- Oct 2022
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Read on Arcadia Science
Oh no! I thought the flag meant post & accidentally reported your thoughtful feedback to moderators instead of replying. Hopefully they figure it out (no obvious way to contact them or "unflag"
Comment Figure 2C → please include indication of statistical significance Figure 3C → please include indication **of statistical significance Figure 6A → please include indication of statistical significance Figure 8B → please include indication of statistical significance Figure S1B → please include indication of statistical significance Figure S3B → please include indication of statistical significance
Response Easy to add
Comment For your overexpression experiments, do the overexpressed proteins have a tag? It would be helpful to have Western blot data showing that the particular proteins are actually being overexpressed. I think the phenotypes that you observe are very compelling so I don’t doubt the conclusions. Western blot data would just provide some additional confirmation that you are actually achieving overexpression of UppS, MraY, and BcrC.
Response The proteins are untagged. For the UppS and BcrC the cell shortening occurs with addition of inducer, , so strong indication expression is occurring. A western would provide information about degree of overexpression, but we don’t think is necessary to support conclusion drawn. Do you think there is an alternative possibility that needs to be excluded? We note that in another preprint (https://www.biorxiv.org/content/10.1101/2022.02.03.479048v1) the authors delete the native uppS in their inducible Phy-uppS strain (Fig S4) and at 100 uM IPTG (10X less than what we used in experiment) the cells have wt growth on LB plates, so we at least know the Phy-uppS is functional and made (or they would die!). We are introducing the uppS deletion into our strain to see if we can identify a concentration of IPTG that doesn’t affect cell growth but still induces shortening.
For MraY, the result is negative, so you are spot on – it is impossible to tell if due to lack of overexpression from data shown. We only know the strain is correctly made from sequencing. We will investigate if there is an antibody or functional fusion available. The reason we were not sure was worth doing is because the MraY reaction is reversible (15131133). This means that without a phenotype, there is no simple way to know the reaction can even be pushed forward even if the overexpression is confirmed (more negative data). We actually overexpressed some other proteins that act downstream (MraY, MurJ, AmJ) and they were also negative for shortening. Probably we should remove the negative data or reword to make the caveats of the negative result clear.
Question Based on your data, there are definitely differences in gene expression when you compare cells grown in media with and without magnesium. Because the majority in cell length increase occurs in such a short time though (the first 10min), I was wondering if you think that some or most of it is not due to gene expression?
Response The shortening is even faster than 10 min (not only statistically significant, but also obvious qualitatively if we mount immediately after adding Mg2+ ). We did not include the first timepoint because original purpose was to check everything was ready with microscope – did not expect shortening so fast! We can definitely add that data in. When we saw, we tried to capture the transition on pads, but going from culture to pad seems to stress the cells too much in the small window where the cool stuff happens. Since growth rate doesn’t appear to be a big factor in those initial divisions, we might be able to grow at lower temp and shift to pads for adjustment period before adding Mg2+. Did not play with it much due to lack of resources atm, but a flowcell setup would probably be best. In short, we think rapid divisions right after transition do not require transcription or translation. It really “smells” more like a biophysical thing.
Question Do you have any hypotheses what is most likely to be affected by magnesium? Do you think if the membrane may be affected?
Response We have a lot of hypotheses, but all speculative. There could be an extracytoplasmic enzyme involved in envelope synthesis is sensitive to Mg2+ availability, and that at lower concentrations, its activity is affected. There is some old literature with membrane preps that suggests PG synthesis requires higher Mg2+ than teichoic acid synthesis. If Und-P is limiting, higher Mg2+ may shift make the pool more available to make the septum. Tingfeng initially hypothesized there might be a receptor/signal mechanism but has not been able to identify one. Und-P seems to be important, but “availability” is not just pool, but how fast (and where!) the flipping across the membrane occurs. If Und-PP needs to be dephosphorylated to Und-P before being flipped back to cytoplasmic side, anything that effects the PP/Pi equilibrium would be predicted to affect the reaction rate, with lower Pi (in periplasm or pseudoperiplasm in case of G+) favoring the dephosphorylation. Cell wall associated Mg2+ could shift equilibrium to be more favorable for a Und-PP phosphatase more closely associated with the divisome. I could go all day… In short, we don’t know enough!
Question Why do you think less magnesium activates this program of less division and more elongation? Additionally why is abundant magnesium activating a program of increased cell division and less elongation? Do you think there is some evolutionary advantage, especially considering how important magnesium is for ATP production?
Response In the window we looked at, the elongation rate is constant (not less or more) and only the division frequency changes. Some bacteria (like Caulobacter and to lesser extent E. coli) clearly elongate and divide simultaneously, so model there is some competition for substrate (like Lipid II) makes sense. Septators like Bacillus seem to delineate the two processes more, though we have found conditions where even Bacillus invaginates during division, so it’s not absolute. Like eukaryotic cells, bacterial undoubtedly have mechanisms not only commit to a round of DNA replication when there is some signal that resources are sufficient. Clearly with some bacteria, this is not the case with cell division. The alternative would be that every cell cycle there is an opportunity to divide if some threshold of something(s) is reached. There is a hypothesis from Mtb literature that it may be GTP, but it’s not at all clear that is sufficient. In yeast, size at cell division is affected by perturbing 1-C pool.
Question Related to this previous question, I also wonder if this magnesium-dependent phenotype would extend to other unicellular organisms, may be protists or algae? That would be a really exciting direction to explore!
Response It’s a great question – lots to do! We didn’t even look at another Gram-positive, but we plan to. It’s trickier to limit Mg2+ in Gram-negatives (see 27471053 – we tried Bsub homolog for those wondering – it’s not responsible for phenotype we see).
Question Regarding the zinc and manganese experiments, why do you think they lead to additional phenotypes compared to magnesium? Do you have any hypotheses?
Response We have hypotheses, but if my (Jen’s @rosh_ba) twitter engagement is any indication, way too speculative for public consumption at present. Need acquire preliminary data/write grant.
Question Regarding your results that Lipid I availability may be a major a problem for the cell division in the absence of magnesium, do you think that is due to effects magnesium has on the enzymes directly, or do you think magnesium affects the substrate availability/conformation by coordinating the phosphate groups? Or something else, may be membrane conformation?
Response Several proteins involved in envelope synthesis (like UppS) are Mg2+ dependent enzymes. But at least for intracellular players, levels of Mg2+ should be more than high enough to support enzyme activity (0.8 – 3.0 mM is Bsub range I recall off top of head). Could have impact extracytoplasmically by lowering pool sponged into the cell wall, but intuition (for what that is worth) is that it is not the coordination of an enzyme with a metal that is impacted rather the equilibrium with other ions like Pi and H+ and their impact on net ATP synthesis. Lots to think about and do, and no simple answers. When Tingfeng started project idea was to find mechanism – didn’t realize we were asking “How does the cell work?” Turned out to be a bit much for a dissertation project :)
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General comments:
This study carefully delineates the role of magnesium in cell division versus cell elongation. The results are really important specifically for rod-shaped bacteria and also an important contribution to the broader field of understanding cell shape. Specifically, I love that they are distinguishing between labile and non-labile intracellular magnesium pools, as well as extracellular magnesium! These three pools are really challenging to separate but I commend them on engaging with this topic and using it to provide alternative explanations for their observations!
A major contribution to prior findings on the effects of magnesium is the author’s ability to visualize the number of septa in the elongating cells in the absence of magnesium. This is novel information and I think the field will benefit from the microscopy data shown here.
I completely agree with the authors that we need to be more careful when using rich media such as LB. It is particularly sad that we may be missing really interesting biology because of that! It’s worth moving away from such media or at least being more careful about batch to batch variability. Batch to batch variability is not as well appreciated in microbiology as it is for growing other cell types (for example, mammalian cells and insect cells).
For me, the most exciting finding was that a large part of the cell length changes within the first 10min after adding magnesium. The authors do speculate in the discussion that this is likely happening because of biophysical or enzymatic effects, and I hope they explore this further in the future!
I love how the paper reads like a novel! Congratulations on a very well-written paper!
Kudos to the authors for providing many alternative explanations for their results. It demonstrates critical thinking and an open-mind to finding the truth.
Specific comments:
Figure 2C → please include indication of statistical significance
Figure 3C → please include indication of statistical significance
Figure 6A → please include indication of statistical significance
Figure 8B → please include indication of statistical significance
Figure S1B → please include indication of statistical significance
Figure S3B → please include indication of statistical significance
For your overexpression experiments, do the overexpressed proteins have a tag? It would be helpful to have Western blot data showing that the particular proteins are actually being overexpressed. I think the phenotypes that you observe are very compelling so I don’t doubt the conclusions. Western blot data would just provide some additional confirmation that you are actually achieving overexpression of UppS, MraY, and BcrC.
Questions:
Based on your data, there are definitely differences in gene expression when you compare cells grown in media with and without magnesium. Because the majority in cell length increase occurs in such a short time though (the first 10min), I was wondering if you think that some or most of it is not due to gene expression? Do you have any hypotheses what is most likely to be affected by magnesium? Do you think if the membrane may be affected?
Why do you think less magnesium activates this program of less division and more elongation? Additionally why is abundant magnesium activating a program of increased cell division and less elongation? Do you think there is some evolutionary advantage, especially considering how important magnesium is for ATP production?
Related to this previous question, I also wonder if this magnesium-dependent phenotype would extend to other unicellular organisms, may be protists or algae? That would be a really exciting direction to explore!
Regarding the zinc and manganese experiments, why do you think they lead to additional phenotypes compared to magnesium? Do you have any hypotheses?
Regarding your results that Lipid I availability may be a major a problem for the cell division in the absence of magnesium, do you think that is due to effects magnesium has on the enzymes directly, or do you think magnesium affects the substrate availability/conformation by coordinating the phosphate groups? Or something else, may be membrane conformation?
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Reply to the reviewers
Reviewer #2 (Evidence, reproducibility and clarity (Required)):
This paper provides a detailed step by step protocol of the CUT&RUN technique, which enables high-resolution chromatin mapping and probing, adapted to the malaria parasite Plasmodium falciparum. In particular, Kafsack and colleagues apply the CUT&RUN protocol to infected red blood cells from in-vitro culture and obtain very good quality genome-wide profiles of two histone modifications, H3K4me3 and H3K9me3. The results are congruent with previous ChIP-seq data with a substantial improvement in terms of coverage and chip-to-input noise. The protocol is very detailed and the figures are great.
Major comments: 1. Authors successfully adapted the CUT&RUN protocol in P. falciparum. First, the binding profiles obtained by CUT&RUN for H3K4me3 and H3K9me3 are very similar to those reported by previous ChIP-seq studies. Secondly, by down-sampling 4X and 16X the test samples, authors demonstrate that 1M PE reads of sequencing depth would be enough to obtain accurate profiling of these histone modifications.
Despite this data is convincing, only one region in chr. 8 is shown as an example in figures 2, 3 and 4.
Different regions should be included, at least as supplementary figures, to reinforce their conclusions.
__Response: __We chose that locus on chromosome 8 to provide a gene-level resolution view at a locus encompassing genes in both eu- and heterochromatin states. We have now included Supplementary Figure 1, which shows these tracks for full length chromosomes 4 and 7. Additionally, genome-wide enrichment tracks for all data sets in this study are available for download at NCBI Gene Expression Omnibus under accession number GSE210062.
Related to this, there is evidence of the impact of chromatin structure on ChIP-seq analysis. Specifically, heterochromatin is typically depleted in ChIP input controls because of technical and experimental issues and this can result in a false enrichment of heterochromatic regions in the tested sample. How represented is heterochromatin (i.e. sub-telomeric and telomeric regions) in the test and control samples using the cut&run protocol?
__Response: __The reviewer is correct that chromatin structure may alter accessibility which may bias absolute measurements but since the accessibility biases based to chromatin-structure are identical for both the histone PTM-specific antibody and the isotype control and cancel out in the enrichment score.
How biased is the cut&run sample compare to the ChIP-seq sample?
__Response: __We have included this in Supplementary Figure 1. The H3K4me3 and H3K9me3 enrichment scores are strongly correlated both between CUT&RUN replicates and between CUT&RUN and previously published ChIP-seq results.
In this sense, it would be desirable if authors provide more information about the quality analysis results, for example the chip to input signal ratio and the coverage for heterochromatic (telomeric, centromeric and subtelomeric) regions.
__Response: __We agree that this would be of interest to the reader. For this reason, the full genome-wide enrichment tracks were made available for all datasets in this study. We have added language to draw further attention to this availability.
Additionally, loci typically biased in ChIP-seq samples, i.e. clonally variant gene families in sub-telomeric regions, should be shown as examples.
__Response: __We chose that locus on chromosome 8 to provide a gene-level resolution view at a locus encompassing genes in both eu- and heterochromatin states, including 2 var genes (PF3D7_0808600 and PF3D7_0808700) and two rifin genes (PF3D7_0808800 and PF3D7_0808900). We have now included Supplementary Figure 1, which shows these tracks for full length chromosomes 4 and 7, which also include subtelomeric and non-subtelomeric heterochromatin loci containing these genes. Additionally, genome-wide enrichment tracks for all data sets in this study are available for download at NCBI Gene Expression Omnibus under accession number GSE210062.
- For P. falciparum WGS a PCR-free library preparation is strongly recommended. We wonder if it would be possible to try to integrate this step in their CUT&RUN protocol.
__Response: __Since such biases are sequence dependent, they would impact raw coverage but cancel out in the enrichment plots since the sequence-based biases are identical in both samples. While PCR-free amplification may be desirable for some applications, we feel this is outside the scope of this study to implement these changes.
It would have been desirable to have tried the CUT&RUN protocol on other type of proteins, different to hPTMs which are highly abundant, for example one of the Pf Api-AP2 transcription factors. Assaying the CUT&RUN protocol on a different type of protein shouldn't be cost/time consuming and would provide evidence of the versatility of the approach.
Response: As indicated by the title, this protocol was optimized specifically for profiling of histone modifications. CUT&RUN has been used in other systems to profile genome-wide binding of other proteins but this was not our aim and outside the scope of this study.
- The step by step protocol is very detailed, however there are some parts that need to be better explained:
In the section "Binding cells to Concanavalin A-coated beads": it's not mentioned the harvest time and the stage of the parasites used. In addition, several methods are proposed for iRBCs enrichment, but is not mentioned which method was used and the life stage of the parasites. In this part of the protocol authors state "resuspend cells containing 1-5x107 nuclei to a cell density to 1x107 cells/mL".
According to our calculations, to guarantee this nuclei number it would be necessary to enrich in iRBCs and late stages. Otherwise the red blood cells density should be much larger. Could you please clarify this point?
Response: For this study we enriched for trophozoites using a percoll/sorbitol density gradient, which we have now clarified in step 8. However, whether and which enrichment strategy is employed will vary based on the desired parasite stages and experimental design.
In the section "P. falciparum culturing and synchronization of erythrocytic stages" the authors indicate that the method used for synchronization was double-synchronization with sorbitol treatment to achieve a {plus minus} 6 h synchrony. The details provided appear insufficient to replicate the procedure. E.g. it's not explained how the double step synchronization was performed and for how long the culture was incubated after the synchronization.
The number of parasite cells and the life-stage used is mentioned at the end (in the section of expected outcomes). It would be more useful if this information is specified at the beginning together with the most appropriate procedure to get an iRBC culture well synchronised and enriched in late stages.
Response: The stage, synchrony and growth conditions are determined by the scientific question the experimenter is asking, not by the assay. For this reason, we provide the number of infected erythrocytes and nuclei used in our studies so that other experimenters can aim for similar numbers regardless of the stage and synchrony. For this study we used asexual blood-stages at 36±4 hp.i. We have clarified this in step 11.
- With regards to reproducibility, all experiments were done in replicate (3 Rs) and the statistics appear adequate.
Minor comments: - Abstract. A closing bracket is missing.
Response: Corrected - Step 11: Split each sample into 1mL aliquots at ?
Response: Corrected
- The affinity of proteins A/G to IgG antibodies varies based on host species and IgG subtype (see link). This link does not seem to work
Response: Corrected
- Low bind tubes are mentioned several times. Please clarify whether it refers to low bind protein or low bind DNA. Step 77.
Response: The vendor and catalog number for the low-bind tubes are specified in the Reagents, Materials & Equipment list.
Which was the desired sequencing depth per library? It could be mentioned here. It is mentioned later in "Quantification and statistical analysis" that the initial desired depth was of 40M read pairs, but what was the real depth obtained? from the Figure 4 seems to be less than 17M read pairs per sample.
Response: Thank you for catching that error. The target was 10M read pairs per library but since CUT&RUN is so specific the isotype controls release less DNA and the resulting libraries produces fewer clusters than aimed for leading to slight over sequencing of the remaining samples.
- Step 79. Please clarify/justify why 50 bp paired-end reads were chosen as sequence length. Response: After excluding the telomere repeats 100 bp (50+50) are sufficient for uniquely mapping 98.3% of the nuclear. Paired-end sequencing was chosen over single-end because it provides the actual size of each fragment.
In the section "Quantification and statistical analysis", references to Figure 3 and 4 are inverted or do not correspond with the actual figures 3 and 4.
Response: Corrected
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Figure 2. Among the replicates, sample 2 seems to have higher background, could you comment why? Response: It is inherent in biological replicates that one would have the greatest amount of noise but we unfortunately have no further insight into why Sample 2 had a higher elevated background that Samples 1 and 3. Furthermore, even with this slightly higher background the relative enrichment of signal to noise ratio enrichment peaks are readily identifiable.
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Below some suggestions that may help the authors improve the presentation of their data and conclusions:
The limitations and potential shortcomings of the protocol are mentioned along the text (e.g. the use of different antibodies, different targets, weak interactions..), but could be good if they are included in a different section, preferably at the end.
Response: A “Limitations” section was added.
Also in this section it would be good if they develop further (or at least speculate) on the differences in the protocol or things to consider if other type of proteins are assayed (i.e. TFs).
Response: As mentioned above, we have not applied to CUT&RUN to profile chromatin other than Histone PTMs, as this was not the aim of our study. Since chromatin-bound histones always occur within a nucleosomal context, we are hesitant to make claims to the utility of this specific protocol for profiling DNA-binding proteins with smaller DNA-binding footprints. That said, CUT&RUN has been used to great success in other systems to profile a wide range of chromatin-bound proteins. We have included mention of this at the end of the introduction.
Authors should better comment on the potential impact of chromatin structure and DNA sequence (i.e. AT richness) on the biased representation of heterochromatic regions in the data, the level of background and the peak calling analysis.
Response: For the enrichment scores, sequence and accessibility biases cancel out since they are the same for both the PTM-specific antibody and the isotype controls.
The coverage of critical loci, like those belonging to clonally variant gene families, should be calculated and examples of tracks included as supplemental figures.
Response: Gene Expression Omnibus under accession number GSE210062 as indicated in the Quantification & Statistical Analysis and data availability sections.
Authors claim that the CUT&RUN protocol has exceptionally low background and has been successfully used to profile chromatin interactions from very small numbers of cells. But it is not specified how many. That is, which is the standard in other fields and how it compares with the number of cells used here.
Response: As stated in the note following step 10, we did not optimize the minimum number of parasites required in this study since at the 1e7 iRBC required for each sample correspond as little as 1mL of bloodstage culture 2% parasitemia and 5% hematocrit. The down-sampling analysis in figure 3 suggests that the number of input cells can likely be reduced at least 10-fold.
Information about synchronisation, estimation of iRBCs density and nuclear content appears insufficiently described and has been fragmented in different sections so it is difficult to replicate. For example, within the section "Binding cells to Concanavalin A-coated beads" different alternative protocols for iRBCs synchronisation and enrichment are mentioned but it is not clear whether authors actually perform that step. It could be convenient to describe it and include it in the step-by-step protocol.
Response: The stage, synchrony and growth conditions are determined by the scientific question the experimenter is asking, not by the assay. For this reason, we provide the number of infected erythrocytes and nuclei used in our studies so that other experimenters can aim for similar numbers regardless of the stage and synchrony. For this study we used asexual blood-stages at 36±4 hp.i. We have clarified this in step 11.
Significance (Required) The CUT&RUN is a novel technique to profile chromatin modifications genome-wide that has been successfully adapted to P. falciparum by the authors. This technique overcomes important limitations of the traditional ChIP-seq and provides better quality data. First, fewer cells and lower sequencing depths are required which is fundamental for the analysis of certain parasite life stages. Second, the binding step is carried out in-situ using unfixed and intact cells. This allows to avoid crosslinking, which can interfere with target recognition that results in unspecific background, and also avoids the random fragmentation of the chromatin, that can bias in the analysis.
This work is significant since it represents the first CUT&RUN step by step protocol adapted to P. falciparum. The results are important for researchers from the malaria field and parasitologists in general who could eventually leverage this protocol to other Apicomplexa.
Our expertise is on transcriptional regulation, molecular parasitology, genomics and epigenomics, of malaria parasites. We hope the comments above will help the authors to improve the ms. Congratulations on the work.
Reviewer #3 (Evidence, reproducibility and clarity (Required)): ____ In general the paper is very clear and convincing and I have only minor comments for the authors to address.
Introduction The authors state that 'crosslinking presents another challenge as it can interfere with antibody recognition.' Would it be possible to provide a reference to strengthen this statement? Response: Additional references (Baranello et al, O’Neill et al) were added.
In the third paragraph the authors mention that CUT&RUN can be used to profile chromatin interactions from very small numbers of cells. This argument would be strengthened by adding references or examples from mammalian systems, and the authors might mention that the slight modification CUT&TAG has been employed for single cell sequencing. https://doi.org/10.1038/s41587-021-00865-z.
Response: The reference was added.
Figure 2 A label of Relative fold enrichment should be added to the y axis. This applies also to Figure 4. In the legend, it isn't entirely clear from what control the fold enrichment is being generated. Based on the other figures I assume it's the isotype control, and it would be helpful to state that in the legend.
Response: Thank you for the suggestion. We have made these changes.
Figure 3 An HP1 ChIP is included but there is no track for HP1 using CUT&RUN. It isn't entirely clear to me why HP1 is included; is it to make the point that it overlaps with H3K9me3? There is a sentence at the end of the Quantifcation and statistical analysis section that indicates that an HP1 CUT&RUN experiment was performed ('Representative tracks of H3K9me3, H3K4me3, and HP1 produced using CUT&RUN or ChIPseq at chromosome 8 of P. faliciparum are shown in Figure 4), but I don't see an HP1 track for Figure 4 and I don't see CUT&RUN HP1 tracks on Figure 3.
Response: Correct, no HP1 CUT&RUN was performed, we are just trying to show that H3K9me3 CUT&RUN recapitulates ChIP-seq of both H3K9me3 and HP1, which binds to H3K9me3.
Figure 4 The downsampling of reads is a nice demonstration that low numbers of reads are required for the CUT&RUN technique. It might be helpful to include downsampling of ChIP-seq reads within this figure to compare the two techniques more directly.
Response: The reason we included the down-sampling of CUT&RUN sequence reads was to explore whether were over-sequencing our CUT&RUN libraries not to provide a comparison to ChIP-seq. For simplicity we have therefore kept the figure as is.
DNA purification by Phenol/Chloroform extraction In step 38, I noticed that RNAse was not added at this step, as described in the original paper by Skene et al. Can the authors make a brief note about why they omit this reagent?
Response: RNAse A is already present since it was included in the STOP buffer at step 35.
The authors mark the TE buffer in bold, but I don't see a description of its makeup in the buffer section, though possibly I missed it. While this is a pretty standard buffer, it might still be nice to include it for completeness.
Response: TE buffer recipe was added.
Clean-up of PCR amplified library Between step 70 and 71 the authors include a warning to not discard the beads. However, this warning is not included in the Post-ligation Clean-up, which involves much the same procedure. Response: Corrected
Typos and writing It might be helpful to define CUT&RUN in the abstract by spelling out the acronym there. Response: It is defined in the 3rd paragraph of the introduction
I've mostly seen ChIP-seq with a dash between the IP and the seq.
Response: Corrected
Powerful is used twice in consecutive sentences in the first paragraph of the introduction. Consider substituting the words 'important tool' for 'powerful tool.' Response: Corrected
Figure 2 legend. “(purple) in of three biological replicates” should be “(purple) in three biological replicates” Response: Corrected
Figure 3 legend Last sentence should include 'to' between the words 'shown' and 'the'. Response: Corrected
Post-ligation Clean-up “Wash twice with 200µl of 80% Ethanol freshly prepared” should be “Wash twice with 200µl of freshly prepared 80% Ethanol” Response: Corrected
Library PCR amplification “Fragments are PCR amplified using Kapa polymerase, which it is more efficient” should be “Fragments are PCR amplified using Kapa polymerase, which is more efficient” Response: Corrected
Figure 7 legend “Indicated in the tope left panel” Should be “Indicated in the top left panel” Response: Corrected
Expected outcomes “to dismiss any sort of contamination” should be “To dismiss contamination” Response: Corrected
Potential Solution After the sentence 'Incubation buffer is added.' The next letter 'i' should be capitalized in the word Isolate. Response: Corrected
CROSS-CONSULTATION COMMENTS Plasmodium is not my model organism, so I'd defer to Reviewer 2 on the comments regarding additional detail for synchronization and Plasmodium culture conditions. I have nothing further to add, and I'm excited to see what experiments come from the addition of this technique to the parasite field.
Reviewer #3 (Significance (Required)):
This excellent methods paper describes a detailed protocol for the adaptation of the Cleavage Under Targets & Release Using Nuclease (CUT&RUN) technique to Plasmodium falciparum, the causative agent of malaria. CUT&RUN is an alternative to ChIP-seq, and has the advantage that it does not require crosslinking of targets, which can introduce artifacts and cause issues with antibody recognition. CUT&RUN can also be performed with low numbers of cells and has an excellent signal to noise ratio, which the authors demonstrate by downsampling the number of reads used in their analysis. The authors also clearly demonstrate that profiling of histone modifications using CUT&RUN yields comparable results to ChIP-seq. Because it can be difficult to obtain large numbers of cells from Plasmodium cultures, CUT&RUN is especially useful in this important model system. Publication of a detailed protocol will help other Plasmodium researchers answer important questions regarding genomic localization for their targets of interest.
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Referee #3
Evidence, reproducibility and clarity
In general the paper is very clear and convincing and I have only minor comments for the authors to address.
Introduction
The authors state that 'crosslinking presents another challenge as it can interfere with antibody recognition.' Would it be possible to provide a reference to strengthen this statement?
In the third paragraph the authors mention that CUT&RUN can be used to profile chromatin interactions from very small numbers of cells. This argument would be strengthened by adding references or examples from mammalian systems, and the authors might mention that the slight modification CUT&TAG has been employed for single cell sequencing. https://doi.org/10.1038/s41587-021-00865-z.
Figure 2
A label of Relative fold enrichment should be added to the y axis. This applies also to Figure 4. In the legend, it isn't entirely clear from what control the fold enrichment is being generated. Based on the other figures I assume it's the isotype control, and it would be helpful to state that in the legend.
Figure 3
An HP1 ChIP is included but there is no track for HP1 using CUT&RUN. It isn't entirely clear to me why HP1 is included; is it to make the point that it overlaps with H3K9me3? There is a sentence at the end of the Quantifcation and statistical analysis section that indicates that an HP1 CUT&RUN experiment was performed ('Representative tracks of H3K9me3, H3K4me3, and HP1 produced using CUT&RUN or ChIPseq at chromosome 8 of P. faliciparum are shown in Figure 4), but I don't see an HP1 track for Figure 4 and I don't see CUT&RUN HP1 tracks on Figure 3.
Figure 4
The downsampling of reads is a nice demonstration that low numbers of reads are required for the CUT&RUN technique. It might be helpful to include downsampling of ChIP-seq reads within this figure to compare the two techniques more directly.
DNA purification by Phenol/Chloroform extraction In step 38, I noticed that RNAse was not added at this step, as described in the original paper by Skene et al. Can the authors make a brief note about why they omit this reagent?
The authors mark the TE buffer in bold, but I don't see a description of its makeup in the buffer section, though possibly I missed it. While this is a pretty standard buffer, it might still be nice to include it for completeness.
Clean-up of PCR amplified library
Between step 70 and 71 the authors include a warning to not discard the beads. However, this warning is not included in the Post-ligation Clean-up, which involves much the same procedure.
Typos and writing
It might be helpful to define CUT&RUN in the abstract by spelling out the acronym there.
I've mostly seen ChIP-seq with a dash between the IP and the seq.
Powerful is used twice in consecutive sentences in the first paragraph of the introduction. Consider substituting the words 'important tool' for 'powerful tool.'
Figure 2 legend.
(purple) in of three biological replicates
Should be
(purple) in three biological replicates
Figure 3 legend Last sentence should include 'to' between the words 'shown' and 'the'.
Post-ligation Clean-up Wash twice with 200µl of 80% Ethanol freshly prepared
Should be
Wash twice with 200µl of freshly prepared 80% Ethanol
Library PCR amplification Fragments are PCR amplified using Kapa polymerase, which it is more efficient
Should be
Fragments are PCR amplified using Kapa polymerase, which is more efficient
Figure 7 legend Indicated in the tope left panel
Should be
Indicated in the top left panel
Expected outcomes to dismiss any sort of contamination
Should be
To dismiss contamination
Potential Solution After the sentence 'Incubation buffer is added.' The next letter 'i' should be capitalized in the word Isolate.
CROSS-CONSULTATION COMMENTS
Plasmodium is not my model organism, so I'd defer to Reviewer 2 on the comments regarding additional detail for synchronization and Plasmodium culture conditions. I have nothing further to add, and I'm excited to see what experiments come from the addition of this technique to the parasite field.
Significance
This excellent methods paper describes a detailed protocol for the adaptation of the Cleavage Under Targets & Release Using Nuclease (CUT&RUN) technique to Plasmodium falciparum, the causative agent of malaria. CUT&RUN is an alternative to ChIP-seq, and has the advantage that it does not require crosslinking of targets, which can introduce artifacts and cause issues with antibody recognition. CUT&RUN can also be performed with low numbers of cells and has an excellent signal to noise ratio, which the authors demonstrate by downsampling the number of reads used in their analysis. The authors also clearly demonstrate that profiling of histone modifications using CUT&RUN yields comparable results to ChIP-seq. Because it can be difficult to obtain large numbers of cells from Plasmodium cultures, CUT&RUN is especially useful in this important model system. Publication of a detailed protocol will help other Plasmodium researchers answer important questions regarding genomic localization for their targets of interest.
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www.biorxiv.org www.biorxiv.org
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Reviewer #2 (Public Review):
Horton et al combined computational and functional approaches to identify a role for a mouse transposable element (TE) family in the transcriptional response to interferon gamma (IFNG, also known as type II interferon). This paper builds on previous work, some of which was done by the corresponding author, in which TE families have been shown to contribute transcription factor binding sites to genes in a species-specific manner. In the current work, the authors analyzed datasets from mouse primary macrophages that had been stimulated by IFNG to identify TEs that might contribute to the transcriptional response to IFNG treatment. In addition to previously identified endogenous retrovirus subfamilies, the authors identified sites from another TE family, B2_Mm2, that they found contained STAT1 transcription factor binding sites and whose binding by STAT1 was induced following IFNG stimulation. To test the hypothesis that a B2_Mm2 element was providing IFNG-inducibility to an associated gene, the authors chose one of the 699 mouse genes that had nearby (<50 kb) B2_Mm2 elements and was upregulated upon IFNG treatment in previous datasets. The gene they chose was Dicer1, which also is upregulated by IFNG in mouse macrophages but not in human primary macrophages, furthering the hypothesis that the presence of B2_Mm2 in mouse cells may provide IFNG-inducibility to Dicer1. Following KO of a ~500 bp region in two separate clones of immortalized mouse macrophages, the authors show a decrease in basal as well as IFNG-induced expression of Dicer1, providing support for their conclusion that a B2_Mm2 is important for IFNG-inducibility. The authors further show that two nearby genes that are also upregulated by IFNG, Serpina3f and Serpina3g, are also reduced at basal conditions as well as when stimulated with IFNG. The authors use these data to suggest that additional elements in the B2_Mm2 element in the Dicer1 gene, possibly CTCF elements, are have long distance effects on transcription of nearby genes.
Overall, this is an interesting and well written manuscript. The computational conclusions are supported by their data and add to the growing field of TEs and their role in transcription regulatory network evolution. While the authors do a good job of experimentally validating one example, inclusion of additional data, all of which they already have, as detailed below would substantially increase the applicability of their work and strengthen their conclusions about the broad role of TEs in the IFNG response in mice versus other species.
1) Following their genome-wide comparisons, the authors hone in on Dicer1 as an interesting example in which they hypothesize that a B2_Mm2 element near the Dicer1 gene could be contributing to the fact that this gene is upregulated by IFNG in mouse cells but not human cells. What would be very useful to the readers of this paper is knowing how many other examples there might be like this one. Adding DEseq values from human RNAseq data the authors already use (current references 10 and/or 37) for identifiable human orthologs to Table S7 would thus strengthen their conclusions. If Dicer1 is unique in this aspect of having (a) a nearby B2_Mm2 element and (b) a binary difference between inducibility in mouse versus human cells, that is interesting. If Dicer1 is not unique, that strengthens the authors' assertion that B2_Mm2 insertions have altered the transcriptional network in a host-specific manner. Either way, the answer is interesting, but without including this analysis, the authors leave out an important aspect of their work and it remains unclear how generalizable their conclusions are.
2) The results with Serpina3g and Serpina3F gene expression in the authors' knockout cells are very interesting. However, the authors focus almost exclusively on Serpina3g and Serpina3F, which makes it difficult to understand what is happening genome wide. Are other IFNG-induced genes (including those not on chromosome 12) similarly affected at the level of basal or induced transcription? How many genes are different in WT versus KO cells, both at basal and induced states? Does this correlate with their CUT&TAG data shown in Fig. 5? By focusing only on nearby genes (Serpina3g and Serpina3F), the authors hint that this may be a long range regulatory effect, "potentially mediated by the CTCF binding activity of the element" that they removed. But by only focusing on two nearby IFNG-induced genes, their data do not rule out the (also potentially quite interesting) possibility that there may be a more indirect role for this TE site or Dicer1 in basal transcription of IFNG-induced genes or IFNG-mediated gene expression. Providing more data on other genes throughout the genome in WT and KO cells, which the authors have generated but do not include in the manuscript, would help distinguish between these models. While a broader effect of these KOs on IFNG expression, or gene expression in general, would not fit as neatly with their model for local gene regulation, these analyses are needed to understand the effects of TE insertion on gene regulation.
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Reviewer #3 (Public Review):
First of all, I enjoyed the manuscript by Horton et al. In the manuscript, they first re-analyzed published ChIP-seq data for STAT1 binding in INF-activated macrophages and found that a fourth of the >20,000 STAT1 binding sites were in transposable elements. Especially, about 10% of the total STAT1 binding sites were in B2_Mm2, a murine-specific SINE. They showed that these B2 elements are associated with H3K27ac signal upon INF treatment, thus likely serve as an INF-inducible enhancer through STAT1 binding. The authors then focus on the STAT1-bound B2_Mm2 in the Dicer1 gene (designated as B2_Mm2.Dicer1), and demonstrated that deletion of this B2 in a macrophage-like murine cell line resulted in loss of STAT1 binding, H3K27ac, and Dicer1 upregulation upon INF treatment. Their findings suggest that B2 transposition events has altered the transcriptional regulatory network in the innate immune response in the mouse.
The manuscript is well organized, and the findings are potentially interesting in terms of the evolution of species-specific regulatory networks of the innate immune response. But, I am not convinced with the enhancer role of the B2_Mm2.Dicer1 copy for the Dicer1 expression (see below).
Major Comments:
(1) In Fig. 4, the degree of Dicer1 induction by INF was small (1.2-fold or so), and accordingly the effect of the B2 deletion on the Dicer1 induction was also small. In addition, this B2 binds to CTCF, and its deletion should also eliminate CTCF binding. Therefore, it is difficult to conclude from the presented data that this B2 serve as an enhancer for Dicer1. The B2 may increase the frequency of transcription (as suggested by the authors), may serve as an obstacle for transcriptional elongation (via binding to CTCF), or may regulate the splicing efficiency. In Fig.5C, promoter acetylation level does not seem to be affected in KO1. Pol II either does not seem to be affected if the Pol II peak is compared to the background level. Taken together, the enhancer role is not supported by strong evidence.
(2) On the other hand, the authors discovered that the B2 deletion resulted in the decrease of Serpina3h, Serpina3g, Serpina3i and Serpina3f by >100-fold, which are 500 kb apart from the B2 locus. This is also interesting, and could be evidence for the B2 enhancer. Given that this B2 binds to both STAT1 and CTCF, the locus could interact with the Serpina3 locus to act as an enhancer. Were there STAT1 CUT&TAG peaks around the Serpina3 genes? Did H3K27ac and Pol II ChIP peaks in the Serpina3 promoters disappear in the KO cells? It would be interesting to see the IGV snapshots for H3K27ac, POLR2A and STAT1 ChIP-seq data around Serpina3 genes. In addition, HiC data for activated macrophages, if available, could be supportive evidence for the interaction between B2_Mm2.Dicer1 and the Serpina3 locus.
Minor Comments:
(3) Regarding Fig.1C, the authors calculated the B2 expression levels by mRNA-seq and DESeq2 analysis. But it does not accurately give the B2 transcription level, because the method does not discriminate B2 RNAs and B2-containing mRNA (and lncRNA as well). I wonder that the apparent upregulation of STAT1-binding B2 loci is due to the increase of Pol II transcription around the loci, rather than Pol III-mediated B2 transcription. This possibility should be discussed in page 6 after "Taken together, these data indicate that thousands of B2_Mm2 elements show epigenetic and transcriptional evidence of IFNG-inducible regulatory activity in primary murine bone marrow derived macrophages."
(4) Fig. 2B shows that about 70-80% of B2_Mm2 loci carry the STAT1 motif, whereas only a limited number (2-3%) of B2_Mm2 bind to STAT1. Is this because of differences in their motif sequences, in genomic locations, or in epigenomic environments? For example, do these STAT1-binding loci have a C-to-A mutation at the second last position in the GAS motif (TTCNNGGAA), like B2_Mm2.Dicer1 (shown in Fig. S4)? Can the authors discuss about it? In addition, although the consensus sequence of B2_mm2 has a GAS motif with only a single mismatch, the presence of the STAT1 motif in >70% of B2_Mm2 is surprising, given that their average divergence to the consensus sequence is about 10% (ref. 26 of the manuscript). Is the binding site significantly conserved in compare to the other regions of the B2 sequence?
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www.flickr.com www.flickr.com
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GTD Card Icon : Square (check box)Tag : 4th block. Squared as open-loop first, and filled later as accomplished. The GTD is advanced To-Do system proposed by David Allen. Next action of your project is described and processed through a certain flow. The GTD cards are classified into this class. 4th block is squared as open-loop first, and filled later as accomplished. The percentage of GTD Cards in my dock is less than 5 %.
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www.reddit.com www.reddit.com
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Posted byu/raphaelmustermann9 hours agoSeparate private information from the outline of academic disciplines? .t3_xi63kb._2FCtq-QzlfuN-SwVMUZMM3 { --postTitle-VisitedLinkColor: #9b9b9b; --postTitleLink-VisitedLinkColor: #9b9b9b; --postBodyLink-VisitedLinkColor: #989898; } How does Luhmann deal with private Zettels? Does he store them in a separate category like, 2000 private. Or does he work them out under is topics in the main box.I can´ find informations about that. Anyway, you´re not Luhmann. But any suggestions on how to deal with informations that are private, like Health, Finances ... does not feel right to store them under acadmic disziplines. But maybe it´s right and just a feeling which come´ out how we "normaly" store information.
I would echo Bob's sentiment here and would recommend you keep that material like this in a separate section or box all together.
If it helps to have an example, in 2006, Hawk Sugano showed off a version of a method you may be considering which broadly went under the title of Pile of Index Cards (or PoIC) which combined zettelkasten and productivity systems (in his case getting things done or GTD). I don't think he got much (any?!) useful affordances out of mixing the two. In fact, from what I can see looking at later iterations of his work and how he used it, it almost seems like he spent more time and energy later attempting to separate and rearrange them to get use out of the knowledge portions as distinct from the productivity portions.
I've generally seen people mixing these ideas in the digital space usually to their detriment as well—a practice I call zettelkasten overreach.
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onlinelibrary.wiley.com onlinelibrary.wiley.com
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Snorkelling surveys were conducted at each site to observe fish locations
Another method with questionable accuracy. A big question that arises is how can you tell different fish apart from one another without a tag and release system?
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
In this paper, the authors use purified Xenopus γ-TuRCs and experiments in cell extract combined with cutting edge imaging techniques to investigate whether binding of the γ-TuNA fragment can activate γ-TuRCs. The authors show that γ-TuNA fragments from both humans and Xenopus are obligate dimers and that dimerization is necessary for γ-TuRC binding. They further show, using direct visualisation of microtubule nucleation from individual purified γ-TuRCs, that γ-TuNA binding increases the nucleation efficiency of γ-TuRCs by ~20 fold, helping to overcome negative regulation by Strathmin.
γ-TuNA, otherwise known as the CM1 domain, CM1 motif or CM1 helix, is well conserved and found within the N-terminal region of proteins across evolution. These proteins bind and recruit γ-TuRCs to MTOCs, such as the centrosome, meaning that γ-TuRC recruitment and activation could be closely linked. Earlier studies had provided strong evidence that binding of γ-TuNA activated γ-TuRCs, hence the name "γ-TuRC mediated nucleation activator" (Choi et al., 2010), and this claim was supported by similar work a few years later (Muroyama et al. 2016). Moreover, several other studies showed that expressing in cells γ-TuNA, or equivalent protein fragments, led to ectopic microtubule nucleation in the cytoplasm, with some of the studies showing that mutations preventing the binding of these fragments to γ-TuRCs ablated this effect (Choi et al., 2010; Lynch et al., 2014; Hanafusa et al., 2015; Cota et al., 2016; Tovey et al., 2021). Collectively, therefore, it was accepted that binding of these fragments somehow activated γ-TuRCs. More recent data, however, including from the authors themselves, had provided evidence that γ-TuNA binding did not activate γ-TuRCs (Liu et al., 2019; Thawani et al., 2020). A major objective of this paper was therefore to help resolve this controversy. The author's data suggest that the ability of these fragments to activate γ-TuRCs depends upon the type and position of tag attached to the N-terminus of the γ-TuNA fragment, with large tags seemingly turning γ-TuNA into a γ-TuRC inhibitor (although they also note that one of the previous studies, which concluded γ-TuNA was an activator, had also used fragments with large N-terminal tags). The authors also insist that the new results benefit from a much-improved γ-TuRC purification protocol that results in higher yield and purity. This purification approach uses the affinity of the γ-TuNA fragment and so could be adopted by others in the field.
The major strength of this paper is directly showing, using very powerful single molecule imaging and their improved protocols, that γ-TuNA is a γ-TuRC activator, thus resolving the controversy that has existed for the last few years. The weakness is that we still don't learn how γ-TuNA binding activates γ-TuRCs (this has been proposed to be via structural changes but other mechanisms can be considered), and thus there is little conceptual advance from the original Choi et al. 2010 paper, which had already concluded that γ-TuNA binding increased the nucleation efficiency of γ-TuRCs. Moreover, the authors do not include experiments with the other proposed γ-TuRC activator, XMAP215, which they have investigated previously (Thawani et al., 2020), and so we are left wondering whether γ-TuNA and XMAP215 work together or as part of separate activation pathways.
Overall, this paper is timely as it finally resolves the controversy over γ-TuNA and it is admirable that the authors are willing to directly address and correct their previous conclusion. The data is solid and well-presented and the text is clear and has appropriate citations. In my opinion, papers that clarify the literature are just as important as those that make conceptual advances.
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Reviewer #2 (Public Review):
This is the first report that establishes gamma-TuNA as an activator of gamma-TuRC-dependent microtubule-nucleation, using purified components. This is an in-depth study that establishes experimental conditions under which gamma-TuNA can function as an activator (dimerization of gamma-TuNA, appropriately sized N-terminal tag) and clarifies why similar attempts to study gamma-TuNA have failed in the past. I think that the information in this manuscript will be of immense value to the scientific community, as it resolves a long-standing mystery concerning the function of gamma-TuNA. A key question that still remains unanswered is whether the gamma-TuNA-dependent activation mechanism involves a conformational change of the gamma-TuRC, from an asymmetric to a ring-shaped template structure, but this may be beyond the scope of the present submission.
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developers.kakao.com developers.kakao.com
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tag
태그(Tag)
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developers.kakao.com developers.kakao.com
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사용자가 어떤 약관들에 동의하고 로그인했는지 확인앱에 등록된 서비스 이용 약관은 각각 태그(Tag) 값 존재동의한 약관 확인하기를 사용해 사용자가 동의한 약관 태그 확인 가능사용자별 응답과 전체 이용약관을 비교해 추가로 동의받을 항목이 있는지 확인필요시 약관 선택해 동의 받기를 호출하거나, 서비스에서 자체적으로 약관 동의 절차를 거치도록 구현
로그인 사용자가 동의한 약관 태그 확인 가능
전체 이용 약관과 사용자가 동의한 약관을 비교하여 추가로 동의 받을 수 있는 항목 확인 가능
추가 동의가 필요한 경우 약관 선택해 동의 받기 사용 또는 서비스 자체 기능 구현 필요
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github.com github.com
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ss="footer">
I think you could have used a <footer>tag instead of creating a footer class.
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github.com github.com
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Skip to content In this repository All GitHub ↵ Jump to ↵ No suggested jump to results In this repository All GitHub ↵ Jump to ↵ In this organization All GitHub ↵ Jump to ↵ In this repository All GitHub ↵ Jump to ↵ Dashboard Pull requests Issues Codespaces Marketplace Explore Sponsors Settings caitgarland Sign out New repository Import repository New gist New organization Sorry, something went wrong. / ... / nic-dgl103-f22 / assignment-c-dlu-... / Clear Command Palette Tip: Type # to search pull requests Type ? for help and tips Tip: Type # to search issues Type ? for help and tips Tip: Type # to search discussions Type ? for help and tips Tip: Type ! to search projects Type ? for help and tips Tip: Type @ to search teams Type ? for help and tips Tip: Type @ to search people and organizations Type ? for help and tips Tip: Type > to activate command mode Type ? for help and tips Tip: Go to your accessibility settings to change your keyboard shortcuts Type ? for help and tips Tip: Type author:@me to search your content Type ? for help and tips Tip: Type is:pr to filter to pull requests Type ? for help and tips Tip: Type is:issue to filter to issues Type ? for help and tips Tip: Type is:project to filter to projects Type ? for help and tips Tip: Type is:open to filter to open content Type ? for help and tips We’ve encountered an error and some results aren't available at this time. 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Issues Pull requests Releases Discussions Discussions are not enabled for this repository Security alerts Apply Cancel Fork 0 Starred 0 Star 0 Code Issues 0 Pull requests 0 Actions Projects 0 Security Insights More Code Issues Pull requests Actions Projects Security Insights Open in github.dev Open in a new github.dev tab Permalink main Switch branches/tags Branches Tags View all branches View all tags assignment-c-dlu-chelsieadam/contact.html Go to file Go to file T Go to line L Copy path Copy permalink This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. chelsieadam Fixed Validation issues Latest commit 44427b0 5 days ago History 2 contributors Users who have contributed to this file 63 lines (57 sloc) 2.04 KB Raw Blame Edit this file E Open in github.dev . Open in GitHub Desktop Open with Desktop View raw Copy raw contents Copy raw contents Copy raw contents Copy raw contents View blame <!DOCTYPE html> <html lang="en"> <head> <link rel="stylesheet" href="style.css"> <link rel="icon" type="image/x-icon" href="images/favicon.ico"> <meta charset="UTF-8"> <meta http-equiv="X-UA-Compatible" content="IE=edge"> <meta name="viewport" content="width=device-width, initial-scale=1.0"> <link rel="preconnect" href="https://fonts.googleapis.com"> <link rel="preconnect" href="https://fonts.gstatic.com" crossorigin> <link href="https://fonts.googleapis.com/css2?family=Open+Sans&family=Raleway:wght@700&display=swap" rel="stylesheet"> <title>Hairpins Salon Contact Page</title> </head> <body> <header> <a href="index.html"><img src="images/hairpins-salon-logo.png" alt="hairpins Logo" width="300"></a> <nav> <ul> <li><a href="index.html">Home</a></li> <li><a href="services.html">Services</a></li> <li><a href="contact.html">Contact Us</a></li> </ul> </nav> </header> <h1>Contact Us</h1> <br> Questions, comments, ready for a new do?<br> We look forward to hearing from you!<br> If you're looking to make an appointment online, please do so here.<br> <br> Monday ~ Closed<br> Tuesday 9:00am ~ 5:00pm<br> Wednesday 9:00am ~ 8:00pm<br> Thursday 9:00am ~ 8:00pm<br> Friday 9:00am ~ 5:00pm<br> Saturday 9:00am ~ 4:00pm<br> Sunday ~ Closed<br> <br> Hairpins Boutique Salon<br> #4 - 224 6th Street<br> Courtenay, BC V9N 1M1<br> <br> <a href="https://www.google.com/maps/place/Hairpins+Boutique+Salon/@49.6904218,-124.9971279,15z/data=!4m2!3m1!1s0x0:0x859b2cfce3bc31ea?sa=X&ved=2ahUKEwiYi_2Ex6T6AhXNMjQIHYkoCUUQ_BJ6BAhSEAc)">Check us out on Google Maps</a><br> <br> Tel: (250) 338-7467<br> <a href="tel:250-338-7467">Click to Call</a><br> <br> Email: salon.hairpins@gmail.com <br> <a href="mailto:salon.hairpins@gmail.com">Email us</a><br> <br> <a href="contact.html">Conctact us today to book an appointment!</a> <br> <div class="footer"> Content taken from<a href="http://www.hairpins.ca/">https://www.hairpins.ca/</a>Used for educational purposes only. </div> </body> </html> Copy lines Copy permalink View git blame Reference in new issue Go Footer © 2022 GitHub, Inc. Footer navigation Terms Privacy Security Status Docs Contact GitHub Pricing API Training Blog About You can’t perform that action at this time. You signed in with another tab or window. Reload to refresh your session. You signed out in another tab or window. Reload to refresh your session. .user-mention[href$="/caitgarland"] { color: var(--color-user-mention-fg); background-color: var(--color-user-mention-bg); border-radius: 2px; margin-left: -2px; margin-right: -2px; padding: 0 2px; } assignment-c-dlu-chelsieadam/contact.html at main · nic-dgl103-f22/assignment-c-dlu-chelsieadam
Similar comments - I would use unordered lists and paragraph elements where necessary!
Also, I found there is an < address > tag you could use. Learn more: https://www.w3schools.com/tags/tag_address.asp
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content.time.com content.time.com
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The concept of assigning a price tag to a life has always made people intensely squeamish.
Introduction ends
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www.biorxiv.org www.biorxiv.org
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biomonitoring
Reviewer 4. Christina Lynggaard
This manuscript assesses the variation in arthropod communities in three ecoregions in Canada. The study is well done, and the sampling was very thorough with a big sampling effort. I only have minor comments. Specially I consider that the aim can be focused on the ecoregions instead of the feasibility of the method, as this has already been shown. In addition, it would be nice to have more details in certain sections in the data analyses and in the results. I have addressed these comments below. -I am not sure why the title "Message in a bottle". -Line 65- Could you specify which indicator species have been targeted? Or cite studies that target those species? - Line 96- Based on the limitations of the ecoregions, it is not clear why ecoregions are an obvious candidate. -In line 104 seems that your aim is to demonstrate how feasible is to use metabarcoding for large-scale monitoring and that you use the ecoregions to prove that. However, showing the feasibility of this method for large-scale studies has already been done (e.g. Svenningsen et al 2021, Detecting flying insects using car nets and DNA metabarcoding; Bush et al 2020, DNA metabarcoding reveals metacommunity dynamics in a threatened boreal wetland wilderness). I suggest keeping it focused on the need to apply this method in different ecoregions. -In the Data description section, you mention that you examined phylogenetic diversity, but in the Analyses section you vaguely mention it. The phylogenetic diversity findings are discussed later on, but it is difficult to follow the discussion when the results were not presented previously. In addition, the authors use the findings in phylogenetic diversity to support the idea of a structure in the ecoregions, so I suggest making more emphasis in this in the results section. -Line 189. I agree that the higher number of BINs could be due to eDNA, but couldn't another reason be that the BINs were oversplit during data analysis? -Line 215-217. Has this been found previously in other studies using Malaise trap? If so, please reference to those findings. -Line222- This is a brief discussion about temporal turnover. However, these results are not presented previously, or at least not clearly enough. -Line 266-267- Yes, you showed compositional shifts using metabarcoding in bulk arthropod samples, but the way this sentence is structured it sounds like you are the first to show this. Compositional shifts in arthropods have been shown previously in other studies using metabarcoding. -Line 321- Did you have negative PCR controls? In line 326 you mention negative controls, but I assume you refer to the extraction negative controls. -Line 340- It is not clear why you queried the data against a bacterial library. -Line 348- What was the reason for choosing "at least three reads"? and the same for line 350 where you cluster sequences with a minimum of 5 reads per cluster. -Line 357- If you see tag switching in your negative controls that means that most likely you have it in the rest of the data. How did you ensure that the rest of the data did not have that? You may have tags switching in sequences not found in the negative controls but found in your samples. -Line 369- As you used the Bray-Curtis index in this metabarcoding data, did you convert your data to presence/absence? It is known that for metabarcoding data the use of read numbers for community analysis is not adequate (see Nichols et al 2018 "Minimizing polymerase biases in metabarcoding") .
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www.reddit.com www.reddit.com
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When people first see your Twitter, without even having to scroll down, they should knowThe name of our Game (make this your Twitter tag, not your company name!)Gameplay footage of our game pinned to the top of the feedOur unique selling point/elevator pitchWhat our logo looks likeWhat genre the game isWhere our Discord isWhere our Patreon isWhere our Facebook isOur email address
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www.kamilgrzybek.com www.kamilgrzybek.com
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Modular Monolith: Domain-Centric Design
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denisetodd.medium.com denisetodd.medium.com
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2) Install the Community Plugin — Tag Wangler
already installed
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1) Ensure the following Core Obsidian plugins are turned ON: Go to Obsidian Settings > Core plugins, and turn on:✅ Backlinks✅ File Explorer✅ Graph view✅ Quick Switch✅ Slash Command✅ Tag panes
Done !
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#BOOK and #book are treated as the same tag. Folders and links ARE case-sensitive.
les tags ne prend pas en compte le majuscule et le minuscule
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www.biorxiv.org www.biorxiv.org
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Note: This rebuttal was posted by the corresponding author to Review Commons. Content has not been altered except for formatting.
Learn more at Review Commons
Reply to the reviewers
Thank you for giving us the opportunity to submit a revised draft of the manuscript “Tup1 is Required for Transcriptional Repression Necessary in Quiescence in S. cerevisiae” to Review Commons. We appreciate the time and effort that you and the other reviewers dedicated to providing feedback on our manuscript and are grateful for the insightful comments on and valuable improvements to our paper. We believe that the experiments suggested in these comments would bring clarity to the manuscript, and wish that we had the ability to perform them all. Unfortunately our lab is closing, and the only remaining lab member is the PI, so we are only able to perform limited experiments to address some of the concerns raised during review. We have incorporated several changes in response to comments from the reviewers. Those changes are highlighted within the manuscript. Please see below, in blue, for a point-by-point response to the reviewers’ comments and concerns. All page numbers refer to the revised manuscript Word file with tracked changes.
Of particular note is the discussion of cellular morphology of the tup1∆ and sds3∆ strains. We realize that our findings are purely descriptive, and are not surprised that all three reviewers had comments on this data. This was the source of much discussion among the authors and consultation with other labs; we debated even including these observations in the manuscript, since we were unable to figure out the underlying mechanism. Ultimately we decided that it was worth reporting in case other labs may benefit from the knowledge, and we have altered the language in the manuscript (page 6) to better reflect this. However, if the reviewers feel that this observation would be better left out of the manuscript, we would be willing to remove Figure 6 and any discussion of these images.
Reviewer #1 Comments:1. The authors chose to examine 3-day SP cells to interrogate quiescence because tup1∆ cells are highly flocculant, interfering with the isolation of purified quiescent cells. These cells are a mixture of both nonquiescent and quiescent cells, so it is not correct to state that they represent a quiescent cell population. The addition of EDTA to the gradients used to isolate quiescent cells could eliminate flocculation and permit the isolation of quiescent cells. EDTA is also often added to media in low amounts to reduce flocculation. The authors need to indicate the proportion of quiescent cells in their SP cultures by applying these tools.
We appreciate the suggestion, but the phenotype of this strain is not typical flocculation (see photo below, also added to the paper as Supplementary Figure 1). We did add EDTA (pH 8.0) to a final concentration of 10 mM to two separate tup1∆ and it did not visibly affect the clumping of cells. Furthermore, changes to the cell wall are a distinct feature of quiescent S. cerevisiae and contribute to the ability to separate different cell types by density-gradient centrifugation, so it is difficult to anticipate how EDTA would affect our ability to isolate Q cells. We have provided more explanation in the manuscript to better explain this (page 3).
- The authors reported that while Xpb1 and Tup1 share many overlapping binding sites, but that Xbp1 does not regulate Tup1's binding. What other factors might be responsible for their shared binding? Could histone deacetylation play a role? This could be addressed by a Tup1 ChIP in an sds3∆ mutant.
This is a good thought; histone acetylation levels may have a role in regulating Tup1 localization and we would have liked to address this if we had more time. Unfortunately, we had some difficulty performing ChIP of Tup1, because initially we used a FLAG tag which caused a phenotype similar to deletion of Tup1, and had to switch to making myc-tagged strains. This delay meant we did not have time to pursue creating myc-tagged Tup1 in an sds3∆ strain, and now we do not have the ability to follow up on this for revisions.
- Has PolII occupancy been examined in Log vs SP cells of tup1∆ to determine if Tup1 inhibits PolII association with its genes that are repressed ?
We did not look at PolII occupancy in our Tup1 deletion, and could not find any existing datasets with this information. It is our hope that another lab is able to carry out this experiment, because it could be very enlightening, but it is beyond the scope of this work.
- The observation that tup1∆ cells have several nuclear puncta is intriguing, although the cytological images need to be improved.
The nuclear puncta we see in the tup1 deletion are definitely a puzzle. We had limited time to investigate this phenomena, and in discussing the matter with some other labs it seemed doubtful that more advanced imaging would yield anything of use to us. We realized that we accidentally omitted important details for this figure and have updated the manuscript to add them. We imaged 2 biological replicates for each strain and imaged many yeast samples for each strain (which has been added to the caption for Figure 6) and found that our findings were statistically significant (p
Reviewer #2 Comments1. The authors acknowledge that it would be better to work with purified quiescent cells but couldn't isolate pure populations. As a result, a mixture of quiescent and nonquiescent cells are analyzed in stationary phase. They say this is because Tup1 deletion strains are flocculent. But they performed ChIP-Seq on Myc-tagged Tup1 strain. Don't these cells express Tup1? If not, could this be performed in wild-type yeast with Myc-tagged Tup1? It seems important to separate quiescent from nonquiescent yeast for the authors' conclusions.
It is true that we could have done ChIP-seq for Tup1 in purified Q cells. We considered it, but decided to look at the mixed population so that we could directly compare our RNA-seq results from the tup1∆ strain. It’s a balance between having some results that are specific to quiescence, versus being able to directly compare the effects of deletion of Tup1 at the sites where it binds. We are now unable to perform this experiment, but we have updated the language in the manuscript (page 3) to better reflect this choice.
- The Chipseq data in Fig 1B do not have a y axis and it is consequently not clear whether these data are normalized and shown with the same axis.
Thank you for pointing this out - these data are normalized to RPKM during processing, and we have updated the caption for figure 1 and the methods on page 10 to reflect this information. Normalizing the data in IGB itself, however, causes an adjustment in the y-axis that makes the tracks appear to be inconsistent. In any case, we are not making claims about the relative amount of signal, and as it is common in the field to not include y-axes on IGB tracks, we have opted to keep the y-axis for Figure 1B as-is.
- In Fig 2, it seems important to determine how many genes are different between WT and Tup1 deletion strains in log phase. Are just as many genes different? Or is Tup1 more important in diauxic shift and stationary phase than log phase?
We did intend to focus only on diauxic shift and stationary phase data for this paper, since there has already been so much work on the role of Tup1 in log phase. As mentioned above, comparisons of RNA between log and DS/Q is difficult. We attempted to find a publicly available dataset to perform some analysis for revisions, but unfortunately most previous work on the effect of Tup1 on transcription was performed via tiling arrays, which is not comparable.
- Are the genes that are regulated by Tup1 normally regulated during diauxic shift or stationary phase compared with log growth?
Because there is a massive global decrease in the level of total RNA in diauxic shift and quiescence (McKnight, Boerma, et al., 2015) it is impossible to directly compare transcript levels between these states in our experiments. If there was time, we could have attempted to repeat these experiments with an external spike-in control; this is potentially something another lab could do to follow up on our findings.
- What fraction of the genes that are differentially expressed in Tup1 knockout yeast have Tup1 binding at the promoter? Enhancer? What fraction can be explained by Tup1, Hap1, Nrg1, Mig1 individually and together?
We have added the number of genes that are differentially expressed in Tup1 knockout yeast during DS to the manuscript (page 3). Regarding enhancers, the genome of S. cerevisiae is very compact, and there is not evidence of long-distance activation of genes as seen in metazoans (Dujon, 1996; Dobi & Winston, 2007; Spiegel and Arnone, 2021). Upstream activating sequences (UASs) are generally considered the closest equivalent to enhancers in cerevisiae, and they tend to function within a few hundred base pairs of the promoter. Our analysis only identifies the nearest gene; it would be difficult to parse out locations in the promoter versus a UAS without a more advanced analysis that is beyond our capabilities now.
As for the effect of Hap1, Nrg1, and Mig1, we were able to look for their motifs in the genes that are differentially expressed in the Tup1 knockout but we do not have binding data for these factors in quiescence or stationary phase so it is impossible to conclusively state what role those TFs play. This would be a very interesting followup to our work, but is outside the scope of this manuscript.
References:
Dujon, B. 1996. The Yeast Genome Project: What did we learn? Trends Genet. 12, 263-270.
Dobi, K.C.; Winston, F. 2007. Analysis of Transcriptional Activation at a Distance in Saccharomyces cerevisiae. Mol Cell Biol. 27(15), 5575-5586. https://doi.org/10.1128/MCB.00459-007
Spiegel, JA; Arnone, J.T. 2021.Transcription at a Distance in the Budding Yeast Saccharomyces cerevisiae. Appl. Microbiol. 1(1), 142-149. https://doi.org/10.3390/applmicrobiol1010011
- The methodology used to generate the gene ontology enrichments should be described in the methods.
Thank you for noticing this omission; we have added the relevant information to the manuscript (page 10) and have also added the related citation (page 11).
- The authors should provide genomewide data to support the statement that Tup1 and Rpd3 ChIP datasets have substantial overlap. They should also provide genomewide data to support the statement that there is substantial overlap between Rpd3 and Tup1. How much overlap is observed and how much is expected by chance?
We have compared the existing ChIP data for Rpd3 binding in quiescent cells to our ChIP data for Tup1 in 3-day cultures and included this in the manuscript (page 4, Supplementary Figure 2B), along with a p-value.
- For Sds3, similar to Tup1 inactivation, it would be helpful to know how many genes change in with Sds3 inactivation in log phase in addition to diauxic shift and stationary phase.
As with our response to comment #3, we focused only on diauxic shift and stationary phase data for this paper, and analysis of this data would be difficult without a spike-in control. While there are some existing datasets for RNA-seq of Rpd3 knockouts, this would include both Rpd3L and Rpd3S activity, rather than just Rpd3L, which is our focus with the Sds3 deletion strains. As such, we did not perform RNA-seq of sds3∆ in log phase.
- If the argument is that Sds3 and Xbp1 cooperate with Tup1 to affect gene expression, testing the gene expression changes that are associated with Tup1 in Sds3 or Xbp1 knockout strains would help the authors make this point.
We do not have tup1∆/sds3∆ or tup1∆/xbp1∆ double knockout strains. We attempted to make these strains but could not, which may indicate that these double deletions are synthetic lethal. Deletion of sds3 alone causes a significant reduction in growth rate, so it is perhaps not surprising that we could not create the double knockouts.
- The final phenotype of extra DAPI positive blobs in the nucleus is not very specific or clear.
We agree, please see our comments at the top of this letter.
Reviewer #3 (Major comments):Did tup1∆/sds3∆ double mutant show the same phenotype with tup1∆ (or sds3∆) single mutant in G0? If Tup1 actually plays role in tandem with Sds3 in the gene regulation during G0, the epistatic relationship might be estimated.
We do not have tup1∆/sds3∆ or tup1∆/xbp1∆ double knockout strains. We attempted to make these strains but could not, which may indicate that these double deletions are synthetic lethal. Deletion of sds3 alone causes a significant reduction in growth rate, so it is perhaps not surprising that we could not create the double knockouts.
The histone acetylation was not synergistically augmented in the above double mutant?
Please see the response above.
The authors showed that tup1∆ but not sds3∆ cells contain multiple DAPI signals but sds3∆ cells show abnormal cell shape in G0 phase. These phenotypic abnormalities in these mutants suggest a potential mitotic defect. Both mutants showed very similar abnormalities in H3K23 acetylation and gene expressions in quiescent state. Why these showed distinctly different abnormality in cell morphology during G0?
Unfortunately we were unable to investigate this further.
Did iswi2∆ cells also show abnormality in G0 phase?
No, they did not; thank you for asking, this is a good question. We have added this information to the manuscript (page 6).
(Minor comments)Supplementary figure1. This data seems to be very important. I recommend to use this data in the main figure with statistical analysis (p-values) to show the significant overlap of Tup1 and Rdp3 distribution.
We have compared the existing ChIP data for Rpd3 binding in quiescent cells to our ChIP data for Tup1 in 3-day cultures and included this in the manuscript (page 4, Supplementary Figure 2B) . We do feel that this data belong in the supplement, however, because the data is not exactly equivalent to our studies: quiescent cells and 3-day cultures are not the same, and knockout of Rpd3 eliminates function of both Rpd3L and Rpd3S complexes, while knocking out Sds3 targets only the Rpd3L complex.
Figure 4. Histone acetylation level data in Figure 4A and the data for gene repressions by Tup1 and Sds3 in Figure 4C seem to be very important. However, statistical analysis data (p-values) was not presented. Please show the statistical analysis data (p-values) as in figure 3 to show that the Tup1 and Sds3 contribute similarly in histone deacetylation and repression. The author did not find the significant changes of histone deacetylation in xbp1∆ cells but said that when filtered in Xbp1 binding motif Xbp1 depletion has similar effect on the acetylation level. Please show this data.
We have added language in the manuscript comparing genes with altered acetylation levels to those that are differentially expressed in our RNA-seq datasets, along with a p-value, to page 5.
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www.reddit.com www.reddit.com
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https://www.reddit.com/r/antinet/comments/xyhpq4/2015_exhibition_of_roland_barthes_zettelkasten/
Johanna Daniel has some interesting reflections (in French) about Barthes' reading, note taking, and writing processes: http://johannadaniel.fr/isidoreganesh/2015/06/archives-roland-barthes/ Perhaps most importantly she's got some photos from an exhibition of his work which includes portions of his note cards and writing. Roland Barthes' note cards on the Sorrows of Young Werther by Goethe. And you thought your makeshift cardboard boxes weren't "enough"? Want more about Barthes' practice? Try my digital notes: https://hypothes.is/users/chrisaldrich?q=tag%3A%22Roland+Barthes%22
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github.com github.com
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<style> body { font-family: "Trirong", serif; font-weight:400;
I'm pretty sure you can add this to your style.css page as it's considered a css tag?. I think this is mixing html & css into one sheet which can become confusing.
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br
The BR tag is already self closing, therefore you don't need to have a closing tag. A BR tag by it's self is perfectly fine.
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Stylist
p tag!
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Located
p tag, It'll still load properly without but it's needed.
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forgravity.com forgravity.com
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You can display the file name and link to your generated PDF in your Gravity Forms confirmation message using merge tags. When editing a confirmation message, there will be a Fillable PDFs group at the bottom of the merge tag drop down. Every configured Fillable PDFs feed will have three merge tags available: one that displays a properly formatted link with the PDF URL and file name, one for only the file name, and one for only the PDF URL.
The fillable pdf IDs are found in the url for each form on the fillable pdf page
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www.wired.com www.wired.com
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Where does clicktivism end and algorithmic gaming begin?
This linked article was super interesting to me. I had never heard of the term "clicktivism" before but it made a lot of sense to hear that, because many online seem to feel like helping things to trend is a notable part of activism, and this in turn can lead to behavior paltforms find suspicious. It's true that it does have its share of impact- causes and people in need can reach more people than was ever possible thanks to the internet- but it has also led to some odd cultural quirks online when it comes to giving such issues a platform. Occasionally the goal to "boost awareness" or publicly declare yourself aligned with the "right" or "correct" cause can overpower the actual execution of concrete, meaningful action. The term "performative activism" also encompasses this phenomenon, in which people publicly post a lot about a tag or trend to sort of assure their followers they too are on the right side of affairs. Accounts that are clearly mining activist circles for engagement (even if they are helping to spread awareness of issues) can definitely act similarly to bots or spammers.
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developers.kakao.com developers.kakao.com
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🅐 약관 제목: 한국어, 영어 모두 입력 🅑 약관 URL: 약관 내용을 확인할 수 있는 웹 페이지 URL 입력 🅒 약관 조건: 필수 동의 항목 또는 선택 동의 항목 중 선택 🅓 태그: 각 서비스 약관을 가리키는 고유값 입력 서비스 약관 등록 시 지켜야 할 규칙은 아래와 같습니다. 약관 제목 한국어 약관 제목은 한글, 영문, 숫자, 공백, 키보드에서 직접 입력 가능한 특수문자만 지원(최대 45자) 영어 약관 제목은 영문, 숫자, 공백, 키보드에서 직접 입력 가능한 특수문자만 지원(최대 100자) 영문 약관이 없더라도 영어 약관 제목은 영어로 입력, 영어 약관 제목은 사용자 기기의 언어 설정이 영어일 때 사용됨 약관 URL 약관 URL은 필수 입력 선택 약관에 한해 URL 생략 가능 약관 조건 가입 시 반드시 동의해야 하는 서비스 약관은 [필수 동의 항목]으로 설정 서비스 제공 범위에 따라 사용자가 추가 동의할 수 있는 서비스 약관은 [선택 동의 항목]으로 설정 태그 다음 카카오 API 요청 시 태그 사용, 실제 서비스 개발 시 사용 가능한 값으로 입력 동의한 약관 확인하기: 사용자의 약관별 동의 여부 확인 약관 선택해 동의 받기: 사용자에게 특정 서비스 약관 동의 요청 영문, 숫자, 하이픈(-), 언더스코어(_)만 입력 가능 ${KEYWORD}_${DATE}, ${KEYWORD}_${ORDER} 등 형식 권장(예: terms_20220701, terms_01)
🅐 제목: 약관의 제목을 입력합니다. (한국어와 영문 모두 필수) 한국어 약관 제목은 한글, 영문, 숫자, 공백, 키보드에서 직접 입력 가능한 특수문자만 지원(최대 45자) 영어 약관 제목은 영문, 숫자, 공백, 키보드에서 직접 입력 가능한 특수문자만 지원(최대 100자) 영문 약관이 없더라도 영어 약관 제목은 영어로 입력, 영어 약관 제목은 사용자 기기의 언어 설정이 영어일 때 사용됨 🅑 URL: 약관 내용을 확인할 수 있는 웹 페이지 URL을 입력합니다. ('약관 조건'이 [필수 동의 항목]인 경우 필수) 🅒 조건: 서비스 약관의 조건을 선택합니다. [필수 동의 항목]: 가입 시 반드시 동의해야 하는 서비스 약관 [선택 동의 항목]: 서비스 제공 범위에 따라 사용자가 추가 동의할 수 있는 서비스 약관 🅓 TAG: 서비스 약관을 가리키는 고유값입니다. (필수) 아래 카카오 API 요청 시 태그 사용 동의한 약관 확인하기 약관 선택해 동의 받기 실제 서비스 개발 시 사용 가능한 값으로 입력 영문, 숫자, 하이픈(-), 언더스코어(_)만 입력 가능 ${KEYWORD}_${DATE}, ${KEYWORD}_${ORDER} 등 형식 권장(예: terms_20220701, terms_01)
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www.biorxiv.org www.biorxiv.org
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Review coordinated via ASAPbio’s crowd preprint review
This review reflects comments and contributions by Ruchika Bajaj, Gary McDowell, Sree Rama Chaitanya Sridhara. Review synthesized by Iratxe Puebla.
The preprint studies the process for mitochondrial targeting of mitochondrial precursor proteins. Using a yeast model, experiments show that the cytosol transiently stores matrix-destined precursors in dedicated granules which the authors name MitoStores. The formation of MitoStores is controlled by the heat shock proteins Hsp42 and Hsp104, and suppresses the toxicity arising from non-imported accumulated mitochondrial precursor proteins.
The manuscript is clear and well-written. The reviewers raised a few comments and suggestions as outlined below:
The introduction was extremely clear and provides a good summary of the protein homeostasis dimension of the problem in question. However, there could be a clearer discussion of the processes of import, in particular with respect to the results discussing “clogging”. It is suggested to add a penultimate transitional paragraph in the introduction that facilitates this transition e.g. this could be expansion of the first paragraph in the Results section, moved into the introduction to provide more context about the cloggers, PACE, and the Rpn4-mediated proteasomal regulation.
Figure 2E and Figure S2 - Can some further explanation be provided about what data belongs to delta-rpn otr WT, or whether the associated fold change is reported - delta-rpn/WT.
Results ‘while the levels of most chaperones were unaffected or even reduced in Δrpn4 cells, the disaggregase Hsp104 and the small heat shock protein Hsp42 were considerably upregulated (Fig. 2F, G)’ - Suggest adding some further clarification as to why Hsp104 and Hsp42 are selected despite perturbations in other protein partners. Are there other proteins than proteosomes and chaperones which are significantly up- or down-regulated? STRING or cytoscape tools may help with the interactome analysis.
Figure 3
- Figure 3A - It seems Δrpn4 cells are bigger in size than control cells, suggest commenting on this point.
- Figure 3B ‘Hsp104-GFP was purified on nanotrap sepharose’ - Please clarify on which tag the purification was based.
- ‘grown at the indicated temperatures’ - Please clarify the rationale for using 30 or 40C.
- ‘SN, supernatant representing the non-bound fraction’ - Please report what is total, wash and elute etc.
Results ‘protein accumulated at similar levels as Hsp104-GFP in the yeast cytosol (Fig. S4B)’ - Please clarify whether the image reports qualitative or quantitative data, and how the levels of DHFR-GFP and Hsp104-GFP are compared based on S4B.
‘Owing to the striking acquisition of nuclear encoded mitochondrial proteins in these structures, we termed them MitoStores’- Suggest providing some discussion about the fraction of Hsp104 that is part of the MitoStores? Does a major portion of Hsp104 in the absence of Rpn4 form MitoStore structures?
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github.com github.com
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<br>
I get what you're trying to do here with the "br" tag, but it falls apart when the window is resized. I think wrapping the content in an element and styling it with a max-width property would be better, as this would prevent it from become really long on wide displays while letting it resize dynamically on small displays
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github.com github.com
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html
use root tag for style the full html file
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github.com github.com
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/>
closing tag should be use on same line.
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</figcaption>
That closing tag should be closed on the same line.
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<!DOCTYP
main tag is not used as it is written in instructions to use definitely .
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<body>
main tag should be used as per instructions.
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<dl>
dl tag is good but in instructions they ask to use embedded style for remove the bullets .so read carefully all the instructions
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github.com github.com
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<br>Meet the Team<br>
Breaks make sense but this text is not surrounded by an element tag. Something like: <br>
Meet the Team
<br>
makes it possible to format that line.
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github.com github.com
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and
Again, Maybe add a (p) tag as it's text.
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github.com github.com
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Located
I'm not to sure what happened here maybe it didn't go through when you committed? There's no (p) tag for the text here? there is for a couple of text's but some don't have anything? Key part!
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www.biorxiv.org www.biorxiv.org
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Author Response
Reviewer #1 (Public Review):
In one of the most creative eDNA studies I have had the pleasure to review, the authors have taken advantage of an existing program several decades old to address whether insect declines are indeed occurring - an active area of discussion and debate within ecology. Here, they extracted arthropod environmental DNA (eDNA) from pulverized leaf samples collected from different tree species across different habitats. Their aim was to assess the arthropod community composition within the canopies of these trees during the time of collection to assess whether arthropod richness, diversity, and biomass were declining. By utilizing these leaf samples, the greatest shortcoming of assessing arthropod declines - the lack of historical data to compare to - was overcome, and strong timeseries evidence can now be used to inform the discussion. Through their use of eDNA metabarcoding, they were able to determine that richness was not declining, but there was evidence of beta diversity loss due to biotic homogenization occurring across different habitats. Furthermore, their application of qPCR to assess changes in eDNA copy number temporally and associate those changes with changes to arthropod biomass provided support to the argument that arthropod biomass is indeed declining. Taken together, these data add substantial weight to the current discussion regarding how arthropods are being affected in the Anthropocene.
Thank you very much for the positive assessment of our work.
I find the conclusions of the paper to be sound and mostly defensible, though there are some issues to take note of that may undermine these findings.
Firstly, I saw no explanation of the requisite controls for such an experiment. An experiment of this scale should have detailed explanations of the field/equipment controls, extraction controls, and PCR controls to ensure there are no contamination issues that would otherwise undermine the entirety of the study. At one point in the manuscript the presence of controls is mentioned just once, so I surmise they must exist. Trusting such results needs to be taken with caution until such evidence is clearly outlined. Furthermore, the plate layout which includes these controls would help assess the extent of tag-jumping, should the plate plan proposed in Taberlet et al., 2018 be adopted.
Second, without the presence of adequate controls, filtering schemes would be unable to determine whether there were contaminants and also be unable to remove them. This would also prevent samples from being filtered out should there be excessive levels of contamination present. Without such information, it makes it difficult to fully trust the data as presented.
Finally, there is insufficient detail regarding the decontamination procedures of equipment used to prepare the samples (e.g., the cryomil). Without clear explanations of the steps the authors took to ensure samples were handled and prepared correctly, there is yet more concern that there may be unseen problems with the dataset.
We are well aware of the potential issues and consequences of contamination in our work. However, we are also confident that our field and laboratory procedures adequately rule out these issues. We agree with the reviewer that we should expand more on our reasoning. Hence, we have now significantly expanded the Methods section outlining controls and sample purity, particularly under “Tree samples of the German Environmental Specimen Bank – Standardized time series samples stored at ultra-low temperatures” (lines 303-304), “Test for DNA carryover in the cryomill” (lines 448-464) and “Statistical analysis” (lines 570-575).
We ran negative control extractions as well as negative control PCRs with all samples. These controls were sequenced along with all samples and used to explore the effect of experimental contamination. With the exception of a few reads of abundant taxa, these controls were mostly clean. We report this in more detail now in the Methods under “Sequence analysis” (lines 570-575). This suggests that our data are free of experimental contamination or tag jumping issues.
We have also expanded on the avoidance of contamination in our field sampling protocols. The ESB has been set up for monitoring even the tiniest trace amounts of chemicals. Carryover between samples would render the samples useless. Hence, highly clean and standardized protocols are implemented. All samples are only collected with sterilized equipment under sterile conditions. Each piece of equipment is thoroughly decontaminated before sampling.
The cryomill is another potential source of cross-contamination. The mill is disassembled after each sample and thoroughly cleaned. Milled samples have already been tested for chemical carryover, and none was found. We have now added an additional analysis to rule out DNA carryover. We received the milling schedule of samples for the past years. Assuming samples get contaminated by carryover between milling runs, two consecutive samples should show signatures of this carryover. We tested this for singletaxon carryover as well as community-wide beta diversity, but did not find any signal of contamination. This gives us confidence that our samples are very pure. The results of this test are now reported in the manuscript (Suppl. Fig 12 & Suppl. Table 3).
Reviewer #2 (Public Review):
Krehenwinkel et al. investigated the long-term temporal dynamics of arthropod communities using environmental DNA (eDNA) remained in archived leave samples. The authors first developed a method to recover arthropod eDNA from archived leave samples and carefully tested whether the developed method could reasonably reveal the dynamics of arthropod communities where the leave samples originated. Then, using the eDNA method, the authors analyzed 30-year-long well-archived tree leaf samples in Germany and reconstructed the long-term temporal dynamics of arthropod communities associated with the tree species. The reconstructed time series includes several thousand arthropod species belonging to 23 orders, and the authors found interesting patterns in the time series. Contrary to some previous studies, the authors did not find widespread temporal α-diversity (OTU richness and haplotype diversity) declines. Instead, β-diversity among study sites gradually decreased, suggesting that the arthropod communities are more spatially homogenized in recent years. Overall, the authors suggested that the temporal dynamics of arthropod communities may be complex and involve changes in α- and β-diversity and demonstrated the usefulness of their unique eDNA-based approach.
Strengths:
The authors' idea that using eDNA remained in archived leave samples is unique and potentially applicable to other systems. For example, different types of specimens archived in museums may be utilized for reconstructing long-term community dynamics of other organisms, which would be beneficial for understanding and predicting ecosystem dynamics.
A great strength of this work is that the authors very carefully tested their method. For example, the authors tested the effects of powdered leaves input weights, sampling methods, storing methods, PCR primers, and days from last precipitation to sampling on the eDNA metabarcoding results. The results showed that the tested variables did not significantly impact the eDNA metabarcoding results, which convinced me that the proposed method reasonably recovers arthropod eDNA from the archived leaf samples. Furthermore, the authors developed a method that can separately quantify 18S DNA copy numbers of arthropods and plants, which enables the estimations of relative arthropod eDNA copy numbers. While most eDNA studies provide relative abundance only, the DNA copy numbers measured in this study provide valuable information on arthropod community dynamics.
Overall, the authors' idea is excellent, and I believe that the developed eDNA methodology reasonably reconstructed the long-term temporal dynamics of the target organisms, which are major strengths of this study.
Thank you very much for the positive assessment of our work.
Weaknesses:
Although this work has major strengths in the eDNA experimental part, there are concerns in DNA sequence processing and statistical analyses.
Statistical methods to analyze the temporal trend are too simplistic. The methods used in the study did not consider possible autocorrelation and other structures that the eDNA time series might have. It is well known that the applications of simple linear models to time series with autocorrelation structure incorrectly detect a "significant" temporal trend. For example, a linear model can often detect a significant trend even in a random walk time series.
We have now reanalyzed our data controlling for autocorrelation and for non-linear changes of abundance and recover no change to our results. We have added this information to the manuscript under “Statistical analysis” (lines 629-644).
Also, there are some issues regarding the DNA sequence analysis and the subsequent use of the results. For example, read abundance was used in the statistical model, but the read abundance cannot be a proxy for species abundance/biomass. Because the total 18S DNA copy numbers of arthropods were quantified in the study, multiplying the sequence-based relative abundance by the total 18S DNA copy numbers may produce a better proxy of the abundance of arthropods, and the use of such a better proxy would be more appropriate here. In addition, a coverage-based rarefaction enables a more rigorous comparison of diversity (OTU diversity or haplotype diversity) than the readbased rarefaction does.
We did not use read abundance as a proxy for abundance, but used our qPCR approach to measure relative copy number of arthropods. While there are biases to this (see our explanations above), the assay proved very reliable and robust. We thus believe it should indeed provide a rough estimate of biomass. As biomass is very commonly discussed in insect decline (in fact the first study on insect decline entirely relies on biomass; Hallmann et al. 2017), we feel it is important go include a proxy for this as well. However, we also discuss the alternative option that a turnover of diversity is affecting the measured biomass. A pattern of abundance loss for common species has been described in other works on insect decline.
We liked the reviewer’s suggestion to use copy number information to perform abundance-informed rarefaction. We have done this now and added an additional analysis rarefying by copy number/biomass. A parallel analysis using this newly rarefied table was done for the total diversity as well as single species abundance change. Details can be found in the Methods and Results section of the manuscript. However, the result essentially remains the same. Even abundance-informed rarefaction does not lead to a pattern of loss of species richness over time (see “Statistical analysis”).
The overall results are supporting a scenario of no overall loss of species richness over time, but a loss of abundance for common species. And we indeed see the pattern of declining abundance for once-common species in our data, for example the loss of the Green Silver-Line moth, once a very common species in beech canopy (Suppl. Fig. 10). We have added details on this to the Discussion (lines 254-260).
These points may significantly impact the conclusions of this work.
Reviewer #3 (Public Review):
The aim of Weber and colleagues' study was to generate arthropod environmental DNA extracted from a unique 30-year time series of deep-frozen leaf material sampled at 24 German sites, that represent four different land use types. Using this dataset, they explore how the arthropod community has changed through time in these sites, using both conventional metabarcoding to reconstruct the OTUs present, and a new qPCR assay developed to estimate the overall arthropod diversity on the collected material. Overall their results show that while no clear changes in alpha diversity are found, the βdiversity dropped significantly over time in many sites, most notable in the beech forests. Overall I believe their data supports these findings, and thus their conclusion that diversity is becoming homogenized through time is valid.
Thank you for the positive assessment.
While overall I do not doubt the general findings, I have a number of comments. Firstly while I agree this is a very nice study on a unique dataset - other temporal datasets of insects that were used for eDNA studies do exist, and perhaps it would be relevant to put the findings into context (or even the study design) of other work that has been done on such datasets. One example that jumps to my mind is Thomsen et al. 2015 https://besjournals.onlinelibrary.wiley.com/doi/full/10.1111/1365-2656.12452 but I am sure there are others.
We have expanded the introduction and discussion on this citing this among other studies now (lines 71-72, 276-278).
From a technical point of view, the conclusions of course rely on several assumptions, including (1) that the biomass assay is effective and (2) that the reconstructed levels of OTU diversity are accurate,
With regards to biomass although it is stated in the manuscript that "Relative eDNA copy number should be a predictor for relative biomass ", this is in fact only true if one assumes a number of things, e.g. there is a similar copy number of 18s rDNA per species, similar numbers of mtDNA per cell, a similar number of cells per individual species etc. In this regard, on the positive side, it is gratifying to see that the authors perform a validation assay on 7 mock controls, and these seem to indicate the assay works well. Given how critical this is, I recommend discussing the details of this a bit more, and why the authors are convinced the assay is effective in the main text so that the reader is able to fully decide if they are in agreement. However perhaps on the negative side, I am concerned about the strategy taken to perform the qPCR may have not been ideal. Specifically, the assay is based on nested PCR, where the authors first perform a 15cycle amplification, this product is purified, then put into a subsequent qPCR. Given how both PCR is notorious for introducing amplification biases in general (especially when performed on low levels of DNA), and the fact that nested PCRs are notoriously contamination prone - this approach seems to be asking for trouble. This raises the question - why not just do the qPCR directly on the extracts (one can still dilute the plant DNA 100x prior to qPCR if needed). Further, given the qPCRs were run in triplicate I think the full data (Ct values) for this should be released (as opposed to just stating in the paper that the average values were used). In this way, the readers will be able to judge how replicable the assay was - something I think is critical given how noisy the patterns in Fig S10 seem to be.
We agree with this point, and this is why we do not want to overstate the decline in copy number. This is an additional source of data next to genetic and species diversity. We have added to our discussion of turnover as another potential driver of copy number change (lines 257-260). We have also added text addressing the robustness of the mock community assay (lines 138-141).
However, we are confident of the reliability and robustness of our qPCR assay for the detection of relative arthropod copy number. We performed several validations and optimizations before using the assay. We have added additional details to the manuscript on this (see “Detection of relative arthropod DNA copy number using quantitative PCR”, lines 548-556). We got the idea for the nested qPCR from a study (Tran et al.) showing its high accuracy and reproducibility. We show that our assay has a very high replicability using triplicates of each qPCR, which we will now include in the supplementary data on Dryad. The SD of Ct values is very low (~ 0.1 on average). NTC were run with all qPCRs to rule out contamination as an issue in the experiments. We also find a very high efficiency of the assay. At dilutions far outside the observed copy number in our actual leaf data, we still find the assay to be accurate. We found very comparable abundance changes across our highly taxonomically diverse mock communities. This also suggests that abundance changes are a more likely explanation than simple turnover for the observed drop in copy number. A biomass loss for common species is well in line with recent reports on insect decline. We can also rely on several other mock community studies (Krehenwinkel et al. 2017 & 2019) where we used read abundance of 18S and found it to be a relatively good predictor of relative biomass.
The pattern in Fig. S10 is not really noisy. It just reflects typical population fluctuations for arthropods. Most arthropod taxa undergo very pronounced temporal abundance fluctuations between years.
Next, with regards to the observation that the results reveal an overall decrease in arthropod biomass over time: The authors suggest one alternate to their theory, that the dropping DNA copy number may reflect taxonomic turnover of species with different eDNA shedding rates. Could there be another potential explanation - simply be that leaves are getting denser/larger? Can this be ruled out in some way, e.g. via data on leaf mass through time for these trees? (From this dataset or indeed any other place).
This is a very good point. However, we can rule out this hypothesis, as the ESB performs intensive biometric data analysis. The average leaf weight and water content have not significantly changed in our sites. We have addressed this in the Methods section (see ”Tree samples of the German Environmental Specimen Bank – Standardized time series samples stored at ultra-low temperatures”, lines 308-311).
With regards to estimates of OTU/zOTU diversity. The authors state in the manuscript that zOTUs represent individual haplotypes, thus genetic variation within species. This is only true if they do not represent PCR and/or sequencing errors. Perhaps therefore they would be able to elaborate (for the non-computational/eDNA specialist reader) on why their sequence processing methods rule out this possibility? One very good bit of evidence would be that identical haplotypes for the individual species are found in the replicate PCRs. Or even between different extractions at single locations/timepoints.
We have repeated the analysis of genetic variation with much more stringent filtering criteria (see “Statistical analysis”, lines 611-615). Among other filtering steps, this also includes the use of only those zOTUs that occur in both technical replicates, as suggested by the reviewer. Another reason to make us believe we are dealing with true haplotypic variation here is that haplotypes show geographic variation. E.g., some haplotypes are more abundant in some sites than in others. NUMTS would consistently show a simple correlation in their abundance with the most abundant true haplotype.
With regards to the bigger picture, one thing I found very interesting from a technical point of view is that the authors explored how modifying the mass of plant material used in the extraction affects the overall results, and basically find that using more than 200mg provides no real advantage. In this regard, I draw the authors and readers attention to an excellent paper by Mata et al. (https://onlinelibrary.wiley.com/doi/full/10.1111/mec.14779) - where these authors compare the effect of increasing the amount of bat faeces used in a bat diet metabarcoding study, on the OTUs generated. Essentially Mata and colleagues report that as the amount of faeces increases, the rare taxa (e.g. those found at a low level in a single faeces) get lost - they are simply diluted out by the common taxa (e.g those in all faeces). In contrast, increasing biological replicates (in their case more individual faecal samples) increased diversity. I think these results are relevant in the context of the experiment described in this new manuscript, as they seem to show similar results - there is no benefit of considerably increasing the amount of leaf tissue used. And if so, this seems to point to a general principal of relevance to the design of metabarcoding studies, thus of likely wide interest.
Thank you for this interesting study, which we were not aware of before. The cryomilling is an extremely efficient approach to equally disperse even traces of chemicals in a sample. This has been established for trace chemicals early during the operation of the ESB, but also seems to hold true for eDNA in the samples. We have recently done more replication experiments from different ESB samples (different terrestrial and marine samples for different taxonomic groups) and find that replication of extraction does not provide much more benefit than replication of PCR. Even after 2 replicates, diversity approaches saturation. This can be seen in the plot below, which shows recovered eDNA diversity for different ESB samples and different taxonomic groups from 1-4 replicates. A single extract of a small volume contains DNA from nearly all taxa in the community. Rare taxa can be enriched with more PCR replicates.
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Reviewer #1 (Public Review):
In one of the most creative eDNA studies I have had the pleasure to review, the authors have taken advantage of an existing program several decades old to address whether insect declines are indeed occurring - an active area of discussion and debate within ecology. Here, they extracted arthropod environmental DNA (eDNA) from pulverized leaf samples collected from different tree species across different habitats. Their aim was to assess the arthropod community composition within the canopies of these trees during the time of collection to assess whether arthropod richness, diversity, and biomass were declining. By utilizing these leaf samples, the greatest shortcoming of assessing arthropod declines - the lack of historical data to compare to - was overcome, and strong timeseries evidence can now be used to inform the discussion. Through their use of eDNA metabarcoding, they were able to determine that richness was not declining, but there was evidence of beta diversity loss due to biotic homogenization occurring across different habitats. Furthermore, their application of qPCR to assess changes in eDNA copy number temporally and associate those changes with changes to arthropod biomass provided support to the argument that arthropod biomass is indeed declining. Taken together, these data add substantial weight to the current discussion regarding how arthropods are being affected in the Anthropocene.
I find the conclusions of the paper to be sound and mostly defensible, though there are some issues to take note of that may undermine these findings.
Firstly, I saw no explanation of the requisite controls for such an experiment. An experiment of this scale should have detailed explanations of the field/equipment controls, extraction controls, and PCR controls to ensure there are no contamination issues that would otherwise undermine the entirety of the study. At one point in the manuscript the presence of controls is mentioned just once, so I surmise they must exist. Trusting such results needs to be taken with caution until such evidence is clearly outlined. Furthermore, the plate layout which includes these controls would help assess the extent of tag-jumping, should the plate plan proposed in Taberlet et al., 2018 be adopted.
Second, without the presence of adequate controls, filtering schemes would be unable to determine whether there were contaminants and also be unable to remove them. This would also prevent samples from being filtered out should there be excessive levels of contamination present. Without such information, it makes it difficult to fully trust the data as presented.
Finally, there is insufficient detail regarding the decontamination procedures of equipment used to prepare the samples (e.g., the cryomil). Without clear explanations of the steps the authors took to ensure samples were handled and prepared correctly, there is yet more concern that there may be unseen problems with the dataset.
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whitmanarchive.org whitmanarchive.org
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Kanadia
interesting... I looked this up and (info coming from not the most reliable website) it seems as though this spelling may just have been one of Whitman's idiosyncracies. No real reason behind it, just a quirk of Whitman's
Clark, Brooke. “Walt Whitman – Wow – Canada!” Wow, https://wowcanada.wordpress.com/tag/walt-whitman/.
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www.biorxiv.org www.biorxiv.org
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Review coordinated via ASAPbio’s crowd preprint review
This review reflects comments and contributions by Luciana Gallo, Claudia Molina Pelayo, Sónia Gomes Pereira, Asli Sadli. Review synthesized by Iratxe Puebla.
The preprint examines the meiotic recombination co-factor MND1 and its role in the repair of double-strand breaks (DSBs) in somatic cells. The paper reports that MND1 stimulates DNA repair through homologous recombination (HR) but is not involved in the response to replication-associated DSBs. MND1 localization to DSBs occurs through direct binding to RAD51-coated ssDNA. MND1 loss potentiates the G2 DNA damage checkpoint and the toxicity of IR-induced damage, opening avenues for therapeutic intervention, particularly in HR-proficient tumors.
The reviewers raised some minor comments and suggestions on the work:
Results ‘Therefore, we conclude that MND1-HOP2 are ubiquitously expressed proteins’ - we understand that the study looked at the transcript's expression level and not protein levels, consider revising this sentence.
Figure 1F - Due to the differences in intensity for the loading control, recommend quantifying the normalized level of MND1.
‘we used live-cell imaging of RPE1 cells’- Are these cells p53 KO? In Suppl. Figure 1K, RPE Delpta-p53 cells are used , but the HALO tag was introduced in the normal (WT) RPE cells. Could some clarification be provided for this difference, and report what's the level of MND1 and the effects of its loss in WT RPE cells?
‘Analysis of 53BP1 foci formation and resolution in asynchronously growing RPE1 cells revealed that MND1 depletion leads to slower repair and retention of DSBs after IR (Figure 2A, Suppl. Figure 2F&G)’ - While the quantification shown in Figure 2A is explicit, the foci in the raw images displayed in Suppl. Figure 2G appears to be more frequent in the siNT, especially in the last 2 time points. It may be worth making the images bigger and maybe clearer?
‘our data show that the role of MND1 in DNA repair is most prominent in G2 phase cells and restricted to repair of two-ended DSBs’ - Can some further context be provided for the last part of this claim. Is this due to the different modes of action of the different drugs used? If so, it would be nice to clarify in the text which drugs induce the two-ended DSBs.
‘These data show that MND1 is recruited to sites of DSBs’ - The data shows that there is an increase in MND1 foci, but whether these are or not the sites of DSBs is not clear. Recommend co-staining with a known DSBs marker.
Methods
- Haploid genetic screen - Please describe how cells were fixed.
- Please detail if/what software was used for the Fisher’s exact test.
- ‘Cells were fixed after 7 days of growth in 80% methanol and stained with 0.2% crystal violet’ - Please report at which temperature and for how long the steps were completed, and provide a reference for the crystal violet reagent.
- ‘Membranes were blocked in 5% BSA’ - Please report the temperature and duration for this step.
- Please describe how the propidium iodide staining was performed.
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openvalidation.io openvalidation.io
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Machines understand languages, that are formal and rigid, with unique and unambiguous instructions that are interpreted in precisely one way. Those formal, abstract languages, and programming languages in general, are hard to understand for humans like ourselves. Primarily, they are tailored towards the requirements of the machine. The user is therefore forced to adapt to the complexity of the formal language.
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github.com github.com
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<h1>Assignment b</h1>
Header tag can be used here. ex: <Header><h1>Assignment b</h1></Header>
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scalingsynthesis.com scalingsynthesis.com
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Through a DSL for decentralized discourse graphs, we would enable people to communicate information in a machine/human readable way
The DSL for discourse graph introduced here, describes an intertwingled associative complex of domain specific terms (in a meta graph as it were) that can be used to mark and name some discourse relevant aspect of what is being talked about.
A network of such terms (a tag bundle) are used here to name pages such that they combine discourse graoh DSL terms with 'concept handles'
TrailMark symmanthetic plain text mark in notation provides the means of articulating such DSLs as you write need to read it but at first glance it seems that you are using these specific discours graph types as qualifier of content and in fact part of the identity of a page, This is what we do with TrailMarks except that leave it for the user to extend the vocabulary. You may do that as well for all I know. And indeed these 'trailmarks' as we call them are like terms in an AST for a DSL
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shrewdies.net shrewdies.net
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Hypothes.is & 📒ShrewdNotes Web Page Annotation
I'm blogging about how I'm using Hypothes.is as a starting point for documentation about 📒ShrewdNotes Web Page Annotation. Because I'm learning how to organize efficient workflows with 📒ShrewdNotes. Then I can be certain that my documentation is accurate for when I get more people involved.
So these are practical notes that guide me. In order to become reference material for anonymous learners, followers, subscribers, and members. Also, these notes can become a framework for Hypothes.is-style 📒ShrewdNotes that I can adapt for Sciwheel and other annotation services.
Hypothes.is Groups and Tags
I use Hypothes.is Groups as follows: * Public Group for Anonymous Learners. * 🗃ShrewdSubjects Groups. * My Private Group.
Public Group for Anonymous Learners
I make most of my Hypothes.is 📒ShrewdNotes in public. Mainly on my own websites. But increasingly whenever I find anything useful or interesting. Especially where I find good content relating to one of my 🗃ShrewdSubjects. So anyone can follow my Public 📒ShrewdNotes.
To recognize 🗃ShrewdSubjects, I use Hypothes.is Tags. Currently, these are Food, Gout, and Learning. Where Learning includes any topic not covered by the other subjects. In this way, as I recognize new subjects, I will separate them from Shrewd Learning.
Note that Public annotations for my subject tags include notes from all Hypothes.is users. So, tags are a great way to collect notes by everyone who is interested in a topic. Also, you can mix and match User, Group, and Tag searches. As well as using free-format search.
Additionally, I've started using Hypothes.is Tags to help me organize my workflows. Currently, I use 4, but I may extend this as I incorporate annotation into my daily life. My current 4 tags are: * New - denotes new content that I'm preparing. * Change - denotes changes I plan to make. * editing - means that I've saved the note that I'm currently working on. Or that I've forgotten to delete my
editing
tag! I use this to avoid losing text as I'm writing it, as Hypothes.is does not have autosave. Though there are ways round that. * BuildInPublic - read more at #BuildInPublic.🗃ShrewdSubjects Groups
Though I like to BuildInPublic, I also like to collaborate. Now, collaboration is possible using public annotation. But I'm trying to create services built around teams. So I've created private groups for each 🗃ShrewdSubject.
Currently, joining these private Hypothes.is groups starts by subscribing to one or more newsletters: * Foodary Nexus Newsletter * GoutPal Links Newsletter * Shrewd Learning Newsletter
My Private Web Annotation Group
I try to do most of my content creation in public. Or in teams. So I only currently have one group for private notes. But Hypothes.is allows you to create as many private groups as you need. Which is useful where you want to keep notes separate. However, I recommend using tags unless you are sure you want separate groups of notes.
Tags
Annotators
URL
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kylethayer.github.io kylethayer.github.io
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#hasjustinelanedyet
Research reports show that anger motivates people to react more than happiness and sadness. When people are angry, they will quickly spread information and discuss, and maintain a high mood. When a tag, such as # hasjustlanedyet, is searched many times, it will become a hot spot, which will further lead more curious people to search the tag.
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www.ascd.org www.ascd.org
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Reconfigure the chalk talk protocol as a graffiti tag billboard. Invite students to "tag" the "billboard" using elements of sketchnoting, doodling, collage, and written word to stimulate thinking before a discussion begins or to deepen it afterwards.
This would be a great starter for my lesson on connotation/denotation. They will need to post a lot of words for that. A graffiti board would be great.
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econfigure the chalk talk protocol as a graffiti tag billboard. Invite students to "tag" the "billboard" using elements of sketchnoting, doodling, collage, and written word to stimulate thinking before a discussion begins or to deepen it afterwards. The idea is to leverage students' comfort with multimodal expression as a way into dialogue, discussion, or debate.
Chalk talk is in my plans this week, so I will give this strategy a try!
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torrent.synology.me torrent.synology.me
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keywords
Embedded in the meta head tag.
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github.com github.com
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<img src="images/meadow.jpg" width="600" alt="meadow">
you are missing the body tag that goes after this and before the H1 entry.
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Historiska tåget i Arvidsjaur sönderslaget: ”Jag vill ge upp”
Fruktansvärt. Få tag på dessa galningar omedelbart.
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github.com github.com
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<p>I would like to become more comfortable with this type of work. I would also like to have a greater understanding of the time and effort that goes into web design. I am currently exploring and learning, and will see where it all takes me. As far as <i>this course</i> specifically, I would like to continue becoming more and more fluent in CSS and HTML, and maintain my newfound comfort with using these languages.</p> <link rel="stylesheet" href="style.css"> </body> <footer><small>This was created on September 19, 2022</small> </footer> </html> <!-- I keep getting an error here with my footer tag, but can not figure it out. -->
If this was broken up into separate lines it might be a little easier to read and edit
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<footer><small>This was created on September 19, 2022</small> </footer> </html> <!-- I keep getting an error here with my footer tag, but can not figure it out. -->
Perhaps try putting the < small > element on a separate line.
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stackoverflow.com stackoverflow.com
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Yes, using custom tags. Example in Python, making the !join tag join strings in an array:
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www.biorxiv.org www.biorxiv.org
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Note: This rebuttal was posted by the corresponding author to Review Commons. Content has not been altered except for formatting.
Learn more at Review Commons
Reply to the reviewers
Reviewer #1 (Evidence, reproducibility and clarity (Required)): ____ *A significant criticism of the paper is an assumption that readers will be familiar with all of the findings in the author's previous 2016 paper and the PGL-1 papers by Aoki et al. Minimal context is given for each approach. *
To address this concern, we have added a paragraph in the Introduction section of the revised manuscript.
*Some conclusions are not well supported and require further analysis, proper controls, and more extensive descriptions of the experiments performed. *
We have addressed the reviewer’s concerns as detailed below.
Most importantly, the central conclusion and title of the paper is that composition can buffer the dynamics of individual proteins within liquid-like condensates. In other words, in vitro condensation assays often do not recapitulate LLPS behavior in vivo. That said, the findings in this study would be significantly strengthened and complemented by observing endogenously tagged PGL-3 and PGL-3 mutants in living worms, considering the efficiency of using CRISPR in C. elegans to insert tags and make precise mutations.
The original manuscript already contained data where we microinjected wild-type PGL-3 and mutant PGL-3 proteins (recombinantly purified) into adult C. elegans gonads to assay how the P granule phase supports diffusion of these proteins.
In the revised version, we now include additional data which shows “dynamics buffering” in transgenic worms generated using CRISPR/Cas9 technology. Briefly, we used CRISPR/Cas9 to generate transgenic C. elegans which expresses PGL-3-mEGFP or PGL-3(D425-452)-mEGFP from the native pgl-3 locus. In vitro, wild-type PGL-3-mEGFP protein generates liquid-like condensates. On the other hand, the recombinantly purified PGL-3(D425-452)-mEGFP protein generates condensates that are non-dynamic. In contrast to these observations in vitro, both wild-type PGL-3-mEGFP and PGL-3(D425-452)-mEGFP show similar dynamics (half-time of FRAP recovery) within P granules in vivo.
*To improve readability, the introduction to P granules should be expanded, and include the reasons for looking at the nematode-specific PGL-3 protein among all the other known P granule proteins. A recap of previous findings on PGL-3 phase separation, in vivo and in vitro, is warranted, starting with the significant results of Saha et al 2016. Setting up the investigative questions in the context of recent work on PGL-1 (Aoki, et al) is also necessary. *
To address this concern, we have added a paragraph in the Introduction section of the revised manuscript.
The physiological concentration of PGL-3 should be more transparent, including why some experiments in this study are done at physiological concentrations while others are not. Describing why salt concentrations, crowding agents, and protein abundance are similar or different for each experiment is necessary and relevant. For example, after showing in Figure 1 that PGL-3 protein phase separates, the paragraph starting on line 161 says that it was previously shown that PGL-3 doesn't phase separate at physiological concentrations without RNA. One has to go back to Figure 1 to realize it was done differently than Figure 2 and Saha 2016.
The concentrations of PGL-3 protein and use of crowding agents (if any) have already been specified within figures or figure legends. Salt concentrations used are specified within figure legends or materials and methods section.
We have added the following paragraph to the materials and methods section of the revised manuscript.
“Saha et al. 2016 showed that at physiological concentrations (approx. 1 mM), the PGL-3 protein is unable to phase separate into condensates. At these concentrations, mRNA promotes phase separation of PGL-3. To assay for mRNA-dependence of condensate assembly, it is therefore essential to use physiological concentrations of the PGL-3 protein or mutants (e.g. Figure 2). However, these condensates are generally too small to assay rate of internal rearrangement of PGL-3 molecules within condensates using fluorescence recovery after photobleaching experiments. Therefore, to generate large condensates for measuring internal rearrangement of PGL-3 or mutant molecules, we primarily used higher concentrations of these proteins where binding to RNA is not essential for phase separation. However, to mimic the in vivo P granule phase as closely as possible, we generally added constituent proteins in proportion to their in vivo abundance estimated in Saha et al. 2016.”
The added paragraph in the Introduction section of the revised manuscript may be helpful to the readers. * *
*Statements in the same paragraph like "in contrast to full-length PGL-3, mRNA does not support phase separation..." should be qualified by stating the concentration observed, with or without salts or other crowding agents. Similarly, line 230 "suggests that interactions involving the disordered C-terminal region of PGL-3 are not essential for the fast dynamics" and should be qualified with "at non-physiological concentrations and with XX crowding agents or salt concentration." It would be more consistent if physiological concentrations were consistent from figure to figure, as extra variables weaken some of the stated conclusions. *
We thank the reviewer for this suggestion. However, we feel the statements (without full experimental details within main text) help convey the conceptual essence of the findings better. Of course, all these statements contain reference to figures or prior publications which provide relevant details about experimental conditions.
*The 2010 review reference stating that there are 40 P granule enriched proteins is outdated. More recent reviews put the number much higher. This is relevant because the approach to put PGL-3 in a more physiological environment by including just PGL-1, GLH-1 and mRNA with the condensate assays, out of ~100 P granule enriched proteins, may not be sufficient to conclude "that the influence of complex composition on dynamics is modest" (line 223), or imply that the multicomponent nature of the P granule is reconstituted by adding these components (line 355). *
We revised the text to indicate that P granules contain approx. 70 proteins and added appropriate references.
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Based on current information of constitutive P granule components (PGL-1, PGL-3, GLH-1, GLH-2, GLH-3, GLH-4, DEPS-1, MIP-1 and mRNA), (Kawasaki et al, 1998, 2004; Spike et al, 2008a, 2008b; Price et al, 2021; Cipriani et al, 2021; Phillips & Updike, 2022) we reconstituted P granule-like phase in vitro with mRNA, PGL- and GLH- proteins that likely constitute the most abundant components within P granules in vivo (based on concentration estimates in Saha et al. 2016).
We do appreciate the reviewer’s comment that more components can be added to our in vitro reconstitution in addition to the limited set of components used in our study. However, we feel it is interesting to observe that a limited set of components can support dynamics buffering (the main message of the paper). Further, the complementary in vivo experiments show that the P granule phase can also support dynamics buffering.
*Figure 1C needs to include PGL-3(370-693) in the analysis. Figure 1E is also incomplete without a comparison of FRAP recovery between PGL-3(1-452) and full PGL-3 as the control.
*
Fig. 1c already includes data with PGL-3 (370-693) [top row, central panel]. FRAP recovery data with full-length PGL-3 is already available in Supplementary Fig. 2c, g.
*Figure 4C is missing an essential control where PGL-3 and S1 FRAP is performed without PGL-1, GLH-1, and mRNA. *
In the revised version, we have added Supplementary Fig. 5f, where FRAP recovery of the following condensates are plotted together: 1) PGL-3 alone, 2) S1 alone, 3) PGL-3 + PGL-1, GLH-1 and mRNA, 4) S1 + PGL-1, GLH-1 and mRNA.
*It would also help show sup Fig4A in the main figure to show concentration dependence. *
We revised Fig. 4 to address the reviewer’s suggestion.
Consider adding subtitles to supplementary figures.
We considered the suggestion but felt it may not be essential.
*M&M should include an explanation for statistical analysis *
We added a paragraph describing statistical analysis within the Materials and Methods section.
*CROSS-CONSULTATION COMMENTS I am also in agreement with the comments and critiques of reviewers 2 and 3.
* Reviewer #1 (Significance (Required)): The paper by Saha and colleagues investigate the in vitro liquid-liquid phase separation propensity of a P granule protein PGL-3 and its structural domains. The findings largely replicate and support the phase-separation properties of a paralogous protein called PGL-1, as recently described by Aoki et al. 2021. Furthermore, they show that the dynamics demonstrated by recombinant PGL-3 may be maintained or buffered by the complex composition of P granules.
Reviewer #2 (Evidence, reproducibility and clarity (Required)):
*Jelenic et al. describe the effect of partner proteins on the FRAP dynamics of recombinant PGL-3 protein and variants in in vitro condensates and C elegans p-granules. The study shows that the N terminal a-helical dimerization domains is required for condensate formation and modulate of it alters aggregation and the FRAP dynamics of its condensates. Interestingly, a construct including the entire IDR region (370-693) by itself does not phase separate on its own at these conditions. The K126E K129E mutant (known previously to disrupt dimerization) and the deletion mutant abrogate llps. A mutant construct that shuffles the sequence in the region 423-453 called S1 here reduces the helicity and the condensate FRAP dynamics but recovered in the presence of a few P granule components. Also, the reduced dynamics of partially unfolded PGL-3 condensates are also rescued by the p-granule components to a certain degree of the unfolded PGL3 concentrations. This threshold concentration for recovering the condensate dynamics is further reduced in the helix reducing S1 mutant, which is also dependent on the number and the nature of P granule components.
Overall, the study aims to probe how "composition can buffer protein dynamics within liquid-like condensates" - yet several underlying aspects of the study do not fully support that conclusion. The introduction does not sufficiently introduce the known structural information of the two dimerization domains in C elegans PGL proteins for which structures are known. The region is discussed as "alpha helical" but really there are two evolutionarily conserved independently folding dimerization domains (referring to the mutants as "reduced alpha helicity" is not helpful - these are mutations that destabilize a folded domain).*
To address this concern, we have added a paragraph in the Introduction section of the revised manuscript.
*Additionally, the abstract and introduction ignore the aspects of aggregation (touched on in discussion) - this is likely what the disruption to the helical region in residue 450 region is doing (the helix is not on the dimer interface based on homology / sequence identity to the crystal structure of PGL-1 central dimerization domain. *
We think elucidating the molecular mechanism of apparent aggregation of PGL-3 (D425-452) could be an interesting direction for future investigation. Here, we focused our analysis predominantly on the mutant S1 since it generates liquid-like condensates with ~20- fold slower dynamics (compared to wild-type) in contrast to non-dynamic condensates/aggregates. Therefore, influence of other P granule components on the dynamics of PGL-3 in liquid-like condensates is easier to address using the mutant S1 rather than PGL-3 (D425-452). We didn’t find evidence that S1 aggregates as we did not detect aggregates of S1 molecules using fluorescence confocal microscopy and the slow dynamics in condensates of S1 does not change significantly over 24 h (Supplementary Fig. 3f).
However, in the revised version, we now include additional in vivo data with C. elegans expressing the aggregation-prone PGL-3 (D425-452)-mEGFP. Briefly, we used CRISPR/Cas9 to generate transgenic C. elegans which expresses PGL-3-mEGFP or PGL-3(D425-452)-mEGFP from the native pgl-3 locus. In vitro, wild-type PGL-3-mEGFP protein generates liquid-like condensates. On the other hand, the recombinantly purified PGL-3(D425-452)-mEGFP protein generates condensates that are non-dynamic. In contrast to these observations in vitro, both wild-type PGL-3-mEGFP and PGL-3(D425-452)-mEGFP show similar dynamics (half-time of FRAP recovery) within P granules in vivo.
Finally, the "dynamics buffering" is not really clearly established and could also be explained as small concentrations of aggregated proteins act like clients while increasing the concentration results in aggregation and "cross linking" in the entire droplet - and this concentration is never achieved in the in worm experiments so it is not clear. In other words, the change in FRAP dynamics not observed in worms is perhaps not surprising if small amount of recombinant proteins are incorporated into the granules. *
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Data with the S1 mutant establishes that dynamics buffering can be observed in condensates with different sets of additives both in vitro (Fig. 5a, b) and in vivo (Fig. 4a, b). Further, data with condensates of S1 containing the additives PGL-3 (K126E K129E) or S1 (K126E K129E) demonstrate that dynamics (half-time of FRAP recovery) within S1 condensates, and in turn “dynamics buffering” depend on inter-molecular interactions. With respect to the hypothesis proposed by the reviewer, we did not detect aggregates within S1 condensates using confocal fluorescence microscopy.
In contrast to S1 condensates, condensates containing partially unfolded PGL-3-mEGFP together with PGL-1, GLH-1 and mRNA showed spatial inhomogeneities in fluorescence signal throughout the condensate (Fig. 4g). We have not tested if areas with higher fluorescence signal represent aggregates. It is a possibility that the partially unfolded PGL-3-mEGFP fluorescence signal becomes more homogeneous if higher concentrations of additives (PGL-1, GLH-1 and mRNA) are used. However, the presented data demonstrate the significant effect of the P granule components (PGL-1, GLH-1 and mRNA) on the FRAP recovery rate of partially unfolded PGL-3-mEGFP in condensates (compare figures Fig. 3e and Fig. 4g).
However, consistent with dynamics buffering, the P granule phase in vivo supports wild-type dynamics of different PGL-3 constructs over a range of concentrations - PGL-3(D425-452)-mEGFP at physiological concentration (CRISPR transgenic strain, Fig. 4e) or at higher concentrations (microinjected S1 and partially unfolded PGL-3-mEGFP, Fig. 4b).
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*It is also not clear what the mechanism of the changes is - is the protein driven to fold more properly (despite S1 disruption of its conserved sequence) inside the condensate? Does it still self interact and act as a dimerization domain? Does this change disrupt interactions? *
We agree with the reviewer that identifying the precise structural changes of the S1 protein within the condensate vs. dilute phase could be an interesting direction for future investigation. However, we have already discussed the issues raised by the reviewer in the original manuscript.
“Our data is consistent with the model that other regions of S1 molecules cooperate with residues 425-452 (shuffled) to generate stronger inter-molecular interactions. For instance, addition of the mutant S1 (K126E K129E) enhances dynamics of S1 within condensates in contrast to maintaining the slower dynamics observed within condensates of S1 alone. This suggests that the interactions disrupted by the mutations K126E and K129E also contribute to slow S1 dynamics. One possibility is that interactions involving the residues K126 and K129 favor S1 conformations that enhance 425-452 (shuffled)-dependent interactions. Indeed, the mutations K126E K129E have been reported to interfere with interactions among N-termini of PGL-3 molecules (Aoki et al, 2021). While two self-association domains within the α-helical N-terminus of PGL-3 have been mapped (Aoki et al, 2021, 2016), structural insights into those associations are limited. However, PGL-3 shares significant sequence similarity with another protein PGL-1. Crystal structures are available for fragments of the PGL-1 protein that show the two self-association domains at the N-terminus are predominantly α-helical and globular in nature (Aoki et al, 2016, 2021). Therefore, one possibility is that shuffling the sequence 425-452 of PGL-3 or heat-induced unfolding of PGL-3 exposes hydrophobic residues that become available to participate in inter-molecular interactions.”
What is the real mechanism by which PGL-3 phase separates if not via the disordered domains? *
*
We agree with the reviewer that elucidating the detailed mechanism of phase separation of PGL-3 is an interesting direction for future investigation. However, we feel this is not required to support the main message of this manuscript.
Throughout the manuscript, the term "dynamics" is used to indicate FRAP, but it would be better to define what is meant (diffusion of PGL-3 in condensates) instead of using dynamics a term that could mean many things. Secondly, FRAP cannot directly measure liquidity etc (see recent critiques by McSwiggen elife 2019, etc) so it is better to be cautious in the claims. Finally, discussing "dyanmics buffering" adds more terminology where it is not needed - perhaps say "changes to diffusion of PGL-3 in condensates".
We feel it is useful to introduce a term that describes our observation. To our knowledge, our observation is novel and therefore requires a new term to describe it.
However, we do appreciate the concern raised by the reviewer. We used a more generic term “dynamics buffering” in contrast to the more specific “diffusion buffering” since we did not directly estimate diffusion behavior at the ‘single-molecule’ level. However, we already described what we mean by “dynamics buffering” in the text as follows.
“We used condensates of similar size for our analysis (average ± 1 SD of diameter of condensates are 6.4 ± 1.7 mm (Fig. 5a) and 5.9 ± 0.4 mm (Fig. 5b)). Therefore, dynamics buffering here is likely to represent similar diffusion rates of S1 within condensates.”
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*The "N-terminus" is not 65% of the protein. One could define this as the N-terminal domain, but again there are two clear folded domains in the first 65% of the protein and this needs to be described better. *
We revised the text to replace the terms “N-terminus” and “N-terminal domain” to “N-terminal fragment”.
*The description of "stickers" and the references to tau and hnRNPA1 are confusing as this is a predominantly ordered domain while those are IDRs. *
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We feel this is important as it aids discussing our work in the context of current literature describing the mechanisms of macromolecular phase separation.
The suggestion in the discussion that "P granule components support dynamics by participating in intermolecular interactions wth PGL-3-mEGFP molecules" is not well supported because no interaction assays are performed and no mutaitons are made that disrupt these interactions to test this.
Indeed, we have not conducted interaction assays or mutational analysis to directly test this. However, our detailed analysis with the S1 mutant supports this suggestion.
While partially unfolded PGL-3-mEGFP molecules lose 30% of a-helicity, the a-helicity of the S1 mutant is reduced by 15% compared to wild-type PGL-3. Data with S1 and partially unfolded PGL-3-mEGFP molecules show that loss of a-helicity correlates with slower diffusion of protein molecules within condensates. Using the mutants PGL-3 (K126E K129E) and S1 (K126E K129E), we show that diffusion rate of S1 molecules within condensates depend on inter-molecular interactions, and presence of other P granule components support faster diffusion rate of S1 molecules within condensates. Therefore, we feel it is safe to speculate that intermolecular interactions with P granule components can support dynamics of a “more unfolded” (compared to S1) version of PGL-3 molecule. * *
*More detailed analysis of some of the claims: Claim 1: An a-helical region mediates the phase separation of PGL-3, and the C-terminal disordered region by itself does not phase separate. The N-terminal dimerization is essential for LLPS. The C-terminal IDR interactions with mRNA facilitate the LLPS. Comments: The authors show sufficient experimental data using microscopy and FRAP on truncated constructs with the N-terminal and C-terminal regions - but see above regarding how these are described - a proper domain structure with the folded domains shown and the RGG motifs highlighted should be added and integrated throughout the discussion. *
In the revised version of the manuscript, we described the predicted PGL-3 domains within a paragraph in the introduction: “The interactions that support phase separation of the PGL-3 protein remains unclear. Structural studies on the orthologous PGL-1 protein revealed two dimerization domains. This raises the possibility that PGL-3 also contains similar dimerization domains, and phase separation depends on interactions involving these domains.”
Our Fig. 1a already includes the schematic representation of PGL-3 with predicted N-terminal and Central Dimerization domains and RGG repeats.
*They show that the N-terminus is necessary and adequate for LLPS, and the C-terminus by itself does not phase separate. But, how does the N-terminal domains phase separate? This is not explained - what are the interactions? *
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Also, a di-mutant (K126E K129E) that is known, and also authors use SEC-MALS to show their N-terminal construct is consistent with the published results. Disrupting the n-terminal dimerization prevents phase separation, suggesting the importance of these residues in the N-terminus for self-assembly and LLPS. The Microscopy data backs the claim that the mRNA-mediated LLPS is facilitated by binding with C-terminus. However, the m-RNA binding to IDR is not sufficient for LLPS. Yet, the authors do not explain how higher salt prevents phase separation - again the mechanism of phase separation is unclear. Is it multivalent interaction of the two dimerization domains? A basic model (that is tested) would be important.
We agree with the reviewer that elucidating the detailed mechanism of phase separation of PGL-3 is an interesting direction for future investigation. However, we feel this is not required to support the main message of this manuscript.
However, our manuscript already provides some relevant insights as follows.
“To investigate the underlying mechanism further, we began by testing if the N-terminal α-helical region of PGL-3 can self-associate. Our analysis using size exclusion chromatography followed by multi-angle light scattering (SEC-MALS) showed that this PGL-3 fragment 1-452 forms a dimer (Supplementary Fig. 2f). Mutation of two residues (K126E K129E) have been shown to interfere with interactions among the N-termini of PGL-3 molecules (Aoki et al, 2021). We mutated these two residues within the full-length PGL-3 protein (K126E K129E) (Fig. 1a) and found that this mutant PGL-3 (K126E K129E) protein cannot phase separate even at high protein concentrations up to ~130 µM (Fig. 1b, c). Addition of mRNA does not trigger phase separation of this protein at physiological concentrations either (Fig. 2a, b). Taken together, our data is consistent with a model where association among folded N-termini of PGL-3 molecules is essential for phase separation.”
A likely possibility is that phase separation of PGL-3 depends on electrostatic inter-molecular interactions among the folded N-terminal fragment of PGL-3 molecules. Therefore, high salt prevents phase separation.
Are the tags removed to ensure that phase separation is not caused by tags or remaining linker regions? Is the protein purified to be without nucleic acid contamination or other purity metrics?
Most of the experiments were done with only 5% of total protein tagged with 6x-His-mEGFP. No additional tags were present on the constructs. For recombinant expression and purification, proteins were cloned such that it is possible to remove the 6xHis-mEGFP tag following treatment with TEV protease. Following removal of the 6xHis-mEGFP tag, the residual linker is just two amino acid residues long. We used 100% tagged-protein for our experiments only in very few cases (indicated in the figure legends).
To demonstrate purity of recombinant proteins, SDS-PAGE gels with all protein constructs used in this study are shown in Supplementary Fig. 1.
To minimize contamination of nucleic acids, we treated samples with Benzonase during the course of purification.
To assess the extent of nucleic acid contamination, the ratio of absorbance at 260 nm and 280 nm (A260/A280) was monitored. In exceptional cases with high A260/A280 values, we analyzed samples further by purifying RNA from the sample using RNA purification kit (Qiagen) and found that RNA represented 1% or less of the sample mass.* *
Claim2: The N-terminal a-helical region modulates the dynamics within condensates. The IDR region has minimal effect on the fast dynamics of PGL-3. Comments: The authors show that the full-length PGL-3 condensates have modest influence of components by comparing the FRAP half times with or without the P granule components, including mRNA. However, have the authors tried this in the presence of mRNAs for the constructs lacking the IDRs as they have several RGG domains and bind with mRNA and are likely to change the dynamics.
We thank the reviewer for this suggestion. However, this experiment is not essential to support the claim made in the context of homotypic condensates of PGL-3 : “The N-terminal a-helical region modulates the dynamics within condensates. The IDR region has minimal effect on the fast dynamics of PGL-3.”
*The authors report the importance of the N-terminal a-helical region by making a construct that lacks/disrupts a part of the helices lowers the thermal stability and significantly lowers the dynamics of the condensates. Also unfolding of helices is shown to reduce the dynamics. One primary concern is whether these "rescued" protein dynamics imply protein functionality. *
An assay of “functionality” e.g. an enzymatic activity of the PGL-3 protein is not available.
However, we compared the fecundity of C. elegans worms expressing from the native pgl-3 locus, PGL-3-mEGFP or the mutant protein PGL-3(D425-452)-mEGFP, to assay the functionality of P granules in these strains. We found that worms of both genotypes produced similar number of offspring (Fig. 4d). This suggests that deletion of residues 425-452 of PGL-3 does not result in significant loss of function of P granules.
Are these semi denatured proteins refolded in the presence of P-granule components?
We feel that identifying the precise structural changes of the semi-denatured PGL-3 proteins within the condensate vs. dilute phase could be an interesting direction for future investigation.
Finally, it is not clear why the authors chose to disrupt folding of the central dimerization domain?
The manuscript included a paragraph to describe the rationale.
“This suggests that interactions involving the disordered C-terminal region of PGL-3 are not essential for the fast dynamics within condensates. Therefore, we addressed the role of the N-terminal α-helical region (1-452) in driving dynamics. In order to avoid engineering mutations that result in significant misfolding of PGL-3 and concomitant loss of its ability to phase separate, we focused our mutational analysis close to the junction of the folded N-terminus and the disordered C-terminus of PGL-3. Surprisingly, we found that a full-length PGL-3 construct (D425-452) that lacks only 27 residues phase separates into condensates that are non-dynamic (Fig. 3a, c). Sequence analysis of the PGL-3 protein predicts that this region 425-452 spans two α-helices (one complete helix and fraction of a second helix) (Supplementary Fig. 3d). We generated a PGL-3 construct (hereafter called ‘S1’) (Fig. 3a) in which the sequence in the region, 425-452, is shuffled while keeping the overall amino acid composition unchanged. We found that S1 phase separates into condensates that are 20- fold less dynamic than with wild-type PGL-3 (Fig. 3d, Supplementary Fig. 3c).”
Saying that "reduced alpha-helicity of PGL-3 correlates with slower dynamics in condensates" may be factual in these assays but "correlation" should be expanded upon to include mechanism and to me it seems that the statement should read "aggregation of PGL-3 causes slower dynamics in condensates" (both the partially destabilized mutant and the fully unfolded WT show similar effects perhaps to different degrees).
We feel that identifying the precise structural changes of the semi-denatured PGL-3 proteins within the condensate vs. dilute phase could be an interesting direction for future investigation.
We did not use the term "aggregation" since we did not detect aggregates of S1 molecules using fluorescence confocal microscopy.
*CROSS-CONSULTATION COMMENTS I agree with the other reviewer's comments and critiques, I have concerns about the biological relevance and also the biophysical mechanisms. Reflecting on the other reviewers' comments, the papers could provide more depth in one or both of these areas to come to firm conclusions that are either revealing about PGL biology or elucidate a (possible) general biophysical mechanism. *
In the revised version, we now include additional data which shows “dynamics buffering” in transgenic worms generated using CRISPR/Cas9 technology. Briefly, we used CRISPR/Cas9 to generate transgenic C. elegans which expresses PGL-3-mEGFP or PGL-3(D425-452)-mEGFP from the native pgl-3 locus. In vitro, wild-type PGL-3-mEGFP protein generates liquid-like condensates. On the other hand, the recombinantly purified PGL-3(D425-452)-mEGFP protein generates condensates that are non-dynamic. In contrast to these observations in vitro, both wild-type PGL-3-mEGFP and PGL-3(D425-452)-mEGFP show similar dynamics (half-time of FRAP recovery) within P granules in vivo.
Reviewer #2 (Significance (Required)): *Hence, although the authors shows how inclusion of other components can alter the one protein component phase separation, this is done with entirely artificial means of destabilizing the fold of one of the domains which likely leads to aggregation. So the true impact of the work is hard to understand because the mutations impact on the basic biophysical properties of the domain (stability, interaction) are not completely characterized and the reason for disrupting this folding is not clear. *
A major impact of our work is elucidation of a novel “dynamics buffering” property within biomolecular condensates in vitro. Our in vivo data is consistent with this finding.
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We have chosen two orthogonal ways of perturbing the PGL-3 protein (i.e. mutations and temperature-dependent unfolding) to assay the effect on diffusion rate against different levels of perturbation (e.g. 30% loss of a-helicity in heat-denatured PGL-3-mEGFP vs. 15% loss of a-helicity in the S1 mutant, compared to wild-type PGL-3). Studying the phase separation behavior of these “artificially-generated” constructs provided the understanding that dynamics of PGL-3 in condensates depends on inter-molecular interactions, and slower dynamics generally correlate with stronger inter-molecular interactions. Further, interactions among two or more P granule components can buffer against large change in dynamics / aggregation within the P granule phase. These insights may lay the groundwork for addressing how more “natural” modifications (e.g., post-translational modifications, high local concentration of “sticky” molecules) may influence dynamics within biomolecular condensates in vivo.
Based on current knowledge of P granule composition, chaperone proteins (e.g. heat-shock family proteins) do not show abundant concentration within P granules. However, it is unclear if chaperone proteins are completely excluded from the P granule phase. Therefore, we speculate that weak interactions among two or more non-chaperone proteins contribute significantly to “dynamics buffering” within the P granule phase in vivo.
In the discussion section of the manuscript, we had speculated that “dynamics buffering” may potentially explain observations reported in the nucleolus: “Similarly, interactions among components could be a potential mechanism of storage of misfolding-prone proteins in non-aggregated state within the liquid-like nucleolus under stress in vivo (Frottin et al, 2019).”
Our finding is also relevant in the context of synthetic biology with applications that require steady diffusion rate of macromolecules during biochemical reactions within biomolecular condensates.
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My field of expertise is protein phase separation and protein structure. * *
Reviewer #3 (Evidence, reproducibility and clarity (Required)):
Summary: P granules are liquid condensates found in the developing germlines and embryos of C. elegans. Prior work by the authors and others have established P granules as a tractable model to investigate the basic biophysical properties of liquid condensates. Much of the prior published work focused on specific P granule scaffold proteins, PGL-1 and PGL-3. How attributes of these PGL proteins and the effect of other P granule components affect condensate properties is not fully understood. Here, Jelenic, et al. probe the biophysical properties of PGL-3. Using recombinant protein, they show that an N-terminal, alpha-helical region of PGL-3 is sufficient for liquid condensate formation and that N-terminal assembly is required for this formation. Creation of a scrambled alpha-helical region in PGL-3 and heat treatment affects PGL-3 fluidity. This fluidity can be "rescued" in vivo and in vitro with the inclusion of other P granule factors, including wildtype PGL-3, PGL-1, GLH-1 and mRNA. The authors note an inverse correlation between fluidity and mutant PGL-3 fluorescent intensity. They propose a model that heterotypic compositions of condensates can buffer their fluidity against components with stronger multivalent interactions. *
MAJOR: 1. PGL-3 is a fantastic model to study the biophysical properties of a liquid condensate. But as the authors address in their discussion, the S1 mutant will likely affect the central domain folding, at its minimum causing exposure of a hydrophobic surface not typically exposed in biology. These helices are found at the terminal portion of the domain determined in the crystal structure and as depicted in the authors' Figure 1A. While the cause of S1's enhanced molecular interactions does not affect the in vitro work presented in this manuscript, it does affect how the conclusions connect to the biological nature of P granules and liquid condensates more generally. *
We have chosen two orthogonal ways of perturbing the PGL-3 protein (i.e. mutations and temperature-dependent unfolding) to assay the effect on diffusion rate against different levels of perturbation (e.g. 30% loss of a-helicity in heat-denatured PGL-3-mEGFP vs. 15% loss of a-helicity in the S1 mutant, compared to wild-type PGL-3). Studying the phase separation behavior of these “artificial” constructs provided the understanding that dynamics of PGL-3 in condensates depends on inter-molecular interactions, and slower dynamics generally correlate with stronger inter-molecular interactions. Further, interactions among two or more P granule components can buffer against large change in dynamics / aggregation within the P granule phase. These insights may lay the groundwork for addressing how more “natural” modifications (e.g., post-translational modifications, high local concentration of “sticky” molecules) may influence dynamics within biomolecular condensates in vivo.
Based on current knowledge of P granule composition, chaperone proteins (e.g. heat-shock family proteins) do not show abundant concentration within P granules. However, it is unclear if chaperone proteins are completely excluded from the P granule phase. Therefore, we speculate that weak interactions among two or more non-chaperone proteins contribute significantly to “dynamics buffering” within the P granule phase in vivo.
In the discussion section of the manuscript, we had speculated that “dynamics buffering” may potentially explain observations reported in the nucleolus: “Similarly, interactions among components could be a potential mechanism of storage of misfolding-prone proteins in non-aggregated state within the liquid-like nucleolus under stress in vivo (Frottin et al, 2019).”
Our finding is also relevant in the context of synthetic biology with applications that require steady diffusion rate of macromolecules during biochemical reactions within biomolecular condensates.
- Recombinant PGL-3 experiments added PGL-1, GLH-1 and mRNA simultaneously and measured fluidity. It will be interesting to know which components contribute to fluidity and whether fluidity enhancement of each component is dependent on one another. Addition experiments with each component should be included and/or at least discussed in the main text. *
Our data with S1-mEGFP or PGL-3-mEGFP (pre-heated at 50°C) proteins microinjected into C. elegans gonads, and the transgenic strain expressing PGL-3(D425-452)-mEGFP from the pgl-3 locus showed that the P granule phase can support fast dynamics of these mutant PGL-3 constructs. Since P granules have a complex composition, one possibility is that fast dynamics of these constructs is supported by interactions involving many P granule components. We found that using only a limited set of P granule components (PGL-1, GLH-1 and mRNA) can buffer dynamics of S1 in condensates in vitro.
In absence of a systematic analysis investigating the individual role of approx. 70 P granule proteins in buffering S1 dynamics in condensates in vitro, we have claimed in the text that dynamics-buffering of S1 in condensates is supported by interactions among two or more components. However, we do appreciate the reviewer’s comment and feel it would be interesting to investigate the contribution of individual P granule components towards fluidity in future studies. We have discussed this in the ‘Discussion’ section of the manuscript.
- The biological relevance of PGL-1, GLH-1, and mRNA were not discussed in the main text. How these factors contribute to P granule assembly and function should be mentioned in the Introduction or Results. *
To address this concern, we have added a paragraph in the Introduction section of the revised manuscript.
*MINOR: 1. Line 20, "most non-membrane-bound compartments...have complex composition": Are there examples of condensates that do not have complex composition? *
Not all non-membrane-bound compartments may have been characterized. To accommodate this possibility, we refrained from making a more general statement, but stated “most non-membrane-bound compartments…”.
- Lines 40-43, RNA interactions driving LLPS: Please include citations from the Parker Lab (e.g. Van Treeck and Parker, Cell. 2018 doi: 10.1016/j.cell.2018.07.023) *
We added the reference suggested by the reviewer.
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Line 60, condensates contain hundreds of different proteins and RNA: Please cite at least a few examples of condensates with their components identified. *
We added some references following suggestion by the reviewer.
- Lines 82-84, PGL-3 drives assembly: Please cite Kawasaki, et al. Genetics 2004 for the discovery of PGL-3. *
We added the reference suggested by the reviewer.
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Lines 88-89, PGL-3 N-terminal fragment predominantly alpha-helical: The PGL domain structures should be cited here as supporting evidence that these regions are composed primarily of alpha helices (Aoki, et al 2016, 2021) *
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To address this concern, we have added a paragraph in the Introduction section of the revised manuscript.
- Lines 158-159, driving forces for phase separation: This statement should be removed or expanded. The authors point regarding the protein concentrations is not clear here but clarified in the Discussion (Lines 691-693). Recommend removing due to its speculative nature. *
We retained the speculative comment in the results section. We feel that this prepares the readers for the discussion later in the manuscript.
- Lines 210: Add commas before and after "PGL-1 and GLH-1"*
We addressed the reviewer’s suggestion.
- Lines 218-219: add "and" instead of comma between PGL-1 and GLH-1 *
We addressed the reviewer’s suggestion.
- Lines 238-239, alpha-helices: The PGL CDD structure should also be referenced here (Aoki, et al 2016). *
To address this concern, we have added a paragraph in the Introduction section of the revised manuscript.
- Lines 680-682, MEG proteins: Please cite accordingly. *
We added the reference suggested by the reviewer.
- Lines 694-695, heterotypic interactions: Please cite Saha, et al. 2016. *
We added the reference suggested by the reviewer.
- Figure 1: Add space between 1 and mM DTT *
We addressed the reviewer’s suggestion.
- Figure 2b: Please provide statistics between condensate numbers. *
We provide statistics between condensate numbers in Fig. 2b.
- Figure 4A: The region of the germline imaged and analyzed should be mentioned in the caption or the main text. *
We revised the Figure legend of Fig. 4a to address this issue.
- Figure 4B,C: Please include statistics between the FRAP curves. *
We have included statistics comparing FRAP curves in Supplementary Fig. 4a-c.
- Figure 4D: It will be helpful to compare this curve to Figure S4A in the same graph. Please also include graph statistics. *
We have revised Fig. 4 to address the reviewer’s suggestion.
- Figure 5: The data points are difficult to resolve. Recommend use of color.*
We considered the suggestion, but felt it works better in the original form.
- Figure 6: This is a very general model that does not highlight the extensive experimental work performed by the authors. Recommend incorporating PGL-3, mutants and P granule factors into this model. *
We thank the reviewer for appreciating our extensive work. However, we retained the original Fig. 6 for the sake of simplicity.
- Methods, Line 939, C. elegans section: What worms were used? TH623? Please describe the genotype. *
We have included a table listing the strains used in the study and their genotype. * CROSS-CONSULTATION COMMENTS While my review was arguably the more favorable of the three, I agree with the other reviewers' comments and evaluation, particularly with Reviewer #1. As written in my review, my primary concern was the biological relevance of the work.*
Reviewer #3 (Significance (Required)):
Overall, the in vitro work presented investigating the biophysical properties of this minimal P granule system was thorough and well-analyzed, and the manuscript was clearly written. Additional citations and statistics will improve the manuscript and the strength of the conclusions, respectively. The biological relevance of this study to P granule form and function in vivo, and to condensates in vivo, is debatable. This work will interest those who study condensate biology, the biophysics of protein-protein and protein-RNA interactions, and RNA biochemists more generally.
A major impact of our work is elucidation of a novel “dynamics buffering” property within biomolecular condensates in vitro. Our in vivo data is consistent with this finding.
We have chosen two orthogonal ways of perturbing the PGL-3 protein (i.e. mutations and temperature-dependent unfolding) to assay the effect on diffusion rate against different levels of perturbation (e.g. 30% loss of a-helicity in heat-denatured PGL-3-mEGFP vs. 15% loss of a-helicity in the S1 mutant, compared to wild-type PGL-3). Studying the phase separation behavior of these “artificially-generated” constructs provided the understanding that dynamics of PGL-3 in condensates depends on inter-molecular interactions, and slower dynamics generally correlate with stronger inter-molecular interactions. Further, interactions among two or more P granule components can buffer against large change in dynamics / aggregation within the P granule phase. These insights may lay the groundwork for addressing how more “natural” modifications (e.g., post-translational modifications, high local concentration of “sticky” molecules) may influence dynamics within biomolecular condensates in vivo.
- *
Based on current knowledge of P granule composition, chaperone proteins (e.g. heat-shock family proteins) do not show abundant concentration within P granules. However, it is unclear if chaperone proteins are completely excluded from the P granule phase. Therefore, we speculate that weak interactions among two or more non-chaperone proteins contribute significantly to “dynamics buffering” within the P granule phase in vivo.
In the discussion section of the manuscript, we had speculated that “dynamics buffering” may potentially explain observations reported in the nucleolus: “Similarly, interactions among components could be a potential mechanism of storage of misfolding-prone proteins in non-aggregated state within the liquid-like nucleolus under stress in vivo (Frottin et al, 2019).”
Our finding is also relevant in the context of synthetic biology with applications that require steady diffusion rate of macromolecules during biochemical reactions within biomolecular condensates.
*I have expertise in P granules, protein/RNA biochemistry, condensate assembly, and C. elegans. *
References
Aoki ST, Kershner AM, Bingman CA, Wickens M & Kimble J (2016) PGL germ granule assembly protein is a base-specific, single-stranded RNase. Proceedings of the National Academy of Sciences of the United States of America
Aoki ST, Lynch TR, Crittenden SL, Bingman CA, Wickens M & Kimble J (2021) C. elegans germ granules require both assembly and localized regulators for mRNA repression. Nat Commun 12: 996
Cipriani PG, Bay O, Zinno J, Gutwein M, Gan HH, Mayya VK, Chung G, Chen J-X, Fahs H, Guan Y, et al (2021) Novel LOTUS-domain proteins are organizational hubs that recruit C. elegans Vasa to germ granules. Elife 10: e60833
Frottin F, Schueder F, Tiwary S, Gupta R, Körner R, Schlichthaerle T, Cox J, Jungmann R, Hartl FU & Hipp MS (2019) The nucleolus functions as a phase-separated protein quality control compartment. Science 365: 342–347
Kawasaki I, Amiri A, Fan Y, Meyer N, Dunkelbarger S, Motohashi T, Karashima T, Bossinger O & Strome S (2004) The PGL family proteins associate with germ granules and function redundantly in Caenorhabditis elegans germline development. Genetics 167: 645–661
Kawasaki I, Shim YH, Kirchner J, Kaminker J, Wood WB & Strome S (1998) PGL-1, a predicted RNA-binding component of germ granules, is essential for fertility in C. elegans. Cell 94: 635–645
Phillips CM & Updike DL (2022) Germ granules and gene regulation in the Caenorhabditis elegans germline. Genetics 220: iyab195
Price IF, Hertz HL, Pastore B, Wagner J & Tang W (2021) Proximity labeling identifies LOTUS domain proteins that promote the formation of perinuclear germ granules in C. elegans. Elife 10: e72276
Saha S, Weber CA, Nousch M, Adame-Arana O, Hoege C, Hein MY, Osborne Nishimura E, Mahamid J, Jahnel M, Jawerth L, et al (2016) Polar Positioning of Phase-Separated Liquid Compartments in Cells Regulated by an mRNA Competition Mechanism. Cell 166: 1572-1584.e16
Spike C, Meyer N, Racen E, Orsborn A, Kirchner J, Kuznicki K, Yee C, Bennett K & Strome S (2008a) Genetic analysis of the Caenorhabditis elegans GLH family of P-granule proteins. Genetics 178: 1973–1987
Spike CA, Bader J, Reinke V & Strome S (2008b) DEPS-1 promotes P-granule assembly and RNA interference in C. elegans germ cells. Development (Cambridge, England) 135: 983–993
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Consolidated peer review report (9 September 2022)
GENERAL ASSESSMENT
This interesting preprint by Suárez-Delgado et al. explores the mechanism by which activation of the Hv1 voltage-activated proton channel is dependent upon both the voltage and pH difference across the membrane. The authors are the first to incorporate the fluorescent unnatural amino acid, Anap, into the extracellular regions of the S4 helix of human Hv1 to monitor transitions of S4 upon changes in voltage or pH. The authors first checked that Anap is pH insensitive for practical use in Hv1, where changes in local pH are known to occur when the voltage sensor activates and the proton pore opens. Anap was incorporated at positions throughout the S3-S4 linker and the extracellular end of S4 (up to the 202nd residue) of hHv1 and some positions showed clear voltage-dependent changes in fluorescence intensity. The authors also obtained fluorescence spectra at different voltages and observed no spectral shifts, raising the possibility that voltage dependent changes in fluorescence intensity could primarily be due to fluorescence quenching. Upon mutation of F150, the Anap signal at the resting membrane voltage increased, suggesting dequenching upon removal of F150. The authors also discovered that the kinetics of Anap fluorescence upon membrane repolarization have two phases (rapid and slow) under certain pH conditions and that there is a pH- dependent negative shift of the conductance-voltage (G-V) relation compared with the fluorescence-voltage (F-V) relation in some mutants. The biphasic kinetics of the fluorescence decay upon repolarization were explained by modelling a slower transition of return from intermediate resting state to a resting state. The pH-dependent shift of the G-V relation from the F-V relation provides insight into mechanisms of ΔpH-dependent gating of Hv1, a longstanding enigma. Overall, the approaches are rigorous, the figures show important results, and this work paves the way for the use of Anap fluorescence to study Hv1 gating and modulation.
RECOMMENDATIONS
Revisions essential for endorsement:
1) In its current form, the narrative of the preprint has two threads. One on the mechanisms of Anap fluorescence changes (mainly quenching) and another on a previously unappreciated transition of the voltage sensor, as revealed by Anap. Our impression is that the preprint suffers somewhat from this split focus, which could be resolved by explaining why Anap was used to explore voltage sensor activation in Hv1 in the introduction. Perhaps the authors could also explain the advantage of smaller sized fluorophores compared to other maleimide-based fluorophores earlier in the introduction, or the utility of being able to insert Anap into transmembrane segments. The authors should more clearly point out how they exploited the advantages of Anap as a tool in this study. It would furthermore be helpful to discuss previous studies using nongenetic tools for VCF and spell out how they have delineated key aspects of Hv1, which would help to emphasize how several positions studied here (for example, 201 and 202) could not be labelled with cysteine-based fluorophores.
2) We think the authors should be cautious about understanding the physicochemical nature of Anap using prodan as a model. It would be helpful to discuss the possibility that undetected spectral shifts due to a nonquenching mechanism could be overlooked, even though major signal changes can be explained by fluorescence quenching in their data. Regarding the mechanisms of remaining voltage-dependent fluorescence changes of F150A-A197Anap, it would be helpful for the authors to suggest possible ideas about which residues might account for remaining signals.
The beautiful spectral data for Anap is impressive. However, the physicochemical basis of the fluorescence change of Anap cannot be understood by simple extension of findings for prodan, which shows structural similarity to Anap. Our understanding is that changes in Anap fluorescence can only reveal a change in the structural relationship between Anap and one of its neighbors because the physicochemical basis of Anap fluorescence is complicated. For example, fluorescence could also be affected by the electrostatic environment, stretch of peptide bond, etc. Previous studies, including those of TRP channels, showed that the kind of environmental changes that Anap faces in ion channels do not necessarily induce large spectral shifts, unlike in cell-free spectral analyses using distinct solvents. Further, only minor shifts in spectra occur upon local structural change, as seen in previous work including Xu et al. Nat. Commun. 2020 11:3790. Such minor shifts could be perhaps overlooked even when Anap is incorporated into S4 and exposed to environmental change. Therefore, it is not easy to decode the physicochemical basis of Anap fluorescence changes. F150A-A197Anap has increased fluorescence and no change in spectral pattern, leading the authors to conclude that F150 quenches Anap fluorescence of A197 position. However, a significant amount of fluorescence change still occurs upon changes in membrane potential after F150 is changed to alanine (Figure 4). It is very likely that quenching is not the only mechanism underlying the observed voltage induced change of Anap fluorescence of Hv1. The authors suggest that remaining voltage-dependent fluorescence change of F150A-A197Anap could be due to interaction with other aromatic residues, but this has not been tested.
3) The current version of the preprint is missing important control experiments, ideally performed using western blots to measure protein expression or, if that is not possible, proton current and fluorescence measurements, to demonstrate that protein expression or functional channels are not seen for all mutants in the absence of ANAP (but in the presence of the tRNA and Rs construct). A similar control for imaging would be to use ANAP alone without encoding.
4) Aromatics in the S4 segment were ruled out as potential quenchers on the assumption that they would move together with Anap during gating. It should be noted, however, that Hv1 is a dimer and therefore a fluorophore attached to S4 in one subunit could be quenched by S4 aromatics in the neighboring subunit if were close to the dimer interface. In Fujiwara et al. J. Gen. Physiol. 2014 143:377-386, for example, W207 does not appear very far from labeled positions in the adjacent S4. This possibility should be mentioned in the discussion.
5) It is not clear whether the Anap spectra purely represent Hv1 incorporated into the plasma membrane or perhaps include signals from the cytoplasm or channels in internal membranes (whether assembled or incompletely assembled). It would be helpful to provide a more complete presentation of the data obtained and to provide more information in the Methods Section. In the Methods section, it is stated “The spectra of both fluorophores (Anap and mCherry) were recorded by measuring line scans of the spectral image of the cell membrane, and the background fluorescence from a region of the image without cells was subtracted”. How are signals from cell membranes specified in this method being discriminated from those associated with the cytoplasm and intracellular membranes? If spectral data include signals from free Anap in the cytoplasm or Hv1 in intracellular membranes, spectral shifts upon membrane potential changes will be difficult to detect, even when Anap is incorporated into Hv1 and senses environmental change by voltage-induced conformational change. In Figure 3E, wavelength spectra were shown as standardized signals for different voltages. Amplitude change would be demonstrated (spectrum at different voltages without standardization would be shown). In Figure 4, spectra were compared between A197Anap and F150A-A197Anap, showing increases of fluorescence in F150A-A197Anap. Was this signal measured at resting membrane potential? How does the spectrum change when the membrane potential is changed?
Rationales for the confirmation of signals originating from the cell surface for Hv1 Anap might include the observations that: a) some mutants showed slightly different spectral patterns (in particular, Q191Anap showed a small hump at longer wavelengths, which is proposed to represent FRET between mCherry and Anap) and b) signal intensity was voltage dependent (if signals originate from endomembranes, they should not be voltage dependent). Mentioning these two points earlier in the text might help to alleviate concerns about the location of the protein that contributes to the measured signals.
6) In Fig 5, the fluorescence kinetics do not really match the current activation kinetics for panels A, B, and C. Is there an explanation for this mismatch? It would be helpful to have the fitted data in the figure. A more thorough comparison of the kinetics of currents and fluorescence would be helpful throughout the study.
7) Which construct of hHv1 was used to obtain the data in Figure 6? Unless we missed it, this information is not provided in the text or figure legend. Is it for L201Anap? This figure also shows an intriguing finding that the G-V relationship is negatively shifted from the F-V relationship at pHo7-pHi7 but not at pHo5.5-pHi5.5. A shifted G-V relation with the same ΔpH contrasts with what has been reported in other papers. However, the authors did not really discuss this surprising finding in the light of previous references. Could the shift of the G-V relation between two pH conditions with the same ΔpH be due to any position-specific effect of Anap? If Figure 6 represents L201Anap mutant, the presence of Anap at L201 probably makes such shift of G-V curve in Figure 6C? The authors should openly discuss this finding in relation to what has been reported in the literature.
8) The authors suggest that the small hump near 600 nm in Figure 1E represents FRET between Anap and mCherry. It is surprising that FRET can take place across the membrane. Can the authors point to another case of FRET taking place across a cell membrane? One possibility might be that misfolded proteins place mCherry and Anap close to each other. It is also curious that only A191Anap did not show such a FRET-like signal. Also, if there is FRET, why wouldn’t this also contribute to the voltage-dependent changes in fluorescence?
9) F150A-A197Anap shows a leftward shift of the F-V relation compared with the G-V relation only when ΔpH=1. Another unusual finding with F150A-A197Anap is the very small shift of the G-V relation between ΔpH=0 and ΔpH=1, when other reports in the literature suggest it should be 40 mV or more. Are these peculiar properties simply due to the absence of Phe at position 150, which might play a critical role in gating as one of the hydrophobic plugs of Hv1? To address this possibility, it would be ideal to compare different ΔpH values with and without F150 when Anap is incorporated at a different position (such as L201Anap). Regardless, it would be helpful to discuss this point.
10) In Figure 1E, I202Anap exhibits a blue shift in its spectrum suggesting the environment of Anap on I202 is more hydrophobic than the other sites. We presume these spectra were obtained at a negative membrane voltage, but the text or legend should clearly state how these were obtained. The authors should also explain whether the whole cell or edge was imaged. If these are at negative membrane voltages, might the Anap spectrum shift to higher wavelengths (i.e. more hydrophilic) when the membrane is depolarized? Did the authors find any spectral shift for I202Anap when doing a similar test as depicted in Figure 3E?
11) In Figure 3E, spectra are shown as normalized signals for different voltages, but an amplitude change should also be demonstrated by providing raw spectra at different voltages.
12) In Figure 4, spectra are compared between A197Anap and F150A-A197Anap, showing increase of fluorescence in F150A-A197Anap. Were these obtained at a negative membrane voltage? How do these spectra change when membrane potential is changed?
Additional suggestions for the authors to consider:
1) The authors propose that Anap fluorescence tracks an S4 movement involved in the opening of the channel. They also argue that the existence of more than one open state could explain why the increase in florescence upon depolarization lags the proton current in most cases. While they convincingly show that Anap is not pH sensitive per se, when incorporated into the protein, the fluorescence efficiency of the fluorophore could still be affected by protonation of channel residues in the immediate environment when the channel opens, even after S4 has completed its movement. To address this alternative explanation, the authors could use Hv1 mutants with strongly reduced proton conductance. Channels bearing mutations corresponding to N214R or D112N were used successfully to isolate Hv1 gating currents from the much larger proton currents (De La Rosa & Ramsey, Biophys. J. 2018 114:2844-2854; Carmona et al. PNAS 2018 115:9240-9245; Carmona et al. PNAS 2021 118: e2025556118). Perhaps, they could be used with patch clamp fluorometry as well?
2) The data showing that Hv1-197Anap is quenched by Phe at position 150 are very nice. Yet, it would be useful to show that the quenching is specific to F150 using a negative control. F149, for instance, is just next to F150 but points in a different direction, so its mutation to alanine should not affect Hv1-197Anap fluorescence.
3) A major finding of this work is the identification of a slow kinetic component that is highly sensitive to ΔpH. Earlier studies found that the ability of Hv1 to sense ΔpH is altered by some channel modifications, e.g., in the loop between TMH2 and TMH3 (Cherny et al. J. Gen. Physiol. 2018 150:851-862). Did the authors check whether any of these modifications alter the transition responsible for the slow kinetic component? For instance, a suppression of the transition resulting from a H168X mutation would help tighten the link to ΔpH sensing.
4) We understand that it is difficult to tightly control intracellular and extracellular pH when Hv1 is heterologously expressed in mammalian cells. The G-V relation is not always reliable because accumulation of protons or depletion of protons upon Hv channel activity will alter gating, as the authors have previously published (De La Rosa et al., J. Gen. Physiol. 2016 147:127-136). Could the kinetic analysis of Anap fluorescence be affected by similar alterations to proton concentration in the vicinity of Hv1? It would be helpful for the authors to comment on this specifically.
5) Quenching of Anap by Phe could be verified in cell free conditions using a spectrophotometer with different concentrations of Phe, or citing the literature if it has already been reported.
6) The authors did not cite any example of Anap incorporation into S4 helices, but there are several recent papers where Anap was utilized to probe motion of S4 in other channels. Examples include Dai et al., Nat. Commun. 2021 12:2802 and Mizutani et al. PNAS 2022 119:e2200364119.
7) In the Anap-free negative control (with only A197TAG plasmid transfection), the mCherry signal seems positive (Supplementary Figure 1, left row, second from the top). Is this due to unexpected skipping of the TAG codon to make mCherry-containing partial polypeptides? It would seem like an explanation is needed.
8) The data of Figure 3E are shown as data with different membrane voltages. But there is no information about membrane voltage for Fig. 1E and Fig. 2A and Fig. 4B. Are these from unpatched cells? Please clarify.
9) G-V relations are shown for F150A-A197Anap, but current traces of F150A-A197Anap are missing.
10) On Page 11, Line 303 says “experimental F-V relationship is positively shifted by 10 mV with respect to the G-V curve”. But looking at the data Fig5D, the shift at ΔpH=2 seems the opposite. Perhaps “positively” should be “negatively” in this sentence?
REVIEWING TEAM
Reviewed by:
Yasushi Okamura, Professor, Osaka University, Japan: voltage-sensing proteins, electrophysiology and fluorescence spectroscopy
Francesco Tombola, Associate Professor, University of California, Irvine, USA: ion channel mechanisms, electrophysiology and fluorescence spectroscopy
Christopher A. Ahern, Professor, University of Iowa, USA: ion channel mechanisms, non-canonical amino acidic mutagenesis
Curated by:
Kenton J. Swartz, Senior Investigator, NINDS, NIH USA
(This consolidated report is a result of peer review conducted by Biophysics Colab on version 1 of this preprint. Minor corrections and presentational issues have been omitted for brevity.)
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Author Response
Reviewer #1 (Public Review):
High resolution mechanistic studies would be instrumental in driving the development of Cas7-11 based biotechnology applications. This work is unfortunately overshadowed by a recent Cell publication (PMID: 35643083) describing the same Cas7-11 RNA-protein complex. However, given the tremendous interest in these systems, it is my opinion that this independent study will still be well cited, if presented well. The authors obviously have been trying to establish a unique angle for their story, by probing deeper into the mechanism of crRNA processing and target RNA cleavage. The study is carried out rigorously. The current version of the manuscript appears to have been rushed out. It would benefit from clarification and text polishing.
We thank the reviewer for the positive and helpful comments that have made the manuscript more impactful.
To summarize the revisions, we have resolved the metal-dependence issue, updated the maps in both main and supplementary figures that support the model, re-organized the labels for clarity, and added the comparison between our and Kato et al.’ structures.
In addition, we describe a new result with an isolated C7L.1 fragment that retains the processing and crRNA binding activities.
Reviewer #2 (Public Review):
In this manuscript, Gowswami et al. solved a cryo-EM structure of Desulfonema ishimotonii Cas7-11 (DiCas7-11) bound to a guiding CRISPR RNA (crRNA) and target RNA. Cas7-11 is of interest due to its unusual architecture as a single polypeptide, in contrast to other type III CRISPR-Cas effectors that are composed of several different protein subunits. The authors have obtained a high-quality cryo-EM map at 2.82 angstrom resolution, allowing them to build a structural model for the protein, crRNA and target RNA. The authors used the structure to clearly identify a catalytic histidine residue in the Cas7-11 Cas7.1 domain that is important for crRNA processing activity. The authors also investigated the effects of metal ions and crRNAtarget base pairing on target RNA cleavage. Finally, the authors used their structure to guide engineering of a compact version of Cas7-11 in which an insertion domain that is disordered in the cryo-EM map was removed. This compact Cas7-11 appears to have comparable cleavage activity to the full-length protein.
The cryo-EM map presented in this manuscript is generally of high quality and the manuscript is very well illustrated. However, some of the map interpretation requires clarification (outlined below). This structure will be valuable as there is significant interest in DiCas7-11 for biotechnology. Indeed, the authors have begun to engineer the protein based on observations from the structure. Although characterization of this engineered Cas7-11 is limited in this study and similar engineering was also performed in a recently published paper (PMID 35643083), this proof-of-principle experiment demonstrates the importance of having such structural information.
The biochemistry experiments presented in the study identify an important residue for crRNA processing, and suggest that target RNA cleavage is not fully metal-ion dependent. Most of these conclusions are based on straightforward structure-function experiments. However, some results related to target RNA cleavage are difficult to interpret as presented. Overall, while the cryo-EM data presented in this work is of high quality, both the structural model and the biochemical results require further clarification as outlined below.
We thank the reviewer for the positive and helpful comments that have made the manuscript more impactful.
To summarize the revisions, we have resolved the metal-dependence issue, updated the maps in both main and supplementary figures that support the model, re-organized the labels for clarity, and added the comparison between our and Kato et al.’ structures.
In addition, we describe a new result with an isolated C7L.1 fragment that retains the processing and crRNA binding activities.
- The DiCas7-11 structure bound to target RNA was also recently reported by Kato et al. (PMID 35643083). The authors have not cited this work or compared the two structures. While the structures are likely quite similar, it is notable that the structure reported in the current paper is for the wild-type protein and the sample was prepared under reactive conditions, resulting in a partially cleaved target. Kato et al. used a catalytically dead version of Cas7-11 in which the target RNA should remain fully intact. Are there differences in the Cas7-11 structure observed in the presence of a partially cleaved target RNA in comparison to the Kato et al. structure? Such a comparison is appropriate given the similarities between the two reports. A figure comparing the two structures could be included in the manuscript.
We have added a paragraph on page 12 that describe the differences in preparation of the two complexes and their structures. We observed minor differences in the overall protein structure (r.m.s.d. 0.918 Å for 8114 atoms) but did observe quite different interactions between the protein and the first 5’-tag nucleotide (U(-15) vs. G(-15)) due to the different constructs in pre-crRNA, which suggests an importance of U(-15) in forming the processing-competent active site. We added Figure 2-figure supplementary 3 that illustrates the similarities and the differences.
2.The cryo-EM density map is of high quality, but some of the structural model is not fully supported by the experimental data (e.g. protein loops from the alphafold model were not removed despite lack of cryo-EM density). Most importantly, there is little density for the target RNA beyond the site 1 cleavage site, suggesting that the RNA was cleaved and the product was released. However, this region of the RNA was included in the structural model. It is unclear what density this region of the target RNA model was based on. Further discussion of the interpretation of the partially cleaved target RNA is necessary. Were 3D classes observed in various states of RNA cleavage and with varied density for the product RNAs?
We should have made it clear in the Method that multiple maps were used in building the structure but only submitted the post-processed map to reviewers. When using the Relion 4.0’s local resolution estimation-generated map, we observed sufficient density for some of the regions the reviewer is referring to. For instance, the site 1 cleavage density does support the model for the two nucleotides beyond site 1 cleavage site (see the revised Figure 1 & Figure 1- figure supplement 3).
However, there are protein loops that remain lack of convincing density. These include 134141 and 1316-1329 that are now removed from the final coordinate.
The “partially cleaved target RNA” phrase is a result of weak density for nucleotides downstream of site 1 (+2 and +3) but clear density flanking site 2. This feature indicates that cleavage likely had taken place at site 1 but not site 2 in most of the particles went into the reconstruction. To further clarify this phrase, we added “The PFS region plus the first base paired nucleotide (+1*) are not observed.” on page 4 and better indicate which nucleotides are or are not built in our model in Figure 1.
- The authors argue that site 1 cleavage of target RNA is independent of metal ions. This is a potentially interesting result, but it is difficult to determine whether it is supported by the evidence provided in the manuscript. The Methods section only describes a buffer containing 10 mM MgCl2, but does not describe conditions containing EDTA. How much EDTA was added and was MgCl2 omitted from these samples? In addition, it is unclear whether the site 1 product is visible in Figures 2d and 3d. To my eye, the products that are present in the EDTA conditions on these gels migrated slightly slower than the typical site 1 product. This may suggest an alternate cleavage site or chemistry (e.g. cyclic phosphate is maintained following cleavage). Further experimental details and potentially additional experiments are required to fully support the conclusion that site 1 cleavage may be metal independent.
As we pointed out in response to Reviewer 1’s #8 comment, this conclusion may have been a result of using an older batch of DiCas7-11 that contains degraded fragments.
As shown in the attached figure below, “batch Y” was an older prep from our in-house clone and “batch X” is a newer prep from the Addgene purchased clone (gel on right), and they consistently produce metal-independent (batch Y) or metal-dependent (batch X) cleavage (gel on left). It is possible that the degraded fragments in batch Y carry a metal-independent cleavage activity that is absent in the more pure batch X.
We further performed mass spectrometry analysis of two of the degraded fragments from batch Y (indicated by arrows below) and discovered that these are indeed part of DiCas7-11. We, however, cannot rationalize, without more experimental evidence, why these fragments might have generated metal-independent cleavage at site 1. Therefore, we simply updated all our cleavage results from the new and cleaner prep (batch X) (For instance, Figure 3c). As a result, all references to “metal-independence” were removed.
With regard to the nature of cleaved products, we found both sites could be inhibited by specific 2’-deoxy modifications, consistent with the previous observation that Type III systems generate a 2’, 3’-cyclic product in spite of the metal dependence (for instance, see Hale, C. R., Zhao, P., Olson, S., Duff, M. O., Graveley, B. R., Wells, L., ... & Terns, M. P. (2009). RNA-guided RNA cleavage by a CRISPR RNA-Cas protein complex. Cell, 139(5), 945-956.)
We added this rationale based on the new results and believe that these characterizations are now thorough and conclusive
- The authors performed an experiment investigating the importance of crRNA-target base pairing on cleavage activity (Figure 3e). However, negative controls for the RNA targets in the absence of crRNA and Cas7-11 were not included in this experiment, making it impossible to determine which bands on the gel correspond to substrates and which correspond to products. This result is therefore not interpretable by the reader and does not support the conclusions drawn by the authors.
Our original gel image (below) does contain these controls but we did not include them for the figure due to space considerations (we should have included it as a supplementary figure). We have now completely updated Figure 3e with much better quality and controls. Both the older and the updated experiments show the same results.
Original gel for Figure 3e containing controls.
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hypothes.is hypothes.is
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Typo in the tag here; "transculsion" should be "transclusion".
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github.com github.com
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<h1>Assignment b</h1
i think you forgot to use the header tag.
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github.com github.com
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<link rel="stylesheet" href="style.css">
I think you have added extra link tag for css file. gone through all code and i felt it you have added extra tags .
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<mark>My name is Lovepreet.</mark> <!--used mark to highlight my name-->
This is interesting that you used a 'mark' tag, because I have not heard about it before.
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</p>
would recomend dropping this end tag to the line below, just to make it easier to see the end tag as
is a block level element.
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metalblueberry.github.io metalblueberry.github.io
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it quickly becomes a mess of non related functions that anyone but the owner feels brave enough to import
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www.biorxiv.org www.biorxiv.org
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Note: This rebuttal was posted by the corresponding author to Review Commons. Content has not been altered except for formatting.
Learn more at Review Commons
Reply to the reviewers
1. General Statements [optional]
In our work, we quantified the abundance and positions of major kinetochore proteins within the metaphase kinetochore in budding yeast using single-molecule localization microscopy. Based on these measures, we revised the current model of the kinetochore and provided a nanoscale view of the complex.
We now revised our manuscript according to reviewers’ points. We performed new analyses to quantify the measurement errors and to justify our data analysis workflows. We further exploited the correlation-based analysis and found a correlation between the spreads of kinetochore proteins perpendicular to the spindle axis and their positions along the axis. We also discussed the potential non-centromeric pools and revised our model of the kinetochore. Further information on our analyses was now provided to improve the clarity. Changes to the text were implemented to better reflect our data. Information from relevant works was incorporated to better connect this work to the field.
We thank the reviewers for their points, which help us show the rigorousness of our analyses, further demonstrate the potential of our work, and improve clarity.
2. Point-by-point description of the revisions
Reviewer #1 (Evidence, reproducibility and clarity (Required)):
The authors have developed a rigorous methodology for using single-molecule imaging of exogenously labeled kinetochore proteins to count and estimate their copy numbers and the average distance from the kinetochore protein Spc105. Although the method is technically sound, its application to the kinetochore raises some crucial questions below. My biggest concern is the effect of non-centromeric pools of the centromeric proteins Cse4, Cep3, and Ctf19 on the estimated copy number per kinetochore. The authors should be able to address most, if not all, questions by presenting a more in-depth data analysis.
Major points
- Accounting for tilt of the yeast spindle relative to the image plane: It is not clear to me how the authors ascertain whether the spindle being imaged is nearly parallel to the image plane. In the companion fission yeast study, spindle poles are used for this purpose, but this study seems to rely only on the labeled kinetochore proteins. The criteria used to select the in-plane spindles should be clearly defined.
We thank the reviewer for pointing this out. We selected the in-plane spindles based on their average PSF size, which informs the z positions of the center of the kinetochore cluster (for simplicity, now all ’half-spindle’ was changed to ‘kinetochore cluster’). To calibrate the z position of kinetochore clusters, we first measured the width of the kinetochore cluster by fitting a cylindrical distribution. Overall, the kinetochores are likely symmetrically distributed around the spindle axes. Therefore, the height and the width of a kinetochore cluster should be the same. We then calibrated the z positions of the PSF size based on fluorescent bead data. Next, we plugged in the cylindrical distribution to the calibration curve to correlate the mean PSF size and position of the kinetochore cluster. We only took the kinetochore clusters with a mean PSF size
- The effects of PSF depth on counting kinetochore proteins: The authors use a well-characterized nuclear pore protein as the reference to estimate kinetochore protein counts per half-spindle. Although this method appears rigorous in principle, I am unsure about the effect of the spatial distribution of kinetochores on the accuracy of the estimated number. Nuclear pore proteins are all localized within an 100 nm away from the focal plane even when the spindle is perfectly parallel to the focal plane. A discussion of this possibility, its effect on the protein count/distance estimates, and any mitigating factors is essential to highlight the caveats associated with the conclusions.
Based on the cylindrical distribution (see please the reply to point 1) of kinetochore clusters and their positions in z, we calculated the upper and lower boundaries of the distribution of kinetochore proteins in z, given a specific mean PSF size cutoff of a kinetochore cluster. Regardless of how stringent the cutoff is (130 and 135 nm), we made sure the boundaries do not exceed the imaging depth defined by our choice of the PSF size filtering (
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Presentation of the cross-correlation analysis: The authors use cross-correlation for an unbiased calculation of the axial separation between a protein of interest and Cse4, but I am curious about the structure of the underlying data, and the intensity image in Figure 1 is not easy to examine. It will be helpful to include more analysis of the underlying data for at least a subset of the proteins (e.g., proteins at short, intermediate, and long distances from Cse4) as supplementary data.
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The authors should include X and Y projections of the cross-correlation function.
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Do the widths of cross-correlation functions (i.e., their spread perpendicular to the spindle axis) match across all proteins and experiments? This should be an almost invariant characteristic of the measurements, assuming that proteins within each kinetochore tightly cluster around the 25 nm microtubule. This line of thinking makes the large width of the cross-correlation shown in Figure 1 somewhat surprising.
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It will also be interesting to test if the correlation between the positions of Spc105 molecules, especially perpendicular to the spindle axis, is comparable to the known separations between adjacent microtubules in the yeast spindle (the authors could use Winey et al. 1995 for serial-section EM of yeast spindles for comparison).
The reviewer is interested in the spread, or the size of the distribution, of a protein in a kinetochore along and perpendicular to the spindle axis. This is an interesting idea and can be done practically. However, the information can be more easily obtained based on auto-correlation instead of cross-correlation, due to its better signal-to-noise ratio along the dimension perpendicular to the spindle axis. Cross-correlations in that dimension are convoluted with background localizations and different localization precisions of the two channels. These factors are hard to interpret and disentangled. In auto-correlations, although the background is still present, it can be modeled and then removed easily, as now mentioned on page 15 lines 500-516.
Accordingly, we performed auto-correlation analysis on all the proteins and compared them to simulations representing different sizes. We find that the size of the distribution correlates to the position of the protein along the spindle axis. The results are now included as the new Fig. S5 and discussed on page 6 lines 169-176.
The cross-correlation analysis was based on only the position of the maximum value, not the projections. To keep the figure concise, we decided not to include the projections. However, the auto-correlation analysis was indeed based on projections, which we now included in Fig. S5.
Regarding the correlation between the positions of Spc105 molecules, we believe the reviewer actually refers to the correlation between the positions of kinetochores. Auto-/cross-correlations contain the information of the cluster sizes, based on the first peak (as shown in Fig. S5), and the relative distance (if the pattern is periodic). Unfortunately, the positions of kinetochores perpendicular to the spindle axis are not periodically distributed. Therefore, we cannot comment on the separations between adjacent microtubules.
- Cse4 count (4 per kinetochore) and the model presented: One of the surprising conclusions of the study is that there are two nucleosomes associated with each microtubule attachment, with Mif2/CENP-C potentially interacting with both nucleosomes. There are two critical issues that the authors must consider.
(1) Fluorescent protein chimeras of Cse4 and CBF3 and COMA complex members do not exclusively localize to kinetochores. Biochemical studies show that both Cse4 and CBF3 proteins interact with non-centromeric DNA, e.g., see work from the Biggins lab regarding Cse4 over-expression and also from the Henikoff group that used ChIP-seq. I can't think of a similar reference for the CBF3 complex, but the DNA-binding proteins are also likely to interact with other parts of the genome. The non-centromeric protein is visible as a significant background fluorescence in wide-field microscopy, e.g., see Cep3 localization here: https://images.yeastrc.org/imagerepo/viewExperiment.do?id=202308&experimentGroupOffset=3&experimentOffset=0&experimentGroupSize=3
Similar background fluorescence can be detected for Cse4 and Ctf19. This extra-centromeric localization of Cse4, Cep3, and Ctf19 makes it possible that the protein counts included by the authors are "contaminated" to some extent by the extra-centromeric protein. The authors should discuss this possibility and how it might affect their counts.
After consideration, we agree with the reviewer that, specifically, a fraction of counted Cse4 molecules should be considered non-centromeric. We agree that the previous data is certainly sufficient to conclude it. The reviewer made a similar suggestion about COMA and CBF3 subcomplexes. In recent years a substantial portion of inner kinetochore components has been reconstituted. In Harrison et al. 2019, the Ctf19 complex structure has been solved. Two copies of the complex were observed. Therefore, the non-centromeric pool of COMA is certainly possible and we now made the adjustments to the text (page 8, lines 219-225) and Fig. 4. Accordingly, we now also modified the abstract (page 1, lines 26-27) and restructured the sections (page 10) to accommodate the different possibility of Cse4 copy numbers. While, fluorescence imaging of CBF3 presents a signal throughout the nuclear region we observed only four copies of Cep3 (part of CBF3). A CBF3 structure also has been resolved by Yan et al. 2018, in which the complex was proposed to exist as a dimer. This translates into four copies of Cep3. Therefore, we find it more suitable to leave all observed Cep3 (CBF3) molecules within a kinetochore model.
(2) The model drawn in Figure 4 makes explicit assumptions about the positioning of the four Cse4 molecules (or two nucleosomes) in each kinetochore relative to the rest of the kinetochore components. Yet, the data shown do not justify this specific arrangement. Lawrimore et al. 2011 claim that the non-centromeric Cse4 nucleosomes must be randomly distributed in the pericentromeric chromatin to evade detection in biochemical tests. Therefore, the nearest-neighbor analysis suggested above will be valuable for gaining new insights into the relative positioning of the centromeric- and non-centromeric Cse4 nucleosomes. A similar analysis for Cep3 and Ctf19 will also be helpful. If stereotypical positioning of these molecules cannot be detected, then the model should be revised accordingly (alternative models that are also consistent with the data can be included).
The reviewer has pointed out that Lawrimore et al. 2011 proposed and justified the existence of a non-centromeric Cse4 pool. This arrangement, also potentially along other inner kinetochore components, makes sense and our data did not indicate it otherwise. Therefore, we now revised our model accordingly by applying changes in the main text on page 10 lines 302-305 __as well as in __Fig. 4.
(3) I suggest one experiment that can help the authors better understand protein organization in one kinetochore. Joglekar et al. 2006 used a dicentric chromosome to isolate single kinetochores on the spindle axis to test the assumption that each kinetochore consists of approximately the same number of molecules of kinetochore proteins. The strains are easy to construct (transform existing strains with a linearized plasmid). Single kinetochores can be seen with a low but reasonable frequency. I leave the decision to perform the experiment to the authors' discretion depending on whether the experiment will be worth the effort in strengthening or enhancing their conclusions.
We performed the suggested experiment using the strain published in Joglekar et al. 2006 (kindly provided by Prof. Kerry Bloom) with Cse4 additionally tagged with mMaple. However, we always observed several super-resolved Cse4 clusters (likely of several kinetochores) overlapping with Nuf2-GFP diffraction-limited signal, therefore unable to assign a single isolated kinetochore to the lagging centromere.
- Information regarding the degree of correction applied to calculate protein count per half-spindle: It will be helpful to include data regarding the degree of correction applied to the expected and measured numbers of NPC protein as supplementary data so that the readers can see the magnitude of this correction relative to the measured counts.
We would like to clarify that we did not correct the data. Instead, we calibrate the copy number, given that the copy number of Nup188 per NPC is known. We assume the same ratio between localization and copy number applies to both Nup188 and the kinetochore proteins. We now include a new Table S4 listing calibration factors of all experiments shown in Fig. 3.
Minor points:
- McIntosh et al. JCB 2013 used microtubule plus-ends in serial section electron micrographs of yeast spindles to align the centromeric region and found a disk-shaped structure that roughly corresponds to the size of a single nucleosome ~ 80 nm away from the tip of the microtubule and centered the microtubule axis. The authors should refer to this finding in their discussion of the model that they present with two nucleosomes. In my opinion, this is compelling evidence for a nucleosome-like structure serving as the kinetochore foundation.
We agree with this reviewer's comment. The study, among others, present compelling evidence for a point-centromere. We now included the finding in the discussion on page 10, lines 293-294.
- As discussed by the authors, the number of Cse4 molecules per kinetochore has been the subject of some controversy. Biochemical data from the Biggins group and ChIPseq data from the Westermann group (Altunkaya et al. 2016 Current Biology) strongly suggest that Cse4 molecules can only be found centered on the centromeric sequence. The latter reference should be included in the discussion.
Thank you for pointing this out. Indeed, this is important. We have now added the relevant reference in the discussion on__ page 10 lines 291-292__.
- Although microscopy-based methods have estimated anywhere from 1, 2, to 6 Cse4 molecules per kinetochore, these studies generally agree on the stoichiometry between Cse4 and the rest of the kinetochore proteins, e.g., Ndc80 complex proteins are ~ 4-fold more abundant that Cse4, etc. The present study seems to disagree with protein stoichiometry. The authors may find it worthwhile to note this feature of their data.
We now discuss the stoichiometry difference between our results and others on page 11 lines 322-324.
- Omission of the Dam1 complex from this study is disappointing to me personally, but I am sure that the authors have good reasons for this. They should briefly comment on the absence of the Dam1 complex in this study.
To provide information on the Dam1 complex, we imaged Ask1, a component of the complex. The measured positioning and copy number of the protein are now included in Fig. 2 and Fig. 3 respectively, and described and discussed in respective parts of the manuscript.
Reviewer #1 (Significance (Required)):
Cieslinski and colleagues present a single-molecule localization-based study to define the copy numbers and relative organization of kinetochore proteins in budding yeast. These numbers confirm and significantly refine prior measurements of the same aspects of the kinetochore. They also raise new questions and point to new research directions. The measurements also reveal a model of the protein organization of the budding yeast kinetochore in metaphase. For these reasons, the manuscript is of significant interest to the cell division field.
Reviewer #2 (Evidence, reproducibility and clarity (Required)):
In this study, Cielinski and colleagues have applied single molecule localization microscopy to map the positions of proteins in the yeast kinetochore. This has not been reported previously and this study is both well-conducted and the data appear solid. They also use a modification of this technique to assess the stoichiometry of kinetochore proteins. The results that they obtain are broadly in line with several previous studies that use other methodology. There may be an improvement in accuracy using this new approach that has not been obtained previously and there are some important novel conclusions from this work. I would like the authors to address the following concerns prior to publication:
Major points
- One interesting finding is that there is a discrepancy in the length of both the MIND and NDC80 complexes (from crystallographic data) with their relative positions. The authors suggest that the outer complexes could be twisted or rotated in respect of the spindle axis. It would be great if the authors could illustrate this in their model (or discuss it in the text), to demonstrate the required angle of twist/rotation of both complexes to account for the discrepancy. A twisted filament structure to the outer kinetochore does have some implications for its response to tension - a key determinant of kinetochore-microtubule attachment. It also may provide some flexibility to the structure under tension.
The discussion about this discrepancy has now been incorporated in the main text, page 9 lines 263-267. For clarity, we only partially reflect this in our schematic model (Fig. 4A; the MIND complex) but we already reflected this in the illustrative structural model in Fig. 4B.
- For the experiment with cycloheximide, the authors state "Although we observed minor changes in copy numbers, the overall effect of CHX was small." For some proteins, Cse4i for example, there appears to be a significant decrease in intensity (30-40%) after cycloheximide treatment, see Figure S3. While the conclusion that tag maturation does not affect copy number measurements is sound, I suggest modifying this section to reflect the data.
We now modified the section accordingly by pointing out that Cse4i under CHX measurements led to reduction of the signal. The modification can be found on page 8 lines 207-211.
- Page 5. The statement "These data agree reasonably well with previous diffraction-limited dual-color microscopy studies ..." provides readers with little ability to compare the data. I would like to see a supplementary figure comparing these new data with previous studies, especially those of Joglekar et al 2009, see Figure 3 in this paper.
We thank the reviewer for suggesting such a table. This will allow readers a direct comparison of the data between our study and Joglekar at al. 2009. The comparison can be found in new Table S1 __and __Fig. S4, which are now mentioned on page 5.
- In terms of the distances quoted, are they in one dimension (as per Jogelkar et al 2009) or in three? The results section is entitled "...positions of kinetochore proteins along the metaphase spindle axis", which suggests a single dimension. Please make this very clear in the results section. In the discussion, is the statement "we mapped the relative positions of 15 kinetochore proteins along the kinetochore axis", which is not entirely clear. It seems from the methods that this is one dimension "...we determined the average distance between the two proteins along the spindle axis. “I suggest clarifying the results section briefly and clearly to indicate that this is a single dimension being measured and also using consistent wording of the axis measured throughout the text.
We agree the previous description may not be clear to the viewers. We now changed the text accordingly in the results section, page 5 lines 129-130.
Minor points:
Abstract: I would drop "all" from "For all major kinetochore proteins...", since full characterisation was performed on 14 proteins (9 in terms of copy number).
We now deleted “all” in the abstract as the reviewer suggested__.__
Page 2: "trough" to through.
Corrected.
Page 2 "S. cerevisiae" to italics
Corrected.
Methods p11. How do the MKY strains relate to common yeast genetic backgrounds? (e.g. are they S288C?).
MKY strains are derivative of S288C. The information was now updated in the Methods section and in Table S2.
Reviewer #2 (Significance (Required)):
This manuscript, together with an accompanying one from Virat et al., are nice complementary studies that provide the first single molecule localization studies of the yeast kinetochore. Although other labs have used super-resolution methods to study individual kinetochore proteins; both of these new studies map distances between many proteins at the kinetochore and thus are able to produce maps of the overall kinetochore structure. Like the previous study using standard resolution methods (Joglekar et al, 2009. Current Biology 19, 694-699); these studies will likely provide a benchmark for future studies on eukaryotic kinetochore architecture, including those in mammalian systems. Additionally, this work will appeal to super-resolution microscopists.
My expertise is as a yeast kinetochore cell biologist.
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Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.
Learn more at Review Commons
Referee #2
Evidence, reproducibility and clarity
In this study, Cielinski and colleagues have applied single molecule localization microscopy to map the positions of proteins in the yeast kinetochore. This has not been reported previously and this study is both well-conducted and the data appear solid. They also use a modification of this technique to assess the stoichiometry of kinetochore proteins. The results that they obtain are broadly in line with several previous studies that use other methodology. There may be an improvement in accuracy using this new approach that has not been obtained previously and there are some important novel conclusions from this work. I would like the authors to address the following concerns prior to publication:
Major points
- One interesting finding is that there is a discrepancy in the length of both the MIND and NDC80 complexes (from crystallographic data) with their relative positions. The authors suggest that the outer complexes could be twisted or rotated in respect of the spindle axis. It would be great if the authors could illustrate this in their model (or discuss it in the text), to demonstrate the required angle of twist/rotation of both complexes to account for the discrepancy. A twisted filament structure to the outer kinetochore does have some implications for its response to tension - a key determinant of kinetochore-microtubule attachment. It also may provide some flexibility to the structure under tension.
- For the experiment with cycloheximide, the authors state "Although we observed minor changes in copy numbers, the overall effect of CHX was small." For some proteins, Cse4i for example, there appears to be a significant decrease in intensity (30-40%) after cycloheximide treatment, see Figure S3. While the conclusion that tag maturation does not affect copy number measurements is sound, I suggest modifying this section to reflect the data.
- Page 5. The statement "These data agree reasonably well with previous diffraction-limited dual-color microscopy studies ..." provides readers with little ability to compare the data. I would like to see a supplementary figure comparing these new data with previous studies, especially those of Joglekar et al 2009, see Figure 3 in this paper.
- In terms of the distances quoted, are they in one dimension (as per Jogelkar et al 2009) or in three? The results section is entitled "...positions of kinetochore proteins along the metaphase spindle axis", which suggests a single dimension. Please make this very clear in the results section. In the discussion, is the statement "we mapped the relative positions of 15 kinetochore proteins along the kinetochore axis", which is not entirely clear. It seems from the methods that this is one dimension "...we determined the average distance between the two proteins along the spindle axis."I suggest clarifying the results section briefly and clearly to indicate that this is a single dimension being measured and also using consistent wording of the axis measured throughout the text.
Minor points:
Abstract: I would drop "all" from "For all major kinetochore proteins...", since full characterisation was performed on 14 proteins (9 in terms of copy number).
Page 2: "trough" to through.
Page 2 "S. cerevisiae" to italics
Methods p11. How do the MKY strains relate to common yeast genetic backgrounds? (e.g. are they S288C?).
Significance
This manuscript, together with an accompanying one from Virat et al., are nice complementary studies that provide the first single molecule localization studies of the yeast kinetochore. Although other labs have used super-resolution methods to study individual kinetochore proteins; both of these new studies map distances between many proteins at the kinetochore and thus are able to produce maps of the overall kinetochore structure. Like the previous study using standard resolution methods (Joglekar et al, 2009. Current Biology 19, 694-699); these studies will likely provide a benchmark for future studies on eukaryotic kinetochore architecture, including those in mammalian systems. Additionally, this work will appeal to super-resolution microscopists.
My expertise is as a yeast kinetochore cell biologist.
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www.convinceandconvert.com www.convinceandconvert.com
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TextOptimizer example
(Could not highlight what attended to) Another good addition to making their web much more accesible to all the people that might go on to there website. And that is a descriptive tag for images on the website, for screen readers to be able to identify and describe the photo that is placed there. This allows people with visual impairments to identify everything that is going on, all with just listening to the Text To Speech.
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betasite.razorpay.com betasite.razorpay.com
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business_model s
This is optional we can add optional tag in bottom at all place
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github.com github.com
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<p>Honestly, I didn't have web experience until this year, the last term I worked on <b>WordPress</b> Projects but it was basic and this semester I am being introduce in how to build a websites with <b>HTML/CSS</b>.
the formatting here makes it difficult to identify where the paragraph tag closes.
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</p>
It would be better if you place the content next to the opening tag and the close it there, not in a new line.
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github.com github.com
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<!DOCTYPE html>
p tag is not used. Few inline tags are used.
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github.com github.com
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<ul><li>contact me on email: <a href="http://aashuu00454@gmail.com">aashuu0045@gmail.com</a> </ul>
More minor nit-picking, the 'li' element is missing its closing tag
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<!DOCTYPE html> <html lang="en"> <head> <!-- DGL 103 CVS2 - ASHUTOSH BHARDWAJ - Assignment B --> <meta charset="UTF-8"> <meta name=“viewport” content="width-device-width, initial-scale=1.0"> <title>Assignment B</title> <link rel="stylesheet" href="style.css"> </head> <body> <header><h1><strong> Assignment B </strong></h1></header><!--I used the strong tag to bold the header--> <h1>Who am i?</h1> <P>My name is ashutosh bhardwaj. I am 18 years old. I am from punjab. I am pursuing web and mobile application development program from North Island College. Right now I am living in comox.</P> <br>You can contact me at: <ul><li>contact me on email: <a href="http://aashuu00454@gmail.com">aashuu0045@gmail.com</a> </ul> <h2>How much web experience do I have?</h2> I do not have any experience with web. <h2>Do I know any coding languages</h2> No, i do not know any programming language. <h2>What I would like from this course?</h2> At the end i want to see myself having good knowledge about languages and able to do programming things. <br> <br> <br> <hr><footer>Copyright ©️ 2022 Ashutosh bhardwaj</footer> </body> </html>
no errors
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github.com github.com
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<i>
keep the tag along with the content it is related to
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github.com github.com
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<!DOCTYPE html> <head> <!-- DGL 103 CVS2 - Arshdeep Singh - Assignment B --> <meta charset="utf-8"> <title> Assignment B</title> <link rel="stylesheet" href="style.css"> </head> <body> <Header><h1><strong>ASSIGNMENT B</strong></h1></Header><!-- I used the strong tag to bold the header --> <div> <hr> <h2>INTRODUCTION</h2> My name is Arshdeep Singh.I was born in NEW DELHI,INDIA and currently I am living in Comox,British Columbia.I wanted to a professional web developer .Currently, I am enrolled in <b>Associate Science Degree</b> at NIC.<!-- I used the b tag to bold the text --> <br>You can contact me: <ul><li>By email <a href="https://mail.google.com/mail/u/0/#inbox">singharshdeep4980@gmail.com</a> <!-- I used the a tag to link the gmailaddress --> </li><li> DM me on instagram <a href="https://www.instagram.com/">arshdeep_7428</a></li></ul> <h2>What's my experience in web development?</h2> Since I am interested in creating websites, I have been learning a little bit about it with the help of <b> YOUTUBE </b>. However, I do not have any expertise in this area. <h2>Do i know any coding language?</h2> Although I have no coding experience, I will learn everything there is to know about creating websites this academic year. <h2>What is my expectations while this academic year?</h2> I want support and assistance from my tutor and pals. I'll develop my abilities during this course.</div> <br> <br> <br> <br> <hr><footer>Copyright © 2022 Arshdeep Singh </footer> </body> </html>
No error. good
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<ul><li>By email <a href="https://mail.google.com/mail/u/0/#inbox">singharshdeep4980@gmail.com</a> <!-- I used the a tag to link the gmailaddress --> </li><li> DM me on instagram <a href="https://www.instagram.com/">arshdeep_7428</a></li></ul>
This looks good! Only improvement could be to format the elements in such a away that would communicate the hierarchy. For example each 'li' element could be on its own line and further indented from the 'ul' tag.
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My name is Arshdeep Singh.I was born in NEW DELHI,INDIA and currently I am living in Comox,British Columbia.I wanted to a professional web developer .Currently, I am enrolled in <b>Associate Science Degree</b> at NIC.<!-- I used the b tag to bold the text -->
again just needs opening and closing 'p' tags
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github.com github.com
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<!DOCTYPE html> <html lang="en"> <head> <!-- DGL 103 CVS2 - Claire Guiot - Assignment B --> <meta charset="UTF-8"> <meta http-equiv="X-UA-Compatible" content="IE=edge"> <meta name="viewport" content="width=device-width, initial-scale=1.0"> <link rel="stylesheet" href="style.css"> <title>Assignment B</title> </head> <body> <header> <h1>Assignment B</h1> <hr> </header> <main> <!-- You might notice I create a new line spacing the content from the tag when the paragraph is long. Not sure if this is considered "proper formatting", but I think its more readable --> <h2>Who Am I?</h2> <p> I was born in the city of <em>Whitehorse</em>, but I moved to the <em>Vancouver Island</em> area when I was 8. <em>Courtenay</em>, while new to me, is only a hundred kilometers north of where I used to live on <em>Gabriola Island</em> </p> <h2>Experience with the Web</h2> <p> I started building websites when my dad founded his own event production business. As someone with no experience with web dev, I looked into the pre-build options and eventually settled on <mark>Webflow</mark> as I felt it had a unique level of control. I eventually moved on to experiment with other <mark>web technologies</mark>. Everything I know is self taught, so my ability when it comes to the web is functional but far from complete </p> <h2>Coding languages</h2> <p> <strong>I know HTML, CSS, Javascript and a little bit of C#.</strong> Just because I can "speak" HTML and CSS doesn't mean I'm fluent, so I'm excited to learn these languages in a structured setting. </p> <h2>Goals for the Course</h2> <ul> <li>To collaborate and learn with peers</li> <li>To build a strong foundation in HTML and CSS</li> <li>To stay on top of the course load without falling behind. <em>(which means avoiding submitting work 3 hours before the deadline)</em></li> </ul> <p>Woah! Bonus <a href="https://stackoverflow.com/" target="_blank">link!</a></p> </main> <footer> <hr> <small>100% Official Copyright © Tomio Miyagawa</small> </footer> </body> </html>
I have tried to find mistakes but i am not able to do so. This is just example of perfect coding.
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<!DOCTYPE html> <html lang="en"> <head> <!-- DGL 103 CVS2 - Claire Guiot - Assignment B --> <meta charset="UTF-8"> <meta http-equiv="X-UA-Compatible" content="IE=edge"> <meta name="viewport" content="width=device-width, initial-scale=1.0"> <link rel="stylesheet" href="style.css"> <title>Assignment B</title> </head> <body> <header> <h1>Assignment B</h1> <hr> </header> <main> <!-- You might notice I create a new line spacing the content from the tag when the paragraph is long. Not sure if this is considered "proper formatting", but I think its more readable --> <h2>Who Am I?</h2> <p> I was born in the city of <em>Whitehorse</em>, but I moved to the <em>Vancouver Island</em> area when I was 8. <em>Courtenay</em>, while new to me, is only a hundred kilometers north of where I used to live on <em>Gabriola Island</em> </p> <h2>Experience with the Web</h2> <p> I started building websites when my dad founded his own event production business. As someone with no experience with web dev, I looked into the pre-build options and eventually settled on <mark>Webflow</mark> as I felt it had a unique level of control. I eventually moved on to experiment with other <mark>web technologies</mark>. Everything I know is self taught, so my ability when it comes to the web is functional but far from complete </p> <h2>Coding languages</h2> <p> <strong>I know HTML, CSS, Javascript and a little bit of C#.</strong> Just because I can "speak" HTML and CSS doesn't mean I'm fluent, so I'm excited to learn these languages in a structured setting. </p> <h2>Goals for the Course</h2> <ul> <li>To collaborate and learn with peers</li> <li>To build a strong foundation in HTML and CSS</li> <li>To stay on top of the course load without falling behind. <em>(which means avoiding submitting work 3 hours before the deadline)</em></li> </ul> <p>Woah! Bonus <a href="https://stackoverflow.com/" target="_blank">link!</a></p> </main> <footer> <hr> <small>100% Official Copyright © Tomio Miyagawa</small> </footer> </body> </html>
no errors
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For instance, particular insights related to the sun or the moon may be filed under the(foreign) keyword “Astronomie” [Astronomy] or under the (German) keyword “Sternkunde”[Science of the Stars]. This can happen even more easily when using just one language, e.g.when notes related to the sociological term “Bund” [Association] are not just filed under“Bund” but also under “Gemeinschaft” [Community] or “Gesellschaft” [Society]. Againstthis one can protect by using dictionaries of synonyms and then create enough referencesheets (e.g. Astronomy: cf. Science of the Stars)
related, but not drawn from as I've been thinking about the continuum of taxonomies and subject headings for a while...
On the Spectrum of Topic Headings in note making
Any reasonable note one may take will likely have a hierarchical chain of tags/subject headings/keywords going from the broad to the very specific. One might start out with something broad like "humanities" (as opposed to science), and proceed into "history", "anthropology", "biological anthropology", "evolution", and even more specific. At the bottom of the chain is the specific atomic idea on the card itself. Each of the subject headings helps to situate the idea and provide the context in which it sits, but how useful within a note taking system is having one or more of these tags on it? What about overlaps with other broader subjects (one will note that "evolution" might also sit under "science" / "biology" as well), but that note may have a different tone and perspective than the prior one.
This becomes an interesting problem or issue as one explores ideas in a pre-designed note taking system. As a student just beginning to explore anthropology, one may tag hundreds of notes with anthropology to the point that the meaning of the tag is so diluted that a search of the index becomes useless as there's too much to sort through underneath it. But as one continues their studies in the topic further branches and sub headings will appear to better differentiate the ideas. This process will continue as the space further differentiates. Of course one may continue their research into areas that don't have a specific subject heading until they accumulate enough ideas within that space. (Take for example Daniel Kahneman and Amos Tversky's work which is now known under the heading of Behavioral Economics, a subject which broadly didn't exist before their work.) The note taker might also leverage this idea as they tag their own work as specifically as they might so as not to pollute their system as it grows without bound (or at least to the end of their lifetime).
The design of one's note taking system should take these eventualities into account and more easily allow the user to start out broad, but slowly hone in on direct specificity.
Some of this principle of atomicity of ideas and the growth from broad to specific can be seen in Luhmann's zettelkasten (especially ZK II) which starts out fairly broad and branches into the more specific. The index reflects this as well and each index heading ideally points to the most specific sub-card which begins the discussion of that particular topic.
Perhaps it was this narrowing of specificity which encouraged Luhmann to start ZKII after years of building ZKII which had a broader variety of topics?
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www.biorxiv.org www.biorxiv.org
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Author Response
Reviewer #3 (Public Review):
1) Validation of reagents: The authors generated a pY1230 Afadin antibody claiming that (page 6) "this new antibody is specific to tyrosine phosphorylated Afadin, and that pY1230 is targeted for dephosphorylation by PTPRK, in a D2-domain dependent manner". The WB in Fig 1B shows a lot of background, two main bands are visible which both diminish in intensity in ICT WT pervanadate-treated MCF10A cell lysates. The claim that the developed peptide antibody is selective for pY1230 in Afadin would need to be substantiated, for instance by pull down studies analysed by pY-MS to substantiate a claim of antibody specificity for this site. However, for the current study it would be sufficient to demonstrate that pY1230 is indeed the dephosphorylated site. I suggest therefore including a site directed mutant (Y1230F) that would confirm dephosphorylation at this site and the ability of the antibody recognizing the phosphorylation state at this position.
We would like this antibody to be a useful and freely accessible tool in the field and have taken on board the request for additional validation. To this end we have significantly expanded Supplementary Figure 2 (now Figure 1 - figure supplement 2) and included a dedicated section of the results as follows: 1. We have now included information about all of the Afadin antibodies used in this study, since Afadin(BD) appears to be sensitive to phosphorylation (Figure 1 - figure supplement 2A). 2. We have demonstrated that the Afadin pY1230 antibody detects an upregulated band in PTPRK KO MCF10A cells, consistent with our previous tyrosine phosphoproteomics (Figure 1 - figure supplement 2B). This indicates that the antibody can be used to detect endogenous Afadin phosphorylation. 3. We have included two new knock down experiments demonstrating the recognition of Afadin by our antibody (Figure 1 - figure supplement 2C). There appear to be two Afadin isoforms recognised in HEK293T cells by both the BD and pY1230 antibody, consistent with previous reports (Umeda et al. MBoC, 2015). We have highlighted these in the figure. 4. We have performed mutagenesis to demonstrate the specificity of the antibody. We tagged Afadin with a fluorescent protein tag, reasoning that it would cause a shift in molecular weight that could be resolved by SDS PAGE, as is the case. We noted that the phosphopeptide used spans an additional tyrosine, Y1226, which has been detected as phosphorylated (although to a much lower extent than Y1230) on Phosphosite plus. The data clearly show that Afadin cannot be phosphorylated when Y1230 is mutated to a phenylalanine (compared to CIP control), indicating that this is the predominant site recognised by the antibody. In addition, the endogenous pervanadate-stimulated signal is completely abolished by CIP treatment (Figure 1 - figure supplement 2D). 5. We have included densitometric quantification of the dephosphorylation assay shown in Figure 1B, which was part of a time course and shows preferential dephosphorylation by the PTPRK ICD compared to the PTPRK D1. The signal stops declining with time, which could indicate antibody background, or an inaccessible pool of Afadin-pY1230 (Figure 1 - figure supplement 2E). 6. To further demonstrate that this site is modulated by PTPRK in post-confluent cells, we have used doxycycline (dox)-inducible cell lines generated in Fearnley et al, 2019. Upon treatment with 500 ng/ml Dox for 48 hours PTPRK is induced to lower levels than wildtype, however, normalized quantification of the Afadin pY1230 against the Afadin (CST) signal clearly indicates downregulation by PTPRK WT, but not the catalytically inactive mutant (Figure 1 - figure supplement 2F and 2G). Together these data strengthen our assertion that this antibody recognises endogenously phosphorylated Afadin at site Y1230, which is modulated in vitro and in cells by PTPRK phosphatase activity. For clarity, we have highlighted and annotated the relevant bands in figures. We have also included identifiers for each Afadin total antibody was used in particular experiments.
2) The authors claim that a short, 63-residue predicted coiled coil (CC) region, is both necessary and sufficient for binding to the PTPRK-ICD. The region is predicted to have alpha-helical structure and as a consequence, a helical structure has been used in the docking model. Considering that the authors recombinantly expressed this region in bacteria, it would be experimentally simple confirming the alpha-helical structure of the segment by CD or NMR spectroscopy.
To clarify, the helical structure in the docking model was independently predicted by several sequence and structural analysis programmes including AlphaFold2, RobettaFold, NetSurfP and as annotated in Uniprot (as a coiled coil). We did not stipulate prior to the AF2 prediction that it was helical. Isolated short peptides frequently adopt helical structure, therefore prediction of a helix within the context of the full Afadin sequence is, in our opinion, stronger evidence than CD of an isolated fragment.
3) Only two mutants have been introduced into PTPRK-ICD to map the Afadin interaction site. One of the mutations changes a possibly structurally important residues (glycine) into a histidine. Even though this residue is present in PTPRM, it does not exclude that the D2 domain no longer functionally folds. Also the second mutation represents a large change in chemical properties and the other 2 predicted residues have not been investigated.
The residues that were selected for mutation are all localised to the protein surface and therefore are unlikely to be involved in stable folding of PTPRK. In support of the correct folding of the mutated PTPRK, we include in Figure 1 below SEC elution traces for wild-type and mutant D2 showing that they elute as single symmetric peaks at the same elution volume as the WT protein. This is consistent with them having a similar shape and size, and not being aggregated or unfolded.
Figure 1. PTPRK-D2 wild-type and mutant preparative SEC elution profiles. A280nm has been normalised to help illustrate that the different proteins elute at the same volume. The main peak from these samples was used for binding assays in the main paper.
Furthermore, the yield for the double mutant was very high (4 mg of pure protein from a 2 L culture, see A280 value in graph below), whereas poorly folded proteins tend to have significantly reduced yields. This protein was also very stable over time whereas unfolded proteins tend to degrade during or following purification.
Figure 2. Analytical SEC elution profile for the PTPRK-D2 DM construct showing the very high yield consistent with a well-folded, stable protein.
Finally, we have carried out thermal melt curves of the WT and mutant PTPRK D2 domains showing that they all possess melting temperatures between 39.3°C and 41.7°C, supporting that they are all equivalently folded. We include these data as an additional Supplementary Figure (Figure 4 - figure supplement 3) in the paper.
4) The interface on the Afadin substrate has not been investigated apart from deleting the entire CC or a central charge cluster. Based on the docking model the authors must have identified key positions of this interaction that could be mutated to confirm the proposed interaction site.
We have now made and tested several additional mutations within both the Afadin-CC and PTPRK-D2 domains to further validate the AF2 predicted model of the complex.
For Afadin-CC we introduced several single and double mutations along the helix including residues predicted to be in the interface and residues distal from the interface. These mutations and the pulldown with PTPRK are described in the text and are included as additional panels to a modified Figure 3. All mutations have the expected effect on the interaction based on the predicted complex structure. To help illustrate the positions of these mutations we have also included a figure of the interface with the residues highlighted.
For the PTPRK-D2 we have also introduced two new mutations, one buried in the interface (F1225A) and one on the edge of the interface encompassing a loop that is different in PTPRM (labelled the M-loop). GST-Afadin WT protein was bound to GSH beads and tested for their ability to pulldown WT and mutated PTPRK. These new mutations (illustrated in the new Figure 4 – figure supplement 2) further support the model prediction. F1225A almost completely abolishes binding as predicted, while the M-loop retains binding. These mutations and their effects are now described in the main text and the pull-down data, including controls and retesting of the original DM mutant, are included as panel H in a newly modified Figure 4 focussed solely on the PTPRK interface.
5) A minor point is that ITC experiments have not been run long enough to determine the baseline of interaction heats. In addition, as large and polar proteins were used in this experiment, a blank titration would be required to rule out that dilution heats effect the determined affinities.
All control experiments including buffer into buffer, Afadin into buffer and buffer into PTPRK were carried out at the same time as the main binding experiment and are shown below overlaid with the binding curve. These demonstrate the very small dilution heats consistent with excellent buffer matching of the samples.
We were able to obtain excellent fits to the titration curves by fitting 1:1 binding with a calculated linear baseline (see Figure 2B,D). Very similar results were obtained by fitting to the sum (‘composite’) of fitted linear baselines obtained for the three control experiments for each titration.
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elearningindustry.com elearningindustry.com
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tag content
"The <meta> tag defines metadata about an HTML document. Metadata is data (information) about data. <meta> tags always go inside the <head> element, and are typically used to specify character set, page description, keywords, author of the document, and viewport settings."
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detentionsolidarity.net detentionsolidarity.net
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Neeraj had been kept in jail without any evidence supporting the police’s charge and only the claim that he was a known “bad character”.
Our justice system in a nutshell. The one who fits the tag of a media defined criminal instantly made to look guilty without validation or solid evidences.
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cpojer.net cpojer.net
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To stick with the theme of consistency, if you want to use your coding font on GitHub to make code reviews feel closer to what they look like in your text editor, drop this into Refined GitHub’s Custom CSS extension settings
.code code
css code, kbd, pre, tt, .ace_editor.ace-github-light, .blame-sha, .blob-code-inner, .blob-num, .branch-name, .commit .sha, .commit .sha-block, .commit-desc pre, .commit-ref, .commit-tease-sha, .default-label .sha, .export-phrase pre, .file-editor-textarea, .file-info, .gollum-editor .expanded textarea, .gollum-editor .gollum-editor-body, .hook-delivery-guid, .hook-delivery-response-status, .input-monospace, .news .alert .branch-link, .oauth-app-info-container dl.keys dd, .quick-pull-choice .new-branch-name-input input, .tag-references > li.commit, .two-factor-secret, .upload-files .filename, .url-field, .wiki-wrapper .wiki-history .commit-meta code { font-family: 'Fira Code' !important; }
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uo.unisa.edu.au uo.unisa.edu.au
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Add a Page Note with the tag Welcome to let us know you've joined
joined :)
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www.goutpal.com www.goutpal.com
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Related Topics
Historically, the related topics section of each GoutPal page identified relationships using the
WordPress Tag
feature. However, after I invented WordPress Transmigration, I need a better approach.So I must replace this with a navigation map. And create new workflows that enable me to update these maps efficiently.
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I am still researching this topic
My latest research summarries about edamame and gout are available to GoutPal Links Subscribers. So far, my research notes cover topics for new edamame pages. Including reviews of studies about edamame and uric acid. Also, I'm researching general health benefits of edamame in my Food Research Channel. So I'll re-purpose some of that for gout sufferers where there is an impact on inflammation.
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developer.mozilla.org developer.mozilla.org
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The request might or might not eventually be acted upon, as it might be disallowed when processing actually takes place.
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web.hypothes.is web.hypothes.is
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Have students highlight, tag, and annotate words or passages that are confusing to them in their readings.
Such a good tool that I wish I knew about earlier.
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www.blackbirdspyplane.com www.blackbirdspyplane.com
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So some people might bug out when they see what you charge for a shirt, but you make the case that it’s a price-tag where the “weight” of the piece is reflected, rather than an artificial cheapness.
this also seems unfortunately like not the right solution, though. should nice clothes always cost a lot of money? how would a utopian society deal with this sort of weighty clothes? are we all making clothes for each other? but then we lose the idea of fashion/designers/luxury - in some sense i wonder how capital and design are intertwined
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www.makeuseof.com www.makeuseof.com
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5 Text-Based Adventure Games You Can Play in Your Browser
Text-Based Adventure Game
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hypothes.is hypothes.is
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website obesity crisis
Taken from Maciej Cegłowski https://idlewords.com/talks/website_obesity.htm.
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github.com github.com
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>
I'm not sure if there is supposed to be a forward slash before the closing bracket in order to properly close the tag
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github.com github.com
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>
I'm not sure if there is supposed to be a forward slash before the closing bracket in order to properly close the tag
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github.com github.com
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One of the reasons I initially pushed back on the creation of a JSON Schema for V3 is because I feared that people would try to use it as a document validator. However, I was convinced by other TSC members that there were valid uses of a schema beyond validation.
annotation meta: may need new tag: fear would be used for ... valid uses for it beyond ...
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without a schema, you do not have a spec, you have an aspiration.
annotation meta: may need new tag: you don't have a _; you have a _
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When we do release a final version of JSON Schema, please do not use JSON Schema to guarantee an OpenAPI document is valid. It cannot do that. There are numerous constraints in the written specification that cannot be expressed in JSON Schema.
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stackoverflow.com stackoverflow.com
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additionalProperties applies to all properties that are not accounted-for by properties or patternProperties in the immediate schema.
annotation meta: may need new tag: applies to siblings only or applies to same level only
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github.com github.com
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<p>This is *Ashutosh Bhardwaj* speaking <p></p>
Make sure every element has one opening and closing tag. (with the exception of some elements don't require closing tags).
So in this case, the middle "p" tag isn't doing anything.
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github.com github.com
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<p>This is Rohan Sharma speaking <p></p>
- It's good practice to put new elements on a new line
- You have two opening paragraph tags (
) before a closing tag (
), paragraph content should be between
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github.com github.com
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However, unevaluatedProperties has dynamic behavior, meaning that the set of properties to which it applies cannot be determined from static analysis of the schema (either the immediate schema object or any subschemas of that object).
annotation meta: may need new tag:
dynamic behavior vs. static analysis [not quite parallel]
or can we reuse something else like?: lexical semantics vs. run-time semantics
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We do not want to change or remove additionalProperties. Providing a clear solution for the above use case will dramatically reduce or eliminate the misunderstandings around additionalProperties.
annotation meta: may need new tag: - don't want to change or remove existing feature [because...] - solving problem B will reduce misunderstandings around feature A
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github.com github.com
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JSONPath contains verbiage that allows for an empty array to be returned in the case that nothing was found, but the primary return in these cases is false.
annotation meta: may need new tag:
distinction between nothing, false, and empty array
verbiage that allows for ...
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McConnell said it’s up to the Republican candidates in various Senate battleground races to explain how they view the hot-button issue. (function () { try { var event = new CustomEvent( "nsDfpSlotRendered", { detail: { id: 'acm-ad-tag-mr2_ab-mr2_ab' } } ); window.dispatchEvent(event); } catch (err) {} })(); “I think every Republican senator running this year in these contested races has an answer as to how they feel about the issue and it may be different in different states. So I leave it up to our candidates who are quite capable of handling this issue to determine for them what their response is,” he said.
Context: Lindsey Graham had just proposed a bill for a nationwide abortion ban after 15 weeks of pregnancy.
McConnell's position seems to be one that choice about abolition is an option, but one which is reserved for white men of power over others. This is painful because that choice is being left to people without any of the information and nuance about specific circumstances versus the pregnant women themselves potentially in consultation with their doctors who have broad specific training and experience in the topics and issues at hand. Why are these leaders attempting to make decisions based on possibilities rather than realities, particularly when they've not properly studied or are generally aware of any of the realities?
If this is McConnell's true position, then why not punt the decision and choices down to the people directly impacted? And isn't this a long running tenet of the Republican Party to allow greater individual freedoms? Isn't their broad philosophy: individual > state government > national government? (At least with respect to internal, domestic matters; in international matters the opposite relationships seem to dominate.)
tl;dr:<br /> Mitch McConnell believes in choice, just not in your choice.
Here's the actual audio from a similar NPR story:<br /> https://ondemand.npr.org/anon.npr-mp3/npr/me/2022/09/20220914_me_gop_sen_lindsey_graham_introduces_15-week_abortion_ban_in_the_senate.mp3#t=206
McConnell is also practicing the Republican party game of "do as I say and not as I do" on Graham directly. He's practicing this sort of hypocrisy because as leadership, he's desperately worried that this move will decimate the Republican Party in the midterm elections.
There's also another reading of McConnell's statement. Viewed as a statement from leadership, there's a form of omerta or silent threat being communicated here to the general Republican Party membership: you better fall in line on the party line here because otherwise we run the risk of losing power. He's saying he's leaving it up to them individually, but in reality, as the owner of the purse strings, he's not.
Thesis:<br /> The broadest distinction between American political parties right now seems to be that the Republican Party wants to practice fascistic forms of "power over" while the Democratic Party wants to practice more democratic forms of "power with".
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www.theoi.com www.theoi.com
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Eleans call the pillar of Oenomaus is in the direction of the sanctuary of Zeus as you go from the great altar.
Pillar of Oenomaus should be a tag added. Wish there was a better location description
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www.theoi.com www.theoi.com
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an altar of Artemis of the Market,
Another possible tag? How many alters should we consider important to tag?
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an altar of Aphrodite
Could this be a potential tag on the map that we dont have?
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dhdebates.gc.cuny.edu dhdebates.gc.cuny.edu
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Tweeting has rapidly become an integral part of the conference scene, with a subset of attendees on Twitter providing real-time running commentary through a common “tag” (#mla09, for example)
I can see how this statement could relate to the previous reading (Ch. Introduction The Digital Humanities Moment) about there being too many people practicing the digital humanities. When hashtags get used and everyone starts contributing information, misinformation can spread just as easily as facts. Maybe this is an example of the kind of situation Gold implied when he said people can ask "disruptive questions"?
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kurs.bibel-fuer-alle.net kurs.bibel-fuer-alle.net
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Wie
Nachdem Gott den Menschen am sechsten Tag schuf, sagte er dass es sehr gut war. Nachdem er [der Mensch] dann im Garten Eden das einzige Gebot brach, dass seinen geistlichen Tod herbeiführte und ihn von Gott trennte, wurde es nötig, dass Gott den Menschen von dieser Trennung erlöst. Die Erlösung kommt nur durch den Glauben an den Erlöser (Jesus Christus) selber, er befreit uns vom geistlichen Tod und hat unsere Schuld auf sich selbst genommen. Er hat uns Erlöst von unserer Schuld, sie kommt nur durch ihn.
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blog.dblp.org blog.dblp.org
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whenever you visit a publication details page in dblp, your browser will automatically load further available information from the OpenAlex API. Currently, two pieces of information will be loaded. The first one is a tag cloud of the contained concepts of a paper. OpenAlex uses more than 65k different concepts, extracted from WikiData and arranged hierarchically in a tree. This concept tree is a modified version that is based on the earlier classification work done for the original MAG, and its concepts are identified by an automated classifier that was trained on MAG data.
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lvc.instructure.com lvc.instructure.com
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Be sure to TAG your annotations using the concepts from Norton,
THIS WILL HELP WITH ORGANIZATION! USE IT (talking to myself here)
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corpgov.law.harvard.edu corpgov.law.harvard.edu
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But do ESG ratings really deliver on the promise? Are highly-ranked ESG businesses really more caring of the environment, more selective of the societies in which they operate, and more focused on countries with good corporate governance? In short, is ESG really good? The answer is no.
black box
opaque score
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www.researchgate.net www.researchgate.net
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derstand basic vocabulary such as words for toys and commands (Walton &McConocha, 1996; Warden & Warner, 1928). In a study by Mitchell andEdmonson (1999), people generally spoke in short, repetitive utterances,with 7 words (including “come,” the dog’s name, and “ball”) accounting forabout 50% of the words used, and commands (imperatives) for over 50% ofthe utterances. However, people also talk to dogs in ways that are unsuitablefor the dog’s comprehension. In the Mitchell and Edmonson study, 377 dif-ferent words accounted for the other 50% of people’s output, and over 10%of their utterances were questions (which, of course, the dogs could not an-swer). Talk to dogs at times seems devoted to producing a conversation-likeengagement, with little expectation of comprehension.Talk to young infants (“baby talk”) shares with dog talk a focus oncontrol and conversation-like engagement (Ferguson, 1977; McDonald &Pien, 1982; Newport, 1977; Snow, 1972, 1977). In contrast, however, peo-ple do not expect infants to understand talk’s content (Garnica, 1977). Inmany cultures, talk to infants is marked by being shorter or slower, mostlyabout the present situation, and having a higher pitch (or more exaggeratedsigns), many diminutive word forms, lower mean length of utterance(MLU), and greater repetitiveness than utterances to adults (e.g., Casa-grande, 1948/1964; Ferguson, 1964; Jocic′, 1978; Newport, 1977; Remick,1976; Snow, 1972).These features are not universally present, however. Not all culturesmark talk to infants with a distinct register (Ochs & Schieffelin, 1984;Ratner & Pye, 1984; Schieffelin, 1990). The age of infants when peoplebegin to speak to them and the age at which adults stop doing baby talkvaries cross-culturally (Casagrande, 1948/1964; Fernald & Morikawa,1993; Harkness, 1976). In addition, features prominent in baby talk insome cultures are less prominent in others. For example, the high pitch socommon to baby talk in several cultures (Fernald et al., 1989; Garnica,1977; Masataka, 1992b; Shute & Wheldall, 1989), and especially salientin American English, is used in Quiche Mayan to speak to high-status per-sons (Ratner & Pye, 1984). Even within a culture, mothers may move inand out of baby talk, and features present in one person’s baby talk maynot be in another’s, based on social status of the participants, context, orindividual style (Blount & Padgug, 1977; Della Corte, Benedict, & Klein,1983; Ferguson, 1977; Kaye, 1980; Snow et al., 1976; Wills, 1977;Zeidner, 1983). The baby’s age also influences the type of baby talk used.According to Kaye (1980), one type, baby talk 1 (BT1), addressed to 1- to6-month-old babies who have no comprehension of English, contains few184 Robert W. Mitchell diminutives, very short MLUs (2.76 words), repetitive utterances, andhigh rates of phatics (21%) and immediate exact repetitions (16%). Theother type, baby talk 2 (BT2), addressed to 2-year-olds (who understandand use English), contains more diminutives, longer MLUs (3.68 words),fewer immediate exact repetitions (<4%), and presumably fewer phatics.These differences raise questions as to which aspects of baby talk make ita distinct register of talk within a culture.Many features of baby talk are found in talk to dogs. Indeed, similartalk is sometimes directed by caregivers to care receivers (Blount, 1977),whether these receivers are animals, foreigners, elderly patients, retardedpeople, lovers, or even dolls (Caporael, Lukaszewski, & Culbertson, 1983;DePaulo & Coleman, 1986; Ferguson, 1964, 1977; Rã±e-DraviÃa, 1977;Sachs & Devin, 1976). Talk to these other recipients is called secondarybaby talk to mark its similarity to talk to infants (Caporael, 1981; Fergu-son, 1977).Secondary uses of baby talk are presumed to derive from its primaryuses (Ferguson, 1977). For example, in both forms of baby talk, high-pitched speech expresses affection, engages attention, and makes compre-hension easier (Caporael, 1981; Fernald & Mazzie, 1991; Garnica, 1977;Masataka, 1992b; Montepare, Steinberg, & Rosenberg, 1992; Sachs,1977; Snow, 1978), and short or slow utterances make comprehensioneasier for the typically less attentive or linguistically endowed receiver(Ferguson, 1977; Freed, 1981; Masataka, 1992a; Newport, Gleitman, &Gleitman, 1977; Pellegrino & Scopesi, 1990; Snow, 1972; cf. Kaye, 1980;Montepare et al., 1992). However, some characteristics of baby talk mayoccur because of the nature of the interaction, rather than because they areaspects of a distinct linguistic register called baby talk. For example, re-petitive utterances in baby talk may result because mothers focus on (andtalk about) one topic at a time, whether it concerns an object or theirbaby’s short bursts of repetitive behavior (Kaye, 1980; Messer, 1980).Repetition is also common when addressees are not attending or respon-sive to the speaker’s attempts to control their behavior (Cross, 1978; Dunn& Kendrick, 1982; Gleason, 1977; Mitchell & Edmonson, 1999; Newport,1977; Pellegrino & Scopesi, 1990; Schaffer & Crook, 1979), again indi-cating a consistent focus. In fact, when the focus of conversation betweenadults is delimited, partial (but not exact) repetition of utterances is com-mon (Kaye, 1980).One explanation that is distinctive to primary baby talk (also calledmotherese) is that it can develop infants’ linguistic skills by teaching in-Americans’ Talk to Dogs 185 fants important features of language (Newport et al., 1977; Snow, 1972), ahypothesis that, in various incarnations, remains controversial (Furrow,Nelson, & Benedict, 1979; Murray, Johnson, & Peters, 1990; Snow, Perl-man, & Nathan, 1987; Wells & Robinson, 1982). Some aspects of primarybaby talk, such as frequent use of deictic (naming) utterances, support a tu-torial function, whereas others do not. For example, a high proportion ofwell-formed sentences was initially thought to be a special characteristic ofmotherese, but in fact baby talk’s brevity breeds grammatical correctness—shorter sentences tend to be more grammatically correct than longer sen-tences no matter to whom they are spoken (Hirsh-Pasek & Treiman, 1982).Secondary baby talk is interesting to compare to primary baby talkbecause the former clearly does not have any tutorial function (Caporael etal., 1983; Ferguson, 1977; Hirsh-Pasek & Treiman, 1982; McLeod, 1993).Thus, any similarities between secondary and primary baby talk suggest afunction not solely tutorial as an explanation.Indeed, one argument against the “motherese is language tutoring”idea is that talk very much like motherese is used toward dogs (Ferguson,1964; Hirsh-Pasek & Treiman, 1982; Murray et al., 1990; Scollon, 1976).For example, Hirsh-Pasek and Treiman (1982) argued that “the strikingsimilarities between motherese and [talk to dogs] indicate that mothereseis not initially tailored to the linguistic or cognitive level of the child . . .[and thus plays] a broader and less specific role than that of teaching for-mal language structure” (p. 235). Yet how similar talk to infants and talk todogs is remains unclear. Oddly, the evidence used to support the claim ofstriking similarities between talk to infants and dogs is that both differ fromtalk between adults in similar ways, rather than that these forms of talk arethemselves very much alike. Indeed, surprisingly few empirical data haveaddressed how many characteristics are shared by secondary and primarybaby talk within a given culture and language. Is talk the same toward bothbabies and dogs? The fact that the talk of only four people to their dogs isthe basis for comparisons between talk to infants and dogs (Hirsh-Pasek &Treiman, 1982) suggests that a more extensive comparison is needed toclarify the accuracy of similarities and differences between them.Using methods employed to analyze talk to infants, the purpose ofthis article is to analyze talk during play episodes with familiar and unfa-miliar dogs by 23 people. I compare talk to dogs (in this study) with talk toinfants (from previous studies) to determine how the forms of talk are sim-ilar, detect differences that might support a tutorial function distinct tobaby talk, and evaluate the significance of these similarities and dissimi-186 Robert W. Mitchell larities. This analysis also raises questions about exactly what constitutesevidence for a distinct register of speech called baby talk.I examined talk to dogs during play because many studies of moth-erese looked at talk to infants during play and other structured, focused,and repetitive activities (Cross, 1977; Kaye, 1980; Messer, 1980; Murrayet al., 1990; Schaffer & Crook, 1979; Snow, 1977; Stern, Beebe, Jaffe, &Bennett, 1977; Sylvester-Bradley & Trevarthen, 1978). However, it is im-portant to remember that play is only one situation in which people talk todogs. For example, people appear to utter questions and declaratives morefrequently than imperatives when interacting in a low-key way with a dog(Robins, Sanders, & Cahill, 1991), a direct contrast with talk during play(Mitchell & Edmonson, 1999). I focus on prosodic, lexical, complexity,redundancy, and content features of talk that have been documented asfeatures of talk to infants (described later; see Kaye, 1980), as well as con-sidering issues of coordination. A first issue of coordination concerns therelations between MLU and the frequencies of diminutives, phatics, andimmediate exact repetitions. Kaye (1980) suggested that BT1 is usedwhen the mother pretends that the infant is a conversant, whereas BT2 oc-curs when the child is actually able to converse and understand. Talk todogs should, presumably, fall between these two types of baby talk, asdogs understand but cannot converse. The other coordination issue con-cerns whether features suggestive of a conversation (diminutives, endear-ments, questions—especially tag questions [tags] and postcompleters[PCs]—and answering these questions) tend to occur together, andwhether features suggestive of a desire to control the other (imperatives,attention-getting devices [AGDs], and repetitiveness) appear together(Dunn & Kendrick, 1982; Snow, 1977). Because playing with dogs is pre-sumably about control (Mitchell & Edmonson, 1999), I expect dog talk tohave few diminutives, endearments, questions, and answers to questions,and more imperatives and AGDs, as well as repetitive utterances
Introduction: The introduction to a scholarly article describes the topic or problem the authors researched. Sometimes it's labeled, sometimes it's not. The authors will present the thesis of their argument or the goal of their research. The introduction may also discuss the relevance or importance of the research question. An overview of related research and findings, called a literature review, may appear in the introduction, though the literature review may be in its own section.
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www.vox.com www.vox.com
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a big setback for the Republican-led states that have been suing the president over the metric, known as the social cost of carbon: a measure, in dollars, of how much damage results from emitting 1 ton of carbon dioxide. Being able to discuss the damage in terms of a precise dollar amount is important because it allows policymakers to show when the benefits of preventing global warming are greater than the costs. At some point it just becomes cheaper to switch to sustainable systems instead of coping with all the wildfires, floods, droughts, and heat waves that result from unsustainable systems.
The idea of social cost of carbon (SCC) is fascinating: seemingly it aims to make the social costs of climate crisis objective by giving them a price tag. But then it becomes clear that the price tag depends on political / value judgements concerning the future, on which the idea of "discounting" depends.
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royjth.bergbuilds.domains royjth.bergbuilds.domains
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The thought experiment and the resultant message the chapter tried to deliever was refreshing because I have always believed agriculture is the no-brainer tag of what defines a civilization.
I totally agree! It was cool to have a walk through on what a civilization entails to the author rather than them operating on assumption.
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legacy.reactjs.org legacy.reactjs.org
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React treats components starting with lowercase letters as DOM tags. For example, <div /> represents an HTML div tag, but <Welcome /> represents a component and requires Welcome to be in scope.
Always start component names with a capital letter.
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www.biorxiv.org www.biorxiv.org
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Author Response
Reviewer #3: (Public Review):
In this ms Li et al. examine the molecular interaction of Rabphilin 3A with the SNARE complex protein SNAP25 and its potential impact in SNARE complex assembly and dense core vesicle fusion.
Overall the literature of rabphilin as a major rab3/27effector on synaptic function has been quite enigmatic. After its cloning and initial biochemical analysis, rather little new has been found about rabphilin, in particular since loss of function analysis has shown rather little synaptic phenotypes (Schluter 1999, Deak 2006), arguing against that rabphilin plays a crucial role in synaptic function.
While the interaction of rabphilin to SNAP25 via its bottom part of the C2 domain has been already described biochemically and structurally in the Deak et al. 2006, and others, the authors make significant efforts to further map the interactions between SNAP25 and rabphilin and indeed identified additional binding motifs in the first 10 amino acids of SNAP25 that appear critical for the rabphilin interaction.
Using KD-rescue experiments for SNAP25, in TIRF based imaging analysis of labeled dense core vesicles showed that the N-terminus of SN25 is absolutely essential for SV membrane proximity and release. Similar, somewhat weaker phenotypes were observed when binding deficient rabphilin mutants were overexpressed in PC12 cells coexpressing WT rabphilin. The loss of function phenotypes in the SN25 and rabphilin interaction mutants made the authors to claim that rabphilin-SN25 interactions are critical for docking and exocytosis. The role of these interaction sites were subsequently tested in SNARE assembly assays, which were largely supportive of rabphilin accelerating SNARE assembly in a SN25 -terminal dependent way.
Regarding the impact of this work, the transition of synaptic vesicles to form fusion competent trans-SNARE complex is very critical in our understanding of regulated vesicle exocytosis, and the authors put forward an attractive model forward in which rabphilin aids in catalyzing the SNARE complex assembly by controlling SNAP25 a-helicalicity of the SNARE motif. This would provide here a similar regulatory mechanism as put forward for the other two SNARE proteins via their interactions with Munc18 and intersection, respectively.
We thank the reviewer #3 for the summary of the paper and for the praise of our work. The point-to-point replies are as follow:
While discovery of the novel interaction site of rabphilin with the N-Terminus of SNAP25 is interesting, I have issues with the functional experiments. The key reliance of the paper is whether it provides convincing data on the functional role of the interactions, given the history of loss of function phenotypes for Rabphilin. First, the authors use PC12 cells and dense core vesicle docking and fusion assays. Primary neurons, where rabphilin function has been tested before, has unfortunately not been utilized, reducing the impact of docking and fusion phenotype.
We have discussed these questions as mentioned in our response to Essential Revisions 3 and added this corresponding passage to the Discussion section (pp.18-19, lines 407-427).
In particular the loss of function phenotype in figure 3 of the n-terminally deleted SNAP25 in docking and fusion is profound, and at a similar level than the complete loss of the SNARE protein itself. This is of concern as this is in stark contrast to the phenotype of rabphilin loss in mammalian neurons where the phenotype of SNAP25 loss is very severe while rabphilin loss has almost no effect on secretion. This would argue that the N-terminal of SNAPP25 has other critical functions besides interacting with rabphilin. In addition, it could argue that the n-Terminal SNAP25 deletion mutant may be made in the cell (as indicated from the western blot) but may not be properly trafficked to the site of release
To test whether the N-peptide deletion mutant of SN25 can properly target to the plasma membrane, we overexpressed the SN25 FL or SN25 (11–206) with C-terminal EGFP-tag in PC12 cells and monitored the localization of SN25 FL-EGFP and SN25 (11–206)-EGFP near the plasma membrane by TIRF microscopy. We observed that the average fluorescence intensity of SN25 (11–206)-EGFP showed no significant difference with SN25 FL-EGFP as below, suggesting that the N-peptide deletion mutant may not influence the trafficking of SN25 to plasma membrane.
(A) TIRF imaging assay to monitor the localization of SN25-EGFP near the plasma membrane. Overexpression of SN25 FL-EGFP (left) and SN25 (11–206)-EGFP (right) using pEGFP-N3 vector in PC12 cells. Scale bars, 10 μm. (B) Quantification of the average fluorescence intensity of SN25-EGFP near the plasma membrane in (A). Data are presented as mean ± SEM (n ≥ 10 cells in each). Statistical significance and P values were determined by Student’s t-test. ns, not significant.
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medium.com medium.com
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我還記得那是我使用 Evernote 的第 4 年。當我的筆記數量突破 4000 大關之後我發現,我突然警覺到:累積這麼多的筆記又如何,我根本不會去用啊!就算能找到又怎樣,這些筆記頂多只是一堆的備忘錄,但對於我想要寫文章、做決策幫助超級少…
真的! 很多筆記是當下的靈感,預計未來在某些適當時機要用的,通常是備課要增加資訊豐富度時用。所以存了一堆。但隨著閱讀不斷的增加,靈感筆記也隨之暴增,即便有粗略以資料夾區分(我不習慣用tag),但是,這麼大量的靈感筆記,已經造成我內心裡極大的壓力,甚至想到要再次整理與組織它時,資料龐大與凌亂到造成我心裡很大的壓力,甚至隱隱地開始討厭筆記起來,但是又不能不使用它,我實在對自己不牢靠的記憶感到抱歉!所以又繼續懷抱著既恨又無法割捨的心態下,繼續囤積筆記。別人的囤物症是衛生紙、鞋子等等,我囤物症是筆記(掩面)。
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It should, at the very least, tag the tile as "done", and not expose it as a playable tile again.
that would be if decision was "yes" or "no", I guess.
Does the game provider know who is playing?
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You can use Danger to codify your team's norms, leaving humans to think about harder problems.
annotation meta: may need new tag: codify a team's norms
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lists.w3.org lists.w3.org
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1) get an extra 'search' attribute on to the <a> tag in HTML so that we have: e.g. <a href='...' search='...'>link text</a> 2) If there's take-up, then later on push for adding a date-time of creation attribute to <a>. This will add link history to the internet. The way (1) works is someone sticks the basic href to a page in the href attribute, and then sticks the text they want to link to in the search attr. The browser fetches the page, and as a secondary action (at user option) searches for the text.
Another approach, inspired by the
<label>
element, would be to encode these selectors as separate<link>
elements in the head. You could write your links as normal, and then add these<link rel="selector" for="foo" href="XXX[...]X" />
to your document (wherefoo
is the ID of the<a>
element, and thehref
value is selector).
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Note: This rebuttal was posted by the corresponding author to Review Commons. Content has not been altered except for formatting.
Learn more at Review Commons
Reply to the reviewers
Reviewer #1 (Evidence, reproducibility and clarity (Required)):
In this paper, Staneva et al describe a novel complex found at RNA PolII promoters that they term the SPARC. The manuscript focuses on defining the core components of the complex and the pivotal role of SET27 in defining its function, and role in PolII transcription. This manuscript is a logical follow on from an initial paper (Staneva et al, 2021) by the same authors where they systematically analyzed chromatin factors, and their role in both transcription start and termination. What is also very clear, is that this complex is one made of histone readers and writers which suggests its function is to change the chromatin structure around a PolII promoters. The authors show that this complex is necessary for the correct positioning of PolII and directionality of transcription.
This was a well-designed study and well written and clear manuscript that provides fascinating insight transcription control in bloodstream form parasites.
I have no major comments only a few minor ones.
1) Localisation of the different SPARC components appears to be either nuclear or nuclear and cytoplasmic. - Both SET27 and CRD1 show a nuclear and cytoplasmic localisation in the bloodstream form IFA (Supplementary Fig 1B), but only a nuclear localisation procyclic form.
Did the authors attempt C terminally tagging SET27, CRD1 to see if this resulted in a change in the pattern?
We have not tagged either protein at the C terminus, however SET27 (Tb927.9.13470) has been tagged both N- and C-terminally in procyclic form (PF) cells as part of the TrypTag project (http://tryptag.org). In both cases, SET27 localized to the nucleus, suggesting that the differences in localization we observe for SET27 depend on the life cycle stage, and not on the position of the tag. One caveat is that in the TrypTag project proteins are tagged with mNeonGreen whereas in our study proteins were tagged with YFP. Based on our images, CRD1 appears to be predominantly nuclear in both bloodstream form (BF) and PF parasites. CRD1 (Tb927.7.4540) has been tagged only N-terminally in PF cells as part of the TrypTag project where it has also been classified as mostly nuclear with only 10% of cells showing cytoplasmic localization for CRD1.
We are well aware that tags can alter the behaviour of a protein. Absolute confirmation of location will require the generation of antibodies that detect untagged proteins. However, this is a longer-term undertaking. We have added the following statement to the Results section to address the point raised:
“We tagged the proteins on their N termini to preserve 3′ UTR sequences involved in regulating mRNA stability (Clayton, 2019). We note, however, that the presence of the YFP tag and/or its position (N- or C-terminal) might affect protein expression and localization patterns”.
- The point is made that JBP2 shows a 'distinct cytoplasmic localisation' in PF cells. by this logic, the SET27 localisation in BF is also distinctly cytoplasmic and a nuclear enrichment is not clear.
Indeed the reviewer is correct - we have inadvertently over accentuated the significance of this difference in the text. We had emphasized the predominantly cytoplasmic localization of JBP2 in PF trypanosomes as potentially related to its weaker association with other (predominantly nuclear) SPARC components in the mass spectrometry experiments. The presence of SET27 in the nuclei of both BF and PF cells is confirmed by a positive ChIP signal. We have revised the manuscript text by changing “distinct cytoplasmic” to “predominantly cytoplasmic” to describe JBP2 localization in PF cells. We hope that this resolves the issue.
- Why would the localisation pattern change between life cycle stages? Surely PolII transcription should remain the same?
Although our analysis suggests that there may be some shift in SET27 and JBP2 localization between BF and PF stages, sufficient amounts of these proteins may be present in the nucleus for proper SPARC assembly and RNAPII transcription regulation in both life cycle forms. The proportion of SET27 and JBP2 proteins that localizes to the cytoplasm may have functions unrelated to transcription.
2) Several of the images in Supplementary Fig 1B seem to show foci in the nucleus (CSD1, PWWP1, CRD1). Do you see foci throughout the cell cycle or just in G1/S phase cells as shown here?
We have not systematically investigated protein localization at different cell cycle stages, so we do not have microscopy images for all proteins at all stages of the cell cycle. However, the images we did collect suggest the punctate pattern is preserved for CRD1 in the G2 phase in both BF and PF cells (see below) as we showed in Supplemental Figure S1B for cells with 1 kinetoplast and 1 nucleus (G1/S phase cells). The significance of these puncta remains to be determined.
3) In Figure 6, what does 'TE' stand for?
TE denotes transposable elements. We have added this to the figure legend.
4) The authors show this interesting link between SPARC complex and subtelomeric VSG gene silencing. -In the CRD1 ChIP or RBP1 ChIP, are there any other peaks in telomere adjacent regions in the WT cells similar to that seen on chromosome 9A? And does the sequence at this point resemble a PolII promoter?
Apart from peaks located on Chromosome 9_3A, there are other CRD1 and RPB1 ChIP peaks in chromosomal regions adjacent to telomeres in WT cells. We observed broadening of RPB1 distribution in these regions upon SET27 deletion, similar to what we show for Chromosome 9_3A. In particular, wider RPB1 distribution on Chromosome 8_5A coincides with upregulation of 10 VSG transcripts. These two loci explain most of the differentially expessed genes (DEGs) detected, but other subtelomeric regions show a similar pattern. We have added the following statement to the Results section to highlight that the phenotype shown for Chromosome 9_3A is not unique:
“We also observed a similar phenotype at other subtelomeric regions, such as Chromosome 8_5A where 10 VSGs and a gene encoding a hypothetical protein were upregulated upon SET27 deletion (Supplemental Table S3)”.
Cordon-Obras et al. (2022) have recently defined key sequence elements present at one RNAPII promoter. We searched for similar sequence motifs but failed to identify them as underlying CRD1 and RPB1 ChIP peaks, highlighting the likely sequence heterogeneity amongst trypanosome RNAPII promoters. To address this point, we have added the following sentence to the Discussion:
“Sequence-specific elements have recently been found to drive RNAPII transcription from a T. brucei promoter (Cordon-Obras et al., 2022), however, we were unable to identify similar motifs underlying CRD1 or RPB1 ChIP-seq peaks, suggesting that T. brucei promoters are perhaps heterogeneous in composition”.
-In the FLAG-CRD1 IP (Figure 3B), the VSG's seen here are not represented (as far as I can tell) in Figure 6B and C. If my reading is correct could, is this a difference in the FC cut off for what is significant in these experiments?
The VSGs detected in the FLAG-CRD1 IP from set27D/D cells are indeed different from the ones shown in Figure 6 (even after setting the same fold change cutoffs). We have highlighted this by adding the following statement to the Results section: “Gene ontology analysis of the upregulated mRNA set revealed strong enrichment for normally silent VSG genes (Figure 6B-D) which were distinct from the VSG proteins detected in the FLAG-CRD1 immunoprecipitations from set27D/D cells (Figure 3B)”.
The VSGs in the mass spectrometry experiments likely represent unspecific interactors of FLAG-CRD1. To clarify this, we have added the following statement to the Results section: ”Instead, several VSG proteins were detected as being associated with FLAG-CRD1 in set27D/D cells, though it is likely that these represent unspecific interactions”.
Reviewer #1 (Significance (Required)):
Trypanosomes are unusual in the way that they transcribe protein coding genes. Recent advances have defined the chromatin composition at the TSS and TTS, and the recent publication of a PolII promoter sequence(s) further adds to our understanding of how transcription here is regulated. Defining the SPARC complex now add to this understanding and highlights the role of potential histone readers and writers. I think that this will be of interest to the kinetoplastid community especially those working on control of gene expression.
Our lab studies gene expression and antigenic variation in T. brucei.
Reviewer #2 (Evidence, reproducibility and clarity (Required)):
In this manuscript, the authors identify a six-membered chromatin-associated protein complex termed SPARC that localizes to Transcription Start Regions (TSRs) and co-localizes with and (directly or indirectly) interacts with RNA polymerase II subunits. Careful deletion studies of one of its components, SET27, convincingly show the functional importance of this complex for the genomic localization, accuracy, and directionality of transcription initiation. Overall, the experiments are well and logically designed and executed, the results are well presented, and the manuscript is easy to read.
There are a few minor points that would benefit from clarification and/or from a more detailed discussion:
1) The concomitant expression of many VSGs (37) in a SET27 deletion strain is remarkable and has important implications for their normally monoallelic expression. It is well established that VSG expression in wild-type T. brucei can only occur from one of ~15 subtelomeric bloodstream expression sites, which include the ESAGs. This result implies that VSG genes are also transcribed from "archival VSG sites" in the genome, not only from expression sites. Are there VSGs from the silent BESs among the upregulated VSGs? Is there precedence in the literature for the expression of VSGs from chromosomal regions besides the subtelomeric expression sites?
Our analysis of differentially expressed genes (DEGs) revealed that 43 VSG genes (37 of which are subtelomeric) and 2 ESAG genes are upregulated in the absence of SET27. Both ESAGs but none of the upregulated VSGs in set27D/D cells are annotated as located in BES regions. While it is possible that recombination events have resulted in gene rearrangements between the reference strain and our laboratory’s strain, at least some of the upregulated VSGs are likely to be transcribed from non-BES archival sites. VSG transcript upregulation from non-BES regions was also recently described by López-Escobar et al (2022).
We note that the upregulated mRNAs in set27D/D are still relatively lowly expressed (Figure 6C). This is presumably insufficient to coat the surface of T. brucei, and expression from BES sites instead may be required to achieve this. We have revised the manuscript Discussion section to make these points more clear:
“Bloodstream form trypanosomes normally express only a single VSG gene from 1 of ~15 telomere-adjacent bloodstream expression sites (BESs). In contrast, in set27D/D cells we detected upregulation of 43 VSG transcripts, none of which were annotated as located in BES regions. Recently, López-Escobar et al (2022) have also observed VSG mRNA upregulation from non-BES locations, suggesting that VSGs might sometimes be transcribed from other regions of the genome. However, the VSG transcripts we detect as upregulated in set27D/D were relatively lowly expressed (Figure 6C) and may not be translated to protein or be translated at low levels compared to a VSG transcribed from a BES site”.
2) The role of SPARC in defining transcription initiation is compelling. It's less clear to the reviewer if the observed transcriptional silencing within subtelomeric regions can also ascribed to SPARC. Have the authors considered the possibility that some components of the SPARC may be shared by other chromatin complexes, which could be responsible for the transcriptional activation of silent genes in SET27 deletion mutants?
We cannot rule out indirect effects through the participation of some SPARC components in other complexes operating independently of SPARC. Indeed, the transcriptional defect within the main body of chromosomes appears to be somewhat different from that observed at subtelomeric regions, particularly with respect to distance from SPARC. We have added a statement in the Discussion section to highlight the possibility raised by the reviewer:
“However, an alternative possibility is that transcriptional repression in subtelomeric regions is mediated by different protein complexes which share some of their subunits with SPARC, or whose activity is influenced by it”.
3) The authors mention that the observed interaction of FLAG-CRD1 with VSGs in the immunoprecipitations (Fig. 3B) is evidence for the actual expression of normally silent VSGs on the protein level. This is true, but it should be spelled out that this interaction is nevertheless likely an artifact, at least the physiological relevance of these interactions is questionable.
We agree that these are likely background associations and have added the following statement to the Results section to clarify this point:
“Instead, several VSG proteins were detected as associated with FLAG-CRD1 in set27D/D cells, though it is likely that these represent unspecific interactions”.
To avoid unnecessary confusion we have also removed the following sentence from the revised Discussion:
“The interactions of FLAG-CRD1 with VSGs in the affinity selections from set27Δ/Δ cells indicate that some of the normally silent VSG genes are also translated into proteins in the absence of SET27”.
4) "ophistokont" is misspelled in the introduction
Thanks for noticing. We have corrected it to “Opisthokonta”.
Reviewer #2 (Significance (Required)):
The manuscript by Staneva et al. addresses the fundamental regulatory mechanism of gene transcription in the protozoan parasite Trypanosoma brucei, a highly divergent eukaryotic organism that is renowned for unusual features and mechanisms in gene regulation, metabolism, and other cellular processes. While post-transcriptional regulation is prevalent and relatively well established in T. brucei, much less is known about the mechanism of transcription initiation and transcriptional control, in part due to the general paucity of well-defined conventional promoter regions in this organism (only very few have been identified thus far). In this context, the work by Staneva et al. is highly significant and represents an important contribution to the field of gene regulation and chromatin biology in T. brucei and other related kinetoplastid parasites.
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keithctaylor.gumroad.com keithctaylor.gumroad.com
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GoutPal Research
My GoutPal Research notes are similar to GoutPal Triage. But they're a response to my own interests and concerns. As such, I usually assign them lower priority than my notes on specific issues.
In fact, this note is an example. Because I'm researching how to best implement my new GoutPal Links services. Then I'm adding notes like this to describe my progress towards a complete set of documented resources.
As I move forward, I will publish extensive notes for subscribers and for members. That will give readers choices about extra information beyond these public gout research notes.
Please note that those public gout notes are from every Hypothes.is user who writes about gout. Currently, that's only me. But I hope other gout sufferers will join me. At which point, you can find my gout notes with my user tag.
To get more gout research notes, join the waitlist for gout subscribers.
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nikitahl.com nikitahl.com
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```html
<div class="select-container" data-content=""> <select class="select" id="words"> <option value="lorem ipsum dolor sit amet">Lorem ipsum dolor sit amet</option> <option value="lorem">Lorem</option> <option value="ipsum">Ipsum</option> <option value="dolor">Dolor</option> <option value="sit">Sit</option> <option value="amet">Amet</option> </select> </div>css .select { color: transparent; appearance: none; padding: 5px; background: transparent url("https://cdn4.iconfinder.com/data/icons/ionicons/512/icon-arrow-down-b-128.png") no-repeat calc(~"100% - 5px") 7px; background-size: 10px 10px; }
.select-container { position: relative; display: inline-block; }
.select-container::before { content: attr(data-content); pointer-events: none; position: absolute; top: 0; right: 10px; bottom: 0; left: 0; padding: 7px; font: 11px Arial, sans-serif; white-space: nowrap; text-overflow: ellipsis; overflow: hidden; text-transform: capitalize; }
js const selectContainer = document.querySelector(".select-container"); const select = selectContainer.querySelector(".select");
select.value = "lorem ipsum dolor sit amet"; selectContainer.dataset.content = select.value;
function handleChange(e) { selectContainer.dataset.content = e.currentTarget.value; }
select.addEventListener("change", handleChange); ```
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www.getrevue.co www.getrevue.co
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如果我们想要将信息记住,那是否可以顺应大脑的习惯,刻意地做出以上行为?比如刻意「使用」?基于这一点,视频作者总结的记忆方法是
- 在阅读的时候记笔记:这个可以是在书本上进行高亮或者使用在书上写笔记。
- 在读完书后,重新阅读你的笔记,并修改笔记:这一步是将书上的笔记转移到卡片上。
- 对笔记进行分类和归档:可以给笔记卡片进行分类,或者打上 tag。
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www.biorxiv.org www.biorxiv.org
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Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.
Learn more at Review Commons
Referee #1
Evidence, reproducibility and clarity
This study shows that the ORF1 protein of the LINE-1 retroelement forms puncta in vivo that they define as cytoplasmic biomolecular condensates based on the characterization of the biophysical properties of ORF1p condensates in vitro.
Defective retrotransposition of some ORF1p mutants correlates with defects in puncta formation in vivo and alteration of biophysical properties of in vitro condensates leading the authors to conclude that condensation of ORF1p is required for retrotransposition.
The study combines biochemical reconstitution, biophysic analysis and live-cell imaging. In particular, the authors take advantage of a new powerful tool they have developed based on the tagging of ORF1 within a functional L1 reporter element. The fluorescent tag allows following the dynamics of ORF1p by live-cell imaging.
The key conclusion is that ORF1p condensation is important for L1 retrotransposition. The correlation is clearly shown but raises several questions: Is the defect in ORF1p condensation the only explanation for the retrotransposition defects of the ORF1p mutants analyzed here? Can we exclude that the mutations in ORF1p affect other functions of the protein such as its binding to RNA (as in the case of the R261 mutant) and cis-preference, or its binding to other factors involved in L1 replication? Could the loss of these functions affect L1 retrotransposition independently of ORF1p condensation?
Major comments:
On several occasions, the authors propose that ORF1p-HALO dynamics in vivo is linked to its co-translational association with L1 RNA. However, they never show the presence of L1 RNAs in ORF1p-HALO puncta in vivo. To strengthen the conclusion that the puncta observed in vivo are L1 RNPs, the authors should add experiments showing the presence of L1 RNA in the cytoplasmic puncta (by RNA FISH) or that the puncta are dependent on the presence of L1 RNA (expressing ORF1p-HALO alone should not be sufficient for puncta formation). These experiments seem to be realistic in few weeks with the tools already available in the laboratory.
Apart from this comment, the authors are cautious in their conclusions. It is clear, as they indicate in the Discussion, that showing that ORF1p condensation is also required for the mobility of other retroelements will strengthen the implication of ORF1p condensation in L1 replication.
The data are well presented and the methods described in detail so that others should be able to use them. The experiments seem to be adequately replicated and the statistical analysis adequate.
Minor comments:
Figure 1F: Having the pictures of cell nuclei (like in Figure 1D) would be nice to know how many cells we are looking at in this panel.
Figure 2E: it is surprising that there is no correlation between the ORF1p:RNA ratio and the number of individual fusion events (i.e. curves of ORF1p+RNA 10000:1 and 1000:1 overlap while 3000:1 is different). Could the authors discuss this point?
Previous studies are appropriately referenced. Text and figures are clear and precise.
Referees cross-commenting
The main critical points shared by all reviewers are: 1) the need to show the presence of LINE1 RNAs in ORF1p condensates in vivo and 2) the lack of evidence for causality between ORF1 condensate formation and L1 transposition efficiency (At this stage, the authors should moderate their conclusions, especially in the abstract). Regarding the other reviews, we noticed the need to cite additional relevant studies in the field (reviewer #2) and the interesting points raised by reviewer #3 to investigate the formation of ORF1 condensates in an endogenous situation, and whether other RNAs do affect ORF1p condensates.
Significance
The study is technically interesting in that it describes a new system for tracking ORF1p puncta formation in vivo. The findings are not unexpected because it comes after the publication of Newton et al. in 2021 (PMID : 33798566), describing that ORF1p does phase separation in vitro. Furthermore, the fact that RNPs form "membrane-less" structures is already established in other situations as the authors point out. Compared to Newton et al., condensates are better-defined biochemically, especially for RNA association features and in vivo dynamics.
The ORF1 protein is widely studied for its role in L1 retrotransposition. The protein forms a homotrimer in vitro, binds to L1 mRNA in a cis-preferential manner, and is required for retrotransposition. On the other hand, RNA-binding proteins are often involved in the formation of membrane-less organelles (stress granules, RNA processing bodies...). These observations suggest that ORF1p may also form RNP condensates required for L1 retrotransposition. A study published in Biophysical Journal in 2021 (Newton et al. PMID: 33798566) has already reported the phase separation of the LINE-1 ORF1p that is mediated by the N-terminus and coiled-coil domain. This former study was based on in vitro microscopy and NMR approaches and is cited in the submitted manuscript. The study submitted to Rev commons goes further by analyzing the biochemical properties of ORF1p condensates in the presence of L1 RNA and by following in vivo condensates of ORF1p (WT or mutants) expressed from a functional L1 reporter element by live-cell imaging. The findings will interest a wide audience investigating the biology of retroelements and more particularly scientists who study the L1 retrotransposon.
I am an expert in retrotransposon biology but I do not work on L1. I am not expert enough to assess the quality and relevance of the biophysical experiments in the paper. In particular, panels 2D, 3B and 3D were difficult to analyze.
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www.top-password.com www.top-password.com
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Constantly spinning down/up can reduce the life of the hard disk, so I recommend you leave the drive spinning all the time, or set the drive to turn off after a longer period (one or two hours) of inactivity
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www.biorxiv.org www.biorxiv.org
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Review coordinated via ASAPbio’s crowd preprint review
This review reflects comments and contributions by Ruchika Bajaj and Gary McDowell. Review synthesized by Bianca Melo Trovò.
This study demonstrates the utility of an L-Methionine analog - ProSeMet - to tag and enrich proteins which have residues that are methylated in vivo, ex vivo and in vitro. Furthermore, the study demonstrates that this can be used in combination with mass spectrometry to identify these sites. Overall this is a useful, well-verified and well-described approach that will be helpful for future identification and investigation of methylation sites.
Major comments
It would be helpful if the manuscript could additionally discuss the reversibility of methylation generally, and the reversibility of the modification of protein residues by the alkyne group specifically, in the discussion, and whether that has any implications for their results. It may be that the dynamics of methylation and demethylation vary between the two; or it may be that they are the same - either way, that may affect how they suggest others use this method and interpret its results.
Perhaps related to the question of reversibility, it would be helpful if the manuscript would comment on whether these are “true” methylation sites or not; i.e. whether they consider all these methylation sites to be functional. Trying to determine this would be an interesting direction for future work, but for this study a reflection on whether these novel functional methylation sites are simply capable of being methylated, or are likely to be methylation sites that are meaningful biologically, would be helpful.
Results, ProSeMet competes with L-Met to pseudo methylate protein in the cytoplasm and nucleus: the manuscript claims that ProSeMet is not incorporated into newly synthesized proteins but rather converted to ProSeAM and used by native methyltransferases. There does appear to be some reduction in the labeling with ProSeMet on cycloheximide treatment in Figure 2D - could this suggest that it is incorporated into newly synthesized proteins as well as being converted to ProSeAM? If not, could the manuscript explain why not? This experiment clearly shows that in contrast to AHA labeling, there is still use of ProSeMet as a substrate when translation is inhibited; however, it is not clear how this demonstrates that it is not incorporated at all into newly synthesized proteins. If methyl has been incorporated in previously present proteins, perhaps this can be clarified in the text.
Results, ProSeMet competes with L-Met to pseudomethylate protein in the cytoplasm and nucleus: the conclusion that “Cell fractionation of the cytosolic and nuclear compartments followed by SDS-PAGE fluorescent analysis revealed no fluorescent labeling of the L-Met control” is correct but may be overstated as there appears to be some background in the cytosolic fraction.
Minor comments
- Introduction: Recommend including a mention to ProSeMet's permeability.
- Introduction, Figure 1: the last step with CuAAC and N3 labeling in the description of the Chemoenzymatic approach for metabolic MTase labeling is not clear. Please, add the description in the legend.
- Results, Figure 2D: the image suggests an overloaded gel, consider using an alternative gel image.
- Supplementary Material, Fig. S1: the data with L-met is only shown with T47D stacks.
- Supplementary Material, Fig. S3: please add the control for the no treatment condition.
- Results, Fig. 2A ‘ incubating for 30 m in L-Met free media’: Please confirm that the length of incubation was 30 minutes.
- Results, Enrichment of pseudo methylated proteins used to determine breadth of methyl proteome: Please provide some description for the SMARB1-deficient G401 cell line. Why smarb1 deficient?
- Results, Figure 3: Please define BP, MF, HP, NES, and label the x and y axes in panel D.
- Results, ProSeMet-directed pseudo methylation is detectable in vivo: Please, clarify if the administration was oral.
Comments on reporting
- Results, ProSeMet competes with L-Met to pseudo methylate protein in the cytoplasm and nucleus: Please verify the quantity reported: 5µg on SDS-PAGE gel seems low.
- Results, ProSeMet-directed pseudo methylation is detectable in vivo: the manuscript reports that “mice starved prior to ProSeMet injection had increased ProSeMet labeling in the heart, whereas mice fed prior to ProSeMet administration had increased labeling in the brain and lungs”. The error bars are large, it would be helpful to show the individual real data points for the graphs in Figure 4.
- Results, Figure 4C: please report the mathematical expression used to calculate the relative fluorescence.
- Supplementary Material, Fig. S7: please provide more details on the antibody employed.
Suggestions for future studies
Future studies could investigate the biological functionality of the novel methylation sites - but this is a great proof of principle.
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twitter.com twitter.com
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ReconfigBehSci. (2021, November 26). RT @mvankerkhove: Following the meeting of the @WHO TAG-VE today, WHO classifies B.1.1.529 as a variant of concern named Omicron. We call… [Tweet]. @SciBeh. https://twitter.com/SciBeh/status/1464302372100976650
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twitter.com twitter.com
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ReconfigBehSci [@SciBeh]. (2021, November 26). RT @mvankerkhove: I thank researchers from 🇿🇦 and 🇧🇼 for sharing information with @WHO & the world about B.1.1.529 variant that has been re… [Tweet]. Twitter. https://twitter.com/SciBeh/status/1464196599773642779
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www.biorxiv.org www.biorxiv.org
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Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.
Learn more at Review Commons
Referee #1
Evidence, reproducibility and clarity
This study characterises a Plasmodium class I Histone deacetylase (PfHDAC1). The manuscript reports a wide range of experiments - some of them complex and involved, but not all of these experiments appear to be well controlled, and some are insufficiently described to know if they have been appropriately designed and interpreted. A link to HDAC1 regulation and artemisinin resistance is advanced, but the evidence here is very indirect and inconclusive.
The study shows that HDAC1 interacts with PfCKII- a homologue of the mammalian casein kinase known to interact with mammalian HDAC1. They also demonstrate that, at least in vitro, HDAC1 can serve as a substrate for phosphorylation by PfCKII, and that this phosphorylation impacts HDAC1's deacetylation of histones. Such assays where a kinase is provided with a single, abundant substrate in vitro, are not always rigourous tests for kinase specificity, but do in this case at least indicate that HDAC1 associated with its activity.
Major issues:
- The authors conduct CHiP seq experiments on a GFP tagged HDAC. It is unclear from the methods and results section what control is used in these experiments. The ENCODE consortium has established minimum standards (Landt et al 2012) for conducting and reporting CHiP seq experiments, and states that the "recommended control for epitope-tagged measurements is an immunoprecipitation using the same antibody against the epitope tag in otherwise identical cells that do not express the tagged factor.". These experiments appear to lack that control and the enrichments reported should be approached with caution in the absence of such a control.
- The genes with apparently altered ChiP seq were subjected to gene ontology enrichment analysis, and the authors report potential enrichments - which appear to impact a range of unconnected biological pathways throughout the parasite and throughout the lifecycle, despite the CHIP seq being conducted only at a single time stage. No mention is made of correction for multiple hypothesis testing, known to present a considerable problem for such analyses, and no correction is described for background GO distributions in the P. falciparum genome, so again it's unknown if or how that was performed. The reported enriched categories must be also treated with considerable caution given the absence of description of these crucial steps. The authors report from this section that HDAC1 is associated with stress responses, but really, by their criteria, HDAC1 is associated with 1/3 of the whole genome, so it's a bit selective to regard it as a stress regulator
- The authors preform a well-designed series of transfection experiments with modulation of HDAC1 to show that an overexpression of HDAC1 leads to increased growth rate, and that this increase reduces when the overexpression of HDAC1 is inducibly repressed. However, I found the presentation of results from these experiments difficult to understand and there is considerable transformation of the data prior to plotting - they would be easier to understand if no background subtraction to normalise for GFP were conducted, and if all strains were plotted on the same axes. A potential confounding factor in this experiment is that many lines overexpressing GFP grow more slowly, and that this growth defect can be localisation dependent, so that over-expression of GFP alone may cause a different growth penalty than GFP on a nuclear protein. I am uncertain that the conclusion of 50% faster growth is a safe one based on these graphs - at some time intervals the over-expressor appears to grow just as slow or even slower (as a percentage of the previous timepoint) than the control, and these appear to have been based on technical replicates of a single biological experiment. The authors contend that the growth rate is due to changed expression of invasion genes (among many other substrate gene categories) giving rise to enhanced invasion - such a phenomenon is readily testable, and the authors should dissect this if they wish to substantiate the frankly surprising claim that overexpression of HDAC leads to increased growth rate.
- The authors also report an apparent down regulation of HDAC abundance in artemisinin resistant parasites. This conflicts with previous global proteomic analyses of artemisinin resistant parasites which found no such change in HDAC1 regulation or abundance (eg Siddiqui et al 2017, Yang et al 2019). Stage matching is a particular challenge in such experiments given the differences in cycle progression between ARTR and ARTS parasites, and it isn't clear that this has been adequately controlled for to have confidence in these results, particularly given their contradiction of previous analyses. The abundance of PfHDAC1 changes considerably throughout the asexual intraerythrocytic cycle, (out of synch with the control used here actin), so potential stage-mismatch might contribute to apparent differences here. Again, explicit mention of replicates is lacking. The authors also mention genes regulated by HDAC1 as including genes related to processes related to artemisin resistance, but this is hard to sustain - indeed with so many genes apparently substrates of HDAC1 it would be highly surprising if there were no overlap with some genes in pathways related to artemisin resistance. An accompanying experiment demonstrating an increase in survival (of both ART resistant and ART sensitive lines) in an artemisinin ring stage survival assay is intriguing, after using a possible inhibitor of HDAC but these results are hard to reconcile with a dynamic transcriptional response. (Why was this done with an uncharacterised inhibitor, rather than the more specific HDAC1 overexpressor/knockdown system? An accompanying RNAseq analysis is described, but the analysis is piecemeal and selective, with the authors pointing out candidate genes representing categories plausibly linked to artemisinin resistance. I found this section unconvincing and indirect - lots of genes are changed in these experiments, and so they inevitably include some that are feasibly linked to artemisinin resistance, but the one gene convincingly known to modulate resistance, K13, isn't mentioned, and presumably wasn't specifically changed in this analysis.
- A previous study by the laboratory of Christian Doerig (Eukaryot Cell. 2010 Jun; 9(6): 952-959.) reported that HDAC1 activity (unclear which of the HDACs) is associated with Pfcrk-3). This activity may not correspond to the HDAC1 characterised here, but deserves some discussion.
- The Western blots are letterboxed and in some cases appear to crop out bands on the limit of the image (eg Fig 5, 6). Please provide fuller pictures of the blots and indicate the relevant bands if there are several background bands.
Minor issues
The text uses breaking spaces for the gap between genus abbreviation and species throughout. Replace with non-breaking spaces. Abstract: "is correlated with parasitemia progression" - Unclear meaning. Reword. Introduction "closes in on 400,000 deaths annually" Unclear meaning/vernacular usage. Reword. Very long paragraph on pages 3-4. Reorder logical flow and break into smaller paragraphs to make this more easily read. "Given the evidence of the role of HDAC inhibition in the emergence of chemotherapeutic resistance in mammalian system" - needs a reference - no mention of this phenomenon up until this point of the manuscript
Referees cross-commenting
I agree with the other reviewers comments. Although the manuscript contains a very large number of complex experiments, necessary controls, sufficient replicates, and appropriate analysis are missing from many of the experiments.
I appreciate that the experiments referred to would require a very substantial time and resource commitment to complete, but in their current form, many of these experiments are not safely interpretable.
Significance
This manuscript makes major claims for HDAC1, in particular for its role in artemisinin resistance. Such a link would be significant, but I regard few of these claims as having been robustly substantiated in this manuscript. The CHIP-seq evidence is of interest as a useful dataset, particularly if accompanied by relevant controls
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www.schneems.com www.schneems.com
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It can be exhausting to backchannel and “find buy-in” for every little thing.
annotation meta: may need new tag: the need to “find buy-in” for every little thing.
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git-scm.com git-scm.com
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Tagging Later You can also tag commits after you’ve moved past them
tag a specific moment in past commits
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level 2hog8541ssOp · 15 hr. agoVery nice! I am a pastor so I am researching Antinet being used along with Bible studies.
If you've not come across the examples, one of the precursors of the slip box tradition was the widespread use of florilegia from the 8th through the 13th centuries and beyond, and they were primarily used for religious study, preaching, and sermon writing.
- https://en.wikipedia.org/wiki/Florilegium
- https://en.wikipedia.org/wiki/Commonplace_book
- https://hypothes.is/users/chrisaldrich?q=tag%3Aflorilegium
A major example of early use was by Philip Melanchthon, who wrote a very popular handbook on how to keep a commonplace. He's one of the reasons why many Lutheran books are called or have Commonplace in the title.
A fantastic example is that of American preacher Jonathan Edwards which he called by an alternate name of Miscellanies which is now digitized and online, much the way Luhmann's is: http://edwards.yale.edu/research/misc-index Apparently he used to pin slips with notes on his coat jacket!
If I recall, u/TomKluender may have some practical experience in the overlap of theology and zettelkasten.
(Moved this comment to https://www.reddit.com/r/antinet/comments/wth5t8/bible_study_and_zettelkasten/ as a better location for the conversation)
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📒 ShrewdNotes Web Page Annotation
I often rush into assessing new applications. Because I learn quicker by applying compared to reading. But one downside is that I frequently miss key features.
That's only a major drawback if I abandon the application where I can't see how it fits my project. And today I avoided that with serendipity. Because… 1. My application was a Chrome Extension 1. I wanted to test to see if was active and change webpage content accordingly 1. I found I could run the app without an extension - as fully described in the documentation that I skipped reading!
All of which is an idea for my next blog post. But the real point is I have established a process for starting ad-hoc Shrewd Learning projects "in the wild". Because normally, I start making notes somewhere. Then forgetting where I put them.
I think we all do that when we spot something interesting that might warrant future research. Now for my established subject areas, I always start annotating new topics within that subject area. So, I can prioritize it in my usual processes.
Today, I've extended this by tagging public notes with
Shrewd Learning
. So when I look at the Shrewd Learning Tag, I see all notes that present potential new learning topics. Which opens a great way to collaborate loosely with other people if I can establish some traction with Shrewd Learning.For now, this is my reminder to do a personal blog entry based on this. More importantly, I should update this blog entry to reflect recent advances in Shrewd Learning and my other 2 online learning projects.
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www.biorxiv.org www.biorxiv.org
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Author Response
Reviewer #1 (Public Review):
Rasicci et al. have developed a FRET biosensor that is designed to light up when cardiac myosin folds. This structure is extremely important to understand, and its link to the super-relaxed (SRX) state has not been fully shown. Their study provides a comprehensive review of the literature and provides compelling data that the 15 heptad+leucine zipper+GFP construct does function well and that the DCM mutant E525K has a similar IVM velocity despite a reduced ATPase compared with HMM. They rely on the ionic strength-dependent changes in the rate of MantATP release to argue that the E525K mutation stabilizes the 'interacting heads motif' (IHM) state, which makes logical sense.
Strengths:
Well written and comprehensive.
Utilizes the appropriate fluorescence-based sensor for measuring the folding of the myosin structure. Provides a detailed range of techniques to support the premise of the study
Weaknesses:
Over-interpretation of the outcomes from this study means that the IHM and SRX are the same. Similar studies, e.g. Anderson 2018 and Chu 2021 support the opposite view that IHM and SRX are not necessarily the same, Anderson (and Rohde 2018) point out that S1 has some element of a reduced ATPase, this clearly cannot be due to folding of the molecule. Also, mavacamten was used in these studies to show that even S1 is inhibited suggesting that SRX and IHM are not connected. This is not to say that with enough supporting evidence that these observations cannot be over-ridden, it is just not clear that there is enough in this study to support this conclusion.
We have revised our discussion to emphasize that our results support a model in which the SRX state is enhanced by formation of the IHM, but given the S1 and 2HP data the IHM may not be required for populating the SRX biochemical state (see page 8).
I felt that the authors passed over the recent Chu 2021 paper too quickly, the Thomas group used a FRET sensor as well and provides a direct comparison as a technique, but with opposite conclusions. They also have supporting data in Rohde 2018 that their constructs were less ionic strength sensitive. It would be useful to understand what the authors think about this.
We have discussed the Rohde and Chu papers in more detail in the discussion (see page 8). In the Rhode paper they used proteolytically prepared HMM and S1. Rohde found 20% SRX at all KCl concentrations in S1, while HMM shifted from 50% to 20% SRX in low and high salt conditions, respectively. Our results are different in terms of the absolute fraction of the SRX state but the trend is similar in terms of S1 being salt-insensitive and HMM being salt-sensitive. The difference could be proteolytic HMM, which is a longer construct, and proteolytic S1, which is prone to internal cleavage that can impact ATPase activity. Another difference could be the mixed isoform of mantATP used in previous studies and the single isoform of mantATP used on our study (see page 5)
Reviewer #2 (Public Review):
The paper by Rasicci et al. examines the impact of the DCM mutation E525K in beta-cardiac myosin on its function and regulation by autoinhibition. The role of the auto-inhibited state of beta-cardiac myosin in fine-tuning cardiac contractility is an active and exciting area of current research related to muscle biology and cardiomyopathies. Several studies in the past have linked the destabilization of the autoinhibited, super-relaxed (SRX) state of myosin to the pathogenesis of hypertrophic cardiomyopathy. This timely study provides one of the first few examples where the hypocontractile phenotype of a DCM mutation has been linked to the stabilization of the SRX state.
One of the strengths here is the utilization of a wide variety of both pre-existing and novel biochemical and biophysical assays for the study. The authors have characterized a new two-headed long-tailed myosin construct containing 15-heptad repeats of the proximal S2 (15HPZ), which they show allows myosin to form the SRX state in vitro using single ATP turnover assays. The authors go on to compare the E525K and WT proteins using the 15HPZ myosin construct in terms of their steady-state actin-activated ATPase activity, in-vitro actin-sliding velocity and single ATP turnover measurements. These assays reveal that the predominant effect of this mutation is the stabilization of the SRX state which is maintained even at 150 mM salt concentration where the WT SRX is largely disrupted. This is an important observation because DCM mutations so far have been believed to only affect the force-generating capacity of myosin.
One of the biggest strengths of this study is the attempt to develop a FRET-based approach to directly ask if the biochemical SRX state here correlates well with the structural IHM state, which is an important unresolved question in the field. The authors have designed a FRET pair (C-terminal GFP and Cy3ATP bound to the active site) that is sensitive to the relative position of the heads and the tail, allowing them to distinguish between the low-FRET closed IHM conformation and the no-FRET open conformation. Remarkably, the authors show that the salt dependence of the FRET efficiency values closely follows their results from the salt dependence of the percent SRX for both WT and E525K proteins. The authors then attempt to substantiate their FRET results by a direct visual analysis of the conformational states populated by both WT and E525K proteins at low salt using negative staining EM analysis. The authors have optimized conditions to allow the deposition of the IHM state on grids without adding the small molecule mavacamten, which was found to be necessary in an earlier study to visualize the closed state using EM. The authors conclude that the SRX state correlates well with the IHM state and that the E525K mutation indeed stabilizes the folded-back conformation of myosin.
This study significantly strengthens the previously illustrated correlation between the SRX and IHM states and provides methodological advances (especially visualization of the IHM state by negative EM in the absence of cross-linking agents) that will be very useful to the field going forward. The observation that a DCM mutation can lead to stabilization of the folded back state is a novel insight that should spark interest in the field to test how broadly this applies to other DCM mutations. The conclusions of the paper are mostly supported by the data; however, some clarifications and qualifications are needed.
Weaknesses:
The extremely low enzymatic activity of the M2β 15HPZ myosins as compared to the WT S1 control (which is a historical control not assayed in parallel with the 15HPZ proteins), is concerning for the low protein quality of the 15HPZ myosins. The authors attribute the low kcat to the high proportion of SRX population in their ensembles. However, the DRX rates reported for the WT and E525K 15HPZ proteins in the single ATP turnover assay are ~3-4 fold lower than those of their S1 counterparts. These rates reflect basal turnover of ATP in the open state and thus should not be affected by the presence of the S2 tail, which leads to concerns about the 15HPZ protein activity. In addition, the very high percentage of stuck filaments in the in vitro motility assay for the 15HPZ constructs (despite the use of dark actin) is also concerning for significant amounts of enzymatically inactive protein.
We thank the reviewer for pointing out the differences in the S1 and HMM DRX rates. We performed additional single turnover measurements with S1, adding two sets of measurements from one additional preparation (N=3), and we demonstrate that there is a significant increase in the DRX rates of WT S1 compared to WT HMM (see pages 4-5, Table 3, Figure 3- figure supplement 3). A faster rate in S1 was also reported in Rohde et al. 2018. Indeed, the DRX rates of E525K S1 are significantly higher than WT in S1, which we also now report in the results (see page 5, Figure 3 – figure supplement 3). We addressed the concerns about 15HPZ activity by performing NH4+ ATPase assays to demonstrate that the number of active heads was similar in S1 and 15HPZ HMM (see page 4). It is possible that the higher percentage of stuck filaments in the HMM motility is due to myosin heads in the IHM state on the motility surface, which generate a drag force by non-specifically interacting with actin, but further study is necessary to examine this question.
The authors assert that the E525K mutation represents a new mechanism by which DCM-causing mutations lead to decreased contractility - by stabilizing the sequestered state rather than affecting motor function. However, there is no evaluation of the motor function (actin-activated ATPase activity or in vitro motility) of the E525K S1, which would reveal the effects of the mutation without confounding effects due to the sequestering of heads. Interestingly, in the single ATP turnover assay, the DRX rate of the E525K S1 is >2-fold higher than the WT control, suggesting that the mutation may have effects beyond stabilization of the SRX state. The conclusion that the E525K mutation's effect on myosin function is mediated via stabilization of the SRX state would be strengthened if the effects of the mutation on the motor domain alone were also known.
We thank the reviewer for this suggestion. We performed actin-activated ATPase assays with WT and E525K S1 and found that E525K increases kcat and lowers KATPase, demonstrating enhanced intrinsic motor activity in the mutant S1 construct (see page 4, Figure 2B). This adds an interesting dimension to the manuscript because we report a mutant that enhances the intrinsic motor activity but stabilizes the SRX/IHM (see Discussion page 10). We did not perform in vitro motility, because this assay depends on the surface attachment strategy, and we would like to compare all constructs with the same attachment strategy using a C-terminal GFP tag (mutant and WT S1 and 15HPZ HMM). Therefore, we are making the S1 construct with a C-terminal GFP tag for this purpose, to be examined in a future study.
While the authors show strong qualitative correlations between the SRX and IHM states using single ATP turnover, FRET, and EM experiments, attempts to quantitatively compare the fraction of heads in the IHM state using the various experimental approaches is problematic. For example, the R0 value of the FRET pair used here doesn't allow precise measurement of the distances being probed here to be made, but the distances are reported and compared to predicted distances. The authors report that the R0 for their FRET pair is 63 Å. Surprisingly the authors go on to use the steady-state FRET efficiency values to determine the average D-A distance (Fig 5B) which is 100 Å when all heads are in the IHM configuration and becomes larger than that when heads open. R0 of 63 Å allows a precise distance measurement to be made in the 31.5-94.5 Å range which corresponds to 0.5-1.5 R0. It is therefore technically incorrect to use the steady-state FRET efficiency values to determine the D-A distance here. Besides, there are several unknown factors here like orientation factor (κ2) which further complicate these calculations. Similarly, the quantification of IHM state molecules from the negative stain EM experiments is significantly hampered by the disruptive effect of the grid surface on the structure of the IHM state. The authors find that limiting the contact time with the grid to ~ 5s is necessary to preserve the IHM state.
Despite that, only ~15% WT molecules were seen in the IHM state at low salt (Fig. 6B). In contrast, ~56% E525K molecules were in the IHM state. Both these proteins have similar SRX proportions (Fig. 3C) and similar FRET efficiency values (Fig. 5A) at this salt concentration. This mismatch highlights the problem arising due to not having a measure of the populations from the FRET data. It is not clear if the hugely different proportions of the IHM state in EM experiments are indicative of the relative stability of this state in the two proteins or a random difference in the electrostatic interactions of WT vs mutant with the grid. These experiments do not provide a correct idea of the %IHM in the two proteins. In the absence of any IHM population measurement, it is important to proceed with caution when quantitatively correlating the SRX and IHM.
We thank the reviewer for pointing out that measuring precise distances by FRET can be difficult. We agree that the low FRET efficiency makes precise distance determination even more challenging. However, FRET is quite good at measuring a change in distance given a specific donor-acceptor pair. We feel our FRET biosensor clearly demonstrates FRET efficiencies that are salt-insensitive in E525K but a clear decrease in FRET at higher salt concentrations in WT. In order to compare the trend in the predicted FRET, based on the single turnover measurements, and the actual FRET we thought it was important to plot the two together on the same graph. We understand that this could have been misleading that we were reporting actual distances. We have now plotted the FRET efficiency instead of distance as a function of KCl concentration (Figure 5B), to prevent any confusion with reporting distances. In addition, we have emphasized that the data are plotted to allow for a comparison of the trend in the single turnover and FRET data (see page 6, 10, Figure 5B).
We agree that it is important to proceed with caution when comparing the EM to the FRET and single turnover data. The EM does not give a quantitative estimate of the fraction of IHM molecules, due to the disruptive effect of the grid surface on protein conformation. However, it does provide direct (though qualitative) evidence that the conformation underlying SRX and enhanced FRET is the IHM, and it is consistent with our interpretation that the E525K mutation enhances FRET and SRX by stabilizing the IHM. To consolidate this result, we have performed EM experiments now with a total of 3 preparations of WT and mutant (see page 6-7 and Figure 6D). We find that while there is variability from experiment to experiment, likely because the grid surface is slightly different each time the experiment is performed, in all cases there was a ~4-fold higher fraction of folded molecules in the mutant. Since each WT/mutant experimental pair was studied in parallel, using identically prepared grids, the results provide further evidence that the mutant stabilizes the IHM. However, we agree that a quantitative, direct visual correlation of the SRX and IHM is not possible based on the current EM data.
Finally, the utility of the methods described in the paper to the field would be greatly enhanced if they were described in more detail. As currently written, it would be difficult for others to replicate these experiments.
Thank you for the comment. We have made significant changes in the methods to clarify the details of the experiments (see pages 11-14). In addition, we have added details to the results and figure legends.
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I would like something to log and tag my spending instantly.
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Don't disregard it because it's cute.
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Referee #1
Evidence, reproducibility and clarity
Summary:
The authors used CRISPR engineering to drop a V5 or GFP tag into teh PGRP-LE locus (protein fusions) to monitor the behavior of this intracellular peptidoglycan sensing receptor in the drosophila midgut. They show that upon immune stimulation with Ecc that PGRP-LE forms some sort of aggregate or punctae that is dynamic during the 24 hour of infection monitored. A similar response is not seen with live E. coli but a week and smaller response is observed with heat killed E. coli, for unclear reasons. These punctae appear to form independent of the classic IMD signaling components, suggesting it is upstream event in the pathway which is consistent with early studies showing the PGRP-LE multimerizes (infinitely) upon binding PGN and also that it forms amyloid fibrils doing signaling. The Ecc punctae tightly colocalize with Rab5 but not Rab7 or other early endosome markers, but in the absence of Rab5 the PGRP-LE punctae are greatly enlarged. Rab5 was found to critical for induction of PGRP-SC1 but not the classic IMD pathway AMP, Attain.
While the conclusions of the report are intriguing and the development of these tools is very exciting, the conclusions are not fully convincing. To start, the author wish to conclude that PGRP-LE localization is altered with Ecc infection but they have not excluded that the expression of the protein is sharply upregulated. I.e. in the uninfected animals there is not really any PGRP-LE observed (1D). The try to tackle this by looking at mRNA expression, but this data lacks the unaffected control. [In fact, the uninfected control is missing on most of the gene expression data, which is a troubling omission and makes it hard to really understand what the data shows.]. Moreover, the mRNA levels do not necessarily corresponding to the protein levels, i.e. there could be post translation control. So, overall, the authors need to provide more compelling evidence that PGRP-LE is relocalized upon Ecc challenge rather than upregulated.
Moreover, the paper contains some seeming contradictory findings that the authors make little effort explain. For example, they conclude "These results suggest that although smaller PGRP-LE aggregates can form normally in the absence of Rab5, the latter is required for proper bigger E.cc mediated PGRP-LE aggregates" because E. coli induced PGRP-LE clusters don't colocalize with Rab5, yet in the absence of Rab5, the Ecc cluster are super-enlarged (4F). This makes no sense with the conclusions.
Finally, the interaction and function of the Rab5 interaction is underdeveloped and lacks insight. For example, why is Rab5 required for the induction of one target gene but not another? And, why not characterize this more completely? Why is there not Rab5 vesicle with E. coli feeding or even uninfected? The cell biology requires more in-depth consideration. From 4E, the authors wish to conclude that the Rab5 vesicle are induced by Ecc (even in the absence of PGRP-LE) yet the uninfected control is not shown. IN a simple world, would not one would expect Rab5 endosomes in all cells, at least to some level?
And, focusing on the big picture, the authors claim that it is "not easily testible" if the PGRP-LE aggregates are amyloidal, as suggested by earlier publications. This could actually be tested by staining with amyloid specific dies and/or suitable mutants engineered int he RHIM domain. This would be very informative if the authors could extend this work to examine this question.
Minor comments:
All the colocalization data should be quantified as in 4B. It is not true that DAP = Gram negative. Gram-positive bacilli also have DAP PGN. The wording in the Introduction should be adjusted. The text needs a careful proofreading.
Referees cross-commenting
I think the comments from #2 and myself are aligned. Working is interesting, tools are especially exciting, but the studies are descriptive and under-developed. I will further add, I found the absence of uninfected controls for many assays a major problem.
Significance
The significance of this work lies in the development of powerful tools to track an intracellular innate immune receptor in an intact animals. The connection to Rab5 is curious and likely an important advance in our understanding of the cell biology of this pathway, but is under-developed. The significance is this difficult to know for certain. The Drosophila immunity field, and the insect immunity field more broadly, will be keenly interested in this study. The wider NF-κB/innate immune field will also be interested in these findings, given teh similarity between this pathway and NOD1/NOD2 immune sensing in mammals.
My area of expertise is the Drosophila immune response and this manuscript is very much in my wheelhouse.
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Reply to the reviewers
August 17, 2022
RE: Review Commons Refereed Preprint #RC-2022-01442
Dear Editor of the EMBO Journal,
Please find our updated manuscript and response to the reviewers’ comments. We appreciate the effort that the reviewers have put into the evaluation of our manuscript.
We are happy with the potential importance the reviewers realise in the study:
Reviewer 1: The finding that ubiquitination occurs inside mitochondria would be an important conceptual advance, which would open new perspectives both for ubiquitination and mitochondrial biology
Reviewer 2: This work would represent a significant/exceptional discovery if supported by compelling data.
Reviewer 3: the results are interesting and very important, as mentioned in the major comments section…
With regard to the major comments raised by the reviewers, you will find below our specific response point by point with explanations and suggested novel experiments (highlighted in yellow). In summary we suggest the following actions to fully support our model:
- We will perform a-complementation with ubiquitin (lacking the GG motif) fused at its C-terminus to the short fragment of b-galactosidase (a). Blue colonies with ωm will indicate import.
- As shown in Figure S2, now added to the manuscript, we show detection of ubiquitinated proteins and mono ubiquitin in extracts of mitochondria pre-treated with trypsin.
- A bio-archives address of our other manuscript will be provided.
- The use of a-complementation for protein localization was developed by us 15 years ago and since then has been used by us and other groups verifying its use as a screening tool. One point is clear, ωm or ωc do not leak into other subcellular compartments. Nevertheless, in the research of specific genes validation is important. Yes!!! ωm and ωc are exclusively located in mitochondria or the cytosol respectively.
- We will highly purify mitochondria on gradients and treat them with protease.
- We cannot be sure that we will be able to detect a protein with ubiquitin modifying activity which functions solely on certain proteins in mitochondria, so publication cannot rely on this.
- Repeat mass spectrometry with careful editing will be undertaken as suggested by the reviewer.
- We will attempt to perform protease protection assays in the presence of specific detergents.
Before tackling the very tough revision, we would like to know if EMBO Journal would positively consider acceptance of our manuscript based on the review and planned revision.
Prof. Ophry Pines Microbiology & Molecular Genetics Hebrew University of Jerusalem Jerusalem 91220 Israel
Reviewer #1 (Evidence, reproducibility and clarity (Required)):
Summary:
In this manuscript, Zhang et al. investigate whether ubiquitination occurs inside mitochondria of the budding yeast S. cerevisiae. They first observe thanks to a sensitive complementation assay that several components of the yeast ubiquitination (and deubiquitination) machinery can localize inside mitochondria. To be able to specifically probe ubiquitin conjugates assembled inside mitochondria they fused HA-tagged ubiquitin to a mitochondrial targeting sequence. Using this construct, they demonstrate that ubiquitin conjugates can be assembled in mitochondria. A series of elegant experiments demonstrates that the pattern of ubiquitin conjugates depends on the mitochondrial localization and the activity of the ubiquitin conjugating enzyme Rad6. Altogether, these results convincingly demonstrate that ubiquitination can occur inside yeast mitochondria when ubiquitin is intentionally targeted inside this organelle. It however remains unclear whether mitochondrial ubiquitination occurs in endogenous conditions (without targeting ubiquitin into this compartment) and whether it affects mitochondrial functions.
Response: Regarding the question whether mitochondrial ubiquitination occurs in endogenous conditions, we feel that this is obvious based on our results. We detect numerous ubiquitination related enzymes (E1, E2, E3, DUB) eclipsed in mitochondria but none of the proteasome subunits. As pointed out by the reviewer “these results convincingly demonstrate that ubiquitination can occur inside yeast mitochondria”. With that said, additional data will be incorporated into the manuscript as suggested by the reviewer and can be seen below.
Major comments:
1) The materials and methods section is lacking important information (western blot protocol, details of antibodies, strains, plasmids...). It is thus difficult to evaluate how several experiments were performed and how their design (e.g. the promoters chosen to express tagged proteins) could impact the interpretation of the results. This is a major issue that needs to be corrected. The main text should also explicitly indicate whether tagged proteins used in the alpha-complementation assay are overexpressed or not.
Response: The materials and methods section will be updated accordingly.
2) Despite the previous comment, the data presented in the manuscript convincingly demonstrate that multiple components of the ubiquitination machinery can localize within mitochondria and that ubiquitin conjugates can be assembled in mitochondria when ubiquitin is modified to be intentionally targeted into this compartment. However, little data is shown to support the hypothesis that ubiquitin conjugates can be assembled in mitochondria when ubiquitin is not fused to a mitochondrial targeting sequence. Thus, in my opinion, the evidences presented in the current manuscript are not sufficient to conclude that ubiquitin conjugates are assembled in mitochondria in endogenous conditions (as this is done implicitly). Additional evidences are needed to draw this conclusion (see some experimental suggestions hereafter). Without further evidences, the speculative aspects of the claim that "ubiquitination occurs in the mitochondrial matrix" should be discussed explicitly.
Response: See the discussion above why we are confident that ubiquitination occurs in mitochondria. Our major problem with ubiquitin and the ubiquitination enzymes is that they are eclipsed in mitochondria. We propose as suggested by the reviewer (item 4 of his review) to perform a-complementation with ubiquitin fused at its C-terminus to the short fragment of b-galactosidase (a). Blue colonies with ωm will indicate import.
3) The authors used a mass spectrometry approach to identify mitochondrial ubiquitination substrates. However, they have not yet succeeded in identifying a substrate whose modification is specifically regulated by a given component of the mitochondrial ubiquitination machinery. They have also not identified a phenotype or process impacted by mitochondrial ubiquitination. Thus, at this stage, the biological consequences of mitochondrial ubiquitination remain elusive.
__Response: __We have not identified a substrate whose modification is dependent on a given component of the mitochondrial ubiquitination machinery, even though we have tried. Again, the problem is low levels of these proteins eclipsed in mitochondria. Even when we do find a protein that is ubiquitinated (e.g. Aco1) its ubiquitination is not exclusively dependent on Rad6. Thus, different ubiquitin enzymes may have the same substrates.
4) The authors have not directly investigated whether ubiquitin itself (without a mitochondrial targeting sequence) localizes in mitochondria. I encourage them to address this question since it would provide an important piece of evidence suggesting that mitochondrial ubiquitination can occur in endogenous conditions. This could be done using the alpha-complementation assay and the results could be presented within Figure 1. Ideally this experiment should be performed without overexpressing ubiquitin. Note that if the authors decide to use a C-terminally tagged form of ubiquitin for this experiment, the GG motif of ubiquitin should be mutated to avoid cleavage of the alpha tag by cellular DUBs. This form of ubiquitin will not be conjugatable, but this is not an issue for this experiment since its aim is to determine whether ubiquitin can be targeted to mitochondria, not to probe conjugates.
Response: We will perform experiments as suggested by the reviewer including ubiquitin fused at its C-terminus to the short fragment of b-galactosidase (a), see item 2. We have previously made a PreSu9-Ubi lacking a GG motif but now will look at a different combination of this and other constructs.
5) In the top panels of Figure 2 and S1, free ubiquitin is well detectable in the total and cytosolic fractions. It is however not clear to me whether it is also detectable in the concentrated mitochondrial fraction. If yes and if it would be resistant to trypsin digestion, it would provide additional evidence that endogenous ubiquitin can be targeted to the mitochondrial matrix (see previous comment).
Response: See Item 6.
6) The data shown in the top panel of Figure 2 and S1 also suggest that free ubiquitin is less concentrated in mitochondria than in the cytosol (since it is more difficult to detect in the concentrated mitochondrial fraction than in the cytosolic fraction, see previous comment). It is thus possible that the use of preSu9-HA-Ubi (or preFum1-HA-Ubi) lead to an artificially high intra-mitochondrial concentration of free ubiquitin. As the concentration of free ubiquitin is known to impact ubiquitination processes, I encourage the authors to compare the relative levels of free ubiquitin present in the mitochondrial fraction prepared from WT and preSu9-HA-Ubi (or preFum1-HA-Ubi) expressing cells. If free ubiquitin is detectable in mitochondrial fractions and resistant to trypsin (see previous comment), this could be done by repeating the experiment shown in Figure 3B and probing the blot with an antibody that recognizes free ubiquitin.
Response to 5 and 6: Detection of ubiquitin in mitochondria is extremely difficult even when mitochondria are 15-fold concentrated versus the cytosol and when HA-Ubi is overexpressed. Thus, ubiquitin is eclipsed in mitochondria. Nevertheless, as shown in the Figure below which was not part of the submitted manuscript yet was performed in parallel to experiments done early on, shows detection of very weak bands of free ubiquitin in extracts of mitochondria pre-treated with trypsin.
Endogenous ubiquitination pattern in mitochondria of _Δrad6 _cells is restored to normal by Rad6-α. __WT or Δrad6 cells containing a Rad6-α construct or an empty plasmid were subjected to subcellular fractionation. Mitochondrial fractions with or without trypsin treatment, were probed for ubiquitin by WB. Aco1 is a matrix mitochondrial protein, and Tom70 is a mitochondrial outer membrane protein (MOM) facing the cytosol.
7) I strongly encourage the authors to provide more data indicating that "ubiquitination occurs in mitochondria" by performing experiments that do not rely on the use of the preSu9-HA-Ubi or other forms of ubiquitin that are intentionally targeted to mitochondria. For instance, they could analyse the pattern of HA-Ubi conjugates of trypsin digested mitochondrial fractions prepared from wt, rad6-delta, and rad6-delta complemented with preSu9-Rad6-alpha-SL17. Note that if trypsin digested mitochondrial fractions are too contaminated by ubiquitinated proteins present outside mitochondria to perform this experiment, the authors may use the unspecific DUB Usp2 as an alternative protease to strip ubiquitinated proteins from the mitochondria periphery.
Response: Concentrated mitochondrial extracts from WT and Δrad6 cells untreated or treated with trypsin were probed with anti-ubiquitin antibodies (Figure above). A very weak band corresponding to free ubiquitin can be detected in extracts of mitochondria treated with trypsin but these are very weak and are on the limit of detection.
Minor comments:
1) Overall, the manuscript is well organized and easy to follow. The text is clearly written; the figures are well annotated.
2) The authors should provide full images of all the blots with anti-ubiquitin and anti-HA antibodies so that one can see the bands corresponding to free ubiquitin (or free HA-Ubi). For instance, in Figure 3B, it is not possible to see the presence (or absence) of the band corresponding to free HA-Ubi because the very bottom of the image is cut.
3) The authors should indicate whether the MTS of Su9 (and Fum1) are expected to be cleaved after import of preSu9-HA-Ubi (and preFum1-HA-Ubi) in mitochondria. They should also label on the corresponding immunoblots the presence (or absence) of the band corresponding to the free preSu9-HA-Ubi (and preFum1-HA-Ubi) (or HA-Ubi if the MTS is expected to be cleaved from these constructs).
4) In Figure 3B, the ubiquitin conjugates produced with preSu9-HA-Ubi and preFum1-HA-Ubi have different migration patterns. I think this should be explicitly mentioned and discussed. Could it be due to the presence of lysine residues in the Su9 or Fum1 MTS that could lead to the assembly of artificial ubiquitin chains?
5) The authors indicate that "endogenous Rad6 [...] is expressed at very low levels and can hardly be detected in the mitochondrial fraction by WB (Figure S5)". I did not manage to observe the band corresponding to endogenous Rad6 in the mitochondrial fraction in the pdf. The authors should provide a more contrasted or better quality image.
CROSS-CONSULTATION COMMENTS I agree with reviewer 2 that proper validation of the complementation assay is crucial for this manuscript. I was myself wondering whether it uses endogenously tagged proteins or whether it is based on an overexpression system. I imagine this information will be detailed in the manuscript in preparation mentioned by the authors. I am therefore wondering whether it would be possible to ask the authors to provide the draft of this manuscript (or at least the validation part).
Response: A bio-archives address of our other manuscript will be provided upon resubmission. See other issues referred to the response Reviewer 2.
I agree with most comments of reviewer 3. Regarding the hypothesis that preSu9-HA-Ubi could form aggregates on the cytosolic surface of the mitochondria, I think that the results presented on Figure 7B rather argue against it (since they indicate that Rad6 localized inside mitochondria can restore the pattern of ubiquitin conjugates). That's why (in my opinion) the major question the author now need to adress is whether intra-mitochondrial ubiquitination occurs in endogenous conditions (ie without forcing ubiquitin into this compartment and without E2 or E3 overexpression).
Response: See response to the other reviewers
Reviewer #1 (Significance (Required)):
The finding that ubiquitination occurs inside mitochondria would be an important conceptual advance, which would open new perspectives both for ubiquitination and mitochondrial biology research. However, the significance of the current manuscript is limited because the presented evidences heavily rely on the use of artificial conditions (ubiquitin tagged with a mitochondrial-targeting sequence) that may trigger irrelevant ubiquitination events. The significance would be much higher if the authors would provide further evidences indicating that intra-mitochondrial ubiquitination occurs in endogenous conditions and/or if they had identified a mitochondrial process specifically impacted by mitochondrial ubiquitination.
Expertise of the reviewer: Ubiquitination, Yeast biology, protein-protein interactions. No specific expertise in mitochondrial biology
Reviewer #2 (Evidence, reproducibility and clarity (Required)):
In the manuscript by Yu et al., the authors test the concept that certain proteins are unevenly distributed within distinct cell compartments. Due to this localization discrepancy, protein detection in some subcellular compartments can be "eclipsed" by a predominant subset of specific protein localizing in another cell compartment their actual distribution. Therefore, tiny amounts of physiologically relevant proteins could be biologically relevant. Still, their function in some locations can be overlooked (or eclipsed) because of the high expression level of the same protein in another subcellular compartment(s). Although, this concept is not particularly novel. For example, it is already known that many different proteins can localize to distinct cellular locations (e.g., permanent mitochondrial and peroxisomal localization of many proteins or transient localization of particular proteins to separate cell compartments). The authors apply a yeast system and an α-complementation assay to test further the role of such eclipsed proteins in mitochondrial biology. Specifically, they focus on the ubiquitin (Ub, or as abbreviated incorrectly in this manuscript; Ubi) conjugation pathway, components of which have never been convincingly shown to localize inside the mitochondria. This work proposes that certain ubiquitination events can occur inside yeast mitochondria. This work would represent a significant/exceptional discovery if supported by compelling data. However, the major problem with this work is that the conclusions are based on the ectopic expression of distinct proteins. This approach is not failproof in precise protein expression/delivery to the specific subcellular locations and is likely to result in a non-specific localization. Thus, the problem of eclipsed proteins is addressed by the methodology that may lead to the artificial generation of eclipsed overexpressed proteins. A more effective approach would be if the authors found a way to study this issue with endogenous proteins. The need for overexpression of mitochondria-targeted ubiquitin makes it challenging to reconcile the physiological role of these fundings. In addition, some critical technical issues and omissions further reduce the potential impact of this work (see Specific comments below). For example, strong evidence of mitochondria fraction purity and additional evidence that all the essential constructs used in this work are not misdirected to a different compartment are needed.
Response: “Although, this concept is not particularly novel” is a very disappointing remark by the reviewer!! While dual targeting of proteins has been known for many, many years, how widespread the phenomenon was unknown and thought to be negligible. We are leaders for the last 30 years in the field of dual targeting and distribution and in particular distribution of single translation products. We coined the terms “echoforms” and “eclipsed distribution” and developed methods to detect and screen for dual targeting. The concept of eclipsed distribution and in particular eclipsed targeting to mitochondria is very new, and is leading to a novel perception of the mitochondrial proteome (see MS submission). While the reviewer appears to be an expert on ubiquitination, we are experts on dual targeting.
- Ub was abbreviated incorrectly in this manuscript, Ubi. __Response: __This will be corrected.
Other comments will be referred to in the response to Specific comments.
Specific comments 1. The authors should demonstrate beyond doubt that the ω components of their assay (ω-C, which supposedly stays in the cytosol-ONLY and the ω-M component, which seemingly remains in the mitochondria-ONLY) are in the compartment that the authors claim. These two proteins are transfected into yeast cells and overexpressed. Therefore it is possible that they leak to other, not intended, subcellular compartments. The authors assume that ω-M and ω-C are exclusively located either in the mitochondria or the cytosol. However, this should be shown as validation of the assay. The indicated reference from 2005 (Ref.13) and others are irrelevant since assays have variations and are often researcher/lab dependent. This validation is very important since a misallocation of the overexpressed ω-M or ω-C, leaking into other subcellular compartments, may cause misdetection of the α-constructs.
Response: The use of a-complementation for protein localization was developed by us 15 years ago and since then has been used by us and other groups verifying its use as a screening tool. One point is clear, ωm or ωc do not leak into other subcellular compartments. Nevertheless, in the research of specific genes validation is important. Yes!!! ωm and ωc are exclusively located in mitochondria or the cytosol respectively.
It is not surprising that Ub conjugates are detected in mitochondrial fractions. It could be due to ubiquitination of the OMM (coming from the cytosol) or perhaps since the subcellular fractions were not pure mitochondria free from contamination (the likely culprit could be the ER). The mitochondrial fractions in this work were obtained by 10,000 g separation between cytosolic and mitochondrial crude fractions. Indeed, these 10,000 g crude fractions are highly impure with membranes from other compartments (i.e., microsomes, lysosomes, and so on). Therefore, more sophisticated purification methods should be used. In addition, the authors should also test these fractions for non-mitochondrial proteins from other membrane organelles.
Response: We agree with the reviewer and therefore will take the following approaches:
- i) We will treat isolated mitochondria with protease in order to remove adhering proteins and digest OMM proteins…… see attached figure.
- ii) We will highly purify mitochondria on gradients and this will be straight forward since we are now employing such methods in other projects in the lab. iii) Matrix protein enrichment (by mass spec) is associated with IP for preSu9-HA-Ub conjugates which is three-fold higher than for HA-Ub. In any case the fact that we identify conjugates of proteins not known to be mitochondrial, strongly supports our thesis.
Figure 2. Coomassie blue staining does not show any signal in the "M" fraction. It can be interpreted that the authors do not get any mitochondria there, and therefore the lack of Ub signal is due to the absence of the protein in the samples. Using the same amount of protein from each fraction would probably reduce the necessity of 15x enrichment.
Response: The Coomassie blue staining does show a signal in the "M" fraction which is weak yet when a 15x enrichment is run, the protein level by Coomassie blue staining is similar to the cytosolic fraction.
Figure 3. It is puzzling why the HA-UBQ presence is so strong in the crude mitochondrial fraction, but the preSu9-HA-Ub signal (mito-matrix) is comparatively weak. These data suggest that the crude mito-fraction could be highly contaminated with OTHER membranes. On the other hand, the preSu9-HA-UBQ signal is no more than 1-5% of the total mitochondrial signal. The high enrichment of the HA-Ubi in both cytosols and the mitochondria could indicate the OMM ubiquitination or (again) contamination by other compartments. The constructs with MTS are detected in the mitochondria. However, the localization of tagged MTS-Ubi in a non-targeted compartment (e.g., cytosol) should be excluded by additional exposure times. Because the manuscript talks about eclipsed proteins, this is important.
Response: The HA-Ub is strong in the mitochondrial fraction, in the absence of trypsin, but is very weak in the presence of the protease indicating that most of the ubiquitinated proteins are externally attached to mitochondria. In contrast, PreSu9-HA-Ub is imported into the mitochondrial matrix and is protected from trypsin. This manuscript refers to “eclipsed in mitochondria” (not the cytosol) and this is true for ubiquitination enzymes as well as for ubiquitin.
Figure 3C-E. These data indeed suggest that the Ub-conjugates could be formed inside the mitochondria. However, the above-discussed possibility that other than mitochondria compartments co-sediment in the 10,000g fractions makes the data interpretation highly challenging.
__Response: __We will highly purify mitochondria on gradients and this will be straight forward since we are now employing such methods in other projects in the lab.
Figure 4. Unsurprisingly, mitochondrial targeting of Ub leads to detecting some co-immunoprecipitating mitochondrial proteins. However, these data do not support the notion that Ub conjugation machinery acts inside the mitochondria and that the target proteins are indeed conjugated with Ub (the interaction with Ub is not equal to being conjugated). At the minimum, the authors should provide a validation that some of the detected mitochondrial matrix proteins are indeed ubiquitinated. To this end, purified mitochondria could be used for the candidate protein IP under denaturing conditions and then blotted for the candidate protein and Ub.
__Response: __As shown in Table S2 and figure S7, forms of Ilv5, a mitochondrial protein, are ubiquitinated in WT and Drad6 cells. These modified forms of Ilv5 can be eluted from mitochondrial extracts of WT and Drad6 cells. However, the ubiquitination of ilv5 is not dependent or effected by the Drad6 mutation. We cannot be sure that we will be able to detect a protein with ubiquitin modifying activity which functions solely on certain proteins in mitochondria.
Figure 5. The knock-out of the E2 Rad6 causes a change in the mitochondria ubiquitination pattern. This is an interesting observation, but again it does not prove that the change in the mitochondrial ubiquitination is due to the activity of Rad6 inside of the mitochondria, as opposed to ubiquitination of the OMM proteins or contaminating fractions. One also wonders why overexpression of mitochondria-targeted Ub would be necessary to detect the ubiquitination if this process was physiologically relevant, especially given that detecting endogenous Ub is not challenging. Furthermore, the apparent increase in ubiquitination in E2 mutant cells (Fig. 5) should also be addressed in more detail. Finally, data from one WB is shown, and quantification of several independent experiments should also be provided.
__Response: __We show in the MS that RAD6 is exclusively targeted to mitochondria (Su9MTS) while unimported molecules are degraded (SL17; degron). This hybrid Rad6 can restore the WT ubiquitin pattern, while a rad6 active site mutant cannot.
Figure 6. Can the authors provide Western blot data showing the expression of Rad6? Furthermore, quantifying these rescue experiments is necessary to make this conclusion more solid.
Response: Even though we did not succeed in making good Rad6 antisera, we can clearly detect Rad6-a fusion proteins (Figure 7B).
Figure 7. The authors found that preSu9-Rad6-α have problems being imported into the mitochondria matrix; therefore, they rebuild it as a preSu9-Rad6-α-SL17 protein. SL17 is a degron that targets the cytosolic protein (not imported into the mitochondria) to the proteasome and degraded (Figs. 7A-B-C). These issues could be a red flag for the rest of the manuscript, suggesting that other constructs (that were not critically evaluated for their localization in this work) could leak to different cellular compartments.
Response: The wording used by the reviewer is particularly disturbing since current understanding in cell biology of eukaryotic cells does not accept “leaking” of proteins to different cellular compartments. One wouldn’t want DNAses, RNAses, Proteases etc leaking from one compartment to another. The localization of proteins to different cellular compartments involves very precise signals on the proteins, and specific cellular components, such as translocases, are required to target proteins to their exact destination. This is true for Rad6; it contains an MTS like sequence which when removed blocks import of the protein into mitochondria. Rad6 according to our analysis is an eclipsed dual targeted protein, so it no surprise that it is in two compartments and the trick with the SL17 degron solves the problem.
The manuscript needs to be carefully edited, some references are in the not correct format, and there are issues with figure labels.
Response: Careful editing will be undertaken as suggested by the reviewer.
CROSS-CONSULTATION COMMENTS I agree with a great summary by reviewer 1. This discovery should be validated by top-quality data.
Reviewer #2 (Significance (Required)):
In the manuscript by Yu et al., the authors test the concept that certain proteins are unevenly distributed within distinct cell compartments. Due to this localization discrepancy, protein detection in some subcellular compartments can be "eclipsed" by a predominant subset of specific protein localizing in another cell compartment their actual distribution. Therefore, tiny amounts of physiologically relevant proteins could be biologically relevant. Still, their function in some locations can be overlooked (or eclipsed) because of the high expression level of the same protein in another subcellular compartment(s). Although, this concept is not particularly novel. For example, it is already known that many different proteins can localize to distinct cellular locations (e.g., permanent mitochondrial and peroxisomal localization of many proteins or transient localization of particular proteins to separate cell compartments). The authors apply a yeast system and an α-complementation assay to test further the role of such eclipsed proteins in mitochondrial biology. Specifically, they focus on the ubiquitin (Ub, or as abbreviated incorrectly in this manuscript; Ubi) conjugation pathway, components of which have never been convincingly shown to localize inside the mitochondria. This work proposes that certain ubiquitination events can occur inside yeast mitochondria. This work would represent a significant/exceptional discovery if supported by compelling data. However, the major problem with this work is that the conclusions are based on the ectopic expression of distinct proteins. This approach is not failproof in precise protein expression/delivery to the specific subcellular locations and is likely to result in a non-specific localization. Thus, the problem of eclipsed proteins is addressed by the methodology that may lead to the artificial generation of eclipsed overexpressed proteins. A more effective approach would be if the authors found a way to study this issue with endogenous proteins. The need for overexpression of mitochondria-targeted ubiquitin makes it challenging to reconcile the physiological role of these fundings. In addition, some critical technical issues and omissions further reduce the potential impact of this work (see Specific comments above). For example, strong evidence of mitochondria fraction purity and additional evidence that all the essential constructs used in this work are not misdirected to a different compartment are needed.
Reviewer #3 (Evidence, reproducibility and clarity (Required)):
Summary: In this study, the authors detected a set of components of a ubiquitination system in the mitochondrial matrix in budding yeast using the subcellular compartment-dependent α-complementation assay. The authors detected the conjugates of mitochondrial targeting signal sequence-directed HA-Ub (preSu9-HA-Ub) in the mitochondrial matrix. The immunoprecipitates of the preSu9-HA-Ubi conjugates were highly enriched for the mitochondrial matrix proteins. Subsequently, the authors focused on the Rad6 E2 ubiquitin conjugating enzyme in the mitochondrial matrix and evaluated its inactivation-altered ubiquitination pattern in the organelle. The authors conclude that ubiquitination occurs in the mitochondrial matrix because of the eclipsed targeted components of the ubiquitination machinery.
Major comments: The authors argued that the proteins that were modified with preSu9-HA-Ubi, which was forced to be imported into the mitochondria, are present in the mitochondrial matrix, because these species are resistant to trypsin digestion. However, it was possible that they formed severe aggregates on the cytosolic surface of the mitochondria, and hence, were resistant to the proteinase. In other words, a small amount of proteins that were not imported into the mitochondria could be deposited on the cytosolic surface of the mitochondria, where they were modified with preSu9-HA-Ubi by cytosolic Rad6. To confirm if the preSu9-HA-Ubi-modified proteins were really present in the mitochondrial matrix, they should perform the protease protection assay in the presence of an appropriate detergent (Figure 3D). In addition, subcellular fractionation of the organelle by density gradient centrifugation, indirect immunofluorescence microscopic analysis of the preSu9-HA-Ubi conjugates, and/or experiments on the in vitro import of preSu9-HA-Ubi and Rad6 into the mitochondria would strongly support the authors conclusion. Other experiments that might support the authors conclusion would be to test whether the band pattern for the preSu9-HA-Ubi conjugates changes when the mitochondrial import is impaired.
Response: We will attempt to perform 1) Protease protection assay in the presence of a detergent (Figure 3D). 2) Subcellular fractionation of the organelle by density gradient centrifugation. 3) In vitro import of Rad6 into the mitochondria.
Minor comments: In Figure 3B, the molecular weight distributions of the preSu9-HA-Ubi conjugates and those of the preFum-HA-Ubi conjugates are different. Is there any reason for this difference?
In Figure 3E, the position of "-" (MG132) for lane 1 is not correct.
In Figure 6A: The band pattern for preSu9-HA-Ubi (lane 13) in the rad6-delta cells expressing Ubc8-alpha is different from that of the wild-type cells expressing Ubc8-alpha (lane 12) as well as that obtained from the rad6-delta cells harboring empty plasmids (lane 9). Is there any explanation for this observation?
In Figure 7B and S6: The level of preSu9-Rad6-alpha-SL17 in the rad6-delta cells is always lower than that in the wild-type cells (compare lanes 13 and 10 in Figure 7B, and lanes 13 and 12 in Figure S6). Is there any explanation for this observation? The protease protection assay (with detergent control) is needed to fully confirm that preSu9-Rad6-alpha-SL17 is present in the mitochondria.
In Figure S7, the authors presented the matrix proteins, Ilv5 and Aco1, detected in the preSu9-HA-Ubi IPed samples and described this observation in the main text. However, the authors also showed the blots for Idh1 and Fum1, which were also pulled down with preSu9-HA-Ubi from the WT cells more than from the rad6-delta cells. Is this correct? If so, please elucidate this observation in the main text.
Figure 8D and 8E are not cited in the main text. Although there are no explanations for these figures in the main text, it looks like Rad6-deltaN11-alpha resides in the mitochondrial fraction. However, the alpha-complementation assay suggests that it resides in the cytosol. Please explain this discrepancy.
First page of the discussion section, item 6): E2 Rad6, but not E3 Rad6?
Figure S7: HA-Ub (cytosolic form) control is needed in addition to the empty vector control.
Figure S7, left panel: There is an unnecessary line break in "Hsp60" and "Ilv5."
Figure S7, right panel: There is an unnecessary line break in "Hsp60."
CROSS-CONSULTATION COMMENTS I agree with comments of reviewer 1 and 2. -Validation of the complementation assay. -I also think that it is important to address whether intra-mitochondrial ubiquitination can be observed with endogenous level of ubiquitin. If even a small amount of preSu9-HA-Ub is mistargeted to the cytosol, proteins at the cytosolic side of mitochondrial outer membrane could be ubiquitinated and detected in the mitochondrial fraction. -Preparation of mitochondria with more sophisticated purification methods (i.e. high resolution density gradient) would be needed to separate mitochondria from ER and other organelles. -More information is needed in the materials and methods section.
Reviewer #3 (Significance (Required)): Significance Although the results are interesting and very important, as mentioned in the major comments section, additional experiments are needed to support their model. However, researchers working on the mitochondrial biology and ubiquitin systems might be interested in and influenced by the reported findings.
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Referee #1
Evidence, reproducibility and clarity
Summary:
In this manuscript, Zhang et al. investigate whether ubiquitination occurs inside mitochondria of the budding yeast S. cerevisiae. They first observe thanks to a sensitive complementation assay that several components of the yeast ubiquitination (and deubiquitination) machinery can localize inside mitochondria. To be able to specifically probe ubiquitin conjugates assembled inside mitochondria they fused HA-tagged ubiquitin to a mitochondrial targeting sequence. Using this construct, they demonstrate that ubiquitin conjugates can be assembled in mitochondria. A series of elegant experiments demonstrates that the pattern of ubiquitin conjugates depends on the mitochondrial localization and the activity of the ubiquitin conjugating enzyme Rad6. Altogether, these results convincingly demonstrate that ubiquitination can occur inside yeast mitochondria when ubiquitin is intentionally targeted inside this organelle. It however remains unclear whether mitochondrial ubiquitination occurs in endogenous conditions (without targeting ubiquitin into this compartment) and whether it affects mitochondrial functions.
Major comments:
1) The materials and methods section is lacking important information (western blot protocol, details of antibodies, strains, plasmids...). It is thus difficult to evaluate how several experiments were performed and how their design (e.g. the promoters chosen to express tagged proteins) could impact the interpretation of the results. This is a major issue that needs to be corrected. The main text should also explicitly indicate whether tagged proteins used in the alpha-complementation assay are overexpressed or not.
2) Despite the previous comment, the data presented in the manuscript convincingly demonstrate that multiple components of the ubiquitination machinery can localize within mitochondria and that ubiquitin conjugates can be assembled in mitochondria when ubiquitin is modified to be intentionally targeted into this compartment. However, little data is shown to support the hypothesis that ubiquitin conjugates can be assembled in mitochondria when ubiquitin is not fused to a mitochondrial targeting sequence. Thus, in my opinion, the evidences presented in the current manuscript are not sufficient to conclude that ubiquitin conjugates are assembled in mitochondria in endogenous conditions (as this is done implicitly). Additional evidences are needed to draw this conclusion (see some experimental suggestions hereafter). Without further evidences, the speculative aspects of the claim that "ubiquitination occurs in the mitochondrial matrix" should be discussed explicitly.
3) The authors used a mass spectrometry approach to identify mitochondrial ubiquitination substrates. However, they have not yet succeeded in identifying a substrate whose modification is specifically regulated by a given component of the mitochondrial ubiquitination machinery. They have also not identified a phenotype or process impacted by mitochondrial ubiquitination. Thus, at this stage, the biological consequences of mitochondrial ubiquitination remain elusive.
4) The authors have not directly investigated whether ubiquitin itself (without a mitochondrial targeting sequence) localizes in mitochondria. I encourage them to address this question since it would provide an important piece of evidence suggesting that mitochondrial ubiquitination can occur in endogenous conditions. This could be done using the alpha-complementation assay and the results could be presented within Figure 1. Ideally this experiment should be performed without overexpressing ubiquitin. Note that if the authors decide to use a C-terminally tagged form of ubiquitin for this experiment, the GG motif of ubiquitin should be mutated to avoid cleavage of the alpha tag by cellular DUBs. This form of ubiquitin will not be conjugatable, but this is not an issue for this experiment since its aim is to determine whether ubiquitin can be targeted to mitochondria, not to probe conjugates.
5) In the top panels of Figure 2 and S1, free ubiquitin is well detectable in the total and cytosolic fractions. It is however not clear to me whether it is also detectable in the concentrated mitochondrial fraction. If yes and if it would be resistant to trypsin digestion, it would provide an additional evidence that endogenous ubiquitin can be targeted to the mitochondrial matrix (see previous comment).
6) The data shown in the top panel of Figure 2 and S1 also suggest that free ubiquitin is less concentrated in mitochondria than in the cytosol (since it is more difficult to detect in the concentrated mitochondrial fraction than in the cytosolic fraction, see previous comment). It is thus possible that the use of preSu9-HA-Ubi (or preFum1-HA-Ubi) lead to an artificially high intra-mitochondrial concentration of free ubiquitin. As the concentration of free ubiquitin is known to impact ubiquitination processes, I encourage the authors to compare the relative levels of free ubiquitin present in the mitochondrial fraction prepared from wt and preSu9-HA-Ubi (or preFum1-HA-Ubi) expressing cells. If free ubiquitin is detectable in mitochondrial fractions and resistant to trypsin (see previous comment), this could be done by repeating the experiment shown in Figure 3B and probing the blot with an antibody that recognizes free ubiquitin.
7) I strongly encourage the authors to provide more data indicating that "ubiquitination occurs in mitochondria" by performing experiments that do not rely on the use of the preSu9-HA-Ubi or other forms of ubiquitin that are intentionally targeted to mitochondria. For instance, they could analyse the pattern of HA-Ubi conjugates of trypsin digested mitochondrial fractions prepared from wt, rad6-delta, and rad6-delta complemented with preSu9-Rad6-alpha-SL17. Note that if trypsin digested mitochondrial fractions are too contaminated by ubiquitinated proteins present outside mitochondria to perform this experiment, the authors may use the unspecific DUB Usp2 as an alternative protease to strip ubiquitinated proteins from the mitochondria periphery.
Minor comments:
1) Overall, the manuscript is well organized and easy to follow. The text is clearly written; the figures are well annotated.
2) The authors should provide full images of all the blots with anti-ubiquitin and anti-HA antibodies so that one can see the bands corresponding to free ubiquitin (or free HA-Ubi). For instance, in Figure 3B, it is not possible to see the presence (or absence) of the band corresponding to free HA-Ubi because the very bottom of the image is cut.
3) The authors should indicate whether the MTS of Su9 (and Fum1) are expected to be cleaved after import of preSu9-HA-Ubi (and preFum1-HA-Ubi) in mitochondria. They should also label on the corresponding immunoblots the presence (or absence) of the band corresponding to the free preSu9-HA-Ubi (and preFum1-HA-Ubi) (or HA-Ubi if the MTS is expected to be cleaved from these constructs).
4) In Figure 3B, the ubiquitin conjugates produced with preSu9-HA-Ubi and preFum1-HA-Ubi have different migration patterns. I think this should be explicitly mentioned and discussed. Could it be due to the presence of lysine residues in the Su9 or Fum1 MTS that could lead to the assembly of artificial ubiquitin chains?
5) The authors indicate that "endogenous Rad6 [...] is expressed at very low levels and can hardly be detected in the mitochondrial fraction by WB (Figure S5)". I did not manage to observe the band corresponding to endogenous Rad6 in the mitochondrial fraction in the pdf. The authors should provide a more contrasted or better quality image.
CROSS-CONSULTATION COMMENTS
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I agree with reviewer 2 that proper validation of the complementation assay is crucial for this manuscript. I was myself wondering whether it uses endogenously tagged proteins or whether it is based on an overexpression system. I imagine this information will be detailed in the manuscript in preparation mentioned by the authors. I am therefore wondering whether it would be possible to ask the authors to provide the draft of this manuscript (or at least the validation part).
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I agree with most comments of reviewer 3. Regarding the hypothesis that preSu9-HA-Ubi could form aggregates on the cytosolic surface of the mitochondria, I think that the results presented on Figure 7B rather argue against it (since they indicate that Rad6 localized inside mitochondria can restore the pattern of ubiquitin conjugates). That's why (in my opinion) the major question the author now need to adress is whether intra-mitochondrial ubiquitination occurs in endogenous conditions (ie without forcing ubiquitin into this compartment and without E2 or E3 overexpression).
Significance
The finding that ubiquitination occurs inside mitochondria would be an important conceptual advance, which would open new perspectives both for ubiquitination and mitochondrial biology research. However, the significance of the current manuscript is limited because the presented evidences heavily rely on the use of artificial conditions (ubiquitin tagged with a mitochondrial-targeting sequence) that may trigger irrelevant ubiquitination events. The significance would be much higher if the authors would provide further evidences indicating that intra-mitochondrial ubiquitination occurs in endogenous conditions and/or if they had identified a mitochondrial process specifically impacted by mitochondrial ubiquitination.
Expertise of the reviewer: Ubiquitination, Yeast biology, protein-protein interactions. No specific expertise in mitochondrial biology
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fvsch.com fvsch.com
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How can you generate category and tag pages? More generally, how do you generate any limited set of pages based on querying information from other content, without having to manually create a new (probably empty) content file?
I am very much a dev, but anything but an expert when it comes to the web or SSGs. This didn't seem that unsolvable to me although I'll acknowledge I do more in Liquid than one "should".
(ETA: Wait, no, the author agrees with me that doing a lot in one's templates is good.)
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
In this work, Chen et al. measured the DNA binding dynamics of HIF transcription factors using single-particle tracking. In particular, they examined the impact of heterodimerization between the alpha and beta subunits, the integrity of the DNA binding domain and the nature of the transactivation domain in DNA binding. As expected, they found that the stoichiometry between the heterodimerization partners directly impacts the bound fraction of the beta subunit which is devoid of a DNA binding domain. More interestingly, using domain swaps between HIF-1alpha and HIF2-alpha they found that the transactivation domain of the alpha subunit plays a major role in determining the bound fraction of the beta subunit (and thus the heterodimer). This work is important because it increases our understanding of how TF search the genome, beyond the traditional conception of the "addressing tag" provided solely by the DNA binding domain. This work is thus of interest to the broad audience of scientists studying gene regulation.
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www.nytimes.com www.nytimes.com
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he war in Ukraine remains a major variable in the worldwide supply outlook since Russia normally supplies one of every 10 barrels of the global 100-million-barrel-a-day market
Umfang des Ölmärkte: 100 Mill. Barrel am Tag.
Russischer Anteil: 10%
Verbrauch der USA: Ca ein Drittel
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Ahmed et al. examine the changes in the enhancer landscape that may contribute to the transition from Barrett's oesophagus (BO) to oesophageal adenocarcinoma (OAC), building upon their past works looking at the chromatin changes within this transition. They identified a repertoire of eRNA regions that display differential expression between OAC and BO, validating their association to enhancers using H3K27ac levels, CUT&TAG, and KAS-seq. The authors look further into the target genes and regulatory TFs that may define eRNA levels, finding several TFs - AP1, KLF5, CTCF, and HNF1 - that have previously been implicated in OAC and confirming that sets of eRNA target genes were downregulated upon depletion of these TFs. Ahmed et al. also showed that eRNA target genes were relevant to OAC phenotypes, akin to that of DEGs in whole RNA-seq datasets. The authors lastly validate the activity of certain eRNAs targeting JUP, MYBL2, and CCNE1 using functional methods to confirm enhancer activity and effects on cell viability, as well as clinical features such as the age of diagnosis and survival time.
The landscape of eRNA activity seems to be well validated. However, deeper analyses to support the relevance of the function of key eRNAs, their specificity in regulating target genes, and the interaction with other OAC features would further support these findings.
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jonudell.info jonudell.info
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Hypothes.is tools<br /> https://jonudell.info/h/tools.html
facet tools<br /> copy annotations<br /> tag rename<br /> annotation powered survey<br /> pagefit
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www.biorxiv.org www.biorxiv.org
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Reply to the reviewers
Manuscript number: RC-2022-01481R
Corresponding author(s): Sebastian Voigt. Mirko Trilling, David Schwefel
1. General Statements [optional]
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2. Description of the planned revisions
Reviewer #1: Evidence, reproducibility and clarity
Using proteome profiling of rat CMV infected cells, the authors of this study identify the E27 protein of rat cytomegalovirus as being crucial for proteasomal degradation of STAT2. Since E27 shares 56% sequence identity to the previously characterized STAT2 antagonist M27 of murine CMV the authors investigated association of E27 with the Cullin4-RING UbL CRL4. Using gel filtration chromatography they provide evidence that E27 forms a stable ternary complex with DDB1 and STAT2 suggesting that E27 bridges STAT2 to DDB1 which is further corroborated by data from cross-linking mass spectrometry. A cross-linked DDB1/DDA1/E27/STAT2 complex was then used for cryo-EM imaging experiments. The subsequent single particle analysis yielded a density map at 3.8 A resolution that was further used to generate an E27 molecular model. At this point it should be noted that resolution was not very high and data form AlphaFold2 prediction and CLMS experiments were necessary to build a model which was described as having "sufficient quality", however, no quality parameters are included for this model. In this model, a cryptic zinc-binding motif was identified that turned out to be well conserved in M27. At this point the study switches to a mutational analysis of M27: MCMV mutants either lacking M27 or bearing an AxAxxAA triple mutation were investigated both in cell culture and in animal models. Surprisingly, the M27-AxAxxA mutant while exhibiting attenuated IFN inhibition was still more active than an M27 deletion mutant. Later during the study it is postulated that this may be due to the fact that E27 binding to STAT2 abrogates the interaction with IRF9, however, this is only predicted from modeling and no experimental data are provided for this hypothesis. Furthermore, modeling approaches were used to predict how E27 replaces endogenous CRL4 substrate receptors and how E27 recruits STAT2 to mediate CRL4-catalysed ubiquitin transfer.
Reviewer #1: Significance
__Reviewer #1: __This is an interesting and well written paper describing for the first time in molecular detail how a cytomegalovirus-encoded interferon antagonist degrades STAT2 by mimicking the molecular surface properties of cellular CRL4 substrate receptors.
This study should be of broad interest for both virologists and structural biologists.
Authors Response: We thank the reviewer for the insightful and constructive evaluation. We are very grateful for highlighting the significance of our work.
Reviewer #1: Major points
__Reviewer #1: __To my opinion the authors should perform mutational analysis in the context of E27 and RCMV. I accept that switching to M27 may be easier due to established procedures for MCMV mutagenesis and analysis, however, since all structural work is primarily done on E27 it would be consequent to confirm these structural predictions in the context of E27 before switching to a related protein.
Authors Response: As the Reviewer appreciated, there were multiple reasons for the switch from RCMV-E E27 to MCMV M27. Most importantly, the MCMV in vivo infection model in mice is very well-established. Please also note that MCMV is applied far more often by virologists and immunologist as a standard model. Thus, the extension of our findings from RCMV to MCMV increases the relevance and outreach of the study. By performing the experiments in the MCMV context, we also aimed to emphasise that the function of the zinc-binding motif, which structurally organises the DDB1-binding domain, is functionally conserved among E27/M27-like proteins. Obviously, Reviewer #1 could ask why we do not solve the structure of M27 parallel to E27. With the sole exception of E27, none of the rodent M27 homologues could be produced recombinantly in a soluble form, preventing the purification and structure analysis of M27.
Since we agree with Reviewer #1 that the extension from E27 to M27 may read “a bit rough” without a mutational analysis in the E27 context, we will construct RCMV-E E27 mutants leading to Cys=>Ala exchanges in the Zn-binding motif. An analysis of the interaction between DDB1 and these E27 mutants will be included in the revised manuscript.
__Reviewer #1: __Moreover, data on the replication of the generated E27 deletion RCMV should be included in the manuscript (i.e. growth curves).
Authors Response: RCMV mutants lacking the E27 gene exhibit an impaired replication. According to the suggestion, the growth curves will be part of the revised manuscript.
Reviewer #1: The hypothesis that STAT2/E27 interaction is sterically incompatible with IRF9 binding is only based on structural prediction. It would help if the authors could present experimental evidence for such a mechanism.
Authors Response: The hypothesis is based on three lines of argumentation: (i) structural data regarding the binding interface between STAT2 and E27 covering the known STAT2-IRF9 interface (Fig. 7F) (Rengachari et al., 2018). (ii) The finding that M27 mutants incapable to bind DDB1 and induce STAT2 degradation along the ubiquitin proteasome pathway retain a residual capacity to inhibit ISRE signaling, suggesting that the binding of M27 to STAT2 suffices to elicit some signaling inhibitory functions (Fig. 7G). (iii) To elicit their function, CRL4 substrate receptors such as E27 interact with two partners. As we discussed elsewhere (Le-Trilling and Trilling, 2020), a simultaneous development of two independent traits violates evolutionary and probability theories. Thus, these receptors must acquire their binding interfaces sequentially, and the first interaction must provide an evolutionary advantage allowing the fixation of the allele in the population. Afterwards, the second binding interface evolves. Thus, a hypothesis in which E27/M27 precursors evolved the capacity to bind STAT2, preventing its association with IRF9 thereby establishing relevant but incomplete IFN inhibition (before the DDB1 interface was invented leading to STAT2 degradation by the proteasome), provides a parsimonious explanation for all these findings without violating evolutionary constraints. To corroborate our argumentation, we will analyse if E27 indeed displaces IRF9 from STAT2 by analytical gel filtration and/or co-immunoprecipitation experiments.
Reviewer #2: Evidence, reproducibility and clarity
__Reviewer #2: __The manuscript entitled "Structure and mechanism of a novel cytomegaloviral DCAF mediating interferon antagonism" by Dr. Schwefel and colleagues cleverly combines biochemistry, mass-spectrometry, Cryo-EM and cell biology to dissect how RCMV-E hijacks its hosts ubiquitylation machinery to mediate proteasomal degradation of STAT2, a key player driving the antiviral IFN response. They identify E27 as DDB1-binding element, which is able promote CRL4-dependent ubiquitylation of STAT2, and demonstrate its effect on STAT2 levels by knockout RCMV-E strains. These findings are supported by in vitro reconstitution of the DDB1/E27/STAT2 complex and analyses via XL-MS and Cryo-EM. The obtained data are then powerfully validated and analysed in mutational strains via infection of homologue in vivo models. The results collectively explain how E27 mimics endogenous CRL4 substrate receptors, thereby recruiting STAT2 to be targeted by CLR4 for ubiquitylation in a NEDD8-dependent manner.
Overall this is an important study that provides convincing insights on how rodent CMVs antagonize their host interferon response by exploiting its ubiquitin-proteasome system.
The manuscript is well written and its introduction is extraordinarily comprehensive. There are a few minor points for the authors to consider below.
Authors Response: We thank the reviewer for this very positive assessment.
Reviewer #2: Significance
Reviewer #2: The work of Schwefel and colleagues combines several powerful state-of-the art techniques to dissect the mechanism of the viral protein E27 and, for the first time, provides a rational for its ability to act as STAT2 antagonist. They performed outstanding structure-function analyses of the ubiquitin system, including the first global proteomic profiling of RCMV-infected cells, setting the standard for its human counterpart as rodent CMVs are commonly used as infection models. The manuscript is highly suitable for publication in any of the journals associated with the review commons platform.
Authors Response: Again, we thank the reviewer for these kind words and the appreciation of our work.
Reviewer #2: CROSS-CONSULTATION COMMENTS
Reviewer #2: This reviewer agrees that at least testing mutants in the E27 in some assays would be appropriate.
Authors Response: As detailed in the response to Reviewer #1, we will generate RCMV-E E27 mutants targeting the Zn-binding motif by site-directed mutagenesis. An analysis of the interaction between DDB1 and these E27 mutants will be included in the revised manuscript.
Reviewer #3: Evidence, reproducibility and clarity
__Reviewer #3: __Le-Trilling et al. present the first proteomic analysis of RCMV-infected cells, where they identified STAT2 as one of the most heavily downregulated (and degraded) proteins. This analysis showed that RCMV mediated degradation of STAT2 is conserved in closely related species used as animal models (rat and mouse) and human, despite the intra-host adaptation of each CMV. They also identify E27 as the RCMV factor that targets STAT2 for degradation, that exhibits ~50% homology with MCMV pM27. This study also identifies a Zinc binding motif in E27 using Cryo-EM which is conserved in other CMV species and is potentially involved in antagonising Type I and III responses.
Reviewer #3: Significance
__Reviewer #3: __The present work provides the first proteomics analysis of RCMV infection in rat cells, comparing infected vs non-infected rat fibroblasts to access potential RCMV targets. Then, it focuses on the characterisation of RCMV E27 and its role targeting and interacting with STAT2 (plus recruiting the Cul4 complex for STAT2 degradation). Finally, it provides the Cryo-EM structure of E27 and its CMV homologues, and the structure of the complex of E27 with elements of the CUL4 complex and STAT2. This is the first time that E27 function and structure are characterised. These are all novel findings - although the mouse homologue M27 has previously been found to interact with and degrade STAT2 (published by some of the same authors in Plos pathogens in 2011, (https://doi.org/10.1371/journal.ppat.1002069). Therefore the chief novel information is the structural studies.
The manuscript will be of interest to researchers working with human and animal herpesviruses.
My field of expertise is in Virology, Innate Immunity and host-virus interactions from an evolutionary perspective. I do not have expertise in Cryo-EM, so I could not evaluate the methods used in the section.
__Authors Response: __We thank the reviewer for the positive evaluation of our work and its significance.
Reviewer #3: Major points
__Reviewer #3: __1. The authors claim the identification of a Zinc-binding motif in the protein E27 (RCMV) using Cryo-EM, then validation of the phenotype with MCMV WT, delM27 and M27 AxAxxA. To justify the change to MCMV to perform the functional validation, they stated "MCMV M27, the closest E27 homologue, exhibits 56% and 76% amino acid sequence identity and similarity, respectively (Fig. S4B). E27 and M27 AlphaFold2 structure predictions are almost indistinguishable (RMSD of 1.195 Å, 6652 aligned atoms) (Figs. 3B, S4A), and structural alignment of these predictions demonstrated conservation of side chain positions involved in zinc-binding (Fig. 3C). Thus, M27 represents a valid model to study functional consequences of interference with the zinc coordination motif through site-directed mutagenesis, and to test the predictive power of our E27/M27 model". Although they rationalise the change to MCMV to validate the functional outcomes of the newly identified zinc binding motif with alignments and Cryo-EM data, it falls within the DDB1 binding region that is less conserved (Fig S4B). The addition of a mouse model here provides a solid result but given the aim of the paper is to provide a proper characterisation of RCMV and elucidate some inter-species adaptations, I strongly recommend the validation with E27 here given the potential impact of this motif. Rather than having to repeat this in a rat model (which would clearly be a large amount of work), this could simply be achieved by constructing the relevant deletion / mutant viruses and assessing in vitro in a relevant cell line (readout - either virus titre or luciferase assay as shown in Figure 3G/H).
__Authors Response: __Please also see our responses to the other reviewers. Briefly, we will apply side-directed mutagenesis to alter the CxCxxC motif in E27 that binds the zinc ion, and analyse the interaction of these E27 mutants with DDB1. In this context, we would like to add that almost two thirds of E27 residues in direct contact with DDB1 are at least type-conserved in M27, and the zinc-coordinating side chains are totally conserved (Fig. 3C). Together with a predicted similar structural organization of the respective binding regions (Fig. S11), and in light of our MCMV mutagenesis results (Fig. 7), it is highly likely that the DDB1-binding mode is conserved between E27 and M27. As mentioned above, we will put this assumption to the test in the revision process.
__Reviewer #3: __Furthermore, in Figure 2, the GF assay was performed using full-length DDB1, however CLMS was performed using DDB1 delBPB (interchange between these two proteins continues in the remainder of the paper). This should be at least justified, and preferably one or other of wt DDB1 and DDB1 delBPB used in the GF or CLMS assay where this has not yet been performed. Later on in the results section (Fig 5E), the authors use wt DDB1 while in fig 4 they used the delBPB to describe the interaction with E27 - would be relevant to have consistency across the paper and some supplementary data that could support using one or the other in each assay.
__Authors Response: __Protein complex preparations including full length DDB1 did not yield cryo-EM reconstructions at appropriate resolution for model building, almost certainly due to the known flexibility of the DDB1 BPB, impeding proper alignment of the cryo-EM particle images. This is why we switched to DDB1ΔBPB. Importantly, the structure model including full length DDB1 (Fig. S12B) clearly demonstrates that the BPB is located on the opposite side of the E27 binding interface on DDB1 (where it is situated to flexibly connect to the CUL4 scaffold to create the ubiquitination zone around immobilised substrates [Fig. 6]). This rules out an involvement of DDB1 BPB in E27- and/or STAT2-binding processes. Several previous studies have employed DDB1ΔBPB to facilitate structure determination, and have successfully applied the resulting structural models for functional follow-up experiments in the context of complete CRL4 assemblies (Bussiere et al., 2020; Petzold et al., 2016; Slabicki et al., 2020). Nevertheless, we will repeat GF experiments with DDB1ΔBPB for consistency and include these data in the revised manuscript.
Reviewer #3: Minor points
__Reviewer #3: __2. Although they present sufficient detail in the methods, further details in the text should be given as to the number of repeats performed in each case, and whether the data shown is representative or based on an average of repeats (preferably the latter; if representative, the data for other repeats should be shown in supplementary information).
Authors Response: We will add this information in the revised version of the manuscript.
3. Description of the revisions that have already been incorporated in the transferred manuscript
Reviewer #1: Major points
__Reviewer #1: __Resolution of the cryoEM structure is rather low and many predictions of the manuscript are based on modeling using AlphaFold2 prediction. The authors describe their model as of "sufficient quality", however, no quality measures are included in the manuscript. At least the discussion should address limitations of the used approach.
Authors Response: While we apologize for not sufficiently describing our quality measures, we respectfully disagree regarding the conclusion. Our resolution (3.8 Å, map 1) lies well within the 3–4 Å resolution range of the vast majority of structures deposited to the Electron Microscopy Data Bank during the last five years (https://www.emdataresource.org/statistics.html). Nevertheless, de novo modelling in this resolution regime is challenging. This is why we sought additional guidance through cross-linking mass spectrometry (XL-MS) restraints and AlphaFold2. Please also note that modelling of E27 was not based solely on the AlphaFold2 prediction. Instead, a partial model corresponding to the α-domain was manually built in map 1, guided by XL-MS information (see Methods - “Model building and refinement” and Fig. S5B, grey cartoon). This partial model proved to be in very good agreement with AlphaFold2 predictions (RMSD of 1.489 Å, 2764 aligned atoms). Only after this initial sanity check, the computational prediction was used for model completion, adjustment, and refinement.
We now added graphical overviews of model fits in Figs. S5 and S10. Furthermore, we included detailed views of the fit of relevant side chains involved in intermolecular interaction to the experimental density (Fig. S7, S9). We also calculated and listed quality indicators of the model-to-map fit in Table S1 (correlation coefficients and model resolution based upon model-map FSC). To ensure the validity of our atomic model using an alternative method besides cryo-EM and XL-MS, we have performed site-directed mutagenesis of critical binding regions in E27, followed by in vitro reconstitution and analytical GF (Fig. S7B, C, S9B, C). The text was revised accordingly (see p10 [ll22] and p14 [ll26]).
__Reviewer #1: __The authors identify a cryptic zinc-binding motif in E27 that is conserved in homologous proteins. For this reviewer it is not clear: is there experimental evidence for zinc binding of E27 or can the presence of zinc reliably be detected in their structural data? If not, it would be worth to confirm zinc binding.
Authors Response: Our structural data show a tetragonal metal coordination geometry, involving three cysteine side chains and one histidine side chain, with coordination bond lengths of 2.2 Å between the histidine nitrogen and the metal ion, and of 2.4 Å between the cysteine sulfurs and the metal ion. The density feature cannot be explained by another type of side chain interaction, e.g. a disulfide bond, because this would lead to a steric clash with the remaining adjacent side chains. Based on the knowledge on metal-binding sites in proteins and metal-coordination chemistry, these characteristics indicate the presence of a structural zinc-binding site for the following reasons: (i) after magnesium, zinc is the second most prevalent metal in the Protein Data Bank (https://metalpdb.cerm.unifi.it/getSummary), however, magnesium is coordinated octahedrally by oxygen ligands (Tang and Yang, 2013); (ii) the most abundant zinc ligands are cysteine and histidine; (iii) the most abundant zinc coordination number is four ligands; (iv) the average coordination bond lengths are 2.12±0.19 Å and 2.33±0.12Å for nitrogen-zinc and sulfur-zinc interactions, respectively (Ireland and Martin, 2019; Laitaoja et al., 2013), which is in very good agreement with our structural observations. We included this argumentation in the revised manuscript (see p9 [ll21]), and added Fig. S5C for visualization.
Reviewer #2: Minor points
Reviewer #2: Page 2, line 3. "Here," should be inserted before "Global proteome profiling..." to highlight the work of this manuscript.
Authors Response: We changed the text accordingly.
Reviewer #2: Page 3, line 21. "IFNs" instead of "IFN"
Authors Response: We changed the text accordingly.
Reviewer #2: Page 4, lines 9,15,27. "Ubiquitin Ligases (UbL)" is not a common abbreviation and could be mistaken for Ubl (Ubiquitin-like proteins). Possible abbreviation is "E3s" for Ubiquitin E3 ligases
Authors Response: We have amended the respective abbreviations accordingly.
Reviewer #2: Page 4 line 25. "RBX1" is the more common term for "ROC1"
Authors Response: This has been corrected throughout the manuscript.
Reviewer #2: Page 5 lines 1-9. Citing of the first structure of DDB1 in complex with a viral protein is recommended. (Ti Li et al. Cell 2006)
Authors Response: We thank the reviewer for this important suggestions and cited this landmark publication.
Reviewer #2: Figure 1 a) STAT2 dot is cut off in second panel. I recommend highlighting STAT2 in both panels.
We amended the figure accordingly. We furthermore additionally highlighted the “STAT2” text in both panels by increasing the font size and putting it in bold type.
Reviewer #2: Page 7 line 17. "Cross-linking MS (CLMS)" is commonly abbreviated as (XL-MS)
Authors Response: We changed the text accordingly.
Reviewer #2: Figure 2 a-c) These panels could benefit from thinner lines in order to increase visibility of chromatograms and cross-links.
Authors Response: The panels were changed accordingly.
Reviewer #2: Figure 2 a-b) Could the authors elaborate on why STAT2 is stoichiometrically
underrepresented in the SDS-PAGE of the E27/DDB1/STAT2 complex?
Authors Response: We applaud Reviewer #2 for their in-depth examination. Honestly, we were also puzzled by this. Based on the cryo-EM single particle analysis, we found an explanation: We separated a major contamination in silico during 2D classification (~12% of all particles). Out of curiosity, we reconstructed a density map from these particles (now shown in Fig. S3). The map was identical to a previous cryo-EM structure of the E. coli protein ArnA (Yang et al., 2019), a notorious contaminant in E. coli Ni-NTA protein purifications (Andersen et al., 2013). ArnA migrates similar to E27 on the SDS-PAGE, the band runs just a little bit faster (compare fraction 6 [ArnA] and fractions 8/9 [E27] from the SDS-PAGE of the analytical GF run of E27 in isolation, Fig. 2A, green trace). However, in analytical GF, ArnA elutes at higher molecular weight fractions, since it forms a hexamers (Ve~10.2 ml). Incidentally, this elution volume of the ArnA hexamer almost equals the one of DDB1 or DDB1ΔBPB/DDA1/E27/STAT2 complexes. This leads to a superposition of ArnA and E27 bands in the respective SDS-PAGE lanes corresponding to GF fraction 6. Accordingly, we conclude that it is actually not STAT2 that is underrepresented, but rather E27 seems overrepresented due to SDS-PAGE band overlap with the ArnA contaminant. We have now indicated the contaminant in Fig. 2A, amended the legend, and extended Fig. S3 to indicate at which point of the cryo-EM analysis the contaminating ArnA particles were separated, and to show the ArnA model to map fit.
In addition to this, it might be that potential STAT2 degradation products (marked by ** in Fig. 2), which seem to co-migrate with STAT2/E27 complexes, occupy FL STAT2 binding sites on E27.
Reviewer #2: Paragraph "The E27 structure.." page 9. Placing this paragraph after the overall
structure is recommended.
Authors Response: Accordingly, we have now moved this section to the end of the results section.
Reviewer #2: Figure 3 a) The grey mesh being laid over the ribbon structures is not contributing to the overall visibility. Adding a panel of the cryo-EM structure alone in cost of alphafold models is recommended.
Figure 4a) same issue with grey mesh
Authors Response: Thank you very much for the very good suggestions. We have removed the mesh representation, and included panels just showing the segmented cryo-EM map in the new Fig. 3A.
Reviewer #2: c) panels could benefit from fewer amino acids being labeled/shown
Authors Response: We understand the motives of the Reviewer. However, we would prefer to depict all relevant side chain interactions in these panels. The rearrangement of the figure, i.e. showing the overview of the interacting regions before the detailed panels, should make them more accessible (new Fig. 3B).
__Reviewer #2: __d) may want to avoid red-green coloring to improve for colorblindness
Authors Response: We are deeply sorry for our ignorance in this regard. We changed the colors accordingly (see new Fig. 3B, C).
__Reviewer #2: __Figure 6a) s.a grey mesh
Authors Response: We removed the mesh representations and included panels just showing the segmented cryo-EM density in the new Fig. 5C.
Reviewer #2: CROSS-CONSULTATION COMMENTS
__Reviewer #2: __A 3.8 A overall resolution map and the approach to fitting may be suitable, but it is unclear from the authors' figures whether the side-chains shown in the figures are clearly visible in the map or if they are modeled by some other approach. Side chains should ideally be visible in the maps if shown in figures, and if not, close-ups of the corresponding regions of the maps should be shown with sufficient depthcue to allow the reader to gauge how the map corresponds to the model.
Authors Response: This is a crucial point. As mentioned in the response to Reviewer #1, major point 2, we have now included very detailed views of the fit of relevant side chains involved in intermolecular interaction to the experimental density (Fig. S7, S9).
__Reviewer #2: __Along these lines, the figures with the mesh maps do not clearly show how well the model fits the map. This needs to be clearly visible in figures, and ideally maps and models provided to reviewers in order for the reviewers to gauge the level of accuracy of the fit.
Authors Response: Please see our response to Reviewer #1, major point 2. Briefly, we have now included graphical overviews of model fits in Figs. S5 and S10. We also calculated and listed quality indicators of the model-to-map fit in Table S1 (correlation coefficients and model resolution based upon model-map FSC). To ensure the validity of our atomic model using an alternative method besides cryo-EM and XL-MS, we have performed site-directed mutagenesis of critical binding regions in E27, followed by in vitro reconstitution and analytical GF (Fig. S7B, C, S9B, C). The text was extended accordingly (see p10 [ll22] and p14 [ll26]).
__Reviewer #2: __At minimum, the authors have nicely assembled proteomics and cell biological data indicating that E27 hijacks CRL4 to turn over Stat2 in rat cells in a manner paralagous to M27 hijacking in mouse cells, biophysical/structural data for a model of a CUL4-DDB1-E27-Stat2 complex, and mutagenesis of a putative zinc binding site in M27.
I feel most of the issues raised by all 3 reviewers could be addressed in the text, with more clarity about the structural models, and better explanation for why the construct with proteins from various organisms were used for structural studies (the authors had made human DDB1 before, and it expressed well, and perhaps didn't consider to make from rat? Or this mixture expressed, purified best? Gave best quality EM data?).
Authors Response: We thank Reviewer #2 for her/his overall assessment. As mentioned in the two cross-consultation comments before, and in the response to Reviewer #1, major point 2, we strived to provide adequate measures allowing to judge the quality of our structural models in the present updated version of the manuscript. In addition, as indicated in the response to reviewer #3, major point 2, we have now added Fig. S12 and extended the Discussion to explain and justify the use of different protein constructs.
__Reviewer #2: __Also, the presentation of the zinc binding site should come after the overall structure. As for the use of MCMV to assess the role of the zinc binding site, placing this last in the text might allow this to flow better.
Authors Response: Thank you very much for this suggestion. The manuscript has been restructured as recommended: details of the zinc-binding motif and the MCMV assays are now shown in Fig. 7 and described in the text just before the Discussion.
Reviewer #3: Major points
__Reviewer #3: __2. Given that previous data in mice showed that the E27 homologue pM27 binds a component of host Cullin4-RING UbLs (CRL4), to induce the poly-ubiquitination of STAT2, the current study also addressed if this mechanism was preserved in RCMV. Yet, they seemed to do this with E27, rnSTAT2 and hsDDB1 - Page 7 lines 1 to 3: "These results prompted us to explore the association of E27 with Rattus norvegicus (rn) STAT2 and Homo sapiens (hs) DDB1 in vitro. Importantly, 1128 of 1140 amino acids are identical between hsDDB1 and rnDDB1 (...)". They identify the residues and regions where the DDB1 is different between both species, but should provide a structure/alignment with this highlighted. In addition, DDB1 is a DNA damage protein that is annotated in the Rattus norvegicus genome. The authors should justify the assays between rnSTAT2-hsDDB1 instead of using the both proteins from rn, and present the equivalent data for rnDDB1 in the paper.
Authors Response: Among the 12 alterations between human and rat DDB1, 4 are type-conserved (Fig. S12A). Thus, >99% of amino acids are identical or similar. We mapped all exchanges on a model of full length human DDB1 bound to E27 and the rat STAT2 CCD. None are involved in intermolecular interactions (Fig. S12B, C). Please note that due to the high conservation of DDB1 across eukaryotes, this inter-species approach has been used by us and others to study DDB1-containing complexes (e.g., the SV5V, WHX, SIV Vpx and Vpr, zebrafish DDB2, and chicken CRBN proteins have been in vitro reconstituted with human DDB1 for structural characterisation) and valid biological conclusions have been drawn from these studies (Angers et al., 2006; Banchenko et al., 2021; Fischer et al., 2014; Fischer et al., 2011; Li et al., 2006; Li et al., 2010; Schwefel et al., 2015; Schwefel et al., 2014; Wu et al., 2015).
Reviewer #3: Minor points
__Reviewer #3: __1. In fig 5D, the authors present the H-box alignment, where it is clear that this motif is not conserved. The lack of H-box conservation should be discussed in the results and discussion, to provide an explanation for the competition/binding observed.
Authors Response: We respectfully disagree. There is conservation of amino acid side chains, regarding their physicochemical properties, observable in the H-box motif. Furthermore, the secondary structure is conserved. Please note, that the H-box is not our invention but rather represented a well-accepted motif known in the field, see e.g., (Li et al., 2010). We extended the discussion to cover this point (p21 [ll15]).
__Reviewer #3: __3. The authors commence their abstract justifying the study on the grounds of the usefulness of rodent HCMV counterparts as common infection models for HCMV. They should return to this theme in the discussion - what is the usefulness of their findings with regards to HCMV (particularly given the relatively low homology between E27 and HCMV pUL27, and the alternative mechanism for STAT2 antagonism encoded by HCMV UL145)?
Authors Response: We extended the discussion in this regard. Briefly, our data, to our knowledge for the first time, reveal that RCMV (like MCMV) exploits CRL4 to induce proteasomal degradation of STAT2. With pUL145, HCMV relies on an analogous protein. In clear contrast to HCMV, RMCV and MCMV are both amenable to in vivo experiments in small animal models. Over 40 years ago, HCMV has been called the troll of transplantation due to its grim impact on immunosuppressed individuals after transplantation surgery (Balfour, 1979). Despite tremendous efforts, HCMV still harms and kills graft recipients. While MCMV allows various experiments regarding general principles of cytomegaloviral pathogenesis and antiviral immunity, one shortcoming is that the mouse obviously is a rather small animal, preventing various chirurgical and solid organ transplantation (SOT) procedures. In clear contrast, SOT procedures that are indispensable for human medicine can be recapitulated in rat models. Thus, according to our opinion, our work lays the molecular foundation for future studies addressing the relevance of STAT2 and CMV-induced STAT2 degradation in rat SOT models.
4. Description of analyses that authors prefer not to carry out
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Reply to the reviewers
Manuscript number: RC-2022-01528
Corresponding author(s): Elena Taverna and Tanja Vogel
1. General Statements [optional]
We thank the reviewers for the comments and points they raised. We think what we have been asked is a doable task for us and we are confident we will manage to address all points in a satisfactory manner.
2. Description of the planned revisions
Reviewer #1 (Evidence, reproducibility and clarity (Required)):
Reviewer’s comment: The manuscript investigated the role of DOT1L during neurogenesis especially focusing on the earlier commitment from APs. Using tissue culture method with single-cell tracing, they found that the inhibition of DOT1L results in delamination of APs, and promotes neuronal differentiation. Furthermore, using single cell RNA-seq, they seek possible mechanisms and changes in cellular state, and found a new cellular state as a transient state. Among differentially expressed genes, they focused on microcephaly-related genes, and found possible links between epigenetic changes led by DOT1L inhibition and epigenetic inhibition by PRC2. Based on these findings, they suggested that DOT1L could regulate neural fate commitment through epigenetic regulation. Overall, it is well written and possible links from epigenetic to metabolic regulation are interesting. However, there are several issues across the manuscript.
Response to Reviewer and planned revision:
We thank the reviewer’s 1 for her/his comments and constructive criticism.
We hope the revision plan will address the points raised by the reviewer in a satisfactory manner.
Major issues:
* *Reviewer’s comment: 1) It is not clear whether the degree of H3K79 methylation (or other histones) changes during development, and whether DOT1L is responsible for those changes. It is necessary to show the changes in histone modifications as well as the levels of DOT1L from APs to BPs and neurons, and to what extent the treatment of EPZ change the degree of histone methylation.
Response to Reviewer and planned revision:
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As for the level of DOT1L protein We tried several commercially available antibodies, but they do not work in the mouse, even after multiple attempts and optimization. So, unfortunately we will not be able to provide this piece of information.
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As for the level of DOT1L mRNA We will provide info regarding the DOT1L mRNA level in APs, BPs and neurons by using scRNAseq data from E12, E14, E16 WT cerebral cortex.
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As for the levels of H3K79methylation, we did not intend to claim that the histone methylation is responsible for the reported fate transition. We will edit the text to avoid any possible confusion. If it is deemed to be necessary to address the point raised by the reviewer, we do have 3 options, that we here in order of priority and ease of execution from our side.
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immunofluorescence with an Ab against H3K79me2 using CON and EPZ-treated hemispheres.
- FACS sort APs, BPs and neurons from CON and EPZ-treated hemispheres, followed by immunoblot for H3K79me2 to assess the H3K79me2 levels. As for the FACS sorting, we will use a combinatorial sorting in the lab on either a TUBB3-GFP or a GFP-reporter line using EOMES-driven mouse lines. This strategy has already been employed in the lab by Florio et al., 2015 and we will use it with minor modifications.
- scCut&Tag for H3K79me2 from CON and EPZ-treated hemispheres. This option entails a collaboration with the Gonzalo Castelo-Branco lab in Sweden and might therefore require additional time to be established and carried out. Reviewer’s comment:
Furthermore, the study mainly used pharmacological bath application. DOT1L has anti-mitotic effect, thus it is not clear whether the effect is coming from the inhibition of transmethylation activity.
Response to Reviewer and planned revision:
In a previous work we used a genetic model (DOT1L KO mouse) that showed microcephaly (Franz et al. 2019). For this study, we wanted to fill a gap in knowledge by understating if the DOT1L effect was mediated by its enzymatic activity. For this reason, we choose to use the pharmacological inhibition with EPZ, whose effect on DOT1L activity has been extensively reported and documented in literature (EPZ is a drug currently in phase clinical 3 studies).
The stringent focus of this study on the pharmacological inhibition is thus a step toward understanding what specific roles DOT1L can play, both as scaffold or as enzyme.
Here, we concentrate on the enzymatic function and the scaffolding function is beyond the scope of this specific study. We can further discuss and elaborate on the rationale behind this in the revised manuscript.
Reviewer’s comment:
In addition, the study assumed that the effect of EPZ is cell autonomous. However, if EPZ treatment can change the metabolic state in a cell, it would be possible that observed effects was non-cell autonomous. It would be important to address if this effect is coming in a cell-autonomous manner by other means using focal shRNA-KD by IUE.
Response to Reviewer and planned revision:
We did not claim that the effect of EPZ is cell autonomous, we are actually open on this point, as we consider both explanations to be potentially valid. We will edit the text to avoid any possible confusion on what we assume and what not.
As a general consideration, it is entirely possible that the effects are non-cell autonomous. We will comment and elaborate on that in the revised manuscript.
If the reviewer/journal considers this a point that must be addressed experimentally, then we will proceed as follows:
- DOT1L shRNA-KD via in utero electroporation, followed by either
- in situ hybridization for ASNS to check if ASNS transcript is increased upon DOT1L shRNA-KD compared to CON
- FACS sorting of the positive electroporated cells (CON and DOT1L shRNA-KD), followed by qPCR to assess the levels of ASNS
- If the reviewer wants us to check for a more downstream effect on fate, then we will immuno-stain the DOT1L shRNA-KD and CON with TUBB3 AB and/or TBR1 AB (as already done in the present version of the manuscript). Reviewer’s comment: 2) The possible changes in cell division and differentiation were found by very nice single-cell tracing system. However, changes in division modes occurring in targeted APs such as angles of mitotic division and the expression of mitotic markers were not addressed. These information is critical information to understand mechanisms underlying observed phenotype, delamination, differentiation and fate commitment.
Response to Reviewer and planned revision:
Previous effects of DOT1L manipulation on the mitotic spindle were observed in a previous paper, using DOT1L KO mouse (Franz et al. 2019). Considering that in our experiments we do use a pharmacological inhibition, we will address this point by quantifying the spindle angle in CON and EPZ-treated cortical hemispheres.
We will co-stain for DAPI to visualize the DNA/chromosomes, and for phalloidin (filamentous actin counterstain) that allows for a precise visualization of the apical surface and of the cell contour, as it stains the cell cortex.
Of note, the protocols we are referring to are already established in the lab, based on published work from the Huttner lab (Taverna et al, 2012; Kosodo et al, 2005).
Reviewer’s comment: 3) The scRNA-seq analysis indicated interesting results, but was not fully clear to explain the observed results in histology. In fact, in single cell RNA-seq, the author claimed that cells in TTS are increased after EPZ treatment, which are more similar to APs. However, in histological data, they found that EPZ treatment increased neuronal differentiation. These data conflicts, thus I wonder whether "neurons" from histology data are actually neurons? Using several other markers simultaneously, it would be important to check the cellular state in histology upon the inhibition/KD of DOT1L.
Response to Reviewer and planned revision:
The reviewer’s comment is valid, and we indeed found that TTS cells are an intermediate state between APs and neurons in term of transcriptional profile. This is the reason why we called this cell cluster transient transcriptional state.
We plan to address this point by staining for TBR1 and/or CTIP2 in CON and EPZ-treated hemispheres and to expand with this EOMES and SOX2 co-staining.
Minor issues:
Reviewer’s comment: Figure 1 - It is not clear delaminated cells are APs, BPs or some transient cells (Sox2+ Tubb3+??). It is important to use several cell type-specific and cell cycle markers simulnaneously to characterize cell-type specific identity of the analysed cells by staining. These applied to Fig1B,D,E,F,G,as well as Fig2,3.
Response to Reviewer and planned revision:
We will address this point by using a combinatorial staining scheme for several fate markers such as TUBB3, EOMES and SOX2, as suggested by the reviewer.
Reviewer’s comment: - Please provide higher magnification images of labelled cells (Fig 1H)
Response to Reviewer and planned revision:
In the revised manuscript, we will provide higher magnification for the staining.
Reviewer’s comment: - Please provide clarification on the criteria of Tis21-GFP+ signal thresholding.
Response to Reviewer and planned revision:
In the revised manuscript, we will provide a clarification on the criteria of Tis21-GFP+ signal thresholding.
Reviewer’s comment: - Splitting the GFP signal between ventricular and abventricular does not convincingly support the "more basal and/or differentiated" states after EPZ treatment.
Response to Reviewer and planned revision:
We will provide a clarification regarding this point.
Reviewer’s comment: - Please explain the presence of Tis21-GFP+ cells at the apical VZ.
Response to Reviewer and planned revision:
Tis21-GFP+ cells at the apical VZ has been extensively reported in the literature, since the first paper by Haubensak et al. regarding the generation of the Tis21-GFP+ line. In a nutshell, T Tis21-GFP+ cells are present throughout the VZ (therefore also in the apical portion) as neurogenic, Tis21-GFP positive cells are undergoing mitosis at the apical surface. Indeed, the presence of Tis-21 GFP signal have been extensively used by the Huttner lab and collaborators to score apical neurogenic mitosis. In addition, since AP undergo interkinetic nuclear migration, it follows that Tis21-GFP+ nuclei are going to be present throughout the entire VZ.
In the revised manuscript, we will explain this point and cite additional literature.
Reviewer’s comment: - Order the legends in same order as the bars.
Response to Reviewer and planned revision:
We will follow reviewers’ recommendation and order the legends accordingly.
Reviewer’s comment: Figure 2 -Fig 2B) The difference between CON and EPZ apical contacts is not clear and does not match with the graph in Fig 2E.
Response to Reviewer and planned revision:
We will explain Fig. 2B in more detail and provide additional images in the revised manuscript.
Reviewer’s comment: -Supp Fig 2 - are these injected slices cultured in control conditions? Please include this in the text and figure/figure legend
Response to Reviewer and planned revision:
In the revised manuscript, the text will be changed to address this point and provide clearer info.
Reviewer’s comment: Fig 2C) The EPZ-treated DxA555+ cells exhibit morphological change of cell shape. Is this phenotype? please comment on the image shown for EPZ treatment panel.
Response to Reviewer and planned revision:
We thank the reviewer for having raised this point.
The change in morphology might be a consequence of delamination and or of cell fate. In the revised manuscript, we will certainly better comment on this very relevant point and expand the discussion accordingly.
Reviewer’s comment: Fig 2F - 2G) Data presented on EOMES+ and TUBB3+ % are counterintuitive. The authors claimed that TUBB3+ cells are increased and neuronal differentiation is promoted. However, no changes in EOMES+ are observed. What is the explanation? Did the author check the double positive cells? These could be TSS cells?
Response to Reviewer and planned revision:
We thank the reviewer to have raised this point.
As envisioned by the reviewer, we suspect that the counterintuitive data might be due to TSS cell, which based on our scRNAseq data are expressing at the same time several cell type specific markers. It is possible that, since the treatment with EPZ is 24h long, cells (like the TTS cluster) have no time to completely eliminate the EOMES protein. If that were to be the case, then we would expect to still detect (as we indeed do) EOMES immunoreactivity.
To address this point, we will:
- analyze scRNA-seq data and check which is the extent of co-expression of Eomes and Tubb3 mRNAs in the TTS population.
- Check for EOMES and TUBB3 double positive cells in the microinjection experiment. Reviewer’s comment: Figure 2 and Figure 3) the number of pairs analyzed for EPZ is twice as that of Con for comparison of the parameters taken into account. Please include n of each graph in the figure legend of the specific panel if not the same for all panels in that figure (i.e. for figure 3)
Response to Reviewer and planned revision:
We will revise the text accordingly.
Reviewer’s comment:
Figure 3) The data indicated that the number of daughter cell pairs in EPZ samples is almost double than Control. Is this the phenotype? More numbers of daughter cells in EPZ treated samples were observed from the same number of injections? or the number of injected cells were different?
Response to Reviewer and planned revision:
Due to technical reasons, we indeed performed a higher number of injections in EPZ-treated slices. We think this is the main reason behind the difference in number.
If the reason were to be biological, one would expect to see the same trend in IUE experiments, but this is actually not the case. This does suggest/corroborate the idea that the reason behind the difference is mainly technical.
Reviewer’s comment: Figure 4)
- Please clarify if the single cell transcriptomic analysis has been performed only once, and if yes, how statistical testing to compare the cell proportion is carried out with only one batch. Fig 4G)
Response to Reviewer and planned revision:
As for the scRNAseq on microinjected cells:
the scRNA-seq analysis was done once using cells pooled from 3 different microinjection experiments performed in 3 different days.
As for the scRNAseq on IUE cells:
The scRNA-seq analysis was done once using cells pooled from 2-3 different IUE experiments performed in 3 different days.
For all scRNAseq experiments the statistical testing is achieved by intrasample comparisons according to established bioinformatics pipelines. We will better explain this point in the revised manuscript.
Reviewer’s comment: Figure 4 and 5) - Figures are not supportive of the statement regarding APs' neurogenic potential upon DOT1L inhibition. TSS transcriptomic profile resembles more progenitors than neurons. Please comment on TSS neurogenic capacity taking into account the provided GO and RNAseq.
Response to Reviewer and planned revision:
We thank Reviewer 1 for raising this point, It is indeed true that TTS resemble more AP than neurons (as indicated in the Fig. S5B, C). We took that to indicate the fact that these cells are transient and therefore still maintain some AP features. Interestingly, TTS downregulate cell division markers, suggesting a restriction of proliferative potential, as one would expect for cells with an increased neurogenic potential. We will discuss this point in the revised manuscript.
Reviewer’s comment: - Please provide GO analysis for APs and BPs.
Response to Reviewer and planned revision:
Following the reviewer’s suggestion, we will incorporate a more careful and in-depth analysis in the revised version of the manuscript.
Reviewer’s comment: - Reconstruct figure 5A by listing genes in the same order in both Con and EPZ and prioritize EPZ-Con differences instead of cell-cell differences.
Response to Reviewer and planned revision:
We will revise Figure 5A based on the reviewer’s comment.
Reviewer’s comment:
Moreover, the presented genes in the heatmap is not the same in two conditions (i.e. NEUROG1 is present in EPZ but absent in Con). Please justify.
Response to Reviewer and planned revision:
This observation is based on different activities of transcription factor networks in the control and EPZ condition. They are not supposed to be the same as the cell states are altered and different TF are expressed and active upon the treatment in the diverse cell types. In a revised manuscript we will justify this point.
Reviewer’s comment: Fig 5D)
- Please explain why binding of EZH2 on the promoter of Asns is strongly reduced in comparison to a mild significant reduction of H3K79me/H3K27me3 in EPZ compared to Control.
Response to Reviewer and planned revision:
Several explanations are possible
First, the variation can be due to batch effects.
Second, the acute reduction of EZH2 might not be directly accompanied by a reduced histone mark, which is reduced either by cell division or by demethylases. The two processes of getting rid of the mark might be slower than the reduction of EZH2 presence at the respective site.
Based on the reviewer’s comment, we will explain this point in the revised manuscript.
- *
Reviewer’s comment:
Also is the changed directly medicated by DOT1L?
Please test whether DOT1L can bind the promoter of Asns.
Response to Reviewer and planned revision:
To address this relevant issue we will proceed with the following protocol:
- electroporate a tagged version of DOT1L into ESCs
- select ESCs and differentiate them into NPC_48h.
- treat NPC with DMSO (Con) or EPZ
- harvest CON and EPZ-treated NPC
- perform ChIP-qPCR DOT1L at the Asns promoter Reviewer’s comment: Please provide the expression patterns of DOT1L and Asns during neuronal differentiation.
Response to Reviewer and planned revision:
As for Dot1l
Dot1l expression was shown in Franz et al 2019, by ISH from E12.5 to E18.5.
As for Asns
We will provide E14.5 in situ staining of Asns in the developing mouse brain using the Gene Paint database (see Figure below).
We will also show immunostainings for ASNS at mid-neurogenesis, provided that Ab against ASNS works in the mouse.
Other General comments:
Reviewer’s comment: Please Indicate VZ, SVZ and CP on the side of the pictures/ with dot lines in the pictures both for primary figures and supplementary.
Response to Reviewer and planned revision:
We will revise the figures accordingly.
Reviewer’s comment: - The Results and figures sometimes do not support the statement made by the authors
Response to Reviewer and planned revision:
We will carefully check on this and eliminate any overinterpretation or non-supported statements from the text.
- Schemes are not informative/explanatory enough, i.e. time windows of treatment and sample collection, culture conditions details.
Response to Reviewer and planned revision:
We will revise the schemes to include more details. In particular, we plan to add a supplementary figure with a detailed visual description of the protocol, to match the detailed description presented in the materials and methods.
Reviewer’s comment: - A more extensive characterization of TTS cells in terms of differentiation progression and integration would be enlightening
Response to Reviewer and planned revision:
In general, we are facing two main challenges while studying the TTS population: one is the lack of a specific marker gene for TTS, the other is the relatively small size of the TTS subpopulation.
For these reasons, our ability to carry on an in-depth analysis of this cell state is limited.
Considering the reviewer’s comment, in the revised manuscript we will expand the analysis ad characterization of the differentiation potential of TTS using RNA velocity trajectory.
We can also expand the discussion on this point.
Reviewer’s comment: - Picture quality can be improved, provide high magnification images.
Response to Reviewer and planned revision:
We will revise the figures to include higher magnification images.
Reviewer #1 (Significance (Required)):
Reviewer’s comment: The study could be important for the specific field in neural development. It aims to understand mutations in respective genes and brain malformation. If the link between epigenetic and metabolic changes is clearly shown, it will be interesting. However, the current manuscript is still rather descriptive, and clear mechanistic insights were not provided. The study have potentials and additional data will strength the value of study.
Response to Reviewer and planned revision:
We will address the direct impact of DOT1L and H3K79me2 on the Asns gene locus during the revision (see the rationale of the experimental strategy also in the revision plan above). We hope we will thus provide a mechanistic link between epigenetics and altered metabolome.
Reviewer #2 (Evidence, reproducibility and clarity (Required)):
Reviewer’s comment: Appiah et al. present a concise manuscript that provides details and possible mechanisms of their previous work (Franz et al., 2019; Ferrari et al., 2020). The study uses diverse lines of investigation to arrive at most conclusions. However, as interesting as the data is, we find that at the present state, it is not sufficient to prove that, indeed, the asparagine metabolism is regulated by DOTL1/PRC2 crosstalk. The neurogenic shift presented in the first part of the paper is not comprehensive and, therefore, not very convincing. The quality of images provided in the main and supplementary data is less than ideal. Additional data analysis and interpretation of the scRNA seq data may be needed. The authors finally conclude with rescue experiments done in culture and in-vivo, which we believe is the stand-out part of this study. Overall the manuscript has some interesting observations that are often over-interpreted with less supporting data. The manuscript reads well but requires additional data and changes in the claims/interpretation to be suited for publication.
Response to Reviewer and planned revision:
In the revised manuscript, we hope we will address the comments and concerns raised by the reviewer in a satisfactory manner. Comments
Reviewer’s comment: 1) Abstract: Is this statement correct: "DOT1L inhibition led to increased neurogenesis driven by a shift from asymmetric self-renewing to symmetric neurogenic divisions of APs. AP undergoes symmetric division for self-renewal and asymmetric neurogenic divisions.
Response to Reviewer and planned revision:
Based on the current literature (cit. Huttner and Kriegstein), AP undergo:
- symmetric division for proliferative division at early stages of neurogenesis
- asymmetric self-renewing division, generating an AP and a BP at mid neurogenesis. This division is also described as neurogenic, as it produces a BP, that is a step further than AP in term of neurogenic potential.
- symmetric consumptive division at late neurogenesis To avoid any possible confusion, we will re-phrase the sentence to include the adjective “consumptive” and specify the composition of the progeny.
In the revised manuscript, the sentence will read as follow:
"DOT1L inhibition led to increased neurogenesis driven by a shift of APs from asymmetric self-renewing (generating one AP and one BP) to symmetric consumptive divisions (generating two neurons)"
Reviewer’s comment: All the data is based on treatments with EPZ (DOTL1 inhibitor), yet no information is shown to support its targeted activity in this system. A proof of principle in the chosen experimental system is missing; for instance, examining the activity or protein level of DOTL1 and decreased methylation of the target(s) is essential.
Response to Reviewer and planned revision:
EPZ is a well characterized drug, that has been used previously in our lab and by others as well.
As for our lab, the information regarding the inhibitor, its activity and efficiency in inhibiting DOT1L towards H3K79me2 was shown in Franz et al. Supplementary Fig. S6 D, E.
In the present manuscript, an additional confirmation that EPZ targets DOT1L in regard to its H3K79me2 activity is shown in Fig. 5D.
We would refer to this information more explicitly in a revised manuscript.
Reviewer’s comment: 2) Figure 1: The scoring of centrosomes and cilia is insufficient to conclude delamination and increase in basal fates. The effect could be on ciliogenesis or centrosome tethering to the apical end-feet of the AP, and other possible explanations for this observation also exist. The images are too small; larger images or graphic representations could be helpful in addition to the data.
Response to Reviewer and planned revision:
We did not intend to claim that the change in centrosome location demonstrate delamination, but only that it suggests delamination. This criterion has been extensively used as a proxy for delamination by several labs working on the cell biology of neurogenesis, such Huttner and Gotz labs. If the issue persists, we can re-phrase in a more cautious way the text referring to Figure 1 to highlight that the data only suggest delamination.
Response to Reviewer and planned revision:
To make a statement regarding delamination, I would like to see either the dynamics of delamination (organotypic slices images), staining with BP markers, or morphological changes of AP (staining that will reveal loss of adherence) or comparable data to support the observation. In my opinion Supp. Figure 1 is insufficient; the single image is not convincing; I would like to see 3D reconstruction and better-quality images.
Response to Reviewer and planned revision:
We can certainly provide better images and co-stain with relevant markers.
We think it is beyond the scope of the manuscript embarking in live imaging as we are not studying the dynamics of delamination per se.
Reviewer’s comment: Tis21 data (1H), again of low quality, is only a single piece of evidence and the conclusion "suggesting that the acquisition of a basal fate was paralleled by a switch to neurogenesis" is premature. I think other cell cycle exit reporters, Fucci markers, pHis, BrdU, NeuroD, or Tbr2 reporters (Li et al., 2020, (Haydar and Sestan labs)) to name a few, are necessary to establish the conclusions. The authors should show other markers such as PAX6, EOMES, or other upper-layer markers upon cell cycle exit in the SVZ/CP. These additional experiments will assist in cell fate analysis.
Response to Reviewer and planned revision:
We completely understand the points raised by the reviewer, and we plan to address them by co-staining with PAX6/SOX2, PH3 and/or EOMES.
We think establishing the Fucci or EOMES mouse system is beyond the scope of the manuscript. In addition, given the present setting of all labs involved, it would be logistically unattainable (see also comments in the section below).
We think the co-staining scheme and plan will be informative enough to satisfactory address the concerns raised by the reviewer.
Reviewer’s comment: 2) Figure 2: The microinjection experiments are elegant; the images, however, do not complement the experiment. The images of the microinjected cells seem not to be reconstructed from z-stacked optical slices, so often, processes are not continuous (panel B, for example); therefore, it is not clear if an apical process is indeed missing or just not seen.
Response to Reviewer and planned revision:
The mentioned images are reconstructed from continuous Z-stacks, as we always do given the type of data. We can provide better reconstructions and/or additional images.
Reviewer’s comment:
The data analysis should include other parameters; BrdU staining could have given information on cell cycle exit, PAX6, SOX2, and EOMES on the location of the cells in the VZ/sVZ. The quality of images showing EOMES and TUBB3 staining is so low that it makes the reader doubt the validity of the quantifications. "Taken together, these data suggest that the inhibition of DOT1L might favor the acquisition of a neuronal over BP cell fate" This interpretation should be subjected to more investigations. It is possible that this treatment just accelerates the AP-> BP -> Neuronal fate. The author's claim needs to be backed by additional experiments or be changed.
Response to Reviewer and planned revision:
To address this point, we will include in the revised manuscript staining and co-staining with PAX6, SOX2 (see also response above) and provide a BrdU labeling experiment.
Reviewer’s comment: 3) Figure 3: The experiment concept and its performance are impressive, yet the data is insufficient. The images in A that are supposed to be representative show two cells; their location is not clear, and the expression of GFP is not clear; in fact, both pairs seem to be GFP negative (not clear what is the threshold for background). Staining with anti-GFP and a second method to follow neurogenesis is necessary.
Response to Reviewer and planned revision:
We did use different staining methods and schemes to follow neurogenesis. As specified above, we will deepen our analysis by using additional markers, such as TBR1.
Reviewer’s comment: 4) On page 9, lines 8-10, the authors claim that their number of cells was "sufficient" for single-cell analysis; the numbers are Response to Reviewer and planned revision:
In the revised manuscript, we will include the analysis of how many cells are needed to identify cluster of 6 cell types in this paradigm, based for example on the algorithms developed in Treppner et al. 2021.
Reviewer’s comment: 5) The authors use Seurat and RaceID without their appropriate citations in the first mention during the results. The authors also stop immediately after DEG analysis along with clustering. The authors could analyze their RNA-seq data with a trajectory; to say the least, the identification/characterization of TTS and neurons as Neurons I, II, and III are insufficient. There could be multiple ways to show the "fate" of cells in the isolated FACS, which the authors have missed.
Response to Reviewer and planned revision:
We will include the respective citations in a revised manuscript. We provide already differentiation trajectories but will include other methods, including scVelo of FateID to extend the trajectory analyses. We kindly ask the reviewer to also refer to the comments above regarding the TTs cluster characterization as part of our effort to provide a better picture of the different clusters.
Reviewer’s comment: 6) The authors detected candidates like Fgfr3, Nr2f1, Ofd1, and Mme as part of their treated (different approaches) datasets (from their DEG analysis). They correctly cite Huang et al., 2020 but fail to give us a sense of the consequences of these gene dysregulations. The authors can also validate if these proteins are expressed in their treated cells.
Response to Reviewer and planned revision:
In the revised manuscript we will comment on the function of the four genes mentioned.
In addition, we will validate the expression of these genes on protein and transcriptional level through immunostainings -provided that antibodies are working in our system- or smFISH, respectively.
Reviewer’s comment: 7) The authors list a few GO terms (page 10, lines 1-10) and associate them with reduced proliferation; they must cite relevant studies. The authors can also add supplementary data showing which genes in their data correspond to these GO terms.
Response to Reviewer and planned revision:
We thank the reviewer for pointing out the missing citations.
We of course agree on the need to add them, and we will do so in the revised manuscript.
Reviewer’s comment: 8) On Page 11, lines 3-7, the authors describe their method to arrive at the 17 targets with TF activity from the previous analysis. Can the authors describe the method used to correlate the two? The reviewer understands this could be MEME analysis or analysis of earlier datasets of Ferrari et al. 2020. But it must be explicitly stated, and a few examples in supplementary need to be exemplified as this analysis is key to discovering the three metabolic genes.
Response to Reviewer and planned revision:
In the revised manuscript, we will clarify the exact analysis that resulted in the identification of the 17 target genes, using the specific tool for gene network analysis, that is based on our scRNA-seq data alone, but not on the Ferrari et al 2020 data set.
3. Description of the revisions that have already been incorporated in the transferred manuscript
n/a
4. Description of analyses that authors prefer not to carry out
Reviewer’s comment: Tis21 data (1H), again of low quality, is only a single piece of evidence and the conclusion "suggesting that the acquisition of a basal fate was paralleled by a switch to neurogenesis" is premature. I think other cell cycle exit reporters, Fucci markers, pHis, BrdU, NeuroD, or Tbr2 reporters (Li et al., 2020, (Haydar and Sestan labs)) to name a few, are necessary to establish the conclusions. The authors should show other markers such as PAX6, EOMES, or other upper-layer markers upon cell cycle exit in the SVZ/CP. These additional experiments will assist in cell fate analysis.
Response to Reviewer and planned revision:
As pointed out above, we think establishing the Fucci or EOMES mice system is beyond the scope of the manuscript as it will not provide more information than the ones we will obtain from systematic and extensive co-staining experiments. In addition, all labs involved are facing a logistic issue (animal house not ready yet, construction works etc) that made the importing and setting up of the colony unattainable for the next 6-10months. If the reviewer and/or the editorial board think this is a major point compromising the entire revision, we kindly ask to contact us again so that we can discuss the issue and arrive to a shared conclusion.
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ljvmiranda921.github.io ljvmiranda921.github.io
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I like to think of thoughts as streaming information, so I don’t need to tag and categorize them as we do with batched data. Instead, using time as an index and sticky notes to mark slices of info solves most of my use cases. Graph notebooks like Obsidian think of information as batched data. So you have a set of notes (samples) that you try to aggregate, categorize, and connect. Sure there’s a use case for that: I can’t imagine a company wiki presented as streaming info! But I don’t think it aids me in how I usually think. When thinking with pen and paper, I prefer managing streamed information first, then converting it into batched information later— a blog post, documentation, etc.
There's an interesting dichotomy between streaming information and batched data here, but it isn't well delineated and doesn't add much to the discussion as a result. Perhaps distilling it down may help? There's a kernel of something useful here, but it isn't immediately apparent.
Relation to stock and flow or the idea of the garden and the stream?
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www.biorxiv.org www.biorxiv.org
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Reply to the reviewers
Reviewer #1 (Evidence, reproducibility and clarity (Required)):
In recent years, the field has investigated crosstalk between cGMP and cAMP signaling (PMID: 29030485), lipid and cGMP signaling (PMID: 30742070), and calcium and cGMP signaling (PMID: 26933036, 26933037). In contrast to the Plasmodium field, which has benefited from proteomic experiments (ex: PMID 24594931, 26149123, 31075098, 30794532), second messenger crosstalk in T. gondii has been probed predominantly through genetic and pharmacological perturbations. The present manuscript compares the features of A23187- and BIPPO-stimulated phosphoproteomes at a snapshot in time. This is similar to a dataset generated by two of the authors in 2014 (PMID: 24945436), except that it now includes one BIPPO timepoint. The sub-minute phosphoproteomic timecourse following A23187 treatment in WT and ∆cdpk3 parasites is novel and would seem like a useful resource.
CDPK3-dependent sites were detected on adenylate cyclase, PI-PLC, guanylate cyclase, PDE1, and DGK1. This motivated study of lipid and cNMP levels following A23187 treatment. The four PDEs determined to have A23187-dependent phosphosites were characterized, including the two PDEs with CDPK3-dependent phosphorylation, which were found to be cGMP-specific. However, cGMP levels do not seem to differ in a CDPK3- or A23187-dependent manner. Instead, cAMP levels are elevated in ∆cdpk3 parasites. This would seem to implicate a feedback loop between CDPK3, the adenylyl cyclase, and PKA/PKG: CDPK3 activity reduces adenylyl cyclase activity, which reduces PKA activity, which increases PKG activity. The authors don't pursue this direction, and instead characterize PDE2, which does not have CDPK3-dependent phosphosites, and seems out of place in the study
Response:
We agree with reviewer 1 that a feedback loop between CDPK3, the adenylyl cyclase and PKA/PKG is certainly one of several possibilities (and we acknowledge this in the manuscript).
We felt, however, that given the observation that A23187 and BIPPO treatment leads to phosphorylation of numerous PDEs (hinting at the presence of an Ca2+-regulated feedback loop), it was entirely relevant to study these in greater detail. Coupled with the A23187 egress assay on ΔPDE2 parasites - our findings suggest that PDE2 plays an important role in this signalling loop (an entirely novel finding). While PDE2 appears to exert its effects in a CDPK3-independent manner (indeed suggesting that CDPK3 might exert its effects on cAMP levels in a different fashion), this does not detract from the important finding that PDE2 is one of the (likely numerous) components that is regulated in a Ca2+-dependent feedback loop to regulate egress.
We have modified our writing to better reflect the fact that our decision to pursue study of the PDEs was not solely CDPK3-centric.
While we feel that our reasoning for studying the PDEs is solid, we appreciate that further clarification on the putative CDPK3-Adenylate cyclase link would make it easier for the reader to follow the rationale.
We have not studied the direct link between CDPK3 and the Adenylate Cyclase β in more detail, as ACβ alone was shown to not play a major role in regulating lytic growth (Jia et al., 2017).
**MAJOR COMMENTS**
1.Some of the key conclusions are not convincing.
The data presented in Figure 6E, F, and G and discussed in lines 647-679 are incongruent. In Figure 6E, the plaques in the PDE2+RAP image are hardly visible; how can it be that the plaques were accurately counted and determined not to differ from vehicle-treated parasites?
Are the images in 6E truly representative? Was the order of PDE1 and PDE2 switched? The cited publication by Moss et al. 2021 (preprint) is not in agreement with this study, as stated. That preprint determined that parasites depleted of PDE2 had significantly reduced plaque number and plaque size (>95% reduction); and parasites depleted of PDE1 had a substantially reduced plaque size but a less substantial reduction in plaque number.
Response:
The plaques for PDE2+RAP were counted using a microscope since they are difficult to see by eye. We thank the reviewer for detecting our incorrect reference to Moss et al. (2021). This has been corrected in the text. We confirm, however, that the images in 6E are representative of what we observed and do indeed differ from what was seen by Moss et al.. We have acknowledged this clearly in the text.
The differences cannot easily be explained other than by the different genetic systems used. Further studies of the individual PDEs will likely illuminate their role in invasion/ growth, but we feel this would be beyond the scope of this study.
Unfortunately, the length of time required for PDE depletion (72h) is incompatible with most T. gondii cellular assays (typically performed within one lytic cycle, 40-48h). Although the authors performed the assays 3 days after initial RAP treatment, is there evidence that non-excised parasites don't grow out of the population. This should be straightforward to test: treat, wait 3 days, infect onto monolayers, wait 24-48h fix, and stain with anti-YFP and an anti-Toxoplasma counterstain. The proportion of the parasite population that had excised the PDE at the time of the cellular assays will then be known, and the reader will have a sense of how complete the observed phenotypes are. As a reader, I will regard the phenotypes with some level of skepticism due to the long depletion time, especially since a panel of PDE rapid knockdown strains (depletion in __Response:
- Cellular assays using KO parasites are commonly performed at the point at which protein depletion is detected. Both our western blots and plaque assay results demonstrate that, at the point of assay, there is no substantial outgrowth of non-excised parasites. The original manuscript also includes PCRs performed at the 72 hr time point (See Fig. 6B) to support this.
- We appreciate the reviewer’s comment re the panel of PDE KD strains. The reviewer notes that there are substantial limitations to conditional KO systems, which similarly applies to KD systems - there are notable pros and cons to each approach. When designing our strategy (pre-publication of the Moss et al., 2022), we made a deliberate decision to use conditional KO strains in light of the fact that residual protein levels in KD systems can cause significant problems, particularly for membrane proteins (all of the investigated PDEs have a transmembrane domain). Tagging of proteins with the degradation domain can have further issues, leading to protein mis-localisation, which we have experienced with several unrelated proteins in the lab.
The authors should qualify some of their claims as preliminary or speculative, or remove them altogether.
The claims in lines 240-260 are confusing. It seems likely that the two drug treatments have at least topological distinctions in the signaling modules, given that cGMP-triggered calcium release is thought to occur at internal stores, whereas A23187-mediated calcium influx likely occurs first at the parasite plasma membrane.The authors' proposed alternative, that treatment-specific phosphosite behavior arises from experimental limitations and "mis-alignment", is unsatisfying for the following reasons: (1) From the outset, the authors chose different time frames to compare the two treatments (15s for BIPPO vs. 50s for A23187); (2) the experiment comprises a single time point, so it does not seem appropriate to compare the kinetics of phosphoregulation. There is still value in pointing out which phosphosites appear treatment-specific under the chosen thresholds, but further claims on the basis of this single-timepoint experiment are too speculative. Lines 264-267 and 281-284 should also be tempered.
Relatedly, graphing of the data in Figure 1G (accompanying the main text mentioned above) was confusing. Why is one axis a ratio, and the other log10 intensity? What does log10 intensity tell you without reference to the DMSO intensity? Wouldn't you want the L2FC(A23187) vs. L2FC(BIPPO) comparisons? Could you use different point colors to highlight these cases on plot 1E? Additionally, could you use a pseudocount to include peptides only identified in one treatment condition on the plot in 1E? (Especially since these sites are mentioned in lines 272-278 but are not on the plot)
Response:
- The kinetics of the responses to A23187 and BIPPO are very different. This is why treatment timings are purposely different as they were selected to align pathways to a point where calcium levels peak just prior to calcium re-uptake. We make no mention of kinetic comparisons, and merely demonstrate that at the chosen timepoints, overall signalling correlation is very high. The observation that most of the sites that behave differently between conditions sit remarkably close to the threshold for differential regulation (in the treatment condition where they are not DR - see Fig. 1G) led us to speculate that many of these sites are likely on the cusp of differential regulation. While it is entirely possible that some of these differences are, in fact, treatment specific (and we clearly acknowledge this in the text), we simply state that we cannot confidently discern clear signalling features that allow us to distinguish between the two treatments. We feel that this is an entirely relevant observation given the observed preponderance of both A23187 and BIPPO-dependent DR phosphosites on proteins in the PKG signalling pathway (as current models place this upstream of Ca2+release).
- Log10 intensity only serves to spread the data for easier visualisation. The only comparison being made relates to the LFCs. Fig. 1Gi shows the LFC scores (x axis) for all sites regulated following A23187 treatment (for which peptides were also identified in BIPPO treatment). On this plot we have highlighted the sites that are differentially regulated following BIPPO but not A23187 treatment (with red showing the DRup and blue showing the DRdown sites). This demonstrates that many of the sites that are regulated following BIPPO but not A23187 treatment cluster close to the threshold for differential regulation in the A23187 dataset - suggesting that many of these sites are likely on the cusp of differential regulation. Fig. 1Gii shows the reverse. While we could highlight the above-mentioned sites on the plot in Fig. 1E, we do not feel that it would demonstrate our point as clearly.
We feel that including a pseudocount on Fig. 1E for peptides lacking quantification in one treatment condition would be visually misleading as the direct correlation being made in Fig. 1E is BIPPO vs A23187 treatment. The sites mentioned in lines 272-278 in the original manuscript (now lines 268-276) are available in the supplement tables.
3.Additional experiments would be essential to support the main claims of the paper.
Genetic validation is necessary for the experiments performed with the PKA inhibitor H89. H89 is nonspecific even in mammalian systems (PMID: 18523239) and in this manuscript it was used at a high concentration (50 µM) The heterodimeric architecture of PKA in apicomplexans dramatically differs from the heterotetrameric enzymes characterized in metazoans (PMID: 29263246), so we don't know what the IC50 of the inhibitor is, or whether it inhibits competitively. Two inducible knockdown strains exist for PKA C1 (PMID: 29030485, 30208022). The authors could request one of these strains and construct a ∆cdpk3 in that genetic background, as was done for the PDE2 cKO strain. Estimated time: 3-4 weeks to generate strain, 2 weeks to repeat assays.
Response:
- While we appreciate that H89 is not 100% specific for PKA, this is not our only line of evidence that cAMP levels are altered. We demonstrate that cAMP levels are elevated in CDPK3 KO parasites – further substantiating our finding.
The H89 concentration used in our experiment is in keeping with/lower than the concentrations used in other Toxoplasma publications (Jia et al., 2017), and both the Toxoplasma and Plasmodium fields have shown convincingly that H89 treatment phenocopies cKD/cKO of PKA (see Jia et al., 2017; Flueck et al., 2019).
While we agree that the genetic validation suggested by reviewer 1 would serve to further support our findings (though it would not provide further novel insights), the suggested time frame for experimental execution was not realistic. Line shipment, strain generation, subcloning and genetic validation would take substantially longer than 3-4 weeks.
cGMP levels are found to not increase with A23187 treatment, which is at odds with a previous study (lines 524-560). The text proposes that the differences could arise from the choice of buffer: this study used an intracellular-like Endo buffer (no added calcium, high potassium), whereas Stewart et al. 2017 used an extracellular-like buffer (DMEM, which also contains mM calcium and low potassium). An alternative explanation is that 60 s of A23187 treatment does not achieve a comparable amount of calcium flux as 15 s of BIPPO treatment, and a calcium-dependent effect on cGMP levels, were it to exist, could not be observed at the final timepoint in the assay. The experiments used to determine the kinetics of calcium flux following BIPPO and A23187 treatments (Fig. 1B, C) were calibrated using Ringer's buffer, which is more similar to an extracellular buffer (mM calcium, low potassium). In this buffer, A23187 treatment would likely stimulate calcium entry from across the parasite plasma membrane, as well as across the membranes of parasite intracellular calcium stores. By contrast, A23187 treatment in Endo buffer (low calcium) would likely only stimulate calcium release from intracellular stores, not calcium entry, since the calcium concentration outside of the parasite is low. Because calcium entry no longer contributes to calcium flux arising from A23187 treatment, it is possible that the calcium fluxes of A23187-treated parasites at 60 s are "behind" BIPPO-treated parasites at 15 s. The researchers could control these experiments by *either* (i) performing the cNMP measurements on parasites resuspended in the same buffer used in Figure 1B, C (Ringer's) or (ii) measuring calcium flux of extracellular parasites in Endo buffer with BIPPO and A23187 to determine the "alignment" of calcium levels, as was done with intracellular parasites in Figure 1C. No new strains would have to be generated and the assays have already been established in the manuscript. Estimated time to perform control experiments with replicates: 2 weeks. This seems like an important control, because the interpretation of this experiment shifts the focus of the paper from feedback between calcium and cGMP signaling, which had motivated the initial phosphoproteomics comparisons, to calcium and cAMP signaling. Further, the lipidomics experiments were performed in an extracellular-like buffer, DMEM, so it's unclear why dramatically different buffers were used for the lipidomics and cNMP measurements.
Response:
While the initial calibration experiments to measure calcium flux were indeed performed in Ringer’s buffer, the parasites were intracellular. We therefore chose to measure cNMP concentrations of extracellular parasites syringe lysed in Endo buffer, which is better at mimicking intracellular conditions than any other described buffer.
As the reviewer suggested, we measured the calcium flux of extracellular parasites in Endo buffer upon stimulation with either A23187 or BIPPO.
We found that peak calcium response to BIPPO in Endo buffer was similar to that of intracellular parasites (~15 seconds post treatment) (See Supp Fig. 6A). Upon treatment with A23187, extracellular parasites in Endo buffer had a much faster response compared to their intracellular counterparts, with peak flux measured at ~25 seconds post treatment (see Supp Fig. 6B). This indeed does suggest that extracellular parasites in Endo buffer behave differently to A23187 compared to their intracellular counterparts. However, peak calcium response is still occuring within the experimental time course and is not being missed, as the reviewer worries. Moreover, since we are able to detect increased cAMP levels in A23187 treated parasites, Ca2+ flux appears sufficient to alter cNMP signalling.
We did notice however that the intensity of the calcium flux was much weaker in Endo buffer compared to intracellular parasites (see Supp Fig. 6B). We found that this was due to the lack of host-derived Ca2+, since supplementation of Endo buffer with 1 uM CaCl2 restored the intensity of the calcium response to match that of intracellular parasites (see Supp Fig. 6C). We therefore decided to repeat our cGMP measurements, this time using extracellular parasites in Endo buffer supplemented with 1 uM CaCl2. However, we found no differences in cGMP levels in the response to ionophore under these conditions (now Supp Fig. 6D) compared to the previous experiments, so the conclusions from the previous data do not change.
As for the lipidomics experiments, we chose to use DMEM so that our dataset could be compared with other published lipidomic datasets (Katris et al., 2020; Dass et al., 2021) where DMEM was also used as a buffer when measuring global lipid profiles of parasites.
We now acknowledge in the paper that Endo buffer has its shortcomings, and that this could be the reason why we do not detect changes in cGMP concentrations. We do, however, believe that Endo buffer is the best alternative to intracellular parasites and is supported by its consistent use in numerous publications studying Toxoplasma signalling (McCoy et al., 2012; Stewart et al., 2017).
Additional information is required to support the claim that PDE2 has a moderate egress defect (lines 681-687). T. gondii egress is MOI-dependent (PMID: 29030485). Although the parasite strains were used at the same MOI, there is no guarantee that the parasites successfully invaded and replicated. If parasites lacking PDE2 are defective in invasion or replication, the MOI is effectively decreased, which could explain the egress delay. Could the authors compare the MOIs (number of vacuoles per host cell nuclei) of the vehicle and RAP-treated parasites at t = 0 treatment duration to give the reader a sense of whether the MOIs are comparable?
Response:
Since PDE2 KO parasites have a substantial growth defect, we did notice that starting MOIs were consistently lower for the RAP-treated samples compared to the DMSO-treated samples. However, this was also the case for PDE1 KO parasites where we did not see an egress delay. We also found that the egress delay was still evident for ∆CDPK3 parasites, despite having higher starting MOIs than WT parasites in our experiments. Therefore there does not appear to be a link between starting MOIs and the egress delay.
To be sure of our results, we also performed egress assays where we co-infected HFFs with mCherry-expressing WT parasites (WT ∆UPRT) and GFP-expressing PDE2 cKO parasites that were treated with either DMSO or RAP or ∆CDPK3 parasites. This recapitulated our previous findings, confirming the deletion of PDE2 leads to delay in A23187-mediated egress.
4.A few references are missing to ensure reproducibility.
The manuscript states that the kinetic lipidomics experiments were performed with established methods, but the cited publication (line 497) is a preprint. These are therefore not peer reviewed and should be described in greater detail in this manuscript, including any relevant validation.
Response:
We thank the reviewer for pointing this out. We have included a greater description of the methods used in the materials and methods section such that the experiment is reproducible, as per the reviewer’s suggestion. We decided to still make mention of the BioRxiv preprint since we thought it was appropriate for the reader to be informed of ongoing developments in the field.
Please cite the release of the T. gondii proteomes used for spectrum matching (lines 972-973).
Response:
We have included this as per the reviewer’s suggestion.
Please include the TMT labeling scheme so the analysis may be reproduced from the raw files.
Response:
We have included this as per the reviewer’s suggestion in Supp Fig. 3A.
5.Statistical analyses should be reviewed as follows:
Have the authors examined the possibility that some changes in phosphopeptide abundance reflect changes in protein abundance? This may be particularly relevant for comparisons involving the ∆cdpk3 strain. Did the authors collect paired unenriched proteomes from the experiments performed? Alternatively, there may be enriched peptides that did not change in abundance for many of the proteins that appear dynamically phosphorylated.
Response:
We did not collect unenriched proteomes from the experiments performed (although we did perform unenriched mixing checks to ensure equal loading between samples), and believe that this wasn’t a necessity for the following reasons:
- For within-line treatment analyses, treatment timings are so short (a maximum of 15-50s in the single timepoint experiment) that it would be unlikely to detect substantial changes in protein abundance. Moreover, these unlikely events would affect all phosphosites across a protein, and therefore be detectable.
In our CDPK3 dependency timecourse experiments, we normalise both the WT and ∆CDPK3 strain to 0s, and measure signalling progression over time. Therefore, any difference at timepoints that are not “0” are not originating from basal differences. We also see a consistent increase/decrease in phosphosite detection across the sub-minute timecourse, further confirming that the observed changes are truly down to dynamic changes in phosphorylation and not protein levels.
In the single timepoint CDPK3 dependency analyses (44 regulated sites identified, Data S2), we acknowledge that there could be some risk of altered starting protein abundance between lines. However, if protein abundance were responsible for the changes in phosphosite detection, we would expect all phosphosites across the protein to shift, and we do not observe this. Moreover, when we look at these CDPK3 dependent proteins and compare their phosphosite abundance in untreated WT and ∆CDPK3 lines, we find that for each protein, either all or the majority of phosphosites detected are unchanged (highlighting that there is no substantial difference in this protein’s abundance between lines). Where there are phosphosite differences between lines, these are only ever on single sites on a protein while most other sites are unchanged - implying that these are changes to basal phosphorylation states and not protein levels.
It seems like for Figs. 3B and S5 the maximum number of clusters modeled was selected. Could the authors provide a rationale for the number of clusters selected, since it appears many of the clusters have similar profiles.
The number of clusters is chosen automatically by the Mclust algorithm as the value that maximizes the Bayes Information Criterion (BIC). BIC in effect balances gains in model fit (increasing log-likelihood) against increasing the number of parameters (i.e. number of clusters).
Please include figure panel(s) relating to gene ontology. Relevant information for readers to make conclusions includes p-value, fold-enrichment or gene ratio, and some sort of metric of the frequency of the GO term in the surveyed data set. See PMID: 33053376 Fig. 7 and PMID: 29724925 Fig. 6 for examples or enrichment summaries. Additionally, in the methods, specify (i) the background set, (ii) the method used for multiple test correction, (iii) the criteria constituting "enrichment", (iv) how the T. gondii genome was integrated into the analysis, (v) the class of GO terms (molecular function, biological process, or cellular component), (vi) any additional information required to reproduce the results (for example, settings modified from default).
Response:
We have included the additional information requested in the materials and methods.
We purposely did not include GO figure panels as our analyses are being done across many clusters, making it very difficult to display this information cohesively. We have included all data in Tables S2-S5. These tables included all the relevant information on p-value, enrichment status, ratio in study/ratio in population, class of GO terms etc.
The presentation of the lipidomics experiments in Figure 4A-C is confusing. First, the ∆cdpk3/WT ratio removes information about the process in WT parasites, and it's unclear why the scale centers on 100 and not 1. Second, the data in Figure S6 suggests a more modest effect than that represented in Fig. 4; is this due to day to day variability? How do the authors justify pairing WT and mutant samples as they did to generate the ratios?
Response:
This is a common strategy used by many metabolomics experts (Bailey et al., 2015; Dass et al., 2021; Lunghi et al., 2022). We had originally chosen to represent the data as a ratio since this form of representation helps get rid of the variability that arises between experiments and allows us to see very clear patterns which would otherwise go unnoticed. This variability arises from the amount of lipids in each sample which varies between parasites in a dish, the batch of FBS and DMEM used, and the solutions and even room temperature used to extract lipids on a given day.
However, we agree with the reviewer that depicting the data in Figure 4A-C as a ratio of ∆CDPK3/WT parasites can be confusing, so we have now changed the graphs, plotting WT and ∆CDPK3 levels instead, and have moved the ratio of ∆CDPK3/WT to the Supplementary Figure 5.
The significance test seems to be performed on the difference between the WT and ∆cdpk3 strains, but not relative to the DMSO treatment? Wouldn't you want to perform a repeated measures ANOVA to determine (i) if lipid levels change over time and (ii) if this trend differs in WT vs. mutant strain?
Response:
The reviewer correctly points out that ANOVA is often used for time courses, but we must point out that it is not always strictly appropriate since it can overlook the purpose of the individual experiment design, which in this case is, 1) to investigate the role of CDPK3 compared to the WT parental strain, and 2) specifically to find the exact point at which the DAG begins to change after stimulus to match the proteomics time course.
Our data is clearly biassed towards earlier time points where we have 0, 5, 10, 30, 45 seconds where DAG levels are mostly unchanged compared to the single timepoint 60 seconds which shows a significant difference in DAG using our method of statistical comparison by paired two tailed t-test. Therefore, it would be unwise to use ANOVA when we really want to see when the A23187 stimulus takes effect, which appears to be after the 45 second mark. Therefore, analysing the data by ANOVA would likely provide a false negative result, where the result is non-significant but there is clearly more DAG in WT than CDPK3 after 60 seconds. T-tests are commonly used when comparing the same cell lines grown in the same conditions with a test/treatment, and in this case the test/treatment is CPDK3 present or absent (Lentini et al., 2020).
In the main text, it would be preferable to see the data presented as the proteomics experiments were in Figure 4B and 4C, with fold changes relative to the DMSO (t = 0) treatment, separately for WT and ∆cdpk3 parasites.
Response:
We have now changed the way that we represent the data, plotting %mol instead of the ratio.
Signaling lipids constitute small percentages of the overall pool (e.g. PMID: 26962945), so one might not necessarily expect to observe large changes in lipid abundance when signaling pathways are modulated. Is there any positive control that the authors could include to give readers a sense of the dynamic range? Maybe the DGK1 mutant (PMID: 26962945)?
Response:
DGK1 is maybe not a good example because the DGK1 KO parasites effectively “melt” from a lack of plasma membrane integrity ((Bullen et al., 2016), so this would likely be technically challenging. We don’t see the added value in including an additional mutant control since we can already see the dynamic change over time from no difference (0 seconds) to significant difference (60 seconds) between WT and CDPK3 for DAG and most other lipids. We already see a significant difference between WT and CDPK3 after 60 seconds for DAG, and we can clearly see in sub-minute timecourses the changes or not at the specific points where the A23187 is added (0-5 seconds), the parasites acclimatise, for the A23187 to take effect (10-30 seconds) and for the parasite lipid response to be visible by lipidomics (45-60 +seconds).
Figure 4E: are the differences in [cAMP] with DMSO treatment and A23187 treatment different at any of the timepoints in the WT strain? The comparison seems to be WT/∆cdpk3 at each timepoint. Does the text (lines 562-568) need to be modified accordingly?
Response:
In WT (and ∆CDPK3) parasites, [cAMP] is significantly changed at 5s of A23187 treatment (relative to DMSO). We have modified our figures to include this analysis. The existing text accurately reflects this.
Figure 6I: is the difference between PDE2 cKO/∆cdpk3 + DMSO or RAP significant?
Response
In our original manuscript, there was no statistical difference in [cAMP] between PDE2cKO/∆CDPK3+DMSO and PDE2cKO/∆CDPK3+DMSO+RAP, likely due to the variation between biological replicates. To overcome the issues in variability between replicates, we have now included more biological replicates (n=7). This has led to a significant difference in [cAMP] between PDE2cKO/∆CDPK3 DMSO- and RAP-treated parasites and between PDE2cKO DMSO- and RAP-treated parasites (now Fig. 6I).
**MINOR COMMENTS**
1.The following references should be added or amended:
Lines 83-85: in the cited publication, relative phosphopeptide abundances of an overexpressed dominant-negative, constitutively inactive PKA mutant were compared to an overexpressed wild-type mutant. In this experimental setup, one would hypothesize that targets of PKA should be down-regulated (inactive/WT ratios). However, the mentioned phosphopeptide of PDE2 was found to be up-regulated, suggesting that it is not a direct target of PKA.
Response:
We thank the reviewer for spotting this error, we have now modified our wording.
Cite TGGT1_305050, referenced as calmodulin in line 458, as TgELC2 (PMID: 26374117).
Response:
We have included this as per the reviewer’s suggestion.
Cite TGGT1_295850 as apical annuli protein 2 (AAP2, PMID: 31470470).
Response:
We have included this as per the reviewer’s suggestion.
Cite TGGT1_270865 (adenylyl cyclase beta, Acβ) as PMID: 29030485, 30449726.
Response:
We have included this as per the reviewer’s suggestion.
Cite TGGT1_254370 (guanylyl cyclase, GC) as PMID: 30449726, 30742070.
Response:
We have included this as per the reviewer’s suggestion.
Note that Lourido, Tang and David Sibley, 2012 observed that treatment with zaprinast (a PDE inhibitor) could overcome CDPK3 inhibition. The target(s) of zaprinast have not been determined and may differ from those of BIPPO (in identity and IC50). The cited study also used modified CDPK3 and CDPK1 alleles, rather than ∆cdpk3 and intact cdpk1 as used in this manuscript. That is to say, the signaling backgrounds of the parasite strains deviate in ways that are not controlled.
Response:
While it is true that zaprinast targets have not been unequivocally identified, zaprinast-induced egress is widely thought to be the result of PKG activation, a conclusion that is further supported by the finding that Compound 1 completely blocks zaprinast-induced egress (Lourido, Tang and David Sibley, 2012). Similarly, BIPPO-induced egress is inhibited by chemical inhibition of PKG by Compound 1 and Compound 2 (Jia et al., 2017). Moreover, like zaprinast, BIPPO has been clearly shown to partially overcome the ∆CDPK3 egress delay (Stewart et al., 2017).
2.The following comments refer to the figures and legends:
Part of the legend text for 1G is included under 1H.
Response:
This has been corrected
Figure 1H: The legend mentions that some dots are blue, but they appear green. Please ensure that color choices conform to journal accessibility guidelines. See the following article about visualization for colorblind readers: https://www.ascb.org/science-news/how-to-make-scientific-figures-accessible-to-readers-with-color-blindness____/ . Avoid using red and green false-colored images; replace red with a magenta lookup table. Multi-colored images are only helpful for the merged image; otherwise, we discern grayscale better. Applies to Figures 1B, 5C, 6D. (Aside: anti-CAP seems an odd choice of counterstain; the variation in the staining, esp. at the apical cap, is distracting.)
Response:
We thank reviewer #1 for bringing this to our attention, and have modified our colour usage for all IFAs and Figures 1H and 3E.
We chose CAP staining as the antibody is available in the laboratory and stains both the apical end (which has been shown to contain several proteins important for signalling as well as PDE9) and the parasite periphery, the location of CDPK3.
Figure 1B: When showing a single fluorophore, please use grayscale and include an intensity scale bar, since relative values are being compared.
Response:
We have modified this as per the reviewer’s suggestion
Figure 1C: it is difficult to compare the kinetics of the calcium response when the curves are plotted separately. Since the scales are the same, could the two treatments be plotted on the same axes, with different colors? Additionally, according to the legend, a red line seems to be missing in this panel.
Response:
Fig1C is not intended to compare kinetics, merely to show peak calcium release in each separate treatment condition. We have removed mention of a red line in the figure legend.
Figure 2A: Either Figure S4 can be moved to accompany Figure 2A, or Figure 2A could be moved to the supplemental.
Figure S4 has now been incorporated into Figure 2.
Reviewer #1 (Significance (Required)):
This manuscript would interest researchers studying signaling pathways in protozoan parasites, especially apicomplexans, as CDPK3 and PKG orthologs exist across the phylum. To my knowledge, it is the first study that has proposed a mechanism by which a calcium effector regulates cAMP levels in T. gondii. Unfortunately, the experiments fall short of testing this mechanism.
Response:
We thank reviewer #1 for their comments, but disagree with their assessment that the key points of the manuscript “fall short of experimental testing”.
- We demonstrate that, following both BIPPO and A23187 treatment, there is differential phosphorylation of numerous components traditionally believed to sit upstream of PKG activation (as well as several components within the PKG signalling pathway itself).
- We show that some of these sites are CDPK3 dependent, and that deletion of CDPK3 leads to changes in lipid signalling and an elevation in levels of cAMP (dysregulation of which is known to alter PKG signalling).
- We show that pre-treatment with a PKA inhibitor is able to largely rescue this phenotype.
- We demonstrate that a cAMP-specific PDE is phosphorylated following A23187 treatment (i.e. Ca2+ flux)
- We show that this cAMP specific PDE plays a role in A23187-mediated egress.
- While the latter PDE may not be directly regulated by CDPK3, these findings suggest that there are likely several Ca2+-dependent kinases that contribute to this feedback loop.
Reviewer #2 (Evidence, reproducibility and clarity (Required)):
**Summary:**
Provide a short summary of the findings and key conclusions (including methodology and model system(s) where appropriate).
In this manuscript, Dominicus et al investigate the elusive role of calcium-dependent kinase 3 during the egress of Toxoplasma gondii. Multiple functions have already been proposed for this kinase by this group including the regulation of basal calcium levels (24945436) or of a tyrosine transporter (30402958). However, one of the most puzzling phenotypes of CDPK3 deficient tachyzoites is a marked delay in egress when parasites are stimulated with a calcium ionophore that is rescued with phosphodiesterase (PDE) inhibitors. Crosstalk between, cAMP, cGMP, lipid and calcium signalling has been previously described to be important in regulating egress (26933036, 23149386, 29030485) but the role of CDPK3 in Toxoplasma is still poorly understood.
Here the authors first take an elegant phosphoproteomic approach to identify pathways differentially regulated upon treatment with either a PDE inhibitor (BIPPO) and a calcium ionophore (A23187) in WT and CDPK3-KO parasites. Not much difference is observed between BIPPO or A23187 stimulation which is interpreted by the authors as a regulation through a feed-back loop.
The authors then investigate the effect of CDPK3 deletion on lipid, cGMP and cAMP levels. The identify major changes in DAG, phospholipid, FFAs, and TAG levels as well as differences in cAMP levels but not for cGMP. Chemical inhibition of PKA leads to a similar egress timing in CDPK3-KO and WT parasites upon A23187 stimulation.
As four PDEs appeared differentially regulated in the CDPK3-KO line upon A23187, the authors investigate the requirement of the 4 PDEs in cAMP levels. They show diverse localisation of the PDEs with specificities of PDE1, 7 and 9 for cGMP and of PDE2 for cAMP. They further show that PDE1, 7 and 9 are sensitive to BIPPO. Finally, using a conditional deletion system, they show that PDE1 and 2 are important for the lytic cycle of Toxoplasma and that PDE2 shows a slightly delayed egress following A23187 stimulation.
**Major comments:**
-Are the key conclusions convincing?
The title is supported by the findings presented in this study. However I am not sure to understand why the authors imply a positive feed back loop. This should be clarified in the discussion of the results.
Response:
We believe in a positive feedback loop as, upon A23187 treatment (resulting in a calcium flux), ΔCDPK3 parasites are able to egress, albeit in a delayed manner. This egress delay is substantially, but not completely, alleviated upon treatment with BIPPO (a PDE inhibitor known to activate the PKG signalling pathway). In conjunction with our phosphoproteomic data (where we see phosphorylation of numerous pathway components upstream of PKG upon BIPPO and A23187 treatment - both in a CDPK3 dependent and independent manner), these observations suggest that calcium-regulated proteins (CDPK3 among them) feed into the PKG pathway. As deletion of CDPK3 delays egress, it is reasonable to postulate that this feedback is one that amplifies egress signalling (i.e. is positive).
The phosphoproteome analysis seems very strong and will be of interest for many groups working on egress. However, the key conclusion, i.e. that a substrate overlaps between PKG and CDPK3 is unlikely to explain the CDPK3 phenotype, seems premature to me in the absence of robustly identified substrates for both kinases.
Response:
We certainly do not fully exclude the possibility of a substrate overlap but do lean more heavily towards a feedback loop given (a) the inability to clearly detect treatment-specific signalling profiles and (b) the phospho targets observed in the A23187 and BIPPO phosphoproteomes. We have further clarified our reasoning, and overall tempered our language in the manuscript as per the reviewer’s suggestion.
I am not sure there is a clear key conclusion from the lipidomic analysis and how it is used by the authors to build their model up. Major changes are observed but how could this be linked with CDPK3, particularly if cGMP levels are not affected?
Response:
Our phosphoproteomic analyses identify several CDPK3-dependent phospho sites on phospholipid signalling components (DGK1 & PI-PLC), suggesting that there is indeed altered signalling downstream of PKG. To test whether these lead to a measurable phenotype, we performed the lipidomics analysis. We did not pursue this arm of the signalling pathway any further as we postulated that the changes in the lipid signalling pathway were less likely to play a role in the feedback loop. Nevertheless, we felt that it was worthwhile to include these findings in our manuscript as they support the conclusions drawn from the phosphoproteomics - namely that lipid signalling is perturbed in CDPK3 mutants. We, or others, may follow up on this in future.
We agree with the reviewer that it is surprising that cGMP levels remain unchanged in our experiments when we treat with A23187. Given the measurable difference in cAMP levels between WT and ΔCDPK3 parasites, we postulate that CDPK3 directly or indirectly downregulates levels of cAMP. This would, in turn, alter activity of the cAMP-dependent protein kinase PKAc. Jia et al. (2017) have shown a clear dependency on PKG for parasites to egress upon PKAc depletion, but were also unable to reliably demonstrate cGMP accumulation in intracellular parasites. Similarly, their hypothesis that dysregulated cGMP-specific PDE activity results in altered cGMP levels has not been proven (the PDE hypothesised to be involved has since been shown to be cAMP-specific).
While it is possible that our collective inability to observe elevated cGMP levels is explained by the sensitivity limits of the assay, it is similarly possible that cAMP-mediated signalling is exerting its effects on the PKG signalling pathway in a cGMP-independent manner.
The evidence that CDPK3 is involved in cAMP homeostasis seems strong. However, the analysis of PKA inhibition is a bit less clear. The way the data is presented makes it difficult to see whether the treatment is accelerating egress of CDPK3-KO parasites or affecting both WT and CDPK3-KO lines, including both the speed and extent of egress. This is important for the interpretation of the experiment.
Response:
Fig. 4F shows that there is a significant amount of premature egress in both WT and ∆CDPK3 parasites following 2 hrs of H89 pre-treatment (consistent with previous reports that downregulation of cAMP signalling stimulates premature egress). When we subsequently investigated A23187-induced egress rates of the remaining intracellular H89 pre-treated parasites (Fig. 4Gi-ii) we found that the ∆CDPK3 egress delay was largely rescued. We have moved Fig. 4F to the supplement (now Supp Fig. 5E) in order to avoid confusion between the distinct analyses shown in 4F (pre-treatment analyses) and 4G (egress experiment). These experiments provided a hint that cAMP signalling is affected, which we then validate by measuring elevated cAMP levels in CDPK3 mutant parasites.
The biochemical characterisation of the four PDE is interesting and seems well performed. However, PDE1 was previously shown to hydrolyse both cAMP and cGMP (____https://doi.org/10.1101/2021.09.21.461320____) which raises some questions about the experimental set up. Could the authors possibly discuss why they do not observe similar selectivity? Could other PDEs in the immunoprecipitate mask PDE activity? In line with this question, it is not clear what % of "hydrolytic activity (%)" means and how it was calculated.
The experiments describing the selectivity of BIPPO for PDE1, 7 and 9 as well as the biological requirement of the four tested PDEs are convincing.
Response:
We believe that the disagreement between our findings and those published by Moss and colleagues are due to the differences in experimental conditions. We performed our assays at room temperature for 1 hour with higher starting cAMP concentrations (1 uM) compared to them. They performed their assays at 37ºC for 2 hours with 10-fold lower starting cAMP concentrations (0.1 uM). We have now repeated this set of experiments using the Moss et al. conditions, and find that PDEs 1, 7 and 9 can be dual specific, while PDE2 is cAMP-specific, thereby recapitulating their findings (Now included in the revised manuscript under Supp Fig. 7B). However, we also now performed a timecourse PDE assay using our original conditions and show that the cAMP hydrolytic activity for PDE1 can only be detected following 4 hours of incubation, compared to cGMP activity that can be detected as early as 30 minutes, suggesting that it possesses predominantly cGMP activity (See Supp Fig. 7C). We therefore believe that our experimental setup is more stringent, because if one starts with a lower level of substrate and incubates for longer and at a higher temperature, even minor dual activity could make a substantial difference in cAMP levels. Our data suggests that the cAMP hydrolytic activity of PDEs 1, 7 and 9 is substantially lower than the cGMP hydrolytic activity that they display.
We have also included a clear description of how % hydrolytic activity was calculated in the methods section.
-Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether?
The claim that CDPK3 affects cAMP levels seems strong however the exact links between CDPK3 activity, lipid, cGMP and cAMP signalling remain unclear and it may be important to clearly state this.
Response:
We have modified our wording in the text to more clearly describe our current hypothesis and reasoning.
-Would additional experiments be essential to support the claims of the paper? Request additional experiments only where necessary for the paper as it is, and do not ask authors to open new lines of experimentation.
I think that the manuscript contains a significant amount of experiments that are of interest to scientists working on Toxoplasma egress. Requesting experiments to identify the functional link between above-mentioned pathways would be out of the scope for this work although it would considerably increase the impact of this manuscript. For example, would it be possible to test whether the CDPK3-KO line is more or less sensitive to PKG specific inhibition upon A23187 induced?
-Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated cost and time investment for substantial experiments.
The above-mentioned experiment is not trivial as no specific inhibitors of PKG are available. Ensuring for specificity of the investigated phenotype would require the generation of a resistant line which would require significant work.
__Response: __We agree that this would be an interesting experiment to further substantiate our findings. As indicated by the reviewer, however, the lack of specific inhibitors of PKG means a resistant line would likely be required to ensure specificity.
-Are the data and the methods presented in such a way that they can be reproduced?
It is not clear how the % of hydrolytic activity of the PDE has been calculated.
Response: We have included a clearer description of how % hydrolytic activity was calculated in the methods section.
-Are the experiments adequately replicated and statistical analysis adequate?
This seems to be performed to high standards.
**Minor comments:**
-Specific experimental issues that are easily addressable.
I do not have any comments related to minor experimental issues.
-Are prior studies referenced appropriately?
Most of the studies relevant for this work are cited. It is however not clear to me why some important players of the "PKG pathway" are not indicated in Fig 1H and Fig 3E, including for example UGO or SPARK.
Response:
We have modified Fig 1H and 3E to include all key players involved in the PKG pathway.
-Are the text and figures clear and accurate?
While all the data shown here is impressive and well analysed, I find it difficult to read the manuscript and establish links between sections of the papers. The phosphoproteome analysis is interesting and is used to orientate the reader towards a feedback mechanism rather than a substrate overlap. But why do the authors later focus on PDEs and not on AC or CNBD, as in the end, if I understand well, there is no evidence showing a link between CDPK3-dependent phosphorylation and PDE activity upon A23187 stimulation?
Response:
We thank reviewer#2 and appreciate their constructive feedback re the flow of the manuscript.
Our key findings from the phosphoproteomics study were that 1) BIPPO and A23187 treatment trigger near identical signalling pathways, 2) that both A23187 and BIPPO treatment leads to phosphorylation of numerous components both upstream and downstream of PKG signalling (hinting at the presence of an Ca2+-regulated feedback loop) and 3) several of the abovementioned components are phosphorylated in a CDPK3 dependent manner.
While several avenues of study could have been pursued from this point onwards, we chose to focus on the feedback loop in a broader sense as its existence has important implications for our general understanding of the signalling pathways that govern egress.
We reasoned that, given the differential phosphorylation of 4 PDEs following A23187 and BIPPO treatment (none of which had been studied in detail previously), it was relevant to study these in greater detail.
Coupled with the A23187 egress assay on PDE2 knockout parasites - our findings suggest that PDE2 plays a role in the abovementioned Ca2+ signalling loop. While PDE2 may not exert its effects in a CDPK3-dependent manner (and CDPK3 may, therefore, alter cAMP levels in a different fashion), this does not detract from the important finding that PDE2 is one of the (likely numerous) components that is regulated in a Ca2+-dependent feedback loop to facilitate rapid egress.
We have modified our wording to better reflect our rationale for studying the PDEs irrespective of their CDPK3 phosphorylation status.
While we feel that our reasoning for studying the PDEs is solid, we do appreciate that further clarification on the putative CDPK3-Adenylate cyclase link would elevate the manuscript substantially. However, given the data that the ACb is not playing a sole role in the control of egress, this is likely a non-trivial task and requires substantial work.
It is also unclear how the authors link CDPK3-dependent elevated cAMP levels with the elevated basal calcium levels they previously described. This is particularly difficult to reconcile particularly in a PKG independent manner.
Response:
We previously postulated that elevated Ca2+ levels allowed ΔCDPK3 mutants to overcome a complete egress defect, potentially by activating other CDPKs (e.g. CDPK1). It is similarly plausible that elevated Ca2+ levels in ΔCDPK3 parasites may lead to elevated cAMP levels in order to prevent premature egress.
As noted in our previous responses, we acknowledge that our inability to detect cGMP is surprising. However, given the clarity of our cAMP findings, and the phosphoproteomic evidence to suggest that various components in the PKG signalling pathway are affected, we postulate that we are either unable to reliably detect cGMP due to sensitivity issues, or that cAMP is exerting its regulation on the PKG pathway in a cGMP-independent manner. As noted previously, while the link between cAMP and PKG signalling has been demonstrated by Jia et al., it is not entirely clear how this is mediated.
The presentation of the lipidomic analysis is also not really clear to me. Why do the authors show the global changes in phospholipids and not a more detailed analysis?
Response:
We performed a detailed phospholipid profile of WT and ∆CDPK3 parasites under normal culture conditions. However, due to the sheer quantity of parasites required for this detailed analysis, we were unable to measure individual phospholipid species in our A23187 timecourse. We therefore opted to measure global changes following A23187 stimulation.
As the authors focus on the PI-PLC pathway, could they detail the dynamics of phosphoinositides? I understand that lipid levels are affected in the mutant but I am not sure to understand how the authors interpret these massive changes in relationship with the function of CDPK3 and the observed phenotypes.
Response:
Our phosphoproteomic analyses identified several CDPK3-dependent phospho sites on phospholipid signalling components (DGK1 & PI-PLC), suggesting that (in keeping with all of our other data), there is altered signalling downstream of PKG. To test whether these changes lead to a measurable phenotype, we performed the lipidomics analysis. Following stimulation with A23187, we found a delayed production of DAG in ∆CDPK3 parasites compared to WT parasites. Since DAG is required for the production of PA, which in turn is required for microneme secretion, our finding can explain why microneme secretion is delayed in ∆CDPK3 parasites, as previously reported (Lourido, Tang and David Sibley, 2012; McCoy et al., 2012).
We did not follow this arm of the signalling pathway any further as we postulated that the changes in the lipid signalling pathway were less likely to play a role in the feedback loop. Nevertheless, we felt that it was worthwhile to include these findings in our manuscript as they support the conclusions drawn from the phosphoproteomics - namely that lipid signalling is perturbed in CDPK3 mutants. We, or others, may follow up on this in future.
Finally, the characterisation of the PDEs is an impressive piece of work but the functional link with CDPK3 is relatively unclear. It would also be important to clearly discuss the differences with previous results presented in this this preprint: https://doi.org/10.1101/2021.09.21.461320____.
My understanding is while the authors aim at investigating the role of CDPK3 in A23187 induced egress, the main finding related to CDPK3 is a defect in cAMP homeostasis that is not linked to A23187. Similarly, the requirements of PDE2 in cAMP homeostasis and egress is indirectly linked to CDPK3. Altogether I think that important results are presented here but divided into three main and distinct sections: the phosphoproteomic survey, the lipidomic and cAMP level investigation, and the characterisation of the four PDEs. However, the link between each section is relatively weak and the way the results are presented is somehow misleading or confusing.
Response:
As mentioned in a previous response, we chose to study PDEs in greater detail because of our observation that both A23187 and BIPPO treatments lead to their phosphorylation (hinting at the presence of a Ca2+regulated feedback loop). We were particularly intrigued to study the cAMP specific PDE, as CDPK3 KO parasites suggested that cAMP may play a role in the Ca2+ feedback mechanism. As PDE2 may not be directly regulated by CDPK3, Ca2+ appears to exert its feedback effects in numerous ways. We have modified our wording to better reflect our rationale for studying the PDEs irrespective of their CDPK3 phosphorylation status.
-Do you have suggestions that would help the authors improve the presentation of their data and conclusions?
This is a very long manuscript written for specialists of this signalling pathway and I would suggest the authors to emphasise more the important results and also clearly state where links are still missing. This is obviously a complex pathway and one cannot elucidate it easily in a single manuscript.
Response:
We have included an additional summary in our conclusions to better illustrate our findings and clarify any missing links.
Reviewer #2 (Significance (Required)):
-Describe the nature and significance of the advance (e.g. conceptual, technical, clinical) for the field.
This is a technically remarkable paper using a broad range of analyses performed to a high standard.
-Place the work in the context of the existing literature (provide references, where appropriate).
The cross-talk between cAMP, cGMP and calcium signalling is well described in Toxoplasma and related parasites. Here the authors show that, in Toxoplasma, CDPK3 is part of this complex signalling network. One of the most important finding within this context is the role of CDPK3 in cAMP homeostasis. With this in mind, I would change the last sentence of the abstract to "In summary we uncover a feedback loop that enhances signalling during egress and links CDPK3 with several signalling pathways together."
Response:
In light of feedback received from several reviewers, we have made our wording less CDPK3 centric - as our findings relate in part to CDPK3 and, in a broader sense, to a Ca2+ driven feedback loop.
The genetic and biochemical analyses of the four PDEs are remarkable and highlight consistencies and inconsistencies with recently published work that would be important to discuss and will be of interest for the field.
__Response: __We thank reviewer#2 and agree that the PDE findings are of significant importance to the field.
While I understand the studied signalling pathway is complex, I think it would be important to better describe the current model of the authors. In the discussion, the authors indicate that "the published data is not currently supported by a model that fits most experimental results." I would suggest to clarify this statement and discuss whether their work helps to reunite, correct or improve previous models.
__Response: __We have expanded on the abovementioned statement to clarify that the presence of a feedback loop is a major pillar of knowledge required for the complete interpretation of existing signalling data.
Could the authors also speculate about a potential role of PDE/CDPK3 in host cell invasion as cAMP signalling has be shown to be important for this process (30208022 and 29030485)?
__Response: __Existing literature (Jia et al., 2017) suggests that perturbations to cAMP signalling play a very minor role in invasion since parasites where either ACα or ACβ are deleted show no impairment in invasion levels. We currently do not have substantial data on invasion, and are not sure that pursuing this is valuable given the minor phenotypes observed in other studies.
-State what audience might be interested in and influenced by the reported findings.
This paper is of great interest to groups working on the regulation of egress in Toxoplasma gondii and other related apicomplexan pathogens.
-Define your field of expertise with a few keywords to help the authors contextualize your point of view. Indicate if there are any parts of the paper that you do not have sufficient expertise to evaluate.
I am working on the cell biology of apicomplexan parasites.
Reviewer #3 (Evidence, reproducibility and clarity (Required)):
**Summary:**
Dominicus et al aimed to identify the intersecting components of calcium, cyclic nucleotides (cAMP, cGMP) and lipid signaling through phosphoproteomic, knockout and biochemical assays in an intracellular parasite, Toxoplasma gondii, particularly when its acutely-infectious tachyzoite stage exits the host cells. A series of experimental strategies were applied to identify potential substrates of calcium-dependent protein kinase 3 (CDPK3), which has previously been reported to control the tachyzoite egress. According to earlier studies (PMID: 23226109, 24945436, 5418062, 26544049, 30402958), CDPK3 regulated the parasite exit through multiple phosphorylation events. Here, authors identified differentially-regulated (DR) phosphorylation sites by comparing the parasite samples after treatment with a calcium ionophore (A23178) and a PDE inhibitor (BIPPO), both of which are known to induce artificial egress (induced egress as opposed to natural egress). When the DCDPK3 mutant was treated with A23187, its delayed egress phenotype did not change, whereas BIPPO restored the egress to the level of the parental (termed as WT) strain, probably by activating PKG.
The gene ontology enrichment of the up-regulated clusters revealed many probable CDPK3-dependent DR sites involved in cyclic nucleotide signaling (PDE1, PDE2, PDE7, PDE9, guanylate and adenylate cyclases, cyclic nucleotide-binding protein or CNBP) as well as lipid signaling (PI-PLC, DGK1). Authors suggest lipid signaling as one of the factors altered in the CDPK3 mutant, albeit lipidomics (PC, PI, PS, PT, PA, PE, SM) showed no significant change in phospholipids. To reveal how the four PDEs indicated above contribute to the cAMP and cGMP-mediated egress, they examined their biological significance by knockout/knockdown and enzyme activity assays. Authors claim that PDE1,7,9 proteins are cGMP-specific while PDE2 is cAMP-specific, and BIPPO treatment can inhibit PDE1-cGMP and PDE7-cGMP, but not PDE9-cGMP. Given the complexity, the manuscript is well structured, and most experiments were carefully designed. Undoubtedly, there is a significant amount of work that underlies this manuscript; however, from a conceptual viewpoint, the manuscript does not offer significant advancement over the current knowledge without functional validation of phosphoproteomics data (see below). A large body of work preceding this manuscript has indicated the crosstalk of cAMP, cGMP, calcium and lipid signaling cascades. This work provides a further refinement of the existing model In a methodical sense, the work uses established assays, some of which require revisiting to reach robust conclusions and avoid misinterpretation. The article is quite interesting from a throughput screening point of view, but it clearly lacks the appropriate endorsement of the hits.The authors accept that identifying the phosphorylation of a protein does not imply a functional role, which is a major drawback as there is no experimental support for any phosphorylation site of the protein identified through phosphoproteomics. In terms of the mechanism, it is not clear whether and how lipid turnover and cAMP-PKA signaling control the egress phenotype (lack of a validated model at the end of this study).
Response:
We thank reviewer #3 for their comments, but respectfully disagree with their assessment that the work presented does not advance current knowledge.
- We demonstrate that, following both BIPPO and A23187 treatment, there is differential phosphorylation of numerous components traditionally believed to sit upstream of PKG activation (as well as numerous components within the PKG signalling pathway itself). While it may have been inferred from previous studies that A23187 and BIPPO signalling intersect, this has never been unequivocally demonstrated - nor has a feedback loop ever been shown.
We provide a novel A23187-driven phosphoproteome timecourse that further bolsters the model of a Ca2+-driven feedback loop.
We show that deletion of CDPK3 leads to a delay in DAG production upon stimulation with A23187.
We show that some of the abovementioned sites are CDPK3 dependent, and that deletion of CDPK3 leads to elevated levels of cAMP (dysregulation of which is known to alter PKG signalling).
We show that pre-treatment with a PKA inhibitor is able to largely rescue this phenotype.
We demonstrate that a cAMP-specific PDE is phosphorylated following A23187 treatment (i.e. Ca2+ flux)
We show that this cAMP specific PDE plays a role in egress.
While the latter PDE may not be directly regulated by CDPK3, these findings suggest that there are likely several Ca2+-dependent kinases that contribute to this feedback loop.
We also firmly disagree with the reviewer’s assertion that without phosphosite characterisation, we have no support for our model. Following treatment with A23187 (and BIPPO), we clearly show broad, systemic changes (both CDPK3 dependent and independent) across signalling pathways previously deemed to sit upstream of calcium flux. Given the vast number of proteins involved in these signalling pathways, and the multitude of differentially regulated phosphosites identified on each of them, it is highly likely that the signalling effects we observe are combinatorial. Accordingly, we believe that mutating individual sites on individual proteins would be a very costly endeavour which is unlikely to substantially advance our understanding of signalling during egress. Moreover, introducing multiple point mutations in a given protein to ablate phosphorylation may lead to protein misfolding and would therefore not be informative. One of the key aims of this study was to assess how egress signalling pathways are interconnected, and we believe we have been able to show strong support for a Ca2+-driven feedback mechanism in which both CDPK3 and PDE2 play a role through the regulation of cAMP.
While we agree with the reviewer’s statement that a large body of work preceding this manuscript has indicated the crosstalk of cAMP, cGMP, calcium and lipid signalling cascades, a feedback loop has not previously been shown. We believe that this finding is absolutely central to facilitate the complete interpretation of existing signalling data. Furthermore, no previous studies have gone to this level of detail in either proteomics or lipidomics to analyse the calcium signal pathway in any apicomplexan parasite. We argue that the novelty in our manuscript is that it is a carefully orchestrated study that advances our understanding of the signalling network over time with subcellular precision. The kinetics of signalling is not well understood and we believe that our study is likely the first to include both proteomic and lipidomic analyses over a timecourse during the acute lytic cycle stage of the disease. In doing so, we found evidence for a feedback loop that controls the signalling network spatiotemporally, and we characterise elements of this feedback in the same study.
**Major Comments:**
Based on the findings reported here there is little doubt that BIPPO and A23187-induced signaling intersect with each other, as very much expected from previous studies. The authors selected the 50s and 15s post-treatment timing of A23187 and BIPPO, respectively for collecting phosphoproteomics samples. At these time points, which were shown to peak cytosolic Ca2+, parasites were still intracellular (Line #171). How did authors make sure to stimulate the entire signaling cascade adequately, particularly when parasites do not egress within the selected time window? There is significant variability between phosphosite intensities of replicates (Line #186), which may also be attributed to insufficient triggers for the egress across independent experiments. This work must be supported by in vitro egress assays with the chosen incubation periods of BIPPO and ionophore treatment (show the induced % egress of tachyzoites in the 50s and 15s).
Response:
- We appreciate that the reviewer acknowledges that our data clearly shows that BIPPO and A23187-induced signalling intersect. While this may have been expected from previous studies, this has not previously been shown - and is therefore valuable to the field. Specifically, the fact that A23187-treatment leads to phosphorylation of targets normally deemed to sit upstream of calcium release is entirely novel and adds a substantial layer of information to our understanding of how these signalling pathways work together.
Treatments were purposely selected to align pathways to a point where calcium levels peak just prior to calcium reuptake. At these chosen timepoints, we clearly show that overall signalling correlation is very high. We know from our egress assays using identical treatment concentrations (Fig. 2C), that the stimulations used are sufficient to result in complete egress. We are simply comparing signalling pathways at points prior to egress.
As mentioned in point 2, we show convincingly that the treatments used are sufficient to trigger complete egress. As detailed clearly in the text, we believe that these variations in intensities between replicates are due to slight differences in timing between experiments (this is inevitable given the very rapid progression of signalling, and the difficulty of replicating exact sub-minute treatment timings). We demonstrate that the reporter intensities associated with DR sites correlate well across replicates (Supp Fig. 3C), suggesting that despite some replicate variability, the overall trends across replicates is very much consistent. This allows us to confidently average scores to provide values that are representative of a site’s phosphorylation state at the timepoint of interest.
The reviewer’s suggestion that we should demonstrate % egress at the 50s and 15s treatment timepoints is obsolete - we state clearly in the text that parasites have not egressed at these timepoints. Our egress assays (Fig. 2C) further support this.
The authors discuss that CDPK3 controls the cAMP level and PKA through activation of one or more yet-to-be-identified PDEs(s). cAMP could probably also be regulated by an adenylate cyclase, ACbeta that was found to have CDPK3-dependent phosphorylation sites. If CDPK3 is indeed a regulator of cAMP through the activation of PDEs or ACbeta, it would be expected that the deletion of CDPK3 would perturb the cAMP level, resulting in dysregulation of PKAc1 subunit, which in turn would dysregulate cGMP-specific PDEs (PMID: 29030485) and thereby PKG. All these connections need to explain in a more clear manner with experimental support (what is positive and what is negatively regulated by C____DPK3).
Response:
- We do not firmly state that CDPK3 regulates cAMP by phosphorylation of a PDE - this is one of the possibilities addressed. We acknowledge the possibility that this could also be via the adenylate cyclase (see line 792).
PMID: 29030485 demonstrates clearly a link between cAMP signalling and PKG signalling, but does not demonstrate how this is mediated. The authors postulate that a cGMP-specific PDE is dysregulated given their observation that PDE2 is differentially phosphorylated in a constitutively inactive PKA mutant, however this was not validated experimentally. We and others (Moss et al., 2022), however, demonstrate that PDE2 is cAMP-specific. This suggests that the model built by PMID: 29030485 requires revisiting. We acknowledge clearly in the text that Jia et al. have shown a link between cAMP and PKG signalling, and hypothesise that CDPK3’s modulation of cAMP levels may affect this (this is in keeping with our phosphoproteomic data).
Moreover, the egress defect is not due to a low influx of calcium in the cytosol because when the ionophore A23187 was added to the CDPK3 mutant, its phenotype was not recovered. Rather, the defect may be due to the low or null activity of PKG that would activate PI4K to generate IP3 and DAG. The latter would be used as a substrate by DGK to generate PA that is involved in the secretion of micronemes and Toxoplasma egress. In this context, authors should evaluate the role of CDPK3 in the secretion of micronemes that is directly related to the egress of the parasite.
- We agree with the reviewer on their point about calcium influx, and have already acknowledged in the text that the feedback loop does not control release of Ca2+ from internal stores as disruption of CDPK3 does not lead to a delay in Ca2+
We agree, and clearly address in the text, that the egress defect could be due to altered PKG/phospholipid pathway signalling.
(Lourido, Tang and David Sibley, 2012; McCoy et al., 2012) have both previously shown that microneme secretion is regulated by CDPK3. We therefore do not deem it necessary to repeat this experiment, but have made clearer mention of their findings in our writing.
When the Dcdpk3 mutant with BIPPO treatment was evaluated, it was observed that the parasite recovered the egress phenotype. It is concluded that CDPK3 could probably regulate the activity of cGMP-specific PDEs. CDPK3 could (in)activate them, or it could act on other proteins indirectly regulating the activity of these PDEs. Upon inactivation of PDEs, an increase in the cGMP level would activate PKG, which will, in turn, promote egress. From the data, it is not clear whether any phosphorylation by CDPK3 would activate or inactivate PDEs, and if so, then how (directly or indirectly). To reach unambiguous interpretation, authors should perform additional assays.
Response:
As mentioned previously, given the abundance of differentially regulated phosphosites, we do not believe that mutating individual sites on individual proteins is a worthwhile or realistic pursuit.
We clearly show systematic A23187-mediated phosphorylation of key signalling components in the PKA/PKG/PI-PLC/phospholipid signalling cascade, and demonstrate that several of these are CDPK3-dependent. We demonstrate that CDPK3 alters cAMP levels (and that the ∆CDPK3 egress delay in A23187 treated parasites is largely rescued following pre-treatment with a PKA inhibitor). We similarly demonstrate that A23187 treatment leads to phosphorylation of numerous PDEs, including the cAMP specific PDE2, and show that PDE2 knockout parasites show an egress delay following A23187 treatment. While PDE2 may not be directly regulated by CDPK3 (suggesting other Ca2+ kinases are also involved), these findings collectively demonstrate the existence of a calcium-regulated feedback loop, in which CDPK3 and PDE2 play a role (by regulating cAMP).
We acknowledge that we have not untangled every element of this feedback loop, and do not believe that it would be realistic to do so in a single study given the number of sites phosphorylated and pathways involved. We do believe, however, that we have shown clearly that the feedback loop exists - this in itself is entirely novel, and of significant importance to the field.
On a similar note, a possible experiment that can be done to improve the work would be to treat the CDPK3 mutant with BIPPO in conjunction with a calcium chelator (BAPTA-AM) to reveal, which proteins are phosphorylated prior to activation of the calcium-mediated cascades?
Response:
We agree that this would be an interesting experiment to carry out but would involve significant work. This could be pursued in another paper or project but is beyond the scope of this work.
The manuscript claims that PDE1, PDE7, PDE9 are cGMP specific, and BIPPO inhibits only cGMP-specific PDEs. All assays are performed with 1-10 micromolar cAMP and cGMP for 1h. There is no data showing the time, protein and substrate dependence. Given the suboptimal enzyme assays, authors should re-do them as suggested here. (1) Repeat the pulldown assay with a higher number of parasites (50-100 million) and measure the protein concentration. (2) Set up the PDE assay with saturating amount of cAMP and cGMP, which is critical if the PDE1,7,9 have a higher Km Value for cAMP (means lower affinity) compared to cGMP. An adequate amount of substrate and protein allows the reaction to reach the Vmax. Once you have re-determined the substrate specificity (revise Fig 5D), you should retest BIPPO (Fig 5E) in the presence of cAMP and cGMP. It is very likely that you would find the same result as PDE9 and PfPDEβ (BIPPO can inhibit both cAMP and cGMP-specific PDE), as described previously
We have repeated our assay using the exact same conditions outlined by Moss et al. This involved using a similar number of parasites, a longer incubation time of 2 hours at a higher temperature (37ºC) and with a lower starting concentration of cAMP (0.1 uM). We demonstrate that we are able to recapitulate both the Moss et al. and Vo et al. (see Supp Fig. 7B). However, we noticed that these reactions were not carried out with saturating cAMP/cGMP concentrations, since all reactions had reached 100% completion at the end of the assay whereby all substrate was hydrolysed. We therefore believe that based on our original assay, as well as the new PDE1 timecourse that we have performed (Supp Fig. 7C), that PDEs 1, 7 and 9 display predominantly cGMP hydrolysing activity, with moderate cAMP hydrolysing activity.
We also repeated the BIPPO inhibition assay using the Moss et al. conditions, and still observe that the cGMP activity of PDE1 is the most potently inhibited of all 4 PDEs. We also see moderate inhibition of the cAMP activities of PDE1 and PDE9, suggesting that cAMP hydrolytic activity can also be inhibited. Interestingly, the cGMP hydrolytic activities of PDEs 7 & 9, which were previously inhibited using our original assay conditions, no longer appear to be inhibited. This is likely due to the longer incubation time, which masks the reduced activities of these two PDEs following treatment with BIPPO.
The authors did not identify any PKG substrate, which is quite surprising as cAMP signaling itself could impact cGMP. Authors should show if they were able to observe enhanced cGMP levels in BIPPO-treated sample (which is expected to stimulate cGMP-specific PDEs). The author mention their inability to measure cGMP level but have they analyzed cGMP in the positive control (BIPPO-treated parasite line)? Why have they focused only on CDPK3 mutant, whereas in their phosphoproteomic data they could see other CDPKs too? It could be that other CDPK-mediated signaling differs and need PKA/PKG for activation.
In the title, the authors have mentioned that there is a positive feedback loop between calcium release, cyclic nucleotide and lipid signaling, which is quite an extrapolation as there is no clear experimental data supporting such a positive feedback loop so the author should change the title of the paper.
Response:
- As addressed in our previous response to the reviewer, PMID: 29030485 demonstrates clearly a link between cAMP signalling and PKG signalling, but does not confirm how this is mediated. The authors surmise that a cGMP-specific PDE is dysregulated (although the PDE hypothesised to be involved has since been shown to be cAMP-specific), but are similarly unable to detect changes in cGMP levels. This suggests that their model may be incomplete.
The BIPPO treatment experiment suggested by the reviewer was already included in the original manuscript (see Fig. 4D in original manuscript, now Fig. 4E). With BIPPO treatment we are able to detect changes in cGMP levels.
We did not deem it to be within the scope of this study to study every single other CDPK. We chose to study CDPK3, as its egress phenotype was of particular interest given its partial rescue following BIPPO treatment. We reasoned that its study may lead us to identify the signalling pathway that links BIPPO and A23187 induced signalling.
As addressed in greater detail in our response to reviewer #2, the fact that the feedback loop appears to stimulate egress implies that it is positive.
**Minor Comments:**
Materials & Methods
Explanation of parameters is not clear (Line #360-367). Phosphoproteomics with A23187 (8 micromolar) treatment in CDPK3-KO and WT, for 15, 30 and 60s at 37{degree sign}C incubation with DMSO control. Simultaneously passing the DR and CDPK3 dependency thresholds: CDPK3-dependent phosphorylation
__Response: __We have modified the wording to make this clearer as per the reviewer’s suggestion.
Line #368: At which WT-A23187 timepoint did the authors identify 2408 DR-up phosphosites (15s, 30s or 60s)? Or consistently in all? It should be clarified?
__Response: __As already stated in the manuscript (see line 366 in original manuscript, now line 1047), phosphorylation sites were considered differentially regulated if at any given timepoint their log2FC surpassed the DR threshold.
A23187 treatment of the CDPK3-KO mutant significantly increased the cAMP levels at 5 sec post-treatment, but BIPPO did not show any change. The authors concluded that BIPPO presumably does not inhibit cAMP-specific PDEs. However, the dual-specific PDEs are known to be inhibited by BIPPO, as shown recently (____https://www.biorxiv.org/content/10.1101/2021.09.21.461320v1____). Authors do confirm that BIPPO-treatment can inhibit hydrolytic activity of PfPDEbeta for cAMP as well as cGMP (Line #612). Besides, it was shown in Fig 5E that BIPPO can partially though not significantly block cAMP-specific PDE2. The statements and data conflict each other under different subtitles and need to be reconciled. Elevation of basal cAMP level in the CDPK3 mutant indicates the perturbation of cAMP signaling, however BIPPO data requires additional supportive experiments to conclude its relation with cAMP or dual-specific PDE.
Response:
- The manuscript to which the reviewer refers does not use BIPPO in any of their experiments. They show that continuous treatment with zaprinast blocks parasite growth in a plaque assay, but do not test whether zaprinast specifically blocks the activity of any of the PDEs.
Having repeated the PDE assay using the Moss et al. conditions (as outlined above), we are now able to recapitulate their findings, showing that PDEs 1, 7 and 9 can display dual hydrolytic activity while PDE2 is cAMP specific. As explained further above, we believe that our original set of experiments are more stringent than the Moss *et al. * To confirm this, we also performed an additional experiment, incubating PDE1 for varying amounts of time using our original conditions (1 uM cAMP or 10 uM cGMP, at room temperature). This revealed that PDE1 is much more efficient at hydrolysing cGMP, and only begins to display cAMP hydrolysing capacity after 4 hours of incubation.
We also measured the inhibitory capacity of BIPPO on the PDEs using the Moss *et al. * During the longer incubation time, it seems that BIPPO is unable to inhibit PDEs 7 and 9, while with the more stringent conditions it was able to inhibit both PDEs. We reasoned that since BIPPO is unable to inhibit these PDEs fully, the residual activity over the longer incubation period would compensate for the inhibition, eventually leading to 100% hydrolysis of the cNMPs. We also see that while the cGMP hydrolysing capacity of PDE1 is completely inhibited, its cAMP hydrolysing capacity is only partially inhibited. These findings and the fact that PDE2 is not inhibited by BIPPO are in line with our experiments where we measured [cAMP] and showed that treatment with BIPPO did not lead to alterations in [cAMP].
The method used to determine the substrate specificity of PDE 1,2,7 and 9 resulted in the hydrolytic activity of PDE2 towards cAMP, while the remaining 3 were determined as cGMP-specific. However, PDE1 and PDE9 have been reported as being dual-specific (Moss et al, 2021; Vo et al, 2020), which questions the reliability of the preferred method to characterize substrate specificity by the authors. It is also suggested to use another ELISA-based kit to double check the results.
Response:
As outlined above, we have repeated the assay using the conditions described by Moss et al. (lower starting concentrations of cAMP, 2 hour incubation period at 37ºC) and find that we are able to recapitulate the results of both Moss et al. and Vo et al.. However, using the Moss et al. conditions, the PDEs have hydrolysed 100% of the cyclic nucleotide, suggesting that these conditions are less stringent than the ones we used originally using higher starting concentrations of cAMP and incubating for 1 hour only at room temperature. With enzymatic assays it is always important to perform them at saturating conditions (as already suggested by the reviewer) and therefore we believe that our original conditions are more stringent than the results using the Moss et al. conditions.
Line #607-608: Authors found PDE9 less sensitive to BIPPO-treatment and concluded PDE2 as refractory to BIPPO inhibition; however, the reduction level of activity seems similar as seen in PDE9-BIPPO treated sample? This strong statement should be replaced with a mild explanation.
__Response: __We have tempered our wording as per the reviewer’s suggestion
Figures and legends:
The introductory model in Fig S1 is difficult to understand and ambiguous despite having it discussed in the text. For example, CDPK1 is placed, but only mentioned at the beginning, and the role of other CDPKs is not clear. In addition, the arrows in IP3 and PKG are confusing. The location of guanylate and adenylate cyclase is wrong, and so on... The figure should include only the egress-related signaling components to curate it. The illustration of host cell in orange color must be at the right side of the figure in connection with the apical pole of the parasite (not on the top). Figure legend should also be rearranged accordingly and citations of the underlying components should be included (see below).
__Response: __We have modified Supp Fig. 1 as per the suggestions of reviewer#2 and #3. We have now modified the localisations of the proteins and have also removed the lines showing the cross talk between pathways. We have also highlighted to the reader that this is only a model and may not represent the true localisations of the proteins, despite our best efforts.
In Figure 5D, would you please provide the western blot analysis of samples before and after pulling down to demonstrate the success of your immunoprecipitation assay. Mention the protein concentration in your PDE enzyme assay. Please refer to the M&M comments above to re-do the enzyme assays.
Response:
We have now included western blots for the pull downs of PDEs 1, 2, 7 and 9 (Supp Fig. 7A). We chose not to measure protein concentrations of samples since all experiments were performed using the same starting parasite numbers, and we do not see large differences in activities between biological replicates of the PDEs.
Figure legend 1C: Line #194: There is no red-dotted line shown in graph! Correct it!
__Response: __We have modified this.
Figure 4Gi-ii: Shouldn't it be labelled i: H89-treatment and ii: A23178, respectively instead of DMSO and H89? (based on the text Line #579).
__Response: __Our labelling of Fig. 4Gi-ii is correct as panel i parasites were pre-treated with DMSO, while panel ii parasites were pre-treated with H89. Subsequent egress assays on both parasites were then performed using A23187.
We have modified the figures to include mention of A23187 on the X axis, and modified the figure legend to clarify pre-treatment was performed with DMSO and H89 respectively.
Bibliography:
Line #57 and 58: Citations must be selected properly! Carruthers and Sibley 1999 revealed the impact of Ca2+ on the microneme secretion within the context of host cell attachment and invasion, not egress as indicated in the manuscript! Similar case is also valid for the reference Wiersma et al 2004; since the roles of cyclic nucleotides were suggested for motility and invasion. Also notable in the fact that several citations describing the localization, regulation and physiological importance of cAMP and cGMP signaling mediators (PMID: 30449726 , 31235476 , 30992368 , 32191852 , 25555060 , 29030485 ) are either completely omitted or not appropriately cited in the introduction and discussion sections.
Response:
We have modified the citations as per the reviewer’s suggestions. We now cite Endo et al., 1987 for the first use of A23187 as an egress trigger, and Lourido, Tang and David Sibley, 2012 for the role of cGMP signalling in egress. We also cite all the GC papers when we make first mention of the GC. We have also removed the Howard et al., 2015 citation (PMID: 25555060) when referring to the fact that BIPPO/zaprinast can rescue the egress delay of ∆CDPK3 parasites.
Grammar/Language
Line #31: After "cAMP levels" use comma
Response:
We have modified this.
36: Sentence is not clear. Does conditional deletion of all four PDEs support their important roles? If so, the role in egress of the parasite?
Response:
We have clarified our wording as per the reviewer’s suggestion. We state that PDEs 1 and 2 display an important role in growth since deletion of either these PDEs leads to reduced plaque growth. We have not investigated exactly what stage of the lytic cycle this is.
40: "is a group involving" instead of "are"
Response:
We found no mention of “a group involving” in our original manuscript at line 40 or anywhere else in the manuscript, so we are unsure what the reviewer is referring to.
108: isn't it "discharge of Ca++ from organelle stores to cytosol"?
__Response: __We thank the reviewer for spotting this error. We have now modified this sentence.
120: "was" instead of "were"
__Response: __Since the situation we are referencing is hypothetical, then ‘were’ is the correct tense.
Reviewer #3 (Significance (Required)):
There is a significant amount of work that underlies this manuscript; however, from a conceptual viewpoint, the manuscript does not offer significant advancement over the current knowledge without functional validation of phosphoproteomics data. In terms of the mechanism, it is not clear whether and how lipid turnover and cAMP-PKA signaling control the egress phenotype (lack of a validated model at the end of this study).In a methodical sense, the work uses established assays, some of which require revisiting to reach robust conclusions and avoid misinterpretation.
Compare to existing published knowledge
A large body of work preceding this manuscript has indicated the crosstalk of cAMP, cGMP, calcium and lipid signaling cascades. This work provides a further refinement of the existing model. The article is quite interesting from a throughput screening point of view, but it clearly lacks the appropriate endorsement of the hits.
Response:
Please refer to our first response to reviewer #3 for our full rebuttal to these points. We respectfully disagree with the assessment that the work presented does not advance current knowledge.
Audience
Field specific (Apicomplexan Parasitology)
Expertise
Molecular Parasitology
References
Bailey, A. P. et al. (2015) ‘Antioxidant Role for Lipid Droplets in a Stem Cell Niche of Drosophila’, Cell. The Authors, 163(2), pp. 340–353. doi: 10.1016/j.cell.2015.09.020.
Bullen, H. E. et al. (2016) ‘Phosphatidic Acid-Mediated Signaling Regulates Microneme Secretion in Toxoplasma Article Phosphatidic Acid-Mediated Signaling Regulates Microneme Secretion in Toxoplasma’, Cell Host & Microbe, pp. 349–360. doi: 10.1016/j.chom.2016.02.006.
Dass, S. et al. (2021) ‘Toxoplasma LIPIN is essential in channeling host lipid fluxes through membrane biogenesis and lipid storage’, Nature Communications. Springer US, 12(1). doi: 10.1038/s41467-021-22956-w.
Endo, T. et al. (1987) ‘Effects of Extracellular Potassium on Acid Release and Motility Initiation in Toxoplasma gondii’, The Journal of Protozoology, 34(3), pp. 291–295. doi: 10.1111/j.1550-7408.1987.tb03177.x.
Flueck, C. et al. (2019) Phosphodiesterase beta is the master regulator of camp signalling during malaria parasite invasion, PLoS Biology. doi: 10.1371/journal.pbio.3000154.
Howard, B. L. et al. (2015) ‘Identification of potent phosphodiesterase inhibitors that demonstrate cyclic nucleotide-dependent functions in apicomplexan parasites’, ACS Chemical Biology, 10(4), pp. 1145–1154. doi: 10.1021/cb501004q.
Jia, Y. et al. (2017) ‘ Crosstalk between PKA and PKG controls pH ‐dependent host cell egress of Toxoplasma gondii ’, The EMBO Journal, 36(21), pp. 3250–3267. doi: 10.15252/embj.201796794.
Katris, N. J. et al. (2020) ‘Rapid kinetics of lipid second messengers controlled by a cGMP signalling network coordinates apical complex functions in Toxoplasma tachyzoites’, bioRxiv. doi: 10.1101/2020.06.19.160341.
Lentini, J. M. et al. (2020) ‘DALRD3 encodes a protein mutated in epileptic encephalopathy that targets arginine tRNAs for 3-methylcytosine modification’, Nature Communications. Springer US, 11(1). doi: 10.1038/s41467-020-16321-6.
Lourido, S., Tang, K. and David Sibley, L. (2012) ‘Distinct signalling pathways control Toxoplasma egress and host-cell invasion’, EMBO Journal. Nature Publishing Group, 31(24), pp. 4524–4534. doi: 10.1038/emboj.2012.299.
Lunghi, M. et al. (2022) ‘Pantothenate biosynthesis is critical for chronic infection by the neurotropic parasite Toxoplasma gondii’, Nature Communications. Springer US, 13(1). doi: 10.1038/s41467-022-27996-4.
McCoy, J. M. et al. (2012) ‘TgCDPK3 Regulates Calcium-Dependent Egress of Toxoplasma gondii from Host Cells’, PLoS Pathogens, 8(12). doi: 10.1371/journal.ppat.1003066.
Moss, W. J. et al. (2022) ‘Functional Analysis of the Expanded Phosphodiesterase Gene Family in Toxoplasma gondii Tachyzoites’, mSphere. American Society for Microbiology, 7(1). doi: 10.1128/msphere.00793-21.
Stewart, R. J. et al. (2017) ‘Analysis of Ca2+ mediated signaling regulating Toxoplasma infectivity reveals complex relationships between key molecules’, Cellular Microbiology, 19(4). doi: 10.1111/cmi.12685.
Vo, K. C. et al. (2020) ‘The protozoan parasite Toxoplasma gondii encodes a gamut of phosphodiesterases during its lytic cycle in human cells’, Computational and Structural Biotechnology Journal. The Author(s), 18, pp. 3861–3876. doi: 10.1016/j.csbj.2020.11.024.
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Referee #2
Evidence, reproducibility and clarity
Summary:
Provide a short summary of the findings and key conclusions (including methodology and model system(s) where appropriate).
In this manuscript, Dominicus et al investigate the elusive role of calcium-dependent kinase 3 during the egress of Toxoplasma gondii. Multiple functions have already been proposed for this kinase by this group including the regulation of basal calcium levels (24945436) or of a tyrosine transporter (30402958). However, one of the most puzzling phenotypes of CDPK3 deficient tachyzoites is a marked delay in egress when parasites are stimulated with a calcium ionophore that is rescued with phosphodiesterase (PDE) inhibitors. Crosstalk between, cAMP, cGMP, lipid and calcium signalling has been previously described to be important in regulating egress (26933036, 23149386, 29030485) but the role of CDPK3 in Toxoplasma is still poorly understood.
Here the authors first take an elegant phosphoproteomic approach to identify pathways differentially regulated upon treatment with either a PDE inhibitor (BIPPO) and a calcium ionophore (A23187) in WT and CDPK3-KO parasites. Not much difference is observed between BIPPO or A23187 stimulation which is interpreted by the authors as a regulation through a feed-back loop. The authors then investigate the effect of CDPK3 deletion on lipid, cGMP and cAMP levels. The identify major changes in DAG, phospholipid, FFAs, and TAG levels as well as differences in cAMP levels but not for cGMP. Chemical inhibition of PKA leads to a similar egress timing in CDPK3-KO and WT parasites upon A23187 stimulation.
As four PDEs appeared differentially regulated in the CDPK3-KO line upon A23187, the authors investigate the requirement of the 4 PDEs in cAMP levels. They show diverse localisation of the PDEs with specificities of PDE1, 7 and 9 for cGMP and of PDE2 for cAMP. They further show that PDE1, 7 and 9 are sensitive to BIPPO. Finally, using a conditional deletion system, they show that PDE1 and 2 are important for the lytic cycle of Toxoplasma and that PDE2 shows a slightly delayed egress following A23187 stimulation.
Major comments:
-Are the key conclusions convincing?
The title is supported by the findings presented in this study. However I am not sure to understand why the authors imply a positive feed back loop. This should be clarified in the discussion of the results. The phosphoproteome analysis seems very strong and will be of interest for many groups working on egress. However, the key conclusion, i.e. that a substrate overlaps between PKG and CDPK3 is unlikely to explain the CDPK3 phenotype, seems premature to me in the absence of robustly identified substrates for both kinases.
I am not sure there is a clear key conclusion from the lipidomic analysis and how it is used by the authors to build their model up. Major changes are observed but how could this be linked with CDPK3, particularly if cGMP levels are not affected?
The evidence that CDPK3 is involved in cAMP homeostasis seems strong. However, the analysis of PKA inhibition is a bit less clear. The way the data is presented makes it difficult to see whether the treatment is accelerating egress of CDPK3-KO parasites or affecting both WT and CDPK3-KO lines, including both the speed and extent of egress. This is important for the interpretation of the experiment.
The biochemical characterisation of the four PDE is interesting and seems well performed. However, PDE1 was previously shown to hydrolyse both cAMP and cGMP (https://doi.org/10.1101/2021.09.21.461320) which raises some questions about the experimental set up. Could the authors possibly discuss why they do not observe similar selectivity? Could other PDEs in the immunoprecipitate mask PDE activity? In line with this question, it is not clear what % of "hydrolytic activity (%)" means and how it was calculated. The experiments describing the selectivity of BIPPO for PDE1, 7 and 9 as well as the biological requirement of the four tested PDEs are convincing.
-Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether?
The claim that CDPK3 affects cAMP levels seems strong however the exact links between CDPK3 activity, lipid, cGMP and cAMP signalling remain unclear and it may be important to clearly state this.
-Would additional experiments be essential to support the claims of the paper? Request additional experiments only where necessary for the paper as it is, and do not ask authors to open new lines of experimentation.
I think that the manuscript contains a significant amount of experiments that are of interest to scientists working on Toxoplasma egress. Requesting experiments to identify the functional link between above-mentioned pathways would be out of the scope for this work although it would considerably increase the impact of this manuscript. For example, would it be possible to test whether the CDPK3-KO line is more or less sensitive to PKG specific inhibition upon A23187 induced?
-Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated cost and time investment for substantial experiments.
The above-mentioned experiment is not trivial as no specific inhibitors of PKG are available. Ensuring for specificity of the investigated phenotype would require the generation of a resistant line which would require significant work.
-Are the data and the methods presented in such a way that they can be reproduced?
It is not clear how the % of hydrolytic activity of the PDE has been calculated.
-Are the experiments adequately replicated and statistical analysis adequate?
This seems to be performed to high standards.
Minor comments:
-Specific experimental issues that are easily addressable.
I do not have any comments related to minor experimental issues.
-Are prior studies referenced appropriately?
Most of the studies relevant for this work are cited. It is however not clear to me why some important players of the "PKG pathway" are not indicated in Fig 1H and Fig 3E, including for example UGO or SPARK.
-Are the text and figures clear and accurate?
While all the data shown here is impressive and well analysed, I find it difficult to read the manuscript and establish links between sections of the papers. The phosphoproteome analysis is interesting and is used to orientate the reader towards a feedback mechanism rather than a substrate overlap. But why do the authors later focus on PDEs and not on AC or CNBD, as in the end, if I understand well, there is no evidence showing a link between CDPK3-dependent phosphorylation and PDE activity upon A23187 stimulation? It is also unclear how the authors link CDPK3-dependent elevated cAMP levels with the elevated basal calcium levels they previously described. This is particularly difficult to reconcile particularly in a PKG independent manner.
The presentation of the lipidomic analysis is also not really clear to me. Why do the authors show the global changes in phospholipids and not a more detailed analysis? As the authors focus on the PI-PLC pathway, could they detail the dynamics of phosphoinositides? I understand that lipid levels are affected in the mutant but I am not sure to understand how the authors interpret these massive changes in relationship with the function of CDPK3 and the observed phenotypes.
Finally, the characterisation of the PDEs is an impressive piece of work but the functional link with CDPK3 is relatively unclear. It would also be important to clearly discuss the differences with previous results presented in this this preprint: https://doi.org/10.1101/2021.09.21.461320. My understanding is while the authors aim at investigating the role of CDPK3 in A23187 induced egress, the main finding related to CDPK3 is a defect in cAMP homeostasis that is not linked to A23187. Similarly, the requirements of PDE2 in cAMP homeostasis and egress is indirectly linked to CDPK3. Altogether I think that important results are presented here but divided into three main and distinct sections: the phosphoproteomic survey, the lipidomic and cAMP level investigation, and the characterisation of the four PDEs. However, the link between each section is relatively weak and the way the results are presented is somehow misleading or confusing.
-Do you have suggestions that would help the authors improve the presentation of their data and conclusions?
This is a very long manuscript written for specialists of this signalling pathway and I would suggest the authors to emphasise more the important results and also clearly state where links are still missing. This is obviously a complex pathway and one cannot elucidate it easily in a single manuscript.
Significance
-Describe the nature and significance of the advance (e.g. conceptual, technical, clinical) for the field.
This is a technically remarkable paper using a broad range of analyses performed to a high standard.
-Place the work in the context of the existing literature (provide references, where appropriate).
The cross-talk between cAMP, cGMP and calcium signalling is well described in Toxoplasma and related parasites. Here the authors show that, in Toxoplasma, CDPK3 is part of this complex signalling network. One of the most important finding within this context is the role of CDPK3 in cAMP homeostasis. With this in mind, I would change the last sentence of the abstract to "In summary we uncover a feedback loop that enhances signalling during egress and links CDPK3 with several signalling pathways together."
The genetic and biochemical analyses of the four PDEs are remarkable and highlight consistencies and inconsistencies with recently published work that would be important to discuss and will be of interest for the field.
While I understand the studied signalling pathway is complex, I think it would be important to better describe the current model of the authors. In the discussion, the authors indicate that "the published data is not currently supported by a model that fits most experimental results." I would suggest to clarify this statement and discuss whether their work helps to reunite, correct or improve previous models.
Could the authors also speculate about a potential role of PDE/CDPK3 in host cell invasion as cAMP signalling has be shown to be important for this process (30208022 and 29030485)?
-State what audience might be interested in and influenced by the reported findings.
This paper is of great interest to groups working on the regulation of egress in Toxoplasma gondii and other related apicomplexan pathogens.
-Define your field of expertise with a few keywords to help the authors contextualize your point of view. Indicate if there are any parts of the paper that you do not have sufficient expertise to evaluate.
I am working on the cell biology of apicomplexan parasites.
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github.com github.com
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```js / Adapted from: https://github.com/openannotation/annotator/blob/v1.2.x/src/plugin/document.coffee Annotator v1.2.10 https://github.com/openannotation/annotator Copyright 2015, the Annotator project contributors. Dual licensed under the MIT and GPLv3 licenses. https://github.com/openannotation/annotator/blob/master/LICENSE /
/* * nb. The
DocumentMetadata
type is renamed to avoid a conflict with the *DocumentMetadata
class below. * * @typedef {import('../../types/annotator').DocumentMetadata} Metadata /import { normalizeURI } from '../util/url';
/* * @typedef Link * @prop {string} link.href * @prop {string} [link.rel] * @prop {string} [link.type] /
/* * Extension of the
Metadata
type with non-optional fields fordc
,eprints
etc. * * @typedef HTMLDocumentMetadata * @prop {string} title * @prop {Link[]} link * @prop {Record<string, string[]>} dc * @prop {Record<string, string[]>} eprints * @prop {Record<string, string[]>} facebook * @prop {Record<string, string[]>} highwire * @prop {Record<string, string[]>} prism * @prop {Record<string, string[]>} twitter * @prop {string} [favicon] * @prop {string} [documentFingerprint] // * HTMLMetadata reads metadata/links from the current HTML document. */ export class HTMLMetadata { / * @param {object} [options] * @param {Document} [options.document] */ constructor(options = {}) { this.document = options.document || document; }
/* * Returns the primary URI for the document being annotated * * @return {string} / uri() { let uri = decodeURIComponent(this._getDocumentHref());
// Use the `link[rel=canonical]` element's href as the URL if present. const links = this._getLinks(); for (let link of links) { if (link.rel === 'canonical') { uri = link.href; } } return uri;
}
/ * Return metadata for the current page. * * @return {HTMLDocumentMetadata} */ getDocumentMetadata() { / @type {HTMLDocumentMetadata} */ const metadata = { title: document.title, link: [],
dc: this._getMetaTags('name', 'dc.'), eprints: this._getMetaTags('name', 'eprints.'), facebook: this._getMetaTags('property', 'og:'), highwire: this._getMetaTags('name', 'citation_'), prism: this._getMetaTags('name', 'prism.'), twitter: this._getMetaTags('name', 'twitter:'), }; const favicon = this._getFavicon(); if (favicon) { metadata.favicon = favicon; } metadata.title = this._getTitle(metadata); metadata.link = this._getLinks(metadata); const dcLink = metadata.link.find(link => link.href.startsWith('urn:x-dc')); if (dcLink) { metadata.documentFingerprint = dcLink.href; } return metadata;
}
/ * Return an array of all the
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. * * @param {string} attribute * @param {string} prefix - it is interpreted as a regex * @return {Record<string,string[]>} */ _getMetaTags(attribute, prefix) { / @type {Record<string,string[]>} */ const tags = {}; for (let meta of Array.from(this.document.querySelectorAll('meta'))) { const name = meta.getAttribute(attribute); const { content } = meta; if (name && content) { const match = name.match(RegExp(^${prefix}(.+)$
, 'i')); if (match) { const key = match[1].toLowerCase(); if (tags[key]) { tags[key].push(content); } else { tags[key] = [content]; } } } } return tags; }/* @param {HTMLDocumentMetadata} metadata / _getTitle(metadata) { if (metadata.highwire.title) { return metadata.highwire.title[0]; } else if (metadata.eprints.title) { return metadata.eprints.title[0]; } else if (metadata.prism.title) { return metadata.prism.title[0]; } else if (metadata.facebook.title) { return metadata.facebook.title[0]; } else if (metadata.twitter.title) { return metadata.twitter.title[0]; } else if (metadata.dc.title) { return metadata.dc.title[0]; } else { return this.document.title; } }
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tags. * @return {Link[]} */ _getLinks(metadata = { dc: {}, highwire: {} }) { / @type {Link[]} */ const links = [{ href: this._getDocumentHref() }];// Extract links from `<link>` tags with certain `rel` values. const linkElements = Array.from(this.document.querySelectorAll('link')); for (let link of linkElements) { if ( !['alternate', 'canonical', 'bookmark', 'shortlink'].includes(link.rel) ) { continue; } if (link.rel === 'alternate') { // Ignore RSS feed links. if (link.type && link.type.match(/^application\/(rss|atom)\+xml/)) { continue; } // Ignore alternate languages. if (link.hreflang) { continue; } } try { const href = this._absoluteUrl(link.href); links.push({ href, rel: link.rel, type: link.type }); } catch (e) { // Ignore URIs which cannot be parsed. } } // Look for links in scholar metadata for (let name of Object.keys(metadata.highwire)) { const values = metadata.highwire[name]; if (name === 'pdf_url') { for (let url of values) { try { links.push({ href: this._absoluteUrl(url), type: 'application/pdf', }); } catch (e) { // Ignore URIs which cannot be parsed. } } } // Kind of a hack to express DOI identifiers as links but it's a // convenient place to look them up later, and somewhat sane since // they don't have a type. if (name === 'doi') { for (let doi of values) { if (doi.slice(0, 4) !== 'doi:') { doi = `doi:${doi}`; } links.push({ href: doi }); } } } // Look for links in Dublin Core data for (let name of Object.keys(metadata.dc)) { const values = metadata.dc[name]; if (name === 'identifier') { for (let id of values) { if (id.slice(0, 4) === 'doi:') { links.push({ href: id }); } } } } // Look for a link to identify the resource in Dublin Core metadata const dcRelationValues = metadata.dc['relation.ispartof']; const dcIdentifierValues = metadata.dc.identifier; if (dcRelationValues && dcIdentifierValues) { const dcUrnRelationComponent = dcRelationValues[dcRelationValues.length - 1]; const dcUrnIdentifierComponent = dcIdentifierValues[dcIdentifierValues.length - 1]; const dcUrn = 'urn:x-dc:' + encodeURIComponent(dcUrnRelationComponent) + '/' + encodeURIComponent(dcUrnIdentifierComponent); links.push({ href: dcUrn }); } return links;
}
_getFavicon() { let favicon = null; for (let link of Array.from(this.document.querySelectorAll('link'))) { if (['shortcut icon', 'icon'].includes(link.rel)) { try { favicon = this._absoluteUrl(link.href); } catch (e) { // Ignore URIs which cannot be parsed. } } } return favicon; }
/* * Convert a possibly relative URI to an absolute one. This will throw an * exception if the URL cannot be parsed. * * @param {string} url / _absoluteUrl(url) { return normalizeURI(url, this.document.baseURI); }
// Get the true URI record when it's masked via a different protocol. // This happens when an href is set with a uri using the 'blob:' protocol // but the document can set a different uri through a <base> tag. _getDocumentHref() { const { href } = this.document.location; const allowedSchemes = ['http:', 'https:', 'file:'];
// Use the current document location if it has a recognized scheme. const scheme = new URL(href).protocol; if (allowedSchemes.includes(scheme)) { return href; } // Otherwise, try using the location specified by the <base> element. if ( this.document.baseURI && allowedSchemes.includes(new URL(this.document.baseURI).protocol) ) { return this.document.baseURI; } // Fall back to returning the document URI, even though the scheme is not // in the allowed list. return href;
} } ```
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srconstantin.wordpress.com srconstantin.wordpress.comRa1
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Also: ho-hoism; see McCarthy to Russell on
eval
Tags
Annotators
URL
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cyberzettel.com cyberzettel.com
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https://cyberzettel.com/chris-aldrich-and-his-research-on-digital-public-zettelkasten/
This looks exciting!
You've also nudged me to convert my burgeoning broader top level tag of "note taking" into a full fledged category (https://boffosocko.com/category/note-taking/) which shortly will contain not only the material on zettelkasten but commonplace books and other related areas.
Usually once a tag has more than a couple hundred entries, it's time to convert it to a category. This one was long overdue.
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www.biorxiv.org www.biorxiv.org
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Reviewer #2 (Public Review):
These studies investigated the identity of cells that migrate in response to stroke from the stem cell niche, the subventricular zone (SVZ). They also showed that these cells are important in the repair processes following cortical ischemia as mice who had stem cells ablated or had age-associated reduced progenitor number had less improvement in a motor task. Finally, they identify the mechanism for this progenitor-driven repair as both synaptic plasticity and angiogenesis following ischemia that is driven by the production of trophic factors most notably VEGF. The major strengths of the paper are the use of multiple promoters to drive the lineage tracing fluorescent marker. In addition to the traditional NesinCre-ER mice with a tdTomato tag, they use an Ascl-1Cre-ER mice which is in fewer progenitors but is more specific to neural progenitors and not upregulated in activated astrocytes to support their findings that the majority of migrating cells are progenitors. To further support this finding they also show the majority of cells do not express the mature astrocyte marker S100beta. The neural stem cell ablation model is the well-established GFAP-TK mouse model which uses ganciclovir to ablate neural progenitors and most importantly they show that it is working for them which increases the rigor of the study. The mechanistic studies are convincing because not only do they use a cortical window and two-photon microscopy to measure changes in the synapsis and vasculature over time but they also do gain and loss of function studies to support that VEGF is a major driver of the reparative response.
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www.jianshu.com www.jianshu.com
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会触发: channel.basicNack(tag, false, true);, 这样会告诉rabbitmq该消息消费失败, 需要重新入队
重试次数跟max-attempts的配置有关,并且因为网络等原因,会导致重试次数高于设定次数, 例子:图中设置为2次,实际执行4次
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blog.csdn.net blog.csdn.net
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broker回传给生产者的确认消息中deliver-tag域包含了确认消息的序列号,此外broker也可以设置basic.ack的multiple域,表示到这个序列号之前的所有消息都已经得到了处理。
事务消息中有用
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Annotators
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preview.iiif.io preview.iiif.io
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We want to tag only a portion of the image thus the motivation of the annotation must be tagging the body of the annotation must be TextualBody containing a text describing what we see in that portion of the X-Ray image, hence the format of the annotation must be text/plain.
Split into two sentences. I think I would write it this way:
We want to tag only a portion of the image and thus the motivation of the Annotation must be tagging. The body of the annotation must be a
TextualBody
— with a format oftext/plain
— that contains the text of our annotation.
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Bạn đủ từng trải để nhận ra rằng:
hay
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Wong et al. developed a new versatile approach with a robust signal to track protein dynamics by inserting a tag into the endogenous loci and different properties of fluorescent dyes for conjugation. Using this approach, the authors monitor the trafficking of Fluorescent dye and Halo-tagged GluA1 with time-lapse imaging and found that neuronal stimulation induces GluA1 accumulation surrounding stimulated synapses on dendritic shafts and actin polymerization at synapses and dendrites. Furthermore, combining with pharmacological manipulations of actin polymerization or myosin activity, the authors found that actin polymerization facilitates exocytosis of GluA1 near activated synapses. The new approach may provide broad impacts upon appropriate control experiments, and the practical application of this approach to GluA1 trafficking upon neuronal activation is significant. However, there are several weaknesses, including confirmation of activity of the tagged receptors and receptor specificity mimicking endogenous LTP machinery. If the receptor tagged by the new robust approach reflects endogenous machinery, this approach will provide a big opportunity to the community as a versatile method to visualize a protein not visualized previously.
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goldhiphop.pro goldhiphop.pro
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2022 New Rap Album
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www.biorxiv.org www.biorxiv.org
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Note: This rebuttal was posted by the corresponding author to Review Commons. Content has not been altered except for formatting.
Learn more at Review Commons
Reply to the reviewers
Reply to the reviewers
- General Statements
It is the common view of all three reviewers that we have not utilized adequate in vitro/biochemical evidence to support the idea that SATB1 protein undergoes liquid-liquid phase separation. We do agree with the reviewers that our manuscript lacks biochemical evidence to support such notion. Though we find it quite interesting and we would like to suggest for the first time in the field of chromatin organization and function, based upon the action of SATB1, that this protein does exist in at least two polypeptide isoforms (764 and 795 amino acids long) which display different phase separation propensity and therefore confer different actions in regulating the (patho)physiological properties of a murine T cell.
Every single research group that works on SATB1, considered so far only a single protein isoform, that is, the shorter isoform of 764 amino acids and no tools, such as isoform-specific antibodies have been developed to discriminate the two isoforms and thus being able to assign unique functions to each isoform. We do understand that such a report, suggesting the presence of two protein isoforms, with potentially quite diverse functions, would question (not necessarily by the authors of this manuscript, since no such comment is included in our manuscript) the conclusions drawn in the literature assigning all biochemical properties to a single, short isoform of SATB1. Moreover, all the genetically modified mice that have been analyzed so far (including our group), deleted both Satb1 isoforms. Our future research approaches should, from now on, consider unraveling the isoform-specific functions of SATB1 and their involvement in physiology and disease. This could also deem useful to explain the quite diverse, both positive and negative effects of SATB1 in transcription regulation. Another major objection of the reviewers was that we should provide cumulative supporting evidence for the existence of the long SATB1 isoform, or at least evaluate the specificity of our custom-made antibody.
Taking under consideration the aforementioned constructive criticism of the three reviewers we would like to perform (most of the suggested experiments have already been performed) additional experiments to support our claims in the manuscript. These experiments are described below as a point-by-point reply to each point raised by the reviewers.
In line with the aforementioned rationale, we propose the title of our manuscript to change into “Two SATB1 isoforms display different phase separation propensity”, if our manuscript is considered for publication.
- Description of the planned revisions
**Reviewer #1**:
4) Lack of in vitro reconstitution experiments with purified long and short SATB1
**PLANNED EXPERIMENT #1**
We do realize this shortcoming of our work. We have to note that purifying recombinant SATB1 protein is quite a challenging task, yet we 1. cloned both Satb1 cDNAs for the long and short isoforms, 2. we successfully expressed both proteins in great quantity and quality and we are willing to perform these experiments if our work is considered for publication.
This proposed experiment has also been requested by Reviewers #2 and #3.
**Reviewer #2**:
- Moreover, an important and direct experiment would be to clone the long isoform in a suitable vector and overexpress in the cell line (as done for the canonical isoform in Supp Fig 1a). This would unequivocally show the efficacy of the antibody and thus the following usage of the same for various assays.
**PLANNED EXPERIMENT #2**
This is a great suggestion. We have cloned the long and short Satb1 cDNAs in pEGFP-C1 vector. We will transfect these plasmids in NIH 3T3 fibroblasts and we will perform Western blot analysis, utilizing the antibody raised against the extra 31 amino acids long peptide present only in the long SATB1 isoform, for the following samples: 1. NIH-3T3 whole cell protein extracts, 2. protein extracts from NIH 3T3 fibroblasts transiently transfected with the pEGFP-C1 plasmid, 3. protein extracts from NIH 3T3 fibroblasts transiently transfected with the pEGFP-long_Satb1_ plasmid and 4. protein extracts from NIH 3T3 fibroblasts transiently transfected with the pEGFP-short_Satb1_ plasmid.
This experiment will consist another proof regarding the specificity of the antibody raised against the extra 31 amino acids long peptide present only in the long SATB1 isoform.
**Minor comments:**
- On pg 6, related to Figure 1, the authors mention 'It should also be noted that when investigating the SATB1 protein levels, we have to bear in mind that the antibodies targeting the N-terminus of SATB1 protein cannot discriminate between the short and long isoforms'. The authors reason that their sizes are too close. It is indeed possible, and widely studied in biochemistry to assess various factors on protein migration (such as PTMs). The authors should validate this aspect (as it is important as per their premise) and perform separation based on charge as well and also use a commercial antibody to validate the same.
(Experiments already performed)
We have adapted the text so that it does not imply that the two isoforms cannot be separated by size. This part in lines 102-107 then reads: “It should also be noted that when investigating the SATB1 protein levels, we have to bear in mind that the antibodies targeting the N-terminus of SATB1 protein cannot discriminate between the short and long isoforms, thus we can only compare the amount of the long SATB1 isoform to the total SATB1 protein levels in vivo conditions. To overcome this limitation and to specifically validate the presence of the long SATB1 protein isoform in primary murine T cells, we designed a serial immunodepletion-based experiment (Fig. 1e, Supplementary Fig. 1a).”
Moreover, in the revised version of the manuscript we now provide a number of additional proofs supporting the presence of the long isoform and also the specificity of the long isoform-specific antibody. As evident in the text cited above, in the revised Fig. 1e,f and revised Supplementary Fig. 1a,b; we present two immunodepletion experiments which should alone address the Reviewer’s concerns. Moreover, we added Supplementary Fig. 1c; demonstrating that the long isoform-specific antibody does not detect any protein in cells with conditionally depleted SATB1 (Satb1_fl/fl_Cd4-Cre+), supporting its specificity. The custom-made and publicly available antibodies targeting all SATB1 isoforms were also verified in Supplementary Fig. 1d. Moreover, the long isoform and all isoform antibodies display similar localization in the nucleus (Supplementary Fig. 1e; their co-localization based on super-resolution microscopy is also quantified in Supplementary Fig. 5a).
In our accompanying revised manuscript Zelenka et al., 2022 (https://doi.org/10.1101/2021.07.09.451769), we will provide yet another piece of evidence, consisting of bacterially expressed short and long SATB1 protein isoforms detected by western blot using either the long isoform-specific or the non-selective all SATB1 isoform antibodies.
**PLANNED EXPERIMENT #3**
Although we think that in the revised version of the manuscript, we have provided enough proof about the existence of the long isoform in primary murine thymocytes we would like to try the following approach as suggested by this Reviewer.
The pI of the two SATB1 isoform is quite similar. The pI of the short SATB1 isoform is 6.09 and for the long SATB1 isoform is 6.18. We will perform 2D PAGE coupled to Western blotting utilizing the antibodies detecting the long and all SATB1 isoforms. Given the fact that both isoforms are post-translationally modified to a various degree, it will be extremely difficult to discriminate between the long and short unmodified versus the long and short post-translationally modified proteins especially in the absence of a specific antibody only for the short isoform.
**Reviewer #3**
- Hexanediol is another assay frequently used in phase-separation studies. However, hexanediol has many deleterious effects on the cell, even at a fraction of the concentration normally used in phase-separation studies. Authors should show controls of cell viability, control proteins that do not phase-separate, etc. See https://www.jbc.org/article/S0021-9258(21)00027-2/fulltext.
Secondly, hexanediol treatment should cause phase-separated protein aggregates to disperse. It is difficult to determine from the images whether or not the aggregates actually disperse or there is just less protein. In any case, small aggregates remain even after treatment, and this appears different from most other hexanediol experiments reported in the literature where the signals become more dispersed and uniform. This is likely because the samples are fixed.
One of the main features of using hexanediol in phase-separation is to show that upon washout, LLPS aggregates can reform. Because the cells are fixed, the critical aspect of this assay is not performed. A washout and LLPS recovery would control for cell viability issues described above and would provide the opportunity to show that total SATB1 protein levels did not change, but its distribution did, which is the essence of this assay in the context of LLPS. This review from the Tjian group is very informative and may be a good resource:
http://genesdev.cshlp.org/content/33/23-24/1619
In line with our reply to point #1 of this Reviewer (page 26 of this document), we should again emphasize that we utilized the hexanediol treatment in primary murine developing T cells as this is the only way to investigate the properties of SATB1 speckles under physiological conditions. This also explains why some small insoluble structure remains after the hexanediol treatment. Note that under physiological conditions, there is a contribution of several protein variants (such as differential PTMs) out of which some will tend to form more stable structures while others could undergo LLPS. It is not clear how the washout experiment could be applied in the primary cell conditions that include cell fixation as the heterogeneity and big variation among cells would make such data analysis highly unreliable.
**PLANNED EXPERIMENT #1**
As we answered to point #4 of Reviewer 1 (page 2), we propose the following experiment. Although the purification of recombinant SATB1 protein is quite a challenging task, yet we 1. cloned both Satb1 cDNAs for the long and short isoforms, 2. we successfully expressed both proteins in great quantity and quality and we are willing to perform in vitro reconstitution experiments if our work is considered for publication.
- The major difference between the long and short isoform of SATB1 is the 31aa segment within the IDR. However the authors find that neither the long or short isoform SATB1 forms LLPS aggregates, and the IDR alone forms aggregates in the cytoplasm (Fig5) but they do not respond to Cry2 light activation. When forced to localize to the nucleus, it does not form aggregates as well (Fig6). The short isoform also did not form any aggregates. These results seem to argue against any isoform specific phase-separation. This experiment seems critical for the story, yet it does not support their overall conclusions. The authors might consider using a different cell line or perhaps do an in vitro assay using purified protein.
I am not certain what to make of the cytoplasmic aggregation, which appears to not form upon localization to the nucleus. Because of this, it is difficult to place weight on the significance of the S635A mutation and the role that a phosphorylation of SATB1 contributes to phase-separation, let alone function There are many additional points of concern, but the ones listed above are perhaps the most significant in terms of the overall conclusions of the paper.
In Fig. 5c we show that the full length long SATB1 isoform often aggregates unlike the short isoform. These data are accompanied with the results for the IDR region, where the situation is even more obvious (Fig. 5f,g). However, in the latter, we have to bear in mind the absence of the multivalent N-terminal part of the protein which seems to be essential for the overall phase behavior of the protein as indicated in Fig. 4b,c.
**PLANNED EXPERIMENT #1**
To further support LLPS of SATB1, we are considering performing the following in vitro experiment, as we answered to point #4 of Reviewer 1 (page 2). Although the purification of recombinant SATB1 protein is quite a challenging task, yet we 1. cloned both Satb1 cDNAs for the long and short isoforms, 2. we successfully expressed both proteins in great quantity and quality and we are willing to perform in vitro reconstitution experiments if our work is considered for publication.
- Description of the revisions that have already been incorporated in the transferred manuscript
**Reviewer #1 (Evidence, reproducibility and clarity)**:
This paper looks at an important nuclear matrix protein SATB1, which is a well known global chromatin organizer and help chromatin loop attach to the nuclear matrix. The paper starts with identification of novel short and long form of SATB1. Both the isoform consist of a prion like low complexity domains, but the long isoform additionally contain an extra EPF domain next the Prion like low complexity domain. The paper reports that in murine cells the long isoform is 3-4 fold more abundant than the short isoform. By using STED microscopy they show SATB1 foci lie next to transcription sites in the nucleus. They conclude by looking at the spherical shape of the SATB1 foci and the susceptibility of SATB1 staining after 1,6 hexanediol treatment that SATB1 forms the small foci in the nucleus due to LLPS. The authors also use RAMAN spectroscopy to conclude a change in nuclear chemical space in absence of SATB1 but without much explanation about which chemical bond or nuclear sub structure change correspond to the change in principal component analysis from Raman spectroscopy. The authors use the light inducible aggregation cry2 tag with the PrD domain of SATB1 and compare it with the Cry2-FUS-LC domain to conclude that the SATB1 LC domain can undergo LLPS. The authors hint at involvement of RNA and also DNA in the LLPS of the SATB1 but without going into any detail. Reviewer: The paper reports that in murine cells the long isoform is 3-4 fold more abundant than the short isoform.
Actually, in page 5 (lines 94-96) of the manuscript we write: “We confirmed that in murine thymocytes the steady state mRNA levels of the short Satb1 transcripts were about 3-5 fold more abundant compared to the steady state mRNA levels of the long Satb1 transcripts (Fig. 1d).” Although the steady state mRNA levels of the long isoform are less abundant compared to the shorter isoforms, the long isoform protein levels are almost comparable to the short isoform as deduced based on immunofluorescence experiments. Moreover, Using our two immunodepletion experiments we quantified the difference, estimating the long isoform being 1.5× to 2.62× less abundant than the short isoform (Fig. 1f and Supplementary Fig. 1b; compare lanes 2 & 3 at the lower panel). • Regarding the RAMAN spectroscopy experiments please see Minor Comment #1 of this Reviewer (page 10).
The key conclusions of the paper are- A) SATB1 undergoes LLPS. But this conclusion is drawn after correlative experiments as detailed below-
This conclusion is indeed made based on correlative experiments only for the primary murine T cells, which do not allow for any targeted experiments. However, the use of in vitro cell lines allowed us to validate these findings using the optogenetic approaches, utilizing additional experimentation.
1) observation of spherical punctae by STED-which could also seem spherical due to their small size. The resolution limit achieved by the STED microscopy used in this paper is not determined or mentioned clearly.
In the revised version of the manuscript, we have specified the resolution of our systems, for STED in Lines 745-746: ”This system enables super-resolution imaging with 35 nm lateral and 130 nm axial resolution.” and for SIM in Lines 759-761: “Images were acquired over the majority of the cell volume in z-dimension with 15 raw images per plane (five phases, three angles), providing ~120-135 nm lateral and ~340-350 nm axial resolution for 488/568 nm lasers, respectively.” The size of the observed speckles is thus above the resolution limit with sizes ranging between 40-80 nm.
The resolution of our systems is routinely verified by the following methods: The resolution of our OMX (SIM-3D) system was tested using ARGO-SIM slide containing a pattern of 36 µm long lines with gradually increasing spacing ranging from (left to right) 0 to 390 nm, with a step of 30 nm (Fig. 1 below). Our SIM system was able to clearly resolve two lines separated by 120 nm.
2) No live cell FRAP experiment with fluorescent SATB1 long or short isoform to show that these foci are liquid like
We did perform FRAP experiments for the SATB1 N-terminus optogenetic construct as demonstrated in Fig. 4f. We did not perform FRAP in the primary murine T cells as this is not technically feasible without creating a new mouse line with fluorescently labeled protein. In the revised version of the manuscript, we additionally performed FRAP experiments for the full length short and long isoform of SATB1 labeled with EGFP and transfected into the NIH-3T3 cell line (Supplementary Figure 6f).
5) LLPS is strongly coupled to the cellular concentration of the proteins. Authors should quantify the cellular concentration of the long and short isoform in the cells.
We did consider protein concentration in our analyses of optogenetic constructs in Fig. 4b,d,e and Supplementary Fig. 6a,b,c. Quantifying the physiological cellular concentration of short and long SATB1 protein isoforms in primary T cells is impossible due to the inherent inability to discriminate between the isoforms by two antibodies, in the absence of Satb1 isoform-specific knockout mice.
However, an approximation of the cellular concentration can be obtained from our immunodepletion experiments. On top of the original immunodepletion experiment that we now present in Supplementary Fig. 1a,b; in the revised version of the manuscript we have repeated the experiment in Fig. 1e,f. Comparison of the two bands for the long and short SATB1 isoforms in the lower panel of the western blot figures suggest that the long SATB1 isoform protein levels are 1.5× to 2.62× less abundant than the short isoform, according to the original and new immunodepletion experiment, respectively. This is now also included in the main text in Lines 110-116: “This experiment can also be used for approximation of the cellular protein levels of SATB1 isoforms in primary murine thymocytes. Comparison of the two bands for long (lane 2) and short SATB1 (lane 3) isoform in the lower panel of Fig. 1f and Supplementary Fig. 1b, suggests that the long SATB1 isoform protein levels may be about 1.5× to 2.62× less abundant than the short isoform, according to the two replicates of our immunodepletion experiment, respectively.”
Major conclusion B)- SATB1 regulates transcription and splicing.
This was also shown previously and in this paper they show the close proximity of the transcription site and SATB1 foci by microscopy. Hexanediol treatment which lead to loss of colocalization between FU foci and SATB1 is also taken as an evidence in regulation of transcription is not right as the transcription foci itself can be dissolved using 1,6 Hexanediol. Although the rate of transcription is not measured quantitatively.
As mentioned in comment #3 (page 29) of this Reviewer, unfortunately there is no better tool to investigate these questions in primary cells than using microscopy approaches in conjunction with hexanediol treatment. However, we should also note that there is an accompanying manuscript from our group that is currently being under revision in another journal (preprint available: Zelenka et al., 2021; https://doi.org/10.1101/2021.07.09.451769). In the preprint manuscript, we showed that: 1. the long SATB1 isoform binding sites have increased chromatin accessibility than what expected by chance (Fig. 3b), 2. there is a drop in chromatin accessibility at SATB1 binding sites in Satb1 cKO mouse (Fig. 3c) and 3. this drop in chromatin accessibility is especially evident at the transcription start sites of genes (Supplementary Fig. 1i)
We believe that, together these data suggest a direct involvement of SATB1 in transcription regulation. Also note the vast transcriptional deregulation that occurs in Satb1 cKO T cells, affecting the expression of nearly 2000 genes (Fig. 2f, this revised manuscript). That is why we believe that the co-localization analysis, using super-resolution microscopy, presented in Fig. 2c and quantified in Fig. 3g, represents a nice additional support to our claims. Moreover, in the revised version of the manuscript we now present a positive correlation between SATB1 binding and deregulation of splicing (Supplementary Fig. 4d) which also supports its direct involvement in the regulation of transcriptional and co-transcriptional processes.
In the revised version of the manuscript we have made this clear in Lines 182-194: “Satb1 cKO animals display severely impaired T cell development associated with largely deregulated transcriptional programs as previously documented19,37,38. In our accompanying manuscript19, we have demonstrated that long SATB1 isoform-specific binding sites (GSE17344619) were associated with increased chromatin accessibility compared to randomly shuffled binding sites (i.e. what expected by chance), with a visible drop in chromatin accessibility in Satb1 cKO. Moreover, the drop in chromatin accessibility was especially evident at the transcription start site of genes, suggesting that the long SATB1 isoform is directly involved in transcriptional regulation. Consistent with these findings and with SATB1’s nuclear localization at sites of active transcription, we identified a vast transcriptional deregulation in Satb1 cKO with 1,641 (922 down-regulated, 719 up-regulated) differentially expressed genes (Fig. 2f). Specific examples of transcriptionally deregulated genes underlying SATB1-dependent regulation are provided in our accompanying manuscript19. Additionally, there were 2,014 genes with altered splicing efficiency (Supplementary Fig. 4d-e; Supplementary File 3-4). We should also note that the extent of splicing deregulation was directly correlated with long SATB1 isoform binding (Supplementary Fig. 4d).”
Major conclusion C)-Post transcriptional modification is important for SATB1 function.
This point is just barely touched upon in the last figure of the paper
We would not call the identification of the novel phosphorylation site as a main conclusion of our manuscript. Though, it is already known that posttranslational modifications of SATB1 are important for its function as they can function as a molecular switch rendering SATB1 into either an activator or a repressor (Kumar et al., 2006; https://doi.org/10.1016/j.molcel.2006.03.010).
In the revised manuscript, we support the effect of serine phosphorylation on the DNA binding capacity of SATB1 by another experiment. We have performed DNA affinity purification experiments utilizing primary thymocyte nuclear extracts treated with phosphatase (Supplementary Fig. 7b). We found that SATB1’s capacity to bind DNA (RHS6 hypersensitive site of the TH2 LCR) is lost upon treatment with phosphatase (Supplementary Fig. 7c). These results are in line with the data presented in Supplementary Fig. 7d, indicating the lost ability of SATB1 to bind DNA upon mutating the discovered phosphorylation site S635. Given the importance of posttranslational modifications of proteins on LLPS, we found it relevant to include it in our manuscript. Even more so, when we identified SATB1 aggregation, upon mutation of this phospho site (Fig. 6d).
Overall I find that the major conclusion-point A and B, is based on very indirect experiments and needs much more convincing data and the role of SATB1 LLPS in cells should be demonstrated more rigorously. And conclusion C is barely described and needs a lot more cell biological and genetic evidence.
One of the major assets of our work is that most of our data are based on the analysis of primary murine T cells and thus investigating the biological roles of the endogenous SATB1 protein, under physiological conditions. We apologize that we did not make it clear to this Reviewer, that our system has certain inherent limitations due to the utilization of primary cells.
I do not recommend publishing the paper in current state. The story needs much more experiment to convincingly prove the major conclusions. Further, the MS needs more careful thinking and presentation to make it streamlined.
We hope that in the revised version we have significantly improved the quality of our manuscript by implementing the suggested changes.
Minor comments: One of the major flaw of the paper is the use too many techniques without proper explanation. E.g. use of STED and RAMAN microscopy need controls and explanation on what is being quantified. The use of Raman microscopy to quantify the nuclear environment of nucleus is not related to the chromatin organization or LLPS of SATB1 at all. And no information is provided at all which aspect of nuclear organization is being measured in Raman and what it means for the LLPS of SATB1.
We do provide quite a thorough explanation of Raman spectroscopy and the underlying quantification in Lines 224-231: “we employed Raman spectroscopy, a non-invasive label-free approach, which is able to detect changes in chemical bonding. Raman spectroscopy was already used in many biological studies, such as to predict global transcriptomic profiles from living cells42, and also in research of protein LLPS and aggregation43–47. Thus we reasoned that it may also be used to study phase separation in primary T cells. We measured Raman spectra in primary thymocytes derived from both WT and Satb1 cKO animals and compared them with spectra from cells upon 1,6-hexanediol treatment. Principal component analysis of the resulting Raman spectra clustered the treated and non-treated Satb1 cKO cells together, while the WT cells clustered separately (Fig. 3h).” We also do provide controls as the method was performed on both treated and untreated WT and Satb1 cKO cells.
Regarding the RAMAN spectroscopy experiments we now provide more information on the changes of chemical bonds altered between wild type and Satb1 cKO thymocytes. Following principal component analysis, we have extracted the two main principal components that were used for the clustering of our data. The differences are presented in Supplementary Fig. 5d.
We do realize that RAMAN spectroscopy, although a quite novel approach utilized to study LLPS, has not been used to study LLPS in live cells. If deemed proper we are willing to avoid presenting these results in this manuscript.
Similarly for Hexanediol treatment, duration of treatment is missing. Hexanediol can also dissolve the liquid like transcription foci. And hence a decrease in correlation between SATB1 foci and FU foci cannot be taken as a measure of SATB1 foci connection to transcription alone
The duration of hexanediol treatment was 5 minutes as presented in Line 724 and in the revised version of the manuscript also in Lines 1206-1207. We should also note that additionally, we performed experiments with different hexanediol concentrations and timing varying from 1 minute to 10 minutes with results consistent with the data presented.
It is not very clear how many times the STED or Raman microscopy is done on how many samples and biological replicates. Similarly for RNA sequencing number of samples and description of controls are missing. Also if the sequencing data is made publicly available is not clear.
Data availability is clearly stated in Lines 506-509: “RNA-seq experiments and SATB1 binding sites are deposited in Gene Expression Omnibus database under accession number GSE173470 and GSE173446, respectively. The other datasets generated and/or analyzed during the current study are available upon request.”
The Reviewer’s token is “wjwtmeeeppovzqx”.
RNA sequencing was performed in a biological triplicate for each genotype as stated in the GEO repository and now also in Line 566 of the revised manuscript.
In Lines 180-181, we also state that it was performed on Satb1 cKO animals and WT mice as a control: “we performed stranded-total-RNA-seq experiments in wild type (WT) and Satb1fl/flCd4-Cre+ (Satb1 cKO) murine thymocytes”.
In Lines 739-740, we now also state that all imaging approaches were performed on at least two biological replicates (different mice) and please also note the fact that all findings were based on data from both STED and 3D-SIM methods, allowing to minimize detection of artifacts. In the Raman spectroscopy figure, each point represents measurements from an individual cell and for each condition we used 2-5 biological replicates (Lines 831-832 & Line 1169).
Similarly, in Lines 129-132 we provided a quite detailed description of differences between STED and 3D-SIM, even though these techniques are not that rare as Raman spectroscopy in biology research.
Additional control is needed to report the resolution limit of Superresolution techniques-STED and 3D-SIM systems used by them.
We have already provided this information in our reply to comment #1 of this Reviewer (pages 6-7): In the revised version of the manuscript, we have specified the resolution of our systems, for STED in Lines 745-746: ”This system enables super-resolution imaging with 35 nm lateral and 130 nm axial resolution.” and for SIM in Lines 759-761: “Images were acquired over the majority of the cell volume in z-dimension with 15 raw images per plane (five phases, three angles), providing ~120-135 nm lateral and ~340-350 nm axial resolution for 488/568 nm lasers, respectively.” The resolution of our systems is routinely verified by the following methods: The resolution of our OMX (SIM-3D) system was tested using ARGO-SIM slide containing a pattern of 36 µm long lines with gradually increasing spacing ranging from (left to right) 0 to 390 nm, with a step of 30 nm (Fig. 1 below). Our SIM system was able to clearly resolve two lines separated by 120 nm.
Would be very helpful if the zonation was plotted for the FluoroUridine (FU) also to show that Zone1 (heterochromatin) is completely depleted of FU, and is present in other regions.
In the revised version of the manuscript, we performed the suggested analysis and in Supplementary Fig. 3a we now show that indeed FU is significantly less localized to Zone 1 (heterochromatin) and has the most abundant localization in Zones 3 and 4, similar to the localization of SATB1 protein, as demonstrated in Fig. 2b.
Scale bar needed figure 3d
In the revised version of the manuscript, we included scale bars which are both 0.5 µm (line 1213).
Perfectly rounded SATB1 foci- this does not mean LLPS. For LLPs measurement, protein condensate dynamics measurement by FRAP or fusion experiments is required. What is the size of condensates? and cellular concentration of SATB1? Will SATB1 undergo LLPS in vitro at similar concentrations? does SATB1 interact with DNA or RNA to undergo LLPS ?
We toned down this sentence which now reads: “Here we demonstrated its connection to transcription and found that it forms spherical speckles (Fig. 1g), markedly resembling phase separated transcriptional condensates. (Lines 200-202)”.
Moreover, as explained in earlier replies to comments of this Reviewer, we cannot perform FRAP on primary murine T cells without generating a new mouse line. We did, however, use FRAP and other in vitro approaches including visualization of droplet fusion in ex vivo experiments utilizing cell lines. Moreover, we are willing to demonstrate the LLPS properties of SATB1 on in vitro purified SATB1 protein as indicated in the suggested experiment of Point#4 (page 2).
After careful reading of the MS I conclude that the main conclusions of the paper are very preliminary and need much more detailed experiments. So does not qualify to get published at all at this stage.
**Reviewer #1 (Significance)**:
The present manuscript tries to connect the phase separation of SATB1 to understanding the mechanism of SATB1 function in cells. One of the major hallmarks of phase separation is dynamic, liquid-like behaviour and in absence of these measurements, it is very difficult to say that the current manuscript has made any contribution to showing that SATB1 can phase separate.
The presence of 2 isoforms of SATB1 is a novel finding and the paper could have focused more on this. E.g. elucidate expression of the isoform during thymocyte development and maturation.
As a reviewer my expertise are cell biology experiments, microscopy, in vitro reconstitution assays, RNA binding proteins, RNA and RBP condensate formation. And I feel that the reconstitution experiments are an important tool for understanding phase behaviour of proteins and also to gauge if this behaviour can occur or not in cellular concentration and conditions.
I do not have sufficient expertise in Raman microscopy and hence the information provided in the MS on this part was not enough to understand the experiment and conclusions drawn from it.
**Reviewer #2 (Evidence, reproducibility and clarity)**:
The authors have reported the existence of a 'long' SATB1 isoform which also undergoes LLPS. The authors tried to draw multiple comparisons and pointed out distinction between phase properties of SATB1 isoforms. The authors also touch upon two functional roles of SATB1. Although a wide array of assays are used, the data presented and hence the manuscript makes multiple transitions into disparate hypotheses without diving deep into a single hypothesis. As a result, the connections drawn are unclear, and do not converge at best. The authors have used number of techniques, however, the results do not support their conclusions and they appear hastily drawn. It is not clear why the authors jump from one context to the other, discussing LLPS first, then transcription, splicing, post-translational modification and finally cancer. The link between all of these isn't clear and not fully supported by data. It appears that the authors wish to focus on Satb1's physiological role in development, hence the data on breast cancer is confusing. Thus, this work suffers from multiple pitfalls. Specific comments are given below:
Major comments 1. Importantly, in Fig 1d, there is no statistics shown. There is no mention of number of replicates as well in the legends. Proper statistical evaluation is critical for interpreting this result.
Please note that Fig. 1d only serves as a control to the sequencing experiment in Fig. 1b. In Line 566, we now state that for the RNA-seq: “A biological triplicate was used for each genotype.” To validate these data, we further designed a RT-qPCR experiment which was performed on three technical replicates from a male and female mouse. We now state this in Line 636. For the low number of samples, statistical tests are not accurate but we still added t test into the figure Fig. 1d and specified it also in the figure legend in Line 1169-1170.
- Figure 1f presents one of the weakest evidences in the manuscript. There are a number of corrections needed. Firstly, being their major and only validation figure for their custom antibody, the immunoblot is not clean, bands are fuzzy. Importantly, as the authors claim that the antibody is highly specific to 'long' SATB1, after the IP there should be only a single band (like input) of Satb1 long. But that does not seem to be the case, rather an array of bands are visible below (lane 2 top panel). This could easily mean that the shorter isoforms or non-specific protein bands are also pulled down with the 'long' form specific antibody. Therefore, raising a critical concern regarding the specificity of the antibody.
• The long antibody was raised in mice inoculated with the extra peptide present in the long isoform only. Therefore, the capacity of this antibody precipitating the shorter isoforms, which do not express the sequence of the extra peptide (EP, Figure 1a) in not possible. • We have repeated the immunodepletion experiment and we now provide the results in Fig. 1f and Supplementary Fig. 1b. The western blot in Fig. 1f is now cleaner and supports quite convincingly the presence of a long SATB1 isoform. Given the lack of isoform-specific knockouts which we could utilize to immunoprecipitate or detect the different isoforms in a single cell (or cell population), the utilized approach of immunodepletion and subsequent western blotting is the approach we thought of implementing. • As shown in Fig. 1f and Supplementary Figure 1b, the long isoform SATB1 antibody has the capacity to recognize the long isoform in murine thymocyte protein extracts but not the short SATB1 isoform (please compare lane 3 in the two western blots utilizing either the antibody for the long isoform -top panel - or the antibody that detects both isoforms (lower panel). • We have performed Immunofluorescence experiments utilizing the antibody detecting the long SATB1 isoform in thymocytes isolated from either C57BL/6 or Satb1 cKO mice. The antibody is specific to the SATB1 protein since there is no signal in immunofluorescence experiments utilizing the knockout cells (Supplementary Figure 1c). • We have performed Immunofluorescence experiments utilizing thymocytes and the antibody detecting the long SATB1 or a commercially available antibody detecting all SATB1 isoforms. The pattern of SATB1 subnuclear localization is similar for both antibodies (Supplementary Figure 1e). • In our accompanying revised manuscript Zelenka et al., 2022 (https://doi.org/10.1101/2021.07.09.451769), we provide yet another piece of evidence, consisting of bacterially expressed short and long SATB1 protein isoforms detected by western blot using either the long isoform-specific or the non-selective all SATB1 isoforms antibodies. • Regarding the additional bands detected in the immunoprecipitation experiment presented in the original Supplementary Figure 1b (lane 2), it is not surprising that additional bands appear in a sample of protein extracts that is used for several hours for the immunoprecipitation experiments, while the “input” sample simply denotes protein extract that is frozen at -80oC right after the preparation of protein extracts until use. It is well-established that SATB1 is the target of proteases which might as well be active during the immunoprecipitation steps (2 consecutive immunoprecipitation steps take place). Therefore, the immunoprecipitated material cannot necessarily be a copy of the input material displaying a single protein band even if protease inhibitors are included in the buffers.
Taken together the experiments described here we showed that the antibody raised against the extra 31 aa long peptide, present only in the long SATB1 isoform, is specific for this isoform.
- Related to Fig. 2 a, the authors state on Pg 5, '....the euchromatin and interchromatin regions (zones 3 & 4, Fig. 2a, b).' Although the DAPI correlation seems clear, there is no mention on how they reached the above said correlation. They should at least show a parallel speckle staining for HP1 or signature modification such as H3K4me9 STEDs for making supporting such a claim. DAPI alone is not sufficient. The authors should rectify the text thoroughly for many such interpretations without validation/reference or provide relevant data.
This is a great suggestion we have again taken under consideration and we added the following experiments and the appropriate changes in the revised version of our manuscript. • We modified the text and added a reference to Miron et al., 2020 (https://doi.org/10.1126/sciadv.aba8811) supporting our claims regarding SATB1 localization in relation to DAPI staining. • We have also added new microscopy images for HP1, H3K4me3 and fibrillarin staining and quantified the localization of FU-stained sites of active transcription in nuclear zones, to further support our claims. • This whole modified part in Lines 139-167 then reads: “ “The quantification of SATB1 speckles in four nuclear zones, derived based on the relative intensity of DAPI staining, highlighted the localization of SATB1 mainly to the regions with medium to low DAPI staining (zones 3 & 4, Fig. 2a, b). A similar distribution of the SATB1 signal could also be seen from the fluorocytogram of the pixel-based colocalization analysis between the SATB1 and DAPI signals (Supplementary Fig. 2a). SATB1’s preference to localize outside heterochromatin regions was supported by its negative correlation with HP1β staining (Supplementary Fig. 2b). Localization of SATB1 speckles detected by antibodies targeting all SATB1 isoforms and/or only the long SATB1 isoform, revealed a significant difference in the heterochromatin areas (zone 1, Fig. 2b), where the long isoform was less frequently present (see also Fig. 2a and Fig. 3c). Although, this could indicate a potential difference in localization between the two isoforms, due to the inherent difficulty to distinguish the two based on antibody staining, we refrain to draw any conclusions. The prevailing localization of SATB1 corresponded with the localization of RNA-associated and nuclear scaffold factors, architectural proteins such as CTCF and cohesin, and generally features associated with euchromatin and active transcription32. This was also supported by colocalization of SATB1 with H3K4me3 histone mark (Supplementary Fig. 2c), which is known to be associated with transcriptionally active/poised chromatin. Given the localization of SATB1 to the nuclear zones with estimated transcriptional activity32 (Fig. 2b, zone 3), we investigated the potential association between SATB1 and transcription. We unraveled the localization of SATB1 isoforms and the sites of active transcription labeled with 5-fluorouridine. Sites of active transcription displayed a significant enrichment in the nuclear zones 3 & 4 (Supplementary Fig. 3a), similar to SATB1. As detected by fibrillarin staining, SATB1 also colocalized with nucleoli which are associated with active transcription and RNA presence (Supplementary Fig. 3b). Moreover, we found that the SATB1 signal was found in close proximity to nascent transcripts as detected by the STED microscopy (Fig. 2c). Similarly, the 3D-SIM approach indicated that even SATB1 speckles that appeared not to be in proximity with FU-labeled sites in one z-stack, were found in proximity in another z-stack (Supplementary Fig. 3c). Additionally, a pixel-based colocalization of SATB1 and sites of active transcription is quantified later in the text in Fig. 3g, supporting their colocalization.”
- The authors mention, '...of the different SATB1 isoforms, uncovered by the use of the two different antibodies, relied in the heterochromatin areas (zone 1), where the long isoform was less frequently...' There is no supporting figure number mentioned. The authors need to show a zone-by-zone comparison images for 'all iso' vs 'long' iso of SATB1. Just to reiterate, there is a need for a heterochromatin mark to unambiguously call out the distinction.
We should remind that there is an inherent difficulty to accurately compare localization of short and long SATB1 isoforms in primary cells, especially due to the lack of Satb1 isoform-specific knockout mice. There is no way to detect only the short isoform in these primary cells as there are only antibodies targeting the long or all SATB1 isoforms. Therefore, we cannot set up additional experiments probing these questions.
In line with this, in the revised version of the manuscript, we toned down our statements regarding the differential localization of the two isoforms in primary cells. We only refer to it as an indication and we support it by adding references to the relevant figures. This part now reads: “Localization of SATB1 speckles detected by antibodies targeting all SATB1 isoforms and/or only the long SATB1 isoform, revealed a significant difference in the heterochromatin areas (zone 1, Fig. 2b), where the long isoform was less frequently present (see also Fig. 2a and Fig. 3c). Although, this could indicate a potential difference in localization between the two isoforms, due to the inherent difficulty to distinguish the two based on antibody staining, we refrain to draw any conclusions. (Lines 145-150)”
- On the same lines, '....Given the localization of SATB1 to the nuclear zones with estimated transcriptional activity (Fig. 2b, zone 3)....' How was the region labelled as transcriptionally active? For the statistical analysis of speckle count for the two antibodies' staining, the claim posited is a bit bigger. This could simply be true for that cell. The authors thus need to statistically analyse the speckle counts for multiple cells. This needs to be done for all imaging statistics done in multiple figures throughout the manuscript.
As mentioned in our reply to the two previous comments of this Reviewer, transcriptional activity in relation to the nuclear zonation is well established in the literature. To make this clear, we have now added the reference to Miron et al., 2020 (https://doi.org/10.1126/sciadv.aba8811) supporting our claims and additionally we have also included HP1, H3K4me3 and fibrillarin staining and quantification of FU signal in the nuclear zones. Moreover, it is not clear to which particular cell the comment refers to. The presented dots in Fig. 2b represent individual cells and the relative proportions of speckles in each nuclear zone are plotted on the y axis. In the revised version of the manuscript, we added into the figure the number of cells scored and we adapted the figure legend so that it is absolutely clear that we have analyzed multiple cells:
“Nuclei of primary murine thymocytes were categorized into four zones based on the intensity of DAPI staining and SATB1 speckles in each zone were counted. Images used represented a middle z-stack from the 3D-SIM experiments. The graph depicts the differences between the long and all SATB1 isoforms’ zonal localization in nuclei of primary murine thymocytes. (Lines 1189-1193)”
- For figure 2c. the authors have used 5 Fluorouridine for nascent RNA speckles. 5FU is known to have a spread signal type (with strong association to nucleolus as well). This is not the case for the image presented 2c. The authors should resolve this by showing different sets of images.
Developing and naive T cells are very unique in terms of their metabolic features and thus they should not be directly compared with other cell types. Therefore, we would not expect to see such a spread FU pattern as previously shown for other cell types. Having said that, we could not find any reference publication that utilized super-resolution microscopy to detect localization of FU-stained sites of active transcription in developing primary T cells. However, we performed additional immunofluorescence experiments to demonstrate the colocalization or its lack between SATB1 and HP1 (Supplementary Fig. 2b), H3K4me3 (Supplementary Fig. 2c) and fibrillarin (Supplementary Fig. 3b). Moreover, we provide additional regions of SATB1 and FU staining in Supplementary Fig. 3c. The modified text reads:
“We unraveled the localization of SATB1 isoforms and the sites of active transcription labeled with 5-fluorouridine. Sites of active transcription displayed a significant enrichment in the nuclear zones 3 & 4 (Supplementary Fig. 3a), similar to SATB1. As detected by fibrillarin staining, SATB1 also colocalized with nucleoli which are associated with active transcription and RNA presence (Supplementary Fig. 3b). Moreover, we found that the SATB1 signal was found in close proximity to nascent transcripts as detected by the STED microscopy (Fig. 2c). Similarly, the 3D-SIM approach indicated that even SATB1 speckles that appeared not to be in proximity with FU-labeled sites in one z-stack, were found in proximity in another z-stack (Supplementary Fig. 3c). Additionally, a pixel-based colocalization of SATB1 and sites of active transcription is quantified later in the text in Fig. 3g, supporting their colocalization. (Lines 157-167)”
- Fig 2 d., the authors have suddenly jumped solely to 'all iso' Satb1 here for IP MS. Is there a reason for that? The authors either need to do this with 'long iso' antibody or remove the analysis from the manuscript as it does not add to their primary aim of the manuscript. Also, the authors have only selectively talked about two clusters? What about chromatin related proteins? It is quite intuitive to have highest enrichment of these given previous literature and even IP MS data by other groups. Thus, it is necessary to revise this thoroughly or remove it.
We appreciate the acknowledgment by the Reviewer that our IP-MS data identified anticipated factors. In the revised version of the manuscript we modified the underlying text to accommodate references to these former findings revealing interactions between SATB1 and chromatin modifying complexes: “Apart from subunits of chromatin modifying complexes that were also detected in previous reports25,33–36, unbiased k-means clustering of the significantly enriched SATB1 interactors revealed two major clusters consisting mostly of proteins involved in transcription (blue cluster 1; Fig. 2d and Supplementary Fig. 4c) and splicing (yellow cluster 2; Fig. 2d and Supplementary Fig. 4c). (Lines 170-174)”
Please note that many subunits of chromatin modifying and chromatin-related complexes are in fact characterized as transcription-related factors, therefore our statements are not in disagreement with the former findings. Note also that we provide Supplementary File 1 & 2 with comprehensive description of our IP-MS data for the readers’ convenience. Please also note that we are the first group to report on the existence of the long isoform. Therefore, we find it absolutely reasonable to perform IP-MS experiment for all SATB1 isoforms which can then be used for a comparison with other publicly available datasets. We believe that there is no contradiction in this experimental setup in relation to the rest of the manuscript. We discuss the two major clusters simply because they are the two major clusters identified as indicated in Fig. 2d. Additionally, in Supplementary Fig. 4c, we provide a comprehensive description of all significantly enriched interactors including their cluster annotation and thus anyone can investigate the data if needed.
- In relation to Fig. 2f, the authors have not mentioned any of the previously published work on Satb1 CD4 specific KO, not even the RNA seq studies the other groups have reported under the same condition. Only an unpublished reference of their own (preprint) is cited. It is imperative to show how much their data corroborates with other published studies. Additionally, what is the binding site status of dysregulated genes?
In the revised version of the manuscript, we have included the references to other studies using the same Satb1 conditional knockout. Moreover, we have clarified the relationship between SATB1 binding and gene transcription. The modified part in Lines 182-194 now reads: “Satb1 cKO animals display severely impaired T cell development associated with largely deregulated transcriptional programs as previously documented19,37,38. In our accompanying manuscript19, we have demonstrated that long SATB1 isoform specific binding sites (GSE17344619) were associated with increased chromatin accessibility compared to randomly shuffled binding sites (i.e. what expected by chance), with a visible drop in chromatin accessibility in Satb1 cKO. Moreover, the drop in chromatin accessibility was especially evident at the transcription start site of genes, suggesting that the long SATB1 isoform is directly involved in transcriptional regulation. Consistent with these findings and with SATB1’s nuclear localization at sites of active transcription, we identified a vast transcriptional deregulation in Satb1 cKO with 1,641 (922 down-regulated, 719 up-regulated) differentially expressed genes (Fig. 2f). Specific examples of transcriptionally deregulated genes underlying SATB1-dependent regulation are provided in our accompanying manuscript19. Additionally, there were 2,014 genes with altered splicing efficiency (Supplementary Fig. 4d-e; Supplementary File 3-4). We should also note that the extent of splicing deregulation was directly correlated with long SATB1 isoform binding (Supplementary Fig. 4d).”
- In context of Figure 3a and b, the authors write .'...The long SATB1 isoform speckles evinced such sensitivity as demonstrated by a titration series with increasing concentrations of 1,6-hexanediol treatment followed...' Whereas it is apparent from the image at least that overall numbers of individual speckles are instead increased at both 2 and 5%. There is although a clear spreading of restricted speckles compared to the controls. The authors should revise their figures to substantiate the associated text. Furthermore, there needs to be 'all iso' SATB1 3D SIM imaging and not just quantitation for comparison. This is also true for panel c in order to demonstrate the effect.
In the revised Fig. 3a we provide new images which better reflect the underlying data analysis. Moreover, in Fig. 3c and Fig. 3d we provide an additional comparison between SATB1 all isoforms and long isoform staining and their changes upon hexanediol treatment, detected by both the 3D-SIM and STED approaches. It is true that upon treatment, there tend to be more speckles, however these are much smaller as they are gradually being dissolved. Depending on the treatment duration, the cells are swollen which is reflected in increased spreading of speckles. Nevertheless, the nuclear size was considered in all the quantification analyses. We believe that the new images provide better evidence of SATB1’s sensitivity to hexanediol treatment.
- Fig. 3 d also does not clearly demonstrate what the authors have claimed '...hexanediol treatment highly decreased colocalization between...' The figure shows at best decreased signal intensity for both SATB1 and FU. We suggest that the authors should give a statistical analysis as well for the colocalization points between the two using multiple source images. Lastly, the two images shown (control and treated), there seems to be a clearly visible magnification difference. The authors should clarify this.
• In the revised version of the manuscript in Figure 3d, we have provided scale bars, which are both 0.5 µm (line 1213). The difference observed by this Reviewer is actually the main reason why we provided this image. Figure 3d demonstrates that upon hexanediol treatment, the speckles are mostly missing or significantly reduced in size, for both FU and SATB1 staining. • Moreover, the suggested statistical analysis is also provided – in Figure 3e. In Figure 3e, we performed pixel-based colocalization analysis which is a method that allows both quantification and statistical comparison of colocalization between two factors and between different conditions. Please note especially the decreased colocalization between long SATB1 isoform and FU-stained sites of active transcription in the left graph, which is in agreement with our claims in the manuscript. • Moreover, our data are compared to a negative control, i.e. 90 degrees rotated samples, which is a common method in colocalization experiments as described for example in Dunn et al., 2011 (https://doi.org/10.1152/ajpcell.00462.2010). • Additionally, we provide Costes’ P values which are based on randomly scrambling the blocks of pixels (instead of individual pixels, because each pixel’s intensity is correlated with its neighboring pixels) in one image, and then measuring the correlation of this image with the other (unscrambled) image. Please see Costes et al., 2004 (https://doi.org/10.1529%2Fbiophysj.103.038422) for more details.
- Figure 3f. The authors show the PC plot for Raman spectroscopy for phase behaviour due to Satb1. The experiment and its related text seems misinterpreted; the authors write...' ese bonds were probably enriched for weak interactions responsible for LLPS that are susceptible to hexanediol treatment. This shifted the cluster of WT treated cells towards the Satb1 cKO cells. However, the remaining covalent bonds differentiated the WT samples from Satb1 cKO cells......' whereas the clusters are clearly far away in 3D for both WT and KO while being closer to their respective treatments. Which is also intuitive given the sensitivity of Raman spectroscopy. Thus, it is more likely to be treatment effect and KO effect as separate. Treatment of WT leads to KO like spectra is far-fetched. Thus, the authors need to show separate PCs and modify their text thoroughly.
We do not present any 3D graph hence it is not clear what the Reviewer refers to. Please also note that as stated in Lines 817-818, we used a customized Raman Spectrometer. Therefore, this approach allowed us to measure Raman spectra at cellular and even sub-cellular levels. For example, solely by utilizing Raman spectroscopy, we can now distinguish euchromatin and heterochromatin, methylated and unmethylated DNA and RNA, etc. This, together with other reports, such as Kobayashi-Kirschvink et al., 2018 (https://doi.org/10.1016/j.cels.2018.05.015) and Kobayashi-Kirschvink et al., 2022 (https://doi.org/10.1101/2021.11.30.470655), indicate a potential use of Raman in biological research. In our manuscript, we used this method as a supplementary approach, however we do find it noteworthy. We should also emphasize that in the revised Raman spectroscopy Fig. 3h, each point represents measurements from an individual cell and for each condition we used 2-5 biological replicates (Lines 831-832 & Lines 1225-1226). We specifically refer to the principal component 1 (PC1) that differentiates the samples. Therefore, there are certain spectra (representing certain chemical bonding) that allowed us to differentiate between WT and Satb1 cKO. The same type of bonding was then affected when WT samples were treated with hexanediol and we also had controls to rule out the impact of hexanediol on the resulting spectra.
- In Fig 4. b, The authors have shown the propensity of SATB1 N terminus to phase separate using different optodroplet constructs. Although the imaging is clear, why are the regions selected not uniform when comparing various constructs?
We have selected images that would best represent each category. Please note that this was live cell imaging of photo-responsive constructs, thus there are many limitations regarding the area selection. Very often, even the brief time of bright light exposure to localize cells may trigger protein clustering. Upon disassembly, every new light exposure of the same cell then triggers much faster assembly which skews the overall results. It is therefore desired to work fast, while neglecting selection of equally sized cells. Moreover, it is not clear how would the proposed change improve the quality of our manuscript.
- Figure 5a, the disassembly should be shown for 'long' SATB1 as well. On pg 13, the authors write '....cytoplasmic protein aggregation has been previously described for proteins containing poly-Q domains and PrLDs..' no reference given.
• In the revised version of the manuscript, we present the assembly and disassembly for both short and long full length SATB1 optogenetic constructs. To increase clarity, we present the behavior of the short and long isoforms as two separate images in Figure 5a and Figure 5b, respectively. • Moreover, we provided references to the statement regarding aggregation of PrLD and poly-Q-containing proteins in Lines 305-309, which now reads: ”Since protein aggregation has been previously described for proteins containing poly-Q domains and PrLDs8,11,38,39, we next generated truncated SATB1 constructs encoding two of its IDR regions, the PrLD and poly-Q domain and in the case of the long SATB1 isoform also the extra peptide neighboring the poly-Q domain (Fig. 1a and 4a).”
- Fig. 5d, Is there an amino-acid specific reasoning to support the authors claim of the phase behaviour due to extra peptide? They need to show a proper control with equal extra (unrelated) peptide to show the specificity. Are the shorter isoform aggregates responsive to light?
• We have referred to the amino acid composition bias in Fig. 5c. In the revised version of the manuscript, we made this clear by showing the composition bias in the new revised Fig. 5e. The related part of the main text then reads: “Computational analysis, using the algorithm catGRANULE37, of the protein sequence for both murine SATB1 isoforms indicated a higher propensity of the long SATB1 isoform to undergo LLPS with a propensity score of 0.390, compared to 0.379 for the short isoform (Fig. 5d). This difference was dependent on the extra peptide of the long isoform. Out of the 31 amino acids comprising the murine extra peptide, there are six prolines, five serines and three glycines – all of which contribute to the low complexity of the peptide region3 (Fig. 5e).” (Lines 298-304) • Moreover, we should note that the low complexity extra peptide of the long SATB1 isoform directly extends the PrLD and IDR regions as indicated in Fig. 4a and which we now directly state in Lines 304-305: “Moreover, the extra peptide of the long SATB1 isoform directly extends the PrLD and IDR regions as indicated in the Fig. 4a.” • We show in Fig. 4, that the N terminus of SATB1 undergoes LLPS. Since this part of SATB1 is shared by both isoforms, it is reasonable to assume that both isoforms would undergo LLPS. This is also in line with the observed photo-responsiveness of both short and long full length SATB1 isoforms in CRY2 optogenetic constructs in revised Fig. 5a,b, and similar FRAP results for both short and long full length SATB1 isoform constructs transiently transfected in NIH-3T3 cells in the revised Supplementary Fig. 6f. However, the main reason why we think that the difference in LLPS propensity between the isoforms is important is because the long isoform is more prone to aggregate compared to the short isoform, as documented in Fig 5c,f,g and Supplementary Fig. 5f.
- Fig 6c., It is important that authors show the data for NLS+short iso data as well to prove their hypothesis.
As shown in original Figure 5d, the long SATB1 isoform undergoes cytoplasmic aggregation, unlike the short SATB1 isoform (as shown in the same Figure). Therefore, an image of the NLS + short isoform would not be related to our hypothesis. Actually, we wanted to reverse the long SATB1 isoform’s relocation, from the aggregated form in the cytoplasm into the nucleus. Nevertheless, to show the complete picture, in the revised version of the manuscript in Figure 6c, we now provide data for both short and long SATB1 isoforms.
- Fig 6d., The authors claim that mutating a specific P site changes the phase behaviour of the 'short iso'. Does it also increase for the long isoform? The authors need to confirm this in order to verify the effect of a single P site outside of oligomerization domain. ...' phosphorylation status; when phosphorylated it remains diffused, whereas unphosphorylated SATB1 is localized to PML bodies....' This being an important premise, thus should be moved to the results text.
In the revised version of the manuscript, we moved the part regarding PML in the results section, as suggested by the Reviewer. Moreover, we included additional experiments probing the impact of association between PML and two SATB1 full length isoforms on their dynamics. The modified section in Lines 357-368 now reads: “In relation to this, a functional association between SATB1 and PML bodies was already described in Jurkat cells64. We should note that PML bodies represent an example of phase separated nuclear bodies65 associated with SATB1. Targeting of SATB1 into PML bodies depends on its phosphorylation status; when phosphorylated it remains diffused, whereas unphosphorylated SATB1 is localized to PML bodies66. This is in line with the phase separation model as well as with our results from S635A mutated SATB1, which has a phosphorylation blockade promoting its phase transitions and inducing aggregation. To further test whether SATB1 dynamics are affected by its association with PML, we co-transfected short and long full length SATB1 isoforms with PML isoform IV. The dynamics of long SATB1 isoform was affected more dramatically by the association with PML than the short isoform (Supplementary Fig. 7e), which again supports a differential behavior of the two SATB1 isoforms.”
Moreover, given the localization of the discussed phosphorylation site in the DNA binding region of SATB1 we did test its impact on DNA binding as documented in the revised Supplementary Fig. 7d. Additionally, as we have noted in our answer in Major Comment C of this reviewer, to further support the effect of serine phosphorylation on the DNA binding capacity of SATB1 we have performed DNA affinity purification experiments utilizing primary thymocyte nuclear extracts treated with phosphatase (Supplementary Fig. 7b) We found that SATB1’s capacity to bind DNA (RHS6 hypersensitive site of the TH2 LCR) is lost upon treatment with phosphatase (Supplementary Fig. 7c).
- Pg 16,. The authors have tried to explain multiple things (concepts of self-regulation, accessibility) which is quite tangential. There is no inference to Fig 6f., which is showing the opposite to what the authors had postulated. This portion should either be removed or explained with a rationale. The writing also needs to be revised thoroughly in this section. Similarly, the discussion should also be modified.
The rationale for the original Fig. 6f (revised Fig. 6g) was described in great detail in Lines 330-343 of the original manuscript. It is not clear why the Reviewer assumes that it shows the opposite to our hypothesis. As we explained, the increased accessibility allows faster read-through by RNA polymerase, and thus the exon with higher accessibility is more likely to be skipped. The exact relationship is shown in the revised Fig. 6g where the increased accessibility is associated with the expression of the short isoform, whereas the long isoform expression needs lower chromatin accessibility which allows the splicing machinery to act on the specific exon to be included. We reason that these findings are important and relevant because: 1) we suggest a potential regulatory mechanism for the SATB1 isoforms production. This is highly relevant to this manuscript given the fact that this is the first report on the existence of the long SATB1 isoform, and 2) the differential production of the long/short SATB1 isoforms has a potential relevance to breast cancer prognosis. In the revised version of the manuscript we added Fig. 6f, which now indicates the differential chromatin accessibility in human breast cancer patients and accordingly the expression of the long SATB1 isoform are associated with worse patient prognosis as indicated in Fig. 6h and Supplementary Fig. 8a,b. In the revised version of the manuscript, we substantially modified the text in Lines 374-408, to make the relevance of all these conclusions clear. The modified text now reads: “Therefore, we reasoned that a more plausible hypothesis would be based on the regulation of alternative splicing. In our accompanying manuscript19, we have reported that the long SATB1 isoform DNA binding sites display increased chromatin accessibility than what expected by chance (Fig. 3b in 19), and chromatin accessibility at long SATB1 isoform binding sites is reduced in Satb1 cKO (Fig. 3c in 19), collectively indicating that long SATB1 isoform binding promotes increased chromatin accessibility. We identified a binding site specific to the long SATB1 isoform19 right at the extra exon of the long isoform (Fig. 6e). Moreover, the study of alternative splicing based on our RNA-seq analysis revealed a deregulation in the usage of the extra exon of the long Satb1 isoform (the only Satb1 exon affected) in Satb1 cKO cells (deltaPsi = 0.12, probability = 0.974; Supplementary File 4). These data suggest that SATB1 itself is able to control the levels of the short and long Satb1 isoforms. A possible mechanism controlling the alternative splicing of Satb1 gene is based on its kinetic coupling with transcription. Several studies indicated how histone acetylation and generally increased chromatin accessibility may lead to exon skipping, due to enhanced RNA polymerase II elongation48,49. Thus the increased chromatin accessibility promoted by long SATB1 isoform binding at the extra exon of the long isoform, would increase RNA polymerase II read-through leading to decreased time available to splice-in the extra exon and thus favoring the production of the short SATB1 isoform in a negative feedback loop manner. This potential regulatory mechanism of SATB1 isoform production is supported by the increased usage of the extra exon in the absence of SATB1 in Satb1 cKO (Supplementary File 4). To further address this, we utilized the TCGA breast cancer dataset (BRCA) as a cell type expressing SATB150. ATAC-seq experiments for a series of human patients with aggressive breast cancer51 revealed differences in chromatin accessibility at the extra exon of the SATB1 gene (Fig. 6f). In line with the “kinetic coupling” model of alternative splicing, the increased chromatin accessibility at the extra exon (allowing faster read-through by RNA polymerase) was positively correlated with the expression of the short SATB1 isoform and slightly negatively correlated with the expression of the long SATB1 isoform (Fig. 6f). Moreover, we investigated whether the differential expression of SATB1 isoforms was associated with poor disease prognosis. Worse pathological stages of breast cancer and expression of SATB1 isoforms displayed a positive correlation for the long isoform but not for the short isoform (Fig. 6g and Supplementary Fig. 6c). This was further supported by worse survival of patients with increased levels of long SATB1 isoform and low levels of estrogen receptor (Supplementary Fig. 6d). Overall, these observations not only supported the existence of the long SATB1 isoform in humans, but they also shed light at the potential link between the regulation of SATB1 isoforms production and their involvement in pathological conditions.”
- The authors should not draw conclusions based on any data which is not shown '....ed differences in chromatin accessibility at the extra exon of the SATB1 gene (data not shown), suggesting its potential involvement in alternative splicing regulation according to the "kinetic coupling" model...'. This has led to overspeculation and needs correction.
In the revised version of the manuscript, we included the ATAC-seq data from human breast cancer patients in the revised Fig. 6f. The legend of this figure now reads: “Human TCGA breast cancer (BRCA) patient-specific ATAC-seq peaks51 span the extra exon (EE: extra exon; labeled in green) of the long SATB1 isoform. Note the differential chromatin accessibility in seven selected patients, emphasizing the heterogeneity of SATB1 chromatin accessibility in cancer. Chromatin accessibility at the promoter of the housekeeping gene DNMT1 is shown as a control. (Lines 1281-1285)” Accordingly, we have also modified the main text: “ATAC-seq experiments for a series of human patients with aggressive breast cancer68 revealed differences in chromatin accessibility at the extra exon of the SATB1 gene (Fig. 6f). In line with the “kinetic coupling” model of alternative splicing, the increased chromatin accessibility at the extra exon (allowing faster read-through by RNA polymerase) was positively correlated with the expression of the short SATB1 isoform and slightly negatively correlated with expression of the long SATB1 isoform (Fig. 6g).” (Lines 395-339)”
Minor comments: 1. On pg 4, the authors state 'Here, we utilized primary murine T cells, in which we have identified two full-length SATB1 protein isoforms.' Whereas only one 'long' isoform is identified and the other is the canonical version. The authors should correct the statement.
In the revised version of the manuscript, we modified this statement as follows: ”In this work, we utilized primary developing murine T cells, in which we have identified a novel full-length long SATB1 isoform and compared it to the canonical “short” SATB1 isoform.” (Lines 64-66)”
- Fig. 1 a , Is there a specific reason to generate a custom-made antibody for 'all' SATB1, using similar regions that are already commercially available. This becomes redundant otherwise, because there is no apparent difference in detection compared to the commercial one (Suppl. Fig 1a). Antibody generation strategy (1a) should be moved to supplementary. Additionally, authors have obtained the custom antibodies from a commercial source, therefore, the text should reflect the same alongside relevant details.
The custom-made SATB1 antibody targeting the amino-terminal region of the protein has been developed in order to be utilized for detecting the native form of the protein. Unlike commercially available antibodies raised against either short peptides or denatured forms of the protein we have utilized the native form of the amino-terminal part of the protein for raising this antibody. To be honest, this antibody has been raised in order to be utilized in ChIP-seq experiments since no commercially available antibody is of high quality for this approach. Moreover, the original Figure 1a was utilized in order to provide an overview of the SATB1 protein structure which is highly relevant to understand its biophysical properties and not for presenting the strategy for raising a custom-made antibody for SATB1.
- Fig 3e: what is the control used here? In their Pearson correlation analysis, there seem to be significant reduction in control sets as well upon treatment. This needs to be clarified.
We used scans rotated by 90° which served as a negative control, as stated in Line 769: “SATB1 scans rotated by 90° served as a negative control for the colocalization with FU.” Note that this is a commonly used control in colocalization experiments as described for example in Dunn et al., 2011 (https://doi.org/10.1152/ajpcell.00462.2010).
Additionally, we provide Costes’ P values which are based on randomly scrambling the blocks of pixels (instead of individual pixels, because each pixel’s intensity is correlated with its neighboring pixels) in one image, and then measuring the correlation of this image with the other (unscrambled) image. Please see Costes et al., 2004 (https://doi.org/10.1529%2Fbiophysj.103.038422) for more details. Moreover, it was actually anticipated to see a decrease in colocalization upon hexanediol treatment even in the negative control, as hexanediol significantly reduces both SATB1 and FU speckles as established in Fig. 3a-d.
- Pg 10, the authors claim that '..., thus we reasoned that it may also be used to study phase separation...' But there have been numerous reports starting from 2018, which have utilized this technique in corelation to phase behaviour (albeit individual proteins). The authors should include proper citations as they are extending an idea from the same field to their specific need.
In the revised version of the manuscript, we included relevant citations to support the use of Raman spectroscopy in LLPS research: “Raman spectroscopy was already used in many biological studies, such as to predict global transcriptomic profiles from living cells42, and also in research of protein LLPS and aggregation43–47. Thus we reasoned that it may also be used to study phase separation in primary T cells.” (Lines 225-228)”
- For Fig 5b, there should be a comparative image for 'short' isoform.
In the revised Figure 5c we have included a comparative image for the short SATB1 isoform.
- In the context of Figure 5c, the authors claim ...' Note also the higher LLPS propensity of the human long SATB1 isoform compared to the murine SATB1...' Why suddenly human and mouse comparisons are drawn? This figure should be moved to supplementary.
The comparison between the human and mouse SATB1 isoforms has been implemented because it is relevant for our claims regarding the increased SATB1 aggregation in human cells in relation to the revised Fig. 6f,g,h and Supplementary Fig. 6c,d. This is also discussed in Lines 479-482, which read: “This is particularly important given the higher LLPS propensity of the human long SATB1 isoform compared to the murine SATB1 (Fig. 5d). Therefore, human cells could be more susceptible to the formation of aggregated SATB1 structures which could be associated with physiological defects.”
**Reviewer #3 (Evidence, reproducibility and clarity):**
Zelenka et al., focus on a T cell genome-organizing protein, SATB1, to show that SATB1 undergoes liquid liquid phase-separation (LLPS), and distinct isoforms confer different LLPS-related biophysical properties. They generate a long-isoform specific antibody and conduct several experiments to test for LLPS and compare LLPS properties between the long-isoform relative to the whole SATB1 protein population. Given that SATB1 plays important roles in T cell development and in cancer, interrogating SATB1 biophysical properties is an important question. However, there are multiple problems with the experimental setup and data that weaken their support of the conclusions. I will detail some of the major issues below:
Regarding phase-separation There are several assays to determine whether a protein undergoes LLPS. 1. One of the first the authors address is the spherocity or roundness. Indeed, formation of spherical droplets is one evidence of the liquid nature of a protein. However, the authors use fixed preparations (which can introduce artifacts), not free-floating protein, and determine roundness by showing a 2D image. Roundness should take into account the diffraction-limits of fluorescent imaging, as many structures can be imaged to appear round by the detector. There are quantifiable measurements that can be taken on 3D images to show roundness. This would best be shown using non-fixed protein.
• We thank this Reviewer for several insightful comments. Although, we agree with most of them, we should highlight the main goal of our manuscript, i.e. to investigate the SATB1 protein with an emphasis on its physiological roles in primary developing murine T cells. We highlight this already in the introduction in Line 64 “In this work, we utilized primary developing murine T cells,...” and mainly also in the respective part of the result section: “To probe differences in phase separation in mouse primary cells, without any intervention to SATB1 structure and expression, we first utilized 1,6-hexanediol treatment, which was previously shown to dissolve the liquid-like droplets34.(Lines 203-205)”
• We believe that this is a very important aspect of our study that should not be overlooked. The majority of proteins perhaps behave differently under physiological and in vitro conditions. However, due to the extensive post-translational modifications affecting the properties of SATB1, its completely different localization patterns between primary developing T cells and other cell types but especially cell lines and many other aspects, it was of utmost importance to focus our research on primary T cells. Unfortunately, this was accompanied with multiple difficulties, such as that we have to use fixed cells as this is the only way to visualize SATB1 in these cells. Alternatively, one could create a new mouse line expressing a fluorescently tagged SATB1 protein, but this is beyond the scope of our work.
• However, we should also note that many LLPS-related studies do not pay any focus on primary physiological functions of proteins and they simply focus on the investigation of protein’s artificial behavior in in vitro conditions. Having said that, we too extended our experiments in primary cells to the ex vivo studies in cell lines to further support our claims. In these experiments, we utilized live cell imaging in Fig. 4-6, quantified the spherocity in Supplementary Fig. 6, showed the ability of speckles to coalesce in Fig. 4c and also used FRAP in Fig. 4f and also in the revised version of the manuscript in Supplementary Figure 6f. Moreover, we should note that most of these experiments were designed and performed during 2017 and 2018 conforming with the standards. We are well aware of the progress in the field and impact of fixation on LLPS, as described in Irgen-Gioro et al., 2022 (https://doi.org/10.1101/2022.05.06.490956), but after over seven months of review process in another journal we also believe that these aspects should be considered not to delay further progress of the SATB1 field.
Regarding the isoform specificity of SATB1 biophysical properties 1. The authors generate a long isoform-specific antibody. However, the western blot is not convincing that this is indeed specific to the long isoform as there is a rather large smear. Can this be improved with antibody preabsorption? Since this is a key reagent for the manuscript, improvement in antibody quality is essential.
The custom-made antibody for the long isoform has been raised against the unique 31 amino acids long peptide present in the long SATB1 isoform. The polyclonal serum has undergone affinity chromatography utilizing the immobilized peptide (antigen) to purify the antibody. In the revised version of the manuscript we have included another immunodepletion experiment with cleaner bands (Fig. 1f). Moreover, please read our answer to Major comment #2 of Reviewer 1 that follows: • The long antibody was raised in mice inoculated with the extra peptide present in the long isoform only. Therefore, the capacity of this antibody precipitating the shorter isoforms, which do not express the sequence of the extra peptide (EP, Figure 1a) in not possible.
• We have repeated the immunodepletion experiment and we now provide the results in Fig. 1f and Supplementary Fig. 1b. The western blot in Fig. 1f is now cleaner and supports quite convincingly the presence of a long SATB1 isoform. Given the lack of isoform-specific knockouts which we could utilize to immunoprecipitate or detect the different isoforms in a single cell (or cell population), the utilized approach of immunodepletion and subsequent western blotting is the approach we thought of implementing.
• As shown in Fig. 1f and Supplementary Figure 1b, the long isoform SATB1 antibody has the capacity to recognize the long isoform in murine thymocyte protein extracts but not the short SATB1 isoform (please compare lane 3 in the two western blots utilizing either the antibody for the long isoform -top panel - or the antibody that detects both isoforms (lower panel).
• We have performed Immunofluorescence experiments utilizing the antibody detecting the long SATB1 isoform in thymocytes isolated from either C57BL/6 or Satb1 cKO mice. The antibody is specific to the SATB1 protein since there is no signal in immunofluorescence experiments utilizing the knockout cells (Supplementary Figure 1c).
• We have performed Immunofluorescence experiments utilizing thymocytes and the antibody detecting the long SATB1 or a commercially available antibody detecting all SATB1 isoforms. The pattern of SATB1 subnuclear localization is similar for both antibodies (Supplementary Figure 1e).
• In our accompanying revised manuscript Zelenka et al., 2022 (https://doi.org/10.1101/2021.07.09.451769), we provide yet another piece of evidence, consisting of bacterially expressed short and long SATB1 protein isoforms detected by western blot using either the long isoform-specific or the non-selective all SATB1 isoforms antibodies.
• Regarding the additional bands detected in the immunoprecipitation experiment presented in the original Supplementary Figure 1b (lane 2), it is not surprising that additional bands appear in a sample of protein extracts that is used for several hours for the immunoprecipitation experiments, while the “input” sample simply denotes protein extract that is frozen at -80oC right after the preparation of protein extracts until use. It is well-established that SATB1 is the target of proteases which might as well be active during the immunoprecipitation steps (2 consecutive immunoprecipitation steps take place). Therefore, the immunoprecipitated material cannot necessarily be a copy of the input material displaying a single protein band even if protease inhibitors are included in the buffers.
Taken together the experiments described here we showed that the antibody raised against the extra 31 aa long peptide, present only in the long SATB1 isoform, is specific for this isoform.
- Fig 4 Optodroplet experiment appears to show that the N-terminus of SATB1 can undergo LLPS. The results of this assay show that SATB1 has a domain that can undergo phase-separation in isolation, but it does not show that the protein itself is a phase-separating protein. The FRAP assay methods are not provided by the authors, but this is important, as continued light activation means proteins are continuously forming aggregates, and the bleaching for FRAP should be balanced with the levels of Cry2 activation. A very good description of the methods is described in the original Optodroplet paper: https://www.sciencedirect.com/science/article/pii/S009286741631666X?via%3Dihub#sec4
We should note that we did follow the FRAP protocol provided by the recommended study Shin et al., 2017 (https://doi.org/10.1016/j.cell.2016.11.054). Indeed, these experiments are very tricky to perform and interpret, as every cell expresses slightly different amounts of protein which is directly associated with the different speed of optoDroplet formation, and thus its propensity to aggregate upon overactivation. On the other hand, there need to be continuous activation during the FRAP experiment as the lack of activation laser would result in fast disassembly of the optoDroplets, counteracting the FRAP results. Moreover, the optoDroplets actively move around the cell in all dimensions which makes the accurate measurement of signal intensity really challenging, even with an adjusted pinhole. Therefore, we do not think that FRAP is the best approach to examine the behavior of optoDroplets.
Either way, we have now described the detailed FRAP protocol in Lines 889-898, which read: “For the FRAP experiments, cells were first globally activated by 488 nm Argon laser illumination (alongside with DPSS 561 nm laser illumination for mCherry detection) every 2 s for 180 s to reach a desirable supersaturation depth. Immediately after termination of the activation phase, light-induced clusters were bleached with a spot of ∼1.5 μm in diameter. The scanning speed was set to 1,000 Hz, bidirectionally (0.54 s / scan) and every time a selected point was photobleached for 300 ms. Fluorescence recovery was monitored in a series of 180 images while maintaining identical activation conditions used to induce clustering. Bleach point mean values were background subtracted and corrected for fluorescence loss using the intensity values from the entire cell. The data were then normalized to mean pre-bleach intensity and fitted with exponential recovery curve in Fiji or in frapplot package in R.”
- Description of analyses that authors prefer not to carry out
**Reviewer #1**:
Can they use the all and long isoform antibodies together, then subtract the signal from long isoform to conclude about the localization of the shorth isoform ?
We thank the Reviewer for the suggestion, though given the differential efficiency of antibodies and other limitations of imaging experiments, we do not find the suggested experiment to have a potential to improve the quality of our manuscript. However, we should note that we have performed a pixel-based colocalization experiment between the signal detected by all isoform and long isoform SATB1 antibodies. Fluorocytogram of the pixel-based colocalization, based on 3D-SIM data is provided on the left, with quantified colocalization on the right of the revised Supplementary Fig. 5a.
3) Lack of better staining with antibody against the long and short SATB1 isoforms after treatment with 1,6 Hexanediol. 1,6 Hexanediol treatment can change many other chromatin associated proteins to which SATB1 can be bound to indirectly. This experiment can
We do understand the controversy and difficulties of experiments using 1,6-hexanediol treatment. However, we have to note that there is no better approach available for the investigation of LLPS in our primary murine T cells. We did use alternative approaches in ex vivo experiments, utilizing cell lines to validate our hypothesis without the involvement of 1,6-hexanediol.
**Reviewer #2**:
- The authors mention, '...of the different SATB1 isoforms, uncovered by the use of the two different antibodies, relied in the heterochromatin areas (zone 1), where the long isoform was less frequently...' There is no supporting figure number mentioned. The authors need to show a zone-by-zone comparison images for 'all iso' vs 'long' iso of SATB1. Just to reiterate, there is a need for a heterochromatin mark to unambiguously call out the distinction.
We should remind that there is an inherent difficulty to accurately compare localization of short and long SATB1 isoforms in primary cells, especially due to the lack of Satb1 isoform-specific knockout mice. There is no way to detect only the short isoform in these primary cells as there are only antibodies targeting the long or all SATB1 isoforms. Therefore, we cannot set up additional experiments probing these questions.
In line with this, in the revised version of the manuscript, we toned down our statements regarding the differential localization of the two isoforms in primary cells. We only refer to it as an indication and we support it by adding references to the relevant figures. This part now reads: “Localization of SATB1 speckles detected by antibodies targeting all SATB1 isoforms and/or only the long SATB1 isoform, revealed a significant difference in the heterochromatin areas (zone 1, Fig. 2b), where the long isoform was less frequently present (see also Fig. 2a and Fig. 3c). Although, this could indicate a potential difference in localization between the two isoforms, due to the inherent difficulty to distinguish the two based on antibody staining, we refrain to draw any conclusions. (Lines 145-150)”
- Fig. 6a, The authors wished to see the effect of RNA on Satb1 nuclear localization. This is not related to the main theme of the paper, thus should be moved to supplementary (true for b as well). Importantly, the experiments should be performed with total cells to show the divergence of localization (like the paper the authors referred to) instead of matrix for clarity.
• We did not wish to see the effect of RNA on SATB1 localization. In fact, there is a long history of SATB1 research that is inherently linked with the concept of nuclear matrix, a putative nuclear structure which is highly associated with nuclear RNAs. SATB1 was described many times as a nuclear matrix protein (https://doi.org/10.1016/0092-8674(92)90432-c; https://doi.org/10.1128/mcb.14.3.1852-1860.1994; https://doi.org/10.1074/jbc.272.17.11463; https://doi.org/10.1128/mcb.17.9.5275; https://doi.org/10.1021/bi971444j; https://doi.org/10.1083/jcb.141.2.335; https://doi.org/10.1101/gad.14.5.521; https://doi.org/10.1038/ng1146).
• Moreover, our data discussed in comments 4-7 of this Reviewer, such as i. the localization of SATB1 to the nuclear zones associated with RNA and nuclear scaffold factors (Fig. 2b, Supplementary Fig. 1c), ii. colocalization of SATB1 with actively transcribed RNAs (Fig. 2c, Fig. 3g, Supplementary Fig. 2a, Supplementary Fig. 2c), iii. including its association with nucleoli (Supplementary Fig. 3b), and also iv. its computationally predicted interaction with Xist lncRNA (Agostini et al., 2013; https://doi.org/10.1093/nar/gks968) as a notable factor of nuclear matrix, all suggest that the interaction between RNA and SATB1 is plausible and potentially relevant for its function and/or at least its subnuclear localization. It is relevant even more so, when considering numerous reports on the ability of RNA-binding, poly-Q and PrLD-containing proteins to undergo LLPS https://doi.org/10.1016/j.molcel.2015.08.018; https://doi.org/10.1042/bcj20160499; https://doi.org/10.1016/j.cell.2018.03.002; https://doi.org/10.1016/j.cell.2018.06.006; https://doi.org/10.1093/nar/gkaa681), including RNAs specifically regulating LLPS behavior, especially for poly-Q and PrLD-containing proteins, such as SATB1 (https://doi.org/10.1126/science.aar7366; https://doi.org/10.1126/science.aar7432; https://doi.org/10.1016/j.ceb.2019.03.007; https://doi.org/10.1038/s41598-020-57994-9; https://doi.org/10.1016/j.molcel.2015.09.017; https://doi.org/10.1038/s41598-019-48883-x; https://doi.org/10.1038/s41467-019-11241-6).
• It should also be noted that SAF and various hnRNPs, as the most prominent proteins of nuclear matrix were many times reported to phase separate (https://doi.org/10.1016/j.molcel.2019.10.001; https://doi.org/10.1074/jbc.ra118.005120; https://doi.org/10.1016/j.celrep.2019.12.080; https://doi.org/10.1038/s41467-019-09902-7; https://doi.org/10.1016/j.molcel.2017.12.022; https://doi.org/10.1074/jbc.tm118.001189). All these aspects show that the relation between nuclear matrix, SATB1 and RNA are quite relevant to our manuscript.
• Moreover, in light of the aforementioned information, we believe that it is much clearer to follow the protocol we did – i.e. to remove soluble proteins by CSK treatment and then, upon RNase treatment, extract the released proteins using ammonium sulfate. In an experiment utilizing whole cells, one would need to microinject RNase A into the nucleus, which 1. is very challenging for primary T cells having a radius of 3-5 micrometers, 2. is of low throughput, 3. would not allow for released protein removal which would thus make the results hard to interpret. Please note that in the reference paper, the authors used cell lines overexpressing heterologous GFP-tagged proteins, which is not related to our setup.
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Referee #1
Evidence, reproducibility and clarity
This paper looks at in important nuclear matrix protein SATB1, which is a well known global chromatin organizer and help chromatin loop attach to the nuclear matrix. The paper starts with identification of novel short and long form of SATB1. Both the isoform consist of a prion like low complexity domains, but the long isoform additionally contain an extra EPF domain next the Prion like low complexity domain. The paper reports that in murine cells the long isoform is 3-4 fold more abundant than the short isoform. By using STED microscopy they show SATB1 foci lie next to transcription sites in the nucleus. They conclude by looking at the spherical shape of the SATB1 foci and the susceptibility of SATB1 staining after 1,6 hexanediol treatment that SATB1 forms the small foci in the nucleus due to LLPS. The authors also use RAMAN spectroscopy to conclude a change in nuclear chemical space in absence of SATB1 but without much explanation about which chemical bond or nuclear sub structure change correspond to the change in principal component analysis from Raman spectroscopy. The authors use the light inducible aggregation cyr2 tag with the PrD domain of SATB1 and compare it with the Cry2-FUS-LC domain to conclude that the SATB1 LC domain can undergo LLPS. The authors hint at involvement of RNA and also DNA in the LLPS of the SATB1 but without going into any detail.
The key conclusions of the paper are- A) SATB1 undergoes LLPS. But this conclusion is drawn after correlative experiments as detailed below-
- observation of spherical punctae by STED-which could also seem spherical due to their small size. The resolution limit achieved by the STED microscopy used in this paper is not determined or mentioned clearly.
- No live cell FRAP experiment with fluorescent SATB1 long or short isoform to show that these foci are liquid like
- Lack of better staining with antibody against the long and short SATB1 isoforms after treatment with 1,6 Hexanediol. 1, 6 Hexanediol treatment can change many other chromatin associated proteins to which SATB1 can be bound to indirectly. This experiment can
- Lack of in vitro reconstitution experiments with purified long and short SATB1
- LLPS is strongly coupled to the cellular concentration of the proteins. Authors should quantify the cellular concentration of the long and short isoform in the cells.
Major conclusion B)- SATB1 regulates transcription and splicing.
This was also shown previously and in this paper they show the close proximity of the transcription site and SATB1 foci by microscopy. Hexanediol tretamnt which lead to loss of colocalization between FU foci and SATB1 is also taken as an evidence in regulation of transcription is not right as the transcription foci itself can be dissolved using 1,6 Hexanediol. Although the rate of transcription is not measured quantitatively.
Major conclusion C)-Post transcriptional modification is important for SATB1 function.
This point is just barely touched upon in the last figure of the paper
Overall I find that the major conclusion-point A and B , is based on very indirect experiments and needs much more convincing data and the role of SATB1 LLPS in cells should be demonstrated more rigorously. And conclusion C is barely described and needs a lot more cell biological and genetic evidence.
I do not recommend publishing the paper in current state. The story needs much more experiment to convincingly prove the major conclusions. Further, the MS needs more careful thinking and presentation to make it streamlined.
Minor comments:
One of the major flaw of the paper is the use too many techniques without proper explanation. E.g. use of STED and RAMAN microscopy need controls and explanation on what is being quantified. The use of Raman microscopy to quantify the nuclear environment of nucleus is not related to the chromatin organization or LLPS of SATB1 at all. And no information is provided at all which aspect of nuclear organization is being measured in Raman and what it means for the LLPS of SATB1.
Similarly for Hexanediol treatment, duration of treatment is missing. Hexanediol can also dissolve the liquid like transcription foci. And hence a decrease in correlation between SATB1 foci and FU foci cannot be taken as a measure of SATB1 foci connection to transcription alone
It is not very clear how many times the STED or Raman microscopy is done on how many samples and biological replicates. Similarly for RNA sequencing number of samples and description of controls are missing. Also if the sequencing data is made publicly available is not clear.
Can they use the all and long isoform antibodies together, then subtract the signal from long isoform to conclude about the localization of the shorth isoform ?
Additional control is needed to report the resolution limit of Superresolution techniques-STED and 3D-SIM systems used by them.
Would be very helpful if the zonation was plotted for the FluoroUridine(FU) also to show that Zone1 (heterochromatin) is completely depleted of FU, and is present in other regions.
Scale bar needed figure 3d
Perfectly rounded SATB1 foci- this does not mean LLPS. For LLPs measurement, protein condensate dynamics measurement by FRAP or fusion experiments is required. What is the size of condensates? and cellular concentration of SATB1 ? Will SATB1 undergo LLPS in vitro at similar concentrations? does SATB1 interact with DNA or RNA to undergo LLPS ?
After careful reading of the MS I conclude that the main conclusions of the paper are very preliminary and need much more detailed experiments. So does not qualify to get published at all at this stage.
Significance
The present manuscript tries to connect the phase separation of SATB1 to understanding the mechanism of SATB1 function in cells. One of the major hallmarks of phase separation is dynamic, liquid-like behaviour and in absence of these measurements, it is very difficult to say that the current manuscript has made any contribution to showing that SATB1 can phase separate.
The presence of 2 isoforms of SATB1 is a novel finding and the paper could have focussed more on this. E.g. elucidate expression of the isoform during thymocyte development and maturation.
As a reviewer my expertise are cell biology experiments, microscopy, in vitro reconstitution assays, RNA binding proteins, RNA and RBP condensate formation. And I feel that the reconstitution experiments are an important tool for understanding phase behaviour of proteins and also to gauge if this behaviour can occur or not in cellular concentration and conditions. I do not have sufficient expertise in Raman microscopy and hence the information provided in the MS on this part was not enough to understand the experiment and conclusions drawn from it.
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automatically tag some of it as important
For Outlook, the Flag for Follow-up feature could prove as an equivalent. Atm, there is no AI/Auto prioritization, but this can be achieved using Filters.
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Reviewer #2 (Public Review):
Here Wang et al have studied the role of the actin cytoskeleton in Trichomonas vaginalis pathogenicity with a focus on understanding the role of the actin cytoskeleton in transitioning from fast-moving flagellates to adherent ameboid cells. Intriguingly they determined that the adherent TH17 strain contains more actin and the actin-bundling protein alpha-actinin than the less adherent T1 strain. The adherent strain more readily morphs into the adherent ameboid form which has more polymerized F-actin than the flagellated form. Disruption of actin polymerization with LatB prevents ameboid morphogenesis and blocks adhesion. Although LatB treatment interferes with adhesion the authors show that their relatively short LatB treatments do not alter the distribution of adhesive molecules such as AP, PFO, and CLP on the cell surface.
To understand how actin is being regulated in T. vaginalis the authors pulldown HA-tagged Tvactin and identify interacting partners with mass spectroscopy. They identify TVAG_47023 as a potential protein of interest due to homology with capping protein and name this protein TvFACP. The authors demonstrate that TvFACP can IP actin from cell extracts. They then proceed to purify His-TvFACP and GST-Tvactin to demonstrate direct interaction. Their approach of using bacterial-expressed actin is non-conventional since it is well known that eukaryotic actin requires several chaperones not present in prokaryotes for proper folding. As expected Tvactin was insoluble and was found in inclusion bodies. The authors used urea to solubilize the protein some of which re-folded into soluble protein after buffer exchange. A major concern with this experiment is that the authors did not use any other assay to confirm that their bacterially expressed actin behaved as expected. They should have verified filament formation by negative EM staining or labeled some of the actin for TIRF microscopy assays. Additionally, the 26 kD GST tag has the potential to interfere with actin dynamics which is why most studies remove affinity tags. Alternatively, the authors could have tested binding with commercially available actin. The authors then proceeded to use the purified components to determine the Kd for Tvactin and TvFACP. Intriguingly the authors determine the Kd is lower for G-actin than F-actin indicating that TvFACP preferentially binds to non-filamentous G-actin which is in contrast to canonical capping protein. However, since the quality of this actin is not verified it is not clear that the assay results can be trusted. Despite the preferential association of TvFACP for G-actin in the in vitro assays, localization studies indicate that TvFACP is associated with phalloidin stained structures which indicates that there is an association of TvFACP with filamentous actin structures. Overexpression of TvFACP reduces the ratio of polymerized to unpolymerized actin.
The authors then explore whether TvFACP might have a role in regulating the transition between flagellated trophozoites and ameboid trophozoites. It was determined that TvFACP has a role in preventing F-actin formation in flagellates. The authors then determined that Ser2 is a phosphosite that regulates the association of TvFACP with actin. An S2A mutant that cannot be phosphorylated associates with actin and prevents ameboid morphogenesis while an S2D mutant does not associate with actin or alter morphogenesis. Since TvFACP S2 is a predicted Casein kinase II (CKII) phosphorylation site, the authors tested the ability of the CKII inhibitor TBB to alter phosphorylation and the association of TvFACP with actin. They found that TBB inhibited phosphorylation and increased the association of TvFACP with actin consistent with the S2A point mutation. Although the result is consistent with the alanine and phosphomimetic mutants, the authors used 250uM of inhibitor which could certainly result in off-target results. As a point of comparison, the IC50 for TBB is reported to be 0.5 uM so here the inhibitor was used at 500x the reported IC50, and at this high level the reduction in phosphorylation may be non-specific for CKII.
Overall, the results of the manuscript align to support a role for TvFACP in regulating morphogenesis between fast swimming flagellated trophozoites and slow crawling adherent ameboid trophozoites and points toward a potential signaling pathway that regulates this transition. However, in addition to the two technical issues raised above, the relationship between TvFACP and its binding to F- and G- actin remains incompletely resolved. To determine if Tv F-actin capping protein truly binds F-actin the authors should perform TIRF microscopy to determine if TvFACP would be found at the end of filaments and also reveal the extent to which TvFACP alters actin organization and dynamics.
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stackoverflow.com stackoverflow.com
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MY_PATH=$(cd "$MY_PATH" && pwd) # absolutized and normalized
scripting: finding absolute path
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danallosso.substack.com danallosso.substack.com
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It's available now at https://a.co/4v7H9hZ
This is a rather clever link to the book! It's an Amazon preview page which provides the opening of the book for evaluation.
It doesn't appear to be an affiliate link, but potentially could be.
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www.biorxiv.org www.biorxiv.org
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Author Response
Reviewer 2
The manuscript by Huisjes et al presented an open-source platform for the storage and processing of imaging data, particularly for single-molecule imaging experiments. Compared to sequencing data, which have a more standardized format for data storage, imaging data have more diverse formats due to the fact that different research labs tend to use different instruments and software (either commercial or home-built) for data collection and analysis. Manual input is almost always necessary at certain steps of data analysis. All these create difficulties in data storage and reproducibility. The authors provide a practical solution to this problem by the molecular archive suite, "Mars". This platform is integrated into imageJ/Fiji, and can be used for storing detailed description of experimental settings, performing standard imaging processing steps, and recording manual input information during data analysis. I judge this platform, if fully functional and generalizable, will be very useful to many labs who are using single-molecule imaging methods in the research.
Strength:
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The work presented a fairly user friendly interface (using Fiji directly), and fairly detailed protocol and other documentations in a very nicely designed website. I was able to download and use it based on the tutorial.
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It is integrated very well with Fiji, and some analysis modules are directly from existing Fiji analysis/plugins.
Weakness:
I invited one of my students to co-test the suite. We tried on both Mac and Windows systems, using the example FRET data set described in the manuscript and one of our own single-molecule images. We encountered some technical issues.
We are very happy with the overall positive assessment of the reviewer that Mars could offer a common format that helps to enforce reproducible analysis workflows that can easily be shared with others.
We are grateful for the additional feedback and testing done by the reviewer and her student. Ensuring that Mars works as expected on all computers and configurations is difficult given that we don’t have them at hand for testing ourselves. During the revision period, we have done more testing on more computer systems and we hope we have addressed the issues. We believe it will be impossible for us to guarantee that Mars works without problems on the first try for everyone. Therefore, Mars is a community partner on the Scientific Community Image Forum where users can report their problems in posts with the mars tag and we can help troubleshoot them (https://forum.image.sc/tag/mars). We believe this approach will offer the best support going forward. Nevertheless, we continue to make improvements and test to make sure all bugs we discover are addressed.
In the revision, we completely reworked the smFRET example workflow and added two additional workflows to address all the comments from the reviewers and reviewing editor. In addition to expanding the explanations, and troubleshooting information on the Mars documentation website, we also created a YouTube channel with tutorial and example videos (https://www.youtube.com/channel/UCkkYodMAeotj0aYxjw87pBQ). We go through the new dynamic smFRET workflow from start to finish in one of the videos provided (https://www.youtube.com/watch?v=JsyznI8APlQ). We hope this will make it clear what inputs and outputs are expected and how the workflow should proceed. This was done on a mac but we have also tested this workflow on windows without encountering problems.
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www.techrepublic.com www.techrepublic.com
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Your email has been sent by Franklin Okeke in Developer on July 7, 2022, 7:48 AM PDT The 12 best IDEs for programming IDEs are essential tools for software development. Here is a list of the top IDEs for programming in 2022. Image: Chaosamran_Studio/Adobe Stock Software developers have battled with text editors and command-line tools that offered little or nothing in the automation, debugging and speedy execution of codes. However, the software development landscape is rapidly changing, and this includes programming tools. To accommodate the evolution in software development, software engineers came up with more sophisticated tools known as integrated development environments. To keep up with the fast pace of emerging technologies, there has been an increasing demand for the best IDEs among software development companies. We will explore the 12 best IDEs that offer valuable solutions to programmers in 2022. Jump to: What is an IDE? The importance of IDEs in software programming Standard features of an IDE Classifications of IDEs Best IDEs for programmers Factors to consider when picking an IDE What is an IDE? IDEs are software development tools developers use to simplify their programming and design experience. IDEs come with an integrated user interface that combines everything a developer needs to write codes conveniently. The best IDEs are built with features that allow developers to write and edit code with a code editor, debug code with a debugger, compile code with a code compiler and automate some software development tasks. SEE: Hiring kit: Back-end Developer (TechRepublic Premium) The best IDEs come with class browsers to examine and reference properties, object browsers to investigate objects and class hierarchy diagrams to see object-oriented programming code. IDEs are designed to increase software developer productivity by incorporating close-knit components that create a perfect playground where they can write, test and do whatever they want with their code. Why are IDEs important in software programming? IDEs provide a lot of support to software developers, which was not available in the old text editors. The best IDEs around do not need to be manually configured and integrated as part of the setup process. Instead, they enable developers to begin developing new apps on the go. Must-read developer coverage The 12 best IDEs for programming Best DevOps Tools & Solutions 2022 CI/CD platforms: How to choose the right system for your business Hiring kit: Python developer Additionally, since every feature a programmer needs is available in the same development environment, developers don’t have to spend hours learning how to use each separately. This can be extremely helpful when bringing on new developers, who may rely on an IDE to familiarize themselves with a team’s standard tools and procedures. In reality, most IDE capabilities, such as intelligent code completion and automatic code creation, are designed to save time by eliminating the need to write out entire character sequences. Other standard IDE features are designed to facilitate workflow organization and problem-solving for developers. IDEs parse code as it is written, allowing for real-time detection of human-related errors. As such, developers can carry out operations without switching between programs because the needed utilities are represented by a single graphical user interface. Most IDEs also have a syntax highlighting feature, which uses visual clues to distinguish between grammar in the text editor. Class and object browsers, as well as class hierarchy diagrams for certain languages, are additional features that some IDEs offer. All these features help the modern programmer to turn out software development projects fast. For a programming project requiring software-specific features, it’s possible to manually integrate these features or utilities with Vim or Emacs. The benefit here is that software developers can easily have their custom-made IDEs. However, for enterprise uses, the above process might take time and impact standardization negatively. Most enterprises encourage their development teams to go for pre-configured IDEs that suit their job demands. Other benefits of IDEs An IDE serves as a centralized environment for the needs of most software developers, such as version control systems, Platform-as-a-Service and debugging tools. An IDE improves workflow due to its fast code completion capabilities. An IDE automates error-checking on the fly to ensure top-quality code. An IDE has refactoring capabilities that allow programmers to make comprehensive and renaming changes. An IDE ensure a seamless development cycle. An IDE facilitates developer efficiency and satisfaction. Standard features of an IDE Text editor Almost all IDEs will offer a text editor made specifically for writing and modifying source code. While some tools may allow users to drag and drop front-end elements visually, the majority offers a straightforward user interface that emphasizes language-specific syntax. Debugger Debugging tools help developers identify and correct source code mistakes. Before the application is published, programmers and software engineers can test the various code parts and find issues. Compiler The compiler feature in IDE assists programmers in translating programming languages into machine-readable languages such as binary code. The compiler also helps to ensure the accuracy of these machine languages by analyzing and optimizing them. Code completion This feature helps developers to intelligently and automatically complete common code components. This process helps developers to save time and reduces bugs that come from typos. Programming language support Although some IDEs are pre-configured to support one programming language, others offer multi-programming language support. Most times, in choosing an IDE, users have to figure out which programming languages they will be coding in and pick an IDE accordingly. Integrations and plugins Integration capability is one feature that makes an IDE stand out. IDEs support the integration of other development tools through plugins to enhance productivity. Classifications of IDEs IDEs come in different types and according to the programming languages they support. While some support one language, others can support more than one. Multi-language IDE Multi-language IDEs are IDE types that support multiple programming languages. This IDE type is best suited for beginner programmers still at the exploration stage. An example of this type of IDE is the Visual Studio IDE. It’s popular for its incredible supporting features. For example, users can easily code in a new programming language by adding the language plugin. Mobile development IDE As the market for mobile app development grows, numerous programming tools are becoming available to help software developers build efficient mobile apps. Mobile development IDEs for the Android and iOS platforms include Android Studio and Xcode. Web/cloud-based IDE If an enterprise supports a cloud-based development environment, it may need to adopt a cloud-based IDE. One of the advantages of using this type of IDE is that it can run heavy projects without occupying any computational resources in a local system. Again, this type of IDE is always platform-independent, making it easy to connect to many cloud development providers. Specific-language IDE This IDE type is a typical opposite of the multiple-language IDE. They are specifically built to support developers who work on only one programming language. Some of these IDEs include Jcreator for Java, Idle for Python and CodeLite for C++. Best IDEs for programmers in 2022 Visual Studio Microsoft Visual Studios The Visual Studio IDE is a Microsoft-powered integrated development interface developed to help software developers with web developments. The IDE uses artificial intelligence features to learn from the edit programmer’s make to their codes, making it easy for it to complete lines of code automatically. One of the top features many developers have come to like about Visual Studio is that it aids collaborative development between teams in live development. This feature is very crucial, especially during the debugging process. The IDE also allows users to share servers, comments and terminals. Visual Studio has the capability to support mobile app, web and game development. It also supports Python language, Node.js, ASP.NET and Azure. With Visual Studio, developers can easily create a development environment in the cloud. SEE: Hiring kit: Python developer (TechRepublic Premium) With its multi-language support, Visual Studio has features that integrate flawlessly with Django and Flask frameworks. It can be used as an IDE for Python on the Mac, Windows and Linux operating systems. IntelliJ IDEA IntelliJ IDEA IntelliJ Idea has been around for years and has served as one of the best IDEs for Java programming. The IntelliJ Idea UI is designed in a sleek way that makes coding appealing to many Java developers. With this IDE, code can get indexed, providing relevant suggestions to help complete code lines. It also takes this suggestive coding further by automating several tasks that may be repetitive. Apart from supporting web, enterprise, and mobile Java programming, it is also a good option for JavaScript, SQL and JPQL programming Xcode Xcode Xcode might be the best IDE tool for Apple product developers. The tool supports iOS app development with its numerous iOS tools. The IDE supports programming languages such as Swift, C++ and Object-C. With XCode, developers can easily manage their software development workflow with quality code suggestions from the interface. Android Studio Android Studio The Android Studio is one of the best IDEs for Android app development. This IDE supports Kotlin and Java programming languages. Some important features users can get from the Android Studio are push alerts, camera integrations and other mobile technology features. Developers can also create variants and different APKs with the help of this flexible IDE, which also offers extended template support for Google Services. AWS Cloud9 IDE AWS Cloud9 The AWS Cloud9 IDE is packed with a terminal, a debugger and a code editor, and it supports popular programming languages such as Python and PHP. With Cloud9 IDE, software developers can work on their projects from almost anywhere in the globe as long as they have a computer that is connected to the internet, because it is cloud-based. Developers may create serverless applications using Cloud9 and easily collaborate with different teams in different development environments. Eclipse Eclipse Eclipse is one of the most popular IDEs. It’s a cross-platform tool with a powerful user interface that supports drag and drop. The IDE is also packed with some important features such as static analysis tools, debugging and profiling capabilities. Eclipse is enterprise development-friendly and it allows developers to work on scalable and open-source software development easily. Although Eclipse is best associated with Java, it also supports multiple programming languages. In addition, users can add their preferred plugins to the IDE to support software development projects. Zend Studio Zend Studio Zend Studio is a leading PHP IDE designed to support PHP developers in both web and mobile development. The tool features advanced debugging capabilities and a code editor with a large community to support its users. There is every possibility that PHP developers will cling to the Zend IDE for a long time as it has consistently proven to be a reliable option for server-side programming. Furthermore, programmers can take advantage of Zend Studio’s plugin integrations to maximize PHP applications’ deployment on any server. PhpStorm PhpStorm PhpStorm is another choice to consider if users use PHP for web development. Although it focuses on the PHP programming language, front-end languages like HTML 5, CSS, Sass, JavaScript and others are also supported. It also supports popular website-building tools, including WordPress, Drupal and Laravek. It offers simple navigation, code completion, testing, debugging and refactoring capabilities. PhpStorm comes with built-in developer tools that help users perform routine tasks directly from the IDE. Some of these built-in tools serve as a version control system, remote deployment, composer and Docker. Arduino IDE Arduino Arduino is another top open source, cross-platform IDE that helps developers to write clean code with an option to share with other developers. This IDE offers both online and local code editing environments. Developers who want to carry out sophisticated tasks without putting a strain on computer resources love it for how simple it is to utilize. The Arduino IDE includes current support for the newest Arduino boards. Additionally, it offers a more contemporary editor and a dynamic UI with autocompletion, code navigation and even live debugger features. NetBeans NetBeans You can’t have a list of the best IDE for web development without including NetBeans. It’s among one of the most popular options for the best IDE because it’s a no-nonsense software for Java, JavaScript, PHP, HTML 5, CSS and more. It also helps users create bug-free codes by highlighting code syntactically and semantically. It also has a lot of powerful refactoring tools while being open source. RubyMine RubyMine Although RubyMine primarily supports the Ruby, it also works well with JavaScript, CSS, Less, Sass and other programming languages. The IDE has some crucial automation features such as code completion, syntax and error-highlighting, an advanced search option for any class and symbol. WebStorm WebStorm The WebStorm IDE is excellent for programming in JavaScript. The IDE features live error detection, code autocompletion, a debugger and unit testing. It also comes with some great integrations to aid web development. Some of these integrations are GitHub, Git and Mercurial. Factors to consider when picking an IDE Programming language support An IDE should be able to support the programming language used in users’ software development projects. Customizable text editors Some IDEs offer the ability to edit the graphical user interface. Check if the preferred IDE has this feature, because it can increase productivity. Unit testing Check if the IDE can add mock objects to some sections of the code. This feature helps test code straight away without completing all the sections. Source code library Users may also wish to consider if the IDE has resources such as scripts and source code. Error diagnostics and reports For new programmers, sometimes it’s good to have an IDE that can automatically detect errors in code. Have this factor in mind if users will need this feature. Code completion Some IDEs are designed to intelligently complete lines of code, especially when it comes to tag closing. If developers want to save some coding time from tag closing, check for IDEs that offer this option. Integrations and plugins Do not forget to check the integration features before making a choice. Code search Some IDEs offer the code search option to help search for elements quickly in code. Look for IDEs that support this productivity feature. Hierarchy diagrams If users often work on larger projects with numerous files and scripts that all interact in a certain way, look for IDEs that can organize and present these scripts in a hierarchy. This feature can help programmers observe the order of file execution and the relationships between different files and scripts by displaying a hierarchy diagram. Model-driven development Some IDEs help turn models into code. If users love creating models for the IDE, consider this factor before choosing an IDE. 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Downloads Published: May 19, 2022, 5:00 PM PDT Modified: May 21, 2022, 12:00 PM PDT Read More See more TechRepublic Premium TechRepublic Premium Quick glossary: Industrial Internet of Things The digital transformation required by implementing the industrial Internet of Things (IIoT) is a radical change from business as usual. This quick glossary of 30 terms and concepts relating to IIoT will help you get a handle on what IIoT is and what it can do for your business.. From the glossary’s introduction: While the ... Downloads Published: May 19, 2022, 5:00 PM PDT Modified: May 21, 2022, 12:00 PM PDT Read More See more TechRepublic Premium TechRepublic Premium Software Procurement Policy Procuring software packages for an organization is a complicated process that involves more than just technological knowledge. There are financial and support aspects to consider, proof of concepts to evaluate and vendor negotiations to handle. 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and seriously you don't mention visual code???
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-
tomcritchlow.com tomcritchlow.com
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A CMS for hosting, editing and maintaining markdown files AND a hosting service for publishing these as blogs.
Another solution, in two steps:
- make your SOPs executable
- give them a promotion; make them first-class content (they should live on the site that you're publishing—although not necessarily front-and-center—not hidden away in the README of some ghost repo)
See also: A New Publishing Discipline.
-
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docs.bmc.com docs.bmc.com
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To synchronize BMC Helix common services container images
I've tried to run this section while harbor runs on http. This fails as docker login command is issued and thinks harbor is on SSL.
The workaround is to do the following
- Create 4 replication rules.
Name ade_part_01 Source resource registry https://containers.bmc.com Source resource filter Name bmc/lp0lz Source resource filter Tag {4.2.2-debian-10-r50,ade-authz-service-149,ade-file-service-e2830be-7,ade-identity-management-portal-12,ade-identity-management-service-15,ade-notification-service-9,adeops-util-v012,adeops-util-v013,adeops-util-v016,adeops-util-v019,adeops-util-v024,adereporting-21.3.02.02,adereporting-content-e0ab22f-251,adereporting-initdb-v001,adereporting-kafkacli-v002,adereporting-puller-7e41b3d-274,adereporting-renderer-dd91f81-216,adereporting-runner-7e41b3d-274,ade-tenant-management-automation-273,ade-tenant-management-portal-14,ade-tenant-management-service-7,ade-ui-content-service-18,aif-api-service-8150462-9,aif-clustering-ingestion-service-3a4ce1d-12,aif-clustering-query-service-3dfbda3-9,aif-clustering-service-08fa171-9,aif-core-service-fdfb78d-6,aif-incident-ingestion-service-3a0f0e2-8,aif-job-manager-service-ab85bfb-8,aif-machine-learning-utilities-8a08716-57,aif-ticket-service-d71f457-11,anomaly-detection-service-58e6996-5}
Name ade_part_02 Source resource registry https://containers.bmc.com Source resource filter Name bmc/lp0lz Source resource filter Tag {authproxy-RSSO_Auth_Proxy_101,authproxy-RSSO_Auth_Proxy_110,authproxy-RSSO_Auth_Proxy_112,authproxy-RSSO_Auth_Proxy_80,bitnami-kafka-2.7.0-debian-10-r124,bitnami-minio-2021.4.18-debian-10-r0,bitnami-zookeeper-3.7.0-debian-10-r25,custom-elasticsearch-1.13.3,custom-postgresql-repmgr-12.9.0,custom-sec-ade-infra-clients-1,custom-sec-redis-5.0.12-alpine,custom-sec-victoriametrics-vminsert-v1.63.0-cluster,custom-sec-victoriametrics-vmselect-v1.63.0-cluster,custom-sec-victoriametrics-vmstorage-v1.63.0-cluster,es-proxy-nginx-service-6d2eb81-6,es-proxy-service-6d2eb81-6,event-ingestion-service-4c0353c-4,event-mgmt-service-fc008be-6,event-processor-service-199851c-10,event-service-a21ce51-7,haproxy-2.0.4,justwatch-elasticsearch_exporter-1.1.0,kibana-proxy-service-c4f46f6-6,kibana-service-c4f46f6-6,kubectl-latest,log-ingestion-service-ff04217-99,log-mgmt-service-ceb53d1-4,log-processing-service-726afae-6,logs-portal-eb0d3a5-8}
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Name ade_part_02 Source resource registry https://containers.bmc.com Source resource filter Name bmc/lp0lz Source resource filter Tag {ade-ims-webhook-114,ade-itsm-identity-sync-199}
- Then you can synchronize them at will
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icla2022.jonreeve.com icla2022.jonreeve.com
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Oh dear, how hard it was to be indifferent like the others! She tried not to smile too much; she tried not to care. But every single thing was so new and exciting...
Reading this passage reminded me of a young girl getting the chance to tag along with her older sister and friends to a night out - the way she tries to appear nonchalant like the others when everything is "so new and exciting" to her. She might be younger than the other girls, or maybe she is not as wealthy and therefore doesn't participate in these events as often.
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bafybeifceccflmbqnoau2ctisurbwssp27mylyrq55ytuby24owez4crti.ipfs.dweb.link bafybeifceccflmbqnoau2ctisurbwssp27mylyrq55ytuby24owez4crti.ipfs.dweb.link
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!- for : - Open Learning Commons - Augmenting Synthesis - Augmented Scaling Synthesis - Externalizing Collective Intellet
- tag : openlerning17
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ecampusontario.pressbooks.pub ecampusontario.pressbooks.pub
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Does/did + Subject + verb + object (optional)+ question tag
This is incorrect! Should be:
*Do/Does + subject + base verb? *
Do you like pizza? Does Sam like pizza?
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www.biorxiv.org www.biorxiv.org
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Review coordinated via ASAPbio’s crowd preprint review
This review reflects comments and contributions by Oana Nicoleta Antonescu, Ruchika Bajaj, Sree Rama Chaitanya and Akihito Inoue. Review synthesized by Ruchika Bajaj.
This study has characterized the function of Hero proteins in improving the recombinant expression of TAR DNA-binding protein in E. coli and restoration of enzymatic activity of firefly luciferase during heat and stress conditions. This study may be useful for future applications of Hero proteins in life sciences research. Please see below a few points offered as suggestions to help improve the study.
- In introduction, 3rd paragraph, in context with “amino acid composition and length of Hero proteins”, please elaborate on the effect of these two factors on the function and stability of hero proteins.
- The manuscript refers to “cis and trans” terms on several occasions. Please explain these terms in context with the association of Hero protein with the target proteins.
- Introduction - A paragraph describing the origin of Hero proteins and the differences between the types of Hero proteins in the introduction section would be helpful for readers to understand the background on these proteins. For example, please explain the background on naming these proteins as Hero 7, 9, 11 etc. The genes SERF2, C9orf16, C19orf53, etc are mentioned in the plasmid construction section in the Material and methods. Please provide a brief explanation for the relationship between these genes and Hero proteins.
- Please add more details in the Material and methods section, especifically in western blotting and the luciferase assay, to support the reproducibility of these experiments.
- Figure 1A. Please explain the role of each component (for example factorXa) either in the text or the legend.
- Figure 1B: Please add clarification regarding the normalization of lanes by total protein concentration.
- Fig 1C. Please provide an explanation for the higher order bands in the western blot. The western blot using anti-FLAG antibodies shows non-specific bands. Alternative tags or antibodies or detection methods may be used, for example, GFP tag and in-gel fluorescence can be used to check the expression.
- Figure 1D and 1E, the error bars are high. Suggest checking the data and providing the mathematical expressions used to calculate relative yields.
- Figure 2D and E, the error bars are high, access to the raw data behind the graphs may aid interpretation. An explanation for the choice of temperatures 33 C and 37 C would be helpful. Is there any relation between the choice of temperature and the Tm of the protein? The protein is directly being treated at high temperature, similar experiments with cell-based assays would be helpful to understand the effect of the Hero proteins on the stability of Fluc. Would it be possible to report the mathematical expressions used to calculate “Remaining Fluc activity”. Recommend indicating n if these activities are calculated per mg of the protein. Please explain if the reduction in activity is due to loss of protein or loss of luminescence activity from each molecule of the protein.
- Figure S1, access to the raw data would be helpful to understand the signal to noise ratio for activity.
- Figure 2 and 3 show similar experiments with wild type and mutants, it may be possible to combine the figures (for example, to avoid the redundancy in Figure 2C and 3A).
- Figure 3D and G, access to the raw data would be helpful to interpret the signal and noise ratio especially given the low values.
- Figure 4, Can some further discussion be provided for the reason for higher residual activity for SM and DM than wild type? Tm experiments during stress conditions (heat shock and freeze thaw cycles) may be helpful to define the stability of Fluc and Fluc mutants.
- Figure 5: Suggest including an explanation for choosing Proteinase K -among other proteases- for these experiments.
- The residual activity is different in Figure 4 and 5, which could be due to different stress conditions. Please include some discussion about possible explanations.
- In section “Hero proteins protect Fluc activity better in cis than in trans”, ‘When the molarity of recombinant GST, Hero9, and Hero11 proteins was increased by 10-fold...’ does molarity refer to the concentration of protein ?
- In the first paragraph of the discussion, “physical shield that prevents collisions of molecules leading to denaturation” and “maintaining the proper folding” is mentioned. Is it the hypothesis for the mechanism behind the stability provided by Hero proteins? Can further discussion on this be provided, along with a relevant reference.
- In the discussion section, it is mentioned that “Hero may be reminiscent of polyethylene glycol (PEG)”. Please provide further explanation for why hero proteins are correlated with PEG in this fragment.
- A discussion on why specific Hero proteins may be better for specific target proteins may be helpful.
- In the second paragraph, of the Discussion “Hero protein can behave differently depending on the client protein and condition” and “important to test multiple Hero proteins to identify one that best protects the protein of interest” are mentioned. Suggest adding further discussion of these points, for example around any alternatives or computational predictions or simulations to test individual Hero proteins for specific client proteins.
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en.wikipedia.org en.wikipedia.org
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He explains the purpose of his "waste book" in his notebook E: Die Kaufleute haben ihr Waste book (Sudelbuch, Klitterbuch glaube ich im deutschen), darin tragen sie von Tag zu Tag alles ein was sie verkaufen und kaufen, alles durch einander ohne Ordnung, aus diesem wird es in das Journal getragen, wo alles mehr systematisch steht ... Dieses verdient von den Gelehrten nachgeahmt zu werden. Erst ein Buch worin ich alles einschreibe, so wie ich es sehe oder wie es mir meine Gedancken eingeben, alsdann kann dieses wieder in ein anderes getragen werden, wo die Materien mehr abgesondert und geordnet sind.[2] "Tradesmen have their 'waste book' (scrawl-book, composition book I think in German), in which they enter from day to day everything they buy and sell, everything all mixed up without any order to it, from there it is transferred to the day-book, where everything appears in more systematic fashion ... This deserves to be imitated by scholars. First a book where I write down everything as I see it or as my thoughts put it before me, later this can be transcribed into another, where the materials are more distinguished and ordered."
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www.biorxiv.org www.biorxiv.org
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Note: This rebuttal was posted by the corresponding author to Review Commons. Content has not been altered except for formatting.
Learn more at Review Commons
Reply to the reviewers
__Manuscript number: __RC-2022-01357
__Corresponding author(s): __Peter Novick and Gang Dong
1. General Statements [optional]
We would like to thank both reviewers for their thorough and constructive evaluation and comments on our manuscript. Following their suggestions, we have reworked our manuscript and added several pieces of new data to address questions from them, including (1) evaluation of how M7 mutant of Sso2 affects its interaction with Sec3 using three independent methods (in vitro); (2) investigation of how the M7 mutant affects the interaction of Sso2 with Sec3 by co-immunoprecipitation (in vivo). We hope that, with all these further introduced changes, this manuscript will be suitable for publication in your journal. Detailed point-to-point responses are shown below.
2. Point-by-point description of the revisions
Reviewer #1 (Evidence, reproducibility and clarity (Required)): *
Using the entire cytoplasmic domain of Sso2 and protein crystallization, Peer and colleagues show that two N-terminal peptides (NPY) of Sso2 synergistically interact with the Sec3 PH domain. This interaction provides an additional low affinity binding site to the previously published interface between the Sso2 four-helix bundle and the PH domain. Mutagenesis, in particular of both NPY motifs, results in reduced cell growth, in the accumulation of transport vesicles at the budding site, and in decreased secretion of invertase and Bgl2. The paper is well written, the data are convincing and the characterization of these novel peptide interaction sites clearly advances the field. Although, the exact role of the Sec3 NPY - Sec3 interaction still needs to be established, the overall functional relevance is apparent and thus the paper could be published with minor changes. *
__Response: __We really appreciate the reviewer for his/her positive comments and clear/constructive feedbacks.
*Nevertheless, the authors may consider to address the following issues to improve the manuscript. - To strictly exclude the possibility that the Sso2 NPY motif also interacts with other components of the exocytosis machinery (e.g. Sec1), thereby causing the observed phenotypes, Sec3 mutagenesis of the NPY motif-binding site would be required. *
__Response: __It would be a good idea to generate reverse mutants on Sec3. However, the pocket on Sec3 bound by the NPY motifs of Sso2 is mostly hydrophobic and contains many semi-buried residues that are in close contact with other residues in the hydrophobic core of structure (including L78, Y82, I109, V112, V208, etc.; see Fig. S3D, E) and thus essential in maintaining the folding of Sec3. Making mutations on these residues would destabilize the folding of Sec3. This was why we have not done this as suggested by the reviewer.
*- The authors suggest that the NPY-peptide binding contributes to the initial interaction/recruitment of Sso2 to the exocytosis site, defined by the localization of Sec3 (exocyst). Further data sustaining this concept/hypothesis could improve the impact of the manuscript. Thus, an experiment analyzing the co-distribution of the Sec3 with Sso2 would directly support the authors' conclusion. (In Figure 7, the authors already show the highly polarized distribution of Sec3-3xGFP.) The M7 mutant could impact the distribution of Sso2. In addition, it would be helpful to determine to which degree the Sso2 NPY - Sec3 PH domain interaction increases the overall affinity of Sso2 for the Sec3 PH domain; e.g. comparison of the binding of Sso2 (1-270) wt and M7 to Sec3 PH domain using ITC. *
Responses:
- We greatly value the reviewer’s suggestion. For the suggestion to investigate how the M7 mutant affects the co-distribution of Sso2 with Sec3 in yeast, we have tried a variety of conditions with both the original serum and affinity purified Sso antibodies. In neither case did we see a clear concentration at sites where we would expect to see Sec3, such as the tips of small buds. We were able to see some detectable concentration of HA-tagged Sso2 in small buds using anti-HA Ab, but it would be difficult to tag the M7 mutant at the same site since it is so close to the M7 mutation. We are also worried that the tag might interfere with Sec3 binding due to the proximity. Given the lack of detectable concentration of WT Sso2, it would not be possible to see a loss of localization in M7.
- For the suggestion to check the binding of Sec3 with either the WT or M7 mutant of Sso2 (aa1-270), we have generated M7 mutant within the same fragment of Sso2 as the WT (i.e. aa1-270) and carefully checked how this M7 mutant affects the interaction of Sso2 with the Sec3 PH domain using three independent methods. Our ITC data show that WT Sso2 bound Sec3 very robustly, with a Kd of approximately 2 µM (Fig. 8C). Surprisingly, however, the M7 mutant of Sso2 (aa1-270) completely abolished its interaction with Sec3 (Fig. 8D). To further verify this observation, we carried out electrophoresis mobility shift assays (EMSA) and size-exclusion chromatography (SEC). Our EMSA data on a native PAGE gel shows that WT Sso2 (aa1-270) bound Sec3, whereas the M7 mutant did not (Fig. S5A, B). Similarly, our SEC data demonstrate that Sec3 was co-eluted with WT Sso2 in the higher molecular weight peak; in contrast, Sec3 and the M7 mutant of Sso2 (aa1-270) were eluted in separate peaks and no stable complex of the two was formed (Fig. S5C, D). All these new data confirm that the NPY motifs play an essential role in maintaining the stable interaction between Sso2 and Sec3, which would explain why the M7 mutant gave such dramatic phenotype in vivo (Fig. 4B-E; Fig. 5D-F; Fig. 6D, E). *Minor point: In the discussion, the authors should mention to which degree the NPY binding site within Sec3 is accessible for / occupied by other known exocyst components, or PI(4,5)P2, etc. *
Response: __Thank you for the suggestion. A new diagram has been added to __Fig. 9E to compare the structures of the previously reported Sec3/Rho1 complex and the Sso2/Sec3 complex determined by us. It shows that the NPY binding site on Sec3 is on the opposite side of the membrane-binding surface patch. The NPY binding site is also far away from the Rho1 interacting site on Sec3 and thus does not interfere with Rho1 binding either.
*Reviewer #1 (Significance (Required)):
The manuscript significantly contributes to our understanding of how the vesicle tethering machinery interacts and coordinates the assembly of the membrane fusion machinery and will be of broad interest in the field of membrane trafficking. I am not an expert in X-ray crystallography. *
__Response: __We sincerely appreciate this reviewer’s positive feedbacks.
***Referees cross-commenting**
I agree with the comments of the other reviewer. It would be nice to show the effect of the M7 mutant in a reconstituted liposome fusion assay, but as already mentioned this may require an additional collaboration. Whether the relatively weak Sec3 - NPY interaction can be resolved in the liposome fusion assay needs to be shown.*
__Response: __Please check our detailed answer to the other reviewer’s question about this.
Reviewer #2 (Evidence, reproducibility and clarity (Required)): * The manuscript of Peer et al. Describe the structural characterization of the interaction of the syntaxin-like Sso2 protein with the exocyst subunit Sec3. The authors identify here a dual NPY motif at the N-terminal part of Sso2 that binds to Sec3 and thus confers functionality. Using x-ray crystallography, they show a nearly full-length Sso2 in complex with Sec3, which reveals how Sso2 binds to Sec3. Subsequent mutagenesis shows that both NPY motifs act together in binding, and are both required for functionality in vivo, using established assays in localization of exocyst subunits, secretion assays and growth tests. Their data suggest an overall model how Sso2 is efficiently recruited by exocyst to promote vesicle secretion.
This is__ an overall very complete and clear manuscript__, where the authors nicely demonstrate, how the two NPY motifs both contribute to efficient Sso2 interaction with Sec3. Their data further show that each motif alone can contribute to function, whereas loss of both motifs (the M7 mutant) result in deficient binding. Likewise, their established assays to determine cellular importance of the NPY motifs in Sso2 show that trafficking and localization in the secretory pathway is strongly impaired in the mutant. I only have a few questions and suggestions. *
__Response: __Thank you for the positive feedback.
*1. The authors present in Figure 4 the mutants. I recommend to show the alignment of the mutants (M5,M6,M7) similar to panel A in Figure S4 here to orient the reader. They could also be listed in Figure 3, since the authors have here the sequences. *
Response: __Alignment of M5-M7 has been added in __Fig. 4A as suggested. Thank you.
2. The authors previously showed that Sso2 mutants affect the Sec3 driven assembly and also the fusion. I am wondering if they have the tools ready to also conduct this assay with their M7 mutant, which has the strongest defect. I am aware that this may be challenging if the tools are not established here as in the previous collaboration (Yue et al., 2017). It may provide additional information on the functional crosstalk.
Responses:
- Thank you for the suggestion. However, we do not think it is necessary to perform such assay based on our new results. As shown in 8C&D and Fig. S5, we found that the M7 mutant of Sso2 (aa1-270) completely abolished its interaction with Sec3, which is in contrast to the robust interaction between the WT Sso2 (aa1-270) and Sec3. Therefore, we expect that the M7 mutant would fail to accelerate liposome fusion in the same way as we had previously seen for the WT Sso2.
- On the other hand, we have to admit that to perform such assay would indeed be challenging for us as the PhD student who had carried out the in vitro liposome fusion assay has left our previous collaborator’s lab and it would take quite a while to re-establish the assay in our own group and to optimize various parameters in that assay. *3. Along the same line, it would be good if the authors show that the mutation also impairs the interaction of Sec3 and Sso2 in vivo. *
Response: __We appreciate the reviewer’s suggestion and have carried out co-immunoprecipitation of Sec3-3×Flag and Sso2 from yeast extract to find out how the M7 mutant affects Sso2’s interaction with Sec3 (__Fig. S6). Our results show that in contrast to the clear signal of WT Sso2 pulled down by Sec3-3×Flag, the pull-down band for the M7 mutant was much weaker and at a similar level to the negative control. This is consistent with what we saw in our in vitro binding assays (Fig. 8D; Fig. S5).
*4. I really like the similarity of the different Munc18-Syntaxin interactions and the Sec3-Sso2 interaction. Do the authors think that Sec3 is an ancestral fragment of a Sec1 like protein, which just maintained this interaction? *
__Response: __This is a very interesting idea. However, it seems too speculative to us to draw such conclusion. It could also be due to co-evolution in function for Sec3 to use a simpler structure (i.e. PH domain) to mimic syntaxin binding of SM proteins and to employ the extra “add-on” NPY motifs as a handle to facilitate and regulate their interaction.
- *Small mistake in the discussionResponses: "plasmas membrane" *
__Response: __This has been corrected. Thank you.
*Reviewer #2 (Significance (Required)): Important advance in our understanding of Exocyst function, which deserves publication. I only had minor issues that can be addressed quickly. *
__Response: __We sincerely appreciate the reviewer’s positive feedbacks and constructive suggestions.
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@chrisaldrich meet @carterb5. An #edu522 student new to micro blog.
👋🏼@carterb5 ! I learned all my best tricks from @jgmac1106. And out of nostalgia, it's sometimes fun revisiting all my old notes: boffosocko.com/tag/edu52... Has it already been 4 years?!
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graceful.dev graceful.dev
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to deepen and mature your coding practice
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thesephist.com thesephist.com
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Most existing tools and browsers treat web pages and pieces of notes like complete black boxes of information. These tools know how to scan for keywords, and they have access to the metadata we use to tag our information like hashtags and timestamps, but unlike a human, most current tools don’t try to peer into the contents of our notes or reading materials and operate with an understanding of our information. With ratcheting progress in machine understanding of language, I think we have good high-quality building blocks to start building thinking mediums and information systems that operate with some understanding of our ideas themselves, rather than simply “this is some text”.
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www.goodreads.com www.goodreads.com
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“To be scientifically literate is to empower yourself to know when someone else is full of shit.” ― Neil deGrasse Tyson
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“Conspiracy theory, like causality, works fantastically well as an explanatory model but only if you use it backwards. The fact that we cannot predict much about tomorrow strongly indicates that most of the explanations we develop about how something happened yesterday have (like history in general) a high bullshit content.” ― Peter J. Carroll, Psybermagick: Advanced Ideas in Chaos Magick
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
In this Research Advance, the authors build on two earlier eLife papers that described and experimentally validated a mathematical model of the transcriptional response of yeast to heat shock in which unfolded proteins sequester Hsp70 away from Hsf1 promoting an Hsf1-driven transcriptional program, and report two new findings. First, they provide evidence that upon heat shock it is newly synthesized proteins rather than denatured mature proteins that sequester the Hsp70 chaperone away from Hsf1 permitting Hsf1 to bind to target genes and drive the heat shock-induced gene transcription program during the heat shock response (HSR), and, second, by analyzing the role of the Sis1 Hsp70 co-chaperone in the HSR they showed that Sis1 does not have a direct negative role in the HSR, but rather is needed for fitness during prolonged stress.
Because recent studies using cycloheximide to block protein synthesis have suggested that it is newly synthesized proteins in the process of folding rather than denatured mature proteins that are the clients for Hsp70 responsible the HSR, the authors reconfigured their model by assuming that heat shock slows the folding of newly synthesized proteins and adding the rate of translation as a new input function. They validated their new model using a yeast strain that has an HSE-YFP reporter gene as an HSR readout, and showed that rapamycin treatment, which reduces the rate of translation, resulted in a decrease in the HSR, that is predicted with kinetics predicted by their new model. In addition, based on their own recent work showing that the Sis1, a J-protein chaperone, regulates the HSR by promoting Hsf1-Hsp70 association in the nucleus to repress Hsf1 activity under non-heat shock conditions, they also incorporated Sis1, a Hsp70 co-chaperone, as a new component of their model circuitry. By experimentally induced eviction of Sis1 from the nucleus, they observed reduced Hsf1 activity towards the HSE-YFP reporter in the absence of a temperature shift, as predicted by the model. The new model also accounted for the rapid initial and then subsequent slowing kinetics of the HSR as it reached a maximum, as well as the different levels of HSR induction at increasing temperatures above 35oC. Moreover, even though the SIS1 promoter has an HSE and its basal transcription is driven by Hsf1, the elimination of this regulatory step experimentally showed that Hsf1-driven Sis1 transcription was not required for temperature shift-induced HSR output, implying, as the model predicted, that increased Sis1 expression is not important and not needed for negative feedback inactivation of Hsf1. This was tested directly by generating a strain in which the SIS1 promoter was replaced with two copies of the SUP35 promoter to maintain the basal expression level of Sis1, which showed normal kinetics of HSR inactivation under several experimental conditions. Using a Halo-tag pulse protocol, they demonstrated that heat shock induction of newly synthesized Sis1-halo was delayed and that the new Sis1 protein was preferentially localized around the nucleolus away from Hsf1, as determined using an Nsr1-mScarlet nucleolar marker, and thus Sis1 would presumably not be in a position to promote Hsp70/Hsf1 interaction and repression of Hsf1 activity. Finally. to investigate what role Sis1 plays in heat-stressed cells, they showed that the 2xSUP35pr-SIS1 yeast strain had reduced fitness compared to the other strains after 4 hours at 37ºC, suggesting that Sis1 has an undefined role in maintaining fitness in heat-stressed cells. Consistent with this, they showed that Sis1 also has a role in maintaining fitness in yeast cells growing on a non-preferred carbon source.
The updated model of the HSR, which still retains the two-component feedback loop consisting of the chaperone Hsp70 and the transcription factor Hsf1 of the original model but replaces the unfolded protein activation step with an equivalent step involving unfolded newly synthesized proteins, appears to be able to model cellar responses to heat shock quite accurately. This refinement of their model, coupled with the demonstration that the Sis1 J protein chaperone does not appear to play a direct role in the inactivation phase of the HSR, provide a significant advance over their earlier work.
A main weakness is that while the evidence that Sis1 is important for fitness of heat-stressed yeast cells is reasonable, exactly how Sis1 achieves this is not clear. In a single sentence the authors suggest that Sis1 might be an orphan ribosome chaperone, partly based on its nucleolar localization, but provide no evidence for this. If this were true, then one might expect a reduction in ribosome content under stress conditions and a decreased rate of protein synthesis, which could be tested. Some further insights into this more general role of Sis1 would strengthen the authors' conclusions.
Moreover, whether Sis1 plays a general role in the fitness of cells under stress has not been firmly established, i.e., is its mechanistic role the same in heat shock conditions and under nutrient stress conditions? Without knowing the mechanistic basis for how Sis1 maintains the fitness of heat-stressed cells, it is not possible to conclude that the same mechanism is at play in cells grown on a non-preferred carbon source.
Figure 4: This is an ingenious experiment to study the subcellular localization of newly synthesized Sis1 in response to heat shock, compared to that of the heat-shock inducible Hsp70 Ssa1. However, based on the images presented in panel B it is hard to know how discrete the subnuclear distributions of Sis1 and Ssa1 really are, and ideally what is needed is to be able to analyze their localizations when both tagged proteins are expressed in the same cell, although this would obviously not be possible using the halo-tagged protein system. In addition, one would like to know the localization of Hsf1 in the cell at the same time. As it stands, these data seem overinterpreted, and it remains possible that dome other event such as an inactivating post-translational modification of Sis1 under heat shock conditions might be involved in inactivating its function.
One way to establish whether Sis1 nucleolar sequestration prevents it from acting on Hsf1 during the inactivation phase of the HSR would be to selectively disrupt its nucleolar localization signal eliminated while retaining its nuclear localization and determine how expression of such a mutant perturbed the inactivation kinetics of the HSR.
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www.lesswrong.com www.lesswrong.com
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The Map Is Not The Territory
- The map is not the territory metaphorically illustrates the differences between belief and reality.
- The phrase was coined by Alfred Korzybski.
Scribbling on the map does not change the territory
- If you change what you believe about an object, that is a change in the pattern of neurons in your brain.
- The real object will not change because of this edit.
The map is a separate object from the territory and the map exists as an object inside the territory
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Author Response
Reviewer #1 (Public Review):
Cheng et al. address one of the fundamental questions of gene expression regulation - what are the relative contributions of RNA-level and protein-level regulation to the final gene expression levels. In order to do that they take advantage of mainly published datasets, especially tumor datasets where matching somatic copy number alterations (SCNAs), RNA expression and protein expression data is available. Performing proteogenomic analysis (taking DNA, RNA and protein into account) they address several open questions, such as: Is gene compensation happening mainly at the RNA level, protein level or both for each gene? Is this the same across different tissue types and also cellular pathways? Taking advantage of the SCNAs in the DNA, the authors use correlation analysis of DNA to RNA and RNA to protein to determine if the expression of a gene is regulated mainly at the level of RNA or protein in the respective samples.
Although it is mainly a very descriptive study, the meta-analysis of existing datasets (and one smaller dataset that was newly generated) yields very interesting observations, which will be of interest to the cancer and gene expression community. However, there is limited mechanistic insight into how the observations can be explained. This is not a problem in my view as the observations are interesting enough in themselves.
The main findings of the study are:
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In general genes are either regulated at the RNA-level or at the protein level, but rarely at both.
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This is the first study (at least as far as I know) to look at tissue-specific RNA-level and protein-level compensation across several different tumor types. Interestingly, the authors show tissue specificity of RNA and protein-level compensation - for example lung adenocarcinoma does not show nearly any compensation.
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Protein complex genes show stronger protein-level regulation than non-complex genes and the opposite trend in regards to RNA level regulation.
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There seems to be an agreement for genes within the same pathway that they show a similar regulatory mode (either RNA level or protein level).
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Genes involved in RNA processing, mRNA translation and mitochondrial regulation are generally upregulated at the protein-level in highly aneuploid primary tumor samples.
However, I do think that two points need to be addressed by additional analyses to strengthen the findings.
- The authors show that SCNAs are often significantly compensated at the protein-level in most tumor types. This compensation is also normally stronger than RNA level compensation. A technical issue about this finding that needs to be addressed is that this is mainly based on proteomics data that used TMT for quantification. TMT-based quantifications, although quite precise, are not always the most accurate measurements in the sense of capturing the true amplitude of changes. This is due to the so-called ratio compression of TMT mass spec data. The authors need to account for that in order to exclude that this technical limitation of TMT-based proteomics measurements is a main contributor to the protein-level compensation seen. Do the authors also have some proteomics data where label-free quantification of SILAC quantification was used? Do the same conclusions hold true when such data sets are used?
We thank the reviewer for this comment and point which we have now addressed through the following literature search or analyses:
• First, we found there are some previous studies which observed the similar protein-level compensation in yeast and human cells by different detection methods. Dephoure et al. compared two different methods, stable isotope labeling by amino acids in cell culture (SILAC) and tandem mass tag (TMT) based proteomics. The protein-level compensation of gained genes in yeast was discovered by both methods (Figure 2 and Figure 2 – figure supplement 1 of Dephoure et al., 2014). Similarly, Stingele et al. identified the protein-level compensation in pairs of isogenic diploid and aneuploid human cell lines by SILAC (Figure 2B of Stingele et al., 2012). Another group also found the protein-level compensation in primary human fibroblasts from individuals with Patau (trisomy 13), Edwards (trisomy 18) or Down (trisomy 21) syndromes by MS3-based approach (Hwang et al., 2021), which should eliminate the interference of ratio distortion (Ting et al., 2011). Taken together, those previous studies suggest the protein-level compensation should not be just the artifacts induced by the technical limitation of TMT-based proteomics.
• To further validate the protein-level compensation, we performed the same analysis on TCGA (The Cancer Genome Atlas Program) (Research Network et al., 2013) COAD samples for which label-free proteomics data is available (Zhang et al., Nature, 2014). Consistent with TMT-based proteomics, significant compensation at the protein level was found, which is higher for complex genes than non-complex genes (Figure 1 – figure supplement 1C, Supplementary File 1G). As we observed before for COAD (Figure 1C), RNA-level compensation was shown in all groups of DNA change, and was stronger for non-complex genes (deep loss and high gain, FDR<0.005, Figure 1 – figure supplement 1C, Supplementary File 1G). These results suggest that the limitations imposed by the TMT quantification do not alter the conclusions of our analysis on gene compensation. We have now added this data in Figure 1 – figure supplement 1C and Supplementary File 1G and corresponding text at page 5.
- Many of the statistically significant differences seen - e.g complexed proteins versus non-complexed proteins, highly conserved proteins versus less conserved proteins - have actually a relatively small effect size. It is not 100% clear to me that the authors apply always the most stringent and appropriate statistical evaluation. For example, when two density plots are compared and it is evaluated if the distributions differ significantly from each other (e.g. the median), the authors constantly use a bootstrapping strategy (most plots in Fig 2 and Fig S2). Due to the high number of iterations, bootstrapping is very sensitive to picking up statistical differences, even if there are very small effect size differences (as is the case for many of the comparisons). Would not a KS test be more appropriate to compare two density distributions? If a KS test is applied - do the authors still recapitulate the same statistical significance tendencies as seen with their bootstrapping strategy?
We thank the reviewer for this comment, and we have addressed it in detail. We have performed the analyses using Mann-Whitney U test and Kolmogorov-Smirnov (KS) test (Supplementary File 2K). Compared with bootstrapping, the p-values calculated by Mann-Whitney U test or KS test were much smaller, close to zero. Therefore, the same statistical significance tendencies were observed no matter which statistic method was used (bootstrapping, Mann-Whitney U test or Kolmogorov-Smirnov test). While Mann-Whitney U test or KS test carries the risk of p-value inflation due to the high sample number, the bootstrapping method can solve the problem as it is independent from the sample number. Initially we had used Mann-Whitney U test for all our analyses and were suggested to include bootstrapping method after consultation with the NYU Biostatistics Resource.
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Reply to the reviewers
1. General Statements
We would like to thank the reviewers for their insightful and useful comments about our manuscript. Based on these comments and as outlined in our revision plan, we plan to strengthen our findings by performing new experiments and quantitative analyses. This particularly applies to our nanoscale (dSTORM) imaging dataset which was discussed by multiple reviewers.
We also appreciate the reviewers’ overall positive evaluation of the significance of our labeling method for the axon initial segment studies. With regards to this, we would like to highlight that this manuscript particularly addresses the labeling of “difficult-to-label” neuronal proteins, such as large ion channels and transmembrane proteins. Although we and another group have recently reported click labeling of neurofilament light chain (PMID: 35031604) and AMPAR regulatory proteins (PMID: 34795271) in primary neurons, both of these proteins have a small size between ~30-68 kDa and compared to larger ion channels/transmembrane proteins are “easier” to express in primary neurons. The novelty in the current manuscript is that we successfully applied this method for the labeling of large and spatially restricted AIS components, such as NF186 and Nav1.6 (186 and 260 kDa, respectively). As some of the reviewers also pointed out, the size and complexity of these proteins makes labeling of the AIS rather challenging. We also used our approach to study the localization of epilepsy-causing Nav1.6 variants and could exclude the retention in the cytoplasm as a possible cause of their loss of function. Finally, we improved the efficiency of genetic code expansion in primary neurons by developing AAV-based viral vectors. Although AAVs are routinely used for gene delivery to neurons, AAVs for click-based labeling need to encode multiple components of the orthogonal translational machinery for genetic code expansion. By trying different promoters and gene combinations, we developed several variants that enable high efficiency of the genetic code expansion in neurons. On their own, these findings will facilitate further genetic code expansion and click chemistry studies, beyond the labeling of the axon initial segment.
2. Description of the planned revisions
Reviewer #2
- On lines 107 and 108, the sentence "The C-terminal HA-tag allowed us to detect the full-length NF-186 protein by immunostaining it with an anti-HA antibody" would have a better place just after lines 104-105 " [...] we modified the previously described plasmid (Zhang et al., 1998) by moving the hemagglutinin (HA) tag from the N terminus to the C terminus".
We will modify the text as the reviewer suggested.
- Fig.2b: the AnkG staining looks substantially longer than that showed in c. However, the results on AIS length show no significant changes in between the groups. This is visually misleading, the authors should choose a picture for the WT construct that is representative of the data.
We thank the reviewer for bringing this up. We will replace the panel in Fig.2b with a more representative image of NF186 WT construct in the revised version of the manuscript.
- Line 238: what is the rationale behind choosing these cells? For example, have they been used in other studies for similar purposes? If so, please provide the reference.
We initially probed neuroblastoma ND7/23 which are commonly used for the electrophysiological recordings of recombinant Nav1.6 (PMID: 30615093, 22623668, 25874799, 27375106). Although we were able to record Na+ currents in those cells, only a small portion of channels was detected on the cell surface by microscopy (Suppl. Fig. 5a). As we discuss in the manuscript (lines 237-240), we then switched to N1E-115-1 cells in which we obtained a higher level of expression of the recombinant NaV1.6 channels on the cell surface (Suppl. Fig. 5b). These cells have also been previously used for the electrophysiological studies of voltage-gated sodium channels, including Nav1.6 (PMID: 8822380, 24077057). We will modify the text and include these references in the revised manuscript.
- Figure 3c, the authors omitted the comparison with the WT construct this time, as opposed to the neurofascin experiments. What is the reason?
As shown by others (PMID: 31900387) and us in this manuscript, one of the main issues with the expression of the recombinant NF186 in neurons was that overexpression led to mislocalization of NF186 in neuronal soma and processes. This was particularly true for WT construct and certain amber mutants (e.g. K809TAG). Based on previous reports (PMID: 31900387), we then tested a weak human neuron-specific enolase promoter. This reduced expression level and improved localization of NF186. However, since we still observed some neurons with mislocalized NF186 WT even with the enolase promoter, we found it important to quantitively compare the AIS length of WT construct and amber mutants to surrounding untransfected cells. On the other hand, since we did not have overexpression and mislocalization problem with Nav1.6 WT construct (all observed neurons have signal localizing in the AIS), we measured only the AIS length of the amber mutants. However, to avoid any confusion, we will also measure the AIS size of the neurons expressing Nav1.6 WT construct and compare it to surrounding cells and amber mutants. For this, we will need to perform new experiments and acquire new images. We will include the data in the revised manuscript.
- Fig. 4: why did the authors chose these cells for electrophysiology experiments and not neurons? Explain the rationale in the text or, alternatively, cite similar studies using the same tool.
Due to the branched neuronal processes which cause the space clamp problem in voltage clamp experiments with neurons, round and none-branching cells are frequently used to examine the biophysical properties of ion channels, including Nav1.6. By far, most of studies investigating the biophysical properties of NaV1.6 channels were performed in neuroblastoma cells e.g. ND7/23 and N1E-115-1 cells (PMID: 25874799; 25242737). We tested these two types of cells and found that N1E-115-1 cells supported higher expression level of the recombinant NaV1.6 channels on the cell surface than the ND7/23 cells (Suppl. Fig 5). Hence, N1E-115-1 were more suitable to get robust and reliable recordings (as we also discuss above in the response to reviewer’s comment). We will clarify this in the revised manuscript.
- Fig.4, biophysical properties: did the authors find differences in passive properties? Measures of resting potential, membrane resistance and cell capacitance should be reported.
Passive properties such as resting membrane potential and membrane resistance are important functional features in neurons measured in current clamp experiments, but not applicable for ND7/23 and N1E-115-1 cells used in our voltage clamp experiments. To measure the Na+ current mediated by WT or mutant NaV1.6 channels expressed in N1E-115-1 cells, the endogenous Na+ channels were blocked by tetrodotoxin and the endogenous K+ channels were blocked by tetraethylammonium chloride, CsCl and CsF in extracellular and intracellular solutions. Under these conditions, resting potential and membrane resistance are not relevant for experiments. Cell capacitance reflects the size of the cell surface area, which can affect the number of channels expressed on the cell surface. To eliminate the effect of different cell sizes, Na+ current densities normalized by cell capacitances were used in our experiments. We will report on these values in the revised manuscript.
- Fig 4, STORM images. The periodic distribution of the dots should be enhanced with some sort of arrows or lines, for the non-specialist audience.
Based on the comments from multiple reviewers, we plan to obtain additional dSTORM images of the neurons expressing recombinant Nav1.6 WT or amber mutants. We also intend to improve the visualization of these results by updating/modifying existing figures and including quantitative data.
- Line 374: rat or mouse primary neurons?
We are here referring to both, rat and mouse neurons. The images shown in Fig. 06 and Suppl. Fig. 08 were obtained from rat cortical neurons expressing Nav1.6 or fluorescent reporter. However, we were also able to successfully transduce mouse neurons with AAV92A carrying orthogonal translational machinery (data not shown). We will clarify this in the revised manuscript.
**Referees cross-commenting**
I fully agree with the following remarks from Reviewers #3, #4 and #5. This is a point that I have raised in my report too. The authors need better images to show the periodicity we visualization, and a quantification would be of great benefit to support the claim with numbers (and how these compare to similar studies in the literature):
R3: 2. For the dSTORM analysis of the tagged Nav1.6 protein, I also cannot tell there is periodic organization from the image directly. Some analysis is needed there. R4: 2."As there was no obvious difference in the nanoscale organization of the NaV1.6WT 317 -HA or NaV1.6TAG 318 -HA channels (Fig. 4. e-g), these experiments confirmed that the NaV1.6 overexpression, TCO*A319 Lys incorporation, and click labeling did not affect the nanoscale periodic organization of the sodium channels in the AIS." It is clearly noticeable that for WT, the spot density is more compared to the other two mutants. Why is that so? Using cluster analysis, one can quantify spot density and discuss nanoscale organization quantitatively. The author should quantify the periodicity and compare it among different variants and with previous reports. R5: 3. The authors claim that there was no obvious difference in the nanoscale organization of the NaV1.6WT 317 -HA or NaV1.6TAG 318 -HA channels (Fig. 4. e-g), but it is hard to conclude this without any quantification and statistical analysis. Sodium channels have been shown to be associated with the membrane-associated periodic skeleton structures in neurons and average autocorrelation analysis has been developed to quantify the degree of periodicity of such structural organizations (Han et al. PNAS 114(32)E6678-E6685, 2017). The authors should use this approach to quantify and compare the average autocorrelation amplitudes.
As we outlined in our responses to the individual reviewers’ comments below, we will address these questions by performing new experiments and quantifications.
I also agree with these comments from Reviewers #3 and #5:
R3: 4. It is unclear, for all the presented data, whether all the cells are collected from a single biological replicate or from multiple replicates. At least 2-3 replicates are needed to see the reproducibility in terms of labeling efficiency, and other related conclusions. R5: 1. The authors should indicate how many replicates were performed and how many cells were analyzed for each experiment.
We thank the reviewers for bringing this up. By mistake, we omitted this important information. We will include it in the revised manuscript, but we would like to highlight here that each experiment was repeated at least 3 times.
Reviewer #3
- There is some patch-like background from the 488 channel from the click reaction, some of which have very as strong signal as the staining on the neurons. What is the potential cause for this? With immunostaining on HA, the background doesn't affect too much on the image data interpretation. However, the major goal of this method development is to use it in live-cell without immunostaining. Without another reference, the high background might cause issues in data interpretation. Can the author also suggest way to avoid or lower this in the discussion?
We thank the reviewer for bringing this up. We have occasionally observed patch-like background in what appears to be the cell debris. Such dead cells do not have an intact cell membrane and therefore can absorb cell-impermeable ATTO488-tetrazine dye during click labeling. This kind of background is also present in the control neurons transfected with the WT Nav1.6, which suggests that it originates from the UAA and tetrazine-dye accumulations. Additionally, since these patches are not visible with the immunostaining, they do not contain our protein of interest, which further confirms that they contain only dye and UAA accumulations. Depending on the neuron prep/quality before and after transfections, the presence of these patches is more or less obvious. However, despite the background we did not have problems identifying AIS during live cell imaging. Especially when overall neuronal health is optimal after transfections, AIS can easily be distinguished from patches that are positioned outside of labeled neurons. We will investigate this further and discuss it in the revised manuscript.
- For the dSTORM analysis of the tagged Nav1.6 protein, I also cannot tell there is periodic organization from the image directly. Some analysis is needed there.
We will address this in the revised manuscript by performing additional experiments and quantifications. We also wrote a detailed answer below, in the response to the other reviewers.
- The authors use the AIS length as a parameter to evaluate the function of the clickable mutant of NF186, and using patch clamp for functional validation of the clickable mutant of Nav1.6. In both cases, the comparison is done between the mutant and the WT construct, but both in transfected cell and exogenously expressed. It's also worth comparing with untransfected cells as the true native situation.
We agree with the reviewer that it is important to compare transfected cells with untransfected cells. As the reviewer points out, we have already performed some of these comparisons. When it comes to the NF186, we used the AIS length as a parameter to estimate if the expression of clickable mutant affected the AIS structure. As we show in the Fig. 02, we co-immunostained neurons transfected with NF186-HA WT or TAG constructs. We used HA antibody to detect neurons expressing NF186, while the ankG was used as a marker of the AIS length. To check if the AIS length of transfected cells is affected, we compared the length of transfected cells (expressing NF186, HA+) to surrounding untransfected cells (HA-). When it comes to the Nav1.6, we also compared the AIS length of cells expressing Nav1.6 (HA+) to surrounding untransfected cells (HA-). Similarly to the experiments with NF186, this allowed us to check if the expression of the recombinant Nav1.6 affect the AIS structure. What is missing is the comparison with untransfected conditions (i.e. neurons that are simply stained with ankG). We assume that is what the reviewer is referring to? We will also include these data in the revised manuscript. Furthermore, since we introduced a labeling modification in NaV1.6, we wanted to check if such modification would affect its function. To do so, as routinely done in the field (PMID: 25874799), we rendered the WT and TAG channels TTX-resistant and recorded only recombinant Na+ currents in neuroblastoma cells in the presence of TTX. Perhaps we misunderstand the reviewer’s comment, but in this regard measurements of untransfected cells are not relevant since they would not allow us to compare WT and TAG mutants.
- It is unclear, for all the presented data, whether all the cells are collected from a single biological replicate or from multiple replicates. At least 2-3 replicates are needed to see the reproducibility in terms of labeling efficiency, and other related conclusions.
We thank the reviewer for the observation. By mistake, we omitted this important information. We will include in the revised version of the manuscript. We would like to highlight here that each experiment was repeated at least 3 times.
Reviewer #4
1."Confocal microscopy revealed that the hNSE promoter lowered the WT and clickable NF186-HA expression levels and consequently improved the localization of these proteins." Is the lower expression level a measure of localization improvement? How does the author conclude that the localization has improved?
Previous report (PMID: 31900387) suggested that the overexpression of the recombinant WT NF186 can affect its trafficking, leading to the NF186 mislocalization. We observed the same in our experiments with CMV NF186 (in particular for NF186 WT). Hence, based on the PMID: 31900387 we probed weak neuron specific enolase promoter. Since the WT was the most problematic in terms of the ectopic expression, we checked if AIS localization was improved with enolase promoter for this construct. To this aim, we counted number of neurons that with mislocalized signal or with the signal in the AIS for both, CMV and enolase promoter. We could observe that number of neurons with mislocalized signal was lower for enolase promoter. Since there were more neurons with the AIS-specific signal when NF186 was expressed from enolase promoter compared to CMV, we concluded that enolase promoter lowered expression and improved localization of the NF186. Therefore, we used enolase promoter for click labeling of NF186 amber mutants. We will include the results of this analysis in the revised version of the manuscript.
2."As there was no obvious difference in the nanoscale organization of the NaV1.6WT 317 -HA or NaV1.6TAG 318 -HA channels (Fig. 4. e-g), these experiments confirmed that the NaV1.6 overexpression, TCO*A319 Lys incorporation, and click labeling did not affect the nanoscale periodic organization of the sodium channels in the AIS." It is clearly noticeable that for WT, the spot density is more compared to the other two mutants. Why is that so? Using cluster analysis, one can quantify spot density and discuss nanoscale organization quantitatively. The author should quantify the periodicity and compare it among different variants and with previous reports.
We thank the reviewer for these suggestions. We will address these remarks by performing additional new experiments and quantifications. The difference in the level of the expression of the recombinant Nav1.6 might explain differences in the spot density for WT vs. TAG clickable mutants. However, as the reviewer suggested quantitative analysis is needed to address these concerns. We also intend to quantify the periodicity and compare it among different variants and with previous reports. It is just important to note that in the current version of the manuscript we looked at the nanoscale organization of the subset of Nav1.6 channels. The reason being that we used anti-HA antibody which will only detect our recombinant protein which got incorporated into the AIS and not the endogenous Nav1.6.
Minor comments
1."Although NF186K809TAG 158 -HA (Supplementary Fig. 4) showed bright click labeling, we excluded it from the analysis due to its frequent ectopic expression along the distal axon." How frequently is this bright click labeling observed for this mutation? Is it not observed for other mutations at all? The authors should state this point clearly with some statistics.
We are not sure what is the exact question from the reviewer. If we understand it correctly, the reviewer is asking us to quantify how frequent was the ectopic expression of this amber mutant compared to other mutants? And not the click labeling (as written in their original comment), since click labeling was observed for all the mutants independently of their ectopic expression?
2."Immunostaining with anti-HA antibody revealed that the expression of NaV1.6WT 239 -HA on the membrane of the N1E-115-1 cells was higher than on the ND7/23 cells (Supplementary Fig. 5a-c). However, click labeling of both NaV1.6K1425TAG 240 -HA and NaV1.6K1546TAG 241 -HA with ATTO488-tz was not successful (Supplementary fig. 5d) indicating insufficient expression of the clickable constructs." Is this due to insufficient expression level or accessibility? The author should make this statement clear.
We thank the reviewer for bringing this up. We will clarify this in the revised version of the manuscript. We believe that the click labeling of the K1546TAG mutant in N1E-115-1 cells is absent due to the insufficient expression of the channels on the membrane, since this mutant was successfully labeled in the primary neurons that represent more native environment and where Nav1.6 form high-density clusters. K1425TAG mutant is not labeled due to the insufficient expression on the membrane in N1E-115-1 cells as well. However, since this mutant is also poorly labeled in primary neurons, we can speculate that K1425TAG position might be less accessible for the tetrazine-dye compared to K1546TAG. To further support our claim that due to the insufficient expression click labeling is low/absent in neuronal cells, we can use NF186 as an additional example. When NF186 was expressed from strong CMV promoter, we observed click labeling for all the mutants in ND7/23 cells (Suppl. Fig.01). However, when CMV was replaced with neuron specific enolase promoter, the expression was of NF186 was substantially lower in ND7/23 cells and click labeling was absent (data not shown). We will clarify this in the revised manuscript.
- Authors should clearly state the drift correction procedure of 3D STORM data. What are the localization precision and photon count for 3D STORM experiments?
We processed 3D dSTORM data in NIS-elements AR software. We used the automatic drift correction from the NIS-elements software that is based on the autocorrelation. We will provide further and updated information in the revised manuscript, including the localization precision and photon count for the new dSTORM images.
- "Click labeling of NaV1.6 channels in living primary neurons" What kind of primary neurons have been used for click labeling of NaV1.6 channels? Is there any specific reason why authors have chosen cortical neurons for labeling NF186? Does this labeling strategy depend on primary neuron type?
For the establishment and click labeling of Nav1.6 we used primary rat cortical neurons (Fig. 03, Fig. 06). The same neuronal type has been used for click labeling of NF186 (Fig. 02). We established labeling of the AIS components in cortical neurons because we use those routinely in the laboratory. However, this labeling strategy does not depend on the neuronal type. As we show in Fig. 05, to study localization of the loss-of-function pathogenic Nav1.6 variants we used mouse hippocampal neurons. The reason for this is that in previous study the same neuronal type was used to characterize these two mutations (lines 361-362). This demonstrates nicely that method can be easily transferred to any neuronal type. Furthermore, we were also able to label Nav1.6 and NF186 in mouse cortical neurons (data are not shown in the manuscript). We will clarify this in the revised manuscript.
Reviewer #5
1.Throughout the manuscript, only one representative image containing one AIG is shown for each condition without statistics and quantifications, so the conclusions are not sufficiently convincing. For example, in Fig. 1b, c, e; Fig. 2b,c,d,e; Fig. 3b,c,d,e ; Fig. 5c; and Supplementary Fig.1-6, the authors should quantify the average fluorescence intensities both for HA immunostaining and ATTO488-tz labeling in different conditions, as well as the labeling ratios (fluorescence intensity ratios between ATTO488 and AF647/AF555) . Without statistics and quantifications, it is unclear whether there is any significant difference between the constructs with different TAG positions, or between different transfection methods (e.g., lipofectamine 2000 vs 3000).
We agree with the reviewer that the quantitative analysis is important and we will provide more quantitative data in the revised manuscript. At the same time, we are a bit confused by this comment which seems to refer to missing quantifications in one of the schemes (Fig. 1) and overlooks existing quantifications (e.g. quantitative analysis of the data set from Fig. 5c is shown in Fig. 5d). However, as suggested by the reviewer and to strengthen our data, in addition to the quantifications already provided in the manuscript (e.g. Fig. 2d: AIS length of NF186TAG constructs; Fig. 3f: AIS length of Nav1.6 TAG constructs; Fig. 5d: click-labeling intensity of LOF mutants), we intend to quantify the differences between labeling ratios of different mutants and transfection methods. When it comes to the different transfection methods, some data is already provided in the manuscript (e.g. we counted number of transfected versus transduced neurons) but we intend to clarify and expand on this in the revised manuscript.
- The only quantification done was for the average AIS length, but the statistical tests should be performed between different conditions and the corresponding P values should be provided. It seems that the transfected neurons generally have a longer AIS length than the transfected neurons (Fig. 2d and 3f). Could the authors provide an explanation for this?
We are a bit confused by the first part of this comment. We measured the AIS lengths of NF186 WT or NF186 TAG as well as Nav1.6 TAG and compared it to the AIS lengths of surrounding untransfected cells (Fig. 2d and Fig.03f). In addition, we compared the AIS lengths of the NF186 WT and TAG to each other, and Nav1.6 TAG to each other. To analyze the differences, we performed statistical tests and provided the corresponding p values in the figure legends (Fig. 02 and 03). Further details on the statistical analysis are provided in supplementary tables (Suppl. table 01 and 02). Regarding the 2nd question, we have also noticed that the AIS lengths of transfected neurons appear longer than those of untransfected cells. This seems to be more pronounced in the case of NF186 which is expressed at the higher level compared to the Nav1.6. The appearance of slightly longer AIS is most likely the consequence of the fact that recombinant constructs are overexpressed in the neurons that express endogenous NF186 and Nav1.6. However, this difference in the AIS length is not significant to the controls. We will discuss this further in the revised manuscript.
- The authors claim that there was no obvious difference in the nanoscale organization of the NaV1.6WT 317 -HA or NaV1.6TAG 318 -HA channels (Fig. 4. e-g), but it is hard to conclude this without any quantification and statistical analysis. Sodium channels have been shown to be associated with the membrane-associated periodic skeleton structures in neurons and average autocorrelation analysis has been developed to quantify the degree of periodicity of such structural organizations (Han et al. PNAS 114(32)E6678-E6685, 2017). The authors should use this approach to quantify and compare the average autocorrelation amplitudes.
We are thankful to the reviewer for suggestions on how to quantify the periodicity of recombinant sodium channels and how to more accurately compare WT and TAG mutants at the nanoscale level. We will perform additional experiments and analysis in order to address the concerns of this and other reviewers.
- The authors should also obtain dSTORM images for the click labeled neurons to demonstrate if the click labeling method would provide sufficient labeling efficiency for dSTORM, compared to immunostaining (HA and Ankyrin G immunostaining).
We would like to thank the reviewer for this suggestion. We have already shown in our previous work that STED can be performed with click labeled neurons (PMID: 35031604). When it comes to this manuscript and AIS labeling, we have already obtained preliminary dSTORM images of click-labeled NF186. Since the expression of Nav1.6 is lower compared to NF186, the labeling is also less bright and dSTORM is a bit more challenging. To try to overcome this issue, in addition to dSTORM of click-labeled Nav1.6, we are planning to try click-PAINT (PMID: 27804198). Click-PAINT has been used for super-resolution imaging of less abundant targets in cells and could possibly allow super-resolution imaging of Nav1.6. We will report on these new experiments in the revised version of the manuscript.
- It seems that the click labeling has a off-target/background labeling in the soma of the neuron (see Fig. 3c,d. Could the authors quantify and determine the sources of such off-target labeling?
We thank the reviewer for pointing this out. We will clarify this in the revised manuscript, but by looking at the other examples from our dataset it appears to us that this background is present in WT constructs as well. In the current version of the manuscript, this is not clear since the WT image that is shown in the Fig. 03b is a single plane confocal image. Therefore, we will replace it in the revised manuscript with a z-stack in which the presence of the background is more obvious (due to the maximum intensity projection). In addition, we will conduct additional control experiments to clarify this.
Minor comments:
- The authors should indicate how many replicates were performed and how many cells were analyzed for each experiment.
We thank the reviewer for bringing this up. By mistake, we omitted this important information. We will include this information in the revised manuscript, but we would like to highlight here that each experiment was repeated at least 3 times.
- The display range (i.e., intensity scale bar) was indicated only for a small portion of the fluorescence images. It is better to be consistent and show the display range for all images presented.
We will include intensity scale bars in all the images in the revised version of the manuscript.
3. Description of the revisions that have already been incorporated in the transferred manuscript
Not applicable.
4. Description of analyses that authors prefer not to carry out
Reviewer #3, comment #5. One application presented in this manuscript is to evaluate the effect of epilepsy-causing mutations of Nav1.6. By comparing the intensity of ATTO488, the result suggests that there is no significant impact of these mutations on membrane tracking. I am wondering if the author should study the membrane tracking by also looking at the diffusion in live-cell with the labeling method. The comparison of the intensity only can be achieved by just immunostaining. It doesn't really demonstrate the benefit of live-cell labeling and imaging with the presented method.
Generally speaking, one of the advantages of click labeling is its compatibility with live cell labeling. As the reviewer also points out, this is especially useful for live-cell imaging but is not limited to it. In addition, click labeling allows selective labeling of membrane population of Nav1.6 in living neurons. We took advantage of this and used cell-impermeable dyes to label unnatural amino acids incorporated into extracellular part of Nav1.6 (Scheme 03a). On the contrary, HA tag that allows immunodetection of recombinant Nav1.6 is added to the intracellular C terminus. Hence, by anti-HA immunostaining total (intra- and extracellular) epilepsy-causing Nav1.6 channel population will be detected. That is why in this case live-cell click labeling was advantageous compared to the conventional immunostaining. We will clarify this in the revised manuscript. In addition, we would like to note that when we started the experiments with the epilepsy-causing mutations, we wanted to a) check if they are present on the membrane and b) depending on the outcome of those experiments follow the trafficking of these LOF Nav1.6 mutants. Since patch clamp recordings of pathogenic Nav1.6 showed loss of Na+ currents, we at first assumed that they are not properly expressed on the membrane. However, our click labeling showed that the pathogenic channels were detected at the AIS membrane despite the loss of Na+ currents. This was also somewhat surprising to us and we would love to investigate this further. We also appreciate the reviewer’s suggestion in this regard and we hope to be able to use all the advantages of our labeling approach in our follow-up studies. However, keeping in mind time and resources limitations, live-cell trafficking study might be beyond the scope of this revision.
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Referee #5
Evidence, reproducibility and clarity
Summary:
In this manuscript, Nevena Stajković et al. present a method for live labeling of the proteins localized at the axon initial segment (AIS) of cultured neurons using unnatural amino acids (UAAs) carrying strained alkenes and click chemistry. Using this method, the authors showed the successful labeling of two AIS-localized proteins, the 186 kDa isoform of neurofascin (NF186) and the 260 kDa voltage-gated sodium channel (NaV1.6). The authors also showed the transduction of neurons using adeno-associated viruses (AAVs) had higher efficiency than transfection by lipofectamine in delivering the vectors expressing required components for the click labeling.
Major comments:
- Throughout the manuscript, only one representative image containing one AIG is shown for each condition without statistics and quantifications, so the conclusions are not sufficiently convincing. For example, in Fig. 1b, c, e; Fig. 2b,c,d,e; Fig. 3b,c,d,e ; Fig. 5c; and Supplementary Fig.1-6, the authors should quantify the average fluorescence intensities both for HA immunostaining and ATTO488-tz labeling in different conditions, as well as the labeling ratios (fluorescence intensity ratios between ATTO488 and AF647/AF555) . Without statistics and quantifications, it is unclear whether there is any significant difference between the constructs with different TAG positions, or between different transfection methods (e.g., lipofectamine 2000 vs 3000).
- The only quantification done was for the average AIS length, but the statistical tests should be preformed between different conditions and the corresponding P values should be provided. It seems that the transfected neurons generally have a longer AIS length than the transfected neurons (Fig. 2d and 3f). Could the authors provide an explanation for this?
- The authors claim that there was no obvious difference in the nanoscale organization of the NaV1.6WT 317 -HA or NaV1.6TAG 318 -HA channels (Fig. 4. e-g), but it is hard to conclude this without any quantification and statistical analysis. Sodium channels have been shown to be associated with the membrane-associated periodic skeleton structures in neurons and average autocorrelation analysis has been developed to quantify the degree of periodicity of such structural organizations (Han et al. PNAS 114(32)E6678-E6685, 2017). The authors should use this approach to quantify and compare the average autocorrelation amplitudes.
- The authors should also obtain dSTORM images for the click labeled neurons to demonstrate if the click labeling method would provide sufficient labeling efficiency for dSTORM, compared to immunostaining (HA and Ankyrin G immunostaining).
- It seems that the click labeling has a off-target/background labeling in the soma of the neuron ( see Fig. 3c,d. Could the authors quantify and determine the sources of such off-target labeling?
Minor comments:
- The authors should indicate how many replicates were performed and how many cells were analyzed for each experiment.
- The display range (i.e., intensity scale bar) was indicated only for a small portion of the fluorescence images. It is better to be consistent and show the display range for all images presented.
Significance
Unnatural amino acid (UAA)-based minimal tags for live-cell protein labeling in mammalian cells were invented about ten years ago (Lang et al., 2012b, Lang et al., 2012a, Nikic et al., 2014, Plass et al., 2012, Uttamapinant et al., 2015), and these authors recently introduced this labeling method to label live cultured neurons (Arsić et al., 2022). Therefore, it is unclear whether the method present in this manuscript has any significant advance compared to the Arsić et al. paper, given that the major difference between the two papers is that in the current manuscript, AIS localized proteins were labeled, whereas in the Arsić et al. paper, neurofilaments were labeled in the neurons. Therefore, the method presented in the current manuscript does not provide much novelty or technical advance compared to what has been described in the Arsić et al. paper.
My expertis is super-resolution flurescence imaging, cell labeling methods, and neurobiology.
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Referee #4
Evidence, reproducibility and clarity
The manuscript demonstrates a novel method of labeling two large components of the initial axon segment, neurofascin (NF186) and Nav1.6 using unnatural amino acids and click chemistry in live cells. They have applied their method for epilepsy causing two Nav1.6 variants without affecting their functionality. Since these proteins are larger in size, selecting the labeling sites and transfection efficiency become critical factors. They have targeted different lysine sites and shown the best performing labeling site. Also, they have developed a viral vector to improve transfection efficiency.
The experiments are well designed, and the manuscript is nicely written. In my opinion, the manuscript can be accepted, but the author should address the following comments.
Major comments
- "Confocal microscopy revealed that the hNSE promoter lowered the WT and clickable NF186-HA expression levels and consequently improved the localization of these proteins." Is the lower expression level a measure of localization improvement? How does the author conclude that the localization has improved?
- "As there was no obvious difference in the nanoscale organization of the NaV1.6WT 317 -HA or NaV1.6TAG 318 -HA channels (Fig. 4. e-g), these experiments confirmed that the NaV1.6 overexpression, TCO*A319 Lys incorporation, and click labeling did not affect the nanoscale periodic organization of the sodium channels in the AIS." It is clearly noticeable that for WT, the spot density is more compared to the other two mutants. Why is that so? Using cluster analysis, one can quantify spot density and discuss nanoscale organization quantitatively. The author should quantify the periodicity and compare it among different variants and with previous reports.
Minor comments
- "Although NF186K809TAG 158 -HA (Supplementary Fig. 4) showed bright click labeling, we excluded it from the analysis due to its frequent ectopic expression along the distal axon." How frequently is this bright click labeling observed for this mutation? Is it not observed for other mutations at all? The authors should state this point clearly with some statistics.
- "Immunostaining with anti-HA antibody revealed that the expression of NaV1.6WT 239 -HA on the membrane of the N1E-115-1 cells was higher than on the ND7/23 cells (Supplementary Fig. 5a-c). However, click labeling of both NaV1.6K1425TAG 240 -HA and NaV1.6K1546TAG 241 -HA with ATTO488-tz was not successful (Supplementary fig. 5d) indicating insufficient expression of the clickable constructs." Is this due to insufficient expression level or accessibility? The author should make this statement clear.
- Authors should clearly state the drift correction procedure of 3D STORM data. What are the localization precision and photon count for 3D STORM experiments?
- "Click labeling of NaV1.6 channels in living primary neurons" What kind of primary neurons have been used for click labeling of NaV1.6 channels? Is there any specific reason why authors have chosen cortical neurons for labeling NF186? Does this labeling strategy depend on primary neuron type?
Significance
Although the use of unnatural amino acids and click chemistry for labelling has been shown before from the same group, labelling large proteins, especially ion channels, without affecting their function is always challenging because of the accessibility of the labelling site as well as poor transfection efficiency. Here, they have selected two such large essential proteins: NF186 and Nav1.6, which are associated with epilepsy, and developed a method for fluorophore labelling with minimal perturbation. Other approaches namely using fluorescent proteins, biotin-streptavidin chemistry and halo-tag have been reported before to label these proteins, but these have a strong impact on their mislocalisation and perturbing their functionality. Therefore, this method will be of great importance in the field of studying these proteins.
Expertise: Live-cell confocal and multi-photon microscopy imaging, Super-resolution microscopy imaging, Live-cell labelling, and Amyloid aggregations
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Referee #2
Evidence, reproducibility and clarity
Summary:
This study proposes a novel tool for AIS live and fixed labelling based on biorthogonal click chemistry. Stajkovic and colleagues used this method to specifically label the AIS proteins NF186 and Nav1.6 of mouse and rat neurons, and did a thorough process of optimization to get convincing results. The authors considered different promoters, transfection strategies and the use of AAVs to get the most efficient labelling strategy for both proteins. They have also gone through a strong validation process based on transfection efficiency, quality of staining, potential effects on AIS length and nanostructure, and electrophysiological properties. Finally, Stajkovic and colleagues used this tool to study how two epilepsy-causing Nav1.6 mutant variants affect AIS function, providing interesting data to the understanding of this pathology. In summary, this method convincingly overcomes some well-described issues associated with pre-existing AIS live cell labelling tools by being minimally "invasive" to the proteins of interest. Besides the scientific content, another strong point of this article is the clarity of the manuscript and the figures: the presence of schematics (i.e. Fig. 1) and the detailed description of experiments and results will help non-specialist readers to follow the study. I strongly recommend this article for journal publication.
Major comments:
I have no major comments
Minor comments:
I have some minor comments:
- On lines 107 and 108, the sentence "The C-terminal HA-tag allowed us to detect the full-length NF-186 protein by immunostaining it with an anti-HA antibody" would have a better place just after lines 104-105 " [...] we modified the previously described plasmid (Zhang et al., 1998) by moving the hemagglutinin (HA) tag from the N terminus to the C terminus".
- Fig.2b: the AnkG staining looks substantially longer than that showed in c. However, the results on AIS length show no significant changes in between the groups. This is visually misleading, the authors should choose a picture for the WT construct that is representative of the data.
- Line 238: what is the rationale behind choosing these cells? For example, have they been used in other studies for similar purposes? If so, please provide the reference.
- Figure 3c, the authors omitted the comparison with the WT construct this time, as opposed to the neurofascin experiments. What is the reason?
- Fig. 4: why did the authors chose these cells for electrophysiology experiments and not neurons? Explain the rationale in the text or, alternatively, cite similar studies using the same tool.
- Fig.4, biophysical properties: did the authors find differences in passive properties? Measures of resting potential, membrane resistance and cell capacitance should be reported.
- Fig 4, STORM images. The periodic distribution of the dots should be enhanced with some sort of arrows or lines, for the non-specialist audience.
- Line 374: rat or mouse primary neurons?
Referees cross-commenting
I fully agree with the following remarks from Reviewers #3, #4 and #5. This is a point that I have raised in my report too. The authors need better images to show the periodicity visualization, and a quantification would be of great benefit to support the claim with numbers (and how these compare to similar studies in the literature):
R3: 2. For the dSTORM analysis of the tagged Nav1.6 protein, I also cannot tell there is periodic organization from the image directly. Some analysis is needed there. R4: 2."As there was no obvious difference in the nanoscale organization of the NaV1.6WT 317 -HA or NaV1.6TAG 318 -HA channels (Fig. 4. e-g), these experiments confirmed that the NaV1.6 overexpression, TCO*A319 Lys incorporation, and click labeling did not affect the nanoscale periodic organization of the sodium channels in the AIS." It is clearly noticeable that for WT, the spot density is more compared to the other two mutants. Why is that so? Using cluster analysis, one can quantify spot density and discuss nanoscale organization quantitatively. The author should quantify the periodicity and compare it among different variants and with previous reports. R5: 3. The authors claim that there was no obvious difference in the nanoscale organization of the NaV1.6WT 317 -HA or NaV1.6TAG 318 -HA channels (Fig. 4. e-g), but it is hard to conclude this without any quantification and statistical analysis. Sodium channels have been shown to be associated with the membrane-associated periodic skeleton structures in neurons and average autocorrelation analysis has been developed to quantify the degree of periodicity of such structural organizations (Han et al. PNAS 114(32)E6678-E6685, 2017). The authors should use this approach to quantify and compare the average autocorrelation amplitudes.
I also agree with these comments from Reviewers #3 and #5:
R3: 4. It is unclear, for all the presented data, whether all the cells are collected from a single biological replicate or from multiple replicates. At least 2-3 replicates are needed to see the reproducibility in terms of labeling efficiency, and other related conclusions. R5: 1. The authors should indicate how many replicates were performed and how many cells were analyzed for each experiment.
Significance
The proposed tool in this article represents a big step forward in the field of AIS live cell imaging. As stated by the authors in the introduction, previous studies have described methods based on tagging fluorescent proteins to the protein of interest or labelling the extracellular part of proteins with antibodies. The same studies reported several issues: the interference with important domains of the protein due to the size and the position of the tag in the case of fluorescent proteins (Dumitrescu et al., 2016, PMID: 27932952; Dzhashiashvili et al., 2007, PMID: 17548513), or the failure to report plasticity changes in the AIS in the case of antibodies (Dumitrescu et al., 2016, PMID: 27932952). This tool can be useful for research teams aiming to understand, for example, the live development of the AIS or understanding the trafficking of its proteins. The authors have applied this method to two transmembrane proteins (NF186 and Nav1.6), but as they state in their discussion, it will be useful to tag other candidates, including cytoplasmic proteins. One of the main problems of immunocytochemistry is to find the right antibody to detect your protein. Sometimes, absence of proof is not proof of absence: just because the protein is not detected via immunostaining does not mean that the protein is not expressed there. This tool offers an alternative to these challenging scenarios.
My expertise keywords: axon initial segment, neuronal polarity, axon biology, super resolution microscopy.
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logseq.com logseq.com
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Connect your ideas like you do
is easy connect the different pages, also the tag are like page.
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developer.chrome.com developer.chrome.com
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When the HTML parser finds a <script> tag, it pauses the parsing of the HTML document and has to load, parse, and execute the JavaScript code. Why? because JavaScript can change the shape of the document using things like document.write() which changes the entire DOM structure
This is why you put script tags at the bottom of an html document.
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www.biorxiv.org www.biorxiv.org
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Reply to the reviewers
We are sincerely grateful to the reviewers for several key comments that led us to correct some mistakes and better appreciate how to put our findings in the context of recently published data. These changes undoubtedly improved the manuscript.
Many other reviewer comments seem to equate chaperone binding with a functional chaperone role in de novo folding. These are not the same. Cytosolic chaperones presumably “sample” nearly every protein that is synthesized by cytoplasmic ribosomes. This does not mean that every such protein would misfold if even one of those chaperones failed to bind it. If we want to understand what chaperone mutations might cause human disease due to septin misfolding, for example, it will not be enough to catalog all the chaperones that bind septins. We have already done that. What will help is to understand which chaperones make functional contributions to septin folding and complex assembly. Our study is the first to experimentally address chaperone roles in de novo septin folding, period. We take responsibility for not being sufficiently clear about the goals of our work, and, to emphasize these points, we added one sentence to the Introduction and revised another.
Another consistent criticism was that the use of the E. coli system, both in vivo and in vitro, limited our ability to gain insight into the folding of septins in eukaryotic cells and led to a “tessellated view”. For example, reviewers claimed that our model about translation elongation rates for Cdc12 were “based mainly on the E. coli system and bioinformatics analysis”. We disagree with this interpretation. Key evidence in support of our model come from published data in yeast, specifically the much higher density of ribosomes on Cdc12 and the accumulation of ribosomes on the Pro-rich cluster near the Cdc12 N terminus. These are precisely the kinds of “more stringent analysis” in “authentic yeast” (to use Reviewers’ language) that we would have wanted to do to test our model, had they not already been done by others. Without specific suggestions, we struggle to imagine what other kinds of experiments the Reviewers have in mind, apart from a eukaryotic version of a reconstituted cell-free translation system, which Reviewer #1 admits “would be substantially difficult” and “time consuming”. While we are intrigued by the reconstituted eukaryotic cell-free translation system that was published last year (which we mentioned on lines 994-995) and look forward to exploring it in future studies, it is not commercially available and we agree that the amount of effort required to prepare it ourselves is unrealistic for the current study. Most importantly, we do not find in the critiques provided any specific reason why our E. coli-based systems experiments are intrinsically less “stringent” or “rigorous”.
Accordingly, we think that, together with the results of multiple new experiments (detailed below), the extensive re-writing and re-ordering that we have done in the revised manuscript will be enough to better emphasize the importance and rigor of our findings and thus to address all of the Reviewers’ specific concerns.
Reviewer 1 thought that our manuscript “does not even provide new information, since the involvement of CCT and the Hsp70 system is not novel” and thought that “the key finding of this manuscript is how chaperones are involved in the de novo folding of septins, which is not conceptually new because of previous findings, including those of the authors”. Reviewer #3 also stated that “the function of Tric/CCT in septin folding and assembly is well documented”.
We were quite surprised at this reaction, since we dedicated a significant portion of the original manuscript (lines 68-76 and 319-322) to explicitly discussing the only other paper in the literature that specifically addresses the question of whether or not CCT is required for de novo septin folding. As a reminder, that paper explicitly stated that “it is unlikely that CCT is required to fold septins de novo” and “septins probably do not need CCT for biogenesis or folding”. With regard to involvement of the Hsp70 system, the only existing evidence in the literature on this subject is the aggregation of some septins in ssb1∆ ssb2∆ cells. Like the CCT study, that study did not distinguish whether this was a result of problems during septin synthesis and before septin complex assembly, or, alternatively, whether pre-folded and assembled septins were subject to disassembly, misfolding, and aggregation. Our experiments specifically test the fate of newly-synthesized septins prior to assembly in living cells. Our previous findings documented physical interactions between wild-type septins and multiple chaperones but did not address whether these interactions had any functional relevance. We previously reported functional effects of interactions between chaperones and MUTANT septins but, again, these studies did not address functional chaperone requirements for WILD-TYPE septins. While we did our best to highlight these points in the original document without devoting excessive amounts of text, we accept responsibility for not making these points sufficiently clear and to address this issue we added additional text, including the text quoted above, to the Introduction.
While Reviewer #3 commented that the manuscript “is overall well presented”, Reviewer 1 thought that the manuscript was “complicated to read” with “no logical connections, just a list of many results” and mentioned that part of the difficulty was “that it contains many negative results”.
In addition to reorganizing the manuscript, as suggested by the reviewers, we added more text at the beginning and end of nearly every section to even more explicitly state the logical connections between results. In our opinion, negative results of properly controlled experiments are valuable to the research community, and we do not understand what it is about negative results that makes them difficult to read about. Many of the extra experiments we performed were in anticipation of being asked to perform them by reviewers, some of which generated negative results. We are reluctant to remove negative results unless there is a more compelling reason. For example, to address another reviewer concern, we did remove the negative results with the Ydj1–Ssa2 compensatory mutants.
Reviewer #2: “4) Figure 2: The labeling on the protein structure makes it seem like the exact region for Ydj1 and Hsp70 was experimentally identified, when it hasn’t.”
We acknowledge that the first sentence of the figure legend (“the colored ribbon follows the color scheme in the sequences at right for overlapping β-aggregation, Ydj1 and Hsp70-binding sites”) could be misinterpreted, since only in the second sentence does it say “Sequence alignments show predicted binding sites”. We corrected this mistake, and added the text “Predicted chaperone binding sites” as the first words in the legend to this figure.
Reviewer #2: “8) The authors confusingly jump back and forth between different Septins and different chaperone (Ssa1-4, Ydj1, Sis1, Hsp104). We would ask the authors to re-arrange the manuscript, collating all the yeast work in one section and bacterial work in another.”
We re-arranged the manuscript and put all the yeast work in one section and all the bacterial work in another, with the exception of the studies of individually purified Cdc3 and Cdc12, which we put in between the yeast studies of the kinetics of de novo assembly and the yeast studies of post-translational assembly. Our reasoning is that the studies with the purified proteins demonstrate challenges with maintaining native conformations in the absence of chaperones and other septins, which flows naturally into the yeast studies asking about the ability of “excess” septins to maintain oligomerization-competent conformations in the absence of other septins and when we experimentally eliminate specific chaperones. All of the work actually manipulating E. coli genes/proteins is now together.
Reviewer #3: “1. The co-translational binding of CCT to nascent polypeptide chains has been studied (Stein et al., Mol Cell 2019). While the authors indicate that septin subunits are engaged co-translationally, they do not comment which ones are interacting with CCT and at which state of translation. This information is crucial and should also be mentioned in the discussion section.”
We are grateful to the Reviewer for bringing up this point, which we had overlooked. We hadn’t noticed that, in the end, only Cdc3 met the CCT confidence threshold to be included in the supplemental data of the Stein et al. paper. All septins co-purified with CCT in an earlier Dekker et al proteomic study, so we strongly suspect that the failure of the other septins to meet the confidence threshold in the Stein et al paper reflects the sensitivity of that assay, rather than a significant difference in how septin GTPase domains interact with CCT. We also hadn’t appreciated that according to that study, the main sites in the Cdc3 GTPase domain bound by CCT and Ssb are the same. Hence our statement that Ssb bound to septins “earlier” during translation, and CCT bound “later” was wrong. Instead, the overlapping Ssb and CCT site in Cdc3 turns out to be remarkably consistent with a conclusion from Stein et al paper, that CCT binds Rossmann-fold proteins like septins at sites where “early” beta strands have been translated and expose a chaperone-binding surface that later becomes buried by an alpha helix. We corrected our mistake in the text and in our model figure and added: (1) a new supplemental figure with predicted septin structures and a sequence alignment indicating where CCT and Ssb bound; and (2) text discussing the confidence thresholds for “calling” septin-CCT interaction, the Rossmann-fold binding, and how we interpret Ssb and CCT binding to the same site.
Reviewer #3 “3. Figure 3: It is recommended to also follow Cdc10-GFP and Cdc12-GFP fluorescence. This will on the one hand generalize the presented findings and provide a direct link to other parts of the study (e.g. crosslinking analysis of Cdc10).
We carried out the requested experiment for Cdc12, using Cdc12-mCherry rather than Cdc12-GFP because of the formation of non-native foci that we observed with Cdc12-GFP. We also attempted to analyze Cdc10, using an existing GAL1/10-promoter-driven Cdc10-mCherry plasmid that we’d made a few years ago, but it did not behave as expected, with high expression even in the absence of galactose (not shown), which prevented us from performing the requested experiment. We have a Cdc10-GFP plasmid with the inducible MET15 promoter, but this promoter does not provide sufficiently low levels of expression in repressive conditions, so there would be too much expression at the beginning of the experiment for us to accurately follow accumulation thereafter. Instead, we tried the only other plasmid we had with the GAL1/10-promoter controlling a tagged septin: Cdc11-GFP. Above a certain threshold of expression, Cdc11-GFP formed unexpected cortical foci, but we were still able to perform the analysis and found a clear delay in septin ring signal in cct4 cells, providing the requested generalization to other septins, if not Cdc10.
Reviewer #3 “5. Figure 4C: The finding that only ssb1 but not ssb2 knockouts have an effect on joining of free Cdc12-mCherry subunits into septin rings is puzzling. Similarly, Ssb1 largely acts co-translationally, while in this assay post-translational septin ring assembly is monitored. The authors need to comment on these two points.”
We did not examine ssb2 knockouts, so we do not know to what the Reviewer is referring in the first point. If the Reviewer means that they are puzzled by the fact that we saw a phenotype in cells in which only SSB1 was deleted and SSB2 remained, we offer two explanations. As can be seen in the Saccharomyces Genome Database entry for SSB1 (https://yeastgenome.org/locus/S000002388/phenotype), there are at least a dozen known phenotypes associated with deletion of SSB1 in cells with wild-type SSB2. We even showed a very clear septin misfolding/mislocalization phenotype in Supplemental Figure 4D. Thus while our findings are new and provide novel insights into Ssb function, they are not unprecedented. The Reviewer is correct that most Ssb is ribosome-bound and thus Ssb1 “largely acts co-translationally” but ~25% of Ssb is not ribosome-associated (PMID: 1394434). Furthermore, the lack of a strong phenotype for ssb1∆ cells in our new kinetics-of-folding experiment (see below), plus the realization that Ssb and CCT both bind the same site in Cdc3, leads us to a new model: Ssb acts both co- and post-translationally in septin folding, but only the post-translational function is associated with a phenotype in ssb1∆ cells, because in that assay we drastically overexpress a tagged septin and thereby exceed the Ssb chaperone capacity that remains when we delete SSB1. This logic also explains the first ssb1∆ phenotype we saw, when overexpressing Cdc10(D182N)-GFP. In the kinetics-of-folding assay, on the other hand, tagged septin expression is much lower and reducing the amount of total Ssb by ~50% (via SSB1 deletion) likely does not compromise Ssb function in folding the tagged septin. We therefore removed our statement that “Ssb dysfunction leaves nascent septins in non-native conformations that are aggregation-prone and unrecognizable to CCT”, revised our model figure accordingly, and added new text and citations to explain our new model.
Reviewer #3 “Additionally, they should test whether the appearance of septin ring fluorescence is slowed down in ssb1 mutants (as shown for cct4-1 mutant cells in Figure 3B).”
We agree that slower septin folding in ssb1∆ cells is a prediction of our model, and we performed the requested experiment and include the results in our revised manuscript. The new data show that the appearance of septin ring fluorescence is not delayed in ssb1∆ mutants, which is easily explained by the ability of Ssb2 to chaperone the folding of the low levels of tagged septin that we express in these kinds of experiments (see above).
Reviewer #3: “7. Figure 5G: The data is not convincing. This reviewer cannot detect a specific Cdc12 band accumulating in presence of GroEL/ES.”
We re-ran the reactions again with fresh reagents and this time ran the gel longer to reduce excess signal from free fluorescent puromycin and the bright Cdc10 bands. We now see a very clear band for full-length Cdc12 in the reaction with added GroEL/ES, fully consistent with our mass spectrometry results. We updated the figure with the new results.
Reviewer #3: “Furthermore, the activity tests done for the chaperonin system are confusing (Supplemental Figure 7). The ATPase rate (slope!) of GroEL/GroES seems higher as compared to GroEL but according to the authors it should be opposite.”
In our assays, the ATPase activity is so fast that for our “time 0” timepoint, much of it has already occurred by the time the reaction can be physically stopped and measured. In other words, the handling time is such that we can’t visualize what happened in the earliest stages of the reaction, where the rates could accurately be estimated as slopes. This is obvious from the fact that at time 0, the absorbance for the “GroEL alone” reaction is already more than twice the absorbance for GroEL+ES. We added clarifying text to the figure legend.
Reviewer #3: “The refolding assay using Rhodanese as substrate is also confusing: What is the activity of native Rhodanese? The aggregated Rhodanese sample seems to have substantial activity that is not too different from a GroEL/ES-treated one. From the presented data it is not clear to the reviewer to which extend GroEL/ES prevents aggregation and supports folding of denatured Rhodanese.”
We thank the Reviewer for bringing this to our attention, because made we mistakenly left out the values for native Rhodanese with the reporter. With regard to the aggregated Rhodanese, we failed to note that this sample contains urea. When the urea absorbance is subtracted, it is clear that the GroEL/ES-treated sample has higher activity. Furthermore, some native enzyme is likely still active within the aggregated sample, explaining the “substantial activity” that the Reviewer correctly notes. We corrected the figure and added clarifying text to the figure legend.
Reviewer #3: “the study goes astray following aspects that does not seem relevant to this reviewer (e.g. the role of N-terminal proline residues for Cdc12 translation, Fig. 5E/F).”
We acknowledge that we did a poor job of introducing the N-terminal Pro-rich cluster in Cdc12 with relation to our model of slow Cdc12 translation. Instead, we have revised and reorganized the manuscript to set up these experiments as a direct test of our model: if ribosome collisions on the body of the ORF drive mRNA decay, then decreasing the spacing of those ribosomes should exacerbate the problem, and eliminating the Pro-rich cluster (where published yeast data already show ribosomes accumulate) is the most logical way to test the prediction. Far from being irrelevant, the results fit the prediction perfectly and thus support the model. We expect that this change will highlight the importance of these experiments for the reader.
Reviewer #2: “1) Fig. 1 Is the folding of Cdc3 being measured in cells lacking chaperones mentioned towards the end of the paper or are the authors referring to the lack of yeast proteins?”
We are unclear as to what the Reviewer is asking here. The title of Figure 1 states that these are “purified yeast septins” and the figure legend further emphasizes this fact. Additionally, the Coomassie-stained gel in Figure 1A shows a single band, corresponding to purified 6xHis-Cdc3. The proteins were purified from wild-type E. coli cells, so all E. coli chaperones were present when Cdc3 initially folded, but chaperones and all other proteins were removed during the purification and prior to the analysis. We do not know what change to make.
Reviewer #2 asked “How do the authors account for the septin defect in Ssa4 delete cells in unstressed conditions where Ssa4 would be very low already? According to the authors previous work, Ssa2 and 3 should be able to compensate.”
We explicitly addressed this point in the original manuscript (lines 893-898). Again, we think here the Reviewer is equating chaperone binding with chaperone function. According to our previous work, Ssa2 and Ssa3 are able to bind septins, but this does not mean that they can fold septins the same way as Ssa4. We cite several papers that discuss the distinct functional roles for the different Ssa proteins. We do not think that additional clarification of this point would strengthen the manuscript.
Reviewer #3: “6. Figure 5B: It is unclear why Cdc3 is observed in the pulldown of His-tagged Cdc12 (37˚C), although no Cdc12 was isolated under these conditions. How is that possible?”
That is not possible. As we indicate in the figure legend and with the red asterisk, the only band appearing in that lane is a non-specific band that cross-reacts with the anti-Cdc3 and/or anti-Cdc11 antibodies. This is why it is also present in the “No septins” control lanes. We made the asterisk larger to help accentuate this point.
Reviewer #3: “Furthermore, the authors observe a specific effect on Cdc12-Cdc11 assembly in the E. coli groEL mutant. How do they rationalize this specific effect as Cdc12-Cdc3 assembly remained unchanged? This observation also seems in conflict with the suggestion of the authors that Cdc12 preferentially recruits Cdc11 before interacting with Cdc3 (page 45, lane 1024).”
Cdc11 was not expressed in the groEL mutants because no Cdc11 gene was present in those cells, as explained in the body text and indicated in the labeling above the lanes in Figure 5A. The band near the size of Cdc11 is a non-septin protein that bound to the beads in the groEL-mutant cells, as is shown in the immunoblot using anti-Cdc11 antibodies in Figure 5B. Thus there is no conflict to rationalize.
Reviewer #1: “The only evidence that CCT binds to septin is the list of LC-MS/MS. Western blotting would provide more solid data.” and “2) The cross-linking experiments appears not to have been successful. Why are the Ssas, Ydjs etc not detected here? “
First, CCT subunits are relatively low-abundance, expressed at 5- to 50-fold lower levels than other chaperone families in the yeast cytosol (see PMID: 23420633). To the Reviewer’s second point, we did in fact detect other chaperones in our crosslinking mass spectrometry experiments, including Ydj1, multiple Ssa and Ssb chaperones, Hsp104, etc., as can be seen in Table S1. However, they were also detected in negative control experiments. This is not surprising, given that these chaperones are among the most common “contaminants” of affinity-based purification schemes (see the CRAPome database at https://reprint-apms.org/). It was for this reason we had to perform so many negative control experiments, which likely produced some false negative results, as some “real” interactions were likely discarded when the same chaperone showed up in our controls. We added a figure panel with a Venn diagram of overlap between experimental and control samples, and text pointing out this caveat of our approach.
Second, in this experiment we attempted to identify proteins that transiently interact with a specific region of Cdc10 that will later become buried in a septin-septin oligomerization interface. Due to the transient nature of the interaction, we do not expect to detect high levels of crosslinked chaperones. Mass spectrometry is significantly more sensitive than immunoblotting, so there is no guarantee that we would be able to detect a band even if the crosslinking works as desired. Indeed, the crosslinked bands we saw by immunoblot for GroEL were quite faint (see Figure 2F), despite the fact that GroEL and the T7-promoter-driven Cdc10 were among the most abundant proteins in those E. coli cells.
Third, there is no commercially available, verified antibody recognizing yeast Cct3 for which to perform the requested immunoblot experiment. Since both the N and C termini of CCT subunits project into the folding chamber, it is unwise to use a standard epitope tagging approach, as the tags may compromise function. Indeed, for purification purposes others inserted an affinity tag in an internal loop in Cct3 (PMID: 16762366). We have a yeast strain with Cct6 tagged in an analogous way, but to perform the requested immunoblot experiment with Cct3 would require creating or obtaining the Cct3-tagged strain, deleting NAM1/UPF1, and introducing our Bpa tRNA/synthetase and GST-6xHis-Cdc10 plasmids. Given the sensitivity of detection concerns stated above, we doubt this would help.
In summary, we prefer not to attempt the requested immunoblot experiments.
Reviewer #1: “-Fig. 3B ant related Figures: The experiment to see if GFP-tagged septin accumulates in the bud neck is important, but only the graphs after the analysis are shown. The authors should provide the readers with representative examples from imaging data.”
We are confused, because the images at the bottom of Figure 3A already show what the Reviewer requests. As stated in the figure legend, these are representative examples of the imaging data from a middle timepoint of one of the experiments. It would be nearly impossible (for space reasons) to provide representative images for all of the timepoints for all of the genotypes for all of the experiments. Since in our new experiments we introduce new tagged septins (Cdc11-GFP and Cdc12-mCherry), we also now include representative images of cells expressing these proteins, as well.
Reviewer #2: “3) If the authors had evidence of chaperone interaction from their previous study, why did they not simply do IPs with fragments of the septins/chaperones?”
We are unclear why the Reviewer is suggesting IPs after referring to our previous study. IPs are a poor choice for transient interactions, which is why we mostly avoided them in previous studies, and instead used a novel approach (BiFC) to “trap” chaperone–septin interactions. Moreover, we seek to identify chaperones that bind wild-type septins at future septin-septin interfaces on the path towards the native conformation. Fragments of septin proteins would likely misfold and would therefore likely attract chaperones that wouldn’t normally bind the full-length septin. Indeed, our previous studies demonstrated that even a single non-conservative amino acid substitution was sufficient to alter chaperone-septin binding. Thus IPs with fragments of septins or chaperones would be highly unlikely to yield informative results for the questions we seek to answer. We strongly prefer not to attempt these suggested experiments.
Reviewer #2: “5) While differences between Ssa paralogs are highly interesting, using deletions of Ssas is not useful, given that yeast compensate by overexpressing other paralogs. The yeast GFP Septin assays should be repeated in yeast lacking all Ssas and expressing one paralog on a constitutive promoter (See numerous papers by Sharma and Masison).”
We disagree that ssa deletions are “not useful”, since if the overexpressed paralogs cannot fulfill the same function as the deleted SSA, then we will see a phenotype. Which we do. Furthermore, we had already obtained and thoroughly tested a strain like the ones mentioned by the reviewer (ECY487, a.k.a. JN516, from Betty Craig’s lab, with ssa2∆ ssa3∆ ssa4∆ and SSA1, which is constitutively expressed, PMID: 8754838), but we found that, as published, it divides slightly more slowly even under the most permissive of conditions. The requested strain cannot be analyzed using our method, because slow accumulation of ring fluorescence could be attributed to other defects unrelated to septin folding. Thus we strongly prefer not to attempt the suggested experiments.
Reviewer #2: “7) The authors need to clarify the experiment with the Ydj1 D36N and Ssa2 R169H. In Reidy et al, they never fully biochemically test this system and it was never examined for Ssa2-Ydj1. The authors would need to do some fundamental experiments to demonstrate the validity and functionality of this double mutant in yeast.”
Given that this experiment was unable to generate meaningful data, since the mutations affected the kinetics of induction of the GAL1/10 promoter, we do not think the requested biochemical experiments would add any value to the study. Instead, we removed these studies from the manuscript.
Reviewer #3: “4. Figure 3B: The difference between wt and cct4-1 cells in appearance of septin ring fluorescence is observed at one timepoint. Since this experiment is considered highly relevant, the authors are asked to include another timepoint to bolster the conclusion that Cdc3-GFP folding and thus septin ring assembly is delayed in the CCT mutant.”
We carried out new experiments with cct4-1 cells using Cdc12-mCherry and Cdc11-GFP with more timepoints than in our original cct4-1 experiments with Cdc3-GFP. Since these experiments provide the same kinds of results, but at multiple timepoints, we do not see the value in repeating the Cdc3-GFP experiment.
Reviewer #3: “If Ssb1 functions to maintain Cdc12 in an assembly competent state preventing misfolding, one would expect either enhanced degradation or aggregation of Cdc12-mCherry in ssb1 mutant cells. Did the authors check for such scenario? Septin aggregation has been shown in a ssb1 ssb2 double deletion strain (Willmund et al., 2013), yet the data shown here predict that aggregation might already occur in single ssb1 mutants.”
We already examined septin aggregation in single ssb1 mutants and showed these data (Supplementary Figure 4D). Indeed, this phenotype was the rationale for testing post-translational septin assembly in ssb1 single mutants. We have seen no evidence of septin degradation in any context (as we mentioned on line 889), so we would not expect it here. While we added new text and a very new citation showing that many “misfolded” conformations of wild-type E. coli proteins avoid aggregation and degradation, we do not think that the suggested experiments would add enough value to the current study to justify the effort, time and expense.
Reviewer #3: “Fig. 3C: The figure showing septin ring fluorescence does not include error bars. This is crucial, also because the difference between wt and ssa4 mutant cells is not large.”
There are, in fact, error bars included in the figure, as can be most clearly seen for the final timepoint for the ssa4∆ cells. For most of the other timepoints the error bars are smaller than the data point symbols (the circles and squares). We do not think that adjusting the size or opacity of the symbols to better show the error bars will be sufficiently valuable to justify the effort.
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I found this comment to be surprising as I have never heard of the "Black Identity Extremist" tag. Because I was interested in this, I did further research using Caulfield's “check for other coverage” technique and looked into it.
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