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Reply to the reviewers
Manuscript number: RC-2022-01682
Corresponding author(s): Peter Keyel
- General Statements
We thank the reviewers for their thorough and critical analysis of our manuscript. We have addressed most of the concerns and questions with our revised version. To address the remaining concerns, we plan to perform two lines of experiments— aerolysin sensitivity of dysferlin null C2C12 muscle cells and aerolysin sensitivity of ESCRT-impaired cells. When these experiments are complete, we believe the revised contribution will provides important novel insights into membrane repair that will appeal to a broad audience.
Reviewer comments below are in italics.
Description of the planned revisions
Reviewer 1
Major
In order to show that patch repair is indeed protecting cells against aerolysin, the authors should disrupt patch repair of the cells under study and observe and increased toxicity.
Reviewer 2
Major
*1. The effect of dysferlin overexpression does not indicate that patch repair is a protective mechanism or that dysferlin plays a significant role in aerolysin resistance. The authors should knock out dysferlin and assess cell resistance to lysis. *
Reviewer 3
Significance
The work presents a foundation to further investigate into the mechanism of aerolysin function, following the discovery of the role of extracellular Ca2+ in its activity. As aforementioned, the role of dysferlin in resisting aerolysin also has potential, but the limitations of this work were discussed including the absence of performing a dysferlin knockout, although performing this experiment may help to strengthen the current finding.
We agree with all 3 reviewers that a dysferlin knockout will complement our gain-of-function studies and this will strengthen the manuscript. We plan to challenge C2C12 myocytes that express control shRNA or dysferlin shRNA with toxin and determine their sensitivity.
We chose this system instead of targeting a patch repair protein in HeLa cells for 3 reasons. First, it will provide the corresponding loss-of-function experiment to match the gain-of-function experiments we have already done. Second, other patch repair proteins work redundantly with other proteins, complicating their knockdown and/or their disruption may interfere with lipid/protein transport. Finally, dysferlin null C2C12 cells are commercially available, so other groups will have an easier time replicating our results.
Reviewer 1
Significance
*and in the statement that a cellular process that has been artificially introduced in the experimental system is the cellular protection mechanism against aerolysin attack. In order to prove that this process is a bona fide protection mechanism, the authors should show that it is present without the need of overexpressing a protein that is not expressed at all either in the used cell line (HeLa), or in the natural cellular target of aerolysin (epithelial cells). The significance of the proposed protection mechanism is therefore questionable. *
We plan to address this concern by using C2C12 muscle cells that have and do not have dysferlin. Muscle cells are natural cellular targets of Aeromonas during necrotizing soft-tissue infections.
Reviewer 2
Major
*2. ESCRT complex was shown to play a role in plasma membrane repair following mechanical damage or perforin treatment of cells (Jimenez 2014, and Ritter, 2022). Whether ESCRT is important in aerolysin pore repair can be assessed by knocking out the Chmp4b gene or overexpressing dominant-negative mutant of VPS4a, E228Q. *
We plan to use a previously characterized (Lin 2005 PMID: 15632132) inducible system (TRex cells) to express the dominant negative VPS4b E235Q in cells. We plan to pulse cells for 2 h with 1 ug/mL doxycycline one day prior to the assay. This pulse time and dose strikes a balance between cell death due to non-functional ESCRT, and compromising ESCRT function. Then we will challenge parental cells (TRex) or TRex cells expressing VPS4b E235Q with toxin and measure lysis. We also plan to compare plus/minus doxycycline as a further control. We will also use fluorescent toxins to compare binding across cell types.
One caveat on the ESCRT work is that ESCRT has an essential role in MVB formation, and ESCRT effects might be due to perturbation of protein/lipid flux through this system in addition to their recruitment to the plasma membrane. Even with knockdowns and overexpression, it can be challenging to interpret some of the pleiotropic effects of altering the ESCRT complex. While we do not contest the role for ESCRT in plasma membrane repair, we suspect the role for ESCRT will be more complicated than previously appreciated. Digging deeper into these possibilities beyond our proposed experiment is beyond the scope of this manuscript.
Description of the revisions that have already been incorporated in the transferred manuscript
Reviewer 1
*Major:
The authors conclusions contradict established results, which they cite. Yet experimental conditions are not similar in two ways: toxin concentration-wise and toxin treatment duration-wise. *
We agree with the reviewer that there were differences in experimental design between our study and the other cited studies. Due to the cited differences, our results, Gonzalez et al and Larpin et al are not necessarily contradictory on most points. Our conclusions differ from Gonzalez et al in that we do not think K+ efflux drives repair in the first hour, and differ from Larpin et al in that we observe Ca2+ flux after aerolysin challenge. Along with the toxin variables discussed below, we also discussed the potential cell type differences between the studies that may account for the discrepancy. We have now included these additional differences in our manuscript on line 435 for Larpin et al and lines 423-425 for Gonzalez.
Our study set out to do something distinct from the prior studies. The prior studies did not compare the efficacy of distinct membrane repair mechanisms to the same toxin because that was not their study aim. Hence, our goal is not to prove the prior literature wrong, but contribute to a better understanding of the immediate membrane repair events triggered by aerolysin. We argue that the significance of our contribution is this comparative approach to membrane repair, which has not previously been done, and our finding that aerolysin engages distinct, but overlapping mechanisms compared to CDCs. We have updated our significance to better convey our advance, which is explained on lines 99-102, 128, 519-525.
*While we appreciate the efforts of the authors to standardize the concentration of toxins used based on hemolytic units, we note that the concentrations used are very much higher than in the other studies cited. Indeed, based on table 1, materials and methods, and the various experiments, aerolysin has a LC50 of approximately 200 HU/ml, which corresponds to about 2 ug/ml. This is approximately 200x more concentrated than for example in Gonzalez et al 2011 and Larpin et al. 2021. It makes the validity of direct comparison with those studies questionable. *
We agree with the reviewer that the toxin concentrations are different from prior studies. This is why we argue hemolytic activity needs to be reported along with toxin mass.
One potential explanation for this difference is purification method. We do nickel NTA purification from whole bacterial lysates, instead of from the periplasm. It is possible that the most active aerolysin precipitates early or is otherwise lost in our purification process, which accounts for both the lower toxin specific activity and lack of toxin precipitation during trypsin activation that we observe. To control for impurities, we purified two preps of our aerolysin to >90% purity after nickel beads. However, we did not observe a significant change in specific activity or cytotoxic activity. We interpret this finding to suggest there was a trade-off between improved specific activity due to increased purity and loss of specific activity due to toxin inactivation during the extended purification process.
We have included a new figure (Fig S10) showing our toxin purification and activity.
*We noticed that the authors activate pro-aerolysin at high concentration (in the range of 1 to 5 mg/ml) and at room temperature. In our experience, under these concentration, activation leads to immediate oligomerization and massive precipitation. The final concentration of active toxin is thus unknown. *
When we titrated the trypsin to determine the optimal concentration of trypsin to use, we did not observe oligomerization/precipitation (Fig S10B). If there was precipitation of aerolysin after trypsin treatment, we would expect a difference in cytotoxicity between pro-aerolysin and aerolysin treatment. We did not observe significant differences in cytotoxicity between pro-aerolysin and activated aerolysin (see Figs 1-2). Finally, we measured hemolytic activity on trypsin-activated toxin, so any precipitation would be expected to occur prior to assessing hemolytic activity. Thus, we argue our use of hemolytic activity measured after trypsin activation mitigates this risk.
*
The authors keep their cells in toxin-containing medium for the whole duration of the experiments, typically 45 minutes. This is in stark contrast with 45 seconds to 3 minutes transient exposure to toxin in Huffman et al 2004. *
We agree this is one of the differences. We also note Huffman et al examined cells at 6 or 28 h later. While we ruled out the impact of MAP kinases on membrane repair occurring within 30 min of toxin challenge, we make no claims about their ability to promote cell survival at later time points. We have clarified these differences in the manuscript (line 461).*
The authors do not report binding and oligomerization assays of the toxins. The only figure showing a western blot (fig. 7) is of low quality and shows unexpected observations. Aerolysin Y221G mutant is expected to bind and oligomerize. Yet, no band is present at about 250 kDa (expected oligomer) or at about 47 kDa (monomer). In addition, in aerolysin lanes (1 and 2) the oligomer is saturated, seems to be covering three lanes, indicating a possible spill-over. *
We performed binding studies in Fig S3C and Fig S5. For Fig 7, in the original blot, the cell lysate is a wider band than the MV band, but there are only two bands, that remained in their respective lanes. We have now included another independent biological replicate of the aerolysin blot as Supplementary Fig S7D which shows clear demarcation between cell lysate and MV pellet. This blot was not included in the main figure because in the process of stripping and reprobing for all of the targets, we lost detection of our penultimate targets. We agree with the reviewer that oligomer bands for the Y221G were very faint, and we expected them to be stronger. In the new blot (Fig S7D), some oligomer can be detected. As a result, we are hesitant to risk over-interpreting these findings.*
Finally, while the patch repair hypothesis is interesting, it is unclear why the authors decided to overexpress dysferlin in cell lines that normally do not express it. Sure, there is a repair phenotype but this phenotype is artificially introduced. Dysferlin is not expressed at all in HeLa cells. *
One challenge with membrane repair is the difficulty perturbing the system due to redundancies. While loss-of-function experiments are important, gain-of-function experiments also add confidence to the system. The simplest way to perform a gain-of-function experiment is to add a well-known patch repair protein to a well-characterized cell line lacking it. Thus, exogenous expression of dysferlin enables us to test the hypothesis that increasing patch repair enhances repair against the toxins.
We have included this rationale now in the manuscript, lines 366-369
*Furthermore, dysferlin is not expressed in epithelial cells, which are the prime target of aerolysin. Why then focus on this protein? *
We chose dysferlin because it is well-characterized as a patch repair protein, whose defect causes Limb-Girdle Muscular Dystrophy 2B and Miyoshi Myopathy. Additionally, setting up this assay enables future work to probe the role of individual dysferlin domains in patch repair.*
Minor:
The graphic legends should be boxed out to be clearly separated from the data. In Figure 4A, it is mixed up with the data. *
This has been corrected.*
Some western blots are saturated, e.g. B-actin in figure 4B. Full blots should be provided. *
We have added full western blots as requested as Supplementary Figs S11-12.*
In the methods, aerolysin sublytic dose for HeLa cells is specified at 62 HU/ml. In figure 5C and D, 31 HU/ml kills more than 50% of HeLa cells. This is not compatible. *
Even when controlling by hemolytic activity, and toxin prep, we find some variability in toxin activity between assays. For the live cell experiments, 62 HU/mL remained sublytic despite the higher activity in the flow cytometry assays. We controlled for death in our live cell imaging experiments, by including TO-PRO. This confirmed the toxin was at a sublytic dose in those experiments.
We included a new figure S10C to show the variation in LC50 per assay as a function of toxin specific activity. We have clarified that the sublytic dose was for live cell imaging experiments, lines 640-641.
*Figure 2A and B have quite different LC50 for starting conditions ({plus minus} 200 HU/ml in A, 600-700 HU/ml in B). Why is it so different? Y-axis has a linear scale in A and a logarithmic scale in B. It would make comparison easier to have the same scale in both panels. *
We agree there is variability between assays. We note that toxin doses change vary in other manuscripts that report toxin mass. For example, aerolysin varies by 10-fold (2 – 20 ng/mL) between figures in Gonzalez et al 2011. We interpret this variation as a common challenge for toxin studies. We mitigate this challenge by including controls for each assay so the relative change can be assessed. We provide additional transparency by including Fig S10 to show batch-to-batch variability of both our toxin preps and assays.
We have changed the scale to linear in Fig 2.*
The letters detonating statistically significant groups are sometimes unclear. For example in Figure 1A and B, PFO belongs to group a and b simultaneously. What does this mean? *
Samples that share letters are not statistically distinct from each other. In the example cited, PFO is not statistically significant compared to all other bars with an a and is not statistically significant compared to all other bars with a b. While confusing at first, the alternative is a mess of stars and bars.
This has been explained in lines 981-985.*
In Figure 8, aerolysin hat a LC50 in cells overexpressing GFP-Dysferin of approximately 1700 HU/ml in A and of approximately 400 HU/ml in B. Why is it so different? *
This is due to intra-assay variation. We include controls for each assay to ensure the trend remains consistent.*
In Figure S1, it is unclear what the plots « all events » vs « single cells » mean. *
We have clarified these plots.*
In the discussion, the authors write « First, survival did not correlate with overexpression, which would be expected if dysferlin acted as Ca2+ sink ». What is meant? GFP-dysferlin overexpression does correlate with survival in Figure 1A. *
We meant that the extent of Dysferlin expression did not correlate with survival. If Dysferlin acted as a calcium sink, cells expressing 100x dysferlin levels should be more resistant than cells expressing 1x dysferlin levels. If Dysferlin needs to serve a cellular function, the brightest cells may not be more resistant (or even be less resistant due to aggregates, etc). We checked to see if the brightest Dysf+ cells had better survival than the dimmest Dysf+ cells. They did not. However, all Dysf+ cells had better survival than Dysf- cells.
We have updated the manuscript (lines 496-498) to reflect these changes.
Significance
*General assessment: The study strength lies in the several possible protection mechanisms that are tested. The weaknesses lie in the contradictions of the results reported here with established mechanisms, *
We disagree with the reviewer that findings that contradict previously proposed mechanisms are a weakness for significance. Instead, we argue this is a strength of our study’s significance. Replication of prior studies’ conclusions using distinct experimental conditions is critical for the reproducibility and rigor of the underlying science, and may give new insights into toxin biology. While we acknowledge the differences in approach, these differences narrow the prior mechanisms that may have been assumed to be widely applicable. The finding that they cannot be replicated in our system suggests one or more of the differences between the studies may drive a critical aspect of aerolysin biology. For example, the Ca2+ difference with Larpin et al could be due to a cellular Ca2+ channel present in HeLa cells that is absent in THP.1/U937 cells.
This distinction is expected to spur additional research in the aerolysin field.
*
Advance: The study contradicts previously established results but the experimental conditions used here are quite different to those used in the earlier studies, which makes the comparison quite difficult. As such it does not really fill a gap. *
We have rephrased the significance to better convey both the gap our study fills in membrane repair and the advance that it has made. See lines 99-102, 128, 519-525.*
Audience: The study will be of interest of specialized audience. *
Given the emerging broad importance of membrane repair in response to endogenous pore-forming toxins, and the large gaps in the field of membrane repair, we respectfully disagree with the reviewer. We have revised our significance statements to better convey this broad appeal. See lines 99-102, 128, 519-525.
Reviewer 2
Major
*3. I find the optimisation of lysin concentrations and data presentation quite confusing. I eventually understood, what was done, but I feel that the authors should be able to transform the data and plots so these are more accessible to a reader, eg a simple dose/time-response curves would be very helpful in that respect. For example, in Figure S1E, why does aerolysin appear to be less cytotoxic after 24 hrs than after 1 hr. In principle, I would expect to observe an additive effect, i.e. cell death at 1, 3, 6, 12, and 24 hrs should add to 100%; however, if 100% cells die at 500HU/ml, how can more cells die after 24hrs? Or am I missing something in the experimental design/data presentation? *
We agree that presenting the results from cytotoxicity can be challenging. We use LC50 in the main text because it is easiest to understand. However, we provide all dose-response curves underlying those numbers in the supplemental data. We recently published our approach to assays and data analysis (Haram et al PMID: 36373947) to make it easier to understand.
In Fig S1E, each time point is a distinct assay. In contrast to the approach suggested by the reviewer, where we read the plate at different timepoints, we used different replicates to generate the time points. As a result, the % will not add to 100. Instead, we observe that the majority of cell death occurs in the first hour. We have clarified our discussion of Fig S1E, lines 154-155.
At 24 h, it is possible that cell growth interfered with the assay. The plate has a finite surface area. If control cells are confluent near the start of the assay, but toxin-treated cells are not due to cell death by aerolysin, the growth rates may not be equal. Since our focus is on proximal membrane repair events, and not on late signaling events, pursuing this further is beyond the scope of the current manuscript.
*I also wonder whether using haemolytic units is appropriate (it may well be, if justified), given that the toxins used here have various membrane-binding properties. Wouldn't it make more sense to compare the cytotoxicity using nucleated cells? *
We agree with the reviewer on the need for standardization, and do compare cytotoxicity using nucleated cells (HeLa). Our first level of standardization is the use of hemolytic units instead of toxin mass. This normalizes toxin activity to the ability to kill human red blood cells, which are widely accepted as having minimal membrane repair mechanisms. This gives us a baseline activity, and allows us to control for toxin impurities/differences between toxin preps/toxins. We prefer cytotoxicity over membrane binding for our baseline because it is a functional assay.
After this first level of standardization, we compare the cytotoxicity in HeLa cells. This is one reason why the majority of our assays are performed in HeLa cells—we know how they behave at different toxin doses in our hands, the cells are easy to use, and we can standardize assays in the lab. We included HeLa cells as a control in Fig 5 to show the standardization requested by the reviewer. We split Fig 1 up differently to better convey the results.*
- The authors use "sublytic" concentrations of aerolysin (64HU) throughout most of the paper, but according to Figure S1C, 50% cells died at that concentration after 1hr, suggesting that when the cells were investigated over a shorter period of time, they were already dying - it's almost like the cells had life support turned off, but still being investigated as though they survived aerolysin treatment. This needs to be clarified or reassessed. *
We agree with the reviewer that we did not track cell survival beyond 45 min in our live cell imaging assays. We labeled cells as ‘surviving >45 min’ to acknowledge the fact that these cells could have died at 46, 47, 60, or 600 min after the experiment ended. We focused on time points earlier than 45 min because proximal membrane repair mechanisms are expected to have occurred in that time, and had time to complete. We have updated the manuscript on lines 214-215.
We next considered the reviewer’s excellent point that the cells alive at 30-40 min could be executing a cell death program. If this were the case, then based on our FACS data (Fig S1C), we would predict ~50% of total cells would be dead by 1 h. From Fig 3A, ~35% of the cells died in the first 45 min. From the remaining 65%, we would predict another 15% dying from this programmed cell death pathway, which would be 15/65 = ~25% of the surviving cells. We did not notice 1/4 of the surviving cells behaving distinctly. For example, the large error bars in 3H is due to a range of cell behaviors that we could not easily subgroup. For individual cells (shown in Figs 6 and 7), there is similarly no clear demarcation of 1/4 of the cells. While we see a gap with pro-aerolysin, that is ~1/3 of the cells (not the expected 1/4), and it is not repeated with aerolysin. While we can’t rule out a cell death program contributing to the top or bottom 1/4 of our results, removing the top or bottom 25% of data points would not alter our major conclusions from the live cell imaging. If a programmed cell death pathway that occurs in the 30-90 min range is identified for aerolysin, it would be interesting to see how that pathway changes repair kinetics. However, that would require identification of the death pathway.
*
- What effect does the addition of 150mM KCl have on the plasma membrane, trafficking/repair - wouldn't the plasma membrane be depolarised? There were a number of papers by John Cidlowski in mid 2000s, where his team explored the effect of potassium supplementation on apoptosis - this may be worth exploring. *
We thank the reviewer for suggesting these interesting papers. We have explored these papers, and our understanding of them is as follows. Franco et al 2008 PMID: 18940791 shows that ferroptosis is independent of high extracellular K+. This contrasts with Fas-dependent apoptosis, which is suppressed by high extracellular K+. This is consistent with the Cidlowski group’s other work (eg Ajiro et al 2008 PMID: 18294629) and Cohen’s group (eg Cain et al 2001 PMID: 11553634) showing that apoptotic DNA degradation performs better at low K+, and extracellular K+ interferes with apoptosis. Similarly, other papers have shown that NLRP3-activated pyroptosis can be blocked by addition of extracellular K+. Depletion of intracellular K+ inhibits endocytosis and other vesicle trafficking pathways.
While these are good papers, they do not directly relate to our K+ findings, which is that blocking K+ efflux via elevated extracellular K+ levels has no impact on aerolysin-mediated killing. Therefore, to stay focused on the repair pathways, we opted not to include these papers to avoid distracting the reader from our key points. *
- Figure 3 and accompanied text: it would be more informative to show all the data rather than breaking it down to 45 min. In my view, *
We have added histograms to show when individual cells died during the assay as supplemental Fig S3E. We used the three bins for the exact reason articulated by the reviewer—we wanted to consider cells that died fast vs slow differently. However, in order to interpret the data, a cutoff of 5 min was chosen as optimal. While we agree with the reviewer that the 5 min death could be dismissed, we presented the data to avoid questions about why we omitted those data.*
- I am curious whether EGTA diffuses into the cytosol through aerolysin pores. If so, then unlike BAPTA-am it would affect Ca inside and outside the cell. *
We agree with the reviewer this is an interesting question. While EGTA might diffuse into the cytosol, its binding properties suggest it would be unsuitable to block cytoplasmic Ca2+ transients (see Nakamura 2019 PMID: 31632263). BAPTA binds to Ca2+ ~40x faster than EGTA, which enables it to capture Ca2+ prior to Ca2+-binding proteins. In contrast, EGTA is thought to be too slow to sequester intracellular Ca2+ before Ca2+-binding proteins. While EGTA might perturb Ca2+ close (
*Are the authors confident that in the absence of extracellular calcium (EGTA treatment), aerolysin formed the pores at all? Have they looked, for example, at intracellular Na/K, or have any other evidence of membrane disruption? *
Prior structural studies suggest that Ca2+ is not required for aerolysin pore formation. For example, Iacovache et al (2011) PMC3136475 induce oligomerization with low salt and pH 2+. Cryo-EM from the same group (Iacovache et al 2016 PMID: 27405240), showed pore formation under similar conditions.
In Fig S3, aerolysin kills in the presence of EGTA at higher concentrations, suggesting that it can form pores when EGTA is present. Also, in Fig 2D, we used Tyrode’s buffer, which was made without Ca2+ or EGTA. We added the indicated amounts of Ca2+ in, and observed a reduction in lysis at low [Ca2+]. This argues against EGTA interfering with toxin oligomerization/pore formation because EGTA was not present, and the toxin still failed to kill.
We have updated the manuscript (lines 203-205) to emphasize this point.*
- Figure 6 (and some other): I find the designation of statistical significance (a-f) quite confusing, as it is unclear which comparisons are statistically different. Looking at Figure S5, there was no difference between the effect of Annexin depletion on the toxicity of the three lysins. *
Samples sharing the same letter are NOT statistically significant. This is done to avoid a mess of stars and bars with multiple comparisons. This has now been explained in lines 981-985.
For Fig 6/ Fig S5 (now S6), there was a statistically significant difference in LC50 between control siRNA and Annexin knockdowns for SLO. We agree that visually the dose-response curve in Fig S6B looks similar. However, we note that the x-axis is a log2 scale, and the control line is distinct over the 250-1000 region. When we calculate the LC50, these differences give different LC50 values. Over multiple reps, these differences were consistent enough to be statistically different.
Significance
*The paper attempts to address an interesting question of aerolysin pore repair, and it is interesting from the perspective of a potential difference between various pore-forming proteins. *
We agree with the reviewer and thank the reviewer for this assessment.*
The study will be potentially interesting to a broad audience of biochemists/cell biologists and microbiologists working in the field of pore-forming proteins/virulence factors. *
We agree with the reviewer and thank the reviewer for this assessment.
Reviewer 3
*Major comments
In the first instance, the authors use a method of assaying the specific lytic activity of aerolysin in comparison to a number of different CDCs. Whilst it is acknowledged that these methods have been published in peer-review papers previously (e.g. Ray et al., Toxins, 2018), it would be great to have more information of how the specific activity is derived. Currently there is a convoluted method that makes a number of assumptions such as, but not limited to, 1) the number of dead cells measured in the FACS experiments is proportional to the activity of the different classes of PFPs however the authors do not show how they account for PFPs leading to loss of cells into debris which would involve a total cell count and *
We thank the reviewer for raising these concerns. We tested these assumptions in our previous papers. We compared the FACS assays to other assays that measure total cells (i.e. MTT assay), and found that the FACS assay corresponds with the MTT findings. These findings were published in Keyel et al 2011 PMID: 21693578 and Ray et al 2018.
Loss of countable events to debris is detected in our assay as saturation of cell death at a number under 100%. Since we perform dose-response curves, we can determine when the killing saturates. This is why loss of countable events does not change our ability to accurately calculate LC50.
2) how the inflection or linear point is identified on individual experiments (e.g. Supp. Fig. 1B, 2A, 2B, 3A, 3B to name a few) and how reliable these points are (e.g showing the data points with model sigmoidal (?) curve and corresponding R values).
This had been calculated manually in the prior version of the manuscript. To address the reviewer’s concern and to improve data quality, we reanalyzed all of our data by fitting our dose-response curves to logistic models, and determining the LC50 using that model. An in-depth explanation of our approach was just published in Haram et al PMID: 36373947, which we now cite (line 821). *
Furthermore, the batch-to-batch variability of protein samples presented in table 1 may be an issue where inactive but folded protein can affect the formation of homo-oligomer pores so more effort to reduce the effects of batch variation would be integral to the foundation of this paper. Given that aerolysin has a very different action on cells then this new characterisation should be provided regardless of what has been previously published by the authors on the activity of CDCs on the cells.*
We agree with the reviewer that batch-to-batch variability is a key concern for pore-forming toxins. To address the concern of batch-to-batch variability and toxin purity, we have added Supplemental Fig S10. In Fig S10C, D, we plot the LC50 against specific activity of each toxin prep when used against control cells. We found a statistical difference in LC50 between two of our toxin preps, but not between any of the others. Notably, there was no association between increasing specific activity and LC50.
Furthermore, we tested the impact of impurities on our toxin prep. While we purify most toxins only using His-beads (obtaining ~40% purity) (Fig S10B), we purified two toxin preps to higher purity (>90%) (Fig S10A). We did not observe differences in LC50 between these toxin preps. The specific activity for these toxins did not increase. We interpret that finding to indicate the gain in specific activity for purity was offset by the loss of specific activity due to prolonged toxin purification.*
- Can the authors provide the raw data for the total FACS observations (scatterplot for all events) and show that there is no significant loss of cells? Or at least there is accountability of the cells? *
Our stop conditions were to collect at least 10,000 gated events instead of running for a set period of time/set volume to determine cell density. We provide example scatterplots in Fig S1A.
*
- Can the authors provide more information about how the linear regression on Supp. Fig. 1B and other experiments showing the model sigmoidal curve performed such that this work is more reproducible? *
We agree with the reviewer that using logistic modeling would strengthen the work. To address this concern, we reanalyzed all of our data and switched to logistic modeling. This improved reproducibility for many figures. Changes that add or remove statistical significance to results include Fig 4A, loss of significance between Ca2+/DMSO and BAPTA/DMSO, Fig 6C, loss of significance for siRNA knockdown of A6 vs scrambled for ILY, and Fig 8A/B, gain of statistical significance for GFP-Dysf protecting SLO. We have updated our results accordingly.*
The SEMs of some data points (specific lysis LC50 scatterplots, for e.g. Fig. 2C, 4A, 4C, 8A and fMAX plots, for e.g. Fig. 3B) may not be apparently representative of the skew (e.g. and individual values (including outliers). A clarification of the statistical analysis behind the results may benefit in a clearer understanding of how the SEMs were calculated and presented in the main figures. Also, further elaboration on the meaning of the lettering in the scatterplots (denoted as a, b, c etc.) across the main figures may help improve the interpretation of the data. *
The SEMs were calculated by Graphpad and graphs also generated by Graphpad. To address the reviewer concern, we have switched all places where we plotted individual data points to median with no error bars. This will enable the reader to judge skew, outliers, etc without reliance on error bars.
We have now further elaborated on the lettering in the scatterplots. Samples sharing the same letter are NOT statistically significant. This is done to avoid a mess of stars and bars with multiple comparisons. This has now been explained in lines 981-985.*
Secondly, the authors present interesting results on the significance of Ca2+ on aerolysin's mechanism behind lytic activity and introduces dysfurlin-mediated patch repair as the primary cellular resistance mechanism against aerolysin mediated lysis. Results from Figure 2-4, indicate that extracellular Ca2+ plays a role in aerolysin's function and cell lysis (aerolysin triggers influx of extracellular Ca2+). However, the results presented in figure 8 suggest an impairment of dysferlin translocation from the cytosol to the plasma membrane upon removal of extracellular Ca2+. If this were the case, wouldn't dysferlin impairment sensitise cells to aerolysin? Thus, in these sets of experiments it seems that Ca2+ is a confounding factor.*
We agree that Ca2+ is a confounding factor, which is one reason we aimed to define better membrane repair mechanisms in response to different pore-forming toxins. Our interpretation is that Ca2+ triggers a death pathway that overcomes repair, and that aerolysin toxicity is due to the activation of this pathway. In this case, the impairment of Ca2+-dependent pathways does not reduce survival because the extent of damage is reduced/not present. Figuring out this death pathway is beyond the scope of the present manuscript, but a one future direction in which we are interested. This would also account for differences observed in different cell lines.*
- Can the authors further elaborate on how the function of dysferlin in protecting cells against aerolysin contrasts to how aerolysin kills cells? *
We have added the requested discussion to our manuscript, lines 519-525.
*Finally, it is also interesting to see that cells deploy different resistance mechanisms between different families of pores. In saying that, the usage of CDCs seems to be inconsistent between each set of results. For example, intermedilysin (ILY) was used in the siRNA knockdown experiments but not in others such as Ca2+ influx assays, while PFO was only used for the initial set of results. A comment on this would benefit in understanding the rationale for selecting certain CDCs for each set of experiments. *
We thank the reviewer for raising this point. We used SLO as the primary CDC in all the experiments because it is the CDC we have best characterized and have extensively published on. We included PFO in initial experiments to give readers a better idea of how multiple CDCs compare to aerolysin in target cells. However, since we’ve previously published on PFO, including it for later experiments would have increased cost and time of experiments without providing new knowledge.
We used ILY because it binds to the GPI-anchored protein human CD59, so its binding determinant is more similar to aerolysin, which binds GPI-anchored proteins. We included it where practical to determine the extent to which targeting may change repair responses. Since ILY does not bind to murine cells, it was omitted from experiments using murine cells.
We have added the rationale to the manuscript on lines 138-140.*
Minor comments
Results
(Nucleated cells are more sensitive to aerolysin and CDCs)
- A statement of the EC50 values of aerolysin and CDCs from the haemolytic assays would be beneficial to compare activities between the two pores. *
The hemolytic activity is defined as the EC50 for the toxin in human red blood cells. The specific activity enables comparison of toxin activity, which is reported in Table 1. We have now added Supplementary Fig S10 which further plots the aerolysin and SLO specific activities against LC50 so that the reader can better assess batch-to-batch variability. In this study, we did not use enough batches of the other toxins to make this analysis useful for them.
*
- Figure 1A: As stated in the introduction, pro-aerolysin exists as a precursor that is functionally inactive unless activated by trypsin, furin or potentially other proteases. It would benefit the reader if an explicit statement were made about this activity and how it may come about in HeLa and 3T3 cells. Why is pro-aerolysin not shown in the Casp 1/11-/- BMDM cells? *
The cell surface furin activity that activates aerolysin is not well-characterized across different cell types. We have revised the manuscript (line 76) to indicate these activities are present on the cell membrane.
We omitted pro-aerolysin from the Casp1/11-/- BMDM because we performed those experiments earlier in the study before we started including pro-aerolysin. Based on the other results, we judged that the time and resource costs of adding pro-aerolysin in this system outweighed the gain to the story.
*
- Figure 1C: It was stated that "Casp 1/11 -/- Mo were ~100 fold more sensitive to pro-aerolysin and aerolysin compared to PFO and SLO" but did not show the activity for pro-aerolysin in these cells. *
We thank the reviewer for catching this typo, and have corrected this statement (line 172).
*
- Supp fig 1E: Shouldn't 24 hr incubation of aerolysin to HeLa cells result in 100% specific lysis? *
We agree with the reviewer that these results were surprising. At 24 h, it is possible that cell growth interfered with the assay. The assay well has a finite surface area. If control cells are confluent near the start of the assay, but toxin-treated cells are not due to cell death by aerolysin, the growth rates between control and experimental wells may not be equal. Since our focus is the proximal membrane repair events, and not the late signaling events, pursuing this further is beyond the scope of the current manuscript.
*
(Delayed calcium flux kills aerolysin-challenged cells)
- What is the intracellular concentration of K+ normally in cells? Similarly, what is the intracellular concentration of Ca2+? *
Intracellular K+ is ~140 mM (see Ajiro et al 2008 PMID: 18294629), while cytosolic Ca2+ is ~100 nM at rest.
*
- Figure 2C: Based on the description in the methods and results, both buffers are supplemented with 2 mM Ca2+ but one buffer (RPMI) shows more killing with SLO and ILY. Does this mean that both buffers contain 2 mM CaCl2? If so, what are the other potential reasons why one buffer enabled greater potency in CDCs? *
RPMI has 0.4 mM Ca2+ prior to Ca2+ supplementation. However, the 2.4 mM Ca2+ did not provide improved protection compared to RPMI alone (See Fig 2 in Ray et al 2018).
We suspect the various amino acids added to RPMI promote membrane integrity and account for the difference from Tyrode’s buffer. Glycine has previously been implicated in promoting membrane repair, but at higher concentrations than it is present in RPMI (0.133 mM in RPMI vs the mM concentrations used to protect cells). If other amino acids also protect, and/or why they protect is beyond the scope of the present work.
*
- Figure 3H: The data for aerolysin (WT) would greatly benefit for comparison to the inactive mutant (and indicate the sustained Ca2+ increase). *
We have added this comparison, and updated the figure legend, line 1015.
*
- Supplementary Video V1: The addition of Triton X-100 permeabilises cells; however, this wasn't evident in (A).
- Video V2: Similar to previous comment on Supplementary Video V1 (for B). *
In V1A, the video was cut short to fit the play time with other videos. From addition, the triton takes a few minutes to diffuse to the cells and permeabilize them. In V2B, the cells do become permeabilized as shown by loss of the Ca dye. The cells are out of focus, which is why the nucleus TO-PRO is not detected.*
(Calcium influx does not activate MEK-dependent repair)
- Figure 4A: Effective ionic concentration inside and outside cell is increased (if intracellular Ca2+ becomes chelated); therefore, Ca2+ may enter the cell by passive diffusion or transport by other intrinsic Ca2+ channels. *
There is already a very steep concentration gradient for Ca2+. The cytosolic Ca2+ is ~0.1 uM, compared with growth medium at 400 uM or assay buffer at 2400 uM. Chelation of the intracellular Ca2+ is not expected to increase Ca2+ import from outside the cell.*
(Caveolar endocytosis does not protect cells from aerolysin)
- Figure 5C: What is the purpose of using HeLa cells as a control? *
We included HeLa cells to demonstrate the toxin was active and to rule out batch-to-batch variability as one interpretation of the reduced killing of differentiated 3T3-L1 cells.
*
- "..with Alexa Fluor 647 conjugated pro-aerolysin K244C" - this should be introduced earlier as it was initially mentioned in Supp. Figure 3C. *
We have now introduced this earlier at line 190, instead of 300
*
- Murine fibroblasts were used earlier (Figure 1). Following from this result (where the WT can be used as a positive control), can MEFs be used instead of adipocytes to see whether caveolar endocytosis plays any role in cellular resistance? *
The 3T3-L1 cells are murine fibroblasts prior to differentiation. Since they can also be differentiated into adipocytes, we used them instead of MEFs. The other reasons we used them include the availability of Cavin knockout cells, and the extensive caveolae present in adipocytes. We included analysis of 3T3-L1 prior to differentiation them in Fig 5B.
*
- Further comment on the increased resistance of K5 knockout would benefit on the mechanism of aerolysin-mediated cytolysis. *
We agree further characterization of this line would be interesting in the future. At the present, however, any further comment would be speculative on our part. Since the resistance was not replicated in the second CRISPR line, we suspect it is either an unexpected mutation(s) in the cell line that arose during routine cell culture, or off-target effect(s) from the CRISPR used to generate the line.
*
(Annexins minimally resist aerolysin)
- Supplementary video V3 - it seems that annexin A6 is recruited to the membrane, to a greater extent (and also quicker) than SLO. This suggests that annexin recruitment is a cellular response against aerolysin challenge. *
We agree with the reviewer that annexins are recruited to the membrane during repair. However, individual knockdown did not enhance death. This is one reason we believe functional studies (i.e. cytotoxicity) are necessary when studying the cell biology of repair events. Recruitment of the protein, and it promoting repair may be two different things.
In V3, three of the SLO-challenged cells have translocated by the time focus is restored. In contrast, the first aerolysin cells translocate ~10 min. One complicating factor is that A6 cycles back off the membrane with the SLO challenge.
*
o SLO also shows A6 recruitment (arrows pointed). However, supplementary figure 6B does not clearly illustrate this. *
Given the 45 min time scale, the rapid initial membrane enrichment is hard to see on the graph.
*
- As annexin A1 is sensitive to calcium, further comment on the significance of intracellular/extracellular calcium in annexin A1 recruitment and aerolysin challenge would explain observations in Figure 4A. *
We have updated the manuscript, line 242 to include annexins and dysferlin as Ca2+-binding proteins in our discussion of intracellular calcium.*
(Patch repair protects cells from aerolysin)
- Supplementary video V4 - the intensity decreases for the inactive mutant; is this due to lysis? *
We included TO-PRO in the experiment to rule out lysis. Since the cells remain in focus, we interpret the lack of TO-PRO to indicate no cellular lysis.
*- The next paragraph sounds like a contradiction: "GFP-dysferlin localized to the plasma membrane and vesicles independently of extracellular Ca2+ (Fig 8C D, Video V5)
o Followed by "To study the Ca2+ dependency of dysferlin, we removed extracellular Ca2+ with 2 mM EGTA and challenged with sublytic toxin doses...found less depletion of dysferlin from cytosol". *
We thank the reviewer for pointing out our unclear language. In the second section, we intended to refer to dysferlin positive vesicles. We have rephrased the manuscript (lines 388-395) to clarify that we are focused on Ca2+-dependence of vesicle fusion, not steady-state.*
(Methods)
- Table 1: The values presented in the methods section are, overall, confusing and require clarification. *
We have added Fig S10, and discussion of toxin activity and purity in the methods (lines 634-641) to provide further clarity on toxin activity.
*
o 10-fold difference in SLO and PFO WT - do the authors think this might change the interpretation between different figures? *
We do not. The reason is that we changed the membrane affinity between SLO and PFO (Ray 2018), and this switches the properties of the respective toxins without changing their yields.
*
o Understood how the haemolytic activity was calculated (referred to work in 2012), but how was the haemolytic unit originally derived? *
It was derived as a measure of activity for toxins by determining the EC50 in RBCs for a given toxin. Since species type of RBC and other factors can change the reported activity, we have normalized to using human red blood cells. This lets us assay human-specific toxins like ILY along with other toxins.
*
o How were these values (from table 1) derived to toxin concentrations used for killing nucleated cells? *
Full discussion of our assay was recently published in Haram et al 2022 PMID: 36373947. For the cytotoxicity assays, we use the hemolytic activity. Suppose from Table 1, the toxin stock is 1.5 x10^5 HU/mL. Then to prepare a 2x working toxin stock, we dilute the toxin to 4 x10^3 HU/mL (this is a 1 in 37.5 dilution). To get the range of concentrations used in the dose response curve, we perform a 2-fold serial dilution. Finally we mix equal volumes of toxin and cells, giving us the final 1x toxin activity (2 x10^3 HU/mL for the highest concentration in this example).
*
o Therefore, an EC50 haemolytic curve showing the activities for all toxins would greatly facilitate in understanding the derivation of values for table 1.*
The hemolytic unit already incorporates the EC50 hemolytic curve. 1 HU is the EC50 of the toxin in the human RBCs.
*
- Flow cytometry assay: What is meant by gating out the debris? And would debris also contribute to the count in dead cells? *
We illustrate our gating strategy in Fig S1. The debris falls in the front left corner of the plot, and includes electronic noise, non-cellular debris and cellular fragments. Since one cell could give rise to multiple pieces of debris, we exclude the debris from analysis.
*
o What was added as the high PI control? *
In Fig S1A, the high dose of toxin was used for maximal killing. In our cell populations, there is a low level (2-5%) of dead cells that serve as a control for PI staining. In the past, we’ve used 0.01% triton to validate permeabilization of the cells. We have also compared PI uptake with MTT assays (Keyel et al 2011, Ray et al 2018) to confirm that the PIhigh cells are dead.
*Elaborating reviewer #2's comment 7 regarding the addition of EDTA : with respect to measuring the binding if fluorescently labelled aerolysin, how can the authors differentiate between full functional pores versus prepores/incomplete pores? *
This requires electron microscopy, which is the beyond the scope of our current study. However, prior work and Fig 2D show that aerolysin forms pores without the need for Ca2+ (see next point).
How else can the authors validate whether aerolysin remains functional in the presence of EDTA?
Prior structural studies suggest that Ca2+ is not required for aerolysin pore formation. For example, Iacovache et al (2011) PMC3136475 induce oligomerization with low salt and pH 2+. Cryo-EM from the same group (Iacovache et al 2016 PMID: 27405240), showed pore formation under similar conditions.
In Fig S3, aerolysin kills in the presence of EGTA at higher concentrations, suggesting that it can form pores when EGTA is present. Also, in Fig 2D, we used Tyrode’s buffer, which was made without Ca2+ or EGTA. We added the indicated amounts of Ca2+ in, and observed a reduction in lysis at low [Ca2+]. This argues against EGTA interfering with toxin oligomerization/pore formation because EGTA was not present, and the toxin still failed to kill.
We have updated the manuscript (lines 203-205) to emphasize this point.
Significance
*While the work has investigated in-depth cellular resistance mechanisms, the significance and benefits of this study are unclear. For example, the authors have used different human cell lines to dissect how these cells are affected by different pores but have not stated the significance and potential benefit of studying these cell lines. Further elaboration in this aspect may increase the relevance of the study, to an audience who is interested in the field of infection and disease. *
We have updated our significance to better convey our advance, which is explained on lines 99-102, 128, 519-525. We also added benefits of testing the cell lines chosen on lines 167-168, and 277-278. We plan to add muscle cells to address the dysferlin points, which has relevance to necrotizing soft-tissue infections.
Description of analyses that authors prefer not to carry out
Not applicable
