in CPT conditions, either in Rad51-dependent or independent manner, before and after replication forks stall or DNA breaks, will require substantial efforts and can be pursued in the future. We will add this point to the revised manuscript.
Moreover, it is worth noting that in single-strand annealing, which is ostensibly Rad51 independent, a defect in completing repair and assuring viability is Srs2-dependent, but this defect is suppressed by deleting Rad51. Does deleting Rad51 have an effect here?
We have shown in our previous paper (Dhingra et al., 2021). that rad51∆ did not rescue the hyper-checkpoint phenotype of srs2∆ cells in CPT condition (Dhingra et al., 2021), while rfa1-zm1 and -zm2 did (Dhingra et al., 2021). Such differential effects were also seen for the srs2 ATPase-dead allele (Dhingra et al., 2021). These and other data described in the Dhingra et al paper suggest that Srs2’s effects on checkpoint vs. recombination are separable at least in CPT condition, and that the Srs2-RPA antagonism in checkpoint regulation is not affected by Rad51 removal (unlike in SSA situation).
Neither this paper nor the preceding one makes clear what really is the consequence of having a weakerbinding Rfa1 mutant. Is DSB repair altered? Neither CPT nor MMS are necessarily good substitutes for some true DSB assay.
In our previous report (Dhingra et al., 2021), we showed that the rfa1-zm mutants did not affect the frequencies of rDNA recombination, gene conversation, or direct repeat repair (Dhingra et al., 2021). Further, rfa1-zm mutants did not suppress the hyper-recombination phenotype of srs2∆, while rad51∆ did (Dhingra et al., 2021). In a DSB system, wherein the direct repeats flanking the break were placed 30 kb away from each other, srs2∆ led to hyper-checkpoint and lethality, both of which were rescued by rfa1-zm mutants (Dhingra et al., 2021). In this assay, rfa1-zm mutants themselves did not show sensitivity, suggesting the repair is largely proficient. Collectively, these data provide evidence to suggest that weaker DNA binding of Rfa1 does not have detectable effect on the recombinational repair assays examined thus far, rather it has a profound effect in Srs2-mediated checkpoint downregulation. In-depth studies of rfa1-zm mutations in the context of various DSB repair steps will be interesting to pursue in the future.
With camptothecin, in the absence of site-specific damage, it is difficult to test these questions directly. (Perhaps there is a way to assess the total amount of RPA bound, but ongoing replication may obscure such a measurement). It should be possible to assess how CPT treatment in various genetic backgrounds affects the duration of Mec1/Rad53-dependent checkpoint arrest, but more than a FACS profile would be required.
Quantitative measurement of RPA residence time on DNA in cells and the duration of Mec1/Rad53-dependent checkpoint arrest will be very informative but requires further technology development. Our current work provides a foundation for such quantitative assessment.
It is also notable that MMS treatment does not seem to yield similar results (Fig. S1).
Figure S1 showed that srs2-∆PIM and srs2-3KR had weaker suppression of rfa1-zm2 growth on MMS plates than on CPT plates. The reasons for the less potent growth suppression in MMS condition compared with CPT condition are unclear, but multiple possibilities should be considered, given that MMS and CPT affect checkpoint responses differently and that RPA and Srs2 affect growth in multiple ways. For example, while CPT only activates the DNA damage checkpoint, MMS additionally induces DNA replication checkpoint (Menin et al., 2018, Redon et al., 2003). It is thus possible that the Srs2-RPA antagonism is more important for the DNA damage checkpoint than the DNA replication checkpoint. Further investigation of this and other possibilities will provide clues to the differential suppressive effects seen in this work. We will include this discussion in the revised text.
Reviewer #3:
The superfamily I 3'-5' DNA helicase Srs2 is well known for its role as an anti-recombinase, stripping Rad51 from ssDNA, as well as an anti-crossover factor, dissociating extended D-loops and favoring non-crossover outcome during recombination. In addition, Srs2 plays a key role in ribonucleotide excision repair. Besides DNA repair defects, srs2 mutants also show a reduced recovery after DNA damage that is related to its role in downregulating the DNA damage signaling or checkpoint response. Recent work from the Zhao laboratory (PMID: 33602817) identified a role of Srs2 in downregulating the DNA damage signaling response by removing RPA from ssDNA. This manuscript reports further mechanistic insights into the signaling downregulation function of Srs2.
Using the genetic interaction with mutations in RPA1, mainly rfa1-zm2, the authors test a panel of mutations in Srs2 that affect CDK sites (srs2-7AV), potential Mec1 sites (srs2-2SA), known sumoylation sites (srs2-3KR), Rad51 binding (delta 875-902), PCNA interaction (delta 1159-1163), and SUMO interaction (srs2SIMmut). All mutants were generated by genomic replacement and the expression level of the mutant proteins was found to be unchanged. This alleviates some concern about the use of deletion mutants compared to point mutations. The double mutant analysis identified that PCNA interaction and SUMO sites were required for the Srs2 checkpoint dampening function, at least in the context of the rfa1-zm2 mutant. There was no effect of these mutants in a RFA1 wild-type background. This latter result is likely explained by the activity of the parallel pathway of checkpoint dampening mediated by Slx4, and genetic data with an Slx4 point mutation affecting Rtt107 interaction and checkpoint downregulation support this notion. Further analysis of Srs2 sumoylation showed that Srs2 sumoylation depended on PCNA interaction, suggesting sequential events of Srs2 recruitment by PCNA and subsequent sumoylation. Kinetic analysis showed that sumoylation peaks after maximal Mec1 induction by DNA damage (using the Top1 poison camptothecin (CPT)) and depended on Mec1. These data are consistent with a model that Mec1 hyperactivation is ultimately leading to signaling downregulation by Srs2 through Srs2 sumoylation. Mec1-S1964 phosphorylation, a marker for Mec1 hyperactivation and a site found to be needed for checkpoint downregulation after DSB induction did not appear to be involved in checkpoint downregulation after CPT damage. The data are in support of the model that Mec1 hyperactivation when targeted to RPA-covered ssDNA by its Ddc2 (human ATRIP) targeting factor, favors Srs2 sumoylation after Srs2 recruitment to PCNA to disrupt the RPA-Ddc2-Mec1 signaling complex. Presumably, this allows gap filling and disappearance of long-lived ssDNA as the initiator of checkpoint signaling, although the study does not extend to this step.
Strengths
(1) The manuscript focuses on the novel function of Srs2 to downregulate the DNA damage signaling response and provide new mechanistic insights.
(2) The conclusions that PCNA interaction and ensuing Srs2-sumoylation are involved in checkpoint downregulation are well supported by the data.
We thank the reviewer for carefully reading our work and for his/her positive comments.
Weaknesses
(1) Additional mutants of interest could have been tested, such as the recently reported Pin mutant, srs2Y775A (PMID: 38065943), and the Rad51 interaction point mutant, srs2-F891A (PMID: 31142613).
srs2-Y775A was shown to be proficient for stripping RPA from ssDNA and behaved like wild-type Srs2 in assays such as gene conversion and crossover control, and exhibited a genetic interaction profile as the wildtype allele. The authors suggest that the Y775 pin can contribute to unwinding secondary DNA structures. Collectively, these findings do not provide a strong rationale for srs2-Y775A being relevant for RPA removal from ssDNA.
We have already included the data showing that a srs2 mutant lacking the Rad51 binding domain (srs2-∆Rad51BD, ∆875-902) did not affect rfa1-zm2 growth in CPT nor caused other defects in CPT on its own (Figure 2D). This data suggest that Rad51 binding is not relevant to the Srs2-RPA antagonism in CPT, a conclusion fully supported by data in our previous study (Dhingra et al., 2021). Collectively, these findings do not provide a strong rationale to test a point mutation within the Rad51BD region.
(2) The use of deletion mutants for PCNA and RAD51 interaction is inferior to using specific point mutants, as done for the SUMO interaction and the sites for post-translational modifications.
We agree with this view generally. However, this is less of a concern for the Rad51 binding site mutant (srs2∆Rad51BD), as it behaved as the wild-type allele in our assays. The srs2-∆PIM mutant (lacking 4 amino acids) has been examined for PCNA binding in vitro and in vivo in several studies (e.g. Kolesar et al., 2016, Kolesar et al., 2012); to our knowledge no unintended defect was reported. We thus believe that this allele is suitable for testing whether Srs2’s ability to bind PCNA is relevant to RPA regulation.
(3) Figure 4D and Figure 5A report data with standard deviations, which is unusual for n=2. Maybe the individual data points could be plotted with a color for each independent experiment to allow the reader to evaluate the reproducibility of the results.
We will include individual data points as suggested and correct figure legend to indicate that three independent biological samples per genotype were examined in both panels.
References:
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