- Mar 2024
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1. General Statements [optional]
We would like to thank all three reviewers for their careful and comprehensive reviews of our manuscript. We have taken on board all the comments and have made appropriate changes to improve the manuscript. The more substantive changes are to the structuring of the text in Introduction section, and to improving the clarity of Figure 2 after reviewers’ comments (we have added extra panels to A, F and G). Other minor changes are individually signposted in each paragraph of the point-by-point response attached below.
We performed a number of pieces of additional analysis to address reviewer comments. To be as transparent as possible we make these and all other data analyses available in the form of .html files exported by Rmarkdown, hosted at https://joebowness.github.io/YY1-XCI-analysis/.
2. Point-by-point description of the revisions
This section is mandatory. *Please insert a point-by-point reply describing the revisions that were already carried out and included in the transferred manuscript. *
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Reviewer #1 (Evidence, reproducibility and clarity (Required)):
Summary: This manuscript uses differentiation of the highly informative inter-specific hybrid mouse ESC to follow features of genes that inactivate slowly. Resistance to silencing is reflected in reduced change in chromatin accessibility and the authors identify YY1 and CTCF as enriched amongst these 'slow' genes. This finding is provocative as these factors have been reported to enrich at both human and mouse escape genes. The authors go on to demonstrate that eviction of YY1 is slowly evicted from the X, and that removal of YY1 increases silencing.
Minor Comments: Overall, the manuscript's conclusions are well supported; however, the brevity of the presentation in some places made it difficult to follow, and in other places seemed a missed opportunity to more fully examine or present their data.
- Introduction is only 2 paragraphs and half of the last is their new findings. First part of results/discussion is then forced to be very introductory. In addition, some discussion of escapees, even if predominantly human, seems warranted in the introduction. There are multiple studies that have tried to identify features enriched at genes that escape inactivation that could be mentioned.
We have now written the introduction as 3 paragraphs instead of 2. In doing this, we have moved the sentence introducing chromatin accessibility from the results section to the introduction. Additionally, we now discuss the studies that focus on escapees (in mouse XCI) in the second introduction paragraph.
Variation in silencing rates. 'Comparable rankings' cites multiple studies (oddly previous sentence cites only two) - how concurrent are they? Developing this further (perhaps a supplementary table) would inform whether the genes assessed are ones that routinely behave similarly across different studies/lines; and also serve as a resource for future studies.
To avoid double-citing, we have made this one sentence and have cited at the end of the sentence 7 studies which describe gene-by-gene variability in rates of silencing. The majority of these studies include comparisons of their categories of fast and slow-silencing gene with previous classifications, and they all conclude that there is substantial concurrence. Some examples:
- Marks et al, 2015, Table S3,
- Loda et al, 2017, Figure 5,
- Barros de Andrade E Sousa et al. 2019, Figure 2
- Pacini et al. 2021, Figure 6e,i We believe this is sufficient evidence for our claim that these studies report “comparable categories” (“ranking” changed to “categories” as not all studies strictly rank). A comprehensive gene-by-gene comparison table would likely serve only to highlight differences due the various silencing assays/model systems/classification approaches used in the studies. If required, however, we would be willing to include a supplemental table which collates where gene silencing categories are discussed in each publication, and links to any supplemental files which provide full lists of X-linked genes.
It would be helpful to give insight into informativity of cross - what proportion of ATAC-seq peaks were informative with allelic information (and similarly, what proportion of genes expressed had allelic information?
Of the 2042 consensus ATAC-seq peaks we defined on ChrX via aggregating macs2 peaks over all time course samples, n = 821 passed our initial criteria for allelic analysis in the iXist-ChrX-Dom model line (ie they are proximal to the Xist locus in ChrX 0-103Mb, overlap SNPs, and contain sufficient allelic reads). A small number of peaks were additionally filtered out during fitting of the exponential decay model, leaving a final ATAC-seq peak set of n = 790 elements (38.6%) which we focus on in this study. We have added this information to the text (first Results paragraph).
Our collections of ChrX genes amenable to allelic analysis were not redefined for this study. We used lists of genes defined in our previous ChrRNA-seq study (10.1016/j.celrep.2022.110830). In general, allelic analysis of gene expression is not as limited by the frequency of SNPs, because the sequence length of transcripts (including introns, which are a significant fraction of the reads in ChrRNA-seq data) is much greater than for ATAC-seq peaks. Only a few very lowly expressed genes are not amenable to allelic ChrRNA-seq analysis.
P5: "can be influenced by Xist RNA via a variety of mechanisms" seems like it this sweeping statement could use expansion, or at least a reference. Authors could also clarify that 'distal elements assigned by linear genomic proximity is their definition of nearest gene.
The statement that “both [chromatin accessibility and gene expression] can be influenced by Xist RNA via a variety of mechanisms” is intentionally broad to support a negative argument that we do not wish to mechanistically over-interpret the observation that Xi chromatin accessibility loss occurs slower than gene silencing. Nonetheless, we have added two references to studies which report mechanisms for how Xist may influence chromatin accessibility; via recruiting PRC1 (Pintacuda et al 2017) or antagonising BRG1 (Jegu et al 2019). That multiple molecular pathways simultaneously contribute towards the effect of Xist RNA on gene silencing is well established in the field (see reviews such as Brockdorff et al 2020, Boeren et al 2021, Loda et al 2022).
We have clarified in the text that our definition of “distal” is all REs which do not overlap with promoter regions (TSS+/-500bp). We have also made it clearer that our definition of “nearest” gene refers to linear genomic proximity in both the Results and Methods sections.
Figure S1 - there are 6-8 other regions that fail to become monoallelic - what are they?
The regions which stand out most by the colour scheme of the heatmap in Figure S1 are those where accessibility increases on Xi, most notably the loci of Firre, Dxz4 and Xist, which are known to have unique features related to the 3D superstructure of the inactive X chromosome. A few other regions which do not become monoallelic harbour classic “escapee” genes. We have now labelled the locations of escapees Ddx3x, Slc25a5 and Eif2s3x in FigS1.
The other regions noticeable in the heatmap have no obvious features which explain why they fail to become monoallelic. We have highlighted a region containing intragenic peaks within Bcor (a gene which is silenced in iXist-ChrX mESCs), but many other regions are not in the vicinity of genes. Some of the persistently Xi-accessible peaks within these regions contain strong YY1 or CTCF sites, although many others do not.
It is also possible that some Xi-accessible peaks are artefacts of mismatches between the Castaneous or Domesticus/129Sv strain SNP databases and ground truth iXist-ChrX genome sequence. The number of these cases are small, and if a misannotated SNP is the only SNP present in a single peak, the peak is discarded by our allelic filtering criteria as it will appear monoallelic in uninduced mESCs.
Is there any correlation between silencing speed and expression (as previously reported)? If yes, then is there also a correlation with YY1 presence - and is this correlation greater than or less than seen on autosomes?
The data we present here pertaining to gene silencing kinetics is reused from our previous study. In that work we did indeed observe a significant association between silencing rate and initial gene expression levels (10.1016/j.celrep.2022.110830, Supplemental Information Figure S5F), which has also been reported by multiple groups previously.
To correlate YY1 binding with gene expression levels, we calculated transcripts per million (TPM) for all genes from our genome-wide mRNA-seq data of uninduced iXist-ChrX-Dom cells (GSE185869). It is indeed true that, on average, X-linked genes classified as “direct” YY1-targets in our analysis have higher levels of initial expression (median TPM 70.8, n=64) compared to non-target genes (median TPM 30.7, n=346). Autosomal YY1 targets are also relatively higher expressed (median TPM 29.6, n=1882) than non-YY1 genes (median TPM 8.0, n=9983). Within the list of YY1-targets, there is no additional correlation between quantitative levels of YY1 ChIP enrichment (calculated in this study using BAMscale (Pongor et al, 2020)) and gene expression (R=-0.05, Spearman correlation).
Therefore, we appreciate that this correlation between YY1-binding and gene expression levels may be a covariate in the correlation we report in this study between YY1-target genes and slow-silencing. This does not invalidate a potential functional role for YY1 in impeding silencing, as it could affect both variables via common or distinct mechanisms. Nevertheless, in an attempt to account for initial expression level as a covariate, we compared the silencing halftimes of YY1-targets versus non-targets within genes grouped by similar expression levels (low, medium and high-expressed genes). YY1-targets have slower halftimes in each comparison, and this difference is highly significant (p=1.9e-05, Wilcoxon test) for the “medium-expressed” gene group. This implies that YY1 contributes towards slower gene silencing kinetics independently of initial gene expression levels. We have added this panel to Fig2 with an associated sentence in the Results section.
These new analyses are also appended to the documentation of the R scripts used to generate the main figures in this study (Figure2_YY1association.Rmd), which will all be published to Github.
It is also important to note that this analysis approach is complicated by the methodology we use to classify YY1 target genes. In this study, we define YY1 targets based on the presence of ChIP-seq peaks overlapping the gene promoters, which is reasonable and widely accepted practice when defining targets of transcription factors. However, as briefly discussed in the Methods, in YY1 ChIP-seq data samples with very high signal:noise (eg Fig3), minor peaks of YY1 enrichment can be detected at almost every active promoter. As enrichment at these peaks is typically much less than at peaks with occurrences of the YY1 consensus DNA motif, we hypothesise that these small peaks result from secondary YY1 cofactors enriched at promoters (eg P300, BAF, Mediator) rather than direct sites of binding to DNA/chromatin. Therefore, for annotating genes as “direct” YY1 targets, we chose to use the YY1 peak set defined from lower signal:noise ChIP-seq data in iXist-ChrX produced with the endogenous YY1 Ab. Nevertheless, this behaviour is likely to confound any analysis correlating YY1 ChIP binding with gene expression.
Figure 2: Have the authors considered using quartiles rather than an arbitrary division into depleted and persistent?
We primarily chose this binary classification of REs as either Xi-“persistent” or Xi-“depleted” to maximise the numbers of sequences that could be used in each group as input for the HOMER motif enrichment software.
It is also not trivial to separate REs into quartiles because our “Xi-persistent” classification includes peaks defined as “biallelically accessible in NPCs”, as well as peaks with slow accessibility halftimes. This is explained in both the Results and Methods but we now have edited Fig2A to make it clearer. Instead of quartiles, we have performed an analysis which keeps “biallelically accessible REs” as a separate category and subdivides the remaining peaks into three groups by halftimes (slow, intermediate and fast accessibility loss). The same trends are evident with this four-category approach as with the two-category approach.
Importantly, our follow-up analyses which confirm the association between YY1 binding and slow Xi accessibility loss (Fig2E) and slow silencing (Fig 2F-H) are independent from categorisations of REs which rely on arbitrary thresholds.
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Could simplify secondary labels to solely YY1 and CTCF. D & F do not print in black and white. Overall the mESC versus NPC can be confusing, perhaps mESC (no diff) would be helpful?
We have simplified the secondary labels in Fig2B and modified the colour scheme of FIg2D and Fig2F as suggested. “mESC” is now modified to “mESC no diff” in Fig2H, FigS2B, Fig3C and Fig3E to reduce the potential for confusion.
The numbers appear to suggest YY1 is generally enriched on X, but not at promoters?? Is this true?
The explanation for this is that clear peaks of YY1 ChIP are found at young LINE1 elements in iXist-ChrX mESCs (specifically over L1Md_T subfamilies). These elements are highly enriched (>2-fold) on the mouse X chromosome compared to autosomes (Waterston 2002), and the majority are not promoter-associated. We chose not to include a discussion of YY1 enrichment at repetitive LINE1 elements in this study primarily because of a) issues related to multiple-mapping reads, such as difficulties distinguishing ChrX vs autosomal reads, and b) the absence of strain-specific SNPs within annotated ChrX L1Md_Ts means that none of these elements are amenable to allelic analysis so we cannot compare Xi versus Xa. However, these LINE1 peaks are a significant fraction (262/521) of the numbers of YY1 ChIP-seq peaks in Fig2C.
For Figure 2f, it might be helpful to show autosomal genes - are Fast depleted or Slow enriched for YY1 relative to autosomes?
We have calculated these numbers as part of the analysis of gene expression on ChrX and autosomes above. Overall, the fraction of genes defined as YY1-targets is the same on ChrX as on autosomes (~0.16). Accordingly, fast-silencing genes are depleted for YY1 compared to autosomes, whereas slow-silencing genes are enriched for YY1 compared to autosomes. Fig2F is now redesigned to include the total numbers of YY1-target genes on ChrX and autosomes.
More generally, is YY1 binding on the X lost more slowly than YY1 binding on autosomes, or is the slow loss a feature of YY1. While I agree YY1 could have direct up or down-regulatory roles, Figure S3 could also be reflecting a secondary impact.
We agree that many of the differentially regulated genes after 52 hours of YY1 degradation could be secondary effects and have added a sentence on this to the relevant paragraph in the text.
Figure 3, 4 and supplementary - the chromosome cartoon introduces the LOH in iXist, but this needs to be described in text. Describing the reciprocal as a biological replicate seems challenging given this LOH.
It is true that the reciprocal lines iXist-ChrX-Dom and iXist-ChrX-Cast are not true biological replicates, and we try to avoid referring to them as such. Writing this in the legend of Fig3 was an error which we have corrected. We have now also mentioned the recombination event in the iXist-ChrX-Dom cell line at the point where data from this line is first discussed (paragraph 1 of Results section).
For the latter parts this work (Figs 3 and 4), we made the conscious decision to proceed with two YY1-FKP12F36V cell lines from different reciprocal iXist-ChrX backgrounds (aF1 in iXist-ChrX-Dom, cC3 in iXist-ChrX-Cast), rather than “biological replicate” clones from either iXist-ChrX-Dom or iXist-ChrX-Cast. Our reasoning was to control against potential confounding effects of strain background on our experiments related to the role of YY1. Although there were some minor differences between the clones, aF1 and cC3 demonstrated essentially equivalent phenotypes in all analyses we performed.
Could a panel of TFs be used rather than OCT4 which has its own unique properties to emphasize that YY1 is unique?
This would indeed be worthwhile, and we did consider attempting to perform ChIP-seq for additional TFs other than OCT4 in order to collect more points of comparison for the slow rate of loss of YY1 binding to Xi. However, it is admittedly hard to identify appropriate candidate TFs in mESCs which a) have similar numbers of discrete peaks of binding in promoters and distal elements on ChrX and b) it is possible to reliably perform ChIP-seq for at sufficiently high signal:noise to allow for quantitative allelic analysis.
We have changed the text to acknowledge that our comparison only to OCT4 limits the scope of the statements we can make about unique properties of YY1 binding.
Figure 4 - by examining 'late' genes, a change in allelic ratio is observed, but what about escape genes (e.g. Kdm5c, Kdm6a)? Do they now become silent? It would be helpful to have all this data as a supplementary table so people could query their 'favourite' gene.
YY1 degradation experiments performed for Figure 4 were performed on mESCs without cellular differentiation (YY1-ablated cells do not survive in our mESC to NPC differentiation protocol). In undifferentiated mESCs, silencing of the inactive X does not reach completion, and in fact all X-linked genes are residually expressed at a higher level than in equivalent timepoints of Xist induction with NPC differentiation (see Figure 4D, Bowness et al 2022). We write in the text “slow-silencing genes are residually expressed from Xi” because genes of this category account for the majority of expression under these conditions, and indeed almost all slow genes would all be classed as “escape genes” in this setting by a conventional definition of >10% residual expression from Xi (see also Figure 4D, Bowness et al 2022). Our analysis in Fig4D (of this study) includes all genes, and we share processed .txt files of allelic ratio and allelic fold changes in GEO, so querying the behaviour of a favourite gene would be easy (GSE240680).
Incidentally, when we do perform NPC differentiation of iXist-ChrX NPC, at late stages very few genes show any expression from Xi (Ddx3x, Slc25a5, Eif2s3x and Kdm5c clearly escape, but even Kdm6a is entirely silenced). Unfortunately, with such a small number of “super” escapees it is hard to make any general conclusions, so in this study we can only make inferences about escape via the transitive property that many “slow-silencing” genes are facultative escapees in other settings without induced Xist overexpression. We now write about this consideration in the introduction and final paragraph of the main text.
It seems surprising that loss of YY1 has no demonstrative impact on the Xa. Figure S3B suggests that over 1000 genes are significantly impacted - primarily down regulated. How many of those are X-linked? Perhaps they could be colored differently?
For the broad-brush differential expression testing in FigS3B, we use all the ChrRNA-seq samples (6 x untreated, 6 x dTAG) as “pseudo-replicates”, disregarding any confounding effects related to induced Xist-silencing as effecting untreated and dTAG sample groups equivalently. We did specifically investigate the behaviour of X-linked genes in this volcano plot, however only a very small number of genes were differentially expressed (n=22 X-linked genes appeared significantly downregulated compared to n=4 genes upregulated). This can be seen in our analysis records uploaded to Github.
Additionally, there is actually a minor effect of YY1 loss on expression of YY1-target genes on Xa. This can be seen in Fig4F, where the median lines of YY1-target boxes lie below the horizontal line of 0-fold change.
Since XIST+/undifferentiated cells retain YY1, is YY1 binding sensitive to DNAme? Indeed, are X chromosome bound sites in islands that become methylated? Figure S4 shows YY1-targetted X genes in SMCHD1 knockout; can CTCF targets also be shown? While identified in Figure 2, CTCF was not examined the way YY1 was, although it has also been identified in somatic studies of genes that escape X inactivation.
Binding of YY1 is indeed sensitive to DNA methylation; specifically it is reported to be blocked by CpG methylation (see refs (Kim et al, 2003; Makhlouf et al, 2014; Fang et al, 2019). Thus, crosstalk with the DNA methylation pathways, which deposit de novo CpG island methylation as a late event of XCI (Lock 1987, Gendrel 2012), did appeal to us as a potential mechanism of YY1 “eviction”. However, preliminary analysis we performed to investigate this revealed limited overlap between YY1 binding sites and de novo meythlated CpG islands in the iXist-ChrX model cell line.
FigS4 presents ATAC-seq data from two iXist-ChrX SmcHD1 KO clonal cell lines, comparing the accessibility loss kinetics between YY1-binding and non-YY1 REs in these cells.
Although FigS4 in this paper does not show genes, we have previously published ChrRNA-seq data from these SmcHD1 KO lines over a similar Xist induction + NPC differentiation time course (Figure 6, Bowness et al, 2022). A reanalysis of this ChrRNA-seq data by YY1-target vs non-target genes shows a similar trend to the accessibility data, although this is expected from the strong overlap of both “YY1-target” and “SmcHD1-dependent” genes with slow-silencing genes in our model.
With respect to CTCF, we have performed a similar analysis of this data separating ATAC-seq peaks by CTCF-binding rather than YY1-binding. This shows a similar trend to YY1, but is overall less pronounced, and is now included in our analysis records. We have reported previously that loss of CTCF from many binding sites on Xi requires SmcHD1 (Gdula et al, 2019).
When the authors use cf. do they simply mean see also, or as wikipedia suggests: "the cited source supports a different claim (proposition) than the one just made, that it is worthwhile to compare the two claims and assess the difference". Perhaps it would be worth spelling out to clarify for the audience.
We used “cf.” in the text to mean “compare with”, when referring to a plot/observation/piece of data outside of the figure being immediately discussed (either in another study or different section of the paper). We were not aware of the recommendation to only use the cf abbreviation when the two items are intended to be contrasted. We do not believe this to be a universal grammatical convention, but nevertheless have changed incidences of cf. to “see also”.
Reviewer #1 (Significance (Required)):
General assessment: An important question in human biology is how much the sex chromosome contributes to sex differences in disease frequency. Genes that escape X inactivation in humans seem to have considerable impact on gene expression genome-wide. While there are not as many genes in mouse that escape inactivation, the use of the mESC cell differentiation approach allows detailed assessment of the timing of silencing during inactivation. The authors utilize an inter-specific cross and it would be interesting to know the limitations of such a system (in terms of informative DHS/genes that are informative).
Advance: As the authors note, there are multiple studies of similar systems that have revealed differences in the speeds of silencing of genes. However, this is the first study to my knowledge that has then tried to assess timing with gene-specific factors. There are multiple studies in humans comparing escape and subject genes for TFs, but lacking the developmental timing that this study incorporates.
Audience: While generally applicable to a basic research audience interested in gene regulation, the applicability to human genes that escape inactivation may interest cancer researchers or clinical audiences interested in sex differences.
Reviewer #2 (Evidence, reproducibility and clarity (Required)):
The authors studied the molecular basis of a variation in the rate of individual gene silencing on the X undergoing inactivation. They took advantage of ATAC-seq to observe the kinetics of chromatin accessibility along the inactive X upon induction of Xist expression in mESCs. They demonstrated a clear correspondence between the decrease in chromatin accessibility and the silencing of nearby genes. Furthermore, they found that persistently accessible regulatory elements and slow-silencing were associated with binding of YY1. YY1 tended to associate longer with genes that required more time to be silenced than those that became silenced fast on the inactive X during XCI. The acute loss of YY1 facilitated silencing of slow genes in a shorter period. They suggest that whether or not the transcription factors stay associated longer is another factor that impacts the variation in the rate of gene silencing on the Xi.
Reviewer #2 (Significance (Required)):
It has been suggested that the rate of gene silencing during XCI is varies depending on the distance of individual genes from the Xist locus or the entry site of Xist RNA on the X, as well as their initial expression levels before silencing. This study provides another perspective on this issue. The persistent association of transcription factors during XCI affects the rate of gene silencing. Although the issued addressed here might draw attention from only the limited fields of specialists, their finding advances our understanding of how the efficiency of silencing is controlled during the process of XCI. The experimental data essentially support their conclusion, and the manuscript was easy to follow. However, I still have some comments, which I would like the authors to consider before further consideration.
Major concerns 1. Based on the results shown in Figure 3E and F, the authors concluded that YY1 was more resistant than other TFs against the eviction from the X upon Xist induction. I am not still convinced with this. YY1 binds DNA via the zinc finger domain, while Oct4 binds DNA via the homeodomain. The difference in the binding module between them might affect their dissociation or the response to Xist RNA-mediated chromatin changes. In addition, given that YY1 has been reported to bind RNA, including Xist, as well, Oct4 might not be a good TF to compare.
We acknowledge and agree that our singular comparison between YY1 and OCT4 is insufficient to support a general conclusion that YY1 is unique with respect to its binding properties on Xi. This was also alluded to by Reviewer #1 (see 10.), where in response we write about the difficulties of selecting other appropriate/feasible candidate TFs for ChIP-seq in order to widen the comparison beyond OCT4. In consideration of this concern, we have re-phrased our conclusions regarding this point in the text, both at the point where it is first presented (Fig3F) and in the first discussion paragraph.
Furthermore, the difference in allelic ratio change between YY1 and OCT4 is admittedly not dramatic, and this metric can be influenced somewhat by the properties of the sets of peaks used (which is also why we have not tried to add statistical significance to this comparison in Fig3F). In order to make the comparison with OCT4 (a classic pluripotency factor), we were also limited to using mESC culture without differentiation conditions. It is possible that more pronounced differences between YY1 and other TFs would be observed under conditions where XCI is able to proceed further.
Even so, we contend that our observation that YY1 binding is lost from the Xi relatively slowly likely stands without a requirement for a comparison with OCT4 or other transcription factors. The decrease in allelic ratio for YY1 ChIP occurs more slowly than overall loss of chromatin accessibility from REs, which is arguably a more general proxy for TF binding, and much slower than kinetics of gene silencing (Fig3D and FigS2C). In addition, no other TF motifs (except CTCF, which has its own unique properties) were found significantly enriched within persistently-accessible REs, which would be an expectation if a different factor had similar properties of late-retained Xi binding as YY1.
Thus, overall we have tried to write the paper without overstating in isolation the importance of our claim that YY1 binding on Xi is relatively resistant to Xist-mediated inactivation, instead emphasising that it should be considered alongside the other pieces of data in the study.
I don't think that Kinetics of YY1 eviction upon Xist induction in SmcHD1 KO cells during NSC differentiation fit the phenotype of Smchd1mutant cells. Although their previous study by Bowness et al (2022) showed that Smchd1-KO cells fail to establish complete silencing of SmcHD1-dependnet genes, their silencing still reached rather appreciable levels according to Figure 6 of Bowness et al (2022). This is, in fact, consistent with the idea that XCI initially takes place in the mutant embryos, at least to an extent that does not compromise early postimplantation development. On the other hand, a significant portion of YY1 appears to remain associated with the target genes on both active and inactive X (Figure S4), which I think suggests that the presence of YY1 is compatible with silencing of SmdHD1-dependent genes. This is contradictory to the proposed role of YY1 that sustains the expression of X-linked genes in this context.
At any given timepoint of XCI, our data sets of gene silencing (ChrRNA-seq) consistently show a more pronounced allelic skew compared to chromatin accessibility (ATAC-seq). This behaviour is discussed in relation to Figure 1 in the text (see Results paragraph 2). We do not wish to overinterpret this quantitative difference because the assays are technically different and accessibility is not linearly correlated with gene expression. With this in consideration, we interpret the ATAC-seq data presented in Figure S4 to be fully consistent with the iXist-ChrX SmcHD1 KO ChrRNA-seq data in Figure 6 of our previous publication ie. a small increase in residual Xi gene expression from SmcHD1 KO NPCs is accompanied by a more appreciable increase in residual Xi chromatin accessibility. In line with this, it would not be contradictory for substantially increased Xi YY1 binding to sustain a quantitively small (but nonetheless meaningful) increase in residual gene expression from Xi.
Additionally, the context in which we include this SmcHD1 KO ATAC-seq data in the current paper is to hypothesise a potential role for SmcHD1 in contributing towards the eventual removal of YY1 binding from Xi. This hypothesis is essentially based on two observations; 1.) There is substantially more residual YY1 binding to Xi in mESC no diff conditions (Figure 3) and 2.) One difference between no diff and diff conditions is absence of SmcHD1 recruitment in the former (Figure 5 in our previous study). The new SmcHD1 KO ATAC-seq data adds a third observation which supports the hypothesis - that YY1-bound REs are appreciably more accessible from Xi in SmcHD1 KO. However, none of these observations are direct evidence of a link between SmcHD1 and YY1, and more experiments would be required to substantiate this potential mechanism. If confirmed, it would be logically reasonable to suggest a role for YY1 in contributing towards the residual expression of X-linked in the context of SmcHD1 KO, but we do not yet claim this, and a potential link with SmcHD1 KO is not the main focus of the paper.
Reviewer #3 (Evidence, reproducibility and clarity (Required)):
In this manuscript, Bowness and colleagues describe the interesting finding that the transcription factor YY1 is associated with slow silencing genes in induced X-Chromosome Inactivation (XCI). The authors have conducted a comprehensive characterization of X-linked gene silencing and the loss of chromatin accessibility of regulatory elements in induced XCI in ESCs and during NPC differentiation. X-linked gene silencing was classified into four categories, ranging from fast-silenced genes to genes that escape silencing. Motif enrichment analysis of regulatory elements associated with slowly silenced genes identified YY1 as the transcription factor most significantly enriched. The separation of YY1-target and non-target genes confirmed that most genes bound by YY1 indeed exhibit slower silencing kinetics. A comparison of the binding kinetics of YY1 to another transcription factor, OCT4, during XCI revealed that YY1 is evicted more slowly compared to OCT4 on the inactive X, suggesting that slower eviction is a unique property of YY1. Conditional knock-outs of YY1 using protein degradation during induced XCI in mESCs demonstrated that the loss of YY1 at target genes enhances silencing. This supports the hypothesis that YY1 serves as a crucial barrier for slow-silenced genes during XCI. Finally, the authors propose a hypothesis regarding the mechanism of YY1 eviction, suggesting a potential connection to the role of SmcHD1 during XCI.
The authors provide an in-depth analysis of the role of YY1 in gene silencing kinetics during induced XCI and believe this manuscript should be published if our comments are addressed.
Major comment:
Based on the allelic ratio in figure 3C only minor loss of YY1 binding occurs in induced XCI in mESCs on the Xi, while silencing is established properly as shown in figure 4C (left panel, red boxplots). This suggests that YY1 eviction is not necessarily required for these genes to be effectively silenced. Could the authors explain this discrepancy in the data regarding their manuscript conclusions? It seems this is true for XCI happening during differentiation towards NPCs, but not if cells are stuck in the pluripotency stage?
Whilst indeed substantial, we do not consider the silencing seen for 6-day mESCs in Fig4C to be “established properly”. We refer to our previous publication (Figure 4 Bowness et al., 2022), which shows that silencing at equivalent timepoints under differentiation conditions (d5-d7) is significantly more pronounced (near-“complete”). Indeed, the level of silencing reached by YY1-FKBP mESCs (Xist induced but no dTAG treatment) aligns with the plateau of silencing in undifferentiated mESCs we describe in our previous study (median allelic ratio of approximately 0.1).
We conclude that YY1 contributes somewhat to sustaining this residual expression in mESCs, because a) substantial YY1 binding remains on Xi at these timepoints in mESCs and b) silencing increases with degradation of YY1 (the latter is more direct evidence). Notably, silencing does not progress to completion (allelic ratio of 0) in the absence of YY1, so we do not claim that YY1 is the only factor sustaining residual Xi gene expression in mESCs.
We interpret this comment to be a fundamentally similar concern to that raised by Reviewer #2 (2.), but in the context of undifferentiated mESCs rather than SmcHD1 KO. As stated above, we do not think it inherently contradictory for substantially increased Xi YY1 binding to sustain a quantitively small (but nonetheless meaningful) increase in residual gene expression from Xi.
Minor comments:
- In the abstract lines 7-8, the authors state that the experiments were performed in mouse embryonic stem cell lines, but much of the data shown is acquired in NPC differentiations. Please adjust abstract.
We have adjusted this sentence in the abstract to include that many of the experiments in the paper involved differentiation of iXist-ChrX mESCs.
The last sentence of the abstract states that YY1 acts as a barrier to silencing but as stated in my major comment, that does seem to be the case in ESC differentiation towards NPCs, but not in ESCs themselves. Please tone down this sentence. Moreover, we do not fully understand where the 'is removed only at late stages' comes from? Is this because of the Smchd1 link? We find this link quite weak with the data presented. We would tone down that last abstract sentence.
We have toned down the final sentence of the abstract accordingly. We agree that “removed only at late stages” is unsubstantiated since YY1 binding on Xi decreases over the entire time course (albeit slowly). However, we maintain that a connection between YY1 and late stages of the XCI process is reasonable to infer from the various pieces of evidence we provide in the study (egs YY1 is persistently enriched in accessible REs, it is associated with slow-silencing genes, and it remains bound to Xi in undifferentiated mESCs).
Several comparisons to human XCI have been made in the article. We do agree that there are similarities between mouse and human XCI. However, there is insufficient data that substantiates that these genes are regulated in a similar manner in humans. We believe the comparisons should be removed altogether or attenuated.
We agree that there is nothing in our data that directly pertains to human XCI. Comparisons to human are only made twice in the paper: Initially in the introduction to make a broad statement that many mechanisms of Xist function are conserved between species, and finally as speculation in the last discussion paragraph. We think it is relevant to acknowledge the parallels between our study, which links YY1 binding with resistance to Xist-silencing in a mouse ESC model, and literature describing a similar association between YY1 and XCI escape in humans.
At bottom of page 4, the authors say that for any given gene, the allelic ration of accessibility at its promoter decreased more slowly than it silenced and then write Fig 1B. They probably mean S1C? Since 1B only shows 4 genes.
The phrase “any given” was used colloquially (ie imprecisely), so we have replaced it with “individual”.
Figure 1B shows the average allelic ratio of multiple clones for genes representing different silencing speeds. Each data point is the average of multiple clones for these representative genes, could the authors show the individual data points or the standard deviation?
Fig1B predominantly shows the averages of only two replicate time-courses of Xist induction with NPC differentiation using the same parental clonal cell line, iXist-ChrX-Dom, but performed on different dates and passages. We regenerated the panel without merging the replicate data points, but this has little effect on the plot (see the Rmarkdown html file of Figure 1 on Github).
Figure 1B. Loss of promoter accessibility lags behind loss of chromatin-associated RNA expression for these 4 genes. What about distal REs? Do the allelic ratios for the distal REs more closely follow chromatin-associated RNA expression? Could the authors show this in a supplemental figure?
We comment from FigS1C on the general trend that accessibility decrease from Xi occurs slower than gene silencing (measured by ChrRNA-seq). We then find in FigS1D that distal elements lose accessibility slightly faster than promoters. Although overall the allelic ratio decrease of distal (non-CTCF) RE accessibility is slightly closer to the trajectory to that of gene silencing, it remains substantially slower (see again the Rmarkdown .html file of Figure 1 on Github).
An equivalent plot to Fig1B showing distal REs would rely on our simplistic assignment of distal elements to their nearest genes. We believe this is reasonable generalisation for investigating chromosome-wide trends but unlikely to be sufficiently accurate at the level of specific genes.
Figure 1B: gene silencing trajectory is depicted left while the legend says right. Same for promoter accessibility.
The legend is now corrected.
Figure S1A shows only part of the X chromosome. The area downstream of Xist is missing. Is this because the iXist-ChrXDom cell line is missing allelic resolution as shown in figure S2A? Could the authors explain in the figure legend that part of the X-Chromosome is missing?
We have now included a reference to the recombination event in the iXist-ChrXDom cell line both when we present data from this background in the first paragraph of the Results section, and in the legend of FigS1A.
Figure 2C shows that 94 TSSs bear a YY1 peak, yet Fig 2F shows 62 are targets of YY1. Is this because the rest are not properly silenced or are escapees?
Fig2C shows the numbers of ChrX YY1 ATAC-seq peaks which overlap with “promoters” (ie regions +/- 500bp of a TSS). By contrast, Fig2F shows ChrX genes classified as direct YY1-targets for allelic silencing analysis. The discrepancy between these numbers is due to a number of reasons:
- It is possible for multiple YY1 peaks to overlap the same promoter (eg one peak overlaps 500bp upstream, a separate peak overlaps 500bp downstream).
- The count in Fig2C is not restrictive to one TSS per gene in cases where there are multiple transcript isoforms in the gene annotation, thus multiple YY1 peaks can overlap different promoters for the same gene.
- A few genes do not pass our filters for allelic silencing analysis (eg they are too lowly expressed). Some YY1 peaks may overlap these genes. We hope the revised version of Fig2F, which includes numbers of direct YY1 target genes on autosomes and ChrX, makes the distinction between these two numbers clearer.
Moreover, YY1 has ~4-fold more peaks on the X chromosome on distal elements compared to promoters. Yet figure 2F exclusively shows the proportion of YY1 binding sites on TSSs. Would distal REs show similar proportions for the silencing categories? Could the authors show the differences in a Supplemental figure?
As discussed in the response to Reviewer #1 (point 8.), a large fraction of distal YY1 peaks on ChrX are at LINE1 elements, which are not amenable to allelic analysis. Excluding these peaks results in a smaller number of distal elements bound by YY1. The application of our filters for allelic analysis reduces the number of distal YY1-bound REs even more, and our assignment of distal REs to their nearest gene is imprecise. For these reasons, we do not think a comparison of genes classified by whether they are putative targets of distal YY1-bound enhancers is informative.
The authors switch between different model systems in the figures, which makes quite confusing which type of XCI is being discussed. We would like to see clearly stated above all panels which cell culture condition is being studied (mESCs or NPCs).
We have tried to improve this potential source of confusion by modifying “mESC” to “mESC no diff” in the relevant figure panels (see response to Reviewer #1 comment 7B), and adding “in mESCs without differentiation” to the title of Figure 4.
In Figure 3E and 3F the authors look at the binding retention of OCT4 during XCI in ESCs. However, it is not clear why the authors choose OCT4. Could the authors explain why specifically OCT4 was chosen for these analyses?
In our responses to the other reviewers, we discuss the limitations of only having one other TF to compare to YY1. The choice of OCT4 was primarily dictated by our experience and confidence in being able to generate high quality ChIP-seq data of this factor.
As it was essentially arbitrary for the purposes of this paper, we have added a comment to this effect in the text (“with that of a different arbitrary TF, OCT4”).
What is the expression level of YY1 in NPCs compared to mESCS? In Supplemental S2A, it seems that YY1 protein levels decrease over time during NPC differentiation. Is part of the increased eviction a result of lower protein levels of YY1? Probably not since you calculate ratios between Xi and Xa. Can you please comment on this?
We were similarly intrigued by this apparent decrease in YY1 protein levels in NPCs (there is no decrease on the RNA level) and initially considered if it could contribute to the relative.
In FigS2A specifically, the d18 NPC band is probably just a poor quality sample extraction. Our ChIP-seq data generated from the same sample is similar poor compared to the others (FigS2B). In other YY1-FKBP12F36V clones we derived and characterised by Western (not described further in this study, but will likely be published as raw source data for the cropped blots we show in FigS2A), the apparent difference in YY1 protein levels in NPCs is less pronounced. Although a minor decrease in YY1 protein in NPCs seems to be robust, we do not think it relevant in the context of our analysis of YY1 and XCI, as we almost always use Xa as internal comparison for any observations made about Xi.
On page 7 the authors state that degrading YY1 does not affect Xist spreading and/or localisation. Indeed, it has been previously shown by other groups that YY1 is required for Xist localisation during XCI. Could the authors elaborate further on the why their cells behave differently compared to the Jeon 2011 paper?
We are working with a mouse ESC model of inducible Xist from its endogenous locus on ChrX and using the dTAG system to degrade YY1 protein. By contrast, Jeon 2011 worked with an Xist transgene integrated at random in the genome of mouse embryonic fibroblasts (MEFs) and siRNA knockdown of YY1. The difference in our observations could be linked to any of these 4 differences (ie cellular context, Xist genomic location, Xist introns, knockdown strategy), but we cannot identify a specific explanation.
In figure 4G and figure S3D elevated levels of Xist are observed in the dTAG conditions. As the authors point out, this could then result in accelerated silencing of the X seen upon YY1 loss. Are these elevated Xist levels that result in enhanced silencing in figure 4 relevant for the kinetics of silencing? Moreover, YY1 could act as transcriptional regulator of those genes in the X and by removing YY1, one would expect decreased transcription, which would be read as accelerated silencing. The authors could see whether the genes that show accelerated silencing are regulated by YY1 in ESCs (+ dTAG, - Dox).
We agree that these points are important to consider when interpreting the results of the YY1-FKBP12F36V ChrRNA-seq we present in Figure 4. However, we believe they are covered in the text during our discussion of the data.
In relation to the final suggestion, the silencing of almost all X-linked genes is increased upon YY1 removal so separating a specific set of genes which show accelerated silencing would be difficult. Nevertheless, in Fig4F we report that the increases in Xi silencing are strongest for direct YY1 target genes. In fact, these genes also show a minor decrease in expression in the + dTAG - Dox condition (see response to Reviewer #1 point 12.). However, by-and-large the differences in Xa log2FCs between YY1-target and non-target genes are less statistically significant. Non-significant p-values are not shown on Fig4F, but can be found in our Rmarkdown analysis records.
Can the authors explain why they decided to put the Smchd1 part after the conclusion? Before the conclusion would have been better? The probable link between YY1 and SmcHD1 is definitely something important to investigate.
Supplemental FigS4 relating to SmcHD1 is more speculative and we lack direct mechanistic evidence linking YY1 and SmcHD1. It would require more experiments to substantiate this as a mechanism. We think these experiments could potentially be very interesting, but are beyond the scope of this study.
In the paper the authors cite Bowness et al., 2022. In it, Figure 5F studies silencing times with respect to silencing dependency on SmcHD1. What is the overlap between SmcHD1 target genes and YY1 target genes? This would provide more data about the correlation between YY1 and SmcHD1.
There is an association between YY1 target genes and our previous categories of genes based on SmcHD1 dependence (13/56 SmcHD1_dependent genes are YY1 targets compared to only 8/101 of SmchD1_not_dependent genes). However, this enrichment of YY1 targets in SmcHD1 dependent genes is not so striking to warrant inclusion into the (very short) discussion of SmcHD1 in this paper. This association is also expected from the fact that both YY1-target genes and SmcHD1-dependent genes associate with the set of slow-silencing genes.
Of note, our categories of SmcHD1 dependency were in fact defined in a previous study (Gdula et al., 2019) from a different cellular model (SmcHD1 KO MEFs).
The authors hypothesise that SmcHD1 might play a role in the eviction of YY1 in NPC differentiation. The current data shows impaired silencing of slow silencing genes and YY1-dependent genes in the SmcHD1 knock-out. However, it doesn't show SmcHD1 is required for YY1 eviction. Could the authors provide direct evidence for their hypothesis by performing NPC differentiation in wild type and SmcHD1 knock-out cells and investigate YY1 binding using ChIP-seq?
The data we show in FigS4 is ATAC-seq data. It shows that YY1 target REs are particularly more accessible from the Xi in SmcHD1 KO, which is not direct evidence but does align with a potential role for SmcHD1 in mediating removal of YY1 binding from Xi (see our response to Reviewer #2’s comment 2.). We agree that YY1 ChIP-seq over the same time course would be an interesting experiment, but arguably this would also only be indirect evidence (ie increased Xi YY1 enrichment may be due to a confounding consequence of SmcHD1 KO). We therefore believe the full suite of experiments needed to rigorously test the hypothesis are beyond the scope of this paper.
In figure S4A and S4B no significance is indicated among the different conditions across the different differentiation days. Could the authors add this?
At all timepoints, differences of Xi accessibility between YY1-binding vs non-YY1 REs are significant. P values are now added to FigS4 and the statistical test is described in the legend.
Finally, we would like the authors to elaborate in the conclusion about the order of events. As they correctly state at the top of page 5 (and we agree), delayed loss of promoter accessibility compared to gene silencing does not automatically mean that it is downstream of gene silencing. Can you elaborate on this? Also, in light of Fig S2C where loss of YY1 binding seems to happen after gene silencing.
We mention in the text and in the above response to Reviewer #2 (point 2.) that we do not wish to overinterpret this quantitative difference because the assays are technically different and accessibility is not linearly correlated with gene expression.
It is possible to speculate plausible biological explanations for this discrepancy in kinetics between accessibility loss, TF binding and gene silencing. For example, a change in the landscape of histone modifications at a promoter may have little effect on its accessibility to TFs but directly hinder RNA Polymerase II in initiation and/or elongation of transcription of the gene. However, we prefer to keep this speculation out of the main text of the paper.
Reviewer #3 (Significance (Required)):
This manuscript highlights a novel role for YY1 in XCI. The manuscript provides an analysis of the correlation and causation of YY1 in gene silencing during XCI. There is a clear correlation between YY1 and delayed silencing of genes on the Xi. To our knowledge, this is the first time such an analysis has been performed for YY1. It advances our conceptual and mechanistic understanding of gene silencing kinetics and what the factors involved in it are. We believe it is an important contribution to the XCI field and will be of great value to the XCI community.
Strength:
This study presents a comprehensive and in-depth characterization of X-linked gene silencing during XCI.
Two different types of inducible XCI are studied and compared (ESCs vs differentiation towards NPCs), which we are grateful for.
Systematic and stepwise analysis of the data is very strong.
Many data points have been collected which provide stronger conclusions.
Weakness:
Some sentences in the abstract should be toned down.
YY1 eviction on the inactive X doesn't seem crucial to establish X-linked gene silencing in mESCs.
The mechanistic approach at the end of the manuscript with relation to SmcHD1 could be studied further.
This paper will be suited for a specialised audience in XCI and transcription factor control of gene expression, i.e. basic research.
Field of expertise: XCI, epigenetics, Xist, gene silencing, X chromosome biology.
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Referee #3
Evidence, reproducibility and clarity
In this manuscript, Bowness and colleagues describe the interesting finding that the transcription factor YY1 is associated with slow silencing genes in induced X-Chromosome Inactivation (XCI). The authors have conducted a comprehensive characterization of X-linked gene silencing and the loss of chromatin accessibility of regulatory elements in induced XCI in ESCs and during NPC differentiation. X-linked gene silencing was classified into four categories, ranging from fast-silenced genes to genes that escape silencing. Motif enrichment analysis of regulatory elements associated with slowly silenced genes identified YY1 as the transcription factor most significantly enriched. The separation of YY1-target and non-target genes confirmed that most genes bound by YY1 indeed exhibit slower silencing kinetics. A comparison of the binding kinetics of YY1 to another transcription factor, OCT4, during XCI revealed that YY1 is evicted more slowly compared to OCT4 on the inactive X, suggesting that slower eviction is a unique property of YY1. Conditional knock-outs of YY1 using protein degradation during induced XCI in mESCs demonstrated that the loss of YY1 at target genes enhances silencing. This supports the hypothesis that YY1 serves as a crucial barrier for slow-silenced genes during XCI. Finally, the authors propose a hypothesis regarding the mechanism of YY1 eviction, suggesting a potential connection to the role of SmcHD1 during XCI.
The authors provide an in-depth analysis of the role of YY1 in gene silencing kinetics during induced XCI and believe this manuscript should be published if our comments are addressed.
Major comment:
Based on the allelic ratio in figure 3C only minor loss of YY1 binding occurs in induced XCI in mESCs on the Xi, while silencing is established properly as shown in figure 4C (left panel, red boxplots). This suggests that YY1 eviction is not necessarily required for these genes to be effectively silenced. Could the authors explain this discrepancy in the data regarding their manuscript conclusions? It seems this is true for XCI happening during differentiation towards NPCs, but not if cells are stuck in the pluripotency stage?
Minor comments:
In the abstract lines 7-8, the authors state that the experiments were performed in mouse embryonic stem cell lines, but much of the data shown is acquired in NPC differentiations. Please adjust abstract.
The last sentence of the abstract states that YY1 acts as a barrier to silencing but as stated in my major comment, that does seem to be the case in ESC differentiation towards NPCs, but not in ESCs themselves. Please tone down this sentence. Moreover, we do not fully understand where the 'is removed only at late stages' comes from? Is this because of the Smchd1 link? We find this link quite weak with the data presented. We would tone down that last abstract sentence.
Several comparisons to human XCI have been made in the article. We do agree that there are similarities between mouse and human XCI. However, there is insufficient data that substantiates that these genes are regulated in a similar manner in humans. We believe the comparisons should be removed altogether or attenuated.
At bottom of page 4, the authors say that for any given gene, the allelic ration of accessibility at its promoter decreased more slowly than it silenced and then write Fig 1B. They probably mean S1C? Since 1B only shows 4 genes.
Figure 1B shows the average allelic ratio of multiple clones for genes representing different silencing speeds. Each data point is the average of multiple clones for these representative genes, could the authors show the individual data points or the standard deviation?
Figure 1B. Loss of promoter accessibility lags behind loss of chromatin-associated RNA expression for these 4 genes. What about distal REs? Do the allelic ratios for the distal REs more closely follow chromatin-associated RNA expression? Could the authors show this in a supplemental figure?
Figure 1B: gene silencing trajectory is depicted left while the legend says right. Same for promoter accessibility.
Figure S1A shows only part of the X chromosome. The area downstream of Xist is missing. Is this because the iXist-ChrXDom cell line is missing allelic resolution as shown in figure S2A? Could the authors explain in the figure legend that part of the X-Chromosome is missing?
Figure 2C shows that 94 TSSs bear a YY1 peak, yet Fig 2F shows 62 are targets of YY1. Is this because the rest are not properly silenced or are escapees?
Moreover, YY1 has ~4-fold more peaks on the X chromosome on distal elements compared to promoters. Yet figure 2F exclusively shows the proportion of YY1 binding sites on TSSs. Would distal REs show similar proportions for the silencing categories? Could the authors show the differences in a Supplemental figure?
The authors switch between different model systems in the figures, which makes quite confusing which type of XCI is being discussed. We would like to see clearly stated above all panels which cell culture condition is being studied (mESCs or NPCs).
In Figure 3E and 3F the authors look at the binding retention of OCT4 during XCI in ESCs. However, it is not clear why the authors choose OCT4. Could the authors explain why specifically OCT4 was chosen for these analyses?
What is the expression level of YY1 in NPCs compared to mESCS? In Supplemental S2A, it seems that YY1 protein levels decrease over time during NPC differentiation. Is part of the increased eviction a result of lower protein levels of YY1? Probably not since you calculate ratios between Xi and Xa. Can you please comment on this?
On page 7 the authors state that degrading YY1 does not affect Xist spreading and/or localisation. Indeed, it has been previously shown by other groups that YY1 is required for Xist localisation during XCI. Could the authors elaborate further on the why their cells behave differently compared to the Jeon 2011 paper?
In figure 4G and figure S3D elevated levels of Xist are observed in the dTAG conditions. As the authors point out, this could then result in accelerated silencing of the X seen upon YY1 loss. Are these elevated Xist levels that result in enhanced silencing in figure 4 relevant for the kinetics of silencing? Moreover, YY1 could act as transcriptional regulator of those genes in the X and by removing YY1, one would expect decreased transcription, which would be read as accelerated silencing. The authors could see whether the genes that show accelerated silencing are regulated by YY1 in ESCs (+ dTAG, - Dox).
Can the authors explain why they decided to put the Smchd1 part after the conclusion? Before the conclusion would have been better? The probable link between YY1 and SmcHD1 is definitely something important to investigate.
In the paper the authors cite Bowness et al., 2022. In it, Figure 5F studies silencing times with respect to silencing dependency on SmcHD1. What is the overlap between SmcHD1 target genes and YY1 target genes? This would provide more data about the correlation between YY1 and SmcHD1.
The authors hypothesise that SmcHD1 might play a role in the eviction of YY1 in NPC differentiation. The current data shows impaired silencing of slow silencing genes and YY1-dependent genes in the SmcHD1 knock-out. However, it doesn't show SmcHD1 is required for YY1 eviction. Could the authors provide direct evidence for their hypothesis by performing NPC differentiation in wild type and SmcHD1 knock-out cells and investigate YY1 binding using ChIP-seq?
In figure S4A and S4B no significance is indicated among the different conditions across the different differentiation days. Could the authors add this?
Finally, we would like the authors to elaborate in the conclusion about the order of events. As they correctly state at the top of page 5 (and we agree), delayed loss of promoter accessibility compared to gene silencing does not automatically mean that it is downstream of gene silencing. Can you elaborate on this? Also, in light of Fig S2C where loss of YY1 binding seems to happen after gene silencing.
Significance
This manuscript highlights a novel role for YY1 in XCI. The manuscript provides an analysis of the correlation and causation of YY1 in gene silencing during XCI. There is a clear correlation between YY1 and delayed silencing of genes on the Xi. To our knowledge, this is the first time such an analysis has been performed for YY1. It advances our conceptual and mechanistic understanding of gene silencing kinetics and what the factors involved in it are. We believe it is an important contribution to the XCI field and will be of great value to the XCI community.
Strength:
This study presents a comprehensive and in-depth characterization of X-linked gene silencing during XCI.
Two different types of inducible XCI are studied and compared (ESCs vs differentiation towards NPCs), which we are grateful for.
Systematic and stepwise analysis of the data is very strong.
Many data points have been collected which provide stronger conclusions.
Weakness:
Some sentences in the abstract should be toned down.
YY1 eviction on the inactive X doesn't seem crucial to establish X-linked gene silencing in mESCs.
The mechanistic approach at the end of the manuscript with relation to SmcHD1 could be studied further.
This paper will be suited for a specialised audience in XCI and transcription factor control of gene expression, i.e. basic research.
Field of expertise: XCI, epigenetics, Xist, gene silencing, X chromosome biology.
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Referee #2
Evidence, reproducibility and clarity
The authors studied the molecular basis of a variation in the rate of individual gene silencing on the X undergoing inactivation. They took advantage of ATAC-seq to observe the kinetics of chromatin accessibility along the inactive X upon induction of Xist expression in mESCs. They demonstrated a clear correspondence between the decrease in chromatin accessibility and the silencing of nearby genes. Furthermore, they found that persistently accessible regulatory elements and slow-silencing were associated with binding of YY1. YY1 tended to associate longer with genes that required more time to be silenced than those that became silenced fast on the inactive X during XCI. The acute loss of YY1 facilitated silencing of slow genes in a shorter period. They suggest that whether or not the transcription factors stay associated longer is another factor that impacts the variation in the rate of gene silencing on the Xi.
Significance
It has been suggested that the rate of gene silencing during XCI is varies depending on the distance of individual genes from the Xist locus or the entry site of Xist RNA on the X, as well as their initial expression levels before silencing. This study provides another perspective on this issue. The persistent association of transcription factors during XCI affects the rate of gene silencing. Although the issued addressed here might draw attention from only the limited fields of specialists, their finding advances our understanding of how the efficiency of silencing is controlled during the process of XCI. The experimental data essentially support their conclusion, and the manuscript was easy to follow. However, I still have some comments, which I would like the authors to consider before further consideration.
Major concerns
Based on the results shown in Figure 3E and F, the authors concluded that YY1 was more resistant than other TFs against the eviction from the X upon Xist induction. I am not still convinced with this. YY1 binds DNA via the zinc finger domain, while Oct4 binds DNA via the homeodomain. The difference in the binding module between them might affect their dissociation or the response to Xist RNA-mediated chromatin changes. In addition, given that YY1 has been reported to bind RNA, including Xist, as well, Oct4 might not be a good TF to compare.
I don't think that Kinetics of YY1 eviction upon Xist induction in SmcHD1 KO cells during NSC differentiation fit the phenotype of Smchd1mutant cells. Although their previous study by Bowness et al (2022) showed that Smchd1-KO cells fail to establish complete silencing of SmcHD1-dependnet genes, their silencing still reached rather appreciable levels according to Figure 6 of Bowness et al (2022). This is, in fact, consistent with the idea that XCI initially takes place in the mutant embryos, at least to an extent that does not compromise early postimplantation development. On the other hand, a significant portion of YY1 appears to remain associated with the target genes on both active and inactive X (Figure S4), which I think suggests that the presence of YY1 is compatible with silencing of SmdHD1-dependent genes. This is contradictory to the proposed role of YY1 that sustains the expression of X-linked genes in this context.
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Referee #1
Evidence, reproducibility and clarity
Summary: This manuscript uses differentiation of the highly informative inter-specific hybrid mouse ESC to follow features of genes that inactivate slowly. Resistance to silencing is reflected in reduced change in chromatin accessibility and the authors identify YY1 and CTCF as enriched amongst these 'slow' genes. This finding is provocative as these factors have been reported to enrich at both human and mouse escape genes. The authors go on to demonstrate that eviction of YY1 is slowly evicted from the X, and that removal of YY1 increases silencing.
Minor Comments:
Overall, the manuscript's conclusions are well supported; however, the brevity of the presentation in some places made it difficult to follow, and in other places seemed a missed opportunity to more fully examine or present their data.
- Introduction is only 2 paragraphs and half of the last is their new findings. First part of results/discussion is then forced to be very introductory. In addition, some discussion of escapees, even if predominantly human, seems warranted in the introduction. There are multiple studies that have tried to identify features enriched at genes that escape inactivation that could be mentioned.
- Variation in silencing rates. 'Comparable rankings' cites multiple studies (oddly previous sentence cites only two) - how concurrent are they? Developing this further (perhaps a supplementary table) would inform whether the genes assessed are ones that routinely behave similarly across different studies/lines; and also serve as a resource for future studies.
- It would be helpful to give insight into informativity of cross - what proportion of ATAC-seq peaks were informative with allelic information (and similarly, what proportion of genes expressed had allelic information?
- P5: "can be influenced by Xist RNA via a variety of mechanisms" seems like it this sweeping statement could use expansion, or at least a reference. Authors could also clarify that 'distal elements assigned by linear genomic proximity is their definition of nearest gene.
- Figure S1 - there are 6-8 other regions that fail to become monoallelic - what are they?
- Is there any correlation between silencing speed and expression (as previously reported)? If yes, then is there also a correlation with YY1 presence - and is this correlation greater than or less than seen on autosomes?
- Figure 2: Have the authors considered using quartiles rather than an arbitrary division into depleted and persistent? B. Could simplify secondary labels to solely YY1 and CTCF. D & F do not print in black and white. Overall the mESC versus NPC can be confusing, perhaps mESC (no diff) would be helpful?
- The numbers appear to suggest YY1 is generally enriched on X, but not at promoters?? Is this true? For Figure 2f, it might be helpful to show autosomal genes - are Fast depleted or Slow enriched for YY1 relative to autosomes? More generally, is YY1 binding on the X lost more slowly than YY1 binding on autosomes, or is the slow loss a feature of YY1. While I agree YY1 could have direct up or down-regulatory roles, Figure S3 could also be reflecting a secondary impact.
- Figure 3, 4 and supplementary - the chromosome cartoon introduces the LOH in iXist, but this needs to be described in text. Describing the reciprocal as a biological replicate seems challenging given this LOH.
- Could a panel of TFs be used rather than OCT4 which has its own unique properties to emphasize that YY1 is unique?
- Figure 4 - by examining 'late' genes, a change in allelic ratio is observed, but what about escape genes (e.g. Kdm5c, Kdm6a)? Do they now become silent? It would be helpful to have all this data as a supplementary table so people could query their 'favorite' gene.
- It seems surprising that loss of YY1 has no demonstrative impact on the Xa. Figure S3B suggests that over 1000 genes are significantly impacted - primarily down regulated. How many of those are X-linked? Perhaps they could be colored differently?
- Since XIST+/undifferentiated cells retain YY1, is YY1 binding sensitive to DNAme? Indeed, are X chromosome bound sites in islands that become methylated? Figure S4 shows YY1-targetted X genes in SMCHD1 knockout; can CTCF targets also be shown? While identified in Figure 2, CTCF was not examined the way YY1 was, although it has also been identified in somatic studies of genes that escape X inactivation.
- When the authors use cf. do they simply mean see also, or as wikipedia suggests: "the cited source supports a different claim (proposition) than the one just made, that it is worthwhile to compare the two claims and assess the difference". Perhaps it would be worth spelling out to clarify for the audience.
Significance
General assessment: An important question in human biology is how much the sex chromosome contributes to sex differences in disease frequency. Genes that escape X inactivation in humans seem to have considerable impact on gene expression genome-wide. While there are not as many genes in mouse that escape inactivation, the use of the mESC cell differentiation approach allows detailed assessment of the timing of silencing during inactivation. The authors utilize an inter-specific cross and it would be interesting to know the limitations of such a system (in terms of informative DHS/genes that are informative).
Advance: As the authors note, there are multiple studies of similar systems that have revealed differences in the speeds of silencing of genes. However, this is the first study to my knowledge that has then tried to assess timing with gene-specific factors. There are multiple studies in humans comparing escape and subject genes for TFs, but lacking the developmental timing that this study incorporates.
Audience: While generally applicable to a basic research audience interested in gene regulation, the applicability to human genes that escape inactivation may interest cancer researchers or clinical audiences interested in sex differences.
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Reply to the reviewers
General Statement We very much appreciate the reviewers' thorough comments and are sincerely grateful for their kind remarks on the novelty and interest of our manuscript. We are confident to have addressed all the points that they have raised including new data, as well as revised figures and text.
Point-by-point description of revisions All the revisions have been already carried out and included in the transferred manuscript.
Reviewer #1
Major comments:
> The number of the replicates/animals for the experiments described in Figures 1 and 2 should be reported either in the figure legends or in the methods (statistical analysis). We have added the required numbers to the corresponding revised figures, as requested.
> A relevant part of the discussion repeats what the authors have already said in the results. I would recommend to reorganize this section, emphasizing the importance of these results in the context of human brain tumors.
Following our own style, we have written a very short (46 lines in length!) Discussion. We dedicate a few lines to highlighting two points: (1) the suggestion, derived from our allograft experiments, that the initial stages of tumour development and long-term tumour growth may be molecularly distinct events, and (2), the unique effect of the combined loss of TrxT and dhd on mbt tumour transcriptomics -unique because none of the suppressors of mbt reported before are as effective in erasing both the MBTS and SDS mbt signatures. Neither of these points are raised in Results. In the remaining few lines we put our results in the context of human Cancer/Testis and elaborate on the fact that the TrxT and dhd pair qualify as head-to-head, CT-X genes, like those reported in human oncology. This is as far as we are willing to go at this stage at emphasizing the importance of our results in the context of human tumours.
Reviewer #2
> 1. Figures should include information regarding the sex of the larvae, particularly as there has been a previously reported sex-linked effect in the phenotypes analysed. (e.g. in Figure 2 and Figure S1, where Indication of the sex of the animals should be provided in the figure OK and not just in the figure legend). We fully agree. Sex must always be taken into account as a biological variable. All the experiments reported in the manuscript were carried out with sexed samples, and were annotated accordingly in the original text. In compliance with the reviewer's request we have added this information also to the revised figure.
*> 2. Data regarding fertility. Can this be shown in a table format? Are dhdKO females fully sterile? What are the fertility levels of Df(1)J5? * Please note that we are not discovering anything here but merely corroborating what has been published before: the lack of TrxT does not affect fertility in either sex; the lack of Dhd results in female sterility (Torres-Campana et al., 2022, Tirmarche et al., 2016, Svensson et al., 2003, Pellicena-Palle et al., 1997). Adding a table would not be justified. Moreover, it would be a rather simple table: all single-pair mating tests (n=10 for each genotype) with Trxt KO and Dhd KO males, and TrxT KO females were as fertile as control flies, while all single-pair mating tests (n=10) with Dhd KO females were sterile.
> 3. Are dhd and TrxT the only genes affected by Df(1)J5? Is there transcriptional data from Df(1)J5 animals to suggest that nearby genes are not affected by the deficiency? Of particular interest would be to assess if snf is affected or not as it is a known regulator of gene expression and splicing. Yes dhd and TrxT are the only genes affected by Df(1)J5. That is the case according to Flybase (citing Svensson et al., 2003, and Salz et al., 1994) and confirmed by our own RNAseq data. No other transcripts, including snf, are affected by Df(1)J5.
> 4. In Figure 1C, statistical test plus indication of significance is not presented. The requested statistical test and significance data have been added as required to the revised figure and figure legend.
> 5. Related to Figure 1D. Additional neural markers could be assessed in dhdKO and TrxTKO flies. Whilst the gross morphology of the brain does not seem to be affected, there is a possibility that cell specification is affected. Specific markers for the NE, MED and CB could be used to assess this in more detail, particularly as the DE-cad images shown for dhdKO and TrxTKO flies seem to differ slightly from the control. We believe that there may be a small misunderstanding here. We have made this point clear in the revised version by referring to substantial published data showing that expression of these two genes is restricted to the germline and that, female fertility aside, TrxT and dhd deficient flies' development and life span are perfectly normal. If anything, Figure 1D is redundant. However, we would rather keep it as a control that our CRISPR KO mutants behave as expected.
> 6. Related to Figure 2A, images from TrxTKO; l(3)mbtts1, dhdKO and l(3)mbtts1 should be added at the very least in a supplementary figure. Additionally, data for NE/BL ratio should be provided for dhdKO, TrxTKO and Df(1)J5 in the absence of l(3)mbtts1 tumours. Related to Figure S1, quantification of NE/BL ratio for female lobes should be added to the figure. All the requested images and data have been included in the revised version in new figures Figure S2B, Figure S2A, and Figure S1A.
> 7. Related to Figure 2B and Figure S1, three rows of images are presented for each genotype. It is unclear whether these correspond to brain lobes from different larvae or different confocal planes from the same animal. This should be clarified in the figure and/or figure legend. This point has been clarified as requested in the revised figure legend. Each group of three rows correspond to brain lobes from different larvae of the same genotype.
> 7 cont. Related to this, in addition to the anti-DE-cadherin data, it would be informative to include immunofluorescence data using antibodies such as anti-Dachshund (lamina), anti-Elav (medulla cortex) and anti-Prospero (central brain and boundary between central brain and medulla cortex) (as assessed in e.g. Zhou and Luo, J Neurosci 2013) in the mbt tumour situation to accurately describe regions disrupted by the tumours. There is no denying that taking advantage of the many cell-type specific markers that are readily available in Drosophila could be of interest. The same applies to cell cycle markers like PH3, FUCCI, and many others. However, we believe that interesting as they may be, none of this markers will give us the clue on the molecular basis of TrxT and Dhd tumour function that is, of course, the open burning question that we are trying to address now.
> 8. Authors should clarify how the NE was defined when mbt tumours are generated, as it is severely affected. From the images provided, it is unclear which region corresponds to NE or how the NE/BL ratio was measured. It would be helpful to outline these regions in the images or, as mentioned above, use antibodies to define them. The figure has been modified to include the requested outlines defining the NE that indeed is correspond to the channel showing DE-Cadh staining.
> 9. Figure 2C does not have indication of statistical significance for the comparisons stated in the text. Potential explanations for the different roles of Dhd and TrxT in long-term tumour development should be explored in the discussion. The requested statistical significance data for these comparisons were stated in the second last paragraph of that section. To make these data more prominent we have also added this information to revised Figure 2C.
>9 cont. Related to this, does the analysis of the RNA-seq data from TrxTKO; l(3)mbtts1 and dhdKO; l(3)mbtts1 animals reveal why they have similar effect on mbt tumour development but do not synergistically contribute to long-term growth? Unfortunately our analysis of the RNA-seq data from TrxTKO; l(3)mbtts1 and dhdKO; l(3)mbtts1 animals does not give us any clue that could help us understand why they have similar effect on mbt tumour development, but not in long-term growth (allografts). To further explore this point, we have added new Figure S3 that includes a Venn diagramme showing the overlap between the affected mMBTS genes in TrxTKO; l(3)mbtts1 and dhdKO; l(3)mbtts1, together with the lists of enriched GOs among overlapping and non-overlapping genes. GO differences are tantalising, indeed, However, they do not immediately suggest any direct explanation for the different roles of Dhd and TrxT in long-term tumour development.
> 10. Authors should clarify if there is any overlap between the affected M-tSDS and F-tSDS in the TrxTKO; l(3)mbtts1 and dhdKO; l(3)mbtts1 conditions. Would the limited overlap suggest that TrxT and dhd act in parallel rather than synergistically? This might also explain the differential effects on long-term tumour development. Additionally, the stronger effect observed in Df(1)J5 animals may be due to TrxT and dhd functional redundancy. Currently, there is limited evidence to suggest that TrxT and dhd act synergistically to regulate mbt tumour growth based on the presented data. See below.
> 11. Authors should include a Venn diagram depicting affected genes (M-tSDS and F-tSDS) in the TrxTKO; l(3)mbtts1, dhdKO; l(3)mbtts1 and Df(1)J5; l(3)mbtts1 genotypes as this could clarify the percentage of overlap of gene signatures in these different conditions. Related to this point, authors could provide results from GO analysis to investigate whether specific functional clusters are altered in the different conditions. We have taken the liberty of fusing points 10 and 11 that are conceptually similar. The requested Venn diagrams showing the overlap between the affected M-tSDS and F-tSDS genes in the TrxTKO; l(3)mbtts1, dhdKO; l(3)mbtts1, and Df(1)J5; l(3)mbtts1 conditions, and GO analysis are now shown in new Figure S5. Unfortunately, these new data do not suggest any obvious explanation for the differential effects of these two genes, nor do they allow us to derive any further conclusions regarding the nature of the pathways through which TrxT and dhd cooperate to sustain mbt tumour growth. However, our analyses demonstrate that efficient suppression of mbt phenotypic traits (in larval brains) and transcriptome requires the combined elimination of both germline thioredoxins, while the effect of individual removal of either of them is only partial. These data demonstrate the synergistic nature of TrxT and dhd function in mbt tumour growth.
> 12. In Figure 3E, authors should indicate more explicitly in the figure panel and/or figure legend which genes display significant differences in expression in the different samples. We apologise for not having made this point clear in the original version: All (21) genes shown in this Table are significantly downregulated in DfJ5;ts1 vs ts1. From these, nanos and Ocho are also significantly downregulated in TrxTKO;ts1 vs ts1, and Ocho, HP1D3csd, hlk, fj, Lcp9, CG43394, and CG14968 are significantly downregulated in dhdKO;ts1 vs ts1. These data have been included in the revised figure legend. Data on all other comparisons are included in Table S1.
> 13. In Figure S2C-F it is not clear if the graphs represent data from all tissues or data from male and female tissues separately, as shown in Figure 4. Apologies for the confusion. All samples were from male tissues as indicated in the original figure legend. To make it more clear, we have labelled all four panels in the revised figure.
> 14. Are TrxT and dhd also deregulated in other tumour types? Or is this specific for mbt tumours? This information could be provided to enhance the scope of the manuscript. Thank you for raising this point. TrxT and dhd are not dysregulated in the other tumour types that were analysed in Janic et al., 2010 (i.e pros, mira, brat, lgl and pins).
> 15. Authors conclude that TrxT and dhd cooperate in controlling gene expression between wild-type and tumour samples and that they act synergistically in the regulation of sex-linked gene expression in male tumour tissue. However, the link between the two observations (if indeed there is a link) has not been well explained. Is the effect on gene expression in tumours simply a result of the regulation of sex-linked transcription? Our data show that TrxT and dhd synergistically contribute to the emergence of both the MBTS (i.e tumour versus wild type) and SDS (i.e. male tumour versus female tumour). The only certainty at this time regarding the interconnection between both signatures is that they overlap, but only partially, which answers one the questions raised by the reviewer: the effect on gene expression in tumours is not simply a result of the regulation of sex-linked transcription. Beyond that, the link (if indeed there is a link) between these two signatures has not been investigated. The lack of insight on this issue is not surprising taking into account that, in contrast to classical tumour signatures (tumour versus healthy tissue), the concept of sex-linked tumour signatures is relatively new and only a handful of such signatures have been published. Moreover, the vast majority of classical tumour signatures have not been worked out in a sex-dependent manner.
Reviewer #3 Comments: > - In the first section of the results, as a first step to study the role of TrxT and dhd genes on mbt tumors the authors generate CRISPR knock outs of these genes and correctly validate them. However, afterwards, the experiment where the authors test the KO of these genes in a wild-type larva brain is not contextualized with the rest of the section. It might be best to first address the role of these genes in a tumor context and only then complement with the experiments in wild-type (in supplementary material). We do appreciate the reviewer's view, but respectfully disagree. In our opinion, the manuscript flows better by presenting the tools that we have generated in Figure 1, By corroborating published data showing that these two germline genes do not affect soma development (Torres-Campana et al., 2022, Tirmarche et al., 2016, Svensson et al., 2003, Pellicena-Palle et al., 1997) this first figure not only validates our CRISPR KO mutants, but also sets the stage to highlight their significant effect on a somatic tumour like mbt.
> - Fig 2 B - To back up the quantifications in Fig 2A the authors could include images of l(3)mbt ts1 tumors with TrxT KO and dhd KO also. The requested images are shown in new figure Figure S2B.
> Fig 2 B and C - Indeed, the results suggest that TrxT seems to be responsible for most tumor lethality upon l(3)mbt allografts, but not dhd. This is curious since l(3)mbt; dhd KO brain tumors have the same partial phenotype as l(3)mbt; TrxT KO (fig 1A). It would be interesting to further explore these phenotypes by staining l(3)mbt; TrxT KO and l(3)mbt; dhd KO brains with, for instance, PH3 to understand if the number of dividing cells of these tumors could be different. In addition, to back up this information, the authors could look at what happens to l(3)mbt tumors with TrxT KO and dhd KO at a later stage of development (or to larva or pupa lethality if that is the case) and compare it with l(3)mbt brains. We did explore the possibility of looking at later stages. Unfortunately, the onset of the lethality phase compounded by major tissue reshaping from larval to adult brain make these stages unsuitable to reach any meaningful conclusion. With regards to staining for PH3, we think that like FUCCI and a long list of other useful labels that could be explored, it is potentially interesting, but hardly likely to give us the clue on the molecular basis of TrxT and Dhd tumour function, that is of course the one important question that we are addressing now.
> - Fig 2 B - What happens to the medulla in a l(3)mbt brain tumor? Although the ratio of NE/BL is the same for wild-type and D(1)J5; l(3)mbt, it still seems that the medulla in D(1)J5; l(3)mbt brains is substantially bigger, although quantifications would be required. Do the authors know if the NE in D(1)J5; l(3)mbt brains is either proliferating less or differentiating more? There are no significant differences in medulla/BL nor in CB/BL ratios. The corresponding quantifications have been added to the revised version. As for the question on proliferation versus differentiation, the simple answer is that we do not know.
> Figure S1 - Although the effects of TrxT KO and dhd KO in male mbt tumors seem to be enhanced in relation to female tumors, the authors should include some form of tumor quantification for female tumors like in Fig 2 A. We have carried out the requested quantifications and added the results in a new panel in revised Figure S1A.
Moreover in the 2nd section of the results, relative to Fig 1S in "...Df(1)J5; l(3)mbtts1 female larvae although given the much less severe phenotype of female mbt tumours, the effect caused by Df(1)J5 is quantitatively minor." to say "quantitatively" minor, the authors should include not only quantifications, but a form of comparison between female tumors vs. male tumors. The requested quantification was published in Molnar et al., 2019. However, we agree on the convenience of doing it again with our new samples. The new data, that confirm published results, are now shown as a new panel in revised Figure S1C.
> - Fig 3D - The hierarchical clustering was done according to which parameters? A brief explanation could help a better interpretation of this results section. The requested information has been added to the Methods section. Hierarchical clustering was done using the function heatmap.2 in R to generates a plot in which samples (columns) are clustered (dendogram); genes (rows) are scaled by “rows"; distance = Euclidean; and hclust method = complete linkage. Expression levels are reported as Row Z-score.
> - Fig 3D - It could be beneficial for the authors to include an analysis of the downregulated genes shared between TrxT KO mbt tumors and dhd KO mbt tumors, as well as the genes that are not shared (besides MBTS genes). Could be something like a Venn diagram. Thanks for pointing this out. New Figure S3 shows the requested Venn diagram, as well as the list of enriched GOs for each group.There are no enriched GOs in the list of overlapping genes. TrxTKO; l(3)mbtts1-specific genes are enriched for GOs related to game generation, sexual reproduction, germ cell development and simlar GOs. dhdKO; l(3)mbtts1 -specific genes are enriched for GOs related to chitin, molting and cuticle development. Tantalising as they are, these observations do not immediately suggest any direct explanation for the different roles of Dhd and TrxT in long-term tumour development. We are happy to add these supplemental information, but we do not deem it worth of any further discussion at this point.
> - Results section 3 - "Expression of nanos is also significantly down-regulated upon TrxT loss, but remains unaffected by loss of dhd" - to corroborate the idea that TrxT and dhd work as a pair, but contribute to different functions within the tumor, it would be interesting for the authors to do an allograft experiment of dhd KO; l(3)mbt male tissue with nanos knock down in the brain, if genetically possible. The suggested experiment is published. The gene in question (nanos) is a suppressor of mbt tumour growth: In a nanos knock down background, l(3)mbt allografts do not grow (Janic 2010).
Minor comments: * > - In the first section of the results, the authors claim that "Consistent with the reported phenotypes of Df(1)J5...", but then the study is not mentioned.* The corresponding references (Salz et al., 1994; Svensson et al., 2003; Tirmarche et al., 2016) have been added.
> - Fig 1 B - It is a bit confusing to follow where TrxT and dhd are in the Genome browser view. I am guessing we should follow the TrxT-dhd locus from A, but the authors could make it clearer. Figure 1 has been changed to make this point more clear.
> - In the same section, in the next sentence, the homozygous and hemizygous is a bit confusing. "...homozygous TrxTKO females, dhdKO males, and TrxTKO males", should be corrected. We appreciate the suggestion, but would rather stick to classical terminology and refer to KO/KO females as homozygous and to KO/Y males as hemizygous.
>- In the same section (Fig 1C): "RNA-seq data also shows that TrxT is significantly upregulated in l(3)mbtts1 males compared to females (FC=7.06; FDR=1.10E-44) while dhd is not (FC=1.89; FDR=2.00E-14)." - But dhd is nevertheless upregulated, although less, in l3mbt males, right? The authors might need to rephrase. We refer to comparing males versus females, not wild type versus tumours. The text has been rephrased in the revised version to make this point clear.
> - Fig 2 A (quantifications), should be after the confocal images (Fig 2 B). We respectfully disagree on this minor point. We initially organised this figure in the order recommended by the reviewer, but we eventually found it easier to write the article using the order shown in the submitted figure. We would rather stick to this version.
> - Fig 2 B and Fig S1 - Please include an outline of at least neuroepithelia and, if possible, Central brain or medulla so that these regions can more clearly identified. Moreover, these results will be easier to interpret if you add a male symbol in this image and a female symbol in Figure S1, otherwise, it might seem like the same figure Outlines and symbols have been added to the revised figure, as required.
> - In results, section 2, "Consequently, in spite of the strong sex dimorphism of mbt tumours, the phenotype of Df(1)J5; l(3)mbtts1 larval brains is not sexually dimorph" - to back this up, quantifications of Df(1)J5; l(3)mbtts1 female vs male tumor size, as well as statistical analysis are needed, like previously said. The requested the new data is now shown in revised Figure S1C.
> - In results section 2 - "For allografts derived from, female larvae, we found that differences in lethality rate caused by TrxTKO; l(3)mbtts1, dhdKO; l(3)mbtts1, Df(1)J5; l(3)mbtts1, and l(3)mbtts1 tissues (7-23%) were not significant (Figure 2C)" - there is no statistical analysis to conclude that the lethality rate is not significant, from 7% to 23% still seems like a difference. Thanks for pointing this out. We did of course generate the requested statistical analysis data, but failed to include it in the manuscript. Chi-square statistical test gives a p value=0.2346. These data have been added to the revised version.
> - Last paragraph of section 2 of results - very long and confusing sentence. Please rephrase text. We have rephrased this sentence to make it shorter and clearer.
> - On section 3 of results: "The vas, piwi and CG15930 transcripts are not significantly down-regulated following either TrxT or dhd depletion alone." - in Fig 3E, not only these transcripts seem to suffer a slight downregulation, but there is also no statistical analysis supporting this. There seems to be a misunderstanding here. The requested statistical data for each gene were shown in Table S1
> - First paragraph of section 3 results - the first sentence is written in a confusing way. Moreover, more context is needed in the sentence afterwards: "we first focused on transcripts that are up-regulated in male mbt tumour samples compared to male wild-type larval brains (mMBTS)." but using which data? The RNA seq data? Agreed; this paragraph has been amended in the revised version.
> - Brief conclusion missing on the second paragraph of the last section of results. As far as the results presented in this paragraph are concerned, we can only mention the two potentially interesting observations, which were pointed out in the original version: (i) the suggestion that nanos upregulation could be critical for sustained mbt tumour growth upon allograft, and (ii) the fact that three genes (vas, piwi and CG15930), also known to be required for mbt tumour growth, are downregulated in Df(1)J5; l(3)mbtts1, but remain unaffected following either TrxT or dhd depletion alone. We are unable to derive any other conclusion from these observations.
> - In the end of 3rd paragraph of last section of results: "...M-tSDS and F-tSDS genes is partially reduced in l(3)mbtts1 brains lacking either TrxT or dhd, but it is completely suppressed upon the lack of both." - "completely" might not be a correct word to use in this case, as there is still some small differences As requested, we have changed "completely" for "strongly".
> - 4th paragraph of last section of results: Either mention the male results and then female (to be in order with the figure, as the female graphs come after the male graphs) or change the order in the figure. Also, this paragraph is not very clear, could benefit from a better explanation of the results and conclusions. Point taken. Figure 4 has been changed and female graphs come before male graphs. The paragraph is clearer now. The conclusion from this paragraph is included in the final paragraph of this section.
> - Fig 4 C,D,E,F: to make it more clear, please write the name of the genotypes in question in the figure. At the reviewer's request, the genotypes in question are now written in each panel. Please note that we did not do so before because all four panels correspond to the same genotype: Df(J5); l(3)mbtts1 vs l(3)mbtts1, as we mentioned in the original figure legend.
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Referee #3
Evidence, reproducibility and clarity
Summary:
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In this manuscript, the authors address the role of the thioredoxins Dhd and TrxT in the development and growth of mbt tumors, a sexually dimorphic brain tumor that derives from the expansion of the neuroephitelium. To this end, the authors have successfully generated dhd and TrxT knock-out mutants using CRISPR-Cas9 and show that both dhd and TrxT individual knock-out partially reduces the mbt tumor-associated brain phenotype. Moreover, using Df(1)J5, a deficiency that affects both TrxT and dhd, the recovery of the phenotype is enhanced. However, although concomitant expression of dhd and TrxT is required for proper tumor development, they show that only TrxT is necessary for the growth of allografts derived from male l(3)mbt tumors. This is interesting, not only because TrxT and dhd are never co-expressed in physiological conditions, but also because this data suggests that the pathways leading to l(3)mbt tumor development are different from the ones that contribute to tumor proliferation and aggressiveness. Moreover, the authors show that TrxT and dhd contribute to the emergence of the mbt tumour signature (MBTS) and sex-dimorphic signature (SDS) of tumours by analysing transcriptomic data of TrxT KO; l(3)mbt, dhd KO; l(3)mbt and Df(1)J5; l(3)mbt. In fact, through hierarchical clustering, the authors show that male Df(1)J5; l(3)mbt brain transcriptomic profile becomes closer to wild-type brains than l(3)mbt ts1 tumors.
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This study presents novelty to the cancer research field and both the model and methodology used were appropriate. Nonetheless, this study deals with mbt tumors which are sexually dimorphic, as well as male and female germline-specific genes that in a tumor can alter male and female sex-dimorphic signatures, making this study very easy to become confusing to non-experts in the field if not written in a very clear way. Therefore, the text, especially in the results and discussion section, could be revised in general to improve the comprehension and flow of the manuscript, given that some sentences and paragraphs are hard to follow. In particular, the results section could benefit with more contextualization and a more detailed explanation of experiments. Moreover, the study is lacking some quantifications and a few additional experiments. These issues can certainly be addressed by reviewing the text as well as reorganizing and including a few quantifications and experiments as described below. I am an expert in Drosophila brain development and tumorigenesis.
Comments:
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In the first section of the results, as a first step to study the role of TrxT and dhd genes on mbt tumors the authors generate CRISPR knock outs of these genes and correctly validate them. However, afterwards, the experiment where the authors test the KO of these genes in a wild-type larva brain is not contextualized with the rest of the section. It might be best to first address the role of these genes in a tumor context and only then complement with the experiments in wild-type (in supplementary material).
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Fig 2 B - To back up the quantifications in Fig 2A the authors could include images of l(3)mbt ts1 tumors with TrxT KO and dhd KO also.
Fig 2 B and C - Indeed, the results suggest that TrxT seems to be responsible for most tumor lethality upon l(3)mbt allografts, but not dhd. This is curious since l(3)mbt; dhd KO brain tumors have the same partial phenotype as l(3)mbt; TrxT KO (fig 1A). It would be interesting to further explore these phenotypes by staining l(3)mbt; TrxT KO and l(3)mbt; dhd KO brains with, for instance, PH3 to understand if the number of dividing cells of these tumors could be different. In addition, to back up this information, the authors could look at what happens to l(3)mbt tumors with TrxT KO and dhd KO at a later stage of development (or to larva or pupa lethality if that is the case) and compare it with l(3)mbt brains.
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Fig 2 B - What happens to the medulla in a l(3)mbt brain tumor? Although the ratio of NE/BL is the same for wild-type and D(1)J5; l(3)mbt, it still seems that the medulla in D(1)J5; l(3)mbt brains is substantially bigger, although quantifications would be required. Do the authors know if the NE in D(1)J5; l(3)mbt brains is either proliferating less or differentiating more?
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Figure S1 - Although the effects of TrxT KO and dhd KO in male mbt tumors seem to be enhanced in relation to female tumors, the authors should include some form of tumor quantification for female tumors like in Fig 2 A. Moreover in the 2nd section of the results, relative to Fig 1S in "...Df(1)J5; l(3)mbtts1 female larvae although given the much less severe phenotype of female mbt tumours, the effect caused by Df(1)J5 is quantitatively minor." to say "quantitatively" minor, the authors should include not only quantifications, but a form of comparison between female tumors vs. male tumors.
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Fig 3D - The hierarchical clustering was done according to which parameters? A brief explanation could help a better interpretation of this results section.
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Fig 3D - It could be beneficial for the authors to include an analysis of the downregulated genes shared between TrxT KO mbt tumors and dhd KO mbt tumors, as well as the genes that are not shared (besides MBTS genes). Could be something like a Venn diagram.
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Results section 3 - "Expression of nanos is also significantly down-regulated upon TrxT loss, but remains unaffected by loss of dhd" - to corroborate the idea that TrxT and dhd work as a pair, but contribute to different functions within the tumor, it would be interesting for the authors to do an allograft experiment of dhd KO; l(3)mbt male tissue with nanos knock down in the brain, if genetically possible.
Minor comments:
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In the first section of the results, the authors claim that "Consistent with the reported phenotypes of Df(1)J5...", but then the study is not mentioned.
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Fig 1 B - It is a bit confusing to follow where TrxT and dhd are in the Genome browser view. I am guessing we should follow the TrxT-dhd locus from A, but the authors could make it clearer.
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In the same section, in the next sentence, the homozygous and hemizygous is a bit confusing. "...homozygous TrxTKO females, dhdKO males, and TrxTKO males", should be corrected.
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In the same section (Fig 1C): "RNA-seq data also shows that TrxT is significantly upregulated in l(3)mbtts1 males compared to females (FC=7.06; FDR=1.10E-44) while dhd is not (FC=1.89; FDR=2.00E-14)." - But dhd is nevertheless upregulated, although less, in l3mbt males, right? The authors might need to rephrase.
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Fig 2 A (quantifications), should be after the confocal images (Fig 2 B).
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Fig 2 B and Fig S1 - Please include an outline of at least neuroepithelia and, if possible, Central brain or medulla so that these regions can more clearly identified. Moreover, these results will be easier to interpret if you add a male symbol in this image and a female symbol in Figure S1, otherwise, it might seem like the same figure if one does not properly read the legend.
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In results, section 2, "Consequently, in spite of the strong sex dimorphism of mbt tumours, the phenotype of Df(1)J5; l(3)mbtts1 larval brains is not sexually dimorph" - to back this up, quantifications of Df(1)J5; l(3)mbtts1 female vs male tumor size, as well as statistical analysis are needed, like previously said.
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In results section 2 - "For allografts derived from female larvae, we found that differences in lethality rate caused by TrxTKO; l(3)mbtts1, dhdKO; l(3)mbtts1, Df(1)J5; l(3)mbtts1, and l(3)mbtts1 tissues (7-23%) were not significant (Figure 2C)" - there is no statistical analysis to conclude that the lethality rate is not significant, from 7% to 23% still seems like a difference.
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Last paragraph of section 2 of results - very long and confusing sentence. Please rephrase text.
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On section 3 of results: "The vas, piwi and CG15930 transcripts are not significantly down-regulated following either TrxT or dhd depletion alone." - in Fig 3E, not only these transcripts seem to suffer a slight downregulation, but there is also no statistical analysis supporting this.
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First paragraph of section 3 results - the first sentence is written in a confusing way. Moreover, more context is needed in the sentence afterwards: "we first focused on transcripts that are up-regulated in male mbt tumour samples compared to male wild-type larval brains (mMBTS)." but using which data? The RNA seq data?
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Brief conclusion missing on the second paragraph of the last section of results.
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In the end of 3rd paragraph of last section of results: "...M-tSDS and F-tSDS genes is partially reduced in l(3)mbtts1 brains lacking either TrxT or dhd, but it is completely suppressed upon the lack of both." - "completely" might not be a correct word to use in this case, as there is still some small differences.
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4th paragraph of last section of results: Either mention the male results and then female (to be in order with the figure, as the female graphs come after the male graphs) or change the order in the figure. Also, this paragraph is not very clear, could benefit from a better explanation of the results and conclusions.
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Fig 4 C,D,E,F: to make it more clear, please write the name of the genotypes in question in the figure.
Significance
This study presents an interesting new concept for Drosophila tumors, the cancer germline genes, which to my knowledge has been a poorly explored field, although it has a lot of potential. It is particularly interesting since it addresses the role of two germline specific thioredoxins, that are dispensable for somatic cells, but have a critical role in somatic mbt tumors, exploring new tumor vulnerabilities. This manuscript will benefit researchers in the field of cancer biology, in particular, to better understand cancer-testis (CT) genes and how they promote tumorigenesis, since the biological function for the most part remains unclear.
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Referee #2
Evidence, reproducibility and clarity
The manuscript by Molnar and colleagues is a follow-up from the authors' previously published work (Molnar et al 2019), where they demonstrated differential sex-linked gene expression in Drosophila l(3)mbt brain tumours and identified the thioredoxin proteins TrxT and Dhd in the mbt tumour signature (MBTS). In the current manuscript, the authors generated genetic mutants for both genes using CRISPR TrxTKO and dhdKO and a deficiency that spans both genes (Df(1)J5) to understand the role played by these thioredoxins in normal larval brain development and l(3)mbt tumour development. Both genes were found to be largely dispensable for normal larval brain development, however the authors uncovered a role in l(3)mbt tumour growth and development. Interestingly, although both TrxT and Dhd were required for l(3)mbt tumour development, they appeared to have distinct roles in long-term tumour growth, as assessed by allograft-induced lethality. Furthermore, the authors also investigated the link between the sexually dimorphic signatures of l(3)mbt tumours and the thioredoxins and suggest that both genes are required for the differential gene expression observed between the sexes.
Some of the conclusions are fairly well supported by the data presented. However, there are some aspects that are potentially not fully explored and that would provide more weight to the claims made by the authors. Some of these can be addressed by clarifications made in the text and/or figures and others would benefit from additional immunofluorescence staining experiments.
Specific comments are provided below.
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Figures should include information regarding the sex of the larvae, particularly as there has been a previously reported sex-linked effect in the phenotypes analysed. (e.g. in Figure 2 and Figure S1, where Indication of the sex of the animals should be provided in the figure and not just in the figure legend).
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Data regarding fertility. Can this be shown in a table format? Are dhdKO females fully sterile? What are the fertility levels of Df(1)J5?
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Are dhd and TrxT the only genes affected by Df(1)J5? Is there transcriptional data from Df(1)J5 animals to suggest that nearby genes are not affected by the deficiency? Of particular interest would be to assess if snf is affected or not as it is a known regulator of gene expression and splicing.
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In Figure 1C, statistical test plus indication of significance is not presented.
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Related to Figure 1D. Additional neural markers could be assessed in dhdKO and TrxTKO flies. Whilst the gross morphology of the brain does not seem to be affected, there is a possibility that cell specification is affected. Specific markers for the NE, MED and CB could be used to assess this in more detail, particularly as the DE-cad images shown for dhdKO and TrxTKO flies seem to differ slightly from the control.
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Related to Figure 2A, images from TrxTKO; l(3)mbtts1, dhdKO and l(3)mbtts1 should be added at the very least in a supplementary figure. Additionally, data for NE/BL ratio should be provided for dhdKO, TrxTKO and Df(1)J5 in the absence of l(3)mbtts1 tumours. Related to Figure S1, quantification of NE/BL ratio for female lobes should be added to the figure.
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Related to Figure 2B and Figure S1, three rows of images are presented for each genotype. It is unclear whether these correspond to brain lobes from different larvae or different confocal planes from the same animal. This should be clarified in the figure and/or figure legend. Related to this, in addition to the anti-DE-cadherin data, it would be informative to include immunofluorescence data using antibodies such as anti-Dachshund (lamina), anti-Elav (medulla cortex) and anti-Prospero (central brain and boundary between central brain and medulla cortex) (as assessed in e.g. Zhou and Luo, J Neurosci 2013) in the mbt tumour situation to accurately describe regions disrupted by the tumours.
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Authors should clarify how the NE was defined when mbt tumours are generated, as it is severely affected. From the images provided, it is unclear which region corresponds to NE or how the NE/BL ratio was measured. It would be helpful to outline these regions in the images or, as mentioned above, use antibodies to define them.
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Figure 2C does not have indication of statistical significance for the comparisons stated in the text. Potential explanations for the different roles of Dhd and TrxT in long-term tumour development should be explored in the discussion. Related to this, does the analysis of the RNA-seq data from TrxTKO; l(3)mbtts1 and dhdKO; l(3)mbtts1 animals reveal why they have similar effect on mbt tumour development but do not synergistically contribute to long-term growth?
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Authors should clarify if there is any overlap between the affected M-tSDS and F-tSDS in the TrxTKO; l(3)mbtts1 and dhdKO; l(3)mbtts1 conditions. Would the limited overlap suggest that TrxT and dhd act in parallel rather than synergistically? This might also explain the differential effects on long-term tumour development. Additionally, the stronger effect observed in Df(1)J5 animals may be due to TrxT and dhd functional redundancy. Currently, there is limited evidence to suggest that TrxT and dhd act synergistically to regulate mbt tumour growth based on the presented data.
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Authors should include a Venn diagram depicting affected genes (M-tSDS and F-tSDS) in the TrxTKO; l(3)mbtts1, dhdKO; l(3)mbtts1 and Df(1)J5; l(3)mbtts1 genotypes as this could clarify the percentage of overlap of gene signatures in these different conditions. Related to this point, authors could provide results from GO analysis to investigate whether specific functional clusters are altered in the different conditions.
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In Figure 3E, authors should indicate more explicitly in the figure panel and/or figure legend which genes display significant differences in expression in the different samples.
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In Figure S2C-F it is not clear if the graphs represent data from all tissues or data from male and female tissues separately, as shown in Figure 4.
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Are TrxT and dhd also deregulated in other tumour types? Or is this specific for mbt tumours? This information could be provided to enhance the scope of the manuscript.
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Authors conclude that TrxT and dhd cooperate in controlling gene expression between wild-type and tumour samples and that they act synergistically in the regulation of sex-linked gene expression in male tumour tissue. However, the link between the two observations (if indeed there is a link) has not been well explained. Is the effect on gene expression in tumours simply a result of the regulation of sex-linked transcription?
Significance
The current manuscript provides additional information regarding the regulation of mbt tumours and establishes TrxT and Dhd as potential cancer-germline genes in Drosophila. This will be of interest to researchers studying basic mechanisms of tumourigenesis and could potentially lead to identification of genes that could serve as biomarkers of disease. However, for this, a more general role of TrxT and Dhd needs to be established, as well as their potential conserved role as cancer-germline genes needs to be established.
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Referee #1
Evidence, reproducibility and clarity
Two cancer-germline (CG) genes encoding the Drosophila thioredoxins Deadhead (Dhd) and Thioredoxin-T (TrxT) are located head-to-head in the X chromosome. Cristina Molnar and coworkers investigate the effects of Dhd and TrxT in brain tumours of either sex caused by mutations in l(3)malignant brain tumour (l(3)mbt). Using CRISPR/Cas9-mediated knock-out alleles and RNA-seq, they demonstrate that, although both TrxT and Dhd are not required for normal brain development, they have a significant but partial effect on l(3)mbt brain tumour development, that is stronger in male than in female larval brains. However, allograft experiments show that only TrxT plays a significant role in long-term, sustained tumour growth. TrxT and dhd play a synergistic contribution role in development of mbt tumours and in the emergence of l(3)mbt tumour-linked transcriptomic signatures.
Major comments:
Most of the work in this paper is well conducted and the key conclusions are convincing. I think that the number of the replicates/animals for the experiments described in Figures 1 and 2 should be reported either in the figure legends or in the methods (statistical analysis). A relevant part of the discussion repeats what the authors have already said in the results. I would recommend to reorganize this section, emphasizing the importance of these results in the context of human brain tumors.
Significance
This work provides the first instance of an X-linked, head-to-head cancer-germline gene pair in Drosophila showing that these genes are dispensable for somatic cell development but have a crucial role to prevent malignant growth. Importantly, in humans, cancer germline genes and cancer testis (CT) genes have been involved in a wide range of cancers and about half of CT genes are located on the X chromosome. Thus, findings in this paper would be of interest to a broad audience that includes all the scientists studying the molecular mechanisms leading to cancer development.
The following keywords describe my expertise: Drosophila genetics, cell division, cancer genetics. I have less expertise to evaluate transcriptomics.
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Reply to the reviewers
'The authors do not wish to provide a response at this time.'
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Referee #2
Evidence, reproducibility and clarity
Biddie et al. address the important question of what genomic annotations are relevant to the fine-mapping of trait-associated variation. They assessed data identifying DNase I hypersensitive sites, footprints, H3K27ac and other ChIP-seq peaks, ATAC-seq peaks, and eRNA locations using a benchmark set of allelically imbalanced DNase I hypersensitive sites and ChIP-seq peaks, and MPRA data. They find that a combination of DNase footprints and eRNA locations gives high enrichment for functional variants (albeit with low sensitivity) and demonstrate their FINDER on 53 traits from the GWAS catalog.
I have some questions to address before publication, all of which relate to clarifying the description in the manuscript.
- I found this line in the abstract unclear: "This signature provides high precision, trading-off low recall".
- Figure 1C is missing a y-axis label and a colour legend.
- The authors note a high genomic coverage "by ATAC-seq (75.2%), [and] H3K27ac (61.5%)", which they attribute in part to "too low a threshold used in peak calling". However, both the benchmark datasets and the genomic predictors are utilized without consideration of the effect of thresholding. To what extent are DNase footprints and eRNA specifically informative, vs. representing datasets processed with highly selective cutoffs?
- The benchmark datasets are described as molQTL, bWTL, and caQTL. "QTL" implies a regression of a trait (e.g. accessibility) on a genotype. This is not accurate here: the Vierstra and Abramov datasets investigate allelic imbalance (a related but orthogonal approach), while van Arensbergen is an MPRA.
- QTLbase is cited alongside the Vierstra paper. I had some trouble searching in QTLbase but did not find the Vierstra dataset. It should be clarified whether QTLbase was used to download the Vierstra results, or to supplement it with other studies.
- Fig. 4 discusses the effect of variant centrality in a DHS for prioritization, but it isn't included in the FINDER schematic in Fig. 7. How come it wasn't employed in FINDER?
- The Discussion notes "Firstly, the identification of DNase footprints may be related to residency time of TFs on DNA, where rapidly exchanging factors impart poor footprints (Sung et al., 2014). Variants associated with altering binding of dynamic factors may therefore be missed. To overcome this, detection of footprints could be improved by enzymatic digestion bias correction". I don't see how enzymatic digestion bias is related to sensitivity to detect rapidly exchanging TFs.
- It looks like the eRNA data were obtained from GRO-seq or PRO-seq data. It would be helpful to note key details like this directly rather than leaving it to the reader to try to figure out what is in the PINTS database.
- The github link https://github.com/sbiddie/FINDER gives a 404 not found error. Is FINDER an actual tool implementation, or more generally describing the approach?
Minor comments:
- Some of the figure text is quite small or blurry (e.g. Fig. 1A/B, Fig. S2).
- Typo in Figure 1A legend: "Heatpmap".
- The author of the last entry in the References is "Zhen Z" but should be "Zheng Z".
Significance
This work is highly relevant and well-done and provides practical information to guide future fine-mapping studies. The authors partially address the tradeoff between enrichment and recall, which is frequently swept under the rug. Their approach ought to be of high interest to the broad genetics and gene regulation communities.
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Referee #1
Evidence, reproducibility and clarity
Summary: Disease and trait associated genetic variation is primarily localizes to non-coding regulatory DNA. A wide-variety methods and assays are routinely used to delineate putative regulatory elements. In this manuscript Bidde et al. sought to evaluate which of these assays is useful for identifying and prioritize trait-associated regulatory variation. To these ends the authors perform enrichment analysis on a genetic variation from different sources encompassing both molecular phenotypes (QTLs) and trait-associated variation via GWA-studies. The authors show that genetic variants localizing to DNase I footprints and within elements associated with RNA production (enhancer RNA) are maximally enriched for both molQTLs and trait-associated variation vs. other markers of regulatory DNA. Overall, I find that this manuscript is technically sound, and is consistent with prior studies (namely the enrichment of GWAS variants within DNase I footprints -- Vierstra et al. 2020). I suggest only a few additional analyses and edits to the presentation.
Major comments:
- The authors should expand the QTL studies and the GWAS variants via LD and recompute the enrichments. For example, I would take all variants in high LD (r2 > 0.8 or 0.9) with either a QTL or GWA-variant. This will likely increase total variants overlapping an annotation, but reduce overall enrichment (odds-score), and possibly provide some information about which chromatin marks are more associated with "causal" variants.
- Can the authors comment on why eRNAs seem to be such a strong marker of functional variation? Are these just "strongest" (most accessible) distal elements? I would assume that these peaks have high overlap with chromatin accessibility peaks.
- Would the ATAC-seq enrichment increase if the authors stratified regions by signal rather than aggregating all peaks? The vast majority of chromatin accessibility peaks are very weak and could be false-positives. Lets imagine that in each dataset 1% of peaks are FPs and that the FP peaks are mostly randomly distributed accross the genome. As such, aggregating hundreds to thousands of samples would have many FP peaks and greatly affect the enrichment analysis. Conversely, DNase I footprints are found in high signal peaks that are less likely to be false-positives. One approach to deal with this is to select ATAC-seq peaks matched to the peak signal in DHS peaks with footprints.
Minor comments:
- Figure 1c -- no legend is provided specifying what the bar colors represent.
- Pg. 10 -- "To overcome this, detection of footprints could be improved by enzymatic digestion bias correction (Calviello et al., 2019)." The DNase I footprinting dataset used in this paper performs extensive bias correction using a 6mer statistical model. Nevertheless, I completely agree the sentiment of the authors that low and variable sensitivity of footprinting is certainly driving a high false-negative rate with regards to comprehensively identifying function variants.
- Figure 3 is a little too complicated for its purpose, which is to show the enrichment of bQTLS, caQTLs and raQTLs.
Significance
This manuscript provides a rigorous analysis characterize how various markers of chromatin help aid in the interpretation of non-coding genetic variation. The findings are not entirely novel, however, the analyses and approaches described are nevertheless useful for variant prioritization. This manuscript is broadly applicable and useful to anyone interested studying non-coding genetic variation.
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Reply to the reviewers
Reviewer #1
The paper by Yammine et al addresses a major problem in peculiarities of genotype to phenotype manifestation in collagen II and chondrodysplasia. It is a lucid and comprehensive study detailing what they see as the fundamental mechanism of Gly1170 Ser mutated Col2a1 gene.
At the heart of the matter is the debunking of the results from a mouse model generated by liang et al (Plos one 2014) paper in which the authors suggested that the phenotype seen only homozygous mice (heterozygous mice appear normal), was related to ER stress -UPR-apoptosis cascade resulting in the chondrodysplasia. Yammine et al paper uses a different model, a robust human iPSC-based tissue, with a CRISPRed variant show that despite the ability of the variant chondrocytes to deposit a Gly1170Ser-substituted collagen II in both the hetero- and homozygous models, is not accompanied by any substantive UPR. The authors of this current paper also argue that their model system is most closely resemble the human context, where heterozygous individual show pathology.
We appreciate the Reviewer highlighting the significance of this manuscript addressing a major issue in the field.
I have sieved all the data related to this topic and have gone back to examine the data and what struck me was the repeated use of the phrase "slow to fold" in the current paper and wondered whether the element of "TIME" is as important in the chondrogenesis of either models and it is this element that generate the difference between the two results? While iPSC-based tissue takes up to 44 days, a female mouse would have had two litters in this time and made many more growth plates. Could it be by "slowing" the chondrogenesis pathway, which is part of the procedure of differentiation of iPS cells into chondrocytes, the ER is not as "stressed" as in mouse development? I would like the authors to reflect and comment and put forward their view given UPR signaling pathways play a crucial role in chondrocytes in phases of high protein synthesis, e.g., during bone development by endochondral ossification (Journal of Bone Metabolism, vol. 24, no. 2, pp. 75-82, 2017).
The Reviewer here emphasizes a likely benefit of the human model that we had not previously considered, as differentiation and growth in our model are indeed far more similar to humans than the rapid timeline in mice. We also note that the evidence that collagen is slow to fold comes from the gold standard assay in the field for collagen folding rate, a point discussed in greater detail in response to Reviewer 2’s query (see below).
The literature evidence does indicate that transient UPR signaling is relevant for chondrogenesis. We selected UPR timepoints that do not interface with the differentiation process, but rather the tissue deposition process while chondrocytes are still actively depositing and maintaining the extracellular matrix, to be able to distinguish a physiological transient UPR during differentiation from a potential chronic and possibly pathologic one. We now clarify this point in the manuscript (see text below).
“These timepoints were selected to reflect an early and a late stage of cartilage maturation, but with both timepoints harvested post-chondrogenesis so as not to interfere with the physiologic transient UPR activation that can be important in that process.”
This is not withstanding the good argument given by the authors in defending their robust results, namely that the there is no evidence that the hydrophilic triple-helical domain of pro-collagen binds BiP, the main detector of accumulated misfolded proteins. What then do they make out of the immunostaining and qPCR with ER stress related genes in Liang et al paper?? I know that the data is not theirs but a comment on the indisputable data gives the reader a better understanding.
It is critical to note that the evidence for ER stress that induces the UPR is, at best, exceptionally weak for heterozygotes in the Liang et al paper, and arguably also weak for homozygotes. Liang et al observed, via quantitative PCR, that the mRNA levels of just Chop (which is also a marker of the integrated stress response and not a good readout for UPR activity) and ATF6 (whose RNA-level upregulation is not a standard marker of the UPR) were significantly upregulated in the disease-relevant heterozygous mice – given that other (more valid) UPR markers were not altered, this is not so different from our observation of a lack of UPR in the disease-relevant heterozygotes.
A somewhat more comprehensive set of UPR markers, including Chop, Xbp1(Total and Spliced), Grp78 (BiP), ATF4, and ATF6, was significantly upregulated only in homozygous mice compared to wild-type. PERK is one of many kinases upstream of ATF4 and Chop that can be activated by a variety of processes (the pathway is part of the integrated stress response, for example). Moreover, transcriptional upregulation of ATF4 (which is actually induced translationally, not transcriptionally) and ATF6 (which is actually induced proteolytically, not transcriptionally) are not normally used to read out UPR activation, so it is not so clear to us that a robust UPR was induced even in homozygotes. Moreover, there was not a substantial increase in Xbp1-S (S = spliced) relative to Xbp1-T (T= total) in the study of homozygous mice, which is the most appropriate measure of UPR activation – rather than change in Xbp1-T and Xbp1-S. The use of mostly non-standard genes to assess UPR induction, the weak upregulation of BiP (2.5-fold), and the unchanged ratio of Xbp1-S to Xbp1-T raise some questions regarding UPR induction even in the homozygotes. Regardless of these homozygote data, as noted above, the evidence for a UPR in heterozygotes is very weak, despite ER stress being the focus of the Liang et al paper.
With respect to immunostaining, Liang et al observed that tissue from homozygous mice (but not heterozygotes) contained significantly more apoptotic cells. Apoptosis could be a result of chronic, unresolved UPR signaling, but it could also result from any number of other pathways and is certainly not direct evidence for UPR-inducing ER stress. Additionally, for the homozygote apoptosis assay, Liang et al do not note how many mice were analyzed for each genotype, a value they did report for their other assays. While examining multiple sections for each genotype is valuable (they state ≥10), the assessment of biological replicates (additional mice) seems critical to confidently reach a conclusion.
Although I understand the choice of cell lines for overexpression, the transfection of the HT-1080 cells using wild-type and Gly1170Ser COL2A1encoding plasmids are not a match to the in vivo model (variation of efficiency, etc.) the appearance of BiP even at a lower fold increase does not negate ER stress, as the authors acknowledge but more important is what other paracrine signals which triggers the UPR signally pathway which is not linked to BiP? or an iPS system may lack? Is there anything else not only ATF6α (activating transcription factor 6 alpha), but IRE1α (inositol-requiring enzyme 1 alpha), and PERK (protein kinase RNA-like endoplasmic reticulum kinase).
Our finding that the UPR is not activated is based on comprehensive RNA-sequencing performed in the physiologically more relevant iPSC-derived chondrocyte, as opposed to the tumor cell line HT-1080. Our interactomic finding that BiP interacts to the same extent with wild-type and Gly1170Ser procollagen-II (in HT-1080 cells) strongly supports our proposal that the reason the UPR is not activated is that BiP fails to recognize unfolded triple-helical domains.
We note that, although HT-1080 cells are not a perfect match, they are the most accessible option for interactome-based studies. Because there is no MS-grade antibody for collagen-II IP, we need to IP a transfected, tagged collagen. We cannot do this in chondronoids, or in isolated chondrocytes that transfect poorly and rapidly dedifferentiate. Critically, Prockop and co-workers extensively validated HT-1080 cells as a platform for fibrillar collagen biochemical studies in Matrix 1993, 13, 399. Our own lab further characterized their capacity to properly handle fibrillar collagen variants in great molecular detail in ACS Chem Biol 2016, 11__, __1408.
Since our chondronoid system contains only chondrocyte cells, as is the case in cartilage, the cells can receive paracrine signals from other chondrocytes, but not other cell types. In joints within a whole animal, it is true that paracrine crosstalk occurs between different cell types of different tissues, including inflammatory cells for example. The chondronoid is very useful for elucidating the defects that occur at the chondrocyte-level, without confounding secondary effects. At the chondrocyte-level, Gly1170Ser-substituted procollagen-II does not activate the UPR.
The Reviewer’s comment regarding the absence of paracrine signals in an iPSC-based system is well-taken, and we added discussion as follows:
“These observations indicate that the chondrocytes were not raising such stress responses, at least when examined in the absence of paracrine signals from other cell types in the joint.”
The authors have given us plenty of alternatives that are relevant, and they prepared us for yet another paper on articular cartilage using iPS tissue model which I am looking forward to.
We are also excited about the upcoming potential of this model system!
Significance
I think this paper is publishable and it is important in understanding the mechanism by which mutation in collagen type II affect chondrogenesis and therefore bone formation. This paper will appeal to musculoskeletal scientist especially those who are interested in bone and its pathology. It would be important for the authors to respond to the critique of "TIME" and speed of protein synthesis which create a duress in the ER pathway.
We greatly appreciate the Reviewer’s comment again on the significance of this work, and their scholarly input which has substantially improved the paper. We hope they will agree that the manuscript is now ready for publication.
Reviewer #2
Evidence, reproducibility and clarity
*System: The investigators have used a human iPSC chondrocyte model system to investigate the biochemistry of the Chondrodysplasia caused by the p.Gly1170Ser mutation in the type II collagen gene (COL2A1). They studied presumably homogeneous chondronoids formed by 3 cell lines they previously reported in which the chondrocytes were either homozygous wild type for the gene, homozygous for the Cas Crispr induced mutation or heterozygous for the two alleles (their refs 42-45). In addition, they utilized cultured HT1080 human fibrosarcoma cells transfected with wild type and mutant Col2A1 to study differences in the interactomes of the two proteins.
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*Analytic Parameters: They investigated the extracellular matrix formed by the three cells using collagen and proteoglycan staining and TEM and the transcriptional responses in chondronoids expressing the wild type and mutant genes.
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*Observations: matrix formation was defective in the two mutation bearing cell populations, reflecting defective fibril formation proportional to the abnormal gene dose. They found increased accumulations of post-translational modifications (hydroxylation, and O-glycosylation) on the mutant collagen extracted from the chondronoids and EM evidence of collagen retention in the ER. They studied the comparative transcriptional profiles in the three phenotypes and failed to find a profound UPR response late in culture and only a mild upregulation of UPR genes in the young cultures. They could not find evidence for activation of the ISR except in the homozygous mutant cells.
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*Using transfected HT-1080 cells (previously shown by these investigators not to express endogenous pro-collagen II but able to synthesize transfected pro-collagen genes) they were able to study the comparative wt and mutant pro-collagen interactomes.
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Conclusions: They conclude that the p.gly1170ser mutation in Col2A1 results in abnormal folding which results in trapping of the protein in the ER and some interaction with cellular elements of the proteostatic response. They concluded that the cellular proteostasis machinery can recognize slow-folding Gly1170Ser through increased interactions with certain ER network components but not in the same fashion that has been described for liver cells producing mutated versions of high volume secreted proteins.
We appreciate this careful summary of our work.
*Major comments:
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Their first conclusion, stated in the abstract, "Biochemical characterization reveals that Gly1170Ser procollagen-II is notably slow to fold and secrete." that the mutant polypeptide chain is slower folding than the wild type chain is based on the premise that the longer the chains are in the ER the greater the degree of lysine hydroxylation and O-glycosylation. Although this may be true, they do not provide a reference and I could not find a definitive description of the phenomenon. Their reference 48 only discusses the occurrence of intracellular post-translational modification of the lysines and continuing modification extracellularly but does not relate these phenomena to the rate at which the peptides traverse the cell. I think the reader would benefit from seeing experiments in which the rate of folding and secretion of the wild type and mutant chains are measured and the degree of post-translational modification are compared. Cabral WA et al showed differences in collagen folding and secretion rates in cyclophilin wt, knockouts and heterozygotes osteoblasts and fibroblasts by western blots. (2014) Abnormal Type I Collagen Post-translational Modification and Crosslinking in a Cyclophilin B KO Mouse Model of Recessive Osteogenesis Imperfecta. PLoS Genet 10(6): e1004465. doi:10.1371 / journal.pgen. 1004465). Performing such experiments in their chondronoids would confirm the authors' interpretation that the increased post-translational modification portrayed in their figure 4 reflects slowed folding and secretion related to the mutation.
We apologize for failing to provide essential background references and information to assess our assay for slow folding/secretion of procollagen. In fact, slow migration on SDS-PAGE is not only a widely used assay for comparing the rate of folding of procollagens, it has also remained the gold standard in the field for the past forty years. The studies cited below are some of the seminal papers in the field linking collagen’s rate of folding with its extent of posttranslational modifications and its electrophoretic mobility. We have now updated our citations accordingly.
- Bateman, J.F.; Mascara, T.; Chan, D.; Cole, W.G. “Abnormal type I collagen metabolism by cultured fibroblasts in lethal perinatal osteogenesis imperfecta” Biochem J 1984, 217, 103.
- Bonadio, J.; Holbrook, K.A.; Gelinas, R.E.; Jacob, J.; Byers, P.H. “Altered triple helical structure of type I procollagen in lethal perinatal osteogenesis imperfecta” J Biol Chem 1985, 260, 1734.
- Bateman, J.F.; Chan, D.; Mascara, T.; Rogers, J.G.; Cole, W.G. “Collagen defects in lethal perinatal osteogenesis imperfecta” Biochem J 1986, 240, 699.
- Godfrey, M.; Hollister, D.W. “Type II achondrogenesis-hypochondrogenesis: Identification of abnormal type II collagen” Am J Hum Genet 1988, 43, 904. The basis for this collagen-specific assay of folding rate is that the ER-localized procollagen proline and lysine hydroxylases require monomeric collagen strands as substrates, and cannot accommodate a folded triple helix in their active sites. Thus, accumulation of post-translational modifications on collagen depends on the procollagen triple-helical domain’s residence time as an unfolded monomeric region of the assembling triple-helical trimer within the ER. Some fraction of the hydroxylated lysines are later glycosylated, which slows migration on SDS-PAGE gels. We have now clarified our slow folding conclusion with more precise references and discussion in the manuscript.
Pulse-chase experiments like those suggested by the Reviewer would indeed be beneficial if they were possible in this system, but they simply are not. Although it might be possible to soak in a radiolabeled amino acid over a short time period, the assay still relies on separating the cell fraction from the secreted fraction. This is possible in monolayer cultures, but in a chondronoid composed of complex cartilage and cells we have no way to do it. One could propose that we extract the chondrocytes and then do the pulse-chase in a monolayer culture, but this unfortunately is also not possible as chondrocytes do not behave well outside the tissue setting and rapidly differentiate into other cell types. Fortunately, the procollagen overmodification assay is a widely used and well-accepted measure of slow folding, and thus addresses the issue.
I think Figure 4 needs more explanation for the reader. While, as expected, the homozygous mutant band is much slower than the homozygous wild type band, in the heterozygotes the band is intermediate rather than showing a discrete mixture of wild type and mutant proteins, reflecting different degrees of post-translational modification. Is this a function of mixed triple helices with heterogeneous degrees of post-translational modification? It deserves more comment, since the argument relating the degree of post-translational modification to the rate of folding is dependent on this observation. It would also be helpful to show the whole gel with collagen II markers.
We modified Figure 4 __to show the whole gel (in the SI, see __Fig. S3) and molecular weight markers. It also shows the wild-type collagen-II band. Most of the procollagen produced by the heterozygote is heterotrimeric for the disease-causing substitution (>87% of trimers will contain at least one mutant chain and thus experience delayed folding) and, therefore, the diffuse banding structure is to be expected. Further, we would speculate that in these challenged ER, even the folding of wild-type only trimers is impaired. The Reviewer’s comment suggests there may be some basis for that speculation. We added a note to this effect.
“The presence of a single broad, slow-migrating band as opposed to distinctive overmodified mutant versus normally modified wild-type strands is due to fact that the vast majority of trimers formed in heterozygotes (>85%) contain at least one Gly1170Ser strand that delays triple-helix folding.”
Another approach to the question of intracellular accumulation due to a slow rate of folding of the mutant collagen would be to perform pulse chase labeling of the three types of chondronoids with radiolabeled amino acids and sugars and processing the media and lysates with analysis using antibodies specific for the two collagen chain types. Given the authors extensive experience in studying collagen biosynthesis (e.g. Chan et al J. Biochem. Biophys. Methods 36 (1997) 11-29), such a supporting study would firmly establish whether the rate of folding/secretion differs between the wt and the homozygous and heterozygous chondroidinomas. Until the slow folding can be directly demonstrated in a quantitative fashion rather than by monitoring the secondary phenomenon of post-translational modification the hypothesis remains unproven.
Discussed above in response to the Reviewer’s earlier suggestion of pulse-chase and question regarding the post-translational modification assay, unfortunately the pulse-chase experiment is infeasible. Fortunately, the modification-based assay is already the gold standard in the collagen field.
Another issue that does not appear to be addressed is the consequence of having misfolded collagen chains in the dilated ER. Liang et al, using mice transgenic for one or two copies of the mutant human gene showed apoptosis in the homozygotes but not in the hets a finding similar to that of Kimura et al using transgenics carrying a different human COL2A1 mutation. Okada et al, using chondrocytes converted from human fibroblasts with clinical collagenopathy (heterozygous), although not the same mutation as in the present study, showed dilated ER and some level of apoptosis in the cultured cells. Hintze et al, examining chondrocytes expressing different mutants associated with different forms of spondyloepiphyseal dysplasia, suggested that the degree of stability of the mutations might determine whether apoptosis occurred, i.e. the thermolabile p.R989C was associated with apoptosis while cells expressing the more thermostable mutants p.275C, P.719C and p.G853E did not reveal any evidence for ongoing apoptosis R989. Is it possible that the smaller size of the homozygous chondronoids reflect fewer cells rather than less matrix (or both) as result of apoptosis? Examination of the chondronoids with reagents for caspase 3 or Tunel staining. One could also measure by Col/DNA ratio in wt, hets and homos. It might also have been useful for these experiments been more quantitative, i.e. by cell sorting rather than by eye. Would ImageJ software been helpful?
We greatly appreciate this suggestion. We now added results of TUNEL assays performed on sections of the chondronoids (see Fig. 8), including quantification of the results. Notably, we do not observe a significant difference in apoptosis between genotypes at the timepoint considered. This result is also supported by our transcriptional data, where we do not observe upregulation of apoptosis-related pathways, via the UPR or otherwise.
It is also unclear as to the conformation of chains trapped in the ER. There are many examples in which the natural tendency of misfolded proteins is to aggregate. This is certainly true in the neurodegenerative diseases. While at the magnification used here in the TEM's the ER inclusions appear homogeneous and amorphous, perhaps at higher magnification/resolution a more discrete structure might be seen.
From collagen-II immunohistochemistry confocal images, the intracellular collagen appears sometimes as aggregated puncta, and in other cases more diffuse and amorphous. Given this heterogeneity, we were not able to readily obtain clear additional structural characterization of the intracellular procollagen-II fraction.
*While the choice of time points for the transcriptional analysis, i.e. early and late seems well thought out, the lack of a significant response may be due to the timing and it might have been useful to do earlier or later time points or intermediate time points in case the response was transient, particularly since other laboratories have reported UPR activation and abnormalities in the context of the silencing of Xbp1, the spliced form of which is a major driver of at least one arm of the UPR. *
While our RNA-sequencing results at the specific timepoints we chose cannot rule out a transient activation of the UPR, they do indicate that chronic, unresolved UPR signaling is not the underlying cause of pathology, which is the main point we are making.
The notion that pro-collagen is largely hydrophilic without the potential for exposure of hydrophobic regions that might engage BiP, thus is not sensitive to BiP sensing, is interesting. Is it possible that the tendency of the mutant polypeptides to form the triple helix which in itself acts as kind of a self chaperoning structure? Looking at the kinetics of assembly inside the cell, see suggestions above, might provide further insight into the process beyond that obtained by looking at the modified state of the lysines.
We believe this notion is very strongly supported by the interactomic experiment showing that BiP fails to preferentially engage the poorly folding triple-helical variant. There are, however, many other chaperones and folding enzymes that assist collagen folding, including prolyl isomerases and Hsp47. Hence, it is not clear to us that substantial self-chaperoning occurs. Still, the self-chaperoning idea is intriguing, and we will note that prior work does indicate that triple-helical domains of individual procollagen polypeptides are strongly pre-organized for triple-helix formation (for a review, see Annu Rev Biochem 2009, 78, 929). That said, we hesitate to speculate here on the self-chaperoning idea without additional evidence.__
__Minor comments:
As I mentioned above, while the transcriptional interactome experiments are computationally sophisticated the cell biology and biochemistry would benefit from more and better quantitation.
We have included quantitation of the extent of intracellular procollagen accumulation and the extent of apoptotic cells, which we hope helps to address this point.
The paper is written in a style in which results and discussion are intermingled. Personally I prefer that the introductions are short, the results clearly and briefly presented and the discussion deals with the interpretation and conclusions. I thought that whole paragraphs could have been omitted. e.g. in the introduction *Omit paragraph "The fibrillar.........achondrogenesis type II" Omit paragraph "Conventional and... for example." Omit "Excitingly........in vitro and in vivo (36)." Results: First paragraph repeats last paragraph of introduction and not necessary in one place or the other, condense. *
We appreciate this feedback and have accordingly edited the manuscript for clarity and brevity, which includes deleting or significantly shortening all the paragraphs indicated by the Reviewer. These improvements are indicated in the track-changes version of the manuscript we resubmitted.
Figure 2 by eye MGP (Matrix gla protein inhibits vascular calcification of type II collagen) seems highly over-expressed in the homozygous mutants; MGP is supposedly an inhibitor of calcification, does its over-expression here reflect something about the adequacy of the matrix
Overexpression of MGP could indeed reflect a defect in the matrix of the homozygous variants. It is also likely a reflection of the delayed hypertrophy and maturation observed in the homozygous variants, as matrix calcification is a step in the endochondral ossification process. We did not follow-up on this particular observation, as it is exclusively observed in the less clinically relevant homozygous variant. We added a note to the manuscript to capture the Reviewer’s point about MGP, as below:
“The upregulation in the homozygous system of Matrix Gla Protein (MGP) (Fig. 2A), which inhibits vascular calcification of the matrix in vivo, further supports the delay in hypertrophy, and could lead to differences in the biomechanical properties of the matrix.”
Figure 5 is good but can it be confirmed by quantitative biochemistry?
We have included quantitation of the extent of intracellular procollagen accumulation and the extent of apoptotic cells.
__ __Did you stain with antibodies to other ER resident chaperones other than calreticulin?
Yes, we also stained the ER with PDI. However, the chondronoids require extensive optimization for immunostaining and we could obtain much better images using the ER marker for calreticulin, hence our choice of images to present in the manuscript.__
__Do cells with large amounts of intracellular G1170S die?
As indicated by the newly included TUNEL data, interestingly, even cells expressing exclusively the Gly1170Ser variant of procollagen-II do not seem to apoptose at a significantly higher rate than wild-type, at least at the timepoint considered. As mentioned above, we added these data as Fig. 8, and added discussion of these results and methodology in the relevant sections of the manuscript.__
__Does higher magnification EM reveal any structure of the material within the dilated ER?
We have so far not been able to use EM to obtain higher-resolution insight into intracellular procollagen structures, but we will work on this idea in future studies.__
__Are there any inflammatory cells in the Chondronoids? To respond to aberrant proteins?
There should not be any such cells present in the chondronoids, and we indeed do not observe any inflammatory response. As noted in the response to Reviewer 1, we added discussion regarding the absence of paracrine signals in this type of model system, which we do believe has major advantages for biochemical studies like those performed here.__
__Paragraph
* "Bypassing the UPR.......often do not" Is discussion not results*
Corrected, thanks.
Significance
The experimental system described here is clearly the wave of the present. Generating human ipSC's of different lineages is now being exploited to study a variety of disorders, to achieve better understanding of pathogenesis at the molecular level to serve as appropriate models for drug development, particularly in the context of high throughput screening. In addition, as in this case, relatively rare autosomal dominant disorders with phenotypes that resemble more common sporadic disease, may allow the development of treatments that are relevant for the sporadic disorder. While it is likely that the osteoarthritis that develops in the carriers of the COL2A1 mutations is a function of the host response to the aberrant mechanics resulting from the defective extra-cellular matrix caused by the mutation, having a pure system in which the primary defect can be corrected and the predisposing matrix deficit reversed, could allow normal reparative processes to mitigate the functional joint disability. While the transgenic mice are useful as a disease model, they represent not only the expression of the primary defect but the host pathophysiologic response to that defect, i.e. in this case how the mouse responds to the defective matrix state and whether those responses add additional pathogenic factors to the disease course. Having a tool in which to relatively assess the pure chondrocyte effect should allow more granular analysis of the primary process.
We appreciate the Reviewer’s careful and enthusiastic assessment of the significance of our work.__
__
Their findings reinforce the notion that involvement of the UPR as well as the other arms of the proteostatic response in chondrocytes expressing a variety of mutant collagens suggests a degree of heterogeneity, perhaps depending on the mutation involved. While I do not believe that their current data prove or rigorously test their proposed hypothesis, i.e. that "perhaps due to the pathologic substitution occurring within a triple-helical domain that lacks hydrophobic character, this ER protein accumulation is not recognized by cellular stress responses, such as the unfolded protein response", it is worth considering.
We provide that hypothesis as a reasonable explanation for the absence of a UPR, and it is strongly supported by our interactomic studies. Furthermore, neither we nor others have found evidence for BiP binding the triple helical domain of procollagen in any other studies. Still, that hypothesis is not the core point of the paper and we do appreciate the Reviewer’s perspective.
Given the fact that this is a relatively small field with a variety of observations concerning the role of proteostasis and the UPR in particular which seem to vary depending on the system, i.e. transgenic mice, transfected fibroblasts, the chondroidomas, these observations particularly with additional biochemistry to confirm their notions regarding folding rates etc, represent a useful technical addition to the field and should be interesting for people working on collagen biology, arthritis and protein folding.
I am not a collagen biologist hence my knowledge of some of the nuances of collagen biology may not be extensive. My own areas of interest include the assembly of multi-peptide proteins (such as immunoglobulins) for secretion; the mechanisms that allow them to exit the cell and the aggregation of misfolded proteins as exemplified by the amyloidoses and other forms of clinically relevant protein aggregation. Hence, I am very familiar with tissue culture, transgenic animals as disease models, studies of protein aggregation, and as a former rheumatologist, osteoarthritis.
We greatly appreciate the Reviewer providing such valuable and scholarly input from the perspective of a scientist with deep expertise in the secretory pathway and other diseases of protein misfolding, as well as from rheumatology. Specifically from the perspective of expertise in collagen biology/biochemistry, we hope that our detailed explanations of assays that are possible versus not possible with collagen in this system, the additional context for why our assessment of the modification of procollagen is correlated with folding/secretion rate, and the further analyses added to the paper, now make a convincing case that the improved manuscript is of high significance and is ready for publication.
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Referee #2
Evidence, reproducibility and clarity
System: The investigators have used a human iPSC chondrocyte model system to investigate the biochemistry of the Chondrodysplasia caused by the p.Gly1170Ser mutation in the type II collagen gene (COL2A1). They studied presumably homogeneous chondronoids formed by 3 cell lines they previously reported in which the chondrocytes were either homozygous wild type for the gene, homozygous for the Cas Crispr induced mutation or heterozygous for the two alleles (their refs 42-45). In addition, they utilized cultured HT1080 human fibrosarcoma cells transfected with wild type and mutant Col2A1 to study differences in the interactomes of the two proteins.
Analytic Parameters: They investigated the extracellular matrix formed by the three cells using collagen and proteoglycan staining and TEM and the transcriptional responses in chondronoids expressing the wild type and mutant genes.
Observations: matrix formation was defective in the two mutation bearing cell populations, reflecting defective fibril formation proportional to the abnormal gene dose. They found increased accumulations of post-translational modifications (hydroxylation, and O-glycosylation) on the mutant collagen extracted from the chondronoids and EM evidence of collagen retention in the ER. They studied the comparative transcriptional profiles in the three phenotypes and failed to find a profound UPR response late in culture and only a mild upregulation of UPR genes in the young cultures. They could not find evidence for activation of the ISR except in the homozygous mutant cells. Using transfected HT-1080 cells (previously shown by these investigators not to express endogenous pro-collagen II but able to synthesize transfected pro-collagen genes) they were able to study the comparative wt and mutant pro-collagen interactomes.
Conclusions: They conclude that the p.gly1170ser mutation in Col2A1 results in abnormal folding which results in trapping of the protein in the ER and some interaction with cellular elements of the proteostatic response. They concluded that the cellular proteostasis machinery can recognize slow-folding Gly1170Ser through increased interactions with certain ER network components but not in the same fashion that has been described for liver cells producing mutated versions of high volume secreted proteins.
Major comments:
Their first conclusion, stated in the abstract, "Biochemical characterization reveals that Gly1170Ser procollagen-II is notably slow to fold and secrete." that the mutant polypeptide chain is slower folding than the wild type chain is based on the premise that the longer the chains are in the ER the greater the degree of lysine hydroxylation and O-glycosylation. Although this may be true, they do not provide a reference and I could not find a definitive description of the phenomenon. Their reference 48 only discusses the occurrence of intracellular post-translational modification of the lysines and continuing modification extracellularly but does not relate these phenomena to the rate at which the peptides traverse the cell. I think the reader would benefit from seeing experiments in which the rate of folding and secretion of the wild type and mutant chains are measured and the degree of post-translational modification are compared. Cabral WA et al showed differences in collagen folding and secretion rates in cyclophilin wt, knockouts and heterozygotes osteoblasts and fibroblasts by western blots. (2014) Abnormal Type I Collagen Post-translational Modification and Crosslinking in a Cyclophilin B KO Mouse Model of Recessive Osteogenesis Imperfecta. PLoS Genet 10(6): e1004465. doi:10.1371 / journal.pgen. 1004465). Performing such experiments in their chondronoids would confirm the authors' interpretation that the increased post-translational modification portrayed in their figure 4 reflects slowed folding and secretion related to the mutation.
I think Figure 4 needs more explanation for the reader. While, as expected, the homozygous mutant band is much slower than the homozygous wild type band, in the heterozygotes the band is intermediate rather than showing a discrete mixture of wild type and mutant proteins, reflecting different degrees of post-translational modification. Is this a function of mixed triple helices with heterogeneous degrees of post-translational modification? It deserves more comment, since the argument relating the degree of post-translational modification to the rate of folding is dependent on this observation. It would also be helpful to show the whole gel with collagen II markers.
Another approach to the question of intracellular accumulation due to a slow rate of folding of the mutant collagen would be to perform pulse chase labeling of the three types of chondronoids with radiolabeled amino acids and sugars and processing the media and lysates with analysis using antibodies specific for the two collagen chain types. Given the authors extensive experience in studying collagen biosynthesis (e.g. Chan et al J. Biochem. Biophys. Methods 36 (1997) 11-29), such a supporting study would firmly establish whether the rate of folding/secretion differs between the wt and the homozygous and heterozygous chondroidinomas. Until the slow folding can be directly demonstrated in a quantitative fashion rather than by monitoring the secondary phenomenon of post-translational modification the hypothesis remains unproven.
Another issue that does not appear to be addressed is the consequence of having misfolded collagen chains in the dilated ER. Liang et al, using mice transgenic for one or two copies of the mutant human gene showed apoptosis in the homozygotes but not in the hets a finding similar to that of Kimura et al using transgenics carrying a different human COL2A1 mutation. Okada et al, using chondrocytes converted from human fibroblasts with clinical collagenopathy (heterozygous), although not the same mutation as in the present study, showed dilated ER and some level of apoptosis in the cultured cells. Hintze et al, examining chondrocytes expressing different mutants associated with different forms of spondyloepiphyseal dysplasia, suggested that the degree of stability of the mutations might determine whether apoptosis occurred, i.e. the thermolabile p.R989C was associated with apoptosis while cells expressing the more thermostable mutants p.275C, P.719C and p.G853E did not reveal any evidence for ongoing apoptosis R989. Is it possible that the smaller size of the homozygous chondronoids reflect fewer cells rather than less matrix (or both) as result of apoptosis? Examination of the chondronoids with reagents for caspase 3 or Tunel staining. One could also measure by Col/DNA ratio in wt, hets and homos. It might also have been useful for these experiments been more quantitative, i.e. by cell sorting rather than by eye. Would ImageJ software been helpful? It is also unclear as to the conformation of chains trapped in the ER. There are many examples in which the natural tendency of misfolded proteins is to aggregate. This is certainly true in the neurodegenerative diseases. While at the magnification used here in the TEM's the ER inclusions appear homogeneous and amorphous, perhaps at higher magnification/resolution a more discrete structure might be seen.
While the choice of time points for the transcriptional analysis, i.e. early and late seems well thought out, the lack of a significant response may be due to the timing and it might have been useful to do earlier or later time points or intermediate time points in case the response was transient, particularly since other laboratories have reported UPR activation and abnormalities in the context of the silencing of Xbp1, the spliced form of which is a major driver of at least one arm of the UPR. The notion that pro-collagen is largely hydrophilic without the potential for exposure of hydrophobic regions that might engage BiP, thus is not sensitive to BiP sensing, is interesting. Is it possible that the tendency of the mutant polypeptides to form the triple helix which in itself acts as kind of a self chaperoning structure? Looking at the kinetics of assembly inside the cell, see suggestions above, might provide further insight into the process beyond that obtained by looking at the modified state of the lysines.
Minor comments:
As I mentioned above, while the transcriptional interactome experiments are computationally sophisticated the cell biology and biochemistry would benefit from more and better quantitation.
The paper is written in a style in which results and discussion are intermingled. Personally I prefer that the introductions are short, the results clearly and briefly presented and the discussion deals with the interpretation and conclusions. I thought that whole paragraphs could have been omitted. e.g. in the introduction
Omit paragraph "The fibrillar.........achondrogenesis type II" Omit paragraph "Conventional and... for example." Omit "Excitingly........in vitro and in vivo (36)."
Results:
First paragraph repeats last paragraph of introduction and not necessary in one place or the other, condense. Figure 2 by eye MGP (Matrix gla protein inhibits vascular calcification of type II collagen) seems highly over-expressed in the homozygous mutants; MGP is supposedly an inhibitor of calcification, does its over-expression here reflect something about the adequacy of the matrix
Figure 5 is good but can it be confirmed by quantitative biochemistry?
Did you stain with antibodies to other ER resident chaperones other than calreticulin?
Do cells with large amounts of intracellular G1170S die?
Does higher magnification EM reveal any structure of the material within the dilated ER?
Are there any inflammatory cells in the Chondronoids? To respond to aberrant proteins?
Paragraph "Bypassing the UPR.......often do not" Is discussion not results
Referees cross-commenting
Are other reviewers concerned about the precise definition of slowed folding rather than utilizing the degree of post-translational modification as a surrogate?
Significance
The experimental system described here is clearly the wave of the present. Generating human ipSC's of different lineages is now being exploited to study a variety of disorders, to achieve better understanding of pathogenesis at the molecular level to serve as appropriate models for drug development, particularly in the context of high throughput screening. In addition, as in this case, relatively rare autosomal dominant disorders with phenotypes that resemble more common sporadic disease, may allow the development of treatments that are relevant for the sporadic disorder. While it is likely that the osteoarthritis that develops in the carriers of the COL2A1 mutations is a function of the host response to the aberrant mechanics resulting from the defective extra-cellular matrix caused by the mutation, having a pure system in which the primary defect can be corrected and the predisposing matrix deficit reversed, could allow normal reparative processes to mitigate the functional joint disability. While the transgenic mice are useful as a disease model, they represent not only the expression of the primary defect but the host pathophysiologic response to that defect, i.e. in this case how the mouse responds to the defective matrix state and whether those responses add additional pathogenic factors to the disease course. Having a tool in which to relatively assess the pure chondrocyte effect should allow more granular analysis of the primary process.
Their findings reinforce the notion that involvement of the UPR as well as the other arms of the proteostatic response in chondrocytes expressing a variety of mutant collagens suggests a degree of heterogeneity, perhaps depending on the mutation involved. While I do not believe that their current data prove or rigorously test their proposed hypothesis, i.e. that "perhaps due to the pathologic substitution occurring within a triple-helical domain that lacks hydrophobic character, this ER protein accumulation is not recognized by cellular stress responses, such as the unfolded protein response", it is worth considering.
Given the fact that this is a relatively small field with a variety of observations concerning the role of proteostasis and the UPR in particular which seem to vary depending on the system, i.e. transgenic mice, transfected fibroblasts, the chondroidomas, these observations particularly with additional biochemistry to confirm their notions regarding folding rates etc, represent a useful technical addition to the field and should be interesting for people working on collagen biology, arthritis and protein folding.
I am not a collagen biologist hence my knowledge of some of the nuances of collagen biology may not be extensive. My own areas of interest include the assembly of multi-peptide proteins (such as immunoglobulins) for secretion; the mechanisms that allow them to exit the cell and the aggregation of misfolded proteins as exemplified by the amyloidoses and other forms of clinically relevant protein aggregation. Hence, I am very familiar with tissue culture, transgenic animals as disease models, studies of protein aggregation, and as a former rheumatologist, osteoarthritis.
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Referee #1
Evidence, reproducibility and clarity
The paper by Yammine et al addresses a major problem in peculiarities of genotype to phenotype manifestation in collagen II and chondrodysplasia. It is a lucid and comprehensive study detailing what they see as the fundamental mechanism of Gly1170 Ser mutated Col2a1 gene.
At the heart of the matter is the debunking of the results from a mouse model generated by liang et al (Plos one 2014) paper in which the authors suggested that the phenotype seen only homozygous mice (heterozygous mice appear normal), was related to ER stress -UPR-apoptosis cascade resulting in the chondrodysplasia. Yammine et al paper uses a different model, a robust human iPSC-based tissue, with a CRISPRed variant show that despite the ability of the variant chondrocytes to deposit a Gly1170Ser-substituted collagen II in both the hetero- and homozygous models, is not accompanied by any substantive UPR. The authors of this current paper also argue that their model system is most closely resemble the human context, where heterozygous individual show pathology.
I have sieved all the data related to this topic and have gone back to examine the data and what struck me was the repeated use of the phrase "slow to fold" in the current paper and wondered whether the element of "TIME" is as important in the chondrogenesis of either models and it is this element that generate the difference between the two results?
While iPSC-based tissue takes up to 44 days, a female mouse would have had two litters in this time and made many more growth plates. Could it be by "slowing" the chondrogenesis pathway, which is part of the procedure of differentiation of iPS cells into chondrocytes, the ER is not as "stressed" as in mouse development? I would like the authors to reflect and comment and put forward their view given UPR signaling pathways play a crucial role in chondrocytes in phases of high protein synthesis, e.g., during bone development by endochondral ossification (Journal of Bone Metabolism, vol. 24, no. 2, pp. 75-82, 2017).
This is not withstanding the good argument given by the authors in defending their robust results, namely that the there is no evidence that the hydrophilic triple-helical domain of pro-collagen binds BiP, the main detector of accumulated misfolded proteins. What then do they make out of the immunostaining and qPCR with ER stress related genes in Liang et al paper?? I know that the data is not theirs but a comment on the indisputable data gives the reader a better understanding.
Although I understand the choice of cell lines for overexpression, the transfection of the HT-1080 cells using wild-type and Gly1170Ser COL2A1encoding plasmids are not a match to the in vivo model (variation of efficiency, etc.) the appearance of BiP even at a lower fold increase does not negate ER stress, as the authors acknowledge but more important is what other paracrine signals which triggers the UPR signally pathway which is not linked to BiP ? or an iPS system may lack? Is there anything else not only ATF6α (activating transcription factor 6 alpha), but IRE1α (inositol-requiring enzyme 1 alpha), and PERK (protein kinase RNA-like endoplasmic reticulum kinase). The authors have given us plenty of alternatives that are relevant, and they prepared us for yet another paper on articular cartilage using iPS tissue model which I am looking forward to.
Significance
I think this paper is publishable and it is important in understanding the mechanism by which mutation in collagen type II affect chondrogenesis and therefore bone formation.
This paper will appeal to musculoskeletal scientist especially those who are interested in bone and its pathology.
It would be important for the authors to respond to the critique of "TIME" and speed of protein synthesis which create a duress in the ER pathway.
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Reply to the reviewers
Reviewer #1 (Evidence, reproducibility, and clarity (Required)):
- In this manuscript, Imoto et al. analyze the specific role of the Dynamin1 splice variant Dyn1xA in so-called ultrafast endocytosis, an important mechanism of synaptic vesicle recycling at synapses. In a previous publication (Imoto et al. Neuron 2022), some of the authors had shown that Dyn1xA, and not the other splice variant Dyn1xB, is essential for ultrafast endocytosis. Moreover, Dyn1xA forms clusters around the active zone for exocytosis and interacts with Syndapin 1 in a phosphorylation dependent manner. However, it was unclear which molecular interactions underlie the specific role of Dyn1xA. Here, the authors provide convincing evidence with pull down assays and CSP that Dyn1xA PRR interacts with EndophilinA1/2 with two binding sites. The first binding site lies in the part common to xA and xB, was previously characterized. The second site was previously uncharacterized, is specific for Dyn1xA, and is regulated by phosphorylation (phosphobox 2). The location of these splice variants and mutated forms at presynaptic sites correlate with the prediction made by the biochemical assays. Finally, the authors perform rescue experiments ('flash and freeze' and VGLUT1-pHluorin imaging experiments) to show that Dyn1xA-EndophilinA1/2 binding is important for ultrafast endocytosis. I find the results interesting, providing an important step in the understanding of the interplay between dynamin and the endocytic proteins interacting with it (endophilin, syndapin, amphiphysin) in the context of synaptic vesicle recycling. The manuscript is clearly written and for the most part the data supports the authors' conclusions (see specific comments below). However, there are some issues which need to be clarified before this manuscript is fully suitable for publication.
We thank the reviewer for noting the importance of our study. Indeed, our previous study has raised the question as to why only the Dyn1xA splice variant mediates ultrafast endocytosis, and our current manuscript now resolves this issue.
Introduction: the dynx1B Calcineurin binding motif is written PxIxIT consensus but actual sequence is PRITISDP. Is this a typo?
The sequence is correct. One thing we failed to mention is that the last amino acid in this motif can be either threonine or serine for calcineurin binding, as we demonstrated previously [Jing, et al., 2011 JBC; PMC3162388]. We have amended the text as follows.
- calcineurin-binding motif (PxIxI[T/S]) 19.
Figure 1: the difference between the constructs used in panels C and D is not clear. In D, is it a truncation without residues 796 and 845? If so, it should be labelled clearly in the Western blots. In Panel E, Dyn1xA 746-798 should be labeled Dyn1x 746-798 because it is common to both splice variants.
We thank the reviewer for pointing this out. Both C and D used the full-length PRRs of Dyn1xA-746 to 864 and xB-746 to 851. To make the labeling clear, we changed Dyn1xA PRR to “Dyn1xA PRR (746-864)” and Dyn1xB PRR to “Dyn1xB PRR 746-851” in Figure 1. In the main text, we made the following changes.
- 4: “To identify the potential isoform-selective binding partners, the full-length PRRs of Dyn1xA746-864 and xB746-851 (hereafter, Dyn1xA-PRR and Dyn1xB-PRR, respectively).”
Figure 1: For amphiphysin binding the authors write that "No difference in binding to Amphiphysin 1 was observed among these peptides (Figure1D-F)." They should write that Dyn1x 746-798 does not bind Amphiphysin1 SH3 domain, confirming the specificity of binding to the 833-838 motif.
We edited the sentence as suggested.
- “Dyn1x 746-798 does not bind Amphiphysin1 SH3 domain (Figure 1G), confirming the specificity of binding to the 833-838 motif as reported in previous studies 29,30. (Figure 1D-F).”
Figure S2. The panels are way too small to see the shifts and the labelling. Please provide bigger panels
As suggested, we have now provided bigger panels in Figure S2, and amended the text and Figure legend accordingly.
We also removed Figure S2B as it was not referred to in the text in any way. (It was the reverse experiment – HSQCs of 15N-labelled SH3 titrated with unlabelled dynamin).l
Figure 2 panel B. There is a typo in the connecting line between the sequence and the CSP peaks. It is 846 instead of 864 (after 839).
Corrected.
Figure 3 panel E. In the text, the authors write that "Western blotting of the bound proteins from the R838A pull-down experiment showed that R838A almost abolished both Endophilin and Amphiphysin binding in xA806-864 (Figure 3D), and reduced Endophilin binding to xA-PRR (Figure 3E)." I think they should write "only slightly reduced Endophilin binding..." it is more faithful to the result and consistent with the conclusion that Endophilin A1 has two binding sites on Dyn1xA PRR.
We have now provided quantitative data for R838A and R846A (Fig. 3F and G). Endophilin binding is significantly reduced with R846A.
It is unclear why the R846A mutant affects binding of Dyn1xA 806-864 but not Dyn1xA-PRR-.
The reviewer asks why the R846A mutant affects binding of Dyn1xA 806-864, but not so much of Dyn1xA-PRR. The explanation is simply that there are two endophilin binding sites in Dyn1xA-PRR. The first is not present in the xA806-864 peptide, while both are present in Dyn1xA-PRR (the full length tail). When doing pull-down experiments, the binding tends to saturate – even when the second site is blocked by R846A. The first site is still able to bind, and the binding appears as normal. The same applies to the R838A mutant.
Moreover, it affects binding to endophilin as well as amphiphysin, and therefore it is not specific. It is thus not correct to write that "R846 is the only residue found to specifically regulate the Dyn1 interaction with Endophilin as a part of an SDE". In the Discussion (page 11), the authors refer to the R846A mutation as specifically affecting Endophilin binding. This should be toned down, as it also affects Amphiphysin binding. For this important point, the data on quantification of Endophilin binding should be presented.
The reviewer’s concern is about our claims of specificity of Endophilin A binding in Dyn1xA R846 mutation experiments. The reviewer is correct, and we have now defined specific parameters for those claims. Specifically, we have added new quantitative data from the Western blots in Fig 3E (full-length Dyn1aX-PRR) as Fig 3F-G. We used full-length Dyn1aX-PRR rather than the xA806-864 peptide because the subsequent transfection experiments use full length Dyn1xA. In the new figures 3F and 3G, we quantified Endophilin A, Amphiphysin and Syndapin1 amounts from the multiple Western blots such as Figure 3E (now n=14, 6 experiments, each in with 2-4 replicates for Dyn1xA PRR). R846A mutated in Dyn1xA-PRR significantly reduces the binding to Endophilin A, but it does not significantly affect the binding to Amphiphysin 1and Syndapin1 (Fig 3G). Therefore, this particular Dyn1xA-PRR mutation specifically affects Endophilin A binding, in the context of the full-length tail Dyn1aX-PRR. To make these results clear, we modified the text as below.
P7. “R838A and R846A caused smaller reductions in Endophilin binding compared to wild-type Dyn1xA-PRR, (Figure 3E, 3F, R838A, median 68.5 ; Figure 3G, R846A, median 59.3 % : R838A reduced the Dyn1/Amphiphysin interaction (Figure 3E, 3F, median 14.2 % binding compared to wild-type Dyn1xA-PRR). By contrast, R846A did not affect Amphiphysin and Syndapin binding to Dyn1xA-PRR (Figure 3E, 3G). Therefore, R846, being part of an SDE, is the only residue we found to specifically regulate the Dyn1 interaction with Endophilin in the context of the full length tail (DynxA-PRR)”.
Additionally, the reviewer notes that “the authors refer to the R846A mutation as specifically affecting Endophilin binding. This should be toned down, as it also affects Amphiphysin binding.” In the light of the above data and new quantitative analysis (Fig 3F-G), we have clarified the conclusion. However, to be clear that this statement is only correct in the context of the full-length DynxA-PRR, we amended texts as follows:
P7. “By contrast, R846A did not affect Amphiphysin and Syndapin binding to Dyn1xA-PRR (Figure 3E, 3G). Therefore, R846, being part of an SDE, is the only residue we found to specifically regulate the Dyn1 interaction with Endophilin in the context of the full length tail (DynxA-PRR)”.
New legends for Figure 3F and G have now been added as follows.
“(F) The binding of Endophilin A, and Amphiphysin 1 and Syndapin1 to Dyn1xA-PRR (wild type) or R838A mutant quantified from Western blots in (E). n=14 (6 experiments with 2-4 replicates in each). Median and 95% confidential intervals are shown. Kruskal-Wallis with Dunn’s multiple comparisons test (**p (G) The binding of Endophilin A, and Amphiphysin 1 and Syndapin1 to Dyn1xA-PRR (wild type) or R846A mutant quantified from Western blots in (E). n=14 (6 experiments with 2-4 replicates in each). Median and 95% confidential intervals are shown. Kruskal-Wallis with Dunn’s multiple comparisons test was applied (*p
Figure 3F-G (which are now 3H and 3I in the revised text): what do the star symbols represent in the graphs? I guess the abscissa represents retention time. Please write it clearly instead of a second ordinate for molecular mass, which does not make much sense if this reflects the estimate for the 3 conditions.
The “stars” are crosses (x) and represent individual data points. The figure legends have been updated for clarity. The reviewer is correct that the X-axis is retention time (min). The second Y-axis is needed to define the points in the curve marked with crosses (x’s). The legends for Figure 3H and I are now changed as follows.
“(H) SEC-MALS profiles for Dyn1xA alone (in green), Endophilin A SH3 alone (in red) and the complex of the two (in black) are plotted. The x-axis shows retention time. The left axis is the corresponding UV absorbance (280 nm) signals in solid lines, and the right axis shows the molar mass of each peak in crosses. The molecular weight of the complex was determined and tabulated in comparison with the predicted molecular weight. x represent individual data points.
(I) SEC-MALS profiles for a high concentration of Dyn1xA-PRR/Endophilin A SH3 complex (0.5 mg) (in dark blue) and a low concentration of Dyn1xA-PRR/endophilin A SH3 complex (0.167 mg) (in blue). The x-axis shows retention time. The left axis is the corresponding UV absorbance (280 nm) signals in solid lines, and the right axis shows the molar mass of each peak in crosses. The molecular weight of the complex was determined and tabulated in the table. x represent individual data points.”
Figure 4: The statement that "By contrast [to Dyn1xA], Endophilin A1 or A2 formed multiple clusters (1-5 clusters)" is not at all clear on the presented pictures. The authors should provide views of portions of axons with several varicosities, for the reader to appreciate the cases where there are more EndoA clusters than Dyn1 clusters.
In the revised Figure S4, we added additional STED images for a region of axons with more EndoA1/2 clusters than Dyn1xA clusters. The locations of Dyn1xA and EndoA1/2 clusters are annotated in each image based on the local maximum of intensity, which is determined using our custom Matlab analysis scripts (Imoto, et al., Neuron 2022; for the description of the methods, please refer to the Point #14 below). We also added Figure S3 to describe our analysis pipelines. In the Dyn1xA channel, outer contour indicates 50% of local maxima (boundary of Dyn1xA cluster) while inner contour indicates 70% of local maxima of the clusters. In the EndoA1/2 channel, local maxima of the clusters are indicated as points. To reflect these changes, we modified text as below.
P 9. “By contrast, Endophilin A1 or A2 formed multiple clusters (1-5 clusters) (Figure S4)”
The legends for Figure S4 are now as follows.
“Figure S4. Additional STED images for Figure 4.
(A) The top image shows an axon containing multiple boutons. Signals show overexpression of GFP-tagged Dyn1xA (Dyn1xA) and mCherry-tagged Endophilin A1 (EndoA1). The bottom images show magnifications of four boutons in the top image. Red hot look-up table (LUT) images on the right side of Dyn1xA and EndoA1 images are enhanced contrast images. Outer and inner contours represent 50% and 70% of local maxima of the Dyn1xA, respectively. Black circles represent local maxima of Endophilin A1. In these boutons, multiple EndophilinA1 puncta are present.
(B) The top image shows an axon congaing multiple boutons. Signals show overexpression of mCherry-tagged Dyn1xA (Dyn1xA) and GFP-tagged Endophilin A1 (EndoA1). The bottom images show magnifications of four boutons in the top image. Red hot LUT images on the right side of Dyn1xA and EndoA2 images are enhanced contrast images. Outer and inner contours represent 50% and 70% of local maxima of the Dyn1xA, respectively. Black circles represent local maxima of Endophilin A2. In these boutons, multiple EndophilinA2 puncta are present.
(C) STED micrographs of the same synapses as in Figure 4E with an active zone marker Bassoon (magenta) visualized by antibody staining. GFP-tagged Dyn1xA, Dyn1xA S851D/857D or Dyn1xA R846A (green) are additionally stained with GFP-antibodies. Local maxima of Dyn1xA, Dyn1xA S851D/857D or Dyn1xA R846A signals and minimum distance to the active zone boundary are indicated by dark blue lines.”
Moreover, overexpression of EndophilinA1/2-mCherry is not sufficient to assess its localization. Please consider either immunofluorescence or genome editing (e.g. Orange or TKIT techniques).
We agree with the reviewer that overexpression obscures the endogenous localization of proteins. To address this point in our previous publication, we titrated the amount of plasmids for Dyn1xA-GFP and transfected neurons just for 20 hours – this protocol allowed us to uncover the endogenous localization of Dyn1xA despite the fact that it was overexpressed in wild-type neurons (Imoto, et al., 2022). We also confirmed this localization by ORANGE-based CRISPR knock-in of GFP-tag in the endogenous locus of Dyn1 just after the exon 23 and confirm the true endogenous localization of Dyn1xA (Imoto, et al., 2022). Similar approaches were taken by the Chapman lab to localize Synaptotagmin-1 and Synaptobrevin 2 in axons (Watson et al, 2023, eLife, PMID: 36729040). We did not emphasize this in the first submission, but we took the same approach for the EndoA1/2 localization. This does not mean that they also unmask the endogenous localization, and the reviewer is correct that additional evidence would strengthen the data here. Thus, as suggested, we have looked at the endogenous EndophilinA1 localization by antibody staining. As the reviewer is likely aware, EndophilinA1 also localizes to other places including dendrites and postsynaptic terminals, making it difficult to analyze the data. However, we observe colocalization of Dyn1xA with endogenous EndoA1. Thus, we believe that our major conclusion here drawn based on EndoA1/2-mCherry overexpression is valid (Reviewer’s Figure 1). Since the Endophilin signals in neighboring processes obscures its localization in synapses-of-interest, repeating this localization experiments with ORANGE-based knock-in would be ideal. However, with the lead author starting his own group and many validations needed to confirm the knock-in results, this experiment would require us at least 4-6 months, and thus, it is beyond the scope of our current study. We will follow up on this localization in the near future, but given that endophilin is required for ultrafast endocytosis (Watanabe, et al., Neuron 2018, PMID: 29953872) and these proteins need to be in condensates at the endocytic sites for accelerating the kinetics of endocytosis (Imoto, et al., Neuron 2022, PMID: 35809574), we are confident that endogenous
EndoA1/2 are localized with Dyn1xA.
The analysis of the confocal microscopy data is not explained. How is the number of clusters determined? How far apart are they? Confocal microscopy may not have the resolution to distinguish clusters within a synapse.
We apologize for the insufficient description of the method. We had provided a more thorough description of the methods in our previous publication (Imoto, et al., Neuron 2022, PMID: 35809574). To make this more automated, we improved our custom Matlab scripts. Please note that all the analysis for the cluster location is performed on STED images, not on normal confocal images. To determine the cluster, first, presynaptic regions (based on Bassoon signals or Dyn1xA signals within boutons) in each STED image are cropped with 900 by 900 nm (regions-of-interest) ROIs. Then, our Matlab scripts calculate the local maxima of fluorescence intensity within the ROIs. To determine the distance between the active zone and the Dyn1xA or EndoA1/2 clusters, the Matlab scripts perform the same local maxima calculations in both channels and make contours at 50% intensity of the local maxima. The minimum distance reflects the shortest distance between the active zone and Dyn1xA/EndoA1/2 contours. To make these points clearer, we modified the main text and the Methods section. In addition, we have added workflow of these analysis as Figure S3.
P9. Main. “Signals of these proteins are acquired by STED microscopy and analyzed by custom MATLAB scripts, similarly to our previous work23.”
P20. Methods. “All the cluster distance measurements are performed on STED images. For the measurements, a custom MATLAB code package23 was modified using GPT-4 (OpenAI) to perform semi-automated image segmentation and analysis of the endocytic protein distribution relative to the active zone marked by Bassoon or relative to Dyn1xA cluster in STED images. First, the STED images were blurred with a Gaussian filter with radius of 1.2 pixels to reduce the Poisson noise and then deconvoluted twice using the built-in deconvblind function: the initial point spread function (PSF) input is measured from the unspecific antibodies in the STED images. The second PSF (enhanced PSF) input is chosen as the returned PSF from the initial run of blind deconvolution62. The enhanced PSF was used to deconvolute the STED images to be analyzed. Each time, 10 iterations were performed. All presynaptic boutons in each deconvoluted image were selected within 3030-pixel (0.81 mm2) ROIs based on the varicosity shape and bassoon or Dyn1xA signals. The boundary of active zone or Dyn1xA puncta was identified as the contour that represents half of the intensity of each local maxima in the Bassoon channel. The Dyn1xA clusters and Endophilin A clusters were picked by calculating pixels of local maxima. The distances between the Dyn1xA cluster and active zone boundary or Endophilin A clusters were automatically calculated correspondingly. For the distance measurement, MATLAB distance2curve function (John D'Errico 2024, MATLAB Central File Exchange) first calculated the distance between the local maxima pixel and all the points on the contour of the active zone or Dyn1xA cluster boundary. Next, the shortest distance was selected as the minimum distance. Signals over crossing the ROIs and the Bassoon signals outside of the transfected neurons were excluded from the analysis. The MATLAB scripts are available by request.”
In the legend of Figure S3,
“Protein localization in presynapses is determined by semi-automated MATLAB scripts (see Methods).
(A) Series of deconvoluted STED images are segmented to obtain 50-100 presynapse ROIs in each condition.
(B) Two representations of the MATLAB analysis interface are shown. The first channel (ch1, green) is processed to identify the pixels of local maxima within this channel. The second channel (ch2, magenta) is normally an active zone protein, Bassoon. Active zone boundary is determined by the contour generated at 50% intensity of the local maxima of ch2. The contours outside of the transfected neurons are manually selected on the interface and excluded from the analysis. Minimum distances from each pixel of the local maxima in ch1 to the contour in ch2 are calculated and shown in the composite image. The plot “Distance distribution” shows all the minimum distance identified in this presynapses ROI (unit of the y axis is nanometer). The plot “Accumulated distance distribution” shows the accumulated distance distribution from the initial to the current presynapses ROI. The plot “Histogram of total intensity” shows the intensity counts around individual local maxima pixels in ch1.”
For the STED microscopy, a representation of the processed image (after deconvolution) and the localization of the peaks would be important to assess the measurement of distances. If Dyn1xA S851/857D is more diffuse, are there still peaks to measure for every synapse?
We thank the reviewer for bringing up this important question. In Figure S4C, we have added the position of the local maxima of wild-type and mutant Dyn1xA shown in the main Figure 4E. As the reviewer pointed out, when a protein is more diffuse, it is difficult to find the peak intensity by STED. However, since these proteins are still found at a higher density within a very confined space of a presynapse and synapses are packed with organelles like synaptic vesicles and macromolecules, signals from even diffuse proteins can be detected as clusters, and local maxima can be detected in these images.
To illustrate this point better, we added Reviewer’s Figure 2 below. In this experiment, we transfected neurons with a typical amount of plasmids (2.0 µg/well) or ~10x lower amount (0.25 µg/well). When the density of cytosolic proteins is high (Reviewer’s Figure 2A), the depletion laser has to be strong enough to induce sufficient stimulated emission and resolve protein localization. Insufficient power would produce low resolution images, leading to inappropriate detection of the local maxima (Reviewer’s Figure 1A). Thus, we set our excitation and depletion laser powers to resolve the protein localization to ~40-80 nm at presynapses. Furthermore, to avoid mislocalization of proteins due to the overexpression, we use 0.25-0.5 ug/well (in 12-well plate) of plasmid DNA for transfection, which is around 10 times lower than the amount used in the typical lipofectamine neuronal transfection protocol (Imoto, et al., Neuron 2022). We also change the medium around 20 hours after the transfection instead of the typical 48 hours (Imoto, et al., Neuron 2022). With these modifications and settings, we can obtain the location of the local maxima of the diffuse signals (Reviewer’s Figure 1B and Figure 4E and Figure S4). We modified the Method section to make these points clearer.
P 17, “Briefly, plasmids were mixed well with 2 µl Lipofectamine in 100 µl Neurobasal media and incubated for 20 min. For Dyn1xA and Endophilin A expressions, 0.5 µg of constructs were used to reduce the overexpression artifacts23. The plasmid mixture was added to each well with 1 ml of fresh Neurobasal media supplemented with 2 mM GlutaMax and 2% B27. After 4 hours, the medium was replaced with the pre-warmed conditioned media. To prevent too much expression of proteins, neurons were transfected for less than 20 hours and fixed for imaging.”
P 20, “Quality of the STED images are examined by comparing the confocal and STED images and measuring the size of signals at synapses and PSF (non-specific signals from antibodies).”
Legends for Figure S4C,
“(C) STED micrographs of the synapses shown in Figure 4F with an active zone marker Bassoon (magenta). GFP-tagged Dyn1xA, Dyn1xA S851D/857D or Dyn1xA R846A are visualized by antibody staining of GFP (green). Local maxima of Dyn1xA, Dyn1xA S851D/857D or Dyn1xA R846A signals and minimum distance to the active zone boundary are overlaid.”
Figures 5 and 6: No specific comment. The data and its analysis are very nice and elegant. The comment on the lack of rescue of Dyn1xA on endosome maturation may be a bit overstated, because many "controls" (shRNA control Figure S5 or Dyn3 KO in Imoto et al. 2022) have a significant number of endosomes 10 s after stimulation.
We thank the reviewer for noting the strength of our data and pointing out this issue on endosomal resolution. In particular, the reviewer is concerned about our interpretation of the ferritin positive endosomes present at 10 s in time-resolved electron microscopy experiments. Indeed, the number of ferritin positive endosomes in Dyn1 KO, Dyn1xA OEx neurons (0.1/profile) is similar to the control conditions: scramble shRNA control (0.1/profile, Figure S5) and Dyn3KO neurons (0.2/profile) in our previous study (Imoto et al. 2022). Although we do not consider Dyn3 KO as a control, given the presence of abnormal endosomal structures, we agree with the reviewer that scramble shRNA control in Figure S5 does indicate that some ferritin-positive endosomes even at 10 s after stimulation. We would like to note that this result is in stark contrast to our previous studies where we observed the number of ferritin positive endosomes returning to the basal level in both wild-type neurons and many scramble shRNA controls (Watanabe et al. 2014, 2018, Imoto et al 2022). Thus, the majority of the data we have indicate that the number of ferritin positive endosomes returns to basal level by 10 s, suggesting that endosomes are typically resolved into synaptic vesicles by this time. However, given that we do not know the nature of the inconsistency here and we cannot exclude the possibility of overexpression artifact of Dyn1xA as an alternative, we changed the following lines.
P. 10, “Interestingly, the number of ferritin-positive endosomes did not return to the baseline (Figure 5E, F) as in previous studies3,35,36, suggesting that Dyn1xA may not fully rescue the knockout phenotypes or that overexpression of Dyn1xA causes abnormal endosomal morphology.”
By the way, why did the authors use Dyn1 KO in this study, and not Dyn1,3 DKO as in Imoto et al. 2022?
This is simply because Dyn3KO displayed an endosomal defect in our previous study (Imoto et al 2022), and we wanted to focus on endocytic phenotypes of Dyn1 KO and mutant rescues in this study.
In the Discussion, the authors present the binding sites (for endophilin and amphiphysin SH3 domains) as independent. However, these proteins form dimers or even multimers as they cluster around the neck of a forming vesicle. Even though they provide evidence in vitro (Figure 3) that in these conditions of high concentration one dyn1xA-PRR binds one SH3 domain, in cells multiple binding sites on the PRR to these proteins may involve avidity effects, as discussed for example in Rosendale et al. 2019 doi 10.1038/s41467-019-12434-9. For example, the high affinity binding of Dyn1-PRR to amphiphysin cannot be explained only by the sequence 830-838.
The reviewer suggests “In the Discussion, the authors present the binding sites (for endophilin and amphiphysin SH3 domains) as independent.” However, we do not claim these interactions are functionally independent, except in the context of in vitro experiments where they are sequence-independent.
They also suggest “However, these proteins form dimers or even multimers as they cluster around the neck of a forming vesicle”. However we do not agree with this in the context of our Discussion, because the evidence of multimers and clustering is convincing but is entirely in vitro data.
Thirdly they comment that “For example, the high affinity binding of Dyn1-PRR to amphiphysin cannot be explained only by the sequence 830-838.” We fully agree with the statement and felt we had addressed this in the manuscript. To explain, it’s important to point out our relatively new concept here and previously reported by us (Lin Luo et al 2016, PMID: 26893375) of the existence and importance of SDE and LDE for SH3 domains (Endophilin here, syndapin in our previous report). These elements act at a distance from the so-called core PxxP motifs and they provide much higher affinity and specificity than the core region alone. We had further mentioned this in the p11 discussion “Although this is a previously characterized binding site for Amphiphysin and is also present in Dyn1xB-PRR, the extended C-terminal tail of Dyn1xA contains short and long distance elements (SDE and LDE) essential for Endophilin binding, making it higher affinity for Endophilin.” Because the NMR identified F862 as a chemical shift for dynamin, we performed a pulldown with this mutant in the xA746-798 construct (which only contains the higher affinity site) and found that indeed “.F862A reduced Endophilin binding 29% (pOverall, the reviewer correctly points out that “multiple binding sites on the PRR to these proteins may involve avidity effects*” could play a role in vivo. We agree that avidity is an additional possibility, not examined in our study. Therefore, as suggested, we added the following sentence to the discussion on the SDE and LDE impacts.
P. 11. “Our pull-down results showed that R846A abolished endophilin binding to xA806-864 (which contains only the second and higher affinity binding site and the associated SDE (A839) and LDE (F862)) and reduced about 40% of endophilin binding to the Dyn1xA-PRR (which contains both binding sites) without affecting its interaction with Amphiphysin, providing important partner specificity, although we cannot exclude the possibility that avidity effects may additionally come in play in vivo 42
Reviewer #1 (Significance (Required)):
This study provides a significant advance on the mechanisms of dynamin recruitment to endocytic zones in presynaptic terminals. The work adds a significant step by experienced labs (Robinson, Watanabe) who have provided important insight in the mechanisms by many publications in the last years.
We thank the reviewer for the careful read of our manuscript and positive outlook of our work.
Reviewer #2 (Evidence, reproducibility and clarity (Required)):
- This is a compelling study that reports a key discovery to understand the molecular mechanism of ultrafast endocytosis. The authors demonstrate that the Dynamin splice version 1xA (Dynamin 1xA) uniquely binds Endophilin A, in contrast to Dynamin splice version 1xB (Dynamin 1xB) that does not bind Endophilin A and it is not required for ultrafast endocytosis. In addition, the Endophilin A binding occurs in a dephosphorylation-regulated manner. The study is carefully carried out and it is based on high quality data obtained by means of advanced biochemical methodologies, state-of-art flash-freezing electron microscopy analysis, superresolution microscopy and dynamic imaging of exo-and endocytosis in neuronal cultures. The results convincingly support the conclusions.
We thank the reviewer for supporting the conclusions of our study.
- Although additional experiments are not essential to support the claims of the paper there is room, however, for improvement within the pHluorin experiments. These experiments, that are clearly informative and consistent with the rest of experimental data, do not apply the useful approach to separate endo- from exocytosis. The use of bafilomycin or folimycin to block the vesicular proton pump allows the unmasking the endocytosis that is occurring during the stimulus, that should correspond to ultrafast endocytosis. It would be very elegant to demonstrate that such a component, as expected according to the electron microscopy data, requires the binding of Endophilin A to Dynamin 1xA. If the authors have the pHluorin experiments running, the suggested experiments are very much doable because the reagents and the methodology is already in place and the new data could be generated in around six weeks.
We thank the reviewer for the suggestion. The reviewer is concerned that vGlut1 pHluorin experiment in Figure 6 may not correspond to ultrafast endocytosis. We agree that bafilomycin/folimycin treatment will reveal the amount of endocytosis that takes place while neurons are stimulated. However, we are not certain that endocytosis during this phase would fully correspond to ultrafast endocytosis because reacidification of endocytosed vesicles typically takes 3-4 s (Atluri and Ryan, 2006, PMID: 16495458; although see https://elifesciences.org/articles/36097) and thus, the nature of endocytosis cannot be fully determined by this assay. To claim that endocytosis measured by pHluorin assay during stimulation all correspond to ultrafast endocytosis, we would need to perform very careful work to track single pHluorin molecules at the ultrastructural level and corelate their internalization to pHluorin signals. Perhaps, a rapid acid quench technique used by the Haucke group would also be appropriate to estimate the amount of ultrafast endocytosis (Soykan et al. 2017 PMID: 28231467), but we are not set up to perform such experiments here. Also, our lead author, Yuuta Imoto, is leaving the lab to start up his own group, and it will take us months rather than weeks to get the requested experiments done. Since the point of this experiment was to test whether the interaction of Dyn1xA and EndoA is essential for protein retrieval regardless of the actual mechanisms and the reviewer acknowledges that this point is sufficiently supported by the experiments, we will set this experiment as the priority for the next paper.
Instead of the bafilomycin or rapid acid quenching experiments, we have now added data from vglut1-pHluorin experiment with a single action potential. With a single action potential, all synaptic vesicle recycling is mediated by ultrafast endocytosis in these neurons (Watanabe et al, 2013 PMID: 24305055; Watanabe et al. 2014, PMID: 25296249). Our electron microscopy experiments in Figure 5 is also performed with a single action potential. As with 10 action potentials, 20 Hz experiments, re-acidification of vglut1-pHluorin is blocked when Dyn1 and EndophilinA1 interaction is disrupted (Figure 6 F-I). We added a description of this result as below.
P 11. “Similar defects were observed when the experiments were repeated with a single action potential – synaptic vesicle recycling is mediated by ultrafast endocytosis with this stimulation paradigm25 (S851/857 recovery is 73.3% above the baseline; R846A, recovery is 30.0% above the baseline) (Figure S9 A-D). Together, these results suggest that the 20 amino acid extension of Dyn1xA is important for recycling of synaptic vesicle proteins mediated by specific phosphorylation and Endophilin binding sites within the extension.”
The methods are carefully explained. Some of the experiments are only replicated in two cultures and the authors should justify the reasons to convince the audience that the approaches used have enough low variability for not increasing the n number. The pHluorin experiments, however, are performed only in a single culture; they should replicate these experiments in at least 3 different cultures (three different mice).
The reviewer is correct. The variability is very low in our ultrastructural studies and STED imaging, and thus, in all our previous publications, two independent cultures are used. We do agree that in the ideal case, we would like to have three independent cultures, but given the nature of ultrastructural studies (control, mutants, and multiple time points), triplicating the data would add another year to our work. We are currently developing AI-based segmentation analysis, and once this pipeline is established, we will be able to increase N. However, please note that for these experiments, we examine around 200 synapses from each condition in electron microscopy studies (Table S2)– these numbers are far more than the gold standard in the field. Likewise, 50-100 synapses are examined for STED experiments (Table S2). To examine variability of our analysis results, we compared a significance between the dataset using cumulative curves and Kolmogorov–Smirnov test (Figure S11). As shown in the summarized data and p value in each condition, there are no significant difference between the datasets.
For pHluorin analysis, the reviewer is correct. We repeated the experiments twice to increase the N after the initial submission. The data are consistent, and the conclusions are not changed by the additional experiments (Figure 6 and Figure S9). We also changed the Statistical analysis section in Methods as below.
P. 19. “All electron microscopy data are pooled from multiple experiments after examined on a per-experiment basis (with all freezing on the same day); none of the pooled data show significant deviation from each replicate (Table S2).”
p 19, “All fluorescence microscopy data were first examined on a per-experiment basis. For Figure 4, the data were pooled; none of the pooled data show significant deviation from each replicate (Figure S11 and Table S2). Sample sizes were 2 independent cultures, at least 50-100 synapses from 4 different neurons in each condition..”
Legends for Figure S11
Figure S11. Data variability in Figure 4.
Cumulative curves are made from each dataset of (A) distance of Endophilin A1 puncta from the edge of Dyn1xA puncta, (B) distance of Endophilin A2 puncta from the edge of Dyn1xA puncta, distance distribution of Dyn1xA from active zone edge in (C) neurons expressing wild-type Dyn1xA-GFP, (D) Dyn1xA-S851/857-GFP and (E) Dyn1xA-R846-GFP. n > 4 coverslips from 2 independent cultures. Kolmogorov–Smirnov (KS) test, p values are indicated in each plot.
Minor comments: 4. Prior studies referenced appropriately and the text and figures are clear and accurate.
We thank the reviewer for the careful read of our manuscript.
The authors should discuss about the mediators (enzymes) responsible for dephosphorylation of phosphor-box 2 that is key for the Dynamin 1xa-Endophilin A interaction.
We thank the reviewer for the suggestion. We added a discussion on a potential mediator, Dyrk1, as below.
P. 12. ”What are the kinases that regulate Dyn1? The phosphorylation of phosphobox-1 is mediated by Glycogen synthase kinase-3 beta (GSK3ß) and Cyclin-dependent kinase 5 (CDK5)17, while phosphobox-2 is likely phosphorylated by Trisomy 21-linked dual-specificity tyrosine phosphorylation-regulated kinase 1A (Mnb/Dyrk1)44,45 since Ser851 in phosphobox-2 is shown to be phosphorylated by Mnb/Dyrk1 in vitro32. Furthermore, overexpression of Mnb/Dyrk1 in cultured hippocampal neurons causes slowing down the retrieval of a synaptic vesicle protein vGlut146. Consistently, our data showed that phosphomimetic mutations in phosphobox-2 results disruption of Dyn1xA localization, perturbation of ultrafast endocytosis, and slower kinetics of vGlut1 retrieval. However, how these kinases interplay to regulate the interaction of Dyn1xA, Syndapin1 and Endophilin A1 for ultrafast endocytosis is unknown.”
It would be very helpful to include a final cartoon depicting the key protein-protein interactions regulated by dephosphorylation (activity) and the sequence of molecular events that leads to ultrafast endocytosis
As suggested, we made a model figure, (new Figure 7) showing how Dyn1xA and its interaction with EndoA and Syndapin1 increases the kinetics of endocytosis at synapses. Regarding the sequence of molecular events, we think that there are already dephosphorylated fraction of Dyn1xA molecules sitting on the endocytic zone at the resting state and they mediate ultrafast endocytosis. However, it is equally possible that activity-dependent dephosphorylation of Dyn1xA also may play a role (Jing et al. 2011, PMID: 21730063). However, we have no evidence about the sequence of activity dependent modulation of Dyn1xA and its binding partners during ultrafast endocytosis yet. This is much beyond what we have reported in this work and therefore, excluded from the model figure. We added the following to the end of the discussion:
p13, “Nonetheless, these results suggest that Dyn1xA long C-terminal extension allows multivalent interaction with endocytic proteins and that the high affinity interaction with Endophilin A1 permits phospho-regulation of their interaction and defines its function at synapses (Figure S7)”.
Figure legend Figure 7,
“Figure 7. Schematics depicting how specific isoforms Dyn1xA and Endophilin A mediate ultrafast endocytosis.
A splice variant of dynamin 1, Dyn1xA, but not other isoforms/variants can mediate ultrafast endocytosis. (A) Dyn1xA has 20 amino acid extension which introduces a new high affinity Endophilin A1 binding site. Three amino acids, R846 at the splice site boundary, S851 and S857, act as long-distance element which can enhance affinity of proline rich motifs (PRM) to SH3 motif from outside of the PRM core sequence PxxP. (B) At a resting state, Dyn1xA accumulates at endocytic zone with SH3 containing BAR protein Syndapin 123 and Endophilin A1/2. When phosphobox-1 (Syndapin1 binding) and phosphobox-2 (Endophilin A1/2 binding, around S851/S857) within Dyn1xA PRD are phosphorylated, these proteins are diffuse within the cytoplasm. A dephosphorylated fraction of Dyn1xA molecules can interact with these BAR domain proteins. Loss of interactions including Dyn1xA-R846A or -S851/857D mutations, disrupts endocytic zone pre-accumulations. Consequently, ultrafast endocytosis fails.”
Reviewer #2 (Significance (Required)):
This is a remarkable and important advance in the field of endocytosis. The study reports a key discovery to understand the molecular mechanism of ultrafast endocytosis. Scientist interested in synaptic function and the general audience of cell biologist interested in membrane trafficking will very much value this study. The mechanism reported will potentially be included in textbooks in the near future.
My field of expertise includes molecular mechanisms of presynaptic function and membrane trafficking.
I have not enough experience to evaluate the quality of the NMR experiments, however, I do not have any problem at all with, in my opinion, elegant results reported.
We thank the reviewer for the positive outlook of our manuscript.
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Referee #2
Evidence, reproducibility and clarity
This is a compelling study that reports a key discovery to understand the molecular mechanism of ultrafast endocytosis. The authors demonstrate that the Dynamin splice version 1xA (Dynamin 1xA) uniquely binds Endophilin A, in contrast to Dynamin splice version 1xB (Dynamin 1xB) that does not bind Endophilin A and it is not required for ultrafast endocytosis. In addition, the Endophilin A binding occurs in a dephosphorylation-regulated manner. The study is carefully carried out and it is based on high quality data obtained by means of advanced biochemical methodologies, state-of-art flash-freezing electron microscopy analysis, superresolution microscopy and dynamic imaging of exo-and endocytosis in neuronal cultures. The results convincingly support the conclusions.
Although additional experiments are not essential to support the claims of the paper there is room, however, for improvement within the pHluorin experiments. These experiments, that are clearly informative and consistent with the rest of experimental data, do not apply the useful approach to separate endo- from exocytosis. The use of bafilomycin or folimycin to block the vesicular proton pump allows the unmasking the endocytosis that is occurring during the stimulus, that should correspond to ultrafast endocytosis. It would be very elegant to demonstrate that such a component, as expected according to the electron microscopy data, requires the binding of Endophilin A to Dynamin 1xA. If the authors have the pHluorin experiments running, the suggested experiments are very much doable because the reagents and the methodology is already in place and the new data could be generated in around six weeks.
The methods are carefully explained. Some of the experiments are only replicated in two cultures and the authors should justify the reasons to convince the audience that the approaches used have enough low variability for not increasing the n number. The pHluorin experiments, however, are performed only in a single culture; they should replicate these experiments in at least 3 different cultures (three different mice).
Minor comments:
Prior studies referenced appropriately and the the text and figures are clear and accurate.
- The authors should discuss about the mediators (enzymes) responsible for dephosphorylation of phosphor-box 2 that is key for the Dynamin 1xa-Endophilin A interaction.
- It would be very helpful to include a final cartoon depicting the key protein-protein interactions regulated by dephosphorylation (activity) and the sequence of molecular events that leads to ultrafast endocytosis
Significance
This is a remarkable and important advance in the field of endocytosis. The study reports a key discovery to understand the molecular mechanism of ultrafast endocytosis. Scientist interested in synaptic function and the general audience of cell biologist interested in membrane trafficking will very much value this study. The mechanism reported will potentially be included in textbooks in the near future.
My field of expertise includes molecular mechanisms of presynaptic function and membrane trafficking.
I have not enough experience to evaluate the quality of the NMR experiments, however, I do not have any problem at all with, in my opinion, elegant results reported.
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Referee #1
Evidence, reproducibility and clarity
In this manuscript, Imoto et al. analyze the specific role of the Dynamin1 splice variant Dyn1xA in so-called ultrafast endocytosis, an important mechanism of synaptic vesicle recycling at synapses. In a previous publication (Imoto et al. Neuron 2022), some of the authors had shown that Dyn1xA, and not the other splice variant Dyn1xB, is essential for ultrafast endocytosis. Moreover, Dyn1xA forms clusters around the active zone for exocytosis and interacts with Syndapin 1 in a phosphorylation dependent manner. However, it was unclear which molecular interactions underlie the specific role of Dyn1xA. Here, the authors provide convincing evidence with pull down assays and CSP that Dyn1xA PRR interacts with EndophilinA1/2 with two binding sites. The first binding site lies in the part common to xA and xB, was previously characterized. The second site was previously uncharacterized, is specific for Dyn1xA, and is regulated by phosphorylation (phosphobox 2). The location of these splice variants and mutated forms at presynaptic sites correlate with the prediction made by the biochemical assays. Finally, the authors perform rescue experiments ('flash and freeze' and VGLUT1-pHluorin imaging experiments) to show that Dyn1xA-EndophilinA1/2 binding is important for ultrafast endocytosis. I find the results interesting, providing an important step in the understanding of the interplay between dynamin and the endocytic proteins interacting with it (endophilin, syndapin, amphiphysin) in the context of synaptic vesicle recycling. The manuscript is clearly written and for the most part the data supports the authors' conclusions (see specific comments below). However, there are some issues which need to be clarified before this manuscript is fully suitable for publication.*
Introduction: the dynx1B Calcineurin binding motif is written PxIxIT consensus but actual sequence is PRITISDP. Is this a typo? Figure 1: the difference between the constructs used in panels C and D is not clear. In D, is it a truncation without residues 796 and 845? If so, it should be labelled clearly in the Western blots. In Panel E, Dyn1xA 746-798 should be labeled Dyn1x 746-798 because it is common to both splice variants. For amphiphysin binding the authors write that "No difference in binding to Amphiphysin 1 was observed among these peptides (Figure1D-F)." They should write that Dyn1x 746-798 does not bind Amphiphysin1 SH3 domain, confirming the specificity of binding to the 833-838 motif. Figure S2. The panels are way too small to see the shifts and the labelling. Please provide bigger panels Figure 2 panel B. There is a typo in the connecting line between the sequence and the CSP peaks. It is 846 instead of 864 (after 839). Figure 3 panel E. In the text, the authors write that "Western blotting of the bound proteins from the R838A pull-down experiment showed that R838A almost abolished both Endophilin and Amphiphysin binding in xA806-864 (Figure 3D), and reduced Endophilin binding to xA-PRR (Figure 3E)." I think they should write "only slightly reduced Endophilin binding..." it is more faithful to the result and consistent with the conclusion that Endophilin A1 has two binding sites on Dyn1xA PRR. It is unclear why the R846A mutant affects binding of Dyn1xA 806-864 but not Dyn1xA-PRR. Moreover, it affects binding to endophilin as well as amphiphysin, and therefore it is not specific. It is thus not correct to write that "R846 is the only residue found to specifically regulate the Dyn1 interaction with Endophilin as a part of an SDE". In the Discussion (page 11), the authors refer to the R846A mutation as specifically affecting Endophilin binding. This should be toned down, as it also affects Amphiphysin binding. For this important point, the data on quantification of Endophilin binding should be presented. Figure 3F-G: what do the star symbols represent in the graphs? I guess the abscissa represents retention time. Please write it clearly instead of a second ordinate for molecular mass, which does not make much sense if this reflects the estimate for the 3 conditions. Figure 4: The statement that "By contrast [to Dyn1xA], Endophilin A1 or A2 formed multiple clusters (1-5 clusters)" is not at all clear on the presented pictures. The authors should provide views of portions of axons with several varicosities, for the reader to appreciate the cases where there are more EndoA clusters than Dyn1 clusters. Moreover, overexpression of EndophilinA1/2-mCherry is not sufficient to assess its localization. Please consider either immunofluorescence of genome editing (e.g. Orange or TKIT techniques). The analysis of the confocal microscopy data is not explained. How is the number of clusters determined? How far apart are they? Confocal microscopy may not have the resolution to distinguish clusters within a synapse. For the STED microscopy, a representation of the processed image (after deconvolution) and the localization of the peaks would be important to assess the measurement of distances. If Dyn1xA S851/857D is more diffuse, are there still peaks to measure for every synapse? Figures 5 and 6: No specific comment. The data and its analysis is very nice and elegant. The comment on the lack of rescue of Dyn1xA on endosome maturation may be a bit overstated, because many "controls" (shRNA control Figure S5 or Dyn3 KO in Imoto et al. 2022) have a significant number of endosomes 10 s after stimulation. By the way, why did the authors use Dyn1 KO in this study, and not Dyn1.3 DKO as in Imoto et al. 2022? In the Discussion, the authors present the binding sites (for endophilin and amphiphysin SH3 domains) as independent. However, these proteins form dimers or even multimers as they cluster around the neck of a forming vesicle. Even though they provide evidence in vitro (Figure 3) that in these conditions of high concentration one dyn1xA-PRR binds one SH3 domain, in cells multiple binding sites on the PRR to these proteins may involve avidity effects, as discussed for example in Rosendale et al. 2019 doi 10.1038/s41467-019-12434-9. For example, the high affinity binding of Dyn1-PRR to amphiphysin cannot be explained only by the sequence 830-838.
Significance
This study provides a significant advance on the mechanisms of dynamin recruitment to endocytic zones in presynaptic terminals. The work adds a significant step by experienced labs (Robinson, Watanabe) who have provided important insight in the mechanisms by many publications in the last years.
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Reply to the reviewers
Please find below a point-by-point reply to the reviewers, with our comments in plain text, and reviewer comments in italics. Direct quotations of MS revisions in the below point-by-point reply are in quotation marks.
*Reviewer #1 (Evidence, reproducibility and clarity (Required)):
**The manuscript "Circadian regulation of protein turnover and proteome renewal" investigates the role of protein degradation in the circadian control of proteostasis. The researchers suggest that the relatively static levels of protein levels in a cell are incongruent with the known oscillation in protein synthesis. They therefore hypothesize that there should be a compensatory mechanism to counteract rhythmic protein synthesis, rhythmic protein degradation. To investigate this, they employ bulk pulse chase labeling to study the process of degradation. They identify a synchronization between the creation and turnover of proteins in a cell, implying the clock helps to maintain homeostasis through a novel mechanism. They note that these phases align with energy availability, granting a plausible reasoning behind the biological implementation of this regulation. In summary, this is a sound manuscript that adds to the research field. The experiments in this manuscript are well thought out, organized, and explained. In general, the authors do not go further in their conclusions than I think is warranted given the data that they have, though I think that there are some key items that should be addressed before the publication of this manuscript. *
Thank you for reading and appreciating our work
Major notes: 1) In figure 1, a clearer idea of what the ** means would be appreciated. What was the standard of significance for this measure?
Thank you, this was already reported in the methods section but is now reported in the figure legend also.
* 2) In Figure 1b, it is important to note clearly in the text that the this is not a direct measure of protein degradation, but a subtractive proxy. Though I don't think that necessarily makes the authors conclusions incorrect, the same result could also be obtained if an extra 15% of the proteins were moved into the insoluble fraction. This is the same for Figure 1E and F. *
Considering only the pulse shown in the left-hand graph of 1B, the reviewer is correct that this could arise by rhythmic partitioning of nascently synthesised proteins between digitonin-soluble and insoluble fractions. This could not readily explain the variation in the % of nascently synthesised digitonin-soluble protein that is degraded however (right hand graph), hence the need for pulse-chase rather than pulse alone. As such, we do not exclude circadian-regulated solubility of nascently synthesised protein or that there is a rhythm of protein synthesis in the soluble fraction, both are likely true. Rather Figure 1B indicates the relative proportion of nascently-synthesised protein in the soluble fraction that is degraded within 1h of synthesis is not constant over time. This is consistent with current understanding of the regulated increase in activity of protein quality control mechanisms (including proteasome-mediated degradation) that are required to maintain protein homeostasis upon an increase in bulk translation (Gandin and Topisirovic, Translation, 2014).
In contrast, the lysates probed in Fig 1F were extracted in denaturing urea/thiourea buffer and so cannot be explained by variation in protein solubility.
Considering 1E, to explain this result entirely through solubility changes would require that puromycinylated polypeptides to become more soluble, at discrete phases of the circadian cycle, but only when the proteasome is inhibited. Whilst we cannot formerly exclude this possibility, we are not aware of evidence to support it, whereas there is prior evidence supporting circadian regulation of protein synthesis and proteasome activity.
To communicate all of this more clearly we have made the following revisions to the text:
Page 6: ".The experiment was performed over a 24h time series followed by soluble protein extraction using digitonin, which preferentially permeabilises the plasma membrane over organelle membrane."
Page 6: " Importantly, the proportion of degraded protein varied over time, being highest at around the same time as increased protein synthesis (Fig 1B), indicating time-of-day variation in digitonin-soluble protein turnover which cannot be solely attributed to previously reported circadian regulation of protein solubility (Stangherlin et al, 2021b). Rather, it suggests that global rates of protein degradation may be co-ordinated with protein synthesis rates, and may vary over the circadian cycle."
Fig 1a legend: "...with digitonin buffer"
Fig 1e legend: "...in digitonin buffer"
Fig1f legend: "... and extracted with urea/thiourea buffer"
* 3) In figure 1c, is the noted oscillation in protease activity due to the oscillation of these proteins? What are the predicted mechanisms behind this? I don't think that this is necessarily within the scope of this paper but should be addressed in the discussion. Also, the peak degradation rate from Figure 1B is 4 hours before the peak enzyme activities. How can this observation be reconciled? *
Besides this study, our two previous proteomic investigations of the fibroblast circadian proteome detected no biologically significant or consistent rhythm in proteasome subunit abundance (Wong et al., EMBO J, 2021; Hoyle et al., Science Translational Medicine, 2017). Moreover, proteasomes are long-lived stable complexes whose activity is determined by a combination of substrate-level, allosteric and post-translational regulatory mechanisms that includes their reversible sequestration into storage granules (Albert et al., PNAS, 2020; Fu et al., PNAS, 2021; Yasuda et al., Nature, 2020). It is therefore very likely that the observed rhythm in trypsin- and chymotrypsin-like activity occurs post-translationally. Proteasome subunit composition is also known to change, which might be another reason for differences between the protease activities (Marshall and Vierstra, Front Mol Biosci, 2019; Zheng et al., J Neurochem, 2012).
Due to the nature of the experiment, the degradation rate inferred from Figure 1B does not reflect proteasome activity, exclusively. Rather it reflects the combined sum of processes that remove nascently produced proteins from the cell's digitonin-soluble fraction, which includes proteasomal degradation, but also autophagy, protein secretion and sequestration into other compartments. Therefore, the peak degradation in Fig 1B would not necessarily be expected to coincide with the peak of proteasome activity in Fig 1C. Figure 1A/B is intended as an exemplar for the investigation's rationale and was the first to be performed chronologically.
To communicate this succinctly, we have revised the relevant text as follows:
Page 7: "Previous proteomics studies under similar conditions have revealed minimal circadian variation in proteasome subunit abundance (Wong et al, 2022), suggesting that proteasome activity rhythmicity, and therefore rhythms in UPS-mediated protein degradation, are regulated post-translationally (Marshall & Vierstra, 2019; Hansen et al, 2021)"
* 4) For the pSILAC analysis, the incorporation scheme has a six-hour window between the comparison of the light and heavy peptides. This makes it somewhat difficult to assess whether you are looking a clock effect from T1 or T1+6. This does not negate the findings, but it does question when the synthesis is occurring and what is being compared, which I think should be more clearly discussed in the manuscript. This is discussed later in the manuscript but should be mentioned in this section. *
Thank you for this suggestion. To communicate this more clearly, we have rearranged the labels at the top of schematic graphs in figures 2b and 3b in order to clearly distinguish the pulse-labelling window from the time of sample collection. The following text has been added to the methods section:
Page 9: "To enable sufficient heavy labelling for detection, a 6h time window was employed, thus measuring synthesis and abundance within each quarter of the circadian cycle "
* 5) There are no error bars on figure 2C. What the pSILAC just done in a singlet? If so, the rhythms estimation is likely a large overestimate and should be noted. *
This first pSILAC experiment was performed in singlet with respect to external time for the RAIN analysis, but is duplicate for the two-way ANOVA that is also reported, by treating each cycle as a separate replicate. In fact, the 6.2% of proteins that were significantly rhythmically abundant by RAIN actually agree well with two previous experiments we performed using mouse fibroblasts under identical conditions: the first with 3h resolution over 3 cycles in singlet (7% rhythmic), the second with 4 biological independent replicates over one cycle (8% rhythmic) (Wong et al., EMBO J, 2021). The curve fits shown in 2C are the standard damped sine wave fits, with p-values from RAIN reported in the figure legend.
Most importantly however, and as noted in the text, the absolute % of rhythmically abundant proteins is rather irrelevant and indeed the absolute numbers of 'rhythmic' proteins can vary wildly, dependent on the analysis method and stringency. The only important point to be gleaned from the estimates shown in Figure 2e is that by either statistical test, most rhythmically abundant proteins are not rhythmically synthesised, and vice versa; however, the % of proteins that are both rhythmically synthesised and rhythmically abundant is 6 to 11--fold higher than would be expected by chance (taking proteins rhythmic by RAIN and ANOVA, respectively; in both cases the overlap between the two sets is highly significant) . This serves as a positive control, i.e., a minority of proteins show correlated rhythms of synthesis and abundance that are consistent with the canonical activity of 'clock-controlled genes' which cannot be explained by overestimation of rhythmicity.
Odds Ratio comparison synthesis vs total
Synthesis rhythmic by RAIN - listA size=148, e.g. A8Y5H7, B2RUR8, E9Q4N7
Total rhythmic by RAIN - listB size=149, e.g. A1A5B6, A2A6T1, A2AI08
Intersection size=34, e.g. A8Y5H7, O08795, O54910
Union size=263, e.g. A8Y5H7, B2RUR8, E9Q4N7
Genome size=2528
Contingency Table:
notA inA
notB 2265 114
inB 115 34
Overlapping p-value=5.4e-13
Odds ratio=5.9
Overlap tested using Fisher's exact test (alternative=greater)
Jaccard Index=0.1
Synthesis rhythmic by ANOVA - listA size=66, e.g. A8Y5H7, O35639, O55143
Total rhythmic by ANOVA - listB size=83, e.g. A8Y5H7, B2RQC6, E9Q6J5
Intersection size=16, e.g. A8Y5H7, P22561-2, Q3TB82
Union size=133, e.g. A8Y5H7, O35639, O55143
Genome size=2528
Contingency Table:
notA inA
notB 2395 50
inB 67 16
Overlapping p-value=9.7e-11
Odds ratio=11.4
Overlap tested using Fisher's exact test (alternative=greater)
Jaccard Index=0.1
Nevertheless, we agree with the reviewer's general point and have revised the text as follows:
Page 9: "... and may be susceptible to overestimation of rhythmicity."
Page 9: "Consistent with similar previous studies, Page 9: "The proportion of such proteins was more than expected by chance (pMethods, Page 21: "...(n=1 per timepoint)"
* 6) Why were the genes selected in 2C? these are not discussed anywhere else in the manuscript.*
These are simply illustrative examples so that the reader can better understand what we mean, i.e., two proteins in different phases and one that did not change, all within a similar range of abundance. The selected proteins were not discussed because we do not expect the reader to attach any specific meaning to them. We have revised the figure to include in 2C examples of each rhythmicity category shown in 2E. To make this clear, we now state the following:
Figure 2 legend: "No specific meaning is inferred from the protein identities”.
- 7) The authors note that for Figure 2 "These observations are consistent with widespread rhythmic regulation of protein degradation." However, only 5-10% of the proteome is oscillating at any level and less with a discrepancy between synthesis and abundance, so "widespread" is an exaggeration and this statement should be limited to the degradation in the rhythmic proteome. *
We take the reviewer's point, but the term rhythmic proteome is also inaccurate since half the proteins with rhythmic degradation did not show an abundance rhythm in both mass spec experiments. We therefore revised this sentence as follows:
Page 10: "These observations are consistent with widespread temporal organisation of protein degradation within the circadian-regulated proteome."
* 8) The authors note that their more developed strategy in figure 3 would allow for the detection of less abundant proteins. However, they do not discuss that they in fact found less proteins overall, or if they were able to detect proteins of lower abundance. This is of some concern in determining if this is indeed the better method that they predict. How can the authors reconcile this issue? How can they rationalize this explains their increase in oscillating elements? *
Thank you for raising this point, we did not explain ourselves sufficiently clearly. As stated in the revised text, once we had analysed the first iteration of pSILAC (Fig 2), we realised that detection of heavy-labelled proteins was "inevitably limited and biased the proteome coverage towards abundant proteins with higher synthesis rates". In other words, in order to be considered in our analysis both unlabelled and heavy-labelled peptides needed to be detected in every sample at every time point. In fact, if we do not consider heavy-labelling, the overall coverage in the Fig 3 experiment (6577 proteins) was better than the Figure 2 experiment (6264 proteins), as expected, due to technical improvements in the methods used (by the time of the experiment in Fig. 3, we were able to perform the analysis using mass spectrometry techniques with better fractionation and detection, namely FAIMS and MS3). When the analysis criteria are applied however, this falls to 2302 and 2528 proteins, respectively. Because of the way that mass spectrometry works, many proteins needed to be excluded from analysis because the heavy label wasn't detected in one or more samples. In these cases, we cannot infer that no heavy-labelled protein was present in that sample or even that it was present at lower levels than other samples - it simply wasn't detected and therefore we cannot make any quantitative comparisons. Non-detection of any given heavy peptide may occur for several reasons, the most likely being that it co-elutes from the chromatography column at the same time as other much more abundant (light) peptides and simply escapes detection. This is an unavoidable limitation of the technique, we hope the reviewer can understand our need to restrict the analysis to those proteins whose nascent synthesis, and total abundance in the MMC fraction, can be confidently quantified.
As the experiments in Fig 2 and Fig 3 were performed independently, with separate TMT sets and different instrumentation, we are also unable to compare absolute abundances of the proteins between the two.
To communicate this more clearly we have amended Figures 2e and 3e to state the total coverage in the legends, as well as clearly stating the coverage of heavy-labelled proteins in the figure itself. We have also added the following explanation to the text:
Page 11:
“Despite enriching for only one cellular compartment, the overall coverage in this experiment was similar to the previous one (6577 and 6264 proteins, respectively), due to the altered and more targeted approach; with heavy peptides detected for 2302 proteins."
*9) In the comparison of complex turnover rates, the authors need to provide a metric that backs their statement that "the majority of component subunits not only showed similar average heavy to total protein ratios but also a similar change in synthesis over the daily cycle" for figure 3F. *
Our apologies for this oversight, this is now presented in new Fig S3D.
* 10) In reference to the AHA incorporation, why is the hypothesis not that, like the puramycin, you would not see oscillation unless you add BTZ? Shouldn't the active degradation regulate the incorporation of AHA such that there is no visible rhythm unless you suppress degradation? *
AHA is a methionine analogue that is sparsely incorporated into polypeptide chains with minimal effect on protein function/structure (Dietrich et al., PNAS, 2006). Unlike puromycin, therefore, AHA does not lead to chain termination or protein misfolding/degradation (Dermit et al., Mol Biosyst, 2017) and so pulsed application at different phases of the circadian cycle is sufficient to reveal protein synthesis rhythms. The novelty in Fig 3H is the combination of AHA labelling with native PAGE that allows us to validate rhythmic production of high molecular weight protein complexes. This would not be possible with puromycin because prematurely-terminated polypeptide chains are not able to assemble into native complexes unless chain termination happens to occur at the extreme C-terminus and the C-terminus does not partake in any intermolecular interactions within the assembled complex.
* 11) The authors claim that there is enrichment of the actin cytoskeleton, but where this data can be found should be explained. The only thing that is shown is a few selected graphs of proteins in this pathway. *
We previously reported circadian regulation of the actin cytoskeleton in Hoyle et al. (Sci Trans Med, 2017). The extremely high relative amplitude of Beta-actin (the structural component of microfilaments) in the MMC fraction is, in and of itself, entirely sufficient to demonstrate a circadian rhythm in the relative ratio of globular to filamentous actin that was originally identified by Ueli Schibler's lab (Gerber et al., Cell, 2013) and then shown to have a cell-autonomous basis in fibroblasts in Hoyle et al (2017). We have included further examples of an actin-binding protein (Corinin1b) and a motor protein (Myosin 6) to further illustrate this, but do not feel further discussion is warranted because it was comprehensively addressed in our previous work. The enrichment for actin was determined by GO analysis, which is now shown in the Fig 4A and referred to in the text.
The important point in Fig 4C is the difference in phase with the examples shown in Fig 4B and summarised in Figure 4A, i.e., there are a small number of proteins whose presence in the MMC fraction is highest in advance of the majority of rhythmically abundant proteins, but this earlier group doesn't show any significant synthesis rhythm. Actin is one of the most abundant cellular proteins, and by mass it accounts for 67% of the circadian variation of rhythmically abundant proteins that peak in this fraction at the same phase. All these data and analyses are available for scrutiny in Supplementary Table 2.
To communicate this more clearly we have expanded on this point as follows:
Page 13: " These proteins were enriched by 9-fold for actin and associated regulators of the actin cytoskeleton (q* 12) The authors note an oscillation in the total levels of p-eif2, commenting that these do not arise from the rhythms in total eif2a but temperature and feeding rhythms. However, unless I misunderstood, this work was done in fibroblast cell culture, so in this case, where would these temperature and feeding rhythms come from? *
We were insufficiently clear. Daily rhythms of p-eIF2 have been observed under physiological conditions in mouse, in vivo. We do not observe similar rhythms in cultured fibroblasts under constant conditions unless the cells are challenged by stress. By inference therefore, it seems likely that daily rhythms of p-eIF2 in vivo arise from the interaction between cell-autonomous mechanisms and daily systemic cues such as, insulin/IGF-1 signalling and body temperature that are in turn driven by daily rhythms in CNS control, daily feed/fast rhythms and daily rest/activity rhythms, respectively. We have amended the text as follows:
Page 15: "...and so suggest that daily p-eIF2α rhythms in mouse tissues likely arise through the interaction between cell-autonomous mechanisms and daily cycles of systemic cues, e.g., insulin/IGF-1 signalling and body temperature rhythms driven by daily feed/fast and rest/activity cycles, respectively."
* 13) In Figure 5d, the treatment impeding degradation is causing cell death while the inhibition of translation does not. However, wouldn't too much, or not enough, translation, without compensatory regulation from degradation cause a problem in the same way that degradation does? *
It is well-established that acute treatment with high concentrations of proteasomal inhibitors rapidly leads to proteotoxic stress that will trigger apoptosis unless resolved (Dantuma and Lindsten, Cardiovasc Res, 2010). Treatment with CHX is certainly stressful to cells, but in a different way, and cells die through mechanisms generally regarded to be necrotic and certainly do not involve the canonical proteotoxic stress responses that are activated by MG132 and similar drugs. Our findings show that, by whatever mechanisms cells die with CHX treatment, it does not change over the circadian cycle whereas death via proteotoxic stress does, consistent with our prediction. We hope the reviewer agrees it is beyond the scope of our study to explain why CHX-mediated cell death does not show a circadian rhythm in mouse fibroblasts.
*Reviewer #1 (Significance (Required)):
*The information that stems from this work is relevant and of interest to circadian clock field as how the regulation of the output of the circadian clock is implemented is still a major question in the field. This manuscript suggests a novel and plausible method for how, at least in part, this regulation occurs. However, the manuscript uses methods that do not measure degradation directly, which is a minor limitation. In addition, the mechanisms by which this regulation is imparted are not addressed in any meaningful way, even in the discussion.
We are sorry that we did not adequately discuss the extensive previous work that has already addressed regulatory mechanisms. We would like to stress that this manuscript concerns protein turnover and proteome renewal, of which degradation is obviously an important part but not the sole focus.
To communicate this more clearly, we have amended the title to:
"Circadian regulation of macromolecular complex turnover and proteome renewal"
... which we previously explicitly predicted in the discussion of previous papers (Feeney et al., Nature, 2016; O'Neill et al., Nat Comms, 2020; Wong et al., EMBO J, 2022) and our recent review (Stangherlin et al., Curr Opin Syst Biol, 2021).
With respect to measurement of degradation - Physiologically, cellular rates of proteasomal degradation are so intimately coupled with protein synthesis that, over circadian timescales, the former cannot meaningfully be studied in isolation. It is possible that the reviewer is alluding to historical methods that measure change over time in the presence of translational or proteasomal inhibitors, but these have long been known to introduce artifacts - because translational inhibition rapidly leads to reduced proteasome activity, whereas proteasomal inhibition rapidly reduces protein synthesis rates through the integrated stress response. We would be interested to hear of any more direct method for measuring protein degradation proteome-wide than the pulsed SILAC method we developed, as we are not aware of any. Even proteasomal proximity labelling coupled with MG132 treatment, recently developed by the Ori lab, does not directly measure degradation (bioarxiv https://www.biorxiv.org/content/10.1101/2022.08.09.503299v1). By definition, degradation can only be measured through the disappearance of something that was previously present, usually by comparing its rate of production with the change in steady state concentration (if any), which we have done using multiple methods.
With respect to regulation of degradation - We speculated on the mechanisms regulating rhythms in protein turnover in our several previous papers (Feeney et al., Nature, 2016; O'Neill et al., Nat Comms, 2020; Wong et al., EMBO J, 2021; Stangherlin et al, Nat Comms, 2021), whereas outside the circadian field these mechanisms have been addressed extensively. This was also discussed in detail in our recent review on the topic (see Stangherlin et al., COISB, 2021). In this review, we lay out the evidence for a model whereby most aspects of circadian cellular physiology might be explained by daily rhythms in the activity of mammalian target-of-rapamycin complexes (mTORC). This model makes multiple predictions and informs the central hypothesis which is tested in the current manuscript: that circadian rhythms in complex turnover and proteome renewal should be prevalent over abundance rhythms. An enormous body of work over the last two decades has already clearly established mTORC1 as the master regulator of bulk protein synthesis and degradation, and a substantial number of independent observations have demonstrated circadian regulation of mTORC1 activity in vivo and in cultured cells. The mechanisms that drive cell-autonomous mTORC1 signalling are only partially understood (e.g. Feeney et al., Nature, 2016; Wu et al., Cell Metab, 2019), and we continue to explore this experimentally but they certainly lie well beyond the scope of this investigation.
Therefore, to address the reviewer's concern about inadequate discussion of mechanism, we have expanded on mTORC in the introduction and discussion, as follows:
Page 3: "Daily rhythms of PERIOD and mTORC activity facilitate daily rhythms of gene expression and protein synthesis. In particular, mTORC1 is a master regulator of bulk 5'-cap-dependent protein synthesis, degradation and ribosome biogenesis (Valvezan & Manning, 2019) whose activity is circadian-regulated in tissues and in cultured cells (Ramanathan et al, 2018; Feeney et al, 2016a; Stangherlin et al, 2021b; Mauvoisin et al, 2014; Jouffe et al, 2013; Sinturel et al, 2017; Cao, 2018). It is plausible that daily rhythms of mTORC activity underlie many aspects of daily physiology (Crosby et al, 2019; Stangherlin et al, 2021a; Beale et al, 2023b)."
Page 17: "The mechanistic underpinnings for cell-autonomous circadian regulation of the translation and degradation machineries remain to be fully explored, but are likely to be driven by daily rhythms in the activity of mTORC: a key regulator of protein synthesis and degradation as well as macromolecular crowding and sequestration (Stangherlin et al, 2021b, 2021a; Cao, 2018; Adegoke et al, 2019; Ben-Sahra & Manning, 2017; Delarue et al, 2018). In particular, global protein synthesis rates are greatest when mTORC1 activity is highest, in tissues and cultured cells, whereas pharmacological treatments that inhibit mTORC1 activity reduce daily variation in crowding and protein synthesis rates (Feeney et al, 2016a; Lipton et al, 2015; Stangherlin et al, 2021b). Given our focus on proteomic flux and translation-associated protein quality control, autophagy was not directly within the scope of this study but is also mTORC-regulated and subject to daily regulation (Ma et al, 2011; Ryzhikov et al, 2019). In vivo, daily regulation of mTORC activity arises primarily through growth factor signalling associated with daily feed/fast cycles (Crosby et al, 2019; Byles et al, 2021). The mechanisms facilitating cell-autonomous circadian mTORC activity rhythms are incompletely understood but may include Mg.ATP availability (Feeney et al, 2016a) and its direct regulation by PERIOD2 (Wu et al, 2019). This will be an important area for future work."
*Reviewer #2 (Evidence, reproducibility and clarity (Required)):
Summary: This is a very interesting and well written paper that addresses key questions in the circadian organization of proteostasis. The paper investigates origins of cellular circadian rhythms, invoking a premise early that there is a poor correlation between rhythmic gene expression - regulated by the canonical TTFL - and rhythms of the proteome, which are rather meager. Specifically, they ask how a relatively stable proteome is possible if cells engage in rhythms of cellular protein synthesis? Their hypothesis is that protein degradation must rhythmically compensate for rhythms of synthesis and much of the manuscript is focused on defining the relationship between rhythmic global synthesis and rhythmic degradation. They employ a series of detailed proteomic investigations and biochemical assessments of protein synthesis coupled with various circadian reporters to assess proteosome function. The proteomic experiments reveal a limited number of proteins with oscillations in either synthesis or abundance or both and no discernible pathway organization however, a followup and more refined study that utilized fractionated samples and boosted heavy SILAC identified strikingly, that many proteins in relatively heavy fractions are rhythmic and that these fall into possible complexes including ribosome and chaperonins. Finally, they perform in vivo experiments testing whether the timing of proteotoxic stimuli regulates the degree of the integrated stress response measured as pEif2a. Overall, I think that this is a fascinating paper that addresses and important question but falls short on mechanistically unifying them and completely contextualizing the findings in light of the canonical modes of circadian timekeeping leaving us with an important, but mostly descriptive set of findings. In addition, there are a number of important questions about data interpretation, some issues with data quality that should be addressed outlined below. With revision and further explication, this study will be an excellent addition to the growing field of circadian organization of the cellular proteome. *
Thank you for reading and appreciating our work
*Major and minor Comments. Figure 1. Fig 1a. The difference in Pulse and Chase at ZT24 does not appear to reflect the quantified data in 1b. This should be reconciled to make the figure convincing. *
When working with radioactive cell lysates it is not possible to equalise the level of protein loaded on each gel beforehand as would happen with a western blot, for example. For this reason, the radioactive signal was normalised to the protein level subsequently measured by coomassie staining, as is standard practise for this type of assay, with all 4 replicates being shown in supplementary Fig.1A. An overnight phosphor screen image is presented in the main Fig.1A for illustrative purposes, but we take the point that this might not be immediately obvious. In revised Fig 1A we therefore now also show the relevant coomassie as well as labelling to make clear that the radioactive signal was normalised to protein levels.
* How was the timing of the chase collection determined? *
For these proof-of-principle experiments, we empirically determined the minimum duration of pulse and chase necessary to detect a quantifiable signal.
*Fig 1d-e. What is the evidence that puro labeling results in 'rapid' turnover. *
Apologies, this has been established for some time. Some additional papers are now cited in this section of the text (Liu et al, PNAS, 2012; Lacsina et al., PLoS One, 2011; Szeto et al., Autophagy, 2006)
*Fig 1e seems to be missing the data from the treated and untreated conditions? How are the lines produced (e.g. linear versus rhythmic? Are these drawn lines or actual regressions?). *
Fig 1e depicts the result of the experiment schematically explained in 1d. The only conditions were +Puro or +Puro+BTZ. There was no completely untreated condition, as puromycin incorporation is the basis of the assay (Lacsina et al., PLoS One, 2012; Szeto et al., Autophagy, 2006) and puromycin does not occur naturally in cells. We realise the figure could potentially be confusing without the associated raw data (anti-puromycin blots) - these are shown in supplementary Fig. 2A.
To explain the method more clearly, the following has been added to the results section where this experiment is described:
" As determined by anti-puromycin western blots, over two days under constant conditions, puromycin incorporation in the presence of BTZ showed significant circadian variation. In contrast, cells that were treated with puromycin alone showed no such variation, and nor did total cellular protein levels (Fig 1E, Fig S2A).”
The fit lines are produced by statistical comparison of fits, i.e., our hypothesis (damped cosine fit) vs null hypothesis (no or constant change over time, linear fit, y = mx+c), using sum-of-squares F test. The statistically preferred fit is plotted and p-value displayed on the graph, i.e., the regression line of the preferred fit and parameters are plotted. These details are reported in the figure legends.
* Why was 30 minutes chosen as labeling time? It seems hard to understand here how protein degradation kinetics can be measured by puromycin labeling if the authors' claim that puromycin labeling potentially changes degradation rates as a function - primary or secondary - of the labeling itself. It seems they are measuring the potential to degrade proteins. *
Puromycin labelling is a 20 year-old widely-used technique that can be employed in a range of applications. It was first used in a circadian context by Lipton et al (Cell, 2015) whose work we quickly followed (Feeney et al, Nature, 2016). Briefly, puromycin mimics tyrosyl-tRNA to block translation by labelling and releasing elongating polypeptide chains from translating ribosomes. When used at low concentrations (1 ug/mL in this case) puromycin is sparsely and sporadically incorporated into a small minority of elongating polypeptide chains. Those prematurely terminated chains have puromycin at the C-terminus, which can be detected by western blotting. We chose 30 minutes after optimisation experiments, as it was the shortest incubation time where a robust signal could be observed in these cells with this concentration of puromycin. The puromycinylated peptides are preferentially degraded by the ubiquitin-proteasome system because they are efficiently recognised as misfolded/aberrant proteins by chaperones within tens of minutes of being translated. Unless used at much higher concentrations, or over much longer timescales, there is no reason to believe that puromycin affects the degradation machinery itself, but the degradation of puromycinylated peptides depends on the proteasome. Therefore, puromycin+a proteasome inhibitor provides a reliable proxy for translation rate in the preceding 30 minutes, whereas puromycin alone tells us the steady state concentration under normal conditions, i.e., where proteasomes remain active. By subtracting the latter from the former we can infer the level of degradation of puromycinylated peptides that must have occurred in the previous 30 minutes. It is not a perfect technique, but its results agree with other findings in this manuscript: that protein turnover varies more than steady state protein abundance. With respect to the potential to degrade proteins, this is measured in Fig 1C.
* How do they determine that they are measuring degradation of functionally relevant proteins as opposed to a host of premature truncations? *
We do not. This is measured by stable isotope labelling in Figures 2-4. Figure 1 provides the rationale for what follows in subsequent figures, i.e., proof-principle experiments suggesting that turnover is not constant over the circadian cycle. No single experiment in Figure 1 is expected to convince the reader that of circadian turnover. Rather, several independent methods suggest that bulk protein synthesis and degradation (turnover) are not constant over time, and deviate from the null hypothesis with variation that appears to change over the 24h circadian cycle.
* Fig 1e bottom - again is this a true regression line? *
It is not a regression line, otherwise a p-value of fit would be shown. Fig1e bottom shows the bioluminescence measured at each timepoint from parallel control cultures (average of triplicates, error bars shown as dotted lines). Due to very high temporal resolution (every 30 min) and robustness of the cell line, it appears as a virtually perfect damped (co)sine wave. We apologise that this was not explained more clearly in the figure legend, now amended as follows:
"Parallel PER2::LUC bioluminescence recording from replicate cell cultures (mean +/- SEM, every 30 min) is shown below, acting as phase marker."
*Perhaps two time points should be examined here - similar to the pulse chase performed with 35S labeling? *
We are sorry we were not fully clear with our method here. The puromycin (+/- BTZ) labelling was performed over two days every 4h (so 12 timepoints in total), which can be inferred from the data points in the top two graphs in Fig. 1E, and x-axis - but is now also clearly stated in the figure legend. The bottom right graph was a continuous bioluminescence recording, integrated every 30 min from the set of parallel culture dishes. The bioluminescence data serves as a circadian phase marker, so that we can infer at which biological times synthesis and inferred turnover was higher vs lower.
We’ve adjusted the text to explain our method more clearly:
“Acute (30 min) puromycin treatment of cells in culture, with or without proteasomal inhibition (by bortezomib, BTZ), allowed us to measure both total nascent polypeptide production (+BTZ) and the amount of nascent polypeptides remaining when the UPS remained active (-BTZ). This allowed inference of the level of UPS-mediated degradation of puromycylated peptides within each time window, as a proxy for nascent protein turnover (Fig. 1D).”
* Fig 1f. It appears that Puro labeling results in a rhythm between ZT1 and ZT13 but no statistic is provided and appears that the 'ns' is the results of variance in the data as opposed to difference in means? - would this not contradict the cellular result? What accounts for the rhythm reversal in the presence/absence of BTZ. *
To be clear, we measured the level of puromycin incorporation in mouse liver in vivo following a similar method employed by Lipton et al, Cell, 2015 (Figure 2). The prediction was that, exactly as in cells (Fig 1E), treatment with a proteasome inhibitor would lead to a much greater increase in puromycinylated peptides at ZT13 than ZT1, because this is when protein synthesis is known to be higher and thus (we predict) protein degradation should also be higher. The experiment was not designed or powered to detect a time effect, it was designed to detect an interaction between time-of-puromycin treatment and BTZ, with the specific prediction being that BTZ would have a greater effect during the active phase. This is what we observed.
* While the authors have previously demonstrated an increase in rhythmicity of the proteome in Cry1/Cry2 double knockout cells, it would have been welcome here to test a global loss of circadian transcription in the degradation assay. One might expect that these rhythms would also be even higher. What I am really asking is: what is the mechanism for rhythmic degradation and is it dependent on the canonical clock? *
To address the reviewer's curiosity, we used the proteasome-Glo assay (also used in Fig 1C) to assess whether there was an interaction between genotype (WT vs CKO) and time at opposite phases of the circadian cycle over 2 days. We found a significant interaction by two-way ANOVA, indicating that components of the 'canonical clock' regulate the temporal organisation of proteasomal activity (see revised Figure S1). Circadian regulation of mammalian cellular functions, such as protein turnover, is a complex and dynamic process, whereas gene deletion affects the steady state and may be epistatic to phenotype rather than revealing gene function. We are therefore reluctant to speculate what this result means in the present manuscript, which is focused entirely on testing the hypothesis that global protein turnover and complex biogenesis have cell-intrinsic circadian rhythms in non-stressed, wild type cells.
To communicate this, the text has been revised as follows:
"Moreover, we detected a significant interaction between genotype and biological time when comparing trypsin-lik proteasome activity between wild type and Cryptochrome1/2-deficient cells, that lack canonical circadian transcriptional feedback repression (Fig S1B-E). "
* **Fig 2. How was the 'fixed window' timeframe determined? *
A trial experiment was performed with labelling windows of various length, and 6h was determined to be the shortest window where enough heavy label incorporation was detected to be able to assess circadian changes. This was the case with our first methodology, which was subsequently improved (Figure 3), and therefore labelling window reduced to 1.5h.
* *Fig 3h. While admittedly difficult, the native PAGE is not of great quality and kind of unconvincing. Also not really sure why the AHA labeling is used here an nowhere else in the paper.
AHA is a methionine analogue that is sparsely incorporated into polypeptide chains with minimal effect on protein function/structure (Dietrich et al., PNAS, 2006). Unlike puromycin, therefore, AHA does not lead to chain termination or protein misfolding/degradation (Dermit et al., Mol Biosyst, 2017). In Figure 1, the aim was to validate previous reports of rhythmic protein synthesis assess whether there was any evidence for rhythmic turnover. To this end, we employed two independent methods (35S-labelling and puromycin-incorporation). We did not want to rely on AHA for measuring turnover: although it has been validated and used for this purpose in some studies (McShane et al., Cell, 2016), AHA is not fully equivalent to methionine, and cellular aminoacyl-tRNA synthetases have much higher affinity to methionine than they do to AHA (Ma and Yates, Expert Rev Proteomics, 2018). It is thus impossible to perform AHA labelling without methionine-free medium, and in turn methionine starvation and media changes are known to have an effect on cell signalling and cell metabolism, which would be particularly pronounced in circadian context (over days rather than over hours).
By contrast, in Fig 3H, we use AHA with native PAGE to specifically validate one inference from the mass spectrometry analyses: circadian production of high molecular weight protein complexes. This would not be possible with puromycin because prematurely terminated polypeptide chains are not able to assemble into native complexes unless chain termination happens to occur at the extreme C-terminus and the C-terminus does not partake in any intermolecular interactions within the assembled complex.
The raw data (full gels, all replicates) are presented in Figure S2e, which of course was used for quantification. We have now picked a different example for the main figure, which hopefully allows for clearer representation.
The text in the results section describing the AHA experiment is now amended as follows:
" To validate these observations by an orthogonal method, we pulse-labelled cells with methionine analogue L-azidohomoalanine (Dieterich et al, 2006). AHA is an exogenous substrate, that cells have lower affinity to than methionine, and it could potentially impact on stability of the labelled proteins (Ma & Yates, 2018) – therefore, we only used AHA to assess nascent complex synthesis, rather than turnover. We analysed the incorporation of the newly synthesised, AHA labelled proteins into highest molecular weight protein species detected under native-PAGE conditions (Fig 3H, S3F). We observed a high amplitude daily rhythm of AHA labelling, indicating the rhythmic translation and assembly of nascent protein complexes. Taken together, these results show that daily rhythms in synthesis and degradation may be particularly pertinent for subunits of macromolecular protein complexes"
Fig 4. I was a little disappointed here that the authors did not directly assess macromolecular assembly of at least one of their "hits" and demonstrate functional relevance and most of the analysis is maintained at a very superficial, systemic level. STRING assemblies are not terribly helpful without clear k-means clustering or some other clearly visualizable metric for stratifying and organizing the putative PPI data - this figure (S3) could be markedly improved.
We agree that validation is important. The ribosome is by far the most abundant macromolecular complex in the cell, and was one of the major complexes to show clear evidence for circadian regulation of turnover, but not abundance, by our pSILAC proteomics. To validate this result, we took advantage of two important observations: (1) that all fully assembled ribosomes incorporate ribosomal RNA (rRNA) which can readily be separated from other cellular RNA by density gradient centrifugation; (2) pulse-labelling with heavy uridine-15N2 allows nascent RNA to be distinguished from pre-existing RNA. Thus, combining stable isotope labelling with ribosome purification, we can distinguish nascently assembled ribosomes from total when the RNA is extracted, digested with RNAse, and the % heavy/total UMP quantified by mass spectrometry. These data are presented in new figure 5, and are consistent with findings in Figures 3/4 that circadian regulation of ribosome turnover is prevalent over abundance, and that the phase of highest ribosome turnover coincides with the phases of high translation and turnover overall. We hope by addressing the reviewer's question by an entirely orthogonal method, they can share more confidence in our conclusions.
The statistical metric for STRING, specifically the p-value for enrichment in physical protein-protein interactions, is presented in the main Fig. 3G. It is now also reported in the legend for new Figure S4 itself.
* Is it possible that some macromolecular complexes have rhythms because their constituent proteins have differential half-lives when in one complex compared with another in circadian time? This possibility was not discussed. *
To our knowledge, there is no evidence that any major macromolecular complex in the cell has a functionally significant rhythm in abundance on a cell-autonomous basis. The reviewer’s suggestion is an intriguing possibility, but we can think of no way that it could be measured, even in principle. The simplest interpretation of our data from the independent techniques we employ (pSILAC with fractionation, native PAGE + AHA incorporation) is a rhythm in synthesis.
*Fig. 5. Why is the first histogram in 3c not at unity? *
This measures the average fold-induction in aggregation when cells are treated with MG132 for 4h at the indicated timepoints. Unity would indicate no induction at all, so the presented quantifications show that MG132 always elicited an increase in aggregation, with an effect size that varied with circadian phase.
* Do ZT24 and ZT48 differ, similarly do ZT36 and ZT60?*
No, neither difference is statistically significant (adjusted p-values of p=0.9 and p=0.07, respectively). This is now specified in the figure legend. Tendency to aggregate is also likely to change as a function of time in culture, which is why we think there is a slight increase overall in the second day of the experiment.
* Fig S4f is not of good quality with missing eIF2a total and therefore no loading controls. *
Thank you for prompting us to double-check this. We found that the levels of eIF2a were quite variable between the animals, and therefore we performed this experiment with 6 biological replicates. We have double-checked the quantification, and have now excluded 3 unreliable samples (the ones with undetectable levels of total eIF2a – ZT18 +BTZ replicate 1 & ZT18 -BTZ replicate 2, as well as ZT6 +BTZ replicate 4, where a smear does not allow for a reliable quantification of phospho-eIF2a) instead of 2 that were excluded originally. This still leaves at least 5 biological replicates in each group. In fact, the difference between BTZ and control in ZT6 is now deemed to be even more significant, going down to adjusted p=0.0007.
*S4e? true regression lines? *
The same method was used as in Figure 1. The fit lines are produced by statistical comparison of fits, i.e. our hypothesis (damped cosine fit) vs null hypothesis (no change over time, linear fit), using sum-of-squares F test. The statistically preferred fit is plotted and p-value displayed on the graph. These details are reported in the figure legends and methods section.
While I thought these experiments were effective, they did not tie back well to the rest of the paper. What are the consequences of a temporally sensitive ISR? Which pathways does it effect in circadian time? Here, the main holes in this study are somewhat exposed; namely, a lack of mechanistic depth in explaining the very fascinating, albeit mostly descriptive, findings. The implicit assumption made here is that aggregation is 'bad' but could the opposite be just as true? Taking these considerations in account would further strengthen the discussion.
The purpose of (former) Fig 5 was entirely to test the functional consequences and potential translational relevance of a daily rhythm in protein turnover. The mechanisms upstream and downstream of the ISR, and link with many diseases, are already quite well understood but we apologise that we did not draw more heavily on the prior literature to provide sufficient context for this experiment. Protein aggregation has long been associated with proteotoxic stress, and we do not assume it is good or bad, we simply use it as an additional validation of a temporally sensitive ISR. To correct this omission we have added the following to the results section before these experiments are introduced:
"Disruption of proteostasis and sensitivity to proteotoxic stress are strongly linked with a wide range of diseases (Wolff et al, 2014; Harper & Bennett, 2016; Labbadia & Morimoto, 2015; Hipp et al, 2019). Evidently, global protein translation, degradation and complex assembly are crucial processes for cellular proteostasis in general, so cyclic variation in these processes would be expected to have (patho)physiological consequences....
...Informed by our observations, we predicted that circadian rhythms of global protein turnover would have functional consequences for maintenance of proteostasis. Specifically, we expected that cells would be differentially sensitive to perturbation of proteostasis induced by proteasomal inhibition using small molecules such as MG132 and BTZ, depending on time-of-day."
Reviewer #2 (Significance (Required)):
This is a fascinating paper that addresses key questions in the circadian organization of the proteome. The paper's main findings are that rhythms of protein synthesis and degradation are temporally coordinated to maintain overall stability of the proteome in mouse fibroblasts. Furthermore, the authors present evidence that this temporal organization may be important for assembly of macromolecular complexes. While very interesting, the main limitations are a lack of biochemical and mechanistic explanation and evidence that verifies these, mostly descriptive, findings.
The fundamental biochemical mechanisms of protein synthesis, degradation, protein quality control and stress response have been studied for decades and are increasingly well understood, at least in cultured cancer cells. What is not understood is the extent to which all of these essential cellular systems are subject to physiological variation over the circadian cycle in quiescent cells. This is the fundamental knowledge gap our study attempts to fill by testing the discrete hypotheses that (1) circadian regulation of macromolecular complex turnover is more prevalent than abundance and that (2) proteome renewal is more prevalent than compositional variation. We suggest that establishing these essential principles of circadian cellular physiology is an essential prerequisite for performing the type perturbational experiments we presume the reviewer would prefer. We would like to reassure the reviewer that such studies have been and are being performed, but we are concerned that the inclusion of a very extensive additional body of work within this manuscript would detract from the clear communication of our major finding that complex turnover and proteome renewal has a cell-autonomous basis.
*There are some relatively minor statistical and data quality issues that are probably addressable relatively quickly.
**Upon revision the study would be a welcome addition to investigators interested in proteostasis, circadian biology, cell biology and proteomics.
**I am a physician-scientist with expertise in circadian rhythms, cell biology, protein synthesis, and biochemistry.
**Reviewer #3 (Evidence, reproducibility and clarity (Required)):
**Seinkmane et al investigate circadian regulation of protein synthesis and degradation in cultured cells and in mice. Their main new finding is that protein synthesis and degradation are in many cases rhythmic but coordinated such that the proteome is rhythmically renewed without an apparent rhythm in total protein abundance. Particularly the pool of large protein complexes is rhythmically renewed in this fashion.
Using pulsed SILAC in combination with mass spectrometry, the authors are able to distinguish between total and newly synthesized protein levels in mouse lung fibroblasts. Analysis of these data shows that the synthesis of a large number of proteins is rhythmic although the total amount is constant, or that proteins are synthesized at a constant rate but the total amount is rhythmic, suggesting that degradation is rhythmic. By analyzing macromolecular complexes, defined as a high-speed pellet, they also present evidence that the rhythmic components of large complexes oscillate in the same phase and have a similar protein turnover rate. The authors conclude that complexes assemble rhythmically. **The authors also present evidence that the activity of the proteasome oscillates in a circadian manner. Based on this observation, they show (in fibroblasts and in mice) that the response to proteotoxic stress (monitored by eIF2alpha phosphorylation levels, protein aggregation, and apoptosis) is higher at circadian times of high proteasome activity.
**I am an expert in the circadian field, and the hypothesis and concept behind the work presented here are potentially very interesting, and the experimental design is in principle suitable to answer these questions. However, after reading the paper several times, I cannot find the set of experiments that would convincingly support the authors' conclusions.
**Major questions/points:
*The major limitation of the manuscript is that the conclusions rely heavily on statistical analysis and massive processing of data from a bewilderingly large number of very different experiments. In looking at the figures, I have often wondered if the presence or absence of a rhythm is real or a product of the heavily processed data. The fact that a cosine wave fits through data points better than a straight line does not necessarily mean that a circadian rhythm is present.
We agree that comparison of fits alone does not provide sufficiently reliable evidence. However, the fact that many independent methods (cosinor, RAIN, ANOVA) yield similar overall findings lends more confidence to our findings. We would also argue that the large number of different experiments is a positive aspect of the paper and lends weight to the general conclusions. We instead ask the reviewer to consider an alternative question - we and many other labs have found no evidence for any change in total cellular protein content, and yet there is extensive evidence from independent labs for a 'translational rush hour' whilst (excepting some low abundance transcription factors) very few cellular proteins change by more than 10% over the circadian cycle (see Stangherlin et al, COISB, 2022 for extended discussion of this). We hypothesised a parsimonious explanation for this clear contradiction, and designed experiments whose data were analysed by widely used methods that yielded results that were consistent with prediction. Perhaps the reviewer will at least concede that, if the presented findings do not refute the hypothesis, it should not be rejected until a superior one is proposed?
* I think that in particular, the SILAC experiment(s) should be repeated and also performed with an arrhythmic control (such as CRY1/2 KO). *
Whilst we agree that CRY1/2 KO cells show no circadian regulation of transcription and much more variable rhythms in PER2::LUC activity than wild type controls (Putker et al., EMBO J, 2021), in our hands circadian rhythms in proteome composition and protein phosphorylation in CRY1/2 KO are at least as prevalent as in wild type cells (see Wong et al., EMBO J, 2022). Indeed, when we performed a proteasome activity assay in CRY1/2 KO fibroblasts, we observed there was an apparent circadian variation, similar to WT but with a different phase. These data are now presented in revised Figure S1. Similarly, Lipton et al (Cell, 2015) showed circadian translational rhythms in cultured Bmal1 KO cells (see final figure), therefore it is not clear what would constitute an appropriate 'arrhythmic' control.
In this study, for proteomics experiments, we used a combination of SILAC and TMT, as each technique alone would not be sufficient to answer our specific questions. These two techniques are very resource-intensive on their own, and even more so in combination. We therefore had to prioritise and for the second SILAC-TMT experiment decided to focus on cellular fractionation and questions pertaining macromolecular complexes, which were directly relevant to our hypothesis. While it would undoubtedly also be interesting to study how canonical clock genes, such as Cry1/2, impact turnover on a proteome-wide scale, the focus of our study is physiological regulation of proteome composition, rather than the function of Cryptochrome genes which we already explored in previous work (Putker et al., EMBO J, 2021; Wong et al., EMBO J, 2022).
Comparability between the whole cell and MMC SILAC experiments is also limited due to the different experimental conditions (6h vs. 1.5h pulse, +booster).
We do not make any direct comparisons, other than to report that broadly comparable numbers of proteins were detected. Implicitly this means there must be greater coverage of protein complexes in the second pSILAC experiment, which our data bears out. If we were not to report the first experiment, the reader would not understand why we refined the method used in the second. In reporting the results of the 6h pulse, we make the limitations of this experiment very clear i.e. biased towards highly abundant, highly turnover proteins, irrespective of cellular compartment. We should add that even in this experiment there was a clear trend towards rhythmic turnover of ribosomal proteins, but this did not quite achieve significance (p = 0.07) and so we did not want to make claims beyond the data.
*The essential and new message of the paper is that (at least some) macromolecular complexes undergo circadian renewal (degradation and synthesis). Rather than just analysing an operationally defined pellet fraction by mass spectrometry, this could be shown in more detail and directly for one or two specific macromolecular complexes. Ribosomes, for example, seem particularly suitable, because there would also be the very simple approach of measuring the synthesis of ribosomal RNA by pulse labelling. To me, such an analysis would be perfectly sufficient as a proof of principle. I would then omit aspects such as rhythmic stress response, since many additional experiments are needed to demonstrate this convincingly. *
Thank you for the excellent suggestion, we agree that validation is important. The ribosome is by far the most abundant macromolecular complex in the cell and was one of the major complexes to show clear evidence for circadian regulation of turnover, but not abundance, by our pSILAC proteomics. To validate this result, we took advantage of two important observations: (1) that all fully assembled ribosomes incorporate ribosomal RNA (rRNA) which can readily be separated from other cellular RNA by density gradient centrifugation; (2) pulse-labelling with heavy uridine-15N2 allows nascent RNA to be distinguished from pre-existing RNA. Thus, combining stable isotope labelling with ribosome purification, we can distinguish nascently assembled ribosomes from total ribosomes when the RNA is extracted, digested with RNAse, and the ratio of light to heavy UMP quantified by mass spectrometry. These data are presented in new figure 5, and are consistent with findings in Figures 3/4 that circadian regulation of ribosome turnover is prevalent over abundance, and that the phase of highest ribosome turnover coincides with the phases of high translation and turnover overall. We hope by addressing the reviewer's question by an entirely orthogonal method, he/she can share more confidence in our conclusions.
The final figure is included because it tests predictions that were informed by the preceding experiments. It is not intended to be comprehensive exploration of how the integrated stress response changes with the circadian cycle, nor have we claimed this.
* Specific points: The reader is strongly influenced by the cosine wave or straight lines in the graphs (e.g. 1c, e, 3h, 5b, etc) produced by the analysis of rhythmicity, which basically only gives a yes or no answer. But it is not really that simple. If the algorithm detects a rhythm what is its period? Is it the same as the period of the luciferase reporter? If the period lengths correlate, do the phases as well (e.g. see differences in phases 1c and e)? These questions are not addressed. *
The temporal resolution of the time course data is much lower than the luciferase reporter and so the error of the fit is greater (usually 1-2h). For the cosine wave curve fit and the associated extra sum-of-squares F test, the period of the oscillation was fixed at either 24h or 25h, as determined from a parallel PER2::LUC control recording. This is now explicitly stated in the methods section
In terms of phase, the general trend across all experiments is that bulk protein turnover, synthesis and degradation is higher during the 6-8h following the peak of PER2::LUC than at any other point in the circadian cycle. This is also consistent with our previous findings in mouse and human cells (Feeney et al, Nature, 2016; Stangherlin et al., Nat Comms, 2021) as well as findings from many different labs in vivo (e.g. Janich et al., Genome Res, 2016; Atger et al., 2015, PNAS; Sinturel et al., 2017, Cell). We are cautious about trying to be any more specific than this because each assay is measuring something different, and (as can be seen across the figures) there is also some modest variation in the phase of PER2::LUC between experiments, with respect the prior entraining temperature cycle (this will be reported in our forthcoming publication, Rzechorzek et al, in prep). To address the reviewer's point therefore, we have added the following to the discussion:
"Across all experiments in this study, we find that protein synthesis, degradation and turnover is highest during the 6-8h that follow maximal production of the clock protein PER2. This is coincident with increased glycolytic flux and respiration (Putker et al, 2018), increased macromolecular crowding in the cytoplasm, decreased intracellular K+ concentration and increased mTORC activity (Feeney et al, 2016a; Stangherlin et al, 2021b; Wong et al, 2022)."
* **The algorithm in Fig 1c predicts a rhythm for the chymotrypsin-like and the trypsin-like but not for the caspase-like activity. The peptide assay measures core proteasome activity independent of ubiquitylation and should therefore be dependent on proteasome concentration in the sample. How can then only two of the three proteasomal activities be rhythmic? Please elaborate and repeat with arrhythmic cells (e.g. CRY1/2 KO). The period length does not seem to correlate with the one of the reporter. Why is that? *
The arrhythmic controls idea is partially addressed in the response above. We did perform a proteasome activity assay in CRY1/2 KO fibroblasts, and observed daily variation similar to WT, albeit with a different apparent phase. These data are now shown in Figure S1, and referred to in the main text as follows:
"Moreover, we detected a significant interaction between genotype and biological time when comparing trypsin-like proteasome activity between wild type and Cryptochrome1/2-deficient cells, that lack canonical circadian transcriptional feedback repression (Fig S1B-E)".
Besides this study, our two previous proteomic investigations of the fibroblast circadian proteome detected no biologically significant or consistent rhythm in proteasome subunit abundance (Wong et al., EMBO J, 2021; Hoyle et al., Science Translational Medicine, 2017). Moreover, proteasomes are long-lived stable complexes whose activity is determined by a combination of substrate-level, allosteric and post-translational regulatory mechanisms that includes their reversible sequestration into storage granules (Albert et al., PNAS, 2020; , Fu et al., PNAS, 2021; Yasuda et al., Nature, 2020). It is therefore very likely that the observed rhythm in trypsin- and chymotrypsin-like activity occurs post-translationally. Proteasome subunit composition is also known to change, which might be another reason for differences between the protease activities (Marshall and Vierstra, Front Mol Biosci, 2019; Zheng et al., J Neurochem, 2012).
To communicate this succinctly, we have revised the relevant text as follows:
Page 7: "Moreover, we detected a significant interaction between genotype and biological time when comparing trypsin-like proteasome activity between wild type and Cryptochrome1/2-deficient cells, that lack canonical circadian transcriptional feedback repression (Fig S1B, (Wong et al, 2022)). Previous proteomics studies under similar conditions have revealed minimal circadian variation in proteasome subunit abundance (Wong et al, 2022), suggesting that proteasome activity rhythmicity, and therefore rhythms in UPS-mediated protein degradation, are regulated post-translationally (Marshall & Vierstra, 2019; Hansen et al, 2021)."
Regarding period length, we apologise for an oversight in Fig 1c: unlike all other experiments presented here, these fits were originally done with a flexible period length (between 20h and 36h). This has now been re-fitted in a similar manner to the other experiments (fixed period of 24h, same as the parallel PER2::LUC controls), and the updated data are presented. This has not influenced the results of the statistical tests (only changed the p-values slightly, but the significance levels remain the same).
Fig. 1a,b suggest that there is a rhythm in global protein synthesis with a significant peak at 40h. Yet, Fig. 1e suggests otherwise. How can that be? Also, the degradation graph (lower panel 1c) has to be plotted with the ratios calculated from the data points and not the heavily processed fitted graphs. This can be very misleading.
Fig1a,b was performed under quite different conditions to 1e. As described in the methods section, 35S-labelling experiments require a medium change during both pulse and chase (to replace normal Met with radioactive Met, and vice versa). To avoid growth factor/mTORC1-mediated stimulation of protein synthesis & turnover, these acute media changes must occur in the absence of serum; otherwise media changes would introduce artifacts. In contrast, puromycin labelling (Fig 1e) is performed without any media changes (as puromycin can be added directly to culture cell media), and therefore was performed in normal culture conditions of 10% serum. Thus, due to its well-established effect of growth factor/mTORC1 signalling on bulk translation rate, it is very likely that differences in the phase of translational rhythms between Fig1a,b and 1e are attributable to differing serum concentrations – this phenomenon of serum-dependency of phase is also described in Beale et al, 2023, bioRxiv https://doi.org/10.1101/2023.06.22.546020. The only important point, is that neither of these proof-of-principle experiments support the null hypothesis: that translation rate and turnover remains constant over the circadian cycle. Thus, the hypothesis being tested in Figure 1 is not rejected, and provides the rationale for the subsequent proteome-wide analyses.
With respect to 1E, given the variance of measurement, the curve fits to Puro and Puro+BTZ already serve to test whether there is any significant ~24h component, a ratio of the respective data points would simply compound the error of measurement. The degradation plot is provided purely for illustrative purposes to help the reader i.e. if these fits were true, what would be expected? We have revised the figure to more clearly communicate that the degradation plot is presented purely as a visual aid, labelled “inferred”, and now show ratio plots in revised Figure 1.
* **It also strikes me as odd that the amplitude of degradation increases (peak at 28h lower than at 30h) while the amplitude of the core clock oscillation dampens over time (peak at 54h higher than at 53h due to desynchronisation. Only two data values around 54h are responsible for the detected rhythm (2nd peak). Furthermore, phase and period do not agree with the rhythm of proteolytic activities shown in 1c. How can this be explained? *
Due to the nature of the experiment, the degradation rate inferred from Figure 1B & 1E does not reflect proteasome activity exclusively. Rather it reflects the combined sum of processes that remove nascently produced proteins from the cell's digitonin-soluble fraction, which includes proteasomal degradation, but also autophagy, protein secretion and sequestration into other compartments. Therefore, the peak degradation in Fig 1B & E would not necessarily be expected to coincide with the peak of proteasome activity in Fig 1C. Again, these experiments in Figure 1 simply serve to test the hypothesis (change over circadian cycle) vs the null hypothesis (no change over the circadian cycle).
To the question of amplitude increase, we speculate that this is due to metabolic changes in cultures over the course of three days – as serum and nutrients from the last medium change at T0 are depleted, cells need to increase degradation to promote turnover and recycling. As we suggest that the rhythms in turnover help cellular bioenergetic efficiency, it is quite plausible that amplitude increases as nutrient-concentrations fall. We are in process of further investigation into how exactly these rhythms vary with nutrient and serum status.i
* Regarding the MS data shown in Figure 2, is it possible to show a positive / quality control? Best would be MS data of Luciferase (or PER2,3, RevErb/alpha, DBP) to show oscillation of protein levels with the same phase and period as the reporter. *
Unfortunately, none of these low abundance transcription factors were detected in our MS runs. This is not surprising, given that their copy numbers are estimated at * In Fig. 2c examples of the 4 groups of proteins presented in 2e should be shown (both synthesis and total abundance arrhythmic, either one rhythmic or both rhythmic) and not just what appears to be random examples of rhythmic and arrhythmic proteins. *
As also requested by another reviewer, we have revised the figure to include examples of each of the rhythmicity categories. No specific meaning is inferred from the chosen protein identities.
Is it possible at all to distinguish between synthesis/turnover and assembly/disassembly of macromolecular complexes in the MMC SILAC experiment? If so, how?
We followed the established protocol originally developed in our collaborator Kathryn Lilley's lab, where it has previously been shown that most proteins in the MMC fraction are in macromolecular assemblies (Geladaki et al, Nat Commun, 2019). Proteins that are rhythmically abundant in this fraction, but without an accompanying synthesis rhythm (e.g. Beta-actin, see Hoyle et al., Sci Trans Medicine, 2017) can be reliably assumed to arise solely from rhythmic assembly/disassembly i.e. they are captured in this fraction when assembled, but lost, and therefore not detected, in this fraction when disassembled. However, in the case of rhythmic synthesis and abundance, it is not possible with this technique to directly infer that rhythmic synthesis of a given protein is responsible for its rhythmic assembly in a complex, though they do correlate.
Therefore, our new figure 5 (with thanks again for this suggestion) approaches this by an orthogonal method, relying on the important observations that a) ribosomes incorporate ribosomal RNA (rRNA) b) this can be readily separated from most other cellular RNA by density gradient centrifugation and c) pulse-labelling with heavy uridine-15N2 allows nascent RNA to be distinguished from pre-existing RNA. Using this technique, we validate a rhythm in production and assembly of mature ribosomes, with its peak consistent with the highest turnover time as measured in Figs 1 and 3, and MMC fraction proteomics (Supplemental table 3), at the descending phase of PER2::LUC.
* **Looking at Fig. 4b,c, what is the fraction of rhythmic proteins from the MMC experiment that also oscillate in either synthesis, total abundance or both in the whole cell? Is there a general correlation at all? Please show. *
There were no correlations greater than would be expected by chance (the sets of proteins rhythmic in either synthesis or degradation did not overlap significantly between whole-cell and MMC fractions, as determined by an odds ratio test).
To communicate this we have added the following text:
"It is also worth noting that although there were small sets of proteins that were rhythmic in both whole-cell (Figure 2) and MMC fractions (Figure 3), in both synthesis and total abundance, none of these four overlaps were higher than would have been expected by chance."
* **Why is the phase of the oscillating proteins different in the two experiments (compare Figs. 2f,g and 4a) and does either of them match with the phase of the PER2::LUC reporter, which should be the peak synthesis phase of the clock? *
This was a labelling error on our part, our apologies and thanks for drawing it to our attention. We had attempted to harmonise all these phase values so that they were mutually comparable between the two mass spec experiments, but omitted to update all the figures. They have now all been updated to be inter-consistent. From our experiments, the peak of PER2::LUC consistently precedes the timing of maximum bulk translation. This phase difference is, at least in part, attributable to the inactivation kinetics of firefly luciferase (see Feeney et al., J Biol Rhythms, 2016), i.e., under conditions of saturating luciferin substrate, PER2 protein abundance peaks several hours later than PER2::LUC activity when measured in longitudinal live cell assays.
* Regarding the sensitivity to MG132 in Fig. 5b it doesn't make sense that, while eIF2alpha phosphorylation is arrhythmic in untreated cells and the levels of eIF2alpha phosphorylation are (apparently) not exhibiting a rhythmic change by administration of MG132 at different circadian timepoints, the ratio of P-eIF2alpha with and without MG132 suddenly is. Please show in Fig. S4b quantifications of the individual experiments with and without MG132. What is presented in 5b is after all the ratio of ratios of quantifications of Western blots, each of which individually does not display any appreciable rhythm. For me this is two much of processing of data. In my opinion, the MG132 4h acute treatment must show a detectable rhythm.*
We apologise for being unclear in this panel and description. Our hypothesis concerned the fold-induction of the p-eIF2alpha:eIF2alpha ratio changing as a function of MG132 and time. Our reasoning being that the ratio may be more biologically-relevant as it is the relative change that cells sense and respond to, and not the absolute abundance of p-eIF2alpha. We applied a quantitative, two-channel fluorescent antibody technique to enable detection and quantification of p-eIF2alpha and eIF2alpha from each replicate at each time point from the same band of the same blot. We agree that no p-eIF2alpha rhythm is evident from a cursory inspection of any of the blots. This is due to the innate variance between dishes in extracted protein concentration, as well as the levels of basal eIF2alpha and its phosphorylation, and is the reason that we took great pains to be as quantitative as possible using the two-channel immuno-detection (LICOR). Due to the natural and stochastic variation in eIF2alpha levels and extraction between replicates and over time, it is difficult to get identical eIF2alpha loading to reveal the overlying rhythm in p-eIF2alpha, and furthermore, identical loading would give a misleading impression of the level of temporal variation of eIF2alpha levels. Quantification reveals temporal variation in the MG132 treated samples but not in the untreated controls (Supp Fig 5A) – suggesting that there may be circadian regulation of the cellular response to MG132 challenge, rather than a cell-autonomous p-eIF2alpha rhythm under basal conditions. We quantified fold-induction from MG132 vs untreated to present in Figure 6A. We have presented all the raw data in supplementary figure 5 for readers to validate through their own analysis.
*Minor:
In Fig. 1f please show dot blot with error bars as well as the individual experiments in the supplementals. Please check the graph legend (N>=3?) *
Thank you for pointing out these omissions. The dot blot with error bars is now shown in Fig. 1F, and the full gels are now included as Fig. S2B. The main figure legend for 1f has also had the following added (explaining the N numbers):s
"Four mice were used per condition, but in some cases one of the four injections were not successful i.e. no puromycin labelling was observed and so no quantification could be performed (full data in Fig. S2B)."
* Please explain the mechanism of the "booster" used in the second SILAC experiment. *
The following has been revised in the text:
" Namely, we added a so-called booster channel: an additional fully heavy-labelled cell sample within a TMT mixture (Klann et al, 2020). When the mixture is analysed by MS, heavy peptides from the booster channel increase the overall signal of all identical heavy peptides at MS1 level; at MS2 and MS3 this results in improved detection of heavy proteins in the other TMT channels of interest, and is particularly advantageous for the proteins with lower turnover that would fall below the MS1 detection limit without the booster."
*
**p10 3rd paragraph: S2e not S3e *
Thank you, this has been fixed.
p12 last paragraph please add reference to Figs. 5f,g
Thank you, this has been added.
*Reviewer #3 (Significance (Required)): *
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Referee #3
Evidence, reproducibility and clarity
Seinkmane et al investigate circadian regulation of protein synthesis and degradation in cultured cells and in mice. Their main new finding is that protein synthesis and degradation are in many cases rhythmic but coordinated such that the proteome is rhythmically renewed without an apparent rhythm in total protein abundance. Particularly the pool of large protein complexes is rhythmically renewed in this fashion.
Using pulsed SILAC in combination with mass spectrometry, the authors are able to distinguish between total and newly synthesized protein levels in mouse lung fibroblasts. Analysis of these data shows that the synthesis of a large number of proteins is rhythmic although the total amount is constant, or that proteins are synthesized at a constant rate but the total amount is rhythmic, suggesting that degradation is rhythmic. By analyzing macromolecular complexes, defined as a high-speed pellet, they also present evidence that the rhythmic components of large complexes oscillate in the same phase and have a similar protein turnover rate. The authors conclude that complexes assemble rhythmically. The authors also present evidence that the activity of the proteasome oscillates in a circadian manner. Based on this observation, they show (in fibroblasts and in mice) that the response to proteotoxic stress (monitored by eIF2alpha phosphorylation levels, protein aggregation, and apoptosis) is higher at circadian times of high proteasome activity.
I am an expert in the circadian field, and the hypothesis and concept behind the work presented here are potentially very interesting, and the experimental design is in principle suitable to answer these questions. However, after reading the paper several times, I cannot find the set of experiments that would convincingly support the authors' conclusions.
Major questions/points:
The major limitation of the manuscript is that the conclusions rely heavily on statistical analysis and massive processing of data from a bewilderingly large number of very different experiments. The critical experiments lack replicates and obvious controls. In looking at the figures, I have often wondered if the presence or absence of a rhythm is real or a product of the heavily processed data. The fact that a cosine wave fits through data points better than a straight line does not necessarily mean that a circadian rhythm is present. I think that in particular, the SILAC experiment(s) should be repeated and also performed with an arrhythmic control (such as CRY1/2 KO). Comparability between the whole cell and MMC SILAC experiments is also limited due to the different experimental conditions (6h vs. 1.5h pulse, +booster). The essential and new message of the paper is that (at least some) macromolecular complexes undergo circadian renewal (degradation and synthesis). Rather than just analysing an operationally defined pellet fraction by mass spectrometry, this could be shown in more detail and directly for one or two specific macromolecular complexes. Ribosomes, for example, seem particularly suitable, because there would also be the very simple approach of measuring the synthesis of ribosomal RNA by pulse labelling. To me, such an analysis would be perfectly sufficient as a proof of principle. I would then omit aspects such as rhythmic stress response, since many additional experiments are needed to demonstrate this convincingly.
Specific points:
The reader is strongly influenced by the cosine wave or straight lines in the graphs (e.g. 1c, e, 3h, 5b, etc) produced by the analysis of rhythmicity, which basically only gives a yes or no answer. But it is not really that simple. If the algorithm detects a rhythm what is its period? Is it the same as the period of the luciferase reporter? If the period lengths correlate, do the phases as well (e.g. see differences in phases 1c and e)? These questions are not addressed.
The algorithm in Fig 1c predicts a rhythm for the chymotrypsin-like and the trypsin-like but not for the caspase-like activity. The peptide assay measures core proteasome activity independent of ubiquitylation and should therefore be dependent on proteasome concentration in the sample. How can then only two of the three proteasomal activities be rhythmic? Please elaborate and repeat with arrhythmic cells (e.g. CRY1/2 KO). The period length does not seem to correlate with the one of the reporter. Why is that?
Fig. 1a,b suggest that there is a rhythm in global protein synthesis with a significant peak at 40h. Yet, Fig. 1e suggests otherwise. How can that be? Also, the degradation graph (lower panel 1c) has to be plotted with the ratios calculated from the data points and not the heavily processed fitted graphs. This can be very misleading. It also strikes me as odd that the amplitude of degradation increases (peak at 28h lower than at 30h) while the amplitude of the core clock oscillation dampens over time (peak at 54h higher than at 53h due to desynchronisation. Only two data values around 54h are responsible for the detected rhythm (2nd peak). Furthermore, phase and period do not agree with the rhythm of proteolytic activities shown in 1c. How can this be explained?
Regarding the MS data shown in Figure 2, is it possible to show a positive / quality control? Best would be MS data of Luciferase (or PER2,3, RevErb/alpha, DBP) to show oscillation of protein levels with the same phase and period as the reporter. In Fig. 2c examples of the 4 groups of proteins presented in 2e should be shown (both synthesis and total abundance arrhythmic, either one rhythmic or both rhythmic) and not just what appears to be random examples of rhythmic and arrhythmic proteins.
Is it possible at all to distinguish between synthesis/turnover and assembly/disassembly of macromolecular complexes in the MMC SILAC experiment? If so, how? Looking at Fig. 4b,c, what is the fraction of rhythmic proteins from the MMC experiment that also oscillate in either synthesis, total abundance or both in the whole cell? Is there a general correlation at all? Please show.
Why is the phase of the oscillating proteins different in the two experiments (compare Figs. 2f,g and 4a) and does either of them match with the phase of the PER2::LUC reporter, which should be the peak synthesis phase of the clock?
Regarding the sensitivity to MG132 in Fig. 5b it doesn't make sense that, while eIF2alpha phosphorylation is arrhythmic in untreated cells and the levels of eIF2alpha phosphorylation are (apparently) not exhibiting a rhythmic change by administration of MG132 at different circadian timepoints, the ratio of P-eIF2alpha with and without MG132 suddenly is. Please show in Fig. S4b quantifications of the individual experiments with and without MG132. What is presented in 5b is after all the ratio of ratios of quantifications of Western blots, each of which individually does not display any appreciable rhythm. For me this is two much of processing of data. In my opinion, the MG132 4h acute treatment must show a detectable rhythm.
Minor:
In Fig. 1f please show dot blot with error bars as well as the individual experiments in the supplementals. Please check the graph legend (N>=3?)
Please explain the mechanism of the "booster" used in the second SILAC experiment.
p10 3rd paragraph: S2e not S3e
p12 last paragraph please add reference to Figs. 5f,g
Significance
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Referee #2
Evidence, reproducibility and clarity
Summary:
This is a very interesting and well written paper that addresses key questions in the circadian organization of proteostasis. The paper investigates origins of cellular circadian rhythms, invoking a premise early that there is a poor correlation between rhythmic gene expression - regulated by the canonical TTFL - and rhythms of the proteome, which are rather meager. Specifically, they ask how a relatively stable proteome is possible if cells engage in rhythms of cellular protein synthesis? Their hypothesis is that protein degradation must rhythmically compensate for rhythms of synthesis and much of the manuscript is focused on defining the relationship between rhythmic global synthesis and rhythmic degradation. They employ a series of detailed proteomic investigations and biochemical assessments of protein synthesis coupled with various circadian reporters to assess proteosome function. The proteomic experiments reveal a limited number of proteins with oscillations in either synthesis or abundance or both and no discernible pathway organization however, a followup and more refined study that utilized fractionated samples and boosted heavy SILAC identified strikingly, that many proteins in relatively heavy fractions are rhythmic and that these fall into possible complexes including ribosome and chaperonins. Finally, they perform in vivo experiments testing whether the timing of proteotoxic stimuli regulates the degree of the integrated stress response measured as pEif2a.
Overall, I think that this is a fascinating paper that addresses and important question but falls short on mechanistically unifying them and completely contextualizing the findings in light of the canonical modes of circadian timekeeping leaving us with an important, but mostly descriptive set of findings. In addition, there are a number of important questions about data interpretation, some issues with data quality that should be addressed outlined below. With revision and further explication, this study will be an excellent addition to the growing field of circadian organization of the cellular proteome.
Major and minor Comments.
Figure 1.
Fig 1a. The difference in Pulse and Chase at ZT24 does not appear to reflect the quantified data in 1b. This should be reconciled to make the figure convincing. How was the timing of the chase collection determined? Fig 1d-e. What is the evidence that puro labeling results in 'rapid' turnover. Fig 1e seems to be missing the data from the treated and untreated conditions? How are the lines produced (e.g. linear versus rhythmic? Are these drawn lines or actual regressions?). Why was 30 minutes chosen as labeling time? It seems hard to understand here how protein degradation kinetics can be measured by puromycin labeling if the authors' claim that puromycin labeling potentially changes degradation rates as a function - primary or secondary - of the labeling itself. It seems they are measuring the potential to degrade proteins. How do they determine that they are measuring degradation of functionally relevant proteins as opposed to a host of premature truncations? Fig 1e bottom - again is this a true regression line? Perhaps two time points should be examined here - similar to the pulse chase performed with 35S labeling? Fig 1f. It appears that Puro labeling results in a rhythm between ZT1 and ZT13 but no statistic is provided and appears that the 'ns' is the results of variance in the data as opposed to difference in means? - would this not contradict the cellular result? What accounts for the rhythm reversal in the presence/absence of BTZ.
While the authors have previously demonstrated an increase in rhythmicity of the proteome in Cry1/Cry2 double knockout cells, it would have been welcome here to test a global loss of circadian transcription in the degradation assay. One might expect that these rhythms would also be even higher. What I am really asking is: what is the mechanism for rhythmic degradation and is it dependent on the canonical clock?
Fig 2. How was the 'fixed window' timeframe determined?
Fig 3h. While admittedly difficult, the native PAGE is not of great quality and kind of unconvincing. Also not really sure why the AHA labeling is used here an nowhere else in the paper.
Fig 4. I was a little disappointed here that the authors did not directly assess macromolecular assembly of at least one of their "hits" and demonstrate functional relevance and most of the analysis is maintained at a very superficial, systemic level. STRING assemblies are not terribly helpful without clear k-means clustering or some other clearly visualizable metric for stratifying and organizing the putative PPI data - this figure (S3) could be markedly improved.
Is it possible that some macromolecular complexes have rhythms because their constituent proteins have differential half-lives when in one complex compared with another in circadian time? This possibility was not discussed.
Fig. 5.
Why is the first histogram in 3c not at unity? Do ZT24 and Zt48 differ, similarly do ZT36 and ZT60? Fig S4f is not of good quality with missing eIF2a total and therefore no loading controls. S4e? true regression lines?
While I thought these experiments were effective, they did not tie back well to the rest of the paper. What are the consequences of a temporally sensitive ISR? Which pathways does it effect in circadian time? Here, the main holes in this study are somewhat exposed; namely, a lack of mechanistic depth in explaining the very fascinating, albeit mostly descriptive, findings. The implicit assumption made here is that aggregation is 'bad' but could the opposite be just as true? Taking these considerations in account would further strengthen the discussion.
Significance
This is a fascinating paper that addresses key questions in the circadian organization of the proteome. The paper's main findings are that rhythms of protein synthesis and degradation are temporally coordinated to maintain overall stability of the proteome in mouse fibroblasts. Furthermore, the authors present evidence that this temporal organization may be important for assembly of macromolecular complexes. While very interesting, the main limitations are a lack of biochemical and mechanistic explanation and evidence that verifies these, mostly descriptive, findings.
There are some relatively minor statistical and data quality issues that are probably addressable relatively quickly.
Upon revision the study would be a welcome addition to investigators interested in proteostasis, circadian biology, cell biology and proteomics.
I am a physician-scientist with expertise in circadian rhythms, cell biology, protein synthesis, and biochemistry.
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Referee #1
Evidence, reproducibility and clarity
The manuscript "Circadian regulation of protein turnover and proteome renewal" investigates the role of protein degradation in the circadian control of proteostasis. The researchers suggest that the relatively static levels of protein levels in a cell are incongruent with the known oscillation in protein synthesis. They therefore hypothesize that there should be a compensatory mechanism to counteract rhythmic protein synthesis, rhythmic protein degradation. To investigate this, they employ bulk pulse chase labeling to study the process of degradation. They identify a synchronization between the creation and turnover of proteins in a cell, implying the clock helps to maintain homeostasis through a novel mechanism. They note that these phases align with energy availability, granting a plausible reasoning behind the biological implementation of this regulation. In summary, this is a sound manuscript that adds to the research field. The experiments in this manuscript are well thought out, organized, and explained. In general, the authors do not go further in their conclusions than I think is warranted given the data that they have, though I think that there are some key items that should be addressed before the publication of this manuscript.
Major notes:
- In figure 1, a clearer idea of what the ** means would be appreciated. What was the standard of significance for this measure?
- In Figure 1b, it is important to note clearly in the text that the this is not a direct measure of protein degradation, but a subtractive proxy. Though I don't think that necessarily makes the authors conclusions incorrect, the same result could also be obtained if an extra 15% of the proteins were moved into the insoluble fraction. This is the same for Figure 1E and F.
- In figure 1c, is the noted oscillation in protease activity due to the oscillation of these proteins? What are the predicted mechanisms behind this? I don't think that this is necessarily within the scope of this paper but should be addressed in the discussion. Also, the peak degradation rate from Figure 1B is 4 hours before the peak enzyme activities. How can this observation be reconciled?
- For the pSILAC analysis, the incorporation scheme has a six-hour window between the comparison of the light and heavy peptides. This makes it somewhat difficult to assess whether you are looking a clock effect from T1 or T1+6. This does not negate the findings, but it does question when the synthesis is occurring and what is being compared, which I think should be more clearly discussed in the manuscript. This is discussed later in the manuscript but should be mentioned in this section.
- There are no error bars on figure 2C. What the pSILAC just done in a singlet? If so, the rhythms estimation is likely a large overestimate and should be noted.
- Why were the genes selected in 2C? these are not discussed anywhere else in the manuscript.
- The authors note that for Figure 2 "These observations are consistent with widespread rhythmic regulation of protein degradation." However, only 5-10% of the proteome is oscillating at any level and less with a discrepancy between synthesis and abundance, so "widespread" is an exaggeration and this statement should be limited to the degradation in the rhythmic proteome.
- The authors note that their more developed strategy in figure 3 would allow for the detection of less abundant proteins. However, they do not discuss that they in fact found less proteins overall, or if they were able to detect proteins of lower abundance. This is of some concern in determining if this is indeed the better method that they predict. How can the authors reconcile this issue? How can they rationalize this explains their increase in oscillating elements?
- In the comparison of complex turnover rates, the authors need to provide a metric that backs their statement that "the majority of component subunits not only showed similar average heavy to total protein ratios but also a similar change in synthesis over the daily cycle" for figure 3F.
- In reference to the AHA incorporation, why is the hypothesis not that, like the puramycin, you would not see oscillation unless you add BTZ? Shouldn't the active degradation regulate the incorporation of AHA such that there is no visible rhythm unless you suppress degradation?
- The authors claim that there is enrichment of the actin cytoskeleton, but where this data can be found should be explained. The only thing that is shown is a few selected graphs of proteins in this pathway.
- The authors note an oscillation in the total levels of p-eif2, commenting that these do not arise from the rhythms in total eif2a but temperature and feeding rhythms. However, unless I misunderstood, this work was done in fibroblast cell culture, so in this case, where would these temperature and feeding rhythms come from?
- In Figure 5d, the treatment impeding degradation is causing cell death while the inhibition of translation does not. However, wouldn't too much, or not enough, translation, without compensatory regulation from degradation cause a problem in the same way that degradation does?
Significance
The information that stems from this work is relevant and of interest to circadian clock field as how the regulation of the output of the circadian clock is implemented is still a major question in the field. This manuscript suggests a novel and plausible method for how, at least in part, this regulation occurs. However, the manuscript uses methods that do not measure degradation directly, which is a minor limitation. In addition, the mechanisms by which this regulation is imparted are not addressed in any meaningful way, even in the discussion.
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Reply to the reviewers
The authors do not wish to provide a response at this time.
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Referee #3
Evidence, reproducibility and clarity
Abe et al. generated multiple novel mouse model that follows and labels Col4a2 by fusing it with GFP. The creation of this mouse model allowed for the analysis of the basement membrane in real-time using live imaging of embryonic explant cultures. The combination of the mouse model with live imaging revealed new insights into how the basement membrane turnover occurs during early hair follicle development. After setting the stage the authors establish its utility with embryonic tissue, which revealed membrane buds that could be visualized with eGFP at different time intervals for 19h. The growth of the hair follicle bud during that time could be divided three distinct areas, the upper, lower stocks, and the tip. Where the tip and lower stalk increased in BM length, while the upper stalk decreased. BM length correlated with increased cellular replication. Using a double transgenic model system, they evaluated the differences between 'cell displacement', 'BM expansion', and 'cell autonomous movement'. Diving deeper with the Col4a2-mKiGR mouse model investigated Col4a2 turnover to reveal similar results mentioned above. Lastly MMP inhibitors were used to investigate how hair follicle growth is affected, which revealed inhibition of cellular replication and inhibition of Col4a2 turnover. These results inhibited hair follicle elongation which made the forming hair follicles thicker.
Overall, this is an interesting paper for hair follicle biologists since it investigates the early moments of the budding follicle in real time using a ex vivo culture model. In addition, there is additional appeal because the authors use live imaging the hair follicle neogenesis as a basement membrane model, which is interesting and novel. The manuscript is clearly written, and the data support the overall conclusions. My comments below are to help in clarity which may be used to develop clearer figures and additional text.
Major:
In Figure 2 for the cell displacement and expansion part. I found the figure and text confusing, particularly in regard to how the data shows the bleached edge of the BM moving alongside the cells. Could the authors make this clearer in the figure and in the writing of the text?
The authors created a Col4a2-mKikGR mouse line that is supposed to follow Col4a2 turnover. It is difficult to understand how the authors can claim that it was turnover with the explanation in the text of how the mouse model works. Could the authors write a better description of the mouse model in the text?
Significance
The strengths of the paper are the use of a novel mouse model that can track collagen (Col4a2) with a tagged GFP and the live imaging model system. This has led to a novel and important knowledge on the interplay between the BM and cells. The limitation of the manuscript is that the entire manuscript utilizes a single protocol (live imaging) to investigate BM dynamics. This might be due to the sophisticated nature of the model systems, but it is a limitation.
To my knowledge the study is novel because of the mouse model to track Col4a2 dynamics with GFP. This model led to some interesting findings about hair follicle development in that different regions expand differently with the BM. This is good foundational knowledge using the latest state of the art techniques in live imaging of embryonic tissue culture systems.
The audience that would be interested in this manuscript is broad, which would span cell and developmental biology but also specialists in membrane and protein biology that can finally see in real time the dynamics of Col4a2 building skin and hair.
My expertise in in hair follicle development and repair and stem cell biology.
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Referee #2
Evidence, reproducibility and clarity
The authors successfully generated a knock-in mouse line expressing fluorescence-tagged endogenous collagen IV. Homozygous mice exhibited normal survival with no apparent developmental abnormalities. Through imaging of the back skin of COL4A2-eGFP mice in ex vivo culture, the authors observed a faster expansion rate of the basement membrane (BM) at the growing tips of developing hair follicles, while the upper stalk region showed a slower BM expansion rate. Real-time imaging also revealed that the BM and basal epithelial cells moved in the same direction. Fluorescence recovery after photobleaching (FRAP) and the photoconvertible protein mKikGR experiments demonstrated a faster turnover rate of COL4A2 at the tips of the hair follicles. The authors used MMP inhibitors to suppress the recovery of COL4A2-eGFP, BM expansion, and observed abnormalities in the developmental process of hair follicle morphology. The findings are novel and interesting, some aspects of how the experiments and quantifications were conducted should be clarified to allow the readers to fully appreciate the results.
Major Comments:
- BM Expansion Statistics: Regarding the statistical analysis of BM expansion, is the length of the BM affected by the z-axis plane at the time of imaging? How is it ensured that the BM length measured at different time points corresponds to the same z-axis?
- Cell Movement Statistics (Figure 2): In the statistical analysis of cell movement in Figure 2, the lack of other references raises questions about ensuring that the cells measured at different time points are the same cells.
- The authors concluded that the inhibition of MMP delayed the recovery of COL4A2-eGFP after photobleaching, indicating the crucial role of MMP activity in the incorporation of COL4A2 into the BM. Does MMP inhibition lead to a reduction in the synthesis of the COL4A2 protein, thereby delaying the recovery of COL4A2 in the BM?
Minor Comments:
In Figure 1D, the representative image and the statistical graph are inconsistent. For example, in the upper stalk region, all basal epithelial cells have Ki67 signals according to the representative image.
Significance
The authors successfully generated knock-in mice expressing fluorescence-tagged endogenous collagen IV. With this novel mouse model, researchers can directly observe the dynamic changes in the extracellular matrix of different organs in mammals during development and disease, revealing the potential roles of the extracellular matrix.
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Referee #1
Evidence, reproducibility and clarity
Summary:
Wuergezhen et al. generated two fluorescently tagged Col4a2 mouse models, including EGFP-Col4a2 and the photoconvertible mKikGR-Col4a2. They showed that tagged collagen IV get incorporated in the basement membranes of various tissues in the developing and adult mice, and fully support embryonic development, fertility, and physiological functions. The authors followed up investigating Col4a2 dynamics during embryonic development of the hair follicle. Using FRAP, they showed that the basement membrane expands with a faster rate near the tip region. This coincided with faster turnover rates of Col4a2 at the tip relative to the lower and upper stalk. In addition, the authors demonstrated that Col4a2 turnover depends on MMPs.
Major comments:
- Are the key conclusions convincing?
The major conclusions of the manuscript are convincing. These include that tagging collagen IV does not compromise its function, differential expansion of the basement membrane, differential turnover of the Col4a2, the MMP dependence for normal basement membrane expansion and turnover. However, some claims detailed below need to be clarified or addressed to improve the manuscript. - Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether?
In Figure 2B-C, the authors conclude that basement membrane expands at different rates, depending on the region with higher expansion rates near the hair follicle tip. From their methods, they conducted repetitive photobleaching cycles every 2-3 hours to maintain the bleached status of ROIs and tracked changes in basement membrane length. However, it sounds challenging to repetitively photobleach the same ROI in a dynamically expanding tissue, which may compromise the accuracy of length measurements. It would be helpful if the authors could provide movies corresponding to these experiments for clarity. In addition, this repetitive bleaching should be highlighted in the figure and figure legend, as readers could get confused about why there is no recovery here when comparing to the FRAP experiment.
In Lines 180-198 and Figure 2F-H, the authors interpreted cell movement as contributed by cell-autonomous vs basement membrane expansion, which is speculative. Another possibility is that cell movement was all autonomous, while basement membrane expansion was caused by mechanical stretching that was in turn caused by cell proliferation. This conclusion should be rephrased.
Following MMPi treatment, the authors found that basement membrane expansion was halted (Figure 4C-D). Yet, they later showed that hair follicles widened under MMPi treatment (Figure 4E-J). Under these conditions, I would have expected such widening to be accompanied by basement membrane expansion at the lower or upper stalk, which is not the case, at least for the first 7 hours (Figure 4C-D). How do the authors interpret this? - Would additional experiments be essential to support the claims of the paper? Request additional experiments only where necessary for the paper as it is, and do not ask authors to open new lines of experimentation.
Considering the rapid expansion of BM near the tips, I wonder whether the authors have explored possible structural differences of the basement membrane in different regions? Is the basement membrane near the tips thinner and/or does it have microperforations as reported in other systems? Looking into this may further support their observations, not only in control conditions but also in MMPi treated follicles. - Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated cost and time investment for substantial experiments.
Yes, for possible structural changes, 3D rendering of fluorescence imaging as shown in Figure 1J may be sufficient.
Increasing sample number using existing mouse strains should also be feasible. It would take 2-3 weeks from setting up timed pregnant mice to imaging the embryonic skin explants. Adding image analysis and figure preparation, it should be doable within 1 month. - Are the data and the methods presented in such a way that they can be reproduced?
In Figure 2D/ Figure 5C, it is unclear how ROIs corresponding to tip/lower/upper stalk are being drawn for quantification of Ki67+ cells.
The images in 2B and 4C, 3A and 4E, are identical. Images should not be re-used in figures. This raised the concern that probably not sufficient samples were imaged to have different representative images. It should also be clarified where the data was re-used, for example, the control data in 2C and 4D, 3B and 4B. - Are the experiments adequately replicated and statistical analysis adequate?
A few experiments have low sample numbers while the data was quite variable. These include Figure 2G-H (n = 3 cells), Figure 3C (unknown sample number), Figure 4B (n = 3 hair follicles), Figure 5B (n = 3 hair follicles). More sample numbers (~10 total) should be included to solidify the findings.
For the mKikGR experiment in Figure 3C, quantification should be included. A ratiometric measurement of green/red fluorescence over time should be a good complementary way of demonstrating region-specific recovery.
In Figure 5B, the authors claim that the percentage of dividing cells in control follicles being different from that of MMPi-treated follicles. How are they extracting these percentages? From the plots, control and MMPi-treated columns do not appear to be normalized as 100% to make such comparisons. Moreover, having two mean+/-SD in each column makes these data confusing to interpret. The authors should consider replotting their data either by combining their data into a unique population per conditions and reporting the percentages, or alternatively, they may consider splitting each of these columns into two (i.e., dividing vs. non-dividing cells), and comparing both conditions as ratios of dividing versus/non-dividing cells.
Minor comments:
- Specific experimental issues that are easily addressable.
Already addressed above. - Are prior studies referenced appropriately?
I believe so. <br /> - Are the text and figures clear and accurate?
All plots measuring basement membrane length are labeled as 'increase in BM length', even when in some cases the BM length is reduced. The authors should consider relabeling these as 'BM length change' or something similar.
The second and third paragraphs of the discussion are too long and should be condensed into a single paragraph. - Do you have suggestions that would help the authors improve the presentation of their data and conclusions?
Use better color combination for visualization of multi-channel images. For instance, magenta/green is a better combination than red/green for the color blind. Color combinations are not consistent across figures in the manuscript.
Include movies for all data derived from live imaging.
Include statistical tests used for all plots, some are missing.
The authors should consider fitting their FRAP data in each condition and report percentages corresponding to the mobile and immobile fractions.
Examples of horizontal vs perpendicular cell division appear to be mislabeled in Video5.
Significance
- Describe the nature and significance of the advance (e.g. conceptual, technical, clinical) for the field.
- The large molecular weight of extracellular proteins makes it challenging to generate genetically engineered versions of such proteins to investigate their function and dynamics in vivo. The present study has addressed such issues for Col4a2, a major component of the basement membrane. This study further provides insights towards the understanding of BM dynamics during embryonic organ development.
- Place the work in the context of the existing literature (provide references, where appropriate).
- Addressed above
- State what audience might be interested in and influenced by the reported findings.
- Cell and developmental biology, extracellular matrix biology, organ development and regeneration.
- 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.
- Tissue morphogenesis, extracellular matrix
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Referee #3
Evidence, reproducibility and clarity
This manuscript has potential interest as a preclinical study for glioblastoma treatment. There is a substantial amount of data that is promising, but there are numerous issues that will require additional experimental effort before publication.
Major concerns:
- The title is overly general and uninformative. The authors should include the drug name (mubritinib) and the specific tumour type (glioblastoma).
- The concept that mubritinib functions through metabolic effects is not surprising given recent publications (PMID: 37382244; PMID: 35429141; PMID: 33245718; PMID: 31287994) and that it impacts the blood-brain barrier (PMID: 36178590). However, there are limitations to the strength of this observation. Most of the experiments are associations between drug treatment and metabolic changes. The NDI1 partially rescue experiments in Figures 1h and 1i are nice but show that NDI1 expression itself increases OCR. This experiment is also performed over a very brief window of time. A better set of experiments would include measurement of cell number over a prolonged time course (Figure 2d has one time point) and to use a genetic targeting strategy against ETC complex 1.
- The authors observe that EGFR expressing lines are more sensitive to mubritinib. As the rescue experiments are only partially effective and ERBB family members may be targeted by mubritinib, it is critical to address the effects of mubritinib on EGFR activation and perform rescue studies, as the application of mubritinib in patients may be guided by the EGFR mutational state.
- The differences found with NSC responses is interesting but needs to be developed. Why are there differences in mubritinib responses? For example, do NSCs not require ETC complex 1 as much?
- I would suggest that the authors also compare sensitivity of the BTSCs (I would suggest a change in nomenclature as these are only from GB) and differentiated tumour cells to determine if the stem cells have greater dependence. Please use similar culture conditions.
- The differences in cell cycle are useful but the mechanism is lacking. The claim that self-renewal is drastically or markedly changed is overstated. The ELDAs are not striking. There is no evidence that stemness is a direct target.
- The in vivo effects on cell biology need greater analysis in mechanism. I am also not sure why the authors switch lines tested in different assays.
- The mechanism of interaction with radiation is not developed. What is happening here? Are there changes in DNA damage repair or simply growth? This is a nice observation that could be better developed.
Minor concerns:
- Grammar needs attention.
- Please remove the overuse of "strikingly", "drastically", "importantly", etc. Most of these descriptions are overstated.
- The number of in vivo replicates needs to be addressed.
- All gene expression data should be deposited. All raw data (numeric) should be made available.
- Please replace all normalized data with raw data. The statistical testing was likely incorrectly performed, and this can give rise to false conclusions. I am particularly concerned about the normalization to cell numbers.
Significance
This manuscript has potential interest as a preclinical study for glioblastoma treatment. There is a substantial amount of data that is promising, but there are numerous issues that will require additional experimental effort before publication.
Major concerns:
- The title is overly general and uninformative. The authors should include the drug name (mubritinib) and the specific tumour type (glioblastoma).
- The concept that mubritinib functions through metabolic effects is not surprising given recent publications (PMID: 37382244; PMID: 35429141; PMID: 33245718; PMID: 31287994) and that it impacts the blood-brain barrier (PMID: 36178590). However, there are limitations to the strength of this observation. Most of the experiments are associations between drug treatment and metabolic changes. The NDI1 partially rescue experiments in Figures 1h and 1i are nice but show that NDI1 expression itself increases OCR. This experiment is also performed over a very brief window of time. A better set of experiments would include measurement of cell number over a prolonged time course (Figure 2d has one time point) and to use a genetic targeting strategy against ETC complex 1.
- The authors observe that EGFR expressing lines are more sensitive to mubritinib. As the rescue experiments are only partially effective and ERBB family members may be targeted by mubritinib, it is critical to address the effects of mubritinib on EGFR activation and perform rescue studies, as the application of mubritinib in patients may be guided by the EGFR mutational state.
- The differences found with NSC responses is interesting but needs to be developed. Why are there differences in mubritinib responses? For example, do NSCs not require ETC complex 1 as much?
- I would suggest that the authors also compare sensitivity of the BTSCs (I would suggest a change in nomenclature as these are only from GB) and differentiated tumour cells to determine if the stem cells have greater dependence. Please use similar culture conditions.
- The differences in cell cycle are useful but the mechanism is lacking. The claim that self-renewal is drastically or markedly changed is overstated. The ELDAs are not striking. There is no evidence that stemness is a direct target.
- The in vivo effects on cell biology need greater analysis in mechanism. I am also not sure why the authors switch lines tested in different assays.
- The mechanism of interaction with radiation is not developed. What is happening here? Are there changes in DNA damage repair or simply growth? This is a nice observation that could be better developed.
Minor concerns:
- Grammar needs attention.
- Please remove the overuse of "strikingly", "drastically", "importantly", etc. Most of these descriptions are overstated.
- The number of in vivo replicates needs to be addressed.
- All gene expression data should be deposited. All raw data (numeric) should be made available.
- Please replace all normalized data with raw data. The statistical testing was likely incorrectly performed, and this can give rise to false conclusions. I am particularly concerned about the normalization to cell numbers.
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Referee #2
Evidence, reproducibility and clarity
In this manuscript Burban et al explore the effect of the mitochondrial oxidative phosphorylation (OXPHOS) inhibitor Mubritinib on patient derived glioblastoma stem cells and murine xenografts. The authors first show that i) Mubritinib is an inhibitor of OXPHOS in brain tumor stem cells (BTSC), ii) that it impairs cell growth and self-renewal of patient-derived BTSC with different genetic background and iii) has an effect on the expression of genes related to stemness. In addition, the authors convincingly show that Mubritinib is a brain penetrant drug, and by transplanting luciferase expressing BTSC into the brain of immunodeficient mice they show it delays GB tumorigenesis and the animal lifespan (either alone, or more efficiently if combined with IR treatment). Finally, by performing toxicological and behavioral studies in mice models, Burban et al demonstrate that Mubritinib has a well-tolerated and safe profile and does not induce damage to healthy cells.
The manuscript is well written and organized and the data is clearly presented. The results are convincing, but a few additional experiments and controls would be beneficial to support the claims of the paper, most of which are easily addressable.
Main comments:
- Finding suitable control cells for BTSC experiments is a widely acknowledged challenge in the field. However, in line with other studies, it is recommended that the authors consider using a non-oncogenic NSC as control line to demonstrate that the effects reported in Figure 1 and Figure 2 are more pronounced in BTSC compared to NSC (as it was done in Suppl Fig3).
- Figure 5 presents a significant finding indicating that Mubritinib enhances the sensitivity of GB tumors to IR. Considering that Temozolomide (TMZ) is the primary chemotherapy drug for GB patients, it would be crucial to investigate the potential outcomes of a combined treatment involving Mubritinib and TMZ. This will help determine if the combination exhibits promising results, comparable to what is demonstrated in Figures 5d, 5g, and 5i for Mubritinib and IR. Such experiment would reinforce the drug's potential for clinical trials in GB treatment.
Minor comments:
- The authors should specify early in the paper what is the number of samples of patient-derived BTSC they use and the fact that their genetic mutations are known (this information is summarized in the supplemental table 1, but only reported later in the manuscript). This information is important and should be clearly stated at the beginning of the manuscript.
- In Figure 2a the inhibition at 20nM is significant but not very pronounced. Based on Figure 1 I would have expected to see a stronger effect at this concentration range. Can the authors comment/provide an explanation for this discrepancy?
- The EdU incorporation experiment presented in Figure2h-I should be repeat with lower concentrations of the drug (in most of the assays the effect of Mubritinib is detectable at much lower concentrations).
- Since the authors have done RNA-seq on the samples why don't they report the specific subtypes of their samples in the text and in Suppl Table 1 (Proneural, Neural, Classical or Mesenchymal) ? It is known that different molecular subtypes respond differently to treatments; therefore this information would be essential to understand if Mubritinib is effective on a wide range of GB subtypes.
- In Figure2b and Supplemental Figure1b-c : instead of correlating the effect with genetic mutations, it would be more relevant if the authors could correlate the data with the molecular subtypes inferred by RNA-seq (see my comment above)
- Regarding the RNA-seq experiment the authors should report what is the percentage (and numbers) of genes that change expression. Is there for example a preference for up- or down- regulation? It would be interesting to see a Gene Ontology (GO) analysis for the up-regulated genes versus a GO analysis of the down-regulated genes to confirm that the relevant categories show dysregulation as expected (e.g. enrichment for cell cycle and stemness genes in the down-regulated list, etc ).
- In Figure2 m-o the difference between CTL and Mubritinib treated cells do not seem substantial, although it is shown as statistically relevant. Can the authors specify the percentage to be able to better assess the differences?
- Add p-value for Figure3a-c
- In the western blot in Supplemental Figure 3b Vinculin shows twice
- Change" Given that Mubritinib is already completed a phase I clinical trial" into "...has completed..."
Referees cross-commenting
I agree with other reviewers that more data is needed to determine if mubritinib could be an effective treatment for various GB subtypes. The models used in this study do not encompass the full spectrum of GBM genetics. The authors should repreat the experiments using models that represent the major genetic/transcriptional subtypes of GBMs and clearly label and identify them in the study. Specifically, the authors should include models like 'classical/EGFR-amplified', 'mesenchymal', 'proneural/PDGFR amplified'. Alternatively, it is advisable to refrain from asserting that mubritinib is effective across genetic alterations in the manuscript.
Significance
Considering the limited effectiveness of existing treatments, it is crucial to explore alternative approaches to improve patient outcomes. This study demonstrates promising potential for the clinical translation of Mubritinib in GB treatment.
A major limitation of this study is the narrow numbers of patient-derived samples used and absence of a proper control cell line. Unfortunately, as evidenced by the existing literature in the field, selecting a control cell line for glioma stem cells research is challenging due to the unknown cell-of-origin for this type of tumor. In addition, all the toxicity/safety tests were performed in mice models and it is difficult to predict how this would translate into human patients. However, the fact that a phase I clinical trial has already been completed for Mubritinib (in the context of a different type of tumor) is encouraging.
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Referee #1
Evidence, reproducibility and clarity
The authors report the use of mubritinib, a drug targeting complex I of the mitochondrial electron transport chain, to halt the proliferation of brain tumor stem cells (BTSCs) isolated as neurospheres from glioblastomas. They demonstrate that mubritinib crosses the blood-brain barrier, and show that this drug delays GBM tumorigenesis and extends lifespan in mouse models that were generated by transplantation of human BTSCs or mouse cell lines. They also provide evidence that this potentially harmful drug is well-tolerated by mice.
The ability of mubritinib (initially conceived as a ERBB2 inhibitor) to block complex I of the electron transport chain was previously identified in acute myeloid leukemia, where this drug proved to selectively inhibit a subset of cases relying on oxidative phosphorylation (OXPHOS). However, the use of mubritinib is novel in GBM, a lethal malignancy for which a few therapeutic options are available, and no substantial progress has been reported since 2005. In addition, the authors show that accumulation of mubritinib in the brain tissue allows for the use of a reduced dose of mubritinib, thereby reducing the risk of the deleterious effects that blunt enthusiasms about targeting of mitochondrial respiration.
However, this manuscript presents significant weaknesses that are detailed below. In particular, the models used appear insufficient to support the conclusion, stated in the abstract, that the drug can be effective in GBMs with different oncogenic mutations. Based on the provided evidence, the claim that 'mubritinib potently impairs stemness and growth of patient-derived BTSCs harboring different oncogenic mutations' should be removed, or supported by using BTSCs that adequately represent the major GBM subtypes identified by genetic and transcriptional analysis. Specifically, BTSCs harboring EGFR amplification (displayed by 40% of GBMs) would need to be added. Equally, it is inappropriate to conclude (Discussion, page 14) that the models used, displaying EGFR mutations, are representative of widespread EGFR alterations: indeed the EGFR alteration observed in 40-50% of patients is EGFR amplification, whose pathogenic effects can not be recapitulated by the EGFR mutation harbored in the models used. If models harboring EGFR amplification are unavailable to these authors, making unrealistic to repeat the experiments in at least two different EGFR-amplified BTSCs in the timeframe allowed for revision, not only the claim that mubritinib inhibits BTSCs harboring different oncogenic mutations should be removed, but lack of experiments in EGFR-amplified BTSCs should be discussed as a limitation of this study. In addition, as detailed below, in vitro experiments should be expanded to corroborate mechanistic aspects of the drug, safety should be better demonstrated and some aspects of in vivo experiments should be clarified. Overall, the methodology seems sufficiently detailed to allow reproduction. The experiments are adequately repeated and the statistical analysis is appropriate, but in one case detailed below.
Major Point N.1
Figure 2a and 2c. Although statistically significant, the effect of mubritinib at 20 nM is biologically of limited significance in a subset of BTSCs, where the drug reduces viability by less than 25% (Fig. 2a). Therefore, the correlation between oxygen consumption rate (OCR) and mubritinib sensitivity (% of live cells), shown in Fig. 2c, should be presented for all mubritinib doses, and particularly for the dose of 500 nM, which is utilized in subsequent experiments. Additionally, it would be useful to display the correlation not only between viability and basal OCR but also with maximal OCR. This analysis could identify varying levels of sensitivity to ECT inhibition, aligning with the expectation that different BTSCs may exhibit varying degrees of dependency on mitochondrial OXPHOS. This would suggest that different GBMs may require different dosages of the drug. In all the experiments presented in the manuscript, the authors use the lines exhibiting the highest mubritinib sensitivity (BTSC 53, BTSC73), which might not be representative of all GBMs. This selection bias need explicit clarification in the text.
Major Point N.2.
In Fig. 2b, the statistics is significantly biased as it is calculated based on technical replicates, rather than on a significant number of independent models featuring either wild-type or mutated EGFR. Presented in this manner, this analysis is unacceptable. Additionally, as noted previously, the models used in this manuscript do not represent the overall GBM genetics, particularly due to lack of EGFR amplified models, which correspond to 40% of cases, and cannot be recapitulated by EGFR mutations. In general, the number of models is too small to draw any conclusion regarding the relationship between genetics and mubritinib sensitivity (including conclusions concerning TP53, or the MGMT status, shown in supplementary figures 1b-c). If the authors intend to claim that GBMs are sensitive to mubritinib independently of the genetic status, they should repeat their experiments by using models representative of the major genetic/transcriptional subtypes of GBMs, by clearly characterizing and identifying them in the experiments: e.g. 'classical/EGFR-amplified'; 'mesenchymal'; 'proneural/PDGFR amplified'. Otherwise (more realistically), it is suggested to remove claims that mubritinib is effective independently of genetic alterations throughout the manuscript (including the abstract and the discussion).
Major Point N.3
Fig. 2k-l present a transcriptional analysis with questionable representativeness as it is performed on the single line BTSC147 from a recurrent GBM, which is unlikely to represent primary GBMs. The analysis appears overly descriptive and fails to add significant information beyond the observation that mubritinib induces a proliferative arrest, as assessed in biological experiments. Additionally, the claim that the Neftel 'Neural Progenitor Cell' signature is altered in a biologically significant manner after only 24 hours of mubritinib treatment seems questionable. As such, this analysis should be moved to supplementary information. A more intriguing alternative would be to compare groups of BTSCs that exhibit high or low sensitivity to mubritinib and attempt to identify gene sets that can correlate with and possibly contribute to explain differences in drug sensitivity.
Major point N. 4
Figure 3. LDA need to be measured at longer timepoints (14-21 days vs. 7 days shown).
Major point N. 5
Supplementary Figure 3c aims to demonstrate that neural stem cells are unaffected by mubritinib merely by showing stem markers in western blots, which is insufficient. To provide convincing evidence, an LDA should be performed using human Neural Progenitor Cells.
Major Point N. 6
Page 9. The mechanistic nexus between OXPHOS inhibition and radiosensitization described by the authors remains unclear. In particular, the link between enrichment in OXPHOS proteins observed in recurrent vs.primary GBMs on the one hand, and downregulation of homologous recombination related-pathways on the other hand is difficult to grasp. The authors should endeavor to more clearly explain how mubritinib can interfere with the adaptive response to ionizing radiation, thereby providing a rationale for experiments combining the two treatments. As noted in the discussion (page 14), 'targeting mitochondrial respiration is an emerging strategy to overcome radioresistance in the tumour hypoxic areas'. Thus, a plausible mechanism of mubritinib-induced radiosensitization may involve reducing oxygen consumption, thereby leaving more oxygen available for diffusion and improving radiation response (by increasing generation of reactive oxygen species). To provide convincing mechanistic evidence, the authors should include in vitro experiments assessing the ability of mubritinib to radiosensitize BTSC in both normoxic and hypoxic conditions. LDA or radiobiological clonogenic assays showing the effect of combination treatment on stem cell frequency are recommended.
Major Point N. 7
Fig. 5d. Concerning the scheme of in vivo treatment, it is unclear why irradiation is administered 5 days after the beginning of mubritinib treatment, considering that mubritinib reaches its peak brain concentration much earlier, as shown in Fig. 4d. Furthermore, if mubritinib alone is effective against the tumor, comparing tumors that have been treated with IR alone at the same time-point as those treated with IR + mubritinib seems inappropriate. This is because, in the latter scenario, IR is applied to tumors that are likely reduced in volume compared to those treated with vehicle prior to IR. This discrepancy could introduce bias in the evaluation of the combined treatment's efficacy.
Major Point N. 8.
Figure 6b. The methodology employed to measure the effect of mubritinib on human neural progenitor cells should be the same as that used for BTSC. Moreover, a positive control (a treatment inducing death, such as bosentan for hepatocytes) needs to be added.
Minor points
Minor point N.1
Please use consistent units (nM or uM) for mubritinib.
Minor point N.2
ND1 expression in transduced cells should be shown by western blot (in Supplementary Figures).
Significance
This manuscript reports preclinical results on the use of mubritinib, a drug targeting the mithochondrial electron chain transport complex 1, to halt proliferation of glioblastoma (GBM) stem cells in vitro and treat experimental GBMs generated by stem cell transplantation. Given that the standard therapy for GBM still relies on a limited number of conventional options, evidence demonstrating the preclinical effectiveness of mubritinib could exert a significant translational impact. Mubritinib has not yet been proposed for GBM treatment, but there is convincing evidence that the drug may be effective in subsets of acute myeloid leukemia that rely on oxidative phosphorylation (Baccelli et al., Cancer Cell 36:84, 2019. PMID: 31287994). Data provided in this manuscript on potential effectiveness of mubritinib are overall convincing. However, in its current form, the manuscript present major limitations regarding the representativeness of models used, which do not support the claim that mubritinib could be universally useful in GBM, and regarding mechanistic aspects of mubritinib combination with radiotherapy. These and other aspects could be addressed through additional experiments.
The audience interested in the reported findings includes preclinical and clinical neuro-oncologists. My field of expertise is biology and genetics of glioblastoma stem cells and generation of in vitro and in vivo GBM preclinical models.
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Reply to the reviewers
Reviewer #1 (Evidence, reproducibility and clarity (Required)):
Summary Maintenance of the histone H3 variant CENP-A at centromeres is necessary for proper kinetochore assembly and correct chromosome segregation. The Mis18 complex recruits the CENP-A chaperone HJURP to centromeres to facilitate CENP-A replenishment. Here the authors characterise the Mis18 complex using hybrid structural biology, and determine complex interface separation-of-function mutants.
Major Comments The SAXS and EM data on the full-length Mis18 components must be included in the main Figures, either as an additional figure or by merging/rearranging the existing figures. The authors discuss these results in three whole paragraphs, which are a very important part of the paper.
We thank the reviewer for this constructive suggestion. We have now included an additional figure (new Fig. 2, attached below), that highlights the fit of the integrative model against the SAXS and EM data.
Could the authors also compare the theoretical SAXS scattering curves generated by their final model(s) with the experimental SAXS curves? This would provide some additional evidence for the overall shape of their complex model beyond the consistency with the Dmax/Rg.
We acknowledge the importance of this suggestion. We have now compared the theoretical SAXS scattering curve of the Mis18a/b core complex (named Mis18a/b DN), which lacks the flexible elements (disordered regions and the helical region flexibility connected to the Yippee domains). The theoretically calculated SAXS scattering curve of the model matches nicely with the experimental data with c2 value of 1.36. This data is now included in new Fig. 2 (Fig. 2f) and is referenced on page 9 line 21.
Minor Comments
While the introduction is clearly written, an additional cartoon schematic, representing the system/question would be helpful to a non-specialist reader to interpret the context of the study.
We have now included a cartoon in the revised Fig. 1 to support the introduction on centromere maintenance and the central role of the Mis18a/b/BP1 complex in this process. Please find the new Fig. 1 below.
No doubt the authors had a reason for choosing their figure allocation, but I wonder if more material couldn't be brought from the supplementary into the main figures?
As addressed in our response to one of the major comments, we have now moved key CLMS, SAXS and EM data from the supplemental figure into the main figure, new Fig. 2.
Page 6 "Mis18-alpha possesses an additional alpha-helical domain" - please make it clear in addition to what (I assume it's in addition to Mis18-beta).
Apologies for the lack of clarity. We have now rephrased this sentence to highlight that this difference is in comparison with Mis18b on page 6 line 15.
Page 7 - Report the RMSD of the Pombe vs. Human Mis18-alpha yipee structures?
The S. pombe Mis18 Yippee structure superposes on to the Human Mis18a Yippee domain with an RMSD of 0.92 angstroms with is now mentioned on page 7 line 9.
Page 7 - "We generated high-confidence structural models...." is there a metric for the confidence as reported by RaptorX? Perhaps includinging the PAE plots in the supplementary for the AlphaFold generated models would be useful?
We thank the reviewer for the valid suggestion. We have now included the PAE plot corresponding to the AlphaFold model in the supplementary Fig. S1d and reference on page 7 line 18. RaptorX ranks models based on estimated error. We have now included this information in the new figure legend for Supplementary Fig. S1.
Figure 1 - Perhaps label figure 1b as being experimentally determined, with the R values (as for Figure 1d), and 1c being a predicted model.
We have included Rfree and Rwork values for the Mis18a Yippee homo dimer structure and labelled Mis18a/b Yippee hetero-dimer as the predicted model in Fig. 1c and 1d.
Page 8 "This observation is consistent with the theoretically calculated pI of the Mis18alpha helix" This is a circular argument, of course this region has a low pI due to the amino acid composition. Please remove this statement.
We have now removed this statement as suggested.
Page 8 "...reveals tight hydrophobic interactions" these are presumably shown in Figure 1d rather than in the referenced 1e.
We apologise for the oversight. We have now referred to the correct figure (Fig. 1f in the revised Fig. 1).
Page 8 - The authors should briefly somewhere discuss why there is a difference between their results and those in Pan et al 2009. As I understand it, the Pan et al paper was based in part on modelling with CLMS data as restraints.
We thank the reviewer for this suggestion. According to Pan et al., 2009, the model shown by them was generated using CCBuilder, and their CLMS data could not differentiate the two models with the 2nd Mis18a C-terminal helix in either parallel or anti-parallel orientation. We now briefly discuss this on page 8 and line 22 as follows: "Although the Pan et al., 2019 model presented the 2nd Mis18a in a parallel orientation, they did not rule out the possibility of this assembling in an anti-parallel orientation within the Mis18a/b C-terminal helical assembly (Pan et al., 2019)."
Figure 1 - The labelling of the residues for Mis18-alpha in Figure 1d is problematic, they are black on dark purple (might be my printer/screen/eyes) suggest amending.
We have now rearranged the label positions to overcome this issue. For clarity, the labels that could not be moved appropriately are shown in white.
Figure S3a - Do the authors have some data to show the mass of the cross-linked complex that was loaded onto grids is consistent with what is expected?
Unfortunately, the amount of material that we recover after performing GraFix is not sufficient enough to determine the molecular weight of the crosslinked sample by techniques such as SEC-MALS. However, GraFix fractions were analysed by SDS PAGE, and fractions that ran around the expected molecular weight were selected for EM analysis. We have now included the corresponding SDS-PAGE showing the migration of the crosslinked sample analysed by EM (Supplementary Fig. S3a).
Figure S3b - scale bar
Revised Fig. 2d now includes the scale bar shown.
Figure S3c - Could the authors show or explain the differences between these different 3D reconstructions?
The models mainly differ in the relative orientations of the bulkier structural features that are referred to as 'ear' and 'mouth' pieces of a telephone handset. This has been mentioned in the text, but we note that the figure is not referenced right next to this statement. We have now amended this (Page 9 line 19), and to make it clear, we have also highlighted the difference using an arrowhead in Fig. 2e and S3b. The different orientations are also stated in the corresponding figure legends.
Page 9 - The use of "AFM" for AlphaFoldMultimer" is a little confusing since AFM is the established acronym for Atomic Force Microscopy. Perhaps AF2M?
We have now replaced AFM with AF2M on page 9 to avoid confusion.
Figure S4a - Control missing for Mis18-alpha wild-type
Apology for the confusion, this control is present in Fig. 4a. We have now stated this in the figure legend of S4a for clarity.
Figure S4 d and e - The contrast between the bands and the background is very bad (at least in my copy).
We have now adjusted the contrast of the blots in Fig. S4d and S4e response to this comment.
Page 13 "Our structural analysis suggests that two Mis18BP1 fragments.....". How did you arrive at this conclusion? Is this based on the AlphaFold/RaptorX model? What additional evidence do you have that the positioning of the Mis18BP1 is correct? Does the CLMS data support this?
We confirm that this statement is based on AlphaFold model. We have now explicitly highlighted this on page 14, line 5. As noted in the same paragraph (page 14, line 19), this model agrees with the contacts suggested by the cross-linking mass spectrometry data presented here.
Figure 4a - Would the authors like to consider using a different colour for Mis18BP1? The contrast is not great, especially in the electrostatic surface inset.
In response to this suggestion, the Mis18BP1 helix is now shown in grey in the inset of Fig. 5a.
Reviewer #1 (Significance (Required)):
General Assessment The paper is extremely clearly written. Likewise the figures are beautifully presented and the data extremely clean and fully supportive of the authors conclusions. Indeed it is seldom that one sees the depth of the structural approaches (X-ray, CLMS, EM, SAXS) in one paper which is a huge strength of the manuscript. In addition the translation of this data into very clean cell biological experiments, makes the paper truly outstanding.
Advance The authors provide the first model of the Mis18 complex, with extensive evidence to back up this model. The authors provide additional evidence as to how the deposition/renewal of CENP-A might be mediated by the Mis18 complex. The advance comes from both the level of clarity, detail, and scope achieved in this paper.
Audience This will likely be of great interest to anyone with an interest in chromosome biology, plus be of interest to structural biologists as an outstanding example of hybrid structural biology.
Expertise I am a biochemist with a background in structural biology with some familiarity with centromere biology
Reviewer #2 (Evidence, reproducibility and clarity (Required)):
Summary: The manuscript "structural basis for Mis18 complex assembly: implications for centromere maintenance" by Thamkachy and colleagues describes a study that uses structural analysis to test essential candidate residues in Mis18 complex components in CENP-A loading. For chromosomes to faithfully segregate during cell division, CENP-A levels must be maintained at the centromere. How CENP-A levels are maintained is therefore important to understand at the mechanistic level. The Mis18 complex has been found to be important, but how exactly the various Mis18 complex components interact and how they regulate new CENP-A loading remains not fully understood. This study set out to characterize the critical residues using X-ray crystallography, negative staining EM, SEC analysis, molecular modeling (Raptorx, AlphaFold2, and AlphaFold-multimer) to identify the residues of Mis18a and Mis18b that are critical for the formation of the Mis18a/b hetero-hexamer and which residues are important for Mis18a and Mis18BP1 interactions. A complex beta-sheet interface dictates the Mis18a and Mis18b interactions. Mutating the Mis18a residues that are important for the Mis18a/b interactions resulted in impaired pull-down of Mis18b and reduced centromeric levels of mutated Mis18a. The functional consequences of mutating residues that impair Mis18a/b interactions is that with reduced centomeric levels of Mis18a, also impaired new CENP-A loading. Interestingly, mutated Mis18b did not impact centromeric Mis18a levels and only modestly impaired new CENP-A loading. These data were interpreted that Mis18a is critical for new CENP-A loading, whereas Mis18b might be involved in finetuning how much new CENP-A is loaded. Overall, it is a very well described and well written study with exciting data.
Major comments:
- Overall, the structural data and the IF data support the importance of Mis18a residues 103-105 are critical for centromeric localization and new CENP-A loading, whereas Mis18b residues L199 and I203 are critical for centromeric localization, but only very modestly impair centromeric Mis18a localization and new CENP-A loading. In the discussion the authors argue that the N-terminal helical region of Mis18a mediate HJURP binding. This latter is postulated based on published work, but not tested in this work. This should be clarified as such.
We thank the reviewer for this comment. Our very recent study aimed at understanding the licencing role of Plk1, independent of the work reported here, serendipitously has now validated this suggestion and demonstrates that a Plk1-mediated phosphorylation cascade activates the Mis18a/b complex via a conformational switch of the N-terminal helical region of Mis18a, which facilitates a robust HJURP-Mis18a/b interaction (Parashara et al. bioRxiv 2024). An independent study from the Musacchio lab (Conti et al. bioRxiv, 2024) also reports similar findings, mutually strengthening our independent conclusions. Overall, these studies highlight the importance of the critical structural insights into the Mis18 complex this study reports. We now explicitly discuss the validation of our original hypothesis by citing our recent work along with that of the Musacchio lab. The corresponding section of the last paragraph now reads as follows (page 17 line 10): "Previously published work identified amino acid sequence similarity between the N-terminal region of Mis18a and R1 and R2 repeats of the HJURP that mediates Mis18a/b interaction (Pan et al., 2019). Deletion of the Mis18a N-terminal region enhanced HJURP interaction with the Mis18 complex (Pan et al., 2019). Here, we show that the N-terminal helical region of Mis18a makes extensive contact with the C-terminal helices of Mis18a and Mis18b, which had previously been shown to mediate HJURP binding by Pan et al., 2019. Collectively these observations suggest that the N-terminal region of Mis18a might directly interfere with HJURP - Mis18 complex interaction. Two independent recent studies (Parashara et al., 2024, Conti et al., 2024) reveal that this is indeed the case and a Plk1-mediated phosphorylation cascade involving several phosphorylation and binding events of the Mis18 complex subunits relieve the intramolecular interactions between the Mis18a N-terminal helical region and the HJURP binding surface of the Mis18a/b C-terminal helical bundle. This facilitates robust HJURP-Mis18a/b interaction in vitroand efficient HJURP centromere recruitment and CENP-A loading in cells. Overall, these studies also highlight the importance of the critical structural insights into the Mis18 complex we report here."
- Overall, the authors clearly describe their data and methodology and use adequate statistical analyses. The structural data of the Mis18a/b complex being a hetero-hexamer is convincing, but the validation in vivo is missing. As structural experiment are not performed under physiological conditions, it is important to establish the stoichiometry in vivo to further support the totality of the findings of the structural experiments and modeling. The data for the hierarchical assembly of Mis18a and Mis18b at the centromere and its importance in new CENP-A loading is convincing. An additional open question is whether "old" centromeric CENP-A or HJURP:new CENP-A complex is needed to recruit Mis18a to the centromere and whether the identified residues have a role in Mis18a centromeric localization. These data would provide a solid link between the Mis18 complex and how it is directly linked to new CENP-A loading.
We agree that establishing the stoichiometry of Mis18 subunits of the Mis18 complex in vivo would be insightful. However, considering that the Mis18 complex assembles in a specific window of the cell cycle (late Mitosis and early G1), we think characterising the stoichiometry in cells is extremely difficult and technically challenging. However, consistent with our structural model, several lines of independent evidence (Pan et al., 2017 and Spiller et al., 2017) using different biophysical methods (Analytical Ultra Centrifugation (Pan et al., 2017), SEC-MALS (Spiller et al., 2017)) showed that recombinantly purified Mis18 complex (irrespective of the expression host, from both E. Coli or insect cells) is a hetero-octamer made of a hetero-hexameric Mis18a/b (4 Mis18a and 2 Mis18 b) complex bound to two copies of Mis18BP1. These observations suggested that hetero-hexamerisation of the Mis18a/b complex may be needed to bind and dimerise Mis18BP1 in cells. Previously published cellular studies support the in vivo requirement of the hetero-octameric Mis18 assembly as: (i) Perturbing the hetero-hexamerisation of the Mis18a/b complex (by introducing mutations at the Mis18a/b Yippee dimerisation interface, which while did not disrupt Mis18a/b complex formation, perturbed its hetero-hexamerisation and resulted in a hetero-trimeric Mis18a/b complex made of 2 Mis18aand 1 Mis18b) abolished Mis18BP1 binding in vitro and in cells, consequently abolished CENP-A deposition (Spiller et al., 2017) and (ii) artificial dimerisation of Mis18BP1, by expressing Mis18BP1 as a GST-tagged protein, enhanced the centromere localisation of Mis18BP1 highlighting the requirement of Mis18a/b hexameric assembly mediated dimerization of Mis18BP1 in cells (Pan et al., 2017). While these studies highlighted the importance of maintaining the right stoichiometry (hetero-octamer of 4 Mis18a, 2 Mis18b and 2 Mis18BP1), lack of structural information on how this essential biological assembly is established remained a major knowledge gap. Our work presented here fills this critical knowledge gap by showing that a segment of Mis18BP1 (aa 20-51) also binds at the Yippee dimerisation interface. To highlight this, we have included the following statements in the introduction on page 5 and 20 "Perturbing the Yippee domain-mediated hexameric assembly of Mis18a/b (that resulted in a Mis18a/b hetero-trimer, 2 Mis18a and 1 Mis18b) abolished its ability to bind Mis18BP1 in vitro and in cells (Spiller et al., 2017), emphasising the requirement of maintaining correct stoichiometry of Mis18a/b subunits. Consistent with this, artificial dimerisation of Mis18BP1, by expressing Mis18BP1 as a GST-tagged protein, enhanced the centromere localisation of Mis18BP1 (Pan et al., 2017)." and in the Results section on page 14 line 12: "Mis18BP120-51 contains two short b strands that interact at Mis18a/b Yippee interface extending the six-stranded-b sheets of both Mis18a and Mis18b Yippee domains. This provides the structural rationale for why Yippee domains-mediated Mis18a/b hetero-hexamerisation is crucial for Mis18BP1 binding (Spiller et al., 2017)."
Regarding the question "whether 'old' centromeric CENP-A or HJURP:new CENP-A complex is needed to recruit Mis18a centromere localisation and whether identified residues have a role in Mis18a centromere localisation": According to the published literature, the Mis18 complex associates with centromeres through interaction with CCAN components CENP-C and CENP-I (Shono et al., 2015, Dambacher et al., 2012, Moree et al., 2011, Hoffmann et al., 2020). Considering CCAN assembles on CENP-A nucleosomes, and HJURP:new CENP-A centromere recruitment depends on the Mis18 complex, it will be reasonable to argue that the 'old' centromeric CENP-A contributes to the centromere localisation of the Mis18 complex. Amongst the components of the Mis18 complex, Mis18BP1 and Mis18bhave previously been suggested to interact with CENP-C. Within the Mis18 complex, we (Spiller et al., 2017) and others (Pan et al., 2017) have shown that Mis18a can directly interact with Mis18BP1, but it does so more efficiently when Mis18a hetero-oligomerises with Mis18b via their Yippee domains. Here, our structural analysis mapped the interaction interfaces and showed that Mis18a residues E103, D104 and T105 contribute to Mis18BP1 binding, as mutating these residues abolishes centromere localisation of Mis18a (Fig. 5c and 5d). To accentuate our findings, we have now included the following paragraph in the discussion section (page 17 line 26): "One of the key outstanding questions in the field is how does the Mis18 complex associate with the centromere. Previous studies identified CCAN subunits CENP-C and CENP-I as major players mediating the centromere localisation of the Mis18 complex mainly via Mis18BP1 (Shono et al., 2015, Dambacher et al., 2012, Moree et al., 2011), although Mis18b subunit has also been suggested to interact with CENP-C (Stellfox et al., 2016). Within the Mis18 complex, we and others have shown that the Mis18a/b Yippee hetero-dimers can directly interact with Mis18BP1. Here our structural analysis allowed us to map the interaction interface mediating Mis18a/b-Mis18BP1 binding. Perturbing this interface on Mis18a completely abolished Mis18a centromere localisation and reduced Mis18BP1 centromere levels. These observations show that Mis18a associates with the centromere mainly via Mis18BP1, and assembly of the Mis18 complex itself is crucial for its efficient centromere association, as previously suggested. Future work aimed at characterising the intermolecular contact points between the subunits of the Mis18 complex, centromeric chromatin and CCAN components and understanding if the Mis18 complex undergoes any conformational and/or compositional variations upon centromere association and/or during CENP-A deposition process, will be crucial to delineate the mechanisms underpinning the centromere maintenance."
Minor comments:
- The bar graphs shown ideally also show the individual data points for the authros to appreciate the spread of the data. These figures can be replicated in the Supplemental to avoid making the main figures look too busy.
We thank the reviewers for this suggestion. Reviewer #3 made a similar comment and suggested we use Superplot, which allows visualisation of individual data points of independent experiments. We have now revised all bar graphs using Superplot to address both reviewers' suggestions.
Reviewer #2 (Significance (Required)):
- This study uses a broad range of structural techniques, including molecular modeling which were subsequently validated by in vitro pull-down assays, co-IP, and IF. This combination of these techniques is important because many structural techniques cannot be performed under physiological conditions. Validating the main findings of the structural results by IF and co-IP is therefore critical.
- This work greatly advances our structural understanding how Mis18a, Mis18b, and Mis18BP1 form the Mis18 complex and how the critical residues in especially Mis18a help the Mis18 complex localize to the centromere and influence new CENP-A loading. This study also provides the first strong evidence in hierarchical assembly of the Mis18 complex.
- How centromere identity is maintained is a critical question in chromosome biology and genome integrity. The Mis18 complex has been identified as an important complex in the process. Several structural and mutational studies (all adequately cited in this manuscript) have tried to address which residues guide the assembly and functional regions of the Mis18 complex. This work builds and expands our understanding how especially Mis18a holds a pivotal role in both Mis18 complex formation and its impact on maintaining centromeric CENP-A levels.
- This work will be of interest to the chromosome field in general and anyone studying the mechanism of cell division.
- Chromatin, centromere, CENP-A, cell division. This reviewer has limited expertise in structural biology.
Reviewer #3 (Evidence, reproducibility and clarity (Required)):
Centromere identity is defined by CENP-A loading to specific sites on genomic DNA. CENP-A loading is known to rely on the Mis18 complex, and several regulators are known; yet how the Mis18 complex achieves this complex process has remained puzzle. By elucidating the structural basis of Mis18 complex assembly using integrative structural approaches the authors show that multiple homo and heterodimeric interfaces of Mis18alpha, beta and Mis18BP1 are involved in centromere maintenance. The authors show that Mis18alpha can associate with centromeres and deposit CENP-A independent of Mis18 β. Mis18α functions in CENP-A deposition at centromeres independent of Mis18β. Mis18β is required for maintaining a specific level of CENP-A occupancy at centromeres. Thus, using structure-guided and separation-of-function mutants the study reveals how Mis18 complex ensures centromere maintenance. Major comments: This is an excellent study on centromere inheritance, combining structural and cell biology techniques. The comments here primarily refer to Cell biology aspect of the work.
Figures show that new CENP-A deposits in Mis18βL199D/I203D mutants, but the level was reduced moderately. Based on this observation, the authors make a strong conclusion that Mis18β licenses the optimal levels of CENP-A at centromeres. Mis18α may be essential for both CENP-A incorporation and depositing a specific amount of CENP-A, as Mis18α and CENP-A levels are both reduced in Mis18βL199D/I203D mutants which failed to form the triple helical assembly with Mis18α as shown in Figure 3B and 3C. The authors may want to qualify some of these claims as preliminary or speculative.
We thank the reviewer for this suggestion. We agree that although the reduction in CENP-A levels upon replacing WT Mis18b with Mis18b L199D/I203D is more prominent than the reduction in centromere localised Mis18a, one cannot completely rule out the contribution of reduced Mis18a on CENP-A loading. This also raises an interesting possibility where Mis18b ensures the correct amount of CENP-A deposition by facilitating the optimal level of Mis18a at centromeres. We now explicitly discuss this in the discussion as follows (page 16 line 26): "Whilst proteins involved in CENP-A loading have been well established, the mechanism by which the correct levels of CENP-A are controlled is yet to be thoroughly explored and characterised. The data presented here suggest that Mis18b mainly contributes to the quantitative control of centromere maintenance - by ensuring the right amounts of CENP-A deposition at centromeres - and maybe one of several proteins that control CENP-A levels. We also note that the Mis18b mutant, which cannot interact with Mis18a, moderately reduced Mis18a levels at centromeres, and hence, it is possible that Mis18b ensures the correct level of CENP-A deposition by facilitating optimal Mis18a centromere recruitment. Future studies will focus on dissecting the mechanisms underlying the Mis18b-mediated control of CENP-A loading amounts along with any other mechanisms involved."
This work and others show that phosphorylation of Mis18BP1 by CDK1 can interfere with complex function (Spiller et al., 2017, Pan et al., 2017). Does the structure provide any insight into PLK1-mediated phosphorylation surfaces for activation of the complex? If yes, a brief discussion would help to link CDK1 and PLK1 mediated opposing actions will strengthen the work.
As described in our response to the first major comment of Reviewer 2, our very recent study aimed at understanding the licencing role of Plk1, independent of the work reported here, identified and evaluated the functional contribution of Plk1 phosphorylation on the subunits of the Mis18 complex (Parashara et al., bioRxiv 2024). Serendipitously, this recent work has now validated our hypothesis proposed based on the structural characterisation reported here and demonstrates that a Plk1-mediated phosphorylation cascade activates the Mis18a/b complex via a conformational switch of the N-terminal helical region of Mis18a which facilitates a robust HJURP-Mis18a/b interaction (Parashara et al. bioRxiv 2024). An independent study from the Musacchio lab (Conti et al., bioRxiv 2024) also reports similar findings, mutually strengthening our independent conclusions. Overall, these studies highlight the importance of the critical structural insights into the Mis18 complex this study reports. We now explicitly discuss the validation of our original hypothesis by citing our recent work along with that of the Musacchio lab. The corresponding section of the last paragraph now reads as follows (page 17 line 10): "Previously published work identified amino acid sequence similarity between the N-terminal region of Mis18a and R1 and R2 repeats of the HJURP that mediates Mis18a/binteraction (Pan et al., 2019). Deletion of the Mis18a N-terminal region enhanced HJURP interaction with the Mis18 complex (Pan et al., 2019). Here, we show that the N-terminal helical region of Mis18a makes extensive contact with the C-terminal helices of Mis18a and Mis18b, which had previously been shown to mediate HJURP binding by Pan et al., 2019. Collectively these observations suggest that the N-terminal region of Mis18a might directly interfere with HJURP - Mis18 complex interaction. Two independent recent studies (Parashara et al., 2024, Conti et al., 2024) reveal that this is indeed the case and a Plk1-mediated phosphorylation cascade involving several phosphorylation and binding events of the Mis18 complex subunits relieve the intramolecular interactions between the Mis18a N-terminal helical region and the HJURP binding surface of the Mis18a/b C-terminal helical bundle. This facilitates robust HJURP-Mis18a/b interaction in vitro and efficient HJURP centromere recruitment and CENP-A loading in cells. Overall, these studies also highlight the importance of the critical structural insights into the Mis18 complex we report here."
I am happy with the way cell biology data and the methods are presented so that they can be reproduced. The experiments are adequately replicated and the statistical analysis adequate. It will help to include sample size of cells or centromeres used for building the graphs.
We have now included this information in figure legends of Fig. 3a, 3c, 4b, 4c, 5b, 5c and 5d.
This is a strong interdisciplinary study using a variety of in vitro and in vivo techniques. Can the authors discuss if they expect chromatin associated Mis18 complex to host a similar structure as the soluble one? In other words, are they able to comment on any key differences between chromatin and non-chromatin associated Mis18 complexes.
We thank the reviewer for the suggestion. We agree that one cannot rule out the possibility of the Mis18 complex undergoing compositional and/or conformational variations during the processes of CENP-A loading at centromeres. We now explicitly discuss this possibility in the last paragraph of the discussion section (page 18 line 10): "Future work aimed at characterising the intermolecular contact points between the subunits of the Mis18 complex, centromeric chromatin and CCAN components and understanding if the Mis18 complex undergoes any conformational and/or compositional variations upon centromere association and/or during CENP-A deposition process, will be crucial to delineate the mechanisms underpinning the centromere maintenance."
Minor comments: -
In cell biology experiments, fluorescence intensities could be presented as a superplot for added value across cells and repeats (instead of bar graphs). More on superplot:https://doi.org/10.1083/jcb.202001064.
We thank the reviewers for this kind suggestion. We have now included graphs made using 'superplot' as suggested.
In general, ACA levels do not appear to change significantly between WT and mutant expressing cells although new CENP-A loading is significantly absent in the presence of a few mutants - please comment if ACA used here can recognise CENP-A. Would this mean that old CENP-A remains normally?
We thank the reviewer for this comment. While new CENP-A incorporated at centromeres is selectively labelled using the SNAP-tag, the ACA antibody used in these experiments can recognise CENP-A, CENP-B and CENP-C, with CENP-B being the primary target (Kallenberg, Clinical Rheumatology,1990). We would also like to note that ACA has commonly been used to locate the centromere in CENP-A loading assays where new CENP-A levels are assessed via selective labelling (e.g. McKinley 2014).
It is unclear whether any of the mutant acted in a dominant negative fashion in the presence of endogenous Mis18 proteins. It would have been useful to test this particularly in the context of mis18alpha mutants that seem to fully abolish new CENP-A recruitment.
As Mis18 subunits oligomerise (homo and hetero), we thought expressing these mutants in the presence of endogenous proteins might interfere with endogenous protein in a heterogenous manner and might make the interpretation difficult. Hence, we did not test this. Instead, as described in the manuscript we have tested these mutants in siRNA rescue experiments (Fig. 3, 4 and 5).
In figure 3a, GFP panel (input lane, 1) is shown to mark a band corresponding to GFP. Is this expected? Please comment.
Yes, as a control, an empty vector was transfected to express just GFP along with Mis18a-mCherry. These were used to show that there was no unspecific interaction between the beads used for IP or Mis18a-mCherry and GFP tag, and that any interaction seen was due to Mis18b. A similar control was used in S4b, where mCherry was expressed along with Mis18b-GFP. We have now clarified this in the corresponding legends of Fig. 4a and S4b.
Would be useful to have the scale for the cropped images presented as insets. Figure 4B should read YFP and not YPF.
We apologise for this typographical error. We have now corrected this.
The authors may want to explain whether the tag differences matter for their study (Case in point: His-SUMO-Mis18a191-233 WT and mutant His-MBP-Mis18b188-229 proteins).
The MBP tag was chosen to perform amylose pull-down assays, whereas the SUMO tag was chosen to increase the protein size. This is crucial as the C-terminal fragments of Mis18a and Mis18b are less than 50 amino acids long and are not easy to visualise by the band intensity in the Coomassie-stained SDS PAGE gels.
Reviewer #3 (Significance (Required)):
This work elucidates the structural basis of Mis18 complex assembly and the intermolecular interfaces essential for Mis18 functions. This is a significant advance in the field as it helps researchers in the field better understand CENP-A deposition and mechanism underpinning the maintenance of centromere identity. This is a broad area of research benefitting those studying cell division, genome stability, centromere identity and epigenetics might all be interested in and influenced by these findings. Novelty and strength lies in combining structural and cell biology work. Strengths of the work are structural details of the Mis18 complex. Minor weakness is the link between Mis18 structure and Centromere inheritance is limited to one immunostaining assay (I have mentioned this as a minor comment because addressing this may not be within the scope of this manuscript and is likely to require a repeat of a vast majority of the work with additional reagents which may not directly add value to the current manuscript).
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Referee #3
Evidence, reproducibility and clarity
Centromere identity is defined by CENP-A loading to specific sites on genomic DNA. CENP-A loading is known to rely on the Mis18 complex, and several regulators are known; yet how the Mis18 complex achieves this complex process has remained puzzle. By elucidating the structural basis of Mis18 complex assembly using integrative structural approaches the authors show that multiple homo and heterodimeric interfaces of Mis18alpha, beta and Mis18BP1 are involved in centromere maintenance. The authors show that Mis18alpha can associate with centromeres and deposit CENP-A independent of Mis18 β. Mis18α functions in CENP-A deposition at centromeres independent of Mis18β. Mis18β is required for maintaining a specific level of CENP-A occupancy at centromeres. Thus, using structure-guided and separation-of-function mutants the study reveals how Mis18 complex ensures centromere maintenance.
Major comments:
This is an excellent study on centromere inheritance, combining structural and cell biology techniques. The comments here primarily refer to Cell biology aspect of the work.
- Figures show that new CENP-A deposits in Mis18βL199D/I203D mutants, but the level was reduced moderately. Based on this observation, the authors make a strong conclusion that Mis18β licenses the optimal levels of CENP-A at centromeres. Mis18α may be essential for both CENP-A incorporation and depositing a specific amount of CENP-A, as Mis18α and CENP-A levels are both reduced in Mis18βL199D/I203D mutants which failed to form the triple helical assembly with Mis18α as shown in Figure 3B and 3C. The authors may want to qualify some of these claims as preliminary or speculative.
- This work and others show that phosphorylation of Mis18BP1 by CDK1 can interfere with complex function (Spiller et al., 2017, Pan et al., 2017). Does the structure provide any insight into PLK1-mediated phosphorylation surfaces for activation of the complex? If yes, a brief discussion would help to link CDK1 and PLK1 mediated opposing actions will strengthen the work.
- I am happy with the way cell biology data and the methods are presented so that they can be reproduced. The experiments are adequately replicated and the statistical analysis adequate. It will help to include sample size of cells or centromeres used for building the graphs.
- This is a strong interdisciplinary study using a variety of in vitro and in vivo techniques. Can the authors discuss if they expect chromatin associated Mis18 complex to host a similar structure as the soluble one? In other words, are they able to comment on any key differences between chromatin and non-chromatin associated Mis18 complexes.
Minor comments:
In cell biology experiments, fluorescence intensities could be presented as a superplot for added value across cells and repeats (instead of bar graphs). More on superplot: https://doi.org/10.1083/jcb.202001064. In general, ACA levels do not appear to change significantly between WT and mutant expressing cells although new CENP-A loading is significantly absent in the presence of a few mutants - please comment if ACA used here can recognise CENP-A. Would this mean that old CENP-A remains normally?
It is unclear whether any of the mutant acted in a dominant negative fashion in the presence of endogenous Mis18 proteins. It would have been useful to test this particularly in the context of mis18alpha mutants that seem to fully abolish new CENP-A recruitment.
In figure 3a, GFP panel (input lane, 1) is shown to mark a band corresponding to GFP. Is this expected? Please comment. Would be useful to have the scale for the cropped images presented as insets.
Figure 4B should read YFP and not YPF.
The authors may want to explain whether the tag differences matter for their study (Case in point: His-SUMO-Mis18a191-233 WT and mutant His-MBP-Mis18b188-229 proteins).
Significance
This work elucidates the structural basis of Mis18 complex assembly and the intermolecular interfaces essential for Mis18 functions. This is a significant advance in the field as it helps researchers in the field better understand CENP-A deposition and mechanism underpinning the maintenance of centromere identity. This is a broad area of research benefitting those studying cell division, genome stability, centromere identity and epigenetics might all be interested in and influenced by these findings. Novelty and strength lies in combining structural and cell biology work.
Strengths of the work are structural details of the Mis18 complex. Minor weakness is the link between Mis18 structure and Centromere inheritance is limited to one immunostaining assay (I have mentioned this as a minor comment because addressing this may not be within the scope of this manuscript and is likely to require a repeat of a vast majority of the work with additional reagents which may not directly add value to the current manuscript).
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Referee #2
Evidence, reproducibility and clarity
Summary:
The manuscript "structural basis for Mis18 complex assembly: implications for centromere maintenance" by Thamkachy and colleagues describes a study that uses structural analysis to test essential candidate residues in Mis18 complex components in CENP-A loading. For chromosomes to faithfully segregate during cell division, CENP-A levels must be maintained at the centromere. How CENP-A levels are maintained is therefore important to understand at the mechanistic level. The Mis18 complex has been found to be important, but how exactly the various Mis18 complex components interact and how they regulate new CENP-A loading remains not fully understood. This study set out to characterize the critical residues using X-ray crystallography, negative staining EM, SEC analysis, molecular modeling (Raptorx, AlphaFold2, and AlphaFold-multimer) to identify the residues of Mis18a and Mis18b that are critical for the formation of the Mis18a/b hetero-hexamer and which residues are important for Mis18a and Mis18BP1 interactions. A complex beta-sheet interface dictates the Mis18a and Mis18b interactions. Mutating the Mis18a residues that are important for the Mis18a/b interactions resulted in impaired pull-down of Mis18b and reduced centromeric levels of mutated Mis18a. The functional consequences of mutating residues that impair Mis18a/b interactions is that with reduced centomeric levels of Mis18a, also impaired new CENP-A loading. Interestingly, mutated Mis18b did not impact centromeric Mis18a levels and only modestly impaired new CENP-A loading. These data were interpreted that Mis18a is critical for new CENP-A loading, whereas Mis18b might be involved in finetuning how much new CENP-A is loaded. Overall, it is a very well described and well written study with exciting data.
Major comments:
- Overall, the structural data and the IF data support the importance of Mis18a residues 103-105 are critical for centromeric localization and new CENP-A loading, whereas Mis18b residues L199 and I203 are critical for centromeric localization, but only very modestly impair centromeric Mis18a localization and new CENP-A loading. In the discussion the authors argue that the N-terminal helical region of Mis18a mediate HJURP binding. This latter is postulated based on published work, but not tested in this work. This should be clarified as such.
- Overall, the authors clearly describe their data and methodology and use adequate statistical analyses. The structural data of the Mis18a/b complex being a hetero-hexamer is convincing, but the validation in vivo is missing. As structural experiment are not performed under physiological conditions, it is important to establish the stoichiometry in vivo to further support the totality of the findings of the structural experiments and modeling. The data for the hierarchical assembly of Mis18a and Mis18b at the centromere and its importance in new CENP-A loading is convincing. An additional open question is whether "old" centromeric CENP-A or HJURP:new CENP-A complex is needed to recruit Mis18a to the centromere and whether the identified residues have a role in Mis18a centromeric localization. These data would provide a solid link between the Mis18 complex and how it is directly linked to new CENP-A loading.
Minor comments:
- The bar graphs shown ideally also show the individual data points for the authors to appreciate the spread of the data. These figures can be replicated in the Supplemental to avoid making the main figures look too busy.
Significance
- This study uses a broad range of structural techniques, including molecular modeling which were subsequently validated by in vitro pull-down assays, co-IP, and IF. This combination of these techniques is important because many structural techniques cannot be performed under physiological conditions. Validating the main findings of the structural results by IF and co-IP is therefore critical.
- This work greatly advances our structural understanding how Mis18a, Mis18b, and Mis18BP1 form the Mis18 complex and how the critical residues in especially Mis18a help the Mis18 complex localize to the centromere and influence new CENP-A loading. This study also provides the first strong evidence in hierarchical assembly of the Mis18 complex.
- How centromere identity is maintained is a critical question in chromosome biology and genome integrity. The Mis18 complex has been identified as an important complex in the process. Several structural and mutational studies (all adequately cited in this manuscript) have tried to address which residues guide the assembly and functional regions of the Mis18 complex. This work builds and expands our understanding how especially Mis18a holds a pivotal role in both Mis18 complex formation and its impact on maintaining centromeric CENP-A levels.
- This work will be of interest to the chromosome field in general and anyone studying the mechanism of cell division.
- Chromatin, centromere, CENP-A, cell division. This reviewer has limited expertise in structural biology.
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Referee #1
Evidence, reproducibility and clarity
Summary
Maintenance of the histone H3 variant CENP-A at centromeres is necessary for proper kinetochore assembly and correct chromosome segregation. The Mis18 complex recruits the CENP-A chaperone HJURP to centromeres to facilitate CENP-A replenishment. Here the authors characterise the Mis18 complex using hybrid structural biology, and determine complex interface separation-of-function mutants.
Major Comments
The SAXS and EM data on the full-length Mis18 components must be included in the main Figures, either as an additional figure or by merging/rearranging the existing figures. The authors discuss these results in three whole paragraphs, which are a very important part of the paper.
Could the authors also compare the theoretical SAXS scattering curves generated by their final model(s) with the experimental SAXS curves? This would provide some additional evidence for the overall shape of their complex model beyond the consistency with the Dmax/Rg.
Minor Comments
While the introduction is clearly written, an additional cartoon schematic, representing the system/question would be helpful to a non-specialist reader to interpret the context of the study.
No doubt the authors had a reason for choosing their figure allocation, but I wonder if more material couldn't be brought from the supplementaries into the main figures?
Page 6 "Mis18-alpha possesses an additional alpha-helical domain" - please make it clear in addition to what (I assume it's in addition to Mis18-beta).
Page 7 - Report the RMSD of the Pombe vs. Human Mis18-alpha yipee structures?
Page 7 - "We generated high-confidence structural models...." is there a metric for the confidence as reported by RaptorX? Perhaps includinging the PAE plots in the supplementary for the AlphaFold generated models would be useful?
Figure 1 - Perhaps label figure 1b as being experimentally determined, with the R values (as for Figure 1d), and 1c being a predicted model.
Page 8 "This observation is consistent with the theoretically calculated pI of the Mis18alpha helix" This is a circular argument, of course this region has a low pI due to the amino acid composition. Please remove this statement.
Page 8 "...reveals tight hydrophobic interactions" these are presumably shown in Figure 1d rather than in the referenced 1e.
Page 8 - The authors should briefly somewhere discuss why there is a difference between their results and those in Pan et al 2009. As I understand it, the Pan et al paper was based in part on modelling with CLMS data as restraints.
Figure 1 - The labelling of the residues for Mis18-alpha in Figure 1d is problematic, they are black on dark purple (might be my printer/screen/eyes) suggest amending.
Figure S3a - Do the authors have some data to show the mass of the cross-linked complex that was loaded onto grids is consistent with what is expected?
Figure S3b - scale bar
Figure S3c - Could the authors show or explain the differences between these different 3D reconstructions?
Page 9 - The use of "AFM" for AlphaFoldMultimer" is a little confusing since AFM is the established acronym for Atomic Force Microscopy. Perhaps AF2M?
Figure S4a - Control missing for Mis18-alpha wild-type
Figure S4 d and e - The contrast between the bands and the background is very bad (at least in my copy).
Page 13 "Our structural analysis suggests that two Mis18BP1 fragments.....". How did you arrive at this conclusion? Is this based on the AlphaFold/RaptorX model? What additional evidence do you have that the positioning of the Mis18BP1 is correct? Does the CLMS data support this?
Figure 4a - Would the authors like to consider using a different colour for Mis18BP1? The contrast is not great, especially in the electrostatic surface inset.
Significance
General Assessment
The paper is extremely clearly written. Likewise the figures are beautifully presented and the data extremely clean and fully supportive of the authors conclusions. Indeed it is seldom that one sees the depth of the structural approaches (X-ray, CLMS, EM, SAXS) in one paper which is a huge strength of the manuscript. In addition the translation of this data into very clean cell biological experiments, makes the paper truly outstanding.
Advance
The authors provide the first model of the Mis18 complex, with extensive evidence to back up this model. The authors provide additional evidence as to how the deposition/renewal of CENP-A might be mediated by the Mis18 complex. The advance comes from both the level of clarity, detail, and scope achieved in this paper.
Audience
This will likely be of great interest to anyone with an interest in chromosome biology, plus be of interest to structural biologists as an outstanding example of hybrid structural biology.
Expertise
I am a biochemist with a background in structural biology with some familiarity with centromere biology
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www.biorxiv.org www.biorxiv.org
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Reply to the reviewers
Reply to the Reviewers
We would like to thank the reviewers for their insightful comments, which will significantly guide us in enhancing our manuscript. We are capable of addressing most of the concerns raised by the reviewers. However, we encounter limitations in addressing Reviewer 2's comment regarding the delineation between cell autonomy and non-autonomy. As highlighted by the reviewer, ideally, we would dissect the mechanisms underlying cell turnover within the M/+ wing pouch, particularly in terms of cell autonomy and non-autonomy. Unfortunately, clonal analysis is not feasible due to the 'salt and pepper' distribution pattern of cell death and subsequent proliferation within the M/+ wing pouch. Despite these challenges, we commit to making efforts to address these issues to the best of our ability. Furthermore, we will aim to present our findings with greater precision and without speculation, an approach we believe will significantly enhance the quality of our manuscript.
In this manuscript, we extend the insights gained from our previous study (Akai et al., PLOS Genetics, 2021) by uncovering a novel mechanism within the context of the M/+ mutant. We demonstrate that JNK-dependent exocytosis in dying cells is crucial for cell turnover in the M/+ wing pouch. This phenomenon of cell turnover, initiated by cell death and the following proliferation, is fundamental to a variety of processes in multicellular organisms, such as normal development, tissue homeostasis, wound healing, tumor development, and potentially tumor recurrence. While our analysis is specific to the M/+ mutant, the underlying mechanisms of cell-cell communication between dying and proliferating cells, which are still not fully understood, may have broader implications. Our findings offer significant contributions to the field of cell competition and suggest a framework for understanding the operating principles of multicellular communities through cell-cell communications. Although it is yet to be determined how these insights apply in various contexts, they possess the potential to guide future research.
Referee #1
It would be important to check how much JNK is sufficient to trigger the exocytosis upregulation. Is the accumulation of Cyt1 and CD63 vesicles in apoptotic cell common to any JNK dependent death or does it require the Minute background? Could the authors check whether clones expressing HepCA transiently in WT background also accumulate the same vesicles?
Response:
Following the reviewer's suggestion, we plan to examine whether the accumulation of Syt1- and CD63-positive vesicles in apoptotic cells is a general characteristic of JNK-dependent cell death or requires the Minute background. Specifically, we intend to check whether mitotic clones expressing HepCA in the wild-type eye-antennal disc to see if these vesicles also accumulate. Additionally, we will assess mitotic clones expressing Eiger in the wild-type eye-antennal disc, which activates JNK signaling. This is due to concerns that HepCA may induce cell death too strongly, potentially resulting in clones too small for effective analysis. Moreover, we also plan to express HepCA transiently only in the posterior region of the wing disc to further explore its effects.
- It would be relevant to have the status of JNK in Minute disc upon downregualtion of exocytosis. One could imagine some positive feedback between JNK activation, exocytosis, cell death and further JNK activation.
Response:
We thank the reviewer for the comment. As pointed out by the reviewer, there could be a positive feedback loop involving JNK activation, exocytosis, cell death, and further JNK activation. Our observations lend support to this hypothesis, as we specifically noted a significant reduction in the number of JNK-activating cells following targeted rab3 knockdown in these cells using puc-gal4 driver within the RpS3/+ wing disc (Fig R1, below). To further confirm the positive feedback loop between JNK activation and exocytosis, we plan to investigate the effects of downregulating unc-13 on JNK activation within the M/+ wing pouch, employing the JNK reporter TRE-DsRed for this purpose.
Additionally, we need to elucidate the molecular mechanism linking cell death and exocytosis. We are currently exploring two potential relationships between JNK activation, caspase signaling, and exocytosis, as depicted in Fig R2 below. To assess these possibilities, we aim to investigate if inhibiting apoptosis-either by introducing the H99/+ mutation or by overexpressing DroncDN or mirRHG-can affect JNK-mediated exocytosis in the RpS3/+ wing pouch.
So far, the evidence for the epistatic link between exocytosis, Wg and cell turnover is mostly based on colocalization and the similarity of the phenotype but I believe this may need some additional evidences. Ideally one would need to be able to enhance exocytosis and test whether Wg downregulation suppress the phenotype, but I am not sure that upregulation of core exocytosis genes will be sufficient to do this. Alternatively, if Wg is indeed downstream of the upregulation of exocytosis, the reduction of cell turnover upon Wg flattening (e.g. : ftz2-/+ background) should not be enhanced by the reduction of exocytosis. Moreover, could the authors test the status of Wg downstreams targets upon inhibition of exocytosis in the Minute background (for instance, do they see a supression of the nmo-LacZ upregulation that they previously characterised in Minute wing disc in 2021) ?
Response:
We thank the reviewer for the comment. In line with the reviewer's suggestion, exploring the enhancement of exocytosis would be valuable to elucidate the epistatic relationship between exocytosis, Wg signaling, and cell turnover. Therefore, we plan to attempt the overexpression of exocytosis-related genes to check if we can indeed enhance exocytosis. Additionally, in response to the reviewer's comment, we intend to investigate whether the reduction in cell turnover observed upon Wg attenuation (ftz2-/+background or Wg-/+ background) is not exacerbated by further reducing exocytosis. Furthermore, we intend to investigate the status of the Wg downstream target, specifically using nmo-lacZ, when exocytosis is inhibited in the RpS3/+ wing pouch.
Since Cyt1 and CD63 seem to mostly accumulate in apoptotic cells, it would be interesting to check their status in Minute wing disc upon apoptosis inhibition (e.g. : with H99 or mirRHG).
Response:
We thank the reviewer for the comment. Following the reviewer's suggestion, we intend to investigate whether inhibiting apoptosis, either through the introduction of H99/+ or by overexpressing DroncDN or mirRHG, could suppress the increase in CD63- or Sty1-positive vesicles in the M/+ wing pouch.
I would remain cautious about some of the statements, notably in the abstract, since some of them are mostly speculative and not really based on any experiments. For instance, the statement "This interaction between dying cells and their neighboring living cells is pivotal in determining cell fate, dictating which cells will undergo apoptosis and which cells will proliferate" is not backed up by any experiment (which would require to show that exocytosis and Wg from the dying cell specifically is required for the survival and proliferation of their neighbours, and/or showing that cell death occurs specifically in cells with local differences in Wg signaling). I would recommend to be more cautious here and us a clear conditional statement.
- *Response:
We thank the reviewer for their insightful comment. In response, we aim to present our findings with greater precision and to avoid speculative interpretations. At this stage, we have focused on revising the Abstract to include clear conditional statements, as suggested. Furthermore, we plan to comprehensively update the remaining sections of the manuscript to reflect the additional experiments requested by the reviewers. These updates will ensure a more cautious approach throughout the paper, aligning with the reviewer's recommendations.
__(page 2, line 34-39 in the "Abstract") __
"Our data also suggest a potential role for the Wg receptor Frizzled-2 (Fz2) in inducing cell-turnover within the M/+ wing pouch. Overall, our findings provide mechanistic insights into robust tissue growth through the orchestration of cell-turnover, which is primarily governed by JNK-mediated exocytosis in the context of Drosophila Minute/+ wing morphogenesis."
Other minor point:
The authors document Wg localisation in Minute wing disc upon expression of P35. It would be interesting to describe what is the status of Wg in Rps3+/- compared to WT without p35 (if I am correct, this was done in their previous article, and in that case it would be relevant to describe these former results in the main text).
Response:
We thank the reviewer for the comment. In the RpS3/+ wing pouch without p35, we were unable to detect any upregulation of Wg using the anti-Wg antibody (Fig R3, below). However, we observed an increase in GFP-Wg-positive puncta originating from a knock-in allele (McGough et al., Nature, 2020) within areas of massive cell death in the RpS3/+ wing pouch lacking p35, compared to the wild-type control (Fig 3B, compared to Fig 3A in the transferred manuscript). This increase is similar to the phenotype observed in the RpS3/+ wing pouch expressing p35, where Wg-positive puncta are significantly elevated (Fig R4B below, corresponding to Fig 3B in the original manuscript). Moreover, the increase in GFP-Wg-positive puncta in regions of massive cell death in the RpS3/+ wing pouch becomes more pronounced when utilizing a membrane-tethered anti-GFP nanobody (Vhh4-CD8) (McGough et al., Nature, 2020) (Fig 3G, compared to Fig 3F in the transferred manuscript). These observations indicate that Wg-positive puncta are indeed upregulated in the RpS3/+ wing pouch without p35 compared to the wild-type control.
In the transferred manuscript, we have now made modifications to Fig. 3 by replacing images of the RpS3/+ wing pouch overexpressing p35, which were stained with the anti-Wg antibody, with new images. These new images depict the RpS3/+ wing pouch that harbors the GFP-Wg knock-in allele, which was stained with both anti-GFP and anti-cDCP1 antibodies.
To clarify this point, we have now modified the sentence as follows:
(page 7, line 204-210)
Interestingly, we found that the RpS3/+ wing pouch expressing the cell death inhibitor p35 (which allows dying RpS3/+ cells to survive) exhibited elevated levels of Wg protein, compared to the wild-type control (Fig 3A and 3B). This increase in Wg protein was significantly diminished by overexpressing the JNK inhibitor Puc (Fig 3C), suggesting that Wg expression is upregulated via JNK signaling in the M/+ wing pouch, similar to apoptotic cells in which JNK signaling induces the production of secreted growth factor, including Wg (18, 53, 54). In addition, ____W____e found t____hat GFP-Wg-positive puncta, derived from a knock-in allele ____(34)____, ____were more abundant in the RpS3/+ wing pouch compared to the wild-type control (Fig 3A and 3B). This increase in GFP-Wg-positive puncta, ____especially in the area with massive cell death within the RpS3/+ wing pouch (Fig S3C-S3D'')_, was more evident when using a membrane-tethered anti-GFP nanobody (Vhh4-CD8), which immobilizes GFP-Wg on the cell surface _(34)____ (Fig 3F and 3G, quantified in Fig 3J).
Referee #2
Primary Concerns:
A significant challenge arises concerning the delineation of cell autonomy/non-autonomy. This study focuses on two distinct cell types, namely dying cells and proliferating cells. However, the consistent use of nub-gal4, a wing pouch driver, and the heterozygous minute mutant throughout the paper impedes the ability to conclusively analyze the autonomy of events. The authors previously posited that caspase-induced cell death triggers non-autonomous proliferation, but recent studies also suggested caspase-induced autonomous proliferation in both flies and mammals (Yosefzon et al. Mol. Cell 2018, Shinoda et al., PNAS 2019). Therefore, a meticulous distinction between autonomous and non-autonomous events, particularly through experimentation involving clones, is imperative. This necessity is particularly evident in Fig 4.
Response:
- As pointed out by the reviewer, it is ideal to dissect the mechanisms underlying cell turnover within the M/+ wing pouch, especially concerning cell autonomy and non-autonomy. However, clonal analysis is not feasible due to the pattern of cell death and subsequent proliferation occurring in a 'salt and pepper' distribution within the M/+* wing pouch. In response to this challenge, we found that almost dying cells do not undergo proliferation, as assessed by staining with the M phase marker phospho-Histone H3 (Fig R5, below).
We also plan to investigate whether JNK-activating cells similarly refrain from proliferating, which will be assessed by staining with the anti-phospho-Histone H3 antibody.
Additionally, about Fig 4, considering the evidence presented in this study, which demonstrates that dying cells increase Wg secretion through JNK-dependent exocytosis (Fig 3G-3H'), and given that Fz2 is expressed in adjacent cells within the M/+ wing pouch (Fig 4B-C'' and Fig S4B-C''), it is plausible that these neighboring cells could receive Wg via Fz2, leading to the upregulation of Wg signaling in these cells in the M/+ wing pouch. This upregulation of Wg signaling is supported by Fig S3A in the transferred manuscript. However, we were unable to delineate the specific role of Fz2, particularly in terms of cell autonomy and non-autonomy. In response to this challenge, we aim to explore whether cell turnover can be inhibited by enhancing Wg signaling exclusively in JNK-activated cells through the overexpression the active form of ArmadilloS10 (Baena-Lopez LA et al., Sci Signal., 2009), utilizing the puc-gal4 driver. Should cell turnover be inhibited under these conditions, it would indicate that differences in Wg signaling activity between dying cells and their neighboring cells drive cell turnover. While the exact mechanism of Fz2 remains unclear, the inhibition of cell turnover under these conditions clearly demonstrates that differences in Wg signaling activity play a significant role in cell turnover. Additionally, in our response to Reviewer 2's comment No. 2, we outline our intention to investigate whether the increase in Wg signaling could be induced by JNK-dependent exocytosis. Accordingly, we plan to assess the effects of downregulating JNK signaling or exocytosis on the elevated Wg signaling activity observed in the RpS3/+ wing pouch.
Furthermore, we intend to present our findings with greater precision, steering clear of speculative interpretations. At this stage, we have focused on revising the Abstract to include clear conditional statements, as detailed below. We plan to comprehensively update the remaining sections of the manuscript to reflect the additional experiments requested by the reviewers.
(page 2, line 34-39 in the "Abstract")
"Our data also suggest a potential role for the Wg receptor Frizzled-2 (Fz2) in inducing cell-turnover within the M/+ wing pouch. Overall, our findings provide mechanistic insights into robust tissue growth through the orchestration of cell-turnover, which is primarily governed by JNK-mediated exocytosis in the context of Drosophila Minute/+ wing morphogenesis."
Closely tied to the issue of cell autonomy/non-autonomy is the question of how cells differentiate Wg from dying cells and the dorsal-ventral boundary.
Response:
Wg is expressed at the dorsal-ventral boundary in both wild-type and M/+ wing discs. However, we observed in our previous study that Wg signaling activity was significantly more elevated in the RpS3/+ pouch compared to the localized activation in wild-type controls at the same developmental stage, as assessed by the nmo-lacZ reporter (Fig 3C-D' in Akai et al., PLOS Genetics, 2021, as also shown in Fig R6A-B' below). Interestingly, the areas of massive cell death in the RpS3/+ wing pouch always corresponded to the areas of relatively lower Wg signaling activity (Fig S3A in the transferred manuscript). Moreover, our previous study revealed that decreasing or increasing Wg signaling activity, thus reducing the aberrant Wg signaling gradient, significantly inhibited cell death in the M/+ wing pouch (Fig 3I-K in Akai et al., PLOS Genetics, 2021, as also shown in Fig R6C-E' below). This suggest that the aberrant Wg signaling gradient is crucial for massive cell-turnover in the M/+ wing pouch. As also described above, considering the evidence presented in this study, which demonstrates that dying cells increase Wg secretion through JNK-dependent exocytosis (Fig 3G-3H'), and given that Fz2 is expressed in adjacent cells (Fig 4B-C'' and Fig S4B-C'') within the M/+ wing pouch, it is plausible that these neighboring cells could receive Wg via Fz2, leading to the upregulation of Wg signaling in these cells within the M/+ wing pouch. To further investigate whether the increase in Wg signaling could be induced by JNK-dependent exocytosis, we plan to examine the effects of downregulating JNK signaling or exocytosis on the elevated Wg signaling activity observed in the RpS3/+ wing pouch. Should Wg signaling activity decrease as a result of these genetic interventions, it would imply that the enhanced Wg signaling in the M/+ wing pouch depends on JNK-mediated exocytosis.
In Fig 1, the authors interpret the upregulation of exocytosis-related genes as indicative of increased exocytosis. However, this interpretation lacks direct evidence and overlooks the possibility of opposing effects. For example, autophagosome accumulation means either activation or inhibition of autophagy. Or, in case of Dilp secretion, absence of vesicles indicates upregulation of secretion. To substantiate their claim, the authors must provide more conclusive evidence of increased exocytosis. Fig 2 suggests that inhibiting exocytosis-related genes suppresses caspase activation, favoring the proposition that exocytosis is upregulated. However, demonstrating a direct increase in exocytosis in minute cells would bolster their argument. Higher resolution imaging of the exosome marker, with overlayed images, would enhance clarity too.
Response:
We have demonstrated an increase in the number of vesicles positive for EGFP-CD63 (an exosome marker) and Syt1-EGFP (a vesicle marker) in the RpS3/+ wing pouch compared to the wild-type control (Fig 1A, 1B, 1G, and 1H in the transferredmanuscript). To more directly investigate whether exocytosis is indeed elevated in the M/+ wing pouch, we plan to assess if cells activating JNK signaling upregulate the production of extracellular vesicles. This will be done by specifically expressing the EGFP-CD63 probe in JNK-activating cells, utilizing the puc-gal4 driver for targeted expression. Additionally, following the reviewer's suggestion, we plan to prepare high resolution images of the exosome marker, with overlayed images in the revised manuscript.
Fig 3 introduces ambiguity regarding the relationship between cell death and exocytosis. The authors assert that dying cells exhibit elevated Wg protein levels compared to the wild-type control but omit an important comparison to the minute disc. Moreover, while Figs 1-2 propose a signaling cascade involving minute>JNK>exocytosis>cell death, Fig 3 implies that cell death regulates exocytosis. The coherence of their model and logic requires clarification - specifically, elucidating the molecular coupling mechanism between cell death and exocytosis.
Response:
We observed an increase in GFP-Wg-positive puncta originating from a knock-in allele (McGough et al., Nature, 2020) in the area of massive cell death within the RpS3/+ wing pouch, compared to the wild-type control (Fig 3A and 3B in the transferredmanuscript). However, as pointed out by the reviewer, it is challenging to determine whether the GFP-Wg-positive puncta are emanating from dying cells, given that Wg is secreted from the cells that produce it. To address this issue, we employed a membrane-tethered anti-GFP nanobody (Vhh4-CD8 morphotrap) designed to capture GFP-Wg on the cell surface, thereby preventing the diffusion of GFP-Wg from its producing cells. By utilizing the Vhh4-CD8 morphotrap, we found that GFP-Wg levels are indeed elevated in areas of cell death compared to adjacent regions within the RpS3/+ wing pouch (Fig 3G in the transferred manuscript).
To clarify this point, we have now modified the sentence as follows:__ __
(page 7, line 204-210)
In addition, ____W____e found t____hat GFP-Wg-positive puncta, derived from a knock-in allele ____(34)____, ____were more abundant in the RpS3/+ wing pouch compared to the wild-type control (Fig 3A and 3B). This increase in GFP-Wg-positive puncta, ____especially in the area with massive cell death within the RpS3/+ wing pouch (Fig S3C-S3D'')_, was more evident when using a membrane-tethered anti-GFP nanobody (Vhh4-CD8), which immobilizes GFP-Wg on the cell surface _(34)____ (Fig 3F and 3G, quantified in Fig 3J).
Additionally, as pointed out by the reviewer, we need to elucidate the molecular mechanism linking cell death and exocytosis. We are currently exploring two potential relationships between JNK activation, caspase signaling, and exocytosis, as depicted in Fig R2 below. To assess these possibilities, we aim to investigate if inhibiting apoptosis-either by introducing the H99/+ mutation or by overexpressing DroncDN or mirRHG-can affect JNK-mediated exocytosis in the RpS3/+ wing pouch.
Specific Points:
In Fig S1D, contrary to the authors' claim, cadp2 is not upregulated in a JNK-dependent manner.
Response:
We apologize for any confusion caused. We found that Cadps expression in the RpS3/+ wing pouch was increased compared to both the wild-type control (2.29-fold increase, RpS3/+ compared to wild-type) and the RpS3/+ wing pouch expressing Puckered (Puc), driven by the nub-gal4 driver (3.33-fold increase, RpS3/+ compared to RpS3/+ + Puckered). This suggests that the increase in Cadps expression in the RpS3/+ wing pouch is dependent on JNK signaling. We have now revised Fig. S1D for clearer representation. We also have made modifications in the transferred manuscript as follows:
(page 5, line 107-113)
"Mining the list of genes differentially expressed in the RpS3/+ wing pouch cells dependent on JNK signaling (Fig S1C and S2 Table), we noticed that among the genes associated with the "secretion by cell" GO term (Fig S1B), the evolutionarily conserved exocytosis-related genes unc-13, SNAP25, and cadps (Calcium-dependent secretion activator) were upregulated in a JNK-dependent manner (2.29-fold increase, RpS3/+ compared to wild-type; 3.33-fold increase, RpS3/+ compared to RpS3/+ +_ Puckered)_ (Fig S1D)."
When detecting multiple proteins in the same tissue, it is advisable for the authors to present overlayed images to enhance the clarity of their findings. Many pictures require higher magnification too.
Response:
Following the reviewer's suggestion, we have overlayed images in Fig 1A-D, Fig 1G-J, and Fig S1E in the transferredmanuscript. Additionally, following the reviewer's suggestion, we plan to prepare high resolution images in the revised manuscript.
In Fig 1A, the observed upregulation of EGFP-CD63 and Syt1-EGFP may potentially result from an artifactual effect of apoptosis. To validate their findings are specific, the authors should include negative controls that do not exhibit upregulation in dying cells.
Response:
Following the reviewer's suggestion, we used the CD8-PARP-Venus probe as a negative control. We observed that CD8-PARP-Venus-positive puncta were minimally present (Fig R7, below), indicating that the upregulation of EGFP-CD63 and Syt1-EGFP in the RpS3/+ wing pouch is indeed occurring, rather than being an artifactual effect of apoptosis. We intend to incorporate this negative control into the revised manuscript.
Referee #3
Major comments:
Figure 1A-H, S1E. The authors used EGFP-CD63 and Syt1-EGFP as markers of exocytosis. They see an increased number of puncta in apoptotic cells. Is this a specific effect in the dying cells in M mutant discs, or is it a general effect in apoptotic cell death? This should be examined in a condition where apoptosis is induced independently of M mutants such as nub-reaper or nub-hid.
Response:
We thank the reviewer for the comment. To ascertain whether the increase in EGFP-CD63-/Sty1-EGFP-positive puncta is specific to dying cells in M/+ mutants or a general characteristic of apoptotic cell death, we examined the presence of EGFP-CD63-positive puncta in the wing pouch, where Reper (Rpr) was expressed under the control of the nub-gal4 driver. Unfortunately, the expression of Rpr driven by nub-gal4 resulted in significant cell death, preventing us from drawing a definitive conclusion (Fig R8, below). Nonetheless, we did observe EGFP-CD63-positive puncta under these conditions, as indicated by the arrowheads in Fig R8 below. To further investigate, we plan to induce temporary expression of Rpr in the wing pouch using a combination of the temperature-sensitive Gal80 and the nub-gal4 driver.
Is exocytosis actually upstream or downstream of cell death, or both? The authors are kind of vague about it. On one hand, they say the dying cells induce exocytosis and secrete Wg. On the other hand, unc13RNAi can suppress cell death (Figure 1D', J'). Please clarify.
Response:
As pointed out by the reviewer, we need to clarify whether exocytosis actually occurs upstream or downstream of cell death. We are currently exploring two potential relationships between JNK activation, caspase signaling, and exocytosis, as depicted in Fig R2 below. To assess these possibilities, we aim to investigate if inhibiting apoptosis-either by introducing the H99/+ mutation or by overexpressing DroncDN or mirRHG-can affect JNK-mediated exocytosis in the RpS3/+ wing pouch.
Figure 1L-P. The observation of Ca++ flashes is very interesting. However, are they important for exocytosis, cell death and compensatory proliferation? Right now, this is just a stand-alone observation. Can mutants affecting Ca++ signaling block exocytosis, cell death and comp prol?
Response:
We thank the reviewer for the comment. we plan to investigate whether the downregulation of Ca++ signaling impacts exocytosis, cell death, and compensatory proliferation in the M/+ wing pouch. This will be achieved by downregulating genes essential for sensing intracellular calcium concentrations (Rizo J and Rosenmund C, Nat Struct Mol Biol., 2008; Sudhof TC, Annu Rev Neurosci., 2004) and genes encoding voltage-gated calcium channels (Kuromi H et al., Neuron, 2004).
Figure 3B'. Can you visualize aberrant wg expression in RpS3/+ wing discs only in the presence of p35? The expression of p35 in apoptotic cells generates undead cells which by itself induce Wg expression in a JNK-dependent manner (Perez-Garijo et al 2004; Ryoo et al 2004). Also, in Figure 3B', Wg is upregulated in the ventral half of the pouch, whereas in other figures (4B for example) apoptosis is strongly induced in the dorsal half. Does that make sense?
Response:
We thank the reviewer for the comment. In the RpS3/+ wing pouch without p35, we were unable to detect any upregulation of Wg using the anti-Wg antibody (Fig R3, below). However, we observed an increase in GFP-Wg-positive puncta, derived from a knock-in allele (McGough et al., Nature, 2020), in areas of massive cell death within the RpS3/+ wing pouch without p35, relative to the wild-type control (Fig 3B, compared to Fig 3A in the transferred manuscript). This increase is similar to the phenotype observed in the RpS3/+ wing pouch expressing p35, where Wg-positive puncta are significantly elevated (Fig R4B below, corresponding to Fig 3B in the original manuscript). Moreover, the increase in GFP-Wg-positive puncta in regions of massive cell death in the RpS3/+ wing pouch becomes more pronounced when utilizing a membrane-tethered anti-GFP nanobody (Vhh4-CD8) (McGough et al., Nature, 2020) (Fig 3G, compared to Fig 3F). These observations indicate that Wg-positive puncta are indeed upregulated in the RpS3/+ wing pouch without p35 compared to the wild-type control.
In the transferred manuscript, we have now made modifications to Fig. 3 by replacing images of the RpS3/+ wing pouch overexpressing p35, which were stained with the Wg antibody, with new images. These new images depict the RpS3/+ wing pouch that harbors the GFP-Wg knock-in allele, which was stained with both anti-GFP and anti-cDCP1 antibodies.
To clarify this point, we have now modified the sentence as follows:
(page 7, line 204-210)
Interestingly, we found that the RpS3/+ wing pouch expressing the cell death inhibitor p35 (which allows dying RpS3/+ cells to survive) exhibited elevated levels of Wg protein, compared to the wild-type control (Fig 3A and 3B). This increase in Wg protein was significantly diminished by overexpressing the JNK inhibitor Puc (Fig 3C), suggesting that Wg expression is upregulated via JNK signaling in the M/+ wing pouch, similar to apoptotic cells in which JNK signaling induces the production of secreted growth factor, including Wg (18, 53, 54). In addition, ____W____e found t____hat GFP-Wg-positive puncta, derived from a knock-in allele ____(34)____, ____were more abundant in the RpS3/+ wing pouch compared to the wild-type control (Fig 3A and 3B). This increase in GFP-Wg-positive puncta, ____especially in the area with massive cell death within the RpS3/+ wing pouch (Fig S3C-S3D'')_, was more evident when using a membrane-tethered anti-GFP nanobody (Vhh4-CD8), which immobilizes GFP-Wg on the cell surface _(34)____ (Fig 3F and 3G, quantified in Fig 3J).
Additionally, we apologize for any confusion caused by Fig 3B'. It is noteworthy that cell death sometimes occurs more prominently in the ventral half of the RpS3/+ wing pouch than in the dorsal half (Fig R9, below). Furthermore, the increase in Wg level can be more pronounced on the ventral side, or at times, it is equally strong on both the dorsal and ventral sides (Fig S3C-D in the transferred manuscript).
Can wg RNAi in cells destined to die (puc-Gal4 UAS-wgRNAi) suppress apoptosis and comp prol?
Response:
Following the reviewer's suggestion, we intend to investigate whether expressing Wg-RNAi in JNK activated cells, using the puc-gal4 driver, could suppress apoptosis and compensatory proliferation.
Figure 3D,E. Use cDcp1 as apoptotic marker instead of CD63-mCherry which is not an apoptotic marker.
Response:
Following the reviewer's suggestion, we have now utilized the cDCP1 antibody as an apoptotic marker in Fig S3B-D'' in the transferred manuscript, as described in the Reviewer 3's comment No.4.
Figure 4A' and B'. I am not sure there is much of a difference in the expression of fz2-lacZ in wild-type and RpS3/+ discs. The quantification in 4F shows there is no difference in the dorsal half of the pouch where massive apoptosis occurs. Can you generate a condition in which only one compartment (anterior or posterior) is mutant for RpS3/+, while the other compartment is wt? That would allow direct side-by-side comparison. Comparisons between different discs is problematic.
Response:
We thank the reviewer for the comment. Following the reviewer's suggestion, we conducted a more detailed investigation into the differences in fz2-lacZ expression levels between wild-type and RpS3/+ wing discs. We found that the expression level of fz2-lacZwas indeed elevated in the RpS3/+ wing pouch. This elevation in expression is demonstrated by the results of the genetic rescue experiment in the posterior compartment of RpS3/+ wing discs, where overexpression of RpS3 using the engrailed-gal4 driver led to a reduction in fz2-lacZ expression compared to the anterior RpS3/+ control (Fig R10, below).
After conducting statistical analysis, we plan to include Fig R10 in the revised manuscript.
There is some inconsistency in the presence of apoptotic cells and presence of cells which secrete Wg. Apoptotic cells occur in large cell clusters (Fig. 2G, 3H', S3A', S4B), while markers of exocytosis and Wg are present in individual puncta (Fig 3D', E', S3C,E). That does not seem to fit with the authors' conclusion that dying cells secrete Wg by exocytosis. Are all dying cells secreting Wg through exocytosis? Please explain.
Response:
We thank the reviewer for the comment. As highlighted by the reviewer, it appears that not all dying cells secrete Wg through exocytosis. Beyond exosomes, various mechanisms for Wg/Wnt transport have been proposed, including those mediated by lipoprotein particles, the cell-surface proteoglycan Dally-like protein (Dlp), and filopodia-like cellular extensions known as cytonemes. Therefore, it's plausible that dying cells may also utilize these additional mechanisms for Wg transport alongside exosomes. We have incorporated this explanation into the transferred manuscript as follows:
(page 9, line 272-286)
Previous studies have identified exosomes as carriers of Wnt/Wg in the extracellular space of both mammalian and Drosophila cells, including wing disc cells (28, 49, 50, 51, 52, 64). Concurrently, alternative mechanisms for Wg transport, such as those involving lipoprotein particles or a lipocalin Swim in the Drosophila wing disc, have been reported (29, 65). Additionally, the cell-surface proteoglycan Dally-like-protein (Dlp) has been reported to enable long-range signaling of the palmitoylated Wg _(51)._ Intriguingly, Wnt/Wg transport has also been observed through filopodia-like cellular extensions known as cytonemes (66, 67, 68, 69). In our study of the M/+_ wing disc, a model characterized by massive cell-turnover, we observed partial colocalization of Wg-GFP puncta with exosomal markers such as CD63-mCherry and Hrs._ Our data also suggest that Wg secretion through exocytosis may not uniformly occur among all dying cells within this context. It is noteworthy that whereas dying cells frequently form large clusters, exosomal markers and Wg typically localize within individual puncta. This disparity suggests that while exosomes from dying cells significantly contribute to Wg transport within the ____M/+____ wing pouch, other pathways may also be operative.
I was a bit confused by the conclusion of the authors about the results in Figure 4G-I. What do they mean by "difference in Fz2 expression"? Are they referring to the gradient that they described in their previous work? Or is it just the absolute level of Fz2 that determines apoptosis and proliferation? If the latter, is the gradient still present (at least in fz2/+), just at a lower level?
Response:
I apologize for any confusion caused by the way we presented our conclusions regarding the results depicted in Figure 4G-I in the original manuscript.
In our previous study, we observed that Wg signaling activity was elevated much more broadly in the RpS3/+ pouch compared to the localized activation observed in the wild-type control at the same developmental stage, as assessed by the nmo-lacZ reporter(Fig 3D in Akai et al., PLOS Genetics, 2021, as also shown Fig. R6 below). Interestingly, the areas of massive cell death in the RpS3/+ wing pouch always corresponded to the areas of relatively lower Wg signaling activity (as also shown in Fig S3A in the transferred manuscript). Moreover, our previous study revealed that decreasing or increasing Wg signaling activity, thus reducing the aberrant Wg signaling gradient, significantly inhibited cell death in the M/+ wing pouch (Fig 3I-K in Akai et al., PLOS Genetics, 2021, as also shown in Fig R6C-E' below). This suggest that the aberrant Wg signaling gradient is crucial for massive cell-turnover in the M/+ wing pouch.
Considering the evidence presented in this study, which demonstrates that dying cells increase Wg secretion through JNK-dependent exocytosis (Figure 3G-3H'), and given that Fz2 is expressed in adjacent cells within the M/+ wing pouch (Figure 4B-C'' and Fig S4B-C''), it is plausible that these neighboring cells could receive Wg via Fz2, leading to the upregulation of Wg signaling in these cells in the M/+ wing pouch.
However, we were unable to delineate the specific role of Fz2, particularly in terms of cell autonomy and non-autonomy as highlighted by Reviewer 2, through clonal analysis due to the occurrence of cell death and subsequent proliferation in a salt-and-pepper pattern within the M/+ wing pouch. In response to this challenge, we aim to explore whether cell turnover can be inhibited by enhancing Wg signaling exclusively in JNK-activated cells through the overexpression the active form of ArmadilloS10(Baena-Lopez LA et al., Sci Signal., 2009), utilizing the puc-gal4 driver. Should cell turnover be inhibited under these conditions, it would indicate that differences in Wg signaling activity between dying cells and their neighboring cells drive cell turnover. While the exact mechanism of Fz2 remains unclear, the inhibition of cell turnover under these conditions clearly demonstrates that differences in Wg signaling activity play a significant role in cell turnover. Additionally, in our response to Reviewer 2's comment No.2, we outline our intention to investigate whether the increase in Wg signaling could be induced by JNK-dependent exocytosis. Accordingly, we plan to assess the effects of downregulating JNK signaling or exocytosis on the elevated Wg signaling activity observed in the RpS3/+ wing pouch.
Furthermore, we intend to present our findings with greater precision, steering clear of speculative interpretations. At this stage, we have focused on revising the Abstract to include clear conditional statements, as detailed below. We plan to comprehensively update the remaining sections of the manuscript to reflect the additional experiments requested by the reviewers.
(page 2, line 34-39 in the "Abstract")
"Our data also suggest a potential role for the Wg receptor Frizzled-2 (Fz2) in inducing cell-turnover within the M/+ wing pouch. Overall, our findings provide mechanistic insights into robust tissue growth through the orchestration of cell-turnover, which is primarily governed by JNK-mediated exocytosis in the context of Drosophila Minute/+ wing morphogenesis."
Regarding point 8, given that reduction of Fz2 can suppress apoptosis in RpS3/+ wing discs, how does it regulate apoptosis when it is down-regulated anyway in apoptotic cells (Fig 4B', S4B')?
Response:
As described in our response to point 9, our previous study suggested that we observed that Wg signaling activity was elevated much more broadly in the RpS3/+ pouch compared to the localized activation observed in the wild-type control at the same developmental stage, as assessed by the nmo-lacZ reporter (Fig 3D in Akai et al., PLOS Genetics, 2021, as also shown Fig. R6 above). This elevation leads to the formation of an ectopic cell population with high Wg signaling activity in the wing pouch, potentially causing non-autonomous cell death among cells exhibiting lower Wg signaling activity, a process akin to cell competition. Notably, the significant reduction of apoptosis in RpS3/+ wing discs following Fz2 downregulation suggests that Fz2 may play a crucial role in the massive cell turnover, through a mechanism similar to cell competition, even though the exact mechanism remains unclear. We plan to incorporate such discussions into the discussion section of the revised manuscript.
Figure S1D. It seems that cadps is further up-regulated if JNK signaling is inhibited in RpS3/+ cells. Why did the authors select this gene?
Response:
We apologize for any confusion caused. We found that Cadps expression in the RpS3/+ wing pouch was increased compared to both the wild-type control (2.29-fold increase, RpS3/+ compared to wild-type) and the RpS3/+ wing pouch expressing Puc, driven by the nub-gal4 driver (3.33-fold increase, RpS3/+ compared to RpS3/+ +Puc). This suggests that the increase in Cadpsexpression in the RpS3/+ wing pouch is dependent on JNK signaling. We have now revised Fig S1D for clearer representation. We also have made modifications in the transferred manuscript as follows:
(page 5, line 107-113)
"Mining the list of genes differentially expressed in the RpS3/+ wing pouch cells dependent on JNK signaling (Fig S1C and S2 Table), we noticed that among the genes associated with the "secretion by cell" GO term (Fig S1B), the evolutionarily conserved exocytosis-related genes unc-13, SNAP25, and cadps (Calcium-dependent secretion activator) were upregulated in a JNK-dependent manner (2.29-fold increase, RpS3/+ compared to wild-type; 3.33-fold increase, RpS3/+ compared to RpS3/+ +_ Puckered)_ (Fig S1D)."
Figure S1H'. I don't see that Hrs is upregulated in this panel.
Response:
We thank the reviewer for the comment. Our quantitative analysis showed an increase in Hrs-positive puncta in the RpS3/+ wing pouch compared to the wild-type control (Fig S1I). We have substituted the relevant Figure with new images that more clearly demonstrate the elevation of Hrs-positive puncta (Fig S1G-H' in the transferred manuscript).
Minor points:
Describe in more detail, what are unc13, SNAP25 and cadps.
Response:
We thank the reviewer for the comment. We have now included an explanation for unc-13, SNAP25 and cadps in the transferredmanuscript as follows:
(page 5, line 117-126)
"It has been shown that unc-13, SNAP25, and cadps collectively regulate the docking process of secretory vesicles to the plasma membrane during Ca2+-mediated exocytosis ____((21, 23, 24), Reviewed in (22)). ____Specifically, UNC-13, a conserved presynaptic protein with calcium-binding domains, interacts with syntaxin to prime vesicles for fusion, crucial for calcium-regulated exocytosis (____23____). SNAP-25, in conjunction with syntaxin-1 and synaptobrevin, forms the pivotal SNARE complex for neuronal exocytosis, assembling into a four-helix bundle that is essential for drawing vesicle and plasma membranes close together to enable membrane fusion (____24, 25____). Like UNC-13, CAPS possesses conserved C-terminal domains that are instrumental in the assembly of SNARE complexes, thus priming vesicles for Ca2+-induced exocytosis (____26)____.____"
I wondered about the use of Hrs as exosome marker. To my knowledge, it is an endosomal marker. Same with Alix. Please clarify.
Response:
As pointed out by the reviewer, ESCRT-0 component Hrs is also localized to endosome. However, Hrs is also used as an exosome marker in the previous manuscript (McGough IJ et al., Nature, 2020), alongside Alix and Tsg101, which are widely recognized as exosome markers (Willms E et al., Sci Rep., 2016; Dear JW et al., Proteomics, 2013). Indeed, Hrs is a key factor for mediating ESCRT-dependent exosome secretion in mammals and flies (Tamai K et al., Biochem Biophys Res Commun., 2010; Gross JC et al., Nat Cell Biol., 2012; Colombo M et al., J Cell Sci., 2013; Vietri M et al., Nat Rev Mol Cell Biol., 2020). We have incorporated this explanation into the revised manuscript as follows:
(page 6, line 139-141)
"____Furthermore, we noted an increase in vesicles positive for the ESCRT protein Hrs, ____an additional exosome marker crucial for exosome secretion (____34, 35____), in the RpS3/+ wing pouch relative to the wild-type control (Fig S1G and S1H, quantified in Fig S1I)."
In the context of references 16 and 17, Huh et al. (2004), Current Biology needs also to be cited.
Response:
We thank the reviewer for the comment. We have referenced the paper by Huh et al. (2004) published in Current Biology in the transferred manuscript as follows:
(page 3, line 68-71)
"Apoptotic cells, for example, can secrete mitogens su____ch as Wingless ____(Wg; a Wnt homolog), dpp (a BMP homolog), and Hh, which could promote the proliferation of nearby cells in the Drosophila epithelium (15, _16_, 17, 18, 19)."
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Referee #3
Evidence, reproducibility and clarity
Summary: In previous work, the authors showed that in the pouch of wing imaginal discs in Minute (M) mutants apoptosis and compensatory proliferation are dramatically increased in a Wingless (Wg) and JNK-dependent manner. Here, they show that JNK-induced exocytosis is mediating the secretion of Wg in apoptotic cells. Wg in turn stimulates the Fz2 receptor in neighboring surviving cells promoting their proliferation.
Major comments:
- Figure 1A-H, S1E. The authors used EGFP-CD63 and Syt1-EGFP as markers of exocytosis. They see an increased number of puncta in apoptotic cells. Is this a specific effect in the dying cells in M mutant discs, or is it a general effect in apoptotic cell death? This should be examined in a condition where apoptosis is induced independently of M mutants such as nub-reaper or nub-hid.
- Is exocytosis actually upstream or downstream of cell death, or both? The authors are kind of vague about it. On one hand, they say the dying cells induce exocytosis and secrete Wg. On the other hand, unc13RNAi can suppress cell death (Figure 1D', J'). Please clarify.
- Figure 1L-P. The observation of Ca++ flashes is very interesting. However, are they important for exocytosis, cell death and compensatory proliferation? Right now, this is just a stand-alone observation. Can mutants affecting Ca++ signaling block exocytosis, cell death and comp prol?
- Figure 3B'. Can you visualize aberrant wg expression in RpS3/+ wing discs only in the presence of p35? The expression of p35 in apoptotic cells generates undead cells which by itself induce Wg expression in a JNK-dependent manner (Perez-Garijo et al 2004; Ryoo et al 2004). Also, in Figure 3B', Wg is upregulated in the ventral half of the pouch, whereas in other figures (4B for example) apoptosis is strongly induced in the dorsal half. Does that make sense?
- Can wg RNAi in cells destined to die (puc-Gal4 UAS-wgRNAi) suppress apoptosis and comp prol?
- Figure 3D,E. Use cDcp1 as apoptotic marker instead of CD63-mCherry which is not an apoptotic marker.
- Figure 4A' and B'. I am not sure there is much of a difference in the expression of fz2-lacZ in wild-type and RpS3/+ discs. The quantification in 4F shows there is no difference in the dorsal half of the pouch where massive apoptosis occurs. Can you generate a condition in which only one compartment (anterior or posterior) is mutant for RpS3/+, while the other compartment is wt? That would allow direct side-by-side comparison. Comparisons between different discs is problematic.
- There is some inconsistency in the presence of apoptotic cells and presence of cells which secrete Wg. Apoptotic cells occur in large cell clusters (Fig. 2G, 3H', S3A', S4B), while markers of exocytosis and Wg are present in individual puncta (Fig 3D', E', S3C,E). That does not seem to fit with the authors' conclusion that dying cells secrete Wg by exocytosis. Are all dying cells secreting Wg through exocytosis? Please explain.
- I was a bit confused by the conclusion of the authors about the results in Figure 4G-I. What do they mean by "difference in Fz2 expression"? Are they referring to the gradient that they described in their previous work? Or is it just the absolute level of Fz2 that determines apoptosis and proliferation? If the latter, is the gradient still present (at least in fz2/+), just at a lower level?
- Regarding point 8, given that reduction of Fz2 can suppress apoptosis in RpS3/+ wing discs, how does it regulate apoptosis when it is down-regulated anyway in apoptotic cells (Fig 4B', S4B')?
- Figure S1D. It seems that cadps is further up-regulated if JNK signaling is inhibited in RpS3/+ cells. Why did the authors select this gene?
- Figure S1H'. I don't see that Hrs is upregulated in this panel.
Minor points:
- Describe in more detail, what are unc13, SNAP25 and cadps.
- I wondered about the use of Hrs as exosome marker. To my knowledge, it is an endosomal marker. Same with Alix. Please clarify.
- In the context of references 16 and 17, Huh et al. (2004), Current Biology needs also to be cited.
Referees cross-commenting
I think all three reviewers agree in their assessment of this manuscript. Some of the comments by the reviewers address the same concerns. I liked the comment by reviewer 2 about the autonomy/non-autonomy of the signaling events in this model. I was thinking that, too, but didn't express it in my review. So, thanks reviewer 2, for bringing this up.
Significance
General assessment. A major strength of the work is that the experiments are done in a very good manner. The authors used multiple assays to come to the same conclusions. Limitations and weaknesses are mentioned in "major comments".
Advance. In my mind, one problem is novelty of this work. The authors showed before that Wg is secreted by dying cells in Minute mutants. It was also shown that Wg can be secreted by exocytosis in many studies from different authors. Here, the authors basically combine both observations and show that Wg is secreted by exosomes in Minute mutants.
Audience. This work likely addresses a specialized audience involved in Minute-induced cell competition. I don't think it will be of interest beyond this specific field.
Background of the reviewer. I have an interest in cell competition, apoptosis and neurodegeneration.
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Referee #2
Evidence, reproducibility and clarity
The authors initiate their study by illustrating that minute cells undergo an augmentation in exocytosis-related proteins and calcium flashes (Fig 1). Subsequently, they establish a correlation between JNK-mediated exocytosis and the regulation of caspase activation in minute cells (Fig 2). Further, the authors unveil a dependency of Wg secretion on exocytosis, elucidated in Fig 3. Finally, they discern the involvement of one of the Wg receptors, Fz2, in the cell death/proliferation phenotype of minute cells. Despite the formulation of an intriguing hypothesis, the presented data falls short of robustly supporting their assertions.
Primary Concerns:
- A significant challenge arises concerning the delineation of cell autonomy/non-autonomy. This study focuses on two distinct cell types, namely dying cells and proliferating cells. However, the consistent use of nub-gal4, a wing pouch driver, and the heterozygous minute mutant throughout the paper impedes the ability to conclusively analyze the autonomy of events. The authors previously posited that caspase-induced cell death triggers non-autonomous proliferation, but recent studies also suggested caspase-induced autonomous proliferation in both flies and mammals (Yosefzon et al. Mol. Cell 2018, Shinoda et al., PNAS 2019). Therefore, a meticulous distinction between autonomous and non-autonomous events, particularly through experimentation involving clones, is imperative. This necessity is particularly evident in Fig 4.
- Closely tied to the issue of cell autonomy/non-autonomy is the question of how cells differentiate Wg from dying cells and the dorsal-ventral boundary.
- In Fig 1, the authors interpret the upregulation of exocytosis-related genes as indicative of increased exocytosis. However, this interpretation lacks direct evidence and overlooks the possibility of opposing effects. For example, autophagosome accumulation means either activation or inhibition of autophagy. Or, in case of Dilp secretion, absence of vesicles indicates upregulation of secretion. To substantiate their claim, the authors must provide more conclusive evidence of increased exocytosis. Fig 2 suggests that inhibiting exocytosis-related genes suppresses caspase activation, favoring the proposition that exocytosis is upregulated. However, demonstrating a direct increase in exocytosis in minute cells would bolster their argument. Higher resolution imaging of the exosome marker, with overlayed images, would enhance clarity too.
- Fig 3 introduces ambiguity regarding the relationship between cell death and exocytosis. The authors assert that dying cells exhibit elevated Wg protein levels compared to the wild-type control but omit an important comparison to the minute disc. Moreover, while Figs 1-2 propose a signaling cascade involving minute>JNK>exocytosis>cell death, Fig 3 implies that cell death regulates exocytosis. The coherence of their model and logic requires clarification - specifically, elucidating the molecular coupling mechanism between cell death and exocytosis.
Specific Points:
- In Fig S1D, contrary to the authors' claim, cadp2 is not upregulated in a JNK-dependent manner.
- When detecting multiple proteins in the same tissue, it is advisable for the authors to present overlayed images to enhance the clarity of their findings. Many pictures require higher magnification too.
- In Fig 1A, the observed upregulation of EGFP-CD63 and Syt1-EGFP may potentially result from an artifactual effect of apoptosis. To validate their findings are specific, the authors should include negative controls that do not exhibit upregulation in dying cells.
Referees cross-commenting
I agree with comments by other reviewers.
Significance
The authors initiate their study by illustrating that minute cells undergo an augmentation in exocytosis-related proteins and calcium flashes (Fig 1). Subsequently, they establish a correlation between JNK-mediated exocytosis and the regulation of caspase activation in minute cells (Fig 2). Further, the authors unveil a dependency of Wg secretion on exocytosis, elucidated in Fig 3. Finally, they discern the involvement of one of the Wg receptors, Fz2, in the cell death/proliferation phenotype of minute cells. Despite the formulation of an intriguing hypothesis, the presented data falls short of robustly supporting their assertions.
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Referee #1
Evidence, reproducibility and clarity
Summary:
In this study, Akai and colleagues study the cellular mechanism leading to high cell turnover in the Minute mutant background in Drosophila wing disc. Previously, the same group characterised an unexpected high rate of proliferation in the wing pouch of the Minute heterozygous larvae, which have been long known to have slower development time. This high rate of proliferation is driven by high apoptosis rate, JNK activation, the release of Dilp8 hormone, and the upregulation of Wg signaling (downstream of JNK) necessary for increased apoptosis and proliferation ( Akai et al., Plos Genetics 2021). Here, the authors address now the molecular link connecting JNK activation and the increased turnover. Using RNAseq and comparing WT, M+/- wing disc with M+/- wing disc upon JNK inhibition, they found a number of genes associated with exocytosis that were upregulated in Minute disc which was lost upon JNK inhibition. The authors first confirm the existence of higher number of exocytic vesicles in Minute wing disc as well as higher calcium activity that were all reduced upon JNK inhibition. Moreover, downregulation of several components of the exocytosis machinery abolished the high turnover rate of Minute wing disc (reducing both apoptosis and proliferation) while leading to the appearance of morphological defects in adult wing, while having no effect in a WT background. Interestingly, Wg accumulates in these exocytosis vesicles, and this accumulation relies on JNK and core exocytosis machinery. The role of Wg is confirmed by reducing the concentration (using heterozygous mutant or RNAi) of the Wg receptor Fz2, which is also specifically downregulated in the cluster of apoptotic cells. Altogether, this study suggests that upregulation of exocytosis by JNK activation is a central regulator of the higher cell turnover in Minute background.
The article is well written and the data overall convincing, including a lot of genetic backgrounds confirming the impact of exocytosis, as well as all the necessary quantifications. Some additional epistatic experiments may help to clearly test to which extend exocytosis is the major downstream target of JNK, and additional control may also help to clarify the sufficiency of JNK for generating such phenotype. Finally, I believe the epistatic link between exocytosis and Wg would deserve more experiments to be definitly proven.
Major comments:
- It would be important to check how much JNK is sufficient to trigger the exocytosis upregulation. Is the accumulation of Cyt1 and CD63 vesicles in apoptotic cell common to any JNK dependent death or does it require the Minute background ? Could the authors check whether clones expressing HepCA transiently in WT background also accumulate the same vesicles ?
- It would be relevant to have the status of JNK in Minute disc upon downregualtion of exocytosis. One could imagine some positive feedback between JNK activation, exocytosis, cell death and further JNK activation.
- So far, the evidence for the epistatic link between exocytosis, Wg and cell turnover is mostly based on colocalization and the similarity of the phenotype but I believe this may need some additional evidences. Ideally one would need to be able to enhance exocytosis and test whether Wg downregulation suppress the phenotype, but I am not sure that upregulation of core exocytosis genes will be sufficient to do this. Alternatively, if Wg is indeed downstream of the upregulation of exocytosis, the reduction of cell turnover upon Wg flattening (e.g. : ftz2-/+ background) should not be enhanced by the reduction of exocytosis. Moreover, could the authors test the status of Wg downstreams targets upon inhibition of exocytosis in the Minute background (for instance, do they see a supression of the nmo-LacZ upregulation that they previously characterised in Minute wing disc in 2021) ?
- Since Cyt1 and CD63 seem to mostly accumulate in apoptotic cells, it would be interesting to check their status in Minute wing disc upon apoptosis inhibition (e.g. : with H99 or mirRHG).
- I would remain cautious about some of the statements, notably in the abstract, since some of them are mostly speculative and not really based on any experiments. For instance, the statement "This interaction between dying cells and their neighboring living cells is pivotal in determining cell fate, dictating which cells will undergo apoptosis and which cells will proliferate" is not backed up by any experiment (which would require to show that exocytosis and Wg from the dying cell specifically is required for the survival and proliferation of their neighbours, and/or showing that cell death occurs specifically in cells with local differences in Wg signaling). I would recommend to be more cautious here and us a clear conditional statement.
Other minor point:
The authors document Wg localisation in Minute wing disc upon expression of P35. It would be interesting to describe what is the status of Wg in Rps3+/- compared to WT without p35 (if I am correct, this was done in their previous article, and in that case it would be relevant to describe these former results in the main text).
Referees cross-commenting
I overall agree with all the other comments. It seems that the overall assessment and criticisms (cell autonomy, better characterisation of the status of exocytsosi) are along the same line
Significance
This article is mostly a follow up of a former study published by the same authors in Plos Genetics in 2021. The high turnover (high proliferation and high apoptosis rate) in the minute background was the most surprising observations that was performed previously by the authors, and the role of JNK and Wg was already quite extensively explored in this previous article. The main novelty here is to provide a systematic analysis of expression profile of Minute disc upon JNK inhibition and identify the strong contribution of exocytosis for increased apoptosis and proliferation in Minute wing disc downstream of JNK. In that sense, I believe these are interesting results, but novelty remains a bit limited (at least relative to their previous study). Still, these results could be interesting for the community studying cell competition, ribosomopathies, and growth regulation specially in Drosophila (so mostly for a specialised readership).
I have expertise in epithelial cell death, apoptosis, and cell competition, specially in Drosophila. I feel confident to evaluate every part of the article.
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Reply to the reviewers
Manuscript number: RC-2024-02352
Corresponding author(s): Elise, Belaidi
1. General Statements
We would like to thank the reviewers for their constructive suggestions and comments. We hope that the “point by point answer” and the revision plan proposed below will convince the reviewers and the editor.
We thank the reviewer 1 for his/her comments. We would like to specify that the involvement of HIF-1 in IH-induced mitochondrial remodeling has indeed been initiated by RNA-seq analysis and confirmed in a cell-based model as well as in wild-type and HIF-1a+/- heterozygous mice subjected to intermittent hypoxia (IH). In vivo, we originally demonstrated that Metformin reversed IH-induced increase in myocardial infarct size through AMPKa2 and, we proposed that metformin could modify HIF-1 activity. Then, we validated our hypothesis in an in vitro model allowing to demonstrate that Metformin, by increasing HIF-1a phosphorylation decreases its activity. We acknowledge that we used several models and this is the reason why we detailed as much as possible the Materials and Methods section including all models, experimental sets designed and methods details. We hope that the point by point response that we made for the reviewer 1 will increase the clarity of our work and we hope that the new results provided will strengthen the evidences concerning the mechanisms by which metformin can inhibit and modulate the deleterious impact of HIF-1 on IH-induced an increase in myocardial infarct size.
We thank the reviewer 2 for his/her conclusion highlighting that “our work opens new avenues for exploring the potential effects of metformin as a modulatory of HIF-1𝛂 activity in obstructive sleep apnea syndrome”. We hope that the clarifications and/or justifications brought will convince him/her.<br /> We thank the reviewer 3 for having underlined that “metformin induces HIF-1α phosphorylation, decreases its nuclear localization and subsequently HIF-1 transcriptional activity are very much interesting” and for having highlighting that “our study is convincing”. We hope that the justification and the corrections brought in the point by point answer will convince him/her.
Alltogether, as underlined by the 3 reviewers, our study is very interesting for translational science in the fields of cardiovascular, respiratory and sleep medicine. We hope that the point by point answer and the revision plan proposed will allow the publication of our article in EMBO Molecular Medicine.
2. Description of the planned revisions
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Please find below the revision that we plan to address to answer to the questions of the reviewer 1.
Figure 1 - it would be helpful to list all of the DEGs (what genes are changed?). Including the expression of HIF-1α and PHD isoforms would be informative. If there is a robust HIF-1α signal, changes in the expression of HIF and PHD isoforms would be anticipated. Fig 1F - with regards to glycolysis and hypoxia pathway analysis, most of the DEGs are not canonical HIF-1α/hypoxia targets.
Figure 1 aimed at better understanding and manipulate the well-recognized involvement of HIF-1 in response to our specific IH stimulus (Semenza, Physiology 2009; Belaidi, Pharmacol & Ther. 2016). __The results provided by the RNA-seq analysis shows that IH induces cardiac oxidative and metabolic stress which are inter-related with HIF-1 activation. __We did not claim that these genes are HIF-1 targets genes. The RNA seq analysis did not allow to reveal HIF-1a and PHD1-3 transcript as the most dysregulated genes of the panel. In case of publication, bulk data and DEGS will be provided in an online file. We agree with the reviewer that the list of the 40 up and down-regulated genes would be very informative and would increase the value of the paper. Thus, we plan to add the name of the 40 up and down-regulated genes on Figure 1B.
Figure 5G-I, show cytoplasmic HIF1a as well as nuclear.
Alternatively, why not use IHC for subcellular localization?
We think that the comments of the reviewer 1 concern Fig.4G-I and not 5G-I. In this figure, we showed that IH increases nuclear HIF-1____a____ expression compared to N condition and that this IH-effect is abolished in mice treated with Metformin, suggesting that, upon IH, Metformin impacts HIF-1__a __nuclear content and subsequently, its activity. The nuclear localization of HIF-1a is the most relevant mean to indicate its activation. We agree with the reviewer that IHC also allows for the indication of the nuclear localization of HIF-1a. Indeed, we previously performed IHC on nuclear HIF-1a localization and demonstrated that IH increased HIF-1a nuclear localization by IHC that was corroborated by Western-blot (Moulin S, TACD, 2020). Western-blot and IHC are both semi-quantitative techniques with different process of analyses. In this study, we choose Western-blot because we have the material to perform this technique and because IHC is associated with an analysis process (size of a slice, areas to analyze, colorimetry…) that is more complex than the analysis process of Western-blot (densitometry solely).
While the nuclear localization of HIF-1a is the most relevant mean to indicate its activation; it could be interesting to see that HIF-1a cytosolic content was neither modify by IH nor by Metformin. This would also corroborate the results of the RNA-seq that did not demonstrate any difference in DEGs of HIF-1a or of other members of the HIF family. This would also confirm that Metformin plays a major role on HIF-1 activaty regulation (and not transcription) in the context of IH.
Thus, we plan to perform a Western-blot of HIF-1a on cytosolic extracts of hearts from mice exposed to N or IH and treated or not with Metformin. These extracts are already available and Western-blot would be performed and replicated in 3 weeks. We could also provide a Western-blot in order to show the purity of our extraction protocol (nucleus vs cytosol).
Figure 5F, it would be important to show the levels of expression of HIF1a in these experiments. Are there positive and negative controls that the authors could use for HIF21a activity in this experiment?
In our manuscript, we aimed at demonstrating that Metformin decreases HIF-1 activity in a context of strong HIF-1____a____expression and/or stabilizion those mimics what happens after chronic IH in mice (Belaidi E, Int J Cardiol 2016, Moulin S, Ther Adv Chronic Dis 2020) and in apneic patients (Moulin S, Can J Cardiol 2020). Thus, we used a transfection allowing to overexpress HIF-1a that is one of the best means to increase HIF-1 activity. In the Figure 1 below, HA-HIF-1α-WT Addgene AmpR and 5 HRE GFP AmpR plasmids co-transfection induced a decrease in H9c2 viability and an increase in GFP-positive cells that were not observed in H9c2 transfected with pcDNA 3.1 HA-C AmpR (negative control). __This validates our in vitro model as a good positive control to mimic IH consequences. __ However, we agree with the reviewer that we could add a supplemental figure or a panel demonstrating that our transfection induced an increase in HIF-1a expression. Thus, we will perform a Western-blot targeting HIF-1a on H9c2 transfected with the control plasmid (pcDNA 3.1 HA-C AmpR) or the plasmid allowing the overexpression of HIF-1a (HA-HIF-1α-WT AmpR). This work would be performed in 2 months.
Moreover, we already improved the lisibility of the Figure 5F to clarify the experimental conditions (table inserted under the graphic); we also completed the Materials and Methods section to specify the plasmid used (modifications are in red in the manuscript).
Figure to see on the downloaded file.
Figure 1 : GFP fluorescence in H9c2 cells transfected with pcDNA 3.1 HA-C AmpR (control condition) or HA-HIF-1α-WT AmpR (positive control, overexpression of HIF-1a) and 5 HRE-GFP AmpR plamids and treated with CoCl2 (1mM, 2h); magnification x100.
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This paragraph concerns only the point 4 of the fifth question.
In these experiments, as well as subsequent studies, it would be very informative to use a specific AMPK activator e.g. MK-8772, to compare with metformin. It is well known that metformin has a number of other targets in addition to AMPK.
We agree with the reviewer that metformin has pleiotropic effect. Very interestingly, we demonstrated that the reduced-infarct size is not related to the metabolic systemic effect of metformin since it failed to improve the IH-induced insulin resistance while it improves the answer to insulin in normoxic mice (supplemental Figure S3B). This demonstrates that in our model, the cardioprotective effects of Metformin are independent of a potential systemic effect. Then, we demonstrated that metformin protects the heart against ischemia-reperfusion through AMPK____a____2 activation by using AMPK____a____2KO exposed to IH in which Metformin failed to decrease infarct size (Fig.4N). MK-8772 is not widely used in vivo models. Moreover a recent study indicates that chronic treatment with MK-8772 (14 days 1 month in mice and rats, respectively) induces cardiac hypertrophy characterized by an increase in heart weight (Myers R, Science 2017). In vivo experiments with MK-8772 would be not clinically relevant as the use of metformin that is already used in clinic. However, in order to improve the mechanistic investigation concerning the role of AMPKa2 activation on inhibiting HIF-1 activity, we propose to perform the in vitroexperiments performed in Figure 5 with a specific allosteric small-molecule activator of AMPKa2 such as 991.
We plan to:
-Expose H9c2 to CoCl2 and treat them with 991 in order to measure HIF-1a phosphorylation.
-Transfect H9c2 with our plasmids HA-HIF-1α-WT AmpR and 5 HRE GFP AmpR and treat them or not with 991 in order to measure HIF-1 activity (GFP fluorescence). These experiments would be performed in 2 months.
__Please find below the revision that we plan to address to answer to the second question of the reviewer 2. __
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2) The WB images were cut and pasted. Please add the original images
We acknowledge the reviewer's comment and will address it by submitting a supplementary file containing the uncropped immunoblot images. Since this file already exists, our plan is to standardize it by providing, for each slide (immunoblot), all relevant information pertaining to our experiments, including groups, molecular weight markers, cutting, membrane stripping, and other pertinent details.
3. Description of the revisions that have already been incorporated in the transferred manuscript
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__Please find below the answers or the revisions that have already been incorporated in response to the comments of the reviewer 1. Please note that we provided new results and new figures at the discretion of the reviewer, but we are ready to insert them as figures or supplemental figures in a new revised manuscript if the reviewers and the editor think that it would improve our message. __
Was mitochondrial content in the hearts after IH experiment measured e.g. mtDNA measurements? IH results in mitochondrial dysfunction/reduced mitochondrial content. It would have been good to show mitochondrial dysfunction by doing basic functional experiments (e.g. TMRM/MitoROS imaging etc.) by isolating cardiomyocytes from the N and IH experiments.
We thank the reviewer for these questions about the mitochondrial function and content. The impact of IH on mitochondrial function has already been demonstrated in heart (Moulin S, Antioxydants 2022, Wei Q, Am J Physiol 2012). __Indeed, we previously showed that mitochondria isolated from hearts of mice exposed to IH had a decrease in maximal respiration in complex I and II that was not observed in HIF-1_a_+/- ____mice (Moulin S, Antioxidants 2022), indicating that HIF-1 is responsible for IH-induced mitochondrial dysfunction. __
Figure 4 shows that Metformin abolished IH-induced mitochondrial remodeling similar to what we observed in HIF-1a+/-(Figure 2). This means that treating with Metformin or partially deleting the gene encoding for HIF-a induce the same impact on IH. Then, we demonstrated that Metformin can control HIF-1 activation and we concluded that metformin could be cardioprotective through inhibiting HIF-1 activation and subsequent mitochondrial stress and remodeling. In this study, we focused on the effects of Metformin on HIF-1 and we did not aim at directly test the effect of metformin on mitochondrial function. Actually, metformin exhibits biphasic effects on bioenergetics of cardiac tissue depending on the modality of administration (i. e. single injection, time of administration during an ischemia-reperfusion procedure); the dose administered and the tissue studied (i. e. hiPSC-CMs, isolated mitochondria…) (Emelyanova N, Transl Res 2021). But, we collected some data that we would like to submit at the discretion of the reviewer. Using oximetry, we measured maximal respiration in complex 1 and 2 on isolated mitochondria from hearts of mice exposed to N, IH and treated or not with metformin during the exposure__. While we observed that IH decreases maximal respiration in complex 1 and 2, we did not find any effect of metformin on mitochondrial respiration alteration induced by IH (Figure 2A, B). Using spectrofluorometry, we measured the mitochondrial membrane potential using TMRM; __we did not find any modification of membrane potential in IH or Metformin-treated mice (Figure 2C). Because we previously did not observe any impact of IH on mtDNA/gDNA ratio (Figure 2D), we did not test metformin on this parameter.
To conclude, we think that these results are not directly in the scope of our work but if the reviewer thinks that they deserve to be discussed, we could add them in a supplementary figure.
Please, see the figure on the dowloaded file
Figure 2 : Mice were exposed to 21 days of Normoxia (N) or Intermittent Hypoxia (IH) (1-min cycle of FiO2 5%-21%) and treated with vehicle (Vh, CmCNa 0.01%, 0,1ml.10g-1) or Metformin (Met, 300mg.kg-1.d-1). (A, B) Mitochondrial function __was measured by oximetry with sequential addition of substrate (state 2), ADP (200mM, state 3, maximal respiration) and oligomycin (12.5 mM, state 4) ; quantification of O2 consumption for NADH-linked mitochondrial respiration (complex I-glutamate-malate, GM, 20mM) (A), and for FADH2-linked mitochondrial respiration (complex II-succinate, S, 5mM, in presence of complex I inhibition by rotenone, 6.25mM) (B) (n=8). (C) Mitochondrial membrane potential measured by spectrofluorometry after Tetramethylrhodamine Methyl Ester (TMRM, 0.2mM) in presence of GM (basal condition), maximal respiration (ADP) and uncoupling condition Carbonyl cyanide 4-(trifluoromethoxy)phenylhydrazone, FCCP, 3mM); fluorescence intensity is expressed relative to fuorescence at baseline (before GM) (n=8). (D__) Mitochondrial content assessed by the expression of mitochondrial DNA (mtDNA, COX1) relative to genomic DNA (gDNA, ApoB) measured after PCR (n=6); *p
Fig 2A-D - CoCl2 is not a good model to mimic hypoxia due its effect on disrupting iron homeostasis in cells, which can mean that some of the effects are due to changes in iron levels and not HIF stabilisation.
The capacity of CoCl2 to chelate iron is the main property of CoCl2 that we used in order to stabilize HIF-1____a____. Actually, prolyl-4-hydroxylases need Fe2+ to hydroxylate HIF-1____a____ and induce its degradation. __Then, intermittent hypoxia (IH) is characterized by very rapid changes in PO2. This stimulus was designed to reproduce sleep apnea syndrome and its associated disorders (i. e. insulin-resistance, hypertension, increase in myocardial infarct size). This model was firstly developed and validated in rodents (Dematteis M, ILARJ 2008, Belaidi E, Eur Resp Rev 2022, Harki , Eur Resp J 2022). Compelling evidence indicate that the involvement of HIF-1 in IH-deleterious consequences is related to the repetitive phases of oxygenation and especially to IH-induced oxidative stress (Semenza Physiology 2009, Belaidi Pharmacol. & Ther 2016). In order to increase the level of mechanistic insights on HIF-1, we next attempted to optimize in vitro models. A device was developed by Minoves et al. (Minoves M, Am J Physiol, 2017) to expose endothelial and cancer cells to IH. __However, as illustrated below, this device does not mimic efficient rapid hypoxia-reoxygenation cycles able to induce cardiac cell death (Figure 3A). However, CoCl2 decreases H9C2 viability by 60% (Figure 3B) that is associated with a sustained stabilization of HIF-1____a (Figure 3C,D). Thus, we choose this in vitro model as it replicates cardiac cell death and HIF-1_a_overexpression or stabilization which we similarly observe in our in vivo model and in apneic patients (Moulin S, Can J Cardiol 2020).
Please see the figure on the dowloaded file
Figure 3 : (A-B) Cell viability measured by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H- tetrazolium bromide (MTT) of H9c2 cells exposed to 6 hours (h) of repetitive cycles of Intermittent hypoxia (2 minutes (min) PO2 16% - 2 min PO2 2%) (n=3) (A) or treated with CoCl2 (1mM, 2h) (n=6) (B). (C-D), __quantification of __total ____HIF-1____𝛂 expression relative to tubulin (C) and representative image of Wetsern-blot (D) (n=2-3); *p****p*
Fig. 2K, change in BNIP3 expression is modest, but change in Parkin is very dramatic. BNIP3 is a HIF-1α target but Parkin is not, so it is plausible that mitophagy could be occurring through a HIF-1α independent mechanism.
Fig. 2K is a representative panel of 2-3 independent experiments. The quantification reported in Figures 2I and 2J demonstrated a significant decrease in BNIP3 and Parkin expressions in HIF-1a heterozygous mice exposed to Intermittent Hypoxia (IH) compared to HIF-1a+/+ mice exposed to IH. While we acknowledge that only BNIP3 is a direct target of HIF-1, the role of HIF-1 in IH-induced auto/mitophagy is demonstrated by our experiments performed in HIF-1____a____heterozygous mice. This shows an important role for HIF-1 without excluding any impact of HIF-1a independent mechanisms.
What are we meant to be looking at in Fig 2L?
Figure 2L aims at illustrating mitochondrial remodeling under IH. Stars indicate that mitochondria have abnormal fate in IH conditions and arrows point autophagosomal membrane and formation. This figure was magnified to be clearer (please see new Figure 2L).
Figure 3B-C, the reduction in pT172 on AMPK is modest. It would be good to include pACC as a downstream target for AMPK.
As recommended by the reviewer, we inserted in the manuscript the quantification of 79Ser-P-ACC/ACC western-blot as well as a representative image of the Western-blot (See new Figure 3). We also modified the legend of the figure. 79Ser-P-ACC is an important target of AMPK; however, in our experimental conditions, its phosphorylation is not associated to the decrease in AMPK phosphorylation. This could be explained by many points. First, Metformin was administered every day and hearts were harvested 24 hours later after the last administration. Most studies demonstrating a modification of AMPK and ACC phosphorylation are experiments performed in vitro or directly (less than 1 hour) after a single dose of Metformin administration. In the context of myocardial ischemia-reperfusion, Yin et al. showed an increase in P-AMPK/AMPK directly after Metformin treatment without showing any data on P-ACC/ACC (Yin M; Am J Physiol 2011); similar data were published in models of chronic cardiac diseases (Soraya H, Eur J Pharmacol, Gundewar S, Circ Res 2009). Second, in line with the previous explanation, the lack of effect of metformin on P-AMPK and/or P-ACC in rodent models could be explained by its rapid distribution (Sheleme T Clin Pharmacokinetics of Metformin 2021) and its short half-life that is around 3.7 hours in mice (Junien N, Arch Int Pharmacodyn Ther 1979).
To conclude, since we performed all our analysis 24h after the last treatment and exposure to hypoxia, we argue that the slight but significative decrease in AMPK phosphorylation that we observed in our study highlight a robust impact of chronic IH. However, this would be elegant to confirm this result by measuring AMPK through its phosphorylation capacity (Cool B, Cell Metab 2006, Ducommun S, Am J Physiol 2014). We already sent hearts from mice exposed to Normoxia or Intermittent Hypoxia to Luc Bertrand’s lab (IREC, Belgium) where they used to perform this assay.
Fig. E-G, show data for mice treated with vehicle.
In Figure 4 I-J, we demonstrated that Metformin significantly decreases infract size in IH condition only and this validates our main hypothesis regarding the specific beneficial effect of this drug in the context of chronic IH. __In order to show that the cardioprotective effect of Metformin is relative to AMPKa2 activation, we first showed that 79Ser-PACC/ACC, one of the main downstream targets of AMPKa2 was increased (Fig. E-G). We did not find it necessary to does not exhibit cardioprotective effects. However, as shown in Figure 3 below, __Metformin also increases 79Ser-PACC/ACC in Normoxic mice validating the treatment. Thus, in normoxic conditions, AMPK____a____2 activation does not exert any cardioprotective effect. We acknowledge that this reinforces our result about the specificity of AMPK____a____2 activation by Metformin under chronic IH condition. We could add this Figure in supplemental results.
Please, see the figure on the dowloaded file
Figure 4 : AMPK activation in Normoxic mice treated with vehicle (Vh, CmCNa 0.01%, 0,1ml.10g-1) or __ __metformin (Met, 300mg.kg-1.d-1 : __ __172Thr-P-AMPK/AMPK (A) and 79Ser-P-ACC/ACC (B) ratio and representative image of Western-blot (C) (n=3-6); *p
Fig. 3K - what cre is used for the a2 KO mice?
As written in the Materials and methods section, AMPKa2KO mice are not inducible Knock-out mice. Constitutive AMPKα2 knockout mice were kindly generated by Benoit Viollet (Viollet B, JCI, 2003).
Include normoxia data for the a2 KO mice studies.
The question of the reviewer concerning the cardioprotective effects of metformin is interesting but is not aligned with the objectives of the study. Indeed, we did not treat normoxic mice with Met for several reasons. First, the objective of the study was to find a cardioprotective strategy against IH-induced an increase in infarct size. Second, Fig. 3I shows that Met significantly reduced infarct size upon IH only; this suggests that AMPK____a____2 activation is specifically involved in IH-induced increase in infarct size but not in reducing infarct size in normoxic mice. Moreover, the beneficial impact of metformin in standard models of myocardial ischemia-reperfusion is controversial and has been extensively discussed (Foretz et al. Cell Metab. 2014). Overall, using AMPKa2 mice was legitimated in the context of IH only. We validated the involvement of AMPKa2 in the cardioprotective effect of metformin especially in IH conditions.
Figure 5G, what is the rationale for switching to CoCl2 in the mice to prove metformin reduced HIF-1α expression? Why not use reduced O2 tension in mice.
We respectfully disagree with the reviewer since mice were exposed to N and IH and treated or not with Metformin to demonstrate that this drug abolished IH-induced increase in HIF-1a nuclear expression (Figure 4 H, I). The same model was used in Figure 3 to demonstrate the impact of Metformin on infarct size. Fig. 5G was conducted to demonstrate the potential link between AMPKa2 and HIF-1a phosphorylation in basal conditions of AMPKa2 content or in absence of AMPKa2 (AMPKa2-/- mice). The single presence of AMPK____a____2 demonstrates an increase in HIF-1____a____ phosphorylation if its stabilization is increased by CoCl2; this was not observed in AMPK____a____2-/- mice highlighting that AMPK____a____2 plays an important role in HIF-1____a phosphorylation.
Please find below the answer to the first question asked by the reviewer 2.
1) Why did authors choose the IH protocol illustrated in Fig. S1A
The choice of the hypoxic stimulus was based on literature and mainly on our recognized expertise in preclinical studies aiming at better understanding obstructive sleep apnea syndrome (OSA); a chronic pathology associated with several comorbidities such as diabetes, hypertension… We are conscious that the hypoxic stimulus used in this study is very severe, with a nadir arterial oxygen saturation (SaO2) around 60%. However, this experimental design is required to induce detrimental cardiovascular effects __in the absence of any confounding factors (i.e., obesity) or genetic susceptibility for complications (i. e. genetic susceptibility to hypertension) (Dematteis M, ILARJ 2008). Especially in the context of myocardial infarction, exposing rodents to 14 to 21 days of IH at 5% and subjected them to a myocardial ischemia-reperfusion protocol allows us to reproduce the increase in infarct size in rats (Belaidi E, J. Am. Coll. Cardiol., 2009; Bourdier G, Am J Physiol, 2016) and in mice (Belaidi E, Int J Cardiol 2016; Moulin S, Can J Cardiol 2020) similar to what has been observed in apneic patients (Buchner S, EHJ 2014). __Moreover, we recently conducted a meta-analysis based on 23 preclinical studies aiming at investigating the impact of the IH pattern (duration, FiO2, repetition of cycles…) on infarct size and cardiomyocyte death (Belaidi E, Eur. Resp. J 2022). We showed that IH significantly increases infarct size when IH is applied several days (especially 14 to 21 days) and when FiO2 is around 5%; whereas IH decreases infarct size when it is applied a single day at a FiO2 at 10%. This meta-analysis provided the confirmation that we need to apply a chronic and severe stimulus to reproduce an increase in infarct size that is observed in apneic patients which are exposed every day, during several days to a decrease in SaO2. If the reviewers and the editor consider that this point should be discussed in the discussion section, we will be happy to include it.
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Please find below the answers or the revisions that have already been incorporated in response to the comments of the reviewer 3. They appear in red in the new manuscript except the modifications performed in the “references” section which appear in black.
1 The authors used H9c2 rat cardiac cells in vitro experiments although they used mouse model in vivo experiments. Using mouse P19.CL6 cardiac cells instead of rat H9c2 cells may much clearer. Why the authors did not use P19.CL6 cells should be explained.
We thank the reviewer for his/her suggestion. P19CL6 cell line has been isolated from pluripotent P19 embryonal carcinoma (EC) cells after long term culture under conditions for mesodermal differentiation (Habara-Ohkubo A, Cell Struc Funct 1996). Therefore, these cells are mostly used to ____study the differentiation of cardiac muscle. Indeed, they were recognized to avoid large variations in the differentiation rates which were extensively reported (Mueller I, J Biomed Biotechnol 2010). To our knowledges no ventricular non-beating mice cell line. In this study, we used H9c2 which are extensively used and recognized as a gold standard cellular model to study the biology of cardiomyocytes including mechanisms involved in cardiac ischemia-reperfusion injury (Paillard M, Circulation, 2013; Zhang G Circulation 2021__), cardiac hypertrophy__ (Zhang N, Cell Death Diff 2020; Hu H, Cardiovasc Res 2020), intra-organites calcium exchanges (Moulin S, Antioxydants, 2022, Paillard M, Circulation, 2013) as drug testing (Beshay NM, J Pharm and Tox Methods, 2007). Recently, H9c2 and P19.CL6 were exposed to intermittent hypoxia (70 cycles of FiO2 1% (5 min) - FiO2 21% (10%)) in order to “mimic OSA” and investigate the transcription level of a pool of genes. The authors show some similiraties and differences of mRNA expression between the two cell lines that, indeed, could be attributed to variations in the cell origin (Takasawa S, IJMS 2022). However, in this study, there are no experiment allowing to assess the state of cardiac cells (apoptosis, life, metabolism, remodeling) questioning the pathophysiologic transposability of the model. Moreover, the number of experiments conducted on H9C2 (pubmed references : 7000 vs 100 for P19.CL6) to understand the mechanism involved in acute and chronic cardiac pathologies makes our choice confident and relevant.
2 The authors described, "The protocol was approved by the French minister (APAFIS#23725-2020012111137561.v2)." in Animals (page 16) without showing approval date, the authors should clearly show the approval date together with their approval numbers.
We added the approvement date in the materials and methods section. It was approved on February 20, 2020.
3 In Figure 2 L, scale bar(s) should be added because figures are magnified and/or reduced by printer.
We agree with the reviewer that scale bars were not visible; we highlighted them.
4 In Figure 3J and 3N, scale bar(s) should be added.
Scale bars have been now added on figures 3J and 3N. All pictures were acquired at the maximal zoom of a camera placed at an equal distance from the slices. Then, analyses were performed, slice per slice, with Image J with the same zoom (x5 to get an image at 100%). In this context, scale was added based on a photo of slice taken close to a ruler.
5 In introduction, "HIF-1" should be changed to "hypoxia-inducible factor 1 (HIF-1)".
Thank you, we replaced HIF-1 by Hypoxia Inducible Factor-1 (HIF-1) in the introduction section.
6 In Results, "Angpt1, Txnip, Nmrk2, Nuak1 or Pfkfb1" should be changed to "Angiopoietin 1 (Angpt1), Thioredoxin-interacting protein (Txnip), Nicotinamide riboside kinase 2 (Nmrk2), NUAK family SNF1-like kinase 1 (Nuak1) or 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 1 (Pfkb1)".
We did the modification and let the abbreviation in italic since it concerns genes name.
7 In Chronic intermittent hypoxia, "FiO2" should be changed to "FiO2".
Thank you, we changed it in the materials and methods section.
8 In Western-blot, "Bio-Rad, California, USA" should be changed to "Bio-Rad, Hercules, CA".
Thank you, we did it.
9 In Western-blot, what "tubulin" (α-tubulin or β-tubulin) should be clarified.
We agree with the reviewer that this point should be specified; α-tubulin was stained, we added the “α”.
As mentioned below, we have done all the modifications required by the reviewer in the references section.
10 In Ref. 8, "Antioxidants (Basel) 11 (2022)" should be changed to "Antioxidants (Basel) 11, 2326 (2022)".
Done
11 In Ref.10, "Pharmacol Ther (2016)" should be changed to "Pharmacol Ther 168, 1-11 (2016)".
Done
12 In Ref.13, "Antioxidants (Basel) 11 (2022)" should be changed to "Antioxidants (Basel) 11, 1462 (2022).
Done
13 In Ref. 21, "Diabetes (2017)" should be changed to "Diabetes 66, 2942-2951 (2017)".
Done
14 In Ref. 28, "Adv Biol (Weinh), e2300292 (2023)" should be changed to "Adv Biol (Weinh), 8, 2300292 (2023)".
Done
15 In Ref. 37, "J Am Heart Assoc 6 (2017)" should be changed to "J Am Heart Assoc 6, e006680 (2017)".
Done
16 In Ref. 41, "Eur Respir Rev 32 (2023)" should be changed to "Eur Respir Rev 32, 230083 (2023)".
Done
17 In Ref. 46, "Int J Mol Sci 22 (2020)" should be changed to "Int J Mol Sci 22, 268 (2021)".
Done
18 In Ref. 47, "Int J Mol Sci 21 (2020)" should be changed to "Int J Mol Sci 21, 2428 (2020)". Done
4. Description of analyses that authors prefer not to carry out
__Please find below the answers to the comment of the reviewer 3 that we cannot provide and that is not in the scope of the study. __
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Figure 5, multiple phosphorylation sites have been identified on HIF1a. What is the nature of the Thr/SerP-HIF1a antibody? It would be far more preferable (essential?) to identify the site(s) within HIF1a that are phosphorylated by AMPK.
The antibody was provided by Cell Signalling, ref. 9631. Phospho-(Ser/Thr) Phe Antibody detects phospho-serine or threonine in the context of tyrosine, tryptophan or phenylalanine.
The identification of the Phosphorylation sites will require a long-time consuming phosphoproteomic analysis and subsequent functional validation in vivo and in vitro (directed mutagenesis, knock-in mice, …) which are out of the scope of our paper.
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Referee #3
Evidence, reproducibility and clarity
Although the findings that metformin inhibits intermittent hypoxia (IH)-induced mitophagy in myocardium and decreases hypoxia-inducible factor 1-α (HIF-1α) nuclear expression in mice subjected to IH. In vitro demonstrated that metformin induces HIF-1α phosphorylation, decreases its nuclear localization and subsequently HIF-1 transcriptional activity are very much interesting, numbers of points need clarifying and certain statements require further justification. These are given below.
Point
- The authors used H9c2 rat cardiac cells in vitro experiments although they used mouse model in vivo experiments. Using mouse P19.CL6 cardiac cells instead of rat H9c2 cells may much clearer. Why the authors did not use P19.CL6 cells should be explained.
- The authors described, "The protocol was approved by the French minister (APAFIS#23725-2020012111137561.v2)." in Animals (page 16) without showing approval date, the authors should clearly show the approval date together with their approval numbers.
- In Figure 2 L, scale bar(s) should be added because figures are magnified and/or reduced by printer.
- In Figure 3J and 3N, scale bar(s) should be added.
- In introduction, "HIF-1" should be changed to "hypoxia-inducible factor 1 (HIF-1)".
- In Results, "Angpt1, Txnip, Nmrk2, Nuak1 or Pfkfb1" should be changed to "Angiopoietin 1 (Angpt1), Thioredoxin-interacting protein (Txnip), Nicotinamide riboside kinase 2 (Nmrk2), NUAK family SNF1-like kinase 1 (Nuak1) or 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 1 (Pfkb1)".
- In Chronic intermittent hypoxia, "FiO2" should be changed to "FiO<sub>2</sub>".
- In Western-blot, "Bio-Rad, California, USA" should be changed to "Bio-Rad, Hercules, CA".
- In Western-blot, what "tubulin" (α-tubulin or β-tubulin) should be clarified.
- In Ref. 8, "Antioxidants (Basel) 11 (2022)" should be changed to "Antioxidants (Basel) 11, 2326 (2022)".
- In Ref.10, "Pharmacol Ther (2016)" should be changed to "Pharmacol Ther 168, 1-11 (2016)".
- In Ref.13, "Antioxidants (Basel) 11 (2022)" should be changed to "Antioxidants (Basel) 11, 1462 (2022).
- In Ref. 21, "Diabetes (2017)" should be changed to "Diabetes 66, 2942-2951 (2017)".
- In Ref. 28, "Adv Biol (Weinh), e2300292 (2023)" should be changed to "Adv Biol (Weinh), 8, 2300292 (2023)".
- In Ref. 37, "J Am Heart Assoc 6 (2017)" should be changed to "J Am Heart Assoc 6, e006680 (2017)".
- In Ref. 41, "Eur Respir Rev 32 (2023)" should be changed to "Eur Respir Rev 32, 230083 (2023)".
- In Ref. 46, "Int J Mol Sci 22 (2020)" should be changed to "Int J Mol Sci 22, 268 (2021)".
- In Ref. 47, "Int J Mol Sci 21 (2020)" should be changed to "Int J Mol Sci 21, 2428 (2020)".
Significance
the study is convincing
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Referee #2
Evidence, reproducibility and clarity
In the submitted paper by Moulin et al., the authors investigated the effect of metformin treatment (an oral anti-diabetic drug and AMPK activator) on cardiac response to ischemia-reperfusion in mice exposed to intermittent hypoxia (IH), a major component of obstructive sleep apnea (OSA). The data demonstrates that IH alters the expression profile of a subset of genes involved in myocardial mitochondrial dysfunction, such as Angpt1, Txnip, Nmrk2, Nuak1 or Pfkfb1, hallmark genes of hypoxia and glycolysis. In H9c2 cells treated with CoCl2 with or without chloroquine, the authors claim that IH induces mitophagy through HIF-1 activation, associated with an increase in autophagic flux. This effect is abolished in HIF-1𝛂+/- mice. Metformin treatment in mice reverses IH-increased in infarct size through AMPK activation, decreases IH-induced mitophagy and HIF-1𝛂 nuclear localization.
The paper is interesting but needs some clarifications:
- Why did authors choose the IH protocol illustrated in Fig. S1A)
- The WB images were cut and pasted. Please add the original images
Significance
This work opens new avenues for exploring the potential effects of metformin as a modulatory of HIF-1𝛂 activity in obstructive sleep apnea syndrome.
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Referee #1
Evidence, reproducibility and clarity
Summary: The manuscript by Moulin and colleagues begins by exploring changes in gene expression in mice subjected to intermittent hypoxia (IH). Based on these results, the authors postulate a link with HIF1a, and so use a cell-based model to examine this link. Next, the authors turn to AMPK showing that IH decreases Thr172 phosphorylation on AMPK. In view of this, the authors use metformin as a way to activate AMPK during IH and monitor necrosis in hearts following ischemia-reperfusion. Metformin treatment reduces necrosis in mice subjected to IH. Mechanistically, the authors link decreased HIF1a activity following AMPK activation in response to metformin and suggest that this is due to phosphorylation of HIF1a by AMPK. Overall, this reviewer found some of these connections to be quite weak and in some cases the evidence supporting the claims was equivocal. In some instances, the lack of appropriate controls or the use on non-specific reagents, undermined the findings. Adding to these issues, there was a lack of experimental detail both in the Figure legends and in the M&M section. Below I have listed some of the major concerns that if addressed satisfactorily would greatly strengthen the manuscript.
Major Comments
Major Points
- Figure 1 - it would be helpful to list all of the DEGs (what genes are changed?). Including the expression of HIF-1α and PHD isoforms would be informative. If there is a robust HIF-1α signal, changes in the expression of HIF and PHD isoforms would be anticipated. Fig 1F - with regards to glycolysis and hypoxia pathway analysis, most of the DEGs are not canonical HIF-1α/hypoxia targets.
- Was mitochondrial content in the hearts after IH experiment measured e.g. mtDNA measurements? IH results in mitochondrial dysfunction/reduced mitochondrial content. It would have been good to show mitochondrial dysfunction by doing basic functional experiments (e.g. TMRM/MitoROS imaging etc.) by isolating cardiomyocytes from the N and IH experiments.
- Fig 2A-D - CoCl2 is not a good model to mimic hypoxia due its effect on disrupting iron homeostasis in cells, which can mean that some of the effects are due to changes in iron levels and not HIF stabilisation. Fig. 2K, change in BNIP3 expression is modest, but change in Parkin is very dramatic. BNIP3 is a HIF-1α target but Parkin is not, so it is plausible that mitophagy could be occurring through a HIF-1α independent mechanism. What are we meant to be looking at in Fig 2L?
- Figure 3B-C, the reduction in pT172 on AMPK is modest. It would be good to include pACC as a downstream target for AMPK. Fig. E-G, show data for mice treated with vehicle. Fig. 3K - what cre is used for the a2 KO mice? Include normoxia data for the a2 KO mice studies. In these experiments, as well as subsequent studies, it would be very informative to use a specific AMPK activator e.g. MK-8772, to compare with metformin. It is well known that metformin has a number of other targets in addition to AMPK.
- Figure 5G-I, show cytoplasmic HIF1a as well as nuclear. Alternatively, why not use IHC for subcellular localisation?
- Figure 5, multiple phosphorylation sites have been identified on HIF1a. What is the nature of the Thr/SerP-HIF1a antibody? It would be far more preferable (essential?) to identify the site(s) within HIF1a that are phosphorylated by AMPK.
- Figure 5F, it would be important to show the levels of expression of HIF1a in these experiments. Are there positive and negative controls that the authors could use for HIF21a activity in this experiment?
- Figure 5G, what is the rationale for switching to CoCl2 in the mice to prove metformin reduced HIF-1α expression? Why not use reduced O2 tension in mice.
Minor Comments
Nothing at this stage of the process. The authors need to focus on the major points to improve the quality of the manuscript.
Significance
Overall, the lack of robust mechanistic studies makes it difficult to fully interpret the impact of the study.
This feels like a preliminary exploration of a potentially important biological system, but the manuscript seems incomplete and requires more attention to details.
Upon revision, I think the study would be of interest to basic and clinical researchers working in the filed of cardiac metabolism and hypoxia.
My expertise is in metabolism and cell signalling.
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Reply to the reviewers
The authors do not wish to provide a response at this time
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Referee #3
Evidence, reproducibility and clarity
Here, Ahel et al characterize complex composiiton, chromatin binding, and respressive function of ADNP2. First they show that ADNP2 forms a complex with CHD4 and HP1b, very similar to, although biochemically distinct from, the ChAHP complex formed by ADNP. This complex is prevalently bound at repeats, and in particular at LTR retrotranspoons. Recruitment of ADNP2 is mostly mediated by HP1b binding to H3K9 and a PxVxL mutant that cannot bind to HP1 does not localize properly to chromatin. While ADNP has its own specific targets in SINE elements, it also binds some ADNP2 targets in an HP1-dependent manner. Depletion of ADNP or ADNP2 results in upregulation of some shared and some distinct transposons, indicating distinct roles but also partial redundancy.
This is a solid study that adds to our knowledge of these repressive complexes and their transposable element targets. I feel that the data could be analyzed a bit more in depth, especially in the comparisons of ChIP-seq vs. RNA-seq.
Major points
- Fig. 5: it would be interesting to analyze differences between repeats that are only under ADNP2 control vs. those that are sensitive to additional loss of ADNP. Presumably they both have K9me3 so why some are also repressed by ADNP?
- Fig. S5B, S7A: degrons are known to destabilize some proteins even before induction of degradation. These western blots should include a WT line to compare abundance of the endogenous protein with the tagged version.
- FIg. 5: it would be good to show a bit more overlap between RNA-seq and ChIP-seq. How many of the bound transposons are derepressed? Can co-occupancy by ADNP and ADNP2 explain which transposons will display synergistic effets from removal of both proteins?
Minor points
- Fig. 2B: Upset plot seems like a strange choice for visualization. I would show as stacked bar plot compared to genome distribution. I.e. are peaks enriched on repeats or is it just that a larger genomic space is occupied by repeats compared to TSSs?
- Fig. 3A: if ADNP2 only binds to a subset of K9me+ retrotransposons, why arent' there regions of K9me+ ADNP2- in this plot?
- Check figure calls for 3B and 3C, some of them seem off.
- Fig. S7B: the text says several dozen genes but I only see 21 up and 15 down upon ADNP with ADNP2 present.
Significance
This is a solid study that adds to our knowledge of these repressive complexes and their transposable element targets. I feel that the data could be analyzed a bit more in depth, especially in the comparisons of ChIP-seq vs. RNA-seq.
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Referee #2
Evidence, reproducibility and clarity
In this work, Ahel, Pandey and Schwaiger et al. examine the function of ChAHP complexes in transposon silencing in mouse embryonic stem cells. This works builds on a proteomics approach previously developed in the Buhler lab, which identified ADNP1-ChAHP as a repressor complex of SINE retrotransposons. In their previous work they also identified the zinc-finger protein ADNP2 as an interactor of the ChAHP component CHD4. Here, the authors test the hypothesis of whether ADNP2 is part of an alternative ChAHP, which they termed ChAHP2. They first establish, through proteomics/biochemistry experiments, that the ChAHP2 complex can form independently of ChAHP. By ChIP-sequencing they then show that the ChAHP2 member ADNP2 predominantly occupies retrotransposons of the LTR families (e.g., ERV elements). They further show that recognition of target transposable elements (TEs) is conferred by the ChAHP2 complex member HP1 and its affinity for H3K9me3. Using RNA-seq they then addressed the repressive activities of ChAHP and ChAHP2 on TEs through degradation of ADNP, ADNP2 or both. The experimental approach is very well thought out and experiments are done with extensive controls.
I have the following comments/suggestions:
- Regarding the ChIP-seq experiments, it is not entirely clear from the manuscript text and also not from the Material and Methods whether ChIP-seq was done with a tagged-version of ADNP2, which is what I assume, or an endogenous ADNP2 antibody. Could you please state this clearly?
- The authors map short read sequencing data to individual TE insertions and conclude that ADNP2 binds retrotransposons both internally and at their terminal sequences. Particularly for the internal parts, how sure can the authors be that their approach, mapping to repeat consensus sequences, is not confounded by e.g., genetic differences between their ESC lines and the references they map to, or simply by the limitations of short read data?
- Page 7, the first sentence starting with "Contrary to the expected behavior of a TF, ...". Could the authors please elaborate on what they mean with "the expected behavior of a TF"?
- In Figure S4B, could the authors please clarify if HP1, CHD4 and Tubulin are high/low exposure?
- SETDB1 is the H3K9me3 methyltransferase responsible for LTR/ERV silencing in mESCs and its disruption leads to a pronounced upregulation of TEs (Karimi et al., 2011). Could the authors comment on the effect of their degron-mediated SETDB1 depletion on de-repression of LTR/ERV elements? At least for the elements shown to lose H3K9me3 upon SETDB1 depletion (Figure S5D - strong depletion replicate)? Could you please also provide information about morphological/pluripotency characteristics of the 2HA-FKBPSETDB1 ESC lines before and after the 48h treatment with 500nM dTAG13?
- Maybe I missed this, but are H3K9me3 levels affected in the ADNP and/or ADNP2 degron lines where transcriptional dysregulation of TEs is observed (Figure 5)? If not H3K9me3, is TE de-repression accompanied by reduction in repressive histone marks in ADNP2 degraded lines?
- When looking at TE de-repression, the upregulation seems very modest (Figure 5) and Log2FoldChanges >0.9 (FDR<0.05) were considered as statistically significant. Is this the result of using mESCs that "approximate a constitutive KO situation through inducible ADNP2 degradation" and 14 days of treatment with 250nM dTAG13? As mention above, could you please also provide information about morphological/pluripotency characteristics?
Significance
The findings are interesting and expand on our understanding of how complexes of chromatin bound proteins control epigenetic silencing of individual retrotransposon classes/families in mouse embryonic stem cells. More specifically, this study adds a new player, ChAHP2, a ChAHP alternative that associates with ERV and LINE1 retrotransposons via HP1-mediated binding of H3K9me3 and is required for transcriptional repression of LTR class retrotransposons. Although, in my opinion, it remains somewhat uncertain how depletion of ADNP2 results in TE upregulation.
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Referee #1
Evidence, reproducibility and clarity
The Buhler group previously identified the ChAHP complex and showed it to be made up of the transcription factor ADNP, chromatin remodeler CHD4, and HP1 proteins. They found that genetic removal of ADNP leads to increased expression of SINE B2 elements in mouse ES cells (mESCs), and an increase in chromatin accessibility and CTCF binding.
In the current manuscript they describe a related protein complex they name ChAHP2. ChAHP2 has a vertebrate paralogue of ADNP, a transcription factor they call ADNP2 and the same chromatin remodeler CHD4, and HP1 proteins. By investigating chromatin occupancy they find that ChAHP2 chromatin binding specificity is distinct from ChAHP, and predominantly associates with ERV and LINE1 retrotransposons via HP1beta-mediated binding of H3K9 trimethylated histones. The ChAHP and ChAHP2 complexes control a wide variety of molecularly disparate retrotransposons, including SINEs, LINEs, and ERVs.
The findings are of significance as the ChAHP2 complex is novel - it has not previously been identified or characterized and its description is therefore worthy of publication. Overall this study was well-performed and nicely-presented. In general, the text is clear, the flow of experiments seemed logical, easy to follow and supported by the presented evidence without the findings being overstated.
The data is mainly descriptive and it was at times hard to identify what were the clear conclusions from their study. Having identified the new ChAHP2 complex they show that its chromatin binding characteristics are distinct from ChAHP, which predominantly binds SINE elements. In contrast, ChAHP2 binds different classes of retrotransposons and recruitment to H3K9me3 heterochromatin is dependent on HP1-Beta. This was all relatively clear. It became a little more confusing trying to unravel the functional consequences of the loss of ChAHP2 - either alone, or in combination with ChAHP.
Although they see changes - both up- and down-regulation of a large number of genes, they say that: 'None of the changing gene categories showed strong and significant patterns either in terms of GO term enrichment (FigureS7C), distance between the promoter and the nearest ADNP/ADNP2 peaks'- does this mean that none of the upregulated genes following ADNP1/2 deletion show ADNP/ADNP2 peaks over the specific gene in question - i.e. do they think that the majority of effects here are indirect?
When it came to the 'repeat' families of genes - the situation was also not entirely clear.
They say: All these differentially expressed repeats belonged to the LTR class of retrotransposons, including families identified as ADNP2-bound in ChIP sequencing - it would be helpful to know which familes are bound and maybe show snapshots of ADNP2 binding. Are these differentially expressed repeats directly regulated by ADNP2? - they seem like a fairly heterogenous group of repeat elements? - do they have any shared features? They say that expression of two LINE1 subclasses were significantly upregulated - do these L1s (L1Mdas) have common features - are they old or young - it would be helpful if these different issues could be clarified.
In the discussion they are upfront about their inability to identify any specific sequence motifs required for ADNP2 occupancy. Since the repression is not obviously H3K9Me3 dependent, then what is the role of H3K9me3 in repressing here? They surmise that repression is likely to be regulated through chromatin remodeling by CHD4 - would ATAC-seq help clarify this suggestion? - particularly as they suggest that having CHD4 as an integral component of the repressor complex is a unique feature of ChAHP1/2?
In this context, do they not consider MORC2 to be an essential component of HUSH-dependent silencing?
Other points
The language in the introduction somewhat confusing and could be improved: They jumble ZNFs/TRIM28/HUSH/HP1 as if there is no specificity here - there clearly is - needs a more balanced and informative description.
What is firstly referring to? Firstly, histone deacetylation and the removal of activating histone methylations disfavor transcription13,14. Secondly, the underlying DNA is extensively methylated, further repressing the locus
They state: Like ERVs, LINE1 retrotransposons are autonomous- would help if they could clarify exactly what is meant here.
Significance
The findings are of significance as the ChAHP2 complex is novel - it has not previously been identified or characterized and its description is therefore worthy of publication. Overall this study was well-performed and nicely-presented. In general, the text is clear, the flow of experiments seemed logical, easy to follow and supported by the presented evidence without the findings being overstated.
The findings will be of broad interest to chromatin biologists - particularly those interested in the regulation of retroelements and repeat regions
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Reply to the reviewers
We would like to thank the reviewers for carefully reviewing our manuscript submitted to Review Commons. Their constructive comments have led us to identify key additional experiments to perform (testing endothelial cells, investigating the role of CXCR4/Sdf1 axis in the asymmetric division). They have shed light on specific points of the manuscript that had to be amended (see below).
First, we are pleased that the reviewers acknowledged the quality of the experiments performed (Reviewer #1: “In general, is a well-done work” ; Reviewer #2: “the evidence is convincing, experiments are rigorously performed with adequate replicates and reproducibility”), as well as interest and large scope our study (Reviewer #1: * “it gives a few more details describing that when HSPCs divide asymmetrically it seems there is an association between centrosome and lysosome distribution”, Reviewer #2: “These results collectively contribute to a deeper understanding of how the hematopoietic niche and interactions with neighboring cells influence HSPC behavior and their commitment to distinct cell fates during division”, “The findings have significance in understanding how the microenvironment influences HSPC behavior. This is broadly significant for stem cell biology”. Reviewer #3 “The manuscript is likely to have broader interest to not only HSPC researchers, but stem cell biologists and even engineers due to the technologies used”).*
Our detailed answers to the reviewers’ concerns are listed below.
Reviewer #1 (Evidence, reproducibility and clarity):
In this manuscript, Candelas and colleagues investigated asymmetric cell division of human hematopoietic stem and progenitor cells (HSPCs) upon heterotypic interactions with osteoblasts. They developed a new in vitro system to test this and found that upon interaction, HSPCs polarized in interphase with centrosome and the Golgi apparatus and lysosomes positioned close to the site of contact. In addition, during mitosis, HSPCs were found to orient their spindle perpendicular to the plane of contact. This division gave rise to siblings with unequal amounts of lysosomes and CD34. In general, is a well-done work and it gives a few more details describing that when HSPCs divide asymmetrically it seems there is an association between centrosome and lysosome distribution.
Authors: We thank the reviewer for this positive assessment of our work.
Reviewer #1 (Significance (Required)):
However, all of these features (described above) have already been independently described even in human HSPCs thus this work does not represent a major advancement in this field (e.g. on the potential molecular mechanism by which heterotypic interactions with osteoblasts promote such behaviours). Overall, this stage is descriptive in nature.
Authors: We respectfully disagree with the reviewer on this point. The main finding of our work does not simply concern the ability of HSPCs to undergo asymmetric division. This ability has indeed been previously shown in mouse and human models, and we refer to the princeps works in our introduction (page 2 “In vitro HSPCs can undergo asymmetric divisions 11 12 13 14 15 16 17 ”). Our main finding is about the instrumental role of heterotypic interactions with stromal cells of the niches. This had not been shown previously, mostly due to the limitations of classical co-culture systems and of in vivo tracking of HSPCs. We have engineered artificial niches in microwells specifically to overcome these limitations. We are confident that this finding is of interest for of hematopoietic niches biology and more globally for the field of stem cell biology. In that sense, the corresponding biorXiv preprint has just been quoted by the seminal review by Hans Clevers “Hallmarks of stemness in mammalian tissues” (doi: 10.1016/j.stem.2023.12.006).
One major caveat of this work is that CD34+ HSPCs represent a very heterogeneous population. Although the underlying features described in this work could be similar between different cell populations, the frequency of these events (e.g. % magnupodium; polarization index, % of asymmetric inheritance, etc) is likely to be different between stem and progenitor cells. This may also explain the wide spread of their data points. Experiments should also be conducted with different cell populations, in particular with HSCs (either with the CD34+CD38-CD45RA-CD90+ or CD34+CD38-CD45RA-CD90+CD49f+ HSC enriched fraction or the highly CD34+CD38-CD45RA-EPCR+ HSCs).
Authors: We agree that we are dealing with an heterogenous population of stem and progenitor cells; we cannot exclude that more pronounced effects could be obtained by analyzing separately stem cells, lymphoid and myeloid progenitors. The use of CD34+ heterogenous population has been a strategical choice. We are working with human primary cells, harvested from cord blood, a rare and precious material, who’s access has been in addition reduced during the COVID period and since. Working with the global CD34+ population was giving us the ability to work with a higher number of cells and avoid material limitations to perform experiments. Importantly, in our initial publication (Bessey et al doi:10.1083/jcb.202005085), we both used CD34+, or CD34+/CD38- versus CD38+/CD34+ subpopulations (see figure 4): the effects we described using global CD34+ population were significant, validating a posteriori this choice. Similarly, the effects observed in the present work with CD34+ population have always been validated by appropriate statistic tests. So, we are confident that the use of the CD34+ population, despite its heterogeneity, did not alleviate the validity and pertinence of our analyzes and conclusions.
Results shown in Figure 2 were obtained with a very limited number of cells; also data obtained for Figure 4; this should be substantiated;
Authors: We acknowledge that the analyses performed on fixed mitotic cells are based on relatively small samples. We have decided to fix and analyze the cells at 40h of culture which corresponds to the peak of mitosis, instead of synchronizing HSPCs in mitosis with available drugs, in order to avoid potential perturbations of these drugs. The consequence was the scarcity of the mitotic HSPCs in each experiment. This limitation has also been encountered by other laboratories working on HSPCs : our samples sizes are in fact within the range of the samples analyzed in other works (see Hinge et al., 2020, doi:10.1016/j.stem.2020.01.016: around 20 cells; Florian, et al., 2018: doi: 10.1371/journal.pbio.2003389. from 8 to 40 cells). However, in order to improve this limitation, few additional experiments and analyses have been performed to increase the number of mitotic cells (Figure 3: from 27 to 38 cells).
In addition, data from Figure 2 adds little and should be combined with Figures 3 and 4 to make a single stronger message.
Authors : We agree on this comment: Figures 2 and 3 have now been merged
It is/was unclear why the authors investigated the distribution of CD34 and CD33 and the major and important question remained to be answered: whether the symmetric cell divisions were/are differentiating or self-renewal in nature hence, the asymmetric cell divisions promoted by the osteoblasts may represent asymmetric self-renewal ones; this needs to be investigated further and potential molecular mechanisms for such promotion should be highlighted.
Authors: CD34 and CD33 were chosen as our “gold standards” according to the princeps work of Loeffler et al (Loeffler et al., 2019, and 2022). Our selection is based on the need for markers that encompass this diverse population. We focused on CD34 and CD33 as they are among the most prevalent CD markers on HSPCs, particularly when working with the CD34+ population, which is broad and necessitates widely expressed CD markers. Importantly, previous works have reported that CD34 anti-correlates with lysosome asymmetric inheritance after the first division, whereas CD33 does not (see Fig3E, Loeffler et al., 2022). So using these markers we can compare two markers: one that follows lysosome inheritance after the first division, and one which doesn’t. We found that osteoblasts inducing asymmetric lysosome inheritance in HSPC do increase asymmetric production of CD34 but not CD33, in concordance with the literature. This has been now explained in more detail in the text.
In addition, higher lysosome inheritance has been previously demonstrated to be associated with the most stem cell (Loeffler et al., 2019), implying a more stem-like profile for the proximal cell during division in our work. However, recent studies using single-cell sequencing approaches challenge the notion of discrete differentiation within this stem cell model (reviewed by Zhang et al., 2018; Laurenti and Gottgens, 2018; Cheng et al., 2020; Liggett and Sankaran, 2020). Our study contributes to this discussion by providing insights into the relationship between CD markers, lysosome inheritance, and the stem cell profile during asymmetric division, and presenting this heterogeneity observed in single-cell sequencing works.
Reviewer #2 (Evidence, reproducibility and clarity (Required)):
The paper titled "Heterotypic Interaction Promotes Asymmetric Division of Human Hematopoietic Stem and Progenitor Cells" presents research on how interactions between Hematopoietic Stem and Progenitor Cells (HSPCs) and osteoblasts impact cell division symmetry. The use of polyacrylamide microwells to simulate the hematopoietic niche and study osteoblast interactions is a novel and valuable approach. The paper effectively explains the experimental design, making it easy for others to replicate and verify the results. The paper provides detailed insights into how interactions with osteoblasts influence HSPCs, particularly in terms of cell polarization, spindle orientation, and organelle distribution during cell division. The evidence is convincing, experiments are rigorously performed with adequate replicates and reproducibility.
Authors: We thank the reviewer for this positive evaluation of our work.
- The study acknowledges that not all HSPCs respond to heterotypic interaction, suggesting that individual variability in HSPC behavior plays a role. Future research could explore the factors that determine which HSPCs undergo asymmetric divisions. This raises questions about the heterogeneity in HSPC responses. The researcher starts culturing CD34+ which is a heterogeneous group with osteoblast. This heterogeneity by default will give different cells progeny which mimics the in vivo BM status. But, to minimize the invitro experiment variables examining a more pure HSC population such as isolated CD34+CD38-CD90+ cells would strengthen the findings?
Authors: We agree that we are dealing with an heterogenous population of stem and progenitor cells; we cannot exclude that more pronounced effects could be obtained by analyzing separately stem cells, lymphoid and myeloid progenitors. The use of CD34+ heterogenous population has been a strategical choice. We are working with human primary cells, harvested from cord blood, a rare and precious material, who’s access has been in addition reduced during the COVID period and since. Working with the global CD34+ population gave us the ability to work with a higher number of cells and avoid material limitations to perform experiments. Importantly, in our initial publication by Bessy et al (doi:10.1083/jcb.202005085), we used both CD34+, or in some cases CD34+/CD38- versus CD38+/CD34+ subpopulations (see figure 4), to investigate HSPC mode of polarization. The effects observed in the case of total CD34+ were significant, validating a posteriori this choice. Similarly, the effects observed in the present work with CD34+ population have always been validated by appropriate statistic tests. Our study indicates that the mechanism we described is conserved throughout the entire HSPC population.
In conclusion, we are confident that the use of the CD34+ population, despite its heterogeneity, did not alleviate the validity and pertinence of our analyzes and conclusions.
What was the Osteoblast/HSCs ratio used in the experimental setup? Does this ratio affect the results?
Authors: The loading of HSPC has been optimized to get one HPSC per microwell, as indicated in the result section (page 3 line 3). This has now been clarified in the material and methods section. However, we observe some wells with more than one HSPC on the stromal cell, but we did not notice any clear impact on cell division asymmetry and did not investigate further this parameter.
- The paper primarily focuses on lysosome inheritance and CD34 expression, leaving room to explore other lineage-specific markers and their correlation with asymmetric division. Do osteoblast/ HSCPs interactions have also an effect on mitochondrial inheritance?
Authors: We fully agree that other markers could have been analyzed to comfort our observations.
A far as mitochondria are concerned, recent publications suggest that lysosomes can be considered as a “inversed” readout of mitochondria inheritance: (1) mitophagy has been shown to take place in quiescent hematopoietic stem cells (Ito et al., 2016), suggesting that lysosomes do participate in the regulation mitochondria levels in HSPCs. (2) Loeffler et al. (2019) has shown an opposite pattern between mitochondria and lysosomes, lysosomes co-inheriting with mitophagosomes. Considering that this mutual or opposite inheritances were already described, we did not investigate them further. However we agree that it could be the focus for future works.
- While the study hints at the clinical implications of its findings, it does not show the practical applications in detail. How the knowledge gained from these interactions could be translated into clinical practices or therapies is not explicitly discussed. Bridging this gap is necessary for understanding the practical utility of these results.
Authors: we are confident that microwell technology could find, in the long term, more medical applications. However, we did not wish to speculate on this point in the present manuscript. The words “clinical” and “therapy” show no occurrence in our text. The potential implications of our findings in the field of leukemia are now mentioned in the discussion section with the corresponding references (page 6 line 10) “Such spatial control of the division is a conserved feature of asymmetric divisions in other stem cell niches 6. It may account for in vivo observations of organization into clusters of blood cell differentiation 44, and may play an important role in competition mechanisms at play within the hematopoietic niches in physiological 45 and pathological 46 contexts.”
__Reviewer #2 (Significance (Required)): __
- Investigating the process of HSPC asymmetric division is highly important to understand HSPC fate decisions and functions. The findings have significance in understanding how the microenvironment influences HSPC behavior. This is broadly significant for stem cell biology.
- The paper's observation of uneven lysosome distribution and its potential impact on differentiation markers, including CD34 and CD33, contribute to our understanding of HSPC division and lineage determination.
- Upon interaction with osteoblasts, HSPCs polarize during interphase, with centrosomes, the Golgi apparatus, and lysosomes positioned close to the site of contact. This reorganization of intracellular architecture plays a significant role in asymmetric division.
- These results collectively contribute to a deeper understanding of how the hematopoietic niche and interactions with neighboring cells influence HSPC behavior and their commitment to distinct cell fates during division.
Authors: We thank the reviewer for this quite positive evaluation of our work.
Reviewer #3 (Evidence, reproducibility and clarity):
Summary: In this study, the authors systematically work to identify the contribution of hematopoietic niche stromal cells in the control of HSPC asymmetric divisions. Using live cell imaging techniques, the authors show that heterotypic interaction with osteoblasts promotes asymmetric division of human HSPCs. The authors find that HSPCs polarize in interphase with centrosome, the Golgi apparatus and lysosomes positioned close to the site of contact. Moreover, during mitosis, HSPCs orient their spindle perpendicular to the plane of osteoblast contact and the subsequent division gives rise to siblings with unequal amounts of lysosomes and differentiation markers such as CD34. Taken together, the authors suggest that this asymmetric inheritance generates heterogeneity in progeny, which is likely to contribute to plasticity during the early steps of hematopoiesis.
Major Comments:
- The study that uses polyacrylamide microwells as minimalist niches to evaluate the role of heterotypic interactions in the asymmetric division of HSPCs. Using this model system, the data clearly indicate that osteoblasts promote HSPC polarization when compared to fibronectin or skin fibroblasts. However, osteoblasts weren't compared to other HSPC stromal niche components. For example, is the same polarization observed with endothelial cells? This would help to determine whether this observation is specific to only osteoblasts in the niche or if there's a broader role for heterotypic interactions, which is the claim made in the discussion.
Authors: We have now performed additional experiments using endothelial cells (see Figure 1 and 2, Page 3 and 4) and found that endothelial cells do also promote asymmetric division.
This is primarily a descriptive study that doesn't attempt to address or even postulate the type of receptors potentially responsible for the polarization-driving heterotypic interactions. Perhaps inhibitors to candidate receptors could be incorporated or at least candidate receptors could be mentioned and described in the discussion as future directions.
Authors: We have now performed additional experiments to address this point: We have analyzed the effect of the CXCR4 antagonist AMD3100 on HSPC division upon interaction with osteoblast and found that blocking these receptors reduce the asymmetry of daughter cells to the level of isolated HSPC (see Figure 3 E -G; Figure S3 H-J; page 4).
__Minor Comments: __
- There is no reference to Figures 2C and D in the text. Authors : This oversight has been corrected.
Page 3: “HSPC cultured on fibronectin exhibited spindle oriented parallel to the well bottom, (Figure 2A-C and S3C and D)”.
Page 4: In contrast, both equal and unequal LysoBriteTM segregations could be observed (Figure 2D and S3E).
The different circle colors in Figure 4C and D are a bit difficult to distinguish.
Authors: The figure has been modified accordingly
It's difficult to identify where the sites of cell contact are in Figure 2. Perhaps contact sites could be indicated in the images.
Authors: The sites of contact have now been systematically indicated using dashed lines, in Figure 2 and 3.
It's not clear how spindle orientation is being identified in Figure 3.
Authors: We are aware of the fact that spindle orientation is not easy to visualize in the still images presented in Figure 3A and B. These images are extracted from the movies that were used to determine the cell division plane visually. This plane, following the long-axis rule, is perpendicular to the spindle orientation, which could therefore be determined. Movies 6 and 7 are shown to support these observations and illustrate how amenable these movies are to support spindle orientation analysis.
Some grammatical errors need to be addressed throughout the manuscript.
Authors: We thank the reviewer for drawing our attention on this point: the modified text has been carefully examined, and hopefully improved.
Reviewer #3 (Significance):
Significance: Overall, this is straightforward study that presents data illustrating the polarization driving capacity of osteoblast interactions with HPSC. The findings are important to the field, as little is known about asymmetric vs symmetric division in HSPCs. However, in its current form, the manuscript lacks clarity with respect to whether specifically osteoblasts promote HSPC polarization, or any stromal niche player has this capacity. Moreover, there is a lack of mechanistic data and/or discussion about how osteoblasts may be driving the observed polarization.
Authors: We have now added data showing the similar role of endothelial cells and the implication of CXCR4 receptors.
The manuscript is likely to have broader interest to not only HSPC researchers, but stem cell biologists and even engineers due to the technologies used.
Authors: We thank the reviewer for his/her enthusiasm for our work
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Referee #3
Evidence, reproducibility and clarity
Title: Heterotypic interaction promotes asymmetric division of human hematopoietic stem and progenitor cells
Authors: Adrian Candelas, Benoit Vianay, Matthieu Gelin, Lionel Faivre, Jerome Larghero, Laurent Blanchoin, Manuel Théry, Stephane Brunet
Summary: In this study, the authors systematically work to identify the contribution of hematopoietic niche stromal cells in the control of HSPC asymmetric divisions. Using live cell imaging techniques, the authors show that heterotypic interaction with osteoblasts promotes asymmetric division of human HSPCs. The authors find that HSPCs polarize in interphase with centrosome, the Golgi apparatus and lysosomes positioned close to the site of contact. Moreover, during mitosis, HSPCs orient their spindle perpendicular to the plane of osteoblast contact and the subsequent division gives rise to siblings with unequal amounts of lysosomes and differentiation markers such as CD34. Taken together, the authors suggest that this asymmetric inheritance generates heterogeneity in progeny, which is likely to contribute to plasticity during the early steps of hematopoiesis.
Major Comments:
- The study that uses polyacrylamide microwells as minimalist niches to evaluate the role of heterotypic interactions in the asymmetric division of HSPCs. Using this model system, the data clearly indicate that osteoblasts promote HSPC polarization when compared to fibronectin or skin fibroblasts. However, osteoblasts weren't compared to other HSPC stromal niche components. For example, is the same polarization observed with endothelial cells? This would help to determine whether this observation is specific to only osteoblasts in the niche or if there's a broader role for heterotypic interactions, which is the claim made in the discussion.
- This is primarily a descriptive study that doesn't attempt to address or even postulate the type of receptors potentially responsible for the polarization-driving heterotypic interactions. Perhaps inhibitors to candidate receptors could be incorporated or at least candidate receptors could be mentioned and described in the discussion as future directions.
Minor Comments:
- There is no reference to Figures 2C and D in the text.
- The different circle colors in Figure 4C and D are a bit difficult to distinguish.
- It's difficult to identify where the sites of cell contact are in Figure 2. Perhaps contact sites could be indicated in the images.
- It's not clear how spindle orientation is being identified in Figure 3.
- Some grammatical errors need to be addressed throughout the manuscript.
Significance
Overall, this is straightforward study that presents data illustrating the polarization driving capacity of osteoblast interactions with HPSC. The findings are important to the field, as little is known about asymmetric vs symmetric division in HSPCs. However, in its current form, the manuscript lacks clarity with respect to whether specifically osteoblasts promote HSPC polarization, or any stromal niche player has this capacity. Moreover, there is a lack of mechanistic data and/or discussion about how osteoblasts may be driving the observed polarization.
The manuscript is likely to have broader interest to not only HSPC researchers, but stem cell biologists and even engineers due to the technologies used.
I have experience with questions of HSPC regulation.
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Referee #2
Evidence, reproducibility and clarity
The paper titled "Heterotypic Interaction Promotes Asymmetric Division of Human Hematopoietic Stem and Progenitor Cells" presents research on how interactions between Hematopoietic Stem and Progenitor Cells (HSPCs) and osteoblasts impact cell division symmetry. The use of polyacrylamide microwells to simulate the hematopoietic niche and study osteoblast interactions is a novel and valuable approach. The paper effectively explains the experimental design, making it easy for others to replicate and verify the results. The paper provides detailed insights into how interactions with osteoblasts influence HSPCs, particularly in terms of cell polarization, spindle orientation, and organelle distribution during cell division. The evidence is convincing, experiments are rigorously performed with adequate replicates and reproducibility.
- The study acknowledges that not all HSPCs respond to heterotypic interaction, suggesting that individual variability in HSPC behavior plays a role. Future research could explore the factors that determine which HSPCs undergo asymmetric divisions. This raises questions about the heterogeneity in HSPC responses. The researcher starts culturing CD34+ which is a heterogeneous group with osteoblast. This heterogeneity by default will give different cells progeny which mimics the in vivo BM status. But, to minimize the invitro experiment variables examining a more pure HSC population such as isolated CD34+CD38-CD90+ cells would strengthen the findings? What was the Osteoblast/HSCs ratio used in the experimental setup ? Does this ratio affect the results?
- The paper primarily focuses on lysosome inheritance and CD34 expression, leaving room to explore other lineage-specific markers and their correlation with asymmetric division. Do osteoblast/ HSCPs interactions have also an effect on mitochondrial inheritance ?
- While the study hints at the clinical implications of its findings, it does not show the practical applications in detail. How the knowledge gained from these interactions could be translated into clinical practices or therapies is not explicitly discusssed. Bridging this gap is necessary for understanding the practical utility of these results.
Significance
- Investigating the process of HSPC asymmetric division is highly important to understand HSPC fate decisions and functions. The findings have significance in understanding how the microenvironment influences HSPC behavior. This is broadly significant for stem cell biology.
- The paper's observation of uneven lysosome distribution and its potential impact on differentiation markers, including CD34 and CD33, contribute to our understanding of HSPC division and lineage determination.
- Upon interaction with osteoblasts, HSPCs polarize during interphase, with centrosomes, the Golgi apparatus, and lysosomes positioned close to the site of contact. This reorganization of intracellular architecture plays a significant role in asymmetric division.
- These results collectively contribute to a deeper understanding of how the hematopoietic niche and interactions with neighboring cells influence HSPC behavior and their commitment to distinct cell fates during division.
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Referee #1
Evidence, reproducibility and clarity
In this manuscript, Candeleas and colleagues investigated asymmetric cell division of human hematopoietic stem and progenitor cells (HSPCs) upon heterotypic interactions with osteoblasts. They developed a new in vitro system to test this and found that upon interaction, HSPCs polarized in interphase with centrosome and the Golgi apparatus and lysosomes positioned close to the site of contact. In addition during mitosis, HSPCs were found to orient their spindle perpendicular to the plane of contact. This division gave rise to siblings with unequal amounts of lysosomes and CD34. In general, is a well-done work and it gives a few more details describing that when HSPCs divide asymmetrically it seems there is an association between centrosome and lysosome distribution.
Significance
However, all of these features (described above) have already been independently described even in human HSPCs thus this work does not represent a major advancement in this field (e.g. on the potential molecular mechanism by which heterotypic interactions with osteoblasts promote such behaviours). Overall, this stage is descriptive in nature.
One major caveat of this work is that CD34+ HSPCs represent a very heterogeneous population. Although the underlying features described in this work could be similar between different cell populations, the frequency of these events (e.g. % magnupodium; polarization index, % of asymmetric inheritance, etc) is likely to be different between stem and progenitor cells. This may also explain the wide spread of their data points. Experiments should also be conducted with different cell populations, in particular with HSCs (either with the CD34+CD38-CD45RA-CD90+ or CD34+CD38-CD45RA-CD90+CD49f+ HSC enriched fraction or the highly CD34+CD38-CD45RA-EPCR+ HSCs).
Results shown in Figure 2 were obtained with a very limited number of cells; also data obtained for Figure 4; this should be substantiated; in addition, data from Figure 2 adds little and should be combined with Figures 3 and 4 to make a single stronger message.
It is/was unclear why the authors investigated the distribution of CD34 and CD33 and the major and important question remained to be answered: whether the symmetric cell divisions were/are differentiating or self-renewal in nature hence, the asymmetric cell divisions promoted by the osteoblasts may represent asymmetric self-renewal ones; this needs to be investigated further and potential molecular mechanisms for such promotion should be highlighted.
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Reply to the reviewers
Reviewer #1
- Albeit the link between CSA and NE integrity the work is in my eyes too preliminary. Although the data presented are well done and carefully evaluated they mostly (except Fig 1A) rely on direct comparisons of one patient cell line (CS-A or CS-B) to the same cells expression the wildtype protein. It remains thus open whether the effects seen on LEM2 expression, LEM2-LaimA/C interaction, stress fibre formation, cGAS/STING signaling pathway activation in the CS-A cells are representative for a number of different CS patient derived cells. This is especially important given the small changes observed. Please note that there are alos clear differences between the CSA-wt and CSB-wt cells. Would the HPA CSA KO cells show in addition to NE irregularities (not even quantified) the same phenotypes and can they be reverted by re-expression of the wildtype CSA protein? We would like to thank the reviewer for this comment. Indeed we have previously observed nuclear circularity defects in CSA KO HAP1 cells but we haven’t investigated the other phenotypes in this cell line. One of the main reasons behind this is the technical difficulties associated with performing immunofluorescence with HAP1 cells who are very small and tend to grow in aggregates.
Proposed experimental plan: To address this reviewer’s comment, we will attempt again to use HAP1 cells (WT and CSA KO) and look at nuclear circularity (with quantification), stress fiber formation and cGas foci. If we don’t succeed, we will use an alternative isogenic cell model consisting of fibroblasts in which we will knock out CSA using CRISPR/Cas9. We will then repeat the same experiments as proposed above for the HAP1 cells.
- The link between CSA and SUN1 is not well worked out. What is the effect of SUN2 downregulation and that of nespirins? It remains unclear whether the observed effects are indeed LINC mediated. Proposed experimental plan: To address this point, we will downregulate SUN2 and nesprins using siRNAs in two different cell models (as described above) and assess nuclear shape as well as cGas/STING pathway activation.
Minor comments:
* Fig 1B: Why is HA-Tagged CSA not shown on the CSA western? This would be helpful to compare to the endogenous levels at least in CSB cells. A western showing an housekeeping marker would allow better comparison. Judging from the proteins markers HA-tagged CSA seems much larger as endogenous CSA (first versus second row). Again, less cropped western blots would help.*
We are sorry for the confusion and we have realised that the molecular weights on the western blots were incorrectly labeled on this figure. This will be modified, and the full, uncropped WB will be provided as a supplementary file.
Fig 3A: Is CSA FLAG or HA-tagged? Or both? If both are expressed the question raises of why the CSA-LEM 2 interaction is only seen in an overexpression situation.
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CSA is HA tagged. To address this reviewer’s comment we will try performing immunoprecipitation on endogenous proteins.
Fig 5: Inconsistency between figure and figure legend: 20 vs 25 nM Jasplakinolide. I assume Latrunculin A should read Cytochalasin D?
Thank you for pointing this out, and yes this is indeed a mistake on our labeling. We will rectify this on the figure legend.
Fig5B: Not clear why in "CSA-wT cells" Cytochalasin D and Jasplakinolide have the same effect on nuclear envelope shape yet only Jasplakinolide increases the number of blebs.
Cyt D inhibits actin polymerization while jasplakinolide increases polymerization. Likely actin polymerization increases blebs through extra force being put on the nucleus through actin cables/ actin based motility. Both drugs decrease nuclear roundness as they disrupt the normal actin network leading to worsening of nuclear shape through different mechanisms.
Page 10: Method for IF: 4% (v/v) paraformaldehyde and 2% /v/v) should likely read (w/v). Page 19: replace "withl" by "with".
We will rectify both these points.
Reviewer #2
The paper is well-written and for the most part, the data support the conclusions of the authors. Some minor caveats could be addressed to improve the quality of the manuscript.
We would like to thank the reviewer for their positive feedback on our manuscript.
• The phenotype of decreased LEMD2 incorporation into the NE in CS-A cells is minor. Only ~20% and thus, it is not clear whether this is causal of any of the NE abnormalities. It should be better explained how these data add to the story.
To address this point, we will overexpress LEMD2 in CS-A cells and assess whether the NE phenotype can be significantly rescued. This will add value to this part of story.
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Inducing actin polymerization and depolarization impact nuclear morphological abnormalities and nuclear blebbing. Do these treatments impact nuclear fragility and cGAS accumulation at NE break sites?* This is a good point indeed. To address this question, we will include cGas foci staining and quantification upon treatment with these chemicals.
- Depletion of SUN1 in CS-A cells increased nuclear circularity, decreased blebbing, and phosphorylation of TBK1. The impact of SUN1 depletion in cGAS foci formation at NE break sites and phosphorylation of STING is not shown. Such experiments will provide stronger evidence that CS-A activates the cGAS-STING pathway in a SUN1 (mechanical stress)-dependent manner.
* We will address this question by analysing cGas foci and cGas-STING pathway activation upon SUN1 depletion by siRNA.
Reviewer #3
- *
The data are generally clear, well performed and well interpreted with some exceptions:*
1) I appreciate the use of isogenic cell lines (a big plus when dealing with patient-derived cell lines). However, these lines were established 30 years ago and the reported phenotypes might be due to genetic drifts. To exclude this, I suggest to complement the HAP-1 ERCC8 KO cell line with exogenously expressed CSA and assess if this rescues the phenotypes reported. Validation of the KO in these lines, either by western blotting or sequencing is needed.*
This point has also been raised by the first reviewer, and will be addressed as described above (and pasted below):
We would like to thank the reviewer for this comment. Indeed we have previously observed nuclear circularity defects in CSA KO HAP1 cells but we haven’t investigated the other phenotypes in this cell line. One of the main reasons behind this is the technical difficulties associated with performing immunofluorescence with HAP1 cells who are very small and tend to grow in aggregates.
Proposed experimental plan: To address this reviewer’s comment, we will attempt again to use HAP1 cells (WT and CSA KO) and look at nuclear circularity (with quantification), stress fiber formation and cGas foci. If we don’t succeed, we will use an alternative isogenic cell model consisting of fibroblasts in which we will knock out CSA using CRISPR/Cas9. We will then repeat the same experiments as proposed above for the HAP1 cells.
2) Related to the complementation of patient cell lines, the exogenous HA-CSA is not recognised by the anti-CSA in the CSA-null patient cell lines (Fig 1B, second blot). Shouldn't you be able to see this exogenous protein? HA-GFP-CSB in the complemented CSB-null patient cell line runs at the same weight as endogenous CSB (Fig 1B, fourth blot). This is also unexpected. I think you need better characterisation of your cell lines and need to demonstrate the level of exogenous transgenes that have been used to complement the cells and that they localise appropriately, presumably to the nucleus. You should also make sure to cite the paper where they were isolated and describe that they were immortalised (Troelstra et al., 1992) and the paper in which transgenes were stably overexpressed (Qiang et al., 2021).*
*
As mentioned above, we have realised that we made some mistakes with the labeling of the molecular weight on this western blot. This will be corrected and the full uncropped western blot will be provided as a supplementary figure.
We will also cite the suggested papers accordingly.
3) Immunolocalisation of INM proteins is notoriously tricky and the permeabilisation steps include only 0.2% Tx100, which can be insufficient to permeabilise the INM. I appreciate the Emerin and Lamin immunostaining seems to have worked, but in many cases successful immunostaining can be antibody-specific. Can you try harsher permeabilisation to expose LEM2 epitopes? I'm somewhat uncomfortable with the suggestion that there is a cytosolic (ER?) pool of endogenous LEM2 as this runs counter to the literature and feel that your antibody or fixation conditions are illuminating a non-specific protein. The WB in Fig 2E shows that there is virtually no LEM2 in the "soluble" fraction. I would be more cautious on this cytoplasmic/nuclear pool interpretation. Biochemical nuclear and cytoplasmic fractionation would help clarify the signal in a NE vs a non-NE pool.*
*
As suggested by the reviewer, we will try harsher permeabilisation conditions to test the LEMD2 antibody. As we suggest in the manuscript however, we think that the “cytoplasmic” LEMD2 pool we observed by IF in the absence of pre-extraction is indeed unspecific. This is why we have performed the rest of the experiments with a pre-extraction step, that we have shown to give a specific LEMD2 signal that disappear upon depleting LEMD2 by siRNA.
4) Page 15: "Using a Proximity Ligation Assay (PLA), we showed a significant reduction in the number of PLA foci in CS-A cells compared to the WT(HA-CSA) cells, reflecting a reduced number of LEMD2-lamin A/C complexes (Figure 2G, 2H). This data suggests defects in the incorporation of LEMD2 into the NE and lamin protein complexes in CS-A cells". If you have less LEM2 in the NE, it is quite expected that you will have less "LEM2-laminA/C" complexes. To me the logic doesn't hold and this data does not suggest that there is an underlying defect in LEM2-lamin interaction. To ascertain whether there is such a defect one could perform an IP against LEM2 and quantify laminA/C, normalizing by the amount of LEM2 in the input.
We feel we may not have been clear in how we interpreted this data. What we mean is that in each individual cell, the number of Lamin-LEMD2 complexes is decreased, probably indeed due to the fact that there is less LEMD2 altogether within the nucleus in the absence of CSA. We will clarify this in the text.
5) "We overexpressed LEMD2-GFP and Flag-CSA constructs, followed by GFP pulldown in WT(HA-CSA) cells". Since the co-IP data are obtained in overexpression conditions (of both HA-CSA and Flag-CSA?), the authors should validate the interaction between LEM2 and CSA using an orthogonal approach. Perhaps anti-HA capture of the WT(HA-CSA) cells would allow you to immunoblot for endogenous LEM2?*
*
To address this point, we will try to immunoprecipitate HA-CSA and look at endogenous LEMD2.
6) Related to the CSA-LEM2 binding in the above experiment, the procedure involves combining a native detergent-extracted cytoplasmic pool with a denatured (RIPA-extracted) nuclear pool for performing the GFP-trap. From which pool was the tagged CSA bound to LEM2 in?*
*
We are sorry about the confusion. We didn’t try to run the IP from the different pools but instead from the combined pools, to ensure we were looking in the whole cell extract. We would expect however that the interaction occurs in the nuclear pool as both CSA and LEMD2 are nuclear proteins.
7) "The absence of CSA in CS-A patient cells does not affect the mobility of LEMD2 at the NE but instead decreases its interaction with A-type lamins". To me the fact that loss of CSA decreases LEM2-lamin interaction is not well supported (see point 3).
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See our response to point 4
8) "Here, we showed by immunoprecipitation that LEMD2 also interacts with CSA. This suggests that the recruitment and stabilization of LEMD2 to the NE is mediated by an interaction with CSA, although the mechanism remains unclear". I think this is an overstatement: there are no data suggesting that CSA recruits or stabilises LEM2 at the NE.
* *We will tone down this statement in the text
9) As the authors suggest in the discussion, it would be worth checking whether LEM2 overexpression is able to rescue some of the NE defects reported, strengthening the hypothesis that LEM2 levels are at least in part responsible for the phenotypes reported.
To address this point, we will perform LEMD2 overexpression in the CSA cells, and analyse the nuclear envelope defects and ruptures (shape and cGas foci quantification)
10) To me it is not clear how the reported phenotypes are interrelated. The first part of the manuscript shows that CSA interacts with LEM2, and that loss-of-function CSA impacts on LEM2 levels and LEM2-lamin interaction, suggesting a direct role for CSA at the nuclear envelope. The second part of the manuscript shows that cells with defective CSA have more actin stress fibres and releasing the cytoskeleton-nuclear tethering is able per se to rescue the nuclear membrane and cGAS phenotypes. How do the authors reconciliate these two parts? Is CSA directly involved in both inner nuclear membrane homeostasis and actin cytoskeleton modulation or is this latter role upstream and the NE defects a mere consequence of increased cytoskeleton rigidity?
At this point indeed we cannot draw definitive conclusions as to whether the two described phenotypes are inter-related. However, by addressing the other points raised by the reviewers, we hope this will help clarifying the mechanism.
11) It is not clear how or why actin stress fibres are elevated in the CS-A cells. Can the authors provide any insight based on their RNAseq analysis? Demonstrating a link to ROCK, LIMK or Rho signalling would be interesting and verifying ppMLC2 levels would help explain why contractility is enhanced. Additionally, is the increase in contractility dependent upon any of the genes identified as up- or downregulated in RNAseq? Presently, the manuscript is missing a link between its two halves.*
*
We would like to reiterate that the RNASeq analysis we performed was done on previously published data from another group (as described in the text). To address the point raised by the reviewer, we will look more specifically into our analysis to look at ROCK, LIMK or Rho signalling to see if any of these pathways appear to be modulated by the absence of CSA.
12) Related to point 1, the RNAseq comparison was performed on patient cells lacking CS-A and patient cells lacking CS-A and later over-expressing HA-CSA, and this comparison is used extensively for phenotype description in the manuscript. In isn't clear to me that this is the most insightful comparison to make; the rescue by overexpression is not as elegant as CRISPR reversion and the ko fibroblasts have presumably been surviving well in culture without CS-A before this protein was overexpressed. Can you validate the differential expression of any identified proteins in the acute HAP1 ko? Can you validate any of the differentially expressed proteins in comparison to normal fibroblasts (e.g., 13O6, as per Qiang et al., 2021)?
As we will validate our experiments in an additional cell model (as described above), we will also indeed validate the level of expression of cytoskeletal proteins upon CSA KO/rescue.
Minor comments
* - Page 14: "To characterize the NE phenotypes further, we obtained CS patient-derived cell lines carrying loss-of-function mutations in CSA (CS-A cells) or CSB (CS-B cells), and their respective isogenic control cell lines (WT(HACSA) and WT(HA-GFP-CSB))." What type of loss-of-function? Is the mutant protein still produced? In Fig 6A there seem to be a band in the CS-A blot (second lane), but in Fig 1B, there isn't. I think this is important to know to interpret the phenotype related to LEM2 interaction.*
We can clarify that in the text. Indeed, the loss of function mutation leads to the absence of CSA protein.
- Figure 1B is poorly annotated. What do - and + stand for? In general, I find a bit confusing how the WB are presented throughout the manuscript, specifically how the antibodies are reported (e.g., HA-CSA instead of HA). Please mark up all western blots with antisera used. Please make sure all expected bands are within the crops - e.g., Fig 3B, the anti-LEM2 blot should be expanded vertically to show the LEM2-GFP relative to endogenous LEM2.
We will correct these on the figures
- From the methods, it appears that you obtained a Please provide clarity on which construct was used in which figure, and verify that an N-terminally tagged LEM2 still localises to the NE.
We actually cloned LEMD2 into an empty pEGFP vector but still maintained LEM2-GFP. We will remove the C1plasmid from the methods to avoid confusion as we removed the MCS and GFP and just used the blank vector and inserted lem2-gfp as we obtained it.
- Fig 1I: there is some text on top of the upper panels (DAPI, cGAS, Merge).
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* - "Through gene ontology analysis, we found that genes involved in endoplasmic reticulum (ER) stress were differentially expressed (Figure 4B)". I don't think that the way data are shown in Fig 4B is effective. Since GO has been performed, I would replace the table with a GO enrichment analysis graph. Ensure to report all the data in a supplementary .xls so that others can see and reuse it. Is there a mandated repository that accepts RNAseq data?*
The RNAseq experiment and data was performed by another group and reported in a previous study, as referenced in the main text of the manuscript (Epanchintsev A, Costanzo F, Rauschendorf MA, Caputo M, Ye T, Donnio LM, et al. Cockayne’s Syndrome A and B Proteins Regulate Transcription Arrest after Genotoxic Stress by Promoting ATF3 Degradation. Mol Cell. 2017 Dec;68(6):1054-1066.e6.). Here, we only re-analysed their data using STRING pathway analysis, as detailed in the Material and Methods. However, as suggested by the reviewer, we will replace the table by a GO enrichment graph.
- The volcano plot looks weird with many values at the maximum log10 (P-value) - is the data processed appropriately?
As mentioned above, the RNA Seq analysis was performed and published in a different study. We think this is because the Y axis shows adjusted P values.
- Figure 5B: the legend says "Latrunculin A". Please correct.
We will correct this
- For a Wellcome funded researcher, I'm surprised that the mandated OA statement and RRS is absent from the acknowledgements.
We will of course comply with the open access policy of the Wellcome Trust. However, and based on the WT requirements detailed on their website, we believe the acknowledgement section complies with the funder’s policy: “All research publications must acknowledge Wellcome's support and list the grant reference number which funded the research reported.”
Maybe mention the changes in nuclear shape is not a causative of nuclear blebbing. But maybe not say that they are completely mutually exclusive phenotype to each other.
suggestion
Maybe say that we will overexpress LEMD2 in CS-A cells and show that the NE phenotype can be significantly rescued. This will add value to this part of story. I remember when I did the FRAP experiment, CS-A cells with expression of LEMD2-GFP (that doesn’t form aggregates) looks better in term of shape.
I think Anne, please check the plasmid map? According to the lab inventory (Plasmids Anne), it is LEMD2-GFP. So probably GFP is at C-terminus.
I think there was a part in discussion was LEMD2-GFP was mistakenly written as GFP-LEMD… But I am sure I used LEMD2-GFP throughout the work
We cloned it into an empty pEGFP vector but still maintained LEM2-GFP. Maybe remove the C1 in the methods to avoid confusion as we removed the MCS and GFP and just used the blank vector and inserted lem2-gfp as we obtained it.
Same construct was used for GFP pulldown and for FRAP. And we can see in FRAp that they localise to the NE. SO it should localise to the NE. Maybe mention that we will do a LEMD2-GFP over expression experiment in CS-A cells and show that they do localise to the NE.
I don’t remember fully if Denny did this and what came out. I thought he did and ER stress and cytoskeleton regulation came out as enriched terms?
Denny will have to check this but I think this is because the Y axis shows adjusted P values?? I have the same in my data and Jack told me this is an artefact of the analysis if you adjust for multiple comparisons and is something more often seen in mass spec data
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Referee #3
Evidence, reproducibility and clarity
Summary
In this manuscript, Yang and colleagues report that the absence of CSA (a protein with a well-characterised role in DNA damage repair and whose mutations cause a premature ageing syndrome) leads to defects in nuclear envelope (NE) integrity. Using a Cockayne syndrome patient-derived cell line they show that CSA deficiency correlates with the presence of an aberrant nuclear morphology, nuclear blebbing and increased cGAS-signalling. Moreover, they suggest that this CSA defective cell line presents decreased LEM2 at the NE and a consequent reduction in LEM2-laminA/C interaction. They were able to observe interaction betweenCSA and LEM2, andsuggested that CSA might interfere with LEM2 functionality at the nuclear envelope. Starting from the analysis of an already published RNAseq dataset, the authors go on investigating the cytoskeleton status in the CSA mutant cell line and identify an increase in actin, which they suggest leads to an increase in actin stress fibres. By promoting general actin depolymerisation and by disanchoring the cytoskeleton from the nuclear envelope, Yang et al are able to rescue the dysfunctional phenotypes reported above, suggesting that increased mechanical forces transmitted from the actin cytoskeleton to the nuclear envelope might cause defects in nuclear envelope integrity. Finally, the authors report that alleviating the nuclear envelope defects in CSA mutant cells does not decrease their sensitivity to a UV mimetic, hinting that CSA role in maintaining nuclear integrity is independent from its DNA damage repair function.
Major comments
The key conclusions of the manuscript are convincing and supported by the data. However, there are some conceptual concerns that limit my enthusiasm.
Firstly, that the actin cytoskeleton can transmit forces to the NE via the LINC complex is established. That these forces that lead to NE deformation, and in some cases, rupture, is somewhat unsurprising. The interesting observation in this manuscript is that CSA mutant patient cells exhibit more stress fibres. This leads to more LINC-dependent transmission of forces to the NE, with consequential effects on NE morphology and rupture. However, the mechanism by which actomyosin contractility is elevated in CSA-mutant patient cells is unexplored.
Secondly, it is unclear whether CSA controls the quality, or simply the number, of LEM2/Lamin interactions. As such, a mechanistic link between elevated stress fibres and CSA-dependent NE/lamina interactions is not provided and the paper sits as two presently unconnected observations.
The data are generally clear, well performed and well interpreted with some exceptions:
- I appreciate the use of isogenic cell lines (a big plus when dealing with patient-derived cell lines). However, these lines were established 30 years ago and the reported phenotypes might be due to genetic drifts. To exclude this, I suggest to complement the HAP-1 ERCC8 KO cell line with exogenously expressed CSA and assess if this rescues the phenotypes reported. Validation of the KO in these lines, either by western blotting or sequencing is needed.
- Related to the complementation of patient cell lines, the exogenous HA-CSA is not recognised by the anti-CSA in the CSA-null patient cell lines (Fig 1B, second blot). Shouldn't you be able to see this exogenous protein? HA-GFP-CSB in the complemented CSB-null patient cell line runs at the same weight as endogenous CSB (Fig 1B, fourth blot). This is also unexpected. I think you need better characterisation of your cell lines and need to demonstrate the level of exogenous transgenes that have been used to complement the cells and that they localise appropriately, presumably to the nucleus. You should also make sure to cite the paper where they were isolated and describe that they were immortalised (Troelstra et al., 1992) and the paper in which transgenes were stably overexpressed (Qiang et al., 2021).
- Immunolocalisation of INM proteins is notoriously tricky and the permeabilisation steps include only 0.2% Tx100, which can be insufficient to permeabilise the INM. I appreciate the Emerin and Lamin immunostaining seems to have worked, but in many cases successful immunostaining can be antibody-specific. Can you try harsher permeabilisation to expose LEM2 epitopes? I'm somewhat uncomfortable with the suggestion that there is a cytosolic (ER?) pool of endogenous LEM2 as this runs counter to the literature and feel that your antibody or fixation conditions are illuminating a non-specific protein. The WB in Fig 2E shows that there is virtually no LEM2 in the "soluble" fraction. I would be more cautious on this cytoplasmic/nuclear pool interpretation. Biochemical nuclear and cytoplasmic fractionation would help clarify the signal in a NE vs a non-NE pool.
- Pag 15: "Using a Proximity Ligation Assay (PLA), we showed a significant reduction in the number of PLA foci in CS-A cells compared to the WT(HA-CSA) cells, reflecting a reduced number of LEMD2-lamin A/C complexes (Figure 2G, 2H). This data suggests defects in the incorporation of LEMD2 into the NE and lamin protein complexes in CS-A cells". If you have less LEM2 in the NE, it is quite expected that you will have less "LEM2-laminA/C" complexes. To me the logic doesn't hold and this data does not suggest that there is an underlying defect in LEM2-lamin interaction. To ascertain whether there is such a defect one could perform an IP against LEM2 and quantify laminA/C, normalizing by the amount of LEM2 in the input.
- "We overexpressed LEMD2-GFP and Flag-CSA constructs, followed by GFP pulldown in WT(HA-CSA) cells". Since the co-IP data are obtained in overexpression conditions (of both HA-CSA and Flag-CSA?), the authors should validate the interaction between LEM2 and CSA using an orthogonal approach. Perhaps anti-HA capture of the WT(HA-CSA) cells would allow you to immunoblot for endogenous LEM2?
- Related to the CSA-LEM2 binding in the above experiment, the procedure involves combining a native detergent-extracted cytoplasmic pool with a denatured (RIPA-extracted) nuclear pool for performing the GFP-trap. From which pool was the tagged CSA bound to LEM2 in?
- "The absence of CSA in CS-A patient cells does not affect the mobility of LEMD2 at the NE but instead decreases its interaction with A-type lamins". To me the fact that loss of CSA decreases LEM2-lamin interaction is not well supported (see point 3).
- "Here, we showed by immunoprecipitation that LEMD2 also interacts with CSA. This suggests that the recruitment and stabilization of LEMD2 to the NE is mediated by an interaction with CSA, although the mechanism remains unclear". I think this is an overstatement: there are no data suggesting that CSA recruits or stabilises LEM2 at the NE.
- As the authors suggest in the discussion, it would be worth checking whether LEM2 overexpression is able to rescue some of the NE defects reported, strengthening the hypothesis that LEM2 levels are at least in part responsible for the phenotypes reported.
- To me it is not clear how the reported phenotypes are interrelated. The first part of the manuscript shows that CSA interacts with LEM2, and that loss-of-function CSA impacts on LEM2 levels and LEM2-lamin interaction, suggesting a direct role for CSA at the nuclear envelope. The second part of the manuscript shows that cells with defective CSA have more actin stress fibres and releasing the cytoskeleton-nuclear tethering is able per se to rescue the nuclear membrane and cGAS phenotypes. How do the authors reconciliate these two parts? Is CSA directly involved in both inner nuclear membrane homeostasis and actin cytoskeleton modulation or is this latter role upstream and the NE defects a mere consequence of increased cytoskeleton rigidity?
- It is not clear how or why actin stress fibres are elevated in the CS-A cells. Can the authors provide any insight based on their RNAseq analysis? Demonstrating a link to ROCK, LIMK or Rho signalling would be interesting and verifying ppMLC2 levels would help explain why contractility is enhanced. Additionally, is the increase in contractility dependent upon any of the genes identified as up- or downregulated in RNAseq? Presently, the manuscript is missing a link between its two halves.
- Related to point 1, the RNAseq comparison was performed on patient cells lacking CS-A and patient cells lacking CS-A and later over-expressing HA-CSA, and this comparison is used extensively for phenotype description in the manuscript. In isn't clear to me that this is the most insightful comparison to make; the rescue by overexpression is not as elegant as CRISPR reversion and the ko fibroblasts have presumably been surviving well in culture without CS-A before this protein was overexpressed. Can you validate the differential expression of any identified proteins in the acute HAP1 ko? Can you validate any of the differentially expressed proteins in comparison to normal fibroblasts (e.g., 13O6, as per Qiang et al., 2021)?
Minor comments
- Pag 14: "To characterize the NE phenotypes further, we obtained CS patient-derived cell lines carrying loss-of-function mutations in CSA (CS-A cells) or CSB (CS-B cells), and their respective isogenic control cell lines (WT(HACSA) and WT(HA-GFP-CSB))." What type of loss-of-function? Is the mutant protein still produced? In Fig 6A there seem to be a band in the CS-A blot (second lane), but in Fig 1B, there isn't. I think this is important to know to interpret the phenotype related to LEM2 interaction.
- Figure 1B is poorly annotated. What do - and + stand for? In general, I find a bit confusing how the WB are presented throughout the manuscript, specifically how the antibodies are reported (e.g., HA-CSA instead of HA). Please mark up all western blots with antisera used. Please make sure all expected bands are within the crops - e.g., Fig 3B, the anti-LEM2 blot should be expanded vertically to show the LEM2-GFP relative to endogenous LEM2.
- From the methods, it appears that you obtained a LEM2-GFP, and cloned it into an expression vector (pEGFPC1) to make GFP-LEM2. Please provide clarity on which construct was used in which figure, and verify that an N-terminally tagged LEM2 still localises to the NE.
- Fig 1I: there is some text on top of the upper panels (DAPI, cGAS, Merge).
- "Through gene ontology analysis, we found that genes involved in endoplasmic reticulum (ER) stress were differentially expressed (Figure 4B)". I don't think that the way data are shown in Fig 4B is effective. Since GO has been performed, I would replace the table with a GO enrichment analysis graph. Ensure to report all the data in a supplementary .xls so that others can see and reuse it. Is there a mandated repository that accepts RNAseq data?
- The volcano plot looks weird with many values at the maximum log10 (P-value) - is the data processed appropriately?
- Figure 5B: the legend says "Latrunculin A". Please correct.
- For a Wellcome funded researcher, I'm surprised that the mandated OA statement and RRS is absent from the acknowledgements.
Referees cross-commenting
I think the other reviews are fair and accurate
Significance
This work provides interesting insights on a possible new moonlighting role of the CSA protein. This could enhance the pathophysiological comprehension of some clinical manifestations in CS patients. The nuclear envelope defects are well described and convincing; however, there is no clear understanding of how (or even if) the reported cytoskeleton and nuclear envelope defects depend on CSA. Better characterising mechanistic roles of CSA in both nuclear envelope integrity and in stress fibre formation will boost the overall impact of the manuscript. At this stage, the manuscript could be of interest for a specialised audience (premature ageing syndromes) but with more mechanistical dissection it could become of broader interest (basic research, nuclear architecture/integrity readership).
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Referee #2
Evidence, reproducibility and clarity
The manuscript by Yang et al. shows that ERCC8 (Cockayne syndrome A protein) mutations/loss of function causes nuclear envelope (NE) abnormalities and fragility, in addition to the well described deficiencies in transcription-coupled nucleotide excision repair (TC-NER). Cells from CS-A patients show decreased LEMD2-lamin A/C complexes at the NE and increased actin stress fibers that cause mechanical stress in the NE, in addition to more blebbing and ruptures of NE. This is turn causes activation of the innate/immune cGAS/STING pathway. Importantly, disrupting the LINC complex rescued NE problems and activation of the cGAS/STING pathway. This effect of ERCC8 dysfunction on NE integrity and activation of the cGAS/STING pathway may be behind patients' phenotypes of neuroinflammation, but not UV sensitivity.
The paper is well-written and for the most part, the data support the conclusions of the authors. Some minor caveats could be addressed to improve the quality of the manuscript.
- The phenotype of decreased LEMD2 incorporation into the NE in CS-A cells is minor. Only ~20% and thus, it is not clear whether this is causal of any of the NE abnormalities. It should be better explained how these data add to the story.
- Inducing actin polymerization and depolarization impact nuclear morphological abnormalities and nuclear blebbing. Do these treatments impact nuclear fragility and cGAS accumulation at NE break sites?
- Depletion of SUN1 in CS-A cells increased nuclear circularity, decreased blebbing, and phosphorylation of TBK1. The impact of SUN1 depletion in cGAS foci formation at NE break sites and phosphorylation of STING is not shown. Such experiments will provide stronger evidence that CS-A activates the cGAS-STING pathway in a SUN1 (mechanical stress)-dependent manner.
Referees cross-commenting
I am more positive than the other reviewers. I agree with reviewer 1 that another patient line would be great, and that some of the westerns need improvement. However, I still find that the phenotypes found in this cell line, which are rescued by the wild-type protein, are interesting and worth reporting. I do not fully agree with technical recommendations from reviewer 3, or suggesting that that the authors address questions outside the focus of their study.
Significance
The significance of the study is that shows for the first time the nuclear envelop defects and fragility in cells from Cockayne Syndrome patients (mutations in ERCC8) are due to mechanical stress that is alleviated by depletion of the LINC complex. In addition, the study shows activation of the cGAS-STING pathway in these cells, although the evidence about this phenotype could be strengthen.
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Referee #1
Evidence, reproducibility and clarity
Summary:
Cockayne syndrome (CS), an autosomal recessive premature ageing/progeria disease, is caused by mutations in the genes coding for CSA and CSB. These play a well-studied role in transcription-coupled nucleotide excision repair. In this manuscript, CSA but not CSB dysfunction is associated with nuclear envelope defects, a typical phenotype of cells from progeria diseases caused by mutations in NE proteins. HPA model cells lacking CSA show an irregular nuclear envelope not observed in cells lacking CSB. Patient cells with defective CSA, compared to isogenic cells expressing the wild-type CSA protein, show more severe nuclear envelope deformation and blebbing and activation of the cGAS/STING signaling pathway, indicating nuclear envelope damage, a slight reduction in the expression of LEM2, a protein of the inner nuclear membrane, and a reduced interaction of LEM2 with the lamina component lamin A/C. Patient cells with defective CSA show aberrant acThe proposed link between CSA and nuclear envelope integrity is interesting. CSA would in this case a factor involved in DNA repair as well as nuclear envelope integrity, two processes linked to progeria. However, the work relies on a single patient derived cell line which is compared to the same cell line expressing the wild type protein. To consolidate, more cells form different CSA patients need to be included. If worked out this idea will be interesting all cell biologists interested in DAN damage repair and nuclear envelope structure and function as well as researchers interested in the molecular mechanisms of progeria syndromes. My expertise: nuclear envelope structure and function, nuclear transport tin stress fiber and their nuclei show different effects toward actin polymerization inhibitors or stabilizers. Downregulation of SUN1, one of the nuclear envelope proteins linking to the cytoskeleton, improves nuclear envelope blebbing phenotypes in CSA patient cells
Major comments:
Albeit the link between CSA and NE integrity the work is in my eyes too preliminary. Although the data presented are well done and carefully evaluated they mostly (except Fig 1A) rely on direct comparisons of one patient cell line (CS-A or CS-B) to the same cells expression the wildtype protein. It remains thus open whether the effects seen on LEM2 expression, LEM2-LaimA/C interaction, stress fibre formation, cGAS/STING signaling pathway activation in the CS-A cells are representative for a number of different CS patient derived cells. This is especially important given the small changes observed. Please note that there are alos clear differences between the CSA-wt and CSB-wt cells. Would the HPA CSA KO cells show in addition to NE irregularities (not even quantified) the same phenotypes and can they be reverted by re-expression of the wildtype CSA protein? The link between CSA and SUN1 is not well worked out. What is the effect of SUN2 downregulation and that of nespirins? It remains unclear whether the observed effects are indeed LINC mediated.
Minor comments:
Fig 1B: Why is HA-Tagged CSA not shown on the CSA western? This would be helpful to compare to the endogenous levels at least in CSB cells. A western showing an housekeeping marker would allow better comparison. Judging from the proteins markers HA-tagged CSA seems much larger as endogenous CSA (first versus second row). Again, less cropped western blots would help.
Fig 3A: Is CSA FLAG or HA-tagged? Or both? If both are expressed the question raises of why the CSA-LEM 2 interaction is only seen in an overexpression situation.
Fig 5: Inconsistency between figure and figure legend: 20 vs 25 nM Jasplakinolide. I assume Latrunculin A should read Cytochalasin D?
Fig5B: Not clear why in "CSA-wT cells" Cytochalasin D and Jasplakinolide have the same effect on nuclear envelope shape yet only Jasplakinolide increases the number of blebs.
Page 10: Method for IF: 4% (v/v) paraformaldehyde and 2% /v/v) should likely read (w/v).
Page 19: replace "withl" by "with".
Significance
The proposed link between CSA and nuclear envelope integrity is interesting. CSA would in this case a factor involved in DNA repair as well as nuclear envelope integrity, two processes linked to progeria. However, the work relies on a single patient derived cell line which is compared to the same cell line expressing the wild type protein. To consolidate, more cells form different CSA patients need to be included. If worked out this idea will be interesting all cell biologists interested in DAN damage repair and nuclear envelope structure and function as well as researchers interested in the molecular mechanisms of progeria syndromes.
My expertise: nuclear envelope structure and function, nuclear transport
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Reply to the reviewers
The authors do not wish to provide a response at this time.
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Referee #3
Evidence, reproducibility and clarity
The authors conducted a comprehensive investigation into the spatial and temporal expression patterns of Pcdh10 during brain development and employed two deficient mouse models to delve into its neurobehavioral functions, with a specific emphasis on ultrasonic vocalizations (USV). Interestingly, the authors found that heterozygous cKO pups showed an exaggerated effect on USV as compared to the ubiquitous heterozygous KO pups. These observations in general agree with previous studies of Pcdh10's complicated function in ASD-related neurodevelopment, as well as USV, indicating its important function in neurodevelopment. However, several key concerns warrant attention:
Major comments:
- The authors analyzed published scRNAseq adult mouse dataset and found that Pcdh10-expressing cells differentially expressed genes involved in vocalization behaviors, including Foxp2, Cntnap2, Nrxn1 and Nrxn3, as compared to cells that did not express Pcdh10. Given that the authors also performed bulk RNA-seq experiments using the sorted cKO cells, it would be interesting and important to include these data in the analysis and validate whether the above genes are differentially expressed in the animal model in the current study. This may provide additional molecular mechanisms of the behavioral abnormality observed in the animal models.
- In Figure 1S, the synapse assembly is one of the most significant GO-terms. Does Pcdh10 deficiency affect neuromophology and synaptic density/assembly? Characterizing the neuroanatomy of the animal model will provide a neuronal explanation for the behavioral abnormalities observed in this study.
- Could the authors explain why cHE mice display a stronger phenotype than cKO at P6? Also, why cHE and cKO show stronger phenotypes than whole-body KO? Does this data indicate that loss of Pcdh10 in the inhibitory neurons only resulted in E-I in-balance? The authors should at least discuss the possibilities of this result they observed.
Minor comments:
- It would be interesting and important to know the level of PCDH10 at the adult stage after P7 to learn whether this gene also plays an important role beyond early development.
- Besides USV, does Pchd10 deficiency in mice show other autistic phenotypes in adolescence and adulthood, such as social interaction and repetitive behavior?
Significance
The experiments are well designed and the detailed characterization of USV in the animal models would be informative for the audience who are interested in Pcdh10's function in neurodevelopment and Social Communication. However, because previous studies already showed the function of PCDH10 in multiple mouse models, the novelty of this study is limited. The observation that cKO/cHE mice show stronger phenotype than whole-body KO mice could be potentially interesting, it would be nice if the authors could provide some explanation of this result with additional experimental evidence.
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Referee #2
Evidence, reproducibility and clarity
Summary
In this paper the authors present a new cKO mouse model for PCDH10-related ASD. This model consists of the ablation of PCDH10 specifically in interneurons of the basolateral complex. Interestingly, the use of this mouse model together with a complete KO adds evidence towards an excitatory/inhibitory imbalance causing the ASD phenotype, rather than the complete ablation of a protein (in this case PCDH10). Firstly, the developmental dynamics of PCDH10 are measured with diverse techniques. The presence of PCDH10 at embryonic stages in different areas of the basal forebrain. Here it is made clear why the specific downregulation of PCDH10 in Gsh2- lineage interneurons. The cKO mouse model is validated with bulk RNA sequencing fluorescence imaging of the eGFP reporter in the telencephalon. The KO mouse model is validated with WB assay showing the gradual decrease of PCDH10 in Het and Ho mice. Secondly, the USV emitted by isolated pups throughout development (P3, P6, P9 and P12) are analysed with different parameters in both mouse models.
Major Comments
- The role of anxiety in the phenotype described in this work should be supported by behavioural experiments in adulthood (Open field/light/dark/Plus Maze test)2-3M for mice to reach the appropriate age + 2 weeks for performing the experiments and extracting results.
- The WB in panel F1C&E should be done with non-pooled biological replicates to be informative 3 weeks
- The statistical test used for F2B and F3D-I needs to be specified.
- The reduced GABA input in the amygdala that is hypothesized to be causing the phenotype could be studied by iPSP analysis through LFP (OPTIONAL) 1M
Minor comments
- The results section should be subdivided in sections corresponding to each figure
- Detail the pinhole opening in M&M used for the imaging of the images in panel of Figure 1 M-R
- The group size and the power calculation used to determine it should be detailed in M&M
- The WB membrane image in Panel 1F has saturated pixels, the image needs to be changed
- Instead of asterisks, writing the exact p-value is more informative in the graphs
- Figure 1B & D: detail what the Pcdh10 levels are normalised to. In the legend there's a typo "no-way ANOVA"
- Figure 1F: specify what it means P17.5 (norm)
- Figures 3-4: choose higher contrast colours for an easier readability and more accessibility.
- Figure 3B: the WB image needs to be at a higher resolution
- Figure 3C: the colour coding for dBFS in the spectrogram needs to be specified in the maximum and minimum number.
- Figure 3D-I & 6G: results would be more clear if shown as a ratio of the WT (would be also more evident the mouse model differences). Also the titles of the graphs are misleading, as the graphs are showing data from all the genotypes of the mouse models.
- Figure 2B: specify what it is normalised to
- Figure 4 E-H: it is not described what the dotted lines correspond to.
- In all the figures, the panels are excessively subdivided, the following panels should be grouped in one:
- a. Figure 1: i. C & E are showing the same data
ii. G-I are showing the same data
iii. J-L are showing the same data
iv. M-R are showing the same data - b. Figure 2: panel 2C-G are showing the same data - c. Figure 3: i. A-B are showing the same data
ii. D-I are showing the same data - d. Figure 4: i. A-C are showing the same data
ii. E-H are showing the same data - e. Figure 5: the frequency parameters (A-E) should be all 1 panel f. Figure 6: B-E are showing the same data
Significance
The detailed study of the socio-affective communication of these mouse models is accurate and quite informative. There is still a big body of work to do for classifying and using pup USV as biomarkers for mouse model phenotyping, and this thorough work is a step forward. This type of work will be of interest to neurodevelopmental neuroscientists interested in behaviour and mouse model phenotyping. However, the claim of an autistic-like phenotype would be much stronger with additional behavioural assessments in adulthood (as USV in mating behaviour, social novelty recognition and stereotypical behaviours). In addition, the hypothesis of an excitation/inhibition imbalance is interesting, but correlational in this work. Further experiments would need to be done to prove causality.
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Referee #1
Evidence, reproducibility and clarity
This paper provides evidence that Pcdh10 (associated with autism spectrum disorder) is involved in anxiety-like behavior and socio-affective communication in developing mouse pups. Using a specific Cre-driver line targeting Gsh2-lineage interneurons, the authors performed a series of behavioral analyses, including isolation-induced ultrasonic vocalization. Particularly, the authors provided detailed analyses to provide distinct clusters that might correspond to identified call types. This work is excellent and I do not have any further comments, except one minor comment: why did the authors use CD1 line to generate the mouse lines, instead of C57BL/6 substrains?
Significance
This is of paramount significance, such that Pcdh10 expressed in Gsh2-lineage interneurons (a subpopulation in the basolateral complex of the amygdala) is required for isolation-induced ultrasonic vocalization.
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General Statements
We thank the reviewers for their constructive feedback on our study. We have updated the manuscript according to their recommendations.
Two of the three reviewers raised concerns about the quality of some of our data, in particular of the DP population. Since most DP samples suffered from low coverage, introducing bias when being compared to the higher quality data, we moved all results involving DP to the Supplement. We mention this in the Discussion. The main text and its figures were updated to focus on the remaining three wild populations and two laboratory strains.
We rewrote parts of the Abstract, Introduction and Discussion to clarify the comparison between the NLR families of Arabidopsis thaliana and Danio rerio. In regard to this, we also added an extra panel to figure 3.
Reply to the reviewers
Reviewer #1 (Evidence, reproducibility and clarity):
General comments:<br /> 1) Odd statement in abstract comparing plants to fishes - why not put in context of animals in general, or vertebrates in particular? Same in the introduction and discussion. Either a more broad comparative framework should be set - from plants, through invertebrates to vertebrates, or it should be shortened and perhaps discussed in the light of diversity present in e.g., fish or just vertebrates. A persistent focus on plants is peculiar and does not seem to provide adequate background/context._
We have made an effort to clarify the reason for mentioning NLRs from A. thaliana in the Abstract, Introduction and Discussion. We added a plot to figure 3, which is analogous to figure 3A from Van de Weyer et al., 2019 where the pan-NLRome of A. thaliana is analysed.
Furthermore, we added a paragraph discussing copy number variation of another immune gene family (MHC genes) in vertebrates.
2) Methods seem overall well described, and the analyses seem to have been performed diligently-although I am not an expert in the field. One aspect that would be important to evaluate methodology is the repeatability of NLR detection - If we perform the procedure twice on DNA sample from a single individual, how repeatable collection do we get?
It is possible that we might have failed to identify a few NLRs from some individuals. Unfortunately, sequencing could not be repeated due to the limited amount of raw tissue. The population DP in particular is problematic since we had low sequencing depths across all of its samples. We have now excluded it from the main results and moved it to the Supplement. Still, we are confident that the general feature of widespread copy number variation both within and between populations persists even if the experiments were repeated. One argument for this is that the non-linear functions describing pan-NLRome sizes are fairly consistent among wild populations. Also, sample sizes of about 20 individuals per (wild) population are large enough to compensate for poor data quality of one or two indviduals. Finally, we found a substantial fraction of NLRs to be present in all wild populations, including DP. It would be unlikely to detect so many shared genes if the amplified sequences were spurious or the NLR identification procedure faulty.
We have expanded the discussion of the caveats of our approach.
3) Discussion is quite speculative, and some claims seem exaggerated; in conclusions, eg: "This study advances our understanding of the evolutionary dynamics affecting very large gene families." - as the study is mostly descriptive documentation od CNV of gene (or, gene fragments) I am not convinces how it really advances "understanding of the evolutionary dynamics".
We toned down Discussion and Conclusions.
Minor points:
At this stage the journal and so the audience is unknown, so perhaps this will not be an issue - but for a broader audience, a better explanation of what PRY/SPRY/B30.2 are would be useful._
We added an explanation.
English could be smoothed, certain sentences sound odd: eg. lines 87-89; or 90-93 - Studies have shown that viral and bacterial infections can induce the expression of specific fish NLRs (reviewed in (24)). Some have PYD or CARD domains and can even form inflammasomes similar to mammalian NLRs (25, 26). - could be read as if infections had PYD or CARD domains, not NLRs. Lines 239-240 - not sure what does "presence/absence variation" mean here.
We made an effort to improve language style.
Sequence of baits used should be provided in some supplement or repository.
The sequences are now attached to the manuscript as a supplementary dataset.
Reviewer #1 (Significance):
The article tackles an overall interesting subject: an expansion of a relevant group of genes in one of the major model species of biomedical importance. The main strength of the study is putting in context variation found in the lab strains - via comparison to wild populations. A limited and "haphazard" genetic variation (especially of genes involved in immune processes) of laboratory models can have paramount implications for the interpretation of experimental studies._
We expand on this in the Discussion._
That being said, expansion of NLR family in teleosts in general, and in zebrafish in particular, has been previously described (eg, https://bmcecolevol.biomedcentral.com/articles/10.1186/1471-2148-8-42_), and this study mainly expands description of this phenomena.
The expansion of NLRs has indeed been described before and in great detail. The manuscript contains multiple references on this topic, including the one recommended by the reviewer (e.g. Stein et al., 2007, Laing et al., 2008, Howe et al., 2016). The previously reported expansion of NLRs in the reference genome was a description, but not an interpretation "in the light of evolution". We demonstrate that gene birth, death, and presence/absence variation are ongoing processes and active on a population-genetic time scale.
Given the methodology, little can be said about possible functions of the discovered diversity. In particular, a technical aspect imposing limitation of sequence length resulted in a collection of exons, but not full genes - precluding e.g., deepened analysis of domain architecture.
We agree that our study does not reveal much about the function of the NLR-C genes. The focus on function in the discussion was disproportionate to our findings and we have reduced it to avoid speculation.
Selection analysis is also quite limited in scope; there are several, more sophisticated tools to infer balancing or purifying selection, either pervasive or episodic (see eg. excellent tools of_ https://www.datamonkey.org__/_).
Yes. However, with our limited amount of data, we deliberately do not want to speculate too much about selection. As mentioned in the text, many genes are monomorphic in our sample. To reliably infer the action of selection, and more so to distinguish it from signatures of demographic history, a much broader basis of sequence data is needed.
Nonetheless, the study certainly highlights the possible importance of such an expanded group of genes in this species, with a potential to inspire further - more mechanistic/functional research in this area. The article will likely interest a few groups of rather specialized audience - e.g., those working in NLR genes in particular, or in immunity of zebrafish (or fish in general). Another, somewhat broader angle, able to attract a wider audience would be subjects of general evolution of multigenic families (birth-and-death models, trade-offs at different CNV etc.) and comparative analysis to other groups of animals - or genes - evolving in a similar way. My field of expertise is diversity and evolution of adaptive branch of the immune system in vertebrates, in particular non-model vertebrates.
Reviewer #2 (Evidence, reproducibility and clarity):
Summary:
The authors have examined the variation of the immune related gene family "Nucleotide-binding domain Leucine-rich Repeat containing" (NLR) in the zebrafish Danio rerio. These proteins, while highly divergent, are conserved across animal and plant species. In humans or rodents, the number of these genes is relatively small (20-30) but other species such as Arabidopsis appear to have >10,000 NLR genes.<br /> Schäfer et al. collected 67 wild-type zebrafish from 4 independent sites near the Bay of Bengal and added 8 fish each from the laboratory strains Tübingen (TU) and Cologne (CGN). Using DNA capture and sequencing technology, they identified 1,560 unique "FISNA-NACHT" domains representing different NLR genes and 574 NLR-associated B30.2 domains. A subset, 714 and 229 respectively, were identified in all of the fish populations representing a "core" set common NLR genes. A significant subset of the genes could not be aligned to the GRCz11 reference suggesting significant variation across subpopulations of zebrafish.
Major comments:<br /> None. The work is straight-forward, carefully done and conservatively interpreted.
Minor comments:<br /> GRCz11 is still a very fragmented assembly, particularly chr4 where heterochromatin repeats on the long arm were intractable to short read sequences. There is a more recent assembly generated by the Tree of Life initiative (GCA_944039275.1) from the SAT fish line that may allow a more robust alignment and placement of the NLR genes, perhaps even some phasing of unassembled fragments._
We have examined some of the existing long-read based zebrafish assemblies and found that even the length of chromosome 4 that contains most of the NLRs can significantly differ between different strains and different genome assemblies. This is also in agreement with the recent findings of McConnell et al., 2023 on large structural differences on this chromosome between three strains derived from the AB genetic background. We now mention this finding and the alternative existing zebrafish assemblies in the Discussion.
Reviewer #2 (Significance):
General assessment:<br /> Obtaining more data on the inherent variation within species of NLR genes as well as collecting more cross-species data for evolutionary comparisons is valuable for our understanding of this interesting but poorly understood class of immune response genes as well as the dynamics of gene duplication/deletion in complex, repeated arrays.<br /> -The major strength of the study is the efforts put into capturing wild-type zebrafish from multiple different locations to maximize the diversity of the NLR sequences.<br /> -The primary limitation is targeted capture is always contingent on having enough homology in the probes to capture all the desired genes in roughly even proportions. Some of the more interesting NLR genes might have diverged too much to be properly captured but could provide critical information on evolutionary functional adaptation. Similarly, while based on cost, it is understandable why sequence capture was chosen, but phasing information across clusters could help explain (or discover) very diverse haplotype sequences in the introns of many of these gene arrays. As sequencing costs drop, this is an important aspect to the evolution of zebrafish chromosome 4 (as well as the rest of the genome). "Pangenome" differences in the zebrafish genome might be quite radically different.
Yes, we are aware of this possibility and discussed it now in more detail._
Advance:<br /> The study represents an important characterization of a poorly understood but important class of immune genes. A very similar (but more detailed) characterization of Arabidopsis NLR genes by Van de Weyer et al., Cell 2019, is considered an important advance to the plant biology community and has been highly cited since its publication. The collected data is potentially quite useful for future studies that want to understand the complex dynamics of highly repetitive, yet functional regions of the genome and how it can result in the creation and extinction of new genes.
Audience:<br /> There are two main likely audiences, those interested in how NLR genes are involved immune protection and those interested in genomes and evolution. It probably doesn't reveal a fundamental biological principle that would be of broad, general interest to the research community.
Reviewer #3 (Evidence, reproducibility and clarity):
Summary:<br /> The authors performed exon capture sequencing of FISNACHT and B30.2 domains from individuals among various inbred and wild zebrafish populations. This study provides average numbers of domains per fish and thus a valuable estimate for the size of the pan-NLRome in zebrafish.
Major comments:<br /> - Are the key conclusions convincing?_ Yes, and overall their findings are also consistent with what has been found in other model systems, most notably Arabidopsis (Weyer 2019, https://www.cell.com/cell/fulltext/S0092-8674(19)30837-2).<br /> - Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether?<br /> 'Complex patterns of inheritance' is unclear from significance statement.
We have reformulated this sentence.
For mechanisms driving copy number differences, haplotypes/segregation need not be presented as a model opposed to birth and death gene evolution/tandem duplication. These may both operate at different scales.
Yes, we reformulated.
- Are the data and the methods presented in such a way that they can be reproduced?<br /> Yes, overall, though the authors could provide sequences for their adapters, similar to Weyer 2019. It seems that raw data for this study is not yet available in NCBI: https://www.ncbi.nlm.nih.gov/bioproject/966920
The data will be made available at the time of publication. The sequences for all baits used, including non-NLR-ones, have been added as a supplementary .fasta-formatted text file.
Minor comments:<br /> - Specific experimental issues that are easily addressable.<br /> Their targeted exon capture approach cannot ensure that all NLR genes will be sequenced. This method also does not sequence across other exons from NLR genes, providing only a partial view of NLR gene structure and evolution. This may miss for example additional integrated domain architectures or evidence of physical clustering in the genome (Thatcher 2023, https://bsppjournals.onlinelibrary.wiley.com/doi/10.1111/mpp.13319). Nevertheless, focusing on capturing and enumerating FISNACHT domains as the most conserved and characteristic domain for NLRs appears to be a reasonable approach for estimating rough copy numbers.
We agree with the reviewer and have now added explanatory text on this topic to the discussion.
Unfortunately, mapping these domains back to only a single reference genome also means that the accuracy of their predictions for these domains, including which belong to genes or pseudogenes, is likely to be more error-prone (Wang 2019,https://www.pnas.org/doi/10.1073/pnas.1910229116), particularly for more divergent sequences. This may lead to additional limitations for assigning one-to-one relationships between FISNACHT domains, which they measure, and genes, which they seek to enumerate.
Thank you for pointing out the above reference. This is a limitation that we realized early on in the study after which we decided to not rely on the reference genome at all, instead opting to assemble and cluster all data de novo. In the manuscript we only use the reference genome for checking which of our identified NLRs have a clear homologue to satisfy potential interest by the biomedical community. All the other analyses were conducted based on the de novo assemblies and orthologous clusters._
In addition, many of their samples appear to be of poor DNA quality, meaning that
modeling estimates of domain copy number for the population can appear erroneous, even perhaps off by as much as a factor of 10 for the DP strain. This may contribute to some curious 'artifact' in some of the figures, such as Figs S2B1, S3B, S4C2, particularly for the B30.2 sequences in DP. The authors mention 'low sequencing depths' and 'low coverage' as contributing factors for this 'artifact' but also invoke possible 'evolutionary factors' in the discussion. Additional discussion for the apparent experimentally-induced effects on underestimating B30.2 sequences (perhaps due to increased DNA fragmentation and smaller domain size?), rather than coincidence of low coverage and actual biological strain-specific loss of B30.2 domains, appears warranted.
As mentioned in the text, although samples from the population CHT were older than the others and slightly degraded, they were rescued by applying the PreCR Repair Mix from New England Biolabs. We incorporated incubation with the reagent to the standard protocol that we used for all samples. The other samples had no quality problem.
Furthermore, the reviewer raises concerns regarding data quality for the DP population samples. After careful consideration, we decided to exclude the DP data and its analysis from the main text and deferred it to the supplementary material with the necessary remarks of caution. The main text now focuses on the other three wild populations, which did not have those issues.
Additionally, as per the reviewer’s suggestion, we discuss the additional caveats of bait-based targeted sequencing, especially for B30.2 domains._
- Do you have suggestions that would help the authors improve the presentation of their data and conclusions?<br /> Statement in the abstract about fewer (not 'less') NLRs in lab strains vs wild: consider revising to average # NLRs per individual._
We changed the respective sentence in the abstract.
Revise Fig 3C legend: 'Totally discovered NLR genes', e.g., to 'total # NLR genes'.
The recommended change was made to the figure legend.
Reviewer #3 (Significance):
- Describe the nature and significance of the advance (e.g. conceptual, technical, clinical) for the field.<br /> This study elucidates the pan-NLRome of zebrafish via application of a somewhat new technique.
-
Place the work in the context of the existing literature (provide references, where appropriate).<br /> The authors apply a targeted capture and long read technology previously used in plants (Weyer 2019) to fish, thereby elucidating the pan-NLRome of zebrafish, a vertebrate with a large # of NLR genes. Previous studies has shown NLR gene variation in zebrafish, but had not compared levels within and between strains, or estimated a total NLR # across populations._
-
State what audience might be interested in and influenced by the reported findings.<br /> Those interested in immune function, genetic diversity and genome evolution.
- 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.<br /> Immune genes and evolution. The specific statistical approach_
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Referee #3
Evidence, reproducibility and clarity
Summary:
The authors performed exon capture sequencing of FISNACHT and B30.2 domains from individuals among various inbred and wild zebrafish populations. This study provides average numbers of domains per fish and thus a valuable estimate for the size of the pan-NLRome in zebrafish.
Major comments:
- Are the key conclusions convincing?
Yes, and overall their findings are also consistent with what has been found in other model systems, most notably Arabidopsis (Weyer 2019, https://www.cell.com/cell/fulltext/S0092-8674(19)30837-2).<br /> - Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether?
'Complex patterns of inheritance' is unclear from significance statement.
For mechanisms driving copy number differences, haplotypes/segregation need not be presented as a model opposed to birth and death gene evolution/tandem duplication. These may both operate at different scales.<br /> - Would additional experiments be essential to support the claims of the paper? Request additional experiments only where necessary for the paper as it is, and do not ask authors to open new lines of experimentation.
Not necessary<br /> - Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated cost and time investment for substantial experiments.
NA<br /> - Are the data and the methods presented in such a way that they can be reproduced?
Yes, overall, though the authors could provide sequences for their adapters, similar to Weyer 2019. It seems that raw data for this study is not yet available in NCBI: https://www.ncbi.nlm.nih.gov/bioproject/966920<br /> - Are the experiments adequately replicated and statistical analysis adequate?
Yes
Minor comments:
- Specific experimental issues that are easily addressable.
Their targeted exon capture approach cannot ensure that all NLR genes will be sequenced. This method also does not sequence across other exons from NLR genes, providing only a partial view of NLR gene structure and evolution. This may miss for example additional integrated domain architectures or evidence of physical clustering in the genome (Thatcher 2023, https://bsppjournals.onlinelibrary.wiley.com/doi/10.1111/mpp.13319). Nevertheless, focusing on capturing and enumerating FISNACHT domains as the most conserved and characteristic domain for NLRs appears to be a reasonable approach for estimating rough copy numbers.
Unfortunately, mapping these domains back to only a single reference genome also means that the accuracy of their predictions for these domains, including which belong to genes or pseudogenes, is likely to be more error-prone (Wang 2019, https://www.pnas.org/doi/10.1073/pnas.1910229116), particularly for more divergent sequences. This may lead to additional limitations for assigning one-to-one relationships between FISNACHT domains, which they measure, and genes, which they seek to enumerate.
In addition, many of their samples appear to be of poor DNA quality, meaning that modeling estimates of domain copy number for the population can appear erroneous, even perhaps off by as much as a factor of 10 for the DP strain. This may contribute to some curious 'artifact' in some of the figures, such as Figs S2B1, S3B, S4C2, particularly for the B30.2 sequences in DP. The authors mention 'low sequencing depths' and 'low coverage' as contributing factors for this 'artifact' but also invoke possible 'evolutionary factors' in the discussion. Additional discussion for the apparent experimentally-induced effects on underestimating B30.2 sequences (perhaps due to increased DNA fragmentation and smaller domain size?), rather than coincidence of low coverage and actual biological strain-specific loss of B30.2 domains, appears warranted.<br /> - Are prior studies referenced appropriately?
yes<br /> - Are the text and figures clear and accurate?
yes<br /> - Do you have suggestions that would help the authors improve the presentation of their data and conclusions?
Statement in the abstract about fewer (not 'less') NLRs in lab strains vs wild: consider revising to average # NLRs per individual.
Revise Fig 3C legend: 'Totally discovered NLR genes', e.g., to 'total # NLR genes'.
Significance
- Describe the nature and significance of the advance (e.g. conceptual, technical, clinical) for the field.
This study elucidates the pan-NLRome of zebrafish via application of a somewhat new technique.<br /> - Place the work in the context of the existing literature (provide references, where appropriate).
The authors apply a targeted capture and long read technology previously used in plants (Weyer 2019) to fish, thereby elucidating the pan-NLRome of zebrafish, a vertebrate with a large # of NLR genes. Previous studies has shown NLR gene variation in zebrafish, but had not compared levels within and between strains, or estimated a total NLR # across populations.<br /> - State what audience might be interested in and influenced by the reported findings.
Those interested in immune function, genetic diversity and genome evolution.<br /> - 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.
Immune genes and evolution. The specific statistical approach
-
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Referee #2
Evidence, reproducibility and clarity
Summary:
The authors have examined the variation of the immune related gene family "Nucleotide-binding domain Leucine-rich Repeat containing" (NLR) in the zebrafish Danio rerio. These proteins, while highly divergent, are conserved across animal and plant species. In humans or rodents, the number of these genes is relatively small (20-30) but other species such as Arabidopsis appear to have >10,000 NLR genes.<br /> Schäfer et al. collected 67 wild-type zebrafish from 4 independent sites near the Bay of Bengal and added 8 fish each from the laboratory strains Tübingen (TU) and Cologne (CGN). Using DNA capture and sequencing technology, they identified 1,560 unique "FISNA-NACHT" domains representing different NLR genes and 574 NLR-associated B30.2 domains. A subset, 714 and 229 respectively, were identified in all of the fish populations representing a "core" set common NLR genes. A significant subset of the genes could not be aligned to the GRCz11 reference suggesting significant variation across subpopulations of zebrafish.
Major comments:
None. The work is straight-forward, carefully done and conservatively interpreted.
Minor comments:
GRCz11 is still a very fragmented assembly, particularly chr4 where heterochromatin repeats on the long arm were intractable to short read sequences. There is a more recent assembly generated by the Tree of Life initiative (GCA_944039275.1) from the SAT fish line that may allow a more robust alignment and placement of the NLR genes, perhaps even some phasing of unassembled fragments.
Significance
General assessment:
Obtaining more data on the inherent variation within species of NLR genes as well as collecting more cross-species data for evolutionary comparisons is valuable for our understanding of this interesting but poorly understood class of immune response genes as well as the dynamics of gene duplication/deletion in complex, repeated arrays.
- The major strength of the study is the efforts put into capturing wild-type zebrafish from multiple different locations to maximize the diversity of the NLR sequences.
- The primary limitation is targeted capture is always contingent on having enough homology in the probes to capture all the desired genes in roughly even proportions. Some of the more interesting NLR genes might have diverged too much to be properly captured but could provide critical information on evolutionary functional adaptation. Similarly, while based on cost, it is understandable why sequence capture was chosen, but phasing information across clusters could help explain (or discover) very diverse haplotype sequences in the introns of many of these gene arrays. As sequencing costs drop, this is an important aspect to the evolution of zebrafish chromosome 4 (as well as the rest of the genome). "Pangenome" differences in the zebrafish genome might be quite radically different.
Advance:
The study represents an important characterization of a poorly understood but important class of immune genes. A very similar (but more detailed) characterization of Arabidopsis NLR genes by Van de Weyer et al., Cell 2019, is considered an important advance to the plant biology community and has been highly cited since its publication. The collected data is potentially quite useful for future studies that want to understand the complex dynamics of highly repetitive, yet functional regions of the genome and how it can result in the creation and extinction of new genes.
Audience:
There are two main likely audiences, those interested in how NLR genes are involved immune protection and those interested in genomes and evolution. It probably doesn't reveal a fundamental biological principle that would be of broad, general interest to the research community.
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Referee #1
Evidence, reproducibility and clarity
Summary:
Study by Schäfer et al. investigates diversity of NLR family genes in zebrafish (Danio rerio). Genes belonging to this vast family are implicated in various defense/immune functions across studied domains of life, and form extensive families of often highly duplicated genes. Here, repertoire of NRL genes was studied in 93 individuals, coming from both laboratory strains and natural populations. Authors found a relevant, intra-specific copy number variation in the NLR genes in zebrafish, and a higher diversity of these genes in wild animals, compared to their laboratory counterparts.
General comments:
- Odd statement in abstract comparing plants to fishes - why not put in context of animals in general, or vertebrates in particular? Same in the introduction and discussion. Either a more broad comparative framework should be set - from plants, through invertebrates to vertebrates, or it should be shortened and perhaps discussed in the light of diversity present in e.g., fish or just vertebrates. A persistent focus on plants is peculiar and does not seem to provide adequate background/context.
- Methods seem overall well described, and the analyses seem to have been performed diligently-although I am not an expert in the field. One aspect that would be important to evaluate methodology is the repeatability of NLR detection - If we perform the procedure twice on DNA sample from a single individual, how repeatable collection do we get?
- Discussion is quite speculative, and some claims seem exaggerated; in conclusions, eg: "This study advances our understanding of the evolutionary dynamics affecting very large gene families." - as the study is mostly descriptive documentation od CNV of gene (or, gene fragments) I am not convinces how it really advances "understanding of the evolutionary dynamics".
Minor points:
At this stage the journal and so the audience is unknown, so perhaps this will not be an issue - but for a broader audience, a better explanation of what PRY/SPRY/B30.2 are would be useful.
English could be smoothed, certain sentences sound odd: eg. lines 87-89; or 90-93 - Studies have shown that viral and bacterial infections can induce the expression of specific fish NLRs (reviewed in (24)). Some have PYD or CARD domains and can even form inflammasomes similar to mammalian NLRs (25, 26). - could be read as if infections had PYD or CARD domains, not NLRs. Lines 239-240 - not sure what does "presence/absence variation" mean here.
Sequence of baits used should be provided in some supplement or repository.
Significance
The article tackles an overall interesting subject: an expansion of a relevant group of genes in one of the major model species of biomedical importance. The main strength of the study is putting in context variation found in the lab strains - via comparison to wild populations. A limited and "haphazard" genetic variation (especially of genes involved in immune processes) of laboratory models can have paramount implications for the interpretation of experimental studies.
That being said, expansion of NLR family in teleosts in general, and in zebrafish in particular, has been previously described (eg, https://bmcecolevol.biomedcentral.com/articles/10.1186/1471-2148-8-42), and this study mainly expands description of this phenomena. Given the methodology, little can be said about possible functions of the discovered diversity. In particular, a technical aspect imposing limitation of sequence length resulted in a collection of exons, but not full genes - precluding e.g., deepened analysis of domain architecture. Selection analysis is also quite limited in scope; there are several, more sophisticated tools to infer balancing or purifying selection, either pervasive or episodic (see eg. excellent tools of https://www.datamonkey.org/). Nonetheless, the study certainly highlights the possible importance of such an expanded group of genes in this species, with a potential to inspire further - more mechanistic/functional research in this area.
The article will likely interest a few groups of rather specialized audience - e.g., those working in NLR genes in particular, or in immunity of zebrafish (or fish in general). Another, somewhat broader angle, able to attract a wider audience would be subjects of general evolution of multigenic families (birth-and-death models, trade-offs at different CNV etc.) and comparative analysis to other groups of animals - or genes - evolving in a similar way.
My field of expertise is diversity and evolution of adaptive branch of the immune system in vertebrates, in particular non-model vertebrates.
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www.biorxiv.org www.biorxiv.org
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Reply to the reviewers
My response to the reviewers appears in the uploaded "Revision Plan" PDF file
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Referee #3
Evidence, reproducibility and clarity
This study by Chourasia et al determined the effects of MTCH2 deletion on the total metabolite content (polar and lipid metabolites) per total protein of HeLa cells, analyzed at different consecutive times after adding fresh and complete media (high glucose, 10%FBS). They also analyzed the effects of nutrient depletion (no FBS In addition, authors assessed the effects of MTCH2 deletion on mitochondrial morphology, lipid droplet number and size in HeLa cells, as well as in the differentiation of mouse fibroblasts to adipocytes. From the metabolite snaphots under htese differents times and conditions, authors conclude that MTCH2 deletion increases mitochondrial oxidative function to induce a catabolic state, which impedes lipid synthesis and, as a result, adipocyte differentiation. The major concerns are that it is unclear whether the metabolic phenotype observed is a consequence of MTCH2 deletion inducing a decrease in proliferation of HeLa, as well as of fibroblasts that need to reach confluence to differentiate. In this regard, it is also unclear whether MTCH2 deletion increases ATP demand and/or promotes a catabolic program, as metabolic flux analyses are missing. A minor concern is the use of computer (processing system), antenna and wifi analogies to describe the role of MTCH2 in mitochondrial function, which is confusing.
Significance
This study represents a thorough characterization of the metabolite content in proliferating HeLa cells in the absence of MTCH2 expression. The changes observed in polar and lipidic metabolites are novel, interesting and contribute to our understanding on the role of MTCH2 function in cellular metabolism. The main limitation of the study is that the levels of most metabolites are normalized by protein content, comparing conditions in which cell number and protein synthesis have changed. Thus, it is unclear whether some of the effects observed are a consequence of the reported role of MTCH2 supporting the proliferation of different tumors and cell lines, or whether it is a direct effect of MTCH2 increasing ATP demand and/or being a direct activator of mitochondrial catabolism. Related to this point, it is unclear whether the defect in adipocyte differentiation induced by MTCH2 KO in NIH3T3 fibroblasts might be caused by an inability of MTCH2 KO to reach confluency at day 0, needed for differentiation.Finally, respirometry and mitochondrial ROS content analyses would be needed to confirm that the changes in the metabolite levels induced by MTCH2 are caused by an increase in mitochondrial oxidation leading to nutrient depletion, as authors conclude. For example, an increase in the ADP/ATP ratio could also be caused by an inhibition of mitochondrial ATP synthase in the mitochondria, concurrent to an increase in ROS production, which would decrease NADH and NADPH content.
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Referee #2
Evidence, reproducibility and clarity
Mitochondrial carrier homolog 2 (MTCH2, SLC25A50) loss induces alterations in mitochondrial dynamics and energy utilization. However, the molecular mechanisms underlying these changes are still unknown. The study employs temporal metabolomic and lipidomic analyses, uncovering heightened catabolism, increased lipid storage, and disrupted adipogenesis in MTCH2 KO cells. The manuscript provides a comprehensive metabolic profile, revealing ATP demand increase, oxidized cellular environment, and adaptive changes in MTCH2 KO cells. Notably, in line with the fundamental role of fatty acid biosynthesis and anabolism in adipogenesis, the authors demonstrates that MTCH2 loss inhibits adipocyte differentiation. This work offers novel insights into the broader metabolic consequences of MTCH2 depletion.
Major comments:
- The key conclusions of the paper align with the conducted experiments, but a few additional experiments are necessary to state some claims and provide more robust conclusions.
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The paper could benefit from the inclusion of specific experiments, particularly those that address the following aspects:
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Validate MTCH2 ablation in HeLa and NIH3T3L1 through sequencing of clonal lines, Western blot analysis to confirm the absence of the protein, and real-time PCR to assess whether the mechanism involves mRNA decay.
- Provide a more detailed rationale for their temporal metabolomics approach, elucidating the choice of the media and the timepoints of cell collection. The method involves an initial culture of the cells in DMEM medium, followed by a switch to complete medium (CM) for overnight cell growth, and subsequent refreshment with CM for different timepoints before the metabolomics analyses. Authors should articulate the reasoning for opting for CM. Furthermore, authors should explicitly explain the rationale behind selecting specific timepoints for cell collection after the addition of the fresh medium.
- In Figure 1, authors conclude that MTCH2 ablation stimulates oxidative metabolism and ATP production to fulfill increased cellular ATP demands. However, this conclusion is based only on metabolomic analyses of the ADP/ATP ratio. To comprehensively assess the impact on cellular respiration, the authors should monitor the Oxygen Consumption Rate (OCR) and report the Respiratory Control Ratio (RCR).
- NAD+/NADH ratio: authors should measure NADH levels in both mitochondria and cytosol. This can be accomplished through NADH autofluorescence (recommended) or commercially available kits. This additional analysis would contribute to a more comprehensive interpretation of the observed changes in oxidative metabolism. They should also include measurement of mitochondrial membrane potential using TMRM. Suggested experiment: measuring NADH autofluorescence. The autofluorescence of mitochondrial NADH can be distinguished from cytosolic NADH by optimizing substrate consumption followed by the complete inhibition of electron feeding to the ETC. The redox state of NADH reflects the equilibrium between mitochondrial ETC activity and the rate of substrate supply. After acquiring basal autofluorescence levels through live imaging, max signal is obtained by stimulating maximal respiration (FCCP), and min signal is obtained by inhibiting respiration (NaCN or Rot+AA). Subsequently, "NADH redox indexes" are generated by expressing the basal NADH levels as a percentage of the difference between the oxidized and reduced signals. Furthermore, by examining the fluorescence signal increase after NaCN addition, the rate of NADH production can be monitored. This rate serves as a proxy of TCA efficiency.
- Authors observe a reduction in the levels of various amino acids and TCA cycle intermediates, indicative of an increased flux through the TCA cycle. This proposition could be further supported by measuring the kinetics of NADH autofluorescence. Additionally, a decrease in metabolites associated with the urea cycle, such as citrulline and ornithine, is observed, yet this observation remains uncommented and warrants discussion. Intriguingly, an elevation in Branched-Chain Amino Acids (BCAAs) and unsaturated acyl carnitines is noted, leading to the hypothesis of an increased transport and breakdown of fatty acids in the mitochondria to meet the heightened cellular demand for ATP in MTCH2 KO cells. To substantiate this, and to quantitatively measure mitochondrial fuel utilization in live cells, authors shall perform a Mitofuel Flex Test by measuring the Oxygen Consumption Rate (OCR) in cells treated with inhibitors of each mitochondrial oxidative pathway including etomoxir. This approach would enable the measurement of the dependency, capacity, and flexibility of cells concerning the pathway of interest in meeting ATP demand. It is also recommended to perform MitoStress test in cells supplemented with only one of the carbon sources (such as Glucose, Glutamine, Long chain and Short Chain Fatty acids).
- In Fig 3, a reduction in membrane lipids, free fatty acids, and non-esterified fatty acids is observed, while there is an increase in esterified fatty acids, storage lipids like Triacylglycerols (TAG) and Cholesterol Esters (CE), and lipid droplet number and size. Notably, these lipid droplets are positioned closer to mitochondria in MKO cells. The authors propose that MKO results in enhanced transfer and metabolism of lipid moieties at the mitochondria to generate ATP. To provide insights into the molecular mechanisms underlying the observed lipid changes in MTCH2 KO cells, the following experiments are recommended: Employ Western blot and real-time PCR to measure the levels of enzymes crucial in TAG and CE formation and accumulation (e.g., Long-chain acyl-CoA synthetase (Acsl), Stearoyl-CoA desaturase (SCD) or others). Evaluate the enzymatic activity of these identified enzymes to understand their functional role in lipid metabolism in MTCH2 KO cells.
- The suggested experiments are realistic in terms of time and resources, ensuring practical feasibility.
- The data and methods are presented in a clear and reproducible manner.
- The experiments appear adequately replicated, and the statistical analysis seems OK.
Minor comments:
- There are no specific experimental issues that require addressing.
- Prior studies are appropriately referenced
- In general, both the text and figures are clear and accurate. The significant alteration of metabolites found in their metabolomic dataset should be plotted using the online tool MetaboAnalyst to analyze metabolic pathways and generate better visualizations.
- Overall, the presentation is satisfactory with only minor language adjustments recommended. A minor suggestion for improvement involves refining the language used in the text. Instead of consistently using the term "produce energy," please use "conversion of energy".
Significance
General Assessment: The study, through the integration of metabolomic and lipidomic data in MTCH2 KO cells, provide a comprehensive overview of the metabolic rewiring of these cells. This metabolic change is particularly interesting in the context of adipogenesis, offering valuable insights into the interconnectedness of a mitochondrial solute carrier, cellular metabolism and adipogenesis.
Comparison and Advance: The current study significantly advances our understanding of the mitochondrial carrier homolog 2 (MTCH2) by uncovering its intricate roles in metabolism, and adipogenesis. While prior research identified MTCH2 as a regulator of apoptosis and mitochondrial dynamics, the present study expands our knowledge by elucidating its involvement in cellular metabolism and adipocyte differentiation. The major advance lies in the detailed exploration of MTCH2's impact on cellular metabolism through temporal metabolomic and lipidomic analyses. The study reveals that MTCH2 deletion leads to heightened ATP demand, an oxidized cellular environment, and alterations in lipid, amino acid, and carbohydrate metabolism. Additionally, the adaptive response in MTCH2 knockout cells involves a strategic decrease in membrane lipids and an increase in storage lipids. Furthermore, the study unveils a novel connection between the imbalance in energy metabolism triggered by MTCH2 deletion and the inhibition of adipocyte differentiation-a process that demands substantial energy and reductive biosynthetic activities. This mechanistic insight provides a conceptual advance, indicating how MTCH2, beyond its known role in apoptosis and mitochondrial dynamics, plays a pivotal role in orchestrating cellular metabolism and adipogenesis. Importantly, this work aligns with prior observations that hinted at MTCH2's involvement in fatty acid synthesis, storage, and use through his identified interactome. In summary, the study advances our knowledge of MTCH2 by providing a more comprehensive understanding of its roles in cellular metabolism and adipocyte differentiation, shedding new light on its multifaceted functions beyond its originally identified roles.
Audience: This research will appeal to a broad audience, ranging from specialists in cellular metabolism to those with a general interest in mitochondrial dynamics and biochemistry.
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Referee #1
Evidence, reproducibility and clarity
In the present study, Chourasia et al. describe the effects of MTCH2 deficiency on various metabolic parameters. Using temporal metabolomics in HeLa cells, they show an increase in ATP demand in cells lacking MTCH2. They also show altered lipid metabolism in NIH3T3L1 preadipocytes lacking MTCH2, associated with impaired maturation.
This study is mainly descriptive, containing large amount of information that would be of interest to the understanding of the role of MTCH2 in cell metabolism. The manuscript would benefit from thorough editing to make it more focused and accurate. This is challenging since there is a very large amount of data. Below are some suggestions, along with a couple of experiments that I suggest to add in order to clarify the mechanism through which MTCH2 acts.
Major Comments:
- The ratio ADP/ATP as well as AMP/ATP as well as the decrease in TCA metabolites are indications of ATP demand. Nevertheless, these are not fluxes. It would therefore be worthy to complement these results with respirometry.
- The dramatic increase in AMP/ATP ratio suggests an increase in AMPK activity. Testing it (by measuring AMPK phosphorylation or ACC phosphorylation) could further strengthen the results but it is not a must-have.
- The cause of the increase in AMP in the NIH3T3L1 is not addressed. The involvement of acyl-CoA synthetase is worth discussing or investigating.
- Fig. 2F shows MKO and WT, but it doesn't show MKO-R. This is an important control since lactate doesn't seem to be affected in the MKO-R.
Minor comments:
In the intro there are a few instances that could benefit from some more accuracy:
- In the abstract there is no mention of the cells that are used.
- Line 56: "...(OXPHOS) converts nutrients into adenosine triphosphate (ATP)". It would be more accurate to write that OXPHOS converts the chemical energy that is stored in nutrients into ATP.
- Line 58: "The mitochondrial NAD+/NADH pool are substrates for OXPHOS". It would be more accurate to write that NADH is the substrate. (NAD+ is after all the product of oxidation)
- Line 59-60: "Along with ADP, NAD+ also plays an important role in the regulation of the Krebs cycle". Instead of "regulation" I think it is more specific to write "stimulates" (otherwise add ATP and NADH which are also involved in regulation. 5. Line 65: "...changing metabolic states. In addition, mitochondria..." A link between the two sentences seems to be missing.
- Figure 1 is a heavy figure. Some results are significant and some show only a tendency. The description (Lines 119-125) is too general. It addresses only the "trends". A bit more specificity as to the metabolites or ratios of metabolites and the time points that are significant would be in place.
- Lines 136-139 "The metabolomics analyses revealed additional important changes in many more nutrient substrates, which included a decrease in most amino acids (Fig. 2A and Fig. S2A). Notably, the most significant change was seen in glutamine (Fig. 2A, left top graph), one of the major amino acid-nutrient sources" Glutamine is indeed an important amino acid and the effect is strong, but in this case it's increased. From the first sentence one would think it's decreased. Again, be more specific in your sentencing.
- Lines 157-159: "Thus, the acyl carnitine profile suggests that 1- to 12-hrs post media change the MKO cells use BCAAs as a nutrient source, and later shift to unsaturated acyl carnitines, specifically to the C16:1 and C18:1 forms". This conclusion does not derive from the description by the result - address the difference between the different carnitines that occurs at different times.
- Lines 167-168: "These results suggest that there is higher metabolism of acetyl CoA in the MKO cells leading to a bell-shape dynamics (low-high-low levels)." The interpretation is unclear. I understand that you mean that there is fluctuation within the group, however the acetyl-CoA levels remain lower MKO than in the control at all time points. This further suggests a decrease in TCA cycle.
- Lines 172-173 addresses the bell shape of lactate, yet the most prominent result is the 3-fold increase in lactate levels compared to WT which is not mentioned. Unfortunately, the MKO-R shows a similar increase. Still, this should be addressed in the text.
- 182-184: "Taken together, the results presented above are consistent with the idea that the increased amino acid/lipid/carbohydrate metabolism and substantial decrease of many metabolites in MKO cells is most likely due to their increased utilization to meet themincreased cellular energy demand." I'm not sure how this conclusion is reached. From metabolite levels alone, it's difficult to conclude about fluxes. Also, in a previous conclusion the authors wrote that the TCA cycle is probably reduced; this contradicts the above conclusion. If the authors mean that the FFAs and amino acids are used for anabolism and glucose for meeting energy demand, they should state so more clearly.
- Figure 3A can be split into 2 or 3 subfigures. I think it would make it more comprehensible.
- Line 210-211: "Notably, we also found that MTCH2 knockout cells showed accelerated mitochondria elongation (Fig. S3D, top panels), which was further pronounced when cells were grown in HBSS". The increase in mitochondrial elongation comes after fragmentation in MTCH2 KO. Although this is a known phenotype, it is good to address it shortly in the text.
- Line 208-209: "LDs from dispersed to a highly clustered distribution that was often observed in close proximity to mitochondria..." The proximity of mitochondria to LD suggests the possibility that there is an increase in peridroplet-mitochondria, which have been shown to be involved in biogenesis LD. It might be interesting to investigate this path as an explanation to the observed phenotype.
- Lines 244-245: "These results suggest that the MTCH2 knockout preadipocytes face a cellular energy crisis that is similar to the one seen in the MTCH2 knockout HeLa cells presented earlier" It's true that NAD+ and AMP (as well as AMP/ATP ratio) are increased but in view of the high ATP and NADH, it's difficult reach the conclusion that there's an energy crisis.
- In the discussion- Lines 267-269: "Thus, MTCH2 might act like a "relay station" by sensing and connecting between metabolic intermediates/pathways and dynamic changes in mitochondria morphology/energy production by receiving and sending Wi-Fi signals." It's difficult to raise such specific hypothesis from the results. Use milder terms.
Significance
Great study
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Reply to the reviewers
The authors do not wish to provide a response at this time.
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Referee #2
Evidence, reproducibility and clarity
Summary
This study highlights the role of the septin cytoskeleton in plasma membrane repair in HeLa cells perforated by the pore-forming toxin listeriolysin O (LLO). The authors performed a silencing RNA screen targeting protein-coding genes involved in endocytosis, exocytosis and intracellular trafficking. Besides the recovery of proteins that were previously identified to be part of the membrane repair machinery, they uncovered novel plasma membrane repair candidates, including septin 7 (SEPT7).
They found that upon LLO treatment, septins redistribute from actin stress fibers to the cell surface where they form knobs and loops together with F-actin, Myosin-IIA and Annexin A2 (ANXA2). Using super resolution microscopy and 3D reconstruction, they showed that these structures often protruding from the cell surface are formed by septins and F-actin that are organized in intertwined filaments associated with Annexin A2, and that they are functionally correlated with plasma membrane repair efficiency. Silencing SEPT7 further revealed that the remodeling of the repair protein ANXA2 at the cell surface is greatly decreased in LLO-injured cells, whereas the down regulation of ANXA2 had no impact on the arrangement of septins and F-actin into knobs and loops. Altogether, their results evidenced that the septin cytoskeleton triggers the organization of membrane domains containing the actomyosin cytoskeleton and ANXA2, that are essential for the repair to occur.
Major comments:
- The authors show that silencing SEPT6 or SEPT7, but not SEPT2 or SEPT9, perturbed plasma membrane repair of LLO-injured cells. The authors explain this result by indicating that the reduced expression of SEPT7 and SEPT6 (according to the siRNA), but not that of SEPT2 results in a reduced expression of septins from other groups. This could have been an explanation but, in Fig. S2B, downregulating SEPT2 clearly seem to impact the expression of SEPT6 and SEPT7 (except for siRNA#3) once normalized with the loading control tubulin. Moreover, it is well accepted in the literature and has been observed in many cell types, including HeLa cells, that knocking down a septin from one group (with sometimes the exception of septins of Group 3) induces the downregulation of septins of the other groups, and that it consistently results in the loss of septin filaments. Therefore, the fact that silencing SEPT2 does not perturb plasma membrane repair is quite surprising. This could suggest that SEPT6 and SEPT7, independently of their filament organization, play a role in membrane repair after LLO treatment. Nevertheless, the SEPT2 staining to study the fate of septin filaments following LLO exposure indicated that it is the redistribution of septin filaments that is crucial in this repair process. Interestingly, BORG proteins which are involved in the association of septin filaments to the actin cytoskeleton in interphase cells bind to the SEPT6/SEPT7 coiled-coil region of septin polymers. Could these proteins be involved, knowing that they are Cdc42 effector proteins, and that links exist between Cdc42 activation and Ca2+ entry? OPTIONAL: silencing BORG proteins (BORG2 for example) and studying septin and F-actin remodeling following LLO exposure could help the authors to understand the reason of such a redistribution.
- What about the terms "knob" and "loop": Are they structurally related to the "specks" described in other papers? Or are they new structures that no one observed before? Nobody has never looked at septins in this repair process before, but actin has long been described to be involved.
- It seems that knobs are formed before loops take over. This would deserve further investigation. Is that a reality? Or are they two independent structures? OPTIONAL: it would be interesting to do time-lapse video microscopy to follow the fate of a knob. Related to the previous point: why to show 3 sets of images in the LLO condition in Fig. 2A? Does the top b-panel represent the knob stage? Where there are still many stress fibers indicating that septins have not yet fully redistributed? And when septins are fully dissociated from actin cables, which are then lost, loops are forming (middle c-panel) and then increase in size (bottom d-panel)?
- Even though, some information is given in the discussion section, it would be helpful to mention in the introduction section the different pathways that cells activate to repair plasma membrane defects, and to precise which one(s) has(ve) already been described in the literature to be switched on in response to the LLO toxin.
- Some experiments are not rigorous enough: Sometimes, they have not been repeated, as exemplified in Fig. 7B. Count less cells but repeat the experiment at least three times. Sometimes, one condition is missing, as in Fig. 6C. Where is the DMSO condition? What about the statistics? Fig. 6A: In the calcium free condition, it seems that the two cells that are illustrated depict a telophase. The subcellular organization is obviously different at the end of cell division. Show only one interphase cell as in the top panels. Fig. 6B and C: It is mentioned in the figure legend: "Cells were treated as indicated in (A) and (D)". But the "C" condition is not mentioned anywhere: Does "C" stand for no DMSO or FCF treatment, in the presence of calcium, but under LLO treatment? Likewise, it would be very helpful to indicate in each figure panel whether cells have been treated with LLO or FCF. Please help the reader. Fig. 7A: Whatever SEPT7 is expressed or downregulated, the actin stress fibers are still present. If these cells were not well transfected, replace the images.
- Concerning the FCF experiments: The FCF cytokinin has been used by many authors to perturb septin dynamics. It induces the stabilization of septin polymers, thus promoting the formation of thick ectopic fibers. It is a potent inducer of septin polymerization and acts as a stabilizer. Fig. 6D: In the Ctr condition, a DMSO condition is needed to visualize the impact of FCF on septin filaments. Does FCF stabilize septins and induce the formation of thick filaments? The SEPT2 image in the FCF condition without LLO is of bad quality (see above remark). Also in Fig. 6D (FCF condition without LLO), the F-actin staining revealed that there are no stress fibers!!??? Usually, the more septins are associated with actin, the thicker stress fibers you get, since septins stabilize actin cables. FCF treatment often induces thick ectopic septin filaments that are not associated with stress fibers (which are therefore lost). Was it the case in all FCF-treated cells? Does FCF treatment really mimic what happens physiologically in the cell? Many off-target effects have been observed with this molecule in non-plant cells.
- The image quality in Figs 3A and B, and 6A and D needs to be improved regarding the septin staining. In control conditions, septin filaments cannot be clearly distinguished.
- Fig. 3B: It seems that ANXA2 is overexpressed in LLO-injured cells. Its accumulation level between both conditions should be compared by immunoblot. ANXA2 is indeed recovered on loops, but it is difficult to consider whether it is a redistribution.
- Fig. 7D: Compared to the control condition (we have to refer to Fig. S5D), ANXA2 again seems to be overexpressed under LLO treatment. To affirm that ANXA2 remodeling in LLO-injured cells requires the formation of septin/F-actin knobs and loops, data in Fig. 7D must be quantified.
- Fig. 6 (B-D): In panel B, there is a significant difference between the "C" and "FCF" conditions regarding the number of knobs + loops per cell. Where are the images corresponding to the "C" condition?
Minor comments:
- Fig. 2A: Report the white squares (selected enlarged areas) in all panels (SEPT2 and overlay). In panels b, do not place an arrowhead where we are supposed to observe an enlarged area. Also, from panels b, it would be worth showing an enlarged area including a knob. Show enlarged areas also from panels d.
- Fig. 3B'i: Septins are not on stress fibers. Select a transfected cell where septins still coalign with actin fibers, not a cell that was impaired by the transfection.
- Fig. 3C: Add the time point "0min". What was the % of colocalization before LLO treatment? and in DMSO condition? What about ALIX at 5 and 10min? Again, it's only one experiment.
- Figs 4 and 5: Very nice images but obtained following FCF exposure. Hopefully FCF would not have induced an aberrant organization!
- The "Ctr" abbreviation is often used, in different conditions, and may be confusing. Precise in the figure (not in the figure legend) whether it is siRNA ("Ctr siRNA"). Mention "DMSO" for the controls of your drugs (like in Figs S4 and S5).
- Fig. S4C: How is this figure different or does it provide additional information compared to Fig. 2C?
- Fig. S5D: It is hard to know that the ANXA2 siRNA worked, since no difference of staining between the Ctr and the transfected cells can be observed. Were these cells really transfected? It would have been helpful to use fluorescent siRNAs. The same applies to Fig. S5C: Silencing SEPT7 supposedly greatly reduces the level of expression of all septins. The SEPT2 staining is still high, and many actin stress fibers are still observable (whereas the loss of septin filaments results in the loss of actin stress fibers, as observed by many authors, including in HeLa cells). Same remark for Fig. S6, regarding the SEPT7 silencing in the Ctr condition (no LLO). No impact on stress fibers! Are these cells transfected? The authors themselves mention that sometimes cells are less effectively silenced (like in Fig. 7A, B). Why not to show cells effectively silenced!!
- In the abstract, it is specified that SEPT7 also plays a role in membrane repair after mechanical wounding. Based only on one type of experiment (SEPT7 silencing, Fig. 1H), this statement should only be mentioned in the text or used to discuss the putative repair mechanisms that septins are involved in, but not stated in the abstract as a main conclusion.
Significance
Strengths:
Despite septins have been involved in endocytosis, exocytosis, membrane protrusions, cell junction integrity or actomyosin constriction at cytokinesis, the involvement of the septin cytoskeleton in the plasma membrane repair machinery has, to my knowledge, never been reported before. The authors not only showed that septins are present in specific membrane protrusions (knobs and loops) but also evidenced that septin filaments trigger the formation of these plasma membrane repair domains by recruiting F-actin and ANXA2, essential for the repair to occur. The novelty of this study has therefore to be acknowledged, and these data will benefit the scientific community, and the septin community in particular.
This is a descriptive paper that nevertheless clearly shows, by different means, the reorganization of the septin cytoskeleton in LLO-injured cells. The use of high-resolution microscopy coupled to 3D reconstruction which enables to easily appreciate the organization of septins, F-actin and ANXA2 in the knobs and loops is a true strength of the paper.
Limitations:
The authors mention in the abstract that septins act as scaffolds to recruit contractile actin fibers and ANXA2. Biochemical experiments such as co-immunoprecipitations could strengthen this notion. The molecular mechanism by which septins are involved in this repair process has not been addressed at all in the paper. Even though the silencing RNA screen highlighted several proteins involved in known membrane repair mechanisms, the authors just presented a few data concerning ALIX, a component of the ESCRT-III machinery. A % of colocalization of SEPT2 and SEPT7 with ALIX is reported in Fig. 3C but this experiment has only been done once (n=1) and only following 15-min exposure to LLO. Is that too late? Immunofluorescence images of SEPT2 and ALIX with or without LLO (15min) are also provided in Fig. S5A but no quantification is reported. Is it sufficient to say that the ESCRT machinery is not involved?
My field of expertise:
Cytoskeleton, Septin, Actin, Microtubule, Signaling pathways
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Referee #1
Evidence, reproducibility and clarity
Review of "The septin cytoskeleton is required for plasma membrane repair" by Prislusky et al.
Eukaryotic cells rapidly repair damage to their plasma membrane and underlying cortical cytoskeleton. Such repair is increasingly recognized as being of major importance to human health (PMID: 33849525). Two broadly conserved cell damage responses have been described: a very rapid membrane resealing response which commences within a second or so following damage, and a cortical cytoskeletal response which commences within ~15-30s and which is based on activation of the Rho GTPases. However, our understanding of either of these responses is extremely limited, a situation which has engendered considerable debate about not only the mechanistic bases of these responses but also their relative roles and the extent to which they may be interdependent.
In the current study, the authors use an siRNA screen to identify Septin7 (hereinafter SEPT7) as a critical participant in the cell repair response. They further demonstrate that cell damage, as induced either by bacterial pore-forming proteins or by mechanical abrasion results in accumumulation of septins (including SEPT7) in curious ring-like structures associated at the plasma membranes; these structures are often associated with plasma membrane protrusions, which are a common feature of damaged cells. Additionally, the authors show that the septins colocalize with F-actin, myosin-2 (an F-actin-based motor protein) and annexin-2A, a protein previously implicated in cell repair. Lastly, the authors show that depletion of septins reduces the recruitment of annexin-2A to the plasma membrane in wounded cells, implying that the septins are upstream of the annexin in the wound response.
This is an exciting study that is also very well-documented. The excitement is provided by the following observations: first, septins have not previously been implicated in cell repair; second, the association of the septins with F-actin and myosin-2 in ring-like structures at the plasma membrane is suggestive of the possibility that local contraction may promote healing, a long-standing idea derived from studies of frog oocyte healing (PMID: 10359696; PMID: 11502762) which has proven controversial for healing of other cell types (see below); third, a link between septins and annexins in cell repair or, for that matter, any other process, is novel. With respect to the support for their claims, the authors go above and beyond to make their case-every point is supported by multiple approaches-for example the importance of septins is shown via siRNA, shRNA, and inducible depletion-and the imaging is very, very nice.
The potential role for actomyosin-powered contraction in healing of wounds made in cultured mammalian cells has been largely discounted because of studies wherein cells are wounded after pharmacological treatment with actin poisons have shown that healing is actually improved. The problem with such studies, is that depolymerization of actin prior to cell damage will dramatically alter the response to damage due to loss of cortical tension (PMID: 19846787). Thus, besides being important in its own right, the current study opens new doors for experimental assessment of the possible roles for cortical actomyosin in cell repair.
I have only minor concerns or questions:
- What is the spatial relationship between the septin rings and actual damage sites? This could be addressed by wounding in the presence of a lysine fixable dextran.
- The information in table 1 could be made more reader-friendly. In particular, it is not clear how the authors are getting their gene/protein names for their hits and what they correspond to. This was most noticeable for IQSEC1, ABI1, and GBF1 which the authors describe in the text as "genes that control the actin cytoskeleton" but in the table are listed as "Signaling proteins". I may have the abbreviations wrong (which is more reason for additional clarity) but GBF1 is the abbreviation for a protein involved in intracellular trafficking; IQSEC1 is a GEF for Arf proteins, and ABI1 is best known as a subunit of the WAVE complex.
- The statement that begins the abstract "Mammalian cells are frequently exposted to mechanical and biochemical stresses..." could just as easily be "Eukaryotic cells..." or even "Cells..." as the membrane repair response is apparently universal and, indeed, was first described in nonmammalian cells. Similarly, the introduction begins "The plasma membrane of mammalian cells forms a biophysical barrier that separates the cell from its external environment". As far as I know, this is not a specific feature of mammalian plasma membranes but rather all plasma membranes. I don't know if it is the author's intention to imply their work is only relevant to mammals, but that is certainly not the case and they end up reducing the impact of their work by making it sound like cell repair is a phenomenon specific to mammalian cells.
- The word "subplasmalemmal" is likely to be confusing for those who are not aware that plasmalemma is an antiquated term for the plasma membrane. It might be easier for the reader if the authors refer to "subdomains of the plasma membrane".
Significance
This is an exciting study that is also very well-documented. The excitement is provided by the following observations: first, septins have not previously been implicated in cell repair; second, the association of the septins with F-actin and myosin-2 in ring-like structures at the plasma membrane is suggestive of the possibility that local contraction may promote healing, a long-standing idea derived from studies of frog oocyte healing (PMID: 10359696; PMID: 11502762) which has proven controversial for healing of other cell types (see below); third, a link between septins and annexins in cell repair or, for that matter, any other process, is novel. With respect to the support for their claims, the authors go above and beyond to make their case-every point is supported by multiple approaches-for example the importance of septins is shown via siRNA, shRNA, and inducible depletion-and the imaging is very, very nice.
The potential role for actomyosin-powered contraction in healing of wounds made in cultured mammalian cells has been largely discounted because of studies wherein cells are wounded after pharmacological treatment with actin poisons have shown that healing is actually improved. The problem with such studies, is that depolymerization of actin prior to cell damage will dramatically alter the response to damage due to loss of cortical tension (PMID: 19846787). Thus, besides being important in its own right, the current study opens new doors for experimental assessment of the possible roles for cortical actomyosin in cell repair.
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Reply to the reviewers
General Statements
We are grateful to the reviewers for reviewing our manuscript. In general, the reviewers agree that our method presents a new approach of Nanopore direct RNA-seq that is not limited to the standard use of only the adenylated fraction of RNAs within a sample but they have also requested more evidence about the effectiveness and usefulness of this approach. Reviewer 1 notes that NERD-seq "extends nanopore direct RNA-Sequencing to beyond the poly(A) fraction." Reviewer 2 notes that "This manuscript has the potential of having major significance to researchers in the field of transcriptomics". At the same time Reviewer 1 remarks that, "the authors need to expand more on why this is useful, and what scenarios this would be used in" and need "to demonstrate that NERD-Seq is more than an incremental improvement to existing approaches". Reviewer 2 notes that "This technique has great potential, as ONT direct RNA sequencing can be used to detect RNA modifications... There are however some issues that need to be addressed before the manuscript is suitable to publication" and agrees with Reviewer 1 that the authors need to demonstrate "that their newly sequencing techniques could indeed improve RNA detection beyond the current techniques." We are grateful to the reviewers for these comments, and we fully agree that the manuscript in its initially submitted form falls "short from providing strong arguments supporting the fidelity, accuracy and coverage of the new technique." and that more "proof of the increased accuracy or utility of the new technique" was needed.
We attach a substantially revised and expanded version of the manuscript that includes additional data needed to ensure the methodology is replicable and further supports the rationale why NERD-seq is a useful addition to the current direct RNA sequencing methodology repertoire. We now provide:
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the repetition of all performed NERD-seq runs with a new enzyme (commercially available), as the one used in our initial study (Omniamp polymerase) is not anymore commercially available
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6 revised main figure panels based on the new sequencing runs and a new main figure (Fig.7),
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20 new supplementary figures, and
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1 new supplementary table (Suppl. Tables 1),
that correspond to the points raised by the reviewers. We have also revised the main text accordingly.
Please find below the reviewers 'comments and a detailed point by point response to these comments. A document with the changes from the initially submitted manuscript being highlighted is attached at the end of this response.
Point-by-point description of the revisions
Reviewer 1
*------------------------------------------------------------------------------ *
*Reviewer #1 (Evidence, reproducibility and clarity (Required)): *
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***Summary:** *
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This reviewer generally remarks that: "Saville et al detail a new method, NERD-Seq, which extends nanopore direct RNA-Sequencing to beyond the poly(A) fraction. In principle, this allows the capture of additional RNA types in a single sequencing reaction, albeit at the expense of sequencing depth. However, the authors need to expand more on why this is useful, and what scenarios this would be used in. The rationale for many of their experimental choices are not explained/contextualized appropriately. The manuscript also suffers from excessive jargon and grammatical errors."
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We appreciate these comments made by the reviewer. We now expand more on why and how NERD-seq is useful, and what scenarios this could be used in. In particular:
In the introduction, we now denote that a significant number of the most well described RNA modification positions are located in classes of RNAs such as tRNAs, snoRNAs and other ncRNAs like 7SK RNA. In the results section, we build on the second reviewer's suggestion that "This technique has great potential, as ONT direct RNA sequencing can be used to detect RNA modifications...", and we first show in revised Figures 3-5 that the standard approach misses the above classes of RNAs. Subsequently, in two new figures (Fig. 7 and Suppl.Fig. S23) we present an example of the ability of NERD-seq to decipher known RNA modifications in a well-studied ncRNA, 7SK, compared with the inability of the standard approach to do so. Widely studied RNAs such as 7SK have the potential and thus often serve as controls for known positions of certain RNA modifications when validating them for novel positions in other RNAs. This however means that the application of the standard approach, which is not able to detect RNAs and thus their modifications for RNAs such as 7SK, makes it difficult to use them as controls. In other words, the ability to perform genome wide studies of RNA modifications using the direct RNA-seq approach relies on the ability to be able to confirm at the same time these findings in already known control positions located in the above classes of RNAs. If these known controls such as short ncRNAs are missing, as we show that it is the case with standard RNA-seq, it is difficult to perform such genome wide epitranscriptome studies. Thus, the usefulness of our approach is not only that it can sequence certain classes of shorter RNAs beyond mRNAs, but that it can do this without affecting the ability to study mRNAs simultaneously or use targeted sequencing adapters. This is now discussed in the text. We have also tried to avoid the excessive use of jargon language and correct any grammatical errors.
*------------------------------------------------------------------------------ *
***Major comments:** *
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Point 1. The reviewer mentions:* "To my understanding, the primary purpose of NERD-Seq is to allow the sequencing of the non-adenylated fraction of RNAs within sample with a size filter step designed to exclude ncRNAs larger than ~200 nt. While this allow for subsequent polyadenylation of the small fraction, it remains quite likely that larger non-adenylated non-rRNAs are being missed by the protocol. It is also not clear why NERD-Seq should be considered the optimal strategy. The authors should show that they have considered/evaluated other strategies such as: *
*- Depletion/Seperation of the poly(A) fraction prior to size selection performed on non-adenylated fraction. *
- Targeted degradation of the rRNA fraction using rRNA depletion kits."
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We thank the reviewer for this comment. The primary purpose of NERD-seq is not only to allow the sequencing of the non-adenylated fraction of shorter RNAs but to do this while maintaining the ability to sequence longer polyadenylated RNAs. In particular, we are not sequencing only the short RNA fraction but also the longer RNA fraction of naturally polyadenylated RNAs. This includes both mRNAs and ncRNAs that are polyadenylated. We apologize that this may have not be presented clearly in our initial text, and we have now revised the respective results part (page 8, lines 13-14 and 30-31). As mentioned below, we now also provide evidence that our approach does not affect the ability to efficiently sequence mRNAs and decipher effectively their isoforms (new Suppl. Fig. S19). Only large non poly-A ncRNAs still evade our detection. Now, we discuss this limitation in the last paragraph of the discussion section (page 19, lines 12-20). We have now also evaluated other strategies such as those mentioned by the reviewer (depletion of rRNA, size selection using magnetic beads, different enzymes) and in the new Suppl. Figure S5 we show that they were suboptimal in providing sufficient reads that pass the quality thresholds in base calling compared to our NERD-seq approach.
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To sum up, we certainly don't claim to be able to capture longer ncRNAs, due to their lack of polyadenylated tails. We show though that while the ability to capture simultaneously all reads under the current Nanopore sequencing protocols may be unattainable, the NERD-seq methodology demonstrates a useful addition to the Nanopore sequencing repertoire due to its ability, in addition to polyadenylated transcripts, to simultaneously capture multiple classes of short ncRNAs, hitherto until now only achievable one transcript at a time with custom adaptor ligation.
Point 2. The reviewer mentions that "Related to this, the authors note that NERD-Seq is designed to allow the sequencing of both adenylated and (short) non-adenylated fractions of RNAs within a study. What is the actual value of this versus, say, simply targeting the short non-adenylated fraction directly? "
Please see our response to the general comment by this reviewer and the new figures Fig. 7 and Suppl. Fig. S23 and the completely new results section at pages 15 and 16 about examples on how NERD-seq expands the study of epitranscriptomic signatures to additional RNA classes while maintaining the ability to efficiently assess the protein coding transcriptome (new Suppl. Fig. S19).
Point 3. The reviewer notes that "The manuscript in general is written in a somewhat subversive style, seemingly focused on highlighting the 'failings' of the standard ONT protocol. This is somewhat disingenuous as these are not 'failings' per se given the design objective of the standard DRS protocol (i.e. to capture and sequence the poly(A) fraction of RNAs) works well. The authors would be better off highlighting the situations (i.e. study questions) where NERD-Seq would provide a measurable benefit over the standard DRS strategy. "
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We apologize if this was indicated in our initial submission, as this was not our intention. We now focus on highlighting what NERD-seq can do, and this is reflected in the changes we have made in the introduction and discussion section.
Point 4. The reviewer asks "The authors state that 1.5ug total RNA is used as input for NERD-Seq but how much input (poly-A RNA) actually goes into the short- and long-fraction parts of the DRS protocol? This is important to know. "
We have now included data in the manuscript for polyadenylation signals in the reads themselves (new Suppl. Fig S5F) and view it as a useful addition to the manuscript as it seems to show there is little difference in the relationship of length of transcript and polyadenylation tail length between the two methods.
RNA RIN values differ across samples so within different samples the portions of poly-A RNA, non poly-A RNA and former poly-A RNA that has lost the poly-A due to degradation may also vary. This however has not been shown to affect the reproducibility of the standard direct RNA-seq methodology, so it should not affect also that of NERD-seq. Nevertheless, we searched the literature for a well characterized methodology for quantifying this further and found little on poly(A) specific quantification approaches that we could use. In fact, poly(A) selection has also been shown to have variable efficiency and could thus produce inaccurate measurements that would make it difficult for us to assess explicitly the exact portions of poly-A vs non poly-A portions. Thus, we feel that in the absence of a well characterized methodology to make these quantifications, developing a new one may have been beyond the scope of this manuscript.
Point 5. The reviewer recommends: "The authors show that NERD-Seq performs well on a tissue that is generally enriched in non-coding RNA activity but without the inclusion of biology replicates or tissue samples from other sources, it is impossible to assess (1) the reproducibility/robustness of the methodology and (2) whether NERD-Seq would produce useable data from other tissues with lower non-coding RNA activity. These experiments are required. "
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We thank the reviewer for this suggestion and we have now included an additional biological replicate for the mouse tissue and data from another tissue in a separate organism (5-person pool source human cerebral cortex RNA).
Point 6. The reviewer notes: "Several figures are poorly explained. For instance, Does Figure 2A show data only from the short RNA fraction? If not then this suggests incredibly high levels of mRNA degradation in the 'standard' ONT fraction - far beyond what is seen in other studies. The legends for all figures should be far more specific and detailed."
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We have now replaced figure 2A with a different mapping strategy and a whole sample assessment of mapped reads lengths. We have also edited the figure legends to include more information.
The reviewer made also the following comments:
Minor comments:
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": Please refrain from using 'next-generation' in a sequencing context (abstract, introduction). Having a 'new' next-generation sequencing is confusing in regard to the old 'next generation' sequencing. "
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The instances mentioned have been removed as per the reviewer's suggestion.
"Introduction should acknowledge that targeted sequencing of (individual) non-adenylated RNAs is possible (i.e. there is an ONT protocol for this)."
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We now include mention of this in the introduction, results and discussion.
"Several figure elements not referenced in the text appropriately (e.g. red bars in Figure 2A). "
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We have now addressed this and thank the reviewer for making us aware of this.
"The authors mention profiling of the epitranscriptome several times in the introduction and discussion but do not include any work geared toward looking for RNA modifications. Indeed it is entirely unclear whether NERD-Seq produces the depth of sequencing (on non-adenylated RNAs) required for current RNA modification detection tools. "
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We have now included a new main figure (Fig. 7) and a new supplementary figure (Suppl. Fig. S23) which profile elements of the epitranscriptome and show that indeed NERD-seq produces the depth of sequencing necessary for RNA modification detection.
Reviewer 1's summary:
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"NERD-Seq presents a modified method for DRS of both short non-adenylated and the standard adenylated fraction of RNAs within a sample. This utility of this approach appears rather niche and it is hard to determine situations in which this approach would be generally useful versus many of the existing (Illumina-based) approaches. The burden to demonstrate that NERD-Seq is more than an incremental improvement to existing approaches lies with the authors. "
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We appreciate the reviewer's comments. While we agree with them that for various applications (such as differential gene expression, quantification of lowly expressed genes) "the existing (Illumina-based) approaches" Illumina RNA-seq or short-RNA-seq would be more appropriate due to higher sequence yields, the main advantage of nanopore direct RNA-seq is the ability to identify RNA modifications directly at the same time (see new Figs 7 and S23). While we also agree that the field of high throughput sequencing epitranscriptomics is quite nascent, it is quickly gaining interest. Based on the reviewer's suggestions we believe that we have now modified the manuscript substantially to provide justification for NERD-seq's feasibility as a methodology to capture multiple classes of ncRNAs for the study of their sequence, quantity and their epitranscriptomic signatures.
We would also like to note that even as a BioRxiv preprint, our manuscript has received already a number of citations, including from an article published in Nature Biotechnology and feel this demonstrates interest in NERD-seq from the scientific community.
Reviewer 2
Reviewer #2 (Evidence, reproducibility and clarity (Required))
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This reviewer generally remarks that "In this manuscript Saville et al. present NERD-seq, a novel method to enrich and directly sequence non-coding RNA using the Oxford Nanopore Technology (ONT). The technique is based on the addition of a poly-A tail to small non-coding RNAs which enables their sequencing by a conventional ONT direct RNA-seq protocol using a poly(T)-tethering adaptor. This technique has great potential, as ONT direct RNA sequencing can be used to detect RNA modifications. Furthermore, non-coding RNAs are known to harbor a lot of these modifications and that they are important to their function. In addition, non-coding RNAs aren't generally poly-adenylated and therefore are underrepresented when using standard ONT direct RNA-seq. The authors have shown that using NERD-seq, they are able to significantly improve the number of reads on several subsets of non-coding RNAs : tRNAs, snoRNAs, snRNAs, scRNAs and rRFs. There are however some issues that need to be addressed before the manuscript is suitable to publication."
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We thank the reviewer for their encouraging comments.
Major comments:
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Point 1. The reviewer recommends that "Data on RNA modifications present in the sequenced non-coding RNA would greatly improve the impact of the manuscript, as the method is presented as read tool to study RNA modifications. If the authors can't include these data, they should at least explain why in the discussion section."
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We have now included a new main figure (Fig.7) and a supplemental figure (Suppl. Fig. S23) which show the ability of NERD-seq to identify previously described RNA modifications and its superiority in the case of non-coding RNAs such as 7SK. We thank the reviewer for this recommendation that significantly improved our manuscript better revealing the rationale and impact of our approach.
Point 2. The reviewer remarks that "The authors did not discuss possible biases of their method. For example, is the poly-A tail ligation efficiency affected by sequence and or structural differences between RNA? Is there detectable differences in the efficiency of sequencing small RNA with structured 3'end when compared to mRNA? Are the proportions of reads obtained per non-coding RNA sub-category and RNA rank supported by other biochemical data (e.g. Northern blots, primer extension, RT-qPCR? "
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We have included commentary in the discussion on these biases (page 19, lines 7-11). We also include a new supplementary figure (Suppl. Fig. S5F) regarding polyadenylation in which we see similar transcript length to polyadenylation tail length dynamics between the two methodologies.
Point 3. The reviewer notes that "It is essential to include external size and sequence markers spike-in to directly evaluate the quality and fidelity of the newly develop sequencing technique. "
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We have now repeated the sequencing, including sequencing with the well described RNA sequins mix B. We include a new supplementary figure with this data (Suppl. Fig. S10) that shows that NERD-seq does not differ from the standard approach regarding its ability to effectively evaluate the quantity and complexity of the transcripts present.
Point 4. The reviewer mentions that "The author compared NERD-seq to ONT standard direct RNA-seq but did not compare it with other methods that are currently used for non-coding RNA sequencing (e.g. Illumina based sequencing, TGIRTseq). There is a need for side by side comparison at least by using data available in the literature if not experimentally. "
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We now include a comparison with Illumina sequencing data for both long and short fractions from each biological replicate (Suppl.Figs S12-15,17,19 and 21). This data shows that NERD-seq combines the advantages of both standard and short RNA-seq with Illumina, enriching both long and short RNAs, while simultaneously as mentioned above, offering the benefits of direct RNA-seq. We feel this also demonstrates the utility of the unique chemistry of Nanopore sequencing where fragmenting of long RNAs is not required for sequencing, allowing the combination of long RNAs and short RNAs in the same library to reproduce what is essentially enriched in short RNA libraries as well as poly(A) sequencing libraries. Since the enzyme included in our initial submission is not anymore widely accessible, we also tested a series of other enzymes, including the commercial replacement for omniamp (the originally used enzyme), lavalamp, and other small tweaks to the library methodology, until finding the GSP SSD2.0 enzyme to be the most suitable for our research goals. The summary of our findings is in Figure S5. Initially, we considered TGIRT as a potential enzyme for the sequencing reaction because of its use for sequencing snoRNAs and other highly structured RNAs but because of its strand switching properties, we felt it would be poorly suited for a nanopore direct RNA sequencing approach.
The reviewer made also the following comments/suggestions:
Minor comments
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"Page 5 line 3, NERD-seq is misspelled. "
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This is now fixed.
"Throughout this section µL and µg are written as uL and ug."
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This is now fixed.
"Several temperatures are missing the o symbol between the number and C."
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This is now fixed.
Final comments:
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"This manuscript has the potential of having major significance to researchers in the field of transcriptomics if the author demonstrated that their newly sequencing techniques could indeed improve RNA detection beyond the current techniques. Unfortunately, the manuscript only show the capacity of the technique to detect non-coding RNA but fall short from providing strong arguments supporting the fidelity, accuracy and coverage of the new technique. The use of Nanopore sequencing is not unique and was used in the past for sequencing non-coding RNA. What is needed now is a proof of the increased accuracy or utility of the new technique to justify yet another publication about Nanopore sequencing paper. The manuscript would potentially be of interest to researcher working on different type of non-coding RNA and transcriptomics.* *
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I am in the field of non-coding RNA sequencing and functional analysis and very familiar with this approach."
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We thank the reviewer again for their encouraging comments and valid concerns. We agree that the initial manuscript fell short of providing evidence of its utility as an addition to the Nanopore sequencing repertoire. We hope the additional data we provide (rerunning with an additional enzyme, use of replicates, use of standard spike in controls, testing an additional organism and tissue, testing and comparing different enzymes and other sequencing platforms) provide the necessary assurances about reproducibility and accuracy, while the new data concerning identification of RNA modifications and detection of important RNA classes missed by the standard protocol provides the necessary assurances about the utility of our approach.
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Referee #2
Evidence, reproducibility and clarity
In this manuscript Saville et al. present NERD-seq, a novel method to enrich and directly sequence non-coding RNA using the Oxford Nanopore Technology (ONT). The technique is based on the addition of a poly-A tail to small non-coding RNAs which enables their sequencing by a conventional ONT direct RNA-seq protocol using a poly(T)-tethering adaptor. This technique has great potential, as ONT direct RNA sequencing can be used to detect RNA modifications. Furthermore, non-coding RNAs are known to harbor a lot of these modifications and that they are important to their function. In addition, non-coding RNAs aren't generally poly-adenylated and therefore are underrepresented when using standard ONT direct RNA-seq. The authors have shown that using NERD-seq, they are able to significantly improve the number of reads on several subsets of non-coding RNAs : tRNAs, snoRNAs, snRNAs, scRNAs and rRFs. There are however some issues that need to be addressed before the manuscript is suitable to publication.
Major Comments:
• Data on RNA modifications present in the sequenced non-coding RNA would greatly improve the impact of the manuscript, as the method is presented as read tool to study RNA modifications. If the authors can't include these data, they should at least explain why in the discussion section.
• The authors did not discuss possible biases of their method. For example, is the poly-A tail ligation efficiency affected by sequence and or structural differences between RNA? Is there detectable differences in the efficiency of sequencing small RNA with structured 3'end when compared to mRNA? Are the proportions of reads obtained per non-coding RNA sub-category and RNA rank supported by other biochemical data (e.g. Northern blots, primer extension, RT-qPCR?
• It is essential to include external size and sequence markers spike-in to directly evaluate the quality and fidelity of the newly develop sequencing technique.
• The author compared NERD-seq to ONT standard direct RNA-seq but did not compare it with other methods that are currently used for non-coding RNA sequencing (e.g. Illumina based sequencing, TGIRTseq). There is a need for side by side comparison at least by using data available in the literature if not experimentally.
Minor Comments:
• Page 5 line 3, NERD-seq is misspelled.
• Throughout this section µL and µg are written as uL and ug.
• Several temperatures are missing the o symbol between the number and C.
We recommend that all these issues should be addressed before publication.
Significance
This manuscript has the potential of having major significance to researchers in the field of transcriptomics if the author demonstrated that their newly sequencing techniques could indeed improve RNA detection beyond the current techniques. Unfortunately, the manuscript only show the capacity of the technique to detect non-coding RNA but fall short from providing strong arguments supporting the fidelity, accuracy and coverage of the new technique. The use of Nanopore sequencing is not unique and was used in the past for sequencing non-coding RNA. What is needed now is a proof of the increased accuracy or utility of the new technique to justify yet another publication about Nanopore sequencing paper. The manuscript would potentially be of interest to researcher working on different type of non-coding RNA and transcriptomics.
I am in the field of non-coding RNA sequencing and functional analysis and very familiar with this approach.
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Referee #1
Evidence, reproducibility and clarity
Summary:
Saville et al detail a new method, NERD-Seq, which extends nanopore direct RNA-Sequencing to beyond the poly(A) fraction. In principle, this allows the capture of additional RNA types in a single sequencing reaction, albeit at the expense of sequencing depth. However, the authors need to expand more on why this is useful, and what scenarios this would be used in. The rationale for many of their experimental choices are not explained/contextualized appropriately. The manuscript also suffers from excessive jargon and grammatical errors.
Major comments:
1: To my understanding, the primary purpose of NERD-Seq is to allow the sequencing of the non-adenylated fraction of RNAs within sample with a size filter step designed to exclude ncRNAs larger than ~200 nt. While this allow for subsequent polyadenylation of the small fraction, it remains quite likely that larger non-adenylated non-rRNAs are being missed by the protocol. It is also not clear why NERD-Seq should be considered the optimal strategy. The authors should show that they have considered/evaluated other strategies such as: - Depletion/Seperation of the poly(A) fraction prior to size selection performed on non-adenylated fraction. - Targeted degradation of the rRNA fraction using rRNA depletion kits.
2: Related to this, the authors note that NERD-Seq is designed to allow the sequencing of both adenylated and (short) non-adenylated fractions of RNAs within a study. What is the actual value of this versus, say, simply targeting the short non-adenylated fraction directly?
3: The manuscript in general is written in a somewhat subversive style, seemingly focused on highlighting the 'failings' of the standard ONT protocol. This is somewhat disingenuous as these are not 'failings' per se given the design objective of the standard DRS protocol (i.e. to capture and sequence the poly(A) fraction of RNAs) works well. The authors would be better off highlighting the situations (i.e. study questions) where NERD-Seq would provide a measurable benefit over the standard DRS strategy.
4: The authors state that 1.5ug total RNA is used as input for NERD-Seq but how much input (polyA RNA) actually goes into the short- and long-fraction parts of the DRS protocol? This is important to know.
5: The authors show that NERD-Seq performs well on a tissue that is generally enriched in non-coding RNA activity but without the inclusion of biology replicates or tissue samples from other sources, it is impossible to assess (1) the reproducibility/robustness of the methodology and (2) whether NERD-Seq would produce useable data from other tissues with lower non-coding RNA activity. These experiments are required.
6: Several figures are poorly explained. For instance, Does Figure 2A show data only from the short RNA fraction? If not then this suggests incredibly high levels of mRNA degradation in the 'standard' ONT fraction - far beyond what is seen in other studies. The legends for all figures should be far more specific and detailed.
Minor quibbles:
1: Please refrain from using 'next-generation' in a sequencing context (abstract, introduction). Having a 'new' next-generation sequencing is confusing in regard to the old 'next generation' sequencing.
2: Introduction should acknowledge that targeted sequencing of (individual) non-adenylated RNAs is possible (i.e. there is an ONT protocol for this).
3: Several figure elements not referenced in the text appropriately (e.g. red bars in Figure 2A).
4: The authors mention profiling of the epitranscriptome several times in the introduction and discussion but do not include any work geared toward looking for RNA modifications. Indeed it is entirely unclear whether NERD-Seq produces the depth of sequencing (on non-adenylated RNAs) required for current RNA modification detection tools.
Significance
NERD-Seq presents a modified method for DRS of both short non-adenylated and the standard adenylated fraction of RNAs within a sample. This utility of this approach appears rather niche and it is hard to determine situations in which this approach would be generally useful versus many of the existing (Illumina-based) approaches. The burden to demonstrate that NERD-Seq is more than an incremental improvement to existing approaches lies with the authors.
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Reply to the reviewers
The authors do not wish to provide a response at this time.
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Referee #3
Evidence, reproducibility and clarity
Summary:
This manuscript examines the effects of fibroblast-derived extracellular vesicles (EV) on axon outgrowth in primary neurons, and investigates potential underlying mechanisms. The authors show that fibroblast EV increase axon outgrowth, which is dependent on components of the Wnt-PCP pathway in neurons. They further show that axonal outgrowth is not affected by neuron- or astrocyte-derived EV and that EV from activated astrocytes inhibit axon elongation. Although several experiments are performed thoroughly, major revision is required to substantiate the main claims of the manuscript.
Major comments:
- Even though the authors made a good effort to characterize fibroblast-derived EV, the data so far does not indicate that strictly 'exosomes' are implicated in axon outgrowth, as it is currently virtually impossible to isolate a pure population of exosomes.
- In the methods the authors state that the conditioned media was stored for up to 8 weeks at 4C. As long-term storage of EV was shown to decrease their activity, the authors should specify whether they took steps to test the effect of storage time on EV concentration and activity.
- In Fig 3F, the authors claim that Vangl2 re-localizes from proximal to distal end of the axon. However, in the representative image the PBS-treated axon is much shorter, and Vangl2 can also be also detected in the growth cone. Therefore, it is not clear how neurons were classified in the analysis. As this is one of the main claims of the paper, the analysis should be performed in a more quantitative manner, such as quantification of intensity and volume of Vangl2 in the soma, proximal / distal axon and growth cone, while accounting for changes in axon length.
- The claim that exosomes mobilize neuronal Wnt to promote axon growth is unsubstantiated. Co-localization between Wnt7b and GFP-CD81 is not convincing given the low magnification and broad distribution of Wnt7b. It is also unclear how EV internalized in the soma would have this effect. Additional experiments to prove the direct influence of fibroblast EV on Wnt-PCP signaling (and optionally, how this is unique for fibroblast EV) would increase the validity of these claims.
- Neuronal EV were isolated at a different developmental time point (8DIV), which most likely has an effect on EV composition. Therefore, the claim that neuronal EV do not promote neurite outgrowth is not convincing. In addition, AraC or LPS used to treat neurons and astrocytes respectively, could be co-purified with EV and therefore have adverse effects on recipient neurons.
- The authors claim that this effect is unique to fibroblast EV. This claim is not valid without a full characterization of EV derived from multiple cell types and is therefore misleading.
Minor comments:
- As in point 1 above, it is recommended to replace the term 'Exosome' in the figures and refer instead to the method of purification (eg. 100k). The term 'Exosome markers' in the text should also be replaced accordingly, as it is not currently clear whether CD81, TSG101 or Flotilin 1 are strictly on exosomes.
- Experiments using EV purified using gradient centrifugation (Fig S3) should be repeated at least once, such that statistical significance is calculated and results are shown as in other functional experiments. Alternatively, experiments could be performed using purified EV treated with a proteinase in the presence or absence of detergent, to verify whether it is EV cargo or extracellular proteins co-isolated with EV that mediate the observed phenotype.
- The authors should show that porcupine knockdown results in decreased Wnt secretion in fibroblast EV using western blotting.
Significance
Overall, the main take home message of this study is that fibroblast EV could have the common feature of upregulating axon outgrowth in neurons during development. While this is not relevant for CNS development per se, it could ultimately be of interest to a specialized audience investigating the translational relevance of fibroblast-derived EV.
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Referee #2
Evidence, reproducibility and clarity
The definition of axonal fate has been under a lot of scrutiny. However nowadays it is not clear how the axonal fate could be distinguished from axon elongation. In other words, how one the neurite is selected to eventually grow as an axon versus the mechanism sustaining axonal growth once the fate is established. In addition, it is not clear, once the axon is growing, what is the mechanism that precludes the other neurites (future dendrites) from growing.
The authors of this manuscript claim that fibroblast-derived exosomes promote axon growth; meanwhile, exosomes from activated astrocytes inhibit axon elongation. Moreover, the authors claim that exosomes mediate axon elongation throughout the PCP and Wnts pathways.
I have several concerns regarding the data and concept presented in this manuscript that I consider precluding its publication in the current form.
First, the claim that axon growth is promoted by exosomes is not well supported by the quantifications. It will be more convincing to show the frequency distribution for each experiment rather than the average growth per experiment (e.g., Figure 1F). In the way the data is presented now, we do not learn the real effect of the treatment on axonal growth. For instance, how is the variability in axon length in each experiment? the way the data is presented now might mask variability that could reduce the effect of their treatment
Second, I find it difficult to explain this concept in neurons differentiating in the developing cortex. Which cell type is the source of exosomes mediating axon elongation? Is this cellular mechanism an artifact of the culture condition? In other words, are exosomes relevant for axonal growth in situ?
In the model presented in Figure 7, authors show that fibroblast might mediate axon extension meanwhile activated astrocytes preclude axon extension. Authors do not consider that in the developing cortex, neurons are formed and elongating an axon (while they migrate to the cortical plate) before astrocytes are produced (Noctor et al Nature Neurosci. 2004). How do the authors reconcile this conceptual discrepancy with her in vitro studies? How do the authors reconcile this discrepancy with their studies in situ?
Significance
The authors of this manuscript claim that fibroblast-derived exosomes promote axon growth; meanwhile, exosomes from activated astrocytes inhibit axon elongation. Moreover, the authors claim that exosomes mediate axon elongation throughout the PCP and Wnts pathways.
I have several concerns regarding the data and concept presented in this manuscript that I consider precluding its publication in the current form.
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Referee #1
Evidence, reproducibility and clarity
Ahmad et al. report that exosomes isolated from fibroblast cell lines stimulate neurite extension in cultured neurons while those from neurons or astrocytes do not. They investigate the role of different components from the planar cell polarity (PCP) pathway and conclude that exosomes stimulate autocrine signaling by Wnts in a PCP pathway-dependent manner. However, the inactivation of most PCP components severely reduces neurite length already in untreated controls suggesting that they are required for neurite growth in general rather than specifically for the response to exosomes. The manuscript reports an extensive set of interesting results but does not provide sufficient evidence for the proposed mechanism.
Major points:
- Knockout, knockdown, pharmacological inhibition or blocking antibodies were used to inactivate multiple components of the PCP pathway in cultured neurons. In most cases, the inactivation resulted in a reduction of neurite length both in control cultures and in cultures with exosomes. Because neurons lack the capacity to extend longer neurites after the inactivation of PCP components, it is not possible to determine if they are required for the response to exosomes. Only Fzd7 appears to be specifically required for the effect of exosomes since its knockdown does not reduce neurite length in controls.
- The physiological relevance of the stimulation of neurite growth by exosomes is unclear. It is not explained how cortical neurons come into contact with fibroblasts or the exosomes produced by them as the authors acknowledge at the end of the discussion.
- The mechanism how exosomes stimulate neurite growth remains unclear. The authors suggest that exosomes modulate autocrine Wnt signaling but do not provide sufficient evidence for this. The knockdown of Wntless or Wnts and blocking Wnt secretion by inhibiting Porcupine suppress neurite extension. This phenotype could results from a defect in autocrine signaling but also from a reduced secretion of Wnts into the medium.
- The authors claim that the cell body takes up exosomes that then acquire endogenous Wnt7b. The co-localization of the signals in Fig. 5H is not informative because Wnt7b shows uniform distribution while the CD81-EYFP signal is present in distinct structures that do not show a stronger EYFP signal.
- The specificity of the siRNAs has to be verified by rescue experiments in neurons.
Minor points:
It is not explained why the authors tested exosomes from fibroblasts.
Fig. 7: The graphical summary shows that exosomes somehow enter the soma of neurons. It is not clear if this happens by endocytosis or fusion with the membrane. In either case, the topology of exosomes in the soma is incorrect.
Significance
Ahmad et al. report that exosomes isolated from fibroblast cell lines stimulate neurite extension in cultured neurons while those from neurons or astrocytes do not. They investigate the role of different components from the planar cell polarity (PCP) pathway and conclude that exosomes stimulate autocrine signaling by Wnts in a PCP pathway-dependent manner. However, the inactivation of most PCP components severely reduces neurite length already in untreated controls suggesting that they are required for neurite growth in general rather than specifically for the response to exosomes. The manuscript reports an extensive set of interesting results but does not provide sufficient evidence for the proposed mechanism.
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Reply to the reviewers
Manuscript number: RC-2024-02335
Corresponding authors: Pöhlmann, Stefan & Karsten, Christina B.
1. General Statements
We would like to express our gratitude to Reviewers 1, 2 and 3 for dedicating their time to assess this manuscript and for sharing their invaluable expertise on the subject matter. We have incorporated most of the suggestions made by reviewers but regrettably we were unable to conduct any additional experiments. This is because we chose to work with a single pooled virus stock for both CD4+ T cell and macrophage-derived simian immunodeficiency virus (SIV, T-SIV, M-SIV) throughout the whole study. While this heightened our data quality by omitting donor-induced variations into our virus productions, accurately estimating the total amount of viruses needed for this project was difficult, and at this point we have depleted our reserves of M-SIV and T-SIV. Nevertheless, we are confident that our manuscript has been substantially improved in response to the reviewer’s feedback, and we firmly believe that this study holds considerable implications for the development of new biomedical interventions against the human immunodeficiency virus (HIV).
Please see below our point-by-point responses to the reviewer’s comments and concerns. All manuscript references refer to the revised manuscript, in which the key changes have been tracked.
2. Point-by-point description of the revisions
Reviewer #1:
Major comments:
1 - As noted above, the differences in glycosylation are difficult to understand without more background and perhaps a figure, but it is also not clear that the changes described between lines 119 and 137 are biologically or statistically meaningful. For example, does it matter that more M-SIV virions have glycans with four antennae than T-SIV? Are there other data that show this or could experiments be done to specifically cleave these glycans at certain points to reduce their complexity and show that the infectivity differences between M-SIV and T-SIV disappear? Further, it is difficult to confirm the statement on lines 124-125 that "profiles of complex-type N-glycans differed between the two viruses (Fig. 2C)", as no statistical tests were done to compare the glycosylation being detailed in the M-SIV and T-SIV. It is more appropriate to make note that there are minor between M-SIV and T-SIV or run specific statistical tests on the data.
These are very good remarks. We have introduced a new figure (Fig. 1A) to illustrate the various glycan types, moieties, and structures discussed in the paper. Additionally, we have modified Fig. 1D-G with visualizations of the investigated N-glycans and adjusted and clarified the text to enhance accessibility for experts not specializing in glycobiology (line 62-66, 204-210, 269-273). With our current dataset, we are unable to establish a direct correlation between glycosylation and functional outcomes. Consequently, we can only speculate about the potential impact of certain glycan characteristics on SIV viral functions, a field that remains largely unexplored. Furthermore, due to the absence of remaining virus samples, we are unable to conduct experiments to validate any potential direct relationship between glycosylation patterns and viral functions. It's important to note that no statistical tests were applied to the glycan analysis data, we have now emphasized this in the revised text (line 13-16, 145-149, 250-254).
2 - On line 161, the authors note that the results showing that "the virus-producing cell has a broader impact on SIV infectivity beyond its influence on Env incorporation." This is certainly one possibility that is suggested by these and prior data, there are also other possibilities. For example, the impact of Env is not linear and perhaps a certain number of Env need to be engaged, creating some kind of threshold effect that means that the virions with fewer Env just have less infectivity. Given that there is significant data that virions are generated in different locations in macrophages and T-cells, this could also be a function of which specific membrane areas in different cell types that Env embeds in, or it could be something else associated with Env that is not cell type specific.
We agree and have adapted the text to emphasize that our interpretation is just one possible interpretation, which assumes a linear relationship between Env incorporation and SIV infectivity (line 176-178).
*3 - For the studies in Figure 5, looking at the direct vs. indirect infectivity, it is not clear why CEMx174 R5 cells (a T-cell/B-cell hybrid line) were used instead of primary macrophages or T-cells, or macrophage or T-cell lines or a fully agnostic cell type. This would be more convincing tested on primary cells, or at least comparing in a myeloid lineage line as well. *
In this experiment, we followed a previously published protocol, which utilizes the CEMx174 R5 indicator cell line as target cell for an easy read-out of the results. We agree that the use of the suggested target cell types would be a useful extension of our existing work. Regrettably, due to the lack of remaining viruses, we are unable to fulfil this request.
*4 - In Figure 6, it is not clear that VSV-G pseudotyped virus is an appropriate control, as it enters via the acidified endosome pathway and not via similar processes as the T- and M-SIV derived virions. While this may show that the glycans can bind to CBA to inhibit entry, it could also mean that the general process of endocytosis is not as susceptible to CBA inhibition and this difference in pathways should be noted as a caveat. *
We acknowledge this caveat and have incorporated a statement into the results section to inform readers about the potential impact of differences in the viral uptake pathways between VSV and HIV/SIV (line 219-223).
*5 - A very large number of cell lines were used, and it is not clear why experiments were done using so many different indicator or target lines, instead of performing most assays in a single line or set of lines so that they are comparable across experiments. Some discussion of the rationale for this would be helpful. *
Thank you for bringing your perspective to our attention. By selecting the specific cell lines for our experiments, we have adhered to established norms within our research domain. Specifically, 293T cells, C8166, and TZM-bl cells are standard choices for virus production via transfection, SIV titration, and infectivity assays, respectively. Moreover, in conducting the transmission assay, we followed a previously published protocol. We have revised the text to elucidate the rationale behind our selection of cell lines for different assays, omitted the potentially perplexing reference to the C8166 cell line and included references to support our cell line choices (lines 160-163, 187-188, 215-217, 458-459, 476).
Minor comments
*1 - Inclusion of the p27 data characterizing the amount of virus in M-SIV and T-SIV stocks (line 95) should be shown as at least a supplemental figure or could easily be added to figure 1. *
Agreed. We have included the information about the p27-concentration, and additionally the information about the infectious units and RNA copy numbers of M-SIV and T-SIV into the results section (line 98-101).
3 - The figures are relatively thin and could be combined with other figures to better connect the experiments. For instance, Figure 1 could serve as panel A for what is currently listed as Figure 2 because it is a preliminary data to the experiments in Figure 2.
As suggested by the reviewer, we have combined Fig. 1-2 (now Fig. 1), and additionally Fig. 3-5 (now Fig. 2), and 6-7 (now Fig. 3) to enhance the connections between the experiments.
3 - The authors should include quantitation of the Western blot data in Figure 1 in an adjoining graph.
We appreciate the suggestion. However, the purpose of Fig. 1B (formerly Fig. 1) was to visually represent gp120 of M-SIV and T-SIV following all treatment conditions, which produce bands of varying intensities and widths. Consequently, the bands for PNGaseF-digested gp120 appear relatively thick, which typically hampers accurate quantification. Therefore, we made the decision not to quantify the results of these blots.
*4 - The legend states that the results in Figure 7 were obtained from two independent experiments (line 778), each with 3 technical replicates. As this represents only 2 biological replicates, and the experiments were performed in easily accessible cells (TZM-bl), they should be performed 1 - 3 more times to provide a more appropriate and robust data set for statistical analysis. *
We agree with the reviewer that this might further improve the results but unfortunately, due to the lack of remaining pooled virus from this study, we are unable to fulfill this request.
Reviewer #2:
Major comments:
*It appears to this assessor that some of the supplementary data can be brought to the front as part of the main figures for presentation. *
We appreciate that you consider our supplementary data worthy enough to be part of the main figure set. We have now included Table S1 into the main figure set as Table 1.
CURRENT figures 3, 5, and 7 can be combined into one figure. Similarly, CUREENT Figure 4, and 6 can also be grouped. Alternatively, incorporating additional approaches in each set of figures to tighten the claims.
Agreed. To address this suggestion, we have combined Fig. 1-2 (now Fig. 1), 3-5 (now Fig. 2), and 6-7 (now Fig. 3).
*Karsten et al pitched their story as glycosylation of SIV from different primary cells are linked to different functionality in its title and abstract, yet the authors then declared in discussion (line 318) that establishing a direct link between Env glycosylation and viral functions is technically challenging and beyond the scope of the study. This assessor feels that authors need to decide whether current manuscript should be a descriptive study (which is more fitting for a less impactful journal) or a study with further mechanistic insights. *
Thank you for bringing this to our attention. We have modified the text in the introduction, results, and discussion section to underscore that our work is only suggesting but not directly proving differential glycosylation as cause for functional differences between M-SIV and T-SIV (lines 71-75, 155-157, 211-215, 251-256, 320-322).
*Table S1 is highly important and should be part of the main figure. Specifically, authors took the opportunity to highlight the differential % of sialic acid terminal glycans in line 133. The charge of the sialic acids would be simple mechanism for these M-SIV particle to attach. Authors should consider some of the described nano-luciferase based viral particle attachment assays used in HIV-glycan biology. Authors should be able to treat SIV (or SIV VLPs) with sialidase to quantify the role of sialic acids on binding. *
Thank you for appreciating the details of our glycan analysis. We have now included Supplementary table 1 into the main figure set as Table 1. Due to the lack of remaining virus, we are unable to address the interesting suggestions for further experiments.
*As authors carefully pointed out (throughput the manuscript) that the identity (and biology) of the producer cells can have profound impacts on glycosylation events of viral particles that are being produced. This assessor was then interested to understand precisely how their simian PBMCs and monocytes derived macrophages were prepared. Additional details in M&M would be very helpful. *
We realized that indeed experimental details appeared to be missing in this section since it was not obvious that kits for magnetic bead isolation have been used to isolate the cells, and adapted the text to make this more clear (395-413).
*With the emphasis of cell type and glycosylation relationship, it is puzzling that authors would have chosen to use TZM-bl (artificially engineered cell line) and spinoculation (2hr to push the viruses down to cell surface with 870 x G force) in Figure 3 for comparison of M-SIV and T-SIV infectivity. To this assessor, this assay neglected the biological roles of SIV glycans. In context, 870 x G is ~150x higher than most human can withstand. *
While we appreciate the reviewer’s feedback, we respectfully disagree. The TZM-bl cell line has long been established as the standard cell line for SIV/HIV infectivity assays and neutralization assays in clinical trials (Sarzotti-Kelsoe et al., 2014). In this project, our initial aim was to conduct infectivity assays on a standard cell line before transitioning to more biologically relevant target cells. However, due to limited virus availability, these studies could not be completed and will be addressed in future studies.
The application of methods to increase virus-cell contact to increase cell infection of cell lines is wide-spread in HIV research. Larger virus quantities could have been used instead of spin infection, which would require the introduction of larger amounts of conditioned cell supernatant from the virus production into the experiment with potential influence on the outcomes. Another option would have been to expose the viruses to even stronger forces during ultracentrifugation to concentrate virus stocks, or to employ "sticky" reagents such as DEAE-dextran, which might generate virus aggregates (Davis et al., 2004). Considering these options, we deemed spin infection to have the smallest overall impact on our experiments, while delivering the most robust results.
Finally, we like to note that sensitivity to force between humans and cells is not comparable and cells can withstand much higher forces than humans. We kindly refer reviewer 2 to the work of Kodaka and colleagues. They carefully assessed the efficiency and impact of spin infection using retroviral constructs on primary human cells, and determined that the best conditions were 2,800xg for 90 min considering important parameter’s such as cell viability, proliferation and in vivo differentiation.
Sarzotti-Kelsoe M, Bailer RT, Turk E, Lin CL, Bilska M, Greene KM, Gao H, Todd CA, Ozaki DA, Seaman MS, Mascola JR, Montefiori DC. 2014. Optimization and validation of the tzm-bl assay for standardized assessments of neutralizing antibodies against hiv-1. J Immunol Methods, 409, 131-146. DOI:10.1016/j.jim.2013.11.022.
Davis HE, Rosinski M, Morgan JR, Yarmush ML. Charged polymers modulate retrovirus transduction via membrane charge neutralization and virus aggregation. Biophys J. 2004 Feb;86(2):1234-42. doi: 10.1016/S0006-3495(04)74197-1. PMID: 14747357; PMCID: PMC1303915.
Kodaka Y, Asakura Y, Asakura A. Spin infection enables efficient gene delivery to muscle stem cells. Biotechniques. 2017 Aug 1;63(2):72-76. doi: 10.2144/000114576. PMID: 28803542; PMCID: PMC5768144.
*Using a single antibody DA6 (in Figure 2, cited Edinger 2000) for Env incorporation estimation via Western seems to be crude and inadequate, even in the context of isogenic virus clone. As authors pointed out, different levels of glycosylation can affect protein folding, therefore affecting Env incorporation. By the same argument, differentially glycosylated Env protein can also impact on the ability of 'epitopes within Env protein' to be recognised by Ab. Therefore, virion incorporation of Env might not be affected, but just the detectability by a specific Ab. Western evaluation with a panel of anti-Env antibodies will help. Furthermore, quantitative proteomics coupling with glycomics would be highly useful. *
We respectfully disagree on some points of your assessment. The antibody DA6 specifically targets a linear epitope in gp120 C1 (amino acids 76 to 99 in SIVmac251, Edinger et al., 2000), and the proteins analyzed by Western blot are denatured. Therefore, changes in protein folding due to differential protein glycosylation of SIV in different target cells should not affect the results. We acknowledge the potential impact of differential N-glycan attachment to gp120 based on the virus-producing cell on the binding of primary antibodies in Western blot analysis and agree that this issue could be mitigated by employing a panel or mixture of primary antibodies. However, please note that in Fig. 1B the input virus of M-SIV and T-SIV was normalized based on the signal received for gp120 removed of N-glycans (PNGase F digested). If the differential glycosylation of M-SIV and T-SIV gp120 would interfere with DA6 binding, we should observed noticeable differences between M-SIV and T-SIV in the signal of the undigested and mannose-reduced gp120 (Endo H) but this is not the case. Thus, we believe it is in this case sufficient to use only the antibody DA6 for gp120 detection.
Edinger AL, Ahuja M, Sung T, Baxter KC, Haggarty B, Doms RW, Hoxie JA. 2000. Characterization and epitope mapping of neutralizing monoclonal antibodies produced by immunization with oligomeric simian immunodeficiency virus envelope protein. J Virol, 74(17), 7922-7935.
*It is understood that T-SIV were pooled from supernatant derived from 9 animals of PBMCs. Levels of p27 production (presumed as particles but including free p27 in reality) from each animal donor should be listed in supplement. Similar types of details should be made available for M-SIV that were derived from 8 animal donors of macrophages. qPCR estimations on the levels of viral particles production in T-SIV and M-SIV from primary cell culture amplifications appear to be already available, such information should be included in supplementary to strengthen the authors' estimated / relationships amongst glycosylation, virion Env incorporation levels, and viral particle productions are carefully controlled. *
Thank you for your suggestion. We opted to include only supernatants containing more than 10 ng p27/ml in the pooled virus that constituted M-SIV and T-SIV. Consequently, we did not determine the p27 concentrations of each virus harvests below this threshold. As a result, we are unable to present replication curves for every virus production. However, we are able to provide additional information on the pooled viruses and now included the information about the p27 concentration, infectious units, and genome copy number of M-SIV and T-SIV (line 98-101).
*Non-glycan biologists generally do not appreciate some of the fine details in glycan biology. The T-SIV and M-SIV system is a great model system to decode some of the functionality of glycan biology. The current team should have (in my opinion) a clear graphic representation on describing what types of different glycans in T-SIV and M-SIV are likely to contribute to the potential differences in biological outcomes. Such incorporation will guide non-glycan biologists to better appreciate the focus and the directions of authors, thereby further improving the citation of this work when it is published after peer reviewed. Importantly, focusing a specific question to be addressed may help to consolidate effort to accelerate publication of this work. A beautiful story line, just need to cross many 't' and dot a few 'i' in my view. *
Thank you for sharing the excellent suggestion. We have now incorporated a new figure (Fig-1A) to help the reader with understanding the glycan biology in our manuscript. We have further adapted Fig. 1D-G to include glycan structures to provide a visual representation of the assessed N-glycan subgroups. Finally, we adapted the text throughout the manuscript to improve the reader’s comprehension of our work (line 62-66, 204-210, 269-273).
To address your concerns regarding the clarity of the research question, we revised the text to become more specific (line 155-157, 277-283, 294-300, 317-319, 320-322, 329-338, 364-365).
Most primate centres often incorporate transcriptomic studies in their animal works. It will be helpful for the audience if the authors could provide additional transcriptomic data (with a focus on glycosylation related genes) of simian CD4+ T cells, simian macrophages, SIV infected simian CD4+ T cells, and SIV infected simian macrophages. These data will improve the comprehensiveness of this study (and should not require any major wet-lab studies) and add weight on the arguments of the authors.
This is an interesting suggestion and should be considered in future studies. Here, we choose to focus exclusively on the investigation of the viruses but not the host cell itself. Nevertheless, we discuss the existing transcriptomics data of glycosylation relevant genes in simian CD4+ T cells and macrophages published by Gaskill and colleagues (line 277-287) and find that their results provide explanations for the results of our N-linked glycan analysis of M-SIV and T-SIV.
Gaskill PJ, Zandonatti M, Gilmartin T, Head SR, Fox HS. 2008. Macrophage-derived simian immunodeficiency virus exhibits enhanced infectivity by comparison with t-cell-derived virus. J Virol, 82(3), 1615-1621.
Reviewer #3:
Major comments *1) Line 85 "These substitutions facilitate efficient utilization of CCR5 in the absence or at very low levels of CD4 expression (Puffer et al.2002). This makes the molecular clone studied rather unique and the authors should aim to address this throughout. It does not take away from the results presented but should be addressed. *
Thank you for this suggestion. We included the information about the M-tropism of our viral strain two more times into the manuscript to emphasize this information in the discussion and the limitations of the study (lines 247-249, 345-347).
*2) (Figure 1) State the predicted size differences between T-SIV and M-SIV stocks with EndoH digestion (and similar for all 3 runs?). *
We would have liked to address this suggestion but despite corresponding with other experts and literature research; we were unable to identify a tool, which would allow us to make such predictions.
*3) Line 95 Data should be shown. This describes infectivity and could incorporated within Figure 3 along with infection of the TZM-bl cells. Infectivity of T-SIV and M-SIV on primary CD4 T-cells and macrophages is of importance. This would only be possible I assume if p27 levels were measured at each time-point collected. *
We agree that the manuscript could be extended by virus replication curves on primary cells. However, we chose to include only supernatants with p27 concentrations exceeding 10 ng/ml in the pooled virus comprising M-SIV and T-SIV. Consequently, we did not determine p27-concentrations for virus harvests below this threshold in all cases, preventing us from presenting replication curves for every virus production. We have updated the results section to incorporate the total p27-concentration of M-SIV and T-SIV (lines 98-101). Prior to the submission of this manuscript, we had initiated replication assays of M-SIV and T-SIV on primary rhesus CD4+ T cells and macrophages were initiated but these could not be completed due to the depletion of available virus.
4) There is a lack of statistical difference in the results shown in Figure 2. I assume this is due to a single measurement, but can comment be made on likelihood of biological significance with such difference between values.
Indeed, we did not conduct statistical analysis on this dataset because, given that a single pooled virus for M-SIV and T-SIV was utilized, only one measurement exists. Although we agree with the assessor on the importance of discussing the potential biological significance of the identified glycosylation differences, we are of the opinion that there is currently insufficient evidence in the literature to make scientifically grounded arguments on this matter.
*5) (Figure 3) On TZM-bl cells the T-SIV stock shown 55-fold lower infectivity compared to M-SIV. This is the reverse as to what was found on macaque CD4 T-cells where T-SIV showed a 6.5-fold higher infectivity than M-SIV? Needs addressing. Again, this should be considered in context of the results with CEMx174 R5 cells where infection between the 2 stocks appears to be similar (Figure 6). *
Thank you for raising these points. We like to remark that p27-content and infectivity are not absolutely linked (Narayan et al. 2023). Virus productions also contain empty or non-functional virions and the proportions can differ depending on the virus producer cell. Thus, T-SIV having a lower infectivity per ng 27 is likely a result of cell type dependent variation in the proportion of non-functional virions and does not represent an inconsistent result.
Kedhar Narayan, Jeongpill Choi, Shreyas S. Gujar, Aidan McGraw, Hasset Tibebe, Lilia Mei Bose, Caroline N. Arnette, Taisuke Izumi, Identifying Discrepancies in HIV Infectivity and Virion Maturation Using FRET-Based Detection and Quantification, bioRxiv 2023.12.25.573317; doi: https://doi.org/10.1101/2023.12.25.573317
*6) (Figure 5) The result may look cleaner if No Lectin value is subtracted from the cell lines carrying the lectin expression? *
Agreed. We have adapted the figure (Fig. 2D) as suggested.
*7) A much clearer introduction to CBA's would be beneficial. *
We agree that this would improve our manuscript and have expanded the introduction on carbohydrate binding agents (lines 204-210).
8) A concern I have is the presentation of data in Figures 6 and 7, especially given that the cell line used is the TZM-bl cell which has been shown to be 55-fold less infectible with T-SIV. Plotting the results as % infectivity on the same graph could be somewhat misleading. Two graphs one panel for M-SIV and one for T-SIV may be easier to follow. The CEMx174 cell line may have been a better choice as similarity to infection was found? But assume those experiments were not performed?
We kindly ask reviewer 3 to note that the virus input in these experiments has been normalized for equal infectivity, as described in the figure legend. An example demonstrating the comparability of results obtained using this method can be observed in Figure 2A, right panel, which justifies our approach. While we agree that conducting neutralization assays on additional cell types might be a valuable extension of the existing work, we chose here to use the TZM-bl cell line, the standard cell line for neutralization assays in the field of HIV research (Sarzotti-Kelsoe, 2013).
Sarzotti-Kelsoe M, Bailer RT, Turk E, Lin CL, Bilska M, Greene KM, Gao H, Todd CA, Ozaki DA, Seaman MS, Mascola JR, Montefiori DC. 2014. Optimization and validation of the tzm-bl assay for standardized assessments of neutralizing antibodies against hiv-1. J Immunol Methods, 409, 131-146. DOI:10.1016/j.jim.2013.11.022.
*9) I do feel the Discussion is extremely long and could be stream-lined to make it clearer and to the point. *
To follow your valuable suggestion, we reduced the length of the discussion by approximately one-third and eliminated sections that were less directly related to our results.
10) Materials and Methods section. Is the first section on Animal studies required. Could this not just be cited if it has been previously published.
While we agree that a manuscript should be as compact as possible, we decided to include this information to ensure complete transparency regarding our animal experiments. Additionally, many journals request this information prior to publication. Consequently, we opt to retain the text in its current form.
Minor comments *1) A) needs to be removed from Figure legend 1. *
Please note that we have not addressed this suggestion since Fig. 1 is now a multi-graph figure.
*2) Line 160 I assume this the result from (Fig 3A). *
That is correct. We have included the figure reference to make this line of text more clear.
*3) Line 255-257 Difficult sentence to understand. *
Thank you for making this point. This sentence has been removed in our efforts to shorten the discussion.
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Referee #3
Evidence, reproducibility and clarity
Summary
In this manuscript the authors have studied a variety of phenotype of two generated viral stocks of SIVmac239/316 molecular cloned virus generated in either CD4 T-cells (T-SIV) and macrophages (M-SIV). These stocks are isogenic apart from the cell type produced in and are identical in Env amino acid sequence. Stocks generated from the different cell-types were found to alter EndoH digestion, mannose profiling, infectivity, Env incorporation and lectin interactions and sensitivity to CBS and monkey sera neutralisation. The claim is that producer cell-type can influence SIV biological properties that associate with viral transmission, dissemination and inhibition.
Major comments
- Line 85 "These substitutions facilitate efficient utilization of CCR5 in the absence or at very low levels of CD4 expression (Puffer et al.2002). This makes the molecular clone studied rather unique and the authors should aim to address this throughout. It does not take away from the results presented but should be addressed.
- (Figure 1) State the predicted size differences between T-SIV and M-SIV stocks with EndoH digestion (and similar for all 3 runs?).
- Line 95 Data should be shown. This describes infectivity and could incorporated within Figure 3 along with infection of the TZM-bl cells. Infectivity of T-SIV and M-SIV on primary CD4 T-cells and macrophages is of importance. This would only be possible I assume if p27 levels were measured at each time-point collected.
- There is a lack of statistical difference in the results shown in Figure 2. I assume this is due to a single measurement, but can comment be made on likelihood of biological significance with such difference between values.
- (Figure 3) On TZM-bl cells the T-SIV stock shown 55-fold lower infectivity compared to M-SIV. This is the reverse as to what was found on macaque CD4 T-cells where T-SIV showed a 6.5-fold higher infectivity than M-SIV? Needs addressing. Again, this should be considered in context of the results with CEMx174 R5 cells where infection between the 2 stocks appears to be similar (Figure 6).
- (Figure 5) The result may look cleaner if No Lectin value is subtracted from the cell lines carrying the lectin expression?
- A much clearer introduction to CBA's would be beneficial.
- A concern I have is the presentation of data in Figures 6 and 7, especially given that the cell line used is the TZM-bl cell which has been shown to be 55-fold less infectible with T-SIV. Plotting the results as % infectivity on the same graph could be somewhat misleading. Two graphs one panel for M-SIV and one for T-SIV may be easier to follow. The CEMx174 cell line may have been a better choice as similarity to infection was found? But assume those experiments were not performed?
- I do feel the Discussion is extremely long and could be stream-lined to make it clearer and to the point.
- Materials and Methods section. Is the first section on Animal studies required. Could this not just be cited if it has been previously published.
Minor comments
- A) needs to be removed from Figure legend 1.
- Line 160 I assume this the result from (Fig 3A).
- Line 255-257 Difficult sentence to understand.
Significance
This is an interesting study and where there is significance for understanding how HIV/SIV viral phenotypes (those associated with transmission and emergence following transmssion) can be influenced by the cell type infected and modifications to glycosylation profiling).
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Referee #2
Evidence, reproducibility and clarity
Assessment for Karsten et al
In this manuscript, Karsten et al described the biology of simian macrophage derived SIV and simian CD4+ T cells derived SIV have different levels and types of glycosylation in their particles. The authors attributed that these differences in glycosylation are related to SIV function (infection / spread).
It appears to this assessor that some of the supplementary data can be brought to the front as part of the main figures for presentation.
CURRENT figures 3, 5, and 7 can be combined into one figure.
Similarly, CUREENT Figure 4, and 6 can also be grouped.
Alternatively, incorporating additional approaches in each set of figures to tighten the claims.
I would support the manuscript for its eventual publication, but I believe several major (but achievable) amendments are needed.
Major suggestions
Karsten et al pitched their story as glycosylation of SIV from different primary cells are linked to different functionality in its title and abstract, yet the authors then declared in discussion (line 318) that establishing a direct link between Env glycosylation and viral functions is technically challenging and beyond the scope of the study. This assessor feels that authors need to decide whether current manuscript should be a descriptive study (which is more fitting for a less impactful journal) or a study with further mechanistic insights.
Table S1 is highly important and should be part of the main figure. Specifically, authors took the opportunity to highlight the differential % of sialic acid terminal glycans in line 133. The charge of the sialic acids would be simple mechanism for these M-SIV particle to attach. Authors should consider some of the described nano-luciferase based viral particle attachment assays used in HIV-glycan biology. Authors should be able to treat SIV (or SIV VLPs) with sialidase to quantify the role of sialic acids on binding.
As authors carefully pointed out (throughput the manuscript) that the identity (and biology) of the producer cells can have profound impacts on glycosylation events of viral particles that are being produced. This assessor was then interested to understand precisely how their simian PBMCs and monocytes derived macrophages were prepared. Additional details in M&M would be very helpful.
With the emphasis of cell type and glycosylation relationship, it is puzzling that authors would have chosen to use TZM-bl (artificially engineered cell line) and spinoculation (2hr to push the viruses down to cell surface with 870 x G force) in Figure 3 for comparison of M-SIV and T-SIV infectivity. To this assessor, this assay neglected the biological roles of SIV glycans. In context, 870 x G is ~150x higher than most human can withstand.
Using a single antibody DA6 (in Figure 4, cited Edinger 2000) for Env incorporation estimation via Western seems to be crude and inadequate, even in the context of isogenic virus clone. As authors pointed out, different levels of glycosylation can affect protein folding, therefore affecting Env incorporation. By the same argument, differentially glycosylated Env protein can also impact on the ability of 'epitopes within Env protein' to be recognised by Ab. Therefore, virion incorporation of Env might not be affected, but just the detectability by a specific Ab. Western evaluation with a panel of anti-Env antibodies will help. Furthermore, quantitative proteomics coupling with glycomics would be highly useful.
It is understood that T-SIV were pooled from supernatant derived from 9 animals of PBMCs. Levels of p27 production (presumed as particles but including free p27 in reality) from each animal donor should be listed in supplement. Similar types of details should be made available for M-SIV that were derived from 8 animal donors of macrophages. qPCR estimations on the levels of viral particles production in T-SIV and M-SIV from primary cell culture amplifications appear to be already available, such information should be included in supplementary to strengthen the authors' estimated / relationships amongst glycosylation, virion Env incorporation levels, and viral particle productions are carefully controlled.
Non-glycan biologists generally do not appreciate some of the fine details in glycan biology. The T-SIV and M-SIV system is a great model system to decode some of the functionality of glycan biology. The current team should have (in my opinion) a clear graphic representation on describing what types of different glycans in T-SIV and M-SIV are likely to contribute to the potential differences in biological outcomes. Such incorporation will guide non-glycan biologists to better appreciate the focus and the directions of authors, thereby further improving the citation of this work when it is published after peer reviewed. Importantly, focusing a specific question to be addressed may help to consolidate effort to accelerate publication of this work. A beautiful story line, just need to cross many 't' and dot a few 'i' in my view.
Most primate centres often incorporate transcriptomic studies in their animal works. It will be helpful for the audience if the authors could provide additional transcriptomic data (with a focus on glycosylation related genes) of simian CD4+ T cells, simian macrophages, SIV infected simian CD4+ T cells, and SIV infected simian macrophages. These data will improve the comprehensiveness of this study (and should not require any major wet-lab studies) and add weight on the arguments of the authors.
Significance
General Assessment - The biological significance system these authors possess is highly valuable in virology and will reveal significant insights in the functions of glycans in infectious diseases. Authors are generally (in my opinion) correct with the big picture impacts / contributions of glycan biology. Presented experimentations need to be tighter controlled to avoid over-interpretations. A tighter focus of research question (or claim) will reduce levels of extra work prior to publication.
Advance - level of advance will be high regarding the role of glycan in biology and infectious diseases. The T-SIV and M-SIV system is a naturally relevant system with many prior works that lay the foundation to understand viral glycan biology.
Audience - with the right pitch and proper explanations, general audience will be highly interested. At the end of the day, glycan biology is shared amongst all living cells.
My expertise is in virology, particular in HIV. I also have a strong interest in glycan biology. I described the first glycan-glycan interaction in viral pathogenesis recently, explaining how these glycan-based interaction serves as a molecular Velcro for attachment, likely a shared mechanism in virology and biology in general.
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Referee #1
Evidence, reproducibility and clarity
This is interesting data and will add to the relatively sparse literature in this area, but there are several issues limiting its utility and accessibility, and other data, experiments or explanations are needed to address these issues. The other major issue is that there is no direct experimental evidence showing specifically that the glycosylation being described, particularly the differences in T-SIV vs. M-SIV, as there had been in some of the prior studies. Specifically removing or adding particular glycans, and then showing changed effects on viral entry - particularly in primary cells - would add substantively to the findings and make this a much stronger study. In addition, there are a number of other more specific and/or minor changes that could be made to enhance the value of this manuscript.
- As noted above, the differences in glycosylation are difficult to understand without more background and perhaps a figure, but it is also not clear that the changes described between lines 119 and 137 are biologically or statistically meaningful. For example, does it matter that more M-SIV virions have glycans with four antennae than T-SIV? Are there other data that show this or could experiments be done to specifically cleave these glycans at certain points to reduce their complexity and show that the infectivity differences between M-SIV and T-SIV disappear? Further, it is difficult to confirm the statement on lines 124-125 that "profiles of complex-type N-glycans differed between the two viruses (Fig. 2C)", as no statistical tests were done to compare the glycosylation being detailed in the M-SIV and T-SIV. It is more appropriate to make note that there are minor between M-SIV and T-SIV or run specific statistical tests on the data.
- On line 161, the authors note that the results showing that "the virus-producing cell has a broader impact on SIV infectivity beyond its influence on Env incorporation." This is certainly one possibility that is suggested by these and prior data, there are also other possibilities. For example, the impact of Env is not linear and perhaps a certain number of Env need to be engaged, creating some kind of threshold effect that means that the virions with fewer Env just have less infectivity. Given that there is significant data that virions are generated in different locations in macrophages and T-cells, this could also be a function of which specific membrane areas in different cell types that Env embeds in, or it could be something else associated with Env that is not cell type specific.
- For the studies in Figure 5, looking at the direct vs. indirect infectivity, it is not clear why CEMx174 R5 cells (a T-cell/B-cell hybrid line) were used instead of primary macrophages or T-cells, or macrophage or T-cell lines or a fully agnostic cell type. This would be more convincing tested on primary cells, or at least comparing in a myeloid lineage line as well.
- In Figure 6, it is not clear that VSV-G pseudotyped virus is an appropriate control, as it enters via the acidified endosome pathway and not via similar processes as the T- and M-SIV derived virions. While this may show that the glycans can bind to CBA to inhibit entry, it could also mean that the general process of endocytosis is not as susceptible to CBA inhibition and this difference in pathways should be noted as a caveat.
- A very large number of cell lines were used, and it is not clear why experiments were done using so many different indicator or target lines, instead of performing most assays in a single line or set of lines so that they are comparable across experiments. Some discussion of the rationale for this would be helpful.
Minor comments
- Inclusion of the p27 data characterizing the amount of virus in M-SIV and T-SIV stocks (line 95) should be shown as at least a supplemental figure or could easily be added to figure 1.
- The figures are relatively thin and could be combined with other figures to better connect the experiments. For instance, Figure 1 could serve as panel A for what is currently listed as Figure 2 because it is a preliminary data to the experiments in Figure 2.
- The authors should include quantitation of the Western blot data in Figure 1 in an adjoining graph.
- The legend states that the results in Figure 7 were obtained from two independent experiments (line 778), each with 3 technical replicates. As this represents only 2 biological replicates, and the experiments were performed in easily accessible cells (TZM-bl), they should be performed 1 - 3 more times to provide a more appropriate and robust data set for statistical analysis.
Significance
The manuscript Karsten et. al., 2024, discusses the differences in infectivity resulting from the cellular origin of SIV virions, specifically comparing virus generated in macrophages and T-cells. The primary focus of this comparison is the differences in glycosylation of the Env proteins on the virions with a T-cell origin (T-SIV) and a macrophage origin (M-SIV). These studies are expansions of a small number of prior publications that focus on this area and are cited extensively. The major innovation in this study were that the differences in glycan composition were assessed using xCGE-LIF glycan profiling, which is more detailed than the glycan profiling methods in the prior studies. Then the T-SIV and M-SIV were compared for their susceptibility to distinct carbohydrate binding agents, either ulex europaeus agglutinin (UEA), cyanovirin-N (CV-N), or galanthus nivalis agglutinin (GNA). These agents each bind different glycans, so differences in the capacity of these agents to bind T-SIV vs. M-SIV suggest confirming the presence of different types of glycans. Similar studies with serum from SIV infected macaques, the results suggesting some differences in susceptibility to neutralization in viruses of different cellular origin.
One primary issue is that many readers will not be familiar with the different types of glycosylation, the differences between subtypes of glycans, different branches, etc ... and what the biological relevance of these differences is to viral infection and/or immune activity. For example, the discussion refers to M5, M6, M8 and M9 on T-SIV vs. M-SIV (lines 234 - 5) but knowledge of these is not universal and there is no background to place these statements in context and understand why this might matter. To address this, additional language is needed, as well as the addition of a figure that helps to visualize the different glycans being discussed. Adding this to the beginning as part of the introduction, or at the end as a summary of the findings in the paper, would increase accessibility for a broader audience.
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Reply to the reviewers
We would like to thank both reviewers for their thorough and constructive evaluation and comments on our manuscript. Following their suggestions, we have edited our manuscript to address all criticisms and comments from them. We hope that, with these introduced changes, this manuscript will be suitable for publication in an appropriate journal. Detailed point-to-point responses are shown below.
__Point-to-point response to reviewers’ critiques: __
Reviewer 1
Summary: Stadler and colleagues characterized CFAP410, using molecular structural biology, biophysics, biochemistry, cellular imaging and genetic engineering, to address molecular mechanism of ciliopathies caused by defect of this protein. They crystalized the C-terminal domain of CFAP410 and its homologue, from Trypanosoma, human and Chlamydomonas. All of them take tetrameric complex formation with four bundle helices in the center. Then they mutated highly conserved residues, L219 and L224, which are located at the helix bundle, and characterized its biophysical properties, demonstrating oligomerization defect and, in case of L224 mutation, collapse of secondary structure as well. This was supported by molecular dynamics. Next they examined the effect of these mutation in vivo using Trypanosoma brucei. They visualized the localization of CFAP410 at the postrior cell tip and its transfer to the basal body. By mutation, transfer of CFAP410 is prohibited and cytokinesis defect occurs. The experiments are logically designed and the results are clearly and convincingly stated. Undoubtedly this work deserves publication after minor revision of the manuscript.
Strength:* This is a compact paper, clearly stating the biological aim and experiments designed for that.
Limitation: While it is undoubtedly proved that the C-terminal domain of CFAP410 forms tetramer and L219 and L224 are key residues and that mutation of these residues causes severe defect at the localization of CFAP410, it is an overstatement to conclude the tetramer formation is essential for the localization. The authors experiments cannot exclude the possibility of another consequence of mutation (different from origomerization), which is the cause of abnormal localization.
*
: Indeed, the reason for the disrupted localization of the disease-causing mutation L224P to the basal body could be caused by mis-folding of TbCFAP410 if that is the only mutation we had tested. However, as shown in our results, the point mutation A267E of TbCFAP410 that breaks the tetramer into two dimers (so as Hs/Cr-CFAP410-A219E) did not change its folding or structural stability. Nevertheless, TbCFAP410-A267E lost its ability to localize to the basal body effectively (Figure 6A). It suggests that even a folded dimer is insufficient to correctly localize to the basal body. Therefore, we can confidently conclude that the fully assembled tetramer of CFAP410 is required for its localization to the basal body.
* Minor points: p.7: It would be interesting, if the authors, beside MD, attempt to predict conformation of the mutants using Alphafold2. *
: We tried to predict conformational changes of the point mutations of CFAP410 via AlphaFold2, but did not observe significant changes in the generated models. It was not so surprising to us though, because, as shown previously, although experimentally point mutations induced complete unfolding of some proteins, the AlphaFold2 models of the same point mutants folded similarly to the wild-type crystal structures (Buel & Walters, 2022, Nat. Struct. Mol. Biol. 29:1-2.)
* p.7-8: A cartoon to describe what proteins exist between the posterior tip and the basal body will help readers to understand. Do the authors have any thought how CFAP410 is transported to the basal body? *
: We thank the reviewer for the suggestion and have revised Figure 7 to illustrate the two distinct localization sites of CFAP410 in T. brucei.
We do not know the mechanism through which CFAP410 localizes to the posterior cell tip and the basal body. Both structures are microtubule based, with the basal body consisting of a barrel of microtubule triplets and the posterior cell tip is the site at which the ends of the microtubules which form the sub-pellicular array in T. brucei are located. This suggests that CFAP410 could interact with microtubules or microtubule binding proteins in these locations. Additionally, in human cells CFAP410 appears to interact with NEK1 and the equivalent interaction in trypanosomes may be important for CFAP410 localization. We have refined our ideas on this in the Discussion section (p.11): “It was shown previously that the L224P mutant of CFAP410 abolishes its interaction with NEK1 [4]. Given that the mutant L224P disassembles the tetramer of CFAP410-CTD (Figure 3), the tetrameric assembly of CFAP410 seems to play an essential role in its interaction with NEK1. Therefore, the disrupted location of TbCFAP410-L272P to the basal body we observed here could be attributed to its abolished interaction with the trypanosome equivalent of NEK1 as occurs in human cells. However, we cannot exclude another possibility that CFAP410 localizes to the basal body by interacting with an unidentified anchoring target there and NEK1 is subsequently recruited via its binding to CFAP410.”
It is worth mentioning though that the localization of TbCFAP410 to the posterior cell tip has only been reported in T. brucei and no other cellular localization sites have been reported for CFAP410 orthologs in other organisms including human. Moreover, in the genome-wide protein tagging project TrypTag many other proteins were found to localize to both the posterior tip and another site in the cell, including the basal body (Billington et al, 2023, Nat. Microbiol. 8: 533-547). The following paragraph discussing about this has been added to the Discussion section (p. 10): “Notably, recent genome-wide protein localizations revealed that the posterior cell tip in T. brucei has unexpectedly high complexity and contains many proteins that also localize to other organelles _[16]_. The tip may thus serve as a “moonlighting” site for those proteins. However, the extra localization site of CFAP410 at the cell tip has only been reported in T. brucei and no other cellular localization sites have been observed for CFAP410 in any other organisms.”
* p.10: Can the authors define "NTD linker" precisely (from which to which residues)? *
: We have defined the sequence range of both the NTD (aa1-160) and NTD-linker (aa1-254) of TbCFAP410 both in the text (p. 9 & p. 10) and legend of Figure 6.
* p.12: Alphafold-multimer may help to have information, which part of CFAP410 is likely interface to NEK1 and SPATA7. *
: We attempted to predict how CFAP410 interacts with NEK1 or SPATA7 by Alphafold-multimer. Results of the former prediction, which are consistent with previous studies (Gregorczyk et al, 2023, Life Sci. Alliance), have been added as a new figure (Figure S4). However, no convincing results were obtained for the latter pair.
* p.16: The paragraph starting with "DSF measurements were ..." is probably not necessary. Figure 4 caption: "HsCFP0-CTD" should be defined precisely. Or is it a typo of HsCFAP410-CTD? *
: We thank the reviewer for pointing out this mistake. This paragraph has been removed.
* Figure 5ad, Figure 6: blue is not defined.
*
: We have now defined blue in the figure legends for 5A, D and 6A. These cells have been counterstained with the DNA stain Hoechst 33342 to highlight the nucleus and kinetoplast (mitochondrial DNA) and this is the blue element in the images.
* Advances: This interdisciplenary work nicely characterized CFAP410 at atomic, molecular and cellular levels and acquired insight of its functional mechanism. *
: We appreciate the reviewer’s constructive comments and positive feedback.
Reviewer 2
*In this paper, the authors described 3 crystal structures of the CTD of CFAP410 from 3 different species. They explored the phenotype mutation L224P in humans which causes ciliopathies using in vitro and in vivo analysis. They were able to explain the oligomerization role of the L224P mutations and its importance for correct localization. In addition, using their structure, they also found A219 as an important residue for tetramerization as well. The paper is well-written and easier to read. *
* __There are some minor concerns: __
- Fig. 5C: Why would the line reduce to lower value at 24hr, 48hr for both non-induced and induced one. *
: During routine culture of T. brucei, we had to split the cells to ensure they do not overgrow and are maintained in log phase growth. The reduction in value at each time point represents the cell splitting event and gives these characteristic “sawtooth” graphs for cell growth. At each time point the cell density is measured and then the cells (both non-induced and induced) are diluted to the same cell density, in this case 2x106 cells/ml, and grown for a further 24 hours before the next measurement.
*2. The authors wrote "Although we observed only little change in the average distance from the posterior cell tip to kinetoplast in 1K1N cytoskeletons after induction, there was a substantial increase in the range of these measurements, with cytoskeletons observed having a more reduced or increased distance from the kinetoplast to the posterior cell tip (Figure 5F)." *
*Why not back the wide range with a standard deviation calculation in the figure caption of 5F or display the std dev directly in the figure if it looks good? Also, the author can include legends for color dots in the figure as Replicate 1,2,3 for easy reading/comprehension. *
: We have included the standard deviations for each of the replicates in 5F in the figure legend. The spread of data is shown in the figure already with the individual points and the overlay of the standard deviation was not clear when we tried it. We have now included a legend for the dots in the figure as suggested.
*3.The information about the construct of Trypanosoma used for Figure 6 is not described at all. What exactly is the region of the construct of the NTD and NTD-linker? *
: The following sentence has been added to the legend of Figure 6: “Except for NTD (aa1-168) and NTD-linker (aa1-254), all other constructs are full-length proteins.”
*4. The author wrote "In the mutant A267E, the mNG::CFAP410 signal was exclusively found at the posterior of most cytoskeletons (63.5%), while full-length TbCFAP410-L272P and the two CTD-lacking constructs, NTD and NTD-linker ... This suggests that both the presence of the CTD and the integrity of its oligomerization are essential for the interaction of TbCFAP410 with the basal body and posterior cell tip." *
*This statement needs to be revised a bit. First, seems like the tetramerization is important for the localization, not dimerization. Second, is there any evidence that full-length TbCFAP410-L272P folds properly? Without the evidence that the NTD and NTD-linker region can fold properly in both full-length TbCFAP410-L272P and CTD truncation, it is not possible to exclude that the N-terminal is essential for the localization as well. *
: Thanks for the comments. We have managed to express and purify TbCFAP410-NTD, which shows that it folds properly on its own. We further checked whether NTD directly interacts with CTD, but ended up with negative results. The following part has been added to the last paragraph of the Results section to address the reviewer’s question. “We found that TbCFAP410-NTD folded properly on its own when expressed in bacteria, and no direct interaction between NTD and CTD was detected (data now shown). It suggests that the two structural modules of TbCFAP410 that are connected by a long disordered linker are folded independently. Therefore, we conclude that the localization of TbCFAP410 to the basal body and the posterior cell tip requires the CTD and its ability to oligomerize.”
* Small things: 1. It is worth define 1K1N, 2K1N and 2kK2N stages in the text for reader not in Trypanosoma field.
*: We have explained the KN nomenclature, and how during the cell cycle the kinetoplast and nucleus are duplicated and segregated in a defined order.
*2.Fig. 5C: label Non-induced black & induced orange as legends directly in the figure so readers don't have to read the Figure captions.
*: This has been done as suggested.
*3. In Methods, there is the part about DSF measurement in the Molecular Dynamic (MD) simulations *
: This paragraph is unnecessary and has been removed. We thank the reviewer for pointing it out.
4.* Abbreviation not defined: DSF (in Methods/MD simulations). Also, the molecular dynamics phrase appears well before the abbreviation MD in the Methods section. *
: As stated above, this paragraph has been removed.
*
Reviewer #2 (Significance (Required)):
Overall I found the methodology and results of the paper solid, and the interpretation and conclusion are sound. *
*The paper addresses the molecular mechanism of a mutation in CFAP410 resulting in severe spondylometaphyseal dysplasia, axial. *
* The audience of the paper should be the cilia field but also the paper is also good for other researchers as the paper is easy to read.*
: We appreciate the reviewer’s constructive feedback and positive evaluation.
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Referee #2
Evidence, reproducibility and clarity
In this paper, the authors described 3 crystal structures of the CTD of CFAP410 from 3 different species. They explored the phenotype mutation L224P in humans which causes ciliopathies using in vitro and in vivo analysis. They were able to explain the oligomerization role of the L224P mutations and its importance for correct localization. In addition, using their structure, they also found A219 as an important residue for tetramerization as well. The paper is well-written and easier to read.
There are some minor concerns:
- Fig. 5C: Why would the line reduce to lower value at 24hr, 48hr for both non-induced and induced one.
- The authors wrote "Although we observed only little change in the average distance from the posterior cell tip to kinetoplast in 1K1N cytoskeletons after induction, there was a substantial increase in the range of these measurements, with cytoskeletons observed having a more reduced or increased distance from the kinetoplast to the posterior cell tip (Figure 5F)."
Why not back the wide range with a standard deviation calculation in the figure caption of 5F or display the std dev directly in the figure if it looks good? Also, the author can include legends for color dots in the figure as Replicate 1,2,3 for easy reading/comprehension. 3. The information about the construct of Trypanosoma used for Figure 6 is not described at all. What exactly is the region of the construct of the NTD and NTD-linker? 4. The author wrote "In the mutant A267E, the mNG::CFAP410 signal was exclusively found at the posterior of most cytoskeletons (63.5%), while full-length TbCFAP410-L272P and the two CTD-lacking constructs, NTD and NTD-linker ... This suggests that both the presence of the CTD and the integrity of its oligomerization are essential for the interaction of TbCFAP410 with the basal body and posterior cell tip."
This statement needs to be revised a bit. First, seems like the tetramerization is important for the localization, not dimerization. Second, is there any evidence that full-length TbCFAP410-L272P folds properly? Without the evidence that the NTD and NTD-linker region can fold properly in both full-length TbCFAP410-L272P and CTD truncation, it is not possible to exclude that the N-terminal is essential for the localization as well.
Small things:
- It is worth define 1K1N, 2K1N and 2kK2N stages in the text for reader not in Trypanosoma field.
- Fig. 5C: label Non-induced black & induced orange as legends directly in the figure so readers don't have to read the Figure captions.
- In Methods, there is the part about DSF measurement in the Molecular Dynamic (MD) simulations
- Abbreviation not defined: DSF (in Methods/MD simulations). Also, the molecular dynamics phrase appears well before the abbreviation MD in the Methods section.
Significance
Overall I found the methodology and results of the paper solid, and the interpretation and conclusion are sound.
The paper addresses the molecular mechanism of a mutation in CFAP410 resulting in severe spondylometaphyseal dysplasia, axial.
The audience of the paper should be the cilia field but also the paper is also good for other researchers as the paper is easy to read.
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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 #1
Evidence, reproducibility and clarity
Summary: Stadler and colleagues characterized CFAP410, using molecular structural biology, biophysics, biochemistry, cellular imaging and genetic engineering, to address molecular mechanism of ciliopathies caused by defect of this protein. They crystalized the C-terminal domain of CFAP410 and its homologue, from Trypanosoma, human and Chlamydomonas. All of them take tetrameric complex formation with four bundle helices in the center. Then they mutated highly conserved residues, L219 and L224, which are located at the helix bundle, and characterized its biophysical properties, demonstrating oligomerization defect and, in case of L224 mutation, collapse of secondary structure as well. This was supported by molecular dynamics. Next they examined the effect of these mutation in vivo using Trypanosoma brucei. They visualized the localization of CFAP410 at the postrior cell tip and its transfer to the basal body. By mutation, transfer of CFAP410 is prohibited and cytokinesis defect occurs.
The experiments are logically designed and the results are clearly and convincingly stated. Undoubtedly this work deserves publication after minor revision of the manuscript.
Significance
strength: This is a compact paper, clearly stating the biological aim and experiments designed for that.
Limitation: While it is undoubtedly proved that the C-terminal domain of CFAP410 forms tetramer and L219 and L224 are key residues and that mutation of these residues causes severe defect at the localization of CFAP410, it is an overstatement to conclude the tetramer formation is essential for the localization. The authors experiments cannot exclude the possibility of another consequence of mutation (different from origomerization), which is the cause of abnormal localization.
Minor points:
p.7: It would be interesting, if the authors, beside MD, attempt to predict conformation of the mutants using Alphafold2.
p.7-8: A cartoon to describe what proteins exist between the posterior tip and the basal body will help readers to understand. Do the authors have any thought how CFAP410 is transported to the basal body?
p.10: Can the authors define "NTD linker" precisely (from which to which residues)?
p.12: Alphafold-multimer may help to have information, which part of CFAP410 is likely interface to NEK1 and SPATA7.
p.16: The paragraph starting with "DSF measurements were ..." is probably not necessary.
Figure 4 caption: "HsCFP0-CTD" should be defined precisely. Or is it a typo of HsCFAP410-CTD?
Figure 5ad, Figure 6: blue is not defined.
advances: This interdisciplenary work nicely characterized CFAP410 at atomic, molecular and cellular levels and acquired insight of its functional mechanism.
audience: cilia community
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Reply to the reviewers
1. General Statements
Regarding significance, we would like to highlight that the main finding and breakthrough of our manuscript is the discovery that intronic polyadenylation (IPA) isoforms are a source of microproteins (indeed, IPA was not known to induce sORF-encoded microproteins). We make the proof of principle of this concept (called miP-5’UTR-IPA) and of its functional relevance for one gene (PRKAR1B).
A second finding of this study is that IPA (including miP-5’UTR-IPA) isoforms are widely upregulated in cell response to cisplatin, and therefore we show the functional relevance of miP-5’UTR-IPA isoforms in this biological context.
Regarding the generality of the miP-5’UTR-IPA concept, we provide evidence that many genes generate miP-5’UTR-IPA isoforms, by crossing our 3’-seq data with available Ribo-Seq and mass spectrometry datasets, which were generated without cisplatin treatment. Also, the miP-5’UTR-IPA isoforms of PHF20 and PRKAR1B are detected both in the presence and absence of cisplatin. Thus, the novel concept of microprotein-coding IPA isoforms opens wide perspectives, way beyond cisplatin response.
2. Description of the planned revisions
REVIEWER #1
Evidence, reproducibility and clarity
Microporteins originating from coding and non-coding transcript are increasingly understood to control various cellular processes. In the present study, the authors investigated whether intronic polyadenylation (IPA) contributes to the formation of transcript isoforms encoding microproteins. Using genotoxic stress by cisplatin as a model in cell cultures, the authors detect abundant IPA. IPA in a subset of such transcripts leads to short 5'UTR transcript isoforms that are poorly associated with heavy polysomes and encode microproteins. For PRKAR1B, they demonstrate the expression of a corresponding microprotein and a function in modulating the cisplatin response. Based on depletion experiments of FANCD2 and STX1, the authors propose that impaired transcription processivity after cisplatin is one mechanism leading to IPA and microprotein production.
While this is an interesting manuscript, I felt the support for the claimed generalization falls a bit short.
Our response: The generality of the miP-5’UTR-IPA concept is supported by the large-scale analysis that we presented (Fig. 6): indeed, by crossing our 3’-seq data with Ribo-Seq and MS data (both of which originate from multiple cell types and tissues), we identified 156 genes with cisplatin-regulated miP-5’UTR-IPA isoforms. To strengthen this part and highlight the generality of the miP-5’UTR-IPA concept, we will provide the cell type/ tissue distribution of our set of 156 miP-5’UTR-IPA isoforms, by exploiting available 3’-seq datasets from various cells/tissues. (Please also see major point 1 below.)
Major:
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- If I see it correctly, the authors mainly refer to existing riboSeq data and evidence from mass spectrometry/proteomics to infer the generality of the mechanism (beyond PRKAR1B). It is important to back this up with further experiments and validate this for the set-up used in this manuscript. This concerns the existence of the microproteins but also the downstream functional impact. Our response: In our study, we make the proof of principle of miP-5’UTR-IPA (that is, a microprotein-encoding IPA isoform) for the PRKAR1B gene and its sORF#2 (microprotein detection by WB and IF, functional evidence by siRNA and CRISPR of IPA site and sORF initiation codon). If I understand well (also based on minor point 3 below), this reviewer is requesting further evidence of microprotein existence (in addition to Ribo-Seq and mass spectrometry [MS] data) and function, for a second IPA-derived sORF that we study in this manuscript (either PHF20 sORF or PRKAR1B sORF#1). To the best of our knowledge, a proof of principle for a new concept is usually done on a single gene. Nevertheless, for the miP-5’UTR-IPA isoform of PHF20*, we already provided evidence for its function by using siRNAs (Fig. 3A-C) and for its translation by polysome profiling (Fig. 4C) in addition to Ribo-Seq and MS evidence (Fig. 4A). The fact that for PHF20 we did not detect the transfected Flag-tagged microprotein in HEK cells could be due to several reasons (as discussed on page 16); __we will __try this approach again with different biological conditions (cell lines, stress) or construct designs (as the sORF context may be important).
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Also, I wonder is this limited to cisplatin-induced genotoxic stress and the specific cell line used or is this a more global mechanism?*
Our response: We provided evidence of IPA isoform regulation by cisplatin in two lung cancer cell lines (A549 and H358; Fig. 1A-B) but we agree that our analyses of miP-5’UTR-IPA were mainly done in A549 cells. We will: (i) clarify that we detected the miP-5’UTR-IPA isoforms of PRKAR1B and PHF20 in A549 cells (total cytosol and light polysomes) both in the presence and absence of cisplatin (Fig. 2D, 3A and S3D); (ii) add RT-qPCR validation of their cisplatin regulation in H358 cells; (iii) try to detect the PRKAR1B-encoded microprotein in a second cell line (Fig. 4); (iv) test the impact of PRKAR1B and PHF20 miP-5’UTR-IPA isoforms on cell survival in a second cell line and with a second genotoxic agent; (v) clarify in Fig. 6 that miP-5’UTR-IPA isoforms are regulated by cisplatin in both A549 and H358 cells (our 3’-seq data) and that the Ribo-Seq and MS datasets supporting their translation originate from multiple cell types and tissues without cisplatin treatment; and (vi) provide the cell type/ tissue distribution of our set of 156 miP-5’UTR-IPA isoforms (by exploiting available 3’-seq datasets from various cells/tissues).
Minor:
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- While the rest of the paper reads well, the abstract could be improved/simplified to increase accessibility* Our response: We will improve the abstract.
Page 11: Pertaining to Figure 3 and the functional impact: The authors analyze the IPA effect by probing cell viability and cell survival. It would be important to define the effects in further detail, as the mere regulation of cell cycle and/or apoptosis could also result in such outcome (which is then not necessarily a direct cisplatin response). Does this also impact the response to other genotoxic stress (also pertains to the effects studied and shown in Fig. 5)?
Our response: Because cisplatin effects on cell growth are usually mediated by effects on cell cycle and cell death, we will determine which aspect is impacted by PRKAR1B and PHF20 miP-5’UTR-IPA isoforms, by carrying out FACS analysis of PI/BrdU and Annexin V (both in the presence and absence of cisplatin). As mentioned in major point 2, we will also test the impact of these isoforms on cell survival to a second genotoxic agent.
Page 12 concerning the microprotein expression: the authors refer to data from other resources to claim that the microproteins are expressed, however they fail to demonstrate this for their setup (at least for 2 out of three they study here). I think this is a weak point as it does not directly support the general claim.
Our response: Please see major point 1 above.
Also, I did not understand what the authors intended to demonstrate with the immunoflourescence (Fig. 4E). What should a defined nuclear expression imply versus the diffuse staining throughout after cisplatin? How does this relate to the functional effects?
Our response: We included in Fig. 4E the observation that the subcellular localization of the PRKAR1B-encoded micropotein is altered in response to cisplatin, because this supports the notion that this micropotein plays a role in cell response to cisplatin. We can remove this data if requested.
Page 13/Fig. 5E: the different clones of the mATG show very high variability. To my understanding it is difficult to draw a clear conclusion from this heterogeneity.
Our response: The statistical analysis shows a significant difference between the mATG and Control groups (p Page 15 on the mechanism: SETX has been demonstrated to control poly(A) site choice (PMID: 21700224, 32976578). However the quantitative role of SETX in poly(A) site choice regulation (compared to other regulators) seems to be rather marginal and not strictly unidirectional, i.e after SETX depletion also longer transcript isoforms can be detected (PMID: 32976578). How does this relate to the proposed mechanism of SETX-dependent processivity? Interestingly, from PMID: 32976578 it also appears that PRKAR1A has a 5'UTR poly(A) site that is regulated in a SETX-dependent manner.
Our response: We will add in the discussion statements that (i) the role of SETX in cisplatin regulation of IPA:LE isoform ratio and processivity might be different from its role in APA regulation in the absence of genotoxic treatment (citing PMID 32976578; keeping in mind that we did not compare them side by side on a genome-wide scale) and (ii) PRKAR1A seems to have a 5'UTR poly(A) site regulated by SETX in TREND-DB (PMID 32976578).
- Page 16, discussion first paragraph. While refs 1-4 are nice reviews that could be quoted here a study that appeared later represents the most comprehensive analysis to date covering the different facets from transcription to RNA processing and the resulting impact on poly(A) site choice (PMID: 30552333).*
Our response: We will cite PMID 30552333 and 32976578 as resources of APA regulation by various regulators of gene expression (keeping in mind, however, that for most factors these studies do not exclude indirect effects).
Significance
This could be a very significant report, provided the generality of the claims and mechanistic insigths are further strengthend.
Overall it targets a rather specialized readership. This could be improved by simplifing the abstract, additional experimental evidence for the generality of the proposed mechanism, and a stringent rewording of the main text drawing a clear line, omitting unnecessary details and focussing on the novel findings.
Our response: Please see our responses above. In addition, we will reword the main text where necessary.
REVIEWER #2
Evidence, reproducibility and clarity
Summary:
*In this manuscript, Devaux et al. report that the anti-cancer drug cisplatin upregulates intronic polyadenylation (IPA) isoforms in non-small cell lung cancer cell lines. Their finding was based on 3' end sequencing and long-read sequencing. Through polysome profiling they confirmed that many of the IPA isoforms are translated, despite being inefficient in most cases. *
Our response: There is some misunderstanding here. We will clarify in the text that inefficient association with heavy polysomes is observed for a minority (not the majority) of IPA isoforms. For this, in Fig. 2B and S2A, we will add the information that for the majority of IPA sites, the IPA:LE ratio is not significantly different (neither up or down) between total cytosol and heavy polysomes.
They validated functions of IPA isoforms from two genes, PHF20 and PRKAR1B, in cell survival upon cisplatin treatment, based on an array of methods, including siRNA knockdown, CRISPR knockout of IPA polyA site, and CRISPR mutation of the start codon. They further found that FANCD2 and Senataxin can regulate cisplatin-mediated IPA activation. The authors advocate a new paradigm of expression of IPA-encoding microproteins in cisplatin-treated cells.
Our response: We would like to point out that our data indicate that cisplatin upregulation of the IPA:LE isoform ratio is mediated at least in part by an inhibition of transcription processivity (explaining the decrease of LE isoforms), and that we do not claim an ‘IPA activation’ (that is, enhanced used of IPA sites) by cisplatin. This remark is also related to major point 1 below.
Major comments:
-
- While the phenomenon of IPA isoform upregulation by Cisplatin is quite convincing, the underlying mechanism is largely elusive. The authors indicated processivity as a potential mechanism and the effects of FACD2 and Senataxin appear in line with this hypothesis. However, they cannot rule out other possibilities based on the data presented in the manuscript. For example, it is not clear if the elongation rate of Pol II (distinct from its processivity) or nuclear RNA degradation is affected by cisplatin, which could also lead to increased expression of IPA isoforms. In addition, enhanced 3' end processing activity has been previously shown to activate IPA sites. Therefore, the underlying mechanism is mostly speculative. Our response: As explained on page 14, the reason why we focused on transcription processivity is that the cisplatin-induced upregulation of the IPA:LE isoform ratio was enriched in long genes and was accompanied by a decrease of LE isoform levels. Importantly, our data (e.g., for the PHF20 and PRKAR1B genes) indicate that the cisplatin-induced decrease of processivity explains –at least in part– the selective decrease of the LE but not IPA isoform levels and therefore the increase of the IPA:LE isoform ratio; we will clarify this in the manuscript (on pages 14 and 15). Our data also show that cisplatin effects on both processivity and IPA:LE isoform ratio are dependent on FANCD2 and SETX. We agree with the reviewer that we cannot exclude that IPA:LE isoform ratio upregulation by cisplatin might also be mediated in part by additional mechanisms (e.g.*, ‘factors involved in cleavage/ polyadenylation, splicing, transcription elongation and termination, and epigenetic marks’, as mentioned in the discussion on page 16) and we will add nuclear RNA degradation to the list of potential factors. However, we want to emphasize that the role of processivity is not speculative.
The authors used the polysome:cytosolic ratio to indicate translational efficiency. However, because the CDS size affects the number of ribosomes per mRNA, the translational efficiency should be based on polysome:cytosolic ratio normalized to CDS size. Ideally, the authors should calculate number of ribosome per transcript based on monosome, light polysome and heavy polysome.
Our response: We cannot normalize ribosome number by CDS size because (i) heavy polysomes are not a precise number of ribosomes and (ii) sORFs are not annotated as CDS.
The functions of PHF20 and PRKAR1B IPA isoforms are based on knockdown or knockout mutations. Because of its gain-of-function property, overexpression of the isoforms in cisplatin-treated cells would be necessary to definitively confirm their funcitons.
Our response: For PRKAR1B sORF#2, we ____will carry out overexpression of the sORF microprotein in A549 cells and CRISPR clones and analyze its effects on cell growth and cisplatin survival. We have appropriate constructs for this.
Minor:
-
- Fig. 1H, the numbers of IPA and LE transcripts should be provided. The statistical significance for the difference should also be included.* Our response: The numbers of IPA and LE transcripts were provided in Fig. S1I and we will provide the statistical significance (which is good), as requested.
Fig. 1I, the image should be accompanied with fold difference as indicated in the text. Some statistics for difference between vehicle only and CisPt only is necessary.
Our response: We will indicate the fold differences and provide the statistical significance, as requested.
- Fig. 6, the authors did data mining of ribo-seq data and mass-spec data and identified 156 genes whose IPA isoforms have potentials of protein expression. The enriched GO terms for the 156 IPA genes are different than the overall IPA isoforms shown in Fig. 1C. Does this mean some genes, like those in DNA damage stimulus, produce IPA isoforms with different consequences, such as to inhibit their expression? *
Our response: We think it is difficult to compare the enriched GO terms between overall IPA and miP-5’UTR-IPA. Indeed, differences could be due in part to trivial reasons (e.g., different number of genes in the lists). As suggested by this reviewer, it could be that for some gene sets enriched in particular functions, IPA may serve to downregulate the expression level of the full-length (canonical) mRNA. We discuss that this may be the case for the PRIM2 gene involved in DNA replication (page 17), but expanding on this would be speculative. Likewise, IPA isoforms encoding carboxy-terminal isoforms of canonical proteins, or IPA isoforms with a noncoding function (like ASCC3 or SPUD), might be enriched in particular gene functions, but again this idea is speculative and it goes beyond the scope of our manuscript.
In addition, the authors need to use ribo-seq and mass spec data as a validation tool for their polysome profiling data to indicate the reliability of using polysome data to call protein expression.
Our response: This comment seems to concern those IPA isoforms that are abundant in heavy polysomes. We do not wish to validate protein production from such isoforms, because they are not the focus of our study.
Significance
The significance of this work is its novelty in reporting IPA isoform activation by cisplatin. More importantly, some IPA isoform give rise to microproteins that have functional roles in cell survival upon cisplatin treatment.
Our response: We would like to highlight that the main finding of our manuscript is the discovery that IPA isoforms are a source of microproteins. Cisplatin response is the biological context in which we did the study, and therefore our functional and mechanistic analyses.
REVIEWER #3
Evidence, reproducibility and clarity
Devaux et al. report how cisplatin treatment changes the abundance of mRNA isoforms, favoring the expression of short transcripts originating from intronic polyadenylation (IPA) events relative to the expression of the corresponding mRNA isoform that includes the last annotated exon (LE). To detect IPA events the authors performed 3' end sequencing of polyadenylated mRNAs, long-read sequencing and conventional total RNA sequencing experiments in control and cisplatin treated cells. Analysis of the 3' end sequencing data revealed numerous genes showing an increase in the IPA:LE ratio upon cisplatin treatment, whereas few events with a decreased IPA:LE ratio were detected. Many of the identified events could be corroborated by the long-read sequencing data, sequencing of total RNA, and an existing polyA database. Furthermore, the authors validate IPA:LE ratios for a few selected genes using quantitative PCR. Subsequently, the authors continue to analyze if IPA isoforms are translated with a specific focus on IPA isoforms that do not contain any parts of the LE isoform coding sequence but terminated transcription in what is annotated as 5' untranslated region (UTR). These experiments show that IPA isoforms (including 5' UTR-IPAs) are translated but frequently associated with fewer ribosomes than the corresponding LE isoform. For two selected 5' UTR-IPA isoforms the authors identified potential small open reading frames (sORFs) that could give rise to microproteins with a potential function during cisplatin treatment. siRNA experiments targeting either the 5' UTR-IPA or the LE mRNA isoform of selected genes identified a small but significant differential effect on cell viability upon cisplatin treatment. Similar results were obtained when the endogenous IPA locus was deleted or the start codon of the potential sORF was mutated. Finally, the authors shed some light onto the molecular mechanisms of how cisplatin affects the IPA:LE ratio by decreasing transcription processivity.
*This is an interesting manuscript suggesting a link between IPA, sORFs and cancer treatment. The manuscript offers valuable datasets as a resource for the research community. While the authors generally present a well-analyzed and validated dataset supporting their claims, some aspects require further evidence or clearer presentation for robustness and reader comprehension. In addition, the manuscript would benefit from improving data visualization and we have several suggestions (see below) on how to make the representation of the data in the figures more appealing to the reader. We encourage the authors to reconsider several of their bar plots and instead plot their data on a continuous axis, e.g. using a scatter plot (fold change versus FDR) instead of a bar chart that can only represent up/down total numbers. *
Our response: Please see our responses below.
Main points:
-
- We disagree with one of the data interpretations concerning the high polysome (HP) versus total cytosolic polysomes (cytosol) localized IPA and LE mRNA isoforms in the paragraph "A subset of IPA isoforms are depleted in heavy polysomes and terminate in the annotated 5'UTR part of genes". Preferential IPA isoform localization to cytosol versus HP in comparison to the LE isoform does not mean that the IPA isoform translation efficiency is lower than that of the LE isoform. It just reflects the fact that IPA isoform coding sequence is considerably shorter than the coding sequence of the LE isoform (and thus can accommodate fewer ribosomes!). The authors mention that point later in the text but it should already be made clear at this point in the manuscript. They should make sure not to confuse translation efficiency (ribosome density across an open reading frame) and open reading frame length. * Our response: We will modify the text of this section (pages 10-11). We will __state that ‘the HP:cytosol ratio is usually considered as a proxy for translation efficiency’ and __we will only make conclusions in terms of ‘HP:cytosol ratio’ or ‘HP recruitment efficiency’, instead of ‘translation efficiency’ (we had used this term in a few sentences for the sake of simplicity). Please note that these changes will not alter the main conclusion of this part, because both the title (‘a subset of IPA isoforms are depleted in heavy polysomes and terminate in the annotated 5'UTR part of genes’) and the end of this section (page 11), as well as the legend of Fig. 2, were already written in such terms. Thus, in this section, we do not need to discuss ORF length (and we cannot, because sORFs are not annotated as CDS and we introduce sORFs only two sections later [Fig. 4]).
-
In Figure 5, the authors claim that the "cisplatin survival phenotype of the PRKAR1B 5'UTR-IPA isoform is attributable to its small ORF#2". This is an interesting phenotype but the authors only present a WST1 assay to support these claims. Given that it is an important Figure in their manuscript and links the observations made earlier to cisplatin-induced survival, it would be critical to bolster these claims with additional data, e.g. AnnexinV/PI staining and flow cytometry to distinguish changes in cisplatin-induced apoptosis from proliferation.*
Our response: We will make the requested experiments with FACS analysis of Annexin V and PI/BrdU to distinguish changes in cisplatin-induced apoptosis from proliferation (cell cycle).
- Along the same line, it would be important to test the overexpression of the sORF microprotein upon cisplatin treatment. Changes in the mRNA sequence (such as the AUG mutation) could potentially also alter the mRNA structure. It would therefore be critical to show that the sORF microprotein is indeed responsible for the changes in cisplatin-induced viability (for instance by expression of a sORF::P2A::GFP construct). *
Our response: As requested, we will test whether overexpression of the sORF microprotein can rescue the cisplatin survival phenotype of our PRKAR1B IPA and ATG mutants. We have appropriate constructs for this.
- Figure 5C: Please show the Western blot of PRKAR1B and GAPDH and not just the quantification. There is plenty of space in Figure 5. *
Our response: We will show the Western blots for PRKAR1B and GAPDH.
- In the following, we list suggestions to improve different figures where the data could be more adequately presented:*
- Figure 1A and B: We suggest representing the data in a scatter plot log fold change on the x-axis and FDR on the y-axis. The authors decided for an FDR cutoff of 10%. This is quite high. Why did the authors decide for this cutoff? How many genes would be identified with a more stringent cutoff (1% for example)? Please list the corresponding FDR values in TableS4.
Our response: We have never seen in the literature 3’-seq (or related) data of IPA:LE ratio regulation plotted as a scatter plot with log fold change on the x-axis and FDR on the y-axis. Instead, we propose to provide scatter plots with IPA fold change on the x-axis and LE fold change on the y-axis, as in many previous studies. We were not very stringent on the FDR or adjusted p values, in order to reduce the rate of false negatives, because we then cross our lists of regulated IPAs in different compartments (e.g., cytosol and heavy polysomes; Fig. 2C). We provided adjusted p values in Table S4; with an adjusted p value of 1%, we observe 1986 upregulated IPA sites and 33 downregulated ones.
*-Figure 1C: There are many ways to visualize fold change, p value and number of genes of a GO term analysis. The authors could choose one of the common ways to represent such data instead of just showing raw numbers in a table. *
Our response: We like showing GO terms as tables, but we can provide a figure if necessary.
-Figure 1E-G: Add to the figure that PRIM2 was assayed. It is only written in the figure legend.
Our response: We will write ‘PRIM2’ in the figure.
*-Figure 2A and B: Same suggestion as for Figure 1A and B, a scatter plot log fold change on the x-axis and FDR on the y-axis would visualize the data much better. *
Our response: Same response as for Fig 1A-B above.
-Figure S1B: Where does the number of 2118 cisplatin regulated genes come from? It was not described anywhere else. Should it not be 1987 regulated genes?
Our response: We will clarify that 2118 is the union of genes with cisplatin upregulated IPA:LE ratio in H358 and/or A549 cells.
-Figure S1H: Typo in the y-axis.
Our response: This typo will be corrected, thanks.
-Figure S2A: Same suggestion as for Figure 1A and B, a scatter plot log fold change on the x-axis and FDR on the y-axis.
Our response: Same response as for Fig 1A-B above.
-Figure S3C: If possible, show the plotted digital data of the polysome curves.
Our response: We do not have digital data for the polysome curves, just the printed graph shown at the bottom of the figure.
- Data availability: The provided UCSC genome browser link unfortunately does not load the data bam files. Please fix.*
Our response: We will fix this upon submission to journal.
Minor points:
- Please check the text for typos, e.g. page 8: artefacts instead of artifacts. *
Our response: We will check for typos.
Significance
The manuscript describes an interesting link between intronic polyadenylation, sORFs and cancer treatment and will be of interest to the gene expression regulation and RNA communities. As a relatively unknown mechanism to induce sORF-encoded microproteins, the study could lead to follow-up studies tackling intronic polyadenylation and their role in sORF expression.
Our response: We would like to highlight that IPA was not previously known to induce sORF-encoded microproteins.
While the authors generally present a well-analyzed and validated dataset, the link between sORF function and cisplatin response will require additional experiments to strengthen the sORF's impact for cellular survival.
Our response: Please see our responses to main points 2 and 3 above.
3. Description of the revisions that have already been incorporated in the transferred manuscript
None.
4. Description of analyses that authors prefer not to carry out
REVIEWER #2
Major point #2: The authors used the polysome:cytosolic ratio to indicate translational efficiency. However, because the CDS size affects the number of ribosomes per mRNA, the translational efficiency should be based on polysome:cytosolic ratio normalized to CDS size. Ideally, the authors should calculate number of ribosome per transcript based on monosome, light polysome and heavy polysome.
Our response: We cannot normalize ribosome number by CDS size because (i) heavy polysomes are not a precise number of ribosomes and (ii) sORFs are not annotated as CDS.
*Minor point #3: Fig. 6, the authors did data mining of ribo-seq data and mass-spec data and identified 156 genes whose IPA isoforms have potentials of protein expression. The enriched GO terms for the 156 IPA genes are different than the overall IPA isoforms shown in Fig. 1C. Does this mean some genes, like those in DNA damage stimulus, produce IPA isoforms with different consequences, such as to inhibit their expression? *
Our response: We think it is difficult to compare the enriched GO terms between overall IPA and miP-5’UTR-IPA. Indeed, differences could be due in part to trivial reasons (e.g., different number of genes in the lists). As suggested by this reviewer, it could be that for some gene sets enriched in particular functions, IPA may serve to downregulate the expression level of the full-length (canonical) mRNA. We discuss that this may be the case for the PRIM2 gene involved in DNA replication (page 17), but expanding on this would be speculative. Likewise, IPA isoforms encoding carboxy-terminal isoforms of canonical proteins, or IPA isoforms with a noncoding function (like ASCC3 or SPUD), might be enriched in particular gene functions, but again this idea is speculative and it goes beyond the scope of our manuscript.
In addition, the authors need to use ribo-seq and mass spec data as a validation tool for their polysome profiling data to indicate the reliability of using polysome data to call protein expression.
Our response: This comment seems to concern those IPA isoforms that are abundant in heavy polysomes. We do not wish to validate protein production from such isoforms, because they are not the focus of our study.
REVIEWER #3
-Figure S3C: If possible, show the plotted digital data of the polysome curves.
Our response: We do not have digital data for the polysome curves, just the printed graph shown at the bottom of the figure.
-
-
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Referee #3
Evidence, reproducibility and clarity
Devaux et al. report how cisplatin treatment changes the abundance of mRNA isoforms, favoring the expression of short transcripts originating from intronic polyadenylation (IPA) events relative to the expression of the corresponding mRNA isoform that includes the last annotated exon (LE). To detect IPA events the authors performed 3' end sequencing of polyadenylated mRNAs, long-read sequencing and conventional total RNA sequencing experiments in control and cisplatin treated cells. Analysis of the 3' end sequencing data revealed numerous genes showing an increase in the IPA:LE ratio upon cisplatin treatment, whereas few events with a decreased IPA:LE ratio were detected. Many of the identified events could be corroborated by the long-read sequencing data, sequencing of total RNA, and an existing polyA database. Furthermore, the authors validate IPA:LE ratios for a few selected genes using quantitative PCR. Subsequently, the authors continue to analyze if IPA isoforms are translated with a specific focus on IPA isoforms that do not contain any parts of the LE isoform coding sequence but terminated transcription in what is annotated as 5' untranslated region (UTR). These experiments show that IPA isoforms (including 5' UTR-IPAs) are translated but frequently associated with fewer ribosomes than the corresponding LE isoform. For two selected 5' UTR-IPA isoforms the authors identified potential small open reading frames (sORFs) that could give rise to microproteins with a potential function during cisplatin treatment. siRNA experiments targeting either the 5' UTR-IPA or the LE mRNA isoform of selected genes identified a small but significant differential effect on cell viability upon cisplatin treatment. Similar results were obtained when the endogenous IPA locus was deleted or the start codon of the potential sORF was mutated. Finally, the authors shed some light onto the molecular mechanisms of how cisplatin affects the IPA:LE ratio by decreasing transcription processivity.
This is an interesting manuscript suggesting a link between IPA, sORFs and cancer treatment. The manuscript offers valuable datasets as a resource for the research community. While the authors generally present a well-analyzed and validated dataset supporting their claims, some aspects require further evidence or clearer presentation for robustness and reader comprehension. In addition, the manuscript would benefit from improving data visualization and we have several suggestions (see below) on how to make the representation of the data in the figures more appealing to the reader. We encourage the authors to reconsider several of their bar plots and instead plot their data on a continuous axis, e.g. using a scatter plot (fold change versus FDR) instead of a bar chart that can only represent up/down total numbers.
Main points:
- We disagree with one of the data interpretations concerning the high polysome (HP) versus total cytosolic polysomes (cytosol) localized IPA and LE mRNA isoforms in the paragraph "A subset of IPA isoforms are depleted in heavy polysomes and terminate in the annotated 5'UTR part of genes". Preferential IPA isoform localization to cytosol versus HP in comparison to the LE isoform does not mean that the IPA isoform translation efficiency is lower than that of the LE isoform. It just reflects the fact that IPA isoform coding sequence is considerably shorter than the coding sequence of the LE isoform (and thus can accommodate fewer ribosomes!). The authors mention that point later in the text but it should already be made clear at this point in the manuscript. They should make sure not to confuse translation efficiency (ribosome density across an open reading frame) and open reading frame length.
- In Figure 5, the authors claim that the "cisplatin survival phenotype of the PRKAR1B 5'UTR-IPA isoform is attributable to its small ORF#2". This is an interesting phenotype but the authors only present a WST1 assay to support these claims. Given that it is an important Figure in their manuscript and links the observations made earlier to cisplatin-induced survival, it would be critical to bolster these claims with additional data, e.g. AnnexinV/PI staining and flow cytometry to distinguish changes in cisplatin-induced apoptosis from proliferation.
- Along the same line, it would be important to test the overexpression of the sORF microprotein upon cisplatin treatment. Changes in the mRNA sequence (such as the AUG mutation) could potentially also alter the mRNA structure. It would therefore be critical to show that the sORF microprotein is indeed responsible for the changes in cisplatin-induced viability (for instance by expression of a sORF::P2A::GFP construct).
- Figure 5C: Please show the Western blot of PRKAR1B and GAPDH and not just the quantification. There is plenty of space in Figure 5.
-
In the following, we list suggestions to improve different figures where the data could be more adequately presented:
- Figure 1A and B: We suggest representing the data in a scatter plot log fold change on the x-axis and FDR on the y-axis. The authors decided for an FDR cutoff of 10%. This is quite high. Why did the authors decide for this cutoff? How many genes would be identified with a more stringent cutoff (1% for example)? Please list the corresponding FDR values in TableS4.
- Figure 1C: There are many ways to visualize fold change, p value and number of genes of a GO term analysis. The authors could choose one of the common ways to represent such data instead of just showing raw numbers in a table.
- Figure 1E-G: Add to the figure that PRIM2 was assayed. It is only written in the figure legend.
- Figure 2A and B: Same suggestion as for Figure 1A and B, a scatter plot log fold change on the x-axis and FDR on the y-axis would visualize the data much better.
- Figure S1B: Where does the number of 2118 cisplatin regulated genes come from? It was not described anywhere else. Should it not be 1987 regulated genes?
- Figure S1H: Typo in the y-axis.
- Figure S2A: Same suggestion as for Figure 1A and B, a scatter plot log fold change on the x-axis and FDR on the y-axis.
- Figure S3C: If possible, show the plotted digital data of the polysome curves.
- Data availability: The provided UCSC genome browser link unfortunately does not load the data bam files. Please fix.
Minor points:
- Please check the text for typos, e.g. page 8: artefacts instead of artifacts.
Significance
The manuscript describes an interesting link between intronic polyadenylation, sORFs and cancer treatment and will be of interest to the gene expression regulation and RNA communities. As a relatively unknown mechanism to induce sORF-encoded microproteins, the study could lead to follow-up studies tackling intronic polyadenylation and their role in sORF expression.
While the authors generally present a well-analyzed and validated dataset, the link between sORF function and cisplatin response will require additional experiments to strengthen the sORF's impact for cellular survival.
-
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Referee #2
Evidence, reproducibility and clarity
Summary:
In this manuscript, Devaux et al. report that the anti-cancer drug cisplatin upregulates intronic polyadenylation (IPA) isoforms in non-small cell lung cancer cell lines. Their finding was based on 3' end sequencing and long-read sequencing. Through polysome profiling they confirmed that many of the IPA isoforms are translated, despite being inefficient in most cases. They validated functions of IPA isoforms from two genes, PHF20 and PRKAR1B, in cell survival upon cisplatin treatment, based on an array of methods, including siRNA knockdown, CRISPR knockout of IPA polyA site, and CRISPR mutation of the start codon. They further found that FANCD2 and Senataxin can regulate cisplatin-mediated IPA activation. The authors advocate a new paradigm of expression of IPA-encoding microproteins in cisplatin-treated cells.
Major comments:
- While the phenomenon of IPA isoform upregulation by Cisplatin is quite convincing, the underlying mechanism is largely elusive. The authors indicated processivity as a potential mechanism and the effects of FACD2 and Senataxin appear in line with this hypothesis. However, they cannot rule out other possibilities based on the data presented in the manuscript. For example, it is not clear if the elongation rate of Pol II (distinct from its processivity) or nuclear RNA degradation is affected by cisplatin, which could also lead to increased expression of IPA isoforms. In addition, enhanced 3' end processing activity has been previously shown to activate IPA sites. Therefore, the underlying mechanism is mostly speculative.
- The authors used the polysome:cytosolic ratio to indicate translational efficiency. However, because the CDS size affects the number of ribosomes per mRNA, the translational efficiency should be based on polysome:cytosolic ratio normalized to CDS size. Ideally, the authors should calculate number of ribosome per transcript based on monosome, light polysome and heavy polysome.
- The functions of PHF20 and PRKAR1B IPA isoforms are based on knockdown or knockout mutations. Because of its gain-of-function property, overexpression of the isoforms in cisplatin-treated cells would be necessary to definitively confirm their funcitons.
Minor:
Fig. 1H, the numbers of IPA and LE transcripts should be provided. The statistical significance for the difference should also be included.
Fig. 1I, the image should be accompanied with fold difference as indicated in the text. Some statistics for difference between vehicle only and CisPt only is necessary.
Fig. 6, the authors did data mining of ribo-seq data and mass-spec data and identified 156 genes whose IPA isoforms have potentials of protein expression. The enriched GO terms for the 156 IPA genes are different than the overall IPA isoforms shown in Fig. 1C. Does this mean some genes, like those in DNA damage stimulus, produce IPA isoforms with different consequences, such as to inhibit their expression? In addition, the authors need to use ribo-seq and mass spec data as a validation tool for their polysome profiling data to indicate the reliability of using polysome data to call protein expression.
Significance
The significance of this work is its novelty in reporting IPA isoform activation by cisplatin. More importantly, some IPA isoform give rise to microproteins that have functional roles in cell survival upon cisplatin treatment.
-
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Referee #1
Evidence, reproducibility and clarity
Microporteins originating from coding and non-coding transcript are increasingly understood to control various cellular processes. In the present study, the authors investigated whether intronic polyadenylation (IPA) contributes to the formation of transcript isoforms encoding microproteins. Using genotoxic stress by cisplatin as a model in cell cultures, the authors detect abundant IPA. IPA in a subset of such transcripts leads to short 5'UTR transcript isoforms that are poorly associated with heavy polysomes and encode microproteins. For PRKAR1B, they demonstrate the expression of a corresponding microprotein and a function in modulating the cisplatin response. Based on depletion experiments of FANCD2 and STX1, the authors propose that impaired transcription processivity after cisplatin is one mechanism leading to IPA and microprotein production.
While this is an interesting manuscript, I felt the support for the claimed generalization falls a bit short.
Major:
If I see it correctly, the authors mainly refer to existing riboSeq data and evidence from mass spectrometry/proteomics to infer the generality of the mechanism (beyond PRKAR1B). It is important to back this up with further experiments and validate this for the set-up used in this manuscript. This concerns the existence of the microproteins but also the downstream functional impact.
Also, I wonder is this limited to cisplatin-induced genotoxic stress and the specific cell line used or is this a more global mechanism?
Minor:
- While the rest of the paper reads well, the abstract could be improved/simplified to increase accessibility
- Page 11: Pertaining to Figure 3 and the functional impact: The authors analyze the IPA effect by probing cell viability and cell survival. It would be important to define the effects in further detail, as the mere regulation of cell cycle and/or apoptosis could also result in such outcome (which is then not necessarily a direct cisplatin response). Does this also impact the response to other genotoxic stress (also pertains to the effects studied and shown in Fig. 5)?
- Page 11: Pertaining to Figure 3 and the functional impact: The authors analyze the IPA effect by probing cell viability and cell survival. It would be important to define the effects in further detail, as the mere regulation of cell cycle and/or apoptosis could also result in such outcome (which is then not necessarily a direct cisplatin response). Does this also impact the response to other genotoxic stress (also pertains to the effects studied and shown in Fig. 5)?
- Page 12 concerning the microprotein expression: the authors refer to data from other resources to claim that the microproteins are expressed, however they fail to demonstrate this for their setup (at least for 2 out of three they study here). I think this is a weak point as it does not directly support the general claim.
- Also, I did not understand what the authors intended to demonstrate with the immunoflourescence (Fig. 4E). What should a defined nuclear expression imply versus the diffuse staining throughout after cisplatin? How does this relate to the functional effects?
- Page 13/Fig. 5E: the different clones of the mATG show very high variability. To my understanding it is difficult to draw a clear conclusion from this heterogeneity.
- Page 15 on the mechanism: SETX has been demonstrated to control poly(A) site choice (PMID: 21700224, 32976578). However the quantitative role of SETX in poly(A) site choice regulation (compared to other regulators) seems to be rather marginal and not strictly unidirectional, i.e after SETX depletion also longer transcript isoforms can be detected (PMID: 32976578). How does this relate to the proposed mechanism of SETX-dependent processivity? Interestingly, from PMID: 32976578 it also appears that PRKAR1A has a 5'UTR poly(A) site that is regulated in a SETX-dependent manner.
- Page 16, discussion first paragraph. While refs 1-4 are nice reviews that could be quoted here a study that appeared later represents the most comprehensive analysis to date covering the different facets from transcription to RNA processing and the resulting impact on poly(A) site choice (PMID: 30552333).
Significance
This could be a very significant report, provided the generality of the claims and mechanistic insigths are further strengthend.
Overall it targets a rather specialized readership. This could be improved by simplifing the abstract, additional experimental evidence for the generality of the proposed mechanism, and a stringent rewording of the main text drawing a clear line, omitting unnecessary details and focussing on the novel findings.
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Reply to the reviewers
Manuscript number: RC-2023-02232
Corresponding author(s): Shinji, Saiki and Nobutaka, Hattori
1. General Statements [optional]
Thank you for the review of our paper entitled “Identification of novel autophagy inducers by accelerating lysosomal clustering against Parkinson's disease” (RC-2023-02232). We have carefully read the critiques and planed experiments. Below we include point-by-point responses to the questions raised by the reviewers. We have also carried out some experiments and highlighted the revised sentences in the transferred manuscript in red. The numbers of pages and lines are indicated based on the MS Word transferred manuscript. We believe this revision plans appropriately addresses the issues raised by Reviewers. Finally, all the authors would like to thank again the Editor and Reviewers for improving our manuscript by providing their invaluable comments and suggestions.
Point-by-point description of the revisions
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Reviewer #1 (Evidence, reproducibility and clarity (Required)):
The manuscript by Date et al employed a cell model by stably expressing LGP120-mCherry and GFP-gamma-tubulin to carry out high-content screening in search of chemical compounds that enhance lysosomal clustering and autophagy. They found 6 clinically approved drugs categorized as topoisomerase II inhibitors and the benzimidazole class. They further validated these compounds by a set of well-designed experiments including autophagy flux assays and mTOR dependence. In the mechanistic study, they demonstrated the compounds induce lysosomal clustering in a JIP4-TRPML1-dependent manner. In a PD cell model, one of the compounds albendazole exhibited the effect on boosting the degradation of insoluble alpha-synuclein. The study is of interest, and the cell model and the approach generated by the authors would be transferable for future studies of other high-content imaging screening. Most of the data is clear and convincing.
Major comment
1) In addition to its role in facilitating a-syn turnover by autophagy, Is the chemical protective against a-syn toxicity?
RESPONSE:
As suggested by the Reviewer, we examined the cytotoxicity of aSyn aggregates in SH-SY5Y cells overexpressing aSyn-GFP by LDH assay. As shown in the revised version of Fig. 1, aSyn aggregates induced by introducing aSyn fibrils into SH-SY5Y cells overexpressing aSyn-GFP did not exhibit any cytotoxicity. In addition, we observed no significant change in cell death after 8 hours of treatment with albendazole compared with DMSO.
Previous studies have reported that induced pluripotent stem cells (iPSCs) derived from patients with PD with a triplication of the human SNCA genomic locus exhibited reduced capacity for differentiation into dopaminergic or GABAergic neurons, decreased neurite outgrowth, and lower neuronal activity compared with control cultures, albeit without showing cytotoxicity (Cell Death and Disease 6: e1994, Oliveira et al., 2015). Given this context, we were thus unable to conduct the suggested assessment due to technical limitations. Therefore, we consider the evaluation of the recovery of aSyn toxicity by drug treatment challenging in this cellular model using fibril aSyn.
__Revised Fig 1. __
SH-SY5Y cells overexpressing aSyn-GFP were transfected with aSyn fibril for 48 h and treated with the indicated albendazole concentrations for 8 h. The cytotoxicity was measured by using Cytotoxicity LDH Assay Kit-WST kit.
2) Please elaborate why albendazole does not change the levels of soluble a-syn, but those of insoluble, as shown Fig 8D.
RESPONSE:
The unchanged aSyn-GFP levels in the soluble fraction (Fig. 8D) are likely due to the abundance of soluble aSyn-GFP. To evaluate the autophagic degradation of aSyn monomers, we used SH-SY5Y cells stably expressing aSyn-Halo and measured aSyn degradation by quantifying cleaved Halo. As shown in the revised version of Fig. 2, albendazole treatment induced a higher cleavage rate of Halo than DMSO treatment for 8 h, suggesting that albendazole degrades both aSyn monomers and aSyn aggregates. We have added the data in Fig. S7A, and the description of these experiments in the Results section (page 10, lines 359 to 364).
__Revised Fig. 2. __
SH-SY5Y cells expressing aSyn-Halo were labeled for 20 min with 100 nM of tetramethylrhodamine-conjugated ligand in a nutrient-rich medium. After washing with phosphate-buffered saline and incubating in normal medium for 30 min, the cells were treated with 10 µM albendazole for 8 h. The experiments were performed in triplicate. Cell lysates were separated by electrophoresis and analyzed by in-gel fluorescence detection (left). The HaloTMR band intensity was normalized by the sum of the band intensities of HaloTMR-aSyn and HaloTMR. The vertical axis of the graph represents the intensity multiplied by 100. Mean values of data from five or three experiments are shown. The graph data are expressed as mean ± standard deviation. ****P
3) Fig 6A shows that some of the compounds (Teniposide, Amsacrine) affect the levels of JIP4. Can albendazole also reduce JIP4 levels. It might be interesting to test this, as JIP4 is important for lysosomal clustering.
RESPONSE:
As the Reviewer pointed out, JIP4 is essential for lysosome accumulation. However, our data showed decreased JIP4 levels with the addition of lysosomal-clustering compounds. We hypothesized that this response was caused by the autophagy-induced degradation of JIP4. The decrease in JIP4 levels was detected by western blot after 4 h of treatment with 10 μM of teniposide. Moreover, the decrease in JIP4 levels induced by teniposide was suppressed by co-treatment with bafilomycin A1, indicating that JIP4 was degraded by teniposide-induced autophagy, as shown in the revised version of Fig. 3. We have added the data in Fig. S6 and the related description of these experiments in the Results section (page 8, lines 289 to 293).
__Revised Fig 3. __
SH-SY5Y cells were treated with 10 µM teniposide and with or without 30 nM bafilomycin A1 for 4 h. Cell lysates were immunoblotted with anti-JIP4 and actin antibodies.
Minor comments: The writing is good generally. Please tide up the text in a few occasions to make the expressions more formal.
RESPONSE: We have revised our manuscript to adopt a more formal tone.
Reviewer #1 (Significance (Required)):
Significance: The study generated a new approach for high-throughput screening of compounds to enhance lysosomal clustering. Audience: Basic and clinical research Expertise: Programmed cell death, neurodegenerative diseases
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Reviewer #2 (Evidence, reproducibility and clarity (Required)):
In this study, the authors focused on lysosome positioning and autophagy activity to search for novel agents effective against Parkinson's disease. As a result, several compounds were successively identified, including Topoisomerase inhibitors and Benzimidazole. Authors showed that these agents regulate lysosomal positioning through different pathways but commonly require JIP4 to regulate lysosomal positioning and subsequent autophagy. They also showed that albendazole treatment promoted the degradation of insoluble ubiquitinated proteins and αSyn in cultured cells.
Major Comments.
1) Two compounds, for instance teniposide and albendazole both requires JIP4 and/or TRPML1 to regulate lysosomal positioning and autophagy but their action seems different. What is the actual mechanism by which these compounds require JIP4/TRPML1. How inhibition of Topoisomerase leads to increase of JIP4 phosphorylation? Do teniposide and albendazole both affect calcium release from TRPML1?
RESPONSE:
We previously reported that acrolein/H2O2 accelerates lysosomal retrograde trafficking by TRPML1 and phosphorylated JIP4. Mechanistically, JIP4 was phosphorylated by CaMK2G activated by Ca2+ released from TRPML1 (EMBO J 41: e111476, Sasazawa et al., 2022). TRPML1 acts as a reactive oxygen species (ROS) sensor in lysosomes (Nat Commun 7: 12109, Zhang et al., 2016). We concluded that acrolein induces ROS production, which then activates TRPML1. (EMBO J 41: e111476, Sasazawa et al., 2022). Therefore, topoisomerase inhibitors (topo-i) may induce ROS and stimulate TRPML1. We examined intracellular ROS levels in response to topo-i. As shown in revised Fig. 4A, the topo-i teniposide, etoposide, and amsacrine significantly increased ROS levels. Moreover, N-acetyl-L-cysteine, an ROS scavenger, partially attenuated lysosomal clustering induced by topo-i (revised Fig. 4B). In addition, Ca2+ imaging showed that teniposide, but not albendazole, upregulates Ca2+ flux (revised Fig. 4C). Based on the activity of CaMK2G siRNA as shown in Fig. 5D, 5E, and S5, topo-i may activate TRPML1 in a ROS-dependent manner and increase PI(3,5)P2 binding with TRPML1 (Nat Commun 1, 38, Dong et al., 2010). Consecutive Ca2+ release via TRPML1 activated CaMK2G and is followed by enhanced lysosomal transport toward the MTOC via JIP4 phosphorylation.
We have added the revised Fig.4A and 4B data in Fig. S8A and S8B, and the related description of these experiments in the Discussion section (page 11, lines 401 to 409). We have also added the data in revised Fig. 4C to Fig. S6 and the related description of these experiments in the Results section (page 7, lines 266 to 267).
Conversely, we showed that benzimidazoles, including albendazole, induce lysosomal clustering mediated by JIP4, TRPML1, ALG2, and Rab7. Moreover, benzimidazoles showed lysosomal clustering activity within a narrow concentration range, as shown in Fig. S7D. Benzimidazoles inhibit tubulin polymerization (Int J Paras 18:885–936. Lacey et al., 1988). We hypothesized that the effect of tubulin polymerization induced by benzimidazole plays a key role in the induction of lysosomal clustering as described in the Discussion section. To clarify this, we observed the behavior of tubulin filaments in response to various albendazole concentrations under confocal microscopy. As shown in revised Fig. 4D, conditions where albendazole was administered to induce lysosomal clustering, tubulin filaments were observed only near the MTOC, and the filaments in the cell periphery were disassembled. In contrast, when exposed to higher albendazole concentrations, tubulin filaments throughout the cell were disassembled, resulting in the inhibition of lysosomal clustering This would explain why benzimidazole exerts lysosomal clustering activity within a narrow concentration range. Under JIP4, TRPML1, ALG2 and Rab7 silencing, lysosomes may fail to interact with microtubules, resulting in the inhibition of lysosomal clustering. We postulated that albendazole-induced lysosomal clustering is not mediated by factors activated by specific stimuli in lysosomal transport but, rather, is induced by spatially constraining conventional lysosomal transport mediated by various adaptors (i.e., JIP4, TRPML1, ALG2, and Rab7) through tubulin disassembly. We have added the data in Fig. S9C and the related description of these experiments in the Discussion section (page 12, lines 428 to 436).
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__Revised Fig. 4. __
- SH-SY5Y cells were treated with the indicated compounds (10 µM) for 4 h. The amount of intracellular reactive oxygen species (ROS) is examined by ROS Assay Kit -Highly Sensitive DCFH-DA (Dojindo) and the normalized pixels above threshold as measured using an INCellAnalyzer 2200 and ImageJ.
- SH-SY5Y cell lines were pretreated with 0.1 mM N-acetyl-L-cysteine (NAC) for 24 h and then treated with the indicated compound (10 µM) for an additional 4 Cells were fixed and stained with anti-g-tubulin (green) and anti-LAMP2 (red) antibodies. Lysosomal distribution was examined using an INCellAnalyzer 2200 and quantified using ImageJ software.
- SH-SY5Y cells were treated with teniposide, amsacrine, etoposide, albendazole (1, 5, 10 µM), oxibendazole (0.1, 0.5, and 1 µM), or and mebendazole (0.5,1, and 5 µM) for 4 h, and stained with Fluo4-AM for 30 min. The fluorescence intensity was measured using a plate reader.
- SH-SY5Y cells were treated with albendazole (10 and 100 µM) or nocodazole (0.5 and 10 µM) for 4 h. Cells were fixed and stained with LAMP1 (red) and a-tubulin (green) antibodies.
2) The authors should clarify the functional advantage of these drugs identified in this study as drugs for Parkinson's disease by comparing with known autophagy inducers such as Torin1 or rapamycin.
RESPONSE:
To evaluate the functional advantage of lysosome-clustering compounds over Torin1, we evaluated the degradation activity of insoluble aSyn induced by the addition of aSyn fibrils to aSyn-GFP cells. Torin1 induced the degradation of insoluble aSyn by autophagy, as shown in revised Fig. 5A. However, the degradation activity of albendazole was more vigorous, as shown in revised Fig. 5B. In contrast, we observed that Torin1 exhibited more autophagic induction activity than albendazole, as assessed using Halo-LC3. Similar results were obtained with teniposide (revised Fig. 5C). These results suggest that albendazole, with its ability to concentrate lysosomes around the degradation substrate, facilitates more effective degradation of insoluble aSyn than Torin1. This presents a significant advantage in the development of therapeutics for Parkinson's Disease. Moreover, Torin1 acts on the upstream signals of autophagy by inhibiting mTORC1, potentially impacting diverse cellular responses. Conversely, compounds that induce lysosomal clustering target the final step of autophagic degradation, which may have fewer side effects. We have added the description of these experiments in the Results section (page 10, lines 366 to 380) and the Discussion section (page 11 lines 410 to 412) and presented the data in Fig. S7B–S7E and Fig. 6D.
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__Revised Fig. 5. __
- SH-SY5Y cells overexpressing aSyn-GFP were transfected with aSyn fibril (0.2 µg/mL) using Lipofectamine 3000. After 48 h, the transfection reagent was washed out, and the SH-SY5Y cells were treated with 100 nM Torin1 with or without 100 nM bafilomycin A1 for 8 h (B). Cell lysates were separated into Triton X-100–soluble (soluble) and pellet fractions (insoluble), then subjected to sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) and immunoblotting with the indicated antibody(left). The amount of insoluble aSyn was quantified using Image J software (C).
- SH-SY5Y cells overexpressing aSyn-GFP were transfected with aSyn fibril (0.2 µg/mL) using Lipofectamine 3000. After 48 h, and washing out the transfection reagent, SH-SY5Y cells were treated with albendazole (10μM) with or without 100 nM Torin1 for 8 h. Cell lysates were separated into Triton X-100–soluble (soluble) and pellet fractions (insoluble), then subjected to SDS-PAGE and immunoblotting with the indicated antibody (left). The amount of insoluble aSyn was quantified using Image J software.
- SH-SY5Y cells stably expressing Halo-LC3 were labeled for 20 min with 100 nM TMR-conjugated ligand in a nutrient-rich medium. After washing with PBS and incubating the cells in normal medium for 30 min, cells were treated with DMSO, teniposide (10 μM), albendazole (10 µM), and/or Torin1 (100 nM) for 8 h. Cell lysates were immunoblotted with the indicated antibody and analyzed by in-gel fluorescence detection (left). The HaloTMR band intensity was normalized by the sum of the band intensities of HaloTMR-LC3B and HaloTMR (right).
3) Related to the previous question, in Fig.6A and B additional data comparing novel compounds with established autophagy inducers, such as torin1 and rapamycin, should be included and discussed.
RESPONSE:
As indicated in a previous response, we evaluated the autophagic induction activity of Torin1, and the results have been added to Fig. 6D. In addition, co-treatment with Torin1 and teniposide or albendazole induced autophagy more effectively than Torin1 treatment alone, without affecting mTOR inhibition activity (revised Fig. 4C). These findings indicate that the induction of autophagy by lysosomal clustering compounds is not caused by autophagosome formation but by the formation of autolysosomes. We have added a description of these experiments in the Results section (page 9, lines 316 to 322) and have added the data in Fig. 6D.
4) The authors should examined whether increased degradation of insoluble proteins and αSyn are dependent on JIP4.
RESPONSE:
As the Reviewer suggested, we have examined whether lysosomal accumulation through the JIP4-TRPML1 pathway is crucial for the degradation of aSyn aggregates. We evaluated the degradation activity of insoluble aSyn induced by the addition of aSyn fibrils to aSyn-GFP cells when JIP4, TMEM55B, or TRPML1 were knocked down. Interestingly, the insoluble fraction assay showed that JIP4 and TRPML1 knockdown regulated the decrease of aSyn-GFP and p-aSyn levels in the insoluble fraction for both DMSO and albendazole treatments. The results were particularly more pronounced with TRPML1 knockdown. However, the knockdown of TMEM55B did not produce such findings (revised Fig. 6). These data suggest that lysosomal clustering via the JIP4–TRPML1 pathway plays a significant role in aSyn degradation. We have added a relevant description in the Results section (page 10, lines 373 to 380) and have added the data in Fig. S7F and S7G.
__Revised Fig. 6. __
SH-SY5Y cells over-expressing aSyn-GFP were transfected with the indicated siRNAs for 24 h and then transfected with aSyn fibril (0.2 µg/mL) using Lipofectamine 3000 for 48 h. After washing out the transfection reagent, the SH-SY5Y cells were treated with dimethyl sulfoxide or albendazole (10 μM) for 8 h. Cell lysates were separated into Triton X-100–soluble (soluble) and pellet fractions (insoluble) and subjected to SDS-PAGE and immunoblotting with the indicated antibody. The bar graph presents the ratio of the insoluble aSyn-GFP to the soluble GAPDH or insoluble p-aSyn to the soluble GAPDH of the intensity of the data in panel F. Data are expressed as mean ± standard deviation.
5) Authors only utilized. SH-SY5Y cells in this study. It is important to examine whether these compounds also regulate lysosomal positioning and autophagy in other cell lines.
RESPONSE:
As per the Reviewer’s suggestion, we evaluated the lysosomal-clustering activity induced by topo-i and benzimidazole in human adenocarcinoma HeLa cells. As shown in revised Fig. 7A and 7B compounds do not induce lysosomal clustering or autophagy in HeLa cells. Furthermore, in the case of benzimidazole, they transport lysosomes to the cell periphery. Previously, we found that oxidative stress accumulates lysosomes in a neuroblastoma-specific manner through the TRPML1–phosphoJIP4-dependent mechanism (EMBO J 41: e111476, Sasazawa et al., 2022). Since we have demonstrated that topo-i-mediated lysosomal trafficking is dependent on the TRPML1–phosphorylated JIP4 complex, we hypothesized that several molecules involved in lysosomal trafficking are absent in HeLa cells.
In contrast, we showed that albendazole-induced lysosomal clustering is due to tubulin depolymerization. Therefore, we examined the relationships between tubulin depolymerization and lysosomal clustering induced by albendazole in HeLa cells and found that albendazole did not induce lysosomal clustering but rather inhibited it at higher concentrations (revised Fig. 7B). Interestingly, similar to SH-SY5Y cells, a low albendazole concentration (10 μM) induced tubulin depolymerization only at the cell periphery, whereas a high concentration (100 μM) depolymerized the entire cell (revised Fig. 7C). However, unlike SH-SY5Y cells, no characteristic accumulation of tubulin filaments was observed near the MTOC under low albendazole concentration (10 µM); instead, they were arranged around the nucleus. Concurrently, lysosomes were around these dispersed tubulin filaments. Therefore, the differences in the effects of benzimidazole in HeLa and SH-SY5Y cells lies in the dose-dependent effects on the state of tubulin filaments. We have added a relevant description in the Discussions section (page 12, lines 419 to 422, and 437 to 453).
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__Revised Fig. 7. __
HeLa cells were treated with teniposide (10 μM), amsacrine (10 μM), etoposide (10 μM), albendazole (10 μM), oxibendazole (1 μM), or mebendazole (5 μM). Images were captured using an INCellAnalyzer2200. INCellAnalyzer2200 images were analyzed using ImageJ for lysosomal clustering. The graph presents the lysosomal clustering values (n > 30). Data are expressed as mean ± standard deviation (SD). ****P HeLa cells were treated with teniposide (10 μM), amsacrine (10 μM), etoposide (10 μM), albendazole (10 μM), oxibendazole (1 μM), or mebendazole (5 μM) for 4 h. Cell lysates were immunoblotted with the indicated antibodies. The amount of LC3II was estimated using Image J software (bottom panel). HeLa cells were treated with albendazole at specified concentrations (in µM). After treatment, cells were fixed and stained with anti-g-tubulin (green) and anti-LAMP2 (red) antibodies, followed by imaging with an INCellAnalyzer2200. INCellAnalyzer2200 images were processed and analyzed using ImageJ for lysosomal clustering. The graph presents the lysosomal clustering values (n > 30). Data are expressed as mean ± SD. *P HeLa cells were treated with albendazole (10 and 25 µM) for 4 h. Cells were fixed and stained with LAMP1 (red) and a-tubulin (green) antibodies.
6) The authors conclude that the six compounds do not mediate mTOR signaling in Fig. 3, but should more carefully describe in the manuscript why they performed this experiment and what the results mean for.
RESPONSE:
As per the Reviewer’s advice, we have changed the description in the manuscript as follows:
Previous studies have shown that lysosomal retrograde transport regulates autophagic flux by facilitating autophagosome formation by suppressing mTORC1 and expediting fusion between autophagosomes and lysosomes (Kimura et al, 2008; Korolchuk et al, 2011). Conversely, we recent found that acrolein/H2O2 induces lysosomal clustering in an mTOR-independent manner (Sasazawa et al., 2022). In this study, we aimed to identify pharmacologic agents that act downstream rather than upstream in the autophagy pathway, with the goal of minimizing side effects. Therefore, we evaluated the effects of the compounds on the mTOR pathway. As shown in Fig. 3, these compounds induced lysosomal clustering without affecting mTOR activity, indicating their potential as promising candidates for PD therapy. We have added the description of these experiments in the Results section (page 6, lines 202 to 208 and line 217).
Minor comments. 1) The name of the compound should be written in the red point of Fig.2A.
RESPONSE:
We have included the names of the six compounds identified and are listed in Fig. 2A.
2) Regarding images of Fig.2B, the magnified images and quantitative data should be added.
RESPONSE:
We have included magnified images, as well as the quantitative results of lysosome clustering analysis using INCellAnalyzer2200 in Fig. 2B.
3) The results of Fig.2C need to be explained more carefully. A quantitative data is missing.
RESPONSE:
We have included the quantitative results of western blot in Fig. 2B.
4) Fig.S2, which compares autophagy activity with conventional agents, should be quantified and added to the Fig.3.
RESPONSE:
We have presented the results of RFP/GFP quantification performed by FACS analysis using SH-SY5Y cells stably expressing RFP-GFP-LC3 in Fig. S2, which is equivalent to the quantification of the data in the Fig. S2 image. These data are now presented as Fig. S2B. Since Fig. 3 focuses on mTOR signaling, we preferred to retain the figure number.
5) In the statistical analysis of Fig.4B, the clustering value was increased by siRILP, which should be briefly described in the manuscript.
RESPONSE:
On the contrary, the enhancement of lysosomal retrograde transport in RILP knockdown cells in Fig. 4B suggests the potential involvement of RILP in anterograde transport. However, to the best of our knowledge, no reports have investigated this matter. We presume that negative feedback mechanisms may be present. We have added this description to the Results section (page 7 lines 238 to 241).
6) In Fig.4A and B, it is possible that the knockdown efficiency of siRILP and siTMEM55B was not sufficient to observe the effect on lysosomes, and this concern should be described in the manuscript.
RESPONSE:
We established starvation conditions, which induce TMEM55B-dependent lysosomal retrograde transport, as a positive control and evaluated the lysosomal induction activity of compounds when TMEM55B was knocked down. As shown below, lysosome accumulation was suppressed only when subjected to starvation treatment, indicating sufficient knockdown efficiency of TMEM55B. These compounds induced lysosomal clustering independently of TMEM55B, unlike under starvation conditions. We have added a description of these experiments in the Results section and presented the data in Fig. S4A (page 7, lines 232 to 237).
On the other hand, we were unable to establish a positive control for RILP knockdown experiments because conditions that regulate RILP-dependent lysosomal distribution dependent are not understood. While we cannot completely rule out the possibility of insufficient knockdown efficiency, considering that RILP knockdown appears to paradoxically enhance lysosomal induction, as mentioned above, it is reasonable to assume that the knockdown effect has occurred.
__Revised Fig. 8. __
SH-SY5Y cells were transfected with TMEM55B siRNA for 48 h and then treated with teniposide (10 μM), albendazole (10 μM), or starvation medium for 4 h. Cells were fixed and stained with anti-g-tubulin (green) and anti-LAMP2 (red) antibodies. Images were captured using an INCellAnalyzer2200. INCellAnalyzer2200 images were analyzed using ImageJ for lysosomal clustering. The graph presents the lysosomal clustering values (n > 30). Data are expressed as mean ± standard deviation (SD). ****P
7) The authors should add the results of the WB experiment showing the amount of JIP4 protein in Fig.5G.
RESPONSE:
We have added western blot data that introduce flag-JIP4 into JIP4KO SH-SY5Y cells, which are presented in Fig. 5G.
8) In Fig.5F, images of JIP4KO cells that do not express FLAG-JIP4 should be added as controls, and further quantification should be done on cells in all three conditions.
RESPONSE:
We have added immunofluorescence data that do not express flag-JIP4 in Fig. 5F, which had been obtained simultaneously during the acquisition of other images. Furthermore, we quantified lysosomal distribution, which is shown in Fig. 5E. Using ImageJ, we automatically delineated approximately 70% of the cell area toward the cell center and designated the region excluded from this area as the cellular peripheral region (revised Fig. 9A). Subsequently, we quantified the proportion of lysosomes contained within that region in cells expressing flag-JIP4 (revised Fig. 9B). We have added this experimental data in Fig. 5E.
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__Revised Fig. 9. __
- Approximately 70% of the cell area toward the cell center was automatically delineated using ImageJ, with the region excluded from this defined as the cellular peripheral region.
- JIP4 KO cells were transfected with flag-tagged JIP4 (wild-type and T217A) for 24 h and treated with teniposide (10 μM) for 4 h. Cell lysates underwent SDS-PAGE and were immunoblotted with anti-JIP4 and anti-actin The graph displays the percentage of cells with peripheral lysosomes. Data are expressed as mean ± standard deviation. *P 20).
9) In Fig.6A, the total amount of JIP4 seems to change in some agent treatments, which needs to be explained.
RESPONSE:
As per our response to Reviewer 1, we evaluated the decrease in JIP4 expression by WB after 4 h of treatment with 10 μM teniposide. The teniposide-induced decrease of JIP4 was suppressed by bafilomycinA1 co-treatment, indicating that JIP4 was degraded by teniposide-induced autophagy (revised Fig. 3). We have added the data in Fig. S6, and the related description of these experiments have been added to the Results section (page 8, lines 289 to 293).
10) In Fig.7C and D, the effect of drug treatment on the amount of ubiquitinated proteins should also be checked.
RESPONSE:
We have included ubiquitin protein blots in Fig. 7C and 7D.
11) In Fig.8B, it is described that lysosomes are more localized in αSyn by drug treatment, but more convincing images and quantitative data are needed.
RESPONSE:
. The colocalization of LAMP2 and aSyn-GFP aggregates was assessed by measuring the fluorescence values of lysosomes in contact within the aSyn-GFP aggregation area using ImageJ. We have added this quantified data in Fig. 8D.
Reviewer #2 (Significance (Required)): Although the reviewer appreciates the discovery of novel drugs to induce autophagy through regulating lysosomal positioning, the detailed action of these compounds and their superiority in the field are not clear.
__Reviewer #3 (Evidence, reproducibility and clarity (Required)):____ __ In this manuscript, Date et al. sought to identify compounds that promote protein aggregates clearance - in particular those formed by mutant alpha synuclein. Briefly the authors screened a library of clinically approved compounds for inducers of lysosomal clustering followed by a secondary screen for autophagy inducers. By this two-step procedure, the authors identified three topoisomerase inhibitors and three anthelmintics as hits. Next, the authors unveiled that lysosomal clustering induced by these compounds is independent of mTORC1 but requires TRPML1 and JIP4. Moreover, the topoisomerase inhibitors hits involved phosphorylation of JIP4 while the anthelmintics additionally required Rab7 and ALG2. Intriguingly, the authors found that lysosomal clustering was prerequisite to autophagy induction. Focusing on the class of anthelmintics (i.e. albendazole) the authors showed that these induce autophagy to degrade aggregates formed upon proteasome inhibition. Lastly, the authors demonstrated that albendazole also led to increased degradation of αSyn aggregates through autophagy induction.
Major points 1) Most importantly, the authors need to tone down the significance of their findings throughout the manuscript. For examples, they should restrain from using "nullified" when it is really reduced only by 10-25 %.
RESPONSE:
We have changed the description in the manuscript according to the Reviewer’s suggestion.
2) The authors claim that the topoisomerase inhibitors led to JIP4 phosphorylation while Figure 5C actually shows the opposite (partially reduced phosphorylation compared to DMSO treatment) and the Jak3 inhibitor has no obvious effect. The authors should quantify the phostag results.
RESPONSE:
We agree with the Reviewer that the Phos-tag PAGE results of JIP4 in Fig. 5C is complicated, and the bands were not clear. We have replaced these with more robust data (Fig. 5C).
3) Figure 6A/B: Why do all compounds except Mebendazole affect the abundance of JIP4?
RESPONSE:
As per our response to Reviewer 1, we evaluated the decrease in JIP4 expression by WB after 4 h of treatment with 10 μM teniposide. The teniposide-induced decrease of JIP4 was suppressed by bafilomycinA1 co-treatment, indicating that JIP4 was degraded by teniposide-induced autophagy (revised Fig. 3). We have added the data in Fig. S6, and the related description of these experiments have been added to the Results section (page 8, lines 289 to 293).
4) Figure 7C: The blot is not convincing. The authors should quantify this effect.
RESPONSE:
We evaluated and confirmed the degradation of p62 by albendazole, as shown in Fig. 7C.
Reviewer #3 (Significance (Required)):
Overall, the work of Date and colleague highlights the role of lysosomal clustering in clearing protein aggregates. Importantly, the identified classes of compounds might open new avenues for rationalizing treatment strategies for neurodegenerative diseases. However, several critical points remain.
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Referee #3
Evidence, reproducibility and clarity
In this manuscript, Date et al. sought to identify compounds that promote protein aggregates clearance - in particular those formed by mutant alpha synuclein. Briefly the authors screened a library of clinically approved compounds for inducers of lysosomal clustering followed by a secondary screen for autophagy inducers. By this two-step procedure, the authors identified three topoisomerase inhibitors and three anthelmintics as hits. Next, the authors unveiled that lysosomal clustering induced by these compounds is independent of mTORC1 but requires TRPML1 and JIP4. Moreover, the topoisomerase inhibitors hits involved phosphorylation of JIP4 while the anthelmintics additionally required Rab7 and ALG2. Intriguingly, the authors found that lysosomal clustering was prerequisite to autophagy induction. Focusing on the class of anthelmintics (i.e. albendazole) the authors showed that these induce autophagy to degrade aggregates formed upon proteasome inhibition. Lastly, the authors demonstrated that albendazole also led to increased degradation of αSyn aggregates through autophagy induction.
Major points
- Most importantly, the authors need to tone down the significance of their findings throughout the manuscript. For examples, they should restrain from using "nullified" when it is really reduced only by 10-25 %.
- The authors claim that the topoisomerase inhibitors led to JIP4 phosphorylation while Figure 5C actually shows the opposite (partially reduced phosphorylation compared to DMSO treatment) and the Jak3 inhibitor has no obvious effect. The authors should quantify the phostag results.
- Figure 6A/B: Why do all compounds except Mebendazole affect the abundance of JIP4?
- Figure 7C: The blot is not convincing. The authors should quantify this effect.
Significance
Overall, the work of Date and colleague highlights the role of lysosomal clustering in clearing protein aggregates. Importantly, the identified classes of compounds might open new avenues for rationalizing treatment strategies for neurodegenerative diseases. However, several critical points remain.
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Referee #2
Evidence, reproducibility and clarity
In this study, the authors focused on lysosome positioning and autophagy activity to search for novel agents effective against Parkinson's disease. As a result, several compounds were successively identified, including Topoisomerase inhibitors and Benzimidazole. Authors showed that these agents regulate lysosomal positioning through different pathways but commonly require JIP4 to regulate lysosomal positioning and subsequent autophagy. They also showed that albendazole treatment promoted the degradation of insoluble ubiquitinated proteins and αSyn in cultured cells.
Major Comments.
- Two compounds, for instance teniposide and albendazole both requires JIP4 and/or TRPML1 to regulate lysosomal positioning and autophagy but their action seems different. What is the actual mechanism by which these compounds require JIP4/TRPML1. How inhibition of Topoisomerase leads to increase of JIP4 phosphorylation? Do teniposide and albendazole both affect calcium release from TRPML1?
- The authors should clarify the functional advantage of these drugs identified in this study as drugs for Parkinson's disease by comparing with known autophagy inducers such as Torin1 or rapamycin.
- Related to the previous question, in Fig.6A and B additional data comparing novel compounds with established autophagy inducers, such as torin1 and rapamycin, should be included and discussed.
- The authors should examined whether increased degradation of insoluble proteins and αSyn are dependent on JIP4.
- Authors only utilized. SH-SY5Y cells in this study. It is important to examine whether these compounds also regulate lysosomal positioning and autophagy in other cell lines.
- The authors conclude that the six compounds do not mediate mTOR signaling in Fig. 3, but should more carefully describe in the manuscript why they performed this experiment and what the results mean for.
Minor comments.
- The name of the compound should be written in the red point of Fig.2A.
- Regarding images of Fig.2B, the magnified images and quantitative data should be added.
- The results of Fig.2C need to be explained more carefully. A quantitative data is missing.
- Fig.S2, which compares autophagy activity with conventional agents, should be quantified and added to the Fig.3.
- In the statistical analysis of Fig.4B, the clustering value was increased by siRILP, which should be briefly described in the manuscript.
- In Fig.4A and B, it is possible that the knockdown efficiency of siRILP and siTMEM55B was not sufficient to observe the effect on lysosomes, and this concern should be described in the manuscript.
- The authors should add the results of the WB experiment showing the amount of JIP4 protein in Fig.5G.
- In Fig.5F, images of JIP4KO cells that do not express FLAG-JIP4 should be added as controls, and further quantification should be done on cells in all three conditions.
- In Fig.6A, the total amount of JIP4 seems to change in some agent treatments, which needs to be explained.
- In Fig.7C and D, the effect of drug treatment on the amount of ubiquitinated proteins should also be checked.
- In Fig.8B, it is described that lysosomes are more localized in αSyn by drug treatment, but more convincing images and quantitative data are needed.
Significance
Although the reviewer appreciates the discovery of novel drugs to induce autophagy through regulating lysosomal positioning, the detailed action of these compounds and their superiority in the field are not clear.
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Referee #1
Evidence, reproducibility and clarity
The manuscript by Date et al employed a cell model by stably expressing LGP120-mCherry and GFP-gamma-tubulin to carry out high-content screening in search of chemical compounds that enhance lysosomal clustering and autophagy. They found 6 clinically approved drugs categorized as topoisomerase II inhibitors and the benzimidazole class. They further validated these compounds by a set of well-designed experiments including autophagy flux assays and mTOR dependence. In the mechanistic study, they demonstrated the compounds induce lysosomal clustering in a JIP4-TRPML1-dependent manner. In a PD cell model, one of the compounds albendazole exhibited the effect on boosting the degradation of insoluble alpha-synuclein. The study is of interest, and the cell model and the approach generated by the authors would be transferable for future studies of other high-content imaging screening. Most of the data is clear and convincing.
Major comments:
- In addition to its role in facilitating a-syn turnover by autophagy, Is the chemical protective against a-syn toxicity?
- Please elaborate why albendazole does not change the levels of soluble a-syn, but those of insoluble, as shown Fig 8D.
- Fig 6A shows that some of the compounds (Teniposide, Amsacrine) affect the levels of JIP4. Can albendazole also reduce JIP4 levels. It might be interesting to test this, as JIP4 is important for lysosomal clustering.
Minor comments:
The writing is good generally. Please tide up the text in a few occasions to make the expressions more formal.
Significance
Significance: The study generated a new approach for high-throughput screening of compounds to enhance lysosomal clustering.
Audience: Basic and clinical research
Expertise: Programmed cell death, neurodegenerative diseases
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Reply to the reviewers
#Reviewer 1 (Evidence, reproducibility and clarity):
This manuscript by Deshmukh et al is aimed at generating chimeric antigens that can be useful for making next generation vaccines that block blood stage infection by malaria parasite. Given that there is no blood stage vaccine against malaria and available liver stage vaccine shows only limited efficacy that too only in Africa, there is dire need for having novel approaches to generate successful vaccines. In the past attempts have been made to make multivalent vaccines but have not been successful. Nevertheless, it is still a good option as single target blood-stage vaccines have failed. Authors propose to target cytoadhesion and host erythrocyte invasion. For this purpose, they have selected epitopes from PfEMP1/VarB family members, which poses a major challenge as at least 60 genes encode them and they exhibit variations which facilitate the escape from the immune system. The other two chimeras target invasion related proteins like MSPs and adhesins shed by micronemes and rhoptries, which are critical for invasion. The reported work is interesting and provides a useful approach towards developing vaccines against blood stage infection.
We appreciate the time and effort given by our reviewer in thoroughly reading the manuscript. We are thankful for all the comments and suggestions for better shaping the article.
Comments:
- __ The peptides used in InvB chimera did not show good reactivity especially when compared to VarB or MSP peptides. Please discuss the possible reasons.__
Response: Thank you for pointing out the difference in the explanation. With chimeric InvP, we see a strong response against a few peptides of SERA-5 and RH-5, while other peptides, in comparison, have lesser antibody responses. We have now included the following statement detailing this difference with possible explanations in the revised manuscript (Page 8, Line 25 to 30).
The IgG responses to chimeric InvP were slightly different from those to chimeric varB and MSP. The intensity of IgG to peptides of SERA-5 and RH-5 was very high in comparison to the rest of the peptides used in the construct, whereas in chimeric varB and MSP, the IgG titers were comparable between the peptides. This could be a result of antigen exposure in the cohort of 19 patient samples that we used, and may change when a larger sample size is considered.
__ It will be interesting to determine if blocking a specific VarB/PfEMP1 alters expression of other members. Based on the data provided in Fig. 4E, can a chimera be designed which only includes PfEMP1 that are represented well in HBEC-5i population?__
Response: We agree that observing the altered expression of PfEMP1 would be an interesting phenomenon to study. The blocking of PfEMP1 using anti-chimeric varB antibodies is a transient process in our assays (just enough to quantify the cytoadhesion). It may take multiple cycles with negative selection pressure on parasites for the switching to take place. Also, it will be interesting to design chimeras based on the HBEC-5i binding PfEMP1. We can certainly plan these as prospective future experiments.
__ Some of the invasion related proteins like RH5 and EBA175 are not present at parasite surface, instead, secreted from rhoptries and micronemes. It will be nice to perform Western blots on condition medium and see if InvP (or even MSP and VarB) antibodies recognizes the secreted version of these proteins.__
Response: We thank the reviewer for this valuable comment and the suggestive experiment. We will perform a western blot on spent media and probe using anti-chimeric MSP and InvP antibodies to detect the proteins selected in chimeric MSP and InvP antigens.
__ Fig. 6E- Statistics need to be provided for inhibition at 12.3 and 25ug.__
Response: We apologize for the missed statistics. It is now included in the figure panel.
__ Plasmodium uses multiple ligand-receptor interaction, which could depend (e.g. EBA-glycohophorins) or operate independent (e.g. RH5-basigin) of sialic acid. While there is representation from candidates from both of these families, most studies especially growth rate assays (Fig. 6E) have been carried using 3D7 strain, which does not require sialic acid. It is possible that if similar experiments were performed using sialic acid-sensitive strains, InvP and MSP antibodies may cause greater inhibition of parasite growth, which may be worth testing.__
Response: We are grateful for the suggestion of using a sialic acid-dependent strain. Indeed, the pathway of reinvasion chosen by the parasite may determine the growth inhibition assay (GIA) outcome. We will perform the GIA assay on the Dd2 strain and 3D7 with neuraminidase treatment (Sialic acid-dependent invasion). We will also note the difference in growth inhibition potential of chimeric antibodies in sialic-acid dependent and independent pathways.
__ The direct effect of InvP and MSP Abs should be tested directly on host erythrocyte invasion.__
Response: We thank the reviewer for this comment. We certainly can determine the inhibitory potential of anti-chimeric MSP and InvP antibodies through invasion assays. We will include the invasion inhibition potential of these antibodies in 3D7, Dd2, with neuraminidase treatment along with GIA data.
Reviewer #1 Significance:
Present study proposes novel strategies for the development of anti-malarial vaccine.
#Reviewer 2 (Evidence, reproducibility and clarity):
The manuscript describes the vaccine potential of unstructured P. falciparum merozoite protein fragments 25 amino acid long belonging to 3 different protein families. The work is well performed, easily reproducible and clearly described.
We appreciate the time and effort given by our reviewer in thoroughly reading the manuscript. We are thankful for all the comments and suggestions for better shaping the article.
Reviewer #2 (Significance):
- The use of protein fragments whose structure can be predicted by their sequence has been exploited in many studies for the development of vaccines or other biologicals. In this studies the authors selected 3 different families belonging to the red blood stage of the parasite. The table showing the sequences selected is not readable and should be clearly provided in the supplementary section.
Response: We apologize for the readability of the sequences. The supplementary Table 1 has the proteins selected, the sequences taken, and the precise order for the stitching.
In addition, polymorphic residues should be highlighted.
Response: We thank the reviewer for pointing this out. We will analyze and compile the protein sequences in 3D conformation, highlighting polymorphic residues and the peptides selected in our study.
In addition, it is not to mention why the authors used immune rabbit sera obtained by injection of the 3 poly-epitopes instead of obtaining by affinity chromatography antigen specific human antibodies from sera of individuals living in endemic regions which could provide a direct and clear answer whether a protective vaccine could be obtained.
Response: We agree that the clear answer to the protective function of antibodies could have been answered using human antibodies. However, we did not have a sufficient volume of patient sera to perform affinity enrichment. The use of rabbits here was to ensure the generation of antigen-specific antibody responses in ample amounts. The patient sera in quantities available were used in ELISA, epitope mapping, and IP, followed by mass-spectrometry. The IP-MS clearly shows the presence of antibodies against the proteins taken in the generation of chimeric antigens (Supplementary Figure 1 D).
#Reviewer 3 (Evidence, reproducibility and clarity):
Multi-protein chimeric antigens... by: Deshmukh et al
This article addresses an extremely important objective, the development of an effective prophylactic vaccine for Malaria. The disease continues to be widespread claiming the lives of hundreds of thousands of people annually, many of them children. Despite efforts towards producing Malaria vaccines, none thus far have been sufficiently protective or long term. As the authors point out vaccines can target the parasite per se, and possibly more attractive would be to focus on parasite derived antigens expressed on the surface of infected erythrocytes, hence targeting the Blood stage of the infection, which is most directly associated with Malaria pathogenesis. The authors propose a somewhat novel approach in which they have selected an array of short (25 amino acids) segments of Plasmodium derived proteins stitched together to produce 3 chimeric recombinant proteins as potential immunogens. Although a considerable amount of work is described, the results are not compelling in proving the efficacy or advantage of using chimeric antigens as worthy vaccine candidates for Malaria.
Unfortunately, the rationale behind the experiments are not clearly defined which is a matter of concern. In addition, details of the work done and the technical aspects needs to better explained to fully understand how and why the target segments were selected and the chimeras produced. This review focuses first on scientific issues and then format and editing, both aspects demonstrate that the manuscript in its present form requires major changes for it to be of relevance to the field. This review focuses first on issues of substance and then format and editing, both aspects disqualify the publication of the manuscript in its present form.
We appreciate the time and effort given by our reviewer in thoroughly reading the manuscript. We are thankful for all the comments and suggestions for better shaping the article.
Experiments and Results:
- The underlying proposal claims that chimeric antigens might be advantageous in eliciting protective antibodies. The authors produced three chimeras: var, MSP and InvP. __The var chimera contains 29 segments of PfEMP1 derived from 8 alleles. The hypothesis is that by expressing 29 different segments one will produce antibodies that can better cope with the antigenic diversity of this target. Indeed, serial monoallelic expression of anyone of the 60 PfEMP1 variants of a given P. falciparum strain has been thought to mediate immune evasion. The parasite is presumed to be able to escape immune defenses, by switching and serially expressing PfEMP1 alleles. Hence, one might assume that by introducing different segments, derived from different alleles, one will gain better protection. The authors have not really tested this idea. They have produced a single chimera and tested it without controlled comparison of performance to any single segment, or for that matter compared to alternative structural domain(s) of PfEMP. This brings me to the question of how the segments were selected and why. The authors implement IEDB-AR to identify presumably preferred B-cell epitopes. The methodology relies on a number of computational methods that predict the propensity of linear segments of proteins to have, for example, secondary structures, or be surface accessible, or relatively hydrophilic or flexible, etc. IEDB-AR is a tool to assist the identification of segments (5-25 amino acids in length), that might be associated with B-cell epitopes, or at least segments comprising linear aspects of B-cell epitopes. The input is a linear sequence of an antigen, proposing linear aspects of what could be associated with B-cell epitopes. B-cell epitopes, however, are typically conformational and discontinuous. They certainly can and do contain linear segments, but even these may require 3D conformations dictated by spatial constraints imposed by the native surrounding aspects of the natural antigen. It is hard to assume that by simply stitching 29 segments, one after the other, one can provide them with the native environment for them to assume a somewhat physiologically relevant conformation. Unfortunately, the authors have not addressed the unique characteristics of the antigen they have selected. PfEMP1, for example, is a family of antigens with discrete sub-domain structures and features (DBL and CIDR for example). It would be relevant and useful to relate the segments that they chose to the natural unique domains of the antigen and how they might best present common vs variant aspects of the antigen. There are at least 30 crystal atomic structures for PfEMP1 in complex with various physiologically relevant proteins (eg ICAM etc). The authors might have considered the 3D structure of PfEMP in their analyses and at least indicated on an atomic structure where the 29 segments lie. __
More concerning is the fact that the expression of the chimera does not produce a crisp single protein, but rather a complex of products as illustrated in the Supplement Figure 1 B. The authors simply claim that they produce the antigen for immunization of rabbits (or one rabbit?) and they collect gel-derived band(s) of what MW?? Assuming that a 25aa segment should be about 2500-2800 daltons and so 29 such segments strung together should be about 80kDa. The gel shows bands at 124kDa, and a slew of bands shorter than 71kDa. There is no mention what the expected MW should be and there is no explanation why the protein pattern contains so many bands of different sizes and what exact bands were taken for the immunogen or why.
Response: We thank the reviewer for this comment, as it tells us the reader’s perspective on how the chimeric construct part is underexplained. We have now expanded the section on chimeric construct design, the sequences used, the functional domains they belong to in the PfEMP1 protein (Supplementary Tables 1 and 2), and the expected sizes of the proteins created. As for the B-cell epitope prediction, we have used the linear epitope prediction tool. However, we will include a 3D conformational study highlighting the placement of peptides that we have used to generate chimeric antigens.
The sequences for chimeric constructs were synthesized commercially and confirmed using Sanger sequencing. The antigens run higher than their expected molecular weights, and we have confirmed them through western blot and mass spectrometry (Supplementary Figure 1 B and C). The chimeric varB antigen specifically shows a cleaving pattern, hence the multiple bands in western blotting (we have considered the top-most band with the highest anti-his intensity). After these confirmations, the antigens were independently injected in rabbits to generate antibodies.
Similar considerations can be made regarding the selection of the segments for the two other chimeras, although they seem to produce a single polypeptide.
Response: The antigens were confirmed using Sanger sequencing, expression using anti-his western blot, and proteins were confirmed using mass spectrometry for all three chimeric constructs (Supplementary Figure 1 B and C).
If the point was to test a "chimera" modality as an improved vaccine, it would have been more useful to focus on one chimera and carefully characterize it and compare it to its components used separately.
Response: The idea of chimera arises from the fact that individual proteins/components are insufficient to generate optimal responses. The proteins considered in our study have already been validated in the field (as separate components) and show that the efficacy observed was sub-optimal. Since our rationale is to include multiple proteins to tackle the redundancy and parasite virulence, we have focused on generating three chimeric constructs covering the entire blood stage of Plasmodium falciparum. Our objective is to demonstrate that a multi-protein, multi-factorial vaccine, as a proof of concept, works better in tackling malaria. We believe that in proving so, a comparison of chimera with their individual components is an unnecessary and economically unviable.
The authors devote much effort to the fluidics system and their assay. This might warrant a paper dedicated to the methodology they have developed.
Response: The Plasmodium virulence genes are extensively studied for their interactions with human endothelial receptors. Unfortunately, these studies fail to take human physiological conditions into account. We wanted to test our anti-chimeric varB antibodies in the best mimicking environment possible. Hence, the efforts were devoted to developing, standardizing, and quantifying the fluidic cytoadherence system. We thank the reviewer for their kind words of encouragement on our methodology.
Format and Editing:
- The manuscript is very poorly written with multiple errors throughout. The authors use abbreviations that are not defined, eg iRBC (pg 5 line 22) or sometimes incorrectly defined, eg MSP ("merozoite-specific proteins - pg 6 line 18).
Response: We apologize for the abbreviation error. The abbreviation for iRBC is defined in the introduction section (page no 4, Line 15); hence, it is not redefined on page 5, line 22. We have corrected merozoite-specific proteins on page 6, line 18.
The Figures are of low resolution to the extent that they can not be read (for example Figure 3 pg 34). Figure 1 is somewhat useless and misleading. In Fig1 C - the diagram illustrates 5 hypothetical chimeras where in fact only three were produced. There really is no detail or explanation as to how the chimeras were produced.
Response: We apologize for the low resolution of the images. We have now improved the image quality. Figure 1C represents the idea of designing the construct, not the number of chimeras we generated. We apologize for this confusion and have explicitly mentioned this in the figure panel for Figure 1C. As for the design and generation of chimeric antigens, we understand that the materials and methods section is underexplained, and we have now expanded on it with all details included.
In the construction of the chimeras there is no mention as to whether short linkers were introduced between the segments or not. What was the expected weight of the chimera? Was the order of segments random or precise and consistent? Were the constructs sequence validated in addition to the MassSpec?
Response: We understand that the section on the chimeric construct is underexplained for the readers, and we thank the reviewer for pointing it out. We have now expanded the section on chimeric antigen design and included the details. Chimera was tested with GSGSGS linkers and without linkers for expression. The final antigen injected in rabbits was serially attached peptides without linkers. The segments stitched were in precise order, as mentioned in Supplementary Sheet 1. The construct was commercially synthesized and sequence validated along with the anti-his western blot and mass spectrometry analysis.
The figures of the Supplement are not numbered.
Response: We thank the reviewer for pointing this out. The figures are now numbered.
Note that the headings in Supplement Figure 1 B and C have overlapping text.
Response: Thank you for pointing this out. We have now rearranged the supplementary figures 1B, and 1C.
Most disturbing is that multiple references that are incomplete. For example: in References 15, 16, 25, 26, 27 there is no indication of the Journal.
Response: We apologize for the mistakes in referencing. These references did not have full citations in Endnote. We have now manually checked all the references and corrected the incomplete formats of the references.
The authors mention reference 13 [2006] in claiming that the antibodies can be protective, and then support this by referring to refs 14, 15 and 16 published in 1961, 1963 and 1962 respectively. Although, old articles can be useful, but the authors should attempt to provide current proof of such basic claims.
Response: We thank the reviewer for pointing this out. We have now separated these two statements and not mentioned the latter as a support to the former. As for references 14, 15, and 16, these were the early studies in the field that show the protective nature of antibodies through the passive immunization process and are foundations for the idea of blood stage vaccination. Current proofs of antibodies against blood-stage antigens are included for blood-stage vaccine candidates.
Reviewer #3 (Significance):
The goal of the study is very important.
The hypothesis that a chimeric presentation of select peptides could be advantageous was not rigorously tested nor well controlled in a meaningful evaluation and thus no conclusion can be made. There are no comparative analyses to test their hypothesis.
The method for selection of epitope segments is not well justified. There is little attempt to provide rationale or description of the segments chosen and how they fit within the antigens, thus justifying segments over multiple antigens.
The grammatical errors, lack of clarity accompanied by little attention to style and readability render the manuscript quite illegible.
There is no excuse for so many errors in the references.
-
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 #3
Evidence, reproducibility and clarity
Multi-protein chimeric antigens... by: Deshmukh et al
This article addresses an extremely important objective, the development of an effective prophylactic vaccine for Malaria. The disease continues to be widespread claiming the lives of hundreds of thousands of people annually, many of them children. Despite efforts towards producing Malaria vaccines, none thus far have been sufficiently protective or long term. As the authors point out vaccines can target the parasite per se, and possibly more attractive would be to focus on parasite derived antigens expressed on the surface of infected erythrocytes, hence targeting the Blood stage of the infection, which is most directly associated with Malaria pathogenesis. The authors propose a somewhat novel approach in which they have selected an array of short (25 amino acids) segments of Plasmodium derived proteins stitched together to produce 3 chimeric recombinant proteins as potential immunogens. Although a considerable amount of work is described, the results are not compelling in proving the efficacy or advantage of using chimeric antigens as worthy vaccine candidates for Malaria.
Unfortunately, the rationale behind the experiments are not clearly defined which is a matter of concern. In addition, details of the work done and the technical aspects needs to better explained to fully understand how and why the target segments were selected and the chimeras produced. This review focuses first on scientific issues and then format and editing, both aspects demonstrate that the manuscript in its present form requires major changes for it to be of relevance to the field. This review focuses first on issues of substance and then format and editing, both aspects disqualify the publication of the manuscript in its present form.
Experiments and Results:
The underlying proposal claims that chimeric antigens might be advantageous in eliciting protective antibodies. The authors produced three chimeras: var, MSP and InvP.
The var chimera contains 29 segments of PfEMP1 derived from 8 alleles. The hypothesis is that by expressing 29 different segments one will produce antibodies that can better cope with the antigenic diversity of this target. Indeed, serial monoallelic expression of anyone of the 60 PfEMP1 variants of a given P. falciparum strain has been thought to mediate immune evasion. The parasite is presumed to be able to escape immune defenses, by switching and serially expressing PfEMP1 alleles. Hence, one might assume that by introducing different segments, derived from different alleles, one will gain better protection. The authors have not really tested this idea. They have produced a single chimera and tested it without controlled comparison of performance to any single segment, or for that matter compared to alternative structural domain(s) of PfEMP. This brings me to the question of how the segments were selected and why. The authors implement IEDB-AR to identify presumably preferred B-cell epitopes. The methodology relies on a number of computational methods that predict the propensity of linear segments of proteins to have, for example, secondary structures, or be surface accessible, or relatively hydrophilic or flexible, etc. IEDB-AR is a tool to assist the identification of segments (5-25 amino acids in length), that might be associated with B-cell epitopes, or at least segments comprising linear aspects of B-cell epitopes. The input is a linear sequence of an antigen, proposing linear aspects of what could be associated with B-cell epitopes. B-cell epitopes, however, are typically conformational and discontinuous. They certainly can and do contain linear segments, but even these may require 3D conformations dictated by spatial constraints imposed by the native surrounding aspects of the natural antigen. It is hard to assume that by simply stitching 29 segments, one after the other, one can provide them with the native environment for them to assume a somewhat physiologically relevant conformation. Unfortunately, the authors have not addressed the unique characteristics of the antigen they have selected. PfEMP1, for example, is a family of antigens with discrete sub-domain structures and features (DBL and CIDR for example). It would be relevant and useful to relate the segments that they chose to the natural unique domains of the antigen and how they might best present common vs variant aspects of the antigen. There are at least 30 crystal atomic structures for PfEMP1 in complex with various physiologically relevant proteins (eg ICAM etc). The authors might have considered the 3D structure of PfEMP in their analyses and at least indicated on an atomic structure where the 29 segments lie. More concerning is the fact that the expression of the chimera does not produce a crisp single protein, but rather a complex of products as illustrated in the Supplement Figure 1 B. The authors simply claim that they produce the antigen for immunization of rabbits (or one rabbit?) and they collect gel-derived band(s) of what MW?? Assuming that a 25aa segment should be about 2500-2800 daltons and so 29 such segments strung together should be about 80kDa. The gel shows bands at 124kDa, and a slew of bands shorter than 71kDa. There is no mention what the expected MW should be and there is no explanation why the protein pattern contains so many bands of different sizes and what exact bands were taken for the immunogen or why.
Similar considerations can be made regarding the selection of the segments for the two other chimeras, although they seem to produce a single polypeptide.
If the point was to test a "chimera" modality as an improved vaccine, it would have been more useful to focus on one chimera and carefully characterize it and compare it to its components used separately. The authors devote much effort to the fluidics system and their assay. This might warrant a paper dedicated to the methodology they have developed.
Format and Editing:
The manuscript is very poorly written with multiple errors throughout. The authors use abbreviations that are not defined, eg iRBC (pg 5 line 22) or sometimes incorrectly defined, eg MSP ("merozoite-specific proteins - pg 6 line 18).
The Figures are of low resolution to the extent that they can not be read (for example Figure 3 pg 34). Figure 1 is somewhat useless and misleading. In Fig1 C - the diagram illustrates 5 hypothetical chimeras where in fact only three were produced. There really is no detail or explanation as to how the chimeras were produced.
In the construction of the chimeras there is no mention as to whether short linkers were introduced between the segments or not. What was the expected weight of the chimera? Was the order of segments random or precise and consistent? Were the constructs sequence validated in addition to the MassSpec?
The figures of the Supplement are not numbered.
Note that the headings in Supplement Figure 1 B and C have overlapping text.
Most disturbing is that multiple references that are incomplete. For example: in References 15, 16, 25, 26, 27 there is no indication of the Journal.
The authors mention reference 13 [2006] in claiming that the antibodies can be protective, and then support this by referring to refs 14, 15 and 16 published in 1961, 1963 and 1962 respectively. Although, old articles can be useful, but the authors should attempt to provide current proof of such basic claims.
Significance
The goal of the study is very important.
The hypothesis that a chimeric presentation of select peptides could be advantageous was not rigorously tested nor well controlled in a meaningful evaluation and thus no conclusion can be made. There are no comparative analyses to test their hypothesis.
The method for selection of epitope segments is not well justified. There is little attempt to provide rationale or description of the segments chosen and how they fit within the antigens, thus justifying segments over multiple antigens.
The grammatical errors, lack of clarity accompanied by little attention to style and readability render the manuscript quite illegible.
There is no excuse for so many errors in the references.
-
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 manuscript describes the vaccine potential of unstructured P. falciparum merozoite protein fragments 25 amino acid long belonging to 3 different protein families. The work is well performed, easily reproducible and clearly described.
Referees cross-commenting
The polymorphic residues should be highlighted in the supplementary figure.
Significance
The use of protein fragments whose structure can be predicted by their sequence has been exploited in many studies for the development of vaccines or other biologicals. In this studies the authors selected 3 different families belonging to the red blood stage of the parasite. The table showing the sequences selected is not readable and should be clearly provided in the supplementary section. In addition, polymorphic residues should be highlighted. In addition, it is not to mention why the authors used immune rabbit sera obtained by injection of the 3 poly-epitopes instead of obtaining by affinity chromatography antigen specific human antibodies from sera of individuals living in endemic regions which could provide a direct and clear answer whether a protective vaccine could be obtained.
-
Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.
Learn more at Review Commons
Referee #1
Evidence, reproducibility and clarity
This manuscript by Deshmukh et al is aimed at generating chimeric antigens that can be useful for making next generation vaccines that block blood stage infection by malaria parasite. Given that there is no blood stage vaccine against malaria and available liver stage vaccine shows only limited efficacy that too only in Africa, there is dire need for having novel approaches to generate successful vaccines. In the past attempts have been made to make multivalent vaccines but have not been successful. Nevertheless, it is still a good option as single target blood-stage vaccines have failed. Authors propose to target cytoadhesion and host erythrocyte invasion. For this purpose, they have selected epitopes from PfEMP1/VarB family members, which poses a major challenge as at least 60 genes encode them and they exhibit variations which facilitate the escape from the immune system. The other two chimeras target invasion related proteins like MSPs and adhesins shed by micronemes and rhoptries, which are critical for invasion. The reported work is interesting and provides a useful approach towards developing vaccines against blood stage infection.
Comments:
- The peptides used in InvB chimera did not show good reactivity especially when compared to VarB or MSP peptides. Please discuss the possible reasons.
- It will be interesting to determine if blocking a specific VarB/PfEMP1 alters expression of other members. Based on the data provided in Fig. 4E, can a chimera be designed which only includes PfEMP1 that are represented well in HBEC-5i population?
- Some of the invasion related proteins like RH5 and EBA175 are not present at parasite surface, instead, secreted from rhoptries and micronemes. It will be nice to perform Western blots on condition medium and see if InvP (or even MSP and VarB) antibodies recognizes the secreted version of these proteins.
- Fig. 6E- Statistics need to be provided for inhibition at 12.3 and 25ug.
- Plasmodium uses multiple ligand-receptor interaction, which could depend (e.g. EBA-glycohophorins) or operate independent (e.g. RH5-basigin) of sialic acid. While there is representation from candidates from both of these families, most studies especially growth rate assays (Fig. 6E) have been carried using 3D7 strain, which does not require sialic acid. It is possible that if similar experiments were performed using sialic acid-sensitive strains, InvP and MSP antibodies may cause greater inhibition of parasite growth, which may be worth testing.
- The direct effect of InvP and MSP Abs should be tested directly on host erythrocyte invasion.
Significance
Present study proposes novel strategies for the development of anti-malarial vaccine.
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www.biorxiv.org www.biorxiv.org
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Reply to the reviewers
We thank the reviewers for their kind works and helpful insights and suggestions. Below, we have pasted the reviews (in italics), with our responses:
Reviewer #1 (Evidence, reproducibility and clarity (Required)):
The study provides insights into how polyploidization via endomitosis may arise in human hepatocytes by studying fetal liver cell line-derived organoids. Using live cell imaging and LSM microscopy, binculeation was consistently observed in two independent cell line systems, at frequencies seen in human liver and sensitive to pharmacological inhibition (GSK3i) and genetic manipulation (E2F7 & E2F8 editing). The findings presented are in line with earlier data, largely gathered studying rodents. The data is convincing and robust indicating that these systems can be used to study cause and consequences of polyploidy in human hepatocytes.
- While the authors do suggest that they provide a mechanisms how polyploidy is initiated in human hepatocytes undergoing endomitosis, ie. loss of membrane association of membrane-anchoring proteins at the midbody (e.g. Anillin, RacGAP1), I do feel that the data provided is rather descriptive and does not address a particular mechanism that may account for loss of membrane anchoring. As such, the title is making a too strong point, as, in my point of view, it associates with loss of membrane anchorage, but may not drive endomitosis. Whether this is a "passive" process in response to changes in physical forces and tension, or regulated via signalling intermediates to initiate regression of the cleavage furrow is not addressed experimentally (mislocalizing these proteins on a larger scale). Discussion seems warranted.
We agree with the reviewer that our mechanistic insights into the molecular mechanisms of endomitosis are limited, and we cannot currently prove that the loss of membrane-anchoring drives endomitosis. We have therefore toned down this conclusion and changed the title to “Binucleated human hepatocytes arise through late cytokinetic regression during endomitosis M phase”. Furthermore, we have expanded the Discussion to reflect on the gaps in knowledge and speculate about possible molecular mechanisms of endomitosis, see pages 12-16 (in particular, lines 404-423, lines 433-443, and 445-472.
I do not see the need for additional experiments, as I believe the data is robust and introduces an interesting new model where the role of ploidy can be studied in human hepatocytes ex vivo. However, if the authors wish to extend their studies and document further similarities with pathways engaged in rodents, some E2F7/8 targets relevant for ploidy control such as Anillin or PIDDosome components, or, maybe MDM2 processing for p53 activation, could be tested in wt and E2F mutant cell lines.
Unfortunately, we have not been able to look at E2F7/8 targets and their expression in E2F mutant Hep-Orgs. We performed qPCRs for some cytokinesis regulators such as Ect2, RacGap1 and Mklp1 in Hep-Orgs, however these genes are so lowly expressed that we can hardly detect them. This is likely because these transcripts are only expressed in a short period of the cell cycle during S/G2 phase, whereas the vast majority of cells in Hep-Orgs are in G1. Therefore, differences in gene expression are very difficult (if not impossible) to detect by qPCR. We also tried to perform single molecule FISH on Hep-Orgs, which would allow us to quantify lowly expressed transcripts in single cells, however despite that the smFISH stainings work well on cholangiocyte organoids and intestinal organoids, we could not get good signals in Hep-Orgs. Taken together, we are unable at this point to look into downstream targets of E2F7/8.
A minor suggestion is to clarify the term M-CDK activity in the introduction, as it may not be fully intuitive to all readers; similarly, ploidy reversal is still controversial in the field, but it is stated as a given fact.
Thank you for these suggestions, we have clarified the term M-CDK on page 3, lines 60-61, and have rephrased the sentence on ploidy reversal on page 3, lines 81-82.
Reviewer #1 (Significance (Required)):
Polyploidy at the cellular and nuclear level is a key feature of hepatocytes albeit the physiological significance of the process is not entirely clear. Increased ploidy has been linked to cancer resistance in the liver, but may pose a threat to hepatocyte survival under conditions of repeated compensatory proliferation cycles. Curiously, during normal regeneration after single surgical intervention liver regeneration is not compromised, even though it may recover faster starting when starting from higher ploidy levels. Mechanistically, most data has been generates studying rodents where it is documented that the proliferation behaviour changes around the time of weaning in mice when hepatocytes start to fail cytokinesis and undergo endomitosis, leading to cellular and nuclear polyploidy. In rodents, insulin signalling / AKT appears involved as is the E2F network and p53, activated by the caspase-2-PIDDosome.
The model system introduced here will allow mechanistic studies in human organoids and help to increase our understanding of this process in steady state and under conditions of stress.
Reviewer #2 (Evidence, reproducibility and clarity (Required)):
Summary:
Polyploid cells arise within various human tissues by multiple different mechanisms. Here, Darmasaputra et al present a study of one such mechanism, endomitosis, in liver cells using fetal-derived human hepatocyte organoids. In this model, they demonstrate that binucleated cells arise through the late regression of the cytokinetic furrow prior to abscission. They identify a rare event in cytokinetic cells - loss of midbody association with the plasma membrane - that could explain the cytokinesis failure observed in a proportion of these cells. Finally, they show that loss of Wnt signalling increases the number of binucleation events in a manner that depends on E2F7 and E2F8, similar to what has been observed in murine hepatocytes.
Major comments:
This is a compelling and well-presented study. The data presented are high quality, the experiments are well described and controlled and the conclusions are convincing. I am particularly impressed by the technical effort that the authors must have put into obtaining high quality live and IF images of dividing cells within organoids and their careful documentation of what are very rare mitotic events. In addition, the manuscript is extremely well written and I found it a pleasure to read.
- I do not think that there are additional experiments that are essential to justify the conclusions of the paper. However, I do have suggestions that I think would strengthen this work and increase its significance. As is, the authors present findings in two different areas: the documentation of cytokinesis failure in hepatocyte organoids and the role of Wnt and E2F7/8 on binucleation. It would be really nice if the two parts could be linked. For example, the authors could examine cell divisions in the organoids without Wnt either live or fixed and show that they have a higher proportion of cells undergoing cytokinetic regression or with membrane-midbody attachment defects. Alternatively, they could look at whether the expression levels of key cytokinetic genes are changed in the Wnt and E2F7/8 organoids. As I said, these experiments are not required for or the publication of this work and I will leave it up to the authors to decide if they have the time or capacity to add additional data.
We thank the reviewer for this suggestion. Unfortunately, despite substantial effort, we have been unable to perform successful live imaging of Hep-Orgs under CHIR99021 removal conditions: these organoids become very sensitive to live imaging and they also proliferate very slowly. We have tried to look at the expression of cytokinetic genes by qPCR, however these experiments were inconclusive (see also our response to reviewer #1, point 2). Thus, we cannot rule out that the increase in binucleation that we see upon CHIR99021 removal is not due to increased endomitosis, but rather occurs independently, for example by an increased survival rate of binucleated cells upon WNT removal. We have now discussed this issue and explained the limitations of our study in the discussion, pages 14-15, lines 451-460.
Finally, before publication, the authors should discuss further the mechanisms by which loss of membrane attachment during cytokinesis could occur - there is quite a lot of literature in this area on the role of RacGAP1 and Ect2 in membrane attachment that is not discussed, particularly from the lab of Mark Pentronczki (eg Kotynkova 2026 PMID: 27926870, Lekmotsev PMID: 23235882). It's surprising that the authors haven't mentioned (or looked at) Ect2 at all, especially since Ect2 levels have been shown to control polyploidy in cardiomyocytes (Liu 2019 PMID: 31597755). This at least warrants some discussion.
We thank the reviewer for pointing us to these articles. We have elaborated the discussion to include the work on rodent and human cardiomyocytes, and to explain why we think that there is no defect in ECT2 and RhoA signaling in human hepatocytes undergoing endomitosis, see pages 13-14, 404-423 and 433-443.
Minor comments:
Table 1 would be more striking as a graphical representation. I appreciate that the n numbers in the regressed cells means that statistical comparisons is not possible, but some kind of colour coding or graph would make this part clearer
We agree that Table 1 was difficult to read – we now show the data schematically in a new figure, Fig.4.
It's not clear what the difference between Hep-Org 1 and Hep-Org 2 are. Are these from different donors?
Indeed Hep-Org1 and Hep-Org2 are from different donors. We have clarified this in the text, see page 5, lines 131-133.
Reviewer #2 (Significance (Required)):
This study is an important technical development in that it reports a new system to study in depth cell biology of liver endomitosis in non-transformed and, crucially, human 3D hepatocyte organoids. The findings reported using this system are potentially interesting although they could be further developed if they were mechanistically linked together (see major comments). This work is likely to be highly interesting to scientists studying cell division, cytokinesis and hepatocyte biology. It also has wider implications for liver biology and particularly liver regeneration. Additionally, given the role of polyploidisation in many different tissues, it will likely be of interest to scientists studying polyploidy and endomitosis more generally.
My area of expertise is in cytokinesis and cell division in general, although not specifically in hepatocytes. I am not an expert in organoids.
Reviewer #3 (Evidence, reproducibility and clarity (Required)):
In this manuscript, Darmasaputra and colleagues took advantage of human hepatocyte organoids (Hep-Org) to investigate the formation of binucleated cells that naturally occurs in liver. So far, the mechanism of hepatocyte binucleation has been studied in rodents, where binucleated hepatocytes arise upon weaning through an insulin/akt pathway that inhibits furrow contraction in a fraction of cells (Ref. 21, 22). In addition, it is known that E2F7 and E2F8 downstream of the Wnt signaling repress the expression in mouse hepatocytes of several key cytokinetic proteins (AuroraB, Mklp1, Ect2, Racgap1) and thereby promote binucleation (Ref. 23).
Advances:
As seen in vivo, the authors first show that a fraction (5-15%) of cells are binucleated in two independently derived human Hep-Orgs. Live cell imaging reveals that binucleation is not due to furrow ingression defects after anaphase but rather arises from post-furrowing intercellular bridge regression. Fixed data suggest that the cytokinetic midbody formed normally but lost its anchorage to the bridge membrane. Activation of the Wnt signaling resulted in a modest but significant increase in the proportion of binucleated cells (4.5 to Major comments
- An outstanding question is whether human Hep-Orgs represent a bona-fide model to study the process of human liver binucleation. The absence of cholangiocytes, vascularization, other cell types and physiological hormones etc. might impact on the mechanism of binucleation, which is the main focus of this study. Since the mechanism of binucleation in human Hep-Orgs appears radically different from what has been reported in vivo in rodents, the authors should reproduce the lack of furrow ingression in mouse Hep-Orgs (that they were able to generate in Ref. 44). This could be done in fixed cells as in Fig. 3. Alternatively, they could use live cell imaging and chemical dyes such as SiR-Tubulin and Cell Mask to label microtubules and the plasma membrane, respectively, without the need of creating genome-edited reporter lines.
The mechanism of endomitosis that we observe in human hepatocyte organoids is indeed different from what has been observed in mouse hepatocytes. Unfortunately, mouse Hep-Orgs are more difficult to generate as they require a two-step perfusion protocol from live mice (described in Hu et al., 2018). Additionally, mouse Hep-Orgs do not survive freezing, so to be able to perform the suggested experiments, we would need to generate new mouse Hep-Org lines. As our collaborators are currently not performing any experiments with mouse livers, we would need to request an ethical permit to generate these organoids, which would take several months. We have seriously considered this option, however due to the substantial investment in time and resources, we feel these experiments would be more suited for a follow-up study.
To nonetheless better clarify the differences between what has been observed in rodents, and what we see in the Hep-Orgs, we have added a paragraph in the discussion, see pages 14-15 lines 433-460.
The videos acquired in Fig. 2 contain much more information than presented. The authors should measure the rate of furrow ingression, the extend of spindle elongation, the time of MT severing and the time of furrow/bridge regression after cytokinesis onset. All these parameters are important since spindle elongation and furrow ingression are altered in rodents. Is this also the case in human Hep-orgs? Furthermore, the spindle seems very different (bent bridges) in endomitotic compared to canonical cytokinesis (Fig. 2A). Finally, the authors should provide more time points during the time of furrow regression to better show how this phenomenon occurs. It seems, based on fixed images, that the midbody stays attached to the plasma yhmembrane in an asymmetric manner (i.e. does not fully detach, contrary to what is stated in the text). 3D reconstructions in fixed cells and a further characterization of the movies would clarify this point.
We thank the reviewer for this suggestion. Although there are some technical limitations that pose some restrictions (explained below), we have extended our analyses where possible. In our live imaging, we use 5-minute time intervals with 4 mm z-slices, which allows a delicate balance between having enough frames in M phase, and imaging for at least 48 hours, which is required to catch enough divisions. We are unable to image with smaller time intervals or smaller z-slices, as this leads to phototoxicity. Nonetheless, using these settings, we can get an indication of the rate of furrow ingression, time of severing and the time of furrow regression:
- We find that the time of furrowing onset and the rate of furrow ingression is very similar between canonical M phases and endomitosis M phases: we have now added this data in the results section, page 7, lines 192-199 and Fig. 2D.
- The time of cytokinetic regression is more variable between endomitoses events, and can range between 30 minutes and 2,5 hours. We have also added this information to page 7, lines 199-202and Fig. 2E
- The time of MT severing is similar between endomitosis M phases, as we show in Fig. 2C
- Unfortunately, we cannot accurately measure the extent of spindle elongation, as the divisions occur in 3D and our Z resolution is not good enough. Regarding the observation that the spindle looks different in the endomitosis example in Fig. 2A: we have quantified how often we observe bent midzones in endomitosis versus canonical M phases, and this occurs in 60% of canonical (n=12/20) and 83% of endomitosis M phases (n=15/18). We have now added this information in the results section, page 6, lines 1862-185.
- We have quantified how often we see the midbody remaining attached to one side of the plasma membrane versus fully detaching: we find that in 6 out of 9 late stage endomitotic regressions, the membrane is detached from both sides, and in 3 out of 9, it remains attached to one side. We have added this information to the results section, page 8 line 249-251.
DAPI staining is not sensitive enough to detect thin chromatin bridges. To rule out that post-furrowing regression is not merely due to the present of DNA bridges, the authors should confirm their results with LAP2b staining (see PMID 19203582).
To exclude the presence of ultrafine DNA bridges during anaphase, we have performed a staining for RIF1, a factor that localizes to ultrafine DNA bridges in anaphase and is required for their resolution (Hengeveld et al, 2015, PMID: 26256213). In early anaphase, we find many RIF1-positive thread-like structures, as has been described before in other non-transformed and non-stressed cells. However, in late anaphase and telophase, we never observe these fibers (n=57/57), suggesting that they are fully resolved and are not the cause of cytokinetic regression. We have added this data to the results section, see page 8, lines 226-234, and Fig. S1.
The authors shows that binucleation results from defective anchorage of the bridge membrane to the midbody, but the molecular mechanism remains elusive and should be further probed. In Fig. 3, there is no obvious changes in the investigated markers. Are the intensities of RACGAP1, Anillin, CIT-K reduced in regressing cells? Are ECT2, activated (phospho) Myosin II, CEP55/ESCRT-III, (activated) AuroraB and MKLP1 normally localized/concentrated? ECT2, AuroraB and MKLP1 are regulated by E2F7/8 (Ref. 23) and AuroraB inactivation after bridge formation leads to late regression (PMID 19203582).
We agree with the reviewer that the molecular mechanism by which midbodies lose their attachment to the membrane is currently unclear. We do not see any clear differences in the intensities of RACGAP1, Anillin, or CIT-K in cells undergoing endomitotic regression. We also do not expect large differences in localization or abundancies of ECT2, AuroraB or MKLP1, because if this were the case, you would expect differences in early cytokinesis in endomitosis, such as a delay or a slower rate of furrow ingression. We did perform additional IF experiments to investigate the localization of SEPT9, a septin that is expressed in human hepatocytes and that has essential functions in membrane anchorage during cytokinesis. Although we find that SEPT9 exhibits more variable localizations than RACGAP1, Anillin, and CIT-K, we find that in the majority of endomitotic regressions, it is also absent from the regressed membrane (n=5/7 cells). We have added this data to the results section on page 9, and in the figures Fig. 3C and Fig.4C.
The results of Fig. 4F indicate that the increased proportion of binucleated cells upon CHIR99021 removal depends on E2F7/8. Without live cell imaging (or FISH experiments) the authors cannot conclude that conclude that the increase in endomitosis is dependent on E2F7/8. A decrease in binucleation could indeed not imply a reduced occurrence of endomitosis. For instance, it is possible that E2F7/8 KO induces the formation of mononucleated 4n cells due to early mitotic failure. This issue should be clarified.
The reviewer raises an important point. Unfortunately, we were unable to generate E2F7/8 KO lines containing fluorescent nuclear and membrane markers, which would allow us to perform live-imaging and confirm that these organoids perform less endomitosis. As an alternative, we tried to use SiR-Tubulin dyes for live imaging, but even at very low concentrations these dyes are toxic for the organoids. To exclude the possibility that E2F7/8 KO induces the formation of mononucleated 4n cells, we have measured the DNA content in wildtype, E2F7 and E2F8 lines, and found that the distribution of ploidies is very similar between these lines, both in normal growth conditions as well as upon removal of CHIR99021 (see the new supplemental figure, Fig. S3). We thus think it is unlikely that E2F7/8 KO induces the formation of mononucleated 4n, however it remains possible that the differences in percentage of binucleated cells arise independently of endomitosis. We have now toned down our conclusions on the function of WNT signaling and E2F7/8 in endomitosis, and discussed alternative explanations for our findings in the discussion, see page 14, lines 451-460.
Binucleation increases with age both in humans and rodents. Could this feature be mimicked in the human Hep-Org by leaving the organoids longer in culture? (optional but would reinforce the value of the model).
We do not see an increase in binucleation percentages in organoids that are kept longer in cultures, and we have now also tested the effect of growing the organoids in a “differentiation medium”, which was previously described to give rise to more mature hepatocyte gene expression (Hu et al. 2018), however we see no significant differences in the percentages of binucleated cells per organoid. We have now included this data, as well as our analyses of the effect of insulin in the growth medium (see our response to point 12 below) in the results section on page 11 lines 341-353 and we further discuss this point in the Discussion, pages 12-13, lines 389-397.
Minor comments
The results of Table 1 are based on very few fixed cells (3 to 6). The authors should consider increasing the number of regressing cells.
We are aware that the number of endomitotic regressions is very low. Unfortunately, it is extremely challenging to catch these events by IF: cells in Hep-Orgs cycle very slowly (they divide once every ±50 hours), and thus very few cells are in M phase at any given moment (only 1 or 2 cells per organoid) – the chance that this cell is then also in telophase is even lower, and then only ± 5% of the telophase are actually undergoing endomitosis. Due to technical limitations of the organoid IF staining protocol, it is not trivial to scale up these experiments, making it very difficult to find more than 3-5 endomitotic regressions per condition. Despite the low numbers of endomitotic regressions that we have identified, we find that RacGAP1, Anillin and CIT-K localize in a very similar manner in cells undergoing endomitosis. For SEPT9, we see a little bit more variation in the localizations, but also here the majority of cells in undergoing endomitosis have lost SEPT9 membrane association on the regressed membrane (see Fig. 4C).
Is WNT signaling modified by E2F7/8 mutations? To conclude that "WNT signaling inhibits binucleation in an E2F7/8-dependent manner", the authors should check that E2F7/8 KO does not impair the increase of WNT signaling upon CHIR99021 removal.
We had not thought of this option, but it is indeed possible that E2F7/8 influences the ability of cells to respond to CHIR99021 removal. WNT regulators are not known to be targets of E2F7 or E2F8 in mice (see PMIDs: 22180533, 18194653, and 23064264), however as we have not analyzed the gene expression changes in E2F7 or E2F8 mutant organoids, we cannot exclude the possibility that CHIR99021 has different effects in E2F7/E2F8 knock-out cells. We now discuss this possibility in the discussion, page 15, lines 459-460.
Please provide movies of the cells presented in Fig. 2A.
We have included movies of these cells, see Supplemental Movie 1 and Supplemental Movie 2.
- Removal of CHIR99021 induces major shape changes and lumen formation (rather than "exhibited some morphological changes" as stated). Could the author speculate on this?
WNT signaling is likely important for many aspects of hepatocyte growth and differentiation, and it is possible that upon CHIR99021 removal, Hep-Orgs are starting to differentiate and become more secretory, which would explain why they start forming larger lumens. We now discuss this in more detail in the final part of the results section, see page 11 lines 341-353, and in the discussion, page 15 lines 462-472.
- Fig. 4: Why do the authors use the cell line-1 that has the lowest level of binucleation in this experiment? Would the results be the same in cell line 2? (optional)
We perform most experiments in Hep-Org line 1 because this line is easier to maintain in culture, and we have been unable to generate CRISPR knock-outs in Hep-Org line 2.
- Would insulin increase the proportion of binucleated cells, as in rodents? (optional)
We have tested this, but do not see a difference in the percentage of binucleated cells when we either increase or decrease the concentration of insulin in the growth medium. We have now added this data in the results section, see page 11, lines 347-350 and Fig. 5J.
Reviewer #3 (Significance (Required)):
Strengths and limitations:
The manuscript is well written, easy to follow, and the quality of the data is overall high. A clear strength of this study is the use of state-of-the-art human hepatocyte organoids and genome editing (to generate reporter lines and to KO E2F7/8). This allows the authors to address the mechanism of binucleation in a human context. Interestingly, it revealed both similarities (e.g. E2F7/8 depends for binucleation) and striking mechanistic differences (e.g. post-furrowing regression) between rodent and human systems. The study is rather descriptive -which is fine- but deeper mechanistic insights would strengthen the conclusions of the manuscript. For instance, "our results identify how human hepatocytes inhibit cell division in endomitosis" appears as an overstatement since the molecular reason of midbody anchorage defects remains elusive.
We thank the reviewer for their kind words. Unfortunately, we have been unable to gain deeper mechanistic insights into the molecular mechanism of membrane regression in endomitosis. We have therefore toned down our conclusions, see the new concluding sentence in the abstract, page 2, lines 35-36.
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Referee #3
Evidence, reproducibility and clarity
In this manuscript, Darmasaputra and colleagues took advantage of human hepatocyte organoids (Hep-Org) to investigate the formation of binucleated cells that naturally occurs in liver. So far, the mechanism of hepatocyte binucleation has been studied in rodents, where binucleated hepatocytes arise upon weaning through an insulin/akt pathway that inhibits furrow contraction in a fraction of cells (Ref. 21, 22). In addition, it is known that E2F7 and E2F8 downstream of the Wnt signaling repress the expression in mouse hepatocytes of several key cytokinetic proteins (AuroraB, Mklp1, Ect2, Racgap1) and thereby promote binucleation (Ref. 23).
Advances:
As seen in vivo, the authors first show that a fraction (5-15%) of cells are binucleated in two independently derived human Hep-Orgs. Live cell imaging reveals that binucleation is not due to furrow ingression defects after anaphase but rather arises from post-furrowing intercellular bridge regression. Fixed data suggest that the cytokinetic midbody formed normally but lost its anchorage to the bridge membrane. Activation of the Wnt signaling resulted in a modest but significant increase in the proportion of binucleated cells (4.5 to <8% or 3 to <6% depending on the subfigures). This increase depended on the presence of E2F7 and E2F8. This study represents the first description of binucleation in a human organoid context.
Major comments
- An outstanding question is whether human Hep-Orgs represent a bona-fide model to study the process of human liver binucleation. The absence of cholangiocytes, vascularization, other cell types and physiological hormones etc. might impact on the mechanism of binucleation, which is the main focus of this study. Since the mechanism of binucleation in human Hep-Orgs appears radically different from what has been reported in vivo in rodents, the authors should reproduce the lack of furrow ingression in mouse Hep-Orgs (that they were able to generate in Ref. 44). This could be done in fixed cells as in Fig. 3. Alternatively, they could use live cell imaging and chemical dyes such as SiR-Tubulin and Cell Mask to label microtubules and the plasma membrane, respectively, without the need of creating genome-edited reporter lines.
- The videos acquired in Fig. 2 contain much more information than presented. The authors should measure the rate of furrow ingression, the extend of spindle elongation, the time of MT severing and the time of furrow/bridge regression after cytokinesis onset. All these parameters are important since spindle elongation and furrow ingression are altered in rodents. Is this also the case in human Hep-orgs? Furthermore, the spindle seems very different (bent bridges) in endomitotic compared to canonical cytokinesis (Fig. 2A). Finally, the authors should provide more time points during the time of furrow regression to better show how this phenomenon occurs. It seems, based on fixed images, that the midbody stays attached to the plasma membrane in an asymmetric manner (i.e. does not fully detach, contrary to what is stated in the text). 3D reconstructions in fixed cells and a further characterization of the movies would clarify this point.
- DAPI staining is not sensitive enough to detect thin chromatin bridges. To rule out that post-furrowing regression is not merely due to the present of DNA bridges, the authors should confirm their results with LAP2b staining (see PMID 19203582).
- The authors shows that binucleation results from defective anchorage of the bridge membrane to the midbody, but the molecular mechanism remains elusive and should be further probed. In Fig. 3, there is no obvious changes in the investigated markers. Are the intensities of RACGAP1, Anillin, CIT-K reduced in regressing cells? Are ECT2, activated (phospho) Myosin II, CEP55/ESCRT-III, (activated) AuroraB and MKLP1 normally localized/concentrated? ECT2, AuroraB and MKLP1 are regulated by E2F7/8 (Ref. 23) and AuroraB inactivation after bridge formation leads to late regression (PMID 19203582).
- The results of Fig. 4F indicate that the increased proportion of binucleated cells upon CHIR99021 removal depends on E2F7/8. Without live cell imaging (or FISH experiments) the authors cannot conclude that conclude that the increase in endomitosis is dependent on E2F7/8. A decrease in binucleation could indeed not imply a reduced occurrence of endomitosis. For instance, it is possible that E2F7/8 KO induces the formation of mononucleated 4n cells due to early mitotic failure. This issue should be clarified.
- Binucleation increases with age both in humans and rodents. Could this feature be mimicked in the human Hep-Org by leaving the organoids longer in culture? (optional but would reinforce the value of the model).
Minor comments
- The results of Table 1 are based on very few fixed cells (3 to 6). The authors should consider increasing the number of regressing cells.
- Is WNT signaling modified by E2F7/8 mutations? To conclude that "WNT signaling inhibits binucleation in an E2F7/8-dependent manner", the authors should check that E2F7/8 KO does not impair the increase of WNT signaling upon CHIR99021 removal.
- Please provide movies of the cells presented in Fig. 2A.
- Removal of CHIR99021 induces major shape changes and lumen formation (rather than "exhibited some morphological changes" as stated). Could the author speculate on this?
- Fig. 4: Why do the authors use the cell line-1 that has the lowest level of binucleation in this experiment? Would the results be the same in cell line 2? (optional)
- Would insulin increase the proportion of binucleated cells, as in rodents? (optional)
Significance
Strengths and limitations:
The manuscript is well written, easy to follow, and the quality of the data is overall high. A clear strength of this study is the use of state-of-the-art human hepatocyte organoids and genome editing (to generate reporter lines and to KO E2F7/8). This allows the authors to address the mechanism of binucleation in a human context. Interestingly, it revealed both similarities (e.g. E2F7/8 depends for binucleation) and striking mechanistic differences (e.g. post-furrowing regression) between rodent and human systems. The study is rather descriptive -which is fine- but deeper mechanistic insights would strengthen the conclusions of the manuscript. For instance, "our results identify how human hepatocytes inhibit cell division in endomitosis" appears as an overstatement since the molecular reason of midbody anchorage defects remains elusive.
Audience:
broad, basic research.
Field of expertise:
cell biology of cytokinesis
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Referee #2
Evidence, reproducibility and clarity
Summary:
Polyploid cells arise within various human tissues by multiple different mechanisms. Here, Darmasaputra et al present a study of one such mechanism, endomitosis, in liver cells using fetal-derived human hepatocyte organoids. In this model, they demonstrate that binucleated cells arise through the late regression of the cytokinetic furrow prior to abscission. They identify a rare event in cytokinetic cells - loss of midbody association with the plasma membrane - that could explain the cytokinesis failure observed in a proportion of these cells. Finally, they show that loss of Wnt signalling increases the number of binucleation events in a manner that depends on E2F7 and E2F8, similar to what has been observed in murine hepatocytes.
Major comments:
This is a compelling and well-presented study. The data presented are high quality, the experiments are well described and controlled and the conclusions are convincing. I am particularly impressed by the technical effort that the authors must have put into obtaining high quality live and IF images of dividing cells within organoids and their careful documentation of what are very rare mitotic events. In addition, the manuscript is extremely well written and I found it a pleasure to read.
I do not think that there are additional experiments that are essential to justify the conclusions of the paper. However, I do have suggestions that I think would strengthen this work and increase its significance. As is, the authors present findings in two different areas: the documentation of cytokinesis failure in hepatocyte organoids and the role of Wnt and E2F7/8 on binucleation. It would be really nice if the two parts could be linked. For example, the authors could examine cell divisions in the organoids without Wnt either live or fixed and show that they have a higher proportion of cells undergoing cytokinetic regression or with membrane-midbody attachment defects. Alternatively, they could look at whether the expression levels of key cytokinetic genes are changed in the Wnt and E2F7/8 organoids. As I said, these experiments are not required for or the publication of this work and I will leave it up to the authors to decide if they have the time or capacity to add additional data.
Finally, before publication, the authors should discuss further the mechanisms by which loss of membrane attachment during cytokinesis could occur - there is quite a lot of literature in this area on the role of RacGAP1 and Ect2 in membrane attachment that is not discussed, particularly from the lab of Mark Pentronczki (eg Kotynkova 2026 PMID: 27926870, Lekmotsev PMID: 23235882). It's surprising that the authors haven't mentioned (or looked at) Ect2 at all, especially since Ect2 levels have been shown to control polyploidy in cardiomyocytes (Liu 2019 PMID: 31597755). This at least warrants some discussion.
Minor comments:
- Table 1 would be more striking as a graphical representation. I appreciate that the n numbers in the regressed cells means that statistical comparisons is not possible, but some kind of colour coding or graph would make this part clearer
- It's not clear what the difference between Hep-Org 1 and Hep-Org 2 are. Are these from different donors?
Significance
This study is an important technical development in that it reports a new system to study in depth cell biology of liver endomitosis in non-transformed and, crucially, human 3D hepatocyte organoids. The findings reported using this system are potentially interesting although they could be further developed if they were mechanistically linked together (see major comments). This work is likely to be highly interesting to scientists studying cell division, cytokinesis and hepatocyte biology. It also has wider implications for liver biology and particularly liver regeneration. Additionally, given the role of polyploidisation in many different tissues, it will likely be of interest to scientists studying polyploidy and endomitosis more generally.
My area of expertise is in cytokinesis and cell division in general, although not specifically in hepatocytes. I am not an expert in organoids.
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Referee #1
Evidence, reproducibility and clarity
The study provides insights into how polyploidization via endomitosis may arise in human hepatocytes by studying fetal liver cell line-derived organoids. Using live cell imaging and LSM microscopy, binculeation was consistently observed in two independent cell line systems, at frequencies seen in human liver and sensitive to pharmacological inhibition (GSK3i) and genetic manipulation (E2F7 & E2F8 editing). The findings presented are in line with earlier data, largely gathered studying rodents. The data is convincing and robust indicating that these systems can be used to study cause and consequences of polyploidy in human hepatocytes.
While the authors do suggest that they provide a mechanisms how polyploidy is initiated in human hepatocytes undergoing endomitosis, ie. loss of membrane association of membrane-anchoring proteins at the midbody (e.g. Anillin, RacGAP1), I do feel that the data provided is rather descriptive and does not address a particular mechanism that may account for loss of membrane anchoring. As such, the title is making a too strong point, as, in my point of view, it associates with loss of membrane anchorage, but may not drive endomitosis. Whether this is a "passive" process in response to changes in physical forces and tension, or regulated via signalling intermediates to initiate regression of the cleavage furrow is not addressed experimentally (mislocalizing these proteins on a larger scale). Discussion seems warranted.
I do not see the need for additional experiments, as I believe the data is robust and introduces an interesting new model where the role of ploidy can be studied in human hepatocytes ex vivo. However, if the authors wish to extend their studies and document further similarities with pathways engaged in rodents, some E2F7/8 targets relevant for ploidy control such as Anillin or PIDDosome components, or, maybe MDM2 processing for p53 activation, could be tested in wt and E2F mutant cell lines.
A minor suggestion is to clarify the term M-CDK activity in the introduction, as it may not be fully intuitive to all readers; similarly, ploidy reversal is still controversial in the field, but it is stated as a given fact.
Significance
Polyploidy at the cellular and nuclear level is a key feature of hepatocytes albeit the physiological significance of the process is not entirely clear. Increased ploidy has been linked to cancer resistance in the liver, but may pose a threat to hepatocyte survival under conditions of repeated compensatory proliferation cycles. Curiously, during normal regeneration after single surgical intervention liver regeneration is not compromised, even though it may recover faster starting when starting from higher ploidy levels. Mechanistically, most data has been generates studying rodents where it is documented that the proliferation behaviour changes around the time of weaning in mice when hepatocytes start to fail cytokinesis and undergo endomitosis, leading to cellular and nuclear polyploidy. In rodents, insulin signalling / AKT appears involved as is the E2F network and p53, activated by the caspase-2-PIDDosome. The model system introduced here will allow mechanistic studies in human organoids and help to increase our understanding of this process in steady state and under conditions of stress.
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Reply to the reviewers
*Reviewer #1 (Evidence, reproducibility and clarity (Required)):
Deletion of CerS4 in the entire mouse epidermis throughout development via the K14-Cre results in enlarged sebaceous glands and perturbed HFSC molecular phenotype. There is low or no expression of CD34, a known marker of the HFSCs along with apparent reduction of several other HFSC markers and acquisition of a more differentiated cell phenotype in these cells. Interestingly, skin and hair follicles seem to remain normal otherwise up to advanced age, though this contradicts the notion that HFSC were indeed affected at the functional level. The data does not demonstrate 'gradual decline' in the HFSC compartment, as claimed by the authors, but rather seem to indicate that the adult HFSC compartment is not properly established in its molecular signatures. Organoid cultures document defects in HFSC, which included reduced proliferation in the CerS4 KO cells. Lipid composition in plasma membranes was also affected by the CerS4 KO. Associated with this, Wnt signal transduction is also affected according to experiments that enhance the strength of wnt signals via a specific small molecular agonist of the pathway. Finally, the authors discover a resemblance of the mouse KO immune-phenotype, with human atopic dermatitis. The study is likely of interest to a specialized readership in skin biology and dermatology and adds to previous studies on CerS4 in skin that erroneously placed its role in the sebaceous gland. [The authors here demonstrate that deletion of CerS4 in the sebaceous glands via SCD3-Cre led to no phenotype, contradicting the previous assessment that CerS4 is important in sebaceous glands.] The study would need to be corrected in a few of its interpretations regarding stem cells to better match the data, as indicated below. *
We thank the reviewer for the constructive comments that will help us to improve the manuscript. In particular, it is clear that we have not been sufficiently clear in the data presentation.
Firstly, contrary to what the reviewer states, the CerS4epi-/- mice have a very strong hair follicle phenotype that results in complete hair loss. Also the epidermis is not normal as an inflammatory phenotype develops later, after the hair follicle architecture and function has been disrupted. Thus, there are clear functional consequences to the hair follicle and epidermis that arise from the dysfunction of the HFSC compartment. We will edit the manuscript and add photodocumentation of the macroscopic phenotype to ensure clarity.
We fully agree with the reviewer that the initial phenotype is inability to establish the adult hair follicle stem cell niche, as shown by the single cell sequencing data and as also stated in the manuscript title. We will further edit the manuscript to clarify this conclusion. Importantly, however, some hair follicle stem cells are generated but these become gradually depleted. So there is a dual phenotype: an inability to efficiently establish and maintain the hair follicle stem cell population. We will clarify this in the text.
Finally, we want to emphasize that the main finding of this manuscript is that hair follicle stem cells contain a unique lipid profile and perturbing this profile by deleting CerS4 leads to profound defects in stem cell fate regulation through Wnt. This is a completely new finding that has implications far beyond dermatology.
Major revisions: Fig1B - the data seems to simply shows that bulge cells express less or no CD34 and not that ' CerS4epi-/- mice showed reduced HFSC numbers'; the primary FACS data should be shown somewhere too.
Outer bulge hair follicle stem cells are defined as a population of cells that expresses CD34 and integrin-a6. The quantifications in Fig 1B show the quantitative FACS analyses of the size of this population and indicate less CD34+/integrin-a6+ cells in CerS4epi-/- epidermis. The mean fluorescence intensity of CD34 and integrin-a6 was not reduced in these CerS4epi-/- stem cells. This FACS analysis therefore allows the conclusion that there are less CD34+/integrin-a6+ cells in CerS4epi-/- epidermis. We will include the original FACS plot data to support this notion and the quantifications.
The conclusion that stemness is affected, and HFSCs lose their normal gene expression signature is at more convincing after looking at other HFSC markers down the road in the paper. However, in the absence of functional assays that would demonstrate stem cell function is lacking and seeing that hair follicles are maintained and grow in long-term, the notion that stem cells are lacking in these conditions is not supported by the data.
We appreciate that the reviewer finds the marker gene analysis convincing. To assay stem cell functionality, we have used the organoid assays (spheroid formation is classical, widely used assay for stemness). Using these functional assays we observe impaired self-renewal of stem cells (Fig. 3D), enhanced differentiation (Fig. 3I), and altered Wnt responsiveness (Fig. 5 E, F), all indicative of stem cell dysfunction and explaining the in vivo phenotypes of altered stem cell differentiation and inability to establish and maintain the stem cell population.
In the revised manuscript we will also include measurements of stem cell self-renewal in vivo using BrdU incorporation and provide more detailed description on the hair loss phenotype of the mice to further strengthen this conclusion.
*The conclusion after figure 2: "Collectively, these data indicate that CerS4-deficiency triggers ... ... gradual depletion of the quiescent HFSC compartment." There is no data showing gradual depletion of the quiescent HFSC compartment. We would need to see a gradual activation of HFSCs with over proliferation to conclude this. There is some data albeit not always convincing (see NFAC1 staining in Fig. 5C) indicating loss of markers associated with quiescence but there is no data indicating 'gradual' loss of markers. *
We agree with the reviewer that showing gradual activation of the HFSCs in vivo is important to conclude loss of quiescence. We will include in situ stainings of in vivo BrdU labeling and quantify proliferation in the hair follicle bulge stem cell region. Preliminary data of P47 mice already shows a clear increase in BrdU+ cell in the stem cell compartment in CerS4epi-/- skin . Further analysis at P21 will be carried out during the revision.
*Minor revisions: *
- Figure 1C legend - please spell out what are the abbreviations for the different subpopulations; please show these populations as % as opposed to absolute numbers. *
We will edit the Figure 1C legend for clarity and express the populations as %.
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*Figure 1D - please make it clear in the cartoon what the different sub-populations listed are; *
We will edit the cartoon for clarity.
Is OB1 a CD34- HFSC population?
The outer bulge 1 (OB1) is a population of cells that expresses hair follicle stem cell markers, including CD34. We will clarify this in the legend.
Fig. 3B - the colors of the legend do not match the colors in the data so it is confusing as to which one is which!
We will alter the colors to match the data and thank the reviewer for pointing this out.
Fig 5C - the differences in NFATc1 are not visible in the images shown
We apologize for the suboptimal quality of these images and will replace them with higher resolution images to more clearly demonstrate the difference.
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Reviewer #2 (Evidence, reproducibility and clarity (Required)):
The manuscript authored by Peters et al. titled "Sphingolipid metabolism orchestrates the establishment of the adult hair follicle stem cell niche to control skin homeostasis" elucidates the critical role of ceramide synthase 4 (CerS4) in the epidermal stem cell niche, particularly in regulating hair follicle bulge stem cells (HFSCs). Using epidermal specific CerS4 knockout mice as an in vivo model and hair follicle organoid culture as an ex vivo model, the authors conducted a comprehensive analysis, which includes cutting edge approaches such as scRNA-seq, proteomics, and lipidomics. The results highlight CerS4's function in the establishment/maintenance of the HFSC niche, as absence of CerS4 changes HFSCs' number and differentiation state. Potential underlying mechanisms identified include altered membrane lipid profiles and Wnt signaling responsiveness. Possible link to a chronic inflammatory skin disease, atopic dermatitis, is also implicated. The data presented are generally of high quality, and the work is significant as it uncovers a new regulator of HFSC fate with mechanistic connection to lipid metabolism. *
We thank the reviewer for the positive assessment of our work and finding it to be of high quality and significance. We further appreciate the constructive comments that will further help us to improve the manuscript.
*However, some issues were identified, most of them having to do with in vivo characterization and data interpretation:
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*Major: 1. The in vivo HFSC phenotype can be better characterized. "Collective, these data show that CerS4 in HFSCs is essential to establish the adult stem cell compartment and to assure lineage fidelity." - this statement premature based on order of the data shown. Also the trajectory difference shown in Figure 2A is not striking. Subclustering out the relative cell subsets and redo the analysis might help to tease out the difference. Additional experiments such as lineage tracing would be useful to support the notion that there is lineage fidelity issue in the mutant - though it is understood that this is quite involved and may lie outside the scope of the current study. Are bulge cells in the mutant proliferative? - the authors should consider in vivo Edu labelling experiment or the like to assess the quiescence/proliferation of the bulge cells. Finally, analyzing hair follicles at earlier stages might help to clarify when and where the bulge and sebaceous gland changes start - is possible that aberrant divergence of bulge/sebaceous fates occur prior to the establishment of a stable bulge fate? *
We thank the reviewer for suggesting additional analyses of the single cell sequencing data. We have performed subclustering of the relevant populations for the trajectory analyses to more clearly demonstrate the altered lineage trajectories. We will include these new analyses in the manuscript. Importantly, the in vitro organoids show abnormal differentiation (Fig. 3H, 3I, Supplementary Fig. 2G), closely resembling the in vivo phenotypes, thereby strengthening the conclusion of cell-autonomously altered lineage trajectories of the hair follicle stem cells.
We will further preform in vivo BrdU labeling as suggested. These experiments have already been initiated and preliminary data show increased proliferation in the bulge stem cell region of CerS4epi-/- mice in older mice (P47). The data will be included to emphasize long term loss of quiescence in the stem cell compartment in CerS4epi-/- mice.
Understanding the early development of bulge and sebaceous fates is indeed an interesting question. This will be addressed by detailed analyses of stem cell fate at early stages (P17-P21) using key markers of stem cell state and sebaceous linages (CD34, Krt15, Lhx2, Nfatc1, SCD1 and FASN).
Finally, we have initiated lineage tracing experiments using the stem cell-specific Lgr5-Cre to conclusively demonstrate that Cers4-deletion leads to altered routing of hair follicle stem cells into upper hair follicle and sebaceous gland fates. This notion is supported by the preliminary analyses of these experiments. We will finalize these analyses and include them in the manuscript.
*2. The exclusion of IFE contribution is not backed up by data. Figure 6D - model emphasizes HFSC involvement in atopic dermatitis, but this could be due to epidermal barrier defect. Barrier defect could already be present even though IFE morphology appears normal. Maybe TEWL is measured at the time of analysis and shows no change - if so, this data should be included. HFSC changes might contribute but the involvement of IFE cannot be excluded. The conclusion that "CerS4 expression was restricted to the hair follicle" is not supported by data. IFE expression is apparent in Figure S1C. Along this line, there is also an apparent expansion of IFE basal II in the mutant (Figure 1C). *
We acknowledge that we have not been clear enough with the evidence that allowed us to exclude the involvement of an IFE-mediated barrier defect in the early skin inflammation phenotype. To address a potential barrier defect early on, we have performed careful analysis of TEWL. In Peters at al., 2020 we demonstrate no changes in TEWL at P0, a reduced TEWL at P21 and an increased TEWL in adult CerS4epi-/- mice starting only at P33. The reduction of the TEWL in adolescent CerS4epi-/- mice (P21) is likely linked to an increased production of sebaceous lipids lubricating the skin surface at this time point (Peters et al., 2020). Thus, defects in the hair follicle stem cell compartment, present at adolescence (P21) arise prior to defects in the adult (P33) IFE barrier function. We will clarify this in the manuscript.
Cers4 expression is overall low in skin, as is typical for enzymes. In situ stainings of Cers4mRNA (Fig.S1C) indeed show a sparse signal also in the IFE. This signal is also detected in CerS4-/- sections, although the KO skin cannot be conclusively used to control background as these mice were generated by deletion of exon 3 only, and Cers4 RNAscope probes might detect remnant Cers4 RNA in these mice. Importantly, our data on FACS sorted basal cells of the IFE shows no substantial Cers4 mRNA expression in IFE progenitors (Fig. S1D) and no mRNA is detected in the IFE in the single cell sequencing. Thus, while we cannot fully exclude low levels of CerS4 expression in the IFE, the levels are substantially lower than in the HFSC and SG compartments, and the phenotype, including the slight expansion of the IFE basal II population, is very minor compared to the hair follicle phenotype. However, to avoid overinterpreting our data, we will carefully edit the conclusions to be less strong on the involvement of the IFE. Furthermore, we will perform hair follicle stem cell lineage tracing experiments as outlined in resspose to the previous point to strengthen the conclusion on the hair follicle stem cell-autonomous phenotype.
3. Figure 1 - single cell analysis was done using only 2 pairs of mice, and data in E lack statistical assessment. At the very least, data for individual pairs should be shown in supplemental data to ensure that changes are consistent in both mutant mice rather than being dominated by dramatic alteration in only 1 mutant mouse.
We naturally have rigorously analyzed the replicates to ensure that the phenotype is consistently present in both. We will include the separate analysis of the mice to document this and include statistical analysis.
Minor: 1. CerS4SCD3-/+ nomenclature is mis-leading.
We will edit this for clarity
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- Figure 2- "Furthermore, we observed expansion of the inner bulge identity marker Krt6 protein expression into outer bulge stem cells and along the infundibulum in CerS4epi-/- hair follicles, whereas in control mice Krt6 was restricted to the inner bulge (Fig. 2C)." - Krt6 staining is presented in Fig 2D, not 2C. *
We thank the reviewer for pointing out this mistake that will correct.
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- Figure 3C - size of the organoids should be quantified with statistics. The images shown do not support the statement that "Strikingly, CerS4epi-/- organoids showed altered morphology characterized by smaller size and loss of cohesion of peripheral cells from the organoid clusters (Fig. 3C), ...".*
We will include quantifications.
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- Section titled "CerS4 regulates HFSC differentiation in a stem cell autonomous manner": "CD34- integrin- a6+ cells, which based on extensive transcriptome and marker expression analyses represent a mixture of HFSCs, hair follicle outer root sheath (ORS) cells and inner bulge cells (collectively termed non-HFSCs)." - shouldn't the CD34- integrin- a6+ population also contain IFE stem/progenitor cells? Are hair follicles micro-dissected out for FACS? *
The hair follicles are not micro-dissected out for FACS, and the entire basal cell population is initially isolated. However the organoid culture conditions speficically promote the expansion of the hair follicle linage, whereas cells of the IFE are not expanded and long term maintained as extensively documented in previous publications using this organoid system (see for example Kim et al., Cell Metabolism 2020; Chacon-Martinez EMBOJ 2016).
*5. Figure 5D - please provide the working concentration of Chir99021. *
We will provide the working concentration.
*6. Figure 5F - explain what arrows mean in legends. *
We will define the arrows.
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- Figure 6A - no significant changes in Th2 and ILC2 were observed at a 95% confidence interval. Increasing mouse number will help to increase statistical power*.
We agree with the reviewer and acknowledge that this experiment was unfortunately underpowered. We will repeat it with a larger cohort.
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- Additional Wnt target genes such as Axin 2 should be looked at.*
We thank the reviewer for this suggestion, we will include analyses of additional Wnt target genes.
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- The increased BMP signaling and decreased Nfatc1 expression are seemingly contradictory.*
We apologize for the lack of clarity here. Single cell sequencing showed increased BMP-signaling of outer bulge cell cells to inner bulge cells on mRNA level (Figure S4A). No alteration in BMP signaling was detected within the outer bulge stem cell compartment (Figure 5A). Nfatc1 protein expression was analyzed in the upper bugle (Figure 5C). The data indicate no differential gene expression of ligand receptor pairs mediating BMP-signaling within the outer bulge. A decrease in Nfact1 protein expression (Fig. 5C) together with an increased proliferation (see above) and loss of label retention (Peters et al., 2015) indicates loss of quiescence in this compartment. This data does not contradict an increased BMP signaling in the inner bulge (Figure S4A). An increase in BMP signaling in the inner bulge is in line with reduced inner bulge cell cluster detected in CerS4epi-/- skin via single cell sequencing, likely contributing to the hair loss observed. We will edit this paragraph to make this more clear.
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- Paragraph starting with "It is interesting to note that ceramide availability was shown to regulate Wnt signaling in Drosophila through strong effects on recycling endocytosis of the receptors (Pepperl et al., 2013)." Is redundant in the manuscript.*
We apologize for the accidental duplication of this paragraph and thank the reviewer for noticing this mistake.
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Reviewer #3 (Evidence, reproducibility and clarity (Required)):
The authors created CerS4 mutant mice to test the role of sphingolipids in hair follicle stem cells (HFSCs) and the hair cycle. This work extends previous studies that show that loss of this enzyme leads to defects in the hair cycle and eventually hair loss. In this study the authors look early on in the course of the deletion in an attempt to understand why loss of this enzyme leads to the phenotype described previously. They use single cell profiling, proteomics, and in situ imaging to pinpoint issues in the stem cell niche that drive phenotypes and propose novel interactions between sphingolipid metabolism, Wnt signaling, and inflammation in regulation of HFSC homeostasis. The data are nicely presented, and the text is well written. The conclusions are clearly defined.*
We thank the reviewer for the positive assessment of our work and finding it well written and presented. We further appreciate the constructive comments that will further help us to improve the manuscript.
*While the data are clearly presented, there are numerous issues that are confusing to this reviewer. In addition, some of the phenotypes described are subtle, and thus do not make a convincing case.
1, In figure 1C, the cell proportion analysis suggests there are no OBII or SG in WT. I am not sure how this could be possible. In addition, there appears to be almost no sebaceous cells in either, but the mutant supposedly has much larger sebaceous glands (in Fig 2). In Fig S1I, there is no change in bulge cells? In Fig 1B, there is less HFSCs in the mutant than in the WT, but in 1C, there is more OBI in the mutant. The results in Fig 1B and C are confusing. Also, the schematic in Fig 1 is hard to read, the authors should color code the text with the image.*
It is important to emphasize that the single cell RNA sequencing was carried out at P19 when the bulge stem cell compartment only starts to be established. This explains why only few bulge stem cells are detected at this point. Nevertheless, the OBII and SG cluster is visible also in the wt in Figure 1D. We will include subclustering of the relevant subpopulations to make these populations more clearly visible also in the wt. We will also edit the labels for clarity.
Mature sebocytes are very large cells, and inherent to the single cell sequencing workflows these large cells are excluded from the sequencing libraries. Importantly, we do not detect a change in bulge stem cells in a mouse line in which CerS4 was specifically deleted only in sebocytes (Figure S1I). This analysis was carried out to exclude a sebocyte intrinsic effect on the hair follicle stem cell state and fate. The data does not contradict Fig. 1, as data in Fig. 1 was generated using a different mouse line in which CerS4 is deleted in the entire epidermal stem cell population using K14Cre. We will edit the manuscript to make this more clear.
Data presented in Fig 1B and C focus on two different aspects. Fig 1B shows the inefficient establishment and maintenance of CD34+/integrin-a6+ bulge hair follicle stem cells. The quantification is based on FACS analyses of cells expressing these cell surface molecules/stem cell markers. Fig 1C shows the quantification of the various cell states based on single cell RNA expression and subsequent clustering of the control and CerS4epi-/- epidermal cells together. The “outer bulge” cluster was annotated based on these cells expressing hair follicle stem cell markers. While the CerS4epi-/- epidermis shows increased number of cells in this cluster, the expression of all key stem cell genes (CD34, Sox9, Krt15, Lhx2) is reduced in CerS4epi-/- outer bulge 1 compartment compared to control. Thus, while this “outer bulge” population is expanded in the KO, the stem cell properties of this population are clearly attenuated, as defined by decreased expression of key stem cell transcription factors and increased expression of differentiation genes. We will clarify this in the revised version of the manuscript and also rename this cluster “outer bulge-like” to highlight that these cells are not necessarily bona fide stem cells and might not express high levels of CD34+/integrin-a6+ protein.
*2, In Figure 5, the signaling chart shows a strong upregulation of non-canonical Wnt signaling in the mutant bulge. Canonical Wnt signaling appears to be unchanged between wt and ko. Thus, it is not clear why the authors came to the conclusion that Wnt signaling is induced in the mutant. They further show expression of Lef1 and Nfatc1, but these are not typical markers used to denote canonical wnt activation, as implied. In fact, the data in Fig S4B suggest the induction of Lef1 and Tcf4 is actually very subtle. Instead, the authors should use nuclear b-catenin or transcriptional targets such as Axin or CyclinD. The authors should in fact explore the observation of Wnt5, as that appears to be the most dramatic change. In addition, the authors should use an ontological analysis with the single cell data from the tissue in the same manner that they did for organoids to take another look at molecular consequences of loss of CerS4. *
We agree with the reviewer that further analysis of canonical and non-canonical Wnt signaling will strengthen this conclusion. In our experience, nuclear b-catenin is very difficult to detect in the skin even when Wnt is highly active, but we will investigate Axin2 and CyclinD1 expression. We will also investigate Wnt5a signaling by analyzing its expression as well as its downstream target genes. We will further perform additional ontological analyses from the single cell sequencing data to strengthen the conclusions on the signaling alterations.
* 3, The authors suggest that much of the phenotype is due to inflammation. In Fig 6A, they showed analysis of CD45 cells in the skin. However, the only change was a very subtle change in Th2 cells, while no other CD45+ cells were altered.*
We agree with the reviewer and acknowledge that this experiment was unfortunately underpowered. We will repeat these analyses with a larger cohort.
4, The authors showed upregulation of Immune response in Fig 6C, but then in Fig S2, the genes downregulated are also related to immune response...how do the authors reconcile this?
We apologize for this confusion. Importantly, keratinocyte-intrinsic downregulation of homeostatic immune modulating activity is a key driver of allergic disorders, like atopic dermatitis. This barrier intrinsic immune modulation is distinct from immune cell-mediated inflammation. There is a strong overlap of genes constituting the term “Inflammatory abnormality of the skin” (Human phenotype ontology terms) Fig 6C and “Immune system process” (GOBP terms) Fig S2F. To name some, i.e. Adam-, ALOX-, ASXL- family members are annotated by both terms. Mutations in these genes are known to cause skin diseases associated with immune dysregulation but are likewise known to regulate immune responses.
Data in Figure 6C shows enrichment of this term from both up and downregulated proteins in the CerS4epi-/- condition compared to control, indicating that proteins involved in “Inflammatory abnormality of the skin” are dysregulated in CerS4epi-/- organoids. Data in Figure S2F shows the downregulation of these proteins in CerS4epi-/- organoids compared to control. We will clarify this in the text and figure legends.
5, The author propose that the phenotype in CerS4 null mice is due to disruption of the stem cell Niche. However, the authors have not shown evidence for such an effect through any in situ analysis. The single cell approaches are valuable, but in that case the niche is dissociated. The organoid work is also nice, but not exactly a stem cell niche either. The authors should instead test their hypothesis through an in situ analysis.
We have used the term niche to describe the cellular interactions between stem cells and the other niche resident cells such as the Krt6+ inner bulge cells that have been analyzed here. We will edit the conclusions for clarity. We will further include additional immunofluorescence analyses of the bulge compartment in situ, as suggested (including markers for quiescence and activation).
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Referee #3
Evidence, reproducibility and clarity
The authors created CerS4 mutant mice to test the role of sphingolipids in hair follicle stem cells (HFSCs) and the hair cycle. This work extends previous studies that show that loss of this enzyme leads to defects in the hair cycle and eventually hair loss. In this study the authors look early on in the course of the deletion in an attempt to understand why loss of this enzyme leads to the phenotype described previously. They use single cell profiling, proteomics, and in situ imaging to pinpoint issues in the stem cell niche that drive phenotypes and propose novel interactions between sphingolipid metabolism, Wnt signaling, and inflammation in regulation of HFSC homeostasis. The data are nicely presented, and the text is well written. The conclusions are clearly defined.
While the data are clearly presented, there are numerous issues that are confusing to this reviewer. In addition, some of the phenotypes described are subtle, and thus do not make a convincing case.
- In figure 1C, the cell proportion analysis suggests there are no OBII or SG in WT. I am not sure how this could be possible. In addition, there appears to be almost no sebaceous cells in either, but the mutant supposedly has much larger sebaceous glands (in Fig 2). In Fig S1I, there is no change in bulge cells? In Fig 1B, there is less HFSCs in the mutant than in the WT, but in 1C, there is more OBI in the mutant. The results in Fig 1B and C are confusing. Also, the schematic in Fig 1 is hard to read, the authors should color code the text with the image.
- In Figure 5, the signaling chart shows a strong upregulation of non-canonical Wnt signaling in the mutant bulge. Canonical Wnt signaling appears to be unchanged between wt and ko. Thus, it is not clear why the authors came to the conclusion that Wnt signaling is induced in the mutant. They further show expression of Lef1 and Nfatc1, but these are not typical markers used to denote canonical wnt activation, as implied. In fact, the data in Fig S4B suggest the induction of Lef1 and Tcf4 is actually very subtle. Instead, the authors should use nuclear b-catenin or transcriptional targets such as Axin or CyclinD. The authors should in fact explore the observation of Wnt5, as that appears to be the most dramatic change. In addition, the authors should use an ontological analysis with the single cell data from the tissue in the same manner that they did for organoids to take another look at molecular consequences of loss of CerS4.
- The authors suggest that much of the phenotype is due to inflammation. In Fig 6A, they showed analysis of CD45 cells in the skin. However, the only change was a very subtle change in Th2 cells, while no other CD45+ cells were altered.
- The authors showed upregulation of Immune response in Fig 6C, but then in Fig S2, the genes downregulated are also related to immune response...how do the authors reconcile this?
- The author propose that the phenotype in CerS4 null mice is due to disruption of the stem cell Niche. However, the authors have not shown evidence for such an effect through any in situ analysis. The single cell approaches are valuable, but in that case the niche is dissociated. The organoid work is also nice, but not exactly a stem cell niche either. The authors should instead test their hypothesis through an in situ analysis.
Significance
The authors created CerS4 mutant mice to test the role of sphingolipids in hair follicle stem cells (HFSCs) and the hair cycle. This work extends previous studies that show that loss of this enzyme leads to defects in the hair cycle and eventually hair loss. In this study the authors look early on in the course of the deletion in an attempt to understand why loss of this enzyme leads to the phenotype described previously. They use single cell profiling, proteomics, and in situ imaging to pinpoint issues in the stem cell niche that drive phenotypes and propose novel interactions between sphingolipid metabolism, Wnt signaling, and inflammation in regulation of HFSC homeostasis. The data are nicely presented, and the text is well written. The conclusions are clearly defined.
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Referee #2
Evidence, reproducibility and clarity
The manuscript authored by Peters et al. titled "Sphingolipid metabolism orchestrates the establishment of the adult hair follicle stem cell niche to control skin homeostasis" elucidates the critical role of ceramide synthase 4 (CerS4) in the epidermal stem cell niche, particularly in regulating hair follicle bulge stem cells (HFSCs). Using epidermal specific CerS4 knockout mice as an in vivo model and hair follicle organoid culture as an ex vivo model, the authors conducted a comprehensive analysis, which includes cutting edge approaches such as scRNA-seq, proteomics, and lipidomics. The results highlight CerS4's function in the establishment/maintenance of the HFSC niche, as absence of CerS4 changes HFSCs' number and differentiation state. Potential underlying mechanisms identified include altered membrane lipid profiles and Wnt signaling responsiveness. Possible link to a chronic inflammatory skin disease, atopic dermatitis, is also implicated. The data presented are generally of high quality, and the work is significant as it uncovers a new regulator of HFSC fate with mechanistic connection to lipid metabolism.
However, some issues were identified, most of them having to do with in vivo characterization and data interpretation:
Major:
- The in vivo HFSC phenotype can be better characterized. "Collective, these data show that CerS4 in HFSCs is essential to establish the adult stem cell compartment and to assure lineage fidelity." - this statement premature based on order of the data shown. Also the trajectory difference shown in Figure 2A is not striking. Subclustering out the relative cell subsets and redo the analysis might help to tease out the difference. Additional experiments such as lineage tracing would be useful to support the notion that there is lineage fidelity issue in the mutant - though it is understood that this is quite involved and may lie outside the scope of the current study. Are bulge cells in the mutant proliferative? - the authors should consider in vivo Edu labelling experiment or the like to assess the quiescence/proliferation of the bulge cells. Finally, analyzing hair follicles at earlier stages might help to clarify when and where the bulge and sebaceous gland changes start - is possible that aberrant divergence of bulge/sebaceous fates occur prior to the establishment of a stable bulge fate?
- The exclusion of IFE contribution is not backed up by data. Figure 6D - model emphasizes HFSC involvement in atopic dermatitis, but this could be due to epidermal barrier defect. Barrier defect could already be present even though IFE morphology appears normal. Maybe TEWL is measured at the time of analysis and shows no change - if so, this data should be included. HFSC changes might contribute but the involvement of IFE cannot be excluded. The conclusion that "CerS4 expression was restricted to the hair follicle" is not supported by data. IFE expression is apparent in Figure S1C. Along this line, there is also an apparent expansion of IFE basal II in the mutant (Figure 1C).
- Figure 1 - single cell analysis was done using only 2 pairs of mice, and data in E lack statistical assessment. At the very least, data for individual pairs should be shown in supplemental data to ensure that changes are consistent in both mutant mice rather than being dominated by dramatic alteration in only 1 mutant mouse.
Minor:
- CerS4SCD3-/+ nomenclature is mis-leading.
- Figure 2- "Furthermore, we observed expansion of the inner bulge identity marker Krt6 protein expression into outer bulge stem cells and along the infundibulum in CerS4epi-/- hair follicles, whereas in control mice Krt6 was restricted to the inner bulge (Fig. 2C)." - Krt6 staining is presented in Fig 2D, not 2C.
- Figure 3C - size of the organoids should be quantified with statistics. The images shown do not support the statement that "Strikingly, CerS4epi-/- organoids showed altered morphology characterized by smaller size and loss of cohesion of peripheral cells from the organoid clusters (Fig. 3C), ...".
- Section titled "CerS4 regulates HFSC differentiation in a stem cell autonomous manner": "CD34- integrin- a6+ cells, which based on extensive transcriptome and marker expression analyses represent a mixture of HFSCs, hair follicle outer root sheath (ORS) cells and inner bulge cells (collectively termed non-HFSCs)." - shouldn't the CD34- integrin- a6+ population also contain IFE stem/progenitor cells? Are hair follicles micro-dissected out for FACS?
- Figurer 5D - please provide the working concentration of Chir99021. Figure 5F - explain what arrows mean in legends.
- Figure 6A - no significant changes in Th2 and ILC2 were observed at a 95% confidence interval. Increasing mouse number will help to increase statistical power.
- Additional Wnt target genes such as Axin 2 should be looked at.
- The increased BMP signaling and decreased Nfatc1 expression are seemingly contradictory.
- Paragraph starting with "It is interesting to note that ceramide availability was shown to regulate Wnt signaling in Drosophila through strong effects on recycling endocytosis of the receptors (Pepperl et al., 2013)." Is redundant in the manuscript.
Significance
The work uncovers a new regulator of HFSC fate with mechanistic connection to lipid metabolism and development signaling. The same group previously reported epidermal and hair cycling phenotypes of the same mutant mice, but this work now identifies a specific defect in HFSCs and present evidence for cellular, molecular and biochemical changes. Linking stem cell regulation to lipid metabolism is conceptually novel, and should have a broad audience. However, the study does have some limitations, such as lack of definitive evidence that CerS4 function in HFSCs is responsible for all the defects reported here, and that lipid alterations have a causal relationship with altered Wnt signaling.
My expertise is in skin biology, stem cell control, and developmental signaling.
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Referee #1
Evidence, reproducibility and clarity
Deletion of CerS4 in the entire mouse epidermis throughout development via the K14-Cre results in enlarged sebaceous glands and perturbed HFSC molecular phenotype. There is low or no expression of CD34, a known marker of the HFSCs along with apparent reduction of several other HFSC markers and acquisition of a more differentiated cell phenotype in these cells. Interestingly, skin and hair follicles seem to remain normal otherwise up to advanced age, though this contradicts the notion that HFSC were indeed affected at the functional level. The data does not demonstrate 'gradual decline' in the HFSC compartment, as claimed by the authors, but rather seem to indicate that the adult HFSC compartment is not properly established in its molecular signatures. Organoid cultures document defects in HFSC, which included reduced proliferation in the CerS4 KO cells. Lipid composition in plasma membranes was also affected by the CerS4 KO. Associated with this, Wnt signal transduction is also affected according to experiments that enhance the strength of wnt signals via a specific small molecular agonist of the pathway. Finally, the authors discover a resemblance of the mouse KO immune-phenotype, with human atopic dermatitis. The study is likely of interest to a specialized readership in skin biology and dermatology and adds to previous studies on CerS4 in skin that erroneously placed its role in the sebaceous gland. [The authors here demonstrate that deletion of CerS4 in the sebaceous glands via SCD3-Cre led to no phenotype, contradicting the previous assessment that CerS4 is important in sebaceous glands.] The study would need to be corrected in a few of its interpretations regarding stem cells to better match the data, as indicated below.
Major revisions:
Fig1B - the data seems to simply shows that bulge cells express less or no CD34 and not that ' CerS4epi-/- mice showed reduced HFSC numbers'; the primary FACS data should be shown somewhere too. The conclusion that stemness is affected, and HFSCs lose their normal gene expression signature is at more convincing after looking at other HFSC markers down the road in the paper. However, in the absence of functional assays that would demonstrate stem cell function is lacking and seeing that hair follicles are maintained and grow in long-term, the notion that stem cells are lacking in these conditions is not supported by the data.
The conclusion after figure 2: "Collectively, these data indicate that CerS4-deficiency triggers ... ... gradual depletion of the quiescent HFSC compartment." There is no data showing gradual depletion of the quiescent HFSC compartment. We would need to see a gradual activation of HFSCs with over proliferation to conclude this. There is some data albeit not always convincing (see NFAC1 staining in Fig. 5C) indicating loss of markers associated with quiescence but there is no data indicating 'gradual' loss of markers.
Minor revisions:
Figure 1C legend - please spell out what are the abbreviations for the different subpopulations; please show these populations as % as opposed to absolute numbers.
Figure 1D - please make it clear in the cartoon what the different sub-populations listed are;
Is OB1 a CD34- HFSC population?
Fig. 3B - the colors of the legend do not match the colors in the data so it is confusing as to which one is which!
Fig 5C - the differences in NFATc1 are not visible in the images shown
Significance
Deletion of CerS4 in the entire mouse epidermis throughout development via the K14-Cre results in enlarged sebaceous glands and perturbed HFSC molecular phenotype. There is low or no expression of CD34, a known marker of the HFSCs along with apparent reduction of several other HFSC markers and acquisition of a more differentiated cell phenotype in these cells. Interestingly, skin and hair follicles seem to remain normal otherwise up to advanced age, though this contradicts the notion that HFSC were indeed affected at the functional level. The data does not demonstrate 'gradual decline' in the HFSC compartment, as claimed by the authors, but rather seem to indicate that the adult HFSC compartment is not properly established in its molecular signatures. Organoid cultures document defects in HFSC, which included reduced proliferation in the CerS4 KO cells. Lipid composition in plasma membranes was also affected by the CerS4 KO. Associated with this, Wnt signal transduction is also affected according to experiments that enhance the strength of wnt signals via a specific small molecular agonist of the pathway. Finally, the authors discover a resemblance of the mouse KO immune-phenotype, with human atopic dermatitis. The study is likely of interest to a specialized readership in skin biology and dermatology and adds to previous studies on CerS4 in skin that erroneously placed its role in the sebaceous gland. [The authors here demonstrate that deletion of CerS4 in the sebaceous glands via SCD3-Cre led to no phenotype, contradicting the previous assessment that CerS4 is important in sebaceous glands.]
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Reply to the reviewers
Manuscript number: RC-2023-02132R
Corresponding author(s): Halyna, Shcherbata
Point-by-point description of the revisions
We would like to sincerely thank the reviewers for the positive evaluation of our work, careful reading of our manuscript, and helpful suggestions. In the revised version of our manuscript, we have introduced the proposed changes and added the new data based on the suggested experiments to address the reviewers’ concerns. We hope that this modified version of the manuscript is now acceptable for publication.
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Reviewer #1 (Evidence, reproducibility and clarity (Required)):
Summary Elucidating the cellular and molecular mechanisms underlying age-related neurodegeneration remains a key challenge for neurobiologists. In this manuscript, Mariana Tsap and colleagues in the team of Halyna Shcherbata focus on the function of the neuropathy target esterase NTE/Swiss Cheese (Sws) in the Drosophila brain. The authors use an elegant combination of genetics, light and electron microscopy, RT-qPCR and GS-MS mass spectrometry to determine the complex role of Sws in cellular blood brain barrier (BBB) integrity, the brain inflammatory response and fatty acid metabolism. The study provides a detailed characterisation as to how the loss of sws affects glial cell morphology in the BBB revealing abnormal membrane accumulations and tight junctions, and in consequence causing permeability issues. Importantly, they observed the upregulation of antimicrobial peptides in the brain, indicative of neuroinflammation, as well as of fatty acids, equally connected with the inflammatory response.
Major comments
The study provides a detailed and comprehensive characterization of the sws mutant phenotype, and in particular the role of this gene in blood-brain barrier forming glia.
The study connects neurodegeneration and inflammation, but also makes a particular point about "inflammaging". However, the age contribution has not been studied in detail. Indeed, the flies analyzed are 15 days old (according to the Material and Methods section, with the exception of Figure 1 where flies are 30 days old), and hence have not been compared with younger or older flies to make a point of age as evoked in the abstract, introduction or discussion. The authors should either add experiments comparing differently aged flies or de-emphasize this point to a brief consideration in the discussion. Instead, it would be very helpful to provide concise information about the current knowledge concerning the inflammatory response in the Drosophila brain. We thank the reviewer for raising this point. The decision to use 15-day-old flies was made due to the high mortality of swsmutants after two weeks and because age-dependent character of sws neurodegeneration has been previously well described. As the reviewer suggested, now we also included old animals in our experiments to show a connection between age-dependent neurodegeneration and inflammation. We measured and compared the mRNA levels of expression of the antimicrobial peptides (AMPs) Attacin A, Cecropin A, and Diptericin in the heads of 15- and 30-day-old sws loss-of-function mutants, in the heads of flies that had sws downregulation only in SPG cells (moody>swsRNAi) and in the heads of flies expressing NTE/SWS in SPG cells in sws mutant background. We found that the expression levels of the antimicrobial peptides are increased in the age-dependent manner in the tested mutants. In addition, we found that the expression of NTE/SWS in SPG in sws mutant background reduces inflammatory response in aging animals (see Figure 5D). Also, as the reviewer suggested, we provide brief information on the current understanding of the inflammatory response in the Drosophila brain in the Introduction and Results sections.
Related to this point, the authors convincingly show that sws is required in surface glia using rescue experiments. Nevertheless, all experiments rely on drivers and mutants that could cause the emergence of phenotypes during development. Thus, to strengthen the causative link between the breakdown of the BBB and the neuroinflammatory response, it would be helpful to consider an acute knock-down in adults after BBB formation has been completed. To strengthen the causative link between the breakdown of the BBB and the neuroinflammatory response during adulthood, we performed qPCR analysis and measured the mRNA levels of the antimicrobial peptides Attacin A, Cecropin A, and Diptericin in the heads of flies with sws downregulation in glia cells induced after the blood-brain barrier was formed using the Gal80ts tool. We found that sws downregulation in glial cells during adulthood, after the BBB is formed, leads to the increased inflammatory response (new Supplementary Figure 4E).
To test the brain permeability barrier, the study uses a 10 KDa dextran permeability assay. Almost 25% of brain in controls show a leaky barrier. It would be helpful to describe the causes for this relatively high occurrence. The observed relatively high occurrence of a leaky barrier phenotype in our control group may be attributed to our experimental procedure. We injected flies peritoneally and waited for over 12 hours before dissecting their brains for the permeability assay. Typically, such analyses are conducted after shorter periods, often around 2 hours. Additionally, we used Dextran with the smallest molecular weight (10kDa). The blood-brain barrier (BBB) is not 100% impermeable, and small molecules can gradually enter the brain over time. Recent studies have shown that this entry could be facilitated by endocytosis (Artiushin et al, 2018), which could partially explain the presence of Dextran 10kDa in control brains. Considering this, using a larger Dextran (70kDa) in our experiments could have been more accurate. Importantly, we always compared mutants and controls that underwent identical treatment, dissection, and analysis. We conducted experiments in multiple biological replicates to accurately assess the significance of the differences between mutants and controls. Therefore, we are confident that the differences we observed between controls and mutant flies in the BBB permeability are significant. We included all relevant numbers and statistics for these experiments in Supplementary Table 4.
An important point in the study concerns the increase of free fatty acids as cause of the inflammatory response. The measurements were based on measurements of whole heads, which could include the hemolymph and fat body within the head in addition to brain. However, the causative relationship remains unclear and the question why a leaky blood brain barrier would increase the free fatty acid levels in the body or brain remains mainly an observation at the descriptive level. Here, it would be helpful to design an experiment, which could test the causative links or to modify the interpretation in scheme 6D and adjust the wording in the text. We agree that the causative relationship between a leaky blood-brain barrier and increased free fatty acid levels in the body or brain is currently an observation at the descriptive level and that it would be important to investigate the correlation between a leaky blood-brain barrier, inflammation, and increased free fatty acid levels in greater detail in future studies. In the modified manuscript, we have changed the scheme in Figure 5G and adjusted the wording in the text.
Related to this, how do the levels of AMP caused by a leaky BBB would compare to an elicited neuroinflammation by the presence of bacteria? The neuroinflammatory response can be accompanied by macrophage entry into the brain following AMP induction. Could the authors detect this response (which could be envisioned as manipulations include pupal development, provided macrophages would persist into adulthood)? This would make a strong point regardless of the outcome. We thank the reviewer for suggesting this excellent experiment. To detect macrophage entry into the mutant brains, we used antibodies (NimC1) and srp(Hemo)>mCherry that label the macrophage cells. We found macrophages in the larval and adult sws mutant brains and also in adult brains upon downregulation of sws in SPG cells (Figure 5E-F and Supplementary Figure 4F-IG. These data additionally support our hypothesis that a leaky BBB in sws mutants induces neuroinflammation, which is accompanied by macrophage entry into the brain following AMP expression.
Expression of sws is determined using sws-Gal4 driving membrane-tethered GFP. As sws is expressed very widely and classical Gal4 lines tend to be active in the BBB, it is important to provide the exact information about the nature of this driver. We appreciate the reviewer for bringing this to our attention. We have now included information about the line we used to express transgenes in a sws-dependent manner. Specifically, we utilized the y*w*P{GawB}swsNP4072/FM7c line (Kyoto Stock Center 104592), which was generated using the Gal4 enhancer trap element P{GawB} insertion strategy.
The Material and Methods section should contain a proper Quantification and Statistical analysis section. In the Figures, it would be helpful to refer to the Table reporting sample numbers. As the reviewer suggested, we have now included a Quantification and Statistical analysis section in the Materials and Methods. Additionally, we ensured that all figure legends include a reference to the corresponding tables reporting sample numbers and statistics.
In Figure 5, it would be important to indicate sample numbers, the nature of the error bar, and show data points together with columns. We agree with the reviewer that it is important to report all sample numbers and statistics. We generated a new Supplementary Table 1 for all qRT-PCT data, and Supplementary Tables 5 containing all "n" values and corresponding p-values. In the Figure Legends, we denoted the type of error bars and deviations, included p-values, and referred to the relevant tables for comprehensive numerical data.
Minor comments
On page 8, cell death is visualized using "the apoptotic marker Cas3". It should be Caspase-3. Moreover, it is not clear whether this antibody (directed against vertebrate Caspase-3) recognizes indeed Caspase-3 in Drosophila? This should be formulated more carefully. As the reviewer correctly noted, the Caspase-3 antibody is designed for human Caspase-3. While it has been employed in Drosophila apoptosis research, its specificity for Caspase-3 in Drosophila is unclear. Given the very well-documented apoptosis in sws mutants (Kretzschmar et al, 1997; Muhlig-Versen et al, 2005) and the non-focus on neuronal cell death in this research, we have opted to exclude this information from the supplementary figure. We appreciate the reviewer for bringing this to our attention and for the valuable suggestion.
On Page 9 (3rd paragraph), the authors report that they "want to understand what signaling pathway is activated." However, the described experiments do not lead to a signaling pathway, but conclude that an antiflammatory response is evoked. This should thus be reworded. Thank you for pointing this out. In the revised version, we state that we wanted to understand whether the compromised brain barrier in sws mutants triggers the activation of any cellular stress pathways, including apoptosis, ferroptosis, oxidative stress, ER stress, and inflammation.
Figure 1 reports the expression pattern and phenotype of sws; thus, the title of the figure should be extended. Thank you for the suggestion. We have updated the title of Figure 1 to more accurately reflect its content. The revised title is now: NTE/SWS is expressed in Drosophila brain and its loss leads to severe neurodegeneration.
Concerning the description of phenotypes, the authors use the term "clumps", but it is not clear what this entails (e.g., Page 6, or Figure 6). For the reader, it is also necessary to refer to original studies of moody to understand the septate junction phenotype represented in the figure. As the reviewer suggested, we changed the word “clumps” to “clusters”. We also agree with the reviewer’s recommendation to cite the original work on Moody to acknowledge previous research and enhance the understanding of moody phenotypes. We have now included the relevant citations in the manuscript.
**Referees cross-commenting**
I fully agree with the comments of the other two reviewers, as they were complementary and overlapping with mine (e.g. the contribution of age).
Reviewer #1 (Significance (Required)):
This study provides a detailed cellular and functional characterization of the swiss cheese phenotype in the blood-brain barrier so far not reported in previous studies, including the team's own earlier publications (e.g., Kretzschmar et al., 1997; Melentev et al., 2021 and Ryabova et al., 2021). Furthermore, it uses cutting-edge technology to provide links to neuroinflammation and neurodegeneration, Previous studies explored neuroinflammation in the brain of Drosophila by challenging the organism with bacteria to mount an inflammatory response (Winkler et al., 2021). Intriguingly, this current study provides evidence, that a leaky blood brain barrier alone could lead to an inflammatory response, and that in turn, treatment with anti-inflammatory agents could reduce the cellular defects in glia and in consequence neurodegeneration. This represents an important conceptual advance that will be of wide interest to neurobiologists interested in glial biology, neuroinflammation and neurodegeneration in Drosophila and in vertebrates. One possible limitation of the study may be that while complex cellular processes have been pinpointed, some of the causative links of the BBB with neuroinflammation remain unexplored, in particular the aspect of elevated free fatty acids/antimicrobial peptides.
We appreciate the reviewer's recognition of the conceptual significance of our study, revealing that a leaky blood-brain barrier alone can induce an inflammatory response, with subsequent treatment using anti-inflammatory agents and the importance of these findings for neurobiologists. We also thank the reviewer for thorough examination and insightful suggestions. Given that prior studies have demonstrated the induction of neurodegeneration by the overactivation of innate immune-response pathways, especially elevated expression of antimicrobial peptides (Cao et al, 2013), our new experimental data showing increased levels of antimicrobial peptides in aging flies with a defective BBB further strengthen the connection between the BBB, AMPs and neuroinflammation. This link is even more enhanced by the rescue experiments and the detection of macrophage entry in the mutant brains. We trust that the implemented revisions, accompanied by supplementary experimental data, enhance the suitability of our manuscript for publication.
Reviewer #2 (Evidence, reproducibility and clarity (Required)):
The manuscript by Tsap et al describes a role of NTE/SWS in forming the BBB in Drosophila. Disruption of the BBB in SWS mutants and knockdown flies results in morphological changes of the glia forming the BBB, increased brain permeability, altered lysosomes, and an upregulation of innate immune genes. The experiments to show a function of SWS in surface glia and the resulting changes in permeability are well supported by the experiments and the statistics appears appropriate.
The authors also show changes in innate immune genes and some fatty acids and that similar changes are found in another mutant affecting the BBB. They discuss that these changes are a consequence of the disruptions of the BBB but also that these changes induce changes in the BBB. To address this and confirm that the changes in immune genes and fatty acids is a consequence of the altered BBB, they should include experiment expressing SWS in the surface glia and measure if that normalizes these changes. Another major aspect that should be addressed is the effect of aging. As the authors point out, loss of SWS causes age-dependent phenotypes (shown by the author and others) and with the exception of figure 3F, the age isn't even mentioned in any of the other figures. Furthermore, at least some of the experiments should be done at different ages to determine whether the phenotype is progressive; this includes the permeability assays and the measurements of immune genes (the latter could also support whether changes in the immune genes affect the BBB or vice versa the BBB changes cause the upregulation of immune genes).
As the reviewer suggested, in order to establish a connection between age-dependent correlation between neurodegeneration and inflammation, we analyzed the mRNA expression levels of antimicrobial peptides in the heads of both 15- and 30-day-old sws loss-of-function mutants, as well as in flies with sws downregulation specifically in SPG cells (moody>swsRNAi). We found that the expression levels of the antimicrobial peptides are increased in the age-dependent manner in the tested mutants (Figure 5D, red and orange bars). Following the reviewer’s recommendation, we also performed an experiment where we expressed NTE/SWS in the surface glia in a sws mutant background (sws1; moody>sws, rescue). We measured mRNA levels of Attacin A, Cecropin A, and Diptericin in the heads of 15- and 30-day-old flies (Figure 5D, blue bars). The results showed that the levels of all three AMPs were not significantly different or slightly upregulated in the heads of “rescue” animals compared to Oregon R controls (Figure 5D, compare green and blue bars, and see Supplementary Table 1). Importantly, the levels of all AMPs were significantly lower in the heads of 30-day-old rescue animals than in the heads of the same age sws1mutants (Figure 5D, compare red and blue bars, green stars, see also Supplementary Table 1). These findings further support our hypothesis that sws deficit in the surface glia induces an immune response in age-dependent manner.
We did not conduct the Dextran permeability assay in older flies because approximately 90% of the 15-day-old flies with swsderegulation already exhibited impaired permeability of the BBB. This suggests that the phenotype is quite severe and may not show significant age-dependent progression. Moreover, older mutant flies were extremely weal, and it is likely that they would not have survived the peritoneal injection procedure.
Lastly, the authors claim that septate junctions are defective in sws mutants. However, this should be confirmed by EM studies (which the authors have already done) besides immunohistochemistry which doesn't provide enough resolution.
As the reviewer suggested, for a more detailed detection of septate junctions, we conducted additional electron microscopy experiments. The images included in Figure 6D-F show irregular aggregates and disruptions in the structures of septate junctions and membranes in sws mutants compared to controls. Additionally, we display the appearance of tight junctions in moody mutants (Supplementary Figure 5E-F), which look dramatically different compared to sws junctions and, as previously described, appear overgrown.
Reviewer #2 (Significance (Required)):
A role of SWS in maintaining the BBB and what consequences this has provides another insight how this protein (and its homolog NTE) affects brain health. Although a function of SWS in glia (as well as in neurons) has previously been described, changes in the surface glia and the BBB is a novel aspect. However, the causative role of SWS on some of the described consequences (see above) should be confirmed. Although the manuscript can add to a better understanding of the connection between disruptions of the BBB and neurodegenerative diseases, which is of interest for a broader field of researchers, the discussion of the results is quite speculative.
We appreciate the recognition of the novelty of this work and its potential contribution of our manuscript to a better understanding of the connection between disruptions of the BBB and neurodegenerative diseases. We thank the reviewer for the constructive feedback and hope that introduced changes, along with additional experimental data that address the concerns raised, strengthen the proposed role of sws in the formation of tight junctions in the BBB and its age-dependent maintenance.
Reviewer #3 (Evidence, reproducibility and clarity (Required)):
Summary: The study of the formation and maintenance of the blood-brain barrier (BBB) is a growing field of study, partly due to its strong link with neurological disorders. The BBB depends on the role of multiple cell types and mechanisms. Mutations in the conserved phospholipase NTE/SWS can lead to neurodegeneration, and previous work from the authors shows that SWS loss leads to abnormal glial morphology. In this work, authors use Drosophila to further study this phenotype, showing that SWS is mostly expressed in the BBB-related glia and that its loss leads to abnormal BBB permeability, increased inflammatory response and neural cell death. Interestingly, authors observed a dependence for the BBB-defective phenotype on aging, with important implications for SWS/NTE and neurodegeneration. Overall, the work represents a clear advance in the poorly explored role of NTE/SWS in neurodegeneration, with a broad impact on the understanding of BBB maintenance. This work shows a combination of multiple and appropriate experimental approaches, including confocal microscopy, EM, RT-qPCR, or gas chromatography-mass spectrometry among others.
Major comments:
The use of sws1 and sws1/sws4 transheterozygous animals, together with the use of sws RNAi is a solid approach to validate that the reported phenotypes are due to SWS loss. Using these models, the authors performed a convincing structural analysis of the subperineurial glia phenotype, and showed that it is accompanied by a defective BBB, inflammation and neuronal cell death. The key conclusions are properly supported by the data. However, there are some claims in the text that are not supported by any data in the Figures, but only qualifications. This needs to be fixed:
-Page 6, third paragraph:
"...we specifically downregulated sws in the nervous system using the double driver line that allows downregulation of sws in glia and neurons (repo, nSyb-Gal4, Suppl. Fig. 2C-Cʹ). Since these animals had the same disorganized structure of brain surface as the loss-of-function mutant..." Supp. Fig. 2C-C' only shows expression of CD8:GFP and nlacZ reporters by repo and nSyb-Gal4, but there is no data showing sws RNAi expression by these drivers.
We thank the reviewer for noticing these referencing mistakes. We have corrected the references to the expression patterns of the glial and/or neuronal Gal4 drivers (Supplementary Figure 1D, E and F). Bar graph in Supplementary Figure 1C shows RT-qPCR analysis of sws mRNA levels from flies with glial and/or neuronal sws downregulation (repo>swsRNAi, nSyb>swsRNAiand repo, nSyb>swsRNAi), and the images of mutant brains in Supplementary Figure 2 and Figure 2A-C show the surface glia phenotypes in these mutants.
"...Moreover, downregulation of sws in all glial cells (repo>swsRNAi) resulted in the same phenotype. At the same time, upon sws downregulation in neurons,... (Suppl. Fig. 4)..." Suppl. Fig. 4 only shows nsyb>swsRNAi data but not repo>swsRNAi
We show now both repo>swsRNAi and nSyb>swsRNAi (Supplementary Figure 2C and 2E, respectively).
-Page 6, fourth paragraph:
"Importantly, expression of Drosophila or human NTE in these glia cells rescued this phenotype (Fig. 2H)"
In addition to the indicated quantifications, it is essential to show some representative data showing the phenotype when Drosophila or human NTE are expressed in glial cells of sws mutant animals. We agree with the reviewer that it is important to show the rescue phenotypes. We have included images of the brain surface of sws mutants that have Drosophila or human NTE expressed in glial cells (Figure 2D and Supplementary Figure 2F).
-Page 9, last paragraph: "We found that in moody mutants, the surface glia phenotype analyzed using CoraC as a marker could also be suppressed by NSAID and rapamycin (Fig. 5A)." In addition to the indicated quantifications, it is essential to show some representative data showing the phenotype with and without treatments.
We appreciate the reviewer's suggestion, and as recommended, we have included representative data showing the phenotype with and without treatments in Supplementary Figure 4C-D.
A more detailed analysis of two aspects of the data would clearly improve the manuscript, whose findings are a bit superficial in the current state:
- The exact mechanism by which BBB permeability leads to brain inflammation remains unknown. Authors show that accumulation of polyunsaturated fatty acids (known to regulate inflammation) occurs in sws-depleted animals. However, they only observed a correlation between this phenotype and the inflammatory response, while is not clear whether the accumulation of polyunsaturated fatty acids causes inflammation in this model or is a consequence of it. An attempt to rescue the accumulation of polyunsaturated fatty acids (i.e., knocking down a required enzyme for their production) in sws mutants might help to understand this. Also, the fact that the defective BBB phenotype observed in either sws KO and glia-specific KD can only be partially rescued by the use of inflammation inhibitors, suggests that other pathways are involved.
We agree with reviewer that since the use of inflammation inhibitors only partially rescue the defective BBB phenotype in swsmutants, it implies the involvement of additional pathways. While our data reveal a correlation between the accumulation of polyunsaturated fatty acids and the inflammatory response, whether this accumulation causes inflammation in our system remains to be studied. We have revised the text to ensure that this explanation is clearly stated without overemphasis.
- While the differences between the phenotypes caused by sws or moody loss are well characterized, it would be key for this work to further study the mechanisms by which sws controls septate junctions. The authors propose the organization of lipid rafts, but some experiments in that direction to check this hypothesis. For example, can authors reproduce the septate junction phenotype of sws mutant (Fig. 6C) by using a different approach to induce defective lysosomes in subperineurial glia?
We appreciate the reviewer's suggestion for such an insightful experiment. To investigate whether the septate junction phenotype observed in sws mutants can be replicated in mutants with defective lysosomes in subperineurial glia, we downregulated several key lysosomal genes in SPG cells: moody>DysbRNAi, moody>Npc1aRNAi, moody>PldnRNAi, andmoody>spinRNAi (Supplementary Figure 6A-E). We were happy to see that downregulation of any of these genes resulted in abnormal formation of SJs and membrane organization in SPG cells. These additional experiments strongly support our hypothesis that lysosomal control of membrane homeostasis significantly impacts the appearance of SJs. Thank you for this excellent idea.
The attempt of the proposed approaches above should require about 3-6 months of investment, with limited economic effort, given the availability and diversity of lines found in the existing stock centres such as Bloomington or Vienna.
The data is presented very clearly, and the methods are adequately detailed, and the experiments and statistical analysis are adequate.
Minor comments:
Prior studies are referenced appropriately, but there is a case that should be addressed. On Page 3, first paragraph, regarding the sentence: "However, the molecular mechanisms underlying inflammaging remain unclear". I recommend specifying what is known and what is unknown in the field. Ideally describing (briefly) the knowledge about lipids, inflammaging and neurodegeneration, which are the specific topics of the research. Otherwise, the current sentence is too vague, while there is a lot of work published about it.
As the reviewer suggested we have extended the first part of our introduction to briefly describe how inflammaging is connected with the BBB, fatty acid metabolism and lysosomal functions.
The text and figures are clear and accurate. The logic of the experiments and the results are exposed very clearly (for example, the Suppl. Tables are very helpful). There are a few minor issues, however, that should be addressed:
- Page 4, first paragraph: regarding the sentence: "For various obvious reasons, humans are not ideal subjects for age-related research.", I recommend specifying the main reasons (i.e. life cycle, ethical issues, etc.?).
Thank you, the main reasons are specified now.
- I would recommend moving the text "For various obvious reasons...disrupted upon ageing." From its current position to just before "Drosophila melanogaster is an excellent...". This would keep a better logic in the text by explaining NTE first and later introducing the models to study its function. Presenting then Drosophila.
Thank you, done.
- To support the sentence "Together, Drosophila satisfies...neurodegeneration during aging", instead of citing so many papers, I recommend citing just one current review about it, since the amount of literature supporting the claim is huge and should not be limited to a few "random" articles. An alternative might be indicating that the lab has used Drosophila for this aim before, and then citing the examples from the literature.
Thank you for this suggestion, now we referenced few recent reviews and referred to our previous work on the topic.
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Page 4, second paragraph: if NTE/SWS is going to be used as a synonym for NTE/SWS loss of function (or other type) model, it needs to be specified. Otherwise, refers to the proteins and sentences like "NTE/SWS has been shown to result in lipid droplet accumulation..." are misleading. Thank you for the suggestion; we have now specified that NTE/SWS is used as a synonym for the SWS protein in Drosophila and corrected this throughout the manuscript.
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Page 4, last paragraph: the first time that "BBB" is used, its meaning should be specified. And three lines below use "BBB" instead of blood-brain barrier.
Thank you, corrected.
**Referees cross-commenting**
I agree with the comments provided by the other reviewers. They are well reasoned and cover some aspects of the work that I did not see. Regarding the main issue, the three revisions point at the same direction, that is the limited analysis about the mechanism underlying the phenotypes.
Reviewer #3 (Significance (Required)):
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Describe the nature and significance of the advance (e.g. conceptual, technical, clinical) for the field. This work represents a substantial advance in the understanding of NTE/SWS function in the context of neurodegeneration, and opens potential approaches to treat related disorders (they successfully use anti-inflammatory compounds to ameliorate some of the key phenotypes). However, the findings are a bit superficial in terms of mechanisms, and further analysis (see major comments) would notably improve the significance of the manuscript. This should be realistic and suitable, given the advantages of the Drosophila model and the availability of tools.
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Place the work in the context of the existing literature.
The role of SWS in regulating lysosomal function is potentially supported by NTE-deficient mice data (Akassoglou et al., 2004; Read et al., 2009), where different types of neurons show similar dense bodies containing concentrically laminated and multilayered membranes than those observed in this work in Drosophila sws mutant. Potentially, the rest of the work has a translation to mammals, which is supported by the fact that ectopic expression of NTE rescues some of the key phenotypes described in the manuscript.
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State what audience might be interested in and influenced by the reported findings. Neuroscience in general, since the study of BBB and neurodegeneration has a clear general interest in the whole field.
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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. Drosophila; Neurodegeneration; Hereditary Spastic Paraplegia; Alzheimer's disease; Motor neurons; Microglia; Endoplasmic reticulum; Mitochondria.
Lipid metabolism is the part of the manuscript where I have less expertise to evaluate, only having general knowledge about it.
We appreciate the positive evaluation of our work, the careful reading, and the valuable suggestions provided by the reviewer, including recommendations for additional experiments and changes in the text. We believe that the implemented changes, combined with the new experimental data, have improved the manuscript, making it ready for publication.
References
Artiushin G, Zhang SL, Tricoire H, Sehgal A (2018) Endocytosis at the Drosophila blood-brain barrier as a function for sleep. Elife 7
Cao Y, Chtarbanova S, Petersen AJ, Ganetzky B (2013) Dnr1 mutations cause neurodegeneration in Drosophila by activating the innate immune response in the brain. Proc Natl Acad Sci U S A 110: E1752-1760
Kretzschmar D, Hasan G, Sharma S, Heisenberg M, Benzer S (1997) The swiss cheese mutant causes glial hyperwrapping and brain degeneration in Drosophila. J Neurosci 17: 7425-7432
Muhlig-Versen M, da Cruz AB, Tschape JA, Moser M, Buttner R, Athenstaedt K, Glynn P, Kretzschmar D (2005) Loss of Swiss cheese/neuropathy target esterase activity causes disruption of phosphatidylcholine homeostasis and neuronal and glial death in adult Drosophila. J Neurosci 25: 2865-2873
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Referee #3
Evidence, reproducibility and clarity
Summary:
In this manuscript the authors are interested in understanding how fission yeast respond to a Nitrogen Signaling Factor (NSF) that has previously been shown to allow Leucine auxotrophs to grow in the presence of Leucine when Nitrogen Catabolite Repression (NCR) is triggered by the presence of a high quality Nitrogen source such as Ammonium Chloride (NH4Cl).
The authors begin with a screen to identify genes that affect the ability of wild type cells grown near cells with leucine auxotrophy to enhance or abolish NCR phenotype. They screened the non-essential gene deletion library which they manipulate so that it only contains a leucine auxotrophy (unlike the original gene deletion library which contains additional auxotrophies). They identify 137 genes whose deletion allows growth of Leu auxotrophs in the presence of Leucine and Ammonia without the presence of WT cells. These genes are required for NCR. They further identify 203 genes which do not bypass NCR even in the presence of wild type cells, and are thus important for bypassing NCR in the presence of WT cells.
They then conduct a second screen to identify which of these genes are important for bypassing NCR in response to the Synthetic NSF, 10(R)-hydroxy-8(Z)-octadecenoic acid, by looking for genes which grow in the presence of leucine when ammonia is not present, but do not grow in the presence of leucine when ammonia is present, even when NSF is added. This second screen identifies 117 strains carrying deletions in a gene set enriched for genes related to cellular respiration and mitochondria. They then show that the NSF bypass of NCR is linked to respiration by showing that it is abolished in the presence of the respiration inhibitor Antimycin A, that growth in low levels of glucose can bypass NCR in the absence of NSF< and that cells supplemented with NSF have a higher oxygen consumption rate.
To gain insight into how the cell responds to NSF, the authors then gather RNA expression data from cells grown in high ammonium concentrations following treatment with NSF relative to a negative control treated only with Methanol (the vehicle into which NSF is dissolved). They argue that the gene expression pattern resembles gene expression data from cells undergoing respiration in glycerol relative to cells undergoing fermentation in glucose. They show that the upregulated genes relate to trehalose synthesis, detoxification of Reactive Oxygen Species, and cellular fusion and the downregulated genes are related to cellular adhesion and flocculation.
They validate their RNA-seq measurements by showing that the two most highly induced and two most highly repressed genes respond to NSF addition in a dose dependent manner and do not respond oleic acid which is chemically similar to NSF. The most highly responsive gene they identify is an uncharacterized gene, SPBPB2B2.01, which they suggest naming "NSF-responsive amino acid transporter 1" (nrt1). They also show that the nrt1 response is dependent on the culture density, and that the response is present (though the magnitude varies) in YES and in EMM under varying nitrogen concentrations, and that yfp driven by the nrt1 promoter is induced by NSF.
The authors then investigate the 8 transcription factors that were present in their list of genes required for NSF-mediated adapted growth. They note that Hsr1 was the only one of these transcription factors, indeed the only gene, that was a hit in their screen for NSF-mediated adapted growth and whose expression was induced upon NSF treatment. To see if the activity of the other transcription factors changed in response to NSF treatment, the authors then gathered ChIP-seq data using 6 of these transcription factors as targets for IP. They saw that for Hsr1 and Php3, targets that had increased RNA-seq expression showed an increase in promoter occupancy while for Hsr1, Php3, Adn2, and Atf1, genes that had decreased RNA-seq expression showed a decrease in promoter activity.
Finally the authors attempt to identify the mode of action of NSF by generating a functionalized NSF with an alkyne tag (AlkNSF) which they then use as a probe to identify NSF binding partners. They first show that AlkNSF does allow bypass of NCR, although at 30-fold higher concentration. Also AlkNSF induces nrt1 expression in a dose dependent manner, although the expression saturates at a lower level and requires a much higher concentration for induction. They then look for proteins that co-purify with AlkNSF compared to a control that was pre-incubated with NSF which was expected to compete off AlkNSF. The only significant protein they saw was Ayr1, which was not identified in their screen and which did not abrogate NSF bypass of NCR when deleted independantly. They saw that Ayr1 deletion actually increases the response of nrt1 and mei2 targets to NSF, and speculate that Ayr1 metabolises NSF and reduces the cell's ability to respond to NSF to bypass NCR.
They then repeat the affinity purification / mass spec protocol in an Ayr1 delete cells to identify other interaction partners, this time incubating with a higher concentration of NSF, and also comparing to an experiment using Alkeyne Oleic Acid as a control for non-specific binding. The top two specific hits from this assay are Hmt2 and Gst3. NSF was still able to rescue NCR in gst3 deletes, indicating that it was not relevant for the phenotype. Cells lacking hmt2 did not grow in EMM, but did grow in YES when not supplemented with ammonium and when supplemented with ammonium did not grow, and addition of NSF did not rescue growth. They also see that nrt1 and mei2 gene induction in response to NSF is abolished when hmt2 is deleted. They then argue that hmt2, a sulfide:quinone oxidoreductase localized in the inner membrane of mitochondria is a direct target of NSF that triggers a switch to respiratory metabolism and allows bypass of NCR.
Below are comments that I think ought to be addressed prior to publication (Major comments)
- In line 70, the authors state that "S. pombe cells rely on their own BCAA synthesis to sustain growth" when grown alongside Leucine when ammonium is supplied in the media. If prototrophs can inhibit NCR via NSFs in neighboring auxotrophic cells on the same plate, couldn't they also inhibit NCR within their own colony? How do we know that prototrophic cells grown in high quality nitrogen sources along with, say leucine, are not taking up leucine? The fact that leucine auxotrophs cannot grow in high quality nitrogen sources when leucine is present does not imply that wild type cells must use be synthesizing BCAAs rather than importing them. In a recent paper (Kamrad et al Nat. Microbiol. 2023, https://www.nature.com/articles/s41564-022-01304-8), it was shown that S. cerevisiae cells grown in lysine and in high concentrations of ammonium uptake lysine rather than synthesize it as lysine concentrations in the media are increased. I am aware via unpublished results that this is the case for Leucine as well. I would be surprised if the same isn't true in S. pombe. The authors should caveat or remove this assertion.
- It is important for the authors to put their observation linking respiration to rescue from NCR in context with findings from a closely related study (Chiu et al 2022) which included some authors from this manuscript and which the authors cite. In that paper, it was shown that the siderefore ferrichrome can also rescue NCR in fission yeast. That paper stated "It is likely that ferrichrome increased mitochondrial activity, which enabled efficient utilization of glucose downstream of the glycolytic pathway" based on experiments in different concentrations of glucose. This evidence seems to support the link between respiration and rescue from NCR proposed by the authors of this manuscript. The authors should acknowledge this closely related and earlier work as it strengthen's the case they are trying to make. They could even test if ferrichrome addition makes cells sensitive to antimycin A (as in fig 1E), but that extra experiment would be optional in my opinion.
- In figure 1B for the second screen I do not understand what the photos represent. For the photos, two rows are meant to have no NH4 and also no NSF and the label on that image makes no mention of Leucine supplementation. In the diagram there are two rows that have NH4 and leucine and one row that has no NH4 but does have leucine. I assume the diagram is correct and the labels on the images are incorrect.
- It would be important for the authors to put their observation linking respiration to rescue from NCR in context with findings from Chiu et al 2022 which the authors cite. In that paper, it was shown that the siderefore Ferrichrome can also rescue NCR in fission yeast which the authors site which found that a siderephore rescues NCR. Also the authors of that paper stated "It is likely that ferrichrome increased mitochondrial activity, which enabled efficient utilization of glucose downstream of the glycolytic pathway." based on experiments in different concentrations of glucose. This evidence seems to support the link between respiration and rescue from NCR proposed by the authors of this manuscript.
- In line 133. The authors state that the 29 mutants that didn't grow under Leucine supplementation either without NH4CL or with NH4Cl whether or not NSF was present were "related to EMM Growth, leucine uptake, or utilization of ammonium as the sole nitrogen source." The first two make sense, but I can't see why a a strain with deletion of a gene related to utilization of ammonium as a sole nitrogen source wouldn't grow when supplemented with leucine. In fact for all the leucine auxotrophs in the screen, if one was to try to grow them with ammonium as the sole nitrogen source they would not grow, so it isn't clear that this screen can identify genes responsible for utilization of ammonium as a sole nitrogen source. The authors should clarify or remove this point.
- 203 strains are important for avoidance of NCR (because in the presence of Ammonium and Leucine, as well as a WT strain, they cannot grow). Of these 57 strains can't grow in the presence of a WT strain but they can grow in the presence of NSF. The authors conclude in line 138 that these strains are "likely to respond to a transmissible signal that is different from NSF". This is confusing because deletion of these genes still does allow cells to respond to NSF, however when these cells are growing in the presence of wild type cells (which in their model are releasing NSF), the cells don't grow. I am confused about the nature of the transmissible signal that the authors suggest. It would appear that when these genes are deleted and grown next to a wild type cell which sends the alternative signal and the NSF, the other transmissible signal would inhibits the ability of NSF to release NCR (as NSF can still rescue the gene). It is not clear how the other transmissible signal would work when the gene is present as it is clearly not necessary to rescue growth.
A simpler explanation might be that there was contamination in the second screen, or that there was a threshold effect - perhaps in the first screen the strains grew just below a threshold and in the second screen it grew just above that level.
The authors should clarify their interpretation for these strains, and acknowledge any alternative technical explanations.<br /> 7. The authors' efforts to removed confounding effects that might stem from additional auxotrophic alleles made the screen more convincing. However, Fig 1E, 1F, 5B, and 5E were done with EMM+Leu+Ade+Ura, while the initial strain was just done in the presence of additional Leucine. It is unclear why this was done from the text and captions, but I assume it was because they used a strain that was ade- and ura- in addition to being leu-. Given that they had strains without these additional mutations, this seems like a strange choice. The authors should acknowledge that there are possible confounding effects of adding adenine and uracil to the media, and, if they did have additional metabolic deletions, acknowledge that that could possibly be confounding.<br /> 8. Fig 1E, it appears that cells can grow without NSF in the presence of ammonium and additional amino acids after 10 days (although NSF is required for growth at 5 days). This is not a problem for the screen as that was taken at 5-6 days, but it appears as though NSF does not rescue growth so much as speed it up. The authors should acknowledge this when describing the phenotype. It also argues for a quantitative time course growth experiment to compare growth over the course of 10 days with and without NSF, although this would not be necessary to the paper's main argument.<br /> 9. In line 191 and 192, the authors suggest that the "downregulation of flocculation/adhesion related genes by NSF could serve to avoid undesirable mating during growth". If this is the case, I don't understand why mating genes and cellular fusion genes would be upregulated. What do the authors mean by undesirable mating? Wouldn't flocculation increase desirable mating as well? If all mating is undesirable, wouldn't upregulation of mating and cellular fusion genes be detrimental? 10. The authors mention that trehalose is an antioxidant, for which they reference Malecki 2019, however that paper shows no direct evidence of trehalose functioning as an antioxidant under respiratory conditions. It only shows that some trehalose synthesis genes are upregulated when cells are grown under glucose. The authors should identify primary literature to back this statement up, or soften the wording. Also trehalose is known to be a storage metabolite (which is mentioned in Malicki et al 2019, but not in this manuscript). In fact work in budding yeast has show that trehalose can be a shared metabolite that can be produced by respiring cells and used as a fermentable carbon source in communities of budding yeast cells that consist of fermenting and non-fermenting cells (Varahan et al, eLife 2019 https://doi.org/10.7554/eLife.46735). It seems that this role should be considered as an alternative explanation for the induction of trehalose in respiratory cells.<br /> 11. Line 208: The stimulatory effect of NSF on NRT1 decreased with cell density, thus cell density is likely to be an important factor in terms of gene expression. The methods section, text and figure captions do not mention the density at which cells were inoculated/harvested for RNA-seq and other experiments. If that density was more than OD 0.1, then this would be inconsistent with the measurements from Fig 3. Also in fig 3D, The culture density is not mentioned in the figure or the caption, even though the text suggests that for that experiment cells were grown at low density (Lines 212-213). The authors should provide information on density for their experiments in order for them to be reproducible, as they show it is a key factor. 12. In suggesting a name for NRT1 (NSF-responsive amino acid transporter 1), the authors assume that the gene has a role in amino acid transmembrane transport, but they have no experiments showing this phenotype. They mention that it is Inferred from homology with other amino acid transporters. I presume this name has already been approved by Pombase and is not provisional, but it seems that including phenotypes inferred from homology, rather than from experiments is unwise. Do the authors have any other direct evidence that this is a bona fide Amino Acid Transporter? Perhaps a name like "NSF-responsive gene" would be more appropriate.
Related to this, it appears that the expression level of Nrt1 may be very low (see Fig S2B in which the scale of the RNA-seq track is very small [-1,1] and the amount of expression is very small even when NSF is added). Looking at Fig 2A, the total transcript abundance did not appear to be very low in terms of counts per million (over 100) is this a discrepancy in fig S2B? Perhaps the large fold change is the result of counts very close to zero in the control condition? Also in Fig 3 the nrt1 expression levels did not appear to be especially low and they appeared repeatable. Is the RNA-seq data shown in fig S2B for nrt1 a fluke or am I misinterpreting it? <br /> 13. To show that their Chip-seq worked, the authors showed specific examples of Chip-seq reads for target genes Line 240, "Previously determined target genes of these TFs were significantly enriched in our data set, demonstrating that the experiment has worked (Figure S2A)." Is the significance here, the threshold from fig S2B? If so that threshold should be clearly stated here in the text. If it is the fact that asn1 shows up as "Fil1 bound" is strange as there are no genes that had significant changes in ChIP-seq signals for fig S2B. If there is another threshold the authors should describe it. While some of the examples they showed were convincing (e.g. php3-flag for the php3 regulated gene gln1 and the increased reads for srw1 for the reb1 target srw1), there were some targets that didn't seem to be especially enriched for their designated transcription factor. For example, the gene trx1 which was identified as an Hsr1 binding target had some binding from Hsr1, but more from Php3 and equivalent amounts for many of the other transcription factors. A clear description of how genes are chosen to be significant in the text, alongside references/selection criteria the authors used to select the specific genes shown should be provided to improve reproducability. <br /> 14. In lines 244-246 the authors state that "These differences in TF occupancy were positively correlated with target gene expression changes. That is, individual genes that were upregulated by NSF tended to be more strongly bound by the TFs, whereas downregulated genes were less occupied by the respective TFs (Figure 4A)." This is far from a general trend. The trend is not there for reb1 and fil1. In fact fil1 looks to the eye like it shows a decrease in occupancy for genes with increased expression, and I worry that the authors did a one sided test for significance that would have missed this, although the variability of the genes that don't change in this case is very high, so there could be no significant effect. The authors elaborate on some of the detail in following statements, but they should soften or remove this statement.
Related to this, in line 254, the authors state: "These results imply that NSF exposure rewires the recipient cell's transcriptional program, for which the TFs Atf1, Adn2, Adn3, Fil1, Hsr1, Php3, Php5, and Reb1 are indispensable (Table S3)." While I am convinced from the RNA-seq evidence and some of the chip-seq evidence that NSF exposure rewires cell's transcriptional program, I am not convinced that the 8 transcription factors they mention are indespensable for rewiring the transcriptional program. While they may be indespensible for the phenotype itself, Reb1, and Fil1 show no no siginificant enrichment in occupancy of upregulated or downregulated targets (Fig 4A) and, along with Atf1, Reb1, and Fil1, have very few genes in which ocupancy is changed significantly (Fig S2B), while no chip-seq experiments were shown for Php5 and Adn3.
The more specific summary of the data (Lines 250-253) from Fig S2B describing how hsr1 and adn2 have the strongest effects of the transcription factors required for NSF-mediated NCR bypass is a much stronger message for this section. 15. In line 335, the authors state that "in contrast to other communication systems, NSF does not induce noticeable changes in S. pombe's morphology", referring to changins in mating, filamentation, and bacterial biofilm formation. However they do show very clearly that NSF does cause a large decrease in expression in flocculation/adhesion genes. The fact that they do not see a change in morphology is likely due to the fact that the lab strain in the conditions used for this assay do not flocculate. We have recently identified conditions and strains which do exhibit flocculation in this preprint [https://www.biorxiv.org/content/10.1101/2023.12.15.571870v2]. It is likely that if they had a strain and conditions that did flocculate addition of NSF would break up flocculation and thus change the morphology based on their evidence. The authors should remove or caveat this point.<br /> 16. Line 270 Fig 5B: The concentration of NH4Cl listed in the text (374mM) does not match the concentration shown on the figure (748mM). I assume this is a typo but it should be corrected prior to publication.
Also I have several minor comments to help improve the manuscript.
m1: Lines 66-70- state that "uptake of the branched-chain amino acids (BCAA) isoleucine (Ile), leucine (Leu), and valine (Val) is suppressed in the presence of high-quality nitrogen sources such as ammonium or glutamate, because the expression of transporters or permeases that are needed for the uptake of poorer nitrogen sources are down regulated (Zhang et al, 2018)." This reference is for S. cerevisiae and is a review. The authors should cite original results in S. pombe if possible, and if that is not available, alert the reader that this result is from a different species.
m2: It is unclear from the methods section how the images taken for the screens were analyzed. Were they analayzed and scored by hand, or using custom image analysis software. Either way, when publishing the authors should publish the scores for each deletion mutant in their screen. If there was custom image analysis, the authors should mention in their methods the cutoffs which they used to score growth, and consider plotting the data as a supplement so readers can get a sense of how sensitive the screen was.
m3: The authors identify 137 mutants that did not require NSF signaling to bypass NCR and claimed these genes were required for NCR. It would be helpful and give more confidence in this screen to demonstrate the extent to which the genes identified in this study overlap with any previous genes required for NCR, and whether there was any GO-term enrichment in this set.
m4: It would be interesting if the authors could speculate a bit in their discussion on why mitochondrial respiration counteracts NCR. Is there something about cells undergoing respiration that would make it easier for them to use BCAAs than to produce them, or conversely something about fermenting cells that makes it easier for them to produce BCAAs rather than importing them?
m5: It is unclear why Figure 1F has 'MP biomedicals TM' listed in the figure. It doesn't seem to be listed in the caption or the methods. Is this different media than in other experiments? If so, the authors should add that information to the methods or the caption.
m6: In Line 160, positively influenced is strange wording, do the authors mean "induced"?
m7: In the section on gene expression change upon exposure to NSF, the authors use a + after each gene name. My understanding is that that notation is meant to refer to strains with the wild type genotype of that gene, and not the gene itself. Shouldn't the gene be italicised in lower case to represent the gene? See: Lera-Ramirez et al 2023 https://doi.org/10.1093/genetics/iyad143.
m8: In Fig 2A, genes are displayed on a plot that depicts level vs log2FC, but a comparison between the fold change and p-value would be more useful, and I believe DESeq2 should provide an adjusted p-value for these genes. A related issue is that it appears as though there were no biological replicates, though there was data gathered at different time points. In these genome wide experiments, replicates can give confidence to data and help distinguish true change from intrinsic variability of expression in specific genes. Though the authors did qPCR to validate specific results, it would have improved the quality of their systems-level data to have replicates for these and other key experiments (Chip-seq, affinity purification and even the screen).
m9: Supp Fig S1: To show that similar gene expression profiles exist for other time points, it would be more convincing to show Log fold change 2h vs 4h and 2h vs 6h and show correlation, or else to make a heat map with all genes to see that genes that go up in one condition go up in the other conditions. It is not clear if the red and blue colors are defined for the 2h dataset and then mapped onto the 4 and 6h dataset, or if they are independently assigned for each plot.
m10: Mbx2 is a key transcription factor related to flocculation and adhesion genes, and its expression is correlated with expression of its targets. If this transcription factor's expression levels decreased in response to NSF, that might strengthen and help explain the decrease in expression the authors observe in flocculation/adhesion genes when cells encounter NSF. If it it does not change, it might also be interesting for readers interested in these phenotypes.
m11: In Fig 3D, The notation for the Ammonium concentrations for EMM and YES are inconcistent (+ vs parentheses), also the units (mM from the caption) are not on the figure, but the abbreviation "N" is which is confusing and inconsistent with the other plots in which NH4CL is not abbreviated. Additionally, the caption lists additional nutrients in the media for the EMM conditions (Leu, Ade, Ura) which ought to also be listed.
m12: In lines 233-235, the authors say "One possibility is that they remain bound to their target genes but become activated or deactivated by NSF directly, or posttranslational modification, such as phosphorylation in the case of Atf1". I don't think the authors intend this, but this sentence could be taken to mean that Atf1 has been shown to be phorphorylated by NSF in the reference they site. I think the authors should clarify, i.e. by saying "..such as phophorylation which is known to regulate activity of Aft1 in response to oxidative and osmotic stress [Lawrence et al 2009]".
m13: In Fig 4B and Fig S2A, there are grey and colored tracks for the chip-seq (- and + NSF), but they are very difficult to see. If grey is in front it is hard to tell how close the colored peak wehn the colored peak is lower. For example, grey is in front for pex7 while color is in front for yhb1. Could the authors add some transparancy so that the data for both conditions could be seen at once? Also there is little information on the control. My assumption for the input(ChIP) sample was that it was cross-linked and sonicated but not immunoprecipitated, but it is not clear what conditions it was in. I would assume it was done without NSF treatment in WT cells, but those details should be added in the caption or methods. In particular, in the input there is a large spike for Gsf2. Do the authors have any explanation for this and does it have anything to do with that gene's NSF responsiveness?
m14: The authors might consider putting something like Fig S2B (or even a corresponding volcano plot) as a main figure for Fig 4 in addition to the other two panels, as the individual examples from fig 4B are nice to see, but do not give a broad overview of the data.
m15: In line 348, the wording "Would score" might be better replaced by "would be identified."
Significance
Assessment:
In general I find the authors arguments compelling and their experiments convincing. The initial and follow on screens were well designed and the authors linked respiration and the action of NSF in a convincing way. The analysis of RNA-seq data was also convincing, especially regarding the decreased expression of flocculation and adhesion genes, and the follow up of specific targets gives confidence in the data (though see Major point 12 below regarding the naming and expression levels of nsf1). The identification of hmt2 as a functional target of NSF was compelling and rigorous, and the authors offer an interesting hypothesis to connect this to respiration that could form the basis of future studies.
At times I thought that some of the interpretation of the results was hard to follow, poorly worded, or off the mark (see comments below). The presentation of the CHiP seq data also felt incomplete, though the influence of Hsr1 and Adn2 on expression of NSF1 targets was convincing. The genome wide assays (RNA-seq, CHiP seq, screen and pull-down/mass spec) could have done with replicates which would have improved statistics and reliability of the results presented for those experiments, although for key messages, the authors followed up with convincing targeted experiments.
The study represents an advance on recent work in NCR in fission yeast in linking this with the broad metabolic switch between fermentation and respiration, and in that sense makes this of interest to a broader swathe of the microbiology community, outside those interested in metabolic regulation in microbes. In addition to being of interest to applied researchers interested in producing metabolites with yeast and other microbes, the link to cell signaling and, via flocculation and adhesion genes, to microbial multicellular-like phenotypes would make this work of interest to those interested in microbial communities.
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Referee #2
Evidence, reproducibility and clarity
This paper uses the model system Schizosaccharomyces pombe to investigate how the oxylipin nitrogen signaling factor functions to send signals and adapt the metabolism upon a change in nutrients in the environment. Combining genome-wide screens, RNA-sequencing and chemical biology, the authors find that the nitrogen signaling factor triggers a change from fermentation to a respiratory metabolism, through a direct interaction with a mitochondrial oxidoreductase Hmt2.
Major comments:
Overall, the manuscript lacks readability and coherence. Quite a lot of genes/TFs and proteins are mentioned, it is difficult to find a coherent story and clear overview and connection between these subparts. The manuscript would benefit from a general proposed scheme/working mechanism in the discussion and streamlining the results and data into a single biological storyline.
Several statements or results are not sufficiently clear, elaborated or nuanced. The paper would benefit from more explanation and discussion.
In the discussion section, the authors are not consistently referencing figures.
179-181: 'GO enrichment analysis of the 92 downregulated genes' but on line 167, it is '74 downregulated genes' that are mentioned. It is unclear where this difference in number of downregulated genes comes from. Similarly, for the upregulated genes. '156 genes' are mentioned on line 181 but only '98' on line 167.
189: The statement that the downregulation of flocculation could serve to avoid mating, though sounding logical, is undermined by the finding that mating-related processes are upregulated in the experiment. I find this statement rather speculative
247-249: The statement is too broad, the effects are visible for maybe 3 TFs, the others don't seem to make a difference in occupancy. Also, why are these two highlighted genes of importance (pex7+, yhb1+), this is the first and last time they are mentioned?
254-256: The statement that these TFs are indispensable may be too strong. Right before, the authors showed that most of these TFs don't change occupancy (and especially Fil1 and Reb1 do not show a correlation with up- and down-regulated genes, nor does Fil1 in FigS2B show a changed ChIP-seq signal).
365: 'independently of the carbon source'. As far as we can see, all experiments were performed using glucose as the carbon source, so this statement seems too strong as there is no clear proof for this. This could be an easy extra experiment to perform these tests on media with other carbon sources than glucose?
Fig1E: It is not clear if the experiment was performed with the Wild-Type or a deletion strain. In the case of the WT, colonies grew in the media not containing NSF but in Fig5E and Fig5I, the WT did grow in the media not containing NSF. It could be more relevant to plate out 1 colony like in the second screen. Thus, unless different strains were used for both experiments, the results seem inconsistent with each other, which is not mentioned in the manuscript.
Fig1E, Fig5B, Fig5E, and Fig5I: For these experiments, different nitrogen concentrations were used depending on the media, but this has not been addressed/mentioned in the manuscript.
Minor comments:
53-57: I would like more elaboration on why CCR and NCR are important for virulence of human pathogens or relevant for industrial applications, and link back to this in the discussion. Otherwise, it is superfluous to include this in the introduction.
108: Does having a h- library have any impact on the outcome compared to the original h+ library?
170: Why would only one of the 117 NSF-linked genes change expression in the RNA-sequencing experiment? Any explanation as to why the expression remains unchanged for the 116 other NSF-linked genes?
212: Please elaborate the discussion of these results. I understand the point that at low cell densities, the cells do not produce NSF as much, and thus adding NSF induces nrt1+. However, the added value of testing this in different media is unclear, especially when the results of strength of increase in nrt1+ show the opposite trend for the two different media between low and high nitrogen content.
216: Why was the ADH1+ promoter chosen as a 'negative control'?
284-288: Fig5E: To test whether AYR1 is indeed metabolizing NSF (and thus supporting this statement), an overexpression strain of AYR1 could be made to see if it grows on the EMM + NH4Cl without NSF added.
385: 'NSF would not strictly revoke NCR only, but also CCR': the authors should try to provide experimental evidence, citation(s), or clearly state it to be a hypothesis. This comment links back to the major comment on line 365.
405: typo: strains were validation, should be 'validated'
644: typo: '+' sign not in superscript
Fig1G: Could the differences in OCR be due to differences in growth rate or remaining glucose? It could for instance be that the culture in the control condition grew less fast, thus still having glucose and therefore still in fermentative metabolism. Showing or mentioning growth rates, nutrient concentrations could help to strengthen this finding.
Fig2A: The top two 'most' upregulated genes (nrt1 and mei2) were taken along for additional experiments. However, one gene with a significant upregulation labeled in red on the left seemingly shows stronger induction than the second gene (mei2). Why was this gene not taken along?
Fig2C: the x-axis label is not immediately clear to the reader.
Fig4B: typo: 'non treatmentt'
Significance
This manuscript advances our understanding of nitrogen signaling pathways and nitrogen catabolite repression in the model organism S. pombe. Specifically, it shows how a nitrogen signaling factor functions to send signals and adapt the metabolism upon a change in nutrients and reveals that this nitrogen signaling factor triggers a change from fermentation to a respiratory metabolism. These findings are relevant for the broad fields of applied microbiology, signal transduction and metabolic regulation. Relevant literature is appropriately cited, although the links with Crabtree repression in S. cerevisiae are perhaps not fully supported.
This manuscript was reviewed by experts with expertise in S. cerevisiae, Crabtree effect, respiration-fermentation balance, adaptation to changing environments.
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Referee #1
Evidence, reproducibility and clarity
Summary
We have now reviewed the manuscript by the groups of Dr. Bühler and Dr Yashiroda entitled: "Nitrogen signaling factor triggers a respiration-like gene expression program". We have enjoyed the topic, the experiments and the science behind it all. The authors study here one part of the fission yeast 'quorum sensing'-like mechanism of counteracting NCR, mediated by the small molecule NSF: they identify pathways required to respond to NSF, and more specifically determine the mechanism by which NSF counteracts NCR: triggering respiration. This is a very interesting manuscript, with nicely executed experiments, and the topic is of great interest. Regarding the major comments, they are specific to the current data. The minor comments are questions raised in light of the present set of data, which should be appropriate for future research and future manuscripts.
Major comments
- Consistency with the numbers of mutants/genes should be improved. Line 119: 203 genes, 206 in 4th datasheet of Table S1; line 139: 117 mutants but 119 analyzed for GO analysis (1st datasheet in Table S2); lines 179 and 181: where are these numbers (92 down and 156 up) coming from? (compare with 74 and 98 in line 167) (maybe they come from the merge of 2, 4 and 6 h, but it is not indicated).
- Lists of genes up- and down-regulated from the RNA seq data should be provided. GO terms are not useful. Add supplementary table, please.
- Comparing the transcriptomic response to that of Malecki et al 2020 in response to Antimycin A (EMBO Rep. 21:e50845) would be useful.
- The optical densities and whether NCR has been induced has to be clearly specified in each experiment. For instance, RNA seq data. Line 165: for the transcriptome experiment, NSF is added or not to low density cells (not indicated in results, figure legend nor materials and methods). Should addition of NSF to wild-type strain en MM trigger the same transcriptomic changes?
- Fig. 1G: Addition of NSF can enhance oxygen consumption at any cell density? And in prototrophs? And without NCR? Add in figure legend that this has been done at OD600 of 0.01.
- Fig. 1 E and F: why 14 d after growth there is not growth at 2% glucose in panel F, but it is 10 d after in panel E? What is EMM Biomedical?
- Fig. 2BC: Venn diagrams should be more useful to demonstrate overlap withn the Malecki data.
- Fig. 4A: not very useful
- Is Hsr1 required for some of the RNA seq changes upon NSF addition? Same with other TFs
- Line 287: '...it is tempting to speculate that Ayr1 dampens adaptive responses by metabolizing NSF'. Calculating MEC for NSF in delta ayr1 and in cells over-expressing Ayr1 would be required to confirm this speculation. According to Pombase, cells lacking Ayr1 have their respiratory functions compromised (no growth in galactose, glycerol...), why is so? The opposite should be expected, if NSF-mediated respiration is enhanced in this background.
- Regarding the two pull-down experiments, one to identify Ayr1 and the second Hmt2, why different negative controls are used? Is addition of NSF to WCE prior to pull-down also used in the second experiment (with delta ayr1 and AlkOle)?
- The data regarding Hmt2 is very interesting. As for delta ayr1, delta hmt2 cells cannot grow in glycerol nor galactose according to Pombase. Is the result shown in Fig. 5J (lack of NSF-dependent activation of nrt1 and mei2 in delta hmt2) a consequence of the absence of the NSF receptor, or is it due to the lack of respiration of this background? Is delta hmt2 really auxotrophic for Cys? Why? In this background, H2S should be enhanced, and Cys and Met biosynthesis improved. In fact, in one manuscript these cells grow fine in SG minimal media (Mol Microbiol 01 42:29), while another report indicates they are auxotrophic for Cys (Genes to Cells 2016, 21:530).
- M&M: regarding RNA isolation and sequencing: add info about OD of cultures, genotype (leu1-32?), growth media; also, number of replicates and filtering (fold-change used, Q value...)
- M&M, ChIP seq: same as above. Also, MACS2 can be used for the unbiased identification of bona fide TF targets, by using a quantification tool reporting percentage of occupancy upstream the TSS (callpeak function).
Minor comments
- Who triggers NCR? Analysis of 137 genes in Figure 1b.
- Synthesis of NSF: how is it regulated, where does it come from?
- NCR impairs import of BCAA. How are the aa importers such as Cat1 or Agp3 eliminated from the plasma membrane? Transporter internalization, degradation, transcriptional repression... And how does NSF block the NCR regarding aa uptake? Or aa usage?
- How can enhanced respiration by NSF counteract all of the above? How can now leu1-32 cells grow?
- Addition of NSF to any cell type would do the same, enhance respiratory rates? With or without previous NCR? Should this signaling molecule also drive different respiratory rates in a cell density-independent manner regarding glucose catabolite repression?
Significance
Within this manuscript, the authors study a cell-to-cell communication process, by which nitrogen catabolite repression can be counteracted by a small molecule called NSF. Specifically, the authors demonstrate here that NSF up-regulates respiratory metabolism as a mechanism to overcome the repression of amino acid internalization, which was blocked by excess nitrogen. This is a wonderful manuscript, with splendid data, on a very interesting topic.
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Referee #3
Evidence, reproducibility and clarity
Summary:
In this manuscript the authors study a unique membraneless organelle (MLO) in the developing germline of the wasp (Nasonia vitripennis) and highlights the differences with polar granules, homologous membraneless assemblies formed in the Drosophila germline. They identify that in contrast to Drosophila, the wasp utilises an alternatively spliced isoform of the conserved RNA Helicase, Vasa, where the longer isoform harbours FG-repeats characteristic of nucleoporins. Additionally, they observe striking differences in the assembly of the perinucelar 'nuage' where the nuage components are heavily enriched at the anterior half as a mechanism to effectively silence transposon activity in the anterior nurse cells which are characterised by a high degree of DNA double strand breaks. In the course of oogenesis to embryogenesis, the authors observe that the oosome is dynamic and conserved germ plasm proteins (Osk, Vas, Tud) transition from diffuse distribution (in the oocytes) to a dense Tud shell surrounding there oosome filled with Osk-Vas granules (in the embryo). <br /> While the study provides insights into a novel germline condensate, there are some key questions which need to addressed to support publication.
Major Comments:
- Nasonia expresses two distinct Vasa isoforms differing by 96 amino acids close to the N-terminus. The authors claim that the 96 amino acid insertion is FG-rich and intrinsically disordered providing experimental evidence with Circular Dichroism of the purified 96-amino acid fragment. However the amino acid sequence of the remaining N-terminal region upstream of the folded RecA domain is low complexity with an apparent over-representation of G, R, D, N as well as several FG repeats. Any computational disorder prediction tool (such as, IUPred, D2P2, etc) can be used to predict the sequence disorder of the entire N-terminus. Therefore, it is unclear why the authors claim that the 96 amino acid insertion exclusively confers special advantages and contribute to mesh-like properties to the oosome. Does the Long isoform provide specific advantages? This needs to be addressed. "Computational analysis predicted two alternatively spliced Nv-vas mRNAs, that should result in 92.3 kD and 82 kD proteins ": Please explain the analysis and tools used in methods. Fig. 1d : Please discuss the source and identity of the multiple non-specific bands of the RT-PCR experiment in the figure legends. Fig. 1f : For ease of readers, it is recommended to label the figure panels with stages as well as proteins probed.
- Are there sequence similarities between the novel 57-residue NTD of Nv-Osk and the Drosophila NTD (138 amino acid long) present exclusively in Drosophila Long Oskar?
- Fig. 2c : Consider including corresponding micrographs of the oocyte oosome imaged with AiryScan.
- Fig 2d,e : Is Osk-GFP cytoplasmic or form peri-nuclear condensates? Is Vasa-mCherry nuclear or cytoplasmic or both? Please include DAPI channels and consider drawing outlines of the cell membrane.
- Are these S2 cell images completely representative of the localisation patterns of Osk and Vas in the cells or do the authors only observe other phenotypic classes as well? If yes, please include the different classes observed with relevant statistics.
- The differential assembly of the 'nuage' between anterior and posterior nurse cells is intriguing and well addressed. The higher degree of nuage assembly coincides with higher amount of DSBs in anterior nurse cells. Is this a cause or a consequence? Exposure to mutagens can induce DSBs uniformly in all nurse cells; will this lead to up regulation of nuage assembly uniformly in all nurse cells?
- Dynamic sub-compartmentalization of Tudor to the periphery of the embryonic oosome suggests remodelling of the proteins components post-fertilization.
- Can the authors perform live-imaging to track oosome dynamics from oogenesis to embryogenesis using FP tagged-germ plasm components? This would provide valuable insights into the assembly mechanism of this giant membraneless organelle.
- Fig. 4 a, b: Line profiles required to show redistribution of Tudor. What do the three panels per condition indicate? What makes the authors conclude that the Tudor shell is "fibrillar" in nature? Is there any evidence?
- Maternal mRNAs form homotypic clusters in Drosophila germ granules (Treck et al., 2015). Where do the maternal mRNAs localise in the oosome? In case they are recruited by Oskar (in line with Drosophila germ granules assembly model), are they diffusely distributed in the oocyte oosome and do they redistribute in the Osk-Vas granules that form at the core of the embryonic oosome? RNA in situ hybridization with a few maternal mRNAs can be done to understand how RNAs are distributed within this giant condensate.
- The 'dense-shell liquid core' architecture of the oosome as proposed by the authors lacks any concrete proof. The migration of the nuclei (lines 342-345) can be facilitated by changes in physical properties of the Tudor shell in that particular embryonic stage, promoted in turn by key PTMs, for instance. Moreover, there is no evidence that the core oosome has liquid-like properties. In absence of live imaging and FRAP data, the 'dense-shell liquid core' architecture can not be addressed.
Minor Comments:
Line 40: "small spherical or amorphous cytoplasmic granules"; the terms "spherical" and "amorphous" have very different implications-one is for shape and the other indicates molecular organization. Consider re-phrasing.
Lines 55-57: mention embryonic stages as the Tud re-organization within oosome is a dynamic process.
Line 63: Is this really addressed in the manuscript?
Lines 95-97: What about Long Oskar in Drosophila? There is a 138 amino acid extension 5' of the LOTUS domain.
Line126: "proteome of the oosome". Proteome analysis would require isolation of the oosome followed by mass spectrometric identification of constituent proteins. Here the authors investigate the conserved germ plasm proteins and not the whole proteome. Please re-phrase accordingly.
Lines 308-310: "protein-free channels or cavities"- how do the authors know that they are protein free by probing for only three proteins? Consider re-phrasing.
Significance
The study describes a giant membraneless organelle in the developing wasp germline by developing an important set of tools and reagents necessary to study this novel organelle in greater depths in future. Experiments are well designed and validations of the tools developed are adequately carried out. However, the study is largely descriptive and the suggested experiments need to be performed to provide deeper insights into the significance of the work.
Considering the existing resources on assembly of germ granules by liquid-liquid phase separation, the 'oosome' represents another class of germ granules whose mechanism of assembly, dynamics and physical properties appear to be distinct from Drosophila polar granules as well as P-granules in C. elegans. Therefore, the work is significant in the fields of condensate biology and germline development as further studies focussing on the oosome can elucidate not only the molecular principles underlying oosome assembly but also address the plasticity in assembly of homologous MLOs across evolution.
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Referee #2
Evidence, reproducibility and clarity
Summary
In this study, Kharel et al use endogenous antibodies to characterize the dynamics of germ granule components throughout development in the wasp Nasonia vitripennis. The authors observe several key differences in Nasonia germ granules as compared to the more well-studied germ granules of Drosophila. Kharel et al describe a novel isoform of the conserved granule component Vasa, which in Nasonia contains an FG domain. The authors use super-resolution microscopy to describe a core/shell architecture for the oosome, the single large germ granule that forms in the oocyte cytoplasm. Additionally, the authors find that a subset of Nasonia nurse cells have comparatively higher levels of perinuclear nuage which they hypothesize is related to high levels of DNA double strand breaks. The authors propose that these observed differences in conserved germ granule components may support the unique demands of germ granules in Nasonia.
Major comments
- In many instances the authors make strong statements that are not directly supported by the presented data. For example, in the Abstract (line 62) the authors write "Our results point to the high degree of plasticity in the assembly of membraneless organelles, which adapt to specific developmental needs of different organisms, and suggest that novel molecular features of conserved proteins result in the unique architecture of the oosome in the wasp." Indeed, the authors have described several differences between germ granules in Drosophila versus Nasonia, but they have not presented data indicating that these differences are functionally relevant. They have also not shown that these differences result in the unique architecture of the oosome. The authors may of course speculate about the functional significance of their observations in the Discussion (emphasizing that certain statements are speculative), but should tone down or limit such statements in the Abstract and Results.
A few more examples of over interpreted data:
a. In line 111 of the Results the authors write: "Our data suggest that the Nv-Tud shell provides mechanical stability to contain a less dense oosome core during its migration in the early embryo." The authors have only observed an enrichment of Nv-Tud at the periphery of the oosome, which is not quantified. The authors have not performed experiments to test whether this enrichment is required for oosome integrity, or whether the core of the oosome is less dense.
b. In line 113 of the Results, the authors state: "Nasonia egg chambers have distinct subset of nurse cells in anterior that show evidence of double-strand DNA breaks and assemble higher amounts of perinuclear nuage than their posterior counterparts, indicating a higher demand for anterior nurse cells to silence transposable elements." Indeed, a subset of nurse cells have strikingly higher levels of nuage, and a subset have significantly higher levels of gH2Av staining. However, a link between high levels of nuage and a need to silence transposable elements seems speculative.
c. In line 421, the authors summarize their conclusions: "the assembly of the oosome...relies on the combination of highly conserved components...as well as a suite of novel features, including a novel Nv-Vas isoform, an unusual shell of Nv-Tud protein demarcating the edges of the oosome, and unusual distribution of nuage in the ovary." As the data presented in this study is largely descriptive, the authors have not directly tested whether any of these features are required for oosome assembly. 2. Throughout the study, the authors often show single western blots or representative images. To determine reproducibility, the authors should quantify their data whenever possible or indicate the number of independent experiments used to generate a figure. Sample size should be included in the Legends.
Some examples:
a. In Figure 1a, the authors show that the short Nv-Vas isoform is decreased in the embryo. How many times was this western performed, and is the short isoform always similarly decreased in the embryo?
b. In Figure 1d, the authors use RT-PCR to show that multiple vas RNA isoforms are present in ovaries, but only the long isoform is detected in embryos. How many times was the RT-PCR performed and how reproducible was this result? Also, there appears to be a third major RNA species present in ovaries, do the authors think this is relevant?
c. In Figure 2d, Nv-Osk forms granules when expressed in S2 cells. What fraction of S2 cells expressing Nv-Osk had granules?
d. In Figures 4 and 6, the authors should quantify core versus shell enrichment for Nv-Tud and other germ granule components (see Major comment 3 below). 3. A main finding of this study is that Nv-Tud forms a fibrillar shell by concentrating at the periphery of the oosome. The authors propose that this shell "fulfills the role of a membrane" (line 371) to protect the integrity of the oosome. This model is based on a handful of images, some of which are not entirely convincing. For example, Nv-Tud does not appear to form a shell in the middle image of Figure 4b. In order to strengthen their model, the authors should quantify the enrichment of different germ granule components in the core versus shell of Nasonia oosomes. Optionally, the authors could directly test a role for Tud in oosome integrity by observing the fate of the oosome core components following tud mutation or RNAi.
Minor comments
- It might be helpful to add the protein structure for Drosophila Vasa for comparison in Figure 1c. Similarly, Drosophila Oskar could be added to Figure 2b.
- The authors mis-reference Extended Data Fig 3 as Extended Data Fig 2 (starting in line 198).
- In the Figures throughout, it would be helpful to label each panel with the antibodies used. Relatedly, in both the Figures and text the authors should always clarify whether they used antibodies recognizing the long Nv-Vas isoform or the entire Nv-Vas. Also make sure to include MWs for all blots.
- For Extended Data Fig. 3d, I'm not sure that migration of an in vitro transcribed Osk "confirms" that the NTD is responsible for the higher molecular weight of Nasonia Osk. Is this experiment is needed?
- In Figure 2e, the authors don't observe recruitment of Nv-Vas to Nv-Osk granules in S2 cells, leading to the proposal that "contrary to Drosophila, Nv-Osk does not directly recruit or associate with Nv-Vas in Nasonia" (line 231). It's possible that Nv-Osk is necessary but not sufficient to recruit Nv-Vas, and the authors might consider directly testing this by RNAi depletion of Osk in Nasonia.
- The authors should mention and discuss the high level of gH2Av staining in the oocyte nucleus (Figure 3b). Has this been reported before?
- The authors find strong gH2Av staining in anterior nurse cells, leading them to write in line 277: "indicating that the same population of nurse cells that assemble high amounts of nuage, shows high level of DSBs." While it is likely that this is the same population, without co-staining of germ granules and gH2Av in the same egg chmaber the authors cannot conclude that this is the same population of cells.
- In Figure 3a, the authors note that Nv-Osk is produced in the cytoplasm of nurse cells, where it assembles into granules. It might be worthwhile to use osk RNAi as a control to make sure that the granular Osk signal in their IF is specific.
- Unless I've missed it, the authors never reference Extended data Figures 6a and b in the text.
- The authors write in line 362: "The spherical shape of these granule, point to their liquid characteristics and their formation inside the oosome core via liquid-liquid phase separation mechanism." Spherical shape alone is not sufficient to conclude liquid-like character or assembly via LLPS.
Referees cross-commenting
I might clarify that analyzing maternal RNA localization should be optional (Reviewer 3 Major Comment 5).
Significance
In this study Kharel et al use endogenous antibodies to observe the dynamics of conserved germ granule components in Nasonia. This approach allowed the authors to uncover several key differences between germ granules in Nasonia versus Drosophila. While these differences have the potential to be of interest to the specialized germ cell community, the data presented in this study are largely descriptive and not quantified. Therefore, the functional relevance of these differences remains uncertain.
The finding that a subset of nurse cells have high levels of nuage is quite striking. Furthermore, the authors write in line 405: "The occurrence of DSBs in a distinct population of nurse cells in any organisms has not been reported before to our knowledge." Therefore, this population of nurse cells may be unique to Nasonia and would be of interest to be explored further in future studies. The authors could use granule mutants to test their hypothesis that high levels of nuage are required to silence transposable elements.
A main goal of this study is to compare germ cell assembly between Nasonia and Drosophila, and thereby identify how unique features of Nasonia contribute to germ granule dynamics and function. Indeed, the oosome is quite unique as an enormous, solitary granule (though perhaps reminiscent of a Balbiani body?), and how it maintains integrity is an open question. The authors propose that Nv-Tud acts as a shell to stabilize the oosome, which would be remarkable for such a large germ granule. This finding could be of interest to a broader field of condensate researchers. Therefore, future studies should directly test whether Nv-Tud is required for oosome integrity. Finally, it would be helpful to the reader to more fully discuss direct comparisons between Nasonia and Drosophila germ granule components. For example, the authors should comment on what is known about isoforms of Drosophila Vasa, and whether Drosophila Vasa may have the potential to be alternatively spliced.
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Referee #1
Evidence, reproducibility and clarity
The manuscript entitled "Dynamic protein assembly and architecture of the large solitary membraneless organelle during germline development in the wasp Nasonia vitripennis" by Kharel et al. aims to examine structural features of the wasp oosome. Specifically, the authors look at the expression of the Vasa and Oskar protein isoforms, their accumulation in the oosome and nuage during oogenesis and early embryogenesis and aim to understand possible functional roles of the structure of these organelles in female germline development.
However, several conclusions in this paper are not fully supported by the data and some of the experiments need additional experimentation and controls. Below I am listing my concerns (listed in the order they appear in the manuscript):
Major concerns:
Lane 141: Extended Data Fig. 1b: Control demonstrating that CIP treatment worked. Lack of change could be due to the enzyme not working.
Lane 149: To demonstrate a differential splicing pattern the authors need to show PCR using primers spanning the intron that is retained or spliced out. These PCR products should also be quantified using qRT-PCR. The authors should explain the multitude of bands on the PCR gel - the gel presented by the authors is not convincing and shows issues with annealing efficiency (non-specificity) of primers.
Lane 168-169: "we detected Nv-Vas outside the oosome, distributed in the embryos' cytoplasm (Fig. 1g)." The authors should show a control of the embryo/oocyte stained the same way but without the primary antibody to evaluate background fluorescence in the staining. The images should be quantified and imaged/displayed using the same imaging and normalization parameters as the one shown in Fig. 1g.
Lane 171: Data showing the result of this mass spec experiment is not shown.3
Lane 181: Extended Data Fig. 2: This graph is hard to interpret. A control is missing that shows how a curve of the structured protein or an FG-repeat containing fragment of the nucleoporin would look like. As it stands now, it is just a curve that cannot be interpreted by someone who has never used CD spectroscopy to study IDRs.
Lane 202-203: "The Nv-osk mRNA 3' RACE mapping was consistent with the previously identified 3'-end of Nv-osk mRNA indicating that Nv-Oskis not extended at its C-terminus." Data for this is not shown in this manuscript.
Lane 204: "However, 5'-end mapping revealed that Nv-osk RNA starts at more than 800 bps upstream of previously predicted Nv-osk transcription start site (Extended Data Fig. 2c)." The authors show a schematic which is not data. Instead, they should show raw dat.
Lane 213-215: "in addition to major 51 kD band, a less intense ~100 kD band is detected, suggesting the formation of Osk dimers (Extended Data Fig. 3e) consistent with previous finding that LOTUS domain of Nv-Osk dimerizes" The authors are (presumably) running denaturing PAGE gels and they add beta-mercaptoethanol to the samples before they load them on the gel. Therefore, dimerization should not be detected on the gel. The band the authors see must be a contaminant.
Lane 231: "that, contrary to Drosophila, Nv-Osk does not directly recruit or associate with Nv-Vas in Nasonia (Fig. 2e)." The authors cannot make this conclusion. It is possible that Osk and Vasa interact directly but that one of the proteins requires a post-translational modification for this interaction and this modification does not happen in S2 cells on Nasonia proteins.
Lane 237: Lack of these specific amino acids in Nasonia proteins does not support the argument that Nasonia Osk and Vasa do not interact. Perhaps changes in amino acids in Vasa are compensated by changes in amino acids in Oskar.
Lane 243: "co-expressed in S2 cells, fail to form granules (Fig. 2e). Overall, our data suggest that while Nv- Osk has the intrinsic ability to condense into spherical granules..." If the expression of Vasa is not high enough, then Vasa will not phase separate in S2 cells. It is possible that both proteins phase separate but at different critical concentrations, which would explain the lack of granule formation of Vasa in S2 cells.
Lane 286: "transposon-related gene in Nasonia ovaries, we found no evidence that transposable elements are selectively upregulated in anterior nurse cells (Extended Data Fig. 5b), suggesting that high assembly of anterior nuage is needed to effectively silence transposable elements despite the prevalence of DSBs in anterior" This is an overstatement and incorrect interpretation. Since the staining is not mutually exclusive, the authors can conclude that there is no correlation between dsDNA breaks, nuage and transposon expression and that therefore nuage is not required for the regulation of transposon expression or dsDNA formation. Regardless, the data is correlative and existence of direct connection has not been tested. Lane 293: Control of IF staining without the primary antibody is missing to evaluate background fluorescence in the staining. The images should be quantified and imaged/displayed using the same imaging and normalization parameters. Also, the authors should do a western on oocytes that do not yet form germplasm to demonstrate Oskar protein expression in early oocytes.
Lane 311: There is no data demonstrating that the oosome has migrated - just two images of an oosome in embryos of different ages. The developmental changes (progression) of the embryo are also not evident. The data currently presented are not evidence of migration. The authors should avoid interpretations connected with migration using the data correctly presented.
Lane 314: the evidence that Tudor makes a shell is weak and only displayed in an image co-stained for Tud and Osk in Figure 4b. Co-staining of Tud and Vasa in the same panel does not display the shell convincingly. More data is needed to show a shell.
Lane 314: There is no data showing that the shell is fibrillar.
Lane 341-345: The authors overinterpret the data. Germ plasm is a cytoplasm and everything in a cell moves through the cytoplasm. This is not in itself evidence of a liquid nature of the oosome.
Lane 363: Round granule shape is consistent with LLPS but is not evidence for it. The authors should fix their statement.
Minor concerns:
Lane 95: Statement" In particular, we provide evidence for the presence of a novel N-terminal segment of Nasonia Oskar (Nv-Osk) adjacent to the conserved LOTUS domain that is absent in other insect Osk proteins." Is not true as written. The Drosophila melanogaster (D mel) Oskar has a N-terminal extension which forms the Long Oskar isoforms. In fact, what the authors report here is that Nosonia Oskar protein is a lot more similar to the D mel Oskar than previously reported by the authors, and that both organisms express long and short Oskar isoforms that with very similar protein structures. The authors should correct their statement.
Lane 134: Where is this data shown (Subsequently, we were able to confirm Nv-Vas identity of both IP-ed proteins with mass spectrometry.)- no mass spec data is reported in this manuscript
Lane 171: " ass spectrometry..." is missing an M.
Lane 200: Extended Data Fig 2b is referencing the wrong figure panel.
In general, western blots are missing molecular weight standards.
Lane 265: Tudor is not a component of nuage in D mel.
Significance
Overall, I found this manuscript interesting. It provided new insights in the expression of Vasa and Oskar and as well as new models of how these two proteins are regulated and how they accumulate in the oosome. Some of the features, like the newly identified N-terminal extension of Nasonia Oskar protein, appear to be shared with those of Drosophila melanogaster Oskar. This is an important finding because it indicates that mechanism by which Osk functions in the female germline might be conserved in insects.
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Reply to the reviewers
Manuscript number: RC-2023-02270
Corresponding author(s): Usha Vijayraghavan
General Statements
We thank all three Reviewers for their thorough assessment of our manuscript and their constructive feedback and comments.
Point-by-point description of the revisions
This section is mandatory. *Please insert a point-by-point reply describing the revisions that were already carried out and included in the transferred manuscript. *
Reviewer #1
We are encouraged by the very positive comments made on the significance of our study that it provides convincing insights on alternative modes of nuclear positioning and division which is an important question in cell biology. We also took all possible suggestions to improve the interpretation of our results, have also added some newer data to address the constructive points raised by the reviewer.
Major comments:
- A) I am concerned about the lethal phenotype caused by slu7 deprivation. Slu7 deficiency causes defective nuclear positioning at the bud in late G2. This phenotype per se should not cause defective mitosis, so slu7 deficiency may also be interfering with other aspects of mitosis which might indeed impinge on cell viability.
Response: Our data indeed show Slu7 knockdown has severe growth defect when grown on non-permissive media (YPD) where a two-fold difference in O.D. was seen by 12 hours (Supplementary figure 2.B).
We agree with the reviewer that defective mitosis, arises from several aspects of cell cycle including those in mitosis. The data we present show G2 arrest, small-budded cells with unsegregated nuclei and large-budded cells with segregated nuclei, all which do not progress through cell cycle phases and contribute to the severe growth defect. Further, GO enrichment analysis of deregulated pathways on knockdown of Slu7 support the above findings as various cell cycle related pathways are abnormal in their expression levels. In this study, we have focused on an in depth analysis of the role of Slu7 in a particular window and uncover how it controls nuclear position for progress G2-M phase cell cycle progression. The likely targets and mechanisms by which Slu7 regulates other phases of the cell cycle which needs similar other deeper investigations in future. Our detailed analysis of nuclear movement in Slu7 knockdown cells grown in YPD for 12 hours showed no nuclear movement (Supplementary figure 3B) which is the terminal phenotype. To examine events that lead to nuclear mispositioning phenotype we investigated the dividing slu7kd cells grown in non-permissive media for only 6 hours; under these conditions Slu7 protein is still detected at lower amount (Supplementary figure 1D). From the studies of nuclear position, mitotic spindle position and dynein distribution in mother and daughter cell, we propose that in the dividing cells, the nucleus does not experience enough force to move inside the daughter bud during mitosis. Further, we delineate the role of Slu7 in the splicing of transcripts for PAC1 encoding a protein whose homolog in S. cerevisiae has a proven role in nuclear migration. In live imaging of slu7kd cells that show nuclear segregation at the start of live imaging, new bud was not formed till the end of 60 minutes, implying that are arrested after transition to mitosis. We could speculate a role for Slu7 through regulation of genes involved in mitotic exit or cytokinesis.
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B) Supp. Fig4 shows defective mitosis in TBZ, so TBZ may be exacerbating defective mitosis of slu7-deficient cells.
__Response: __Studies with yeast and mammalian model systems have revealed that the mobility and repair of damaged DNA are compromised upon disruption of microtubules (Wu et al, 2008; Chung et al, 2015; Lottersberger et al, 2015; Lawrimore et al, 2017; Oshidari et al, 2018; Laflamme et al, 2019). These data point to reasons why the mutants in DNA damage checkpoint genes are sensitive to TBZ. In this context, we observed that CnSlu7 knockdown is also sensitive to MMS stress (shown below). In addition, recent work on human Slu7 in Hela cell lines has elucidated the its role in the maintenance of genome integrity by preventing the formation of R-loops (Jiménez et al, 2019). We suggest that TBZ may exacerbate the defective mitosis of Slu7 depleted cells, however, whether it is particular only to mitosis or to the other cellular processes where the microtubules are involved needs further investigation.
Throughout the figures it can be observed uneven chromosome/nuclear segregation in cells deprived of slu7, however, these mitotic defects have not been mentioned or explored in depth. From Supp Figure 3C it can be inferred that CENP-A segregation is uneven. Is this correct? Is CENP-A-GFP segregation normal?
__Response: __ It should be noted that in Cryptococcus, the kinetochore remains unclustered during the early phase of cell cycle, cluster to a single punctum at the end of G2 phase and then de-cluster at the end of mitosis. Since this is a highly dynamic process, its technically challenging to measure the intensity CENP-A in mother and daughter cell. In the fixed cell imaging or live imaging data, there are no appreciable differences in intensity of the GFP signal of the tagged proteins (H4 and CENPA). The uneven chromosome/nuclear segregation observed in certain panels images presented are due to technical issues in that particular stack while generating the montage. This has been re-examined and we infer that there are no major differences in the signals from GFP-H4 and GFP - CENPA through mitosis.
Additionally, taking the cue from the reviewer’s comment, we examined the likelihood of improper chromosome segregation by evaluating if there are any appreciable cell populations that are aneuploid. We revisited our flow cytometry data, we found no significant difference in the population of aneuploid cells between the knockdown strain and wildtype strain grown in non-permissive condition for 12 hours. This data was assessed again in new experiments where we also analyzed by flow cytometry the ipl1 mutant where aneuploidy is reported (Varshney et al, 2019). It has been reported in Cryptococcus neoformans that aneuploid cells are resistance to anti-fungal drug fluconazole. Preliminary experiments showed that slu7kd cells were sensitive to fluconazole and in this assay were similar to wildtype cells. Hence, we speculate that chromosome segregation is normal in Slu7 depleted cells.
If chromosome segregation is altered upon slu7 deprivation, this might also explain the drop in cell viability and slow growth rates of this condition.
__Response: __ From live microscopy imaging and flow cytometry data, we believe that the chromosome segregation is normal in Slu7 depleted cells. Dilution spotting in permissive media after growth in non-permissive media revealed that slu7kd cells resumed growth without losing viability, indicating the arrest phenotype associated with the depletion of Slu7 is largely reversible and does not cause chromosome mis-segregation (figure is now added to manuscript as supplementary figure 2D). Prolonged arrest at various cell cycle phase might lead to cell death and hence drop in cell viability.
The manuscript will improve if authors analyse chromosome segregation for example, by showing time-lapse images of chromosome dynamics during mitosis.
__Response: __Chromosome dynamics during the mitotic phase is given below. We observe that the chromosome segregation is equal in both mother and daughter bud. The uneven chromosome/nuclear segregation observed in certain panels images presented in original manuscript were due to technical issues while generating the montage.
The authors perform an RNA seq comparing wild-type cells with slu7 deficiency and detect changes in gene expression, however, they do not explore from this data the percentage of un-spliced introns genome-wide which might be very informative, even more than changes in gene expression, which many of them, might be an indirect consequence of Slu7 deficiency. Authors should re-analyze the RNA seq data looking for unprocessed mRNAs and provide information about the overall impact of slu7 in intron processing.
__Response: __ A very detailed bioinformatic analysis of the impact on slu7 on global transcriptome and splice pattern, is an ongoing study in the laboratory. The findings are indeed giving good leads which are being validated by further experiments using mini-gene exon-intron constructs. These studies are extensive and form a future manuscript identifying and characterizing intronic features which predispose an intron towards Slu7 dependency. Therefore, it falls outside the scope for this study on the cell biological role of Slu7 on mitosis, specifically nuclear position to ensure faithful mitotic segregation.
Minor comments:
__ __1. "Previous studies of slu7 mutants in S. cerevisiae and the conditional knockdown of its S. pombe homolog". Consider replacing homolog with Ortholog.
Response: The suggestion is well taken, and the word “homolog” has been replaced with word “ortholog”.
- A) Taking these results together, we conclude that the inability of the conditional mutant to grow in the non-permissive media is due to impaired progression through the G2-M phase of the cell cycle. Is the G2/M delay the cause of the slow growth phenotype of the Slu7 deficiency?
Response: From the live microscopy, we note that even when the budding index for mitosis has been reached the nucleus in slu7kd cells is still in the mother cell and spends more time here rather than reaching the bud or bud neck. We present G2/M delay as ONE of the reasons for the slow growth of Slu7 depleted cells. Although we have showed that Slu7 depletion does not activate MAD2 dependent Spindle Assembly Checkpoint, we have not investigated the activation of other cell cycle checkpoints such as G2 DNA damage checkpoint. These are potential new leads as we infer from our RNA seq datasets that CHK1, TEL1, BDR1 and RAD51 show increased expression in Slu7 knockdown condition when compared to wildtype. It is therefore reasonable to conclude that Slu7 might play a role at various cell cycle phases through direct or indirect effect on genes involved in these phases. Delayed positioning of the nucleus during G2/M is one of the major effects that is investigated in depth in this study.
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B) If so, growth defects of slu7 deficiency could be suppressed by ectopic expression of G2/M activators.
Response: We have not tested this possibility, but we predict that expression of G2/M activators would at best offer only partial rescue the growth defect of Slu7 depleted cells since multiple pathways are adversely affected in cells depleted of Slu7.
In this line of investigation, we have tested the consequences of PAC1 overexpression, as PAC1 expression levels and splicing are affected by loss of Slu7. We report a partial rescue of nuclear position defect during mitosis, yet these cells were arrested at cytokinesis. Further, the unavailability of an array of suitable auxotrophic (or other) markers in this model system makes it technically challenging to do rescue experiments by overexpression of multiple candidate downstream genes.
Supp Figure 3C, remove the drawing on the right. Adjust times relative to panels.
Response: The drawing has been removed and the time points have been adjusted.
- Tracking the nucleus in wild-type cells with a small bud showed that the nucleus moved into the daughter bud, divided into two, and one-half migrated to the mother bud (Supplementary Figure 3B, top row).
Please replace the sentence: "one-half" with "one of the daughter nuclei". Additionally, as this nuclear positioning occurring during late mitosis is due to spindle elongation, I would not use the term migrated but "positioned" or "moved". Nuclear movement into the bud, which is referred to as "moved", can indeed be named "migrated".
Response: The word “migrated” in the above sentence has been replaced with the word “moved”.
- Indicates in Figure 2B the marker used (GFP-H4), as in Fig Supp 3B.
Response: The marker has been indicated in the figure.
- Nuclear division initiates in the bud, and one of the divided nuclei with segregated chromosomes migrates back to the mother cell (Figure 2B, top panel, wildtype, quantified in Figure 2C grey bar).
As mentioned before, I would not name this, nuclear migration as it is the result of spindle elongation, and it can be confusing or misleading for non-expert readers.
Response: The word “migrate” in the above sentence has been replaced with the word “move”.
- These two conclusions should be revised and described in temporal/sequential order.
- Thus, we identify that the depletion of CnSlu7 severely affects the temporal and spatial sequence of events during mitosis, particularly nuclear migration and division.
- Together, these results confirmed that without affecting the kinetochore clustering, depletion of Slu7 affects nuclear migration during the G2 to mitotic transition in Cryptococcus neoformans.
Response: We thank the reviewer for bringing out the clarity in the concluding statements. These has now been revised to read as follows:
“Together, these results confirm that without affecting the kinetochore clustering, depletion of Slu7 affects nuclear movement during the G2 to mitotic transition in Cryptococcus neoformans. Thus, we identify that the depletion of CnSlu7 severely affects the temporal and spatial sequence of events during mitosis, particularly nuclear migration, and division.”
- In slu7d cells, in cells with small buds, numerous cMTs were nucleated from the MTOCs, and as the cell cycle progressed, they organized to form the unipolar mitotic spindle (Figure 3A, slu7kd GFP-TUB1 panel, time point 55 mins).
Please, revise whether the term unipolar mitotic spindle is correct here.
Response: The word unipolar has been removed.
- I suggest including page and line numbers in the manuscript to facilitate revision.
Response: We regret missing out this formatting guideline. The Page and line numbers have provided.
Reviewer #2
We are thankful by the very positive comments on the significance of our work, its novelty and findings being of broad interest to microbiology; splicing; cell cycle and cell division communities. We respond to all comments raised below.
- The authors test the Mad2-dependent spindle assembly checkpoint and show that it is not relevant for slu7-depletion. This is as expected if the defect is in nuclear positioning. They could test other checkpoint pathways that would monitor nuclear positioning in budding yeasts. Perhaps they have considered this: Bub2, Bfa1, Tem1, Lte1 mutants? I don't think this experiment is essential for publication, but it could strongly support their model.
Response: We appreciate the comment on other checkpoints operating during mitosis. However, we have not done these experiments to examine role of components that arrest mitosis (Bub2, Tem1 etc.) in response to spindle or kinetochore damage. We hope the reviewer appreciates that this line of work would require the generation of bub2Δ strain and extensive characterization for their role in checkpoint in Cryptococcus before it can be brought into strains compromised for Slu7.
__ Minor comments:__ 1. in Figure 3, Dyn1-GFP is imaged and in many of the cells in which Slu7 is depleted, nothing (or very little) can be seen. It is later argued that this is an indirect effect, due to defects in Pac1 and associated functions. Have the authors attempted a Dynein western blot (the 3xGFP tag should be quite sensitive)? It would be good to demonstrate that the Dynein motor complex hasn't simply fallen apart and Dynein been degraded in the slu7-depletion.
Response: A study in S. cerevisiae has reported the dynein expression does not change in pac1Δ cells (Lee et al., 2003). Since the molecular weight of CnnDYN1 along with the tag is 630kDa, we did attempt the very challenging experiment of western blot to check for the expression levels this very large protein in wildtype and slu7kd cells. Based on the reviewer’s suggestion, we have attempted dot blot of protein lysates from wild type and from slu7kd cells probed with anti GFP antibody for estimating DYN-GFP levels. Untagged WT H99 strain was used as negative control. The same blot was stripped and re-probed for PSTAIRE which served as a loading control. This experiment revealed that dynein levels are same in both wildtype and slu7kd cells.
in Figure 7: have any intronless genes been tested for rescue of the post-mitotic delay/arrest? This is not necessary for publication, but if any have been tested already, they could be listed here.
Response: We have not tested intronless genes for their role in the rescue of post mitotic delay/arrest. From the RNA seq data, we observed that most of the genes involved in mitotic exit network (MEN) and cytokinesis were highly expressed in slu7kd cells as compared to the wildtype indicating and indirect role for Slu7 in their expression level. So, we had validated three candidates MOB2, CDC12 and DBF2 by qRT PCR (Supplementary 7.D) and found they were upregulated in slu7kd cells and hence speculate that deregulation of these transcript could contribute to the post mitotic arrest in slu7kd.
In SFig2C legend make it clear that these cells are HU arrested at time zero. Are the cells in glucose or galactose during HU treatment.?
Response: We regret the lack of clarity in the legend and the required details have been added. The cells were initially grown in non-permissive media for 2 hours to deplete Slu7 and then HU was added to the non-permissive media and the cell were allowed to grow for 4 hours.
in SFig4, the TBZ sensitivity isn't very convincing as the slu7kd strain is struggling to grow at all on YPD.
Response: We agree with the reviewer comment on the growth of slu7kd cells on media YPD containing TBZ. TBZ may exacerbate the defective mitosis of Slu7 depleted cells, however whether it pertains only to mitosis or any cellular processes where microtubules are involved requires further investigation.
In SFig5 legend the volcano plot needs to be better explained. What are the dashed lines etc. ?
Response: We regret missing these details on the volcano plot which has now been added to the legend.
__Reviewer #3 __
We appreciate the views that our work provides strong evidence to support out conclusions that Cryptococcus neoformans Slu7 controls mitotic progression by efficient splicing of cell cycle regulators and cytoskeletal elements. We have taken all comments of the reviewer into account to revise our manuscript with additional data, and by improving the presentation. The key additional data are summarized below.
Major comments:
1) The authors claimed that CnSlu7 is the most divergent among the fungal homologs and closer to its human counterpart (Fig. 1A, Supplementary Fig 1A). -Just based on the phylogenetic tree including limited members, as in Supplementary Fig. 1, it cannot be concluded that CnSlu7 is closer to its human counterpart since the basidiomycete yeast such as C. neoformans itself is more closely positions to humans compared to the ascomycete yeasts S. cerevisiae and Sch. pombe in phylogenetic tree analysis. It is strongly recommended to include other fungal species from the Basidiomycota, such as Ustilago maydis, in phylogenetic analysis in Supplementary Fig. 1. - Conservation analysis among diverse eukaryotes is more meaningful data that the conservation withing the fungi group, so that it is recommended that the data of Fig. 1 A would be replaced with the revised Supplementary Fig 1. -The analysis data on amino acid identities among Slu7 homologues should be presented to support the claim.
Response: We agree with the reviewer that our data would be better served by an improved analysis of the phylogenetic relationship between various Slu7 homologs. We have therefore reconstructed the phylogenetic tree by including other fungal groups. This is presented here and also in the revised manuscript Supplementary Figure 1A. These data too, show that Cryptococcus (deneoformans and neoformans) Slu7 is the most diverged among its homologs from various fungal species with its closest homologs being other pathogens Puccinia graminis and Ustilago maydis.
2) Despite that CnSlu7 is the main key subject, the comparative analysis of CnSlu7 to the previously reported Slu7 homologues, in the aspect of functional domain organization, is not provided in the present manuscript. - It was reported that Slu7 contains the four motifs that control its cellular localization and canonical function as a splicing factor, such as a nuclear location signal, a zinc knuckle motif, four stretches of leucine repeats and a lysine-rich domain. Notably, human Slu7 protein is 204 amino acids longer than S. cerevisiae homolog with only 24% identity in the zinc knuckle motif (Molecular Biology of the Cell Vol. 15, 3782-3795). Thus, it is strongly recommended to provide additional information on the conserved and diverged features of CnSlu7 compared to other Slu7 homologs as a part of revised Figure.
Response: The multiple sequence alignment of Cryptococcus neoformans Slu7 with its fungal and higher eukaryote homologs such as human Slu7 and plant Slu7 proteins revealed that only the CCHC zinc finger motif is highly conserved. We do not detect conservation in the nuclear localization signal, stretch of leucine repeats and lysine rich domain except for leucine 3 stretch near the C terminal. This additional information is presented in revised Figure 1A.
3) The manuscript clearly demonstrated that one of key targets of Slu7-mediated splicing is PAC1 in C. neoformans. Considering, Pac1 is also conserved from S. cerevisiae to human, it could be speculated that the defect of Slu7 can affect nuclear migration in other fungal species and human cells by inefficient splicing of PAC1, despite striking differences in their nuclear position during cell division. Please discuss this possibility or provide the qRT-PCR analysis data of PAC1 homologs in the available fungal Slu7 mutant strains.
Response: Cell cycle arrest phenotypes of splicing factor mutants (studied largely in budding and fission yeast) results from inefficient pre-mRNA splicing of cell cycle-related genes. Slu7 is a well characterized second step splicing factor in S. cerevisiae where in vitro splicing assays with ACT1 minigene transcripts with a modified single intron showed ScSlu7 is dispensable for splicing when the branchpoint to 3'SS distance is less than seven nucleotides in the mini transcript (Brys and Schwer, 1996). In fission yeast we reported the effects of metabolic depletion of Slu7, which is an essential gene (Banerjee et al., 2013) and showed unexpectedly that in addition to BrP to 3'SS distance new intronic features contributors of dependency of fission yeast intron containing transcripts on Slu7 functions. The work also showed in multi-intronic transcripts its role is intron-specific and thus the candidate gene/ transcript is likely to be to dependent on Slu7 by virtue of the intronic features and not its biological function. In this study a splicing dependent role of CnSlu7 in cell cycle progression is investigated where based on a strong nuclear mis-positioning phenotype we narrowed on PAC1 transcripts as one of targets. We show PAC1, encoding a cytoskeletal factor, has introns dependent on CnSlu7 for efficient splicing and show partial rescue of nuclear position in strain complemented with expression of an intronless PAC1 gene. In this scenario, while it is likely that in other species where PAC1 exon-introns nucleotide sequences are similar to that in Cryptococcus a role for Slu7 may be predicted, for validation by other experimentalists.
Interestingly, PAC1 in S. cerevisiae is an intronless gene and its homolog is not annotated in S. pombe. In human cell lines, knockdown of Slu7 by siRNA resulted in metaphase arrest by inefficient splicing of soronin – which is crucial in sister chromatid cohesion and correct spindle assembly, according to recent research in human cell lines (Jiménez et al., 2019).
Hence the roles of splicing factor in cell cycle is through splicing of targets involved in cell cycle wherein the targets regulated by splicing factor may or may not be conserved in other species.
Minor comments:
General points 1) Provide information on the marker sizes in the data of qRT-PCR analysis presented in Figures 5 and 6, and Supplementary Fig 2A.
Response: We regret the omission of this technical data and have corrected the same by providing the marker sizes in all the figures.
2) Please unify the format of gene names. Some genes were written with superscript of "+", such as CLN1+ and PAC1+ in Fig. 4. What does "+" mean in the gene names?
Response: We have taken the suggestion to carefully review the nomenclature of genes and their expressed transcripts as is typical for Cryptococcus neoformans. To depict the wildtype form of transcript we had used +. Thus CLN1+ was used to denote Cyclin 1 cellular transcript from expressed from its own locus without any modification of promoter or the intronic features.
3) Supplementary Figure 1 C: Please correct "Slu7KD" 6 hrs YPD to "slu7kd" 6 hrs YPD.
Response: This error has been corrected.
4) Supplementary Figure 2A: What do "mRNA" and "No RT29X/", respectively, indicate?
Response: The mRNA indicates the spliced form across any intron after intron is spliced out, so denotes exon-exon sequences in the mRNA. The reactions marked as “No RT 29 X” denote semi- quantitative PCR performed on DNase treated RNA sample, without reverse transcription to generate the cDNA. These reactions were done to confirm that there is no genomic DNA present in the RNA sample used for reverse transcription reaction of the cellular transcripts. Some of these details are now included in the Supp Fig 2A legend.
5) Supplementary Figure 4C: Please provide brief explanation in the text on why the authors employed mad2Δ slu7kd cells.
Response: In Page 8, line 6, we had provided the rationale for generating and studying mad2Δ slu7kd strain. This is recapitulated below:
“To investigate whether Slu7 knockdown triggers the activation of spindle assembly checkpoint (SAC), we generated a strain with conditional slu7kd in cells with mad2Δ allele and the GFP-H4 nuclear marker.”
6) Supplementary Figure 6D legend: Please correct the description of "slu7kd SH:Slu7 FL" from "expressing intronless PAC1" to "expressing full length of SLU7".
Response: The error in the legend is regretted and this has been corrected.
7) Supplementary Figure 7D: The authors confirmed that MOB2, CDC12, and DFB1 were expressed at higher levels in slu7kd when compared to wildtype. Please briefly explain in the text why the expression level of these genes in slu7kd was mentioned.
Response: slu7kd cells expressing intronless Pac1 arrest post nuclear division. Revisiting our transcriptomic data, we found that genes involved in mitosis exit network and cytokinesis, such as DFB1, MOB2, CDC12, BUD4, and CHS2, were deregulated in slu7kd when compared to wildtype. We confirmed the same by performing qRT PCRs for three candidates, MOB2, DBF1 and CDC12 and that these transcript were expressed at high levels in knockdown when compared to wildtype.
8) The species name should be written as abbreviation after the first mention. For example, please correct Cryptococcus neoformans to C. neoformans throughout manuscript.
Response: The suggestion is well taken, and the required edits have been made throughout the text.
9) Please unify the format of paper titles listed in References.
Response: This formatting error is regretted and corrected to have all references in a single format.
10) No page information for Hoffmann et al (2010) in References.
Response: This omission is corrected.
11) Update the information on the published journal of Chatterjee et al. (2021) in References.
Response: This omission is regretted and is now corrected.
12) Information on the authors, title, published journal and pages should be provided for the papers (Yadav and Sanyal, 2018; Sridhar et al., 2021) in Supplementary Table 1, which were not included in the main Reference list.
Response: The references are now added to the main list.
References used for addressing the reviewer’s comments:
- Chung DKC, Chan JNY, Strecker J, Zhang W, Ebrahimi-Ardebili S, Lu T, Abraham KJ, Durocher D, Mekhail K (2015) Perinuclear tethers license telomeric DSBs for a broad kinesin- and NPC-dependent DNA repair process. Nat Commun doi:10.1038/NCOMMS8742.
- Jiménez M, Urtasun R, Elizalde M, Azkona M, Latasa MU, Uriarte I, Arechederra M, Alignani D, Bárcena-Varela M, Alvarez-Sola G et al (2019) Splicing events in the control of genome integrity: Role of SLU7 and truncated SRSF3 proteins. Nucleic Acids Res 47: 3450–3466. doi:10.1093/nar/gkz014.
- Laflamme G, Sim S, Leary A, Pascariu M, Vogel J, D’Amours D (2019) Interphase Microtubules Safeguard Mitotic Progression by Suppressing an Aurora B-Dependent Arrest Induced by DNA Replication Stress. Cell Rep 26: 2875-2889.e3. doi:10.1016/J.CELREP.2019.02.051.
- Lawrimore J, Barry TM, Barry RM, York AC, Friedman B, Cook DM, Akialis K, Tyler J, Vasquez P, Yeh E et al (2017) Microtubule dynamics drive enhanced chromatin motion and mobilize telomeres in response to DNA damage. Mol Biol Cell 28: 1701–1711. doi:10.1091/MBC.E16-12-0846.
- Lee WL, Oberle JR, Cooper JA (2003) The role of the lissencephaly protein Pac1 during nuclear migration in budding yeast. J Cell Biol. doi:10.1083/jcb.200209022.
- Lottersberger F, Karssemeijer RA, Dimitrova N, De Lange T (2015) 53BP1 and the LINC Complex Promote Microtubule-Dependent DSB Mobility and DNA Repair. Cell 163: 880–893. doi:10.1016/J.CELL.2015.09.057.
- Oshidari R, Strecker J, Chung DKC, Abraham KJ, Chan JNY, Damaren CJ, Mekhail K (2018) Nuclear microtubule filaments mediate non-linear directional motion of chromatin and promote DNA repair. Nat Commun doi:10.1038/S41467-018-05009-7.
- Varshney N, Som S, Chatterjee S, Sridhar S, Bhattacharyya D, Paul R, Sanyal K (2019) Spatio-temporal regulation of nuclear division by Aurora B kinase Ipl1 in Cryptococcus neoformans. PLoS Genet doi:10.1371/journal.pgen.1007959.
- Wu G, Zhou L, Khidr L, Guo XE, Kim W, Lee YM, Krasieva T, Chen PL (2008) A novel role of the chromokinesin Kif4A in DNA damage response. Cell Cycle 7: 2013–2020. doi:10.4161/CC.7.13.6130.
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Referee #3
Evidence, reproducibility and clarity
Summary:
The manuscript by Krishnan et al. reports the key role of a RNA splicing factor CnSlu7 in mitotic progression during the cell cycle of Cryptococcus neoformans, an intron-rich human pathogenic yeast. Using a conditional knockdown strategy and a time-lapse live imaging analysis of C. neoformans cells expressing a set of fluorescently tagged cell cycle markers (GHF-H4, GFP-CENPA, and GFP-TUB1), the authors clearly demonstrated the defective nuclear movement and cell division during mitosis under Slu7 depletion conditions. The global transcriptome analysis of the Slu7 knockdown strain revealed the downregulation of transcripts encoding several cell cycle regulators and cytoskeletal factors for nuclear migration, including PAC1. The requirement of PAC1 splicing by CnSlu7 for nuclear migration was validated by the rescue of nuclear migration defects in the CnSlu7 knockdown cells complemented with an intron-less PAC1 minigene, although the PCA1 complementation did not recover cell division defects. Based on their findings, the authors conclude that Slu7 ensures nuclear positioning during mitotic progression through RNA splicing in C. neoformans.
Major comments:
Overall, the manuscript provides a set of evident strongly supporting its conclusion that Slu7 controls cell cycle mitotic progression by efficient mRNA splicing of several cell cycle regulators and cytoskeletal factors in C. neoformans. However, there are a few points to be clarified and complemented by providing additional informatic analysis data and explanations in more detail.
- The authors claimed that CnSlu7 is the most divergent among the fungal homologs and closer to its human counterpart (Fig. 1A, Supplementary Fig 1A).
- Just based on the phylogenetic tree including limited members, as in Supplementary Fig. 1, it cannot be concluded that CnSlu7 is closer to its human counterpart since the basidiomycete yeast such as C. neoformans itself is more closely positions to humans compared to the ascomycete yeasts S. cerevisiae and Sch. pombe in phylogenetic tree analysis. It is strongly recommended to include other fungal species from the Basidomycota, such as Ustilago maydis, in phylogenetic analysis in Supplementary Fig. 1.
- Conservation analysis among diverse eukaryotes is more meaningful data that the conservation withing the fungi group, so that it is recommended that the data of Fig. 1 A would be replaced with the revised Supplementary Fig 1.
- The analysis data on amino acid identities among Slu7 homologues should be presented to support the claim.
- Despite that CnSlu7 is the main key subject, the comparative analysis of CnSlu7 to the previously reported Slu7 homologues, in the aspect of functional domain organization, is not provided in the present manuscript.
- It was reported that Slu7 contains the four motifs that control its cellular localization and canonical function as a splicing factor, such as a nuclear location signal, a zinc knuckle motif, four stretches of leucine repeats and a lysine-rich domain. Notably, human Slu7 protein is 204 amino acids longer than S. cerevisiae homolog with only 24% identity in the zinc knuckle motif (Molecular Biology of the Cell Vol. 15, 3782-3795). Thus, it is strongly recommended to provide additional information on the conserved and diverged features of CnSlu7 compared to other Slu7 homologs as a part of revised Figure 1 or Supplementary Figure 1.
- The manuscript clearly demonstrated that one of key targets of Slu7-mediated splicing is PAC1 in C. neoformans. Considering, Pac1 is also conserved from S. cerevisiae to human, it could be speculated that the defect of Slu7 can affect nuclear migration in other fungal species and human cells by inefficient splicing of PAC1, despite striking differences in their nuclear position during cell division. Please discuss this possibility or provide the qRT-PCR analysis data of PAC1 homologs in the available fungal Slu7 mutant strains.
Minor comments:
General points
- Provide information on the marker sizes in the data of qRT-PCR analysis presented in Figures 5 and 6, and Supplementary Fig 2A.
- Please unify the format of gene names. Some genes were written with superscript of "+", such as CLN1+ and PAC1+ in Fig. 4. What does "+" mean in the gene names?
- Supplementary Figure 1 C: Please correct "Slu7KD" 6 hrs YPD to "slu7kd" 6 hrs YPD.
- Supplementary Figure 2 A: What do "mRNA" and "No RT29X/", respectively, indicate?
- Supplementary Figure 4C: Please provide brief explanation in the text on why the authors employed mad2Δ slu7kd cells.
- Supplementary Figure 6D legend: Please correct the description of "slu7kd SH:Slu7 FL" from "expressing intronless PAC1" to "expressing full length of SLU7".
- Supplementary Figure 7D: The authors confirmed that MOB2, CDC12, and DFB1 were expressed at higher levels in slu7kd when compared to wildtype. Please briefly explain in the text why the expression level of these genes in slu7kd was mentioned.
- The species name should be written as abbreviation after the first mention. For example, please correct Cryptococcus neoformans to C. neoformans throughout manuscript.
- Please unify the format of paper titles listed in References.
- No page information for Hoffmann et al (2010) in References.
- Update the information on the published journal of Chatterjee et al. (2021) in References.
- The information on the authors, title, published journal and pages should be provided for the papers (Yadav and Sanyal, 2018; Sridhar et al., 2021) in Supplementary Table 1, which were not included in the main Reference list.
Referees cross-commenting
The slu7 deficiency would generate massive defects in intron processing, thus causing an overall alteration of gene expression. However, I agree with the reviewers #1 and # 2 that additional analysis on specifically focusing on (i) chromosome segregation and (ii) checkpoint pathways other than Mad2 could strengthen their conclusions on the key roles of Slu7 in nuclear position and cell division.
Significance
As a splicing factor necessary for the correct selection of 3 splice sites, Slu7 (Splicing factor synergistic lethal with U5 snRNA 7) strongly impacts the expression of diverse genes involved in various essential cellular functions. The Slu7 homologs have been intensively studied in the model yeast systems and human cell lines, revealing Slu7 as a pleiotropic factor with a holistic function at different levels of gene expression regulation in various cellular processes. This work presents advanced findings on a pivotal role of Slu7 in controlling nuclear migration and cell cycle progression, uncovering the molecular mechanism of a Slu7-dependent cell cycle mitotic progression in C. neoformans.
Considering that Slu7 is a general splicing factor, the depletion of Slu7 would affect diverse cellular functions besides nuclear migration and cell cycle progression. Thus, further studies on other physiological defects by Slu7 depletion in the human pathogenic fungi, C. neoformans, particularly such as the altered expression of virulence-associated genes under stress conditions mimicking host environments, can provide intriguing information on the possible involvement of splicing factors in regulating the virulence of pathogenic fungi.
My expertise is the protein secretion and glycosylation in various yeast species, including C. neoformans.
- The authors claimed that CnSlu7 is the most divergent among the fungal homologs and closer to its human counterpart (Fig. 1A, Supplementary Fig 1A).
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Referee #2
Evidence, reproducibility and clarity
Summary:
This manuscript reports the effects of depleting the Slu7 splicing factor in Cryptococcus neoformans. Mitotic defects are apparent, in particular in positioning the nucleus with cells struggling to get this into the bud (daughter) before chromosome segregation. The manuscript is well written, logically presented and the data of high quality. I suggest minor modifications and a few additional experiments that could be attempted.
Major comments:
- Are the key conclusions convincing? Yes. Splicing is clearly perturbed. Pac1 is likely to be one of the targets, as expression of an intronless minigene rescues the spindle positioning defect in the slu7 depleted cells. Importantly, other defects are still apparent (late mitotic delay/block) and so growth is not rescued. This is not surprising, as the expression of hundreds of genes are affected by Slu7-depletion.
- the authors test the Mad2-dependent spindle assembly checkpoint, and show that it is not relevant for the slu7-depletion. This is as expected if the defect is in nuclear positioning. They could test other checkpoint pathways that would monitor nuclear positioning in budding yeasts. Perhaps they have considered this: Bub2, Bfa1, Tem1, Lte1 mutants? I don't think this experiment is essential for publication, but it could strongly support their model.
- Are the data and the methods presented in such a way that they can be reproduced? Yes.
- Are the experiments adequately replicated and statistical analysis adequate? Yes.
Minor comments:
- in Figure 3, Dyn1-GFP is imaged and in many of the cells in which Slu7 is depleted, nothing (or very little) can be seen. It is later argued that this is an indirect effect, due to defects in Pac1 and associated functions. Have the authors attempted a Dynein western blot (the 3xGFP tag should be quite sensitive)? It would be good to demonstrate that the Dynein motor complex hasn't simply fallen apart and Dynein been degraded in the slu7-depletion.
- in Figure 7: have any intronless genes been tested for rescue of the post-mitotic delay/arrest? This is not necessary for publication, but if any have been tested already they could be listed here.
- In SFig2C legend make it clear that these cells are HU arrested at time zero. Are the cells in glucose or galactose during HU treatment.?
- in SFig4, the TBZ sensitivity isn't very convincing as the slu7kd strain is struggling to grow at all on YPD. In SFig5 legend the volcano plot needs to be better explained. What are the dashed lines etc. ?
- Are prior studies referenced appropriately? Yes
- Are the text and figures clear and accurate? Yes
- Do you have suggestions that would help the authors improve the presentation of their data and conclusions? A few are listed above.
Significance
This manuscript will be of broad interest to the microbiology; splicing; cell cycle and cell division communities. The links between splicing and cell division is a novel area of research in Cryptococcus.
I am an expert in mitotic regulation in yeast. Not a splicing expert.
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Referee #1
Evidence, reproducibility and clarity
Summary
In this work, Vishnu Priya Krishnan et al., show that deprivation of the Slu7 splicing factor severely compromises the viability of Cryptococcus neoformans. The authors show convincingly that slu7 deprivation leads to G2/M arrest, defective nuclear migration to the bud, and improper nuclear positioning at the bud neck during mitosis. Authors correlate this phenotype with defective mRNA processing of the Pac1 gene, which in S. cerevisiae is required to target dynein to the plus end of microtubules and ensures nuclear migration during mitosis. Consistently, expression of an intron-less Pac1 mRNA partially rescued nuclear positioning defects of slu7 deficiency. The data showing the involvement of slu7 in mRNA intron processing is convincing.
Despite partially correcting nuclear positioning, expression of intron-less pac1 gene does not complement at all slu7 deficiency, suggesting that the lethality of slu7 lack of function is not caused by the nuclear positioning defects described here and it might arise from either deregulation of other specific factors as the authors suggest, to an overall unbalance of gene expression, or other reasons yet unknown.
Major comments:
-I am concerned about the lethal phenotype caused by slu7 deprivation.Slu7 deficiency causes defective nuclear positioning at the bud in late G2. This phenotype per se should not cause defective mitosis, so slu7 deficiency may also be interfering with other aspects of mitosis which might indeed impinge on cell viability. Supp. Fig4 shows defective mitosis in TBZ, so TBZ may be exacerbating defective mitosis of slu7-deficient cells. Throughout the figures it can be observed uneven chromosome/nuclear segregation in cells deprived of slu7, however, these mitotic defects have not been mentioned or explored in depth. From Supp Figure 3C it can be inferred that CENP-A segregation is uneven. Is this correct? Is CENP-A-GFP segregation normal? If chromosome segregation is altered upon slu7 deprivation, this might also explain the drop in cell viability and slow growth rates of this condition. The manuscript will improve if authors analyze chromosome segregation for example, by showing time-lapse images of chromosome dynamics during mitosis.
The authors perform an RNA seq comparing wild-type cells with slu7 deficiency and detect changes in gene expression, however, they do not explore from this data the percentage of un-spliced introns genome-wide which might be very informative, even more than changes in gene expression, which many of them, might be an indirect consequence of Slu7 deficiency. Authors should re-analyze the RNAseq data looking for unprocessed mRNAs and provide information about the overall impact of slu7 in intron processing.
Minor comments: -"Previous studies of slu7 mutants in S. cerevisiae and the conditional knockdown of its S. pombe homolog"
Consider replacing homolog with Ortholog.
-Taking these results together, we conclude that the inability of the conditional mutant to grow in the non-permissive media is due to impaired progression through the G2-M phase of the cell cycle.
Is the G2/M delay the cause of the slow growth phenotype of the Slu7 deficiency? If so, growth defects of slu7 deficiency could be suppressed by ectopic expression of G2/M activators.
-Supp Figure 3C, remove the drawing on the right. Adjust times relative to panels.
-Tracking the nucleus in wild-type cells with a small bud showed that the nucleus moved into the daughter bud, divided into two, and one-half migrated to the mother bud (Supplementary Figure 3B, top row).
Please replace the sentence: "one-half" with "one of the daughter nuclei". Additionally, as this nuclear positioning occurring during late mitosis is due to spindle elongation, I would not use the term migrated but "positioned" or "moved". Nuclear movement into the bud, which is referred to as "moved", can indeed be named "migrated".
-Indicates in Figure 2B the marker used (GFP-H4), as in Fig Supp 3B.
-Nuclear division initiates in the bud, and one of the divided nuclei with segregated chromosomes migrates back to the mother cell (Figure 2B, top panel, wildtype, quantified in Figure 2C grey bar).
As mentioned before, I would not name this, nuclear migration as it is the result of spindle elongation, and it can be confusing or misleading for non-expert readers.
-These two conclusions should be revised and described in temporal/sequential order. 1. Thus, we identify that the depletion of CnSlu7 severely affects the temporal and spatial sequence of events during mitosis, particularly nuclear migration and division. 2. Together, these results confirmed that without affecting the kinetochore clustering, depletion of Slu7 affects nuclear migration during the G2 to mitotic transition in Cryptococcus neoformans.
-In slu7d cells, in cells with small buds, numerous cMTs were nucleated from the MTOCs, and as the cell cycle progressed, they organized to form the unipolar mitotic spindle (Figure 3A, slu7kd GFP-TUB1 panel, time point 55 mins).
Please, revise whether the term unipolar mitotic spindle is correct here.
-I suggest including page and line numbers in the manuscript to facilitate revision.
Significance
Understanding different strategies of nuclear positioning and division is an important question in cell biology. The model organism used in this study, Cryptococcus neoformans, performs a mode of division that is different from S. cerevisiae, as the nucleus migrates to the bud in late G2 and later to the bud-neck, whereas in S cerevisiae the nucleus remains in the mother cell during G2 before its positioning to the bud-neck prior mitosis. In both cases, proper nuclear positioning at the bud neck ensures DNA-nuclear segregation between the mother and the daughter cells by elongating the intranuclear mitotic spindle. Thus, understanding this alternative mode of nuclear positioning and division is a relevant problem in the field.
Strength
The demonstration of the involvement of slu7 in mRNA intron processing is convincing and the suppression of nuclear positioning defects of slu7 deficiency by expressing an intron-less Pac1 gene provides evidence that indeed, as in S. cerevisiae, both dynein and Pac1 also play a critical role in nuclear positioning in Cryptococcus neoformans.
Limitation
The authors get to the problem of nuclear positioning by using the deficiency of the intron processing factor, slu7. Deficiency of slu7 is lethal possibly due to massive defects in intron processing and an overall deregulation of gene expression. However, the authors of this study analyze slu7 deficiency in a short window of time followed slu7 switch-off and describe some of the phenotypes resulting from this condition.
The result presented in this study might be useful for a specialized audience. The suggested genome-wide analysis of intron processing defects and a better analysis of chromosome segregation during mitosis under slu7 deficiency might be useful to increase the impact of this study and reach a greater audience.
My expertise.
I have been working in nuclear positioning in the fission yeast and have made some contributions to this field by generating a procedure to displace the nucleus within the cell. This approach allowed us to study forces and mechanisms responsible for nuclear positioning. I have also recently made key contributions to the field of nuclear mechanics, by describing how interphase microtubules contribute to cohesin loading, and the field of nuclear division, by describing mechanisms of spindle disassembly and nuclear partitioning in the fission yeast.
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Reply to the reviewers
REPLY TO REVIEWERS
Reviewer #1
__Evidence, reproducibility and clarity: __Interesting results from exposing human brain organoids to FGF8 include suggestions that FGF8 contributes to the anterior to posterior patterning of the neocortex, as previously reported in mouse. Good, varied methods with reproducibility described well in the methods section. It would improve the reader's experience however to cite numbers of organoids used in specific experiments/assays in the main text.
Response: We thank the Reviewer for the positive assessment of our study, and we agree that citing the number of organoids per experimental approach would better allow the readers to appreciate the intrinsic variability of organoid protocols. We will include the number of organoids per experiment both in figure legends and in Materials and Methods as a summary table.
....Organoids do not develop individual neocortical areas. To approach this issue of area identity, however, the authors compared control and FGF8-treated organoids against an existing dataset of transcriptomes of human fetal brains that separated pre-frontal, motor, somatosensory, and visual areas. This seems a good idea, but results showed both treated and untreated organoids alike expressed genes characteristic of somatosensory and pre-frontal cortical regions (anterior and midlevel areas) apparently suggesting that exogenous FGF8 had little effect. Because the previous dataset was not the authors' work, however, and because a comparison between organoids and actual human tissue is hard to interpret, this whole section is probably only confusing to include.
Response: We would like to clarify to the reviewer that the effect of FGF8 on antero-posterior area identity is only partial in our organoid system, suggesting that different doses or temporal windows of FGF8 treatment may be necessary to achieve a stronger modulation of area identity genes. We agree with the Reviewer that, due to this partial effect, the transcriptomic comparison with fetal brain areas might be confusing for readers. Therefore, we plan to move this type of data to the Supplementary Material. We thank the Reviewer for bringing this to our attention.
The authors further stress a dorsal/ventral effect in FGF8-treated organoids. The population of ventral telencephalic interneurons, produced in the lateral ganglionic eminence in mice, expand in the human organoids at the expense of glutamatergic neurons of the dorsal telencephalon. This may be consistent with the loss of ventral telencephalic structures in FGF8-deficient mice. The authors suggest that FGF8 expansion of interneurons is a novel finding not previously seen in animal research and may point to a human-specific characteristic. Readers may believe this part of the paper requires more support, just because multiple studies of FGF8 have not revealed this action. Overall, this paper would benefit from shortening, and by statements that some of the results suggest, but do not guarantee, particular conclusions.
Response: We agree with the reviewer that before stating that FGF8-induced expansion of interneurons in dorsal telencephalic territories is a human-specific characteristic, more support in mouse studies would need to be performed. However, as suggested by reviewer 2 below, there is some evidence that ventral interneuron markers, such as ASCL1 and DLX2, are expressed in the dorsal telencephalon of the early fetal human cerebral cortex, even if at much lower levels than in the ventral telencephalon, and that individual human cortical progenitors can generate both excitatory neurons and inhibitory interneurons in culture. Thus, FGF8 might promote an intrinsic capacity of dorsal cortical neurons to induce the generation of ventral interneurons, which would indeed be a human (or maybe primate)-specific trait. We plan to better discuss this issue in the revised version of the manuscript.
Significance
The paper is for a fairly specialized audience interested in the development of the cerebral cortex, but also has interest regarding developmental human brain defects
Response: Although the manuscript sounds upon first reading specific to a specialized audience interested in cortical development, we believe that the strength of our human organoid system is the formation of regionalized organoids including brain regions other than the cortex. Moreover, considering the increasing attention on brain organoids in general, and the lack of information on the action of FGF8 during human cortical development, we are confident that this study will attract a broader audience.
Interesting results from exposing human brain organoids to FGF8 include suggestions that FGF8 contributes to the anterior to posterior patterning of the neocortex, as previously reported in mouse. Good, varied methods with reproducibility described well in the methods section. It would improve the reader's experience however to cite numbers of organoids used in specific experiments/assays in the main text.
Response: We thank again the reviewer for acknowledging the potential of our study. As previously mentioned, we agree that providing information about the number of organoids used will enhance the statistical analysis. This will definitely be added in a revised version.
Reviewer #2
Evidence, reproducibility and clarity
……However, organoid technology offers a solution to this and the present study presents an elegant approach to addressing how FGF8 signalling directs both anterior/posterior and dorsal/ventral identity in neural progenitors and their offspring in human development. This has both biological and clinical relevance has the study demonstrates how FGF8 may be a key regulator of expression of susceptibility genes for neurodevelopmental conditions. The methods and approach are described clearly and in great detail and it serves as an exemplar for how studies like this might be pursued in the future. Likewise, the results are presented logically, using excellent figures with clear descriptions of the findings. It is positively entertaining to read and very thought provoking. We don't have any major issues with the conclusions.
Response: We sincerely appreciate the reviewer’s enthusiastic and thoughtful feedback. The positive remarks on the clarity and detail of our methods and results are very encouraging, and we are pleased that the reviewer found our study both entertaining and thought-provoking.
We have some minor issues over presentation and interpretation that we would like the authors to consider.
1) Developmental staging. It is stated that the organoids have reached a developmental stage equivalent to 16.5 GW based on expression of key genes such as CRYAB. Firstly, we would prefer an unambiguous way of stating age such as post-conceptional age. It is never clear what gestational weeks exactly means (post-menstrual, post-ovulatory?). Secondly, in several figures, UMAPs generated from the organoids are presented alongside representative mouse brain sections from E13.5 which is equivalent to about 11 post conceptional weeks in human. Although we find the mouse sections helpful, perhaps the potential discrepancy in developmental stage should be pointed out.
Response: We agree with the reviewer that the staging of human organoids in vitro can be very tricky. We will clarify this issue by using post-conceptional weeks (PCW) instead of gestational weeks in the revised version of the manuscript. It is true, that schematic representations of brain sections of mouse telencephalon of around E13.5 were used in the paper, but the idea was to choose an age where dorsal and ventral territories are clearly separated during embryogenesis to highlight the expression of the different genes. We will change the schematics to make sure they can be better compared with scRNA-seq data and will highlight that they represent early mid-gestation stages of mouse embryos.
2) Dorso-ventral patterning. Firstly, we wondered why VGLUT2 was used as a marker for dorsal identity when it is generally regarded as being expressed by subcortical neurons, e.g. thalamus and midbrain, whereas VGLUT1 is the standard marker for cortical neurons :https://doi.org/10.1016/j.tins.2003.11.005? Potentially, VGLUT2 expression may be more an indicator of mid/hindbrain identity than cortical identity. Is there any evidence for VGLUT2 expression by cortical cells in development? Also, MASH1 (more correctly called ASCL1) is not exclusively ventral, having shown to be expressed in a subset of intermediate progenitor cells for glutamatergic neurons in rodent doi:10.1093/cercor/bhj168 and particularly human doi: 10.1111/joa.12971. We are surprised that the recent evidence that human cortical progenitors do have capacity to generate GABAergic neurons 10.1038/s41586-021-04230-7; 10.1101/2023.11.06.565899 is not mentioned in this section as perhaps FGF8 doesn't so much ventralise progenitor cells as promote an inherent property. This might explain why MGE-like identity is not observed, whereas LGE/CGE like is, as it has already been shown that MGE-like gene expression by dorsal progenitors is very much less likely than LGE/CGE like expression 10.1038/s41586-021-04230-7; DOI 10.1007/s00429-016-1343-5
Response: We fully agree and thank the reviewer for bringing to our attention this interesting discussion and pointing to our confusion between VGLUT1 and VGLUT2 expression profiles. After checking our scRNA-seq data, we realized that the Reviewer is absolutely correct about the issue of using VGLUT2 as a dorsal telencephalic marker, as it is expressed in both dorsal and ventral cells. In contrast, VGLUT1 appears to be more specific for neocortical (dorsal) neurons (see UMAP images below). Moreover, it perfectly fits with our results showing a downregulation of VGLUT1 in dorsal glutamatergic neurons.
We are currently conducting additional staining experiments to support this point. Specifically, our plan includes:
- Performing immunostaining assays to validate the expression patterns of VGLUT2 in dorsal cortical neurons, notably triple VGLUT2/TRB1/CTIP2 and double VGLUT2/SATB2 stainings, to be added in Supplementary material. This will allow to confirm the use of VGLUT2 as a dorsal marker.
- Performing additional immunostainings involving VGLUT1, either juxtaposed with GAD67 to assess dorso-ventral neuronal balance or in conjunction with dorsal cortical markers to examine co-expression. This new analysis will be quantified using AI and integrated into Figure 4. Notably, these experiments will provide a comprehensive understanding of the expression patterns of VGLUT1 and VGLUT2 in the dorsal or ventral telencephalon and will further elucidate their utility as markers for specific neuronal populations in human brain organoids.
Furthermore, and importantly, we fully agree with the reviewer that human dorsal cortical progenitors do have the ability to generate GABAergic neurons, even if at lower efficiency than glutamatergic neurons, and that FGF8 might promote this inherent property in human organoids. This new discussion and the new references suggested by the reviewer will significantly contribute to our data interpretation about LGE/MGE development. Therefore, we intend to incorporate them into the revised version of the text. Again, thank you to the reviewer for these insightful suggestions.
3) MEA recordings. The presentation of electrophysiological data is quite simple. Detection of spikes is claimed therefore representative traces of the spikes should be included and these can be easily generated with the Maxwell system software. It isn't clear how many times the experiments were repeated and there is no statistical analysis. For example, in the text they state on page 15 'Notably, WNTi+FGF8 organoids showed lower spike frequency (firing rate) and amplitude'. The amplitude difference is 43uV vs 41uV; we doubt this is significantly different. Threshold for detecting burst firing appears to be different between Figure 5C and 5d. Why? Shouldn't it be the same? The axonal tracking analysis in fig 5E/F needs more explanation. How many axons were tracked? Is there any statistical analysis beyond means and standard deviation?
Response: We agree with the Reviewer that the presentation of our electrophysiological data need further improvement. We are currently repeating key recordings on four additional samples coming from two different batches, which will allow us to conduct a better statistical analysis.
In detail, we plan to:
- Extract representative traces of spikes from the Maxwell software, which will be included as Supplementary material. Footprints of action potentials will be extracted using the in-built analysis tool available in the software.
- Perform axon tracking analysis on three control and three FGF8-treated samples coming from two distinct batches of organoids. Recordings and analyses will be conducted over a period of two weeks to monitor the growth of axonal tracts, enabling us to perform statistical analysis and observe the temporal evolution of axonal growth. Furthermore, placing the threshold for detecting bursts in the network analysis at different levels in control or treated samples seems to be a routine procedure in this MEA system. Indeed, while the user can set a fixed multiplying factor (that is, of course, the same for both control and treated samples), it is the software that multiplies such factor by the basal average activity of the sample. In this way, bursts can be detected as synchronized activity emerging from the basal one, which, of course, varies in every sample. We plan to better explain this point in the Materials and Methods section, and we thank the reviewer for raising this lack of clarity.
4) Anterior/posterior patterning. Returning to the subject of cortical GABAergic neurons, it has been proposed that the prefrontal cortex contains a relatively higher proportion of GABAergic neurons, although the mechanism for this has not been elucidated (see https://doi.org/10.1111/joa.13055 and references therein). Might higher anterior FGF8 specifying cortical progenitors to produce GABA neurons have a role in this?
Response: We thank the reviewer for citing this very interesting review. It is highly possible that FGF8 normally expressed anteriorly might have a role in inducing distinct GABAergic subtypes, such as Calretinin+ interneurons, which have been found to be more abundant in frontal cortices of the developing human fetal brain. Our organoids are too early in terms of developmental age to verify whether interneuron subtypes such as CalR+ are more or less represented, but we will definitely add this very interesting point to our discussion in the revised version.
5) Nomenclature. As this study principally presents data on mRNA expression levels it might be preferable to use italicised capitals for all gene names (except where referring to mouse genes). Also, common names are used in places and standard gene names in others, e.g. COUPTF1 is referred to NR2F1 but VGLUT1 is not referred to SLC17A7 (also see above re MASH1). It would be good to see everything standardised.
Response: We appreciate the Reviewer for highlighting these discrepancies. We will standardize gene names both in the text and figures accordingly.
Significance
This study involves a very imaginative use of organoids combined with a variety of approaches to test if fundamental principles of forebrain development, particularly cell specification and regional patterning, that we have learnt from mouse models are relevant to human brain development. It also has clinical relevance as it explores potential disruptions to development that leader to diseases of higher cognition, such as autism of schizophrenia. It is a very accessible manuscript that should have broad appeal. It makes several incremental additions to the field and points the way to future experiments in this area.
Response: We sincerely thank the Reviewer's insightful comments and positive assessment of our study.
__Reviewer #3 __
__Evidence, reproducibility and clarity: __
In the manuscript "FGF8-mediated gene regulation affects regional identity in human cerebral organoids" the authors used FGF8 to change cellular fate in human brain organoids. The experiments are well-performed and the authors used well-established protocols to generate brain organoids. The results clearly show that FGF8 addition induces an increase of diencephalon/midbrain markers (OTX2, EN2), suggesting that long-term FGF8 treatment can induce also posterior regional identities. These data are reinforced also by scRNAseq highlighting a possible mix of cellular identity.
Response: We thank the reviewer for this encouraging report about our study highlighting the significance of our findings.
Main concern:
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The authors should start using FGF8 at later stages than day 19-21, in trying to maintain the forebrain identity.
Response: As the Reviewer correctly pointed out, the temporal window of FGF8 treatment seems of pivotal importance for the final outcome of regional identity acquisition. Indeed, while early treatment with FGF8 at day 5 disrupts FOXG1 expression in organoids, as demonstrated in Supplementary Figure 1, our first attempts at adding FGF8 at day 15 resulted in poor regulation of the major FGF8-target gene NR2F1. However, we noticed that high expression of FOXG1 was still maintained, supporting forebrain identity. We fully agree with the reviewer that it is worth treating organoids with FGF8 at later stages to test whether forebrain identity becomes enriched while midbrain one is reduced, which would highlight an FGF8-dependent dosage of forebrain identity acquisition. To this purpose, we have already started additional experiments to assess the effect of delayed FGF8 treatment on forebrain markers and FGF-target genes, such as ETV1, SPRY4, DUSP6, ETV4 and ETV5, but also on representative midbrain markers. Importantly, we will treat the same batch of organoids with the same amount of FGF8 but at different times to be able to compare the different treatments in parallel. We plan to incorporate these supplementary analyses into the Supplementary material to provide a more comprehensive characterization of the efficiency time windows of FGF8.
In detail, we plan to structure these additional experiments as follows:
- We will culture in parallel neural progenitors (cortical induction protocol, with XAV-939 as a WNT inhibitor) that will be treated with 100 ng/ML FGF8 starting at day5 (early treatment), at day10 (normal treatment) or at day 20 (late treatment).
- Each condition will require at least n=6 organoids.
- Samples will be cultured until day 30.
- At day 30, we will fix n=3 organoids per condition to be processed by immunostaining, and harvest n=3 organoids per condition for RNA extraction and Real Time RT-PCR analysis.
- By immunostaining, we will measure the number of FOXG1+ cells as a read-out of telencephalic identity and the intensity of NR2F1 staining to evaluate FGF8 action.
- By RT-PCR, we will measure the expression level of the following regional identity markers and FGF8 target genes: FOXG1, EN2, OTX2, NR2F1, ETV1, SPRY4, DUSP6, ETV4 and ETV5. This experimental setup will allow us to further detail the efficiency of distinct temporal windows for FGF8 treatment and their effects on cell identity and FGF target gene modulation. However, based on the first data we already obtained, we expect poor FGF target gene modulation upon late FGF8 treatment. This is why we believe that the temporal window we selected for our study already represents an optimal compromise between maintaining high levels of FOXG1 while effectively modulating FGF8 targets in human organoids.
To verify the identity of the neurons in the organoids the authors should check their ability to make projections in immunodeficient mice. Human iPSC-derived cortical neurons establish subcortical projections in the mouse brain after transplantation and the location of the different neuronal projections could reveal the rosto-caudal identity of the cortical neurons.
Response: We agree with the reviewer that in general conducting in vivo transplants of human organoids offers an interesting approach to testing the identity of differentiated neurons by tracking their projections. However, we believe that due to the multi-regional character of FGF8-treated organoids (which includes also midbrain-like neurons), their transplant into the neocortex would be of difficult interpretation and would not reveal the precise rostrocaudal identity of transplanted human cortical neurons, as requested by the reviewer. Furthermore, this would almost constitute an entire project on its own, given the technical challenges associated with such experimental approaches. We think that our thorough scRNA sequencing analysis is powerful enough for assessing cell identity, as supported by the majority of organoid studies investigating cell identity through scRNA-seq without resorting to transplantation. In our study, the scRNA-seq analysis was subsequently validated by several steps of immunostainings, a simple but fundamental corroborative control approach that is sometimes overlooked in similar studies. Finally, we would like to emphasize that reviewers #1 and 2 found our complementary approaches (molecular, cellular, and functional) appropriate, well-performed, logical and reproducible.
Significance:
The proposed protocol is useful to generate brain organoids with mixed cell populations from different regions of the brain (forebrain, midbrain, hindbrain). However, has limited applications since is not clear whether the proposed structures have some kind of organization.
Response: We agree with the Reviewer that each protocol comes with its own limitations and that a careful characterization of the proportion of different regional domains could definitively improve the significance and applicability of our protocol. To this aim, we are now using artificial intelligence-mediated detection of cortical versus midbrain-like domains in control and FGF8-treated organoids, to further improve the characterization of distinct cellular populations and quantify the extent of their domains in multi-regional organoids. These data will be added in Figure 3.
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Referee #3
Evidence, reproducibility and clarity
In the manuscript "FGF8-mediated gene regulation affects regional identity in human cerebral organoids" the authors used FGF8 to change cellular fate in human brain organoids. The experiments are well-performed and the authors used well-established protocols to generate brain organoids. The results clearly show that FGF8 addition induces an increase of diencephalon/midbrain markers (OTX2, EN2), suggesting that long-term FGF8 treatment can induce also posterior regional identities. These data are reinforced also by scRNAseq highlighting a possible mix of cellular identity.
Main concern:
- The authors should start using FGF8 at later stages than day 19-21, in trying to maintain the forebrain identity.
- To verify the identity of the neurons in the organoids the authors should check their ability to make projections in immunodeficient mice. Human iPSC-derived cortical neurons establish subcortical projections in the mouse brain after transplantation and the location of the different neuronal projections could reveal the rosto-caudal identity of the cortical neurons.
Significance
The proposed protocol is useful to generate brain organoids with mixed cell populations from different regions of the brain (forebrain, midbrain, hindbrain). However, has limited applications since is not clear whether the proposed structures have some kind of organization.
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Referee #2
Evidence, reproducibility and clarity
Almost everything we know about development of functional arealisation and cell specification in the telencephalon comes from studies in mouse, but it is important to compare our mouse models with human if we wish to understand the origins of our more evolved cognition and of neurodevelopmental diseases. Some work using transcriptomics and histology has already been done in this area, but directly studying mechanisms of guided differentiation is more difficult because of the accessibility issues surrounding live human fetal tissue and cells. However, organoid technology offers a solution to this and the present study presents an elegant approach to addressing how FGF8 signalling directs both anterior/posterior and dorsal/ventral identity in neural progenitors and their offspring in human development. This has both biological and clinical relevance has the study demonstrates how FGF8 may be a key regulator of expression of susceptibility genes for neurodevelopmental conditions. The methods and approach are described clearly and in great detail and it serves as an exemplar for how studies like this might be pursued in the future. Likewise, the results are presented logically, using excellent figures with clear descriptions of the findings. It is positively entertaining to read and very thought provoking. We don't have any major issues with the conclusions.
We have some minor issues over presentation and interpretation that we would like the authors to consider.
- Developmental staging. It is stated that the organoids have reached a developmental stage equivalent to 16.5 GW based on expression of key genes such as CRYAB. Firstly, we would prefer an unambiguous way of stating age such as post-conceptional age. It is never clear what gestational weeks exactly means (post-menstrual, post-ovulatory?). Secondly, in several figures, UMAPs generated from the organoids are presented alongside representative mouse brain sections from E13.5 which is equivalent to about 11 post conceptional weeks in human. Although we find the mouse sections helpful, perhaps the potential discrepancy in developmental stage should be pointed out.
- Dorso-ventral patterning. Firstly, we wondered why VGLUT2 was used as a marker for dorsal identity when it is generally regarded as being expressed by subcortical neurons, e.g. thalamus and midbrain, whereas VGLUT1 is the standard marker for cortical neurons :https://doi.org/10.1016/j.tins.2003.11.005? Potentially, VGLUT2 expression may be more an indicator of mid/hindbrain identity than cortical identity. Is there any evidence for VGLUT2 expression by cortical cells in development? Also, MASH1 (more correctly called ASCL1) is not exclusively ventral, having shown to be expressed in a subset of intermediate progenitor cells for glutamatergic neurons in rodent doi:10.1093/cercor/bhj168 and particularly human doi: 10.1111/joa.12971. We are surprised that the recent evidence that human cortical progenitors do have capacity to generate GABAergic neurons 10.1038/s41586-021-04230-7; 10.1101/2023.11.06.565899is not mentioned in this section as perhaps FGF8 doesn't so much ventralise progenitor cells as promote an inherent property. This might explain why MGE-like identity is not observed, whereas LGE/CGE like is, as it has already been shown that MGE-like gene expression by dorsal progenitors is very much less likely than LGE/CGE like expression 10.1038/s41586-021-04230-7; DOI 10.1007/s00429-016-1343-5
- MEA recordings. The presentation of electrophysiological data is quite simple. Detection of spikes is claimed therefore representative traces of the spikes should be included and these can be easily generated with the Maxwell system software. It isn't clear how many times the experiments were repeated and there is no statistical analysis. For example, in the text they state on page 15 'Notably, WNTi+FGF8 organoids showed lower spike frequency (firing rate) and amplitude'. The amplitude difference is 43uV vs 41uV; we doubt this is significantly different. Threshold for detecting burst firing appears to be different between Figure 5C and 5d. Why? Shouldn't it be the same? The axonal tracking analysis in fig 5E/F needs more explanation. How many axons were tracked? Is there any statistical analysis beyond means and standard deviation?
- Anterior/posterior patterning. Returning to the subject of cortical GABAergic neurons, it has been proposed that the prefrontal cortex contains a relatively higher proportion of GABAergic neurons, although the mechanism for this has not been elucidated (see https://doi.org/10.1111/joa.13055 and references therein). Might higher anterior FGF8 specifying cortical progenitors to produce GABA neurons have a role in this?
- Nomenclature. As this study principally presents data on mRNA expression levels it might be preferable to use italicised capitals for all gene names (except where referring to mouse genes). Also, common names are used in places and standard gene names in others, e.g. COUPTF1 is referred to NR2F1 but VGLUT1 is not referred to SLC17A7 (also see above re MASH1). It would be good to see everything standardised.
Significance
This study involves a very imaginative use of organoids combined with a variety of approaches to test if fundamental principles of forebrain development, particularly cell specification and regional patterning, that we have learnt from mouse models are relevant to human brain development. It also has clinical relevance as it explores potential disruptions to development that leader to diseases of higher cognition, such as autism of schizophrenia. It is a very accessible manuscript that should have broad appeal. It makes several incremental additions to the field and points the way to future experiments in this area.
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Referee #1
Evidence, reproducibility and clarity
Interesting results from exposing human brain organoids to FGF8 include suggestions that FGF8 contributes to the anterior to posterior patterning of the neocortex, as previously reported in mouse. Good, varied methods with reproducibility described well in the methods section. It would improve the reader's experience however to cite numbers of organoids used in specific experiments/assays in the main text.
Full review
During mouse embryonic development FGF8 protein disperses through the neocortical primordium in an anterior/posterior (A/P) gradient, regulating patterned expression of specific transcription factors (TFs) as the first step in generating the neocortical area map. More specifically, FGF8 upregulates area patterning genes expressed anteriorly and downregulates those expressed posteriorly. Both actions lead to the formation of the area map in mouse neocortex.
The authors of this paper investigate whether FGF8 and its downstream TFs play a similar patterning role in the human brain, a very significant question. A series of experiments assess effects of exogenous FGF8 on human brain organoids in regulating relevant genes using RTPCR, in situ hybridization, and, most convincingly, single cell RNA-Seq. Results for both neuroepithelial cells and neurons indicate appropriate upregulation of "anterior" cortical patterning genes, such as Pax6, alongside knock-down of "posterior" genes including Nr2f1 and Fgfr3. Surprisingly, expression of Emx2, another powerful gene implicated in the formation of posterior neocortex, shows only a slight, though significant, decrease in expression.
Organoids do not develop individual neocortical areas. To approach this issue of area identity, however, the authors compared control and FGF8-treated organoids against an existing dataset of transcriptomes of human fetal brains that separated pre-frontal, motor, somatosensory, and visual areas. This seems a good idea, but results showed both treated and untreated organoids alike expressed genes characteristic of somatosensory and pre-frontal cortical regions (anterior and midlevel areas) apparently suggesting that exogenous FGF8 had little effect. Because the previous dataset was not the authors' work, however, and because a comparison between organoids and actual human tissue is hard to interpret, this whole section is probably only confusing to include.
The authors further stress a dorsal/ventral effect in FGF8-treated organoids. The population of ventral telencephalic interneurons, produced in the lateral ganglionic eminence in mice, expand in the human organoids at the expense of glutamatergic neurons of the dorsal telencephalon. This may be consistent with the loss of ventral telencephalic structures in FGF8-deficient mice.<br /> The authors suggest that FGF8 expansion of interneurons is a novel finding not previously seen in animal research and may point to a human-specific characteristic. Readers may believe this part of the paper requires more support, just because multiple studies of FGF8 have not revealed this action.
Overall, this paper would benefit from shortening, and by statements that some of the results suggest, but do not guarantee, particular conclusions.
Significance
The paper is for a fairly specialized audience interested in the development of the cerebral cortex, but also has interest regarding developmental human brain defects
Interesting results from exposing human brain organoids to FGF8 include suggestions that FGF8 contributes to the anterior to posterior patterning of the neocortex, as previously reported in mouse. Good, varied methods with reproducibility described well in the methods section. It would improve the reader's experience however to cite numbers of organoids used in specific experiments/assays in the main text.
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The authors do not wish to provide a response at this time
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Referee #3
Evidence, reproducibility and clarity
Bianca Köhler and colleagues investigate the influence of miR-200c on cancer cell migration through a series of in vitro and in vivo experiments. After inducing miR-200c overexpression in MDA-MB 231 cells with doxycycline treatment, the researchers observe a reduction in metastases when these cells are implanted into mice. Using live imaging analysis, the authors found that MCF7 cells lacking miR-200c display increased mobility compared to wildtype cells, particularly at low cell density. Conversely, MDA-MB 231 cells with miR-200c overexpression show decreased mobility, irrespective of cell density in culture. Scratch assays show a diminished invasive capacity of MDA-MB 231 cells with heightened miR-200c expression. This finding aligns with results from transwell assays, where wildtype MCF7 cells exhibit reduced migration compared to MCF7 cells lacking miR-200c. In examining the impact of miR-200c on single-cell migration, a micropattern assay with two square islands connected by a thin bridge reveals a decrease in both transition frequency and transition speed of migrating MDA-MB-231 cells upon miR-200c expression.
In summary, this study provides a comprehensive exploration of the effects of miR-200c on cancer cell migration in various experimental contexts, offering insights into potential therapeutic implications.
The manuscript exhibits clear and articulate writing, coupled with well-explained experiments. To enhance its value, a more thorough characterization of miR-200c's mechanism of action, validation of its targets, and a more detailed analysis of in vivo metastases would be beneficial.
The manuscript's novelty appears limited, as the role of miR-200c as a tumor suppressor and its association with decreased metastatic potential in breast cancer cells have been previously documented (Klicka et al., Front Oncol 2022; Ljepoja et al., Plos One 2019). Highlighting unique contributions or contextualizing findings within existing literature would strengthen the manuscript's distinctiveness.
Comments to the authors: I recommend integrating these suggestions into the manuscript to enhance its scientific rigor and relevance.
Metastases Characterization:
Consider providing histological images illustrating the distribution of cancer cells in metastatic organs. This visual representation could offer readers valuable insights into the nature and characteristics of metastases arising from MDA-MB 231 cells.
Tumor Growth Impact:
Address the potential impact of tumor growth on metastatic dissemination by correcting for variations in primary tumor size when quantifying metastases in vivo. Accounting for this variable will strengthen the reliability and interpretation of the results.
Control Experiments:
Strengthen the experimental design by including a scrambled miRNA sequence as a control. This addition will contribute to a more robust comparison, ensuring observed effects are specifically attributed to miR-200c.
Target Validation for Mechanistic Insights:
Improve the understanding of miR-200c's mechanism of action by validating some of its natural targets. This step will provide a more solid foundation for interpreting experimental outcomes and unraveling the intricacies of miR-200c function.
Clinical Correlation:
Explore the possibility of correlating miR-200c expression with the progression of specific tumor diseases in patients. This potential correlation could contribute valuable clinical insights to the manuscript.
Translational Potential:
Once natural targets of miR-200c are validated, explore the translational potential by investigating whether these targets can be targeted by available drugs. Testing these drugs in tumor mouse models would further assess their efficacy and potential clinical applications.
Significance
In summary, this study provides a comprehensive exploration of the effects of miR-200c on cancer cell migration in various experimental contexts, offering insights into potential therapeutic implications.
The manuscript exhibits clear and articulate writing, coupled with well-explained experiments. To enhance its value, a more thorough characterization of miR-200c's mechanism of action, validation of its targets, and a more detailed analysis of in vivo metastases would be beneficial.
The manuscript's novelty appears limited, as the role of miR-200c as a tumor suppressor and its association with decreased metastatic potential in breast cancer cells have been previously documented (Klicka et al., Front Oncol 2022; Ljepoja et al., Plos One 2019). Highlighting unique contributions or contextualizing findings within existing literature would strengthen the manuscript's distinctiveness.
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Referee #2
Evidence, reproducibility and clarity
In this manuscript, Kohler et al analyze the impact of miR200c on cell motility in vitro and breast cancer metastasis in mouse models. The they show that miR200c represses metastasis to several different organs and propose that reduced motility is a significant cause of this. The experiments are generally sound and well performed. However, the insight gained with the study does not go much beyond what is already known about miR200c function in breast cancer. The experimental tools used in the study could provide the opportunity to reveal novel insights into the role of miR200c in metastasis. However, the investigators did not take full advantage of this and thus we are left with findings that are rather predictable based on the current literature. Details below.
Major points:
- The primary weakness of this study is limited novelty. miR200c has been shown to regulate migration and invasion of breast cancer cells in several previous studies, and this includes analysis using the same breast cancer cell lines that Kohler et al use in the current study, MCF7 and MDA-MB-231 (Jurmeister et al Mol Cell Bio 2012; Zhang et al Genet Mol Res 2017) and a study by the same group (Ljepoja et al Plos One 2019). Moreover, previous studies have also shown that miR200c represses metastasis in two different claudin low triple negative breast cancer models, MDA-MB-231 and genetically-engineered p53 null transplantable model (Simpson et al Genes 2022, Knezevic et al Oncogene 2016). Of note, Kohler et al do analyze metastases not only in lungs, but also in liver, brain and spleen and this could be a source of novel insights depending on the scientific questions. Is the miR200c mediated repression of metastasis caused by the same mechanisms in all these organs, or is it context dependent? What about molecular mediators downstream of miR200c?
- The authors focus primarily on migration issues as the potential cause of miR200c mediated repression of metastasis. However, there is significant literature on the role of miR200c in cancer progression. miR200c has been associated with multiple cellular functions, including regulation of epithelial mesenchymal transition (EMT) by repressing key EMT transcription factors ZEB1 and ZEB2. EMT regulation of course may suggest an effect on cell motility, but also several other functions, such as stem cell activity, plasticity, survival under stress and many more. Indeed, in a clinical setting some may question the importance of migration, considering that breast cancer cells disseminate from the primary tumor early in the process and upon diagnosis the cells are likely already lodged in secondary organs. Therefore, it is probable that cell functions such as survival under stress, proliferation and plasticity would be of even higher importance compared to cell motility. I would think that miR200c functional studies need to go beyond cell motility to generate additional insights into its role in metastasis and reveal potentially actionable targets.
- The investigators use a dox inducible system to express miR200c in MDA-MB-231 mammary tumors in mice. The mice were treated with dox to induce miR200c when the tumors reached 200 mm3 in size. This is a rather early induction of miR200c and may not address the ability of miR200c to repress actively growing metastatic lesions. I think these experiments should also be done by waiting longer before miR200c induction. What happens if the tumors are allowed to grow to 500 mm3 or 750 mm3? This would really test the ability of miR200c to inhibit overt metastasis.
Minor points:
- Although in some figures the plots/graphs show individual data points, this is not always the case. All box plots and bar graphs should show individual data points (biological replicates).
- Representative histological examples of the metastases in Figure 1C-1D should be shown.
- Presentation of the data in Figure 2C-2F is confusing. Statistics are also missing.
Significance
Although the study is technically sound, it suffers from limited novelty. Overall conclusions are predictable from previous studies. Of note, this study does provide somewhat more detailed analysis of migratory regulation by miR200c in cancer cells compared to previous reports. However, the study's advance is still quite modest.
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Referee #1
Evidence, reproducibility and clarity
Summary: in this manuscript, Kohler and coworkers describe the role of miR-200c in preventing breast cancer cell migration in vitro and metastasis in vivo (using sub cutaneous injections of human breast cancer cell lines in nude mice). The novelty of this manuscript resides in the in vivo work, as the role of miR-200c in preventing cell migration and EMT in vitro is widely established (and recognised in this manuscript).
Major comments:
- the authors need to measure miR-200c expression in their experimental systems. Here they described a DOX-inducible system to express miR-200c in MDA-MB-231 cells and they used KO MCF7 cells, but the levels of miR-200c are not reported at all in the manuscript. It is essential to show that DOX treatment induces miR-200c expression both in vitro and in vivo.
- the experiments presented in figure 4 do not contain the appropriate controls. In all the other figures, inducible MDA-MB-231 cells are presented, in the presence and absence of DOX. However, in this figure WT MDA-MB-231 cells are compared with the inducible variant in the presence of DOX. All the experiments in this figures need to be repeated with the inducible cells in the absence of DOX
- in the would healing experiments (figure 3), both KO and induction of miR-200c result in increased migration (which is not consistent with the rest of the data shown in the paper). This point should be explained more clearly in the discussion. In addition, the behaviour of the cells in the absence of DOX (figure 3G) seems very different in the control vs miR-200c cells (figure 3E) - this issue needs to be addressed in the discussion, as it could suggest that other factors independent of miR-200c expression might contribute to the difference between the 2 cell lines.
- in some instances, the authors draw conclusions from data that are not statistically significant, as in supplementary figure S2A and B, in relation to which the authors state 'both analysis were additionally validated... by crystal violet staining', but the quantifications show no significant differences
- all the migration experiments in vitro are in 2D. This should be highlighted as a limitation of this study. In addition, it is not appropriate to describe migrating cells as 'invasive', when this was not assessed in the experiment.
Minor comments:
- it is not clear what the difference between figure 4 A and B is
- it would be good to better clarify the rational behind and the physiological relevance of the confined cell motility experiment
- the authors measured differences in tumour volume it vivo, therefore it would be useful to assess cell proliferation in vitro as well. This is also important as proliferation can impact the cell migration assays used in this study.
- MCF7 cell migration is minimal, making it difficult to draw meaningful conclusions from these experiments. Longer migration times might be helpful here
- I was not able to open the supplementary videos, so I cannot comment on them.
Significance
General assessment: the strongest aspect of the study is the characterisation of the role of miR-200c expression in metastasis formation. However, the study lacks several controls. In my opinion, the in vivo work should be expanded, as the in vitro is mostly a confirmation of previous work. The data seem to hint to potential effect in organo-tropism, which warrant further investigation.
Advance: the in vivo work is novel, extending the knowledge of miR200c role in metastasis, while most of the in vitro work is incremental or confirmatory.
Audience: cancer biology researchers will mostly be interested in this work. There is potential for translational implications, but this needs to be strengthen.
I am a cancer cell biologist, expert in cancer cell migration and invasion. Most of my expertise is in 2D and 3D in vitro models, but I am also very familiar with mouse breast cancer models. I don't have sufficient expertise to comment on the analysis of the confined cell motility assay.
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Reply to the reviewers
We appreciate the positive and constructive comments of the reviewers on our paper. Below please find our point-by-point response to their comments.
Reviewer #1:
Main comments:
1) The expression levels of many genes, including some major TFs (like CEBPa or HNF4) in isolated primary hepatocytes greatly differ from that in normal liver. This is due to the disruption of cell-cell contacts. For this reason, single nuclei sequencing is more reliable and it is the preferred method. It is not indicated how many biological replicates were used and what level of variability was observed between different preparations.
We thank the reviewer for pointing out the immediate response of hepatocytes to dissociation, including in expression of CEBPa or HNF4 (this reviewer) and stress-related genes (reviewer 3), which we were aware of.
Unfortunately, however no perfect method exists to explore only hepatocytes in the context of the liver and single nuclei RNA-seq, which was not available at the start of our study, also has its limitations (e.g. substantial ambient RNA contamination, a lower median number of genes detected and potential for biases and higher doublet rates due to increased amplification steps (PMID: 34515767)).
Importantly, in our current study, we were interested in exploring gene regulatory networks in hepatocytes by the combination of RNA-seq and ATAC-seq. In our hands, data that we obtained from single cell ATAC-seq was far too shallow and noisy to predict gene regulatory networks. Hence, we needed to rely on pure populations of hepatocytes to perform our studies with bulk ATAC-seq, for which we optimized perfusion and subsequent density gradient centrifugation. While we succeeded in obtaining a very pure hepatocyte population, we agree with the reviewer that due to dissociation-associated changes the results that we obtain might not fully reflect the events happening in hepatocytes in the liver.
To address this issue brought up by reviewer 1 and 3, i) we will better indicate our rationale within the manuscript, and the limitations as indicated by both reviewer 1 and 3; ii) to provide an overview of potential changes that were induced by the perfusion procedure that we applied, we will compare the hepatocyte RNA-seq transcriptomes that we obtained with in vivo liver RNA-seq, with specific attention to transcription factors and stress-related genes (see reviewer 3, point 1); iii) we will better separate in the figures data obtained from hepatocytes versus data obtained from liver (see also point 2 from this reviewer).
Additionally, we will indicate how many replicated were used, and the level of variability between different preparations (donors).
2) The regulome studies involved analysis of ENCODE data sets (ChIP-seq), while the RNA-seq data were obtained in the current work. Due to the different source of the data (e.g primary hepatocytes used for ENCODE consortia members and this study) differences are expected. In the present study the cells were FACS-sorted immediately after isolation, while the ones used to produce ENCODE data sets were not subjected to sorting and were also probably cultured. This limits the accuracy of comparisons. Furthermore, the authors should indicate exactly which ENCODE data-sets were used.
It is also unusual to observe broad distribution of the ATF3, JUND and EGR1 ChIP-seq reads over the PCK1 gene or the Alb gene (Fig S3). Peaks called by MACS should be indicated. Have the authors verified this distribution, e.g by ChIP-PCR or other means? It is quite unlikely that binding motifs are present all over the gene bodies. Is it possible that these factors interact with elongating RNA Pol-II complexes? What is the situation in other actively transcribing gene bodies?
In the first paragraph of this comment, the reviewer rightfully points out that we use data from different sources in the first part of our study: scRNA-seq and ATAC-seq from perfusion-obtained hepatocytes (this study) and ENCODE ChIP-seq data which, in contrast to what the reviewer seems to assume, is obtained from liver (as profiled by ENCODE).
We did choose to use ChIP-seq data from liver tissue to corroborate our findings in isolated hepatocytes in the tissue of origin (largely composed of hepatocytes). Indeed, the near perfect co-localization of HNF4A and ATF3/EGR1 in liver tissue and the enrichment of corresponding DNA motifs in our ATAC-seq data strongly suggests interaction between bZIP family members and hepatocyte-specific transcription factors (including HNF4A) and hence support our conclusion.
To further address this issue, we will better separate the data obtained from hepatocytes versus data obtained from liver in the figures and include additional data for liver if available (see also point 1 from this reviewer). Additionally, we will indicate exactly which ENCODE datasets were used (see table below). Where relevant, we will explicitly mention the limitations/confounding factors of our analysis.
EGR1-liver ChIP-seq
ENCODE Project Consortium
ENCFF389LQC, ENCFF132PDR
JUND-liver ChIP-seq
ENCODE Project Consortium
ENCFF215GBK, ENCFF978CPC
ATF3-liver ChIP-seq
ENCODE Project Consortium
ENCFF522PUA, ENCFF094LXX
HNF4A-liver ChIP-seq
ENCODE Project Consortium
ENCFF302XOK, ENCFF500ZBE
FOXA1-liver ChIP-seq
ENCODE Project Consortium
ENCFF765EAP, ENCFF945VNK
CTCF-liver ChIP-seq
ENCODE Project Consortium
ENCFF002EXB
RAD21-liver ChIP-seq
ENCODE Project Consortium
ENCFF643ZXX, ENCFF171UDL
EGR1- K562 ChIP-seq
ENCODE Project Consortium
ENCFF000PZK, ENCFF000PZP
JUND- K562 ChIP-seq
ENCODE Project Consortium
ENCFF000YSC, ENCFF000YSE
ATF3- K562 ChIP-seq
ENCODE Project Consortium
ENCFF000PWC, ENCFF000PWA
With respect to the second paragraph: We obtained these liver tissue ChIP-seq profiles from ENCODE, in which these have gone through thorough validation procedures. Furthermore, we do observe very similar patterns with a complementary, but independent approach, ATAC-seq in hepatocytes. Hence, we do not think that further validation by ChIP-qPCR will have much added value.
We will follow the advice of the reviewer by i) indicating MACS peaks in our examples, ii) check whether ChIP-seq peaks in coding regions are typical for these datasets. If not, we will show better examples. If they are, we will are investigate potential motifs present in gene bodies, iii) investigate literature for a possible link between these factors and elongating RNA Pol-II complexes; and iv) investigate actively transcribing gene bodies
3) The synergism between AP1 and HNF4 is based on RNA and ChIP data in Primary hepatocytes. The main evidence for the synergism are co-binding of the two factors and the regulome profiles in the individual cells. In ICOs where both factors are expressed at high levels ChIP-seq data are not available and the potential binding distribution is estimated by the presence of binding motifs in ATAC-seq positive areas. Considering the concern described in point 2, it is important to obtain ChIP-seq data in ICOs too.
We would like to point out that, we make the central observations on overlapping regulatory modules in perfusion-derived hepatocytes, the ChIP-seq data to show co-binding of AP-1 and other factors with HNF4A (Fig 2c-f; Fig S3c-e) is all based on liver tissues. By showing this in the tissue or origin, we feel we provide sufficient evidence for the (potential) interplay between these factors in the liver, making ChIP-seq in ICOs redundant and beyond the scope of this study.
In addition, more direct experimental evidence for the synergism is needed. For example, demonstrating the synergism between HNF4 and some AP1 factors in specific genes by co-transfection experiments.
With regards to the potential synergy between HNF4 and AP1 in adult hepatocytes: previous studies have shown an essential role for c-Jun (part of AP1) in normal hematogenesis, with hepatocytes being rounded and detached in c-Jun KO mice (PMID: 8371760). This clearly shows the critical role of c-Jun in liver development and support to a potential interaction with HNF4 factors.
Yet, we agree with the reviewers that co-transfection (or knock down) experiments would be an elegant means to further support our conclusion. Unfortunately, however, PHHs are refractory to transfection making this experiment nearly impossible. Hence, instead we will tone down our statements about cooperation between these factors, instead referring to overlapping regulatory modules and co-binding as we observe.
4) Transcriptome comparisons between primary hepatocytes and intrahepatic cholangiocyte organoids (ICO) or ICOs cultured in hepatocyte differentiation medium (DM-ICO) were performed before (Ref. 6). These cells were derived from the same donor. In the current study ICOs were obtained from a biobank, thus they were from different donors. Differences between the expression patterns of primary cells and EM-IOC and DM-IOC organoid cultures are expected even if they derived from the same donor. In Ref.6 it is clearly demonstrated that DM-IOCs closely mimic many, but not all aspects of the liver phenotype. The present paper therefore provides only incremental new knowledge about the usefulness of organoid cultures in general. On the other hand, the scRNA-seq data with cells from the organoids point to the lack of zonation, which is an important new information, not analysed in Ref.6
We agree with the reviewer that the EM-ICOs and DM-ICOs have been well characterized in the ground-breaking works Reference 6. Indeed, in Figure 5d of Reference 6, it is shown that DM-ICOs display more comparable expression profile to hepatocytes than EM-ICOs. However, there are also clear differences between hepatocytes and DM-ICOs, indicating incomplete differentiation of the later. In our study, we now make the important observation that the differentiation potential of ICOs at least in part depends on the expression of ELF3 (Figure 3B).
To address this issue, we will put emphasis on the findings in Ref 6, and we will put our observations in better perspective in relation to Ref 6.
5) In the methods section the description of ICO culture conditions are very epigrammatic. It refers to previously published protocols but also mentions the addition of BMP7 in the first round of culturing without explaining why was this important. It would be useful if the authors describe exactly the culture conditions they used. Were the ICOs from the biobank established under culture conditions described in Ref 6 or by previous protocols?
We apologize for this being unclear. We will include this information in the revised manuscript.
6) The results about ELF3 function are interesting and convincing. This is a novel finding and may worth to perform a global transcriptome analysis and some immunostainings with specific markers in siELF3 cells to further strengthen its regulatory role in cholangiocyte-hepatocyte conversion.
We agree with the reviewer. To follow this up, we will perform RNA-seq during differentiation of ICOs towards hepatocytes, with and without siRNA-mediated ELF3 knockdown. This will further reveal the precise regulatory role of ELF3 in during hepatocyte differentiation.
Reviewer #2:
Comments:
1) Hepatocyte nuclear factors do not form a transcription factor (TF) family, they are from different TF families: the nuclear receptor, homeobox, and forkhead TF (super)families.
We thank the reviewer for pointing the mistakes in points 1 to 6 with regards to the naming of protein and protein families in our manuscript, we apologize for these inaccuracies. We will correct these naming and references, and check for any further inconsistencies.
2) AP-1 is not a TF family either. It is basically a heterodimer of FOS and JUN (sub)family members, which are part of the bZIP (super)family such as C/EBPs and ATF3, which latter is related to JDP2.
We will adapt this.
3) EGR1 is not a bZIP protein, it is a zinc finger protein from the EGR family. Was the motif of EGRs enriched? Only the motif of C/EBPs is shown on Fig. 2D.
We will adapt this. We will also analyze whether the motif of EGRs is enriched
4) RAD21 is not a TF, it is part of the Cohesin ring, which is associated to the insulator-binding CTCF.
We will adapt this.
5) EP300 (Fig. 2A) and PPARGC1A (Fig. 3B) are not TFs, they are co-regulators, basically co-activators, which can interact with several TFs. EP300 is otherwise not so specific, its presence in the chromatin is one of the major active enhancer marks.
We will adapt this.
6) DNA sequence motifs are typically not specific for a single TF, rather for a TF (sub)family, so based on a motif, it is usually not possible to identify a certain TF (Fig. 3F). Are there other nuclear receptors, SOX or ETS proteins that can bind to the identified motifs? (For example, FLI1 and several other ETS proteins can bind to the motif of ELF3/EHF, or there are several DR1-binding nuclear receptor dimers like HNF4/HNF4 or PPAR/RXR.)
We agree with the reviewer. We will analyze this and adapt the manuscript according to our findings.
&) Although the manuscript is easy to follow and understand, it needs to be checked for grammar.
We have asked a native speaker to proofread and adapt the manuscript.
Reviewer #3:
1) It is well known that perfusion of primary hepatic tissues (mice and human) results in immediate genetic responses, which will be captured right away in the performed RNASeq analysis. Stress pathways are upregulated and will normalize when the cells are put in culture for a couple of days. (Not too long, as they then undergo EMT and de-differentiate into non-parenchyma cells.) These responses can influence the expression profiles observed.
We thank the reviewer for this comment. Please see how we will address this concern in our reply to reviewer 1, issue 1, who raised a very similar point.
2) Why were the organoid cultures not differentiating properly into hepatocytes using different media cocktails (EM versus DM)? They seem to maintain cholangiocyte features, which questions the culture conditions used.
We thank the reviewer for the chance to clarify this important point. We like to stress that we do use the standard differentiation protocol as published (which we will also better detail in our material methods) and it does lead to differentiation towards hepatocyte like cells (both morphologically and gene expression-wise). However, what is not highlighted in previous publications, but broadly observed in the field, is that this differentiation is far from being complete and that the extent to which proper differentiation occurs varies between organoids from different donors. In our study, we now make the important observation that the differentiation potential of ICOs at least in part depends on the expression of ELF3 (Figure 3B).
3) The authors found the up-regulation of the AP-1 family proteins such as ATF3 and EGR1 which are known to induce apoptosis/cell death. Hepatic organoids are often found to have the un-intended necrotic core development which is caused by the oxygen diffusion matter and this issue is highly likely relevant to the size of the organoids. So, it would be advisable to specify the size of hepatic organoids (i.e., diameter) and check the necrosis-related genes.
To follow-up on this comment of the reviewer: We will measure the size of our organoids. These organoids indeed are typically hollow inside and hence we will check the expression of necrosis related genes and adjust our conclusions accordingly.
4) The KD approach with ELF3 in the ICOs is a good way forward, however only a minor number of hepatocellular genes are recovered, questioning the central role of ELF3 in driving the hepatocellular program. Functional assays, such as albumin release, bile acid production and CYP450 response should be coupled with the gene expression analysis.
In line with the response to reviewer 1 (point 6) we will perform RNA-seq to better characterize ELF3 KD-associated genes expression changes including genes typical and functionally relevant for hepatocyte function (e.g. albumin release and bile acid secretion)
5) The manuscript should be supplemented by adding the statement regarding the specific reason why a different set of donors was selected for two transcriptomics. The authors used three different donors for scRNA-seq and other two donors for the ATAC-seq. It seems better if all five donors were used for both transcriptomics analyses to reduce the inconsistent proportion of primary human hepatocytes (PHHs) from each donor. In addition, the donors which are selected should have identical genetic backgrounds for in-depth analysis of PHHs. The various backgrounds such as age, sex and ethnicity cause the transcriptional and translational heterogeneity. The authors need to explain the criteria on the selection of the donors.
We do agree with the reviewer that ideally all experiments are performed on the same set of donors. However, PHHs are obtained from surgical margins and hence provide a very limited source, leading to different experiments being performed on different donors. Importantly, the replicates for each experiment type have been obtained from multiple donors enabling us to capture common rather than donor specific expression/chromatin accessibility signatures.
Within the revised manuscript, we will include a paragraph on the criteria on the selection of the donors, and why a different set of donors was selected for two transcriptomics. Also, we will provide information with respect to the background of the donors.
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Referee #3
Evidence, reproducibility and clarity
In this study the authors aimed at characterizing the differences between primary human hepatocytes and hepatic organoids derived from human intrahepatic cholangiocytes (ICO), which can differentiate into hepatocytes, using scRNA-seq and ATAC-seq approaches. Their goal was to identify gene regulatory signatures that differ between the two models and to single out transcription factors that could drive hepatocellular functionality. They found the AP-1 family members to be associated with increased hepatic function together with known hepatocyte identity markers, such as HNF4A, FOXA1 and FOXA2. In ICOs they observed an increase of ELF3, which represent cholangiocyte-like features. KD of this factor induced the expression of known hepatocellular marker genes, such as ALB, CYP3A4, TTR, GC, and GLUL, indicating ELF3 may function as a barrier in hepatocyte differentiation.
Although this is an interesting approach to decipher, which transcription factors are involved in the development of proper human related hepatic organoids, it requires a more thorough analysis and ideally an improvement in the culture conditions to support their claims.
- It is well known that perfusion of primary hepatic tissues (mice and human) results in immediate genetic responses, which will be captured right away in the performed RNASeq analysis. Stress pathways are upregulated and will normalize when the cells are put in culture for a couple of days. (Not too long, as they then undergo EMT and de-differentiate into non-parenchyma cells.) These responses can influence the expression profiles observed.
- Why were the organoid cultures not differentiating properly into hepatocytes using different media cocktails (EM versus DM)? They seem to maintain cholangiocyte features, which questions the culture conditions used.
- The authors found the up-regulation of the AP-1 family proteins such as ATF3 and EGR1 which are known to induce apoptosis/cell death. Hepatic organoids are often found to have the un-intended necrotic core development which is caused by the oxygen diffusion matter and this issue is highly likely relevant to the size of the organoids. So, it would be advisable to specify the size of hepatic organoids (i.e., diameter) and check the necrosis-related genes.
- The KD approach with ELF3 in the ICOs is a good way forward, however only a minor number of hepatocellular genes are recovered, questioning the central role of ELF3 in driving the hepatocellular program. Functional assays, such as albumin release, bile acid production and CYP450 response should be coupled with the gene expression analysis.
- The manuscript should be supplemented by adding the statement regarding the specific reason why a different set of donors was selected for two transcriptomics. The authors used three different donors for scRNA-seq and other two donors for the ATAC-seq. It seems better if all five donors were used for both transcriptomics analyses to reduce the inconsistent proportion of primary human hepatocytes (PHHs) from each donor. In addition, the donors which are selected should have identical genetic backgrounds for in-depth analysis of PHHs. The various backgrounds such as age, sex and ethnicity cause the transcriptional and translational heterogeneity. The authors need to explain the criteria on the selection of the donors.
Significance
General assessment: This study used two powerful transcriptomics methods. The liver zonation was considered in the analysis which is reasonable. Limitations are related to cell culture conditions and lack of validations.
Advance: This study extends the knowledge in human in vitro model system (mostly technical, but also clinical field).
Audience: The audience from the basic and clinical research will be interested in this study.
The field of expertise: Liver metabolism, pathophysiology of liver diseases, pre-clinical investigation
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Referee #2
Evidence, reproducibility and clarity
Comments:
- Hepatocyte nuclear factors do not form a transcription factor (TF) family, they are from different TF families: the nuclear receptor, homeobox, and forkhead TF (super)families.
- AP-1 is not a TF family either. It is basically a heterodimer of FOS and JUN (sub)family members, which are part of the bZIP (super)family such as C/EBPs and ATF3, which latter is related to JDP2.
- EGR1 is not a bZIP protein, it is a zinc finger protein from the EGR family. Was the motif of EGRs enriched? Only the motif of C/EBPs is shown on Fig. 2D.
- RAD21 is not a TF, it is part of the Cohesin ring, which is associated to the insulator-binding CTCF.
- EP300 (Fig. 2A) and PPARGC1A (Fig. 3B) are not TFs, they are co-regulators, basically co-activators, which can interact with several TFs. EP300 is otherwise not so specific, its presence in the chromatin is one of the major active enhancer marks.
- DNA sequence motifs are typically not specific for a single TF, rather for a TF (sub)family, so based on a motif, it is usually not possible to identify a certain TF (Fig. 3F). Are there other nuclear receptors, SOX or ETS proteins that can bind to the identified motifs? (For example, FLI1 and several other ETS proteins can bind to the motif of ELF3/EHF, or there are several DR1-binding nuclear receptor dimers like HNF4/HNF4 or PPAR/RXR.)
- Although the manuscript is easy to follow and understand, it needs to be checked for grammar.
Significance
Haoyu Wu and his colleagues investigated the gene regulatory mechanisms contributing to human hepatocyte differentiation and maintenance integrating scRNA-seq, ATAC-seq, and ChIP-seq data and applying knock-down experiments. They differentiated the hepatocytes of the individual liver zones, identified the "lineage-determining" transcription factors of hepatocytes and intrahepatic cholangiocyte organoids, showed the co-localization of hepatocyte-specific and other, e.g., AP-1 transcription factors, and showed that the knock-down of ELF3 enhances hepatocyte characteristics. Although several findings and conclusions of the manuscript are available from the literature in some form, and some results could be interpreted better, this manuscript provides a novel insight in liver biology with results useful to the field. After thorough revision, this reviewer recommends the manuscript for publication.
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Referee #1
Evidence, reproducibility and clarity
In this manuscript Wu et al., present results from a comparative analysis of transcriptomes of primary hepatocytes and organoid cultures derived from intrahepatic cholangiocytes. The authors also performed scRNA-seq and ATAC-seq experiments. Using SCENIC R computational tool and ENCODE ChIP-seq data they performed regulon analysis. The main findings of the paper are the following: 1) The cell-to-cell heterogeneity of primary hepatocytes are mainly due to their zonal expression patterns within porto-central axis. 2) AP1 family of factors (JUN, FOS, ATF3 and others) co-occupy gene regulatory regions bound by HNF4 and the associated transcriptome profiles suggest that AP1 factors cooperate with liver-specific factors to regulate hepatic genes. 3) Different sets of transcription factors are active in primary hepatocytes and intrahepatic cholangiocyte organoids that were differentiated in vitro to hepatocyte-like cells. 4) Identification of ELF3 as a factor required for cholangiocyte to hepatocyte conversion. The findings are interesting, although in many cases are expected. There are some issues that need to be addressed.
Main comments:
- The expression levels of many genes, including some major TFs (like CEBPa or HNF4) in isolated primary hepatocytes greatly differ from that in normal liver. This is due to the disruption of cell-cell contacts. For this reason, single nuclei sequencing is more reliable and it is the preferred method. It is not indicated how many biological replicates were used and what level of variability was observed between different preparations.
- The regulome studies involved analysis of ENCODE data sets (ChIP-seq), while the RNA-seq data were obtained in the current work. Due to the different source of the data (e.g primary hepatocytes used for ENCODE consortia members and this study) differences are expected. In the present study the cells were FACS-sorted immediately after isolation, while the ones used to produce ENCODE data sets were not subjected to sorting and were also probably cultured. This limits the accuracy of comparisons. Furthermore, the authors should indicate exactly which ENCODE data-sets were used. It is also unusual to observe broad distribution of the ATF3, JUND and EGR1 ChIP-seq reads over the PCK1 gene or the Alb gene (Fig S3). Peaks called by MACS should be indicated. Have the authors verified this distribution, e.g by ChIP-PCR or other means? It is quite unlikely that binding motifs are present all over the gene bodies. Is it possible that these factors interact with elongating RNA Pol-II complexes? What is the situation in other actively transcribing gene bodies?
- The synergism between AP1 and HNF4 is based on RNA and ChIP data in Primary hepatocytes. The main evidence for the synergism are co-binding of the two factors and the regulome profiles in the individual cells. In ICOs where both factors are expressed at high levels ChIP-seq data are not available and the potential binding distribution is estimated by the presence of binding motifs in ATAC-seq positive areas. Considering the concern described in point 2, it is important to obtain ChIPs-seq data in ICOs too. In addition, more direct experimental evidence for the synergism is needed. For example, demonstrating the synergism between HNF4 and some AP1 factors in specific genes by co-transfection experiments.
- Transcriptome comparisons between primary hepatocytes and intrahepatic cholangiocyte organoids (ICO) or ICOs cultured in hepatocyte differentiation medium (DM-ICO) were performed before (Ref. 6). These cells were derived from the same donor. In the current study ICOs were obtained from a biobank, thus they were from different donors. Differences between the expression patterns of primary cells and EM-IOC and DM-IOC organoid cultures are expected even if they derived from the same donor. In Ref.6 it is clearly demonstrated that DM-IOCs closely mimic many, but not all aspects of the liver phenotype. The present paper therefore provides only incremental new knowledge about the usefulness of organoid cultures in general. On the other hand, the scRNA-seq data with cells from the organoids point to the lack of zonation, which is an important new information, not analysed in Ref.6
- In the methods section the description of ICO culture conditions are very epigrammatic. It refers to previously published protocols but also mentions the addition of BMP7 in the first round of culturing without explaining why was this important. It would be useful if the authors describe exactly the culture conditions they used. Were the ICOs from the biobank established under culture conditions described in Ref 6 or by previous protocols?
- The results about ELF3 function are interesting and convincing. This is a novel finding and may worth to perform a global transcriptome analysis and some immunostainings with specific markers in siELF3 cells to further strengthen its regulatory role in cholangiocyte-hepatocyte conversion.
Referees cross-commenting
I fully agree with the comments of Reviewer 2. Addressing them would clearly improve the paper. I also fully agree with Reviewer 3. In my opinion, special emphasis should be put on addressing point 1, 3, 4 and 5. Properly addressing these points would also answer at least partially my concerns (Reviewer 1) described in point 1, 2, 3 and 6. I would recommend the authors focus on the above issues.
Significance
Strengths: combines scRNA-seq with regulome analysis to identify synergism between different classes of transcription factors.
Weaknesses: The data sets come from different sources. Key conclusions drawn from computational analysis are not validated experimentally. Comparing expression patterns of primary cells with those of organoid cultures is risky due to a number of technical limitations.
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Reply to the reviewers
We appreciate the time and effort that you and the reviewers have dedicated to providing your valuable feedback on our manuscript. Those comments are all valuable and very helpful for revising and improving our paper, as well as the importance guiding significance to our researches. We have highlighted the changes in yellow within the manuscript.
*Here is a point-by-point response to the reviewers’ comments and concerns. *
Comments from Reviewer #1 (Evidence, reproducibility and clarity (Required)):
The provided document, titled "Camel Milk Affects Serum Metabolites by Modulating the Intestinal Microflora," is an extensive research paper. My summary covers the first 44 pages of the total 63 pages. The document begins with a standard review commons manuscript notice and provides contact information for the Review Commons office.
The research focuses on the effects of camel milk on serum metabolites and the intestinal microflora. It starts with a detailed introduction to the topic, outlining the crucial role of gut microbes in human health and the influence of various factors like diet, genetics, and environment on these microbes. The paper emphasizes the nutritional richness of camel milk and its potential as a functional food, particularly its impact on gut microbiota and host metabolism.
Initial sections of the paper discuss the research methodologies, including the study's keywords, abstract, and introduction. The abstract highlights the study's significant findings, such as the presence of various beneficial bacteria in sour camel milk, the inter- and intra-species transportation of microbiomes, and the impact of camel milk on the gut microflora and serum metabolites of type 2 diabetic rats.
The introduction further delves into the composition of the human gut microbiota and the shaping factors of the adult gut microbiome. It also examines the role of diet in modulating gut microbiota and the potential health benefits of dairy products, with a particular focus on camel milk.
Subsequent sections present detailed research findings, including the results of microbial composition and source analysis in camel milk, the composition and changes of rat gut microbiota under camel milk regulation, and the effects of camel milk-regulated gut microbiota on metabolism in rats. The research also explores the interspecies transfer of microbes using camel milk as a vector and analyzes the gut microbiota in people consuming camel milk.
The paper further discusses the endophytic flora of camel edible desert plants and their possible influence on the camel's gut microbiota. The discussion section integrates the findings, offering insights into the potential health benefits of camel milk and its probiotic qualities. It also compares the effects of camel milk with other dairy products and discusses its role as a vector for beneficial microbes.
Materials and methods used in the study are detailed towards the end of the summarized portion, describing sample collection and processing, the experimental setup for rats, and data processing and analysis techniques.
Reviewer #1 (Significance (Required)):
The paper continues with detailed research findings, including the microbial composition in camel milk, the impact on the gut microflora of rats and humans, and the serum metabolism effects.
There's a focus on how camel milk, as a vector, can transfer beneficial microbes between species, influencing gut microbiota and host metabolism.
The paper compares the effects of camel milk with other dairy products, emphasizing its unique health benefits and its role in transferring beneficial microbes.
It discusses various bacteria found in camel milk and their potential health benefits.
The research findings extend to understanding how camel milk affects human gut microbiota, with studies on pastoral herders who consume camel or bovine milk.
Author response: We thank you for your approval and constructive and valuable feedback from you and other reviewers.
Comments from Reviewer #2 (Evidence, reproducibility and clarity (Required)):
summary:
The authors introduce a study assessing the bacterial flora of sour fermented camel milk and its capability to introduce beneficial species into consumer's gut. They further tested the potential of its nutrients and species for beneficial effects on type 2 diabetic (t2d) rats. They claim that t2d rats fed with high-dose camel whey reveal a microbiota closer to that of healthy rats rather than that of other t2d rats not receiving the camel whey treatment. Further they claim that this effect is due to the presence of Eubacterium limnetica that was exclusively found in the gut microflora of rats taking camel milk and producing MtcB protein. They conclude that camel milk may have the potential to be functional food.
Overall, I think the approach of looking into camel milk and its microbiota is of broad interest, as it is food consumed traditionally by many tribes and in several countries. However, to me the presentation of the findings, the data and the analysis is often unprecise and confusing.
For example, the MtcB protein they claim to be the mechanism of reducing the risk for t2d in the abstract is mentioned only once in the whole study and there only as a finding of another study (cited). According to my understanding the abstract should contain the main findings of the study, rather than some side-finding from other studies happens to match with the study results. I assume the authors have plenty of results from their sequencing data and metabolomics that they could mention in the abstract.
In the text the authors mention the analysis of the microbial composition and source analysis of camel milk, the analysis of the gut microbiota of young camels, the composition, and changes of rat gut microbiota under the regulation of camel milk, the structure and changes of gut microbiota in people taking camel milk and the analysis of the endophytic flora of camel edible desert plants. And this just quoting the headers in the results section. Why is that not represented/mentioned in the abstract? Instead the authors focus on the t2d rats and the MtcB mechanism they fail to present.
Further the authors are sloppy when it comes to typos and preciseness. For example, in the abstract they talk first about sour camel milk, then whey and then milk again.
I suggest a major restructuring/rewriting and if necessary partial reanalysing of the results and the conclusions.
It would be good to have an overview figure combining the work done, also stating the number of samples for each experiment.
__Author response: __Thank you very much for your nice suggestion on our manuscript, we applied some restructuring to our manuscript and the changes were highlighted in yellow.
Major comments:
1) Please make sure all raw data (sequences and filtering/assembly results) are deposited in public databases, like NCBI, ENA or else.
__Author response: __The corresponding data is available as Mendeley Data, V1, https://doi.org/10. 17632/4w8n8n96tc.1, some datasets with bigger size uploaded failed owing to internet problem. The full version could be offered in other approaches if requested.
2) Please state briefly for each dataset analysed, which sequencing method was used, how many samples were collected and how many were pooled for the sequencing runs:
AmpliAeq, whole metagenome HiSeq, MiSeq?
__Author response: __Sample and dataset information for sequence was supplied in Supplementary Table 9 and 12. Sequencing library was prepared following Illumina library preparation instructions, and sequenced using Illumina Miseq platform at Majorbio Bio-Pharm Technology Co., Ltd. (Shanghai, China) with pair-end (PE) 150 bp reads.
3) Page14 line283:
F082? What is it? A strain, species or a sample?
Please state clearly in the text.
Also please avoid using abbreviations where possible and if you have to use them, please define.
__Author response: __When applying diversity analysis at the specie level, a species annotated as unclassified_g_norank_f_F082 was found abundant in camel feces in Darbancheng.
4) Page14 line307:
"These evidenced that camel milk was a vector transferring microbes from the female camel to their cubs."
Yes, that may be likely, but 16S amplicon-seq cannot provide evidence. Evidence would be strain similarity confirmed by SNP's or the like. So please state that this is speculative or show appropriate evidence.
__Author response: __We completely agree that SNP’s is better evidence for this point and thank you. Microbial diversity analysis was a main part of initial design, and our limited sample couldn’t meet the needs of diversity and SNPs in the same time. There also were reports which used 16S based methods to trace the microbes source(Du et al., 2022; El-Mokdad, 2014; Wang et al., 2018).
5) Page15 line322 ff:
"Besides, using raw milk was not effective in type 2 diabetic rat model, so we chose camel whey and bovine whey as the diet of type 2 diabetic rats in follow-up experiments"
Data/evidence? How is it different from whey on a nutrient perspective, as whey was more effective? Any explanation for this difference? And the bovine whey, what species did it contain? Can they be transferred regarding the processing of whey prior to application?
__Author response: __This is an interesting and valuable question. We prepared raw milk and whey for the pre-test, then directly turned to validate the function of whey. Maybe we will investigate the composition difference in the future. The whey was prepared using the following protocol: Centrifuge fresh milk for 20 mins at 5000 r/min, discard the fat, and precipitate and obtain the middle layer of skim milk. After 20 mins in a 40 ℃ water bath, adjust the pH to 4.6 with 10% glacial acetic acid, and store in a 4°C refrigerator, overnight. Then, the skim milk was centrifuged at 8000 r/min for 20 min, repeated twice, and the middle whey fraction was collected. The centrifuged whey was poured into a petri dish and sealed. It was frozen at -80°C for 12 hours and then pierced with a sterile toothpick on the petri dish and then freeze-dried to get whey powders. A speculation was the preparing progress of whey played an important role in their functional difference. A comprehensive comparison of camel raw milk, camel whey, bovine raw milk, and whey will be an interesting point and we may investigate it shortly.
6) Page17 line366ff:
"Taking the number of microbes involved in this pathway, 8001 species were noted in the high-dose camel whey group, 3447 in the positive drug group, and only 1467 in the diabetics." How many species were present in the rats initially? Was species abundance different in the first place, or did they get lost, or came from the camel whey?
__Author response: __The rats were fed with broad-spectrum antibiotics for 2 weeks, which ensured the same species abundance in the beginning.
7) Page17 line369 ff:
"It indicated that these microbes might resist the high glucose environment of the host through the synthesis and metabolism of their amino acids, and the effect of high-dose camel milk was more effective than that of metformin"
-> How high was the glucose level in the rat gut? Or were there any obvious physiological changes in the t2d model rats that are characteristic for such a high-glucose environment? Please explain.
__Author response: __This is an interesting and critical question. We didn’t measure the glucose level in the rat gut directly because we had to make sure other related characterizations worked properly. Besides, we thought camel milk could regulate microbial community, and further influence the blood sugar level, which was more representative in our sight. Blood sugar level is supplied in Fig.4O and Supplementary Table 11.
8) The resolution/quality of the figures is low and the labelling often small. So not all text is readable.
__Author response: __We adjusted the figures in the manuscript and offered additional independent picture files. Additionally, it seemed caused by the PDF merge progress, please check the pictures in .docx or .png files for details.
9) Page19 line400 ff:
What serum metabolites were analysed and why? Please write an intro-sentence to make it easier for the reader.
Please write more precise what methods were used. Maybe I missed it, but I didn't find it in the methods part as well (Page40/41).
__Author response: __The rats fed high-dose camel whey or metformin showed similar improvement in serum metabolite imbalance and were closer to normal. Caproylcarnitine, taurodeoxycholic acid, acetylcarnitine, creatinine, linoleic acid, and tridecanoic acid were detected as upregulated; 2-deoxyuridine, cyclohexylamine, L-pipecolic acid, LysoPC(18:0), uracil, caprylic acid, cholesterol sulfate, L-citrulline, pelargonic acid, and phenol downregulated. Carnitine supplementation, due to its key role in lipid metabolism and antioxidant effects, may effectively manage Type 2 Diabetes by addressing fatty acid metabolism dysregulation and oxidative stress(Bene, Hadzsiev, & Melegh, 2018). Studies have shown that taurodeoxycholic acid can enhance the effect of insulin and reduce blood sugar levels by regulating endoplasmic reticulum stress, and have potential in the treatment of diabetes(Xing, Zhou, Wang, & Xu, 2023). Low serum creatinine is associated with the development of T2D(Song, Hong, Sung, & Lee, 2022). Increased linoleic acid consumption was recommended for the prevention of T2D(Henderson, Crofts, & Schofield, 2018). The uridine is phosphorylated into uracil, which is converted to 2-deoxyuridine. Then 2-deoxyuridine is further converted to thymine with thymidine phosphorylase, the expression of thymidine phosphorylase was lost or considerably reduced when the organism suffered nephropathy and the high concentration of thymidine is a cause of DNA impairment, which is related to diabetes and diabetic nephropathy(Spinazzola et al., 2002; Szabo et al.; Xia, Hu, Liang, Zou, Wang, & Luo, 2010). L-Pipecolic acid are associated with higher incidence of T2D(Razquin et al., 2019). A research showed LysoPC(16:0) and (18:0) may mediated a fast progression of diabetic kidney disease(Yoshioka et al., 2022). Cholesterol sulfate is the most abundant known sterol sulfate in human plasma, and it plays a significant role in the control of glucose metabolism, which contribute to the pathogenesis of insulin resistance and the resultant development of diabetes(Shi et al., 2014; Zhang et al., 2022). L-citrulline supplementation might improve glucose homeostasis, some lipid factors and inflammatory markers in overweight and obese patients with T2D(Azizi, Mahdavi, Mobasseri, Aliasgharzadeh, Abbaszadeh, & Ebrahimi-Mameghani, 2021). T2D mellitus is associated with increased total plasma free fatty acid and modulating its concentration is the mechanism of some fibrates and statins drugs(I. S. Sobczak, A. Blindauer, & J. Stewart, 2019). Most of these metabolites have been reported as causes of T2D or consequences of T2D progress, some have been designed as therapeutic target.
The serum metabolites were carried out using Agilent 1290 Infinity UHPLC system equipped with a HILIC column. The mobile phase of the optimized method consisted of (A) water with 25 mM ammonium acetate and 25 mM ammonia; and (B) acetonitrile (ACN). The following gradient elution was used: 5% A at 0-1min; 5-35% A at 1-14 min; 35-60% A at 14-16 min; 60% A at 16-18 min ; 60-5% A at 18-18.1 min and 5% A at 18.1-23 min. The flow rate was 0.3 mL/min, injection volume 2 μL, and column temperature was 25 ℃. Triple TOF 5600 mass spectrometer was applied for mass spectrometer analysis. The condition was used as following: Ion Source Gas1:60,Ion Source Gas2:60,Curtain gas:30,source temperature:600℃,IonSapary Voltage Floating ± 5500 V. TOF MS scan m/z range:60-1000 Da,product ion scan m/z range:25-1000 Da,TOF MS scan accumulation time 0.20 s/spectra, product ion scan accumulation time 0.05 s/spectra.MS/MS was gathered by information dependent acquisition (IDA) using high sensitivity mode, Declustering potential:±60 V, Collision Energy:35±15 eV, and IDA was set as Exclude isotope within 4 Da, Candidate ions to monito per cycle: 6. The methods part was complemented.
Minor comments:
1) Page1, line56-58 ff
Please phrase more clearly:
"This study specified that the transportation of microbiome happened both intra- and inter-species and played a principal role in the formation of progeny gut microflora."
While the content is mostly comprehensible, there is a need for rephrasing and correction of language also in the following text.
__Author response: __As suggested by the reviewer, we have rephrased and modified the abstract part.
2) Page14 line300 ff:
There is no need to show the OTU numbers in the text, please provide your results as a table in the supplements and refer to it in the text.
Author response: We deleted OTU numbers in the manuscript and added the corresponding table in supplementary file.
3) Page15 line328: Please check for typos, it is Shannon index, not Shanno.
__Author response: __The corresponding correction was applied in the manuscript.
4) Page16 line334:
Please mention the number, age and sex of the rats used and how many groups you had in your experiments.
__Author response: __SPF-grade male rats weighing 180-220 g were used for our related experiments. The detailed information is available in Supplementary Material (Supplementary Table 11-13).
5) The headlines should logically structure the paper:
For example, the authors have two very similar sections in the results part: "Composition and changes of rat gut microbiota under the regulation of camel milk" and "Analysis of the composition of gut microbiota in rats". Those can be combined or stated more concise.
Also, other headlines improvement to make it easier for the reader to follow.
__Author response: __We adjusted this part in the manuscript according to the reviewer’s suggestion.
Reviewer #2 (Significance (Required)):
I do think the study is of broad interest and relevance. However, the presentation of the analysis and data needs major revision. Especially it is lacking clarity on what was done for which samples and how the authors draw their conclusions. Also, I think that abstract and main text have a different focus. I would suggest to the authors to concentrate on their findings in abstract and text and state precisely what was done and what they found.
__Author response: __Thank you very much for your recognition of our manuscript.
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Referee #2
Evidence, reproducibility and clarity
Summary:
The authors introduce a study assessing the bacterial flora of sour fermented camel milk and its capability to introduce beneficial species into consumer's gut. They further tested the potential of its nutrients and species for beneficial effects on type 2 diabetic (t2d) rats. They claim that t2d rats fed with high-dose camel whey reveal a microbiota closer to that of healthy rats rather than that of other t2d rats not receiving the camel whey treatment. Further they claim that this effect is due to the presence of Eubacterium limnetica that was exclusively found in the gut microflora of rats taking camel milk and producing MtcB protein. They conclude that camel milk may have the potential to be functional food.
Overall, I think the approach of looking into camel milk and its microbiota is of broad interest, as it is food consumed traditionally by many tribes and in several countries. However, to me the presentation of the findings, the data and the analysis is often unprecise and confusing. For example, the MtcB protein they claim to be the mechanism of reducing the risk for t2d in the abstract is mentioned only once in the whole study and there only as a finding of another study (cited). According to my understanding the abstract should contain the main findings of the study, rather than some side-finding from other studies happens to match with the study results. I assume the authors have plenty of results from their sequencing data and metabolomics that they could mention in the abstract. In the text the authors mention the analysis of the microbial composition and source analysis of camel milk, the analysis of the gut microbiota of young camels, the composition, and changes of rat gut microbiota under the regulation of camel milk, the structure and changes of gut microbiota in people taking camel milk and the analysis of the endophytic flora of camel edible desert plants. And this just quoting the headers in the results section. Why is that not represented/mentioned in the abstract? Instead the authors focus on the t2d rats and the MtcB mechanism they fail to present. Further the authors are sloppy when it comes to typos and preciseness. For example, in the abstract they talk first about sour camel milk, then whey and then milk again.
I suggest a major restructuring/rewriting and if necessary partial reanalysing of the results and the conclusions.
It would be good to have an overview figure combining the work done, also stating the number of samples for each experiment.
Major comments:
- Please make sure all raw data (sequences and filtering/assembly results) are deposited in public databases, like NCBI, ENA or else.
- Please state briefly for each dataset analysed, which sequencing method was used, how many samples were collected and how many were pooled for the sequencing runs: AmpliAeq, whole metagenome HiSeq, MiSeq?
- Page14 line283: F082? What is it? A strain, species or a sample? Please state clearly in the text. Also please avoid using abbreviations where possible and if you have to use them, please define.
- Page14 line307: "These evidenced that camel milk was a vector transferring microbes from the female camel to their cubs." Yes, that may be likely, but 16S amplicon-seq cannot provide evidence. Evidence would be strain similarity confirmed by SNP's or the like. So please state that this is speculative or show appropriate evidence.
- Page15 line322 ff: "Besides, using raw milk was not effective in type 2 diabetic rat model, so we chose camel whey and bovine whey as the diet of type 2 diabetic rats in follow-up experiments" Data/evidence? How is it different from whey on a nutrient perspective, as whey was more effective? Any explanation for this difference? And the bovine whey, what species did it contain? Can they be transferred regarding the processing of whey prior to application?
- Page17 line366ff: "Taking the number of microbes involved in this pathway, 8001 species were noted in the high-dose camel whey group, 3447 in the positive drug group, and only 1467 in the diabetics." How many species were present in the rats initially? Was species abundance different in the first place, or did they get lost, or came from the camel whey?
- Page17 line369 ff: "It indicated that these microbes might resist the high glucose environment of the host through the synthesis and metabolism of their amino acids, and the effect of high-dose camel milk was more effective than that of metformin"
- How high was the glucose level in the rat gut? Or were there any obvious physiological changes in the t2d model rats that are characteristic for such a high-glucose environment? Please explain.
- The resolution/quality of the figures is low and the labelling often small. So not all text is readable.
- Page19 line400 ff: What serum metabolites were analysed and why? Please write an intro-sentence to make it easier for the reader. Please write more precise what methods were used. Maybe I missed it, but I didn't find it in the methods part as well (Page40/41).
Minor comments:
- Page1, line56-58 ff Please phrase more clearly: "This study specified that the transportation of microbiome happened both intra- and inter-species and played a principal role in the formation of progeny gut microflora." While the content is mostly comprehensible, there is a need for rephrasing and correction of language also in the following text.
- Page14 line300 ff: There is no need to show the OTU numbers in the text, please provide your results as a table in the supplements and refer to it in the text.
- Page15 line328: Please check for typos, it is Shannon index, not Shanno.
- Page16 line334: Please mention the number, age and sex of the rats used and how many groups you had in your experiments.
- The headlines should logically structure the paper: For example, the authors have two very similar sections in the results part: "Composition and changes of rat gut microbiota under the regulation of camel milk" and "Analysis of the composition of gut microbiota in rats". Those can be combined or stated more concise. Also, other headlines improvement to make it easier for the reader to follow.
Significance
I do think the the study is of broad interest and relevance. However, the presentation of the analysis and data needs major revision. Especially it is lacking clarity on what was done for which samples and how the authors draw their conclusions. Also I think that abstract and main text have a different focus. I would suggest to the authors to concentrate on their findings in abstract and text and state precisely what was done and what they found.
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Referee #1
Evidence, reproducibility and clarity
The provided document, titled "Camel Milk Affects Serum Metabolites by Modulating the Intestinal Microflora," is an extensive research paper. My summary covers the first 44 pages of the total 63 pages. The document begins with a standard review commons manuscript notice and provides contact information for the Review Commons office.
The research focuses on the effects of camel milk on serum metabolites and the intestinal microflora. It starts with a detailed introduction to the topic, outlining the crucial role of gut microbes in human health and the influence of various factors like diet, genetics, and environment on these microbes. The paper emphasizes the nutritional richness of camel milk and its potential as a functional food, particularly its impact on gut microbiota and host metabolism.
Initial sections of the paper discuss the research methodologies, including the study's keywords, abstract, and introduction. The abstract highlights the study's significant findings, such as the presence of various beneficial bacteria in sour camel milk, the inter- and intra-species transportation of microbiomes, and the impact of camel milk on the gut microflora and serum metabolites of type 2 diabetic rats.
The introduction further delves into the composition of the human gut microbiota and the shaping factors of the adult gut microbiome. It also examines the role of diet in modulating gut microbiota and the potential health benefits of dairy products, with a particular focus on camel milk.
Subsequent sections present detailed research findings, including the results of microbial composition and source analysis in camel milk, the composition and changes of rat gut microbiota under camel milk regulation, and the effects of camel milk-regulated gut microbiota on metabolism in rats. The research also explores the interspecies transfer of microbes using camel milk as a vector and analyzes the gut microbiota in people consuming camel milk.
The paper further discusses the endophytic flora of camel edible desert plants and their possible influence on the camel's gut microbiota. The discussion section integrates the findings, offering insights into the potential health benefits of camel milk and its probiotic qualities. It also compares the effects of camel milk with other dairy products and discusses its role as a vector for beneficial microbes.
Materials and methods used in the study are detailed towards the end of the summarized portion, describing sample collection and processing, the experimental setup for rats, and data processing and analysis techniques.
Significance
The paper continues with detailed research findings, including the microbial composition in camel milk, the impact on the gut microflora of rats and humans, and the serum metabolism effects. There's a focus on how camel milk, as a vector, can transfer beneficial microbes between species, influencing gut microbiota and host metabolism. The paper compares the effects of camel milk with other dairy products, emphasizing its unique health benefits and its role in transferring beneficial microbes. It discusses various bacteria found in camel milk and their potential health benefits. The research findings extend to understanding how camel milk affects human gut microbiota, with studies on pastoral herders who consume camel or bovine milk.
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www.biorxiv.org www.biorxiv.org
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Reply to the reviewers
Reviewer #1 (Evidence, reproducibility and clarity (Required)):
DBF4 and DRF1 knockout cells were generated and used to separate DBF4- and CDC7-dependent from DRF1- and CDC7-dependent activities. DBF4- and CDC7-dependent activities at replication forks were independent of DRF1. These include the replication timing pattern, replication fork velocity, DNA damage signaling. DBF4 is required to recruit CDC7 to active replication forks. The study is in large part exceptional.
The inclusion of quantitation for a modest bandshift on CDC7 in figure 2 (30% vs 50% reduced) is not justified given the abundance of the main band and our knowledge of the lack of linearity of western blot quantitation. This should be removed.
We thank the reviewer for evaluating our manuscript and for the positive feedback.
In the revised manuscript we have removed the quantification of the bandshift related to CDC7 autophosphorylation in mitotic cells which was reported in Figure 1E. We recognise that the quantification may not be accurate although performed using semiquantitative near-infrared scanning technology. Importantly the experiment was performed three times with almost identical results.
The only significant weakness in the paper is the explanation of the replication timing analyses in Figure 3. I don't understand what the differences between the plots equate to in terms of timing. I understand the replication of these regions that diverge is either early or late, but their were only two fractions of cells - 2N-3N and 3N-4N (the cells are "normal"). If this is the case, isn't the readout binary? a sequence either replicates in S phase between 2N and 3N or in S phase between 3N and 4N. Why are the differences so small? Are they only evident in a small population of cells? If that is the case, then what does the difference really mean? I think the description of these data needs to be precise.
The replication timing experiments were performed with a well-established and reliable protocol (Ryba et al., 2011, https://doi.org/10.1038/nprot.2011.328). Asynchronous cells are labelled with a short pulse of BrdU, and sorted in two fractions, early and late S-phase, as described in Hiratani et al., 2008, Ryba et al., 2010, Hadjadj et al, 2016 and 2020 (https://doi.org/10.1371/journal.pbio.0060245) (https://doi.org/10.1101/gr.099655.109, https://doi.org/10.1016/j.gdata.2016.07.003, https://doi.org/10.1093/nargab/lqaa045).
This method does not take into account the variation in the DNA copy number (2N vs 4N) between replicated and non-replicated parts of the genome (S/G1 ratio) as in Siefert et al., 2017 (https://doi.org/10.1101/gr.218602.116).
The profiles depict the average replication timing of a population of 20,000,000 cells; thus, the readout is not binary.
Replication timing profiles display the log ratio between early and late replicated fractions along the chromosome. Early replicated regions show positive log ratios and late replicated regions show negative ratios. The differential analysis performed with the START-R suite allows the comparison of the profiles (Ctrl vs either CDC7i-treated or DBF4-deficient cells). The genomic regions with altered timing are shown in green or in purple below the profiles, showing advanced and delayed regions, respectively.
Importantly, the differences in replication timing are expressed with log ratio, that explains why the profiles are varying from -2 (very late replicating regions) and +2 (very early replicating regions). The differences we observed in Figure 3 are representative of two experiments, each composed of two technical replicates that are highly reproducible.
To better describe the data, we have modified the text in the results section with the words in bold, as below: “These two neo-synthesized DNA fractions were then hybridised on human whole genome microarrays, as previously described. The log ratio between early and late replicated fractions was calculated and visualised for the whole genome.” We also changed the labelling of the replication profiles in Figure 3 and former Figure S3 (now Figure S4) by adding Log2 (Early/Late) to intensity and added two new sentences to the figure legend 3.“____Replication timing profiles display the log ratio between early and late replicated fractions along the chromosome. Positive log ratios correspond to early replicated regions whereas negative ratios correspond to late replicated regions.”
Reviewer #1 (Significance (Required)):
I think this paper is a significant advance that should be published. CDC7 is a critical kinase and identifying its co-factor at the replication fork is important both for our understanding of mechanisms of DNA replication and the impact of CDC7 kinase inhibitors in the clinic. I think the majority of the experiments are well designed and the results are unambiguous and precisely described.
Reviewer #2 (Evidence, reproducibility and clarity (Required)):
CDC7 is a master cell cycle kinase with essential functions in DNA replication and important roles in the DNA damage response. For its functions, CDC7 relies on a regulatory factor, DBF4, which is essential in many species but not in human cells as a consequence of the presence of a second DBF4-related factor, DRF1. In this work, Göder and colleagues study the relative relevance of these regulatory proteins in CDC7 roles. Their study reveals DBF4 as the major regulatory subunit both in DNA replication, DNA damage checkpoint and fork dynamics. The objective of the study is highly relevant to understand an essential cell cycle kinase with potential applications in cancer therapies, the experiments are well performed and the conclusions are "in principle" sound.
We thank this reviewer for the time and attention in evaluating the manuscript, for the positive feedback and for indicating key points for improvement and discussion.
The major handicap of the study is the absence of western blots showing the elimination of DBF4 and DRF1 in the edited cell lines due to the lack of specific antibodies. The authors have generated homozygous mutations that lead to premature stop codons behind critical CDC7 domains. However, as they mention, it is not possible to fully exclude some proteins arising from internal start sites or exon skipping events with residual (functional or altered, and not necessarily residual) activity. This is not unexpected, especially for essential proteins. This would not be a major handicap if the study were focused in a specific factor because it would only question the impact of but not the affected function, but it aims to compare the relative effect of two defective genes. In this case, it is essential to confirm that both genes are eliminated, at least to the same degree.
We agree with the reviewer that it would be valuable to confirm the effect of the mutations by immunoblotting.
Over the years we have had multiple attempts at generating sensitive antibodies against both DBF4 and DRF1, using recombinant proteins and synthetic peptides. We also tested several commercially available anti-DBF4 and anti-DRF1 antibodies. While often we were able to detect overexpressed proteins, the detection of endogenous levels has been particularly challenging especially in non-transformed cells, such MCF10A.
Nevertheless, with an anti-DBF4 serum we obtained from the Diffley lab, which was generated against the C-terminus fragment of hDBF4, we managed to detect endogenous full length DBF4 in parental but not in the DBF4-KO cells (this blot is now included as supplementary Fig S1B). Even with this reagent the detection levels are low and multiple non-specific immunoreactive bands are present, making the detection of DBF4 particularly challenging across the experiments. Interestingly, while DBF4 is no longer detectable in DBF4-11, one the two clones used in this work , we detect a new immunoreactive band of approximately 55kDa in the other clone DBF4-30. We reckon that this may be the result of mRNA translation from the next downstream methionine. In this case this aberrant protein would lack the N domain and most of the M domain, involved in CDC7 binding and activation, and thus this fragment is very likely not functional.
Importantly, most results in this study were obtained using both DBF4-11 and DBF4-30 clones with indistinguishable results. Only the replication timing experiments were done using a single clone DBF4-11, in which DBF4 protein is not detected.
We had less success with the direct detection of DRF1. As also suggested by reviewer #3, to screen the clones after genome editing, we originally performed IP-western experiments. We used an anti-DRF1 mAb and unrelated IgG for the immunoprecipitations and an anti-CDC7 antibody as a probe in western blotting. We detected an immunoreactive band above the background at the expected molecular weight for CDC7 when the immunoprecipitation was performed with extracts from parental cells (as well as in a clone obtained with a different sgRNA, targeting DRF1 Exon1 and never used in this study) but not when the immunoprecipitation was performed with extracts from the DRF1- 5 and DRF1-7 clones used in the study. These original co-IPs are credible although not particularly pretty and importantly the result was confirmed in a more convincing experiment in the DRF1-5 clone.
These new data are now included in the resubmission in Figure S1. So, while the detection of the CDC7 regulatory subunits still remains particularly difficult, we can now provide evidence that their expression is altered in the engineered cell lines used in the study.
The computational analysis in Figure 1C is consistent with the major conclusion about the primary regulatory role of DBF4 in replication, but it is insufficient to validate the specific phenotypes addressed in the study.
The figure reports the effects of targeting single genes with multiple sgRNA (4 to 8 according to the library used) on proliferation rate/fitness measured after multiple days in more than 1000 screens across many different human cell types. Loss of fitness can be due either to a direct problem with DNA replication or with other cellular processes.
We agree with the reviewer that the analysis in Fig 1C is consistent with the phenotypes shown in the study. Particularly it is consistent with the lack of a major defect of DRF1-deficient cells in DNA replication, and it strongly indicates an essential role for CDC7 which was somehow challenged by Suski and co-workers (see also below).
Indeed, there is a result that is hard to understand if the edited cell lines are defective in the expression of the regulators, specially DRF1. Figure S2D-E shows no synergistic defect in DNA synthesis when the second regulator is knock down with specific siRNAs, not even DRF1 defective cell lines treated with a siDBF4 that reduces its expression 10 times. Also, it is not clear why the defects, specially in DBF4-defective cell lines, are less severe than in cells treated with an inhibitor that causes a partial inhibition of CDC7. If it is due to the expression of DRF4, a siRNA against DRF4 should cause more severe defects.
Yes, we did not detect synergy or additive effect on the rate of DNA replication when targeting both DBF4 and DRF1 by multiple approaches. This was also for us an unexpected result, that we examined to the best of our capabilities.
The lack of the expected synergy in the replication assays could be explained in multiple ways and could be of biological or technical nature such as 1) residual low levels of DBF4/DRF1 proteins remaining in the cells upon either CRISPR/Cas9 or siRNA targeting, 2) alternative mechanisms of kinase activation by a different, yet unidentified protein, 3) minimal residual enzymatic activity of hCdc7 kinase not requiring an activating subunit.
We performed further computational analysis using the dataset of the DepMap project, assessing if the effect of targeting DBF4 on fitness may be dependent on the levels of DRF1 expression. In several instances, when dealing with paralogues the gene effect of knocking out one of the paralogues directly correlates with the expression levels of the second, a phenomenon known as paralogue buffering (De Kegel et al. 2019 https://doi.org/10.1371/journal.pgen.1008466 ).
In the case of DBF4 and DRF1, this correlation is minimal (plot below: X and Y axes are DRF1 expression levels and DBF4 gene effect respectively, Pearson's correlation = 0.12) so that there are ~ 470 other genes whose expression is more correlated with DBF4 essentiality. Furthermore, by stratifying cell lines according to whether DBF4 was essential or not and then looking at DBF4B (DRF1) expression, we failed to see significant association (graph below).
Thus, this analysis reinforces the idea that if cooperation between DBF4 and DRF1 exists, it is particularly difficult to demonstrate. To date the interplay between DBF4 and DRF1 is only indicated by the partial impairment on MCM2 phosphorylation and CDC7 autophosphorylation observed in the individual KOs and by the fact that we were unable to obtaining viable double KO mutant clones. We recognise that the latter is a negative result and double KO may be generated in other cellular models or with different strategies.
We are happy to include the above computational analysis in a revised manuscript and to expand the discussion on the essentiality of CDC7, DBF4 and DRF1.
The effects of directly inhibiting CDC7 with 10 microM XL413 (concentration used in this study) are indeed stronger than DBF4 KO / depletion on both DNA synthesis (Fig 2A-B) and MCM2 phosphorylation (Fig 4A and Fig 5A).
We and others have previously shown that CDC7 inhibition by XL413 causes a dose dependent decrease in MCM2 phosphorylation and DNA synthesis. Importantly in the experiments where XL413 was titrated on MCF10A cells from 0.3 microM to 80 microM, we demonstrated that these parameters are uncoupled and that doses that are ~20-fold higher are required to cause a strong impediment of DNA synthesis compared to the dose required to cause full MCM2 dephosphorylation (Rainey et al. 2017 https://doi.org/10.1021/acschembio.7b00117 ).
DBF4 deficiency only partially affects MCM2 phosphorylation thus it is comparable to very low doses of XL413, that we can estimate to be in the range between 1 and 2 microM.
Minor points
- Title in Pag 12. "DBF4 mediates the majority of CDC7 functions in the replication stress response". In this section the authors address only the role of CDC7 in checkpoint signalling but not in other processes related to the replication stress response.
We agree and we have modified the title of this section accordingly.
- Figure 2. "EdU incorporation in late S-phase/ per cell" is clearer
We have modified the label of this figure.
- Right panels in Figures 3A and 3B are duplicated
We sincerely apologise for the mistake occurred while assembling the figure. The figure has been corrected, and shows that the changes in the replication timing with the CDC7i or with DBF4-KO are indeed similar but not identical.
**Referees cross-commenting**
I am aware of the difficulty to sort out the detection problem, a major handicap of the work. Immunoprecipitation as suggested by rev. 3 might be an interesting possibility. The results should be published, in any case, as they are well performed and try to answer a relevant question. But, if finally the authors fail to detect the proteins, they should make clear in the paper the limitation of their conclusions by the possibility that the expression of the regulators is not completely eliminated or could be altered. Indeed, the apparent contradiction with Suski's results raised by Rev 3 might be discussed in this context.
We appreciate the reviewer’s recognition of the technical problems we have encountered. We are glad that we now are in a position to provide evidence of impairment of DBF4 and DRF1 expression in the engineered cells (discussed above and reported in new Figure S1 and S2).
Also, it is important to explain the lack of synergism when combining the edited mutations with siRNAs.
In a revised manuscript we will explain the potential reasons why lack of synergism either doesn’t exist or is not observed, as discussed above.
Reviewer #2 (Significance (Required)):
In summary, the work is relevant and interesting, but the lack of controls about the effect of the edition rises important concerns about the conclusions. It is evident from the acknowledgment section that the authors have tried without success to generate specific antibodies. An alternative possibility would be 1) to get similar results with at least two clones addressing different exons (actually, only one clone was used for DRF1 in most cases) and 2) show synergistic effects for the more important phenotypes in edited cells transfected with efficient siRNAs. This is particularly important for DRF1-defective cells, which show no phenotypes except for an increase in micronuclei. If DBF4 is not essential because the complementary activity of DRF1, impairment of DBF4 expression with siRNAs in DRF1 deficient cells should cause synergistic defects at least in DNA replication and cell viability.
We hope we have satisfactory addressed this reviewer’s comments, by providing experimental evidence of the impairment of DBF4 and DRF1 expression/function in the engineered cells and several points for discussion addressing the lack of obvious synergy between DBF4 and DRF1.
Reviewer #3 (Evidence, reproducibility and clarity (Required)):
Summary Assembly of the CMG helicase during DNA replication initiation is regulated by the DBF-Dependent Kinase known as CDC7 (or DDK), which also plays roles at DNA replication forks during elongation. In vertebrates, DDK has two regulatory subunits called DBF4 and DRF1. Until now, the division of labour between these two activators of CDC7 was poorly understood in mammalian cells. To address this issue, the authors used CRISPR-Cas9 to edit the DBF4 and DRF1 genes in immortalised human breast cells (MCF10A), thereby truncating key domains of the DBF4 and DRF1 proteins. The DBF4-deficient and DRF1-deficient lines are viable, whereas the double mutant was unobtainable and likely inviable, as reported previously by the authors for knockout of CDC7 in MCF10A cells. The authors compare the DBF4-deficient and DRF1-deficient lines with the CDC7 inhibitor XL413, providing evidence that DBF4 has the major role in supporting CDC7 activity in MCF10A cells compared to DRF1, in terms of DNA replication, origin firing, fork progression, and checkpoint activation. Curiously, DRF1 appears to be more important in preventing the formation of micronuclei - another phenotype seen upon inhibition of CDC7 kinase activity.
Major comments: The data are of high quality and the key conclusions are convincing, although it is unfortunate that the authors were not able to monitor the level of DBF4 and DRF1 by immunoblotting to validate their edited cell lines. The authors previously reported using immunoprecipitation of CDC7, DBF4 and DRF1 (Tenca et al, 2007, 10.1074/jbc.M604457200) to monitor DDK subunits in HeLa cells, which would presumably have been helpful here in MCF10A cells. Nevertheless, the DNA sequence of the edited clones indicates frameshift mutations that lead to premature STOP codons, and the various phenotypes reported in this manuscript are consistent with loss of DBF4 / DRF1 function as described.
We thank the reviewer the time an effort in carefully assessing the manuscript, and with his/her positive assessment.
We have now included experimental evidence indicating that DBF4 expression is deficient in the DBF4 KO cells used in this study and that the interaction with DRF1 and CDC7 is deficient in the DRF1-KO cells using the same Co-IP strategy previously reported in Hela cells. Please see also the response to reviewer #2 to the same point.
Minor comments: 1. The authors should discuss their data in the context of the recent study by Suski et al (https://doi.org/10.1038/s41586-022-04698). The latter study reported that knockout of DBF4 in mouse fibroblasts impairs proliferation but is not lethal, in agreement with the present manuscript, but Suski et al also argue that CDC7 is dispensable for DNA replication in mammalian cells due to redundancy with CDK1.
The requirement for CDC7 kinase activity for genome duplication in mammalian cells has become a contentious point of debate. CRISPR screens in more than 1000 cell lines indicate that CDC7 is a core essential gene required for proliferation (DepMap.org). Clearly human cells can clearly withstand reduced CDC7 activity, and several proteins contribute both positively and negatively to the effectiveness of CDC7 inhibition in DNA replication and cell proliferation e.g. RIF1 depletion, ATR inhibition, PTBP1 mutation. (Hiraga et al. 2017 https://doi.org/10.15252/embr.201641983 ; Rainey et al. 2020 https://doi.org/10.1016/j.celrep.2020.108096 : Jones et al. 2021 https://doi.org/10.1016/j.molcel.2021.01.004 ; Göder et al. 2023 https://doi.org/10.1016/j.isci.2023.106951).
Specifically CDK1-phosphporylatyon of RIF1 was shown to disrupt RIF1/PP1 interaction and PP1’s ability to counteract CDC7-dependnet phosphorylation of the MCM complex (Moiseeva et al. 2019 https://doi.org/10.1073/pnas.1903418116 ; Jones et al. 2021 https://doi.org/10.1016/j.molcel.2021.01.004). Thus increased CDK1 activity can be helpful in dealing with low levels of CDC7 kinase.
Suski et al argue that CDC7 is dispensable for DNA replication in human cells based on acute degradation of CDC7 or by its inhibition using an “Shokat type” analogue sensitive CDC7 allele. However, another study showed that DNA replication is not completed using the same approach and the same analogue sensitive allele (Jones et al. 2021 https://doi.org/10.1016/j.molcel.2021.01.004). In mouse embryonic stem cells, the Masai group had previously shown that CRE-Lox mediated inactivation of mDBF4 leads to a strong decrease of DNA synthesis and that mDBF4, like mCDC7 is essential for cell ES cells viability (Kim et al, 2002 https://doi.org/10.1093/emboj/21.9.2168 and Yamashita 2005 https://doi.org/10.1111/j.1365-2443.2005.00857.x ). Intriguingly mDRF1 has yet not been identified nor characterised. In our opinion, the simplest explanation to reconciliate the different reports is that human and mouse CDC7 are indeed required for DNA replication and for cell proliferation, but the phenotype of the most severe effects of its inhibition requires the complete loss of function of the kinase and may be delayed in time. We are happy to add these considerations in the discussion section of the revised manuscript.
- Some discussion of the increased frequency of micronuclei in DRF1-deficient cells compared to DBF4-deficient lines would be useful (c.f. Figure 1F-G).
In the discussion we have suggested that the increase of micronucleated cells in the DRF1 deficient clones “could be consistent with a (DRF1) specific but not yet identified function in chromosome segregation, in the fine-tuning of DNA replication or the DNA repair process”. Of interest, CDC7 kinase was recently involved in modulating ATR function in cytokinetic abscission, and impairment of this process can lead to increase frequency of micro nucleated cells (Luessing et al. 2023 https://doi.org/10.1016/j.isci.2022.104536 ). It is possible that this new role of CDC7 could be dependent on DRF1, an hypothesis at present purely speculative, that we will be testing in the future. We are happy to add these considerations to the discussion section of the revised manuscript.
- It would be helpful to present actual p values in Figure 2, rather than asterisks.
Asterisks report the range in which the p values fall into, which currently is specified in the legend. These can be substituted with actual numbers in the figures, and we will comply with the requirement of the journal in which the manuscript will be accepted.
Reviewer #3 (Significance (Required)):
The main strength of this manuscript is the exploration of the division of labour between DBF4 and DRF1 in human cells, regarding the roles of CDC7 kinase during DNA replication initiation, fork progression and checkpoint control. A limitation would be the failure to monitor the level of DBF4 and DRF1 in the CRISPR-edited cell lines, whilst it is also possible that the relative roles of DBF4 and DRF1 might vary in different cell types.
Previous studies of DNA replication in Xenopus egg extracts (e.g. Takahashi et al, 2005: doi: 10.1101/gad.1339805) indicated that DRF1 is the dominant activator of CDC7. In contrast, past work from the current authors (Tenca et al, 2007, 10.1074/jbc.M604457200) indicated that DBF4 is the major partner of CDC7 in human HeLa cells, at least at the level of promoting MCM2 phosphorylation (the only parameter monitored in the previous study, whereas the present manuscript goes much deeper into the various roles of CDC7 in DNA replication control and focusses on the role of CDC7 at replication forks and in checkpoint control).
This study should be of interest to those studying chromosome replication, checkpoints and genome integrity. It should also interest those with a more clinical perspective, due to the potential importance of CDC7 kinase inhibitors as anti-cancer agents.
My own expertise is in the field of chromosome replication.
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Referee #3
Evidence, reproducibility and clarity
Summary
Assembly of the CMG helicase during DNA replication initiation is regulated by the DBF-Dependent Kinase known as CDC7 (or DDK), which also plays roles at DNA replication forks during elongation. In vertebrates, DDK has two regulatory subunits called DBF4 and DRF1. Until now, the division of labour between these two activators of CDC7 was poorly understood in mammalian cells. To address this issue, the authors used CRISPR-Cas9 to edit the DBF4 and DRF1 genes in immortalised human breast cells (MCF10A), thereby truncating key domains of the DBF4 and DRF1 proteins. The DBF4-deficient and DRF1-deficient lines are viable, whereas the double mutant was unobtainable and likely inviable, as reported previously by the authors for knockout of CDC7 in MCF10A cells. The authors compare the DBF4-deficient and DRF1-deficient lines with the CDC7 inhibitor XL413, providing evidence that DBF4 has the major role in supporting CDC7 activity in MCF10A cells compared to DRF1, in terms of DNA replication, origin firing, fork progression, and checkpoint activation. Curiously, DRF1 appears to be more important in preventing the formation of micronuclei - another phenotype seen upon inhibition of CDC7 kinase activity.
Major comments:
The data are of high quality and the key conclusions are convincing, although it is unfortunate that the authors were not able to monitor the level of DBF4 and DRF1 by immunoblotting to validate their edited cell lines. The authors previously reported using immunoprecipitation of CDC7, DBF4 and DRF1 (Tenca et al, 2007, 10.1074/jbc.M604457200) to monitor DDK subunits in HeLa cells, which would presumably have been helpful here in MCF10A cells. Nevertheless, the DNA sequence of the edited clones indicates frameshift mutations that lead to premature STOP codons, and the various phenotypes reported in this manuscript are consistent with loss of DBF4 / DRF1 function as described.
Minor comments:
- The authors should discuss their data in the context of the recent study by Suski et al (https://doi.org/10.1038/s41586-022-04698). The latter study reported that knockout of DBF4 in mouse fibroblasts impairs proliferation but is not lethal, in agreement with the present manuscript, but Suski et al also argue that CDC7 is dispensable for DNA replication in mammalian cells due to redundancy with CDK1.
- Some discussion of the increased frequency of micronuclei in DRF1-deficient cells compared to DBF4-deficient lines would be useful (c.f. Figure 1F-G).
- It would be helpful to present actual p values in Figure 2, rather than asterisks.
Significance
The main strength of this manuscript is the exploration of the division of labour between DBF4 and DRF1 in human cells, regarding the roles of CDC7 kinase during DNA replication initiation, fork progression and checkpoint control. A limitation would be the failure to monitor the level of DBF4 and DRF1 in the CRISPR-edited cell lines, whilst it is also possible that the relative roles of DBF4 and DRF1 might vary in different cell types.
Previous studies of DNA replication in Xenopus egg extracts (e.g. Takahashi et al, 2005: doi: 10.1101/gad.1339805) indicated that DRF1 is the dominant activator of CDC7. In contrast, past work from the current authors (Tenca et al, 2007, 10.1074/jbc.M604457200) indicated that DBF4 is the major partner of CDC7 in human HeLa cells, at least at the level of promoting MCM2 phosphorylation (the only parameter monitored in the previous study, whereas the present manuscript goes much deeper into the various roles of CDC7 in DNA replication control and focusses on the role of CDC7 at replication forks and in checkpoint control).
This study should be of interest to those studying chromosome replication, checkpoints and genome integrity. It should also interest those with a more clinical perspective, due to the potential importance of CDC7 kinase inhibitors as anti-cancer agents.
My own expertise is in the field of chromosome replication.
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Referee #2
Evidence, reproducibility and clarity
CDC7 is a master cell cycle kinase with essential functions in DNA replication and important roles in the DNA damage response. For its functions, CDC7 relies on a regulatory factor, DBF4, which is essential in many species but not in human cells as a consequence of the presence of a second DBF4-related factor, DRF1. In this work, Göder and colleagues study the relative relevance of these regulatory proteins in CDC7 roles. Their study reveals DBF4 as the major regulatory subunit both in DNA replication, DNA damage checkpoint and fork dynamics. The objective of the study is highly relevant to understand an essential cell cycle kinase with potential applications in cancer therapies, the experiments are well performed and the conclusions are "in principle" sound.
The major handicap of the study is the absence of western blots showing the elimination of DBF4 and DRF1 in the edited cell lines due to the lack of specific antibodies. The authors have generated homozygous mutations that lead to premature stop codons behind critical CDC7 domains. However, as they mention, it is not possible to fully exclude some proteins arising from internal start sites or exon skipping events with residual (functional or altered, and not necessarily residual) activity. This is not unexpected, especially for essential proteins. This would not be a major handicap if the study were focused in a specific factor because it would only question the impact of but not the affected function, but it aims to compare the relative effect of two defective genes. In this case, it is essential to confirm that both genes are eliminated, at least to the same degree. The computational analysis in Figure 1C is consistent with the major conclusion about the primary regulatory role of DBF4 in replication, but it is insufficient to validate the specific phenotypes addressed in the study. Indeed, there is a result that is hard to understand if the edited cell lines are defective in the expression of the regulators, specially DRF1. Figure S2D-E shows no synergistic defect in DNA synthesis when the second regulator is knock down with specific siRNAs, not even DRF1 defective cell lines treated with a siDBF4 that reduces its expression 10 times. Also, it is not clear why the defects, specially in DBF4-defective cell lines, are less severe than in cells treated with an inhibitor that causes a partial inhibition of CDC7. If it is due to the expression of DRF4, a siRNA against DRF4 should cause more severe defects.
Minor points
- Title in Pag 12. "DBF4 mediates the majority of CDC7 functions in the replication stress response". In this section the authors address only the role of CDC7 in checkpoint signalling but not in other processes related to the replication stress response.
- Figure 2. "EdU incorporation in late S-phase/ per cell" is clearer
- Right panels in Figures 3A and 3B are duplicated
Referees cross-commenting
I am aware of the difficulty to sort out the detection problem, a major handicap of the work. Immunoprecipitation as suggested by rev. 3 might be an interesting possibility. The results should be published, in any case, as they are well performed and try to answer a relevant question. But, if finally the authors fail to detect the proteins, they should make clear in the paper the limitation of their conclusions by the possibility that the expression of the regulators is not completely eliminated or could be altered. Indeed, the apparent contradiction with Suski's results raised by Rev 3 might be discussed in this context. Also, it is important to explain the lack of synergism when combining the edited mutations with siRNAs.
Significance
In summary, the work is relevant and interesting, but the lack of controls about the effect of the edition rises important concerns about the conclusions. It is evident from the acknowledgment section that the authors have tried without success to generate specific antibodies. An alternative possibility would be 1) to get similar results with at least two clones addressing different exons (actually, only one clone was used for DRF1 in most cases) and 2) show synergistic effects for the more important phenotypes in edited cells transfected with efficient siRNAs. This is particularly important for DRF1-defective cells, which show no phenotypes except for an increase in micronuclei. If DBF4 is not essential because the complementary activity of DRF1, impairment of DBF4 expression with siRNAs in DRF1 deficient cells should cause synergistic defects at least in DNA replication and cell viability.
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Referee #1
Evidence, reproducibility and clarity
DBF4 and DRF1 knockout cells were generated and used to separate DBF4- and CDC7-dependent from DRF1- and CDC7-dependent activities. DBF4- and CDC7-dependent activities at replication forks were independent of DRF1. These include the replication timing pattern, replication fork velocity, DNA damage signaling. DBF4 is required to recruit CDC7 to active replication forks.
The study is in large part exceptional. The inclusion of quantitation for a modest bandshift on CDC7 in figure 2 (30% vs 50% reduced) is not justified given the abundance of the main band and our knowledge of the lack of linearity of western blot quantitation. This should be removed.
The only significant weakness in the paper is the explanation of the replication timing analyses in Figure 3. I don't understand what the differences between the plots equate to in terms of timing. I understand the replication of these regions that diverge is either early or late, but their were only two fractions of cells - 2N-3N and 3N-4N (the cells are "normal"). If this is the case, isn't the readout binary? a sequence either replicates in S phase between 2N and 3N or in S phase between 3N and 4N. Why are the differences so small? Are they only evident in a small population of cells? If that is the case, then what does the difference really mean? I think the description of these data needs to be precise.
Significance
I think this paper is a significant advance that should be published. CDC7 is a critical kinase and identifying its co-factor at the replication fork is important both for our understanding of mechanisms of DNA replication and the impact of CDC7 kinase inhibitors in the clinic. I think the majority of the experiments are well designed and the results are unambiguous and precisely described.
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Reply to the reviewers
Reviewer #1 (Evidence, reproducibility and clarity): Summary:
This research article describes genetic identification and expression analyses of six Ephrin type-B receptor 4 (EPHB4) variants identified in patients with dilated cardiomyopathy (DCM). Variants were identified Variants were identified in a cohort of 573 patients enrolled through the multicenter DZHK-TORCH (TranslatiOnal Registry for CardiomyopatHies) study and the Institute for Cardiomyopathies Heidelberg registry. Expression of downstream molecules, CAV1 and CD36, was assessed in human cardiac tissues by immunohistochemistry. EPHB4 cardiac expression was assessed using recently published single-cell/nucleus RNA sequencing data (Nicin et al 2022) incorporating siRNA-seq data from two other studies (healthy cardiac tissue, Litvinukova et al 2020) and (hypertrophic/aortic stenosis, Nicin et al. 2020).
We thank the reviewer for the recommendations that have improved our manuscript.
Major Comments:
- Details of identified truncating RBM20 and TTN variants must be provided. These should be integrated into Table 1 alongside each co-occurring EPHB4 variant. List whether the TTN truncating variant is located in the A-band and whether these variants would be adjudicated as pathogenic/likely pathogenic, variant of uncertain significance by ACMG and/or similarly refined DCM criteria (Morales et al. 2020, Circ-Genom Precis Med).
Details of the truncating RNM20 and TTN have been provided in the new supplementary table 1. As indicated in the table both mutations are pathogenic, and thus, most probable the cause for the disease in these patients. In case of TTN this is a truncating variant and is located in the M-band in exon 358, which is annotated with a PSI in DCM of 100% in cardiodb.org. The fact that these mutations are most probably the cause for DCM in these patients has been included in the discussion section and reads as follows:
Although it is most probable that in the case of the patients carrying TNN and RNM20 variants this would be the cause of the disease, this study further supports, the importance of EPHB4 regulating CD36 caveolar trafficking to the membrane, whether this happens in endothelial cells or cardiomyocytes, maintaining cardiac homeostasis in humans and its implication on DCM
- Discuss co-occurrence of multiple EPHB4 variants in two patients (DCM1, DCM3) and identification of 2 EPHB4 variants in more than one proband.
As shown in Figure 1A, the detected variants are found in multiple domains of the protein, hence no clear hotspot is detected. We did not yet investigate on the exact mechanisms of action, however, when we compare the two patients with multiple EPHB4 variants, the average LVEF (echo) is 17.5 compared to 38,67 for the remaining 4 patients with only one EPHB4 variant and 35,17 for the six non-EPHB4 variant-carriers. Although the sample number only allows for a semi-quantitively analysis, it still hints at a possible EPHB4-variant effect, which certainly needs verification in a larger cohort.
Since we do not postulate the detected variants as independently disease-causing, and we also did not explicitly filter for very rare variants, it is not surprising that we find two variants in multiple patients. As stated above, we did not investigate this further, but evidence is growing that compound heterozygosity is playing a role in heritable diseases. It will be interesting to analyze e.g. phasing (Hofmeister et al., Nature Genetics, 2023) or additive (biallelic) effects, which have come to attention also in cardiomyopathies recently (Lipov et al., Nature Cardiovascular Research, 2023).
This fact has now been included in the manuscript, both in the results and in the discussion. It reads as follows:
Interestingly, two of the analysed patients present more than one variant of EPHB4 and we could identify the same variant in more than one patient (Table 1)
(…)
Nevertheless, two of the patients carrying one benign or likely benign also carry another variant classified as likely pathogenic or of uncertain significance (Table 1) and interestingly, the average LVEF of the two patients with multiple EPHB4 variants is 17.5 compared to 38,67 for the remaining 4 patients with only one EPHB4 variant and 35,17 for the six non-EPHB4 variant-carriers. Although the sample number only allows for a semi-quantitively analysis, it still hints at a possible EPHB4-variant effect, which certainly needs verification in a larger cohort.
- Three of the six variants (p.Lys635Asn, Val113Ile, Glu890Asp) are classified as Clinvar Benign/Likely Benign. Additionally, p.Glu890Asp has been identified in 50 homozygotes in gnomAD non-Finnish European population. These data cast doubt on the pathogenicity of these variants. These classifications, as well as VUS classification of p.Pro79Leu, should be listed in Table 1. The authors should reconcile the benign/likely benign Clinvar classifications with their presented evidence for pathogenicity in the discussion.
We have now included the ACMG classification in Table 1. Similar to the Clinvar classification, some of the variants are classified benign or likely benign. Still, the fact that the patients that carry them also carry another variant and that the histological findings are similar among the patients carrying an EPHB4 variant and different to those that don’t and the enriched presence of EPHB4 variants in the DCM population support our hypothesis that the Eph-ephrin signalling pathway plays a role in the development of DCM.
Nevertheless, we agree with the reviewer that the fact that some of these variants have been classified as benign, and the presence of mutations in other genes already related to DCM like TNN or RMM20 may suggest that the EPHB4 mutations may not be the only cause for the disease but rather have an additive effect. As a consequence, we have toned down our conclusions and the discussion reads now as follows:
Finally, although not as the main disease cause, this study not only supports the role of EPHB4 in the heart, but it also corroborates the importance of CD36 and CAV1 for the cardiac health, and has the potential to improve diagnosis and risk stratification tools for DCM. In addition, as other genes crucial for fatty acid transport may be involved in cardiac disease, this study may help identify new diagnostic or therapeutic targets.
- CD36 and CAV1 expression are not quantified. Qualitatively, it is difficult to confirm CD36 reduction in DCM and disruption in EPHB4 variant samples as imaging parameters are not specified and do not appear to be standardized across treatments. Clearly state (either in the figure legend or in the methods) whether identical imaging parameters were used across panels 1C-1E. Note any differences in these parameters.
We have now quantified the two IHC. It is very clear that the total CD36 is significantly reduced in both groups when compared to the healthy donor (Figure for the reviewer 1A). In case of CAV1 this is not so evident, although the signal seems reduced this is not significant (Figure for the reviewer 1B). These new data have been included in the figure of the manuscript.
Figure for the reviewer 1. Quantification of (A) CD36 and (B) CAV1 in the immunohistochemistry analysis of patients biopsies. Data shown as mean ± SEM. (A) P value was calculated using one sample one sample Wilcoxon test for DCM and one sample t test for DCM EPHB4. Both cohorts where compared to the mean of HD. P value < 0.05 was considered significant. (B) P value was calculated with one sample t test for both cohorts. P value < 0.05 was considered significant.
All the images have been taken in the same conditions. The observed difference in the background is due to the disease conditions of the DCM samples. Furthermore, the apparent reduced number of capillaries observed in the DCM patients are caused by the hypertrophic state of the cardiomyocytes in the diseased state. These are bigger and thus, less cells and capillaries appear per picture. The parameters have been included in the methods and read as follow:
Immunohistochemistry was imaged in a Leica Stellaris confocal microscope. All images were obtained with 63x magnification and the same laser and gain intensities. Images were acquired using the software LAS X (Leica, version 4.4) and quantified using the Volocity Software (Quorum Technologies, version 6.5.1)
- Why was EPHB4 membrane localization not assessed or reported?
We agree with the reviewer that this would be a very interesting point. Unfortunately, we had very limited amount of material and we did not have a proper working antibody.
- A key finding of the manuscript is that all six variants produce similar histological impacts on CAV1 and CD36 expression, denoting downstream impacts of EPHB4 genetic disruption. There is no granular data presented to support this claim. Additional discussion is also required to address how the authors anticipate variants in functionally distinct domains on either side of the plasma membrane to similarly impact downstream expression of CAV1/CD36. Mapping to available crystal structures in the Protein Data Bank (PDB) may be insightful to determine which variants may be most likely to have an impact on heterotetramer formation or to exert dominant negative effects on receptor function.
As an appendix to this revision we have included a figure with representation images of all biopsies analysed to support our claim.
The whole protein structure is not solved and only some individual domains are present in the Protein Data Bank making difficult to analyse the effect on the tetramer without crystallising the whole protein.
- Study limitations are not discussed and are significant. 5 of the 6 samples were from male patients, there are limitations to analyses of non-diverse patient ancestry, there is uncertainty regarding pathogenic contributions of variants in established DCM genes in 2/6 patients, data is limited to expression-only analyses highlighting need for additional functional modeling in cell or animal based systems.
We have now included a limitation sections that includes all the points raised by the reviewer. It reads as follows:
Although this study offers valuable insights to the potential implication of the Eph-ephrin signalling pathway in the development of DCM it has some limitations that need to be discussed. Despite finding increased presence of EPHB4 variants in the DCM population when compared to the healthy population, analysis of the identified variants in using different classifications (CADD and ACMG) not always predicted pathogenicity for these variants. For this reason, further experiments should be performed to determine the effect of every variant.
It is also important to note that given the lower number of patients analysed these are not age and gender matched. The EPHB4 carrying DCM patients were younger than the DCM patients carrying a wild type EPHB4 sequence and mainly male. Finally, no biomaterial nor genetic testing from family related patients is available.
- Language used in conclusions overstates study findings ["our results confirm a crucial role of the Eph-ephrin signaling pathway in DCM" (page 3), "this study not only confirms the crucial role of EPHB4 in the heart..." (page 8)]. Change to "suggest" or "support".
We have revised our discussion according to the limitations discussed in the previous remark and these words have been corrected.
Major Methods Comments:
- DCM diagnostic criteria (clinical and imaging) for inclusion in the DZHK-TORCH study and the Institute for Cardiomyopathies Heidelberg registry should be stated or referenced. Likewise, describe and/or reference DCM exclusion criteria. State any relevant differences in DCM enrolment criteria for the two registries.
We have now included our inclusion criteria in the methods and include two references to support this. The paragraph reads as follows:
The criteria to be included in the study was reduced left ventricular ejection fraction (LVEF) <50% validated either with two independent image techniques or at two different time points with the same imaging technique. Furthermore, patients should include left ventricular dilation (LVEDD) >117% corrected with age and body surface according to the Henry-Formel formula (LVEDD= 45,3 * BSA1/3 – 0,03*Age –7,2). In both cases the heart were analysed either by echocardiography or magnetic resonance tomography (MRT)
- Describe how the final cohort of 573 DCM patients was reached. (All patients with DCM in the DZHK-TORCH study/Heidelberg registry? All patients with available exome data meeting QC standards and having available cardiac tissue?).
From the 573 DCM patients, 100 have been recruited as part of the DZHK-TORCH registry and have been genome sequenced. Further 62 genomes and 411 exomes have been sequenced from patients of the cohort from the Institute for Cardiomyopathies (ICH) at the Heidelberg University Hospital.
From this cohort, we selected 6 patients with and 6 without an EPHB4 variant and received heart tissue slides from the pathology department.
- State whether any family/segregation data is available for these patients.
DCM4 has a mother and aunt (mother’s sister) who are also affected by CMP. In case of DCM6, the mother was also diagnosed with CMP. Unfortunately, no further biomaterial nor genetic testing of those individuals is available. This has been included in the new limitation sections as described above.
- Description of genetic testing methods are inadequate. Describe how genetic analyses were completed for each study/registry and how results were filtered/quality controlled. If sequencing methods were different across registries, state which patients were tested by which methods. If any testing was gene-targeted rather than whole exome/genome, list the specific DCM genes tested.
All data has been sequenced using Illumina paired-end technology with either 2x100bp or 2x150bp. Exome enrichment was achieved using SureSelect Human All Exon V6 Target Enrichment (Agilent Genomics) was used. Bioinformatics analysis pipeline was based on “Best Practices Guideline” from the Genome Analysis Toolkit (GATK) (https://gatk.broadinstitute.org/hc/en-us). Besides the analysis for EPHB4, we assessed further genes associated with cardiomyopathies (ACTC1, ACTN2, ALPK3, BAG3, CRYAB, CSRP3, DES, DMD, DSC2, DSG2, DSP, FLNC, GLA, HCN4, HRAS, JPH2, JUP, KRAS, LAMP2, LDB3, LMNA, MIB1, MYBPC3, MYH7, MYL2, MYL3, MYPN, NEXN, PKP2, PLN, PRDM16, PRKAG2, PTPN11, RAF1, RBM20, RYR2, SCN5A, SHOC2, TAZ, TMEM43, TNNC1, TNNI3, TNNT2, TPM1,TTN, TTR, VCL).
This is information has been included in the methods section.
- Provide additional detail for human cardiac biopsies. Was the same chamber/tissue biopsied in all samples? Is an endomyocardial biopsy available for all 573 patients included in this study? If not, were additional EPHB4 variants identified in patients without biopsy samples?
All biopsies investigated are from left-ventricular tissue, accessed during cardiac catheterization.
We did find additional, mainly non-coding variants in the cohort. However, as the focus on the study was on the histological analysis of the CD36 and CAV1 expression, we did restrict our analysis to our selected samples as described in the response to comment 2.
- Describe the source of the healthy control biopsy, alongside brief clinical detail establishing suitability as a control. Did DCM controls carry variants in known DCM genes (including truncating variants in RBM20 or TTN)? How were DCM controls selected?
The healthy control biopsy was kindly donated by Prof. Dettmeyer from the University Gießen. This is a postmortem sample with unrelated cause of death. Cardiac biopsy was examined to discard any pathological alterations. This sample originates from a 27 years old female, and thus ideal as a healthy sample. This information has been included in the methods.
- List statistical analyses and associated experiments. (Page 5).
Statistical tests have been included in the figure legend of each experiment. This reads as follows:
(B) EPHB4 variant allelle frequency analysis. Each variant is compared in a paired wise manner between the two population. P value was calculated with a paired one-tailed Student’s t test comparing the frequencies of the different variants in the two populations.
And
(F) Quantification of CD36 and CAV1 expression in the immunohistochemistry analysis of patients biopsies. Data shown as mean ± SEM. In the case of CD36, P value was calculated using one sample one sample Wilcoxon test for DCM and one sample t test for DCM EPHB4. P value < 0.05 was considered significant. In the case of CAV1, P value was calculated with one sample t test for both cohorts. P value < 0.05 was considered significant. In both cases, the cohorts where compared to the mean of HD.
- List microscopes/equipment and software used to complete immunohistochemistry experiments. Describe imaging parameters to facilitate comparisons between treatments in Figure 1C-E.
Immunohistochemistry was imaged in a Leica Stellaris confocal microscope. All images were obtained with 63x magnification and the same laser and gain intensities. Images were acquired using the software LAS X (Leica, version 4.4) and quantified using the Volocity Software (Quorum Technologies, version 6.5.1)
This paragraph has now been included in the methods section.
- Please reword the following passage, which is almost verbatim to the same passage in Nicin et al. 2022.
Page 4
**"In brief, a combination of two human snRNA-seq datasets was used. Data from healthy cardiac tissue from the septum of 14 individuals in the Litvinukova et al. study and data from location-matched hypertrophic cardiac tissues from five patients with aortic stenosis."
Nicin et al. 2022 (https://doi.org/10.1038/s44161-022-00019-7)**
"Two human snRNA-seq datasets were used: data from healthy cardiac tissue from the septum of 14 individuals in the Litvinukova et al. study and data from location-matched hypertrophic cardiac tissues from five patients with aortic stenosis."
We have reworded the paragraph in the methods sections. Now it reads as follows:
Healthy cardiac tissue data was derived from the cardiac septum of 14 individuals 15. Subsequently, it was integrated with data from the septum of hypertrophc cardiac tissue from 5 patients with aortic stenosis 16.
Minor Comments:
- Results: List source for Non-Finnish European Control cohort (gnomAD) (Page 5).
The Non-Finnish European Control cohort (gnomAD) was obtained from https://gnomad.broadinstitute.org/. This information has been included in the methods section.
- Discussion: "all DCM patients" (page 6) requires clarification.
We have made clear that this refers to the patients analysed in this study. The new sentence reads as follows:
Furthermore, our results stress the importance of the endothelial CD36 in the onset of cardiac disease as all DCM patients analysed by immunohistochemistry show a downregulation of CD36 in the endothelium and warrant a more detailed assessment of genes involved in vascular function20
- Discussion: Define acronyms. CSF, IL4, LPS (Page 7)
We have defined the acronyms in the discussion. The new sentence reads as follows:
CD36 expression is upregulated by the nuclear hormone transcription factor Peroxisome Proliferator-Activated Receptor-Gamma (PPAR-ɣ), cerebrospinal fluid (CSF) cytokines and Interleukin-4 (IL4). In the other hand, lipopolysaccharides (LPS) and dexamethasone downregulate its expression In microvascular endothelial cells, CD36 is downregulated by lysophosphatidic acid.
- Table 1. Table is confusingly arranged. It would make more sense to organize the table by cDNA/AAchange to better correspond to Figure 1A. List the impacted protein domain for each variant in a separate column. It is also unclear how DCM allele frequencies were calculated as the reported number of patients (DCM1-6) carrying each variant do not universally correspond to the listed allele frequencies (see AFs of 0.0052 and 0.0208). Clarification should be added to the legend so it is clear to the reader how these frequencies were determined
In case of the EPHB4 variants table, we agree with the reviewer and to make the table more understandable we have removed the first three columns, which are the same for all variants. This information has been included in the table legend. Nevertheless, this information has been kept in the new Supplementary table 1 that contains the variants on the other DCM causing genes.
Regarding the calculation of the allele frequency we made by dividing the number of alleles found in the population by the total number of alleles in the population. This information has been included in the methods.
We want to note that we performed a mistake in the original table. We had calculated the frequencies by dividing the number of alleles by the number of individuals in the population. We have now corrected both Table 1 and Figure 1B.
- Figure 1B. Add variant labels. Indicate relevant p-values for each variant. It is unclear to which comparison the p = 0.024 belongs. State in legend that 2 variants were omitted (presumably due to absence from gnomAD)
No variants were omitted in the representation of Figure 1B. Some of them have the same allele frequency in the DCM population and thus, the individual data points appear overlapping. The variants that were not detected in the genomAD population were considered as 0 for the representation and for the analysis.
For the comparison with P=0.024 (now corrected to 0.0011) between the two groups we have performed a one tail paired t test comparing the frequencies in both populations. The information regarding the test has been included in the figure legend and included in the methods section as indicated above.
- Figure 1E. Add label to indicate which EPHB4 variant is depicted.
The DCM sample from which the images originates is now indicated in Figure 1E.
<br /> Referees cross-commenting****
As is, this manuscript is not ready for publication. Our comments are in complete alignment. Like the other reviewer, I also emphasize the need for other DCM genes tested to be listed. I also reiterate that any similarly worded passages to other published material must be corrected
Reviewer #1 (Significance): This study presents genetic and expression data on a novel DCM gene candidate (EPHB4) from a European cohort of 573 DCM patients. This work is of interest as much of genetic DCM remains unexplained and identification of novel genes and pathways will be critical to advance understanding of the disease and to develop novel treatments. Reported data will be of greatest interest to cardiovascular practitioners and translational/basic researchers working with genetic heart disease/DCM. The fact that cardiac tissue was available for histological analyses for all six patients is an asset. There are considerable weaknesses to the paper, as written. There is a lack of detail in the included genetic methods and results. While the premise of the study is intriguing, additional detail is required for identified TTN and RBM20 truncating variants and additional discussion is needed to resolve confusion regarding reported allele frequencies and benign/likely benign Clinvar classifications. Because study design is restricted to genetic and expression analyses, reported data do not address possible pathogenic mechanisms. Overall, there is insufficient data presented to confirm a role for EPHB4 in causing DCM. Manuscript-specific (as-opposed to study specific) weaknesses include insufficient methods detail, a lack of clarity in the presented genetic and expression data (particularly Figure 1), insufficiently described study limitations, and overstated study conclusions. These scientific and manuscript issues will need to be addressed for the manuscript to be suitable for publication.
Reviewer fields of expertise: cardiovascular genetics, DCM.
Insufficient expertise to evaluate statistical methods.
Reviewer #2 (Evidence, reproducibility and clarity):<br /> I reviewed a paper by Luxan et al. describing EPHB4 variants as a novel disease gene for dilated cardiomyopathy (DCM).
The short report is interesting, however, not enough evidence is given to convince me EPHB4 is indeed a novel disease gene for DCM. More work is needed before this can be published.
Major points:
- Genetics: two individuals have EPHB4 variants together with DCM causing TTN tv or RBM20 variants. Which other DCM genes were excluded for the remaining four cases? GnomAD MAF of 0.008748404 suspiciously high.
So overall the small case number makes it hard to judge whether these are truly pathogenic variants.<br /> Could the authors attempt co-segregation of DCM with EPHB4 variant in families?
Unfortunately we do not have family information from these patients. We have included this in the new limitation sections in the discussion that reads as follows:
Although this study offers valuable insights to the potential implication of the Eph-ephrin signalling pathway in the development of DCM it has some limitations that need to be discussed. Despite finding increased presence of EPHB4 variants in the DCM population when compared to the healthy population, analysis of the identified variants in using different classifications (CADD and ACMG) not always predicted pathogenicity for these variants. For this reason, further experiments should be performed to determine the effect of every variant.
It is also important to note that given the lower number of patients analysed these are not age and gender matched. The EPHB4 carrying DCM patients were younger than the DCM patients carrying a wild type EPHB4 sequence and mainly male. Finally, no biomaterial nor genetic testing from family related patients is available.
- Only CADD tools was used for pathogenicity, several tools should be used. Is the structure solved? Structural predictions on the consequences of the variants should be done.
We have now included the ACMG classification in Table 1. As discussed above in the comments of Reviewer 1, some of the variants are classified as benign or likely benign. For this reason we have now toned down our conclusion suggesting that the EPHB4 may not be sufficient to trigger DCM but act as modifiers. This is supported by the fact that the histological analysis revealed that the patients carrying EPHB4 variants are similar among themselves and different to the other patients. Furthermore, our hypothesis is also supported by the fact that those patients carrying benign or potentially benign variants also carry another variant and the fact that they even have lower LVEF. The new classification has been included in the results and discussion sections and it reads as follows:
Nevertheless, the classification of the variants according to the American College of Medical Genetics (ACMG) 25 suggests that two of the variants are benign, two likely benign, one likely pathogenic and one variant of uncertain significance (Table1). Nevertheless, two of the patients carrying one benign or likely benign also carry another variant classified as likely pathogenic or of uncertain significance (Table 1) and interestingly, the average LVEF of the two patients with multiple EPHB4 variants is 17.5 compared to 38,67 for the remaining 4 patients with only one EPHB4 variant and 35,17 for the six non-EPHB4 variant-carriers. Although the sample number only allows for a semi-quantitively analysis, it still hints at a possible EPHB4-variant effect, which certainly needs verification in a larger cohort.
And
Our analysis identified several variants in EPHB4 enriched in a cohort of DCM patients. According to the CADD score prediction, all these variants have a deleterious potential. Nevertheless, the ACMG classified some of the variants as benign or potentially benign. Also the fact, that one variant has identified in two non-related patients suggests that this variant may be benign for the protein. Nevertheless, two of the patients carrying a benign or potentially benign variant also carried another potentially pathogenic or of uncertain significance. During Eph-ephrin signalling, the binding of the ligand induces Eph receptor heterotetramers to initiate the signalling via Eph–Eph cis interactions30. Thus, variant EPHB4 molecules could have a dominant negative effect on these heterotetramers, and while maybe not completely abrogating its function, reducing the functionality of the heterotetramers. This observation could explain why the presence of one variant copy in the DCM patients of our cohort would be sufficient to reduce the activity of the Eph-ephrin signalling pathway. Although this shows that some of the variants may indeed not be the sole cause for DCM it shows that the Eph-ephrin signalling pathway, and in particular EPHB4 may be important for the development of DCM.
Only parts of the protein have been resolved and present in the Protein Data Base.
- The microscopy Figure 1C-E is not convicing. Only one sample shown while 6 were available/investigated. I would not be comfortable to identify cardiomyocytes/endothelial cells from these sections
As an appendix to this document, we included figures with images obtained from all the analysed patients. These were not included on the original figure for space reasons.
These sections are perfect to identify cardiomyocytes and endothelial cells in cardiac tissue. First, endothelial cells, that form the microvasculature are labelled with ULEX, a well known marker of endothelial cells. Secondly, cardiomyocytes are really big cells easy to score for their size and location between the capillaries in the heart. Other cells present in the heart, like fibroblasts, macrophages, or pericytes would also be located in the space left in between cardiomyocytes but would need to be labelled for visualization. We believe that our interpretation of the immunohistochemistry pictures is correct.
- Functional work is needed to understand the interplay between EPHB4, CAV1 and CD36. Such as transfecting mutant EPHB4 into cells and probing for altered localisation/attachment of binding partners, most likely in endothelial - cardiomyocyte co-culture systems.
Our study is based in our previous murine study in which we showed that the deletion of EphB4 or its ligand ephrinB2 would induce a phenotype similar to DCM in mice. At the molecular level, defects in the Ephb4 are linked to compromised caveolar function and reduced CAV1 phosphorylation, which involves the kinase Src, a known mediator of Eph receptor signalling. In the healthy heart, caveolar transport is required for the membrane translocation and correct function of fatty acid translocase FAT/CD36, which mediates the uptake of fatty acids. The objective of this follow up study was to study whether we could identify EPHB4 mutations in DCM patients. As seen in the results we have observed that there is an enrichment of EPHB4 variants in the DCM population. We think that the previous study supports our conclusions and hope that the reviewer agrees with us. Nevertheless, we agree with the reviewer that functional assays could be performed with every variant. We have included this in the new limitation sections of the manuscript described above.
Minor points:
- Figure 1B does not make sense
Figure 1B confirms the enrichment of EPHB4 mutations in the DCM population. We have corrected the labelling to make this clearer. We have now labelled the figure “EPHB4 variant allele frequency in control and DCM population”.
- Statistics: Which tests were performed, if normality tests were applied, which one was used?
The tests used for every comparison are included in the figure legend. In case of EPHB4 variant allele frequency, we performed a paired one-tailed Student’s t test comparing the frequencies of the different variants in the two populations. In case of the CD36 and CAV1 quantifications, we performed a two-tailed one sample t test. In this case, we compare the expression of CD36 and CAV1 to an hypothetical healthy population with mean equal 1 as que have used this value for normalization.
- Please do not use contractions, e.g. 'can't' in discussion section
Contractions have been removed from the manuscript.
<br /> Referees cross-commenting****
Overall I agree with the other reviewer on the points raised.
Reviewer #2 (Significance): Description of EPHB4 as a novel DCM gene is of interest, but the current data are not convincing enough to make this statement.
Mechanistic work on the interplay of endothelial cells and cardiomyocytes and consequences of EPHB4 variants would make it a very compelling story.
Reviewer #3 (Evidence, reproducibility and clarity): Summary:
The authors of this manuscript studied the prevalence of a population of Ephrin type-B receptor 4 (EPHB4) in a cohort of 573 DCM patients and found six new EPHB4 variants, possibly pathogenic based on the Combined Annotation Dependent Depletion (CADD) score and population frequency. Moreover, the authors perform immunofluorescence (IF) and histologic analysis on 6 EPHB4 variant carrying DCM patients, 6 DCM patients with wild type EPHB4 and one healthy control biopsy and found dysregulation of Caveolin 1 (CAV1) and CD36 (which are implicated in fatty acid transport in endothelial cells and cardiomyocytes) in both groups of DCM patients.
Major comments:
- Additional experiments are necessary to prove the hypothesis: for example, co-IF staining with endothelial markers should be provided. IF should be supported by western blots and qPCR.
The objective of this study was to explore whether we could identify EPHB4 mutants in a DCM cohort. Interestingly we have shown that EPHB4 mutations are enriched in the DCM population when compared to the general population. Nevertheless, we agree with the reviewer that a more in depth mechanistic study would improve the significance of the study. We have included a limitations section that reads as follows:
Although this study offers valuable insights to the potential implication of the Eph-ephrin signalling pathway in the development of DCM it has some limitations that need to be discussed. Despite finding increased presence of EPHB4 variants in the DCM population when compared to the healthy population, analysis of the identified variants in using different classifications (CADD and ACMG) not always predicted pathogenicity for these variants. For this reason, further experiments should be performed to determine the effect of every variant.
It is also important to note that given the lower number of patients analysed these are not age and gender matched. The EPHB4 carrying DCM patients were younger than the DCM patients carrying a wild type EPHB4 sequence and mainly male. Finally, no biomaterial nor genetic testing from family related patients is available.
- The DCM samples with wild type EPHB4, have no CD36: the mechanism by which a mutation in another gene could affect the Eph-ephrin signaling pathway should be at least discussed.
These patients do not have any mutation on EPHB4. Based in the literature and the previous murine study show that the Eph-ephrin signaling pathway is upstream of CD36. For these reasons we believe that our observation that shows that CD36 expression is reduced in all DCM patients confirms the important role of CD36 in cardiac homeostasis and the development of DCM. We further, as indicated in the discussion, other genes crucial for fatty acid transport may be involved in cardiac disease and thus, this study may help identify new diagnostic or therapeutic targets.
- The authors should discuss and possibly prove the correlation between mutant EPHB4 and CD36 and CAV1 expression and localization in endothelial cells vs cardiomyocytes and explain the mechanistic implications of co-localization of CAV1 with CD36.
In a previous study we showed that the deletion of EphB4 or its ligand ephrinB2 would induce a phenotype similar to DCM in mice. At the molecular level, defects in the Ephb4 are linked to compromised caveolar function and reduced CAV1 phosphorylation, which involves the kinase Src, a known mediator of Eph receptor signalling. In the healthy heart, caveolar transport is required for the membrane translocation and correct function of fatty acid translocase FAT/CD36, which mediates the uptake of fatty acids. We have expanded the introduction to explain the relationship between these molecules. It reads as follows:
Mechanistically, EPHB4 deficient endothelial cells are characterized by compromised caveolar function and reduced Caveolin 1 (CAV1) phosphorylation. EPHB4 is required for the phosphorylation of CAV1 at Tyr-149. The phosphorylation of CAV1 promotes the release of caveolae from the plasma membrane10. Caveolae are required for the correct membrane translocation of the fatty acid translocase FAT/CD3611 and fatty acids are used by cardiomyocytes to obtain about 50% to 70% of their energy12. Absence of CD36 in cardiomyocytes reduces fatty acid uptake by the cardiac muscle cells13 and accelerates the progression from compensated hypertrophy to heart failure14. Finally, some cardiomyopathies a causally related to defects in the synthesis of the proteins required for fatty acid uptake in the heart15.
- The available snRNAseq raw data are from normal subjects and aortic stenosis patients who are different from DCM patients. A better dataset would be the one from Reichart D, et al. Pathogenic variants damage cell composition and single cell transcription in cardiomyopathies. Science 2022.
The single nucleus RNA sequencing data was used in an exploratory manner to study whether EPHB4 would also be expressed in cardiomyocytes. We did not perform any study on gene expression comparing the two groups. We believe that the use of this dataset is justified. We hope that the reviewer agrees with us.
- Furthermore, the link between the analysis done on the published snRNA seq datasets and the authors' own data is not clearly explained.
As we stated above and in the methods, we have used the single nucleus RNA sequencing to explore whether cardiomyocytes express EPHB4. The sentence in the methods reads as follows:
The single-nucleus-RNA-sequencing data set generated in the paper by Nicin et al.14 was used to explore EPHB4 expression in human cardiac cells
- DCM1 and DCM 3 carry 2 EPHB4 variants: please describe if the phenotype was more severe.
As discussed above in the response to reviewer 1, the two patients with multiple EPHB4 variants present an average LVEF (echo) of 17.5 compared to 38,67 for the remaining 4 patients with only one EPHB4 variant and 35,17 for the six non-EPHB4 variant-carriers. Although the sample number only allows for a semi-quantitively analysis, it still hints at a possible EPHB4-variant effect, which certainly needs verification in a larger cohort.
This information has been included in the manuscript and reads as follows:
and interestingly, the average LVEF of the two patients with multiple EPHB4 variants is 17.5 compared to 38,67 for the remaining 4 patients with only one EPHB4 variant and 35,17 for the six non-EPHB4 variant-carriers. Although the sample number only allows for a semi-quantitively analysis, it still hints at a possible EPHB4-variant effect, which certainly needs verification in a larger cohort.
- Provide p values on suppl table 1. The 2 groups are not matched by age and maybe gender, and this could affect the histological findings.
We have not performed any comparison between the two groups in the characteristics shown in supplementary table 1. Nevertheless, we agree with the reviewers that the fact that the patients are not matched in age and gender is a limitation to our study. We have acknowledged this in the new included limitations section that is mentioned above.
- Please discuss why in the DCM population the EPHB4 variant is enriched as compared with controls. Causal role? Modifiers?
The deletion of EphB4 and its ligand ephrin-B2 induce DCM in mouse. The objective of this study was to determine whether there would be mutations in EPHB4 associated to DCM. We agree with the reviewer that in depth mechanistic studies both in vivo and in vitro would be required to determine the exact role of the here identified mutations in the development of DCM. This has been acknowledged in the new limitations sections and indicated in the discussion of the results as follows:
Finally, this study not only supports the crucial role of EPHB4 in the heart, but it also corroborates the importance of CD36 and CAV1 for the cardiac health, and has the potential to improve diagnosis and risk stratification tools for DCM. Nevertheless, whether mutations in EPHB4 are causative or modifiers of the disease should be further studied. In addition, as other genes crucial for fatty acid transport may be involved in cardiac disease, this study may help identify new diagnostic or therapeutic targets.
- The data and the methods are presented in such a way that they could be reproduced however,
We thank the reviewer for the positive comment on our methods section.
- At least 2 more healthy controls should be included, and the DCM groups should be matched by gender and age.
Healthy donor biopsies are very rare and difficult to obtain. Although we agree with the reviewer that this could strengthen our study, we cannot add more healthy biopsies. We hope the reviewer understands this.
As stated above, we have included a limitation section in the manuscript discussing the issue with the gender and age.
- The causal mutation of the DCM patients should be provided.
Only 35% of DCM cases have been related to mutations in genes encoding cytoskeletal, sarcomere or nuclear envelope proteins. In our case, the DCM patients that we use do not carry a variant in any of the DCM known genes. We have now expanded the methods sections explaining the inclusion criteria for the DCM patients including this issue:
The criteria to be included in the study was reduced left ventricular ejection fraction (LVEF) <50% validated either with two independent image techniques or at two different time points with the same imaging technique. Furthermore, patients should include left ventricular dilation (LVEDD) >117% corrected with age and body surface according to the Henry-Formel formula (LVEDD= 45,3 * BSA1/3 – 0,03*Age –7,2). In both cases the heart were analysed either by echocardiography or magnetic resonance tomography (MRT).
Minor comments:
- I would explain in more detail the interactions among EPHB4, CD36 and CAV1 in the introduction, as the readers may not be familiar with this pathway.
We have completed the introduction expanding the paragraph where the relationship between EPHB4, CD36 and CAV1 is presented. It now reads as follows:
Mechanistically, EPHB4 deficient endothelial cells are characterized by compromised caveolar function and reduced Caveolin 1 (CAV1) phosphorylation. EPHB4 is required for the phosphorylation of CAV1 at Tyr-149. The phosphorylation of CAV1 promotes the release of caveolae from the plasma membrane10. Caveolae are required for the correct membrane translocation of the fatty acid translocase FAT/CD3611 and fatty acids are used by cardiomyocytes to obtain about 50% to 70% of their energy12. Absence of CD36 in cardiomyocytes reduces fatty acid uptake by the cardiac muscle cells13 and accelerates the progression from compensated hypertrophy to heart failure14. Finally, some cardiomyopathies a causally related to defects in the synthesis of the proteins required for fatty acid uptake in the heart15.
- Panel B in Fig 1 shows 4 variants and not 6.
All variants are shown in the panel As stated in the response to reviewer 1, it the fact that some variants have the same value that induces to think that only four are shown. The variants that do not appear in the genomAD have been considered 0 for this analysis.
- IF in Fig 1: make sure that control and DCM are at the same magnification.
Both control and DCM are at the same magnification. The reason why it looks different is the DCM phenotype. Cardiomyocytes are hypertrophic in the in the disease samples giving the impression that they are shown in a higher magnification.
- The authors analyze snRNA seq data from available datasets and not from their own patients: so, the paragraph title in the method section should be changed as it is misleading.
We have changed the title of this section of the methods. We have labelled it now “Analysis of single-nucleus-RNA-sequencing”.
Reviewer #3 (Significance): Despite the main focus of the manuscript is EPHB4, dysregulation of CD36 and its interaction with CAV1 seem to be a common mechanism in the pathogenesis of all DCM. The significance of these findings is higher than the role of EPHB4 alone and should be improved.<br /> Metabolic abnormalities, mainly affecting the fatty acid metabolism, have been described as causes or modifiers of DCM pathogenesis but in my knowledge the role of EPHDB4, CD36 and CAV 1 have not been studied in human tissues. The discovery of the mechanisms through which dysregulation of metabolism is induced by DCM genetic mutations would be an advance in the field. However, the paper in the present form is not going to have a significant impact. There is no clear connection between the sets of experiments and more mechanistic experiments should be provided to prove causality. This may take months or even years depending on the availability of human tissues and resources.
The type of audience interested in this research are mainly translational scientists mainly in the field of genetic cardiomyopathies. Furthermore, the elucidation of the metabolic effects of genetic mutations on DCM evolution may be of interest in the field of heart failure in general.
The focus of my research is genetic and molecular pathogenesis of cardiomyopathies.
-
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Referee #3
Evidence, reproducibility and clarity
Summary:
The authors of this manuscript studied the prevalence of a population of Ephrin type-B receptor 4 (EPHB4) in a cohort of 573 DCM patients and found six new EPHB4 variants, possibly pathogenic based on the Combined Annotation Dependent Depletion (CADD) score and population frequency. Moreover, the authors perform immunofluorescence (IF) and histologic analysis on 6 EPHB4 variant carrying DCM patients, 6 DCM patients with wild type EPHB4 and one healthy control biopsy and found dysregulation of Caveolin 1 (CAV1) and CD36 (which are implicated in fatty acid transport in endothelial cells and cardiomyocytes) in both groups of DCM patients.
Major comments:
- Additional experiments are necessary to prove the hypothesis: for example, co-IF staining with endothelial markers should be provided. IF should be supported by western blots and qPCR.
- The DCM samples with wild type EPHB4, have no CD36: the mechanism by which a mutation in another gene could affect the Eph-ephrin signaling pathway should be at least discussed.
- The authors should discuss and possibly prove the correlation between mutant EPHB4 and CD36 and CAV1 expression and localization in endothelial cells vs cardiomyocytes and explain the mechanistic implications of co-localization of CAV1 with CD36.
- The available snRNAseq raw data are from normal subjects and aortic stenosis patients who are different from DCM patients. A better dataset would be the one from Reichart D, et al. Pathogenic variants damage cell composition and single cell transcription in cardiomyopathies. Science 2022.
- Furthermore, the link between the analysis done on the published snRNA seq datasets and the authors' own data is not clearly explained.
- DCM1 and DCM 3 carry 2 EPHB4 variants: please describe if the phenotype was more severe.
- Provide p values on suppl table 1. The 2 groups are not matched by age and maybe gender, and this could affect the histological findings.
- Please discuss why in the DCM population the EPHB4 variant is enriched as compared with controls. Causal role? Modifiers?
- The data and the methods are presented in such a way that they could be reproduced however,
- At least 2 more healthy controls should be included, and the DCM groups should be matched by gender and age.
- The causal mutation of the DCM patients should be provided.
Minor comments:
- I would explain in more detail the interactions among EPHB4, CD36 and CAV1 in the introduction, as the readers may not be familiar with this pathway.
- Panel B in Fig 1 shows 4 variants and not 6.
- IF in Fig 1: make sure that control and DCM are at the same magnification.
- The authors analyze snRNA seq data from available datasets and not from their own patients: so, the paragraph title in the method section should be changed as it is misleading.
Significance
Despite the main focus of the manuscript is EPHB4, dysregulation of CD36 and its interaction with CAV1 seem to be a common mechanism in the pathogenesis of all DCM. The significance of these findings is higher than the role of EPHB4 alone and should be improved.
Metabolic abnormalities, mainly affecting the fatty acid metabolism, have been described as causes or modifiers of DCM pathogenesis but in my knowledge the role of EPHDB4, CD36 and CAV 1 have not been studied in human tissues. The discovery of the mechanisms through which dysregulation of metabolism is induced by DCM genetic mutations would be an advance in the field. However, the paper in the present form is not going to have a significant impact. There is no clear connection between the sets of experiments and more mechanistic experiments should be provided to prove causality. This may take months or even years depending on the availability of huma tissues and resources.
The type of audience interested in this research are mainly translational scientists mainly in the field of genetic cardiomyopathies. Furthermore, the elucidation of the metabolic effects of genetic mutations on DCM evolution may be of interest in the field of heart failure in general.<br /> The focus of my research is genetic and molecular pathogenesis of cardiomyopathies.
-
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Referee #2
Evidence, reproducibility and clarity
I reviewed a paper by Luxan et al. describing EPHB4 variants as a novel disease gene for dilated cardiomyopathy (DCM).
The short report is interesting, however, not enough evidence is given to convince me EPHB4 is indeed a novel disease gene for DCM. More work is needed before this can be published.
Major points:
- Genetics: two individuals have EPHB4 variants together with DCM causing TTN tv or RBM20 variants. Which other DCM genes were excluded for the remaining four cases? GnomAD MAF of 0.008748404 suspiciously high.<br /> So overall the small case number makes it hard to judge whether these are truly pathogenic variants.<br /> Could the authors attempt co-segregation of DCM with EPHB4 variant in families?
- Only CADD tools was used for pathogenicity, several tools should be used. Is the structure solved? Structural predictions on the consequences of the variants should be done.
- The microscopy Figure 1C-E is not convicing. Only one sample shown while 6 were available/investigated. I would not be comfortable to identify cardiomyocytes/endothelial cells from these sections
- Functional work is needed to understand the interplay between EPHB4, CAV1 and CD36. Such as transfecting mutant EPHB4 into cells and probing for altered localisation/attachment of binding partners, most likely in endothelial - cardiomyocyte co-culture systems.
Minor points:
- Figure 1B does not make sense
- Statistics: Which tests were performed, if normality tests were applied, which one was used?
- Please do not use contractions, e.g. 'can't' in discussion section
Referees cross-commenting<br /> Overall I agree with the other reviewer on the points raised.
Significance
Description of EPHB4 as a novel DCM gene is of interest, but the current data are not convincing enough to make this statement.
Mechanistic work on the interplay of endothelial cells and cardiomyocytes and consequences of EPHB4 variants would make it a very compelling story.
-
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Referee #1
Evidence, reproducibility and clarity
Summary:
This research article describes genetic identification and expression analyses of six Ephrin type-B receptor 4 (EPHB4) variants identified in patients with dilated cardiomyopathy (DCM). Variants were identified Variants were identified in a cohort of 573 patients enrolled through the multicenter DZHK-TORCH (TranslatiOnal Registry for CardiomyopatHies) study and the Institute for Cardiomyopathies Heidelberg registry. Expression of downstream molecules, CAV1 and CD36, was assessed in human cardiac tissues by immunohistochemistry. EPHB4 cardiac expression was assessed using recently published single-cell/nucleus RNA sequencing data (Nicin et al 2022) incorporating siRNA-seq data from two other studies (healthy cardiac tissue, Litvinukova et al 2020) and (hypertrophic/aortic stenosis, Nicin et al. 2020).
Major Comments:
- Details of identified truncating RBM20 and TTN variants must be provided. These should be integrated into Table 1 alongside each co-occurring EPHB4 variant. List whether the TTN truncating variant is located in the A-band and whether these variants would be adjudicated as pathogenic/likely pathogenic, variant of uncertain significance by ACMG and/or similarly refined DCM criteria (Morales et al. 2020, Circ-Genom Precis Med).
- Discuss co-occurrence of multiple EPHB4 variants in two patients (DCM1, DCM3) and identification of 2 EPHB4 variants in more than one proband.
- Three of the six variants (p.Lys635Asn, Val113Ile, Glu890Asp) are classified as Clinvar Benign/Likely Benign. Additionally, p.Glu890Asp has been identified in 50 homozygotes in gnomAD non-Finnish European population. These data cast doubt on the pathogenicity of these variants. These classifications, as well as VUS classification of p.Pro79Leu, should be listed in Table 1. The authors should reconcile the benign/likely benign Clinvar classifications with their presented evidence for pathogenicity in the discussion.
- CD36 and CAV1 expression are not quantified. Qualitatively, it is difficult to confirm CD36 reduction in DCM and disruption in EPHB4 variant samples as imaging parameters are not specified and do not appear to be standardized across treatments. Clearly state (either in the figure legend or in the methods) whether identical imaging parameters were used across panels 1C-1E. Note any differences in these parameters.
- Why was EPHB4 membrane localization not assessed or reported?
- A key finding of the manuscript is that all six variants produce similar histological impacts on CAV1 and CD36 expression, denoting downstream impacts of EPHB4 genetic disruption. There is no granular data presented to support this claim. Additional discussion is also required to address how the authors anticipate variants in functionally distinct domains on either side of the plasma membrane to similarly impact downstream expression of CAV1/CD36. Mapping to available crystal structures in the Protein Data Bank (PDB) may be insightful to determine which variants may be most likely to have an impact on heterotetramer formation or to exert dominant negative effects on receptor function.
- Study limitations are not discussed and are significant. 5 of the 6 samples were from male patients, there are limitations to analyses of non-diverse patient ancestry, there is uncertainty regarding pathogenic contributions of variants in established DCM genes in 2/6 patients, data is limited to expression-only analyses highlighting need for additional functional modeling in cell or animal based systems.
- Language used in conclusions overstates study findings ["our results confirm a crucial role of the Eph-ephrin signaling pathway in DCM" (page 3), "this study not only confirms the crucial role of EPHB4 in the heart..." (page 8)]. Change to "suggest" or "support".
Major Methods Comments:
- DCM diagnostic criteria (clinical and imaging) for inclusion in the DZHK-TORCH study and the Institute for Cardiomyopathies Heidelberg registry should be stated or referenced. Likewise, describe and/or reference DCM exclusion criteria. State any relevant differences in DCM enrolment criteria for the two registries.
- Describe how the final cohort of 573 DCM patients was reached. (All patients with DCM in the DZHK-TORCH study/Heidelberg registry? All patients with available exome data meeting QC standards and having available cardiac tissue?).
- State whether any family/segregation data is available for these patients.
- Description of genetic testing methods are inadequate. Describe how genetic analyses were completed for each study/registry and how results were filtered/quality controlled. If sequencing methods were different across registries, state which patients were tested by which methods. If any testing was gene-targeted rather than whole exome/genome, list the specific DCM genes tested.
- Provide additional detail for human cardiac biopsies. Was the same chamber/tissue biopsied in all samples? Is an endomyocardial biopsy available for all 573 patients included in this study? If not, were additional EPHB4 variants identified in patients without biopsy samples?
- Describe the source of the healthy control biopsy, alongside brief clinical detail establishing suitability as a control. Did DCM controls carry variants in known DCM genes (including truncating variants in RBM20 or TTN)? How were DCM controls selected?
- List statistical analyses and associated experiments. (Page 5).
- List microscopes/equipment and software used to complete immunohistochemistry experiments. Describe imaging parameters to facilitate comparisons between treatments in Figure 1C-E.
- Please reword the following passage, which is almost verbatim to the same passage in Nicin et al. 2022.
Page 4<br /> "In brief, a combination of two human snRNA-seq datasets was used. Data from healthy cardiac tissue from the septum of 14 individuals in the Litvinukova et al. study and data from location-matched hypertrophic cardiac tissues from five patients with aortic stenosis."
Nicin et al. 2022 (https://doi.org/10.1038/s44161-022-00019-7)<br /> "Two human snRNA-seq datasets were used: data from healthy cardiac tissue from the septum of 14 individuals in the Litvinukova et al. study and data from location-matched hypertrophic cardiac tissues from five patients with aortic stenosis."
Minor Comments:
- Results: List source for Non-Finnish European Control cohort (gnomAD) (Page 5).
- Discussion: "all DCM patients" (page 6) requires clarification.
- Discussion: Define acronyms. CSF, IL4, LPS (Page 7)
- Table 1. Table is confusingly arranged. It would make more sense to organize the table by cDNA/AAchange to better correspond to Figure 1A. List the impacted protein domain for each variant in a separate column. It is also unclear how DCM allele frequencies were calculated as the reported number of patients (DCM1-6) carrying each variant do not universally correspond to the listed allele frequencies (see AFs of 0.0052 and 0.0208). Clarification should be added to the legend so it is clear to the reader how these frequencies were determined
- Figure 1B. Add variant labels. Indicate relevant p-values for each variant. It is unclear to which comparison the p = 0.024 belongs. State in legend that 2 variants were omitted (presumably due to absence from gnomAD)
- Figure 1E. Add label to indicate which EPHB4 variant is depicted.
Referees cross-commenting
As is, this manuscript is not ready for publication. Our comments are in complete alignment. Like the other reviewer, I also emphasize the need for other DCM genes tested to be listed. I also reiterate that any similarly worded passages to other published material must be corrected
Significance
This study presents genetic and expression data on a novel DCM gene candidate (EPHB4) from a European cohort of 573 DCM patients. This work is of interest as much of genetic DCM remains unexplained and identification of novel genes and pathways will be critical to advance understanding of the disease and to develop novel treatments. Reported data will be of greatest interest to cardiovascular practitioners and translational/basic researchers working with genetic heart disease/DCM. The fact that cardiac tissue was available for histological analyses for all six patients is an asset. There are considerable weaknesses to the paper, as written. There is a lack of detail in the included genetic methods and results. While the premise of the study is intriguing, additional detail is required for identified TTN and RBM20 truncating variants and additional discussion is needed to resolve confusion regarding reported allele frequencies and benign/likely benign Clinvar classifications. Because study design is restricted to genetic and expression analyses, reported data do not address possible pathogenic mechanisms. Overall, there is insufficient data presented to confirm a role for EPHB4 in causing DCM. Manuscript-specific (as-opposed to study specific) weaknesses include insufficient methods detail, a lack of clarity in the presented genetic and expression data (particularly Figure 1), insufficiently described study limitations, and overstated study conclusions. These scientific and manuscript issues will need to be addressed for the manuscript to be suitable for publication.
Reviewer fields of expertise: cardiovascular genetics, DCM.
Insufficient expertise to evaluate statistical methods.
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Reply to the reviewers
Revision summary.
Additional new data.
- CYPA expression levels in Scrm Vs KO Vs R55A isogenic cell lines as new Fig 1C.
- ATR signaling: western blot analysis of HU-induced p-CHK1 (S345) in Scrm, KO and R55A isogenic cell lines as new Suppl Fig 1B.
- MRN expression: western blot analysis of expression of NBS1, MRE11, RAD50 and MCM2 is Scrm, KO and R55A isogenic cell lines as new Suppl Fig 7A.
- NBS1 subcellular fractionation: western blot analysis of NBS1 from whole cell extract Vs cytoplasmic extract Vs nuclear extract comparing expression/distribution in Scrm, KO and R55A isogenic cell lines, as new Suppl Fig 7B.
- CYPA immunofluorescence (IF) staining on untreated and HU treated U2OS, as new Suppl Fig 7C.
- CYPA immunofluorescence (IF) staining on untreated and HU treated U2OS following pre-extraction, as new Suppl Fig 7D.
- DepMap Project Score Cancer Gene Dependency cell survival (“fitness”) following PPIA/CYPA-KO in breast carcinoma cell lines mapped against BRCA2 status, as a new Suppl Table 5.
- DepMap Project Score Cancer Gene Dependency cell fitness following PPIA/CYPA-KO in Neuroblastoma cell lines, as a new Suppl Spreadsheet 4.
- DepMap Project Score Cancer Gene Dependency cell fitness following PPIA/CYPA-KO in Multiple Myeloma cell lines, as a new Suppl Spreadsheet 4.
- DepMap Project Score Cancer Gene Dependency cell fitness following PPIA/CYPA-KO in Chronic Myelogenous Leukaemia cell lines, as a new Suppl Spreadsheet 4.
Revised and/or additional text.
The Abstract, Introduction, Materials & Methods, Results and Discussion have been amended as necessary, to facilitate the issues raised by the Reviewers.
Reviewer #1: We thank this reviewer for their understanding and appreciation of our CYPA study as espoused by their comprehensive summary of the content, importance, and potential implications of our work; “The manuscript presents clear and comprehensive data, demonstrating the profound impact of CYPA on DNA repair.” Furthermore, we very much appreciate their robust and complementary words regarding the significance of our work and its wide appeal; “The significance of this study is twofold: it adds a new layer to our understanding of DNA repair mechanisms and, importantly, it could point the way to novel therapeutic strategies for cancer. It will spark interest from molecular biologists to clinicians and pharmaceutical researchers.”
Query:
It's surprising to find that the loss of CYPA abolished HU-induced NBS1 foci, as the MRE11 interactive domain of NBS1 should remain intact in CYPA deficient conditions and the N-terminus of NBS1 is dispensable for ATM activation (Kim et al., 2017; Stracker and Petrini, 2011). A more detailed mechanistic explanation of this phenotype would be appreciated. The authors should check the subcellular localization of NBS1 and the stability of MRN in wildtype and CYPA KO cells. Additionally, including the kinetics of NBS1 foci formation using multiple timepoints in wildtype and CYPA KO cells after damage will further support the observation.
RESPONSE:
Regarding NBS1 foci formation, we note that rather than abolish HU-induced NBS1 foci formation, CYPA loss (through KO) and/or inhibition (through p.R55A) in fact results in a “…spontaneously elevated yet unresponsive amount of NBS1 foci/cells when compared to scrambled” (see original Fig 9A legend and associated Results section text). We have reinforced this observation in the revised Results section entitled ‘CYPA influences NBS1 and MDC1 foci formation’ and in the Discussion section. We do describe a kinetic impairment of RAD51 foci formation in the CYPA-engineered lines up to 16hrs post HU-treatment (Fig 6D). Our mechanistic working model is that CYPA interacts directly with NBS1 via a Pro residue within the short linking peptide between the FHA and BRCT1, and that this likely influences the relative dynamic positioning of the FHA with BRCA1-BRCT2, at least following acute HU treatment; replication fork stalling, likely biased towards ATR-dependent signaling initially, rather than that of ATM. The relative positioning of these functional domains can impact MRN function, and we discuss this possible mechanism in the section entitled ‘CYPA and the MRN complex’, with reference to the detailed structure-function analyses and complementary DDR activation models described by<br /> - Williams, R.S., et al., Nbs1 flexibly tethers Ctp1 and Mre11-Rad50 to coordinate DNA double-strand break processing and repair. Cell, 2009. 139(1): p. 87-99.<br /> and<br /> - Lloyd, J., et al., A supramodular FHA/BRCT-repeat architecture mediates Nbs1 adaptor function in response to DNA damage. Cell, 2009. 139(1): p. 100-11.<br /> and<br /> - Rotheneder, M., et al., Cryo-EM structure of the Mre11-Rad50-Nbs1 complex reveals the molecular mechanism of scaffolding functions. Mol Cell, 2023. 83(2): p. 167-185.e9.
The N-terminal FHA-BRCT region of NBS1 does indeed influence MRN recruitment and HRR execution, a point we highlight in the section entitled ‘CYPA influences NBS1 and MDC1 foci formation’, with reference to the seminal original observations of<br /> - Sakamoto, S., et al., Homologous recombination repair is regulated by domains at the N-<br /> and C-terminus of NBS1 and is dissociated with ATM functions. Oncogene, 2007. 26(41): p.6002-6009<br /> and<br /> - Tauchi, H., et al., The forkhead-associated domain of NBS1 is essential for nuclear foci formation after irradiation but not essential for hRAD50-hMRE11-NBS1 complex<br /> DNA repair activity. J Biol Chem, 2001. 276(1): p. 12-15.<br /> and<br /> - Zhao, S., W. Renthal, and E.Y. Lee, Functional analysis of FHA and BRCT domains of NBS1 in chromatin association and DNA damage responses. Nucleic Acids Res, 2002. 30(22): p. 4815-22.<br /> and<br /> - Cerosaletti, K.M. and P. Concannon, Nibrin forkhead-associated domain and breast cancer C-terminal domain are both required for nuclear focus formation and phosphorylation. J Biol Chem, 2003.<br /> 278(24): p. 21944-21951.
HU-unresponsive NBS foci (indicative of MRN dysfunction) and MDC1 foci formation are consistent with the DNA-R (i.e., DR-GFP reporter systems: Fig 3A-C and impaired RAD51 foci formation: Fig 6D) and resection-related phenotypes (Fig 6A-B) we report here and are also consistent with the relative resistance to HU-induced killing we report for CYPA-KO and CYPA-R55A cells (Fig 11A and as reported by Manthey, K.C., et al., NBS1 mediates ATR-dependent RPA hyperphosphorylation following replication-fork stall and collapse. J Cell Sci, 2007. 120(Pt 23): p. 4221-9).
At the reviewer’s request we include additional novel experimental data showing that MRN expression is stable and equivalent in control, CYPA-KO and CYPA-R55A cells (Suppl Fig 7A). We also provide evidence that NBS1 subcellular distribution (via extract fractionation) is not altered upon CYPA loss and/or inhibition (Suppl Fig 7B).
Query:
The authors showed that the interaction between CYPA and MRN didn't change after HU treatment. The authors should also include co-localization analysis of CYPA and NBS1 after HU.
RESPONSE:
At the reviewer’s suggestion we undertook a series of IF analyses concerning endogenous CYPA (i.e., +/- HU, +/- pre-extraction). We found that endogenous CYPA failed to form foci following HU thereby precluding CYPA-NBS1 foci co-localization analysis (Suppl Fig 7C-D).
Query:
The paper demonstrated that BRCA2 knockdown cells were sensitive to CsA. The authors should also examine CsA sensitivity in BRCA2 deficient cancer cells. In addition, the authors could elaborate more on their criteria for selecting cancers for CYPA inhibition, whether it is based on high genomic instability or an addiction to HRR for survival.
RESPONSE:
Despite repeated attempts we have been unable to successfully routinely culture the TNBC suspension line HCC1599 (BRCA2 c.4154_5572del1419 and p.K1517fs*23), consistent with its reported ~5 days population doubling time. Although not a tumour line per se, we also failed to effectively culture the FANC-D1 patient FB line HSC62 (BRCA2 c.8488-1 G>A (IVS19-1G>A)) to enable survival analysis. We provide new quantification analysis of the CsA survival on the H1299 conditional shBRCA2 line (Fig 11E). Additionally, we include a comprehensive new analysis of cell survival (“fitness”) of a range of breast carcinoma cell lines following PPIA/CYPA-KO, extracted from DepMap Project Score Cancer Gene Dependency portal (https://score.depmap.sanger.ac.uk/), and also specify the BRCA2 status of each line. Interestingly, we find that reduced BRCA2 copy number is more commonly associated with loss of fitness following PPIA/CYPA loss (Suppl Table 5). We also include similar cell line fitness datasets for each of the cancers for whom we demonstrate elevated sensitivity to CYPAi (i.e., Neuroblastoma, Multiple Myeloma and CML) (Suppl Spreadsheet 4). Fascinatingly, PPIA/CYPA loss clearly results in loss of fitness in most of these cancer cell lines. Collectively, these new independent comprehensive datasets support our argument that targeting CYPA in select cancer scenarios shows impact in the preclinical setting and may represent an effective new strategy.
The unifying features of the cancers showing elevated sensitivity to CYPAi are indeed high genomic instability, denoted by elevated RS and hence a dependency upon replication fork protection machinery. This would be consistent with the observed lethality of our CYPA-panel to shBRCA2, siXRCC3 and siRAD51C. The cancers are additionally characterised by aberrantly elevated HRR (i.e. an addiction to/dependency on HRR). This would be consistent with the observed lethality of our CYPA-panel to siCtIP, siRAD52, siXRCC3, and siRAD51C. At the Reviewer’s request we have reinforced and better clarified this point in the section Potential rational applications of CYPA inhibition in select cancers and in the Discussion.
Reviewer #2:
We thank this reviewer for their positive and supportive comments concerning our work; “Authors have quite conclusively explored the interaction between NBS1 and cyclophilinA as well as the putative proline residue important for this interaction.” We appreciate the constructive feedback concerning the range of consequences/impacts of CYPA impairment and we concur with their contention that “This manuscript will have broad interest from groups working on genomic stability, immunology as well as cancer therapy.”; a general view also voiced by Reviewer #1.
We do stress that whilst other prolyl isomerases have previously been linked to DNA repair (e.g., most notably the Parvulin family member PIN1), this is the first time that CYPA has been directly implicated in DNA repair, and the first time CYPA has been shown to directly interact with a known DNA-R protein (i.e. NBS1).
We believe that the comprehensive CYPA-BioID we describe is worthy of report and should serve as a very useful starting point for additional studies concerning CYPA biology, which is undoubtedly complex. The interactome will also function as a useful tool in helping dissect the clinically significant wider biological consequences of CYPA inhibition. Our interactome findings demonstrate that CYPA may influence DNA-R via multiple, and not necessarily mutually exclusive, routes. We do not argue that CYPA’s role in DNA-R is exclusively via NBS1/MRN. This is clearly demonstrated by our validation of CYPA interactions via co-IP with endogenous CYPA with proteins including PCNA, 53BP1, CHAMP1 and ILF2-3 complex (Fig 5). These are completely novel observations that furthermore reinforce the validity and efficacy of our experimental approach in leveraging the CYPA-BioID to provide new biological insight into this druggable prolyl cis-trans isomerase.
Query:
Authors show delayed S-phase transit along with reduced replication speed indicating replication stall. However, authors have not discussed how cyclophilinA might regulate replication (other than hypothesizing regarding altered dynamism of FHA-BRCT). It is conceivable that it could be an indirect effect on cellular metabolism or if authors believe it could be due to direct disruption to core replication machinery or signaling. In this regard, it will be helpful to see if there is shortening of (premature entry) G1 phase and comment on the status of the associated G1/S checkpoint.
RESPONSE:
The reviewer makes a very interesting and astute observation concerning the DNA replication phenotypes we report following CYPA loss and/or inhibition. The bases of these phenotypes are likely multifactorial, and we have revised the associated Discussion text to reflect this. Specifically, we highlight the elevated and unresponsive NBS1 and MDC1 foci seen in the CYPA-KO lines (Fig 9. i.e., persistent protein-DNA complexes) and dependence upon fork protection factors (XRCC3, RAD51C, BRCA2: Fig 11). We also report that a range of DNA replication factors are found in the CYPA-BioID (Fig 5A). Untangling the functional significance of these putative interactions would involve further study. Are they direct/indirect interactors? If direct, are they prolyl isomerase substrates or chaperone clients or regulated by liquid-liquid phase separation (LLPS)? Similarly, the CYPA-BioID throws-up an extensive set of RNA binding factors (Suppl Table 2), many of whom may conceivably contribute to the replication–transcription fork conflicts/collisions under conditions of CYPA-dysfunction. As this is the first comprehensive report of the cellular impacts of CYPA loss and inhibition, we thought it worth reporting the DNA replication associated phenotypes specifically to demonstrate the pleiotropic impact of loss and inhibition of this particular prolyl isomerase, to underscore its significance/importance. Although we have indeed found cell cycle phase transition impairments in our CYPA-KO and CYPA-R55A cells (for both G1-S and G2-M), these constitute additional studies requiring more thorough molecular-mechanistic characterization. We chose to focus on DNA repair for this first manuscript, as the CYPA-NBS1 interaction was the physical relationship for which we have assembled the most detailed and interconnected datasets, to-date. We do intend to pursue the cell cycle work as it too is derived from our CYPA-BioID (Suppl Spreadsheet 1), and we have already validated some of those relevant interactions by CYPA co-IP, but this is very much a work-in-progress. With this manuscript we’re endeavoring to tread a fine line by showcasing a wide range of cellular phenotypes resultant from CYPA loss and inhibition, but then also showing a deeper level of characterisation with at least one relevant interactor known to function in a range of DNA-R pathways wherein we’ve found impairments and dependencies.
Query:
In connection to this, it will also be interesting to see if the ATR/Chk1 signaling axis is intact in CYPA KO cells with or without additional DNA damage compared to WT.
RESPONSE:
At the reviewer’s request we include new data showing that HU-induced ATR-dependent CHK1 phosphorylation is normal in CYPA-KO and CYPA-R55A cells, and that ATR does not appear to be spontaneously activated in the absence of replication stress in these cells (Suppl Fig 1B).
Query:
Authors show that the P112 residue of NBS1 is important for the binding of cyclophilinA. What is the status of interaction among components of the MRN complex in CYPAKO cells and P112G NBS1? Further, what are the authors' thoughts on rescue experiments and whether P112G containing NBS1 to perform resection function.
RESPONSE:
We include new data showing normal expression of MRN components and normal subcellular localisation of NBS1 in the CYPA-KO and CYPA-R55A cells (Suppl Fig 7A-B). Regarding the interaction status of P112G, we show that this fails to co-IP endogenous CYPA when transiently expressed in HEK293 cells, in marked contrast to WT-NBS1 (Fig 8A). Furthermore, we show that ablation of another FHA Pro residue (P64) does not impair co-IP with endogenous CYPA under similar conditions, suggesting P112G is unique in this regard. Our recombinant protein interaction work demonstrates that CYPA-Step directly interacts with a HIS-(FHA-BRCT1) peptide and that P112G abolishes this interaction (Fig 8B). Regarding rescue experiments, we’ve found that stable overexpression of NBS1 can be neomorphic, resulting in resistance to certain DNA damaging agents, thereby complicating cell-based rescue analyses. We stress that along with our engineered KO and R55A (isomerase-dead) lines we have employed the well-known CYPAi Cyclosporin A (CsA) to reproduce several of the DNA-R related phenotypes (e.g., Fig 1, Fig 3, Fig 6, Fig 10, Fig 11). To further examine impacts upon resection specifically, a logical approach would be to engineer P112G into a full-length recombinant (baculoviral produced) human MRN complex for in vitro kinetic assessment using various labelled DNA substrates. But we think that this specialist and not insignificant undertaking is outside the scope of our report of the extensive cellular consequences of CYPA loss and dysfunction and it’s potential (pre)clinical significance with regards CYPAi repurposing.
Query:
What are the protein levels of MRN, RAD51 etc. in CYPAKO cells? It will be important control to delineate the effects of CYPA on global transcription and translation vs specific and direct effect on end-resection. Can overexpression of NBS1 rescue the observed resection and focus phenotypes?
RESPONSE:
Basal levels of RAD51 foci/cell are comparable between Scrm and both CYPA-KO and R55A cells (Fig 6D). We also find comparable levels of MRN components between these lines (Suppl Fig 7A). Importantly, we observe the pRPA/resection defect following an acute (up to 3hrs) treatment with CsA; conditions unlikely to grossly impair translation to an extent that would result in reduced expression of the relevant DNA-R proteins. Furthermore, microarray based transcriptomic analyses of these isogenic lines did not show evidence of a global impact upon transcription following CYPA-KO or R55A, nor was there evidence of reduced expression of any genome stability/DNA-R genes. We did not include this negative data so as to maintain the focus on the functional link with DNA repair.
Reviewer #3: This critically negative review is myopic, unbalanced, self-contradictory and frustratingly mis-represents some of our key findings. The dismissive tone of the text unnecessarily and unprofessionally crosses into the pejorative (“Either evidence is lacking or experiments were not performed in a convincing way”). The stark contrast between this review and the summations of Reviewer #1 and Reviewer #2 serve to highlight this hyper-negative approach.
It is very frustrating that this reviewer describes our findings as “…an interesting story…”, that “…the identification of NBS1 as a novel substrate of CYPA is significant” , that the “..manuscript may provide new insight…”, and that “…the role of CYPA in DNA repair is fairly well described using its inhibitor or KO cells”, and yet then concludes by stating “… the current manuscript suffers lack of evidence to support the main conclusion”. This is self-contradictory and unbalanced. Again, the contrast with Reviewer #1 and Reviewer #2 in this regard is stark.
Major critical theme no. 1.
Expression of CYPA-R55A: “…vastly different…”
RESPONSE.
This reviewer dismisses the entirety of the R55A model cell line work based upon the apparent “…vastly different…” expression levels of the reconstituted lines. This is an overstatement of the situation and notably not an issue for either Reviewer #1 or Reviewer #2. Nonetheless, we have replaced the original CYPA blot in Fig 1C with a clearer and more representative depiction of expression levels between the engineered lines and control. Importantly, the pRPA/resection work, siRAD52 and siXRCC3 dependency work were all corroborated/reproduced using the CYPA PPI inhibitor Cyclopsorine A (CsA). The plurality of our complementary approaches showing the influence of CYPA upon DNA-R is minimised and/or ignored by this Reviewer. Although not shown in this study, we find that the R55A cells are selectively sensitive to DNA cross-linker melphalan, in contrast to the CYPA-KO cells. Although we don’t yet understand the basis of this observation, this clearly indicates that R55A expression is a valid model in our hands and is not a like-for-like mimic of CYPA-KO simply because of reduced expression. We appreciate the reviewer could not know this.
Major critical theme no. 2.
CYPA-NBS1 work: “Another major concern is that the evidence to support that NBS1 is the major substrate of CYPA is lacking since all the experiments were performed with the CYPA mutant or CsA treatment.”
RESPONSE:
We do not claim that NBS1 is ”… the major substrate of CYPA.” . We do not claim that all the DNA-R deficits we have identified are specifically a consequence of impaired NBS1 function. These are misrepresentations of our findings and how we’ve presented and discussed them. This Reviewer ignores our comprehensive CYPA-BioID, and specifically our discussion pertaining to the DNA-R and Replication factors found therein (section entitled ‘CYPA Interacting protein partners’ and Fig 5A). We explicitly discuss the fact that “A recurring theme amongst these CYPA interactors is that all are involved in end-resection” whilst also demonstrating CYPA co-IP with 53BP1, CHAMP1 and ILF2-3 (Fig 5C-E). In the ‘Discussion’ section we describe a “homesostatic role for CYPA in genome stability”, including possible contributions to controlling LLPS of well-known DNA-R factors and the fact that several mitotic, kinetochore, centrosomal and spindle proteins are found in the CYPA-BioID.
Major critical theme no. 3.
A major repeated criticism levelled by this reviewer as a basis for dismissing the entirety our findings is that we have failed to demonstrate that the catalytic activity of CYPA is required for DSB repair.
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Their conclusion should be supported by additional key experiments to prove that the catalytic activity of CYPA is indeed required for DSB repair…
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Another major concern is that the evidence to support that NBS1 is the major substrate of CYPA is lacking since all the experiments were performed with the CYPA mutant or CsA treatment.
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One major weakness of this study is that it focuses on characterizing the interaction between CYPA and NBS1, then jumps into a conclusion that the catalytic activity of CYPA is required for DSB repair based on its direct interaction with NBS1
RESPONSE:
As this criticism is repeated, the impression created, and no doubt intended, is that the manuscript is irreparably flawed (“…major weakness…”). This is an over-simplification and a misdirection. It’s notable that this critique isn’t raised in such a manner by either Reviewer #1 or Reviewer #2. This is likely because any modest inferences we made concerning the possible role of CYPA catalytic isomerase activity were based on a combination of differing but complementary approaches. Firstly, we routinely used the p.R55A engineered CYPA variant, although this Reviewer regards our use of this as invalid. This longstanding peptidyl prolyl isomerase (PPI)-dead mutant model has frequently been employed to invoke the catalytic function of CYPA. The mutant was originally proposed and characterized as catalytically-dead using the in vitro chymotrypsin-coupled prolyl isomerase assay using N-succinyl-AAPF-p-nitroanilide as a substrate as far back as 1992 (Zydowsky, L.D., et al., Active site mutants of human cyclophilin A separate peptidyl-prolyl isomerase activity from cyclosporin A binding and calcineurin inhibition. Protein Science, 1992. 1(9): p.1092-1099). In addition, we routinely use Cyclopsorin A (CsA), the longstanding clinically relevant CYPA PPI inhibitor, and we also use a different and more potent CYPA PPI inhibitor, namely NIM811 (N-methyl-4-isoleucine-cyclosporine) for the DR-GFP reporter assays of individual DNA-R pathway function (i.e.’ NHEJ, HRR and SSA).
With regards to our findings concerning CYPA-NBS1 interaction, in the Discussion section we clearly state that mechanistic analyses of prolyl isomerase on the dynamism of NBS1 FHA-BRCT would require specialist approaches outside the scope of this manuscript, as the manuscript is firmly within the realm of cellular biology. This is ignored by this Reviewer. Specifically, we state that “A regulated cis-trans isomerisation of the E111-P112 peptide bond could conceivably dynamically alter the relative positioning of the FHA domain with the tandem BRCTs of NBS1 (Fig 7C-D). This may then impact on these domains’ abilities to dynamically interact with their respective phospho-threonine (for FHA) and phospho-serine (BRCT) containing targets, consequently likely shaping/impacting NBS1 recruitment dynamics and/or plasticity of its interactome [120-122]. Demonstrating this hypothesis would require additional structural analysis using techniques such as 2D-NMR which is outside the scope of this manuscript.”
Minor comments: 1.
Fig. 1E; is the survival between KO and R55A statistically significant? If so, do the authors have an explanation? Why is the reconstitution of R55A more toxic than KO alone?
RESPONSE:
Yes, R55A is slightly more sensitive compared to KO for this endpoint. The irony that this observation runs contrary to the Reviewer’s dismissal of the R55A model line is not lost on us (Major critical theme no. 1). As is well-known for PARP1, inhibition is not equivalent to absence. A possible speculative explanation is that the R55A isomerase-dead could have additional dominant impacts compared to the KO situation. Nonetheless, we suspect this Reviewer would object to such speculation in the absence of ever more data.
Minor comments: 2.
In Fig. 3D, the NHEJ activity of CsA- or NIM811-treated cells is significantly downregulated in comparison to control, which raises the possibility of the pleiotropic effect of CYPA inhibition. The authors should discuss this issue.
RESPONSE:
Not necessarily indicative of a pleiotropic effect if one accepts that absence of a protein is not always biologically equivalent to the presence of an inhibited version the same protein. Of note, we do see somewhat reduced NHEJ following siCYPA (Fig 3A), something not mentioned by this Reviewer. Furthermore, we explicitly discuss and show interaction between CYPA and 53BP1, CHAMP1 and ILF2-3 complex, all players in NHEJ and in the intricate balance between NHEJ and resection-mediated recombination directed repair pathways.
Minor comments: 3.
In Figure 8A, since the expressions of Flag-NBS1 WT, P112G, and P64G are very different, the conclusion that the isomerization of CYPA is essential for NBS1 cannot be supported. Given the variation of input levels, it appears that the P64G mutation actually enhances the interaction with endogenous CYPA. Is this reproducible? This co-IP result may need to be quantified from independent sets for statistical analysis.
RESPONSE:
We do not claim that “…isomerization of CYPA is essential for NBS1…”. Fig 8A data is derived from a transient transfection. Whilst there is some variation in expression, we do not make any precise quantitative conclusions from these co-IPs. Nonetheless, FLAG-NBS1-P112G clearly interacts less with endogenous CYPA in this system. Importantly, and ignored by this Reviewer, the associated recombinant protein work shown in Fig 8B clearly confirms that NBS1-P112G is profoundly compromised in its ability to interact with CYPA.
Minor comments: 4.
A defect in DSB repair generally hypersensitizes cells to DNA replication stress, including HU. In this regard, resistance of the CYPA KO (or R55A cells) to HU is interesting, but it may be due to the nonspecific effect of the CYPA loss in multiple DNA damage signaling and repair processes. Alternatively, cell cycle may be affected nonspecifically, rendering cells resistant to replication-associated genotoxic stress. This needs to be addressed further. Analysis of overall cell cycle profile may be required.
RESPONSE:
Resistance to HU is likely multifactorial and cell cycle transition kinetics may be relevant here. That is why we linked the DNA replications phenotypes to this discussion in the section entitled “Impaired CYPA function reveals novel genetic dependencies/vulnerabilities”. A comprehensive analysis of cell cycle profile and phase transits is outside the scope of the current manuscript (see response to Reviewer #2).<br /> Impaired HU-induced pRPA has been linked to HU-resistance via NBS1 previously: Manthey, K.C., et al., NBS1 mediates ATR-dependent RPA hyperphosphorylation following replication-fork stall and collapse. J Cell Sci, 2007. 120(Pt 23): p. 4221-9.
Minor comments: 5.
Text not to mention Abstract is too dense. The manuscript will benefit a lot from extensive editing and rearrangement of figures to make the story more succinct for journal submission.
RESPONSE:
The Reviewer’s view concerning a lack of succinctness is not shared by Reviewer #1 and Reviewer #2. We have endeavored to draft a concise and accessible manuscript, the main body of which comes in at just over 23x sides of A4 (including Materials & Methods). Considering we guide the reader through 12x multipart figures, 5x supplementary tables and 8x supplementary figure, we believe we have achieved succinctness. Nonetheless, we will of course take direction from the appropriate journal editorial team regarding house style and format.
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Referee #3
Evidence, reproducibility and clarity
In this manuscript, O'Driscoll and colleagues identify the role of cyclophilin A (CYPA), a peptidyl-prolyl cis-trans isomerase, in promoting DNA repair. They propose that the catalytic activity of CYPA is required for the action of the MRE11-RAD50-NBS1 (MRN) complex and thus double-strand break (DSB) repair. This study originated from their previous finding that cyclosporin A (CsA) induces replication-associated DNA breakage and genome instability in LIG4 syndrome patient fibroblasts. As CsA is an inhibitor of the CYPA, the authors reasoned that the negative effect of CsA in DNA repair results from its inhibition of CYPA and presumably its essential downstream substates in DNA repair. Using CRISPR/Cas-based U2OS knockout cells, they showed that the catalytic activity of CYPA is necessary for homology-directed repair. Series of BioID-proximity interactome analysis, biochemical studies (e.g., co-immunoprecipitation), and AIphaFold-derived structural determination revealed that CYPA directly interacts with the MRN complex, specifically through the Pro112 of NBS1, and its catalytic activity is required for damage-induced NBS1 foci formation, which all together led to the conclusion that the MRN complex is a direct substrate of CYPA and that CYPA controls DNA end resection and DSB repair via isomerization of NBS1.
This is an interesting story as it reveals a new role of prolyl isomerization, which is mediated by CYPA, in promoting DSB repair. The identification of NBS1 as a novel substrate of CYPA is significant, and the manuscript may provide new insight into how prolyl isomerization of NBS1 regulates the function of the MRN complex that is engaged in DNA end resection during DSB repair. However, the authors' major claim that CYPA controls DSB repair via the MRN complex is not substantiated by the data provided at its current form. Either evidence is lacking or experiments were not performed in a convincing way. Their conclusion should be supported by additional key experiments to prove that the catalytic activity of CYPA is indeed required for DSB repair and NBS1 is a major substrate of CYPA, through which CYPA regulates DNA end resection at the stalled DNA replication fork.
Major comments
- The authors reconstituted the CYPA knockout (KO) cells with WT or a catalytic mutant (R55A) for the structure-function analysis. However, re-expression levels of CYPA are vastly different between WT vs. R55A, R55A being expressed at much lower levels (not near to endogenous CYPA) (Fig. 1C). Consequently, the loss-of-function phenotypes of R55A may be simply explained by its inadequate reconstitution, thus failing to complement KO phenotypes. For instance, the lack of pRPA2 S4/S8 induction in R55A cells may be just due to the insufficient expression of R55A, thus resulting in the same phenotype as KO. Additionally, the R55A cells were compared to parental cells, not to the WT-reconstituted cells for the majority of functional analysis, so it is not clear whether WT is able to complement the KO phenotype in their system (Figs. 1, 2, 6, 9, 10, and 11). Whether the catalytic activity of CYPA is indeed responsible for the phenotypes of DNA repair deficiency is not supported. The authors should compare the phenotypes between WT- vs. R55A-reconstitued cells side-by-side for the key experiments. Ideally, expression of WT and R55A should be similar in KO cells to exclude the possibility that the R55A phenotypes merely result from insufficient mutant expression rather than true loss of catalytic activity.
- Another major concern is that the evidence to support that NBS1 is the major substrate of CYPA is lacking since all the experiments were performed with the CYPA mutant or CsA treatment. Whether the NBS1 P112G isomerization-defective mutant indeed exhibits a defect in DNA repair similarly to the CYPA mutant is not shown. For instance, one key experiment would be to test whether the P112G mutant fails to form damage-inducible NBS1 foci formation.
- In Figure 7A, the authors showed that the interaction between CYPA and NBS1 is dependent on the isomerization activity of CYPA. It should be checked whether the CYPA R55A mutant fails to interact with NBS1 in contrast to WT to support the main conclusion that NBS1 is controlled by the isomerization activity of CYPA.
- OPTIONAL) One major weakness of this study is that it focuses on characterizing the interaction between CYPA and NBS1, then jumps into a conclusion that the catalytic activity of CYPA is required for DSB repair based on its direct interaction with NBS1. How the isomerization of NBS1 affects its localization, stability, and/or function is not addressed. At its current form, the functional link between NBS1 isomerization and stalled fork processing is weak. Elucidating how the catalytic activity of CYPA controls the action of the MRN complex via the isomerization of NBS1 will add significant impact on the manuscript. Otherwise, the story fails to fully support the description of its title.
Minor comments
- Fig. 1E; is the survival between KO and R55A statistically significant? If so, do the authors have an explanation? Why is the reconstitution of R55A more toxic than KO alone?
- In Fig. 3D, the NHEJ activity of CsA- or NIM811-treated cells is significantly downregulated in comparison to control, which raises the possibility of the pleiotropic effect of CYPA inhibition. The authors should discuss this issue.
- In Figure 8A, since the expressions of Flag-NBS1 WT, P112G, and P64G are very different, the conclusion that the isomerization of CYPA is essential for NBS1 cannot be supported. Given the variation of input levels, it appears that the P64G mutation actually enhances the interaction with endogenous CYPA. Is this reproducible? This co-IP result may need to be quantified from independent sets for statistical analysis.
- A defect in DSB repair generally hypersensitizes cells to DNA replication stress, including HU. In this regard, resistance of the CYPA KO (or R55A cells) to HU is interesting, but it may be due to the nonspecific effect of the CYPA loss in multiple DNA damage signaling and repair processes. Alternatively, cell cycle may be affected nonspecifically, rendering cells resistant to replication-associated genotoxic stress. This needs to be addressed further. Analysis of overall cell cycle profile may be required.
- Text not to mention Abstract is too dense. The manuscript will benefit a lot from extensive editing and rearrangement of figures to make the story more succinct for journal submission.
Referees cross-commenting
I agree with concerns on the pleiotropic effect of CYPA KO, which exhibit many distinct phenotypes in DNA repair and replication fork stability.
Significance
While establishing a new link between CYPA-dependent prolyl isomerization and DSB repair is significant, the current manuscript suffers lack of evidence to support its main conclusion. Specifically, although the role of CYPA in DNA repair is fairly well described using its inhibitor or KO cells, whether its isomerization activity is indeed essential and whether NBS1 is the major target for its action in DSB repair is not clear. Existence of many other targets cannot be excluded. Whether the role of CYPA is specific to replication-associated DSB repair processes or can be generally applicable to homologous recombination in any DSB repair is not shown. The role of MRN in stalled fork processing and in response to DSBs could be different, but how CYPA would modulate these distinct processes is not addressed. As such, the manuscript is targeting more specialized audience, but if the link between CYPA and the MRN complex can be further elaborated, including how isomerization affects the function of NBS1 (e.g., using the isomerization-defective NBS1 mutant), it could reach out to broader readership.
My field of expertise includes DNA replication stress and replication-associated repair processes including stalled fork processing and recovery. I am familiar with most of the genetic, cellular, and biochemical experiments presented in the manuscript. I do not have significant expertise on the structural analysis of protein-protein interactions.
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Referee #2
Evidence, reproducibility and clarity
The current manuscript by Bedir et al. explores the role of cyclophilin A in DNA repair, particularly homologous recombination. Authors show that the absence of cyclophilin A or loss of PP1 activity affects end-resection via direct interaction with NBS1. Authors have conducted a series of experiments to confirm their findings. While the findings are interesting, further discussion/ experiments mentioned below will perhaps assure readers with respect to pointed direct vs consequence facilitated indirectly through global cellular effects of CYPA.
- Authors show delayed S-phase transit along with reduced replication speed indicating replication stall. However, authors have not discussed how cyclophilinA might regulate replication (other than hypothesizing regarding altered dynamism of FHA-BRCT). It is conceivable that it could be an indirect effect on cellular metabolism or if authors believe it could be due to direct disruption to core replication machinery or signaling. In this regard, it will be helpful to see if there is shortening of (premature entry) G1 phase and comment on the status of the associated G1/S checkpoint.
- In connection to this, it will also be interesting to see if the ATR/Chk1 signaling axis is intact in CYPA KO cells with or without additional DNA damage compared to WT.
- Authors show that the P112 residue of NBS1 is important for the binding of cyclophilinA.
- What is the status of interaction among components of the MRN complex in CYPAKO cells and P112G NBS1? Further, what are the authors' thoughts on rescue experiments and whether P112G containing NBS1 to perform resection function.
- What are the protein levels of MRN, RAD51 etc. in CYPAKO cells? It will be important control to delineate the effects of CYPA on global transcription and translation vs specific and direct effect on end-resection. Can overexpression of NBS1 rescue the observed resection and focus phenotypes?
Significance
Current study highlights the role of cyclophilin A or in large peptidyl-prolyl cis- trans isomerases activity in DNA repair. Although this is not the first study showing the relevance of cyclophilin A in DNA repair, they do highlight its role in homologous recombination and DNA repair. Authors have quite conclusively explored the interaction between NBS1 and cyclophilinA as well as the putative proline residue important for this interaction.
One of the drawbacks of the study is the pleotrophic effects of CyclophilinA. This needs to be at least discussed. Authors themselves observe induction of DSBs, replication stall, reduced NHEJ, SSA as well as HR efficiencies. Taken together, the effects of CyclophilinA even on resection could be a combination of both direct and indirect effects.
This manuscript will have broad interest from groups working on genomic stability, immunology as well as cancer therapy. I have expertise in NHEJ, mammalian replication and replication-stress response.
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Referee #1
Evidence, reproducibility and clarity
In this manuscript, the authors reveal a previously unexplored role of CYPA in DNA repair, particularly in the context of cells sensitive to the CsA. The authors' multi-faceted approach involved using CRISPR/Cas9-engineering, siRNA, BioID, co-immunoprecipitation, and specific DNA repair investigations. They suggest that CYPA, through its PPI activity, plays an active role in DNA repair, specifically in DNA end resection. They also demonstrate that inhibition or loss of CYPA results in impaired HRR following DNA replication fork stalling. Furthermore, the authors associate the loss and inhibition of CYPA with certain genetic vulnerabilities, suggesting potential therapeutic applications by exploiting CYPA PPI inhibition to selectively target cancer cells with characteristic genomic instability.
The manuscript presents clear and comprehensive data, demonstrating the profound impact of CYPA on DNA repair. It would be suitable for publication after addressing the following points:
- It's surprising to find that the loss of CYPA abolished HU-induced NBS1 foci, as the MRE11 interactive domain of NBS1 should remain intact in CYPA deficient conditions and the N-terminus of NBS1 is dispensable for ATM activation (Kim et al., 2017; Stracker and Petrini, 2011). A more detailed mechanistic explanation of this phenotype would be appreciated. The authors should check the subcellular localization of NBS1 and the stability of MRN in wildtype and CYPA KO cells. Additionally, including the kinetics of NBS1 foci formation using multiple timepoints in wildtype and CYPA KO cells after damage will further support the observation.
- The authors showed that the interaction between CYPA and MRN didn't change after HU treatment. The authors should also include co-localization analysis of CYPA and NBS1 after HU.
- The paper demonstrated that BRCA2 knockdown cells were sensitive to CsA. The authors should also examine CsA sensitivity in BRCA2 deficient cancer cells. In addition, the authors could elaborate more on their criteria for selecting cancers for CYPA inhibition, whether it is based on high genomic instability or an addiction to HRR for survival.
Significance
The significance of this study is twofold: it adds a new layer to our understanding of DNA repair mechanisms and, importantly, it could point the way to novel therapeutic strategies for cancer. It will spark interest from molecular biologists to clinicians and pharmaceutical researchers.
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Reply to the reviewers
Reviewer #1 (Evidence, reproducibility and clarity (Required)):
Redhardt and colleagues describe a structure of the voltage and Ca-activated Slo1 channel in complex with an auxiliary subunit, γ1. In complex with γ1, Slo1 adopts an open state that closely resembles previous open state structures. Of γ1, only the single membrane-spanning helix, which binds to the periphery of the Slo1 VSD, is resolved. There, it establishes several interactions with Slo1 that authors propose may favor adoption of the open state, potentially explaining how γ1 can shift I-V profile of Slo1 to be activated at more negative membrane potentials. The interactions described fit well with existing mutagenesis analyses.
While this report provides a first glimpse of how γ1 can bind to Slo1, its impact will be minimal. It describes a single structural snapshot and there are no functional analyses presented. Additional analyses would be helpful in understanding of how γ1 can regulate Slo1 channels.
We thank the reviewer for their honest judgment. We agree that validating the structure by biochemical and/or functional data would have significantly strengthened the manuscript. However, we are convinced that our structural data alone already provides significant novel understanding of the assembly of the Slo1-γ1 complex and regulation of Slo1 by γ1. Thus, we feel that publication of this manuscript is justified by the high importance of Slo channels and our data will have an impact in the field.
__Major comments: __ 1. The authors propose several models for how γ1 regulates Slo1, yet none of them are experimentally evaluated. For example, on page 8, it is written that "we propose that the combination of three different principles, namely shape complementarity, covalent anchoring and lowering the resting state potential by a positively charged intracellular stretch, act in concert to stabilize an active VSD conformation in the Slo1-γ1 complex." This is a testable hypothesis and one that should be experimentally evaluated to better understand regulation by γ1.
We agree with the reviewer that experimental validation of this hypothesis would have been an asset. Nevertheless, we think that our structural data in context of previous functional data e.g. from Li et al. 2015,2016) and also in comparison with the other two manuscripts on the same topic which have been published while this manuscript was under review, allows us to draw conclusions about the mechanism of γ1-mediated activation of Slo1. We have now, however, toned down some of the earlier statements and changed parts of our interpretations in light of the novel findings by Yamanouchi et al. and Kallure et al.
The authors analysis of the extracellular domain of γ1 is incomplete. The only presented structure was performed with C4 symmetry imposed, in which extracellular domains were largely lost. The authors propose that these domains are dynamic and that their dynamism would enable simultaneous binding of both γ and b subunits, as occurs in cells. A more thorough analysis of the dynamics and well as potential asymmetric conformations should be performed to better understand how these domains interact with Slo1.
We completely agree with the reviewer that a thorough analysis of the extracellular domain is important and thank the reviewer for their valuable suggestions. We had attempted such analysis already from the beginning, but were not successful. More specifically, we have attempted reconstructions with lower symmetry (C2 and C1) from the beginning or by symmetry relaxation after initial C4 reconstruction. Also, we tested different masking and signal subtraction strategies in combination with different global and local refinements, as well as symmetry expansion and 3D classification. Unfortunately, none of these strategies led to a better resolved LRR module.
We now think that in comparison with Kallure et al. and Yamanouchi et al., the ice in our sample was thinner, which allowed us to reach higher resolution in the core particle (Slo1 and γ1 TM helix), but at the cost of the γ1 LRRs being denatured or at least distorted by the air-water interface.
The refinement statistics suggest that the model was incompletely refined. This reviewer was not provided with the map or models, but the validation report lists a clashscore of 9 and 5.7% of the rotamers as being outliers, both of which are high for the reported resolution of the structure. It is also strange that the Q-score varied between different γ1 protomers. Why are the four protomers not identical when the map is 4-fold symmetric? The authors should carefully inspect their model to insure that it is as correct as possible.
We thank the reviewer for pointing this out, and while the values for clashscores and rotamers were not outside the range of values typically found in many other cryo-EM structures, we agree that there was still some room for improvement. We have worked on this and could lower the values to a clashscore of 7.0 and 1.8 % rotamer outliers.
The difference in Q-score is also something not too uncommon since, while the map is indeed C4-symmetric, during model refinement the NCS restraints are not completely preventing small deviations between the protomers. We have now also successfully attempted to minimize these differences further.
Reviewer #1 (Significance (Required)):
The impact of this report is limited. Functional analyses will be necessary to uncover precisely how gamma subunits regulate Slo1 channels.
We thank the reviewer for this honest statement, but respectfully disagree. While additional functional analyses would have certainly boosted the impact, we are certain that our structural data and their interpretation will be very valuable for the field, because they provide (as stated by Reviewer 3) new insights into the regulation of Slo channel activity by the γ subunits and suggest (as stated by reviewer 2) a novel mechanism of activation of voltage-gated ion channels..
Reviewer #2 (Evidence, reproducibility and clarity (Required)):
Summary This study presents a high resolution cryo-EM study of a voltage-gated Ca++-dependent K+ channel in the presence of a gamma1 subunit. Analysis of the structure and sequence alignments suggest a novel mechanism of activation of voltage-gated ion channels.
__Major comments __ The major issue in this paper is that it is only a structural biology paper. There is no structure-function relationship study, no functional studies of mutants that could validate -or not- the inferred underlying mechanism. Even though the authors have identified good candidates for mutations (e.g. p. 6) they have not attempted to validate their importance experimentally. As a result, reading their discussion is somewhat frustrating and full of assumptions, as indicated by sentences (p.7) like
"a possible mechanism... might be... which would make... more likely".
"... which might act ... seems important... might indicate... might lower... likely most pronounced... could be responsible..."
"... might play an important role... does not allow a certain conclusion..."
We completely agree with the reviewer that the paper would have been much stronger if we would have been able to perform biochemical or functional assays testing mutations in the binding interface. However, this would have unfortunately been beyond the scope of the project. We are nevertheless confident that our structural data will be of value for the field, also in context of the two structure-function papers that have been published since which confirm and validate our data and provide the link to function.
__Minor comments which could be confidently addressed __ The Introduction contains no description of the state-of-the-art in the field concerning the available structures in the same system or similar ones. Hence, it is difficult to judge for people outside the field if the novelty. is incremental or significant.
We have adjusted the introduction to explicitly mention previously published structural data on the Slo channels.
References 10 and 42 (eLife) lacj some details.
We have adjusted said references accordingly.
__Reviewer #2 (Significance (Required)): ______
Significance general assessment As it turns out, at least two papers in exactly the same field just appeared: -one in Molecular Cell by a Japanese group, which is much more developed and contains functional tests and structure-function relationships, in addition to beautiful structures (available on-line early December) https://www.sciencedirect.com/science/article/pii/S1097276523009218
-one in biorxiv, deposited yesterday https://www.biorxiv.org/content/biorxiv/early/2023/12/20/2023.12.20.572542.full.pdf
Advances wrt known results See above. As a result of these new papers in Mol Cell and biorxiv, I think the authors should reconsider submitting their article elsewhere, perhaps for a more specialized audience.
We agree with the reviewer that in light of the other two publications which both were published a while after we deposited our preprint on biorxiv and while the manuscript was under review, the uniqueness of our data is somewhat lowered. However, since our data is overall in large agreement with these two other publications, but we report a structure at significantly higher resolution and from a different species (indeed the first Slo1 structure from rabbit, a model organism of BK channel characterization in the last decades), we are confident that our data are still very valuable for the field and qualify for publication in one of the affiliate journals of Review Commons. After all, the fact that three papers reporting very similar data were published within a few weeks (plus another preprint reporting structures of a Slo channel, but unrelated to γ subunits) illustrates the importance for understanding the regulation of this essential ion channel and the impact of all structural data enhancing this understanding, and independent confirmation by three different labs is something very valuable to the community.
Reviewer #3 (Evidence, reproducibility and clarity (Required)):
"This manuscript by Redhardt et al. presents the cryo-EM structure of the Slo K+ channel from rabbits in conjunction with its auxiliary subunit, γ1, and proposes a mechanistic model for regulating channel activation. "This manuscript by Redhardt et al. presents the cryo-EM structure of the Slo K+ channel from rabbits in conjunction with its auxiliary subunit, γ1, and proposes a mechanistic model for regulating channel activation. The Slo channel, also known as the large-conductance calcium-activated potassium channel or BK channel, is an ion channel type found in various cell membranes, including neurons, muscle cells, and other tissue types. Its key features encompass Ca2+ activation, voltage dependence, and regulation by auxiliary subunits. Different auxiliary subunits have been shown to modulate channel functions distinctly; notably, the γ1 subunit enables channel activation at lower voltages compared to the wild-type channel. This manuscript offers a structural-functional framework that enhances our comprehension of how Slo channels are regulated by auxiliary subunits, such as gamma and beta subunits. While the structure of Slo channels in complex with the beta subunit is understood, the binding and interaction of the gamma subunit with the channels remain elusive due to the absence of corresponding structures. Along these lines, the presented structure here indeed provides new insights into the regulation of Slo channel activity by the gamma subunit. However, there are some important questions below that should be addressed."
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In Figure 1D panel, the calcium ions appear to be indistinct, likely due to the figure's low resolution. The authors are recommended to enhance the figure quality and consider a better positioning to effectively illustrate the ions.
We have adjusted the coloring of calcium ions Fig. 1D to increase their visibility.
It would be beneficial for the readers if the authors provided detailed methodology explaining how they arrived at the 7% and 11% coexpression, aiding in the complex formation. Additionally, it would be informative to know the observed shift in the size exclusion chromatography (SEC) profile of Slo1-Y1 compared to apo Slo1.
We have arrived at these concentrations of the respective viruses by empirically testing ranges between 3 % and 15 %. We have now added a sentence to the manuscript to explain this.
Is there any rationale behind initially purifying using strep affinity followed by His affinity?
The idea behind using a dual-affinity protocol is to ensure that all purified complexes contain at least one copy of Slo1 and one copy of γ1. Using the Strep tag first allows to remove most contaminants already in the first step, due to its higher specificity compared to the His tag. We have added a sentence to the methods section to explain this.
Regarding the Slo1 tetramer with gamma subunit binding, are there other classes where one, two, or three gamma subunits are bound to Slo1? Or is there only one class where all protomers of Slo1 are occupied by the gamma subunit? How do these classes appear when refined in C1 symmetry? Are there classes displaying C1 or C2 symmetry, or is the four-fold symmetry preserved across all refined classes?"
We exclusively observe complexes with four γ1 subunits. This is also in agreement with the other two recent publications reporting Slo1-γ1 complex structures, but could in principle be an artifact of artificial overexpression. Also when we refine the particles in C1, we retain C4 symmetry and do not observe any classes with C2 or C1 symmetry.
The authors utilized nearly 1.9 million particles to reconstruct the final class, resulting in a high resolution. Is such a large number of particles truly necessary to achieve high resolution in this context?
The large number of particles is not strictly necessary, i.e. we could obtain similar quality by using fewer particles. In the end, we have now further classified down to ~827k particles, which very slightly improved the resolution and quality of the map.
Authros mentioned that F273 of γ1 forms pi-stacking interactions, it remains unclear with which components of the channel these interactions occur.
F273 forms (slightly distorted) T stacking interactions with F164 in S2 and F187 in S3. We now changed the sentence in the manuscript to mention the residues that line the hydrophobic pocket to make it more clear which elements contribute to the interaction with F273.
The authors propose that the disulfide bond between the γ subunit and Slo1 could play a crucial role in their interaction. Was there any observation of a covalent linkage in SDS page analysis? Furthermore, how would this interaction be affected if either cysteine C253 of gamma1 or C141 on the channel were mutated or neutralized?"
We have run all our SDS-PAGE experiments under reducing conditions, thus destroying any disulfide bridges that might have been present in the complex. We have now, however obtained a slightly better defined reconstruction (as pointed out in our answer to point 5 raised by this reviewer) where we do not see as clear continuous density anymore between the two cysteine side chains. Thus, we have removed the cystine bond from the final model and have adjusted text and figures accordingly. We still think that it might be more than coincidence that those two side chains come into such close proximity, though, and still discuss the possibility of a cystine bridge in the manuscript.
Author's state that "The presence of several immobile positive charges on the intracellular side in close proximity to the VSD as in the case of the Slo1-γ1 complex is likely to locally lower the resting state potential and repulse the gating charges, thereby reducing the energy to overcome for the VSD to transition to the active conformation." Authors need to be little more elaborative here as it is not clear what authors mean repulse of gating charges.
We have expanded our description of the proposed repulsive effect of the positive charges in the manuscript and in addition also discuss the additional role of the charges in stabilizing the Ca2+-bound conformation of the gating ring as proposed by Yamanouchi et al.
Probably beyond this study but I was wondering whether it is possible that Beta and gamma subunit can together assemble as heteromers to form a cage-like structure with contribution from both.
We agree with the reviewer that this is an interesting question which we have also thought about and one which should be tested, but as the reviewer already mentioned, this would go beyond the present study and should be subject to an independent follow-up investigation.
Are there any specific lipids observed within the structure that could potentially contribute to the functional conformation or stability of the complex?"
Given the high resolution of our structure, we observe a number of ordered lipid and detergent molecules, most of which were located at similar positions as in previous structures of Slo channels. Besides those molecules clustering in the deep cleft between neighboring voltage-sensor domains, we also observe lipid densities close to the binding site of γ1 on the distal side of the VSD. However, as their relevance for γ1 binding is unclear, we don’t discuss them in the manuscript. In general, of course, we agree with the reviewer that lipids can have a large impact on the function of membrane proteins.
It would be interesting to see if the kink in the gamma subunit is entirely neutralized through mutations of proline and glycine, how these alteration might impact the assembly of the mutated gamma subunit with the channel. The authors should provide insights into whether this mutated form of the gamma subunit assembles effectively with the channel and whether there are functional consequences associated with this alteration.
As shown by Kallure et al., substituting P270 in the kink by serine (the native residue at this position in γ3) strongly diminished the ability of γ1 to associate with Slo1 in vitro, demonstrating the importance of the kink and providing a rationale for the observed differences in the potency of the TM helices of γ1 and γ3 in Slo1 activation.
It would be generally beneficial for the authors to provide functional insights that can support the physiological relevance of this kink in the gamma subunit. Understanding the potential consequences of this mutation and its implications for the assembly and function of the channel complex will offer valuable insights into the physiological role of the kink.
We absolutely agree with the reviewer that functional insights on the relevance of the kink would be very valuable, but we think that the available experimental data together with the natural sequence differences in γ1-γ4 and the correlation with their physiological activity are very clear indications that the kink is relevant. However, future follow-up studies that prove this beyond any doubt would be valuable.
Is it known that binding of beta or gamma subunit can impact the subsequent binding of beta and gamma to channels. If it is, it need to be discussed briefly in the discussion part.
This is, to the best of our knowledge, not known. The only existing data that suggests co-presence of beta and gamma subunits on Slo1, reported in Gonzalez-Perez et al., 2015, stems from electrophysiological experiments and does not reveal anything about hierarchy and temporal order of binding events.
Reviewer #3 (Significance (Required)):
The Slo channel, also known as the large-conductance calcium-activated potassium channel or BK channel, is an ion channel type found in various cell membranes, including neurons, muscle cells, and other tissue types. Its key features encompass Ca2+ activation, voltage dependence, and regulation by auxiliary subunits. Different auxiliary subunits have been shown to modulate channel functions distinctly; notably, the γ1 subunit enables channel activation at lower voltages compared to the wild-type channel. This manuscript offers a structural-functional framework that enhances our comprehension of how Slo channels are regulated by auxiliary subunits, such as gamma and beta subunits. While the structure of Slo channels in complex with the beta subunit is understood, the binding and interaction of the gamma subunit with the channels remain elusive due to the absence of corresponding structures. Along these lines, the presented structure here indeed provides new insights into the regulation of Slo channel activity by the gamma subunit.
We thank the reviewer for this positive assessment of the data and agree that our structural data, also when regarded together with the complementary manuscripts by Kallure et al. and Yamanouchi et al., provides significant new insight into the assembly and activity of γ subunits.
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Referee #3
Evidence, reproducibility and clarity
"This manuscript by Redhardt et al. presents the cryo-EM structure of the Slo K+ channel from rabbits in conjunction with its auxiliary subunit, γ1, and proposes a mechanistic model for regulating channel activation.
"This manuscript by Redhardt et al. presents the cryo-EM structure of the Slo K+ channel from rabbits in conjunction with its auxiliary subunit, γ1, and proposes a mechanistic model for regulating channel activation.
The Slo channel, also known as the large-conductance calcium-activated potassium channel or BK channel, is an ion channel type found in various cell membranes, including neurons, muscle cells, and other tissue types. Its key features encompass Ca2+ activation, voltage dependence, and regulation by auxiliary subunits. Different auxiliary subunits have been shown to modulate channel functions distinctly; notably, the γ1 subunit enables channel activation at lower voltages compared to the wild-type channel. This manuscript offers a structural-functional framework that enhances our comprehension of how Slo channels are regulated by auxiliary subunits, such as gamma and beta subunits. While the structure of Slo channels in complex with the beta subunit is understood, the binding and interaction of the gamma subunit with the channels remain elusive due to the absence of corresponding structures. Along these lines, the presented structure here indeed provides new insights into the regulation of Slo channel activity by the gamma subunit. However, there are some important questions below that should be addressed."
- In Figure 1D panel, the calcium ions appear to be indistinct, likely due to the figure's low resolution. The authors are recommended to enhance the figure quality and consider a better positioning to effectively illustrate the ions.
- It would be beneficial for the readers if the authors provided detailed methodology explaining how they arrived at the 7% and 11% coexpression, aiding in the complex formation. Additionally, it would be informative to know the observed shift in the size exclusion chromatography (SEC) profile of Slo1-Y1 compared to apo Slo1.
- Is there any rationale behind initially purifying using strep affinity followed by His affinity?
- Regarding the Slo1 tetramer with gamma subunit binding, are there other classes where one, two, or three gamma subunits are bound to Slo1? Or is there only one class where all protomers of Slo1 are occupied by the gamma subunit? How do these classes appear when refined in C1 symmetry? Are there classes displaying C1 or C2 symmetry, or is the four-fold symmetry preserved across all refined classes?"
- The authors utilized nearly 1.9 million particles to reconstruct the final class, resulting in a high resolution. Is such a large number of particles truly necessary to achieve high resolution in this context?
- Authros mentioned that F273 of Y1 forms pi-stacking interactions, it remains unclear with which components of the channel these interactions occur.
- The authors propose that the disulfide bond between the Y subunit and Slo1 could play a crucial role in their interaction. Was there any observation of a covalent linkage in SDS page analysis? Furthermore, how would this interaction be affected if either cysteine C253 of gamma1 or C141 on the channel were mutated or neutralized?"
- Author's state that "The presence of several immobile positive charges on the intracellular side in close proximity to the VSD as in the case of the Slo1-γ1 complex is likely to locally lower the resting state potential and repulse the gating charges, thereby reducing the energy to overcome for the VSD to transition to the active conformation." Authors need to be little more elaborative here as it is not clear what authors mean repulse of gating charges.
- Probably beyond this study but I was wondering whether it is possible that Beta and gamma subunit can together assemble as heteromers to form a cage-like structure with contribution from both.
- Are there any specific lipids observed within the structure that could potentially contribute to the functional conformation or stability of the complex?"
- It would be interesting to see if the kink in the gamma subunit is entirely neutralized through mutations of proline and glycine, how these alteration might impact the assembly of the mutated gamma subunit with the channel. The authors should provide insights into whether this mutated form of the gamma subunit assembles effectively with the channel and whether there are functional consequences associated with this alteration.
- It would be generally beneficial for the authors to provide functional insights that can support the physiological relevance of this kink in the gamma subunit. Understanding the potential consequences of this mutation and its implications for the assembly and function of the channel complex will offer valuable insights into the physiological role of the kink.
- Is it known that binding of beta or gamma subunit can impact the subsequent binding of beta and gamma to channels. If it is, it need to be discussed briefly in the discussion part.
Significance
The Slo channel, also known as the large-conductance calcium-activated potassium channel or BK channel, is an ion channel type found in various cell membranes, including neurons, muscle cells, and other tissue types. Its key features encompass Ca2+ activation, voltage dependence, and regulation by auxiliary subunits. Different auxiliary subunits have been shown to modulate channel functions distinctly; notably, the γ1 subunit enables channel activation at lower voltages compared to the wild-type channel. This manuscript offers a structural-functional framework that enhances our comprehension of how Slo channels are regulated by auxiliary subunits, such as gamma and beta subunits. While the structure of Slo channels in complex with the beta subunit is understood, the binding and interaction of the gamma subunit with the channels remain elusive due to the absence of corresponding structures. Along these lines, the presented structure here indeed provides new insights into the regulation of Slo channel activity by the gamma subunit.
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Referee #2
Evidence, reproducibility and clarity
Summary
This study presents a high resolution cryo-EM study of a voltage-gated Ca++-dependent K+ channel in the presence of a gamma1 subunit.
Analysis of the structure and sequence alignments suggest a novel mechanism of activation of voltage-gated ion channels.
Major comments
The major issue in this paper is that it is only a structural biology paper. There is no structure-function relationship study, no functional studies of mutants that could validate -or not- the inferred underlying mechanism. Even though the authors have identified good candidates for mutations (e.g. p. 6) they have not attempted to validate their importance experimentally. As a result, reading their discussion is somewhat frustrating and full of assumptions, as indicated by sentences (p.7) like "a possible mechanism... might be... which would make... more likely". "... which might act ... seems important... might indicate... might lower... likely most pronounced... could be responsible..." "... might play an important role... does not allow a certain conclusion..."
Minor comments which could be confidently addressed
The Introduction contains no description of the state-of-the-art in the field concerning the available structures in the same system or similar ones. Hence, it is difficult to judge for people outside the field if the novelty is incremental or significant.
References 10 and 42 (eLife) lack some details.
Significance
Significance general assessment
As it turns out, at least two papers in exactly the same field just appeared:
- one in Molecular Cell by a Japanese group, which is much more developed and contains functional tests and structure-function relationships, in addition to beautiful structures (available on-line early December) https://www.sciencedirect.com/science/article/pii/S1097276523009218
- one in biorxiv, deposited yesterday https://www.biorxiv.org/content/biorxiv/early/2023/12/20/2023.12.20.572542.full.pdf
Advances
wrt known results
See above.
As a result of these new papers in Mol Cell and biorxiv, I think the authors should reconsider submitting their article elsewhere, perhaps for a more specialized audience.
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Referee #1
Evidence, reproducibility and clarity
Redhardt and colleagues describe a structure of the voltage and Ca-activated Slo1 channel in complex with an auxiliary subunit, 1. In complex with 1, Slo1 adopts an open state that closely resembles previous open state structures. Of 1, only the single membrane-spanning helix, which binds to the periphery of the Slo1 VSD, is resolved. There, it establishes several interactions with Slo1 that authors propose may favor adoption of the open state, potentially explaining how 1 can shift I-V profile of Slo1 to be activated at more negative membrane potentials. The interactions described fit well with existing mutagenesis analyses. While this report provides a first glimpse of how 1 can bind to Slo1, its impact will be minimal. It describes a single structural snapshot and there are no functional analyses presented. Additional analyses would be helpful in understanding of how 1 can regulate Slo1 channels.
Major comments:
- The authors propose several models for how 1 regulates Slo1, yet none of them are experimentally evaluated. For example, on page 8, it is written that "we propose that the combination of three different principles, namely shape complementarity, covalent anchoring and lowering the resting state potential by a positively charged intracellular stretch, act in concert to stabilize an active VSD conformation in the Slo1-γ1 complex." This is a testable hypothesis and one that should be experimentally evaluated to better understand regulation by 1.
- The authors analysis of the extracellular domain of 1 is incomplete. The only presented structure was performed with C4 symmetry imposed, in which extracellular domains were largely lost. The authors propose that these domains are dynamic and that their dynamism would enable simultaneous binding of both and subunits, as occurs in cells. A more thorough analysis of the dynamics and well as potential asymmetric conformations should be performed to better understand how these domains interact with Slo1.
- The refinement statistics suggest that the model was incompletely refined. This reviewer was not provided with the map or models, but the validation report lists a clashscore of 9 and 5.7% of the rotamers as being outliers, both of which are high for the reported resolution of the structure. It is also strange that the Q-score varied between different 1 protomers. Why are the four protomers not identical when the map is 4-fold symmetric? The authors should carefully inspect their model to insure that it is as correct as possible.
Significance
The impact of this report is limited. Functional analyses will be necessary to uncover precisely how gamma subunits regulate Slo1 channels.
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www.biorxiv.org www.biorxiv.org
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Reply to the reviewers
Reviewer #1 (Evidence, reproducibility and clarity (Required)):
The coupling between cell polarity and cell cycle progression is an important aspect of symmetric and asymmetric cell division. Although there are several examples of cell cycle kinases phosphorylating polarity proteins, it has been difficult to assess the importance of these on cell division due to the strong and pleiotropic effects of manipulating these kinases. Here, the authors generate an analogue-sensitive allele of cdk1 in flies to tackle this question in neuroblasts (NBs) and sensory organ precursors (SOPs), two well characterised examples of asymmetric cell divisions. They show that partial Cdk1 inhibition (which still allows cell cycle progression) does not block Bazooka (PARD3 in mammals) polarization in NBs, but prevents coalescence of the Baz crescent, which has previously been shown to be an actomyosin-based process. They further identify a Cdk1 consensus site on Baz (S180) for which they generate a phospho-specific antibody, allowing them to show that this site is specifically phosphorylated in dividing NBs and SOPs. Although mutations at this site do not recapitulate the effect of Cdk1 on Baz coalescence, they do delay Miranda polarization in NBs and affect lateral inhibition and asymmetric cell division of SOPs. Finally, the authors show that human PARD3 can also be phosphorylated by Cyclin B/Cdk1 in vitro.
Major comments:
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Figure 2A: it would be good to show that polarization of Baz::GFP in consecutive divisions is maintained in cdk1as2 animals in the absence of 1-NA-PP1. We now show in Fig S2B a panel with two consecutive divisions of a cdk1as2 neuroblast in the absence of 1-NAP-PP1, followed by a third division in the presence of 1-NAP-PP1. The neuroblast shows high levels of Baz polarization in the two first divisions.
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The interpretation of the observed SOP phenotypes is complicated by the uneven expression of the pnr-GAL4 driver and the fact that it is expressed in epithelial cells rather than just SOPs. The authors could express their control and mutant Baz constructs under the control of neurP72-GAL4. It is not likely they would be able to deplete endogenous Baz as they have done in NBs, as neurP72-GAL4 is expressed too late to deplete most proteins before SOP division, but they could at least look at localization of the mutants and any possible gain-of-function phenotypes.
Following this suggestion, we have recombined Neur-GAL4 with UAS-delta RNAi to attempt to deplete both endogenous Baz::mScarlet and Delta while expressing our Baz::GFP constructs specifically in SOPs. Baz::mScarlet depletion was surprisingly efficient considering, as the reviewer points out, the late timing of Neur-GAL4 expression. However, the adult flies did not present any sensory organs transformations, perhaps because Delta might not be as efficiently depleted. We can at least rule out dominant-negative effects.
We thank the reviewer for his constructive feedback and as suggested, we now extensively analysed the localisation of the Baz-S180 mutants in SOPs and found significant defects. We describe these observations in a new Figure 6. Briefly, we observed that the Baz phosphomutants have localisation defects during the pIIa cell division but not the pI cell division. We also observed a very surprising mosaicism of expression of our UASz-driven constructs within the SOP lineage that allowed us to make a few interesting observations which should be of interest to SOP specialists. Briefly, mosaic expression of Baz::GFP within the SOP lineage allowed to analyse the relative contributions of pIIa and pIIb/pIIIb to different Baz cortical pools and revealed an unexpected cell non-autonomous mechanism controlling pIIb division orientation. We describe these findings in a new associated supplemental figure.
The authors speculate that Baz phosphorylation during lateral inhibition may be the reason for the observed excess specification of SOPs in the S180 mutants. This could easily be tested by looking at their antibody staining at earlier stages in the notum. Following this suggestion (also coming from Reviewer #2), we have stained nota between around 8h APF. We observed that patches of cells of the early notum display a strong Baz-pS180 phospho-signal. These patches partially overlap with the Delta-positive stripes in which lateral inhibition occurs (as described for example in (Corson et al., 2017), consistent with the possibility that Baz-S180 phosphorylation does somehow regulate lateral inhibition.
These new experiments clearly show that Baz can be phosphorylated on S180 in cells that do not divide asymmetrically. This led us to change the title.
Reviewer #2 (Evidence, reproducibility and clarity (Required)):
Cell polarization in dividing cells, including stem cells, is typically coupled such that polarity can inform the architecture, orientation, and/or asymmetry during cell division. In Drosophila neural stem cells (neuroblasts/SOP), Par polarity is coupled to the cell cycle, but the nature of this coupling remains unclear. In this work, Loyer and colleagues report on impacts of CDK1 inhibition on Bazooka/Par3 localization and basal fate determinant localization. They provide evidence for a novel phosphorylation site that appears unique to asymmetrically dividing cells and may be involved in regulation of asymmetric division. Finally, they show that CDK1 can, at least in principle, phosphorylate human Par3 in vitro.
Overall, the major claims of the abstract appear supported by the experimental work; however, we think the title overstates the overall conclusions that can be drawn from the work.
Major comments:
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The major claim of the paper is the role of specific phosphorylation of S180 in asymmetrically dividing cells in polarization and sensory organ formation, which relies heavily on interpretation of S180A/D phosphomutants. The experiments are carefully performed and quantified, and are consistent with the conclusions drawn. However, we wondered if it possible that the phenotypes are not linked to phosphorylation (the authors acknowledge this in the Discussion)? In other words could the A/D mutants simply be weak Baz mutants? This could this potentially explain the extra-SOP phenotype if Baz function is generally altered, especially given that it is difficult to rationalise a role for SOP-specific phosphorylation in the processes that specify SOP cells in the precursor epithelial cells. The authors speculate that these early precursors may exhibit also phosphorylation, but this isn't examined. Chasing this down seems key to support the core titular claim of the paper. Following this suggestion (also coming from Reviewer #1), we have stained nota around 8h APF. We observed that patches of cells of the early notum display a strong Baz-pS180 phospho-signal. These patches partially overlap with the Delta-positive stripes in which lateral inhibition occurs (as described for example in Corson et al., 2017). This result is presented in Fig. 5H. As would be the case for any phosphomutant, this does not strictly rule out that the S180A and S180D could simply be weak Baz mutants, but it strongly supports the possibility that the lateral inhibition defects observed in these mutants result from defective Baz-S180 phosphorylation.
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Implicit in the core message of the paper is the elucidation of CDK1 regulation of polarity and specifically Baz. However, the connection between CDK1 and S180 (and Baz regulation overall) is relatively tenuous in this work. First, the S180A mutant does not phenocopy CDK1 inhibition with respect to basal determinant phenotypes, though obviously CDK1 may be more pleiotropic. Second, whether the CDK1 inhibition phenotype is linked to any effect on Baz/PAR behaviour is not really explored. Third, they do not test whether S180 phosphorylation is CDK1-dependent. We fully agree with these comments. We cannot think of any way of addressing the first two points, which would require fully inhibiting CDK1 and somehow maintaining neuroblasts in mitosis to examine how it impacts Baz localisation. We tried to arrest neuroblasts in mitosis and block the proteasome as this at least in HeLa cells led to persistence of mitosis when CDK1 was inhibited (Skoufias et al., 2007). However, neuroblasts arrested in mitosis by proteasome inhibition slipped out of mitosis.
However, concerning the third point, we now provide evidence showing that, at least in vitro, Drosophila BazS180 is phosphorylated by CDK1 (see below).
The method for quantifying domain signal only references prior work and should be described in this work. From our search of the cited reference, it appears to be peak signal intensity at a user specified point on the cortex. While this does not undermine the core findings as presented, it may not capture additional features that may be informative (domain size, fluorescence distribution, total signal etc.). For example domain coalescence would imply smaller, brighter domains, but similar total protein amounts, which appears to be the case from images, but isn't quantified per se. We now describe our method for quantifying average signal intensity in the middle of the Baz crescents. We agree that quantifying additional features to check whether they are affected by partial CDK1 inhibition would be interesting. However, doing so requires determining exactly where Baz crescents start and end. As Baz crescent edges in neuroblasts often end in a gradient rather than a sharp edge (Hannaford et al., 2018), we are not sure to be able to confidently do so in every case with the image quality of our dataset: we prioritised limiting photobleaching to accurately quantify the levels of endogenously expressed Baz rather than obtaining very sharp and high contrast images. This is further complicated by the fact that, depending on the depth of neuroblasts within the tissue and the orientation of their division relative to the imaging plane, the signal intensity of Baz crescents is quite variable, preventing a simple thresholding approach to arbitrarily determine the limits of crescents based on signal intensity. In short, accurately determining the size of crescents is very challenging.
The phosphospecific antibody signal is relatively weak, leading to relatively low signal to noise, which could compromise the ability to detect phospho-S180 in non-asymmetrically dividing cells or generally in cells in which Baz is not polarised and thus signal would be diffused around the cell rather than concentrated. Similar caveats could also apply to the lack of signal in interphase cells, where Baz may be less enriched at the cortex and not polarized. We are inclined to believe the authors conclusions, particularly given their examination of multiple cell types and tissues. However, it is a potential caveat as it may be most visible in polarised cells where it is asymmetrically enriched. We thank the reviewer for pointing this out. Given the fact that Baz levels at the neuroepithelial cells adherens junctions are similar, we are confident that Baz-S180 is phosphorylated in dividing neuroblasts but not in non-mitotic epithelial cells, which is at least consistent with our new finding that CDK1 phosphorylates Baz-S180 in vitro. However, we agree that we cannot strictly rule out that Baz-S180 is phosphorylated but below a detection threshold in mitotic neuroepithelial cells as cortical Baz levels decrease in these cells.
We have also gathered new data showing that, in the early notum, Baz-S180 is detected in epithelial cells that are not dividing asymmetrically, definitely ruling out the notion that Baz-S180 is strictly ACD-specific. We have changed the title of the paper accordingly, toned down the mention of apparently ACD-specific Baz-S180 phosphorylation in the abstract and now describe and discuss the fact that the apparent ACD-specificity of Baz-S180 phosphorylation is context-specific.
Examination of in vitro phosphorylation of human Par3D (Figure 6) seems out of place and does not add much. It is human, not Bazooka. They reveal 30 sites, 18 of which in both replicates, but most are not obvious CDK sites and the S180 equivalent site is missing. None of these sites is validated in vivo, at least in this work.
We fully agree with these comments. We initially attempted to purify both full length Baz and human PARD3 but only managed to purify small amounts of PARD3, which is why our analysis was limited to human PARD3. To circumvent these difficulties, we instead purified a smaller N-terminal fragment of Baz and PARD3, which was successful for both proteins and gave us much higher quantities of sample for analysis. Using two different approaches (Western blot with our phospho-specific antibody on Baz and targeted mass spectrometry on Baz and PARD3), we now show in a new Figure 7 that CDK1 phosphorylates Baz-S180 and PARD3-S187 in vitro.
Minor comments: Figure 1: Uses metaphase arrested cells, presumably colcemid, but colcemid is only noted in Figure 2. We now mention Colcemid in the legend of Figure 1. - Figure 2A: Scale bar is truncated. We have corrected this. - Figure 2A: Example images of control neuroblasts could be useful to readers. We now show control neuroblasts in Figure 2A. - Figure 2G' vs H': Because G' has two panels and H' has only one, we often confused the PKC and Mira box plots when comparing to Numb. Perhaps Mira could be in a separate sub panel or be more closely juxtaposed with Numb? The quantification of the Mira signal is now right next to Numb. - Whereas both Numb/Mira were examined in CDK1(as), only Mira is reported for the S180A/D experiments. Is there a Numb phenotype as well?
We actually co-stained Numb and Miranda in the dataset that we analysed in the S180A/D experiments shown in Fig 4E, F. We did not analyse Numb localisation in the first version we submitted because of a penetration issue of the Numb antibody: the Numb signal fades extremely fast as we image deeper in the tissue, causing large difference of signal intensity even within a single cell. This prevents us from performing any meaningful quantitative measurement of the Numb signal like the one we did in Fig. 2H, K, for which we did not encounter this issue. All our further immunostaining experiments with this antibody have had the same problem since then, even after using Triton concentrations up to 4% for permeabilization.
Nonetheless, following the reviewer’s question, we have at least performed a simple qualitative analysis of Numb localisation in this experiment. We observed that Numb localised to the basal pole in most cases in controls and Baz phosphomutants, but localised uniformly at the cortex in half the cases where Miranda showed very low levels of polarisation in metaphase in BazS180D mutants. This Numb localisation defect suggests a loss of function of the PAR complex whereas, intriguingly, the Miranda localisation defect suggests a gain of function of the PAR complex. These new observations are described in Fig. 4G-H’.
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The discussion of the notch / Baz phenotypes (Figure 5) is rather complicated and a bit difficult to follow. We agree with this, we have rewritten this part. This is further simplified by our new observation that Baz-S180 is phosphorylated in the early notum during lateral inhibition.
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Figure 5A: captions should indicate that RFP RNAi is depleting Baz. We have modified the figure accordingly.
- Box plots are used, but not described. i.e. outliers seem to be marked, but criteria unclear. Mean vs median, etc. We now describe boxplots in the legend in the first instance they are used (Fig 2A’), and in the material and methods
- Some grammatical mistakes:
- Title: neuroblast (no 's'),
- Page 1: Cell fate difference(s?) in the resulting daughter cells
- Page 4: (As) CDK1 inhibition with 10 μM 1-NA-PP1 prevents neuroblasts from cycling and causes metaphase- arrested neuroblasts to slip out of mitosis. (Reword)
- Page 6: increased levels of basal fate(no 's') determinants
We have corrected these mistakes.
Reviewer #2 (Significance (Required)):
The links between cell cycle and cell polarity are clearly important and remain poorly understood. Hence, the work addresses key conceptual/mechanistic questions relevant to our fundamental understanding of stem cell biology and regulation of polarity and asymmetric cell division. In our opinion, there are clearly some interesting observations in the manuscript, the experiments are performed carefully, and the data are generally well described. That said, overall, the work seems somewhat premature.
The direct impact of CDK1 on Baz behaviour remains somewhat unclear. The authors do a good job of limiting the concentration of inhibitor to decouple effects of cell cycle progression from CDK1 levels per se, but this does potentially impact the strength of the phenotypes they can detect and hence the observed phenotypes are relatively minor. Note that driving cells out of mitosis with stronger CDK1 inhibition clearly impacts Baz localization, so the 'real' effect of CDK1 inhibition on Baz could be stronger than reported here. It is also unclear whether the phenotypes observed are directly linked to CDK1 regulation of PAR polarity or an indirect effect of cell cycle control of other processes. The authors' suggestion that it could be related to defects in cortical actin organization, which is known to be cell cycle controlled, seems most likely, but neither this or other models are explored further. We agree but are not aware of any experiment that would allow testing full inhibition of CDK1 on membrane-bound Baz in mitotic neuroblasts. As mentioned above in our response to reviewer #1 we tried to arrest neuroblasts in mitosis and block the proteasome as this at least in HeLa cells led to persistence of mitosis when CDK1 was inhibited (Skoufias et al., 2007). However, neuroblasts arrested in mitosis by proteasome or Colcemid or both slipped out of mitosis upon inhibition of CDK1.
We agree it would be interesting to study how CDK1 affects the actomyosin network in neuroblasts but feel that this is somewhat beyond the scope of the manuscript.
Using phosphospecific antibodies, they report on a novel putative CDK1 phosphorylation site, but aside from looking like a consensus CDK1 site, whether this site is CDK1 dependent is not examined. Notably, the corresponding phosphomutants have modest effects and don't obviously account for the CDK1 inhibition phenotype, leaving it somewhat unclear whether it is under cell cycle regulation. We now provide a new figure 7 to address this point. As mentioned already above, using two different approaches (Western blot with our phospho-specific antibody on Baz and targeted mass spectrometry on Baz and PARD3 using), we now show in a new Figure 7 that CDK1 phosphorylates Baz-S180 and PARD3-S187 in vitro. Again, we cannot identify any experiment that would allow us testing whether S180 Baz is a direct target of CDK1 in vivo. The fact that we now report significant defects on Baz localisation in pIIa divisions, strongly suggests functional relevance and CDK1 seems a plausible kinase based on the new in vitro results.
The observation that S180 phosphorylation appears unique to asymmetrically dividing cells is very curious, but this observation is not followed up extensively. Again phenotypes of phosphomutants are quite modest, and while one can propose models to rationalise the phenotypes observed, these models are not fully explored. As mentioned above, we now show that Baz-S180 phoshorylation is not strictly ACD-specific and changed the title accordingly. We also have new data showing that the S180 phosphomutants of Baz have localisation defects in mitotic pIIa divisions (new figure 6). Therefore, this phosphorylation event on Baz can be linked to Baz’s cortical localisation and interestingly shows context dependency.
The findings that human Par3D can be phosphorylated by CDK1 in vitro do not add much particularly as they obtain a very large number of putative sites raising questions of specificity, the sites are not validated, and an S180 equivalent site was not identified. We agree that this has been a weakness which we feel we have addressed. We paste here the answer already provided above when replying to reviewer #1.
We initially attempted to purify both full length Baz and human PARD3 but only managed to purify small amounts of PARD3, which is why our phospho-proteomics analysis was limited to human PARD3. To circumvent these difficulties, we instead purified a smaller N-terminal fragment of Baz and PARD3, which was successful for both proteins and gave us much higher quantities of sample for analysis. Using two different approaches (Western blot with our phospho-specific antibody on Baz and phosphor proteomics on Baz and PARD3 using mass spectrometry), we now show in a new Figure 7 that CDK1 phosphorylates Baz-S180 and PARD3-S187 in vitro.
References
CORSON, F., COUTURIER, L., ROUAULT, H., MAZOUNI, K. & SCHWEISGUTH, F. 2017. Self-organized Notch dynamics generate stereotyped sensory organ patterns in Drosophila. Science, 356.
HANNAFORD, M. R., RAMAT, A., LOYER, N. & JANUSCHKE, J. 2018. aPKC-mediated displacement and actomyosin-mediated retention polarize Miranda inDrosophilaneuroblasts. eLife, 7__,__ 166.
SKOUFIAS, D. A., INDORATO, R. L., LACROIX, F., PANOPOULOS, A. & MARGOLIS, R. L. 2007. Mitosis persists in the absence of Cdk1 activity when proteolysis or protein phosphatase activity is suppressed. J Cell Biol, 179__,__ 671-85.
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Referee #2
Evidence, reproducibility and clarity
Cell polarization in dividing cells, including stem cells, is typically coupled such that polarity can inform the architecture, orientation, and/or asymmetry during cell division. In Drosophila neural stem cells (neuroblasts/SOP), Par polarity is coupled to the cell cycle, but the nature of this coupling remains unclear. In this work, Loyer and colleagues report on impacts of CDK1 inhibition on Bazooka/Par3 localization and basal fate determinant localization. They provide evidence for a novel phosphorylation site that appears unique to asymmetrically dividing cells and may be involved in regulation of asymmetric division. Finally, they show that CDK1 can, at least in principle, phosphorylate human Par3 in vitro.
Overall, the major claims of the abstract appear supported by the experimental work; however, we think the title overstates the overall conclusions that can be drawn from the work.
Major comments:
- The major claim of the paper is the role of specific phosphorylation of S180 in asymmetrically dividing cells in polarization and sensory organ formation, which relies heavily on interpretation of S180A/D phosphomutants. The experiments are carefully performed and quantified, and are consistent with the conclusions drawn. However, we wondered if it possible that the phenotypes are not linked to phosphorylation (the authors acknowledge this in the Discussion)? In other words could the A/D mutants simply be weak Baz mutants? This could this potentially explain the extra-SOP phenotype if Baz function is generally altered, especially given that it is difficult to rationalise a role for SOP-specific phosphorylation in the processes that specify SOP cells in the precursor epithelial cells. The authors speculate that these early precursors may exhibit also phosphorylation, but this isn't examined. Chasing this down seems key to support the core titular claim of the paper.
- Implicit in the core message of the paper is the elucidation of CDK1 regulation of polarity and specifically Baz. However, the connection between CDK1 and S180 (and Baz regulation overall) is relatively tenuous in this work. First, the S180A mutant does not phenocopy CDK1 inhibition with respect to basal determinant phenotypes, though obviously CDK1 may be more pleiotropic. Second, whether the CDK1 inhibition phenotype is linked to any effect on Baz/PAR behaviour is not really explored. Third, they do not test whether S180 phosphorylation is CDK1-dependent.
- The method for quantifying domain signal only references prior work and should be described in this work. From our search of the cited reference, it appears to be peak signal intensity at a user specified point on the cortex. While this does not undermine the core findings as presented, it may not capture additional features that may be informative (domain size, fluorescence distribution, total signal etc.). For example domain coalescence would imply smaller, brighter domains, but similar total protein amounts, which appears to be the case from images, but isn't quantified per se.
- The phosphospecific antibody signal is relatively weak, leading to relatively low signal to noise, which could compromise the ability to detect phospho-S180 in non-asymmetrically dividing cells or generally in cells in which Baz is not polarised and thus signal would be diffused around the cell rather than concentrated. Similar caveats could also apply to the lack of signal in interphase cells, where Baz may be less enriched at the cortex and not polarized. We are inclined to believe the authors conclusions, particularly given their examination of multiple cell types and tissues. However, it is a potential caveat as it may be most visible in polarised cells where it is asymmetrically enriched.
- Examination of in vitro phosphorylation of human Par3D (Figure 6) seems out of place and does not add much. It is human, not Bazooka. They reveal 30 sites, 18 of which in both replicates, but most are not obvious CDK sites and the S180 equivalent site is missing. None of these sites is validated in vivo, at least in this work.
Minor comments:
- Figure 1: Uses metaphase arrested cells, presumably colcemid, but colcemid is only noted in Figure 2.
- Figure 2A: Scale bar is truncated
- Figure 2A: Example images of control neuroblasts could be useful to readers.
- Figure 2G' vs H': Because G' has two panels and H' has only one, we often confused the PKC and Mira box plots when comparing to Numb. Perhaps Mira could be in a separate sub panel or be more closely juxtaposed with Numb?
- Whereas both Numb/Mira were examined in CDK1(as), only Mira is reported for the S180A/D experiments. Is there a Numb phenotype as well?
- The discussion of the notch / Baz phenotypes (Figure 5) is rather complicated and a bit difficult to follow.
- Figure 5A: captions should indicate that RFP RNAi is depleting Baz.
- Box plots are used, but not described. i.e. outliers seem to be marked, but criteria unclear. Mean vs median, etc.
Some grammatical mistakes:
- Title: neuroblast (no 's'),
- Page 1: Cell fate difference(s?) in the resulting daughter cells
- Page 4: (As) CDK1 inhibition with 10 μM 1-NA-PP1 prevents neuroblasts from cycling and causes metaphase- arrested neuroblasts to slip out of mitosis. (Reword)
- Page 6: increased levels of basal fate(no 's') determinants
Significance
The links between cell cycle and cell polarity are clearly important and remain poorly understood. Hence, the work addresses key conceptual/mechanistic questions relevant to our fundamental understanding of stem cell biology and regulation of polarity and asymmetric cell division. In our opinion, there are clearly some interesting observations in the manuscript, the experiments are performed carefully, and the data are generally well described. That said, overall, the work seems somewhat premature.
- The direct impact of CDK1 on Baz behaviour remains somewhat unclear. The authors do a good job of limiting the concentration of inhibitor to decouple effects of cell cycle progression from CDK1 levels per se, but this does potentially impact the strength of the phenotypes they can detect and hence the observed phenotypes are relatively minor. Note that driving cells out of mitosis with stronger CDK1 inhibition clearly impacts Baz localization, so the 'real' effect of CDK1 inhibition on Baz could be stronger than reported here. It is also unclear whether the phenotypes observed are directly linked to CDK1 regulation of PAR polarity or an indirect effect of cell cycle control of other processes. The authors' suggestion that it could be related to defects in cortical actin organization, which is known to be cell cycle controlled, seems most likely, but neither this or other models are explored further.
- Using phosphospecific antibodies, they report on a novel putative CDK1 phosphorylation site, but aside from looking like a consensus CDK1 site, whether this site is CDK1 dependent is not examined. Notably, the corresponding phosphomutants have modest effects and don't obviously account for the CDK1 inhibition phenotype, leaving it somewhat unclear whether it is under cell cycle regulation.
- The observation that S180 phosphorylation appears unique to asymmetrically dividing cells is very curious, but this observation is not followed up extensively. Again phenotypes of phosphomutants are quite modest, and while one can propose models to rationalise the phenotypes observed, these models are not fully explored.
- The findings that human Par3D can be phosphorylated by CDK1 in vitro do not add much paritcularly as they obtain a very large number of putative sites raising questions of specificity, the sites are not validated, and an S180 equivalent site was not identified.
In summary, the individual findings of this work are interesting and generally solid. Each could be followed up to provide mechanistic insight into cell cycle- or cell type-dependent regulation of Par polarity. However, in their current state, the results seem more like a loosely connected set of observations.
Expertise: Cell polarity and asymmetric cell division
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Referee #1
Evidence, reproducibility and clarity
The coupling between cell polarity and cell cycle progression is an important aspect of symmetric and asymmetric cell division. Although there are several examples of cell cycle kinases phosphorylating polarity proteins, it has been difficult to assess the importance of these on cell division due to the strong and pleiotropic effects of manipulating these kinases. Here, the authors generate an analogue-sensitive allele of cdk1 in flies to tackle this question in neuroblasts (NBs) and sensory organ precursors (SOPs), two well characterised examples of asymmetric cell divisions. They show that partial Cdk1 inhibition (which still allows cell cycle progression) does not block Bazooka (PARD3 in mammals) polarization in NBs, but prevents coalescence of the Baz crescent, which has previously been shown to be an actomyosin-based process. They further identify a Cdk1 consensus site on Baz (S180) for which they generate a phospho-specific antibody, allowing them to show that this site is specifically phosphorylated in dividing NBs and SOPs. Although mutations at this site do not recapitulate the effect of Cdk1 on Baz coalescence, they do delay Miranda polarization in NBs and affect lateral inhibition and asymmetric cell division of SOPs. Finally, the authors show that human PARD3 can also be phosphorylated by Cyclin B/Cdk1 in vitro.
Major comments:
- Figure 2A: it would be good to show that polarization of Baz::GFP in consecutive divisions is maintained in cdk1as2 animals in the absence of 1-NA-PP1.
- The interpretation of the observed SOP phenotypes is complicated by the uneven expression of the pnr-GAL4 driver and the fact that it is expressed in epithelial cells rather than just SOPs. The authors could express their control and mutant Baz constructs under the control of neurP72-GAL4. It is not likely they would be able to deplete endogenous Baz as they have done in NBs, as neurP72-GAL4 is expressed too late to deplete most proteins before SOP division, but they could at least look at localization of the mutants and any possible gain-of-function phenotypes.
- The authors speculate that Baz phosphorylation during lateral inhibition may be the reason for the observed excess specification of SOPs in the S180 mutants. This could easily be tested by looking at their antibody staining at earlier stages in the notum.
Significance
This work advances our knowledge of the coupling between the cell cycle and cell polarity during cell division, and shows that Baz/PARD3 receives inputs from Cdk1 that is specific to asymmetrically dividing cells. The reagents generated here (cdk1as2 and phospho-specific antibody) will also be of interest to the field. The data are convincing and well documented. This work should be of broad interest to the stem cell and developmental biology fields. Above are a few suggestions to improve the manuscript.
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Reply to the reviewers
Point-by-point response to reviewers’ comments:
Reviewer #1 (Evidence, reproducibility and clarity (Required)):
Major comments: 1. Previous studies using HDR and donor templates have shown that mutating the PAM sites in donor templates can enhance repair efficiencies. It would be helpful to add a discussion about the fact that SpRY does not have a PAM sequence that could be mutated and the potential consequences on repair efficiency.
We find that one mismatch in the target sequence (i.e. albino wt v. albino[b4]) is enough to completely abolish activity of SpRY. We have stated this more clearly in the manuscript.
It is also unclear how the template for the induction of mutations in kcnj13 was chosen. From the experiment with SpRY it seems that an HDR template equivalent to the sequence of the sgRNA target strand was most efficient, while in this experiment the alternative strand was used. An explanation should be added to the text.
Oligonucleotides corresponding to both DNA strands were tested, only one of them yielded positive results. We do not know the mechanistic basis for this finding, but amended the manuscript accordingly.
Minor comments: 1. It is not directly evident what the difference between the OP2 and OP2* sgRNA is. A short explanation would help clarify this and make it easier for the reader to understand.
OP2 (now re-named: U6) targets the wild type sequence, whereas OP2* (now: U6*) targets the albino[b4] sequence, which has one mutation leading to a premature stop codon. As this mutation is in the target region, we need adapt the sgRNA accordingly. We have stated this in the text more clearly now.
Similarly, it would be helpful to add the length of the different donor templates to Figure 2.
We have added the lengths of the oligonucleotides (in nt) to Fig.2.
While the PAM sequences and their difference between guides is discussed for two of them (OP2 and U5), it would be helpful to add the PAM sequences for all guides to Table 1 or figure 1.
We have added a table with all target sites including PAM sequences.
For people who are unfamiliar with the obelix phenotype/pigment pattern, it would be helpful to add a picture of an obelix mutant to Figure 4, so they would know what the phenotype would look like and how obvious it would be.
We have added a panel showing an obelix mutant fish to Fig.4.
Reviewer #2:
While every new and improved method to generate stable allele swap lines is greatly needed in the community, the results are not sufficient to convince me that the new version is leading to better success than previous methods. While they found one successful founder event, a single one is not enough to calculate efficiencies. Could just be luck that they got one. It is already known that HDR is very locus-specific, so maybe the locus they chose is such a locus.
This comment is difficult to address; while we found that the improved HDR method we present in the paper leads to better success for the repair of the albinob4 mutation and the one specific allele exchange we performed, we, of course, agree that one founder event is not enough to calculate efficiencies. However, we would like to maintain that one founder will in almost all cases be better than none. We also think that the locus we chose, kcnj13, is not a particularly lucky one yielding positive results easily, because it used to be refractory to editing following published protocols for a long time.
Overall, the paper suffers from the problem that the authors initially set out to investigate a specific genetic mutation in zebrafish but, upon observing that the resultant mutant exhibited no discernible phenotype, they shifted their focus towards refining and showcasing their methodological approach. This dual identity results in a study that, while informative, lacks the comprehensive exploration typical of dedicated research papers or the focused, technical depth one might expect from methodological publications.
Overall, we feel that there might be a slight misunderstanding here. The reviewer states that ‘… the paper suffers from the problem that the authors initially set out to investigate a specific genetic mutation in zebrafish but, upon observing that the resultant mutant exhibited no discernible phenotype, they shifted their focus…’, which is quite the opposite of what actually lead to the writing of the manuscript. We had already suspected that the single amino acid difference in the protein sequence between the two sister species might not be responsible for the observed functional divergence of the gene. We had also already found allele-specific differences in expression levels in hybrids, which make cis-regulatory evolution more likely. So, the null-hypothesis of our experiments was that both protein sequences would be functionally equivalent. However, as we had difficulties with the allele exchange due to low HDR efficiencies we needed to improve the method before we could definitively show this.
We have re-written some parts of the manuscript to make it clearer that we do not claim to have invented a method for HDR that is superior to all previously published ones. Rather, we think that we offer a variation of these published methods, which other researchers, struggling with low editing efficiencies (as we did), might want to try. What we do show in the manuscript is that the addition of an aNLS to Cas9 or SpRY leads to an increase in the efficiency in the generation of albino k.o. alleles and in HDR to repair the albinob4 mutation (see Fig. 3). If this will also be the case when editing other genes in the zebrafish genome needs to be investigated, but is clearly beyond the scope of this manuscript. We investigated one other locus in the zebrafish genome and could get one founder fish for the allele exchange in kcnj13, as opposed to zero we obtained with previously tried methods (conventional Cas9 with long or short donor-DNAs, prime editing). One advantage of ’our method’ is the simplicity of implementation. The Cas9 and SpRY proteins are easy to express in E. coli and the purification using two affinity tags is highly efficient resulting in samples of sufficient purity and high enough concentration for immediate use in injection experiments. So, we think that other researchers could easily try out the aNLS tagged proteins without changing much else of the protocols they usually employ for genome editing in zebrafish.
Reviewer #3:
Major comments: • The Cas9SpRY has been previously analyzed for the efficiency in zebrafish (Liang et al, Nat Comm 2022). This becomes only clear after reading the discussion. A comparison of these previously published SpRYCas9 proteins containing the bpNLS is missing, also a comparison of the efficiencies. The same locus (Albino) has been used in the study, are the guides identical? This study has not efficiently put the results in perspective of published results of the afore mentioned paper. And it seems that addition of the aNLS is not providing any benefit, which is good to know for the community.
We have added information to the introduction making it clear that the SpRY protein has previously been used in zebrafish. We also expanded the discussion and added more details comparing our results to previously published ones. However, this comparison is not always easy because the evaluation methods are different, sequencing v. phenotypic read-out. While the addition of the aNLS to the SpRY protein did not significantly enhance the (already high) k.o. efficiency for the albino locus, it did result in a significant boost of the repair efficiency of the albino[b4] mutation (see Fig.3C). Therefore, we think that the general statement it ’is not providing any benefit’ might not be entirely accurate. We think that the use of SpRY could be beneficial in some instances, but it must be assessed one a case-by-case basis.
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The HDR numbers is relying on 1 germline founder fish and might not be representative. More loci and higher numbers would be desirable.
We completely agree with the reviewer on this point. However, we feel that this is beyond the scope of this manuscript; we are looking forward to seeing other labs using the aNLS tagged proteins and finding out about their experiences.
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The allele exchange in Obelix is an interesting approach to use HDR but should be explained a little bit more. The motivation behind this experiments rains unclear.
We have added some information on obelix to provide more context
minor points: • All y axes require a labeling: % of what?!
We have changed the labels to % of larvae.
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When showing the specific classes of phenotpes the reader would benefit if the classes were written directly into the fish picture rather than using B, C, D, etc...
We have added this information directly to the pictures.
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OP2 should be called U6 to avoid unnecessary confusion, or is there anything special about it, why does it have another name?
We have changed OP2 to U6, as requested. The naming was completely due to historic reasons, there is nothing special about this target site / sgRNA.
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Differences in efficiency could potentially attributed to the PAM sequence as discussed. Please list the different PAM sequences and discuss in more detail. Why are so many gRNAs not efficient in the KO approach (Figure1)?
We added a table with the different target sites and the corresponding PAM sequences.
While we cannot provide a satisfactory explanation for the low efficiencies of five from six sgRNAs in our experiments, we notice that in the published data from Liang et al., 2022, a sizeable proportion of the tested sgRNAs with the SpRY protein also show low efficiency or no activity at all (see Fig. 2B, Liang et al., 2022, https://doi.org/10.1038/s41467-022-31034-8). This phenomenon is likely to be locus-specific and more data will be needed to come to a mechanistic understanding. We also do acknowledge that there is the possibility that our assay, the albino mutant phenotype in larvae, is likely not as sensitive as sequencing-based approaches. For one, we rely on the bi-allelic k.o. of the target gene, and we only assess a small proportion of all larval cells. However, we think that our approach with a phenotypic read-out is still valid, as it will reflect the practical requirements for an HDR method in many laboratories, where low efficiencies will result in no or weak and variable F0 phenotypes and in very low probabilities for germ-line transmission, which in most cases researchers will want to avoid.
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Line 217: correct co.injected to co-injected
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The scientific advancement is not clear. Readers would benefit if the advancement can be worked out better. Most readers would like to decide if it is worth changing their Cas9 design for genome editing in zebrafish and what efficiencies to expect.
We have modified the manuscript to better convey the scientific advancement it presents. We think it lies mainly in the fact that no other changes to the design of genome editing experiments is required, but to exchange the Cas9 protein usually employed for the aNLS tagged proteins. Both proteins, aNLS tagged Cas9 or SpRY, can easily be produced and purified in the lab following standard protocols. In less than one week enough protein for several hundred or thousands of injection experiments can be purified and aliquoted. We suggest that everybody uses their tried and tested method to produce knock-in alleles, and, as long as it works for them, don’t change it. If, however, the efficiencies are too low to get the desired allele, it will be very quick and simple to try our method. This is what we wanted to demonstrate with the editing of the obelix locus. In all cases we can envisage identifying one founder fish will be considerably better than not finding a single one.
Reviewer #4:
Major
- The authors use a mutated version of the widely used Cas9 protein from Streptococcus pyogenes, SpRY which basically does not rely on a PAM motif adjacent to the sgRNA target site. While this has certain advantages which are properly described, lowering stringency also comes with disadvantages, i.e. enhanced off target site activity. While assessing these is of the scope of the paper, these considerations should be properly discussed. Under which circumstances do the authors suggest to use SpRY and at which the conventional Cas9 or TALENs?
This is an important point and we have expanded on this. We think that SpRY offers a possibility to target sites that are not accessible to conventional Cas9, but it should not be expected to work as well as Cas9 for all loci (see also Liang et al., 2022 Fig.2). Whether the reduced stringency leads to more off-target effects is unclear; we did not experience higher rates of deformations or mortality in the injected larvae. This is, admittedly, a very crude measure for potential off-target effects, but is also in good accordance with the findings of Liang et al., 2022. In contrast to this, all labs that produce their own Cas9 protein could easily switch to the aNLS tagged version. It does not seem to have any disadvantages.
The authors designed 6 guides against slc42a2/alb according to the text and to Fig1 U1-U5+OP. Table 1 contains 16 sequences fitting these criteria. Which ones where used? Why are they named differently (U vs OP)? What method was used to design them? Does their design include PAM requirements? Have these guides been used previously and confirmed to work efficiently using CAS9? If the authors intend to provide an improved method that can widely and easily be adopted by other labs, they should put special emphasis in describing the procedure properly possibly including a supplemental figure detailing the workflow.
We have added a table with the target sites and the corresponding PAMs (see response to reviewer #1). The oligonucleotides shown in Table 1, which is now Table 2, are the ones used to generate the plasmid templates for the in vitro transcription of the sgRNAs.
The naming of the target sites, which was solely due to ’historic’ reasons, has been changed to U1 - U6.
They were designed (basically by hand) to allow in vitro transcription with T7 RNA polymerase (i.e. 5’ with GG), to have a G/C content of 50 - 65% and to represent a variety of different PAM sequences, that should potentially result in high activity (according to the data published by Walton et al., 2020 DOI: 10.1126/science.aba8853).
These sgRNAs could not be tested with Cas9 as they lack the PAM (NGG) required for activity of this protein.
We think that the main advantage of ’our’ method lies in the fact that aNLS-Cas9 (and aNLS-SpRY) can easily incorporated into the experimental procedures and workflows already in place in other laboratories. There is no need to follow exactly our protocol, eg. regarding sgRNA production or target site selection. We think that we showed that SpRY can be as effective as conventional Cas9, but not for all target sites, and that the addition of an aNLS sequence to Cas9 or SpRY is beneficial for genome editing in zebrafish, even when the aNLS is not combined with a myc-tag, as is the case shown by Thumberger et al., 2022, i.e. hei-tag.
The authors use a recessive pigment mutant (albino) to validate and quantify precise genome editing by HDR applying their toolbox. This is very clever and probably the most robust readout possible. The authors found that adding an aNLS to CAS9 and SpRY improves rescue efficiency, possibly also for germ line transmission. The authors should compare their efficiency for accurate editing with that of other papers in the field to allow for a better comparison.
We have now included a more detailed comparison of our results with previously published data in the discussion. However, this comparison is not always easy because the evaluation methods are different, sequencing v. phenotypic read-out. In terms of accuracy of the methods, we found that the majority of the HDR events we detected were associated with additional mutations. Some of these were possibly due to synthesis errors in the donor oligonucleotides, which might be alleviated by different purification methods. Other mutations, however, most likely occurred during cellular repair of dsDNA breaks and are therefore not easily avoided, unless double strand breaks are avoided, which would be the case if base editors are used. However, with base editors it is so far not possible to introduce every possible DNA change, making HDR methods still useful.
Minor:
- Fig.1A: Please indicate orientation of the gene
done
Line 168: ... tested sperm... à Method not explained in the methods section
The sperm samples extracted from anaesthetized males were used in exactly the same way as larvae were in other genotyping experiments; as is mentioned in the methods section. We have re-phrased this section a bit to make it clearer that we used larvae or sperm in exactly the same way for genotyping.
Kcnj13 editing. Explain obelix pigment phenotype to the non expert reader in pigmentation possibly illustrating D. aesculapii. This is a very powerful method allowing such comparisons, however it is not properly explained.
We have added some information on the obelix phenotype and included a panel of a mutant zebrafish in Fig.4.
Line 130: 'hei-tag' not properly explained
The hei-tag, published by Thumberger et al., 2022, consists of a myc-tag, a flexible linker and an aNLS in exactly that order. We have added some more details on the hei-tag to the text.
The co-editing of a restriction site for later identification of the edited allele is clever. However precise editing should be performed carefully and include splice site prediction algorithms to avoid enabling ectopic splice sites by silent mutagenesis. Also, an example of the analysis would be benefitial to Fig.4 or in the supplement.
We agree that this is an important point. We originally designed the edit in a way that would not result in the generation of a strong ectopic splice site by avoiding the creation of AG or GT di-nucleotide sequences.
We now also performed analysis with spliceator (http://www.lbgi.fr/spliceator/), a splice site prediction tool using convolutional neural networks, which confirmed that no ectopic splice site should be generated.
We could include this into a supplementary figure, if deemed necessary.
The manuscript is well written, the data are presented in an accessible way and the results look convincing. The work clearly shows a path to improvement of a fundamental method of gene editing in zebrafish and other species and clearly provides essential data on the topic. However, some aspects of the work are not properly described for the non-expert. Given the nature of the work which aims to improve an important, established method a more precisely described workflow in form of a table and workflow chart would certainly help the reader to focus on the essentials of the procedure.
As mentioned above, we think that it will be easy for other labs to incorporate our improvements into their existing protocols by exchanging normal Cas9 for aNLS-Cas9 or aNLS-SpRY. There should not be the need to strictly follow our protocols, e.g., for target site selection or sgRNA synthesis. The proteins can easily be expressed in bacteria and purified by standard methods using the His- and Strep-tags, as we published previously for conventional Cas9 (Podobnik et al. 2023).
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Referee #4
Evidence, reproducibility and clarity
In this manuscript, Dorner, Stratmann et al. developed a new variant of the homologous directed repair mediated genome editing technique in zebrafish using modified Cas9 proteins. They focus on the SpRY Cas9 protein variant, which offers a more relaxed PAM requirement for gene targeting. The requirement of a PAM has particularly hampered the feasabilty of HDR in the zebrafish model as the genomic sites of interest often do not meet the PAM requirements for conventional Cas9. Their improved method enhances the versatility of CRISPR/Cas methods in zebrafish, a crucial model organism in biomedical research. The authors also demonstrate that integrating an artificial nuclear localization signal (aNLS) into Cas9 variants not only improves gene knockout efficiency but also boosts homology-directed repair (HDR) frequency. This advancement allows for more precise genetic modifications, including single base pair changes, offering significant potential for research and other applications in genetics.
The manuscript is well written, the data are presented in an accessible way and the results look convincing. The work clearly shows a path to improvement of a fundamental method of gene editing in zebrafish and other species and clearly provides essential data on the topic. However, some aspects of the work are not properly described for the non-expert. Given the nature of the work which aims to improve an important, established method a more precisely described workflow in form of a table and workflow chart would certainly help the reader to focus on the essentials of the procedure.
Major comments:
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The authors use a mutated version of the widely used Cas9 protein from Streptococcus pyogenes, SpRY which basically does not rely on a PAM motif adjacent to the sgRNA target site. While this has certain advantages which are properly described, lowering stringency also comes with disadvantages, i.e. enhanced off target site activity. While assessing these is of the scope of the paper, these considerations should be properly discussed. Under which circumstances do the authors suggest to use SpRY and at which the conventional Cas9 or TALENs?
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The authors designed 6 guides against slc42a2/alb according to the text and to Fig1 U1-U5+OP. Table 1 contains 16 sequences fitting these criteria. Which ones where used? Why are they named differently (U vs OP)? What method was used to design them? Does their design include PAM requirements? Have these guides been used previously and confirmed to work efficiently using CAS9? If the authors intend to provide an improved method that can widely and easily be adopted by other labs, they should put special emphasis in describing the procedure properly possibly including a supplemental figure detailing the workflow.
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The authors use a recessive pigment mutant (albino) to validate and quantify precise genome editing by HDR applying their toolbox. This is very clever and probably the most robust readout possible. The authors found that adding an aNLS to CAS9 and SpRY improves rescue efficiency, possibly also for germ line transmission. The authors should compare their efficiency for accurate editing with that of other papers in the field to allow for a better comparison.
Minor comments:
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Fig.1A: Please indicate orientation of the gene
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Line 168: ... tested sperm... Method not explained in the methods section
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Kcnj13 editing. Explain obelix pigment phenotype to the non expert reader in pigmentation possibly illustrating D. aesculapii. This is a very powerful method allowing such comparisons, however it is not properly explained.
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Line 130: 'hei-tag' not properly explained
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The co-editing of a restriction site for later identification of the edited allele is clever. However precise editing should be performed carefully and include splice site prediction algorithms to avoid enabling ectopic splice sites by silent mutagenesis. Also, an example of the analysis would be benefitial to Fig.4 or in the supplement.
Significance
The manuscript is well written, the data are presented in an accessible way and the results look convincing. The work clearly shows a path to improvement of a fundamental method of gene editing in zebrafish and other species and clearly provides essential data on the topic. However, some aspects of the work are not properly described for the non-expert. Given the nature of the work which aims to improve an important, established method a more precisely described workflow in form of a table and workflow chart would certainly help the reader to focus on the essentials of the procedure.
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Referee #3
Evidence, reproducibility and clarity
The manuscript "efficient genome editing using modified Cas9 Proteins in zebrafish" by Dorner et al. is using the modified SpRY Cas9 protein with the addition of an artificial nuclear localization sequence (aNLS) and compares its efficiency in the generation of making KO animals with other Cas9 proteins and its use to generate a HDR mediated KI in zebrafish. The paper shows that the SpPY Cas9 works efficiently and that addition of aNLS can increase the HDR mediated efficiency in one locus.
Major comments:
• The Cas9SpRY has been previously analyzed for the efficiency in zebrafish (Liang et al, Nat Comm 2022). This becomes only clear after reading the discussion. A comparison of these previously published SpRYCas9 proteins containing the bpNLS is missing, also a comparison of the efficiencies. The same locus (Albino) has been used in the study, are the guides identical? This study has not efficiently put the results in perspective of published results of the afore mentioned paper. And it seems that addition of the aNLS is not providing any benefit, which is good to know for the community.
• The HDR numbers is relying on 1 germline founder fish and might not be representative. More loci and higher numbers would be desirable.
• The allele exchange in Obelix is an interesting approach to use HDR but should be explained a little bit more. The motivation behind this experiments rains unclear. minor points:
• All y axes require a labeling: % of what?!
• When showing the specific classes of phenotpes the reader would benefit if the classes were written directly into the fish picture rather than using B, C, D, etc...
• OP2 should be called U6 to avoid unnecessary confusion, or is there anything special about it, why does it have another name?
• Differences in efficiency could potentially attributed to the PAM sequence as discussed. Please list the different PAM sequences and discuss in more detail. Why are so many gRNAs not efficient in the KO approach (Figure1)?
• Line 217: correct co.injected to co-injected
Significance
The scientific advancement is not clear. Readers would benefit if the advancement can be worked out better. Most readers would like to decide if it is worth changing their Cas9 design for genome editing in zebrafish and what efficiencies to expect.
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Referee #2
Evidence, reproducibility and clarity
The manuscript: Efficient genome editing using modified Cas9 proteins in zebrafish by Dorner and Stratmann et al. provides a putative improved method of modifying single base pairs in the genome of zebrafish through homology-directed repair. The authors use a modified Cas9 protein called SpRY in zebrafish. The SpRY protein has fewer restrictions on the PAM sequence it requires, which broadens its genome targeting potential. The paper presents experiments on zebrafish using SpRY for efficient genome editing. However, not all target sites are equally efficient, and the authors suggest that individual sequences may need to be evaluated on a case-by-case basis.
The paper also explores the benefits of using an optimized artificial nuclear localization signal (aNLS) for the Cas9 protein, which significantly increases genome editing efficiency in zebrafish. Using this improved method, the researchers demonstrate precise editing of the kcnj13 gene in zebrafish to match the sequence found in Danio aesculapii, their closest sister species. The edited zebrafish do not show any visible phenotypic changes, suggesting that the Kcnj13 proteins from both species are functionally equivalent.
While every new and improved method to generate stable allele swap lines is greatly needed in the community, the results are not sufficient to convince me that the new version is leading to better success than previous methods. While they found one successful founder event, a single one is not enough to calculate efficiencies. Could just be luck that they got one. It is already known that HDR is very locus-specific, so maybe the locus they chose is such a locus.
Significance
Overall, the paper suffers from the problem that the authors initially set out to investigate a specific genetic mutation in zebrafish but, upon observing that the resultant mutant exhibited no discernible phenotype, they shifted their focus towards refining and showcasing their methodological approach. This dual identity results in a study that, while informative, lacks the comprehensive exploration typical of dedicated research papers or the focused, technical depth one might expect from methodological publications.
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Referee #1
Evidence, reproducibility and clarity
Summary:
The manuscript "Efficient genome editing using modified Cas9 proteins in zebrafish" by Dorner et al. describes the utility of combining Cas9 variants with an alternative NLS to improve the efficiency of induction of single base pair changes in zebrafish through HDR. The authors confirm findings from previous studies, that the SpRY variant of Cas9 can be used in zebrafish to induce knockouts at efficiencies similar to Cas9 and additionally show the ability of SpRY to induce point mutations via HDR. They further confirm other studies that showed that the addition of an artificial NLS can significantly increase targeting efficiency of Cas9 in zebrafish. They extend their studies to show that the increased efficiency through addition of this alternative NLS also enhances HDR mediated induction of single base-pair changes using donor templates for both Cas9 variants. Most conclusions of the paper are well supported by the presented data and the experiments are explained in sufficient detail for replication. The paper could benefit from a few modifications/additions to the text to clarify a few details.
Major comments:
Previous studies using HDR and donor templates have shown that mutating the PAM sites in donor templates can enhance repair efficiencies. It would be helpful to add a discussion about the fact that SpRY does not have a PAM sequence that could be mutated and the potential consequences on repair efficiency. It is also unclear how the template for the induction of mutations in kcnj13 was chosen. From the experiment with SpRY it seems that an HDR template equivalent to the sequence of the sgRNA target strand was most efficient, while in this experiment the alternative strand was used. An explanation should be added to the text.
Minor comments:
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It is not directly evident what the difference between the OP2 and OP2* sgRNA is. A short explanation would help clarify this and make it easier for the reader to understand.
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Similarly, it would be helpful to add the length of the different donor templates to Figure 2.
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While the PAM sequences and their difference between guides is discussed for two of them (OP2 and U5), it would be helpful to add the PAM sequences for all guides to Table 1 or figure 1.
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For people who are unfamiliar with the obelix phenotype/pigment pattern, it would be helpful to add a picture of an obelix mutant to Figure 4, so they would know what the phenotype would look like and how obvious it would be.
Significance
General assessment: Strength of the study are the use of multiple, independent injection experiments for each group to test guide and repair efficiency. Clear presentation of methods which will allow replication of experiments and also production of reagents. While the study clearly shows that SpRY does work for HDR mediated repair, only one specific repair template design (single stranded oligo) was tested. This study could be enhanced through testing of additional HDR template designs and a direct comparison of repair efficiency between Cas9 and SpRY.
Advance: This study does provide a minor advance in our understanding of how the efficiency of Cas9 and its variants can be optimized and how these modifications can enhance repair efficiency. The use of the SpRY variant in zebrafish as well as the enhancement of Cas9 efficiency through the use of the aNLS has been shown before (Liang et al. 2022, Thumberger et al. 2022). Novelties in this study are the use of SpRY for HDR mediated repair and the improvement of the repair efficiency through the addition of the aNLS to SpRY and Cas9.
Audience: The methods described in this paper will be of interest to the zebrafish and Medaka communities as well as people using HDR mediated repair for the induction of mutations.
Expertise: I am a geneticist who has worked with the zebrafish model for over 20 years and uses CRISPR/Cas for genome editing in zebrafish routinely.
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Referee #3
Evidence, reproducibility and clarity
Genome-wide association studies (GWAS) were used to identify potential risk variants associated with amyotrophic lateral sclerosis (ALS), and a specific variant of GGNBP2 has emerged as a critical player, exhibiting increased expression, and prompting the authors to investigate its role in the disease progression.
The study, focusing on Drosophila Ggnbp2 (dGgnbp2) in motor neurons, revealed crucial insights into its function. Loss-of-function experiments underscored the necessity of dGgnbp2 in motor neuron synaptic development. Strikingly, introducing a human transgene fully restored these phenotypes, demonstrating functional conservation between humans and flies. Contrary to expectations, overexpression of dGgnbp2 resulted in severe locomotor defects in adult flies, mirroring aspects of ALS pathology, suggesting a tight regulation for this protein in the control of NMJ function.
The authors also suggest a role of the gene in regulating autophagy, as RNA-seq showed abnormalities in the expression levels of genes involved in autophagy when dGGNPB2 was mutated. Finally, they described a potential molecular mechanism through which GGNBP2 may regulate autophagy and that is by controlling phospholipid levels specifically PI(3)P.
Understanding the cellular mechanisms, the study suggests dGgnbp2's role in regulating autophagy, a process frequently impaired in ALS, and both overexpression and depletion of dGgnbp2 led to altered levels of phosphorylated lipid PI(3)P, a vital component of autophagosomes. Add PI3K This comprehensive investigation provides compelling evidence that Ggnbp2 plays a pivotal role in motor neurons, exerting regulatory control over a cellular process commonly compromised in ALS. These findings also provide insights into the functional implications of the GGNBP2 variant and also open new avenues for potential therapeutic crucial pathways like autophagy and InR, offering a promising direction in ALS treatment.
Major:
The experiments outlined in this paper, which elucidate the function of the Ggnbp2 in the neuromuscular junction (NMJ), are compelling and crucial for characterizing a novel gene implicated in ALS. However, my primary concern revolves around the demonstration of the influential role of the Ggnbp2 in regulating autophagy and its responsiveness to insulin signaling.
Indeed, the author should better analyze and also genetically demonstrate an interaction between Ggnbp2 and components of the insulin signaling pathway. For instance, analyzing PTEN (utilizing available mutants) could enhance the understanding of the pathway linking Ggnbp2 downstream of PIP2.
The connections drawn in the paragraph regarding autophagy (paragraph title: dGgnbp2 is linked to autophagy in motor neurons) might be a bit tenuous for the described observations. In the end it seems to only suggest a link to autophagy without explicitly asserting that it drives autophagy. The authors have overlooked providing a clear explanation or speculation on the correlation between GGNBP2's regulation of autophagy and its impact on synaptic development. A more explicit emphasis, then, on whether a loss-of-function or gain-of-function is more pertinent to human disease is necessary.
The authors should take advantage of the available Drosophila lines to elucidate the relative dependence of the autophagic flux controlled by Ggnbp2 and macroautophagy, using mutants or RNAi lines for Atg1, Atg5, and potentially Atg6/beclin, as these factors have been demonstrated to be relevant in neurodegenerative diseases, including ALS and Parkinson's.
Furthermore, alternative approaches for testing InR activation exist, such as the widely employed tPH-GFP method (Britton et al., 2002) that could be used to implement the activation of Akt in NMJ.
The observation that dGgnbp2 serves specific functions in the cytoplasm of motor neurons is particularly interesting, and further investigation to better understand this function would be valuable. Additionally, is this soluble form also identified in humans?
Minor:
Line 113-119: This does not seem relevant to the study. This is not discussed or investigated anywhere else in this work. However, I understand and appreciate the intent.
Line 135-138/Figure 2L: The authors do not address the non-significant "continuous" data.
Line 191: Define the age of young animals.
Line 192: Why did the authors change to OK371-Gal4 promoter in the experiments in Figure 4.
Line 192: The authors need to specify how young were the animals.
Line 202: Is the human GGNBP2 expressed with OK6-Gal4 able to rescue the reduced motility of the d Ggnbp2null flies?
Line 223: Typo, "to the" is repeated.
Referees cross-commenting
The comments I read are all feasible and in line with what I also suggest, and I accept them. What is not clear is how much time the authors need if they reply to all, which, of course, depends on how much deeper they decide to go to complete the characterization of GGNBP2 in autophagy and the relevance of InR/TOR signaling. This will also depend on the journal they decide for their final submission.
Significance
This study outlined in this paper rests on a robust experimental design and yields conclusive results. It shows strong evidence of a role of the GGNBP2 gene in ALS pathology. It provides clear evidence of a synaptic development defect as well as a locomotor dysfunction in mutants, building on its relevance in human pathology. It solidly proves a functional conservation between flies and humans. It then suggests a potential role in regulating autophagy. However, further experiments demonstrating the actual interaction between GGNBP2 and class I and III PI3K is needed to fully elucidate the mechanisms through which GGNBP2 controls autophagy.
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Referee #2
Evidence, reproducibility and clarity
Kerwin et al. conducted a study on the function of dGgnbp2 and its role in motoneurons. There are some general oversights that make the paper less robust than it could be. Firstly, the connection between autophagy dysregulation and the autophagic defects shown in the last figures is not clear. Combining these two parts would add more value to the paper. Secondly, the actual connection to ALS - made by the authors throughout the study - is not very strong. The only link with ALS is mentioned at the beginning when it is stated that Futsch is a target of TDP-43 and later when the authors mention that autophagy is a key dysregulated pathway in ALS. Although this is true, there is no strong connection to ALS pathology. It would have been appropriate to measure TDP-43 mislocalization in the animals and see whether the Futsch decrease observed in both null and OE models is related to it, or whether TDP-43 aggregates.
Figure 2: Although the results presented in Fig S3R-X suggest a possible reduction in dGgnbp2 protein, it would be more reliable to validate the knockout strategy used for this figure with a PCR or a WB. The same comment applies to Figure 3.
Figure 5H: Why aren't the results with dGgnbp2 OE shown in the locomotion sets, but rather a het null + GGNBP2OE is reported? This does not match the groups represented in the previous panels of the same figure.
Line 223 typo: In motor neurons, it was localized to the cytoplasm
Figure 6: I suggest performing N/C fractionation and WB probing for V5 to better characterize protein localization. This data is relevant given results in the next figure.
Figure 6I:To claim dGgnbp2 function is cytoplasmic, data on mutant alone needed (not in null background).
Figure 7: The volcano plot shows that the over expression system and the insertion only exhibit similar genes, which suggests that most of the observed changes are due to the insertion alone. As we do not have a clear understanding of GGNBP2's function in the nucleus, we need more precise data on over expression.
Figure 8: Autophagy experiments are very interesting, despite the lack of crucial data. While it is evident that autophagy dysregulation occurs due to dGgnbp2 dysregulation, it is unclear whether it is a direct cause of the pathology. This assumption can only be confirmed by conducting a few experiments. Firstly, auto-Nagy defects should be measured in rescue models such as the one presented in figure 5. Secondly, treatment should be administered to restore autophagic flux, such as rapamycin or Torin1, as these drugs are known to help in cases of autophagy dysregulation. Another experiment that could be conducted is the overexpression of key autophagic proteins, such as Atg8.
Significance
This study is unique as few studies have focused on this protein and none on its role in motor neurons. The experiments were well-conducted, with the proper controls in place. The authors clearly demonstrate the significance of balanced protein levels for proper synapsis development and optimal motor neuron performance. The study also evaluated RNA dysregulation in different models used in the previous section of the paper. The authors found that autophagy was one of the dysregulated pathways. They characterized the autophagic defects in these cells.
The study would be of interest to a specialized audience since its potential translational implications.
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Referee #1
Evidence, reproducibility and clarity
In this paper, Kerwin et al. investigate the role of the GGNBP2 in synaptic morphology and autophagy in motor neurons. Using Drosophila, the authors performed functional studies of GGNBP2, a putative nuclear protein which has been linked to ALS through GWAS. Through creating clean mutants using CRISPR, the authors found that the null mutants of the fly homolog of GGNBP2 (CG2182, a previously uncharacterized gene which they propose to name Ggnbp2) are viable and fertile, but exhibit motor defects in adult flies accompanied by synaptic phenotypes in the larval neuromuscular junction (NMJ). In addition, the authors show that overexpression of Ggnbp2 also cause behavioral and NMJ defects, which is significant for ALS studies since the variant associated with this condition seems to increase the levels of GGNBP2 based on eQTL studies. Interestingly, the human GGNBP2 was able to rescue the fly LOF mutant phenotypes, suggesting that they have conserved molecular functions. Surprisingly, while mammalian GGNBP2 has been suggested to function as a transcription factor and gain and loss of this gene seems to mildly alter the transcriptome in flies, the authors showed that majority of the endogenously expressed fly Ggnbp2 protein is found in the cytoplasm and that the predicted nuclear localization signal (NLS) is not required for its function in motor neurons. Finally, the authors performed some additional experiments to propose a functional link between this gene and autophagy, focusing on its potential regulation of PI(3)P and genetic interaction with a fly ortholog of TBK1, which have also been linked to ALS in human.
Overall, I feel this work addresses an important question in the field and the genetics experiments have been conducted with rigor. This study somewhat lacks mechanistic insights (e.g. how does Ggnbp2 regulate PI(3)P and motor neuron function?) but there are a number of novel findings (e.g. first generation and characterization of the null mutant of Ggnbp2 in flies, showing that it's predicted NLS is not important) that makes this paper provide value to the literature and community in its current form. While I have several major and minor issues that I would like to see addressed the authors, I would be generally in favor of this paper to be published in an appropriate journal that targets readers with interests in human neurological disorders and Drosophila biology.
Major Points
Major #1: In Figs 5, 6 and S3, the authors demonstrated significant rescue of Ggnbp2 null phenotypes by overexpressing fly Ggnbp2 or human GGNBP2 protein using the GAL4/UAS system. However, data shown in Fig 3 and elsewhere reveals that overexpression of fly Ggnbp2 results in smaller bouton numbers and larger boutons. Regarding this...
1A: Does overexpression of human GGNBP2 in a wild-type background show similar NMJ and motor behavioral defects as fly Ggnbp2?
1B: It is quite surprising that the authors were able to rescue the null mutant NMJ phenotype using GAL4/UAS (in this case OK6-GAL4) system considering that overexpression of this protein seems to have a strong effect using this driver as well. Is this because they used the UAS-dGgpnb2::V5 as a heterozygous in FigS3, which is a condition in which the overexpression phenotype is not seen? If so, the genotype of FigS3 (and Fig3) should be matched with FigS4 (otherwise, it looks like the authors used homozygous of the UAS in FigS3).
Major #2: To assess adult fly locomotor performance, the authors employed the negative geotaxis assay to measure their climbing activity (Fig4). While the data show that the flies with LOF or GOF of Ggnbp2 have age-dependent defects, it is possible that the effect is developmental, especially for the overexpression paradigm. Considering that ALS is considered to be an adult onset neurodegenerative disease, it would be valuable if the authors can perform a conditional overexpression study of Ggnbp2[OE-EPgy2] using the Gal80[ts] system in which the fly Ggnbp2 that is overexpressed post-developmentally (i.e. overexpression of this protein induced only after eclosion) can also have an age-dependent motor defect. Considering that the authors do not perform any synaptic studies in adults (i.e. all NMJ experiments are performed in the larva), such experiments will increase the value of this work in the context of ALS research.
Major #3: The authors generated several of UAS-fly Ggnbp2 (V5 tagged with or without the NLS) and UAS-human GGNBP2 (Myc tagged). Regarding these...
3A: Other than in Fig6A, the authors do not show their expression pattern in motor neurons. It would appreciate if the authors can provide an immunostaining image of the all three proteins in the cell body and neurons of flies when expressed using OK6 or OK371. This way, the readers can appreciate whether the human and fly proteins behave similarly, and whether the deletion of the predicted NLS alters the subcellular localization of the protein. I acknowledge that it may be already difficult to observe the wild-type Ggnbp2 in the nucleus so one may not see a major difference but it would be important to document these.
3B: Considering that the Ggnbp2::V5 seems to show a punctate pattern, may be interesting to see if this signal overlaps with the Atg8a, PIP2 and 2xFYVE::GFP in the cell body or in the synapse.
Minor points
Minor #1: In line 62, "Given that 75% of genes..." needs a minor correction, as 77% is the the number of gene that is mentioned in the cited reference (77%). Perhaps the authors can say "Given that about 75% of genes...".
Minor #2: In line 266, the title of this section is "dGgnbp2 is linked to autophagy in motor neurons" but the author only shows data regarding the genetic interaction between Ggnbp2 and ik2 (official gene name is IKKε in FlyBase) in this section. Although IKKε and its mammalian homolog TBK1 is known to regulate autophagy, these are kinases that are involved in other processes (e.g. cell proliferation, cell death, cell polarity) so the title is a bit of an overstatement. Since the connection to autophagy is more directly shown in subsequent sections, I would recommend modifying the title of this section (e.g. "dGgnbp2 genetically interacts with IKKε, an ortholog of mammalian TBK1"". Also, note that IKKε is orthologous to both TBK1 and IKBKE so this may need to be clearly mentioned in the text.
Minor #3: In line 282, the loss-of-function (lof) allele for ik2[1] requires proper reference that experimentally showed that this is indeed a lof allele. Also, please change the 'ik2' nomenclature to 'IKKε' to match with the latest official gene name.
Minor #4: In FigS2, can the author show where the predicted NLS of the fly protein is that they deleted in Fig6E so the readers can see how conserved this region is between the fly and human proteins?
Minor #5: I personally feel that the section regarding "RNA-seq analysis of Ggnbp2" is a bit out of place. Currently, this follows the section that says Ggnbp2 is does not function in the nucleus, so it doesn't make much sense to perform RNA-seq experiment for something that you think primarily works in the cytoplasm if the goal of this assay was to find direct mechanistic targets. Perhaps the authors can consider showing moving this section to before the "dGgnbp2 functions in the cytoplasm of motor neurons" (and place Fig7 before Fig6) so you can use the fact that you didn't see much dramatic gene expression changes in the LOF/GOF mutants as a rationale of why you decided to question its nuclear requirements. Just a suggestion, but this may make your paper flow better.
Significance
Overall, I feel this work addresses an important question in the field and the genetics experiments have been conducted with rigor. This study somewhat lacks mechanistic insights (e.g. how does Ggnbp2 regulate PI(3)P and motor neuron function?) but there are a number of novel findings (e.g. first generation and characterization of the null mutant of Ggnbp2 in flies, showing that it's predicted NLS is not important) that makes this paper provide value to the literature and community in its current form. While I have several major and minor issues that I would like to see addressed the authors, I would be generally in favor of this paper to be published in an appropriate journal that targets readers with interests in human neurological disorders and Drosophila biology.
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Referee #3
Evidence, reproducibility and clarity
In this manuscript, the authors reveal the genetic basis for why two different null alleles of Fasiclin II (Fas2), a member of the Igg superfamily of cell surface proteins, result in very different phenotypes in the follicular epithelia of the developing Drosophila egg chamber. One null allele - Fas2G0336 - results in rare occurrences of follicular cells being found outside of and apical to the plane of the epithelia in mutant clones, whereas the other null allele - Fas2EB112 - results in frequent occurrences of cells apical to the plane of the epithelia in mutant clones. Using recombination, they map a second mutation on the Fas2EB112 chromosome and demonstrate that it is a known allele of another Igg superfamily protein member - Neuroglian (Nrg). Thus, the severe phenotypes associated with only one of the two Fas2 null alleles can be explained by the additional absence of Nrg function, supporting previous studies that, in the follicular epithelia, the functions of Fas2 and Nrg are overlapping and compensatory.
The authors fully support this finding by several carefully done experiments, all of which are thoroughly described and nicely illustrated in the figures in the main body of the paper, with helpful information provided in the supplemental figures. Indeed, the authors explore a number of possible explanations for the phenotypic differences with the two null Fas2 alleles and their conclusion of there being a known mutation in Nrg on one of the two null chromosomes is supported by several independent approaches. No additional experiments are necessary, and the findings should be easily reproducible by others using the reagents described in the study.
Minor point: On the second page of the results, the last paragraph starts with "The second chromosome" in the first sentence. This is a bit confusing - could be considered chromosome 2, when the authors do not mean chromosome 2. It would be better to refer to this as "The other chromosome generated by recombination".
Referees cross-commenting
The other two reviewers have picked up some minor issues that should be addressed by the authors (quantitation of the Western, labels on all figure panels, etc). These changes would definitely improve the manuscript and should be done. I'm not convinced that the overall findings are important for a significant part of the Drosophila community - seems more of a specialty audience who needs to know that there is a second mutation in Neuroglian on one of the Fas2 null chromosomes that are available through the stock centers.
Significance
The findings are particularly relevant to anyone who has used the Fas2EB112 allele for their studies or who plans to do so. Otherwise, it serves as a cautionary tale to all to examine and report phenotypes using multiple different alleles as a control for what other mutations may also exist on mutant chromosomes of interest.
I am a Drosophila developmental biologist who uses most of the same tools used in this manuscript on a regular basis. I am also quite familiar with the experimental system used for this work.
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Referee #2
Evidence, reproducibility and clarity
Epithelial integrity is fundamental to organ function and development. There are mechanisms to reintegrate cells that divide outside of the cell layer that depend on cell adhesion. In many cases, including the Drosophila follicular epithelium, this adhesion and reintegration is dependent on partially redundant functions of the IgCAMs Fas2, Fas3, and Neruoglian (Nrg).
Here, Finegan et al have identified discrepancies in phenotypic strength between two null alleles of Fas2 and show that this is due to an additional mutation in Nrg on the phenotypically stronger chromosome (likely due to a submission of a double mutant rather than a single mutant to the stock center, as this Nrg allele seems to be the same aberration as the Nrg14 null alle used in this study as well). Overall, the data is sound and of interest to people working with these genes in the adhesion field, but not of a broader interest. Over passages the paper is lengthy (such as a description of recombinations separating the mutations (or not) on p5 or the extensive description of the Nrg splice variants on p7.
Points to address:
Major:
Fig 1C and Fig 4B: Why do the shRNAs used for Fas2 and Nrg have stronger phenotypes than the mutants? As clones were used, the argument of adaptation is harder to make. Specificity of shRNAs may have to be shown in a mutant background. Therefore, actually, this is particularly puzzling/worrisome in case of Fig. 4B where Nrg RNAi is stronger than the Nrg14 null allele (i.e. e(Fas2)mut) background.
P8/Fig 3F Western blot: Despite description of quantification of blots in methods, nothing is quantified, and the arguments of dosage compensation thus cannot be made. Comes up again in the discussion. Furthermore, would the resolution of the blot allow distinction of Nrg180-YFP from Nrg167-YFP to really exclude that only one of them is expressed from the tagged locus?
Discussion: Similarly, Mannheim Fas2EB112 has a lower average number of...., though this difference is not significant. Thus, is does not have a lower average!
Discussion: Sentence ending in '...that E(Fas2)mut is suppressed' is confusing. Suppressed with repressed to what by what?
Minor:
- P2 second paragraph: insert 'Drosophila' before 'follicular epithelium'.
- P4: Dr. Riechmann's first name is misspelled.
- P8 last line: Fig. X should be Fig. 4A.
- P12, legend of Fig. 2: description of panel B missing.
- Tables are supplementary and should be labeled as such in the methods.
- Fig. S3C: the non-disjunction aspect is not straight forward to see in the figure (e.g. XXY genotype and its correlation to eye shape from balancers).
Significance
Overall, the data is sound and of interest to people working with these genes in the adhesion field, but not of a broader interest.
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Referee #1
Evidence, reproducibility and clarity
This manuscript reports an intriguing genetic puzzle and its solution that is very relevant to Drosophila researchers studying the Immunoglobulin-superfamily cell adhesion molecules (IgCAMs) Fasciclin 2 (Fas2) and Neuroglian (Nrg), homologs of vertebrate NCAM and L1-CAM, respectively. In their earlier work, the authors described the roles of these IgCAMs in the Drosophila follicle epithelium, where Fas2 and Nrg are required for cell reintegration after mitosis. During cell division, errors in spindle positioning can cause newly born cells to get displaced from the epithelial sheet. Such apically extruded cells normally re-integrate with high efficiency into the epithelium. As the authors previously showed through genetic studies in the Drosophila follicle epithelium, mutations in Fas2 and Nrg act synergistically to disrupt reintegration, leading to the accumulation of extruded ("popped out") cells. A puzzle arose when the authors compared the phenotypes of two different presumed protein-null alleles of Fas2 (Fas2(EB112) and Fas2(G0336)), which showed different strengths of epithelial cell reintegration defects. They systematically examined the phenotypes of Fas2(G0336) and two different fly strains carrying the Fas2(EB112) allele and discovered that the more severe defects seen in one of the Fas2(EB112) strains are due to the presence of an additional mutation in Nrg on the same chromosome. Intriguingly, they identified the mutation in the Nrg locus as the previously characterized Nrg(14) allele. This suggests that the Fas2 Nrg double mutant chromosome did not arise naturally through random appearance of a second-site mutation, but that it was generated intentionally and then apparently got mixed up with the Fas2(EB112) strain (however, the authors do not comment on this point). The authors spared no effort to resolve this genetic puzzle in a clear and convincing manner. The used clever genetics, genome sequencing and polytene chromosome preparations to unveil the Nrg mutation as Nrg(14). The results are very clearly documented, and the text is well written, almost in the style of a criminal investigation. I have only minor comments to be addressed by the authors before the manuscript should be published. p. 5: " The second chromosome that we generated through recombination did not demonstrate decreased anti-Fas2 immunoreactivity or the presence of popped-out cells (Figure 2A,B)..." The latter finding is surprising, as the authors previously showed that the Nrg(14) mutation leads to an increase in the number of popped out cells (Cammarota et al. 2020). They discuss this issue later in the text, but the reason for this discrepancy remains unclear. In the same context, p. 9: " Consistent with this, we find that E(Fas2)mut does not increase the number of popped-out cells in Nrg knockdown tissue (Figure 4B)." But Fig. 4B shows that Nrg knockdown increases the number of popped out cells in E(Fas2) mutant clones. Assuming that Nrg14 is a true null allele, this result would suggest that the effect of Nrg knockdown on the frequency of popped out cells is an RNAi artifact (off-target effect)? The authors should comment on this issue.
Fig. 3F: The Nrg(167) band in the Fas2(EB112) Mannheim lane is stronger than in the control (w1118), suggesting that Nrg(167) expression is upregulated when Fas2 levels are reduced. Please comment.
The authors refer to the enhancer of Fas2 mutation interchangeably as e(Fas2) and E(Fas2). As I understand, the mutation is recessive, and should therefore be referred to as e(Fas2).
p. 4: "Both Fas2EB112 (Grenningloh, Rehm, and Goodman 1991) and Fas2G0336 are thought to be protein null (Bergstralh, Lovegrove, and St Johnston 2015)." The authors should explain why these mutations are "thought to be protein null". They show that Nrg immunoreactivity is lost in Nrg(14) mutants, and likewise for Fas2. If both anti-Fas2 (1D4) and anti-Nrg antisera detect all isoforms of the respective proteins, the authors should state this clearly and modify their rather vague statement on p. 4 ("thought to be protein null").
Fig. 4C: Please add labels to indicate the gene locus (Fas2, Nrg) analyzed in each panel.
Fig. 4D: The chromosomes shown are from heterozygous flies carrying the respective mutation in trans to the w1118 X-chromosome. Correct genotypes should be indicated.
For the genome sequencing, what was the exact genotype of the flies that were sequenced? Hemizygous (lethal) embryos or heterozygotes? If DNA from heterozygotes was analyzed, how were short reads assigned to one of the parental (mutation-bearing or wild-type) chromosomes?
p. 8/9: "Figure X".
Figure legends: scale bars are in µm, not µM.
Referees cross-commenting
I agree that the results are important for a specialty audience concerned with the specific mutant strains described here.
Significance
Although the manuscript does not report a conceptual advance, the findings are very important for a significant part of the Drosophila community, particularly those studying Fas2 and Nrg. These proteins are involved in development of the nervous system, in synapse formation, as well as in epithelial morphogenesis and barrier formation. The Fas2(EB112) mutant has been widely used in at least 37 publications (dating back to 1991), several of which will need to be revisited in the light of the new findings reported here. This reviewer is a cell and developmental biologist with expertise in Drosophila genetics.
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Reply to the reviewers
We would like to sincerely thank both reviewers for taking the time to examine our work, for the cogent points they have raised, and their constructive attitude aimed at improving our manuscript.
Reviewer #1
- Single-cell RNAseq (Fig. 1B) and in situ (Fig. 3D) results both indicate that SNHG7 is broadly expressed in multiple epidermal layers but more enriched in the spinous layer. Although most assays, such as colony formation and Ki67 staining, did not specifically examine the role of SNHG7 in the spinous layer, the raft culture experiment seemed to indicate specific reduction of the spinous layer (Fig. 3H), which was more prominent than basal defects. The authors should examine the defects more carefully in the raft culture system by using basal, spinous and granular markers. It is possible that SNHG7 functions to maintain limited cell proliferation while restrict premature differentiation. In addition, they should perform serial passage experiments to distinguish whether overexpression of SNGH7 can indeed confer self-renewal in long-term experiments.*
We have included staining of a range of epidermal markers in the raft cultures (ITGB1, K14, K10 and IVL) in the revised manuscript (Fig. S6B). We do not observe major changes in the distribution of any of the differentiation markers.
In terms of serial passage, we have cultured SNHG7-overexpressing or control cells for multiple passages until their growth capacity was exhausted. The SNHG7-overexpressing cells grew for approximately seven more passages than the control cells. We have added this information to the revised manuscript (Fig. S6L).
- The main proposed mechanism is the sequestration of miR34 by SNHG7. While miR34 is well known for its function in inhibiting cell proliferation, the ability of coding or noncoding RNA to sequestrate miRNAs is highly dependent on the stability and copy number of these RNAs. Since they have single-cell data with UMI information, they should estimate the copy number of SNHG7 in epithelial cell populations, and this could provide a range for the "buffering" capacity of SNHG7. They should also examine, ideally by in situ hybridization, the expression patterns of miR34 in human vs mouse skin. While miR34 expression can be induced by p53 activation, it is possible that its expression varies in different species. It'll be interesting to determine whether the lack of miR34 expression in mouse keratinocyte or mouse skin could explain the insensitivity of mouse keratinocytes to SNHG7. Finally, to further demonstrate the competition between SNHG7 and miR34 targets, they can use a heterologous luciferase reporter system with a canonical miR34 targeting site in the 3'UTR and quantify luciferase activities with or without SNHG7 (or SNHG7 mut34 variant). This assay could quantify the impact of SNHG7 on individual miR34 targets.*
We will include the analysis of the scRNAseq data to estimate the copy number of SNHG7 in the epidermal populations.
We will also perform in situ hybridization staining for miR-34 in human and mouse epidermis as well as mouse keratinocytes.
Finally, we will carry out the luciferase reporter experiments.
Reviewer #2
Major comments:
1) The premise of the study relies on the observation that SNHGs have low levels of sequence conservation. Indeed the authors aim to prove that biological functions can be identified even in the absence of evolutionary conservation. However, the extent of evolutionary conservation strongly depends on the phylogenetic scale at which it is analyzed. Here, the authors evaluate sequence conservation using PhastCons and PhyloP scores determined using alignments of human and 99 other vertebrate species. These scores reflect the extent of long-term sequence conservation. At this scale, only a small percentage of the human genome can be considered to be "conserved". It is thus not surprising that SNHG and other lncRNAs are not conserved at this scale, even if they carry some biological functions in the human genome. Here, it would be useful to redo the sequence conservation analyses using PhastCons and PhyloP scores computed on less distant species. Pre-computed scores exist for alignments containing human and other mammalian species, mainly primates (UCSC genome browser). It would also be good to provide comparisons of sequence conservation levels on the snoRNA genes and on the non-snoRNA parts of SNHGs. In addition to protein-coding genes, pseudogenes and lncRNAs, it would be good to add a perfectly neutral control for the sequence conservation in Figure 1C - for example, flanking intergenic regions for SNHGs. It might also be a good idea to analyze the GC content of SNHGs compared to other lncRNAs, since GC content can be correlated with sequence conservation levels, in particular in noncoding regions.
Importantly, the SNHG selected for detailed investigation (SNHG7) appears to be more conserved than the bulk of human lncRNAs, given that it is found in another primate and in mouse. It would be interesting to analyze in details what sequence features of this lncRNAs are conserved among species - for example, are the SNHG7 splice sites and promoter regions conserved? Are the snoRNA genes always located in the introns?
The reviewer raises very good points. We have added the conservation data of snoRNA genes (all or SNHG-resident, both significantly more conserved than SNHGs or lncRNA), and a “true neutral” control (we used the introns of 10,000 randomly sampled genes) to our PhastCons analysis (Fig.1C). We also added a conservation analysis of the promoters (defined as the 500 bp upstream of the transcription start site) of coding genes, pseudogenes, lncRNA and SNHGs (Fig, S1B). We have now performed all our conservation analyses using both PhastCons scores generated from the 100-vertebrate alignment and PhastCons scores generated from the 30-mammals (28 primate) alignment (Fig. S1E-G). We do not detect any marked difference between the two alignment sets. We have also added a comparison of the GC content in lncRNA, SNHGs, coding genes and introns (Fig.S1C).
Due to the nature of the PhyloP scores, the 30-mammal PhyloP track (phyloP30) would be unsuitable to detect additional conservation in the primate lineage using the thresholding analysis we employed in Fig. 1E. The PhyloP track gives base-wise p-values for conservation (positive values) or accelerated evolution (negative values). Using alignments of genomes that are overall more similar to each other (as in the 30-mammal alignment set) makes it more difficult to distinguish between conserved and neutrally evolving regions, because even segments that are not under constraint will look relatively similar due to the evolutionary proximity of the species in the set. For the same reason this alignment set is quite sensitive to accelerated evolution, as it contains many relatively similar genomes it the alignment.
This causes the PhyloP30 scores to be very asymmetrical around zero: the conservation (positive) scores never reach 2 (p-value of 0.01) in the whole track (not even coding regions of very well-conserved genes), while acceleration scores can reach very significant values, down to -20. Conversely, the PhyloP100 track (used in Fig.1E) is quite symmetrical around 0 and is thus better suited for the purposes of the analysis in Fig.1E, which are to detect both conserved and accelerated portions of SNHGs. We have however also inspected the PhyloP30 track manually and do not observe any clear evidence of presence of additional conserved elements in SNHG7. We have added all conservation tracks for SNHG7 to Fig. 3A.
While lncRNA orthologs can be identified by using a combination of sequence conservation, conserved synteny with surrounding genes and in some cases conserved gene structure, SNHG orthologs can additionally be identified by the embedded (conserved) intronic snoRNA sequence, which makes them easier to find even when the transcript sequence bears no similarity across species. The mouse SNHG7 sequence, for example, does not match with human SNHG7 even using the least stringent BLAST parameters. The monkey sequence is similar enough to match with the human in the 3’ of the gene, but the intron-exon structure of the 5’ is completely different. We agree with the reviewer’s assessment, however, when it comes to identification of SNHG orthologs in more evolutionary distant species, closer to the root of the vertebrate clade.
Regarding splice sites, they are often conserved among lncRNA in general (gene structure conservation occurs more frequently than sequence conservation, see Ulitsky, Nat Rev Genet, 2016). In the case of SNHG7 the structure of the gene appears conserved in the mouse (though this annotation has likely not been fully confirmed experimentally), and in the monkey based on genome alignments. However, our RACE experiments show that the 5’ end of SNHG7 in the monkey has a radically different splicing pattern when compared to human, so it is difficult to assess splicing conservation in the absence of full isoform characterization.
2) I am not perfectly convinced by the enrichment of miRNA target genes among the genes that are downregulated upon SNHG knockdown. The methods do not clearly explain how this enrichment is calculated. What is the background used for this enrichment analysis? In Figure 5C, we see that the genes predicted to be targeted by the top 10 microRNAs tend to have negative fold changes in the differential expression analysis (downregulation following knockdown). However, from Figure 5A it seems that the great majority of significantly differentially expressed (DE) genes have negative fold changes. How do the miRNA target genes differ from all other DE genes? What proportions of all predicted miRNA target genes (expressed in keratinocytes) are DE following knockdown, and how does this compare with the target genes of other miRNAs?
We have added a description of the statistical test used by MIENTURNET for the enrichment analysis to the methods section. More details can be found in the original publication. The significance of the enrichment is calculated by performing a hypergeometric test using as background the total number of miRNA-target interactions in the database and the total interactions the individual miRNA being tested engages in.
Figure 5C only includes the genes we used in our enrichment analysis (i.e. the significantly downregulated genes, not all DE genes) and it’s meant to show the extent of downregulation exhibited by the targets of the most significantly enriched miRNAs within this group of genes.
The reviewer is correct in pointing out that the imbalance between downregulated and upregulated genes (which we now further highlight in the plots in Fig. 5A-B) will tend to skew any group of genes towards having a relatively large number of downregulated genes. However, we found this bias to be particularly strong in the case of our candidate miRNAs. We now show this in volcano plots for validated targets of the candidate miRNAs and a control miRNA (Fig. S8E). In a similar way, when looking at the cumulative distributions of the fold changes of all predicted targets for a certain miRNA and comparing it to the fold change cumulative distribution of all other genes, our candidate miRNAs displayed a more pronounced shift towards downregulation than the control miR-21-5p (which we now added in Fig. S8F).
3) If keratinocyte RNA-seq data is available for other species (for example mouse), it would be interesting to test whether the high expression levels of SNHG7 and the other analyzed SNHGs are also conserved in the other species.
We will include the RNA-seq data, if available.
Minor comments:
1) The AD (atopic dermatitis) abbreviation should be explained the first time it is mentioned in the text.
We thank the reviewer for pointing out the missing abbreviation, we have now added it.
2) More details are needed regarding the MIENTURNET analyses in the methods and in the main text
We have added more details about the statistics involved to the methods (see above).
*3) Figure 5C, it is not clear how to interpret the color code for the boxplot. Does this represent the median or mean FDR of the target genes? Are only genes with FDRThe genes included in the enrichment analysis are all downregulated genes with an adjusted p-value (or FDR adjustment after the Wald test) adj”. The color scale in Fig 5C reports the significance of the enrichment for targets of the single miRNAs within the significantly downregulated genes list (FDR adjustment after the hypergeometric test), not the significance of the downregulation itself. FDR values are also used for all other enrichment analyses (GO terms, REACTOME Pathways). We apologise to the reviewer for the confusion, we have now modified the text and figures to make this clearer.
4) Figure 6D, I am not sure how to the D panel. Do the gray rectangles represent the exonic length of the SNHGs? Do the dots correspond to the positions of the miRNA target sites? Here, a more quantitative comparison with the extent of sequence conservation of miRNA binding sites in SNHGs, other lncRNAs and in protein-coding genes would be perhaps better suited.
The grey rectangles in Fig. 6D represent the total exonic length of the SNHGs (basically all exons are “stitched together” head to tail irrespective of the actual isoforms) and the dots represent the positions of the miRNA binding sites within this “maximum exonic coverage”. Since not all individual isoforms are analysed it is possible that some additional miRNA sites can be created at alternatively spliced junctions, however we would estimate the number of such sites to be small. We have added this caveat to the methods section.
The degree of conservation that is estimated by TargetScan to underlie a functional MRE in coding genes is taken into account in this analysis, as sites within SNHGs that pass this threshold are highlighted with yellow borders in the figure. We have now added a plot of the distribution of Branch length scores for MREs in SNHGs and the distribution of Branch length scores for MREs in a random sample of 250 Coding genes UTRs (Fig. S9E). A similar comparison for lncRNA is more challenging as the data is not readily available and is likely to be confounded by the nuclear localisation of a majority of lncRNA species.
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Referee #2
Evidence, reproducibility and clarity
Summary
The manuscript submitted by M. Vietri Rudan and co-authors presents a functional analysis of a specific class of long non-coding RNA transcripts, namely the small nucleolar RNA host genes (SNHGs). These genes are defined by the fact that snoRNA molecules are embedded within their loci, often in the SNHGs introns. The rationale presented by the authors for studying this specific class of lncRNA genes is the fact that they display very low levels of evolutionary sequence conservation (even compared to the generally low conserved lncRNA transcripts) and that they are expressed at remarkably high levels (contrary to most lncRNA genes, which are very weakly expressed). The overarching goal of this study thus appears to be determining whether functional transcripts can exist in the absence of evolutionary conservation.
The authors study SNHGs in the human keratinocytes model system. They analyze the expression levels of SNHGs in skin affected by atopic dermatitis and psoriasis, compared to normal skin. They identify several SNHGs that are differentially expressed between diseased and normal skin, and which are also detected at strong expression levels in single cell RNA-seq assays of human keratinocytes. The authors use knockdown assays to investigate the potential roles of these SNHGs in keratinocytes and show that the knockdown of each of 5 selected SNHGs results in a loss of clonogenicity.
The last part of the manuscript focuses on the functional characterization of SNHG7, chosen because it is dysregulated in both atopic dermatitis and psoriasis and because its knockdown strongly affects clonogenicity. Additional assays showed that SNHG7 knockdown results in a reduced rate of proliferation and an increase in the fraction of differentiating cells. To ensure that the effects of the knockdown are not simply due to the absence of the snoRNA molecules embedded in the SNHG7 locus, the authors overexpressed the spliced form of SNHG7 (which lacks the snoRNA genes), successfully rescuing the cellular phenotype. They also verified that the knockdown does not affect the abundance of the corresponding snoRNA molecules.
To propose a potential mechanism for the involvement of SNHG7 in keratinocyte proliferation, the authors investigated its capacity to act as a miRNA "decoy". They searched for an enrichment of miRNA binding sites among the genes that are downregulated following SNHG7. They identified several miRNAs which are predicted to target SNHG7 as well as (a substantial fraction of) the genes that are downregulated following SNHG7 knockdown. The transfection of two of these miRNAs (miR-193-3p and miR-34-5p) has a negative effect on keratinocyte proliferation, supporting the authors's hypothesis that SNHG7 may act via "sponging" these miRNAs, thereby positively contributing to the control of the expression of the other miRNA target genes. Consistent with this hypothesis, the authors show that overexpression of a SNHG7 mutant sequence that lacks the miRNA binding sites is not able to rescue the knockdown phenotype.
However, this hypothesis is not supported (or at leat not further reinforced) by the evolutionary analysis performed by the authors. They were able to identify homologues for SNHG7 in another primate species (night monkey) and in the mouse. Transfection of the human SNHG7 sequence was able to increase clonogenicity in night monkey cells, but not in mouse cells. Given that miR-34 is also present in mouse and was previously shown to affect keratinocyte proliferation, it is not clear why the human SNHG7 sequence is not able to act as a miRNA sponge in this species. Likewise, only a slight effect on clonogenicity is observed upon SNHG7 transfection in night monkey. The authors conclude (correctly, in my view) that further investigations are needed to confirm the potential functions of SNHG7.
Overall, I find that this study is interesting and carefully conducted. Nevertheless, I have several comments that I hope can improve this manuscript.
Major comments:
- The premise of the study relies on the observation that SNHGs have low levels of sequence conservation. Indeed the authors aim to prove that biological functions can be identified even in the absence of evolutionary conservation. However, the extent of evolutionary conservation strongly depends on the phylogenetic scale at which it is analyzed. Here, the authors evaluate sequence conservation using PhastCons and PhyloP scores determined using alignments of human and 99 other vertebrate species. These scores reflect the extent of long-term sequence conservation. At this scale, only a small percentage of the human genome can be considered to be "conserved". It is thus not surprising that SNHG and other lncRNAs are not conserved at this scale, even if they carry some biological functions in the human genome. Here, it would be useful to redo the sequence conservation analyses using PhastCons and PhyloP scores computed on less distant species. Pre-computed scores exist for alignments containing human and other mammalian species, mainly primates (UCSC genome browser). It would also be good to provide comparisons of sequence conservation levels on the snoRNA genes and on the non-snoRNA parts of SNHGs. In addition to protein-coding genes, pseudogenes and lncRNAs, it would be good to add a perfectly neutral control for the sequence conservation in Figure 1C - for example, flanking intergenic regions for SNHGs. It might also be a good idea to analyze the GC content of SNHGs compared to other lncRNAs, since GC content can be correlated with sequence conservation levels, in particular in noncoding regions.
Importantly, the SNHG selected for detailed investigation (SNHG7) appears to be more conserved than the bulk of human lncRNAs, given that it is found in another primate and in mouse. It would be interesting to analyze in details what sequence features of this lncRNAs are conserved among species - for example, are the SNHG7 splice sites and promoter regions conserved? Are the snoRNA genes always located in the introns? 2. I am not perfectly convinced by the enrichment of miRNA target genes among the genes that are downregulated upon SNHG knockdown. The methods do not clearly explain how this enrichment is calculated. What is the background used for this enrichment analysis? In Figure 5C, we see that the genes predicted to be targeted by the top 10 microRNAs tend to have negative fold changes in the differential expression analysis (downregulation following knockdown). However, from Figure 5A it seems that the great majority of significantly differentially expressed (DE) genes have negative fold changes. How do the miRNA target genes differ from all other DE genes? What proportions of all predicted miRNA target genes (expressed in keratinocytes) are DE following knockdown, and how does this compare with the target genes of other miRNAs? 3. If keratinocyte RNA-seq data is available for other species (for example mouse), it would be interesting to test whether the high expression levels of SNHG7 and the other analyzed SNHGs are also conserved in the other species.
Minor comments:
- The AD (atopic dermatitis) abbreviation should be explained the first time it is mentioned in the text.
- More details are needed regarding the MIENTURNET analyses in the methods and in the main text
- Figure 5C, it is not clear how to interpret the color code for the boxplot. Does this represent the median or mean FDR of the target genes? Are only genes with FDR<5% included in this analysis?
- Figure 6D, I am not sure how to the D panel. Do the gray rectangles represent the exonic length of the SNHGs? Do the dots correspond to the positions of the miRNA target sites? Here, a more quantitative comparison with the extent of sequence conservation of miRNA binding sites in SNHGs, other lncRNAs and in protein-coding genes would be perhaps better suited.
Significance
Overall, this study is highly relevant in the field of lncRNA functionality and evolution. It presents evidence for a potential involvement in the regulation of cell proliferation for SNHGs, a role that appears to be independent of the snoRNAs produced by these loci. This study reinforces the current body of work suggesting that lncRNAs and other noncoding transcripts can sometimes function as miRNA "decoy" targets. This study will be of interest for a specialized audience, oriented towards understanding lncRNA biological functions.
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Referee #1
Evidence, reproducibility and clarity
Vietri Rudan and colleagues present an interesting study to examine the function and mechanism of small nucleolar RNA Host Gene 7 (SNHG7) in human keratinocytes. The key findings are that a widely expressed SNHG7, a long noncoding RNA hosting two snoRNAs in the introns, promotes keratinocyte proliferation and inhibits differentiation likely by sequestrating miR34a from its targets. The experiments are generally well-executed with proper controls. Notably, they leveraged human, night monkey and mouse keratinocytes to reveal primate specific functions of SNHG7 in a miR34 dependent manner. I have a few comments and suggestions that should be addressed to further strengthen the study.
- Single-cell RNAseq (Fig. 1B) and in situ (Fig. 3D) results both indicate that SNHG7 is broadly expressed in multiple epidermal layers but more enriched in the spinous layer. Although most assays, such as colony formation and Ki67 staining, did not specifically examine the role of SNHG7 in the spinous layer, the raft culture experiment seemed to indicate specific reduction of the spinous layer (Fig. 3H), which was more prominent than basal defects. The authors should examine the defects more carefully in the raft culture system by using basal, spinous and granular markers. It is possible that SNHG7 functions to maintain limited cell proliferation while restrict premature differentiation. In addition, they should perform serial passage experiments to distinguish whether overexpression of SNGH7 can indeed confer self-renewal in long-term experiments. Based on these results, they may need to refine their hypothesis/conclusion whether SNHG7 functions primarily on stem cell self-renewal or transiently maintain proliferation in transitioning cells.
- The main proposed mechanism is the sequestration of miR34 by SNHG7. While miR34 is well known for its function in inhibiting cell proliferation, the ability of coding or noncoding RNA to sequestrate miRNAs is highly dependent on the stability and copy number of these RNAs. Since they have single-cell data with UMI information, they should estimate the copy number of SNHG7 in epithelial cell populations, and this could provide a range for the "buffering" capacity of SNHG7. They should also examine, ideally by in situ hybridization, the expression patterns of miR34 in human vs mouse skin. While miR34 expression can be induced by p53 activation, it is possible that its expression varies in different species. It'll be interesting to determine whether the lack of miR34 expression in mouse keratinocyte or mouse skin could explain the insensitivity of mouse keratinocytes to SNHG7. Finally, to further demonstrate the competition between SNHG7 and miR34 targets, they can use a heterologous luciferase reporter system with a canonical miR34 targeting site in the 3'UTR and quantify luciferase activities with or without SNHG7 (or SNHG7 mut34 variant). This assay could quantify the impact of SNHG7 on individual miR34 targets.
Significance
This study reveals a potential function and mechanism of primate specific noncoding RNA for its role in modulating gene expression and cellular functions in the skin. It provides a new paradigm for identifying molecular functions of poorly conserved RNAs.
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Reply to the reviewers
Manuscript number: #RC-2023-02281
Corresponding author(s): Maurizio Molinari
Point-by-point description of the revisions
This section is mandatory. *Please insert a point-by-point reply describing the revisions that were already carried out and included in the transferred manuscript. *
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Reviewer #1 (Evidence, reproducibility and clarity (Required)):
In this manuscript from Fasana et al., the authors present data that investigates potential compensatory degradation pathways for misfolded glycoproteins in the ER - postulating that the ER-to-lysosome associated degradation (ERLAD) pathway becomes employed in the absence of a path for substrates to reach the ER-associated degradation (ERAD) mechanism. Using the classic ERAD substrate alpha1-antitrypsin NHK variant (NHK), the authors first demonstrate that pharmacologically preventing access of NHK to ERAD either with KIF (early) or PS-341 (late) elevates the number of LAMP-1 positive endolysosomes also immunoreactive for NHK (via HA), similar to what is observed for the ATZ variant that forms polymers in the ER (Fig 2). The authors next use shRNAs that silence essential ERAD factors (EDEM1, OS-9) involved in glycan recognition to demonstrate comparable enrichment of NHK in endolysosomes through genetic disruption (Fig 3). Next, the authors employ FAM134B-deficient MEFs to demonstrate the requirement for this ER-phagy receptor when ERAD is unavailable (Fig 4). Reconstituting FAM134B-/- MEFs treated with KIF/PS-341 + Baf, with a full length FAM134B rescue plasmid restores endolysosomal accumulation of NHK while a FAM134B-∆LIR does not, providing supporting evidence for substrate rerouting to ERLAD. Finally, the authors use knockouts of Atg7 and Atg13 to demonstrate dependence on LC3 lipidation and independence from macro-ERphagy (Fig 6), that points towards a pathway that is like that used to remove ATZ polymers. From these data, the authors conclude that ERLAD is increasingly engaged for substrate degradation when ERAD is impaired.
MAJOR COMMENTS 1. All assays rely on quantification of the NHK-HA substrates by microscopy. Would it be possible for the authors to also include biochemical analysis of NHK - potentially including data assessing its changing abundance and glycosylation state?
To consider this, and other comments, the new submission includes biochemical data (pulse-chase analyses) on NHK (new panels A-D in Fig. 2) and on BACE457delta, an additional ERAD substrate (new Fig. 6). Please also refer to Comment 3.
In Figure 3D, the knockdown of OS-9.1/2 is modest compared to that of EDEM1 (Fig 3A). Moreover, there is only data from single shRNAs presented. Could the authors please at least include another shRNA to confirm and demonstrate whether the targeting to ERLAD is accordingly scaled to loss of access to ERAD (based on the degree of OS-9 or EDEM1 remaining)?
__The reviewer is right. The phenotype (i.e., lysosomal delivery of NHK, Figs. 3B, 3C) is quite modest upon EDEM1 silencing. However, one has to consider that in contrast to OS9 lectins, EDEM1 is an enzyme, and residual protein may partially facilitate NHK de-mannosylation and access to the ERAD pathways and therefore reduce the ERLAD contribution for NHK clearance in these cells. Moreover, cells also express EDEM2 and 3 that may partially compensate the loss of EDEM1. __
While degradation is implied, it is not specifically demonstrated at any point in the manuscript. Perhaps the authors might include some demonstration of NHK stabilization in one of the figures via a translational shutoff or pulse-chase assay.
__In the new submission, we show biochemical analyses (pulse-chase) that reveal the decay of radiolabeled NHK (Fig. 2A, lanes 1-3) and BACE457delta (Fig. 6A, lanes 1-3), the inhibition by PS341 (lanes 4, 5) and by KIF (lanes 8, 9), and the intervention of lysosomal enzymes when ERAD is inhibited (lanes 6, 7 and 10, 11). Moreover, we confirm that the protein delivered to the endolysosome is eventually degraded by performing a Bafilomycin washout experiment (new Fig. 2J-2O). __
10-30% of NHK-HA positive endolysosomes are detected even with Baf alone (e.g. Fig 2E)? Does this mean that Baf impairs ERAD to some extent since or is it evidence for continuous ERLAD involvement when ERAD is intact? If so, how much is its contribution?
Pulse-chase analyses (new Fig. 2D) and published data show that BafA1 or chloroquine do not inhibit clearance of the ERAD substrates NHK and BACE457delta (e.g., Liu et al 1999, Molinari et al 2002, references in the manuscript). A basal level of endolysosomal delivery between the 20 and 30% as quantified with LysoQuant is observed in all experiments (Figs. 2I, 2O, 3C, 3F, 4C, 4K, 5H, 6G, 6O), which have been performed in 3 different cell lines (3T3, HEK293, MEF). We measure similar basal levels also when ER-phagy is monitored on quantification of lysosomal delivery of endogenous ER marker proteins (e.g., CNX), possibly to be ascribed to constitutive ER phagy that controls physiologic ER turnover.
An accounting of how much ERLAD is contributing to NHK degradation with or without ERAD impairment is not really present.. Effectively, how much degradation capacity is ERLAD making up? These would be interesting data to include if possible as they would speak to the "division of labour" for ER substrate degradation its potentially dynamic nature.
The biochemical analyses show the contribution of ERLAD on NHK (new Figs 2B, 2C, grey zones) and BACE457delta (new Figs. 6B,C, grey zones) clearance, when ERAD is dysfunctional.
MINOR COMMENTS 1. In Figure 4, an increase is observed for the rescue of FAM134B-/-MEFs with WT FAM134B that is 50% greater that of WT MEFs, suggesting that its availability might be rate limiting. Could the authors compare the relative levels of FAM134B for the WT and KO-rescue MEFs to address this possibility?
__The referee is right in assuming that FAM134B, expressed at low levels in these cells, is limiting. We now show the levels of endogenous FAM134B and of recombinant FAM134B in WB (new Fig. 4A). __
In Figures 1 and 6, the terms siOS9 and siEDEM1 are used but Figure 3 shows data from shRNAs and not siRNAs.
We apologize for the mistake. We have corrected this in the new Figures 1 and 7.
Samples from Figure 3 treated with Baf but this is not indicated in the figure or figure legend.
We have corrected this, thank you.
VCP/p97 inhibitors typically stabilize ERAD glycoprotein substrates better than proteasome inhibitors do. Is the same degree of endolysosomal targeting present ?
__For the convenience of the reviewer (we did not put these data in the new manuscript). In our experiments, the p97 inhibitor DBeQ is less efficient in deviating NHK to the endolysosomal degradative compartments, if compared with KIF (see below). At higher doses, DBeQ also inhibits other AAA-ATPases (e.g., VPS4, which plays a role in certain types of autophagy). This, or other cross-reactivities of DBeQ could explain the moderate capacity to activate ERLAD pathways as a response of ERAD inhibition, if compared with the phenotypes observed when ERAD is inhibited with KIF or PS341. __
Reviewer #1 (Significance (Required)):
Deconvolution of the different pathways taken by misfolded proteins to escape the ER is of great interest not only to the ER community but also represents consequences to consider for those interested in therapeutics involving UPS inhibition. While concise, this manuscript does a good job of trying to demonstrate the principal of substrate rerouting and the prioritisation of degradation pathways. Overall, the manuscript is well written, the experiments presented are performed to a sufficient standard, the data are lean but of good quality, and the appropriate statistical analyses have mostly been included where necessary and are described. The Methods and Materials is brief but describes the experiments that have been performed. The manuscript is brief in its results and would obviously benefit from additional complementary assays that would strengthen and broaden the authors arguments for rerouting. But too their credit, the authors do not grossly overstate their findings and merely present the culmination of a set of experiments to answer a single question - what happens to a misfolded glycoprotein substrate when ERAD is impaired. This is a key question with broad implications.
While their limited data clearly demonstrates an acquired dependence on ERLAD, one can't help but wonder how broadly these findings hold true, as only a single glycoprotein substrate example is used.
We have now added a complete set of experiments (imaging + biochemical to monitor clearance of the model polypeptides by pulse-chase analyses) performed with a second ERAD substrate (BACE457delta, Fig. 6). These data fully recapitulate the results obtained with NHK.
Moreover, it is not clear what percentage ERLAD contributes to overall NHK degradation (with or without ERAD) as the total NHK amount remaining is not assessed or measured.
Pulse-chase analyses (new Fig. 2D) and published data (e.g., Liu et al 1999, Molinari et al 2002, references in the manuscript) show that BafA1 or chloroquine do not inhibit clearance of the ERAD substrates NHK and BACE457delta. The biochemical analyses now show the contribution of ERLAD on NHK (new Figs 2B, 2C, grey zones) and BACE457delta (new Figs. 6B,C, grey zones) clearance, when ERAD is dysfunctional.
Nevertheless, the manuscript is an advancement of understanding of the fate of substrates unable to access ERAD and raises many future questions of interdependency between the ERAD and ERLAD pathways. The data just need a bit of shoring up.
Expertise - ERAD, UPS, protein quality control
Reviewer #2 (Evidence, reproducibility and clarity (Required)):
The endoplasmic reticulum (ER) is a crucial site for protein synthesis and folding within the cell, and strict protein quality control is essential for maintaining ER homeostasis. In this context, ER-associated degradation (ERAD) and the unfolded protein response (UPR) play pivotal roles. Recent researches have highlighted the significance of ER-phagy in protein quality control. In this manuscript, the authors demonstrate the role of FAM134B in degrading misfolded proteins such as ATZ through the ER-phagy pathway when the ERAD pathway is obstructed. This work partially addresses a prominent issue in the field, unveiling the interconnections between different regulatory pathways in maintaining ER homeostasis.
Major issues: 1: In a multitude of experiments, the authors employed Bafilomycin A1 (BafA1) to block the fusion between autophagosomes and lysosomes, attempting to demonstrate that the clearance of misfolded proteins mediated by FAM134B is independent of autolysosomes. However, in Figure 4, the lack of rescue of FAM134B knockout by overexpressing FAM134B△LIR suggests a dependence on the interaction between FAM134B and LC3. The conclusions drawn before and after appear contradictory.
We apologize if our explanations were unclear. We have now modified the text and performed new experiments to clarify these issues.
__The inhibitor of the V-ATPase BafA1 is used here to inhibit the activity of lysosomal hydrolases and to accumulate undegraded material in the LAMP1-endolysosomes (note that these endolysosomes also display RAB7 at their limiting membrane) (Fregno et al 2018, Forrester et al 2019, Fregno et al 2021, …). __
__In Figs. 2A-2D, we now monitor the lack of NHK stabilization by cell exposure to BafA1 (Fig. 2D), which correlates with lack of accumulation of NHK in the LAMP1-positive compartment (e.g., Fig. 2F, 2J, and quantifications in 2I and 2O). The biochemical data also show that BafA1 stabilizes NHK in cells where ERAD has been inactivated with PS341 or KIF (Fig. 2A, lanes 6, 7, 10, 11 and grey zones in Figs. 2B and 2C), which correlates with accumulation of NHK in LAMP1-positive organelles (Figs. 2G, 2H, 2I, 2K, 2M, 2O). __
__In Figs. 2J-2O, we have now added panels showing that NHK clearance from the LAMP1-positive endolysosome lumen is restored upon BafA1 washout. __
Importantly, the involvement of the lipidation machinery, of the ER-phagy receptor FAM134B and of the LC3-binding function of FAM134B (the LIR), does not necessarily imply the involvement of autophagosomes in the process under investigation, as the comment by the referee seems to suggest. For example, both the clearance from the ER of ATZ polymers and of mutant forms of procollagen rely on the LC3 lipidation machinery and on the LC3-binding function of FAM134B, but ERLAD of ATZ polymers does not rely on autophagosomes intervention (new Fig. 1B, arrow 1 and Fregno et al 2018), whereas ERLAD of procollagen relies on intervention of autophagosomes (new Fig. 1B, arrow 2 and Forrester et al 2019).
2: Some Western blot data are insufficient to substantiate the author's conclusions. For instance, in Figure 5D, the ATG7 KO line is inadequately supported
The WB show____s the absence of ATG7 in the ATG7-KO cells (a well-established cell line generated in the lab of Masaaki Komatsu (____Komatsu M, et al. J Cell Biol 169: 425-434_) and used in many_ laboratories, including our lab in Fumagalli et al 2016, Fregno et al 2018, Fregno et al 2021, Loi et al 2019, Kucinska et al 2023). We agree with the reviewer that the anti-Atg7 shows cross-reactions. We have now added a WB showing the lack of LC3 lipidation in the Atg7-KO cells exposed to nutrient deprivation (new Fig. 5D).
3: The author employed Lamp1 antibody for lysosomal staining in cells and observed a significant abundance of lysosomes in some experiments, as depicted in Figure 2C, 2D, 4I, etc. Is the phenomenon of lysosomes extensively filling the entire cell a common occurrence? Is it indicative of a normal physiological state?
There may be variations depending on the cell type used for the experiments. In the new version of the manuscript, we now present imaging data for 3 cell lines (NIH 3T3 with stable expression of NHK and ATZ (Figs. 2E-2H), MEF (Figs. 2J-2N, 4, 5, 6) and HEK293 with transient expression of ERAD clients (Figs. 3).
Minor issues: 1: Some immunofluorescence experimental data are unclear. Please request the authors to replace these with more distinct images, as seen in Figure 3B and 3E.
We hope that the quality of the new images will be considered sufficient for publication.
2: Some expressions appear to be questionable. For instance, the necessity of utilizing endolysosomes requires clarification.
For the use of endolysosomes (lysosome would be incorrect in our opinion to indicate these LAMP1/RAB7-positive degradative organelles), we now refer to the papers by Bright et al ____Endolysosomes Are the Principal Intracellular Sites of Acid Hydrolase Activity_ Curr Biol 2016, and the original definition by Huotari and Helenius _Endosome maturation EMBO J 2011 (Introduction, page 2).
3: Some writing lacks precision, such as referring to FAM134B as FAM134.
__Corrected, thank you____ __ Reviewer #2 (Significance (Required)):
o General assessment: o Advance: provide an meaningful evidence that how two degradative pathways are coordinated in maintaining ER homeostasis. o Audience: cell biologist o Reviewer's expertise: autophagy, vesicle trafficking, organelle biolgy Reviewer #3 (Evidence, reproducibility and clarity (Required)):
In their study, Fasana and colleagues investigate protein quality control in the ER. Specifically, they test whether folding-incompetent proteins that are normally cleared by ER-associated degradation (ERAD) can also be targeted for degradation by direct vesicular transport from the ER to lysosomes in case ERAD is blocked. They show that blocking ERAD pharamacologically or genetically indeed leads to re-rerouting of an ERAD model substrate (the NHK variant of alpha-antitrypsin) to lysosomes and that this pathway requires the reticulon-like protein FAM134B, the ability of FAM134B to interact with the ubiquitin-like protein LC3 and the machinery for LC3 lipidation.
The paper is, for the most part, easy to follow. There are, however, a few minor issues and I think the authors could do more to connect their work with similar studies in the literature. Accordingly, I have some general and specific suggestions to make the manuscript more accessible for the reader.
General suggestions
- To avoid confusion, it would be helpful to more clearly distinguish between vesicular transport to endolysosomes and autophagy. Previous work by the authors has defined a trafficking pathway from the ER to endolysosomes that appears to rely on conventional vesicle-mediated transport (Fregno et al, EMBO J 2018). This pathway delivers material from the ER lumen to the lumen of endolysosomes, which are both topologically equivalent to the extracellular space. Hence, this pathway is distinct from autophagy, which is the transport of cytoplasmic components to endolysosomes and thus the transport of material from intracellular to extracellular space. This distinction is particularly important as both vesicular ER-to-lysosome transport and autophagy of the ER involve LC3 and FAM134B, which is typically referred to as an ER-phagy receptor. To make this less confusing, it may be helpful to explain that FAM134B appears to be a multifunctional molecule that can function as a receptor for macroautophagy but also in the vesicular transport pathway studied here. In addition, it would be helpful to point out that LC3 appears to also have roles unrelated to autophagosome formation.
The reviewer is referring to the original definition of ERLAD to describe the mechanisms of clearance of ATZ polymers (Fregno et al 2018). The definition of ERLAD has now been expanded and is given, for example, in Klionsky DJ, et al (2021) Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition). Autophagy 17: 1-382 and is explained in detail in our recent review Rudinskiy M, Molinari M (2023) ER-to-lysosome-associated degradation in a nutshell: mammalian, yeast, and plant ER-phagy as induced by misfolded proteins. Febs Letters: 1928-1945.
__Notably, the acronym ERAD for ER-associated degradation has originally been used to describe ____the proteasomal clearance from the ER of misfolded pro-alpha factor in a reconstituted yeast system in McCracken AA, Brodsky JL (1996) Assembly of ER-associated protein degradation in vitro: dependence on cytosol, calnexin, and ATP. The Journal of cell biology 132: 291-298. Only later on, the acronym has been used as an umbrella term that now covers all the pathways that control proteasomal clearance of misfolded proteins from the ER. A short historical excursus is presented in the new introduction to better explain these issues. __
It is well established that LC3 and the LC3 lipidation machinery have functions that go beyond macroautophagy (which involves double membrane autophagosomes). Micro-autophagy (or micro-ER-phagy to remain on the topic of our paper) is an example of autophagic pathway relying on ER-phagy receptor that engage LC3, on the LC3 lipidation machinery, without involving autophagosomes. This is schematically represented in the new Fig. 1B.
Several recent papers that appear relevant to the present study are not mentioned. In particular, Sun et al., Dev Cell 2023 (PMID: 37922908) appears worthy of discussion, as does Gonzalez et al., Nature 2023 (PMID: 37225996).
Thank you. Both papers are not directly linked to our study addressing the intervention of ERLAD pathways when ERAD activity is impaired. In particular the work of Gonzales et al describes post-translational modification of ER-phagy receptors for their activation. The Sun et al paper is not really related to the topic covered in our manuscript, but we cite it as an alternative pathway that removes ATZ from the ER (page 8).
Specific suggestions
- Abstract: The abstract begins with "About 40% of the eukaryotic cell's proteome is synthesized ... in the ER." Similar statements can be found in many papers and purportedly reflect common knowledge. However, it is unclear where the figure of 'about 40%' comes from. It would be proper to provide a reference and demonstrate that giving such a fairly precise estimate is supported by experimental data. Alternatively, the statement could be modified to avoid being precise than is justified.
No reference is allowed in the abstract. We therefore modified the sentence as suggested by the reviewer.
- p2: "The ER is site of gene expression in nucleated cells and ... native proteins to be delivered at their site of activity ...". There is something missing at the beginning of this sentence. Also, it should be 'delivered to their site of activity', not 'delivered at'.
Thank you
- p2: "... by mechanistically distinct ER-phagy pathways collectively defined as ER-to-lysosome-associated degradation ERLAD." This statement suggests that all pathways subsumed under the term ERLAD are ER-phagy pathways, which I believe is misleading (see comment above on the distinction between autophagy and vesicular transport pathway).
See point 1.
- p2: "KIF selectively ...". Please spell out KIF and explain what kind of compound it is.
Thank you, we changed to “_The alkaloid kifunensine (KIF) is a cell permeable selective inhibitor of the members of the glycosyl hydrolase 47 family of a____1,2-mannosidases_”____ __ 5. p3: "Notably, ERAD inhibition delays, rather than blocking degradation of ERAD clients ...". Please correct, for example: Notably, ERAD inhibition delays rather than blocks degradation of ERAD clients ...
Thank you
Figures 2 - 5: The number of quantified cells is given but it is not clear if experiments were done once or in biological replicates. Please indicate this in the figure legends.
__N is now given for all panels in the corresponding figure legends.____ __ 7. p4: "To verify if ERAD inactivation ..." sounds odd. Less ambiguous would be 'To test whether' or 'To ask if'.
Thank you
- p7, beginning of discussion: Please correct "delivered at" to 'delivered to'.
Thank you
Reviewer #3 (Significance (Required)):
This is a concise and convincing manuscript with a clear message. The idea that proteins that cannot be processed by ERAD can be eliminated by other means, for instance by autophagy, is not new. Similarly, the FAM134B- and LC3-dependent pathway for ER-to-lysosome transport has been described by the authors before (Fregno et al, EMBO J 2018). Furthermore, the study exclusively relies on microscopy and does not attempt to tackle new mechanistic questions. Still, this study presents a definite functional advance in our understanding of the interplay of various ER quality control pathways.
The findings presented here will be of interest mainly to molecular cell biologists working on protein quality control and organelle homeostasis. However, given the disease-relevance of misfolded proteins, and alpha-antitrypsin in particular, the impact of this study may eventually go beyond basic research and may also interest translational researchers.
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Referee #3
Evidence, reproducibility and clarity
In their study, Fasana and colleagues investigate protein quality control in the ER. Specifically, they test whether folding-incompetent proteins that are normally cleared by ER-associated degradation (ERAD) can also be targeted for degradation by direct vesicular transport from the ER to lysosomes in case ERAD is blocked. They show that blocking ERAD pharamacologically or genetically indeed leads to re-rerouting of an ERAD model substrate (the NHK variant of alpha-antitrypsin) to lysosomes and that this pathway requires the reticulon-like protein FAM134B, the ability of FAM134B to interact with the ubiquitin-like protein LC3 and the machinery for LC3 lipidation.
The paper is, for the most part, easy to follow. There are, however, a few minor issues and I think the authors could do more to connect their work with similar studies in the literature. Accordingly, I have some general and specific suggestions to make the manuscript more accessible for the reader.
General suggestions
- To avoid confusion, it would be helpful to more clearly distinguish between vesicular transport to endolysosomes and autophagy. Previous work by the authors has defined a trafficking pathway from the ER to endolysosomes that appears to rely on conventional vesicle-mediated transport (Fregno et al, EMBO J 2018). This pathway delivers material from the ER lumen to the lumen of endolysosomes, which are both topologically equivalent to the extracellular space. Hence, this pathway is distinct from autophagy, which is the transport of cytoplasmic components to endolysosomes and thus the transport of material from intracellular to extracellular space. This distinction is particularly important as both vesicular ER-to-lysosome transport and autophagy of the ER involve LC3 and FAM134B, which is typically referred to as an ER-phagy receptor. To make this less confusing, it may be helpful to explain that FAM134B appears to be a multifunctional molecule that can function as a receptor for macroautophagy but also in the vesicular transport pathway studied here. In addition, it would be helpful to point out that LC3 appears to also have roles unrelated to autophagosome formation.
- Several recent papers that appear relevant to the present study are not mentioned. In particular, Sun et al., Dev Cell 2023 (PMID: 37922908) appears worthy of discussion, as does Gonzalez et al., Nature 2023 (PMID: 37225996).
Specific suggestions
- Abstract: The abstract begins with "About 40% of the eukaryotic cell's proteome is synthesized ... in the ER." Similar statements can be found in many papers and purportedly reflect common knowledge. However, it is unclear where the figure of 'about 40%' comes from. It would be proper to provide a reference and demonstrate that giving such a fairly precise estimate is supported by experimental data. Alternatively, the statement could be modified to avoid being precise than is justified.
- p2: "The ER is site of gene expression in nucleated cells and ... native proteins to be delivered at their site of activity ...". There is something missing at the beginning of this sentence. Also, it should be 'delivered to their site of activity', not 'delivered at'.
- p2: "... by mechanistically distinct ER-phagy pathways collectively defined as ER-to-lysosome-associated degradation ERLAD." This statement suggests that all pathways subsumed under the term ERLAD are ER-phagy pathways, which I believe is misleading (see comment above on the distinction between autophagy and vesicular transport pathway).
- p2: "KIF selectively ...". Please spell out KIF and explain what kind of compound it is.
- p3: "Notably, ERAD inhibition delays, rather than blocking degradation of ERAD clients ...". Please correct, for example: Notably, ERAD inhibition delays rather than blocks degradation of ERAD clients ...
- Figures 2 - 5: The number of quantified cells is given but it is not clear if experiments were done once or in biological replicates. Please indicate this in the figure legends.
- p4: "To verify if ERAD inactivation ..." sounds odd. Less ambiguous would be 'To test whether' or 'To ask if'.
- p7, beginning of discussion: Please correct "delivered at" to 'delivered to'.
Significance
This is a concise and convincing manuscript with a clear message. The idea that proteins that cannot be processed by ERAD can be eliminated by other means, for instance by autophagy, is not new. Similarly, the FAM134B- and LC3-dependent pathway for ER-to-lysosome transport has been described by the authors before (Fregno et al, EMBO J 2018). Furthermore, the study exclusively relies on microscopy and does not attempt to tackle new mechanistic questions. Still, this study presents a definite functional advance in our understanding of the interplay of various ER quality control pathways.
The findings presented here will be of interest mainly to molecular cell biologists working on protein quality control and organelle homeostasis. However, given the disease-relevance of misfolded proteins, and alpha-antitrypsin in particular, the impact of this study may eventually go beyond basic research and may also interest translational researchers.
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Referee #2
Evidence, reproducibility and clarity
The endoplasmic reticulum (ER) is a crucial site for protein synthesis and folding within the cell, and strict protein quality control is essential for maintaining ER homeostasis. In this context, ER-associated degradation (ERAD) and the unfolded protein response (UPR) play pivotal roles. Recent researches have highlighted the significance of ER-phagy in protein quality control. In this manuscript, the authors demonstrate the role of FAM134B in degrading misfolded proteins such as ATZ through the ER-phagy pathway when the ERAD pathway is obstructed. This work partially addresses a prominent issue in the field, unveiling the interconnections between different regulatory pathways in maintaining ER homeostasis.
Major issues:
- In a multitude of experiments, the authors employed Bafilomycin A1 (BafA1) to block the fusion between autophagosomes and lysosomes, attempting to demonstrate that the clearance of misfolded proteins mediated by FAM134B is independent of autolysosomes. However, in Figure 4, the lack of rescue of FAM134B knockout by overexpressing FAM134B△LIR suggests a dependence on the interaction between FAM134B and LC3. The conclusions drawn before and after appear contradictory.
- Some Western blot data are insufficient to substantiate the author's conclusions. For instance, in Figure 5D, the ATG7 KO line is inadequately supported
- The author employed Lamp1 antibody for lysosomal staining in cells and observed a significant abundance of lysosomes in some experiments, as depicted in Figure 2C, 2D, 4I, etc. Is the phenomenon of lysosomes extensively filling the entire cell a common occurrence? Is it indicative of a normal physiological state?
Minor issues:
- Some immunofluorescence experimental data are unclear. Please request the authors to replace these with more distinct images, as seen in Figure 3B and 3E.
- Some expressions appear to be questionable. For instance, the necessity of utilizing endolysosomes requires clarification.
- Some writing lacks precision, such as referring to FAM134B as FAM134.
Significance
- General assessment:
- Advance: provide an meaningful evidence that how two degradative pathways are coordinated in maintaining ER homeostasis.
- Audience: cell biologist
- Reviewer's expertise: autophagy, vesicle trafficking, organelle biolgy
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Referee #1
Evidence, reproducibility and clarity
In this manuscript from Fasana et al., the authors present data that investigates potential compensatory degradation pathways for misfolded glycoproteins in the ER - postulating that the ER-to-lysosome associated degradation (ERLAD) pathway becomes employed in the absence of a path for substrates to reach the ER-associated degradation (ERAD) mechanism. Using the classic ERAD substrate alpha1-antitrypsin NHK variant (NHK), the authors first demonstrate that pharmacologically preventing access of NHK to ERAD either with KIF (early) or PS-341 (late) elevates the number of LAMP-1 positive endolysosomes also immunoreactive for NHK (via HA), similar to what is observed for the ATZ variant that forms polymers in the ER (Fig 2). The authors next use shRNAs that silence essential ERAD factors (EDEM1, OS-9) involved in glycan recognition to demonstrate comparable enrichment of NHK in endolysosomes through genetic disruption (Fig 3). Next, the authors employ FAM134B-deficient MEFs to demonstrate the requirement for this ER-phagy receptor when ERAD is unavailable (Fig 4). Reconstituting FAM134B-/- MEFs treated with KIF/PS-341 + Baf, with a full length FAM134B rescue plasmid restores endolysosomal accumulation of NHK while a FAM134B-∆LIR does not, providing supporting evidence for substrate rerouting to ERLAD. Finally, the authors use knockouts of Atg7 and Atg13 to demonstrate dependence on LC3 lipidation and independence from macro-ERphagy (Fig 6), that points towards a pathway that is like that used to remove ATZ polymers. From these data, the authors conclude that ERLAD is increasingly engaged for substrate degradation when ERAD is impaired.
Major comments:
- All assays rely on quantification of the NHK-HA substrates by microscopy. Would it be possible for the authors to also include biochemical analysis of NHK - potentially including data assessing its changing abundance and glycosylation state?
- In Figure 3D, the knockdown of OS-9.1/2 is modest compared to that of EDEM1 (Fig 3A). Moreover, there is only data from single shRNAs presented. Could the authors please at least include another shRNA to confirm and demonstrate whether the targeting to ERLAD is accordingly scaled to loss of access to ERAD (based on the degree of OS-9 or EDEM1 remaining)?
- While degradation is implied, it is not specifically demonstrated at any point in the manuscript. Perhaps the authors might include some demonstration of NHK stabilization in one of the figures via a translational shutoff or pulse-chase assay.
- 10-30% of NHK-HA positive endolysosomes are detected even with Baf alone (e.g. Fig 2E)? Does this mean that Baf impairs ERAD to some extent since or is it evidence for continuous ERLAD involvement when ERAD is intact? If so, how much is its contribution?
- An accounting of how much ERLAD is contributing to NHK degradation with or without ERAD impairment is not really present.. Effectively, how much degradation capacity is ERLAD making up? These would be interesting data to include if possible as they would speak to the "division of labour" for ER substrate degradation its potentially dynamic nature.
Minor comments:
- In Figure 4, an increase is observed for the rescue of FAM134B-/-MEFs with WT FAM134B that is 50% greater that of WT MEFs, suggesting that its availability might be rate limiting. Could the authors compare the relative levels of FAM134B for the WT and KO-rescue MEFs to address this possibility?
- In Figures 1 and 6, the terms siOS9 and siEDEM1 are used but Figure 3 shows data from shRNAs and not siRNAs.
- Samples from Figure 3 treated with Baf but this is not indicated in the figure or figure legend.
- VCP/p97 inhibitors typically stabilize ERAD glycoprotein substrates better than proteasome inhibitors do. Is the same degree of endolysosomal targeting present
Significance
Deconvolution of the different pathways taken by misfolded proteins to escape the ER is of great interest not only to the ER community but also represents consequences to consider for those interested in therapeutics involving UPS inhibition. While concise, this manuscript does a good job of trying to demonstrate the principal of substrate rerouting and the prioritisation of degradation pathways. Overall, the manuscript is well written, the experiments presented are performed to a sufficient standard, the data are lean but of good quality, and the appropriate statistical analyses have mostly been included where necessary and are described. The Methods and Materials is brief but describes the experiments that have been performed. The manuscript is brief in its results and would obviously benefit from additional complementary assays that would strengthen and broaden the authors arguments for rerouting. But too their credit, the authors do not grossly overstate their findings and merely present the culmination of a set of experiments to answer a single question - what happens to a misfolded glycoprotein substrate when ERAD is impaired. This is a key question with broad implications.
While their limited data clearly demonstrates an acquired dependence on ERLAD, one can't help but wonder how broadly these findings hold true, as only a single glycoprotein substrate example is used. Moreover, it is not clear what percentage ERLAD contributes to overall NHK degradation (with or without ERAD) as the total NHK amount remaining is not assessed or measured. Nevertheless, the manuscript is an advancement of understanding of the fate of substrates unable to access ERAD and raises many future questions of interdependency between the ERAD and ERLAD pathways. The data just need a bit of shoring up.
Expertise - ERAD, UPS, protein quality control
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Reply to the reviewers
The authors do not wish to provide a response at this time.
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Referee #3
Evidence, reproducibility and clarity
The authors used hIPSCs to generate spheroids capable of elongation when cultured in KSR and exposed to BMP4. After examining all three developmental lineages of these treatments, the spheroids were embedded in different hydrogels to restrict movement and observed how this affected elongation and lineage differentiation. This manuscript was difficult to review because of the the style of the writing, the sometimes confused narrative of results, the problematic statistics and questionable interpretation of the literature. Authors should actively address the issues presented below with a significant overhaul of the text and presentation.
Overall comments
Major concerns - The body of the manuscript should be re-written to offer a coherent narrative that delivers a clear and condensed message . In fact, it was quite surprising given the well written and concise format of the introduction. However, there is some confusion about the interpretation of the first reference (https://doi.org/10.1038/s41586-020-2383-9) in which it was already presented that BMP4 treatment did not induce elongation in a hIPSC-derived gastruloid model. This is not to say that there is anything wrong with repeated experiments and different results, but the results from this reference were interpreted as if BMP4 treatment had induced elongation. The use of the methodology present in this manuscript as opposed to the validated model of using Wnt agonism to induce elongation is not convincingly justified. The results themselves have potential if reworded and condensed but in their current format they are not convincing. Statistics have substantial problems. According to the methodology, only one-way ANOVAs were used, when many of the circumstances would call for t-tests (if parametric) or at least mention the normality tests used to justify the ANOVAs. There is no clear mention of the number of independent differentiations and only one cell line was used. As a result of this, and the state of the statistics and interpretation of the data, the conclusions presented in this paper are inconclusive or misrepresented. The article should be re-written in a coherent scientific style, including not writing in the first person/active voice, and addressing the grammatical errors mentioned below.
Minor concerns - Throughout the methods there are issues with inconsistent notation, e.g. acronyms aren't always in brackets (HBSS, PBS, KSR), units are sometimes spaced from the value (10ng/mL or 10 µg/mL), units are incorrectly written (u instead of µ). There are also typographical errors such as basic grammar (capital letters and full stops), double spacing, typos, strange sentence construction, as well as interchangeable use of commas and semi colons when listing antibodies. These issues were not confined to the methods, but were particularly noticeable there, and so the whole manuscript requires thorough proofreading. Positive comments - The introduction was well written and concise, the images were mostly clear and easy to interpret, illustrating a result even if not directly the one described.
Specific Comments
Introduction - Comments
The introduction was well written and easy to follow. However, certain aspects should be refined in order to highlight the argument as to why the mechanical forces and environment are of importance to lineage determination in hIPSCs. For example, the paragraph describing 2D micropattern cultures could be reduced or integrated into the introduction of 3D gastruloid models. In its place, further exploration of examples of mechanical force's impact on stem cell/embryonic differentiation, both in vitro and in vivo, would be beneficial (perhaps including the geometric shape aspect mentioned in the 2D micropattern paragraph here instead). This would emphasise the necessity for investigation of environmental forces on 3D in vitro differentiation, tying it back to the first paragraph's broader developmental questions. Currently, it lacks the reiteration of the overarching purpose of this investigation.
Materials and Methods - Comments
hIPSC culture - The paper suggests that only one hIPSC line was used for this research; considering the variability innate to each stem cell line and their differentiation capabilities, at least two cell lines should be used. Please reference that stem cell validation was conducted by HipSci. It is concerning that antibiotics were used for tissue culture on such a short protocol and should not be used in future. Similarly, were these hIPSCs tested regularly for mycoplasma? Reference briefly the method in which hIPSCs were passaged and what range of passage number was used.
Spheroids derivation from hIPSCs - There is no mention of hIPSC confluency upon differentiation. Based on the brief 4 minutes of Accutase exposure, colonies would either be small to achieve single cell dissociation (which is not in the best interest of hIPSC colonies) or that single cell dissociation was not achieved. Seeding density is also close to double seeding density for currently circulating gastruloid protocols (see https://doi.org/10.1242/dev.150391) with no explanation as to why this cell count was chosen. Make mention of whether or not they were fed during the initial 48 hours. There is also no reference to how many independent differentiations were executed and therefore replicability is of significant concern considering the use of an unvalidated protocol.
Gastrulation-like induction of 3D hIPSCs - Difficult to follow timeline of treatments without reference to Figure 1 and therefore requires a rewrite for clarity. In addition, media 3 and 4 are formatted differently from 1 and 2, making it more confusing. Do not rely on Figure 1 to explain the treatment course, it should be clear in the methodology.
Live Imaging - No need to state each media, particularly if it is out of numerical order as described previously. Can be written as "Live hIPSC spheroids were imaged for 96 hours....". Also include magnification and time frame of each hour, e.g. between 48 and 96 hours. Immunofluorescence staining - Other than the grammatical errors referenced above, as there are numerous in this paragraph in particular, the catalogue number for each antibody should also be supplied. Considering the number of antibodies, perhaps this would be best supplied as a supplemental table. No mention either here or previously as to how non-encapsulated spheroids were mounted and if cleared.
Results - Comments
As mentioned previously, the results are written in a style which is not sufficiently rigorous for a scholarly article and should therefore be edited to reflect the standard expected quality. BMP4 signalling induces axial elongation in 3D gastrulation-like models -
Figure 1 - Nice and clean diagram but unnecessarily large, could be shrunk and placed at the top of Figure 2. Also is lacking key methodological details e.g. seeding density, reference to media changes in time line, etc.
An example of a statement that lacks rigor and specificity is the following: "We used defined medium conditions that provided consistent shape variation in spheroid morphology. E8 medium promotes self-renewing conditions, while KSR BMP4 triggers differentiation [31,32]". Self-renewing conditions of what? Differentiation of what? Into what cells?
These statements are too vague and remain without connection to the research This kind of issues are unfortunately recurrent throughout the manuscript. They are easily rectifiable with concise text rather than expecting the reader to search through references. "Consistent with our previous results..." - not referenced. Mention of size is brief in text and instead description of results is found in Figure 2 legend.
Figure 2 - Although Figure 2.A and 2.B are clear images, Figure 2.B is unnecessary and doesn't add anything to the message. Figure 2.C: The statistics for this table are hard to believe, except between E8 and KSR BMP4, due to the spread of the data. Change references to "size" to "sphericity", as size would arguably be better investigated using area as a metric, again be precise in choice of language. There isn't even a description of what Figure 2.D is portraying, nor error bars or notation of statistical testing.
Figure 3 - Figure 3.A Writing on scale bars is too small to be useful and unnecessary if mentioned in the legend. The images highlight the issue with the size/sphericity issue, although the images themselves are reasonably clear and will highlighted (if slightly overexposed and not cleared). The title of this figure is also misleading - E8 BMP4 is not emulating gastruloid development, and the gastruloid-like entity of KSR BMP4 has yet to be validated. A more appropriate title would be "Exposure to BMP4 in spheroid and elongated spheroid culture increases SOX17 expression". There is no mention of how cells were counted in methods and considering the variable fluorescence observed in Figure 3.A OCT4 for E8, this could easily be misconstrued. Inappropriate dictation of p value, should only be reporting the alpha. Much like the similar issue with sphericity, the error bars in Figure 3.E in particular make it difficult to believe the statistical significance achieved. Overall it seems inappropriate to focus solely on endodermal lineage and leave ectoderm and mesoderm to supplementals, when classically axial elongation in gastruloids is punctuated not just by SOX17 but also by BRACH expression throughout the extended region. This suggests that the authors may not have sufficiently evaluated the literature referenced. The justification provided by the authors for choosing SOX17 reinforces this fact by declaring that SOX17 is expressed during early development, as if SOX2 and BRACH isn't! Most concerningly, claims of SOX2's absence in E8 media spheroids as if to be a positive should actually be worrisome, considering SOX2 is a Yamanaka factor. Arguably, without further validation, this result undermines the foundation of this work.
PEG-peptide hydrogel encapsulation disturbs SOX17 patterning - The interchangeable use of "control" and E8 makes for difficult reading. Although no further substantial issues were taken with Figure 4 that had not already been addressed (scale bars, overexposure), the final comment of this section is simply inaccurate: "Overall, this suggests that embedding hiPSCs in a confining environment blocks morphogenesis, and despite the addition of BMP4, this was not sufficient to enable SOX17 expression.". It does not define that the hIPSCs in this case are spheroids and determines this assumption based off data in Figure 6.B and Figure 6.C which could have been easily integrated into Figure 4. Rather than comparing non-deg PEG to deg-PEG, in order to make this statement, it is necessary to compare the non-embedded spheroids to the embedded spheroids. There is also reference to a Figure 3.C. that does not exist.
Modulating PEG-peptide degradability promotes SOX17 expression - This section had similar issues to the one above, predominantly flitting between Figure 5 and 6 when it could have been condensed. The microscope images are also particularly poor, with high background in the 488 channel, overexposure for Hoechst and incomplete light penetrance in the centre for both E8 and E8 BMP4. Despite the lack of methodological explanation of how counting was conducted, these aspects are still likely to have had significant impact on cell count regardless of how the count was conducted. The last comment of this section is again questionable, as there is no definitive comparison as to what the deg-PEG is improving upon with regards to SOX17 expression.
Biochemical cues regulate morphogenesis via cell proliferation and cellular tension - There is no explanation as to why the manuscript pivots away from hydrogels to look at proliferation and F-actin. It does not appear to benefit the overarching goal of this manuscript (i.e. investigating the impact of confinement on 3D hIPSC-derived elongation models), with proliferation investigations feeling like an afterthought and F-actin investigations being placed about 3 sections too late. It was surprising to see EdU to check cell proliferation in this manner; similar can and should be achieved by using KI67 staining. This was a significantly missed opportunity to do pulse-chase experiments to understand potential cell cycle changes, and suggests the experimental design was not thought through. However, it is more reasonable to examine the F-actin network as shown by the manuscript. Although the pipeline in Figure 7.D is an interesting take on quantifying F-actin staining, no statistical analysis was undertaken to confirm a link between conditions and F-actin, nor F-actin and SOX17 expression, despite what this manuscript suggests. This should be coupled with information prior to the introduction to hydrogels, and then re-evaluated in those confined to hydrogels.
Overall these results need to be substantially edited for clarity, rigor and completeness. The narrative of the results is lost half way through, the statistics are questionable or non-existent and the logic behind certain experiments are debatable.
Discussion - Comments
To consider the models generated in this manuscript as gastruloids is misleading and inaccurate and should be replaced with something that reflects what was actually generated, e.g., BMP4-induced elongated spheroids. A quick search of key gastruloid papers, such as https://doi.org/10.1242/dev.113001, indicates how far detached the spheroids examined in this paper are, only sharing similar polarised SOX17 expression. In fact, the above referenced paper already examined aspects of classic gastruloid differentiation when exposed to BMP4, albeit using mESCs, and indicated that elongation only occurred in a proportion of the population. Similarly in the first reference which used hIPSCs specifically, https://doi.org/10.1038/s41586-020-2383-9, it was reported that BMP4 treatment did not induce elongation. At no point in this manuscript were these results discussed, which is concerning. Instead, this manuscript claims to have "robustly" concluded many of the results which have been questioned in detail above, with little reference to the variability across multiple differentiations or adequate statistical analysis. Noticeably they have also not mentioned their results on proliferation, which again makes the question of its relevance to the paper's aims.
Significance
The authors used hIPSCs to generate spheroids capable of elongation when cultured in KSR and exposed to BMP4. After examining all three developmental lineages of these treatments, the spheroids were embedded in different hydrogels to restrict movement and observed how this affected elongation and lineage differentiation. This manuscript was difficult to review because of the the style of the writing, the sometimes confused narrative of results, the problematic statistics and questionable interpretation of the literature. Authors should actively address the issues presented here with a significant overhaul of the text and presentation.
Our expertise is in stem cell biology, 2D and 3D model systems, microscopy, and single cell analysis.
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Referee #2
Evidence, reproducibility and clarity
Within the manuscript "Morphogen-driven human iPSCs differentiation in 3D in vitro models of gastrulation is precluded by physical confinement" by Alsehli et al, the authors aim to dissect the effects of biochemical cues and physical confinement using gastruloid models. Using this model, the authors find some indications that physical confinement prevents morphological changes and reduces lineage commitment of cells (as assayed by Sox 17).
While the manuscript addresses an interesting and important question, I do not think that the setup and data as present in the manuscript provide conclusive insight in any of the questions studied. First of all, the authors use a very different system (BMP4 induction) as compared to mainstream conditions for gastruloid formation. Based on the images and movies within the manuscript, symmetry breaking and elongation seem to be very sub-optimal under the conditions used by the authors, which makes any further functional assaying highly challenging. Importantly, it remains unclear why the authors did not (at least) include mainstream conditions (Chiron pulse) within their assays for comparative purposes, I feel this is a missed chance. On top of that, KSR is known to be poorly compatible with gastrulation and further development, at least in mouse (https://pubmed.ncbi.nlm.nih.gov/35988542/), so it remains unclear why the authors include a KSR condition.
Referees cross-commenting
Like me, both other reviewers indicated (major) shortcomings of the current paper, and indicated potential directions for improvement. Both these other reviews are very balanced as well. Altogether, there are significant changes required for the manuscript, and it depends on the authors which direction they would like to take this manuscript. Hence, I do not know what else to conclude than that in the current format there too many shortcomings to be of added value to current literature (similar to reviewer 3, and in line w/ reviewer 1 but who is somewhat more mild in their evaluation). If the authors decide to move on with this story, this paper requires a re-evaluation of a much improved version.
Significance
Secondly, I am not convinced by the data quality and representation in the manuscript. As outlined above, symmetry breaking and elongation seem to be very sub-optimal. Also, Fig 4b and Fig 5b hardly show any visible SOX17, in particular also not in the deg-PEG E8 BMP4 condition. Yet, the authors claim high expression of SOX17 in this condition in Fig 6C, as well as large and significant differences between conditions. To my feeling, Fig 6C does not represent the Sox17 observations of the IF. Similarly, I am not convinced by the EdU staining in Fig 7A. Importantly, the authors base their conclusions on only a single cell line, very few spheroid of this cell line, and an unknown number of biological experimental replicated (which to me seems single experiments). Altogether, the setup and data lacks reliability and robustness.
Currently, the efficiency of gastruloid formation is a important discussion in the field. Therefore, it is important to report on this in the current manuscript.
Altogether, while the manuscript makes a few interesting observations, it is very preliminary and not-well worked out or validated. Without being more robust and conclusive, I do not think the manuscript is of much added value to current literature.
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Referee #1
Evidence, reproducibility and clarity
Summary: This manuscript developed a BMP-based culturing protocol for gastruloid-like tissue that eexpresses markers from ectoderm, mesoderm, and endoderm. Through modulating the mechanical properties of extracellular environments, the expression of endodermal marker, SOX17, was found to correlate with the mechanical properties of the extracellular environment. However, the data presented only constitute a crude characterization of the cell lineages within the tissue and, therefore, the biological relevance of the gastruloid-like tissue, together with the associated discoveries, is not immediately evident.
Major comments
- Extra explanation should be provided to justify why mechanical property of extracellular environments is a relevant/important factor for either early embryo development or gastruloid technology.
- (OPTIONAL) To demonstrate the impact of mechanical property of extracellular environments, the authors compared two different gels, a stiffer gel with non-significant stress relaxation, and a softer gel with non-trivial stress relaxation. However, such comparison can be somewhat non-intuitive since a variety of mechanical properties are modulated simultaneously between two groups, including both tissue stiffness and its time-dependency. Since it has been well established that both elasticity and viscoelasticity can affect cell behavior, respectively, I would suggest the authors consider adding an extra comparison between a stiff elastic gel and a soft elastic gel.
Minor comments
- The author provided individual staining of SOX2, BRA and SOX17, it would be more helpful to co-stain these markers to demonstrate their relative spatial distribution.
- The quantification method for Fig. 7D&E seems missing from the method section, and more explanation for the method would be helpful. What is the area ratio between the inner and outer ROI? What does the y-axis number mean in Fig.7E?
- In the last 2nd paragraph of "Biochemical cues regulate morphogenesis via cell proliferation and cellular tension", it was mentioned that "spheroids cultured in E8 medium exhibited organised and tightly packed F-actin with a homogenous network orientation", yet in the next paragraph, it was claimed that "F-actin orientation in round spheroids in E8 medium is mostly distributed in the inner core". Aren't these statements contradictory? Also in this paragraph, it was mentioned "Whereas in KSR conditions, F-actin was distributed in the periphery without significant differences compared to KSR medium conditions", I assume the authors intended to say "KSR BMP4" here?
- The authors mentioned that "cells in the KSR BMP4 spontaneously elongate mirroring A-P elongation", yet based on the data presented, the elongation orientation appears more consistent with the D-V embryo axis?
Significance
This manuscript demonstrates a rudimentary investigation towards how mechanical properties of the extracellular environment may affect the marker expression within a gastruloid-like tissue. Such information may provide certain useful knowledge for the field of gastruloid. However, compared with the established gastruloid models in the field, the advantage of the tissue model developed in this study isn't very clear. Further, the physiological relevance of extracellular mechanics (and particularly, matrix viscoelasticity, which is studied in this manuscript) is not immediately evident.
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Reply to the reviewers
The authors do not wish to provide a response at this time.
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Referee #3
Evidence, reproducibility and clarity
This is a manuscript that focuses on understanding the function of BLTP2 protein in regulation of ciliation. BLTP family of proteins recently emerged as a lipid transporters in several contexts, such as formation and extension of autophagic membrane. The entire study is build on very intriguing observation that BLTP2 depletion leads to enhanced ciliation in RPE1 cells grown in the presence of serum. That makes BLPT2 a negative regulation of cilia formation that appears to mediate serum-dependent inhibition of ciliation in RPEs. Since molecular machinery governing serum-dependent inhibition of cilia formation remains poorly understood, this study does have a potentially high significance and interest. Unfortunately, most of the study (besides Figure 1) is done using Hela cells. It is a puzzling choice since Hela cells do not form cilia. Additionally, mots analyses are fairly descriptive and do not really lead to any specific hypothesis. As the result author's conclusion is very vague, specifically stating that "BLTP2 may suppress ciliogenesis by altering the lipid dynamics and/or densities of unidentified integral membrane proteins that suppress ciliogenesis". Thus, as it stands, this study does not really lead to new insights in BLPT2-dependent regulation of cilia formation.
Few specific other comments are listed below.
- Figure 1. Two different individual siRNAs for each target should be used (unless authors show rescues) to minimize the possibility of off target effects.
- Figure 2-4. Not quite sure what was the rationale to study BLTP2 localization in HeLa cells instead of RPE1. Considering that the main focus of this manuscript is ciliation, one would want to see extensive analysis of localization of BLPT2 in RPE1 cells.
- The key to this manuscript (considering its focus on ciliation) would be to look at BLPT2 dynamics in the RPE1 cells in the presence and absence of serum, especially during ciliary vesicle and cilia formation. Instead, authors do most of their analysis in HeLa cells that do not even form cilia.
Significance
This is a manuscript that focuses on understanding the function of BLTP2 protein in regulation of ciliation. BLTP family of proteins recently emerged as a lipid transporters in several contexts, such as formation and extension of autophagic membrane. The entire study is build on very intriguing observation that BLTP2 depletion leads to enhanced ciliation in RPE1 cells grown in the presence of serum. That makes BLPT2 a negative regulation of cilia formation that appears to mediate serum-dependent inhibition of ciliation in RPEs. Since molecular machinery governing serum-dependent inhibition of cilia formation remains poorly understood, this study does have a potentially high significance and interest. Unfortunately, most of the study (besides Figure 1) is done using Hela cells. It is a puzzling choice since Hela cells do not form cilia. Additionally, mots analyses are fairly descriptive and do not really lead to any specific hypothesis. As the result author's conclusion is very vague, specifically stating that "BLTP2 may suppress ciliogenesis by altering the lipid dynamics and/or densities of unidentified integral membrane proteins that suppress ciliogenesis". Thus, as it stands, this study does not really lead to new insights in BLPT2-dependent regulation of cilia formation.
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Referee #2
Evidence, reproducibility and clarity
The manuscript by Parolek at al demonstrates the role of Bridge-like lipid transfer protein family member 2 (BLTP2) as a negative regulator of ciliogenesis in cultured retinal pigmental epithelial (RPE-1) cells. Based on genetic interaction of BLTP2 with another ciliogenesis negative regulator, WDR44, a RAB11 effector, the authors mechanistically study the regulation of cilia by these proteins. The authors nicely show Hela cell specific colocalization of BLTP2 and WDR44 in the ER-tubular endosome network membrane contact sites (ER-TEN MCS). They demonstrate that the C-terminus of BLTP2 is necessary for localization to the TEN. They also find that the WDR44 network to be present in higher proportion of Hela cells lacking BLTP2. Interestingly, BLTP2 and WDR44 also localize at tips of GFP-Rab8 and GFP Rab10 tubular membrane network in Hela cells. However, RPE-1 cells do not possess WDR44- and BLTP2-associated tubules, so the context of the TEN with the ciliogenesis phenotype in RPE cells, if any, is presently unclear. The rigor and reproducibility of the presented experiments is high and the presented results are novel for cilia, membrane trafficking, memembrane contact sites and lipid transfer fields. Overall, the authors suggest that BLTP2 and WDR44 are common components of a pathway that suppresses ciliogenesis in serum-fed RPE-1 cells.
Major comments
How general are the effects of BLTP2 on ciliogenesis? Effects on ciliogenesis in other cells would consolidate the current results in RPE-1 cells.
Are the effects on ciliogenesis in RPE cells mediated by the role of BLTP2 and WDR44 in TEN network shown in Hela cells? If not, can the authors demonstrate the subcellular localization of these proteins with respect to ciliogenesis, and optionally if possible with the Rab8-Rabin8-Rab11 cascade? For eg., WDR44 knockdown has been shown to increase peri-centrosomal localization of Rabin8 in serum-fed conditions. Does BLTP2 knockdown have similar effects?
The authors show that the C-term of BLTP2 is necessary for its recruitment into TEN network, irrespective of WDR44 in Hela cells. Does the C-term of BLTP2 also regulate ciliogenesis?
Optional: Interactions between BLTP2 and WDR44 are currently unclear other than their colocalization. Can the authors further address if there are close physical interactions between these proteins and/or Rab11?
Minor comments
Fig 3C. In merge/inset: please check the white bar.
If possible, show rescue of ciliogenesis phenotype from BLTP2 knockdown or knockout.
Significance
The roles of lipid transfer proteins in ciliogenesis are currently unknown. By showing the function of BLTP2 in ciliogenesis, the authors suggest the possibility of lipid transfer between the ER and the endo-lysosomal network in regulating ciliogenesis pathways. The results showing co-localization of BLTP2 and WDR44 in ER-tubular endosome network membrane contact sites (ER-TEN MCS) is nicely done and the effects on TEN upon WDR44 loss is also very intriguing. Recent papers suggest a role of WDR44 in ciliogenesis and in ciliopathies. The current data will be of broad interest to readers in ciliogenesis, intracellular trafficking, and lipid transport fields. From my own expertise in cilia biology, I think the results are exceptionally novel but needs more context to further solidify the role of BLTP2 in ciliogenesis.
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Referee #1
Evidence, reproducibility and clarity
Summary
This manuscript by Parolek and Burd addresses the role of the evolutionarily conserved Bridge-like lipid transfer protein 2 (BLTP2) VPS13 family member in negatively regulating ciliogenesis. BLTP proteins are thought to mediate the transfer of lipids between a variety of different organelles, and while BLTP2 loss-of-function in plants and multicellular organism including flies and mice has been connected to various phenotypes, the role of human BLTP2 is poorly understood. In the current study, the authors initially used the Cancer Dependency Map Portal to find a very high mutual co-dependency between the BLTP2 gene and WDR44, a previously well-established negative regulator of primary ciliogenesis. This led the authors to ask whether BLTP2 (similar to WDR44) affects ciliogenesis and indeed they demonstrated that knock-down of either protein in serum-containing RPE1 cells (conditions that normally do not facilitate robust cilia formation) led to an increased percentage of ciliated cells. The authors next addressed the localization of human BLTP2, finding it on ER membranes as well as in linear/tubular structures that correlate with ER subdomains, at least in HeLa cells. Moreover, BLTP2 localization overlapped with that of WDR44. The authors then demonstrated that in BLTP2 knockout cell lines a significantly greater percentage of cells displayed a robust tubular endosome network than in wild-type cells. Finally, the authors show that both BLTP2 and WDR44 tend to localize to the tips of the endocytic tubular network, suggesting that these proteins may localize to contact sites between the ER and (tubular) endosomes, and further, that these contact sites may be required for primary ciliogenesis.
Major Comments
This is an interesting manuscript that addresses a poorly understood protein, and potentially provides a novel connection between ER-recycling endosome contact and ciliogenesis. The experimentation is well executed, and the presented data are clear. The strengths of the manuscript lie in partially unveiling new function for BLTP2, functionally associating BLTP2 with WDR44, and the potentially novel relationship between ER-endosome contact sites and ciliogenesis. Moreover, the tubular network of endosomes (which has been primarily implicated in recycling), remains an incompletely understood organelle and this manuscript suggests a new role for it. The weaknesses lie in the preliminary nature of the studies (which in the current form are largely correlative/speculative), and the somewhat descriptive nature of the study. For example, while the proposed connection between ER-endosome contacts, TEN, and cilia is intriguing, there is little attempt to address how such contact sites and TEN might affect ciliogenesis. Developing these ideas would greatly increase the significance of the findings, which as presented are mainly correlative. Other key questions include whether these proteins affect functions previously attributed to tubular endosomes, such as receptor recycling and endocytosis? What is the function of the TEN in maintenance or generation of ER contact sites? There is some literature suggesting that TEN serve in the sorting and/or fission process that might separate Rab5 anterograde transport from Rab4 recycling endosomes, but this is not addressed in the context of the current manuscript. How do ER contact sites and TEN impact ciliogenesis at a molecular level? How might a lipid transfer protein affect primary ciliogenesis? Is the TEN network connected to lipid transfer? Reports hold that PI4,5P2, PI4P, PA and other lipids might be enriched in the TEN; are these (or other lipids in the TEN) affected by BLTP2? In addition, while BLTP2 and WDR44 are linked by localization (and their mutual co-dependency), little attempt has been made to understand how these proteins function together. Do they physically interact? Are Rab8/10 responsible for their recruitment to the tips of endosomes?
Minor comments:
Could endogenous Rab proteins be used to address localization of BLTP2 and WDR44 to tubule tips?
Could the authors please explain how the R=0.61 mutual co-dependency was arrived at? This reviewer used the portal website to find an R value of 0.58. Admittedly these numbers are both very high and the difference between them not significant, but nonetheless they are not identical.
Significance
The novelty of this study is that it identifies a new player, BLTP2, involved in the regulation of primary ciliogenesis. Since ciliogenesis impacts so many physiological events and underlies over 100 distinct ciliopathgies, there is clear significance in identifying new proteins that regulate this process (even if hundreds have already been identified). Perhaps the most (potentially) novel finding is the relationship between the ER contact sites, the tubular network of endosomes and ciliogenesis. Few papers have made any connection between tubule generation and ciliogenesis, with the exception of Insinna et al. (Nat Comm., 2019), a paper reporting that the tubular endosome scaffold MICAL-L1 is required for ciliogenesis (Xie et al., J. Cell Sci., 2019), and the recent Biorxiv manuscript by Ott and colleagues suggesting that tubules allow formation of "deconstructed" cilia, none of these connect ciliogenesis to ER contact sites. The limitations of the study are the preliminary nature; as noted, while the individual experiments are clear, substantial data that clearly connect ER contact sites, tubular endosomal networks and ciliogenesis remain largely uncharacterized in this study. In terms of the audience, if a more tangible relationship between ER contact sites/TEN and cilia could be derived, the study would be cross-disciplinary and of interest to a wide audience.
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- General Statements [optional]
Response: We would like to thank both reviewers for their insightful comments. We have addressed most comments in the transferred manuscript and are willing to perform additional experiments to respond to some remaining points, as detailed in the following sections.
- Description of the planned revisions
Insert here a point-by-point reply that explains what revisions, additional experimentations and analyses are planned to address the points raised by the referees.
Reviewer #1:
Fig. 5, It would also be interesting to explore the involvement of IFN-I receptors (IFNAR1 vs IFNAR2) by dissecting IFN-α from IFN-β responses.
Response: Our understanding is that IFNAR1 and IFNAR2 form a heterodimer, which can be activated by both IFN-α and IFN-β. It is thus difficult to dissect the role of individual receptors or cytokines from each other. However, to confirm that IFN-α and IFN-β are both acting through the IFNAR1 receptor to prime for IL-1b activation and release in human neutrophils, we will perform additional experiments by treating neutrophils isolated from healthy individuals with both cytokines individually (as opposed to using them synergistically as in the current manuscript) and blocking their effects by a commercial IFNAR1 blocking antibody.
Reviewer #2:
- The authors are encouraged to specify the number of independent experiments conducted. For mouse model studies, it is recommended to include results that are either representative of, or aggregated from, a minimum of two independent experiments to ensure robustness of the data.
Response: We did three independent animal experiments in total. The first two experiments involved two time points (2 and 4 days post infection) with different downstream experiments: The first experiment was used for the detection of viral loads by PCR as well as IHC-based quantification of viral antigen and neutrophil influx into the lungs (Exp1, new suppl. Fig 6) while the second experiment (Exp2) was used to isolate neutrophils from the lungs in order to assess neutrophil caspase1 activity and to obtain samples for RNAseq (new Fig.7 A-D). The third experiment (Exp3) was to perform anti-IFNAR and isotype treatments for infected mice; here, all animals were at day 2 post infection. For this experiment we prepared lung samples for IHC and PCR (new suppl Fig. 7) and isolated neutrophils for the assessment of caspase1 activity and for PCR assays (new Fig. 7E-G). We have now improved the text and supplementary Table S2 to indicate these separate experiments more clearly. In our experience, this approach, i.e. making use of the lungs of oe animals for the determination of several parameters, is of benefit not only because we can directly compare these parameters in a given animal and can thereby reduce the number of animals used for the project (following the 3R principles).
However, in order to increase sample size and to respond to the various issues raised by the reviewer regarding our mouse work, we have decided to undertake another mouse infection experiment to analyze the effect of the anti-IFNAR treatment on viral loads by assaying for viral titers in the lung sample (which will hopefully directly answer the reviewer’s concerns raised below regarding the effect of anti-IFNAR treatment on viral replication). We will also confirm the negative effect of anti-IFNAR treatment on the expression of IFN-responsive genes by measuring OAS2 mRNA levels by PCR in the lungs of the anti-IFNAR treated as compared to isotype-treated mice. Finally, we will isolate neutrophils from the lungs to repeat the experiment showing the effect of anti-IFNAR treatment on neutrophil inflammasome activity as shown in Fig 7. E-G and will take a sample each for the histological and immunohistological analysis to complement the other tests.
- The authors are advised to employ more quantitative methods, such as flow cytometry, to measure neutrophil recruitment in mice. Additionally, it should be clarified how many tissue sections from each mouse were assessed for every experimental condition to ensure the reproducibility and statistical validity of the results.
Response: While we are not aware that flow cytometry can be considered as a “more quantitative method” than morphometry, we agree that it is an alternative, i.e. complementary quantitative method. Furthermore, we feel that direct quantification of isolated Ly-6G+ neutrophils which are obtained from homogenized lung tissue by magnetic beads (as we have done for some mouse experiments of the current manuscript) is another quantitative approach and a method comparable to flow cytometry. Therefore, we are willing to repeat the mouse infection experiments and quantify the isolated neutrophils in parallel to IHC-based morphometry in order to determine the robustness of our morphometrical neutrophil quantification but are not inclined to undertake flow cytometry, in particular since this would not allow the assessment of all other relevant parameters in the same lung.
The reviewer asked for information regarding the number of tissue sections that were assessed from each mouse. In our opinion, for quantitative purposes (i.e. morphometry), it is more meaningful to determine the total tissue area that is examined, as different pathologists take different approaches to trim the lung for histological examination (cross sections vs. longitudinal section of a lobe). In our study we examined a tissue area of 19.5 ± 6 mm2 for each lung, which is stated now also in the revised manuscript.
Revised manuscript, methods section, line 307:
“The average total tissue area used for the quantification was 19.5 ± 6 mm2”.
- The authors need to address discrepancies in their text regarding the effects of anti-IFNAR1 blockade on viral titers and neutrophil recruitment in SARS-CoV-2 infected mice. While they state there is no change, Supplementary Figure 5D suggests increased SARS-CoV-2 NP staining with anti-IFNAR1 treatment, and there appears to be a lack of quantitative data on lung neutrophils to substantiate the claim that neutrophil recruitment remains unaffected. It is necessary for the authors to provide a more detailed explanation or additional data to resolve these inconsistencies *
Response: We did not observe any significant differences in the antigen expression between anti-IFNAR treated and isotype-treated mice. The lack of differences in viral loads was also shown by PCR (suppl Fig. 6B). However, since we are suggesting to repeat the anti-IFNAR experiment which will also include the quantification of viral titers in lung tissue with and without anti-IFNAR treatment, we will gain further insight whether and how IFN-I activity could regulate infection kinetics. We will also repeat the quantification of neutrophils in the lungs of anti-IFNAR and isotype-treated mice by IHC-based morphometry as well as by determining the number of isolated LY-6G+ neutrophils.
- The authors should demonstrate the effectiveness of anti-IFNAR1 blockade in mice by providing evidence of sustained inhibition of IFN-I signaling throughout the duration of the experiment to validate the treatment protocol used.
Response: We feel the observed inhibition of inflammasome-related pathways by anti-IFNAR treatment strongly argues that blockade of IFNAR activity was successful during the 2 day time course of the direct experiment (Exp3). However, the reviewer’s comment is valid since we have not shown the effect of anti-IFNAR treatment on specific IFN-induced genes. Therefore, we will repeat the anti-IFNAR treatment in infected mice and confirm its negative effect on the expression of IFN-responsive genes by detecting the expression of OAS2 mRNA in lung samples by PCR (OAS2 is one of the mostly upregulated genes by SARS-CoV-2 infection based on our neutrophil transcriptomics analysis). We will also assess whether the treatment directly affects the levels of infectious virus by quantifying viral titers in lung tissue.
*Referee Cross-Commenting*
- I agree with Reviewer#1 about trying to dissect the role of IFNAR-1 vs IFNAR-2. Authors partially look at this in the in vivo mice experiments using the anti-IFNAR1 blocking Ab, but it would reinforce the study to see if this holds with human cells.
Response: To confirm that IFN-α and IFN-β are both acting through the IFNAR1 receptor to prime for IL-1b activation in human neutrophils, we will perform additional experiments by treating neutrophils isolated from healthy individuals with both cytokines individually (as opposed to using them synergistically as done for the current manuscript) and blocking their effects by a commercial IFNAR1 blocking antibody.
The study presents an investigation into the role of neutrophils and inflammasome formation in COVID-19 pathology, contributing to the field with transcriptomic profiling of neutrophils from varying severity of patient cases and a SARS-CoV-2 mouse model. A significant IFN-I gene signature in severe cases was confirmed, and differences in inflammasome response were identified, adding to our understanding of disease mechanisms.
Strengths of the paper include the comprehensive analysis of neutrophil maturation states and the novel insights into the priming of inflammasome activation by IFN-I. However, limitations were noted in the purity of samples for RNAseq analysis and the lack of conclusive in vivo evidence for the direct role of IFN-I in neutrophil inflammasome priming. The study's implications suggest potential avenues for targeted therapies, but the authors were advised to moderate their conclusions without stronger in vivo evidence and to clarify the potential therapeutic implications of their findings.
Additional suggestions for improvement include the use of more quantitative methods like flow cytometry for neutrophil recruitment measurements, clarification on experimental replication, and resolving discrepancies in data presentation regarding anti-IFNAR1 blockade effects. Furthermore, the paper would benefit from discussing the relevance of autoantibodies against IFN-I in the context of their findings and from exploring the causal relationship between inflammasome patterns and disease severity.
Response: We would like to thank the reviewer for highly impactful comments. As suggested, we have redone the RNAseq analysis including only samples of higher neutrophil content, with similar conclusions as those previously made, and have amended the discussion based on the reviewer’s comments. Furthermore, to address the remaining questions raised by the reviewer, we will undertake the following additional animal experiments:
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Five groups of animals (n = 4);
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PBS-inoculated animals
- Infected with SARS-CoV-2 for 2 days, treated with isotype
- Infected with SARS-CoV-2 for 2 days, treated with anti-IFNAR
- Infected with SARS-CoV-2 for 2 days
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Infected with SARS-CoV-2 for 4 days
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Measurements from lung tissue
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Quantification of LY-6G neutrophils by morphometry
- RT-PCR for OAS2 mRNA (assessment of the successful blockade of IFN-I signaling by IFNAR antibody)
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Viral titers by quantification of infectious virus in cell culture (assessment of the successful blockade of IFN-I signaling by IFNAR antibody)
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Isolation of LY-6G neutrophils from lung tissue
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Quantification of the number of isolated LY-6G neutrophils
- Repeating measurement of caspase1 activity
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Repeating RT-PCR for caspase1 and IL-1b mRNA
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Description of the revisions that have already been incorporated in the transferred manuscript
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Reviewer #1:
IFN-I promotes immune responses to diverse viruses. Some of them have evolved to dampen IFN-I responses in order to weaken or delay antiviral responses. A number of studies support the idea that this could be the case of SARS-CoV-2 (0.1038/s41586-022-04447-0, 10.1016/j.it.2021.02.003, 10.1038/s41467-022-34895-1, to cite a few). The authors should refer to some of these studies to counterbalance the statements of increased IFN-I response in severe COVID-19 patients in some parts of the manuscript, such as in the Discussion.
Response: This is a good point and we added discussion on this topic.
Revised manuscript, discussion section, between lines 634-648:
“It should be noted that several SARS-CoV-2 encoded proteins have been shown to inhibit IFN-I signaling (60). However, no evidence suggests that neutrophils can be infected by SARS-CoV-2 and therefore it seems unlikely that such direct virus mediated effects could play a role in the observed neutrophil unresponsiveness to IFN-I.
The dualistic nature of the IFN-I response in COVID-19 has been recognized previously. It seems that a strong initial IFN-I response to SARS-CoV-2 is more likely to result in asymptomatic or mild COVID-19 whereas a decreased initial IFN-I activity, due to e.g. genetic defects or increased levels of IFN-I autoantibodies, can lead to more severe COVID-19 (61). This initial beneficial effect of IFN-I is probably due to its ability to limit viral replication at early stages of the infection. However, at later stages of the disease IFN-I can be detrimental by promoting inflammatory pathways instead of direct antiviral effects (62). Thus, similarly to the IFN-I response in general, the role of neutrophil inflammasomes in development and severity of COVID-19 might be dualistic in nature with an initial protective effect while damaging when sustained for prolonged periods.”
- Rashid F, et al. Roles and functions of SARS-CoV-2 proteins in host immune evasion [preprint]. Front Immunol. 2022;13. https://doi.org/10.3389/fimmu.2022.940756.
- da Silva RP, et al. Circulating Type I Interferon Levels and COVID-19 Severity: A Systematic Review and Meta-Analysis. Front Immunol. 2021;12. https://doi.org/10.3389/fimmu.2021.657363.
- Smith N, et al. Defective activation and regulation of type I interferon immunity is associated with increasing COVID-19 severity. Nat Commun. 2022;13(1). https://doi.org/10.1038/s41467-022-34895-1.
In Fig 5, the authors stimulate PMNs from healthy controls in vitro with IFN-I and use mainly IL-1b as a readout for neutrophil priming. The authors should analyse whether IFN-I-mediated priming ultimately leads to NETosis, given the relevance of NETs to COVID-19 pathology (10.1016/j.tips.2023.06.007), which is acknowledged by the authors in the Introduction.
Response: We agree that NETosis is a potential outcome of neutrophil activation. This is in part why we assayed for the release of MPO, which can be used as a marker of NETosis, in the ex vivo activated PMNs. However, while a clear increase in MPO levels was observed in response to nigericin treatment, no increase was seen with IFN-I or LPS treatments alone in COVID-19 or HC PMNs (Fig. 4C). We slightly modified the text to make it clearer that MPO served to detect PMN degranulation and NETosis in our study.
Revised manuscript, results section, lines 440-444:
“However, the release of myeloperoxidase (MPO), used as a marker of degranulation and/or NETosis, in response to nigericin was similar between COVID-19 PMNs and HC PMNs, and therefore the observed diminished IL-1β release by COVID-19 PMNs is not due to general cellular inertia but may be specific to the ex vivo induced inflammasome pathway.”
In Methods (Histology and immunohistochemistry), the authors mention that histone H3 is a NET marker and use this in Supp Fig 5 to support evidence of NETosis. The authors should state which antibody clone/company was used. Histone H3 is expressed in high levels by non-NETotic neutrophils. Citrullinated histone H3 (CitH3), on the other hand, is detectable by few commercially available antibodies and can be used as a NET marker in conjunction with other markers such as DNA staining (10.1084/jem.20201129).
Response: For immunohistochemical detection of NETosis, we have used the following antibody: rabbit anti-histone H3 (citrulline R2 + R8 + R17; Abcam). We have provided a reference to a publication of a co-author (Schmid AS, et al. Antibody-based targeted delivery of interleukin-4 synergizes with dexamethasone for the reduction of inflammation in arthritis. Rheumatology (United Kingdom). 2018;57(4):748–755. Doi: 10.1093/rheumatology/kex447) which includes this information and fully describes the staining protocol. We admit that our labelling of the figure and the text was misleading by stating that the used antibody was anti-histone H3 instead of indicating that an antibody detecting citrullinated form of histone H3 was used. We have therefore relabeled Supplementary Fig. 7 and rewritten the text to indicate this more clearly.
In the publication kindly referred to by the reviewer, the following antibody was used: rabbit anti-histone H3 (H3Cit; Abcam; cat. ab5103; 1:500) in immunofluorescence, where DAPI fluorescence served to highlight the DNA. We generally work with immunohistochemistry instead of immunofluorescence as it allows better alignment with histopathological features. However, we have now applied the anti-H3cit antibody in a fluorescence protocol, using the same tissues and antibody as shown in the immunohistochemistry image of suppl. Fig7, to indicate that the used antibody works equally well in immunofluorescence and immunohistochemistry.
In the PDF version of this revision there is a figure plate that shows: NET IHC, showing abundant expression in the lumen of a bronchiole (top) and NET IF, showing part of a bronchiole with NET (green) and nuclei (DAPI; blue) and a closer view (bottom) with NET expression in a cell with the nuclear morphology of a neutrophil (arrowhead).
In Fig 8, the authors show that neutrophils migrate to the lungs of infected animals. This finding is showed in many previous studies and does not seem to favour the structure of the manuscript. Insteand, it seems it would fit a Supp Fig better, or a portion of the following figure.
Response: We are aware that neutrophil recruitment into the lungs with SARS-CoV-2 infection has been shown previously. However, this was so far not done in the model that we have used, mouse-adapted SARS-CoV-2 infection in wild type (BALB/C) mice in which the infection is short-lived and wanes off after 4 days (Gawish et al., 2022). We are happy to move this figure plate to the Supplements as Reviewer #2 shares this opinion. In the revised manuscript, it now features as Supplementary Fig. 6.
Reviewer #2:
Major points:
-Figure 2A: for this RNAseq analysis, the authors claim that "This analysis also demonstrated that cells in the LDG fraction were predominantly immature neutrophils, meanwhile PMNs were composed of mainly mature neutrophils (Figure 2A)". Nevertheless, there are 2 samples in the "Severe COVID-19" group that show a fraction of neutrophils {less than or equal to}0.6, which indicates low levels of purity. In addition, there is one "PMN" sample with high LDG fraction (around 40%). Authors should remove from this analysis samples with such a low purity since the big fraction ({greater than or equal to}40%) of contaminating cells could introduce a bias in this group. Are the differences observed still present in the absence of these low-purity samples?
Response: For Figure1 of the original manuscript, we first performed the analyses including all the samples, and after assessing their purity, included only the samples with highest purity in the following figures. However, we followed the reviewer’s recommendation and redefined the purity of the samples as >65% of total neutrophils, independent of their maturity. Of note, unlike the reviewer suggests, we did not remove the one “PMN” sample with high degree of immaturity, since PMNs and LDGs are defined based on their isolation method and not their degree of maturity. Along these lines, we have decided to move the new unsupervised heatmap and present it together with the RNA deconvolution plot as supplementary Figure 1. Therefore, Figure 1 now contains the samples with high purity based on the redefined criteria, with PCA in panel A, pathway analyses in panel B (PMN vs LDG) and interferon-related genes heatmap in panel C. We also redid suppl Fig. 2 to include samples with the redefined criteria and modified the results text accordingly.
Revised manuscript, results section, lines 333-380:
“Unsupervised RNA-seq analysis reveals an antiviral gene expression signature of circulating neutrophils in COVID-19 that is strongly influenced by maturity
With our recent findings on increased frequencies of low-density granulocytes (LDGs, isolated from the PBMC fraction) during COVID-19 and their likely relevant role in disease progression (7), we sought to understand in more detail how the transcriptomic profile of LDGs differs from their higher “normal” density counterpart, the circulating polymorphonuclear cells (PMNs) (31), typically consisting mainly of mature neutrophils. Neutrophils isolated from different cohorts comprised three PMN groups (severe COVID-19, mild COVID-19, and healthy controls), and one LDG group. Initial deconvolution of the RNA sequencing (RNA-seq) data allowed us to gain a comprehensive understanding of the cellular composition within PMN and LDG fractions and verified that most cells present in the samples were neutrophils (Supplementary Figure 1A). This analysis also demonstrated that cells in the LDG fraction were predominantly immature neutrophils, meanwhile PMNs were composed of mainly mature neutrophils.
The samples with predominant neutrophil cell populations were selected for subsequent gene expression analysis (neutrophils ≥ 65 %). The high variance in gene expression between PMNs and LDGs was confirmed by principal component analysis (PCA) (Figure 1A), which revealed that the gene expression patterns of COVID-19 LDGs differed from those of all PMNs regardless of the patients’ disease state. Functional enrichment analyses through gene overrepresentation (ORA) and gene-set enrichment analyses (GSEA) (Figure 1B) compared PMNs with LDGs from severe COVID-19 patients. The most statistically significant result was an overrepresentation of the NOD-like receptor signaling pathway in PMNs in contrast with LDGs, highlighting that the different neutrophil fractions have a distinct inflammatory profile. This was supported by GSEA, where the most obvious increases in fold changes were the enrichment of the interferon signaling pathways. Another relevant difference was the cell cycle and DNA replication pathways, identified by both ORA and GSEA, which supported our previous findings suggesting LDGs to be predominantly immature cells (7). Furthermore, a heatmap of selected type I IFN (IFN-I) related genes confirmed a robust IFN-I gene signature in severe COVID-19 PMNs, while LDGs from severe COVID-19 distinctively lacked this signature (Figure 1C). Unsupervised clustering analysis, namely Iterative Clustering and Guide Gene Selection (ICGS) using the AltAnalyze software, supported these findings by identifying the top 118 differentially expressed (DE) genes, including several IFN-related genes (Supplementary Fig. 1B). Similarly to the selected samples included in Figure 1, this analysis classified the samples into two major clusters: a first one containing all isolated LDG samples, and a second one comprising all isolated PMN samples. The former cluster consisted of neutrophil antimicrobial and granule marker genes (e.g. DEFA3, DEFA4, SERPINB10, CTSG), while in the latter cluster the most significantly upregulated genes in the PMNs from severe COVID-19 subgroup were mainly interferon inducible (e.g. IFI44L, IFI6, GBP3, IRF7). These differences were supported by a detailed gene analysis (Supplementary Fig. 2A).
Inflammasomes are activated in severe COVID-19 PMNs, but not directly by SARS-CoV-2
Looking more closely into PMN fractions, pathway analyses identified the inflammasome related NOD-like and RIG-like receptor signaling pathways among the most significantly overrepresented pathways, differentially expressed in severe COVID-19 PMNs versus HC PMNs (Figure 2A and Supplementary Fig. 2B-C) or mild COVID-19 PMNs (Figure 2B and Supplementary Fig. 2D, E). However, mild COVID-19 PMNs did not significantly differ from HC PMNs in their inflammatory profile (Supplementary Fig. 2F).”
Finally, to respond to the reviewer’s specific question concerning whether the observed differences are still present in the absence of the newly defined low-purity samples, we can conclude that the results continue to highlight the differences we had previously described (increased cell cycle and metabolism-related pathways in LDGs and a distinct IFN-I signature in severe COVID-19 PMNs).
- While the in vitro data suggest that IFN-I may prime the inflammasome response in neutrophils, in vivo evidence remains inconclusive. The systemic blockade of IFNAR1 with antibodies in infected mice does not confirm that IFN-I directly primes neutrophil inflammasomes, as other cells could initially sense IFN-I and subsequently produce neutrophil-activating stimuli. In the absence of in vivo experiments utilizing conditional IFNAR1 knockout models, such as Mrp8-Cre x IFNAR1 fl/fl mice, the authors should consider moderating the stated significance of these findings in the discussion about the limitations of the study.
Response: We agree with the reviewer on this point. Thus, we modified the “limitations of study” paragraph in the discussion.
Revised manuscript, discussion section, lines 674-677:
“Furthermore, the observed inhibitory effects on neutrophil inflammasome activity by IFNAR blockade does not exclude the possibility that IFN-I could promote neutrophil inflammasome formation by indirect effects such as stimulating the release of pro-inflammatory cytokines by other cell types.”
- Given the reports of life-threatening COVID-19 infections occurring in conjunction with autoantibodies against type I IFNs (DOI: 10.1126/science.abd4585), the authors should explore how this intersects with their findings. A discussion is needed on whether patients with such autoantibodies may exhibit inflammasome activation patterns similar to the severe cases in this study, which could provide valuable insights into patient stratification and treatment approaches.
Response: This is a good point, thank you. Based on our data it is unlikely that patients with IFN-I autoantibodies or genetic defects in the production of IFN-I would show significant neutrophil inflammasome activation. Like with IFN-I response in general, neutrophil inflammasomes can probably be either protective or damaging to the host, depending on the context and durability of the response. We have discussed this topic further in the revised manuscript, in response to this concern and the first point of reviewer 1.
Revised manuscript, discussion section, lines 639-648:
“The dualistic nature of the IFN-I response in COVID-19 has been recognized previously. It seems that a strong initial IFN-I response to SARS-CoV-2 is more likely to result in asymptomatic or mild COVID-19 whereas a decreased initial IFN-I activity, due to e.g. genetic defects or increased levels of IFN-I autoantibodies, can lead to more severe COVID-19 (61). This initial beneficial effect of IFN-I is probably due to its ability to limit viral replication at early stages of the infection. However, at later stages of the disease IFN-I can be detrimental by promoting inflammatory pathways instead of direct antiviral effects (62). Thus, similarly to the IFN-I response in general, the role of neutrophil inflammasomes in development and severity of COVID-19 might be dualistic in nature with an initial protective effect while damaging when sustained for prolonged periods.”
- The authors need to delve deeper into whether the inflammasome patterns observed in severe COVID-19 cases are a contributing factor to the disease's progression or a result of the infection's severity, thereby clarifying the causality in their discussion.
Response: This is an important aspect of the study and we agree that the relationship between neutrophil inflammasome activity and disease severity could be highlighted better. However, understanding causality by analyzing clinical patient samples is difficult due to the typical lack of patient samples from the early phase of the disease. Hospitalization and thereby patient sample collection typically occurs when the patients are already experiencing the peak of symptomatic phase of the disease. To highlight the link between neutrophil inflammasome formation and disease severity more clearly, we have marked the statistically significant correlations between inflammasome activation and disease severity parameters by an asterisk in the correlation plot (Fig. 5) and added text in the discussion accordingly.
Revised manuscript, discussion section, lines 649-654:
“Our study demonstrated a strong association between PMN caspase1 activity and plasma levels of calprotectin, a marker of neutrophil activation. Additionally, increased disease severity, as assessed by the WHO ordinal scale, was significantly linked to PMNs being less responsive to ex vivo IFN-induced inflammasome activation, which is suggestive of prior in vivo inflammasome activation. Thus, these results suggest that neutrophil inflammasomes play a potential role in disease severity rather than being protective in COVID-19.”
This point links to the previous comment by the reviewer regarding the role of IFN-I in disease severity. We have added text in the discussion highlighting the dual nature of the IFN-I response and neutrophil inflammasome activation in COVID-19 disease severity (see response above).
-Authors should clarify if and how their findings may lead to any therapeutic advantage for severe COVID-19 patients.
Response: The text has been adapted accordingly, and more details have been added into the revised manuscript.
Revised manuscript, discussion section, lines 685-687:
“For example, pharmacologically targeting the inflammasome pathway in neutrophils with novel inhibiting molecules, may help mitigate the exaggerated inflammatory response observed in severe cases.”
Reference added: Mangan, M. S., Olhava, E. J., Roush, W. R., Seidel, H. M., Glick, G. D., & Latz, E. (2018). Targeting the NLRP3 inflammasome in inflammatory diseases. Nature reviews Drug discovery, 17(8), 588-606.
Minor points:
- Authors should increase the font in all the figures as most of them are difficult to be read
Response: Thank you for your suggestion. The font sizes have been increased, but their size will ultimately depend on the requirements of the journal where is the work will be published.
Thank you for your suggestion. The font sizes have been increased, but their size will ultimately depend on the requirements of the journal where the work will be published.
- Authors should better clarify how the choice for statistics tests was conducted "depending on sample distribution and the number of groups analyzed" in the Methods.
Response: We added additional details to the methods.
Revised manuscript, methods section, lines 329-331:
“To elaborate, nonparametric tests like Mann-Whitney and Kruskall-Wallis were employed when the data violated assumptions of normality, while ANOVA tests were applied when the data met parametric assumptions”.
Referee Cross-Commenting*
-I agree with Reviewer#1 with adding relevant references about the evolution of some viruses, including SARS-COV-2, in evading type I IFN response.
Response: We added this information into the manuscript.
Revised manuscript, discussion section, lines 635-638:
“It should be noted that several SARS-CoV-2 encoded proteins have been shown to inhibit IFN-I signaling. However, no evidence suggests that neutrophils can be infected by SARS-CoV-2 and therefore it seems unlikely that such direct virus mediated effects could play a role in the observed neutrophil unresponsiveness to IFN-I".
Reference added: Rashid F, et al. Roles and functions of SARS-CoV-2 proteins in host immune evasion [preprint]. Front Immunol. 2022;13.
-I agree with Reviewer#1 about Figure 8 not delivering a novel message. I also suggest to move this to the supplementary section.
Response: We have moved the figure plate to the Supplements.
- Description of analyses that authors prefer not to carry out
Please include a point-by-point response explaining why some of the requested data or additional analyses might not be necessary or cannot be provided within the scope of a revision. This can be due to time or resource limitations or in case of disagreement about the necessity of such additional data given the scope of the study. Please leave empty if not applicable.
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Referee #2
Evidence, reproducibility and clarity
The authors of this study seek to examine the role of neutrophils, particularly their inflammasome formation potential, in the pathophysiology of COVID-19. They conducted transcriptomic profiling of neutrophils from both mild and severe COVID-19 patients, as well as SARS-CoV-2 infected mice, and compared these profiles to non-infected healthy controls. Their analysis confirmed a prominent IFN-I gene signature in severe cases previously reported by others. Furthermore, they observed that neutrophils from severe COVID-19 patients have an altered response to inflammasome activation and that IFN-I can serve as a priming stimulus for neutrophil inflammasomes, a finding further supported by a COVID-19 mouse model. Last, in this study the authors revealed that in severe COVID-19, LDGs show gene upregulation indicating immaturity, while PMNs exhibit enhanced pathogen-responsive NLR signaling.
Major points:
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Figure 2A: for this RNAseq analysis, the authors claim that "This analysis also demonstrated that cells in the LDG fraction were predominantly immature neutrophils, meanwhile PMNs were composed of mainly mature neutrophils (Figure 2A)". Nevertheless, there are 2 samples in the "Severe COVID-19" group that show a fraction of neutrophils {less than or equal to}0.6, which indicates low levels of purity. In addition, there is one "PMN" sample with high LDG fraction (around 40%). Authors should remove from this analysis samples with such a low purity since the big fraction ({greater than or equal to}40%) of contaminating cells could introduce a bias in this group. Are the differences observed still present in the absence of these low-purity samples?
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While the in vitro data suggest that IFN-I may prime the inflammasome response in neutrophils, in vivo evidence remains inconclusive. The systemic blockade of IFNAR1 with antibodies in infected mice does not confirm that IFN-I directly primes neutrophil inflammasomes, as other cells could initially sense IFN-I and subsequently produce neutrophil-activating stimuli. In the absence of in vivo experiments utilizing conditional IFNAR1 knockout models, such as Mrp8-Cre x IFNAR1 fl/fl mice, the authors should consider moderating the stated significance of these findings in the discussion about the limitations of the study.
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The authors are encouraged to specify the number of independent experiments conducted. For mouse model studies, it is recommended to include results that are either representative of, or aggregated from, a minimum of two independent experiments to ensure robustness of the data
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The authors are advised to employ more quantitative methods, such as flow cytometry, to measure neutrophil recruitment in mice. Additionally, it should be clarified how many tissue sections from each mouse were assessed for every experimental condition to ensure the reproducibility and statistical validity of the results.
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The authors need to address discrepancies in their text regarding the effects of anti-IFNAR1 blockade on viral titers and neutrophil recruitment in SARS-CoV-2 infected mice. While they state there is no change, Supplementary Figure 5D suggests increased SARS-CoV-2 NP staining with anti-IFNAR1 treatment, and there appears to be a lack of quantitative data on lung neutrophils to substantiate the claim that neutrophil recruitment remains unaffected. It is necessary for the authors to provide a more detailed explanation or additional data to resolve these inconsistencies
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The authors should demonstrate the effectiveness of anti-IFNAR1 blockade in mice by providing evidence of sustained inhibition of IFN-I signaling throughout the duration of the experiment to validate the treatment protocol used.
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Given the reports of life-threatening COVID-19 infections occurring in conjunction with autoantibodies against type I IFNs (DOI: 10.1126/science.abd4585), the authors should explore how this intersects with their findings. A discussion is needed on whether patients with such autoantibodies may exhibit inflammasome activation patterns similar to the severe cases in this study, which could provide valuable insights into patient stratification and treatment approaches
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The authors need to delve deeper into whether the inflammasome patterns observed in severe COVID-19 cases are a contributing factor to the disease's progression or a result of the infection's severity, thereby clarifying the causality in their discussion.
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Authors should clarify if and how their findings may lead to any therapeutic advantage for severe COVID-19 patients.
Minor points:
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Authors should increase the font in all the figures as most of them are difficult to be read
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Authors should better clarify how the choice for statistics tests was conducted "depending on sample distribution and the number of groups analyzed" in the Methods.
Referee Cross-Commenting
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I agree with Reviewer#1 with adding relevant references about the evolution of some viruses, including SARS-COV-2, in evading type I IFN response.
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I agree with Reviewer#1 about trying to dissect the role of IFNAR-1 vs IFNAR-2. Authors partially look at this in the in vivo mice experiments using the anti-IFNAR1 blocking Ab, but it would reinforce the study to see if this holds with human cells.
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I agree with Reviewer#1 about Figure 8 not delivering a novel message. I also suggest to move this to the supplementary section.
Significance
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The study presents an investigation into the role of neutrophils and inflammasome formation in COVID-19 pathology, contributing to the field with transcriptomic profiling of neutrophils from varying severity of patient cases and a SARS-CoV-2 mouse model. A significant IFN-I gene signature in severe cases was confirmed, and differences in inflammasome response were identified, adding to our understanding of disease mechanisms.
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Strengths of the paper include the comprehensive analysis of neutrophil maturation states and the novel insights into the priming of inflammasome activation by IFN-I. However, limitations were noted in the purity of samples for RNAseq analysis and the lack of conclusive in vivo evidence for the direct role of IFN-I in neutrophil inflammasome priming. The study's implications suggest potential avenues for targeted therapies, but the authors were advised to moderate their conclusions without stronger in vivo evidence and to clarify the potential therapeutic implications of their findings.
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Additional suggestions for improvement include the use of more quantitative methods like flow cytometry for neutrophil recruitment measurements, clarification on experimental replication, and resolving discrepancies in data presentation regarding anti-IFNAR1 blockade effects. Furthermore, the paper would benefit from discussing the relevance of autoantibodies against IFN-I in the context of their findings and from exploring the causal relationship between inflammasome patterns and disease severity.
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The study is of relevance to immunologists specializing in viral infections and researchers focused on neutrophil biology.
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Referee #1
Evidence, reproducibility and clarity
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IFN-I promotes immune responses to diverse viruses. Some of them have evolved to dampen IFN-I responses in order to weaken or delay antiviral responses. A number of studies support the idea that this could be the case of SARS-CoV-2 (0.1038/s41586-022-04447-0, 10.1016/j.it.2021.02.003, 10.1038/s41467-022-34895-1, to cite a few). The authors should refer to some of these studies to counterbalance the statements of increased IFN-I response in severe COVID-19 patients in some parts of the manuscript, such as in the Discussion.
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In Fig 5, the authors stimulate PMNs from healthy controls in vitro with IFN-I and use mainly IL-1b as a readout for neutrophil priming. The authors should analyse whether IFN-I-mediated priming ultimately leads to NETosis, given the relevance of NETs to COVID-19 pathology (10.1016/j.tips.2023.06.007), which is acknowledged by the authors in the Introduction. It would also be interesting to explore the involvement of IFN-I receptors (IFNAR1 vs IFNAR2) by dissecting IFN-a from IFN-b responses.
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In Methods (Histology and immunohistochemistry), the authors mention that histone H3 is a NET marker and use this in Supp Fig 5 to support evidence of NETosis. The authors should state which antibody clone/company was used. Histone H3 is expressed in high levels by non-NETotic neutrophils. Citrullinated histone H3 (CitH3), on the other hand, is detectable by few commercially available antibodies and can be used as a NET marker in conjunction with other markers such as DNA staining (10.1084/jem.20201129).
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In Fig 8, the authors show that neutrophils migrate to the lungs of infected animals. This finding is showed in many previous studies and does not seem to favour the structure of the manuscript. Instead, it seems it would fit a Supp Fig better or a portion of the following figure.
Significance
By conducting transcriptomics analyses, Cabrera LE et al. elucidate the inflammasome formation in neutrophils during SARS-CoV-2 infection. The authors have found a strong IFN-I signature in neutrophils from severe COVID-19 patients and show that IFN-I functions as a priming stimulus for neutrophil inflammasome.
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www.biorxiv.org www.biorxiv.org
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1. General Statements
We thank the reviewers for their excellent work that greatly improved our work. We are very content that reviewer #1 considered our work to be “novel, interesting and important for understanding the mitochondrial biology of PD”. This reviewer also valued our work as “a significant advancement” and suggested further study of the relationship of CISD1 (dimerization) to general mitophagy/autophagy. We addressed this in the already transferred revision (version 1, v1).
Also reviewer #2 considered our work to be “an exciting and well-executed piece of research focusing on the defects in iron homeostasis observed in Parkinson's disease which a wide audience will appreciate”. This reviewer had a very specific suggestion on how to improve our manuscript which makes a lot of sense and is feasible. As the suggested experiments include fly breeding and behavioral analysis, these experiments will be included in the second revision to be uploaded as soon as possible (version 2, v2).
Finally, reviewer #3 gathered that parts of our results “are confirmatory to recently published work” but also appreciated that our results established that iron-depleted apo-Cisd is an important determinant of toxicity which has not been shown before. I would like to comment here, that in contrast to the paper mentioned by this reviewer, our contribution includes data from dopaminergic neurons obtained from human patients suffering from familial Parkinson’s disease that demonstrate the same increase in apo-Cisd levels as the flies. This reviewer mainly suggested that the manuscript would be improved by a more balanced discussion of the strengths and weaknesses of the study and more circumspection in interpretation of data which we did in the revised version of our manuscript. We also added data on the expression levels of Cisd and apo-Cisd in transgenic flies as also suggested.
2. Description of the planned revisions
Reviewer #1 (Evidence, reproducibility and clarity):
Summary: The manuscript focuses on mitochondrial CISD1 and its relationship to two Parkinson's disease (PD) proteins PINK1 and Parkin. Interestingly, CISD1 is a mitochondrial iron sulfur binding protein and an target of Parkin-mediated ubiquitinylation. Disruption of iron metabolism and accumulation of iron in the brain has long since been reported in PD but the involvement of iron sulfur binding is little studied both in vivo and in human stem cell models of PD. This work addresses the relationship between CISD1 and two mitochondrial models of PD (PINK1 and Parkin) making use of in vivo models (Drosophila), PINK1 patient models (iPSC derived neurons) and Mouse fibroblasts. The authors report a complex relationship between CISD1, PINK1 and Parkin, where iron-depleted CISD1 may illicit a toxic gain of function downstream of PINK1 and Parkin.
Major comments:
The conclusions are overall modest and supported by the data. One question remains unaddressed. Is mitochondrial CISD1 a downstream target that specifically mediates PINK1 and Parkin loss of function phenotypes or are the phenotypes being mediated because CISD1 is downstream of mitophagy in general?
It would be interesting to know what happens to CISD1 (dimerization?) upon initiation of mitophagy in wild type cells? Would dissipation of mitochondrial membrane potential be sufficient to induce changes to CISD1 in wild type cells or PINK1 deficient cells? Since iron chelation is a potent inducer of mitophagy (Loss of iron triggers PINK1/Parkin-independent mitophagy. George F G Allen, Rachel Toth, John James, Ian G Ganley. EMBO Reports (2013)14:1127-1135) it would be useful to show one experiment addressing the role of CISD1 dimerization under mitochondrial depolarizing and non-depolarizing conditions in cells.
Based on the overall assumption of the reviewer that our work is “novel, interesting and important for understanding the mitochondrial biology of PD” and “a significant advancement” we understand the word “modest” here as meaning “not exaggerated”. To address this question, we studied CISD1 dimerization in response to more classical activators of mitophagy namely FCCP and antimycin/oligomycin which had no significant effect on dimerization suggesting that this phenotype is more pronounced under iron depletion. These data are shown in the new Fig. 2c.
Alternatively, the authors should discuss the topic of mitophagy (including PINK1-parkin independent mitophagy), the limitation of the present study not being able to rule out a general mitophagy effect and previous work on the role of iron depletion on mitophagy induction in the manuscript.
The data and the methods are presented in such a way that they can be reproduced.
The experiments are adequately replicated and statistical analysis is adequate.
Minor comments:
Show p values even when not significant (ns) since even some of the significant findings are borderline < p0.05.
Here, I decided to leave it as it is, because the figures became very cluttered and less easy to understand. Borderline findings are however indicated and mentioned in the text.
Because the situation for CISD1 is complicated (overexpression, different models etc.) it would be helpful if in the abstract the authors could summarize the role. E.g. as in the discussion that iron-depleted CISD1 could represent a toxic function.
The abstract has been completely rewritten and now mentions the potential toxic function of iron-depleted CISD1.
If there is sufficient iron (accumulation in PD) why would CISD1 be deactivated? Perhaps that could be postulated or discussed in a simplified way?
We actually think that apo-CISD1 without its iron/sulfur cluster is incapable of transferring its Fe/S cluster to IRP1 and IRP2. This then results in increased levels of apo-IRP1/2 and subsequent changes that lead to iron overload. Such a sequence of events would place CISD1 upstream of the changes in iron homeostasis observed in PD and models of PD. This is now discussed in more detail.
In the methods section both reducing and non-reducing gel/Western blotting is mentioned but the manuscript only describes data from blots under reducing conditions. Are there blots under non-reducing conditions that could be shown to see how CISD1 and dimerized CISD1 resolve?
We now show these blots as supplemental data in new supplemental Figure 2.
In the results section, PINK1 mutant flies, it is said that the alterations to CISD1 (dimerization) are analogous to the PINK1 mutation patient neurons. The effect is seen in old but not young flies. Since iPSC-derived neurons are relatively young in the dish, would one not expect that young flies and iPSC-derived neurons have similar CISD1 phenotypes? Could the authors modify the text to reflect that? or discuss the finding in further context.
We only studied one time point in PINK1 mutation patient neurons and controls. It would indeed be interesting whether neuronal aging (as far as this can be studied in the dish) would result in increased CISD1 dimerization. This is now discussed.
Reviewer #1 (Significance):
The strengths of this work are in the novelty of the topic and the use of several well established in vivo and cell models including patient-derived neurons. The findings discussed in the text are honest and avoid over-interpretation. The findings are novel, interesting and important for understanding the mitochondrial biology of PD.
We thank the reviewer for their kind words.
Limitations include the lack of strong phenotypes in the CISD1 models and the lack of robust, sustained and consistent increase in CISD1 dimers in the patient and fly models (just significant because of variability). The relationship of CISD1 (dimerization) to general mitophagy/autophagy is not shown here.
We do not completely agree with the assumption that all CISD1 models lack a strong phenotype. At least the CISD1-deficient fibroblasts exhibit a strong phenotype consisting of fragmented mitochondria and increased oxidative stress. The lack of a strong phenotype in Cisd-deficient flies could actually hint to a potential compensatory mechanism that could also protect the Pink1 mutant x Cisd-deficient double-knockout flies. It is correct that the increase in CISD1/Cisd dimers in the PD models are not overwhelming but – as also mentioned by the reviewer – this could be increased in “older” cultures. This is now discussed in more detail. As suggested by the reviewer, we have now added experiments that study the relationship between CISD1 dimerization and conventional mitophagy as described above.
There is a significant advancement. So far researchers were able to describe the importance of iron metabolism in PD (For example refer to work from the group of Georg Auburger such as PMID 33023155 and discussion of therapeutic intervention such as reviewed by Ma et al. PMID: 33799121) but few papers describe involvement of iron sulfur cluster proteins specifically (such as Aconitase) in relation to PINK1 and parkin (these are cited). The fact that CISD1 is a protein of the mitochondrial outer membrane makes it particularly interesting and further studies looking more closely at the interaction of CISD1 with mitochondrial proteins associated with PD will be of interest.
We thank the reviewer for pointing out these excellent publications. Key et al present an enormous wealth of data on protein dysregulation of wildtype and Pink1-/- fibroblast cell lines upon perturbation of the iron homeostasis (Key et al, 2020). Both cell lines exhibit a downregulation of CISD1 levels upon iron deprivation with the agent 2,2′ -Bipyridine possibly as a compensatory mechanism to limit the toxic gain of function of iron-depleted CISD1. The other paper, Ma et al. is a recent review on changes in iron homeostasis in PD and PD models (Ma et al, 2021). Both papers are now cited in the manuscript.
This paper describes CISD1 as a new and relevant player in PINK1 and Parkin biology. Further work could lead to exploration of whether CISD1 could be a therapeutic target, considering its role in maintaining mitochondrial redox and mitochondrial health. This is of particular interest to mitochondrial biologists and pre-clinical research in PD.
This preprint was reviewed by three scientists whose research focus in the mitochondrial biology underlying Parkinson's disease. The group has a special interest in the functions of the mitochondrial outer membrane. We work with several cell models of Parkinson's disease and work with patient donated samples. We do not have expertise in Drosophila models of PD nor the quantification of iron described in the manuscript.
Reviewer #2 (Evidence, reproducibility and clarity):
Summary: In the paper entitled 'Mitochondrial CISD1 is a downstream target that mediates PINK1 and Parkin loss-of-function phenotypes', Bitar and co-workers investigate the interaction between CISD1 and the PINK1/Parkin pathway. Mutations in PINK1 and PARKIN cause early onset Parkinson's disease and CISD1 is a homodimeric mitochondrial iron-sulphur binding protein. They observed an increase in CISD1 dimer formation in dopaminergic neurons derived from Parkinson's disease patients carrying a PINK1 mutation. Immuno-blots of cells expressing CISD1 mutants that affects the iron sulphur cluster binding and as well as cells treated with iron chelators, showed that the tendency of CISD1 to form dimers is dependent on its binding to iron-sulphur clusters. Moreover, the Iron-depleted apo-CISD1 does not rescue mitochondrial phenotypes observed in CISD1 KO mouse cells. Finally, In vivo studies showed that overexpression of Cisd and mutant apo-Cisd in Drosophila shortened fly life span and, using a different overexpression model, apo-Cisd caused a delay in eclosion. Similar as patient derived neurons, they observed an increase in Cisd dimer levels in Pink1 mutant flies. Additionally, the authors showed that double mutants of Cisd and Pink1 alleviated all Pink1 mutant phenotypes, while double mutants of Prkn and Cisd rescued most Prkn mutant phenotypes.
Major comments:
1) The authors observed an increase in the levels of Cisd dimers in Pink1 mutant flies and removing Cisd in Pink1 mutant background rescues all the mutant phenotypes observed in Pink1 mutant flies, suggesting that the Cisd dimers are part and partial of the Pink1 mutant phenotype. The authors also generated a UAS_C111S_Cisd fly which can overexpress apo-Cisd. Overexpression of the C111S_Cisd construct with Tub-Gal4 showed a developmental delay. Since apo-Cisd forms more dimeric Cisd, my question is: does the strong overexpression (e.g. with Tub-Gal4) of the C111S_Cisd in wild type flies shows any of the Pink1 mutant phenotypes? If not, the authors should mention this and elaborate on it.
We thank the reviewer for their comments. In fact, we only observed very few flies ecclosing after overexpression of wildtype Cisd or C111S Cisd using the strong tubP-Gal4 driver during development. We considered these very few flies to be escapees (also indicated by the rather low induction of Cisd mRNA suggesting compensatory downregulation) and only used them to conduct the analysis shown in Figure 4c-e. This is now mentioned in more detail in the manuscript.
2) Figure 6g: Shows the TEM pictures of the indirect flight muscles of Pink1 mutant flies and Pink1, Cisd double mutants. To me, the Picture of Pink1 mutant mitochondria is not very convincing. We expect swollen (enlarged) mitochondria with disrupted mitochondrial matrix. However, this is not clear in the picture. Moreover, in my opinion, Figure6 g, is missing an EM Picture of the Cisd mutant indirect flight muscles.
We now show exemplary pictures from Pink1 mutant and DKO in a higher magnification which better demonstrate the rounded Pink1 mutant mitochondria and the disrupted cristae structure. EM pictures of all four genotypes in different magnifications are now shown in new supplemental Figure 6.
3) OPTIONAL: The authors suggest that most probably apo-Cisd, assumes a toxic function in Pink1 mutant flies and serves as a critical mediator of Pink1-linked phenotypes. If this statement is correct, we can hypothesize that increasing apo-Cisd in Pink1 mutant background should worsen the pink1 mutant defects.
Therefore, I suggest overexpressing Cisd1 wild type (and/or C111S Cisd) in pink1 mutant flies, as pink1 is on the X chromosome, and mild overexpression of Cisd1 with da is not lethal, these experiments could be done in 3-4 fly crosses and hence within 1.5 - 2 months.
We have set up this experiment and will report in the second revision (v2) of our manuscript.
Since Pink1 mutant flies contain higher levels of endogenous Cisd dimers, we can expect that overexpression of wild type Cisd will result in an even stronger increase of dimers. If these dimers indeed contribute to Pink1 mutant phenotypes we can expect that overexpression of Cisd will result in a worsening of the Pink1 mutant phenotypes.
We have set up this experiment and will report in the second revision of our manuscript.
Minor Comments:
-) In the Introduction (Background) there are some parts without references:
E.g., there is not a single reference in the following part between
'However, in unfit mitochondria with a reduced mitochondrial membrane potential ...&... compromised mitochondria safeguards overall mitochondrial health and function.'
We thank the reviewer for pointing out this flaw. We have now added a suitable reference to the introduction.
-) In the introduction there is some confusion about the nomenclature used in the article: e.g. following comments are made in the text: Cisd2 (in this publication referred to as Dosmit) or fly Cisd2 (in this publication named MitoNEET).
However, the names Dosmit and MitoNEET do not appear in the manuscript (except in references)
The literature and nomenclature for CISD1 are indeed confusing. We have now revised the introduction.
-) Figure 1: I am not sure why some gels are shown in this figure. The two last lanes of figure 1c are redundant and Figure 1c' which is also not mentioned in the text, is also a repetition of figure 1c.
The blots in 1c and 1c’ represent all data points (different patients and different individual differentiations) shown in the quantification in 1d. This is now explained better in the revised manuscript.
-) The authors mention in material and methods that T2A sites are used at the C-terminus of CISD1 to avoid tagging of CISD1. However, this is not entirely true as T2A will leave some amino acids (around 20) after the self-cleaving and therefore CISD1 will be tagged.
This is indeed true and we have now changed the wording in the revised manuscript.
-) In figure 5 P1 is used to abbreviate Pink1 mutants, however P1, to me, refers to pink1 wild type. It would be clearer to abbreviate Pink1 mutants as P1B9 in the graphs as B9 is the name of the mutant pink1 allele.
We thank the reviewer for pointing out this flaw. We have now altered Fig. 5 to be clearer.
-) In figure 7: Parkin is abbreviated both as Prkn and as Park
We thank the reviewer for pointing out this flaw, we indeed mixed up both names because it is complicated. The gene symbol is Prkn, the fly line is called Park25. We have now clarified this in the text and Fig. 7.
-) I suggest changing the title. Recently an article (Ham et al, 2023 PMID: 37626046) was published showing similar genetic interactions between Pink1/Prkn and Cisd. However, the article of Ham et al, 2023 was focused on Pink1/Prkn regulation of ER calcium release, while this article is more related to iron homeostasis. I suggest that the title shows this distinction.
This is indeed a very good suggestion. We have now altered the title to “Iron/sulfur cluster loss of mitochondrial CISD1 mediates PINK1 loss-of-function phenotypes”.
Reviewer #2 (Significance):
In general, this is an exciting and well-executed piece of research focusing on the defects in iron homeostasis observed in Parkinson's disease which a wide audience will appreciate. Very recently, a similar genetic interaction between Cisd and Pink1/Prkn in flies was published (Ham et al, 2023 PMID: 37626046) however, from a different angle. While, Ham et al focused on the role of Pink1/Prkn and Cisd in IP3R related ER calcium release, this manuscript approaches the Pink1/Prkn - Cisd interaction from an iron homeostasis point of view. Since, iron dysregulation contributes to the pathogenesis of Parkinson's disease, the observations in this manuscript are relevant for the disease. Hence, the work is sufficiently novel and deserves publication. However, additional experiments are suggested to strengthen the authors' conclusions.
We thank the reviewer for their kind words. As mentioned above, these additional experiments are on their way and will be included in version 2 of our revised manuscript (v2).
I work on Drosophila models of Parkinson's disease
Referees cross-commenting
I agree with the reviewer number 1 that it would be interesting to investigate CISD1 dimerisation status during mitophagy.
As mentioned above, we now studied CISD1 dimerization in response to more classical activators of mitophagy namely FCCP and antimycin/oligomycin which had no significant effect on dimerization suggesting that this phenotype is more pronounced under iron depletion. These data are shown in the new Fig. 2c.
Reviewer #3 (Evidence, reproducibility and clarity):
Here the authors provide evidence that Cisd is downstream of Parkin/Pink1 and suggest that the levels of apo-Cisd correlate with neurotoxicity. The data presented generally supports the conclusions of the authors and will be useful to those in the field. The manuscript would be improved by a more balanced discussion of the strengths and weaknesses of the study and more circumspection in interpretation of data.
We thank the reviewer for their comments aimed to improve our manuscript. We have now discussed the strengths and weaknesses of our study in more detail.
Introduction. While iron has been implicated in Parkinson's disease, it is an overstatement to say that disruption in iron metabolism contributes significantly to the pathogenesis of the disease.
There is certainly a plethora of data implicating perturbed iron homeostasis in PD as also pointed out by reviewer #1. We have tried to tone down our wording in the text and added a recent review on the topic (Ma et al, 2021) as also suggested by reviewer #1.
Introduction. The discussion of the various names for Cisd2 is important, but confusing as written. Specifically, the use of "this" makes the wording unclear.
We thank the reviewer for pointing out this flaw. We have altered the wording in the introduction.
Methods. It would be preferable to use heterozygous driver lines or a more similar genetic control rather than w-1118.
The exact controls were indeed not well explained in the Methods section, this has been corrected in the revised version. In brief, homozygous driver and UAS lines were indeed used in Fig. 4, this will be addressed in the second revision of our manuscript together with the experiments reviewer #2 suggested. The data shown in Fig. 5, 6, and 7 all used w1118 as control because all other fly strains are on the same genetic background.
Page 10. It appears that the PINK1 lines have been described previously. The authors should clarify this point and ensure that the new data presented in the current manuscript (presumably the mRNA levels, Fig. 1a) is indicated, as well as data that is confirmatory of prior findings (Fig. 1b).
Yes, these PINK1 lines have been described previously as pointed out in the manuscript. The original paper did not quantify the PINK1 mRNA levels shown in Fig. 1a. The blots shown in Fig. 1b are from new differentiations and have also not been shown before but confirm findings published in Jarazo et al. (Jarazo et al, 2022). This has been clarified in the revised version of our manuscript.
Fig. 3 legend. There is a typographical error, "ne-way ANOVA."
We thank the reviewer for pointing out this flaw. This has been corrected in the revised version.
Page 15. The nature of the Pink1-B9 mutant should be specified.
We now added a supplemental Figure 1 that depicts the specific mutation in these flies.
Fig. 4. Levels of mutant and wild type Cisd should be compared in transgenic flies.
We now added a quantification of mutant and wildtype Cisd levels to the new Figure 4d.
Fig. 5b,d. The striking change seems to be the decrease in dimers in young Pink1 mutant animals, not the small increase in dimers in the older Pink1 mutants.
It is always difficult to find a “typical” picture that reflects all changes observed in quantitative data. This Figure actually shows a decrease of total Cisd levels in young flies in Fig. 5c but no difference of the dimer/monomer ratio in Fig. 5d.
Fig. 5f. Caution should be used in interpreting the results. Deferiprone has toxicity to wildtype flies (trend) and may simply be making sick Pink1 mutants sicker.
There is certainly a tendency for wildtype flies to thrive less in food containing deferiprone. To make this more obvious, we have now added the exact p value (0.0764, which we don’t consider borderline but a tendency) to this figure and mention this fact in the text.
Fig. 5e. The data are hard to interpret. The number of animals is very small for a viability study and the strains are apparently in different genetic backgrounds, though this is not clearly specified. The experiment in Supplementary Fig. 1 appears better controlled and supports the Pink1 data; however, a similar concern pertains to Fig. 7. The authors may thus wish to be more circumspect in their interpretation, especially of the Parkin data.
In Fig 5e we quantified total iron levels and the Fe3+/Fe2+ ratio using capillary electrophoresis-inductively coupled plasma mass spectrometry (CE-ICP-MS). Although indeed not so many flies were used in this quantification, the results are highly significant. If the reviewer was referring to Fig. 5f, we agree that this experiment was not well (to be honest, even wrongly explained) which we corrected in the revised version of this manuscript. We thank the reviewer for pointing out this flaw.
Reviewer #3 (Significance):
The major significance of the study is in putting downstream of Parkin/Pink1 (largely confirmatory to recently published work) and suggesting that the levels of apo-Cisd are an important determinant of toxicity. The work will be of interest to those in the field.
3. Description of the revisions that have already been incorporated in the transferred manuscript
The changes already carried out and included in the transferred manuscript (v1) are indicated above in bold orange. All changes pending on ongoing experiments to be included in the second revision of the manuscript are indicated above in bold magenta.
4. Description of analyses that authors prefer not to carry out
All changes suggested by the reviewers were addressed (v1) or will be addressed (v2).
References
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Referee #3
Evidence, reproducibility and clarity
Here the authors provide evidence that Cisd is downstream of Parkin/Pink1 and suggest that the levels of apo-Cisd correlate with neurotoxicity. The data presented generally supports the conclusions of the authors and will be useful to those in the field. The manuscript would be improved by a more balanced discussion of the strengths and weaknesses of the study and more circumspection in interpretation of data.
- Introduction. While iron has been implicated in Parkinson's disease, it is an overstatement to say that disruption in iron metabolism contributes significantly to the pathogenesis of the disease.
Introduction. The discussion of the various names for Cisd2 is important, but confusing as written. Specifically, the use of "this" makes the wording unclear.<br /> - Methods. It would be preferable to use heterozygous driver lines or a more similar genetic control rather than w-1118.<br /> - Page 10. It appears that the PINK1 lines have been described previously. The authors should clarify this point and ensure that the new data presented in the current manuscript (presumably the mRNA levels, Fig. 1a) is indicated, as well as data that is confirmatory of prior findings (Fig. 1b).<br /> - Fig. 3 legend. There is a typographical error, "ne-way ANOVA."<br /> - Page 15. The nature of the Pink1-B9 mutant should be specified.<br /> - Fig. 4. Levels of mutant and wild type Cisd should be compared in transgenic flies.<br /> - Fig. 5b,d. The striking change seems to be the decrease in dimers in young Pink1 mutant animals, not the small increase in dimers in the older Pink1 mutants.<br /> - Fig. 5f. Caution should be used in interpreting the results. Deferiprone has toxicity to wildtype flies (trend) and may simply be making sick Pink1 mutants sicker.<br /> - Fig. 5e. The data are hard to interpret. The number of animals is very small for a viability study and the strains are apparently in different genetic backgrounds, though this is not clearly specified. The experiment in Supplementary Fig. 1 appears better controlled and supports the Pink1 data; however, a similar concern pertains to Fig. 7. The authors may thus wish to be more circumspect in their interpretation, especially of the Parkin data.
Significance
The major significance of the study is in putting downstream of Parkin/Pink1 (largely confirmatory to recently published work) and suggesting that the levels of apo-Cisd are an important determinant of toxicity. The work will be of interest to those in the field.
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Referee #2
Evidence, reproducibility and clarity
Summary:
In the paper entitled 'Mitochondrial CISD1 is a downstream target that mediates PINK1 and Parkin loss-of-function phenotypes', Bitar and co-workers investigate the interaction between CISD1 and the PINK1/Parkin pathway. Mutations in PINK1 and PARKIN cause early onset Parkinson's disease and CISD1 is a homodimeric mitochondrial iron-sulphur binding protein. They observed an increase in CISD1 dimer formation in dopaminergic neurons derived from Parkinson's disease patients carrying a PINK1 mutation. Immuno-blots of cells expressing CISD1 mutants that affects the iron sulphur cluster binding and as well as cells treated with iron chelators, showed that the tendency of CISD1 to form dimers is dependent on its binding to iron-sulphur clusters. Moreover, the Iron-depleted apo-CISD1 does not rescue mitochondrial phenotypes observed in CISD1 KO mouse cells. Finally, In vivo studies showed that overexpression of Cisd and mutant apo-Cisd in Drosophila shortened fly life span and, using a different overexpression model, apo-Cisd caused a delay in eclosion. Similar as patient derived neurons, they observed an increase in Cisd dimer levels in Pink1 mutant flies. Additionally, the authors showed that double mutants of Cisd and Pink1 alleviated all Pink1 mutant phenotypes, while double mutants of Prkn and Cisd rescued most Prkn mutant phenotypes.
Major comments:
- The authors observed an increase in the levels of Cisd dimers in Pink1 mutant flies and removing Cisd in Pink1 mutant background rescues all the mutant phenotypes observed in Pink1 mutant flies, suggesting that the Cisd dimers are part and partial of the Pink1 mutant phenotype. The authors also generated a UAS_C111S_Cisd fly which can overexpress apo-Cisd. Overexpression of the C111S_Cisd construct with Tub-Gal4 showed a developmental delay. Since apo-Cisd forms more dimeric Cisd, my question is: does the strong overexpression (e.g. with Tub-Gal4) of the C111S_Cisd in wild type flies shows any of the Pink1 mutant phenotypes? If not, the authors should mention this and elaborate on it.
- Figure6 g: Shows the TEM pictures of the indirect flight muscles of Pink1 mutant flies and Pink1, Cisd double mutants. To me, the Picture of Pink1 mutant mitochondria is not very convincing. We expect swollen (enlarged) mitochondria with disrupted mitochondrial matrix. However, this is not clear in the picture. Moreover, in my opinion, Figure6 g, is missing an EM Picture of the Cisd mutant indirect flight muscles.
- OPTIONAL: The authors suggest that most probably apo-Cisd, assumes a toxic function in Pink1 mutant flies and serves as a critical mediator of Pink1-linked phenotypes. If this statement is correct, we can hypothesize that increasing apo-Cisd in Pink1 mutant background should worsen the pink1 mutant defects.
Therefore, I suggest overexpressing Cisd1 wild type (and/or C111S Cisd) in pink1 mutant flies, as pink1 is on the X chromosome, and mild overexpression of Cisd1 with da is not lethal, these experiments could be done in 3-4 fly crosses and hence within 1.5 - 2 months.
Since Pink1 mutant flies contain higher levels of endogenous Cisd dimers, we can expect that overexpression of wild type Cisd will result in an even stronger increase of dimers. If these dimers indeed contribute to Pink1 mutant phenotypes we can expect that overexpression of Cisd will result in a worsening of the Pink1 mutant phenotypes.
Minor Comments:
- In the Introduction (Background) there are some parts without references:<br /> E.g., there is not a single reference in the following part between<br /> 'However, in unfit mitochondria with a reduced mitochondrial membrane potential ...&... compromised mitochondria safeguards overall mitochondrial health and function.'
- In the introduction there is some confusion about the nomenclature used in the article: e.g. following comments are made in the text: Cisd2 (in this publication referred to as Dosmit) or fly Cisd2 (in this publication named MitoNEET).<br /> However, the names Dosmit and MitoNEET do not appear in the manuscript (except in references)
- Figure 1: I am not sure why some gels are shown in this figure. The two last lanes of figure 1c are redundant and Figure 1c' which is also not mentioned in the text, is also a repetition of figure 1c.
- The authors mention in material and methods that T2A sites are used at the C-terminus of CISD1 to avoid tagging of CISD1. However, this is not entirely true as T2A will leave some amino acids (around 20) after the self-cleaving and therefore CISD1 will be tagged.
- In figure 5 P1 is used to abbreviate Pink1 mutants, however P1, to me, refers to pink1 wild type. It would be clearer to abbreviate Pink1 mutants as P1B9 in the graphs as B9 is the name of the mutant pink1 allele.
- In figure 7: Parkin is abbreviated both as Prkn and as Park
- I suggest changing the title. Recently an article (Ham et al, 2023 PMID: 37626046) was published showing similar genetic interactions between Pink1/Prkn and Cisd. However, the article of Ham et al, 2023 was focused on Pink1/Prkn regulation of ER calcium release, while this article is more related to iron homeostasis. I suggest that the title shows this distinction.
Referees cross-commenting
I agree with the reviewer number 1 that it would be interesting to investigate CISD1 dimerisation status during mitophagy.
Significance
In general, this is an exciting and well-executed piece of research focusing on the defects in iron homeostasis observed in Parkinson's disease which a wide audience will appreciate. Very recently, a similar genetic interaction between Cisd and Pink1/Prkn in flies was published (Ham et al, 2023 PMID: 37626046) however, from a different angle. While, Ham et al focused on the role of Pink1/Prkn and Cisd in IP3R related ER calcium release, this manuscript approaches the Pink1/Prkn - Cisd interaction from an iron homeostasis point of view. Since, iron dysregulation contributes to the pathogenesis of Parkinson's disease, the observations in this manuscript are relevant for the disease. Hence, the work is sufficiently novel and deserves publication. However, additional experiments are suggested to strengthen the authors' conclusions.<br /> I work on Drosophila models of Parkinson's disease
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Referee #1
Evidence, reproducibility and clarity
Summary:
The manuscript focuses on mitochondrial CISD1 and its relationship to two Parkinson's disease (PD) proteins PINK1 and Parkin. Interestingly, CISD1 is a mitochondrial iron sulfur binding protein and an target of Parkin-mediated ubiquitinylation. Disruption of iron metabolism and accumulation of iron in the brain has long since been reported in PD but the involvement of iron sulfur binding is little studied both in vivo and in human stem cell models of PD. This work addresses the relationship between CISD1 and two mitochondrial models of PD (PINK1 and Parkin) making use of in vivo models (Drosophila), PINK1 patient models (iPSC derived neurons) and Mouse fibroblasts. The authors report a complex relationship between CISD1, PINK1 and Parkin, where iron-depleted CISD1 may illicit a toxic gain of function downstream of PINK1 and Parkin.
Major comments:
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The conclusions are overall modest and supported by the data. One question remains unaddressed. Is mitochondrial CISD1 a downstream target that specifically mediates PINK1 and Parkin loss of function phenotypes or are the phenotypes being mediated because CISD1 is downstream of mitophagy in general?<br /> It would be interesting to know what happens to CISD1 (dimerization?) upon initiation of mitophagy in wild type cells? Would dissipation of mitochondrial membrane potential be sufficient to induce changes to CISD1 in wild type cells or PINK1 deficient cells?
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Since iron chelation is a potent inducer of mitophagy (Loss of iron triggers PINK1/Parkin-independent mitophagy. George F G Allen, Rachel Toth, John James, Ian G Ganley. EMBO Reports (2013)14:1127-1135) it would be useful to show one experiment addressing the role of CISD1 dimerization under mitochondrial depolarizing and non-depolarizing conditions in cells.
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Alternatively, the authors should discuss the topic of mitophagy (including PINK1-parkin independent mitophagy), the limitation of the present study not being able to rule out a general mitophagy effect and previous work on the role of iron depletion on mitophagy induction in the manuscript.
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The data and the methods are presented in such a way that they can be reproduced.<br /> The experiments are adequately replicated and statistical analysis is adequate.
Minor comments:
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Show p values even when not significant (ns) since even some of the significant findings are borderline < p0.05.
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Because the situation for CISD1 is complicated (overexpression, different models etc.) it would be helpful if in the abstract the authors could summarize the role. E.g. as in the discussion that iron-depleted CISD1 could represent a toxic function.
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If there is sufficient iron (accumulation in PD) why would CISD1 be deactivated? Perhaps that could be postulated or discussed in a simplified way?
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In the methods section both reducing and non-reducing gel/Western blotting is mentioned but the manuscript only describes data from blots under reducing conditions. Are there blots under non-reducing conditions that could be shown to see how CISD1 and dimerized CISD1 resolve?
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In the results section, PINK1 mutant flies, it is said that the alterations to CISD1 (dimerization) are analogous to the PINK1 mutation patient neurons. The effect is seen in old but not young flies. Since iPSC-derived neurons are relatively young in the dish, would one not expect that young flies and iPSC-derived neurons have similar CISD1 phenotypes? Could the authors modify the text to reflect that? or discuss the finding in further context.
Significance
- The strengths of this work are in the novelty of the topic and the use of several well established in vivo and cell models including patient-derived neurons. The findings are discussed in the text are honest and avoid over-interpretation. The findings are novel, interesting and important for understanding the mitochondrial biologyof PD.
- Limitations include the lack of strong phenotypes in the CISD1 models and the lack of robust, sustained and consistent increase in CISD1 dimers in the patient and fly models (just significant because of variability). The relationship of CISD1 (dimerization) to general mitophagy/autophagy is not shown here.
- There is a significant advancement. So far researchers were able to describe the importance of iron metabolism in PD (For example refer to work from the group of Georg Auburger such as PMID 33023155 and discussion of therapeutic intervention such as reviewed by Ma et al. PMID: 33799121) but few papers describe involvement of iron sulfur cluster proteins specifically (such as Aconitase) in relation to PINK1 and parkin (these are cited). The fact that CISD1 is a protein of the mitochondrial outer membrane makes it particularly interesting and further studies looking more closely at the interaction of CISD1 with mitochondrial proteins associated with PD will be of interest.
- This paper describes CISD1 as a new and relevant player in PINK1 and Parkin biology. Further work could lead to exploration of whether CISD1 could be a therapeutic target, considering its role in maintaining mitochondrial redox and mitochondrial health. This is of particular interest to mitochondrial biologists and pre-clinical research in PD.
- This preprint was reviewed by three scientists whose research focus in the mitochondrial biology underlying Parkinson's disease. The group has a special interest in the functions of the mitochondrial outer membrane. We work with several cell models of Parkinson's disease and work with patient donated samples. We do not have expertise in Drosophila models of PD nor the quantification of iron described in the manuscript.
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Reply to the reviewers
1. General Statements [optional]
__We thank all the reviewers for their time and their constructive criticism, based on which we will revise our manuscript. All our responses are indicated in red. __
2. Description of the planned revisions
Insert here a point-by-point reply that explains what revisions, additional experimentations and analyses are planned to address the points raised by the referees.
__Reviewer #1 (Evidence, reproducibility and clarity (Required)): __
The manuscript by Nguyen and Cheng is investigating the timing and mechanism of cessation of neuroblasts in the pupal optic lobe. Previous studies by several groups have determined the spatial and temporal factors required for the neuroepithelial to neuroblast transition and neuroblast to neural/glycogenesis in third instar larvae such that neuroblasts are eliminated. The mechanism of elimination of neuroblasts in the VNC or mushroom bodies have been investigated, but the mechanism(s) and the timing of elimination of medulla neuroblasts has not been investigated. The authors suggest that medulla neuroblasts are eliminated via a combination of mechanisms including apoptosis, prospero induced size symmetric terminal differentiation and a switch to gliogenesis by gcm expression. Expression of Tailless also was found to affect the timing of medulla neuroblast termination. They also ruled out several mechanisms such as ecdysone pulses.
Major comments
Clearly written and logical flow to experiments and results not over interpreted.
Clearly show that the neuroblast number and size decrease (12 to 18 hrs) and are eliminated by 30 hours
Figure 2a Marking of the Neuroepithelium. Would be more convincing if shown by PatJ expression and is clonal analysis. While the following panels use PatJ in clones suggesting are NE and NBs present it is more difficult to put into the context in the higher magnification images (Figure 2 D- M) and the Miranda expression in F' seems to be the entire lobe and it is not clear if would be any NE which does not agree with what is shown in panel A.
We will perform clonal analysis using MARCM to show that the elimination of medulla NBs (marked by Dpn) is accompanied by the depletion of NE (marked by PatJ). For Figure 2 D, E, I, L, we will change the images to the whole lobes to clearly show the shift in the NE-NB transition upon Notch OE/KD.
Is difficult to see the neuroblasts in Figure 2 D D" and E. The figure does not match what is stated in the results in that the neuroblasts are difficult to observe. If the point is that there is fewer NE cells and more neuroblasts then this is hard to see. It has been previously shown that with Notch RNAi clones prematurely extrude form the NE (Egger 20210; Keegan 2023) and could be expressing more Neuroblast markers but this is not visible in the panels as shown. Are the images single focal plane or maximum projections? Imaging more deeply in the brain or viewing in cross section would account for these possibilities. The possibility that are more neuroblasts but not all at the surface of the OL should be addressed as this could also alter the overall results.
Figure 2 is key to first point of the paper so needs to be addressed.
The images are single focal plane of the superficial layer of the medulla. We will specify this information in the figure legends. We will include cross-section of the notch RNAi clones to show the delamination of precocious NBs.
Minor comments
Why express volume of DPN in clone volume. Would make the point more clear and more strong be to express as number of NB in the 3-D volume of the clone. This measurement occurs in several figures.
We will redo the quantification as suggested.
Use of Miranda to mark NBs is unclear in Figure 2. Perhaps more clear in B&W.
We will redo the staining with Dpn instead of Mira to mark medulla NBs. Figures will be presented in B&W as suggested.
Make clear in figures (or figure legend) if single focal plane or projections.
We will do so.
It is unclear what percentage of NB the Gal4 line eyR16F10 are expressed in. Veen 2023 state that the GAL4 is also expressed in neurons and at different levels whether deeper within the brain or superficially on the surface of the brain. At 16 APF it is expressed but it is not clear whether it is in all cells at a low level or only within a few cells
We will further characterize the expression of eyR16F10-GAL4 in the pupal medulla as suggested.
Some RNAi lines referenced as previously validated and other are not. For example: EcR, Oxphos, Med27, Notch need references or confirmation of specificity to the intended target (qRT)
We will perform RT-qPCR to validate the use of UAS-med27 RNAi. For RNAi stocks such as UAS-EcR RNAi, UAS-Atg1 RNAi, UAS-notch RNAi that have been previously used in other publications, we will provide appropriate references.
At least 2 animals per genotype were used. While I appreciate the technical difficulty of working in pupae this seems a bit low in terms of number of samples and data would be more robust with more numbers.
Any experiments in which less than 3 animals were used, we will redo the experiments.
Reviewer #1 (Significance (Required)):
This provides mechanism and timing for the elimination of neuroblasts (NE to NB) that arise from the medulla. As these are most similar to mammalian brain development (Radial glial to NSC) this information provides more context to interpret the formation of glial and neurons in the adult optic lobe given the effect on timing and mechanisms of elimination.
This paper would be of interest to developmental biologist who work with Drosophila or mice who are looking at neural development. An understanding of how neural diversity is achieved and the mechanisms behind this that can be dysfunctional in terms of etiology of neural diseases. Is a well done study for the most part that would be improved by clarifying some data and provided more replicates for robustness of the data.
I am a developmental biologist working with Drosophila in larval and adult neural development.
__Reviewer #2 (Evidence, reproducibility and clarity (Required)): __
Lineages of neural stem cells are of great interest to understand how many neural types are generated. They produce very diverse neurons, often in a highly stereotyped series. However, they must terminate their life when the animal becomes functional or if neurons need time to become mature before birth.
In the Drosophila optic lobes, neural stem cells are produced over a period of several days by a wave of neurogenesis that transforms a neuroepithelium into neural stem cells that undergo a series of temporal patterning steps. It has been reported that they finish their life when a symmetric division generates glial cells. The authors however analyze the end of a particular lineage, that of the latest born neural stem cells of the medulla.
The paper shows that neural stem cells stop being produced when the neuroepithelium is consumed. But how do the latest born neural stem cells stop their lineage?
The results show that they do so by several means, which is quite unexpected: they may die from apoptosis, or autophagy, by becoming glioblasts or by a terminal symmetric division.
There are no major issues affecting the conclusions
- The paper shows that the end of production of neural stem cells occurs the neuroepithelium is completely transformed. The experiments performed by the authors are fine and show that, if the transition is delayed, neural stem cells terminate their life later, and vice versa. However, the lifespan of the neural stem cells is not affected by the timing of the transition. Therefore, these experiments do not tell us how neural stem cells terminate their life, which is the central question of the study. The discussion should be written accordingly and the title and the model in Fig 6 modified to reflect the importance of the end of life of the stem cells, the main theme of the paper.
We agree that our said experiments did not elucidate how NBs terminate at the end of neurogenesis. Nevertheless, our aim is to show that the timing of NB termination in the medulla is dependent on the timing of the NE-NB transition.
In Supplementary Figure 1, we showed that factors previously shown to be involved in NB termination in other lineages did not play similar roles in the medulla NBs. Thus, we think that NB termination in the medulla is likely regulated at the levels of the NE, but not the NBs themselves. Although we have briefly mentioned this in our manuscript, we hope by conducting the experiments suggested by the reviewer (see below), we can subsequently modify our model in Figure 6 and our discussion.
- The authors talk about Pros-dependent symmetric division and gliogenic switch as two separate processes, but these may be two sides of the same phenomenon. Tll+ gcm+ neural stem cells undergo Pros-dependent cell cycle exit, generating glial progeny. If the authors agree with this, could they update their model (and discussion) to reflect the fact that gliogenic switch occurs via a Pros-dependent symmetric division, and these are not two separate processes independently contributing to the depletion of the neural stem cell pool? Ideally, a triple staining between Dpn, Pros, and gcm would show that the symmetrically dividing cells seen by the authors are committed to the glial fate.
We will further test how gliogenesis is affected in pros RNAi clones. The results may shed light on whether Pros-mediated symmetric division is required for Gcm-mediated gliogenesis in the medulla. Regarding the model, we have summarized our findings and suggestions in Figure 5K, however, we will integrate this information into our final model.
In Figure 5C, we showed that at 12h APF, there are Dpn+ NBs in the medulla that expressed both Pros and Gcm, suggesting that it is very likely that Pros is upstream of Gcm to induce the glial cell fate switch of the medulla NBs.
- Why were Notch RNAi experiments assessed for the presence of neural stem cells at P12 and gcm RNAi experiments at P24? Given that most optic lobe neural stem cells disappear between P12-18, a subtle effect of gcm RNAi may have been missed. Do the authors have data for gcm RNAi at P12?
We hypothesized that the timing of NE-NB transition affects the timing of NB termination in the medulla. Because Notch KD was previously shown to induce precocious NE-NB transition in the OL, meaning that medulla NBs are born prematurely, we expected that this manipulation will lead to a corresponding premature elimination of the NBs. In contrast, gcm RNAi which inhibits the switch into the glial cell fate of the NBs, is expected to prolong the neurogenic phase of the NBs, and thereby, their persistence by 24h APF when WT NBs are eliminated.
- The authors should acknowledge that the inhibition of either apoptosis or autophagy alone may not be fully sufficient to prevent the death of NBs. In mushroom body neural stem cells, both processes must be inhibited simultaneously to produce a strong effect on their survival (Pahl et al. 2019, PMID 30773368).
We will add this information in our discussions.
- There is an important missing point that should be addressed: is there a specific point in time when all neural stem cells must stop their lineage wherever they are in the temporal series and either die or divide symmetrically? One possibility that is not discussed is that most neural stem cells end their life through a gliogenic symmetric division while those that were generated late must stop en route and die by apoptosis and/or autophagy. This would solve the strange diversity of end-of-life, which could be easily addressed by identifying the temporal stage of the neural stem cells that undergo apoptosis
We agree that it would be of interest to understand how there are diverse mechanisms by which medulla NBs terminate during pupal development. To address if temporal progression is involved in apoptosis of the medulla NBs, we will first characterize the expression of some temporal TFs (e.g., Ey, Slp, Tll) at 12h APF when we found a subset of medulla NBs undergo apoptosis in the wildtype animals.
Minor suggestions:
We agree with these minor modifications.
-
Line 46: Specify that there are 8 type II neural stem cells in each hemisphere*.
-
The statement in lines 181-182 that "cell death, and not autophagy, makes a minor contribution to..." should be replaced with "apoptosis, and not autophagy," as autophagy is also a type of cell death.
-
The authors should adjust the logic of the section "Medulla neuroblasts terminate during early pupal development": Describe the wild-type pattern first (the decrease in the number of neural stem cells and their size with age) and then describe the perturbations aimed at disrupting the number and the size of neural stem cells
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Line 151 should refer to Fig. 2I-K, not Fig. 2J-K.
**Referees cross-commenting**
How can NBs die by different mechanisms?? This might only happen is they are in a different states, an issue that is not addressed.
it has been shown that optic lobe NBs end their life by a symmetric, gliogenic last division at the end of the last temporal window, and not by PCD.
It is likely, and the authors do hint at it, that NBs only die by PCD when they prematurely interrupt the temporal series in early pupation when neurons synchronously start undergoing maturation.
I believe that the authors should explain this, if this is indeed their model, and show that NBs die while still in early temporal windows.
Reviewer #2 (Significance (Required)):
Lineages of neural stem cells are of great interest to understand how many neural types are generated. They produce very diverse neurons, often in a highly stereotyped series. However, they must terminate their life when the animal becomes functional or if neurons need time to become mature before birth.
In the Drosophila optic lobes, neural stem cells are produced over a period of several days by a wave of neurogenesis that transforms a neuroepithelium into neural stem cells that undergo a series of temporal patterning steps. It has been reported that they finish their life when a symmetric division generates glial cells. The authors however analyze the end of a particular lineage, that of the latest born neural stem cells of the medulla.
The paper shows that neural stem cells stop being produced when the neuroepithelium is consumed. But how do the latest born neural stem cells stop their lineage?
The results show that they do so by several means, which is quite unexpected: they may die from apoptosis, or autophagy, by becoming glioblasts or by a terminal symmetric division.
There are no major issues affecting the conclusions
Reviewer #3 (Evidence, reproducibility and clarity (Required)):
Summary
In this manuscript, the authors address the timing and mechanisms responsible for the termination of medulla neuroblasts in Drosophila visual processing centres, also known as optic lobes. Through time course experiments the authors demonstrate the medulla NBs are completely eliminated by 30h APF during early pupal development. By manipulating the Notch signalling pathway as well as proneural genes such as lethal of scute, the authors show that altering the NE-NB transition is sufficient to change the timing of NB termination. In contrast, ecdysone signalling and components of the mediator complex, known to terminate proliferation of central brain NBs, are not required for the termination of medulla NBs. Medulla NBs sequentially express a variety of temporal transcription factors to promote cellular diversity, however, the authors demonstrate that altering temporal factors such as Ey, Sco or Hth, does not affect the timing of the medulla NBs termination. Interestingly however overexpression of the transcription factor tailless can cease medulla NB termination via the conversion of type I to type II NB fate. They further go on to show the importance of the differentiation factor, Prospero, in promoting the differentiation of medulla NBs as well as terminating medulla neurogenesis during pupal development. Finally, in addition to differentiation, the authors show another mechanism responsible for the cessation of neurogenesis which is the commencement of gliogenesis. Through manipulation of the neurogenic to gliogenic switch by knockdown or overexpressing the glial regulatory gene, gcm, the authors show that even though the downregulation of gcm is is not sufficient to induce NB persistence, gcm overexpression can cause premature termination of NBs.
Major comments:
- Are the key conclusions convincing?
Yes, the key conclusions are convincing with proper controls, quantifications and statistical analyses.
- Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether?
The conclusion that temporal transcription factors (TTF) do not affect the timing of medulla NB termination is somewhat preliminary. The authors investigated a simplified temporal series including Homothorax, Eyeless, Sloppy-paired, Dichaete and Tailless. However, there are additional temporal factors that have not been examined for their potential involvement in medullar NB termination. Previous reports have identified several other temporal factors that play a role in medulla TTF cascade, such as, SoxNeuro (SoxN) and doublesex-Mab related 99B (Dmrt99B) that start their expression in the NE similar to Hth, however, Dmrt99B is likely to be repressed much later than Hth (Li, Erclik et al. 2013, Zhu, Zhao et al. 2022). At this point, it remains challenging to completely rule out the possibility that other temporal factors play a role in medullar NB termination or have redundant functions in regulating the timing of medulla NB cessation. It is suggested to tone down this claim and provide a brief discussion on alternative possibilities, citing relevant papers on the functions of other temporal factors in medullar NBs.
We agree.
- Would additional experiments be essential to support the claims of the paper? Request additional experiments only where necessary for the paper as it is, and do not ask authors to open new lines of experimentation.
Loss of pros by RNAi caused the formation of ectopic NBs and the NBs persist even at 24h APF. Do these NBs persist at 30h or 48h APF? Does overexpression of Pros result in early termination of medulla NBs?
We will do these experiments in clones as suggested.
- Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated cost and time investment for substantial experiments.
Yes, I believe the suggested experiments are realistic in terms of time and resources, with an estimation of 3 months to complete the experiments.
- Are the data and the methods presented in such a way that they can be reproduced?
Yes.
- Are the experiments adequately replicated and statistical analysis adequate?
The experiments are straight forward and were performed with proper controls, supported by quantifications and proper statistical analyses. However, there is no mention about how many replicates were used.
We will add this information in our Material and Methods section.
Minor comments:
- The authors use the eyR6F10-Gal4 driver in certain experiments. The eyR6F10-Gal4 driver is however expressed only in a subset of medulla NBs. Can the authors comment on what percentage of medulla NBs is the driver expressed in? We will characterize this.
Does the EGFR signalling pathway or JAK/STAT pathway affect the timing of termination of medulla NBs? Experiments are not necessary. The author can speculate on their roles.
We will modify our discussion accordingly.
Figure 1C has a p value of only 0.03 (*) but shows a strong reduction in the number of Dpn+ cells from 12h to 18h, etc. Is this correct? Also, is the p value the same for the comparison between 12h and 24h as well as 12h and 30h APF?
Yes. P-values showed no significant differences between 28-24h and 24-30h APF.
The controls in figure 2B and to some extent figure 2H show one major outlier (much higher than the other brain lobes in the control). Will the removal of this outlier affect the significance/ p-value of the experiment?
No, removing the outliers do not change the statical results.
In figure 2B what is the p-value between 12h and 18h APF? Is it *** as well?
No, it’s not significant.
Line 84 of the introduction introduces Tll, Gcm and Pros for the first time in the manuscript and should be written out in full.
We will change this.
- Are prior studies referenced appropriately?
Yes.
- Are the text and figures clear and accurate?
Yes.
- Do you have suggestions that would help the authors improve the presentation of their data and conclusions?
Quite a few of data mentioned in the manuscript have been described as data not shown. I think it would be nice to show quantifications or representative images in the supplementary figures.
We will add the data which was previously not shown.
Reviewer #3 (Significance (Required)):
Since the mechanisms by which medulla NBs are terminated are currently unknow, this is an important and interesting study to understand how medulla neuroblasts in the optic lobe are terminated. The balance between stem cell maintenance and differentiation is critical for proper brain development and the results presented in this paper are impactful. Furthermore, Drosophila melanogaster is an excellent model to study stem cell niches and neuroblast temporal patterning. The authors provide key mechanisms namely cell death, Pros-mediated differentiation and the gliogenic switch that contribute to a better understanding of how the NB progenitor pool can be terminated in the Drosophila OL, which is largely supported by the data.
- Place the work in the context of the existing literature (provide references, where appropriate).
So far, most work in this field has focused on the regulation of the temporal factors to promote the progression of the TTF transcriptional cascade and thereby diversity of the neural progenitors (Li, Erclik et al. 2013, Naidu, Zhang et al. 2020, Ray and Li 2022, Zhu, Zhao et al. 2022). Furthermore, work on pathways such as EGFR and Notch signalling that allows the proneural wave to progress and subsequently induce neuroblast formation in a precise and orderly manner have also been studied (Yasugi, Umetsu et al. 2008, Yasugi, Sugie et al. 2010). Here, considering previous literature, the authors move one step forward to determine how and when these neuroblast progenitors cease proliferation during development thus providing mechanisms for the regulation of the neuroepithelial stem cell pool, its timely conversion into NSCs and the switch from neurogenesis to gliogenesis thus providing important implications for brain size determination and function.
- State what audience might be interested in and influenced by the reported findings.
Stem cell research, neurobiologists and developmental biologists.
- Define your field of expertise
Stem cells, developmental biology
-
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Referee #3
Evidence, reproducibility and clarity
Summary
In this manuscript, the authors address the timing and mechanisms responsible for the termination of medulla neuroblasts in Drosophila visual processing centres, also known as optic lobes. Through time course experiments the authors demonstrate the medulla NBs are completely eliminated by 30h APF during early pupal development. By manipulating the Notch signalling pathway as well as proneural genes such as lethal of scute, the authors show that altering the NE-NB transition is sufficient to change the timing of NB termination. In contrast, ecdysone signalling and components of the mediator complex, known to terminate proliferation of central brain NBs, are not required for the termination of medulla NBs. Medulla NBs sequentially express a variety of temporal transcription factors to promote cellular diversity, however, the authors demonstrate that altering temporal factors such as Ey, Sco or Hth, does not affect the timing of the medulla NBs termination. Interestingly however overexpression of the transcription factor tailless can cease medulla NB termination via the conversion of type I to type II NB fate. They further go on to show the importance of the differentiation factor, Prospero, in promoting the differentiation of medulla NBs as well as terminating medulla neurogenesis during pupal development. Finally, in addition to differentiation, the authors show another mechanism responsible for the cessation of neurogenesis which is the commencement of gliogenesis. Through manipulation of the neurogenic to gliogenic switch by knockdown or overexpressing the glial regulatory gene, gcm, the authors show that even though the downregulation of gcm is is not sufficient to induce NB persistence, gcm overexpression can cause premature termination of NBs.
Major comments:
- Are the key conclusions convincing?
Yes, the key conclusions are convincing with proper controls, quantifications and statistical analyses. - Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether?
The conclusion that temporal transcription factors (TTF) do not affect the timing of medulla NB termination is somewhat preliminary. The authors investigated a simplified temporal series including Homothorax, Eyeless, Sloppy-paired, Dichaete and Tailless. However, there are additional temporal factors that have not been examined for their potential involvement in medullar NB termination. Previous reports have identified several other temporal factors that play a role in medulla TTF cascade, such as, SoxNeuro (SoxN) and doublesex-Mab related 99B (Dmrt99B) that start their expression in the NE similar to Hth, however, Dmrt99B is likely to be repressed much later than Hth (Li, Erclik et al. 2013, Zhu, Zhao et al. 2022). At this point, it remains challenging to completely rule out the possibility that other temporal factors play a role in medullar NB termination or have redundant functions in regulating the timing of medulla NB cessation. It is suggested to tone down this claim and provide a brief discussion on alternative possibilities, citing relevant papers on the functions of other temporal factors in medullar NBs. - Would additional experiments be essential to support the claims of the paper? Request additional experiments only where necessary for the paper as it is, and do not ask authors to open new lines of experimentation.
Loss of pros by RNAi caused the formation of ectopic NBs and the NBs persist even at 24h APF. Do these NBs persist at 30h or 48h APF? Does overexpression of Pros result in early termination of medulla NBs? - Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated cost and time investment for substantial experiments.
Yes, I believe the suggested experiments are realistic in terms of time and resources, with an estimation of 3 months to complete the experiments. - Are the data and the methods presented in such a way that they can be reproduced?
Yes. - Are the experiments adequately replicated and statistical analysis adequate?
The experiments are straight forward and were performed with proper controls, supported by quantifications and proper statistical analyses. However, there is no mention about how many replicates were used.
Minor comments:
- The authors use the eyR6F10-Gal4 driver in certain experiments. The eyR6F10-Gal4 driver is however expressed only in a subset of medulla NBs. Can the authors comment on what percentage of medulla NBs is the driver expressed in?
- Does the EGFR signalling pathway or JAK/STAT pathway affect the timing of termination of medulla NBs? Experiments are not necessary. The author can speculate on their roles.
- Figure 1C has a p value of only 0.03 (*) but shows a strong reduction in the number of Dpn+ cells from 12h to 18h, etc. Is this correct? Also, is the p value the same for the comparison between 12h and 24h as well as 12h and 30h APF?
- The controls in figure 2B and to some extent figure 2H show one major outlier (much higher than the other brain lobes in the control). Will the removal of this outlier affect the significance/ p-value of the experiment?
- In figure 2B what is the p-value between 12h and 18h APF? Is it *** as well?
-
Line 84 of the introduction introduces Tll, Gcm and Pros for the first time in the manuscript and should be written out in full.
-
Are prior studies referenced appropriately?
Yes. - Are the text and figures clear and accurate?
Yes. - Do you have suggestions that would help the authors improve the presentation of their data and conclusions?
Quite a few of data mentioned in the manuscript have been described as data not shown. I think it would be nice to show quantifications or representative images in the supplementary figures.
Significance
Since the mechanisms by which medulla NBs are terminated are currently unknow, this is an important and interesting study to understand how medulla neuroblasts in the optic lobe are terminated. The balance between stem cell maintenance and differentiation is critical for proper brain development and the results presented in this paper are impactful. Furthermore, Drosophila melanogaster is an excellent model to study stem cell niches and neuroblast temporal patterning. The authors provide key mechanisms namely cell death, Pros-mediated differentiation and the gliogenic switch that contribute to a better understanding of how the NB progenitor pool can be terminated in the Drosophila OL, which is largely supported by the data.
- Place the work in the context of the existing literature (provide references, where appropriate).
So far, most work in this field has focused on the regulation of the temporal factors to promote the progression of the TTF transcriptional cascade and thereby diversity of the neural progenitors (Li, Erclik et al. 2013, Naidu, Zhang et al. 2020, Ray and Li 2022, Zhu, Zhao et al. 2022). Furthermore, work on pathways such as EGFR and Notch signalling that allows the proneural wave to progress and subsequently induce neuroblast formation in a precise and orderly manner have also been studied (Yasugi, Umetsu et al. 2008, Yasugi, Sugie et al. 2010). Here, considering previous literature, the authors move one step forward to determine how and when these neuroblast progenitors cease proliferation during development thus providing mechanisms for the regulation of the neuroepithelial stem cell pool, its timely conversion into NSCs and the switch from neurogenesis to gliogenesis thus providing important implications for brain size determination and function. - State what audience might be interested in and influenced by the reported findings.
Stem cell research, neurobiologists and developmental biologists. - Define your field of expertise
Stem cells, developmental biology
-