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This is a really interesting finding; isn’t drought also often seasonal/episodic?

Supporting this with some transcription factor analysis might be useful to assess if there are commonalities in who the molecular regulators are for these AM-expanded gene families.

Great paper with lots of food for thought regarding genomic trends associated with symbioses.

Organization*

Organization*

Las principales inversoras han promovido un 5% de rentabilidad en fondos de Renta Fija (Bonos), para que puedan atraer inversionistas. Todo ello antes del recorte de la tasa de interés de los bonos EEUU

Hay una preferencia por Renta Fija, ante la situación de conflictos entre Irán e Israel. El dólar ha bajado, el Bitcoin ha repuntado, el petróleo se ha mantenido.

I just liked how this line clearly shows how changing the way a question is phrased opens up more doors for conversation.

they

words

Please add below Economics:

Principles of Public Service

Anyone can throw out a line or two for an argumentative statement, but the thing that keeps me going back for more is if they have evidence or can give statements that is supporting their claims.

obviously there is more in the second because its longer but its not all about size because smaller ones can also get the job done

I think this is important to remember just because when you are in a debate or whatever you want to call it, the most annoying thing is when they keep circling back to the same thing over and over again. It’s like I get it, and now I'm uninterested because you are telling me the same thing and have no other information on the situation.

Très bon prof ! Et ce qui est bien dans cette formule, c'est que l'on peut le faire répéter indéfiniment ^^ ;)

test

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Reply to the reviewers

Manuscript number: RC-2023-02218R

Corresponding author(s): Steven, McMahon

1. General Statements [optional]

*We were pleased to receive the encouraging critiques and very much appreciate the Reviewer's specific comments and suggestions. In this revised version of our manuscript, we have made a number of substantive additions and modifications in response to these comments/suggestions. We hope you agree that the study is now improved to the point where it is suitable for publication. *

2. Point-by-point description of the revisions

Reviewer #1 (Evidence, reproducibility and clarity (Required)):

Summary This study describes efforts to characterize differences in the roles of the two related human decapping factors Dcp1a and Dcp1b by assessing mRNA decay and protein associations in knockdown and knockout cell lines. The authors conclude that these proteins are non-redundant based on the observations that loss of DCp1a versus Dcp1b impacts the decapping complex (interactome) and the transcriptome differentially.

Major comments • While the experiments appear to be well designed and executed and the data of generally high quality, the conclusions are drawn without sufficient consideration for the fact that these two proteins form a heterotrimeric complex. The authors assume that there are distinct homotrimeric complexes rather than a single complex with both proteins in. Homotrimers may have new/different functions not normally seen when both proteins are expressed. Thus while it is acceptable to infer that the functions of these two proteins within the decapping complex are distinct, it is not clear that they act separately, or that complexes naturally exist without one or the other. A careful evaluation of the relative ratios of Dcp1a and b overall and in decapping complexes would be informative if the authors want to make stronger statements about the roles of these two factors.

RESPONSE: Thank you for this valuable comment. We have substantially edited the manuscript to incorporate these points. Examples include a detailed analysis of iBAQ values for the DDX6, DCP1a, and DCP1b interactomes (which now allows us to estimate the ratios of DCP1a and DCP1b in these complexes) and cellular fractionation to interrogate complex integrity (using Superose 6).

• The concept of buffering is not adequately introduced and the interpretation of observations that RNAs with increased half life do not show increased protein abundance - that Dcp1a/b are involved in transcript buffering is nebulous. In order to support this interpretation, the mRNA abundances (NOT protein abundances) should be assessed, and even then, there is no way to rule out indirect effects. RESPONSE: Thank you for this comment. In the revised version of the manuscript, we introduced the concept of transcript buffering at an earlier stage as one of the potential explanations for our findings. We were also able to use a new algorithm (grandR) to estimate half-lives and synthesis rates from our data. These new data add strength to the argument that DCP1a and DCP1b are linked to transcript buffering pathways.

• It might be interesting to see what happens when both factors are depleted to get an idea of the overall importance of each one.

RESPONSE: In our work we tried to emphasize the differences between the two paralogs. We believe that doing double knockout or knockdown would mask the distinct impacts of the paralogs. In data not included in this study, we have shown that cells lacking both DCP1a and DCP1b are viable. We did check PARP cleavage in the CRISPR generated cell pools of DCP1a KO, DCP1b KO, and the double KO. The WB measuring the PARP cleavage is shown in the supplemental material (Supplementary Material: Replicates)

• The algorithms etc used for data analysis should be included at the time of publication. Version number and settings used for SMART to define protein domains, and webgestalt should be indicated

RESPONSE: We apologize for this oversight. Version number and settings used for the webtools (SMART, Webgestalt) are now included. The analysis pipeline for half-lives and synthesis rates estimation as well as all the files and the code needed to generate the figures in the paper are available on zenodo (https://zenodo.org/records/10725429).

• Statistical analysis is not provided for the IP experiments, the number of replicates performed is not indicated and quantification of KD efficiency are not provided.

RESPONSE: The number of replicates performed in each experiment is now clearly indicated and quantifications of knockdown efficiency are provided (Supplemental Figure 3A and 3B, Figure 3A, Figure 3B).

• The possibility that the IP Antibody interferes with protein-protein interactions is not mentioned.

RESPONSE: Thank you for this comment. The revised manuscript includes a discussion of the antibody epitope location and the potential for impact on protein-protein interactions.

Minor comments • P4 - "This translational repression of mRNA associated with decapping can be reversed, providing another point at which gene expression can be regulated (21)" - implies that decapping can be reversed or that decapped RNAs are translated. I don't think this is technically true.

RESPONSE: There have been several studies that document the reversal of decapping. These findings are summarized in the following reviews.

Schoenberg, D. R., & Maquat, L. E. (2009). Re-capping the message. Trends in biochemical sciences, 34(9), 435-442.

Trotman, J. B., & Schoenberg, D. R. (2019). A recap of RNA recapping. Wiley Interdisciplinary Reviews: RNA, 10(1), e1504.

• P11 - how common is it for higher eukaryotes to have 2 DCP genes? *RESPONSE: Metazoans have 2 DCP1 genes. *

• Fig S1 - says "mammalian tissues" in the text but the data is all human. The statement that "expression analyses revealed that DCP1a and DCP1b have concordant rather than reciprocal expression patterns across different mammalian tissues (Supplemental Figure 1)" is a bit misleading as no evidence for correlation or anti-correlation is provided. Also co-expression is not strong support for the idea that these genes have non-redundant functions. Both genes are just expressed in all tissues - there's no evidence provided that they are concordantly expressed. In bone marrow it may be worth noting that one is high and the other low - i.e. reciprocal. *RESPONSE: We appreciate this comment. We have corrected the interpretation of the aforementioned dataset. We have also incorporated a more detailed discussion in the text of the paper. As the Reviewer pointed out, there are a subset of tissues where their expression appears to be reciprocal. *

• Fig 1A - it is not clear what the different colors mean. Does Sc DCP1 have 1 larger EVH or 2 distinct ones. Are the low complexity regions in Sc DCP2 the SLiMs. *RESPONSE: Thank you for this comment. We have corrected this ambiguity to reflect that Sc DCP1 has one EVH1 domain that is interconnected by a flexible hinge. The low-complexity regions typically contain short linear motifs (SLIMs), however, not all low-complexity regions have been verified to contain them. In the figure, only low-complexity regions are shown. The text of the paper refers only to verified SLIMs . *

• P11 - why were HCT116 cells selected? RESPONSE: HCT116 cells are an easily transfectable human cell line and have been widely used in biochemical and molecular studies, including studies of mRNA decapping (see references below). Since decapping is impacted by viral proteins we avoided the use of other commonly used cell models such as HEK293T or HeLa.

https://pubmed.ncbi.nlm.nih.gov/?term=decapping+hct116&sort=date&size=200

• Fig 1B - what are the asterisks by the RNA names? Might be worth noting that over-expression of DCP1b reduced IP of DCP1a. There's no quantification and no indication of the number of times this experiment was repeated. Data from replicates and quantification of the knockdown efficiency in each replicate would be nice to see. *RESPONSE: Thank you for this comment. Asterisks indicate that those bands were from a second gel, as DCP1a and DCP1b run at approximately the same molecular weight. We have now included a note in our figure legend to indicate this. The knockdown efficiency is provided (Figure 3 and Supplemental Figure 3). We also noted the number of replicas for each IP in figure 1. The replicas are provided as supplementary material (Supplementary Materials: Replicates). *

• Fig 1C/1D - why are there 3 bands in the DCP1a blot? Quantification of the IP bands is necessary to say whether there is an effect or not of over-expression/KO. RESPONSE: The additional bands in DCP1a blots are background. When we stained the whole blot for DCP1a, in cells which with complete DCP1a KO cells (clone A3), these bands still appear (Supplementary Material: Validation of the KO clones). Quantifications of the bands in the overexpression experiments is now provided.

• Fig 3 - is it possible that differences are due to epitope positions for the antibodies used for IP? RESPONSE: We do not believe so. DCP1a antibody binds roughly 300-400 residues on DCP1a, and DCP1b antibody binds around Val202. Antibodies therefore do not bind DCP1a or DCP1b low-complexity regions (which are largely responsible for interacting with the decapping complex interactome). Antibodies don't bind the EVH1 domains or the trimerization domain, which are needed for their interaction with DCP2 and each other.

• Fig 5A - the legend doesn't match the colors in the figure. It is not clear how the pRESPONSE: Thank you for this comment. We have corrected this issue in the revised version of the paper. High-confidence proteins are those with pRESPONSE: Thank you for this comment. We have corrected this issue in the revised version of the paper.*

• There are a few more recent studies on buffering that should be cited and more discussion of this in the introduction is necessary if conclusions are going to be drawn about buffering. *RESPONSE: We have included a discussion of transcript buffering in the introduction. *

• The heatmaps in figure 2 are hard to interpret. RESPONSE: To clarify the heatmaps, we included a more detailed description in the figure legends, have enlarged the heatmaps themselves, and have added more extensive labeling.

Reviewer #1 (Significance (Required)):

• Strengths: The experiments appear to be done well and the datasets should be useful for the field. • Limitations: The results are overinterpreted - different genes are affected by knocking down one or other of these two similar proteins but this does not really tell us all that much about how the two proteins are functioning in a cell where both are expressed. • Audience: This study will appeal most to a specialized audience consisting of those interested in the basic mechanisms of mRNA decay. Others may find the dataset useful. • This study might complement and/or be informed by another recent study in BioRXiv - https://doi.org/10.1101/2023.09.04.556219 • My field of expertise is mRNA decay - I am qualified to evaluate the findings within the context of this field. I do not have much experience of LC-MS-MS and therefore cannot evaluate the methods/analysis of this part of the study.

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

The authors provide evidence that Dcp1a and Dcp1b - two paralogous proteins of the mRNA decapping complex - may have divergent functions in a cancer cell line. In the first part, the authors show that interaction of Dcp2 with EDC4 is diminished upon depletion of Dcp1a but not affected by depletion of Dcp1b. The results have been controlled by overexpression of Dcp1b as it may be limiting factor (i.e. expression levels too low to compensate for depletion of Dcp1a reduced interaction with EDC3/4 while depletion of Dcp1b lead to opposite and increase interactions). They then defined the protein interactome of DDX6 in parental and Dcp1a or Dcp1b depleted cells. Here, the authors show some differential association with EDC4 again, which is along results shown in the first part. The authors further performed SLAM-seq and identified subsets of mRNA whose decay rates are common but also different upon depletion with Dcp1a and Dcp1b. Interestingly, it seems that Dcp1a preferentially targets mRNAs for proteins regulating lymphocyte differentiation. To further test whether changes in RNA decay rates are also reflected at the protein levels, they finally performed an MS analysis with Dcp1a/b depleted cells. However no significant overlap with mRNAs showing altered stability could be observed; and the authors suggested that the lack of congruence reflects translational repression.

Major comments: 1. While functional difference between Dcp1a and Dcp1b are interesting and likely true, there are overinterpretations that need correction or further evidence for support. Sentences like "DCP1a regulates RNA cap binding proteins association with the decapping complex and DCP1b controls translational initiation factors interactions (Figure 2E)" sound misleading. While differential association with proteins has been recognised with MS-data, it does not necessary implement an active process of control/regulation. To make the claim on 'control/regulation', and inducible system or introduction of mutants would be required.

RESPONSE: This set of comments were particularly useful in helping us refine the presentation of our findings. We have edited our manuscript to be more specific about the limits of our data.

1. The MS analysis is not clearly described in the text and it is unclear how authors selected high-confident proteins. The reader needs to consider the supplemental tables to find out what controls were used. Furthermore, the authors should show correlation plots of MS data between replicates. For instance, there seems to be limited correlation among some of the replicates (e.g. Dcp1b_ko3 sample, Fig. 2c). Any explanation in this variance?

*RESPONSE: We have now included a clear description of how all high-confidence proteins were selected in the Methods and Results sections. The revised manuscript also includes a more thorough description of the controls used and the number of replicates for individual experiments. The PCA plots have now been included where appropriate. The variance in this sample is likely technical. *

1. GO analysis for the proteome analysis should consider the proteome and not the genome as the background. The authors should also indicate the corrected P-values (multiple testing) FDRs.

*RESPONSE: Webgestalt uses a reference set of IDs to recognize the input IDs, and it does not use it for the background analysis in the classical sense. We repeated a subset of our proteome analyses using the 'genome-protein coding' as background and obtained the same result as in our original analysis. All ontology analyses now include raw p-values and/or FDRs when appropriate. *

1. Fig 2E. The figures display GO enrichments needs better explanation and additional data can be added. The enrichment ratio is not explained (is this normalised?) and p-values and FDRs, number of proteins in respective GO category should be added. *RESPONSE: More thorough explanations of the GO enrichments are now included. The supplemental data contains all p-values (raw and adjusted), as well as the number of proteins in each GO category. The Enrichment ratio is normalized and contains information about the number of proteins that are redundant in multiple groups. GO Ontology analyses are now displayed with p-values and/or FDR values, and in this case the enrichment ratio contains information regarding the number of proteins found in our input set and the number of expected proteins in the GO group. The network analysis shows the FDR values and the number of proteins found in the groups compared. *

Minor: 5. These studies were performed in a colorectal carcinoma cell line (HCT116). The authors should justify the choice of this specialised cell line. Furthermore, one wonders whether similar conclusions can be drawn with other cell lines or whether findings are specific to this cancer line.

RESPONSE: The study that is currently in pre-print in BioRxiv (https://doi.org/10.1101/2023.09.04.556219*) utilized HEK293Ts and found similar results to ours when examining the various relationships between the core decapping core members. *

1. Fig. 1B. It is unclear what DCP1b* refers to? There are bands of different size that are not mentioned by the authors - are those protein isoforms or what are those referring to? A molecular marker should be added to each Blots. Uncropped Western images and markers should be provided in the Supplement. *RESPONSE: The asterisk indicates that these images came from a second western blot gel (DCP1a and DCP1b have a similar molecular weight and cannot be probed on the same membrane). Uncropped western blot images and markers (as available) are provided in the supplement. *

2. MS data submitted to public repository with access. No. indicated in the manuscript.

RESPONSE: MS data is submitted as supplementary datasets to the paper. It contains the analyzed data as well as the LCMSMS output. We are in the process of submitting the raw LSMSMS data to a public repository.

Fig 3. A Venn Diagram displaying the overlap of identified proteins should be added. GO analysis should be done considering the proteome as background (as mentioned above).

*RESPONSE: A Venn diagram showing the overlap among the proteins identified is now included in the revised version. *

Reviewer #2 (Significance (Required)):

Overall, this is a large-scale integrative -omics study that suggest functional difference between Dcp1 paralogues. While it seems clear that both paralogous have some different functions and impact, there are overinterpretations in place and further evidence would to be provided to substantiate conclusions made in the paper. For instance, while the interactions with Dcp2/Ddx6 in the absence of Dcp1a,b with EDC4/3 may be altered (Fig. 1, 2), the functional implications of this changed associations remains unresolved and not further discussed. As such, it remains somehow disconnected with the following experiments and compromises the flow of the study. The observed differences in decay-rates for distinct functionally related sets of mRNAs is interesting; however, it remains unclear whether those are direct or rather indirect effects. This is further obscured by the absence of any correlation to changes in protein levels, which the authors interpreted as 'transcriptional buffering'. In this regard, it is puzzling how the authors can make a statement about transcriptional buffering? While this may be an interesting aspect and concept of the discussion, there is no primary data showing such a functional impact.

As such, the study is interesting as it claims functional differences between DCP1a/b paralogous in a cancer cell line. Nevertheless, I am not sure how trustful the MS analysis and decay measurements are as there is not further validation. It woudl be interesting if the authors could go a bit further and draw some hypothesis how the selectivty could be achieved i.e interaction with RNA-binding proteins that may add some specificity towards the target RNAs for differential decay. As such, the study remains unfortunately rather descriptive without further functional insight.

Reviewer #3 (Evidence, reproducibility and clarity (Required)):

Review on "Non-redundant roles for the human mRNA decapping cofactor paralogs DCP1a and DCP1b" by Steven McMahon and co-workers mRNA decay is a critical step in the regulation of gene expression. In eukaryotes, mRNA turnover typically begins with the removal of the poly(A) tail, followed by either removal of the 5' cap structure or exonucleolytic 3'-5' decay catalyzed by the exosome. The decapping enzyme DCP2 forms a complex with its co-activator DCP1, which enhances decapping activity. Mammals are equipped with two DCP1 paralogs, namely DCP1a and DCP1b. Metazoans' decapping complexes feature additional components, such as enhancer of decapping 4 (EDC4), which supports the interaction between DCP1 and DCP2, thereby amplifying the efficiency of decapping. This work focuses on DCP1a and DCP1b and investigates their distinct functions. Using DCP1a- and DCP1a-specific knockdowns as well as K.O. cell lines, the authors find surprising differences between the DCP1 paralogs. While DCP1a is essential for the assembly of EDC4-containig decapping complexes and interactions with mRNA cap binding proteins, DCP1b mediates interactions with the translational machinery. Furthermore, DCP1a and DCP1b target different mRNAs for degradation, indicating that they execute non-overlapping functions. The findings reported here expand our understanding of mRNA decapping in human cells, shedding light on the unique contributions of DCP1a and DCP1b to mRNA metabolism. The manuscript tackles an interesting subject. Historically, the emphasis has been on studying DCP1a, while DCP1b has been deemed a functionally redundant homolog of DCP1a. Therefore, it is commendable that the authors have taken on this topic and, with the help of knockout cell lines, aimed to dissect the function of DCP1a and DCP1b. Despite recognizing the significance of the subject and approach, the manuscript falls short of persuading me. Following a promising start in Figure 1 (which still has room for improvement), there is a distinct decline in overall quality, with only relatively standard analyses being conducted. However, I do not want to give the authors a detailed advice on maximizing the potential of their data and presenting it convincingly. So, here are just a few key points for improvement: Figure 1C: Upon closer examination, a faint band is still visible at the size of DCP1a in the DCP1a knockout cells. Could this be leaky expression of DCP1a? The authors should provide an in-depth characterization of their cells (possibly as supplementary material), including identification of genomic changes (e.g. by sequencing of the locus) and Western blots with longer exposure, etc.

*RESPONSE: Thank you for this comment. The in-depth characterization of our cells is now included in the Supplementary Material. DCP1a KO cells and DCP1b KO cells indicated as single cell clones have been confirmed to have no DCP1a or DCP1b expression. In Figure 1D and Figure 3, polyclonal pool cells were used as indicated (only for DCP1a KO). *

Figure 2: It is great to see that the effects of the KOs are also visible in the DDX6 immunoprecipitation. However, I wonder if the IP clearly confirms that the KO cells indeed do not express DCP1a or DCP1b. In the heatmap in Figure 2B, it appears as if the proteins are only reduced by a log2-fold change of approximately 1.5? Additionally, Figure 2 shows a problem that persists in the subsequent figures. The visual presentation is not particularly appealing, and essential details, such as the scale of the heatmap in 2B (is it log2 fold?), are lacking.

*RESPONSE: The in-depth characterization of our cells is included in the Supplementary Materials and confirms the presence of single-cell clones where indicated. As noted above, only Figure 1D and Figure 3 used DCP1a KO pooled cells. The heatmap in Figure 2B is scaled by row using the pheatfunction in R studio. The actual data for the heatmap comes from protein intensities from the LC-MS/MS analysis. We have improved the visual presentation in the revised manuscript. *

Figure 3: I wonder why there are no primary data shown here, only processed GO analyses. Wouldn't one expect that DCP2 interacts mainly with DCP1a, but less with DCP1b? Is this visible in the data? Moreover, such analyses are rather uninformative (as reflected in the GO terms themselves, for instance, "oxoglutarate dehydrogenase complex" doesn't provide much meaningful insight). The authors should rather try to derive functional and mechanistic insights from their data.

RESPONSE: We have now revised this Figure to include primary data as well as the IP of DCP1a in DCP1b KO cells (single cell clones) and the IP of DCP1b in DCP1a KO cells (pooled cells). We identified EDC3 in the high-confidence protein pool. The EDC3:DCP1a interaction is enhanced in DCP1b KO cells. We also found that the EDC3:DCP1b interaction is less abundant in DCP1a KO cells. This is consistent with our data in Figures 1 and 2. DCP2 was not identified in the interactomes of either DCP1a or DCP1b. This is not unusual as DCP2 is highly flexible and the association between DCP1s with DCP2 is transient and facilitated by other proteins.

In Fig. 4 the potential of the approach is not fully exploited. Firstly, I would advocate for omitting the GO analyses, as, in my opinion, they offer little insight. Again, crucial information is missing to assess the results. While 75 nt reads are mentioned in the methods, the sequencing depth remains unspecified. Figure 4b should be included in the supplements. Furthermore, I strongly recommend concentrating on insights into the mechanisms of DCP1a and DCP1b-containing complexes. E.g. what characteristics distinguish DCP1a and DCP1b-dependent mRNAs? Are these targets inherently unstable? Why are they degraded? Are they known decapping substrates?

*RESPONSE: Thank you for this comment. We have now revised this figure and have included information about sequencing depth and other pertinent information. We have been able to use a newly available algorithm (grandR) and were able to estimate half-lives and synthesis rates. This is a significant addition to the paper. We were also able to compare significantly impacted mRNAs (by DCP1a or DCP1b loss) to the established DCP2 target list. *

In general, I suggest the authors revise the manuscript with a focus on the potential readers. Reduce Gene Ontology (GO) analyses and heatmaps, and instead, incorporate more analyses regarding the molecular processes associated with the different decapping complexes.

*RESPONSE: We removed selected GO analyses and heatmaps from the main body of the manuscript (included as Supplementary Figures instead). For our LC-MS/MS datasets, we added iBAQ analyses of the DDX6 IP, DCP1a IP, and DCP1b IP in the control conditions. Cellular fractionation studies (using Superose 6 chromatography) were also added to the paper and allow us to interrogate decapping complex composition in more detail. The revised version of the manuscript includes a new 4SU labeling experiment (pulse-chase) as well as estimation of half-lives and synthesis rates in our conditions. Also included is relevant information about DCP1b transcriptional regulation. *

Reviewer #3 (Significance (Required)):

The manuscript in its current form could benefit from substantial revisions for it to be considered impactful for researchers in the field.

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

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Referee #3

Evidence, reproducibility and clarity

Review on "Non-redundant roles for the human mRNA decapping cofactor paralogs DCP1a and DCP1b" by Steven McMahon and co-workers

mRNA decay is a critical step in the regulation of gene expression. In eukaryotes, mRNA turnover typically begins with the removal of the poly(A) tail, followed by either removal of the 5' cap structure or exonucleolytic 3'-5' decay catalyzed by the exosome. The decapping enzyme DCP2 forms a complex with its co-activator DCP1, which enhances decapping activity. Mammals are equipped with two DCP1 paralogs, namely DCP1a and DCP1b. Metazoans' decapping complexes feature additional components, such as enhancer of decapping 4 (EDC4), which supports the interaction between DCP1 and DCP2, thereby amplifying the efficiency of decapping.

This work focuses on DCP1a and DCP1b and investigates their distinct functions. Using DCP1a- and DCP1a-specific knockdowns as well as K.O. cell lines, the authors find surprising differences between the DCP1 paralogs. While DCP1a is essential for the assembly of EDC4-containig decapping complexes and interactions with mRNA cap binding proteins, DCP1b mediates interactions with the translational machinery. Furthermore, DCP1a and DCP1b target different mRNAs for degradation, indicating that they execute non-overlapping functions.

The findings reported here expand our understanding of mRNA decapping in human cells, shedding light on the unique contributions of DCP1a and DCP1b to mRNA metabolism. The manuscript tackles an interesting subject. Historically, the emphasis has been on studying DCP1a, while DCP1b has been deemed a functionally redundant homolog of DCP1a. Therefore, it is commendable that the authors have taken on this topic and, with the help of knockout cell lines, aimed to dissect the function of DCP1a and DCP1b.

Despite recognizing the significance of the subject and approach, the manuscript falls short of persuading me. Following a promising start in Figure 1 (which still has room for improvement), there is a distinct decline in overall quality, with only relatively standard analyses being conducted. However, I do not want to give the authors a detailed advice on maximizing the potential of their data and presenting it convincingly. So, here are just a few key points for improvement:

Figure 1C: Upon closer examination, a faint band is still visible at the size of DCP1a in the DCP1a knockout cells. Could this be leaky expression of DCP1a? The authors should provide an in-depth characterization of their cells (possibly as supplementary material), including identification of genomic changes (e.g. by sequencing of the locus) and Western blots with longer exposure, etc.

Figure 2: It is great to see that the effects of the KOs are also visible in the DDX6 immunoprecipitation. However, I wonder if the IP clearly confirms that the KO cells indeed do not express DCP1a or DCP1b. In the heatmap in Figure 2B, it appears as if the proteins are only reduced by a log2-fold change of approximately 1.5? Additionally, Figure 2 shows a problem that persists in the subsequent figures. The visual presentation is not particularly appealing, and essential details, such as the scale of the heatmap in 2B (is it log2 fold?), are lacking.

Figure 3: I wonder why there are no primary data shown here, only processed GO analyses. Wouldn't one expect that DCP2 interacts mainly with DCP1a, but less with DCP1b? Is this visible in the data? Moreover, such analyses are rather uninformative (as reflected in the GO terms themselves, for instance, "oxoglutarate dehydrogenase complex" doesn't provide much meaningful insight). The authors should rather try to derive functional and mechanistic insights from their data.

In Fig. 4 the potential of the approach is not fully exploited. Firstly, I would advocate for omitting the GO analyses, as, in my opinion, they offer little insight. Again, crucial information is missing to assess the results. While 75 nt reads are mentioned in the methods, the sequencing depth remains unspecified. Figure 4b should be included in the supplements. Furthermore, I strongly recommend concentrating on insights into the mechanisms of DCP1a and DCP1b-containing complexes. E.g. what characteristics distinguish DCP1a and DCP1b-dependent mRNAs? Are these targets inherently unstable? Why are they degraded? Are they known decapping substrates?

In general, I suggest the authors revise the manuscript with a focus on the potential readers. Reduce Gene Ontology (GO) analyses and heatmaps, and instead, incorporate more analyses regarding the molecular processes associated with the different decapping complexes.

Significance

The manuscript in its current form could benefit from substantial revisions for it to be considered impactful for researchers in the field.

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

The authors provide evidence that Dcp1a and Dcp1b - two paralogous proteins of the mRNA decapping complex - may have divergent functions in a cancer cell line. In the first part, the authors show that interaction of Dcp2 with EDC4 is diminished upon depletion of Dcp1a but not affected by depletion of Dcp1b. The results have been controlled by overexpression of Dcp1b as it may be limiting factor (i.e. expression levels too low to compensate for depletion of Dcp1a reduced interaction with EDC3/4 while depletion of Dcp1b lead to opposite and increase interactions). They then defined the protein interactome of DDX6 in parental and Dcp1a or Dcp1b depleted cells. Here, the authors show some differential association with EDC4 again, which is along results shown in the first part. The authors further performed SLAM-seq and identified subsets of mRNA whose decay rates are common but also different upon depletion with Dcp1a and Dcp1b. Interestingly, it seems that Dcp1a preferentially targets mRNAs for proteins regulating lymphocyte differentiation. To further test whether changes in RNA decay rates are also reflected at the protein levels, they finally performed an MS analysis with Dcp1a/b depleted cells. However no significant overlap with mRNAs showing altered stability could be observed; and the authors suggested that the lack of congruence reflects translational repression.

Major comments:

1. While functional difference between Dcp1a and Dcp1b are interesting and likely true, there are overinterpretations that need correction or further evidence for support. Sentences like "DCP1a regulates RNA cap binding proteins association with the decapping complex and DCP1b controls translational initiation factors interactions (Figure 2E)" sound misleading. While differential association with proteins has been recognised with MS-data, it does not necessary implement an active process of control/regulation. To make the claim on 'control/regulation', and inducible system or introduction of mutants would be required.
2. The MS analysis is not clearly described in the text and it is unclear how authors selected high-confident proteins. The reader needs to consider the supplemental tables to find out what controls were used. Furthermore, the authors should show correlation plots of MS data between replicates. For instance, there seems to be limited correlation among some of the replicates (e.g. Dcp1b_ko3 sample, Fig. 2c). Any explanation in this variance?
3. GO analysis for the proteome analysis should consider the proteome and not the genome as the background. The authors should also indicate the corrected P-values (multiple testing) FDRs.
4. Fig 2E. The figures display GO enrichments needs better explanation and additional data can be added. The enrichment ratio is not explained (is this normalised?) and p-values and FDRs, number of proteins in respective GO category should be added.

Minor:

1. These studies were performed in a colorectal carcinoma cell line (HCT116). The authors should justify the choice of this specialised cell line. Furthermore, one wonders whether similar conclusions can be drawn with other cell lines or whether findings are specific to this cancer line.
2. Fig. 1B. It is unclear what DCP1b* refers to? There are bands of different size that are not mentioned by the authors - are those protein isoforms or what are those referring to? A molecular marker should be added to each Blots. Uncropped Western images and markers should be provided in the Supplement.
3. MS data submitted to public repository with access. No. indicated in the manuscript.
4. Fig 3. A Venn Diagram displaying the overlap of identified proteins should be added. GO analysis should be done considering the proteome as background (as mentioned above).

Significance

Overall, this is a large-scale integrative -omics study that suggest functional difference between Dcp1 paralogues. While it seems clear that both paralogous have some different functions and impact, there are overinterpretations in place and further evidence would to be provided to substantiate conclusions made in the paper. For instance, while the interactions with Dcp2/Ddx6 in the absence of Dcp1a,b with EDC4/3 may be altered (Fig. 1, 2), the functional implications of this changed associations remains unresolved and not further discussed. As such, it remains somehow disconnected with the following experiments and compromises the flow of the study. The observed differences in decay-rates for distinct functionally related sets of mRNAs is interesting; however, it remains unclear whether those are direct or rather indirect effects. This is further obscured by the absence of any correlation to changes in protein levels, which the authors interpreted as 'transcriptional buffering'. In this regard, it is puzzling how the authors can make a statement about transcriptional buffering? While this may be an interesting aspect and concept of the discussion, there is no primary data showing such a functional impact.

As such, the study is interesting as it claims functional differences between DCP1a/b paralogous in a cancer cell line. Nevertheless, I am not sure how trustful the MS analysis and decay measurements are as there is not further validation. It woudl be interesting if the authors could go a bit further and draw some hypothesis how the selectivty could be achieved i.e interaction with RNA-binding proteins that may add some specificity towards the target RNAs for differential decay. As such, the study remains unfortunately rather descriptive without further functional insight.

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Referee #1

Evidence, reproducibility and clarity

Summary

This study describes efforts to characterize differences in the roles of the two related human decapping factors Dcp1a and Dcp1b by assessing mRNA decay and protein associations in knockdown and knockout cell lines. The authors conclude that these proteins are non-redundant based on the observations that loss of DCp1a versus Dcp1b impacts the decapping complex (interactome) and the transcriptome differentially.

Major comments

• While the experiments appear to be well designed and executed and the data of generally high quality, the conclusions are drawn without sufficient consideration for the fact that these two proteins form a heterotrimeric complex. The authors assume that there are distinct homotrimeric complexes rather than a single complex with both proteins in. Homotrimers may have new/different functions not normally seen when both proteins are expressed. Thus while it is acceptable to infer that the functions of these two proteins within the decapping complex are distinct, it is not clear that they act separately, or that complexes naturally exist without one or the other. A careful evaluation of the relative ratios of Dcp1a and b overall and in decapping complexes would be informative if the authors want to make stronger statements about the roles of these two factors.
• The concept of buffering is not adequately introduced and the interpretation of observations that RNAs with increased half life do not show increased protein abundance - that Dcp1a/b are involved in transcript buffering is nebulous. In order to support this interpretation, the mRNA abundances (NOT protein abundances) should be assessed, and even then, there is no way to rule out indirect effects.
• It might be interesting to see what happens when both factors are depleted to get an idea of the overall importance of each one.
• The algorithms etc used for data analysis should be included at the time of publication. Version number and settings used for SMART to define protein domains, and webgestalt should be indicated
• Statistical analysis is not provided for the IP experiments, the number of replicates performed is not indicated and quantification of KD efficiency are not provided.
• The possibility that the IP Antibody interferes with protein-protein interactions is not mentioned.

Minor comments - P4 - "This translational repression of mRNA associated with decapping can be reversed, providing another point at which gene expression can be regulated (21)" - implies that decapping can be reversed or that decapped RNAs are translated. I don't think this is technically true. - P11 - how common is it for higher eukaryotes to have 2 DCP genes?<br /> - Fig S1 - says "mammalian tissues" in the text but the data is all human. The statement that "expression analyses revealed that DCP1a and DCP1b have concordant rather than reciprocal expression patterns across different mammalian tissues (Supplemental Figure 1)" is a bit misleading as no evidence for correlation or anti-correlation is provided. Also co-expression is not strong support for the idea that these genes have non-redundant functions. Both genes are just expressed in all tissues - there's no evidence provided that they are concordantly expressed. In bone marrow it may be worth noting that one is high and the other low - i.e. reciprocal. - Fig 1A - it is not clear what the different colors mean. Does Sc DCP1 have 1 larger EVH or 2 distinct ones. Are the low complexity regions in Sc DCP2 the SLiMs.<br /> - P11 - why were HCT116 cells selected? - Fig 1B - what are the asterisks by the RNA names? Might be worth noting that over-expression of DCP1b reduced IP of DCP1a. There's no quantification and no indication of the number of times this experiment was repeated. Data from replicates and quantification of the knockdown efficiency in each replicate would be nice to see. - Fig 1C/1D - why are there 3 bands in the DCP1a blot? Quantification of the IP bands is necessary to say whether there is an effect or not of over-expression/KO. - Fig 3 - is it possible that differences are due to epitope positions for the antibodies used for IP? - Fig 5A - the legend doesn't match the colors in the figure. It is not clear how the p<0.05 high confident genes are identified - only some of the genes with p<0.05 are colored red. - Fig 5E and F - x-axis should be log2 fold change - There are a few more recent studies on buffering that should be cited and more discussion of this in the introduction is necessary if conclusions are going to be drawn about buffering. - The heatmaps in figure 2 are hard to interpret.

Significance

• Strengths: The experiments appear to be done well and the datasets should be useful for the field.
• Limitations: The results are overinterpreted - different genes are affected by knocking down one or other of these two similar proteins but this does not really tell us all that much about how the two proteins are functioning in a cell where both are expressed.
• Audience: This study will appeal most to a specialized audience consisting of those interested in the basic mechanisms of mRNA decay. Others may find the dataset useful.
• This study might complement and/or be informed by another recent study in BioRXiv - https://doi.org/10.1101/2023.09.04.556219
• My field of expertise is mRNA decay - I am qualified to evaluate the findings within the context of this field. I do not have much experience of LC-MS-MS and therefore cannot evaluate the methods/analysis of this part of the study.

Something insightful

TPF - potential collaboration

for - Extinction Rebellion - Vancouver - Extinction Rebellion - change of strategy - climate crisis - protests - Extinction Rebellion - moving away from public disruption - Unify Regional Extinction Rebellion

potential collaboration - opportunity - partnership - there is an opportunity to collaborate with them - as they enter this new phase of their work

We need to get approval!

@alisha, do we have approval to release this one?

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Reply to the reviewers

Revision Plan

Manuscript number: RC-2024-02385

Corresponding author(s): Jennifer R. Kowalski

1. General Statements [optional]

Our manuscript describes a novel role for the conserved glycoprotein hormone receptor, FSHR-1, in regulating C. elegans neuromuscular function through an inter-tissue, gut-brain signaling pathway. FSHR-1 is the sole C. elegans homolog of a family of vertebrate glycoprotein receptors that includes FSHR, TSHR, and LHR, and has previously been shown to regulate body size, germline differentiation, lipid homeostasis, and various stress responses in the worm (Kenis at al 2023; Cho et al 2007; Torzone et al 2023; Powell et al 2009; Miller et al 2015; Robinson and Powell 2016; Wei and Kowalski, 2018; Kim and Sieburth 2020; Wang et al 2023) but its role in neuromuscular regulation, although identified in a 2005 RNA interference screen (Sieburth et al 2005), has not been previously explored. Here, through a combination of genetic, behavioral, and fluorescence imaging approaches, we demonstrate that FSHR-1 is both necessary and sufficient in the intestine of the worm (and may also act in several other distal tissues, including glia and head neurons) to promote muscle excitation through effects on active zone protein localization and synaptic vesicle release from cholinergic motor neurons. Additionally, we identify the FSHR-1 ligands, glycoproteins GPLA-1 and GPLB-1, as well as several known downstream effectors of FSHR-1 in other contexts, GSA-1/GalphaS, ACY-1/adenylyl cyclase, and the lipid kinase SPHK-1, as interactors in the FSHR-1 pathway for neuromuscular control. This work represents a detailed description of the ability of this conserved and multi-functional receptor in inter-tissue coordination that may ultimately be connected to its functions in other physiological processes, such as the stress response, and may also prove relevant for understanding roles for FSHR-1 homologs in humans.

We greatly appreciate the thoughtful and constructive feedback provided by each of the three reviewers of this manuscript. We are pleased that all three reviewers noted the novelty of the mechanisms of cross-tissue regulation of neuromuscular function by FSHR-1 that we uncovered. Reviewer 1 comments, "They demonstrate a novel phenomenon of cross-tissue regulation by restoring FSHR-1 in neurons, intestines, or glia to restore NMJ function." Reviewer 2 echoes this sentiment, also noting, "The data is well presented, compelling and the conclusions are well supported by the data. . .. [T]his study provides a solid foundation to address many interesting questions regarding the role of fshr-1 signaling in regulating neuronal function." Reviewer 3 adds "This is a highly worthy contribution to the field of cell non-autonomous signaling and neuromodulation, and specifically synaptic transmission modulation. The study deepens and enhances the understanding of fshr-1 function within the C. elegans intestine and adds in several molecular components into the signaling pathway, acting both upstream and downstream. . . While this work relies on an invertebrate system of C. elegans, all components have vertebrate counterparts, so findings are likely of broader interest."

As described below, we are working to address many of the comments made by the reviewers and have already made some of the suggested minor changes to the manuscript. We are hopeful that, given the reviewers' excitement about this work, the changes we have already made, and the additional revisions we intend to make in the coming months, including the completion of several new experiments we propose in the revision plan below, our manuscript will be of interest to a broad genetics audience.

2. Description of the planned revisions

Planned Revisions based on comments from Reviewer #1

• __The authors found that expressing FSHR-1 in intestinal cells was sufficient to compensate for the fshr-1 mutation phenotype, suggesting that intestinal cell FSHR-1 can regulate neuromuscular junction (NMJ) function across tissues. However, the molecular mechanism remains unexplored. Since the downstream signaling pathways of FSHR-1 are clear, analyzing the gain-of-function (gf) mutations of gsa-1 and acy-1 in different tissues can help elucidate the signaling pathways transmitted across tissues. __ We completely agree that tissue-specific pathway analysis is important for understanding the molecular mechanism underlying the ability of FSHR-1 to control neuromuscular function from its location in distal tissues, like the intestine. Because of the complexity of these questions and the time required for us to generate strains to perform tissue-specific protein depletion or overexpression experiments, we intend these studies to be the focus of a future manuscript However, in lieu of performing a full suite of tissue-specific analyses of FSHR-1 downstream components, we will perform intestine-specific RNA interference experiments (as we did for fshr-1 in Figure 4B) of gsa-1, acy-1, and sphk-1 in wild type worms and in animals overexpressing fshr-1 in the intestine (which causes increased swimming behavior, Figure 3A) to determine if these downstream players are required for the effects of intestinal fshr-1 on the NMJ. __ __We appreciate the reviewer's suggestion to address these important questions regarding the site of action of the downstream players.

• The images of neurons should be presented in higher resolution and magnification to provide clearer visualization. __ We appreciate the reviewer's request for increased visualization of the neurons; however, because the current larger, lower resolution images show several release sites and were used for the quantitative analyses we present, we would like to keep the images as they are. __However, *we will provide higher resolution insets for the images in Figures 2A, 2C-F, and 4C, as requested. *

• It is unclear whether the glycoprotein subunit orthologs act in the intestine to regulate NMJ function with FSHR-1. This should be investigated and clarified in the manuscript. __ We fully agree that determining where and how the glycoproteins GPLA-1 and GPLB-1 interact with FSHR-1 - and if this is happening at the level of the intestine - is an important outstanding question. Based on prior work, it is known that these subunits are not expressed in intestinal cells, but they are found in several gut-associated neurons and tissues. Specifically, gpla-1 is expressed in neurons of the gastrointestinal tract, including M1, M5, I5 and NSM pharyngeal motor neurons, as well the AVL and DVB excitatory motor neurons that control defecation contractions in the hindgut. gplb-1 is also expressed in the DVB neuron, as well as in non-neuronal tissues (head mesodermal cells and the hindgut enteric muscles), and both glycoprotein genes show reporter expression in the RME motor neurons in the head (Kenis et al 2023). We will complete experiments testing whether the effects of intestinal FSHR-1 overexpression require the ligands, as suggested by Reviewer #2. __We intend that our future work will explore the glycoprotein-FSHR-1 interactions more deeply in a variety of contexts.

• __In Figure 4C, there are no error bars, and individual values should be shown in all statistical analyses to provide a complete representation of the data and its variability. __ We again thank the reviewer for catching this error in Figure 4C. We have replaced the graph with the complete one that includes error bars. We will replace the graphs in 1B, 1C, 3D, 4A, 4C, 5A, 5B, and 6E, as well as Supplemental Figure 5A, 5B, 6A, 6B, 7A, and 7C with bars overlaid with the individual data points. We are unable to do this for Figures 2A-F or Supplemental Figures 2A-C, 7B or 7D because these analyses were run using Custom-written Igor software (Burbea et al 2002) that does not provide individual values, only mean values and cumulative probability plots of the datasets. We recently showed consistency between the Igor analysis program and the newer Fiji plug-in we used for our more recent imaging data, supporting concordance of results despite not having the individual data points in Igor (Hulsey-Vincent et al 2023).

Planned Revisions based on comments from Reviewer #2

• __Fig 4B: An intestinal site of action seems likely for fshr-1 and is nicely supported by the intestine-specific RNAi experiment in Fig 4B. Does intestine-specific knockdown of fshr-1 also cause the aldicarb and SNB-1 defects seen in the mutant? Including this data especially for the synaptic markers would strengthen the gut to neuron inter-tissue signaling model that is proposed here (OPTIONAL). __ We appreciate the reviewer's suggestion to include additional intestine-specific knockdown data for the aldicarb, SNB-1::GFP, and other imaging data. We have the reagents to perform the intestine-specific knockdown of fshr-1 in the aldicarb assay and will complete these experiments as part of our revision plan. Although performing the same experiments in the imaging strains requires first crossing each imaging line to the intestine-specific RNAi line, which may may prove challenging, we are currently working to cross the intestinal RNAi line with nuIs152, the cholinergic SNB-1::GFP line and, assuming the cross goes well, will include results in our revised manuscript.

• Fig 5A: The authors show that G alpha s and adenylyl cyclase function downstream of fshr-1, but it is unclear whether these are direct fshr-1 effectors or whether they function less directly. Does expressing gsa-1(gf) or acy-1(gf) transgenes specifically in the intestine (or neurons) suppress the fshr-1 defects? (OPTIONAL) __ As stated in our response to Reviewer #1, we completely agree that tissue-specific pathway analysis is important for understanding the molecular mechanism underlying the ability of FSHR-1 to control neuromuscular function from its location in distal tissues, like the intestine. While the complexity of these questions and the time required for us to generate strains to perform tissue-specific protein depletion or overexpression experiments is likely more than is suitable for the revision time frame of this manuscript (and will be the focus of future work), in lieu of these experiments we will perform intestine-specific RNA interference experiments (as we did for fshr-1 in Figure 4B) of gsa-1, acy-1, and sphk-1 in wild type worms and in animals overexpressing fshr-1 in the intestine (which causes increased swimming behavior, Figure 3A) to determine if these downstream players are required for the effects of intestinal fshr-1 on the NMJ. __We appreciate the reviewer's suggestion to address these important questions regarding the site of action of the downstream players.

• __Fig 6A-D: The authors propose that fshr-1 is activated by its ligands for locomotion, but no evidence is presented to support this. This could be experimentally addressed with the reagents that are used in this study by determining whether the increased locomotion caused by overexpressing fshr-1 in the intestine (reported in Fig 3A), is dependent upon gpla-1 and/or gplb-1 activity. This experiment would help to distinguish whether gpla-1 and/or gplb-1 indeed are fshr-1 ligands or whether fshr-1 functions in a ligand-independent manner, and would justify the sentence on line 526 "...ligands...act upstream in this context..." __ We agree with the reviewer that the question of GP ligand activation of FSHR-1 in this context is an important and interesting question. We plan to cross the intestinal fshr-1 transgene into the gpla-1, gplb-1, and gpla-1gplb-1 mutants, as suggested and then will test their swimming behavior to see if the overexpression effect depends upon the ligands. We thank the reviewer for this experimental suggestion.

Planned Revisions based on comments from Reviewer #3

• __Within Figure 6, the authors state that an experiment was run 2-3X which seems inconsistent with other figure panels. It would be better if three times was consistently used. Adding in another run seems appropriate. To add another experimental run where needed within Figure 6 A-D seems realistic. The strains, reagents and skills are all in place, so the only significant investment is time. These experiments should be able to be completed in a few weeks/months. __ We appreciate the reviewer's desire for consistency in terms of the number of replicates. We will ensure all swimming experiments, which were the experiments in question in Figure 6, have been completed at least 3 times as part of our revision plan.

• The authors findings would be strengthened by doing further work to delineate in which tissues the downstream factors act, by doing tissue specific epistasis basically for gsa-1, acy-1 etc. This would entail a lot of work and would delay publication significantly. I do not see this as necessary unless the authors wish for a big impact journal publication. __ As stated in our response to Reviewers #1 and 2, we agree that tissue-specific pathway analysis is important for understanding the molecular mechanism underlying the ability of FSHR-1 to control neuromuscular function from its location in distal tissues, like the intestine. While the complexity of these questions and the time required for us to generate strains to perform tissue-specific protein depletion or overexpression experiments is likely more than is suitable for the revision time frame of this manuscript (and will be the focus of future work), in lieu of these experiments we will perform intestine-specific RNA interference experiments (as we did for fshr-1 in Figure 4B) of gsa-1, acy-1, and sphk-1 in wild type worms and in animals overexpressing fshr-1 in the intestine (which causes increased swimming behavior, Figure 3A) to determine if these downstream players are required for the effects of intestinal fshr-1 on the NMJ. __We appreciate the reviewer's suggestion to address these important questions regarding the site of action of the downstream players.

• __Figures:____ Overall the authors have presented everything in a clear and thorough manner. Some modification of the Y-axes on several aldicarb resistance graphs & body bend bar graphs could improve the clarity. Trying to standardize the Y axis range and the tick mark locations would make it easier to read and compare between figures and panels. __ We appreciate the reviewer's attention to detail here and will work to further standardize the Y-axes on the graphs as requested.

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

Revisions made to the manuscript in response to comments by Reviewer #1

• __The authors should demonstrate the expression of FSHR-1 in various tissues, as this is essential for analyzing its function. __ We appreciate the reviewer's request for additional clarity regarding the sites of tissue-specific FSHR-1 expression and agree that this information was not sufficiently clear in the text. It is already known that FSHR-1 is expressed in various tissues (e.g., head neurons, glia, intestine) from prior studies (Cho et al, 2007; Kenis et al 2023; Hammarlund et al 2018); thus, we would like to defer to Reviewer #3's suggestion about the expression information and have added a description of FSHR-1 expression patterns to lines 129 -130 within the Introduction of the paper. (Reviewer #3: "In the discussion there is a section about the reported areas of endogenous fshr-1 expression. I would have appreciated knowing that information much earlier in the paper. Without being reminded of the reported normal expression pattern it is difficult to fully appreciate why how the neuronal and glial expression could be at work") This expression information is also mentioned in the Results section lines 420-421 when we first discuss the tissue-specific rescue experiments.

• __Figure 4A appears to be the same as Figure S5B. The authors should ensure that the figures are correctly labeled and distinct from each other. __ We thank the reviewer for noticing this oversight. We apologize for the inadvertent duplication. We have replaced the graphs in Figure 4A with the correct rescue experiment using the Pges-1, ibtEx35-expressing strain.

Revisions made to the manuscript in response to comments by Reviewer #2

• Fig 3: Using transgenic rescue experiments the authors observe rescue when expressing fshr-1 under promoters for the intestine as well as glia and neurons. Is it possible that the apparent rescue using glia and neuronal promoters may arise from leaky expression of these transgenes in the intestine? Leaky intestinal expression is a reported caveat for rescue experiments. This possibility should be discussed. We appreciate the reviewer's note regarding the potential caveat of leaky intestinal expression. We have added a mention of this possibility to the discussion (lines 612-616) where we outline other potential explanations for the ability of multiple transgenes to rescue the neuromuscular phenotype. This possibility is why we feel most confident in the intestine site of action given that we have intestine-specific RNA interference data showing fshr-1 necessity in this tissue. We also acknowledge the need for tissue-specific depletion studies to address requirements for fshr-1 in the other distal tissues. We hope to be able to address these other potential sites of action in our future work.

• __Fig 4B: Please clarify at what stage the intestine-specific knockdown of fshr-1 was conducted. It would be informative to treat animals with fshr-1 RNAi at various developmental stages to distinguish whether fshr-1 plays a developmental or post-developmental role in this process (OPTIONAL). __ We thank the reviewer for bringing to our attention the omission of details regarding the feeding RNA interference experiments. We have added an "RNA Interference" subsection with this information to the Materials and Methods section of the manuscript. Briefly, the intestine-specific knockdown was performed by feeding worms at the L4 stage HT115(DE) bacteria containing L4440 empty plasmid or one targeting fshr-1. Worms were grown for 4 days on NGM agar plates containing Ampicillin and IPTG, then offspring of the treated worms were assayed at the young adult stage. Thus, the knockdown animals we tested had been exposed to the RNAi for their lifetime. We are very interested in exploring the developmental timing of fshr-1 expression and function in future work; thus, we thank the reviewer for this suggestion. However, we feel that a detailed panel of developmental knockdown effects of fshr-1 is beyond the scope of the current study.

• Fig 4C: Is rescue significant? p values are not shown. In figure 4C, p-values are only shown for statistically significant differences, as noted in the figure legend. A Tukey's post-hoc test indicates that the Intestinal Rescue strain is not significantly different from either the wild type or the fshr-1 mutants, indicating partial rescue. While we cannot fully explain the discrepancy between the partial rescue of the SNB-1::GFP phenotype in light of the full behavioral rescue in the swimming, aldicarb, and crawling assays, we suspect it may be due to the fact that synaptic vesicle release has been sufficiently restored to recover neuromuscular signaling even though synaptic vesicle localization is not fully returned to wild type levels, given the variable and likely non-endogenous levels of fshr-1 re-expression from the tissue-specific transgenes. We have noted this discrepancy in the Discussion (lines 633-639) when considering the levamisole and SNB-1::GFP data in light of the aldicarb and swimming results. * "*For some tissue-specific fshr-1 expression experiments, we observed partial rescue of the swimming and crawling fshr-1 mutant phenotypes without a restoration of normal synaptic vesicle localization (e.g., cholinergic motor neurons, GABAergic motor neurons, glial cells, Supplemental Figures 6 and 7). We conclude that GFP::SNB-1 accumulation may not solely report on rates of synaptic vesicle release and/or that there are compensatory mechanisms for increasing muscle excitation (e.g. upregulation of postsynaptic ACh receptors or muscle excitatory machinery."

• __Fig 6E. There are two bars in this graph labeled gpla-1; gplb-1 that show significantly different amplitudes. Please clarify and define the different colors that each graph is outlined with. __ We thank the reviewer for catching this error. The third bar from the left should say "gpla-1;fshr-1". We have corrected this in the manuscript. We have also added descriptions of the colors to the figure legend indicating the following: dark blue = wild type, yellow = fshr-1; green = glycopeptide mutants; blue = glycopeptide;fshr-1 mutants. Similar clarification has been added to the legend for the bar graph in Figure 3D.

Revisions made to the manuscript in response to comments by Reviewer #3

Suggested Text Revisions: I have some suggestions to consider.

• In the abstract the term expression analysis is used to analyses of areas of FSHR-1 function using tissue specific rescue experiments. Expression analysis often means directly exploring mRNA, localization, or levels using transcriptomic approaches or reporter genes so some revision of language could improve accuracy in the abstract. We appreciate the reviewer's point and have removed the phrase "expression analysis" from the summary at the end of the Introduction section where it initially appeared.

• __In Figure 1, the authors do not comment on the overexpression phenotype or why this strain was included. __ We thank the reviewer for noticing this oversight. We have added a sentence describing the overexpression experiment and its implications in our description of Figure 1 in the Results section (lines 337-339).

• __In the discussion there is a section about the reported areas of endogenous fshr-1 expression. I would have appreciated knowing that information much earlier in the paper. Without being reminded of the reported normal expression pattern it is difficult to fully appreciate why how the neuronal and glial expression could be at work. __ We appreciate the reviewer's request for additional clarity regarding the sites of tissue-specific FSHR-1 expression and agree that this information was not sufficiently clear in the text prior to the discussion. We have added a description of FSHR-1 expression patterns to lines 129 -130 within the Introduction of the paper. It is also mentioned in Results section lines 420-421 when we first discuss the tissue-specific rescue experiments.

• __The section on tissue specific rescue could be written more strongly. The use of many "transition" phrases dilutes the importance of the findings in this paragraph. __ We are grateful for the reviewer's suggestions to improve the clarity of the text, specifically regarding the tissue-specific rescue section. We have tightened up the text in this section of the Discussion (lines 547-621) to remove some of the transitional phrases. We believe this has enhanced the readability of the manuscript and the impact of our findings.

• Figures: __ 3 panel D: it is not clear what the last 2 bars (Neuronal rescues) are being compared to, its it w.t.? Were the differences between fshr-1 and these rescues not significantly different? __ We appreciate the reviewer bringing this point of confusion to our attention with Figure 3D. We have clarified in the figure legend that the Neuronal rescue bars are compared to wild type and that there is no significant difference from the fshr-1 mutants for these two lines, further supporting our central focus on the intestine as the best-supported site of FSHR-1 action.

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

Comment from Reviewer #1

• __The article concludes that the fshr-1 mutation affects the release of acetylcholine vesicles. However, using fluorescent proteins to label key proteins released by vesicles may introduce artifacts. Therefore, electron microscopy should be used to analyze vesicle accumulation for more reliable results. __ We thank the reviewers for this suggestion and acknowledge the potential value of EM to definitively show vesicle accumulation in fshr-1 mutants. However, these experiments are technically demanding, involve specialized high-pressure freezing, and would require us to establish new collaborations to complete; thus, we would not be able to be complete such experiments in a timeframe reasonable for revision. While the fluorescence microscopy experiments admittedly offer less resolution, this approach has been used with great success in numerous other studies to identify alterations in synaptic vesicle localization in motor neurons that correlate with electron microscopy, electrophysiology, and aldicarb data that more directly measure numbers of synaptic vesicles and synaptic function (Jorgensen et al 1995; Jin et al 1999; Nonet et al 1999). Thus, we believe that the pHluorin experiments, coupled with the SNB-1::GFP imaging, are sufficient to demonstrate defects in vesicle release, regardless of the specific effects on vesicle clustering. We have been mindful not to overstate our conclusions (lines 371-372: "Together, these data demonstrate that FSHR-1 signaling promotes the localization and/or release of cholinergic synaptic vesicles.") We hope the reviewer will agree that our analysis provides meaningful information about SV organization in the absence of EM level experiments.

• __The authors analyzed the release of vesicles from GABA and acetylcholine (Ach) neurons separately to demonstrate that the fshr-1 mutation specifically affects Ach neuron vesicle release. However, while GFP::SNB-1 and GFP::SYD-1 accumulated in GABA neurons, mCherry::UNC-10 did not change significantly in GABA neurons. To fully understand vesicle release, the authors should also use synaptopHluroin (SpH) to analyze GABA neuron vesicle release. __ We agree that our data indicate that, in addition to effects on cholinergic synaptic vesicle release, there may be effects on release of vesicles from GABAergic neurons, and we acknowledge this in the manuscript. However, while we are interested in potentially exploring the effects of fshr-1 in GABAergic neurons, we believe this question requires extensive additional work that is beyond the scope of this manuscript, which is focused on fshr-1 effects on cholinergic signaling. Moreover, given that fshr-1-deficient animas are aldicarb resistant (Figure 1A), it is unlikely that GABA release is decreased. If GABA release was decreased, we would expect hypersensitivity to aldicarb. Thus, while it is still possible there are different effects on GABA vesicles, our data suggest the most physiological relevant effect is on cholinergic signaling. We do acknowledge in the Discussion that it will be of interest to determine the relevance of effects in the GABA neurons (lines 649-651).

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Referee #3

Evidence, reproducibility and clarity

The authors investigate fshr-1's role in regulation of NMJ signaling using a variety of assays within C. elegans. The power of epistatic analyses is employed to fill in the upstream and downstream signaling components of this non-cell autonomous signaling pathway. The study is strengthened by the inclusion of assays that allow multiple levels of functionality to be assessed, including pharmacological sensitivities, vesicle fusion, locomotory traits and synaptic marker protein distributions.

The study shows that fshr-1 acts within the intestine to set off a signaling cascade that alters NMJ function and aspects of synaptic transmission. Intestinal activity is both necessary and sufficient. Expression of fshr-1 in other areas, while not necessarily linked to endogenous expression, can rescue many NMJ functional activities and some SV localization markers. Ligands for FSHR-1, GPLA-1A and GPLA-1B, were identified using epistasis, as were several downstream signaling components, namely GSA-1, ACY-1 and SPHK-1. The key conclusions are convincing and the authors have stayed truthful and circumspect in their experimental interpretations.

Within Figure 6, the authors state that an experiment was run 2-3X which seems inconsistent with other figure panels. It would be better if three times was consistently used. Adding in another run seems appropriate. To add another experimental run where needed within Figure 6 A-D seems realistic. The strains, reagents and skills are all in place, so the only significant investment is time. These experiments should be able to be completed in a few weeks/months.

The authors findings would be strengthened by doing further work to delineate in which tissues the downstream factors act, by doing tissue specific epistasis basically for gsa-1, acy-1 etc. This would entail a lot of work and would delay publication significantly. I do not see this as necessary unless the authors wish for a big impact journal publication.

Smaller comments for improvement:

Text: I have some suggestions to consider. In the abstract the term expression analysis is used to analyses of areas of FSHR-1 function using tissue specific rescue experiments. Expression analysis often means directly exploring mRNA, localization, or levels using transcriptomic approaches or reporter genes so some revision of language could improve accuracy in the abstract.

In Figure 1, the authors do not comment on the overexpression phenotype or why this strain was included.

In the discussion there is a section about the reported areas of endogenous fshr-1 expression. I would have appreciated knowing that information much earlier in the paper. Without being reminded of the reported normal expression pattern it is difficult to fully appreciate why how the neuronal and glial expression could be at work.

The section on tissue specific rescue could be written more strongly. The use of many "transition" phrases dilutes the importance of the findings in this paragraph.

Figures: Overall the authors have presented everything in a clear and thorough manner. Some modification of the Y-axes on several aldicarb resistance graphs & body bend bar graphs could improve the clarity. Trying to standardize the Y axis range and the tick mark locations would make it easier to read and compare between figures and panels.

Fig. 3 panel D: it is not clear what the last 2 bars (Neuronal rescues) are being compared to, its it w.t.? Were the differences between fshr-1 and these rescues not significantly different?

Significance

This is a highly worthy contribution to the field of cell non-autonomous signaling and neuromodulation, and specifically synaptic transmission modulation. The study deepens and enhances the understanding of fshr-1 function within the C. elegans intestine and adds in several molecular components into the signaling pathway, acting both upstream and downstream. The authors were able to define the output of intestinal fshr-1 function in relation to synaptic vesicle localization and fusion using the pHlourin assay which significantly extends our understanding of the mechanistic dissection of the non-autonomous regulation of Ach synaptic transmission. The manuscript is written with care and insight. The discussion contextualizes the study's findings in relation to the prior studies with care and attempts to elucidate how their findings interrelate.

This would be of high interest to those focused on neuromodulation, synaptic function, and signaling. While this work relies on an invertebrate system of C. elegans, all components have vertebrate counterparts, so findings are likely of broader interest.

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Referee #2

Evidence, reproducibility and clarity

In this study Buckley et al. examine the role of the follicle stimulating hormone receptor homolog FSHR-1 in regulating excitatory neurotransmission at worm neuromuscular junctions (NMJs). They showed that mutations in fshr-1 impair neuromuscular function as measured by aldicarb sensitivity, movement, and abundance of presynaptic markers. They show that these defects can be rescued by expressing fshr-1 in the intestine, glia and neurons to varying extents. Using genetic epistasis analysis, they identify two potential FSHR-1 effectors that function downstream of fshr-1 to control locomotion. Finally, they show that mutations in genes that share homology to mammalian FSH ligands function in a common genetic pathway with fshr-1 to promote locomotion. The authors propose that fshr-1 is part of an inter tissue signaling pathway by which tissues such as the intestine can regulate cholinergic function. The authors have presented a clear story by utilizing genetics, behavioral analysis, and synaptic imaging to demonstrate that intestinal fshr-1 positively regulates cholinergic signaling. The data is well presented, compelling and the conclusions are well supported by the data. The study reinforces prior studies that implicate fshr-1 in positively regulating cholinergic signaling, and the authors use largely indirect assays (movement) to evaluate NMJ function, limiting conceptual and mechanistic advances. However, this study provides a solid foundation to address many interesting questions regarding the role of fshr-1 signaling in regulating neuronal function.

Comments:

1. Fig 3: Using transgenic rescue experiments the authors observe rescue when expressing fshr-1 under promoters for the intestine as well as glia and neurons. Is it possible that the apparent rescue using glia and neuronal promoters may arise from leaky expression of these transgenes in the intestine? Leaky intestinal expression is a reported caveat for rescue experiments. This possibility should be discussed.
2. Fig 4B: An intestinal site of action seems likely for fshr-1, and is nicely supported by the intestine-specific RNAi experiment in Fig 4B. Does intestine-specific knockdown of fshr-1 also cause the aldicarb and SNB-1 defects seen in the mutant? Including this data especially for the synaptic markers would strengthen the gut to neuron inter-tissue signaling model that is proposed here (OPTIONAL).
3. Fig 4B: Please clarify at what stage the intestine-specific knockdown of fshr-1 was conducted. It would be informative to treat animals with fshr-1 RNAi at various developmental stages to distinguish whether fshr-1 plays a developmental or post-developmental role in this process (OPTIONAL).
4. Fig 5A: The authors show that G alpha s and adenylyl cyclase function downstream of fshr-1, but it is unclear whether these are direct fshr-1 effectors or whether they function less directly. Does expressing gsa-1(gf) or acy-1(gf) transgenes specifically in the intestine (or neurons) suppress the fshr-1 defects? (OPTIONAL)
5. Fig 6A-D: The authors propose that fshr-1 is activated by its ligands for locomotion, but no evidence is presented to support this. This could be experimentally addressed with the reagents that are used in this study by determining whether the increased locomotion caused by overexpressing fshr-1 in the intestine (reported in Fig 3A), is dependent upon gpla-1 and/or gplb-1 activity. This experiment would help to distinguish whether gpla-1 and/or gplb-1 indeed are fshr-1 ligands or whether fshr-1 functions in a ligand-independent manner, and would justify the sentence on line 526 "...ligands...act upstream in this context..."
6. Fig 4C: Is rescue significant? p values are not shown.
7. Fig 6E. There are two bars in this graph labeled gpla-1; gplb-1 that show significantly different amplitudes. Please clarify and define the different colors that each graph is outlined with.

Significance

The authors have presented a clear story by utilizing genetics, behavioral analysis, and synaptic imaging to demonstrate that intestinal fshr-1 positively regulates cholinergic signaling. The data is well presented, compelling and the conclusions are well supported by the data. The study reinforces prior studies that implicate fshr-1 in positively regulating cholinergic signaling, and the authors use largely indirect assays (movement) to evaluate NMJ function, limiting conceptual and mechanistic advances. However, this study provides a solid foundation to address many interesting questions using a powerful genetic model organism regarding the role of fshr-1 signaling in regulating neuronal function.

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Referee #1

Evidence, reproducibility and clarity

In this manuscript, the authors investigate the role of the glycoprotein hormone receptor FSHR-1 in regulating cholinergic neurotransmission. They first demonstrate that fshr-1 mutants exhibit strong resistance to the acetylcholine esterase inhibitor aldicarb, consistent with previous findings (Sieburth et al., 2005). The authors further analyze other behaviors of the fshr-1 mutant and conclude that the fshr-1 gene affects neuromuscular regulation.

Next, the authors use GFP::SNB-1 to label acetylcholine neuron vesicles and observe a significant accumulation of GFP::SNB-1 in neurons of the fshr-1 mutant. Using fluorescence recovery after photobleaching (FRAP) experiments with synaptopHluroin (SpH) to label vesicle release, they find a reduction in vesicle release in the fshr-1 mutant.

Furthermore, the authors re-express fshr-1 in the intestine, glia, or neurons of fshr-1 mutants and find that this restoration restores neuromuscular function. They focus on intestinal fshr-1 re-expression for further study, showing that it partially restores the aberrant synaptic vesicle accumulation seen in fshr-1 mutants. Lastly, the authors investigate the involvement of GPLA-1 and GPLB-1, the ligands of FSHR-1, and GSA-1, ACY-1, and SPHK-1, downstream factors of FSHR-1, in the same signaling pathway as fshr-1 in regulating neuromuscular function.

In summary, the authors explore the phenotypes of aldicarb resistance in fshr-1 mutants and confirm the reduction of acetylcholine release in the fshr-1 mutant by labeling the process of acetylcholine neuronal vesicle release. They also analyze the involvement of FSHR-1 ligands and downstream factors in its regulation of the neuromuscular junction (NMJ). Furthermore, they demonstrate a novel phenomenon of cross-tissue regulation by restoring FSHR-1 in neurons, intestines, or glia to restore NMJ function. However, the underlying mechanisms of this cross-tissue regulation remain unexplored.

Major point:

1. The article concludes that the fshr-1 mutation affects the release of acetylcholine vesicles. However, using fluorescent proteins to label key proteins released by vesicles may introduce artifacts. Therefore, electron microscopy should be used to analyze vesicle accumulation for more reliable results.
2. The authors analyzed the release of vesicles from GABA and acetylcholine (Ach) neurons separately to demonstrate that the fshr-1 mutation specifically affects Ach neuron vesicle release. However, while GFP::SNB-1 and GFP::SYD-1 accumulated in GABA neurons, mCherry::UNC-10 did not change significantly in GABA neurons. To fully understand vesicle release, the authors should also use synaptopHluroin (SpH) to analyze GABA neuron vesicle release.
3. The authors found that expressing FSHR-1 in intestinal cells was sufficient to compensate for the fshr-1 mutation phenotype, suggesting that intestinal cell FSHR-1 can regulate neuromuscular junction (NMJ) function across tissues. However, the molecular mechanism remains unexplored. Since the downstream signaling pathways of FSHR-1 are clear, analyzing the gain-of-function (gf) mutations of gsa-1 and acy-1 in different tissues can help elucidate the signaling pathways transmitted across tissues.
4. The images of neurons should be presented in higher resolution and magnification to provide clearer visualization.

Minor point:

1. The authors should demonstrate the expression of FSHR-1 in various tissues, as this is essential for analyzing its function.
2. It is unclear whether the glycoprotein subunit orthologs act in the intestine to regulate NMJ function with FSHR-1. This should be investigated and clarified in the manuscript.
3. Figure 4A appears to be the same as Figure S5B. The authors should ensure that the figures are correctly labeled and distinct from each other.
4. In Figure 4C, there are no error bars, and individual values should be shown in all statistical analyses to provide a complete representation of the data and its variability.

Significance

They demonstrate a novel phenomenon of cross-tissue regulation by restoring FSHR-1 in neurons, intestines, or glia to restore NMJ function.

However, the underlying mechanisms of this cross-tissue regulation remain unexplored.

Those girls took advantage of Maggie as she could not defend herself. This fueled a feeling of power of Maggie for the girls and as we later see for Twyla and Roberta.

Twyla mentioned having the same sentiment. These girls share a lot of experiences from their childhood, and it is apparent as they both continue to think about similar things about their past well into their adult lives.

Both of these girls have experienced unstable home lives and the feeling of not being wanted or not being abled to be taken care of. This shared feeling/experience is probably why Roberta understands Twyla so well.

I wonder what this means. Is she under the influence of drugs? Is she an alcoholic?

This may have been a subconscious action that they took to ensure that they did not settle down at the shelter. This could be a form of entertainment as it was a way of adding something new to their daily lives and/or it could be a way of making the shelter not feel like a permanent home.

Least Authority = Advancing digital security and preserving privacy as a fundamental human right.

Computer and Network Security Berlin 865 followers 11-50 employees

https://media.licdn.com/dms/image/C4E1BAQGvLGo_52CFLA/company-background_10000/0/1617041547182/leastauthority_cover?e=1714161600&v=beta&t=Ac2qK7FAbbxjv7lXCbbCF2qHJproazog6DjnmTl8hTM

Never understood why she didn't change beforehand and questioned why she needed to be there next to him.

I find it interesting that this is still a common and popular conspiracy theory. It puts into perspective that people believe in conspiracy theories when they are scared of the uncertainty and confusion.

It is interesting that this is not a limiting factor in plant growth!

Wow! I think this would be a fascinating fact to share with students, especially since trees are often viewed as plants that show little to no visible growth to students.

I think that this is true because if one thing is for sure I usually tend to remember “arguments” over casual conversations. So it just kind of proves if you speak strongly about something, people are going to remember it, even if they don’t agree.

est ullamcorper eget nulla facilisi etiam. In egestas erat imperdiet sed euismod nisi porta. Pharetra et ultrices neque ornare. Morbi tristique senectus et netus. Non quam lacus suspendisse faucibus interdum.

I love how writers and commentators talk about Steph Curry. It's fascinating to see people try to capture his greatness and how it affects others and transforms the experience for everyone.

Instrument

Observation Facilyt

Feature

Dataset

Dataset

De quel dépôt s'agit-il?

est ullamcorper eget nulla facilisi etiam. In egestas erat imperdiet sed euismod nisi porta. Pharetra et ultrices neque ornare. Morbi tristique senectus et netus. Non quam lacus suspendisse faucibus interdum.

Rodgers, Dennis, and Bruce O’Neill. “Infrastructural Violence: Introduction to the Special Issue.” Ethnography 13, no. 4 (October 23, 2012): 401–12.

Nixon, Rob. Slow Violence and the Environmentalism of the Poor. Cambridge: Harvard ! <br /> University Press, 2011. Accessed March 23, 2024. ProQuest Ebook Central

Lee, Jaclyn, Tesfaye Negussie, and Deena Zaru. “Flint Residents Grapple with Water Crisis 9 Years Later: ‘No Justice.’” ABC News, April 21, 2023.

IPFS china

These are the sample size

They want to see the evolution of enamel growth using homo naledi, that overlap significantly with the emergence of homo sapien

This doesn't point to any specific entry in the blog, but I do find this "the world’s largest open-source non-profit search engine for shadow libraries" (https://annas-blog.org/how-to-run-a-shadow-library.html). There is a difference between a shadow library and a search engine for shadow libraries. Thoughout this document OCLC claims that Anna's is a shadow library rather than a search engine. It appears to be both but the Anna's site isn't entirely clear. It does say that it mirrors other sites, but not precisely which ones.

This is irrelevant to OCLC's claims.

Oh ho, now we get to talk about how OCLC holds ITSELF as a non-profit. See: https://dltj.org/article/oclc-tax-exemption-status/

This actually does not make sense to me. Though they view one record at a time, the enhancements are what is valuable? And I'm sure that it would not be hard to question the "high-quality" records. I'm sure that some are but we all know that there is a fair amount of cruft.

This doesn't make sense. That the data supports other products is true only because there are customers for those products. There's no value to OCLC on its own.

I would like to see them quantify this 'exceptionally high quality'

It's a record number. Yes, it can be used to search the OCLC database, but it is no more authoritative than the model number in the Ikea catalog. Record identifiers are of course quick searches, but they probably are rarely used by humans search bibliographic databases.

The emphasis in WC is on library holdings and the bib data supports that. The bib data alone is not WC.

Perhaps a sort of protobuf is better.

Goes against democratic principles.

A democratic way will be to raise a BAN poll.

I.e., an edge of a hypergraph is a set of vertices.

This is akin to a pub/sub topic.

Multiaddr could be used instead, to aid connectivity

Agent = process

How do you do hypothesis testing for trends for an ordered categorical variable?

Could you convert x to numbers (1,2,3) and run a linear regression y ~ x? or even categorical ordered variables can be linearly regressed?

charles's law

Not necessarily, how to store received events is an implementation detail. One could dump them in an array on a side. Can be as efficient as array of pointers to events. Where idx of this array is event's position in total order.

remove the callout

remove from here

Lo que quiero hacer con ese elmento en particular

elemento de la colección donde estoy ubicado dentro de la colección

mensaje: qué es lo que quiero hacer en esa colección.

Otros mensajes son:

• collect: coleccionar elementos que satisfagan una condición.
• reject: rechazar elementos que satisfagan una condición.
• select: seleccionar elementos que satisfagan una condición.
• `detect: detectar el primer elemento que satisfaga una condición.
• doWithIndex: hacer algo con los elementos teniendo en cuenta también la posición del elemento en el arreglo.

colección: la secuencia de objetos que quiero recorrer.

Ok

Yes

Las pedagogías decoloniales buscan desafiar las estructuras de poder y dominación presentes en los sistemas educativos que reflejan y perpetúan la colonialidad. Al cuestionar las narrativas hegemónicas y dar voz a las perspectivas marginadas, estas pedagogías promueven la inclusión, la justicia social y la equidad en el ámbito educativo. Al integrar enfoques interculturales y respetar la diversidad cultural, las pedagogías decoloniales fomentan un ambiente de aprendizaje en el que los estudiantes pueden desarrollar un sentido crítico, reflexivo y empático hacia las realidades históricas y sociales de diferentes comunidades. En última instancia, contribuyen a la construcción de una educación más inclusiva, igualitaria y emancipadora.

test

루이15세의 광장이 혁명의 광장으로

test

blablabl

TEST 123

3 comments on the same text

2 comments on the same text

qwe

This is a comment about this

Nançay Decameter Array

Stéphane Corbel

Paris Astronomical Data Center

Karl-Ludwig Klein

Isabelle Bualé

Sylvain Cnudde

Marie-Pierre Issartel

Laurent Denis

Philippe Zarka

Jean-Marie Malherbe

Carine Briand

H. Rucker

A. Konovalenko

E. Echer

W. S. Kurth

C. Higgins

CNES

Observatoire de Paris-PSL, LESIA

Observatoire de Paris-PSL, ORN

NDA 35-mm film collection

it is also timeliness because the new album just dropped today.

Taylor swift is a prominance story because so many people want to know about her albums and life

异步执行的，但js又是单线程，因此先执行完当前函数，才能再执行那些异步任务

elemento químico é um conjunto de átomos com o mesmo número atômico

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Reply to the reviewers

*Reviewer #1 (Evidence, reproducibility and clarity (Required)):

I have trialled the package on my lab's data and it works as advertised. It was straightforward to use and did not require any special training. I am confident this is a tool that will be approachable even to users with limited computational experience. The use of artificial data to validate the approach - and to provide clear limits on applicability - is particularly helpful.

The main limitation of the tool is that it requires the user to manually select regions. This somewhat limits the generalisability and is also more subjective - users can easily choose "nice" regions that better match with their hypothesis, rather than quantifying the data in an unbiased manner. However, given the inherent challenges in quantifying biological data, such problems are not easily circumventable.

*

* I have some comments to clarify the manuscript:

1. A "straightforward installation" is mentioned. Given this is a Method paper, the means of installation should be clearly laid out.*

__This sentence is now modified. In the revised manuscript we now describe how to install the toolset and we give the link to the toolset website if further information is needed. __On this website, we provide a full video tutorial and a user manual. The user manual is provided as a supplementary material of the manuscript.

* It would be helpful if there was an option to generate an output with the regions analysed (i.e., a JPG image with the data and the drawn line(s) on top). There are two reasons for this: i) A major problem with user-driven quantification is accidental double counting of regions (e.g., a user quantifies a part of an image and then later quantifies the same region). ii) Allows other users to independently verify measurements at a later time.*

We agree that it is helpful to save the analyzed regions. To answer this comment and the other two reviewers' comments pointing at a similar feature, we have now included an automatic saving of the regions of interest. The user will be able to reopen saved regions of interest using a new function we included in the new version of PatternJ.

* 3. Related to the above point, it is highlighted that each time point would need to be analysed separately (line 361-362). It seems like it should be relatively straightforward to allow a function where the analysis line can be mapped onto the next time point. The user could then adjust slightly for changes in position, but still be starting from near the previous timepoint. Given how prevalent timelapse imaging is, this seems like (or something similar) a clear benefit to add to the software.*

We agree that the analysis of time series images can be a useful addition. We have added the analysis of time-lapse series in the new version of PatternJ. The principles behind the analysis of time-lapse series and an example of such analysis are provided in Figure 1 - figure supplement 3 and Figure 5, with accompanying text lines 140-153 and 360-372. The analysis includes a semi-automated selection of regions of interest, which will make the analysis of such sequences more straightforward than having to draw a selection on each image of the series. The user is required to draw at least two regions of interest in two different frames, and the algorithm will automatically generate regions of interest in frames in which selections were not drawn. The algorithm generates the analysis immediately after selections are drawn by the user, which includes the tracking of the reference channel.

* Line 134-135. The level of accuracy of the searching should be clarified here. This is discussed later in the manuscript, but it would be helpful to give readers an idea at this point what level of tolerance the software has to noise and aperiodicity.

*

We agree with the reviewer that a clarification of this part of the algorithm will help the user better understand the manuscript.__ We have modified the sentence to clarify the range of search used and the resulting limits in aperiodicity (now lines 176-181). __Regarding the tolerance to noise, it is difficult to estimate it a priori from the choice made at the algorithm stage, so we prefer to leave it to the validation part of the manuscript. We hope this solution satisfies the reviewer and future users.

*

**Referees cross-commenting**

I think the other reviewer comments are very pertinent. The authors have a fair bit to do, but they are reasonable requests. So, they should be encouraged to do the revisions fully so that the final software tool is as useful as possible.

Reviewer #1 (Significance (Required)):

Developing software tools for quantifying biological data that are approachable for a wide range of users remains a longstanding challenge. This challenge is due to: (1) the inherent problem of variability in biological systems; (2) the complexity of defining clearly quantifiable measurables; and (3) the broad spread of computational skills amongst likely users of such software.

In this work, Blin et al., develop a simple plugin for ImageJ designed to quickly and easily quantify regular repeating units within biological systems - e.g., muscle fibre structure. They clearly and fairly discuss existing tools, with their pros and cons. The motivation for PatternJ is properly justified (which is sadly not always the case with such software tools).

Overall, the paper is well written and accessible. The tool has limitations but it is clearly useful and easy to use. Therefore, this work is publishable with only minor corrections.

*We thank the reviewer for the positive evaluation of PatternJ and for pointing out its accessibility to the users.

*

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

# Summary

The authors present an ImageJ Macro GUI tool set for the quantification of one-dimensional repeated patterns that are commonly occurring in microscopy images of muscles.

# Major comments

In our view the article and also software could be improved in terms of defining the scope of its applicability and user-ship. In many parts the article and software suggest that general biological patterns can be analysed, but then in other parts very specific muscle actin wordings are used. We are pointing this out in the "Minor comments" sections below. We feel that the authors could improve their work by making a clear choice here. One option would be to clearly limit the scope of the tool to the analysis of actin structures in muscles. In this case we would recommend to also rename the tool, e.g. MusclePatternJ. The other option would be to make the tool about the generic analysis of one-dimensional patterns, maybe calling the tool LinePatternJ. In the latter case we would recommend to remove all actin specific wordings from the macro tool set and also the article should be in parts slightly re-written.

*

We agree with the reviewer that our initial manuscript used a mix of general and muscle-oriented vocabulary, which could make the use of PatternJ confusing especially outside of the muscle field. To make PatternJ useful for the largest community, we corrected the manuscript and the PatternJ toolset to provide the general vocabulary needed to make it understandable for every biologist. We modified the manuscript accordingly.

* # Minor/detailed comments

# Software

We recommend considering the following suggestions for improving the software.

## File and folder selection dialogs

In general, clicking on many of the buttons just opens up a file-browser dialog without any further information. For novel users it is not clear what the tool expects one to select here. It would be very good if the software could be rewritten such that there are always clear instructions displayed about which file or folder one should open for the different buttons.*

We experienced with the current version of macOS that the file-browser dialog does not display any message; we suspect this is the issue raised by the reviewer. This is a known issue of Fiji on Mac and all applications on Mac since 2016. We provided guidelines in the user manual and on the tutorial video to correct this issue by changing a parameter in Fiji. Given the issues the reviewer had accessing the material on the PatternJ website, which we apologize for, we understand the issue raised. We added an extra warning on the PatternJ website to point at this problem and its solution. Additionally, we have limited the file-browser dialog appearance to what we thought was strictly necessary. Thus, the user will experience fewer prompts, speeding up the analysis.

*

## Extract button

The tool asks one to specify things like whether selections are drawn "M-line-to-M-line"; for users that are not experts in muscle morphology this is not understandable. It would be great to find more generally applicable formulations. *

We agree that this muscle-oriented vocabulary can make the use of PatternJ confusing. We have now corrected the user interface to provide both general and muscle-specific vocabulary ("center-to-center or edge-to-edge (M-line-to-M-line or Z-disc-to-Z-disc)").*

## Manual selection accuracy

The 1st step of the analysis is always to start from a user hand-drawn profile across intensity patterns in the image. However, this step can cause inaccuracy that varies with the shape and curve of the line profile drawn. If not strictly perpendicular to for example the M line patterns, the distance between intensity peaks will be different. This will be more problematic when dealing with non-straight and parallelly poised features in the image. If the structure is bended with a curve, the line drawn over it also needs to reproduce this curve, to precisely capture the intensity pattern. I found this limits the reproducibility and easy-usability of the software.*

We understand the concern of the reviewer. On curved selections this will be an issue that is difficult to solve, especially on "S" curved or more complex selections. The user will have to be very careful in these situations. On non-curved samples, the issue may be concerning at first sight, but the errors go with the inverse of cosine and are therefore rather low. For example, if the user creates a selection off by 5 degrees, which is visually obvious, lengths will be affected by an increase of only 0.38%. The point raised by the reviewer is important to discuss, and we therefore added a paragraph to comment on the choice of selection (lines 94-98) and a supplementary figure to help make it clear (Figure 1 - figure supplement 1).*

### Reproducibility

Since the line profile drawn on the image is the first step and very essential to the entire process, it should be considered to save together with the analysis result. For example, as ImageJ ROI or ROIset files that can be re-imported, correctly positioned, and visualized in the measured images. This would greatly improve the reproducibility of the proposed workflow. In the manuscript, only the extracted features are being saved (because the save button is also just asking for a folder containing images, so I cannot verify its functionality). *

We agree that this is a very useful and important feature. We have added ROI automatic saving. Additionally, we now provide a simplified import function of all ROIs generated with PatternJ and the automated extraction and analysis of the list of ROIs. This can be done from ROIs generated previously in PatternJ or with ROIs generated from other ImageJ/Fiji algorithms. These new features are described in the manuscript in lines 120-121 and 130-132.

*

## ? button

It would be great if that button would open up some usage instructions.

*

We agree with the reviewer that the "?" button can be used in a better way. We have replaced this button with a Help menu, including a simple tutorial showing a series of images detailing the steps to follow by the user, a link to the user website, and a link to our video tutorial.

* ## Easy improvement of workflow

I would suggest a reasonable expansion of the current workflow, by fitting and displaying 2D lines to the band or line structure in the image, that form the "patterns" the author aims to address. Thus, it extracts geometry models from the image, and the inter-line distance, and even the curve formed by these sets of lines can be further analyzed and studied. These fitted 2D lines can be also well integrated into ImageJ as Line ROI, and thus be saved, imported back, and checked or being further modified. I think this can largely increase the usefulness and reproducibility of the software.

*

We hope that we understood this comment correctly. We had sent a clarification request to the editor, but unfortunately did not receive an answer within the requested 4 weeks of this revision. We understood the following: instead of using our 1D approach, in which we extract positions from a profile, the reviewer suggests extracting the positions of features not as a single point, but as a series of coordinates defining its shape. If this is the case, this is a major modification of the tool that is beyond the scope of PatternJ. We believe that keeping our tool simple, makes it robust. This is the major strength of PatternJ. Local fitting will not use line average for instance, which would make the tool less reliable.

* # Manuscript

We recommend considering the following suggestions for improving the manuscript. Abstract: The abstract suggests that general patterns can be quantified, however the actual tool quantifies specific subtypes of one-dimensional patterns. We recommend adapting the abstract accordingly.

*

We modified the abstract to make this point clearer.

* Line 58: Gray-level co-occurrence matrix (GLCM) based feature extraction and analysis approach is not mentioned nor compared. At least there's a relatively recent study on Sarcomeres structure based on GLCM feature extraction: https://github.com/steinjm/SotaTool with publication: *https://doi.org/10.1002/cpz1.462

• *

We thank the reviewer for making us aware of this publication. We cite it now and have added it to our comparison of available approaches.

* Line 75: "...these simple geometrical features will address most quantitative needs..." We feel that this may be an overstatement, e.g. we can imagine that there should be many relevant two-dimensional patterns in biology?!*

We have modified this sentence to avoid potential confusion (lines 76-77).

• *

• Line 83: "After a straightforward installation by the user, ...". We think it would be convenient to add the installation steps at this place into the manuscript. *

__This sentence is now modified. We now mention how to install the toolset and we provide the link to the toolset website, if further information is needed (lines 86-88). __On the website, we provide a full video tutorial and a user manual.

* Line 87: "Multicolor images will give a graph with one profile per color." The 'Multicolor images' here should be more precisely stated as "multi-channel" images. Multi-color images could be confused with RGB images which will be treated as 8-bit gray value (type conversion first) images by profile plot in ImageJ. *

We agree with the reviewer that this could create some confusion. We modified "multicolor" to "multi-channel".

* Line 92: "...such as individual bands, blocks, or sarcomeric actin...". While bands and blocks are generic pattern terms, the biological term "sarcomeric actin" does not seem to fit in this list. Could a more generic wording be found, such as "block with spike"? *

We agree with the reviewer that "sarcomeric actin" alone will not be clear to all readers. We modified the text to "block with a central band, as often observed in the muscle field for sarcomeric actin" (lines 103-104). The toolset was modified accordingly.

* Line 95: "the algorithm defines one pattern by having the features of highest intensity in its centre". Could this be rephrased? We did not understand what that exactly means.*

We agree with the reviewer that this was not clear. We rewrote this paragraph (lines 101-114) and provided a supplementary figure to illustrate these definitions (Figure 1 - figure supplement 2).

* Line 124 - 147: This part the only description of the algorithm behind the feature extraction and analysis, but not clearly stated. Many details are missing or assumed known by the reader. For example, how it achieved sub-pixel resolution results is not clear. One can only assume that by fitting Gaussian to the band, the center position (peak) thus can be calculated from continuous curves other than pixels. *

Note that the two sentences introducing this description are "Automated feature extraction is the core of the tool. The algorithm takes multiple steps to achieve this (Fig. S2):". We were hoping this statement was clear, but the reviewer may refer to something else. We agree that the description of some of the details of the steps was too quick. We have now expanded the description where needed.

* Line 407: We think the availability of both the tool and the code could be improved. For Fiji tools it is common practice to create an Update Site and to make the code available on GitHub. In addition, downloading the example file (https://drive.google.com/file/d/1eMazyQJlisWPwmozvyb8VPVbfAgaH7Hz/view?usp=drive_link) required a Google login and access request, which is not very convenient; in fact, we asked for access but it was denied. It would be important for the download to be easier, e.g. from GitHub or Zenodo.

*

We are sorry for issues encountered when downloading the tool and additional material. We thank the reviewer for pointing out these issues that limited the accessibility of our tool. We simplified the downloading procedure on the website, which does not go through the google drive interface nor requires a google account. Additionally, for the coder community the code, user manual and examples are now available from GitHub at github.com/PierreMangeol/PatternJ, and are provided as supplementary material with the manuscript. To our knowledge, update sites work for plugins but not for macro toolsets. Having experience sharing our codes with non-specialists, a classical website with a tutorial video is more accessible than more coder-oriented websites, which deter many users.

* Reviewer #2 (Significance (Required)):

The strength of this study is that a tool for the analysis of one-dimensional repeated patterns occurring in muscle fibres is made available in the accessible open-source platform ImageJ/Fiji. In the introduction to the article the authors provide an extensive review of comparable existing tools. Their new tool fills a gap in terms of providing an easy-to-use software for users without computational skills that enables the analysis of muscle sarcomere patterns. We feel that if the below mentioned limitations could be addressed the tool could indeed be valuable to life scientists interested in muscle patterning without computational skills.

In our view there are a few limitations, including the accessibility of example data and tutorials at sites.google.com/view/patternj, which we had trouble to access. In addition, we think that the workflow in Fiji, which currently requires pressing several buttons in the correct order, could be further simplified and streamlined by adopting some "wizard" approach, where the user is guided through the steps.

*As answered above, the links on the PatternJ website are now corrected. Regarding the workflow, we now provide a Help menu with:

1. __a basic set of instructions to use the tool, __
2. a direct link to the tutorial video in the PatternJ toolset
3. a direct link to the website on which both the tutorial video and a detailed user manual can be found. We hope this addresses the issues raised by this reviewer.

*Another limitation is the reproducibility of the analysis; here we recommend enabling IJ Macro recording as well as saving of the drawn line ROIs. For more detailed suggestions for improvements please see the above sections of our review. *

We agree that saving ROIs is very useful. It is now implemented in PatternJ.

We are not sure what this reviewer means by "enabling IJ Macro recording". The ImageJ Macro Recorder is indeed very useful, but to our knowledge, it is limited to built-in functions. Our code is open and we hope this will be sufficient for advanced users to modify the code and make it fit their needs.*

Reviewer #3 (Evidence, reproducibility and clarity (Required)):

Summary In this manuscript, the authors present a new toolset for the analysis of repetitive patterns in biological images named PatternJ. One of the main advantages of this new tool over existing ones is that it is simple to install and run and does not require any coding skills whatsoever, since it runs on the ImageJ GUI. Another advantage is that it does not only provide the mean length of the pattern unit but also the subpixel localization of each unit and the distributions of lengths and that it does not require GPU processing to run, unlike other existing tools. The major disadvantage of the PatternJ is that it requires heavy, although very simple, user input in both the selection of the region to be analyzed and in the analysis steps. Another limitation is that, at least in its current version, PatternJ is not suitable for time-lapse imaging. The authors clearly explain the algorithm used by the tool to find the localization of pattern features and they thoroughly test the limits of their tool in conditions of varying SNR, periodicity and band intensity. Finally, they also show the performance of PatternJ across several biological models such as different kinds of muscle cells, neurons and fish embryonic somites, as well as different imaging modalities such as brightfield, fluorescence confocal microscopy, STORM and even electron microscopy.

This manuscript is clearly written, and both the section and the figures are well organized and tell a cohesive story. By testing PatternJ, I can attest to its ease of installation and use. Overall, I consider that PatternJ is a useful tool for the analysis of patterned microscopy images and this article is fit for publication. However, i do have some minor suggestions and questions that I would like the authors to address, as I consider they could improve this manuscript and the tool:

*We are grateful to this reviewer for this very positive assessment of PatternJ and of our manuscript.

* Minor Suggestions: In the methodology section is missing a more detailed description about how the metric plotted was obtained: as normalized intensity or precision in pixels. *

We agree with the reviewer that a more detailed description of the metric plotted was missing. We added this information in the method part and added information in the Figure captions where more details could help to clarify the value displayed.

* The validation is based mostly on the SNR and patterns. They should include a dataset of real data to validate the algorithm in three of the standard patterns tested. *

We validated our tool using computer-generated images, in which we know with certainty the localization of patterns. This allowed us to automatically analyze 30 000 images, and with varying settings, we sometimes analyzed 10 times the same image, leading to about 150 000 selections analyzed. From these analyses, we can provide with confidence an unbiased assessment of the tool precision and the tool capacity to extract patterns. We already provided examples of various biological data images in Figures 4-6, showing all possible features that can be extracted with PatternJ. In these examples, we can claim by eye that PatternJ extracts patterns efficiently, but we cannot know how precise these extractions are because of the nature of biological data: "real" positions of features are unknown in biological data. Such validation will be limited to assessing whether a pattern was found or not, which we believe we already provided with the examples in Figures 4-6.

* The video tutorial available in the PatternJ website is very useful, maybe it would be worth it to include it as supplemental material for this manuscript, if the journal allows it. *

As the video tutorial may have been missed by other reviewers, we agree it is important to make it more prominent to users. We have now added a Help menu in the toolset that opens the tutorial video. Having the video as supplementary material could indeed be a useful addition if the size of the video is compatible with the journal limits.

* An example image is provided to test the macro. However, it would be useful to provide further example images for each of the three possible standard patterns suggested: Block, actin sarcomere or individual band.*

We agree this can help users. We now provide another multi-channel example image on the PatternJ website including blocks and a pattern made of a linear intensity gradient that can be extracted with our simpler "single pattern" algorithm, which were missing in the first example. Additionally, we provide an example to be used with our new time-lapse analysis.

* Access to both the manual and the sample images in the PatternJ website should be made publicly available. Right now they both sit in a private Drive account. *

As mentioned above, we apologize for access issues that occurred during the review process. These files can now be downloaded directly on the website without any sort of authentication. Additionally, these files are now also available on GitHub.

* Some common errors are not properly handled by the macro and could be confusing for the user: When there is no selection and one tries to run a Check or Extraction: "Selection required in line 307 (called from line 14). profile=getProfile( ;". A simple "a line selection is required" message would be useful there. When "band" or "block" is selected for a channel in the "Set parameters" window, yet a 0 value is entered into the corresponding "Number of bands or blocks" section, one gets this error when trying to Extract: "Empty array in line 842 (called from line 113). if ( ( subloc . length == 1 ) & ( subloc [ 0 == 0) ) {". This error is not too rare, since the "Number of bands or blocks" section is populated with a 0 after choosing "sarcomeric actin" (after accepting the settings) and stays that way when one changes back to "blocks" or "bands".*

We thank the reviewer for pointing out these bugs. These bugs are now corrected in the revised version.

* The fact that every time one clicks on the most used buttons, the getDirectory window appears is not only quite annoying but also, ultimately a waste of time. Isn't it possible to choose the directory in which to store the files only once, from the "Set parameters" window?*

We have now found a solution to avoid this step. The user is only prompted to provide the image folder when pressing the "Set parameter" button. We kept the prompt for directory only when the user selects the time-lapse analysis or the analysis of multiple ROIs. The main reason is that it is very easy for the analysis to end up in the wrong folder otherwise.

* The authors state that the outputs of the workflow are "user friendly text files". However, some of them lack descriptive headers (like the localisations and profiles) or even file names (like colors.txt). If there is something lacking in the manuscript, it is a brief description of all the output files generated during the workflow.*

PatternJ generates multiple files, several of which are internal to the toolset. They are needed to keep track of which analyses were done, and which colors were used in the images, amongst others. From the user part, only the files obtained after the analysis All_localizations.channel_X.txt and sarcomere_lengths.txt are useful. To improve the user experience, we now moved all internal files to a folder named "internal", which we think will clarify which outputs are useful for further analysis, and which ones are not. We thank the reviewer for raising this point and we now mention it in our Tutorial.

I don't really see the point in saving the localizations from the "Extraction" step, they are even named "temp".

We thank the reviewer for this comment, this was indeed not necessary. We modified PatternJ to delete these files after they are used.

* In the same line, I DO see the point of saving the profiles and localizations from the "Extract & Save" step, but I think they should be deleted during the "Analysis" step, since all their information is then grouped in a single file, with descriptive headers. This deleting could be optional and set in the "Set parameters" window.*

We understand the point raised by the reviewer. However, the analysis depends on the reference channel picked, which is asked for when starting an analysis, and can be augmented with additional selections. If a user chooses to modify the reference channel or to add a new profile to the analysis, deleting all these files would mean that the user will have to start over again, which we believe will create frustration. An optional deletion at the analysis step is simple to implement, but it could create problems for users who do not understand what it means practically.

* Moreover, I think it would be useful to also save the linear roi used for the "Extract & Save" step, and eventually combine them during the "Analysis step" into a single roi set file so that future re-analysis could be made on the same regions. This could be an optional feature set from the "Set parameters" window. *

We agree with the reviewer that saving ROIs is very useful. ROIs are now saved into a single file each time the user extracts and saves positions from a selection. Additionally, the user can re-use previous ROIs and analyze an image or image series in a single step.

* In the "PatternJ workflow" section of the manuscript, the authors state that after the "Extract & Save" step "(...) steps 1, 2, 4, and 5 can be repeated on other selections (...)". However, technically, only steps 1 and 5 are really necessary (alternatively 1, 4 and 5 if the user is unsure of the quality of the patterning). If a user follows this to the letter, I think it can lead to wasted time.

*

We agree with the reviewer and have corrected the manuscript accordingly (line 119-120).

• *

*I believe that the "Version Information" button, although important, has potential to be more useful if used as a "Help" button for the toolset. There could be links to useful sources like the manuscript or the PatternJ website but also some tips like "whenever possible, use a higher linewidth for your line selection" *

We agree with the reviewer as pointed out in our previous answers to the other reviewers. This button is now replaced by a Help menu, including a simple tutorial in a series of images detailing the steps to follow, a link to the user website, and a link to our video tutorial.

* It would be interesting to mention to what extent does the orientation of the line selection in relation to the patterned structure (i.e. perfectly parallel vs more diagonal) affect pattern length variability?*

As answered to reviewer 1, we understand this concern, which needs to be clarified for readers. The issue may be concerning at first sight, but the errors grow only with the inverse of cosine and are therefore rather low. For example, if the user creates a selection off by 3 degrees, which is visually obvious, lengths will be affected by an increase of only 0.14%. The point raised by the reviewer is important to discuss, and we therefore have added a comment on the choice of selection (lines 94-98) as well as a supplementary figure (Figure 1 - figure supplement 1).

* When "the algorithm uses the peak of highest intensity as a starting point and then searches for peak intensity values one spatial period away on each side of this starting point" (line 133-135), does that search have a range? If so, what is the range? *

We agree that this information is useful to share with the reader. The range is one pattern size. We have modified the sentence to clarify the range of search used and the resulting limits in aperiodicity (now lines 176-181).

* Line 144 states that the parameters of the fit are saved and given to the user, yet I could not find such information in the outputs. *

The parameters of the fits are saved for blocks. We have now clarified this point by modifying the manuscript (lines 186-198) and modifying Figure 1 - figure supplement 5. We realized we made an error in the description of how edges of "block with middle band" are extracted. This is now corrected.

* In line 286, authors finish by saying "More complex patterns from electron microscopy images may also be used with PatternJ.". Since this statement is not backed by evidence in the manuscript, I suggest deleting it (or at the very least, providing some examples of what more complex patterns the authors refer to). *

This sentence is now deleted.

* In the TEM image of the fly wing muscle in fig. 4 there is a subtle but clearly visible white stripe pattern in the original image. Since that pattern consists of 'dips', rather than 'peaks' in the profile of the inverted image, they do not get analyzed. I think it is worth mentioning that if the image of interest contains both "bright" and "dark" patterns, then the analysis should be performed in both the original and the inverted images because the nature of the algorithm does not allow it to detect "dark" patterns. *

We agree with the reviewer's comment. We now mention this point in lines 337-339.

* In line 283, the authors mention using background correction. They should explicit what method of background correction they used. If they used ImageJ's "subtract background' tool, then specify the radius.*

We now describe this step in the method section.

*

Reviewer #3 (Significance (Required)):

• Describe the nature and significance of the advance (e.g. conceptual, technical, clinical) for the field. Being a software paper, the advance proposed by the authors is technical in nature. The novelty and significance of this tool is that it offers quick and simple pattern analysis at the single unit level to a broad audience, since it runs on the ImageJ GUI and does not require any programming knowledge. Moreover, all the modules and steps are well described in the paper, which allows easy going through the analysis.
• Place the work in the context of the existing literature (provide references, where appropriate). The authors themselves provide a good and thorough comparison of their tool with other existing ones, both in terms of ease of use and on the type of information extracted by each method. While PatternJ is not necessarily superior in all aspects, it succeeds at providing precise single pattern unit measurements in a user-friendly manner.
• State what audience might be interested in and influenced by the reported findings. Most researchers working with microscopy images of muscle cells or fibers or any other patterned sample and interested in analyzing changes in that pattern in response to perturbations, time, development, etc. could use this tool to obtain useful, and otherwise laborious, information. *

We thank the reviewer for these enthusiastic comments about how straightforward for biologists it is to use PatternJ and its broad applicability in the bio community.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

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Referee #3

Evidence, reproducibility and clarity

Summary

In this manuscript, the authors present a new toolset for the analysis of repetitive patterns in biological images named PatternJ. One of the main advantages of this new tool over existing ones is that it is simple to install and run and does not require any coding skills whatsoever, since it runs on the ImageJ GUI. Another advantage is that it does not only provide the mean length of the pattern unit but also the subpixel localization of each unit and the distributions of lengths and that it does not require GPU processing to run, unlike other existing tools. The major disadvantage of the PatternJ is that it requires heavy, although very simple, user input in both the selection of the region to be analyzed and in the analysis steps. Another limitation is that, at least in its current version, PatternJ is not suitable for time-lapse imaging.

The authors clearly explain the algorithm used by the tool to find the localization of pattern features and they thoroughly test the limits of their tool in conditions of varying SNR, periodicity and band intensity. Finally, they also show the performance of PatternJ across several biological models such as different kinds of muscle cells, neurons and fish embryonic somites, as well as different imaging modalities such as brightfield, fluorescence confocal microscopy, STORM and even electron microscopy.

This manuscript is clearly written, and both the section and the figures are well organized and tell a cohesive story. By testing PatternJ, I can attest to its ease of installation and use. Overall, I consider that PatternJ is a useful tool for the analysis of patterned microscopy images and this article is fit for publication. However, i do have some minor suggestions and questions that I would like the authors to address, as I consider they could improve this manuscript and the tool:

Minor Suggestions:

In the methodology section is missing a more detailed description about how the metric plotted was obtained: as normalized intensity or precision in pixels. The validation is based mostly on the SNR and patterns. They should include a dataset of real data to validate the algorithm in three of the standard patterns tested. The video tutorial available in the PatternJ website is very useful, maybe it would be worth it to include it as supplemental material for this manuscript, if the journal allows it. An example image is provided to test the macro. However, it would be useful to provide further example images for each of the three possible standard patterns suggested: Block, actin sarcomere or individual band. Access to both the manual and the sample images in the PatternJ website should be made publicly available. Right now they both sit in a private Drive account. Some common errors are not properly handled by the macro and could be confusing for the user: When there is no selection and one tries to run a Check or Extraction: "Selection required in line 307 (called from line 14). profile=getProfile( <)>;". A simple "a line selection is required" message would be useful there. When "band" or "block" is selected for a channel in the "Set parameters" window, yet a 0 value is entered into the corresponding "Number of bands or blocks" section, one gets this error when trying to Extract: "Empty array in line 842 (called from line 113). if ( ( subloc . length == 1 ) & ( subloc [ 0 <]> == 0) ) {". This error is not too rare, since the "Number of bands or blocks" section is populated with a 0 after choosing "sarcomeric actin" (after accepting the settings) and stays that way when one changes back to "blocks" or "bands".<br /> The fact that every time one clicks on the most used buttons, the getDirectory window appears is not only quite annoying but also, ultimately a waste of time. Isn't it possible to choose the directory in which to store the files only once, from the "Set parameters" window? The authors state that the outputs of the workflow are "user friendly text files". However, some of them lack descriptive headers (like the localisations and profiles) or even file names (like colors.txt). If there is something lacking in the manuscript, it is a brief description of all the output files generated during the workflow. I don't really see the point in saving the localizations from the "Extraction" step, they are even named "temp". In the same line, I DO see the point of saving the profiles and localizations from the "Extract & Save" step, but I think they should be deleted during the "Analysis" step, since all their information is then grouped in a single file, with descriptive headers. This deleting could be optional and set in the "Set parameters" window. Moreover, I think it would be useful to also save the linear roi used for the "Extract & Save" step, and eventually combine them during the "Analysis step" into a single roi set file so that future re-analysis could be made on the same regions. This could be an optional feature set from the "Set parameters" window. In the "PatternJ workflow" section of the manuscript, the authors state that after the "Extract & Save" step "(...) steps 1, 2, 4, and 5 can be repeated on other selections (...)". However, technically, only steps 1 and 5 are really necessary (alternatively 1, 4 and 5 if the user is unsure of the quality of the patterning). If a user follows this to the letter, I think it can lead to wasted time. I believe that the "Version Information" button, although important, has potential to be more useful if used as a "Help" button for the toolset. There could be links to useful sources like the manuscript or the PatternJ website but also some tips like "whenever possible, use a higher linewidth for your line selection" It would be interesting to mention to what extent does the orientation of the line selection in relation to the patterned structure (i.e. perfectly parallel vs more diagonal) affect pattern length variability? When "the algorithm uses the peak of highest intensity as a starting point and then searches for peak intensity values one spatial period away on each side of this starting point" (line 133-135), does that search have a range? If so, what is the range? Line 144 states that the parameters of the fit are saved and given to the user, yet I could not find such information in the outputs. In line 286, authors finish by saying "More complex patterns from electron microscopy images may also be used with PatternJ.". Since this statement is not backed by evidence in the manuscript, I suggest deleting it (or at the very least, providing some examples of what more complex patterns the authors refer to). In the TEM image of the fly wing muscle in fig. 4 there is a subtle but clearly visible white stripe pattern in the original image. Since that pattern consists of 'dips', rather than 'peaks' in the profile of the inverted image, they do not get analyzed. I think it is worth mentioning that if the image of interest contains both "bright" and "dark" patterns, then the analysis should be performed in both the original and the inverted images because the nature of the algorithm does not allow it to detect "dark" patterns. In line 283, the authors mention using background correction. They should explicit what method of background correction they used. If they used ImageJ's "subtract background' tool, then specify the radius.

Significance

• Describe the nature and significance of the advance (e.g. conceptual, technical, clinical) for the field. Being a software paper, the advance proposed by the authors is technical in nature. The novelty and significance of this tool is that it offers quick and simple pattern analysis at the single unit level to a broad audience, since it runs on the ImageJ GUI and does not require any programming knowledge. Moreover, all the modules and steps are well described in the paper, which allows easy going through the analysis.
• Place the work in the context of the existing literature (provide references, where appropriate). The authors themselves provide a good and thorough comparison of their tool with other existing ones, both in terms of ease of use and on the type of information extracted by each method. While PatternJ is not necessarily superior in all aspects, it succeeds at providing precise single pattern unit measurements in a user-friendly manner.
• State what audience might be interested in and influenced by the reported findings. Most researchers working with microscopy images of muscle cells or fibers or any other patterned sample and interested in analyzing changes in that pattern in response to perturbations, time, development, etc. could use this tool to obtain useful, and otherwise laborious, information.
• 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 a biologist with extensive experience in confocal microscopy and image analysis using classical machine vision tools, particularly using ImageJ and CellProfiler.

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Referee #2

Evidence, reproducibility and clarity

Summary

The authors present an ImageJ Macro GUI tool set for the quantification of one-dimensional repeated patterns that are commonly occurring in microscopy images of muscles.

Major comments

In our view the article and also software could be improved in terms of defining the scope of its applicability and user-ship. In many parts the article and software suggest that general biological patterns can be analysed, but then in other parts very specific muscle actin wordings are used. We are pointing this out in the "Minor comments" sections below. We feel that the authors could improve their work by making a clear choice here. One option would be to clearly limit the scope of the tool to the analysis of actin structures in muscles. In this case we would recommend to also rename the tool, e.g. MusclePatternJ. The other option would be to make the tool about the generic analysis of one-dimensional patterns, maybe calling the tool LinePatternJ. In the latter case we would recommend to remove all actin specific wordings from the macro tool set and also the article should be in parts slightly re-written.

Minor/detailed comments

Software

We recommend considering the following suggestions for improving the software.

File and folder selection dialogs

In general, clicking on many of the buttons just opens up a file-browser dialog without any further information. For novel users it is not clear what the tool expects one to select here. It would be very good if the software could be rewritten such that there are always clear instructions displayed about which file or folder one should open for the different buttons.

Extract button

The tool asks one to specify things like whether selections are drawn "M-line-to-M-line"; for users that are not experts in muscle morphology this is not understandable. It would be great to find more generally applicable formulations.

Manual selection accuracy

The 1st step of the analysis is always to start from a user hand-drawn profile across intensity patterns in the image. However, this step can cause inaccuracy that varies with the shape and curve of the line profile drawn. If not strictly perpendicular to for example the M line patterns, the distance between intensity peaks will be different. This will be more problematic when dealing with non-straight and parallelly poised features in the image. If the structure is bended with a curve, the line drawn over it also needs to reproduce this curve, to precisely capture the intensity pattern. I found this limits the reproducibility and easy-usability of the software.

Reproducibility

Since the line profile drawn on the image is the first step and very essential to the entire process, it should be considered to save together with the analysis result. For example, as ImageJ ROI or ROIset files that can be re-imported, correctly positioned, and visualized in the measured images. This would greatly improve the reproducibility of the proposed workflow. In the manuscript, only the extracted features are being saved (because the save button is also just asking for a folder containing images, so I cannot verify its functionality).

? button

It would be great if that button would open up some usage instructions.

Easy improvement of workflow

I would suggest a reasonable expansion of the current workflow, by fitting and displaying 2D lines to the band or line structure in the image, that form the "patterns" the author aims to address. Thus, it extracts geometry models from the image, and the inter-line distance, and even the curve formed by these sets of lines can be further analyzed and studied. These fitted 2D lines can be also well integrated into ImageJ as Line ROI, and thus be saved, imported back, and checked or being further modified. I think this can largely increase the usefulness and reproducibility of the software.

Manuscript

We recommend considering the following suggestions for improving the manuscript. Abstract: The abstract suggests that general patterns can be quantified, however the actual tool quantifies specific subtypes of one-dimensional patterns. We recommend adapting the abstract accordingly.

Line 58: Gray-level co-occurrence matrix (GLCM) based feature extraction and analysis approach is not mentioned nor compared. At least there's a relatively recent study on Sarcomeres structure based on GLCM feature extraction: https://github.com/steinjm/SotaTool with publication: https://doi.org/10.1002/cpz1.462

Line 75: "...these simple geometrical features will address most quantitative needs..." We feel that this may be an overstatement, e.g. we can imagine that there should be many relevant two-dimensional patterns in biology?!

Line 83: "After a straightforward installation by the user, ...". We think it would be convenient to add the installation steps at this place into the manuscript.

Line 87: "Multicolor images will give a graph with one profile per color." The 'Multicolor images' here should be more precisely stated as "multi-channel" images. Multi-color images could be confused with RGB images which will be treated as 8-bit gray value (type conversion first) images by profile plot in ImageJ.

Line 92: "...such as individual bands, blocks, or sarcomeric actin...". While bands and blocks are generic pattern terms, the biological term "sarcomeric actin" does not seem to fit in this list. Could a more generic wording be found, such as "block with spike"?

Line 95: "the algorithm defines one pattern by having the features of highest intensity in its centre". Could this be rephrased? We did not understand what that exactly means.

Line 124 - 147: This part the only description of the algorithm behind the feature extraction and analysis, but not clearly stated. Many details are missing or assumed known by the reader. For example, how it achieved sub-pixel resolution results is not clear. One can only assume that by fitting Gaussian to the band, the center position (peak) thus can be calculated from continuous curves other than pixels.

Line 407: We think the availability of both the tool and the code could be improved. For Fiji tools it is common practice to create an Update Site and to make the code available on GitHub. In addition, downloading the example file (https://drive.google.com/file/d/1eMazyQJlisWPwmozvyb8VPVbfAgaH7Hz/view?usp=drive_link) required a Google login and access request, which is not very convenient; in fact, we asked for access but it was denied. It would be important for the download to be easier, e.g. from GitHub or Zenodo.

Significance

The strength of this study is that a tool for the analysis of one-dimensional repeated patterns occurring in muscle fibres is made available in the accessible open-source platform ImageJ/Fiji. In the introduction to the article the authors provide an extensive review of comparable existing tools. Their new tool fills a gap in terms of providing an easy-to-use software for users without computational skills that enables the analysis of muscle sarcomere patterns. We feel that if the below mentioned limitations could be addressed the tool could indeed be valuable to life scientists interested in muscle patterning without computational skills.

In our view there are a few limitations, including the accessibility of example data and tutorials at sites.google.com/view/patternj, which we had trouble to access. In addition, we think that the workflow in Fiji, which currently requires pressing several buttons in the correct order, could be further simplified and streamlined by adopting some "wizard" approach, where the user is guided through the steps. Another limitation is the reproducibility of the analysis; here we recommend enabling IJ Macro recording as well as saving of the drawn line ROIs. For more detailed suggestions for improvements please see the above sections of our review.

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

I have trialled the package on my lab's data and it works as advertised. It was straightforward to use and did not require any special training. I am confident this is a tool that will be approachable even to users with limited computational experience. The use of artificial data to validate the approach - and to provide clear limits on applicability - is particularly helpful.

The main limitation of the tool is that it requires the user to manually select regions. This somewhat limits the generalisability and is also more subjective - users can easily choose "nice" regions that better match with their hypothesis, rather than quantifying the data in an unbiased manner. However, given the inherent challenges in quantifying biological data, such problems are not easily circumventable.

I have some comments to clarify the manuscript:

1. A "straightforward installation" is mentioned. Given this is a Method paper, the means of installation should be clearly laid out.
2. It would be helpful if there was an option to generate an output with the regions analysed (i.e., a JPG image with the data and the drawn line(s) on top). There are two reasons for this: i) A major problem with user-driven quantification is accidental double counting of regions (e.g., a user quantifies a part of an image and then later quantifies the same region). ii) Allows other users to independently verify measurements at a later time.
3. Related to the above point, it is highlighted that each time point would need to be analysed separately (line 361-362). It seems like it should be relatively straightforward to allow a function where the analysis line can be mapped onto the next time point. The user could then adjust slightly for changes in position, but still be starting from near the previous timepoint. Given how prevalent timelapse imaging is, this seems like (or something similar) a clear benefit to add to the software.
4. Line 134-135. The level of accuracy of the searching should be clarified here. This is discussed later in the manuscript, but it would be helpful to give readers an idea at this point what level of tolerance the software has to noise and aperiodicity.

Referees cross-commenting

I think the other reviewer comments are very pertinent. The authors have a fair bit to do, but they are reasonable requests. So, they should be encouraged to do the revisions fully so that the final software tool is as useful as possible.

Significance

Developing software tools for quantifying biological data that are approachable for a wide range of users remains a longstanding challenge. This challenge is due to: (1) the inherent problem of variability in biological systems; (2) the complexity of defining clearly quantifiable measurables; and (3) the broad spread of computational skills amongst likely users of such software.

In this work, Blin et al., develop a simple plugin for ImageJ designed to quickly and easily quantify regular repeating units within biological systems - e.g., muscle fibre structure. They clearly and fairly discuss existing tools, with their pros and cons. The motivation for PatternJ is properly justified (which is sadly not always the case with such software tools).

Overall, the paper is well written and accessible. The tool has limitations but it is clearly useful and easy to use. Therefore, this work is publishable with only minor corrections.

@article{swamy_2014, title={Financial Inclusion, Gender Dimension, and Economic Impact on Poor Households}, volume={56}, url={https://consensus.app/papers/inclusion-gender-dimension-economic-impact-poor-swamy/b902747571a85e4da522fb1ab9820260/?extracted-answer=Financial+inclusion+programs+result+in+8.40%25+income+growth+for+women+compared+to+3.97%25+for+men%2C+indicating+that+gender+affects+the+outcomes+of+these+programs.&q=Nivel+de+inclusi%C3%B3n+de+financiera+en+Latinoam%C3%A9rica+entre+hombres+y+mujeres&synthesize=on}, DOI={https://doi.org/10.1016/j.worlddev.2013.10.019}, journal={World development}, publisher={Elsevier BV}, author={Swamy, Vighneswara}, year={2014}, month={Apr}, pages={1–15} }

Noooooooooooo voglio internet

DRC - low militarisation pros and cons

But

前段落に移動

報酬罰と同じような

修正

The correct authors are: Victoria Brügger; Tobias Kowatsch; Mia Jovanova

Author response:

Reviewer #1 (Public Review):

Summary:

[...] This study is a fundamental step towards our better understanding of the mechanisms underlying light effects on cognition and consequently optimising lighting standards.

Strengths:

While it is still impossible to distinguish individual hypothalamic nuclei, even with the high-resolution fMRI, the authors split the hypothalamus into five areas encompassing five groups of hypothalamic nuclei. This allowed them to reveal that different parts of the hypothalamus respond differently to an increase in illuminance. They found that higher illuminance increased the activity of the posterior part of the hypothalamus encompassing the MB and parts of the LH and TMN, while decreasing the activity of the anterior parts encompassing the SCN and another part of TMN. These findings are somewhat in line with studies in animals. It was shown that parts of the hypothalamus such as SCN, LH, and PVN receive direct retinal input in particular from ipRGCs. Also, acute chemogenetic activation of ipRGCs was shown to induce activation of LH and also increased arousal in mice.

Weaknesses:

While the light characteristics are well documented and EDI calculated for all of the photoreceptors, it is not very clear why these irradiances and spectra were chosen. It would be helpful if the authors explained the logic behind the four chosen light conditions tested. Also, the lights chosen have cone-opic EDI values in a high correlation with the melanopic EDI, therefore we can't distinguish if the effects seen here are driven by melanopsin and/or other photoreceptors. In order to provide a more mechanistic insight into the light-driven effects on cognition ideally one would use a silent substitution approach to distinguish between different photoreceptors. This may be something to consider when designing the follow-up studies.

We thank the reviewer for acknowledging the quality and interest of our work and agree with the weaknesses they pointed out.

Blue-enriched light illuminances were set according to the technical characteristics of the light source and to keep the overall photon flux similar to prior 3T MRI studies of our team (between ~1012 and 1014 ph/cm²/s) (Vandewalle et al. 2010 PNAS, Vandewalle et al. 2011 Biol. Psy.). The orange light was introduced as a control visual stimulation for potential secondary whole-brain analyses. It’s photopic illuminance should ideally have been set similar to the low illuminance blue-enriched light condition, but it was not the case. For the present region of interest analyses, we discarded colour differences between the light conditions and only considered illuminance as indexed by mel EDI lux. This constitutes indeed a limitation of our study as it does not allow attributing the findings to a particular photoreceptor class.

The revised version of the manuscript will include a better explanation as to the choice of illuminances and spectra. The discussion will make clear that these choices limit the interpretation about the photoreceptors involved. The discussion will also point out that silent substitution could be used in the future to resolve such question.

Reviewer #2 (Public Review):

[...] By shedding light on these complex interactions, this research endeavors to contribute to the foundational knowledge necessary for developing innovative therapeutic strategies aimed at enhancing cognitive function through environmental modulation.

Strengths:

(1) Considerable Sample Size and Detailed Analysis: The study leverages a robust sample size and conducts a thorough analysis of hypothalamic dynamics, which enhances the reliability and depth of the findings.

(2) Use of High-Resolution Imaging: Utilizing 7 Tesla fMRI to analyze brain activity during cognitive tasks offers high-resolution insights into the differential effects of illuminance on hypothalamic activity, showcasing the methodological rigor of the study.

(3) Novel Insights into Illuminance Effects: The manuscript reveals new understandings of how different regions of the hypothalamus respond to varying illuminance levels, contributing valuable knowledge to the field.

(4) Exploration of Potential Therapeutic Applications: Discussing the potential therapeutic applications of light modulation based on the findings suggests practical implications and future research directions.

Weaknesses:

(1) Foundation for Claims about Orexin and Histamine Systems: The manuscript needs to provide a clearer theoretical or empirical foundation for claims regarding the impact of light on the orexin and histamine systems in the abstract.

(2) Inclusion of Cortical Correlates: While focused on the hypothalamus, the manuscript may benefit from discussing the role of cortical activation in cognitive performance, suggesting an opportunity to expand the scope of the manuscript.

(3) Details of Light Exposure Control: More detailed information about how light exposure was controlled and standardized is needed to ensure the replicability and validity of the experimental conditions.

(4) Rationale Behind Different Exposure Protocols: To clarify methodological choices, the manuscript should include more in-depth reasoning behind using different protocols of light exposure for executive and emotional tasks.

We thank the reviewer for recognising the interest and strength of our study. We agree that corrections and clarifications to the text were needed. We will address the weaknesses they pointed out as follows:

(1) As detailed in the discussion, we do believe orexin and histamine are excellent candidates for mediating the results we report. As also pointing out, however, we are in no position to know which neurons, nuclei, neurotransmitter and neuromodulator underlie the results. We will therefore remove the last sentence of the abstract as we agree our final statement in the abstract was too strong. We will carefully reconsider the discussion to avoid such overstatements.

(2) We are unsure at this stage how to address the comment of the reviewer without considerably lengthening the manuscript with statements which can only be putative. Hypothalamus nuclei are connected to multiple cortical (and subcortical) structures. The relevance of these projections will vary with the cognitive task considered. In addition, we have not yet considered the cortex in our analyses such that truly integrating cortical structures appears premature. We will nevertheless refer to the general statement that subcortical structures (and particularly those receiving direct retinal projections) are likely to receive light illuminance signal first before passing on the light modulation to the cortical regions involved in the ongoing cognitive process.

(3) Illuminance and spectra could not be directly measured within the MRI scanner due to the ferromagnetic nature of measurement systems. The MR coil and the associated optic fibre stand, together with the entire lighting system were therefore placed outside of the MR room to reproduce the experimental conditions of the in a completely dark room. A sensor was placed 2 cm away from the mirror of the coil (mounted at eye level), i.e. where the eye of the first author of the paper would be positioned, to measure illuminance and spectra. The procedure was repeated 4 times for illuminance and twice for spectra and measurements were averaged. This procedure does not take into account inter-individual variation in head size and orbit shape such that the reported illuminance levels may have varied slightly across subjects. The relative differences between illuminance are very unlikely to vary substantially across participants such that statistics consisting of tests for the impact of relative differences in illuminance were not affected. We will report these methodological details in the supplementary material file associated to the paper.

(4) The comment is similar to the issue raised by reviewer 1 (and reviewer 3) so we refer to the response provided to reviewer 1 to address the final comment of reviewer 2.

Reviewer #3 (Public Review):

[...] The authors find evidence in support of a posterior-to-anterior gradient of increased blood flow in the hypothalamus during task performance that they later relate to performance on two different tasks. The results provide an enticing link between light levels, hypothalamic activity, and cognitive/affective function, however, clarification of some methodological choices will help to improve confidence in the findings.

Strengths:

The authors' focus on the hypothalamus and its relationship to light intensity is an important and understudied question in neuroscience.

Weaknesses:

I found it challenging to relate the authors' hypotheses, which I found to be quite compelling, to the apparatus used to test the hypotheses - namely, the use of orange light vs. different light intensities; and the specific choice of the executive and emotional tasks, which differed in key features (e.g., block-related vs. event-related designs) that were orthogonal to the psychological constructs being challenged in each task.

Given the small size of the hypothalamus and the irregular size of the hypothalamic parcels, I wondered whether a more data-driven examination of the hypothalamic time series would have provided a more parsimonious test of their hypothesis.

We thank the reviewer for acknowledging the originality and interest of our study. We agree that some methodological choices needed more explanations. We will address the weaknesses they pointed out as follows:

The first comment questions the choices of the light conditions and of the tasks. Regarding light conditions, since reviewer 1 (and reviewer 2) raised a similar issue, we refer to the response provided to reviewer 1. We agree that many different tasks could have been used to test our hypotheses. Prior work of our team showed that the n-back task and emotional task we used were successful probes to demonstrate that light illuminance modulates cognitive activity, including within subcortical structures (though resolution did not allow precise isolation of nuclei or subparts). When taking the step of ultra-high field imaging we therefore opted for these tasks as our goal was to show that illuminance affects subcortical brain activity across cognitive domains in general and we were not interested in tasks that would test specific aspects of these domains. The fact that one task is event-related while the other consists of a block design adds, in our view, to the robustness of our finding that a similar anterior-posterior gradient of activity modulation by illuminance is present in hypothalamus. We will update the discussion to highlight this aspect.

As mentioned in the text, the protocol also included an auditory attentional task that could have further broadened the potential generalisability of our findings, but it was not part of the analyses as it could only include 2 illuminance levels due to time constrains.

We agree that a data driven approach could have constituted an alternative means to tests our hypothesis. We opted for an approach that we mastered best while still allowing to conclusively test for regional differences in activity across the hypothalamus. Examination of time series of the very same data we used will mainly confirm the results of our analyses – an anterior-posterior gradient in the impact of illuminance - and may yield slight differences in the limits of the subparts of the hypothalamus undergoing decreased or increased activity with increasing illuminance. While the suggested approach may have been envisaged if we had been facing negative results (i.e. no differences between subparts, potentially because subparts would not correspond functional differences in response to illuminance change), it would now constitute a circular confirmation of our main findings (i.e. using the same data). While we truly appreciate the suggestion, we do not consider that it would constitute a more parsimonious test of our hypothesis now that we successfully applied GLM/parcellation and GLMM approaches.

Reviewer #2 (Public Review):

Summary:

The interplay between environmental factors and cognitive performance has been a focal point of neuroscientific research, with illuminance emerging as a significant variable of interest. The hypothalamus, a brain region integral to regulating circadian rhythms, sleep, and alertness, has been posited to mediate the effects of light exposure on cognitive functions. Previous studies have illuminated the role of the hypothalamus in orchestrating bodily responses to light, implicating specific neural pathways such as the orexin and histamine systems, which are crucial for maintaining wakefulness and processing environmental cues. Despite advancements in our understanding, the specific mechanisms through which varying levels of light exposure influence hypothalamic activity and, in turn, cognitive performance, remain inadequately explored. This gap in knowledge underscores the need for high-resolution investigations that can dissect the nuanced impacts of illuminance on different hypothalamic regions. Utilizing state-of-the-art 7 Tesla functional magnetic resonance imaging (fMRI), the present study aims to elucidate the differential effects of light on the hypothalamic dynamics and establish a link between regional hypothalamic activity and cognitive outcomes in healthy young adults. By shedding light on these complex interactions, this research endeavors to contribute to the foundational knowledge necessary for developing innovative therapeutic strategies aimed at enhancing cognitive function through environmental modulation.

Strengths:

(1) Considerable Sample Size and Detailed Analysis:<br /> The study leverages a robust sample size and conducts a thorough analysis of hypothalamic dynamics, which enhances the reliability and depth of the findings.

(2) Use of High-Resolution Imaging:<br /> Utilizing 7 Tesla fMRI to analyze brain activity during cognitive tasks offers high-resolution insights into the differential effects of illuminance on hypothalamic activity, showcasing the methodological rigor of the study.

(3) Novel Insights into Illuminance Effects:<br /> The manuscript reveals new understandings of how different regions of the hypothalamus respond to varying illuminance levels, contributing valuable knowledge to the field.

(4) Exploration of Potential Therapeutic Applications:<br /> Discussing the potential therapeutic applications of light modulation based on the findings suggests practical implications and future research directions.

Weaknesses:

(1) Foundation for Claims about Orexin and Histamine Systems:<br /> The manuscript needs to provide a clearer theoretical or empirical foundation for claims regarding the impact of light on the orexin and histamine systems in the abstract.

(2) Inclusion of Cortical Correlates:<br /> While focused on the hypothalamus, the manuscript may benefit from discussing the role of cortical activation in cognitive performance, suggesting an opportunity to expand the scope of the manuscript.

(3) Details of Light Exposure Control:<br /> More detailed information about how light exposure was controlled and standardized is needed to ensure the replicability and validity of the experimental conditions.

(4) Rationale Behind Different Exposure Protocols:<br /> To clarify methodological choices, the manuscript should include more in-depth reasoning behind using different protocols of light exposure for executive and emotional tasks.

eLife assessment

This fundamental work describes the complex interplay between light exposure, hypothalamic activity, and cognitive function. The evidence supporting the conclusion is compelling with potential therapeutic applications of light modulation. The work will be of broad interest to basic and clinical neuroscientists.

Reviewer #1 (Public Review):

Summary:

Campbell et al investigated the effects of light on the human brain, in particular the subcortical part of the hypothalamus during auditory cognitive tasks. The mechanisms and neuronal circuits underlying light effects in non-image forming responses are so far mostly studied in rodents but are not easily translated in humans. Therefore, this is a fundamental study aiming to establish the impact light illuminance has on the subcortical structures using the high-resolution 7T fMRI. The authors found that parts of the hypothalamus are differently responding to illuminance. In particular, they found that the activity of the posterior hypothalamus increases while the activity of the anterior and ventral parts of the hypothalamus decreases under high illuminance. The authors also report that the performance of the 2-back executive task was significantly better in higher illuminance conditions. However, it seems that the activity of the posterior hypothalamus subpart is negatively related to the performance of the executive task, implying that it is unlikely that this part of the hypothalamus is directly involved in the positive impact of light on performance observed. Interestingly, the activity of the posterior hypothalamus was, however, associated with an increased behavioural response to emotional stimuli. This suggests that the role of this posterior part of the hypothalamus is not as simple regarding light effects on cognitive and emotional responses. This study is a fundamental step towards our better understanding of the mechanisms underlying light effects on cognition and consequently optimising lighting standards.

Strengths:

While it is still impossible to distinguish individual hypothalamic nuclei, even with the high-resolution fMRI, the authors split the hypothalamus into five areas encompassing five groups of hypothalamic nuclei. This allowed them to reveal that different parts of the hypothalamus respond differently to an increase in illuminance. They found that higher illuminance increased the activity of the posterior part of the hypothalamus encompassing the MB and parts of the LH and TMN, while decreasing the activity of the anterior parts encompassing the SCN and another part of TMN. These findings are somewhat in line with studies in animals. It was shown that parts of the hypothalamus such as SCN, LH, and PVN receive direct retinal input in particular from ipRGCs. Also, acute chemogenetic activation of ipRGCs was shown to induce activation of LH and also increased arousal in mice.

Weaknesses:

While the light characteristics are well documented and EDI calculated for all of the photoreceptors, it is not very clear why these irradiances and spectra were chosen. It would be helpful if the authors explained the logic behind the four chosen light conditions tested. Also, the lights chosen have cone-opic EDI values in a high correlation with the melanopic EDI, therefore we can't distinguish if the effects seen here are driven by melanopsin and/or other photoreceptors. In order to provide a more mechanistic insight into the light-driven effects on cognition ideally one would use a silent substitution approach to distinguish between different photoreceptors. This may be something to consider when designing the follow-up studies.

Reviewer #3 (Public Review):

Summary:

Campbell and colleagues use a combination of high-resolution fMRI, cognitive tasks, and different intensities of light illumination to test the hypothesis that the intensity of illumination differentially impacts hypothalamic substructures that, in turn, promote alterations in arousal that affect cognitive and affective performance. The authors find evidence in support of a posterior-to-anterior gradient of increased blood flow in the hypothalamus during task performance that they later relate to performance on two different tasks. The results provide an enticing link between light levels, hypothalamic activity, and cognitive/affective function, however, clarification of some methodological choices will help to improve confidence in the findings.

Strengths:

* The authors' focus on the hypothalamus and its relationship to light intensity is an important and understudied question in neuroscience.

Weaknesses:

* I found it challenging to relate the authors' hypotheses, which I found to be quite compelling, to the apparatus used to test the hypotheses - namely, the use of orange light vs. different light intensities; and the specific choice of the executive and emotional tasks, which differed in key features (e.g., block-related vs. event-related designs) that were orthogonal to the psychological constructs being challenged in each task.

* Given the small size of the hypothalamus and the irregular size of the hypothalamic parcels, I wondered whether a more data-driven examination of the hypothalamic time series would have provided a more parsimonious test of their hypothesis.

¿Cómo afectará esto a los clientes finales?

Microsoft seguramente comience a ofrecer como alternativa su propio software equivalente a Redis, https://github.com/microsoft/garnet

Не уверена, торговавших или торговавшими. Форумы или завсегдатаи? Если форумы, то, наверное, всё-таки не совсем корректно. ...форумов, где торговали украденными учетными записями...

loại trừ 1 nữa

Südsudan: nicht-muslimisches Land, abgespalten von merhetilich-muslimischen Sudan

politische Elite = Dinka (Majority Volksgruppe) Kampf um Einfluss / Ressourcen in neuem Staat

Nationalstaat in ethnischen Gruppen?!

Reviewer #3 (Public Review):

Summary:

In this study, Han and co-authors showed that implantation of Pik3ca deficient KPC cells (aKO) induced clonal expansion of CD8 T cells in the tumor microenvironment. Using aKO cells, they conducted an in vivo genome-wide gene-deletion screen, which showed that deletion of propionyl-CoA carboxylase subunit B gene (Pccb) in αKO cells (p-aKO) leads to immune evasion and tumor progression. Eventually, mice injected with p-aKO but not aKO succumbed to their tumors. Similar to the parental aKO cell line, p-aKO tumors were still infiltrated with clonally expanded CD8+ and CD4+ T cells, as shown by the IHC. Further analyses showed that T cells infiltrating p-aKO tumors expressed high levels of exhaustion markers (PD-1, CTLA-4, TIM3, and TIGIT). Furthermore, PD-1 signaling blockade using PD-1 mAb or genetic depletion of PD-1 reactivated the infiltrated T cells, controlling tumor progression and improving the overall mice survival. Thus, the authors concluded in the abstract that "Pccb can modulate the activity of cytotoxic T cells infiltrating some pancreatic cancers." Although the data clearly showed that the loss of Pccb facilitated the immune evasion of pancreatic cancer cells, there is no clear evidence provided that Pccb deletion can actually modulate the activity of CD8 T cells. One may argue that the deletion of Pccb reduces the immunogenicity of the p-aKO cancer cells, making them less susceptible to killing by normally functional CD8+ T cells.

Strengths:

In vivo, Crisper-Cas-9 screen using tumor cell lines.

Identify a gene that could reduce the immunogenicity of cancer cells.

Weaknesses:

The IHC technique that was used to stain and characterize the exhaustion status of the tumor-infiltrating T cells.

eLife assessment

The significance of the findings is valuable, with implications for immunotherapy design in pancreatic ductal adenocarcinoma. The evidence was considered incomplete and partially supportive of the major claims.

Reviewer #1 (Public Review):

Summary:

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive disease that does not respond to immunotherapy. This work represents an extension of the authors' prior observation that PI3Ka deletion in an orthotopic KPC pancreatic tumor model confers susceptibility to immune-mediated elimination. The authors' major claims in the present manuscript are as follows:

(1) PI3Ka (Pik3ca) knockout in KPC pancreatic tumor cells induces clonal T cell expansion.

(2) Genome-wide LOF screen in aKPC cells to identify tumor-intrinsic determinants of PI3Ka-KO-enhanced T cell response identified Pccb.

(3) When Pccb is knocked out in the context of Pi3ka knockout KPC, anti-tumor T cell response is reduced as measured by<br /> a. Increased tumor progression<br /> b. Decreased survival<br /> c. T cells are still clonally expanded but less functional

(4) ICB is able to "reactivate" clonally expanded T cells.

(5) Conclusion: Pccb modulates the activity of T cells in PDAC.

Overall, the experiments were appropriately executed and technically sound, albeit underpowered for single-cell analyses. Upon careful consideration of the data, the biggest weakness of the paper is the authors' interpretations of results, particularly for claims 1 and 4 (see below for details). Much of the data is correlative and does not delve into causation, leaving this reviewer wishing for experiments that would clearly demonstrate that Pccb in tumor cells directly impacts T cell anti-tumor activity.

Strengths:

(1) Tumor intrinsic determinants of intratumoral T cell infiltration in PDAC are less commonly evaluated as combination therapies for ICB. This is a point of conceptual innovation and importance.

(2) A sensitized CRISPR screen to identify mutations that rescue KPC/PI3Ka-KO tumors from immune-mediated killing is an elegant method to better understand the molecular mechanisms contributing to KPC immunosurveillance. Further, one screen candidate (Pccb) was experimentally validated.

(3) Single-cell clonotype analyses hold promise for identifying tumor-reactive T cells (though authors never demonstrated that specific clones were tumor antigen specific).

Weaknesses:

(1) "Clonal expansion of cytotoxic T cells infiltrating the pancreatic αKO tumors"<br /> a. Only two tumor-bearing hosts were evaluated by single-cell TCR sequencing, thus limiting conclusions that may be drawn regarding repertoire diversity and expansion.<br /> b. High abundance clones in the TME do not necessarily have tumor specificity, nor are they necessarily clonally expanded. They may be clones which are tissue-resident or highly chemokine-responsive and accumulate in larger numbers independent of clonal expansion. Please consider softening language to clonal enrichment or refer to clone size as clonal abundance throughout the paper.<br /> c. The whole story would be greatly strengthened by cytotoxicity assays of abundant TCR clones to show tumor antigen specificity.

(2) "A genome-wide CRISPR gene-deletion screen to identify molecules contributing to Pik3ca-mediated pancreatic tumor immune evasion"<br /> a. CRISPR mutagenesis yielded outgrowth of only 2/8 tumors. A more complete screen with an increased total number of tumors would yield much stronger gene candidates with better statistical power. It is unsurprising that candidates were observed in only one of the two tumors. Nevertheless, the authors moved forward successfully with Pccb.

(3) T cells infiltrate p-αKO tumors with increased expression of immune checkpoints<br /> a. In Figure 4D, cell counts are not normalized to totalCD8+ T cell counts making it difficult to directly compare aKO to p-aKO tumors. Based on quantifications from Figure 4D, I suspect normalization will strengthen the conclusion that CD8+ infiltrate is more exhausted in p-aKO tumors.<br /> b. Flow cytometric analysis to further characterize the myeloid compartment is incomplete (single replicate) and does not strengthen the argument that p-aKO TME is more immunosuppressive.<br /> c. It could, however, strengthen the argument that TIL has less anti-tumor potential if effector molecule expression in CD8+ infiltrating cells were quantified.

(4) Inhibition of PD1/PD-L1 checkpoint leads to elimination of most p-αKO tumors<br /> a. It is reasonable to conclude that p-aKO tumors are responsive to immune checkpoint blockade. However, there is no data presented to support the statement that checkpoint blockade reactivates an existing anti-tumor CD8+ T cell response and does not instead induce a de novo response.<br /> b. The discussion of these data implies that anti-PD-1 would not improve aKO tumor control, but these data are not included. As such, it is difficult to compare the therapeutic response in aKO versus p-aKO. Further, these data are at best an indirect comparison of the T cell responsiveness against tumor, as the only direct comparison is infiltrating cell count in Figure 4 and there are no public TCR clones with confirmed anti-tumor specificity to follow in the aKO versus p-aKO response.

Reviewer #2 (Public Review):

Summary:

Pancreatic ductal adenocarcinoma is generally considered a "cold" tumor type with little T cell infiltration. This group demonstrated previously that deletion of the PIK3CA isoform of PI3K in the orthotopic pancreatic ductal adenocarcinoma KPC mouse tumor model led to the elimination of tumors by T cells. Here they performed a genome-wide gene-deletion screen in this tumor using CRISPR to determine what was required for this T cell-mediated infiltration and tumor rejection. Deletion of Pccb in the tumors, which encodes propionyl-CoA carboxylase subunit B, allowed for the outgrowth of the PIK3CA-deleted KPC tumors. This was confirmed with the specific deletion of Pccb in the tumor cells. Demonstrating a likely role in tumor progression in human patients as well, high expression of PCCB in pancreatic ductal adenocarcinoma correlated with lower patient survival. T cells still infiltrated these tumors, but had much higher expression of exhaustion markers. Blockade of PD-1 signaling allowed for the rejection of these tumors. While these are intriguing data demonstrating that loss of PCCB by pancreatic ductal adenocarcinoma is a mechanism to escape T cell immunity, the mechanism by which this occurs is not determined. In addition, there are a few issues that suggest the conclusions of the manuscript should be tempered.

Strengths:

In vivo analysis of tumor CRISPR deletion screen.

The study describes a possible novel mechanism by which a tumor maintains a "cold" microenvironment.

Weaknesses:

(1) A major issue is that it seems these data are based on the use of a single tumor cell clone with PIK3CA deleted. Therefore, there could be other changes in this clone in addition to the deletion of PIK3CA that could contribute to the phenotype.

(2) The conclusion that the change in the PCCB-deficient tumor cell line is unrelated to mitochondrial metabolic changes may be incorrect based on the data provided. While it is true that in the experiments performed, there was no statistically significant change in the oxygen consumption rate or metabolite levels, this could be due to experimental error. There is a trend in the OCR being higher in the PCCB-deficient cells, although due to a high standard deviation, the change is not statistically significant. There is also a trend for there being more aKG in this cell line, but because there were only 3 samples per cell line, there is no statistically significant difference.

(3) More data are required to make the authors' conclusion that there are myeloid changes in the PCCB-deficient tumor cells. There is only flow data from shown from one tumor of each type.

(4) The previous published study demonstrated increased MHC and CD80 expression in the PIK3CA-deficient tumors and these differences were suggested to be the reason the tumors were rejected. However, no data concerning the levels of these proteins were provided in the current manuscript.

Reviewer #1 (Public Review):

Summary:

In this manuscript, the authors delineate the crucial role of the SIRT2-ACSS2 axis in ACSS2 degradation. They demonstrate that SIRT2 acts as an ACSS2 deacetylase specifically under nutrient stress conditions, notably during amino acid deficiency. The SIRT2-mediated deacetylation of ACSS2 at K271 consequently triggers its proteasomal degradation. Additionally, they illustrate that acetylation of ACSS2 at K271 enhances ACSS2 protein levels, thereby promoting De Novo lipogenesis.

Strengths:

The findings presented in this manuscript are clearly interesting.

Weaknesses:

Further support is required for the model put forward by the authors.

eLife assessment

This useful study describes a role for acetylation in controlling the stability of acetyl-CoA synthetase 2, which converts acetate to acetyl-CoA for de novo lipid synthesis. While some aspects of the study are solid, the overall evidence supporting these findings is incomplete. Including additional critical controls for protein levels and stability and extending the findings to additional cell lines will strengthen the study. This work will be of interest to researchers studying lipid metabolism and related diseases.

Reviewer #2 (Public Review):

Summary:

Karim et al investigated the regulation of ACSS2 by SIRT2. The authors identified a previously undescribed acetylation that they then show is important for the regulation and stability of ACSS2 in cells. The authors show that ACSS2 ubiquitination and degradation by the proteasome is regulated by SIRT2-mediated deacetylation of ACSS2 and that stabilizing ACSS2 by blocking SIRT2 can alter lipid accumulation in adipocytes.

Strengths:

Identification of a novel acetylation site on ACSS2 that regulates its protein stability and that has consequences on its activity in adipocytes. Multiple standard approaches were used to manipulate the expression and function of SIRT2 and ACSS2 (i.e., overexpression, knockdown, inhibitors).

Weaknesses:

The authors do not show direct deacetylation of ACSS2 by SIRT2 in an in vitro biochemical assay.

It would have been nice to have included a bona-fide SIRT2 target as a control throughout the study.

Throughout the manuscript, normalizing the data to 1 and then comparing the fold-change using a t-test is not the best statistical approach in that situation since every normalized value for control is 1 with zero standard deviation. The authors should consider an alternative statistical approach.

Though not necessary, using 13C-acetate or D3-acetate tracing would be better for understanding the impact of acetylation on the activity of ACSS2 and its impact on lipogenesis.

Did the authors also consider investigating SIRT1 in their assays? SIRT1 activates ACSS2 while SIRT2 leads to degradation of ACSS2. They should at least discuss these seemingly opposing roles of SIRT1 and SIRT2 in the regulation of ACSS2 and acetate metabolism in more depth, particularly as it concerns situations (i.e., diseases, pathologies) where either SIRT1, SIRT2, or both sirtuins, are active. This would enhance the significance of the findings to the broader research community.

In Figure 3, the authors should consider immunoblotting for endogenous ACSS2 throughout the differentiation and lipogenesis study since the total ACSS2 levels is the crucial aspect to affecting acetate-dependent promotion of lipogenesis in adipocytes, and to confirm TM-dependent stabilization of ACSS2 in that assay.

Do the authors have any data proving the K271 mutants of ACSS2 are still functional? Or that K271 ACSS2 protein is folded correctly?

Reviewer #3 (Public Review):

Summary:

The manuscript shows SIRT2 can regulate acetylation of ACSS2 at residue 271, acetylation of 271 protects ACSS2 from proteasomal degradation in a SIRT2-dependent manner. Lastly, authors show that ACSS2 acetylation at K271 promotes lipid accumulation.

Strengths:

The author provides solid data showing ACSS2 acetylation can be regulated by targeting SIRT2 and that SIRT2 regulates ACSS2 ubiquitination. They identify K271 as a site of acetylation and show this is a site when mutated alters SIRT2-mediated ubiquitination.

Weaknesses:

However, data for this manuscript seems preliminary as nearly all data is performed in one cell line, some of the conclusions are not well supported by data and the overall role of ACSS2 K271 acetylation is not well characterized.

Author response:

The following is the authors’ response to the original reviews.

Public Reviews:

Reviewer #1 (Public Review):

Summary:

In this manuscript, Bell et al. provide an exhaustive and clear description of the diversity of a new class of predicted type IV restriction systems that the authors denote as CoCoNuTs, for their characteristic presence of coiled-coil segments and nuclease tandems. Along with a comprehensive analysis that includes phylogenetics, protein structure prediction, extensive protein domain annotations, and an in-depth investigation of encoding genomic contexts, they also provide detailed hypotheses about the biological activity and molecular functions of the members of this class of predicted systems. This work is highly relevant, it underscores the wide diversity of defence systems that are used by prokaryotes and demonstrates that there are still many systems to be discovered. The work is sound and backed-up by a clear and reasonable bioinformatics approach. I do not have any major issues with the manuscript, but only some minor comments.

Strengths:

The analysis provided by the authors is extensive and covers the three most important aspects that can be covered computationally when analysing a new family/superfamily: phylogenetics, genomic context analysis, and protein-structure-based domain content annotation. With this, one can directly have an idea about the superfamily of the predicted system and infer their biological role. The bioinformatics approach is sound and makes use of the most current advances in the fields of protein evolution and structural bioinformatics.

Weaknesses:

It is not clear how coiled-coil segments were assigned if only based on AF2-predicted models or also backed by sequence analysis, as no description is provided in the methods. The structure prediction quality assessment is based solely on the average pLDDT of the obtained models (with a threshold of 80 or better). However, this is not enough, particularly when multimeric models are used. The PAE matrix should be used to evaluate relative orientations, particularly in the case where there is a prediction that parts from 2 proteins are interacting. In the case of multimers, interface quality scores, such as the ipTM or pDockQ, should also be considered and, at minimum, reported.

A description of the coiled-coil predictions has been added to the Methods. For multimeric models, PAE matrices and ipTM+pTM scores have been included in Supplementary Data File S1.

Reviewer #2 (Public Review):

Summary:

In this work, using in-depth computational analysis, Bell et al. explore the diverse repertoire of type IV McrBC modification-dependent restriction systems. The prototypical two-component McrBC system has been structurally and functionally characterised and is known to act as a defence by restricting phage and foreign DNA containing methylated cytosines. Here, the authors find previously unanticipated complexity and versatility of these systems and focus on detailed analysis and classification of a distinct branch, the so-called CoCoNut, named after its composition of coiled-coil structures and tandem nucleases. These CoCoNut systems are predicted to target RNA as well as DNA and to utilise defence mechanisms with some similarity to type III CRISPR-Cas systems.

Strengths:

This work is enriched with a plethora of ideas and a myriad of compelling hypotheses that now await experimental verification. The study comes from the group that was amongst the first to describe, characterize, and classify CRISPR-Cas systems. By analogy, the findings described here can similarly promote ingenious experimental and conceptual research that could further drive technological advances. It could also instigate vigorous scientific debates that will ultimately benefit the community.

Weaknesses:

The multi-component systems described here function in the context of large oligomeric complexes. Some of the single chain AF2 predictions shown in this work are not compatible, for example, with homohexameric complex formation due to incompatible orientation of domains. The recent advances in protein structure prediction, in particular AlphaFold2 (AF2) multimer, now allow us to confidently probe potential protein-protein interactions and protein complex formation. This predictive power could be exploited here to produce a better glimpse of these multimeric protein systems. It can also provide a more sound explanation for some of the observed differences amongst different McrBC types.

Hexameric CnuB complexes with CnuC stimulatory monomers for Type I-A, I-B, I-C, II, and III-A CoCoNuT systems have been modeled with AF2 and included in Supplementary Data File S1, albeit without the domains fused to the GTPase N-terminus (with the exception of Type I-B, which lacks the long coiled-coil domain fused to the GTPase and was modeled with its entire sequence). Attempts to model the other full-length CnuB hexamers did not lead to convincing results.

Recommendations for the authors:

Reviewing Editor:

The detailed recommendations by the two reviewers will help the authors to further strengthen the manuscript, but two points seem particularly worth considering: 1. The methods are barely sketched in the manuscript, but it could be useful to detail them more closely. Particularly regarding the coiled-coil segments, which are currently just statists, useful mainly for the name of the family, more detail on their prediction, structural properties, and purpose would be very helpful. 2. Due to its encyclopedic nature, the wealth of material presented in the paper makes it hard to penetrate in one go. Any effort to make it more accessible would be very welcome. Reviewer 1 in particular has made a number of suggestions regarding the figures, which would make them provide more support for the findings described in the text.

A description of the techniques used to identify coiled-coil segments has been added to the Methods. Our predictions ranged from near certainty in the coiled-coils detected in CnuB homologs, to shorter helices at the limit of detection in other factors. We chose to report all probable coiled-coils, as the extensive coiled-coils fused to CnuB, which are often the only domain present other than the GTPase, imply involvement in mediating complex formation by interacting with coiled-coils in other factors, particularly the other CoCoNuT factors. The suggestions made by Reviewer 1 were thoughtful and we made an effort to incorporate them.

Reviewer #1 (Recommendations For The Authors):

I do not have any major issues with the manuscript. I have however some minor comments, as described below.

• The last sentence of the abstract at first reads as a fact and not a hypothesis resulting from the work described in the manuscript. After the second read, I noticed the nuances in the sentence. I would suggest a rephrasing to emphasize that the activity described is a theoretical hypothesis not backed-up by experiments.

This sentence has been rephrased to make explicit the hypothetical nature of the statement.

• In line 64, the authors rename DUF3578 as ADAM because indeed its function is not unknown. Did the authors consider reaching out to InterPro to add this designation to this DUF? A search in interpro with DUF3578 results in "MrcB-like, N-terminal domain" and if a name is suggested, it may be worthwhile to take it to the IntrePro team.

We will suggest this nomenclature to InterPro.

• I find Figure 1E hard to analyse and think it occupies too much space for the information it provides. The color scheme, the large amount of small slices, and the lack of numbers make its information content very small. I would suggest moving this to the supplementary and making it instead a bar plot. If removed from Figure 1, more space is made available for the other panels, particularly the structural superpositions, which in my opinion are much more important.

We have removed Figure 1E from the paper as it adds little information beyond the abundance and phyletic distribution of sequenced prokaryotes, in which McrBC systems are plentiful.

• In Figure 2, it is not clear due to the presence of many colorful "operon schemes" that the tree is for a single gene and not for the full operon segment. Highlighting the target gene in the operons or signalling it somehow would make the figure easy to understand even in the absence of the text and legend. The same applies to Supplementary Figure 1.

The legend has been modified to show more clearly that this is a tree of McrB-like GTPases.

• In line 146, the authors write "AlphaFold-predicted endonucelase fold" to say that a protein contains a region that AF2 predicts to fold like an endonuclease. This is a weird way of writing it and can be confusing to non-expert readers. I would suggest rephrasing for increased clarity.

This sentence has been rephrased for greater clarity.

• In line 167, there is a [47]. I believe this is probably due to a previous reference formatting.

Indeed, this was a reference formatting error and has been fixed.

• In most figures, the color palette and the use of very similar color palettes for taxonomy pie charts, genomic context composition schemes, and domain composition diagrams make it really hard to have a good understanding of the image at first. Legends are often close to each other, and it is not obvious at first which belong to what. I would suggest changing the layouts and maybe some color schemes to make it easier to extract the information that these figures want to convey.

It seemed that Figure 4 was the most glaring example of these issues, and it has been rearranged for easier comprehension.

• In the paragraph that starts at line 199, the authors mention an Ig-like domain that is often found at the N-terminus of Type I CoCoNuTs. Are they all related to each other? How conserved are these domains?

These domains are all predicted to adopt a similar beta-sandwich fold and are found at the N-terminus of most CoCoNuT CnuC homologs, suggesting they are part of the same family, but we did not undertake a more detailed sequenced-based analysis of these regions.

We also find comparable domains in the CnuC/McrC-like partners of the abundant McrB-like NxD motif GTPases that are not part of CoCoNuT systems, and given the similarity of some of their predicted structures to Rho GDP-dissociation inhibitor 1, we suspect that they have coevolved as regulators of the non-canonical NxD motif GTPase type. Our CnuBC multimer models showing consistent proximity between these domains in CnuC and CnuB GTPase domains suggest this could indeed be the case. We plan to explore these findings further in a forthcoming publication.

• In line 210, the authors write "suggesting a role in overcrowding-induced stress response". Why so? In >all other cases, the authors justify their hypothesis, which I really appreciated, but not here.

A supplementary note justifying this hypothesis has been added to Supplementary Data File S1.

• At the end of the paragraph that starts in line 264, the authors mention that they constructed AF2 multimeric models to predict if 2 proteins would interact. However, no quality scores were provided, particularly the PAE matrix. This would allow for a better judgement of this prediction, and I would suggest adding the PAE matrix as another panel in the figure where the 3D model of the complex is displayed.

The PAE matrix and ipTM+pTM scores for this and other multimer models have been added to Supplementary Data File S1. For this model in particular, the surface charge distribution of the model has been presented to support the role of the domains that have a higher PAE in RNA binding.

• In line 306, "(supplementary data)" refers to what part of the file?

This file has been renamed Supplementary Table S3 and referenced as such.

• In line 464, the authors suggest that ShdA could interact with CoCoNuTs. Why not model the complex as done for other cases? what would co-folding suggest?

As we were not able to convincingly model full-length CnuB hexamers with N-terminal coiled-coils, we did not attempt modeling of this hypothetical complex with another protein with a long coiled-coil, but it remains an interesting possibility.

• In line 528, why and how were some genes additionally analyzed with HHPred?

Justification for this analysis has been added to the Methods, but briefly, these genes were additionally analyzed if there were no BLAST hits or to confirm the hits that were obtained.

• In the first section of the methods, the first and second (particularly the second) paragraphs are extremely long. I would suggest breaking them to facilitate reading.

This change has been made.

• In line 545, what do the authors mean by "the alignment (...) were analyzed with HHPred"?

A more detailed description of this step has been added to the Methods.

• The authors provide the models they produced as well as extensive supplementary tables that make their data reusable, but they do not provide the code for the automated steps, as to excise target sequence sections out of multiple sequence alignments, for example.

The code used for these steps has been in use in our group at the NCBI for many years. It will be difficult to utilize outside of the NCBI software environment, but for full disclosure, we have included a zipped repository with the scripts and custom-code dependencies, although there are external dependencies as well such as FastTree and BLAST. In brief, it involves PSI-BLAST detection of regions with the most significant homology to one of a set of provided alignments (seals-2-master/bin/wrappers/cog_psicognitor). In this case, the reference alignments of McrB-like GTPases and DUF2357 were generated manually using HHpred to analyze alignments of clustered PSI-BLAST results. This step provided an output of coordinates defining domain footprints in each query sequence, which were then combined and/or extended using scripts based on manual analysis of many examples with HHpred (footprint_finders/get_GTPase_frags.py and footprint_finders/get_DUF2357_frags.py), then these coordinates were used to excise such regions from the query amino acid sequence with a final script (seals-2-master/bin/misc/fa2frag).

Reviewer #2 (Recommendations For The Authors):

(1) Page 4, line 77 - 'PUA superfamily domains' could be more appropriate to use instead of "EVE superfamily".

While this statement could perhaps be applied to PUA superfamily domains, our previous work we refer to, which strongly supports the assertion, was restricted to the EVE-like domains and we prefer to retain the original language.

(2) Page 5. lines 128-130 - AF2 multimer prediction model could provide a more sound explanation for these differences.

Our AF2 multimer predictions added in this revision indeed show that the NxD motif McrB-like CoCoNuT GTPases interact with their respective McrC-like partners such that an immunoglobulin-like beta-sandwich domain, fused to the N-termini of the McrC homologs and similar to Rho GDP-dissociation inhibitor 1, has the potential to physically interact with the GTPase variants. However, we did not probe this in greater detail, as it is beyond the scope of this already highly complex article, but we plan to study it in the future.

(3) Page 8, line 252 - The surface charge distribution of CnuH OB fold domain looks very different from SmpB (pdb3iyr). In fact, the regions that are in contact with RNA in SmpB are highly acidic in CoCoNut CnuH. Although it looks likely that this domain is involved in RNA binding, the mode of interaction should be very different.

We did not detect a strong similarity between the CnuH SmpB-like SPB domain and PDB 3IYR, but when we compare the surface charge distribution of PDB 1WJX and the SPB domain, while there is a significant area that is positively charged in 1WJX that is negatively charged in SPB, there is much that overlaps with the same charge in both domains.

The similarity between SmpB and the SPB domain is significant, but definitely not exact. An important question for future studies is: If the domains are indeed related due to an ancient fusion of SmpB to an ancestor of CnuH, would this degree of divergence be expected?

In other words, can we say anything about how the function of a stand-alone tmRNA-binding protein could evolve after being fused to a complex predicted RNA helicase with other predicted RNA binding domains already present? Experimental validation will ultimately be necessary to resolve these kinds of questions, but for now, it may be safe to say that the presence of this domain, especially in conjunction with the neighboring RelE-like RTL domain and UPF1-like helicase domain, signals a likely interaction with the A-site of the ribosome, and perhaps restriction of aberrant/viral mRNA.

eLife assessment

This paper marks a fundamental advance in our understanding of prokaryotic Type IV restriction systems. The authors provide an encyclopedic overview of a hitherto uncharacterized branch of these systems, which they name CoCoNuTs, for coiled-coil nuclease tandems. They provide compelling evidence that these nucleases target RNA and are part of an echeloned defense response following viral infection. This article will be of great interest to scientists studying prokaryotic immunity mechanisms, as well as broadly to protein scientists engaged in the analysis, classification, and functional annotation of the proteome of life.

Reviewer #1 (Public Review):

Summary:

In this manuscript, Bell et al. provide an exhaustive and clear description of the diversity of a new class of predicted type IV restriction systems that the authors denote as CoCoNuTs, for their characteristic presence of coiled-coil segments and nuclease tandems. Along with a comprehensive analysis that includes phylogenetics, protein structure prediction, extensive protein domain annotations, and in-depth investigation of encoding genomic contexts, they also provide detailed hypothesis about the biological activity and molecular functions of the members of this class of predicted systems. This work is highly relevant, it underscores the wide diversity of defence systems that are used by prokaryotes and demonstrates that there are still many systems to be discovered. The work is sound and backed up by a clear and reasonable bioinformatics approach.

Strengths:

The analysis provided by the authors is extensive and covers the three most important aspects that can be covered computationally when analysing a new family/superfamily: phylogenetics, genomic context analysis, and protein-structure-based domain content annotation. With this, one can directly have an idea about the superfamily of the predicted system and infer about their biological role. The bioinformatics approach is sound and makes use of the most current advances in the fields of protein evolution and structural bioinformatics.

Weaknesses:

It is not clear how coiled-coil segments were assigned if only based on AF2-predicted models or also backed by sequence analysis, as no description is provided in the methods. The structure prediction quality assessment is based solely on the average pLDDT of the obtained models (with a threshold of 80 or better). However, this is not enough, particularly when multimeric models were used. The PAE matrix should be used to evaluate relative orientations, particularly in the case where there is a prediction that parts from 2 proteins are interacting. In the case of multimers, interface quality scores, as the ipTM or pDockQ, should also be considered and, at minimum, reported.

These weaknesses were addressed during revision, and the results provided by the authors support their conclusions. The data resulting from this work will be useful for the general life sciences community, particularly the prokaryotic defense and microbiology communities. It also underscores the high range of functionally unknowns in sequenced genomes that are now much easier to find and interpret due to the success of deep-learning based methods and automated robust bioinformatics pipelines.

Reviewer #2 (Public Review):

Summary:

In this work, using in-depth computational analysis, Bell et al. explore the diverse repertoire of type IV McrBC modification dependent restriction systems. The prototypical two-component McrBC system has been structurally and functionally characterised and is known to act as a defence by restricting phage and foreign DNA containing methylated cytosines. Here, the authors find previously unanticipated complexity and versatility of these systems and focus on detailed analysis and classification of a distinct branch, the so-called CoCoNut, named after its composition of coiled-coil structures and tandem nucleases. These CoCoNut systems are predicted to target RNA as well as DNA and to utilise defence mechanisms with some similarity to type III CRISPR-Cas systems.

Strengths:

This work is enriched with a plethora of ideas and a myriad of compelling hypotheses that now will await experimental verification. The study comes from the group that was amongst the first to describe, characterise, and classify CRISPR-Cas systems. By analogy, the findings described here can similarly promote ingenious experimental and conceptual research that could further drive technological advances. It could also instigate vigorous scientific debates that will ultimately benefit the community.

Weaknesses:

The multi-component systems described here function in the context of large oligomeric complexes similarly to the prototypical McrBC system. While the AlphaFold2 (AF2) multimer predictions are provided in this work, these are not compared with the known McrBC structures. These comparisons could have been helpful not only for providing insights into these multimeric protein systems but also for giving more sound explanations of the differences observed amongst different McrBC types.

eLife assessment

The paper presents valuable insights into the success of the parasitoid Trichopria drosophilae on Drosophila suzukii, elucidating the importance of both molecular adaptations, such as specialized venom proteins and unique cell types, and ecological strategies, including tolerance of intraspecific competition and avoidance of interspecific competition. Through convincing methodological approaches, the authors demonstrate how these adaptations optimize nutrient uptake and enhance parasitic success, highlighting the intricate coordination between molecular and ecological factors in driving parasitization success.

Reviewer #1 (Public Review):

Summary:

Major findings or outcomes include a genome for the wasp, characterization of the venom constituents and teratocyte and ovipositor expression profiles, as well as information about Trichopria ecology and parasitism strategies. It was found that Trichopria cannot discriminate among hosts by age, but can identify previously parasitized hosts. The authors also investigated whether superparasitism by Trichopria wasps improved parasitism outcomes (it did), presumably by increasing venom and teratocyte concentrations/densities. Elegant use of Drosophila ectopic expression tools allowed for functional characterization of venom components (Timps), and showed that these proteins are responsible for parasitoid-induced delays in host development. After finding that teratocytes produce a large number of proteases, experiments showed that these contribute to digestion of host tissues for parasite consumption.<br /> The discussion ties these elements together by suggesting that genes used for aiding in parasitism via different parts of the parasitism arsenal arise from gene duplication and shifts in tissue of expression (to venom glands or teratocytes).

Strengths:

The strength of this manuscript is that it describes the parasitism strategies used by Trichopria wasps at a molecular and behavioral level with broad strokes. It represents a large amount of work that in previous decades might have been published in several different papers. Including all of these data in a manuscript together makes for a comprehensive and interesting study.

Weaknesses:

The weakness is that the breadth of the study results in fairly shallow mechanistic or functional results for any given facet of Trichopria's biology. Although none of the findings are especially novel given results from other parasitoid species in previous publications, integrating results together provides significant information about Trichopria biology.

Reviewer #2 (Public Review):

Summary:

Key findings of this research include the sequencing of the wasp's genome, identification of venom constituents and teratocytes, and examination of Trichopria drosophilae (Td)'s ecology and parasitic strategies. It was observed that Td doesn't distinguish between hosts based on age but can recognize previously parasitized hosts. The study also explored whether multiple parasitisms by Td improved outcomes, which indeed it did, possibly by increasing venom and teratocyte levels. Utilizing Drosophila ectopic expression tools, the authors functionally characterized venom components, specifically tissue inhibitors of metalloproteinases (Timps), which were found to cause delays in host development. Additionally, experiments revealed that teratocytes produce numerous proteases, aiding in the digestion of host tissues for parasite consumption. The discussion suggests that genes involved in different aspects of parasitism may arise from gene duplication and shifts in tissue expression to venom glands or teratocytes.

Strengths:

This manuscript provides an in-depth and detailed depiction of the parasitic strategies employed by Td wasps, spanning both molecular and behavioral aspects. It consolidates a significant amount of research that, in the past, might have been distributed across multiple papers. By presenting all this data in a single manuscript, it delivers a comprehensive and engaging study that could help future developments in the field of biological control against a major insect pest.

Weaknesses:

While none of the findings are particularly groundbreaking, as similar results have been reported for other parasitoid species in prior research, the integration of these results into one comprehensive overview offers valuable biological insights into an interesting new potential biocontrol species.

eLife assessment

This important study asks whether motor neurons within the vestibulo-ocular circuit of zebrafish are required to determine the identity, connectivity, and function of upstream premotor neurons. They provide convincing genetic, anatomical and behavioral evidence that the answer is no. This work is of general interest to developmental neurobiologists and motivates future studies of whether motor neurons are dispensable for assembly of other sensorimotor neural circuits.

Reviewer #1 (Public Review):

Summary:

This study has as its goal to determine how the structure and function of the circuit that stabilizes gaze in the larval zebrafish depends on the presence of the output cells, the motor neurons. A major model of neural circuit development posits that the wiring of neurons is instructed by their postsynaptic cells, transmitting signals retrogradely on which cells to contact and, by extension, where to project their axons. Goldblatt et al. remove the motor neurons from the circuit by generating null mutants for the phox2a gene. The study then shows that, in this mutant that lacks the isl1-labelled extraocular motor neurons, the central projection neurons have 1) largely normal responses to vestibular input; 2) normal gross morphology; 3) minimally changed transcriptional profiles. From this, the authors conclude that the wiring of the circuit is not instructed by the output neurons, refuting the major model.

Strengths:

I found the manuscript to be exceptionally well-written and presented, with clear and concise writing and effective figures that highlight key concepts. The topic of neural circuit wiring is central to neuroscience, and the paper's findings will interest researchers across the field, and especially those focused on motor systems.

The experiments conducted are clever and of a very high standard, and I liked the systematic progression of methods to assess the different potential effects of removing phox2a on circuit structure and function. Analyses (including statistics) are comprehensive and appropriate and show the authors are meticulous and balanced in most of the conclusions that they draw. Overall, the findings are interesting, and with a few tweaks, should leave little doubt about the paper's main conclusions.

Weaknesses:

The main point is the incomplete characterisation of the effects of removing phox2a on the extra-ocular motor neurons. Are these cells no longer there, or are they there but no longer labelled by isl1:GFP? If they are indeed removed, might they have developed early on, and subsequently lost? These questions matter as the central focus of the manuscript is whether the presence of these cells influences the connectivity and function of their presynaptic projection neurons. Therefore, for the main conclusions to be fully supported by the data, the authors would need to test whether 1) the motor neurons that otherwise would have been labelled by the isl1:GFP line are physically no longer there; 2) that this removal (if, indeed, it is that) is developmental. If these experiments are not feasible, then the text should be adjusted to take this into account. A further point to address is the context of the manipulation. If the phox2a removal does indeed take out the extra-ocular motor neurons, what percentage of postsynaptic neurons to the projection neurons are still present? In other words, how does the postsynaptic nMLF output relate to the motor neurons? If, for instance, the nMLF (which, as the authors state, are likely still innervated by the projection neurons) are the main output of the projections neurons, then this would affect the interpretation of the results.

Reviewer #2 (Public Review):

Summary:

This study was designed to test the hypothesis that motor neurons play a causal role in circuit assembly of the vestibulo-ocular reflex circuit, which is based on the retrograde model proposed by Hans Straka. This circuit consists of peripheral sensory neurons, central projection neurons, and motor neurons. The authors hypothesize that loss of extraocular motor neurons, through CRISPR/Cas9 mutagenesis of the phox2a gene, will disrupt sensory selectivity in presynaptic projection neurons if the retrograde model is correct.

Account of the major strengths and weaknesses of the methods and results:

The work presented is impressive in both breadth and depth, including the experimental paradigms. Overall, the main results were that the loss of function paradigm to eliminate extraocular motor neurons did not 1) alter the normal functional connections between peripheral sensory neurons and central projection neurons, 2) affect the position of central projection neurons in the sensorimotor circuit, or 3) significantly alter the transcriptional profiles of central projection neurons. Together, these results strongly indicate that retrograde signals from motor neurons are not required for the development of the sensorimotor architecture of the vestibulo-ocular circuit.

Appraisal of whether the authors achieved their aims, and whether the results support their conclusions:

The results of this study showed that extraocular motor neurons were not required for central projection neuron specification in the vestibulo-ocular circuit, which countered the prevailing retrograde hypothesis proposed for circuit assembly. A concern is that the results presented may be limited to this specific circuit and may not be generalizable to other circuit assemblies, even to other sensorimotor circuits.

Discussion of the likely impact of the work on the field, and the utility of the methods and data to the community:

As mentioned above, this study sheds valuable new insights into the developmental organization of the vestibulo-ocular circuit. However, different circuits likely utilize various mechanisms, extrinsic or intrinsic (or both), to establish proper functional connectivity. So, the results shown here, although begin to explain the developmental organization of the vestibulo-ocular circuit, are not likely to be generalizable to other circuits; though this remains to be seen. At a minimum, this study provides a starting point for the examination of patterning of connections in this and other sensorimotor circuits.

Reviewer #3 (Public Review):

In this manuscript by Goldblatt et al. the authors study the development of a well-known sensorimotor system, the vestibulo-ocular reflex circuit, using Danio rerio as a model. The authors address whether motor neurons within this circuit are required to determine the identity, upstream connectivity and function of their presynaptic partners, central projection neurons. They approach this by generating a CRISPR-mediated knockout line for the transcription factor phox2a, which specifies the fate of extraocular muscle motor neurons. After showing that phox2a knockout ablates these motor neurons, the authors show that functionally, morphologically, and transcriptionally, projection neurons develop relatively normally.

Overall, the authors present a convincing argument for the dispensability of motor neurons in the wiring of this circuit, although their claims about the generalizability of their findings to other sensorimotor circuits should be tempered. The study is comprehensive and employs multiple methods to examine the function, connectivity and identity of projection neurons.

Specific comments:

(1) In the introduction the authors set up the controversy on whether or not motor neurons play an instructive role in determining "pre-motor fate". This statement is somewhat generic and a bit misleading as it is generally accepted that many aspects of interneuron identity are motor neuron-independent. The authors might want to expand on these studies and better define what they mean by "fate", as it is not clear whether the studies they are citing in support of this hypothesis actually make that claim.

(2) Although it appears unchanged from their images, the authors do not explicitly quantitate the number of total projection neurons in phox2a knockouts.

(3) For figures 2C and 3C, please report the proportion of neurons in each animal, either showing individual data points here or in a separate supplementary figure; and please perform and report the results of an appropriate statistical test.

(4) In the topographical mapping of calcium responses (figures 2D, E and 3D), the authors say they see no differences but this is hard to appreciate based on the 3D plotting of the data. Quantitating the strength of the responses across the 3-axes shown individually and including statistical analyses would help make this point, especially since the plots look somewhat qualitatively different.

(5) The transcriptional analysis is very interesting, however, it is not clear why it was performed at 72 hpf, while functional experiments were performed at 5 days. Is it possible that early aspects of projection neuron identity are preserved, while motor neuron-dependent changes occur later? The authors should better justify and discuss their choice of timepoint. The inclusion of heterozygotes as controls is problematic, given that the authors show there are notable differences between phox2a+/+ and phox2a+/- animals; pooling these two genotypes could potentially flatten differences between controls and phox2a-/-.

(6) Projection neurons appear to be topographically organized and this organization is maintained in the absence of motor neurons. Are there specific genes that delineate ventral and dorsal projection neurons? If so, the authors should look at those as candidate genes as they might be selectively involved in connectivity. Showing that generic synaptic markers (Figure 4E) are maintained in the entire population is not convincing evidence that these neurons would choose the correct synaptic partners.

eLife assessment

This is a fundamental study that addresses the key question of how the tetraspanin Tspan12 functions biochemically as a co-receptor for Norrin to initiate β-catenin signaling. The strength of the work lies in the rigorous and compelling binding analyses involving various purified receptors, co-receptors, and ligands, as well as molecular modeling by AlphaFold that was subsequently validated by an extensive series of mutagenesis experiments. The study advances the field by providing a novel mechanism of co-receptor function and shedding new light on how signaling specificity is achieved in the complex Wnt/Norrin signaling system.

Reviewer #1 (Public Review):

Though the Norrin protein is structurally unrelated to the Wnt ligands, it can activate the Wnt/β-catenin pathway by binding to the canonical Wnt receptors Fzd4 and Lrp5/6, as well as the tetraspanin Tspan12 co-receptor. Understanding the biochemical mechanisms by which Norrin engages Tspan12 to initiate signaling is important, as this pathway plays an important role in regulating retinal angiogenesis and maintaining the blood-retina-barrier. Numerous mutations in this signaling pathway have also been found in human patients with ocular diseases. The overarching goal of the study is to define the biochemical mechanisms by which Tspan12 mediates Norrin signaling. Using purified Tspan12 reconstituted in lipid nanodiscs, the authors conducted detailed binding experiments to document the direct, high-affinity interactions between purified Tspan12 and Norrin. To further model this binding event, they used AlphaFold to dock Norrin and Tspan12 and identified four putative binding sites. They went on to validate these sites through mutagenesis experiments. Using the information obtained from the AlphaFold modeling and through additional binding competition experiments, it was further demonstrated that Tspan12 and Fzd4 can bind Norrin simultaneously, but Tspan12 binding to Norrin is competitive with other known co-receptors, such as HSPGs and Lrp5/6. Collectively, the authors proposed that the main function of Tspan12 is to capture low concentrations of Norrin at the early stage of signaling, and then "hand over" Norrin to Fzd4 and Lrp5/6 for further signal propagation. Overall, the study is comprehensive and compelling, and the conclusions are well supported by the experimental and modeling data.

Strengths:

• Biochemical reconstitution of Tspan12 and Fzd4 in lipid nanodiscs is an elegant approach for testing the direct binding interaction between Norrin and its co-receptors. The proteins used for the study seem to be of high purity and quality.

• The various binding experiments presented throughout the study were carried out rigorously. In particular, BLI allows accurate measurement of equilibrium binding constants as well as on and off rates.

• It is nice to see that the authors followed up on their AlphaFold modeling with an extensive series of mutagenesis studies to experimentally validate the potential binding sites. This adds credence to the AlphaFold models.

• Table S1 is a further testament to the rigor of the study.

• Overall, the study is comprehensive and compelling, and the conclusions are well supported by the experimental and modeling data.

Suggestions for improvement:

• It would be helpful to show Coomassie-stained gels of the key mutant Norrin and Tspan12 proteins presented in Figures 2E and 2F.

• Many Norrin and Tspan12 mutations have been identified in human patients with FEVR. It would be interesting to comment on whether any of the mutations might affect the Norrin-Tspan12 binding sites described in this study.

• Some of the negative conclusions (e.g. the lack of involvement of Tspan12 in the formation of the Norrin-Lrp5/6-Fzd4-Dvl signaling complex) can be difficult to interpret. There are many possible reasons as to why certain biological effects are not recapitulated in a reconstitution experiment. For instance, the recombinant proteins used in the experiment may not be presented in the correct configurations, and certain biochemical modifications, such as phosphorylation, may also be missing.

Reviewer #2 (Public Review):

This is an interesting study of high quality with important and novel findings. Bruguera et al. report a biochemical and structural analysis of the Tspan12 co-receptor for norrin. Major findings are that Norrin directly binds Tspan12 with high affinity (this is consistent with a report on BioRxiv: Antibody Display of cell surface receptor Tetraspanin12 and SARS-CoV-2 spike protein) and a predicted structure of Tspan12 alone or in complex with Norrin. The Norrin/Tspan12 binding interface is largely verified by mutational analysis. An interaction of the Tspan12 large extracellular loop (LEL) with Fzd4 cannot be detected and interactions of full-length Tspan12 and Fzd4 cannot be tested using nano-disc based BLI, however, Fzd4/Tspan12 heterodimers can be purified and inserted into nanodiscs when aided by split GFP tags. An analysis of a potential composite binding site of a Fzd4/Tspan12 complex is somewhat inconclusive, as no major increase in affinity is detected for the complex compared to the individual components. A caveat to this data is that affinity measurements were performed for complexes with approximately 1 molecule Tspan12 and FZD4 per nanodisc, while the composite binding site could potentially be formed only in higher order complexes, e.g., 2:2 Fzd4/Tspan12 complexes. Interestingly, the authors find that the Norrin/Tspan12 binding site and the Norrin/Lrp6 binding site partially overlap and that the Lrp6 ectodomain competes with Tspan12 for Norrin binding. This result leads the authors to propose a model according to which Tspan12 captures Norrin and then has to "hand it off" to allow for Fzd4/Lrp6 formation. By increasing the local concentration of Norrin, Tspan12 would enhance the formation of the Fzd4/Lrp5 or Fzd4/Lrp6 complex.

The experiments based on membrane proteins inserted into nano-discs and the structure prediction using AlphaFold yield important new insights into a protein complex that has critical roles in normal CNS vascular biology, retinal vascular disease, and is a target for therapeutic intervention. However, it remains unclear how Norrin would be "handed off" from Tspan12 or Tspan12/Fzd4 complexes to Fzd4/Lrp6 complexes, as the relatively high affinity of Norrin to Fzd4/Tspan12 dimers likely does not favor the "handing off" to Fzd4/Lrp6 complexes.

Areas that would benefit from further experiments, or a discussion, include:

- The authors test a potential composite binding site of Fzd4/Tspan12 heterodimers for norrin using nanodiscs that contain on average about 1 molecule Fzd4 and 1 molecule Tspan12. The Fzd4/Tspan12 heterodimer is co-inserted into the nanodiscs supported by split-GFP tags on Fzd4 and Tspan12. The authors find no major increase in affinity, although they find changes to the Hill slope, reflecting better binding of norrin at low norrin concentrations. In 293F cells overexpressing Fzd4 and Tspan12 (which may result in a different stoichiometry) they find more pronounced effects of norrin binding to Fzd4/Tspan12. This raises the possibility that the formation of a composite binding requires Fzd4/Tspan12 complexes of higher order, for example, 2:2 Fzd4/Tspan12 complexes, where the composite binding site may involve residues of each Fzd4 and Tspan12 molecule in the complex. This could be tested in nanodiscs in which Fzd4 and Tspan12 are inserted at higher concentrations or using Fzd4 and Tspan12 that contain additional tags for oligomerization.

- While Tspan12 LEL does not bind to Fzd4, the successful reconstitution of GFP from Tspan12 and Fzd4 tagged with split GFP components provides evidence for Fzd4/Tspan12 complex formation. As a negative control, e.g., Fzd5, or Tspan11 with split GFP tags (Fzd5/Tspan12 or Fzd4/Tspan11) would clarify if FZD4/Tspan12 heterodimers are an artefact of the split GFP system.

- Fzd4/Tspan12 heterodimers stabilized by split GFP may be locked into an unfavorable orientation that does not allow for the formation of a composite binding site of FZD4 and Tspan12, this is another caveat for the interpretation that Fzd4/Tspan12 do not form a composite binding site. This is not discussed.

- Mutations that affect the affinity of norrin/fzd4 are not used to further test if Fzd4 and Tspan12 form a composite binding site. Norrin R41E or Fzd4 M105V were previously reported to reduce norrin/frizzled4 interactions and signaling, and both interaction and signaling were restored by Tspan12 (Lai et al. 2017). Whether a Fzd4/Tspan12 heterodimer has increased affinity for Norrin R41E was not tested. Similarly, affinity of FZD4 M105V vs a Fzd4 M105V/Tspan12 heterodimer were not tested.

- An important conclusion of the study is that Tspan12 or Lrp6 binding to Norrin is mutually exclusive. This could be corroborated by an experiment in which LRP5/6 is inserted into nanodiscs for BLI binding tests with Norrin, or Tspan12 LEL, or a combination of both. Soluble LRP6 may remove norrin from equilibrium binding/unbinding to Tspan12, therefore presenting LRP6 in a non-soluble form may yield different results.

- The authors use LRP6 instead of LRP5 for their experiments. Tspan12 is less effective in increasing the Norrin/Fzd4/Lrp6 signaling amplitude compared to Norrin/Fzd4/Lrp5 signaling, and human genetic evidence (FEVR) implicates LRP5, not LRP6, in Norrin/Frizzled4 signaling. The authors find that Norrin binding to LRP6 and Tspan12 is mutually exclusive, however this may not be the case for Lrp5.

- The biochemical data are largely not correlated with functional data. The authors suggest that the Norrin R115L FEVR mutation could be due to reduced norrin binding to tspan12, but do not test if Tspan12-mediated enhancement of the norrin signaling amplitude is reduced by the R115L mutation. Similarly, the impressive restoration of binding by charge reversal mutations in site 3 is not corroborated in signaling assays.

Reviewer #3 (Public Review):

Brugeuera et al present an impressive series of biochemical experiments that address the question of how Tspan12 acts to promote signaling by Norrin, a highly divergent TGF-beta family member that serves as a ligand for Fzd4 and Lrp5/6 to promote canonical Wnt signaling during CNS (and especially retinal) vascular development. The present study is distinguished from those of the past 15 years by its quantitative precision and its high-quality analyses of concentration dependencies, its use of well-characterized nano-disc-incorporated membrane proteins and various soluble binding partners, and its use of structure prediction (by AlphaFold) to guide experiments. The authors start by measuring the binding affinity of Norrin to Tspan12 in nanodiscs (~10 nM), and they then model this interaction with AlphaFold and test the predicted interface with various charge and size swap mutations. The test suggests that the prediction is approximately correct, but in one region (site 1) the experimental data do not support the model. [As noted by the authors, a failure of swap mutations to support a docking model is open to various interpretations. As AlphFold docking predictions come increasingly into common use, the compendium of mutational tests and their interpretations will become an important object of study.] Next, the authors show that Tspan12 and Fzd4 can simultaneously bind Norrin, with modest negative cooperativity, and that together they enhance Norrin capture by cells expressing both Tspan12 and Fzd4 compared to Fzd4 alone, an effect that is most pronounced at low Norrin concentration. Similarly, at low Norrin concentration (~1 nM), signaling is substantially enhanced by Tspan12. By contrast, the authors show that LRP6 competes with Tspan12 for Norrin binding, implying a hand-off of Norrin from a Tspan12+Fzd4+Norrin complex to a LRP5/6+Fzd4+Norrin complex. Thanks to the authors' careful dose-response analyses, they observed that Norrin-induced signaling and Tspan12 enhancement of signaling both have bell-shaped dose-response curves, with strong inhibition at higher levels of Norrin or Tspan12. The implication is that the signaling system has been built for optimal detection of low concentrations of Norrin (most likely the situation in vivo), and that excess Tspan12 can titrate Norrin at the expense of LRP5/6 binding (i.e., reduction in the formation of the LRP5/6+Fzd4+Norrin signaling complex). In the view of this reviewer, the present work represents a foundational advance in understanding Norrin signaling and the role of Tspan12. It will also serve as an important point of comparison for thinking about signaling complexes in other ligand-receptor systems.

Catch Me If You Can is one of my favorite shows. The main character, Frank, is really good at disguising and pretending to be people. He was able to fool many professionals, and he was able to scam many stores and banks with the fake checks that we made. At last, he turned himself in because he was lonely and called the police, who had been chasing him for years. The story ended with a good ending as he was hired by the government to be a fraud detector.

1. Редис как элемент, для синхронизаций кэша на большом количестве серверов, чтоб пользователь не кидался на разные сервисы, и каждый раз не кэшировал данные с одного и тоже же запроса, но с разных серверов.

2.

There are many incentives for social media companies to violate privacy. The obvious one is social media earns most of its revenue through ads. If social media companies know what their users like and promote ads, they would most likely buy, which would boost the advertising companies' sales, encouraging companies to put ads on social media platforms.

What is this assumption based on?

For an early silo patient who has randomisation revelead for all domains but receives non-randomised DAIR and no rifampicin?

DaVinci 软件的功能

"pipeline"一词指的是一个有序的、结构化的流程或步骤，用于处理数据并进行分析。它描述了从获取数据和模拟样本开始，到执行各种分析步骤，最终得出结果的一系列连贯的操作。在科研或数据分析的上下文中，"procedure pipeline"或简称为"pipeline"常用来指这样的流程。

This quotation emphasizes how deeply slavery has impacted racial identity formation and society beliefs. The idea that the justification of slavery came from making the enslaved seem like children emphasizes the dehumanizing ideas that were employed to support the system. According to the remark, marriage was a way for people to demonstrate their agency and maturity in a system that denied them both, by portraying it as a journey into adulthood for both themselves and their race. It also suggests how the larger story of racial advancement was entwined with personal stories, highlighting the group's fight for acceptance and equality. This viewpoint emphasizes how intricately intimate connections and larger social dynamics interact when racialized oppression is present.

Is very interesting to know that Piaget stages are similar to the Montessori method like for example : “ practical life” and “ sensory area “ are designated to potential fine motor skills , grosor skills and cognitive development in which consists that the child can manipulate or build blocks or transport objects to another tray . Sounds pretty simple but everything had a purpose .

the ordinary depends on the political and the gender of said person living in the present. can something actually be ordinary to everyone? or must we always look at the external forces that drive the "ordinary" moment in question.

perhaps the word "ordinary" cannot be universally understood. it is dependent on perspective and subject position - it depends on the person, location, time, etc.

Referring to a targeted space over a period of time. In the context of the study, it emphasizes the importance of both the timing and location of nerve cooling for managing neuropathic pain.

Spared nerve injury is a type of nerve injury model used in research to simulate neuropathic pain conditions. Two of the three sciatic nerves are specifically targeted and injured (peroneal and tibial nerves), while the third nerve, the sural nerve, remains intact. This allows researchers to study neuropathic pain mechanisms and test potential treatments in animals.

Combined electrical activity generated by a group of nerve fibers when they are stimulated together.

Describes the sharp temperature contrast between the actively cooled regions of the cuff, which directly contact the nerve tissue, and the passive regions that do not. This indicates effective localized cooling, with the actively cooled areas being significantly cooler than the passive ones.

DOI: 10.1016/j.celrep.2021.108889

Resource: (Jackson ImmunoResearch Labs Cat# 703-165-155, RRID:AB_2340363)

Curator: @Naa003

SciCrunch record: RRID:AB_2340363

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DOI: 10.1016/j.celrep.2021.108883

Resource: (Sigma-Aldrich Cat# T9026, RRID:AB_477593)

Curator: @Naa003

SciCrunch record: RRID:AB_477593

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What is this?

DOI: 10.1016/j.molcel.2024.03.017

Resource: R Project for Statistical Computing (RRID:SCR_001905)

Curator: @abever99

SciCrunch record: RRID:SCR_001905

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What is this?